Bacterial Bios or Bents and ion

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Biotechnology Advances 26 (2008) 266–291www.elsevier.com/locate/biotechadv

Research review paper

Bacterial biosorbents and biosorption

K. Vijayaraghavan ⁎, Yeoung-Sang Yun ⁎

Division of Environmental and Chemical Engineering, Research Institute of Industrial Technology, Chonbuk National University, Chonju 561-756, South Korea

Received 31 July 2007; received in revised form 5 February 2008; accepted 7 February 2008Available online 15 February 2008

Abstract

Biosorption is a technique that can be used for the removal of pollutants from waters, especially those that are not easily biodegradable such asmetals and dyes. A variety of biomaterials are known to bind these pollutants, including bacteria, fungi, algae, and industrial and agriculturalwastes. In this review, the biosorption abilities of bacterial biomass towards dyes and metal ions are emphasized. The properties of the cell wallconstituents, such as peptidoglycan, and the role of functional groups, such as carboxyl, amine and phosphonate, are discussed on the basis of theirbiosorption potentials. The binding mechanisms, as well as the parameters influencing the passive uptake of pollutants, are analyzed. A detaileddescription of isotherm and kinetic models and the importance of mechanistic modeling are presented. A systematic comparison of literature,based on the metal/dye binding capacity of bacterial biomass under different conditions, is also provided. To enhance biosorption capacity,biomass modifications through chemical methods and genetic engineering are discussed. The problems associated with microbial biosorption areanalyzed, and suitable remedies discussed. For the continuous treatment of effluents, an up-flow packed column configuration is suggested and thefactors influencing its performance are discussed. The present review also highlights the necessity for the examination of biosorbents within realsituations, as competition between solutes and water quality may affect the biosorption performance. Thus, this article reviews the achievementsand current status of biosorption technology, and hopes to provide insights into this research frontier.© 2008 Elsevier Inc. All rights reserved.

Keywords: Biosorption; Bacteria; Metals; Dyes; Wastewater treatment; Packed column; Isotherm model; Kinetic model; Biomass reuse; Multicomponent biosorption

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2672. Overview of treatment methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2673. Biosorbents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2684. History of bacterial biosorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2705. Bacterial structure and mechanism of bacterial biosorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271

5.1. Bacterial structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2715.2. Mechanism of bacterial biosorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2725.3. Characterization of bacterial surface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272

6. Preparation of bacterial biosorbents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2736.1. Chemically modified biosorbents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2736.2. Genetically modified biosorbents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2746.3. Immobilized biosorbents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274

7. Biosorption experimental procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2757.1. Factors influencing bacterial batch biosorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2757.2. Biosorption isotherms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2777.3. Batch experimental data modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277

⁎ Corresponding authors. Tel.: +82 63 270 2308; fax: +82 63 270 2306.E-mail addresses: [email protected] (K. Vijayaraghavan), [email protected] (Y.-S. Yun).

0734-9750/$ - see front matter © 2008 Elsevier Inc. All rights reserved.doi:10.1016/j.biotechadv.2008.02.002

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267K. Vijayaraghavan, Y.-S. Yun / Biotechnology Advances 26 (2008) 266–291

7.3.1. Empirical modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2777.3.2. Mechanistic modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278

7.4. Batch kinetic studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2798. Desorption and regeneration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2809. Continuous biosorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280

9.1. Column biosorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2819.2. Column regeneration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2829.3. Modeling of column data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282

10. Multicomponent systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28311. Application of biosorption to real industrial effluents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28412. Fate of exhausted biosorbent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28513. Scope and future directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286

1. Introduction

Comprising over 70% of the Earth's surface, water is un-deniably themost valuable natural resource existing on our planet.Without this invaluable compound, the life on the Earth would benon-existent. Although this fact is widely recognized, pollution ofwater resources is a common occurrence. In particular, potablewater has become greatly affected, and in many instances has lostits original purpose.

There are many sources of water pollution, but two maingeneral categories exist: direct and indirect contaminant sources.Direct sources include effluent outfalls from industries, refineriesand waste treatment plants; whereas, indirect sources includecontaminants that enter the water supply from soils/ground watersystems and from the atmosphere via rain water. In general, con-taminants come under two broad classes, viz. organic and inor-ganic. Some organic water pollutants include industrial solvents,volatile organic compounds, insecticides, pesticides and foodprocessing wastes, etc. Inorganic water pollutants include metals,fertilizers and acidity caused by industrial discharges, etc. To limitour scope, this review takes into consideration only dyes, whichcome under organic, and metals, which come under inorganicpollutants. They are common contaminants in industrial waste-waters and many of them are known to be toxic and carcinogenic.

A dye can generally be described as a colored substance withan affinity to the substrate to which it is applied. Dyes are widelyused in industries, such as textiles, paper, plastics and leather,etc., for the coloration of products. The effluents emanating fromthese industries often contain high concentrations of dye wastes.Two percent of the dyes produced are discharged directly inaqueous effluent, with a further 10% subsequently lost duringthe textile coloration process (Easton, 1995). It has been reportedthat over 100,000 dyes are commercially available, with a pro-duction of over 7×105 tonnes per year (Zollinger, 1987; Aksu,2005). Dyes are generally believed to be toxic and carcinogenicor prepared from other known carcinogens (Banat et al., 1996).The discharge of these dye stuffs from industries into rivers andlakes results in a reduced dissolved oxygen concentration caus-ing anoxic conditions, which subsequently affect aerobic organ-isms (Chander and Arora, 2007). Apart from the toxicologicalproperties of dyes, their color is one of the first signs ofcontamination recognized in a wastewater. Since a very small

quantity of dyes in water is highly visible, it often affects theaesthetic merit and water transparency (Banat et al., 1996).

Another group of contaminants of concern, which comesunder the inorganic division, are metals. Metals are extensivelyused in several industries, including mining, metallurgical,electronic, electroplating and metal finishing. The presence ofmetal ions in final industrial effluents is extremely undesirable, asthey are toxic to both lower and higher organisms. Under certainenvironmental conditions, metals may accumulate to toxic levelsand cause ecological damage (Jefferies and Firestone, 1984). Ofthe important metals, mercury, lead, cadmium and chromium(VI)are regarded as toxic; whereas, others, such as copper, nickel,cobalt and zinc are not as toxic, but their extensive usage andincreasing levels in the environment are of serious concerns(Brown and Absanullah, 1971; Moore, 1990; Volesky, 1990).Radionuclides, such as uranium, possess high toxicity and radio-activity, and exhibit a serious threat, even at small concentrations.

In most developed and developing countries, stricter envi-ronmental regulations, with regard to contaminants dischargedfrom industrial operations, are being introduced. This means thatindustries need to develop on-site or in-plant facilities to theirown effluents and minimize the contaminant concentrations toacceptable limits prior to their discharge (Banat et al., 1996).However, before selecting a wastewater treatment facility, aconsiderable amount of laboratory and engineering work mustbe completed prior to system design (Atkinson et al., 1998).

2. Overview of treatment methods

Various techniques have been employed for the treatment ofdye/metal bearing industrial effluents, which usually comeunder two broad divisions: abiotic and biotic methods. Abioticmethods include precipitation, adsorption, ion exchange,membrane and electrochemical technologies. Much has beendiscussed about their downside aspects in recent years(Atkinson et al., 1998; Crini, 2006), which can be summarizedas expensive, not environment friendly and usually dependenton the concentration of the waste. Therefore, the search forefficient, eco-friendly and cost effective remedies for waste-water treatment has been initiated.

In recent years, research attention has been focused onbiological methods for the treatment of effluents, some of which

268 K. Vijayaraghavan, Y.-S. Yun / Biotechnology Advances 26 (2008) 266–291

are in the process of commercialization (Prasad and Freitas, 2003).There are three principle advantages of biological technologies forthe removal of pollutants; first, biological processes can be carriedout in situ at the contaminated site; Second, bioprocess tech-nologies are usually environmentally benign (no secondary pollu-tion) and third, they are cost effective.

Of the different biological methods, bioaccumulation andbiosorption have been demonstrated to possess good potential toreplace conventional methods for the removal of dyes/metals(Volesky and Holan, 1995; Malik, 2004). Some confusion hasprevailed in the literature regarding the use of the terms “bio-accumulation” and “biosorption” based on the state of the biomass.Herein, therefore, bioaccumulation is defined as the phenomenonof living cells; whereas, biosorption mechanisms are based on theuse of dead biomass. To be precise, bioaccumulation can bedefined as the uptake of toxicants by living cells. The toxicant cantransport into the cell, accumulate intracellularly, across the cellmembrane and through the cell metabolic cycle (Malik, 2004).Conversely, biosorption can be defined as the passive uptake oftoxicants by dead/inactive biological materials or by materialsderived from biological sources. Biosorption is due to a number ofmetabolism-independent processes that essentially take place inthe cell wall, where the mechanisms responsible for the pollutantuptake will differ according to the biomass type.

Biosorption possesses certain inherent advantages over bio-accumulation processes, which are listed in Table 1. In general, theuse of living organisms may not be an option for the continuoustreatment of highly toxic organic/inorganic contaminants. Once thetoxicant concentration becomes too high or the process operated fora long time, the amount of toxicant accumulated will reachsaturation (Eccles, 1995). Beyond this point, an organism'smetabolism may be interrupted, resulting in death of the organism.This scenario can be avoided in the case of dead biomass, which is

Table 1Comparison of the features of biosorption and bioaccumulation

Features Biosorption

Cost Usually low. Most biosorbents used were industrial, agrictype of waste biomass. Cost involves mainly transportatiosimple processing charges.

pH The solution pH strongly influences the uptake capacity othe process can be operated under a wide range of pH con

Temperature Since the biomass is inactive, temperature does not influeIn fact, several investigators reported uptake enhancemen

Maintenance/storage Easy to store and use

Selectivity Poor. However, selectivity can be improved by modificatibiomass

Versatility Reasonably good. The binding sites can accommodate a v

Degree of uptake Very high. Some biomasses are reported to accommodatenearly as high as their dry weight.

Rate of uptake Usually rapid. Most biosorption mechanisms are rapid.

Toxicant affinity High under favorable conditions.Regeneration and reuse High possibility of biosorbent regeneration, with possible

number of cycles.Toxicant recovery With proper selection of elutant, toxicant recovery is poss

acidic or alkaline solutions proved an efficient medium to

flexible to environmental conditions and toxicant concentrations.Thus, owing to its favorable characteristics, biosorption has, notsurprisingly, received much attention in recent years.

3. Biosorbents

Biosorbents for the removal ofmetals/dyesmainly come underthe following categories: bacteria, fungi, algae, industrial wastes,agricultural wastes and other polysaccharidematerials. In general,all types of biomaterials have shown good biosorption capacitiestowards all types of metal ions.

Potent metal biosorbents under the class of bacteria includegenre ofBacillus (Nakajima and Tsuruta, 2004; Tunali et al., 2006),Pseudomonas (Chang et al., 1997; Uslu and Tanyol, 2006) andStreptomyces (Mameri et al., 1999; Selatnia et al., 2004a), etc.Important fungal biosorbents include Aspergillus (Kapoor andViraraghavan, 1997; Jianlong et al., 2001; Binupriya et al., 2006),Rhizopus (Bai and Abraham, 2002; Park et al., 2005) and Peni-cillium (Niu et al., 1993; Tan and Cheng, 2003), etc. Since thesemicroorganisms are used widely in different food/pharmaceuticalindustries, they are generated aswaste,which can be attained free orat low cost from these industries. Another important biosorbent,which has gained momentum in recent years, is seaweed. Marinealgae, popularly known as seaweeds, are biological resources,which are available in many parts of the world. Algal divisionsinclude red, green and brown seaweed; of which brown seaweedsare found to be excellent biosorbents (Davis et al., 2003). This isdue to the presence of alginate, which is present in gel form in theircell walls. Also, their macroscopic structure offers a convenientbasis for the production of biosorbent particles that are suitable forsorption process applications (Vieira andVolesky, 2000). However,it should be noted that seaweeds are not regarded as wastes; in factthey are the only source for the production of agar, alginate and

Bioaccumulation

ultural and othern and other

Usually high. The process involves living cellsand; hence, cell maintenance is cost prone.

f biomass. However,ditions.

In addition to uptake, the living cells themselvesare strongly affected under extreme pH conditions.

nce the process.t with temperature rise.

Temperature severely affects the process.

External metabolic energy is needed formaintenance of the culture.

on/processing of Better than biosorption

ariety of ions. Not very flexible. Prone to be affected by highmetal/salt conditions.

an amount of toxicant Because living cells are sensitive to hightoxicant concentration, uptake is usually low.Usually slower than biosorption. Sinceintracellular accumulation is time consuming.Depends on the toxicity of the pollutant.

reuse over a Since most toxicants are intracellularly accumulated,the chances are very limited.

ible. In many instances,recover toxicants.

Even if possible, the biomass cannot be utilizedfor next cycle.

Table 2Important results from the literature on metal biosorption by various bacterial species

Metal Organism Operating conditions Uptake (mg/g) Reference

pH Temp (°C) Other information

Aluminum Chryseomonas luteola 5.0 NA M=1 g/l, teq=1 h 55.2 (L) Ozdemir and Baysal, 2004Chromium (VI) Aeromonas caviae 2.5 20 M=0.5 g/l; teq=2 h 284.4 (L) Loukidou et al., 2004a,b

Bacillus coagulans 2.5 28±3 M=2 g/l, teq=1 h 39.9 (E) Srinath et al., 2002Bacillus licheniformis 2.5 50 M=1 g/l, teq=2 h 69.4 (L) Zhou et al., 2007Bacillus megaterium 2.5 28±3 M=2 g/l, teq=1 h 30.7 (E) Srinath et al., 2002Bacillus thuringiensis 2.0 25 M=1 g/l 83.3 (L) Şahin and Öztürk, 2005Chryseomonas luteola 4.0 NA M=1 g/l, teq=1 h 3.0 (L) Ozdemir and Baysal, 2004Pseudomonas sp. 4.0 NA M=1 g/l, teq=1.5 h 95.0 (L) Ziagova et al., 2007Staphylococcus xylosus 1.0 NA M=1 g/l, teq=1.5 h 143.0 (L) Ziagova et al., 2007Zoogloea ramigera 2.0 25 NA 27.5 (L) Sağ and Kutsal, 1989

Copper Bacillus sp. (ATS-1) 5.0 25 M=2 g/l, teq=2 h 16.3 (E) Tunali et al., 2006Bacillus subtilis IAM 1026 5 25 M=0.5 g/l, teq=1 h 20.8 (L) Nakajima et al., 2001Enterobacter sp. J1 5.0 25 teq=24 h 32.5 (L) Lu et al., 2006Micrococcus luteus IAM 1056 5 25 M=0.5 g/l, teq=1 h 33.5 (L) Nakajima et al., 2001Pseudomonas aeruginosa PU21 5.0 NA M=1–2 g/l; teq=24 h 23.1 (L) Chang et al., 1997Pseudomonas cepacia 7 30 NA 65.3 (L) Savvaidis et al., 2003Pseudomonas putida 6.0 NA NA 6.6 (L) Pardo et al., 2003Pseudomonas putida 5.5 30 M=1 g/l, teq=24 h 96.9 (L) Uslu and Tanyol, 2006Pseudomonas putida CZ1 4.5 30 M=1 g/l; teq=24 h 15.8 (L) Chen et al., 2005Pseudomonas stutzeri IAM 12097 5 25 M=0.5 g/l, teq=1 h 22.9 (L) Nakajima et al., 2001Sphaerotilus natans 6 NA M=3 g/l; teq=0.5 h 60 (E) Beolchini et al., 2006Sphaerotilus natans b 5.5 30 NA 5.4 (L) Beolchini et al., 2006Streptomyces coelicolor 5.0 25 M=1 g/l; teq=8 h 66.7 (L) Öztürk et al., 2004Thiobacillus ferrooxidans a 6.0 37 M=0.2 g/l; teq=2 h 198.5 (L) Ruiz-Manriquez et al., 1997Thiobacillus ferrooxidans a 5.0 40 M=300 g/l; teq=2 h 39.84 (L) Liu et al., 2004

Cadmium Aeromonas caviae 7.0 20 M=1 g/l; teq=2 h 155.3 (L) Loukidou et al., 2004a,bBacillus circulans 7.0 30 M=0.5 g/l; teq=2 h 26.5 (E) Yilmaz and Ensari, 2005Enterobacter sp. J1 6.0 25 teq=24 h 46.2 (L) Lu et al., 2006Pseudomonas aeruginosa PU21 6.0 NA M=1–2 g/l; teq=24 h 42.4 (L) Chang et al., 1997Pseudomonas putida 6.0 NA NA 8.0 (L) Pardo et al., 2003Pseudomonas sp. 7.0 NA M=1 g/l, teq=1.5 h 278.0 (L) Ziagova et al., 2007Staphylococcus xylosus 6.0 NA M=1 g/l, teq=1.5 h 250.0 (L) Ziagova et al., 2007Streptomyces pimprina a 5.0 NA teq=1 h 30.4 (L) Puranik et al., 1995Streptomyces rimosus a 8.0 NA M=3 g/l 64.9 (L) Selatnia et al., 2004a

Iron (III) Streptomyces rimosus a NA NA M=3 g/l; teq=4 h 122.0 (L) Selatnia et al., 2004cLead Bacillus sp. (ATS-1) 3.0 25 M=2 g/l, teq=2 h 92.3 (E) Tunali et al., 2006

Corynebacterium glutamicum 5.0 20±2 M=5 g/l, teq=2 h 567.7 (E) Choi and Yun, 2004Enterobacter sp. J1 5.0 25 teq=24 h 50.9 (L) Lu et al., 2006Pseudomonas aeruginosa PU21 5.5 NA M=1–2 g/l; teq=24 h 79.5 (L) Chang et al., 1997Pseudomonas aeruginosa PU21b 5 50 M=200 g/l 0.7 (L) Lin and Lai, 2006Pseudomonas putida 5.5 25 M=1 g/l, teq=24 h 270.4 (L) Uslu and Tanyol, 2006Pseudomonas putida 6.5 NA NA 56.2 (L) Pardo et al., 2003Streptomyces rimosus a NA NA M=3 g/l; teq=3 h 135.0 (L) Selatnia et al., 2004bStreptoverticillium cinnamoneum a 4.0 28±3 M=2 g/l, teq=0.5 h 57.7 (E) Puranik and Paknikar, 1997

Mercury Bacillus sp. 6 25 M=2 g/l, teq=2 h 7.9 (L) Green-Ruiz, 2006Nickel Bacillus thuringiensis 6 35 M=1 g/l, teq=8 h 45.9 (L) Öztürk, 2007

Streptomyces rimosus a 6.5 NA M=3 g/l, teq=2 h 32.6 (L) Selatnia et al., 2004dPalladium Desulfovibrio desulfuricans 2.0 30 M=0.15 g/l, teq=4 d 128.2 (L) de Vargas et al., 2004

Desulfovibrio fructosivorans 2.0 30 M=0.15 g/l, teq=4 d 119.8 (L) de Vargas et al., 2004Desulfovibrio vulgaris 2.0 30 M=0.15 g/l, teq=4 d 106.3 (L) de Vargas et al., 2004

Platinum Desulfovibrio desulfuricans 2.0 30 M=0.15 g/l, teq=4 d 62.5 (L) de Vargas et al., 2004Desulfovibrio fructosivorans 2.0 30 M=0.15 g/l, teq=4 d 32.3 (L) de Vargas et al., 2004Desulfovibrio vulgaris 2.0 30 M=0.15 g/l, teq=4 d 40.1 (L) de Vargas et al., 2004

