Bioremoval of heavy metals by bacterial biomass.

Environ Monit Assess (2015) 187:4173 DOI 10.1007/s10661-014-4173-z

Bioremoval of heavy metals by bacterial biomass Mahendra Aryal & Maria Liakopoulou-Kyriakides

Received: 16 June 2014 / Accepted: 17 November 2014 # Springer International Publishing Switzerland 2014

Abstract Heavy metals are among the most common pollutants found in the environment. Health problems due to the heavy metal pollution become a major concern throughout the world, and therefore, various treatment technologies such as reverse osmosis, ion exchange, solvent extraction, chemical precipitation, and adsorption are adopted to reduce or eliminate their concentration in the environment. Biosorption is a cost-effective and environmental friendly technique, and it can be used for detoxification of heavy metals in industrial effluents as an alternative treatment technology. Biosorption characteristics of various bacterial species are reviewed here with respect to the results reported so far. The role of physical, chemical, and biological modification of bacterial cells for heavy metal removal is presented. The paper evaluates the different kinetic, equilibrium, and thermodynamic models used in bacterial sorption of heavy metals. Biomass characterization and sorption mechanisms as well as elution of metal ions and regeneration of biomass are also discussed.

Keywords Heavy metals . Bacteria . Biosorption . Desorption . Biosorption models M. Aryal : M. Liakopoulou-Kyriakides (*) Faculty of Chemical Engineering, Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece e-mail: [email protected]

Introduction Environmental pollution by heavy metals is considered as a major problem in the recent years due to their toxicity and widespread occurrence (Chao et al. 2014; Mejias Carpio et al. 2014; Fang et al. 2014; Volesky 2001). Natural processes such as weathering reactions, biological activities, and volcanic emissions result in increased heavy metal concentrations in soil, water, and sediments. Beside the natural activities, almost all human activities such as mining, refining of ores, combustion of fossil fuels, industrial processes, processed foods, personal care products, and disposal of industrial, medical, and domestic wastes also have a potential contribution to heavy metals in the environmental pollution (Wang and Chen 2009). The heavy metals cannot be degraded by any physical or chemical means and therefore can last for a long time in the environment. Some of them could be transformed from relevant lower toxic species into more toxic forms under certain environmental conditions. The bioaccumulation of heavy metals in the food chain may affect the human physiological activity. Heavy metals such as Fe, Zn, Cu, Mn, Ni, and Co are essential trace elements in biochemical reactions in living organisms, whereas others are harmful to humans due to their xenobiotic nature (Fan et al. 2014; Dogru et al. 2007; Chen et al. 2005). Specifically, they can cause various diseases and disorders, even in relatively low concentrations. Therefore, the presence of heavy metals in the environment above critical values is unacceptable and their removal should be considered (Gautam et al. 2014; Yalçin 2014).

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However, the conventional methods such as chemical precipitation, chemical oxidation and reduction, electrochemical treatment, solvent extraction, ion exchange, reverse osmosis, evaporative recovery, and adsorption are the most commonly used for the removal of heavy metals from aqueous solutions. These techniques may lead to further environmental problems due to the production of secondary toxic chemical sludge (Rawat et al. 2014; Serencam et al. 2013; Esposito et al. 2001). Furthermore, these technologies are uneconomical and inconvenient for treating of industrial effluents with less than 100 mg/L of dissolved metal ions (Gabr et al. 2008). In recent years, biosorption has become one of the alternative treatment technologies to remove heavy metals from aqueous solutions, since bacterial biomass could be used as an inexpensive and highly efficient bioagent to remove heavy metals from contaminated aqueous environment (El Hassouni et al. 2014; Guo et al. 2012; Aryal et al. 2010; Dogru et al. 2007; Celaya et al. 2000). This review aims to compare the sorption capacity of various bacterial species; to discuss the kinetic, equilibrium, and thermodynamic models used in the biosorption of heavy metals; and to evaluate the pretreatment methods for increasing sorption capacity, biomass characterization, and finally the elution recovery of metal ions from metal-loaded bacterial cells.

Bioaccumulation and biosorption The use of microorganisms for removal of heavy metal ions from aqueous solutions has been emerged as a potential technique (Salehi et al. 2014; KordialikBogacka and Diowksz 2014; Raja Rao et al. 2014). The retaining of heavy metal ions within microorganisms is referred to as bioaccumulation (Liang et al. 2014b). The main disadvantages of this process are as follows: Living microorganisms need a continuous supply of nutrients, heavy metals can be very toxic for their metabolic process, pH and temperature may affect bacterial growth, and recovery of metals and regeneration of bacterial biomass may be more complicated. Biosorption is the phenomenon of removing heavy metals from aqueous solutions applying inactive or dead biomass (Ilamathi et al. 2014: Koduru et al. 2014; Volesky 2001). In this process, metal ions can interact on bacterial surface via physical or chemical mechanisms. The main advantages of biosorption referred to

Environ Monit Assess (2015) 187:4173

the low cost of the biosorbent, no need of costly growth media, rapid process, high metal binding efficiency, selectivity for specific metals of interest, no generation of toxic sludge, recovery of metal ions in concentrated form, and regeneration of biomass (Javanbakht et al. 2014; Rangabhashiyam et al. 2013; Sari and Tuzen 2009). The schematic diagram of heavy metal biosorption and desorption is depicted in Fig. 1.

Bacterial structure Bacteria were among the first life forms to appear on Earth. They are prokaryotic microorganisms and have a wide diversity of shapes such as spherical, rods, spiral, and filamentous. Many bacteria exist as a single cell and some exist in diploid (Neisseria sp.), chain (Streptococcus sp.), and cluster (Staphylococcus sp.) forms. The bacterial cell wall is present on the outside of the cytoplasmic membrane and surrounded by a lipid membrane. It consists of peptidoglycan, which is made from polysaccharide chains. The bacterial species are divided into Gram-positive and Gram-negative according to composition of the cell wall. The cell wall of Grampositive bacteria consists of a thick layer of peptidoglycan connected by amino acid bridges, whereas Gramnegative cell walls contain that of thin layer compared to Gram-positive cells. The Gram-positive cell walls are polyalcohols, i.e., teichoic acids, some of which are covalently linked to lipids to form lipoteichoic acids and they are responsible for linking peptidoglycan to the cytoplasmic membrane (Vijayaraghavan and Yun 2008), while Gram-negative bacteria have a complex outer membrane, but they do not include teichoic and teichuronic acid constituents (Beveridge 1981). In addition, the cell wall contains an additional outer membrane composed of phospholipids and lipopolysaccharides (Sheu and Freese 1973). The bacterial cell walls play an important role in heavy metal biosorption. The functional groups of bacteria such as of peptidoglycan, teichoic and teichuronic acids, phospholipids, lipopolysaccharides, and various proteins are responsible for metal binding (Din et al. 2014; Vijayaraghavan and Yun 2008). According to Joo et al. (2010), Gram-positive bacteria exhibit lower levels of surface complexation due to the heavily cross-linked peptidoglycan layer, and Gram-negative bacteria expose most of their lipopolysaccharides, phospholipids, and proteins on cell walls. At pH values greater than


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Fig. 1 General scheme for biosorption and desorption of heavy metals

dissociation constant (pKa), the surface functional groups are protonated and the negatively charged ligands can participate for metal cations interactions, whereas at pH values lower than pKa, complexation can also occur specifically for carboxylic groups (Esposito et al. 2001). At lower pH values, bacterial cell wall becomes positive due to the deprotonation of surface functional groups, and thus, formed positively charged active sites are responsible for metal anion binding. Transition metal ions can coordinate three to eight ligands and often exhibit an octahedral coordination because of free d-orbital presence in their electronic structure (Aryal and Liakopoulou-Kyriakides 2013a). Thus, the three-dimensional network structure of peptidoglycan can be responsible for metal binding (Fomina and Gadd 2014; Wang et al. 2006).

Factors influencing the heavy metal sorption The degree of biosorption efficiency of bacterial cells for heavy metal ions depends upon various external operating factors such as pH, contact time, temperature, concentration of biomass and metal ions, and the nature of aqueous environment (Liang et al. 2014a; Chathuranga et al. 2014; Gupta et al. 2014). Therefore, data from literature cannot be compared directly due to the different operating conditions applied.

Effect of pH The pH is an important parameter, which affects the solution chemistry of metal ions and the surface functional groups of the bacterial cell wall (Long et al. 2014). It also affects the solubility of the metal ions in the solution, where H+ ions replace some of the positive ions from the biomass surface. The biosorption capacity of metal cations increases with increase in pH values, and this may be due to the more negative binding sites exposed on biomass surface (Aksu and Gulen 2002). At low pH values, the binding sites of the cell wall are blocked and associated with hydrogen ions that hinder the access of metal cations due to repulsive forces to the surface functional groups. On the contrary, biosorption efficiency of metal anions increases with decrease in pH values due to the increase in positively charged biomass surface groups, whereas at higher pH, the repulsive forces between metal anions and negatively charged biomass surface diminish the metal uptake capacity (Aryal et al. 2010; Ziagova et al. 2007). It has been stated that biosorption of Cr(III) increased with increasing pH from 1.0 to 5.0 and decreased upon further increase to 7.0, whereas sorption capacity for Cr(VI) increased at pH values from 1.0 to 2.0 and then decreased up to pH 7.0 (Aryal and LiakopoulouKyriakides 2013b). The decrease in the sorption efficiency at pH higher than 5.0 may be due to the precipitation of Cr(III) as hydroxide, which subsequently

