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Degradation of different pesticides in water by microplasma: the roles of individual radicals and degradation pathways

Pesticides are emergent toxins often identified in aquatic environments. In the present study, microplasma was employed to reduce the pesticide content in water. The degradation efficacy, rate, and pathways of standard organophosphorus pesticides (namely, chlorpyrifos, chlorpyrifos oxone, and diazin...

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Published in:Environmental science and pollution research international 2021-02, Vol.28 (7), p.8296-8309
Main Authors: Khan, Muhammad Saiful Islam, Lee, Na Ri, Ahn, Jaehwan, Kim, Ji Young, Kim, Jong Hoon, Kwon, Ki Hyun, Kim, Yun-Ji
Format: Article
Language:English
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Summary:Pesticides are emergent toxins often identified in aquatic environments. In the present study, microplasma was employed to reduce the pesticide content in water. The degradation efficacy, rate, and pathways of standard organophosphorus pesticides (namely, chlorpyrifos, chlorpyrifos oxone, and diazinone) and an organochlorine pesticide (namely, DDT solution) were evaluated using microplasma. High-performance liquid chromatography (HPLC) analysis was performed to elucidate the degradation efficiency of pesticides as a function of plasma-produced substances that originally contributed to the main reduction procedure. Microplasma produces several types of radicals or reactive substances, for instance dissolved ozone (O 3 ), nitrogen oxides, hydroxyl radicals (OH radicals), and hydrogen peroxide (H 2 O 2 ). The removal potential differs due to the existence or absence of varieties of plasma-produced substances. The functions of major plasma-produced species on pesticide removal were determined by a passive technique. Nitrogen oxides showed a key role in organophosphorus pesticide removal, whereas dissolved ozone and OH radicals played major roles in DDT degradation. HPLC data showed that plasma-induced pesticide removal showed first-order reaction kinetics. The pesticide removal pathways through microplasma were validated by investigating the achieved data from LC-MS and GC-MS.
ISSN:0944-1344
1614-7499
DOI:10.1007/s11356-020-11127-x