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美国空气污染暴露不平等指标与环境正义和公平目标的一致性。

Alignment of Air Pollution Exposure Inequality Metrics with Environmental Justice and Equity Goals in the United States.

作者信息

Chambliss Sarah, La Frinere-Sandoval Natasha Quynh Nhu Bui, Zigler Corwin, Mueller Elizabeth J, Peng Roger D, Hall Emily M, Matsui Elizabeth C, Cubbin Catherine

机构信息

Department of Population Health, The University of Texas at Austin Dell Medical School, Austin, TX 78712, USA.

Steve Hicks School of Social Work, The University of Texas at Austin, Austin, TX 78712, USA.

出版信息

Int J Environ Res Public Health. 2024 Dec 21;21(12):1706. doi: 10.3390/ijerph21121706.

DOI:10.3390/ijerph21121706
PMID:39767545
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11727678/
Abstract

A growing literature within the field of air pollution exposure assessment addresses the issue of environmental justice. Leveraging the increasing availability of exposure datasets with broad spatial coverage and high spatial resolution, a number of works have assessed inequalities in exposure across racial/ethnic and other socioeconomic groupings. However, environmental justice research presents the additional need to evaluate exposure inequity-inequality that is systematic, unfair, and avoidable-which may be framed in several ways. We discuss these framings and describe inequality and inequity conclusions provided from several contrasting approaches drawn from recent work. We recommend that future work addressing environmental justice interventions include complementary "Exposure-driven" and "Socially weighted" metrics, taking an intersectional view of areas and social groups that are both disproportionately impacted by pollution and are impacted by additional health risks resulting from structural racism and consider implications for environmental justice beyond distributional equity.

摘要

空气污染暴露评估领域中越来越多的文献涉及环境正义问题。利用具有广泛空间覆盖范围和高空间分辨率的暴露数据集的可用性不断提高,一些研究评估了不同种族/族裔和其他社会经济群体之间的暴露不平等。然而,环境正义研究还需要评估暴露不公平——即系统性、不公平且可避免的不平等——这可以通过多种方式来界定。我们讨论这些界定方式,并描述从近期研究中采用的几种对比方法得出的不平等和不公平结论。我们建议,未来涉及环境正义干预措施的研究应包括互补的“暴露驱动”和“社会加权”指标,从交叉视角看待那些受到污染影响尤为严重且因结构性种族主义而面临额外健康风险的地区和社会群体,并考虑除分配公平之外的环境正义影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ba7/11727678/7f78000a0d33/ijerph-21-01706-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ba7/11727678/c152c07d4179/ijerph-21-01706-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ba7/11727678/7f78000a0d33/ijerph-21-01706-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ba7/11727678/c152c07d4179/ijerph-21-01706-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ba7/11727678/7f78000a0d33/ijerph-21-01706-g002.jpg

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本文引用的文献

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An exploratory analysis of sociodemographic characteristics with ultrafine particle concentrations in Boston, MA.在马萨诸塞州波士顿,对超细微粒浓度的社会人口特征进行探索性分析。
PLoS One. 2022 Mar 30;17(3):e0263434. doi: 10.1371/journal.pone.0263434. eCollection 2022.
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An applied environmental justice framework for exposure science.应用于暴露科学的环境正义框架。
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选择数据分析和建模方法以支持空气污染和环境正义调查:批判性回顾和指导框架。
Environ Sci Technol. 2022 Mar 1;56(5):2843-2860. doi: 10.1021/acs.est.1c01739. Epub 2022 Feb 8.
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Air pollution exposure disparities across US population and income groups.美国人口和收入群体的空气污染暴露差距。
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Accounting for Health Risk Inequality in Regulatory Impact Analysis: Barriers and Opportunities.健康风险不平等在监管影响分析中的核算:障碍与机遇。
Risk Anal. 2021 Apr;41(4):610-618. doi: 10.1111/risa.13714. Epub 2021 Feb 13.
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Examining PM concentrations and exposure using multiple models.使用多种模型检测 PM 浓度和暴露情况。
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