WATER RESEARCH A Journal of the International Water Association
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w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 6 0 3 e6 6 1 4
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Waterborne transmission of protozoan parasites: Review of worldwide outbreaks e An update 2004e2010 Selma Baldursson, Panagiotis Karanis* University of Cologne, Faculty of Medicine, Center of Anatomy, Institute II, Medical and Molecular Parasitology, Joseph-Stelzmann-Strasse 35, D-50937 Cologne, Germany
article info
abstract
Article history:
The present update gives a comprehensive review of worldwide waterborne parasitic
Received 13 July 2011
protozoan outbreaks that occurred and were published globally between January 2004 and
Received in revised form
December 2010. At least one hundred and ninety-nine outbreaks of human diseases due to
11 October 2011
the waterborne transmission of parasitic protozoa occurred and were reported during the
Accepted 12 October 2011
time period from 2004 to 2010. 46.7% of the documented outbreaks occurred on the
Available online 20 October 2011
Australian continent, 30.6% in North America and 16.5% in Europe. Cryptosporidium spp. was the etiological agent in 60.3% (120) of the outbreaks, Giardia lamblia in 35.2% (70) and
Keywords:
other protozoa in 4.5% (9). Four outbreaks (2%) were caused by Toxoplasma gondii, three
Contamination
(1.5%) by Cyclospora cayetanensis. In two outbreaks (1%) Acanthamoeba spp. was identified as
Diarrhea
the causative agent. In one outbreak, G. lamblia (in 17.6% of stool samples) and Cryptospo-
Protozoan parasites
ridium parvum (in 2.7% of stool samples) as well as Entamoeba histolytica (in 9.4% of stool
Public health surveillance systems
samples) and Blastocystis hominis (in 8.1% of stool samples) were detected. In those coun-
Waterborne disease outbreak (WBDO)
tries that are likely affected most a lack of surveillance systems is noticeable. However,
Worldwide review
countries that established surveillance systems did not establish an international standardization of reporting systems. ª 2011 Elsevier Ltd. All rights reserved.
Contents 1. 2. 3. 4. 5.
1.
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Material and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Introduction
Waterborne parasitic protozoan diseases have a worldwide distribution and are, in both developed and developing countries, reasons for epidemic and endemic human suffering
6603 6604 6604 6610 6612 6612
(Cotruva et al., 2004). They are one of the main reasons for 4 billion cases of diarrhea that causes annually 1.6 million deaths (www.who.int) and 62.5 million Disability Adjusted Life Years (DALYs) worldwide (Wright and Gundry, 2009). Diarrhea belongs to the five most common disease causes of
* Corresponding author. Tel.: þ49 221 478 5655; fax: þ49 221 478 3808. E-mail address:
[email protected] (P. Karanis). 0043-1354/$ e see front matter ª 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2011.10.013
6604
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death (www.who.int) and is responsible for 21% of deaths of children younger than five years of age (Kosek et al., 2003). The most prevalent waterborne parasitic infections producing diarrhea are cryptosporidiosis and giardiasis, already the appearance of infections caused by Giardia lamblia account 2.8 10^8 cases yearly (Lane and Lloyd, 2002). Other parasitic protozoa with a waterborne transmission that cause human infections are Toxoplasma gondii, Entamoeba histolytica, Acanthamoeba spp., Cyclospora cayetanensis, Microsporidia, Isospora, Blastocystis hominis, Sarcocystis spp., Naegleria spp. and Balantidium coli. Since most of these protozoa use the faecal-oral way of transmission they can infect humans through sewage and contamination of land and rivers by animal or human feces (Lanata, 2003). Efficient sanitation and improved water supplies are the main safety measures against parasitic protozoan hazards. The United States created organizations like the Center for Disease Control and Prevention (CDC) and the US Environmental Protection Agency (USEPA) that enforced waterborne disease outbreak surveillance since 1971 (WBDOSS). In 1980 Sweden established a surveillance system (Stanwell-Smith et al., 2003) and in 1981 Japan started the National Epidemiological Surveillance of Infectious Diseases (NESID). The National Notifiable Diseases Surveillance System (NNDSS) in Australia was founded in 1990, the Health Protection Agency (HPA) of the United Kingdom in 2003, and furthermore, the Public Health Agency of Canada (PHAC) in 2004. Following the example of the USA European Countries created the European Center for Disease Control and Prevention (ECDC) in 2005. From most of these centers highly qualified information and documentations of waterborne parasitic protozoan outbreaks are approachable. In developing countries, governmental systems to register incidence and prevalence of protozoan infections or waterborne outbreaks are not established. Consequently there is a lack of documentation of waterborne parasitic protozoan outbreaks in developing countries. In 2007, the Journal of Water and Health published a review of worldwide waterborne outbreaks caused by parasitic protozoa (Karanis et al., 2007: Waterborne transmission of protozoan parasites: A worldwide review of outbreaks and lessons learnt) which spans a time period of almost hundred years from the beginning of the previous century. The aim of the present work is to update worldwide waterborne outbreaks of pathogenic protozoa during the time period of 2004e2011 and to figure out their worldwide distribution pattern.
2.
Material and methods
For the collection of data a variety of global literature sources was used. The research included articles from the databases MEDLINE/PubMed, MEDPILOT and Scopus as well as available electronic data from surveillance systems all over the world, like the Center for Disease Control and Prevention (CDC) and the European Center of Disease Prevention and Control (ECDC). The collection of data entailing this present review of waterborne parasitic protozoan outbreaks is based on a search of the medical literature databases MEDLINE/PubMed, MEDPILOT and Scopus, as well as on the use of electronic data from Morbidity and Mortality Weekly Report (MMWR by CDC), Euro
Surveillance (published by ECDC), Canada Communicable Disease Report (CCDR by PHAC), Communicable Disease Report (CDR by HPA) and CRYPTNET (www.mednetvet.org). In the named electronic databases the terms “outbreak (and) Cryptosporidium”, “outbreak (and) cryptosporidiosis”, “outbreak (and) Giardia”, “outbreak (and) giardiasis”, “outbreak (and) Cyclospora”, “outbreak (and) Blastocystis”, “outbreak (and) Entamoeba”, “outbreak (and) Acanthamoeba”, “outbreak (and) Amoebiasis”, “outbreak (and) Toxoplasma”, “outbreak (and) microsporidia”, “outbreak (and) Sarcocystis”, “outbreak (and) Naegleria”, “outbreak (and) Balantidium coli”, “outbreak (and) Isospora” were exerted and the listed articles critically reviewed.
3.
Results
During a time period of almost hundred years, between the previous century and 2004, a number of 325 waterborne protozoan parasitic outbreaks have been reported worldwide (Karanis et al., 2007), while in the considerable shorter time period of seven years, between 2004 and 2010, 199 reports of waterborne protozoan parasitic outbreaks were published. Between January 2004 and December 2010, one hundred and ninety-nine waterborne outbreaks of parasitic protozoan diseases occurring during this time period have been published worldwide and could be detected in the considered databases. The outbreaks are summarized in Tables 1e3. Table 1 documents worldwide waterborne outbreaks caused by Cryptosporidium spp., Table 2 shows worldwide waterborne outbreaks caused by G. lamblia and Table 3 summarizes the worldwide waterborne outbreaks caused by T. gondii, E. histolytica, Acanthamoeba spp., C. cayetanensis, Microsporidia, Isospora, Blastocystis spp., Sarcocystis spp., Naegleria spp. and Balantidium coli. Additional, Tables 1e3 point out the parameters of time (month and year), place (region and country), estimated cases and labor-confirmed cases in brackets if denoted in the original article. For each outbreak, the suspected cause and the key reference is annotated. In the reported outbreaks, Cryptosporidium spp. was the etiological agent in 60.3% (120) of the outbreaks, G. lamblia in 35.1% (70) and other protozoa in 4.5% (9). Four outbreaks (2%) were caused by T. gondii and three (1.5%) by C. cayetanensis. In two outbreaks (1%) Acanthamoeba was identified as causative agent. In one outbreak, four parasitic protozoa were implicated: G. lamblia (in 17.6% of stool samples) and Cryptosporidium parvum (in 2.7% of stool samples) as well as E. histolytica (in 9.4% of stool samples) and B. hominis (in 8.1% of stool samples) were detected. The outbreak occurred in Malaysia during April and May 2004 among Orang Asli (Aborigine) (Hakim et al., 2007). Summarizing the outbreaks, we count this outbreak as a single one, while it is mentioned in all three tables of each detected pathogen. From the Australian continent, 46.7% (93) of worldwide waterborne outbreaks caused by parasitic protozoa were reported. In New Zealand 80 outbreaks occurred (40.2%), in Australia 13 (6.5%). The waterborne outbreaks on the American continent amount to 33.1% (66) of worldwide waterborne outbreaks.
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Table 1 e List of worldwide waterborne outbreaks caused by Cryptosporidium spp. Month/year Aug 2001
a
Location/country
Est. cases
Susp. cause
Nu¨rnberg/Germany
201 (15)
Potentially tap water during field exercise among military recruits Drinking water from a well in a factory G. lamblia (17.6%), Entamoeba (9.4%), Blastocystis hominis (8.1%), Cryptosporidium (2.7%)b/source of infection probably contaminated water or food Swimming pool Swimming pool
Jan 2004 ApreMay 2004
Ohio/USA Cameron Highlands/ Malaysia
82 Probably 79
Mar 2004 MayeJun 2004
4 (4) 7 (7)
Jun 2004
North West England Northern and Yorkshire/England Georgia/USA
14
Jul 2004
Ohio/USA
160
Jul 2004
Illinois/USA
37
Aug 2004
California/USA
336
AugeSep 2004
Nagano/Japan
41 (30)/74e288d
Aug 2004
Wisconsin/USA
6
Aug 2004 AugeSep 2004
Colorado/USA California/USA
6 >250
AugeNov 2004 Sep 2004 Oct 2004
133 8 10 (9)
2004
Bergen/Norway Illinois/USA Northern and Yorkshire/England New Zealand
Treated recreational water in a community pool Treated recreational water of a hotel pool Oocysts in backwash and sand from waterslides’ filter in a water park Additive during large giardiasis outbreak Treated recreational water in a hotel pool Swimming pool
8
Untreated water supply
2004 Mar 2005
Queensland/Australia South-east-Ireland
5 (5) 31
Public swimming pool Waterborne and person-to-person community outbreak
Apr 2005
West-Ireland
7
Waterborne
Jun 2005 Jun 2005
New York/USA Kentucky/USA
2307 53
Jun 2005 Jun 2005
Florida/USA Iowa/USA
47 24
Jun 2005
Kentucky/USA
9
Jul 2005
Kansas/USA
84
Jul 2005
Oregon/USA
20
JuleAug 2005
New York State/USA
>3000 (425)
JuleAug 2005 Aug 2005
Madison, Missouri/USA Ohio/USA
56 523
Aug 2005 Aug 2005 AugeSep 2005
New York/USA Louisiana/USA Copenhagen/Denmark
97 31 99 (13)
AugeDec 2005
London/England
84
Interactive fountain, state park Treated recreational water in community pools Treated recreational water in a hotel pool Treated recreational water in a community pool Treated recreational water in a community wading pool Treated recreational water in a water park pool Treated recreational water in a membership club pool Use of a recreational water interactive fountain Recreational pool water Treated recreational water in a community pool Treated recreational water in a camp pool Interactive fountain in a water park Carrots served in a basin with water at a canteen salad bar Swimming pools
Treated recreational water in a community pool Treated recreational water in a community wading pool Treated recreational water in a community pool, wading pool and interactive fountain Treated recreational water of a water park pool Swimming pool in a hotel
Key reference Brockmann et al., 2008 Liang et al., 2006 Hakim et al., 2007
Nichols et al., 2006 Nichols et al., 2006 Dziuban et al., 2006 Dziuban et al., 2006 Dziuban et al., 2006
Dziuban et al., 2006 Ichinohe et al., 2005, Yokoi et al., 2005, Takagi et al., 2008 Dziuban et al., 2006 Dziuban et al., 2006 Wheeler et al., 2006 Robertson et al., 2006a, b Dziuban et al., 2006 Nichols et al., 2006 Institute of Environmental Science and Research Ltd (ESR), New Zealand, 2004 Dale et al., 2010 Health Protection Surveillance Center (HPSC) 2006, Ireland Health Protection Surveillance Center (HPSC), Ireland Yoder et al., 2008 Yoder et al., 2008 Yoder et al., 2008 Yoder et al., 2008 Yoder et al., 2008 Yoder et al., 2008 Yoder et al., 2008 Schaffzin et al., 2006 Turabelidze et al., 2007 Yoder et al., 2008 Yoder et al., 2008 Yoder et al., 2008 Ethelberg et al., 2009 Nichols et al., 2006 (continued on next page)
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Table 1 e (continued ) Month/year
Location/country
Est. cases
Sep 2005
Western Turkey
191 (15)
SepeNov 2005 SepeDec 2005
South East England North-west Wales
140 (140) 218
Oct 2005
New York/USA
22
Nov 2005
100e232
2005 2005 2005
Gwynedd and Anglesey, northwest Wales/UK Kentucky, Ohio/USA New South Wales/Australia New Zealand
2005 2005 2005
Victoria/Australia Victoria/Australia Victoria/Australia
9 (9) 6 (5) 20 (18)
Jan 2006 May 2006
England Florida/USA
14 (6) 55
May 2006
South West England
35
Jun 2006
Missouri/USA
116
Jun 2006
Wyoming/USA
29
Jun 2006
Pennsylvania/USA
13
JuneOct 2006
Wyoming/USA
34
JuneNov 2006
85
Jul 2006
Charleston region, South Carolina/USA Montana/USA
Jul 2006
Illinois/USA
65
Jul 2006
Louisiana/USA
29
Jul 2006
South-Ireland
28
Jul 2006
California/USA
16
Jul 2006
South Carolina/USA
12
Jul 2006
Missouri/USA
6
Jul 2006
South-Ireland
2
JuleAug 2006
Louisiana/USA
35
Aug 2006
Wisconsin/USA
22
Aug 2006
Georgia/USA
19
Aug 2006
Illinois/USA
18
>800 254 (254) 5 outbreaks, 17 cases
82
Susp. cause Public drinking water supply contaminated by sewage or animal waste following heavy rainfall Public water supply Drinking unboiled tap water, washing fruit or salad, fruit juice drinks, and other transmission ways Treated recreational water in a membership club pool Drinking water from several sources, incl. Lake Cwellyn Multiples modes of transmission Public swimming pool 63% untreated water supply, 22.2% contamination of water source, 7.4% contamination of reservoirs, 37% unknown factors (percentages relate to a total number of 27 waterborne outbreaksc) Public swimming pool Unknown swimming pool Suspected waterborne, public Swimming pool Swimming pool Treated recreational water, interactive fountain Faecally contaminated surface water, consumption of water from private well Treated recreational water, interactive fountain, water park Multiple community pools and untreated reservoir Treated recreational water, pool of a membership club Recreational water use at any public swimming pool and one local reservoir Recreational water venues and 13 day care centers Treated recreational water of community pools Treated recreational water in a water park of a day camp Treated recreational water, interactive fountain, water park pool Waterborne
Treated recreational water, interactive fountain Treated recreational water of a community pool Treated recreational water of a community pool Waterborne, private house
Recreational water use at commercial water park Treated recreational water of a community pool Treated recreational water in a community pool Treated recreational water of a water park
Key reference Aksoy et al., 2007
Nichols et al., 2006 Mason et al., 2010
Yoder et al., 2008 Carnicer-Pont et al., 2005; Nichols et al., 2006 Yoder et al., 2008 Dale et al., 2010 Institute of Environmental Science and Research Ltd (ESR), New Zealand, 2005
Dale et al., 2010 Dale et al., 2010 Dale et al., 2010 Davison, 2006 Yoder et al., 2008 Hoek et al., 2008 Yoder et al., 2008 Yoder et al., 2008 Yoder et al., 2008 Alden et al., 2007 Alden et al., 2007 Yoder et al., 2008 Yoder et al., 2008 Yoder et al., 2008 Health Protection Surveillance Center (HPSC) 2007, Ireland Yoder et al., 2008 Yoder et al., 2008 Yoder et al., 2008 Health Protection Surveillance Center (HPSC) 2007, Ireland Alden et al., 2007 Yoder et al., 2008 Yoder et al., 2008 Yoder et al., 2008
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Table 1 e (continued ) Month/year
Location/country
Est. cases
Susp. cause
Aug 2006
Colorado/USA
15
Birthday party at indoor community swimming pool Day camp pool and community water park Treated recreational water of a community pool Treated recreational water of a water park Treated recreational water in a hotel pool Treated recreational water in school pools Drinking water from a well (in a church) Interactive water fountain in neighborhood Waterborne
Aug 2006
Illinois/USA
7
Aug 2006
Wisconsin/USA
4
Aug 2006
Illinois/USA
4
Aug 2006
Florida/USA
3
Sep 2006
Minnesota/USA
47
Sep 2006
Ohio/USA
10
Sep 2006
Florida/USA
49 (9)
Oct 2006
West-Ireland
6
Oct 2006
Georgia/USA
4
Nov 2006
South-east-Ireland
8
Treated recreational water in a community pool Waterborne community outbreak
Dec 2006
USA
7
Waterborne community outbreak
2006
Victoria/Australia
134 (134)
2006
Victoria/Australia
30 (11)
2006 2006
South Australia Victoria/Australia
19 (14) 18 (18)
2006
New Zealand
6 outbreaks, 15 cases
2006
Western Australia
14 (14)
2006
Victoria/Australia
10 (7)
Jan 2007
South-east-Ireland
7
Suspected waterborne, unknown swimming pool Suspected waterborne, school swimming pool Waterborne, unspecified source Suspected waterborne, public swimming pool 83.3% untreated water supply, 44.4% contamination of water source, 5.6% contamination of reservoirs, 5.6% unknown factors (percentages relate to a total number of 18 waterborne outbreaksc) Suspected waterborne, public swimming pool Suspected waterborne, public swimming pool Waterborne community outbreak
Feb 2007
182 (98)
Mar 2007
City and county of Galway/Ireland West-Ireland
304
Public water supply using Lough Corrib (a large lake) Waterborne community outbreak
Mar 2007
USA
186
Waterborne community outbreak
Mar 2007
Norway
25 (10)
Jun 2007
USA
2
Drinking water from hotel dispensers and tap water, consuming ice cubes in hotel bar, eating broccoli soup Waterborne, private house
JuneDec 2007 Jul 2007
Utah/USA South-Ireland
1902 2
Treated recreational water venues Waterborne, private house
Key reference Boehmer et al., 2009 Alden et al., 2007 Yoder et al., 2008 Yoder et al., 2008 Yoder et al., 2008 Yoder et al., 2008 Yoder et al., 2008 Eisenstein, 2008 Health Protection Surveillance Center (HPSC) 2008, Ireland Yoder et al., 2008 Health Protection Surveillance Center (HPSC) 2008, Ireland Departments of Public Health 2007 Dale et al., 2010 Dale et al., 2010 Dale et al., 2010 Dale et al., 2010 Institute of Environmental Science and Research Ltd (ESR), New Zealand, 2006
Dale et al., 2010 Dale et al., 2010 Health Protection Surveillance Center (HPSC) 2008, Ireland Pelly et al., 2007 Health Protection Surveillance Center (HPSC) 2008, Ireland Departments of Public Health 2007 Hajdu et al., 2008
Departments of Public Health 2007 Rolfs et al., 2008 Health Protection Surveillance Center (HPSC), Ireland (continued on next page)
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Table 1 e (continued ) Month/year
Location/country
Est. cases
Susp. cause
Aug 2007 Aug 2007
Idaho/USA Stockholm/Sweden
50 23 (9)
OcteDec 2007 2007
Staffordshire/England Galway/Ireland
57 (39) 182
2007
New Zealand
5 outbreaks, 16 cases
2007
4 (2)
Jan 2008
Northern Territory/ Australia West-Ireland
Mar 2008
South-Ireland
2
Waterborne and person-to-person in a private house
JuneJul 2008
Northamptonshire/UK
33 (23)
Jul 2008
South-east-Ireland
2
Drinking water supplied from the Pitsford Reservoir Waterborne and animal transmission in a private house
2008
New Zealand
4 outbreaks, 17 cases
2009
New Zealand
5 outbreaks, 13 cases
Nov 2010
¨ stersund/Sweden O
10,000
3
Recreational water at splash parks Drinking water from a well at a camping site close to a field with sheep Swimming pool associated Heavy precipitation of historic proportions and the water source reaching the highest level on record 80% untreated water supply, 20% contamination of water source, 6.7% treatment process failure, 6.7% contamination of reservoirs, 6.7% post treatment contamination, 13.3% unknown factors (percentages relate to a total number of 15 waterborne outbreaksc) Suspected waterborne, public swimming pool Waterborne, private house
61.5% contamination of water source, 50% untreated water supply, 11.5% contamination of reservoirs, 15.4% unknown factors (percentages relate to a total number of 26 waterborne outbreaksc) 66.7% untreated drinking water supply, 20.8% contamination of reservoirs, 16.7% contamination of water sources, 20.8% unknown factors (percentages relate to a total number of 24 waterborne outbreaksc) Contaminated water supply
Key reference Jue and Schmalz, 2009 Persson et al., 2007
Coetzee et al., 2008 Pelly et al., 2007
Institute of Environmental Science and Research Ltd (ESR), New Zealand, 2007
Dale et al., 2010 Health Protection Surveillance Center (HPSC) 2009, Ireland Health Protection Surveillance Center (HPSC) 2009, Ireland Smith et al., 2010 Health Protection Surveillance Center (HPSC), Ireland Institute of Environmental Science and Research Ltd (ESR), New Zealand, 2008
Institute of Environmental Science and Research Ltd (ESR), New Zealand, 2009
Sveriges Radio 2010
( ): laboratory confirmed cases. a outbreak occurred before 2004, but was published at 2010 and is not included in the review of Karanis et al. (2007). b infectious rate of tested stool samples. c for some waterborne outbreaks more than one contributing factor was recorded. d variation between authors.
From the 61 outbreaks in North America (30.6%) 60 appeared in the United States (30.1%) and 1 in Canada (0.5%). The documented five outbreaks in South America (2.5%) occurred in Peru (two outbreaks, 1%), in Brazil (two outbreaks, 1%) and in French Guiana (one outbreak, 0.5%). Europe contributes 16.5% (33) of worldwide waterborne outbreaks. The distribution within the European countries is as follows: Ireland 6.5% (13) of worldwide waterborne outbreaks, the United Kingdom 5.5% (11), Norway 2% (4),
Sweden 1% (2) and at least 0.5% (1) in Finland, Denmark and Germany, respectively. In Asia 7 (3.5%) waterborne outbreaks of parasitic protozoan diseases were reported, 3 (1.5%) in Turkey and 1 (0.5%) in each of the following countries: Japan, China, India and Malaysia. The worldwide distribution of waterborne outbreaks caused by parasitic protozoa on the individual continents is presented in Fig. 1, while Fig. 2 shows the distribution across countries.
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Table 2 e List of worldwide waterborne outbreaks caused by Giardia lamblia. Month/year
Location/country
Est. cases
Nov 2003eJul 2004 Mar 2004 AprileMay 2004
Trondheim/Norway Missouri/USA Cameron Highlands /Malaysia
12 9 (Probably 79)
MayeSep 2004 Jun 2004 AugeOct 2004
Ohio/USA Vermont/USA Bergen/Norway
3e1450 11 2500 (1300)
2004
New Zealand
11 outbreaks, 34 cases
Jul 2005
California/USA
3
Aug 2005 Oct 2005 2005
41 196 (7) 12 (3)
2005
California/USA Izmir/Turkey New South Wales /Australia New Zealand
May 2006 Sep 2006 2006
Colorado/USA Florida/USA New Zealand
6 49 (38) 7 outbreaks, 22 cases
JuleAug 2007
California/USA
50 (26)
Sep 2007 Nov 2007e Feb 2008 2007
New Hamshire/USA Nokia/Finland
31 ND
Northern Ontario /Canada
ND
2007
New Zealand
7 outbreaks, 32 cases
2008
New Zealand
14 outbreaks, 63 cases
2009
New Zealand
13 outbreaks, 44 cases
9 outbreaks, 34 cases
Susp. cause/parasite Waterborne, child day care center Untreated recreational water, lake G. lamblia (17.6%), Entamoeba (9.4%), Blastocystis hominis (8.1%), Cryptosporidium (2.7%)a/source of infection probably contaminated water or food Sewage contaminated groundwater Drinking water from a well in a camp Leaking sewage pipes and insufficient water treatment 8 outbreaks caused untreated water supplies, 1 by inadequate water source, 2 by multiple sources Water not intended to drink in a private residence Drinking water Faecal contamination in public water supply Suspected rainwater tank or bore water in a health spa resort 63% untreated water supply, 22.2% contamination of water source, 7.4% contamination of reservoirs, 37% unknown factors (percentages relate to a total number of 27 waterborne outbreaksb) River water in wilderness Interactive water fountain in neighborhood 83.3% untreated water supply, 44.4% contamination of water source, 5.6% contamination of reservoirs, 5.6% unknown factors (percentages relate to a total number of 18 waterborne outbreaksb) Unsterilized sand in slow sand water filtration system in a private recreational camp Community drinking water associated (tap water) Sewage contamination of drinking water distribution network Water source in a tree-planting camp
80% untreated water supply, 20% contamination of water source, 6.7% treatment process failure, 6.7% contamination of reservoirs, 6.7% post treatment contamination, 13.3% unknown factors (percentages relate to a total number of 15 waterborne outbreaksb) 61.5% contamination of water sources, 50% untreated water supply, 11.5% contamination of reservoirs, 15.4% unknown factors (percentages relate to a total number of 26 waterborne outbreaksb) 66.7% untreated drinking water supply, 20.8% contamination of reservoirs, 16.7% contamination of water sources, 20.8% unknown factors (percentages relate to a total number of 24 waterborne outbreaksb)
Key reference Wahl and Bevanger, 2007 Dziuban et al., 2006 Hakim et al., 2007
O’Reilly et al., 2007 Liang et al., 2006 Nyga˚rd et al., 2006, Robertson et al., 2006a, b; Strand et al., 2008 Institute of Environmental Science and Research Ltd (ESR), New Zealand, 2004 Yoder et al., 2008 Yoder et al., 2008 Tuncay et al., 2008 Dale et al., 2010 Institute of Environmental Science and Research Ltd (ESR), New Zealand, 2005 Yoder et al., 2008 Eisenstein, 2008 Institute of Environmental Science and Research Ltd (ESR), New Zealand, 2006 Karon et al., 2010 Daly et al., 2009 Rimhanen-Finne et al., 2010 C-EnterNet Annual Report 2007, Public Health Agency of Canada Institute of Environmental Science and Research Ltd (ESR), New Zealand, 2007
Institute of Environmental Science and Research Ltd (ESR), New Zealand, 2008
Institute of Environmental Science and Research Ltd (ESR), New Zealand, 2009
ND: no data. ( ): laboratory confirmed cases. a infectious rate of tested stool samples. b for some waterborne outbreaks more than one contributing factor was recorded.
