Arsenic Removal From Aqueous Solution: A Comprehensive Synthesis with Meta-Data

Abstract

Removal of arsenic from drinking water is one of the most important global concerns. Among the various techniques, adsorptive removal of arsenic is considered as a viable most effective method. However, limited attention is given to understand the overall relative sorption capacity of different sorbents (e.g., biocomposite, biochar and nano-composite etc.) since various factors influence the sorption capacity. The aim of this study is to assess the effectiveness of various adsorbents with quantitative estimation (Langmuir adsorption maxima, Qmax) as well as to evaluate the influence of experimental conditions on the achievement of maximum adsorption. A number of analyses including meta-analysis, analysis of variance (ANOVA), scientometric and regression were performed. The results revealed that among the sorbents, nanoparticles show the greatest sorption capacity while pre-doped biochar performed the best among different biochars. Average across all sorbents, As (V) removal efficacy was higher than As (III). As expected, a high point of zero charge (PZC) and higher positive surface charge favored adsorption. The relative contribution of different mechanisms was also discussed. Our scientometric analyses revealed that, research should focus on the development of low-cost adsorbents and increase their reusability, safe disposal of adsorbed arsenic. Altogether, our findings provide a molecular understanding of arsenic sorption to different sorbents with implications for tailoring a good sorbent for arsenic removal from drinking water.