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Dressel IM, Zhang S, Demetillo MAG, Yu S, Fields K, Judd LM, Nowlan CR, Sun K, Kotsakis A, Turner AJ, Pusede SE. Neighborhood-Level Nitrogen Dioxide Inequalities Contribute to Surface Ozone Variability in Houston, Texas. ACS ES&T AIR 2024; 1:973-988. [PMID: 39295746 PMCID: PMC11406531 DOI: 10.1021/acsestair.4c00009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Revised: 07/19/2024] [Accepted: 07/19/2024] [Indexed: 09/21/2024]
Abstract
In Houston, Texas, nitrogen dioxide (NO2) air pollution disproportionately affects Black, Latinx, and Asian communities, and high ozone (O3) days are frequent. There is limited knowledge of how NO2 inequalities vary in urban air quality contexts, in part from the lack of time-varying neighborhood-level NO2 measurements. First, we demonstrate that daily TROPOspheric Monitoring Instrument (TROPOMI) NO2 tropospheric vertical column densities (TVCDs) resolve a major portion of census tract-scale NO2 inequalities in Houston, comparing NO2 inequalities based on TROPOMI TVCDs and spatiotemporally coincident airborne remote sensing (250 m × 560 m) from the NASA TRacking Aerosol Convection ExpeRiment-Air Quality (TRACER-AQ). We further evaluate the application of daily TROPOMI TVCDs to census tract-scale NO2 inequalities (May 2018-November 2022). This includes explaining differences between mean daily NO2 inequalities and those based on TVCDs oversampled to 0.01° × 0.01° and showing daily NO2 column-surface relationships weaken as a function of observation separation distance. Second, census tract-scale NO2 inequalities, city-wide high O3, and mesoscale airflows are found to covary using principal component and cluster analysis. A generalized additive model of O3 mixing ratios versus NO2 inequalities reproduces established nonlinear relationships between O3 production and NO2 concentrations, providing observational evidence that neighborhood-level NO2 inequalities and O3 are coupled. Consequently, emissions controls specifically in Black, Latinx, and Asian communities will have co-benefits, reducing both NO2 disparities and high O3 days city wide.
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Affiliation(s)
- Isabella M Dressel
- Department of Environmental Sciences, University of Virginia, Charlottesville, Virginia 22904, United States
| | - Sixuan Zhang
- Department of Environmental Sciences, University of Virginia, Charlottesville, Virginia 22904, United States
| | - Mary Angelique G Demetillo
- Department of Environmental Sciences, University of Virginia, Charlottesville, Virginia 22904, United States
- NASA Langley Research Center, Hampton, Virginia 23681, United States
| | - Shan Yu
- Department of Statistics, University of Virginia, Charlottesville, Virginia 22904, United States
| | - Kimberly Fields
- Carter G. Woodson Institute for African American and African Studies, University of Virginia, Charlottesville, Virginia 22904, United States
| | - Laura M Judd
- NASA Langley Research Center, Hampton, Virginia 23681, United States
| | - Caroline R Nowlan
- Atomic and Molecular Physics Division, Center for Astrophysics | Harvard & Smithsonian, Cambridge, Massachusetts 02138, United States
| | - Kang Sun
- Department of Civil, Structural and Environmental Engineering, University at Buffalo, Buffalo, New York 14260, United States
- Research and Education in eNergy, Environment and Water (RENEW) Institute, University at Buffalo, Buffalo, New York 14260, United States
| | - Alexander Kotsakis
- NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, United States
| | - Alexander J Turner
- Department of Atmospheric Sciences, University of Washington, Seattle, Washington 98195, United States
| | - Sally E Pusede
- Department of Environmental Sciences, University of Virginia, Charlottesville, Virginia 22904, United States
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Koolik LH, Alvarado Á, Budahn A, Plummer L, Marshall JD, Apte JS. PM 2.5 exposure disparities persist despite strict vehicle emissions controls in California. SCIENCE ADVANCES 2024; 10:eadn8544. [PMID: 39259801 PMCID: PMC11389777 DOI: 10.1126/sciadv.adn8544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 07/31/2024] [Indexed: 09/13/2024]
Abstract
As policymakers increasingly focus on environmental justice, a key question is whether emissions reductions aimed at addressing air quality or climate change can also ameliorate persistent air pollution exposure disparities. We examine evidence from California's aggressive vehicle emissions control policy from 2000 to 2019. We find a 65% reduction in modeled statewide average exposure to PM2.5 from on-road vehicles, yet for people of color and overburdened community residents, relative exposure disparities increased. Light-duty vehicle emissions are the main driver of the exposure and exposure disparity, although smaller contributions from heavy-duty vehicles especially affect some overburdened groups. Our findings suggest that a continued trend of emissions reductions will likely reduce concentrations and absolute disparity but may not reduce relative disparities without greater attention to the systemic factors leading to this disparity.
