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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Thind MPS, Tessum CW, Marshall JD. Correction to "Environmental Health, Racial/Ethnic Health Disparity, and Climate Impacts of Inter-Regional Freight Transport in the United States". Environ Sci Technol 2024; 58:5186. [PMID: 38446129 PMCID: PMC10956488 DOI: 10.1021/acs.est.4c00052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Indexed: 03/07/2024]
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3
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Wang Y, Apte JS, Hill JD, Ivey CE, Johnson D, Min E, Morello-Frosch R, Patterson R, Robinson AL, Tessum CW, Marshall JD. Air quality policy should quantify effects on disparities. Science 2023; 381:272-274. [PMID: 37471550 DOI: 10.1126/science.adg9931] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/22/2023]
Abstract
New tools can guide US policies to better target and reduce racial and socioeconomic disparities in air pollution exposure.
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Affiliation(s)
- Yuzhou Wang
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA
| | - Joshua S Apte
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
- School of Public Health, University of California, Berkeley, CA, USA
| | - Jason D Hill
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St Paul, MN, USA
| | - Cesunica E Ivey
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
| | - Dana Johnson
- WE-ACT for Environmental Justice, Washington, DC, USA
| | | | - Rachel Morello-Frosch
- School of Public Health, University of California, Berkeley, CA, USA
- Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, USA
| | - Regan Patterson
- Department of Civil and Environmental Engineering, University of California, Los Angeles, CA, USA
| | - Allen L Robinson
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Christopher W Tessum
- Department of Civil and Environmental Engineering, University of Illinois, Urbana-Champaign, IL, USA
| | - Julian D Marshall
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA
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Gallagher CL, Holloway T, Tessum CW, Jackson CM, Heck C. Combining Satellite-Derived PM 2.5 Data and a Reduced-Form Air Quality Model to Support Air Quality Analysis in US Cities. Geohealth 2023; 7:e2023GH000788. [PMID: 37181009 PMCID: PMC10169548 DOI: 10.1029/2023gh000788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 04/03/2023] [Accepted: 04/06/2023] [Indexed: 05/16/2023]
Abstract
Air quality models can support pollution mitigation design by simulating policy scenarios and conducting source contribution analyses. The Intervention Model for Air Pollution (InMAP) is a powerful tool for equitable policy design as its variable resolution grid enables intra-urban analysis, the scale of which most environmental justice inquiries are levied. However, InMAP underestimates particulate sulfate and overestimates particulate ammonium formation, errors that limit the model's relevance to city-scale decision-making. To reduce InMAP's biases and increase its relevancy for urban-scale analysis, we calculate and apply scaling factors (SFs) based on observational data and advanced models. We consider both satellite-derived speciated PM2.5 from Washington University and ground-level monitor measurements from the U.S. Environmental Protection Agency, applied with different scaling methodologies. Relative to ground-monitor data, the unscaled InMAP model fails to meet a normalized mean bias performance goal of <±10% for most of the PM2.5 components it simulates (pSO4: -48%, pNO3: 8%, pNH4: 69%), but with city-specific SFs it achieves the goal benchmarks for every particulate species. Similarly, the normalized mean error performance goal of <35% is not met with the unscaled InMAP model (pSO4: 53%, pNO3: 52%, pNH4: 80%) but is met with the city-scaling approach (15%-27%). The city-specific scaling method also improves the R 2 value from 0.11 to 0.59 (ranging across particulate species) to the range of 0.36-0.76. Scaling increases the percent pollution contribution of electric generating units (EGUs) (nationwide 4%) and non-EGU point sources (nationwide 6%) and decreases the agriculture sector's contribution (nationwide -6%).
