WATER RESEARCH A Journal of the International Water Association
Editor-in-Chief Mark van Loosdrecht Delft University of Technology Department of Biochemical Engineering Julianalaan 67 2628 BC Delft The Netherlands Tel: +31 15 27 81618 E-mail:
[email protected] Editors J. Block Université H. Poincaré, Nancy I France David Dixon University of Melbourne Australia Hiroaki Furumai The University of Tokyo Japan Xiaodi Hao Beijing University of Civil Engineering and Architecture China Gregory Korshin University of Washington USA Anna Ledin Formas Sweden Eberhard Morgenroth Swiss Federal Institute of Aquatic Science and Technology (EAWAG) Switzerland W. Rauch University Innsbruck Austria Maria Reis Universidade Nova de Lisboa/FCT Portugal Hang-Shik Shin Korea Advanced Institute of Science and Technology Korea Thomas Ternes Bundesanstalt für Gewässerkunde Germany Stefan Wuertz Univ. of California, Davis USA
Associate Editors Andrew Baker University of New South Wales Australia
Damien Batstone The University of Queensland Australia G-H. Chen The Hong Kong University of Science & Technology Hong Kong China Tom Curtis Univ. of Newcastle upon Tyne UK Ana Deletic Monash University USA Francis de los Reyes III North Carolina State University USA Rob Eldridge The University of Melbourne Australia Rosina Girones University of Barcelona Spain Stephen Gray Victoria University Australia Kate Grudpan Chiang Mai University Thailand E.E. Herricks University of Illinois - Urbana USA Peter Hillis United Utilities Plc UK H-Y. Hu Tsinghua University China P.M. Huck University of Waterloo Canada Bruce Jefferson Cranfield University UK Ulf Jeppsson Lund University Sweden Sergey Kalyuzhnyi Moscow State University Russian Federation Jaehong Kim Georgia Institute of Technology USA Jes La Cour Jansen Lund Institute of Technology Sweden G. Langergraber BOKU/Univ. of Natural Res. and Applied Life Scs. Austria S-L. Lo National Taiwan University Taiwan Dionisis Mantzavinos Technical University of Crete Greece
Y. Matsui Hokkaido University Japan A. Maul Université Paul Verlaine-Metz France Max Maurer EAWAG Switzerland How Yong Ng National University of Singapore Singapore Satoshi Okabe Hokkaido University Japan S.L. Ong National University of Singapore Singapore Jong M. Park Pohang University of Science & Technology Korea Susan Richardson U.S. Environmental Protection Agency USA Miguel Salgot University of Barcelona Spain David Sedlak University of California, Berkeley USA Jean-Philippe Steyer LBE-INRA France M. Takahashi Hokkaido University Japan Kai Udert EAWAG Switzerland V.P. Venugopalan BARC Facilities India E. von Sperling Federal University of Minas Gerais Brazil Hanqing Yu University of Science & Technology of China China J. Zilles University of Illinois Urbana USA A.I. Zouboulis Aristotle University Greece
Editorial Office Mailing address Water Research Radarweg 29 1043 NX Amsterdam The Netherlands Tel: 31 20 485 2701 Fax: 31 20 485 2521; 31 20 485 3264 E-mail:
[email protected] Publication information: Water Research (ISSN 0043-1354). For 2011, volume 45 is scheduled for publication. Subscription prices are available upon request from the publisher or from the Elsevier Customer Service Department nearest you or from this journal’s website (http://www.elsevier.com/locate/watres). Further information is available on this journal and other Elsevier products through Elsevier’s website (http://www.elsevier.com). Subscriptions are accepted on a prepaid basis only and are entered on a calendar year basis. Issues are sent by standard mail (surface within Europe, air delivery outside Europe). Priority rates are available upon request. Claims for missing issues should be made within six months of the date of dispatch. Author Enquiries: Please visit this journal’s homepage at http://www.elsevier.com/locate/watres. You can track accepted articles at http://www.elsevier.com/ trackarticle and set up e-mail alerts to inform you of when an article’s status has changed. Also accessible from here is information on copyright, frequently asked questions and more. Contact details for questions arising after acceptance of an article, especially those relating to proofs, will be provided by the publisher. Orders, claims, and journal enquiries: Please contact the Elsevier Customer Service Department nearest you: St. Louis: Elsevier Customer Service Department, 11830 Westline Industrial Drive, St. Louis, MO 63146, USA; phone: (877) 8397126 [toll free within the USA]; (+1) (314) 4537076 [outside the USA]; fax: (+1) (314) 5235153; e-mail:
[email protected] Oxford: Elsevier Customer Service Department, The Boulevard, Langford Lane, Kidlington OX5 1GB, UK; phone: (+44) (1865) 843434; fax: (+44) (1865) 843970; e-mail:
[email protected] Tokyo: Elsevier Customer Service Department, 4F Higashi-Azabu, 1-Chome Bldg, 1-9-15 Higashi-Azabu, Minato-ku, Tokyo 106-0044, Japan; phone: (+81) (3) 5561 5037; fax: (+81) (3) 5561 5047; e-mail:
[email protected] Singapore: Elsevier Customer Service Department, 3 Killiney Road, #08-01 Winsland House I, Singapore 239519; phone: (+65) 63490222; fax: (+65) 67331510; e-mail:
[email protected] Application for membership of International Water Association should be made to: Executive Director, IWA, Alliance House, 12 Caxton Street, London SW1H 0QS, U.K. (Tel.: +44 207 654 5500; Fax: +44 207 654 5555; e-mail:
[email protected]; website: http://www.IWAhq.org.uk). Registered Charity (England) No. 289269. Individual membership is available from £30 upwards. For details contact IWA.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 0 5 e1 0 1 4
Available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Influence of sampling strategies on the monitoring of cyanobacteria in shallow lakes: Lessons from a case study in France David Pobel a, Joe¨l Robin a, Jean-Franc¸ois Humbert b,* a b
ISARA-Lyon, Equipe Ecosyste`mes et Ressources Aquatiques, 23 rue Jean Baldassini 69364 Lyon Cedex 07, France INRA, UMR 7618 BIOEMCO, Site de l’ENS, 46 rue d’Ulm, 75005 Paris, France
article info
abstract
Article history:
Sampling cyanobacteria in freshwater ecosystems is a crucial aspect of monitoring programs
Received 6 August 2010
in both basic and applied research. Despite this, few papers have dealt with this aspect, and
Received in revised form
a high proportion of cyanobacteria monitoring programs are still based on monthly or twice-
5 October 2010
monthly water sampling, usually performed at a single location. In this study, we conducted
Accepted 10 October 2010
high frequency spatial and temporal water sampling in a small eutrophic shallow lake that
Available online 20 October 2010
experiences cyanobacterial blooms every year. We demonstrate that the spatial and temporal aspects of the sampling strategy had a considerable impact on the findings of
Keywords:
cyanobacteria monitoring in this lake. In particular, two peaks of Aphanizomenon flos-aquae
Sampling strategy
cell abundances were usually not picked up by the various temporal sampling strategies
Cyanobacteria
tested. In contrast, sampling once a month was sufficient to provide a good overall estima-
Spatiotemporal dynamic
tion of the population dynamics of Microcystis aeruginosa. The spatial frequency of sampling
Microcystis aeruginosa
was also important, and the choice in the location of the sampling points around the lake was
Aphanizomenon flos-aquae
very important if only two or three sampling points were used. When four or five sampling points were used, this reduced the impact of the choice of the location of the sampling points, and allowed to obtain fairly similar results than when six sampling points were used. These findings demonstrate the importance of the sampling strategy in cyanobacteria monitoring, and the fact that it is impossible to propose a single universal sampling strategy that is appropriate for all freshwater ecosystems and also for all cyanobacteria. ª 2010 Elsevier Ltd. All rights reserved.
1.
Introduction
Due to eutrophication and, to a lesser extent, to climatic changes (Markensten et al., 2010; Paerl and Huisman, 2009) cyanobacterial blooms seem to be increasing in freshwater ecosystems worldwide. These blooms severely disrupt the functioning of these ecosystems and potential water use. Furthermore, many cyanobacterial species are able to produce a variety of toxic metabolites, which can be harmful to both human (Kuiper-Goodman et al., 1999) and animal (Codd et al.,
2005) health. For these reasons, numerous attempts have been made in the last 20 years to elucidate the factors that control cyanobacterial blooms and toxin production, and thus to make it possible to evaluate better the health risks associated with bloom events. From all these studies, it is clear that the spatial distribution of cyanobacteria in freshwater ecosystems can display marked horizontal and vertical variations (Porat et al., 2001; Welker et al., 2003). Moreover, by means of a real-time PCR analysis of a gene involved in the biosynthesis of microcystins we have shown that considerable fluctuations
* Corresponding author. E-mail address:
[email protected] (J.-F. Humbert). 0043-1354/$ e see front matter ª 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2010.10.011
1006
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 0 5 e1 0 1 4
can also occur in the proportions of potentially microcystinproducing and non-producing cells during the course of Microcystis aeruginosa blooms (Briand et al., 2009). Similar results have been found for various M. aeruginosa populations located in the same geographic area (Sabart et al., 2009), which makes it difficult to manage the health risks associated with these events. All these studies indicate that the sampling strategy used for monitoring cyanobacteria is a critical aspect, both in basic research on cyanobacteria, (e.g. investigation of the factors and processes involved in the development of the blooms), and in applied research, (e.g. implementing monitoring programs of these microorganisms in freshwater ecosystems used to provide drinking water or for recreational activities). In recent years, new tools have been tested with the intention of improving cyanobacterial sampling, for example, remote sensing reconnaissance to determine the horizontal distribution of cyanobacteria in freshwater ecosystems (Hunter et al., 2009), or spectrofluorometric probes to reveal the vertical distribution of these cyanobacteria in the water column (Leboulanger et al., 2002). Moreover, these spectrofluorometric probes and other sensors have now been integrated into buoys, to provide real-time monitoring of cyanobacteria in freshwater ecosystems (Le Vu et al., in press). However, despite the great potential interest of these tools, their cost will remain prohibitive for their routine use in the foreseeable future, and most of the monitoring programs worldwide for the survey of cyanobacteria will continue to be based on more conventional methods for some years to come. Taking discrete samples of various volumes of water taken from the shoreline of ecosystems is probably the method one most often used in studies. Unfortunately, as a result of spatial and temporal differences in the distribution of cyanobacteria, this approach can often provide a very poor estimation of cyanobacterial abundance and, consequently, of the associated health risk. We therefore need to devise simple sampling strategies for the low cost monitoring of cyanobacteria in shallow lakes. In an attempt to do this, we performed intense spatiotemporal monitoring of cyanobacteria in a shallow lake known to experience cyanobacterial blooms every year.
2.
Materials and methods
2.1.
Study site
This study was performed in a shallow lake named Place (0.08 km2, 2.5 m max depth, 45 430 N, 4 140 E) located in the plain of Forez (Central France), (Fig. 1). This lake is used for extensive fish production and its trophic status is eutrophic to hypereutrophic (OCDE, 1982). M. aeruginosa blooms occur every summer.
2.2.
Data acquisition
2.2.1.
Sampling strategy and cell counting
In order to assess the variations in the horizontal distribution of cyanobacteria in this pond, we monitored six sampling points located around the lake at 1 m from the shore (V1eV6; Fig. 1). The water depth in each of these sampling points was around 1 m. Samples were taken every two days, between 09:00 and 10:00 a.m., from early June 2008 to early October 2008. The first 40-cm of the water column were sampled using a water sampler (Uwitech, Austria). This water sample was shacked and then divided into two 1-L bottles, 1 L being stored at room temperature with Lugol’s iodine solution, and the other at 4 C. In order to evaluate the diel variations in the subsurface cyanobacterial biomass, we performed a 22-h survey (from 4:30 p.m. August 4, 2009 to 2:30 p.m. August 5, 2009) at five sampling points (AeE; Fig. 1) using a BBE Algaetorch (Moldaenke, Germany). This torch is based on the same principle as the BBE spectrofluorometric probe (Beutler et al., 2002), but provides only an estimation of the concentrations of cyanobacteria and total chlorophyll in water. Every hour, the torch was immersed to a depth of 20 cm at the five sampling points, and triplicate measurements were performed in each point. The cyanobacterial cell concentrations were estimated using a Nageotte cell and an optical microscope, as described in Brient et al. (2008). For each rectangular area, we counted at least 400 cells of each cyanobacterial species..
Fig. 1 e Geographical location of the study site in France (left), and of the sampling points in the lake (right).
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 0 5 e1 0 1 4
2.2.2.
Meteorological data
The speed and direction of wind during our study were obtained from the Mete´o France meteorological station at St Etienne-Bouthe´on (45 32’N e 4 18’E). The wind direction rose for this station is given in Supplemental Figure 1, and shows that the two dominant wind directions were NW and SE. The direction of winds blowing from 240 e60 was classified as NW, and that of winds blowing from 60 e240 as SE.
2.3.
Data analysis
The spatial distribution of cyanobacteria in the lake was represented using Surfer (v. 7.0, Golden Software Inc.), and statistical analyses (Wilcoxon test, Spearman correlation) were performed using the R package version 2.10 (R development core Team, 2010).
3.
1007
Results
3.1. Change over time in the population dynamics of the two dominant cyanobacterial species Two cyanobacterial species, M. aeruginosa and Aphanizomenon flos-aquae, dominated the phytoplankton community during the summer of 2008. The population dynamics of these two species displayed very contrasting patterns (Fig. 2). The population dynamics of M. aeruginosa was characterized by a steady increase in the cell abundance from June to August, apart from a brief dip in the middle of July. The maximum population was reached on August 21 (264,000 cells/mL), and subsequently the cell concentration remained stable until the end of September, and then decreased in October. In contrast,
Fig. 2 e Changes over time of the concentrations of M. aeruginosa (top) and A. flos-aquae (bottom). These concentrations were estimated by calculating the average cell count for the six samples at each date. The error bars indicate the standard deviation.
1008
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 0 5 e1 0 1 4
the population dynamics of A. flos-aquae was much more chaotic, with the cell abundance reaching two very high and short-lived peaks in July (400,000 cells/mL on July 17, and 560,000 cells/mL on July 23).
Our assessment of the changing population dynamics of the two cyanobacteria was obtained using a very frequent high temporal sampling regime (every two days), which would not be practicable in the context of normal monitoring programs. In
order to evaluate the impact of the sampling frequency, we simulated weekly, twice-monthly and monthly sampling frequencies to our data set. The results of these simulations are shown in Figs. 3 and 4. From these figures, we can see that changes in M. aeruginosa cell abundance over time would have been fairly accurately estimated at all these sampling frequencies. Moreover, for all sampling frequencies, the quality of the estimation of the M. aeruginosa population dynamics was not influenced by choice of the first sampling date (Fig. 3). In contrast, the population dynamics of A. flos-aquae would have been badly or even very badly estimated by using weekly, twice-monthly and monthly sampling frequencies (Fig. 4). We
Fig. 3 e Simulation of the change over time of M. aeruginosa cell concentrations found using a weekly (top), twicemonthly (middle) or monthly sampling frequency (bottom), with lags for the first sampling day of zero days (_), 2 days (ee) and 4 days (..) comparing to our first sampling day. The gray curve corresponds to the reference data.
Fig. 4 e Simulation of the change over time of the biomass of A. flos-aquae found using a weekly (top), twice-monthly (middle), or monthly sampling frequency (bottom), and with lags for the first sampling day of zero days (_), 2 days (ee) and 4 days (..) comparing to our first sampling day. The gray curve corresponds to the reference data.
3.2. Influence of sampling frequency on the estimation of the population dynamics
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 0 5 e1 0 1 4
1009
would only have detected both A. flos-aquae peaks in one of the three trials testing the weekly sampling strategy, and we would never have detected these peaks with twice-monthly and monthly sampling frequencies.
3.3. Evolution of the horizontal distribution of cyanobacteria in the lake during the bloom As shown in the Video S1 (Supplemental Fig. 2), the horizontal distribution of both cyanobacteria displayed marked variations during the course of the study. Moreover, when the spatial distributions of the two species at the same sampling dates were compared, it could be seen that similar or contrasting patterns in the horizontal distribution of M. aeruginosa and A. flos-aquae cells would have been found, depending on the dates chosen (some examples are provided in Fig. 5). Supplementary data related to this article can be found online at doi: 10.1016/j.watres.2010.10.011 In order to obtain a better picture of this spatial variability in the cell concentrations of the two species, we estimated the coefficients of variation in the mean abundance for each sampling date and for each species from the results obtained at the six sampling points (Fig. 6). These coefficients were usually higher for A. flos-aquae than for M. aeruginosa (Wilcoxon test, p ¼ 3.25 1005), suggesting that the horizontal distribution of A. flos-aquae was more variable. Finally, there was no correlation (Spearman coefficient) between the coefficient of variation and the mean cell abundance for A. flos-aquae, and only a weak correlation was found for M. aeruginosa (Spearman coefficient, p ¼ 0.003 r ¼ 0.4; Supplemental Fig. 3). In order to find out whether wind speed/direction could account for the variations in the horizontal distribution of cyanobacterial cell abundance in the lake, we recorded in a first time, for each species and for each sampling date, the sampling point (out of the six) at which the highest cell
Fig. 6 e Change over time in the coefficients of variation of the mean cell abundances of M. aeruginosa (black triangle) and A. flos-aquae (white square) estimated at all six sampling points.
abundance was detected. We then constructed a table in which we related these findings to the wind direction and speed in the 5 h before the sampling, knowing that only data with wind speed values 2.0 m/s were taken into consideration. For M. aeruginosa, the highest cell abundances in the southernmost sampling points V2 and V3 were associated with winds blowing from the NW (Table 1), whereas those at the V1 and V4 sampling points were more surprisingly associated with winds from the SE. High cell abundances in the northern most sampling points V5 and V6 were equally associated with winds from NW and SE. For A. flos-aquae, the results were more complicated, and no obvious link could be seen between the direction of the wind and the distribution of the cyanobacteria (Table 1). The same analyses were performed by taking into account the wind data one and two days before sampling (instead 5e10 h before sampling), but no obvious relationship was detected (data not shown).
Fig. 5 e Spatial distribution of two cyanobacteria, M. aeruginosa and A. flos-aquae, in the lake at four sampling dates (July, 9, 17 and 23; August, 8).
1010
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 0 5 e1 0 1 4
Table 1 e Relationship between wind direction and high cell abundance recorded for M. aeruginosa and A. flosaquae at the different sampling points. V1 M. aeruginosa SeE 4 NeW 2 A. flos-aquae SeE 9 NeW 6
V2
V3
V4
V5
V6
1 5
1 3
8 2
7 6
2 2
2 5
4 0
0 0
5 5
2 4
3.4. Influence of the number of sampling points on the estimated cyanobacterial cell abundances in the lake The cyanobacterial cell abundances in the shallow lake were estimated by calculating the average value for the six sampling points (see Fig. 1). In order to determine the number of sampling points required to obtain a good estimation of cyanobacterial cell abundances in the lake, we compared the
estimations of cell abundance based on using samples from just one, two, three, four or five sampling points with that based on all six. To do this, we calculated the correlation coefficients (Spearman) between the estimations based on the six sampling points and those based on one to five sampling points for each species (Fig. 7). We considered all possible combinations of points, and the results are classified in the figure on the basis of increasing order of r values within each combination of groups. For both species, we found that the estimations of cell abundances based on only one or two sampling points were generally rather badly correlated with those obtained using all six sampling points. On the other hand, it appeared that good correlations (around or >0.9) were obtained when at least three sampling points were used, but also that the variations due to the choice of the sampling points were still considerable when only three sampling points were used. In order to find out which combinations of sampling points provided the best results when only two or three sampling points were used, we classified all the possible combinations
Spearman coefficients
1
0,9
Microcystis 0,8
0,7
Microcystis - 1 point: ▲ ; 2 points: ■ ; 3 points: ♦; 4 points: ○ ; 5 points: □ V5 V4 V1 V2 V6 V3 V 1V 5 V 1V 4 V 4V 5 V 3V 5 V 5V 6 V 2V 5 V 1V 6 V 1V 2 V 4V 6 V 2V 3 V 2V 6 V 3V 4 V 1V 3 V 2V 4 V 3V 6 V 1V4V5 V 1V4V6 V 1V2V6 V 1V3V4 V 1V3V5 V 2V3V4 V 3V4V5 V 3V5V6 V 4V5V6 V 1V2V4 V 1V2V5 V 2V4V5 V 2V5V6 V 1V2V3 V 1V5V6 V 2V3V5 V 1V3V6 V 2V3V6 V 2V4V6 V 3V4V6 V1V 2V3V 6 V1V 4V5V 6 V1V 2V3V 4 V1V 2V3V 5 V1V 2V4V 5 V1V 2V4V 6 V1V 2V5V 6 V1V 3V4V 5 V1V 3V4V 6 V1V 3V5V 6 V1V2V3V4V 6 V1V2V3V5V 6 V1V2V3V4V 5 V1V2V4V5V 6 V1V3V4V5V 6 V2V3V4V5V 6
0,6
Sampling points
Spearman coefficients
1
0,9
Aphanizomenon 0,8
0,7
Aphanizomenon - 1 point: ▲ ; 2 points: ■ ; 3 points: ♦; 4 points: ○ ; 5 points: □ V3 V4 V1 V5 V2 V6 V 2V 3 V 3V 4 V 1V 3 V 1V 5 V 2V 4 V 1V 4 V 3V 5 V 4V 5 V 1V 2 V 1V 6 V 4V 6 V 3V 6 V 2V 6 V 2V 5 V 5V 6 V 2V 3V4 V 3V 5V6 V 1V 3V4 V 1V 5V6 V 4V 5V6 V 1V 2V3 V 1V 2V4 V 1V 3V5 V 3V 4V5 V 3V 4V6 V 1V 3V6 V 1V 4V5 V 2V 3V6 V 2V 4V6 V 1V 2V6 V 1V 4V6 V 2V 3V5 V 2V 4V5 V 2V 5V6 V 1V 2V5 V1V 3V 5V6 V1V 2V 3V4 V1V 4V 5V6 V1V 2V 3V5 V1V 2V 3V6 V1V 2V 4V5 V1V 2V 4V6 V1V 2V 5V6 V1V 3V 4V6 V1V 3V 4V5 V 1V3V 4V 5V6 V 2V3V 4V 5V6 V 1V2V 3V 4V5 V 1V2V 3V 4V6 V 1V2V 4V 5V6 V 1V2V 3V 5V6
0,6
Sampling points
Fig. 7 e Spearman correlation values between M. aeruginosa (top) and A. flos-aquae (bottom) cell abundances estimated from the mean values for all six sampling point values, and those estimated from only one, two, three, four or five of these six sampling points.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 0 5 e1 0 1 4
1011
Fig. 8 e Location of the sampling points providing the best (left) and worst (right) estimations of cyanobacterial cell abundances (M. aeruginosa and A. flos-aquae), compared to estimations based on six sampling points. We give the combinations for two (top) and three (bottom) sampling points. The polar plot shows the direction of the maximum daily wind speed during the study. The different line types permit to distinguish the two best or the two worst combinations of sampling points, using two or three sampling points.
of points. To do this, we added the rank of each combination of sampling points obtained for the two species (M. aeruginosa and A. flos-aquae). From Fig. 8, we can see that the best estimations obtained using only two or three sampling points were provided by combinations in which the sampling points used were on the shore opposite to the prevailing wind direction over the lake.
3.5. Diel variations in the subsurface cyanobacterial biomass in the lake Finally, we carried out a 22-h estimation of the variations in the total cyanobacterial biomass in the subsurface water (20 cm depth) of the lake, at five sampling points using the BBE torch (AeE, see Fig. 1). As shown in Fig. 9, there was a steady fall in the cyanobacterial biomass at all sampling points during the
Fig. 9 e Cyanobacterial biomass in the subsurface water of the lake over a 22-h period at five sampling points (A point A, - point B, : point C, 3 point D, and > point E). The error bars indicate the standard deviation.
1012
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 0 5 e1 0 1 4
afternoon and evening, and conversely an increase late at night and in the morning. Moreover, the differences in biomass between the five sampling points were smaller during the night than during the day, as was the standard error (three measurements per sampling point). A multidimensional scaling analysis performed on the same values confirmed these observations, with all the night sampling times being grouped together, whereas the sampling times during the day were much more scattered (Data not shown).
4.
Discussion
As far as we are aware, this is the first attempt to investigate the influence of sampling strategies on the evaluation of spatial and temporal variations in cyanobacterial abundances in shallow lakes, which constitute unstable and complex ecosystems. These lakes are used by humans for numerous activities, including recreational activities and the supply of drinking water, which makes the monitoring of cyanobacteria in such ecosystems of particular importance, especially as part of the evaluation of the health risks linked to cyanobacterial blooms and their toxins. Sampling strategy is also very important in the context of basic studies, because the quality of sampling has a major impact on the quality of the final results. In this study, we found that the sampling frequency required to obtain a good estimation of the temporal evolution of the cyanobacterial abundance depends on the blooming species, M. aeruginosa or A. flos-aquae. Twice-monthly or monthly sampling provided good results for M. aeruginosa, whereas this was not often enough to monitor the chaotic population dynamics of A. flos-aquae. These findings are in contradiction with the recommendations of Codd et al. (1999), who proposed weekly or a twice-monthly sampling for species that do not form scum (A. flos-aquae for example), and more frequent sampling for scum-forming species (such as M. aeruginosa), because they can display more rapid changes in concentration. On the other hand, in agreement with these authors, our findings also demonstrate that a reactive approach to cyanobacterial sampling is called for, and that appropriate monitoring programs must be devised for each ecosystem based on what is known about how these systems function. It is clear that sampling only once or twice a month can lead to a very considerable under-estimation of cyanobacterial concentrations, and thus of the health risks associated with the bloom. As a result, a weekly sampling frequency seems to be required for cyanobacteria in small freshwater ecosystems. Our data on the variability of the spatial distribution of cyanobacteria in the lake indicate that at least three sampling points were needed to obtain a good estimation of the abundance, based on a comparison with estimations based on six sampling points. It appeared also that if only three sampling points are used, the choice of the location of these sampling points is very important for the quality of the estimation. The most reliable results were obtained using sampling points located on the opposite side of the lake shore to the main axis of the wind direction, and that adding more sampling points reduces the impact of the choice of the location of the sampling points. Such horizontal variability in the
distribution of cyanobacteria has been previously documented for many ecosystems, and also for many cyanobacterial species. For example, in a recent study, Briand et al. (2009) showed that the spatial distribution of M. aeruginosa in a large freshwater reservoir on a given date could vary from 7.103 cells/mL to 2.108 cells/mL, depending on the location of the sampling points in the reservoir. Many factors and processes can influence the horizontal distribution of cyanobacteria in a freshwater ecosystem. Among them, wind and surface currents seem to have the greatest impact. For example, the distribution of Microcystis spp. in lake Taihu (see the review paper of Qin et al., 2010) and in Lake Ontario (Hotto et al., 2007) is clearly influenced by both winds and currents. Similarly, Moreno-Ostos et al. (2009) have shown that in a Spanish reservoir currents have a marked effect on the distribution of cyanobacteria, and more globally on the phytoplankton community. In this study, we found that the horizontal distribution of M. aeruginosa in the lake was influenced more by wind direction than that of A. flos-aquae. This could be explained by the fact that M. aeruginosa colonies are located at the surface of the lake at the end of the night, and thus are more subjected to the influence of the wind than A. flos-aquae filaments, which are distributed over the entire water column. We found also that two sampling points in the lake (V5 and V6) were less influenced by wind direction than the others. This could be explained by the fact that these two sampling points are protected from the influence of winds blowing from the NW by an embankment located in the North part of the lake. Finally, we also demonstrated that in such a small lake, the impact of wind occurred at the scale of a few hours, in contrast to the previous findings of Welker et al. (2003) showing that the distribution of cyanobacteria was influenced by winds that had been blowing one or two days earlier. In addition to this variability in their horizontal distribution; the vertical distribution of cyanobacteria was also variable. Indeed, during the 22 h for which we used the BBE Torch to monitor the concentrations of cyanobacteria, we found that they were lower in the subsurface layer early at night than during the day. The greatest variations in biomass were recorded during the daytime, both at the scale of one sampling point when the three measurements were compared, and at the scale of the five sampling points monitored during this study. These findings also suggest that several sampling points are necessary to obtain an accurate assessment of the cyanobacterial biomass and that integrated sampling of the first meter of the water column reduces the variability in the estimation of the biomass due to the position of cyanobacteria in the water column. This finding is consistent with data reported by Ahn et al. (2008) showing that an integrated method was the most appropriate sampling method for Oscillatoria and Microcystis blooms. The causes of these variations in the position of cyanobacteria in the water column have been studied for different species. Several papers (Porat et al., 2001; Rabouille and Salenc¸on, 2005; Rabouille et al., 2005; Visser et al., 2005; Walsby, 1994) have shown that migrations of cyanobacteria in the water column are probably due to the dynamics of the carbon-reserve metabolism, and are strongly influenced by light, temperature, and water mixing.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 0 5 e1 0 1 4
From all these findings, guidelines should be proposed for the monitoring of cyanobacteria in shallow lakes. Codd et al. (1999) propose that the choice of sampling frequency and the choice of the number and location of the sampling sites should depend on the purpose of monitoring. For example, sampling near public bathing sites was recommended in freshwater ecosystems used for recreational activities. However, this strategy might generate data relevant only to the immediate vicinity of the bathing area, which do not reflect the global distribution of cyanobacteria in the lake. This is especially true when this distribution is very varied, and could make it difficult to prevent or manage blooms. On the basis of our findings, we proposed a different sampling strategy, which does not depend on the purpose of the monitoring. In order to minimize the cost of the cyanobacteria survey, twice-monthly sampling could be the norm for monitoring, but only if it is complemented by regular visual surveys. Changes in the appearance of the water (e.g. its color) between two successive dates would lead to an immediate increase in the sampling frequency. If it is not possible to carry out this visual survey, only a weekly sampling strategy can ensure that a sporadic cyanobacterial bloom is not missed. With regard to the number of sampling points, we found that at least three sampling points were necessary to obtain an accurate assessment of the cyanobacterial biomass (based on comparison with six sampling points). However, even when three sampling points were used, we found that the choice of the location of the sampling points was also very important (Fig. 8), even though the lake was fairly rectangular in shape and its perimeter small (around 1.3 km). These findings suggest that for large lakes and also for lakes with a more complex shape, a large number of sampling points would be necessary to obtain a good estimation of the cyanobacterial abundance. Clearly such sampling is time consuming and expensive. One way to reduce these costs would be to collect a large number of samples and then pool equal volumes of these samples in the same flask, before carrying out a single analysis. In this study, as in most of the monitoring programs performed in small lakes, all samples were taken from the shoreline of the lake. This kind of sampling is suitable for small lakes, but it has been shown that for large lakes (Rogalus and Watzin, 2008) shoreline sampling may miss early warning signs of bloom development, and also lead to the overestimation of the concentration of microcystins, when compared to data obtained from offshore samples. For bigger lakes, therefore, the sampling strategy must include offshore samples. Different programs worldwide are testing alternatives to water sampling for the monitoring of cyanobacteria in freshwater ecosystems. Two main approaches have been investigated. The first one is based on the use of remote sensing, which has long been in use in marine ecosystems (see for example Bracher et al., 2009). In freshwater ecosystems, the paper of Hunter et al. (2008) has shown the potential of high resolution images for the assessment of the spatial distribution of M. aeruginosa in a shallow eutrophic lake. However, the cost of these images and the impact of meteorological conditions are limiting factors for envisaging the use of this tool in routine cyanobacteria monitoring programs. One alternative, lower-cost solution could be based, in the future, on the use of
1013
drones to take aerial photographs of freshwater ecosystems, but these tools are still in development. Moreover, they will be only useful for cyanobacterial species that live in the surface water of lakes. The second way of monitoring of cyanobacteria without sampling the water being investigated is the use of buoys equipped with a variety of sensors, including, for example, a submersible spectrofluorometer to quantify the biomass of the cyanobacteria. This kind of tool permits the real-time monitoring of phytoplankton, including cyanobacteria, as shown for example in the paper of Le Vu et al. (in press). The two obstacles to their use in routine cyanobacteria monitoring programs are the high price of these systems, and the fact that they only provide estimations for one sampling point. Despite this, the possible use of such buoys, combined with the spatial monitoring of cyanobacteria by water sampling looks very promising for surveying cyanobacteria in freshwater ecosystems.
5.
Conclusion
The sampling of cyanobacteria in freshwater ecosystems is a hot topic, in particular in the context of programs for surveying these toxic microorganisms in ecosystems used for the production of drinking water or for recreational activities. Paradoxically, fewer studies deal with the impact of sampling strategies on the estimation of cyanobacterial cell abundances in freshwater ecosystems. In this study, we demonstrate that the choice of sampling strategy can lead to very different estimations of the cell abundances of two blooming species in a shallow lake and also that, depending on the cyanobacterial species involved, different sampling strategies are required to obtain a good estimation of their population dynamics. All these findings suggested that monthly or twice-monthly sampling strategies at just one sampling point do not allow to provide an accurate estimation of cyanobacterial abundances, and thus of the health risks associated with the presence of toxic species in aquatic ecosystems. Moreover, although promising new technologies are being developed for monitoring freshwater cyanobacteria, their cost and some other drawbacks mean that at present they cannot replace water sampling, which will remain the basis of most of these monitoring programs for the foreseeable future.
Acknowledgment This work was funded by the Re´gion Rhoˆne-Alpes and the Conseil Ge´ne´ral de la Loire. Monika Ghosh is acknowledged for improving the English version of the manuscript. The comments and suggestions of the two anonymous reviewers were greatly appreciated.
Appendix Supplementary data Supplementary data related to this article can be found online at doi:10.1016/j.watres.2010.10.011.
1014
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 0 5 e1 0 1 4
references
Ahn, C.Y., Joung, S.H., Park, C.S., Kim, H.S., Yoon, B.D., Oh, H.M., 2008. Comparison of sampling and analytical methods for monitoring of cyanobacteria-dominated surface waters. Hydrobiologia 596, 413e421. Beutler, M., Wiltshire, K.H., Meyer, B., Moldaenke, C., Luring, C., Meyerhofer, M., Hansen, U.P., Dau, H., 2002. A fluorometric method for the differentiation of algal populations in vivo and in situ. Photosynthesis Research 72, 39e53. Bracher, A., Vountas, M., Dinter, T., Burrows, J.P., Rottgers, R., Peeken, I., 2009. Quantitative observation of cyanobacteria and diatoms from space using PhytoDOAS on SCIAMACHY data. Biogeosciences 6, 751e764. Briand, E., Escoffier, N., Straub, C., Sabart, M., Quiblier, C., Humbert, J.-F., 2009. Spatiotemporal changes in the genetic diversity of a bloom-forming Microcystis aeruginosa (cyanobacteria) population. The ISME Journal 3, 419e429. Brient, L., Lengronne, M., Bertrand, E., Rolland, D., Sipel, A., Steinmann, D., Baudin, I., Legeas, M., Le Rouzic, B., Bormans, M., 2008. A phycocyanin probe as a tool for monitoring cyanobacteria in freshwater bodies. Journal of Environmental Monitoring 10, 248e255. Codd, G.A., Chorus, I., Burch, M., 1999. Design of monitoring programmes. In: WHO (Ed.), Toxic Cyanobacteria in Water: A Guide to Their Public Health Consequences, Monitoring and Management. E&F Spon ed, London & New York, p. 302e316. Codd, G.A., Lindsay, J., Young, F.M., Morrison, L.F., Metcalf, J.S., 2005. Harmful cyanobacteria. In: Huisman, J., Matthijs, H.C.P., Visser, P.M. (Eds.), Harmful Cyanobacteria. Springer, Dordrecht, pp. 1e23. Hotto, A.M., Satchwell, M.F., Boyer, G.L., 2007. Molecular characterization of potential microcytsin-producing cyanobacteria in lake Ontario embayments and nearshore waters. Applied and Environmental Microbiology 73, 4570e4578. Hunter, P.D., Tyler, A.N., Gilvear, D.J., Willby, N.J., 2009. Using remote sensing to aid the assessment of human health risks from blooms of potentially toxic cyanobacteria. Environmental Science & Technology 43, 2627e2633. Hunter, P.D., Tyler, A.N., Willby, N.J., Gilvear, D.J., 2008. The spatial dynamics of vertical migration by Microcystis aeruginosa in a eutrophic shallow lake: a case study using high spatial resolution time-series airborne remote sensing. Limnology and Oceanography 53, 2391e2406. Kuiper-Goodman, T., Falconer, I., Fitzgerald, J., 1999. Human health aspects. In: Chorus, I., Bartram, J. (Eds.), Toxic Cyanobacteria in Water: A Guide to Their Public Health Consequences, Monitoring and Management. WHO, pp. 125e160. Le Vu, B., Vinc¸on-Leite, B., Lemaire, B., Bensoussan, N., Calzas, M., Drezen, C., Deroubaix, J., Escoffier, N., De´gre´s, Y., Freissinet, C., Groleau, A., Humbert, J.-F., Paolini, G., Pre´vot, F., Quiblier, C., Rioust, E., Tassin, B. High-frequency monitoring of phytoplankton dynamics within the European water framework directive: application to metalimnetic cyanobacteria. Biogeochemistry, in press, doi:10.1007/s10533010-9446-1.
Leboulanger, C., Dorigo, U., Jacquet, S., Le Berre, B., Paolini, G., Humbert, J.-F., 2002. Application of a submersible spectrofluorometer for rapid monitoring of freshwater cyanobacterial blooms: a case study. Aquatic Microbial Ecology 30, 83e89. Markensten, H., Moore, K., Persson, I., 2010. Simulated lake phytoplankton composition shifts toward cyanobacteria dominance in a future warmer climate. Ecological Applications 20, 752e767. Moreno-Ostos, E., Cruz-Pizarro, L., Basanta, A., George, D.G., 2009. Spatial heterogeneity of cyanobacteria and diatoms in a thermally stratified canyon-shaped reservoir. International. Review of Hydrobiology 94, 245e257. OCDE, 1982. Eutrophisation des eaux: me´thodes de surveillance, d’e´valuation et de lutte. OCDE, 164 pp. Paerl, H.W., Huisman, J., 2009. Climate change: a catalyst for global expansion of harmful cyanobacterial blooms. Environmental Microbiology Reports 1, 27e37. Porat, R., Teltsch, B., Perelman, A., Dubinsky, Z., 2001. Diel buoyancy changes by the cyanobacterium Aphanizomenon ovalisporum from a shallow reservoir. Journal of Plankton Research 23, 753e763. Qin, B., Zhu, G., Gao, G., Zhang, Y., Li, W., Paerl, H., Carmichael, W., 2010. A drinking water crisis in Lake Taihu, China: linkage to climatic variability and lake management. Environmental Management 45, 105e112. R Development Core Team, 2010. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, ISBN 3-900051-07-0. http://www. R-project.com. Rabouille, S., Salenc¸on, M.J., 2005. Functional analysis of Microcystis vertical migration: a dynamic model as a prospecting tool. II. Influence of mixing, thermal stratification and colony diameter on biomass production. Aquatic Microbial Ecology 39, 281e292. Rabouille, S., Salenc¸on, M.J., Thebault, J.M., 2005. Functional analysis of Microcystis vertical migration: a dynamic model as a prospecting tool I - Processes analysis. Ecological Modelling 188, 386e403. Rogalus, M.K., Watzin, M.C., 2008. Evaluation of sampling and screening techniques for tiered monitoring of toxic cyanobacteria in lakes. Harmful Algae 7, 504e514. Sabart, M., Pobel, D., Latour, D., Robin, J., Salenc¸on, M.J., Humbert, J.-F., 2009. Spatiotemporal changes in the genetic diversity in French bloom-forming populations of the toxic cyanobacteria Microcystis aeruginosa. Environmental Microbiology Reports 1, 263e272. Visser, P.M., Ibelings, B.W., Mur, L.R., Walsby, A.E., 2005. The ecophysiology of the harmful cyanobacterium Microcystis features explaining its success and measures for its control. In: Huisman, J., Matthijs, H.C.P., Visser, P.M. (Eds.), Harmful Cyanobacteria. Springer, Dordrecht, pp. 109e142. Walsby, A.E., 1994. Gas vesicles. Microbiological Reviews 51, 94e144. Welker, M., Do¨hren von, H., Ta¨uscher, H., Steinberg, C.E.W., Erhard, M., 2003. Toxic Microcystis in shallow lakes Mu¨ggelsee (Germany) - dynamics, distribution, diversity. Archiv fu¨r Hydrobiologie 157, 227e248.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 1 5 e1 0 2 4
Available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Ozonation and activated carbon treatment of sewage effluents: Removal of endocrine activity and cytotoxicity Daniel Stalter*, Axel Magdeburg, Martin Wagner, Jo¨rg Oehlmann Goethe University Frankfurt am Main, Biological Sciences Division, Department Aquatic Ecotoxicology, Siesmayerstrasse 70, 60323 Frankfurt, Germany
article info
abstract
Article history:
Concerns about endocrine disrupting compounds in sewage treatment plant (STP) effluents
Received 14 July 2010
give rise to the implementation of advanced treatment steps for the elimination of trace
Received in revised form
organic contaminants. The present study investigated the effects of ozonation (O3) and
4 October 2010
activated carbon treatment (AC) on endocrine activities [estrogenicity, anti-estrogenicity,
Accepted 10 October 2010
androgenicity, anti-androgenicity, aryl-hydrocarbon receptor (AhR) agonistic activity] with
Available online 16 October 2010
yeast-based bioassays. To evaluate the removal of non-specific toxicity, a cytotoxicity assay using a rat cell line was applied. Wastewater (WW) was sampled at two STPs after conventional activated sludge treatment following the secondary clarifier (SC) and after
Keywords: Micropollutants
subsequent advanced treatments: O3, O3 þ sand filtration (O3-SF), and AC. Conventional
Anti-androgens
treatment reduced estrogenicity, androgenicity, and AhR agonistic activity by 78e99%
Anti-estrogens
compared to the untreated influent WW. Anti-androgenicity and anti-estrogenicity were not detectable in the influent but appeared in SC, possibly due to the more effective
Dioxin-like xenobiotics Aryl-hydrocarbon
receptor
(AhR)
removal of respective agonists during conventional treatment. Endocrine activities after SC
activity
ranged from 2.0 to 2.8 ng/L estradiol equivalents (estrogenicity), from 4 to 22 mg/L
Yeast estrogen screen (YES)
4-hydroxytamoxifen equivalents (anti-estrogenicity), from 1.9 to 2.0 ng/L testosterone
Yeast androgen screen (YAS)
equivalents (androgenicity), from 302 to 614 mg/L flutamide equivalents (anti-androge-
GH3 cells
nicity), and from 387 to 741 ng/L b-naphthoflavone equivalents (AhR agonistic activity). In
Polyaromatic hydrocarbons (PAHs)
particular, estrogenicity and anti-androgenicity occurred in environmentally relevant
Wastewater treatment plant
concentrations. O3 and AC further reduced endocrine activities effectively (estrogenicity: 77e99%, anti-androgenicity: 63e96%, AhR agonistic activity: 79e82%). The cytotoxicity assay exhibited a 32% removal of non-specific toxicity after O3 compared to SC. O3 and sand filtration reduced cytotoxic effects by 49%, indicating that sand filtration contributes to the removal of toxicants. AC was the most effective technology for cytotoxicity removal (61%). Sample evaporation reduced cytotoxic effects by 52 (AC) to 73% (O3), demonstrating that volatile substances contribute considerably to toxic effects, particularly after O3. These results confirm an effective removal or transformation of toxicants with receptor-mediated mode of action and non-specific toxicants during O3 and AC. However, due to the limited extractability, polar ozonation by-products were neglected for toxicity analysis, and hence non-specific toxicity after O3 is underestimated. ª 2010 Elsevier Ltd. All rights reserved.
* Corresponding author. Tel.: þ49 6979824882; fax: þ49 6979824748. E-mail address:
[email protected] (D. Stalter). 0043-1354/$ e see front matter ª 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2010.10.008
1016
1.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 1 5 e1 0 2 4
Introduction
The conventional activated sludge treatment of wastewater (WW) removes endocrine disrupting compounds (EDCs) very effectively (Liu et al., 2009). Nevertheless, sewage effluents considerably contribute to surface water contamination with (xeno-) hormones on trace levels and thus to widespread endocrine disruption in aquatic wildlife (Jobling and Tyler, 2006). Feminization of fish and molluscs results in population relevant effects on reproduction or development (Jobling and Tyler, 2006). Besides estrogenicity, anti-androgenicity has recently attracted augmented attention regarding its impact on aquatic ecosystems as it contributes to the feminization of fish and molluscs (Santos et al., 2008; Jobling et al., 2009). The study by Jobling et al. (2009) suggests that reproductive health effects in fish (e.g., intersexuality and vitellogenin induction) are mediated primarily by anti-androgenic combined with estrogenic mechanisms rather than by estrogenic mechanisms alone. Besides anti-androgens, anti-estrogens are known to potentially influence endocrine disrupting effects. Benzotriazole, for example, is only partly removed in sewage treatment plants (STPs) and hence might affect in vitro experiments (Harris et al., 2007). As androgenic and anti-androgenic compounds are known to influence each other’s interaction with the androgen receptor, the analysis of agonists and antagonists is important to evaluate the in vitro endocrine disrupting potential of a complex chemical mixture (Weiss et al., 2009). Advanced WW treatment technologies, like ozonation (O3) and activated carbon filtration (AC), provide effective barriers to a wide range of organic pollutants (Nowotny et al., 2007; Hollender et al., 2009; Schaar et al., 2010) and can thus reduce the emission of EDCs via STP effluents. While estrogenicity removal by advanced treatment methods has already been investigated (Huber et al., 2004; Escher et al., 2009; Stalter et al., 2010b), the impact on androgenicity, antiandrogenicity, and anti-estrogenicity remains unclear. Therefore, the present study examined the effect of O3 and AC on estrogenicity, androgenicity, and the respective antagonistic activities. Additionally, the aryl-hydrocarbon receptor (AhR) agonistic activity was analysed. AhR regulates genes involved in xenobiotic metabolism (Miller, 1999). Thus, the measurement of AhR agonists is a suitable tool to detect hazardous substances like halogenated aromatic hydrocarbons (e.g., dibenzodioxins, dibenzofurans, and biphenyls) and polyaromatic hydrocarbons (PAHs; Alnafisi et al., 2007). A vertebrate cell-based test system is applied to test for non-specific toxicity because ozonation results in potentially hazardous oxidation products (Petala et al., 2006; Benner and Ternes, 2009; Stalter et al., 2010a,b). This work is part of a comprehensive study within the Neptune project (www.neptune-eu.org), covering in vivo tests with six different test organisms (Stalter et al., 2010a,b) and a variety of in vitro bioassays.
2.
Material and methods
2.1.
Characterization of the STPs
WW samples of a treatment plant in Regensdorf (Switzerland; STP A) and a pilot treatment plant in Neuss (Germany; STP B)
were investigated. Both STPs operated experimentally with a full scale (STP A) or half scale ozonation (STP B) after the secondary clarifier (SC) subsequent to conventional activated sludge treatment and with a sand filtration step after the ozone reactor. Applied ozone doses were 0.8 (STP A) and 0.7 g O3/g DOC (dissolved organic carbon). At STP B, powdered activated carbon treatment (AC; 20 mg/L, contact time 60 min) was tested in parallel with a subsequent sand filtration step. The applied ozone and AC doses at both treatment plants were chosen because they eliminate pollutants effectively and are regarded as economically feasible (Nowotny et al., 2007; Joss et al., 2008). More detailed information is provided in the supplementary information (SI), including WW quality parameters after SC (Table S1).
2.2.
Collection and extraction of the WW samples
At STP A, six grab samples were collected from each sampling point after SC, after the ozone reactor (O3), and after the following sand filtration (O3-SF; sampling period: 08/2008e09/ 2008). At STP B, nine 24 h composite samples were collected from each sampling point after SC, O3, O3-SF, and after the parallel AC treatment subsequent to sand filtration (ACSF; sampling period: 09/2008e03/2009). WW from the treatment plant influent (INF) was sampled (n ¼ 3) at both STPs to allow an estimation of the removal effectiveness during conventional treatment. At STP B, WW was additionally sampled after treatment with different ozone doses ranging from 0.4 to 1.6 g O3/g DOC. All WW samples were processed by solid phase extraction (SPE). The detailed extraction method is described in SI 3 and the sampling points are displayed in Figure S1.
2.3.
Recombinant yeast screens
All yeast screens in this study base upon the same principle. The yeast cells contain a gene for the human estrogen receptor, the human androgen receptor or the aryl-hydrocarbon receptor, respectively, each fused to the reporter gene lacZ. The binding of agonistic ligands leads to a colour change in the assay medium, which is photometrically measurable and provides a marker for the agonistic activity. The detection of antagonistic activity requires a background concentration of the agonistic reference substance, and hence antagonistic activity in the sample leads to a reduced colour change. 96-well microtiter plates were loaded with 30 mL 80-fold concentrated methanol extracts (prepared as described in SI 3), providing a 20-fold sample concentration per well (for INF: 7.5 mL/well, providing a 5-fold concentration). These concentrations were chosen to avoid cytotoxic effects. WW extracts were evaporated to dryness and re-dissolved in the respective assay medium. Assay procedure and data analysis were conducted as described previously (Routledge and Sumpter, 1996) with modifications according to Wagner and Oehlmann (2009). The yeast-based test on aryl-hydrocarbon receptor (AhR) agonists (yeast dioxin screen, YDS) was performed in analogy to the yeast estrogen screen with a slightly modified medium according to Miller (1999). For the YDS, 1000-fold concentrated dimethyl sulfoxide (DMSO) extracts (prepared as described in SI 3) were used because Gustavsson et al. (2004) reported
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 1 5 e1 0 2 4
a significant fraction of volatile AhR agonists in STP sludge. As evaporation in the wells might lead to a loss of agonistic substances, DMSO extracts were directly added to the assay medium in volumes providing a 1e5-fold final sample concentration. Sample concentration was adapted to avoid cytotoxic effects. Total solvent portion was adjusted to 0.5% in each treatment group. In all in vitro screens, microtiter plates were sealed with gas permeable membranes (Breath-Easy, Diversified Biotech, Boston, USA) during incubation to reduce the risk of cross-contamination via volatile substances. The AhR agonist b-naphthoflavone (b-NF) was used as reference instead of 2,3,7,8-tetrachlorodibenzodioxin (TCDD). Because of its high hydrophobicity, the bioavailability of TCDD is reduced considerably when the test is conducted in plates consisting of plastic compared to glass material (Miller, 1999), and hence resulting sample activity might be overestimated. Thus, the results by Miller (1999) suggest that b-NF is a more appropriate reference substance than TCDD for the respective test system. In this study, reference equivalents (R-EQs) are interpolated nonlinearly from the appropriate doseeresponse relationship of the reference agonist or antagonist under presence of a fixed concentration of the corresponding agonist according to Wagner and Oehlmann (2009). Estradiol equivalents (E-EQs) were calculated as R-EQs for estrogenic activity, 4-hydroxytamoxifen equivalents (OHT-EQs) for anti-estrogenicity, testosterone equivalents (T-EQs) for androgenicity, flutamide equivalents (F-EQs) for anti-androgenicity, and b-NF equivalents (b-NF-EQ) for AhR agonistic activity. The applied concentrations for the reference dilution series, the background agonist concentration for the anti-screens as well as the corresponding EC50 for each test system is provided in Table S2. The doseeresponse curves of the reference dilution series are displayed in Figure S2. Each sample was analysed in eight pseudo replicates for every test system. Box and whisker plots display the range of mean activities of all samples per sampling point. If a clear removal pattern was observed, Tables S3eS8 state the mean values, standard errors, and percentage removals compared to SC for the samples from each sampling campaign.
2.4.
Cytotoxicity assay
Cytotoxic effects were analysed using the rat pituitary cell line GH3 to assess the non-specific toxicity of WW samples. This cell line was chosen because of its enhanced sensitivity compared to a rainbow trout liver cell line (RTL-W1; Lee et al., 1993) that was employed in parallel (data not shown). Six samples from the serial treatment steps at STP B were extracted at pH 2 and pH 7 and tested as DMSO extracts and methanol extracts each (SI 3). 0.5% DMSO extract was added to the cell suspension for a final 5-fold concentration. Methanol extracts were evaporated to dryness in the microtiter wells in volumes providing a 10-fold final concentration. Different dosings were chosen as 5-fold concentrated methanol extracts did not induce significant toxic effects after conventional treatment and 10-fold concentrated DMSO extracts led to maximum toxicity in all treatment groups. No dilution series were applied due to the limited sample extract volumes. Cell culturing and preparation of the cell suspension is described in SI 5.1.
1017
100 mL of the suspension was added to the wells of 96-well tissue culture test plates (Orange Scientific, Braine-l’Alleud, Belgium). Microtiter plates were sealed using Breath-Easy membranes and incubated for 120 h (37 C, 5% CO2). Each sample was analysed in eight pseudo replicates. After incubation, the cell activity was determined according to Palomino et al. (2002) with slight modifications. Resazurin sodium salt powder (VWR International GmbH, Darmstadt, Germany) was dissolved at 0.01% (w/v) in phosphate buffer saline and filter sterilized (0.2 mm). 30 mL resazurin solution was added to each well, incubated for 5.5 h and photometrically measured at 540 and 595 nm. The percentage resazurin reduction (calculated as described in SI 5.2) served as measurement for cell viability. Correlation between cell density and resazurin reduction is documented in Figure S3 (r2 ¼ 0.99). Cytotoxicity (percentage inhibition of cell density) was calculated according to SI 5.3. The blank (wells with culture medium, 0.5% DMSO, without cells) was defined as 100% cytotoxicity and negative control (wells with cell suspension, 0.5% DMSO) as 0%. 2,4-dichlorophenol in concentrations from 1.5 to 24 mg/L served as reference toxicant (doseeresponse curve in Figure S4).
2.5.
Statistical analysis
Statistical analyses were performed using GraphPad Prism version 5.03 for Windows (GraphPad Software, San Diego, California, USA). To test for significant differences, data were Ln-transformed and one-way ANOVA was applied with Dunnett’s post test. Percentage data were transformed by arcsin before ANOVA. In cases of unequal variances (Bartlett’s test, p < 0.05), KruskaleWallis with Dunn’s post test was used instead.
3.
Results and discussion
3.1.
Estrogenicity
Compared to the influent (13e23 ng/L E-EQ), the estrogenic activity was reduced by 78% (STP A) to 91% (STP B; Fig. 1A, B) during conventional treatment, confirming literature data, which report percentage removals between 70 and 99% (Liu et al., 2009). Despite the effective elimination of estrogenicity, remaining (xeno-) estrogens in sewage effluents potentially are of environmental relevance (Jobling et al., 2002). At both STPs, the average estrogenic activity after SC ranged from 2.0 to 2.8 ng/L E-EQ. Ozonation further diminished this activity with a percentage removal following O3-SF of 88e95% compared to SC (Fig. 1A, B). ACSF was less effective (77% average removal, Fig. 1B) than O3-SF at the applied AC dose of 20 mg/L. The remaining average estrogenic activity of all sampling campaigns after advanced treatment was 0.1e0.2 ng/L E-EQ after O3-SF and 0.4 ng/L after ACSF (Table S3, S4). Hence, final activity was below the environmental quality standard proposed for estradiol (0.5 ng/L; Moltmann et al., 2007). Therefore, estrogenicity reduction could be a relevant environmental benefit, helping to reduce the feminization of fish populations (Jobling et al., 2002) as reported by Filby et al. (2010). At STP A, the reduced estrogenic activity led to reduced vitellogenin levels in juvenile rainbow trout (Stalter et al.,
1018
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 1 5 e1 0 2 4
Fig. 1 e Estrogenic (estradiol equivalents, E-EQs; A, B) and anti-estrogenic activities (4-hydroxytamoxifen equivalents, OHTEQs; C, D) during six (STP A) or nine sampling campaigns (STP B, INF: n [ 3) as determined in recombinant yeast screens. Displayed are the mean activities of eight pseudo replicates for each sample. Average endocrine activity removal is stated as % compared to INF (DINF) or SC (DSC). INF, influent; SC, after the secondary clarifier; O3, SC after ozonation; O3-SF, O3 after sand filtration; ACSF, SC after activated carbon treatment.
2010b). The removal of estrogenicity by ozonation was already investigated in previous studies (Huber et al., 2004; Escher et al., 2009; Stalter et al., 2010b) and is a result of the oxidative transformation of estrogenically active chemicals (Huber et al., 2004). Phenols are an important functional group, interacting with the estrogen receptor (Nishihara et al., 2000) and are known to be particularly susceptible to ozone attack (von Gunten, 2003). Consequently, estrogenicity removal via ozonation is to be expected. The less pronounced removal efficiency of AC treatment compared to O3 might be a result of the elevated DOC level at STP B (up to 12 mg/L, Table S1), because adsorbability of pollutants is significantly lower at higher background DOC concentrations (Nowotny et al., 2007). Finally, further in vitro studies with a steroidgenesis assay could be appropriate to evaluate potential effects on the cellular production of estradiol before and after advanced treatments to complement the present findings (Grund et al., 2010).
3.2.
Anti-estrogenicity
The anti-estrogenic activity exhibited no clear removal pattern. At STP A, OHT-EQs were elevated after ozonation and decreased to the level of SC after sand filtration (Fig. 1C).
However, these results are based on only 3 samples, due to limited sample extract volumes. At STP B, anti-estrogenicity was slightly increased after O3 and O3-SF, while in INF no antiestrogenic activity was detectable (Fig. 1D). Possibly the occurrence of anti-estrogenic compounds in INF was masked by the high estrogenicity at both STPs (Fig. 1A, B). A nonspecific quenching by influent extracts is not likely to explain the absence of antagonistic activity because the test system for the agonists works well at the same sample concentration. However, fractionation studies are required for separating agonists from antagonists to confirm masking effects, which were already observed by Weiss et al. (2009). During ozonation, the estrogenic compounds were probably more effectively removed than anti-estrogens, resulting in a slightly elevated anti-estrogenicity in O3 and O3-SF. The further increase after activated carbon treatment cannot be explained conclusively, except by a higher adsorption of estrogens compared to anti-estrogenic compounds. Nonetheless, the increased anti-estrogenicity after advanced treatments do not necessarily implicate that these methods are not applicable for pollution reduction as the reduced estrogenicity might be of higher benefit for aquatic wildlife. However, further research on potential negative effects of anti-estrogens on aquatic organisms is desirable.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 1 5 e1 0 2 4
3.3.
Androgenicity
Androgenic activity from the influent (201e400 ng/L T-EQs) was reduced by more than 99% during conventional activated sludge treatment (Fig. 2A, B). At STP A, average activity after SC reached 2.0 ng/L T-EQs. After O3 and O3-SF, average activities were noticeably but not significantly elevated to 5.2 and 7.0 ng/L (Fig. 2A). At STP B, androgenicity was on an average level of 1.9 ng/L after SC, without a consistent removal during advanced treatment steps (Fig. 2B). Potential interactions between androgens and anti-androgens might explain the lack of androgenicity removal during advanced treatment steps and are discussed in the following section.
3.4.
Anti-androgenicity
Anti-androgenic activity was not detectable in the influent WW (Fig. 2C, D). After conventional treatment, the average activity ranged from 302 (STP B) to 614 mg/L F-EQs (STP A). Following O3-SF, the average removal reached 78% (STP B) to 90% (STP A, Fig. 2C, D), while ACSF was slightly less effective (63% removal, Fig. 2D). Besides estrogenic activity, antiandrogenicity is an important causative factor for the feminization of wild fish (Jobling et al., 2009). Anti-androgenic activity predicted to be present in UK rivers ranged from 0 to
1019
100 mg/L F-EQs (Jobling et al., 2009). Considering a potential WW dilution in the receiving water body of 1:10, the values in the present study (Table S5, S6) conform to literature data (Jobling et al., 2009). Moreover, anti-androgenic activity measured in the conventionally treated WW samples might be sufficient to induce biological responses in fish. Katsiadaki et al. (2006) determined a lowest observed effect concentration (LOEC) of 10 mg/L flutamide (concentration, where the production of a glue protein in the kidney of sticklebacks was depleted significantly) for in vivo anti-androgenic activity. Even if a dilution factor of 10 is assumed in the receiving water body, each sample after SC exceeded this effect concentration (Table S5, S6). Finally, the studies of Jobling et al. (2009) and Katsiadaki et al. (2006) provide clear indications that antiandrogenic compounds have a significant impact on aquatic organisms while this study demonstrates that anti-androgens are introduced to rivers via STP effluents in environmentally relevant concentrations. After O3 and O3-SF, activity was below 100 mg/L F-EQ in most cases, what could be a relevant benefit for aquatic wildlife. Nonetheless, if the dilution factor is below 10 in the receiving water body, remaining activity may exceed the LOEC for flutamide and hence may still be of environmental relevance. Several potential causative substances for anti-androgenicity in the environment have been identified, for example,
Fig. 2 e Androgenic (testosterone equivalents, T-EQs; A, B) and anti-androgenic activities (flutamide equivalents, F-EQs; C, D) during six (STP A) or nine sampling campaigns (STP B, INF: n [ 3) as determined in recombinant yeast screens. Displayed are the mean activities of eight pseudo replicates for each sample. Average endocrine activity removal is stated as % compared to INF (DINF) or SC (DSC). INF, influent; SC, after the secondary clarifier; O3, SC after ozonation; O3-SF, O3 after sand filtration; ACSF, SC after activated carbon treatment.
1020
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 1 5 e1 0 2 4
several PAHs, butyl-benzyl-phthalate, dibutyl-phthalate, triclosan, and dichlorophene (Thomas et al., 2009; Hill et al., 2010). However, the explicit identity of compounds causing the observed anti-androgenicity in municipal WW remains unclear. The identification of anti-androgens and their contribution to the overall activity is however required to develop source control strategies. Additionally, with regard to the high hydrophobicity of the suspected compounds (Zhang and Huang, 2003; Clara et al., 2010), it could be assumed that anti-androgens primarily enter the environment bound to particulate matter (Clara et al., 2010). The analysed water samples were membrane filtrated (1.2 mm pore size) before solid phase extraction, and hence the determined activities might be underestimated. The lack of anti-androgenicity in INF is possibly a result of masking effects due to the high androgenic activity. Environmental samples contain a complex mixture of chemicals and EDCs. When endocrine activity is analysed, only the gross activity resulting from the present receptor agonists and antagonists can be measured. Accordingly, antagonistic activity could easily be masked by its agonists in the influent (Figs. 1 and 2), and androgenic activity could even increase with advanced treatment processes in the case of a more effective antagonist removal (Fig. 2A). Comparable masking effects of androgens and anti-androgens in sediment samples were already reported by Weiss et al. (2009). Consequently, the appearance of anti-androgenic activity in SC is possibly a consequence of the effective androgen removal by >99% during conventional treatment (Fig. 2), whereas anti-androgens like PAHs or phthalates are more stable (Clara et al., 2010).
3.5.
AhR agonistic activity
The aryl-hydrocarbon agonistic activity was reduced by an average of 81% (STP A)e96% (STP B) during conventional WW treatment (Fig. 3A, B). Ozonation resulted in further reduction by 80% (STP B) to 90% (STP A; Fig. 3A, B). Removal effectiveness of ACSF (average of 82%) was comparable to that of O3. The considerable removal of AhR agonistic activity after advanced WW treatment steps indicates an effective
reduction of potentially hazardous compounds like PAHs, PCBs (polychlorinated biphenyls), furans, and dioxins. A study by Macova et al. (2010) point out that AhR agonistic activity in WW may be attributed to chemicals other than dioxins, polychlorinated biphenyls (PCBs) and furans. Macova et al. (2010) reported AhR agonistic activities in STP effluents below 1 ng/L TCDD-EQs. According to a circa 10-fold lower 50% effect concentration (EC50) for TCDD compared to b-NF (Miller, 1999), the assumed TCDD-EQs should be approximately one order of magnitude lower than the calculated b-NF-EQs. Thus, the measured activities in the present study are probably about 100 times higher compared to the Australian study. Such discrepancies might be a result of a different effluent composition at the investigated treatment plants. Furthermore, evaporation of sample extracts might lead to the loss of volatile AhR agonists as reported by Gustavsson et al. (2004). Due to their high hydrophobicity, AhR agonists largely bind to particulate organic matter (Dagnino et al., 2010) and are subsequently released to a certain extend in STPs (Suares Rocha et al., 2010). Consequently, different pore sizes of the sample filters influence the results as well. In the present study, WW samples were filtered before extraction with a pore size of 1.2 mm, and hence the overall activity in the WW samples (including particulate matter) was presumably higher than analysed. Nonetheless, our data emphasize that STP effluents are potential point sources for dioxin-like chemicals and PAHs in the aquatic environment. Especially sediments in urbanized areas are often contaminated by AhR agonists (Hollert et al., 2002). According to a study by Brack et al. (2005), dioxins, PCBs, and furans contribute only to a minor extend to AhR-mediated effects in sediments, conforming to the study by Macova et al. (2010). Brack et al. (2005) identified nonpriority PAHs as major contributors to respective activities in river sediments. An effective PAH degradation with O3 has already been documented, however, possibly at the expense of an increased non-specific toxicity as a result of oxidation by-product formation (Luster-Teasley et al., 2002). However, results of the applied yeast-based reporter gene test system are not necessarily transferable to in vivo conditions as it does not take into account the potential adsorption
Fig. 3 e AhR agonistic activities (b-naphthoflavone equivalents, b-NF-EQs) during 6 (STP A) or 9 sampling campaigns (STP B; INF: n [ 3) as determined in a recombinant yeast screen. Displayed are the mean activities of eight pseudo replicates for each sample. Average b-NF-EQ removal is stated as % compared to INF (DINF) or SC (DSC). INF, influent; SC, after the secondary clarifier; O3, after ozonation; O3-SF, O3 after sand filtration; ACSF, SC after activated carbon treatment.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 1 5 e1 0 2 4
1021
Fig. 4 e Percentage removal of estrogenic (A), anti-androgenic (B) and aryl-hydrocarbon agonistic activity (C) at different ozone doses.
of substances to test material, the bioconcentration ability as well as metabolic transformation and excretion of chemicals. Consequently, the yeast dioxin screen can deliver different results as test systems based upon the AhR-dependent induction of CYP1A1 (EROD assay; Sugihara et al., 2008) and hence further research might be appropriate.
3.6.
Ozone dose dependent removal of endocrine activity
Estrogenicity removal reached 90% even at the lowest ozone dose of 0.4 g O3/g DOC (Fig. 4A), confirming the high susceptibility of estrogenically active compounds to ozone attack (Huber et al., 2004). F-EQ removal was less effective at 0.4 g O3/g DOC (45%), whereas removal was elevated to >80% at doses >1.0 g O3/g DOC (O3-SF, Fig. 4B). AhR agonistic activity was least effectively reduced at 0.4 g O3/g DOC (27%), while around 80% removal was achieved at doses >0.7 g O3/g DOC (Fig. 4C). These results suggest that O3 doses of 0.4 g O3/g DOC might be too low for an effective endocrine activity removal.
3.7.
Cytotoxicity
The cytotoxicity assay revealed non-specific toxic effects after SC at an average of 89% compared to the negative control (Fig. 5A, Table S10A). Compared to SC, cytotoxicity was reduced by 32% after O3 and further reduced by 49% during
sand filtration. Activated carbon treatment reduced toxic effects most effectively by 61% compared to SC. Samples extracted at pH 7 in DMSO revealed a reduced cytotoxicity in O3 compared to pH 2 by an average of 24% (Fig. 5B; Table S10A, B). Evaporation of methanolic extracts (extracted at pH 2) led to a reduction of cytotoxic effects by 52% (AC) to 73% (O3) after advanced treatments (Fig. 5C; Table S10D), in spite of a doubled sample concentration compared to the DMSO extracts. The different dosings were required to maximize differences between the treatment steps. The results underline that the choice of extraction method and sample preparation remarkably influences cytotoxic effects. Reduced toxicity of samples extracted at pH 7 compared to pH 2 indicates the presence of toxic compounds with acidic moieties after O3. Additionally, the complete evaporation of solvent extracts in the test wells led to a considerable loss of toxic volatile substances and hence to a consistent underestimation of toxic effects, particularly in O3. The observed cytotoxic effects were a result of a mixture of the extractable fraction of contaminants present in WW. This study focused on toxic effects induced by extractable organic pollutants. Potentially toxic ozonation by-products are neglected in the present toxicity analysis because such substances are hardly extractable via conventional SPE due to high polarities (Benner and Ternes, 2009) and degradability (Petala et al., 2006). Consequently, further research on the
Fig. 5 e Reduction of cell density compared to negative control after exposure to WW extracts. A: at pH 2 extracted samples in DMSO (5-fold concentrated), B: at pH 7 extracted samples in DMSO (5-fold), C: at pH 2 extracted samples in methanol (10-fold, evaporated to dryness before test). Average cytotoxicity removal is stated as % compared to SC (DSC). Negative control [ 0%; blank [ 100%; n [ 6. SC, secondary clarifier; O3, after ozonation; O3-SF, O3 after sand filtration; ACSF, activated carbon treatment; SE, standard error.
1022
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 1 5 e1 0 2 4
choice of extraction method is desirable to increase the portion of extractable polar oxidation products. The observed cytotoxicity after O3 did not argue for an effective non-specific toxicity reduction during ozonation as cytotoxicity was still on an average level of 62%, whereas in three out of six samples toxicity was >88%. These results point to the possibility that cytotoxic effects after O3 were caused by extractable oxidation products. Toxicity reduction after sand filtration of 23% possibly supports an effective byproduct removal, but non-specific toxicity was still elevated compared to ACSF by an average of 23% (Table S10A). An in vivo test with the zebra mussel e performed at the same treatment plant e led to comparable results: non-specific toxic effects occurred after O3, toxicity decreased after O3-SF, and ACSF was most effective in non-specific toxicity removal (Stalter et al., 2010a). Therefore, the applied cytotoxicity assay is possibly a sensitive in vitro tool to evaluate the non-specific toxicity reduction of advanced WW treatment methods. Reliable in vitro screening methods are preferable compared to chronic in vivo approaches due to logistical, cost and time constraints as well as ethical considerations. However, the portion of extractable polar oxidation products has to be increased, not to underestimate a potential toxication after ozonation (Stalter et al., 2010a,b). For a comprehensive evaluation of advanced WW treatment technologies, the analysis of EDC removal effectiveness is important, however, this should not be regarded as the essence of the matter. The challenge is not to confirm an effective reduction of receptor-mediated toxicity (because this is rather predictable with respect to pollutant degradation/ removal) but to test for an increase in non-specific toxicity due to by-product formation during ozonation (Petala et al., 2006; Stalter et al., 2010a,b). An appropriate in vitro bioassay, which enables a fast and reliable toxicity screening, would help to verify the by-product removal with post treatments like sand filtration and could promote an effect directed identification of toxic oxidation by-products.
4.
suggests that doses 0.4 g O3/g DOC are too low for an effective elimination of endocrine disrupting compounds. Cytotoxicity was most effectively removed during activated carbon treatment (61%), while ozonation is less efficient (32%). Volatile substances contribute considerably to cytotoxic effects, particularly after ozonation. Therefore, sample evaporation should be avoided for tests on non-specific toxicity. In the long run, on-site field studies at WW receiving water bodies (including, for example, community analyses of fish, macroinvertebrates, plants and microorganisms as well as biomarker approaches) e before and after upgrading STPs e could allow to draw environmentally relevant conclusions regarding benefits and risks of advanced WW treatment methods.