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Affiliation(s)
- Libby H Koolik
- Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley CA 94720, USA
| | - Álvaro Alvarado
- California Office of Environmental Health Hazard Assessment, Sacramento, CA 95814, USA
| | - Amy Budahn
- California Office of Environmental Health Hazard Assessment, Sacramento, CA 95814, USA
| | - Laurel Plummer
- California Office of Environmental Health Hazard Assessment, Sacramento, CA 95814, USA
| | - Julian D Marshall
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA
| | - Joshua S Apte
- Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley CA 94720, USA
- School of Public Health, University of California, Berkeley, Berkeley, CA 94704, USA
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3
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Nyawanda BO, Khagayi S, Obor D, Odhiambo SB, Beloconi A, Otieno NA, Bigogo G, Kariuki S, Munga S, Vounatsou P. The effects of climatic and non-climatic factors on malaria mortality at different spatial scales in western Kenya, 2008-2019. BMJ Glob Health 2024; 9:e014614. [PMID: 39244219 PMCID: PMC11381700 DOI: 10.1136/bmjgh-2023-014614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 08/22/2024] [Indexed: 09/09/2024] Open
Abstract
BACKGROUND Malaria mortality is influenced by several factors including climatic and environmental factors, interventions, socioeconomic status (SES) and access to health systems. Here, we investigated the joint effects of climatic and non-climatic factors on under-five malaria mortality at different spatial scales using data from a Health and Demographic Surveillance System (HDSS) in western Kenya. METHODS We fitted Bayesian spatiotemporal (zero-inflated) negative binomial models to monthly mortality data aggregated at the village scale and over the catchment areas of the health facilities within the HDSS, between 2008 and 2019. First order autoregressive temporal and conditional autoregressive spatial processes were included as random effects to account for temporal and spatial variation. Remotely sensed climatic and environmental variables, bed net use, SES, travel time to health facilities, proximity from water bodies/streams and altitude were included in the models to assess their association with malaria mortality. RESULTS Increase in rainfall (mortality rate ratio (MRR)=1.12, 95% Bayesian credible interval (BCI): 1.04-1.20), Normalized Difference Vegetation Index (MRR=1.16, 95% BCI: 1.06-1.28), crop cover (MRR=1.17, 95% BCI: 1.11-1.24) and travel time to the hospital (MRR=1.09, 95% BCI: 1.04-1.13) were associated with increased mortality, whereas increase in bed net use (MRR=0.84, 95% BCI: 0.70-1.00), distance to the nearest streams (MRR=0.89, 95% BCI: 0.83-0.96), SES (MRR=0.95, 95% BCI: 0.91-1.00) and altitude (MRR=0.86, 95% BCI: 0.81-0.90) were associated with lower mortality. The effects of travel time and SES were no longer significant when data was aggregated at the health facility catchment level. CONCLUSION Despite the relatively small size of the HDSS, there was spatial variation in malaria mortality that peaked every May-June. The rapid decline in malaria mortality was associated with bed nets, and finer spatial scale analysis identified additional important variables. Time and spatially targeted control interventions may be helpful, and fine spatial scales should be considered when data are available.
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Affiliation(s)
- Bryan O Nyawanda
- Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Sammy Khagayi
- Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya
| | - David Obor
- Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya
| | - Steve B Odhiambo
- Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya
| | - Anton Beloconi
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Nancy A Otieno
- Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya
| | - Godfrey Bigogo
- Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya
| | - Simon Kariuki
- Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya
| | - Stephen Munga
- Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya
| | - Penelope Vounatsou
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
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Prasanth S, Oloyede N, Zhang X, Chen K, Carrión D. Simulating desegregation through affordable housing development: An environmental health impact assessment of Connecticut zoning law. Health Place 2024; 88:103277. [PMID: 38781859 PMCID: PMC11190844 DOI: 10.1016/j.healthplace.2024.103277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2024] [Revised: 04/22/2024] [Accepted: 05/16/2024] [Indexed: 05/25/2024]
Abstract
Residential segregation drives exposure and health inequities. We projected the mortality impacts among low-income residents of leveraging an existing 10% affordable housing target as a case study of desegregation policy. We simulated movement into newly allocated housing, quantified changes in six ambient environmental exposures, and used exposure-response functions to estimate deaths averted. Across 1000 simulations, in one year, we found on average 169 (95% CI: 84, 255) deaths averted from changes in greenness, 71 (49, 94) deaths averted from NO2, 9 (4, 14) deaths averted from noise, 1 (1, 2) excess death from O3, and 2 (1, 2) excess deaths from PM2.5, with rates of deaths averted highest among non-Hispanic Black and non-Hispanic White residents. Strengthening desegregation policy may advance environmental health equity.
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Affiliation(s)
- Saira Prasanth
- Department of Chronic Disease Epidemiology, Yale University School of Public Health, 60 College Street, New Haven, CT, 06520, United States; Yale Center on Climate Change and Health, Yale University School of Public Health, 60 College Street, New Haven, CT, 06520, United States.
| | - Nire Oloyede
- Yale College, Yale University, 1 Prospect Street, New Haven, CT, 06511, United States.
| | - Xuezhixing Zhang
- Yale Center on Climate Change and Health, Yale University School of Public Health, 60 College Street, New Haven, CT, 06520, United States; Department of Environmental Health Sciences, Yale University School of Public Health, 60 College Street, New Haven, CT, 06520, United States.
| | - Kai Chen
- Yale Center on Climate Change and Health, Yale University School of Public Health, 60 College Street, New Haven, CT, 06520, United States; Department of Environmental Health Sciences, Yale University School of Public Health, 60 College Street, New Haven, CT, 06520, United States.
| | - Daniel Carrión
- Yale Center on Climate Change and Health, Yale University School of Public Health, 60 College Street, New Haven, CT, 06520, United States; Department of Environmental Health Sciences, Yale University School of Public Health, 60 College Street, New Haven, CT, 06520, United States.