4173, Page 4 of 26

interferes with the sorption process. At higher pH values of their aqueous solution, Cr+3 will shift to Cr(OH)+2, and HCrO4− to Cr2O7−2 and CrO4−2 ions. Ziagova et al. (2007) reported that the highest uptake of Cr(VI) was determined at pH 1.0 and 4.0 using Staphylococcus xylosus and Pseudomonas sp. biomass, respectively. As studied by Goyal et al. (2003), the optimum pH for Fe(III) sorption on Streptococcus equisimilis was 2.0, while Selatnia et al. (2004a) determined the maximum removal of Fe(III) by Streptomyces rimosus at pH 10.0. This variation of metal sorption with pH may be due to the changes in surface property of the bacterial cells. Effect of biomass concentration Biosorption of heavy metals dependents on biomass concentration used as the sorption medium. An increase in biomass concentration usually results in increase of biosorption efficiency, probably due to the increase in the number of binding sites. It was observed that the sorption efficiency increased with increase in biomass concentration, but biomass concentrations above 1.0 and 2.0 g/L had lower impact in sorption efficiency of As(III) and As(V), respectively (Aryal et al. 2010). This lower increment in percentage removal above optimum biomass concentration may be attributed to the interference between active sites. Some studies have pointed out that uptake capacity of heavy metals decreases with increasing the biomass concentration as a result of strong limitations of ionic species mobility in the biosorption medium, leaving some binding sites for metal ions unsaturated (Aryal et al. 2012; Tangaromsuk et al. 2002). The specific uptake of Zn(II) decreased, when Aphanothece halophytica biomass concentration exceeded that of 0.2 g/L (Incharoensakdi and Kitjaharn 2002). Ziagova et al. (2007) reported the significant increase in the Cr(VI) uptake efficiency, when the biomass concentration of Staphylococcus xylosus increased from 1.0 to 8.0 g/L, whereas removal efficiency of this metal anion did not change significantly above 1.0 g/L of Pseudomonas sp. biomass. Effect of equilibrium time The equilibrium time is also one of the most important parameters for treatment of wastewater using biosorbents. The sorption equilibrium time indicates the sorption–desorption processes occurring after saturation of metal ions on biomass surface. After the


equilibrium time, equilibrium capacities are almost constant, suggesting an equilibrium balance for sorption process. The fast sorption capacity of Ni(II) and Cu(II) onto Streptomyces coelicolor A3(2) at 5 min was reported by Ozturk et al. (2004). The contact time was also determined at 5 and 10 min for Cu(II) sorption using Arthrobacter sp. Sphe3 and Bacillus sphaericus biomass, respectively (Aryal et al. 2012). The rapid metal sorption could be an advantage in the treatment of largescale industrial effluents for practical applications. The equilibrium time was established at 8.0 h for Cr(VI) sorption on Bacillus thuringiensis (Şahin and Öztürk 2005) and 12 h for Cd(II) sorption using Pseudomonas plecoglossicida biomass (Guo et al. 2012). In some cases, 24 h has been reported as sorption time for heavy metal ion removal (Jian-hua et al. 2007; Lu et al. 2006; Uslu and Tanyol 2006). The sorption of Cr(VI) and As(V) in binary mixture with Fe(III)-treated Staphylococcus xylosus biomass showed that the sorbed Cr(VI) species were gradually replaced by As(V) species from biomass surface after the first 5 min and continued for 3 h, suggesting the greater affinity of As(V) toward the biomass surface compared to Cr(VI) ions (Aryal et al. 2011).

Effect of temperature The temperature of the medium affects the sorption of metal ions on biosorbents. Biosorption of heavy metals is usually modified with increase in temperature due to the increase in surface activity and kinetic energy of the solute, but destruction of some binding sites available for metal ions can occur at higher temperatures (Aryal and Liakopoulou-Kyriakides 2013b). The sorption capacity of bacterial cells for metal ions depends on whether the interaction between metal ions and binding sites is exothermic or endothermic in nature. The effect of temperature on Cu(II) sorption using two different bacterial species was compared and pointed out that uptake capacity of Arthrobacter sp. Sphe3 was decreased from 20 to 40 °C, whereas that of Bacillus sphaericus was increased from 20 to 40 °C, respectively (Aryal et al. 2012). The maximum uptake capacity of Bacillus subtilis for Cr(III) (Aravindhan et al. 2012) and Anoxybacillus amylolyticus for Mn(II) (Özdemir et al. 2013) was reported at relatively high temperature of 60 °C. However, most of the literature determined the optimum temperature for heavy metal sorption between


20 and 35 °C (Oves et al. 2013; Veneu et al. 2013; Calfa and Torem 2008; Kao et al. 2008). Effect of initial metal ion concentration The initial metal ion concentrations are an important parameter for biosorption process. The metal ions per unit mass of biomass is increased upon an increase in metal ion concentrations, since the initial metal ion concentration provides the necessary driving force to overcome the resistance to the mass transfer of metal ions between aqueous and solid phases, but decreases the sorption percentage (Aryal et al. 2010). At lower metal ion concentrations, all metal ions present in the solution may enhance the interaction between metal ions and bacterial binding sites and thus result in higher biosorption efficiency. At higher concentrations, uptake capacity is almost constant, may be due to the saturation of potential binding sites (Kang et al. 2007). Rodríguez et al. (2006) used low initial Ni(II) concentration from 0.4 to 1.0 mg/L with Acinetobacter baumannii UCR2971, whereas Sahmoune et al. (2009) studied the sorption of Cr(III) in the range of 10–1000 mg/L on Streptomyces rimosus species. Ozturk et al. (2004) performed the effect of initial concentration of Ni(II) and Cu(II) ions on Streptomyces coelicolor A3(2) and found greater affinity for Ni(II) than Cu(II) ions, whereas Aryal et al. (2012) reported that the effect of initial concentration of Cu(II) for both Arthrobacter sp. Sphe3 and Bacillus sphaericus was almost the same. Effect of interfering ions The presence of co-ions including metal cations and anions in wastewater may cause interference and competition phenomena for biosorption sites. Pagnanelli et al. (2000) reported that biosorption of Cu(II), Cd(II), and Fe(III) was not affected by the addition of alkaline and alkali earth metal ions using Arthrobacter sp. biomass. It has been shown that alkali and alkaline earth metals as well as anion of non-metals did not affect Cr(III) and Cr(VI) removal, whereas removal efficiency of dominant metal ions decreased in the presence of competent metal cations with increasing concentrations (Aryal and Liakopoulou-Kyriakides 2013b). The presence of an equimolar concentration of Mn(II), Mg(II), Co(II), K(I), and Na (I) had no effect on zinc biosorption, whereas Ca(II), Hg(II), and Pb(II) showed an inhibitory effect (Incharoensakdi and

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Kitjaharn 2002). On the other hand, Na(I), K(I), and Ca(II) ions increased the sorption capacity of Pseudomonas aeruginosa biomass for Ni(II) and Cu(II), respectively (Sar et al. 1999). In some cases, metal cations as competent ions may increase biosorption of anionic species by enhancing the additional binding sites (Aryal and Liakopoulou-Kyriakides 2011). The decrease in sorption capacity of Paenibacillus jamilae biomass for Cd(II), Co(II), Ni(II), Zn(II), and Cu(II) (Morillo et al. 2008), Mycobacterium sp. strain Spyr1 for Cr(III) and Cr(VI) (Aryal and Liakopoulou-Kyriakides 2013b), and Arthrobacter sp. Sphe3 and Bacillus sphaericus for Cu(II) (Aryal et al. 2012) in multi-ion systems was also reported. As it was shown, the effect of co-cations on Cr(VI) biosorption was less pronounced than on Cr(III) biosorption (Aryal and Liakopoulou-Kyriakides 2013b). Masood and Malik (2011) compared the biosorption efficiency of Bacillus sp. FM1 biomass to remove Cr(VI) and Cu(II) from synthetic and tannery effluents and found that removal of both metal ions from tannery effluent was less than synthetic metal ion solutions. The decrease in sorption performance in the presence of co-metallic ions may be due to the competition of both metal ions for the same binding sites on the cell surface.

Bacterial biosorption of heavy metals Bacterial biomass has a tendency to remove the heavy metals from aqueous solutions in very dilute conditions. Both active (live) and inactive (dead) bacterial cells have been used to remove heavy metals from aqueous solutions (Huang et al. 2013; Wierzba and Latala 2010; Gabr et al. 2008; Srinath et al. 2002; Jaafarzadeh et al. 2014; Bakyayita et al. 2014). Researchers have extensively used either untreated bacterial or pre-treated bacterial biomass to improve sorption efficiency for certain metal ions (Aryal et al. 2010; Chen et al. 2005; Wierzba and Latala 2010). Bacterial cells used as sorbents for removal of heavy metals under various operational conditions are listed in Table 1. The highest uptake capacity was reported at 800 mg As(III)/gLactobacillus acidophilus (Singh and Sarma 2010), 714 mg Cr(III)/gRhodococcus opacus (Calfa and Torem 2008), 567.72 mg Pb(II)/g Corynobacterium glutamicum (Choi and Yun 2004), 508 mg Ni(II)/gPseudomonas sp. (Gialamouidis et al. 2009), and 498 mg Mn(II)/gArthrobacter sp. (Veglio et al. 1997). Nevertheless, comparison between bacterial

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sorbents is almost impossible, since all the parameters and the biomass used are not the same. The sorption capacity of heavy metals was found to be dependent on pH, biomass loading, equilibrium time, initial metal ion concentration, temperature, and the method of sorption process applied.


