open access

https://hdl.handle.net/2115/87674

Selection of Priority Pesticides in Japanese Drinking Water Quality Regulation : Validity, Limitations, and Evolution of a Risk Prediction Method

英語

Risk ranking

2021-01-10

Elsevier

Science of the Total Environment

751

141636

Several risk scoring and ranking methods have been applied for the prioritization of micropollutants, including pesticides, and in the selection of pesticides to be regulated regionally and nationally. However, the effectiveness of these methods has not been evaluated in Japan. We developed a risk prediction method to select pesticides that have a high probability of being detected in drinking water sources where no monitoring data is available. The risk prediction method was used to select new pesticides for the 2013 Primary List in the Japanese Drinking Water Quality Guidelines. Here, we examined the effectiveness of the method on the basis of the results of water quality examinations conducted by water supply authorities across Japan, and studied ways to improve the risk prediction method. Of the 120 pesticides in the 2013 Primary List, 80 were detected in drinking water sources (raw water entering water treatment plants). The rates of detection of the newly selected pesticides and previously listed pesticides were not significantly different: 64% and 68%, respectively. When the risk predictor was revised to incorporate degradability of dry-field pesticides and current pesticide sales data, the rate of detection of pesticides selected as having a high risk of detection improved from 72% to 88%. We prepared regional versions of the Primary List using the revised risk predictors and verified their utility. The number of listed pesticides varied greatly by region, ranging from 32 to 73; all regional lists were much shorter than the national Primary List. In addition, 55% to 100% of the pesticides detected in each region were included in a Regional Primary List. This work verifies the ability of the risk prediction method to screen pesticides and select those with a high risk of detection.

学術雑誌論文

Accepted Manuscript

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

©2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/

0048-9697

AA00836666