Heavy metal ions such as Cd2+, Pb2+, Cu2+, Mg2+, and Hg2+ from industrial waste water constitute a major cause of pollution for ground water sources. These ions are toxic to man and aquatic life as well, and should be removed from wastewater before disposal. Various treatment technologies have been reported to remediate the potential toxic elements from aqueous media, such as adsorption, precipitation and coagulation. Most of these technologies are associated with some shortcomings, and challenges in terms of applicability, effectiveness and cost. However, adsorption techniques have the capability of effectively removing heavy metals at very low concentration (1–100 mg/L). Various adsorbents have been reported in the literature for this purpose, including, to a lesser extent, the use of hydrogel adsorbents for heavy metal removal in aqueous phase. Here, we provide an in-depth perspective on the design, application and efficiency of hydrogel systems as adsorbents.

NOMENCLATURE

     
  • C0

    initial dye concentration (mg dm−3)

  •  
  • Ce

    equilibrium sorbate (dye) concentration in solution (g dm−3)

  •  
  • Cs

    amount of the sorbed dye per dm−3 of the solution at the equilibrium (mg dm−3)

  •  
  • Ct

    dye concentration after certain sorption time t (mg dm−3)

  •  
  • K

    kinetic model rate constant (h−1)

  •  
  • k0

    Bangham parameter (g)

  •  
  • Kd

    distribution coefficient

  •  
  • KF

    Freundlich constant (mg g−1)1/n

  •  
  • kf

    pseudo-first order kinetic model rate constant (min−1)

  •  
  • kid

    diffusion rate constant (mg g−1 h−0.5)

  •  
  • KL

    Langmuir sorption coefficient (dm3 g−1)

  •  
  • Ks

    pseudo-second order kinetic model rate constant (min−1)

  •  
  • MAA

    methacrylic acid

  •  
  • MBA

    N,N0-methylenebisacrylamide

  •  
  • meq

    weight of equilibrium swollen hydrogel sample (g)

  •  
  • ms

    sorbent (xerogel) weight (g)

  •  
  • n

    Freundlich parameter

  •  
  • qe

    equilibrium sorption capacity (mg g−1)

  •  
  • qe,cal

    calculated value of maximum sorption capacity (mg g−1)

  •  
  • qe,exp

    experimental value of maximum sorption capacity (mg g−1)

  •  
  • qm

    maximum sorption capacity at complete monolayer coverage (mg g−1)

  •  
  • qt

    sorption capacity at time t (mg g−1)

  •  
  • R

    universal gas constant (8.314 J mol−1 K1)

  •  
  • R2

    linear correlation coefficient

  •  
  • RL

    separation factor

  •  
  • SDeq

    equilibrium swelling degree

  •  
  • DH

    change of enthalpy (kJ mol−1)

  •  
  • DS

    change of entropy (kJ mol−1 K−1)

  •  
  • AMPS/PVA

    2-Acrylamido-2-methyl-1-propane sulfonicacid (AMPS) and polyvinyl alcohol (PVA) copolymer hydrogel

  •  
  • PVA/AAc

    Polyvinyl alcohol/acrylic acid copolymer hydrogel

  •  
  • PMAA

    Poly(methacrylic acid) based hydrogel

  •  
  • PAA

    Poly acrylic acid (PAA) hydrogel beads

  •  
  • Poly(EGDMA–VIM)

    Poly(ethylene glycol dimethacrylate-n-vinyl imidazole)

INTRODUCTION

In the last two decades there has been a remarkable increase of heavy metal pollution of ground water due to industrialization. This has posed many serious environmental problems due to the toxicity of heavy metals to many life forms. Ingestion of cadmium, vanadium and lead above the tolerance levels have been linked to cancer (Storr et al. 2006; Thompson et al. 2009; He et al. 2014; Wang & Chen 2014), brain damage (Storr et al. 2006; He et al. 2014), kidney, DNA damage (Shechter et al. 2003; Kammerer et al. 2004; Facchini et al. 2006; Thompson et al. 2009; Gad & Pham 2014), blocking of protein and oxidation of lipids, which is a preliminary step in the development of cardiovascular disease (Willsky et al. 2001; Kammerer et al. 2004; Bishayee et al. 2010). Heavy metal ions have the tendency to form complexes with biological matter (Storr et al. 2006; Holder 2010; He et al. 2014). These elements, along with amino and fatty acids and vitamins, are required for normal biochemical processes such as respiration, biosynthesis and metabolism (Lin 2014; Raimundo et al. 2014). Environmental monitoring agencies have set permissible limits (12 μg/L) for heavy metal levels in drinking water due to their harmful effects. The efficient removal of these toxic metal ions is a very difficult task due to the high cost of treatment methods. In recent years, research interest has increased in terms of the production of low-cost alternatives.