In this review, 36.2% (72) of the documented worldwide outbreaks caused by protozoan pathogens had multiple ways of transmission, e.g. untreated water supplies, contamination of water sources, treatment process failures, contamination of
reservoirs and post treatment contamination. In 33.7% (67 outbreaks), the transfer through recreational water was detected as the source of infection, mainly due to the contamination with Cryptosporidium spp. in 32.7% (65) of
Mao et al., 2009 Khan et al., 2006 31 (23) 8 Jiangshan City/China Agronomica/Brazil MayeJun 2006 ND/between 2003 and 2005
112 (27) 138 37 (7) 191 (9) Lima/Peru 35 states and Puerto Rico Lima/Peru Izmir/Turkey Nov 2004 Jan 2005eMay 2007 Mar 2005 Sep 2005
249 (178) Coimbatore City/India Aug 2004eJul 2005
Fig. 1 e Distribution of worldwide waterborne outbreaks caused by parasitic protozoan between 2004 and 2010 by continent.
described outbreaks. In 20.6% (41) of the listed outbreaks, drinking water systems were contaminated with a protozoan pathogen. In 9.5% (19 outbreaks) of the reported outbreaks the way of transmission was not mentioned.
4.
( ): labor-confirmed cases. ND : no data. a outbreak occurred before 2004, but was published at 2010 and is not included in the review of Karanis et al. (2007). b infectious rate of tested stool samples.
Palanisamy et al., 2006, Balasundaram et al., 2010 Torres-Slimming et al., 2006 MMWR 2007 Mundaca et al., 2008 Aksoy et al., 2007
Vaudaux et al., 2010 Joslin et al., 2006 Demar et al., 2007 Hakim et al., 2007
T. gondii/contaminated cistern, municipal water supply Acanthamoeba (Keratitis)/probably waterborne T. gondii/unknown source G. lamblia (17.6%), Entamoeba (9.4%), B. hominis (8.1%), Cryptosporidium (2.7%)b/source of infection probably contaminated water or food T. gondii (ocular)/probably contaminated supplying water after heavy rainfall C. cayetanensis/way of transmission unclear Acanthamoeba (Keratitis)/probably waterborne C. cayetanensis/unknown way of transmission Cyclospora, co-infection with outbreak of cryptosporidiosis/ contaminated public drinking water supply E. histolytica T. gondii/non-treated water in common neighborhood 20 40 11 Probably 79 Santa Isabel do Ivai/Brazil Chicago-Gary-Kanosha area, Illinois/USA Patam/French Guiana Cameron Highlands/Malaysia OcteDec 2001 Jun 2003eNov 2005 Dec 2003eJan 2004 AprileMay 2004
Est. cases Location/country
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 6 0 3 e6 6 1 4
a
Month/year
Table 3 e List of worldwide waterborne outbreaks caused by other parasitic protozoa.
Parasite/susp. cause
Key reference
6610
Discussion
The gathering of worldwide waterborne parasitic protozoan outbreaks illustrates their global distribution pattern. The present survey shows a large number of outbreaks in a short time period, 199 worldwide outbreaks in 7 years, while the previous overview of Karanis et al. (2007) presented 325 reported outbreaks in 100 years. This significant difference in the number of reported outbreaks is caused by the substantial improvements of data reporting and the establishment of surveillance systems in developed countries. Both achievements of the developed countries are also the reasons for the distortion in the reflection of the global distribution pattern. The highest prevalence of parasitic protozoan infections is known to occur in developing countries due to their low hygiene standards. Thus, the highest rate of waterborne parasitic protozoan outbreaks should be estimated in these countries. Though, we found a higher rate of reported waterborne protozoan outbreaks in developed nations. These findings are due to the better technological and logistical possibilities of the developed countries. As the collection of data depends on the detection, investigation and reporting system of the outbreaks (Leclerc et al., 2002) many waterborne parasitic protozoan outbreaks stay unrecognized or unreported. In 1990, Craun estimated that
Fig. 2 e Distribution of worldwide waterborne outbreaks caused by parasitic protozoa between 2004 and 2010 by country.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 6 0 3 e6 6 1 4
only a low fractional amount of waterborne outbreaks affecting the United States are detected and reported, possibly as low as one-tenth (Craun, 1990). In 1995, Morris and Levin suggested that the annual incidence of waterborne infectious diseases in the United States could even be as high as 8 million cases of illness and around 1200 cases of death (Morris and Levin, 1995). Likewise, in the Annual Epidemiological Report on Communicable Diseases in Europe 2009, ECDC infectious diseases due to protozoan are described to be underreported, e.g. the data of cryptosporidiosis from several EU countries are lacking and several countries have not established a surveillance system for toxoplasmosis (www.ecdc.europa.eu). The National Institute of Hygiene in Poland (PZH) does not report human cases of cryptosporidiosis although they are registered and the annual number of human giardiasis is probably underestimated (Bajer, 2008). As water is the transmission route of the referred protozoa Giardia cysts and Cryptosporidium oocysts are widely distributed in aquatic ecosystems and could be detected in 81% and 87% of raw water samples of 66 surface water treatment plants in the United States 1991 (LeChevallier et al., 1991). Worldwide, G. lamblia is one of the most prevalently identified causative pathogen in waterborne disease outbreaks (WBDOs). Waterborne outbreaks of giardiasis are usually associated with ingestion of contaminated surface water or groundwater while the contamination of recreational water has also been noticed (Marshall et al., 1997). In developed countries G. lamblia and Cryptosporidium spp. are the most common waterborne pathogens. Slifko et al. (2000) described three reasons for this: domestic animals are often infected with cryptosporidiosis or giardiasis, the aquatic ecosystem is contaminated by the high frequency of environmental burden and lastly, Giardia cysts and Cryptosporidium oocysts are resistant against commonly used water disinfectants (Slifko et al., 2000). In the early 1900s waterborne diseases were accountable for 25% of deaths due to infectious diseases. Chlorination, the first used disinfection for public water supplies, lead to a dramatic decrease of waterborne diseases in the United States (Cutler and Miller, 2005). The WHO introduced treatment guidelines for the quality of drinking water which includes the treatment of water intended to drink with plain sedimentation, pre-filtration, slow sand filtration, coagulation, flocculation and sedimentation, rapid sand filtration, aeration and disinfection via boiling, UV radiation, chlorine and ozone. For water treatment plants multi-barrier systems are recommended (www.who.int). After the introduction of membrane filtration in North West England, the incidence of cryptosporidiosis decreased around 79% (Goh et al., 2005). The CDC in collaboration with the Pan American Health Organization (PAHO) generated a Safe Water System (SWS) which includes three elements: water treatment with sodium hypochlorite at the point-of-use (reduction of diarrheal disease incidence: 26e84%), storage of water in safe containers, as well as advanced hygiene and water handling practices. Since 1998 national, regional and local SWS projects have been implemented with NGO and government partners in over 30 countries. A systematic review of interventions to improve water quality for preventing diarrhea published 2007 by Clasen pointed out that interventions generally are effective (Clasen et al., 2007).
6611
USEPA and CDC established protection and prevention guidelines as well as national statistics of waterborne outbreaks caused by different agents in the United States. In 1994, USEPA published the Cryptosporidium Criteria Document (www.epa.gov) and thus declared Cryptosporidium as a primary drinking water contaminant. The attention on this protozoon raised and led to more investigation. Beside traditional microscopy and staining methods, enzyme immunoassays (EIAs), direct fluorescent-antibody (DFA) and the polymerase chain reaction (PCR) have become established as sensitive and specific detection methods (Morgan et al., 1996). As a result of the enhanced surveillance the USEPA announced the Interim Enhanced Surface Water Treatment Rule to minimize the level of Cryptosporidium spp. in finished water and estimated that the incidence of endemic illness caused by Cryptosporidium spp. will decrease by 463,000 cases each year (www.epa. gov). Due to the advertence and the surveillance system, the data reported for the United States are the most complete of waterborne diseases worldwide (Leclerc et al., 2002). The increasing quality of documentation led to a rise in reported outbreaks during recent years, especially in cryptosporidiosis and giardiasis (Craun et al., 2005). Nevertheless, the supreme incidence of waterborne parasitic protozoan infection is suggested to occur in developing countries. In Latin America, Asia and Africa around 600 million people live in unhealthy homes (Cotruva et al., 2004), 1.1 billion people lack access to improved water supplies and 2.6 billion people lack adequate sanitation (www.who.int). Hence high prevalence rates of waterborne infectious diseases can be expected in developing countries where water supply and waste disposal are deficient. Lanata (2003) stated that the majority of giardiasis outbreaks occur in Latin America, Africa and Asia, with about 5 105 new cases each year. However, gastrointestinal infections are under-diagnosed in developing countries and the prevalence is underestimated (Lanata, 2003). Current and Garcia (1991) recorded prevalence rates of Cryptosporidium in stool samples of patients with gastroenteritis of 1e4% in Europe and North America, while the prevalence rates in Africa, Asia, Australia and South America amount to between 3 and 20%. They also detected high rates of asymptomatic carriage of Cryptosporidium (10e30%) in developing countries compared to low rates of 35 C inhibit reductive dechlorination activity at the Great Lakes and Ft. Lewis sites, and that the majority of reducing equivalents released from the soil matrix during heat treatment are consumed in methanogenesis rather than reductive dechlorination. These observations suggest that bioaugmenting thermal treatment sites with cultures that do not contain methanogens may allow practitioners to realize enhanced dechlorination activity, a potential benefit of coupling thermal treatment with bioremediation. ª 2011 Elsevier Ltd. All rights reserved.
* Corresponding author. Department of Microbiology, University of Tennessee, M409 Walters Life Sciences, Knoxville, TN 37996-0845, USA. Tel.: þ1 865 974 4933; fax: þ1 865 974 4007. E-mail address:
[email protected] (F.E. Lo¨ffler). 1 Present address: USEPA/OCSPP/OPP, Antimicrobials Division, 2777 S. Crystal Dr., Arlington, VA 22202, USA. 0043-1354/$ e see front matter ª 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2011.09.033
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1.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 6 2 5 e6 6 3 6
Introduction
Tetrachloroethene (PCE) and trichloroethene (TCE) often exist in the subsurface as dense non-aqueous phase liquids (DNAPLs), which can serve as long-term sources of groundwater contamination (Ramsburg et al., 2004). In situ thermal treatment coupled with soil vapor extraction can rapidly remove significant amounts of chlorinated ethene mass (Heron et al., 1998, 2009; McGuire et al., 2006), but like other source zone remedies, thermal treatment is unlikely to remove 100% of the DNAPL mass (Davis, 1998; Sale and McWhorter, 2001; Christ et al., 2005). Anaerobic bioremediation has been employed successfully for the cleanup of chlorinated ethene plumes (Lo¨ffler and Edwards, 2006), and recent studies suggest that bioremediation may be an effective posttreatment polishing step following thermal treatment (Christ et al., 2005; Friis et al., 2006b, 2007). Anaerobic bioremediation of PCE and TCE occurs via stepwise reductive dechlorination reactions, i.e., PCE is transformed to TCE, TCE is transformed to dichloroethenes (mainly cis-1,2dichloroethene [cis-DCE]), DCEs are transformed to vinyl chloride (VC), and VC is transformed to non-toxic ethene. While numerous bacteria dechlorinate PCE and TCE to cisDCE, strictly hydrogenotrophic Dehalococcoides (Dhc) strains are the only known organisms capable of gaining energy from cisDCE to ethene reductive dechlorination (He et al., 2003). Dhc have stringent redox, temperature, and nutritional requirements (He et al., 2003; Friis et al., 2007; Amos et al., 2008). While previous studies have suggested that electrical resistance heating (ERH) may have little impact on redox conditions (Friis et al., 2005, 2006b), thermal treatment obviously affects subsurface temperature as source zones are routinely heated to temperatures of 100 C or greater (Heron et al., 1998). Optimal temperatures for complete microbial reductive dechlorination to ethene are 25e30 C, higher than those of most aquifers, but much lower than source zone temperatures during heat treatment (Friis et al., 2007; Costanza et al., 2009; Fletcher et al., 2010). Therefore, dechlorination activity is unlikely to occur during active thermal treatment of DNAPL source zones, but accelerated dechlorination and ethene formation may be observed during thermal treatment in the perimeter of the source zone where temperatures are in the range for Dhc activity. To effectively treat residual source zone contamination following thermal treatment, bioaugmentation with Dhc-containing PCE-toethene dechlorinating consortia may be necessary (Major et al., 2002; Lendvay et al., 2003; Lo¨ffler and Edwards, 2006; Hood et al., 2008; Scheutz et al., 2010). Previous studies reported the release of organic carbon from the subsurface matrix during thermal treatment and suggested that the increase in bioavailable electron donors could support microbial dechlorination (Friis et al., 2005, 2006a). However, the released organic carbon, suggested to be in the form of long-chain fatty acids (Friis et al., 2005), cannot directly serve as an electron donor for Dhc and must be fermented to produce H2. Furthermore, Dhc must compete with other organisms, such as methanogens, for available H2. Thermal treatment has been shown to reduce methanogenesis, even after bioaugmentation with the methanogenic
dechlorinating consortium KB-1, suggesting that dechlorinating Dhc may outcompete methanogens for H2 following thermal treatment (Friis et al., 2006a). Therefore, if thermal treatment both increases H2 flux and decreases the activity of competing H2 utilizers such as methanogens, dechlorination could be supported by indigenous electron donors, thus alleviating the need for biostimulation (i.e., the introduction of external substrates). To further explore the utility of combining thermal treatment and bioremediation, (i) the potential for dechlorination activity to occur in the perimeter of the source zone during thermal treatment and (ii) the impact of competing H2 utilizers (e.g., methanogens) on reductive dechlorination activity were evaluated experimentally. Microcosms, established with soils from two chlorinated ethene-contaminated sites, were incubated at 24, 35, 50, 70, and 95 C and, following cooling to 24 C, were bioaugmented with a methanogenic PCE-to-ethene-dechlorinating consortium. Reductive dechlorination and methanogenesis were monitored to determine if the activity of dechlorinators and/or their competitors correlated with previous incubation temperature.
2.
Materials and methods
2.1.
Site descriptions and soil preparation
Soil and groundwater samples impacted with TCE and cis-DCE (90% over one year (compared to
Biofuels
the control with only 53%). Increased dominance of Pediastrum sp. greatly improved the
High rate algal ponds
efficiency of algal harvest (annual average of >85% harvest for the HRAPr compared with
Wastewater treatment
w60% for the control). Imhoff cone experiments demonstrated that algal settleability was
Algal harvest
influenced by both the dominance of Pediastrum sp. and the species composition of
Algal species control
remaining algae. Algal biomass recycling increased the average size of Pediastrum sp.
Algal recycling
colonies by 13e30% by increasing mean cell residence time. These results indicate that recycling gravity harvested algae could be a simple and effective operational strategy to maintain the dominance of readily settleable algal species, and enhance algal harvest by gravity sedimentation. ª 2011 Elsevier Ltd. All rights reserved.
1.
Introduction
High rate algal ponds (HRAPs) provide cost-effective and efficient wastewater treatment with minimal energy consumption and have considerable potential to upgrade oxidation ponds (Craggs et al., 2003; Garcı´a et al., 2006; Heubeck et al., 2007; Park and Craggs, 2010). Furthermore, the algal biomass produced and harvested from these wastewater treatment systems could be converted through various pathways to biofuels, for example anaerobic digestion to biogas, transesterification of lipids to biodiesel, fermentation of
carbohydrate to bioethanol and high temperature conversion to bio-crude oil (Sukias and Craggs, 2011; Vasudevan and Fu, 2010; Craggs et al., 2011). Wastewater treatment and algal biofuel production both require rapid and cost-effective harvest of algal biomass from HRAP effluent, therefore, methods to improve algal harvest efficiency would be of great benefit (Benemann, 2003; Chen and Yeh, 2005; van Harmelen and Oonk, 2006; Brennan and Owende, 2010). However, algal cells are very difficult to remove due to their small size (300 mg TSS/ L) to allow adjacent algal cells or colonies to be distinguished, a 1 mL sample of diluted HRAP water was used.
2.4.2.
Taking microscopic images
Safi (2009) found that taking microscopic images of the whole settling chamber is neither necessary nor feasible, particularly when algal cell/colony numbers are high. If the algae have settled evenly across the base of the settling chamber (checked by scanning the whole settling chamber at low magnification), microscopic images can be taken of randomly selected fields of view (FOV). If the algae have not settled evenly, images may be taken of equally spaced FOV along transects that run perpendicular to any observed settling gradient (Safi, 2009). The number of microscopic images required for the measurement of cell/colony dimensions and counts varied with algal population density but were typically 10.
2.4.3.
Identification of algal species
The most abundant algal species in the microscopic images of the HRAP water were identified using an identification guide (Brook, 2002). Dominant invertebrate grazers (e.g. Moina) were
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Table 1 e Operational parameters of wastewater treatment pilot-scale HRAP with and without recycling gravity harvested algae in terms of design/weather compensated inflow rate, influent nutrient concentrations (NH44D-N and PO43L-P), hydraulic retention time (HRT), algal mean cell residence time (MCRT) and algal recycling rate to the HRAPr. Parameters
Winter
Spring
Summer
Autumn
Winter
67 (July 1e Sept 6, 09) 1.0 1.1 0.2 30.3 4.0 5.5 1.1 8.0 7.7 1.2 8.9 1.4 7.7 1.2 105 32
76 (Sept 7e Nov 22, 09) 1.3 1.4 0.2 22.5 7.5 4.0 1.0 6.0 5.9 0.8 6.5 0.9 5.9 0.8 66 25
113 (Nov 23, 09e Mar 16, 10) 2.0 2.0 0.2 20.6 9.2 4.0 0.7 4.0 4.1 0.4 4.6 0.4 4.1 0.4 76 22
70 (Mar 17e May 25, 10) 1.3 1.3 0.2 39.5 6.5 5.9 1.0 6.0 6.1 0.5 7.2 0.6 6.1 0.5 170 89
34 (May 26e Jun 30, 10) 1.0 1.2 0.3 34.3 7.3 4.8 1.2 8.0 7.0 1.5 10.4 2.2 7.0 1.5 212 8
Design Actual
6 5.8 0.8 35 5.1
4.5 4.4 0.6 38 6.2
3 3.1 0.3 33 5.8
4.5 4.6 0.4 32 5.1
6 5.2 1.1 30 9.0
Design Actual
12 11.61.7
9 8.91.1
6 6.20.5
9 9.20.8
12 10.22.2
Experimental duration (d) Experimental period Inflow to HRAPs (m3/d) Influent nutrient concentrations (mg/L) HRAP HRT (d) MCRT (d)b Daily algal recycling rate to HRAPr (g recycled/kg production)c ASC1 HRT (h) Harvested biomass conc. (TS, g/L) ASC2 HRT (h)d
a b c d
Design Actuala NHþ 4 -N PO43-P Design Actuala HRAPr HRAPc
Weather compensated (daily precipitation and evaporation) daily inflow and hydraulic retention time (HRT). Calculated using Eq. (1) below. Volume of algal biomass recycled (L/d) harvested algal biomass concentration (g/L)/the total mass of algae biomass harvested (kg). Combined HRT of ASC1 and ASC2.
MCRT ¼
V1 X1 Qc X1 Qre Xh
ð1Þ
where MCRT ¼ algal mean cell residence time (d), V1: HRAP volume (m3), X1: HRAP algal biomass concentration (g/m3), Qc: compensated HRAP effluent flow rate (m3/d), Qre: algal biomass recycled per day (L/d), Xh: harvested algal biomass concentration (g/L).
also identified and counted; and the occurrence of fungal hyphae in the algal/bacterial floccs was confirmed using the Calcofluor White protocol suggested by Kagami et al. (2007) and Rasconi et al. (2009).
images depending on the algal biomass concentration. Therefore counts for each pond water sample had an accuracy of 10% with 95% confidence limits (Lund et al., 1958; Rott et al., 2007).
2.4.6. 2.4.4. Measurement of algal cell/colony dimensions and algal counts Only viable algal cells/colonies were included (clear or collapsed cells and cell fragments were ignored). Due to the variable and sometimes high number of cells in the colonies of the algae that often dominate HRAP (e.g. Pediastrum sp. can have 8, 16, 32, or 64 cells/colony and Desmodesmus sp. can have 2, 4, or 8 cells/colony), it was not practical to count every cell in a colony. Therefore, the number of colonies of each species was counted and the dimensions (length and width) of each colony were measured to determine the algal biovolume using microscopic image analysis software (Leica Application Suite, LAS version 3.1.0).
2.4.5. Total cell/colony number counts and measurement uncertainty Lund et al. (1958) recommended that for a FOV count, a minimum of 100 cells/colonies should be enumerated to ensure that the count is representative of the sample (20% accuracy with 95% confidence limits). In this study, 200e500 algal cells or colonies were counted from w10 microscopic
Calculation of algal biovolume
Algal biovolume is a more accurate measure of relative algal dominance (%) than cell counts because not all algal cells are the same size (Lyakh, 2007; Rott et al., 2007; Vadrucci et al., 2007). Hillebrand et al. (1999) and Vadrucci et al. (2007) developed geometrical equations to calculate the biovolume of algal species of different shapes from microscopically measured linear dimensions. The equations for the five most dominant algae in the HRAPs (Pediastrum sp., Desmodesmus sp., Micractinium sp., Dictyosphaerium sp. and unicellular algae (including Chlorella sp., flagellates and Thalassiosira sp.)) are shown in Table 2 along with the number of cells per colony. Microscopic image analysis was conducted each month and the data used to calculate algal biovolume, which was in turn used to determine relative algal dominance in the HRAP.
2.5.
Water quality monitoring
Weekly samples of HRAP influent (primary settled raw sewage) and effluent were taken and then analyzed using
Table 2 e Calculations of algal cell/colony biovolume using geometric measurement. Dominant Algae
Pediastrum sp.
Desmodesmus sp.
Micractinium sp.
Dictyosphaerium sp.
Unicellular algae
Photo
Disc/star-shaped, flat and single-layered
Flat, straight or slightly curved
Number of cells/colony
4/8/16/32/64-celled
2/4/8-celled
Calculation of single cell biovolume
Cuboidal, tetrahedral or polyhedral (spherical cells) >4-celled distinguishing into single cells
Spherical (Chlorella sp.), cube (Thalassiosira sp.)
>4-celled distinguishing into single cells
Single cell
p V ¼ $L3 6 (Colonial sphere) L: length (mm)
p V ¼ $d3 (Single 6 sphere) V ¼ d3 (Cube) L: length (mm)
6641
p p L2 p V ¼ $L$W$D V¼ $ $W 4 V ¼ $L3 4 6 4 6 (Elliptic disc) (Prolate spheroid) (Colonial sphere) L: length (mm) W: width (mm) D: depth (mm) L: length (mm) W: width (mm) L: length (mm)
Hollow, spherical
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 6 3 7 e6 6 4 9
Shape of the cell/colony
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w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 6 3 7 e6 6 4 9
standard methods (APHA, 2005) for the following parameters: dissolved reactive phosphorus ammoniacal-N (NHþ 4 -N), (DRP). During the period when a unicellular diatom (Thalassiosira sp.) occurred in the ponds (6the30th March 2010) reactive Silica (as SiO2) was also measured (APHA, 2005) at weekly intervals.
3.
Results and discussion
3.1.
Algal species and algal biovolume
The types of algae found in the HRAPs over the one year experimental period are summarized in Table 3. These included 13 genera of green algae which are commonly found in eutrophic waters and four colonial algae including: two species of Pediastrum sp., Desmodesmus sp., Micractinium pusillum, and Dictyosphaerium sp., which typically dominate wastewater treatment HRAPs around the world (Benemann et al., 1978, 1983; Benemann, 1986; Garcı´a et al., 2000; Park and Craggs, 2010; Craggs et al., 2011). The two species of Pediastrum (Pediastrum boryanum and Pediastrum duplex) were easily distinguished since P. duplex has intercellular spaces and P. boryanum does not. The cell or colony biovolume of the five most abundant algae in the HRAPs (4 colonial species and unicellular algae including the diatom, Thalassiosira sp.) were calculated by image analysis of microscopic photographs of pond water samples. A positive correlation (r ¼ 0.881) was found between HRAP algal biovolume and biomass concentration (measured as TSS) (Fig. 2), indicating that biovolume is a particularly useful measure of algal biomass for wastewater treatment HRAPs. Particularly as the HRAPs selected for colonial algae (Micractinium sp., Dictyosphaerium sp., Desmodesmus sp. and Pediastrum sp.) with colonies of different shapes and varying numbers of cells. For example, the biovolume of a Pediastrum sp. colony can vary with both the number of cells (8, 16, 32 or 64 cells) and the size of the
-0.6
µ
Fig. 2 e The relationship between the algal biovolume and algal biomass concentration in the HRAPs (r [ 0.881).
cells within the colony depending on life-cycle stage and culture conditions.
3.2. Influence of harvested algal biomass recycling on relative algal dominance The relative dominance of the five most abundant algae in the HRAPs was determined at monthly intervals based on biovolume (Fig. 3). The colonial algae Pediastrum sp., Micractinium sp., and Dictyosphaerium sp. were each dominant in the control pond (HRAPc) for periods of two months or more (Fig. 3a). Changes in dominance between these algae occurred within a few weeks. For example, Pediastrum sp. was replaced by
Table 3 e Algae found in the wastewater treatment HRAPs over one year experimental period. Phyllum
Green algae (Chlorophyta)
Dominance
Dominant algae
Occasionally found algae
Diatoms (Bacillariophyceae)
e
HRAPc
HRAPr Genus
Species
Genus
Species
Pediastrum Pediastrum Desmodesmus Micractinium Dictyosphaerium Gonium Ankistrodesmus Monoraphidium Pandorina Radiococcus Kirchneriella Actinastrum Coelastrum Thalassiosira
boryanum duplex sp. pusillum sp. sp. falcatus sp. sp. sp. sp. hantzschii sp. sp.