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5
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McCann ZH, Chang HH, D'Souza R, Scovronick N, Ebelt S. Assessment of census-tract level socioeconomic position as a modifier of the relationship between short-term PM 2.5 exposure and cardiovascular emergency department visits in Missouri. J Epidemiol Community Health 2024; 78:296-302. [PMID: 38302278 PMCID: PMC11006568 DOI: 10.1136/jech-2023-221438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 01/16/2024] [Indexed: 02/03/2024]
Abstract
INTRODUCTION Ambient particulate matter ≤ 2.5 µm in aerodynamic diameter (PM2.5) exposure elevates the risk for cardiovascular disease morbidity (CVDM). The aim of this study is to characterise which area-level measures of socioeconomic position (SEP) modify the relationship between PM2.5 exposure and CVDM in Missouri at the census-tract (CT) level. METHODS We use individual level Missouri emergency department (ED) admissions data (n=3 284 956), modelled PM2.5 data, and yearly CT data from 2012 to 2016 to conduct a two-stage analysis. Stage one uses a case-crossover approach with conditional logistic regression to establish the baseline risk of ED visits associated with IQR changes in PM2.5. In the second stage, we use multivariate metaregression to examine how CT-level SEP modifies the relationship between ambient PM2.5 exposure and CVDM. RESULTS We find that overall, ambient PM2.5 exposure is associated with increased risk for CVDM. We test effect modification in statewide and urban CTs, and in the warm season only. Effect modification results suggest that among SEP measures, poverty is most consistently associated with increased risk for CVDM. For example, across Missouri, the highest poverty CTs are at an elevated risk for CVDM (OR=1.010 (95% CI 1.007 to 1.014)) compared with the lowest poverty CTs (OR=1.004 (95% CI 1.000 to 1.008)). Other SEP modifiers generally display an inconsistent or null effect. CONCLUSION Overall, we find some evidence that area-level SEP modifies the relationship between ambient PM2.5 exposure and CVDM, and suggest that the relationship between air-pollution, area-level SEP and CVDM may be sensitive to spatial scale.
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Affiliation(s)
- Zachary H McCann
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Howard H Chang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory Univeristy, Atlanta, Georgia, USA
| | - Rohan D'Souza
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory Univeristy, Atlanta, Georgia, USA
| | - Noah Scovronick
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Stefanie Ebelt
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
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6
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Giang A, Edwards MR, Fletcher SM, Gardner-Frolick R, Gryba R, Mathias JD, Venier-Cambron C, Anderies JM, Berglund E, Carley S, Erickson JS, Grubert E, Hadjimichael A, Hill J, Mayfield E, Nock D, Pikok KK, Saari RK, Samudio Lezcano M, Siddiqi A, Skerker JB, Tessum CW. Equity and modeling in sustainability science: Examples and opportunities throughout the process. Proc Natl Acad Sci U S A 2024; 121:e2215688121. [PMID: 38498705 PMCID: PMC10990085 DOI: 10.1073/pnas.2215688121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/20/2024] Open
Abstract
Equity is core to sustainability, but current interventions to enhance sustainability often fall short in adequately addressing this linkage. Models are important tools for informing action, and their development and use present opportunities to center equity in process and outcomes. This Perspective highlights progress in integrating equity into systems modeling in sustainability science, as well as key challenges, tensions, and future directions. We present a conceptual framework for equity in systems modeling, focused on its distributional, procedural, and recognitional dimensions. We discuss examples of how modelers engage with these different dimensions throughout the modeling process and from across a range of modeling approaches and topics, including water resources, energy systems, air quality, and conservation. Synthesizing across these examples, we identify significant advances in enhancing procedural and recognitional equity by reframing models as tools to explore pluralism in worldviews and knowledge systems; enabling models to better represent distributional inequity through new computational techniques and data sources; investigating the dynamics that can drive inequities by linking different modeling approaches; and developing more nuanced metrics for assessing equity outcomes. We also identify important future directions, such as an increased focus on using models to identify pathways to transform underlying conditions that lead to inequities and move toward desired futures. By looking at examples across the diverse fields within sustainability science, we argue that there are valuable opportunities for mutual learning on how to use models more effectively as tools to support sustainable and equitable futures.
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Affiliation(s)
- Amanda Giang
- Institute for Resources, Environment and Sustainability, University of British Columbia, Vancouver, BCV6T 1Z4, Canada
- Department of Mechanical Engineering, University of British Columbia, Vancouver, BCV6T 1Z4, Canada
| | - Morgan R. Edwards
- La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI53706
- Nelson Institute Center for Sustainability and the Global Environment, University of Wisconsin-Madison, Madison, WI53706
| | - Sarah M. Fletcher
- Department of Civil and Environmental Engineering, Stanford University, Stanford, CA94305
- Woods Institute for the Environment, Stanford University, Stanford, CA94305
| | - Rivkah Gardner-Frolick
- Department of Mechanical Engineering, University of British Columbia, Vancouver, BCV6T 1Z4, Canada
| | - Rowenna Gryba
- Department of Statistics, University of British Columbia, Vancouver, BCV6T 1Z4, Canada
- Department of Geography, University of British Columbia, Vancouver, BCV6T 1Z4, Canada
- Institute for the Oceans and Fisheries, University of British Columbia, Vancouver, BCV6T 1Z4, Canada
| | - Jean-Denis Mathias
- Université Clermont Auvergne, INRAE, UR LISC, Centre de Clermont-Ferrand, AubièreF-63178, France
| | - Camille Venier-Cambron
- Department of Environmental Geography, Instituut voor Milieuvraagstukken, Vrije Universiteit Amsterdam, Amsterdam1081 HV, The Netherlands
| | - John M. Anderies
- School of Sustainability, Arizona State University, Tempe, AZ85287