Microbe-based technologies can provide an alternative to the conventional methods for removal of these metal ions, since they are important in biological systems and in the environment at regulated concentrations. Chemical precipitation, coagulation, solvent extraction, membrane separation, ion exchange and adsorption methods have also been used (Kumar et al. 2001; Akkaya & Ulusoy 2008; Chatterjee et al. 2010; Cao et al. 2011; Yetimoğlu et al. 2011; Kumar et al. 2012; Wan Ngah et al. 2012; Barakat et al. 2013; Kipp et al. 2013; Wan Ngah et al. 2013; Liu et al. 2014a; Liu et al. 2014b).

However, the common use of ion exchange and reverse osmosis is restricted by the high operating cost. As an alternative to chemical precipitation, membrane filtration or ion exchange and adsorption processes with a wide variety of adsorbents have been used, including hydrogels. The mechanism of biosorption process includes chemisorption, complexation, adsorption on surface, diffusion through pores and ion exchange. Conventional techniques have inherent limitations such as low efficiency, sensitive operating conditions, production of secondary sludge and high cost of disposal (Barakat 2011; Barakat et al. 2013). Adsorption of heavy metals by activated carbon is a powerful technology and has been applied mostly in treating domestic and industrial waste water. However, the high cost of activated carbon and loss of the adsorbent during the regeneration process restricts its application. Since the 1990s, the adsorption of heavy metal ions by low-cost renewable organic materials has gained popularity (Wan Ngah & Hanafiah 2008; Zhang et al. 2014). The utilization of sea weeds, moulds, yeasts, and other dead microbial biomass and agricultural waste materials for removal of heavy metals has been explored (Ng et al. 2013; Sun et al. 2013). Recently, attention has been diverted towards biomaterial, which comes mostly as by-products of large-scale industrial operations. The major advantages of biosorption over conventional treatment methods for copper, chromium, cadmium, and nickel at the second oxidation state include: low cost, high efficiency, minimization of chemical or biological sludge, no additional nutrient requirement, regeneration of biosorbents, and possibility of metal recovery (Demirbas 2008; Doelsch et al. 2010). Agricultural materials, particularly those containing cellulose, show potential biosorption capacity for Cd2+, Pb2+, Cu2+, and Mg2+). The basic components of the agricultural waste material biomass include hemicellulose, lignin, extractives, lipids, proteins, simple sugars, water, hydrocarbons, and starch containing a variety of functional groups that facilitate metal complexation, which helps in the sequestering of Cd2+, Pb2+, Cu2+, and Ni2+ (Namasivayam & Sangeetha 2006; Achiba et al. 2009; Smith 2009; Ng et al. 2013). Most agricultural waste materials are environmentally friendly due to their unique chemical compositions, great abundance, and low cost, and they are an efficient option for heavy metal remediation.

MECHANISM OF BIOSORPTION

The removal of metal ions from aqueous streams using agricultural materials is based upon metal biosorption (Zheng et al. 2010). The process of biosorption involves a solid phase (sorbent) and a liquid phase (solvent) containing the dissolved species that will be adsorbed. Due to high affinity of the sorbent for the metal ion species, the latter is attracted and bound by a complex process which is affected by several mechanisms involving chemisorption, complexation, adsorption on surface and pores, ion exchange, chelation, adsorption by physical forces, and entrapment in inter- and intra-fibrillar capillaries and spaces of the structural polysaccharide network as a result of the concentration gradient and diffusion through cell wall and membrane (Feng et al. 2000). Functional groups present in biomass molecules, such as acetamido groups, carbonyl, phenolic, structural polysaccharides, amido, amino, sulphydryl carboxyl groups, alcohols and esters, have the affinity for cadmium, copper and lead detection within a limit range of 150–350 mg/L (Wang & Chen 2014). Some biosorbents are non-selective and bind to a wide range of heavy metals with no specific priority, whereas others are specific for certain types of metals depending on their chemical composition. The complexation of various functional groups with heavy metal ions (Cd2+, Pb2+, Cu2+, Mg2+ and Hg2+) during the biosorption process has been reported by different research workers using spectroscopic techniques (Chen et al. 2013; Wang & Chen 2013). The processes of biosorption can be optimized to enhance the regeneration of the biosorbents and recovery of heavy metal ions. Most of the optimizations are performed in the batch process; this allows the design of continuous flow systems for industrial remediation applications (Figure 1).
Figure 1

Two-stage biosorption diagram.

Figure 1

Two-stage biosorption diagram.

Hydrogels as sorbents

Hydrogels are three-dimensional networks of crosslinked polymers which are able to swell rapidly and retain large volumes of water in their swollen structure (Figure 2). They are usually made of hydrophilic polymer molecules which are crosslinked by either chemical bonding or other cohesion forces such as ionic interaction, hydrogen bonding or hydrophobic interaction (Holback et al. 2011; Buenger et al. 2012; Abeer et al. 2014; Liu et al. 2014a; Pourbeyram   & Mohammadi 2014).
Figure 2

Hydrogel adsorption mechanism.

Figure 2

Hydrogel adsorption mechanism.

They are also used in the preparation of molecular recognition interfaces for biosensors (Holback et al. 2011; Buenger et al. 2012; Oun et al. 2014). Various hydrogels have been employed in biosynthesis processes and adsorbents such as cellulose graft acrylic acid (C-g-AA), chitosan hydrogel with 2,5-dimercapto-1,3,4-thiodiazole (CTS-DMTD), PVA-hydrogel biomass of Penicillium cyclopium and starch graft acrylic acid/montmorillonite (S-g-AA/MMT) (Jamnongkan et al. 2014).