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Affiliation(s)
- Ciaran L. Gallagher
- Nelson Institute Center for Sustainability and the Global EnvironmentUniversity of Wisconsin—MadisonMadisonWIUSA
| | - Tracey Holloway
- Nelson Institute Center for Sustainability and the Global EnvironmentUniversity of Wisconsin—MadisonMadisonWIUSA
- Department of Atmospheric and Oceanic SciencesUniversity of Wisconsin—MadisonMadisonWIUSA
| | - Christopher W. Tessum
- Department of Civil and Environmental EngineeringUniversity of Illinois—Urbana‐ChampaignUrbanaILUSA
| | - Clara M. Jackson
- Nelson Institute Center for Sustainability and the Global EnvironmentUniversity of Wisconsin—MadisonMadisonWIUSA
| | - Colleen Heck
- Nelson Institute Center for Sustainability and the Global EnvironmentUniversity of Wisconsin—MadisonMadisonWIUSA
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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. Environ Sci Technol 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] [What about the content of this article? (0)] [Affiliation(s)] [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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6
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Wang Y, Apte JS, Hill JD, Ivey CE, Patterson RF, Robinson AL, Tessum CW, Marshall JD. Location-specific strategies for eliminating US national racial-ethnic [Formula: see text] exposure inequality. Proc Natl Acad Sci U S A 2022; 119:e2205548119. [PMID: 36279443 PMCID: PMC9636929 DOI: 10.1073/pnas.2205548119] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 08/30/2022] [Indexed: 07/22/2023] Open
Abstract
Air pollution levels in the United States have decreased dramatically over the past decades, yet national racial-ethnic exposure disparities persist. For ambient fine particulate matter ([Formula: see text]), we investigate three emission-reduction approaches and compare their optimal ability to address two goals: 1) reduce the overall population average exposure ("overall average") and 2) reduce the difference in the average exposure for the most exposed racial-ethnic group versus for the overall population ("national inequalities"). We show that national inequalities in exposure can be eliminated with minor emission reductions (optimal: ~1% of total emissions) if they target specific locations. In contrast, achieving that outcome using existing regulatory strategies would require eliminating essentially all emissions (if targeting specific economic sectors) or is not possible (if requiring urban regions to meet concentration standards). Lastly, we do not find a trade-off between the two goals (i.e., reducing overall average and reducing national inequalities); rather, the approach that does the best for reducing national inequalities (i.e., location-specific strategies) also does as well as or better than the other two approaches (i.e., sector-specific and meeting concentration standards) for reducing overall averages. Overall, our findings suggest that incorporating location-specific emissions reductions into the US air quality regulatory framework 1) is crucial for eliminating long-standing national average exposure disparities by race-ethnicity and 2) can benefit overall average exposures as much as or more than the sector-specific and concentration-standards approaches.
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Affiliation(s)
- Yuzhou Wang
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195
| | - Joshua S. Apte
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA 94720
- School of Public Health, University of California, Berkeley, CA 94720
| | - Jason D. Hill
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN 55108
| | - Cesunica E. Ivey
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA 94720
| | - Regan F. Patterson
- Center for Policy Analysis and Research, Congressional Black Caucus Foundation, Washington, DC 20036
| | - Allen L. Robinson
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213
| | - Christopher W. Tessum
- Department of Civil and Environmental Engineering, University of Illinois, Urbana, IL 61801
| | - Julian D. Marshall
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195
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Tessum MW, Anenberg SC, Chafe ZA, Henze DK, Kleiman G, Kheirbek I, Marshall JD, Tessum CW. Sources of ambient PM 2.5 exposure in 96 global cities. Atmos Environ (1994) 2022; 286:119234. [PMID: 36193038 PMCID: PMC9297293 DOI: 10.1016/j.atmosenv.2022.119234] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 06/03/2022] [Accepted: 06/06/2022] [Indexed: 05/28/2023]
Abstract
To improve air quality, knowledge of the sources and locations of air pollutant emissions is critical. However, for many global cities, no previous estimates exist of how much exposure to fine particulate matter (PM2.5), the largest environmental cause of mortality, is caused by emissions within the city vs. outside its boundaries. We use the Intervention Model for Air Pollution (InMAP) global-through-urban reduced complexity air quality model with a high-resolution, global inventory of pollutant emissions to quantify the contribution of emissions by source type and location for 96 global cities. Among these cities, we find that the fraction of PM2.5 exposure caused by within-city emissions varies widely (μ = 37%; σ = 22%) and is not well-explained by surrounding population density. The list of most-important sources also varies by city. Compared to a more mechanistically detailed model, InMAP predicts urban measured concentrations with lower bias and error but also lower correlation. Predictive accuracy in urban areas is not particularly high with either model, suggesting an opportunity for improving global urban air emission inventories. We expect the results herein can be useful as a screening tool for policy options and, in the absence of available resources for further analysis, to inform policy action to improve public health.