The increase in biomass surface will result to the higher number of surface binding sites, which will favor the biosorption of heavy metals. Paul et al. (2012) reported that autoclaving of bacterial biomass enhanced the sorption ability of heavy metal ions. This may be due to the rupture of bacterial cell wall and expose more number of potential binding sites for metal ions. The sorption capacity of heat-treated, lyophilized, and live cells of Pseudomonas aeruginosa ASU 6a biomass for Pb(II) and Ni(II) was estimated at 123, 93, and 79 mg/g, and 113.6, 77, and 70 mg/g, respectively (Gabr et al. 2008), whereas live and dead biomass of the same species demonstrated almost the same uptake capacities for Cd(II) ions (Guo et al. 2012). Puranik and Paknikar (1997) introduced the boiling water treated Streptoverticillium cinnamoneum cells for Pb(II) and Zn(II) removal and found to increase the lead and zinc sorption by 52 and 41 % compared to that of live ones. Lower uptake capacity of dead Pseudomonas putida CZ1 cells compared to live ones for Cu(II) and Zn(II) was reported by Chen et al. (2005). This may be due to the loss of intracellular uptake and/or heat treatment may cause the loss of amino groups from the bacterial surface (Yan and Viraraghavan 2000).

of pre-treated biomass with (Na)2CO3, TritonX-100 for Pb(II), NaOH, Triton-X-100, C2H5OH, CH3OH, and acetone increased for Cd(II) and with Triton-100 for Zn(II) removal. Polyacrylic-acid-modified Corynebacterium glutamicum biomass exhibited 3.2 times greater uptake capacity for Cd(II) than untreated biomass (Mao et al. 2013). The treatment of Pseudomonas putida 5-x cells with HCl for Ni(II) removal (Wang et al. 2003), and Thiobacillus thiooxidans with NaOH for Zn(II) and Cu(II) (Liu et al. 2004) resulted in increased sorption capacity. Sar et al. (1999) reported that pre-treated Pseudomonas aeruginosa cells with NaOH, NH4OH, and toluene enhanced the Ni(II) and Cu(II) binding capacities, whereas acid-, detergent-, and acetone-treated sorbents retarded sorption capacity. In addition, chloroform-methanol/concentrated-KOH-treated Micrococcus luteus IAM 1056 biomass showed a higher uptake capacity for Cu(II) than untreated biomass (Nakajima et al. 2001). Aminated Lactobacillus casei DSM20011 biomass was also utilized to change the negative charge of carboxylic groups into positive amino groups for As(V) anion sorption (Halttunen et al. 2007). Fe(III)-treated Staphylococcus xylosus cells was proved to be an effective biomass for removal of As(III) and As(V) from aqueous solutions (Aryal et al. 2010). Chemically treated Atheta coriaria, Erythrina abyssinica, and Musa spp. were reported as potential biosorbents for remediation of Cd2+ ions and the untreated materials suitable for removing Pb2+ ions from contaminated aqueous media (Bakyayita et al. 2014). In addition, removal of hexavalent chromium from aqueous solution by chemically modified seaweed Bifurcaria bifurcata resulted in significant higher adsorption capacity than the raw biomass (Ainane et al. 2014).

Chemically modified bacterial cells

Biologically modified bacterial cells

The pre-treatment of bacterial biomass with inorganic and organic substances increases the sorption capacity of heavy metals, which may be due to the rupture of bacterial cell wall and/or formation of additional binding sites for metal ions. The uptake capacity of Zn(II) with untreated and NaOH-treated Streptomyces rimosus biomass was calculated at 30 and 80 mg/g, respectively (Mameri et al. 1999). Puranik and Paknikar (1999) treated Citrobacter strain MCM B-181 biomass with HCl, H 2 SO 4 , Na 2 CO 3 , (NH 4 ) 2 SO 4 , TritonX-100, C2H5OH, CH3OH, and acetone, where uptake capacity

The affinity of binding sites for metal ion sorption on microorganisms may be enhanced by the application of genetic and protein engineering and may lead to the development of new peptides or biopolymers (Goyal et al. 2003). Kao et al. (2008) used Escherichia coli with over-express metal-binding proteins (MerP) originating from Gram-positive (Bacillus cereus RC607) and Gram-negative (Pseudomonas sp. K-62) bacteria as sorbents for Cr(III), Zn(II), and Ni(II) removal. They further reported that sorbent containing Gram-positive MerP proteins seemed to work better for Ni(II) removal,

Heat-treated bacterial biomass


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Table 1 Bacteria used for biosorption of some heavy metals Metal

Sorbent

Operating conditions

Q (mg/ Reference g)

pH

X (g/L)

4.5

1

Escherichia coli

NA

3

120 28±2

Mycobacterium sp. strain Spyr1

5

1

45

Pseudomonas aeruginosa

NA

2.5

10e

Cr(III) Bacillus subtilis a

b

t T (°C) Co (mg/L) (min) 6e

60

25–100

23.9

Aravindhan et al. 2012

29.741

Kao et al. 2008

30

8.83– 1001.96 10–600

87.09

Aryal and Liakopoulou-Kyriakides 2013b

25

0–259.98

7.071

Kang et al. 2007


9

2

60

NA

20

6.23

Tuzen et al. 2008

Rhodococcus opacus

5

0.5

200

20

10–90

714.29

Calfa and Torem 2008

Streptomyces rimosus

4.8

3

5e

20

10–2400

83

Sahmoune et al. 2009

Cr(VI) Acinetobacter junii VITSUKMW2 Aeromonas caviae

2

2

60

27±1

5–200

22.70

Paul et al. 2012

2.5

0.5

120

20

5–350

284.4

Loukidou et al. 2004a

Arthrobacter viscosus

4

2

NA

NA

100

17

Silva et al. 2012

Bacillus licheniformis

2.5

1

120

50

20–300

69.35

Zhou et al. 2007

Bacillus sp. FM1

2

1

60

37

50–400

64.102

Masood and Malik 2011

Chryseomonas luteola TEM05

4

1

60

NA

0–90

3

Ozdemir and Baysal 2004


2

1

60

30

10–600

61.51

Aryal and Liakopoulou-Kyriakides 2013b

Ochrobacterium anthrobi

2

1

120

30

30–280

86.2

Ozdemir et al. 2003

Pseudomonas fluorescens TEM08

2

1

60

27

24.9–494.5

40.8

Uzel and Ozdemir 2009

Pseudomonas sp.

4.0

1

90

NA

5–450

95.0

Ziagova et al. 2007

Spirulina sp.

7

0.5

30

35

NA

185

Chojnacka et al. 2005

Streptococcus equisimilis

2

0.75

40

30

25–250

56.5

Goyal et al. 2003

Staphylococcus xylosus Mn(II) Anoxybacillus amylolyticus

1

8

165

NA

5–1100

143.0

Ziagova et al. 2007

6

2.5

60

60

10–300

9.980

Özdemir et al. 2013

e

Bacillus sp.

6-7

0.1

24

37

20–300

43.5

Hasan et al. 2012

Geobacillus thermantarcticus

6

2.5

60

60

10–300

23.200

Özdemir et al. 2013 Gialamouidis et al. 2010

Pseudomonas sp.

6

1

10

25

10–500

109

Pseudomonas aeruginosab

9

2

60

NA

20

5.83

Tuzen et al. 2008

Staphylococcus xylosus

6

1

10

25

10–500

59

Gialamouidis et al. 2010

Fe(III) Acidiphilium 3.2Sup(5)d Pseudomonas sp. Streptococcus equisimilis c

2

4

60

NA

2000

536.1

Tapia et al. 2011

2.5

1

25

35

10–400

86.20

Aryal and Liakopoulou-Kyriakides 2013a

2

0.75

40

30

50

19.73

Goyal et al. 2003

e


10

3

4

NA

10–800

125

Selatnia et al. 2004a


3

7

60

NA

10–1000

69

Aryal et al. 2010

Zoogloea ramigera

2

1

24e

25

25–200

36.36

Sag and Kutsal 1995

Co(II) Anoxybacillus amylolyticus

5

2.5

60

60

10–300

8.084



5

2.5

60

60

10-300

11.930


Paenibacillus jamilaed

5.5

NA

NA

NA

0.589–58.93 30.12

Pseudomonas aeruginosab

9

2

60

NA

20

6.06

Tuzen et al. 2008

Streptomyces noursei

5.8

3.5

60

30

58.93

1.2

Mattuschka and Straube 1993

Morillo et al. 2008

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Table 1 (continued) Metal

Ni(II)

Sorbent

Operating conditions pH

X (g/L)

t T (°C) Co (mg/L) (min)

4.5

4

100

7

2

Bacillus thuringiensis strain OSM29 7

1

Acinetobacter baumannii UCR2971 Bacillus pumilus a

28

0.4–1.0

8.8

Rodríguez et al. 2006

60

30

50–300

73.9

Wierzba and Latala 2010

30

32±2

25–150

43.13

Oves et al. 2013

Escherichia coli

NA

3

120 28±2


5.5

NA

NA

Pseudomonas aeruginosa ASU 6a

7

1

30

Pseudomonas fluorescens

7

2

60

Pseudomonas putida 5-xc

6.5

0.5

20

Pseudomonas sp.

5

1

10

NA e

NA

9.97– 34.33 1128.60 0.586–58.69 17.66

Kao et al. 2008 Morillo et al. 2008

30

0–160

113.6

Gabr et al. 2008

30

50–300

65.1

Wierzba and Latala 2010

25

9.2–46

36.8

Wang et al. 2003

10–600

508


Streptomyces coelicolor A3(2)

8

1

8

25

25–250

416.6

Ozturk et al. 2004

Streptomyces rimosusc

8

33

120

NA

10–600

32.9

Selatnia et al. 2004b Gialamouidis et al. 2009


6

1

20

NA

10–600

89

Zoogloea ramigera

4.5

1

24e

25

25–200

57.43

Sag and Kutsal 1995

4

2.5

60

60

10–300

12.390


Cu(II) Anoxybacillus amylolyticu

Zn(II)

Q (mg/ Reference g)

Arthrobacter sp.Sphe3

5

1

5

20

10–300

54.94

Aryal et al. 2012

Bacillus sp. FM1

5

1

60

37

50–400

78.125


Bacillus subtilisb

7

NA

NA

NA

0.05–0.5

1.884

Dogru et al. 2007


1

30

32±3

25–150

39.84

Oves et al. 2013

Enterobacter sp. J1

NA

24e

25

0–500

32.5

Lu et al. 2006

5


5

2.5

60

60

10–300

25.04


Micrococcus luteus IAM 1056c

5

0.5

60

25

NA

38.74

Nakajima et al. 2001


3

1

120

30

30–280

32.6

Ozdemir et al.2003


6

5.5

NA

NA

0.635–63.54 7.81

[33] Morillo et al. 2008

Paenibacillus polymyx

5

1

90

25

10–90

49

Colak et al. 2013

Pseudomonas stutzeri

5

1

30

30

50–300

33.16

Hassan et al. 2009

Spirulina sp.