Pediastrum Pediastrum Desmodesmus Micractinium Dictyosphaerium Gonium Ankistrodesmus Monoraphidium Dictyosphaerium Kirchneriella Actinastrum Coelastrum Chlamydomonas Thalassiosira
boryanum duplex sp. pusillum sp. sp. falcatus sp. sp. sp. hantzschii sp. sp. sp.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 6 3 7 e6 6 4 9
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Fig. 3 e Algal dominance based on calculated biovolume in the pilot-scale wastewater treatment HRAPs over a one year experimental period (from July 2009 to June 2010), a: control HRAPc without algal biomass recycling and; b: HRAPr with algal biomass recycling.
Micractinium sp. in October 2009, which was replaced by Pediastrum sp. in December 2009, which was replaced by the unicellular diatom Thalassiosira sp. in March 2010, which was then replaced by Dictyosphaerium sp. in April 2010. These shifts in algal dominance were probably caused by changes in environmental conditions (notably seasonal variation of solar radiation and pond water temperature which are known to affect species selection, succession and co-existence) and HRAP operational parameters such as hydraulic retention time (Benemann et al., 1977; Harris, 1978; Sommers, 1984; Oswald, 1988). Garcı´a et al. (2000) also reported similar changes in relation to environmental parameters by the dominant algae (including Dictyosphaerium sp., Chlorella sp., Micractinium sp., and Desmodesmus sp.) of a small-scale (0.5 m3) wastewater treatment HRAP without CO2 addition in Spain over a one year experimental period. As can be seen in Fig. 3b, recycling a portion of selectively harvested algal biomass increased the dominance of Pediastrum sp. (76e99% dominance) in the HRAPr compared to the control HRAPc (0e98% dominance) during the one year experimental period. Other colonial algae including Micractinium sp., Desmodesmus sp., Dictyosphaerium sp. and the unicellular diatom Thalassiosira sp. were temporarily present and co-occurred with Pediastrum sp. in the HRAPr but at much lower populations than in HRAPc. Maintaining dominance of a single algal species (Pediastrum sp., >90% dominance) over similarly sized algal species in wastewater treatment HRAP for over one year has not been previously reported in the literature. This suggests that recycling of settled algal biomass could provide a simple method to promote the dominance of readily settleable algal species such as Pediastrum sp. in HRAP.
3.3. Settling characteristics of the dominant algal species Recycling harvested algal biomass preferentially selected is algae that settle rapidly. Since all algae in the HRAP effluent are exposed to the same settling conditions (e.g. water viscosity (h) and temperature) in the algae settling cones, differences in settling efficiency between species, therefore, depend on their physiological state, and morphology (Smith, 1982; Alldredge and Gotschalk, 1989; Chen and Yeh, 2005; Choi et al., 2006). The morphology (i.e. size and irregularity) of the algal cell or colony influences settling velocity according to the frictional drag force exerted as it falls through the fluid under the pull of gravity (Smith, 1982; Padisa´k et al., 2003; Chen and Yeh, 2005; Choi et al., 2006). Therefore, cells or colonies with small surface areas settle faster than cells or colonies of the same density but with larger surface areas (Padisa´k et al., 2003; Choi et al., 2006). Average cell and/or colony biovolume, calculated nominal radius (rs) and approximate theoretical settling velocity (Vtheo) of the five dominant algae were determined using the one year experimental data and are summarized in Table 4. The nominal radius of Pediastrum sp. colonies (the most dominant algae in both HRAPs) ranged from 5.1 to 13.5 mm and depended on colony age and the number of cells per colony (8, 16, 32, or 64). The nominal radius of Pediastrum sp. colonies were 1.4e3.8 times larger than that of the unicellular algae (3.6 mm) and nearly 2 times larger than those of the other colonial algal species present (4.8e5.3 mm for 2e4 celled Desmodesmus sp., 5.5 mm for Micractinium sp., and 7.9 mm for Dictyosphaerium sp.). The theoretical settling velocity, Vtheo, of each alga was
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Table 4 e Average algal cell or colony biovolume of the four dominant algal species/type over the one year experimental period, the number of cells, relative abundance with genera (%), nominal radius (ø, mm) of a sphere of equivalent biovolume to the algal cell or colony, and the approximate relative settling velocity (r2). Algal species
Pediastrum sp.
Desmodesmus sp. Micractinium sp. Dictyosphaerium sp. Unicellular algae
Relative Vtheob Nominal Cell numbers Relative Total cell Average biovolume Total biovolume 3 (mm s.d.) radius radius within abundance counts of cell/colony (rr)a (rs, mm s.d.) a colony within (counts/mL) (mm3 s.d.) genera (%) 8-celled 16-celled 32-celled 64-celled 2-celled 4-celled e e e
7.2 40.2 43.2 9.3 20.4 79.6 e e e
9.59Eþ06 3.37Eþ04 1.78Eþ04 1.10Eþ03 8.20Eþ02 2.87Eþ03 7.96Eþ03 5.45Eþ03 4.04Eþ04
561 308 1834 670 4115 2009 10,219 3217 458 265 617 292 679 446 2073 118 193 82
9.59Eþ06 5.33Eþ07 5.73Eþ07 1.23Eþ07 4.91Eþ05 1.92Eþ06 2.13Eþ06 1.20Eþ06 7.53Eþ06
5.1 4.2 7.6 5.4 9.9 7.8 13.5 9.2 4.8 4.0 5.3 4.1 5.5 4.7 7.9 3.0 3.6 2.7
1.4 2.1 2.8 3.8 1.3 1.5 1.5 2.2 1.0
2.0 4.5 7.7 14.1 1.8 2.2 2.3 4.9 1.0
a Radius relative to a unicellular algae. b Vtheo (theoretical relative settling velocity) is proportional to r2r according to Stoke’s law (Vs ¼ ð2=9Þðr2s gðrp rf Þ=hFr Þ), assuming all other parameters are same. where, g gravitational acceleration, (rp rf) excess density between particles and fluid, h viscosity of the medium, rs nominal radius of the sphere of equivalent biovolume to the algae, F form resistance (the effects of algal shape upon settling).
calculated from the biovolume, assuming form resistance (F) between algae was negligible (Table 4). The larger biovolume and nominal radius of Pediastrum sp. colonies suggest that they could have better settling characteristics (calculated theoretical settling velocity, Vtheo was 2e14 times greater than that of any other algae present in the HRAPs). Therefore, when the HRAP algal biomass was dominated by Pediastrum sp. it was easily harvested by gravity sedimentation.
3.4. Algal biomass harvest depending on dominant algal species The algal biomass concentrations (as TSS) in the HRAP, ASC1 and ASC2 effluents and the algal biomass harvest efficiency after the ASC2 are shown in Fig. 4. Algal biomass concentrations in the HRAP effluent varied from w50 to 420 g/m3 during the one year experimental period depending on seasonal algal
Fig. 4 e Algal biomass concentrations in the effluents from two pilot-scale high rate algal ponds and primary and secondary algal settling cones (ASCs); and calculated total removal efficiency measured over one year: a: HRAPc operated without harvested biomass recycling; b: HRAPr operated with harvested algal biomass recycling.
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growth and invertebrate grazing. However, algal biomass concentrations of the ASC effluents and algal harvest efficiency were highly dependant on the algae that was dominant in the HRAP at that time. Increased dominance (annual average of >90%, Fig. 3) of Pediastrum sp. in HRAPr with algal biomass recycling greatly improved algal biomass harvest efficiency by gravity sedimentation (>75% and >85% algal harvest efficiency after ASC1 and ASC2 respectively). Low final effluent TSS concentrations (90% Pediastrum dominance). However, by June 2010 the Pediastrum dominance in the HRAPc had declined to less than 20%, as Pediastrum sp. was replaced by the poorly-setteable alga, Thalassiosira sp. (w85% dominance) by March 2010, and then Dictyosphaerium sp. (dominance increased from 40% to 85% by June 2010). These results demonstrate that maintaining readily settleable algae such as Pediastrum sp. as the dominant species could provide a way of promoting efficient algal harvest by gravity sedimentation. The temporary establishment of the unicellular diatom (Thalassiosira sp.) in both HRAPs (>82% dominance in the HRAPc and 32% dominance in HRAPr; Fig. 3) during a four week period from 6th to 30th March 2010 was an interesting observation, since it is very unusual for diatoms to grow at high concentration in wastewater treatment HRAP and has not been previously observed at our wastewater treatment HRAP research facility, or reported in the literature (Benemann et al., 1978, 1983; Benemann, 1986; Garcı´a et al., 2000; Craggs et al., 2011; Park and Craggs, 2010). The occurrence of Thalassiosira sp. may be explained by a temporary increase in the dissolved silica concentration (SiO2) of the HRAP influent wastewater, since silica is an essential element for diatom growth and the typical low concentration in wastewater limits the growth of diatoms. Analysis of the influent wastewater to the HRAPs for SiO2 during the period of Thalassiosira sp. occurrence showed a high dissolved silica level (w30 mg/L as SiO2), which declined to 100 spherical single cells with a nominal radius of 5.5e7.9 mm. When these two species were dominant in the ponds algal biomass harvest efficiency was particularly poor (63e77% for Micractinium sp. and only 16e38% for Dictyosphaerium sp, Fig. 4a). In contrast, during the period from December to
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February 2010 when Pediastrum sp. was dominant very high algal harvest efficiency (>85% after the ASC2 with 6 h HRT) was achieved. The lower settling efficiency of Micractinium sp. and Dictyosphaerium sp. compared with Pediastrum sp. might be due to lower density and higher drag resulting from the dispersed structure of the colonies (i.e. large spaces between groups of cells) compared with Pediastrum sp. colonies in which the cells are tightly packed together. Over the one year experimental period, nutrient removal 3 efficiency (86e98% NHþ 4 -N and 50e75% PO4 -P) of HRAPr (in which Pediastrum sp. was maintained at >90% dominance) 3 was similar to that (90e96% NHþ 4 -N and 52e68% PO4 -P) of HRAPc (which had a mixed population of algae). Further detailed wastewater treatment performance of the HRAP in terms of organic compounds (TSS/VSS and BOD5) and nutrient (N and P) removal and a nitrogen mass balance with CO2 addition have been described previously (Park and Craggs, 2010, 2011a, 2011b).
3.5. HRAP
Enhancing algal harvest in wastewater treatment
The Imhoff cone settling efficiency of algae in the HRAP effluent after 10, 30 and 60 min and 24 h was measured throughout the year and was found to be greatly improved when Pediastrum sp. was dominant (Fig. 5a). Average algal settling efficiencies of 75.3 13.7%, 86.0 9.1%, 93.6 2.8%, and 99.2 1.6% were achieved after 10, 30 and 60 min, and 24 h of settling respectively, when Pediastrum sp. was present at over 80% dominance in the HRAPs. However, as Pediastrum sp. dominance declined to less than 40%, algal settling efficiencies reduced to 19.8 8.6%, 25.6 10.2%, 35.2 10.1% and 76.0 10.9% for the respective settling periods. These algal settling efficiency test results confirmed that the dominance of Pediastrum sp. in the HRAP promoted algal settling efficiency particularly for settling periods of less than 1 h. Overall Imhoff cone settling efficiency was also influenced by settling characteristics of the algae that co-existed with Pediastrum sp. (Fig. 5a). For example, when Pediastrum sp. was present at 70% dominance and co-existed with other colonial algae such as Micractinium sp., and Desmodesmus sp. (shown in circle “i”) the 10 min settling efficiency was high (58%), however, when the co-existing algae were mainly poorly settleable unicellular algae such as Thalassiosira sp. (average cell size 3.6 2.7 mm) (shown in circle “ii”), the 10 min settling efficiency was only 38%. Analysis of the data on the population density of unicellular algae (counts/mL) including Thalassiosira sp. and algal settling efficiency during the one year experimental period indicates that algal settling efficiency at all settling times declined if the unicellular algal population was greater than 1 105 cells/mL (Fig. 5b). Therefore, controlling the population density of poorly settleable unicellular algae to below this level could be necessary to achieve efficient algal biomass harvest. The percentage solids (as % total solids) of the algal biomass collected at the bottom of an Imhoff cone after a 24 h settling period were also influenced by the settling characteristics of the dominant algal species and other biological factors (e.g. zooplankton grazing and fungal infection) in the HRAPs (Fig. 6). Pediastrum sp. dominant algal biomass (>90%
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a
b
Fig. 5 e a. Relationship between: a. Pediastrum sp. dominance and algal biomass settling efficiency after 10, 30, and 60 min and 24 h settling in an Imhoff cone (Note: within circle i: 72% Pediastrum sp. D 16% Micractinium sp. D 12% Desmodesmus sp., and circle ii: 70% Pediastrum sp. D 30% Unicellular algae); and, b. unicellular algal counts (counts/mL) and algal biomass settling efficiency in an Imhoff cone.
dominance) was harvested as 2.5e3.0% solids after 24 h gravity sedimentation (December 2009 for HRAPc: Fig. 6a, NovembereDecember 2009 and MayeJune 2010 for HRAPr: Fig. 6b). However, when less settleable colonial (Micractinium sp., and Dictyosphaerium sp.) and poorly settleable unicellular algae (Thalassiosira sp.) were dominant in the control HRAPc, the % solids of harvested algae was only about 1.5e2.0% (Fig. 6a). Moreover, fungal infection in both HRAPs during the summer period of Pediastrum dominance (JanuaryeFebruary 2010) reduced the settled algal biomass solids concentrations from 2.5e3.0% to less than 2.0%, which may have been due to the lower density of algal/fungal floccs. Two species of Pediastrum (P. duplex and P. boryanum) were present in the HRAPs, of which, P. boryanum
a
(intercellular space absent) was the most prevalent species throughout the one year experimental period. In particular, during the three month summer period from December 2009 to February 2010, P. boryanum accounted for 80e98% of total algal biomass in both HRAPs. This period of P. boryanum prevalence coincided with very high algal harvest efficiency (80e95%) in the two ASC (HRT 6 h) (Fig. 4) of both HRAPs. Imhoff cone algal settling experiments in the laboratory conducted during the same period showed that algal biomass recycling in the HRAPr enhanced the algal settling efficiency by 8e15% (76.0 6.4%, 89.3 3.5%, and 97.2 1.9% removal after 10, 30, and 60 min respectively compared with 59.3 13.5%, 76.5 8.9%, and 88.2 9.9% for the control, P-value: 80%) in both HRAPs with and without harvested algal biomass recycling. (The data for each settling were compared to investigate the effect of algal biomass recycling using one-way ANOVA analysis.)
improved algal settling efficiency in the HRAPr may be explained by the presence of larger colonies of P. boryanum as recycling of harvested algae at an algal recycling rate of 66e212 g/kg/d (depending on season, Table 1) extended the mean cell residence time (MCRT) (i.e. the period for growth) in the pond by w0.5 d in summer and w3.4 d in winter.
Extending the MCRT increased the average size and biovolume of P. boryanum colonies in HRAPr by 13e30% and 50e80% respectively compared to those in the control HRAPc measured over the three month period when P. boryanum was prevalent in both HRAPs (December 2009 to February 2010) (Fig. 8).
a
b
Fig. 8 e Average size (a) and biovolume (b) of P. boryanum colonies with different numbers of cells (8e64) in HRAPr with biomass recycling and the control, HRAPc without biomass recycling during the period of P. boryanum dominance (>80%).
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Conclusions
Recycling of harvested algal biomass to the HRAPr increased the dominance of the colonial alga, Pediastrum sp., which settles rapidly, so that >90% dominance was achieved for the majority of the one year study compared to the control HRAPc (53% dominance). Maintaining dominance of a single algal species over similarly sized algal species in wastewater treatment HRAP over one year has not been previously reported in the literature. Increased dominance of Pediastrum sp. greatly improved algal biomass harvest efficiency (90% compared to 60% in the control) from the HRAPr to consistently achieve low TSS concentrations (50% clouds (SANDEC, 2002). Following SODIS
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recommendations, commercially available PET bottled water containers of a single brand with 2 L volume, 30 cm height and 10 cm diameter dimensions were procured from a supermarket in Boston, MA (USA) and emptied prior to experimentation. Due to extensive use of 19 L PC bottles around the world, being disinfected via a combination of chemical and high temperature treatments, PC bottles were also included in the leaching experiments. Laboratory PC bottles (2 L), 20 cm height and 15 cm diameter with similar dimensions to those of PET bottles were emptied, washed thoroughly, air dried and used in our experiments. Bottles were cleaned after each use (emptying all contents) using 0.5 mL of liquid soap and tap water, followed by thorough rinsing with deionized water, and air drying. Each bottle was filled with 2 L ultra-pure water (18.2 MU-cm) from a Barnstead nanopure water purification system (Thermo Scientific, NJ, USA) as a migration stimulant. Solar exposure was simulated via the use of a UV-A lamp (365 nm, UVL-28 EL series, UVP Company, Upland, CA, USA); the 320e400 nm wavelength of UV-A light possesses germicidal properties (Wegelin et al., 2001). The UV-A lamp intensity was about 1500 mW cm2 at a 5 cm distance from the lamp, which was placed within the incubator (personal communication, technical support staff, UVP Company, CA, USA). In a temperature-controlled biological incubator (Blue-M, model #B2730Q, Blue Island, IL, USA), bottles representing the n-th time of reuse from a specific experimental run of the CCD design were subject to the following procedure repeated for n times: deionized-water filled bottle was exposed to UV-A radiation for 1 h at 50 C, being equivalent to one SODIS cycle (SANDEC, 2002); after each cycle, aliquots were collected and analyzed for soluble Br and Sb concentrations. After subjecting bottles to the respective frequency of reuse, they
were exposed to simulated SODIS conditions in the incubator according to Table 1 factorial combinations of the CCD. Filled bottled waters were placed horizontally (on long axis) in the incubator (no shaking) and the following range of SODISsimulated conditions was applied: i) temperatures in the range of 13 C to 47 C; ii) UV-A exposure in the range of 0 h to 16 h; and iii) frequency of bottle reuse in the range of 0 to 27 times (Table 1).
2.2.
Central composite design
Conventional full factorial designs have limitations when the factor number is greater than two since the experimental runs appear to be very large (N ¼ 3k) making it difficult in practice. The central composite design (CCD) presents fewer experimental points and it has been widely used in the fields of science and engineering (Mason et al., 1989). Examples of CCD use in related fields are studies measuring chlorobenzenes in water (Vidal et al., 2007), arsenic bioavailability in contaminated soils (Makris et al., 2008), polybrominated diphenyl ethers in sediment (Yusa et al., 2006), aluminum in fruit juices and soft drinks (Jalbani et al., 2006), toxic metals in mussel tissues etc. (Farfal et al., 2004), polychlorinated biphenyls in human serum (Lopez et al., 2007), just to name a few. Influence of temperature, UV exposure duration, and frequency of reuse on leaching of Sb and Br into bottled water was evaluated with the CCD using Design-Expert software, version 6.0 (Stat-Ease, Inc., Minneapolis, MN, USA). Five levels of each variable, ranging from 13 to 47 C, 0 to 16 h, and 0 to 27 times for the temperature, UV exposure duration, and frequency of reuse, respectively, were studied using the CCD (Table 1). Number of experiments used by the CCD was determined by
Table 1 e Factorial combinations and measured values of leached Sb and Br in bottled water under the experimental conditions of the central composite design. #
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Factors
Response
Temperature ( C)
UV-A exposure (h)
Bottle reuse (#)
PET_Sb (ng L1)
PC_Sb (ng L1)
PET_Br (mg L1)
PC_Br (mg L1)
20 40 20 30 30 20 13 40 40 20 30 30 30 30 30 30 30 40 47 30
0 0 12 6 0 0 6 12 0 12 6 6 6 6 6 6 16 12 6 6
0 0 0 0 10 20 10 0 20 20 10 10 10 10 10 10 10 20 10 27
temperature (Table SI-4). Interaction terms of the three aforementioned factors were not significant at the 95% confidence level with the exception of Sb leaching from PC bottles, where interaction of frequency of bottles reuse and UV exposure was significant ( p < 0.05) (Table SI-4). Frequency of bottle reuse was the major factor that linearly increased Sb leaching from PET bottles at all temperatures tested (13 C to 47 C) regardless of UV exposure duration (Fig. 1). In the case of PC bottles, Sb leaching was significantly greater for UV-exposed bottles that were never used before (just purchased container), but not for reused PC bottles (Fig. 1). Upon frequent PC bottle reuse, Sb leaching was unaffected by changes in UV exposure duration at any temperature (Fig. 1). However, the magnitude of leached Sb concentrations in PC bottles was minimal, overall ( 0.05). Aggregating all CCD data obtained for both Sb and Br leaching from PET and PC bottles resulted in a significant ( p < 0.001) linear correlation between leached Sb and Br concentrations obtained under all factorial combinations of CCD (Fig. 3). Because of the significant correlation, it was suggested that a common mechanism was responsible for the concurrent leaching of Sb and Br, but elucidation of possible leaching mechanisms was not the focus of this study (Fig. 3). Data from a market-representative bottled water survey conducted in Boston, USA showed a highly significant ( p < 0.001) correlation between log-transformed soluble Br and Sb concentrations indicating similar leaching mechanisms from aggregated data obtained from non-carbonated, carbonated, and enriched (vitamin, fruit aroma, etc.) bottled water classes (Andra et al., 2012). The final pH of all bottles used in our CCD study did not change ( p > 0.05) for all factorial combinations, remaining approximately equal to 6.5. Chemical migration from water packaging materials has been thoroughly studied, showing Sb leaching from PET bottles as a function of temperature (Westerhoff et al., 2008;
Keresztes et al., 2009) and solar UV exposure duration (Westerhoff et al., 2008). In this study, PET or PC bottle reuse resulted in gradual Sb leaching without reaching pseudoequilibrium even after 27 times of reuse (Fig. 4). Water Sb concentrations in a PET bottle reused up to 27 times were 250 ng L1, being lower than the maximum contaminant level of Sb in drinking-water (5 mg L1, EU Council Directive 98/83/ EC, 1998). According to CCD model, conditions inducing minimum leaching of Sb from bottled water were considered those of 20 C temperature, 0 h UV (no UV) exposure, and new (never reused) bottles (Table 2). Concentrations of Sb in PET and PC bottled water under these conditions were below limit of quantification (0.5 ng L1), since bottles were initially filled with deionized water (Table 2). Leaching of Sb and Br was predicted (based on the linear model) for the SODIS conditions (6 h at 30 C) to be significantly higher for a reused (20), when compared with that of a never used (0) PET or PC bottle (Table 2). In effect, three times higher Sb concentrations were predicted for a reused, versus a brand new PET or PC bottle subject to SODIS treatment (Table 2). Five times higher Sb concentrations leached from PET or PC reused (27) bottles subject to a worst-case treatment (12 h UV, 47 C) when compared with Sb leaching from new bottles subject to SODIS (Table 2).
