| Literature DB >> 32072869 |
Claudia Erika Mendoza-Chávez1, Anne Carabin2, Ahmad Dirany2, Patrick Drogui2, Gerardo Buelna2, María Mercedes Meza-Montenegro1, Ruth Gabriela Ulloa-Mercado1, Lourdes Mariana Diaz-Tenorio1, Luis Alonso Leyva-Soto1, Pablo Gortáres-Moroyoqui1.
Abstract
Arsenic presence in the water has become one of the most concerning environmental problems. Electrocoagulation is a technology that offers several advantages over conventional treatments such as chemical coagulation. In the present work, an electrocoagulation system was optimized for arsenic removal at initial concentrations of 100 µg/L using response surface methodology. The effects of studied parameters were determined by a 23 factorial design, whereas treatment time had a positive effect and current intensity had a negative effect on arsenic removal efficiency. With a p-value of 0.1629 and a confidence of level 99%, the type of electrode material did not have a significant effect on arsenic removal. Efficiency over 90% was reached at optimal operating conditions of 0.2 A of current intensity, and 7 min of treatment time using iron as the electrode material. However, the time necessary to accomplish with OMS arsenic guideline of 10 µg/L increased from 7 to 30 min when real arsenic-contaminated groundwater with an initial concentration of 80.2 ± 3.24 µg/L was used. The design of a pilot-scale electrocoagulation reactor was determined with the capacity to meet the water requirement of a 6417 population community in Sonora, Mexico. To provide the 1.0 L/s required, an electrocoagulation reactor with a working volume of 1.79 m3, a total electrode effective surface of 701 m2, operating at a current intensity of 180 A and an operating cost of 0.0208 US$/day was proposed. Based on these results, electrocoagulation can be considered an efficient technology to treat arsenic-contaminated water and meet the drinking water quality standards.Entities:
Keywords: Electrocoagulation; arsenic contaminated water; optimization; real groundwater; response surface methodology
Year: 2020 PMID: 32072869 DOI: 10.1080/09593330.2020.1732472
Source DB: PubMed Journal: Environ Technol ISSN: 0959-3330 Impact factor: 3.247