Microplastics removal efficiency of drinking water treatment plant with pulse clarifier

被引:122
作者
Sarkar, Dhruba Jyoti [1 ]
Sarkar, Soma Das [2 ]
Das, Basanta Kumar [1 ]
Praharaj, Jaya Krushna [3 ]
Mahajan, Dev Kumar [3 ]
Purokait, Bidesh [3 ]
Mohanty, Trupty Rani [4 ]
Mohanty, Debasmita [4 ]
Gogoi, Pranab [4 ]
Kumar, V. Santhana [1 ]
Behera, Bijay Kumar [1 ]
Manna, Ranjan Kumar [4 ]
Samanta, Srikanta [4 ]
机构
[1] Cent Inland Fisheries Res Inst, ICAR, Aquat Environm Biotechnol & Nanotechnol Div, Kolkata 700120, India
[2] Cent Inland Fisheries Res Inst, ICAR, Fisheries Resource Assessment & Informat Div, Kolkata 700120, India
[3] Indira Gandhi Water Treatment Plant, Kolkata 700120, India
[4] Cent Inland Fisheries Res Inst, ICAR, Riverine & Estuarine Fisheries Div, Kolkata 700120, India
关键词
Microplastics; Drinking water treatment plant; Pulse clarification; Removal efficiency; MARINE-ENVIRONMENT; NILE RED; SEDIMENTS; PARTICLES; ABUNDANCE; POLLUTION; VECTORS; RELEASE; DAMAGE; ALUM;
D O I
10.1016/j.jhazmat.2021.125347
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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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页数:9
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