Acknowledgments The authors would like to thank Stefan Ingenhaag (Grontmij Deutsche Projekt Union GmbH, Cologne, Germany) for his technical assistance at STP Neuss. Installation and support with maintenance of the ozonation plant in Regensdorf was conducted by Daniel Rensch, Steve Brocker (Hunziker-Betatech AG), Saskia Zimmerman and Dr Christoph Ort (EAWAG, Switzerland). Furthermore we thank Prof Charles A. Miller (Tulane University, New Orleans, USA) and Prof John Sumpter (Brunel University, Uxbridge, UK) for providing the recombinant yeast strains, Prof Gu¨nter Stalla and Dr Ulrich Renner (MPI, Munich, Germany) for providing GH3 cells as well as Prof Henner Hollert (RWTH Aachen, Germany), Prof Lucy Lee (Wilfrid Laurier University,), and Prof Niels Bols (University of Waterloo, Canada) for providing RTL-W1 cells. Moreover, we thank Dr Ulrike Schulte-Oehlmann for reviewing the manuscript. This study was part of the EU project Neptune (contract no 036845, SUSTDEV-2005-3.II.3.2) and co-funded by the BAFU (Switzerland) within the Strategy MicroPoll program (contract no 05.0013.PJ/F471-0916).
Conclusions
Conventional activated sludge treatment of wastewater reduces endocrine activity effectively (78e99%), but remaining concentrations of estrogens and anti-androgens still exceed environmental quality standards or effect concentrations, respectively, and hence might be of environmental relevance. Masking effects could explain the absence of anti-androgenicity and anti-estrogenicity due to the high agonistic activities in the untreated wastewater. Accordingly, the appearance of antagonistic activities after the secondary clarifier is possibly due to the more effective removal of respective agonists during conventional treatment. These results indicate the importance of analysing agonists as well as antagonists to evaluate the in vitro endocrine disrupting potential of a complex chemical mixture. The endocrine activity and AhR agonistic activity is effectively reduced during advanced wastewater treatment steps (63e99%), apart from androgenicity and anti-estrogenicity, which were not affected consistently. The analysis of endocrine activity removal at different ozone doses
Appendix. Supplementary material Additional information on treatment plant characteristics, test systems, and test results are available at the journal’s homepage. Supplementary data associated with this article can be found in the online version, at doi:10.1016/j.watres.2010.10.008.
references
Alnafisi, A., Hughes, J., Wang, G.D., Miller, C.A., 2007. Evaluating polycyclic aromatic hydrocarbons using a yeast bioassay. Environmental Toxicology and Chemistry 26 (7), 1333e1339. Benner, J., Ternes, T.A., 2009. Ozonation of propranolol: formation of oxidation products. Environmental Science & Technology 43 (13), 5086e5093. Brack, W., Schirmer, K., Erdinger, L., Hollert, H., 2005. Effectdirected analysis of mutagens and ethoxyresorufin-O-
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 1 5 e1 0 2 4
deethylase inducers in aquatic sediments. Environmental Toxicology and Chemistry 24 (10), 2445e2458. Clara, M., Windhofer, G., Hartl, W., Braun, K., Simon, M., Gans, O., Scheffknecht, C., Chovanec, A., 2010. Occurrence of phthalates in surface runoff, untreated and treated wastewater and fate during wastewater treatment. Chemosphere 78 (9), 1078e1084. Dagnino, S., Gomez, E., Picot, B., Cavailles, V., Casellas, C., Balaguer, P., Fenet, H., 2010. Estrogenic and AhR activities in dissolved phase and suspended solids from wastewater treatment plants. Science of the Total Environment 408 (12), 2608e2615. Escher, B.I., Bramaz, N., Ort, C., 2009. Monitoring the treatment efficiency of a full scale ozonation on a sewage treatment plant with a mode-of-action based test battery. Journal of Environmental Monitoring 11 (10), 1836e1846. Filby, A.L., Shears, J.A., Drage, B.E., Churchley, J.H., Tyler, C.R., 2010. Effects of advanced treatments of wastewater effluents on estrogenic and reproductive health impacts in fish. Environmental Science & Technology 44 (11), 4348e4354. Grund, S., Higley, E., Scho¨nenberger, R., Suter, M., Giesy, J., Braunbeck, T., Hecker, M., Hollert, H., 2010. The endocrine disrupting potential of sediments from the Upper Danube River (Germany) as revealed by in vitro bioassays and chemical analysis. Environmental Science and Pollution Research. doi:10.1007/s11356-010-0390-3. Gustavsson, L.K., Klee, N., Olsman, H., Hollert, H., Engwall, M., 2004. Fate of ah receptor agonists during biological treatment of an industrial sludge containing explosives and pharmaceutical residues. Environmental Science and Pollution Research 11 (6), 379e387. Harris, C.A., Routledge, E.J., Schaffner, C., Brian, J.V., Giger, W., Sumpter, J.P., 2007. Benzotriazole is antiestrogenic in vitro but not in vivo. Environmental Toxicology and Chemistry 26 (11), 2367e2372. Hill, E.M., Evans, K.L., Horwood, J., Rostkowski, P., Oladapo, F.O., Gibson, R., Shears, J.A., Tyler, C.R., 2010. Profiles and some initial identifications of (anti) androgenic compounds in fish exposed to wastewater treatment works effluents. Environmental Science & Technology 44 (3), 1137e1143. Hollender, J., Zimmermann, S.G., Koepke, S., Krauss, M., McArdell, C.S., Ort, C., Singer, H., von Gunten, U., Siegrist, H., 2009. Elimination of organic micropollutants in a municipal wastewater treatment plant upgraded with a full-scale postozonation followed by sand filtration. Environmental Science & Technology 43 (20), 7862e7869. Hollert, H., Durr, M., Olsman, H., Halldin, K., Van Bavel, B., Brack, W., Tysklind, M., Engwall, M., Braunbeck, T., 2002. Biological and chemical determination of dioxin-like compounds in sediments by means of a sediment triad approach in the catchment area of the River Neckar. Ecotoxicology 11 (5), 323e336. Huber, M.M., Ternes, T.A., von Gunten, U., 2004. Removal of estrogenic activity and formation of oxidation products during ozonation of 17 alpha-ethinylestradiol. Environmental Science & Technology 38 (19), 5177e5186. Jobling, S., Beresford, N., Nolan, M., Rodgers-Gray, T., Brighty, G.C., Sumpter, J.P., Tyler, C.R., 2002. Altered sexual maturation and gamete production in wild roach (Rutilus rutilus) living in rivers that receive treated sewage effluents. Biology of Reproduction 66 (2), 272e281. Jobling, S., Tyler, C.R., 2006. Introduction: the ecological relevance of chemically induced endocrine disruption in wildlife. Environmental Health Perspectives 114, 7e8. Jobling, S., Burn, R.W., Thorpe, K., Williams, R., Tyler, C., 2009. Statistical modeling suggests that antiandrogens in effluents from wastewater treatment works contribute to widespread sexual disruption in fish living in English rivers. Environmental Health Perspectives 117 (5), 797e802.
1023
Joss, A., Siegrist, H., Ternes, T.A., 2008. Are we about to upgrade wastewater treatment for removing organic micropollutants? Water Science and Technology 57 (2), 251e255. Katsiadaki, I., Morris, S., Squires, C., Hurst, M.R., James, J.D., Scott, A.P., 2006. Use of the three-spined stickleback (Gasterosteus aculeatus) as a sensitive in vivo test for detection of environmental antiandrogens. Environmental Health Perspectives 114, 115e121. Lee, L.E.J., Clemons, J.H., Bechtel, D.G., Caldwell, S.J., Han, K.B., Pasitschniakarts, M., Mosser, D.D., Bols, N.C., 1993. Development and characterization of a rainbow-trout livercell line expressing cytochrome P450-dependent monooxygenase activity. Cell Biology and Toxicology 9 (3), 279e294. Liu, Z.-h., Kanjo, Y., Mizutani, S., 2009. Removal mechanisms for endocrine disrupting compounds (EDCs) in wastewater treatment e- physical means, biodegradation, and chemical advanced oxidation: a review. Science of the Total Environment 407 (2), 731e748. Luster-Teasley, S.L., Yao, J.J., Herner, H.H., Trosko, J.E., Masten, S. J., 2002. Ozonation of chrysene: evaluation of byproduct mixtures and identification of toxic constituent. Environmental Science & Technology 36 (5), 869e876. Macova, M., Escher, B.I., Reungoat, J., Carswell, S., Chue, K.L., Keller, J., Mueller, J.F., 2010. Monitoring the biological activity of micropollutants during advanced wastewater treatment with ozonation and activated carbon filtration. Water Research 44 (2), 477e492. Miller, C.A., 1999. A human aryl hydrocarbon receptor-signaling pathway constructed in yeast displays additive responses to ligand mixtures. Toxicology and Applied Pharmacology 160 (3), 297e303. Moltmann, J.F., Liebig, M., Knacker, T., Keller, M., Scheurer, M., Ternes, T., 2007. Relevance of Endocrine Disrupting Substances and Pharmaceutical in Surface Waters. Final report. German Federal Environmental Agency. http://www. umweltdaten.de/publikationen/fpdf-l/3324.pdf Contract no. 20524205. Nishihara, T., Nishikawa, J., Kanayama, T., Dakeyama, F., Saito, K., Imagawa, M., Takatori, S., Kitagawa, Y., Hori, S., Utsumi, H., 2000. Estrogenic activities of 517 chemicals by yeast two-hybrid assay. Journal of Health Science 46 (4), 282e298. Nowotny, N., Epp, B., von Sonntag, C., Fahlenkamp, H., 2007. Quantification and modeling of the elimination behavior of ecologically problematic wastewater micropollutants by adsorption on powdered and granulated activated carbon. Environmental Science & Technology 41 (6), 2050e2055. Palomino, J.C., Martin, A., Camacho, M., Guerra, H., Swings, J., Portaels, F., 2002. Resazurin microtiter assay plate: Simple and inexpensive method for detection of drug resistance in Mycobacterium tuberculosis. Antimicrobial Agents and Chemotherapy 46 (8), 2720e2722. Petala, M., Samaras, P., Zouboulis, A., Kungolos, A., Salkellaropoulos, G., 2006. Ecotoxicological properties of wastewater treated using tertiary methods. Environmental Toxicology 21 (4), 417e424. Routledge, E.J., Sumpter, J.P., 1996. Estrogenic activity of surfactants and some of their degradation products assessed using a recombinant yeast screen. Environmental Toxicology and Chemistry 15 (3), 241e248. Santos, M.M., Reis-Henriques, M.A., Guillot, R., Lima, D., FrancoDuarte, R., Mendes, I., Queiros, S., Castro, L.F.C., 2008. Antiandrogenic effects of sewage treatment plant effluents in the prosobranch gastropod Nucella lapillus. Comparative Biochemistry and Physiology.Toxicology & Pharmacology 148 (1), 87e93. Schaar, H., Clara, M., Gans, O., Kreuzinger, N., 2010. Micropollutant removal during biological wastewater
1024
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 1 5 e1 0 2 4
treatment and a subsequent ozonation step. Environmental Pollution 158 (5), 1399e1404. Stalter, D., Magdeburg, A., Oehlmann, J., 2010a. Comparative toxicity assessment of ozone and activated carbon treated sewage effluents using an in vivo test battery. Water Research 44 (8), 2610e2620. Stalter, D., Magdeburg, A., Weil, M., Knacker, T., Oehlmann, J., 2010b. Toxication or detoxication? In vivo toxicity assessment of ozonation as advanced wastewater treatment with the rainbow trout. Water Research 44 (2), 439e448. Suares Rocha, P., Azab, E., Schmidt, B., Storch, V., Hollert, H., Braunbeck, T., 2010. Changes in toxicity and dioxin-like activity of sediments from the Tieteˆ River (Sa˜o Paulo, Brazil). Ecotoxicology and Environmental Safety 73 (4), 550e558. Sugihara, K., Okayama, T., Kitamura, S., Yamashita, K., Yasuda, M., Miyairi, S., Minobe, Y., Ohta, S., 2008. Comparative study of aryl hydrocarbon receptor ligand activities of six chemicals in vitro and in vivo. Archives of Toxicology 82 (1), 5e11.
Thomas, K.V., Langford, K., Petersen, K., Smith, A.J., Tollefsen, K. E., 2009. Effect-directed identification of naphthenic acids as important in vitro xeno-estrogens and anti-androgens in North Sea offshore produced water discharges. Environmental Science & Technology 43 (21), 8066e8071. von Gunten, U., 2003. Ozonation of drinking water: part I. Oxidation kinetics and product formation. Water Research 37 (7), 1443e1467. Wagner, M., Oehlmann, J., 2009. Endocrine disruptors in bottled mineral water: total estrogenic burden and migration from plastic bottles. Environmental Science and Pollution Research 16 (3), 278e286. Weiss, J.M., Hamers, T., Thomas, K.V., van der Linden, S., Leonards, P.E.G., Lamoree, M.H., 2009. Masking effect of antiandrogens on androgenic activity in European river sediment unveiled by effect-directed analysis. Analytical and Bioanalytical Chemistry 394 (5), 1385e1397. Zhang, H.C., Huang, C.H., 2003. Oxidative transformation of triclosan and chlorophene by manganese oxides. Environmental Science & Technology 37 (11), 2421e2430.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
Available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Surveillance of adenoviruses and noroviruses in European recreational waters A. Peter Wyn-Jones a,*, Annalaura Carducci b, Nigel Cook c, Martin D’Agostino c, Maurizio Divizia d, Jens Fleischer e, Christophe Gantzer f, Andrew Gawler g, Rosina Girones h, Christiane Ho¨ller i, Ana Maria de Roda Husman j, David Kay a, Iwona Kozyra k, Juan Lo´pez-Pila l, Michele Muscillo m, Maria Sa˜o Jose´ Nascimento n, George Papageorgiou o, Saskia Rutjes j, Jane Sellwood p, Regine Szewzyk l, Mark Wyer a a
IGES, University of Aberystwyth, Ceredigion, SY23 3DB, UK Department of Biology, Universita` di Pisa, Italy c Food and Environment Research Agency, FERA, York, UK d Faculty of Medicine, Tor Vergata University, Rome, Italy e Landesgesundheitsamt Baden-Wu¨rttemberg, Germany f Faculte´ de Pharmacie, University Henri Poincare´, Nancy, France g Environment Agency, United Kingdom h Department of Microbiology, Faculty of Biology, University of Barcelona, Spain i Bayerisches Landesamt fu¨r Gesundheit und Lebensmittelsicherheit, Germany j National Institute for Public Health and the Environment (RIVM), The Netherlands k National Veterinary Research Institute, Pulawy, Poland l Umweltbundesamt, Berlin, Germany m Istituto Superiore Sanita`, Rome, Italy n Faculdade de Farma´cia, Universidade do Porto, Porto, Portugal o Environmental Virology Laboratory, State General Laboratory, Cyprus p Environmental Virology Unit, Health Protection Agency, UK b
article info Article history: Received 27 April 2010 Received in revised form 20 August 2010 Accepted 13 October 2010 Available online 29 October 2010
abstract Exposure to human pathogenic viruses in recreational waters has been shown to cause disease outbreaks. In the context of Article 14 of the revised European Bathing Waters Directive 2006/7/EC (rBWD, CEU, 2006) a Europe-wide surveillance study was carried out to determine the frequency of occurrence of two human enteric viruses in recreational waters. Adenoviruses were selected based on their near-universal shedding and environmental survival, and noroviruses (NoV) selected as being the most prevalent gastroenteritis agent worldwide. Concentration of marine and freshwater samples was done by adsorption/elution followed by molecular detection by (RT)-PCR. Out of 1410 samples, 553 (39.2%)
Keywords:
were positive for one or more of the target viruses. Adenoviruses, detected in 36.4% of
Adenoviruses
samples, were more prevalent than noroviruses (9.4%), with 3.5% GI and 6.2% GII, some
Noroviruses
samples being positive for both GI and GII. Of 513 human adenovirus-positive samples, 63
Bathing water
(12.3%) were also norovirus-positive, whereas 69 (7.7%) norovirus-positive samples were
River water
adenovirus-negative. More freshwater samples than marine water samples were virus-
Sea water
positive. Out of a small selection of samples tested for adenovirus infectivity,
* Corresponding author. Tel.: þ44 191 384 2749. E-mail address:
[email protected] (A.P. Wyn-Jones). 0043-1354/$ e see front matter ª 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2010.10.015
1026
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
Recreational water
approximately one-quarter were positive. Sixty percent of 132 nested-PCR adenovirus-
Water quality
positive samples analysed by quantitative PCR gave a mean value of over 3000 genome copies per L of water. The simultaneous detection of infectious adenovirus and of adenovirus and NoV by (RT)PCR suggests that the presence of infectious viruses in recreational waters may constitute a public health risk upon exposure. These studies support the case for considering adenoviruses as an indicator of bathing water quality. ª 2010 Elsevier Ltd. All rights reserved.
1.
Introduction
Enteric viruses have frequently been implicated in recreational water-related gastro-intestinal (G.I.) disease (Sinclair et al., 2009). Studies in Europe and the US suggest that most infections contracted as a result of swimming, canoeing or other recreational use of sewage-polluted water may be viral in nature (e.g. Medema et al., 1995; Gray et al., 1997). Enteric viruses may cause asymptomatic or mild infections in humans, but these faecal-orally transmitted viruses may also cause more serious disease, such as hepatitis and meningitis, especially in vulnerable groups, e.g. young children (Nwachuku and Gerba, 2006). Enteric viruses are recognized as agents that can cause large outbreaks throughout the world with thousands of cases (Sarguna et al., 2007; Bucardo et al., 2007; Iijima et al., 2008; Zhang et al., 2009). Novel emerging viruses such as SARS coronavirus, human parechovirus and zoonotic influenza viruses also appear to be excreted in faeces but the evidence for enteric transmission is not always clear (Ding et al., 2004). Transmission routes for enteric viruses may be diverse such as personeperson, food- or waterborne associated with insufficient hygiene and sanitation (Koopmans et al., 2002; Wyn-Jones and Sellwood, 2001). Disease outbreaks associated with enteric viruses, such as noroviruses and astroviruses, in bathing water have been described (Hauri et al., 2005; Maunula et al., 2004). However, bathing water-related outbreaks may be easily missed due to either unidentified source or unidentified agent, or both. Enteric viruses in water may originate from discharges of raw or treated sewage, run-off of animal manure or directly from humans or animals. Viruses commonly associated with waterborne disease include the human adenoviruses (HAdVs), noroviruses (NoVs), hepatitis A and E viruses (HAV, HEV), parvoviruses, enteroviruses, and rotaviruses (RVs). In addition, sewage, especially from slaughterhouses, may contain (for example) animal adenoviruses, sapoviruses, and HEV (Hundesa et al., 2006), which may be zoonotic. Viruses originating from (un)treated sewage can contaminate bathing water after discharge into surface waters (in)directly used for recreational water activities. All are capable of infection by ingestion. Some multiply in the intestine and may cause diarrhoea and/or vomiting, while some are associated with tissues (e.g. the liver) other than the gut. The viruses responsible for waterborne infections are not usually identified at the time of a disease outbreak following recreational water activity, and robust associations between the simultaneous presence of virus in faeces of affected individuals and in the water are only occasionally demonstrated (e.g. Hoebe et al., 2004). The epidemiological picture of disease associated with recreational use of water is therefore far from complete, and measures to limit
enteric disease after exposure to recreational water are based on water quality parameters built on the detection of faecal bacterial indicator organisms (FIOs). However, it has been shown that water conforming to bacterial standards may contain high levels of human enteric viruses and that FIOs often fail to predict the risk for waterborne pathogens including enteric viruses (Gerba et al., 1979; Lipp et al., 2001). Further, several studies have shown that levels of indicator bacteria do not correlate with those of viruses, particularly when faecal indicator concentrations are low (Contreras-Coll et al., 2002). Viruses are known to be more resistant to environmental degradation than bacteria (Vasl et al., 1981; Thurston-Enriquez et al., 2003; Rzezutka and Cook, 2004; de Roda Husman et al., 2009). Together with the understanding that G.I. illness may be due to viruses rather than bacteria, this provides a case for using a viral indicator of human faecal pollution rather than to rely exclusively on bacterial parameters. Bathing water quality in the European Union (EU) has been regulated since 1976 by the Bathing Water Directive (76/160/ EEC). In 2006 this was revised (rBWD, CEU, 2006) by including enterococci (and, in fresh waters, Escherichia coli) as the principal microbial determinants which placed the microbiological parameters on a firmer scientific footing (Kay et al., 1994, 2004: Wiedenmann et al., 2006; WHO, 2003) and allowed classification of bathing waters to be undertaken with more confidence. When tested at sufficient frequency E. coli may be a useful indicator of faecal pollution and therefore of the probability of waterborne disease. However, in the EU Directive the frequency is only about once in two weeks and testing takes two days. The earlier Directive included an enterovirus parameter which stipulated that 95% of 10-L water samples taken during the bathing season should contain no (zero p.f.u.) enteroviruses. This was based on early work (described by Farrah and Bitton, 1990) which suggested that, for poliovirus, Coxsackie A and Coxsackie B viruses, between one and twenty virus infectious units might be sufficient to cause infection. The pathogenesis of enterovirus infections is now better understood, and this belief is considered unsound in determining water quality. Further, although important pathogens in many contexts, the presence of enteroviruses in water does not necessarily correlate with the presence of pathogens such as hepatitis A virus (Dubrou et al., 1991; Pina et al., 1998). The enterovirus parameter was removed during the revision of the 1976 Directive. Concentrations of some viruses in surface waters can be determined by cell culture monolayer plaque assays, but the technique is not applicable to most viruses of prime interest. Furthermore, cell culture is expensive and time-consuming, and detection of viruses is now done mainly by molecular methods such as reverse transcription RT-PCR or nucleic acid
1027
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
sequence-based amplification (NASBA) which amplify RNA/ DNA. Although mainly described as end-point assays, amplification products of both techniques can be detected by realtime methods. The major advantages of real-time detection are hands-on time and the ability to quantify amplification products, which is very important in being able to estimate the public health risks of low levels of enteric viruses in bathing water. A viral indicator may be better suited to indicate the risk of human pathogenic viruses in bathing waters. However, cell culture-based methods for viral detection are costly, require specialised skills and equipment, and have too long a turnaround time. For this reason, the EU Framework 6 Project VIROBATHE was done to devise a robust, rapid and cost-efficient method for routine compliance monitoring of enteric viruses in recreational waters. Part of the work involved Europe-wide surveillance of recreational waters to determine the frequency of target virus occurrence and, to a limited extent, serotypes and quantities. So that the virus levels could be seen in the context of compliance-related water quality, the work also included determination of FIO levels to provide general water quality data. The viruses selected as targets were adenoviruses and noroviruses. The former are shed by many individuals (often without showing symptoms), they are more environmentally robust than enteroviruses (Enriquez et al., 1995; ThurstonEnriquez et al., 2003), they have been found in surveys of polluted waters (e.g. Pina et al., 1998; Laverick et al., 2004; Lee et al., 2004; Miagostovich et al., 2008), and have been associated with outbreaks of disease in swimming pools (e.g. Papapetropolou and Vantarakis, 1995; Harley et al., 2001) and other recreational waters (Sinclair et al., 2009). Being DNA viruses, their detection by PCR does not have the problems associated with the genetic variation seen with RNA viruses. They are also more likely to be detected in recreational water samples (e.g. Pina et al., 1998; Miagostovich et al., 2008), especially if sensitive nucleic acid detection methods are used, and they may therefore provide the best indicator of viral faecal pollution. Noroviruses are the most important cause of acute viral gastroenteritis in people of all age groups and many waterborne outbreaks have been reported. Sinclair et al. (2009) reviewed 55 recreational water-related G.I. disease outbreaks of which 25 (46%) were reported as caused by noroviruses. The study reported here was performed to demonstrate that a common concentration protocol could be used across recreational waters in widely diverse geographical areas, that viruses concentrated by this protocol could be detected by a rapid molecular method, that it was possible to enumerate viruses and to investigate whether there was a range of sero/ genotypes of the target viruses present across the locations studied.
2.
Materials and methods
2.1.
Survey design
Each of the 15 Surveillance Laboratories located in nine countries selected up to two sites for study which were sampled during the EU Bathing Season 2006, and samples were concentrated and analysed for the target viruses by
molecular means. FIOs and various physico-chemical parameters were also determined. Data were sent to the coordinating Laboratory at the University of Aberystwyth for collation.
2.2.
Sampling sites
Each laboratory selected up to two sites (main site and second site) for the study (Table 1 and Fig. 1). The principal criterion for a site being chosen was its current use for recreational water activity; sites were not chosen on the basis of being EUdesignated bathing waters, nor because they had a history of pollution in the area, though several sites were known to be impacted by sewage effluent. A minimum of 80 10-L water samples from the main site was taken and up to 20 additional samples were taken in the event of (e.g.) heavy rain or when investigators considered that there was some other occurrence which may have resulted in deterioration of water quality. The second site could also be used if the main site yielded negative data in the first stages of sampling, or for taking the 20 additional samples following the 80 minimum to be taken at the main site. Thus, each laboratory could focus on one site (100 samples) or divide surveillance between the main site (80 samples) and the second site (20 samples). In practice both approaches were used, so in total, 24 sites were sampled. Sites were sampled at approximately weekly intervals from the end of May to the beginning of November 2006, which included the Bathing Season in all Member States. On each
Table 1 e Location of sampling sites. Site* 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Country
Location
Cyprus France Germany
Larnaca Nancy BadenWu¨rttemberg Germany BadenWu¨rttemberg Germany Bavaria Germany Berlin Germany Berlin Italy Pisa Italy Pisa Italy Castel Gandolfo Italy Ardea (Rome) Italy Pomezia (Rome) Netherlands Durgerdam Netherlands Leerdam Poland Pulawy Portugal Porto Portugal Porto Spain Barcelona Spain Barcelona UK York UK Devon UK Devon UK Kew (London) UK Reading
*See also Fig. 1 for site locations.
Site name
Water type
Larnaca Marina Tomblaine Neckar River
Marine Fresh Fresh
Kirchentellinsfurt Lake Amper Grasslfing Wannsee Landwehrkanal San Rossore Bocca d’Arno Castel Gandolfo Lake Fosso dell’Incastro Rio Torto Kinselmeer Linge VistulaRiver Molhe South Molhe North Gava` Gava` Naburn Lock Axmouth Harbour River Kenn River Thames River Thames
Fresh Fresh Fresh Fresh Marine Marine Fresh Marine Marine Fresh Fresh Fresh Marine Marine Marine Marine Fresh Marine Marine Fresh Fresh
1028
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
Fig. 1 e Location of sampling sites.
sampling occasion, four 10-L samples (a ‘tetrad’), plus one additional sample for positive Quality Control (QC) purposes, were collected from each site. One 250 mL sample for bacterial faecal indicators was also taken. In total each laboratory processed and analysed at least 100 water samples for virus detection and 25 samples for bacterial enumeration.
2.3.
Sample processing
Many methods for the concentration and detection of enteric viruses in water samples have been described (Wyn-Jones and Sellwood, 2001). For virological water quality to be assessed on a comparable basis, a single method common to all laboratories was needed for each water type (fresh or coastal/transitional) analysed during the surveillance programme. Prior to the surveillance stage several different methods were evaluated (see Section 3.1) using HAdV2 and NoV GII.4, and the best in terms of virus recovery and capital/recurrent costs was selected. The HAdV2 was obtained from the UK Health Protection Agency (HPA) National Collection of Pathogenic Viruses (NCPV), where the virus genome was authenticated. Virus was grown and assayed by plaque assay in A549 cultures and distributed by the HPA Environmental Virology Unit to
other laboratories. Norovirus GII.4 was identified in a faecal sample from an outbreak in a care home and the identity confirmed by sequencing. End-point dilution assay by RT-PCR gave a titre of 109. The suspension was distributed at 103 which provided sufficient virus for evaluation and quality control purposes for all laboratories throughout the project. Process characterisation was done by four experienced laboratories concentrating replicate samples of water spiked with HAdV2 and analysing the concentrates for recovered virus.
2.3.1. Concentration of freshwater samples by glass wool filtration For freshwater samples a modification of the glass wool method of Vilagine`s et al. (1993) was used. The glass wool filter was made by compressing 10 g glass wool (type 725; Rantigny, Saint-Gobain, France) into a 30 cm by 3 cm polystyrene column to obtain a filter height of 6e8 cm. The filter was washed by gravity with 50 mL volumes of (in order) 1 M HCl, tap water, and 1 M NaOH, followed by tap water until the filtrate pH was neutral. Water samples (10-L) were conditioned with 1 M or 0.1 M HCl to pH 3.5 to enhance binding of the viruses to the filter and passed through the filter at a rate not exceeding 1.5 L min1. When all the sample had passed
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
through the filter the virus was eluted from the glass wool by slow (20e30 min) passage of 200 mL 3% (w/v) beef extract at pH 9.5 in 0.05 M glycine buffer through the filter. The eluate was flocculated by the addition of 1 M and 0.1 M HCl until the pH reached 3.5. The resultant protein floc, containing virus, was deposited by centrifugation at 7500 g for 30 min, dissolved to a final volume of 10 mL phosphate buffered saline (PBS) and stored at 20 C pending further analysis.
2.3.2. Concentration of marine water samples by nitrocellulose membrane filtration Coastal/transitional water samples were processed by filtration through nitrocellulose membranes, elution and organic flocculation (Wyn-Jones et al., 2000). The sample, at pH 3.5, was passed through a 142 mm diameter glass fibre pre-filter and a nitrocellulose membrane in a Sartorius filter holder at a maximum rate of 1.5 L min1. The filtrate was run to waste and the virus was then eluted from the membrane by slow passage (10 min) of 200 ml skimmed milk solution (0.1% in 0.05 M glycine buffer). The eluate was flocculated by reducing its pH to 4.5 with M HCl and centrifuging as above.
2.4.
Extraction of nucleic acids from sample concentrates
Nucleic acid (NA) was extracted from 5 mL volumes of sample concentrate using the NucliSens miniMAG system (Biome´rieux, France) according to manufacturer’s instructions, with slight modifications comprising centrifugation at 1500 g for 2 min after addition of the silica suspension to reduce the chance of cross-contamination. The final 100 mL NA extract was centrifuged at 13,000 g for 1 min to pellet any remaining traces of silica which could inhibit downstream (RT)PCR reactions, the supernatant was transferred to a clean microfuge tube and was stored at 80 C if not used immediately.
2.5.
Human adenovirus PCR
For the detection of human adenovirus in the water samples the nested-PCR based on the method of Allard et al. (2001) was employed, using primers Hex1deg and Hex2deg for the first round of amplification and primers nehex3deg and nehex4deg for the second round. Additionally, an internal amplification control (IAC, see below) was incorporated in the assay, and a carryover contamination prevention system utilising uracil-Nglycosylase (UNG) in the first round PCR and dUTP (replacing dTTP) in both PCRs. The reaction incorporated a hot-start polymerase (Platinum Taq DNA polymerase, Life Technologies Inc.). The target amplicon sizes were 301 bp in the first round and 171 bp in the second round. The first round reaction conditions were as follows: 10 mL DNA, 1X Platinum Taq buffer, 1.5 mM Mgþþ, 250 mM dNTPs, 0.5 mM primer Hex1deg, 0.5 mM primer Hex2deg, 1U Platinum Taq (Life Technologies Inc.), and 1 U HK-UNG (Epicentre, Madison, Wisconsin). Five mL IAC were added in the first round. Adenovirus DNA (20 ng mL1), and ultrapure water were included as positive and negative reaction control, respectively. After 10 min at 50 C (UNG) and 10 min at 95 C (activation of Taq polymerase), cycling conditions included 45 cycles of 94 C for 30 s, 55 C for 30 s and 72 C for 1 min, followed by a final extension of 72 C for 5 min. The second round reaction conditions were: 1X
1029
Platinum Taq buffer, 1.5 mM Mgþþ, 100 mM dNTPs, 0.5 mM primer nehex3deg, 0.5 mM primer nehex4deg, and 1U Platinum Taq. Two mL from the first round reaction were used as target. The thermocycling conditions were 94 C for 3 min, then 45 cycles of 94 C for 30 s, 55 C for 30 s and 72 C for 1 min, followed by a final extension of 72 C for 5 min. The amplicons were electrophoresed in a 2% agarose gel stained with 10 ng mL1 ethidium bromide or equivalent nucleic acid staining methods such as SYBR-Gold, and subsequently visualised by UV transillumination.
2.6.
Norovirus RT-PCR
To detect norovirus, the nested RT-PCR based on the method of Vennema et al. (2002) was used, and comprised amplification of norovirus RNA-dependent RNA polymerase (RdRp) gene sequences by RT-PCR followed by a semi-nested PCR for each genogroup (G). Depending on the laboratory, contamination carryover prevention was also incorporated utilising uracil-N-glycosylase (UNG) in the PCR. The target amplicon sizes were 327 bp in the RT-PCR, 188 bp in the GI nested PCR, and 237 bp in the GII nested PCR. Reverse transcription PCR conditions were as follows: 1X OneStep buffer (Qiagen, UK), 400 mM each dNTP, 1X OneStep enzyme mix (Qiagen, UK), 0.5 mM primer JV12Y, 0.5 mM primer JV13i, and 50U RNasin (RNasinPlus, Promega, UK), 1U Platinum Taq (Life Technologies Inc.). Five mL IAC were added in the first round. A 10 mL sample of nucleic acid was used as target. The thermocycling conditions were 50 C for 30 min, 95 C for 15 min, then 40 cycles of 94 C for 1 min, 37 C for 1 min and 72 C for 1 min, followed by a final extension of 72 C for 10 min. The second round PCR conditions were as follows: 1X Platinum Taq buffer, 2.0 mM Mgþþ, 200 mM dATP, 200 mM dCTP, 200 mM dGTP, 400 mM dUTP, 0.4 mM primer JV12Y, 0.4 mM primer Ni-R, 1U HK-UNG and 1U Platinum Taq. One mL from the first round reaction was used as target. The thermocycling conditions were 50 C for 10 min, 95 C for 10 min, 96 C for 3 min then 40 cycles of 95 C for 1 min, 40 C for 1 min and 72 C for 1 min, followed by a final extension of 72 C for 10 min. The amplicons were electrophoresed in a 2% agarose gel stained with 10 ng mL1 ethidium bromide or equivalent nucleic acid staining methods such as SYBR-Gold, and subsequently visualised by UV transillumination.
2.7.
Internal amplification controls (IACs)
The need to guard against false negative results required the use of a novel IAC in each PCR. For adenovirus IACs, oligonucleotides were constructed which contained the adenovirus primer sequences used in each round flanking primer sequences for amplification of invA sequences from Salmonella enterica (Malorny et al., 2003, 2004). The amplicon was cloned into a plasmid (pGem T-Easy vector) by Yorkshire Bioscience Ltd. (York, UK). The resulting pADENOIAC plasmid was linearised at the unique PstI site downstream of the adenovirus IAC insert region. Yorkshire Bioscience supplied pADENOIAC in 100 mL volumes containing 1 mg mL1 plasmid DNA in 10 mM TriseHCl, 1 mM EDTA buffer pH 8.0. The IAC amplicon sizes were 384 bp in the first round and 337 bp in the second round.
1030
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
For the norovirus IAC the RNA was synthesized by the addition of complementary sequences of the first round primers JV12Y and JV13i to part of the b-globin gene, resulting in a PCR product of 369 base pairs. In this same construct sequences complementary to the GI nested-primer Ni-R and to the GII nested-primer GI were included. The construct was subsequently cloned downstream of a T7 RNA-polymerase promoter. The RNA IAC was prepared by Yorkshire Bioscience Ltd. (York, UK) using plasmid pnJV IAC which was linearised with Sal1 restriction endonucleases and purified. The resulting RNA was transcribed using the T7 RNA polymerase transcription system. Template DNA was removed from the preparation during incubation with RNase-free DNase. The RNA was purified by LiCl precipitation followed by multiple phenol/chloroform extractions. The preparation was concentrated to 1.0 mg mL1 by precipitation with ethanol and dissolving in a minimal volume of MilliQ/18.2 MU quality water. Both types of IAC were prepared in single batches by Yorkshire Bioscience, and checked and distributed to all participants by one of the participant laboratories (FERA). Amplification products of the IAC with the GI specific primers produced a PCR product of 228 base pairs, GII-specific amplification resulted in a PCR product of 277 base pairs. The working concentration of each IAC (in 10 mM TriseHCl, 1 mM EDTA buffer pH 8.0, plus 500 ng mL1 bovine serum albumin) was empirically determined as the dilution which consistently (triplicate determinations) gave a positive signal. Aliquots were stored at 20 C (adenovirus IAC) or 70 C (norovirus IAC). In a correctly functioning reaction, an IAC signal should always be produced in the absence of a target signal (high amounts of target can out-compete amplification of the IAC, but then the target signal itself shows that the reaction has worked). In this study, when an (RT)PCR of a sample produced neither IAC nor target signal, the presence of inhibitory substances derived from the water sample was assumed. Consequently, the nucleic extract was diluted ten-fold until the appearance of an IAC or target signal revealed that no inhibition was occurring.
2.8.
Infectivity determination
At least 10 adenovirus-positive (by nested-PCR) samples from each Laboratory were tested for virus infectivity by integrated cell culture-PCR (ICC-PCR, Reynolds et al., 2001; Greening et al., 2002). If any of the four test samples in a tetrad was positive by human adenovirus nested-PCR then the sample concentrate which had given the strongest PCR band was tested for infectious adenovirus by inoculation of cell cultures and nested-PCR analysis of the cultures after zero and five days’ incubation. No infectivity assay was performed if the adenovirus nested-PCR on all four concentrates was negative. At least two 25 cm2 flasks, each containing a monolayer of confluent A549 cells (European Collection of Cell Culture, ECACC, UK) were inoculated with 1 mL of sample concentrate. At least one flask was incubated for five days (T ¼ 5). One flask was analysed without incubation (T ¼ 0), to guard against detection of seed virus. One negative control with cell culture medium only was set up. Following incubation, flasks in the first set (T ¼ 5) were frozen and thawed three times and the
separated supernatant analysed by the adenovirus nested PCR. A positive nested-PCR signal after five days, coupled with a negative reaction after zero days (confirming that inoculum was not being detected) was taken as evidence of virus multiplication, and hence of infectivity.
2.9.
QPCR assay for the detection of HAdV DNA
Virus nucleic acid in at least 10 samples which were positive for adenovirus by nested-PCR from each Laboratory was quantified by real-time qPCR. The nucleic acid extracts from these samples were diluted as was found necessary to observe a signal in the PCR (see Section 2.7). Assays were done in 25-mL reaction mixtures each containing 10 mL of nucleic acid extract and 15 mL of TaqMan Universal PCR Master Mix (Applied Biosystems) containing 0.9 mM of each primer (AdF and AdR) and 0.22 5 mM of fluorogenic probe (AdP1) as previously described (Hernroth et al., 2002). Following activation of the uracil-N-glycosylase (2 min, 50 C) and activation of the AmpliTaq Gold for 10 min at 95 C, 45 cycles (15 s at 95 C and 1 min at 60 C) were performed. A pBR322 plasmid containing the HAdV 41 hexon sequence kindly donated by Dr. Annika Allard from the University of Umea˚, Sweden, was used to construct a standard containing 101e107 copies of DNA in the 10 mL added to the PCR reaction. Each dilution of standard DNA suspensions was run in triplicate. Ten mL of undiluted and a ten-fold dilution of the DNA suspensions obtained from water samples were run in duplicate. In all QPCRs the amount of DNA was defined as the mean of the data obtained. A non-template control and a nonamplification control were added to each run.
2.10.
Sequence analysis
The amplicons obtained after nested-PCR assays of HAdV or NoV were purified using the QIAquick PCR purification kit (QIAGEN, Inc.). Purified DNA was directly sequenced with the ABI PRISM Dye Terminator Cycle Sequencing Ready Reaction kit version 3.1 with Ampli Taq DNA polymerase FS (Applied Biosystems) following the manufacturer’s instructions. The conditions for the 25-cycle sequencing amplification were: denaturing at 96 C for 10 s, annealing for 5 s at 50 C and extension at 60 C for 4 min. The nested primers were used for sequencing at a concentration of 0.05 mM. The results were checked using the ABI PRISM 377 automated sequencer (PerkineElmer, Applied Biosystems). The sequences were compared with the GenBank and the EMBL (European Molecular Biology Library) using the basic BLAST program of the NCBI (The National Center for Biotechnology Information, http://www.ncbi.nlm.nih.gov/BLAST/). Alignments of the sequences were carried out using the ClustalW program of the EBI (European Bioinformatics Institute of the EMBL, http://www.ebi.ac.uk/clustalw/).
2.11.
Faecal indicator organisms
Detection of E. coli and intestinal enterococci was done according to ISO 9308-3 and ISO 7899-1 using Microtiter plates. One laboratory enumerated bacteria by colony-forming units (cfu).
1031
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
The robustness of the methods was calculated using the results obtained from the analysis of quality control samples. Nine laboratories participated in the trial of the methods for analysis of fresh waters and six laboratories participated in the trial of the methods for analysis of marine samples. Test samples comprised 1 mL aliquots of adenovirus Type 2 (containing 200 pfu of virus), and norovirus GII.4 which were added by the participants to their own water samples. A batch of adenovirus Type 2 and a batch of norovirus GII.4 were prepared, distributed into single-use ampoules and sent to each participant. On each sampling occasion 1 mL of the adenovirus Type 2 and 1 mL of the norovirus-positive control material were added to a separate 10-L quality control sample of the recreational water being tested. Negative samples were prepared from a mixture of de-ionised and tap water, or artificial seawater. Each participant analysed at least 25 sets of quality control samples. The raw data sent by each laboratory were statistically analysed according to the recommendations of Scotter et al. (2001) by the methods of Langton et al. (2002). The trial sensitivity was defined as the percentage of positive samples giving a correct positive signal, and trial specificity was defined as the percentage of negative samples giving a correct negative signal. Accordance (repeatability of qualitative data) was defined as the percentage chance of finding the same result, positive or negative, from two identical samples analysed in the same laboratory under predefined repeatability conditions, and concordance (reproducibility of qualitative data) was defined as the percentage chance of finding the same result, positive or negative, from two identical samples analysed in different laboratories under predefined repeatability conditions. These calculations take into account different replication in different laboratories by weighting results appropriately. The concordance odds ratio (COR) was the degree of inter-laboratory variation in the results, and expressed as the ratio between accordance and concordance percentages (Langton et al., 2002). The COR value may be interpreted as the likelihood of getting the same result from two identical samples, whether they are sent to the same laboratory or to two different laboratories. The closer the value is to 1.0, the higher is the likelihood of getting the same result. Confidence intervals for accordance, concordance and COR were calculated by the method of Davison and Hinckley (1997); each laboratory was considered representative of all laboratories in the “population” of laboratories, not just those participating in this analysis.
3.
Results
The study surveillance period ran from the end of May until early November 2006. Nine participant Laboratories collected samples at both of their sampling sites, whereas six Laboratories took samples from only their main site. Thirteen fresh water sites and 11 marine sites were sampled (Table 1 and Fig. 1). A total of 1410 samples was taken of which 928 were from fresh water and 482 were from marine sites (Table 1).
3.1.
Virus detection
Four experienced laboratories evaluated the concentration methods by processing replicate samples using different methods, and analysing the concentrates by (RT)PCR and, for HAdV2, monolayer plaque assay in A549 cultures. Concentration by three different methods gave mean recoveries of 49% and 37% of seeded HAdV2 from fresh and artificial sea water respectively, as measured by plaque assay. Across all evaluating laboratories, concentration of HAdV2 in spiked freshwater samples by glass wool with elution using beef extract gave a mean recovery of 57.1% (range 34.2%e78.2%), while concentration of virus in spiked artificial seawater samples with skimmed milk elution gave a mean recovery of 35.4% (range 22.5%e43.8%). The variation between laboratories’ performance made decisions on method choice based only on recovery values less than clearcut, which is why other factors such as cost were also taken into account. From the overall surveillance data 553 out of 1410 samples (39.2%) were positive for one or more of the target viruses (Fig. 2). This corresponded to 582 virus detections, some samples being positive for more than one kind of virus. Adenoviruses were detected more often than noroviruses, 513 (36.4%) samples being positive for one or more human adenovirus types, while 132 samples (9.4%) tested positive for one or both norovirus genogroups; these were divided between GI (49, 3.5% samples positive) and GII (88, 6.2%, Fig. 2). Five samples (two marine and three fresh water) were positive for both norovirus genogroups. Out of the 513 human adenovirus-positive samples, 63 (12.3%) were also positive for one or both NoV genogroups (33 out of 381 freshwater samples and 30 out of 132 marine samples). Just four samples (two fresh water and two marine), were positive for all three virus types. Interestingly, 69 samples (22 fresh water and 47 marine) were positive for one or both norovirus genogroups while testing negative for adenovirus.
3.2.
Water type
Freshwater sites showed a higher frequency of virus-positive samples than marine sites (Fig. 3). Adenoviruses were detected more often in fresh water (381 adenovirus-positive samples out of 928, 41.1%, Fig. 3) than in marine water (132 out of 482, 27.4%). Conversely, noroviruses (either GI or GII or both)
50
% positive of 1410 samples
2.12. Quality assurance e robustness of the concentration and detection methods
40
30 553
20
samples samples positive positive
513
10 132
0
49
All viruses %
HAdV %
All NoV %
NoV GI %
88
NoV GII %
Fig. 2 e Summary of virus detection in all water types.
1032
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
were detected less often in freshwater samples (58 noroviruspositive samples out of 928, 6.3%) than in marine water (79 out of 482, 16.4%, Fig. 3). Further, in marine waters the detection rate of norovirus GI was almost as high as norovirus GII (7.9% compared with 8.5%), which differs from the clinical context where GI viruses are found much less frequently than GII types in patients from gastroenteritis outbreaks, even in surveys of unaffected individuals (e.g. Verhoef et al., 2009). However, these high GI detection rates were mainly due to just four sites having higher frequencies of NoV GI.
3.3.
Variation according to site
Virus occurrence ranged widely between sites. Some Laboratories reported no viruses at all in any sample while others found many samples positive for at least one virus. Human adenoviruses were detected in all except two sites, one marine and one fresh water. Sites were chosen on the basis of their recreational use, and most were impacted by sewage effluent. Among the marine sites, 55% of samples from Pomezia, Rome, were positive for HAdV, while none was found at one of the Barcelona sites (though more samples were positive at the second site), and none was detected at Larnaca, Cyprus, where it is known no sewage is discharged. Among the freshwater sites, no HAdV was found at Kirchentellinsfurt Lake in BadenWu¨rttemberg, while 80% of samples were HAdV-positive at Amper Grasslfing in Bavaria and 91% were positive at the site at Tomblaine, Nancy, a site well recognised for its anthropogenic effects as well as its recreational activities (mainly canoeing). With respect to noroviruses, five out of 11 marine water sites, and four out of 13 freshwater sites gave samples positive for GI noroviruses, the highest recovery from a marine site being 30% of samples positive at Pomezia (Rome), and that from a freshwater site being 10% of samples positive at Reading. Genogroup II noroviruses were detected at eight marine and eight freshwater sites, the highest frequencies being 16.3% positive samples at Ardea (Rome, marine), and 15% at Durgerdam (freshwater). Overall, the data showed that adenoviruses were present at more sites than noroviruses. Some sites had more than 25% samples virus-positive in respect of both adenoviruses and noroviruses. To illustrate
3.4.
Virus infectivity by ICC-PCR
From each Laboratory, at least 10 samples that gave a strong HAdV-positive signal by nested PCR were analysed further by inoculation into cell culture and analysis of the supernatants by PCR. Fifty-one of 482 marine sample concentrates and 226 of 928 freshwater sample concentrates were tested. The results are shown in Table 2. Twenty-four (47%) of the marine water samples were found to be positive by nested PCR following inoculation of A549 cell cultures and where uninoculated control cultures remained negative, and where cultures inoculated and sampled immediately after inoculation also remained negative. Forty-six (20%) freshwater samples were positive for infectious HAdV.
3.5.
QPCR assay for the detection of HAdV DNA
A total of 132 marine and freshwater samples which had previously tested HAdV-positive by nested-PCR were further
14 12
Number of sites
Fig. 3 e Adenovirus and norovirus detection in marine and fresh waters.
the distribution of sites relative to the frequency of virus detection, Fig. 4 (marine sites) and Fig. 5 (freshwater sites) show the frequencies of positive samples divided into five groups (0%, 1e25%, 26e50%, 51e75% and 76e100% positive samples) plotted against the number of sites in each group. Thus there was, for example, one of the 11 marine sites which reported no samples being HAdV-positive, five sites in which between 1% and 25% samples were HAdV-positive, three sites between 26% and 50% and two sites with between 51% and 75% HAdV-positive (Fig. 4). There were several sites where the adenovirus frequency was in the higher categories and two freshwater sites where over 76% samples were HAdV-positive. Examination of the marine water norovirus GI data, when divided according to sites, shows that almost all the norovirus GI-positive samples (37/38) were found in four sites in Italy, the only other norovirus GI-positive marine water sample being found in one of the sites in Portugal. There was no evidence of outbreaks of norovirus-related disease in Italy in the areas local to the detection of GI virus in the environmental samples at the time when the samples were taken.
10
HAdV NoV GI
8
NoV GII
6 4 2 0 0%
1-25%
26-50%
51-75%
76-100%
% positive samples
Fig. 4 e Distribution of virus-positive sites e marine. Frequencies of positive samples divided into five groups (0%, 1e25%, 26e50%, 51e75% and 76e100% samples positive) plotted against the number of sites in each group.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
3.7.
14
1033
Relationship of virus frequency to faecal indicators
Number of sites
12 10
HAdV NoV GI NoV GII
8 6 4 2 0 0%
1-25%
26-50%
51-75%
76-100%
% positive samples
Fig. 5 e Distribution of virus-positive sites e fresh water. Frequencies of positive samples divided into five groups (0%, 1e25%, 26e50%, 51e75% and 76e100% samples positive) plotted against the number of sites in each group.
analysed by the QPCR assay of Hernroth et al. (2002). Eighty (60.6%) samples were positive, with a mean value of 3260 genome copies (GC)/L of water. The percentage of positive samples was similar in both types of recreational water; 61.3% positive for fresh water with mean GC values of 558 GC/L versus 58.6% positive for marine waters with mean concentrations of 8810 GC/L.
3.6. Analysis of the sequence of the PCR products obtained Fifty-three samples were further analysed to type the HAdV present. The most frequently detected HAdV serotypes were 12 (n ¼ 4), 31 (n ¼ 8), 40 (n ¼ 4) and 41 (n ¼ 22). Serotypes 1 and 19 were observed with lower frequency. Serotypes 1, 2, 3, 12, and 31 were observed after analysing 7 samples which had been cultured in A549 cells as part of the infectivity detections. Nineteen samples were studied for determining NoV genotypes. Fifteen were confirmed as GII, with seven of them being GII.4. Four were GI, with one being GI.2. Over the last few years the most newly emerging NoV strains belong to GII.4 and show a global presence (Bull et al., 2006; Rowena et al., 2006).
Table 2 e Adenovirus infectivity over all sampling sites.
Marine (51 tested)
Fresh (226 tested)
T¼0
T¼5
Number of samples
% of those tested
e* e þ þ e e þ þ
e þ e þ e þ e þ
15 24 0 12 169 46 2 9
29 47 0 24 75 20 1 4
* Nested-PCR test result on cell culture after zero (T ¼ 0) or five (T ¼ 5) days’ incubation.
Frequencies of virus-positive samples were compared with the threshold values for E. coli and intestinal enterococci defining “good” water quality in the rBWD. The levels specified in the Directive for E. coli are 500/100 mL (coastal/transitional waters) and 1000/100 mL (inland waters), and the corresponding values for intestinal enterococci are 200/100 mL (coastal/transitional waters) and 400/100 mL (inland waters). Matching E. coli and intestinal enterococci data were available for 193 adenovirus-positive samples of which 117 (60.6%) had E. coli concentrations below the thresholds for “good” water quality whilst 151 (78.2%) had intestinal enterococci concentrations below the “good” water quality thresholds. For norovirus, matching E. coli and intestinal enterococci data were available for 52 positive samples, and the E. coli concentration in 31 (59.6%) of these was below the rBWD thresholds for “good” water quality. For intestinal enterococci, 38 (73.1%) norovirus-positive samples had concentrations below the “good” water quality thresholds. These results demonstrate the presence of PCR-detected virus in samples that would be considered “clean”, and of low illness risk, in terms of their faecal indicator organism concentration.
3.8.
Robustness of virus detection methods
The results of the robustness calculations of the virus/water detection methods are shown in Table 3. With the adenovirus/ freshwater method the trial sensitivity, or percentage of correctly identified positive samples, was 77.2%, and the concordance was lower than the accordance. A value of 1.0 lies just outside the COR 95% confidence intervals (CI), indicating that the method was not quite as reproducible as repeatable. The trial specificity, or percentage of correctly identified negative samples, was 96.1%, and 1.0 fell within the COR 95% CI, indicating that with identification of negative samples the method was as reproducible as it was repeatable. With the adenovirus/seawater method the trial sensitivity was 89.3%, and the concordance was lower than the accordance. Again, 1.0 lies just outside the COR 95% confidence intervals (CI). The trial specificity was 99.2%, and 1.0 fell within the COR 95% CI. With the norovirus/freshwater method the trial sensitivity was 91.4%, and the concordance was lower than the accordance, 1.0 lying just outside the COR 95% confidence intervals (CI). The trial specificity was 96.1%, and 1.0 fell within the COR 95% CI. With the norovirus/seawater method the trial sensitivity was 91.7%, and 1.0 fell within the COR 95% CI. The trial specificity was 92.6%, and 1.0 fell within the COR 95% CI.
4.
Discussion
This study has shown clearly that it is possible to use relatively straightforward methods for the detection of two important enteric viruses in water samples across a range of geographical sites with varying degrees of pollution. The common occurrence of adenoviruses (36.4% of samples tested) reflected the intermittent shedding of these viruses in the faeces by most adults. The difference in
1034
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
Table 3 e Statistical evaluation of methods for virus detection from recreational waters. Method A
Adenovirus/freshwater
B
Adenovirus/seawater
C
Norovirus/freshwater
D
Norovirus/seawater
Sample type
Sensitivity (%)
Specificity (%)
Positive Negative Positive Negative Positive Negative Positive Negative
77.2 N/A 89.3 N/A 91.4 N/A 91.7 N/A
N/A 96.1 N/A 99.2 N/A 96.1 N/A 92.6
(71.3e82.1)* (82.5e93.6) (87.1e94.3) (85.5e95.5)
(92.8e98.0) (95.5e99.9) (92.8e98) (86.5e96.0)
Accordance (%) 73.9 93.0 85.9 98.6 86.2 92.9 85.3 88.0
(61.2e86.5) (85.2e100) (68.9e94.9) (97.4e100) (74.4e96.1) (87e97.7) (75.6e94.9) (70.8e100)
Concordance (%) 63.5 (50.9e81.7) 92.5 (84.8e100) 79.6 (66.1e92.7) 98.3 (94.6e100) 83.9 (71.9e95.7) 92.5 (86.8e97.5) 84.6 (75.3e94.9) 85.7 (70.1e100)
COR 1.63 1.08 1.57 1.25 1.2 1.06 1.05 1.22
(1.07e2.52) (1.00e1.16) (1.01e2.29) (0.97e1.44) (1.02e1.35) (0.97e1.14) (0.81e1.38) (0.92e2.18)
*Numbers in parentheses indicate lower and upper 95% confidence intervals.
detection frequency may have been due to the greater dispersing and diluting power of the sea compared with that of the fresh waters. Alternatively, viruses may be less stable in marine waters due to the higher salt content, especially with higher temperatures (Hawley and Garver, 2008; Lo et al., 1976). The frequent detection of HAdVs by most laboratories reflected their known environmental robustness; though it was not possible to perform ICC-PCR on all the adenovirus-positive samples and thus show that all contained infectious viruses, it is known that adenoviruses can persist in an infectious state in various environments over long periods (Rzezutka and Cook, 2004). Charles et al. (2009) found a strong relation between PCR detection and infectivity of adenovirus Type 2 in groundwater over one year. Although noroviruses are spread principally by person-toperson transmission, environmental spread is also important, for instance in outbreaks associated involving drinking water (e.g. Hewitt et al., 2007) and consumption of bivalve molluscs (Lees, 2000). In this study, the high frequency of NoV GI detection in two Laboratories suggests a higher level in the environment than was demonstrated by consideration of the rest of the data for this virus. Detection of GI noroviruses in the environment is not matched by their detection in clinical samples; GI NoV strains have been detected frequently in sewage, effluent, and surface waters (da Silva et al., 2007; Katayama et al., 2008; Myrmel et al., 2006), which contributes to the view that many norovirus infections are symptomless, with GI viruses being under-represented among those found in clinical cases. It is unclear whether this relates to our data as most of the GI isolates were found in only four sites. The frequency of GII norovirus detection (approximately 6%) was as expected. It is commonly accepted that norovirusrelated disease shows a seasonal trend, with most outbreaks and sporadic cases occurring in winter. Whilst it would have been interesting to obtain a temporal distribution of environmental norovirus detection similar to that of Nordgren et al. (2009), this was not feasible in this study since it was specifically planned to be related to the EU bathing season, and in any case RT-PCR detection might not have provided resolution high enough to show temporal differences in norovirus levels. Further studies are planned using a norovirus QPCR to investigate this aspect. The performance characteristics of the methods used for concentration and detection of HAdV and NoV in both fresh and marine water samples were determined. Recovery values of 49% (seeded fresh water) and 37% (seeded artificial sea water) were considered acceptable, though variations
between laboratories prevented direct statistical comparisons of performance, and a modified method for marine water samples was developed during the project (Calgua et al., 2008). The percentage of correctly identified positive samples was around 90%, except for HAdV in freshwater, which showed a sensitivity of 77%, while the specificity of the methods was shown to be 93% or more. The sensitivity and specificity values compare well with those of some PCR-based methods for foodborne pathogen detection (Abdulmawjood et al., 2004; Malorny et al., 2004). The lower sensitivity value of the adenovirus/freshwater may be due to the fact that the HAdV concentration in the seeded sample was lower than the NoV concentration used. This may also explain the higher COR values for the HAdV-positive marine and freshwater samples. Furthermore, it should be noted that the samples used for the QC were not actually identical, whereas for the COR estimation this would be preferred. Each participant used the water from their own site(s), and this would differ from site to site and from week to week. River water, particularly, will contain varying levels of material that may reduce the effectiveness of the concentration method and/or inhibit the molecular assays. Notwithstanding this, the results demonstrate that the methods used are robust, although currently no criteria exist on lower limits of acceptability for robustness of methods for detection of viruses in water. The theoretical limit of detection of the method reported here can be estimated. If an (RT)PCR signal was obtained from an undiluted nucleic acid extract, and the assumption is made that the assay could detect one target molecule, this signifies that there was one virus equivalent in 10 mL nucleic acid extract. There were thus 10 virus equivalents in 100 mL nucleic acid extract, and on the assumption that this extract was obtained from 5 mL concentrate with no loss of target nucleic acid, this implies that there were 20 virus particles in the 10 mL concentrate. Assuming that the concentrate was derived from the original sample with no loss of virus, the conclusion is that a signal from the neat extract indicates that there were at least 20 virus particles in the 10-L water sample. If the extract had to be diluted to 101, then there were 200 virus particles in the 10-L sample. In selecting methods for concentration and detection of the target viruses practical and cost factors were considered in addition to recovery efficiency. Concentration by glass wool filtration is inexpensive requiring no specialised equipment beyond a centrifuge capable of 7000 g, and running costs are minimal. Membrane filtration is slightly more expensive, requiring a filtration stand, but again, running costs are low.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
Both approaches contrast with (for example) ultrafiltration (high costs of filtration units and pumps, or disposable cartridges) and ultracentrifugation, which is unlikely to be found in routine environmental virology laboratories. The time taken to process samples was also an important factor; using the selected methods it was possible to process up to eight samples in one day (including controls) following familiarisation with the method. For detection, cell culture was not considered for the surveillance stage, being too slow, expensive and requiring specialised facilities; the costs and labour time spent on molecular detection was as might be expected in any laboratory equipped for PCR and related techniques. The amount of sewage discharged in the vicinity of many of the sites studied will affect the likelihood of human viruses being present in the water. Sewage input was not measured directly but the level of faecal indicators found reflects the contamination level. Viruses were found less often in sites where the sewage input was expected to be lower. The influence of organic contaminants that occur naturally in water must not be underestimated. Reaction inhibition by substances in the sample is a well-known problem associated with analysis of environmental samples (e.g. da Silva et al., 2007), and was observed in this study. The use of the IACs in both NoV and HAdV PCRs was of significant benefit in guarding against false negative reactions. In the current study the norovirus RT-PCR suffered about 5.5% of reactions failing to give a conclusive result (4.4% of freshwater samples and 7.7% of marine samples). Samples were tested at a higher dilution (up to 103) to remove inhibition and achieve a positive IAC signal. Successive dilutions were done when a higher concentration failed to give a target signal or an IAC signal. Inhibition of the adenovirus PCR was much less problematic, with PCR reactions of 0.9% of freshwater samples and 5.6% of marine water samples being inhibited. Samples from one inland major river site (Kew Bridge, UK) had often to be diluted up to 103 and consequently unexpectedly low numbers of samples positive for adenovirus (23%) were recorded. Subsequent tests with bovine serum albumin (BSA) in the PCR reaction suggest that routine incorporation of this reagent in the reaction mix may reduce enzymatic inhibition. Integrated cell culture-PCR provided a method of determining the infectivity of adenoviruses, which was particularly useful since naturally-occurring virus strains do not always grow in cell culture with the same rapidity nor with the same evidence of cellular destruction. The enteric Ad40 and Ad41 viruses cannot be grown in most cell culture systems that support the growth of adenoviruses from the other subgroups, A549, HeLa, primary human amnion and primary human embryo kidney cells (Tiemessen and Kidd, 1995). They have been shown to replicate in cell culture systems using Graham 293 cells, HEp-2 cells and HT-29 cells (Ko et al., 2003; Tiemessen and Kidd, 1995). Our data support these findings, because the presence of both Ad40 and Ad41 was shown by direct PCR, not in the cell culture-PCR assay using A549 cells. Direct inoculation of cell cultures followed by observation over an extended period would not provide a good indication of infectivity and would not be in the interests of providing a rapid test. The finding that about 20% of freshwater samples and about 47% of marine water samples contained infectious
1035
adenovirus supports laboratory observations (e.g. ThurstonEnriquez et al., 2003) that these agents are environmentally robust. The FIO levels encountered in this project exhibited a wide range. Comparisons with FIO thresholds defined in the current European Directive bathing water standards (2006/7/ EC) suggest that over 50% of samples that are relatively clean in terms of FIO concentrations and which exhibit “good” water quality, with a low associated illness risk, can be positive for adenovirus and norovirus. However, use of an adenovirus PCR, for example, as a means of determining recreational water quality would require the use of quantitative, rather than presence/absence detection. Quantitative PCRs for different types of environmental adenovirus are now available. Whether such a test would detect infectious virus may be addressed by, for example, detection of virus-specific mRNA, and also there is some evidence that in adenovirus preparations from which free DNA has been removed before analysis virus titres measured by infectivity and by QPCR are very similar (Girone`s, personal communication). It would then be necessary to determine any association between adenovirus levels and health risk, and there is thus a need for further work before the viral parameters investigated here could be used in a regulatory framework prior to epidemiological investigation to provide an appropriate evidence-base for policy development.
5.
Conclusions
A comprehensive surveillance study of EU recreational waters was done through the 2006 bathing season. It may be concluded from the results that: 1. Almost 40% of bathing water samples in Europe were viruspositive entailing a possible public health risk from bathing; 2. Adenoviruses are more prevalent than noroviruses in both marine and fresh waters and appear to be a promising viral indicator for bathing water quality; 3. A single concentration method can be used to concentrate adenoviruses and noroviruses in fresh water recreational samples and a further single method can be used for marine waters; 4. Concentration and detection methods may be used effectively even in polluted waters; 5. Though the majority of sites returned frequencies of 0e25% positive, some were so polluted that >50% of samples contained one or both target viruses; 6. Adenoviruses remain infectious in the environment, and this may be true for other pathogenic viruses such as noroviruses.
6.
The ‘Virobathe’ group
This work was performed by scientists and technicians from 16 Institutions across Europe. In addition to the Authors of this paper, those making significant contributions were as follows:
1036
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
Dr. Silvia Bofill-Mash, Ms. Pilar Clementeh, Dr. Donia Domenicad, Ms. Alexandra Duarten, Dr. Inge Gra¨berl, Dr. Wafa Hollisterp, Ms. Stephanie Huberi, Dr. Marcello Iaconellim, Dr. Giuseppina La Rosam, Prof. Beata Cuvelierk, Ms. Leslie Orgorzalyf, Dr. Nicholas Pissarides, Dr. Gabrieli Rosannad, Ms. Elyne Salagnonc, Dr. Oliver Schneidere, Ms. Arieke Docters van Leeuwenj, Dr. Marco Veranib, and Mr. Steve Wildeg.
Acknowledgements This work was funded by an EU contract number 513648 VIROBATHE, as part of the Sixth Framework Programme. The authors are grateful to Dr. Jan Vinje´ for helpful comments on the manuscript.
references
Abdulmawjood, A., Bu¨lte, M., Roth, S., Scho¨nenbru¨cher, H., Cook, N., Heuvelink, A.E., Hoorfar, J., 2004. Development, validation, and standardization of polymerase chain reactionbased detection of E. coli O157. Journal of AOAC International 87 (3), 596e603. Allard, A., Albinsson, B., Wadell, G., 2001. Rapid typing of human adenoviruses by a general PCR combined with restriction endonuclease analysis. Journal of Clinical Microbiology 39, 498e505. Bucardo, F., Karlsson, B., Nordgren, J., Paniagua, M., Gonza´lez, A., Amador, J.J., Espinoza, F., Svensson, L., 2007. Mutated G4P[8] rotavirus associated with a nationwide outbreak of gastroenteritis in Nicaragua in 2005. Journal of Clinical Microbiology 45 (3), 990e997. Bull, R.A., Tu, E.T., McIver, C.J., Rawlinson, W.D., White, P.A., 2006. Emergence of a new norovirus genotype II.4 variant associated with global outbreaks of gastroenteritis. Journal of Clinical Microbiology 44 (2), 327e333. Calgua, B., Mengewein, A., Grunert, A., Bofill-Mas, S., ClementeCasares, P., Hundesa, A., Wyn-Jones, A.P., Lo´pez-Pila, J.M., Girones, R., 2008. Development and application of a one-step low cost procedure to concentrate viruses from seawater samples. Journal of Virological Methods 153, 79e83. CEU, 2006. Directive 2006/7/EC of the European Parliament and of the Council of 15 February 2006 concerning the management of bathing water quality and repealing Directive 76/160/EEC. Charles, K.J., Shore, J., Sellwood, J., Laverick, M., Hart, A., Pedley, S., 2009. Assessment of the stability of human viruses and coliphage in groundwater by PCR and infectivity methods. Journal of Applied Microbiology 106, 1827e1837. Contreras-Coll, N., Lucena, F., Mooijman, K., Havelaar, A., Pierz, V. , Boque, M., Gawler, A., Ho¨ller, C., Lambiri, M., Mirolo, G., Moreno, B., Niemi, M., Sommer, R., Valentin, B., Wiedenmann, A., Young, V., Jofre, J., 2002. Occurrence and levels of indicator bacteriophages in bathing waters throughout Europe. Water Research 36 (20), 4963e4974. da Silva, A.K., le Saux, J.-C., Parnaudeau, S., Pommepuy, M., Elimelech, M., le Guyader, F.S., 2007. Evaluation of removal of noroviruses during wastewater treatment using real-time reverse transcription-PCR: different behaviors of genogroups I and II. Applied and Environmental Microbiology 73 (24), 7891e7897. Davison, A.C., Hinckley, D.V., 1997. Bootstrap Methods and Their Application. Cambridge University Press, Cambridge, UK.
de Roda Husman, A.M., Lodder, W.J., Rutjes, S.A., Schijven, J.F., Teunis, P.F., 2009. Long-term inactivation study of three enteroviruses in artificial surface and groundwaters using PCR and cell culture. Applied and Environmental Microbiology 75 (4), 1050e1057. Ding, Y., He, L., Zhang, Q., Huang, Z., Che, X., Hou, J., Wang, H., Shen, H., Qiu, L., Li, Z., Geng, J., Cai, J., Han, H., Li, X., Kang, W., Weng, D., Liang, P., Jiang, S., 2004. Organ distribution of severe acute respiratory syndrome (SARS) associated coronavirus (SARS-CoV) in SARS patients: implications for pathogenesis and virus transmission pathways. Journal of Pathology 203 (2), 622e630. Dubrou, S., Kopecka, H., Lopez-Pila, J.M., Marechal, J., Prevot, J., 1991. Detection of hepatitis A virus and other enteroviruses in wastewater and surface water samples by gene probe assay. Water Science and Technology 24 (2), 267e272. Enriquez, C.E., Hurst, C.J., Gerba, C.P., 1995. Survival of the enteric adenoviruses 40 and 41 in tap, sea and wastewater. Water Research 29, 2548e2553. Farrah, S.R., Bitton, G., 1990. In: Jean-Marc, Bollag, Stotzky, Arthur Douglas, Peterson, G., George, H. (Eds.), Soil Biochemistry, vol. 6. CRC Press, ISBN 0824782321. Gerba, C.P., Goyal, S.M., LaBelle, R.L., Cech, I., Bodgan, G.F., 1979. Failure of indicator bacteria to reflect the occurrence of enteroviruses in marine waters. American Journal of Public Health 69, 1116e1119. Gray, J.J., Green, J., Gallimore, C., Lee, J.V., Neal, K., Brown, D.W.G., 1997. Mixed genotype SRSV infections among a party of canoeists exposed to contaminated recreational water. Journal of Medical Virology 52, 425e429. Greening, G.E., Hewitt, J., Lewis, G.D., 2002. Evaluation of integrated cell culture-PCR (ICC-PCR) for virological analysis of environmental samples. Journal of Applied Microbiology 93 (5), 745e750. Harley, D., Harrower, B., Lyon, M., Dick, A., 2001. A primary school outbreak of pharyngoconjunctival fever caused by adenovirus type 3. Communicable Diseases Intelligence 25 (1), 9e12. Hauri, A.M., Schimmelpfennig, M., Walter-Domes, M., Letz, A., Diedrich, S., Lopez-Pila, J., Schreier, E., 2005. An outbreak of viral meningitis associated with a public swimming pond. Epidemiology and Infection 133 (2), 291e298. Hawley, L.M., Garver, K.A., 2008. Stability of viral hemorrhagic septicemia virus (VHSV) in freshwater and seawater at various temperatures. Diseases of Aquatic Organisms 82, 171e178. Hernroth, B.E., Conden-Hansson, A.C., Rehnstam-Holm, A.S., Girones, R., Allard, A.K., 2002. Environmental factors influencing human viral pathogens and their potential indicator organisms in the blue mussel, Mytilus edulis: the first Scandinavian report. Applied and Environmental Microbiology 68 (9), 4523e4533. Hewitt, J., Bell, D., Simmons, G.C., Rivera-Aban, M., Wolf, S., Greening, G., 2007. Gastroenteritis outbreak caused by waterborne norovirus at a New Zealand ski resort. Applied and Environmental Microbiology 73, 7853e7857. Hoebe, C.J.P.A., Vennema, H., de Roda Husman, A.M., van Duynhoven, Y.T.H.P., 2004. Norovirus outbreak among primary schoolchildren who had played in a recreational water fountain. Journal of Infectious Diseases 189, 699e705. Hundesa, A., Maluquer de Motes, C., Bofill-Mas, S., AlbinanaGimenez, N., Girones, R., 2006. Identification of human and animal adenoviruses and polyomaviruses for determination of sources of fecal contamination in the environment. Applied and Environmental Microbiology 72, 7886e7893. Iijima, Y., Tanaka, S., Ohishi, H., 2008. Multiple outbreaks of gastroenteritis due to a single strain of genotype GII/4 norovirus in Kobe, Japan: risk factors for norovirus spread in health care settings. Japanese Journal of Infectious Diseases 61 (5), 419e422.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
Katayama, H., Haramoto, E., Oguma, K., Yamashita, H., Tajima, A. , Nakajima, H., Ohgaki, S., 2008. One-year monthly quantitative survey of noroviruses, enteroviruses, and adenoviruses in wastewater collected from six plants in Japan. Water Research 42, 1441e1448. Kay, D., Fleisher, J.M., Salmon, R.L., Jones, F., Wyer, M.D., Godfree, A.F., Zelenauch-Jacquotte, Z., Shore, R., 1994. Predicting the likelihood of gastroenteritis from sea bathing e results from randomized exposure. The Lancet 344 (8927), 905e909. Kay, D., Bartram, J., Pru¨ss, A., Ashbolt, N., Wyer, M.D., Fleisher, J. M., Fewtrell, L., Rogers, A., Rees, G., 2004. Derivation of numerical values for the World Health Organization guidelines for recreational waters. Water Research 38 (5), 1296e1304. Ko, G., Cromeans, T.L., Sobsey, M.D., 2003. Detection of infectious adenovirus in cell culture by mRNA reverse transcriptase-PCR. Applied and Environmental Microbiology 69, 7377e7384. Koopmans, M., von Bonsdorff, C.H., Vinje´, J., de Medici, D., Monroe, S., 2002. Foodborne viruses. FEMS Microbiology Reviews 26 (2), 187e205. Langton, S.D., Chevennement, R., Nagelkerke, N., Lombard, B., 2002. Analysing collaborative trials for qualitative microbiological methods: accordance and concordance. International Journal of Food Microbiology 79 (3), 175e181. Laverick, M.A., Wyn-Jones, A.P., Carter, M.J., 2004. Quantitative RT-PCR for the enumeration of noroviruses (Norwalk-like viruses) in water and sewage. Letters in Applied Microbiology 39, 127e136. Lee, C., Lee, S.H., Han, E., Kim, S.J., 2004. Use of cell culture-PCR assay based on combination of A549 and BGMK cell lines and molecular identification as a tool to monitor infectious adenoviruses and enteroviruses in river water. Applied and Environmental Microbiology 70, 6695e6705. Lees, D., 2000. Viruses and bivalve shellfish. International Journal of Food Microbiology 59 (1e2), 81e116. Lipp, E.K., Farrah, S.A., Rose, J.B., 2001. Assessment and impact of microbial fecal pollution and human enteric pathogens in a coastal community. Marine Pollution Bulletin 42, 286e329. Lo, S., Gilbert, J., Hetrick, F., 1976. Stability of human enteroviruses in estuarine and marine waters. Applied and Environmental Microbiology 32, 245e249. Malorny, B., Bunge, C., Hoorfar, J., Helmuth, R., 2003. Multicenter validation of the analytical accuracy of Salmonella PCR: towards an international standard. Applied and Environmental Microbiology 69, 290e296. Malorny, B., Cook, N., D’Agostino, M., de Medici, D., Croci, L., Abdulmawjood, A., Fach, P., Karpiskova, R., Aymerich, T., Kwaitek, K., Kuchta, T., Hoorfar, J., 2004. Multicenter collaborative trial validation of a PCR-based method for detection of Salmonella in chicken and pig samples. Journal of AOAC International 87, 861e866. Maunula, L., Kalso, S., von Bonsdorff, C.-H., Po¨nka¨, A., 2004. Wading pool water contaminated with both noroviruses and astroviruses as the source of a gastroenteritis outbreak. Epidemiology and Infection 132 (4), 737e743. Medema, G.J., van Asperen, I.A., Kokman-Houweling, J.M., Nooitgedagt, A., van de Laar, M.J.W., Havelaar, A.H., 1995. The relationship between health effects in triathletes and microbiological quality of freshwater. Water Science and Technology 31 (5e6), 19e26. Miagostovich, M.P., Ferreira, F.F., Guimara˜es, F.R., Fumian, T.M., Diniz-Mendes, L., Luz, S.L., Silva, L.A., Leite, J.P., 2008. Molecular detection and characterization of gastroenteritis viruses occurring naturally in the stream waters of Manaus, Central Amazonia, Brazil. Applied and Environmental Microbiology 74 (2), 375e382.
