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监管性颗粒物监测仪的分配公平性

Equity in the Distribution of Regulatory PM Monitors.

作者信息

Haskell-Craig Zoé, Josey Kevin P, Kinney Patrick L, deSouza Priyanka

机构信息

Department of Biostatistics, New York University School of Global Public Health, New York, New York 10003, United States.

Department of Biostatistics & Informatics, Colorado School of Public Health, Aurora, Colorado 80045, United States.

出版信息

Environ Sci Technol. 2025 Aug 5;59(30):15843-15852. doi: 10.1021/acs.est.4c12915. Epub 2025 Jul 23.

Abstract

Unequal exposure to air pollution by race and socioeconomic status is well-documented in the U.S. However, relatively little research has examined inequities in the collection of PM data, creating a critical gap in understanding which neighborhood exposures are represented in these data sets. In this study, we use multilevel models with random intercepts by county and state, stratified by urbanicity, to assess associations between six key environmental justice (EJ) attributes (%AIAN, %Asian, %Black, %Hispanic, %White, %Poverty) at the census tract level and proximity to the nearest regulatory monitor. Our results show that most EJ attributes exhibit weak or statistically insignificant associations with monitor proximity, with the exception of %Poverty, where higher poverty levels are significantly linked to closer monitors in urban (β = -0.88, 95% CI = [-0.93, -0.83]) and farther monitor distances in rural (β = 0.6, 95%CI = [0.49, 0.71]) areas. While the U.S. EPA's siting criteria may be effective in ensuring equitable monitor distribution in many contexts, the low density of monitors in rural areas may impact the accuracy of national-level air pollution monitoring.

摘要

在美国,种族和社会经济地位导致的空气污染暴露不平等现象有充分的文献记载。然而,相对较少的研究考察了PM数据收集方面的不公平现象,这在理解这些数据集中所代表的社区暴露情况方面造成了关键差距。在本研究中,我们使用按县和州设置随机截距、并按城市化程度分层的多层次模型,来评估人口普查区层面的六个关键环境正义(EJ)属性(美洲印第安人和阿拉斯加原住民百分比、亚裔百分比、黑人百分比、西班牙裔百分比、白人百分比、贫困率)与距离最近的监管监测站的关联。我们的结果表明,除贫困率外,大多数EJ属性与监测站距离的关联较弱或在统计上不显著。在城市地区,贫困率较高与监测站距离较近显著相关(β = -0.88,95%置信区间 = [-0.93, -0.83]);在农村地区,贫困率较高与监测站距离较远显著相关(β = 0.6,95%置信区间 = [0.49, 0.71])。虽然美国环境保护局(EPA)的选址标准在许多情况下可能有效地确保监测站分布公平,但农村地区监测站密度较低可能会影响国家级空气污染监测的准确性。

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