| | - Emily Berglund
- Department of Civil Construction, and Environmental Engineering, North Carolina State University, Raleigh, NC27695
| | - Sanya Carley
- Kleinman Center for Energy Policy, Stuart Weitzman School of Design, Department of City Planning, University of Pennsylvania, Philadelphia, PA19104
| | - Jacob Shimkus Erickson
- Nelson Institute Center for Sustainability and the Global Environment, University of Wisconsin-Madison, Madison, WI53706
- Department of Agricultural and Applied Economics, University of Wisconsin-Madison, Madison, WI53706
| | - Emily Grubert
- Keough School of Global Affairs, University of Notre Dame, Notre Dame, IN46556
| | - Antonia Hadjimichael
- Department of Geosciences, College of Earth and Mineral Sciences, Pennsylvania State University, University Park, PA16802
- Earth and Environmental Systems Institute, College of Earth and Mineral Sciences, Pennsylvania State University, University Park, PA16802
| | - Jason Hill
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, Minneapolis, MN55455
| | - Erin Mayfield
- Thayer School of Engineering, Dartmouth College, Hanover, NH03755
| | - Destenie Nock
- Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA15213
| | - Kimberly Kivvaq Pikok
- International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK99775
| | - Rebecca K. Saari
- Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ONN2L 3G1, Canada
| | - Mateo Samudio Lezcano
- Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA15213
| | - Afreen Siddiqi
- Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA02139
| | - Jennifer B. Skerker
- Department of Civil and Environmental Engineering, Stanford University, Stanford, CA94305
| | - Christopher W. Tessum
- Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL61801
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Bradley A, Croes BE, Harkins C, McDonald BC, de Gouw JA. Air Pollution Inequality in the Denver Metroplex and its Relationship to Historical Redlining. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:4226-4236. [PMID: 38380822 PMCID: PMC10919081 DOI: 10.1021/acs.est.3c03230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 01/30/2024] [Accepted: 01/31/2024] [Indexed: 02/22/2024]
Abstract
Prior studies have shown that people of color (POC) in the United States are exposed to higher levels of pollution than non-Hispanic White people. We show that the city of Denver, Colorado, displays similar race- and ethnicity-based air pollution disparities by using a combination of high-resolution satellite data, air pollution modeling, historical demographic information, and areal apportionment techniques. TROPOMI NO2 columns and modeled PM2.5 concentrations from 2019 are higher in communities subject to redlining. We calculated and compared Spearman coefficients for pollutants and race at the census tract level for every city that underwent redlining to contextualize the disparities in Denver. We find that the location of polluting infrastructure leads to higher populations of POC living near point sources, including 40% higher Hispanic and Latino populations. This influences pollution distribution, with annual average PM2.5 surface concentrations of 6.5 μg m-3 in census tracts with 0-5% Hispanic and Latino populations and 7.5 μg m-3 in census tracts with 60-65% Hispanic and Latino populations. Traffic analysis and emission inventory data show that POC are more likely to live near busy highways. Unequal spatial distribution of pollution sources and POC have allowed for pollution disparities to persist despite attempts by the city to rectify them. Finally, we identify the core causes of the pollution disparities to provide direction for remediation.
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Affiliation(s)
- Alexander
C. Bradley
- University
of Colorado Boulder, Boulder, Colorado 80309, United States
- Cooperative
Institute for Research in Environmental Sciences, Boulder, Colorado 80309, United States
| | - Bart E. Croes
- Cooperative
Institute for Research in Environmental Sciences, Boulder, Colorado 80309, United States
| | - Colin Harkins
- Cooperative
Institute for Research in Environmental Sciences, Boulder, Colorado 80309, United States
- Chemical
Sciences Laboratory, National Oceanic and
Atmospheric Administration, Boulder, Colorado 80305, United States
| | - Brian C. McDonald
- Chemical
Sciences Laboratory, National Oceanic and
Atmospheric Administration, Boulder, Colorado 80305, United States
| | - Joost A. de Gouw
- University
of Colorado Boulder, Boulder, Colorado 80309, United States
- Cooperative
Institute for Research in Environmental Sciences, Boulder, Colorado 80309, United States
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8
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Estien CO, Wilkinson CE, Morello-Frosch R, Schell CJ. Historical Redlining Is Associated with Disparities in Environmental Quality across California. ENVIRONMENTAL SCIENCE & TECHNOLOGY LETTERS 2024; 11:54-59. [PMID: 38371654 PMCID: PMC10867848 DOI: 10.1021/acs.estlett.3c00870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 01/10/2024] [Accepted: 01/17/2024] [Indexed: 02/20/2024]
Abstract
Historical policies have been shown to underpin environmental quality. In the 1930s, the federal Home Owners' Loan Corporation (HOLC) developed the most comprehensive archive of neighborhoods that would have been redlined by local lenders and the Federal Housing Administration, often applying racist criteria. Our study explored how redlining is associated with environmental quality across eight California cities. We integrated HOLC's graded maps [grades A (i.e., "best" and "greenlined"), B, C, and D (i.e., "hazardous" and "redlined")] with 10 environmental hazards using data from 2018 to 2021 to quantify the spatial overlap among redlined neighborhoods and environmental hazards. We found that formerly redlined neighborhoods have poorer environmental quality relative to those of other HOLC grades via higher pollution, more noise, less vegetation, and elevated temperatures. Additionally, we found that intraurban disparities were consistently worse for formerly redlined neighborhoods across environmental hazards, with redlined neighborhoods having higher pollution burdens (77% of redlined neighborhoods vs 18% of greenlined neighborhoods), more noise (72% vs 18%), less vegetation (86% vs 12%), and elevated temperature (72% vs 20%), than their respective city's average. Our findings highlight that redlining, a policy abolished in 1968, remains an environmental justice concern by shaping the environmental quality of Californian urban neighborhoods.
