Knobel Pablo, Hwang Inhye, Castro Edgar, Sheffield Perry, Holaday Louisa, Shi Liuhua, Amini Heresh, Schwartz Joel, Sade Maayan Yitshak
Icahn School of Medicine at Mount Sinai, Department of Environmental Medicine and Public Health, New York, NY, USA.
Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Atmos Environ (1994). 2023 Jun 15;303. doi: 10.1016/j.atmosenv.2023.119753. Epub 2023 Apr 5.
Fine particulate matter (PM) air pollution exposure is associated with short and long-term health effects. Several studies found differences in PM exposure associated with neighborhood racial and socioeconomic composition. However, most focused on total PM mass rather than its chemical components and their sources. In this study, we describe the ZIP code characteristics that drive the disparities in exposure to PM chemical components attributed to source categories both nationally and regionally. We obtained annual mean predictions of PM and fourteen of its chemical components from spatiotemporal models and socioeconomic and racial predictor variables from the 2010 US Census, and the American Community Survey 5-year estimates. We used non-negative matrix factorization to attribute the chemical components to five source categories. We fit generalized nonlinear models to assess the associations between the neighborhood predictors and each PM source category in urban areas in the United States in 2010 (n=25,790 zip codes). We observed higher PM levels in ZIP codes with higher proportions of Black individuals and lower socioeconomic status. Racial exposure disparities were mainly attributed to Heavy Fuel, Oil and Industrial, Metal Processing Industry and Agricultural, and Motor Vehicle sources. Economic disparities were mainly attributed to Soil and Crustal Dust, Heavy Fuel Oil and Industrial, Metal Processing Industry and Agricultural, and Motor Vehicle sources. Upon further analysis through stratifying by regions within the United States, we found that the associations between ZIP code characteristics and source-attributed PM levels were generally greater in Western states. In conclusion, racial, socioeconomic, and geographic inequalities in exposure to PM and its components are driven by systematic differences in component sources that can inform air quality improvement strategies.
暴露于细颗粒物（PM）空气污染与短期和长期健康影响相关。多项研究发现，与邻里种族和社会经济构成相关的PM暴露存在差异。然而，大多数研究关注的是PM的总质量，而非其化学成分及其来源。在本研究中，我们描述了在美国全国和区域层面上，导致因来源类别而产生的PM化学成分暴露差异的邮政编码区域特征。我们从时空模型中获得了PM及其14种化学成分的年度平均预测值，以及来自2010年美国人口普查和美国社区调查5年估计值的社会经济和种族预测变量。我们使用非负矩阵分解将化学成分归因于五个来源类别。我们拟合了广义非线性模型，以评估2010年美国城市地区邻里预测变量与每个PM来源类别之间的关联（n = 25,790个邮政编码区域）。我们观察到，黑人比例较高且社会经济地位较低的邮政编码区域中PM水平更高。种族暴露差异主要归因于重质燃料、石油和工业、金属加工业和农业以及机动车来源。经济差异主要归因于土壤和地壳尘埃、重质燃料油和工业、金属加工业和农业以及机动车来源。通过按美国各地区进行分层进一步分析后，我们发现邮政编码区域特征与来源归因的PM水平之间的关联在西部各州通常更大。总之，PM及其成分暴露方面的种族、社会经济和地理不平等是由成分来源的系统性差异驱动的，这些差异可为空气质量改善策略提供参考。