PVA-hydrogel synthesis was achieved by precipitation of an aqueous solution of PVA out of absolute ethanol (Al-qudah et al. 2014). Glutaraldehyde was used as crosslinking agent to PVA polymer and HCl as catalyst. The hydrogel was further immobilized with P. cyclopium by dispersing a pre-weighed amount of wet biomass in the PVA aqueous solution prior to the precipitation. Hydrogels' adsorptive capacities and absorption kinetics are influenced by many factors, like metal concentration (Kaksonen et al. 2003), pH of the solution (Cao et al. 2011), composition of the absorbent (Chen et al. 2000; Chen et al. 2013; Bekin et al. 2014), and contact time (Chatterjee et al. 2010). pH is an important parameter that affects hydrogel performance by influencing its swelling and metal ion chelation on chelating adsorbents. For selective adsorption, besides the use of a specific ligand-modified sorbent, selectivity could be achieved by adjusting the pH to different values, and maximum adsorption is achieved at pH range 4–6 (Hua et al. 2012; Dragan 2014). pH control is the most important parameter for the selective adsorption of metal ions. pH 5.0 was found to be the optimal condition for Cd(II) and Pb(II) in controlled laboratory work. The sorption of Cd(II) and Pb(II) ions by hydrogel was found to be minimal at pH 2. The minimum adsorption observed at low pH was due to the higher mobility of H+ ions present, favoring the preferential adsorption of hydrogen ions compared with metal ions (Cd2+, Pb2+, Cu2+, and Mg2+). At lower pH values, the surface of the adsorbent is surrounded by hydronium ions (H+), thereby preventing the metal ions from approaching the binding sites of the sorbent. This means that at higher H+ concentration, the biosorbent surface becomes more positively charged, such that the attraction between biomass and metal cations is reduced. In contrast, as the pH increases, more negatively charged surface becomes available, thus facilitating greater metal removal. It is commonly agreed that the sorption of metal cations increases with increasing pH as the metal ionic species become less stable in the solution.

Effect of adsorbate solution pH

The pH of the metal ions strongly affects the adsorption properties of hydrogels, as discussed (Akkaya & Ulusoy 2008; Cao et al. 2011). At pH > 6, precipitation of hydroxides may occur simultaneously, depending on the metal and its oxidation state, and may not lead to accurate interpretation of adsorption. However at low pH ≤ 3 condition, the main effective adsorption sites of the hydrogel, namely, the alcoholic and carboxyl groups, are both easily protonated, leading to the reduction of the adsorptive activity. At higher pH conditions, the protonated functional groups may be deprotonated, resulting in higher adsorption activity (Al-qudah et al. 2014)

Effect of contact time and adsorption kinetics

The time for treatment is an important factor in metal uptake, and thus, the effect of immersion time on the metal uptake of different metal ions was investigated. It could be observed that the increase in immersion duration is accompanied by an increase in metal ion adsorption, and this reaches its maximum value after 180 min of soaking, and then levels out (Jamnongkan et al. 2014). The results of much research revealed that at the initial immersion time the metal ion adsorption is fast, and it becomes slower near the equilibrium. Such behavior occurs due to the fact that during the initial stage, a large number of vacant active sites were available for adsorption; after that, repulsion occurred between the adsorbate molecules on the adsorbent surface, which slowed down the adsorption process (Al-qudah et al. 2014). Therefore, it is imperative to consider the time positively in future research and monitor the adsorption during timed intervals in order to maximize the adsorption and detection of a specific metal.

Effect of initial concentration and adsorption isotherms

Metal ion concentration has an effect on the adsorption capacity. It could be observed that as the initial concentration increased, the adsorption capacities also increased, but the rate of increase became slow after the concentration reached 150 mg/L for Zn2+, Co2+ and Mn2+ (Lazaridis et al. 2004; Al-qudah et al. 2014). This indicates that there were few empty adsorption sites on the adsorbents and suggests that the adsorption almost reached equilibrium. The initial concentration provided the driving force needed to overcome the resistance due to the mass transfer of metal ions between adsorbed and adsorbate. Therefore, if the initial concentration is high, the driving force will also be high; consequently, the adsorption capacity will be high. The adsorption capacities of hydrogels are based on adsorption isotherm and the kinetics of adsorption and typically modeled as first and second order kinetic models.

