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越南湄公河三角洲不同水稻种植策略下使用农药的水生风险预测比较。

Comparison of predicted aquatic risks of pesticides used under different rice-farming strategies in the Mekong Delta, Vietnam.

机构信息

Department of Ecology, Environment and Plant Sciences, Stockholm University, Stockholm, Sweden.

Department of Physical Geography, Stockholm University, Stockholm, Sweden.

出版信息

Environ Sci Pollut Res Int. 2018 May;25(14):13322-13334. doi: 10.1007/s11356-016-7991-4. Epub 2016 Nov 16.

DOI:10.1007/s11356-016-7991-4
PMID:27854060
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5978820/
Abstract

This study evaluates the risks of pesticides applied in rice-fish and rice farming, with and without integrated pest management (IPM) strategies, to non-target aquatic organisms in two provinces of the Mekong Delta, Vietnam. Pesticide inventories and application patterns were collected from 120 Vietnamese farmers through interviews. Risks were assessed using (1) Pesticide RIsks in the Tropics to Man, Environment, and Trade (PRIMET), a first-tier model, which calculates predicted environmental concentrations (PECs) of pesticides in the rice field, based on the compound's physico-chemical properties and the application pattern, and then compares the PECs to safe concentrations based on literature data, and (2) species sensitivity distribution (SSD), a second-tier assessment model using species sensitivity distributions to calculate potentially affected fraction (PAF) of species based on the PECs from PRIMET. Our results show that several of the used insecticides pose a high risk to fish and arthropods and that the risks are higher among rice farmers than among rice-fish farmers. This study indicates that the PRIMET model in combination with SSDs offer suitable approaches to help farmers and plant protection staff to identify pesticides that may cause high risk to the environment and therefore should be substituted with safer alternatives.

摘要

本研究评估了在越南湄公河三角洲两个省份,采用和不采用综合虫害管理(IPM)策略的情况下,水稻-鱼类和水稻种植中使用的农药对非靶标水生生物的风险。通过访谈从 120 位越南农民那里收集了农药清单和使用模式。使用(1)热带地区对人类、环境和贸易的农药风险(PRIMET),这是一个一级模型,根据化合物的物理化学性质和使用模式,计算稻田中农药的预测环境浓度(PEC),然后将 PEC 与文献数据中的安全浓度进行比较,以及(2)物种敏感度分布(SSD),这是一个二级评估模型,使用物种敏感度分布根据 PRIMET 的 PEC 计算基于物种的潜在受影响分数(PAF)。我们的结果表明,几种使用的杀虫剂对鱼类和节肢动物构成高风险,且在水稻农民中的风险高于水稻-鱼类农民。本研究表明,PRIMET 模型结合 SSD 为帮助农民和植保人员识别可能对环境造成高风险的农药提供了合适的方法,因此应使用更安全的替代品替代这些农药。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5626/5978820/1f3ef43badbd/11356_2016_7991_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5626/5978820/d8b1ead4f445/11356_2016_7991_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5626/5978820/de88dee3a0da/11356_2016_7991_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5626/5978820/1f3ef43badbd/11356_2016_7991_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5626/5978820/d8b1ead4f445/11356_2016_7991_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5626/5978820/de88dee3a0da/11356_2016_7991_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5626/5978820/1f3ef43badbd/11356_2016_7991_Fig3_HTML.jpg

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