Center for Public Health and Environmental Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27709, United States.
Region 08, Water Division, U.S. Environmental Protection Agency, Helena, Montana 59626, United States.
Environ Sci Technol. 2023 Sep 19;57(37):14024-14035. doi: 10.1021/acs.est.3c03670. Epub 2023 Sep 5.
Decision makers in the Columbia River Basin (CRB) are currently challenged with identifying and characterizing the extent of per- and polyfluoroalkyl substances (PFAS) contamination and human exposure to PFAS. This work aims to develop and pilot a methodology to help decision makers target and prioritize sampling investigations and identify contaminated natural resources. Here we use random forest models to predict ∑PFAS in fish tissue; understanding PFAS levels in fish is particularly important in the CRB because fish can be a major component of tribal and indigenous people diet. Geospatial data, including land cover and distances to known or potential PFAS sources and industries, were leveraged as predictors for modeling. Models were developed and evaluated for Washington state and Oregon using limited available empirical data. Mapped predictions show several areas where detectable concentrations of PFAS in fish tissue are predicted to occur, but prior sampling has not yet confirmed. Variable importance is analyzed to identify potentially important sources of PFAS in fish in this region. The cost-effective methodologies demonstrated here can help address sparsity of existing PFAS occurrence data in environmental media in this and other regions while also giving insights into potentially important drivers and sources of PFAS in fish.
哥伦比亚河流域（CRB）的决策者目前面临着确定和描述全氟和多氟烷基物质（PFAS）污染程度以及人类接触 PFAS 的挑战。本研究旨在开发和试点一种方法，帮助决策者确定和优先进行采样调查，并识别受污染的自然资源。在这里，我们使用随机森林模型来预测鱼类组织中的∑PFAS；了解鱼类中的 PFAS 水平在 CRB 尤为重要，因为鱼类可能是部落和土著人民饮食的主要组成部分。我们利用包括土地覆盖和与已知或潜在 PFAS 来源和工业的距离在内的地理空间数据作为预测因子进行建模。我们使用有限的可用经验数据为华盛顿州和俄勒冈州开发和评估了模型。绘制的预测结果显示了几个可能存在鱼类组织中可检测到的 PFAS 浓度的区域，但之前的采样尚未证实。我们分析了变量的重要性，以确定该地区鱼类中 PFAS 的潜在重要来源。本研究中展示的具有成本效益的方法可以帮助解决该地区及其他地区环境介质中现有 PFAS 出现数据稀疏的问题，同时还可以深入了解鱼类中 PFAS 的潜在重要驱动因素和来源。