Thorium Arthrobacter nicotianae IAM 12342 3.5 30 M=0.15 g/l, teq=1 h 75.9 (E) Nakajima and Tsuruta, 2004Bacillus licheniformis IAM 111054 3.5 30 M=0.15 g/l, teq=1 h 66.1 (E) Nakajima and Tsuruta, 2004Bacillus megaterium IAM 1166 3.5 30 M=0.15 g/l, teq=1 h 74.0 (E) Nakajima and Tsuruta, 2004Bacillus subtilis IAM 1026 3.5 30 M=0.15 g/l, teq=1 h 71.9 (E) Nakajima and Tsuruta, 2004Corynebacterium equi IAM 1038 3.5 30 M=0.15 g/l, teq=1 h 46.9 (E) Nakajima and Tsuruta, 2004Corynebacterium glutamicum IAM 12435 3.5 30 M=0.15 g/l, teq=1 h 36.2 (E) Nakajima and Tsuruta, 2004Micrococcus luteus IAM 1056 3.5 30 M=0.15 g/l, teq=1 h 77.0 (E) Nakajima and Tsuruta, 2004Nocardia erythropolis IAM 1399 3.5 30 M=0.15 g/l, teq=1 h 73.8 (E) Nakajima and Tsuruta, 2004Zoogloea ramigera IAM 12136 3.5 30 M=0.15 g/l, teq=1 h 67.8 (E) Nakajima and Tsuruta, 2004

(continued on next page)


Table 2 (continued)

Metal Organism Operating conditions Uptake (mg/g) Reference


Uranium Arthrobacter nicotianae IAM 12342 3.5 30 M=0.15 g/l, teq=1 h 68.8 (E) Nakajima and Tsuruta, 2004Bacillus licheniformis IAM 111054 3.5 30 M=0.15 g/l, teq=1 h 45.9 (E) Nakajima and Tsuruta, 2004Bacillus megaterium IAM 1166 3.5 30 M=0.15 g/l, teq=1 h 37.8 (E) Nakajima and Tsuruta, 2004Bacillus subtilis IAM 1026 3.5 30 M=0.15 g/l, teq=1 h 52.4 (E) Nakajima and Tsuruta, 2004Corynebacterium equi IAM 1038 3.5 30 M=0.15 g/l, teq=1 h 21.4 (E) Nakajima and Tsuruta, 2004Corynebacterium glutamicum IAM 12435 3.5 30 M=0.15 g/l, teq=1 h 5.9 (E) Nakajima and Tsuruta, 2004Micrococcus luteus IAM 1056 3.5 30 M=0.15 g/l, teq=1 h 38.8 (E) Nakajima and Tsuruta, 2004Nocardia erythropolis IAM 1399 3.5 30 M=0.15 g/l, teq=1 h 51.2 (E) Nakajima and Tsuruta, 2004Zoogloea ramigera IAM 12136 3.5 30 M=0.15 g/l, teq=1 h 49.7 (E) Nakajima and Tsuruta, 2004

Zinc Aphanothece halophytica 6.5 30 M=0.2 g/l, teq=1 h 133.0 (L) Incharoensakdi and Kitjaharn, 2002Pseudomonas putida 7.0 NA NA 6.9 (L) Pardo et al., 2003Pseudomonas putida CZ1 5.0 30 M=1 g/l; teq=24 h 17.7 (L) Chen et al., 2005Streptomyces rimosus 7.5 20 M=3 g/l 30.0 (L) Mameri et al., 1999Streptomyces rimosus a 7.5 20 M=3 g/l 80.0 (L) Mameri et al., 1999Streptoverticillium cinnamoneum a 5.5 28±3 M=2 g/l, teq=0.5 h 21.3 (E) Puranik and Paknikar, 1997Thiobacillus ferrooxidans a 6.0 25 M=0.2 g/l, teq=2 h 82.6 (L) Celaya et al., 2000Thiobacillus ferrooxidans a 6.0 40 M=300 g/l; teq=2 h 172.4 (L) Liu et al., 2004

(E)=experimental uptake, (L)=uptake predicted by the Langmuir model; M=biomass dosage, teq=equilibrium time, NA=not available.a Chemically modified.b Immobilized.


carrageenan. Therefore, utmost care should be taken while select-ing seaweeds for a biosorption process. Many investigators haveworked on brown seaweed and in particular Volesky and his co-workers (Davis et al., 2000; Yang and Volesky, 1999a; Voleskyet al., 2003) investigated the metal sorbing properties of one of thebest metal sorbent Sargassum seaweed. Davis et al. (2003)reviewed the metal sorbing properties of brown seaweeds, andhighlighted their biosorption mechanisms.

Recently, numerous approaches have been made for thedevelopment of low-cost sorbents from industrial and agriculturalwastes. Of these, crab shells (Lee et al., 1997), activated sludge(Al-Qodah, 2006), rice husks (Chuah et al., 2005), egg shell(Vijayaraghavan et al., 2005b) and peat moss (Sharma andForster, 1993) deserve particular attention. Recent publicationsindicate that crab shells possess excellent arsenic (Niu et al.,2007), chromium (Kim, 2003), copper (Vijayaraghavan et al.,2006b), cobalt (Vijayaraghavan et al., 2006b) and nickel sorbentabilities (Vijayaraghavan et al., 2004).

With respect to dye biosorption, microbial biomass (bacteria,fungi, microalgae, etc.) outperformed macroscopic materials (sea-weeds, crab shell, etc.). The reason for this discrepancy is due to thenature of the cell wall constituents and functional groups involvedin dye binding. Many bacteria, fungi and microalgae have beenfound to bind a variety of dye classes. Won et al. (2005) identifiedCorynebacterium glutamicum as a potent biosorbent of Reactivered 4,which can bind 104.6mg/g at pH1.Aksu andÇağatay (2006)indicated that Rhizopus arrhizus was capable of binding 773 mg/gof Gemazol Turquise blue-G at 45 °C and pH 2. Aksu and Tezer(2005) explored the biosorption capacity of Chlorella vulgaris,using several reactive dyes, and identified that the microalga wascapable of binding 419.5mg/g ofRemazol blackB.Very little efforthas beenmade to utilize seaweeds for the biosorption of dyes, but ofnote, Rubin et al. (2004) employed Sargassum muticum for theremoval of methylene blue and Vijayaraghavan and Yun (2008)utilized Laminaria sp. for the removal Reactive black 5.

Hundreds of biosorbents have been proposed for the removalof metals and dyes; therefore, their consolidation in a singlereview would be impossible. Therefore, in this study, bacterialbiosorbents have been taken in general, with other biosorbentsconsidered only in special instances. Hence, the importantaspects of biosorption will be discussed, but will not be limitedto bacteria. Readers are encouraged to refer to other reviews forinformation on fungal (Kapoor and Viraraghavan, 1995), algal(Davis et al., 2003) and other low-cost biosorbents (Crini, 2006).

4. History of bacterial biosorption

Early 1980witnessed the capability of somemicroorganisms toaccumulate metallic elements. Numerous research reports havebeen published from toxicological points of view, but these wereconcerned with the accumulation due to the active metabolism ofliving cells, the effects of metal on the metabolic activities of themicrobial cell and the consequences of accumulation on the foodchain (Volesky, 1987). However, further research has revealed thatinactive/dead microbial biomass can passively bind metal ions viavarious physicochemical mechanisms. With this new finding,research on biosorption became active,with numerous biosorbentsof different origins being proposed for the removal ofmetals/dyes.Researchers have understood and explained that biosorptiondepends not only on the type or chemical composition of thebiomass, but also on the external physicochemical factors andsolution chemistry. Many investigators have been able to explainthe mechanisms responsible for biosorption, which may be one orcombination of ion exchange, complexation, coordination,adsorption, electrostatic interaction, chelation and microprecipita-tion (Vegliò and Beolchini, 1997; Volesky and Schiewer, 1999).

Table 2 summarizes some of the important results of metalbiosorption using bacterial biomasses. A direct comparison ofexperimental data is not possible, due to different systematicexperimental conditions employed (pH, pH control, temperature,

Table 3Important results from the literature on dye biosorption by various bacterial species

Organism Dye Operating conditions Uptake (mg/g) Ref.


Corynebacterium glutamicum Reactive black 5 1.0 35 M=2.5 g/l; teq=12 h 419.0 (L) Vijayaraghavan and Yun, 2007bReactive red 4 1.0 20±2 M=10 g/l; teq=24 h 104.6 (L) Won et al., 2005Reactive orange 16 1.0 20±2 M=10 g/l; teq=24 h 186.6 (L) Won et al., 2004Reactive blue 4 4.0 25±2 M=10 g/l; teq=24 h 173.1 (L) Han and Yun, 2007Reactive yellow 2 1.0 25±2 M=10 g/l; teq=24 h 178.5 (L) Won and Yun, 2008

Streptomyces rimosus Methylene blue NA 20 M=4.5 g/l, 34.3 (L) Nacèra and Aicha, 2006

(L)=uptake predicted by the Langmuir model; M=biomass dosage, teq=equilibrium time, NA=not available.


equilibrium time and biomass dosage). However, Table 2provides basic information to evaluate the possibility of usingbacterial biomass for the uptake of metal ions. Also, it should benoted that Table 2 is only comprised of biosorption studies thatemployed either inactive or dead bacterial biomasses.

Some variability in the results has been observedwhen the samebacterium was employed for the same metal, but under differentinstances. Apart from the different experimental conditions, this isdue to the fact that the biomass was pretreated or immobilized toimprove the biosorbent characteristics, as highlighted in Table 2.Also for most metal ions, weak acidic pH resulted in maximumbiosorption. This is because of the involvement of carboxyl groupand other acidic functional groups, which are responsible forbindingmetal cations through variousmechanisms. In addition, theformation of metal hydroxide and other metal-ligand complexessignificantly reduce the amount of metal ions sorbed at high pH.However, themechanisms for the biosorption have not always beenconfirmed or discussed in most studies; therefore, generalizationsare not possible in these cases. The extent of biosorption not onlydepends on the type of metal ions, but also on the bacterial genus,due to variations in the cellular constituents. Very short contacttimes were generally sufficient to attain metal-bacterial biomasssteady state. This is because biomass was either used in the form offine powder or wet cells; where mass transfer resistances areusually negligible. The rapid kinetics observed with bacterialbiomasses represents an advantageous aspect for the design ofwaste water treatment systems.

Table 3 summarizes some of the important results of dyebiosorption using bacterial biomass. It was surprising to see thatmuch less attention has been paid on employing dead bacterialbiomass for the sorption of dyes. Most of the earlier works on dyebiosorption have focused on utilization of fungal biomasses andother low-cost adsorbents (Fu andViraraghavan, 2001;Crini, 2006).Also, most research focused on studying the biodegradation/deco-lorization potential of bacteria (Forgacs et al., 2004; Pandey et al.,2007). Of the limited results on bacterial biosorption,C. glutamicumhave been shown to performwell in the biosorption of reactive dyes,with dye uptakes in the range of 0.1–0.4 times that of its dry weight.

5. Bacterial structure and mechanism of bacterial biosorption

5.1. Bacterial structure

Bacteria are a major group of unicellular living organismsbelonging to the prokaryotes, which are ubiquitous in soil and

water, and as symbionts of other organisms. Bacteria can befound in a wide variety of shapes, which include cocci (such asStreptococcus), rods (such as Bacillus), spiral (such as Rho-dospirillum) and filamentous (such as Sphaerotilus). Eubacteriahave a relatively simple cell structure, which lack cell nuclei,but possess cell walls (Salton, 1964). The bacterial cell wallprovides structural integrity to the cell, but differs from that ofall other organisms due to the presence of peptidoglycan (poly-N-acetylglucosamine and N-acetylmuramic acid), which islocated immediately outside of the cytoplasmic membrane(Rogers et al., 1980). Peptidoglycan is responsible for therigidity of the bacterial cell wall, and determines the cell shape(Kolenbrander and Ensign, 1968). It is also relatively porousand considered as an impermeability barrier to small substrates.

The cell walls of all bacteria are not identical. In fact, the cellwall composition is one of the most important factors in theanalysis and differentiation of bacterial species. Accordingly,two general types of bacteria exist, of which Gram-positivebacteria (Fig. 1) are comprised of a thick peptidoglycan layer(Beveridge, 1981; Dijkstra and Keck, 1996) connected byamino acid bridges. Imbedded in the Gram-positive cell wall arepolyalcohols, known as teichoic acids, some of which are lipid-linked to form lipoteichoic acids. Because lipoteichoic acids arecovalently linked to lipids within the cytoplasmic membrane,they are responsible for linking peptidoglycan to the cytoplas-mic membrane. The cross-linked peptidoglycan molecules forma network, which covers the cell like a grid. Teichoic acids givethe Gram-positive cell wall an overall negative charge, due tothe presence of phosphodiester bonds between the teichoic acidmonomers (Sonnenfeld et al., 1985). In general, 90% of theGram-positive cell wall is comprised of peptidoglycan.

On the contrary, the cell wall of Gram-negative bacteria(Fig. 1) is much thinner, and composed of only 10–20% pepti-doglycan (Kolenbrander and Ensign, 1968; Beveridge, 1999). Inaddition, the cell wall contains an additional outer membranecomposed of phospholipids and lipopolysaccharides (Sheu andFreese, 1973). The highly charged nature of lipopolysaccharidesconfers an overall negative charge on theGram-negative cell wall.

Sherbert (1978) showed that the anionic functional groupspresent in the peptidoglycan, teichoic acids and teichuronic acidsof Gram-positive bacteria, and the peptidoglycan, phospholi-pids, and lipopolysaccharides of Gram-negative bacteria werethe components primarily responsible for the anionic characterand metal-binding capability of the cell wall. Extracellularpolysaccharides are also capable of binding metals (McLean

Fig. 1. Structure of Gram-positive and negative bacteria.


et al., 1992). However, their availability depends on the bacterialspecies and growth conditions; and they can easily be removedby simple mechanical disruption or chemical washing (Yee andFein, 2001).

5.2. Mechanism of bacterial biosorption

The bacterial cell wall is the first component that comes intocontact with metal ions/dyes, where the solutes can be depositedon the surface or within the cell wall structure (Beveridge andMurray, 1976; Doyle et al., 1980). Since themode of solute uptakeby dead/inactive cells is extracellular, the chemical functionalgroups of the cell wall play vital roles in biosorption. Due to thenature of the cellular components, several functional groups arepresent on the bacterial cell wall, including carboxyl, phospho-nate, amine and hydroxyl groups (Doyle et al., 1980; van der Walet al., 1997).

As they are negatively charged and abundantly available,carboxyl groups actively participate in the binding ofmetal cations.Several dye molecules, which exist as dye cations in solutions, arealso attracted towards carboxyl and other negatively chargedgroups. Golab and Breitenbach (1995) indicated that the carboxylgroups of the cell wall peptidoglycan of Streptomyces pilosuswereresponsible for the binding of copper. Also, amine groups are veryeffective at removing metal ions, as it not only chelates cationicmetal ions, but also adsorbs anionic metal species or dyes viaelectrostatic interaction or hydrogen bonding. Kang et al. (2007)observed that amine groups protonated at pH 3 and attractednegatively charged chromate ions via electrostatic interaction.Vijayaraghavan and Yun (2007b) confirmed that the amine groupsof C. glutamicum were responsible for the binding of reactive dyeanions via electrostatic attraction. In general, increasing the pHincreases the overall negative charge on the surface of cells until allthe relevant functional groups are deprotonated, which favors the

electrochemical attraction and adsorption of cations. Anions wouldbe expected to interact more strongly with cells with increasingconcentration of positive charges, due to the protonation offunctional groups at lower pH values.

The solution chemistry affects not only the bacterial surfacechemistry, but the metal/dye speciation as well. Metal ions insolution undergo hydrolysis as the pH increases. The extent ofwhich differs at different pH values and with each metal, but theusual sequence of hydrolysis is the formation of hydroxylatedmonomeric species, followed by the formation of polymericspecies, and then the formation of crystalline oxide precipitatesafter aging (Baes and Mesmer, 1976). For example, in the caseof nickel solution, López et al. (2000) indicated that within thepH range from 1 to 7, nickel existed in solution as Ni2+ ions(90%); whereas at pH 9, Ni2+ (68%), Ni4OH4

4+ (10%) and Ni(OH)+ (8.6%) co-existed. The different chemical species of ametal occurring with pH changes will have variable charges andadsorbability at solid–liquid interfaces. In many instances,biosorption experiments conducted at high alkaline pH valueshave been reported to complicate evaluation of the biosorbentpotential as a result of metal precipitation (Selatnia et al., 2004b;Iqbal and Saeed, 2007).

5.3. Characterization of bacterial surface

Characterization of bacterial biomass and the biosorptionmechanisms can be elucidated using different methods, includ-ing potentiometric titrations (Texier et al., 2000; Yee and Fein,2001; Phoenix et al., 2002), Fourier transform infrared spectro-scopy (Beveridge and Murray, 1980; Jiang et al., 2004; Vannelaand Verma, 2006), X-ray diffraction (Carito et al., 1967; Lópezet al., 2000; Kelly et al., 2002; Kazy et al., 2006), scanningelectron microscopy (Tunali et al., 2006; Lu et al., 2006;Vijayaraghavan et al., 2007), transmission electron microscopy


(Mullen et al., 1989; Kazy et al., 2006; Vannela and Verma,2006) and energy dispersive X-ray microanalysis (Small et al.,1999; Kazy et al., 2006).

Potentiometric titrations have aided several researchers in thedetermination of the type and number of binding sites. Yee andFein (2001) titrated two Gram-negative and seven Gram-positivebacteria, and determined the pKa values and number of availablebinding sites. Davis et al. (2000) successfully correlated theamount of acidic groups, determined via potentiometric titrations,with the metal uptake capacity. The nature of the binding sites andtheir involvement during biosorption can be approximately eval-uated using FT-IR. Vannela and Verma (2006) analyzed the FT-IRspectra of virgin and Cu2+ exposed Spirulina platensis. Severalband transformations allowed the authors to predict the possibleinvolvement of amide, amino and carboxyl groups in the bio-sorption of Cu2+. Won et al. (2005) used FT-IR spectra to confirmthe presence of carboxyl, amine and phosphonate groups inC. glutamicum biomass.

EDX can provide information regarding the chemical andelemental characteristics of a biomass. Tunali et al. (2006)analyzed both Pb(II) and Cu(II) loaded Bacillus sp. using EDX,and confirmed the involvement of an ion exchange mechanismduring their biosorption. In order to elucidate the chemical natureof bacterial cell-bound lanthanum, Kazy et al. (2006) employedXRD analysis, and confirmed the involvement of cellularcarboxyl and phosphate groups in the binding of lanthanum byPseudomonas biomass. To analyze the morphology of the cellsurface before and after biosorption, SEM micrographs are oftenused. With the aid of SEM photographs, Lu et al. (2006)visualized the surface of metal-loaded Enterobacter sp., whichappeared to be vague and damaged by the heavy-metal ions.Vijayaraghavan et al. (2007) used SEM photographs to show thepattern of C. glutamicum immobilization within a polysulfonematrix. Methods for analyzing the biomass surface and possiblebiosorption mechanism; therefore, are well established.