1037
Myrmel, M., Berg, E.M.M., Grinde, B., Rimstad, E., 2006. Enteric viruses in inlet and outlet samples from sewage treatment plants. Journal of Water and Health 4, 197e209. Nordgren, J., Matussek, A., Mattsson, A., Svensson, L., Lindgren, P.-E., 2009. Prevalence of norovirus and factors influencing virus concentrations during one year in a fullscale wastewater treatment plant. Water Research 43, 1117e1125. Nwachuku, N., Gerba, C.P., 2006. Health risks of enteric viral infections in children. Reviews of Environmental Contamination and Toxicology 186, 1e56. Papapetropolou, M., Vantarakis, A.C., 1995. Detection of adenovirus outbreak at a municipal swimming pool by nested PCR amplification. Journal of Infection 36, 101e103. Pina, S., Puig, M., Lucena, F., Jofre, J., Girones, R., 1998. Viral pollution in the environment and in shellfish: human adenovirus detection by PCR as an index of human viruses. Applied and Environmental Microbiology 64, 3376e3382. Reynolds, K.A., Gerba, C.P., Abbaszadegan, M., Pepper, I.L., 2001. ICC-PCR detection of enteroviruses and hepatitis A virus in environmental samples. Canadian Journal of Microbiology 47, 153e157. Rowena, A., Bull, Elise, Tu, T.V., McIver, Christopher J., Rawlinson, William D., White, Peter A., 2006. Emergence of a new norovirus genotype II.4 variant associated with global outbreaks of gastroenteritis. Journal of Clinical Microbiology 44 (2), 327e333. Rzezutka, A., Cook, N., 2004. Survival of human enteric viruses in the environment and food. FEMS Microbiology Reviews 28, 441e453. Sarguna, P., Rao, A., Sudha Ramana, K.N., 2007. Outbreak of acute viral hepatitis due to hepatitis E virus in Hyderabad. Indian Journal of Medical Microbiology 25 (4), 378e382. Scotter, S.L., Langton, S., Lombard, B., Lahellec, C., Schulten, S., Nagelkerke, N., in’t Veld, P.H., Rollier, P., 2001. Validation of ISO method 11290 part 2. Enumeration of Listeria monocytogenes in foods. International Journal of Food Microbiology 70 (1e2), 121e129. Sinclair, R.G., Jones, E.L., Gerba, C.P., 2009. Viruses in recreational water-borne disease outbreaks: a review. Journal of Applied Microbiology 107 (6), 1769e1780. Thurston-Enriquez, J.A., Haas, C.N., Jacangelo, J., Gerba, C.P., 2003. Inactivation of feline calicivirus and adenovirus type 40 by UV radiation. Applied and Environmental Microbiology 69, 577e582. Tiemessen, C.T., Kidd, A.H., 1995. The subgroup F adenoviruses. Journal of General Virology 76, 481e497. Vasl, R., Fattal, B., Katzenelson, E., Shuval, H., 1981. Survival of enteroviruses and bacterial indicator organisms in the sea. In: Goddard, M., Butler, M. (Eds.), Viruses and Wastewater Treatment. Pergamon Press, pp. 113e116. Vennema, H., de Bruin, E., Koopmans, M., 2002. Rational optimization of generic primers used for Norwalk-like virus detection by reverse transcriptase polymerase chain reaction. Journal of Clinical Virology 25 (2), 233e235. Verhoef, L.P., Kroneman, A., van Duynhoven, Y., Boshuizen, H., van Pelt, W., Koopmans, M., 2009. Foodborne viruses in Europe network. Selection tool for foodborne norovirus outbreaks. Emerging Infectious Diseases 15 (1), 31e38. Vilagine`s, P., Sarrette, B., Husson, G., Vilagine`s, R., 1993. Glass wool for virus concentration at ambient water pH level. Water Science and Technology 27, 299e306. WHO, 2003. Guidelines for Safe Recreational Water Environments Volume 1: Coastal and Freshwaters. World Health Organisation, Geneva, p. 219. Wiedenmann, A., Kru¨ger, P., Dietz, K., Lo´pez-Pila, J., Szewzyk, R., Botzenhart, K., 2006. A randomized controlled trial assessing
1038
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 2 5 e1 0 3 8
infectious disease risks from bathing in fresh recreational waters in relation to the concentration of Escherichia coli, intestinal enterococci, Clostridium perfringens and somatic coliphages. Environmental Health Perspectives 8115, 1e41. Wyn-Jones, A.P., Sellwood, J., 2001. Enteric viruses in the aquatic environment. Journal of Applied Microbiology 91, 945e962. Wyn-Jones, A.P., Pallin, R., Dedoussis, C., Shore, J., Sellwood, J., 2000. The detection of small round-structured viruses in water
and environmental materials. Journal of Virological Methods 87, 99e107. Zhang, Y., Tan, X.J., Wang, H.Y., Yan, D.M., Zhu, S.L., Wang, D.Y., Ji, F., Wang, X.J., Gao, Y.J., Chen, L., An, H.Q., Li, D.X., Wang, S. W., Xu, A.Q., Wang, Z.J., Xu, W.B., 2009. An outbreak of hand, foot, and mouth disease associated with subgenotype C4 of human enterovirus 71 in Shandong, China. Journal of Clinical Virology 44 (4), 262e267.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 3 9 e1 0 4 8
Available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Effect of selected metal ions on the photocatalytic degradation of bog lake water natural organic matter Luis A. Tercero Espinoza*, Eike ter Haseborg, Matthias Weber, Elly Karle, Rafael Peschke, Fritz H. Frimmel Water Chemistry, Engler-Bunte-Institut, Karlsruhe Institute of Technology, Engler-Bunte-Ring 1, 76131 Karlsruhe, Germany
article info
abstract
Article history:
Herein we report the photocatalytic degradation of natural organic matter from a bog lake
Received 11 April 2010
(Lake Hohloh, Black Forest, Germany) in the presence of 0, 5, and 10 mmol L1 of added Cu2þ,
Received in revised form
Mn2þ, Zn2þ and Fe3þ. The reactions were followed by size exclusion chromatography with
14 September 2010
organic carbon detection (SEC-DOC) and by measurements of low molecular weight organic
Accepted 13 October 2010
acids. Addition of Cu2þ had the largest effect of all four studied metals, leading to a retarda-
Available online 21 October 2010
tion in the molecular size changes in NOM: degradation of the larger molecular weight fraction was inhibited leading to reduced production of smaller molecular weight metabo-
Keywords:
lites. Similarly, addition of Cu2þ reduced the production of formic and oxalic acids, and
Heterogeneous photocatalysis
reduced the bioavailability of the partially degraded NOM.
Natural organic matter
ª 2010 Elsevier Ltd. All rights reserved.
Size exclusion chromatography Low molecular weight organic acids Degradation
1.
Introduction
Natural organic matter (NOM) is present in varying concentrations in all raw waters used for the production of drinking water. Its concentration is often reduced through flocculation and filtration prior to oxidation and disinfection. In spite of this, NOM is the principal natural precursor for unwanted byproducts in disinfection during water treatment (Frimmel et al., 2002; Zwiener, 2006). Thus, it is necessary to understand the behavior of NOM in established and alternative processes, especially those inducing chemical changes in the NOM. One alternative oxidation process with deployment potential in small, decentralized water treatment units is heterogeneous photocatalysis with titanium dioxide as the photocatalyst. This process is one of the so-called advanced oxidation processes
(AOP), the effectiveness of which is based largely on the oxidation potential of OH radicals (2.8 V vs. standard hydrogen electrode) and has been extensively demonstrated (Hoffmann et al., 1995; Kabra et al., 2004). The TiO2/UV process is particularly attractive for use in regions where the UV photons can be provided by sunlight. An overview of the work on solar heterogeneous photocatalysis is given by Malato et al. (2007). NOM is known to bleach and undergo changes in adsorption properties under photocatalysis with TiO2 suspensions (Bekbo¨let et al., 1996; Eggins et al., 1997) e for a recent review please see Matilainen and Sillanpa¨a¨ (2010). It was recently shown that aquatic NOM from a bog lake is progressively degraded in this process starting with the higher molecular weight fraction (Tercero Espinoza et al., 2009). Iterative calculations based on that experimental data show a cascade
* Corresponding author. Present address: Fraunhofer Institute for Systems and Innovation Research, Breslauer Str. 48, 76139 Karlsruhe, Germany. E-mail addresses:
[email protected] (L.A. Tercero Espinoza),
[email protected] (F.H. Frimmel). 0043-1354/$ e see front matter ª 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2010.10.013
1040
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 3 9 e1 0 4 8
in which NOM is progressively degraded and that this progression is different in homogeneous and heterogenous AOP (Tercero Espinoza and Frimmel, 2009). The work presented herein is a continuation of our efforts to characterize the photocatalytic degradation of NOM under simulated solar ultraviolet (UV) irradiation. Here we examine the effect of the presence of selected metal ions commonly found in natural waters, namely iron(III), manganese(II), copper(II) and zinc(II) on the photocatalytic degradation of NOM, taking into account changes in molecular size as measured by size exclusion chromatography with dissolved organic carbon detection (SEC-DOC), as well as the production of low molecular weight organic acids (LMWOA) and changes in the bioavailability of the DOC upon irradiation.
2.
Materials and methods
2.1.
Experiments without added metals
20 mg P25 (Degussa, Germany) was added to 40 mL of Lake Hohloh water (r(DOC) ¼ 21 mg L1) previously filtered with 0.45 mm cellulose acetate membrane filters and mixed. P25 is comprised of TiO2 (approx. 75% anatase and 25% rutile) nanoparticles with average particle diameter around 20e30 nm and a BET surface area of 50 15 m2 g1 (Doll and Frimmel, 2005, and manufacturer’s specifications). Lake Hohloh water was extensively described by Frimmel et al. (2002). Samples were sonicated for 10 min prior to irradiation. The samples were then placed in a solar UV simulator (Oriel Corp., Stratford, CT), where they were stirred, open to the atmosphere, and irradiated from above by a homogeneous light field. The estimated photon flow in the UV range (290 < l < 400 nm) was 1.4 107 mol s1 (polychromatic actinometry following Defoin et al., 1986). The sample volume was 40 mL in all experiments, with an irradiation pathlength of z3.5 cm.
2.2.
Experiments with added metals
Lake Hohloh water was mixed with an appropriate amount of CuSO4 or CuCl2$2H2O, FeCl3, ZnCl2, and MnCl2 solutions and let stand for a minimum of 3 days in the dark. This spiked water was used instead of the original lake Hohloh water in the procedure described in Section 2.1. In order to systematically explore the experimental region, we turned to a full factorial design for 4 variables in 2 levels (24 experimental runs), which comprise all possible combinations of the þ1 and
Table 1 e Variable settings for the 24 full factorial design. Variable
cadded(Cu2þ) cadded(Fe2þ) cadded(Zn2þ) cadded(Mn2þ)
Coded var.
x1 x2 x3 x4
Variable setting 1 (mmol L1)
0 (mmol L1)
þ1 (mmol L1)
0 0 0 0
5 5 5 5
10 10 10 10
Table 2 e Experimental matrix for the irradiation experiments with added metals. Each row represents one experimental run. The experimental runs were performed in random order. Runs with tirrad [ 30 min and those with tirrad [ 60 min were performed separately. cadded(Cu2þ) (mmol L1) 0 10 0 10 0 10 0 10 0 10 0 10 0 10 0 10 5 5 5
cadded(Fe3þ) (mmol L1)
cadded(Zn2þ) (mmol L1)
cadded(Mn2þ) (mmol L1)
0 0 10 10 0 0 10 10 0 0 10 10 0 0 10 10 5 5 5
0 0 0 0 10 10 10 10 0 0 0 0 10 10 10 10 5 5 5
0 0 0 0 0 0 0 0 10 10 10 10 10 10 10 10 5 5 5
1 levels shown in Table 1, plus repetitions of the “center point” (level “0” for all variables, see Box et al., 2005). The full experimental matrix is shown in Table 2.
2.3. Size exclusion chromatography with dissolved organic carbon detection (SEC-DOC) Filtered (0.45 mm) samples were analyzed using the apparatus described in detail by Huber and Frimmel (1991) using Toyopearl HW 50S resin (Tosoh Corp., Japan) as column packing and phosphate eluent (1.5 g L1 Na2HPO4$2H2O þ 2.5 g L1 KH2PO4) flowing at a rate of 1 mL min1 as the mobile phase. Samples were diluted 1:5 prior to analysis. The dimensions of the column were: length ¼ 250 mm, inner diameter ¼ 20 mm. The injection volume was 1 mL and the DOC concentration of each sample was calculated on the basis of an external calibration using potassium hydrogen phthalate as a standard. The resulting chromatograms were divided operationally into three fractions (cf. Tercero Espinoza et al., 2009), as follows: Fraction 1: 28.0 min < tr < 45.8 min, where tr is the retention time (in this case numerically equal to the elution volume in mL); the DOC contained in this fraction is commonly attributed to the relatively high molecular sized humic material (Huber et al., 1994), Fraction 2: 45.8 min < tr < 50.7 min; the DOC contained in this fraction is sometimes referred to as “building blocks”, representing medium sized molecules (Frimmel, 1998; Huber et al., 1994). Fraction 3: 50.7 min < tr < 56.5 min; this peak includes totally permeating molecules, as well as molecules which elute prematurely due to the difference in electrical conductivity between sample and buffer (Specht and Frimmel, 2000; Huber et al., 1994).
1041
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 3 9 e1 0 4 8
2.4.
Ion chromatography (IC)
KD
Measurements of total metal concentrations were performed by means of inductively coupled plasma-optical emission spectroscopy (ICP-OES) using a Vista-Pro CCD simultaneous ICP-OES spectrometer (Varian) with yttrium as an internal standard.
2.6. Degradation experiments with bacteria from activated sludge The biodegradability of the irradiated samples was assessed by performing SEC-DOC measurements of filtered samples after incubation with a mixed bacterial culture following Tercero Espinoza et al. (2009). Briefly, 4 mL of activated sludge inoculum (mixed from two wastewater treatment plants, one municipal and one industrial) were added to 50 mL of the irradiated samples, which were previously filtered to remove the TiO2 particles. The samples were then incubated in the dark on a shaker (70 rpm) for 48 h at 36 . The choice of bacterial cultures reflects the expectation that the mixed inoculum from two wastewater treatment plants possesses a larger bacterial diversity and a correspondingly larger metabolic potential compared e.g. to the “native” inoculum used by Brinkmann et al. (2003).
3.
Results and discussion
3.1.
Degradation of NOM in the absence of added metals
As a base case for later experiments with added Cu2þ, Mn2þ, Zn2þ and Fe3þ, we first performed irradiation experiments in the absence of added metals (Fig. 1). A further aim was to select an adequate time scale for the ensuing experiments with added metals. To this end, the SEC-DOC chromatograms of the original and irradiated samples were divided into three fractions based on retention time (tr) as described in Section 2.3. The fractions are presented graphically in Fig. 1, and are also referred to as F1eF3 in the following presentation and discussion. In good agreement with previous results (Tercero Espinoza et al., 2009), irradiation of the samples led to a rapid decrease in F1 (0.05 mg L1 min1), initially accompanied by an increase in F2 and F3, each at a rate approximately half that of decrease of F1. Therefore, the sum of the DOC contained in F1eF3 did not change appreciably during the first hour of irradiation but decreased steadily at longer irradiation time (tirrad), indicating mineralization of the NOM.
1.0
1.3
1.7
2. 0
0 min 60 min 120 min
1. 0
Relative DOC signal
2.5. Inductively coupled plasma-optical emission spectroscopy (ICP-OES)
0.7
Irrad. time
F1
0. 0
The determination of low molecular weight organic acids on filtered samples (0.45 mm) was performed by ion exchange chromatography (IC) using a Dionex DX500 system, equipped with an IonPacAS11 column (length 250 mm, inner diameter 4 mm) as described earlier (Tercero Espinoza et al., 2009). The eluent was aqueous KOH with concentrations shown in Table S1 in the supporting information.
0.3
3.0
0.0
20
30
40
F2 F3
50
60
70
80
t r / min
Fig. 1 e SEC-DOC chromatograms showing the defined fractions (F1eF3) and their time evolution under UV irradiation in the presence of 0.5 g LL1 TiO2. The DOC signal is directly proportional to the mass of organically bound carbon leaving the SEC column at retention time tr. Notice the marked shift in the chromatograms from left to right with increasing irradiation time, pointing to the progressive degradation of the NOM (for a more detailed discussion, see e.g. Tercero Espinoza et al., 2009; Tercero Espinoza and Frimmel, 2009).
Because F2 experienced a maximum in DOC content at tirrad z 60e90 min, we chose irradiation times of 30 and 60 min for the following experiments with added metals. See the supporting information for a plot of DOC content vs. tirrad for F1eF3 (Figure S1). Through this choice of tirrad (i.e. in the early stages of the reaction, before the maximum in F2) we aimed to avoid having to distinguish between values on either side of the UV (Figure S2) and DOC maxima for F2.
3.2. Degradation of NOM in the presence of added metals In order to study the influence of added metals on the photocatalytic degradation of NOM, we performed irradiation experiments with added iron(III), copper(II), manganese(II) and zinc(II) in the range 0e10 mmol L1. The original Lake Hohloh water contained 1 mmol L1 of each Cu and Mn, approx. 2 mmol L1 Zn, and approx. 6 mmol L1 Fe, as measured by ICP-OES. No steps were taken to change this natural background concentration. Thus, the concentration of the spiked samples is given as cadded(metal ion) instead of total concentration. As expected from the irradiation experiments without added metals (Section 3.1; cf. Tercero Espinoza et al., 2009), the DOC content of F1 decreased upon irradiation, and that of F2 and F3 increased with increasing tirrad. While more than half of the DOC initially contained in F1eF3 was present as F1, this fraction was reduced to approximately half after tirrad ¼ 30 min and less than half after tirrad ¼ 60 min. The sum of F1eF3 remained nearly constant. The results for all experiments containing added metals are summarily presented in Fig. 2. For comparison, the values
1042
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 3 9 e1 0 4 8
corresponding to the experimental runs without added metals are given at the bottom of the histograms (gray and black stubs). After tirrad ¼ 30 min, the DOC content of the sample without added metals (gray stub in Fig. 2, left panel) was close to the mean of all samples for F1 and F3. However, for F2, the DOC content of this sample was at the high end of the distribution, suggesting that the addition of metals led to a smaller F2. After tirrad ¼ 60 min, the value of the DOC content of the sample without metals (black stub in Fig. 2, left panel) was at the lower end of the distribution for F1, pointing to a retardation of the degradation of F1 in the presence of added metals. Congruently, this sample showed larger F2 and F3 (both close to the upper end of their respective distributions). Thus, addition of the selected metal ions appears to generally slow down the transformations of NOM in the direction F1 / F2 / F3 as observed after tirrad ¼ 60 min. This inhibitive effect may be related either to the presence of metal ions as scavengers of both electrons and OH radicals (Litter, 1999), or to the complexation of metal ions with NOM. These aspects are discussed in the following sections. It is interesting to note that not only the mean but also the shape of the histograms changes as the irradiation progresses, with peaks for the individual fractions apparently acquiring a more pronounced bimodal character after 60 min of irradiation than after 30 min, as seen in Fig. 2. For example, the mode of the DOC content of F1 after tirrad ¼ 30 min is between 5 and 5.5 mg L1. However, there are two modes visible after tirrad ¼ 60 min: one around 3.5e4.0 mg L1 and one around 4.5e5.0 mg L1. This suggests that the DOC content of these fractions, originally the same regardless of the added metals, splits into two distinct “groups” during the course of irradiation. These groups may in turn result from the action of one or more of the added metals. This aspect is explored below.
3.3.
DOC content of the individual fractions
In order to help quantify the effect of the added metals on the “internal” changes in the apparent molecular size distribution of the NOM samples, we fitted the polynomial model
y ¼ b0 þ b1 x1 þ b2 x2 þ b3 x3 þ b4 x4 |{z} |fflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl{zfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl} mean
main effects
þ b12 x1 x2 þ b13 x1 x3 þ . þ b34 x3 x4 |fflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl{zfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl} firstorder or twoway interaction effects
þ
b123 x1 x2 x3 þ . þ b234 x2 x3 x4 |fflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl{zfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl} secondorder or threeway interaction effects
þ
b1234 x1 x2 x3 x4 |fflfflfflfflfflfflfflfflfflffl{zfflfflfflfflfflfflfflfflfflffl} thirdorder or fourway interaction effect
to the data, where the subscripts 1e4 are defined in Table 1. We then analyzed the magnitude of the coefficients by using the techniques from Daniel (1959) and Lenth (1989) to identify the most important factors influencing the DOC content of each fraction.
3.3.1.
Fraction 1 (F1)
There was no clear effect of the added metals on the DOC content of F1 at tirrad ¼ 30 min (cf. Fig. 2, left panel). However, evaluation of the data after tirrad ¼ 60 min shows an effect of added Cu2þ. Plotting the results only as a function of cadded(Cu2þ) reveals that an increasing concentration of Cu2þ results in a larger DOC content of F1, indicating a retardation in the degradation of this fraction as compared to samples without added Cu2þ. For cadded(Cu2þ) ¼ 0 mmol L1, the DOC contained in F1 was 3.8 0.2 mg L1, while for cadded(Cu2þ) ¼ 10 mmol L1 it was 4.7 0.5 mg L1. These data are shown as box plots in Fig. 3, left panel. Note that the results in Fig. 3 are presented as if the other metals were not present. Therefore, the variability observed for cadded(Cu2þ) ¼ 0 and 10 mmol L1 also includes the variations caused by the presence/absence of the other three added metals. In spite of this, the difference observed for F1 in Fig. 3 between cadded(Cu2þ) ¼ 0 and at cadded(Cu2þ) ¼ 10 mmol L1 is statistically significant when considering a 99% confidence interval (CI) for the difference of means. The data at cadded(Cu2þ) ¼ 5 mmol L1 (center point) show the variability of true replicates of the same experiment (n ¼ 3). The experimental error associated with true replicate runs of a single experiment was, therefore, small when compared with the variability observed with cadded(Cu2þ) ¼ 0 and 10 mmol L1, indicating that
Irrad. time
30 min 60 min
F1
F2
F3
F1 + F2 + F3
2 2.5 3 3.5 4
1.5 2 2.5 3 3.5
10 Frequency
8 6 4 2 0 3
4
5
6
7
8
9
10 11 12
−1
DOC contained in fraction(s) / mg L
Fig. 2 e Frequency distribution of the DOC content of F1eF3 as a function of time (each data point corresponds to one experiment in Table 2). The gray and black stubs at the bottom of the histograms indicate the values corresponding to samples without added metals after 30 and 60 min of irradiation, respectively. Note the different bin sizes: 0.5 mg LL1 for F1 and F1 D F2 D F3 but 0.25 mg LL1 for F2 and F3.
1043
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 3 9 e1 0 4 8
F2
F3
5
4
3
2 0
5
10
0
5
c added(Cu
)
2+
10
0
5
10
−1
/ μmol L
Fig. 3 e Box plots showing the DOC content of F1, F2 and F3 after 60 min of irradiation. The box at cadded(Cu2D) [ 5 mmol LL1 (x1 [ 0) results from the repetitions at the center point (true replicate runs, n [ 3). Box plots (sometimes called box and whisker plots) summarily present all data in a distribution. The lower end of the bottom whisker in a box plot corresponds to the minimum of all observations while the top of the upper whisker represents the maximum. The bottom of the box represents the 25th percentile (1st quartile), the central line the median (50th percentile or 2nd quartile), and the top of the box the 75th percentile (3rd quartile) of the distribution (Lapin, 1997).
the influence of the other added metals on the degradation of F1, though small compared to that of Cu2þ, may not be negligible. The largest of these other influences was that of added Mn2þ. The change in DOC content with added Cu2þ was different in the absence and in the presence of added Mn2þ: rðDOCF1 Þx1 ¼þ1 rðDOCF1 Þx1 ¼1 ¼ 1:2 0:3 mg L1 for cadded (Mn2þ) ¼ 0 mmol L1 but only 0.6 0.4 mg L1 for cadded(Mn2þ) ¼ 10 mmol L1. Thus, the magnitude of the observed effect of added Cu2þ decreased with increasing cadded(Mn2þ) (first-order interaction effect). We note that the addition of Mn2þ alone did not have a significant effect on the DOC content of the fractions. Fig. 3 also reveals that the change in DOC content of F1 after 60 min of irradiation did not depend linearly on cadded(Cu2þ). Instead, it appears that already small amounts of added Cu2þ strongly retarded the degradation of F1, with the effect of cadded(Cu2þ) becoming smaller per mmol L1 as cadded(Cu2þ) increased. The presence of Cu2þ in NOM samples has been reported to interfere with wet chemical oxidation methods, such as the one used to quantify DOC in this study. In fact, using the same analytical system and the same water source,1 Brinkmann
(2003) reported reduced carbon recovery rates when adding Cu2þ at concentrations greater than 25 mmol L1. However, for c(Cu2þ) 10 mmol L1, no detection problems were observed. Furthermore, in our experiments, added Cu2þ led to higher DOC content of F1, indicating a retardation in the photocatalytic degradation of F1 rather than an inhibition in DOC detection as observed by Brinkmann (2003), which would have led to an erroneously lower value. Therefore, we rule out a biasing of our results due to systematic measurement error in the presence of added Cu(II) ions. Accordingly, we conclude that the effect of added Cu(II) ions is real and requires an explanation. Because the nature of the counterion ðSO2 4 Þ could play a role in the retarding effect observed for Cu2þ (Abdullah et al., 1990), control experiments were performed using Cl as a counterion 2þ and using SO2 4 in the absence of Cu . These results are shown in Fig. 4. Comparison of the original Lake Hohloh water with a sample spiked with 10 mmol L1 K2SO4 showed no difference between the samples, indicating that the presence of SO2 4 alone does not lead to a retardation of the photocatalytic degradation of NOM at this concentration. Furthermore, the effect of adding 10 mmol L1 CuSO4 or CuCl2$2H2O was essentially identical. Therefore, we conclude that the observed effect is due to the presence of the added Cu(II) ions. Different authors have reported the acceleration and inhibition of degradation reaction kinetics when copper(II) ions are added to titanium dioxide suspensions (e.g. Aarthi and Madras, 2007; Bideau et al., 1991; Cai et al., 2003; Chen et al., 2002; Lindner et al., 1997; Wang et al., 2007). The mechanisms proposed therein are based on the electron acceptor role of copper(II) ions for the conduction band electrons from the irradiated TiO2. This effect has been reported to be concentration dependent (Litter, 1999): at “low” concentrations (similar to those in the present study), the effect of added Cu(II) ions is often reported to be accelerating. This is explained by the ability of Cu(II) ions to
5 4 3 2 1 0 5 4 3 2 1 0
original
+ 10 μmol L−1 K2SO4
+ 10 μmol L−1 CuSO4
+ 10 μmol L−1 CuCl2
35 1
Water from Lake Hohloh exhibits moderate changes in DOC content depending on the sampling time and season. However, the quality of the NOM is essentially constant Abbt-Braun and Frimmel, (2002).
0 min 30 min 60 min
t irrad
Relative DOC signal / AU
DOC contained in fraction / mg L−1
F1
45
55
35
45
55
t r / min Fig. 4 e Control experiments for the inhibiting effect of added Cu2D.
1044
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 3 9 e1 0 4 8
accept electrons from the conduction band, thus inhibiting recombination. at “high” concentrations, the effect of added Cu(II) ions is generally inhibiting. This is attributed to the Cu(II) ions acting as scavengers for OH radicals. These two explanations require the Cu(II) ions to be free in solution. This is a reasonable assumption if the DOC present does not possess complexing moieties (e.g. phenol), as has been the case in most previous studies (Litter, 1999). However, NOM is known to have a high copper complexation capacity. Thus, the formation of NOMeCu2þ complexes may well play a key role in the inhibiting effect observed when adding Cu(II) ions to the TiO2 suspensions. Frimmel and Geywitz (1983) reported complexation capacities of isolated aquatic humic substances from different German lakes and rivers ranging from 1.8 to 6.8 mmol Cu per mg C, as measured by polarography. The complexation capacity of NOM is largely determined by the acidic functional groups present in it (Prado et al., 2006), although Cu2þ is known to be able to bind to both carboxylic and phenolic groups in humic substances (Martyniuk and Wieckowska, 2003). Lake Hohloh water has been shown to possess an acidic functional group in every 4e8th carbon (based on proton titration), with approximately every 10th of these functional groups being able to form stable bivalent metal complexes. Measurements of the copper complexation capacity of Lake Hohloh water yielded a value of z1.9 mmol Cu per mg C (Abbt-Braun and Frimmel, 2002). If all the added copper in our experiments was bound in complexes with the NOM, this would lead to (0:5 mmol Cu per mg C, a value well below the complexation capacity for this NOM. Thus, we expect most Cu2þ ions to be present as Cu2þeNOM complexes. While there is no literature information regarding the photocatalytic degradation of NOM in the presence of Cu(II) ions, indirect information on this process can be obtained from other advanced oxidation processes. Using the H2O2/UV process, Liao et al. (2001) report the inhibition of humic acid (HA) mineralization in the presence of added copper(II) ions, albeit at higher concentrations (40e60 mmol L1) than those used in this study. They proposed that HAecopper complexes are more resistant to attack by HO than HA alone. This would agree with the results presented in Fig. 3 (left panel). However, the experiments by Liao et al. (2001) are strongly convoluted with the radical scavenging effect of Cu2þ because the concentrations present in their experiments exceed by a factor of 5e8 the copper(II) complexation capacity of the humic acid used in those experiments (CCCu2þ ;AldrichHA z1 mmol per mg C; Kolokassidou et al., 2009). No other reports of the degradation of coppereNOM or coppereHA complexes by hydroxyl radicals are known to us. However, the complexing agent EDTA is known to be degraded more rapidly by HO (in the sonolysis process) than its copper complex (CueEDTA; Frim et al., 2003). Thus, it appears that a stabilization of the NOM by complexation is responsible for the inhibition in degradation observed in our experiments. This stabilization of the NOMeCu2þ complexes has practical consequences, such as a reduced formation of bromoform in bromide-containing waters (Tercero Espinoza et al., 2010). It is unclear how the addition of Mn2þ affects the effect of added Cu2þ. Uyguner and Bekbolet (2007) reported that the addition of Mn2þ ions did not significantly alter the degradation
kinetics of humic acids, in agreement with our results for the effect of added Mn2þ alone. However, the type of interaction described above has not yet been reported. A possibility would be, that the Cu2þ complexes are largely substituted by Mn2þ complexes. An analogous behavior was observed by Park et al. (2006) in the system EDTA-Cu2þ/Fe3þ, where the Cu2þ replaced the Fe3þ and changed the degradation kinetics accordingly. However, such a substitution is unlikely for the case NOM-Cu2þ/ Mn2þ because the stability of the Cu2þ complexes of humic and fulvic acids is approx. one order of magnitude higher than that of the corresponding Mn2þ complexes (Hirata, 1981). Cu2þ and Fe3þ generally bind more strongly to humic acids than Mn2þ and Zn2þ (Van Dijk, 1971). We stress, however, that complex stability and increased stability against attack by HO are not the same, as shown for example by the work of Madden et al. (1997) with EDTA complexes of several metal ions. Instead, the effect of complex formation on the degradation kinetics in irradiated TiO2 suspensions appears to depend both on the nature of the metal ion and on the nature of the complexing partner. For example, in the case of EDTA complexes, addition of Fe3þ and Zn2þ inhibit the photocatalytic degradation of the complexes to a much larger extent than addition of Cu2þ, although Cu2þ complexes of EDTA are more stable (Park et al., 2006; Madden et al., 1997). In our experiments, the formation of Cu2þ complexes was the dominating factor.
3.3.2.
Fraction 2 (F2)
Inspection of the fitted coefficients for Equation (1) applied to F2 after tirrad ¼ 30 min shows an influence of cadded(Cu2þ) and suggested small interaction effects between Cu2þ and Zn2þ as well as between Fe3þ and Mn2þ. After 60 min, the effect of added Cu2þ became more dominant. Plotting the DOC content of F2 as a function of only cadded(Cu2þ) reveals a strong, nonlinear dependence (Fig. 3, center panel). This dependence closely mirrored the one shown for F1. Thus, the finding that increasing concentrations of Cu2þ led to a lower DOC content of F2 is complimentary to the observation that adding Cu2þ led to a larger F1.
3.3.3.
Fraction 3 (F3)
Following the same procedure as above, we found a marked effect of added Cu2þ on the DOC content of F3 already after 30 min of irradiation. As already seen for F2, increasing cadded(Cu2þ) also led to a lower DOC content of F3. Analysis of the results after tirrad ¼ 60 min shows qualitatively the same results (shown in Fig. 3, right panel). Thus, the presence of the added metals, especially of copper, slows down the degradation and mineralization of NOM, apparently by stabilizing the high molecular weight material through complexation.
3.4. Formation of low molecular weight organic acids (LMWOA) We then investigated the formation of low molecular weight organic acids upon irradiation. The concentration of four out of six identified acids (formic, acetic, malonic, oxalic, succinic and glutaric acids) was quantified by using ion chromatography (IC). The quantified acids were formic, oxalic, succinic and glutaric acids.
1045
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 3 9 e1 0 4 8
Table 3 e Concentration after irradiation of the quantified low molecular weight organic acids (LMWOA). r (LMWOA), mg L1
LMWOA
Formic acid Oxalic acid Succinic acid Glutaric acid
0 min
30 min
60 min
0.3 0.2 0.1 0.1 18 MU) prepared by a Milli-Q water purification system (Millipore, Billerica, MA) and analytical reagent grade chemicals (Aldrich Co., USA) were used to prepare all the experimental solutions. All glassware was cleaned with distilled water and further sterilized by autoclaving at 121 C for 15 min. The test suspension (10 mM PBS at pH 7.0) contained 3 106 pfu/mL MS-2 phages or 3 106 cfu/mL B. subtilis spores. The concentration of H2O2 was varied from 0 to 0.6 mM. For selected single-step disinfection experiments, test suspensions contained p-chlorobenzoic acid ( pCBA) as OH probe compound and 350 mg/L of 4,40 -dihydroxy-2,2-diphenylpropane (bisphenol-A), 2,4-dichlorophenoxyacetic acid (2,4-D) and geosmine as model organic contaminants. Primary disinfection with UV or UV/H2O2 was performed using a bench-scale collimated-beam UV reactor equipped with 15-W low-pressure UV lamps (Philips Co., Netherlands), emitting nearly monochromatic UV radiation at 253.7 nm (Bolton and Linden, 2001). This equipment introduced parallel UV light to experimental reactor through a 60 50 cm long collimating tube placed below the UV lamps. The experiments were conducted following the procedure described by Bolton and Linden (2003). Prior to the experiment, the UV lamps were turned on for 10 min. The experiments were initiated once a 80 45 mm sterile Petri dish containing 40 mL experimental suspension was placed normal to the incident UV light. The depth of suspension was approximately 1 cm and the UV intensity at 254 nm at surface of suspension was measured using a radiometer equipped with a UV 254 detector (UVX Radiometer, UVP Co., USA). The UV absorbance of experimental suspension containing phosphate buffer, target microorganisms, and/or H2O2 was measured using a UV/Vis
1065
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 6 3 e1 0 7 0
spectrophotometer (Agilent 8453, Agilent Co., Germany) and the average light intensity (Bolton and Linden, 2003) in the suspension was determined to be 0.38 mW/cm2. Sample aliquots (1 mL) were withdrawn from the reactor at various reaction times. Temperature was controlled at 20 C throughout the experiments. Sequential disinfection was performed using the suspension obtained from the above UV or UV/H2O2 experiments. After the primary disinfection achieved 1 log inactivation, the sample suspension was immediately separated using a membrane (0.02 mm hollow-fiber membrane, H2L Co., South Korea) and washed and re-suspended in 10 mM PBS. The recovery of phages and spores from each filtration was over 99.9%. Secondary disinfection was carried out in a 50 mL batch reactor by adding various amounts of free chlorine (sodium hypochlorite, Junsei Co., Japan) from 0.1 to 3 mg/L as active free chlorine. At various reaction times, the residual free chlorine was instantaneously quenched with sodium thiosulfate (Na2S2O3) and samples were collected for viability assessment. All disinfection experiments were repeated three times.
2.3.
Analytical methods
For viability assessments, samples were serially diluted up to a 1/10,000 dilution ratio using 150 mM PBS at pH 7.1. Aliquots of dilutes (0.4 mL for MS-2 phages and 0.1 mL for B. subtilis spores) were inoculated onto three replicate 47-mm sterile Petri dishes containing nutrient agar (and host E. coli for MS-2 phage). Plaque forming unit for MS-2 phage and colony forming units for subtilis spores were counted after incubation at 37 C for 24 h. Selection of statistically meaningful plate counts was carried out according to Standard Methods (APHA et al., 1999). Concentrations of H2O2 and free chlorine were measured based on a titanium sulfate method and N,N-diethyl-p-phenylene diamine (DPD) colorimetric method, respectively, using a UV/ vis spectrophotometer (Agilent 8453, Agilent Co, Germany) (Cho et al., 2006). Concentrations of pCBA, bisphenol-A, and 2, 4-D were determined using a HewlettePackard 1100 HPLC system (Wilmington, DE) equipped with a C18 reverse-phase column (XTerra Rp-18 reverse-phase column) using
acetonitrile as the eluent. Geosmine concentrations were determined by an Agilent 6890 GC/MS equipped with a purge and trap and DB-5 column (30 mm 0.25 mm 0.25 mm) (Cho et al., 2003a; Cho and Yoon, 2008).
3.
Results and discussion
3.1.
Analysis of inactivation kinetics
Fig. 1 shows the decrease in the viability of MS-2 phages (Fig. 1a) and B. subtilis spores (Fig. 1b) versus IT (UV dose: i.e., the average light intensity at 254 nm, I, in mW/cm2, and exposure time, T, in s: Bolton and Linden, 2003) during the single-step disinfection with UV/H2O2. Fig. 2 shows the decrease in viability plotted versus CT (i.e., the product of time-averaged free chlorine concentration, C, and contact time) during free chlorine disinfection. These were performed either as the primary disinfectant in a single-step or as the secondary disinfectant after 1 log inactivation had been achieved by the primary UV or UV/H2O2 disinfection following the kinetics determined in Fig. 1. Note that the secondary disinfection data in Fig. 2 were normalized such that the first data point (i.e., 1 log after primary disinfection) was placed at the origin. Therefore, 1 log inactivation achieved by secondary disinfection with free chlorine would correspond to an overall 2 log inactivation by the sequential process (i.e., 1 log by primary disinfection with UV or UV/H2O2 and an additional 1 log by secondary disinfection by free chlorine). The inactivation curves in Figs. 1 and 2 were characterized by pseudo-first order decrease in viability with respect to IT (i.e., UV dose) or CT, respectively, with the presence of initial lag phase in some of the curves during which little inactivation occurred. The kinetics for UV and UV/H2O2 disinfection were analyzed using the following delayed Chick-Watson model (Rennecker et al., 2000): 8 > > >
> > :
if IT ITlag ; if IT > ITlag ;
(1)
Fig. 1 e Inactivation kinetics of (a) MS-2 phage and (b) B. subtilis spores during the single-step application of UV/H2O2 (Insets in (a) and (b) show changes in k and ITlag as a function of initial H2O2 concentration, respectively; pH 7, 20 C, [I]0 [ 0.38 mW/cm2).
1066
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 6 3 e1 0 7 0
0
log(N/N0)
-1
-2 Synergistic Inactivation
Synergistic Inactivation
Cl2 only
-3
-4 0.0
UV followed by Cl2
Cl2 only
UV/H2O2 followed by Cl2
UV followed by Cl2
UV/H2O2 followed by Cl2 + t-BuOH
UV/H2O2 followed by Cl2
0.1
a
0.2
0.3
0.4
0
60
120
b
CT (mg-min/L)
180
240
300
360
CT (mg-min/L)
Fig. 2 e Inactivation kinetics of (a) MS-2 phage and (b) B. subtilis spores during the single-step application of free chlorine and sequential application of free chlorine after UV and UV/H2O2 (pH 7, 20 C, UV dose: 42 mJ/cm2, [H2O2]0 [ 0.6 mM, [HOCl]0 [ 0.04e4 mg/L). where N ¼ concentration (pfu/mL or cfu/mL) of viable microorganisms at time t, N0 ¼ initial concentration (pfu/mL or cfu/ mL) of viable microorganisms, I ¼ incident light intensity (mW/cm2), k ¼ inactivation rate constant (cm2/mJ), and ITlag ¼ x-axis intercept of the linear portion of inactivation curve. For free chlorine disinfection, IT, in the above equaRt tions, was replaced by CT ¼ 0 Cdt where C ¼ concentration of free chlorine as Cl2 (mg/L), k in cm2/mJ by k in L/(mg-min), and ITlag by CTlag Correlation coefficients for the linear regressions on all the data in the linear region were relatively high (R2 > 0.97). These kinetic parameters determined from Figs. 1 and 2 are summarized in Tables 1 and 2, respectively.
3.2.
for B. subtilis spores to UV light (Mamane-Gravetz et al., 2005; USEPA, 2006), although slight differences in absolute values of UV dose might have resulted from lot to lot variations in microorganisms and differences in test methods. Control test results suggested that addition of H2O2 up to 2 mM did not result in inactivation of either MS-2 phage or B. subtilis spores when UV was not applied. The kinetics of MS-2 phage and B. subtilis spores inactivation increased as the H2O2 concentration was increased (Fig. 1 and Table 1) under the UV irradiation treatment. For example, the UV dose required to achieve a 3 log inactivation at H2O2 concentration of 0.6 mM was 32 and 21 mJ/cm2 for MS-2 phage and B. subtilis spores, respectively. These values were approximately 43% and 24% of the UV dose required to achieve a 3 log inactivation of MS-2 phage and B. subtilis spores by the UV irradiation treatment only. This suggests that the addition of H2O2 was more effective in enhancing inactivation kinetics for MS-2 phage than B. subtilis spores. It is noteworthy that the pseudo-first order rate constant (k) gradually increased as H2O2 concentration was increased for MS-2 phage (Fig. 1a inset). In contrast, for B. subtilis spores, rate constant negligibly changed but the lag-phase factor (ITlag) gradually decreased as H2O2 concentration was increased (Fig. 1b inset). The kinetics were found to be enhanced mostly by OH produced from the photolysis of H2O2 by UV. When excess t-butanol (30 mM) was added to the reaction mixture
Single-step disinfection: UV or UV/H2O2
When the UV irradiation treatment was applied without H2O2, MS-2 phage and B. subtilis spores were inactivated following pseudo-first order kinetics with rate constants (k) of 0.053 and 0.129 cm2/mJ, respectively. The inactivation kinetics for B. subtilis spores was faster by approximately 2.5 times, but exhibited an initial lag phase with ITlag ¼ 4.7 mJ/cm2. The UV dose required to achieve a 3 log inactivation of MS-2 phage and B. subtilis spores by UV alone was 57 and 28 mJ/cm2, respectively. These results are consistent with earlier findings that the UV dose required to achieve 3 log inactivation was 49 mJ/cm2 for MS-2 phage and 24.5 mJ/cm2 for B. subtilis spores, corresponding to approximately 50% higher sensitivity
Table 1 e Lag-phase factor and inactivation rate constant during single-step application of UV/H2O2 (obtained from fitting data in Fig. 1). [H2O2]0 (mM) [t-butanol]0 (mM) MS-2 B. subtilis spores
a
ITlag kb ITlaga kb
a Lag phase: mJ/cm2. b Inactivation rate constant: cm2/mJ.
0
0.05
0.10
0.20
0.25
0.35
0.60
0.60
0
0
0
0
0
0
0
30
0.22 0.053 4.7 0.129
0.54 0.056 e e
0.01 0.060 3.98 0.141
0.82 0.069 e e
e e 2.30 0.146
0.68 0.080 e e
1.46 0.089 0.99 0.155
0.63 0.054 5.34 0.137
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 6 3 e1 0 7 0
Table 2 e Lag-phase factor and inactivation rate constant during the sequential application of free chlorine after UV or UV/H2O2 (obtained from fitting data in Fig. 2). Experimental conditions
Kinetics
Primary Secondary t-BuOH CTlaga disinfection disinfection (mM) MS-2 phage
B. subtilis spores
e UV UV/H2O2 UV/H2O2 e UV UV/H2O2 UV/H2O2
Cl2 Cl2 Cl2 Cl2 Cl2 Cl2 Cl2 Cl2
0 0 0 30 0 0 0 30
0.03 0.03 0.02 0.05 61 45 30 e
kb 8.986 9.276 13.002 10.213 0.011 0.011 0.013 e
a Lag phase: mg-min/L. b Inactivation rate constant: L/mg-min.
containing 0.6 mM H2O2 (i.e., the greatest amount of H2O2 examined), the kinetics of inactivation for both MS-2 phage and B. subtilis spores were significantly reduced and became the same as those obtained with the UV irradiation treatment alone. It is noteworthy that the kinetics was not slower than those obtained with UV alone, since the attenuation of the UV radiation by H2O2 was negligible (UV transmittance: near 97% at the highest H2O2 concentration of 0.6 mM). If UV absorption by H2O2 were significant, the inactivation by UV in UV/H2O2 system could have been inhibited to some degree. The role of OH on MS-2 phage inactivation was quantified separately from that of the UV irradiation treatment. The OH CTwas determined using pCBA as a surrogate using the method described by Elovitz and von Gunten (1999). Fig. 3 shows the level of MS-2 phage inactivation plotted versus CT of OH, which was determined by measuring the steady-state OH concentration using pCBA in the same experimental conditions of Fig. 1. Note that the first data point in the curve is located at 2 logs which represents the inactivation level achieved by the UV irradiation treatment only. The result suggests that the additional inactivation achieved with
Fig. 3 e Level of MS-2 phage inactivation versus H2O2 concentration during single-step UV/H2O2 disinfection (UV dose: 42 mJ/cm2).
1067
H2O2 addition was linearly correlated with the level of OH exposure (CT). For example, increasing the H2O2 concentration from 0.10 mM to 0.60 mM increases the OH CT by a factor of six (0.5 108 to 3.0 108 mg-min/L as OH) and inactivation by OH by a factor of four (from an additional 0.4 log to 1.6 log inactivation). This analysis confirms that OH plays a major role in the enhanced microbial inactivation in the UV/H2O2 system. Enhanced MS-2 phage inactivation might be related to the oxidation of the outer protein coat by OH (Dean et al., 1997; Fiers et al., 1976; Mamane et al., 2007). For B. subtilis spores, oxidation of the cell membrane or cell wall components by OH resulted in the disintegration of the cell and enhanced UV light penetration (Maness et al., 1999; Sunada et al., 2003). The OH CT determined in this study was different from that reported by Mamane et al. (2007) for MS-2 phage (e.g., for 1 log inactivation, OH CT of 0.34 108 mgmin/L was reported by Mamane et al. (2007), while 1.5 108 mg-min/L was measured in this study (Fig. 3), although reasons for such a difference are unclear.
3.3. Sequential disinfection: UV or UV/H2O2 followed by free chlorine Fig. 2 shows the inactivation kinetics of MS-2 phage (Fig. 2a) and B. subtilis spores (Fig. 2b) by the sequential application of UV with and without 0.6 mM H2O2 to achieve 1 log inactivation followed by Cl2. Although chlorine concentration was varied between 0.1 and 3.0 mg/L as Cl2 for each case, all the data points merged into a single inactivation curve when plotted versus CT. When UV alone was applied as the primary disinfectant and chlorine was subsequently applied (i.e., the kinetics were the same with and without preceding UV treatment), no synergistic effect was observed for both MS-2 phage (Shang et al., 2007) and B. subtilis spores (Cho et al., 2006). In contrast, significant synergistic effects were observed when free chlorine was applied after UV/H2O2. For example, the CT required to achieve 2 log inactivation by free chlorine after UV/H2O2 pretreatment was reduced by 32% for MS-2 phage and 18% for B. subtilis spores, when compared to the CT required by single-step inactivation by free chlorine. The observed synergism for MS-2 phage consisted of a decrease in the lag-phase factor (from 0.03 to 0.02 mg-min/L) as well as an increase in the inactivation rate constant (from 8.986 to 13.002 L/mg-min from a linear portion of the curve). For B. subtilis, post-shoulder rate constant did not change, but lag-phase factor decreased from 61 to 30 mg/L-min (Table 2). The synergism observed in the sequential disinfection process with UV/H2O2 followed by free chlorine might be related to the disruption of cell membrane and/or cell wall components by OH during the primary disinfection which facilitates the reactive diffusion of free chlorine during the secondary disinfection step (Arana et al., 1999; Cho et al., 2006). Similar synergistic effects have been previously reported when chemical disinfectants are subsequently applied (Cho et al., 2006). Table 3 summarizes synergistic effects quantified using Percent Synergistic Effect previously defined as “additional log inactivation achieved via sequential disinfectant application compared to individual application” (Cho et al., 2006). Percent synergistic effects ranged from 40 to 250% depending on the microorganisms (B. subtilis spores
1068
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 6 3 e1 0 7 0
Table 3 e Comparison of Percent Synergistic Effect in sequential disinfection with previous studies. Sequential disinfection Percent Synergistic Effect (%)a Primary Secondary Bacillus subtilis spores
O3 ClO2 UV UV/H2O2
HOCl HOCl HOCl HOCl
75%b,c 145%c 0c 65% (this study)
MS-2 phage
UV/H2O2
HOCl
75% (this study)
Cryptosporidium parvum oocyst
O3 O3 ClO2 ClO2
HOCl Chloramine HOCl Chloramine
100%d,e,f, 250%g 100%h, 250%d 100%i 40%i
a Additional log inactivation obtained via sequential disinfectant application (compared to 1 log inactivation by primary disinfectant and 1 log inactivation by secondary disinfectant when each was applied independently) (Cho et al., 2006). b (Cho et al., 2003b). c (Cho et al., 2006). d (Rennecker et al., 2000). e (Driedger et al., 2000). f (Corona-Vasquez et al., 2002). g (Li et al., 2001). h (Biswas et al., 2005). i (Corona-Vasquez et al., 2002).
and C. parvum oocyst in this survey, no data available for MS2 phage during chemical sequential disinfection) and the sequence of disinfectant application. Percent synergistic effects for UV/H2O2-followed-by-HOCl process for MS-2 phage and B. subtilis spores were 75% and 65%, respectively. Also evident in Table 3 is the absence of synergism when the UV irradiation treatment was followed by chemical disinfection. Inactivation by UV has been primarily linked to damages in DNA and RNA without damage to cell wall/ membrane components (Shin et al., 2001; USEPA, 2006). Therefore, synergism is not expected with subsequent application of free chlorine; the inactivation mechanism involving reactive diffusion across the cell wall/membrane (Young and Setlow, 2003).
Effect of the OH on synergism was further quantitatively analyzed in Fig. 4. Sequential disinfection was first performed to achieve 1 log inactivation by primary disinfection with UV and additional 1 log inactivation by secondary application of free chlorine, i.e., overall 2 log inactivation for both microorganisms (i.e., the first bar in Fig. 4 (a) and (b)). Addition of 0.6 mM of H2O2 during the primary UV disinfection step, with other conditions fixed, achieved overall inactivation of 3.5 log for MS-2 phage and 3.3 log for B. subtilis spores. Approximately 0.9 log additional inactivation for MS-2 phage and 0.8 log for B. subtilis spores were achieved during the primary disinfection step due to the additional contribution of OH as discussed above. Furthermore, approximately 0.6 log inactivation for MS-2 phage and 0.5 log for B. subtilis spores were additionally achieved during the secondary chlorine disinfection step. Collectively, the synergism achieved by adding H2O2 occurred in both disinfection steps and summed up to 1.5 log (96.8%) and 1.3 log (95.0%) inactivations that were additionally achieved for MS-2 phage and B. subtilis spores, respectively.
3.4.
Degradation of selected organic contaminants
Addition of H2O2 in the UV disinfection process, whether followed by secondary free chlorination or not, could result in additional benefit with respect to destruction of some organic contaminants. Chemicals such as bisphenol-A, geosmin and 2,4-D (each 350 mg/L) were all found to be negligibly degraded by the individual application of 57 mJ/cm2 (0.38 mW/cm2 for 150 s) of UV or 0.6 mM of H2O2. When 0.6 mM H2O2 was added under 0.38 mW/cm2 of UV irradiation, 73%, 65% and 37% of bisphenol-A, geosmin and 2,4-D were degraded, respectively, within 2.5 min (i.e., hence UV dose ¼ 57 mJ/cm2). These resulted from relatively high rate constants between these chemicals and OH (k(OH þ bisphenol-A) ¼ 1010 M1 s1, k (OH þ geosmin) ¼ 8 109 M1 s1 and k(OH þ 2,4D) ¼ 3 109 M1 s1 (Buxton et al., 1988)). Using these rate constants and steady-state OH concentration (i.e., independently measured using pCBA) would predict 75%, 67%, and 34% degradation of bisphenol-A, geosmin, and 2,4-D, respectively, which are consistent with the above observations.
Fig. 4 e Schematic illustration of synergism observed with the sequential application of UV/H2O2 followed by free chlorine (right bar) compared to UV followed by free chlorine (left bar) for inactivation of (a) MS-2 phage and (b) B. subtilis spores (pH 7, 20 C, UV dose: 19 mJ/cm2, [H2O2]0 [ 0.6 mM, [Cl2]0 [ 0.15 mg/L).
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 6 3 e1 0 7 0
Similar findings have been reported for destruction of endocrine disrupting compounds such as bisphenol-A, ethinyl estradiol and estradiol (Rosenfeldt and Linden, 2004) and taste and odor causing compounds such as methylisoborneol (MIB) and geosmin (Rosenfeldt et al., 2005), amongst others.
4.
Conclusion
The results from this study collective suggest that it could be beneficial to add H2O2 in UV disinfection process in particular when free chlorine is subsequently added as the residual disinfectant. Synergistic effects with respect to microorganism inactivation would be two folds. First, enhanced inactivation of MS-2 phage and B. subtilis spores was observed during the primary UV disinfection step due to the additional inactivation achieved by OH that is produced by H2O2 photolysis. Second, additional level of inactivation was achieved during the secondary disinfection with chlorine. Alternatively, secondary disinfection could benefit from reduced chlorine dosage and accompanying reduction in disinfection by-product formation, while a care must be taken not to induce chlorine decay due to residual H2O2. Overall, the synergism was significant, for example, as much as 1.5 log and 1.3 log inactivation, in addition to the 2 logs expected without synergism, for MS-2 phage and B. subtilis spores for the case discussed above. Finally, the addition of H2O2 in UV process could result in organic contaminant degradation, which otherwise would not be achieved by UV nor free chlorine. These synergistic effects and contaminant degradations resulted from advanced oxidation by OH. It should be noted that all the experiments were performed in organic-free water (except when model contaminants were added) in this study and therefore further studies are required to accurately assess and quantify the synergistic effects in natural waters when UV/H2O2 process is applied. In natural waters, it is expected that more OH (hence more UV irradiation and H2O2) would be required to bring about the similar level of synergistic effects due to UV light absorption and OH scavenging by organic matter and carbonate species.
Acknowledgements The study was supported by the Eco-Technopia 21 project from the Ministry of Environment in Korea and the Korea Research Foundation Grant funded by the Korean Government (KRF-2008-357-D00142).
references
American Public Health Association(APHA), American Water Works Association (AWWA), Water Environmental Federation (WEF), 1999. Standard Methods for the Examination of Water and Wastewater, twentieth ed. American Public Health Association, Washington, D.C. Arana, I., Santorum, P., Muela, A., Barcina, I., 1999. Chlorination and ozonation of waste-water: comparative analysis of
1069
efficacy through the effect on Escherichia coli membranes. Journal of Applied Microbiology 86 (5), 883e888. Biswas, K., Craik, S., Smith, D.W., Belosevic, M., 2005. Synergistic inactivation of Cryptosporidium parvum using ozone followed by monochloramine in two natural waters. Water Research 39 (14), 3167e3176. Bolton, J.R., Linden, K.G., 2001. Determination of Fluence (UV Dose) in a Bench-scale Collimated Beam Apparatus for Monochromatic and Broadband UV Lamps. Proceedings of the American Water Works Association, Water Quality Technology Conference. American Water Works Association, Denver, Colo. Bolton, J.R., Linden, K.G., 2003. Standardization of methods for fluence (UV dose) determination in bench-scale UV experiments. Journal of Environmental Engineering 129 (3), 209e216. Bolton, J.R., Dussert, Z., Bukhari, Z., Hargy, T., and Clancy, J.L. (1998) Inactivation of Cryptosporidium parvum by mediumpressure ultraviolet light in finished drinking water. Proceedings of the American Water Works Association. Water Quality Technology Conference. Annual Conference, Dallas, TX. Bukhari, Z., Hargy, T.M., Bolton, J.R., Dussert, B., Clancy, J.L., 1999. Medium-pressure UV for oocyst inactivation. Journal American Water Works Association 91 (3), 86e94. Buxton, G.V., Greenstock, C.L., Helman, W.P., Ross, A.B., 1988. Critical-review of rate constants for reactions of hydrated electrons, hydrogen-atoms and hydroxyl radicals ($OH/$O) in aqueous solution. Journal of Physical and Chemical Reference Data 17 (2), 513e886. Cho, M., Yoon, J., 2008. Measurement of OH radical CT for inactivating Cryptosporidium parvum using photo/ferrioxalate and photo/TiO2 systems. Journal of Applied Microbiology 104 (3), 759e766. Cho, M., Chung, H.M., Yoon, J., 2003a. Disinfection of water containing natural organic matter by using ozone initiated radical reactions. Applied and Environmental Microbiology 69 (4), 2284e2291. Cho, M., Chung, H.M., Yoon, J., 2003b. Quantitative evaluation of the synergistic sequential inactivation of Bacillus subtilis spores with ozone followed by chlorine. Environmental Science & Technology 37 (10), 2134e2138. Cho, M., Chung, H.M., Choi, W.Y., Yoon, J.Y., 2005. Different inactivation behaviors of MS-2 phage and Escherichia coli in TiO2 photocatalytic disinfection. Applied and Environmental Microbiology 71 (1), 270e275. Cho, M., Kim, J.H., Yoon, J., 2006. Investigating synergism during sequential inactivation of Bacillus subtilis spores with several disinfectants. Water Research 40 (15), 2911e2920. Clancy, J.L., Hargy, T.M., Marshall, M.M., Dyksen, J.E., 1998. UV light inactivation of Cryptosporidium oocysts. Journal American Water Works Association 90 (9), 92e102. Corona-Vasquez, B., Rennecker, J.L., Driedger, A.M., Marin˜as, B.J., 2002. Sequential inactivation of Cryptosporidium parvum oocysts with chlorine dioxide followed by free chlorine or monochloramine. Water Research 36, 178e188. Craik, S.A., Finch, G.R., Bolton, J.R., Belosevic, M., 2000. Inactivation of Giardia muris cysts using medium-pressure ultraviolet radiation in filtered drinking water. Water Research 34 (18), 4325e4332. Dawson, D.J., Paish, A., Staffell, L.M., Seymour, I.J., Appleton, H., 2005. Survival of viruses on fresh produce, using MS2 as a surrogate for norovirus. Journal of Applied Microbiology 98 (1), 203e209. Dean, R.T., Fu, S.L., Stocker, R., Davies, M.J., 1997. Biochemistry and pathology of radical mediated protein oxidation. Biochemical Journal 324, 1e18. Driedger, A.M., Rennecker, J.L., Marin˜as, B.J., 2000. Sequential inactivation of Cryptosporidium parvum oocysts with ozone and
1070
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 6 3 e1 0 7 0
free chlorine. Water Research 34 (14), 3591e3597. Elovitz, M.S., von Gunten, U., 1999. Hydroxyl radical/ozone ratios during ozonation processes. I. The Rct concepts. Ozone: Science & Engineering 21 (3), 239e260. Fiers, W., Contreras, R., Duerinck, F., Haegeman, G., Iserentant, D., Merregaert, J., Minjou, W., Molemans, F., Raeymaekers, A., Vandenberghe, A., Volckaert, G., Ysebaert, M., 1976. Complete nucleotide sequence of bacteriophage MS-RNA - primary and secondary structure of replicase gene. Nature 260 (5551), 500e507. Grabow, W.O.K., Gaussmuller, V., Prozesky, O.W., Deinhardt, F., 1983. Inactivation of Hepatitis-A virus and indicator organisms in water by free chlorine residuals. Applied and Environmental Microbiology 46 (3), 619e624. Keswick, B.H., Satterwhite, T.K., Johnson, P.C., Dupont, H.L., Secor, S.L., Bitsura, J.A., Gary, G.W., Hoff, J.C., 1985. Inactivation of Norwalk virus in drinking-water by chlorine. Applied and Environmental Microbiology 50 (2), 261e264. Larson, M.A., Marin˜as, B.J., 2003. Inactivation of Bacillus subtilis spores with ozone and monochloramine. Water Research 37 (4), 833e844. Li, H.B., Finch, G.R., Smith, D.W., Belosevic, M., 2001. Sequential inactivation of Cryptosporidium partum using ozone and chlorine. Water Research 35 (18), 4339e4348. Linden, K.G., Shin, G.A., Faubert, G., Cairns, W., Sobsey, M.D., 2002. UV disinfection of Giardia lamblia cysts in water. Environmental Science & Technology 36 (11), 2519e2522. Mamane-Gravetz, H., Linden, K.G., Cabaj, A., Sommer, R., 2005. Spectral sensitivity of Bacillus subtilis spores and MS2 coliphage for validation testing of ultraviolet reactors for water disinfection. Environmental Science & Technology 39 (20), 7845e7852. Mamane, H., Shemer, H., Linden, K.G., 2007. Inactivation of E. coli, B. subtilis spores, and MS2, T4, and T7 phage using UV/H2O2 advanced oxidation. Journal of Hazardous Materials 146 (3), 479e486. Maness, P.C., Smolinski, S., Blake, D.M., Huang, Z., Wolfrum, E.J. , Jacoby, W.A., 1999. Bactericidal activity of photocatalytic TiO2 reaction: toward an understanding of its killing mechanism. Applied and Environmental Microbiology 65 (9), 4094e4098. Nakayama, A., Yano, Y., Kobayashi, S., Ishikawa, M., Sakai, K., 1996. Comparison of pressure resistances of spores of six
Bacillus strains with their heat resistances. Applied and Environmental Microbiology 62 (10), 3897e3900. Rennecker, J.L., Driedger, A.M., Rubin, S.A., Marin˜as, B.J., 2000. Synergy in sequential inactivation of Cryptosporidium parvum with ozone/free chlorine and ozone/monochloramine. Water Research 34 (17), 4121e4130. Rosenfeldt, E.J., Linden, K.G., 2004. Degradation of endocrine disrupting chemicals bisphenol A, ethinyl estradiol, and estradiol during UV photolysis and advanced oxidation processes. Environmental Science & Technology 38 (20), 5476e5483. Rosenfeldt, E.J., Melcher, B., Linden, K.G., 2005. UV and UV/H2O2 treatment of methylisoborneol (MIB) and geosmin in water. Journal of Water Supply Research and Technology-Aqua 54 (7), 423e434. Shang, C., Cheung, L.M., Liu, W., 2007. MS2 coliphage inactivation with UV irradiation and free chlorine/monochloramine. Environmental Engineering Science 24 (9), 1321e1332. Shin, G.A., Linden, K.G., Arrowood, M.J., Sobsey, M.D., 2001. Lowpressure UV inactivation and DNA repair potential of Cryptosporidium parvum oocysts. Applied and Environmental Microbiology 67 (7), 3029e3032. Shin, G.A., Sobsey, M.D., 2008. Inactivation of norovirus by chlorine disinfection of water. Water Research 42 (17), 4562e4568. Sjogren, J.C., Sierka, R.A., 1994. Inactivation of phage Ms2 by ironaided titanium-dioxide photocatalysis. Applied and Environmental Microbiology 60 (1), 344e347. Stefan, M.I., Bolton, J.R., 1998. Mechanism of the degradation of 1,4-dioxane in dilute aqueous solution using the UV hydrogen peroxide process. Environmental Science & Technology 32 (11), 1588e1595. Sunada, K., Watanabe, T., Hashimoto, K., 2003. Studies on photokilling of bacteria on TiO2 thin film. Journal of Photochemistry and Photobiology A: Chemistry 156 (1e3), 227e233. USEPA (2006) Ultraviolet Disinfection Guidance Manual for the Final Long Term 2 Enhanced Surface Water Treatment Rule. United States Environmental Protection Agency EPA 815-R-06-007. Young, S.B., Setlow, P., 2003. Mechanisms of killing of Bacillus subtilis spores by hypochlorite and chlorine dioxide. Journal of Applied Microbiology 95 (1), 54e67.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 7 1 e1 0 7 8
Available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Synthetic musk emissions from wastewater aeration basins Nabin Upadhyay a, Qinyue Sun b, Jonathan O. Allen c, Paul Westerhoff d, Pierre Herckes a,* a
Department of Chemistry and Biochemistry, Arizona State University, PO Box 871604, Tempe, AZ 85287-1604, USA School of Mechanical, Aerospace, Chemical and Materials Engineering, Arizona State University, PO Box 871604, Tempe, AZ 85287-1604, USA c Allen Analytics LLC, 3444 N. Country Club Rd., Suite 100, Tucson AZ 85716-1200, USA d School of Sustainable Engineering and The Built Environment, Arizona State University, PO Box 5306, Tempe, AZ 85287- 5306, USA b
article info
abstract
Article history:
Wastewater aeration basins at publicly owned treatment works (POTWs) can be emission
Received 12 May 2010
sources for gaseous or aerosolized sewage material. In the present study, particle and gas
Received in revised form
phase emissions of synthetic musks from covered and uncovered aeration basins were
22 September 2010
measured. Galaxolide (HHCB), tonalide (AHTN), and celestolide (ADBI) were the most
Accepted 18 October 2010
abundant, ranging from 6704 to 344,306 ng m3, 45e3816 ng m3, and 2e148 ng m3 in the
Available online 26 October 2010
gas phase with particle phase concentrations 3 orders of magnitude lower. The musk species were not significantly removed from the exhaust air by an odor control system,
Keywords:
yielding substantial daily emission fluxes (~200 g d1 for HHCB) into the atmosphere.
Synthetic musks
However, simple dispersion modeling showed that the treatment plants are unlikely to be
Wastewater
a major contributor to ambient air concentrations of these species. Emission of synthetic
Publicly owned treatment works
musk species during wastewater treatment is a substantial fate process; more than 14% of
Aeration basin
the influent HHCB is emitted to the atmosphere in a POTW as opposed to the 99%) from Fisher Scientific (Fairlawn, NJ), ACS Reagent Grade Na2SO4 (>99%) from SigmaeAldrich (St. Louis, MO), and Pesticide Grade Glass Wool from Supelco (Bellefonte, PA).
2.2.
