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使用机器学习方法揭示农业地表水中农药对人类和生态系统健康的全球风险。

Uncovering global risk to human and ecosystem health from pesticides in agricultural surface water using a machine learning approach.

作者信息

Chen Jian, Zhao Li, Wang Bin, He Xinyi, Duan Lei, Yu Gang

机构信息

State Key Joint Laboratory of Environmental Simulation and Pollution Control, Beijing Key Laboratory for Emerging Organic Contaminants Control, Beijing Laboratory for Environmental Frontier Technologies, School of Environment, Tsinghua University, Beijing 100084, China.

Guangdong Institute for Drug Control, Guangdong, Guangzhou 510180, China.

出版信息

Environ Int. 2024 Dec;194:109154. doi: 10.1016/j.envint.2024.109154. Epub 2024 Nov 19.

Abstract

Pesticides typically co-occur in agricultural surface waters and pose a potential threat to human and ecosystem health. As pesticide screening in global agricultural surface waters is an immense analytical challenge, a detailed risk picture of pesticides in global agricultural surface waters is largely missing. Here, we create the first global maps of human health and ecological risk from pesticides in agricultural surface waters using random forest models based on 27,411 measurements of 309 pesticides and 30 geospatial parameters. Our global risk maps identify the hotspots, mainly in Southern Asia and Africa, with extensive pesticide use and poor wastewater management infrastructure. We identify 4 and 5 priority pesticides for protecting the human and ecosystem health, respectively. Importantly, we estimate that 305 million people worldwide are at potential health risk associated with the surface-water pesticide mixture exposure, with the vast majority (86%) being in Asia. We further identify the hotspots in the Ganges River basin in India, where more than 170 million people are at potential health risk. As pesticides are increasingly used to ensure the food production due to future population growth and climate change, our findings have implications for raising awareness of pesticide pollution, identifying the hotspots and helping to prioritize testing.

摘要

农药通常在农业地表水中同时出现,对人类和生态系统健康构成潜在威胁。由于对全球农业地表水进行农药筛查是一项巨大的分析挑战,因此全球农业地表水中农药的详细风险状况在很大程度上尚属空白。在此,我们利用基于309种农药的27411次测量数据和30个地理空间参数的随机森林模型,绘制了首份全球农业地表水中农药对人类健康和生态风险的地图。我们的全球风险地图确定了主要位于南亚和非洲的热点地区,这些地区农药使用广泛且废水管理基础设施薄弱。我们分别确定了4种和5种保护人类和生态系统健康的优先农药。重要的是,我们估计全球有3.05亿人面临与地表水农药混合物接触相关的潜在健康风险,其中绝大多数(86%)在亚洲。我们还确定了印度恒河流域的热点地区,那里有超过1.7亿人面临潜在健康风险。由于未来人口增长和气候变化,人们越来越多地使用农药来确保粮食生产,我们的研究结果对于提高人们对农药污染的认识、确定热点地区以及帮助确定检测重点具有重要意义。

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