6. Preparation of bacterial biosorbents

In recent years, interest has been focused on increasing thesorption capacity of the biomass. Several biomasses, regarded asindustrial wastes following certain processes, possess low bio-sorption capacities. As sorptionmainly takes place on the biomasssurface, increasing/activating the binding sites on the surfacewould be an effective approach for enhancing the biosorptioncapacity.

6.1. Chemically modified biosorbents

Chemical modification procedures include pretreatment, bind-ing site enhancement, binding site modification and polymeriza-tion. Common chemical pretreatments include acid, alkaline,ethanol and acetone treatments of the biomass (VijayaraghavanandYun, 2007b; Selatnia et al., 2004a; Göksungur et al., 2005; Baiand Abraham, 2002). The success of a chemical pretreatmentstrongly depends on the cellular components of the biomass itself.In many instances, acidic pretreatment has proved successful; thisis because some of the impurities and ions blocking the binding

sites can easily be eliminated. Vijayaraghavan and Yun (2007b)employed several chemical agents (mineral acids, NaOH,Na2CO3, CaCl2 and NaCl) for the pretreatments ofC. glutamicumin the biosorption ofReactive black 5.The authors identified 0.1MHNO3 as beingmost suitable for opening new binding sites, whichenhanced Reactive black 5 uptake capacity by 1.3 times as that ofthe raw biomass. However, utmost care and careful screeningmethods must be employed for selecting appropriate chemicalagents for pretreatment. Sar et al. (1999) observed that the metal(Cu2+ and Ni2+) uptake capacity of lyophilized Pseudomonasauruginosa cells was enhanced when pretreated with NaOH,NH4OH or toluene; whereas, oven heating (80 °C), autoclaving,acid, detergent and acetone treatments were inhibitory. Eventhough these chemical pretreatments are almost essential for mostof the biosorbents, especially industrial wastes, vast improvementsin their biosorption capacities cannot always be expected.

Conversely, enhancement or modification of the binding siteson a biomass seems to enhance the biosorption capacities bymultiple folds. Carboxyl, amine, phosphonate, sulfonate andhydroxyl groups have become well established as being res-ponsible for metal/dye binding. As the density of these groups islow, most biosorbents show low sorption capacities. Variousprocedures are available for the enhancement of these functionalgroups on the biomass. In general, futile/less important functionalgroups can be converted into active binding groups via severalchemical treatment methods. Jeon and Höll (2003) usedchloroacetic acid to introduce carboxyl in the place of hydroxylgroups. Then the carboxylated biomass was treated with ethyl-enediamine followed by carbodiimide to form aminated biomass.The authors observed that increase in amine groups increasedmercury uptake by 47% compared to that of control. Li et al.(2007) employed citric acid to modify an alkali-saponifiedbiomass, which increased the total acidic sites, but a decrease ofbasic sites. In particular, they reported that biomass modifiedusing 0.6 mol/L citric acid at 80 °C for 2 h exhibited cadmiumuptake capacity twice than that of the raw biomass.

Many studies have focused on enhancing the active bindingsites to improve the biosorption; however, less attention has beenpaid to the inhibition sites. For instance, amine groups areresponsible for the binding of dye anions via electrostaticinteraction; whereas the presence of negatively charged groups,such as carboxyl, may repel dye anions. Vijayaraghavan andYun(2007a) observed biosorption of 111.8 mg Reactive black 5/g forvirgin C. glutamicum, but when the carboxyl groups weremasked from participation, the biomass exhibited biosorption of257.3 mg Reactive black 5/g.

Another efficient way for the introduction of functional groupsonto the biomass surface is the grafting of long polymer chainsonto the biomass surface via direct grafting or polymerization of amonomer. However, very little research has focused specificallyon this aspect. Deng and Ting (2005a,b,c, 2007) workedextensively with polyethylenimine, composed of a large numberof primary and secondary amine groups, whichwhen cross-linkedwith biomass exhibited good biosorption abilities towardschromium (VI), copper, lead, nickel and arsenic. In 2005b,Deng and Ting copolymerized acrylic acid onto the biomasssurface to enhance the carboxyl groups, which resulted in five and


seven fold enhancements for the uptakes of copper and cadmium,respectively, compared with the pristine biomass. Poly(amicacid), from reaction of pyromellitic dianhydride and thiourea,which comprises a large number of carboxyl and secondary aminegroups in a molecule, when grafted on the biosorbent surface,exhibited 15- and 11-fold increases in the uptakes of cadmium andlead, respectively, compared to the pristine biomass. (Yu et al.,2007).

6.2. Genetically modified biosorbents

Genetic engineering has the potential to improve or redesignmicroorganisms, where biological metal-sequestering systemswill have a higher intrinsic capability as well as specificity andgreater resistance to ambient conditions (Bae et al., 2000;Majareand Bulow, 2001). It is well known that virgin biosorbentsusually lack specificity in metal-binding, which may causedifficulties in the recovery and recycling of the desired metal(s).Genetic modification is a potential solution to enhance theselectivity as well as the accumulating properties of the cells(Pazirandeh et al., 1995).

Genetic modification would be feasible especially when themicrobial biomass is produced from fermentation processeswhere genetically engineered microorganisms are used. Nowa-days, many kinds of amino acids and nucleic acids are beingproduced in an industrial scale by using genetically engineeredmicrobial cells.

Higher organisms respond to the presence of metals, with theproduction of cysteine-rich peptides, such as glutathione (GSH)(Singhal et al., 1997), phytochelatins (PCs) and metallothioneins(MTs) (Mehra and Winge, 1991), which can bind and sequestermetal ions in biologically inactive forms (Hamer, 1986; Bae et al.,2000). The overexpression of MTs in bacterial cells will result inan enhanced metal accumulation and; thus, offers a promisingstrategy for the development of microbial-based biosorbents forthe remediation of metal contamination (Pazirandeh et al., 1995).In addition to the high selectivity and accumulation capacity,Pazirandeh et al. (1995) demonstrated that the uptake by re-combinant E. coli (expressing the Neurospora crassa metal-lothionein gene within the periplasmic space) was rapid. Greaterthan 75% Cd uptake occurred in the first 20 min, with maximumuptake achieved in less than 1 h. However, the expression of suchcysteine-rich proteins is not devoid of problems, due to thepredicted interference with redox pathways in the cytosol. Moreimportantly, the intracellular expression of MTs may prevent therecycling of the biosorbents, as the accumulated metals cannot beeasily released (Gadd and White, 1993). Chen and Georgiou(2002) suggested a solution to bypass this transport problem byexpressing MTs on the cell surface. Sousa et al. (1996)demonstrated the possibility of inserting MTs into the permissivesite 153 of the LamB sequence. The expression of the hybridproteins on the cell surface dramatically increased the whole-cellaccumulation of cadmium. Also, the expression of proteins on thesurface offers an inexpensive alternative for the preparation ofaffinity adsorbents (Georgiou et al., 1993).

The use of PCs in a similar manner to MTs has also beensuggested (Bae et al., 2000). PCs are short, cysteine-rich

peptides, with the general structure (γGlu-Cys)nGly (n=2–11)(Zenk 1996). PCs offer many advantages over MTs, due to theirunique structural characteristics, particularly the continuouslyrepeating γGlu-Cys units. Also, PCs have been found to exhibithigher metal-binding capacity (on a per cysteine basis) thanMTs (Mehra and Mulchandani, 1995). However, the develop-ment of organisms overexpressing PCs requires a thoroughknowledge of the mechanisms involved in the synthesis andchain elongation of these peptides.

Several biosorbents, displaying metal-binding peptides on thecell surface, have been successfully engineered. A typical exam-ple includes creating a repetitive metal-binding motif, consistingof (Glu-Cys)nGly (Bae et al., 2000). These peptides emulate thestructure of PCs; however, they differ in the fact that the peptidebond between the glutamic acid and cysteine is a standard αpeptide bond. Phytochelatin analogs were found to be present onthe bacterial surface, which enhanced the accumulation of Cd2+

and Hg2+ by 12- (Bae et al., 2000) and 20-fold (Bae et al., 2001),respectively.

Attempts to create recombinant bacteria with improved metal-binding capacity have so far been restricted to mostlyEscherichiacoli. This is because E. coli greatly facilitates genetic engineeringexperiments and it is found to have more surface area per unit ofcell mass, which potentially should give higher rates of metalremoval from solution (Chen and Wilson, 1997). Nevertheless, aGram-positive surface display system also possesses its ownmerits compared to Gram-negative bacteria (Malik et al., 1998,Samuelson et al., 2000): (a) translocation through only onemembrane is required, and (b) Gram-positive bacteria have beenshown to be more rigid and; therefore, less sensitive to shearforces (Kelemen and Sharpe, 1979) due to the thick cell wallsurrounding the cells, which potentially make themmore suitablefor field applications, such as bioadsorption. Samuelson et al.(2000) generated recombinant Staphylococcus xylosus and Sta-phylococcus carnosus strains, with surface-exposed chimericproteins containing polyhistidyl peptides. Both strains ofstaphylococci gained improved nickel-binding capacities due tothe introduction of theH1orH2 peptide into their surface proteins.

Owing to their high selectivity, genetically engineered bio-sorbents may prove very competitive for the separation of toxinsand other pollutants from dilute contaminated solutions.

6.3. Immobilized biosorbents

Microbial biosorbents are basically small particles, with lowdensity, poor mechanical strength and little rigidity. Even thoughthey have merits, such as high biosorption capacity, rapid steadystate attainment, less process cost and good particle mass trans-fer, they often suffer several drawbacks. The most importantinclude solid–liquid separation problems, possible biomassswelling, inability to regenerate/reuse and development of highpressure drop in the column mode (Vegliò and Beolchini, 1997;Vijayaraghavan and Yun 2007a).

Several established techniques are available to make biosor-bents suitable for process applications. Among these, immobili-zation techniques such as entrapment and cross linking have beenfound to be practical for biosorption (Vegliò and Beolchini, 1997;


Volesky, 2001). Immobilization of microorganisms within apolymeric matrix has exhibited greater potential, especially inpacked or fluidized bed reactors, with benefits including thecontrol of particle size, regeneration and reuse of the biomass,easy separation of biomass and effluent, high biomass loading andminimal clogging under continuous-flow conditions (Hu andReeves, 1997). Very few efforts have been made to utilize theimmobilization concept for dye (Fu and Viraraghavan, 2003;Vijayaraghavan et al., 2007) compared to metal biosorption (Huand Reeves, 1997; Prakasham et al., 1999; Yan andViraraghavan,2001; Khoo and Ting, 2001; Beolchini et al., 2003; Bai andAbraham, 2003). Important immobilization matrices used inbiosorbent immobilization include sodium alginate (Bai andAbraham, 2003; Xiangliang et al., 2005), polysulfone (Beolchiniet al., 2003; Vijayaraghavan et al., 2007), polyacrylamide (Baiand Abraham, 2003) and polyurethane (Hu and Reeves, 1997).The choice of immobilization matrix is a key factor in theenvironmental application of immobilized biomass. The poly-meric matrix determines the mechanical strength and chemicalresistance of the final biosorbent particle to be utilized forsuccessive sorption–desorption cycles (Bai and Abraham, 2003).

However, care must be taken to avoid the practical problemsgenerated during the immobilization process; in particular, themass transfer limitations and additional process costs. Afterimmobilization, the biomass will usually be retained within theinterior of the matrix used for the immobilization; hence, masstransfer resistance will play a vital role in deciding the rate ofbiosorption. The presence of mass transfer resistance usuallyslows the attainment of equilibrium; however, a successfulimmobilization matrix should allow all the active binding sitesto have access to the solute, even at a slower rate. Vijayaraghavanet al. (2007) reported the immobilization ofC. glutamicumwithina polysulfone matrix has delayed the attainment of equilibrium;however, the dye uptake was almost comparable to that of the freebiomass. Next, immobilizing the biomass usually enhances theprocess costs. Biosorption is usually portrayed as a cost effectiveprocess, which is often highlighted as attractive option comparedto that of other proven technologies. Although immobilizing thebiomass for the sole purpose of biosorption will enhance theprocess costs, it is often necessary for practical implementation ofbiosorption in real applications. The need formicrobial biomass inbiosorption applications is arguable especially when there isavailability of highly rigid and efficient biosorbents such asseaweeds. Raw/unprocessed seaweeds have been shown to begood biosorbents for metal ions, and are also highly stable underacidic conditions. Several investigators have successfully regen-erated and reused seaweeds over a number of cycles for theremoval ofmetal ions (Vijayaraghavan et al., 2005a; Senthilkumaret al., 2006). Volesky et al. (2003) regenerated and reused virginSargassum filipendula loaded flow-through packed column overten cycles during the biosorption of copper. However, the stabilityof seaweeds under alkaline conditions is of concern, as they tendto swell under high pH conditions, mainly due to their cellularconstituents. In general, seaweeds are not very efficient in thebiosorption of dyes, due to the nature of the binding sites.Conversely, microbial biomaterials, such as bacteria and fungi,exhibit high metal and dye uptakes. Also, the microbial wastes

generated bymany fermentation/food industries cause a nuisance,and their disposal is of great concern. For instance,C. glutamicum,aGram-positive bacterium, iswidely used for the biotechnologicalproduction of amino acids. Currently, the production of aminoacids from fermentative processes using C. glutamicum amountsto 1,500,000 and 550,000 t per year of L-glutamate and L-lysine,respectively (Hermann, 2003). Hence the waste C. glutamicumgenerated after fermentation is usually high and the potentialutilization of this waste is of interest. Yun and co-workers exam-ined the biosorption potential of C. glutamicum and identified itsexcellent reactive dye binding capacity. However, this biomass isassociated with problems during desorption, as it tends to swellunder alkaline environments. Vijayaraghavan et al. (2007)immobilized C. glutamicum into several polymeric matrices,and identified polysulfone as a favorable and practical immobiliz-ing agent, which showed the ability for the biosorption of reactivedyes over twenty successive sorption–desorption cycles.

A review of literature relating to biosorption revealed thatseveral microbial biomasses have been cultivated and exploredfor their biosorption potential. The cost for producing biomassfor the sole purpose of its transformation into biosorbents hasbeen shown to be too expensive (Tsezos, 2001). Furthermore,the continuous supply of biomass cannot be assured, which willhave a huge impact on its successful application in industrialbiosorption applications.

7. Biosorption experimental procedures

Abiosorption process can be performed via several modes; ofwhich, batch and continuous modes of operation are frequentlyemployed to conduct laboratory scale biosorption processes.Although most industrial applications prefer a continuous modeof operation, batch experiments have to be used to evaluate therequired fundamental information, such as biosorbent efficiency,optimum experimental conditions, biosorption rate and possibi-lity of biomass regeneration.

7.1. Factors influencing bacterial batch biosorption

A schematic representation of the batch biosorption process isillustrated in Fig. 2. Batch experiments usually focus on the studyof factors influencing biosorption, which are important in theevaluation of the full biosorption potential of any biomaterial. Theimportant factors include:

# Solution pH# Temperature# Ionic strength# Biosorbent dosage# Biosorbent size# Initial solute concentration# Agitation rate

Of these, the solution pH usually plays a major role in bio-sorption, and seems to affect the solution chemistry of metals/dyes and the activity of the functional groups of the biomass.For metals, the pH strongly influences the speciation and

Fig. 2. Schematic diagram of batch biosorption equilibrium experimental procedure.


biosorption availability of the metal ions (Yang and Volesky,1999b; Esposito et al., 2002). At higher solution pH, thesolubility of metal complexes decreases sufficiently allowingprecipitation, which may complicate the sorption process. Theactivity of binding sites can also be altered by adjustment of thepH. For instance, during the biosorption of metal ions bybacterial biomass, pH 3 to 6 has been found favorable forbiosorption (Table 2), due to the negatively charged carboxylgroups (pKa=3–5), which are responsible for the binding metalcations via ion exchange mechanism. In the case of thebiosorption of dyes, different dye classes require different pHranges. For instance, basic dyes require alkaline or neutralconditions (Farah et al., 2007); whereas, reactive dyes demandstrong acidic conditions (O'Mahony et al., 2002) for theiroptimum biosorption.

Temperature seems to affect biosorption only to a lesserextent within the range from 20 to 35 °C (Vegliò and Beolchini,1997). Higher temperatures usually enhance sorption due to theincreased surface activity and kinetic energy of the solute (Sağand Kutsal, 2000; Vijayaraghavan and Yun, 2007b); however,physical damage to the biosorbent can be expected at highertemperatures. Due to the exothermic nature of some adsorptionprocesses, an increase in temperature has been found to reducethe biosorption capacity of the biomass (Mameri et al., 1999;Suhasini et al., 1999). It is always desirable to conduct/evaluatebiosorption at room temperature, as this condition is easy toreplicate.

Another important parameter in biosorption is the ionicstrength, which influences the adsorption of solute to thebiomass surface (Daughney and Fein, 1998; Borrok and Fein,2005). The effect of ionic strength may be ascribed to thecompetition between ions, changes in the metal activity, or in theproperties of the electrical double layer. When two phases, e.g.biomass surface and solute in aqueous solution are in contact,they are bound to be surrounded by an electrical double layer

owing to electrostatic interaction. Thus, adsorption decreaseswith increase in ionic strength (Dönmez and Aksu, 2002). Someinorganic ions, such as chloride, may form complexes with somemetal ions and therefore, affect the sorption process (Boro-witzka, 1988).

The dosage of a biosorbent strongly influences the extent ofbiosorption. In many instances, lower biosorbent dosages yieldhigher uptakes and lower percentage removal efficiencies (Aksuand Çağatay, 2006; Vijayaraghavan et al., 2006b). An increasein the biomass concentration generally increases the amount ofsolute biosorbed, due to the increased surface area of thebiosorbent, which in turn increases the number of binding sites(Esposito et al., 2001). Conversely, the quantity of biosorbedsolute per unit weight of biosorbent decrease with increasingbiosorbent dosage, which may be due to the complex interactionof several factors. An important factor at high sorbent dosages isthat the available solute is insufficient to completely cover theavailable exchangeable sites on the biosorbent, usually resultingin low solute uptake (Tangaromsuk et al., 2002). Also, assuggested by Gadd et al. (1988), the interference betweenbinding sites due to increased biosorbent dosages can not beoverruled, as this will result in a low specific uptake.

The size of the biosorbent also plays a vital role in biosorption.Smaller sized particles have a higher surface area, which in turnfavors biosorption and results in a shorter equilibration time.Simultaneously, a particle for biosorption should be sufficientlyresilient to withstand the applicable pressures and extremeconditions applied during regeneration cycles (Volesky, 2001).Therefore, preliminary experiments are mandatory to decide thesuitable size of a biosorbent. If a biosorbent is available inpowdered form, such as industrial waste, efforts should be madeto improve the mechanical strength, such as granulation, for itseffective use in biosorption columns.

The initial solute concentration seems to have impact onbiosorption, with a higher concentration resulting in a high


solute uptake (Ho and McKay, 1999b; Ho and McKay, 2000;Binupriya et al., 2007a). This is because at lower initial soluteconcentrations, the ratio of the initial moles of solute to theavailable surface area is low; subsequently, the fractionalsorption becomes independent of the initial concentration.However, at higher concentrations, the sites available forsorption become fewer compared to the moles of solute presentand; hence, the removal of solute is strongly dependent upon theinitial solute concentration. It is always necessary to identify themaximum saturation potential of a biosorbent, for whichexperiments should be conducted at the highest possible initialsolute concentration.

