Biosorption and Bioaccumulation in Practice

BIOSORPTION AND BIOACCUMULATION IN PRACTICE

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BIOSORPTION AND BIOACCUMULATION IN PRACTICE

KATARZYNA CHOJNACKA

Nova Science Publishers, Inc. New York

Copyright © 2009 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA

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CONTENTS Preface

vii

Abstract

ix

Chapter 1

Introduction

1

Chapter 2

Biosorption and Bioaccumulation of Toxic Metals: The Fundamentals of the Processes

3

New Research in Biosorption and Bioaccumulation of Toxic Metals

21

Similarities and Differences between Biosorption and Bioaccumulation Processes

25

Brief Information on Analytical Techniques in Determination of Fate of Toxic Metals in Biosorption and Bioaccumulation

29

Using Bioaccumulation in Biomonitoring of Environmental Pollution

31

Using Biosorption and Bioaccumulation Processes in Wastewater Treatment

61

Using Biosorption and Bioaccumulation in Integrated Processes

71

Using Biosorption and Bioaccumulation to Treat Microelement Hunger

75

Conclusion

95

Chapter 3 Chapter 4 Chapter 5

Chapter 6 Chapter 7 Chapter 8 Chapter 9 Chapter 10 References Index

99 123

PREFACE In the present book, various practical aspects related with new applications of biosorption and bioaccumulation are discussed. These natural processes, which concern every living organism and biomass on the Earth, can find an application in pollution control and also in industry. Environmental applications include biomonitoring as the tool of the assessment of not only concentration, but first of all bioavailability of pollutants in the environment. On the other hand, biosorption and bioaccumulation can be used in the treatment of industrial wastewaters containing toxic metal ions. Biosorption and bioaccumulation can be useful in the manufacture of new kind of products – biofortified food. Plant food can be enriched with micronutrients by the excessive fertilization. The content of micronutrients in animal food can be increased by the supplementation of livestock diet with new preparations, consisting of the biomass enriched with microelements by either biosorption or bioaccumulation. This highly bioavailble and non-toxic form of microelements leads to fortification of animal food. The consumption of biofortified plant or animal food in the future should enable substitutition of mineral inorganic diet supplements with natural products. In order to make a practical use of biosorption and bioaccumulation, it is necessary to thouroughly investigate the processes. Since the biomass is involved here, together with complex mechanisms and multiplicity of interactions of metals with the biomass, it is necessary to carry out a thorough research to get to know the process mechanism and also to be able to model it. These aspects were discussed here. This work was financially supported by Polish Ministry of Science and Higher Education (grant No. R05 014 01 and N N204 019135).

ABSTRACT Natural and controlled processes of biosorption and bioaccumulation may be efficiently used in the assessment of environmental pollution as well as in pollution prevention and cleaning the polluted environment. The property that is used in such pollution control processes is the ability of all types of biomasses to bind toxic metals, in different extent though, depending on morphology and physiology of an organism. If the processes are performed at controlled conditions, the efficiency can be greatly improved. If we would like natural processes to work for us, it would be indispensable to understand their mechanism, rules that govern them, we should know how to model their kinetics and equilibrium. Basically, we should be able to predict the course of the processes at given process parameters in order to design a complete technique and to make a practical use of it. Biosorption and bioaccumulation differ when considering the mechanism and for this reason the potential applications will also be diverse. While in the process of biosorption, pollutants are bound to the surface of cellular wall of the biomass, in bioaccumulation contaminants are also transferred into cellular interiors. The latter can affect the metabolic functions of an organism. Biosorption can be performed by non-living biomass (materials of biological origin), but the essential condition for bioaccumulation to occur is that an organism should be metabolically-active. The present work discusses practical aspects of biosorption and bioaccumulation. The processes have the potential to find environmental applications but also in the manufacture of new high value products. Environmental applications include biomonitoring performed by living organisms. The property that is used here is that the level of a given contaminant in biological tissues is related to the concentration of this substance in the environment. This is expressed by the assessment of bioaccumulation factors. This book reports examples of the application of human hair and consumable

x

Abstract

tissues of animals, and various parts of plants (green parts as well as wood) in environmental pollution monitoring. Biosorption as well as bioaccumulation can find an application in removal of contaminants from aqueous solutions. Biosorption by different materials of plant (microalgal biomass, aquatic plants, plant leaves, straw, grass) and animal origin (eggshells, bones) can be applied in industrial wastewater treatment processes. Also, bioaccumulation by aquatic organisms: microalgae, macroalgae and aquatic plants in metal ions removal from effluents can be used to bind metal ions simultaneously with nutrients. Biosorption and bioaccumulation have the potential to be used in the production of plant and animal food biofortified with microelements, which would be used to treat mineral deficiencies in food and feed. Various aspects related with excessive bioaccumulation of micronutrients by plants were discussed. Biofortification of animal food can be achieved by the proper supplementation of livestock diet. A new preparation consisting of the biomass enriched with microelements by biosorption was elaborated. An attempt to make the processes predictable is discussed here, including screening for good biosorbents/bioaccumulators, determining biosorption and bioaccumulation capacity as well as bioavailability as the function of the concentration of metals in the environment in which an organism is present, together with growth requirements, mathematical modeling, carrying out processes at different operational conditions. This should constitute the basis for the assessment of standardized procedures, in the design of biosorption or bioaccumulation treatment plants and for environmental biomonitoring.

Chapter 1

INTRODUCTION Biosorption and bioaccumulation are processes instantaneously performed by all biomasses either living or dead. It is a natural property and the processes are carried out either by purpose or by mistake (toxic metal ions are taken up instead of essential ions). Capacity of the biomass to bind and concentrate toxic metals from solutions may create the fundamentals for a cost-effective technology for detoxification of industrial effluents [1], mainly from mining and electroplating industry or to recover precious metals from processing solutions [2]. The potential uses and mechanisms of biosorption and bioaccumulation for toxic metals control are shown in Figure 1. Biosorption and bioaccumulation are significant stages of toxic elements cycles in the environment. Thanks to these processes, metals can be transferred from e.g., aquatic environment and become concentrated in bottom sediments.

Figure 1. Binding of metal ions by the biomass.

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These phenomena have been used for decades in conventional biological wastewater treatment plants in which scattered soluble impurities (nutrients, toxic metals and organic compounds) are transferred from dilute soluble form into concentrated, condensed several fold in the biomass of activated sludge with the simultaneous use of processes of biosorption, bioaccumulation and biodegradation. While organic pollutants can be processed by the biomass with the use of all three processes, metal ions can only be utilized with biosorption and bioaccumulation – biodegradation is not possible. The advantage of activated sludge method is that the impurities become concentrated and transferred into solid state that facilitates their utilization. The other practical aspect of the discussed processes is environmental pollution monitoring which bases on known bioaccumulation behavior of metals and organisms [3]. It has been observed that the concentration of toxic metals in biological tissues reflects their concentration in the environment over extended period of time. This theory created the fundamentals for biological monitoring – a technique that determines not only the degree of environmental pollution but also investigates bioavailability of toxic elements from the surrounding environment to living organisms and assessment of the risk posed by these contaminants.

Chapter 2

BIOSORPTION AND BIOACCUMULATION OF TOXIC METALS: THE FUNDAMENTALS OF THE PROCESSES 2.1. TOXIC METALS A term “heavy metal” is commonly used to describe metals that are toxic. However, the term is rather used in causal language and has never been defined by any authority i.e., IUPAC [4]. There are numerous definitions of “heavy metals” classifying according to certain physical, chemical or biological properties, including density (specific gravity), atomic weight and number, other chemical properties, definitions without a clear basis other than toxicity or nonchemical definitions [4]. The majority of definitions have no relation with toxicity of these metals to living organisms since in fact no relation between density and atomic/molecular weight and toxicity has been observed [4]. In the present chapter, toxic metals are understood to be elements (not only metals) commonly used in industry and generally toxic to living organisms even at low concentrations [1], including As, Cd, Cr, Cu, Pb, Hg, Ni, Se, Zn [5]. Se and As are frequently named with a term “heavy metal” although these elements are not metallic [6]. However, when considering toxic properties, they are classified to the same group, similarly as the remaining toxic elements, and are named toxic metals [6]. It is always questionable whether a given element should be considered as toxic. There are metals that play only harmful role in living organisms, through enzyme inhibition or activation, damage of subcellular organelles, carcinogenicity, and effects on kidneys, nervous system, endocrine system, reproduction, and respiratory system [7]. They do not play any positive function

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in living organisms. This is so-called toxic trio that includes Hg, Pb and Cd – the mostly toxic elements used by the industry [8]. Another group includes metals that are needed for the proper functioning of an organism, in low quantities, but simultaneously at elevated levels are toxic [9]. In some cases the difference between essential and harmful concentration is very narrow (such as in the case of selenium). Sometimes, oxidation degree determines toxicity and essentiality of a given metal, e.g., Cr(III) is considered to be microelement, but Cr(VI) is toxic (carcinogenic) [6]. The presence of toxic metals in the scattered and bioavailable form in the environment is highly undesirable. Metals occur in nature in rocks, ores, soil, water, air in naturally low levels and in dispersed form [7]. We should bear in mind though that the total amount of toxic metals such as the majority of other elements present on the Earth has remained and will remain constant. The problem that arose with the industrialization was that metals were mobilized from their deposits (the forms that were not available to living organisms) by anthropogenic activity (making utensils and machinery, mining, smelting, welding, grinding, soldering and printing [7, 9]) and were transferred into bioavailable form and redistributed in such form in the environment [7]. Metals have been mainly mobilized by the branches of industry such as mining and metallurgy [10] and are generally commonly used by industry, agriculture and medicine [7]. The result was that toxic metals began to cycle in ecosystem at elevated concentrations between its biotic and abiotic components and also in the trophic chain becoming concentrated on the top of it in organisms of final consumers, frequently in human body [1]. Because it is impossible to degrade toxic metals, the only method of utilization is safe disposal – immobilization in a solid state and concentration into the form that will not undergo biological cycles and will be basically not available to living organisms [1]. Since the presence of toxic metals in the environment is not desired, their emission by the industry is regulated by law. Recently, environmental law has become more stringent (Table 1) [11]. It is difficult to employ conventional methods to remove metal ions below the level of “ppm’s” since these methods if applied at such low concentrations cause that the methods become expensive and highly energy consuming [11]. These disadvantages of conventional technologies created the need to elaborate a new generation of efficient methods of environmental prevention (intervening at the impact source, in advance of pollutant event), protection (elimination of the effects of pollutant actions or minimization of these effects) and restoration (removing damages caused by previous actions) [12], as well as monitoring [9].

Biosorption and Bioaccumulation of Toxic Metals

5

Table 1. The levels of contaminants in raw effluents, maximum admissible concentration of contaminants in effluents and drinking water (American and European regulations) [mg/L] Metal ion Ag Al As Ba Be Cd Co Cr (total) Cr(VI) Cu Fe Hg Mn Ni Pb Sb Se Sn Th Zn

Domestic wastewater1 0.003-0.01 0.25-1 0.001-0.005

0.001-0.004 0.0005-0.002 0.01-0.004 0.03-0.1 0.4-1.5 0.001-0.003 0.04-0.15 0.01-0.04 0.025-0.08

Wastewater discharge limits European2 American3 0.1 1

Drinking water standards European4 American5

0.1 2

2

0.05 0.05

0.1-0.2 1 0.5 0.1 0.5

1

0.005

0.05 2 0.004 0.005

2

0.05

0.1

0.05

5 100 0.05

0.5 0.5

5 2

1 2

1.3 0.001

0.002

0.05 0.05 0.01 0.01

0.1 0.015 0.006 0.05 0.0005

0.08-0.3

2

5

1

Typical content of metals in domestic wastewater [13]. German requirements for the effluent concentrations in direct discharge into receiving water and indirect discharge into municipal sewers considered dangerous [14]. 3 Wastewater discharge limits (U.S., EPA); pretreatment standards [15]. 4 NPDW (national primary drinking water) regulations for inorganic chemicals MCLG (maximum contaminant level goal) [16]. 5 European Economic Community Standards (maximum admissible concentration) [17]. 2

2.2. BIOSORPTION Biosorption is defined as the ability of materials of biological origin to bind e.g., toxic metals to the surface of cellular wall or membrane in the equilibrium process (Figure 2). More recently, it has been discovered that biosorption is the interaction between metal ions and functional groups present on the cell wall biopolymers of dead organisms [18].