For this study, the Langmuir equation is a fairly good fit to the adsorption isotherms of Pb2+ and Cd2+ ions on the hydrogels. The maximum adsorption capacity found for Pb2+ and Cd2+ ions by using the Langmuir equation was in milligrams per gram (El-Sayed & Mostafa 2014). Therefore, more research should be conducted on the same hydrogel to improve selectivity and sensitivity and enhance the detection of these metal ions at micrograms per litre if not nanograms per litre. Conversely, the kinetics of the adsorption data was calculated using kinetic models to understand the dynamic of the adsorption process in terms of the order and rate constant of Pb(II) into hydrogel beads. These models were pseudo-first order and pseudo-second order models (Féris et al. 2004; Chen et al. 2009; Cheng et al. 2011; Dragan 2014; El-Sayed & Mostafa 2014). The adsorption model predicts the rate at which adsorption takes place for a given system, and it is probably the most important factor in adsorption system design, with adsorbate residence time and the reactor dimensions controlled by the system's kinetics. The sorption isotherms represent the relationship between the amount adsorbed by a unit weight of solid sorbent and the amount of solute remaining in the solution at equilibrium (Féris et al. 2004). Langmuir and Freundlich isotherm models are frequently used for describing short-term and mono-component adsorption of metal ions. The reaction orders based on the capacity of the adsorbents have also been studied, such as Lagergren's first-order equation, the Redlich Peterson model and the Brunauer, Emmett and Teller (BET) model. However, Langmuir and Freundlich isotherm models have been shown to be suitable for describing short-term and mono-component adsorption of metal ions by different biosorbents. The adsorption kinetic data were described by the Lagergren pseudo-first order model, which is the earliest known equation describing the adsorption rate based on the adsorption capacity. The adsorption isotherm data were evaluated by means of the Langmuir and Freundlich adsorption models. The two models are expressed by the following equations: 
formula
1
 
formula
2
In the above equations, qm (mg/g) is representative of monolayer maximum uptake of metal ions, and b (L/mg) is the Langmuir adsorption constant and is related to the free energy of adsorption. KF (mg/g) and n are the Freundlich adsorption constants indicative of the adsorption extent and adsorption intensity, respectively. Based on these equations, the slope and intercepts of Ce/qe versus Ce are used to determine qm and b, and in the same way KF and n can be obtained from the plot of (ln qe) versus (ln Ce) (Demirbas 2008; Doelsch et al. 2010).
Selected kinetics parameters for metal adsorption (cadmium, lead and copper) by common adsorbent materials have been extracted for comparison (Table 1). The performances of the hydrogel adsorbents have been extracted to highlight the sorption parameters (Figure 3). Alginate beads and chitosan nanofibrils showed high adsorption capacity for Cd, Pd and Cu at pH 5, respectively (Table 1). Maximum adsorption was observed due to the fact that at that pH the biomass becomes preferentially protonated and releases the reduced metal cations, which adsorb onto the alginate beads, resulting in improved metal removal. PAA hydrogels and Poly(EGDMA–VIM) hydrogel showed very poor adsorptive capacity (Table 2). The mobility of H+ ions present favored the preferential adsorption of hydrogen ions compared with metal ions, and the surface of the adsorbent is surrounded by hydronium ions (H+), thereby preventing the metal ions from approaching the binding sites of the sorbent and resulting in poor adsorption (Figure 3). Alginate beads showed the highest sorption capacity for cadmium and lead (182 and 165 mg/g, respectively). Chitosan indicated the second highest sorption for cadmium (140 mg/g), lowest for lead (61 mg/g) and highest for copper (169 mg/g), whereas PAA hydrogel adsorbed only lead with a maximum sorption of 113 mg/g, and Poly(EGDMA–VIM) hydrogel displayed significant adsorption of cadmium (71 mg/g) and lead (118 mg/g). Based on the information provided (Figure 3), chitosan performed as the best adsorbent based on its sensitivity and selectivity toward a wide range of metal ions (Cd, Pd and Cu) compared with other adsorbents, in particular PAA hydrogel, which was only capable of detecting lead.
Table 1

Coefficient of pseudo-first and second order kinetics models

  Pseudo-first order kinetics
 
Pseudo- second order kinetics
 
Adsorbent Metal ions Adsorption capacity (mg/g) Kf(l/g) qe R2 Ks KF R2 References 
Alginate beads Cd2+ 182 0.063 – 0.898 8.07 2.97 0.992 Mandal & Ray (2013)  
Pb2+ 165 0.069 – 0.910 6.55 3.65 0.994 
AMPS/PVAc Copolymer hydrogel Ni2+ 230 1.064 – 0.995 0.013 4.94 0.986 Al-qudah et al. (2014)  
Mn2+ 160 0.719 – 0.996 0.011 4.99 0.989 
Chitosan nanofibril Cd2+ 140 0.400 – 0.990 0.008 6.14 0.994 Liu et al. (2014a)  
Cu3+ 169 0.021 86 0.970 0.0008 0.41 0.999 
Pb2+ 61 0.017 114 0.986 0.0001 0.44 0.995 
PVA/AAc hydrogel Zn2+ 388 0.017 415 0.942 1.76 2.40 0.991 Al-qudah et al. (2014)  
Co2+ 245 0.015 278 0.960 5.17 2.03 0.998 
Mn2+ 152 0.03 145 0.948 8.11 1.42 0.997 
PAA hydrogel Pb2+ 113 0.23 119 1.000 51.85 6.32 0.857 Akkaya & Ulusoy (2008)  
PVA Cu2+ 14 0.049 – 0.99 4.298 0.43 0.95 Jamnongkan et al. (2014)  
Poly(EGDMA–VIM) hydrogel Cd2+ 71 0.106  0.99 24 5.25 0.93 Vogel et al. (2014)  
Pb2+ 118 0.098  0.99 38 5.19 0.96 
Hg2+ 172 0.070  0.99 43 4.17 0.90 
  Pseudo-first order kinetics
 