7

1

30

35

NA

196

Chojnacka et al. 2005

Sphaerotilus natans

6

3

30

30

NA

60

Beolchini et al. 2006

Stenotrophomonas maltophilia

6

0.25

30

25

0–100

26

Ye et al. 2013

Streptomyces lunalinharesii

5

3

240

25

5–200

11.53

Veneu et al. 2013

Thiobacillus thiooxidansc

5

3

120

40

25–150

39.84

Liu et al. 2004

e

Zoogloea ramigera

4

1

24

25

25–200

34.05

Sag and Kutsal 1995

Aphanothece halophytica

7

0.2

60

30

0–100

133

Incharoensakdi and Kitjaharn 2002

6

1

30

30

0–200

66.66

Joo et al. 2010

Citrobacter strain MCM B-181

6.5

0.5

30

NA

6.53–114.43 27.71

Puranik and Paknikar 1999

Escherichia coli HD701

6

1

20

25

0–300

Morsy 2011

Escherichia colia

NA

3

120 28±2


5.5

NA

NA


6

1

30

Bacillus cereus AUMC B52 c

162.1

NA

11.11– 37.40 1257.44 0.653–65.39 12.31

Morillo et al. 2008

30

0–200

Joo et al. 2010

83.33

Kao et al. 2008


Page 9 of 26, 4173


Sorbent

Operating conditions pH

X (g/L)


Streptoverticillium cinnamoneum

5.5

2

30

28±3

50–1000

156.8



6

3

240

25

5–200

13.64

Veneu et al. 2013


7.5

3

240

20

10–300

88

Mameri et al. 1999

Thiobacillus ferrooxidanc

6

2

30

25

25–150

82.61

Celaya et al. 2000

As(III) Acidithiobacillus ferrooxidans

4

2

60

30

0.5–3

0.293

Yan et al. 2010

Arthrobacter sp.

7

1

30

28

25–200

74.91

Prasad et al. 2013

Bacillus cereus

7.5

6

60

30±2

1–10

32.42

Giri et al. 2011

Lactobacillus acidophilus

7

2

180

–

2000

800

Singh and Sarma 2010

Rhodococcus sp. WB-12

7

1

30

30

25–200

77.3

Prasad et al. 2011

–

c

Staphylococcus xylosus As(V) Arthrobacter sp.

7

1

30

3

1

30

10–300

54.35

Aryal et al. 2010

25–200

81.63

Prasad et al. 2013

Lactobacillus casei DSM20011c

7

2

5

22

0.1–5

0.312

Halttunen et al. 2007

Staphylococcus xylosusc

3

2

150

–

10–300

61.34

Aryal et al. 2010

Cd(II) Aeromonas caviae

7

1

120

20

5–350

155.3

Loukidou et al. 2004b

Acidiphilium symbioticum H8

6

10

24e

25

100–3000

248.62

Chakravarty and Banerjee 2012

Anoxybacillus amylolyticus

5

2.5

60

60

10–300

18.720


Bacillus cereus RC-1

5

1

30

28±2

5–60

31.95

Huang et al. 2013

Bacillus subtilisb

7.5

NA

NA

NA

0.025–0.5

3.920

Dogru et al. 2007 Oves et al. 2013


1

30

32±2

25–150

59.17

Brevundimonas sp. ZF12

6

20

150

30

50–350

49.01

Masoudzadeh et al. 2011

Citrobacter Strain MCM B-181c

6

0.5

30

–

66.10


Corynebacterium glutamicumc

6

2.5

30

25

11.24– 112.41 0–1000

139.9

Mao et al. 2013


6

1

20

25

0–300

162.1

Morsy 2011


4

2.5

60

60

10–300

32.88



8

1

120

30

30–280

37.3

Ozdemir et al. 2003


6

NA

NA

NA

112.41

20.49

Morillo et al. 2008

Pseudomonas sp.

7

2

30

NA

10–1000

278

Ziagova et al. 2007

Pseudomonas sp. LKS06

6

1

60

30

10–300

27.5

Huang and Liu 2013

Sphaerotilus natans

6

0–1

NA

25

500–1000

43.84

Esposito et al. 2001


8

3

120

NA

10–600

64.9

Selatnia et al. 2004c


6

2

60

NA

10–1000

250

Ziagova et al. 2007

7

0.02

72e

30

5–30

104.1

Sinha et al. 2012

Hg(II) Bacillus cereusb

Pb(II)

Q (mg/ Reference g)

Bacillus sp.

6

2

120

25

0.25–10

7.94

Green-Ruiz 2006

Pseudomonas aeruginosa PU 21 (Rip 64) Arthrobacter sp.

6.8

0.353

40e

25

10–500

194.4

Chang and Hong 1994

NA

30

10–400

125

Veglio et al.1997

Bacillus cereus

5– 1.4 5.5 6 1

80

25

10–80

23.25

Colak et al. 2011

Bacillus cereus M116b

6

24e

30

500

49.75

Paul et al. 2006

10

4173, Page 10 of 26



Sorbent

Operating conditions

Bacillus pumilus b

Q (mg/ Reference g)

pH

X (g/L)


6

1

80

25

10–80

29.57 12.4

Colak et al. 2011

Brevundimonas vesicularis

4

0.5

60

NA

5–30

Citrobacter Strain MCM B-181

4.5

0.5

30

NA

20.72–362.6 70.80


Corynobacterium glutamicum

5

5

120

20±2

0–3936.8

567.72

Choi and Yun 2004 Lu et al. 2006

e

Resmi et al. 2010

Enterobacter sp. J1

5

NA

24

25

0–500

50.9

Gloeocapsa gelatinosa

4

0.1

30

25

1–120

256.41

Raungsomboon et al. 2006

Hydrilla verticillata

4

2

120

25

2–50

125

Chathuranga et al. 2014


6

1

30

30±2

0–160

123

Gabr et al. 2008

Pseudomonas aeruginosa PU21b

5

200

15

50

73.4–329

0.723

Lin and Lai 2006


4

1

30

28±3

50–1000

109.3



NA

3

180

NA

10–800

137

Selatnia et al. 2004d

Zoogloea ramigera

4– 1 4.5

24e

25

25–200

81.23

Sag and Kutsal 1995

X biomass concentration, t contact time, T temperature, Co initial metal ion concentration, Q biosorption capacity, NA not available a

Genetically modified

b

Immobilized

c

Chemically modified

d

Bacterial by-product

e

Hours

while Gram-negative MerP displayed a higher sorption capacity for Zn(II) and Cr(III), respectively.

produced by Arthrobacter viscosus for Cd(II) was 2.3 times greater than that of intact cells.

Immobilized biomass Bacterial by-products High molecular weight substances, such as carbohydrates and proteins, are mainly produced by bacterial secretion (Yin et al. 2013). The literature showed that bacterial by-products have a great potential for heavy metal interaction (Tapia et al. 2011; Morillo et al. 2008; Scott and Palmer 1988). The extracellular polymeric substances (EPSs) of Acidiphilium 3.2 Sup (5) were able to remove Fe(III) at 536.1 mg/g from initial Fe(III) concentration of 2000 mg/L (Tapia et al. 2011). The EPS of Paenibacillus jamilae removed Co(II), Cu(II), Zn(II), Cd(II), and Pb(II) at 30.12, 77.81, 12.31, 20.49, and 303.03 mg/g, respectively, as reported by Morillo et al. (2008). Scott and Palmer (1988) showed that the sorption capacity of exopolysaccharides (EPS)

For industrial application, the use of an immobilized (palletized) biomass can improve biomass performance for heavy metal removal and makes reuse of biomass easier. The use of free bacterial cells for removal of heavy metals on a commercial scale may create problems due to the low density particle sizes, poor mechanical strength, and isolation of solid and liquid phase. Immobilization of bacterial biomass by matrixes makes the biomass more stable, rigid, and heat resistant with porosity for practical applications. Therefore, it needs to consider the immobilization of bacterial cells for heavy metal treatment from industrial effluents to overcome these shortcomings. The literature showed that very few efforts have been directed toward the remediation of heavy metals using immobilized bacterial biomass


(Ziagova et al. 2014; Ahmad et al. 2014; Chen et al. 2014). Higher uptake capacity of 104.1 mg/g for Hg(II) using sodium-alginate-immobilized Bacillus cereus biomass was reported by Sinha et al. (2012). The volcanic rock matrix–immobilized Pseudomonas putida and agar-immobilized Brevundimonas vesicularis biomass were proved efficient sorbents for Cu(II) and Pb(II) removal (Ni et al. 2012; Resmi et al. 2010). In addition, Lin and Lai (2006) also used Chitosan-alginateimmobilized Pseudomonas aeruginosa PU21 biomass for Pb(II) removal and reported much less sorption capacity at 0.723 mg/g.

Column packed bacterial biomass The batch sorption process is insufficient, and therefore, the column process can be used commercially. In order to describe the fixed bed column behavior and to scale it up for industrial application, successful design of a column process requires to predict the concentration time profile or breakthrough curve for the effluent (Resmi et al. 2010). Colak et al. (2011) compared the sorption potential of Bacillus cereus and Bacillus pumilus biomass for Pb(II) in batch and column methods and recorded that the column sorption capacity of both strains was higher than that of the batch system. Resmi et al. (2010) reported that agarimmobilized Brevundimonas vesicularis biomass was quite effective for Pb(II) removal in column system. According to Addour et al. (1999), column uptake capacity of Streptomyces rimosus biomass for Zn(II) removal was much lower compared to the batch system.