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Figure 2. Biosorption of metal ions.

That is why, biosorption can be classified as a typical adsorption process. There are various classes of biosorbents: by-products or waste materials (with an intermediate sorption capacity), naturally grown and collected biomass [10, 19] (that is practically of no cost) and especially propagated biomass (with high sorption capacity and a possibility to become recovered [19] (e.g. Spirulina [20])). Biosorbents are materials of biological origin that can bind metals and organic compounds. Biosorbents can be of microbial, fungal, seaweed, plant or animal origin [21]. Practically, each type of biomass possesses metal-binding properties. This is determined by the chemical structure of biomolecules that all expose similar functional groups. Of course, there are differences in metal-binding capacities and binding mechanisms between sorbents. Fundamental for the complete design of the process is investigation of the mechanism. The reported mechanism of biosorption is very complex (a combination of ion-exchange, physical adsorption, surface complexation and surface microprecipitation [10, 21-23]), such as diverse is the structure of biological materials [10]. In the past, physical adsorption was thought to be the dominating mechanism. However, recent studies [2, 24-45] showed that the mechanism is similar to ion-exchange process with the functional groups (amino, carboxyl, phosphate, sulfate, hydroxyl groups) exposed by the cellular wall, which is composed mainly of polysaccharides, proteins and lipids [46], and for this reason biosorbents can be considered as weak acidic cation-exchangers [47-48]. Protons and metal cations are released from the biomass, and cations of other metal ions become bound by cellular surface [49]. Therefore, the biomass acts as organic polyelectrolyte. In the process, metal ions compete with protons for the binding sites [46] and hence pH is probably the mostly important process

Biosorption and Bioaccumulation of Toxic Metals

7

parameter. Since the biomass is not uniform and chemically defined material, there are some difficulties in modelling the process in terms of ion-exchange [18]. Recent literature reports that biomaterials can be characterized in terms of acidbase and metal based potentiometric titrations, used in studies of organo-metallic complexes [18]. Biosorption is a metabolically-passive process [2], which means that there is no need for the biosorbent to carry out metabolic functions during biosorption. For this reason, non-living biomasses are used. Process involving toxic metals and non-living biomass is much easier and cheaper since keeping biomass alive requires expenditures of nutrients and energy. Also, toxic effects that might be potentially posed by these metals can be avoided. The mostly important process parameters include concentration of metal ions and the biomass, temperature, contact time, agitation and pH. The latter influences three significant parameters, such as speciation of metal ions and their solubility, as well as surface properties of the biomass [11]. The process may find a practical application only if its mechanism, process parameters, kinetics and equilibrium are known. Only then it will be reliable, predictable and possible to design and control [2]. In modeling of biosorption and bioaccumulation processes similar simplifications are used as in the case of microbial growth modelling (which is simplified to single enzymatic reaction). Biosorption is a quick process. The equilibrium is usually reached within few minutes. Since the rate of the process is high, in some cases it is even difficult to select and fit the proper equation and to determine the order of the reaction due to errors related with quick sampling. The process is usually described with either first- [50], second- [51], pseudo-first- [52] or pseudo-second [52-53] order kinetic equation. The reaction order is related with the mechanism of biosorption, which is the most frequently ion exchange or surface precipitation (metal hydroxide, sulfide or carbonate) [54]. Literature reports that the rate limiting step is chemisorption which involves valent forces by sharing or exchange of electrons between sorbent and sorbate [54-55]. In kinetics modeling, Lagergren pseudo-first order and pseudo-second order models are used [56]:

ln

qeq − qt qeq

= − k1t , k1 (1/min)

t t 1 , k2 (g/(mg min)) = + 2 qt k 2 qeq qeq

- assumes that metal cation binds only to one sorption site on the sorbent surface: R(s)+ Me2+(aq)=RMe2+(ads) - metal cations are bound to two binding sites on the sorbent surface 2R(s)+ Me2+(aq)=R2Me2+(ads)

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Katarzyna Chojnacka

The equilibrium of biosorption can be described with either Langmuir [26, 57-98] or Freundlich [57-59] model (Figure 3). In studies on sorption behavior, both capacity and affinity of a given sorbent to sorbate are investigated [2]. If the dominating mechanism is ion-exchange, which means that a biosorbent possesses a finite number of cations binding sites, we can observe a plateau on isotherm graph. The equilibrium can be described with Langmuir equation, since it is more suitable for description of chemisorption process. It was observed that biosorption is usually a reversible process. It is possible to remove bound metal ions with weakly acidic solutions or with strong brine and thus to recover the biomass such as in classical cation-exchange process. Through the selection of the proper eluents, it is possible to restore biosorption properties of biosorbent and reuse it another biosorption cycle [60-61].

Freundlich

qeq

Langmuir

Ceq Figure 3. A comparison of Langmuir and Freundlich models.

Multi-component biosorption Biosorption is influenced by both: surface properties of the biomass and physicochemical parameters of the solution (pH, ionic strength, temperature, biomass concentration, presence of organic and inorganic ligands in the solution

Biosorption and Bioaccumulation of Toxic Metals

9

[62]. The majority of works devoted to biosorption is carried out in single-metal system and single-metal isotherms are plotted. This is, of course, idealistic approach. In real systems, if real effluents are treated, a multiplicity of various ions is present in the solution. Under those conditions, predicted biosorption performance in single metal experiments does not comply with the performance in real systems, due to the presence of competitive phenomena and multiplicity of interactions. Competition between metal ions hinders observed sorption capacity. Usually, the biomass binds cations selectively – some ions are preferred over the other [63]. A lot of further research needs to be done in order to elaborate a uniform approach to multi-metallic biosorption. Only then the process will find an application in practice. In biosorption process, the following equilibrium reactions take place in the solution [54]:

R 2− + M 2+ ⇔ MeR at low pH protons compete for the binding sites:

R 2− + 2 H + ⇔ H 2 R A possible approach in modeling is to measure the ratio between the maximum biosorption capacity in multi-metal system to single metal system at different pH [54]. In multi-metal systems, interaction between particular cations for the binding sites is observed [64]. Also, internal competition (competition between cations of the same type) occurs as well as competition between metal cations and protons [54]. Biosorption performance in multi-metal systems depends on variety of factors: the number and the type of competing metal ions for the binding sites, metals combination, concentration, the type of biosorbent. Also, the type of interactions vary and can be either synergistic, antagonistic or none [64]. The biomass possesses different selectivity towards various metal cations. This selectivity depends on the type of the biomass, the composition of the solution, physicochemical conditions [62]. This makes it difficult to elaborate a universal model describing multi-ion biosorption. Generally, it is impossible to predict biosorption performance in multi-metal system theoretically. Although, some attempts in the literature have been made to forecast biosorption on the basis of known Langmuir isotherms determined in single-metal system [64]. In the majority of cases an approach includes the use of isotherm model parameters determined in single-metal system and correction factors evaluated in multi-metal system experiments, which are characteristic for a given cation and depend on the concentrations of other species in the solution [62].

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Modeling biosorption in multi-metal system Recently, many efforts have been made in the literature to elaborate a universal model which would describe multi-component biosorption well. This is required to transfer the process into industrial scale, to be able to design and predict a continuous process, adsorbent selectivity in multi-metal systems, to carry out the process in continuous fixed bed columns after immobilization in a polymeric matrix [65]. Usually, simple extensions of classical isotherms are used. However, it is necessary to take into consideration that these models do not predict, but only correlate the model with the experimental data [66]. Generally, competitive isotherms describing multi-component biosorption are classified according to their relationships with single component isotherms [67]: 1. competitive Langmuir/Freundlich models are related only with individual parameters of isotherm 2. modified competitive Langmuir/Freundlich models are related with both: individual parameters of isotherm and correction factors A model better fits experimental data if coefficients from experimental competitive isotherms were included [67]. The model parameters can be determined by nonlinear least-squares regression. Multi-metal isotherms found in the literature are presented in Table 2. The constants qmax and b are derived from individual isotherms, η is multicomponent Langmuir constant; Qmax and B determined from multicomponent experiments; N- total number of metals in the system. Predictive models do not require fitting to data from multi-component systems. All parameters are determined from single-metal isotherms [69]. Consequently, these models frequently fail to describe multi-metal biosorption data well. The assumption of multi-sorbate Langmuir model is that sorption does not involve competition. Competitive models, though assume the presence of other metals in the solution which affect only the apparent affinity for the active site. The shape of the isotherm changes if other metal ions are present in the solution. However, the maximum biosorption capacity does not change [70]. In this case, the model proposed by Jain and Snoeyink [70] is used.

Table 2. Different Langmuir and Freundlich-type equations used in modeling multi-metal biosorption Model

qi ,eq =

qmax,i bi Ci ,eq N

1 + ∑ b j C j ,eq j =1

qmax,i bi qi ,eq =

qi ,eq =

Ci ,eq

ηi

N

C j ,eq

j =1

ηj

1 + ∑ bj

Qmax,i Bi Ci ,eq N

1 + ∑ B j C j ,eq j =1

Name

Decription Equations based on Langmuir model the predictive derived from corresponding individual Lanmguir isotherms; assumes competitive the same selectivity, uniform surface and that all cations compete for Langmuir the same binding sites without interaction nor competition between model ions; qmax is determined from single metal system and theoretically should be the same for all metal cations; if qmax differs, this means that binding sites are not homogeneous and are specific towards metal cations; but this is not consistent with the basic assumption of Langmuir equation; if sorbent shows heterogeneity, then affinity should differ empirical beside mono-component coefficients, additional competition extension coefficients are determined from experimental multi-metal data; nonLangmuir ideal competition between sorbates is assumed; the model is more model flexible and represents complexity of multi-metal system; qmax is general for various multi-component systems Langmuir model

all parameters are determined by fitting to multi-component equilibrium data

Ref. [65, 68-69]

[62, 65, 69]

[65]

Table 2. (Continued) Model

qi ,eq =

Name Langmuir model with general total binding capacity

qmax,Total bi Ci ,eq N

1 + ∑η j b j C j ,eq j =1

qi ,eq =

qmax,i bi Ci ,eq N

extension LangmuirFreundlich model

ni

1 + ∑ b j C j ,eq

nj

j =1

qi ,eq =

(qmax,i − q max, j )bi Ci ,eq 1 + bi Ci ,eq

+

q max, j bi Ci ,eq N

1 + ∑ bjC j ,eq j =1

qi ,eq =

K F Ci ,eq N

n

nj

j =1

K F ,i Ci ,eq

qi ,eq = Ci ,eq

ni 1

N

ni0 + ni 1

+ ∑ K F , ij C j ,eq j =1

(qmax,i − qmax, j ) -

the fraction of ions which adsorb without

nij

empirical extension Freundlich model

Ref. [69]

[66]

