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• W4366989327 abstract "Microplastics and benzyldimethyldodecylammonioum chloride (DDBAC) enter the environment more frequently during the COVID-19 pandemic and their co-occurrence will be a potential threat to the environment in the post-pandemic era. This study investigates the performance of an electrochemical system for the simultaneous removal of microplastics and DDBAC. During experimental studies, effects of applied voltage (3-15 V), pH (4-10), time (0-80 min), electrolyte concentration (0.01-0.0.09 M), electrode configuration, and perforated anode were investigated to identify their influence on DDBAC and microplastics removal efficiency. Eventually, the techno-economic optimization yielded to evaluate the commercial feasibility of this process. The central composite design (CCD) and analysis of variance (ANOVA) are employed for evaluation and optimization of the variables and response, DDBAC-microplastics removal, and for determining the adequacy and significance of mathematical models proposed by response surface methodology (RSM). Experimental results indicate that optimum conditions are pH = 7.4, time = 80 min, electrolyte concentration = 0.05 M, and applied voltage = 12.59, in which the removal of microplastics, DDBAC, and TOC reached the maximum level, which was 82.50%, 90.35%, and 83.60% respectively. The results confirm that the valid model is adequately significant for the target response. Overall, financial and energy consumption analyses confirmed that this process is a promising technology as a commercial method for the removal of DDBAC-microplastics complexes in water and wastewater treatment." @default.
• W4366989327 created "2023-04-27" @default.
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• W4366989327 date "2023-04-25" @default.
• W4366989327 modified "2023-10-13" @default.
• W4366989327 title "Simultaneous removal of microplastics and benzalkonium chloride using electrocoagulation process: statistical modeling and techno-economic optimization" @default.
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• W4366989327 doi "https://doi.org/10.1007/s11356-023-26971-w" @default.
• W4366989327 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37095214" @default.
• W4366989327 hasPublicationYear "2023" @default.
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