☆ 4.7 Article

Microplastics removal efficiency of drinking water treatment plant with pulse clarifier

JOURNAL OF HAZARDOUS MATERIALS (2021)

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Journal

JOURNAL OF HAZARDOUS MATERIALS
Volume 413, Issue -, Pages -

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ELSEVIER
DOI: 10.1016/j.jhazmat.2021.125347

Keywords

Microplastics; Drinking water treatment plant; Pulse clarification; Removal efficiency

Categories

Engineering, Environmental Environmental Sciences

Funding

  1. Indian Council of Agricultural Research (ICAR), New Delhi, India [FREM/17-20/14]

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Microplastics are recognized as common pollutants in aquatic environments that may have adverse effects on human health. A study evaluated the occurrence and removal efficiency of microplastics at different treatment stages in a typical DWTP with pulse clarification, showing good removal efficiency at the sand filtration stage and strong associations with other components in water. The results suggest that DWTPs with pulse clarification systems may have comparable microplastics removal efficiency to advanced DWTPs.
Microplastics are recognized as ubiquitous pollutants in aquatic environments; however, very little study is done on their occurrence and fate at drinking water treatment plants (DWTPs). Though, the toxic effect of microplastics on human health is not yet well established; there is global concern about their possible ill effect on the human. Hence, the present study evaluates the occurrence of microplastics at different treatment stages of a typical DWTP with pulse clarification and its removal efficiency. In the test DWTP, raw water, sourced from river Ganga, was found to contain microplastics 17.88 items/L. Cumulative microplastic removal at key treatment stages viz. pulse clarification and sand filtration was found to be 63% and 85%, respectively. The study also revealed higher microplastic abundance on the sand filter bed due to the screening effect. The most frequently occurring microplastics were fibers and films/fragments with polyethylene terephthalate and polyethylene as a major chemical type. The t-distributed stochastic neighbor embedding machine learning algorithm revealed a strong association between microplastic abundance with turbidity, phosphate and nitrate. The test DWTP with a pulse clarification system was having comparable microplastics removal efficiency with previously reported advanced DWTPs.

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