Investigating the complex interactions among physicochemical variables that influence the adsorptive removal of pollutants is a challenge for conventional one-variable-at-a-time (OVAT) batch methods. The adoption of machine learning-based chemometric prediction models is expected to be more accurate than the conventional method. This study proposed a novel modeling framework for predicting and optimizing the adsorptive removal of N-Nitrosodiphenylamine (NDPhA).
View Article and Find Full Text PDFChemosphere
August 2024
Microplastics (MPs) and their co-pollutants pose significant threats to soil and marine environments, necessitating understanding of their colonization processes to combat the plastic pandemic and protect ecosystems. MPs can act as invisible carriers, concentrating and transporting pollutants, leading to a more widespread and potentially toxic impact than the presence of either MPs or the pollutants alone. Analyzing the sorption and desorption dynamics of MPs is crucial for understanding pollutants amplification and predicting the fate and transport of pollutants in soil and marine environments.
View Article and Find Full Text PDFInt J Mol Sci
February 2021
This study deals with the preparation of activated carbon (CDSP) from date seed powder (DSP) by chemical activation to eliminate polyaromatic hydrocarbon-PAHs (naphthalene-CH) from synthetic wastewater. The chemical activation process was carried out using a weak Lewis acid of zinc acetate dihydrate salt (Zn(CHCO)·2HO). The equilibrium isotherm and kinetics analysis was carried out using DSP and CDSP samples, and their performances were compared for the removal of a volatile organic compound-naphthalene (CH)-from synthetic aqueous effluents or wastewater.
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