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Affiliation(s)
- Mei W. Tessum
- Department of Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Susan C. Anenberg
- Department of Environmental and Occupational Health, George Washington University, Washington, DC, United States
| | - Zoe A. Chafe
- C40 Cities Climate Leadership Group Inc., New York, NY, United States
| | - Daven K. Henze
- Department of Mechanical Engineering, University of Colorado, Boulder, CO, United States
| | | | - Iyad Kheirbek
- C40 Cities Climate Leadership Group Inc., New York, NY, United States
| | - Julian D. Marshall
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, United States
| | - Christopher W. Tessum
- Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States
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D’Evelyn SM, Jung J, Alvarado E, Baumgartner J, Caligiuri P, Hagmann RK, Henderson SB, Hessburg PF, Hopkins S, Kasner EJ, Krawchuk MA, Krenz JE, Lydersen JM, Marlier ME, Masuda YJ, Metlen K, Mittelstaedt G, Prichard SJ, Schollaert CL, Smith EB, Stevens JT, Tessum CW, Reeb-Whitaker C, Wilkins JL, Wolff NH, Wood LM, Haugo RD, Spector JT. Wildfire, Smoke Exposure, Human Health, and Environmental Justice Need to be Integrated into Forest Restoration and Management. Curr Environ Health Rep 2022; 9:366-385. [PMID: 35524066 PMCID: PMC9076366 DOI: 10.1007/s40572-022-00355-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/08/2022] [Indexed: 02/03/2023]
Abstract
PURPOSE OF REVIEW Increasing wildfire size and severity across the western United States has created an environmental and social crisis that must be approached from a transdisciplinary perspective. Climate change and more than a century of fire exclusion and wildfire suppression have led to contemporary wildfires with more severe environmental impacts and human smoke exposure. Wildfires increase smoke exposure for broad swaths of the US population, though outdoor workers and socially disadvantaged groups with limited adaptive capacity can be disproportionally exposed. Exposure to wildfire smoke is associated with a range of health impacts in children and adults, including exacerbation of existing respiratory diseases such as asthma and chronic obstructive pulmonary disease, worse birth outcomes, and cardiovascular events. Seasonally dry forests in Washington, Oregon, and California can benefit from ecological restoration as a way to adapt forests to climate change and reduce smoke impacts on affected communities. RECENT FINDINGS Each wildfire season, large smoke events, and their adverse impacts on human health receive considerable attention from both the public and policymakers. The severity of recent wildfire seasons has state and federal governments outlining budgets and prioritizing policies to combat the worsening crisis. This surging attention provides an opportunity to outline the actions needed now to advance research and practice on conservation, economic, environmental justice, and public health interests, as well as the trade-offs that must be considered. Scientists, planners, foresters and fire managers, fire safety, air quality, and public health practitioners must collaboratively work together. This article is the result of a series of transdisciplinary conversations to find common ground and subsequently provide a holistic view of how forest and fire management intersect with human health through the impacts of smoke and articulate the need for an integrated approach to both planning and practice.
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Affiliation(s)
- Savannah M. D’Evelyn
- Dept. of Environmental & Occupational Health Sciences, University of Washington, 3980 15th Ave NE, Seattle, WA 98105 USA
| | - Jihoon Jung
- Dept. of Environmental & Occupational Health Sciences, University of Washington, 3980 15th Ave NE, Seattle, WA 98105 USA
| | - Ernesto Alvarado
- School of Environmental and Forest Sciences, University of Washington, Seattle, USA
| | - Jill Baumgartner
- Dept of Epidemiology, Biostatistics & Occupational Health, McGill University, Montreal, Canada
| | | | - R. Keala Hagmann
- School of Environmental and Forest Sciences, University of Washington, Seattle, USA
- Applegate Forestry, LLC, Corvallis, USA
| | | | - Paul F. Hessburg
- School of Environmental and Forest Sciences, University of Washington, Seattle, USA
- USDA Forest Service, Pacific Northwest Research Station, Wenatchee, WA USA
| | - Sean Hopkins
- Washington State Department of Ecology, Lacey, USA
| | - Edward J. Kasner
- Dept. of Environmental & Occupational Health Sciences, University of Washington, 3980 15th Ave NE, Seattle, WA 98105 USA
| | - Meg A. Krawchuk
- Dept. of Forest Ecosystems and Society, Oregon State University, Corvallis, USA
| | - Jennifer E. Krenz
- Dept. of Environmental & Occupational Health Sciences, University of Washington, 3980 15th Ave NE, Seattle, WA 98105 USA
| | - Jamie M. Lydersen
- California Department of Forestry and Fire Protection, Sacramento, USA
| | - Miriam E. Marlier
- Department of Environmental Health Sciences, Fielding School of Public Health, University of California Los Angeles, Los Angeles, USA
| | | | | | | | - Susan J. Prichard
- School of Environmental and Forest Sciences, University of Washington, Seattle, USA
| | - Claire L. Schollaert
- Dept. of Environmental & Occupational Health Sciences, University of Washington, 3980 15th Ave NE, Seattle, WA 98105 USA
| | | | - Jens T. Stevens
- Department of Biology, University of New Mexico, Albuquerque, NM USA
| | - Christopher W. Tessum
- Dept. of Civil & Environmental Engineering, University of Illinois at Urbana-Champaign, Champaign, USA