Sample collection
Particle and gas phase samples were collected at two POTWs in the Phoenix (AZ) metropolitan area using a commercial semivolatile polyurethane foam (PUF) sampler (TE-1000 PUF, Tisch Environmental Inc., Cleves, OH). Plant A has a design treatment capacity of 68 million liters per day (MLD) of wastewater and includes the following covered processes: headworks, primary sedimentation, aerated activated sludge treatment, secondary sedimentation, tertiary filtration, and disinfection. However, these processes are not closed to air inflow from outside. All of these processes are equipped with ventilation systems to collect and treat off-gases from the facility. Off-gas is passed through an odor control unit (OCU) that consists of packed beds of activated carbon. Air samples at Plant A were collected via an aluminum inlet pipe (4-inch diameter) with one end inserted through a hole in the exhaust side wall of the aeration basin and the other end connected to the inlet of the PUF sampler. Similarly, one end of the aluminum duct faced downward at the OCU vent while the other end was secured to the inlet of the sampler. Plant B has a design capacity of 680 MLD of wastewater, is an uncovered facility (i.e., no odor control), and employs primary sedimentation, aerated activated sludge treatment, secondary treatment, and disinfection. Ambient samples from Plant B were collected at the aeration basin as well as at a perimeter site 200 m away from the aeration basin. Additional urban ambient samples were collected from the rooftop of the School of Life Sciences at the Tempe campus of Arizona State University (ASU). Sampling was conducted during December 2008eFebruary 2009 at Plant A, May 2009 at Plant B, and April 2009 at ASU. The sampled air volume ranged from 133 to 387 m3. Meteorological data, which included speed and direction of wind, were obtained from the meteorological station at Sky Harbor International Airport (http://www. wunderground.com/US/AZ/Phoenix.html). Prevalent wind directions during sampling were ESE, SE, ENE at Plant A; SE, W, SW at Plant B; and SE, ENE, WSW at ASU with a daily average wind speed of 1.3e3.1 m s1. During each sampling, the PUF sampler was operated at a flow rate of 24 L min1 for 9e24 h. Total suspended particulate matter (TSP) was collected on a 4-inch diameter quartz fiber filter (QFF) that was followed by a polyurethane foam plug (PUFP, 3-inch diameter 4-inch height) to trap gas phase species. QFFs were wrapped in aluminum foil and fired at 550 C overnight before use. PUFPs were cleaned prior to use with Alconox and Milli-Q water three times and air-dried under a hood before sonication (20 min) in DCM three times and air-drying. The cleaned PUFPs were stored in amber glass bottles until sampling and extraction. Representative grab samples were collected from the aeration basins close to the sampling inlets during air sampling. Samples were collected in polypropylene bottles cleaned with deionized water (>18 MU-cm) and were stored in the dark at 4 C prior to analysis.
2.3.
Sample preparation
An overview of sample preparation for musk analysis is shown in supporting information (SI Fig. S1). For the particle phase
1073
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 7 1 e1 0 7 8
musk compounds, one-half of a QFF was spiked with the set of internal standards (10 mL each) and extracted 3 times in 25 mL of DCM under sonication. For the gas phase musk samples, the PUFPs were spiked with the internal standards (10 mL each) and extracted 3 times in 50 mL of DCM using compressionerelease cycles. The combined extracts for each phase were filtered through a 0.7 mm pore size Whatman glass fiber filter (GFF), dried under nitrogen, and concentrated to 250 mL separately. Filter blanks for PUFF and PUFP were subject to same extraction and analytical procedures as the samples. Wastewater samples (two from each plant) were first filtered through GFFs. A 250 mL filtrate aliquot was spiked with the internal standards and the salinity increased with 10 g of NaCl. The aqueous phase was then extracted 3 times in 50 mL of DCM. The combined DCM extracts were dried over anhydrous Na2SO4 and concentrated to 250 mL prior to analysis by GC/MS.
2.4.
GC/MS analysis
An Agilent 6890 gas chromatograph coupled to an Agilent 5973 inert mass selective detector with electron impact ionization was used to determine the musk species. Separation was accomplished using an HP 5MS capillary column (30 m
250 mm 0.25 mm, 5% phenyl-methyl-siloxane film). Injections of 1 mL aliquots were performed in splitless mode, and helium (ultra-high purity) was used as a carrier gas. The GC temperature profile consisted of an initial hold time of 10 min at 65 C followed by a temperature gradient of 10 C min1 to a final temperature of 300 C, which was held constant for 20 min. Authentic standards were used for identification and quantification of the target species.
3.
Results and discussion
The synthetic musk compounds under investigation as well as their physicochemical properties are shown in Table 1. Watereoctanol partition coefficients (KOW), water solubility (SW), and Henry’s constants (HC) for these compounds are similar to those for hydrophobic semivolatile organic compounds (Balk and Ford, 1999; Paasivirta et al., 2002; Tas et al., 1997). The observed bioconcentration factors of MK and MX correlate well with their KOW values, whereas those for HHCB and AHTN are lower than predicted from KOW (Rimkus, 1999; Rimkus et al., 1997).
Table 1 e Synthetic musks and their properties. CAS No.
MW
Ions quantified
Retention time (min)
Log KOW
SW, (mg L1)
HC, (Pa m3 mol1)
Galaxolide, HHCB
1222-05-5
258.4
243, 213
25.03
5.9a
1.75
11.3a
Tonalide, AHTN
1506-02-1
258.4
243, 258
25.15
5.7a
1.25
12.5a
Celestolide, ADBI
13171-00-1
244.3
229, 244
23.55
6.6b
0.015
Musk xylene, MX
81-15-2
297.2
282, 229
25.12
4.9c
0.49
0.018c
Musk ketone, MK
81-14-1
294.3
279, 294
26.33
4.3c
1.9
0.0061c
Compound
a Balk and Ford, 1999. b Paasivirta et al., 2002. c Tas et al., 1997.
1801b
Structure
1074
3.1.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 0 7 1 e1 0 7 8
Occurrence of musk species
Table 2 presents the observed concentrations of the target musk species. In the present study, MX and MK were not detected in any samples, so they are not included in any tables or figures. Considering the sampling times and analytical protocols used, atmospheric (gas and particle phases) concentrations of these species would be substantially below 1 ng m3. HHCB, AHTN, and ADBI were detected in atmospheric samples. Trace amounts of HHCB were detected in field blanks; however, the equivalent air concentrations (0.12 ng m3 in gas and 3.2 ng m3 in particle phase) were orders of magnitude lower than the typical sample concentrations. Detection limits (DLs) for the present work were defined as the smallest signal of the analyte that can be distinguished from background noise by the GC/MS. DLs for HHCB, AHTN, and ADBI were 0.6, 0.03, and 0.03 ng m3 (air volume ¼ 350 m3), respectively. Gas-phase HHCB and AHTN ranged from 74,585 to 344,306 ng m3 and 374 to 3816 ng m3 at Plant A and 6704 to 17223 ng m3 and 45 to 192 ng m3 at Plant B, respectively. Gasphase ADBI in our POTW samples ranged from 2 to 148 ng m3, which are several orders of magnitude higher than reported in urban or background samples in the published literature (Peck and Hornbuckle, 2004; Xie et al., 2007). Particle phase concentrations were much lower, with HHCB and AHTN ranging from 11 to 146 ng m3 and 2 to 26 ng m3 at Plant A and 73 to 110 ng m3 and 15 to 23 ng m3 at Plant B, respectively. It is noteworthy that the gas and particle phase HHCB and AHTN showed a steep decline, e.g., at Plant B, by 1e2 orders of magnitude between the over-the-aeration basin and the off-site location (Table 2). Short atmospheric lifetime on the order of 5.3 h (for HHCB) (Aschmann et al., 2001), quick diffusion, and sampling on different days at the aeration basin and off-site
location might have caused these large discrepancies in concentrations between the emission source and off-site location. However, high concentrations of gas phase HHCB and AHTN close to the plant (Plant B) and background ASU (Table 2) could not be explained. Atmospheric concentrations of musk species during our study were highly variable with one sample (5-Nov-08, Plant A) having exceptionally high concentrations of musk compounds. This is likely reflective of changes in wastewater contents. In the present study, daily liquid samples were not collected. However, Reiner and coworkers (Reiner et al., 2007) report HHCB and AHTN in POTWs vary by a factor of 6 in wastewater samples collected within 5 consecutive days. In all cases, the musk species were partitioned nearly exclusively into the gas phase. The percentage concentrations of gas-phase HHCB and AHTN (cg/(cgþcp) 100%, where cp and cg are the particle and gas phase concentrations, respectively) at both plants and off-site at Plant B were >99% and 95.5%, respectively. Urban background gas-phase concentrations of HHCB and AHTN ranged from 213 to 238 ng m3 and 1 to 2 ng m3, respectively, while particle-phase concentrations of HHCB and AHTN were both 0.99). Quantitatively, the maximum adsorption capacity was 2.27 mmol/g for copper, versus 1.27 mmol/g for lead and nearly 0.65 mmol/g for cadmium, corresponding to the sequence of metal electro negativity (Ling et al., 2010) and log b (MEDTA), which was the index of the stability constant and well documented of the order Cu (18.83) > Pb (17.04) > Cd (16.54) (Abollino et al., 2000). These thermodynamic data suggested that the complex MEDTA (formed by the metal M and the chelating agent) of EDTA (Ethylene Diamine Tetraacetic Acid) with Cu (II) should be more stable than those with Pb (II) and Cd (II). According to our previous investigation (Ling et al., 2010), the adsorption process of metal ions onto IDA resin could be contributed to both ion-exchange and chlelation. In addition, the isotherm data could be well described with the Langmuir model and the maximum capacities calculated were all close to those actually determined. Thus, the chemical interaction was considered to be the dominant mechanism, as was consistent with the earlier manuscript (Liao and Shi, 2005). And the detailed properties of the resin were as follows: the content of nitrogen and oxygen was 5.00% and 20.58%, the specific area was 14.24 m2/g, the pore volume was 0.12 cm3/g and the average pore size was 34.53 nm. In addition, the cation exchange capacity was about 5.50 mmol/g, so the concentration of different functional group was calculated to be 2.75 mmol/g for iminodiacetic acid group, 0.47 mmol/g for amino acetic acid and 0.35 mmol/g for amino-group. The adsorption of metal ions toward both the synthesized resin and chelating reagent EDTA followed the same tendency, implying the dominant functional group attached to resin beads was iminodiacetic acid which had the same characteristic with the chelating reagent.
3.1.2.
Binary solutes
The competitive adsorption equilibrium isotherms for Cu (II)/ Pb (II), Pb (II)/Cd (II) and Cu (II)/Cd (II) binary solutes were obtained by fixing the initial concentration of interferential metal ions.
Table 2 e Separation factors for Cu (II)/Pb (II)and Cu (II)/Cd (II) on IDA resin at different concentrations. C02 Pb ¼ 2.0 Pb ¼ 5.0 Cd ¼ 2.0 Cd ¼ 5.0 C01 (mmol/L) (mmol/L) Cu ¼ 0.5 Cu ¼ 1.0
16.40 10.68
21.30 13.50
1181
65.88 37.66
133.91 74.08
component solution, the uptake amount of copper increased with the increasing initial concentration under the fixed concentration of lead as the background, and the trend was similar with that of the single solute. However, the capacity of copper decreased with the increase in the initial concentration of lead, obviously in the higher concentration. The maximum uptake toward copper reduced from 2.24 mmol/g in sole solution to 1.59 mmol/g with the coexistence of 5 mmol/L lead, and the decreasing ratio value, Dr, was about 30%. The antagonistic phenomena could also be found when lead was the target species. The maximum capacity of lead in single system was 1.23 mmol/g, while the value decreased to 0.58 mmol/g in the presence of 5 mmol/L of copper. In the comparison of Dr, the inhibitory extent by copper was around 53%, almost twice of that by lead. The lower adsorption yield in the binary system validated the antagonism between the two metal ions. The analogous trend could also be observed in the ternary metal solution of Cd (II)/Zn (II)/Ni (II) (Srivastava et al., 2008), Cu (II)/Pb (II)/Cd (II) (Sheng et al., 2007), as the sorption capacity of the primary metal decreased because of the coexistent metal ions in the system (Balasubramanian et al., 2009). One possible explanation for the antagonism phenomenon was the direct competitive effects on the active adsorption sites. The distribution coefficients Kd (mL/g) (Eq. (2)), a potential mobility index of a metal, also verified the interaction between the two species in solution because of the competition effect. Kd reduced significantly with the coexistence of copper or lead, whereas the diversity could be examined from Fig. 1. The reduction of distribution coefficients of Cd (II), Ni (II) and Zn (II) was also found in the competitive adsorption onto sludge-amended soil (Antoniadis et al., 2007). In addition, the trend was in good agreement with the former results (Prasad et al., 2008). The Kd value dropped significantly at the higher background metal concentrations, slightly at the low concentrations. At a lower metal concentration, each metal species was mainly adsorbed onto specific sites, and the adsorption sites in binary systems may be partially overlapped with the further increase in total metal concentration (Saha et al., 2002; Papini et al., 2004). The Kd value of copper or lead reduced obviously when the target ion concentration was fixed at 0.5 mmol/L and the concentration of interferential species increased from 0.5 mmol/L to 5 mmol/L. However, it was noteworthy the decrease degree of lead should be more obvious than that of copper, 82% and 99% versus 62% and 94%, which was consistent with the adsorption capacity.
3.1.2.2. For Cu (II)/Cd (II) binary system. In Cu (II)/Cd (II) system, although the presence of cadmium seemed to make no pronounced inhibitory effect on the adsorption of copper, the coexistence of copper putted significant influence upon the adsorption for cadmium. Obviously when 5.0 mmol/L of copper was introduced, the removal of cadmium was almost negligible with a decreasing ratio Dr of 89%. The Kd value of copper in single solute of 0.5 mmol/L was 126.79 mL/g, but was remarkably decreased to 69.36 mL/g and 18.22 mL/g in the presence of 0.5 mmol/L and 5 mmol/L of cadmium as the competitive ions, with a reduction of 45% and 86% respectively. However, the Kd of cadmium was dropped with a more obvious reduction of 69% and 99% at the same case.
1182
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 7 7 e1 1 8 8
Table 3 e Multi-component isotherm models parameters for the adsorption of Cu (II), Pb (II) and Cd (II) at 303 K. Nonmodified Langmuir
Modified Langmuir
Cu (II)/Pb (II) RSS Parameters
0.964 e
0.619 hCu ¼ 0.88; hPb ¼ 1.30
0.907 Qmax ¼ 1.92; KEL,Cu ¼ 22.23; KEL,Pb ¼ 2.37
Cu (II)/Cd (II) RSS Parameters
1.728 e
0.966 hCu ¼ 0.97; hCd ¼ 2.05
1.123 Qmax ¼ 2.00; KEL,Cu ¼ 12.62; KEL,Cd ¼ 0.25
Pb (II)/Cd (II) RSS Parameters
0.702 e
0.284 hPb ¼ 1.45; hCd ¼ 3.19
0.280 Qmax ¼ 1.22; KEL,Cd ¼ 0.46; KEL,Pb ¼ 3.99
3.1.2.3. For Pb (II)/Cd (II) binary system. Similarly, a greater inhibitory effect was exerted by lead than cadmium. In Pb (II)/Cd (II)system, the uptake amount of lead slightly reduced to 1.14 mmol/g in the presence of 5 mmol/L cadmium with a Dr
Extended Langmuir
value of only 7%. While the capacity of cadmium was significantly affected by the coexistence of lead and the Dr was nearly 92%. The Kd value of lead in single solute of 0.5 mmol/L was 33.79 mL/g, but decreased by 91.36% and 94.73% in the
Fig. 2 e Three-dimensional isotherm surfaces simulated with the modified Langmuir isotherm model: (a) Cu (II)/Pb (II) binary system, (b) Pb (II)/Cd (II) binary system and (c) Cu (II)/Cd (II) binary system.
1183
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 7 7 e1 1 8 8
Table 4 e Kinetic rate equation parameters for the adsorption of Cu (II), Pb (II) and Cd (II) on the chelating resin at initial concentration of 0.5 mmol/L,1.0 mmol/L and 2.0 mmol/L. Metals
C0 (mmol/L)
First-order
Second-order 2
Intraparticle diffusion 2
Qe
k1
r
Qe
k2
h
r
kint
r2
Cu (II)
0.5 1.0 2.0
0.23 0.46 1.05
0.03 0.01 0.01
0.937 0.926 0.976
0.55 1.00 1.64
0.09 0.03 0.01
0.017 0.026 0.039
0.996 0.991 0.990
0.06 0.05 0.01
0.879 0.876 0.908
Pb (II)
0.5 1.0 2.0
0.26 0.73 0.97
0.02 0.03 0.01
0.945 0.947 0.965
0.47 0.72 0.96
0.06 0.03 0.02
0.014 0.016 0.016
0.996 0.991 0.990
0.03 0.03 0.06
0.980 0.990 0.976
Cd (II)
0.5 1.0 2.0
0.31 0.30 0.58
0.11 0.03 0.04
0.932 0.987 0.978
0.35 0.45 0.65
0.11 0.03 0.04
0.011 0.012 0.015
0.997 0.999 0.991
0.09 0.08 0.04
0.987 0.934 0.954
presence of 0.5 mmol/L and 5.0 mmol/L of cadmium, respectively. Whereas, the Kd of cadmium dropped more at the coequal condition.
3.1.3. Selectivity of IDA resin toward Cu (II) over Pb (II) and Cd (II) The separation factor was predicted to be concentration and coexistence species dependent. At the fixed initial concentration of Cu (II), the separation factor doubled when the initial concentration of Cd (II) ranged from 2.0 mmol/L to 5.0 mmol/L, but when the concomitant was Pb (II), the separation factor was only 1.3 times (Table 2). When the initial concentration of secondary species (lead or cadmium) was
constant, the separation factor decreased at elevated concentration of Cu (II). The aCu Pb value was always lower than at the same ratio value, moreover, the value of aCu aCu Cd Cd achieved to 133.91 when the initial concentration molar ratio was 10 while the value of aCu Pb was 21.30. The difference may indicate the good selectivity of this resin toward Cu (II) over Cd (II) especially at higher ratio.
3.1.4.
Model of binary adsorption isotherms
The parameters of multi-component models are shown in Table 3, from which the modified Langmuir model could describe the experimental data well over the other two with a lowest RSS value. Adding no more extra parameters, the
Fig. 3 e Time profiles of Cu (II) and Pb (II) adsorption by the chelating resin under noncompetitive and competitive conditions at equal molar ratio (C0 [ 0.5 mmol/L, 1.0 mmol/L and 2.0 mmol/L).
1184
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 7 7 e1 1 8 8
nonmodified Langmuir isotherm model could not explain the adsorption profiles of the metal ions in the binary system with a RSS value of 0.964.The use of parameters, Qmax and KEL,i which were irrespective of those derived from the individual isotherm improved the agreement of the extended Langmuir isotherm model. The value of KEL,i revealing the affinity of the chelating resin toward the adsorbates duplicated the order of single isotherm. For example, the KEL,i value for copper ions in Cu (II)/Cd (II) binary system was almost 50 times of the cadmium species while the ratio of the KEL,i between the preferred ions and the secondary species in Cu (II)/Pb (II) and Pb (II)/Cd (II) system was only 9.3 and 8.6 (Table 3). The higher the interaction coefficient, h, the smaller the inhibitory effect of the metal ions on the adsorption of the other species. The interaction coefficient followed the order of Cu (II) < Pb (II) < Cd (II), which did not agree with the phenomena observed in the biosorption of the three metal ions toward a marine alga (Sheng et al., 2007), where the sequence was Pb (II) < Cu (II) < Cd (II). But the conclusion kept coincidence with the affinity of metal species which was mentioned above in Section 3.1.1 associated with the characteristic of functional group and the metal ions. The adsorption of copper was depressed clearly by the presence of lead neither cadmium while the suppressive influence of lead toward cadmium was more obvious than copper, but the cadmium exerted more inhibitory effect on the adsorption of lead than copper. Fig. 2 displays the three-dimensional adsorption surfaces for the metal uptakes of each species against the concentration at equilibrium. It is obvious from Fig. 2(a) that the shape of the isotherm surface of copper component was affected slightly by varying the initial concentration of lead from 0 to 5.0 mmol/L, whereas the surface of lead could not be duplicated accurately. The adsorption surface of lead behaved concavely downward and even close to the XY plane at a higher initial concentration of copper ions. As illustrated in Fig. 2(b) and (c), similar uptake surfaces were observed in the other two binary systems. For instance, in Cu (II)/Cd (II) system where the copper component was favorably adsorbed over cadmium ions, the cadmium removal was more significantly influenced by the presence of the coexistent copper species.
3.2.
Adsorption kinetics
3.2.1.
For single metal system
The adsorption rate was rapid at the first 100 min after which the rate slowed down and the equilibrium was reached in 6 h contact time. The same result was observed for all the examined metal species at three different initial concentrations. The pseudo second-order rate equation could describe the single metal species system with extremely high correlation coefficients highlighting the chemisorption rate-controlling mechanism (Reddad et al., 2002) and the parameters are tabulated in Table 4. The initial sorption rate, h, followed the order Cu (II) > Pb (II) > Cd (II) at the fixed initial concentration which was in accordance with the affinity order observed in the equilibrium isotherm experiments. But the reverse affinity order of initial sorption rate and equilibrium capacity was obtained because the weakly adsorbed metal species, nickel, strongly reacted with some functional groups and not with all moieties of the
polysaccharide (Reddad et al., 2002). The fact might also reveal the iminodiacetic acid group was the dominant functional group of the resin beads. For certain metal species, the sorption rate constants, k2, increased with a decrease in the initial concentration owing to the numerous metal ions competing against limited sorption sites and higher initial concentration reducing the diffusion in the boundary layer (Liu et al., 2005). However, the initial sorption rate, h, increased with an increase in the initial metal concentration which was consistent with the adsorption of lead onto a biosorbent of sugar beet pulp (Reddad et al., 2002).
3.2.2.
Binary component
3.2.2.1. For Cu (II)/Pb (II) binary systems. Fig. 3 shows the competitive kinetic results in Cu (II)/Pb (II) binary system at equimolar levels with the initial concentration of 0.5 mmol/L, 1.0 mmol/L and 2.0 mmol/L. When the initial concentrations were 0.5 mmol/L and 1.0 mmol/L, for both two components, the uptake amount was increased as the time prolonged and then followed by a plateau just as in the single solute. But the inhibitory effect caused by the competition of the two species could still be observed evidently from Fig. 3. As to the uptake amount of certain metal species, comparing the profiles of the single and binary systems, the latter were always lower during the experimental processes. When the initial concentration was 2.0 mmol/L, the kinetic adsorption behavior of copper and
Fig. 4 e Schematic illustration for the displacement mechanism between Cu (II) and Pb (II).
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 7 7 e1 1 8 8
lead was found diverse completely. The uptake capacity of copper ions was increasing upon the contact time while the adsorbed lead reduced gradually after a maximum, and such similar displacement results were also well documented in earlier literature (Kang et al., 2004; Lv et al., 2005). The possible elucidative mechanism was that both the copper and lead ions were adsorbed at the initiative stage when the most functional groups were available but the ever adsorbed lead released from the active sites because of the higher affinity of resin toward copper over lead. The desorption behavior resulted a decreasing uptake amount of lead ions at the succedent stage. Liu et al. (Liu et al., 2008) verified the conclusion with a pre-loaded experiment and speculated the displacement mechanism through an adjacent attachment and repulsion effect. As depicted in Fig. 4, the case here was not the same as the above reference because the IDA resin used in the present paper produced no net electric repulsion during the adsorption process. The lead ions could be adsorbed early because of the available active sites in the resin beads at the beginning, and then the favorable species copper ions approached the binding sites which were occupied by the lead ions, finally the copper ions displaced the lead species directly due to the more stable complexes formed between the copper species and the functional groups. The displacement phenomenon conduced desorption of the unfavorable component.
3.2.2.2. For Cu (II)/Cd (II) and Pb (II)/Cd (II) binary systems. The similar adsorption results on the behavior of metal ions in
1185
Cu (II)/Cd (II) and Pb (II)/Cd (II) binary system were observed. For instance, as shown in Fig. 5, in Cu (II)/Cd (II) systems, copper exerted a greater inhibitory effect on cadmium and desorption of cadmium ions was revealed when the initial concentration was as high as 2.0 mmol/L. While in the Pb (II)/ Cd (II) component, lead was the favorable adsorbed species which replaced the previously adsorbed cadmium species (Fig. 6).
3.2.3.
Description of the binary adsorption kinetics
Only the time profiles of copper species in Cu (II)/Pb (II) and Cu (II)/Cd (II) competitive solution at the initial concentration of 0.5 mmol/L showed a good correlation with the pseudo second-order rate equation well (r2 > 0.99). The deviation of the other species might due to the competitive effect of the two adsorbates and the displacement mechanism conducted by the stronger affinity to copper ions over the other two species toward resin beads, which was agree with the conclusion that only the favorable species, lead, can follow the pseudo-second-order equation in earlier literature (Lv et al., 2005). In addition, the fact should also be noted when the initial concentration was 1.0 mmol/L and 2.0 mmol/L, the pseudosecond-order rate model was not applicable, even for the most preferentially copper component. The possible reason was the higher the initial concentration, the stronger competitive effect because of the more numerous metal ions in the system and the less active sites available. Comparing the kinetic rate
Fig. 5 e Time profiles of Cu (II) and Cd (II) adsorption by the chelating resin under noncompetitive and competitive conditions at equal molar ratio (C0 [ 0.5 mmol/L, 1.0 mmol/L and 2.0 mmol/L).
1186
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 7 7 e1 1 8 8
Fig. 6 e Time profiles of Pb (II) and Cd (II) adsorption by the IDA-chelating resin under noncompetitive and competitive conditions at equal molar ratio (C0 [ 0.5 mmol/L, 1.0 mmol/L and 2.0 mmol/L). constant of pseudo second-order rate equation, Qe, k2 and h, in single and binary systems, the antagonism in the mixture could be substantiated once again. For instance, the adsorption rate constants, k2, for copper were 0.09, 0.0346, 0.0399 (g mmol1 min1) in mono-metal solution, Cu (II)/Pb (II) and Cu (II)/Cd (II) binary systems, with a reduction of 62% and 56%. The smaller k2 value for copper in Cu (II)/Pb (II) solutions elucidated the greater inhibitory effect on copper removal exerting by lead than cadmium which was agree with the conclusion from the isotherm section.
concentration because of the competitive influence. Desorption of the unfavorable species (lead or cadmium) in binary solute was observed in the kinetic section and the possible mechanism could be described as direct displacement effect. It will be potential to apply the chelating resin in selectively separating and concentrating copper from Cu/Pb or Cu/Cd solution. The direct displace mechanism of the adsorption process might enlighten that the interaction time should be a key factor associated with the recovery efficiency for the favorite species.
Acknowledgements 4.
Conclusion
Due to the complex interaction of metal species and the IDA functional group, the maximum uptake capacity of individual adsorption was 2.27 mmol/g, 1.27 mmol/g and 0.65 mmol/g for Cu (II), Pb (II) and Cd (II) respectively. The antagonism between the two species resulted in the modified Langmuir isotherm with an introduction of the interaction coefficient representing the data adequately. The interaction coefficient followed the order of Cu (II) < Pb (II) < Cd (II), implying copper was the most favorable species and the affinity toward cadmium was the weakest. The separation factor achieved 21.30 and 133.91, implying the good selectivity of IDA resin toward Cu (II) over Pb (II) and Cd (II). The initial sorption rate, h, followed the same order with the affinity obtained from the isotherm study, but the time profile of the binary system could not fit the kinetic equations except the adsorption of copper ions at the low initial
The authors gratefully acknowledge generous support provided by the State Key Program of National Natural Science (Grant No. 50938004), the Resources Key Subject of National High Technology Research & Development Project (863 Project, Grant Nos. 2009AA06Z315 and SQ2009AA06XK1482331) P.R. China, the National Natural Science Foundation of P.R. China (No. 50878103, No.51078178) and the Discipline Crossing Foundation of Nanjing University.
references
Abollino, O., Aceto, M., Sarzanini, C., Mentasti, E., 2000. The retention of metal species by different solid sorbents: mechanisms for heavy metal speciation by sequential three column uptake. Analytica Chimica Acta 411, 223e237.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 7 7 e1 1 8 8
Aksu, Z., Acikel, U., Kabasakal, E., Tezer, S., 2002. Equilibrium modelling of individual and simultaneous biosorption of chromium(VI) and nickel (II) onto dried activated sludge. Water Research 36, 3063e3073. Antoniadis, V., Tsadilas, C.D., Ashworth, D.J., 2007. Monometal and competitive adsorption of heavy metals by sewage sludge-amended soil. Chemosphere 68, 489e494. Atia, A.A., Donia, A.M., Yousif, A.M., 2003. Synthesis of amine and thio chelating resins and study of their interaction with zinc (II), cadmium (II) and mercury (II) ions in their aqueous solutions. Reactive and Functional Polymers 56, 75e82. Balasubramanian, R., Perumal, S.V., Vijayaraghavan, K., 2009. Equilibrium isotherm studies for the multicomponent adsorption of lead, zinc, and cadmium onto Indonesian Peat. Industrial and Engineering Chemistry Research 48, 2093e2099. Basha, S., Murthy, Z.V.P., Jha, B., 2009. Removal of Cu (II) and Ni (II) from industrial effluents by brown seaweed, Cystoseira indica. Industrial and Engineering Chemistry Research 48, 961e975. Bernal-Martinez, L.A., Hernandez-Lopez, S., Barrera-Diaz, C., Urena-Nunez, F., Bilyeu, B., 2008. Pb (II) sorption under batch and continuous mode using natural, pretreated, and aminomodified ectodermis of Opuntia. Industrial and Engineering Chemistry Research 47, 1026e1034. Bhattacharyya, K.G., Sen Gupta, S., 2007. Adsorptive accumulation of Cd (II), Co (II), Cu (II), Pb (II), and Ni (II) from water on montmorillonite: influence of acid activation. Journal of Colloid and Interface Science 310, 411e424. Celis, R., Hermosin, M.C., Cornejo, J., 2000. Heavy metal adsorption by functionalized clays. Environmental Science and Technology 34, 4593e4599. Dabrowski, A., Hubicki, Z., Podkoscielny, P., Robens, E., 2004. Selective removal of the heavy metal ions from waters and industrial wastewaters by ion-exchange method. Chemosphere 56, 91e106. Deng, S.B., Ting, Y.P., 2005a. Characterization of PEI-modified biomass and biosorption of Cu (II), Pb (II) and Ni,(II). Water Research 39, 2167e2177. Deng, S.B., Ting, Y.P., 2005b. Fungal biomass with grafted poly (acrylic acid) for enhancement of Cu (II) and Cd (II) biosorption. Langmuir 21, 5940e5948. Deng, S.B., Bai, R.B., Chen, J.P., 2003. Aminated polyacrylonitrile fibers for lead and copper removal. Langmuir 19, 5058e5064. Gurgel, L.V.A., Gil, L.F., 2009. Adsorption of Cu (II), Cd (II) and Pb (II) from aqueous single metal solutions by succinylated twicemercerized sugarcane bagasse functionalized with triethylenetetramine. Water Research 43, 4479e4488. Ho, Y.S., 2006. Second-order kinetic model for the sorption of cadmium onto tree fern: a comparison of linear and nonlinear methods. Water Research 40, 119e125. Huang, L.Y., Ou, Z.Y., Boving, T.B., Tyson, J., Xing, B.S., 2009. Sorption of copper by chemically modified aspen wood fibers. Chemosphere 76, 1056e1061. Jal, P.K., Patel, S., Mishra, B.K., 2004. Chemical modification of silica surface by immobilization of functional groups for extractive concentration of metal ions. Talanta 62, 1005e1028. Jeon, C., Holl, W.H., 2003. Chemical modification of chitosan and equilibrium study for mercury ion removal. Water Research 37, 4770e4780. Kang, S.Y., Lee, J.U., Moon, S.H., Kim, K.W., 2004. Competitive adsorption characteristics of Co2þ, Ni2þ, and Cr3þ by IRN-77 cation exchange resin in synthesized wastewater. Chemosphere 56, 141e147. Liao, X.P., Shi, B., 2005. Adsorption of fluoride on zirconium (IV)impregnated collagen fiber. Environmental Science and Technology 39, 4628e4632. Lim, S.F., Zheng, Y.M., Zou, S.W., Chen, J.P., 2008. Characterization of copper adsorption onto an alginate
1187
encapsulated magnetic sorbent by a combined FT-IR, XPS and mathematical modeling study. Environmental Science and Technology 42, 2551e2556. Lin, L.-C., Juang, R.-S., 2007. Ion-exchange kinetics of Cu (II) and Zn (II) from aqueous solutions with two chelating resins. Chemical Engineering Journal 132, 205e213. Ling, P., Liu, F., Li, L., Jing, X., Yin, B., Chen, K., Li, A., 2010. Adsorption of divalent heavy metal ions onto IDA-chelating resins: simulation of physicochemical structures and elucidation of interaction mechanisms. Talanta 81, 424e432. Liu, C.C., Kuang-Wang, M., Li, Y.S., 2005. Removal of nickel from aqueous solution using wine processing waste sludge. Industrial and Engineering Chemistry Research 44, 1438e1445. Liu, C.K., Bai, R.B., Ly, Q.S., 2008. Selective removal of copper and lead ions by diethylenetriamine-functionalized adsorbent: behaviors and mechanisms. Water Research 42, 1511e1522. Lv, L., Hor, M.P., Su, F.B., Zhao, X.S., 2005. Competitive adsorption of Pb2þ, CU2þ, and Cd2þ ions on microporous titanosilicate ETS-10. Journal of Colloid and Interface Science 287, 178e184. Meena, A.K., Mishra, G.K., Rai, P.K., Rajagopal, C., Nagar, P.N., 2005. Removal of heavy metal ions from aqueous solutions using carbon aerogel as an adsorbent. Journal of Hazardous Materials 122, 161e170. Mumford, K.A., Northcott, K.A., Shallcross, D.C., Stevens, G.W., Snape, I., 2007. Development of a two parameter temperaturedependent semi-empirical thermodynamic ion exchange model using binary equilibria with Amberlite IRC 748 resin. Industrial and Engineering Chemistry Research 46, 3766e3773. Muraviev, D., Gonzalo, A., Valiente, M., 1995. Ion-exchange on resins with temperature-responsive selectivity.1. Ionexchange equilibrium of Cu2þand Zn2þ on iminodiacetic and aminomethylphosphonic resins. Analytical Chemistry 67, 3028e3035. Papini, M.P., Saurini, T., Bianchi, A., Majone, M., Beccari, M., 2004. Modeling the competitive adsorption of Pb, Cu, Cd, and Ni onto a natural heterogeneous sorbent material (Italian Red soil. Industrial and Engineering Chemistry Research 43, 5032e5041. Petrus, R., Warchol, J.K., 2005. Heavy metal removal by clinoptilolite. An equilibrium study in multi-component systems. Water Research 39, 819e830. Pilsniak, M., Trochimczuk, A.W., 2007. Synthesis and characterization of polymeric resins with aliphatic and aromatic amino ligands and their sorption behavior towards gold from ammonium hydroxide solutions. Reactive and Functional Polymers 67, 1570e1576. Prasad, M., Xu, H.Y., Saxena, S., 2008. Multi-component sorption of Pb (II), Cu (II) and Zn (II) onto low-cost mineral adsorbent. Journal of Hazardous Materials 154, 221e229. Reddad, Z., Gerente, C., Andres, Y., Le Cloirec, P., 2002. Adsorption of several metal ions onto a low-cost biosorbent: kinetic and equilibrium studies. Environmental Science and Technology 36, 2067e2073. Sag, Y., Akcael, B., Kutsal, T., 2002. Ternary biosorption equilibria of chromium(VI), copper (II), and cadmium (II) on Rhizopus arrhizus. Separation Science and Technology 37, 279e309. Saha, U.K., Taniguchi, S., Sakurai, K., 2002. Simultaneous adsorption of cadmium, zinc, and lead on hydroxyaluminumand hydroxyaluminosilicate-montmorillonite complexes. Soil Science Society of America Journal 66, 117e128. Seo, D.C., Yu, K., DeLaune, R.D., 2008. Comparison of monometal and multimetal adsorption in Mississippi River alluvial wetland sediment: batch and column experiments. Chemosphere 73, 1757e1764. Sheng, P.X., Ting, Y.P., Chen, J.P., 2007. Biosorption of heavy metal ions (Pb, Cu, and Cd) from aqueous solutions by the marine alga Sargassum sp. in single- and multiple-metal systems. Industrial and Engineering Chemistry Research 46, 2438e2444.
1188
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 7 7 e1 1 8 8
Srivastava, V.C., Mall, I.D., Mishra, I.M., 2008. Antagonistic competitive equilibrium modeling for the adsorption of ternary metal ion mixtures from aqueous solution onto bagasse fly ash. Industrial and Engineering Chemistry Research 47, 3129e3137. Trochimczuk, Andrzej W., 2000. Synthesis and chelating properties of resins with methylthiourea, guanylthiourea and dithiocarbamate groups. European Polymer Journal 36, 2359e2363.
Wingenfelder, U., Nowack, B., Furrer, G., Schulin, R., 2005. Adsorption of Pb and Cd by amine-modified zeolite. Water Research 39, 3287e3297. Xiao, B., Thomas, K.M., 2004. Competitive adsorption of aqueous metal ions on an oxidized nanoporous activated carbon. Langmuir 20, 4566e4578. Xiao, B., Thomas, K.M., 2005. Adsorption of aqueous metal ions on oxygen and nitrogen functionalized nanoporous activated carbons. Langmuir 21, 3892e3902.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 8 9 e1 1 9 8
Available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Molecularly imprinted polymer microspheres enhanced biodegradation of bisphenol A by acclimated activated sludge Ya-ting Xie a, Hai-bin Li b, Ling Wang a, Qian Liu a, Yun Shi a, Hai-yan Zheng c, Meng Zhang a, Ya-ting Wu a, Bin Lu a,* a
MOE Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China b Department of Public Health, Xinxiang Medical University, East Jin Sui Road, Xinxiang, Henan 453003, China c School of Pharmacy, Tongji Medical College, Huazhong University of Science and Technology, # 13Hangkong Road, Wuhan, Hubei 430030, China
article info
abstract
Article history:
The impacts of bisphenol A imprinted polymeric microspheres (MIPMs) on the biodeg-
Received 24 August 2010
radation of bisphenlol A by acclimated activated sludge were studied. Due to the selective
Received in revised form
adsorption of MIPMs to bisphenol A (BPA) and its analogues, addition of MIPMs to activated
7 November 2010
sludge increased levels of BPA and its metabolites, which were also the substrates of
Accepted 8 November 2010
biodegradation. Higher substrates (BPA and its metabolites) level promoted biodegradation
Available online 18 November 2010
efficiencies of activated sludge via accelerating removal speed of BPA and its metabolites, increasing degradation rate and decreasing half-lives of biodegradation. The enhancement
Keywords:
of MIPMs in degradation efficiencies was more significant in environmental water con-
Bisphenol A
taining low-level of pollutants, and water containing interferences such as heavy metals and humic acid. Furthermore, MIPMs were more suitable than non-selective sorbents such
Biodegradation Molecularly
imprinted
polymeric
as active carbon to be used as enhancer for BPA biodegradation. MIPMs combined with
microspheres
activated sludge are simple, effective, environmental-friendly processes to biodegrade low-
Acclimated activated sludge
level pollutants in environmental water.
Enhancement
1.
Introduction
Bisphenol A (BPA) is a widely used intermediate in the production of polycarbonate plastics and epoxy resins. As one of the most ubiquitous environmental estrogen disruptors, BPA can cause adverse health effects on ecosystems and on human being by mimicking or interfering hormonal activities to affect growth, development, and reproduction. The health impacts of BPA may be cumulative and are irreversible, endangering the sustainable development of humans (Staples et al., 1998). Even trace BPA produces adverse effects on
ª 2010 Elsevier Ltd. All rights reserved.
aquatic life. Based on the capability of BPA to increase vitellogenin levels in male rainbow trout, the predicted no-effect concentration of BPA for aquatic life was 64 mg/L (Lahnsteiner et al., 2005). However, concentrations lower than predicted no-effect concentration can cause alterations in reproduction. When male and female brown trout (Salmo trutta f. fario) were exposed to BPA during the late pre spawning and spawning period, the ovulated time of female brown trout delayed for 2 weeks (1.75 mg/L), 3 weeks (2.4 mg/L) or even did not ovulate (5 mg/L). Male brown trout produced low quality semen at the beginning and in the middle of spawning, which resulted in
* Corresponding author. Tel.: þ86 27 83691809; fax: þ86 27 83657765. E-mail addresses:
[email protected] (Y.-t. Xie),
[email protected] (H.-b. Li),
[email protected] (L. Wang),
[email protected] (Q. Liu),
[email protected] (Y. Shi),
[email protected] (H.-y. Zheng),
[email protected] (M. Zhang),
[email protected] (Y.-t. Wu),
[email protected] (B. Lu). 0043-1354/$ e see front matter ª 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2010.11.014
1190
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 8 9 e1 1 9 8
a spawning delay for 4 weeks in late spawning period (Lahnsteiner et al., 2005). Furthermore, BPA is easily accumulated through food chain. To bream (Abramis brama) and flounder (Platichthysflesus) living in surface water containing less than 0.01e0.33 mg/L BPA, the levels of BPA in liver varied from 2 to 75 mg/kg dry weight, and from 1 to 11 mg/kg dry weight in the muscle (Kang et al., 2006). A daily exposure dose of 50 mg/kg body weight/day was stated to be safe for humans by the U.S. Food and Drug Administration and the U.S. Environmental Protection Agency in the 1980s. However, several recent studies have reported significant impacts on rats at doses below the predicted safe dose. For example, a reduction in the epididymal sperm motility and sperm count were observed in rats exposed to 0.2e20 mg/kg/day BPA for 45 days (Kang et al., 2006). Nowadays, BPA can be removed by physicochemical methods (e.g. H2O2 þ UV, UV þ O3, H2O2 þ O3, TiO2 photocatalysis) (Gogate and Pandit, 2004; Torres et al., 2007), adsorption methods (Choi et al., 2005; Lin et al., 2008), and biological degradation methods (Lobos et al., 1992; Spivack et al., 1994; Suzuki et al., 2004). Physicochemical methods are not cost-effective in dealing with large volume of low-level pollutants. Sometimes secondary pollutants that are not effectively eliminated by the same technique are developed, which may be more hazardous than the original pollutant (Gogate and Pandit, 2004; Torres et al., 2007). Adsorption methods need further treatment to completely degrade the adsorbed pollutants (Choi et al., 2005; Lin et al., 2008). Biological degradation methods are practical to degrade relatively low concentration of pollutants in large amount of water. BPA-degrading bacterium, isolated from activated sludge in sewage plants or natural river water, mineralized 60% of the total carbon of BPA to CO2, assimilated 20% into bacterial cells, and converted 20% to soluble organic compounds (Lobos et al., 1992; Spivack et al., 1994; Suzuki et al., 2004). Compared with BPA, very low acute toxicity was detected among all the BPA biodegradation products, and only 4-hydroxyacetophenone (HAP) had slight estrogenic activity (Ike et al., 2002). Biological degradation methods have the prospect to eliminate BPA by degrading them into less harmful intermediates or, ultimately, carbon dioxide and water. The initial concentration of target pollutant is one major factor that will affect biodegradation efficiency. The biodegradation rates of p-chlorobenzoate and chloroacetate increased significantly when the initial concentrations increased from 47 ng/L to 47 mg/L (Boethling and Alexander, 1979). Biodegradation mainly depends on enzymes produced by microorganisms to degrade target pollutants. The target pollutants are also the substrates of the enzyme reactions. There is usually a hyperbolic relationship between the biodegradation rate and the substrate concentration in enzyme-catalyzed reaction (Leskovac, 2003). According to MichaeliseMenten kinetics, certain amount of BPA is necessary to achieve good biodegradation efficiency. Low concentration of BPA is difficult to be degraded effectively in ordinary wastewater treatment plants. For example, BPA (15e5400 mg/ L) in landfill leachates can be degraded to 0.5e5.1 mg/L (Yamada et al., 1999). But 0.08e4.98 mg/L BPA can only be degraded to 0.01e1.08 mg/L in wastewater treatment plants of Canada with removal efficiencies of 37e94%. After treatment,
0.542 and 3.01 mg/L BPA in wastewater were reduced to 0.162 and 0.258 mg/L respectively in a wastewater treatment plant in Germany. The removal efficiency was 70% and 91% respectively (Zhao et al., 2008). BPA (mean concentration 933.2 ng/L) in the influent can be reduced to 81.4 ng/L (mean concentration) in the effluents with mean removal efficacy about 90% in three sewage treatment plants of China (Zhou et al., 2010). Besides, the degradation of low concentration of BPA usually required a long incubation time and sometimes had a lag phase (Klecka et al., 2001; Ying and Kookana, 2003). For example, biodegradation half-lives for BPA were 0.5e3 days at the initial concentrations of 50e5500 mg/L, but 3e6 days at environmentally relevant concentrations (0.05e0.5 mg/L) with lag phases of 2e4 days using sediment and water collected from rivers (Klecka et al., 2001). To increase the biodegradation efficiency, methods such as membrane bioreactor and microorganism immobilization have been developed. Although membrane bioreactor could bear higher volume loadings, efficiency of membrane bioreactor to degrade BPA was only slightly higher than that of ordinary activated sludge reactor (Chen et al., 2008). This is because membrane bioreactor could only increase biomass level, not the substrate (target pollutant) concentration. Microorganism immobilization is more useful in degrading high concentration of pollutant by maintaining high level of microorganisms in carriers, which is helpful to solve normal problems of biodegradation system such as high substrate toxicity for cells and loss of large number of microorganisms (Zhao et al., 2009). BPA levels in the influent of wastewater treatment plants are usually in the range of ng/L or mg/L, which cannot be degraded effectively in modern wastewater treatment plants. Effluent of wastewater treatment plants is a major source for BPA entering surface waters. Therefore new technique that can degrade low concentration of BPA effectively is in great need. Molecularly imprinted polymer microspheres (MIPMs) are a class of smart sorbents that exhibit high affinity and selectivity. MIPMs have advantages such as physical robustness, resistance to elevated temperature and pressure, and inertness towards organic solvents, acids or bases (Tamayo et al., 2007). In our previous study, BPA-imprinted MIPMs were able to selectively remove trace phenolic estrogens (BPA and its analogues) from different sources of water. The selective binding characters of MIPMs enable them to have better removal efficiencies compared with non-selective sorbents such as active carbon (Lin et al., 2008). Therefore, we suggested that using MIPMs and activated sludge together, the selective adsorption of MIPMs would increase concentrations of substrates (also the target pollutants) effectively, which will enhance the degradation of trace target pollutants. To the best of our knowledge, no paper using MIPMs with activated sludge was reported. Therefore, the impacts of BPA-imprinted MIPMs on biodegrading BPA by acclimated activated sludge were studied in this paper. Factors such as heavy metals, humic acid (HA), different kinds of water and initial BPA concentration on the degradation efficiency were evaluated. BPA biodegradation pathway under our experimental conditions is not clear. But according to the pathway proposed by Spivack et al. (1994), HAP is one of the main metabolites. And HAP is the only major intermediate metabolite that has slight estrogenic activity among all the BPA biodegradation
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 8 9 e1 1 9 8
metabolites (Ike et al., 2002). Therefore, BPA and HAP were used as indexes to evaluate biodegradation efficiency.
2.
Materials and methods
2.1.
Materials
BPA, Bisphenol C (BPC), Bisphenol Z (BPZ), 4-vinylpyridine (4VP), HAP, trimethylolpropane trimethacrylate (TRIM) and HPLC-grade acetonitrile and methanol were provided by Sigma (St. Louis, MO). Analytical grade azobisisobutyronitrile (AIBN), dichloromethane, active carbon and other chemicals were obtained from Kemiou Company (Tianjin, China). TRIM and 4-VP were purified prior to use via general distillation methods in vacuo under nitrogen protection to remove the polymerization inhibitor. AIBN was recrystallized from methanol and then dried at room temperature in vacuum prior to use. Unless indicated, triple distilled water was used throughout. Figure S1 (supporting information) showed the molecular structures of chemicals used in this study.
2.2.
Apparatus and analytical conditions
HPLC analyses were performed on a Waters symmetry C18 column (5 mm, 250 mm 4.6 mm i.d.) using a Waters 1525 HPLC system with 2487 dual l absorbance detector operating at 281 nm (Waters, USA). The mobile phase was a mixture of water: acetonitrile (6:4). The injected sample volume was 20 mL and the flow-rate of the mobile phase was 1 mL/min. The oven temperature was set at 25 C. The calibration curves for all compounds had good linearity, with correlation coefficients higher than 0.999 over the studied concentration ranges (10e500 mg/L and 22.8e1140 mg/L, respectively). The limit of detection (LOD, a signal-to-noise ratio of 3) for BPA, BPC, BPZ, HAP was 5, 18, 38 and 9 mg/L, respectively. The limit of quantification (LOQ, a signal-to-noise ratio of 10) was 17, 60, 125 and 30 mg/L, respectively. BPZ (250 or 20 mg/L) was used as internal standard. The BPZ recovery rates in all tests were in the range of 95e105%.
2.3.
Preparation and characters of MIPMs
MIPMs were synthesized using precipitation polymerization conditions optimized in our lab (Lin et al., 2008). Briefly, the template BPA (6 mmol), monomer 4-VP (6 mmol), cross-linker TRIM (12 mmol) and free-radical initiator AIBN (40 mg) weredissolved in 250 mL acetonitrile. The solution was degassed in an ultrasonic bath for 5 min, purged with oxygen-free nitrogen for 10 min. The flask was then attached to a rotor-arm and rotated about 50 rpm at 65 C for 24 h. After centrifugation, the microspheres were extracted using methanol: acetic acid (9:1) for nine times and acetonitrile for five times to remove the template. Then microspheres were dried in vacuo overnight at 25 C. Non-imprinted microspheres (nMIPMs) were prepared under identical conditions except that the template was omitted. To detect binding capacity, BPA solutions (22.8e1140 mg/L in acetonitrile) were added to 10 mg MIPMs respectively. The samples were shaken at 25 C for 24 h. BPA concentration in
1191
the supernatant (free BPA) was analyzed by HPLC. The bound BPA was calculated by subtracting the free amount of BPA from its initial level. Scatchard plot was constructed by plotting the ratios of bound to free BPA concentration against the bound concentration. The absorption capacity (the maximum number of binding sites, Bmax) was determined from the equation, (B/[free]) ¼ (B/Kd) þ (Bmax/Kd), where Kd is the equilibrium dissociation constant, B the concentration of bound BPA, [free] the concentration of free BPA. The dissociation constant (Kd) was calculated from the Scatchard plot. To analyze binding selectivity, a range of structural analogues of BPA (2 mL BPA, BPC, BPZ and HAP solutions, 57, 64, 67 and 31.5 mg/L each in acetonitrile) were added to 10 mg MIPMs separately. The samples were shaken at 25 C for 24 h. IPB (imprinting-induced promotion of binding, IPB ¼ (Cmip Cnip)/Cnip 100% was used to demonstrate the specificity of MIPMs due to the molecular imprinted effect. Cmip was the amount of BPA or its analogues bound to MIPMs, and Cnip was the corresponding value for nMIPMs.
2.4.
Degradation test
Activated sludge was collected from the secondary sedimentation tank of wastewater treatment station of Wuhan Beer Company, China. Eight liters of sludge were mixed with 24 L of the inorganic salt solution (1 g/L NaCl, 1 g/L K2HPO4$3H2O, 0.5 g/L NH4Cl and 0.4 g/L MgSO4$7H2O) in an incubation reactor. Proper ratios of carbon, nitrogen and phosphate are necessary for acclimation efficiency. BPA was the sole carbon and energy source, while the inorganic salt solution provided nitrogen and phosphate. Considering the potential toxicity of BPA to microorganisms in the sludge, the acclimation process was conducted at room temperature by increasing BPA levels gradually from 10 to 450 mg/L for at least 8-week. When the activated sludge was acclimated completely after 8-week incubation, BPA removal efficiency was steadily above 90% and the mixed liquor suspended solid (MLSS) was in the range of 3000e3500 mg/L. L16 (43) table including three factors (shaking speed of water bath incubator, pH, temperature) and four levels were used to explore the optimal BPA-degrading conditions (Table 1). Completely acclimated activated sludge was taken from the incubation reactor and washed with triple distilled water three times to remove the residual BPA. After centrifugation (300 rpm, 10 min), 5 g condensed activated sludge was distributed into 100 mL BPA synthetic water sample (containing BPA and inorganic salt solution in distilled water with MLSS 3000e3100 mg/L) to degrade BPA under different shaking speed of water bath incubator, pH and temperature for 4 h. The initial concentration of BPA was 500 mg/L. Each experimental group was conducted in duplicate. Variable with high R value has strong effect on the degradation. Active carbons were washed first with 0.1 mol/L hydrochloric acid and then with distilled water until pH level of the washing elute was 7. Finally they were dried at 100 C for 24 h before use. BPA-imprinted MIPMs (10 mg), nMIPMs (10 mg) and active carbons (10 mg) were applied to BPA synthetic water sample containing 5 g activated sludge, respectively. Experiments were conducted at the optimal degrading conditions and carried out in duplicate. Mixture of 5 g activated sludge
1192
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 8 9 e1 1 9 8
Table 1 e Orthogonal test of acclimated activated sludge on BPA biodegradation. No.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 K1b K2 K3 K4 Rc
Factor Shaking speed of water bath incubator (r/min)
pH
Temperature
0 0 0 0 50 50 50 50 100 100 100 100 150 150 150 150 23.28 28.01 32.03 36.84 13.55
5 6 7 8 5 6 7 8 5 6 7 8 5 6 7 8 27.33 27.58 33.73 31.52 6.15
25 30 35 40 30 25 40 35 35 40 25 30 40 35 30 25 17.32 26.32 42.02 34.5 24.7
Degradated BPA (mg)a
7.32 16.13 40.28 29.41 22.44 13.48 34.8 41.31 42.18 36.44 21.33 28.19 37.36 44.3 38.53 27.16
a Degradated BPA: Qd ¼ Q0 Qe Qx,. Q0 the initial BPA level (mg), Qe and Qx were the amount of BPA (mg) in the water phase and the solid phase respectively. b Ki (i ¼ 1, 2, 3. . .)was defined as mean value of sum of degradated amount of every level and the optimal level of factor can be confirmed by comparing the value of Ki. c R value refers to the result of extreme analysis; R ¼ max {K1, K2, K3, K4}min{K1, K2, K3, K4}. Factor with high R value has strong effect on the degradation.
with BPA synthetic water samples was used as activated sludge control groups to evaluate the degradation capacity of activated sludge. BPA synthetic water samples contained 10 mg MIPMs were used as MIPMs control groups to detect BPA level that was only adsorbed by MIPMs. Because BPA leaking
from MIPMs (template bleeding) will affect the accurate determination of BPA treatment efficiency, BPA bleeding tests were preformed by mixing 10 mg MIPMs with 5 g activated sludge in distilled water for 5 days to evaluate BPA leakage during water treatment. During activated sludge treatment, the removal of BPA should be attributed to the adsorption of BPA by different adsorbents (including the sludge, active carbon or MIPMs), and the biodegradation by activated sludge. In order to calculate the degraded BPA level, the amounts of BPA in the solid phase and in the water phase must be detected separately. The amount of BPA in the solid phase was the adsorbed BPA (BPA adsorbed by sludge or different sorbents). And the amount of BPA in water phase was the BPA that was not adsorbed nor degraded. At each designed sampling time (0, 1, 2, 3, 4 h), two samples were taken out of the shaking water bath incubator and immediately centrifuged at 6000 rpm for 3 min to separate the solid phase (the sludge and the sorbent together) and the water phase. The solid phase was extracted by 20 mL methanol 5 times. The water phase was extracted by 70 mL dichloromethane 3 times. Then the methanol or dichloromethane was volatilized using a rotary evaporator (Heidolph, Germany) at 55 C. The dried residue was re-dissolved by 2 mL acetonitrile. The amount of degraded BPA was calculated as: Qd ¼ Q0 Qe Qx. The degradation rate % ¼ (Qd/Q0) 100%. Where Qd was the amount of degraded BPA (mg), Q0 the initial BPA level (mg), Qe and Qx were the amount of BPA (mg) in the water and solid phase respectively. The first-order reaction equation: lnC ¼ kt þ A, was used to describe the degradation processes. C is the substrate (BPA) concentration (mg/L), calculated as: C ¼ C0 Cd, Where C0 is the initial BPA concentration (mg/L), Cd (Cd ¼ Qd/V) is the degraded BPA concentration (mg/L) (not include the BPA absorbed by sludge or sorbent), k is the biodegradation rate constant (h1), t is the time period (h), A is a constant. The degradation half-life (t1/2) of BPA is ln2/k. AgNO3, HgCl2 or HA was added to the BPA synthetic water sample respectively to get a final concentration of 10 mg/L. Except distilled water, environment water collected from Donghu Lake and Hanjiang River (Wuhan, China) was also used to prepare the BPA synthetic water samples. Total organic carbon (TOC), chemical oxygen demand (COD), metal ions, total
Table 2 e BPA biodegradation rate constants (k) and half-lives (t1/2) of different treated groups. Interference
Sorbent Sludge þ active carbon
Sludge a
k Distilled waterd Distilled water with AgNO3d Distilled water with HgCl2d Distilled water with HAd Lake waterd River waterd River water (20 mg/L) a b c d
0.6145 0.2757 0.2536 0.6808 0.225 0.2007 0.1145
t1/2
b
1.13 2.51 2.73 1.02 3.08 3.45 6.05
k is the biodegradation rate constant(h1). t1/2 is the half-life(h). r2 is correlation coefficient. the initial BPA level is 500 mg/L.
2c
r
0.9902 0.9917 0.9961 0.9919 0.9995 0.9981 0.9911
a
b
k
t1/2
0.7549 0.2879 0.2618 0.8003 0.2657 0.2344 0.1365
0.92 2.41 2.65 0.87 2.61 2.96 5.07
2c
r
0.9987 0.9986 0.9981 0.9992 0.9982 0.9983 0.9907
Sludge þ nMIPMs a
b
k
t1/2
0.7629 0.2987 0.2732 0.8242 0.2815 0.2622 0.1503
0.91 2.32 2.54 0.84 2.46 2.64 4.61
2c
r
0.9968 0.9964 0.9983 0.9989 0.9901 0.99 0.9910
Sludge þ MIPMs ka
t1/2b
r2c
0.8391 0.3327 0.3297 0.9458 0.3361 0.2985 0.1893
0.83 2.08 2.10 0.73 2.06 2.32 3.66
0.9909 0.9974 0.9964 0.9953 0.9974 0.9992 0.9973
1193
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 8 9 e1 1 9 8
bacteria count and other parameters of lake and river water were detected according to Sanitary Standard for Drinking Water, Ministry of Health, China (2001). Then these BPA synthetic water samples (500 mg/L or 20 mg/L) were applied to degradation test under the optimal degrading conditions and were carried out in duplicate.
3.
Results and discussion
3.1.
Binding characters of MIPMs and nMIPMs
phase, no BPA was detected in MIPMs-sludge group after 2 h treatment, compared with higher than 2.83 mg BPA in other groups. And high levels of HAP remained in other groups (higher than 8.48 mg) except only 0.60 mg HAP was detected in MIPMs-sludge group after 4 h treatment. In solid phase, levels of BPA (1.93 mg) and HAP (9.31 mg) in MIPMs-sludge group were a little bit lower than those in active carbon-sludge group (2.45 and 10.03 mg respectively) after 4 h treatment (Figs. 2 and 3). Among all groups, MIPMs-sludge group had the highest degraded BPA level at each tested time (Fig. 1), the highest degradation rate constant (Table 2) and degradation rate (Table 3), but the shortest degradation half-lives (Table 2). On the other hand, non-selective sorbents active carbon and nMIPMs could adsorb fewer amounts of BPA and HAP (Figs. 2 and 3). Therefore the speed and efficiency to degrade BPA and HAP in active carbon-sludge and nMIPMs-sludge groups were also higher than activated sludge group, but lower than MIPMs-sludge group (Figs. 1e3, Tables 2 and 3). It was obvious that selective increasing levels of substrates (BPA and HAP) by MIPMs were critical to enhance BPA biodegradation.
Scanning electron micrographs of MIPMs and nMIPMs were shown in Figure S2 (supporting information). Binding isotherm and Scatchard plot of MIPMs and nMIPMs were shown in Figure S3 (supporting information). The Bmax for the MIPMs and nMIPMs used in this study were 5.33 mg/g and 0.96 mg/g respectively. IPB values were 318, 221, 214 and 183% respectively for BPA, BPC, BPZ and HAP.
3.2.
Optimal conditions for BPA degradation 3.4. Effects of heavy metals and HA on degradation efficiency
From orthogonal test (Table 1), factors that can influence the degradation were listed as: temperature > shaking speed of water bath incubator > pH value. Shaking speed 150 rpm, 35 C and pH ¼ 7 were the optimized degradation conditions. Further studies were carried out under these optimal conditions.
Heavy metals are major components that may affect water treatment efficiency. Compared with other heavy metals, Hg and Ag are the most potent antiseptics and can reduce the biomass of activated sludge significantly (Battistoni et al., 1993; Mowat, 1976). Therefore AgNO3 and HgCl2 were used as models of heavy metals in this study. Compared with distilled water, addition of AgNO3 or HgCl2 decreased degradation rate (Table 3) but increased half-lives of degradation (Table 2). More BPA but less HAP remained in water and solid phase combined with less degraded BPA (Figs. 1e3). It was obvious that heavy metals reduced the degradation capability of activated sludge, which led to less degraded BPA and less HAP although there was high level of BPA in water and solid phase (Figs. 1e3). Heavy metals could combine with biomolecules and act as potent enzyme inhibitors to hamper the activities of biodegradation enzymes and biodegradation processes (Fergusson, 1990; Passow et al., 1961; Poli et al., 2009). Heavy metals could also reduce the bacteria biomass that is respond for biodegradation. Toxicity of heavy metals on degradation bacterium and enzymes reduced
3.3. Effects of different sorbents on degradation efficiency After 5 days treatment, no BPA was detected either in the solid or water phase of BPA bleeding test groups. BPA leaking from MIPMs is not a problem for the usage of MIPMs in water treatment. In distilled water, addition of sorbents promoted biodegradation by increasing the degraded BPA level (Fig. 1) and degradation rate (Table 3) but decreasing half-lives of degradation (Table 2). MIPMs can adsorb BPA and its structural analogous HAP selectively (Figs. 2 and 3). Thus MIPMs-sludge groups had the highest level of BPA and HAP in solid phase at the 1st and 2nd h (Figs. 2b and 3b). High levels of substrates (BPA and HAP) accelerated the degradation efficiency. In water
Table 3 e BPA biodegradation rate after 4 h treatment. Degradation rate(%)a Sludge Distilled waterb Distilled water with AgNO3b Distilled water with HgCl2b Distilled water with HAb Lake waterb River waterb River water(20 mg/L)
90.38 67.74 62.67 93.97 59.63 54.65 37.00
1.05 1.44 1.06 1.18 3.13 1.37 3.96
Active carbon þ sludge 94.89 68.89 64.80 95.89 64.75 60.16 42.00
1.77 1.64 2.81 0.66 1.60 2.72 1.70
nMIPMs þ sludge 94.92 70.41 67.12 96.30 66.23 63.24 44.90
0.72 1.58 2.7 0.48 2.83 3.66 1.13
MIPMs þ sludge 96.14 74.30 74.26 97.89 73.89 69.24 53.60
0.92 2.82 1.73 0.31 1.02 2.63 3.82
a Degradation rate % ¼ (Qd/Q0) 100%. Qd was the amount of degraded BPA (mg): Qd ¼ Q0 Qe Qx. Q0 was the initial BPA amount (mg), Qe and Qx were the amount of BPA (mg) in the water phase and the solid phase respectively. b the initial BPA level is 500 mg/L.
1194
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 8 9 e1 1 9 8
Fig. 1 e Degraded BPA level in different treated groups. The initial BPA level is 500 mg/L.
the degradation capability of activated sludge, which resulted in longer degradation half-lives (Table 2) and lower degradation rate (Table 3). Although AgNO3 or HgCl2 reduced degradation capability of activated sludge, applying MIPMs to activated sludge still increased the degradation rate (Table 3), the degraded BPA level and HAP level (Figs. 1e3), but decreased half-lives of degradation (Table 2). Heavy metals increased the selective adsorption of MIPMs, but reduced the adsorption capacity of active carbon (Figs. 2b and 3b). It was reported that the exchange of protons between the functional groups of the sorbents and cations (Ag2þ or Hg2þ in this case) removed the hydrogen bond donor groups necessary for selective retention. This effect was more significant to non-selective absorption than in selective retention (Hu et al., 2007). Thus, heavy metals reduced the adsorption capacity of active carbon and nMIPMs but did not affect the adsorption capacity of MIPMs (Figs. 2b and 3b). Selective adsorption of MIPMs led to the highest BPA and HAP levels from the 1st to the 3rd h in solid phase of MIPMs-sludge group. High levels of substrates (BPA and HAP) accelerated the degradation efficiency of remaining alive microorganisms to increase biodegradation efficiency and degradation speed at some extent. Therefore, BPA was almost completely removed in water phase of MIPMs-sludge groups (0.17 or 0.5 mg in the existence of AgNO3 or HgCl2 respectively), compared with higher than 3.45 or 4.08 mg respectively in other groups after 4 h treatment. While HAP levels in water phase of MIPMs-sludge groups were 6.99 and 9.68 mg respectively, lower than those in other groups (higher than 10.98 and 11.97 mg respectively). And levels of BPA (lower than 12.68 mg) and HAP (lower than 9.48 mg) in solid phase were similar to those in active carbon groups (lower than 11.74 mg or 8.72 mg, respectively) at the 4th h (Figs. 2 and 3). The differences on degradation rate (Table 3) and degradation half-lives (Table 2) among MIPMs-sludge and other groups were more significant in water containing heavy metals than in distilled water. These data indicated that the
capability of MIPMs to promote degradation efficiencies was more significantly in water containing HgCl2 or AgNO3 than in distilled water. Furthermore, MIPMs were better than active carbon to enhance biodegradation efficiencies in water containing heavy metals. HA is another factor that may affect the biodegradation efficiency. The level of HA in environmental water is about 1e10 mg/L (Li and Lee, 2001). HA was reported to increase, inhibit, or have no effect on the biodegradation of polycyclic aromatic hydrocarbons and aromatic pollutants (Burgos et al., 2000; Amador and Alexander, 1988; Holman et al., 2002; Larsson et al., 1988). In this study, water containing HA had higher degradation rate constants (Table 2) and degradation rate (Table 3), but shorter degradation half-lives (Table 2). HA increased the efficiency and speed of activated sludge to eliminate BPA and HAP. These may because the strong positive correlation between bacterial biomass and the concentration of HA (Hessen, 1985; Tranvik and Ho¨fle, 1987). Higher HA level will increase bacterial biomass, which is helpful to increase degradation capability. In water containing HA, addition of MIPMs still enhanced degradation efficiency by increasing degradation rate constant (Table 2) and degradation rate (Table 3) but reduced degradation half-lives (Table 2). Detail analysis showed that HA increased the selective adsorption of MIPMs, but reduced the adsorption capacity of active carbon (Figs. 2b and 3b). Similar results were also observed in our previous study (Lin et al., 2008). HA increased the selective adsorption of MIPMs because functional monomer 4-VP did not have an effective molecular interaction with HA. But HA can be easily adsorbed by relatively hydrophobic stationary phase such as active carbon to interfere the adsorption of target pollutants (Kubo et al., 2003; Lin et al., 2008). MIPMs enriched much higher BPA (14.88 mg) and HAP (19.64 mg) level in solid phase at the 1st h than those in other groups (less than 7.91 and 10.96 mg, respectively) (Figs. 2b and 3b). High levels of substrates (BPA and HAP) led to rapid and effective reduction of BPA and HAP in
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 8 9 e1 1 9 8
1195
Fig. 2 e BPA level in different treated groups. (a) water phase (b) solid phase. The initial BPA level is 500 mg/L.
MIPMs-sludge group. No BPA or HAP was detected in water phase at the 2nd or the 4th h respectively in MIPMs-sludge group, compared with higher than 4.56 mg BPA or 2.97 mg HAP in other groups (Figs. 2a and 3a). After 4 h treatment, BPA and HAP in solid phase were 1.06 and 9.22 mg in MIPMs-sludge group, lower than those of active carbon group (1.56 and 12.37 mg respectively) (Figs. 2b and 3b). The enhancement of MIPMs in degradation efficiencies was more significant than that of active carbon in water containing high level of HA (Figs. 1e3, Tables 2 and 3).
3.5. Effects of different kinds of water on degradation efficiency Environmental lake and river water were applied to degradation tests to evaluate the practical usage of MIPMs. The physiochemical characters of Hanjiang River and Donghu Lake water used in this study were listed in Table S1 (supporting
information). When lake or river water instead of distilled water was used, the degradation rate constants (Table 2) and degradation rates (Table 3) decreased but degradation halflives increased (Table 2). The degradation capability of activated sludge was inhibited by river or lake water as the degraded BPA level decreased (Fig. 1) although adsorbed BPA level did not reduce compared with distilled water (Figs. 2b and 3b). This inhibition could be attributed to the contaminants in lake and river water. Factors such as COD level, heavy metals and bacterium in the river and lake water (Table S1, supporting information) can affect the degradation capability of activated sludge. In distilled water, microorganisms in the activated sludge utilized BPA as the only carbon source. Water with certain COD level contains other organic substrates, which can be more easily degraded by activated sludge than BPA. Therefore BPA degradation was slowed down in water with higher initial COD level (Urase and Kikuta, 2005; Zhao et al., 2008). Heavy metals (Table S1, supporting information) in lake and
1196
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 8 9 e1 1 9 8
Fig. 3 e HAP level in different treated groups. (a) water phase (b) solid phase. The initial BPA level is 500 mg/L.
river water also reduced biodegradation capability of activated sludge (Figs. 1e3, Tables 2 and 3). Some bacterium (such as pseudomonas fluorescens) could produce bacterio-toxins to inhibit or kill other bacterium (Lewis, 1929; Terpstra, 1947), which would reduce the biodegradability of activated sludge. Contaminants in lake and river water decreased the biodegradation capability of activated sludge. Application of MIPMs to river and lake water increased degradation rate constants (Table 2) and degradation rates (Table 3), thereby decreased half-lives of degradation (Table 2). Compared with distilled water, MIPMs had much higher adsorption capabilities than those of active carbon in river and lake water (Figs. 2b and 3b). These were because MIPMs could resist the interference of pollutants that normally reduce the adsorption efficiency of active carbon in environmental water (Lin et al., 2008). Higher substrates level is optimal to increase degradation efficiencies of alive microorganisms in the activated sludge. After 4 h treatment, BPA was completely
removed from water phase (either lake or river water) of MIPMssludge groups, compared with higher than 3.72 mg BPA in other groups (Fig. 2a). And HAP levels (less than 6.63 mg) in water phase of MIPMs-sludge groups were the lowest among all the groups (higher than 7.64 mg) (Fig. 3a). In solid phase, BPA (lower than 15.38 mg) and HAP (lower than 9.32 mg) in MIPMs-sludge groups were almost similar to those of other groups (lower than 14.67 mg and 8.07 mg respectively) at the 4th h (Figs. 2b and 3b). The differences on degraded BPA level (Fig. 1), degradation rate (Table 3) and degradation half-lives (Table 2) among MIPMssludge and other groups were more significant in lake or river water than in distilled water. MIPMs were more suitable than active carbon to be mixed with activated sludge to increase BPA biodegradation efficiencies in complicated environmental water. Because only trace BPA was existed in environmental water, river water containing low concentration of BPA (20 mg/ L, 500 mL) was also applied to biodegradation test. Compared
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 8 9 e1 1 9 8
1197
Fig. 4 e Biodegradation of river water containing 20 mg/L initial BPA level (a) Degraded BPA level. (b) BPA level (c) HAP level.
with river water containing 500 mg/L BPA, lower degradation rate (Table 3) and degraded BPA level (Fig. 4), but higher degradation half-lives (Table 2) were observed in water containing 20 mg/L BPA. Low initiated BPA concentration means low substrate level, which decreased degradation efficiencies significantly. Although low initiated BPA level reduced degradation capability, addition of adsorbs to 20 mg/L BPA groups increased degradation efficiencies. MIPMs enriched trace BPA and HAP effectively because both BPA and HAP levels in solid phase during the 1st and 2nd h were the highest in MIPMs-sludge groups. Higher substrate (BPA and HAP) levels promoted the degradation. After 4 h treatment, MIPMs-sludge group had the lowest BPA and HAP level in water phase (Fig. 4b and c). And lower BAP or HAP levels in solid phase than those in active carbon-sludge group (Fig. 4b and c) were observed. MIPMssludge group had the highest degraded BPA level (Fig. 4a) and degradation rate (Table 3) but the shortest degradation halflives (Table 2). The differences on degraded BPA level, degradation rate and degradation half-lives among MIPMs-sludge and other groups were more significant in 20 mg/L groups than in 500 mg/L groups (Fig. 4, Tables 2 and 3). The enhancement of MIPMs in degradation efficiencies was more significant in water containing lower BPA level. Selective increasing substrates levels were very important to enhance degradation efficiencies in environmental water containing trace pollutants. Furthermore, the degradation rates in MIPMs-sludge and active carbon-sludge groups were 53.6% and 42% respectively in 20 mg/L BPA groups, compared with 69.24% and 60.16% respectively in 500 mg/L BPA groups (Table 3). And the degradation half-lives of MIPMs-sludge and active carbon-sludge groups were 3.66 h and 5.07 h respectively in 20 mg/L BPA groups, but 2.32 h and 2.96 h respectively in 500 mg/L BPA samples (Table 2). Compared with active carbon, MIPMs is much more suitable to be used with activated sludge to degrade trace pollutants in complex environmental water.