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Temperature (30C)
Temperature (13C) UV exposure (h)
5
0
-5
10
5
0
7
14
20
27
0
20
27
0
27
14
20
27
Temperature (47C) UV exposure (h)
30
20
10
0
-10
-10 20
7
Bottle reuse (#)
PC_Br (µg L-1)
PC_Br (µg L-1)
10
14
0
UV exposure (h)
30
20
7
0
Temperature (30C)
UV exposure (h)
0
5
Bottle reuse (#)
Temperature (13C)
PC_Br (µg L-1)
14
7
Bottle reuse (#)
30
10
-5
-5 0
UV exposure (h)
15
PET_Br (µg L-1)
10
Temperature (47C)
UV exposure (h)
15
PET_Br (µg L-1)
PET_Br (µg L-1)
15
20
10
0
-10 0
7
Bottle reuse (#)
14
Reuse (#)
20
27
0
7
14
20
27
Reuse (#)
Fig. 2 e Frequency of bottle reuse and UV exposure duration interaction plots for Br leaching from PET (linear model) and PC (quadratic model) bottles at three different temperatures. Circles, triangles and rectangles stand for experimentally obtained CCD design points, model predicted 12 h UV exposure points, and no UV exposure points, respectively. Black and red lines represent UV exposure (h) at their low (no UV) and high (16 h UV exposure) levels from the CCD. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Antimony concentrations in PC bottles were remarkably lower than those leaching from PET, since Sb is not used in the polymerization process of PC, but could be perhaps added in minor quantities as a flame retardant (Albemarle, 2011). The highest concentrations of leached Br were observed for PET bottles subject to SODIS treatment. No effect of the tested factors used by SODIS or the worst-case scenario influenced leaching of Br from PC bottles, remaining unaffected at w7e8 mg L1 (Table 2). A similar, but not identical parameter of chemical leaching to frequency of bottle reuse is storage time, since storage time refers to storing a bottle with the same liquid for a long time. Storage time has been shown to affect chemical leaching from plastic bottles, primarily PET (Shotyk et al., 2006; Shotyk and Krachler, 2007; Andra et al., 2012). Storage of PET bottles for three months at room temperature resulted in considerable Sb leaching, reaching average concentrations of 630 ng L1 from 360 ng L1 at time zero analysis (Shotyk et al., 2006). Keresztes et al. (2009) reported similar storage effect on Sb leaching from non-carbonated PET bottles from 100 ng L1 (after 10 days) increased to 950 ng L1 after 950 days at room temperature. Increasing both storage time and temperature resulted in considerable increase in leached Sb concentrations
from PET bottles (Keresztes et al., 2009). In specific, storage at 60 C for 72 h resulted in Sb leaching of up to 2000 ng L1 (Keresztes et al., 2009). Interestingly, a specific PET brand used by Westerhoff et al. (2008) leached >2400 ng Sb L1 at 45 C under UV exposure for 6 h, much higher than the Sb concentrations encountered by our PET bottles. Differences in the magnitude of Sb leaching could be ascribed to differences in purity of plastic material (recycled or not) and/or differences in the bottled water class, i.e., non-carbonated, or carbonated, or enriched with vitamin or color (Andra et al., 2012). Enriched bottled water along with carbonated bottled PET bottles leached significantly higher Sb concentrations than the typical non-carbonated bottled water (Andra et al., 2012). Frequency of reuse has never been tested before with respect to its influence on chemical leaching from drinkingwater plastic containers. Our study showed that frequency of reuse exerted greater influence on Sb and Br leaching from PET and PC containers when compared with that attributed to UV exposure duration and temperature. This finding comes in contrast with earlier work on plasticizer leaching from PET bottles subject to SODIS procedure that were reused, but they did not report significant increase in plasticizer leaching from
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Fig. 3 e Relationship between measured Sb and Br concentrations in bottled water from PET and PC bottles under the study conditions. ** and *** represents probability of Pearson’s correlation coefficient less than 0.01 and 0.001, respectively.
reused containers; the authors did not mention how many times containers were reused (Schmid et al., 2008). In certain countries e for example India, the big 19 L PC water containers are reused for about 6 to 12 months until they are deformed beyond visual acceptance and/or break beyond repair. During this period these bottles will undergo up to 100 cycles of refilling by bottling companies (personal communication, Ram Das, Sri Krishna Bottling Company, Delhi, India). Figure SI-1 depicts changes in physical appearance and condition of these bottled water containers that hints to an accelerated constituent leaching from plastic walls into contained water. Our new findings come handy with the recently proposed public health goal (PHG) of 0.7 mg Sb L1 in drinking-water by California’s Office for Environmental Health and Hazard Assessment (OEHHA, 2009). The proposed PHG underlines current attempts in revisiting Sb critical human health effects
in conjunction with increasing human exposure to Sbcontaining food and water packaging materials. In our study, water consumption of 3.08 L day1 person1 and an average body mass of 70 kg were used in calculating daily and cumulative Sb and Br intakes, per OEHHA suggestions (OEHHA, 2009). The cumulative average daily Sb intake due to leaching from PET and PC bottles that were reused for at least 27 times were 100 and 6.3 ng kg1 day1, respectively, (Fig. 4). Minimal Sb leaching from PC bottles occurred as a function of bottle reuse, possibly due to the magnitude of concentrations being close to the limit of quantification (1 ng L1). In specific, Sb leaching increased up to 13 cycles of PC bottle reuse (w8 ng L1) and remained almost unchanged thereafter, while Sb leaching from PET continued to increase even after 27 cycles of bottle reuse (w230 ng L1) (Fig. 4). Current regulatorybased tolerable daily intake (TDI) estimate for Sb is 6 mg kg1 body weight (WHO, 2003), which is much higher than our
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Fig. 4 e Antimony leaching and cumulative daily intake values as a function of bottle reuse. Circle data points refer to Sb cumulative daily intake (second y-axis). Each reuse number (x-axis) indicates one cycle of deionized-water filled bottle exposure to UV-A radiation for 1 h at 50 C, being equivalent to one SODIS cycle (SANDEC, 2002).
estimate of Sb daily intake under SODIS conditions (Fig. 4). Migrated Sb concentrations from PET and PC bottles did not pose a serious risk to human health per the existing MCL value of 6 mg Sb L1 in drinking water that corresponds to an acceptable daily dose of 1.1 mg kg1 day1 (OEHHA, 1997). This suggests that under our experimental conditions, leached Sb into bottled water despite repeated bottle reuse may not be a major human health consideration based on current MCL value of Sb for drinking-water. However, Sb MCL is currently under revision by regulatory agencies based on new findings, such as, recent in-vitro studies call for increased proliferation of breast cancer cells in the presence of metalloestrogens, like Sb (Choe et al., 2003). In addition, in-vitro rapid tests evaluating biologic activity of bottled water call for increased genotoxicity (Ceretti et al., 2010; Ubomba-Jaswa et al., 2010) and estrogenicity (Pinto and Reali, 2009; Wagner and Oehlmann, 2009, 2010). Contrasting results on the magnitude of estrogenic activity in bottled water (Wagner and Oehlmann, 2009, 2010; Pinto and Reali, 2009; Stanford et al., 2010) may be ascribed to differences in study design, PET material, raw water composition prior to bottling, or test sensitivity (Sax, 2010). Similarly, the cumulative average daily Br intake due to leaching from PET and PC bottles that were reused for at least 27 times were 4.3 and 7.8 mg kg1 day1, respectively (Fig. 5). Bromine leaching increased up to 22 cycles of both PET and PC bottle reuse (w7 and w10 ng L1, respectively) and remained almost unchanged thereafter (Fig. 5). Total soluble Br concentrations leaching to bottled water were not considered toxic, since Br is not considered a primary water contaminant. Toxicity associated with Br presence in drinking water containers is most likely ascribed to organo-brominated compounds such as PBDE or TBBPA, used as flame retardants in polymeric applications of PET and PC (Albemarle, 2011; CDS Analytical, 2010; Talsness et al., 2009). Assuming all of the migrated Br in the form of bromide, our measured Br intake estimates were below the acceptable daily Br intake value of 0.4 mg kg1 day1 (EMEA, 1997). No toxicological-based health
Table 2 e Predicted leaching responses of Sb and Br into bottled water using the central composite design under various scenarios relevant to SODIS treatment. Antimony and Br leaching prediction models were based on the central composite design. Limit of detection for Sb and Br were 0.5 ng LL1 and 0.1 mg LL1, respectively. A [ UV Exposure (h); B [ Temperature ( C); C [ Bottle Reuse (#). Criteria
Conditions
Response
UV Exposure (h)
Temperature ( C)
Bottle reuse (#)
PET_Sb (ng L1)
PC_Sb (ng L1)
PET_Br (mg L1)
PC_Br (mg L1)
0 6 6 12
20 30 30 47
0 0 20 27
temperature. This study illustrated the importance of a so far unaccounted factor, i.e., frequency of bottle reuse in everyday activities that could enhance substantial leaching of plastic constituents into packaged water. Bottle reuse represents an everyday scenario for either household owner applying SODIS to reused PET bottles, or those consuming drinking water from reused PC large 19 L bottles supplied by bottling water companies. SODIS is a method typically used by developing countries, while drinking-water consumption from reused 19 L PC containers steadily gains popularity among both developed and developing countries. Our study illustrated the importance of a so far underestimated factor of deteriorating bottled water quality, e.g., that of frequency of bottle reuse, which in certain countries may reach as high as 100 times (personal communication, Ram Das, Sri Krishna Bottling Company, Delhi, India). Leaching of plastic constituents other than Sb and Br remains to be investigated for reused water containers. Cost-benefit analyses may soon be needed to tackle effectiveness of recycling plastic bottles in light of our findings calling for increased health risk associated with reused bottles. It is currently unknown whether frequent recycling of water packaging materials (smaller frequency of bottle reuse) as advocated by this study’s findings is supported by sustainability metrics of energy and economic aspects. Additional research is warranted on evaluating the effect of the three major tested conditions encountered during solar disinfection on other chemicals associated with the polymeric structure of the drinking water containers. It is warranted that further studies need to focus on organobrominated compounds instead of total soluble Br as a better indicator of neurotoxic and highly potent PBDE leaching into bottled water. Such chemicals under investigation are plasticizer compounds like phthalates, BPA, alkyl phenols and PBDE, i.e., decabromodiphenyl ether congener 209 (Andra et al., 2012) that are currently under investigation in our laboratory.
Conclusions
Solar disinfection of microbial-contaminated water in plastic containers at the household level represents a cost-effective intervention measure in reducing total social cost associated with mortality and morbidity burden of water-borne disease in developing countries. Concerns related to chemical leaching from plastic containers subject to solar disinfection were not validated, based on our Sb and Br leaching data. Antimony leaching in water was primarily enhanced with extending frequency of reuse, but not to levels posing serious public
Funding Partial support for this work was provided by the HarvardCyprus program.
Competing interests None declared.
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Acknowledgments \We would like to thank Mr. Nicola Lupoli, Drs. Innocent Jayawardene and Chitra Amarasiriwardena at the Trace Metals Laboratory, Harvard School of Public Health for providing assistance and guidance with the ICP-MS.
Appendix. Supplementary data Supplementary data related to this article can be found online at doi:10.1016/j.watres.2011.10.001.
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Sulfur transformations in pilot-scale constructed wetland treating high sulfate-containing contaminated groundwater: A stable isotope assessment Shubiao Wu a, Christina Jeschke b, Renjie Dong c,*, Heidrun Paschke d, Peter Kuschk e, Kay Kno¨ller b a
Key Laboratory of Agricultural Engineering in Structure and Environment of Ministry of Agricultural, College of Water Conservancy & Civil Engineering, China Agricultural University, 100083 Beijing, PR China b Department of Catchment Hydrology, Helmholtz Centre for Environmental Research - UFZ, Theodor-Lieser-Strasse 4, Halle D-06120, Germany c College of Engineering, China Agricultural University, 100083 Beijing, PR China d Department of Groundwater Remediation, Helmholtz Centre for Environmental Research - UFZ, Permoserstrasse 15, Leipzig D-04318, Germany e Department of Environmental Biotechnology, Helmholtz Centre for Environmental Research - UFZ, Permoserstrasse 15, Leipzig D-04318, Germany
article info
abstract
Article history:
Current understanding of the dynamics of sulfur compounds inside constructed wetlands is
Received 17 June 2011
still insufficient to allow a full description of processes involved in sulfur cycling. Experiments
Received in revised form
in a pilot-scale horizontal subsurface flow constructed wetland treating high sulfate-
30 September 2011
containing contaminated groundwater were carried out. Application of stable isotope
Accepted 7 October 2011
approach combined with hydro-chemical investigations was performed to evaluate the sulfur
Available online 19 October 2011
transformations. In general, under inflow concentration of about 283 mg/L sulfate sulfur, sulfate removal was found to be about 21% with a specific removal rate of 1.75 g/m2$d. The
Keywords:
presence of sulfide and elemental sulfur in pore water about 17.3 mg/L and 8.5 mg/L, respec-
Constructed wetland
tively, indicated simultaneously bacterial sulfate reduction and re-oxidation. 70% of the
Bacterial sulfate reduction
removed sulfate was calculated to be immobilized inside the wetland bed. The significant
Sulfide re-oxidation
enrichment of 34S and 18O in dissolved sulfate (d34S up to 16&, compared to average of 5.9& in
Stable isotopes
the inflow, and d18O up to 13&, compared to average of 6.9& in the inflow) was observed clearly correlated to the decrease of sulfate loads along the flow path through experimental wetland bed. This enrichment also demonstrated the occurrence of bacterial sulfate reduction as well as demonstrated by the presence of sulfide in the pore water. Moreover, the integral approach shows that bacterial sulfate reduction is not the sole process controlling the isotopic composition of dissolved sulfate in the pore water. The calculated apparent enrichment factor (3 ¼ 22&) for sulfur isotopes from the d34S vs. sulfate mass loss was significantly smaller than required to produce the observed difference in d34S between sulfate and sulfide. It indicated some potential processes superimposing bacterial sulfate reduction, such as direct reoxidation of sulfide to sulfate by oxygen released from plant roots and/or bacterial disproportionation of elemental sulfur. Furthermore, 41% of residual sulfate was calculated to be
* Corresponding author. Tel.: þ86 10 62737852; fax: þ86 10 62737885. E-mail address:
[email protected] (S. Wu). 0043-1354/$ e see front matter ª 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2011.10.008
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from sulfide re-oxidation, which demonstrated that the application of stable isotope approach combined with the common hydro-chemical investigations is not only necessary for a general qualitative evaluation of sulfur transformations in constructed wetlands, but also leads to a quantitative description of intermediate processes. ª 2011 Elsevier Ltd. All rights reserved.
1.
Introduction
Since the 1980s, constructed wetlands as an alternative ecological technology for wastewater treatment have been increasingly used for remediation of various contaminated waters (Bulc, 2006; Braeckevelt et al., 2008; Garcia et al., 2010). However, despite the successful application, the knowledge of the removal processes inside the systems is still insufficient, because of the variability of the redox states in the near-root zones and the complex interactions of different microbial transformations (Faulwetter et al., 2009). In the wetland bed, the spatial and temporal micro-scale gradients of oxygen concentrations and redox states established close to root surfaces enable the development of microbial biofilms of functionally different microorganisms. Those microorganisms can simultaneously mediate processes such as nitrification, denitrification, mineralization of organic carbon, methanogenesis, sulfate reduction, and sulfide oxidation on a small spatial scale (Lee et al., 1999; Holmer and Storkholm, 2001). As sulfate is a common constituent of wastewaters, different processes of sulfur cycling, depending on the availability of organic carbon and/or oxygen, are accordingly prevalent in constructed wetlands (Sturman et al., 2008; Wiessner et al., 2010). The wetland system can influence the sulfur cycling by e.g. releasing organic carbon compounds and/or oxygen from the plant roots to enhance the sulfate reduction or re-oxidation of the reduced sulfur compounds. Moreover, the processes of sulfur transformations, such as sulfate reduction can also influence the conditions for the biochemical processes, changing the pH and redox conditions (Leon et al., 2002; Geurts et al., 2009). In addition, the nitrogen removal and other removal processes under sulfur cycling can be influenced as well due to the toxicity of the reduced sulfur compounds like H2S, as well as competition for oxygen (Aesoy et al., 1998; Stein et al., 2007). Previous studies of sulfur transformations focus mainly on the removal of metals by precipitation with sulfide in constructed wetlands, particularly in treating acid mine drainage (Webb et al., 1998; Machemer et al., 1993; Woulds and Ngwenya, 2004), and some focus on negative effects caused by sulfide toxicity on wetland plants and microorganisms (Aesoy et al., 1998; Wiessner et al., 2010; Armstrong et al., 1996). However, the knowledge of evaluation on the dynamics of sulfur cycling in the constructed wetlands, particularly the quantitative description of intermediate turnover is still limited (Choi et al., 2006; Faulwetter et al., 2009). Moreover, the quantification of microbial sulfur transformations by concentration pattern of reactant (SO2 4 ) consumption or product formation (S2) in aquifers may be obscured by concurrent abiotic transformations, e.g. dilution due to the rainfall, concentration resulted from high
evapotranspiration, matrix effects, and mineral precipitation such as precipitation of gypsum and sulfide with metals (Anderson and Lovley, 2000; Schroth et al., 2001; Kno¨ller et al., 2006; Rahman et al., 2008). Furthermore, the coexisting of biotic processes, such as bacterial dissimilatory sulfate reduction and sulfide re-oxidation as well as disproportionation of different reduced sulfur compounds under specific micro gradients, also makes the understanding of different turnover processes of sulfur species inside the constructed wetlands be insufficient (Finster et al., 1998; Liesack et al., 2000). As a tool to discern microbial activity from abiotic transformations and assess pathways and rates of sulfur transformations, stable isotope analyses have been found increasingly applied in recent years (Schroth et al., 2001; Kno¨ller et al., 2004, 2008). Microbial sulfate reduction usually results in significant isotope enrichment of 34S in residual sulfate coupled to a depletion of 34S in produced sulfide (Rees, 1973; Fry et al., 1988; Bottrell et al., 1995). Sulfur isotope fractionation appears to be a valuable indicator for microbial sulfate reduction in complex environments. Thus, sulfur isotope fractionation in groundwater was previously observed in forest hydrological studies (Robertson and Schiff, 1994; Alewell and Giesemann, 1996) as well as in contaminated aquifers (Kno¨ller et al., 2006, 2008). Presently, little is know about sulfur isotope fractionation in constructed wetlands with complex coexisting reductive and oxidative conditions. In this study, evaluation of application of stable isotope investigation combined with common hydro-chemical examination in pilot-scale constructed wetland treating high sulfate-containing contaminated groundwater was conducted for: 1) the identification of microbial sulfate reduction; 2) recognition of further bacterial sulfur transformations superimposing sulfate reduction, such as disproportionation of reduced sulfur compounds and re-oxidation of sulfide; 3) the impact of wetland plants on sulfur cycling which was facilitated by the oxygen and organic carbon compounds released from plant roots; 4) quantitative assessment of reoxidation of sulfide to sulfate.
2.
Materials and methods
2.1.
Site description and experimental setup
The experimental pilot-scale constructed wetland was built at the SAFIRA research site in Bitterfeld, Germany in 2003 (Braeckevelt et al., 2008). The local groundwater used for loading this system during this experiment contained monochlorobenzene (MCB) as the main organic compound with concentration of 6e12 mg/L and sulfate (710e920 mg/L) as the
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main inorganic compound. The constructed wetland was designed to operate in a horizontal subsurface flow mode with dimension of 6 m length 1 m width and was filled to an average depth of 0.5 m with autochthonous quaternary aquifer material consisting predominantly of about 25% mica sand and about 67% gravel (porosity 0.35). The wetland bed was planted with common reed (Phragmites australis). The loading contaminated groundwater from a well installed in 22 m depth was pumped up and supplied continuously at a flow rate of 5.0 L/h to the wetland bed. The water level was maintained at approximate 0.1 m below the surface of the wetland. The samples took from 4 m (distance from inlet) were defined as effluent and the theoretical hydraulic retention time in the wetland bed was about 6 days. The outflow volumes were measured by a flow meter in order to determine water loss and allow the calculation of load removal. The system had been run with the same groundwater for 7 years before the current investigation was carried out from March to November in 2010.
2.2.
Sampling
Pore water samples for the evaluation of hydro-chemical parameters were taken from the wetlands at 0.5, 1, 2, 3 and 4 m distance from the inflow at 0.3, 0.4 and 0.5 m depth of the bed. Inflow samples were taken from the feeding pipe. The 18 2 isotope fractionation samples for d34SeSO2 4 , d OeSO4 were added 5% Zn-Acetate solution to removal the interference of sulfide. The samples for d34S in sulfide were only taken from 0.5 m depth of the bed and precipitated with 5% Zn-Acetate solution. Water sampling at each depth was carried out using stainless steel lancets (3.5 mm inner diameter) and peristaltic pumps at a rate of 78 ml/min. Water samples were stored without headspace at 4 C until analysis.
2.3.
Physical-chemical analysis
The redox potential was determined in the field using a SenTix ORP electrode (WTW, Weilheim, Germany) and the temperature was measured with a temperature sensor (PT 1000, PreSens, Regensburg, Germany). Sample filtration was carried out using a 5 mm-syringe filter (Ministart NML, Sartorius) for particles removal before the quantitative ions analysis. The pH value was measured by a SenTix41 electrode with pH 537 Microprocessor (WTW, Weilheim, Germany). For the conservation of Fe(II) samples, hydrochloric acid was added and after derivatisation with ferrocin, photometric measurement was carried out at 562 nm using a Cadas 100 photometer (Hach Lange, Dusseldorf, Germany) (Lovley and Phillips, 1986). Sulfate concentrations were determined by ion chromatography (DX 500) with an IonPacAG11 (4 250 mm) column (Dionex Corporation, Sunnyvale, USA) and conductivity detection (CD 20). Sulfide concentrations were measured by photometric method using Test kit LCW053 from HACH LANGE, Germany. Elemental sulfur in the pore water was estimated according to Rechmeier et al. (Rethmeier et al., 1997), by extracting samples with chloroform and subsequent detection by HPLC (Beckman, USA) using a Li-Chrospher 100, RP 18 column (5 mm, Merck, Germany) equipped with a UV-detector at 263 nm.
2.4.
Isotope analysis
Sulfur isotope analysis was conducted according to Kno¨ller and Schubert (2010). The precipitated ZnS was removed by filtration (0.45 mm). After adding concentrated hydrochloric acid in the laboratory, the hydrogen sulfide was stripped with N2 gas and then trapped as ZnS in Zn-acetate solution. The precipitated ZnS was subsequently converted to Ag2S by addition of 0.1 M AgNO3 solution. Dissolved sulfate was recovered by precipitation as BaSO4 at 70 C after the pH of the solution was adjusted to 3.0 and BaCl2 solution was added. Sulfur isotopic compositions were measured after conversion of BaSO4 (or Ag2S) to SO2 using an elemental analyzer (continuous flow flash combustion technique) coupled with an isotope ratio mass spectrometer (delta S, ThermoFinnigan, Bremen, Germany). Sulfur isotope measurements were performed with an analytical error of better than 0.3& and results are reported in delta notation (d34S) as part per thousand (&) deviations relative to the Vienna Can˜on Diablo Troilite (VCDT) standard (according to general Eq. (1)) dð&Þ ¼
Rsample Rstandard
Rstandard 1000
(1) 34
32
where R is the ratio of the heavy to light isotopes (e.g. S/ S or 18O/16O). Oxygen isotope analysis with barium sulfate samples was carried out by high temperature pyrolysis at 1450 C in a TC/EA connected to a delta plus XL mass spectrometer (ThermoFinnigan, Bremen, Germany) with an analytical error of better than 0.5&. According to Eq. (1), results of oxygen isotope measurements are expressed in delta notation (d18O) as part per thousand (&) deviations relative to Vienna Standard Mean Ocean Water (VSMOW). For normalizing the d34S data, the IAEA-distributed reference materials NBS 127 (BaSO4) and IAEA-S1 (Ag2S) were used. The assigned values were þ20.3& (VCDT) for NBS 127 and 0.3& (VCDT) for IAEA-S1. The normalization of oxygen isotope data of sulfate was carried out using the reference material NBS 127 with an assigned d18O value of þ8.7& (VSMOW).
2.5.
Calculation
Water loss generally occurs in constructed wetlands via evaporation from the filter surface and transpiration by plants, which is combined to be called evapotranspiration. The area specific water loss (ΔV) during a defined period is calculated by measuring the influent and effluent streams as well as rainfall, DV ¼ fðVin þ Prain A Vout Þ=Vin g 100
(2)
where ΔV is the water loss by evapotranspiration in %, Vin and Vout are the influent and effluent volumes in L/d, and Prain is the precipitation, which was measured by a weather station near the SAFIRA site and its amount was related to specific area in L/m2d. For the evaluation of treatment performance of constructed wetlands, the consideration of water loss and load calculation is necessary. The following assumptions were made: 1) Evapotranspiration along the wetland flow path increases in a linear way
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2) An simplified ideal plug flow though the soil filter exists. Therefore, the load of the contaminants in the defined sampling points can be expressed as Eq. (3) and the residual fraction of the contaminants through the bed (e.g. 4 m sampling point) was defined as Eq. (4). Load4m ¼ ðVin þ Prain A4m DV4m Vin Þ C4m
(3)
Residual fraction ð%Þ ¼ fðVin þ Prain A4m DV4m Vin Þ C4m g=Vin Cin
(4)
where Cin is the influent concentration in mg/L, C4m is the concentration at 4 m sampling point in mg/L, and A4m is the area from the inflow to the sampling point ¼ 4 m2.
3.
Results
Concentrations of sulfate, sulfide and elemental sulfur in the pore water of experimental constructed wetland along flow path from inlet to outlet are presented in Table 1. The sulfide and elemental sulfur depending on the distance from inlet to outlet gradually increased to 18.5 mg/L and 8.2 mg/L, respectively. However, the concentrations of sulfate-sulfur varied from 266 mg/L to 293 mg/L through the wetland and did not show any decreasing tendency. The clearly production of sulfide and elemental sulfur was not proved by the decrease of sulfate concentrations along the flow path, which was attributed to the concentrating effect of considerable water losses occurring via evapotranspiration. As shown in Fig. 1, the monthly average water loss calculated from inflow and outflow streams varied from 55% to 1%, correlating to the changes of temperature from 25 C to 8 C during sampling months. The loss of water from the wetland was mainly (about 92%) conducted by the plants transpiration.
Concerning the considerable water losses from wetland, the concentrations can not really reflect the microbial sulfur transformations here. Thus, according to Eqs. (2) and (3) the daily loads along the flow path from inlet to outlet were calculated and used to interpret the sulfur dynamics through the wetland. As shown in Fig. 2, with gradual increase of sulfide and elemental sulfur in the pore water through the wetland, sulfate-sulfur decreased correspondingly from 34 g/ d to 27 g/d, indicating the calculation of load with consideration of water loss fits the case study in the field. The reduction of sulfate was generally achieved 21% with a specific area removal rate of 1.75 g/m2$d. The compositions of isotopic sulfur and oxygen of sulfate and sulfide along the flow path from inlet to outlet were shown in Table 2 and Fig. 3. In general, d34S of sulfate and sulfide and d18O of sulfate increased from inlet with values of þ5.7&, 33.2& and þ6.7& to outlet with values of þ16&, 25& and þ13&, respectively. Significant enrichment of heavy isotopes in this experiment was observed. The pH measured in all sampling points was within the range of 6.5e6.9. Redox potential gradually decreased from about 50 mV in the inflow to 120 mV in the outflow (4 m sampling point). Ferrous iron from the pore water through the whole bed was constant around 0.5 mg/L.
4.
Discussion
Sulfide is a product of bacterial dissimilatory sulfate reduction (BSR) by using organic compounds as electron donors. Elemental sulfur is a product of sulfide oxidation, which may be performed by abiotic oxidation and/or biological oxidation by using different electron acceptors, such as oxygen, nitrite and nitrate (Buisman et al., 1990; Mahmood et al., 2009; Zheng, 2007; Zheng and Cai, 2007). In this study, the coexisting of sulfide and elemental sulfur in the pore water of experimental
Table 1 e Sulfur species concentrations of the soil pore water of experimental pilot-scale constructed wetland along flow path from inlet to outlet (in mg/L, n [ 15). Flow path (m)
0 (inflow) 0.5
1
2
3
4 (outflow)
SO2 4 S
Depth (m)
0.3 0.4 0.5 0.3 0.4 0.5 0.3 0.4 0.5 0.3 0.4 0.5 0.3 0.4 0.5
S2
S0
Mean
STDEV
Mean
STDEV
Mean
STDEV
283.1 281.5 282.0 282.7 280.5 284.6 292.7 261.2 270.5 269.2 288.4 285.2 263.9 266.0 257.9 288.1
12.1 12.1 10.4 12.4 11.7 11.1 15.3 19.8 16.9 18.5 15.8 18.3 18.5 17.2 24.1 14.8
B.D.L 2.2 1.1 1.1 3.2 2.9 1.8 14.2 10.3 8.4 15.5 15.8 18.5 14.1 14.6 17.9
B.D.L 0.9 0.6 0.8 2.8 2.8 1.7 5.1 2.5 3.6 7.1 3.6 4.9 4.6 3.1 6.2
B.D.L 1.3 1.3 0.4 1.6 0.8 0.4 7.2 4.3 4.1 6.7 6.9 8.2 6.1 6.5 6.8
B.D.L 0.8 1.0 0.3 1.4 0.6 0.3 1.7 1.4 1.7 2.6 3.8 3.7 2.7 5.1 2.4
B.D.L means the estimated concentration below detection limit. The detection limit for sulfide and elemental sulfur is 0.1 mg/L.