In some instances, external film diffusion can influence the rateof a biosorption process. With appropriate agitation, this masstransfer resistance can be minimized. When increasing the agi-tation rate, the diffusion rate of a solute from the bulk liquid to theliquid boundary layer surrounding particles becomes higher dueto the enhanced turbulence and the decrease in the thickness of theliquid boundary layer (Evans et al., 2002). Under these condi-tions, the value of the external diffusion coefficient becomeslarger (Shen andDuvnjak, 2005). Finally, at higher agitation rates,the boundary layer becomes very thin, which usually enhances therate at which a solute diffuse through the boundary layer.

7.2. Biosorption isotherms

The quality of a biosorbent is judged by how much sorbate itcan attract and retain in an immobilized form. The solute uptakeby a biosorbent can be calculated from the differences betweenthe initial quantities of solute added to that contained in thesupernatant, which is achieved using the following equation:

Q ¼ V0C0 � VfCfð Þ=M ð1Þwhere Q is the solute uptake (mg/g); C0 and Cf the initial andequilibrium solute concentrations in solution (mg/l), respectively;V0 and Vf the initial and final solution volumes (l), respectively;and M the mass of biosorbent (g). The sorption uptake can beexpressed in different units depending on the purpose of theexercise: for example, milligrams of solute sorbed per gram of the(dry) biosorbent material (the basis for engineering process–massbalance calculations), or mmol/g (when the stoichiometry and/ormechanism are to be considered).

A biosorption isotherm, the plot of uptake (Q) versus theequilibrium solute concentration in the solution (Cf), is often usedto evaluate the sorption performance. Isotherm curves can beevaluated by varying the initial solute concentrations, while fixingthe environmental parameters, such as pH, temperature and ionicstrength. In general, the uptake increases with increase in concen-tration, and will reach saturation at higher concentrations. In mostbiosorption studies, pH seems to be an important parameter for theevaluation of an isotherm. However, confusion prevails in report-ing isotherms based on the pH. In the literature pertaining tobiosorption, isotherms have been reported on the basis of theinitial (Aksu et al., 2002; Fu and Viraraghavan, 2002), final(Reddad et al., 2002) or controlled (Davis et al., 2000; Espositoet al., 2001) pH conditions. This is because; during biosorption,the pH of the reactionmixture tends to change due to the chemical

interaction between the biomass and sorbent. The chemicalconstituents of a biosorbent and the nature of the biosorptionmechanism seem to bemainly responsible for any pH change. Forinstance, a protonated bacterial biomass releases H+ ions duringthe biosorption of metals/dyes, which in turn decreases the solu-tion pH. These changes in pH are rapid during the initial period, asmost of the reaction tends to occur during the initial stage, fol-lowed by slow attainment of equilibrium. Several reports havestressed that the pH should be controlled over the entire contactperiod until equilibrium is reached (Kratochvil and Volesky,1998; Vieira and Volesky, 2000). However, this is a fairlycomplex task, which necessitates sophisticated instrumentation.Also, the addition of chemical agents to maintain the pH at theoptimum level should be incorporated when calculating a specificuptake (Eq. (1)). Biosorption has also been reported on the basisof the final pH, with the claim that final equilibrium pHdetermines the performance of a sorption system. Since batchexperiments are designed to evaluate the fundamental informationregarding a biosorbent, cases where the pH is controlled will givea real picture of the potential of a biosorbent and usage in chemicalequilibrium modeling.

7.3. Batch experimental data modeling

Models have an important role in technology transfer from alaboratory- to industrial-scale. Appropriate models can help inunderstanding process mechanisms, analyze experimental data,predict answers to operational conditions and optimize processes.As an effective quantitative means to compare binding strengthsand design biosorption processes, employing mathematicalmodels for the prediction of binding capacities can be useful(Volesky and Holan, 1995; Limousin et al., 2007).

Biosorption modeling can be performed in two general ways:empirical or mechanistic equations, which are able to explain,represent and predict the experimental behavior.

7.3.1. Empirical modelingEmpirical models are simple mathematical relationships,

characterized by a limited number of adjustable parameters,which give a good description of the experimental behaviorover a large range of operating conditions (Esposito et al.,2002). Some frequently employed and well establishedempirical models involve two, three or even four parametersto model the isotherm data (Vijayaraghavan et al., 2006a).Although these conventional empirical models do not reflectthe mechanisms of sorbate uptake, they are capable ofreflecting the experimental curves (Kratochvil and Volesky,1998). Also, in most cases, the assumptions from which thesemodels were derived are not valid for biosorption. Despite this,conventional adsorption isotherm models are used with a highrate of success for replicating biosorption isotherm curves.Within the literature, the Langmuir (Langmuir, 1918) andFreundlich (Freundlich, 1907) models (two-parameter models)have been used to describe biosorption isotherm. The modelsare simple, well-established and have physical meaning andare easily interpretable, which are some of the important rea-sons for their frequent and extensive use.


The Langmuir model can be represented as:

Q ¼ QmaxbLCf

1þ bLCfð2Þ

This classical model incorporates two easily interpretableconstants:Qmax, which corresponds to the maximum achievableuptake by a system; and bL, which is related to the affinitybetween the sorbate and sorbent. The Langmuir constant “Qmax”is often used to compare the performance of biosorbents; whilethe other constant “bL” characterizes the initial slope of the iso-therm. Thus, for a good biosorbent, a high Qmax and a steepinitial isotherm slope (i.e., high bL) are generally desirable(Kratochvil and Volesky, 1998).

The Freundlich isotherm can be represented as:

Q ¼ KFC1=nFf ð3Þ

The Freundlich isotherm was originally empirical in nature,but was later interpreted as the sorption to heterogeneous surfacesor surfaces supporting sites with various affinities. It is assumedthat the stronger binding sites are initially occupied, with thebinding strength decreasing with increasing degree of siteoccupation. It incorporates two constants: KF, which correspondsto the binding capacity; and nF, which characterize the affinitybetween the sorbent and sorbate.

Some other two-parameter models widely used for describ-ing biosorption isotherms include,

Temkin (Temkin, 1934):

Q ¼ RTbTe

ln aTeCfð Þ ð4Þ

Dubnin–Radushkevich (Dubinin, 1960):

Q ¼ QDexp �BD RT ln 1þ 1Cf

� �� 2" #

ð5Þ

where bTe is the Temkin constant related to the heat of sorption; aTethe Temkin isotherm constant; R the gas constant (8.314 J/mol K);T the absolute temperature; QD the Dubinin–Radushkevich mod-el uptake capacity and BD the Dubinin–Radushkevich modelconstant.

Despite the simplicity of these two-parameter models, somethree-parameter models have also been widely used by investiga-tors, including:

Redlich–Peterson (Redlich and Peterson, 1959):

Q ¼ KRPCf

1þ aRPCbRPf

ð6Þ

Sips (Sips, 1948):

Q ¼ KSCbSf

1þ aSCbSf

ð7Þ

Khan (Khan et al., 1997b):

QmaxbKCf
Q ¼1þ bKCfð ÞaK ð8Þ
Radke–Prausnitz (Radke and Prausnitz, 1972a):

Q ¼ aRrRCbRf

aR þ rRCbR�1f

ð9Þ

Toth (Toth, 1971):

Q ¼ QmaxbTCf

1þ bTCfð Þ1=nTh inT ð10Þ

where KRP is the Redlich–Peterson model isotherm constant,aRP the Redlich–Peterson model constant; βRP the Redlich–Peterson model exponent; KS the Sips model isotherm constant;aS the Sips model constant; βS the Sips model exponent; bK theKhan model constant; aK the Khan model exponent; aR and rRare Radke–Prausnitz model constants; βR the Radke–Prausnitzmodel exponent; bT the Toth model constant and nT the Tothmodel exponent.

Of these three-parameter models, the Redlich–Peterson andSips models have been used with most success (Ho et al., 2002;Vijayaraghavan et al., 2005a). The Redlich–Peterson model iscomprised of an exponent (βRP), which lies between 0 and 1.There are two limiting behaviors: the Langmuir form for βRP=1and Henry's law form for βRP=0. In the case of the Sips model,under low sorbate concentrations, it effectively reduces to theFreundlich isotherm and; thus, does not obey Henry's law. Forhigh sorbate concentrations, it predicts a monolayer sorptioncapacity, characteristic of the Langmuir isotherm (Ho et al.,2002). The descriptions and assumptions of these two- andthree-parameter models have been explained elsewhere (Aksu,2005; Vijayaraghavan et al., 2006a; Limousin et al., 2007).

The most common method found in the literature for thedetermination of the isotherm constants from the two-parametermodels involves the transformation of the isotherm variables sothe equation can be converted into a linear form, with linearregression analysis then applied. Although a linear regressionanalysis is not possible for three- or four-parameter models, a trialand error procedure can be employed (Ho et al., 2002). Recently,there has been concern over the use of the linearization procedure.Linearization of non-linear models distorts the fit, resulting inprediction errors. Also, the use of linearization has becomeobsoletewith recent advancement in computers and software. Thesuccessful predication of isotherm constants should make use ofthese extremely powerful tools for the acquisition of moreaccurate results. Non-linear optimization provides a morecomplex, yet mathematically rigorous, method for determiningisotherm parameter values (Khan et al., 1997a; Ho et al., 2002).

7.3.2. Mechanistic modelingMechanistic models have been proposed to describe solute

adsorption onto the surfaces of biomass (Plette et al., 1995; Feinet al., 1997, 2001; Cox et al., 1999; Haas et al., 2001). Thedevelopment of a mechanistic model is usually based onpreliminary biomass characterization, with the formulation of aset of hypothesized reactions between the sorbent sites andsolutes, which also considers the particular solution chemistryof the solutes. Mechanistic models can often be characterized by


the different degrees of complexity or accuracy in a systemdescription to account for the surface heterogeneity and otherfactors that contribute to non-ideal adsorption phenomena(Pagnanelli et al., 2005). Mechanistic modeling of biosorptionhas been attempted in several investigations, with significantsuccess (Yang and Volesky 1999b; Pagnanelli et al., 2000; Yunet al., 2001).

Yang and Volesky (1999b) used the ion exchange relationshipbetween protons in the biomass and hydrolyzed uranium ionspecies to develop a biosorption model, which was able to predictthe biosorption isotherms at different pH values as well as theequilibrium uranium desorption concentrations. With respect tothe chromium speciation, Yun et al. (2001) developed a model topredict the equilibrium sorption experimental data at different pHvalues and chromium concentrations.Metal hydrolysis was foundto play an important part in the biosorption of chromium, with thedeveloped model able to describe the experimental data with highaccuracy. Yee and Fein (2001) developed an adsorption model tocorrelate the cadmium adsorption behavior over a wide range ofdifferent bacterial species. For this purpose, they employedseveral Gram-positive and -negative bacteria, and postulated thatmetal–bacteria adsorption was not dependent on the bacterialspecies involved. Pagnanelli et al. (2003) formulated mechanisticmodels that accounted for the acidic properties of the cell wallconstituents derived from the characterization of Arthrobacterbiomass. These models revealed the complexity of metal bio-sorption phenomenon and also showed a good agreement with theexperimental data.

From literature accounts, it must be emphasized that empiricalmodels have often been employed to describe experimental data.Greater complexity, the requirement of titration or other biomasscharacterization data and the solution chemistry often limit theapplication of these mechanistic models. However, this approachwould be useful in the understanding and isolation of theoperating binding mechanisms as well as the proper and truerepresentation of experimental sets. Also, it must be stressed thatonly metals, humic (Fein et al., 1999; Borrok and Fein, 2004) andfulvic (Borrok and Fein, 2004) substances had previously beenused as model solutes in mechanistic modeling, with no attemptsmade to consider dyes as the model solute, the reason for which isunknown, but is probably associated with the complication inunderstanding the mechanism of dye sorption by biomaterials.

7.4. Batch kinetic studies

For any practical applications, the process design, operationcontrol and sorption kinetics are very important (Azizian, 2004).The sorption kinetics in a wastewater treatment is significant, asit provides valuable insights into the reaction pathways and themechanism of a sorption reaction (Ho and McKay 1999a). Also,the kinetics describes the solute uptake, which in turn controlsthe residence time of a sorbate at the solid-solution interface (Hoet al., 2000).

Since biosorption is metabolism-independent, it would beexpected to be a rapid process. Usually, free cell microbial bio-sorption is comprised of two phases: a very fast initial uptake for30–60 min, followed by slow attainment of equilibrium within 2

to 3 h (Celaya et al., 2000; Choi and Yun, 2004; Lu et al., 2006).However, when the bacterial biomass is immobilized, a delay inthe attainment of equilibrium would be expected as a result ofmass transfer resistances (Vegliò and Beolchini, 1997; Wu andYu, 2007).

Sorption is a multi-step process, comprising of four con-secutive elementary steps in the case of immobilized beads (Guoet al., 2003): (1) transfer of solute from the bulk of solution to theliquid film surrounding the beads, (2) transport of the solute fromthe boundary liquid film to the surface of the bead (externaldiffusion), (3) transfer of solute from the surface to the internalactive binding sites (intraparticle diffusion), and (4) interactionof the solute with the active binding sites. In general, the first twosteps (external diffusion) are usually fast; as long as sufficientagitation is provided to avoid the formation of a concentrationgradient within solution. If the fourth step is assumed to be rapid,the subsequent intraparticle diffusion becomes the rate-limitingstep. Intraparticle diffusion has often been shown to be animportant factor in deciding the attainment of equilibrium withthe use of immobilized beads (Vijayaraghavan et al., 2007;Vijayaraghavan and Yun, 2007a).

The most commonly used technique for identifying theinvolvement of intraparticle diffusion during sorption is fittingof the kinetic data to an intraparticle diffusion plot, as previouslysuggested by Weber and Morris (1963) which is as follows,

qt ¼ kit1=2 ð11Þ

This involves plotting the uptake at a given time versus thesquare root of that time. If this plot passes through the origin,then intraparticle diffusion is the rate determining step.

Over 25models have been reported in the literature, all of whichhave attempted to quantitatively describe the kinetic behaviorduring the adsorption process (Khraisheh et al., 2002; Ho, 2006).Each adsorption kinetic model has its own limitations, which arederived according to specific experimental and theoreticalassumptions. Even though they violate the fundamental assump-tions, many adsorption models have been used to successfully testexperimental biosorption data. Of these, pseudo-first and -secondorder models have often been used to describe biosorption kineticdata.

Pseudo-first order model

qt ¼ qe 1�exp�k1tð Þð Þ ð12ÞPseudo-second order model

qt ¼ qe 1� 11þ qekt

� �ð13Þ

where qe is the amount of solute sorbed at equilibrium (mg/g); qtthe amount of solute sorbed at time t (mg/g); k1 the first orderequilibrium rate constant (min−1) and k2 the second order equi-librium rate constant (g/mg min). In most published casesinvolving biosorption, the pseudo-first order equation was foundto not fit well over the entire contact time range, but was generallyapplicable over the initial periods of the sorption process. This ismainly due to use of linearized form of Eq. (12), which requiresprevious knowledge of the equilibrium sorption capacity (qe).Therefore, a means of extrapolating the experimental data to t=∞,


or treat qe as an adjustable parameter, has to be employed for atrial and error determination (McKay et al., 1999). Conversely,there is no prior need to know qe for solving the linear form of apseudo-second order equation. It is also based on the sorptioncapacity of the solid phase, which predicts the behavior over theentire study range,with a chemisorptionmechanism being the ratecontrolling step (McKay et al., 1999). Due to above merits, thepseudo-second order equation is able to describe almost all kineticdata originating from metal/dye interactions with biomaterials(Ho and McKay, 1999a; Reddad et al., 2002; Deng and Ting,2005b). Also, it should again be stressed that the use of the non-linear form of equations may avoid this error in kinetic modeling.

8. Desorption and regeneration

Biosorption is a process of treating pollutant-bearing solu-tions to make it contaminant free. However, it is also necessaryto be able to regenerate the biosorbent. This is possible only withthe aid of appropriate elutants, which usually results in aconcentrated pollutant solution. Therefore, the overall achieve-ment of a biosorption process is to concentrate the solute, i.e.,sorption followed by desorption. Desorption is of utmostimportance when the biomass preparation/generation is costly,as it is possible to decrease the process cost and also the de-pendency of the process on a continuous supply of biosorbent. Asuccessful desorption process requires the proper selection ofelutants, which strongly depends on the type of biosorbent andthe mechanism of biosorption. Also, the elutant must be (i) non-damaging to the biomass, (ii) less costly, (iii) environmentalfriendly and (iv) effective. Several investigators have conductedexhaustive screening experiments to identify appropriateelutants for this process. Of these, the work of Kuyucak andVolesky (1989) is noteworthy; they examined several chemicalagents to desorb Co2+ from cobalt-laden Ascophyllum nodosum,and identified CaCl2 in the presence of HCl as a suitable elutant.

Even though some chemical agents perform well in deso-rption, they may be detrimental to the biosorbent. As discussed inSection 7, bacterial biomasses pose problems during desorptiondue to their microscopic structure. They tend to be affected by thepresence of both strong acidic and alkaline conditions, which areoften used during desorption processes. Vijayaraghavan et al.(2007) observed that C. glutamicum performed well in reactivedye biosorption; however, the biomass was severely damagedwhen desorption was attempted using 0.1 M NaOH.

The performance of an elutant also strongly depends on thetype of mechanism responsible for the biosorption. For instance,electrostatic attraction was found to be the main mechanismresponsible for the biosorption of negatively charged dye anionsto a positively charged cell surface (O'Mahony et al., 2002).Therefore, it would be logical to make the cell surface negativeusing alkaline solutions to repel the negatively charged reactivedyes (Won and Yun, 2008).

Elution is also often influenced by the volume of the elutant,which should be as low as practically possible to obtain themaximum solute concentration in the smallest possible volume(Volesky, 2001). At the same time, the volume of the solutionshould be sufficient to provide maximum solubility for the

desorbed solute. Also, one has to realize that the desorbed sorbatestays in the solution and a new equilibrium is established betweenthat and the one (remaining) still fixed on the biosorbent. Thisleads to the concept of a “desorption isotherm”where the equilib-rium is strongly shifted towards the sorbate dissolved in thesolution (Yang and Volesky, 1996). Thus, it is necessary to eval-uate the suitable elutant volume, which can be performed usingexperiments with different solid-to-liquid ratios. The solid-to-liquid ratio is defined as the mass of solute-laden biosorbent to thevolume of elutant. Davis et al. (2000) observed that the solid-to-liquid ratio affected the copper elution efficiency of CaCl2solutions, while it was nearly independent in the case of 0.1 MHCl. The purpose of desorption is to unbind a contaminant from abiosorbent, so both the recovered solute and biosorbent can bereused. After desorption, the biosorbent should be close to itsoriginal form, both morphologically and effectually. Also, duringthe desorption process; removal of all the bound sorbate from thebiosorbent should be assured. If this does not happen, an un-diminished uptake can not be expected in the next cycle. In thefield of bacterial biosorption, Puranik and Paknikar (1999) re-generated and reused polysulfone-immobilizedCitrobacter strainover three cycles for the biosorption of lead, cadmium and zinc,using 0.1 M HCl and 0.1 M EDTA as elutants; but only withlimited success, and emphasized the need for further screeningwork. Beolchini et al. (2003) immobilized Sphaerotilus natansinto a polysulfone matrix for the biosorption of copper, and withthe aid of 0.05 M CaCl2, regenerated and reused the beads over10 cycles, with satisfactory results.

