文獻(xiàn)名： Adsorption of five emerging contaminants on activated carbon from aqueous medium: kinetic characteristics and computational modeling for plausible mechanism
作者：Archana Rao, Anupama Kumar, Rita Dhodapkar & Sukdeb Pal
Department of Chemistry, Visvesvaraya National Institute of Technology, Nagpur, 440010, India
摘要：Pharmaceuticals and personal care products (PPCPs) do not have standard regulations for discharge in the environment and are categorized as contaminants of emerging concern as they pose potential threats to ecology as well as humans even at low concentrations. Conventional treatment processes generally employed in the wastewater treatment plants are not adequately engineered for effective removal of PPCPs. Identifying cost-effective tertiary treatment is therefore, important for complete removal of PPCPs from wastewater prior to discharge or reuse. Present study demonstrates adsorption using granular-activated carbon (GAC) as a possible tertiary treatment for simultaneous removal of five PPCPs from aqueous media. Adsorbent was characterized in terms of morphology, surface area, surface charge distribution, and presence of functional groups. Performance of GAC was investigated for sorption of three hydrophilic (ciprofloxacin, acetaminophen, and caffeine) and two hydrophobic (benzophenone and irgasan) PPCPs from aqueous solution varying the process parameters (initial concentration, adsorbent dose, pH, agitation time). Langmuir isotherm model (correlation coefficients (R2): 0.993 to 0.998) appeared to fit the isotherm data better than Temkin isotherm model for these adsorbates. Adsorption efficiencies of these compounds (8.26 to 20.40 mg g−1) were in accordance with their log Kow values. While the adsorption kinetics was best explained in terms of a pseudo-second-order kinetic model, the data suggested that adsorption mechanism was mainly governed by the intraparticle diffusion. The role of physical factors like molecular volume, molecular size, and area of targeted PPCPs were investigated through computational studies which in turn can help predicting their uptake onto GAC.
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