Pseudo- second order kinetics
 
Adsorbent Metal ions Adsorption capacity (mg/g) Kf(l/g) qe R2 Ks KF R2 References 
Alginate beads Cd2+ 182 0.063 – 0.898 8.07 2.97 0.992 Mandal & Ray (2013)  
Pb2+ 165 0.069 – 0.910 6.55 3.65 0.994 
AMPS/PVAc Copolymer hydrogel Ni2+ 230 1.064 – 0.995 0.013 4.94 0.986 Al-qudah et al. (2014)  
Mn2+ 160 0.719 – 0.996 0.011 4.99 0.989 
Chitosan nanofibril Cd2+ 140 0.400 – 0.990 0.008 6.14 0.994 Liu et al. (2014a)  
Cu3+ 169 0.021 86 0.970 0.0008 0.41 0.999 
Pb2+ 61 0.017 114 0.986 0.0001 0.44 0.995 
PVA/AAc hydrogel Zn2+ 388 0.017 415 0.942 1.76 2.40 0.991 Al-qudah et al. (2014)  
Co2+ 245 0.015 278 0.960 5.17 2.03 0.998 
Mn2+ 152 0.03 145 0.948 8.11 1.42 0.997 
PAA hydrogel Pb2+ 113 0.23 119 1.000 51.85 6.32 0.857 Akkaya & Ulusoy (2008)  
PVA Cu2+ 14 0.049 – 0.99 4.298 0.43 0.95 Jamnongkan et al. (2014)  
Poly(EGDMA–VIM) hydrogel Cd2+ 71 0.106  0.99 24 5.25 0.93 Vogel et al. (2014)  
Pb2+ 118 0.098  0.99 38 5.19 0.96 
Hg2+ 172 0.070  0.99 43 4.17 0.90 
Table 2

Summary table of metals ions concentrations dependence based on pH, adsorbent time and concentration

  Pseudo-first and second order kinetics
 
Adsorbent Metal ions Metal concentration pH Kinetic model Adsorption capacity (mg/g) References 
PVA/AAc Cu2+ 300 mg/L 4.5 KS 13 Jamnongkan et al. (2014)  
Poly(EGDMA–VIM) hydrogel Cd2+ 300 mg/L 3–5 KS 69 Panic et al. (2013)  
Pb2+ 300 mg/L 3–5 KS 112 Panic et al. (2013)  
Hg2+ 300 mg/L 3–5 KS 162 Panic et al. (2013)  
Alginate beads Cd2+ 200–300 mg/L 6.5 KS 182 Mandal & Ray (2013)  
Pd2+ 100 mg/L 6.0 KS 165 
AMPS/PVAc Copolymer hydrogel Ni2+ 200 mg/L 6.5 KS 230 Al-qudah et al. (2014)  
Mn2+ 350 mg/L 5.5 KS 160 
PAA hydrogel Pb2+ 150 mg/L 6.5 KS 113 Akkaya & Ulusoy (2008)  
Chitosan nanofibril Cd2+ 300 mg/L 6.0 KS 140 Liu et al. (2014a)  
Cu3+ 250 mg/L 5.5 KS 169 
Pb2+ 200 mg/L 6.7 KS 61 
  Pseudo-first and second order kinetics
 
Adsorbent Metal ions Metal concentration pH Kinetic model Adsorption capacity (mg/g) References 
PVA/AAc Cu2+ 300 mg/L 4.5 KS 13 Jamnongkan et al. (2014)  
Poly(EGDMA–VIM) hydrogel Cd2+ 300 mg/L 3–5 KS 69 Panic et al. (2013)  
Pb2+ 300 mg/L 3–5 KS 112 Panic et al. (2013)  
Hg2+ 300 mg/L 3–5 KS 162 Panic et al. (2013)  
Alginate beads Cd2+ 200–300 mg/L 6.5 KS 182 Mandal & Ray (2013)  
Pd2+ 100 mg/L 6.0 KS 165 
AMPS/PVAc Copolymer hydrogel Ni2+ 200 mg/L 6.5 KS 230 Al-qudah et al. (2014)  
Mn2+ 350 mg/L 5.5 KS 160 
PAA hydrogel Pb2+ 150 mg/L 6.5 KS 113 Akkaya & Ulusoy (2008)  
Chitosan nanofibril Cd2+ 300 mg/L 6.0 KS 140 Liu et al. (2014a)  
Cu3+ 250 mg/L 5.5 KS 169 
Pb2+ 200 mg/L 6.7 KS 61 
Figure 3

Comparison of kinetics parameters (qm and qe) of different metal ions and adsorbents.

Figure 3

Comparison of kinetics parameters (qm and qe) of different metal ions and adsorbents.