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90
35
80
30
Temperature (°C)
60
20
50
15
40 30
10
W ater loss (%)
70 25
20 5 0 07/2010
10
08/2010
09/2010
10/2010
11/2010
0 12/2010
Date (month / year) Daily average temperature Monthly average temperature Monthly water loss
into the rhizosphere, the spatial and temporal micro-scale gradients of oxygen concentrations and redox states are consequently established close to root surfaces (Colmer, 2003; Bezbaruah and Zhang, 2004). The coexisting reductive and oxidative conditions in the root-near zones could enable microbial processes such as mineralization of organic carbon, sulfate reduction and sulfide re-oxidation realized on a small spatial scale simultaneously (Holmer and Storkholm, 2001). In concert with decreasing sulfate-sulfur load from inlet to outlet presented in Fig. 3, the significant enriched 34S of sulfate values along flow path (Fig. 4) are strong evidence for the occurrence of BSR. Generally, under closed system conditions, 34 the relationship between SO2 4 concentrations and d S values is expressed by a Rayleigh Eq. (5) where 3 is the respective enrichment factor for sulfur and f stands for the fraction of 2 residual sulfate expressed as CeSO2 4 /C0eSO4 . d34 S ¼ d34 SSO42initial þ εlnðfÞ
Fig. 1 e The dynamics of temperature and water loss in the experimental constructed wetland. The down arrows show the isotope sampling campaigns. Box plot shows median (central thick lines), 25% and 75% quartile ranges around the median, upper and lower edge (hinge) of the box. The ends of the vertical lines (whiskers) indicate the minimum and maximum data values.
Since considerable water loss via plant transpiration occurred in this study, the concentrations of sulfate measured in the pore water can really not reflect the BSR. Thus, the 2 parameter of f in Eq. (5) expressed as CeSO2 4 /C0eSO4 can also not fit here. Accordingly, the load of sulfate calculated as a result of combined concentration and water loss was used in this study and the modified f in Eq. (5) was expressed as L2 SO2 4 /L0-SO4 . Besides, the application of Eq. (5) on field data often only yields an apparent enrichment factor 3 , because closed system conditions are rarely achieved under aquifer conditions (Kno¨ller et al., 2006). For the investigation in this
40
4
35
3
S (g/d)
30
2-
SO42--S (g/d)
wetland (Table 1 and Fig. 2) indicates the simultaneous reduction and re-oxidation of sulfur compounds. Regarding the oxygen and organic compounds released from the roots
(5)
2
25
1
20 2.0
0 0
1
2
3
4
Distance from inlet (m)
S0 (g/d)
1.5
1.0
0.5
0.0 0
1
2
3
4
Distance from inlet (m)
Fig. 2 e The load dynamics of sulfate-sulfur, sulfide and elemental sulfur along flow path in the experimental constructed wetland from inflow to outflow. The meaning of box plot was described in Fig. 2.
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Table 2 e Isotope fractionation data for investigated sampling points of experimental pilot-scale constructed wetland along flow path from inlet to outlet (in &). Flow path (m) 0 (inflow) 0.5
1
2
3
4 (outflow)
Depth (m)
Sampling campaign in August SeSO2 4
34
d
d
5.8 6.7 6.0 5.9 6.5 6.2 6.3 12.0 9.8 9.3 13.0 13.6 13.2 16.6 16.3 14.3
0.3 0.4 0.5 0.3 0.4 0.5 0.3 0.4 0.5 0.3 0.4 0.5 0.3 0.4 0.5
OeSO2 4
18
7.0 7.9 7.7 7.9 8.0 7.6 7.3 11.2 9.6 8.3 11.4 10.2 11.4 12.8 12.4 11.2
33.2
28.7
28.4
24.9
13
‰ (VSMOW )
16
Delta- O-SO4
10 8
18
34
2-
2-
‰ (VCDT)
14
12
6 4 -24
d18OeSO2 4
6.0 7.0 6.2 5.7 6.4 6.0 6.3 8.0 7.6 7.1 9.4 9.9 10.2 11.8 12.4 13.0
6.7 7.8 7.4 7.0 7.6 7.7 7.4 9.7 10.1 9.0 12.0 11.4 9.6 12.1 11.6 10.3
d34S-HS
31.0
32.0
28.3
Besides the enrichment of heavy sulfur isotope in the residual sulfate during BSR, the fractionation of oxygen isotopes in the residual sulfate molecule was also carried out. Even though the breaking of the SeO bondage will result in a kinetic isotopic effect as observed for sulfur, the kinetic isotopic effect of oxygen is masked by an isotope exchange between oxygen in sulfate and oxygen in ambient water in natural environments (Kno¨ller and Schubert, 2010). The enrichment of heavy oxygen
18
14
d SeSO2 4 34
d S-HS
study, the apparent isotopic enrichment factor (3 ) for 34S was 22&, which obtained by fitting the logarithmic Eq. (5) to the measured data (Fig. 4). The convincing logarithmic relationship shown in Fig. 4 as well as the high value of correlation coefficient (R2) suggest that BSR could be the main process determining the distribution and isotope composition of sulfate at the site, as compared to the processes like adsorption and/or desorption.
Delta- S-SO4
Sampling campaign in October
34
12 11 10 9 8 7 6 0
1
2
3
4
-28
34
Delta- S-S
2-
‰ (VCDT)
Distance from inlet (m) -26
-30
-32
-34 0
1
2
3
4
Distance from inlet (m)
Fig. 3 e The dynamics of isotopic compositions of d34S and d18O in sulfate and d34S in sulfide of pore water along flow path in the experimental constructed wetland from inflow to outflow.
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8 15 6
y= -21.9 * ln(x) + 5.7 R2=0.86
10
4
2
5
0 1.0
0.9
0.8
0.7
0.6
0.5
Fraction residual sulfate (L/L0) 18
O-sulfate S-sulfate Logarithmic fitting of 34S-sulfate 34
Fig. 4 e The correlation of isotopic compositions of d34S and d18O in sulfate and fraction residual sulfate which expressed as fraction of the residual sulfate load to the initial inflow sulfate load.
in residual sulfate via isotope exchange usually was reached up to a certain equilibrium value. This equilibrium takes place within the sulfate reducing bacteria via intermediate intracellular sulfur compounds formed during BSR that are subject to re-oxidation (Brunner et al., 2005; Kno¨ller et al., 2006; Mangalo et al., 2007; Turchyn et al., 2010). As shown in Figs. 3 and 4, the significant enrichment of oxygen in the residual sulfate may again imply that the reduction of sulfate in constructed wetlands is exclusively due to BSR. As a product of BSR, sulfide is generally present in the pore water of the constructed wetlands. However, if reactive metals (e.g. iron) are also present in the aquifer, a considerable part of the sulfide may immediately be precipitated as metal sulfide and then immobilized in the wetland matrix. The isotopic evolution of the sulfide pool is depending on the isotopic composition of the precursor sulfate, enrichment factor (3 ) and the fraction of sulfide which is removed from the dissolved pool by precipitation with metals (Kno¨ller and Schubert, 2010). In closed systems, the estimation of isotopic composition of sulfide pool could be obtained by two different derivations according to Rayleigh Eq. (5). If the sulfide is precipitated under conditions with sufficient metals, the approximate d34S values of the immediate produced sulfide (d34Ssulfide-Instanous-t) can be calculated from Eq. (6). If in case of accumulation of sulfide in the pore water reservoir without any precipitation with metals, the isotopic composition of sulfide at a certain stage of BSR can be obtained according to Eq. (7). d34 SsulfideInstanoust ¼ d34 Ssulfatet þ ε
(6)
d34 Ssulfidereservoirt ¼ d34 Ssulfateinitial f$ε$lnf=ð1 fÞ
(7)
12
y= x
10
0
10
8
2-
20
Delta-18O-SO42- ‰ (VSMOW )
2-
Delta-34S-SO4 ‰ (VCDT)
12
The correlation between assumed bacterial sulfate consumption and the sum of existing reduced sulfur compounds such as sulfide and elemental sulfur are shown in Fig. 5. The sum of estimated sulfide and elemental sulfur in the pore water from bacterial sulfate consumption was lower than the expected product reservoir accumulation. In general, the measured reduced sulfur only takes 30% of the decreased sulfate in this experimental wetland bed and 70% was immobilized in the wetland matrix such as precipitation of sulpide with metals and elemental sulfur. In addition, as well as immobilization in the matrix, formation of dissolved organic sulfur compounds and plant uptake could also account for some of the lost sulfur as shown by the few studies that have examined these in peatlands (Steinmann and Shotyk, 1997; Bottrell et al., 2010; Bartlett et al., 2009). Unfortunately, the data on sulfur species in the substrate of wetland was not available in this study and should be further investigated. Considering the presence of sulfide measured in the pore water (Table 1 and Fig. 2) and considerable immobilization of sulfur compounds (Fig. 5), the d34S values of dissolved sulfide should be plotted within a theoretical range defined by Eqs. (6) and (7). As shown in Fig. 6, this range is enclosed by the two curves modeled from Eqs. (6) and (7). However, surprisingly, no sulfide samples were plotted within the expected isotopic range and all samples were quite below this range in this study. This finding indicated that the enrichment factor for sulfur isotopes calculated from the d34S vs. sulfate mass loss is significantly smaller than required to produce the observed large difference in d34S between sulfate and sulfide. Also, this
Sum of dissolved S and S (g/d)
14
25
6
70%
4
y= 0.3 x (R2= 0.53)
2
30% 0 0
2
4
6
8
10
12
Sulfate reduction (g/d)
Fig. 5 e Correlation between assumed bacterial sulfate reduction and sum of estimated sulfide and elemental sulfur in the pore water of constructed wetland. The straight dashed line illustrates the theoretical correlation for a complete accumulation of reduced sulfur reservoir. The straight line stands for the regression of measured sum of sulfide and elemental sulfur in the pore water. Regarding the slopes of the two lines, 30% of the reduced sulfate was expressed as dissolved sulfide and elemental sulfur, indicating 70% of the reduced sulfate was deposited in the wetland matrix such as precipitation of sulfide with metals and elemental sulfur.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 6 8 8 e6 6 9 8
suggested one or more sulfur transformation processes superimposing on BSR, such as bacterial disproportionation of elemental sulfur (Bo¨ttcher et al., 2001; Holmkvist et al., 2011) and direct oxidation of sulfide to sulfate by elemental oxygen which was introduced by plant roots. In constructed wetlands, the release of oxygen from plant roots into rhizosphere was well reported (Armstrong et al., 1990). The re-oxidation of sulfide to elemental sulfur using oxygen as electron acceptor is accordingly quiet reasonable here. Besides, nitrite and nitrate as a product of ammonium oxidation can also easily stimulate sulfide oxidation to elemental sulfur in wetlands (Krishnakumar and Manilal, 1999; Londry and Suflita, 1999). The process associated with sulfide re-oxidation to elemental sulfur only provides a minor isotope effect and the isotopic composition of sulfide pool would not change significantly (Bo¨ttcher et al., 1990; Balci et al., 2007). However, if elemental sulfur undergoes microbial disproportionation into sulfate and sulfide (Eq. (8)), considerable sulfur isotope fractionation and significant isotopic difference between sulfate and sulfide can be easily reached. þ 4H2 O þ 4S0 /3H2 S þ SO2 4 þ 2H
(8)
The microbial disproportionation of elemental sulfur produces more enriched sulfate and more depleted sulfide. 20 15
y= -21.9 * ln(x) + 5.7 R2=0.86
34
2-
Delta- S-SO4 ‰ (VCDT)
10 5 0 -5 -10 -15 -20 -25 -30 -35 1.0
0.9
0.8
0.7
0.6
0.5
Fraction residual sulfate (L/L0) Sulfate Sulfide Calculated sulfide instantaneous Calculated sulfide product reservoir Fitting sulfate
Fig. 6 e Relationship between the fraction of the residual sulfate and the measured sulfur isotopic composition of d34S in dissolved sulfate and sulfide. The curves represent the calculated isotopic evolution of the sulfate pool (Eq. (5)), of the instantaneously produced sulfide (Eq. (6)), and of the sulfide pool in case of an accumulation of a product reservoir (Eq. (7)) during progressing bacterial sulfate reduction under closed system conditions. For the calculation, the field based apparent isotopic enrichment factor of L21.9& was used.
6695
When the new produced sulfate mixed with the precursor sulfate, the isotopic pool of 34S will be slightly enriched. In like manner, the new sulfide pool is isotopically lighter than the precursor pool (Bo¨ttcher et al., 2001). Consequently, the isotopic difference between sulfate and sulfide will increase, as compared to the difference as a result of BSR only. Moreover, if the newly formed sulfide is oxidized again to S0, its disproportionation will further increase the isotopic difference. In this case with periodical re-oxidation of sulfide and disproportionation of elemental sulfur, the isotopic difference between coexisting sulfate and sulfide would be significantly enlarged. So far, no direct evidence for the occurrence of bacterial sulfur disproportionation has been provided in constructed wetlands. A stable isotope fractionation during formation of sulfate via this disproportionation process was experimentally investigated in a pure culture. It was found that the dissolved sulfate was enriched in 18O by 17.4& (Bo¨ttcher et al., 2001). Compared to this, the smaller enrichment of 18O in dissolved sulfate (6&) in this study demonstrated the potential occurrence of disproportionation of reduced sulfur compounds in CWs. In addition to the microbial disproportionation, direct reoxidation of sulfide to sulfate by elemental oxygen released from wetland plant roots, may also be a possible explanation for the unexpected enlarged isotopic differences between the coexisting sulfate and sulfide. Considering the hypothesis of significant direct re-oxidation of sulfide to sulfate, the enrichment factor (3 ) obtained by fitting the logarithmic analysis of measured sulfate isotope data can be underestimated to reflect the real enrichment factor. The isotopic composition of sulfate pool can be depleted when new formed sulfate from reoxidation of sulfide with a more depleted sulfate isotopic composition mixed with the precursor sulfate. Compared to the sulfur isotope fractionation during BSR only, the sulfide pool does not significantly change its isotopic composition during re-oxidation of sulfide to sulfate. Consequently, if considerable re-oxidation of sulfide to sulfate occurred, the enrichment factor obtained by fitting the logarithmic analysis of measured sulfate isotope data should not be the real evaluation of BSR. According to Eq. (6) under the assumption that the produced sulfide from sulfate reduction was immediately precipitated in the matrix, the real enrichment factor obtained for pure BSR process can be presented as isotopic difference between coexisting sulfate and sulfide. Based on this case, the real isotope curves from process of BSR only in this study was modeled using the average isotopic difference (38.9&) between sulfate and sulfide as the enrichment factor (Fig. 7). In this way, the sulfide samples as shown in Fig. 7 were perfectly enclosed within the range which calculated from the modeled sulfide isotope fractionation curve. If one considers the hypothesis of re-oxidation as valid in this study, the fraction of newly produced sulfate from sulfide re-oxidation can be modeled according to Eq. (9). d34 Smixed ¼ d34 Sprecursor ð1 XÞ þ d34 Sproduced X
(9)
in which the X stands for the fraction of newly produced sulfate from oxidation of sulfide. Using liner regression analysis of the modeled real sulfate isotope (as precursor pool) and fitting sulfate by measured values (as mixed pool), the fraction
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of newly produced sulfate from oxidation of sulfide (X) was calculated as 41%. This fraction indicates that there was 41% of the measured sulfate resulted from sulfide re-oxidation. The mixture of 41% new produced sulfate with precursor sulfate made the enrichment factor of the whole sulfate pool decreased from 38.9& to 21.9&. Moreover, the reaction of sulfide oxidation to sulfate drived by oxidizing reactant like oxygen can be expressed as Eq. (10). Considering the fraction of 41% new produced sulfate, the oxygen equivalent consumption was calculated up to be 4.1 g/ m2d by using the minimum mean sulfate load of 27 g/d in 4 m from the inlet of the wetland with corresponding area of 4 m2 in this study. S2 þ 2O2 /SO2 4
(10)
Regarding the fine sand as the matrix used in the wetland and the horizontal saturated flow model, the oxygen diffusion from atmosphere into the wetland could be neglected in this
30
y= -38.9 * ln(x) + 5.7
25
Delta-34S-SO42- ‰ (VCDT)
20 15
y= -21.9 * ln(x) + 5.7 R2=0.86
10 5 0 -5 -10 -15
study. The oxygen supply here was mainly attributed to the plants. The oxygen flux from the roots of P. australis into their surroundings reported by Lawson (1985) and Armstrong et al. (1990) was up to be 4.3 g/m2$d and 5e12 g/m2$d, respectively. The calculated plant oxygen transfer capacity of 4.1 g/m2d using isotopic technology here was well agreed. This agreement strongly indicates the important role of plants in constructed wetlands and also indicates the potential application of isotope fractionation in constructed wetlands for deep understanding of the internal complex sulfur transformation processes. Besides the role of plants in constructed wetlands for the release of oxygen, the release of organic carbon as providing extra electron donors is as well important to influence the various microbial processes. The inflow sulfate load of the experimental wetland is about 34 g/d and outflow (4 m) sulfate is reduced to be approximate 27 g/d, yielding a net difference of 7 g/d. Regarding the 41% (11.6 g/d) of the outflow sulfate coming from the re-oxidation of sulfide, the net flux of bacterial sulfate reduction could be calculated up to be 18.6 g/ d with a specific area reduction rate of 4.65 g/m2d. The concentration of MCB as the main organic compound in the inflow water is around 0.3 g/m2d in this study. According to the reaction of MCB as electron donor coupled to the reduction of sulfate as electron acceptor expressed as Eq. (11) (Colberg, 1990), the reduction of 4.65 g/m2d sulfate needs 1.56 g/m2d consumption of MCB. The net difference of 1.26 gMCB/m2d from inflow supply and theoretical consumption strongly gives the indication of extra electron donors involved in the sulfate reduction process, underlining the role of organic compounds release from plant roots deriving sulfur cycling in constructed wetlands.
-20 -25
þ 2C6 H5 Cl þ 7SO2 4 þ 5H /12CO2 þ 7HS þ 2Cl þ 4H2 O
-30 -35 -40 1.0
0.9
0.8
0.7
0.6
0.5
Fraction residual sulfate (L/L0) Sulfide Sulfate Initial sulfate Fitting sulfate Calculated sulfide instantaneous Calculated sulfide product reservoir
Fig. 7 e Relationship between the fraction of the residual sulfate and the measured sulfur isotopic composition of d34S in dissolved sulfate and sulfide. The curves represent the calculated isotopic evolution of the initial sulfate pool which processing by BSR only, of the measured sulfate pool (Eq. (5)), of the instantaneously produced sulfide (Eq. (6)), and of the sulfide pool in case of an accumulation of a product reservoir (Eq. (7)) during progressing bacterial sulfate reduction under closed system conditions. For the calculation, the isotopic enrichment factor for the initial sulfate pool was modified to L38.9& according to the average isotopic difference between coexisting dissolved sulfate and sulfide.
(11)
In general, the effect of vegetation in constructed wetland was well reported (Brix, 1997; Chazarenc et al., 2009) and the role of plants improving the performance by releasing organic carbon compounds and/or oxygen from roots is also proved (Merbach et al., 1999; Picek et al., 2007). However, due to quite a biodegradation availability of the released organic carbons, the fast consumption by various microbes sitting around the roots surface makes the quantification of the released organic compounds into the wetland bed become extreme difficult. The consumption of some pollutants only under irreversible reaction using organic compounds as electron donor can be used to calculate the theoretical amount of organic carbon released from roots. However, as sulfate is undergoing microbial reversible reactions including sulfate reduction and re-oxidation of reduced sulfur compounds, the estimation of organic carbon consumption here is extremely difficult. In this study, a progressive step was made by using the approach of stable isotope combined with the common hydro-chemical parameters, and the capacity of organic carbon release from roots was calculated to 1.26 g/m2d MCB equivalent. But this value was derived by only considering the process of bacterial sulfate reduction. If considering the consumption of organic compounds by denitrification, methanogenesis and microbial respiration, the capacity of organic matter release from roots should be larger.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 6 8 8 e6 6 9 8
5.
Conclusion
The significant enrichment of heavy isotopes of sulfur and oxygen in dissolved sulfate was observed to be clearly correlated to the decrease of sulfate loads along the flow path through an experimental horizontal subsurface flow wetland bed. This strongly indicates the occurrence of bacterial dissimilatory sulfate reduction. - Lack of sulfur isotope mass balance between sulfate removed and sulfide produced implies that other processes are superimposed on bacterial sulfate reduction. These include re-oxidation of sulfide to sulfate by oxygen and bacterial disproportionation of elemental sulfur in constructed wetlands. - The application of the stable isotope approach combined with common hydro-chemical investigations enables a general qualitative evaluation of sulfur transformations in constructed wetlands, but also leads to a quantitative description of intermediate processes. -
Acknowledgement This work was supported by a grant of China Scholarship Council (CSC) and by the Helmholtz Centre for Environmental Research e UFZ within the scope of the SAFIRA II Research Program (Revitalization of Contaminated Land and Groundwater at Megasites, subproject ‘‘Compartment Transfer e CoTra”). We are grateful to Martina Neuber and Sandra Zuecker-Gerstner of the stable isotope laboratory Halle/Salle for conducting isotope analyses of the samples. Thanks are also addressed to the A. Al-Dahoodi and M. Schro¨te for their valuable assistance in the laboratory and field. Furthermore, we would like to thank Simon Botrell for his valuable comments that considerably helped improve the paper.
references
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Garcia, J., Rousseau, D.P.L., Morato, J., Lesage, E., Matamoros, V., Bayona, J.M., 2010. Contaminant removal processes in subsurface-flow constructed wetlands: a review. Critical Reviews in Environmental Science and Technology 40, 561e661. Geurts, J.J.M., Sarneel, J.M., Willers, B.J.C., Roelofs, J.G.M., Verhoeven, J.T.A., Lamers, L.P.M., 2009. Interacting effects of sulphate pollution, sulphide toxicity and eutrophication on vegetation development in fens: a mesocosm experiment. Environmental Pollution 157, 2072e2081. Holmer, M., Storkholm, P., 2001. Sulphate reduction and sulphur cycling in lake sediments: a review. Freshwater Biology 46, 431e451. Holmkvist, L., Ferdelman, T.G., Jørgensen, B.B., 2011. A cryptic sulfur cycle driven by iron in the methane zone of marine sediment (Aarhus Bay, Denmark). Geochimica et Cosmochimica Acta. Kno¨ller, K., Fauville, A., Mayer, B., Strauch, G., Friese, K., Veizer, J., 2004. Sulfur cycling in an acid mining lake and its vicinity in Lusatia, Germany. Chemical Geology 204, 303e323. Kno¨ller, K., Schubert, M., 2010. Interaction of dissolved and sedimentary sulfur compounds in contaminated aquifers. Chemical Geology, 284e293. Kno¨ller, K., Vogt, C., Feisthauer, S., Weise, S., Weiss, H., Richnow, H., 2008. Sulfur cycling and biodegradation in contaminated aquifers: insights from stable isotope investigations. Environmental Science & Technology 42, 7807e7812. Kno¨ller, K., Vogt, C., Richnow, H.-H., Weise, S.M., 2006. Sulfur and oxygen isotope fractionation during benzene, toluene, ethyl benzene, and xylene degradation by sulfate-reducing bacteria. Environmental Science & Technology 40, 3879e3885. Krishnakumar, B., Manilal, V., 1999. Bacterial oxidation of sulphide under denitrifying conditions. Biotechnology Letters 21, 437e440. Lawson, G., 1985. Cultivating Reeds (Phragmites Australis) for Root Zone Treatment of Sewage. Contract Report ITE Project 965. Water Research Centre, Cumbria, UK. Lee, R., Kraus, D., Doeller, J., 1999. Oxidation of sulfide by Spartina alterniflora roots. Limnology and Oceanography 44, 1155e1159. Leon, P.M.L., Falla, S.-J., Samborska, E.M., Dulken, I.A.R.v., Hengstum, G.v., Roelofs, J.G.M., 2002. Factors controlling the extent of eutrophication and toxicity in sulfate-polluted freshwater wetlands. Limnology and Oceanography 47, 585e593. Liesack, W., Schnell, S., Revsbech, N.P., 2000. Microbiology of flooded rice paddies. FEMS Microbiology Reviews 24, 625e645. Londry, K., Suflita, J., 1999. Use of nitrate to control sulfide generation by sulfate-reducing bacteria associated with oily waste. Journal of Industrial Microbiology and Biotechnology 22, 582e589. Lovley, D., Phillips, E., 1986. Organic matter mineralization with reduction of ferric iron in anaerobic sediments. Applied and Environmental Microbiology 51, 683. Machemer, S.D., Reynolds, J.S., Laudon, L.S., Wildeman, T.R., 1993. Balance of S in a constructed wetland built to treat acid mine drainage, Idaho Springs, Colorado, USA. Applied Geochemistry 8, 587e603. Mahmood, Q., Zheng, P., Hayat, Y., Ren-cun, J., Azim, M.R., Jilani, G., Islam, E., Ahmed, M., 2009. Effect of nitrite to sulphide ratios on the performance of anoxic sulphide oxidizing reactor. Arabian Journal for Science and Engineering 34, 45e54. Mangalo, M., Meckenstock, R.U., Stichler, W., Einsiedl, F., 2007. Stable isotope fractionation during bacterial sulfate reduction
is controlled by reoxidation of intermediates. Geochimica et Cosmochimica Acta 71, 4161e4171. Merbach, W., Mirus, E., Knof, G., Remus, R., Ruppel, S., Russow, R., Gransee, A., Schulze, J., 1999. Release of carbon and nitrogen compounds by plant roots and their possible ecological importance. Journal of Plant Nutrition and Soil Science 162, 373e383. Picek, T., Cizkova, H., Dusek, J., 2007. Greenhouse gas emissions from a constructed wetland-Plants as important sources of carbon. Ecological Engineering 31, 98e106. Rahman, K., Wiessner, A., Kuschk, P., Mattusch, J., Ka¨stner, M., Mu¨ller, R., 2008. Dynamics of arsenic species in laboratory-scale horizontal subsurface-flow constructed wetlands treating an artificial wastewater. Engineering in Life Sciences 8, 603e611. Rees, C., 1973. A steady-state model for sulphur isotope fractionation in bacterial reduction processes. Geochimica et Cosmochimica Acta 37, 1141e1162. Rethmeier, J., Rabenstein, A., Langer, M., Fischer, U., 1997. Detection of traces of oxidized and reduced sulfur compounds in small samples by combination of different highperformance liquid chromatography methods. Journal of Chromatography A 760, 295e302. Robertson, W., Schiff, S., 1994. Fractionation of sulphur isotopes during biogenic sulphate reduction below a sandy forested recharge area in south-central Canada. Journal of Hydrology 158, 123e134. Schroth, M.H., Kleikemper, J., Bolliger, C., Bernasconi, S.M., Zeyer, J., 2001. In situ assessment of microbial sulfate reduction in a petroleum-contaminated aquifer using pushpull tests and stable sulfur isotope analyses. Journal of Contaminant Hydrology 51, 179e195. Stein, O.R., Borden-Stewart, D.J., Hook, P.B., Jones, W.L., 2007. Seasonal influence on sulfate reduction and zinc sequestration in subsurface treatment wetlands. Water Research 41, 3440e3448. Steinmann, P., Shotyk, W., 1997. Chemical composition, pH and redox state of sulphur and iron in complete vertical profiles from two Sphagnum peat bogs, Jura mountains, Switzerland. Geochimica et Cosmochimica Acta 61, 1143e1163. Sturman, P., Stein, O., Vymazal, J., Kro¨pfelova´, L., 2008. Sulfur cycling in constructed wetlands. In: Vymazal, J. (Ed.), Wastewater Treatment, Plant Dynamics and Management in Constructed and Natural Wetlands. Springer, pp. 329e344. Turchyn, A.V., Bruchert, V., Lyons, T.W., Engel, G.S., Balci, N., Schrag, D.P., Brunner, B., 2010. Kinetic oxygen isotope effects during dissimilatory sulfate reduction: a combined theoretical and experimental approach. Geochimica et Cosmochimica Acta 74, 2011e2024. Webb, J., McGinness, S., Lappin-Scott, H., 1998. Metal removal by sulphate-reducing bacteria from natural and constructed wetlands. Journal of Applied Microbiology 84, 240e248. Wiessner, A., Rahman, K.Z., Kuschk, P., Ka¨stner, M., Jechorek, M., 2010. Dynamics of sulphur compounds in horizontal subsurface flow laboratory-scale constructed wetlands treating artificial sewage. Water Research 44, 6175e6185. Woulds, C., Ngwenya, B.T., 2004. Geochemical processes governing the performance of a constructed wetland treating acid mine drainage, Central Scotland. Applied Geochemistry 19, 1773e1783. Zheng, P., 2007. Anoxic sulfide biooxidation using nitrite as electron acceptor. Journal of Hazardous Materials 147, 249e256. Zheng, P., Cai, J., 2007. Comparison of anoxic sulfide biooxidation using nitrate/nitrite as electron acceptor. Environmental Progress 26, 169e177.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 6 9 9 e6 7 0 8
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Nitrogen removal assessment through nitrification rates and media biofilm accumulation in an IFAS process demonstration study Pusker Regmi a,*, Wes Thomas b, Gary Schafran a, Charles Bott c, Bob Rutherford c, David Waltrip c a
Old Dominion University, Civil and Environmental Engineering, Rm 135 Kaufman Hall, Hampton Blvd, Norfolk, VA 23529, USA Virginia Polytechnic Institute and State University, USA c Hampton Roads Sanitation District, USA b
article info
abstract
Article history:
An IFAS demonstration study was conducted at the 76,000 m3/day (20MGD) James River
Received 5 April 2011
Wastewater Treatment Plant (JRTP) located in Newport News, Virginia by converting one
Received in revised form
fully-aerobic conventional aeration basin with dedicated secondary clarification to
23 September 2011
a 7041 m3/day (8404 m3/day max month) IFAS train in a modified Ludzack-Ettinger (MLE)
Accepted 11 October 2011
configuration. During the study, biomass concentrations on the biofilm carriers were
Available online 19 October 2011
monitored (weekly) as well as nitrogen species concentrations in the IFAS reactor to quantify the nitrogen transformations occurring within the demonstration tank. In
Keywords:
a related effort, nitrification kinetics for ammonia and nitrite oxidizing bacteria were
Biofilm carriers
monitored on a weekly basis for IFAS media alone, IFAS process mixed liquor without
IFAS
media, and IFAS mixed liquor and media together in an effort to identify the location of
MLE
nitrification activity (i.e. on the media or in the suspended culture) in the IFAS process.