| | - Carolyn Reeb-Whitaker
- Safety & Health Assessment & Research for Prevention Program, Washington State Department of Labor and Industries, Tumwater, USA
| | - Joseph L. Wilkins
- School of Environmental and Forest Sciences, University of Washington, Seattle, USA
- Interdisciplinary Studies Department, Howard University, Washington, DC USA
| | | | - Leah M. Wood
- Evan’s School of Public Policy and Governance and The Department of Global Health, University of Washington, 3980 15th Ave NE, Seattle, WA 98105 USA
| | | | - June T. Spector
- Dept. of Environmental & Occupational Health Sciences, University of Washington, 3980 15th Ave NE, Seattle, WA 98105 USA
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Thakrar SK, Tessum CW, Apte JS, Balasubramanian S, Millet DB, Pandis SN, Marshall JD, Hill JD. Global, high-resolution, reduced-complexity air quality modeling for PM2.5 using InMAP (Intervention Model for Air Pollution). PLoS One 2022; 17:e0268714. [PMID: 35613109 PMCID: PMC9132322 DOI: 10.1371/journal.pone.0268714] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 05/05/2022] [Indexed: 11/19/2022] Open
Abstract
Each year, millions of premature deaths worldwide are caused by exposure to outdoor air pollution, especially fine particulate matter (PM2.5). Designing policies to reduce these deaths relies on air quality modeling for estimating changes in PM2.5 concentrations from many scenarios at high spatial resolution. However, air quality modeling typically has substantial requirements for computation and expertise, which limits policy design, especially in countries where most PM2.5-related deaths occur. Lower requirement reduced-complexity models exist but are generally unavailable worldwide. Here, we adapt InMAP, a reduced-complexity model originally developed for the United States, to simulate annual-average primary and secondary PM2.5 concentrations across a global-through-urban spatial domain: “Global InMAP”. Global InMAP uses a variable resolution grid, with horizontal grid cell widths ranging from 500 km in remote locations to 4km in urban locations. We evaluate Global InMAP performance against both measurements and a state-of-the-science chemical transport model, GEOS-Chem. Against measurements, InMAP predicts total PM2.5 concentrations with a normalized mean error of 62%, compared to 41% for GEOS-Chem. For the emission scenarios considered, Global InMAP reproduced GEOS-Chem pollutant concentrations with a normalized mean bias of 59%–121%, which is sufficient for initial policy assessment and scoping. Global InMAP can be run on a desktop computer; simulations here took 2.6–8.4 hours. This work presents a global, open-source, reduced-complexity air quality model to facilitate policy assessment worldwide, providing a screening tool for reducing air pollution-related deaths where they occur most.
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Affiliation(s)
- Sumil K. Thakrar
- Department of Bioproducts & Biosystems Engineering, University of Minnesota, St Paul, Minnesota, United States of America
- Department of Applied Economics, University of Minnesota, St Paul, Minnesota, United States of America
- * E-mail: (SKT); (JDH)
| | - Christopher W. Tessum
- Department of Civil and Environmental Engineering, University of Illinois at Urbana−Champaign, Urbana, Illinois, United States of America
| | - Joshua S. Apte
- Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California, United States of America
- School of Public Health, University of California, Berkeley, California, United States of America
| | - Srinidhi Balasubramanian
- Department of Bioproducts & Biosystems Engineering, University of Minnesota, St Paul, Minnesota, United States of America
| | - Dylan B. Millet
- Department of Soil, Water, and Climate, University of Minnesota, St Paul, Minnesota, United States of America
| | - Spyros N. Pandis
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
- Department of Chemical Engineering, University of Patras, Patras, Greece
| | - Julian D. Marshall
- Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America
| | - Jason D. Hill
- Department of Bioproducts & Biosystems Engineering, University of Minnesota, St Paul, Minnesota, United States of America
- * E-mail: (SKT); (JDH)
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10
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Domingo NGG, Balasubramanian S, Thakrar SK, Clark MA, Adams PJ, Marshall JD, Muller NZ, Pandis SN, Polasky S, Robinson AL, Tessum CW, Tilman D, Tschofen P, Hill JD. Air quality-related health damages of food. Proc Natl Acad Sci U S A 2021; 118:e2013637118. [PMID: 33972419 PMCID: PMC8158015 DOI: 10.1073/pnas.2013637118] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Agriculture is a major contributor to air pollution, the largest environmental risk factor for mortality in the United States and worldwide. It is largely unknown, however, how individual foods or entire diets affect human health via poor air quality. We show how food production negatively impacts human health by increasing atmospheric fine particulate matter (PM2.5), and we identify ways to reduce these negative impacts of agriculture. We quantify the air quality-related health damages attributable to 95 agricultural commodities and 67 final food products, which encompass >99% of agricultural production in the United States. Agricultural production in the United States results in 17,900 annual air quality-related deaths, 15,900 of which are from food production. Of those, 80% are attributable to animal-based foods, both directly from animal production and indirectly from growing animal feed. On-farm interventions can reduce PM2.5-related mortality by 50%, including improved livestock waste management and fertilizer application practices that reduce emissions of ammonia, a secondary PM2.5 precursor, and improved crop and animal production practices that reduce primary PM2.5 emissions from tillage, field burning, livestock dust, and machinery. Dietary shifts toward more plant-based foods that maintain protein intake and other nutritional needs could reduce agricultural air quality-related mortality by 68 to 83%. In sum, improved livestock and fertilization practices, and dietary shifts could greatly decrease the health impacts of agriculture caused by its contribution to reduced air quality.