The adsorption capacity of hydrogels is based on isotherms and the kinetics of adsorption, which predict the rate at which adsorption takes place for a given system. The data derived from comparing the different hydrogels showed that their reactions were mostly pseudo-first order kinetics. Chitosan nanofibril, Poly(EGDMA–VIM) hydrogel and alginate beads exhibited high pseudo-first order rate constant for cadmium and lead, respectively, whereas PAA hydrogel only showed a high value for lead (Figure 4). In contrast, chitosan and alginate beads showed the highest rate of adsorption for all four metals evaluated.
Figure 4

Comparison of kinetics parameters (Kf) of different metal ions and adsorbents.

Figure 4

Comparison of kinetics parameters (Kf) of different metal ions and adsorbents.

ELECTROCHEMICAL DETECTION OF METALS

Today, electrochemical sensors are tightly integrated and hyphenated with sampling, fluidic handling, separation and other detection principles. Unfortunately, this review does not have sufficient room to cover these topics, and the reader should keep in mind that the topic of electrochemical sensors is relatively mature and has found its way into commercial products and advanced integrated sensing systems. A steady effort has been made on the development of efficient and easy-use electrochemical sensors. Hydrogel sensors for heavy metals, with rapid and highly sensitive detection capabilities, are in great demand in many areas of science. Developing hydrogel sensors for detecting lower concentrations of heavy metal ions becomes very significant due to the fact that they hold special advantages in drug delivery based on their loading capacity and controlled drug release. Electrochemical devices with accuracy and sensitivity have already been developed for certain applications. Although still at the basic research stage, many new applications are yet to be discovered. The detection of low concentration of toxic heavy metal ions in environment water is essential because of its lethal effects on the environment and living organisms. To date, only a few researchers have reported on hydrogel sensors for detection of heavy metals, including: hydrogel sensor for metal oxide (Chen et al. 2009), PVA hydrogel sensor for heavy metal cations, P(MBTVBC-co-VIM)-coated QCM (Cao et al. 2011), and P(NIPAM-co-BCAm) hydrogels (Chen et al. 2013). However most of them could not detect heavy metals at lower levels (micrograms and nanograms) except PVA hydrogel, which detected nickel at a range of 0.1–0.214 μM.

DISCUSSION AND RECOMMENDATION

The World Health Organization and Environmental Protection Agency (EPA) have established a maximum concentration for toxic heavy metals and precious metals in drinking water. A maximum of 5–20 μg/L is permissible for toxic heavy metals (Ar, Cr, Cu and Pb) as well as 0.1 μg/L for Hg and 500 μg/L for precious metals (Zn, Mn) in their secondary oxidation states (Mohod & Dhote 2013). The use of hydrogels in heavy metal remediation showed better performance than precipitation methods, activated carbon, and agricultural waste, and offers promising application prospects. To date, research has focused mainly on specific metals, including copper, lead, silver, cadmium, nickel, chromium, gold and mercury. Other transition metals with high toxicity or transition metals which are known disease markers have not been as widely addressed. Vanadium and selenium have been identified as carcinogenic agents that disrupt cellular metabolic processes at high dosage (200 μg/L) in drinking water. Evidence from literature indicates that exposure to selenium could induce neuro-mental effects on the development of fetuses, infants and children as well as development of diabetes type II (Crans et al. 2011; Gad & Pham 2014). These metals block the reactivity of essential functional groups of biomolecules and disrupt the integrity of bio-membranes. There is also a need to investigate the simultaneous removal of many co-existing pollutants in waste water. It is preferable to develop a multipurpose adsorbent which can remove different kinds of pollutants at micro and nano scale. To achieve these aims, new materials and methods are required that utilize our understanding of parameters which affect adsorption of heavy metal ions, including pH, analyte concentration, contact time and adsorbent functional group. Hydrogels are a promising group of materials due to their compatibility with the aqueous phase, and future work should involve functionalization of hydrogel materials for selective and sensitive metal remediation as well as sensitive analytical methods for ultra-low concentration evaluation. Electrochemical methods for metal quantification and speciation have emerged as a promising tool for evaluation of a wide range of metal ion species. The success of electrochemical detection of nickel, lead, copper, mercury and cadmium has been established using chemical sensors (hydrogel sensors) with results possible in the micrograms per milliliter range. Hence, the combination of electrochemical methods with the removal efficiency of stimuli-responsive hydrogel materials could produce highly efficient water treatment solutions, in particular for metal remediation.

CONCLUSION

A wide range of treatment technologies have been developed for heavy metal removal from wastewater. Agricultural waste and hydrogels are relatively new processes that have shown a significant contribution to the removal of these contaminants from aqueous effluents. However, it is evident from the literature that agricultural waste, activated carbon and hydrogel adsorbents do not adequately remove heavy metals at micro and nano scale. Even though hydrogels have shown improved adsorption efficiency, they still suffer from a number of limitations, such as low tensile strength, which limit their use in load-bearing applications and result in the premature dissolution or flow away from the hydrogel for a targeted purpose, and hence low sorption capacity. Therefore, it is essential to identify new hydrogel composites with the appropriate physical and chemical properties capable of comprehensive metal species adsorption from aqueous media. The advantage offered by electrochemical control of hydrogel sorption shows great promise with respect to adsorption of a wide range of transition metal species at very low concentration.

