Saul Bradley C, Hudgens Michael G, Mallin Michael A
Department of Biostatistics, University of North Carolina Chapel Hill.
Center for Marine Science, University of North Carolina Wilmington.
J Am Stat Assoc. 2019;114(528):1493-1504. doi: 10.1080/01621459.2019.1574226. Epub 2019 Apr 23.
The United States Environmental Protection Agency considers nutrient pollution in stream ecosystems one of the U.S.' most pressing environmental challenges. But limited independent replicates, lack of experimental randomization, and space- and time-varying confounding handicap causal inference on effects of nutrient pollution. In this paper the causal g-methods are extended to allow for exposures to vary in time and space in order to assess the effects of nutrient pollution on chlorophyll - a proxy for algal production. Publicly available data from North Carolina's Cape Fear River and a simulation study are used to show how causal effects of upstream nutrient concentrations on downstream chlorophyll levels may be estimated from typical water quality monitoring data. Estimates obtained from the parametric g-formula, a marginal structural model, and a structural nested model indicate that chlorophyll concentrations at Lock and Dam 1 were influenced by nitrate concentrations measured 86 to 109 km upstream, an area where four major industrial and municipal point sources discharge wastewater.
美国环境保护局认为河流生态系统中的营养物污染是美国最紧迫的环境挑战之一。但独立重复样本有限、缺乏实验随机化以及时空变化的混杂因素妨碍了对营养物污染影响的因果推断。在本文中，因果g方法得到扩展，以允许暴露在时间和空间上变化，从而评估营养物污染对叶绿素-a（藻类生产的一个指标）的影响。利用北卡罗来纳州开普菲尔河的公开数据和一项模拟研究，展示了如何从典型的水质监测数据中估计上游营养物浓度对下游叶绿素水平的因果效应。从参数化g公式、边际结构模型和结构嵌套模型获得的估计表明，1号水闸和大坝处的叶绿素浓度受到上游86至109公里处测量的硝酸盐浓度的影响，该区域有四个主要工业和市政点源排放废水。