Nitrogen
Biomass quantity on the media was generally observed to be inversely related to
Nutrient removal
temperature except during a period when an auxiliary carbon source contaminated with fungi was introduced. Both ammonia oxidizing and nitrite oxidizing bacterial activity were elevated on the carriers compared to the suspended culture (AOBmedia: 4.97 mgNOx/gMLSS/ hr; AOBsuspended: 1.72 mgNOx/gMLSS/hr; NOBmedia: 7.55 mgNOx/gMLSS/hr; NOBsuspended: 0.82 mgNOx/gMLSS/hr) during all periods of the study. In-basin nitrification rates calculated based on nitrogen profiling efforts averaged 0.90 mgNOx/m2/day which was in good agreement with the average of 0.89 mgNOx/m2/day for IFAS mixed liquor and media from batch testing. ª 2011 Elsevier Ltd. All rights reserved.
1.
Introduction
Biofilm technologies are increasingly being implemented in wastewater treatment due to their advantages with respect to smaller reactor sizes, ease of operation, less demanding solids
separation requirements, and the increased specialization of attached biomass (Ødegaard, 2006). One of these technologies is the integrated fixed-film activated sludge (IFAS) process which is a hybrid process relying on microorganisms both in suspended culture and attached to free-floating media to
* Corresponding author. Tel.: þ1 757 255 8465. E-mail addresses:
[email protected],
[email protected] (P. Regmi). 0043-1354/$ e see front matter ª 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2011.10.009
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achieve soluble BOD and nitrogen removal. Because IFAS media are retained within an aeration basin, process decoupling of the growth rate of nitrifying organisms from the SRT of the suspended mixed liquor phase occurs (Onnis-Hayden et al., 2011). This situation is particularly attractive for processes targeting nitrogen removal since slow-growing nitrifying organisms can be retained in the process where otherwise they would be lost under operational conditions where SRT is shorter than needed for suspended culture populations to proliferate. If this understanding is applicable it means in colder months, nitrification is more dependent on attached growth nitrification activity than on suspended growth and this activity will determine the successful operation of an IFAS treatment process for nitrogen removal during cold conditions. The fact that in an IFAS process nitrification takes place predominantly in the attached biofilm whereas removal of BOD is carried out by the suspended growth makes it possible to keep SRT of the activated sludge shorter than when nitrification occurs solely within a suspended culture. In attached growth systems such as a moving-bed bioreactor (MBBR), the surface area for biofilm growth can be increased by designing carriers with a higher specific surface area or by adding more biofilm carriers to the same reactor volume (Ødegaard et al., 2000). This allows future expansion of treatment capacity without the need for construction of new reactors. However, mixing problems restrict the volumetric fill fraction for carriers to exceed approximately70%, which imposes limitation on increasing the surface area in a given reactor volume (Ødegaard, 2006). Generally principles of microbial ecology apply to biofilms, however, biofilm communities also have distinct features that affect their microbiology and community dynamics (Wuertz et al., 2004). The nitrification rates in integrated biofilm systems are also less affected by changes in temperature (Christensson and Welander, 2004), which makes them favorable in cold climates as a nitrogen removal process. Higher dissolved oxygen concentrations at lower temperature can also compensate for the low growth rate of nitrifiers as there will be deeper penetration of oxygen within the biofilm promoting the growth of active nitrifiers. Hubbell and McDowell (2003) reported significant ammonia reduction at Donner Summit Public Utility District at influent wastewater temperatures as low as 8 C. Stable nitrification has been demonstrated by IFAS processes at even lower mixed liquor concentrations than those where it can be achieved by the conventional activated sludge process (Ross et al., 2004). To date, there are more than 300 wastewater treatment plants operating or under construction based on IFAS-like biofilm processes worldwide with most of them in Europe (Ødegaard, 2006). Several studies have reported successful installation and operation of IFAS (Sriwiriyarat and Randall, 2005) but these plants are located in more northern temperate zones than the JRTP. In North America there are only two full-scale IFAS plants using free-floating plastic carriers. One of these is the Broomfield Wastewater Treatment Plant (BWTP) in Denver, Colorado which started operation in November 2002 as an IFAS process (Rutt et al., 2006; Onnis-Hayden et al., 2007) and has shown capabilities of N
and P removal (Rutt et al., 2006). In Ontario, Canada, the Lakeview Wastewater Treatment Plant has been operating as a full-scale IFAS demonstration project (Ross et al., 2004; Maas et al., 2008; Stricker et al., 2009) since August 2003. Because IFAS is a relatively new technology, limited experience exists in the design of the process particularly retrofitting it into existing facilities. To better understand the process operation and to guide the design for a full-scale plant conversion, the study described here was conducted as a fullscale demonstration study using one of nine aeration tanks and two dedicated secondary clarifiers. The goals of the demonstration study were: 1) To demonstrate the capability of the IFAS treatment process to achieve an annual average settled effluent total nitrogen concentration of 12 mg N/L under design load and flow conditions; 2) To understand the temporal and spatial changes in biomass attached to the biofilm carriers over time and their effect on performance of the IFAS process; 3) Investigate nitrogen conversion across the IFAS process train; 4) Identify the location of nitrogen conversion activity and understand the influence of warm and cold weather conditions on this activity in both the carriers and in the mixed liquor.
2.
Material and methods
2.1.
Demonstration train
To conduct a full-scale demonstration study, one of nine aeration tanks was modified and two secondary clarifiers were isolated and dedicated to the IFAS demonstration process train. The IFAS demonstration reactor consisted of anoxic and aerobic zones similar to a modified LudzackEttinger (MLE) configuration, with the anoxic zone consisting of 35% of total tank volume and the aerobic zone occupying 65% (Fig. 1). The IFAS train consisted of five compartments labeled R1 through R5, with each compartment separated by a baffle wall. Direct-drive submersible mechanical mixers in each of the anoxic chambers provided mixing. The plastic carrier media (AnoxKaldnes K3) was contained within chamber R4 while chamber R5 (no media) was also aerated by a small aeration grid to provide further ammonia reduction. The narrow tank configuration (length to width ratio of 4:1) resulted in high approach velocities and led to more media accumulation at the downstream side of R4 particularly under high recirculation rates of nitrified mixed liquor. The demonstration tank included two internal mixed liquor recycle (IMLR) pumps. Of these two, one is installed at the upstream end of R4 and the other one installed in R5. The purpose of the IMLR pump installed at the upstream end of R4
Fig. 1 e IFAS reactor schematic and average flows during the study.
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in monitoring influent and effluent of IFAS train for the above mentioned parameters are presented in Table 3.Operational parameters, flow rate, SRT, and dissolved oxygen were also closely monitored and recorded.
Table 1 e Periods of time for studies carried out during the IFAS demonstration. Study effort
Period
Influent/effluent monitoring Biomass measurements Nitrification rate study Nutrient profiling
January 2008 to June 2009a February 2008 to February 2009 January 2008 to June 2009 June 2008 to January 2009
2.4.
a The influent/effluent monitoring was carried out from November 2007 to June 2009, however, data before January 2008 is not presented in this paper. During this time IFAS train was receiving as much as 14000 m3/d while it was designed to handle 8330 m3/ d (Rutherford, 2010).
(IMLR1) was to limit the high approach velocities caused by the recycle from the second IMLR pump installed in R5 (IMLR2) and ensure more even distribution of media across the R4 chamber. The plastic carrier media used in this demonstration project was AnoxKaldnes K3 media made of virgin polyethylene with a density (0.95 g/cm3) similar to water measuring 12 mm deep and 25 mm in diameter and having specific surface area of 500 m2/m3. The carriers are designed to provide a large protected surface for the microorganisms and good mass transfer. The biofilm carriers were installed in the aerobic reactor and kept suspended and in continuous movement by a coarse bubble aeration system. The carriers were kept within the aerobic reactor by a sieve arrangement at the reactor outlet. At the beginning of the study, 465 m3of this media was installed in the aerobic reactor with the volume corresponding to a fill fraction of 50% and providing the aerobic reactor with an effective media surface area of 250 m2/ m3 of aeration tank volume.
2.2.
Study periods
Several activities or studies were conducted throughout the IFAS demonstration beginning at different dates and lasting for different periods of time. These efforts are summarized in Table 1. Some of the key parameters under which the demonstration tank was operated during these study periods are presented in Table 2. Temporal variation in influent flow, temperature and influent TKN are also presented for the period of biomass monitoring (Fig. 2).
2.3.
Influent/effluent monitoring
Throughout the IFAS demonstration, nitrogen species (TKN, NHþ 4 N, NO3 N and NO2 N), phosphorus, BOD, COD were monitored in the influent (primary clarifier effluent) and effluent to the IFAS reactor. The methods and procedures used
Biomass concentration measurements
Media samples were collected from three different locations within the aerobic bioreactor to identify whether spatial variation of biomass on the media occurred. Biomass measurements were conducted on an approximately weekly basis from January 2008 to January 2009. Total biofilm solids on the media were measured by drying twenty carrier samples collected from each of three locations (60 total) at 105 C for 2 h. The dried samples were weighed and the biomass removed by placing the carriers in a 2 N H2SO4 solution, shaking vigorously using a vortex mixer for 3 min, and then soaking the carriers in the same container and solution for more than 2 h. The carriers were then rinsed several times using de-ionized, distilled water and then dried for more than 2 h at 105 C. High-pressure air was then applied to each media individually to ensure that no dry biofilm remained. The difference in initial and final weight was used to calculate the biomass on the carriers. This method to quantify the biomass on the media was similar to that used by Maas et al. (2008).
2.5.
Attached and suspended biomass calculations
The total suspended biomass in the IFAS zone was calculated by multiplying the MLSS (mg/L) concentration and reactor volume; reactor volume occupied by the mixed liquor was 8.74 106 L. The total attached biomass was calculated based on the biomass density (g/m2) and total surface area of the media in the IFAS zone. The total surface is the product of specific surface area (500 m2/m3) and reactor volume (465 m3) occupied by the media. Multiplying total surface area with biomass density gave the mass of the attached biomass in the IFAS zone.
2.6.
Nitrification rate measurements
Nitrification rates were measured on an approximately weekly basis from January 2008 to February 2009. Both AOB and NOB activity were measured in separate bench-scale experiments. In these experiments nitrification rates for the IFAS mixed liquor alone, IFAS media alone and IFAS media and mixed liquor combined were measured. The bench scale reactors used were 9 L (7 L active volume) rectangular polycarbonate containers with provisions for DO and pH probes access. A sample port located in the middle of the active volume was used to collect samples during different
Table 2 e Summary of selected demonstration tank influent wastewater characteristics and operational conditions (Period: January 2008 to June 2009).
Average Max Min
Flow, m3/d
TKN, mg/L
Temperature, C
SRT, days
COD/TKN
MLSS, mg/L
6743 10542 2468
40.3 69.2 25.5
21.3 29.0 14.0
4.8 13.6 1.9
7.0 10.1 2.9
2514 6980 1180
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Additional details of the analytical procedures can be found in Thomas et al. (2009).
2.7. Half-saturation coefficient evaluation (low NHþ 4 N and NO2eN)
Fig. 2 e Influent flow, temperature and influent TKN during influent/effluent monitoring period.
experiments. Mixing was provided by a gang stirrer (Phipps and Bird) to ensure equal mixing to the four reactors. The dissolved oxygen was maintained roughly between 3 and 5 mg/L using pure oxygen. The temperature of the four reactors was maintained similar to that of the IFAS tank by placing them in a temperature controlled water bath and pH was maintained between 7.2 and 7.3 by automated addition of a base (concentrated Na2CO3). Dissolved oxygen, pH and temperature values were recorded directly to a laptop computer. For AOB experiments, reactors with samples were spiked with 40e50 mg/L NHþ 4 N and sampled continuously for 2 h at 25 min intervals. In a similar manner reactors with freshly aerated samples were spiked with 40e50 mg/L of NO 2 N for NOB experiments. To avoid nutrient limitation, reactors were also spiked with 5 mg/L of phosphorus. All collected samples were analyzed for NHþ 4 N, NO2 N, and NO3 N. For field þ analysis, NH4 N was analyzed using HACH colorimetric method TNT plus 832. Colorimetric methods were performed per HACH protocols with evaluation of matrix interference and other issues as needed. NO 3 N was analyzed using HACH colorimetric method TNT plus 836. Nitrite analysis was conducted in the field as soon as possible after sample filtration. The standard colorimetric method was performed using HACH Nitriver 3 reagent and 10 mL samples. HACH method 8507 is a low range method, so all samples were diluted to concentrations between 0.002 and 0.3 mg/L NO2eN and analyzed per standard protocols.
Variable D.O. concentrations of 2, 4, 6, and 8 mg/L were maintained in the controlled reactors and allowed to mix and aerate with pure O2 until each reactor reached the desired D.O. level. The reactors were spiked to 25 mg/L of either ammonia or nitrite; in addition to that phosphate is added to ensure that the biomass was not nutrient limited. Samples were taken at desired intervals to capture the linear rate of nitrification as well as nitrification rates in low substrate concentrations. The recorded results from these tests were analyzed to calculate half-saturation coefficient using four different D.O. concentrations. These tests were conducted three times for AOB and NOB activity on the media at 175 RPM and 100 RPM and as twice for AOB and NOB activity on the media at 100 RPM. In addition to testing the IFAS media, the same experiments were conducted one for AOB and NOB activity in the mixed liquor at 175 RPM.
2.8.
Nutrient profiling
To better understand the fate of the various forms of nitrogen and the total nitrogen removal occurring across the IFAS train, samples were collected at seven locations from the inlet to outlet of the demonstration tank. Three samples were collected from the anoxic basin (referred to as AN1 through AN3 and corresponding to R1, R2, and R3 chambers) and four samples across the aerated basin (OX1-OX4). This effort was carried out on a weekly basis over a seven-month period (June 2008 to January 2009). The profiling conducted over an extended period allowed an evaluation of both spatial and temporal trends in performance across the IFAS basin. To avoid loss/conversion of nitrogen due to biological activities samples were filtered through a 0.45 mm filter immediately after collection and on site and transported on ice back to the laboratory within 45 min. These samples were then analyzed for total dissolved nitrogen (TDN) using a TOC analyzer (Shimadzu TOC-Vcsn, Kyoto, Japan) connected in series with a TNM-1 total
Table 3 e Methods and procedures used for influent/effluent monitoring of IFAS train. Parameter Total and Volatile Suspended Solids (TSS, VSS) Total Kjeldahl Nitrogen (TKN) Total Phosphorous (TP) Ammonia (NH3eN) Nitrate/nitrite (NO2, NO3) Nitrite (NO2) Nitrate (NO3) by calculation Biochemical Oxygen Demand (BOD) Chemical Oxygen Demand (COD)
Method title
Reference method
TSS e Total suspended solids dried at 103e105 C TVSS e Fixed and volatile solids ignited at 550 C Determination of Total Kjeldahl Nitrogen by flow injection analysis colorimetry (Block Digestion) Determination of Total Phosphorous by flow injection analysis colorimetry (Acid Persulfate Digestion) Determination of ammonia by flow injection analysis colorimetry Determination of nitrate/nitrite by flow injection analysis colorimetry
SM 20th 2540D SM 18th 2540E EPA 351.2 10-107-06-2-I EPA 365.1 Lachat 10-115-01-1-E EPA 350.1 Lachat 10-107-06-1-C EPA 353.2 Lachat 10-107-04-1-C/A
Biochemical Oxygen Demand (BOD) 5-day BOD test Chemical Oxygen Demand, Reactor Digestion Method
SM 18TH 5210B Hach 8000
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nitrogen module, nitrate and nitrite by ion chromatography (Dionex Model 4500 IC, Sunnyvale, CA, USA), and ammonia using the indophenol blue method (Method 4500-Ammonia, Standard Methods, 1998). The soluble org-N fraction was calculated as the difference of TDN and the sum of the inorganic nitrogen species (NH4eN, NO3eN and NO2eN).
3.
Results and discussion
During the period between February 2008 and June 2009 the average TN concentration in the IFAS effluent was 9.95 mg/L corresponding to 75.1% TN removal (Rutherford, 2010). The average chemical oxygen demand (COD) influent to the IFAS process train was 267 mg/L and the COD/TKN ratios remained low during the period averaging 7.0. The temperature of wastewater in the IFAS tank ranged from 14 C to 29 C and averaged 23 C. The mixed liquor suspended solids concentrations were on average 2786 mg/L and varied between a low of 1180 mg/L and high of 6980 mg/L corresponding to changes in operational SRT varying between 1.9 and 13.6 days. Controlling of SRT by wasting sludge from a return line proved difficult because of wide variations in return sludge concentrations (Rutherford, 2010). The problem was obviated by wasting directly from the IFAS tank.
3.1.
Biomass coverage of K3 media
The total solids attached to the IFAS media was monitored from February 2008 to January 2009. During this study period biofilm total solids on the K3 media ranged from a high of 12.6 g/m2 to a low of 2.4 g/m2, with an average of 6.0 g/m2. The difference in the total biofilm solids among the three sites sampled within the IFAS tank was minimal (Fig. 3), and there was also no visible difference observed among the IFAS media samples at the three sites in terms of color and physical appearance. This observation suggests that mixing in the IFAS tank caused the media to be well mixed along the axis of flow as well as laterally. In the first month of measurement (February 2008) the biofilm solids concentration was 7.0 g/m2 and increased through March 2008 at which point it was 12 g/m2. This increase may be related to acclimatization of the biofilm, which had not reached steady state conditions prior to the first sampling. The temperature of wastewater in the IFAS aerobic bioreactor was approximately 17 C for the month of February and most of March increasing to 20 C by mid-April. Beginning in mid-April the biofilm mass on the IFAS media began decreasing and by the end of the month it was less than 3 g/m2. Examining the full year of biofilm measurements, a seasonal pattern can be observed (biofilm mass inversely related to temperature, Fig. 3). In suspended growth systems the role temperature and its impact have been well understood, however, in attached growth systems temperature effects are not fully known (Wheaton et al., 1994; Okey and Albertson, 1989). The difficulty in assessing temperature effects on biofilm based systems stems from the fact that temperature has a deep impact on biological kinetics as well as substrate diffusion and transport (Zhu and Chen, 2002). In biofilm systems gradients of electron acceptors such as
Fig. 3 e Biofilm solids concentrations at three sites (influent end, middle, effluent end) along the aerobic bioreactor in the IFAS process train from February 2008 to January 2009.
dissolved oxygen and nitrate can potentially cause stratification of microorganisms exhibiting vastly different metabolisms (Okabe et al., 1996). Similar relationships between temperature and biomass on the carriers have been observed by Rutt et al. (2006) and Maas et al. (2008). Bjonberg et al. (2010) also reported an almost inverse relationship between biomass and operating temperature at The Moorhead, Minnesota Wastewater Treatment Facility (WWTF) operating a moving-bed biofilm reactor (MBBR). Boltz and Daigger (2010) have attributed this relationship to macronutrient and other substrates not being exhausted immediately under cold water conditions resulting in biochemical processes occurring deeper into the biofilm resulting in thicker and heavier biomass coverage. In the case of nitrifying biofilm on IFAS media at higher temperature the depth of NH3 diffusion is reduced as biochemical processes occur faster at the interface. As a response to cold weather the MBBR/IFAS biofilm mass increases as a consequence of slower biochemical transformations (Boltz and Daigger, 2010). The biomass on the media accounted for on average 38% of the total biomass within the IFAS zone, which is a significant amount considering that biofilm carriers were present at 50% fill with 88% void spaces (Table 4). During the winter months the biomass on the media was comparable to the suspended biomass while the quantity was far less during the summer months (Fig. 4). In a completely different situation the biomass on the media increased during the month of June 2008 (Fig. 3). This increase occurred due to the introduction to the IFAS train of an external organic substrate (to improve denitrification), which after introduction to the system was found to be high in yeast. Rapid microbial growth on the media was microscopically confirmed to be due to yeast
Table 4 e Amount Suspended and Attached Biomass and Attached Fraction (Period: February 2008 to February 2009).
Average Max Min
Suspended biomass, kg
Attached biomass, kg
Attached biomass/ total biomass
2280 6102 1250
1383 2919 558
38% 68% 10%
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during the yeast episode. Therefore, it appears that at higher biomass concentrations recycle NO 3 concentrations will be decreased and the total nitrogen removal will decrease. The episode highlights the importance of successful monitoring of the biomass on the media to resolve situations such as this one that was encountered during the study period. The sixweek-long yeast problem was resolved by over-aerating the IFAS tank and raising the pH to encourage more nitrification (Rutherford, 2010).
3.2.
Fig. 4 e Temporal changes in biomass on suspended and attached biomass phase in the IFAS zone.
proliferation causing process upset in terms of nitrogen removal most notably observed in the effluent ammonia concentration (Fig. 5). During the period when the media was at its thickest coverage, the media migrated and accumulated at the effluent end of the aerobic basin. This condition likely inhibited water movement through the media compared to when the media was more evenly distributed throughout the aerobic basin and highly mixed. The high approach velocities of the wastewater coming through the anoxic to the aerobic zone are experienced due to the low width to length ratio of the IFAS bioreactor and coupled with the operation of the IMLR 2 pump, which pulled the media toward the downstream end of the aerobic basin. By design and to counteract this effect, the IMLR 1 pump was operated at the upstream end of the aerobic basin. However, during the period of high biomass coverage on the media the IMLR 1 pump was not able to keep the media from migrating toward the downstream end of the aeration basin. Consequently, the IMLR 2 pumping rate was decreased and the flow rate of the IMLR 1 pump was increased. The compounding effect of operating the IMLR 1 pump at much higher flow rate was that in the upstream end of the aeration basin (OX1) the NO 3 concentration was significantly lower than at the downstream end (OX4). Considering that the NO 3 recycle is the backbone for successful nitrogen removal by the MLE process, the low NO 3 concentration in the recycle had a negative effect on total nitrogen removal performance
Fig. 5 e Temporal variation of primary effluent TKN, IFAS Effluent TN and IFAS effluent ammonia during yeast event.