One of the main attractions of biosorption is the potentialability to regenerate the biomass. However, most of the publishedwork has aimed to evaluate the binding ability of biomass and theparameters affecting the process. Less attention has been paid tothe regeneration ability of the biosorbent, which often decides theindustrial applicability of a process. Thus, biosorption studiesshould emphasize the possibility of biomass regeneration toimprove the process viability.

9. Continuous biosorption

Continuous biosorption studies are of utmost importance toevaluate the technical feasibility of a process for real applications.Among the different column configurations, packed bed columnshave been established as an effective, economical and mostconvenient for biosorption processes (Zhao et al., 1999; Saeedand Iqbal., 2003; Volesky et al., 2003; Chu, 2004). They makebest use of the concentration difference, which is known to be thedriving force for sorption, and allow more efficient utilization ofthe sorbent capacity, resulting in better effluent quality (Aksu andGönen, 2004). Also, packed bed sorption has a number of processengineering merits, including a high operational yield and therelative ease of scaling up procedures (Aksu, 2005).Other columncontactors, such as fluidized and continuous stirred tank reactors,are very rarely used for the purpose of biosorption (Prakashamet al., 1999; Solisio et al., 2000). Continuous stirred tank reactorsare useful when the biosorbent is in the form of a powder (Cossichet al., 2004); however, they suffer from high capital and operatingcosts (Volesky, 1987). Fluidized bed systems, which operate

Fig. 3. Schematic diagram of packed column arrangement with biosorption breakthrough and elution curves.


continuously, require high flow rates to keep the biosorbent parti-cles in suspension (Muraleedharan et al., 1991).

9.1. Column biosorption

A schematic representation of a packed bed configuration isshown in Fig. 3, which basically comprises a cylindrical columnpacked firmly with sorbent, through which wastewater is allowedto flow. Initially, most of the solute will be sorbed as it is exposedto the fresh biosorbent bed and; thus, almost zero concentrationwould be expected at the column outlet. Theoretically, this iswhere the highest mass transfer occurs. However, as time isrequired (and column length) for stabilized performance, theinitial column behavior can not be considered as this will onlyrepresent a transient and unsteady state regime (Naja andVolesky,2006a). With increasing time, the biosorbent bed will becomesaturated with solute, the concentration of which will graduallyincrease at the column outlet. Here, the breakthrough/serviceconcentration can be fixed, which depends on the toxicity of thesolute. For most solutes, 0.01 to 1 mg/l is considered the break-through concentration. When the solute concentration exceedsthis limit in real industrial applications, the column has to beremoved from active operation, with the column regenerated orthe flow switched to another column. However, for laboratorytrails, the operation of the column should be terminated onlywheninlet solute concentration approximately equals that at the outlet.This is because complete column saturation, which results in S-shaped breakthrough curve, is important to evaluate thecharacteristics and dynamic response of a biosorption column(Aksu, 2005). A typical breakthrough curve is shown in Fig. 3.Recording the concentration profile at the column exit usuallyresults in a typical S-shaped curve, whose shape and slope are the

result of equilibrium sorption isotherm relationships, mass trans-fer to and throughout the sorbent in the column, and operationalmacroscopic fluid-flow parameters (da Silva et al., 2002).

Various parameters can be used to characterize the perfor-mance of a packed bed biosorption, including the length of thesorption zone, uptake, removal efficiency and slope of thebreakthrough curve (Volesky et al., 2003; Vijayaraghavan et al.,2004). A mass transfer zone will develop between the graduallysaturated section of the column and the fresh biosorbent section(Naja and Volesky, 2006a). The length of this zone is importantpractically, which can be calculated from:

Zm ¼ Z 1� tbte

� �ð14Þ

where Z denotes the bed depth (cm), and tb and te the columnbreakthrough and exhaustion times (h), respectively.

The uptake is an important parameter often used to charac-terize the performance of a biosorbent in a packed column. Thecolumn uptake (Qcol) can be calculated by dividing the total massof biosorbed sorbate (mad) by that of the biosorbent (M). Themassof biosorbed sorbate is calculated from the area above thebreakthrough curve (C vs. t) multiplied by the flow rate.

The removal efficiency (%) can be calculated from the ratioof the sorbate mass biosorbed to the total mass of sorbate sent tothe column, as follows:

Removal efficiency kð Þ ¼ mad

C0Fte� 100 ð15Þ

where C0 and F are the inlet solute concentration (mg/l) andflow rate (l/h), respectively. It is important to note that theremoval efficiency is independent of the biosorbent mass, butsolely dependent on the flow volume. Therefore, it is necessary


to consider both the uptake and removal efficiency when eval-uating the biosorbent potential.

The slope of the breakthrough curve from tb to te (dc / dt) isoften used to characterize the shape of the curve (Volesky et al.,2003). It is always preferential to have an extended breakthroughcurve with a steep slope, as a steep slope is usually the result of ashorter mass transfer zone, which implies a longer column ser-vice time and greater utilization of the sorbent portion inside thecolumn (Kratochvil and Volesky, 1998).

Thus, for good biosorbents, a delayed breakthrough, earlierexhaustion, shortened mass transfer zone, high uptake, steepbreakthrough curve and high removal efficiency would beexpected.

Some microorganisms show high biosorption capacities inbatch tests, but fail when applied to continuous-flow processes.This is because the performance in a column mode stronglydepends on the mechanical strength of biosorbent and the kineticsof the process. This is the reason for non-applicability of freemicrobial biomasses in column mode. Vijayaraghavan and Yun(2007a) indicated that it was not possible to use the free biomassof C. glutamicum in a packed column, as it tended to swell andform dense slurry that blocked the liquid flow, but suggestedimmobilization as a potential remedy to this limitation. However,a column operation provides only a short contact time for soluteand sorbent, and the mass transfer resistances prevailing in im-mobilized beads strongly affect the column biosorption perfor-mance. Therefore, utmost care must be taken in specificallypreparing a biosorbent for use in the column mode. In addition,systematic evaluation of the biosorbent and parameters affectingthe biosorption should be evaluated. Some important parametersaffecting the biosorption in a packed column include, bed depth,flow rate and initial solute concentration.

The accumulation of a solute in a fixed column is largelydependent on the amount of biosorbent loaded into the column.Zulfadhly et al. (2001) reported that the metal uptake increased onincreasing the bed height in a Pycnoporus sanguineus loaded-fixed column. Similarly, Vijayaraghavan et al. (2004) observed anincrease in the nickel biosorption capacitywhen the bed heightwasincreased from 15 to 25 cm in a crab shell loaded packed column.The increase in the uptake capacity with increasing bed depth wasdue to the increased surface area of the sorbent, providing a greateramount of available binding sites for biosorption.

The flow rate is a crucial characteristic in the evaluation ofsorbents for the continuous treatment of effluents in an industrialscale. In general, a low flow rate favors biosorption, which canbe explained as follows: (1) when the flow rate increases, theresidence time of the solute in the column decreases, whichcauses the effluent to leave the column prior to the attainment ofequilibrium; (2) when the process is controlled by intraparticlemass transfer, a slower flow rate favors sorption, but if controlledby external mass transfer, a higher flow rate will decrease thefilm resistance (Ko et al., 2000).

The driving force for a sorption process is the concentrationdifference between the solute on the sorbent and that in thesolution. Thus, an increased inlet solute concentration increasesthe concentration difference, which favors biosorption. Padmeshet al. (2006) indicated during Acid blue 15 biosorption, the

highest initial dye concentration resulted in a favorable break-through curve, as well as high uptake and percentage removal.

9.2. Column regeneration

Regeneration of a biosorbent is relatively easier in a packedcolumn arrangement, with the aid of an appropriate elutant.Whenthe column becomes saturated, the contaminant solution flowshould be switched to the elutant flow. In general, an elutionprocess is usually fast compared to that of sorption. Thus, a highcontaminant concentration in a small elutant volume would beexpected under optimized process conditions. Also, it is alwaysdesirable to limit the contact of the elutant with the sorbent. This isbecause, extreme process conditions such as highly alkaline oracidic solutions are often employed for elution; and thus morpho-logical damage to the biosorbent can be expected. Therefore, theoptimal flow rate for the elution should be identified forsuccessful reuse of the biosorbent over multiple cycles. A typicalelution curve is shown in Fig. 3. Usually, a sharp concentrationincrease would be expected at the beginning, followed by a grad-ual decrease (Volesky et al., 2003; Vijayaraghavan et al., 2005a).

Even with the successful optimization of an elution process,several investigators have observed a decrease in the biosorp-tion performance over subsequent cycles (Saeed and Iqbal,2003; Volesky et al., 2003; Vijayaraghavan et al., 2004). A lossof sorption performance during long-term use may occur for avariety of reasons; changes in the chemistry and structure of thebiosorbent, as well as the flow and mass transport conditionswithin the column.

From the literature, it is evident that very few attempts have beenmade to examine bacterial biomass in a continuous mode of oper-ation. Many investigators have proposed the suitability of bacterialbiomass for industrial applications, based on batch experimentalresults. As discussed earlier, a continuous mode of operation ispreferred formost industrial applications and; thus, only careful andsystematic investigation of biosorbent performance in a columnmode will ensure its application in real situations.

9.3. Modeling of column data

Mathematical models for flow-through fixed bed columnshave mainly originated from research on activated carbon sorp-tion and ion exchange or chromatographic applications. Numer-ous models have been tested for fixed bed biosorption columns,including:

Bohart–Adams model (Bohart and Adams, 1920):

CC0

¼exp kABC0t � kABN0ZU0

� �ð16Þ

Thomas model (Thomas, 1944):

C0

C¼ 1þexp

kTHF

Q0M � C0Veffð Þ� �

ð17Þ

Yoon–Nelson model (Yoon and Nelson, 1984):

CC0

¼ exp kYNt � skYNð Þ1þexp kYNt � skYNð Þ ð18Þ


Modified dose–response model (Yan et al., 1999):

CC0

¼ 1� 1

1þ Veffbmdr

� �amdrð19Þ

Clark model (Clark, 1987):

CC0

¼ 1

1þ Cn�10

Cn�1break

� 1� �

ertbreake�rt

0B@

1CA

1=n�1

ð20Þ

where kAB is the Bohart–Adams rate constant (ml/min mg);N0 thebed saturation capacity (mg/l); U0 the superficial velocity (cm/min); kTH the Thomas model rate constant (ml/min mg); Q0 themaximum solid-phase concentration of the solute (mg/g); Veff thevolume of solute passed into the column (l); kYN the Yoon–Nelsonmodel rate constant (1/min); τ the time required for 50% sorbatebreakthrough (min); amdr and bmdr the modified dose–responsemodel constants; n the Freundlich constant; r the adsorption rate(mg/l min); and Cbreak and tbreak the breakthrough concentration(mg/l) and time (min), respectively.

The successful design of a column sorption process requiresthe concentration-time profile or effluent breakthrough curve tobe predicted (Volesky and Prasetyo, 1994); the maximum sorp-tion capacity of a sorbent is also required in the design. Both theBohart–Adams and Thomas models have been found to fulfillthis purpose and thus widely applied to many investigations.Texier et al. (2002) successfully employed the Bohart–Adamsmodel to determine the characteristic parameters during thebiosorption of lanthanide ions onto Pseudomonas aeruginosa.Addour et al. (1999) used a linearized Thomas equation todescribe the biosorption of zinc by Streptomyces rimosus bio-mass, and successfully calculated the maximum biosorptioncapacity. Despite its wide usage, the Thomas model suffers amajor disadvantage i.e., it has a fixed value when the experi-mental time is zero, which will not be the case in reality. Yanet al. (1999) highlighted this aspect and proposed a new model(modified-dose response), which minimized the error resultingfrom the use of the Thomas model.

Apart these models, several investigators have used masstransfer and mechanistic models to describe column biosorption(Kratochvil and Volesky, 2000; Hatzikioseyian et al., 2001;Zulfadhly et al., 2001; Naja and Volesky, 2006a). Since themechanism responsible for dye/metal biosorption onto biologi-cal materials is different from that of activated carbon, it is notappropriate to employ conventional column adsorption modelswith these types of biosorption data (Naja and Volesky, 2006a).However, careful understanding of the mechanism and itsincorporation into the model might be an appropriate approachtowards column modeling.

10. Multicomponent systems

Considerable amount of information is available on the bio-sorption of single-component systems, but many industries dis-charge effluents that contain several components. Correspondingly,knowledge of how one solute may influence the uptake of another

is desirable. Many studies have analyzed biosorbents using puremetal/dye solutions, with their use recommended for real effluentswhich is usually misleading as the behavior of a biosorbent tends todiffer inmulticomponent systems. In these systems, the biosorptionof the solute of interest not only depends on the biomass surfaceproperties and physical–chemical parameters of a solution such aspH and temperature, but also on the number of solutes and theirconcentrations. In such cases, the biosorption will become com-petitive, with one solute competing with another to occupy thebinding sites.

Multicomponent biosorption has been the subject of limitedstudies (Kratochvil and Volesky, 2000; Sağ et al., 2000, 2001;Pagnanelli et al., 2002; Borrok and Fein, 2004; Borrok et al.,2004; Naja and Volesky, 2006b; Park et al., 2006). The extent ofcompetition and nature of the mechanism in multicomponentsystems should be clearly understood. However, with theexception of a few cases, the mechanism and competition effecthave been inadequately understood. Biosorption depends on thesize and relative concentration of each solute, which usually playvital roles in deciding the nature of competition between solutes.Maurya et al. (2006) reported that during the biosorption ofMethylene blue and Rhodamine B, the ionic radii played a vitalrole and; owing to its greater ionic radius, Methylene blue wasbiosorbed to a greater extent than Rhodamine B. However, somestudies revealed that the ionic radii cannot be used as soledeciding factor when interpreting high solute biosorption duringmulticomponent systems. For instance, Texier et al. (1999) ob-served no correlation with the ionic radius, as the smaller sizedytterbium ions were found to be significantly affected in the pre-sence of the larger lanthanum ions. Metal biosorption by bacteriacan also be influenced bymetal speciation in the aqueous phase aswell as by the surface properties, such as charge and orientation ofthe functional groups on the cell surface. Premuzic et al. (1991)showed that in addition to metal selectivity, there was also aspecies-dependent differentiation in the uptake capacity. Theseauthors also found significant differences in the uptake of uraniumand thorium by two strains of P. aeruginosa.

Comparatively, multi-metal biosorption has been more ex-tensively studied than multi-dye systems. The reason for this isunclear, but it is our belief that it is not associatedwith the analysisof multi-dye solutions. The spectrophotometric procedure fordetermining the concentration of each dye in a binary system iswell established, and has been successfully employed in somebiosorption studies; however, its validity strongly depends on thesolution chemistry of each dye (Al-Duri and McKay, 1991).

The prediction ofmulticomponent biosorption data has alwaysbeen complicated due to the interactive and competitive effectsinvolved. Consequently, the appropriate selection of a model,where the competitive mechanism is taken into account is crucial.However, an analysis of the literature revealed that single-compo-nent isotherm data have frequently been used to predict multi-component data. The extended Langmuir equation is one suchmodel, which has been widely employed for multicomponentadsorption data (Sağ et al., 1998; Choy et al., 2000). This modelassumes a constant energy of sorption, no interaction betweencomponents and equal competition between species for the sorp-tion sites (Choy et al., 2000). These assumptions are not valid


under real conditions, since sorbate interactions tend to occur inmulticomponent systems. To incorporate sorbate–sorbate inter-action and competition, an interaction factor (η) has been intro-duced in an extended Langmuir equation (McKay and Al-Duri,1987), which for binary mixtures has the following forms:

Q1 ¼ Qmax1b1 C1=g1ð Þ1þ b1 C1=g1ð Þ þ b2 C2=g2ð Þ ð21Þ

Q2 ¼ Qmax2b2 C2=g2ð Þ1þ b1 C1=g1ð Þ þ b2 C2=g2ð Þ ð22Þ

These equations have been used with some success (Choyet al., 2000; Aksu and Isoglu, 2007); however, the use of single-component data to describe a multicomponent isotherm oftenlimits its applicability. Similarly, Sheindrof et al. (1981)proposed a multicomponent Freundlich type equation, whichincluded a competitive coefficient (θij), based on the assumptionthat there is an exponential distribution of adsorption energiesavailable for each solute. This can be represented as follows:

Qð Þ ji¼ KFiCfi Cfi þ hijCfj

� 1=nið Þ�1½ � ð23Þwhere (Q)i

j is the amount of solute, i, sorbed per unit weight ofsorbent in the presence of solute j, KFi the single-componentFreundlich constant for solute i and ni the Freundlich exponentfor solute i. Eq. (23) also involves single-component equilibriumdata and thus, often fail to accurately calculate experimentalmixture equilibria. In addition to the two equations above, severalequations; for example, those of Fritz and Schluender (1974),Crittenden andWeber (1978) and Khan et al. (1996, 1997a), withadditional adjustable parameters have been proposed. However,as the number of solutes in a mixture increases, the number ofadditional parameters to be determined from the experimentalmixture equilibria becomes higher, where the use of these equa-tions becomes impractical.

The Ideal Adsorbed Solution (IAS) theory has been successfullyused to characterize the competitive adsorption for activatedcarbons. Myers and Prausnitz (1965) presented the IAS theory forgaseous phase multicomponent adsorption. Radke and Prausnitz(1972b) later extended the IAS theory to dilute liquid solutions.Suzuki and Misic (1973) applied the Freundlich isotherm to theIAS theory, and developed easy-to-use equations for the estimationof multicomponent equilibria. Finally, Furuya et al. (1986) exten-ded Suzuki's model, and developed a technique to determine theisotherm parameters from multicomponent aqueous samples.

Apart from being widely used for gas-phase sorption ofhydrocarbons (Li and Orhan, 1994), the IAS theory has becomethe focus to study the sorption of dyes/metals onto adsorbents(Ko et al., 2004; Choy et al., 2004). The major advantages of theIAS theory are that it has a sound thermodynamic basis andrequires only single-component isotherm parameters to predictthe sorption equilibrium for a multicomponent system. The IAStheory is based on the assumption that the adsorbed phase can betreated as an ideal solution to that of the adsorbed components.The theory has proved successful in several cases; for instance,Choy et al. (2004) tested four isotherms using the IAS theory,namely the Langmuir, Freundlich, Redlich–Peterson and Sips

isotherms. Of the isotherms examined, the authors identified theIAST-Redlich–Peterson model provides the best prediction ofthe binary data for the sorption of acidic dyes onto activatedcarbon. However, the IAS theory requires time-consuminggraphical solutions or extensive computational methods.

Few investigators have attempted to perform mechanisticmodeling of multicomponent biosorption data. Chong andVolesky (1995) proposed a mechanistic model that considerednot only a Langmuir type interaction, but also the simultaneouspresence of ion exchange reactions, which took into account thepossible effect of the reverse reactions of the displaced ionsactually present at the beginning on the active sites. Fowle andFein (1999) proposed a mechanistic model for both binary andternary metal biosorption onto two Gram-positive bacteria. Thismodel considered the metal speciation, and hypothesized a setof reactions, combining constants and site balances.

As a concluding remark, it should be highlighted that veryless work has been performed on the study of the competitioneffects during biosorption especially in the case of dyes. Theproper understanding and evaluation of competition mechan-isms are mandatory for the successful application of biosorptionto real effluents.