Methods for biomass characterization Different techniques have been used to characterize the biomass and sorption mechanism. In order to understand the surface binding mechanism, it is important to identify the functional groups and their number present on the biomass surface. The pKa values of surface functional groups in bacterial species have been determined using potentiometric titration as the addition of acid or alkali solutions (Aryal et al. 2012; Gabr et al. 2008; Kang et al. 2007; Esposito et al. 2001; Pagnanelli et al. 2000; Seki et al. 1998). However, it cannot be solely considered for determination of binding sites responsible for metal interaction, since some pKa values

Page 11 of 26, 4173

are overlapped due to the complex nature of bacterial biomass. Pagnanelli et al. (2000) reported that the phosphate and amino or amide groups were present on Arthrobacter sp. cell wall. The presence of carboxyl and hydroxyl groups in Sphaerotilus natans cells was also identified by Pagnanelli et al. (2002). The carboxyl, amine, and phosphate groups were determined on Pseudomonas aeruginosa ASU 6a (Gabr et al. 2008), Rhodobacter sphaeroides, and Alcaligenes eutrophus H16 surface (Seki et al. 1998). The higher active sites in living Shewanella putrefaciens (Chubar et al. 2008) and Acinetobacter junii VITSUKMW2 cells (Paul et al. 2012) than dead cells were recorded. In addition, carboxylic groups were mainly responsible for Fe(III) sorption in Staphylococcus xylosus biomass, where 2 mol of carboxylic groups was involved for 1 mol Fe(III) ions sorption (Aryal et al. 2010). The shifting of wave number as well as disappearance and reappearance of spectral bands from raw biomass to metal-loaded biomass was used to illustrate the binding of metal ions on biomass surface. Fourier transform infrared (FTIR) spectroscopy results revealed that carboxylic, amine, amide, phosphate, hydroxyl, carbonyl, phosphoryl, sulphonate, aldehyde, and amide sites of bacterial cells are the key functional groups for metal ion interaction (Guo et al. 2012; Hasan et al. 2012; Masood and Malik 2011; Aryal et al. 2010; Gabr et al. 2008; Jian-hua et al. 2007; Kang et al. 2007; Tunali et al. 2006; Sar et al. 1999). Oliveira et al. (2014) showed that alginate carboxylate groups are responsible for La(III) complexation on Sargassum sp. biomass. Carboxylic groups on the surface of Sargassum ilicifolium were also found to interact with Zn+2, Cu+2, and Ni+2 as reported by Tabaraki and Nateghi (2014). In some other cases, aliphatic and aromatic groups were also suggested for metal binding sites (Huang et al. 2013; Ye et al. 2013; Li et al. 2010; Tunali et al. 2006). Huang et al. (2013) reported that more functional groups were involved in the biosorption of Cd(II) in dead Bacillus cereus RC-1 biomass than that of live one, whereas Chubar et al. (2008) reported that live and dead Shewanella putrefaciens cells exhibited the same absorption bands for Zn(II) and Cu(II), respectively. The zeta potential study provides the valuable information of the net effective charges present on the bacterial cell surface. Huang et al. (2013) reported that dead Bacillus cereus RC-1 cells exhibited a greater amount of negative surface charges than active cells. It was further reported the electrostatic interaction as the predominant

4173, Page 12 of 26

mechanism for Cd(II) sorption. Paul et al. (2012) explained that negatively charged Cr(VI) ions were interacted with positively charged Acinetobacter junii VITSUKMW2 surface, whereas Calfa and Torem (2008) stated that positively charged Cr(III) species were bonded with negatively charged Rhodococcus opacus surface through electrostatic interaction. Transmission electron microscopy (TEM) analysis can be generally used to determine the metal ions present inside the living cell. Wang et al. (2003) reported that the acid used for pre-treatment of bacterial cells degraded the superficial layer-capsule outside of the intact cell and improved Ni(II) sorption. Huang et al. (2013) mentioned that intracellular uptake of live cells for Cd(II) was negligible and attributed to the cell surface sorption. Chakravarty and Banerjee (2012) also observed the electron-dense region/layer throughout the Acidiphilium symbioticum H8 cell wall and not intracellular accumulation of Cd(II) ions. Scanning electron microscopy (SEM) analysis has been used for the interaction of metal ions on biomass surface. Tunali et al. (2006) suggested that the Pb(II) and Cu(II) sorption on Bacillus sp. (ATS-1) surface was proceeded as an ion exchange mechanism. Paul et al. (2012) expressed that protein and polysaccharides of Acinetobacter junii VITSUKMW2 cells were involved for Cr(VI) sorption through oxy-anionic binding mechanism, and further examined that lower sorption capacity of inactive biomass than active biomass may be due to the loss of surface functional groups. Guo et al. (2012) observed that the precipitation of organic functional groups of Pseudomonas plecoglossicida cells and metal complexation were involved in the Cd(II) biosorption process. Huang et al. (2013) concluded that Cd(II) significantly damaged the Bacillus cereus RC-1 biomass surface and therefore dead cells showed higher removal efficiency than live cells. The literature also showed that metal-loaded bacterial surface was distorted and seemed to be damaged by the heavy metal ion sorption (Colak et al. 2013; Kao et al. 2008; Lu et al. 2006; Masoudzadeh et al. 2011). In addition, Hasan et al. (2012) demonstrated that Bacillus sp. cells were morphologically rod-shaped and the small size of Bacillus sp. was enhanced by the Mn(II) biosorption due to a rapid metabolic process. Electron magnetic resonance (EPR) spectroscopy has also been used for studying the material with unpaired electrons. Paul et al. (2012) conducted the EPR analysis in order to detect the possible valence states of


chromium before and after sorption on Acinetobacter junii VITSUKMW2 biomass and concluded the paramagnetic nature of Cr(VI) and that reduction of Cr(VI) to Cr(V) occurred by functional groups upon sorption on the bacterial surface. Nakajima et al. (2001) reported that Cu(II) sorption on raw and chemically modified Micrococcus luteus IAM 1056 cells with NaOH, chloroform-methanol, and chloroform-methanol/concentrated KOH proceeds through coordination with oxygen and nitrogen atoms, whereas the interaction between Cu(II) ions and chloroform-methanol-treated cells was more stable compared to remaining sorbents used. The X-ray powder diffraction (XRD) is a method using X-ray on microcrystalline samples for structural characterization of materials. Sar et al. (1999) investigated that both Ni(II) and Cu(II) were deposited on the Pseudomonas aeruginosa cell predominantly as phosphide crystals. Masoudzadeh et al. (2011) revealed that Cd (II) biosorption on Brevundimonas sp. ZF12 surface is more complicated, due to the appearance of new peaks in XRD spectrum. X-ray photoelectric spectroscopy (XPS) can be performed to characterize the surface chemistry of metal ions. Ye et al. (2013) showed that proteins and polysaccharides were present on Stenotrophomonas maltophilia surface. Cu(II) ions adsorbed via ion-exchange mechanism, and Cu(II) was also reduced to Cu(I) by these bacterial cells. The presence of As(III) as surface species on Lactobacillus acidophilus biomass surface was also recorded by Singh and Sarma (2010). Energy-dispersive X-ray (EDX) is a useful analytical tool to evaluate the elemental or chemical characterization of sample or to observe the identity of metal ions on bacterial cell wall. Huang et al. (2013) confirmed the destruction of some binding sites on live Bacillus cereus RC-1 biomass surface after sorption of Cd(II) ions, thus resulting in lower sorption capacity than dead cells. Paul et al. (2012) observed that protein and polysaccharides of Acinetobacter junii VITSUKMW2 cells participated in Cr(VI) uptake. The results obtained by Guo et al. (2012) and Tunali et al. (2006) showed that the ion exchange mechanism was involved in Cd(II) sorption on Pseudomonas plecoglossicida biomass, and in Pb(II) and Cu(II) sorption on Bacillus sp. (ATS-1) biomass. Huang and Liu (2013) expressed that polysaccharides and proteins were present in Pseudomonas sp. LKS06 cell wall. Colak et al. (2013) reported the accumulation of Cu(II) and Ni(II) ions on Paenibacillus polymyxa biomass surface. Chakravarty and Banerjee (2012)


determined that the accumulation of Cd(II) ions on Acidiphilium symbioticum H8 cell envelop via extracellular association, may be due to the electrostatic/or ion exchange, and complexation mechanism. Extended X-ray absorption fine structure (EXAFS) methodology can be applied to explore the mechanism of metal ion sorption on bacterial cells. Moon and Peacock (2011) reported Cu(II) sorption on the Bacillus subtilis biomass surface as a (CuO5Hn)n-8 mono-dentate, inner-sphere surface complex via carboxyl groups.

Kinetic studies Biosorption kinetics can provide valuable information on the reaction pathways and the mechanism of the biosorption process (Blázquez et al. 2014; Maurya and Mittal 2014). The prediction of sorption rate gives an idea for designing the batch sorption systems. Several kinetic models have been applied to correlate the kinetic data of different metal ions in various bacterial cells (Vijayaraghavan and Joshi 2014). Kinetic models used for biosorption of some selected heavy metals using bacteria are presented in Table 2. It can be observed that pseudo-second-order kinetic model described the experimental kinetic data in most of the cases. The best fit of experimental kinetic data with pseudo-second-order kinetic model assumes that the chemisorptions may be the rate-controlling step. The pseudo-first-order equation also correlated the experimental kinetic data in some cases (Mao et al. 2013; Morsy 2011; Rodriguez-Tirado et al. 2012; Hassan et al. 2009; Selatnia et al. 2004a) and assumes that metal ions bind only to one active site of bacterial biomass surface. The k1/ko values obtained using Langmuir-Hinshelwood kinetic model suggested the higher loading of Cr(III) than Cr(VI) on Mycobacterium sp. biomass (Aryal and Liakopoulou-Kyriakides 2013b).