[70]

competition

qmax, j - the fraction of ions which adsorbs with competition

Equations based on Freundlich model the predictive KF,i and ni are determined from individual Freundlich isotherms; competitive Freundlich model

ni + n1

Ci ,eq 1 + ∑ b j C j ,eq

Decription general total binding capacity (qmax,Total) and additional correction coefficients (η) are used in this isotherm; the total binding capacity is the same for all the cations and can be determined by potentiometric titration (total active site concentration or total cation exchange capacity); total metal uptake at given pH is constant for all the cations; if pH decreases, binding capacity also decreases; all the cations compete for the same binding sites artificial neural networks were used to solve this equation

KF,ij, nij are correction coefficients determined in multi-metal system

[62]

[62]

Biosorption and Bioaccumulation of Toxic Metals

13

According to the literature [69] the best model for the description of multimetal biosorption is simple competitive Langmuir equation with additional correction coefficients. This makes the model flexible. There was also found a completely different approach to modeling biosorption in multi-metal systems. Ma and Tobin [71] suggested that oxygen containing functional groups act as metal binding sites. Ion exchange and surface complexation were the dominating mechanisms. This can be understood as the explanation of selectivity order. Selectivity should differ as the affinity constants of metal cations to the binding sites differ. Biosorption followed the following reactions and equilibria [71]:

R − + H + ⇔ RH

KH =

αR − + M 1α + ⇔ Rα M 1

[ R − ][ H + ] [ RH ] α+

βR − + M 2 β + ⇔ Rβ M 2

K M1 =

[ R − ]α [ M 1 ] [ Rα M 1 ]α

K M2 =

[ R − ]β [ M 2 ] [ Rβ M 2 ] β

β+

χR − + M 3 χ + ⇔ R χ M 3

χ+

K M3

[ R − ]χ [ M 3 ] = [ Rχ M 3 ] χ

The total number of sites can be expressed with the following equation:

[R ] = [R ]+ [RH ] + α1 [R M ] + β1 [R M ]+ χ1 [R M ] −

T

−

α

1

β

2

χ

3

The above set of equations can be used to model multi-model biosorption. The uptake of metal ions is related with its hydrolytic properties:

HO − H + M n+ ⇔ M ( OH )( n−1 )+ + H + and also with interaction among metal cations and the protonated site:

R − H + M n+ ⇔ R( M )( n−1 )+ + H + If metal is very acidic (which can be evaluated by determination of the ratio

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Katarzyna Chojnacka

charge:mass), then the metal cation binds more easily with a protonated site, when related to weaker acidic metal cation [69]. For this reason, the most acidic ion is less affected by the presence of other less acidic ions and influences their binding the mostly. Consequently, the values of hydrolysis constants describe the following selectivity order: Pb(II)>Cu(II)>Zn(II)>Cd(II) [69].

State-of-the-art in research on multi-metal biosorption Ma and Tobin [71] carried out biosorption of Cr(III), Cu(II) and Cd(II) cations onto peat moss. It was found that the selectivity order was as follows: Cr(III)>Cu(II)>Cd(II). Mohapatra nad Gupta [72] investigated concurrent biosorption of Zn, Co and Cu by Oscillatoria angustissima in binary and ternary system. In single metal system, the following selectivity order was identified: Zn>Co>Cu. In binary system: Cu(II)>Zn(II), Cu(II)>Co(II), Zn(II)≈Co(II). The domination of Cu(II) was found. In ternary system, Co(II) protection against inhibitory effect of Cu(II) on Zn(II) was found. Inhibitory effect of Zn(II) and Cu(II) on Co(II) was additive. While it was achievable to model binary system, the problems were encountered in modeling ternary system [72]. Mehta and Gaur (2001) proposed the use of two-dimensional contour plots. But those were confined only to binary systems. It is also possible to propose triangular graph, which would be useful in modeling biosorption in ternary system. Such equilibrium diagrams were proposed by Sag et al. [73]. In biosorption in ternary system at equal initial molar concentrations of metal ions in the solution, the relative surface coverage of the biomass was 45-55 % for Cr(VI), 36-41 % for Fe(III) and 8-14 % for Cu(II). Sag and Kutsal [64] studied competitive biosorption of Cr(VI) and Fe(III) in binary system by a filamentous fungus Rhizopus arrhizus. This was investigated as the potential method of wastewater treatment. The results were described with competitive Langmuir model. Sag et al. [67] carried out work on biosorption of Cu(II) and Zn(II) in binary metal mixtures by the same fungus. The results were described with competitive Freundlich model. Pagnanelli et al. [62] investigated selectivity of the biomass towards Cu(II) and Cd(II) in binary solution. The biomass was more selective towards Cu(II) and the selectivity changed with pH. The same authors [69] found that low pH masks the competition between metal ions for the binding sites, which is another proof that biosorption phenomenon is related with ion exchange. In this work biosorption by Sphaerotilus natans in various binary systems (Cu-Cd, Cu-Pb, Cu-Zn) at different pH was investigated. Cu(II) uptake was strongly influenced by increasing Pb(II) concentration, while the influence of Cd(II) was much weaker. In another study, where the experiments

Biosorption and Bioaccumulation of Toxic Metals

15

were carried out in ternary system, Pagnanelli et al. [65] identified a typical selectivity order for ternary system: Pb>Cu>Cd. Sun et al. [54] carried out biosorption in binary solutions containing Co(II) and Zn(II) ions on aerobic granules. Biosorption of Co(II) was quicker than of Zn(II). The mechanism of biosorption investigated in this study was binding to the functional groups (carboxylate, alcoholic). The groups were identified by using FTIR and XPS techniques. Chen and Wang [74] used also instrumental techniques: FTIR (Fourier Transformed Infrared Spectroscopy), SEM (Scanning Electron Microscopy), TEM (Transmission Electron Microscopy) to identify the mechanism of biosorption. Resulting, the possible mechanism was ion exchange, chelation and microprecipitation [75-76]. Chen and Wang [74] studied how ionic characteristics of various cations influence their biosorption properties. A quantitative structure activity model for biosorption of 10 metal cations to Saccharomyces cerevisiae was proposed. Physicochemical parameters (22) were correlated with the maximum biosorption capacity of a given cation. The mostly important parameter was covalent index: the higher index, the higher potential to form covalent bonds with biological ligands (thiol, amino, carboxyl, hydroxyl groups). However in the study of Tobin et al. [77] the most significant physicochemical parameter which influenced biosorption capacity was ionic radius. The following selectivity order of maximum biosorption capacities were proposed (expressed as meq/g): Pb(II)>Ag(I)>Cr(III)>Cu(II)>Zn(II)>Cd(II)>Co(II)>Sr(II)>Ni(II)>Cs(I) [74]. Saeed et al. [78] investigated removal of Cd, Cu, Ni and Zn by a crop milling agro-waste (black gram husk) in single, binary and ternary systems. Selectivity order determined in this study was similar and was as follows: Pb(II)>Cd(II)>Zn(II)>Cu(II)>Ni(II). The presence of Pb(II) did not significantly affect sorption of other metal cations. The authors also managed to completely desorb metal cations from the biomass by 0.1 M HCl [78].

2.3. BIOACCUMULATION Bioaccumulation is the process in which toxic metals or organic compounds become bound within the inner cellular structures. According to the definition [79], bioaccumulation is the process by which living organisms absorb and retain chemicals or elements from their surrounding environment. Other definitions say that bioaccumulation is the accumulation of a chemical either from a medium (usually water) directly or from the consumption of food containing the chemical

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[9]. Bioaccumulants are substances the concentration of which in living organisms increases as they are taken up from contaminated air, water or food [79]. The critical condition for bioaccumulation to occur is that the biomass should be alive. Bioaccumulation can be performed only by metabolically active cells [2] and therefore the process is metabolically controlled [79-81]. All living organisms throughout their lives accumulate essential, non-essential and toxic substances. All living beings developed pathways that protect them either from an excessive bioaccumulation (e.g. routes through which bioaccumulant enters an organism is blocked or bioaccumulant is excreted outside of an organism) or bioaccumulant is safely deposited within the cell to prevent incorporation into metabolic reactions (e.g. metal ions are bound by special chelating proteins that are rich in thiol groups, so-called phytochelatins in algae or metallothioneins [82]). For simplification, bioaccumulation can also be described as absorption of metal ions by whole cells (not only by cellular surface as in biosorption). The route through which a bioaccumulant enters an organism is usually the same through which it takes up nutrients or food. In unicellular organisms, toxic metals enter through the transport channels, usually erroneously with essential elements (e.g. Ca(II) or Mg(II)). In plants, some toxic metals are transported from water and soil through the root system, some are acquainted foliarly (from atmospheric deposition) [83]. The route of transfer also depends on which environment is the mostly polluted with a given metal: water, soil or air. In animals, the routes through which toxic metals are bioaccumulated are mainly alimentary tract (food and water contaminated with toxic metals), but also from respiratory system (from polluted air) and through skin (contact exposure) [84]. In some cases the route of bioaccumulation determines toxic effect and protective response that is activated. Bioaccumulation can find a dual application in pollution control. It can be used to monitor environmental pollution, since there is a correlation between bioaccumulation capacity (the concentration of metal in the biomass) and the concentration in the environment in pollution prevention (wastewater treatment) [85-90] and in cleaning the environment (soil remediation by bioaccumulating plants – so-called hyperaccumulators) [91]. If a method of environmental monitoring is elaborated, it is necessary to screen for good bioaccumulators – biomonitors [92-93]. The analysis of such biomass on the basis of known correlation between the level in the environment and biological material, enables to measure the concentration of a given pollutant in the environment (Figure 4). The mostly advantageous would be to find such biomonitors, the analysis of which would be non invasive nor painful to sample and would not cause any damage to an organism. An example of such biomonitor is human hair or fingernails.

Cbiological tissue

Biosorption and Bioaccumulation of Toxic Metals

17

bioaccumulation factor

Cenvironment Figure 4. Correlation between the level of contaminant in environment and in biological tissues.

The use of cosmopolitan organisms to monitor bioavailability of a given contaminant enables comparison of contaminants levels in different geographical regions. There are two types of bioaccumulating organisms distinguished: bioindicators that are used for identification and qualitative determination of environmental pollution and biomonitors that are used for quantitative analysis of contaminants. In the latter group, sensitive (optical type - morphological changes are observed) and accumulative biomonitors (ability to store contaminants is assessed) are distinguished. Also, the route of absorption may influence the subsequent distribution of the metal within the body [3, 12]. For instance in human, bioaccumulation occurs through inhalation, oral ingestion and dermal exposure [3]. Bioaccumulation itself is the result of the equilibrium of biota intake and discharges from and into the surrounding environment [12]. The process depends on many factors: availability of elements, characteristics of an organism (species, age, state of health etc.) and parameters, such as temperature, available moisture, substrate characteristics, climatic factors, frequently being also parameters that influence metabolic functions of an organism [12]. Therefore, there are difficulties to elaborate standardized procedures and obtain reference values.