11. Application of biosorption to real industrial effluents

As highlighted in the previous sections, biosorption is a proventechnique potentially for the removal ofmetals/dyes from aqueoussolutions. However, its performance under real industrial condi-tions is of concern. There have been few investigations examiningthe compatibility of the biosorbent for real industrial effluents.Kratochvil and Volesky (1998) explained the necessity ofextended testing of a biosorption process before its commercialapplication. In general, industrial effluents can be classified intotwo broad categories: those bearing low contaminant concentra-tions in large volumes, i.e. mining wastewaters, and those charac-terized by high TDS values in small volumes, i.e. electroplatingand textile dye bath effluents. For the first case, a biosorbent withstrong affinity towards the contaminant of interest is mandatory;whereas, the latter case requires a biosorbent with high uptakecapacity (Atkinson et al., 1998). However, irrespective of theeffluent, interference by counter ions, such as light metal ions,should be considered. Vijayaraghavan et al. (2006c) characterizedtwo effluents originating from nickel electroplating industries,which contained high amounts of light metal ions and anions,coupled with high nickel concentrations. They observed stronginterference from co-ions during the removal of nickel(II) in bothbatch and columnmodes of operation. The presence of anions canlead to the following: 1) Formation of complexes with higheraffinity for the sorbent than the free metal ions (i.e., an enhance-ment of sorption); 2) Formation of complexes with lower affinityfor the sorbent than free metal ions (i.e., a reduction of sorption)(Volesky and Schiewer, 1999). There may be instances, owing tothe occurrence of competitive ion exchange in the column, whereone ormore of the contaminants present at trace levelsmay exceedthe acceptable column effluent limit well before the targetedcontaminant, thereby reducing the column service time (Kratoch-vil and Volesky, 1998).


Since mixtures are comprised of organic as well as inorganicconstituents, it is often mandatory to study the solution chemistryof the effluents for the proper implementation of biosorptiontechnology. If necessary, an appropriate effluent pretreatmentshould be performed prior to applying the biosorption process. Ithas been reported that extreme characteristics (pH, conductivityand total hardness) may affect the binding abilities of a biosorbent(Vijayaraghavan et al., 2006c). As indicated previously, therehave been very few reports on employing biosorbents for realeffluents; of which Tobin and Roux (1998) used Mucor meihibiomass to remove chromium from tanning industry effluents.The authors thoroughly characterized the effluent and success-fully removed chromium from the effluent; with performancescorresponding closely to those of commercial ion exchange res-ins. In another study, Aravindhan et al. (2004) used Turbinariaspp. to treat a tanning industry effluent comprising of 750 mg/lchromium. As the Cr(III) concentration was high, the authorsemployed a five stage biosorption process, which successfullyreduced the Cr(III) concentration to 2 mg/l.

Considering the number of biosorbents proposed for metal/dye removal, it would be expected that more attempts be made tocommercialize biosorption in the fields of wastewater treatment.However, there have only been few instances where biosorptionprocesses have managed to reach commercialization. One suchexample involved the process developed by AMT-Bioclaim™,which comprises of Bacillus subtilis, treated using strong causticsolution, washed with water, and immobilized as porous ballsonto polyethyleneimine and glutaraldehyde (Brierley, 1990).This commercial biosorbent is capable of accumulating gold,cadmium and zinc from cyanide solutions and; therefore, wouldbe suitable for many metal-finishing operations (Atkinson et al.,1998). The biosorbent BIO-FIX is made up of a variety ofbiomasses, including bacteria, fungi, sphagnum peat moss andalgae, immobilized onto high density polysulfone. Thisbiosorbent has been found to be selective for toxic heavy metalsover that of alkaline earth metals. The biosorbent AlgaSORBconsists of C. vulgaris and other non-living algae immobilizedin a silica gel matrix (Brierley, 1990). The material has shownremarkable heavy-metal ion affinities; for instance when appliedat US nuclear sites to clean up ground water contaminated withuranium and mercury, at concentrations of 200 and 30 μg/l,respectively, it exhibited process efficiencies of about 95% forboth metals (Eccles, 1995). However, other attempts have failedto obtain successful commercial application in the market(Tsezos, 2001). To the best of our knowledge, no biosorbentcapable of accumulating dye has reached the commercial level.

Atkinson et al. (1998) highlighted questions that should beconsidered relating to the feasibility of a potential biosorbent for theremoval of metals/dyes from industrial effluents. These includesthe effluent characteristics, such as volume, type of contaminantand competitive ions, solution chemistry, pH and temperatureadjustment; biomass characteristics, such as availability, mechan-ical stability, regeneration ability, contaminant specificity andreaction kinetics; and process characteristics, such as capital andoperating costs, batch/continuous and land space requirements.

The design and type of process to be employed (batch/con-tinuous) is entirely dictated by the choice of biomass and its

method of immobilization. If it is feasible to operate a biomass in abatch contactor configuration, the initial capital expenditure forthe process development and setup can be estimated as beingsimilar to that of chemical precipitation methods. Both systemsrequire the same basic equipments, such as a contact vessel, somemode of agitation, piping and other peripheral equipment, includ-ing pH probes and level controllers (Atkinson et al., 1998). Ifproper and cheap immobilization techniques are available, abiosorbent can be used in a packed or fluidized column mode ofoperation. The choice can be made on whether to use an up-flowor down-flow packed column, but the latter is the most costeffective to operate; however, there is no control over the effluentretention times, which may affect the biosorbent capacity. Thewaste stream may also allow for passing through the columns/reactors in series, where more effective results will be obtained.However, care must be taken that the automation and complexityof a treatment facility may substantially increase the costs.

Other important aspects requiring consideration are the costand availability of the biomass. Even if the biomass can beacquired free of charge, the processing and transportation costsshould be considered. Almost all biomasses require drying andchemical pretreatment, at least with acid or alkali pretreatment,for their effective performance. As with any industrial process,the nearer the source of raw material to the point of application,the more feasible will be the process. Tsezos (2001) clearlypointed out that successful biosorption technology not onlydepends on the biosorption potential, but also on the continuoussupply of biomass for the process. The source for raw materialmust be enthusiastic to secure a steady supply of waste biomass.

12. Fate of exhausted biosorbent

One of the more common questions aroused by biosorptionprocesses involves the fate of the biosorbent after the process.Also, the fate of the concentrated metal/dye solutions obtainedafter the elution process remains relatively unanswered. Caremust be taken that solving one problem should not createanother. Since the ultimate purpose of a biosorption process is toconcentrate a solute, very high concentrations, in the order of 10times higher than that of the initial solute, can commonly beexpected by the end of elution process (Vijayaraghavan et al.,2006c). The recovery of a solute from these high concentratedsolutions can be accomplished using another process, such asprecipitation or electrowinning. Volesky and Schiewer (1999)suggested it is often feasible to use electrowinning procedures torecover metals from concentrated solutions. Binupriya et al.(2007b) desorbed Reactive blue MR from dye-loaded Trametesversicolor using ethanol and; thereby suggested that Reactiveblue MR-rich ethanol medium can be distilled to remove dyesand the recovered dye can be used as low-grade dyes in coloredglass, plastic and ceramic industries.

Even if the biosorbent can be efficiently reused over severalcycles, the final disposal of the material should be addressed.The common answer to the disposal of the final material is vialandfill or incineration. However, due to the increasing levels oflandfill tax, and the potential restrictions due to contaminationof ground waters, the landfill option has become less attractive.


Alternatively, when recycling is not considered worthwhile,biomass combustion would yield ash with a high concentrationof the desired metal (Volesky, 1987). This case would not befeasible if the biomass was immobilized in a polymeric matrix.

If the biomass is free of cost, or the transportation and pro-cessing costs areminimal, themetal or dye loaded biosorbents canbe used to sorb other solutes. For example, with molybdate-loaded chitosan beads, the chelating affinity of molybdate forarsenic has been used for the recovery of As(V) from dilutesolutions (Dambies et al., 2000). In another instance, Cibacronblue F3GA-attached polyvinylbutyral microbeads have beenshown to be effective in the removal of Cu(II), Cd(II) and Pb(II)ions (Denizli et al., 1998).

However, one should understand that waste microbial bio-masses originating from their respective industries are alreadycreating a disposal nuisance. The biosorbents developed fromthese waste microbial biomasses are; thereby, solving their owndisposal problems as well as adding value to their waste. Thedeveloped biosorbent, after serving multiple times in the re-mediation of metal/dye polluted effluents, should be regarded ashaving served its purpose.

13. Scope and future directions

Bacterial biomass represents an efficient and potential classof biosorbents for the removal of both dyes and metal ions.Unfortunately, the difficulties in reusing the microbial biomass,as well as the poor selectivity, hinder their applications underreal conditions. Although some attempts have been made at thecommercialization of biosorption for wastewater treatment, theprogress is very modest considering that there has been morethan a decade of fundamental research. The important featuresrequired for the successful application of biosorption technol-ogy to real situations include, but are not limited to:

◆ Screening and selection of the most promising biomass, withsufficiently high biosorption capacity and selectivity.

◆ Optimizing the conditions for maximum biosorption,including optimization of pH, temperature, ionic strengthand co-ion effects, etc

◆ Improving the selectivity and uptake via chemical and/orgenetic modification methods.

◆ Examining the mechanical strength of biomass and ifinsufficient for reuse, improving rigidity by proper immo-bilization or other chemical methods.

◆ Testing the performance of biosorbents under differentmodes of operation.

◆ Analyzing the behavior of biosorbent for use with realindustrial effluents and, simultaneously analyzing the impactof water quality on the biosorption uptake of the specificpollutant of interest.

Conversely, it is no small feat to replace well establishedconventional techniques. However, in addition to being costeffective, biosorption has huge potential, as many biosorbents areknown to perform well, if not better than most conventionalmethods. Also being aware of the hundreds of biosorbents able to

bind various pollutants, sufficient research has been performed onvarious biomaterials to understand the mechanism responsible forbiosorption. Therefore, through continued research, especially onpilot and full-scale biosorption process, the situation is likely tochange in the near future, with biosorption technology becomingmore beneficial and attractive than currently used technologies.

Acknowledgements

This work was supported by a grant from the Post-Docprogram, Chonbuk National University (the second half term of2006) and, in part, by KOSEF through AEBRC at POSTECH.The authors would like to express sincere thanks to all researchersof Environmental Biotechnology Laboratory (Chonbuk NationalUniversity), for their help. Finally, the authors would like to thankone anonymous journal reviewer who provided constructivecomments in the improvement of this manuscript.

References

Addour L, Belhocine D, Boudries N, Comeau Y, Pauss A, Mameri N. Zincuptake by Streptomyces rimosus biomass using a packed-bed column.J Chem Technol Biotechnol 1999;74:1089–95.

Aksu Z. Application of biosorption for the removal of organic pollutants: areview. Process Biochem 2005;40:997–1026.

Aksu Z, Gönen F. Biosorption of phenol by immobilized activated sludge in acontinuous packed bed: prediction of breakthrough curves. Process Biochem2004;39:599–613.

Aksu Z, Tezer S. Biosorption of reactive dyes on the green alga Chlorellavulgaris. Process Biochem 2005;40:1347–61.

Aksu Z, Çağatay SS. Investigation of biosorption of Gemazol Turquise Blue-Greactive dye by dried Rhizopus arrhizus in batch and continuous systems.Sep Purif Technol 2006;48:24–35.

Aksu Z, Isoglu IA. Use of dried sugar beet pulp for binary biosorption ofGemazol Turquoise Blue-G reactive dye and copper(II) ions: equilibriummodeling. Chem Eng J 2007;127:177–88.

Aksu Z, Gönen F, Demircan Z. Biosorption of chromium(VI) ions by Mowital(R)B30H resin immobilized activated sludge in a packed bed: comparisonwith granular activated carbon. Process Biochem 2002;38:175–86.

Al-Duri B, McKay G. Prediction of binary systems for kinetics of batchadsorption using basic dyes onto activated carbon. Chem Eng Sci1991;46:193–204.

Al-Qodah Z. Biosorption of heavy metal ions from aqueous solutions byactivated sludge. Desalination 2006;196:164–76.

Aravindhan R, Madhan B, Raghava Rao J, Unni Nair B. Recovery and reuse ofchromium from tannery wastewaters using Turbinaria ornata seaweed.J Chem Technol Biotechnol 2004;79:1251–8.

Atkinson BW, Bux F, Kasan HC. Considerations for application of biosorptiontechnology to remediate metal-contaminated industrial effluents. Water SA1998;24:129–35.

Azizian S. Kinetic models of sorption: a theoretical analysis. J Colloid InterfaceSci 2004;276:47–52.

Bae W, Chen W, Mulchandani A, Mehra RK. Enhanced bioaccumulation ofheavy metals by bacterial cells displaying synthetic phytochelatins.Biotechnol Bioeng 2000;70:518–24.

Bae W, Mehra R, Mulchandani A, Chen W. Genetic engineering of Escherichiacoli for enhanced uptake and bioaccumulation of mercury. Appl EnvironMicrobiol 2001;67:5335–8.

Baes CF, Mesmer RE. The Hydrolysis of Cations. New York: John Wiley andSons; 1976. p. 241–310.

Bai RS, Abraham TE. Studies on enhancement of Cr(VI) biosorption by chemicallymodified biomass of Rhizopus nigricans. Water Res 2002;36:1224–36.

Bai RS, Abraham TE. Studies on chromium(VI) adsorption–desorption usingimmobilized fungal biomass. Biores Technol 2003;87:17–26.


Banat IM, Nigam P, Marchant R. Microbial decolorization of textile-dye-containing effluents: a review. Biores Technol 1996;58:217–27.

Beolchini F, Pagnanelli F, Toro L, Vegliò F. Biosorption of copper by Sphaer-otilus natans immobilised in polysulfone matrix: equilibrium and kineticanalysis. Hydrometallurgy 2003;70:101–12.

Beolchini F, Pagnanelli F, Toro L, Vegliò F. Ionic strength effect on copperbiosorption by Sphaerotilus natans: equilibrium study and dynamicmodelling in membrane reactor. Water Res 2006;40:144–52.

Beveridge TJ. Ultrastructure, chemistry and function of the bacterial wall. IntRev Cytol 1981;72:229–317.

Beveridge TJ. Structures of Gram-negative cell walls and their derivedmembrane vesicles. J Bacteriol 1999;181:4725–33.

Beveridge TJ, Murray RGE. Uptake and retention of metals by cell walls ofBacillus subtilis. J Bacteriol 1976;127:1502–18.

Beveridge TJ, Murray RGE. Sites of metal deposition in the cell wall of Bacillussubtilis. J Bacteriol 1980;141:876–87.

Binupriya AR, Sathishkumar M, Swaminathan K, Jeong ES, Yun SE, Pattabi S.Biosorption of metal ions from aqueous solution and electroplating industrywastewater by Aspergillus japonicus: Phytotoxicity studies. Bull EnvironContam Toxicol 2006;77:219–27.

Binupriya AR, Sathishkumar M, Kavitha D, Swaminathan K, Yun SE, Mun SP.Experimental and isothermal studies on sorption of Congo red by modifiedmycelial biomass of wood-rotting fungus. Clean 2007a;35:143–50.

Binupriya AR, Sathishkumar M, Kavitha D, Swaminathan K, Yun SE. Aeratedand rotated mode of decolorization of a textile dye solution by native andmodified mycelial biomass of Trametes versiocolor. J Chem TechnolBiotechnol 2007b;82:350–9.

Bohart G, Adams EQ. Some aspects of the behavior of charcoal with respect tochlorine. J Am Chem Soc 1920;42:523–44.

Borowitzka MA. Algal media and sources of algal cultures. In: Borowitzka MA,Borowitzka LJ, editors. Micro-algal technology. Cambridge: Cambridgeuniversity press; 1988. p. 456–65.

Borrok D, Fein JB. Distribution of protons and Cd between bacterial surfacesand dissolved humic substances determined through chemical equilibriummodeling. Geochim Cosmochim Acta 2004;68:3043–53.

Borrok DM, Fein JB. The impact of ionic strength on the adsorption of protons,Pb, Cd, and Sr onto the surfaces of Gram negative bacteria: testing non-electrostatic, diffuse, and triple-layer models. J Colloid Interface Sci2005;286:110–26.

Borrok D, Fein JB, Kulpa CF. Proton and Cd adsorption onto natural bacterialconsortia: testing universal adsorption behavior. Geochim Cosmochim Acta2004;68:3231–8.

Brierley CL. Bioremediation of metal-contaminated surface and ground waters.Geomicrobiol J 1990;8:201–23.

Brown B, Absanullah M. Effects of heavy metals on mortality and growth. MarPollut Bull 1971;2:182–7.

Carito SL, Bazil SL, Digiacomo G. X-ray diffraction studies on selectedbacterial cell walls. J Bacteriol 1967;93:122–4.

Celaya RJ, Noriega JA, Yeomans JH, Ortega LJ, Ruiz-Manriquez A.Biosorption of Zn by Thiobacillus ferrooxidans. Bioprocess Eng2000;22:539–42.

Chander M, Arora DS. Evaluation of some white-rot fungi for their potential todecolorize industrial dyes. Dyes Pigm 2007;72:192–8.

Chang J-S, Law R, Chang C-C. Biosorption of lead, copper and cadmium bybiomass of Pseudomonas aeruginosa PU21. Water Res 1997;31:1651–8.

Chen S, Wilson DB. Genetic engineering of bacteria and their potential for Hg2+

bioremediation. Biodegradation 1997;8:97–103.Chen W, Georgiou G. Cell-surface display of heterologous proteins: from high-

throughput screening to environmental applications. Biotechnol Bioeng2002;79:496–503.

ChenXC,WangYP, Lin Q, Shi JY,WuWX, ChenYX. Biosorption of copper(II)and zinc(II) from aqueous solution by Pseudomonas putida CZ1. ColloidsSurf B Biointerfaces 2005;46:101–7.

Choi SB, Yun YS. Lead biosorption by waste biomass of Corynebacteriumglutamicum generated from lysine fermentation process. Biotechnol Lett2004;26:331–6.

Chong KH, Volesky B. Description of two-metal biosorption equilibria byLangmuir-type models. Biotechnol Bioeng 1995;47:451–60.

Choy KKH, Porter JF, McKay G. Langmuir isotherm models applied to themulticomponent sorption of acid dyes from effluent onto activated carbon.J Chem Eng Data 2000;45:575–85.

Choy KKH, Porter JF, McKay G. Single and multicomponent equilibriumstudies for the adsorption of acidic dyes on carbon from effluents. Langmuir2004;20:9646–56.

Chu KH. Improved fixed bed models for metal biosorption. Chem Eng J2004;97:233–9.

ChuahTG, JumasiahA,Azni I, Katayon S,ChoongSYT.Rice husk as a potentiallylow-cost biosorbent for heavy metal and dye removal: an overview.Desalination 2005;175:305–16.

Clark RM. Evaluating the cost and performance of field-scale granular activatedcarbon systems. Environ Sci Technol 1987;21:573–80.

Cossich ES, da Silva EA, Tavares CRG, Filho LC, Ravagnani TMK.Biosorption of chromium(III) by biomass of seaweed Sargassum sp. in afixed-bed column. Adsorption 2004;10:129–38.

Cox JS, Smith DS, Warren LA, Ferris FG. Characterizing heterogeneousbacterial surface functional groups using discrete affinity spectra for protonbinding. Environ Sci Technol 1999;33:4514–21.

Crini G. Non-conventional low-cost adsorbents for dye removal: a review.Biores Technol 2006;97:1061–85.