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Affiliation(s)
- Nina G G Domingo
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN 55108
| | - Srinidhi Balasubramanian
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN 55108
| | - Sumil K Thakrar
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN 55108
| | - Michael A Clark
- Oxford Martin School, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7DQ, United Kingdom
| | - Peter J Adams
- Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213
| | - Julian D Marshall
- Department of Civil & Environmental Engineering, University of Washington, Seattle, WA 98195
| | - Nicholas Z Muller
- Department of Engineering and Public Policy, Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA 15213
| | - Spyros N Pandis
- Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213
| | - Stephen Polasky
- Department of Applied Economics, University of Minnesota, St. Paul, MN 55108
| | - Allen L Robinson
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213
| | - Christopher W Tessum
- Department of Civil and Environmental Engineering, University of Illinois, Urbana, IL 61801
| | - David Tilman
- Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN 55108
| | - Peter Tschofen
- Department of Engineering and Public Policy, Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA 15213
| | - Jason D Hill
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN 55108;
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11
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Tessum CW, Paolella DA, Chambliss SE, Apte JS, Hill JD, Marshall JD. PM 2.5 polluters disproportionately and systemically affect people of color in the United States. Sci Adv 2021; 7:7/18/eabf4491. [PMID: 33910895 DOI: 10.1126/sciadv.abf4491] [Citation(s) in RCA: 173] [Impact Index Per Article: 57.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 03/10/2021] [Indexed: 05/17/2023]
Abstract
Racial-ethnic minorities in the United States are exposed to disproportionately high levels of ambient fine particulate air pollution (PM2.5), the largest environmental cause of human mortality. However, it is unknown which emission sources drive this disparity and whether differences exist by emission sector, geography, or demographics. Quantifying the PM2.5 exposure caused by each emitter type, we show that nearly all major emission categories-consistently across states, urban and rural areas, income levels, and exposure levels-contribute to the systemic PM2.5 exposure disparity experienced by people of color. We identify the most inequitable emission source types by state and city, thereby highlighting potential opportunities for addressing this persistent environmental inequity.
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Affiliation(s)
- Christopher W Tessum
- Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
| | - David A Paolella
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA
| | - Sarah E Chambliss
- Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, TX 78712, 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
| | - Jason D Hill
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN 55108, USA
| | - Julian D Marshall
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA
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12
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Thind MPS, Tessum CW, Azevedo IL, Marshall JD. Fine Particulate Air Pollution from Electricity Generation in the US: Health Impacts by Race, Income, and Geography. Environ Sci Technol 2019; 53:14010-14019. [PMID: 31746196 DOI: 10.1021/acs.est.9b02527] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Electricity generation is a large contributor to fine particulate matter (PM2.5) air pollution. However, the demographic distribution of the resulting exposure is largely unknown. We estimate exposures to and health impacts of PM2.5 from electricity generation in the US, for each of the seven Regional Transmission Organizations (RTOs), for each US state, by income and by race. We find that average exposures are the highest for blacks, followed by non-Latino whites. Exposures for remaining groups (e.g., Asians, Native Americans, Latinos) are somewhat lower. Disparities by race/ethnicity are observed for each income category, indicating that the racial/ethnic differences hold even after accounting for differences in income. Levels of disparity differ by state and RTO. Exposures are higher for lower-income than for higher-income, but disparities are larger by race than by income. Geographically, we observe large differences between where electricity is generated and where people experience the resulting PM2.5 health consequences; some states are net exporters of health impacts, other are net importers. For 36 US states, most of the health impacts are attributable to emissions in other states. Most of the total impacts are attributable to coal rather than other fuels.