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Affiliation(s)
- Cesar O. Estien
- Department
of Environmental Science, Policy, and Management, University of California−Berkeley, 130 Mulford Hall, Berkeley, California 94720, United States
| | - Christine E. Wilkinson
- Department
of Environmental Science, Policy, and Management, University of California−Berkeley, 130 Mulford Hall, Berkeley, California 94720, United States
- California
Academy of Sciences, 55 Music Concourse Drive, San Francisco, California 94118, United States
| | - Rachel Morello-Frosch
- Department
of Environmental Science, Policy, and Management, University of California−Berkeley, 130 Mulford Hall, Berkeley, California 94720, United States
- School
of Public Health, University of California−Berkeley, 2121 Berkeley Way, Berkeley, California 94720, United States
| | - Christopher J. Schell
- Department
of Environmental Science, Policy, and Management, University of California−Berkeley, 130 Mulford Hall, Berkeley, California 94720, United States
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9
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Chambliss SE, Campmier MJ, Audirac M, Apte JS, Zigler CM. Local exposure misclassification in national models: relationships with urban infrastructure and demographics. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2023:10.1038/s41370-023-00624-z. [PMID: 38135708 DOI: 10.1038/s41370-023-00624-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 11/27/2023] [Accepted: 11/28/2023] [Indexed: 12/24/2023]
Abstract
BACKGROUND National-scale linear regression-based modeling may mischaracterize localized patterns, including hyperlocal peaks and neighborhood- to regional-scale gradients. For studies focused on within-city differences, this mischaracterization poses a risk of exposure misclassification, affecting epidemiological and environmental justice conclusions. OBJECTIVE Characterize the difference between intraurban pollution patterns predicted by national-scale land use regression modeling and observation-based estimates within a localized domain and examine the relationship between that difference and urban infrastructure and demographics. METHODS We compare highly resolved (0.01 km2) observations of NO2 mixing ratio and ultrafine particle (UFP) count obtained via mobile monitoring with national model predictions in thirteen neighborhoods in the San Francisco Bay Area. Grid cell-level divergence between modeled and observed concentrations is termed "localized difference." We use a flexible machine learning modeling technique, Bayesian Additive Regression Trees, to investigate potentially nonlinear relationships between discrepancy between localized difference and known local emission sources as well as census block group racial/ethnic composition. RESULTS We find that observed local pollution extremes are not represented by land use regression predictions and that observed UFP count significantly exceeds regression predictions. Machine learning models show significant nonlinear relationships among localized differences between predictions and observations and the density of several types of pollution-related infrastructure (roadways, commercial and industrial operations). In addition, localized difference was greater in areas with higher population density and a lower share of white non-Hispanic residents, indicating that exposure misclassification by national models differs among subpopulations. IMPACT Comparing national-scale pollution predictions with hyperlocal observations in the San Francisco Bay Area, we find greater discrepancies near major roadways and food service locations and systematic underestimation of concentrations in neighborhoods with a lower share of non-Hispanic white residents. These findings carry implications for using national-scale models in intraurban epidemiological and environmental justice applications and establish the potential utility of supplementing large-scale estimates with publicly available urban infrastructure and pollution source information.
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Affiliation(s)
- Sarah E Chambliss
- Department of Statistics and Data Sciences, The University of Texas at Austin, Austin, TX, 78712, USA.
| | - Mark Joseph Campmier
- Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Michelle Audirac
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Joshua S Apte
- Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, CA, 94720, USA
- School of Public Health, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Corwin M Zigler
- Department of Statistics and Data Sciences, The University of Texas at Austin, Austin, TX, 78712, USA
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10
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Nair AA, Lin S, Luo G, Ryan I, Qi Q, Deng X, Yu F. Environmental exposure disparities in ultrafine particles and PM 2.5 by urbanicity and socio-demographics in New York state, 2013-2020. ENVIRONMENTAL RESEARCH 2023; 239:117246. [PMID: 37806474 DOI: 10.1016/j.envres.2023.117246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 09/07/2023] [Accepted: 09/17/2023] [Indexed: 10/10/2023]
Abstract
BACKGROUND The spatiotemporal and demographic disparities in exposure to ultrafine particles (UFP; number concentrations of particulate matter (PM) with diameter ≤0.1 μm), a key subcomponent of fine aerosols (PM2.5; mass concentrations of PM ≤ 2.5 μm), have not been well studied. OBJECTIVE To quantify and compare the aerosol pollutant exposure disparities for UFP and PM2.5 by socio-demographic factors in New York State (NYS). METHODS Ambient atmospheric UFP and PM2.5 were quantified using a global three-dimensional model of chemical transport with state-of-the-science aerosol microphysical processes validated extensively with observations. We matched these to U.S. census demographic data for varied spatial scales (state, county, county subdivision) and derived population-weighted aerosol exposure estimates. Aerosol exposure disparities for each demographic and socioeconomic (SES) indicator, with a focus on race-ethnicity and income, were quantified for the period 2013-2020. RESULTS The average NYS resident was exposed to 4451 #·cm-3 UFP and 7.87 μg·m-3 PM2.5 in 2013-2020, but minority race-ethnicity groups were invariably exposed to greater daily aerosol pollution (UFP: +75.0% & PM2.5: +16.2%). UFP has increased since 2017 and is temporally and seasonally out-of-phase with PM2.5. Race-ethnicity exposure disparities for PM2.5 have declined over time; by -6% from 2013 to 2017 and plateaued thereafter despite its decreasing concentrations. In contrast, these disparities have increased (+12.5-13.5%) for UFP. The aerosol pollution exposure disparities were the highest for low-income minorities and were more amplified for UFP than PM2.5. DISCUSSION: We identified large disparities in aerosol pollution exposure by urbanization level and socio-demographics in NYS residents. Jurisdictions with higher proportions of race-ethnicity minorities, low-income residents, and greater urbanization were disproportionately exposed to higher concentrations of UFP and PM2.5 than other NYS residents. These race-ethnicity exposure disparities were much larger, more disproportionate, and unabating over time for UFP compared to PM2.5 across various income strata and levels of urbanicity.