Diffusion studies Parabolic diffusion, external mass diffusion, intraparticle diffusion, and Boyd kinetic models as well as a combinative model of pseudo-second-order and intraparticle diffusion were used in order to investigate the mechanism of heavy metal sorption and potential rate-controlling steps (Aryal and LiakopoulouKyriakides 2013b; Rodriguez-Tirado et al. 2012; Lu

Page 13 of 26, 4173

et al. 2006; Loukidou et al. 2004ab; Selatinia et al. 2004a–d). Intraparticle diffusion kinetic model revealed the biosorption complex nature and that more than one diffusive mechanism are involved in sorption of heavy metals (Aryal and Liakopoulou-Kyriakides 2013b; Aravindhan et al. 2012; Gialamouidis et al. 2010; Sahmoune et al. 2009). A study by Loukidou et al. (2004a) proposed that the external mass transfer was the predominant mechanism of the sorption of Cr(VI) on Aeromonas caviae biomass. Film diffusion mechanism was suggested for Cr(III) and Cr(VI) sorption with Mycobacterium sp. biomass using Boyd kinetic model (Aryal and Liakopoulou-Kyriakides 2013b). Lu et al. (2006) used a combinative kinetic model of second order and the intraparticle diffusion in sorption of Cu(II), Cd(II), and Pb(II) ions on Enterobacter sp. J1 biomass and reported that intracellular accumulation played a crucial role.

Equilibrium studies Biosorption isotherm is the relationship between quantities of metal ions per unit of bacterial biomass and the concentration of these metal ions in the solution. The isotherm parameters give information about surface properties and the affinity of binding sites of bacterial cells as well as biosorption mechanism. Determination of isotherm parameters provides important information about the design of biosorption systems. Several isotherm models have been used to fit the equilibrium data in order to study the nature of biosorption process. However, two-parameter isotherm models have been widely used for heavy metal sorption with bacteria, since they are simple and explain the experimental equilibrium data very well. The isotherm model used in heavy metal sorption is given in Table 3. The literature showed that Langmuir and Freundlich models are among the best models for sorption of heavy metals. The theoretical basis of the Langmuir model relies that there are a finite number of binding sites on the adsorbent surface with the same affinity for adsorption of a single molecular layer and there is no interaction between adsorbed molecules, whereas Freundlich model assumes that the adsorption energy of a metal binding to a site on an adsorbent depends on whether the adjacent sites are already occupied or not. Both Langmuir and Freundlich

4173, Page 14 of 26


Table 2 Kinetic studies of sorption of some heavy metals on bacterial biomass Metal

Sorbent

Cr(III) Bacillus subtilis Mycobacterium sp. strain Spyr1

Rhodococcus opacus Streptomyces rimosus

Reference

Pseudo-first order and pseudo-second order

Pseudo-second order


Langmuir-Hinshelwood, Lagergren pseudo-first order, pseudo-second order, Ritchie pseudo-second-order, and Sobkowsk and Czerwinskipseudo second order Pseudo-first order and pseudo-second order

Pseudo-second order

Aryal and LiakopoulouKyriakides 2013b

Pseudo-second order


Pseudo-second order


Pseudo-first order

Paul et al. 2012

Pseudo-second order Pseudo-second order

Zhou et al. 2007



Pseudo-second order


Lysinibacillus sp. BA2


Pseudo-second order

Prithviraja et al. 2014


Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order

Pseudo-second order Pseudo-first order

Colak et al. 2013

First order, second order, third order, pseudo-first order, pseudo-second order, and Elovich Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order Pseudo-second order

Pseudo-second order

Rodriguez-Tirado et al. 2012

Pseudo-second order Pseudo-second order Pseudo-second order Zero order, first order, and second order First order

Colak et al. 2013

Bacillus licheniformis Mycobacterium sp. strain Spyr1

Mn(II) Bacillus sp. Pseudomonas sp.


Streptomyces rimosus Cu(II) Bacillus thioparans strain U3

Paenibacillus polymyx Streptomyces lunalinharesii Pseudomonas putida Pseudomonas stutzeri Zn(II)

Kinetic model applicability

Fractional power, pseudo-first order, and pseudo-second order Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order Langmuir–Hinshelwood, Lagergren pseudo-first order, pseudo-second order, Ritchie pseudo-second order, and Sobkowsk and Czerwinskipseudo second order Pseudo-first order and pseudo-second order Zero order, First order, pseudo-first order, pseudo-second order, and Elovich Zero order, first order, pseudo-first order, pseudo-second order

Cr(VI) Acinetobacter junii VITSUKMW2

Ni(II)

Kinetic model used

Bacillus cereus AUMC B52 Escherichia coli HD701 Pseudomonas aeruginosa, Pseudomonas fluorescens, Escherichia coli, Chlorella vulgaris, Spirulina platensis Pseudomonas aeruginosa ASU 6a

Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order

Pseudo-second order Pseudo-second order Pseudo-first order and pseudosecond order Pseudo-second order

Aryal and LiakopoulouKyriakides 2013b Hasan et al. 2012

Selatnia et al. 2004b

Veneu et al. 2013 Ni et al. 2012 Hassan et al. 2009 Joo et al. 2010 Morsy 2011 Péter et al. 2014

Joo et al. 2010


Page 15 of 26, 4173


Sorbent

Kinetic model used

Kinetic model applicability

Reference


Pseudo-first order and pseudo-second order Pseudo-first order

Pseudo-second order Pseudo-first order

Veneu et al. 2013

Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order

Pseudo-second order Pseudo-second order Pseudo-second order Pseudo-second order

Yan et al. 2010

Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order


Huang et al. 2013

Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order

Pseudo-second order Pseudo-second order Pseudo-second order

Streptomyces rimosus As(III) Acidithiobacillus ferrooxidans Arthrobacter sp. Rhodococcus sp. WB-12 Cd(II) Acidiphilium symbioticum H8 Bacillus cereus RC-1 Brevundimonas sp. ZF12 Corynebacterium glutamicum Escherichia coli HD701 Pseudomonas sp. LKS06

Pb(II)

Mameri et al. 1999

Prasad et al. 2013 Prasad et al. 2011 Chakravarty and Banerjee 2012

Masoudzadeh et al. 2011 Mao et al. 2013 Morsy 2011 Huang and Liu 2013


Zero order, first order, and second order First order

Hassan et al. 2009



Pseudo-second order


Bacillus cereus

Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order First order, second order, third order, pseudo-first order, pseudo-second order, and Elovich Pseudo-first order and pseudo-second order Pseudo-first order and pseudo-second order

Pseudo-second order Pseudo-second order Pseudo-second order

Colak et al. 2011

Pseudo-first order

Lin and Lai 2006

Pseudo-second order

Huang and Liu 2013


Pseudo-first order


Bacillus pumilus Bacillus thioparans strain U3

Pseudomonas aeruginosa PU21 Pseudomonas sp. LKS06 Streptomyces rimosus

models were suitable for sorption of some metal ions (Huang and Liu 2013; Joo et al. 2010; Gabr et al. 2008; Lu et al. 2006; Puranik and Paknikar 1997; Sag and Kutsal 1995), but no one explained how these two opposite models fitted the experimental data simultaneously. Li et al. (2010) reported that Zn(II) sorption on dead and live Streptomyces ciscaucasicus strain CCNWHX 72–14 biomass followed Langmuir and Freundlich isotherm models. The Scatchard plot analysis was also applied to

Colak et al. 2011 Rodriguez-Tirado et al. 2012

equilibrium data for Ni(II) and Cu(II) on Streptomyces coelicolor A3(2) (Ozturk et al. 2004), Mn(II), Cd(II), Co(II), and Cu(II) on Anoxybaccilus amylolyticus and Geobaccilus thermantarcticus (Ozdemir et al. 2003), Mn(II) on Bacillus sp. and Anoxybacillus amylolyticus (Hasan et al. 2012), Cr(VI) on Bacillus thuringiensis (Şahin and Öztürk 2005), and Cu(II) and Zn(II) on Pseudomonas putida CZ1 biomass, respectively (Chen et al. 2005), and suggested that single or distinct types

4173, Page 16 of 26

of binding sites are present on biomass surface, which is indicative of monolayer coverage (Puranik and Paknikar 1997). The equilibrium data were well described by the Temkin model for Cr(III) sorption and Hill-der Boer isotherm model for Cr(VI) sorption on Mycobacterium sp. biomass (Aryal and Liakopoulou-Kyriakides 2013b). The threeparameter isotherm model, Langmiur-Freundlich, or Sips was also suitable for Cd(II) sorption on Acidiphilium symbioticum H8 and Pseudomonas sp. LKS06 (Huang and Liu 2013; Chakravarty and Banerjee 2012) and Cd(II) and Pb(II) on Escherichia coli and Pseudomonas sp. LKS06, respectively (Huang and Liu 2013). In most of the column studied, Thomas model was tested and observed the best fit to the experimental data (Colak et al. 2013; Resmi et al. 2010).