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Quantitative biomarkers are used to identify toxic responses in populations exposed to very low concentrations in the environment [94]. Monitoring is the repetitive observation for defined purposes using comparable and standardized methods [95]. Thus, it is very important to elaborate standardized procedures that would enable to monitor environmental pollution on the basis of analysis of contaminants levels in biological tissues. Recently evolved, so-called bioaccumulation monitoring is the exposure assessment by measuring contaminant level in biota [95]. Since living organisms bioaccumulate toxic metals from the environment, their concentration in biological tissues is related with the concentration of a given pollutant in the environment in which they live and with the length of their life. The concentration of bioaccumulant in the biomass, when related to its concentration in the environment (bioaccumulation factor) (Figure 4) [96-97], is the measure of bioavailability of a given metal from the polluted environment in an organism of a given species. It was observed that the higher organization level an organism possesses, the more perfect protective system preventing bioaccumulation or excreting bioaccumulant it would have. E.g. in human body metals become concentrated in keratinous materials: hair or fingernails that are indicators of longterm exposure [3]. Basically, the lower organism is, the higher bioaccumulation capacity it possesses. Therefore, if we would like to employ bioaccumulation process as a method of toxic metals removal from the environment, it would be the mostly advantageous to employ the smallest and the mostly primitive organisms – microorganisms since they have the highest bioaccumulation capacity [19]. In bioaccumulation, two distinctive processes can be distinguished (Figure 5). In the first step, metal ions are bound to the surface of cells – the process is metabolically passive, it is identical with biosorption. In the second stage, metal ions are transported into the cellular interior. In order to perform this stage, cells must be metabolically active. In another stage, if nutrients are available, the concentration of the biomass increases. More metal binding sites and cellular interiors are available to metal ions. This enables to bind more metal ions when comparing with biosorption.

Biosorption and Bioaccumulation of Toxic Metals

Figure 5. The stages of bioaccumulation of metal ions.

19

Chapter 3

NEW RESEARCH IN BIOSORPTION AND BIOACCUMULATION OF TOXIC METALS The recent research on biosorption focuses mainly on removal of toxic metals commonly used in industrial processes, such as Cu [48, 85, 88, 98-102], Cd [18, 48, 100, 103-106], Pb [18, 48, 100, 103, 107-109], Cr [53-54, 57, 81], Zn [52, 99], Ni [110] (Figure 6). There are few studies devoted Hg [104], Al [57] and Co, As, Th. In bioaccumulation literature concentrates mainly on Cd [97, 109, 111-112], Cu [80, 109], Hg [109], Pb [109], Cr [109], Zn [111], As and Ni (Figure 6). Currently studied sorbents include: aerobic [8, 50] and anaerobic [110] granular biomass, bacteria (Sphaerotilus natans [12, 21, 82], Pseudomonas putida [99]), microalgae (Chlorella vulgaris [98], Microcystis aeruginosa [104]), macroalgae ((Gelidium) and algal waste [101, 103], Sargassum muticum [106]) fungi (Cephalosporium aphidicola [108], Rhizopus arrhizus [46, 58], Neurospora crassa [100]), biological products (extracellular polysaccharide (Pestan) produced by fungus Pestalotiopsis [107] and other fungal by-products (Botrytis cinerea) [105], cellulose/chitin bed [113], chaff [114]). Trends in current research include studies on kinetics [50, 52, 108] and equilibrium [12, 21, 51, 53, 102-104, 108], influence of pH [8, 38, 101], ionic strength [12, 21, 101-102] and temperature [101], including modelling [12, 21, 24, 51, 102-103]. Reports contain investigation of biosorption in single- and multi-metal systems [98]. A particular attention is paid to identification of the mechanism of the process [113], including i.e., metal-based potentiometric titration [19, 46]. Also, some modifications (pretreatments) of the biomass are tested [80], i.e., protonation [106]. The new process configurations are also studied extensively, including carrying out the process in membrane bioreactors [12]. Bioaccumulators that are currently studied include: bacteria (genetically engineered Escherichia coli [86]), yeasts (Kluyveromyces marxianus [88]),

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microalgae (Chlorella kessleri [114]), plants (grass Dactylis glomerata [115]), aquatic plants (Lemna minor) [85], aquatic animals (Baikal seal (Phoca sibirica) [116], scleractinian coral (Stylophora pistillata) [117], tube worm Riftia pachyptila [109], soft tissues of mollusks Patella aspera [118] and zebra mussel (Dreissena polymorpha) [119], mangrove oysters (Crassostrea rhizophorae) [92], amphibian larvae [120], marine fish [89, 111], freshwater fish (European eel Anguilla anguilla [121]), multispecies monitoring of muscle tissue of fish [122]), terrestrial animals (earthworm Lumbricus terrestris [123-124], animals (rats [125126]). Th 0.3% As 0.3% Co 0.4% Al 1% Hg 3% Ni 9%

Cu 25%

Zn 12%

Cr 14%

Cd 18% Pb 17%

As 5%

a)

Ni 3% Cd 23%

Zn 10% Cr 10%

Cu 18% Pb 14% Hg 16%

Figure 6. Current trends in research in biosorption (a) and bioaccumulation (b).

b)

New Research in Biosorption and Bioaccumulation of Toxic Metals

23

The majority of studies concern environmental monitoring of aquatic environment with the use of bioaccumulating aquatic animals: invertebrates and vertebrates. Recently appeared also reports on monitoring by terrestrial plants and animals, including human (assessment of exposure by the analysis of hair and fingernails) [6]. Toxicity tests using metals bioaccumulation usually are performed on rats. New research on bioaccumulation focuses on: monitoring of pollution of aquatic environment through the analysis of levels of toxic metals in tissues of aquatic organisms [109, 111, 120, 121-122], wastewater treatment [85-86, 88-89], bioaccumulation by plants grown on contaminated soils [115], bioaccumulation of metals from wastes by earthworms [124], inhalation toxicity tests by rats [125], effect of the presence of one metal on the accumulation of other toxic metals [111], the effect of solubility of toxic metals salts on their bioavailability [124], the assessment of relationship between bioaccumulation of toxic metals with environmental conditions and genetic variability [82], analytical studies on bioaccumulation of toxic metals in biological tissues [126].

Chapter 4

SIMILARITIES AND DIFFERENCES BETWEEN BIOSORPTION AND BIOACCUMULATION PROCESSES When comparing biosorption and bioaccumulation processes, bioaccumulation although performed in simpler installations, requires troublesome cultivation of the biomass in the presence of contaminants that may pose toxic effects to the biomass itself. The difference between the equilibrium of biosorption and bioaccumulation process is shown in Figure 7.

qmax

Bioaccumulation

q

external

(mg/g)

Biosorption

C0

Ceq (mg/kg)

Figure 7. Equilibrium shift towards lower values of Ceq in bioaccumulation process when comparing with biosorption.

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Biosorption itself is the first stage of bioaccumulation. In the second stage, ions are furtherly transferred into cellular interior that results in the equilibrium shift towards lower concentration of metal ions. Table 3 discusses the differences between biosorption and bioaccumulation processes. Table 3. The comparison between biosorption and bioaccumulation process Biosorption Passive process Metals are bound with cellular surface Adsorption Reversible process Biomass is not alive Nutrients are not required Single-stage process The rate is quick Not controlled by metabolism No danger of toxic effect No cellular growth Intermediate equilibrium concentration of metal ions

Bioaccumulation Active process Metals are bound with cellular surface and interior Absorption Partially reversible process Biomass is alive Nutrients are required Double-stage process The rate is slow Controlled by metabolism Danger of toxic effects caused by contaminants Cellular growth occurs Very low equilibrium concentration of metal ions

Biosorption is an equilibrium process. The efficiency of biosorption is expressed in terms of biosorption capacity, which is the mass or molar equivalent of metal bound by the unit mass of a biosorbent [mg/g or meq/g]. The basic characterization of a biosorbent includes evaluation of maximum sorption capacity (qmax) and affinity (b parameter in the case of Langmuir equation). The mostly advantageous in the case of both bioremoval and biobinding would be for a sorbent to have simultaneously high sorption capacity and affinity. In Figure 8 there are shown sorbents with different characteristics. Sorbent 1 possesses high affinity and high maximum binding capacity. This is the best sorbent. Sorbent 2 possesses high maximum sorption capacity but low affinity. Sorbent 3 – high sorption affinity but low maximum sorption capacity and sorbent 4 – low affinity and low maximum sorption capacity. The latter sorbent possesses the worse characteristics. In bioremoval processes of particular importance is affinity of a biosorbent. This is related with the potential applications of this process as polishing treatment in order to reduce the concentration of pollutants below the acceptable limits.

Similarities and Differences Between Biosorption and Bioaccumulation... 27

1

qeq

2 3 4

Ceq

Figure 8. Isotherms for different types of sorbents.

For this reason the mostly desired characteristic would be high affinity of sorbent to sorbate, which is low equilibrium concentration of pollutant reached even at low equilibrium sorption capacities. Therefore, it is recommended to use sorbent possessing characteristics such as material 1 and 3 (Figure 8). If we are interested in other than bioremoval applications – biobinding (e.g. production of bioavailable feed supplements), of the primary importance would be the highest maximum sorption capacity since the goal is to bind possibly high quantities of metal ions by a unit of the biosorbent biomass. In this case it is recommended to use either sorbent 1 or 2.

Chapter 5

BRIEF INFORMATION ON ANALYTICAL TECHNIQUES IN THE DETERMINATION OF FATE OF TOXIC METALS IN BIOSORPTION AND BIOACCUMULATION Analytical techniques used in studies on biosorption and bioaccumulation processes should be very sensitive in determination of elements on the level of even ng/kg and should minimize interferences and matrix effects. These include modern instrumental techniques, such as atomic absorption spectrometry, atomic emission spectrometry, inductively coupled plasma emission spectrometry: ICP Optical Emission Spectrometry (ICP-OES) and ICP – Mass Spectrometry (ICPMS). It is very significant to use methods with very low detection limit, since in the majority of cases the concentration of elements is below 1 mg/kg. Prior the analysis, the studied materials are digested with mineral acids, preferably in microwave oven in closed vessels. This generates 50-100 times dilution. For this reason, it is advantageous to use methods with detection limit below μg/L, such as ICP-OES with ultrasonic nebulization or ICP with mass detector [127]. The analytical process should be controlled by the use of certified reference materials that have similar matrix as the analyzed material. E.g. in the analysis of human hair, Reference Material Human Hair was used [128]. It is recommended to perform semi-quantitative analysis of samples prior the quantitative analysis in order to evaluate the expected levels of analytes and to determine the main components. The knowledge of the levels of the main components is used in the preparation of calibration solutions. The mostly advantageous is to add the main components into the calibration solution. Such an approach minimizes matrix effects and also in some extent, interferences.

Chapter 6

USING BIOACCUMULATION IN BIOMONITORING OF ENVIRONMENTAL POLLUTION The processes of biosorption and bioaccumulation have found or will find in the nearest future an application in various areas related with environmental protection (Figure 9). Among these processes, two types of methods can be distinguished, which have common mechanisms, but the goals are different – bioremoval and biobinding. In the case of bioremoval, the goal is to achieve the highest possible removal of toxic metal ions via either biosorption or bioaccumulation processes.

Figure 9. Biosorption and bioaccumulation understood as bioremoval and biobinding.

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The objective is first of all to remove metal ions to the concentration below the level required by obligatory law, which is usually ca. 1 mg/L from large volume diluted solutions. This use of biosorption and bioaccumulation methods is recommended as the final, polishing step, before the final discharge of effluents. Biobinding processes that can be applied in environmental protection include biomonitoring. In this case, the aim would be not to bind the highest amounts of metals but to assess the concentration and bioavailability of pollutant in the environment. Biobinding processes can also find another application – in the production of highly bioavailable mineral feed additives. In this case the goal would be to bind the highest quantities of metals via either biosorption or bioaccumulation. The content of toxic metals in tissues or in the biomass of each organism reflects the level of a given contaminant in the environment. But, on the other hand, not every organism has the potential to be a good biomonitor or biondicator. First of all, biomonitoring should be ethically correct. Sampling of biomonitor tissues should not be invasive, nor should not pose destruction or deterioration of an organism, nor pain. Another issue is that the concentration factor of a pollutant in the studied material should be high enough to be possible to determine after digestion and dilution of a sample. Criteria of good biomonitor fulfill particularly non-living tissues, such as human hair [128-130], animal fear or birds feather, as well as animal products, advantageously consumable, such as eggs and milk [132142]. Also, plant tissues are good biomonitors of soil pollution [143-147]. The analysis of human hair provides the information on pollution of environment in which an organism lives, as well as contamination of food and drinks [128-129]. The level of soil pollution can be determined by the analysis of plant tissues [143]. It was also found that it is possible, through the use of specially elaborated extraction procedures to determine content of bioavailable forms of metals and on this basis (knowing so-called transfer factor) to predict the composition of plants that are to be cultivated on a given soil [143-147].

