Green Synthesis Characterization and Optimization of Copper Nanoparticles for the Remediation of Arsenic Bearing Underground water

Abstract

Arsenic, one of the common constituent of earth crust, is a carcinogenic and toxic newlinecontaminant of ground water and surface water resources. High levels of arsenic can newlinecause acute toxic effects on human health including gastrointestinal symptoms, newlinedisturbance of cardiovascular and nervous system function, pigmentation, newlinedepigmentation, keratosis, skin cancer, teratogenicity, reproduction disorder and even newlinedeath. The major pathway to human exposure of arsenic is from drinking of newlinecontaminated groundwater. Arsenic is introduced into environment through both newlinenatural and anthropogenic means. In natural water, the inorganic forms of arsenic newlinesuch as arsenite species (arsenious acid, H3AsO3) and negatively charged arsenate newline(H2AsO4 and HAsO4) are prevailing. Many different technologies have been newlinedeveloped to remove arsenic from drinking water in order to comply with the new newlineWHO limit (1 ppb). The common method for removal of arsenic from water involves newlineboth physical and chemical treatment including precipitation, adsorption, ion newlineexchange, membrane filtration and microbial transformation. Therefore the purpose of newlinethis study is to find the conditions favorable for removal of arsenic from drinking newlinewater by using adsorption using copper nanoparticles. Different production water newlineflow rates and pH were applied for removal of arsenic from drinking water, and it was newlineconcluded that in this experiment 95% removal efficiency was achieved. Arsenic (V) newlineis more efficiently removed by adsorption using Cu nanoparticles and the removal newlineefficiency was found to depend on pH of solution. Cu/CuO nanoparticles were found newlineto be a potential nano-adsorbent for arsenic removal from water. The kinetics of newlinearsenic adsorption onto Cu/CuO nanoparticles was evaluated using different models newlinesuch as pseudo-first-order, pseudo-second-order. The experimental data were fitted to newlinepseudo-first-order and pseudo-second-order equations. The correlation coefficient newlinevalues show that the pseudo-second-order model is more suitable than the pseudofirst- newlineorder model for arsenic adsorption. These results suggest that the adsorption of newlinearsenic onto Cu/CuO nanoparticles follows pseudo-second-order kinetics. In order to newlinestudy the extent of adsorption the classical isotherm models viz. Langmuir and newlineFreundlich models were analyzed in order to check the fitness of data obtained in newlinepresent study. newline