Thermodynamic studies The thermodynamic studies can provide valuable information of the overall heat and energies associated with complex multipath biosorption processes and biosorption mechanisms. Standard Gibbs free energy change (ΔGo) indicates the degree of spontaneity of the sorption process. The negative and positive ΔGo values indicate the spontaneous and non-spontaneous sorption process, whereas ΔGo values up to −20 kJ/mol and greater than −40 kJ/ mol indicate the physical and chemical adsorption. Based on the magnitudes of ΔGo values, spontaneous (Prasad et al. 2013; Aryal et al. 2012; Chakravarty and Banerjee 2012; Yan et al. 2010; Lin and Lai 2006) and non-spontaneous (Gialamouidis et al. 2010; Uslu and Tanyol 2006) biosorption processes were reported. Interestingly, Paul et al. (2012) reported that Cr(VI) sorption on live cells of Acinetobacter junii VITSUKMW2 was spontaneous, whereas Cr(VI) sorption on heatkilled cells was non-spontaneous. The data showed that Cr(VI) and As(V) sorption on Fe(III)-treated Staphylococcus xylosus biomass involved the electrostatic interaction as predominant mechanism, since the calculated ΔG o values were found on the border line of physisorption and chemisorptions (Aryal et al. 2011). The negative and positive values of ΔHo indicate the exothermic and the endothermic nature of biosorption process. The exothermic nature in heavy metal sorption was suggested in most of the cases (Prasad et al. 2013;


Aryal et al. 2012; Chakravarty and Banerjee 2012; Lin and Lai 2006), whereas endothermic nature was reported in some extent (Gialamouidis et al. 2010; Uslu and Tanyol 2006). According to Gialamouidis et al. (2010), endothermic nature of Mn(II) sorption on Pseudomonas sp. and Staphylococcus xylosus cells may be due to the Mn(II) ions solvated in water, and dehydration process requires heat energy. Paul et al. (2012) reported the negative values of ΔHo for Cr(VI) sorption on active Acinetobacter junii VITSUKMW2 cells, whereas the opposite trend was observed in dead biomass. ΔHo values ranging from 2.1 to 20.9 kJ/mol correspond to physisorption, whereas values ranging from 20.9 to 418.4 kJ/mol indicate the chemisorption. Based on these, Cr(VI) and As(V) sorption on Fe(III)-treated Staphylococcus xylosus proceeded through physisorption mechanism (Aryal et al. 2011). As(III) sorption on Rhodococcus sp. (Prasad et al. 2011), Mn(II) sorption on Pseudomonas sp. and Staphylococcus xylosus (Gialamouidis et al. 2010), As(III) and As(V) sorption on Arthrobacter sp. (Prasad et al. 2013), and As(III) sorption on Acidithiobacillus ferrooxidans biomass (Yan et al. 2010) were also supposed as chemisorption. Positive and negative values of entropy change (ΔSo) indicate the increased and decreased randomness at the solid/solution interface during the heavy metal sorption. The majority of literature reported positive values of ΔS (Aryal and Liakopoulou-Kyriakides 2013b; Aryal et al. 2012; Chakravarty and Banerjee 2012; Yan et al. 2010; Lin and Lai 2006), while other few calculated the negative values for heavy metal sorption (Aryal and Liakopoulou-Kyriakides 2013a; Prasad et al. 2013).

Activation energy of biosorption The activation energy (Ea) is an energy level that must be achieved over the initial energy level of a substance in order to make an effective chemical reaction. The greater the activation energy, the slower is the reaction rate. The Ea values in the range of 8 to 25 correspond to physical adsorption, less than 21 to aqueous diffusion, and 20–40 to pore diffusion, whereas values greater than 84 suggest the ion exchange as the sorption mechanism. The data indicated that Cr(III) and Cr(VI) sorption onto Mycobacterium sp. cells followed a physisorption mechanism (Aryal and Liakopoulou-Kyriakides 2013b).


Page 17 of 26, 4173

Table 3 Equilibrium studies of sorption of some heavy metals on bacterial biomass Metal

Sorbent

Isotherm model used

Isotherm applicability

Reference

Langmuir and Freundlich

Freundlich


Langmuir and Temkin



Langmuir, Freundlich, Temkin, Hill-der Boer, and Dubinin–Radushkevich Langmuir and Freundlich

Langmuir

Kang et al. 2007

Rhodococcus opacus


Freundlich



Langmuir, Freundlich, and Brunnauer-Emmett-Teller




Langmuir, Freundlich, and Temkin

Langmuir


Langmuir

Paul et al. 2012

Aeromonas caviae

Langmuir, Freundlich, and Dubinin–Radushkevich Langmuir and Freundlich

Langmuir

Loukidou et al. 2004a

Bacillus licheniformis


Langmuir

Zhou et al. 2007

Cr(III) Bacillus subtilis Mycobacterium sp. strain Spyr1

Cr(VI) Acinetobacter junii VITSUKMW2

Bacillus sp. FM1


Freundlich


Bacillus thuringiensis strain OSM29


Oves et al. 2013

Chryseomonas luteola TEM05


Langmuir and Freundlich Freundlich


Langmuir and Hill-der Boer



Langmuir, Freundlich, Temkin, Hill-der Boer, and Dubinin–Radushkevich Langmuir and Freundlich

Freundlich

Ozdemir et al. 2003

Pseudomonas fluorescens TEM08


Langmuir


Pseudomonas sp.


Freundlich

Ziagova et al. 2007

Streptococcus equisimilis

Freundlich

Freundlich

Goyal et al. 2003



Freundlich

Ziagova et al. 2007


Langmuir


Mn(II) Anoxybacillus amylolyticus

Ozdemir and Baysal 2004

Arthrobacter sp.

Langmuir

Langmuir

Veglio et al.1997

Bacillus sp.

Langmuir

Hasan et al. 2012


Langmuir, Freundlich, Temkin, Dubinin-Radushkevich, and Redlich-Peterson Langmuir and Freundlich

Langmuir


Pseudomonas sp.


Langmuir




Freundlich


Langmuir

Langmuir

Pagnanelli et al. 2000

Fe(III) Arthrobacter sp. Staphylococcus xylosus


Langmuir

Aryal et al. 2010



Langmuir

Selatnia et al. 2004a

Zoogloea ramigera


Sag and Kutsal 1995

Co(II) Anoxybacillus amylolyticus


Langmuir and Freundlich Langmuir



Langmuir


Geobacillus thermantarcticus Ni(II)

Paenibacillus jamilae

Langmuir

Langmuir

Morillo et al. 2008

Acinetobacter baumannii UCR-2971 Bacillus thuringiensis strain OSM29

Langmuir

Langmuir

Rodríguez et al. 2006



Oves et al. 2013

4173, Page 18 of 26



Sorbent

Isotherm model used


Reference

Lysinibacillus sp. BA2 (dead biomass) Paenibacillus polymyxa



Prithviraja et al. 2014

Pseudomonas aeruginosa ASU 6a Pseudomonas fluorescens TEM08 Pseudomonas sp. Streptomyces coelicolor A3(2)


Colak et al. 2013





Freundlich



Freundlich

Ozturk et al. 2004



Langmuir

Selatnia et al. 2004b

Zoogloea ramigera

Langmuir, Freundlich

Gabr et al. 2008

Sag and Kutsal 1995 Özdemir et al. 2013



Arthrobacter sp. Sphe3


Freundlich

Aryal et al. 2012

Cu(II) Anoxybacillus amylolyticus

Zn(II)


Bacillus sp. FM1


Freundlich


Bacillus sphaericus


Langmuir

Aryal et al. 2012

Bacillus thuringiensis strain OSM29 Enterobacter sp. J1


Oves et al. 2013




Langmuir and Freundlich Langmuir and Freundlich Langmuir


Micrococcus luteus IAM 1056


Langmuir

Nakajima et al. 2001



Langmuir

Ozdemir et al. 2003



Langmuir

Colak et al. 2013

Pseudomonas putida


Ni et al. 2012




Hassan et al. 2009

Shewanella putrefaciens

Langmuir

Langmuir

Chubar et al. 2008

Sphaerotilus natans

Langmuir


Streptomyces coelicolor A3(2)

Langmuir, Freundlich and Redlich-Peterson Langmuir and Freundlich

Langmuir

Ozturk et al. 2004



Freundlich

Veneu et al. 2013


Langmuir, Freundlich, and Brunnauer-Emmett-Teller



Zoogloea ramigera


Sag and Kutsal 1995

Aphanothece halophytica

Langmuir


Bacillus jeotgali strain U3


Freundlich

Green-Ruiz et al. 2008

Bacillus cereus AUMC B52


Joo et al. 2010 Morsy 2011

Lu et al. 2006

Incharoensakdi and Kitjaharn 2002





Langmuir

Langmuir

Morillo et al. 2008



Joo et al. 2010

Pseudomonas putida CZ1



Chen et al. 2005

Shewanella putrefaciens

Langmuir

Langmuir

Chubar et al. 2008


Page 19 of 26, 4173


Sorbent

Isotherm model used


Reference







Langmuir

Veneu et al. 2013


Langmuir

Yan et al. 2010

Langmuir, Freundlich and DubininRadushkevich Langmuir, Freundlich and DubininRadushkevich Langmuir and Freundlich

Langmuir

Prasad et al. 2013

Langmuir

Prasad et al. 2011

Langmuir

Aryal et al. 2010

Langmuir, Freundlich, and DubininRadushkevich Langmuir

Langmuir

Prasad et al. 2013

Langmuir

Halttunen et al. 2007

As(III) Acidithiobacillus ferrooxidans Arthrobacter sp. Rhodococcus sp. WB-12 Staphylococcus xylosus As(V) Arthrobacter sp. Lactobacillus casei DSM20011 Staphylococcus xylosus


Langmuir

Aryal et al. 2010

Langmuir– Freundlich dual model Langmuir

Chakravarty and Banerjee 2012

Aeromonas caviae

Langmuir, Freundlich, Temkin, Dubinin-Radushkevich, Temkin, and Langmuir–Freundlich dual model Langmuir and Freundlich

Loukidou et al. 2004b

Anoxybacillus amylolyticus


Langmuir


Arthrobacter sp.