ACKNOWLEDGEMENTS

The authors of this review would like to thank National Research Foundation (NRF), and Water Research Commission (WRC) South Africa, for financial support.

REFERENCES

REFERENCES
Abeer
M. M.
Amin
M. C. I. M.
Lazim
A. M.
Pandey
M.
Martin
C.
2014
Synthesis of a novel acrylated abietic acid-g-bacterial cellulose hydrogel by gamma irradiation
.
Carbohydrate Polymers
110
,
505
512
.
Achiba
W. B.
Gabteni
N.
Lakhdar
A.
Laing
G. D.
Verloo
M.
Jedidi
N.
Gallali
T.
2009
Effects of 5-year application of municipal solid waste compost on the distribution and mobility of heavy metals in a Tunisian calcareous soil
.
Agriculture, Ecosystems & Environment
130
(
3–4
),
156
163
.
Al-qudah
Y. H. F.
Mahmoud
G. A.
Abdel Khalek
M. A.
2014
Radiation crosslinked poly (vinyl alcohol)/acrylic acid copolymer for removal of heavy metal ions from aqueous solutions
.
Journal of Radiation Research and Applied Sciences
7
(
2
),
135
145
.
Barakat
M. A.
2011
New trends in removing heavy metals from industrial wastewater
.
Arabian Journal of Chemistry
4
(
4
),
361
377
.
Barakat
M. A.
Ramadan
M. H.
Alghamdi
M. A.
Algarny
S. S.
Woodcock
H. L.
Kuhn
J. N.
2013
Remediation of Cu(II), Ni(II), and Cr(III) ions from simulated wastewater by dendrimer/titania composites
.
Journal of Environmental Management
117
,
50
57
.
Bishayee
A.
Waghray
A.
Patel
M. A.
Chatterjee
M.
2010
Vanadium in the detection, prevention and treatment of cancer: the in vivo evidence
.
Cancer Letters
294
(
1
),
1
12
.
Buenger
D.
Topuz
F.
Groll
J.
2012
Hydrogels in sensing applications
.
Progress in Polymer Science
37
(
12
),
1678
1719
.
Cao
Z.
Guo
J.
Fan
X.
Xu
J.
Fan
Z.
Du
B.
2011
Detection of heavy metal ions in aqueous solution by P(MBTVBC-co-VIM)-coated QCM sensor
.
Sensors and Actuators B: Chemical
157
(
1
),
34
41
.
Chatterjee
S.
Chatterjee
T.
Woo
S. H.
2010
A new type of chitosan hydrogel sorbent generated by anionic surfactant gelation
.
Bioresource Technology
101
(
11
),
3853
3858
.
Chen
B.-Y.
Utgikar
V. P.
Harmon
S. M.
Tabak
H. H.
Bishop
D. F.
Govind
R.
2000
Studies on biosorption of zinc(II) and copper(II) on Desulfovibrio desulfuricans
.
International Biodeterioration & Biodegradation
46
(
1
),
11
18
.
Chen
M.-C.
Tsai
H.-W.
Liu
C.-T.
Peng
S.-F.
Lai
W.-Y.
Chen
S.-J.
Chang
Y.
Sung
H.-W.
2009
A nanoscale drug-entrapment strategy for hydrogel-based systems for the delivery of poorly soluble drugs
.
Biomaterials
30
(
11
),
2102
2111
.
Cheng
Y.
Sun
X.
Liao
X.
Shi
B.
2011
Adsorptive recovery of Uranium from nuclear fuel industrial wastewater by titanium loaded collagen fiber
.
Chinese Journal of Chemical Engineering
19
(
4
),
592
597
.
Demirbas
A.
2008
Heavy metal adsorption onto agro-based waste materials: a review
.
Journal of Hazardous Materials
157
(
2–3
),
220
229
.
Doelsch
E.
Masion
A.
Moussard
G.
Chevassus-Rosset
C.
Wojciechowicz
O.
2010
Impact of pig slurry and green waste compost application on heavy metal exchangeable fractions in tropical soils
.
Geoderma
155
(
3–4
),
390
400
.
Facchini
D. M.
Yuen
V. G.
Battell
M. L.
McNeill
J. H.
Grynpas
M. D.
2006
The effects of vanadium treatment on bone in diabetic and non-diabetic rats
.
Bone
38
(
3
),
368
377
.
Féris
L. A.
De León
A. T.
Santander
M.
Rubio
J.
2004
Advances in the adsorptive particulate flotation process
.
International Journal of Mineral Processing
74
(
1–4
),
101
106
.
Gad
S. C.
Pham
T.
2014
Vanadium
. In:
Wexler
P.
(ed.).
Encyclopedia of Toxicology
. 3rd edn.
Academic Press
, pp.
909
911
.
Holback
H.
Yeo
Y.
Park
K.
2011
1 - Hydrogel swelling behavior and its biomedical applications
. In:
Rimmer
S.
(ed.).
Biomedical Hydrogels
.
Woodhead Publishing, Cambridge, UK