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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 Washington , Seattle , Washington 98195 , United States
| | - Inês L Azevedo
- Department of Energy Resources Engineering, School of Earth, Energy and the Environment , Stanford University , Stanford , California 94305 , United States
| | - Julian D Marshall
- Department of Civil and Environmental Engineering , University of Washington , Seattle , Washington 98195 , United States
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13
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Goodkind AL, Tessum CW, Coggins JS, Hill JD, Marshall JD. Fine-scale damage estimates of particulate matter air pollution reveal opportunities for location-specific mitigation of emissions. Proc Natl Acad Sci U S A 2019; 116:8775-8780. [PMID: 30962364 PMCID: PMC6500143 DOI: 10.1073/pnas.1816102116] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Fine particulate matter (PM2.5) air pollution has been recognized as a major source of mortality in the United States for at least 25 years, yet much remains unknown about which sources are the most harmful, let alone how best to target policies to mitigate them. Such efforts can be improved by employing high-resolution geographically explicit methods for quantifying human health impacts of emissions of PM2.5 and its precursors. Here, we provide a detailed examination of the health and economic impacts of PM2.5 pollution in the United States by linking emission sources with resulting pollution concentrations. We estimate that anthropogenic PM2.5 was responsible for 107,000 premature deaths in 2011, at a cost to society of $886 billion. Of these deaths, 57% were associated with pollution caused by energy consumption [e.g., transportation (28%) and electricity generation (14%)]; another 15% with pollution caused by agricultural activities. A small fraction of emissions, concentrated in or near densely populated areas, plays an outsized role in damaging human health with the most damaging 10% of total emissions accounting for 40% of total damages. We find that 33% of damages occur within 8 km of emission sources, but 25% occur more than 256 km away, emphasizing the importance of tracking both local and long-range impacts. Our paper highlights the importance of a fine-scale approach as marginal damages can vary by over an order of magnitude within a single county. Information presented here can assist mitigation efforts by identifying those sources with the greatest health effects.
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Affiliation(s)
- Andrew L Goodkind
- Department of Economics, University of New Mexico, Albuquerque, NM 87131;
| | - Christopher W Tessum
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195
| | - Jay S Coggins
- Department of Applied Economics, University of Minnesota, St. Paul, MN 55108
| | - Jason D Hill
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN 55108
| | - Julian D Marshall
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195
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14
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Tessum CW, Apte JS, Goodkind AL, Muller NZ, Mullins KA, Paolella DA, Polasky S, Springer NP, Thakrar SK, Marshall JD, Hill JD. Inequity in consumption of goods and services adds to racial-ethnic disparities in air pollution exposure. Proc Natl Acad Sci U S A 2019; 116:6001-6006. [PMID: 30858319 PMCID: PMC6442600 DOI: 10.1073/pnas.1818859116] [Citation(s) in RCA: 209] [Impact Index Per Article: 41.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Fine particulate matter (PM2.5) air pollution exposure is the largest environmental health risk factor in the United States. Here, we link PM2.5 exposure to the human activities responsible for PM2.5 pollution. We use these results to explore "pollution inequity": the difference between the environmental health damage caused by a racial-ethnic group and the damage that group experiences. We show that, in the United States, PM2.5 exposure is disproportionately caused by consumption of goods and services mainly by the non-Hispanic white majority, but disproportionately inhaled by black and Hispanic minorities. On average, non-Hispanic whites experience a "pollution advantage": They experience ∼17% less air pollution exposure than is caused by their consumption. Blacks and Hispanics on average bear a "pollution burden" of 56% and 63% excess exposure, respectively, relative to the exposure caused by their consumption. The total disparity is caused as much by how much people consume as by how much pollution they breathe. Differences in the types of goods and services consumed by each group are less important. PM2.5 exposures declined ∼50% during 2002-2015 for all three racial-ethnic groups, but pollution inequity has remained high.