Langmuir

Langmuir

Pagnanelli et al. 2000

Bacillus cereus RC-1

Langmuir, Freundlich, and Redlich– Peterson

Huang et al. 2013

Bacillus jeotgali strain U3


Langmuir and RedlichPeterson Langmuir



Brevundimonas sp. ZF12



Corynebacterium glutamicum


Langmuir

Mao et al. 2013



Langmuir

Morsy 2011

Enterobacter sp. J1


Lu et al. 2006







Langmuir



Langmuir

Langmuir

Morillo et al. 2008

Pseudomonas aeruginosa CA207Ni, Langmuir and Freundlich Burkholderia cepacia AL96Co, Corynebacterium kutscheri FL108Hg, Rhodococcus sp AL03N Pseudomonas sp. Langmuir and Freundlich

Langmuir

Oyetibo et al. 2014

Freundlich

Ziagova et al. 2007


Langmuir, Freundlich, and LangmuirFreundlich dual model

Huang and Liu 2013

Sphaerotilus natans Staphylococcus xylosus

Langmuir, Freundlich, and RedlichPeterson Langmuir and Freundlich

LangmuirFreundlich dual model Langmuir Freundlich

Ziagova et al. 2007



Langmuir


Langmuir, Freundlich, and DubininRadushkevich Langmuir and Freundlich

Langmuir

Sinha et al. 2012

Freundlich

Green-Ruiz 2006

Cd(II) Acidiphilium symbioticum H8

Hg(II) Bacillus cereus Bacillus sp.

Green-Ruiz et al. 2008 Oves et al. 2013 Masoudzadeh et al. 2011


4173, Page 20 of 26



Sorbent

Isotherm model used


Reference

Freundlich

Langmuir

Chang and Hong 1994

Pb(II)

Pseudomonas aeruginosa PU 21 (Rip64) Arthrobacter sp.

Langmuir

Langmuir

Veglio et al.1997

Bacillus cereus


Langmuir

Colak et al. 2011

Bacillus cereus M116

Freundlich

Freundlich

Paul et al. 2006

Brevundimonas vesicularis

Langmuir

Langmuir

Resmi et al. 2010



Oves et al. 2013 Lu et al. 2006

Enterobacter sp. J1


Langmuir and Freundlich Freundlich


Langmuir

Langmuir

Morillo et al. 2008



Gabr et al. 2008

Pseudomonas aeruginosa PU21




Langmuir, Freundlich, and LangmuirFreundlich dual model


Lin and Lai 2006

Langmuir, Freundlich, and BrunnauerEmmett-Teller

LangmuirFreundlich dual model Langmuir and Freundlich




Langmuir






Zoogloea ramigera



Sag and Kutsal 1995

Isosteric heat of biosorption The heat of sorption determined for a constant amount of metal ions adsorbed is known as the isosteric heat of adsorption (ΔHr). The negative and positive values of ΔHr suggest an exothermic and endothermic nature of sorption process. In addition, ΔHr values lower than 80 kJ/mol were for physical sorption and those between 80 and 400 kJ/mol were for chemical sorption. It has been reported that Cu(II) biosorption on Arthrobacter sp. Sphe3 and Bacillus sphaericus was exothermic and endothermic in nature (Aryal et al. 2012). In addition, Cr(III) and Cr(VI) sorption onto Mycobacterium sp. cells via physisorption mechanism with exothermic nature was also suggested (Aryal and LiakopoulouKyriakides 2013b).

Mean free energy of biosorption The mean free energy of sorption (E) gives an idea about biosorption mechanism. The E values between 8 and

Huang and Liu 2013

16 kJ/mol and ≤8 kJ/mol indicate the chemical and physical sorption as the predominant mechanism. Mn(II) sorption on Bacillus sp. (Hasan et al. 2012), and As(III) and As(V) sorption on Arthrobacter sp. biomass (Prasad et al. 2013) indicated the chemical ion exchange mechanism. Sinha et al. (2012) reported that Pb(II) sorption on calcium-alginate-immobilized Bacillus cereus cells was chemisorption in nature. Furthermore, physical sorption as the predominant mechanism for both Cr(III) and Cr(VI) sorption on Mycobacterium sp. biomass was also reported (Aryal and LiakopoulouKyriakides 2013b).

Desorption and regeneration studies Recovery of metal ions from metal-loaded biomass and reuse of biomass are very important for any successful biosorption process in practical applications, since metal ions can be recovered in concentrated form and regenerated biomass may reduce the operational costs. Mineral acids proved as quite effective in metal desorption,


but they may damage the biomass binding sites and decrease the biosorption efficiency in subsequent uses. The desorption of As(III) and As(V) approached around 28 and 25 % using de-ionized water at solid-to-liquid ratio of 2 g/L (Aryal et al. 2010). Sahmoune et al. (2009) reported that 95 % of Cr(III) desorption was resulted at zero pH using HCl and H2SO4. Masoudzadeh et al. (2011) carried out the desorption of Cd(II) from Brevundimonas sp. ZF12 cells using HCl at pH 2.0, 3.0, 4.0, and 5.0, respectively, where higher than 90 % of metal ions were desorbed in all pH conditions except that at 5.0. Addour et al. (1999) reported that Zn(II) was recovered around 90 % at 0.1 M HCl, whereas around 50 % was desorbed in 0.5 and 1.0 M HCl in column system. Huang et al. (2013) found that 91.2 and 70.2 % of Cd(II) were desorbed from dead and live Bacillus cereus RC-1 cells using HCl at pH 1.0. Mattuschka and Straube (1993) examined that desorption of Cu(II) and Pb(II) was efficient with 0.1 and 2.5 M HCl, whereas highly concentrated HCl was able to desorb chromium ions from Streptomyces noursei biomass. They further reported that acetic acid, lactic acid, and HNO3 showed a higher desorption capacity while H 2O, NaOH, NaHCO3, and EDTA seemed to give insignificant Cu(II) desorption. Sar et al. (1999) revealed that 0.1 N HCl, H2SO4, and HNO3 as well as 1 mM nitrilotriacetic acid gave more than 75 % Ni(II) and Cu(II) desorption, while Ni(II) and Cu(II) desorbed at 71 and 57 %, and 21 and 88 % with 10 mM of CaCO3 and Na2CO3 solutions from Pseudomonas aeruginosa biomass. Falla et al. (1995) reported that nitrilotriacetic acid at 1 mM recovered around 95 % of Cu(II), Cd(II), and Zn(II) from Pseudomonas fuorescence biomass. Tuzen et al. (2008) used multiwalled carbon nanotube–immobilized Pseudomonas aeruginosa for Co(II), Cd(II), Pb(II), Mn(II), Cr(III), and Ni(II) sorption with high removal efficiency of more than 50 cycles. The extent of desorption efficiency may predict whether physical or chemical mechanism is involved in the biosorption process. Highest desorption at low concentrations and lowest desorption at high concentration of desorbing agents may indicate the physical and chemical sorption processes (Aryal and Liakopoulou-Kyriakides 2011).

Conclusions and perspectives Biosorption has been used for both toxic metal and nonmetal removal from aqueous solutions. The sorption

Page 21 of 26, 4173

capacity of heavy metals was found to be dependent on pH, biomass loading, equilibrium time, initial metal ion concentration, temperature, and the method of the sorption process applied. It is advantageous that biosorption of heavy metals is a fast process and, in most cases, ambient temperature is the optimum temperature for heavy metal sorption. Chemically or, in some cases, biologically treated bacterial biomass presented better characteristics with high sorption capacities. Thermodynamic studies conducted in many cases provide valuable information of the overall heat and energies associated with the complex multipath biosorption processes and mechanisms. Standard Gibbs free energy change (ΔGo) estimation indicated the spontaneous and non-spontaneous sorption process, while activation energy (Ea) values gave information on reaction rates and the mechanism of metal sorption (physical adsorption, aqueous diffusion, pore diffusion, ion exchange). Despite this bulk of information so far, there are no extended studies and results from wastewater treatment, where more than one metal species exist. Most biosorption processes are still in fundamental research and should be soon directed to pilot or industrial scale. The removal of co-existing toxic metals such as arsenic, chromium, cadmium, mercury, and lead with respect to certain cell biomass modifications should be of concern and must be the target in the near future. Researchers should conduct further studies on modeling of biosorption process, methods of biosorption, recovery of adsorbed metal ions, and regeneration of biomass. Investigations toward these directions need to be considered in depth. Recovery of toxic metals in a condensed form and reuse of regenerated biomass will be the integration key and the applicability of biosorption as an environmental friendly technique for wastewater treatment and therefore with high impact to human health.

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Bioremoval of Reactive Blue 220 by Gonium sp. biomass.

Transport of heavy metals by the kidney.

Composition of the saprophytic bacterial communities in freshwater systems contaminated by heavy metals.

Clostridia initiate heavy metal bioremoval in mixed sulfidogenic cultures.

Sorption of heavy metals in the biomass of alga Palmaria palmata.

Biosorption kinetics of heavy metals by leaf biomass of Jatropha curcas in single and multi-metal system.

Disorders of heavy metals.

Heavy Metals Biosorption from Aqueous Solution by Endophytic Drechslera hawaiiensis of Morus alba L. Derived from Heavy Metals Habitats.

Inhibition of drug metabolizing enzymes by heavy metals in vitro.

Earliest evidence of pollution by heavy metals in archaeological sites.

Phytochemicals Mediated Remediation of Neurotoxicity Induced by Heavy Metals.

Biomagnification of heavy metals by organisms in a marine microcosm.

Removal of heavy metals by hybrid electrocoagulation and microfiltration processes.

16S rDNA pyrosequencing analysis of bacterial community in heavy metals polluted soils.

Remobilization of toxic heavy metals adsorbed to bacterial wall-clay composites.

Facultative hyperaccumulation of heavy metals and metalloids.

Accumulation of heavy metals using Sorghum sp.

Chemical monitoring of exposure to heavy metals.

Contamination, toxicity and speciation of heavy metals in an industrialized urban river: Implications for the dispersal of heavy metals.

Heavy metals in the environment II: overview.

Comment on occupational heavy metals absorption.

Enhancing microalgal biomass productivity by engineering a microalgal-bacterial community.

Benthic bacterial biomass supported by streamwater dissolved organic matter.

Impact of hydrocarbons, PCBs and heavy metals on bacterial communities in Lerma River, Salamanca, Mexico: Investigation of hydrocarbon degradation potential.