Nitrogen removal
Nitrogen removal across the IFAS tank was evaluated from profiling data collected during the study and significant removal of nitrogen was observed from February 2008 to June 2009 (Fig. 5). The effluent total dissolved nitrogen averaged around 12.8 mg/L (profiling period) which slightly exceeded the target of 12 mg/L. On average the percent nitrogen removal achieved by the IFAS demonstration tank was sixty-seven, and ranged between 39 and 89 percent. The effluent ammonia concentration remained low, averaging 1.6 mg/L, signifying extensive nitrification during the nutrient profiling period. There were several days with effluent ammonia below detection indicating complete nitrification. As observed with nitrifying/denitrifying treatment processes with internal mixed liquor recycle similar to the IFAS demonstration process, the dominant species of nitrogen in the effluent was NO 3 . With nitrification being relatively stable in the IFAS tank during the study period it was the extent of denitrification that controlled the effluent total nitrogen concentration. The nitrogen species at seven sampling sites across the demonstration tank illustrate transformations that occurred (Fig. 6). The total nitrogen concentration did not change dramatically over the length of the demonstration tank, but the nitrogen species distribution did. The effluent ammonia concentration remained low, on average 1.4 mg/L, while NO 3 concentration averaged 8.4 mg/L signifying extensive nitrification. Nitrite concentrations generally remained low averaging 0.2 mg/L across all sites illustrating that there was no nitrite accumulation in the demonstration tank. This observation suggests a stable population of AOB and NOB were present causing extensive conversion of ammonia to nitrate. The soluble organic nitrogen concentration also remained low in the effluent. On average there was 0.6 mg N/L of soluble organic nitrogen leaving the aeration basin to the secondary clarifier. The fact that there was an average of 2 mg/L of soluble organic-N entering the aerobic basin and only 0.6 mg/L leaving illustrates that ammonification or direct uptake of organic nitrogen was occurring across the IFAS reactor. The measurement of nitrogen species across the IFAS process train allowed assessment of the denitrifcation that occurred in the anoxic zone. On average about 54% of NO 3 was denitrified. Denitrification was limited and there was always some effluent NO 3 escaping the anoxic basin to the aerobic basin (Fig. 6). The rate of denitrification in a pre-denitrification system may be governed by the NO 3 concentration, the bioavailable organic matter concentration and/or by dissolved oxygen concentration in a denitrifying anoxic reactor. At NO 3 concentrations of approximately 3 mg/L and above, the denitrification rate will be entirely controlled by the quantity
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Fig. 6 e Average concentrations of nitrogen species and dissolved oxygen from June 2008 to January 2009 at the seven sampling sites.
and type of biodegradable organic matter (Rusten et al., 1995). The COD/TKN ratio during the study period was on average 7.0 which is lower than the desired COD/TKN ratio (>9) for higher nitrogen removal efficiencies (Grady et al., 1999).
3.3.
Nitrification kinetics and in-basin nitrification rates
The results of nitrification rate testing (AOB and NOB activity) during the study period for IFAS mixed liquor, the IFAS media, and the media and mixed liquor combined is presented in Fig. 7. As noted previously, this effort was conducted to determine where nitrification activity was taking place in the process (i.e. suspended or attached) and how the operational and seasonal conditions influenced nitrogen transformations. The average AOB activity on the IFAS media during the study was 4.97 mgNOx/gMLSS/hr which was much higher than the average of 1.72 mgNOx/gMLSS/hr for the IFAS mixed liquor. The NOB activity on the media averaged 7.55 mgNOx/gMLSS/ hr much higher than the IFAS mixed liquor, which was only 0.82 mgNOx/gMLSS/hr on average. In an IFAS study OnnisHayden et al. (2011) reported 75% nitrification activity residing on the carried media rather than in the mixed liquor which is similar to the distribution of activity observed in this study. The AOB activity in the IFAS suspended culture was present throughout the study period, but the activity was substantially lower in suspension compared to the media during colder temperatures (Fig. 7). The fluctuations in AOB activity were more gradual in IFAS media as opposed to mixed liquor where it drastically increased with warmer temperatures. The fact that there was presence of AOB activity year round in the IFAS mixed liquor, even in low SRT in winter, suggests that sloughing of biofilm biomass was seeding the mixed liquor continuously. Unlike AOB activity, the NOB activity resided attached to the media even in warmer temperature (Fig. 7). In the full-scale plant (conventional activated sludge (CAS): average flow of 96,700 m3/d, MLSS of
2483 mg/L, SRT of 3.7 days and temperature of 21.4 C for the month November) profiling revealed that the NOB activity in November 2008 was much lower than AOB activity leading to nitrite accumulation (CAS NO 2 N ¼ 11.2 mg N/L measured on 11/18/2008). In contrast, there was no nitrite accumulation in the IFAS zone throughout the study (Fig. 6) as nitrite
Fig. 7 e Nitrification rates for AOB and NOB experiments.
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produced by the AOB activity was immediately converted to nitrate by NOB activity. The half-saturation constants for microorganisms on the biofilm carriers were modeled using Monod kinetics using the results of the nitrification kinetic studies (Thomas, 2009). The calculated KS values in the IFAS process were higher than accepted KS (0.7 mg N/L for AOB and 0.05 mg N/L for NOB according to Envirosim (2008)) values for mixed liquor in activated sludge systems as expected. Modeled NOB effective KS values for the carriers were much higher (2168%) than KS of a typical suspended growth culture. This suggests nitrite accessibility within the biofilm is greatly limited by substrate diffusion. Compared to ammonia and oxygen, nitrite has a lower diffusivity, which explains the high effective NOB halfsaturation coefficient in the attached growth systems. It also supports the hypothesis that NOB reside deeper within the biofilm. Unlike the NOB KS value, the AOB KS value was only 33% higher than what is accepted for suspended cultures of microorganisms. This indicates ammonia was more available to biofilm and supports the hypothesis that AOB populations inhabited the surface of the biofilm where substrate diffusion has less effect. It also explains the lower NOB activity in the IFAS mixed liquor that may be attributed by the NOB population growing deeper into the biomass and detaching less than AOB population. The lower NOB population in the mixed liquor may also depend on the fact that NOB have a lower maximum specific growth rate than AOB at temperatures higher than 15 C. The difference between nitrite and ammonia concentration should be also considered. Nitrite concentrations were everywhere lower, so k-strategist rather than rstrategist NOB could be favored. In a molecular analysis using florescent in-situ hybridization (FISH) at the Broomfield WWTP Nitrospira spp. was observed to be the most abundant NOB (Onnis-Hayden et al., 2007). Schramm et al. (1999) proposed that Nitrospira spp. might be k-strategist capable of reaching higher population densities at weaker nitrite environments. This is again suggesting that NOB require a higher SRT and explains why they are more prevalent in attached form. Close monitoring of the nitrogen species across the IFAS process train allowed the calculation of nitrification rates for each sampling date over the period of the nutrient profiling effort. The calculated nitrification rates allow an indirect evaluation of nitrifying activity. In-basin nitrification rates
Fig. 9 e Nitrification rates measured along the IFAS tank.
were calculated based on the NO X produced rather than ammonia removed and represents the difference in NO X measured at sites AN3 and OX4. The in-basin nitrification rate, which is based on a mass balance of dissolved nitrogen species across the aerobic basin, includes ammonia removal through assimilation by attached and suspended microorganisms. The nitrification rate averaged 0.90 gNOxeN/m2/ d (Fig. 8); samples less than 1 mg N/L ammonia were excluded from the average rate calculation since low ammonia concentrations achieved before the end of the tank would artificially lower the nitrification rate due to the availability of ammonia. This value was in good agreement with the average nitrification rate of 0.89 gNOxeN/m2/d for IFAS media and mixed liquor observed from the kinetic testing phase. OnnisHayden et al. (2007) reported a nitrification rate of 1.12 gNOxeN/m2/d for the Broomfield IFAS demonstration that was similar to the IFAS demonstration at JRTP. The carrier biomass was measured to be constant along the length of IFAS tank; however, profiling of the IFAS tank clearly suggested concentration gradients of nitrogen species (ammonia, nitrite and nitrate) over the length of the tank. This prompted assessment of IFAS media nitrification rates over the length of IFAS tank. The results indicate that the effect of location was not significant on the carrier nitrification potential (Fig. 9). This high activity on the IFAS carriers throughout of tank volume can be advantageous over a two reactor design where lower nitrification rates are observed in the downstream reactor. The slightly higher nitrification rates at OX3 and OX4 might be attributed to higher dissolved oxygen in the bench scale test reactors (Fig. 9).
4.
Fig. 8 e Biofilm solids and in basin nitrification rates for the IFAS train during the study period.
Conclusion
A CAS train at JRTP was converted from carbonaceous removal to nitrification/denitrification within the existing footprint by dividing the tank into anoxic and aerobic compartments and installing the free-floating plastic carriers in the aerobic stage of the reactor. Carrier biomass was monitored throughout the study, which helped assess biofilm conditions. Biofilm density was constant in three sampling locations, which indicate that biomass growth was homogeneous throughout the IFAS tank. Similarly, uniform
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 6 9 9 e6 7 0 8
nitrification activity was observed independent of location in the IFAS tank. The biomass growth on the media exhibited a seasonal pattern where biomass coverage was highest during winter months and lowest during summer excluding the yeast event. The decrease of biomass occurred while the SRT of mixed liquor remained fairly stable thus the trend appears independent of suspended culture conditions. The observed increase in suspended biomass (Fig. 4) was due to the rapid loss of biomass from the carrier media toward the end of the yeast event. As temperature cooled in the basin in the late autumn and early winter, biomass content on the carriers steadily increased from about 3 g MLSS/m2 to about 7 g MLSS/m2. This increase in biomass should correlate directly with increased nitrifier abundance on the media. Another possible reason for increased biomass on the carriers could be a reduction in mixing input to the tank. At low temperatures, less aeration was required to maintain dissolved oxygen in the tank, so the decreased aeration intensity likely also resulted in decreased agitation of the media and thus less sloughing of biomass. From June 2008 to January 2009 the demonstration tank was monitored for nitrogen species at seven sampling sites along the length of the IFAS process train. The results of profiling have shown that under different loading and temperature conditions the IFAS process train was able to achieve significant removal of total nitrogen. The effluent TDN level averaged 12.8 mg/L during the nutrient profiling period while effluent ammonia averaged 1.6 mg/L during the same time. Nitrate was the most dominant nitrogen species at the effluent averaging 9.8 mg/L. Soluble organic nitrogen in the treated effluent was consistently less than 0.6 mg/L across the range of load and temperature conditions. During the study period aerobic nitrification was consistently over 87 percent whereas anoxic denitrification resulted in 51 percent conversion of nitrate. There was high nitrate concentration (average 4.0 mg/L) in the anoxic effluent which indicates that denitrification was incomplete. The fact that the COD/TKN ratio of influent wastewater remained low averaging around 7.0 and significant dissolved oxygen was recycled from the IFAS zone by two IMLR pumps indicating that denitrification was COD limited. Consequently, one way to improve the total nitrogen removal efficiencies is to improve the anoxic denitrification through augmentation of available biodegradable organic matter. The activities of both ammonia oxidizing and nitrite oxidizing were elevated on the carriers compared to the suspended culture (AOBmedia: 4.97 mgNOx/gMLSS/hr; AOBsuspended: 1.72 mgNOx/gMLSS/hr; NOBmedia: 7.55 mgNOx/gMLSS/hr; NOBsuspended: 0.82 mgNOx/gMLSS/hr) during all periods of the study. In-basin nitrification rates calculated based on nitrogen profiling efforts averaged 0.90 mgNOx/m2/day which was in good agreement with the average of 0.89 mgNOx/m2/day for IFAS mixed liquor and media from batch testing.
Acknowledgment The authors would like to thank Mr. Jim McQuarrie, CH2MHILL (at the time) and Mr. Rick Baumler, Hampton Roads Sanitation
6707
District for their invaluable input. Funding for this study was provided by the Hampton Roads Sanitation District.
references
Bjonberg, C., Lin, W., Zimmerman, R., 2010. Kinetic evaluation and model simulation of temperature impact on biofilm growth and nitrification in a full-scale MBBR system. Proceedings of the Water Environment Federation, 4146e4171. Boltz, J.P., Daigger, G.T., 2010. Uncertainty in bulk-liquid hydrodynamics and biofilm dynamics creates uncertainties in biofilm reactor design. Water Science and Technology 61 (2), 307e316. Christensson, M., Welander, T., 2004. Treatment of Municipal Wastewater in a Hybrid Process Using a New Suspended Carrier with Large Surface Area, pp. 207e214. IWA Publishing. Envirosim, 2008. BioWin Version 3.0 Default Parameters. Grady, C.P.L., Daigger, G.T., Lim, H.C., 1999. Biological Wastewater Treatment. Marcel Dekker, New York. Hubbell, S.B., McDowell, C., 2003. Cold temperature BNR using integrated fixed film activated sludge (IFAS) hybrid technology. Proceedings of the Water Environment Federation, 162e172. Maas, C.L.A., Parker, W.J., Legge, R.L., 2008. Oxygen uptake rate tests to evaluate integrated fixed film activated sludge processes. Water Environment Research 80 (12), 2276e2283. Ødegaard, H., Gisvold, B., Strickland, J., 2000. The influence of carrier size and shape in the moving bed biofilm process. Water Science and Technology 41 (4e5), 383e391. Ødegaard, H., 2006. Innovations in wastewater treatment: the moving bed biofilm process. Water Science and Technology 53 (9), 17e33. Okabe, S., Hiratia, K., Ozawa, Y., Watanabe, Y., 1996. Spatial microbial distributions of nitrifiers and heterotrophs in mixed-population biofilms. Water Science and Technology 50, 24e35. Okey, R., Albertson, O., 1989. Evidence for oxygen-limiting conditions during tertiery fixed film nitrification. Journal Water Pollution Control Federation 61, 510e519. Onnis-Hayden, A., Dair, D., Johnson, C., Schramm, A., Gu, A.Z., 2007. Kinetcis and nitrifying populations in nitrogen removal processes at a full-scale integrated fixed-film activated sludge (IFAS) plant. Proceedings of the Water Environment Federation, 3099e3119. Onnis-Hayden, A., Majed, N., Schramm, A., Gu, A.Z., 2011. Process optimization by decoupled control of key microbial populations: distribution of activity and abundance of polyphosphate-accumulating organisms and nitrifying populations in a full-scale IFAS-EBPR plant. Water Research 45 (13), 3845e3854. Ross, D., Fernandes, W., Briggs, T., Kim, N., Booth, G., Neely, D., Welp, J., 2004. Integrated fixed film activated sludge (IFAS) at the lakeview WWTP the real implementation issues. Proceedings of the Water Environment Federation, 286e298. Rutherford, B., 2010. IFAS enables Virginia plant to meet permit demands. Water Environment & Technology, 64e69. May 2010. Rusten, B., Hem, L.J., Degaard, H., 1995. Nitrogen removal from dilute wastewater in cold climate using moving-bed biofilm reactors. Water Environment Research 67, 65e74. Rutt, K., Seda, J., Johnson, C.H., 2006. Two year case study of integrated fixed film activated sludge (IFAS) at broomfield, CO WWTP. Proceedings of the Water Environment Federation, 225e239. Schramm, A., de Beer, D., van den Heuvel, J.C., Ottengraf, S., Amann, R., 1999. Microscale distribution of populations and
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activities of nitrosospira and Nitrospira spp. along a macroscale gradient in a nitrifying bioreactor: quantification by in situ hybridization and the use of microsensors. Applied and Environmental Microbiology 65 (8), 3690. Sriwiriyarat, T., Randall, C.W., 2005. Performance of IFAS wastewater treatment processes for biological phosphorus removal. Water Research 39 (16), 3873e3884. Stricker, A.E., Barrie, A., Maas, C.L.A., Fernandes, W., Lishman, L., 2009. Comparison of performance and operation of side-byside integrated fixed-film and conventional activated sludge processes at demonstration scale. Water Environment Research 81 (3), 219e232. Thomas, W.A., Bott, C.B., Regmi, P., McQuarrie, J., Rutherford, B., Baulmer, R., Waltrip, D., 2009. Evaluation of nitrification
kinetics for a 2.0 MGD IFAS process demonstration. Proceedings of the Water Environment Federation. Thomas, W.A. 2009 Evaluation of Nitrification Kinetics for a 2. 0 MGD IFAS Process Demonstration; Master of Science thesis; Environmental Engineering Department; Virginia Polytechnic Institute and State University: Blacksburg, VA. Wheaton, F., Hochheimer, J., Kaiser, G., Krones, M., 1994. Nitrification Principles: Aquaculture and Reuse Systems. Elsevier, Amsterdam. Wuertz, S., Okabe, S., Hausner, M., 2004. Microbial communities and their interactions in biofilm systems: an overview. Water Science and Technology 49 (11e12), 327e336. Zhu, S., Chen, S., 2002. The impact of temperature on nitrification rate in fixed film biofilters. Aquacultural Engineering 26, 221e237.
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Available online at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Reconnaissance of selected PPCP compounds in Costa Rican surface waters Alison L. Spongberg a,*, Jason D. Witter a, Jenaro Acun˜a b, Jose´ Vargas b, Manuel Murillo b, Gerardo Uman˜a b, Eddy Go´mez b, Greivin Perez c a
Department of Environmental Sciences, University of Toledo, 2801 W. Bancroft St, Toledo, OH 43606, United States Centro de Investigacio´n en Ciencias del Mar y Limnologı´a (CIMAR), Universidad de Costa Rica, San Jose´, Costa Rica c Centro de Investigacio´n en Contaminacion Ambiental (CICA), Universidad de Costa Rica, San Jose´, Costa Rica b
article info
abstract
Article history:
Eighty-six water samples were collected in early 2009 from Costa Rican surface water and
Received 27 January 2011
coastal locations for the analysis of 34 pharmaceutical and personal care product
Received in revised form
compounds (PPCPs). Sampling sites included areas receiving treated and untreated
5 October 2011
wastewaters, and urban and rural runoff. PPCPs were analyzed using a combination of
Accepted 8 October 2011
solid phase extraction and liquid chromatography tandem mass spectrometry. The five
Available online 17 October 2011
most frequently detected compounds were doxycycline (77%), sulfadimethoxine (43%), salicylic acid (41%), triclosan (34%) and caffeine (29%). Caffeine had the maximum
Keywords:
concentration of 1.1 mg L1, possibly due to coffee bean production facilities upstream.
Costa Rica
Other compounds found in high concentrations include: doxycycline (74 mg L1), ibuprofen
Pharmaceutical and personal care
(37 mg L1), gemfibrozil (17 mg L1), acetominophen (13 mg L1) and ketoprofen (10 mg L1).
products
The wastewater effluent collected from an oxidation pond had similar detection and
Liquid
chromatography
mass spectrometry
tandem
concentrations of compounds compared to other studies reported in the literature. Waters receiving runoff from a nearby hospital showed higher concentrations than other areas for many PPCPs. Both caffeine and carbamazepine were found in low frequency compared to other studies, likely due to enhanced degradation and low usage, respectively. Overall concentrations of PPCPs in surface waters of Costa Rica are inline with currently reported occurrence data from around the world, with the exception of doxycycline. Published by Elsevier Ltd.
1.
Introduction
The active ingredients in pharmaceutical and personal care products (PPCPs) and veterinary antibiotics have increasingly been detected in a wide variety of environmental matrices. These include surface and groundwaters, wastewater treatment end products (effluents, reclaimed waters and sludges), soils and biota in the United States and Europe (Kolpin et al., 2002; Loos et al., 2009; Martı`nez-Carballo et al., 2007;
Ramirez et al., 2009). The widespread therapeutic and preventative use in both human and animal populations of products containing these active ingredients and their incomplete elimination in both the body and conventional wastewater treatment has resulted in their environmental introduction. Major pathways into the aquatic environment for these compounds include runoff from areas where both animal and human waste is not confined and treated (i.e landfills, manure piles, land application of sewage sludges),
* Corresponding author. Tel.: þ1 419 530 4091; fax: þ1 419 530 4421. E-mail addresses:
[email protected],
[email protected] (J.D. Witter). 0043-1354/$ e see front matter Published by Elsevier Ltd. doi:10.1016/j.watres.2011.10.004
(A.L.
Spongberg),
[email protected] 6710
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and the direct discharge of untreated wastewater and treated wastewaters (effluent) into surface waters. Once released into the environment many of these compounds persist and can possibly be transported to locations far from the source (e.g. Walters et al., 2010; Wu et al., 2009). Research has mostly focused on the occurrence of PPCPs in temperate environments, with only limited studies being conducted in the warm and humid sub-tropical and tropical climates. Managaki et al. (2007) analyzed the occurrence of twelve veterinary antibiotics in waters from the Mekong Delta, Viet Nam and the urban Tamagawa River in Japan. Increased detections and higher concentrations were found for the Japanese sampling compared to the Mekong Delta for most analyzed compounds, although some PPCPs were common in both locations. Locatelli et al. (2010) surveyed Brazilian surface waters for eight antibiotic compounds and found that usage and sample collection during dry versus wet season determined the distribution and occurrence patterns. Martins et al. (2008) analyzed Brazilian hospital effluent for the presence of ciprofloxacin, a fluoroquinolone antimicrobial agent. The high concentrations detected caused the authors to conclude that the risk associated with the use and emission of pharmaceuticals into the environments of developing countries might be higher than in developed countries. Siemens et al. (2008) reported detection of several acidic and basic pharmaceutical compounds surviving the treatment process in reclaimed wastewaters used as an irrigation source in Mexico City. The inefficient or lack of treatment of wastewaters in developing countries can lead to increased introduction into the environment of these “emerging” contaminants. Costa Rica is a moderately developed country with major urban and vast rural areas. Undeveloped land, rural agricultural areas and highly contaminated sites where identified during previous studies on PCB and pesticide residues (Spongberg and Davis, 1999; Spongberg, 2004). Wastewater treatment in Costa Rica can range from modern regional or city level treatment plants, to areas with primary treatment only, to discharge of untreated waste into local waterways by runoff or pipe. No previous study has been conducted in Costa Rica to assess the occurrence of PPCPs in surface waters. The goal of this study was to detail the occurrence of PPCPs in Costa Rican surface waters, a tropical country, with relation to previous sampling sites used for PCB and pesticide determination, wastewater sources and potentially contaminated runoff. Thirty-four PPCPs ranging in therapeutic class and usage were chosen for analysis. Compounds were selected based on occurrence data reported in other similar large-scale studies, established analytical methodology in our laboratory and suspected usage in Costa Rica.
2.
Materials and methods
2.1.
Nationwide sampling
Eighty-six sampling locations, along with one wastewater effluent sample, were selected from a wide range of localities within Costa Rica and are presented in Fig. 1 with detailed descriptions of the sites listed in Table 1 and S-1 (supplementary material). Site locations were based on
access, previous survey for other compounds, correlation with other studies, or location near a possible source of contamination (wastewater treatment plant, city waste discharge, hospital discharge, urban runoff etc.). Sampling points were recorded using a GPSMAP 76 global positioning satellite receiver (Garmin, Olathe, KS, USA).
2.2.
Sample collection
One liter of surface water from both salt and freshwater environments was collected in high-density polyethylene (HDPE) sampling bottles (Fisher Scientific, Pittsburg, PA, USA). Prior to sampling bottles were washed with dilute hydrochloric acid and methanol. At each sampling site bottles used were rinsed and shaken twice with a full volume of surface water. When necessary bulk samples were collected using a 5liter bucket, then transferred to the 1-liter HDPE containers. All samples were stored on ice until being processed at the Centro de Investigacion en Contaminacion Ambiental (CICA), located at the University of Costa Rica (typically less than 48 h). Once in the laboratory samples were filtered through 47 mm, 0.7 micron glass fiber filters (Fisher Scientific, Pittsburg, PA, USA) using a vacuum apparatus, containers were then rinsed with a 50% (v:v) methanol in water solution, combined and subsequently extracted using solid phase extraction.
2.3.
Chemicals and reagents
All pharmaceutical standards (purity, 90%w99%) were purchased from SigmaeAldrich (St. Louis, MO), except clarithromycin (purity, 98%), obtained from Abbott (Chicago, IL). Instrumental internal standards 13C3-Caffeine (purity, 99%), josamycin (purity, 98%), and 2-(3-chlorophenoxy) propionic acid (purity, 99%) were also obtained from SigmaeAldrich (St. Louis, MO) and simatone was obtained from AccuStandard (New Haven, CT). All other chemicals and solvents were American Chemical Society certified or HPLC grade and supplied by Fisher Chemicals (Fair Lawn, NJ). Deionized water (18.3 MU) was provided by a Barnstead NANOpureÒ Infinity Water System (Dubuque, IA).
2.4.
Solid phase extraction (SPE)
SPE was conducted according to the method reported in Wu et al. (2008). For all samples an aliquot of 350 mL was transferred to a glass container. Twenty-eight milligrams of Na2-EDTA was added and allowed to dissolve while mixing. Sample pH was then adjusted to 5 using H2SO4 and/or 5% (v:v) NH4OH in water. For SPE, Phenomenex Strata X polymeric cartridges, 6 mL 200 mg packing (Torrance, CA, USA), were conditioned three times with 2 mL methanol then three times with 2 mL deionized water containing 1% (w/v) Na2-EDTA in water. Each 350 mL sample aliquot was loaded into the SPE cartridge at a rate of 10 mL min1 using large volume sampling tubes connected to a 24 port SPE vacuum manifold (Phenomenex, Torrance, CA, USA). After loading, cartridges were washed with 2 mL of 5% (v/v) methanol in water and dried under vacuum for 2 min. The analytes were then eluted twice with 3 mL methanol without the use of
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Fig. 1 e Overall map showing sampling locations, surface hydrography and points of interest in Costa Rica, Central America (10N, 85W).
vacuum. The eluate was collected in a glass conical vial and evaporated using nitrogen and a water bath at 40 C to around 200 mL using a Turbo Vap LV (Caliper Life Sciences, Hopkinton, MA, USA). Samples were spiked with 100 ng instrumental internal standards, reconstituted to 0.45 ml using 50% (v/v) methanol in water, vortexed and transferred to 2 ml amber glass vials. SPE extracts were stored at 20 C until instrumental analysis.
2.5. Liquid chromatography mass spectrometry analysis (LC-MS/MS) The LC-MS/MS system consists of a ProStarÒ 210 solvent delivery module with a ProStar 430 autosampler and a 1200L triple-stage quadrupole mass spectrometer with a dual offaxis electrospray ionization interface (Varian Inc., Walnut Creek, CA). Analytes were separated using a Supelco DiscoveryÒ HS C18 column (150 4.6 mm, 3 mm). The column was maintained at 25 C using a ThermaSphere TS-430 Column Chiller/Heater (Phenomenex, Torrance, CA, USA). Mobile phase A was 0.1% (v/v) formic acid in water, mobile phase B was 100% acetonitrile and the total flow rate was 0.3 mL min1. The gradient started with 5% B, held for 2 min, ramped to 100% in 18 min, held 10 min, dropped to 5% B in 2 min, and equilibrated for 8 min. The precursor ions and two most abundant transition ions are provided in Table 2.
Detailed MS/MS parameters and method development procedure is presented elsewhere (Wu et al., 2008).
2.6.