, pp.
3
24
.
Holder
A. A.
2010
Inorganic pharmaceuticals
.
Annual Reports Section A (Inorganic Chemistry)
106
,
504
525
.
Hua
M.
Zhang
S.
Pan
B.
Zhang
W.
Lv
L.
Zhang
Q.
2012
Heavy metal removal from water/wastewater by nanosized metal oxides: a review
.
Journal of Hazardous Materials
211–212
,
317
331
.
Jamnongkan
T.
Wattanakornsiri
A.
Wachirawongsakorn
P.
Kaewpirom
S.
2014
Effects of crosslinking degree of poly(vinyl alcohol) hydrogel in aqueous solution: kinetics and mechanism of copper(II) adsorption
.
Polymer Bulletin
71
(
5
),
1081
1100
.
Kaksonen
A. H.
Riekkola-Vanhanen
M. L.
Puhakka
J. A.
2003
Optimization of metal sulphide precipitation in fluidized-bed treatment of acidic wastewater
.
Water Research
37
(
2
),
255
266
.
Kammerer
M.
Mastain
O.
Le Dréan-Quenech'du
S.
Pouliquen
H.
Larhantec
M.
2004
Liver and kidney concentrations of vanadium in oiled seabirds after the Erika wreck
.
Science of The Total Environment
333
(
1–3
),
295
301
.
Kipp
A. P.
Frombach
J.
Deubel
S.
Brigelius-Flohé
R.
2013
Chapter five – selenoprotein W as biomarker for the efficacy of selenium compounds to act as source for selenoprotein biosynthesis
. In:
Enrique
C.
Lester
P.
(eds).
Methods in Enzymology
.
Academic Press, Rockville, USA
, pp.
87
112
.
Kumar Sani
R.
Geesey
G.
Peyton
B. M.
2001
Assessment of lead toxicity to desulfovibrio desulfuricans G20: influence of components of lactate C medium
.
Advances in Environmental Research
5
(
3
),
269
276
.
Lazaridis
N. K.
Peleka
E. N.
Karapantsios
T. D.
Matis
K. A.
2004
Copper removal from effluents by various separation techniques
.
Hydrometallurgy
74
(
1–2
),
149
156
.
Mohod
C. V.
Dhote
J.
2013
Review of heavy metals in drinking water and their effect on human health
.
International Journal of Innovative Research in Science
2
(
7
),
2992
2996
.
Panic
V. V.
Madzarevic
Z. P.
Volkov-Husovic
T.
Velickovic
S. J.
2013
Poly(methacrylic acid) based hydrogels as sorbents for removal of cationic dye Basic Yellow 28: kinetics, equilibrium study and image analysis
.
Chemical Engineering Journal
217
,
192
204
.
Shechter
Y.
Goldwaser
I.
Mironchik
M.
Fridkin
M.
Gefel
D.
2003
Historic perspective and recent developments on the insulin-like actions of vanadium; toward developing vanadium-based drugs for diabetes
.
Coordination Chemistry Reviews
237
(
1–2
),
3
11
.
Storr
T.
Thompson
K. H.
Orvig
C.
2006
Design of targeting ligands in medicinal inorganic chemistry
.
Chemical Society Reviews
35
(
6
),
534
544
.
Thompson
K. H.
Lichter
J.
LeBel
C.
Scaife
M. C.
McNeill
J. H.
Orvig
C.
2009
Vanadium treatment of type 2 diabetes: a view to the future
.
Journal of Inorganic Biochemistry
103
(
4
),
554
558
.
Vogel
K. R.
Arning
E.
Wasek
B. L.
McPherson
S.
Bottiglieri
T.
Gibson
K. M.
2014
Brain-blood amino acid correlates following protein restriction in murine maple syrup urine disease
.
Orphanet Journal of Rare Diseases
9
(
January
),
73
.
doi:10.1186/1750-1172-9-73
.
Wan Ngah
W. S.
Teong
L. C.
Toh
R. H.
Hanafiah
M. A. K. M.
2013
Comparative study on adsorption and desorption of Cu(II) ions by three types of chitosan–zeolite composites
.
Chemical Engineering Journal
223
,
231
238
.
Willsky
G. R.
Goldfine
A. B.
Kostyniak
P. J.
McNeill
J. H.
Yang
L. Q.
Khan
H. R.
Crans
D. C.
2001
Effect of vanadium(IV) compounds in the treatment of diabetes: in vivo and in vitro studies with vanadyl sulfate and bis(maltolato)oxovandium(IV)
.
Journal of Inorganic Biochemistry
85
(
1
),
33
42
.
Yetimoğlu
E. K.
Fırlak
M.
Kahraman
M. V.
Deniz
S.
2011
Removal of Pb2+ and Cd2+ ions from aqueous solutions using guanidine modified hydrogels
.
Polymers for Advanced Technologies
22
(
5
),
612
619
.