6.1. HUMAN HAIR AS BIOMONITOR OF ENVIRONMENTAL POLLUTION AND NUTRITIONAL STATUS OF INDIVIDUALS It is well known that the concentration of metals in biological tissues reflects their level in the environment. The property that is used in biomonitoring is that a mechanism that protects an organism from the excessive accumulation and toxic effects posed by a given contaminant is excretion outside an organism via

Using Bioaccumulation in Biomonitoring of Environmental Pollution

33

different routes: urine and feces, sweat and also transfer to external non-living tissues, such as hair and nail or birds feather. Elements enter living organism via different routes: are transferred from air, water, foods, drugs, through skin, respiratory tract and gastro-intestinal tract. Metals are transported by blood and deposited in organs [129]. The elements are distributed in an organism by blood and deposited in organs and tissues [129]. The elements that are present in hair can be divided into macroelements and trace elements. The latter group consists of toxic trace elements and essential trace elements (microelements) that comprises of major essential trace elements (Fe, Zn and Cu) and minor essential trace elements (Mn, Se, Cr, Co, Ni, Si, F, I) [128-130]. Table 4 presents the composition of hair from a population living in urban and industrialized area [129]. Table 4. Concentration of elements in human hair: reference values reported by commercial laboratories and scientific literature Reference values

Average values in populations

Commercial laboratories

Literature data

Element Doctor’s Data, Inc. Ag Al As B Ba Be Ca Cd Co Cr Cu Fe Hg K Mg Mn Mo Na

< 0.13 . [211] Michalak I., Chojnacka K., Dobrzański Z., Górecki H., Zielińska A., Korczyński M., Opaliński S., Biofortification of hens' eggs with microelements by bio-metallic feed additives from seaweeds. Animal Feed Science and Technology (in review) [212] McClafferty B., Bio+fortification. Breeding for nutrition. Rice Today. 2003, 2, 24-26

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[213] Jamroz D., Żywienie zwierząt i paszowznawstwo, Wyd. Nauk. PWN, Warszawa, 2002. [214] Kabata Pendias J., Pendias H., Biogeochemia pierwiastków śladowych, Wyd. Nauk. PWN, Warszawa, 1999. [215] Wierny A., Dodatki mineralne w żywieniu zwierząt. Pasze Przemysłowe 2002, 4, 9-16. [216] Gustafson G.M., Olsson I., Partitioning of nutrient and trace elements in feed between body retention, faeces and urine by growing dairy-breed steers. Acta Agriculturæ Scandinavica 2004 54, 10-19. [217] Poultry feeding standards, Omnitech IFIŻZ PAN Jabłonna, 1996. [218] Swine feeding standards, Omnitech IFIŻZ PAN Jabłonna, 1993. [219] Chojnacka K., Górecka H., Praktyczne aspekty wykorzystania zdolności biosorpcyjnych i bioakumulacyjnych metali przez algi. In: Mikroelementy w rolnictwie. Cz. 2. Warszawa: Wydaw. Nauk. PWN 2004 (Zeszyty Problemowe Postępów Nauk Rolniczych, ISSN 0084-5477, 723-728). [220] Shoeib T., Mester Z., Towards the characterization of metal binding proteins in metal enriched yeast. Microchemical Journal 2007, 85, 329–340. [221] Demirci, A., Pometto A.L. Enhanced Organically Bound Chromium Yeast Production. Journal of Agricultural and Food Chemistry 2000, 48, 531-536. [222] Spears J.W., Beef nutrition in the 21st century. Animal Feed Science and Technology 1996, 58, 29-35. [223] Spears J.W., Organic trace minerals in ruminant nutrition. Animal Feed Science and Technology, 1996, 58:151-163 [224] Chojnacka K. Usuwanie jonów metali ciężkich przez mikroalgi Spirulina sp. w procesach biosorpcji i bioakumulacji. Ph.D. Thesis, Wrocław, 2003. [225] Goyal N., Jain S.C., Banerjee U.C., Comparative studies on the microbial adsorption of heavy metals. Advances in Environmental Research 2003, 7, 311–319. [226] 226 Dz.U. 2003 nr 62 poz. 570, Rozporządzenie Ministra Rolnictwa i Rozwoju Wsi z dnia 1 marca 2003 r. w sprawie dopuszczalnych zawartości substancji niepożądanych w paszach. [227] Tait R.M., Fisher L.J., Variability in individual animal’s intake of minerals offered free-choice to grazing ruminants. Animal Feed Science and Technology 1996, 62, 69-76. [228] Caussy D., Gochfeld E., Gurzau E., Neagu C., Ruedel H., Lessons from case studies of metals: investigating exposure, bioavailability, and risk. Ecotoxicology and Environmental Safety 2003, 56, 45-51. [229] McDowell L.R., Feeding minerals to cattle on pasture. Animal Feed Science and Technology 1996, 60, 247-271.

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INDEX

A abiotic, 4 absorption, 16, 17, 29, 36, 38, 39, 79, 81, 89, 108, 119, 121 access, 75 accidents, 37 accumulation, 15, 23, 32, 45, 46, 54, 57, 95, 109 acetone, 35 acid, 7, 68, 79, 80, 81, 105 acidic, 6, 8, 13, 64 activated carbon, 66 activation, 3, 111 active site, 10, 12, 62 adaptation, 35, 74 additives, 32, 58, 71, 77, 79, 80, 83, 85, 114, 115 ADHD, 38 adsorption, 6, 67, 102, 103, 107, 116, 119 adults, 43 aerobic, 15, 21, 99, 102 aerobic granules, 15, 102 affect, ix, 34, 48, 74 Africa, 99 Ag, 5, 15, 33, 43, 44, 45, 53, 55 agar, 102, 106 age, 17, 34, 35, 36, 38, 39, 41, 43, 44, 109 agent, 35, 49, 52, 110

agricultural, 54, 76, 78, 90, 109 agriculture, 4, 95, 97, 109, 115 agrochemicals, 109, 110, 111, 114, 121 air, ix, 4, 16, 29, 32, 33, 34, 35, 37, 38, 43, 44, 45, 46, 47, 49, 55, 59, 99, 108, 111, 112, 113 air pollution, 99 alcoholics, 37, 111 algae, 16, 68, 73, 75, 76, 78, 80, 82, 83, 84, 85, 86, 87, 97, 99, 101, 106, 114, 118 algal, 21, 86, 101, 102, 106 alkaline, 49, 52, 93 alternative, 62, 95, 101 aluminosilicate, 58, 109, 110 aluminosilicates, 58 aluminum, 103 amino, 6, 15, 68, 79, 80, 81, 83 amino acid, 79, 80, 81, 83 amino acids, 81, 83 ammonia, 69 ammonium, 47 amphibia, 22, 108 anaerobic, 21, 107 analytical techniques, 35, 36, 47 anemia, 90 animal tissues, 55 animals, x, 16, 22, 23, 54, 56, 57, 59, 75, 77, 78, 79, 80, 81, 83, 84, 85, 86, 90, 95, 110

124

Index

anions, 48 antagonism, 59 antagonist, 40, 43 antagonistic, 9, 48, 59, 95 antagonists, 38 anthropogenic, 4 APC, 85 application, vii, ix, x, 7, 9, 16, 31, 32, 35, 47, 49, 65, 68, 69, 71, 76, 79, 91, 92, 93, 96, 103, 104, 105, 108, 109, 113, 114, 121 aquatic, x, 1, 22, 23, 61, 69, 84, 87, 97, 106, 114 aqueous solution, x, 86, 100, 101, 106, 107 aqueous solutions, x, 86, 101, 106, 107 arsenic, 38 arterial hypertension, 39 arteriosclerosis, 40 arthritis, 37 artificial, 12 ash, 49, 50, 52, 53, 67, 95, 111, 113 Asia, 115, 119 Aspergillus niger, 101 assessment, vii, ix, x, 2, 18, 23, 36, 37, 41, 42, 46, 54, 84, 85, 86, 99, 106 atmospheric deposition, 16 atomic absorption spectrometry, 29, 108 atomic emission spectrometry, 29 attention, 21, 39, 77, 90 Australia, 119, 121 authority, 3 autism, 38, 39 availability, 17, 74, 76, 77, 79, 81, 91, 92, 95, 97, 120

B Bacillus, 82 bacteria, 21, 82, 104 Baikal, 22, 107 bananas, 88 Bangladesh, 112 barley, 93, 119 barrier, 81, 93 battery, 56 behavior, 2, 8

behavioral disorders, 38 binding, 6, 7, 8, 9, 11, 12, 13, 14, 15, 18, 26, 35, 59, 64, 67, 68, 69, 73, 78, 79, 80, 82, 84, 89, 91, 93, 95, 100, 104, 108, 116 bioaccumulation, vii, ix, x, 1, 2, 7, 15, 16, 17, 18, 19, 21, 22, 23, 25, 26, 29, 31, 32, 47, 57, 64, 69, 71, 72, 75, 76, 79, 82, 84, 85, 87, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 104, 105, 106, 107, 108, 114 bioavailability, vii, x, 2, 17, 18, 23, 32, 46, 48, 52, 53, 54, 55, 76, 77, 78, 79, 80, 81, 86, 95, 97, 116, 118 biochemical, 118 biochemistry, 99 biodegradation, 2 biodiversity, 76, 115 bioindicators, 17, 99 biological, ix, 2, 3, 4, 5, 6, 15, 16, 17, 18, 21, 23, 32, 34, 37, 57, 65, 71, 74, 75, 78, 79, 80, 83, 97, 114 biological activity, 79 biological control, 83 biological form, 75, 83 biologically, 75, 78, 80, 84, 96 biomarkers, 18, 106 biomass, vii, ix, x, 1, 2, 6, 7, 8, 9, 14, 15, 16, 18, 21, 25, 27, 32, 49, 61, 62, 64, 68, 69, 71, 72, 73, 74, 75, 79, 80, 81, 82, 83, 84, 85, 86, 87, 96, 97, 101, 102, 103, 104, 106, 107, 114, 117 biomaterials, 7, 78 biomolecules, 6, 82 biomonitoring, vii, ix, x, 32, 56, 95 biopolymers, 5 bioreactor, 64 bioreactors, 21 biosorption, vii, ix, x, 1, 2, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 18, 21, 22, 25, 26, 29, 31, 32, 61, 63, 64, 65, 66, 67, 68, 71, 72, 73, 74, 75, 76, 79, 82, 84, 85, 87, 88, 95, 96, 99, 100, 101, 102, 103, 104, 106, 107, 114, 117 biosorption rate, 67 biota, 17, 18 biotechnology, 72, 97, 114, 117

Index biotic, 4 biotransformation, 83 Biotransformation, 117 birds, 32, 33, 56, 57 black, 15, 35, 104 blood, 33, 36, 39, 40, 44, 55, 57, 59, 109 body, 4, 17, 18, 35, 57, 106, 108 body fluid, 37 body weight, 84, 86, 87 bonds, 15, 81 bone, 103, 112 bone density, 112 bowel, 112 boys, 38 BP, 104 brain, 41 Brazil, 42 breast, 40, 113 breast cancer, 40, 113 breeding, 54, 57, 77, 78, 80, 86 broilers, 84, 117 Brussels, 109, 110, 111, 114, 121 by-products, 6, 21, 61, 106