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Affiliation(s)
- Christopher W Tessum
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195
| | - Joshua S Apte
- Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TX 78712
| | - Andrew L Goodkind
- Department of Economics, University of New Mexico, Albuquerque, NM 87131
| | - Nicholas Z Muller
- Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA 15213
| | | | - David A Paolella
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195
| | - Stephen Polasky
- Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN 55108
- Department of Applied Economics, University of Minnesota, St. Paul, MN 55108
| | | | - Sumil K Thakrar
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN 55108
| | - Julian D Marshall
- Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195
| | - Jason D Hill
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN 55108
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15
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Chang KM, Hess JJ, Balbus JM, Buonocore JJ, Cleveland DA, Grabow ML, Neff R, Saari RK, Tessum CW, Wilkinson P, Woodward A, Ebi KL. Ancillary health effects of climate mitigation scenarios as drivers of policy uptake: a review of air quality, transportation and diet co-benefits modeling studies. Environ Res Lett 2017; 12:113001. [PMID: 38605885 PMCID: PMC11007749 DOI: 10.1088/1748-9326/aa8f7b] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/13/2024]
Abstract
Background Significant mitigation efforts beyond the Nationally Determined Commitments (NDCs) coming out of the 2015 Paris Climate Agreement are required to avoid warming of 2°C above pre-industrial temperatures. Health co-benefits represent selected near term, positive consequences of climate policies that can offset mitigation costs in the short term before the beneficial impacts of those policies on the magnitude of climate change are evident. The diversity of approaches to modeling mitigation options and their health effects inhibits meta-analyses and syntheses of results useful in policy-making. Methods/Design We evaluated the range of methods and choices in modeling health co-benefits of climate mitigation to identify opportunities for increased consistency and collaboration that could better inform policy-making. We reviewed studies quantifying the health co-benefits of climate change mitigation related to air quality, transportation, and diet published since the 2009 Lancet Commission 'Managing the health effects of climate change' through January 2017. We documented approaches, methods, scenarios, health-related exposures, and health outcomes. Results/Synthesis Forty-two studies met the inclusion criteria. Air quality, transportation, and diet scenarios ranged from specific policy proposals to hypothetical scenarios, and from global recommendations to stakeholder-informed local guidance. Geographic and temporal scope as well as validity of scenarios determined policy relevance. More recent studies tended to use more sophisticated methods to address complexity in the relevant policy system. Discussion Most studies indicated significant, nearer term, local ancillary health benefits providing impetus for policy uptake and net cost savings. However, studies were more suited to describing the interaction of climate policy and health and the magnitude of potential outcomes than to providing specific accurate estimates of health co-benefits. Modeling the health co-benefits of climate policy provides policy-relevant information when the scenarios are reasonable, relevant, and thorough, and the model adequately addresses complexity. Greater consistency in selected modeling choices across the health co-benefits of climate mitigation research would facilitate evaluation of mitigation options particularly as they apply to the NDCs and promote policy uptake.
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Affiliation(s)
- Kelly M Chang
- University of Washington Center for Health and the Global Environment, Seattle, WA 98105, United States of America
| | - Jeremy J Hess
- University of Washington Center for Health and the Global Environment, Seattle, WA 98105, United States of America
| | - John M Balbus
- National Institute of Environmental Health Sciences, Durham, NC, United States of America
| | - Jonathan J Buonocore
- Center for Health and the Global Environment, Harvard School of Public Health, Landmark Center 4th Floor, Suite 415, 401 Park Drive, Boston, MA 02215, United States of America
| | - David A Cleveland
- University of California Santa Barbara, Santa Barbara, CA, United States of America
| | - Maggie L Grabow
- Family Medicine and Community Health, University of Wisconsin Madison School of Medicine and Public Health, 1100 Delaplaine Ct, Madison, WI 53715, United States of America
| | - Roni Neff
- Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, United States of America
| | | | | | - Paul Wilkinson
- London School of Hygiene and Tropical Medicine, University of London, London, United Kingdom
| | | | - Kristie L Ebi
- LLC, ClimAdapt, 424 Tyndall Street, Los Altos, CA 94022, United States of America
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16
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Abstract
Mechanistic air pollution modeling is essential in air quality management, yet the extensive expertise and computational resources required to run most models prevent their use in many situations where their results would be useful. Here, we present InMAP (Intervention Model for Air Pollution), which offers an alternative to comprehensive air quality models for estimating the air pollution health impacts of emission reductions and other potential interventions. InMAP estimates annual-average changes in primary and secondary fine particle (PM2.5) concentrations-the air pollution outcome generally causing the largest monetized health damages-attributable to annual changes in precursor emissions. InMAP leverages pre-processed physical and chemical information from the output of a state-of-the-science chemical transport model and a variable spatial resolution computational grid to perform simulations that are several orders of magnitude less computationally intensive than comprehensive model simulations. In comparisons run here, InMAP recreates comprehensive model predictions of changes in total PM2.5 concentrations with population-weighted mean fractional bias (MFB) of -17% and population-weighted R2 = 0.90. Although InMAP is not specifically designed to reproduce total observed concentrations, it is able to do so within published air quality model performance criteria for total PM2.5. Potential uses of InMAP include studying exposure, health, and environmental justice impacts of potential shifts in emissions for annual-average PM2.5. InMAP can be trained to run for any spatial and temporal domain given the availability of appropriate simulation output from a comprehensive model. The InMAP model source code and input data are freely available online under an open-source license.
