Competitive biosorption of lead, cadmium, copper, and arsenic ions using algae
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- Sulaymon, A.H., Mohammed, A.A. & Al-Musawi, T.J. Environ Sci Pollut Res (2013) 20: 3011. doi:10.1007/s11356-012-1208-2
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The present study aims to evaluate the competitive biosorption of lead, cadmium, copper, and arsenic ions by using native algae. A series of experiments were carried out in a batch reactor to obtain equilibrium data for adsorption of single, binary, ternary, and quaternary metal solutions. The biosorption of these metals is based on ion exchange mechanism accompanied by the release of light metals such as calcium, magnesium, and sodium. Experimental parameters such as pH, initial metal concentrations, and temperature were studied. The optimum pH found for removal were 5 for Cd2+ and As3+ and 3 and 4 for Pb2+ and Cu2+, respectively. Fourier transformation infrared spectroscopy analysis was used to find the effects of functional groups of algae in biosorption process. The results showed that Pb2+ made a greater change in the functional groups of algal biomass due to high affinity to this metal. An ion exchange model was found suitable for describing the biosorption process. The affinity constants sequence calculated for single system was KPb > KCu > KCd > KAs; these values reduced in binary, ternary, and quaternary systems. In addition, the experimental data showed that the biosorption of the four metals fitted well the pseudo-second-order kinetics model.
KeywordsCompetitive biosorptionAlgaeIon exchange modelAffinity constantKinetics
Concentration of metal at any time (in milligrams per liter)
Equilibrium concentration of metal ion (in milligrams per liter)
Initial concentration of metal ion (in milligrams per liter)
Light metal normality (in milliequivalents per liter)
Heavy metal normality (in milliequivalents per liter)
Total normality of solution (in milliequivalents per liter)
Adsorption rate constant of the pseudo-first-order equation (1/min)
Adsorption rate constant of the pseudo-second-order equation (in kilograms per gram per minute)
Total number of ion exchangeable binding sites (in milliequivalents per gram)
Adsorption amount of metal ions (in milligrams per kilogram)
Light metal concentration in the solid phase (in milliequivalents per gram)
Heavy metal concentration in the solid phase (in milliequivalents per gram)
Amount of metal ions adsorbed (in milligrams per kilogram)
Time (in minute)
Volume of solution (in liter)
Weight of adsorbent (in gram)
Light metal equivalent fraction in the liquid
Heavy metal equivalent fraction in the liquid
Light metal equivalent fraction in the solid
Heavy metal equivalent fraction in the solid
Heavy metal pollution has become a major issue in many countries because their existence in drinking waters and wastewaters often exceed the permissible standards (Ahmet and Mustafa 2008). Metal ions in the environment are bio-magnified in the food chain and are accumulated in tissues; therefore, toxic effects of heavy metals in particular are especially found in animals of higher trophic levels and especially in human. Heavy metals discharged into the aquatic environment will be bound predominantly to suspended materials and finally accumulate in the sediment. The most direct potential routes of human exposure to such discharged metals into a river would be any consumption of water or fish or other food derived from the river.
The metals hazardous to human include lead, cadmium, mercury, arsenic, copper, zinc, and chromium. Arsenic and cadmium can cause cancer. Mercury can cause mutations and genetic damage, while copper, lead, and chromium can cause brain and bone damage. Heavy metals are often derived from industries such as electroplating and battery factories, metal finishing, and chemical manufacturing (Apiratikul et al. 2004).
The removal and recovery of heavy metal ions from wastewater involve many techniques such as ion exchange, evaporation, precipitation, membrane separation, etc. However, these common techniques are too expensive to treat low levels of heavy metals in wastewater. In addition, they have some disadvantages such as requiring a large area of lands, a sludge dewatering facility, skillful operators, and multiple basin configurations (Zhou et al. 1999). For example, the most serious limitation of ion exchange is the cost of resin. The price of resin is ranging from US$30 to 60/kg.
Biosorption is a process which utilizes inexpensive dead biomass to sequester toxic heavy metals (Kratochvil and Volesky 1998). Biosorption is proven to be quite effective at removing metal ions from contaminated solutions in a low-cost and environment-friendly manner. Herrera et al. (2004) found that an approximate cost of biosorption 10 g of Ag(II) onto cellulose phosphate was about US$2. Additionally, low-cost biosorption process using algae as adsorbent has lately been introduced as an alternative (unit cost of virgin algae is approximately ranging from US$1 to 3/kg).
Various dead biomasses were used as biosorbent for different toxic materials. The use of dead cells in biosorption has many advantages; dead cells are not affected by toxic wastes and do not require a continuous supply of nutrients. They can be regenerated and reused from many cycles. Dead cells may be stored or used for extended periods at room temperature without putrefaction occurring. Moreover, dead cells have shown to accumulate pollutants to the same or greater extended than growing cell (Fu and Viraraghavan 2002).