C Ca2+, 67 cadmium, 49, 56, 69, 102, 103, 106, 107, 109, 110 calcium, 65, 67 calcium carbonate, 65 calibration, 29 California, 107, 120 cancer, 37, 40, 91, 113 Cancer, 40 Candida, 82, 83, 84 candidates, 80, 88 capacity, x, 6, 8, 9, 10, 12, 15, 16, 18, 26, 27, 61, 62, 65, 66, 67, 68, 73, 82, 83, 84, 96, 104, 114 Capacity, 1 Cape Town, 99 carbon, 66, 69, 73, 85, 86, 87, 96, 104, 115 carbon dioxide, 69, 73, 86 carbonates, 69, 81

125

carboxyl, 6, 15, 35, 68 carboxyl groups, 35 carcinogenic, 4 carcinogenicity, 3 carcinoma, 38, 40, 111 cardiovascular, 91 cardiovascular system, 91 carotene, 86 carotenoids, 85 carrier, 62, 79, 84, 86, 89, 97 catalytic, 108 cation, 6, 7, 8, 9, 12, 14, 15, 66, 68, 82, 83 cations, 6, 7, 8, 9, 11, 12, 13, 14, 15, 35, 58, 66, 68, 79, 80, 81, 82, 84, 89, 90 cattle, 85, 116 CD, 110 cell, 5, 16, 83, 85, 86, 95 cellulose, 21, 85, 107 channels, 16, 89 chelates, 80, 81, 92, 93 chemical, 3, 6, 15, 56, 65, 68, 74, 79, 89, 97, 107, 113 chemical interaction, 89 chemical properties, 3, 89 chemicals, 5, 15, 72, 102 chemisorption, 7, 8 chemistry, 79, 97, 119 chicken, 86 chicks, 86 children, 38, 39, 41, 43, 111, 112, 113 chitin, 21, 107 cholesterol, 86 chromatography, 103 chromium, 84, 102, 103, 112, 114, 117 Chromium, 103, 104, 116 chronic, 36, 38 classes, 6, 61 classical, 8, 10, 74 classified, 3, 6, 10, 77, 84, 96 clay, 89 cleaning, ix, 16 climatic factors, 17 Co, 5, 14, 15, 21, 33, 37, 43, 44, 45, 49, 51, 53, 55, 57, 58, 77, 78, 80, 87, 104, 107 CO2, 72, 85

126

Index

coal, 58 cobalt, 50, 80, 102 collagen, 67 combustion, 49, 50, 68 commercial, 33, 34, 42, 72, 74, 85 competition, 9, 10, 11, 12, 14 complementary, 115 complexity, 11 components, 4, 29, 52, 54, 76, 78, 80, 81, 83, 84, 85, 86, 90, 91, 93 composition, 9, 32, 33, 35, 36, 38, 40, 44, 45, 46, 48, 49, 51, 52, 53, 54, 58, 59, 97, 109, 112, 117, 120 compounds, 2, 6, 15, 69, 72, 73, 81, 83, 93, 96, 108 concentrates, 21, 49, 71 concentration, vii, ix, x, 2, 4, 5, 7, 8, 9, 12, 14, 16, 18, 26, 27, 29, 32, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 50, 52, 54, 55, 56, 58, 59, 61, 64, 65, 66, 67, 68, 69, 73, 74, 76, 85, 86, 89, 90, 91, 92, 96, 108, 112, 115, 117, 119 conformity, 42 Congress, iv, 110 coniferous, 49, 50 consumers, 4, 113 consumption, vii, 15, 46, 76, 84, 90, 92, 95 contact time, 7 contaminant, ix, 5, 17, 18, 32 contaminants, ix, x, 2, 5, 17, 18, 25, 26, 46, 96, 97 contaminated soils, 23, 47, 95 contamination, 32, 37, 46, 86 control, vii, ix, 1, 7, 16, 39, 40, 41, 74, 79, 83, 87, 95, 108, 112, 115 control group, 39, 40, 41, 87 controlled, ix, 16, 26, 29, 79, 82, 85 copper, 55, 69, 80, 100, 101, 104, 105, 106, 107, 110, 111, 112, 114, 119, 120 coral, 22, 107 corn, 92 coronary heart disease, 39 correction factors, 9, 10 correlation, 16, 37, 43, 46, 47, 48, 49, 55, 92 correlation coefficient, 43, 46, 49, 92

correlations, 37, 43, 45, 48, 91 cost-effective, 1 costs, 61, 62 covalent, 15, 81 covalent bond, 15, 81 coverage, 14, 77, 91 cow milk, 54, 55, 109 cows, 55, 57, 58, 109, 117 CP, 47, 85 Crassostrea gigas, 118 CRC, 99, 100, 102, 104, 118, 121 crimes, 41 crops, 75, 90, 91, 115, 118, 120 CS, 66 cultivation, 25, 69, 73, 74, 77, 86, 90, 91, 93 culture, 73, 90, 93, 94, 96, 115, 118 culture media, 118 cuticle, 93 cyanobacteria, 84 cycles, 1, 4, 46, 54, 61 cycling, 52 cystine, 35 Czech Republic, 108

D dairy, 42, 75, 116 dairy products, 42 damage, 3, 16, 52 danger, 26 deafness, 38 death, 38, 111 deciduous, 50 deficiency, 36, 37, 40, 74, 75, 76, 77, 80, 92, 93, 121 definition, 15, 64 degree, 2, 4 delivery, 79 demand, 119 denaturation, 67 density, 3, 40, 75, 90, 91, 92, 93, 112, 115, 118 Department of Agriculture, 119 deposition, 16, 35, 37, 47, 49 deposits, 4

Index dermal, 17 desorption, 62, 68 destruction, 32 detection, 29, 47 detoxification, 1, 38, 40, 44, 57, 59, 95 detoxifying, 41 developed countries, 76 developing countries, 89 development policy, 97 diabetes, 39, 40, 76, 112 diabetes mellitus, 40 diet, vii, x, 40, 41, 75, 76, 78, 79, 80, 84, 85, 86, 87, 88, 90, 91, 96, 112, 113, 115, 118 dietary, 43, 109, 110, 117 dietary habits, 43 diets, 118 diffusion, 55, 62 digestion, 32 digestive enzymes, 81 directives, 46 discharges, 17 discipline, 72 diseases, 37, 38, 39, 40, 76, 89, 91, 115 distribution, 17, 54 dosage, 93 dosing, 90 drainage, 105 dressings, 119 drinking water, 5, 38, 43 drought, 89 drugs, 33 dry, 67, 84 durability, 81 duration, 41 dyskinesia, 41

E earth, 97 earthworm, 22, 108 earthworms, 23, 108 eating, 35, 42 ecological, 46, 55, 56, 95, 110 ecology, 111 economic, 62

127

ecosystem, 4 ecotoxicology, 108 Education, vii effluent, 5, 64, 69 effluents, x, 1, 5, 9, 32, 69, 72, 82, 87, 97, 103, 114 egg, 56, 78, 86, 88 eggs, 32, 54, 55, 56, 57, 59, 75, 76, 87, 88, 95, 97, 109, 110, 115 elaboration, 34, 35, 76, 79, 82, 97, 108, 114 elderly, 40 electric power, 41 electrochemical, 100 electronic, iv electrons, 7 electroplating, 1 electrostatic, iv emission, 4, 29, 47, 100, 108 endocrine, 3 endocrine system, 3 energy, 4, 7, 68, 72, 73, 74, 77, 85, 86, 115 engineering, 97 enteritis, 39 environment, vii, ix, x, 1, 2, 4, 15, 16, 17, 18, 23, 32, 36, 37, 38, 45, 52, 54, 61, 74, 79, 84, 90, 105, 109, 110, 112, 114, 120 environmental, ix, x, 2, 4, 16, 17, 18, 23, 31, 32, 34, 35, 37, 43, 45, 46, 49, 52, 54, 56, 59, 65, 72, 76, 77, 78, 85, 87, 90, 91, 93, 95, 96, 97, 105, 106 environmental change, 76 environmental conditions, 23, 85, 91 environmental factors, 35, 90 environmental protection, 31, 32, 72 Environmental Protection Agency (EPA), 5, 37 enzymatic, 7, 84 enzymatic activity, 84 enzyme, 3, 39, 85 enzymes, 37, 41, 81 epidemiological, 36, 37 epilepsy, 41, 113 equilibrium, ix, 5, 7, 8, 9, 11, 14, 17, 21, 25, 26, 27, 36, 65, 66, 67, 68, 87, 100, 103, 106, 114

128

Index

equilibrium sorption, 27 erosion, 76 Escherichia coli, 21, 105 estrogens, 106 Europe, 117 European, 5, 22, 108, 110, 113 evidence, 119 evolutionary, 108 excretion, 32, 36, 37, 38, 40, 95 exogenous, 37 expenditures, 7 expert, iv exposure, 16, 17, 18, 23, 34, 36, 37, 38, 41, 43, 45, 46, 107, 108, 111, 116 extracellular, 21, 107 extraction, 32, 47, 53, 102, 106

F family, 45, 108 family relationships, 108 farm, 55, 56, 110 farms, 55, 56, 86 fat, 54 fatty acid, 78, 85 fatty acids, 78, 85 fear, 32 feces, 33, 77 feed additives, 32, 71, 77, 79, 83, 85, 114, 115 feeding, 58, 77, 80, 83, 84, 85, 86, 87, 105, 114, 116 females, 44, 45 fertilization, vii, 75, 80, 90, 91, 92, 93, 96, 110, 113, 120 fertilizer, 49, 52, 90, 91, 93, 96, 110, 119 fertilizers, 52, 75, 85, 89, 91, 92, 93, 96, 110, 113, 120 fibromyalgia, 40 filtration, 62 Finland, 91, 120 fish, 22, 41, 85, 86, 87, 105, 107, 108, 113, 118 fish meal, 85, 118 fishing, 87 FL, 118

floating, 87 flood, 121 flow, 100 flue gas, 72, 73 fluorine, 110 focusing, 113 follicular, 35 food, vii, x, 15, 16, 32, 35, 42, 43, 45, 46, 75, 76, 79, 88, 90, 91, 96, 112, 115, 118, 120 food products, 76 foodstuffs, 42 forecasting, 36 fortification, vii, 115 Fourier, 15 Fox, 120 free radical, 39, 40, 41 free radicals, 39, 40, 41 freshwater, 22, 87, 105, 108 Freundlich isotherm, 12 fruits, 50, 93 FTIR, 15 fungal, 6, 21, 101, 104, 106 fungi, 21, 82, 83, 103 fungus, 14, 21

G gases, 72, 73, 93 gastric, 38 geese, 54, 56 generation, 4, 41, 78 genes, 76 genetic, 23, 36, 88, 108 Geneva, 115 genotype, 92 genotypes, 75, 120 geochemical, 35, 80 germination, 47, 52 gestational diabetes, 40, 112 girls, 38 gland, 40 glass, 41 glucose, 40, 73 goals, 31, 115 gold, 79

Index grain, 90, 91, 92, 93, 120 grains, 88, 90, 91, 92, 93, 118 granules, 15, 102 graph, 8, 14 grass, x, 22, 61, 67, 114 gravity, 3 grazing, 116 ground water, 52 groups, 5, 6, 13, 15, 16, 35, 39, 43, 44, 66, 68, 81, 84, 85, 87, 89 growth, x, 7, 26, 35, 36, 64, 73, 78, 81, 83, 86, 90, 91, 93, 96, 105, 114, 118, 119, 120 growth rate, 35, 36, 78, 81, 86, 91 guilty, 41