Quantification and method validation
Instrument control, peak detection and integration were accomplished using Varian MS Workstation (Version 6.8). Data acquisition was performed under multiple reaction monitoring (MRM) mode. Identification of the target analytes was based on the presence of two MRM transitions and match of retention time with the reference standard. The ratio of two MRM transitions was used for confirmation. The most abundant transition was selected for quantification. Instrumental internal standards (Wu et al., 2008) were added prior to LCMS/MS analysis, but after SPE, to compensate for instrumental and ionization variation (matrix effect). Ratios of the analyte peak areas to appropriate internal standard peak area were used to construct calibration curves and for sample extract quantification. Powdered standards were dissolved in 450 mL of methanol at five concentration levels (10e500 mg L1), including 100 ng internal standards, to create calibration curves for external quantification. All calibration curves were linear (r2 > 0.98) between 10 and 500 mg L1. Method blanks and reagent water used in the extractions were also run for quality assurance, and data were adjusted for any carryover and background accordingly. A quality control sample (50 mg L1 calibration standard) was run every six injections, and the
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Table 1 e Detailed sampling location information for Costa Rica study. CRP Type Influence 1 2 3 7 8
Fresh Fresh Fresh Tap Salt
Rural Rural Rural Urban Urban
9
Salt
Urban
10 11 12
Salt Salt Salt
Urban Urban Urban
13 14
Salt Salt
Urban Urban
15 16 17
Fresh Salt Fresh
Rural Rural Rural
18 19 20 21 22 23 24 25 26
Fresh Fresh Fresh Fresh Fresh Fresh Fresh Salt Salt
27 28 29 30 31 32 33 34
Salt Salt Salt Salt Salt Salt Salt Salt
Urban Effluent Rural Urban Rural Rural Urban Urban Open water Urban Urban Urban Urban Rural Rural Rural Urban
35
Salt
Urban
36 37
Salt Salt
38 39 40
Description Rı´o Para´ Tributary to Rı´o Virilla Rı´o San Miguel UCR Campus Puntarenas Estuary, exit, near the Ferry Puntarenas beach, near cruise ship Puntarenas dock Puntarenas, 1 km east of dock Puntarenas, Fertica channel, dry dock Puntarenas, Fertica channel Puntarenas, north side of peninsula Rı´o Barranca, end of low tide Puntarenas, Port Caldera Puntarenas, Port Caldera, Mata de Limo´n San Isidro, upstream of wastewater San Isidro, downtream of wastewater Dominical Beach Corte´s, Rı´o Balsar, upstr Osa hospital Rı´o Te´rraba, Palmar Norte Rı´o Esquinas, from Road Golfito, Rı´o Can˜azas Golfo Dulce, Punta Gallardo Golfo Dulce, Punta Gallardo
CRP Type Influence Urban Effluent Urban Urban Rural
Liberia, near oxidation ponds Liberia, WWT oxidation pond Liberia, Rı´o Liberia, upstream of WWT Rı´o Liberia, near hospital Can˜as, Tilapias El Sol, irrigation canal
53 Fresh
Rural
Can˜as, Rı´o Corobicı´
54 Fresh 55 Fresh 56 Salt
Rural Rural Rural
Can˜as, irrigation channel Arenal, Bahı´a San Luis Parque Nacional Manuel Antonio, beach
57 Fresh 58 Fresh
Urban Rural
Quepos, downstream of hospital Quepos, upstream of hospital
59 Fresh 60 Fresh 61 Fresh
Urban Urban Rural
Quepos, downstream of city, low tide Jaco Rı´o Ta´rcoles
62 63 64 65 66 67 68 69 70
Fresh Fresh Fresh Salt Fresh Fresh Fresh Fresh Fresh
Urban Rural Rural Rural Rural Rural Rural Rural Rural
Puntarenas, Talmana Estuary, residential Rı´o Bebedero, falling tide Rı´o Tempisque Golfo de Nicoya, ECMAR dock, high tide Rı´o Lagarto Santa Marta, Te´rraba-Sierpe wetland El Caite, Te´rraba-Sierpe wetland Rı´o Te´rraba, Samu, Te´rraba-Sierpe wetland Isla Loros, Te´rraba-Sierpe wetland
71 72 73 74 75 76 77 78
Fresh Salt Salt Salt Salt Fresh Fresh Fresh
Rural Urban Urban Urban Urban Urban Urban Urban
Golfo Dulce, Golfito, Isla Pelı´cano
79 Fresh
Urban
Urban Urban
Golfo Dulce, Golfito, Purruja Estuary Golfo Dulce, Golfito
80 Fresh 81 Fresh
Urban Urban
Salt Salt Salt
Urban Urban Urban
Golfo Dulce, Golfito, near cemetary Golfo Dulce, Golfito, municipal pier Golfo Dulce, Golfito, hospital
82 Fresh 83 Fresh 84 Fresh
Rural Urban Urban
41 42
Fresh Fresh
Urban Urban
Golfo Dulce, Golfito, urban drainage Golfo Dulce, Rı´o Coto-Colorado, near ferry
85 Fresh 86 Fresh
Urban Urban
43 44
Fresh Fresh
Urban Urban
Golfo Dulce, Golfito, ditch drainage for hospital 87 Fresh Rı´o Corredores, Neily, downstream of hospital 88 Fresh
Urban Urban
45 46
Fresh Fresh
Urban Urban
89 Fresh 90 Fresh
Urban Urban
47
Fresh
Rural
Rı´o Corredores, Neily Rı´o Java, San Vito, near animal feed factory Rı´o Te´rraba
91 Fresh
Urban
Rı´o Sierpe, Te´rraba-Sierpe wetland Limo´n, Cieneguita Limo´n, Vargas Park Limo´n, near hospital, accumulation of waste Limo´n, Moı´m pier Stream running through UCR campus Rı´o Torres, Barrio Tournon River at end of airport runway, Juan Santamarı´a Rı´o San Joaquı´n de Flores, near medical clinic Rı´o Pirro Rı´o Bermu´dez, btwn San Pablo-Santo Domingo Ciudad Quesada, upstream of city Ciudad Quesada, upstream of city, residential Ciudad Quesada, upstream, before confluence Ciudad Quesada, Rı´o Platanar, in city Ciudad Quesada, Rı´o Platanar, hospital and residential drainage Cartago, Rı´o Purires Cartago, Rı´o Reventado, downstream of slum homes Cartago, Quebrada Creek,center of city Cartago, Rı´o Agua Caliente, la Ciudad de los Nin˜os (Hervidero) Cartago, Rı´o Toyogres, drains san Rafeal de Oreamuno
Golfo Golfo Golfo Golfo Golfo Golfo Golfo Golfo
Dulce, Dulce, Dulce, Dulce, Dulce, Dulce, Dulce, Dulce,
Rı´o Tigre, coral reef Puerto Jime´nez Puerto Jime´nez near Hotel Cocodrilo Rı´o Coto-Colorado Rı´o Coto-Colorado, inland Coto-Colorado mouth Golfito, end of low tide
response factor was found to vary less than
1 a1 expðF=kTÞ
(5)
is satisfied, the particle adheres to the pore surface and the pore size decreased due to blocking. Then it is assumed that the pore shape keeps circular and pore size reduces in proportional to square root of difference of the areas of the pore and of the particle. So R¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi R2pore R2part
(6)
Case II: particle size > pore size; i. e., b > 1 The particle covers the pore segment completely if it adheres to the pore entrance. But, as we know, if the particle size is much larger than 1 mm, the role of gravity can not be ignored and hydrodynamic effects are expected to dominate over diffusive effects. So the larger particles can be taken away by the hydrodynamic force. We define g2 ¼ a2 bexpðF=kTÞ
(7)
where a2 is a fitted parameter. So g2 > 1, that is g2 ¼ a2 bexpðF=kTÞi1
(8)
Rearranging Eq. (8) we got: b>
1 a2 expðF=kTÞ
(9)
Thus when Eq. (9) is satisfied, the particle is taken away by the hydrodynamic force, and while Eq. (10) b
1/[a2exp(F/kT)], the right hand side term mainly depends on the energy barrier, temperature, and fitted parameter a2. The effect of energy barrier was described above. a2 is a fitted parameter which is influenced by the processing conditions (mainly depends on the cross-flow rate). With increasing the cross-flow rate, the probability of capturing a particle on the pore decreases. So the parameter a2 and energy barrier F give a pair of competitive effects on the sticking of a particle. They determine b value which decides whether a particle sticks on the pore surface or is taken away by the hydraulic force from the pore.
2.3.
Analysis of the simulation
If all the particles of a certain concentration (i.e. a fix number of particles) are all deposited, one Monte Carlo step (MCS) is executed. The permeability of the membrane is calculated after each MCS and a new iteration begins until the time is reached at a maximum set. The normalized permeability is calculated as the area of the pore cross-section which allows the particles permeate through at certain time divided by the initial area of the pore cross section. The permeate flux is calculated as the number of particles passing trough the membrane divided by the total number of distributed particles. For each simulation and all the results are averaged for five configurations of the membranes.
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The hydraulic resistance is described by Poiseuille flow as (Mortensen et al., 2005): Rhyd h
hL S2
(11)
where h is the dynamic viscosity of the liquid, L the channel length, and S is the cross-sectional area. Integrating all the pores on the membrane at time t the total membrane hydraulic resistance is obtained as hL Rhyd ðtÞ ¼ PNðtÞ 2 i¼1 SðtÞi
size ranges from mg =d3g to mg d3g , where 99% of the theoretical pore size population is included (Lu and Tsai, 2002). Typical pore size distributions are shown in Fig. 3(a) and (b). N pores were generated according to the given distribution, where N is such a value that controls the porosity of the membrane surface which is defined as the sum of the pore cross-section area divided by the total surface area of the membrane. The area of 200 200 is used as the membrane surface. The pores within the membrane were generated without overlapping
(12)
where S(t)i is the cross-sectional area of the ith pore at time t and N is the total number of pores on the membrane at time t. For the microfiltration of constant transmembrane, the permeate flux can be described by Darcy’s law as: J0 ¼
DP mRm
(13)
where J0 is the permeation, DP the transmembrane pressure, m the absolute viscosity of the liquid, and Rm is the resistance of the clean membrane. The initial permeate J0 mainly depends on Rm since there is no pore blocking initially. During the microfiltration, pore blocking causes the increasing of Rp and the permeate can be given, by modifying Darcy’s law, as: DP J¼ m Rm þ Rp
(14)
According to the physical blocking mechanisms of the pore, the pore fouling can be subdivided as standard blocking (particle deposition on the pore) and complete blocking (pore clogging). The complete pore blocking model can be described by (Lim and Bai, 2003): J ¼ J0 exp Kp t
(15)
Or lnJ ¼ Kp t þ lnJ0
(16)
where Kp is the system constant related to pore blocking resistance.
2.4.
Pore and particle size distribution
In this study two different distributions for surface pore generation were used: normal and lognormal. For the normal distribution, the density function of distribution is given as # " 1 ðr mÞ2 f ðrÞ ¼ pffiffiffiffiffiffiexp 2d2 d 2p
(17)
where m is the mean radius of the pores and d is the standard deviation. The pore size ranges from 0.1 to m þ 3d. For lognormal distribution, the density function of distribution is given as 2 # " lnr lnmg 1 pffiffiffiffiffiffiexp f ðrÞ ¼ 2 rlndg 2p 2 lndg
(18)
where mg is the geometric mean radius of the pores and dg is the geometric standard deviation of the distribution. The pore
Fig. 3 e Membrane pore size distributions: (a) normal distribution with mean radius 1.5 and standard deviation 1.72, (b) lognormal distribution with mean radius 1.53 and standard deviation 0.89, and (c) Particle size distribution with mean radius 0.72 and standard deviation 0.51.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 7 8 9 e6 7 9 7
and periodic boundary condition was used to extend the simulation domains. The particles are also generated with lognormal size distribution ranging from 0.1 to 10 mm (See Fig. 3(c)). The number of particles is relative to the feed concentration. When all the particles are deposited, one Monte Carlo Step is finished and a new iteration begins. The Monte Carlo steps are relative to the filtration time. The overall flowchart of Monte Carlo simulation procedures is shown in Fig. 4.
3.
Results and discussion
3.1.
Influence of particle concentration
The number of particles released in per MCS is strongly related to the concentration of the particles in the feed. Different concentrations of 2500, 5000 and 10,000 were used to observe the influence on the normalized permeability of the processing. As shown in Fig. 5 all curves of the permeability as a function of the filtration time can be separated into two parts. Within 100 MCS, the permeability decreases sharply. After that the filtration process reaches a pseudo steady-state stage with a long term decreasing of the permeability. The permeability tends to a stable value although it has a lightly
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decrease. Within the 100 MCS showing pore blocking of the membrane surface, the higher the concentration the faster the pore was clogged. It can be seen from the figure that the slopes of the curves increased with increasing the particle concentration. It was also shown that the permeability decreases with increasing the particle concentration. As the particle concentration increases, the rate of convective particle transport toward the membrane surface increases and hence, the overall rate of colloid deposition onto the membrane increases. Consequently, the amount of deposited colloid increases, resulting in higher resistance and lower permeability (Zhu and Elimelech, 1997).
3.2.
Influence of pore size distribution
In order to examine the effect of pore size distribution on the normalized permeability of the membrane filtration, two membrane surface pore models with different pore size distributions were constructed with the same mean pore radius. The lognormal and normal pore size distributions are described as f(r, m ¼ 1.53, d ¼ 0.89) and f(r, m ¼ 1.5, d ¼ 0.4667) and the size in the range of (mg =d3g , mg d3g ) and (0.1, m þ 3d), respectively. Under this setting 99% of the particle population is included (both of the integrals are more than 99.7%). Fig. 6 illustrates the influence of pore size distributions on the
Fig. 4 e Flow chart of the simulation program.
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Fig. 5 e Influence of particle concentration on normalized permeability as a function of time.
permeability. The membrane with a lognormal size distribution holds a higher normalized permeability than the membrane with a normal distribution during all filtration processing period. The normal distribution with wider deviation from the average size induces faster and more drastic blocking of the membrane than lognormal one. From the view point of membrane preparation, it is important to regulate the morphology and pore size distribution of the membrane thus to control the membrane fouling.
3.3.
Influence of filtration conditions
The capture probability of a particle is influenced by filtration conditions such as membraneeparticle interaction, transmembrane pressure, feeding rate, concentration and viscosity of the solution, temperature and so forth. While b < 1, the size of particle is less than that of the membrane pore it approaching to. Whether the particle passes through the pore or is adsorbed on the pore mainly depends on the interaction energy barrier between the particles and the pore, the transmembrane pressure, and the absolute temperature. The g1 value with the ranges of 0.5e1, 0.7e1, and 0.9e1 (for g1 < 1, the values set as 0.5, 0.7 and 0.9) were chosen for the particle capture at the pore, and the permeability reduction was examined and shown in Fig. 7(a). The narrower the range of g1
Fig. 6 e Influence of membrane pore size distribution on normalized permeability as a function of time.
value the higher the permeability. It can be explained that, for the narrower range of g1 value which corresponds to a lower membraneeparticle interaction and a higher transmembrane pressure, the particle holds a lower probability to adsorb on the pore. When b > 1, the size of particle is bigger than that of the corresponding membrane pore. The particle may stick to the pore or flow away by the bulk solution, which mainly depends on the interaction energy barrier between the particle and the pore, the filtration rate, and the absolute temperature. The g2 value with the ranges of 1e1.2 and 1e2 (for g2 > 1, the values set as 1.2 and 2.0) were used to study the sticking of particles and the results are presented in Fig. 9. As shown in Fig. 7(b), for the g2 value of 1e2.0, the number of particles sticking to the pore surface is much more than that for the g2 value of 1e1.2. The increasing of particles sticking onto the pore can be explained that for higher g2 value, the membraneeparticle interaction is high while the cross-flow velocity is low, which increases the concentration polarization and thus more particles stick to the membrane pores. The results show good agreement with those reported by Niina Laitinen et al. (Laitinen et al., 2001) who also observed that the flux increases with enhancing the filtration pressure and the fouling diminished with increasing the cross-flow velocity.
3.4.
Influence of surface porosity of membrane
Surface porosity of membranes is an important factor influencing the performance of the filtration. Increasing the surface porosity can advance the flux of the membrane. However, the probability of particles adsorbed and sticking to the pore increases as increasing the surface porosity of the
Fig. 7 e Influence of (a) g1 and (b) g2 on normalized permeability as a function of time.
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 7 8 9 e6 7 9 7
6795
membrane. The results were shown from Fig. 8. In Fig. 8(a) the numbers of particles passing through the membrane both increase for membrane surface porosity of 0.1 and 0.2 as time goes by. But the membrane with the porosity of 0.2 has more particles transported than the membrane with the porosity of 0.1, which illustrates that the flux strongly depends on the surface porosity of the membrane. The increasing rate (from the slopes as shown in Fig. 8(a)) for both membranes decreases as time goes by. It is explained that, as the time goes by, the particles block the membrane and thus induce the reduction of the particles passing through the membrane. Fig. 8(b) and (c) show the number of particles adsorbed on the pore and sticking to the pore, respectively. Both of the numbers of adsorbed and sticking particles increase sharply within 100 MCS for both membranes with a porosity of 0.1 and 0.2. And after that a slightly increasing or stable value reached for the sever fouling of the membranes.
3.5.
Analysis of the simulation
As the processing time increasing, the membrane hydraulic resistance increases due to the formation of pore blocking. As time goes by, some pores are clogged completely or blocked partially inducing the decreasing of the total pore crosssectional area and increasing of the hydraulic resistance. As shown in Fig. 9, before processing, the membrane resistance is 1 1012 L/(m.s). At the beginning of the filtration, the resistance increases sharply to 1 1017 L/(m.s), and then slowly increases to 1 1018 L/(m.s). After 800 MCS, the resistance has some jumps. It can be considered from two aspects. First, after
Fig. 8 e Influence of membrane surface porosity on cumulative number of particles (a) passing through the membrane, (b) adsorbed in the pore and (c) sticking on the pore as a function of time.
Fig. 9 e Hydraulic resistance (log Rhyd) as a function of time.
Fig. 10 e ln J as a function of time for membrane with (a) different b value and (b).
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w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 7 8 9 e6 7 9 7
long time filtration, almost all of the pores are clogged or blocked, and the resistance becomes sensitive to the change of cross-sectional area. Secondly, in this model the cake formation was not considered. It is reasonable at the initial stage but not after long time filtration. The relationship between ln J and time obtained from the results of the simulation is a linear as shown in Fig. 10, which well satisfy Eq. (16). It is noted that the results fit the complete pore blocking model well in the initial stage. The values of Kp (slope of the curves in Fig. 10(a)) increased with increasing b value, which demonstrates that, with increasing b value, the complete blocking is easier to occur. It agrees with rule of the model and the results. Changing the initial membrane porosity has little obvious influence on the Kp value (see the slopes of the curves in Fig. 10(b)). It is also demonstrated that the flux changes but not the fouling mechanism with varied membrane porosity.
4.
Conclusions
Pore blocking is the dominant fouling mechanism in the early stage of microfiltration. The decline of permeability caused by pore blocking was simulated in the present model using a reasonable size matching criterion. Membrane with a high porosity and narrow distribution (lognormal distribution) is more effective to decrease the pore blocking and thus increase the permeability. Particle concentration and size distribution influence on the number of particles passing through, adsorbed, and sticking on the membrane pore can be predicted using the model. b value which is related to a number of parameters, including a1, a2, 4, and T, is successfully used to predict the degree of pore blocking at the initial stage. With increasing b value, the mechanism of pore blocking tends to complete pore blocking and the pore blocking mechanism does not change with varying the porosity of membranes. Very good agreements were found between the model and existing theories.
Acknowledgment This research was supported by National Natural Science Foundation of China (50903063) and Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0010353).
references
Aimar, P., 2003. Recent Progress in Understanding Particle Fouling of Filtration Membranes. Proc. IMSTEC‘03 conference, 10e14 November. University of New South Wales, Sydney, Australia, ISBN 0 7334 2089 3. Babu, B.R., Rastogi, N.K., Raghavarao, K.S.M.S., 2006. Mass transfer in osmotic membrane distillation of phycocyanin colorant and sweet-lime juice. J. Membr. Sci. 272, 58e69. Baralla, G., Mattea, M., Gekas, V., 2001. A computer-aided model to simulate membrane fouling processes. Sep. Purif. Technol. 22-23, 489e498. lu, G., Yalc¸ın, E., Arıca, M.Y., 2005. Characterization of Bayramog polyethylenimine grafted and Cibacron Blue F3GA
immobilized poly(hydroxyethylmethacrylate-coglycydylmethacrylate) membranes and application to bilirubin removal from human serum. Colloid Surf. A 264, 195e202. Broeckmam, A., Busch, J., Wintgens, T., Marquardt, W., 2006. Modeling of pore blocking and cake layer formation in membrane filtration for wastewater treatment. J. Membr. Sci. 189, 97e109. Chang, I.-S., Clech, P.L., Jefferson, B., Judd, S., 2002. Membrane fouling in membrane bioreactors for wastewater treatment. J. Environ. Eng. 128, 1018e1029. Chen, Y., Kim, H., 2008. Monte Carlo Simulation of pore blocking and cake formation by interfacial interactions during membrane filtration. Desalination 233, 258e266. Duclos-Orsello, C., Kelly, W.P., Grant, D.C., Zahka, J., Thom, V., 2004. Neutral adsorptive capture of particles by membranes: network modeling near the membrane isoelectric point. J. Membr. Sci. 237, 167e180. Duclos-Oresello, C., Li, W., Ho, C.C., 2006. A three mechanism model to describe fouling of microfiltration membranes. J. Membr. Sci. 280, 856e866. Frey, J.M., Schmitz, P., 2000. Particle transport and capture at the membrane surface in cross-flow microfiltration. Chem. Eng. Sci. 55, 4053e4065. Kawakatsu, T., Nakajima, M., Nakao, S.-I., 1995. Threedimensional simulation of random packing and pore blocking phenomena during microfiltration. Desalination 101, 203e209. Laitinen, N., Michaud, D., Piquet, C., 2001. Effect of filtration conditions and backflushing on ceramic membrane ultrafiltration of board industry wastewater. Sep. Purif. Technol. 24, 319e328. Lim, A.L., Bai, R., 2003. Membrane fouling and cleaning in microfiltration of activated sludge wastewater. J. Membr. Sci. 216, 279e290. Lu, S.-Y., Tsai, C.-M., 2002. Membrane microstructure resulting from deposition of polydisperse particles. J. Membr. Sci. 177, 55e71. Marchese, J., Ponce, M., Ochoa, N.A., Pra´danos, P., Palacio, L., Herna´ndez, A., 2003. Fouling behaviour of polyethersulfone UF membranes made with different PVP. J. Membr. Sci. 211, 1e11. Meier-Haack, J., Booker, N.A., Carroll, T., 2003. A permeabilitycontrolled microfiltration membrane for reduced fouling in drinking water treatment. Water Res. 37, 585e588. Mortensen, N.A., Okkels, F., Bruus, H., 2005. Reexamination of Hagen-Poiseuille flow: shape dependence of the hydraulic resistance in microchannels. Phys. Rev. E 71 (057301), 1e4. Oliveira, R., 1997. Understanding adhesion: a means for preventing fouling. Exper. Therm. Fluid Sci. 14, 316e322. Seminario, L., Rozas, R., Bo´rquez, R., Toledo, P.G., 2002. Pore blocking and permeability reduction in cross-flow microfiltration. J. Membr. Sci. 209, 121e142. Tung, K.-L., Chuang, C.-J., 2002. Effect of pore morphology on fluid flow and particle deposition on a track-etched polycarbonate membrane. Desalination 146, 129e134. Wessling, M., 2001. Two-dimensional stochastic modeling of membrane fouling. Sep. Purif. Technol. 24, 375e387. Yoon, S.-H., Lee, C.-H., Kim, K.-J., 1999. Three-dimensional simulation of the deposition of multi-dispersed charged particles and prediction of resulting flux during cross-flow microfiltration. J. Membr. Sci. 161, 7e20. Zhu, X., Elimelech, M., 1997. Colloidal fouling of reverse osmosis membranes: measurement and fouling mechanism. Environ. Sci. Technol. 31, 3654e3662.
Glossary J: [m3/m2s] permeability J0: [m3/m2s] initial permeability k: [kgm2s2K1] Boltzmann’s constant (1.381 1023) Kp: [s1] system constant related to pore blocking resistance L: [m] length of the pore channel
w a t e r r e s e a r c h 4 5 ( 2 0 1 1 ) 6 7 8 9 e6 7 9 7
MCS: [-] Monte Carlo Step N: [-] number of pore in the membrane Np: [-] number of particle R: [m] radius of pore after fouling Rhyd: [m1s1] hydraulic resistance Rm: [m1] membrane resistance Rp: [m1] blocking resistance Rpart: [m] radius of particle Rpore: [m] radius of pore S: [m2] cross-sectional area of pore T: [K] absolute temperature t: [s] filtration time
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a1, a2: [-] fitted parameter b: [m/m] ratio of particle size to pore size g1, g2: [-] revision of b d: [-] standard deviation of normal distribution dg: [-] geometric standard deviation of lognormal distribution DP: [kgm1s2] transmembrane pressure ε: [m2/m2] porosity of membrane h: [m2s1] dynamic viscosity m: [-] mean of normal distribution mg: [-] geometric mean of lognormal distribution ms: [gm1s1] viscosity of the solution F: [kgm2s2] energy barrier
water research 45 (2011) 6798
Available online at www.sciencedirect.com
journal homepage: www.elsevier.com/locate/watres
Corrigendum
Corrigendum to “Fate of N-nitrosodimethylamine, trihalomethane and haloacetic acid precursors in tertiary treatment including biofiltration” [Water Research 45 (2011) 5695e5704] Maria Jose´ Farre´*, Julien Reungoat, Francois Xavier Argaud, Maxime Rattier, Ju¨rg Keller, Wolfgang Gernjak The University of Queensland, Advanced Water Management Centre (AWMC), Level 4 Gehrmann Bldg, Research Road, Brisbane Qld 4072, Australia
On page 5699 right column, second line, the last sentence of Section 3.1.1 should read ‘below’ instead of ‘beyond’. Therefore the sentence should read as follows: “NDMA and NMOR were detected below LOQ across the plant (i.e., 5 ng/L for NDMA and 10 ng/L for NMOR).”
DOI of original article: 10.1016/j.watres.2011.08.033. * Corresponding author. Tel.: þ61 7 33463233; fax: þ61 7 33654726. E-mail address:
[email protected] (M.J. Farre´). 0043-1354/$ e see front matter ª 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.watres.2011.10.044