4.
Conclusions
In this study, BPA-imprinted MIPMs were mixed with activated sludge to evaluate the potential impacts of MIPMs on biodegradation. Our results proved that the application of MIPMs enhanced biodegradation efficiency of activated sludge effectively via increasing levels of substrates (BPA and its metabolites) selectively. This enhancement was more significant in environmental water containing trace pollutants, and in water containing different interferences such as heavy metals and HA. MIPMs were more suitable than active carbon to be used as enhancer for BPA biodegradation. Combined usage of MIPMs and activated sludge provides a reliable and practical solution to degrade trace environmental pollutants in environmental water effectively.
Acknowledgements This work was supported by the National Natural Science Foundation of China (Grant No. 30972435, 30771775, 20728708 and 30771776) and NCET Program by the Chinese Ministry of Education (No. NCET-06-0640).
Appendix. Supplementary data Supplementary data associated with the article can be found in online version, at doi:10.1016/j.watres.2010.11.014.
references
Amador, J.A., Alexander, M., 1988. Effect of humic acids on the mineralization of low concentrations of organic compounds. Soil Biology and Biochemistry 20 (2), 185e191.
1198
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 8 9 e1 1 9 8
Battistoni, P., Fava, G., Ruello, L.M., 1993. Heavy metal shock load in activated sludge uptake and toxic effects. Water Research 27 (5), 821e827. Boethling, R.S., Alexander, M., 1979. Effect of concentration of organic chemicals on their biodegradation by natural microbial communities. Applied and Environmental Microbiology 37 (6), 1211e1216. Burgos, W.D., Pisutpaisal, N., Tuntoolavest, M., Chorover, J., Unz, R. F., 2000. Biodegradation of 1-naphthol in the presence of humic acid. Environmental Engineering Science 17 (6), 343e351. Chen, J., Huang, X., Lee, D., 2008. Bisphenol A removal by a membrane bioreactor. Process Biochemistry 43 (4), 451e456. Choi, K.J., Kim, S.G., Kim, C.W., Kim, S.H., 2005. Effects of activated carbon types and service life on removal of endocrine disrupting chemicals: amitrol, nonylphenol, and bisphenol-A. Chemosphere 58 (11), 1535e1545. Fergusson, J.E., 1990. The Heavy Elements: Chemistry, Environmental Impact and Health Effect. Oxford Pergamon Press, Oxford, U.K. Gogate, P.R., Pandit, A.B., 2004. A review of imperative technologies for wastewater treatment II: hybrid methods. Advances in Environmental Research 8 (3e4), 553e597. Hessen, D.O., 1985. The relation between bacterial carbon and dissolved humic compounds in oligotrophic lakes. FEMS Microbiology Letters 31 (4), 215e223. Holman, H.N., Nieman, K., Sorensen, D.L., Miller, C.D., Matin, M.C., Borch, T., Mckinney, W.R., Sims, R.C., 2002. Catalysis of PAH biodegradation by humic acid shown in synchrotron infrared studies. Environmental Science & Technology 36 (6), 1276e1280. Hu, M., Jiang, M., Wang, P., Mei, S., Lin, Y., Hu, X., Shi, Y., Lu, B., 2007. Selective solid-phase extraction of tebuconazole in biological and environmental samples using molecularly imprinted polymers. Analytical and Bioanalytical Chemistry 387 (3), 1007e1016. Ike, M., Chen, M., Jin, C., Fujita, M., 2002. Acute toxicity, mutagenicity, and estrogenicity of biodegradation products of bisphenol A. Environmental Toxicology 17 (5), 457e461. Kang, J., Kondo, F., Katayama, Y., 2006. Human exposure to bisphenol A. Toxicology 226 (2e3), 79e89. Klecka, G.M., Gonsior, S.J., West, R.J., Goodwin, P.A., Markham, D. A., 2001. Biodegradation of bisphenol A in aquatic environments: river die-away. Environmental Toxicology and Chemistry 20 (12), 2725e2735. Kubo, T., Hosoya, K., Watabe, T., Ikegami, N., Tanaka, T., Kaya, K., 2003. On-column concentration of bisphenol A with on-step removal of humic acids in water. Journal of Chromatography A 987 (1e2), 389e394. Lahnsteiner, F., Berger, B., Kletzl, M., Weismann, T., 2005. Effect of bisphonl A on maturation and quality of semen and eggs in the brown trout, Salmo trutta f.fario. Aquatic Toxicology 75 (3), 213e224. Larsson, P., Okla, L., Tranvik, L., 1988. Microbial degradation of xenobiotic, aromatic pollutants in humic water. Applied and Environmental Microbiology 54 (7), 1864e1867. Leskovac, V., 2003. Comprehensive Enzyme Kinetics. Kluwer Academic/Plenum Publishers, New York. Lewis, M.I., 1929. Bacterial antagonism with special reference to the effect of Pseudomonas fluorescens on spore forming bacteria of soils. Journal of Bacteriology 17 (2), 89e103. Lin, Y., Shi, Y., Jiang, M., Peng, Y., Dai, K., Lu, B., 2008. Removal of phenolic estrogen pollutants from different sources of water using molecularly imprinted polymeric microspheres. Environmental Pollution 153 (2), 483e491. Li, N., Lee, H.K., 2001. Solid-phase extraction of polycyclic aromatic hydrocarbons in surface water negative effect of humic acid. Journal of Chromatography A 921 (2), 255e263.
Lobos, J.H., Leib, T.K., Su, T., 1992. Biodegradation of bisphenol A and other bisphenols by a gram-negative aerobic bacterium. Applied and Environmental Microbiology 58 (6), 1823e1831. Mowat, A., 1976. Measurement of metal toxicity by biochemical oxygen demand. Journal of Water Pollution Control Federation 48 (5), 853e859. Passow, H., Rothstein, A., Clarkson, T.W., 1961. The general pharmacology of the heavy metals. Pharmacological Reviews 13 (2), 185e224. Poli, A., Salerno, A., Laezza, G., Donato, P., Dumontet, S., Nicolaus, B., 2009. Heavy metal resistance of some thermophiles: potential use of a-amylase from Anoxybacillus amylolyticus as a microbial enzymatic bioassay. Research in Microbiology 160 (2), 99e106. Spivack, J., Leib, T.K., Lobos, J.H., 1994. Novel pathway for bacterial metabolism of bisphenol A. The Journal of Biological Chemistry 269 (10), 7323e7329. Staples, C.A., Dorn, P.B., Klecka, G.M., O’Block, S.T., Hariis, L.R., 1998. A review of the environmental fate, effects, and exposures of bisphenol A. Chemosphere 36 (10), 2149e2173. Suzuki, T., Nakagawa, Y., Takano, I., Yaguchi, K., Yasuda, K., 2004. Environmental fate of bisphenol A and its biological metabolites in river water and their xeno-estrogenic activity. Environmental Science & Technology 38 (8), 2389e2396. Tamayo, F.G., Turiel, E., Martı´n-Esteban, A., 2007. Molecularly imprinted polymers for solid-phase extraction and solidphase microextraction: recent developments and future trends. Journal of Chromatography A 1152 (1e2), 32e40. Terpstra, I.J., 1947. A peculiar example of bacterial antagonism. Antonie Van Leeuwenhoek 13 (1), 44e54. Torres, R.A., Petrier, C., Combet, E., Moulet, F., Pulgarin, C., 2007. Bisphenol A mineralization by integrated ultrasound-UV-iron (II) treatment. Environmental Science & Technology 41 (1), 297e302. Tranvik, L.J., Ho¨fle, M.G., 1987. Bacterial growth in mixed cultures on dissolved organic carbon from humic and clear waters. Applied and Environmental Microbiology 53 (3), 482e488. Urase, T., Kikuta, T., 2005. Separate estimation of adsorption and degradation of pharmaceutical substances and estrogens in the activated sludge process. Water Research 39 (7), 1289e1300. Yamada, K., Urase, T., Matsuo, T., Suzuki, N., 1999. Constituents of organic pollutions in leachates from different types of landfill sites and their fate in the treatment processes. Journal of Japan Society on Water Environment 22 (1), 40e45. Ying, G., Kookana, R.S., 2003. Degradation of five selected endocrine-disrupting chemicals in seawater and marine sediment. Environmental Science & Technology 37 (7), 1256e1260. Zhao, G., Zhou, L., Li, Y., Liu, X., Ren, X., Liu, X., 2009. Enhancement of phenol degradation using immobilized microorganisms and organic modified montmorillonite in a two-phase partitioning bioreactor. Journal of Hazardous Materials 169 (1e3), 402e410. Zhao, J., Li, Y., Zhang, C., Zeng, Q., Zhou, Q., 2008. Sorption and degradation of bisphenol A by aerobic activated sludge. Journal of Hazardous Materials 155 (1e2), 305e311. Zhou, H., Huang, X., Wang, X., Zhi, X., Yang, C., Wen, X., Wang, Q., Tsuno, H., Tanaka, H., 2010. Behaviour of selected endocrinedisrupting chemicals in three sewage treatment plants of Beijing, China. Environmental Monitoring and Assessment 161 (1e4), 107e121.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 1 9 9 e1 2 1 2
Available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Indicator compounds for assessment of wastewater effluent contributions to flow and water quality Eric R.V. Dickenson a, Shane A. Snyder b, David L. Sedlak c, Jo¨rg E. Drewes a,* a
Advanced Water Technology Center (AQWATEC), Environmental Science and Engineering Division, Colorado School of Mines, Golden, CO 80401, USA b Applied Research and Development Center (ARDC), Water Quality Research and Development Division, Southern Nevada Water Authority, Henderson, NV 89015, USA c Department of Civil and Environmental Engineering, University of California at Berkeley, Berkeley, CA 94720, USA
article info
abstract
Article history:
Numerous studies have reported the presence of trace (i.e., ng/L) organic chemicals in
Received 6 March 2010
municipal wastewater effluents, but it is unclear which compounds will be useful to
Received in revised form
evaluate the contribution of effluent to overall river flow or the attenuation processes that
30 October 2010
occur in receiving streams. This paper presents a new approach that uses a suite of
Accepted 9 November 2010
common trace organic chemicals as indicators to assess the degree of impact and atten-
Available online 16 November 2010
uation of trace organic chemicals in receiving streams. The utility of the approach was validated by effluent monitoring at ten wastewater treatment plants and two effluent-
Keywords:
impacted rivers with short retention times (50% are shown (500 replicates). The scale bar represents 5% estimated sequence divergence.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 1 3 e1 2 2 8
specialised metabolism restricted to the oxidation of methane or methanol. Similar sequences were retrieved from a permafrost soil in Siberia (Liebner et al., 2009; EU124843) and an Arctic wetland soil (Wartiainen et al., 2006; AJ414655). Surprisingly, a few clones from Vidy sediments were related to phototrophic purple sulphur bacteria (Chromatiaceae) despite the fact that there is not much light to be expected at 30 m depth. However, some species can also grow under chemotrophic conditions in the dark, either autotrophically or heterotrophically using oxygen as terminal electron acceptor. Sequences similar to ours were retrieved from an anaerobic digestor (Riviere et al., 2009) and the sediment surface of Fayetteville Green Lake, USA (FJ437977). Several groups of Gammaproteobacteria clones remained unclassified but with similar sequences found in bacterioplankton communities of Lake Michigan (Mueller-Spitz et al., 2009. EU640647), river sediments (Li et al., 2008. EF590053), mangroves (EF125457) and agricultural soils (FJ444695). A large number of sequences affiliated with the division Bacteroidetes (CytophagaeFlexibactereBacteroidetes) were found in both sites, particularly in Vidy sediments. Bacteroidetes constitute the second largest group in Vidy sediments after the Betaproteobacteria, and the third largest group in Ouchy sediments (Fig. 4). Bacteroidetes phylotypes were diverse and their closest relatives were sequences found in freshwater lakes (Mueller-Spitz et al., 2009), anthropogenically impacted sediments, tundra soils (Liebner et al., 2008) and aquifers. Most of the sequences found in the 2 investigated sites remained unclassified. One clone found in Vidy sediments was affiliated to the genus Cytophaga sp. and one clone from Ouchy was related to the genus Flavobacterium sp. A large proportion of the Euryarchaeota phylotypes, mostly retrieved from Vidy sediments, were related to methanogens like Methanosaeta sp. (Methanosaetaceae) and Methanomicrobiales (Fig. 9). A few species of Methanosaeta sp. have been isolated from anaerobic sewage digestors or sewage sludge (Zinder et al., 1984; Huser et al., 1982). Similar sequences to the clones found in this study, were retrieved from anaerobic sludge and a meromictic lake (Lehours et al., 2007). The rest of the archaeal sequences were only distantly related to any cultured species but similar to sequences retrieved from lake sediments (Pouliot et al., 2009; AY531743, EU782007), Arctic peat (AM712495) and the anoxic zone of a hydropower plant reservoir in the Brazilian Amazon (GU127420 and GU127500). The two investigated sites differ clearly in terms of sediment chemical parameters and degree of pollution. It was therefore expected that the bacterial community composition would be different and reflect the differences in environmental conditions. Fig. 4 and Figs. 6e9 clearly show the diverse bacterial and archaeal lineages detected in the two sites. The results of the genetic diversity tests confirm the significant genetic differentiation of the sediment bacterial communities between the two sites at all depths. Seven and twelve divisions were identified in the sediments from Vidy and Ouchy, respectively. Among them Nitropsira, Planctomycetes, Verrucomicrobia and Gemmatimonadetes were only detected in Ouchy sediments. The apparent lower bacterial diversity in Vidy sediments may be explained by the high levels of a broad range of pollutants, which may induce adverse biological effects on microbial communities. The bacterial community
1225
composition changed with depth in the uncontaminated sediment. Conversely, no statistically significant variations were observed for the two sediment layers (0e2 and 4e6 cm) in the Bay of Vidy, which is explained by the high sedimentation rates and the non-consolidated nature of the sediment, permitting mobilisation and vertical mixing. The microbial composition of both sites was correlated with the environmental variables, as shown by the Mantel correlation test (r ¼ 0.9429, p ¼ 0.044). This result suggests that the diversity of microbial communities may be affected by nutrients, organic matter as well as the degree of pollution. Many environmental variables are implicated, which is a situation inherent to all field studies. The Bay of Vidy is contaminated by all kinds of contaminants but also with high quantities of organic matter and nutrients. Under these conditions it is difficult to separate out the influence of the different environmental variables on microbial diversity and community composition. To learn more about the relative importance of individual environmental factors, microcosm studies will be required. The integrative picture of the relationship between bacterial community structures and environmental factors at the two sites (Fig. 10) indicated that the sampling sites Ouchy and Vidy were clearly different with respect to both. Previous results already showed that the bacterial diversity in comparable contaminated and uncontaminated environments may differ significantly. The difference may be explained by the nature of pollution and a wide diversity of organic carbon
Fig. 10 e The Multiple factor analysis (MFA) is a PCA-based technique allowing the simultaneous ordination of a composite table obtained by the juxtaposition of the species and the two environmental datasets, after weighting the different matrices The superimposed representation shows one global point for each site, Vidy and Ouchy, at each depth (“A” stands for the 0e2 cm sediment section and “B” for the 4e6 cm sediment section). The three associated partial points correspond to the three datasets (microbial composition, organic matter and nutrients and heavy metals). The values on the axes indicate the percentage of total variation.
1226
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 1 3 e1 2 2 8
sources (Sandaa et al., 1999; Sorci et al., 1999; Zhang et al., 2008). The polluted environment of Vidy Bay may have selected, among the dispersed microbes in sediments, certain functional bacterial groups which adapted to these conditions and became more dominant in that particular environment.
5.
Conclusion
This is the first study reporting on the microbial community structures of Bacteria and Archaea in contaminated and uncontaminated sediments of Lake Geneva. Results show that the sediments of the two sites differed clearly in their organic matter and nutrient contents. Intense mineralisation of organic matter under sulphate-reducing and methanogenic conditions was indicated for the sediments from Vidy Bay. Furthermore, results confirm data of previous studies showing that the area around the WWTP outlet pipe in the Vidy Bay is heavily contaminated with various organic and inorganic pollutants. Phylogenetic analysis of sedimentary prokaryotes revealed that (i) archaeal and bacterial communities differed significantly between the contaminated and the noncontaminated sediments. (ii) For both sites, a correlation was observed between the microbial community structure and environmental variables suggesting that microbial diversity may be affected by nutrients, organic matter content and by the degree of pollution. (iii) Betaproteobacteria was the dominant bacterial group, representing more than 30% of the clones from surface sediments at both sites. (iv) A large proportion of Betaproteobacteria clones, mostly from Vidy sediments, were related to the reductively dechlorinating Dechloromonas sp. (iv) Consistent with geochemical data, Deltaproteobacteria including clones related to iron- (Geobacter sp.) and sulphatereducing bacteria, were relatively more abundant in the contaminated sediments. (v) The archaeal communities were dominated by methanogenic Euryarchaeota, particularly in the organic matter-rich Vidy Bay sediments. This study suggests that each site harbours a specific sediment microbial community. The apparent lower bacterial diversity in Vidy sediments may be explained by the significant concentrations of contaminants, which may induce adverse biological effects on benthic metazoa and microbes. However, given the long history of pollution in the bay, specific bacterial and archaeal communities may well have adapted to these particular conditions. Hence, more research on microbial community composition and specific activities of microorganisms inhabiting similar environments should be performed, in order to improve the understanding how pollution and eutrophication may affect microbial communities.
Acknowledgements We thank Nadia Ruggeri-Bernardi (Cantonal Institute of Microbiology, Bellinzona, Switzerland) for assisting with the molecular analysis, Dr. Pierre Rossi and Noam Shani (EPFL-IIELBE, Switzerland) and Dr. Mathias Currat (University of Geneva, Switzerland) for helping with the statistical analyses. Philippe Arpagaus (Institute FA Forel) is acknowledged for
navigating R/V “La Licorne” and the Municipality of Lausanne for financial support.
references
APHA, 1985. Standard Methods for the Examination of Water and Wastewater. American Public Health Association, Washington. 408e410. Becue-Bertaut, M., Pages, J., 2008. Multiple factor analysis and clustering of a mixture of quantitative, categorical and frequency data. Computational Statistics & Data Analysis 52, 3255e3268. Brosius, J., Dull, T.J., Sleeter, D.D., Noller, H.F., 1981. Gene organization and primary structure of ribosomal RNA operon from Escherichia coli. Journal of Molecular Biology 148, 107e127. Burrus, D., Thomas, R.L., Dominik, B., Vernet, J.P., Dominik, J., 1990. Characteristics of suspended sediment in the Upper Rhone River, Switzerland, including the particulate forms of phosphorus. Hydrological Processes 4, 85e98. Canfield, D.E., Thamdrup, B., 2009. Towards a consistent classification scheme for geochemical environments, or, why we wish the term “suboxic” would go away. Geobiology 7, 385e392. Cline, J.D., 1969. Spectrophotometric determination of hydrogen sulfide in natural waters. Limnology & Oceanography 14, 454e458. Coates, J.D., Chakraborty, R., Lack, J.G., O’Connor, S.M., Cole, K.A., Bender, K.S., Achenbach, L.A., 2001. Anaerobic benzene oxidation coupled to nitrate reduction in pure culture by two strains of Dechloromonas. Nature 411, 1039e1043. Coates, J.D., Ellis, D.J., Blunt-Harris, E.L., Roden, E., Gaw, C., Lovley, D.R., 1998. Recovery and identification of humicreducing bacteria from a diversity of environments. Applied and Environmental Microbiology 64, 1504e1509. Conseil Canadien des Ministres de l’Environnement, 1999. Introduction, dans Recommandations canadiennes pour la qualite´ de l’environnement. Winnipeg, le Conseil. Corvi, C., Majeux, C., Vogel, J., 1986. Les polychlorobiphe´nyles et le DDE dans les se´diments superficiels du Le´man et de ses affluents. Rapport de la Commission Internationale pour la protection des eaux du Le´man contre pollution. Campagne 1985, 205e216. Dorioz, J.M., Pelletier, J.P., Benoit, P., 1998. Physico-chemical properties and bioavailability of particulate phosphorus of various origins in a watershed of Lake Geneva (France). Water Research 32, 275e286. Eggleton, J., Thomas, K.V., 2004. A review of factors affecting the release and bioavailability of contaminants during sediment disturbance events. Environment International 30, 973e980. Escofier, B., Pages, J., 1994. Multiple factor-analysis (Afmult Package). Computational Statistics & Data Analysis 18, 121e140. Fo¨rstner, U., Wittmann, G.T.W., 1979. Metal Pollution in the Aquatic Environment. SpringereVerlag, Berlin, 486 pp. Fossing, H., Jørgensen, B.B., 1989. Measurement of bacterial sulphate reduction in sediments: evaluation of a single-step chromium reduction method. Biogeochemistry 8, 205e222. Gillan, C.D., Danis, B., Pernet, P., Joly, G., Dubois, P., 2005. Structure of sediment-associated microbial communities along a heavy-metal contamination gradient in the marine environment. Applied and Environmental Microbiology 71, 679e690. Glo¨ckner, F.O., Zaichikov, E., Belkova, N., Denissova, L., Pernthaler, J., Pernthaler, A., Amann, R., 2000. Comparative 16S rRNA analysis of lakebacterioplankton reveals globally distributed phylogenetic clusters including an abundant group
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 1 3 e1 2 2 8
of Actinobacteria. Applied and Environmental Microbiology 66, 5053e5065. Grobkopf, R., Janssen, P.H., Liesack, W., 1998. Diversity and structure of the methanogenic community in anoxic rice paddy soil microcosms as examined by cultivation and direct 16S rRNA gene sequence retrieval. Applied and Environmental Microbiology 64, 960e969. Hahn, M.W., 2006. The microbial diversity of inland waters. Current Opinion in Biotechnology 17, 256e261. Hall, G.E.M., Pelchat, P., 1997. Evaluation of a direct solid sampling atomic absorption spectrometer for the trace determination of mercury in geological samples. The Analyst 122, 921e924. Haller, L., Pote´, J., Loizeau, J.-L., Wildi, W., 2009. Distribution and survival of faecal indicator bacteria in the sediments of the Bay of Vidy, Lake Geneva, Switzerland. Ecological Indicators 9, 540e547. Hiorns, W.D., Methe´, B.A., Nierzwicki-Bauer, S.A., Zehr, J.P., 1997. Bacterial diversity in Adirondack mountain lakes as revealed by 16S rRNA Gene sequences. Applied and Environmental Microbiology 63, 2957e2960. Huser, B.A., Wuhrmann, K., Zehnder, A.J.B., 1982. Methanothrix soehngenii gen. nov. sp. nov., a new acetotrophic nonhydrogen-oxidizing methane bacterium. Archive of Microbiology 132, 1e9. Jenkins, O., Byrom, D., Jones, D., 1987. Methylophilus: a new genus of methanol-utilizing bacteria. International Journal of Systematic and Evolution Microbiology 37, 446e448. Karr, E.A., Sattley, W.M., Rice, M.R., Jung, D.O., Madigan, M.T., Achenbach, L.A., 2005. Diversity and distribution of sulphatereducing bacteria in permanently frozen Lake Fryxell, McMurdo Dry Valleys, Antarctica. Applied and Environmental Microbiology 71, 6353e6359. Koelmans, A.A., Van der Heijde, A., Knijff, L.M., Alderink, R.H., 2001. Integrated modelling of eutrophication and organic contaminant fate & effects in aquatic ecosystems. A review. Water Research 15, 3517e3536. Kumar, S., Tamura, K., Nei, M., 2004. MEGA3: integrated software for Molecular Evolutionary Genetics Analysis and sequence alignment. Brief Bioinform 5, 150e163. Lane, D.J., 1991. 16S/23S rRNA sequencing. In: Stackebrandt, E., Goodfellow, M. (Eds.), Nucleic Acid Techniques in Bacterial Systematics. John Wiley & Sons, Inc., New York, pp. 115e175. Lehours, A.C., Evans, P., Bardot, C., Joblin, K., Fonty, G., 2007. Phylogenetic diversity of archaea and bacteria in the anoxic zone of a meromictic lake (Lake Pavin, France). Applied and Environmental Microbiology 73, 2016e2019. Li, D., Yang, M., Li, Z., Qi, R., He, J., Liu, H., 2008. Change of bacterial communities in sediments along Songhua River in Northeastern China after a nitrobenzene pollution event. FEMS Microbiology Ecology 65, 494e503. Liebner, S., Harder, J., Wagner, D., 2008. Bacterial diversity and community structure in polygonal tundra soils from Samoylov Island, Lena Delta, Siberia. International Microbiology 11, 195e202. Liebner, S., Rublack, K., Stuehrmann, T., Wagner, D., 2009. Diversity of aerobic methanotrophic bacteria in a permafrost active layer soil of the Lena Delta, Siberia. Microbial Ecology 57, 25e35. Loizeau, J.-L., Arbouillle, D., Santiago, S., Vernet, J.-P., 1994. Evaluation of a wide range laser diffraction grain size analyser for use with sediments. Sedimentology 41, 353e361. Loizeau, J.-L., Pardos, M., Monna, F., Peytremann, C., Haller, L., Dominik, J., 2004. The impact of a sewage treatment plant’s effluent on sediment quality in a small bay in Lake Geneva (Switzerland-France). Part 2: Temporal evolution of heavy metals. Lakes & Reservoirs: Research and Management 9, 53e63.
1227
Lors, C., Tiffreau, C., Laboudigue, A., 2004. Effects of bacterial activities on the release of heavy metals from contaminated dredged sediments. Chemosphere 56, 619e630. Maidak, B.L., Olsen, G.J., Larsen, N., Overbeek, R., McCaughey, M.J., Woese, C.R., 1999. A new version of the RDP (Ribosomal Database Project). Nucleic Acids Research 27, 171e173. Mantel, N., 1967. The detection of disease clustering and a generalized regression approach. Cancer Research 27, 209e220. Martin, A.P., 2002. Phylogenetic approaches for describing and comparing the diversity of microbial communities. Applied and Environmental Microbiology 68, 3673e3682. Mueller-Spitz, S.R., Goetz, G.W., McLellan, S.L., 2009. Temporal and spatial variability in nearshore bacterioplankton communities of Lake Michigan. FEMS Microbiology Ecology 67, 511e522. Nealson, K.H., 1997. Sediment bacteria: who’s there, what are they doing, and what’s new? Articles in Annual Review of Earth and Planetary Sciences 25, 403e434. Nevin, K.P., Holmes, D.E., Woodard, T.L., Hinlein, E.S., Ostendorf, D.W., Lovley, D.R., 2005. Geobacter bemidjiensis sp. nov. and Geobacter psychrophilus sp. nov., two novel Fe(III)reducing subsurface isolates. International Journal of Systematic and Evolutionary Microbiology 55, 1667e1674. Pardos, M., Benninghoff, C., de Alencastro, L.P., Wildi, W., 2004. The impact of a sewage treatment plant’s effluent on sediment quality in a small bay in Lake Geneva (SwitzerlandFrance). Part 1: spatial distribution of contaminants and the potential for biological impacts. Lakes & Reservoirs: Research and Management 9, 41e52. Pote´, J., Haller, L., Loizeau, J.-L., Garcia Bravo, A., Sastre, V., Wildi, W., 2008. Effects of a sewage treatment plant outlet pipe extension on the distribution of contaminants in the sediments of the Bay of Vidy, Lake Geneva, Switzerland. Bioresource Technology 99, 7122e7131. Pouliot, J., Galand, P.E., Lovejoy, C., Vincent, W.F., 2009. Vertical structure of archaeal communities and the distribution of ammonia monooxygenase A gene variants in two meromictic High Arctic lakes. Environmental Microbiology 11, 687e699. Powell, S.M., Bowman, J.P., Snape, I., Stark, J.S., 2003. Microbial community variation in pristine and polluted nearshore Antartic sediments. FEMS Microbiology Ecology 45, 135e145. Pronk, M., Goldscheider, N., Zopfi, J., 2009. Microbial communities in karst groundwater and their potential use for biomonitoring. Hydrogeology Journal 17, 37e48. R Development Core Team, 2005. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, ISBN 3-900051-07-0. http://www. R-project.org. Riviere, D., Desvignes, V., Pelletier, E., Chaussonnerie, S., Guermazi, S., Weissenbach, J., Li, T., Camacho, P., Sghir, A., 2009. Towards the definition of a core of microorganisms involved in anaerobic digestion of sludge. ISME Journal 3, 700e714. Ross-Barraclough, F., Givelet, N., Martinez-Cortizas, A., Goodsite, M.E., Biester, H., Shotyk, W., 2002. An analytical protocol for the determination of total mercury concentrations in solid peat samples. Science of Total Environment 292, 129e139. Salomons, W., Fo¨rstner, U., 1984. Metals in the Hydrocycle. SpringereVerlag, Berlin, 349 pp. Sandaa, R.A., Torsvik, V., Enger, O., Daae, F.L., Castberg, T., Hahn, D., 1999. Analysis of bacterial communities in heavy metal-contaminated soils at different levels of resolution. FEMS Microbiology Ecology 30, 237e251. Schloss, P.D., Westcott, S.L., Ryabin, T., Hall, J.R., Hartmann, M., Hollister, E.B., Lesniewski, R.A., Oakley, B.B., Parks, D.H., Robinson, C.J., Sahl, J.W., Stres, B., Thallinger, G.G., Van
1228
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 1 3 e1 2 2 8
Horn, D.J., Weber, C.F., 2009. Introducing mothur: opensource, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology 75, 7537e7541. Schneider, S., Roessli, D., Excoffier, L., 2000. Arlequin Ver 2.0: A Software for Population Genetic Data Analysis. Genetics and Biometry Lab, University of Geneva, Geneva. Schwarzenbach, R.P., Escher, B.I., Fenner, K., Hofstetter, T.B., Johnson, C.A., von Gunten, U., Wehrli, B., 2006. The challenge of micropollutants in aquatic systems. Science 313, 1072e1077. Sorci, J.J., Paulauskis, J.D., Ford, T.E., 1999. 16 rRNA Restriction fragment length polymorphism analysis of bacterial diversity as a biomarker of ecological health in polluted sediments from New Bedford Harbor, Massachusetts, USA. Marine Pollution Bulletin 38, 663e675. Stahl, D.A., Amann, R.I., 1991. Development and application of nucleic acid probes. In: Stackebrandt, E., Goodfellow, M. (Eds.), Nucleic Acid Techniques in Bacterial Systematics. John Wiley & Sons, Inc., New York, pp. 205e248. Tanaka, K., Nakamura, K., Mikami, E., 2003. Fermentation of maleate by a gram-negative strictly anaerobic non-sporeformer, Propionivibrio dicarboxylicus gen.nov., sp.nov. Archive of Microbiology 154, 323e328. Thamdrup, B., Fossing, H., Jørgensen, B.B., 1994. Manganese, iron and sulfur cycling in a coastal marine sediment, Aarhus Bay, Denmark. Geochimica et Cosmochimica Acta 58, 5115e5129. Verweij, F., Booij, K., Satumalay, K., Molen, N., Oost, R., 2004. Assessment of bioavailable PAH, PCB and OCP concentrations in water, using semipermeable membrane devices (SPMDs), sediments and caged carp. Chemosphere 54, 1675e1689. Wang, Q.G., Garrity, G.M., Tiedje, J.M., Cole, J.R., 2007. Naı¨ve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied Environmental Microbiology 73, 5261e5267. Wang, Q., Kim, D., Dionysiou, D.D., Sorial, G.A., Timberlake, D., 2004. Sources and remediation for mercury contamination in aquatic systemsda literature review. Environmental Pollution 131, 323e336.
Wartiainen, I., Hestnes, A.G., McDonald, I.R., Svenning, M.M., 2006. Methylobacter tundripaludum sp. nov., a methaneoxidizing bacterium from Arctic wetland soil on the Svalbard islands, Norway (78 degrees N). International Journal of Systematic and Evolutionary Microbiology 56, 109e113. Wildi, W., Dominik, J., Loizeau, J.-L., Thomas, R.L., Favarger, P.-Y., Haller, L., Perroud, A., Peytremann, C., 2004. River, reservoir and lake sediment contamination by heavy metals downstream from urban areas of Switzerland. Lakes & Reservoirs: Research and Management 9, 75e87. Williams, J.D.H., Jaquet, J.M., Thomas, R.L., 1976. Forms of phosphorus in the superficial sediments of Lake Erie. Journal of the Fisheries Research Board of Canada 33, 413e429. Wolterink, A., Kim, S., Muusse, M., Kim, I.S., Roholl, P.J.M., van Ginkel, C.G., Stams, A.J.M., Kengen, S.W.M., 2005. Dechloromonas hortensis sp. nov. and strain ASK-1, two novel (per)chlorate-reducing bacteria, and taxonomic description of strain GR-1. International Journal of Systematic and Evolutionary Microbiology 55, 2063e2068. Ye, W., Liu, X., Lin, S., Tan, J., Pan, J., Li, D., Yang, H., 2009. The vertical distribution of bacterial and archaeal communities in the water and sediment of LakeTaihu. FEMS Microbiology Ecology 70, 263e276. Zhang, W., Ki, J.S., Qian, P.Y., 2008. Microbial diversity in polluted harbor sediments I: bacterial community assessment based on four clone libraries of 16S rDNA. Estuarine. Coastal and Shelf Science 76, 668e681. Zinder, S.H., Cardwell, S.C., Anguish, T., Lee, M., Koch, M., 1984. Methanogenesis in a thermophilic (58 C) anaerobic digestor: Methanothrix sp. as an important aceticlastic methanogen. Applied Environmental Microbiology 47, 796e807. Zopfi, J., Bo¨ttcher, M.E., Jørgensen, B.B., 2008. Biogeochemistry of sulfur and iron in Thioploca-colonized surface sediments in the upwelling area off central Chile. Geochimica et Cosmochimica Acta 72, 827e843. Zwart, G., Crump, B.C., Kamst-van Agterveld, M.P., Hagen, F., Han, S.-K., 2002. Typical freshwater bacteria: an analysis of available 16S rRNA gene sequences from plankton of lakes and rivers. Aquatic Microbial Ecology 28, 141e155.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 2 9 e1 2 3 7
Available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Evaluation and improvement of total organic bromine analysis with respect to reductive property of activated carbon Yao Li a, Xiangru Zhang a,*, Chii Shang a, Stuart W. Krasner b a
Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR, China b Metropolitan Water District of Southern California, 700 Moreno Ave., La Verne, CA 91750, USA
article info
abstract
Article history:
A collective parameter and a toxicity indicator for all the halogenated organic disinfection
Received 4 July 2010
byproducts in a water sample is total organic halogen (TOX), which can be differentiated as
Received in revised form
total organic chlorine (TOCl), total organic bromine (TOBr) and total organic iodine. The
22 September 2010
TOX method involves concentration of organic halogens from water by adsorption onto
Accepted 28 September 2010
activated carbon (AC). A previous study showed that a portion of TOCl can be reduced to
Available online 7 October 2010
chloride during the adsorption procedure, which can be minimized by ozonation of the AC. In this study, a portion of TOBr was sometimes found to be reduced by AC to bromide, and
Keywords:
the reduction was generally less than that of corresponding TOCl. The results suggested
Disinfection byproducts
that around 10% of brominated Suwannee River fulvic acid was reduced to bromide.
Total organic halogen
However, some brominated amino compounds (especially glycylglycine, phenylalanine,
Total organic bromine
and cytosine) were found to be more reactive with the AC. For the iodinated compounds
Drinking water
studied, the reduction to iodide was not significant. The method for the TOBr measurement
Activated carbon
was improved by using ozonated AC when reduction occurred on the original AC. The improved method was also evaluated on treated wastewater and swimming pool water samples. ª 2010 Elsevier Ltd. All rights reserved.
1.
Introduction
When bromide is present in water (e.g., due to saltwater intrusion, connate water, oil field brines), hypobromous acid will be rapidly formed with the addition of chlorine or other disinfectants. Hypobromous acid undergoes reactions with organic matter in the water to form organic disinfection byproducts (DBPs) that contain bromine (Cowman and Singer, 1996; Richardson, 1998; Richardson et al., 2003; Xie, 2004). Kinetic studies have shown that the reaction of organic matter with hypobromous acid is much faster than that with hypochlorous acid (Westerhoff et al., 2003; Acero et al., 2005; Echigo and Minear, 2006; Hua et al., 2006). Research has shown that
brominated DBPs generally are dozens to hundreds times more toxic than their chlorinated analogues (Plewa and Wagner, 2009). For instances, bacterial studies have shown that bromoacetic acid is 201.3 times more mutagenic in Salmonella typhimurium strain TA100 than chloroacetic acid; mammalian cell studies have shown that bromoacetic acid is 89.8 times more cytotoxic in Chinese hamster ovary cells than chloroacetic acid; bromoacetic acid is 23.6 times more genotoxic in Chinese hamster ovary cells than chloroacetic acid (Plewa et al., 2004). With the presence of iodide in water, iodinated DBPs can also be formed during disinfection (Bichsel and von Gunten, 1999). Iodinated DBPs might be several times more toxic than their brominated analogues (Plewa et al.,
* Corresponding author. Tel.: þ86 852 2358 8479; fax: þ86 852 2358 1534. E-mail address:
[email protected] (X. Zhang). 0043-1354/$ e see front matter ª 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2010.09.038
1230
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 2 9 e1 2 3 7
2004), but they are typically formed at lower concentrations (Krasner et al., 2006). Even though brominated (and iodinated) DBP species are being increasingly discovered, numerous of them remain unknown (Krasner et al., 2006; Ding and Zhang, 2009). A collective parameter to give an estimation of all forms of organic-bound halogenated DBPs (Jekel and Roberts, 1980) is total organic halogen (TOX). As “a master parameter” and “a toxicity indicator” for halogenated organic DBPs, TOX has been studied and applied in more than 800 journal papers (Singer and Chang, 1989; Li et al., 2002, 2010 and references therein). An improvement in TOX measurement will surely benefit researchers and practitioners in the more accurate study/control of halogenated organic DBPs in drinking waters, wastewaters, swimming pool waters, etc. The components of TOX include total organic chlorine (TOCl), total organic bromine (TOBr) and total organic iodine (TOI). TOX, TOCl, TOBr, and TOI can be measured with the adsorptionepyrolysis method based on Standard Method 5320B (APHA et al., 1995; Hua and Reckhow, 2006). The first two steps of this method involve enrichment of organic halogens from water by adsorption onto activated carbon (AC), and elimination of inorganic halides present on the AC by competitive displacement by nitrate ions. Because AC can also act as a reductant, if some halogenated DBPs are reduced to inorganic halides when in contact with AC, they will be removed from the AC during the rinse step with nitrate, leading to an underestimation of the amount of TOX present. In a previous study, a portion of TOCl has been found to be reduced during the adsorption procedure, where w20% of chlorinated Suwannee River fulvic acid (SRFA) was reduced to chloride by AC (Li et al., 2010). For the same concentrations, brominated (and iodinated) DBPs are thought to have significantly higher adverse health effects than their chlorinated analogues (Plewa and Wagner, 2009), so there is a critical need to evaluate and improve the accuracy of the TOBr (and TOI) measurement. In the current research, the reduction of TOBr by AC during the TOX measurement was evaluated, and the extent to which this reduction affects the measurement of TOBr was explored with various types of organics. Also, according to the previous study, AC that was slightly oxidized by ozone can fully or partially inhibit the reductive property of the AC. Thus, whether ozonated AC can also inhibit the reduction of TOBr but still maintain its adsorption capacity was investigated. In addition, the reductions of some iodine- and chlorine-containing DBPs (i.e., TOI and TOCl) by AC were evaluated and compared following a similar procedure.
2.
Materials and methods
2.1.
Preparation of halogenated samples
All solutions used in this study were prepared with ultrapure water (18.2 MU/cm) supplied by a NANOpure system (Barnstead). A chlorine stock solution (5000e5500 mg/L as Cl2) was prepared by absorption of ultra high-purity chlorine gas with a 1.0 M NaOH solution. By following the method outlined by Pinkernell et al. (2000), a bromine stock solution (13 mg/L as
Br2) was prepared from a 0.20 mM solution of potassium bromide by addition of 0.25 mM of an ozone solution at pH 4 (10 mM phosphate buffer). The bromine solution was standardized by Standard Method 4500F (APHA et al., 1995). After the pH was adjusted to 11 by sodium hydroxide, the bromine solution was stable for several days when stored at 4 C. The preparation of an iodine stock solution followed a similar procedure. The bromine and iodine stock solutions were adjusted to pH 6.5 before use. Compared to the commercial ones, the bromine and iodine stock solutions generated in such a method minimized the levels of inorganic halides in them by over 50%. SRFA from the International Humic Substances Society was dissolved into ultrapure water to prepare a SRFA stock solution. One brominated SRFA sample was prepared. The initial concentrations of SRFA and bromine were 3 mg/L as C and 2 mg/L as Br2, respectively. Bromide is naturally present in many source waters across the world, with the highest natural level of w2 mg/L present in Israel’s source water (Richardson et al., 2003). The high concentration of bromine (from oxidation of bromide during chlorination) was used to magnify the possible reactions and products. The pH of the sample was w6.8. After a reaction time of 5 d at ambient temperature (20 C), the sample was measured for bromine residual with the DPD ferrous titrimetric method (APHA et al., 1995). After 5 d, no residual bromine was left in the brominated SRFA sample. In addition, one chlorinated SRFA sample with/without ultrafiltration was prepared based on a previous study (Li et al., 2010). The initial concentrations of SRFA and chlorine were 3 mg/L as C and 5 mg/L as Cl2, respectively, which were used to simulate the typical concentrations in drinking water treatment. The reaction lasted for 5 d at ambient temperature. After 5 d, no residual chlorine was left in the chlorinated SRFA sample. Ultrafiltration was used to flush out most of the inorganic ions in the chlorinated SRFA sample. The objective of this step was to remove chloride ions remaining after chlorination, so that when chlorinated DBPs was degraded on the AC to release chloride, the amount released could be seen over the background level. Detailed information on the ultrafiltration can be found in a previous study (Li et al., 2010). For the iodinated SRFA sample preparation, the initial concentrations of SRFA and iodine were 3 mg/L as C and 1.27 mg/L as I2, respectively. In natural waters, iodide is found at concentrations of 0.5e212 mg/L (Moran et al., 2002), whereas the higher concentration of iodine was used to magnify the possible reactions and products. The reaction also lasted for 5 d at ambient temperature and no residual iodine was left after 5 d. In other research, inorganic chloramines have been reported to be reduced by AC to chloride (Bauer and Snoeyink, 1973). It has been demonstrated that chlorination of some amino compounds forms organic chloramines, which are one type of DBPs in TOCl that could be reduced by AC (Li et al., 2010). Therefore, eight amino compounds were used as model compounds, including glycine, glycylglycine, cytosine, leucine, methylamine, adenine, phenylalanine, and tryptophan. For the preparation of brominated model compounds, 1 mM of each amino compound was dissolved in a 12.5 mM bromine solution (2 mg/L as Br2). The pH of the mixture was around 7.2.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 2 9 e1 2 3 7
After a reaction time of 2 h at ambient temperature, the samples were measured for bromine residuals, and no bromine residuals were left. Chlorinated and iodinated amino compounds were prepared with a similar procedure. Briefly, 1 mM of each amino compound was dissolved in a 0.1 mM chlorine solution (7.1 mg/L as Cl2) or a 5 mM iodine solution (1.27 mg/L as I2). After a reaction time of 2 h at ambient temperature, no chlorine or iodine residuals were left. Three real water samples were also evaluated, including two wastewater samples from Hong Kong (one from a primary effluent and the other from a secondary effluent), and one swimming pool water sample (from a Hong Kong indoor swimming pool with a water temperature of w24.5 C). The characteristics and chlorination of the three water samples are shown in the Supplementary Information. These chlorinated water samples were expected to contain different levels of organic chloramines/bromamines and thus exhibit different TOCl/TOBr concentrations when measured with original and ozonated AC columns.
2.2.
Measurement of TOCl, TOBr, TOI, Cl, Br, and I
TOCl, TOBr, and TOI were determined using an AC adsorption and pyrolysis method with off-line ion chromatography as a halide detector (Hua and Reckhow, 2006). Sample preparation and AC adsorption followed Standard Method 5320B (APHA et al., 1995). Pre-packed AC columns were obtained from Mitsubishi Corporation. Halogenated samples were adjusted to pH 2 with nitric acid and then passed through two consecutive AC columns in a 3-channel adsorption module (TXA03C, Mitsubishi). After that, the AC columns were washed with 5 mL of 5000 mg/L as NO 3 of potassium nitrate (with a flow rate of 3 mL/min) to remove inorganic halides and were subsequently subjected to pyrolysis at 1000 C with an AQF-100 automatic quick furnace (Mitsubishi). The hydrogen halide and halogen gases from the pyrolysis unit were trapped by 5 mL of 0.003% hydrogen peroxide absorbent (freshly made daily), which contained 2 mg/L of phosphate serving as an internal standard to estimate the volume variations induced by the GA-100 gas absorption unit (Mitsubishi). An ICS-3000 ion chromatography system (Dionex, Sunnyvale, CA) equipped with an IonPac analytical column (AS19, 4 250 mm) and a guard column (AG19, 4 50 mm) was used. The eluent was generated by an EGC potassium hydroxide cartridge at a flow rate of 1 mL/min. Chloride and Br ions were determined with an isocratic eluent of 10 mM KOH from 0 to 10 min followed by a linear gradient eluent of 10e45 mM KOH from 10 to 25 min. Iodide was determined with an isocratic eluent of 10 mM KOH from 0 to 10 min followed by a linear gradient eluent of 10e58 mM KOH from 10 to 40 min. The concentrations of the halides were quantified with a conductivity detector. The practical quantitation limits for TOCl, TOBr, and TOI in a 40mL sample were 0.002 mg/L as Cl, 0.002 mg/L as Br, and 0.009 mg/L as I, respectively. The concentrations of Cl, Br, and I in a sample were measured with the same ion chromatograph under the same instrument settings. The practical quantitation limits for Cl, Br, and I were 0.010, 0.010, and 0.050 mg/L, respectively. The relative standard deviations (RSDs) for the Cl measurement in 7 aliquots of a standard NaCl solution (0.010 mg/L as Cl in
1231
ultrapure water) and a chlorinated SRFA sample were 0.05% and 0.60%, respectively. The RSDs for the Br measurement in 7 aliquots of a standard NaBr solution (0.010 mg/L as Br in ultrapure water) and a brominated SRFA sample were 0.10% and 0.75%, respectively. The RSDs for the I measurement in 7 aliquots of a standard KI solution (0.050 mg/L as I in ultrapure water) and an iodinated SRFA sample were 0.05% and 0.55%, respectively. Unless otherwise specified, triplicates of a sample were analyzed for TOCl, TOBr, TOI, Cl, Br, and I.
2.3.
Reactions of halogenated samples with AC
Two 20-mL aliquots of a brominated DBP sample were collected in two vials. One aliquot was used as a control, and the other aliquot was allowed to react with AC. The AC was purchased from Mitsubishi (coconut-based with particle sizes of 100e200 mesh and a very low halide background of 0.4 mg Cl/40 mg AC), and was the same as the one packed in the AC columns for TOX analyses. The aliquot was spiked with 40 mg of the AC and was adjusted to pH 2 immediately (to simulate the TOX measurement procedure). After a contact time of 5 min, the aliquot was filtered with a syringe coupled with a 0.45 mm Durapore PVDF membrane filter (Millipore Corporation). The filtrate was collected and adjusted back to pH 7 for determination of the Br concentration. As the nitrate peak overlapped with the Br peak in the ion chromatograph, a chloride solution was used to substitute for the nitrate wash. The syringe filter was rinsed three times (to rinse out all the Br in the AC and the syringe filter), each time with 10 mL of 6008 mg/L of a chloride solution, which was used to simulate 5000 mg/L of a nitrate solution, and the Br concentration in each filtrate (10 mL) was measured. Finally, the total Br concentration in the aliquot after contact with the AC was calculated by combining the Br concentrations in all the filtrates. It was designated as the one with a contact time of “5 min” with the AC. For the aliquot used for a control, it was treated in the same way, except that no AC was used, and thus was designated as the one with a contact time of “0 min” with the AC. Since the AC might contain some rinsable Br ions, another control was conducted as follows: 20 mL of ultrapure water was spiked with 40 mg of the AC. After a contact time of 5 min, the sample was filtered with a syringe coupled with a 0.45 mm Durapore PVDF membrane filter, followed by rinsing the syringe filter with 10 3 mL of a 6008 mg/L chloride solution. The chloride solution was found not to contain any measurable Br ions. The Br concentrations in all the filtrates were measured and combined. The total Br concentration would be deducted from the Br concentration in the aliquot with a contact time of 5 min with the AC. The iodinated and (ultrafiltered) chlorinated DBP samples were treated with the similar procedures, except that the 5000 mg/L nitrate solution was used to rinse the syringe filter.
2.4.
Treatment of AC
The results in a previous study showed that AC treated with ozone minimized the reduction of a portion of the TOCl to Cl (Li et al., 2010). In this study, ozone gas from an ozone generator (10K-2U, Enaly) was absorbed in ultrapure water to
1232
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 2 9 e1 2 3 7
3.
Results and discussion
3.1.
Reactions of brominated SRFA with AC
Fig. 2 shows the Br concentrations in the brominated SRFA sample before and after reaction with the AC. The Br concentration in the brominated SRFA sample was 1.70 mg/L and the measured TOBr concentration was 0.28 mg/L as Br. After reaction with the AC, the Br concentration in the brominated SRFA sample increased to 1.73 mg/L. Such an increase was not significant ( p > 0.05) as shown in Supplementary Information Table S1. The net Br increment in the 5-min contact was 0.03 mg/L, which means that 0.03 mg/L of TOBr may have been reduced to Br in 5 min. Considering that the measured TOBr concentration in brominated SRFA sample was 0.28 mg/L as Br, the measurement error for the brominated SRFA sample with the standard method may be estimated as 0.03/(0.28 þ 0.03) ¼ 9.8%. As a comparison, the ultrafiltered chlorinated SRFA sample was also used to react with the AC (Fig. 2). After a contact time of 5 min, the Cl concentration in the ultrafiltered sample increased from 0.18 to 0.31 mg/L, indicating a significant
2.0 0 min
Cl− or Br− conc. (mg/L)
prepare a w15 mg/L ozone stock solution, which was diluted immediately to prepare ozone solutions ranging from 0.25 to 10 mg/L. Ten mL of each diluted ozone solution was passed through an AC column immediately at a flow rate of 2 mL/min. It was found that 10 mL of a 2.4 mg/L ozone solution was the optimal ozone dose for treating the AC (Fig. 1). Accordingly, to prepare an ozonated AC column, 10 mL of a 2.4 mg/L ozone solution was passed through an AC column immediately at a flow rate of 2 mL/min. The ozonated AC column was kept in a fume hood for over 24 h until used for TOX analysis. The TOCl, TOBr and TOI recoveries with the ozonated and original AC columns were tested with monochloroacetic acid, monobromoacetic acid and monoiodoacetic acid, which have been used to test the recoveries by Hua and Reckhow (2006).
5 min
1.6 1.2 0.8
0.4
5 min 0 min
0.0
Cl− conc. in chlorinated SRFA + AC
Br− conc. in brominated SRFA + AC
Fig. 2 e ClL and BrL concentrations in the brominated SRFA and the ultrafiltered chlorinated SRFA samples after a contact time of 0 or 5 min with AC.
increase ( p < 0.05). The net Cl increment in 5 min was 0.13 mg/L. The measured TOCl concentration in the ultrafiltered sample was 0.42 mg/L as Cl, thus the measurement error for the ultrafiltered sample with the standard method can be estimated as 0.13/(0.42 þ 0.13) ¼ 23.6%. The results show that the chlorinated SRFA can be reduced by AC, whereas it seems as if the TOBr reduction, at least for the brominated SRFA, occurred in a less extent. It needs pointing out that, to observe the Cl increment from the reduction of chlorinated SRFA by the AC, the use of the “ultrafiltered” chlorinated SRFA sample to react with the AC was a choice with no alternative because of the high Cl concentration in the original sample. As shown later in Section 3.3, the TOCl concentrations in the “original” chlorinated SRFA sample measured with AC and ozonated AC were 0.484 and 0.600 mg/ L as Cl, respectively. The net TOCl increment corresponded an improvement of 19.3%, which further confirms that the reduction of the TOBr in the brominated SRFA occurred in a less extent than that of the TOCl in the chlorinated SRFA. Finally, the reduction of the TOI in the iodinated SRFA sample by the AC was barely detectable.
TOCl or TOBr conc. (mg/L as Cl or Br)
0.40 TOCl TOBr
3.2.
0.30
0.20
0.10 0
2
4 6 O3 concentration (mg/L)
8
10
Fig. 1 e TOCl and TOBr levels in a chlorinated SRFA sample measured with AC columns that were treated with different ozone doses (10 mL). The chlorinated SRFA sample was prepared as follows: SRFA 3 mg/L as C, BrL 0.4 mg/L, alkalinity 90 mg/L as CaCO3, chlorine dose 5 mg/L as Cl2, and chlorine contact time 5 d (with no free chlorine residual at end of 5 d).
Reactions of brominated amino compounds with AC
The concentrations of the brominated amino compounds measured as TOBr are shown in Table 1. As a comparison, the concentrations of chlorinated and iodinated amino compounds measured as TOCl and TOI, respectively, are also shown in this table. For brominated cytosine, TOBr was detected at a significant level (0.772 mg/L as Br), whereas the TOBr concentrations of the other brominated amino compounds were below 0.10 mg/L as Br. Considering that the brominated amino compounds were prepared using a bromine solution of 2 mg/L as Br2, cytosine had a 38.6% bromine utilization, whereas the other amino compounds had 0.05), the net increment was 0.015 mg/L as I, and the improvement was only 8.8%. The TOCl and TOBr concentrations in chlorinated and brominated SRFA samples were also compared in Fig. 4b. The concentrations of TOCl measured with the original and ozonated AC columns were 0.484 0.044 mg/L and 0.600 0.024 mg/L as Cl, respectively (a significant increase, p < 0.05). The net improvement was 19.3%. The concentrations of TOBr measured with the original and ozonated AC columns were 0.278 0.007 and 0.300 0.015 mg/L as Br, respectively (a significant increase, p < 0.05). The net improvement was 7.3%. The results showed a similar impact of the AC column on the TOX reduction: TOI < TOBr < TOCl. The reduction of TOCl, TOBr, and TOI by the AC was likely associated with organic haloamines, which may inherit certain oxidation power from the precursor halogens (whose oxidation potentials are in the order of HOI < HOBr < HOCl). To confirm the reduction inhibition with the ozonated AC, the bromide concentrations of the brominated amino compound and SRFA samples were tested before and after these samples reacted with the original and ozonated ACs. Fig. 5a shows the Br concentrations in different brominated amino compound samples before and after reactions with the ACs. After a contact time of 5 min, the Br concentration in the brominated glycine sample with the original AC increased from 2.35 to 2.41 mg/L (not a significant increase, p > 0.05), whereas in the sample with the ozonated AC it was 2.38 mg/L. Alternatively, the Br concentration in the brominated glycylglycine sample with the original AC increased from 2.32 to 2.44 mg/L (a significant increase, p < 0.05), whereas in the sample with the ozonated AC it was less (2.38 mg/L). The Br decrement between the original and ozonated ACs was 0.06 mg/L, which was close to the corresponding TOBr increment (0.05 mg/L as Br, Fig. 4a). Similar results were obtained with brominated leucine and phenylalanine samples. As shown in Fig. 5b, the Br concentration in the brominated SRFA sample with the original AC increased from 1.68 mg/L to 1.74 mg/L (not a significant increase, p > 0.05), whereas in the sample with the ozonated AC (1.69 mg/L) it was close to the initial Br concentration. Alternatively, the Cl concentration in the ultrafiltered chlorinated SRFA sample
1235
with the original AC increased from 0.320 to 0.427 mg/L (a significant increase, p < 0.05), whereas in the sample with the ozonated AC (0.350 mg/L) it was close to the initial Cl concentration. Similar results were obtained with the chlorinated and brominated cytosine samples. The results demonstrated that the ozonated AC inhibited the reduction of TOCl and TOBr. However, the impact on TOBr was much less than that on TOCl. This may have been due (in part) to there being (in general) much less reduction of TOBr than TOCl on the original AC.
3.4. Measurement of TOCl and TOBr concentrations with ozonated AC for chlorinated wastewater effluents and swimming pool water samples Two chlorinated wastewater effluent samples and one chlorinated swimming pool water sample were used as alternative organic matter sources to evaluate the TOX adsorption and reduction inhibition by the ozonated AC. After treatment, TOCl and TOBr concentrations in all water samples were measured with the original and ozonated AC columns. As shown in Fig. 6, the TOCl concentrations were 0.268 0.030 and 0.346 0.033 mg/L as Cl respectively in the primary effluent (a significant increase, p < 0.05), and 0.176 0.007 and 0.204 0.018 mg/L as Cl respectively in the secondary effluent
Fig. 5 e (a) BrL concentrations in the brominated amino compound samples after a contact time of 0 or 5 min with the original and ozonated ACs. (b) ClL and BrL concentrations in the chlorinated SRFA, brominated SRFA, chlorinated cytosine, and brominated cytosine samples after a contact time of 0 or 5 min with the original and ozonated ACs.
1236
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 2 9 e1 2 3 7
TOCl or TOBr conc. (mg/L as Cl or Br)
1.2 1.0 0.8
4. AC ozonated AC
0.6 0.4 0.2 0.0 TOCl TOBr TOCl TOBr TOCl TOBr chlorinated primary chlorinated secondary chlorinated swimming pool water wastewater effluent wastewater effluent
Fig. 6 e TOCl and TOBr concentrations in the chlorinated wastewater primary effluent, chlorinated wastewater secondary effluent, and chlorinated swimming pool water samples measured with the original and ozonated ACs.
(a significant increase, p < 0.05). The net increments in TOCl concentrations were 0.078 and 0.028 mg/L as Cl, respectively. The error bars slightly overlapped for the TOCl measurements for the secondary effluent. The TOBr concentrations were 0.142 0.011 and 0.195 0.015 mg/L as Br respectively in the primary effluent (a significant increase, p < 0.05), and 0.447 0.035 and 0.487 0.020 mg/L as Br respectively in the secondary effluent (not a significant increase, p > 0.05). The net increments in TOBr concentrations were 0.053 and 0.040 mg/L as Br, respectively. The error bars partially overlapped for the TOBr measurements for the secondary effluent. The results showed that the TOCl and TOBr concentrations measured with the ozonated AC increased significantly, especially for the chlorinated primary effluent sample. Because the ammonia concentration in the primary effluent was much higher than that in the secondary effluent, the N/Br ratio was much higher in the primary effluent. Galal-Gorchev and Morris (1965) demonstrated that the formation of inorganic bromamine species was impacted by the N/Br ratio. This and differences in the organic matter makeup (e.g., organic nitrogen content) of the two wastewater effluents may have also impacted organic haloamine formation. Certain organic haloamines are considered to be important compounds reduced by AC. As shown in Fig. 6, the TOCl concentrations in the bromidespiked swimming pool water sample were 0.966 0.019 and 1.002 0.022 mg/L as Cl, respectively (a significant increase, p < 0.05), and the TOBr concentrations were 0.089 0.008 and 0.091 0.004 mg/L as Br, respectively (not a significant increase, p > 0.05). The net increments were 0.036 mg/L as Cl and 0.002 mg/L as Br. However, the error bars partially overlapped for both TOCl and TOBr. Compared with the primary wastewater effluent sample, the increments for TOCl and TOBr were relatively small. The difference in results may have been due (in part) to the low concentrations of the ammonia and organic nitrogen content in the swimming pool water sample, where breakpoint chlorination should have been achieved. The results again suggest the importance of organic haloamines to the TOX reduction by AC.
Conclusions
The results showed that brominated DBPs may be reduced by the AC used in the TOX standard method, but the reduction was lower than that of the chlorinated DBPs. Around 10% of the TOBr in the brominated SRFA sample was reduced by the AC, which was less than what was observed with the chlorinated SRFA (around 20%). The reduction of the TOI in the iodinated SRFA by the AC was negligible. A similar trend was observed for some halogenated amino compounds, i.e., the impact of the AC on the TOX reduction was in the order of TOI < TOBr < TOCl. The reductions in TOBr by the AC were significant in the brominated glycylglycine, phenylalanine, and cytosine samples, leading to the measurement errors with the standard method up to 68.0%, 56.2% and 13.5%, respectively. TOBr measurements may be improved by using the ozonated AC, which can minimize the reduction of the brominated DBPs during the adsorption procedure in cases where it occurred. The TOCl and TOBr concentrations in the chlorinated primary wastewater effluent were improved dramatically when measured with the ozonated AC columns. The results suggest the importance of organic haloamines to the TOX reduction by the AC.
Acknowledgments The work was supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. HKUST622808).
Appendix. Supplementary information Supplementary information associated with this article can be found, in the online version, at doi:10.1016/j.watres.2010.09. 038.
references
Acero, J.L., Piriou, P., von Gunten, U., 2005. Kinetics and mechanisms of formation of bromophenols during drinking water chlorination: assessment of taste and odor development. Water Res. 39, 2979e2993. APHA, AWWA, WEF, 1995. Standard Methods for the Examination of Water and Wastewater, nineteenth ed. Washington, DC. Bauer, R.C., Snoeyink, V.L., 1973. Reactions of chloramines with active carbon. J. Water Pollut. Control Fed. 45, 2290e2301. Bichsel, Y., von Gunten, U., 1999. Oxidation of iodide and hypoiodous acid in the disinfection of natural waters. Environ. Sci. Technol. 33, 4040e4045. Cowman, G.A., Singer, P.C., 1996. Effect of bromide ion on haloacetic acid speciation resulting from chlorination and chloramination of aquatic humic substances. Environ. Sci. Technol. 30, 16e24. Ding, G., Zhang, X., 2009. A picture of polar iodinated disinfection byproducts in drinking water by (UPLC/)ESI-tqMS. Environ. Sci. Technol. 43, 9287e9293.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 2 9 e1 2 3 7
Echigo, S., Minear, R.A., 2006. Kinetics of the reaction of hypobromous acid and organic matters in water treatment processes. Water Sci. Technol. 56, 235e243. Galal-Gorchev, H., Morris, J.C., 1965. Formation and stability of bromamide, bromimide, and nitrogen tribromide in aqueous solution. Inorg. Chem. 4, 899e905. Hua, G., Reckhow, D.A., 2006. Determination of TOCl, TOBr, and TOI in drinking water by pyrolysis and off-line ion chromatography. Anal. Bioanal. Chem. 384 (2), 495e504. Hua, G., Reckhow, D.A., Kim, J., 2006. Effect of bromide and iodide ions on the formation and speciation of disinfection byproducts during chlorination. Environ. Sci. Technol. 40, 3050e3056. Jekel, M.R., Roberts, P.V., 1980. Total organic halogen as a parameter for the characterization of reclaimed waters: measurement, occurrence, formation, and removal. Environ. Sci. Technol. 14, 970e975. Krasner, S.W., Weinberg, H.S., Richardson, S.D., Pastor, S.J., Chinn, R., Sclimenti, M.J., Onstad, G.D., Thruston Jr., A.D., 2006. Occurrence of a new generation of disinfection byproducts. Environ. Sci. Technol. 40, 7175e7185. Li, C., Benjamin, M.M., Korshin, G.V., 2002. The relationship between TOX formation and spectral changes accompanying chlorination of pre-concentrated or fractionated NOM. Water Res. 36, 3265e3272. Li, Y., Zhang, X., Shang, C., 2010. Effect of reductive property of activated carbon on total organic halogen analysis. Environ. Sci. Technol. 44, 2105e2111. Moran, J.E., Oktay, S.D., Santschi, P.H., 2002. Sources of iodine and iodine 129 in rivers. Water Resour. Res. 38 (8), 1149. Pinkernell, U., Nowack, B., Gallard, H., von Gunten, U., 2000. Methods for the photometric determination of reactive
1237
bromine and chlorine species with ABTS. Water Res. 34, 4343e4350. Plewa, M.J., Wagner, E.D., Jazwierska, P., Richardson, S.D., Chen, P.H., McKague, A.B., 2004. Chemical and biological characterization of newly discovered iodoacid drinking water disinfection byproducts. Environ. Sci. Technol. 38, 4713e4722. Plewa, M.J., Wagner, E.D., 2009. Quantitative Comparative Mammalian Cell Cytotoxicity and Genotoxicity of Selected Classes of Drinking Water Disinfection By-Products. AWWA Research Foundation, Denver, USA. Richardson, S.D., 1998. Drinking water disinfection by-products. In: Encyclopedia of Environmental Analysis and Remediation. John Wiley & Sons, New York, pp. 1398e1421. Richardson, S.D., Rav-Acha, C., Groisman, L., Popilevsky, I., Juraev, O., Glezer, V., Mckague, A.B., Plewa, M.J., Wagner, E.D., 2003. Tribromopyrrole, brominated acids, and other disinfection byproducts produced by disinfection of drinking water rich in bromide. Environ. Sci. Technol. 37, 3782e3793. Singer, P.C., Chang, S.D., 1989. Correlations between trihalomethanes and total organic halides formed during water treatment. J. Am. Water Works Assoc. 81 (8), 61e65. Westerhoff, P., Chao, P., Mash, H., 2003. Reactivity of natural organic matter with aqueous chlorine and bromine. Water Res. 38, 1502e1513. Xie, Y., 2004. Disinfection Byproducts in Drinking Water: Formation, Analysis and Control. Lewis Publishers, Boca Raton, FL, USA. Zhang, X., Minear, R.A., 2006. Formation, adsorption and separation of high molecular weight disinfection byproducts resulting from chlorination of aquatic humic substances. Water Res. 40, 221e230.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 3 8 e1 2 4 6
Available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Evaluation and modeling of benzalkonium chloride inhibition and biodegradation in activated sludge Chong Zhang a, Ulas Tezel b, Kexun Li a,*, Dongfang Liu a, Rong Ren a, Jingxuan Du a, Spyros G. Pavlostathis b a b
The College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0512, USA
article info
abstract
Article history:
The inhibitory effect and biodegradation of benzalkonium chloride (BAC), a mixture of
Received 17 March 2010
alkyl benzyl dimethyl ammonium chlorides with different alkyl chain lengths, was
Received in revised form
investigated at a concentration range from 5 to 20 mg/L and different biomass concen-
30 August 2010
trations in an activated sludge system. A solution containing glucose and mineral salts was
Accepted 29 September 2010
used as the wastewater in all the assays performed. The inhibition of respiratory enzymes
Available online 7 October 2010
was identified as the mode of action of BAC as a result of oxygen uptake rate analysis performed at BAC concentrations ranging between 5 and 70 mg/L. The glucose degradation
Keywords:
in the activated sludge at different BAC and biomass concentrations was well-described
Benzalkonium chloride
with Monod kinetics with competitive inhibition. The half-saturation inhibition constant
Inhibition
(KI) which is equivalent to EC50 of BAC for the activated sludge tested ranged between 0.12
Biodegradation
and 3.60 mg/L. The high KI values were recorded at low BAC-to-biomass ratios, i.e. less than
Modeling
10 mg BAC/g VSS, at which BAC was almost totally adsorbed to biomass and not
Activated sludge
bioavailable. BAC degradation started as soon as glucose was totally consumed. Although BAC was almost totally adsorbed on the biomass, it was degraded completely. Therefore, BAC degradation was modeled using two-phase biodegradation kinetics developed in this study. This model involves rapid partitioning of BAC to biomass and consecutive degradation in both aqueous and solid phases. The aqueous phase BAC degradation rate was twenty times, on average, higher than the solid phase degradation rate. The specific aqueous (kI1) and solid (kI2) phase BAC utilization rate constants were 1.25 and 0.31 mg BAC/g VSS h, respectively. The findings of this study would help to understand the reason of extensive distribution of quaternary ammonium compounds in wastewater treatment plant effluents and in natural water systems although QACs are biodegradable, and develop strategies to avoid their release and accumulation in the environment. ª 2010 Elsevier Ltd. All rights reserved.
1.
Introduction
Benzalkonium chloride (BAC) is a mixture of alkyl benzyl dimethyl ammonium chlorides with C8 to C18 alkyl groups. BAC, which is a group of quaternary ammonium compounds
(QACs), is the active ingredient of many pharmaceutical formulations, cosmetics, commercial disinfectants, industrial sanitizers and food preservatives (Tezel and Pavlostathis, 2009). About 75% of the QACs consumed in domestic and industrial applications annually are released into wastewater
* Corresponding author. Tel./fax: þ86 22 23501117. E-mail address:
[email protected] (K. Li). 0043-1354/$ e see front matter ª 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2010.09.037
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 3 8 e1 2 4 6
treatment systems. BAC is the most frequently found QAC group worldwide in municipal wastewater at concentrations ranging between 20 and 300 mg/L (Martinez-Carballo et al., 2007; Clara et al., 2007). The QACs present in the wastewater upset activated sludge process (Boethling, 1984). The EC50 values for hexadecyl trimethyl ammonium bromide and dodecyl benzyl dimethyl ammonium chloride obtained from a respirometric assay conducted with activated sludge ranged between 10 and 40 mg/L (Reynolds et al., 1987). The EC50 of a mixture of alkyl trimethyl ammonium chlorides (C14e18) for unacclimated activated sludge determined based on the inhibition of [14C] glucose uptake was 28 mg/L (Larson and Schaeffer, 1982). Another study showed that didecyl dimethyl ammonium chloride inhibited the COD removal in a rotating biological contactor at concentrations above 20 mg/L and the biofilm was totally eliminated at 160 mg/L. A variety of physiologically different microorganisms participate in the wastewater treatment process, therefore the response of each species to QAC inhibition is expected to be different. For instance, QACs are particularly toxic to nitrifiers. Benzalkonium chloride was inhibitory to a mixed nitrifying culture at 10e15 mg/L with a non-competitive inhibition coefficient equal to 1.5 mg/L (Yang, 2007). Overall, these studies suggest that QACs are inhibitory to activated sludge microbial community at concentrations higher than what is found in the wastewater. However, sudden discharges of QACs resulting in temporarily high levels in treatment plants could upset plant function. BACs rapidly and strongly adsorb onto biomass or are biodegraded during the biological wastewater treatment. Therefore, adsorption and biotransformation are the main routes of BAC removal from the wastewater. Average removal up to 99% by means of adsorption and biodegradation is reported in wastewater treatment systems (Clara et al., 2007; Boethling, 1984). Microorganisms that utilize QACs as the carbon and energy source at high concentrations have been identified in the activated sludge. The majority of the QAC degraders in the activated sludge are classified in the genus Pseudomonas (Dean-Raymond and Alexander, 1977; Geftic et al., 1979; van Ginkel et al., 1992; Nishihara et al., 2000; Kaech and Egli, 2001; Nishiyama and Nishihara, 2002; Takenaka et al., 2007; Liffourrena et al., 2008). Other species that can catabolize various QACs are Xanthomonas sp. (DeanRaymond and Alexander, 1977) and Aeromonas sp. (Patrauchan and Oriel, 2003). Until recently, few studies had focused on the biotransformation/biodegradation of BAC (Patrauchan and Oriel, 2003; van Ginkel, 2004; Qin et al., 2005). According to the results of these studies, BAC biotransformation commences with the fission of the alkyl group from the quaternary nitrogen resulting in the formation of benzyl dimethyl amine as the first intermediate. Benzyl dimethyl amine is then converted to ammonia through either two demethylation followed by a debenzylation or a debenzylation followed by two demethylation processes. Although biodegradation potential and mechanism of BAC and other QACs have been elucidated, none of the studies presented above reported the biodegradation kinetics of QACs. In spite of the fact that, the information on the inhibitory effects and biodegradation of BAC as well as its adsorption to activated sludge is present in the literature, the interaction of these processes, i.e. adsorption, inhibition and biodegradation,
1239
and how it affects the overall fate of BAC in the activated sludge is not well understood. Given the toxicity of BAC to aquatic organisms and the role in the induction of antibiotic resistance in the environment (Gaze et al., 2005), BAC has to be removed completely in the wastewater treatment systems (i.e., activated sludge) before wastewater and the residual (i.e., sludge) are discharged to the environment. As the ultimate biodegradation of BAC is the main goal, BAC inhibition and biodegradation kinetics in activated sludge systems need to be well-understood. The objectives of this study were to: (a) investigate the potential inhibitory effect and biodegradation of BAC in activated sludge; and (b) develop a comprehensive dynamic model to elucidate the fate and effect of BAC in activated sludge. All the experiments were carried out with a mixed aerobic culture at a range of BAC and biomass concentration.