H harmful, 3 harvest, 61 health, 17, 36, 37, 77, 78, 81, 83, 84, 88, 109, 110, 111, 114, 115 health effects, 37, 77 health problems, 78 heart, 39, 76, 112 Heart, 39 heart disease, 39, 76, 112 heat, 83 heating, 67 heavy metal, 3, 41, 82, 99, 100, 101, 102, 103, 104, 105, 107, 108, 110, 111, 116 heavy metals, 3, 41, 101, 102, 104, 105, 107, 110, 111, 116 heterogeneity, 11 heterotrophic, 73, 85, 114 homeostasis, 107 homogeneity, 81 homogeneous, 11 Hong Kong, 117 House, 111 housing, 110 human, ix, 4, 16, 17, 18, 23, 29, 32, 33, 34, 35, 36, 38, 42, 43, 59, 75, 76, 79, 80, 84, 85, 88, 90, 91, 108, 111, 113, 118 human exposure, 111 humans, 83

129

hydrolysis, 14 Hydrometallurgy, 99, 101, 102, 103, 114 hydroxide, 7 hydroxides, 89 hydroxyapatite, 67 hydroxyl, 6, 15, 68, 89 hydroxyl groups, 6, 15, 89 hypercholesterolemia, 39 hyperinsulinism, 40 hyperplasia, 113 hypersensitive, 112 hypertension, 39 hypertrophy, 40 hypothesis, 112

I id, 35, 44, 92 identification, 17, 21, 38, 41 imbalances, 41 immobilization, 4, 10, 52 immunological, 36, 83 implementation, 79 impurities, 2 inactive, 83 incineration, 105 Indian, 112 indicators, 18 indices, 107 indigenous, 103 industrial, vii, x, 1, 10, 21, 69, 78, 79, 82, 83, 85, 86, 95, 109, 114 industrial wastes, 83 industrialization, 4 industry, vii, 1, 3, 4, 43, 100, 110 infants, 39 infarction, 39, 112 infertility, 40 inflammatory, 112 inflammatory bowel disease, 112 influence, 17, 21, 35, 43, 45, 46, 67, 108, 114 ingestion, 17 inhalation, 17, 23 inhibition, 3 inhibitory, 14

130

Index

inhibitory effect, 14 injury, iv inorganic, vii, 5, 8, 38, 67, 73, 77, 78, 79, 80, 81, 86, 87, 90, 92, 93, 97, 121 inorganic growth, 86 inorganic salts, 78, 79, 81, 93 insulin, 39, 40 insulin resistance, 40 intelligence, 41 intensity, 52, 73, 79 interaction, 5, 9, 11, 13, 62 Interaction, 89, 101 interactions, vii, 9, 35, 43, 45, 47, 55, 59, 89, 108 interdisciplinary, 97 interference, 103 international, 80 international law, 80 interpretation, 35, 36, 42, 104 intestinal tract, 33 intestine, 81 invasive, 16, 32, 37, 59 invertebrates, 23 iodine, 75, 76, 118 Iodine, 78 ionic, 8, 15, 21, 95, 104, 106 ions, vii, x, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 26, 27, 31, 32, 47, 48, 61, 64, 66, 67, 68, 69, 71, 73, 79, 81, 82, 87, 89, 95, 96, 100, 102, 103, 104, 106, 114 iron, 75, 76, 80, 84, 90, 103, 111, 121 irrigation, 90 ischemic, 39, 112 ischemic heart disease, 39, 112 isotherms, 9, 10, 11, 12, 102, 107

K keratin, 35 kidneys, 3, 54 kinetic model, 102, 106, 114 kinetics, ix, 7, 21, 37, 65, 66, 67, 68, 73, 102, 107, 114 knowledge, 29, 48, 95 Kolmogorov, 113

Korean, 113

L LA, 85 lagoon, 107 lakes, 74, 87 land, 78 landfills, 65 Langmuir, 8, 9, 10, 11, 12, 13, 14, 26, 66, 67, 68, 87, 88, 103 language, 3 lanthanum, 99, 101 larvae, 22, 108 law, 4, 32, 69, 80, 96 lead, 91, 101, 103, 104, 106, 107, 108, 109, 110 learning, 41 lifestyle, 37, 45 ligands, 8, 15, 89 linear, 43, 73, 74, 93 lipids, 6, 86 liquid chromatography, 103 literature, 7, 9, 10, 13, 21, 33, 34, 35, 36, 38, 42, 75, 80 liver, 54, 55, 59, 110 livestock, vii, x, 54, 58, 71, 75, 77, 78, 79, 80, 83, 84, 85, 86, 87, 96, 97, 114 Livestock, 77, 117 living environment, 38, 84 location, 35 London, 99, 102, 115 long period, 62 long-term, 18, 120 low temperatures, 86 lungs, 40, 54, 55 lysine, 81

M machinery, 4 macroalgae, x, 21, 61, 84, 86, 87, 102, 114 macromolecules, 80 macronutrients, 52, 91, 110

Index Madison, 119 magnesium, 65, 86, 111, 118, 120 magnetic, iv males, 44, 45 malnutrition, 39, 75, 90, 112, 115 mammals, 54 management, 46 manganese, 41, 80, 118, 121 Manganese, 78 manure, 77, 78 market, 79, 80, 81 mass, 26, 29, 47, 56, 61, 108 mathematical, x, 66, 112 matrix, 10, 29, 62 maximum sorption, 26, 27 measures, 90 meat, 57, 75, 76, 88, 97, 118 mechanical, iv, 62 media, 83, 86, 118 medicine, 4, 35 melanin, 35 melter, 55, 69, 114 membranes, 89 mental retardation, 41 mercury, 49, 59, 105, 106, 108, 109, 113, 114 metabolic, ix, 7, 16, 17, 40, 59, 65, 73, 96 metabolism, 26, 36, 42, 73, 85, 115, 117 metal ions, vii, x, 1, 2, 4, 5, 6, 7, 8, 9, 10, 13, 14, 16, 18, 19, 26, 27, 31, 32, 47, 48, 61, 64, 66, 68, 69, 73, 79, 81, 82, 87, 95, 96, 100, 104 metal recovery, 71 Metallothionein, 104 metallothioneins, 16, 84 metallurgy, 4 metals, vii, ix, x, 1, 2, 3, 4, 5, 6, 7, 9, 10, 15, 16, 18, 21, 23, 32, 34, 35, 36, 37, 38, 39, 41, 43, 44, 45, 46, 48, 49, 50, 52, 54, 55, 56, 57, 59, 61, 68, 69, 71, 77, 79, 80, 90, 95, 96, 99, 101, 102, 104, 105, 107, 108, 110, 111, 116, 120 methionine, 81, 83 Mexico, 119 microalgae, x, 21, 22, 61, 69, 72, 73, 83, 84, 85, 86, 114, 115, 118

131

microbes, 76 microbial, 6, 7, 100, 116 Microbial, 102, 114, 117 micronutrients, vii, x, 46, 49, 50, 52, 53, 75, 76, 77, 78, 80, 88, 89, 90, 91, 92, 93, 96, 110, 113 microorganisms, 18, 82 microwave, 29 middle-aged, 43 milk, 32, 54, 55, 56, 57, 58, 59, 75, 95, 97, 109, 117 mineralization, 84 minerals, 38, 55, 76, 77, 78, 79, 83, 85, 111, 114, 116, 120 mining, 1, 4, 102 mixing, 77 mobility, 121 mode, 73 modeling, x, 7, 9, 11, 13, 14, 66, 102, 103 models, 7, 8, 10, 46, 103 moisture, 17 molasses, 105 molecular weight, 3 molecules, 89 mollusks, 22, 80 monitoring, 2, 4, 16, 18, 22, 23, 34, 99, 105, 108 Moon, 107 Morocco, 111 morphological, 17, 56 morphology, ix MS, 29, 47, 55, 113 multi-component systems, 10, 11 multiple regression, 43, 45 multiple regression analysis, 43, 45 multiplicity, vii, 9, 35 muscle, 22, 108, 110 muscle tissue, 22, 108 muscles, 54, 55, 56, 59 myocardial infarction, 39, 112

N nasopharyngeal carcinoma, 40, 111 national, 5

132

Index

National Academy of Sciences, 119 natural, vii, ix, 1, 37, 45, 69, 74, 77, 78, 79, 82, 84, 87, 106, 114 natural environment, 74 Nb, 51, 53 nebulizer, 47 nephritic syndrome, 40 nervous system, 3 Netherlands, 110 neural networks, 12 neurotoxicity, 41 New York, iii, iv, 99, 100, 111, 115 Ni, 3, 5, 15, 21, 33, 34, 39, 40, 41, 43, 44, 45, 46, 48, 49, 51, 53, 54, 55, 57, 58, 77, 104, 107 niacin, 79 nickel, 99, 101, 107, 112 nitrate, 47 nitric acid, 68 nitrogen, 49, 69, 96 non invasive, 16 non-invasive, 37 nonlinear, 10 non-linear, 74 non-smokers, 44 normal, 36, 42, 112 nutrient, 116, 119, 120 nutrients, x, 2, 7, 16, 18, 52, 65, 69, 74, 77, 83, 91, 93, 96, 111 nutrition, 41, 80, 113, 115, 116, 117, 118, 120, 121 nutritional supplements, 79

O obesity, 76 occupational, 41, 105 Ohio, 118 oil, 58, 75, 120 older people, 44 oligosaccharides, 83 optical, 17, 47 oral, 17 ores, 4 organelles, 3

organic, 2, 6, 8, 15, 49, 65, 67, 69, 73, 79, 80, 81, 83, 85, 86, 87, 90, 92, 105, 108, 121 organic compounds, 2, 6, 15, 73, 81 organic matter, 49, 65, 67, 92 organism, vii, ix, x, 4, 16, 17, 18, 32, 34, 35, 36, 37, 38, 40, 41, 42, 44, 59, 74, 77, 82, 89, 93, 95 organization, 18 oxidation, 4 oxidative, 40, 41 oxidative stress, 40, 41 oxygen, 13 oysters, 22, 86, 107, 118

P Pacific, 86, 115, 118 pain, 32 Pakistani, 112 PAN, 116 Paper, 115, 119 parameter, 7, 15, 26, 49, 67, 74 parenteral, 41 Parkinson, 41, 111 particles, 119 passive, 7, 18, 46, 89 pasture, 116 pathogenesis, 39 pathology, 40 pathways, 16 patients, 37, 39, 40, 41, 111, 112, 113 Pb, 3, 4, 5, 14, 15, 21, 34, 36, 37, 38, 39, 41, 42, 43, 44, 45, 46, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 71, 72, 96, 106, 107 PCR, 104 peat, 14, 83, 104 perception, 120 performance, 9, 67, 68, 69, 74, 87, 106, 117, 118 personal, 35, 45, 46 Perth, 119 pesticides, 101 pH, 6, 7, 8, 9, 12, 14, 21, 48, 52, 65, 66, 67, 68, 93, 99, 101, 104, 106 pharmaceutical, 37, 79