Crittenden JC, Weber WJ. Model for design of multicomponent adsorptionsystems. J Environ Eng Div 1978;104:1175–93.

da Silva EA, Cossich ES, Tavares CRG, Filho LC, Guirardello R. Modeling ofcopper(II) biosorption by marine alga Sargassum sp. in fixed column.Process Biochem 2002;38:791–9.

Dambies L, Guibal E, Roze A. Arsenic(V) sorption on molybdate-impregnatedchitosan beads. Colloids Surf A Physicochem Eng Asp 2000;170:19–31.

Daughney CJ, Fein JB. The effect of ionic strength on the adsorption of H+,Cd2+, Pb2+ and Cu2+ by Bacillus subtilis and Bacillus licheniformis: asurface complexation model. J Colloid Interface Sci 1998;198:53–77.

Davis TA, Volesky B, Vieira RHSF. Sargassum seaweed as biosorbent for heavymetals. Water Res 2000;34:4270–8.

Davis TA, Volesky B, Mucci A. A review of the biochemistry of heavy metalbiosorption by brown algae. Water Res 2003;37:4311–30.

de Vargas I, Macaskie LE, Guibal E. Biosorption of palladium and platinum bysulfate-reducing bacteria. J Chem Technol Biotechnol 2004;79:49–56.

Deng S, Ting YP. Characterization of PEI-modified biomass and biosorption ofCu(II), Pb(II) and Ni(II). Water Res 2005a;39:2167–77.

Deng S, Ting YP. Fungal biomass with grafted poly(acrylic acid) forenhancement of Cu(II) and Cd(II) biosorption. Langmuir 2005b;21:5940–8.

Deng S, Ting YP. Polyethylenimine-modified fungal biomass as a high-capacitybiosorbent for Cr(VI) anions: sorption capacity and uptake mechanisms.Environ Sci Technol 2005c;39:8490–6.

Deng S, Ting YP. Removal of As(V) and As(III) from water with a PEI-modifiedfungal biomass. Water Sci Technol 2007;55:177–85.

Denizli A, Tanyolaç D, Salih B, Özdural A. Cibacron blue F3GA-attachedpolyvinylbutyral microbeads as novel magnetic sorbents for removal of Cu(II),Cd(II) and Pb(II) ions. J Chromatogr 1998;793:47–56.

Dijkstra A, Keck W. Peptidoglycan as a barrier to transenvelope transport.J Bacteriol 1996;178:5555–62.

Doyle RJ, Matthews TH, Streips UN. Chemical basis for selectivity of metalions by the Bacillus subtilis cell wall. J Bacteriol 1980;143:471–80.

Dönmez G, Aksu Z. Removal of chromium(VI) from saline wastewaters byDunaliella species. Process Biochem 2002;38:751–62.

DubininMM.The potential theory of adsorption of gases and vapors for adsorbentswith energetically non-uniform surface. Chem Rev 1960;60:235–66.

Easton J. The dye makers's view. In: Cooper P, editor. Colour in dye houseeffluent. Bradford, UK: Society of Dyers and Colourists; 1995. p. 11.

Eccles H. Removal of heavy metals from effluent streams — why select abiological process? Int Biodeterior Biodegrad 1995;35:5–16.

Esposito A, Pagnanelli F, Lodi A, Solisio C, Vegliò F. Biosorption of heavymetals by Sphaerotilus natans: an equilibrium study at different pH andbiomass concentrations. Hydrometallurgy 2001;60:129–41.

Esposito A, Pagnanelli F, Vegliò F. pH-related equilibria models for biosorptionin single metal systems. Chem Eng Sci 2002;57:307–13.

Evans JR, Davids WG, MacRae JD, Amirbahman A. Kinetics of cadmiumuptake by chitosan-based crab shells. Water Res 2002;36:3219–26.


Farah JY, El-Gendy NS, Farahat LA. Biosorption of Astrazone Blue basic dyefrom an aqueous solution using dried biomass of Baker's yeast. J HazardMater 2007;148:402–8.

Fein JB, Daughney CJ, Yee N, Davis TA. A chemical equilibrium model for metaladsorption onto bacterial surfaces. Geochim Cosmochim Acta 1997;61:3319–28.

Fein JB, Boily JF, Gl K, Kaulbach E. Experimental study of humic acidadsorption onto bacteria and Al-oxide mineral surfaces. Chem Geol1999;162:33–45.

Fein JB, Martin AM, Wightman PG. Metal adsorption onto bacterial surfaces:development of a predictive approach. Geochim Cosmochim Acta2001;65:4267–73.

Forgacs E, Cserháti T, Oros G. Removal of synthetic dyes from wastewaters: areview. Environ Int 2004;30:953–71.

Fowle DA, Fein JB. Competitive adsorption of metal cations onto two Grampositive bacteria. Geochim Cosmochim Acta 1999;63:3059–67.

Freundlich H. Ueber die adsorption in loesungen. Z Phys Chem 1907;57:385–470.

Fritz W, Schluender EU. Simultaneous adsorption equilibria of organic solutes indilute aqueous solutions on activated carbon.ChemEngSci 1974;29:1279–82.

Fu Y, Viraraghavan T. Fungal decolorization of dye wastewaters: a review.Biores Technol 2001;79:251–62.

Fu Y, Viraraghavan T. Removal of Congo Red from an aqueous solution byfungus Aspergillus niger. Adv Environ Res 2002;7:239–47.

Fu Y, Viraraghavan T. Column studies for biosorption of dyes from aqueoussolutions on immobilized Aspergillus niger fungal biomass. Water SA2003;29:465–72.

Furuya E, Suzuki Y, Takeuchi Y. Adsorption equilibria of multi-componentsubstances dissolved in water on activated carbon. Proceedings of WorldCongress III, 8f-202, Tokyo; 1986. p. 817–20.

Gadd GM, White C. Microbial treatment of metal pollution: a workingbiotechnology? TIBTECH 1993;11:353–9.

Gadd GM, White C, DeRome L. Heavy metal and radionuclide uptake by fungiand yeasts. In: Norri PR, Kelly DP, editors. Biohydrometallurgy. Chippen-ham, Wilts, UK: A. Rowe; 1988.

Georgiou G, Poetschke HL, Stathopoulos C, Francisco JA. Practical applica-tions of engineering Gram-negative bacterial cell surfaces. TIBTECH1993;11:6–10.

Göksungur Y, Üren S, Güvenç U. Biosorption of cadmium and lead ions byethanol treated waste baker's yeast biomass. Biores Technol 2005;96:103–9.

Golab Z, Breitenbach M. Sites of copper binding in Streptomyces pilosus. WaterAir Soil Pollut 1995;82:713–21.

Green-Ruiz C. Mercury(II) removal from aqueous solutions by nonviable Ba-cillus sp. from a tropical estuary. Biores Technol 2006;97:1907–11.

Guo B, Hong L, Jiang HX. Macroporous poly(calcium acrylate-divinylbenzene)bead — a selective orthophosphate sorbent. Ind Eng Chem Res 2003;42:5559–65.

Haas JR, Dichristina TJ, Wade R. Thermodynamics of U(VI) sorption ontoShewanella putrefaciens. Chem Geol 2001;180:33–54.

Hamer DH. Metallothionein. Annu Rev Biochem 1986;55:913–51.Han MH, Yun YS. Mechanistic understanding and performance enhancement of

biosorption of reactive dyestuffs by the waste biomass generated from aminoacid fermentation process. Biochem Eng J 2007;36:2–7.

Hatzikioseyian A, Tsezos M, Mavituna F. Application of simplified rapidequilibrium models in simulating experimental breakthrough curves fromfixed bed biosorption reactors. Hydrometallurgy 2001;59:395–406.

Hermann T. Industrial production of amino acids by coryneform bacteria.J Biotechnol 2003;104:155–72.

Ho YS. Review of second-order models for adsorption systems. J Hazard Mater2006;B136:681–9.

Ho YS, McKay G. Pseudo-second order model for sorption processes. ProcessBiochem 1999a;34:451–65.

Ho YS, McKay G. The sorption of lead(II) ions on peat. Water Res 1999b;33:578–84.

Ho YS, McKay G. The kinetics of sorption of divalent metal ions ontosphagnum moss peat. Water Res 2000;34:735–42.

Ho YS, Ng JCY, McKay G. Kinetics of pollutant sorption by biosorbents:review. Sep Purif Methods 2000;29:189–232.

Ho YS, Porter JF, McKay G. Equilibrium isotherm studies for the sorption ofdivalent metal ions onto peat: copper, nickel and lead single componentsystems. Water Air Soil Pollut 2002;141:1–33.

Hu MZC, Reeves M. Biosorption of uranium by Pseudomonas aeruginosastrain CSU immobilized in a novel matrix. Biotechnol Prog 1997;13:60–70.

Incharoensakdi A, Kitjaharn P. Zinc biosorption from aqueous solution by ahalotolerant cyanobacterium Aphanothece halophytica. Curr Microbiol2002;45:261–4.

Iqbal M, Saeed A. Production of an immobilized hybrid biosorbent for thesorption of Ni(II) from aqueous solution. Process Biochem 2007;42:148–57.

Jefferies DJ, Firestone P. Chemical analysis of some coarse fish from a Suffolkriver carried out as part of the preparation for the first release of captive-bredotters. J Otter Trust 1984;1:17–22.

Jeon C, Höll WH. Chemical modification of chitosan and equilibrium study formercury ion removal. Water Res 2003;37:4770–80.

Jiang W, Saxena A, Song B, Ward BB, Beveridge TJ, Myneni SCB. Elucidationof functional groups on Gram-positive and Gram-negative bacterial surfacesusing infrared spectroscopy. Langmuir 2004;20:11433–42.

JianlongW, Xinmin Z, Decai D, Ding Z. Bioadsorption of lead(II) from aqueoussolution by fungal biomass of Aspergillus niger. J Biotechnol 2001;87:273–7.

Kang S-Y, Lee J-U, Kim K-W. Biosorption of Cr(III) and Cr(VI) onto the cellsurface of Pseudomonas aeruginosa. Biochem Eng J 2007;36:54–8.

Kapoor A, Viraraghavan T. Fungal biosorption — an alternative treatmentoption for heavy metal bearing wastewaters: a review. Biores Technol1995;53:195–206.

Kapoor A, Viraraghavan T. Heavy metal biosorption sites in Aspergillus niger.Biores Technol 1997;61:221–7.

Kazy SK, Das SK, Sar P. Lanthanum biosorption by a Pseudomonas sp.:equilibrium studies and chemical characterization. J Ind Microbiol Biotech2006;33:773–83.

Kelemen MV, Sharpe JE. Controlled cell disruption: a comparison of the forcesrequired to disrupt different micro-organisms. J Cell Sci 1979;35:431–41.

Kelly SD, Kemner KM, Fein JB, Fowle DA, Boyanov MI, Bunker BA, Yee N.X-ray absorption fine structure determination of pH-dependent U-bacterialcell wall interactions. Geochim Cosmochim Acta 2002;66:3855–71.

Khan AR, Al-Waheab IR, Al-Haddad A. A generalized equation for adsorptionisotherms for multicomponent organic pollutants in dilute aqueous solution.Environ Technol 1996;17:13–23.

Khan AR, Al-Bahri TA, Al-Haddad A. Adsorption of phenol based organicpollutants on activated carbon from multi-component dilute aqueoussolutions. Water Res 1997a;31:2102–12.

Khan AR, Ataullah A, Al-Haddad A. Equilibrium adsorption studies of somearomatic pollutants from dilute aqueous solutions on activated carbon atdifferent temperatures. J Colloid Interface Sci 1997b;194:154–65.

Khoo K-M, Ting Y-P. Biosorption of gold by immobilized fungal biomass.Biochem Eng J 2001;8:51–9.

Khraisheh MAM, Al-Degs YS, Allen SJ, AhmadMN. Elucidation of controllingsteps of reactive dye adsorption on activated carbon. Ind Eng Chem Res2002;41:1651–7.

Kim DS. The removal by crab shell of mixed heavy metal ions in aqueoussolution. Biores Technol 2003;87:355–7.

Ko DCK, Porter JF, McKay G. Optimised correlations for the fixed-bedadsorption of metal ions on bone char. Chem Eng Sci 2000;55:5819–29.

Ko DCK, Cheung CW, Choy KKH, Porter JF, McKay G. Sorption equilibria ofmetal ions on bone char. Chemosphere 2004;54:273–81.

Kolenbrander PE, Ensign JC. Isolation and chemical structure of thepeptidoglycan of Spirillum serpens cell walls. J Bacteriol 1968;95:201–10.

Kratochvil D, Volesky B. Advances in the biosorption of heavy metals.TIBTECH 1998;16:291–300.

Kratochvil D, Volesky B. Multicomponent biosorption in fixed beds. Water Res2000;34:3186–96.

Kuyucak N, Volesky B. Desorption of cobalt-laden algal biosorbent. BiotechnolBioeng 1989;33:815–22.

Langmuir I. The adsorption of gases on plane surfaces of glass, mica andplatinum. J Am Chem Soc 1918;40:1361–403.

Lee MY, Park JM, Yang JW. Micro precipitation of lead on the surface of crabshell particles. Process Biochem 1997;22:671–7.


Li J, Orhan T. Adsorption equilibrium of benzene-p-xylene vapor mixture onsilicate. Chem Eng Sci 1994;49:189–97.

Li X, Tang Y, Xuan Z, Liu Y, Luo F. Study on the preparation of orange peelcellulose adsorbents and biosorption of Cd2+ from aqueous solution. SepPurif Technol 2007;55:69–75.

Limousin G, Gaudet JP, Charlet L, Szenknect S, Barthes V, Krimissa M.Sorption isotherms: a review on physical bases, modeling and measurement.Appl Geochem 2007;22:249–75.

Lin C-C, Lai Y-T. Adsorption and recovery of lead(II) from aqueous solutions byimmobilized Pseudomonas aeruginosa PU21 beads. J Hazard Mater 2006;137:99–105.

Liu H-L, Chen B-Y, Lan Y-W, Cheng YC. Biosorption of Zn(II) and Cu(II)by the indigenous Thiobacillus thiooxidans. Chem Eng J 2004;97:195–201.

López A, Lázaro N, Priego JM, Marquès AM. Effect of pH on the biosorption ofnickel and other heavy metals by Pseudomonas fluorescens 4F39. J IndMicrobiol Biotech 2000;24:146–51.

Loukidou MX, Karapantsios TD, Zouboulis AI, Matis KA. Diffusion kineticstudy of cadmium(II) biosorption by Aeromonas caviae. J Chem TechnolBiotechnol 2004a;79:711–9.

Loukidou MX, Karapantsios TD, Zouboulis AI, Matis KA. Diffusion kineticstudy of chromium (VI) biosorption by Aeromonas caviae. Ind Eng ChemRes 2004b;43:1748–55.

Lu W-B, Shi J-J, Wang C-H, Chang J-S. Biosorption of lead, copper andcadmium by an indigenous isolate Enterobacter sp. J1 possessing highheavy-metal resistance. J Hazard Mater 2006;134:80–6.

Majáre M, Bülow L. Metal-binding proteins and peptides in bioremediation andphytoremediation of heavy metals. TIBTECH 2001;19:67–73.

Malik A. Metal bioremediation through growing cells. Environ Int 2004;30:261–78.

Malik P, Terry TD, Bellintani F, Perham RN. Factors limiting display of foreignpeptides on the major coat protein of filamentous bacteriophage capsids anda potential role for leader peptidase. FEBS Lett 1998;436:263–6.

Mameri N,BoudriesN,AddourL,BelhocineD, LouniciH,GribH, PaussA. Batchzinc biosorption by a bacterial nonliving Streptomyces rimosus biomass.WaterRes 1999;33:1347–54.

Maurya NS, Mitta AK, Cornel P, Rother E. Biosorption of dyes suing deadmacro fungi: effect of dye structure, ionic strength and pH. Biores Technol2006;97:512–21.

McKay G, Al-Duri B. Simplified model for the equilibrium adsorption of dyesfrom mixtures using activated carbon. Chem Eng Process 1987;22:145–56.

McKay G, Ho YS, Ng JCP. Biosorption of copper from waste waters: a review.Sep Purif Methods 1999;28:87–125.

McLeanRJC, BeaucheminD, Beveridge TJ. Influence of oxidation-state on iron-binding by Bacillus licheniformis capsule. Appl Environ Microbiol 1992;55:3143–9.

Mehra RK, Winge DR. Metal ion resistance in fungi-molecular mechanisms andtheir regulated expression. J Cell Biochem 1991;45:30–40.

Mehra RK, Mulchandani P. Glutathione-mediated transfer of Cu(I) intophytochelatins. Biochem J 1995;307:697–705.

Moore JW. Inorganic Contaminants of Surface Water Residuals and MonitoringPriorities. New York: Springer-Verlag; 1990. p. 178–210.

Mullen MD, Wolf DC, Ferris FG, Beveridge F, Flemming CA, Bailey GW.Bacterial sorption of heavy metals. Appl Environ Microbiol 1989;55:3143–9.

Muraleedharan TR, Iyengar L, Venkobachar C. Biosorption: an attractivealternative for metal removal and recovery. Curr Sci 1991;61:379–85.

Myers AL, Prausnitz JM. Thermodynamics of mixed-gas adsorption. AIChE J1965;11:121–6.

Nacèra Y, Aicha B. Equilibrium and kinetic modeling of methylene bluebiosorption by pretreated dead Streptomyces rimosus: effect of temperature.Chem Eng J 2006;119:121–5.

Naja G, Volesky B. Behavior of the mass transfer zone in a biosorption column.Environ Sci Technol 2006a;40:3996–4003.

Naja G, Volesky B. Multi-metal biosorption in a fixed-bed flow-throughcolumn. Colloids Surf A Physicochem Eng Asp 2006b;281:194–201.

Nakajima A, Tsuruta T. Competitive biosorption of thorium and uranium byMicrococcus luteus. J Radioanal Nucl Chem 2004;260:13–8.

Nakajima A, Yasuda M, Yokoyama H, Ohya-Nishiguchi H, Kamada H. Copperbiosorption by chemically treatedMicrococcus luteus cells. World J MicrobiolBiotechnol 2001;17:343–7.

Niu H, XuXS,Wang JH. Removal of lead from aqueous solutions by Penicilliumbiomass. Biotechnol Bioeng 1993;42:785–7.

Niu CH, Volesky B, Cleiman D. Biosorption of arsenic (V) with acid-washedcrab shells. Water Res 2007;41:2473–8.

O'Mahony T, Guibal E, Tobin JM. Reactive dye biosorption by Rhizopusarrhizus biomass. Enzyme Microb Technol 2002;31:456–63.

Ozdemir G, Baysal SH. Chromium and aluminum biosorption onChryseomonasluteola TEM05. Appl Microbiol Biotechnol 2004;64:599–603.

Öztürk A. Removal of nickel from aqueous solution by the bacterium Bacillusthuringiensis. J Hazard Mater 2007;147:518–23.

Öztürk A, Artan T, Ayar A. Biosorption of nickel(II) and copper(II) ions fromaqueous solution by Streptomyces coelicolor A3(2). Colloids Surf B Bio-interfaces 2004;34:105–11.

Padmesh TVN, Vijayaraghavan K, Sekaran G, Velan M. Biosorption of AcidBlue 15 using fresh water macroalga Azolla filiculoides: batch and columnstudies. Dyes Pigm 2006;71:77–82.