2.
Materials and methods
Details on the a) properties and characterization of benzalkonium chloride; b) mixed aerobic heterotrophic culture used in all assays; c) analytical methods; d) model simulations and parameter estimation; and e) adsorption kinetics and isotherm assays are given in the Supplementary Material (Text S1eS5).
2.1.
Respirometric assay
Inhibition of BAC in activated sludge was investigated based on the oxygen uptake rate. A 100 mL sample of mixed aerobic heterotrophic culture in the endogenous growth phase was transferred into a series of Erlenmeyer flasks. A glucose solution, which served as carbon/energy source, and BAC at desired concentrations were added and the total liquid volume was adjusted to 100 mL with culture media. The glucose COD in the bottles was about 300 mg/L. The culture series included six bottles that were amended with BAC resulting in total BAC concentrations of 5, 10, 20, 30, 50 and 70 mg/L. Two additional flasks were prepared: seed blank and reference which consisted of only seed and culture media and seed, culture media, and glucose (300 mg COD/L), respectively. Dissolved oxygen in each flask was measured during the time course using a DO meter while the content was continuously mixed. The oxygen uptake rate (OUR) of each culture at different BAC concentrations was determined by calculating the slope of DO versus time curve using a linear regression performed by using Sigma Plot Version 10 software (Systat Software Inc., San Jose, CA, USA). The specific oxygen uptake rate (SOUR) of each culture was determined by normalizing the OUR to the volatile suspended solids (VSS) concentration in each individual flask. At the end of the assay, BAC concentration in each flask was measured to verify that BAC was not degraded during the course of the assay.
2.2. Batch inhibition assay using the mixed aerobic culture The inhibitory effect of BAC on glucose utilization and BAC biodegradation in the mixed heterotrophic culture was tested
1240
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 3 8 e1 2 4 6
in a batch assay. The assay was performed in 1.5-L glass reactors stirred with a Teflon-coated stirring bar and aerated with compressed air. A sample of mixed liquor from the mixed aerobic heterotrophic culture was transferred to each reactor. Glucose and NH4Cl were added as the carbon and nitrogen source. The initial total glucose concentration was about 300 mg COD/L in the reactor. The cultures were then amended with BAC resulting in a total initial BAC concentration of 5, 10, and 20 mg/L, respectively. The total liquid volume was adjusted to 1 L with the mineral media. The initial pH in the culture was 7.0 and the reactor was maintained at 25 C. During the incubation period, the DOC and BAC concentration was measured at pre-specified time intervals. pH, TSS, VSS were measured at the beginning and at the end of the incubation period. Another batch assay testing the effect of biomass concentration on the inhibition and biodegradation of BAC in the mixed heterotrophic culture was performed using the same methodology described above. The biomass concentration in each reactor was adjusted by diluting the stock mixed culture with mineral media. The biomass concentration tested in this study ranged from 180 to 1300 mg VSS/L and the BAC concentration applied was either 5 or 10 mg/L. DOC and BAC concentration, VSS and pH were measured during the test period. All the assays described above were performed in duplicate. A dynamic model delineating the effect of BAC on substrate (glucose) utilization and BAC degradation was developed using the results of the assays described above. The model simulations and parameter estimation procedures used are given in Text S4.
2.3.
A DISSOLVED OXYGEN (mg/L)
8
3.
Results and discussion
3.1.
BAC inhibition assessment via oxygen consumption
The impact of BAC on the oxygen uptake rate of the mixed heterotrophic culture was assessed at different BAC concentrations ranging from 5 to 70 mg/L (Fig. 1(A)). The dissolved oxygen present in the reference culture in which there was no BAC was depleted in less than 25 min. The SOUR of the reference culture was measured as 49 mg O2/g VSS h which indicates that the culture was at the exponential growth phase. Although, nitrifiers were present in the activated sludge, their population was low enough to assume that the major fraction of the oxygen is consumed by the heterotrophic population (Fig. S1). The SOUR of the cultures decreased exponentially as the BAC concentration increased. The SOUR approached to that of seed culture, which was amended with neither glucose nor BAC, at the highest BAC concentration tested which indicates that the culture was at the endogenous respiration phase and did not utilize the added glucose (Fig. 1(B)).
6
4 BAC Conc. (mg/L) 0 30 5 50 10 70 20
2
0 6
8 10 12 14 16 18 20 22
TIME (Min) SOUR (mg O2/g VSS.hr)
B
50 40 30 20 10 0 0
20
40
60
80
BAC CONC. (mg/L)
Adsorption kinetic and isotherm assays
An adsorption kinetic assay was carried out to determine the time required for the adsorption of BAC to reach equilibrium. Subsequently, an adsorption isotherm assay was conducted to determine the BAC adsorption capacity of the activated sludge. Both assays are described in detail in Text S5.
blank
Fig. 1 e The profile of dissolved oxygen consumption (A) and specific oxygen uptake rate of activated sludge used in this study at different BAC concentrations (0e70 mg/L).
The effective BAC concentration that reduces the SOUR to half of the reference culture SOUR (EC50) is calculated as 22 mg/ L Boethling (1984) reported a range between 20 and 50 mg/L as the EC50 value of BAC for acclimated and unacclimated activated sludge in his review on cationic surfactants. Moreover, the EC50 of BAC for Pseudomonas putida was reported as 6 mg/L (Sutterlin et al., 2008). The results of the respirometric assay performed in this study revealed that BAC affects oxygen uptake rate therefore the primary mode of action of BAC in activated sludge is the inhibition of the respiratory enzymes. Inhibition of other terminal electron accepting processes (TEAPs) such as denitrification at the same concentration range was recently reported (Tezel and Pavlostathis, 2009).
3.2.
Modeling BAC inhibition and biodegradation
Glucose utilization as well as BAC biodegradation by activated sludge at 5, 10 and 20 mg/L BAC was investigated in another batch assay. The time at which half of the glucose was utilized (t1/2) in the reference culture which did not receive any BAC was calculated as 0.6 h (Fig. S2). The glucose utilization slowed
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 3 8 e1 2 4 6
down at the higher BAC concentrations (Fig. 2). The glucose consumption t1/2 values were 1.6, 2.3 and 10.2 h at 5, 10 and 20 mg BAC/L. On the other hand, the BAC concentration was almost constant and equal to the initial concentration during the utilization of glucose (Fig. 2). Following the utilization of the major fraction of the glucose present in the cultures, BAC degradation was initiated. Given that the major fraction of the microbial community used in this study was composed of heterotrophs, and nitrifiers cannot degrade BAC (Yang, 2007), BAC was consumed by the heterotrophic microbial community in the activated sludge which also consumed glucose. The
A
400
200
15
Glucose BAC
10
Model
100
5
GLUCOSE (mg COD/L)
0
0
B
400
20
300
15
200
10
100
5
0
BAC CONC. (mg/L)
300
20
0
C
400
20
300
15
200
10
100
5
0
0 0 10 20 30 40 50 60 70 80
TIME (hr) Fig. 2 e Observed and simulated glucose and BAC utilization profiles in the cultures amended with (A) 5, (B) 10, and (C) 20 mg BAC/L at 500 mg VSS/L (Error bars represent one standard deviation of the means). In glucose utilization simulations; k [ 0.41 g COD/g VSS h, Ks [ 22 mg COD/L, Y [ 0.6 g COD/g COD and b [ 0.0025 hL1 was used and KI was estimated. In BAC utilization simulations, k, Ks, Y and b were kept constant and (A) KI [ 0.41 mg/L and kI1, kI2, KSI were estimated, (B) KI [ 0.30 mg/L, kI1 [ 0.0013 mg BAC/mg VSS-h, KSI [ 0.6 mg/L and, kI2 was estimated, (C) KI [ 0.12 mg/L, kI1 [ 0.0013 mg BAC/mg VSS-h, KSI [ 0.6 mg/L, and kI2 was estimated.
1241
calculated half-life of BAC in the cultures at 5, 10 and 20 mg/L BAC was 20.7, 21.5 and 36.9 h. The t1/2 value for BAC degradation are strongly correlated (r2 ¼ 0.999) to the t1/2 value for glucose utilization (Fig. S3). This result supports two conclusions: (1) the initial delay in the BAC degradation observed in all cultures was not related to acclimation; given that the inoculum used in this study was obtained from a wastewater treatment facility serving a very complex industrial area, the probability of the microbial community to have been exposed to QACs is high; and (2) the delay in the glucose degradation caused by BAC inhibition was the major reason for the retardation in the BAC degradation. An adsorption kinetic assay was performed in order to evaluate the dynamics of BAC partitioning in the activated sludge. The liquid phase BAC concentration reached equilibrium in half an hour which indicates that BAC sorption to the activated sludge at the concentration used was instantaneous (Fig. S4). The rapid attainment of equilibrium is consistent with previously published reports on the adsorption of quaternary ammonium compounds on a variety of municipal sludge (Ismail et al., 2010). Adsorption of BAC on activated sludge was investigated at BAC concentrations up to 70 mg/L. The Freundlich isotherm was used to model the equilibrium (Fig. S5). The estimated values for KF, capacity factor/sorption affinity and n, Freundlich exponent were 42.1 1.4 (mg/g VSS)(L/mg)n and 0.25 0.01, respectively (r2 ¼ 0.995). Similar constants for adsorption of BAC on activated sludge were reported in other studies (Ismail et al., 2010; Garcia et al., 2006). The Freundlich isotherm model represented well the BAC adsorption on activated sludge. The results of BAC adsorption kinetic and isotherm assays suggest that BAC is rapidly and extensively adsorb on activated sludge. Based on the adsorption isotherm, the calculated equilibrium liquid phase BAC concentration in the cultures at 5, 10, and 20 mg BAC/L was 0.003, 0.02 and 0.32 mg/L, respectively. Given that above 99% of BAC was adsorbed on the activated sludge and the desorption of adsorbed BAC was almost negligible under the test conditions (Ismail et al., 2010), the biodegradation of BAC proceeds both in the liquid and the solid phases. By using the facts demonstrated above which are: (1) BAC inhibits respiratory enzymes; (2) BAC degradation starts after the utilization of the major fraction of readily degradable COD; (3) BAC instantaneously and extensively partitions to the activated sludge; and (4) BAC gets degraded in both the liquid and solid phases, and assuming that all microbial cells in the activated sludge community are capable of BAC degradation, a model composed of four ordinary differential Eq. (1)e(4) and one algebraic Eq. (5) was developed. The Monod equation (Rittmann and McCarty, 2001) is the foundation of the model and used for modeling COD substrate utilization Eq. (1), and BAC utilization Eqs. (3) and (4) as well as the microbial growth Eq. (3). A novel approach was developed to model the biodegradation of BAC in the activated sludge and a schematic of the concept is given in Fig. 3. Based on this approach, BAC is instantaneously adsorbed on the biomass and gets degraded at different rates in the liquid Eq. (3) and the solid phases Eq. (4). We assumed that the same enzyme or group of enzymes
1242
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 3 8 e1 2 4 6
BAC
product kI1
adsorption
aqueous phase
kI2
BAC
biomass
enzyme
Fig. 3 e Conceptual model of BAC degradation in activated sludge.
catalyzes the BAC degradation in the liquid and the solid phase, however other processes such as diffusion in the membrane, also may affect the degradation of biomass-sorbed BAC. Therefore, kI2 Eq. (4) is expressed as the observed biodegradation rate and may be composed of true maximum specific utilization rate plus membrane migration (diffusion within the membrane) rate. Biodegradation of dodecyl trimethyl ammonium chloride at different rates in the liquid and solid phases of a sediment slurry was previously demonstrated in another study (Shimp and Young, 1988), which also indicates that such a phenomenon occurs not only in biological reactors but also other natural environments in which QACs sorb. Therefore, combining phase distribution and biodegradation kinetics in such a way demonstrated above would contribute to a better understanding of the dynamics of pollutants in both engineered and natural systems. The Freundlich isotherm equation is incorporated in the model to calculate total BAC concentration as it was degraded in both the liquid and solid phases. An inhibition factor, (1 þ I/ KI), was included in both Eqs. (1) and (2) to reflect competitive inhibition as the inhibition mechanism for BAC which was justified by fact (1) given above. A switching factor, KS/(KSþS), was included in Eqs. (3) and (4) to reflect the substrate competition which was justified by fact (2) listed above. The biomass growth on BAC was assumed to be very small compared to the growth on glucose therefore this term (YdI/ dt) was neglected in Eq. (2). dS kSX ¼ dt Ks 1 þ I þ S
(1)
dX kSX bX ¼Y dt Ks 1 þ I þ S
(2)
dCe kI1 Ce X Ks ¼ dt KsI þ Ce Ks þ S
(3)
dqe kI2 qe X Ks ¼ dt KsI þ qe Xinit Ks þ S
(4)
I ¼ qe Xinit þ Ce
(5)
KI
KI
In the above equations, S is the glucose concentration (mg COD/L), X is the active biomass concentration (mg VSS/L), Ce is the liquid phase BAC concentration (mg/L), qe is the solid phase BAC concentration (mg BAC/g VSS), I is the total BAC concentration (mg BAC/L). The parameters used in the model equations include: k, maximum specific glucose utilization
rate constant (mg COD/mg VSS h); KS, glucose half-saturation coefficient (mg COD/L); Y, true yield coefficient (g VSS/g COD); b, biomass decay rate constant (h1); KI, “observed” inhibition coefficient (mg BAC/L); kI1, maximum specific liquid phase BAC utilization rate constant (mg BAC/mg VSS h); kI2, “observed” solid phase BAC utilization rate constant (mg BAC/ mg VSS h); KSI, BAC half-saturation coefficient (mg BAC/L); and Xinit, initial biomass concentration (g VSS/L). Before simulating the effect of BAC and its biodegradation in the activated sludge, the key parameters, i.e. k, KS, Y and b, of Monod growth equations were estimated. The estimation of each parameter was done by using the glucose consumption profile in the reference culture (Fig. S2). The range for each parameter value was limited by typical parameter values reported for activated sludge (Tchobanoglous et al., 2003). The RMSD of the fit was 24.7 (9.7% of the initial conc.) and the estimated values for each parameter are given in Table 1. The estimated parameter values were kept as constants for the rest of the simulations. The identifiability of each parameter estimated was determined using local sensitivity functions obtained by Sensitivity Toolbox of Berkeley-Madonna (Gujer, 2008) (Fig. S6). According to the sensitivity analysis, sensitivity is largest for k which indicated that a minor change in the k would have the largest effect on the model output S. From the visual inspection of the sensitivity figure (Fig. S6), it was obvious that the sensitivity of Y and b had exactly the same form, while k and Ks were different. Given that Y and b were the parameters describing mainly the biomass growth, the change of one of Y or b can be compensated by an appropriate adjustment of the other. Thus, these two parameters could not be identified uniquely from the data used. On the other hand, the values estimated for k and Ks were absolute. The identifiability of Y and b was less of concern in this study because the sensitivity of S to these parameters dominated after the major fraction of the substrate was utilized. Moreover, curve fitting performed with 15 randomly selected initial estimate values for each of four parameters within the constraints specified in Table 1 resulted in the estimation of the same value for Y and b. Overall, Y and b could be identifiable within the constraints used in the curve fitting. The glucose and BAC utilization at different BAC concentrations were simulated and KI, kI1 and kI2 were estimated using the glucose and BAC utilization profiles in the cultures amended with 5, 10 and 20 mg BAC/L (Fig. 2). The estimation was performed in two steps.
Table 1 e Estimated model parameters and previously reported range of typical parameter values used for parameter estimation in this study. Parameter k, g COD/g VSS h Ks, mg COD/L Y, g VSS/g COD b, h1 c2
Estimated value
Typical value rangea
0.41 0.06 22 19.8 0.6 0.9 0.0025 0.321 3086
0.08e0.41 10e60 0.3e0.6 0.0025e0.0060
a (Tchobanoglous et al., 2003).
1243
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 3 8 e1 2 4 6
2009; van Ginkel and Kolvenbach, 1991; Ying, 2006). On the other hand, Tezel (2009) reported more than an order of magnitude higher degradation rate for a BAC, tetradecyl benzyl dimethyl ammonium chloride (C14BDMA-Cl) in a BACenriched culture. The Monod-type specific C14BDMA-Cl utilization rate constant for the BAC enrichment culture, which utilizes BAC as the sole carbon and energy source for almost three years, was 0.03 mg C14BDMA-Cl/mg VSS h. The BACenriched culture is mainly composed of Pseudomonas spp. which is the primary species known to degrade various types QACs. Pseudomonas spp. accounts for 2e12% of the activated sludge microbial community (Dias and Bhat, 1964). The low BAC utilization rate constant estimated by assuming all of the
A
400 300 200
8 Glucose BAC
6
Model
4
100
2
0
0
B
400
In all simulations the previously estimated parameter values at each BAC concentration were kept constant. The initial estimation of the aforementioned parameters, i.e. KSI, kI1 and kI2, was done using the BAC utilization profiles of the culture amended with 5 mg BAC/L (Fig. 2(A)). The estimated KSI, kI1 and kI2 values were 0.6 mg/L, 0.0013 mg BAC/mg VSS h and 0.00028 mg BAC/mg VSS h, respectively (RMSD: 0.15 (2.9%)). The sensitivity analysis revealed that each parameter was identified uniquely from the data sets used (Fig. S7). The liquid phase BAC degradation was twenty times faster than the solid phase BAC degradation (Fig. S8). However, given the high adsorption affinity of BAC, the solid phase transformation is the limiting step in the BAC removal in activated sludge systems. The specific BAC utilization rate constants are consistent but lower than the first order liquid and solid phase dodecyl trimethyl ammonium chloride, a monoalkonium chloride (MAC), degradation rate constants obtained in experiments performed using sediments which were 0.0032 0.0008 h1 and 0.0009 0.0002 h1, respectively (Shimp and Young, 1988). The lower rate constants obtained in the present study are attributed to the type of QAC used which was confirmed by other studies indicating that BACs are less biodegradable than the MACs (Tezel and Pavlostathis,
10 8
300
6 200 4 100
2
0
3.2.2. Step 2 e estimation of BAC biodegradation constants KSI, kI1 and kI2
10
BAC CONC. (mg/L)
Step 1 e estimation of inhibition constant, KI
Since the BAC concentration was almost constant throughout the glucose utilization period, KI was estimated using only Eqs. (2) and (3) in the first step (Fig. 2). During KI estimations, only glucose consumption profiles at different BAC concentrations were used (Fig. 2). Since only KI was estimated, its value was identified uniquely from the data sets used for curve fitting. Altogether three KI values were obtained for cultures tested at the three BAC concentrations. These KI values were 0.383 0.015, 0.292 0.014 and 0.120 0.006 mg/L at 5, 10 and 20 mg BAC/L, respectively. The corresponding RMSD (the values in parentheses represent the coefficient of variation with respect to the initial concentration) of the fits was 7.9 (2.6%), 10.7 (3.4%) and 17.1 (5.2%), respectively. The mean KI was calculated as 0.28 0.15 mg/L. The mean KI value for BAC is at least two orders of magnitude lower than what is observed for conventional activated sludge which is attributed to the lower biomass concentration (450e650 mg VSS/L) used in our experiments compared to conventional activated sludge process (ca. 2000 mg VSS/L). On the other hand, inhibitory concentrations ranging from 0.2 to 6 mg QAC/L were reported for dilute activated sludge systems (Boethling, 1984). However, the biomass concentrations used in these studies were unknown. In addition, Microtox was used to determine the acute inhibitory concentration of the BAC mixture used in our experiments. The 5-min and 15-min EC50 values were 0.22 mg/ L (r2 ¼ 0.95, and 95% confidence range ¼ 0.17e0.27 mg/L) and 0.14 mg/L (r2 ¼ 0.88, and 95% confidence range ¼ 0.10e0.20 mg/ L). These results suggest that the mean KI obtained in the batch inhibition assay is the “minimum inhibitory concentration” for the activated sludge tested. KI may increase as the biomass concentration increases. This phenomenon is discussed in a subsequent section.
GLUCOSE (mg COD/L)
3.2.1.
0
C
400
10 8
300
6 200 4 100 0
2 0 0 10 20 30 40 50 60 70 80
TIME (hr) Fig. 4 e Observed and simulated glucose and BAC utilization profiles in the cultures amended with 5 mg BAC/L at (A) 615, (B) 394 and (C) 179 mg VSS/L (Error bars represent one standard deviation of the means). In glucose utilization simulations; k [ 0.41 g COD/g VSS h, Ks [ 22 mg COD/L, Y [ 0.6 g COD/g COD and b [ 0.0025 hL1 was used and KI was estimated. In BAC utilization simulations, k, Ks, Y and b were kept constant and (A) KI [ 2.04 mg/L, kI1 [ 0.0013 mg BAC/mg VSS-h, KSI [ 0.6 mg/L and kI2 was estimated, (B) KI [ 0.38 mg/L, kI1 [ 0.0013 mg BAC/mg VSS-h, KSI [ 0.6 mg/ L, and kI2 was estimated, (C) KI [ 0.14 mg/L, kI1 [ 0.0013 mg BAC/mg VSS-h, KSI [ 0.6 mg/L, and kI2 was estimated.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 3 8 e1 2 4 6
3.3. Effect of BAC-to-biomass ratio on inhibition and biodegradation The toxicity of BAC varies depending on the biomass concentration in the activated sludge most probably due to the extent of adsorption. Therefore, BAC-to-biomass ratio plays a crucial role in identifying inhibition and assessing BAC degradation since inhibition directly affects the BAC degradation by prolonging the half-life of the substrate COD utilization. The glucose and BAC utilization was tested at various biomass concentrations ranging from 179 to 1280 mg VSS/L and at 5, 10 and 20 mg BAC/L resulting in a BAC:VSS ratio ranging between 8 and 38 mg/g in a series of batch assays (Figs. 4 and 5, Fig. S9). The KI and kI2 values were estimated for each set of data following the two steps described above. The glucose and BAC utilization profiles presented in Figs. 4 and 5 were used for the estimation of these parameters. The estimated KI (mg/L) and kI2 (mg BAC/mg VSS h) values in the cultures having 615, 394 and 179 mg VSS/L and amended with 5 mg BAC/L were 2.04 and 0.0002, 0.38 and 0.0003, and 0.14 and 0.0003, respectively (Fig. 4). These parameter values in the cultures having 1280, 701 and 437 mg VSS/L and amended with 10 mg BAC/L were 3.61 and 0.0002, 0.56 and 0.0003, and 0.23 and 0.0004, respectively (Fig. 5). At both BAC concentrations, kI2 was constant having a mean value of 2.89 0.73 104 mg BAC/mg VSS-h. On the contrary, KI was high at the highest VSS concentration tested at both BAC concentrations and in a range of 0.14e0.56 mg/L at the rest of VSS concentrations tested. A comprehensive plot was created by using the estimated KI and kI2 as well as the BAC adsorption isotherm at different BAC-to-biomass (BAC:VSS) ratios tested in this study (Fig. 6). Multi-dimensional analysis of the data obtained in this study
A
400 300 200
20 15
Glucose BAC
10
Model
100
5
0
0
B
400
20
300
15
200
10
100
5
0
BAC CONC. (mg/L)
species present in the activated sludge are capable of BAC degradation may suggest that only about 4% (the ratio of BAC utilization rates of activated sludge and BAC enrichment community) can degrade BAC. The profiles of glucose and BAC utilization in the cultures at 10 and 20 mg BAC/L were simulated and only kI2 was estimated at each BAC concentration using the previously estimated parameter values as constants. The estimated kI2 values were 0.0004 (RMSD ¼ 0.24 (2.4%)) and 0.0013 (RMSD ¼ 0.63 (3.2%)) mg BAC/mg VSS h, respectively. Thus, the estimated kI2 values increased and approached the kI1 value as the BAC concentration increased from 5 to 20 mg/L. As it was discussed above, kI2 was a lumped parameter which may represent both biodegradation and membrane migration. The BAC concentration may affect the dominance of one or the other. For instance, the membrane migration process is the rate limiting step at low BAC concentrations at which BAC sorption is heterogeneous through the biomass surface, thus there is a concentration gradient on the biomass. On the contrary, the membrane migration process diminishes at high BAC concentrations at which the biomass surface is saturated, and the biodegradation rate in the solid phase, therefore, becomes equal to that in the liquid phase. The adsorption isotherm presented in this study supports that saturation of biomass was reached at 20 mg BAC/L (Fig. S5). The phenomenon presented here is discussed in detail below.
GLUCOSE (mg COD/L)
1244
0
C
400
20
300
15
200
10
100
5
0
0 0 10 20 30 40 50 60 70 80
TIME (hr) Fig. 5 e Observed and simulated glucose and BAC utilization profiles in the cultures amended with 10 mg BAC/L at (A) 1280, (B) 701 and (C) 437 mg VSS/L (Error bars represent one standard deviation of the means). In glucose utilization simulations; k [ 0.41 g COD/g VSS h, Ks [ 22 mg COD/L, Y [ 0.6 g COD/g COD and b [ 0.0025 hL1 was used and KI was estimated. In BAC utilization simulations, k, Ks, Y and b were kept constant and (A) KI [ 3.61 mg/L and kI1, kI2, KSI were estimated, (B) KI [ 0.56 mg/L, kI1 [ 0.0013 mg BAC/mg VSS-h, KSI [ 0.6 mg/L and, kI2 was estimated, (C) KI [ 0.23 mg/L, kI1 [ 0.0013 mg BAC/mg VSS-h, KSI [ 0.6 mg/L, and kI2 was estimated.
suggests that BAC does not exert an inhibitory effect to activated sludge at and below 10 mg BAC/g VSS at which almost all of the BAC is adsorbed on the biomass. The inhibition increases as BAC:VSS increases, and KI approaches to a constant value which is defined as “minimum inhibitory concentration (MIC)”. The MIC was reached at the BAC:VSS around 28 mg BAC/g VSS at which the liquid phase BAC concentration (Ce) is equal to the MIC. This implies that BAC is inhibitory only if it is in the liquid phase. The kI2 was constant around 3.08 0.83 104 mg BAC/mg VSS-h at between 7 and 28 mg BAC/g VSS. A sudden increase in the kI2 was obtained at
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 3 8 e1 2 4 6
0.35
4
Ceq
0.0012 3
0.0006 0.0004
KI (mg BAC/L)
-1
kI2 (hr )
0.0010 0.0008
KI
0.30 0.25 0.20
2
kI2
0.15
0.05 0 5
10
15
20
25
30
35
0.00 40
BAC:VSS (mg BAC/g VSS)
Fig. 6 e Profile of liquid phase BAC concentration (Ceq: solid line e), estimated inhibition coefficient (KI: hollow circle B) and solid phase BAC utilization rate constant (kI2: upward triangle 6) at different BAC-to-biomass ratios (BAC:VSS).
32 mg BAC/g VSS at which the available biomass surface reached saturation by BAC according to the adsorption isotherm obtained in this study. The kI2 approached the kI1 value at that particular BAC:VSS at which the rate limiting step, i.e. membrane migration, diminished and biodegradation dominated. The kI2 stayed constant and equal to kI1 above 32 mg BAC/g VSS (Fig. 6).
4.
in higher than typical BAC removal efficiencies. The model, which integrates inhibition, adsorption and biodegradation processes to simulate the dynamics of BAC in the activated sludge, developed in this study may effectively be used to simulate the dynamics of other compounds (e.g., triclosan, triclocarban, linear alkyl and alkyl benzene sulfonates, perfluoroalkyl carboxylates and sulfonates etc) with properties and behavior similar to QACs.
0.10
1
0.0002 0.0000
Ceq (mg/L)
0.0014
1245
Conclusions
In this study, the dynamics of BAC in an activated sludge system were investigated. Respiratory inhibition, adsorption and biodegradation were identified as the three major processes which affect the fate of BAC in activated sludge. A comprehensive model was developed by integrating these processes into the Monod equation. The model agreed well with the data obtained from a series of batch assays performed. In conclusion, BAC inhibits oxygen uptake and use, thereby causing prolonged COD substrate utilization. BAC degradation initiates after the major portion of the readily degradable COD is utilized. Therefore, a delay in the readily degradable COD utilization causes retardation in the BAC degradation, as well. A major fraction of BAC instantly adsorbs on the biomass. Biodegradation of BAC proceeds both in the liquid and solid phases, however the solid phase BAC degradation is about twenty times slower than in the liquid phase. Given the low BAC concentrations found in municipal wastewaters, BAC is unlikely to be toxic in wastewater treatment. However, since the biodegradation rate of BAC is very slow, a major fraction of BAC is likely to be transferred and accumulated in the environment, especially in anaerobic compartments. In order to mitigate this problem, we suggest the implementation of activated sludge systems with long solid retention times such as extended aeration or employment of attached growth systems. These systems would favor the prolonged retardation of BAC by facilitating the adsorption on the biomass and increase in the degradation rate, resulting
Acknowledgements This work was financially supported by the National Water Pollution Control and Treatment Technological project (No. 2008ZX07314-002) and the National Natural Science Foundation of China (No. 50908117).
Appendix. Supplementary data Supplementary data associated with this article can be found in the on-line version, at doi:10.1016/j.watres.2010.09.037.
references
Boethling, R.S., 1984. Environmental fate and toxicity in wastewater treatment of quaternary ammonium surfactants. Water Res. 18 (3), 1061e1076. Clara, M., Scharf, S., Scheffknecht, C., Gans, O., 2007. Occurrence of selected surfactants in untreated and treated sewage. Water Res. 41 (19), 4339e4348. Dean-Raymond, D., Alexander, M., 1977. Bacterial metabolism of quaternary ammonium compounds. Appl. Environ. Microbiol. 33, 1037e1041. Dias, F.F., Bhat, J.V., 1964. Microbial ecology of activated sludge: I. Dominant bacteria. Appl. Microbiol. 12 (5), 412e417. Garcia, M.T., Campos, E., Sanchez-Leal, J., Comelles, F., 2006. Sorption of alkyl benzyl dimethyl ammonium compounds by activated sludge. J. Dispers. Sci. Technol. 27 (5), 739e744. Gaze, W.H., Abdouslam, N., Hawkey, P.M., Wellington, E.M.H., 2005. Incidence of class 1 integrons in a quaternary ammonium compound polluted environment. Antimicrob. Agents Chemother. 49 (5), 1802e1807. Geftic, S.G., Heymann, H., Adair, F.W., 1979. 14 year survival of Pseudomonas cepacia in a salts solution preserved with benzalkonium chloride. Appl. Environ. Microbiol. 37, 505e510. Gujer, W., 2008. Systems Analysis for Water Technology. Springer, Berlin, Germany. Ismail, Z.Z., Tezel, U., Pavlostathis, S.G., 2010. Sorption of quaternary ammonium compounds to municipal sludge. Water Res. 44, 2303e2313. Kaech, A., Egli, T., 2001. Isolation and characterization of a Pseudomonas putida strain able to grow with trimethyl-1,2dihydroxy-propyl-ammonium as sole source of carbon, energy and nitrogen. Syst. Appl. Microbiol. 24, 252e261. Liffourrena, A.S., Lopez, F.G., Salvano, M.A., Domenech, C.E., Lucchesi, G.I., 2008. Degradation of tetradecyl trimethyl ammonium by Pseudomonas putida A ATCC 12633 restricted by accumulation of trimethylamine is alleviated by addition of Al3þ ions. J. Appl. Microbiol. 104, 396e402. Martinez-Carballo, E., Sitka, A., Gonzalez-Barreiro, C., Kreuzinger, N., Furhacker, M., Scharf, S., Gans, O., 2007.
1246
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 3 8 e1 2 4 6
Determination of selected quaternary ammonium compounds by liquid chromatography with mass spectrometry. Part I. Application to surface, waste and indirect discharge water samples in Austria. Environ. Pollut. 145 (2), 489e496. Nishihara, T., Okamoto, T., Nishiyama, N., 2000. Biodegradation of didecyl dimethyl ammonium chloride by Pseudomonas fluorescens TN4 isolated from activated sludge. J. Appl. Microbiol. 88, 641e647. Nishiyama, N., Nishihara, T., 2002. Biodegradation of dodecyl trimethyl ammonium bromide by Pseudomonas fluorescens F7 and F2 isolated from activated sludge. Microbes Environ. 17, 164e169. Patrauchan, M.A., Oriel, P.J., 2003. Degradation of benzyl dimethyl alkyl ammonium chloride by Aeromonas hydrophila sp K. J. Appl. Microbiol. 94, 266e272. Qin, Y., Zhang, G.Y., Kang, B.A., Zhao, Y.M., 2005. Primary aerobic biodegradation of cationic and amphoteric surfactants. J. Surfactants Detergents 8, 55e58. Reynolds, L., Blok, J., Demorsier, A., Gerike, P., Wellens, H., Bontinck, W.J., 1987. Evaluation of the toxicity of substances to be assessed for biodegradability. Chemosphere 16, 2259e2277. Rittmann, B.E., McCarty, P.L., 2001. Environmental Biotechnology: Principles and Applications. McGraw-Hill, Boston. Shimp, R.J., Young, R.L., 1988. Availability of organic-chemicals for biodegradation in settled bottom sediments. Ecotoxicol. Environ. Saf. 15 (1), 31e45. Sutterlin, H., Alexy, R., Kummerer, K., 2008. The toxicity of the quaternary ammonium compound benzalkonium chloride alone and in mixtures with other anionic compounds to bacteria in test systems with Vibrio fischeri
and Pseudomonas putida. Ecotoxicol. Environ. Saf. 71 (2), 498e505. Takenaka, S., Tonoki, T., Taira, K., Murakami, S., Aoki, K., 2007. Adaptation of Pseudomonas sp strain 7-6 to quaternary ammonium compounds and their degradation via dual pathways. Appl. Environ. Microbiol. 73, 1797e1802. Tchobanoglous, G., Burton, F.L., Stensel, H.D., 2003. Wastewater Engineering: Treatment, Disposal and Reuse, Fourth ed. McGraw-Hill Professional, New York, NY. Tezel, U., 2009. Fate and effect of quaternary ammonium compounds in biological systems. Ph. D. Thesis, Georgia Institute of Technology, Atlanta, GA. Tezel, U., Pavlostathis, S.G., 2009. Transformation of benzalkonium chloride under nitrate reducing conditions. Environ. Sci. Technol. 43 (5), 1342e1348. van Ginkel, C.G., Kolvenbach, M., 1991. Relations between the structure of quaternary alkyl ammonium salts and their biodegradability. Chemosphere 23 (3), 281e289. van Ginkel, C.G., Vandijk, J.B., Kroon, A.G.M., 1992. Metabolism of hexadecyl trimethyl ammonium chloride in Pseudomonas strain-B1. Appl. Environ. Microbiol. 58, 3083e3087. van Ginkel, C.G., 2004. Biodegradation of cationic surfactants. In: Zoller, U. (Ed.), Handbook of Detergents Part B: Environmental Impact, vol. 121. Marcel Dekker, Inc., New York, USA. Yang, J., 2007. Fate and effect of alkyl benzyl dimethyl ammonium chloride in mixed aerobic and nitrifying cultures. MS Thesis. Georgia Institute of Technology, Atlanta, GA. Ying, G.G., 2006. Fate, behavior and effects of surfactants and their degradation products in the environment. Environ. Int. 32 (3), 417e431.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 4 7 e1 2 5 7
Available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Molecular subtypes of Campylobacter spp., Salmonella enterica, and Escherichia coli O157:H7 isolated from faecal and surface water samples in the Oldman River watershed, Alberta, Canada C. Jokinen a, T.A. Edge b, S. Ho a, W. Koning c, C. Laing a, W. Mauro a, D. Medeiros d, J. Miller e, W. Robertson d,1, E. Taboada a, J.E. Thomas f, E. Topp g, K. Ziebell h, V.P.J. Gannon a,* a
Laboratory for Foodborne Zoonoses, Public Health Agency of Canada, Box 640, Township Road 9-1, Lethbridge, Alberta, Canada T1J 3Z4 Aquatic Ecosystem Protection Research Division, Water Science and Technology Directorate, National Water Research Institute (NWRI), Environment Canada, Box 5050, Burlington, Ontario, Canada L7R 4A6 c Alberta Environment, 2938 11 St. N.E., Calgary, Alberta, Canada T2E 7L7 d Water Air and Climate Change Bureau, Health Canada, 269 Laurier Ave W, Ottawa, Ontario, Canada K1A 0K9 e Agriculture and Agri-Food Canada, Box 3000, Lethbridge, Alberta, Canada T1J 4B1 f University of Lethbridge, Biological Sciences Department, 4401 University Drive West, Lethbridge, Alberta, Canada T1K 3M4 g Agriculture and Agri-Food Canada, 1391 Sandford Street, London, Ontario, Canada N5V 4T3 h Laboratory for Foodborne Zoonoses, Public Health Agency of Canada, 110 Stone Rd. W, Guelph, Ontario, Canada N1G 3W4 b
article info
abstract
Article history:
Campylobacter spp., Salmonella enterica, and Escherichia coli O157:H7 isolated from 898 faecal,
Received 10 June 2010
43 sewage, and 342 surface water samples from the Oldman River were characterized using
Received in revised form
bacterial subtyping methods in order to investigate potential sources of contamination of
29 September 2010
the watershed. Among these pathogens, Campylobacter spp. were the most frequently
Accepted 1 October 2010
isolated from faecal, sewage, and surface water samples (266/895, 11/43, and 91/342, respectively), followed by Salmonella (67/898, 8/43, and 29/342, respectively), and E. coli O157:H7 (16/898, 2/43, and 8/342, respectively). Salmonella Rubislaw was the most common
Keywords:
serovar isolated from water. This serovar was also isolated from two wild bird species.
Comparative genomic fingerprinting
Most other serovars isolated from water were either not isolated from animals or were
flaA
isolated from multiple species. E. coli O157:H7 was predominantly isolated from cattle. The
PFGE
most common phage-types of this pathogen from cattle were also the most common
Phage-type
among water isolates, and there were exact pulsed field gel electrophoresis and compar-
Serovar
ative genomic fingerprint matches between cattle, sewage, and water isolates. Campylobacters were commonly isolated from surface waters and faeces from most animal species.
Abbreviations: BB, Bolton’s broth; BPW, buffered peptone water; CGF, comparative genomic fingerprinting; PFGE, pulsed field gel electrophoresis; PT, phage-type; RFLP, restriction fragment length polymorphism; UPGMA, unweighted pair group method with arithmetic mean; VTEC, verotoxin-producing E. coli. * Corresponding author. Tel.: þ1 403 382 5514; fax: þ1 403 381 1202. E-mail addresses:
[email protected] (C. Jokinen),
[email protected] (T.A. Edge),
[email protected] (W. Koning),
[email protected] (D. Medeiros),
[email protected] (J. Miller),
[email protected] (J.E. Thomas),
[email protected]. ca (E. Topp),
[email protected] (K. Ziebell),
[email protected] (V.P.J. Gannon). 1 Retired from: Water Air and Climate Change Health Bureau, Health Canada, 269 Laurier Ave W, Ottawa, Ontario, Canada, K1A 0K9. 0043-1354/$ e see front matter ª 2010 Published by Elsevier Ltd. doi:10.1016/j.watres.2010.10.001
1248
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 4 7 e1 2 5 7
Restriction fragment length polymorphism of the Campylobacter flaA gene identified several location and host species-specific (cattle, goose, pig) fingerprints. Molecular subtyping of these bacterial pathogens shows considerable promise as a tool for determining the sources of faecal pollution of water. ª 2010 Published by Elsevier Ltd.
1.
Introduction
Waterborne disease is a significant cause of morbidity and mortality worldwide (Hrudey and Hrudey, 2007; Yoder et al., 2008b). While much of this waterborne disease can be traced to contamination of water with human waste, in many regions animal waste in water can also represent a significant human health risk. Bacterial pathogens derived from animal waste such as Campylobacter jejuni, non-typhoid Salmonella enterica, and Escherichia coli O157:H7 are the most frequently associated with waterborne disease outbreaks in the United States (Yoder et al., 2008a and 2008b). Illness associated with these agents has resulted from inadequate treatment of contaminated drinking water supplies such as wells, contaminated surface waters used for recreation, and water used in the irrigation of fruits and vegetables (Yoder et al., 2008a). Many small communities within southern Alberta rely on the Oldman River for drinking water, recreation, and irrigation of field crops. This region has high levels of mixed animal agriculture and one of the highest incidences of gastroenteritis in Canada (Khakhria et al., 1996). Knowledge of the frequency of occurrence of the three most important zoonotic, bacterial pathogens (C. jejuni, S. enterica, and E. coli O157:H7) in surface water would be helpful in determining the human health risks associated with accidental consumption of this water. Differences in the isolation rates of these specific pathogens from animal waste would help to identify whether certain animal species may present a greater risk to human health than others. Finally, the discovery of common pathogenic subtypes in animal waste and water would provide evidence for specific animal sources of these pathogens. In this study the distribution of these three important zoonotic pathogens was determined, and the subtypes of these pathogens isolated in animal faecal sources, untreated human sewage, and flowing surface waters of the Oldman River watershed in southern Alberta, Canada were compared.
2.
Methods
2.1.
Study area
The study area is located in a semi-arid region within the Oldman River drainage basin of southern Alberta, and occupies approximately 26,000 km2. It is the region’s principle source of water used for agriculture, maintenance of livestock operations, recreation, and residential purposes in both rural and urban centres. Flowing surface waters in the basin are influenced by mountain snowmelt, rainfall runoff, and tile drainage (Koning et al., 2006).
2.2.
Water and faecal sample collection
From July 2005 to November 2007, a total of 342 surface water samples were collected from nine different sites within the Oldman River basin and analysed for the presence of three pathogens, Campylobacter spp., E. coli O157:H7, and Salmonella spp. No water samples were collected from December to March in any year. Using gloves and hip waders, water samples were collected approximately 1e2 m from shore by submersing a sterile, polyethylene glycol bottle through the water column at a depth of 20e30 cm. From May 2004 to November 2007, a total of 43 untreated human sewage samples were collected from the Fort Macleod sewage treatment plant and 898 faecal samples (buffalo, n ¼ 7; cattle, n ¼ 215; goat, n ¼ 33; sheep, n ¼ 82; deer, n ¼ 113; chicken, n ¼ 77; duck, n ¼ 38; goose, n ¼ 81; pelican, n ¼ 19; other birds, n ¼ 25; horse, n ¼ 80; pig, n ¼ 57; cat, n ¼ 14; dog, n ¼ 36; human, n ¼ 16; small mammals, n ¼ 5) were collected from domestic and wild animal species within the watershed and analysed for the same pathogens as were the water samples. Faecal samples were collected from the ground. An attempt was made to collect fresh samples; however, it was difficult to ensure freshness of wildlife faecal samples. Following collection, all samples were placed on ice. Water samples were processed within 24 h of collection and faecal samples were processed within 6 h. Animal faecal samples that were collected from the same municipal district or county were considered to be from the same geographic location in the analysis.
2.3. Processing of faecal and water samples for pathogen detection and confirmation Approximately 5 g of faecal matter and 5 mL of phosphate buffered saline (PBS; 137 mM NaCl, 8.1 mM Na2HPO4, 1.5 mM KH2PO4, 2.7 mM KCl, pH 7.4) were mixed together to form a uniform slurry. One-millilitre aliquots of the PBS-faecal samples were added to 20 mL of buffered peptone water (BPW; Oxoid Ltd., Basingstoke, Hampshire, England) for the preenrichment of E. coli O157:H7 (Chapman et al., 1994) and Salmonella spp. (D’Aoust and Purvis, 1998), and to 20 mL of Bolton’s broth supplemented with 20 mg L1 cefoperazone, 20 mg L1 vancomycin, 20 mg L1 trimethoprim, 50 mg L1 cycloheximide, and 5% lysed horse blood (BB; Oxoid Ltd., Basingstoke, Hampshire, England) for the enrichment of Campylobacter spp. (Diergaardt et al., 2004). Water sample filtration, as well as the enrichment, isolation, and confirmation of Campylobacter spp., Salmonella spp., and E. coli O157:H7 were carried out for water and faecal samples according to Jokinen et al. (2010).
1249
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 4 7 e1 2 5 7
2.4.
Subtyping of faecal and waterborne pathogens
Serotyping of Salmonella isolates was performed by the Public Health Agency of Canada, Laboratory for Foodborne Zoonoses, at the Office International des E´pizooties Salmonella Reference Laboratory in Guelph, Ontario. Serotyping and verotoxin detection of E. coli O157:H7 isolates was carried out at the Verotoxin-Producing E. coli (VTEC) Reference Laboratory in Guelph, Ontario, at the Public Health Agency of Canada, Laboratory for Foodborne Zoonoses. Phage-typing of E. coli O157:H7 isolates was carried out as described by Ahmed et al. (1987) and extended by Khakhria et al. (1990). Two different advanced molecular methods, PFGE (pulsed field gel electrophoresis) and CGF (comparative genomic fingerprinting), were also used to type the E. coli O157:H7 isolates. PFGE of these isolates was carried out according to the Centers for Disease Control and Prevention manual standard PFGE protocol (www. cdc.gov/pulsenet). Genomic DNA was digested with XbaI (Invitrogen, Burlington, ON) and analysed in 1% Seakem Gold agarose gels (Lonza, Rockland, ME USA) in 0.5 TBE buffer at 14 C using the CHEF DRIII system (Bio-Rad, Mississauga, ON) with the following parameters; switch time of 2.2 and 54.2 s, angle of 120 , voltage 200 V and a temperature of 14 C. The XbaI-digested DNA from S. enterica Braenderup H9812 was used as a molecular size marker. Each unique banding pattern (fingerprint) is based on at least a single band difference between strains. CGF of the E. coli O157:H7 isolates was performed according to the methods of Laing et al. (2008). Briefly, the E. coli O157:H7 CGF tests for the presence or absence of 23 loci, which were previously found to be highly variable in the E. coli O157 genome. The binary (0 and 1) results for the 23 loci serve as the fingerprint for each strain and the relatedness among strains can be determined by assessing their similarity of loci presence/absence. CGF has been used to identify epidemiologically related strains from endemic strains and to identify genomic differences within epidemiologically related strains. A randomly chosen subset of the Campylobacter isolates obtained from water (62 isolates) and faecal samples (253 isolates) were analysed using restriction fragment length polymorphism (RFLP) typing of the flaA gene according to the methods of Nachamkin et al. (1993) and Harrington et al. (2003). For all pathogens, isolates obtained from the same sample with identical serovars and/or fingerprints were removed from the analyses.
of the high resolution of CGF (Laing et al., 2008), clusters were assigned at the 95% similarity level, allowing for a one locus difference (i.e. 1/23, 4.3%) between isolates in the same cluster. Any isolates with two or more differences were assigned to different clusters. A host species-specific cluster was defined as a group containing one or more isolates from the same host source with 95e100% similarity in their fingerprints. A host group-specific cluster was defined as a group containing one or more isolates from biologically similar groups of animals such as ruminants or birds.
3.
Results
Of the three pathogens analysed in this study, Campylobacter was most frequently detected in animal faecal samples (266/895, 29.7%), untreated human sewage (11/43, 25.6%), and surface water (91/342, 26.6%), followed by Salmonella spp. (67/898, 7.5%; 8/43, 18.6%; and 29/342, 8.5%, respectively) and E. coli O157:H7 (16/898, 1.8%; 2/43, 4.7%; and 8/342, 2.3%, respectively; Fig. 1).
3.1.
Campylobacter spp. distribution
A total of 266 faecal samples from 16 different animal species, 11 untreated human sewage samples, and 91 water samples were positive for Campylobacter spp. (Figs. 1 and 2). The majority of these isolates were identified as C. jejuni (279/368, 75.8%), while C. coli and other Campylobacter spp. accounted for 17.9% (66/368) and 9.2% (34/368), respectively (Fig. 3). More than one species of Campylobacter was isolated from only a small proportion of the water (4/91, 4.4%) and faecal (7/266, 2.6%) samples (data not shown). C. jejuni was isolated at least once from each of the 18 different sources. In contrast, C. coli was isolated at least once from seven different animal species, human sewage, and water, and Campylobacter spp. other than C. coli or C. jejuni were isolated at least once from six different animal species, human sewage, and water. C. jejuni was isolated at the greatest frequency from all sources with the exception of deer and pig faeces. C. coli and ‘other’ Campylobacter spp. were isolated at the greatest frequency from pig and deer faeces, respectively.
32
Analysis of fingerprint data
Cluster analyses of the Campylobacter spp. flaA-RFLP profiles and the E. coli O157:H7 PFGE banding patterns were performed with Bionumerics (Version 5.1, Applied Maths, BVBA, Austin, TX) using the UPGMA clustering algorithm and the dice similarity coefficient with an optimization of 1.5% and a tolerance of 1.5%. A cluster was defined as a group of C. jejuni isolates with identical flaA-RFLP fingerprints (banding patterns), or a group of E. coli O157:H7 isolates with identical PFGE fingerprints (banding patterns). Any isolates with at least a single band difference between strains were assigned to different clusters. Hierarchical clustering of the CGF data was performed with the statistical package “R” using the hclust method with Euclidean distance and average linkage. Because
28 Isolation R ate (%)
2.5.
24 20 16 12 8 4 0 Campylobacter spp.
Salmonella spp.
E. coli O157:H7
Fig. 1 e Percentage (%) of animal faecal (n [ 898, white), sewage (n [ 43, grey), and surface water (n [ 342, black) samples positive for Campylobacter spp., Salmonella spp., and E. coli O157:H7. Samples were collected from the Oldman River watershed. 895 animal faecal samples were analysed for Campylobacter spp.
1250
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 4 7 e1 2 5 7
Other birds Dog Pelican Cat Human
Type of Animal Faeces
Horse Deer Goat Goose Gull Sheep Duck Pig Cattle Chicken Turkey Buffalo 0
5
10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Isolation Rate (%)
Fig. 2 e Percentage (%) of animal faecal samples positive for Campylobacter spp. (white), Salmonella spp. (grey), and E. coli O157:H7 (black). Only those faecal sources from which pathogens were isolated are included. (Other birds, n [ 19; Dog, n [ 36; Pelican, n [ 19; Cat, n [ 14; Human, n [ 16; Horse, n [ 80; Deer, n [ 112; Goat n [ 33; Goose, n [ 80; Gull, n [ 3; Sheep, n [ 74; Duck, n [ 38; Pig, n [ 57; Cattle, n [ 199; Chicken, n [ 75; Turkey, n [ 3; Buffalo, n [ 7).
3.2.
C. jejuni flaA-RFLP typing
Two hundred and fifty three C. jejuni isolates, each obtained from different animal faecal samples, were further characterized via RFLP of the flaA gene. Approximately 40% of these faecal isolates (102/253) grouped into various host speciesspecific or host group-specific (e.g. birds) clusters (Table 1). The remaining isolates were “singletons” that did not form clusters (75/253), or they were grouped into mixed-species clusters (76/253). With respect to the host species-specific clusters, some RFLP fingerprints appeared to be unique to specific geographic areas, whereas other fingerprints were observed in more than one geographic area. Where geographic location is known (11/ 22, 50.0%), five clusters (45.5%) included animals of the same species sampled from different locations, while 6 clusters (54.5%) included different animals of the same species sampled from the same geographic location. The same fingerprints were also detected over long periods of time. Eleven of the 22 host species-specific clusters (50.0%) contained isolates obtained from animals sampled on different days, separated by months and up to three years. The remaining 11 (50.0%) clusters contained isolates obtained from animals of the same species sampled on the same day. Of the C. jejuni isolates obtained from water samples, 62 isolates were further characterized via RFLP of the flaA gene. Evidence of overlap between water and faecal clusters was
observed (Fig. 4). Thirty-nine percent of the water isolates (24/ 62) grouped with at least one faecal isolate, resulting in eight faecal-water clusters. Three of these clusters contained water and mixed-species faecal isolates (data not shown). The remaining water isolates did not cluster with any faecal isolates but instead formed water-only clusters (22/62, 6 clusters) or were singletons (16/62). Five clusters contained both water and either cattle-specific, goose-, duck and goose-, or pig-specific faecal isolates, accounting for 16/62 (25.8%) water isolates and 12/253 (4.7%) faecal isolates. Some of the water-only clusters contained isolates with identical fingerprints from the same site detected over 3 years (data not shown). There were also water-only clusters that contained isolates with identical fingerprints from different sites over three months, and also between different sites on the same sampling date.
3.3. Distribution and molecular typing of S. enterica subsp. enterica High serovar diversity was observed among the Salmonella spp. isolates from faecal, sewage, and water sources (Table 2). Of the faecal samples from which at least one of the three pathogens was isolated, Salmonella spp. were not isolated from dog, cat, human, deer, goat, or buffalo faeces (Fig. 2). Among the samples positive for Salmonella spp., a total of 36 different serovars were observed (Table 2). Twenty-six different Salmonella serovars were isolated from animal faeces, five
1251
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 4 7 e1 2 5 7
Water Sewage Pig Deer Turkey Goat Duck
Source
Goose Cattle Dog Pelican Cat Human Horse Gull Sheep Chicken Buffalo 0
10
20
30
40
50
60
70
80
90
100
Isolation Rate (%) Fig. 3 e Distribution (%) of Campylobacter jejuni (white), C. coli (grey), and other Campylobacter spp. (black) isolated from animal faecal, sewage, and surface water samples collected from the Oldman River watershed. Samples containing more than one species of Campylobacter are indicated by a white bar. Only those sources from which Campylobacter spp. were isolated are included. (Water, n [ 91; Sewage, n [ 11; Pig, n [ 25; Deer, n [ 22; Turkey, n [ 2; Goat, n [ 7; Duck, n [ 16; Goose, n [ 21; Cattle, n [ 88; Dog, n [ 1; Pelican, n [ 1; Cat, n [ 1; Human, n [ 2; Horse, n [ 10; Gull, n [ 1; Sheep, n [ 29; Chicken, n [ 34; Buffalo, n [ 6).
different serovars were isolated from untreated human sewage, and 11 different serovars were isolated from surface water samples. More than one serovar was isolated from each Salmonella-positive source with the exception of horse faeces. Very little overlap between sources of specific Salmonella spp. serovars was observed, since more than 80% (29/36) of the serovars detected were isolated from single sources (Table 2). However, five serovars were isolated from multiple faecal sources (Serovars Give variant 15þ, Hadar, Heidelberg, Indiana, and Typhimurium variant Copenhagen) and four serovars were isolated from at least one animal species or untreated human sewage sample, as well as from water (Serovars Give variant 15þ, Heidelberg, Rubislaw, and I:11:r:-). Serovar Rubislaw was isolated at the greatest frequency from water (21/29, 72.4%) and was also isolated from sparrow and swallow faeces. In addition to water, serovar Give var. 15þ was isolated from bird (goose, duck, gull, and sparrow) and ruminant (sheep and cattle) faeces, serovar Heidelberg was isolated from untreated human sewage and chicken, pig, and horse faeces, and I:11:r:- was isolated from cattle faeces.
3.4. Distribution of phage-types (PTs) among E. coli O157:H7 isolates Cattle were the primary source of E. coli O157:H7 isolates examined in this study (Fig. 2). Five different PTs were identified among the E. coli O157:H7 isolates (Table 3). The two PTs identified at the greatest frequency (PT 14a and PT 8) were isolated from both water and faecal sources. PT 8 was isolated from water and cattle faeces only, while PT 14a was isolated from each of the E. coli O157:H7 sources, with the exception of goose faeces. Although PT 14a was isolated from duck faeces and sewage, this PT was identified in more than 78% of the cattle faecal isolates. The remaining three PTs (PT 21, PT 33, and PT 34) were each isolated from only one source (goose, water, and cattle faeces, respectively).
3.5.
E. coli O157:H7 CGF and PFGE typing
E. coli O157:H7 isolates from water (n ¼ 8), faecal (n ¼ 16), and sewage (n ¼ 2) were further characterized by CGF and PFGE
1252
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 4 7 e1 2 5 7
Table 1 e Analysis of Campylobacter jejuni sources among clusters obtained by flaA-RFLP. Isolates were obtained from animal faeces collected from the Oldman River watershed. The number of samples refers to discrete faecal samples obtained from separate sampling events. Only results for clusters containing multiple faecal isolates are shown. Cluster #
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
Sample type
No. samples
Isolated from same geographic area?
Isolated on same date?
Buffalo Cattle Cattle Cattle Cattle Cattle/Deer Sheep Sheep Cattle/Sheep Cattle/Sheep Chicken Chicken Chicken Chicken Chicken Goose Goose Duck/Goose Duck/Goose Pig Pig Pig
2 4 3 3 7 1/1 7 2 10/5 3/2 5 9 4 2 2 3 4 4/4 2/1 8 2 2
na N na Y N na Y Y Y na na Y na na na N na N na N na Y
Y Nb Y Y Na Na Na Na Nb Nc Y Y Y Y Y Na Y Na Nb Nb Y Y
Y, yes; N, no; na, municipal district/county information not available; In order to be assigned a “Y”, all isolates within the same cluster must have been isolated from the same geographic area or isolated on the same date. Samples were collected over: a Different months of the same year. b Two different years. c Three different years.
fingerprinting. Both CGF 95% and PFGE yielded five clusters containing more than one E. coli O157:H7 isolate. One of the five clusters contained only water isolates (data not shown), and four of the clusters contained faecal isolates (Table 4). The remaining isolates did not group into any of these five clusters and had unique fingerprints (singletons). The multi-isolate clusters were generally comprised of the same isolates regardless of the typing method used; i.e. there was 85% concordance between the PFGE and CGF data (Table 4). Clusters 2 and 3 contained the same cattle isolates regardless of the method used. Isolates from two different PFGE clusters (clusters 1 and 4) grouped into only one CGF 95% cluster (cluster 1). The main difference between the two methods was that the members of a CGF 95% cluster (cluster 4), containing 3 cattle isolates and one duck isolate, were all singletons according to PFGE. When overlap between faecal and water isolates was examined (Fig. 5), both methods identified a cluster that contained water, cattle, and sewage isolates (cluster 1), and also a cluster that contained both cattle and water isolates (cluster 2). All isolates with the same fingerprint
were also of the same PT with the exception that one CGF cluster contained isolates from PT 8 and 14a (Table 4). Both methods identified the same fingerprint in two different cattle from the same geographic area (cluster 3), which was not found in animals from any other locations (Table 4). Another unique CGF fingerprint was observed in two animals of different species that were obtained from the same geographic area (cluster 4). With respect to sampling dates, identical fingerprints were obtained from more than one sample collected on the same day and also during different months of the year (Table 4).
4.
Discussion
The primary objectives of this work were to examine the distribution of Campylobacter spp., S. enterica, and E. coli O157:H7 in human, wildlife, and livestock faecal sources, to compare subtypes of these pathogens to those isolated from surface water samples, and finally, to determine if animal host species-specific subtypes could be detected in these surface waters. Pathogen subtyping is used by public health laboratories around the world to determine the relatedness of pathogens in disease outbreak investigations (Swaminathan et al., 2001); therefore, we also wanted to assess the usefulness of molecular typing in determining the relatedness of pathogens identified in faecal sources. Salmonella spp. serotyping has been shown to be an invaluable tool in epidemiological surveillance. It can provide information about serovar distribution in animals and humans, and how this distribution changes over time or during different seasons (van Duijkeren et al., 2002). This information in turn may be useful in the development of risk assessment models. Salmonella spp. serotyping has also demonstrated potential in pinpointing specific locations of contaminating sources in the pre-harvest turkey production environment (Nayak and Stewart-King, 2008). In the current study, the overlap between Salmonella serovars isolated from water and faecal samples identified several possible sources of contamination, including chickens, geese, ducks, sparrows, swallows, pigs, sheep, cattle, horses, and human sewage. Salmonella serovar Rubislaw was the most prevalent serovar isolated from water samples. It was also isolated once from a swallow and once from a sparrow; however, since only four birds were sampled, it is difficult to determine the significance of these isolations with respect to the high frequency of isolation of this serovar from water. According to five years of province-wide laboratory surveillance data from Canada (for an example, see Demczuk and Pankhurst, 2007), serovar Rubislaw has rarely been isolated from non-human sources in any province other than Alberta. Throughout 2000e2001, serovar Rubislaw was the most commonly isolated (52.4%) Salmonella serovar from irrigation canals and reservoirs located within the Oldman River watershed in Alberta (Gannon et al., 2004), suggesting that a significant source of serovar Rubislaw is contributing to the contamination of water specifically in the Oldman River watershed. However, the source of this serovar is not yet clear, nor do we know if there is a geographically isolated source of contamination, or if serovar Rubislaw
1253
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 4 7 e1 2 5 7
n = 3, 33%
n = 6, 67%
n = 4, 67%
Cluster 4 Sources:
water
n =1, 25%
n = 2, 33%
n = 3, 75%
Cluster 17 Sources:
cattle
water
Cluster 19 Sources:
goose
water
n = 1, 50%
n = 1, 14%
n = 1, 50%
n = 6, 86% Cluster 23 Sources:
water
duck / goose
Cluster 24 Sources:
cattle
water
pig
Fig. 4 e Overlap of water and faecal sources of Campylobacter jejuni among clusters obtained by flaA-RFLP. The number of samples refers to discrete water and/or faecal samples obtained from separate sampling events. Clusters 23 and 24 contained singleton faecal samples.
contamination of water is widespread and also occurs in other watersheds. Alternatively, there were many serovars isolated from various animal faecal samples that were not isolated from any of the water samples. This may suggest that certain animals were not important contributing sources of faecal contamination of the surface waters during the sampling periods in this study. While the current study used identical culture-based methods for the isolation of Salmonella from both water and faeces, factors such as cultivation bias have been shown to significantly skew the serovar-specific Salmonella selective isolation frequencies (Singer et al., 2009). Although it would be best to use both culture-based and culture-independent methods of Salmonella detection, there are advantages and disadvantages inherent to both approaches (Girones et al., 2010). Campylobacter isolates obtained from water and faecal samples in the current study were characterized using RFLP of the flaA gene. This method was chosen because it has been used successfully to discriminate between outbreak strains (Nachamkin et al., 1993), and recently has also shown to be useful in epidemiological surveillance (Huang et al., 2009). While MLST (multilocus sequence typing) is considered the gold standard for Campylobacter spp. typing, it is a laborious and costly procedure. RFLP of the flaA gene appears to be a suitable preliminary typing method (O’Reilly et al., 2006), and may also serve as an alternative to MLST when used in routine surveillance (Djordjevic et al., 2007). C. jejuni is readily isolated from surface waters and a variety of animal hosts (Jokinen et al., 2010), and several host species-specific flaA-RFLP clusters were generated in the
current study, demonstrating that this method of subtyping may be useful in the identification of various animal sources of faecal contamination including buffalo, cattle, sheep, chickens, geese, pigs, and birds. Specifically, C. jejuni isolates from water that clustered with host species-specific faecal isolates identified cattle, pigs, ducks, and geese as possible sources of water contamination. Sixty-one percent of the water isolates typed by RFLP of the flaA gene did not cluster with any of the faecal isolates in this study. This suggests that animal species not tested in this study (possibly certain other wild species) are contributing to surface water contamination by Campylobacter, although it is also possible that a larger sample size of the domestic and wild animal species sampled in this study would have increased the number of matching animal and water isolate flaA-RFLP profiles. Of the host species-specific flaA-RFLP clusters identified, some were obtained from different animals from the same geographic area, suggesting that this method of typing may be useful not only in identifying the species of animal that shed the organism but also specific sites and groups of animals responsible for contamination of water by these pathogens. There were also examples of clusters containing isolates from the same species of animal obtained at different times throughout the three-year sampling period, suggesting that flaA profiles persist over time. Other molecular subtyping techniques, such as MLST have identified location and species-specific clusters of Campylobacters (Ragimbeau et al., 2008; French et al., 2009; Hannon et al., 2009; Huang et al., 2009). Although flaA-RFLP may not be
1254
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 4 7 e1 2 5 7
Table 2 e Distribution (%) of Salmonella serovars isolated from animal faeces, sewage, and surface water collected from the Oldman River watershed. Serovars isolated from both water and faecal sources are highlighted grey. Only those sources from which Salmonella species were isolated are included. (Chicken, n [ 14; Goose, n [ 8; Duck, n [ 3; Pelican, n [ 5; Other Bird, n [ 6; Cattle, n [ 2; Sheep n [ 18; Horse n [ 1; Pig, n [ 10; Sewage, n [ 8; Water, n [ 29). Chicken Goose Duck Pelican Other birdb Cow Sheepc Horse Pig Sewage Water
Source Salmonella enterica serovar distribution (%)
Anatum Bovismorbificans Bradford Brandenburg Bredeney Derby Give var. 15þ Hadar Heidelberg I:11:r:IIIb:61:-:1,5 Indiana Infantis Mbandaka Muenchen Rubislaw Saintpaul Senftenberg Stanley Tennessee Typhimurium Typhimurium Copenhagen Othera >1 Serovar
14 30 10 20 13 25
33
29 50
50
100
7 3
6
80 100
20
38 50
50
3 21
89 50
33
17 10 3 13 33
72
25 3 13 20 3 33 21 14
13 25
10 40 20
17
50
11 6
20 10
13 25
10 24
a Includes 14 ‘other’ serovars. b Includes gull, sparrow, swallow, and vulture. c Serovar data not available for one sample.
as discriminatory as other multilocus typing methods, we were still able to identify source-specific clusters. Phage-typing of E. coli O157:H7 is often used in conjunction with higher resolution molecular typing techniques such as PFGE (Karmali et al., 2010) in order to help with the interpretation of PFGE data or to eliminate further analyses of isolates unrelated to those implicated in an outbreak. In the current study we applied phage-typing, PFGE fingerprinting, and CGF of isolates in order to assess whether or not the E. coli O157:H7 PTs and/or molecular fingerprints detected in human and
Table 3 e Distribution of E. coli O157:H7 PTs isolated from animal faeces, sewage, and surface water collected from the Oldman River watershed. PTs isolated from both water and faecal sources are highlighted grey. Only those sources from which E. coli O157:H7 species were isolated are included. E. coli O157:H7 Phageetype Distribution (No.) Source 8 Duck Goose Cow 2 Sewage Water 4
14a 1
21
33
34
No PT Data
>1 PT
1 11 1 4
1 1
1 1
2
animal faeces could also be detected in surface waters within the same watershed. Results from the present study as well as other research suggest that various E. coli O157:H7 PTs and molecular fingerprints are widespread in the environment (Zhang et al., 2007; Laing et al., 2008); and while it is accepted that cattle are the primary reservoir of E. coli O157:H7, this pathogen may also be isolated occasionally from other animal species and the environment (Oporto et al., 2008; La Ragione et al., 2009). The most common PTs of this pathogen were observed in both cattle and water isolates, and there were exact matches of molecular fingerprints between sewage, cattle, and water isolates. Molecular fingerprinting of E. coli O157:H7 may also provide valuable information on the distribution and persistence of fingerprints at specific locations over time. Results of this study suggest that molecular fingerprinting can provide more precise information that may also be useful in pinpointing the source(s) responsible for contamination of water. This study showed that identical fingerprints could be isolated from different cattle from the same geographic area which were distinct from those fingerprints obtained from cattle from other geographic areas. Identical fingerprints were also obtained from animals and specific surface water sampling locations which were distinct from isolates obtained from any other animals and surface water sampling locations. This study also demonstrated that both CGF and PFGE could
1255
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 4 7 e1 2 5 7
Table 4 e Analysis of E. coli O157:H7 sources among clusters obtained by PFGE fingerprints and CGF. Isolates were obtained from animal faeces and sewage collected from the Oldman River watershed. The number of samples refers to discrete water and/or faecal samples obtained from separate sampling events. Cluster #
Sample type
No. samples
PFGE, 100%
1 2 3 4
cattle/sewage cattle cattle cattle
2/1 1 2 2
CGF, 95%
1 2 3 4
cattle/sewage cattle cattle cattle/duck
5/1 1 2 3/1
Phage-type
Isolated from same geographic area?
Isolated on same date?
14a 14a 14a 14a
na e Y na
N e Y Y
8, 14a/14a 14a 14a 14a
na e Y Y
N e Y N
Y, yes; N, no; na, municipal district/county information not available; –, not applicable. Only results for clusters containing multiple faecal isolates are shown. In order to be assigned a “Y”, all isolates within the same cluster must have been isolated from the same geographic area or isolated on the same date.
generate identical clusters, supporting the use of CGF as an alternative to PFGE (Laing et al., 2008). An interesting finding from our CGF analysis is that although clustering at 95% stringency yielded host speciesspecific clusters that could be useful for determining sources of contamination, analysis at 100% stringency provided enhanced discrimination that could, in addition, allow the separation of isolates by date and geographic location. High resolution genotyping methods such as CGF allow the stringency of clusters to be adjusted depending on the objective,
and they could prove to be useful in pinpointing specific groups of animals or sources of faecal contamination. Although CGF of E. coli O157:H7 isolates shows promise, the inherent deficiency in using this particular organism for determining sources of faecal contamination is its low prevalence in surface waters and its limited host range. It may also be possible, however, to apply similar high-resolution molecular typing techniques such as CGF to organisms which are more prevalent and have a broader host range such as Campylobacter spp., to identify other species sources of surface
A n = 1,
n = 1,
25%
50% n = 2,
n = 1,
50%
50%
n = 1, 25% PFGE Cluster 2 Sources:
PFGE Cluster 1 Sources: cattle
sewage
water
cattle
water
B n = 2, 25%
n = 1, 50% n = 1, 50%
n = 1,
n = 5,
13%
63% CGF Cluster 1 Sources:
cattle
sewage
CGF Cluster 2 Sources: water
cattle
water
Fig. 5 e Overlap of water and faecal sources of E. coli O157:H7 among clusters obtained by PFGE fingerprinting (A) and corresponding CGF profiles (B). The number of samples refers to discrete water and/or faecal samples obtained from separate sampling events.
1256
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 4 7 e1 2 5 7
water contamination by identifying location- and sourcespecific clusters of the organism.
5.
Conclusions
From the current study, the following conclusions can be drawn: The high prevalence of zoonotic pathogens in domestic animal faeces, municipal sewage, and in flowing waters found in this watershed underlines the risks to human health associated with exposure to these potential sources of infection. Bacterial pathogen subtyping has the potential to identify not only host species sources, but also the location and/or specific groups of animals that are the sources of water contamination. This specific information may in many cases be more helpful and effective in watershed management than simply determining the animal species responsible for contamination.