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Affiliation(s)
- Arshad Arjunan Nair
- Atmospheric Sciences Research Center, University at Albany, State University of New York, Albany, NY 12226, USA.
| | - Shao Lin
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, NY 12144, USA; Department of Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, NY 12144, USA
| | - Gan Luo
- Atmospheric Sciences Research Center, University at Albany, State University of New York, Albany, NY 12226, USA
| | - Ian Ryan
- Department of Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, NY 12144, USA
| | - Quan Qi
- Department of Economics, University at Albany, State University of New York, Albany, NY 12222, USA
| | - Xinlei Deng
- Department of Epidemiology and Biostatistics, University at Albany, State University of New York, Rensselaer, NY 12144, USA
| | - Fangqun Yu
- Atmospheric Sciences Research Center, University at Albany, State University of New York, Albany, NY 12226, USA.
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11
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Camilleri SF, Kerr GH, Anenberg SC, Horton DE. All-Cause NO 2-Attributable Mortality Burden and Associated Racial and Ethnic Disparities in the United States. ENVIRONMENTAL SCIENCE & TECHNOLOGY LETTERS 2023; 10:1159-1164. [PMID: 38106529 PMCID: PMC10720462 DOI: 10.1021/acs.estlett.3c00500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 10/19/2023] [Accepted: 10/23/2023] [Indexed: 12/19/2023]
Abstract
Nitrogen dioxide (NO2) is a regulated pollutant that is associated with numerous health impacts. Recent advances in epidemiology indicate high confidence linking NO2 exposure with increased mortality, an association that recent studies suggest persists even at concentrations below regulatory thresholds. While large disparities in NO2 exposure among population subgroups have been reported, U.S. NO2-attributable mortality rates and their disparities remain unquantified. Here we provide the first estimate of NO2-attributable all-cause mortality across the contiguous U.S. (CONUS) at the census tract-level. We leverage fine-scale, satellite-informed, land use regression model NO2 concentrations and census tract-level baseline mortality data to characterize the associated disparities among different racial/ethnic subgroups. Across CONUS, we estimate that the NO2-attributable all-cause mortality is ∼170,850 (95% confidence interval: 43,970, 251,330) premature deaths yr-1 with large variability across census tracts and within individual cities. Additionally, we find that higher NO2 concentrations and underlying susceptibilities for predominately Black communities lead to NO2-attributable mortality rates that are ∼47% higher compared to CONUS-wide average rates. Our results highlight the substantial U.S. NO2 mortality burden, particularly in marginalized communities, and motivate adoption of more stringent standards to protect public health.
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Affiliation(s)
- Sara F Camilleri
- Department
of Earth and Planetary Sciences, Northwestern
University, Evanston, Illinois 60208, United States
| | - Gaige Hunter Kerr
- Department
of Environmental and Occupational Health, The George Washington University, Washington, DC 20052, United States
| | - Susan C Anenberg
- Department
of Environmental and Occupational Health, The George Washington University, Washington, DC 20052, United States
| | - Daniel E Horton
- Department
of Earth and Planetary Sciences, Northwestern
University, Evanston, Illinois 60208, United States
- Trienens
Institute for Sustainability and Energy, Northwestern University, Evanston, Illinois 60208, United States
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12
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Kerr GH, Goldberg DL, Harris MH, Henderson BH, Hystad P, Roy A, Anenberg SC. Ethnoracial Disparities in Nitrogen Dioxide Pollution in the United States: Comparing Data Sets from Satellites, Models, and Monitors. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:19532-19544. [PMID: 37934506 DOI: 10.1021/acs.est.3c03999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2023]
Abstract
In the United States (U.S.), studies on nitrogen dioxide (NO2) trends and pollution-attributable health effects have historically used measurements from in situ monitors, which have limited geographical coverage and leave 66% of urban areas unmonitored. Novel tools, including remotely sensed NO2 measurements and estimates of NO2 estimates from land-use regression and photochemical models, can aid in assessing NO2 exposure gradients, leveraging their complete spatial coverage. Using these data sets, we find that Black, Hispanic, Asian, and multiracial populations experience NO2 levels 15-50% higher than the national average in 2019, whereas the non-Hispanic White population is consistently exposed to levels that are 5-15% lower than the national average. By contrast, the in situ monitoring network indicates more moderate ethnoracial NO2 disparities and different rankings of the least- to most-exposed ethnoracial population subgroup. Validating these spatially complete data sets against in situ observations reveals similar performance, indicating that all these data sets can be used to understand spatial variations in NO2. Integrating in situ monitoring, satellite data, statistical models, and photochemical models can provide a semiobservational record, complete geospatial coverage, and increasingly high spatial resolution, enhancing future efforts to characterize, map, and track exposure and inequality for highly spatially heterogeneous pollutants like NO2.