Pagnanelli F, Papini MP, Toro L, Trifoni M, Vegliò F. Biosorption of metal ionson Arthrobacter sp.: biomass characterization and biosorption modeling.Environ Sci Technol 2000;34:2773–8.

Pagnanelli F, Esposito A, Vegliò F. Multi-metallic modelling for biosorption ofbinary systems. Water Res 2002;36:4095–105.

Pagnanelli F, Beolchini F, Esposito A, Toro L, Vegliò F. Mechanistic modelingof heavy metal biosorption in batch and membrane reactor systems. Hydro-metallurgy 2003;71:201–8.

Pagnanelli F, Mainelli S, Toro L. Optimisation and validation of mechanisticmodels for heavy metal bio-sorption onto a natural biomass. Hydrome-tallurgy 2005;80:107–25.

Pandey A, Singh P, Iyengar L. Bacterial decolorization and degradation of azodyes. Int Biodeterior Biodegrad 2007;59:73–84.

Pardo R, Herguedas M, Barrado E, Vega M. Biosorption of cadmium, copper,lead and zinc by inactive biomass of Pseudomonas putida. Anal BioanalChem 2003;376:26–32.

Park D, Yun YS, Park JM. Use of dead fungal biomass for the detoxification ofhexavalent chromium: screening and kinetics. Process Biochem 2005;40:2559–65.

Park D, Yun YS, Yim KH, Park JM. Effect of Ni(II) on the reduction of Cr(VI)by Ecklonia biomass. Biores Technol 2006;97:1592–8.

Pazirandeh M, Chrisey LA, Mauro JM, Campbell JR, Gaber BP. Expression ofthe Neurospora crassa metallothionein gene in Escherichia coli and itseffects on heavy-metal uptake. Appl Microbiol Biotechnol 1995;43:1112–7.

Phoenix VR, Martinez RE, Konhauser KO, Ferris FG. Characterization andimplications of the cell surface reactivity of Calothrix sp. strain KC97. ApplEnviron Microbiol 2002;68:4827–34.

Plette CC, Benedetti MF, Van Riemsdijk WH, van der Wal A. pH dependentcharging behavior of isolated cell walls of a Gram-positive soil bacterium.J Colloid Interface Sci 1995;173:354–63.

Prakasham RS, Merrie JS, Sheela R, Saswathi N, Ramakrishna SV. Biosorptionof chromium VI by free and immobilized Rhizopus arrhizus. Environ Pollut1999;104:421–7.

Prasad MNV, Freitas HMO. Metal hyperaccumulation in plants — biodiversityprospecting for phytoremediation technology. Electron J Biotechnol 2003;6:285–321.

Premuzic ET, LinM,ZhuHL,GremmeAM.Selectivity inmetal uptake by stationaryphase microbial populations. Arch Environ Contam Toxicol 1991;20:234–40.

Puranik PR, Paknikar KM. Biosorption of lead, cadmium, and zinc byCitrobacterstrain MCM B-181: characterization studies. Biotechnol Prog 1999;15:228–37.

Puranik PR, Paknikar KM. Biosorption of lead and zinc from solutions usingStreptoverticillium cinnamoneum waste biomass. J Biotechnol 1997;55:113–24.

Puranik PR, Chabukswar NS, Paknikar KM. Cadmium biosorption by Strep-tomyces pimprina waste biomass. Appl Microbiol Biotechnol 1995;43:1118–21.

Radke CJ, Prausnitz JM. Adsorption of organic solutions from dilute aqueoussolutions on activated carbon. Ind Eng Chem Fundam 1972a;11:445–51.


Radke CJ, Prausnitz JM. Thermodynamics of multi-solute adsorption fromdilute liquid solutions. AIChE J 1972b;18:761–8.

Reddad Z, Gerente C, Andres Y, Le Cloirec P. Adsorption of several metal ionsonto a low-cost biosorbent: kinetic and equilibrium studies. Environ SciTechnol 2002;36:2067–73.

Redlich O, Peterson DL. A useful adsorption isotherm. J Phys Chem 1959;63:1024.

Rogers HJ, Perkins HR, Ward JB. Microbial cell walls and membranes. London:Chapman and Hall; 1980.

Rubin E, Rodriguez P, Herrero R, Cremades J, Barbara I, de Vicente MES.Removal of methylene blue from aqueous solutions using as biosorbentSargassum muticum: an invasive macroalga in Europe. J Chem TechnolBiotechnol 2004;80:291–8.

Ruiz-Manriquez A, Magana PI, López V, Guzmán R. Biosorption of Cu byThiobacillus ferrooxidans. Bioprocess Eng 1997;18:113–8.

Saeed A, Iqbal M. Bioremoval of cadmium from aqueous solution by blackgram husk (Cicer arientinum). Water Res 2003;37:3472–80.

SağY, Kutsal T. Application of adsorption isotherms to chromium adsorption onZ. ramigera. Biotechnol Lett 1989;11:141–4.

Sağ Y, Kutsal T. Determination of the biosorption heats of heavy metal ions onZoogloea ramigera and Rhizopus arrhizus. Biochem Eng J 2000;6:145–51.

Sağ Y, Acikel U, Aksu Z, Kutsal T. A comparative study for the simultaneousbiosorption of Cr(VI) and Fe(III) on C. vulgaris and R. arrhizus: appli-cation of the competitive adsorption models. Process Biochem 1998;33:273–81.

Sağ Y, Atacoglu I, Kutsal T. Equilibrium parameters for the single- andmulticomponent biosorption of Cr(VI) and Fe(III) ions on R. arrhizus in apacked column. Hydrometallurgy 2000;55:165–79.

Sağ Y, Akcael B, Kutsal T. Evaluation, interpretation, and representation ofthree-metal biosorption equilibria using a fungal biosorbent. ProcessBiochem 2001;37:35–50.

Şahin Y, Öztürk A. Biosorption of chromium(VI) ions from aqueous solution bythe bacterium Bacillus thuringiensis. Process Biochem 2005;40:1895–901.

Salton MRJ. The bacterial cell wall. Amsterdam: Elsevier; 1964.Samuelson P, Wernérus H, Svedberg M, Ståhl S. Staphylococcal surface display

of metal-binding polyhistidyl peptides. Appl Environ Microbiol 2000;66:1243–8.

Sar P, Kazy SK, Asthana RK, Singh SP. Metal adsorption and desorption bylyophilized Pseudomonas aeruginosa. Int Biodeterior Biodegrad 1999;44:101–10.

Savvaidis I, Hughes MN, Poole RK. Copper biosorption by Pseudomonascepacia and other strains. World J Microbiol Biotechnol 2003;19:117–21.

Selatnia A, Bakhti MZ, Madani A, Kertous L, Mansouri Y. Biosorption of Cd2+

from aqueous solution by a NaOH-treated bacterial dead Streptomycesrimosus biomass. Hydrometallurgy 2004a;75:11–24.

Selatnia A, Boukazoula A, Kechid N, Bakhti MZ, Chergui A, Kerchich Y.Biosorption of lead (II) from aqueous solution by a bacterial dead Strepto-myces rimosus biomass. Biochem Eng J 2004b;19:127–35.

Selatnia A, Boukazoula A, KechidN, BakhtiMZ, Chergui A. Biosorption of Fe3+

from aqueous solution by a bacterial dead Streptomyces rimosus biomass.Process Biochem 2004c;39:1643–51.

Selatnia A, Madani A, Bakhti MZ, Kertous L,Mansouri Y, Yous R. Biosorption ofNi2+ from aqueous solution by a NaOH-treated bacterial dead Streptomycesrimosus biomass. Min Eng 2004d;17:903–11.

Senthilkumar R, Vijayaraghavan K, Thilakavathi M, Iyer PVR, Velan M.Seaweeds for the remediation of wastewaters contaminated with zinc(II)ions. J Hazard Mater 2006;136:791–9.

Sharma DC, Forster CF. Removal of hexavalent chromium using sphagnummoss peat. Water Res 1993;27:1201–8.

Sheindrof C, Rebhun M, Sheintuch M. A Freundlich type multicomponentisotherm. J Colloid Interface Sci 1981;79:136–42.

Shen J, Duvnjak Z. Adsorption kinetics of cupric and cadmium ions on corncobparticles. Process Biochem 2005;40:3446–54.

Sherbert GV. The biophysical characterization of the cell surface. London:Academic press; 1978.

Sheu CW, Freese E. Lipopolysaccharide layer protection of gram-negativebacteria against inhibition by long-chain fatty acids. J Bacteriol 1973;115:869–75.

Singhal RK, Andersen ME, Meister A. Glutathione, a first line of defenseagainst cadmium toxicity. FASEB J 1997;1:220–3.

Sips R. On the structure of a catalyst surface. J Chem Phys 1948;16:490–5.Small TD, Warren LA, Roden EE, Ferris FG. Sorption of strontium by bacteria,

Fe(III) oxide, and bacteria-Fe(III) oxide composites. Environ Sci Technol1999;33:4465–70.

Solisio C, Lodi A, Converti A, Borghi MD. The effect of acid pre-treatment onthe biosorption of chromium(III) by Sphaerotilus natans from industrialwastewater. Water Res 2000;34:3171–8.

Sonnenfeld EM, Beveridge TJ, Koch AL, Doyle RJ. Asymmetric distribution ofcharge on the cell wall of Bacillus subtilis. J Bacteriol 1985;163:1167–71.

Sousa C, Cebolla A, de Lorenzo V. Enhanced metalloadsorption of bacterialcells displaying poly-His peptides. Nat Biotechnol 1996;14:1017–20.

Srinath T, Verma T, Ramteke PW, Garg SK. Chromium (VI) biosorption andbioaccumulation by chromate resistant bacteria. Chemosphere 2002;48:427–35.

Suhasini IP, Sriram G, Asolekar SR, Sureshkumar GK. Biosorptive removal andrecovery of cobalt from aqueous systems. Process Biochem 1999;34:239–47.

Suzuki M, Misic DM. 5th CHISA Congress, J3-1, Prague; 1973.Tan T, Cheng P. Biosorption of metal ions with Penicillium chrysogenum. Appl

Biochem Biotechnol 2003;104:119–28.Tangaromsuk J, Pokethitiyook P, Kruatrachue M, Upatham ES. Cadmium

biosorption by Sphingomonas paucimobilis biomass. Biores Technol2002;85:103–5.

Temkin M. Die gas adsorption und der nernstsche wärmesatz. Acta PhysicochimURSS 1934;1:36–52.

Texier AC, Andrès Y, Le Cloirec P. Selective biosorption of lanthanide (La, Eu,Yb) ions by Pseudomonas aeruginosa. Environ Sci Technol 1999;33:489–95.

Texier AC, Andrès Y, Illemassene M, Le Cloirec P. Characterization oflanthanide ions binding sites in the cell wall of Pseudomonas aeruginosa.Environ Sci Technol 2000;34:610–5.

Texier AC, Andrès Y, Faur-Brasquet C, Le Cloirec P. Fixed-bed study forlanthanide (La, Eu, Yb) ions removal from aqueous solutions byimmobilized Pseudomonas aeruginosa: experimental data and modeliza-tion. Chemosphere 2002;47:333–42.

Thomas HC. Heterogeneous ion exchange in a flowing system. J Am Chem Soc1944;66:1664–6.

Tobin JM, Roux JC. Mucor biosorbent for chromium removal from tanningeffluent. Water Res 1998;32:1407–16.

Toth J. State equations of the solid gas interface layer. Acta Chem Acad Hung1971;69:311–7.

Tsezos M. Biosorption of metals. The experience accumulated and the outlookfor technology development. Hydrometallurgy 2001;59:241–3.

Tunali S, Çabuk A, Akar T. Removal of lead and copper ions from aqueoussolutions by bacterial strain isolated from soil. Chem Eng J 2006;115:203–11.

Uslu G, Tanyol M. Equilibrium and thermodynamic parameters of single andbinary mixture biosorption of lead(II) and copper(II) ions onto Pseudomo-nas putida: effect of temperature. J Hazard Mater 2006;135:87–93.

van der Wal A, Norde W, Zehnder AJB, Lyklema J. Determination of the totalcharge in the cell walls of gram-positive bacteria. Colloids Surf. BBiointerfaces 1997;9:81–100.

Vannela R, Verma SK. Cu2+ removal and recovery by SpiSORB: batch stirredand up-flow packed bed columnar reactor systems. Bioprocess Biosyst Eng2006;29:7–17.

Vegliò F, Beolchini F. Removal of metals by biosorption: a review. Hydro-metallurgy 1997;44:301–16.

Vieira RHSF, Volesky B. Biosorption: a solution to pollution. Int Microbiol2000;3:17–24.

Vijayaraghavan K, Yun YS. Chemical modification and immobilization ofCorynebacterium glutamicum for biosorption of Reactive black 5 fromaqueous solution. Ind Eng Chem Res 2007a;46:608–17.

Vijayaraghavan K, Yun YS. Utilization of fermentation waste (Corynebacteriumglutamicum) for biosorption of Reactive Black 5 from aqueous solution.J Hazard Mater 2007b;141:45–52.

Vijayaraghavan K, Yun YS. Biosorption of C.I. Reactive Black 5 from aqueoussolution using acid-treated biomass of brown seaweed Laminaria sp. DyesPigm 2008;76:726–32.


Vijayaraghavan K, Jegan J, Palanivelu K, Velan M. Removal of nickel(II) ionsfrom aqueous solution using crab shell particles in a packed bed up-flowcolumn. J Hazard Mater 2004;113:223–30.

Vijayaraghavan K, Jegan J, Palanivelu K, Velan M. Batch and column removalof copper from aqueous solution using a brown marine alga Turbinariaornata. Chem Eng J 2005a;106:177–84.

Vijayaraghavan K, Jegan J, Palanivelu K, Velan M. Removal and recovery ofcopper from aqueous solution by eggshell in a packed column. Min Eng2005b;18:545–7.

Vijayaraghavan K, Padmesh TVN, Palanivelu K, VelanM. Biosorption of nickel(II) ions onto Sargassum wightii: application of two-parameter and three-parameter isotherm models. J Hazard Mater 2006a;133:304–8.

Vijayaraghavan K, Palanivelu K, Velan M. Biosorption of copper(II) and cobalt(II) from aqueous solutions by crab shell particles. Biores Technol 2006b;97:1411–9.

Vijayaraghavan K, Palanivelu K, Velan M. Treatment of nickel containingelectroplating effluents with Sargassum wightii biomass. Process Biochem2006c;41:853–9.

Vijayaraghavan K, Han MH, Choi SB, Yun YS. Biosorption of Reactive black 5by Corynebacterium glutamicum biomass immobilized in alginate andpolysulfone matrices. Chemosphere 2007;68:1838–45.

Volesky B. Biosorbents for metal recovery. TIBTECH 1987;5:96–101.Volesky B. Biosorption and biosorbents. In: Volesky B, editor. Biosorption of

heavy metals. Florida: CRC press; 1990. p. 3–5.Volesky B. Detoxification of metal-bearing effluents: biosorption for the next

century. Hydrometallurgy 2001;59:203–16.Volesky B, Prasetyo I. Cadmium removal in a biosorption column. Biotechnol

Bioeng 1994;43:1010–5.Volesky B, Holan ZR. Biosorption of heavy metals. Biotechnol Prog

1995;11:235–50.Volesky B, Schiewer S. Biosorption of metals. In: FlickingerM, Drew SW, editors.

Encyclopedia of Bioprocess Technology. New York: Wiley; 1999. p. 433–53.Volesky B, Weber J, Park JM. Continuous-flow metal biosorption in a

regenerable Sargassum column. Water Res 2003;37:297–306.Weber WJ, Morris JC. Kinetics of adsorption on carbon solution. J Sanit Eng

Div Am Soc Civ Eng 1963;89:31–59.Won SW, Yun YS. Biosorptive removal of Reactive Yellow 2 using waste

biomass from lysine fermentation process. Dyes Pigm 2008;76:502–7.Won SW, Choi SB, Chung BW, Park D, Park JM, Yun YS. Biosorptive

decolorization of Reactive orange 16 using the waste biomass of Coryne-bacterium glutamicum. Ind Eng Chem Res 2004;43:7865–9.

Won SW, Choi SB, Yun YS. Interaction between protonated waste biomass ofCorynebacterium glutamicum and anionic dye Reactive Red 4. ColloidsSurf A Physicochem Eng Asp 2005;262:175–80.

Wu J, Yu HQ. Biosorption of 2,4-dichlorophenol by immobilized white-rotfungus Phanerochaete chrysoporium from aqueous solutions. BioresTechnol 2007;98:253–9.

Xiangliang P, Jianlong W, Daoyong Z. Biosorption of Pb(II) by Pleurotusostreatus immobilized in calcium alginate gel. Process Biochem2005;40:2799–803.

Yan G, Viraraghavan T. Heavy metal removal in a biosorption column byimmobilized M. rouxii biomass. Biores Technol 2001;78:243–9.

Yan G, Viraraghavan T, Chen M. A new model for heavy metal removal in abiosorption column. Adsorp Sci Technol 1999;19:25–43.

Yang J, Volesky B. Intraparticle diffusivity of Cd ions in a new biosorbentmaterial. J Chem Technol Biotechnol 1996;66:355–64.

Yang J, Volesky B. Biosorption of uranium on Sargassum biomass. Water Res1999a;33:3357–63.

Yang J, Volesky B. Modeling the uranium-proton ion exchange in biosorption.Environ Sci Technol 1999b;33:4079–85.

Yee N, Fein J. Cd adsorption onto bacterial surfaces: a universal adsorptionedge? Geochim Cosmochim Acta 2001;65:2037–42.

Yilmaz EI, Ensari NY. Cadmium biosorption by Bacillus circulans strain EB1.World J Microbiol Biotechnol 2005;21:777–9.

YoonYH,Nelson JH.Application of gas adsorption kinetics. I. A theoreticalmodelfor respirator cartridge service time. Am Ind Hyg Assoc J 1984;45:509–16.

Yu J, Tong M, Sun X, Li B. A simple method to prepare poly(amic acid)-modified biomass for enhancement of lead and cadmium adsorption.Biochem Eng J 2007;33:126–33.

Yun YS, Park D, Park JM, Volesky B. Biosorption of trivalent chromium on thebrown seaweed biomass. Environ Sci Technol 2001;35:4353–8.

Zenk MH. Heavy metal detoxification in higher plants: a review. Gene1996;179:21–30.

Zhao M, Duncan R, Van Hille RP. Removal and recovery of zinc from solutionand electroplating effluent using Azolla filiculoides. Water Res 1999;33:1516–22.

ZhouM, Liu Y, Zeng G, Li X, XuW, Fan T. Kinetic and equilibrium studies of Cr(VI) biosorption by dead Bacillus licheniformis biomass. World J MicrobiolBiotechnol 2007;23:43–8.

Ziagova M, Dimitriadis G, Aslanidou D, Papaioannou X, Tzannetaki EL,Liakopoulou-Kyriakides M. Comparative study of Cd(II) and Cr(VI)biosorption on Staphylococcus xylosus and Pseudomonas sp. in single andbinary mixtures. Biores Technol 2007;98:2859–65.

Zollinger H. Azo Dyes and Pigments, Colour Chemistry-Synthesis, Properties andApplications of Organic Dyes and Pigments. NewYork: VCH; 1987. p. 92–100.

Zulfadhly Z, Mashitah MD, Bhatia S. Heavy metals removal in a fixed-bedcolumn by the macro fungus Pycnoporus sanguineus. Environ Pollut2001;112:463–70.

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