Biosorbents are prepared from the naturally abundant and/or waste biomass which has the ability to sequester heavy metals; these biosorbents are: yeast (Padmavathy 2008), bacteria (Sulaymon et al. 2012), algae (Rathinam et al. 2010), and fungi (Holan and Volesky 1995).
Algal biomass has proven to be highly effective as well as reliable and predictable in the removal of heavy metals from aqueous solutions. The term algae refers to a large and diverse assemblage of organisms that contain chlorophyll and carry out oxygenic photosynthesis (Davis et al. 2003). There are seven divisions of algae; four of which contain algae as members. Divisions which include the larger visible algae are: Cyanophyta (blue–green algae), Chlorophyta (green algae), Rhodophyta (red algae), and Phaeophyta (brown algae). These divisions are subdivided into orders, which are subsequently divided into families and then into genus and species (Naja et al. 2010).
The metal ion-binding mechanism in biosorption may involve different processes such as complexation, coordination, electrostatic attraction, or microprecipitation; whereby ion exchange plays a major role in the binding of metal ions by algae biomass. Therefore, the use of ion exchange reaction model instead of Langmuir- or Freundlich-type sorption isotherm has been recommended for describing the process (Schiwer and Volesky 1996).
The aim of the present research is to investigate the experimental and theoretical removal of lead, cadmium, copper, and arsenic ions as single, binary, ternary, and quaternary from simulated wastewater using algae as a biosorbents. Batch experiments were carried out for kinetic studies on the removal of those ions from aqueous solution. The influence of various important parameters such as pH, contact time, agitation speed, adsorbent dose, and initial concentration is investigated.
Equation (6) represents an ion exchange isotherm for a single sorption system; the biosorption equilibrium data were set for heavy metal/light metals, where the first element indicates the sorbing metal, and the light metals specify the total amount of light metals released due to metal biosorption. The fraction of yM and xM is calculated from the experimental data and the affinity constant KM,L is calculated from Eq.(6) by using the STATISTICA computer program. The higher KM,L value means higher affinity of ions towards the adsorbent.
Experiments and materials
Biomass and heavy metals
Various green (Chlorophyta) and blue–green (Cyanophyta) algae were used as biosorbent for the removal of Pb2+, Cd2+, Cu2+, and As3+ ions. The algae were collected in April and September 2011 from the Tigris River, Iraq. They were washed several times with tap water and then with deionized water to remove impurities and unwanted materials. The algae were analyzed by using microscope and their division, genus, and species were Cyanophyta (Oscillatoria princeps 92 %, Oscillatoria subbrevis 2 %, and Oscillatoria formosa 1 %) and Chlorophyta (Spirogyra aequinoctialis 3 %, Mougeta sp. 1 %, and others 1 %).
The algae biomass was sun-dried and then dried in oven at 50 °C for 24 h. The dried algae biomass was shredded, ground in a mortar, and sieved. An average size of 500–600 μm was used for biosorption experiments. Pb2+, Cd2+, Cu2+, and As3+ ion solutions were prepared by dissolving Pb(NO3)2·2H2O, Cd(NO3)2, Cu(NO3)2·3H2O, and As2O3 in distilled water. These solutions were kept at 25 °C. Concentrations of 50 ppm from these salts were used as adsorbate for different weight of algae biomass. The pH of solutions was adjusted to the required value using 0.1 M HNO3 and 0.1 M NaOH solutions. A pH meter type WTW/inoLab series was used. All chemicals used in this work were analytical reagent grade and were used without further purification. The solubility of Pb(NO3)2·2H2O, Cd(NO3)2, Cu(NO3)2·3H2O, and As2O3 in water is 54.3, 136, 125, and 1.8 g/100 g H2O, respectively.
Biosorbent batch experiments
The experimental works were carried out to plot the isotherm curves by changing the weights of adsorbent and keeping constant adsorbate concentration at 50 ppm for single and polymetallic systems.
Adsorption kinetic experiments were carried out by agitating 1 l of lead, cadmium, copper, and arsenic solutions of 50 ppm initial concentration. The dosage of algae to reach equilibrium concentration (C/Ci) equals to 0.1 was calculated by using Eq. (10). Beaker of 2 l is filled with 1 l of solution and agitation is started before adding the optimum weight of algae, and then, samples were taken for each 1, 2, 3, 5, 10, 15, 20, 25, 30, 40, 50, 60, 80, 100, 120, 150, 180, 210, and 240 min. The optimum pH of removal of each solution obtained from equilibrium isotherm experiments was fixed for each solution before agitation process was started.