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Affiliation(s)
- Gaige Hunter Kerr
- Department of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia 20052, United States
| | - Daniel L Goldberg
- Department of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia 20052, United States
| | - Maria H Harris
- Environmental Defense Fund, 257 Park Avenue South, New York, New York 10010, United States
| | - Barron H Henderson
- U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, United States
| | - Perry Hystad
- College of Public Health and Human Sciences, Oregon State University, Corvallis, Oregon 97333, United States
| | - Ananya Roy
- Environmental Defense Fund, 257 Park Avenue South, New York, New York 10010, United States
| | - Susan C Anenberg
- Department of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia 20052, United States
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13
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Gohlke JM, Harris MH, Roy A, Thompson TM, DePaola M, Alvarez RA, Anenberg SC, Apte JS, Demetillo MAG, Dressel IM, Kerr GH, Marshall JD, Nowlan AE, Patterson RF, Pusede SE, Southerland VA, Vogel SA. State-of-the-Science Data and Methods Need to Guide Place-Based Efforts to Reduce Air Pollution Inequity. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:125003. [PMID: 38109120 PMCID: PMC10727036 DOI: 10.1289/ehp13063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 11/19/2023] [Accepted: 11/27/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND Recently enacted environmental justice policies in the United States at the state and federal level emphasize addressing place-based inequities, including persistent disparities in air pollution exposure and associated health impacts. Advances in air quality measurement, models, and analytic methods have demonstrated the importance of finer-scale data and analysis in accurately quantifying the extent of inequity in intraurban pollution exposure, although the necessary degree of spatial resolution remains a complex and context-dependent question. OBJECTIVE The objectives of this commentary were to a) discuss ways to maximize and evaluate the effectiveness of efforts to reduce air pollution disparities, and b) argue that environmental regulators must employ improved methods to project, measure, and track the distributional impacts of new policies at finer geographic and temporal scales. DISCUSSION The historic federal investments from the Inflation Reduction Act, the Infrastructure Investment and Jobs Act, and the Biden Administration's commitment to Justice40 present an unprecedented opportunity to advance climate and energy policies that deliver real reductions in pollution-related health inequities. In our opinion, scientists, advocates, policymakers, and implementing agencies must work together to harness critical advances in air quality measurements, models, and analytic methods to ensure success. https://doi.org/10.1289/EHP13063.
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Affiliation(s)
- Julia M. Gohlke
- Environmental Defense Fund, Washington, District of Columbia, USA
- Department of Population Health Sciences, Virginia Tech, Blacksburg, Virginia, USA
| | - Maria H. Harris
- Environmental Defense Fund, Washington, District of Columbia, USA
| | - Ananya Roy
- Environmental Defense Fund, Washington, District of Columbia, USA
| | | | - Mindi DePaola
- Environmental Defense Fund, Washington, District of Columbia, USA
| | - Ramón A. Alvarez
- Environmental Defense Fund, Washington, District of Columbia, USA
| | - Susan C. Anenberg
- Department of Environmental and Occupational Health, George Washington University, Washington, District of Columbia, USA
| | - Joshua S. Apte
- Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California, USA
- School of Public Health, University of California, Berkeley, Berkeley, California, USA
| | | | - Isabella M. Dressel
- Department of Environmental Sciences, University of Virginia, Charlottesville, Virginia, USA
| | - Gaige H. Kerr
- Department of Environmental and Occupational Health, George Washington University, Washington, District of Columbia, USA
| | - Julian D. Marshall
- Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, USA
| | - Aileen E. Nowlan
- Environmental Defense Fund, Washington, District of Columbia, USA
| | - Regan F. Patterson
- Department of Civil and Environmental Engineering, University of California, Los Angeles, Los Angeles, California, USA
| | - Sally E. Pusede
- Department of Environmental Sciences, University of Virginia, Charlottesville, Virginia, USA
| | - Veronica A. Southerland
- Environmental Defense Fund, Washington, District of Columbia, USA
- Department of Environmental and Occupational Health, George Washington University, Washington, District of Columbia, USA
| | - Sarah A. Vogel
- Environmental Defense Fund, Washington, District of Columbia, USA
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14
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Swetschinski L, Fong KC, Morello-Frosch R, Marshall JD, Bell ML. Exposures to ambient particulate matter are associated with reduced adult earnings potential. ENVIRONMENTAL RESEARCH 2023:116391. [PMID: 37308068 DOI: 10.1016/j.envres.2023.116391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 05/27/2023] [Accepted: 06/09/2023] [Indexed: 06/14/2023]
Abstract
The societal costs of air pollution have historically been measured in terms of premature deaths (including the corresponding values of statistical lives lost), disability-adjusted life years, and medical costs. Emerging research, however, demonstrated potential impacts of air pollution on human capital formation. Extended contact with pollutants such as airborne particulate matter among young persons whose biological systems are still developing can result in pulmonary, neurobehavioral, and birth complications, hindering academic performance as well as skills and knowledge acquisition. Using a dataset that tracks 2014-2015 incomes for 96.2% of Americans born between 1979 and 1983, we assessed the association between childhood exposure to fine particulate matter (PM2.5) and adult earnings outcomes across U.S. Census tracts. After accounting for pertinent economic covariates and regional random effects, our regression models indicate that early-life exposure to PM2.5 is associated with lower predicted income percentiles by mid-adulthood; all else equal, children raised in high pollution tracts (at the 75th percentile of PM2.5) are estimated to have approximately a 0.51 decrease in income percentile relative to children raised in low pollution tracts (at the 25th percentile of PM2.5). For a person earning the median income, this difference corresponds to a $436 lower annual income (in 2015 USD). We estimate that 2014-2015 earnings for the 1978-1983 birth cohort would have been ∼$7.18 billion higher had their childhood exposure met U.S. air quality standards for PM2.5. Stratified models show that the relationship between PM2.5 and diminished earnings is more pronounced for low-income children and for children living in rural environments. These findings raise concerns about long-term environmental and economic justice for children living in areas with poor air quality where air pollution could act as a barrier to intergenerational class equity.