Index pharmaceuticals, 85 phloem, 93 phosphate, 6, 119, 120 phosphates, 58, 67 phosphorus, 65, 69, 91, 96, 120, 121 photobioreactors, 85 photosynthesis, 84 photosynthetic, 69, 74, 87 physical activity, 115 physical factors, 74 physicochemical, 8, 9, 15 physiological, 36, 54, 74, 117 physiology, ix, 79 pigments, 85, 86 pigs, 118 plants, x, 2, 16, 22, 23, 32, 46, 47, 48, 49, 61, 75, 76, 77, 78, 81, 84, 86, 87, 88, 89, 90, 91, 92, 93, 96, 105, 110, 111, 114, 119, 121 plasma, 29, 47, 108, 112 platinum, 108 play, 3, 39, 83 plumbism, 38 poisoning, 38 Poland, 33, 34, 42, 52 pollutant, 4, 16, 18, 27, 32, 96 pollutants, vii, ix, 2, 26, 57, 65, 69, 73, 78, 95, 97, 105 pollution, vii, ix, x, 2, 16, 17, 18, 23, 32, 34, 35, 37, 41, 49, 52, 54, 56, 59, 90, 93, 95, 99, 108, 109, 113 polysaccharide, 21, 80, 81, 107 polysaccharides, 6, 86 polyunsaturated fat, 78 polyunsaturated fatty acid, 78 polyunsaturated fatty acids, 78 pond, 86 pools, 75 poor, 36, 76, 77, 81, 92 population, 33, 35, 42, 43, 46, 112 Portugal, 42, 111 positive correlation, 92 potassium, 48, 52, 119 poultry, 54, 57, 58 poverty, 115 poverty reduction, 115

133

power, 41, 113 power plant, 41, 113 precipitation, 7, 64, 102 pregnant, 112 pregnant women, 112 premenstrual syndrome, 40 preparation, iv, x, 29, 37, 57, 58, 76, 87, 88, 95, 109, 110 prevention, ix, 4, 16, 83, 95, 115 preventive, 57, 110 printing, 4 prisoners, 41 probability, 77 procedures, x, 17, 18, 32, 35, 36, 37, 46 producers, 84, 86 production, x, 27, 32, 52, 71, 72, 75, 76, 78, 82, 83, 85, 86, 87, 88, 93, 96, 97, 109, 111, 113, 114, 121 productivity, 65, 74, 85 profession, 39 property, iv, ix, 1, 32, 69 protection, 4, 14, 31, 32, 72 protein, 67, 78, 81, 85, 91, 120 proteins, 6, 16, 81, 83, 86, 89, 116, 118 protons, 6, 9, 101 pseudo, 7, 66 Pseudomonas, 21, 101, 106 pyrite, 41

R race, 35 radius, 15 range, 42, 43, 54, 55, 56, 67, 86, 110 rat, 108 rats, 22, 23, 108 raw material, 85, 110 raw materials, 85 RC, 118 reaction order, 7 recall, 36 reclamation, 79 Reclamation, 105 recovery, 71, 101, 104 redox, 46

134

Index

reduction, 59, 76, 95, 109, 115 regenerate, 64 regeneration, 62, 71 regression, 10, 43, 45 regression analysis, 43, 45 regulation, 89 regulations, 5, 79 relationship, 23, 45, 112 relationships, 10, 76, 108, 115 remediation, 16, 95, 105 reparation, 58 reproduction, 3 research, vii, 9, 14, 21, 22, 23, 90 reservoirs, 87 resins, 83 resistance, 40, 62, 119 resolution, 100 respiratory, 3, 16, 33 restoration, 4, 68 retardation, 41 retention, 52, 116, 121 rheumatic, 40 rheumatic diseases, 40 rice, 76, 90 Rio de Janeiro, 33, 34 risk, 2, 41, 46, 86, 91, 106, 110, 112, 116 risk assessment, 46, 106 risk factors, 112 risks, 81 river systems, 106 ruminant, 116 rural, 41, 109

S SA, 119 Saccharomyces cerevisiae, 15, 82, 84, 104 salt, 83 salts, 23, 38, 48, 75, 77, 78, 79, 80, 81, 88, 93 sample, 16, 32, 37 sampling, 7, 37 scalp, 112, 113 Scanning Electron Microscopy (SEM), 15 scientific, 33, 34, 42 search, 78, 79, 115

seaweed, 6, 101 sebum, 37 sediments, 1, 2 seed, 91, 119, 120 segregation, 81 selectivity, 9, 10, 11, 13, 14, 15, 89 selenium, 4, 58, 59, 83, 86, 91, 109, 117 self, 74, 115 self-control, 74, 115 separation, 62, 87 series, 118 services, iv severity, 41 sewage, 107 sex, 34, 35, 36, 38, 39, 41, 44, 45, 46, 109 shape, 10 sharing, 7 side effects, 81 silicon, 111 simulation, 46, 102, 103 simulations, 103 sites, 6, 7, 8, 9, 11, 12, 13, 14, 18, 54, 62, 67, 87, 100, 101 skin, 16, 33, 54 sludge, 2, 99, 102, 103, 107 smelting, 4 smokers, 44 smoking, 35, 109 sodium, 47, 48, 86, 91, 117 soil, 4, 16, 32, 46, 47, 48, 49, 51, 52, 53, 55, 65, 75, 76, 81, 89, 90, 91, 92, 93, 96, 105, 107, 108, 110, 111, 113, 119, 120 soil particles, 119 soil pollution, 32 soils, 23, 46, 77, 89, 91, 92, 93, 95, 110, 113, 119, 120, 121 solid state, 2, 4 solid-state, 71 solubility, 7, 23, 48, 52, 67, 81, 108 solutions, x, 1, 8, 15, 29, 32, 69, 82, 86, 87, 96, 101, 104, 106, 107 sorbents, 6, 21, 26, 27, 61, 67, 79, 96 sorption, 6, 7, 8, 9, 10, 15, 26, 27, 61, 62, 65, 66, 67, 68, 73, 96, 104, 113, 114 South Africa, 99

Index soybeans, 120 spatial, 92 specialists, 97 speciation, 7, 46, 67, 111 species, 9, 17, 18, 46, 49, 50, 51, 52, 74, 80, 84, 85, 89, 91, 92, 105, 107 specific gravity, 3 spectroscopy, 47 stability, 81 stages, 1, 19 standardization, 34 standards, 5, 55, 116 Standards, 5 starches, 81 sterile, 85 sterilization, 66 stomach, 81 storage, 37 strains, 85 strength, 8, 21, 81, 100, 106 Streptomyces, 82 stress, 40, 41 substances, 16, 37, 67, 80, 105 substrates, 73 suffering, 37, 39, 40, 41 sulfate, 6, 93, 120, 121 sulfur, 49 sulphate, 67, 119 Sun, 15, 102 sunlight, 73, 85 superoxide, 39, 41 superoxide dismutase, 39, 41 supplemental, 117 supplements, vii, 27, 57, 59, 75, 76, 77, 78, 79, 80, 81, 82, 86, 87, 97, 114, 118 supply, 76, 79, 89, 119 surface area, 68 surface layer, 89 surface properties, 7, 8, 79 susceptibility, 89 sustainable development, 97 sweat, 33, 37 Sweden, 33, 34, 42, 113 symbiotic, 76 symptoms, 36, 37, 38, 39, 40

135

syndrome, 40 synergistic, 9, 43, 45, 48, 95 synergistic effect, 45 synthesis, 74 synthetic, 92, 106, 118 systematic, 114 systems, 9, 10, 11, 13, 14, 15, 21, 77, 78, 86, 102, 103, 104, 106

T Taiwan, 105 technological, 121 technology, 1, 97, 110, 114 temperature, 7, 8, 17, 21, 65, 67, 74, 86, 106 TF, 47, 48, 49 theory, 2, 56 therapeutic, 86 therapy, 113 thermolysis, 108 Ti, 34, 43, 44, 45, 51, 53, 55, 57, 58 TI, 45 time, 2, 7, 36, 37, 45, 62, 64, 74, 90, 91 tissue, 22, 36, 37, 40, 107, 108 titration, 12, 21, 66, 68, 100, 102 tobacco, 44 tolerance, 37, 119 toxic, vii, ix, 1, 2, 3, 4, 5, 7, 15, 16, 18, 21, 23, 25, 26, 31, 32, 36, 37, 39, 41, 42, 44, 45, 46, 49, 50, 52, 54, 55, 56, 57, 58, 59, 68, 69, 71, 77, 78, 79, 80, 81, 83, 90, 93, 95, 96, 110 toxic effect, 7, 16, 25, 26, 32, 77, 78, 79, 90, 96 toxic metals, ix, 1, 2, 3, 4, 5, 7, 15, 16, 18, 21, 23, 32, 36, 39, 41, 44, 46, 49, 50, 52, 54, 55, 56, 57, 59, 68, 69, 71, 77, 90, 95, 96 toxic side effect, 81 toxic substances, 16 toxicity, 3, 4, 23, 85, 97, 117 toxicology, 99, 105 toxin, 37 trace elements, 33, 35, 36, 38, 39, 42, 49, 50, 54, 55, 57, 109, 111, 112, 113, 116 trade, 119

136

Index

transfer, 10, 16, 32, 33, 46, 47, 48, 57, 87, 105 transformation, 92 transgenic, 76, 90 transgenic plants, 76 transition, 115 translocation, 93, 121 Transmission Electron Microscopy (TEM), 15 transport, 16, 55, 89, 93, 96 trees, 49, 50 tryptophan, 79 two-dimensional, 14 type II diabetes, 40

U UK, 119 UNICEF, 115 uniform, 7, 9, 11, 77 United Kingdom, 113 uranium, 102, 105, 108 urban, 33, 43, 45, 111 urbanized, 95 urine, 33, 36, 40, 44, 77, 116

V values, 14, 17, 25, 33, 34, 35, 36, 38, 39, 42, 56, 64, 67, 76, 111 variability, 23, 55, 92, 108 variable, 80, 81, 119 variation, 120 vegetables, 88, 93 vegetation, 93 vertebrates, 23 vessels, 29 vitamin A, 76 vitamin C, 38 vitamins, 78, 83, 85

waste, 6, 15, 21, 61, 65, 67, 71, 96, 97, 102, 103, 104, 105, 106 waste incineration, 105 wastes, 23, 83, 108, 117 wastewater, x, 2, 5, 14, 16, 23, 62, 64, 67, 69, 71, 72, 73, 78, 79, 80, 82, 87, 95, 96, 97, 100, 101, 105, 111, 115 wastewater treatment, x, 2, 14, 16, 23, 64, 67, 69, 71, 78, 79, 80, 82, 87, 95, 96, 97, 100, 115 wastewaters, vii, 71, 87, 101, 105 water, 4, 5, 15, 16, 33, 35, 38, 42, 43, 46, 55, 56, 74, 78, 79, 87, 90, 105 waterfowl, 56, 57, 109 welding, 4 wetlands, 108 wheat, 67, 89, 114, 118, 119, 120, 121 wine, 38 Wisconsin, 119 women, 39, 40, 112 wood, x, 49, 50, 52, 53, 95, 110, 111, 113 wood species, 50 work, vii, ix, 61, 62 workers, 41, 105 workplace, 37 World Bank, 119 World Health Organisation (WHO), 115 worm, 22, 107

X XPS, 15 xylem, 93

Y yeast, 83, 97, 116, 117 yield, 36, 74, 88, 90, 91, 92, 93, 96, 120 yolk, 56, 78

W Z Warsaw, 110 washing procedures, 35 Washington, 115, 119

zeolites, 69, 114

Index zinc, 75, 76, 80, 101, 102, 106, 107, 108, 111, 112, 118, 119, 120, 121 Zinc, 78, 120 zinc sulfate, 120, 121

137

Zn, 3, 5, 14, 15, 21, 33, 34, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 48, 49, 50, 51, 53, 55, 56, 57, 58, 65, 77, 78, 80, 81, 87, 88, 89, 90, 91, 92, 93, 96, 103, 104, 107, 108, 112, 120