Data to assess pesticide exposure in soil and water are scarce and unevenly distributed in Latin America, especially due to the size of the region and the vast agricultural landscape. This makes it difficult to assess associated environmental risks. We suggest that the lack of pesticide exposure or monitoring data can be addressed by using validated models to provide estimated pesticide exposure concentrations in soil and water bodies. This exposure modeling approach has been used by regulatory agencies in other countries and regions such as the United States, Canada, and the European Union. In order to properly estimate pesticide exposure concentrations, we advocate for the development of local scenarios containing local weather, soil, and crop data to be used in the existing models. A sensitivity analysis of the models can be performed to determine parameters that are sensitive and therefore inputs to these parameters are derived locally. We believe the development of local scenarios in the region is attainable and can be a pragmatic approach for developing a more comprehensive picture of potential pesticide exposure in the region. Integr Environ Assess Manag 2021;17:901–904. © 2021 Syngenta Proteção de Cultivos Ltda

中文翻译：

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估计拉丁美洲的农药环境浓度：制定当地情景的重要性

在拉丁美洲，评估土壤和水中农药暴露的数据稀少且分布不均，特别是由于该地区的面积和广阔的农业景观。这使得评估相关的环境风险变得困难。我们建议可以通过使用经过验证的模型来提供土壤和水体中估计的农药暴露浓度来解决缺乏农药暴露或监测数据的问题。这种暴露建模方法已被美国、加拿大和欧盟等其他国家和地区的监管机构使用。为了正确估计农药暴露浓度，我们提倡开发包含当地天气、土壤和作物数据的当地情景，以用于现有模型。可以执行模型的敏感性分析来确定敏感的参数，因此这些参数的输入是在本地导出的。我们相信在该地区制定当地情景是可以实现的，并且可以成为更全面地了解该地区潜在农药暴露情况的务实方法。Integr Environ Assess Manag 2021；17:901-904。© 2021 先正达 Proteção de Cultivos Ltda