Acknowledgements This study was funded in part by the Agriculture Policy Framework’s National Water Quality Surveillance Research Initiative through an agreement between Agriculture and Agri-Food Canada and Health Canada; Environment Canada under the National Agricultural Environmental Standards Initiative (NAESI); and the Public Health Agency of Canada. The authors thank Ray Walker of Alberta Environment and Bruce Beasley of Agriculture and Agri-Food Canada for their sampling contributions. We would also like to thank Steven Mutschall, Allison Kindt, Anita James, Susan Ross, Rommy Rodriguez, and Garrett Kennedy of the Public Health Agency of Canada for their excellent assistance with laboratory analyses. We would like to thank Linda Cole, Betty Wilkie, Ketna Mistry and Ann Perets of the OIE Salmonella Reference Laboratory, as well as Irene Yong and Nina Enriquez of the E. coli Reference Laboratory of the Public Health Agency of Canada in Guelph, Ontario, for serotyping and PFGE analysis of isolates.
references
Ahmed, R., Bopp, C., Borczyk, A., Kasatiya, S., 1987. Phage-typing scheme for Escherichia coli O157:H7. J. Infect. Dis. 155 (4), 806e809. Chapman, P.A., Wright, D.J., Siddons, C.A., 1994. A comparison of immunomagnetic separation and direct culture for the isolation of verocytotoxin-producing Escherichia coli O157 from cattle faeces. J. Med. Microbiol. 40 (6), 424e427. D’Aoust, J.Y., Purvis, U., 1998. Isolation and Identification of Salmonella from Foods. Health Protection Branch Method MFHPB-20. Health Protection Branch. Demczuk, W., Pankhurst, R., 2007. Laboratory Surveillance Data for Enteric Pathogens in Canada: Annual Summary 2006.
Public Health Agency of Canada, National Microbiology Laboratory for Enteric Pathogens, Winnipeg, Manitoba, ISBN 978-0-662-46900-1. Catalogue No.: HP57-1/2006E-PDF. Diergaardt, S.M., Venter, S.N., Spreeth, A., Theron, J., Brozel, V.S., 2004. The occurrence of Campylobacters in water sources in South Africa. Water Res. 38 (10), 2589e2595. Djordjevic, S.P., Unicombe, L.E., Adamson, P.J., Mickan, L., Rios, R. the Australian Campylobacter Subtyping Study Group, 2007. Clonal complexes of Campylobacter jejuni identified by multilocus sequence typing are reliably predicted by restriction fragment length polymorphism analyses of the flaA gene. J. Clin. Microbiol. 45 (1), 102e108. French, N.P., Midwinter, A., Holland, B., Collins-Emerson, J., Pattison, R., Colles, F., Carter, P., 2009. Molecular epidemiology of Campylobacter jejuni isolates from wild-bird fecal material in children’s playgrounds. Appl. Environ. Microbiol., 779e783. Gannon, V.P.J., Graham, T.A., Read, S., Ziebell, K., Muckle, A., Mori, J., Thomas, J., Selinger, B., Townshend, I., Byrne, J., 2004. Bacterial pathogens in rural water supplies in southern Alberta. J. Toxicol. Environ. Health A 67 (20), 1643e1653. Girones, R., Ferrus, M.A., Alonso, J.L., Rodriguez-Manzano, J., Calgua, B., de Abreu CorreaHundesa, A., Carratala, A., BofillMas, S., 2010. Molecular detection of pathogens in water e the pros and cons of molecular techniques. Water Res. 44, 4325e4339. Hannon, S.J., Taboada, E.N., Russell, M.L., Allan, B., Waldner, C., Wilson, H., Potter, A., Babiuk, L., Townsend, H.G.G., 2009. Genomics-based molecular epidemiology of Campylobacter jejuni isolates from feedlot cattle and from people in Alberta, Canada. J. Clin. Microbiol. 47 (2), 410e420. Harrington, C.S., Moran, L., Ridley, A.M., Newell, D.G., Madden, R. H., 2003. Inter-laboratory evaluation of three flagellin PCR/ RFLP methods for typing Campylobacter jejuni and C. coli: the CAMPYNET experience. J. Appl. Microbiol. 95 (6), 1321e1333. Hrudey, S.E., Hrudey, E.J., 2007. Published case studies of waterborne disease outbreaksdevidence of a recurrent threat. Water Environ. Res. 79 (3), 233e245. Huang, J.L., Xu, H.Y., Bao, G.Y., Zhou, X.H., Ji, D.J., Zhang, G., Liu, P. H., Jiang, F., Pan, Z.M., Liu, X.F., Jiao, X.A., 2009. Epidemiological surveillance of Campylobacter jejuni in chicken, dairy cattle and diarrhoea patients. Epidemiol. Infect. 137 (8), 1111e1120. Jokinen, C.C., Schreier, H., Mauro, W., Taboada, E., Isaac-Renton, J. L., Topp, E., Edge, T., Thomas, J.E., Gannon, V.P.J., 2010. The occurrence and sources of campylobacter spp., Salmonella enterica and Escherichia coli O157:H7 in the Salmon River, British Columbia, Canada. J. Water Health 8 (2), 374e386. Karmali, M.A., Gannon, V., Sargeant, J.M., 2010. Verocytotoxinproducing Escherichia coli (VTEC). Vet. Microbiol. 140 (3), 360e370. Khakhria, R., Duck, D., Lior, H., 1990. Extended phage-typing scheme for Escherichia coli O157:H7. Epidemiol. Infect. 105 (3), 511e520. Khakhria, R., Woodward, D., Johnson, W., 1996. Salmonella, Shigellae, Pathogenic E. coli, Campylobacter and Aeromonas Identified in Canada: Annual Summary 1994. National Laboratory for Enteric Pathogens, LCDC, Health Canada. Koning, C.W., Saffran, K.A., Little, J.L., Fent, L., 2006. Water quality monitoring: the basis for watershed management in the Oldman River Basin, Canada. Water Sci. Technol. 53 (10), 153e161. La Ragione, R.M., Best, A., Woodward, M.J., Wales, A.D., 2009. Escherichia coli O157:H7 colonization of small domestic ruminants. FEMS Microbiol. Rev. 33 (2), 394e410. Laing, C., Pegg, C., Yawney, D., Ziebell, K., Steele, M., Johnson, R., Thomas, J.E., Taboada, E.N., Zhang, Y., Gannon, V.P., 2008. Rapid determination of Escherichia coli O157:H7 lineage types and molecular subtypes by using comparative genomic fingerprinting. Appl. Environ. Microbiol. 74 (21), 6606e6615.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 4 7 e1 2 5 7
Nachamkin, I., Bohachick, K., Patton, C.M., 1993. Flagellin gene typing of Campylobacter jejuni by restriction fragment length polymorphism analysis. J. Clin. Microbiol. 31 (6), 1531e1536. Nayak, R., Stewart-King, T., 2008. Molecular epidemiological analysis and microbial source tracking of Salmonella enterica serovars in a preharvest turkey production environment. Foodborne Pathog. Dis. 5 (2), 115e126. Oporto, B., Esteban, J.I., Aduriz, G., Juste, R.A., Hurtado, A., 2008. Escherichia coli O157:H7 and non-O157 shiga toxin-producing E. coli in healthy cattle, sheep and swine herds in Northern Spain. Zoonoses Public Health 55 (2), 73e81. O’Reilly, L.C., Inglis, T.J.J., Unicomb, L.the Australian Campylobacter Subtyping Study Group, 2006. Australian multicentre comparison of subtyping methods for the investigation of Campylobacter infection. Epidemiol. Infect. 134 (4), 768e779. Ragimbeau, C., Schneider, F., Losch, S., Even, J., Massong, J., 2008. Multilocus sequence typing, pulsed-field gel electrophoresis, and fla short variable region typing of clonal complexes of Campylobacter jejuni strains of human, bovine, and poultry origins in Luxembourg. Appl. Environ. Microbiol. 74 (24), 7715e7722. Singer, R.S., Mayer, A.E., Hanson, T.E., Isaacson, R.E., 2009. Do microbial and cultivation media decrease the accuracy of Salmonella surveillance systems and outbreak investigations? J. Food Prot. 72 (4), 707e713.
1257
Swaminathan, B., Barrett, T.J., Hunter, S.B., Tauxe, R.V.The CDC PulseNet Task Force, 2001. PulseNet: the molecular subtyping network for foodborne bacterial disease surveillance, United States. Emerg. Infect. Dis. 7 (3), 382e389. van Duijkeren, E., Wannet, W.J.B., Houwers, D.J., van Pelt, W., 2002. Serotype and phage type distribution of Salmonella strains isolated from humans, cattle, pigs, and chickens in the Netherlands from 1984 to 2001. J. Clin. Microbiol. 40 (11), 3980e3985. Yoder, J.S., Hlavsa, M.C., Craun, G.F., Hill, V., Roberts, V., Yu, P.A., Hicks, L.A., Alexander, N.T., Calderon, R.L., Roy, S.L., Beach, M. J., 2008a. Surveillance for waterborne disease and outbreaks associated with recreational water use and other aquatic facility-associated health eventseUnited States, 2005e2006. MMWR CDC Surveill. Summ. 57 (9), 1e29. Yoder, J., Roberts, V., Craun, G.F., Hill, V., Hicks, L., Alexander, N.T., Radke, V., Calderon, R.L., Hlavsa, M.C., Beach, M.J., Roy, S.L., 2008b. Surveillance for waterborne disease and outbreaks associated with drinking water and water not intended for drinkingeUnited States, 2005e2006. MMWR CDC Surveill. Summ. 57 (9), 39e62. Zhang, Y., Laing, C., Steele, M., Ziebell, K., Johnson, R., Benson, A. K., Taboada, E., Gannon, V.P.J., 2007. Genome evolution in major Escherichia coli O157:H7 lineages. BMC Genomics 8 (1), 121 [Online]. Available at: http://www.biomedcentral.com/ content/pdf/1471-2164-8-121.pdf (Accessed 10.07.2009).
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 5 8 e1 2 6 6
Available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Applying an electric field in a built-in zero valent iron e Anaerobic reactor for enhancement of sludge granulation Yiwen Liu, Yaobin Zhang*, Xie Quan, Shuo Chen, Huimin Zhao Key Laboratory of Industrial Ecology and Environmental Engineering, Ministry of Education, School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China
article info
abstract
Article history:
A zero valent iron (ZVI) bed with a pair of electrodes was installed in an upflow anaerobic
Received 16 July 2010
sludge blanket (UASB) reactor to create an enhanced condition to increase the rate of
Received in revised form
anaerobic granulation. The effects of an electric field and ZVI on granulation were inves-
27 September 2010
tigated in three UASB reactors operated in parallel: an electric field enhanced ZVI-UASB
Accepted 2 October 2010
reactor (reactor R1), a ZVI-UASB reactor (reactor R2) and a common UASB reactor (reactor
Available online 19 October 2010
R3). When a voltage of 1.4 V was supplied to reactor R1, COD removal dramatically increased from 60.3% to 90.7% over the following four days, while the mean granule size
Keywords:
rapidly grew from 151.4 mm to 695.1 mm over the following 38 days. Comparatively, COD
Anaerobic reactor
removal was lower and the increase in granule size was slower in the other two reactors (in
Zero valent iron
the order: R1 > R2 > R3). The electric field caused the ZVI to more effectively buffer acidity
Granulation
and maintain a relatively low oxidationereduction potential in the reactor. In addition, the
Electric field
electric field resulted in a significant increase in ferrous ion leaching and extracellular polymeric substances (EPS) production. These changes benefited methanogenesis and granulation. Scanning electron microscopy (SEM) images showed that different microorganisms were dominant in the external and internal layers of the reactor R1 granules. Additionally, fluorescence in situ hybridization (FISH) analysis indicated that the relative abundance of methanogens in reactor R1 was significantly greater than in the other two reactors. Taken together, these results suggested that the use of ZVI combined with an electric field in an UASB reactor could effectively enhance the sludge granulation. Crown Copyright ª 2010 Published by Elsevier Ltd. All rights reserved.
1.
Introduction
Upflow anaerobic sludge blanket (UASB) reactors are considered one of the most effective anaerobic reactors for digestion of organic substances in various effluents (Seghezzo et al., 1998; Lettinga et al., 1993). The presence of granular sludge is a major characteristic of the UASB reactor (Ghangrekar et al., 2005). The excellent settling property of granular sludge leads to a high level of biomass and rich microbial diversity being maintained in the reactor, which leads to high biodegradation efficiency. However, sludge granulation is a long-term process (Hulshoff Pol et al., 1983; Hickey et al., 1991) that generally takes
three to eight months. There has been a great deal of effort to increase the rate at which the granulation process occurs through microbiological, physico-chemical and hydraulic methods (El-Mamouni et al., 1997; Lettinga et al., 1993; Mahoney et al., 1987; Arcand et al., 1994). It was recently reported that multivalent metal ions such as Ca2þ, Mg2þ, Al3þ and Fe2þ could enhance granulation (Mahoney et al., 1987; Schmidt and Ahring, 1993; Yu et al., 2000, 2001a, 2001b) through charge neutralization and double-layer compression that may condense the diffusive double-layers to form a relatively strong effect of van der Waals forces. Moreover, it is believed that these metal ions can bind to extracellular
* Corresponding author. Tel.: þ86 411 84706460; fax: þ86 411 84706263. E-mail address:
[email protected] (Y. Zhang). 0043-1354/$ e see front matter Crown Copyright ª 2010 Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2010.10.002
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 5 8 e1 2 6 6
polymeric substances (EPS) of anaerobic sludge to form more stable complexes, thereby maintaining the integrity of the granules (Rudd et al., 1984; Mahoney et al., 1987). Granular sludge is composed of methanogens, acidogens and other types of microorganisms, among which methanogens present the slowest growth rate and are most influenced by operational conditions. Generally, the successful start-up of an UASB reactor indicates that the reactor has achieved relatively high COD removal efficiency and methane production, which is dependent on methanogenesis. Therefore, granulation can be considered a process that leads to the development of methanogens in the granule (Tiwari et al., 2006). Accordingly, creating a favorable environment for the growth of methanogens in the reactor is essential to accelerating sludge granulation. Zero valent iron (ZVI) is a reducing agent that is expected to help create an enhanced anaerobic environment that may improve the performance of UASB due to its reductive property. When utilized in an anaerobic environment, ZVI can serve as an electron donor to lower oxidationereduction potential (ORP) and buffer acid produced by acidogens, which are crucial to maintain a stable and favorable condition for methanogens. Therefore, we developed a ZVI packed UASB reactor (ZVI-UASB) in our laboratory. Our previous work demonstrated that the ZVI-UASB reactor had higher performance with respect to the removal of COD and color than a normal UASB without the ZVI. Additionally, the performance of the reactor was found to be closely related to the reduction reaction of ZVI (Fe0 2e ¼ Fe2þ) (Zhang et al., in press). It is believed that proper electric stimulation can promote microbial metabolism (Thrash and Coates, 2008), thereby leading to higher biochemical performance. Indeed, there are several examples of bio-electrochemical methods that have been established and applied in biological electrocatalysis (Schlegel and Lafferty, 1965; Islam and Suidan, 1998) and biofuel cells (Chaudhuri and Lovley, 2003; Logan et al., 2006). In the field of wastewater treatment, it has been reported that hydrogen produced from the cathode can serve as a substrate for denitrification and dechlorination, thereby improving the efficiency of pollutant degradation (Hayes et al., 1998; Son et al., 2006; Guiot et al., 2008; Aulenta et al., 2008). Moreover, it is believed that an electric field can enhance the surface reaction by promoting the ion migration rate. Therefore, when an electric field is supplied to the ZVI bed, it is likely to intensify the reaction of ZVI and further improve the anaerobic process. However, no studies have identified a method of enhancing anaerobic granulation using an electric field to date. In this study, ZVI combined with an electric field was installed in an UASB reactor with the goal of accelerating anaerobic granulation. The effectiveness of this method was then investigated and the potential mechanisms were explored.
2.
Materials and methods
2.1.
Experimental set-up
A ZVI bed (4120 mm 200 mm) was installed at 3/5 depth in a transparent acrylic plastic UASB reactor (4140 mm 1200 mm)
1259
to form an electric field enhanced ZVI-UASB reactor (hereafter referred to as reactor R1). The ZVI bed was constructed of a cylindrical acrylic plastic tube (4120 mm 200 mm) packed with a mixture of waste scrap iron (300 g, 20# steel) and waste granular activated carbon (150 g). The goal of mixing the granular carbon (45 mm 10 mm) and the ZVI was to reduce conglutination among the scrap iron and to improve the hydraulic distribution in the ZVI bed. A pair of graphite plate electrodes (180 mm 70 mm 15 mm) was then inserted into the ZVI bed with a distance between the electrodes of 70 mm and supplied by a regulated DC power source. Scrap iron (about 8 mm 4 mm 2 mm) collected from a machine shop was soaked in 1% NaOH solution for 24 h, after which it was washed with dilute HCl and water to clean its surfaces. The granular carbon was then pre-adsorbed in the wastewater used in the study until equilibrium to eliminate any adsorption effect. The control experiments were conducted in the following two reactors, a ZVI-UASB reactor that was the same as reactor R1, but without the electrodes (hereafter referred to as reactor R2), and a common UASB reactor that was the same as reactor R1, except without the ZVI bed and the electrodes (hereafter referred to as reactor R3). These three reactors were operated with a hydraulic retention time (HRT) of 24 h at a temperature controlled at 35 1 C using a heating jacket system. The influent COD increased gradually from 1400 mg/L (1.4 kg/m3/d) to 8000 mg/L (8 kg/m3/d) for all three reactors during the 80 day operation period. To further clarify the function of electricity, reactor R1 was operated with and without the voltage supply in sequence. During the initial 22 days of start-up, reactor R1 was operated without voltage, which resulted in the conditions being the same as for reactor R2. From day 23, a voltage of 1.4 V (I ¼ 150 mA) was supplied to the ZVI bed of reactor R1. The real potential determined between the electrodes was about 1.2e1.3 V. Although the potential was close to the theoretical value of electrolysis of water (1.23 V), the resistance and overpotential in this system was far greater than the classical electrolytic solution (H2SO4 or NaOH solution). Therefore, the wastewater in the reactor could not be electrolyzed.
2.2.
Sludge and wastewater
Sludge obtained from a sedimentation tank in Chunliu municipal sewage plant in Dalian (China) was used as the seed sludge. Following removal of large debris with a sieve, the ratio of volatile suspended sludge to total suspended sludge (VSS/TSS) was 0.74 and the sludge volume index (SVI) was 53 mL/g. Five liters of these seed sludges were inoculated into each of the reactors with an initial TSS of 14.88 g/L. An artificial wastewater was used in this study. Specifically, sucrose, NH4Cl and KH2PO4 were added as the carbon, nitrogen, and phosphorus sources, respectively, to give a COD: N: P ratio of 200: 5: 1. The trace elements were added according to the following composition: 1 mL/L of a trace element solution containing Zn at 0.37 mmol/L, Mn at 2.5 mmol/L, Cu at 0.14 mmol/L, Co at 8.4 mmol/L, Ni at 0.25 mmol/L, H3BO3 at 0.8 mmol/L and EDTA at 3.4 mmol/L. The pH of the influent wastewater was adjusted to 8 using NaHCO3 solution.
1260
2.3.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 5 8 e1 2 6 6
Analysis
measured with a wet type gas meter (LMF-2, Changchun, China), after which its volume was calculated as standard temperature and pressure (STP). The composition of the biogas was analyzed by gas chromatography (Shimadzu, GC2010/TCD, Japan) according to the method described by Jiang et al. (2007). The concentration of Fe (II) in the aqueous phase was determined using ortho phenanthroline spectrophotometry at 510 nm (Techcomp, UV-2301, Shanghai, China).
TSS, VSS and COD were determined according to Standard Methods for the Examination of Water and Wastewater (APHA, 1998). The ORP was measured using an ORP combination class-body redox electrode (Sartorius PY-R01, Germany). The pH was recorded using a pH analyzer (Sartorius PB-20, Germany). Biogas collected from the reactors was
a
10000
100
9000
9
90
Reactor R1
8000
80
7000
70
6000
60
5000
50
influent effluent
Reactor R1
with voltage
3000
40 30
influent effluent COD removal
2000
without volatge
pH
without voltage
4000
COD removal (%)
COD (mg/L)
8
6
20
1000
10
0
0 0
10
20
30
40
50
60
70
5
80
0
10
20
10000
40
50
60
70
80
9
100
Reactor R2
9000
30
Time (days)
Time (days)
b
with volatge
7
8000
80
7000
70
6000
60
influent effluent
Reactor R2
90
50
influent effluent COD removal
4000 3000
40 30
2000
20
1000
10
0
pH
5000
COD removal (%)
COD (mg/L)
8
6
0 0
10
20
30
40
50
60
70
7
5
80
0
10
20
30
c 10000
100
Reactor R3
80
7000
70
6000
60
5000
50
4000
40
influent effluent COD removal
30 20
1000
10
0
0 10
20
30
40
Time (days)
50
70
80
60
70
influent effluent
8
7
6
2000
0
60
Reactor R3
pH
8000
3000
50
9
90
COD removal (%)
COD (mg/L)
9000
40
Time (days)
Time (days)
80
5 0
10
20
30
40
50
60
70
80
Time (days)
Fig. 1 e COD Removal and pH changes in each reactor during start-up. (a) Reactor R1, (b) reactor R2, (c) reactor R3. (Reactor R1 was operated with voltage from day 23).
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 5 8 e1 2 6 6
a
was conducted according to the method described by Wu et al. (2001). Fluorescence labels of the oligonucleotide probes used in this study included EUB338 (Bacteria), ARC915 (Archaea) and MB1174 (Methanobacteriaceae) (Raskin et al., 1994; Sekiguchi et al., 1999). The samples were observed under a confocal laser scanning microscope (Leica SP2, Heidelberger, Germany). The FISH images obtained were imported to Image-Pro Plus 6.0 for analysis of the relative abundance of microorganisms.
1000
Reactor R1 Reactor R2 Reactor R3
Granule size (µ m)
800
R1 with voltage
600
400
200
3.
0 0
10
20
30
40
50
60
1261
70
80
Results and discussion
3.1. COD removal and pH changes in the reactors during start-up
Time (days)
b
10
Inoculum on day 1 Reactor R1 on day 80 Reactor R2 on day 80 Reactor R3 on day 80
9
Percentage of sludge (%)
8 7 6 5 4 3 2 1 0 0
500
1000
1500
2000
Particle size (µm)
Fig. 2 e Characterization of the granular sludge during start-up. (a) Time series of mean granule size in each reactor, (b) size distribution of the granules from the three reactors on day 80 (inoculum sludge is presented for comparison).
The iron content in the granules was determined by atomic absorption spectroscopy (Vlyssides et al., 2009). The settling velocity of the granules was determined by measuring the mean time required for an individual granule to fall a certain distance in a measuring cylinder. The morphology of the granular sludge was examined using a scanning electron microscope (SEM; Quanta 200 FEG, The Netherlands). For the SEM observation, the sludge was immobilized in a 2.5% glutaraldehyde solution, dehydrated in graded water-ethanol solutions, then lyophilized and sputter-coated with gold (Zhou et al., 2006). The average granular sludge size was measured using a Malvern Mastersizer 2000 (UK). Each size distribution obtained was calculated by instrument software. EPS was extracted using a cation exchange resin (CER) according to the method described by Frolund et al. (1996). Polysaccharide in the EPS was determined by a sulfuric acideanthrone method and protein in the EPS was analyzed according to the method described by Lowry et al. (1951). Fluorescence in situ hybridization (FISH) was used to determine the abundance of methanogens in the granules. FISH
To investigate the effects of the electric field on the start-up, reactor R1 was operated with and without voltage successively. During the initial 22 days from inoculation, reactor R1 was operated without voltage, during which time it was identical to reactor R2. As shown in Fig. 1, the COD removal in reactor R1 and R2 ranged from 60% to 70% and the effluent pH of both reactors was maintained between 6.0 and 6.5. When compared with these two reactors, reactor R3 showed less COD removal (50%e60%) and lower pH stability (5.0e6.5). As a voltage of 1.4 V was supplied to reactor R1 from day 23, its effluent COD decreased dramatically from 1082 mg/L to 229 mg/L over the next four days. In addition, the effluent pH increased to 6.5e7.0 from 6.0 to 6.5. Although the influent COD concentration rose rapidly from 2500 mg/L to 6500 mg/L after seven days, the COD removal in reactor R1 still increased to 97.1%. The removal efficiency fell to 90.8% and the pH decreased from 6.6 to 6.1 when the influent COD increased to 7500 mg/L on day 36; however, the COD removal recovered to more than 94.5% and the pH recovered to 6.5 after two days. The COD removal was then maintained between 92.2% and 95.4% and the pH was maintained between 6.4 and 6.8 in reactor R1 for the remainder of the experiment. Reactor R2 required 17 days to elevate the COD removal from 68.1% to 91.4% from day 23. In addition, when the influent COD increased from 2500 mg/L to 7000 mg/L, reactor R2 showed a gradual decrease in COD removal from 91.5% to 74.1% and a decline in pH from 6.5 to 5.6. After these decreases, nearly ten days were required for the COD removal to recover to 90%. The increase in COD removal was the slowest for reactor R3, with the highest level of 85% not being attained until day 63. After day 63, the COD removal in R3 showed a declining trend, reaching 76.5% on day 80. The pH of reactor R3 varied from 5.5 to 6.3 throughout the experimental period. It is well known that acidogens breaks down organic matters into H2, acetic acid and CO2, and methanogens convert these intermediate products to CH4. In the processes, methanogenesis is a major way to mineralize organic substrates. However, methanogenic metabolism is slow and often influenced by operational conditions. Improper conditions such as fluctuating organic loading rate may lead to imbalance between acidogenesis and methanogenesis so as to accumulate organic acids, which may further deteriorate the methanogenesis. Therefore, to maintain a near neutral pH extent is crucial for the performance and start-up of an UASB
1262
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 5 8 e1 2 6 6
Fig. 3 e Images of the granular sludge on day 80. (a) Digital image of sludge from reactor R1, (bed) SEM observation of granules from reactor R1, R2 and R3, respectively, (e, g) a higher magnification of the surface (ex) of granules from reactor R1 and R3, (f, h) a higher magnification of the inner layer (in) of granules from reactor R1 and R3.
reactor. The ZVI in reactor R1 and R2 could buffer acid produced by acidogens according to the reaction, Fe0 þ 2Hþ ¼ Fe2þ þ H2, which likely helped the reactor maintain a favorable pH for methanogenesis (6.8e7.2). This reaction may have intensified in response to the application of electricity to the ZVI. Also, iron was documented as
a component of the essential enzymes that drive numerous anaerobic reactions. Oleszkiewicz and Sharma (1990) reported limited conversion of COD at deficient concentrations of iron. Thus, ZVI could be responsible for the significant COD removal. In this process, the ZVI reaction was the major reason for the improved performance, but the reaction might
80
-150
Reactor R1 Reactor R2
70
Reactor R1 Reactor R2 Reactor R3
R1 with voltage -200
60
ORP (mV)
40
2+
Fe (mg/L)
50
30
-250
-300
20 -350
10 0
-400
10
20
30
40
50
60
70
80
Time (days) Fig. 4 e Ferrous ion leaching in reactor R1 and R2. (Reactor R1 was operated with voltage from day 23).
30
40
50
60
70
80
Time (days) Fig. 5 e The ORP variation of the three reactors from day 30 to day 80.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 5 8 e1 2 6 6
Table 1 e Composition of extracellular polymeric substances (EPS) extracted from reactor sludges. Inoculum sludge is presented for comparison. Sludge
EPS Polypeptides (mg protein/g VSS) 15.33 26.78 23.13 16.32
Inoculum Reactor R1 Reactor R2 Reactor R3
0.54 1.06 0.93 0.60
Polysaccharides (mg glucose/g VSS) 9.90 18.13 13.47 10.54
0.39 0.53 0.62 0.41
be weak. The electric field could intensify the ZVI reaction so as to enhance the roles of ZVI in anaerobic process.
3.2.
Granulation
The granule size variation during 80 days of operation is shown in Fig. 2. The mean granule size in reactor R1 increased from 86.2 mm to 151.4 mm during the initial 22 days without voltage (Fig. 2a), which was similar to that observed in reactor R2. Comparatively, the granule size in reactor R3 only rose to 88.9 mm during this period. As the voltage was supplied to reactor R1 from day 23, a marked increase in the granule size was observed. The mean granule size reached 695.1 mm on day 60, which was almost five times greater than on day 22. Afterwards, it gradually reached a relatively steady size of 723.5 mm on day 80. Comparatively, the granule size in reactor R2 only reached 189.8 mm on day 30, after which it grew slowly to 216.79 mm on day 80. The granule size in reactor R3 grew the most slowly, being only 113.0 mm on day 80. As shown in Fig. 2b, the size of the granules in reactor R1 presented a near normal distribution. The settling velocity of the granular sludge in each reactor was determined on day 80. The velocity was 56.1 m/h in reactor R1, which was much higher than the 38.6 m/h and 17.1 m/h observed in reactor R2 and R3, respectively. It is believed that the general range of settling velocities in UASB sludge is 2e90 m/h (Lettinga et al., 1983), and a settling velocity of 50e60 m/h is believed to be ideal (Hulshoff Pol et al., 2004) because it reduces washout of the sludge while maintaining a uniform distribution of sludge in the reactor.
3.3.
Morphology of granules
Digital and SEM images of the granular sludge are displayed in Fig. 3. The digital image of sludge taken from reactor R1 revealed a compact structure (Fig. 3a). The SEM images revealed that the texture of granules in reactor R1 was clear-
Table 2 e Contents of CH4 and H2 in the biogas of each reactor from day 70 to day 80. Reactor Reactor R1 Reactor R2 Reactor R3
Average CH4 (%) 50.71 1.01 45.92 0.93 42.49 0.96
Average H2 (%) Not detectable 0.11 0.02 0.73 0.07
1263
cut, rigid and stable (Fig. 3b), while the granules in reactors R2 (Fig. 3c) and R3 (Fig. 3d) showed a loose and rough surface. A higher magnification of SEM showed that cocci prevailed the surface of the granules from reactor R1 (Fig. 3e), while rodshaped (or filamentous) species dominated the inner layer (Fig. 3f). It is believed that filamentous Methanothrix are important to granule formation (De Zeeuw, 1987). Dubourgier et al. (1987) suggested that the granulation process started as a result of the bridging of microflocs by Methanothrix filaments, after which other bacteria and acidogens colonized the flocs to form sludge with increasing granule sizes. According to the description of the granular structure by Macleod et al. (1990), methanogens are primarily located in the interior layer, while acetate producers and fermentative bacteria form the exterior layer. This structure can prevent the exposure of susceptible methanogens to stressful changes in the environment such as low pH and toxic substances. From this point of view, the cocci observed on the surface in the present study were likely acidogens. Evaluation of the granules of reactor R3 revealed that the microorganisms on the exterior and interior did not differ greatly (Fig. 3f and h), and acidogen-like and Methanothrix-like microorganisms were intertwined, indicating that a double-layer structure had not formed.
3.4.
Fe2þ leaching
Fe2þ is a product of the ZVI reaction, so its amount can reflect the intensity of the reaction. Iron leaching under anaerobic conditions resulted in ferrous iron. As shown in Fig. 4, the Fe2þ concentration in both reactor R1 and R2 ranged from 38 mg/L to 40 mg/L during the first 22 days. As voltage was supplied, the Fe2þ concentration in reactor R1 rapidly increased to 61e63 mg/L in the following days. According to the reaction of ZVI, the production of more Fe2þ indicates that more Hþ was consumed. Therefore, the pH in reactor R1 was well maintained in a near neutral range. According to the DLVO theory, the divalent metal ions could decrease electric repulsion and facilitate cell-to-cell interaction between bacteria (Mahoney et al., 1987; Schmidt and Ahring, 1993). Therefore, ferrous iron ions could enhance cell aggregation. Yu et al. (2000) reported that Fe2þ at a concentration of 300 mg/L (dosage in the form of FeCl2) enhanced the granulation process, while a dose of FeCl2 less than 150 mg/L (Fe2þ) had little effect on sludge granulation. However, in the present study, a lower Fe2þ “dose” (61e63 mg/ L) resulted in significant enhancement of granulation. The role of iron in cell aggregation and its other functions, such as interaction with EPS, indicate that it would be involved in the formation of sludge. The amount of iron in the sludge could partially reflect the level of these effects. After 80 days of operation, the iron content of the sludge from reactor R1 was the greatest (22.45 mg Fe/g VSS, data not shown), while it was only 11.59 mg Fe/g VSS in sludge from reactor R2 and 3.94 mg Fe/g VSS in that of reactor R3. Together with the results of Fig. 4, the iron content of the sludge was related to the Fe2þ concentration in the bulk liquid. Fe2þ leaching increased the iron content of the sludge, which benefited the formation of the granule matrix with EPS. The ZVI reaction was assumed to be essential for enhanced granulation. ZVI serving as a reductant could decrease the
1264
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 5 8 e1 2 6 6
Fig. 6 e FISH images of granular sludge in different reactors. (aec) Granules from reactor R1, R2 and R3 respectively, hybridized with specific probes for Archaea and Bacteria (ARC915-FITC, green and EUB338-CY3, red), (def) granules from reactor R1, R2 and R3 respectively, hybridized with specific probes for Archaea and H2-utilizing methanogens (ARC915-FITC, green and MB1174-CY3, red). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
ORP, and the ORP level in the reactor could reflect the rate of the ZVI reaction. The ORP values of the reactors were recorded from day 30 to day 80 and the results are shown in Fig. 5. From the figure, the ORP values of reactor R1 and R2 were more negative than that of reactor R3, indicating that ZVI could effectively decrease the ORP. Moreover, the ORP of reactor R1 ranged from 340 mV to 370 mV, while it ranged from 270 mV to 320 mV in reactor R2. These results indicated that the ORP was further decreased under the voltage supply, implying that the reaction of ZVI was enhanced under an electric field, which was in agreement with the results of Fe2þ leaching (seen in Fig. 4). It is well known that a lower ORP is instrumental in the survival and growth of obligate anaerobes, especially methanogens. These results indicated that an electric field could enhance the ZVI reaction to further create a favorable environment for the development of methanogens, thereby enhancing the granulation.
3.5.
EPS content of the sludge
EPS secreted by bacteria can mediate cohesion as well as adhesion of cells, which is crucial to maintenance of the structural integrity of anaerobic granules (Schmidt and Ahring, 1996; Shen et al., 1993; Liu et al., 2003). Therefore, the EPS content of the sludge is an important factor in anaerobic granulation (Zhou et al., 2006). Proteins and polysaccharides are the two dominant compositions in extracted EPS, which are believed to represent the entire EPS of the sludge (Yu et al., 2006). After 80 days of operation, these two compositions extracted from the sludge of each reactor and from the inoculum were analyzed. As shown in Table 1, both
compounds increased in all three reactors when compared with the inoculum. Indeed, the level of proteins and polysaccharides extracted from reactor R1 was nearly double that of the inoculum, and was higher than the levels in reactor R2 and R3. The levels of these compounds in reactor R3 were only slightly higher than those of the inoculum. The different EPS contents in the three reactors were related to Fe2þ leaching. EPS preferred to bind with divalent metals to form a stable three dimensional structure to maintain the structural integrity of the granule (Rudd et al., 1984; Cammarota and Sant’Anna, 1998), which was important for the response of the granule to stressful changes. Thus, as the Fe2þ content of the sludge increased, more EPS was bound and immobilized in the sludge (Shen et al., 1993).
3.6.
Gas composition
It has been suggested that H2 production accompanies the ZVI reaction (acid buffering); therefore, its production should increase in response to the application of electricity because the reaction was enhanced. However, no hydrogen was detected in the biogas of reactor R1, while it was detected in the biogas produced in reactors R2 and R3 (shown in Table 2). These results were contrary to the expected results based on the explanation presented above. This may have been due to the presence of hydrogenotrophic methanogens that could utilize H2 and CO2 for the production of CH4. Based on these biogas results, we assumed that hydrogenotrophic methanogens were present in R1, and that they were so active that they consumed all of the H2 produced by acidogenesis and the ZVI reaction (Daniels et al., 1987). Accordingly, the percentage
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 5 8 e1 2 6 6
1265
of CH4 in the biogas of reactor R1 was the greatest, 50.71% (shown in Table 2), while it was 45.92% in reactor R2 and 42.49% in reactor R3, respectively. Certainly, such little difference in the H2 percentage was insufficient to create obvious differences in CH4 production. It is assumed that the ZVI in conjunction with the voltage also enhanced the growth of other methanogenic species. CH4 production in reactor R1 was in the range of 40.3e45.1 L/d from day 70e80, amounting to 296e332 mL CH4/g CODremoved (STP), which was close to the theoretical CH4 production from per gram removed COD, i.e., 350 mL CH4/g CODremoved (Toprak, 1995).
and reduction in start-up time. These findings indicate that coupling of ZVI and an electric field was an effective method of enhancing sludge granulation, which is meaningful for wider application of anaerobic reactors in the wastewater treatment associated with engineering. This method also improved wastewater treatment efficiency during the anaerobic startup period, enabling the anaerobic reactor to more easily respond to the requirements of various environmental criterions.
3.7.
Acknowledgments
FISH analysis
FISH was used to analyze the specific microbial composition of the granules after 80 days of operation, and the results are shown in Fig. 6. The primary microorganisms in the anaerobic reactors consisted of Bacteria and Archaea; therefore, the sum of these two domains was considered to be 100% (Griffin et al., 1998). In addition, it is well known that methanogens are members of Archaea and acidogens are members of Bacteria. In most anaerobic reactors, methanogens can represent Archaea (Sekiguchi et al., 1999). According to analysis conducted using Image-Pro Plus 6.0, the relative abundance of methanogens in reactor R1 was 86.25%, while it was 74.81% in reactor R2 and 63.31% in reactor R3. These findings are coincident with their performance in terms of COD removal and granulation. As shown in Fig. 6d, e and f, the relative abundance of H2-utilizing methanogens in the total population of methanogens was 29.97%, 22.19% and 13.24% in reactor R1, R2 and R3, respectively, which could explain the different H2 levels in the biogas. The high percentage of methanogens in the granules of reactor R1 was ascribed to the following reasons. The reaction of ZVI could help to maintain a near neutral pH and lower ORP level, which were beneficial to the growth of methanogens. Additionally, electricity could enhance the reaction of ZVI to further intensify the function of ZVI. Due to the formation of a favorable environment for the growth of methanogens, the start-up of the reactor and process of sludge granulation were effectively accelerated. Moreover, Fe2þ as a product of the reaction of ZVI promoted the aggregation of granules and colligation with EPS, both of which helped to form a stable and intact structure for methanogenesis and granulation.
4.
Conclusion
The application of ZVI in combination with an electric field installed in an UASB reactor effectively sped up sludge granulation and improved the performance of the reactor. When an electric field of 1.4 V was supplied to reactor R1, COD removal increased dramatically from 60.3% to 90.7% in four days and the granule size rapidly increased from 151.4 mm to 695.1 mm in 38 days. The electric field enhanced the ZVI reaction to decrease ORP values and buffer acidity, which created a favorable environment for the growth of methanogens. At the same time, increases in the Fe2þ dissolution and EPS content were helpful for the growth of granule size. These factors all led to the observed increase in granulation
This study was conducted with financial support from the National Key Scientific and Technology Project for Water Pollution Treatment of China (2008ZX07208-004, 2008ZX07208-002) and the Program for Changjiang Scholars and Innovative Research Team at the University of China (IRT0813).
reference
APHA, 1998. Standard Methods for the Examination of Water and Wastewater, twentieth ed. American Public Health Association/American water work Association/Water environment Federation, Washington D.C., USA. Arcand, Y., Guiot, S.R., Desrochers, M., Chavarie, C., 1994. Impact of the reactor Hydrodynamics and organic loading on the size and Activity of anaerobic granules. Chemical Engineering Journal and the Biochemical Engineering Journal 56 (1), B23eB35. Aulenta, F., Canosa, A., Majone, M., Panero, S., Reale, P., Rossetti, S., 2008. Trichloroethene dechlorination and H2 evolution are alternative biological pathways of electric charge utilization by a dechlorinating culture in a bioelectrochemical system. Environmental Science and Technology 42 (16), 6185e6190. Cammarota, M.C., Sant’Anna, G.L., 1998. Metabolic blocking of exopolysaccharides synthesis: effects on microbial adhesion and biofilm accumulation. Biotechnology Letters 20 (1), 1e4. Chaudhuri, S.K., Lovley, D.R., 2003. Electricity generation by direct oxidation of glucose in mediatorless microbial fuel cells. Nature Biotechnology 21 (10), 1229e1232. Daniels, L., Belay, N., Rajagopal, B.S., Weimer, P.J., 1987. Bacterial methanogenesis and growth from CO2 with elemental iron as the sole source of electrons. Science 237 (4814), 509e511. De Zeeuw, W.J., 1987. Granular sludge in UASB reactors. In: Lettinga, G., Zehnder, A.J.B., Grotenhuis, J.T.C., Hulshoff Pol, L. W. (Eds.), Granular Anaerobic Sludge: Microbiology and Technology. Microbiology and Technology. Pudoc, Wageningen, The Netherlands, pp. 132e145. Dubourgier, H.C., Prensier, G., Albagnac, G., 1987. Structure and microbial activities of granular anaerobic sludge. In: Lettinga, G., Zehnder, A.J.B., Grotenhuis, J.T.C., Hulshoff Pol, L. W. (Eds.), Granular Anaerobic Sludge: Microbiology and Technology. Pudoc, Wageningen, The Netherlands, pp. 18e33. El-Mamouni, R., Leduc, R., Guiot, S.R., 1997. Influence of the starting microbial nucleus type on the anaerobic granulation dynamics. Applied Microbiology and Biotechnology 47 (2), 189e194. Frolund, B., Palmgren, R., Keiding, K., Nielsen, P.H., 1996. Extraction of extracellular polymers from activated sludge
1266
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 5 8 e1 2 6 6
using a cation exchange resin. Water Research 30 (8), 1749e1758. Ghangrekar, M.M., Asolekar, S.R., Joshi, S.G., 2005. Characteristics of sludge developed under different loading conditions during UASB reactor start-up and granulation. Water Research 39 (6), 1123e1133. Griffin, M.E., McMahon, K.D., Mackie, R.I., Raskin, L., 1998. Methanogenic population dynamics during start-up of anaerobic digesters treating municipal solid waste and biosolids. Biotechnology and Bioengineering 57 (3), 342e355. Guiot, S.R., Cimpoia, R., Kuhn, R., Alaplantive, A., 2008. Electrolytic methanogenic e methanotrophic coupling for tetrachloroethylene bioremediation: proof of concept. Environmental Science and Technology 42 (8), 3011e3017. Hayes, A.M., Flora, J.R.V., Khan, J., 1998. Electrolytic stimulation of denitrification in sand columns. Water Research 32 (9), 2830e2834. Hickey, R.F., Wu, W.M., Veiga, M.C., Jones, R., 1991. Start-up, operation, monitoring and control of high-rate anaerobic treatment systems. Water Science and Technology 24 (8), 207e255. Hulshoff Pol, L.W., de Zeeuw, W.J., Velzeboer, C.T.M., Lettinga, G., 1983. Granulation in UASB-reactors. Water Science and Technology 15 (8e9), 291e304. Hulshoff Pol, L.W., Lopes, S.I.D., Lettinga, G., Lens, P.N.L., 2004. Anaerobic sludge granulation. Water Research 38 (6), 1376e1389. Islam, S., Suidan, M.T., 1998. Electrolytic denitrification: long term performance and effect of current intensity. Water Research 32 (2), 528e536. Jiang, S., Chen, Y.G., Zhou, Q., 2007. Effect of sodium dodecyl sulfate on waste activated sludge hydrolysis and acidification. Chemical Engineering Journal 132 (1e3), 311e317. Lettinga, G., Hulshoff Pol, L.W., Homba, S.W., Grin, P., Jong de, P., Roersma, R., Jspeert, P.I., 1983. The use of a floating settling granular sludge bed reactor in anaerobic treatment. In: van den Brink, W.J. (Ed.), Proceedings of the European Symposium on Anaerobic Waste Water Treatment. Noordwijkerhout, The Netherlands, pp. 411e429. Lettinga, G., Deman, A., Vanderlast, A.R.M., Wiegant, W., Vanknippenberg, K., Frijns, J., Vanbuuren, J.C.L., 1993. Anaerobic treatment of domestic sewage and waste-water. Water Science and Technology 27 (9), 67e73. Liu, Y., Xu, H.L., Yang, S.F., Tay, J.H., 2003. Mechanisms and models for anaerobic granulation in upflow anaerobic sludge blanket reactor. Water Research 37 (3), 661e673. Logan, B.E., Hamelers, B., Rozendal, R.A., Schrorder, U., Keller, J., Freguia, S., Aelterman, P., Verstraete, W., Rabaey, K., 2006. Microbial fuel cells: methodology and technology. Environmental Science and Technology 40 (17), 5181e5192. Lowry, O.H., Rosebrough, N.J., Farr, A.L., Randall, R.J., 1951. Protein measurement with the folin phenol reagent. Journal of Biological Chemistry 193 (1), 265e275. Macleod, F.A., Guiot, S.R., Costerton, J.W., 1990. Layered structure of bacterial aggregates produced in an upflow anaerobic sludge bed and filter reactor. Applied and Environmental Microbiology 56 (6), 1598e1607. Mahoney, E.M., Varangu, L.K., Cairns, W.L., Kosaric, N., Murray, R. G.E., 1987. The effect of calcium on microbial aggregation during UASB reactor start-up. Water Science and Technology 19 (1e2), 249e260. Oleszkiewicz, J.A., Sharma, V.K., 1990. Stimulation and inhibition of anaerobic processes by heavy-metals e a review. Biological Wastes 31 (1), 45e67. Raskin, L., Stromley, J.M., Rittmann, B.E., Stahl, D.A., 1994. Groupspecific 16s ribosomal-RNA hybridization probes to describe
natural communities of methanogens. Applied and Environmental Microbiology 60 (4), 1232e1240. Rudd, T., Sterritt, R.M., Lester, J.N., 1984. Complexation of heavy metals by extracellular polymers in the activated sludge process. Water Pollution Control Federation 56 (12), 1260e1268. Schlegel, H.G., Lafferty, R., 1965. Growth of Knallgas bacteria (Hydrogenomonas) using direct electrolysis of culture medium. Nature 205 (4968), 308. Schmidt, J.E., Ahring, B.K., 1993. Effects of magnesium on thermophilic acetate-degrading granules in upflow anaerobic sludge blanket (UASB) reactors. Enzyme and Microbial Technology 15 (4), 304e310. Schmidt, J.E., Ahring, B.K., 1996. Granular sludge formation in upflow anaerobic sledge blanket (UASB) reactors. Biotechnology and Bioengineering 49 (3), 229e246. Seghezzo, L., Zeeman, G., van Lier, J.B., Hamelers, H.V.M., Lettinga, G., 1998. A review: the anaerobic treatment of sewage in UASB and EGSB reactors. Bioresource Technology 65 (3), 175e190. Sekiguchi, Y., Kamagata, Y., Nakamura, K., Ohashi, A., Harada, H., 1999. Fluorescence in situ hybridization using 16S rRNAtargeted oligonucleotides reveals localization of methanogens and selected uncultured bacteria in mesophilic and thermophilic sludge granules. Applied and Environmental Microbiology 65 (3), 1280e1288. Shen, C.F., Kosaric, N., Blaszczyk, R., 1993. The effect of selected heavy-metals (Ni, Co and Fe) on anaerobic granules and their extracellular polymeric substance (EPS). Water Research 27 (1), 25e33. Son, A., Lee, J., Chiu, P.C., Kim, B.J., Cha, D.K., 2006. Microbial reduction of perchlorate with zero-valent iron. Water Research 40 (10), 2027e2032. Thrash, J.C., Coates, J.D., 2008. Review: direct and indirect electrical stimulation of microbial metabolism. Environmental Science and Technology 42 (11), 3921e3931. Tiwari, M.K., Guha, S., Harendranath, C.S., Tripathi, S., 2006. Influence of extrinsic factors on granulation in UASB reactor. Applied Microbiology and Biotechnology 71 (2), 145e154. Toprak, H., 1995. Temperature and organic loading dependency of methane and carbon-dioxide emission rates of a full-scale anaerobic waste stabilization pond. Water Research 29 (4), 1111e1119. Vlyssides, A., Barampouti, E.M., Mai, S., 2009. Influence of ferrous iron on the granularity of a UASB reactor. Chemical Engineering Journal 146 (1), 49e56. Wu, J.H., Liu, W.T., Tseng, I.C., Cheng, S.S., 2001. Characterization of microbial consortia in a terephthalate-degrading anaerobic granular sludge system. Microbiology-UK 147, 373e382. Yu, H.Q., Fang, H.H.P., Tay, J.H., 2000. Effect of Fe2þ on sludge granulation in upflow anaerobic sludge blanket reactor. Water Science and Technology 41 (12), 199e205. Yu, H.Q., Fang, H.H.P., Tay, J.H., 2001a. Enhanced sludge granulation in upflow anaerobic sludge blanket (UASB) reactors by aluminum chloride. Chemosphere 44 (1), 31e36. Yu, H.Q., Tay, J.H., Fang, H.H.P., 2001b. The roles of calcium in sludge granulation during UASB reactor start-up. Water Research 35 (4), 1052e1060. Yu, T., Lei, Z., Sun, D.Z., 2006. Functions and behaviors of activated sludge extracellular polymeric substances (EPS): a promising environmental interest. Journal of Environmental Sciences-China 18 (3), 420e427. Zhang, Y.B., Jing, Y.W., Zhang J.X., Sun, L.F. and Quan, X. Performance of a ZVI-UASB reactor for azo dye wastewater treatment. Journal of Chemical Technology & Biotechnology, in press. Zhou, W.L., Imai, T., Ukita, M., Sekine, M., Higuchi, T., 2006. Triggering forces for anaerobic granulation in UASB reactors. Process Biochemistry 41 (1), 36e43.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 6 7 e1 2 7 9
Available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Effects of free cyanide on microbial communities and biological carbon and nitrogen removal performance in the industrial activated sludge process Young Mo Kim a,c, Dae Sung Lee b, Chul Park c, Donghee Park b,**, Jong Moon Park a,* a
Advanced Environmental Biotechnology Research Center, Department of Chemical Engineering, School of Environmental Science and Engineering, Pohang University of Science and Technology, San 31, Hyoja-dong, Pohang 790-784, Republic of Korea b Department of Environmental Engineering, Kyungpook National University, Daegu 702-701, Republic of Korea c Department of Civil and Environmental Engineering, University of Massachusetts, Amherst, MA 01003, USA
article info
abstract
Article history:
The changes in process performance and microbial communities under free cyanide (CN)
Received 31 May 2010
were investigated in a lab-scale activated sludge process treating industrial wastewater.
Received in revised form
The performance of phenol degradation did not appear to be adversely affected by
28 September 2010
increases in CN concentrations. In contrast, CN was found to have an inhibitory effect on
Accepted 7 October 2010
SCN biodegradation, resulting in the increase of TOC and COD concentrations. Nitratation
Available online 19 October 2010
also appeared to be inhibited at CN concentrations in excess of 1.0 mg/L, confirming that nitrite-oxidizing bacteria (NOB) is more sensitive to the CN toxicity than ammonia
Keywords:
oxidizing bacteria (AOB). After CN loads were stopped, SCN removal, denitrification, and
Free cyanide
nitrification inhibited by CN were recovered to performance efficiency of more than 98%.
Activated sludge
The AOB and NOB communities in the aerobic reactor were analyzed by terminal restric-
T-RFLP
tion fragment length (T-RFLP) and quantitative real-time PCR (qPCR). Nitrosomonas europaea
qPCR
lineage was the predominant AOB at all samples during the operation, but an obvious
Nitrifying bacteria
change was observed in the diversity of AOB at the shock loading of 30 and 50 mg/L CN,
Denitrifying bacteria
resulting in Nitrosospira sp. becoming dominant. We also observed coexisting Nitrospira and Nitrobacter genera for NOB. The increase of CN loading seemed to change the balance between Nitrospira and Nitrobacter, resulting in the high dominance of Nitrobacter over Nitrospira. Meanwhile, through using the qPCR, it was observed that the nitrite-reducing functional genes (i.e., nirS ) were dominant in the activated sludge of the anoxic reactor, regardless of CN loads. ª 2010 Elsevier Ltd. All rights reserved.
1.
Introduction
Biological nitrification coupled to denitrification is commonly used in wastewater treatment plants to simultaneously remove carbon and nitrogen. Nitrification is achieved through the aerobic oxidation of ammonium (NHþ 4 ) or ammonia (NH3)
into nitrite (NO 2 ) by ammonia oxidizing bacteria (AOB), often Nitrosomonas spp., and followed by the oxidation of the nitrite (NO 2 ) into nitrate (NO3 ) by nitrite-oxidizing bacteria (NOB), often Nitrobacter spp. The former is called nitritation and the latter nitratation. Denitrification consists of consecutive reaction steps in which nitrate is reduced to dinitrogen gas by
* Corresponding author. Tel.: þ82 54 279 2275; fax: þ82 54 279 2699. ** Corresponding author. Tel.: þ82 53 950 7566; fax: þ82 53 950 7879. E-mail addresses:
[email protected] (D. Park),
[email protected] (J.M. Park). 0043-1354/$ e see front matter ª 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2010.10.003
1268
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 6 7 e1 2 7 9
denitrifying bacteria using the organic matter of wastewater under anoxic conditions: the reduction of nitrate via nitrite and nitric oxide to nitrous oxide or dinitrogen gas (Zumft, 1997). Although the biological processes treating industrial wastewater are efficient and reliable, they may be susceptible to disturbances and toxic loadings (Juliastuti et al., 2003; Mertoglu et al., 2008; Kim et al., 2009). In particular, the presence of cyanide in industrial wastewaters from mining, coke or steel industries leads to severe problems for biological wastewater treatment (Wild et al., 1994). It is known that cyanide inhibits nitrification and denitrification in activated sludge systems (Kelly et al., 2004; Kim et al., 2008a), with only 1e2 mg/L of free cyanide in the form of HCN or CN being more toxic to biological processes than thiocyanate and metalecyanide complexes (Park and Ely, 2008). Although the inhibitory effects of free cyanide on microbial reactions have been investigated by many researchers, most of them have focused on the threshold levels of free cyanide, at which pure or mixed cultures can tolerate without any inhibition (Kim et al., 2008b; Neufeld et al., 1986; Park and Ely, 2008). A few researchers have investigated the process performances on free cyanide (Lewandowski, 1984; Richards and Shieh, 1989). However, little is known about the microbial populations of nitrifiers and denitrifiers in an activated sludge system treating industrial wastewater containing free cyanide. Therefore, this study aimed to investigate bacterial populations relevant to nitrification and denitrification processes, particularly those in an activated sludge system treating wastewater from a coke plant under free cyanide shock loading. Diversity surveys, and the relationship of the bacterial abundance and activity to the overall processing conditions, may lead to an understanding of the basis of the process instability under free cyanide shock loading.
2.
Materials and methods
2.1.
Actual wastewater and microbial inoculums
Actual wastewater was collected from the full-scale wastewater treatment plant (WWTP) of a coke manufacturing plant in Pohang, Korea. During the operation of our reactor, the concentrations of pollutants in the raw wastewater were as follows: 1950e2325 mg/L of chemical oxygen demand (COD), 606e644 mg/L of total organic carbon (TOC), 190e229 mg/L of phenol, 186e218 mg-N/L of total nitrogen (TN), 103e119 mg-N/ L of ammonia, 405e486 mg/L of thiocyanate (SCN) and 15.0e50.0 mg-CN/L of free cyanide (CN). The pH was in the range of 8.9e9.4. To mimic the full-scale process as closely as possible, no supplementary nutrients were added into the raw wastewater. Activated sludge from the anoxic and aerobic tanks of the full-scale process was sampled and used as microbial inoculums for the anoxic and aerobic reactors of the lab-scale process, respectively.
2.2.
Set-up and operation of the lab-scale reactor
The lab-scale pre-denitrification process reactor, consisting of an anoxic reactor, an aerobic reactor, and a settler, was designed to mimic a full-scale one (Kim et al., 2008b). The working volumes of the anoxic and aerobic tanks were 8 L and
16 L, respectively. The reactor was operated in down flow mode. In the anoxic reactor, a variable-speed stirrer was used to maintain suspended-growth system. In the aerobic reactor, compressed air was supplied for mixing and aeration. Effluent from the aerobic reactor was allowed to flow into a settler for the settling of sludge, which was then recycled to the anoxic reactor. The concentration of suspended solids in each reactor was maintained at 3500e4000 mg/L, similar to that of the fullscale process. A temperature controller was used to keep each reactor at 33e34 C and the pH of the aerobic reactor was controlled at 7.3e7.5 by adding a 1 N NaOH solution. The dissolved oxygen (DO) concentration in the aerobic reactor was more than 4.0 mg/L, while the DO level of the anoxic reactor was maintained below 0.3 mg/L. The total hydraulic retention time (HRT) of the reactor was 16.7 h and the internal recycling ratio of nitrified effluent was 5. The sludge retention time (SRT) was 24 days. The performance of the reactor was monitored under four CN shock loadings of 3.6, 4.8, 7.2, and 12 mg/L d. The shock loadings were continuously given for 5 days by increasing the influent CN concentration to 15, 20, 30 and 50 mg/L respectively. Extra CN was added into the feed as potassium cyanide (Junsei Chemical Co. Ltd., Japan), while the other influent components were maintained equal to those of normal wastewater. After each shock loading, the reactor was allowed to recover fully from the effect of the shock without CN loading.
2.3.
Microbial activity test
To investigate microbial activities of nitrifiers and denitrifiers during the shock loading tests, nitrification and denitrification rates were evaluated through batch experiments with synthetic medium containing ammonia or nitrate, but without CN. Batch experiments for nitrification and denitrification activity were carried out in 500 mL Erlenmeyer flasks filled with 100 mL of test solution containing 50 mg-N/L of ammonia and nitrate ion, respectively. Each flask was inoculated with activated sludge sampled directly from the reactor, and then agitated on a thermostatic shaker at 200 rpm and 35 C, maintaining the pH at 7.5 (Kim et al., 2007, 2008a). The specific nitrification and denitrification rate were calculated following the equation provided by Kim et al. (2008b).
2.4.
DNA extraction
One milliliter of the sample was centrifuged at 16,000 g for 5 min before the supernatant was decanted. The pellet was washed with 1 mL of deionized and distilled water (DDW) and centrifuged again in the same manner to ensure a maximal removal of residual medium. The supernatant was carefully removed, and the pellet was resuspended in 100 mL of DDW. All DNA in the suspension was immediately extracted using an automated nucleic acid extractor (Magtration System 6GC, PSS, Chiba, Japan). Purified DNA was eluted with 100 mL of TriseHCl buffer (pH 8.0) and stored at 20 C for further analyses.
2.5.
T-RFLP analysis
T-RFLP was used to analyze the nitrifying bacteria community in the pre-denitrification process reactor based on the known
1269
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 6 7 e1 2 7 9
16S rDNA genes of AOB and NOB, as was described in the protocol of a previous study (Siripong and Rittmann, 2007). Considering the low concentration of DNA from the nitrifiers, we amplified DNA through nested PCR, using the universal primers 11f and 1492r (Table 1), followed by the specific amplification of nitrifier genes (Nitrifier-specific reverse primer: Nso1225r, NIT3r, Ntspa685r, Forward primer: Eub338f included phosphoramidite dye 6-FAM, Table 1) (Siripong and Rittmann, 2007). We used 2 mL of template DNA for the universal amplification step and 1 mL of the universal amplification product as the template for the nitrifier-specific amplification. Finally, we purified the PCR products and digested 16S rDNA gene amplicons with MspI restriction endonuclease (Siripong and Rittmann, 2007). Digested PCR products were run through an ABI 3130XL Genetic Analyzer (Applied Biosystems, Foster City, USA) at the SolGent Company (Korea). The peak results were analyzed using the Peak Scanner software v 1.0 (https:// products.appliedbiosystems.com; Applied Biosystems, Foster City, USA). Details of the PCR conditions, product purification and restriction digestion are provided elsewhere (Siripong and Rittmann, 2007).
2.6.
qPCR analysis
To investigate the changes in the nitrifying and denitrifying bacteria populations according to the variation of the process
performance, all qPCR assays were performed using a 7300 Real-Time PCR system (Applied Biosystems, Foster City, USA). To determine the amount of the nitrifying bacteria, four independent qPCR assays were conducted by quantifying total bacterial 16S rDNA, ammonia oxidizing bacterial 16S rDNA, Nitrospira spp. 16S rDNA, and Nitrobacter spp. 16S rDNA (Table 1). Each capillary tube was separately loaded with 2 mL of template DNA (at 14e26 ng/mL), followed by 4.0 pmol of the forward and reverse primers (1 mL), together with 2.0 pmol of the TaqMan probe (0.5 mL) corresponding to each primer and probe set, 12.5 mL of TaqMan Universal PCR Master Mix (No 4304437 Applied Biosystems, New Jersey, USA), and PCR-grade sterile water for a final volume of 25 mL. The amount of total bacterial 16S rDNA was amplified using primer (1055f and 1392r) (Ferris et al., 1996). The TaqMan probe (16S Taq1115) was modified by the 1114f primer (Harms et al., 2003). The PCR program was 2 min at 50 C, 10 min at 95 C; 45 cycles of 30 s at 95 C, 60 s at 50 C, and 40 s at 72 C. To determine the amount of AOB 16S rDNA genes, two forward primers (CTO 189A/B and CTO 189C), one reverse (RT1r), and the TaqMan probe (TMP1) were used as described previously by Hermansson and Lindgren (2001). The PCR program for AOB 16S rDNA quantification included 2 min at 50 C, 10 min at 95 C; 40 cycles of 30 s at 95 C, 60 s at 60 C. The Nitrospira spp. 16S rDNA primers (NSR 1113f/NSR 1264r) (Dionisi et al., 2002) and the TaqMan probe (NSR 1143Taq) (Harms et al.,
Table 1 e Primers and probes used in T-RFLP and qPCR. Target For T-RFLP Bacterial 16S rDNA Bacterial 16S rDNA AOB 16S rDNA Nitrobacter 16S rDNA Nitrospira 16S rDNA For qPCR Bacterial 16S rDNA
AOB 16S rDNA
Nitrospira spp. 16S rDNA
Nitrobacter spp. 16S rDNA
narG gene nirS gene nirK gene nosZ gene
Primer/probe
Sequence (50 e30 )
References
11f 1492r Eub 338f Nso 1225r NTT 3r Ntspa 685r
50 -GTTTGATCCTGGCTCAG-30 50 -TACCTTGTTACGACTT-30 50 -(6-FAM)-ACTCCTACGGGAGGCAGC-30 50 -CGCCATTGTATTACGTGTGA-30 50 -CCTGTGCTCCATGCTCCG-30 50 -CGGGAATTCCGCGCTC-30
Kane et al., 1993 Lin and Stahl, 1995 Amann et al., 1990 Mobarry et al., 1996 Wagner et al., 1995 Regan et al., 2002
1055f 1392r 16S Taq1115 CTO 189fA/Ba CTO 189fCa RT1r TMP1 NSR 1113f NSR 1264r NSR 1143Taq Nitro 1198f Nitro 1423r Nitro 1374Taq narG 1960m2f narG 2050m2r nirS 1f nirS 3r nirK 876 nirK 1040 nosZ 2f nosZ 2r
50 -ATGGCTGTCGTCAGCT-30 50 -ACGGGCGGTGTGTAC-30 50 -(6-FAM)-CAACGAGCGCAACCC-(TAMRA)-30 50 -GGAGRAAAGCAGGGGATCG-30 50 -GGAGGAAAGTAGGGGATCG-30 50 -CGTCCTCTCAGACCARCTACTG-30 50 -(6-FAM)-CAACTAGCTAATCAGRCATCRGCCGCT-(TAMRA)-30 50 -CCTGCTTTCAGTTGCTACCG-30 50 -GTTTGCAGCGCTTTGTACCG-30 50 -(6-FAM)-AGCACTCTGAAAGGACTGCCCAGG-(TAMRA)-30 50 -ACCCCTAGCAAATCTCAAAAAACCG-30 50 -CTTCACCCCAGTCGCTGACC-30 50 -(6-FAM)-AACCCGCAAGGAGGCAGCCGACC-(TAMRA)-30 50 -TAYGTSGGGCAGGARAAACTG-30 50 -CGTAGAAGAAGCTGGTGCTGTT-30 50 -TACCACCCSGARCCGCGCGT-30 50 -GCCGCCGTCRTGVAGGAA-30 50 -ATYGGCGGVCAYGGCGA-30 50 -GCCTCGATCAGRTTRTGGTT-30 50 -CGCRACGGCAASAAGGTSMSSGT-30 50 -CAKRTGCAKSGCRTGGCAGAA-30
Ferris et al., 1996 Ferris et al., 1996 Harms et al., 2003 Hermansson and Lindgren, Hermansson and Lindgren, Hermansson and Lindgren, Hermansson and Lindgren, Dionisi et al., 2002 Dionisi et al., 2002 Harms et al., 2003 Graham et al., 2007 Graham et al., 2007 Graham et al., 2007 Lo´pez-Gutie´rrez et al., 2004 Lo´pez-Gutie´rrez et al., 2004 Braker et al., 1998 Braker et al., 1998 Henry et al., 2004 Henry et al., 2004 Henry et al., 2006 Henry et al., 2006
a A mixture of CTO 189fA/B and CTO 189fC at the weight ratio of 2:1 was used as the forward primer.
2001 2001 2001 2001
1270
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 6 7 e1 2 7 9
2003) were tested. PCR amplification consisted of 2 min at 50 C, 10 min at 95 C; 50 cycles of 30 s at 95 C, 60 s at 60 C. Lastly, the amount of Nitrobacter spp. from Graham et al. (2007) was amplified using primer (Nitro 1198f/Nitro 1423r) and TaqMan probe (Nitro 1374Taq). The program used for amplification was 2 min at 50 C, 10 min at 95 C; 50 cycles of 20 s at 94 C, 60 s at 58 C, and 40 s at 72 C. Meanwhile, the denitrifying functional genes were quantified with SYBR Premix Ex Tag (Takara, Japan). Amplification reactions were performed in a volume of 25 mL loaded with 2 mL of template DNA (at 17.5e22.5 ng/mL), 4.0 pmol of the forward and reverse primers (1 mL), together with 0.5 mL (1X) of the ROX reference dye (50X), 12.5 mL of SYBR Premix, and PCR-grade sterile water. The qPCR program for 16S rDNA amplification using (primer 1055f and 1392r) was 30 s at 95 C; 30 cycles of 15 s at 95 C, 20 s at 55 C, and 31 s at 72 C. Primers designed by Lo´pezGutie´rrez et al. (2004) were used to determine the amount of narG gene. The PCR program for narG gene quantification included 30 s at 95 C; 35 cycles of 15 s at 95 C, 30 s at 58 C, and 31 s at 72 C. The nirS gene PCR amplification using primers (nirS 1f and nirS 3r) (Braker et al., 1998) consisted of 30 s at 95 C; 30 cycles of 15 s at 95 C, 20 s at 60 C, and 31 s at 72 C. The PCR condition for nirK gene included 30 s at 95 C; 30 cycles of 15 s at 95 C, 30 s at 58 C, and 31 s at 72 C. Lastly, Primers (nosZ 2f and nosZ 2r) designed by Henry et al. (2006) were used to determine the amount of nosZ gene. The program used for amplification was 30 s at 95 C; 30 cycles of 15 s at 95 C, 30 s at 60 C, and 31 s at 72 C.
All experiments were performed in duplicate per sample and all PCR runs included control reactions without the template. The specificity of each PCR assay was confirmed using both melting curve analysis and agarose gel electrophoresis. The gene copy numbers were calculated through a comparison of threshold cycles obtained in each PCR run with those of known standard DNA concentrations. Standards were prepared using serially diluted plasmid DNA with 103e108 gene copies/mL. Standard curves for the 16S rDNA, AOB, Nitrospira spp., Nitrobacter spp., narG, nirS, nirK, and nosZ assays were generated by plotting the threshold cycle values versus log10 of the gene copy numbers. The amplification efficiency (E ) was estimated using the slope of the standard curve through the following formula: E ¼ ð101=slope Þ 1. The efficiency of PCR amplification for each gene was between 90% and 100%.
2.7.
Analytical methods
The collected samples were centrifuged at 3500 rpm for 3 min (MF550, Hanil Sci. Ind., Korea), and then the supernatants were used for the following analyses. According to standard methods (APHA, 1998), COD, ammonia, phenol, and SCN were analyzed by the colorimetric method with a spectrophotometer (Genesys TM-5, Spectronic Inc., USA). The CN concentration was determined by the pyridine-pyrazolone method after distillation. Nitrite and nitrate ions were measured with an ion
Fig. 1 e Variation of influent- and effluent concentrations of CNL in the lab-scale pre-denitrification process during the shock loading of CNL.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 6 7 e1 2 7 9
chromatograph (ICS-1000, Dionex Co., USA). TOC, inorganic carbon (IC), and TN were measured with a TOC/TN analyzer (TOC-V csu, TNM-1, Shimadzu Co., Japan).
3.
Results and discussion
3.1.
The pollutants removal performance
After stable operation of the lab-scale reactor was achieved, extra CN was added into the feed for 5 days to examine its effects on the nitrification and denitrification as well as the removal of other pollutants. Fig. 1 shows the variation of effluent CN from the reactors under different CN shock loading conditions. During the first shock loading (15 mg/L for 5 days), CN concentration in the effluent of the anoxic reactor was maintained below 0.4 mg/L. As the loading concentration of CN into the anoxic reactor increased to 50 mg/L, however, CN concentration in the effluent from the anoxic reactor gradually increased to 2.0 mg/L, thus the CN removal efficiency of the anoxic reactor slightly decreased from 84% to
1271
76%. Meantime, the remaining CN in the aerobic reactor was completely removed in the aerobic reactor during the first and second shock loading periods. From third shock loading (30 mg/L for 5 days), however, over 1.0 mg/L CN flowed from the anoxic reactor into the aerobic reactor, resulting in the detection of CN in the range of below 0.2 mg/L. It must be noted that removal efficiency of CN in the aerobic reactor was not so efficient in this study. The removal efficiency of phenol was not affected by the shock loading of CN (Fig. 2(a)), and was always maintained at higher than 98%. The aerobic degradation of phenol is known to be fast in an activated sludge system, so its degradation may not be inhibited by CN. Staib and Lant (2007) also did not observe a toxic effect on phenol biodegradation by CN in their study with real cokes wastewater. On the other hand, the CN shock loading test showed inhibition of SCN removal performance in the pre-denitrification process (Fig. 2(b)). This means that CN is an inhibitor of SCN biodegradation. Figs. 1 and 2(b) show the SCN removal pattern corresponding to the variation of CN concentration. When the CN concentration flowing into the aerobic reactor reached to 2.0 mg/L, SCN removal was totally inhibited. This result was similar to the
Fig. 2 e Variation of influent- and effluent concentrations and final removal efficiencies of (a) phenol, (b) SCNL in the lab-scale pre-denitrification process during the shock loading of CNL.
1272
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 6 7 e1 2 7 9
threshold level of CN on SCN removal reported in another previous study (Staib and Lant, 2007). Fig. 3 shows the COD and TOC values of the effluent of the anoxic and aerobic reactors, as well as final efficiency at different CN shock loading. Before increasing CN concentration in the influent feed to 30 mg/L, effluent COD and TOC concentrations in the anoxic and aerobic reactors were consistent with no inhibition of carbon removal. Final removal efficiencies of COD and TOC were maintained at 88%. When the CN concentration in the influent increased to 30 mg/L, however, COD and TOC removal efficiencies decreased to about 81%, and then recovered to normal performance level when the shock loading was stopped. Under the fourth shock load corresponding to 50 mg/L CN in the influent, final removal efficiencies of COD and TOC were observed at 67% and 72%, and the effluent COD and TOC concentrations in the aerobic reactor reached to 700 mg/L and 150 mg/L, respectively. This might be due to the inhibition of SCN biodegradation by CN. Effluent concentrations of COD and TOC increased in ratios of about 1.5 mg-COD/ mg-SCN and 0.4 mg-TOC/mg-SCN with increasing SCN concentration in the aerobic reactor (Fig. 2(b) and 3). To sum up,
the removal behavior of organic matters was affected by SCN biodegradation efficiency.