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Affiliation(s)
- Lucien Swetschinski
- Yale School of the Environment, Yale University, 195 Prospect Street, New Haven, CT, 06511, USA.
| | - Kelvin C Fong
- Department of Earth and Environmental Sciences, Dalhousie University, Halifax, Nova Scotia, Canada.
| | - Rachel Morello-Frosch
- Department of Environmental Science, Policy, and Management, University of California-Berkeley, Berkeley, CA, USA; School of Public Health, University of California-Berkeley, Berkeley, CA, USA.
| | - Julian D Marshall
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA.
| | - Michelle L Bell
- Yale School of the Environment, Yale University, 195 Prospect Street, New Haven, CT, 06511, USA.
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15
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Liu J, Marshall JD. Spatial Decomposition of Air Pollution Concentrations Highlights Historical Causes for Current Exposure Disparities in the United States. ENVIRONMENTAL SCIENCE & TECHNOLOGY LETTERS 2023; 10:280-286. [PMID: 36938149 PMCID: PMC10019334 DOI: 10.1021/acs.estlett.2c00826] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 02/14/2023] [Accepted: 02/15/2023] [Indexed: 06/18/2023]
Abstract
Racial-ethnic disparities in exposure to air pollution in the United States (US) are well documented. Studies on the causes of these disparities highlight unequal systems of power and longstanding systemic racism-for example, redlining, white flight, and racial covenants-which reinforced racial segregation and wealth gaps and which concentrated polluting land uses in communities of color. Our analysis is based on empirical estimates of ambient concentrations for two important pollutants (NO2 and PM2.5). We show that spatially decomposed concentrations can be used to infer and quantify types of root causes for local- to national-scale disparities. Urban-scale segregation is important yet reflects less than half of the overall national disparities. Other historical causes of national exposure disparities include those that led current populations of Black, Asian, and Hispanic Americans to live in larger cities; those outcomes are consistent with, for example, greater economic opportunity in large cities, land-takings from non-White farmers, and racism in homesteading and between-state migration. Our results suggest that contemporary national exposure disparities in the US reflect a broad set of historical local- to national-scale mechanisms-including racist laws and actions that include, but also extend beyond, urban-scale aspects-and offer a first attempt to quantify their relative importance.
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Affiliation(s)
- Jiawen Liu
- Department
of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98125, United States
| | - Julian D. Marshall
- Department
of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98125, United States
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16
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Thind MPS, Tessum CW, Marshall JD. Environmental Health, Racial/Ethnic Health Disparity, and Climate Impacts of Inter-Regional Freight Transport in the United States. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:884-895. [PMID: 36580637 PMCID: PMC9851153 DOI: 10.1021/acs.est.2c03646] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 12/08/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
We quantify and compare three environmental impacts from inter-regional freight transportation in the contiguous United States: total mortality attributable to PM2.5 air pollution, racial-ethnic disparities in PM2.5-attributable mortality, and CO2 emissions. We compare all major freight modes (truck, rail, barge, aircraft) and routes (∼30,000 routes). Our study is the first to comprehensively compare each route separately and the first to explore racial-ethnic exposure disparities by route and mode, nationally. Impacts (health, health disparity, climate) per tonne of freight are the largest for aircraft. Among nonaircraft modes, per tonne, rail has the largest health and health-disparity impacts and the lowest climate impacts, whereas truck transport has the lowest health impacts and greatest climate impacts─an important reminder that health and climate impacts are often but not always aligned. For aircraft and truck, average monetized damages per tonne are larger for climate impacts than those for PM2.5 air pollution; for rail and barge, the reverse holds. We find that average exposures from inter-regional truck and rail are the highest for White non-Hispanic people, those from barge are the highest for Black people, and those from aircraft are the highest for people who are mixed/other race. Level of exposure and disparity among racial-ethnic groups vary in urban versus rural areas.
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Affiliation(s)
- Maninder P. S. Thind
- Department
of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98195, United States
| | - Christopher W. Tessum
- Department
of Civil and Environmental Engineering, University of Illinois at Urbana−Champaign, Urbana, Illinois 61801, United States
| | - Julian D. Marshall
- Department
of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98195, United States
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17
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Qiu M, Zigler CM, Selin NE. Impacts of wind power on air quality, premature mortality, and exposure disparities in the United States. SCIENCE ADVANCES 2022; 8:eabn8762. [PMID: 36459553 PMCID: PMC10936048 DOI: 10.1126/sciadv.abn8762] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 10/19/2022] [Indexed: 06/17/2023]
Abstract
Understanding impacts of renewable energy on air quality and associated human exposures is essential for informing future policy. We estimate the impacts of U.S. wind power on air quality and pollution exposure disparities using hourly data from 2011 to 2017 and detailed atmospheric chemistry modeling. Wind power associated with renewable portfolio standards in 2014 resulted in $2.0 billion in health benefits from improved air quality. A total of 29% and 32% of these health benefits accrued to racial/ethnic minority and low-income populations respectively, below a 2021 target by the Biden administration that 40% of the overall benefits of future federal investments flow to disadvantaged communities. Wind power worsened exposure disparities among racial and income groups in some states but improved them in others. Health benefits could be up to $8.4 billion if displacement of fossil fuel generators prioritized those with higher health damages. However, strategies that maximize total health benefits would not mitigate pollution disparities, suggesting that more targeted measures are needed.
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Affiliation(s)
- Minghao Qiu
- Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Corwin M. Zigler
- Department of Statistics and Data Sciences, University of Texas, Austin, TX, USA
| | - Noelle E. Selin
- Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
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