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多尺度空间模型在人类暴露于局部源到全球摄入中的应用。

Multiscale Spatial Modeling of Human Exposure from Local Sources to Global Intake.

机构信息

Department of Environmental Health Sciences, School of Public Health (SPH), University of Michigan , 6622 SPH Tower, 1415 Washington Heights, Ann Arbor, Michigan 48109-2029, United States.

Quantitative Sustainability Assessment Division, Department of Management Engineering, Technical University of Denmark , Bygningstorvet 116, 2800 Kongens Lyngby, Denmark.

出版信息

Environ Sci Technol. 2018 Jan 16;52(2):701-711. doi: 10.1021/acs.est.7b05099. Epub 2018 Jan 2.

Abstract

Exposure studies, used in human health risk and impact assessments of chemicals, are largely performed locally or regionally. It is usually not known how global impacts resulting from exposure to point source emissions compare to local impacts. To address this problem, we introduce Pangea, an innovative multiscale, spatial multimedia fate and exposure assessment model. We study local to global population exposure associated with emissions from 126 point sources matching locations of waste-to-energy plants across France. Results for three chemicals with distinct physicochemical properties are expressed as the evolution of the population intake fraction through inhalation and ingestion as a function of the distance from sources. For substances with atmospheric half-lives longer than a week, less than 20% of the global population intake through inhalation (median of 126 emission scenarios) can occur within a 100 km radius from the source. This suggests that, by neglecting distant low-level exposure, local assessments might only account for fractions of global cumulative intakes. We also study ∼10 000 emission locations covering France more densely to determine per chemical and exposure route which locations minimize global intakes. Maps of global intake fractions associated with each emission location show clear patterns associated with population and agriculture production densities.

摘要

暴露研究常用于化学品对人类健康风险和影响的评估,这些研究主要在当地或地区范围内进行。通常情况下,人们并不清楚因接触点源排放而产生的全球影响与当地影响相比如何。为了解决这个问题,我们引入了 Pangea,这是一种创新的多尺度、空间多媒体归趋和暴露评估模型。我们研究了与法国各地废物转化能源工厂位置相匹配的 126 个点源排放相关的本地到全球人群暴露情况。我们以三种具有不同物理化学特性的化学物质为例,将其作为吸入和摄入途径的人群摄入量分数的演变,作为距离源的函数。对于大气半衰期超过一周的物质,通过吸入(126 种排放情景的中位数)进入全球人口的摄入量中,不到 20%发生在距源 100 公里的范围内。这表明,通过忽略远距离的低水平暴露,局部评估可能只占全球累积摄入量的一部分。我们还研究了覆盖法国的约 10000 个排放地点,以更密集地确定每个化学物质和暴露途径的位置,这些位置可以使全球摄入量最小化。与每个排放地点相关的全球摄入量分数的地图显示了与人口和农业生产密度相关的明确模式。

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