Results and discussion
Fourier transformation infrared spectroscopy analysis
Many authors have used Fourier transformation infrared (FTIR) spectroscopy to detect vibration frequency changes in algae. FTIR offers excellent information on the nature of the bands present on the surface of the algae and also presents three main advantages as an analytical technique: it is fast, nondestructive, and requires only small sample quantities (Pereira et al. 2003).
The characteristics of absorption bands of hydroxyl and amine groups were identified at 3,414 cm−1, alkyl chains at 2,966 and 2,943 cm−1, C=0 of the carboxylic groups or ester groups at 1,797, C=O of amide groups at 1,647 cm−1, COO− of the carboxylate groups appeared at 1,427 cm−1, S=O of the sulfonate groups and COO− groups of the fatty acids at 1,300 cm−1, and the wave number at 1,033 cm−1 were attributed to the P–O–C links of the organic phosphate groups (Naja et al. 2005, 2010). Some bands in the fingerprint regions could be attributed to the phosphate groups (Diniz et al. 2008).
Values of observed peak bands for virgin algae and Pb2+-, Cd2+-, Cu2+-, and As3+-loaded algae
Effect of pH
For pH values lower than pKa, equilibrium (14) shifts to the left, consuming protons and increasing pH until its value equals the pKa, the opposite will happen.
Effect of initial concentration
Effect of temperature
Further increase in temperature (above 25 °C) leads to a decrease in the percentage removal. This decrease in biosorption efficiency may be attributed to many reasons: increasing in the relative escaping tendency of the heavy metals from the solid phase to the bulk phase, deactivating the biosorbent surface, or destructing some active sites on the biosorbent surface due to bond ruptures (Meena et al. 2005) or due to the weakness of biosorption forces between the active sites of the sorbents and the sorbate species and also between the adjacent molecules of the sorbed phase (Ahmet and Mustafa 2008).
Ionic properties of Pb2+, Cd2+, Cu2+, and As3+
Atomic radius (A°)
Ionization energy (kcal/g/mol)
Values of affinity constant (K) and R2 for each metal system
Binary, ternary, and quaternary mixtures of heavy metals are usually present in effluent from different industries. As shown previously in single isotherm experiments, the pH of mixtures in binary, ternary, and quaternary systems was fixed at 4 since this value was correspondent for all metal removal.
The values of affinity constants gave a good indicator to understand the biosorption capacity of metals. For single system, the greatest values of K were 16.55 for Pb2+ then 15.97, 10.52, and 7.45 for Cu2+, Cd2+, and As3+, respectively.
The decrease in affinity constant values in binary, ternary, and quaternary systems when compared with the single metal biosorption of four metals is due to the competition between metals for binding sites present in algal biomass wall. The biosorption capacity for each metal decreases when increasing the number of metals, so that at quaternary system, the lowest biosorption capacity was obtained.
Optimum agitation speed
Vijayaraghavan and Yun (2008) indicated that with appropriate agitation, the mass transfer resistance can be minimized. Additionally, increasing the agitation rate, the diffusion rate of a solute from the bulk liquid to the liquid boundary layer surrounding particles becomes higher due to the enhanced turbulence and the decrease in the thickness of the liquid boundary layer. Under these conditions, the value of the external diffusion coefficient becomes larger.
The study of biosorption kinetics of heavy metal removal from wastewater is significant as it provides valuable insights into the reaction pathways and into the mechanism of sorption reactions. Monitoring a kinetic experiment helps to study how the biosorption system is affected by process variables and to understand the steps which limit biosorption. In addition, the biosorption kinetics describes the solute uptake rate which in turn controls the residence time of biosorbate uptake at the solid–solution interface. Therefore, it is important to predict the rate at which sorbate is removed from aqueous solutions in order to design appropriate sorption treatment processes.
Calculated kinetic parameters for pseudo-first and pseudo-second order for Pb2+, Cd2+, Cu2+, and As3+ with correlation coefficients
Pseudo-first-order kinetic model
Pseudo-second-order kinetic model
The present study evaluated the competition removal of Pb2+, Cd2+, Cu2+, and As3+ using algae. The biosorption process depends significantly on the pH of the solution and is favored at around pH of 3–5.
The result showed that a well fitting exists between the ion exchange model and experimental data. The affinity constant sequence calculated for single system was KPb > KCu > KCd > KAs; then, the affinity constant values reduce in binary and ternary systems, while the lowest value in the quaternary system is reached due to the competition among the four metals. The optimum agitation speed to reach 90 % removal efficiency was 300, 600, 500, and 600 rpm for Pb2+, Cd2+, Cu2+, and As3+, respectively. Kinetics investigation of the equilibrium data showed that the biosorption of Pb2+, Cd2+, Cu2+, and As3+ onto algae followed well the pseudo-second-order kinetic model.
We would like to express our sincere thanks and deep gratitude to the Ministry of Water Resources/Center for the Restoration of Iraqi Marshlands for supporting this work.
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