3.2.
Nitrification and denitrification performance
The main role of the aerobic reactor in the activated sludge system was to nitrify ammonia into nitrite and/or nitrate. Fig. 4(a) shows not only the variation of ammonia concentration, but also the total removal efficiency via nitrification. The ammonia concentration in the feed of industrial wastewater ranged between 103 and 119 mg-N/L. Until the second CN shock loading (20 mg/L for 5 days) was done, the ammonia concentration in the aerobic effluent was maintained at below 2.0 mg-N/L, corresponding to a total removal efficiency of more than 97%. Therefore, it took only 5 days to stabilize the reactor performance. Under the third shock load (30 mg/L for 5 days), ammonia concentration in the aerobic reactor effluent reached to 36 mg-N/L, and the total ammonia removal efficiency decreased to 67%. After the 30 mg/L CN loading was stopped, the system took 14 days to come back to normal performance level. Finally, when the CN
Fig. 3 e Variation of influent- and effluent concentrations and final removal efficiencies of (a) COD (b) TOC in the lab-scale pre-denitrification process during the shock loading of CNL.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 6 7 e1 2 7 9
1273
Fig. 4 e Variation of influent- and effluent concentrations of (a) ammonia, (b) nitrite/nitrate in the lab-scale pre-denitrification process during the shock loading of CNL.
concentration in the influent feed increased to 50 mg/L, ammonia concentration in the aerobic reactor effluent increased to 100 mg-N/L and nitrification efficiency sharply decreased to 8.0%, resulting in severe nitrification performance damage. Contrary to the 0.1 mg/L CN threshold level on nitrification observed in a batch system (Neufeld et al., 1986), above 1.0 mg/L CN inflow inhibited nitrification performance in this continuous system. Interestingly, the threshold level of the CN on nitrification was the same as that on SCN removal in this study. The nitrification performance, which was severely damaged by CN shock loading, could be gradually recovered to normal performance level, but took much longer than SCN removal recovery. Fig. 4(b) shows variation of the NOxeN (nitrite þ nitrate) concentration generated from nitrification and denitrification reactions at different CN shock loadings. During the first shock loading (15 mg/L for 5 days), about only 2.5 mg/L CN flowed into the anoxic reactor due to the diluting effect of the internal recycling ratio. However, denitrification efficiency decreased to 75%, and a concentration of nitrite in the anoxic
effluent gradually accumulated. In addition, some of the nitrate recycled from the aerobic reactor was not fully denitrified. As more CN was removed in the anoxic reactor (Fig. 1), nitrate concentration decreased to below 1.0 mg-N/L, but nitrite concentration increased to 15 mg-N/L. These results indicated that the denitrification performance catalyzed by the nitrite reductase might be more sensitive to CN toxicity than by the nitrate reductase. Meanwhile, nitrite concentration gradually accumulated 17 mg-N/L in the aerobic effluent. This result might be due to the inhibition of the nitrite oxydase by nitrite accumulation (Kelly et al., 2004) as well as increased nitrite concentration flowing from the anoxic effluent. At the second shock loading, we could not find denitrification inhibition. This indicates that the denitrifying bacteria might have adapted to toxic CN to some degree during the first shock loading of CN. As the CN concentration into the aerobic reactor increased to over 1.0 mg/L at the third shock loading, nitrate concentration began to drop from 40 to 5.0 mg-N/L sharply, and nitrite concentration accumulated to 47 mg-N/L, while no significant increase in ammonia
1274
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 6 7 e1 2 7 9
was seen. This result suggests NOB may be more sensitive to the toxic CN shock than AOB. A similar result was observed in a previous study (Kelly et al., 2004), but the exact reason for the increased sensitivity of the NOB vs. the AOB remains unidentified (Kelly et al., 2004). Meanwhile, denitrification was achieved irrespectively of nitrification inhibition, and the pH level was also maintained at between 8.5 and 9.0, but ORP level slightly increased to 170 mV. After the reactor performance was stabilized, the fourth shock loading was begun. As soon as increased CN concentration flowed into the aerobic reactor, the nitrification performance was totally inhibited. No nitrate concentration was detected and nitrite concentration decreased to below 2.0 mg-N/L. In the aerobic reactor, the pH level increased to 8.3 and the ORP level decreased to 200 (data not shown). Therefore, 2.0 mg/L CN could be considered the threshold concentration on the nitrification performance in this activated sludge process (Figs. 1 and 4). In the case of the denitrification performance at the fourth shock loading, it could be determined that the denitrification did not occur through the toxicity of high concentration CN as well as providing no substrate such as nitrite or nitrate ion by the nitrification inhibition. Fig. 5 shows the variation of TN concentrations in the reactor and the total removal efficiency. The concentration of TN in raw wastewater ranged between 186 and 218 mg-N/L, and the TN was consistently kept below 60 mg-N/L through the pre-denitrification process until before the 30 mg/L CN shock loading. At the third and fourth CN shock loading, however, nitrification and SCN biodegradation were inhibited, resulting
in the increase of effluent TN concentration to 125 mg-N/L, corresponding to the decrease of TN removal efficiency to 36%. In the range of the CN shock loading from 15 to 20 mg/L, more than 90% of TN in the final effluent was in the form of nitrites and nitrates generated by nitrification. At the fourth shock loading, however, the fraction of nitrites and nitrates in the effluent reduced to almost zero and the fraction of other nitrogen compounds, such as ammonia and SCN, accounted for all TN concentrations in the final effluent.
3.3.
Microbial activity
Batch experiments in observation of the variations of nitrification and denitrification activities in the activated sludge process were carried out. The specific nitrification and denitrification rate in the batch test was analyzed through the variations of ammonia, nitrite and nitrate concentrations. As shown in Fig. 6, nitrifying and denitrifying bacteria activities were changed according to CN shock loading. Until the third shock loading (from 10 to 30 mg/L CN concentration inflow), the specific nitrification rate was not drastically changed according to the variation of CN inflow. The specific nitrification rate on normal performance was maintained at about 4.0 mg-N/g-VSS h. As CN concentration in the influent reached 50 mg/L, however, the specific nitrification rate decreased four times more than the normal performance. Therefore, we could additionally confirm that the nitrification activity significantly decreased through the batch test as the continuous process appeared to be inhibited. Like the recovery
Fig. 5 e Variation of influent- and effluent concentrations and final removal efficiencies of TN in the lab-scale pre-denitrification process during the shock loading of CNL.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 6 7 e1 2 7 9
Fig. 6 e Variation of nitrification and denitrification activities by batch test during the shock loading of CNL.
pattern of the nitrification performance shown in Fig. 4, the specific nitrification rate increased to its normal performance level after the shock loads were stopped. As shown in Fig. 6, the specific denitrification rate changed rapidly, unlike the variation of the nitrification activity. Under normal conditions, the specific denitrification rate maintained in the range of 7.3e8.6 mg-N/g-VSS h, but it considerably decreased by more than half, when CN was added into the process. It is very interesting that the complete denitrification of the process was achieved even during the second and third shock loading periods, in spite of the considerable decrease of the denitrification rate (Figs. 4 and 6). Similarly, upon the administration of the fourth shock load (50 mg/L CN), the denitrification activity was significantly inhibited, corresponding to the decrease of the specific denitrification rate from 8.4 to 0.4 mg-N/g-VSS h. After being returned into normal condition, however, the denitrification activity of the process rapidly recovered to the normal performance.
3.4.
Microbial community
We determined the nitrifying bacterial communities present in the activated sludge process using T-RFLP designed for the identification of AOB and NOB with terminal fragment (TF) lengths (Regan et al., 2002). Figs. 7 and 8 show electropherograms of AOB, Nitrobacter-specific NOB, and Nitrospira-specific NOB, respectively, according to the variation of CN shock loading. As shown in Fig. 7, AOB-targeted T-RFLP allowed us to differentiate between AOB groups. All samples from each different loading condition showed a peak at 164 bp, a signature peak of Nitrosomonas europaea/eutropha and Nitrosomonas marina lineage (Table 2). Because the influents are from industrial wastewater, marine AOB species are not relevant. Besides the major peak at 164 bp, we detected a peak at 273 bp, which represents the potential presence of N. europaea/eutropha, Nitrosomonas oligotropha, Nitrosomonas cryotolerans, or
1275
Nitrosomonas communis lineage (Table 2). We also observed a peak at 102 bp, which indicates the presence of the Nitrosospira lineage. This 102 bp peak was detected from the third shock load (30 mg/L CN). When the nitrification was inhibited, the 102 bp peak appeared, and became the major peak of the 50 mg/L CN loading period when the nitrification was totally inhibited. As the nitrification recovered to normal performance, the 102 bp peak gradually disappeared. To obtain a finer understanding of the AOB community present in the process, AOB 16S rDNA gene based cloning and sequencing was performed using the AOB-target primer (Nso1225r and Eub338f) without the fluorescent dye (Table 1). Eighty-two of total 87 AOB clones from the reactor were closely associated with N. europaea in the N. europaea/ eutropha lineage and N. nitrosa in the N. communis lineage, and the rest of the AOB clones related to the Nitrosospira lineage were also detected. As a result, through the 16S rDNA gene sequences, the microorganisms corresponding to the peaks at 102 bp, 164 bp, and 273 bp could be identified as Nitrosospira, N. europaea, and N. nitrosa lineage, respectively (Table 2). Thus, the high peak at 164 bp implies the dominance of N. europaea of AOB in this activated sludge process, irrespective of the variation of CN shock loading. N. nitrosa corresponding to the 273 bp peak was dominant with N. europaea at each recovery stage, but became a minor population during CN loading (Fig. 7). Meanwhile, Nitrosospira sp. was found to be predominant in habitats exposed to the highly toxic CN concentration (Fig. 7). Although microbial shifts were clearly not observed from Nitrosomonas sp. to Nitrosospira sp. in the inhibited nitrifying system, due to the dominance of N. europaea, these results showed Nitrosospira sp. could tolerate higher CN toxicity. Many studies have found a competitive dominance between the two AOB species in habitats exposed to low-substrate or DO and metal toxicity (Schramm et al., 1999; Mertoglu et al., 2008), but there have been few reports on the AOB community changing in relation to CN toxicity. Based on Nitrobacter-specific T-RFLP, Fig. 8(a) shows a prominent peak at 137 bp, which belongs to Nitrobacter species. We also found TF sizes at 93, 104, 125, 163, and 273 in the samples. These unexpected peaks could be the result of an incomplete digestion, uncharacterized Nitrobacter species, or imperfectly matched primer (Siripong and Rittmann, 2007). The results of Nitrospira-specific T-RFLP showed two dominant peaks at 272 and 334 bp. (Fig. 8(b)). The peak at 272 corresponds to several Nitrospira clones in the database. The 334 TF belongs to one of the Nitrospira moscoviensis strains (Siripong and Rittmann, 2007). The Nitrospira species corresponding to the peak at 272 bp and 334 bp was a consistently dominant population under the variation of CN loading, but the dominance between the Nitrospira species in the reactor shifted to the Nitrospira species corresponding to the peak at 136 bp and 164 bp, when the totally inhibited nitrification of the 50 mg/L CN loading gradually recovered. Fig. 9(a) shows the changes in the 16S rDNA gene copies for the total bacteria, AOB, Nitrobacter, and Nitrospira, quantified using qPCR assays in the aerobic reactor of the predenitrification process under CN shock loadings. In all samples, the total bacterial population in the aerobic reactor ranged from 1.2 1013 to 3.6 1013 copies/L and remained
1276
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 6 7 e1 2 7 9
Fig. 7 e T-RFLP profiles of AOB in the aerobic reactor during the shock loading of CNL.
constant during the shock loading of CN. These values are in the same order of magnitude as those obtained from activated sludge samples of the sewage from WWTPs (Limpiyakorn et al., 2005). The concentration of AOB determined using the AOB 16S rDNA assay was almost consistent. However, while the AOB number slightly decreased at every CN shock load stage, it gradually increased at the recovery stage. As the 2.0 mg/L CN concentration flowed into the aerobic reactor, however, an approximately 3-fold decrease was observed in the number of AOB 16S copies/L. After CN loading was stopped, the number of AOB 16S copies/L recovered to the level of the normal performance. Thus, the increase or decrease of the AOB number might affect nitrification activity (Fig. 6). Meanwhile, the percentages of the AOB within the total bacteria varied from 0.36 to 1.71% in the aerobic reactor. Contrary to expectation, the activated sludge with normal nitrification activity did not have a higher percentage of AOB than that which had inhibited nitrification activity. Thus, the AOB/bacterial ratio did not correlate with the nitrification activity.
We also observed coexisting Nitrospira and Nitrobacter genera for NOB. The Nitrospira and Nitrobacter populations in the initial operating condition were similar, at 1.0 1011 copies/L and 2.0 1010 copies/L, respectively. However, a shift in the NOB community was observed as the CN loading progressed. The 16S rDNA gene concentration of the Nitrobacter increased to a range of 2.0 1010e6.2 1010 copies/L, and the percentages of the Nitrobacter population within the total bacteria also sharply increased from 0.07 to 0.54% in the aerobic reactor, irrespective of CN shock loading. Finally, after the 30 mg/L CN shock loading, the Nitrobacter populations in the nitrifying system were higher than the Nitrospira populations. On the other hand, the number of Nitrospira gradually decreased from 1.0 1011 to 2.2 1010 copies/L, until the third shock loads (30 mg/L CN). When the 50 mg/L CN concentration in the influent was allowed to flow into the activated sludge process, a 10-fold decrease was observed in the number of Nitrospira 16S copies/L. The percentage of the Nitrospira population within the total bacteria shrank to 0.01%. The previous research reported that Nitrospira were far more
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 6 7 e1 2 7 9
1277
Fig. 8 e T-RFLP profiles of (a) Nitrobacter (b) Nitrospira in the aerobic reactor during the shock loading of CNL.
sensitive to the toxicity of free ammonia than Nitrobacter (Blackburne et al., 2007). Meanwhile, the abundance of narG, nirS, nirK, and nosZ genes of denitrifying bacteria was investigated during the CN shock loading in the activated sludge process. The narG, nirS, nirK, and nosZ target molecules were less abundant than the 16S rDNA gene copies for the total bacteria: total bacteria ranged from 1.8 1013 to 3.7 1013 copies/L, narG ranged from 3.8 109 to 1.7 1010 copies/L, nirS ranged from 1.9 y 1012 to 1.3 y 1013 copies/L, nirK ranged from 4.4 1010 to 1.7 1011 copies/ L, and nosZ ranged from 1.7 1011 to 8.3 1011 copies/L (Fig. 9 (b)). In the activated sludge process treating industrial wastewater, the gene copy numbers per liter of the nirS gene were higher than those of the narG and nosZ genes at all
Table 2 e Expected TF sizes and their corresponding AOB and NOB groups based on T-RFLP of 16S rDNA gene (Siripong and Rittmann, 2007). TF size (bp) 164e166, 276 276 276 166 276 105e107 141, 196 133, 194, 265e267, 277,333
Nitrifying bacteria group Nitrosomonas europaea/eutropha lineage Nitrosomonas oligotropha lineage Nitrosomonas cryotolerans lineage Nitrosomonas marina lineage Nitrosomonas communis lineage Nitrosospira lineage Nitrobacter species Nitrospira species
sampling points. This trend implies that there is a greater abundance of genes for the nitrite-reducing genes than for the nitrate and nitrous oxide reducing genes. There was no major difference in the copy numbers of all of the genes during the CN shock loading progression, but the copy numbers of narG and nosZ genes decreased 3-fold after the 50 mg/L CN in the influent was allowed to flow into the activated sludge process. Meanwhile, for nirS, the copy numbers of genes detected were much higher than those for nirK at all sampling points. It is known that the more taxonomically diverse nirK denitrifiers are more sensitive to environmental changes than the nirS denitrifiers; however, the latter are more abundant (Yoshie et al., 2004). According to CN shock loading, however, the sensitivity of nirK denitrifiers to CN toxicity was not found in this study. To evaluate the abundance of denitrifies relative to total bacteria, percentages of denitrification genes in proportion to 16S rDNA were calculated, which resulted in proportions of around 0.03%, 17.9%, 0.34%, and 1.41% for narG, nirS, nirK, and nosZ genes respectively. The maximum abundance of nirS relative to 16S rDNA was 31%, confirming the high proportion of denitrifiers to total bacteria in this activated sludge process. However, a correlation between the abundance of functional genes and the denitrifying activity was not observed in the experimental period. Lastly, it should be noted that the presence of functional genes for target microorganisms in the activated sludge samples does not necessarily indicate that the corresponding bacteria present in the activated sludge will display the expected activities (Philippot and Hallin, 2005).
1278
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 6 7 e1 2 7 9
but Nitrosospira sp. became dominant at the 30 and 50 mg/L CN shock loadings. Among the NOB, Nitrobacter and Nitrospira co-existed, Nitrospira seem to be more sensitive to CN. Meanwhile, in denitrifying genes from industrial activated sludge, nitrite-reducing functional genes (i.e., nirS ) were dominant in the anoxic reactor.
Acknowledgement This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (No. 2010-0001437). This work was also partially supported by the second phase of the Brain Korea 21 Program in 2010 as well as by the Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the MEST (2009-0093819). The authors thank Dr. Seungyong Lee, Dr. Seung Gu Shin, and Min Ji Kim for assistance during this work.
references
Fig. 9 e Changes in copies per liter of (a) the total bacteria, AOB, Nitrobacter, and Nitrospira (b) the total bacteria, narG, nirS, nirK, nosZ in the lab-scale pre-denitrification process during the shock loading of CNL.
4.
Conclusions
The microbial communities and reactor performance under gradually increased CN loading were monitored in a lab-scale industrial activated sludge process using T-RFLP and qPCR. The performance of phenol degradation did not appear to be adversely affected by increases in CN concentrations. In contrast, CN- significantly inhibited SCN biodegradation, resulting in the increase of TOC and COD concentrations. Nitratation also appeared to be inhibited at CN concentrations in excess of 1.0 mg/L, confirming that NOB is more sensitive to the toxic CN than AOB. After CN loads were stopped, SCN removal, denitrification, and nitrification affected by CN toxicity recovered to normal performance. During the operation, N. europaea as the AOB was dominant,
Amann, R.I., Binder, R.J., Olson, S., Chisholm, S.W., Devereux, R., Stahl, D.A., 1990. Combination of 16S ribosomal RNA targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Appl. Environ. Microbiol. 56, 1919e1925. APHA, 1998. Standard Methods for the Examination of Water and Wastewater. APHA, AWWA, WPCF, twentieth ed.. American Public Health Association, Washington, DC, USA. Blackburne, R., Vadivelu, V.M., Yuan, Z.G., Keller, J., 2007. Kinetic characterisation of an enriched Nitrospira culture with comparison to Nitrobacter. Water Res. 41, 3033e3042. Braker, G., Fesefeldt, A., Witzel, K.P., 1998. Development of PCR primer systems for amplification of nitrite reductase genes (nirK and nirS ) to detect denitrifying bacteria in environmental samples. Appl. Environ. Microbiol. 64, 3769e3775. Dionisi, H.M., Layton, A.C., Harms, G., Gregory, I.R., Robinson, K.G., Sayler, G.S., 2002. Quantification of Nitrosomonas oligotrophalike ammonia-oxidizing bacteria and Nitrospira spp. from fullscale wastewater treatment plants by competitive PCR. Appl. Environ. Microbiol. 68, 245e253. Ferris, M.J., Muyzer, G., Ward, D.M., 1996. Denaturing gradient gel electrophoresis profiles of 16S rRNA-defined populations inhabiting a hot spring microbial mat community. Appl. Environ. Microbiol. 62, 340e346. Graham, D.W., Knapp, C.W., Van Vleck, E.S., Bloor, K., Lane, T., Graham, C.E., 2007. Experimental demonstration of chaotic instability in biological nitrification. ISME J. 1, 385e394. Harms, G., Layton, A.C., Dionisi, H.M., Gregory, I.R., Garrett, V.M., Hawkins, S.A., Robinson, K.G., Sayler, G.S., 2003. Real-time PCR quantification of nitrifying bacteria in a municipal wastewater treatment plant. Environ. Sci. Technol. 37, 343e351. Henry, S., Baudouin, E., Lo´pez-Gutie´rrez, J.C., Martin-Laurent, F., Brauman, A., Philippot, L., 2004. Quantification of denitrifying bacteria in soils by nirK gene targeted real-time PCR. J. Microbiol. Methods 59, 327e335. Henry, S., Bru, D., Stres, B., Hallet, S., Philippot, L., 2006. Quantitative detection of the nosZ gene, encoding nitrous oxide reductase, and comparison of the abundances of 16S rRNA, narG, nirK, and nosZ genes in soils. Appl. Environ. Microbiol. 72, 5181e5189.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 6 7 e1 2 7 9
Hermansson, A., Lindgren, P.E., 2001. Quantification of ammoniaoxidizing bacteria in arable soil by real time PCR. Appl. Environ. Microbiol. 67, 972e976. Juliastuti, S.R., Baeyens, J., Creemers, C., 2003. Inhibition of nitrification by heavy metals and organic compounds: the ISO 9509 test. Environ. Eng. Sci. 20, 70e90. Kane, M.D., Poulsen, L.K., Stahl, D.A., 1993. Monitoring the enrichment and isolation of sulfate-reducing bacteria by using oligonucleotide hybridization probes designed from environmentally derived 16S ribosomal RNA sequences. Appl. Environ. Microbiol. 59, 682e686. Kelly, R.T., Henriques, I.D., Love, N.G., 2004. Chemical inhibition of nitrification in activated sludge. Biotechnol. Bioeng. 85, 683e694. Kim, Y.M., Park, D., Lee, D.S., Park, J.M., 2007. Instability of biological nitrogen removal in a cokes wastewater treatment facility during summer. J. Hazard. Mater. 141, 27e32. Kim, Y.M., Park, D., Ahn, C.K., Lee, M.W., Park, J.M., 2008a. Temperature-dependent effects of pollutants on biological denitrification process for treating cokes wastewater. Korean Chem. Eng. Res. 46, 1124e1129. Kim, Y.M., Park, D., Lee, D.S., Park, J.M., 2008b. Inhibitory effects of toxic compounds on nitrification process for cokes wastewater treatment. J. Hazard. Mater. 152, 915e921. Kim, Y.M., Park, D., Lee, D.S., Jung, K.A., Park, J.M., 2009. Sudden failure of biological nitrogen and carbon removal in the fullscale pre-denitrification process treating cokes wastewater. Bioresour. Technol. 100, 4340e4347. Lewandowski, Z., 1984. Biological denitrification in the presence of cyanide. Water Res. 18, 289e297. Limpiyakorn, T., Shiohara, Y., Kurisu, F., Yagi, O., 2005. Communities of ammonia-oxidizing bacteria in activated sludge of various sewage treatment plants in Tokyo. FEMS Microbiol. Ecol. 54, 205e217. Lin, C., Stahl, D.A., 1995. Comparative analyses reveal a highly conserved endoglucanase in the cellulolytic genus Fibrobacter. J. Bacteriol. 177, 2543e2549. Lo´pez-Gutie´rrez, J.C., Henry, S., Hallet, S., Martin-Laurent, F., Catrou, G., Philippot, L., 2004. Quantification of a novel group of nitrate-reducing bacteria in the environment by real-time PCR. J. Microbiol. Methods 57, 399e407. Mertoglu, B., Semerci, N., Guler, N., Calli, B., Cecen, B., Saatci, A.M., 2008. Monitoring of population shift in an enrich nitrifying system under gradually increased cadmium loading. J. Hazard. Mater. 160, 495e501.
1279
Mobarry, B.K., Wagner, M., Urbain, V., Rittmann, B.E., Stahl, D.A., 1996. Phylogenetic probes for analyzing abundance and spatial organization of nitrifying bacteria. Appl. Environ. Microbiol. 62, 2156e2162. Neufeld, R., Greenfield, J., Rieder, B., 1986. Temperature, cyanide and phenolic nitrification inhibition. Water Res. 20, 633e642. Park, S., Ely, R.L., 2008. Whole-genome transcriptional and physiological responses of Nitrosomonas europaea to cyanide: identification of cyanide stress response genes. Biotechnol. Bioeng. 99, 1374e1383. Philippot, L., Hallin, S., 2005. Finding the missing link between diversity and activity using denitrifying bacteria as a model functional community. Curr. Opin. Microbiol. 8, 234e239. Regan, J.M., Harrington, G.W., Noguera, D.R., 2002. Ammonia- and nitrite-oxidizing bacterial communities in a pilot-scale chloraminated drinking water distribution system. Appl. Environ. Microbiol. 68, 73e81. Richards, D.J., Shieh, W.K., 1989. Anoxiceoxic activated sludge treatment of cyanides and phenols. Biotechnol. Bioeng. 33, 32e38. Schramm, A., de Beer, D., van den Heuvel, J.C., Ottengraf, S., Amann, R., 1999. Microscale distribution of populations and activities of Nitrosospira and Nitrospira spp. along a macroscale gradient in a nitrifying bioreactor: quantification by in situ hybridization and the use of microsensors. Appl. Environ. Microbiol. 65, 3690e3696. Siripong, S., Rittmann, B.E., 2007. Diversity study of nitrifying bacteria in full-scale municipal wastewater treatment plants. Water Res. 41 (5), 1110e1120. Staib, C., Lant, P., 2007. Thiocyanate degradation during activated sludge treatment of coke-ovens wastewater. Biochem. Eng. J. 34, 122e130. Wagner, M., Rath, G., Amann, R., Koops, H.P., Schleifer, K.H., 1995. In situ identification of ammonia-oxidizing bacteria. Syst. Appl. Microbiol. 18, 251e264. Wild, S.R., Rudd, T., Neller, A., 1994. Fate and effects of cyanide during wastewater treatment processes. Sci. Total Environ. 156, 93e107. Yoshie, S., Noda, N., Tsuneda, S., Hirata, A., Inamori, Y., 2004. Salinity decreases nitrite reductase gene diversity in denitrifying bacteria of wastewater treatment systems. Appl. Environ. Microbiol. 70, 3152e3157. Zumft, G., 1997. Cell biology and molecular basis of denitrification. Microbiol. Mol. Biol. Rev. 61, 533e536.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 8 0 e1 2 8 6
Available at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Direct and indirect photolysis of sulfamethoxazole and trimethoprim in wastewater treatment plant effluent Christopher C. Ryan, David T. Tan, William A. Arnold* Department of Civil Engineering, University of Minnesota, 500 Pillsbury Dr. SE, Minneapolis, MN 55455, USA
article info
abstract
Article history:
The photolysis of two antibacterial compounds, sulfamethoxazole and trimethoprim, was
Received 27 June 2010
studied in wastewater effluent. The rate of loss of sulfamethoxazole was enhanced in
Received in revised form
wastewater effluent due to indirect photolysis reactions, specifically reactions with
7 October 2010
hydroxyl radicals and triplet excited state effluent organic matter. Photolysis in the pres-
Accepted 9 October 2010
ence of natural organic matter, however, did not lead to enhanced degradation of sulfa-
Available online 16 October 2010
methoxazole. Trimethoprim was also found to be susceptible to indirect photolysis in wastewater effluents, with hydroxyl radical and triplet excited effluent organic matter
Keywords:
being the responsible species. Deoxygenation of solutions led to more rapid direct
Pharmaceuticals
photolysis of sulfamethoxazole and trimethoprim, indicating that direct photolysis
Photolysis
proceeds through a triplet excited state, which was verified by demonstrating that
Wastewater
trimethoprim is a singlet oxygen sensitizer. In the wastewater effluents tested, photolysis
Dissolved oxygen
could be apportioned into direct photolysis (48% for sulfamethoxazole, 18% for trimetho-
Triplet organic matter
prim), reaction with hydroxyl radicals (36% and 62%, respectively) and reaction with triplet
Nitrate
excited effluent organic matter (16% and 20%, respectively). These results indicate that allowing photolysis in wastewater stabilization ponds or wastewater treatment wetlands may lead to enhanced pharmaceutical removal prior to discharge and that effluent organic matter has different photoreactivity than natural organic matter. ª 2010 Elsevier Ltd. All rights reserved.
1.
Introduction
Sulfamethoxazole and trimethoprim are two human-use antibacterial compounds that are often prescribed together to treat various bacterial infections. Sulfamethoxazole belongs to the sulfonamide class of antibacterial compounds, while trimethoprim does not belong to any specific class. Antibiotics/antibacterials that are used by humans are not entirely metabolized by the digestive system and pass into the sanitary sewer system. At wastewater treatment plants, some fraction of the drugs entering the plants are degraded, but a portion may pass through, either sorbed to the waste solids or dissolved in the liquid effluent (Renew and Huang, 2004; Brown et al., 2006; Go¨bel et al., 2007; Batt et al., 2007).
The discharge of effluent or the application of solids to the land surface leads to the contamination of environmental systems with the residual pharmaceuticals (Kolpin et al., 2002; Kinney et al., 2008; Barber et al., 2009). Concerns about sulfamethoxazole and trimethoprim are related to the potential for resistance to be developed to this drug combination because of its widespread use. Since these compounds first began to be used in combination in 1968, the frequency of bacterial isolates showing resistance to the combination has gradually increased (Huovinen et al., 1995). Besides resistance developed through normal use, concerns exist about resistance developing due to bacteria being exposed to the drugs at low concentrations in the environment (Daughton and Ternes, 1999).
* Corresponding author. Tel.: þ1 612 625 8582; fax: þ1 612 626 7750. E-mail address:
[email protected] (W.A. Arnold). 0043-1354/$ e see front matter ª 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2010.10.005
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 8 0 e1 2 8 6
When sulfamethoxazole and trimethoprim reach environmental systems, there are multiple routes for their possible removal, including photodegradation, biodegradation, and partitioning to sediments. Focusing on photodegradation, previous work has found sulfamethoxazole to degrade predominantly by direct photolysis (Boreen et al., 2004; Lam and Mabury, 2005). Reported solar quantum yields (F) for photolysis of sulfamethoxazole are 0, 0.5, and 0.09 for the three protonation states, with the 0.09 value being relevant for most environmental conditions (pH > 7) (Boreen et al., 2004). Indirect photolysis was found to be important for sulfamethoxazole in one study, for adding nitrate or humic acids to solutions increased the degradation rates above what was observed for distilled water solutions (Andreozzi et al., 2003). Sulfamethoxazole was also found to act as a photosensitizer (Zhou and Moore, 1997), producing singlet oxygen and radical species. For trimethoprim, direct photolysis proceeds at slow rates under environmentally relevant conditions when compared to other pharmaceutical compounds (Lunestad et al., 1995; Zhou and Moore, 1997). A quantum yield of 3 104 (in methanol) was found, and trimethoprim degradation was sensitized by aromatic ketones (Dedola et al., 1999). Zhou and Moore (1997) found that trimethoprim did not generate singlet oxygen or radicals in solution upon photolysis. Photolysis is a potential means to limit the release of pharmaceuticals carried by wastewater effluents into the environment. An engineered ultraviolet light photolysis system could be used to photodegrade the compounds. Alternatively, photolysis in sunlight may occur in stabilization ponds or treatment wetlands. The photochemistry of pharmaceutical compounds in a wastewater matrix, however, has not yet been thoroughly evaluated. Natural surface waters are dominated by natural organic matter (NOM) as a photosensitizer, whereas wastewater effluents contain effluent organic matter (EfOM). EfOM has different characteristics than NOM (Shon et al., 2006), which may affect its photoreactivity. Additionally, wastewater effluents that have gone through a nitrification process will have potentially high levels of nitrate, which is a photosensitizer for the production of hydroxyl radicals (Blough and Zepp, 1995). In effluent dominated streams, the dissolved constituents in the effluent (organic matter, nitrate) may impact photolysis more so than the dissolved constituents in the upstream waters (e.g., natural organic matter), pointing to the need to understand photolysis in the wastewater matrix. The goal of this study was to examine various aspects of the direct and indirect photolysis of sulfamethoxazole and trimethoprim in wastewater effluents. The photolysis rates in ultrapure water, natural water, and wastewater effluent were compared to determine the important processes in each matrix.
2.
Materials and methods
2.1.
Chemicals
Sulfamethoxazole (98%), trimethoprim (98%), 4-chlorobenzoic acid (pCBA; 99%), perinaphthenone (97%), cimetidine (99%), 2-propanol (IPA; 99.5%), 4-nitroacetophenone (PNAP; 98%) and pyridine (99%) were purchased from SigmaeAldrich. Isoprene
1281
(99%), 4-nitroanisole (PNA; 99%) and 30 -methoxyacetophenone (98%) were purchased from Acros Organics. Nitrogen (zero grade) and oxygen (ultrapure grade) were purchased from Minneapolis Oxygen Company. Argon (zero grade) was obtained from Airgas. All solvents were high-performance liquid chromatography (HPLC) grade. Chemicals were used as received except for PNA, which was recrystallized before use. Ultrapure (Milli-Q) water was obtained from a Millipore Simplicity UV purification system. Samples of final effluent from wastewater treatment plants were collected in 1-L glass bottles, filtered through 0.2 mm filters, acidified with sulfuric acid to pH 2, and stored at 4 C until use in experiments. The pH was readjusted to 8.0 with sodium hydroxide before initiating photolysis experiments.
2.2.
Analytical methods
Concentrations were quantified using an Agilent Technologies 1200 Series HPLC equipped with UV/visible and photodiode array detectors. All compounds were analyzed on a Supelco Ascentis RP Amide 150 mm 4.6 mm, 5 mm column. For sulfamethoxazole and trimethoprim, a methanol:pH 3 phosphate buffer gradient method was used, starting at 20:80 and changing to 50:50 over 1 min and then holding for 4 min, with a 1 ml/min flow rate and a detection wavelength of 274 nm. For PNAP and PNA, a 50:50 acetonitrile:pH 3 phosphate buffer mobile phase at a flow rate of 1 ml/min was used, with detection wavelengths of 254 nm and 280 nm respectively. Cimetidine analysis was carried out with a 5:10:85 methanol:acetonitrile:pH 3 phosphate buffer mobile phase at a flow rate of 1 ml/min with a detection wavelength of 219 nm. Analysis for pCBA used an isocratic 75:25 methanol:pH 3 phosphate buffer mobile phase at a flow rate of 1 ml/min with a detection wavelength of 240 nm. Dissolved organic carbon concentrations of the wastewater effluents were determined using a Sievers 900 portable TOC analyzer and nitrate concentrations were measured with a Metrohm 761 compact ion chromatograph. UVevisible light absorption spectra of trimethoprim were obtained with a Shimadzu 1601-PC spectrophotometer. UVevisible light absorption spectra for sulfamethoxazole have been reported previously (Boreen et al., 2004).
2.3.
Photolysis
Laboratory photolysis experiments were conducted using a Suntest CPS þ solar simulator with a UV-Suprax optical filter (Atlas Materials Testing Solutions) with the light intensity set at 765 W/m2. Samples were held in quartz test tubes (o.d. ¼ 1.3 cm, i.d. ¼ 1.1 cm, V ¼ 10 ml) set at an angle of 30 from horizontal. Tubes were filled with approximately 7 ml of solution of the desired composition. Deoxygenated samples had nitrogen or argon gas bubbled through them for 5 min and were subsequently capped and sealed. As subsamples were taken from the tubes, the appropriate gas, either nitrogen or argon, was injected into the headspace of the vials to replace the lost volume. In determination of the quantum yield of trimethoprim, PNA/pyridine and PNAP/pyridine actinometers were used (Dulin and Mill, 1982), and the quantum yield was determined by comparison of the first order rate constant for
1282
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 8 0 e1 2 8 6
0.0
-0.5
ln(C/C0)
trimethoprim to that of PNA or PNAP, which have known quantum yields. The ratio of rate constants and the spectral overlap integrals (determined from the molar absorptivities determined from UVevisible spectra of trimethoprim and the actinometers and the manufacturer-reported lamp output spectrum) were used to calculate the quantum yield as described by Leifer (1988). Quantum yields were determined in pH 5 Milli-Q water adjusted with phosphoric acid and in 10 mM phosphate pH 8 buffered Milli-Q water under both air saturated and deoxygenated conditions. These pH values were selected to evaluate the photolysis of the protonated (positively charged) and deprotonated (neutral) forms of trimethoprim (pKa of 6.7; Zhou and Moore, 1997). Experiments investigating indirect photolysis compared the behavior of 1 mM solutions of either sulfamethoxazole or trimethoprim in a 10 mM phosphate pH 8 buffered Milli-Q water, wastewater effluent from the Blue Lake treatment plant (42 MGD, advanced secondary treatment of domestic and industrial wastewater, Shakopee, MN; final effluent DOC ¼ 7.49 mg/L, NO 3 ¼ 16.5 mg/L as N, pH ¼ 8.0), effluent from the Metro wastewater treatment plant (250 MGD, advanced secondary treatment of domestic and industrial wastewater, St. Paul, MN, DOC ¼ 8.12 mg/L, NO 3 ¼ 11.8 mg/L as N, pH ¼ 8.0), and Lake Josephine water (Roseville, MN, DOC ¼ 6.03 mg/L, NO 3 ¼ 0.4 mg/L as N, pH ¼ 8.0). To verify the roles of different photochemically produced reactive intermediates, quencher and sensitizer experiments were also performed. Solutions of 1% isopropyl alcohol were used to scavenge (hydroxyl) radicals. Isoprene, at a concentration of 0.1%, was added to selected experiments with sulfamethoxazole, as a scavenger of triplet excited states. Deoxygenation of solutions was also used to explore the role of triplet excited states. To verify susceptibility to reaction with triplet excited states, perinapthenone and 30 -methoxyacetophenone (Canonica et al., 1995) were used in the Milli-Q water as model triplet sensitizers, at a concentration of approximately 1 mM. The involvement of a triplet excited state in the degradation of trimethoprim was also examined using 40 mM trimethoprim and 2.5 mM cimetidine (which only reacts via singlet oxygenation; Latch et al., 2003) in 10 mM phosphate pH 8 buffered Milli-Q water solutions. Experiments quantifying the relative importance of direct and indirect photolysis of sulfamethoxazole and trimethoprim were conducted outdoors on August 3, 2009 in Minneapolis, MN, USA (w45 N latitude). These experiments involved comparing the degradation rates of trimethoprim, sulfamethoxazole, and pCBA in Milli-Q water, effluent from the Blue Lake plant, and solutions containing 1 mM potassium nitrate and 1 mg/L octanol (Fulkerson Brekken and Brezonik, 1988). pCBA was used as a hydroxyl radical probe to quantify hydroxyl radical steady state concentrations. Photolyses were performed on individual compounds in duplicate for each water sample/set of conditions.
wastewater effluent + isoprene
-1.0 wastewater effluent + IPA
-1.5 waste water effluent
-2.0 deoxygenated wastewater effluent
-2.5 0.0
0.5
Results and discussion
3.1.
Sulfamethoxazole
As shown in Fig. 1, sulfamethoxazole is susceptible to photolysis in wastewater effluent from the Blue Lake
1.5
2.0
2.5
3.0
3.5
Time (h) Fig. 1 e Photolysis of sulfamethoxazole in Blue Lake wastewater effluent with and without quenchers for photochemically produced reactive intermediates. Isopropanol (IPA) is a radical quencher. Isoprene is a quencher of excited triplet states, and deoxygenation removes the triplet quencher, oxygen.
treatment plant. Adding a radical quencher (IPA) suppressed the reaction rate, indicating that reaction with photogenerated radicals (an indirect photolysis process) also occurred. Addition of isoprene suppressed the reaction rate, and an increase in the reaction rate was observed in the absence of oxygen (Fig. 1; Table 1). Oxygen (a ground state triplet because of its unpaired electrons) is a quencher of triplet excited states, and thus its removal decreases the total
Table 1 e Photolysis rate constants (kobs) for sulfamethoxazole and trimethoprim. Matrix Sulfamethoxazole Wastewater effluent
Ultrapurified water
Lake water
Trimethoprim Wastewater effluent
Ultrapurified water
3.
1.0
Lake water
Quencher/alterationa
kobs (h1)
None Isopropyl alcohol Deoxygenation Isoprene None Isopropyl alcohol Deoxygenation None Deoxygenation
0.68 0.43 1.37 0.32 0.40 0.40 0.66 0.43 0.63
0.07b 0.04 0.29 0.07 0.01 0.006 0.10 0.02 0.23
None Isopropyl alcohol Deoxygenation None Deoxygenation None
0.18 0.016 0.23 0.03 0.36 0.06
0.01 0.019 0.01 0.01 0.03 0.02
a Isopropyl alcohol (IPA) is a free radical quencher, deoxygenation removes a triplet quencher (and thus increases reactive triplet lifetimes), isoprene is a triplet quencher. b Errors are 95% confidence intervals.
1283
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 8 0 e1 2 8 6
quenching rate of triplets in the system. These results taken together provide strong evidence for the involvement of triplet excited species in the indirect photolysis of sulfamethoxazole. Such effects have previously been used to substantiate a role for triplet excited organic matter in the degradation of pharmaceuticals (Werner et al., 2005). Photolysis in Milli-Q water in the presence of 1 mM perinapthenone led to rapid loss of sulfamethoxazole (45 12 h1; all reported errors are 95% confidence intervals), indicating that sulfamethoxazole reacts with triplet excited states. (While perinapthenone is also a singlet oxygen sensitizer, sulfamethoxazole has a relatively small singlet oxygenation rate constant; Boreen et al., 2004). Because the IPA and isoprene quenchers did not completely suppress reaction, direct photolysis is also important in the wastewater matrix. The reaction of sulfamethoxazole via indirect photolysis was unexpected, given that our previous results (Boreen et al., 2004) in Milli-Q and natural (Lake Josephine) water had indicated that direct photolysis was the primary process. Thus, experiments in Milli-Q water and Lake Josephine water were repeated and compared to the results in wastewater effluent (Fig. 2; Table 1). Sulfamethoxazole was found to degrade with a rate constant of 0.40 0.01 h in pH 8 buffered Milli-Q water. Similar to previous results (Boreen et al., 2004), the rate constant in Lake Josephine water was identical, pointing to direct photolysis as the dominant process in natural waters (Table 1). Both of these rate constants, however, are significantly slower than that in the Blue Lake wastewater effluent (Table 1). Photolysis in the Metro Plant effluent gave similar results (0.61 0.05 h1) to the Blue Lake wastewater, verifying that indirect photolysis was an important loss process for sulfamethoxazole in both the wastewater effluents. The suppression of the sulfamethoxazole photolysis rate constant in wastewater effluent by either IPA or isoprene to values lower than that of unaltered wastewater (Table 1) indicates that radicals and triplet excited states are both
active as indirect photolysis process. As shown in Fig. 2, adding IPA to the Milli-Q water had no effect, and similar results with Lake Josephine water were seen previously (Boreen et al., 2004). Deoxygenation of both Milli-Q water and Lake Josephine water leads to an increase in the loss rate (Table 1, Fig. 2). The fact that the magnitude of the change is the same in both of these matrices, however, indicates that the excited state triplet NOM in the natural water is not serving as a photosensitizer. Rather, the direct photolysis of sulfamethoxazole proceeds through a triplet excited state, and the removal of oxygen increases the lifetime (and decreases the quenching) of this excited state (SterneVolmer quenching), allowing a greater fraction of the photo-excited molecules to be transformed (i.e., the quantum yield increases in the absence of oxygen). This explanation is consistent with previous findings that sulfamethoxazole is a singlet oxygen sensitizer (Zhou and Moore, 1997). The effect of deoxygenation further demonstrates that singlet oxygen is not important in the transformation of sulfamethoxazole. If singlet oxygen were the major reactive species responsible for the indirect photolysis, deoxygenating samples would dramatically decrease degradation rates, which was not observed.
3.2.
Trimethoprim
Like sulfamethoxazole, trimethoprim was photolyzed much more rapidly in Blue Lake wastewater effluent than in pH 8 buffered Milli-Q water or Lake Josephine water (Table 1; Fig. 3). Quenching with IPA dramatically lowered the rate constant in wastewater effluent, whereas deoxygenation led to a slight, but statistically significant, increase (Table 1; Fig. 3). The difference between the wastewater effluent and the natural water again indicates that the photosensitizing ability of the wastewater matrix is greater than that of the natural water. Deoxygenating the pH 8 buffered Milli-Q also dramatically increased the rate constant, indicating that the excited triplet state trimethoprim is effectively quenched by oxygen. This is
1.8 1.6
0.4 1.4
0.3 1.0
-1
kobs (h )
-1
ko b s ( h )
1.2
0.8 0.6
0.2
0.4
0.1 0.2
W
O no D
I,
LJ
2
I
o W
W
,n
+ W
D
O
2
A IP
W W
o
Fig. 2 e Comparison of observed first order rate constants for the photolysis of sulfamethoxazole in Blue Lake wastewater effluent (WW), Milli-Q water (DI), and Lake Josephine water (LJW). Results with quenchers (isoprene, isopropyl alcohol) and under deoxygenated conditions are also shown. Errors are 95% confidence intervals (n [ 1e3).
0.0
W
2 O
W LJ
,n W LJ
2 I,
D
D
I
+
no
O
IP A
I D
ne
2
re
O
op
o W
W
+
is
,n W W
W
W
+
W
W
IP A
0.0
Fig. 3 e Comparison of observed first order rate constants for the photolysis of trimethoprim in Blue Lake wastewater effluent (WW), Milli-Q water (DI), and Lake Josephine water (LJW). Results with isopropyl alcohol and under deoxygenated conditions are also shown. Errors are 95% confidence intervals (n [ 1e4).
1284
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 8 0 e1 2 8 6
Table 2 e Quantum yields for direct photolysis of trimethoprim.a pH 5 8
Air saturated 4
6.2 10 1.2 103
Deoxygenated 7.9 103 7.0 102
a Quantum yields are for the simulated solar spectrum of the lamp. See Supplementary data.
borne out by the quantum yields measured for trimethoprim which are an order of magnitude higher in deoxygenated solutions (Table 2). The quantum yield reported here at pH 5 is similar to that previously reported in methanol (Dedola et al., 1999). The difference is likely due to the solvent. Trimethoprim has a pKa of 6.7 (Zhou and Moore, 1997) and the absorbance spectrum is influenced by pH (Supplementary Data). Thus, the quantum yield is pH, as well as oxygen, dependent. If trimethoprim in an excited triplet state is quenched by oxygen, singlet oxygen should be produced. This was tested by conducting experiments in pH 8 buffered Milli-Q water containing both trimethoprim (40 mM) and cimetidine (2.5 mM), a compound that is only susceptible to indirect photolysis via singlet oxygenation (Latch et al., 2003). In the presence of trimethoprim and oxygen, cimetidine degraded (first order rate constant of 0.49 0.04 h1 when sparged with oxygen and 0.21 0.05 h1 when sparged with air), whereas in deoxygenated solutions, trimethoprim degraded, but cimetidine loss was negligible, with a rate constant that was not statistically different than zero (0.04 0.09 h1). This indicates that trimethoprim is a singlet oxygen sensitizer, contrary to the findings of Zhou and Moore (1997). The more rapid reaction in deoxygenated wastewater could either be caused by a decrease in the rate of quenching of the trimethoprim itself or a decrease in the quenching rate of triplet excited effluent organic matter. Experiments performed with the triplet sensitizers perinapthenone and 30 -methoxyacetophenone in pH 8 buffered water gave the rate constants of 1.2 0.2 h1 and 0.12 0.01 h1 respectively, confirming the finding of Dedola et al. (1999) that trimethoprim is susceptible to reactions with triplet excited states. Again, the observed increase in rate upon deoxygenation rules out a major role for singlet oxygen in the photolysis of trimethoprim.
3.3.
Contribution of indirect photolysis processes
To quantify the fraction of reaction occurring via direct and indirect photolysis processes, a series of experiments were performed in sunlight in air saturated solutions. To determine the steady state concentration of hydroxyl radicals, pCBA was used in Blue Lake wastewater effluent and in an aqueous solution containing nitrate (a sensitizer for hydroxyl radical) and 1-octanol (to serve as a hydroxyl radical quencher). pCBA degrades exclusively by interaction with hydroxyl radicals, with a known second order rate constant of 5 109 M1 s1 (Buxton et al., 1988). When exposed to natural sunlight in a Blue Lake wastewater effluent solution, pCBA was found to degrade with a first order rate constant of 7.3 106 s1. By dividing the observed first order constant by the second order rate constant for reaction with hydroxyl radicals, the steady
state hydroxyl radical concentration was determined to be 1.5 1015 M, which is higher than normally reported for natural waters (Cooper et al., 1985), but reasonable given the nitrate concentration of the water (16.5 mg/L as N). The solution containing 1 mM nitrate (14 mg/L as N) and 1 mg/L octanol had a steady state hydroxyl radical concentration of 1.8 1015 M. For sulfamethoxazole, the overall rate constant in the sunlit wastewater effluent was 2.35 105 s1 (0.085 h1). Boreen et al. (2004) determined a second order rate constant of 5.8 109 M1 s1 for sulfamethoxazole reaction with hydroxyl radicals. Multiplying this rate constant by the steady state hydroxyl rate constant found in the effluent, gives a pseudofirst order reaction rate constant of 8.5 106 s1, which accounts for 36% of the total degradation of sulfamethoxazole. Direct photolysis of sulfamethoxazole in a parallel test tube containing pH 8 buffered Milli-Q water was found to proceed with a rate constant of 1.1 105 s1, which should be the same in Blue Lake effluent, ignoring the effect of screening by EfOM (calculated to be 4 m h1) is the key operating feature, which expands the sludge bed and maximizes sludge-wastewater contact (Seghezzo et al., 1998). The IFB bioreactor has been identified as a new, promising design for AD (Garcia-Bernet et al., 1998). The novelty of this configuration arises from the use of floatable particles with a specific density lower than the liquid, such that the particles are fluidized downward (Garcia-Calderon et al., 1998). Due to the large specific area of support particles available for biomass retention, this technology offers advantages in the treatment of highstrength effluents by using reduced spaces and shorter hydraulic retention times (Alvarado-Lassman et al., 2008). The liquid and the produced biogas are flowing in opposite directions, which help for bed expansion (Arnaiz et al., 2003). Therefore, the down-flow (or inverse) configuration reduces energy requirements, because of the low fluidization velocities (Garcia-Calderon et al., 1998) when compared to up-flow systems. The links between changes in microbial community and perturbations in anaerobic digesters are not well understood and there may even be changes in community without apparent changes in performance. There is a need for more comprehensive studies on this topic, which can be done by aid of high throughput molecular tools (Talbot et al., 2008). Culture-free molecular techniques, particularly based on 16S rRNA genes, have been successfully applied to numerous microbial ecology studies, and helped us to link microbial community structure and dynamics to process performance (Fernandez et al., 2008; Lee et al., 2008). Many studies concerning anaerobic reactors have focused only on qualitative techniques, such as DGGE (Muyzer et al., 1993), and thus quantitative population dynamics of anaerobic bioreactors are still in its infancy. In particular, there is no information
1299
regarding quantitative comparison of different types of anaerobic reactors during transitional changes. Besides the community diversity and composition, the quantitative changes in microbial communities represent a significant factor affecting process performance (Wittebolle et al., 2005). Quantitative information about population structure can be therefore very useful in diagnosing problems with process performance or comparing anaerobic digesters. Acidogenic bacteria and the methanogen are the two major groups underpinning AD. However, methanogenesis is usually a rate-limiting step and requires effective control for successful operation of most AD systems (Yang et al., 2003; Yu et al., 2005, 2006). Five methanogenic groups: three hydrogenotrophic orders and two aceticlastic families are considered to cover most methanogens in anaerobic digesters (Yu et al., 2005; Lee et al., 2009). Consequently in the present study, the methanogenic community structure of the EGSB and the IFB bioreactors was quantitatively investigated using five methanogenic order or family-specific primer and probe sets employing real-time PCR. Quantitative community shifts were visualized using Non-metric multidimensional scaling (NMS) technique, based on real-time PCR data. Methanogenic community dynamics associated with operational changes were monitored using moving-window analysis (Wittebolle et al., 2008). Additionally changes in archaeal community structure in both reactors were examined using denaturing gradient gel electrophoresis (DGGE). The obtained microbial information was linked with the variations in process performance and operating conditions (i.e., hydraulic retention time (HRT)), in the IFB and EGSB reactors tested.
2.
Materials and methods
2.1.
Reactor operation
Lab-scale EGSB (Fig. 1a) and IFB (Fig. 1b) reactors (3.6-l working volume each) were continuously operated, at 37 C, for 200 days. Extendosphere (Sphere One, Chattanooga, Tennessee, USA) light mineral material composed mostly of silica and traces of aluminum, density of 0.69 g/cm3, was used as a carrier material for the IFB reactor. Particle size distribution analyses of virgin carrier material were performed using Mastersizer (Malvern Instruments) to determine particle distribution and percentage of each fraction. The range of particle size distribution was broad, from 73.6 mm to 2000 mm, but the majority of particles were in the range of 194e236 mm. The seed sludge used to inoculate both reactors was obtained from a full-scale internal circulation (IC) anaerobic digester located at the Carbery Milk Products (Ballineen, Co Cork, Ireland). The volatile solids (VS) concentration used to inoculate bioreactors was 60 g/l and granular seed sludge was crushed prior to inoculation. Both reactors were fed with a synthetic dairy wastewater (4 g COD/l) buffered with NaHCO3 and fortified with macro- (10 ml/l) and micro- (1 ml/l) nutrients (Shelton and Tiedje, 1984; Arnaiz et al., 2003). The applied hydraulic retention time (HRT) was decreased in a stepwise manner from 72 to 12 h during the operation of both reactors.
1300
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 9 8 e1 3 0 8
Fig. 1 e Laboratory scale anaerobic reactors: a) Expanded Granular Sludge Bed (EGSB) and b) Inverted Fluidized Bed (IFB).
2.2.
DNA extraction
Total genomic DNA was extracted from seed sludge and biomass obtained from the reactors at various points during the reactor trial (Fig. 2). All biomass samples (50 ml) were mechanically disrupted by manual grinding with a pestle and mortar and diluted 10-fold with deionised and distilled water (DDW). Cells from each 1 ml sample were harvested by centrifugation at 13,000 rpm for 5 min, followed by decantation of the supernatant. The residual pellet was washed with 1 ml of DDW, and centrifuged again in the same manner to ensure a maximal removal of residual medium. After two washing cycles, pellet was resuspended in 1 ml of DDW. Total DNA in the suspension was extracted using an automated nucleic acid extractor (Magtration System 6 GC, PSS, Chiba, Japan). Purified DNA was eluted with 100 ml of
Fig. 2 e Chemical oxygen demand (COD) removal efficiencies of IFB and EGSB reactors. Arrows indicate biomass sampling points.
TriseHCl buffer (pH 8.0) and stored at 20 C for further analyses. DNA extraction was performed in duplicate.
2.3.
QPCR
Real-time PCR (QPCR) analysis was performed using a LightCycler 480 instrument (Roche, Mannheim, Germany) using three methanogenic order-specific primer and probe sets: Methanobacteriales (MBT), Methanomicrobiales (MMB), Methanococcales (MCC) and two methanogenic family-specific primer and probe sets: Methanosarcinaceae (Msc), Methanosaetaceae (Mst) as described previously (Yu et al., 2005; Lee et al., 2009). Each reaction mixture of 20 ml was prepared using the LightCycler 480 Probe Master kit (Roche Diagnostics): 2 ml of PCR-grade water, 1 ml of each primers (final concentration 500 nM), 1 ml of the TaqMan probe (final concentration 200 nM), 10 ml of 2 LightCycler 480 Probes Master, and 5 ml of template DNA. Amplification was performed in a two-step thermal cycling procedure: predenaturation for 10 min at 94 C followed by 40 cycles of 10 s at 94 C and 30 s at 60 C. All DNA templates were analyzed in duplicate. Quantitative standard curves were constructed as previously described (Yu et al., 2006) using the representative strains corresponding to each primer and probe sets targeting the following methanogenic groups: MBT (Methanobacterium formicicum M.o.H. (DSM 863) and Methanobrevibacter arboriphilicus DH1 (DSM 1536)); MMB (Methanospirillum hungatei JF1 (DSM 864) and Methanomicrobium mobile BP (DSM 1539)); MCC (Methanococcus vannielii SB (DSM 1224) and Methanococcus voltae PS (DSM 1537)); Msc (Methanosarcina acetivorans C2A (DSM 2834), Methanosarcina barkeri MS (DSM 800), Methanosarcina mazei Go1 (DSM 3647)); Mst (Methanosaeta concilli GP6 (DSM 3671)). For each standard solution, a 10-fold serial dilution series of 101e109 copies/ml was generated and analyzed by real-time PCR in duplicate with its corresponding primer/probe set.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 9 8 e1 3 0 8
2.4.
Statistical analysis
Non-metric multidimensional scaling (NMS) was performed, based on the real-time PCR results, to visualize the methanogenic community shifts during the operation. Two separate matrices, based on the absolute quantity and the relative abundance of each target methanogenic group, respectively, were analyzed employing Sørensen distance measure in the PC-ORD software ver. 5.0 (McCune and Grace, 2002). The NMS plot mirrors the relationships between the community profiles by closely locating the communities with high similarity. Moving-window analysis was also carried out based on the absolute quantity and relative abundance matrices to monitor the variations in methanogenic community composition associated with decreases in the applied HRT in the two bioreactors. Moving-window analysis was previously demonstrated to be a valuable tool for monitoring microbial community dynamics (Wittebolle et al., 2008). The community similarity between two consecutive phases with different HRTs was calculated using PC-ORD software ver. 5.0 (McCune and Grace, 2002) and used as the indicator of community variation in response to the corresponding HRT change.
2.5.
Archaeal DGGE
Archaeal 16S rRNA genes were amplified by PCR using the primers ARC 787F and ARC 1059R (Takai and Horikoshi, 2000). To stabilize the melting behavior of the PCR products, a 40-bp GC-clamp was attached at the 50 -end of the forward primer (Muyzer et al., 1993). Touchdown PCR was conducted using thermal cycler G-Storm (Gene Technologies Ltd., Essex UK) and the following protocol was applied: initial denaturation at 94 C for 10 min; 20 cycles of denaturation at 94 C for 1 min, annealing at 65 Ce55 C (reducing 0.5 C per cycle) and elongation at 72 C for 1 min; followed by 20 cycles at 94 C for 1 min, 55 C for 1 min, 72 C for 1 min and final elongation at 72 C for 30 min (Janse et al., 2004). DGGE was performed using a D-Code system (BioRad Hercules, CA). Fifteen ml of the PCR product were loaded onto 8% acrylamide gel containing a 40e65% denaturant gradient (100% denaturant contained 7 M urea and 40% (v/v) formamide). After electrophoresis, the DGGE gel was stained with ethidium bromide and distained for 20 min, respectively. Gel image was captured using a UV transillumination camera. Bands of interest were cut directly from the gel using a sterile razor blade and eluted in 40 ml of DDW. Two ml of eluted DNA solution were further amplified using the ARC 787F and ARC 1059R primers, without the GC clamp. The PCR products were gel-purified and cloned into pGEM-T Easy vector (Promega, Madison, WI). The cloned gene fragments were sequenced using T7 primer and compared against the Ribosomal Database Project (RDP) database. Sequencing alignment and phylogenetic analyses were performed using MEGA 4 software (Tamura et al., 2007). All nucleotide sequence data reported in this study were deposited in the GenBank database under accession numbers GQ429188eGQ429206.
2.6.
Analytical methods
Biogas and effluent from both reactors were routinely sampled to analyze methane content and residual chemical
1301
oxygen demand (COD) concentration according to Standard Methods (APHA, 1998). All analyses were performed in duplicate. Analysis of effluent volatile fatty acids (VFA), by heated (85 C) and agitated headspace, were performed in a Varian Saturn 2000 GC/MS system, with CombiPAL autosampler (Varian Inc., Walnut Creek, CA). Separation was carried out on a Varian Capillary column, CP-WAX 58 (FFAP) CB (25 m length 0.32 mm i.d. 0.2 mm film thickness, Varian). The injector volume was 2 ml and the injector temperature was 250 C. The carrier gas was helium and the flow rate was 1 ml/min. The temperature program was as follows: 50 C (20 s) to 110 C (20 s) at a rate of 2 C/min; from 110 C to 200 C (20 s) at a rate of 20 C/min. The MS-detector was operated in the scan mode in the range of 40e150 m/z at a temperature of 210 C. Identification of VFAs was achieved by matching chromatographic retention times and spectra of standard compounds (acetic-, butyric-, iso-butyric-, propionic-, valericand iso-valeric acid). Calibration curves of standard VFAs were conducted and used for relative concentration of VFAs in effluent headspace samples and then expressed in mg/l.
3.
Results and discussion
3.1.
Process performance
The start-up of the IFB reactor was prolonged and perturbed, with large fluctuations in COD removal efficiency (CODre) and effluent VFA concentration, whereas the EGSB performance remained relatively constant throughout the initial period of operation (Figs. 2 and 3). The high initial effluent VFA concentration corresponded to poor COD removal efficiency by the IFB reactor (Fig. 2). After 2 months of operation, the IFB reactor stabilized, with a marked decrease in VFA concentration and significant improvement in COD removal. From day 60 to 160 of the trial, both the EGSB and IFB reactors performed very similarly in terms of COD removal (>80%; Fig. 2), effluent VFA concentration (60% biogas methane content (data not shown) at an applied HRT of 72 h. With further decreases in the applied HRT from 72 down to 18 h (Fig. 2), the two reactors exhibited comparable performance with no significant deterioration recorded (Fig. 2). A further decrease in HRT to 12 h, however, caused a significant performance drop (i.e., decrease in CODre and increase in residual VFA concentration) in the IFB (Figs. 2 and 3), indicating that a loading rate threshold may have been reached. On the other hand, the EGSB showed no marked change in performance and maintained a similar level of treatment efficiency, even at the shortest HRT tested (Figs. 2 and 3).
3.2.
QPCR of methanogenic communities
In contrast to the conventional end-point detection PCR, quantitative real-time PCR (QPCR) technology based on the detection of fluorescence during amplification of target DNA (Higuchi et al., 1993) has better sensitivity and reproducibility than conventional PCR and can be easily used in studies requiring a large number of samples (Talbot et al., 2008). TaqMan QPCR primers and probe sets for the methanogenic orders:
1302
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 9 8 e1 3 0 8
Fig. 3 e Volatile fatty acids (VFA presented as sum of: acetic-, butyric-, iso-butyric-, propionic-, valeric- and isovaleric acid); acetic acid and propionic acid concentrations in IFB and EGSB reactors.
Methanobacteriales, Methanomicrobiales and the two families: Methanosarcinaceae and Methanosaetaceae; demonstrated satisfactory specificity to allow quantitative comparison between the two bioreactors to be made and for correlation of the molecular data with process performance changes. In our study, the EGSB and IFB bioreactors displayed a noticeable disparity in terms of the quantitative composition of the methanogenic community by real-time PCR (Fig. 4). The order Methanobacteriales (MBT) was commonly the most dominant methanogen group in both reactors (i.e., 63e86% in the IFB and 52e71% in the EGSB), in terms of 16S rRNA gene concentration, during the trial. The 16S rRNA gene concentration of Methanobacteriales, in both reactors, remained stable at approximately 108 copies/ml, regardless of changes in operating conditions, which were characterized by decrease in HRT from 72 to 12 h (Fig. 4). The fact that Methanobacteriales were predominant throughout the trial, in both reactors, at all HRT’s, although it was not dominant group in the seed, was an
interesting finding. It is not clear whether high initial 16S rRNA gene concentration in the seed (i.e., 1.4 109 copies/ml), influent composition or other factors had a stimulating effect on growth of this group e but this should now be investigated. The hydrogenotrophic order Methanomicrobiales (MMB) was detected in both the EGSB and IFB reactors but its quantitative dynamics differed in each reactor configuration. Although the initial 16S rRNA gene concentration of Methanomicrobiales in the seed sludge was approximately 107 copies/ml in both reactors, the MMB were much more abundant in the IFB reactor during the trial (18e90-fold greater than EGSB; Fig. 4). The 16S rRNA gene concentration of Methanomicrobiales in the IFB biomass, during the operational period when the applied HRT was reduced from 72 to 18 h, stabilized between 106 and 107 copies/ml (Fig. 4). Following a further decrease in HRT to 12 h, however, the concentration of Methanomicrobiales significantly increased to 6 107 copies/ml. The Methanomicrobiales population was much less abundant in the EGSB reactor during the operational period corresponding to the HRT reduction from 72 to 18 h (1.2e2.2 105 copies/ml; Fig. 4). A slight increase in the 16S rRNA gene concentration of 6.7 105 copies/ml was, however, recorded following the reduction in HRT to 12 h (Fig. 4). In both reactors, therefore, the HRT change from 18 to 12 h seemed to evoke an increase in the abundance of this hydrogenotrophic group, which may be due to higher organic loading rate (OLR), or some morphological or biokinetic traits of the group. It is generally accepted that reducing the applied HRT, at a constant influent concentration (as was in case of this study at 4 g COD/l), will increase the OLR (Mahmoud et al., 2003). The applied HRT change from 18 to 12 h resulted in OLR increase of 50% (5.3 g COD/l/day at 18 h HRT to 8 g COD/l/ day at 12 h HRT), which had a direct and positive influence on the abundance of Methanomicrobiales. Although our results differ from those observed by Rinco´n et al. (2008), who reported a stable methanogenic community of Archaea, at every OLR tested, the archaeal community in their study was represented only by the genus Methanosaeta. Hypothetically, an increased abundance of Methanomicrobiales might be correlated with more diverse bacterial communities, and Rinco´n et al. (2008) did observe higher number of bacterial phylotypes at increased OLR; but this was not determined during our study.
Fig. 4 e Absolute quantification of methanogenic communities in the IFB and the EGSB bioreactors. Methanogenic groups: MBT (Methanobacteriales), MMB (Methanomicrobiales), Msc (Methanosarcinaceae), Mst (Methanosaetaceae).
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 1 2 9 8 e1 3 0 8
The aceticlastic family, Methanosaetaceae (Mst), was the most abundant group in the seed biomass and 16S rRNA gene concentration of this group was detected at 2 109 copies/ml (Fig. 4). During reactor operation between 72 and 18 h HRT, the 16S rRNA gene concentration of Methanosaetaceae in the IFB was 3.0e4.3 107 copies/ml (Fig. 4). On the other hand, Methanosaetaceae was about >2.6 fold more abundant in the EGSB (16S rRNA gene concentration of 1.0e1.5 108 copies/ml; Fig. 4). An increase in the 16S rRNA gene levels was observed, following a decrease in HRT to 12 h, to 8.3 107 copies/ml and 3.2 108 copies/ml in IFB and EGSB reactors, respectively. Previous studies have revealed the importance of Methanosaeta spp. in determining the development of granules in EGSB reactors (Liu et al., 2002; Collins et al., 2003). Methanosaeta spp. rods appear to provide a network, within the granule, to which other bacteria become associated. It is generally accepted that abundant Methanosaeta spp. improve granulation and result in more stable reactor performance (Liu et al., 2002). The predominance of Methanosaeta in our EGSB reactor (>2.6 fold higher population compared to the IFB), therefore, could be associated with more stable reactor performance and lower inreactor VFA concentrations, particularly during the first two months of the trial (Figs. 2 and 3). It has been reported that Methanosarcina spp. have higher maximum growth rates on acetate than Methanosaeta spp., but that the minimum threshold for acetate utilization by Methanosaeta spp. is 5e10 times lower than for Methanosarcina spp. (Zinder, 1990; Jetten et al., 1992). These kinetic data indicate that a selection for granules in anaerobic systems dominated by Methanosaeta spp. should be favored by low steady-state acetate concentration. Additionally, a decrease in HRT from 72 to 12 h seemed to enhance the granulation of initially crushed biomass in the EGSB reactor, which was particularly prominent after transition from 18 to 12 h HRT (visual examination). It has also been reported previously that increases in up-flow liquid velocity and reduction in applied HRT have a stimulating influence on granulation (Alphenaar et al., 1993). The appearance of the family Methanosarcina in anaerobic digesters, by contrast, has been associated with high inreactor acetate concentrations, accompanied by process deterioration (Collins et al., 2003; O’Reilly et al., 2009). VFA and acetic acid concentration data from the EGSB and IFB reactors apparently confirmed this observation (Fig. 3). Throughout the 200-day trial, the VFA concentration in EGSB reactor effluent was relatively constant, not exceeding 80 mg/l in the transitional periods associated with HRT decreases. Low VFA and therefore, low acetate concentrations, in the EGSB, especially during start-up, did not favor growth of Methanosacrcina and this tendency was maintained until the end of trial. On the other hand, the high initial VFA concentration (210e320 mg/l) where acetate constitutes 36e76% (80e220 mg/ l) apparently stimulated the growth of Methanosacrina in the IFB reactor. In addition, it should be noted that elevated concentrations of propionate (60e160 mg/l; 22e56% of all VFA; Fig. 3) in the IFB reactor effluent, during the start-up period may have played a role in stimulating the growth of propionate-oxidizing syntrophic bacteria (Zheng et al., 2006). Hypothetically, the presence of propionate-oxidizing syntrophic consortia could be linked with the more dynamic population of Methanomicrobiales, which was observed in the IFB
1303
system (Fig. 4). Higher levels of Methanomicrobiales have previously been reported (Zheng et al., 2006) in a reactor fed a mixture of glucose and propionate to enhance the growth of propionate-oxidizing syntrophic consortia. An interesting observation was that, although Methanosaetaceae was the dominant group in the seed sludge, once the reactors were started up, the Methanobacteriales become the predominant group (Fig. 4). The dominance of Methanosaetaceae in the original (seed) sludge is unsurprising and has been previously demonstrated in other studies (Raskin et al., 1994; McHugh et al., 2003; Sawayama et al., 2006), but the predominance of Methanobacteriales, in both reactors, at all HRT’s as recorded in this study, is unusual and has not, to our knowledge been reported previously in high-rate anaerobic sludge reactors. Quantitative PCR results demonstrated that the aceticlastic family Methanosarcinaceae (Msc) was only detected in the IFB reactor (Fig. 4). The initial 16S rRNA gene concentration of Methanosarcinaceae in the seed sludge, 1.8 105 copies/ml, markedly increased during the IFB reactor trial (to 3.5 106 copies/ml; Fig. 4). In case of the EGSB biomass, the Methanosarcinaceae 16S rRNA gene concentration was under the real-time PCR reaction detection limit (i.e., 1.6 104 copies/ml) throughout the trial. It is possible that Methanosarcinaceae were out-competed by Methanosaetaceae, due to the competitive growth relationship between both families for acetate, and that Methanosarcinaceae were washed out from EGSB system (Yu et al., 2006). As mentioned earlier, low acetate concentrations, as observed in the EGSB reactor, create an unfavorable environment for Methanosarcinaceae, which tend to predominate at higher acetate concentrations as identified in the IFB reactor. The order Methanococcales (MCC) was not detected in either of the reactors, presumably since organisms from this group require high-salt conditions for they growth (0.3e9.4% (w/v) NaCl), which are not normally found in anaerobic reactors (Boone et al., 2001).
3.3. Statistical analyses of the quantitative shifts in methanogenic communities Based on 16S rRNA gene concentration data, two different matrices were created: an absolute quantity-matrix and relative abundance matrix. The absolute quantity-matrix was based on the amount of rDNA detected by QPCR assay for each order-specific sets (MBT and MMB) and family-specific sets (Msc and Mst). The relative abundance matrix was created using the ratio between the rDNA concentration detected by the QPCR assay quantified for each order/family-specific sets (MBT, MMB, Msc and Mst) and the total rDNA concentration of methanogens detected in the sample. NMS analysis avoids the assumption of linear relationships among variables and it is reported to be the most generally effective ordination method for ecological community data (McCune and Grace, 2002). In both NMS plots (Fig. 5a and b), the cumulative r2 represented by the axes was >0.9, the final stress value was
