Environmental Monitoring and Contaminants Research
Online ISSN : 2435-7685
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Contamination levels, monthly variations, and predictions of neonicotinoid pesticides in surface waters of Gifu Prefecture in Japan
Yoshitaka HAYASHINozomi SASAKIMari TAKAZAWATomomi INAGAKIHiroki NAKAMURAAtsushi YAMAMOTOShigeru SUZUKI
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2021 Volume 1 Pages 17-27

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Abstract

The neonicotinoid pesticides acetamiprid (ACE), clothianidin (CTD), dinotefuran (DIN), imidacloprid (IMI), nitenpyram (NTP), thiacloprid (THI), and thiamethoxam (TMX) are widely used in over 120 countries. These pesticides have been regulated in many jurisdictions, including the European Union (EU), the United States, and the United Kingdom, due to adverse effects on non-target organisms, whereas some of these pesticides are permitted in Japan. In the present study, we have 1) measured levels of these pesticides at 103 locations (n=672) across Gifu Prefecture, 2) analyzed the monthly trends and regionality using R and ArcGIS, and 3) created a predicted contamination map by an ordinary kriging analysis. The concentration levels of the seven neonicotinoid pesticides in surface waters were determined using liquid chromatography with tandem mass spectrometry (LC/MS/MS) and ranged from <2.0 to 530 ng/L during the ten-month period. In a total of 672 samples, the top three pesticides detected at high frequency were DIN (76.9%), CTD (48.4%), and IMI (19.6%). The concentration of the neonicotinoid pesticides in environmental waters varied with the time periods of application, physiochemical properties of the pesticides, land use, geological properties of the contamination sources, and other factors. Potential contamination sources were depicted in the predicted contamination maps by using ordinary kriging models, which showed that DIN and CTD are widely present in Gifu Prefecture. Monthly variance of the concentration of IMI differed in the two geological regions, due to differences in the time of application and agricultural products yield. The results of our study contribute to a better understanding of the contamination status of neonicotinoid pesticides by providing reference data (actual pesticide concentrations) as well as predicted contamination maps.

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