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Affiliation(s)
- Christopher W. Tessum
- Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America
- * E-mail:
| | - Jason D. Hill
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, Minnesota, United States of America
| | - Julian D. Marshall
- Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America
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17
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Tessum CW, Hill JD, Marshall JD. Life cycle air quality impacts of conventional and alternative light-duty transportation in the United States. Proc Natl Acad Sci U S A 2014; 111:18490-5. [PMID: 25512510 PMCID: PMC4284558 DOI: 10.1073/pnas.1406853111] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Commonly considered strategies for reducing the environmental impact of light-duty transportation include using alternative fuels and improving vehicle fuel economy. We evaluate the air quality-related human health impacts of 10 such options, including the use of liquid biofuels, diesel, and compressed natural gas (CNG) in internal combustion engines; the use of electricity from a range of conventional and renewable sources to power electric vehicles (EVs); and the use of hybrid EV technology. Our approach combines spatially, temporally, and chemically detailed life cycle emission inventories; comprehensive, fine-scale state-of-the-science chemical transport modeling; and exposure, concentration-response, and economic health impact modeling for ozone (O3) and fine particulate matter (PM2.5). We find that powering vehicles with corn ethanol or with coal-based or "grid average" electricity increases monetized environmental health impacts by 80% or more relative to using conventional gasoline. Conversely, EVs powered by low-emitting electricity from natural gas, wind, water, or solar power reduce environmental health impacts by 50% or more. Consideration of potential climate change impacts alongside the human health outcomes described here further reinforces the environmental preferability of EVs powered by low-emitting electricity relative to gasoline vehicles.
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Affiliation(s)
- Christopher W Tessum
- Department of Civil, Environmental, and Geo- Engineering, University of Minnesota, Minneapolis, MN 55455; and
| | - Jason D Hill
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN 55108
| | - Julian D Marshall
- Department of Civil, Environmental, and Geo- Engineering, University of Minnesota, Minneapolis, MN 55455; and
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18
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Millet DB, Apel E, Henze DK, Hill J, Marshall JD, Singh HB, Tessum CW. Response to comment on "Natural and anthropogenic ethanol sources in North America and potential atmospheric impacts of ethanol fuel use". Environ Sci Technol 2013; 47:2141. [PMID: 23244221 DOI: 10.1021/es305112s] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
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19
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Tessum CW, Marshall JD, Hill JD. A spatially and temporally explicit life cycle inventory of air pollutants from gasoline and ethanol in the United States. Environ Sci Technol 2012; 46:11408-17. [PMID: 22906224 DOI: 10.1021/es3010514] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
The environmental health impacts of transportation depend in part on where and when emissions occur during fuel production and combustion. Here we describe spatially and temporally explicit life cycle inventories (LCI) of air pollutants from gasoline, ethanol derived from corn grain, and ethanol from corn stover. Previous modeling for the U.S. by Argonne National Laboratory (GREET: Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) suggested that life cycle emissions are generally higher for ethanol from corn grain or corn stover than for gasoline. Our results show that for ethanol, emissions are concentrated in the Midwestern "Corn Belt". We find that life cycle emissions from ethanol exhibit different temporal patterns than from gasoline, reflecting seasonal aspects of farming activities. Enhanced chemical speciation beyond current GREET model capabilities is also described. Life cycle fine particulate matter emissions are higher for ethanol from corn grain than for ethanol from corn stover; for black carbon, the reverse holds. Overall, our results add to existing state-of-the-science transportation fuel LCI by providing spatial and temporal disaggregation and enhanced chemical speciation, thereby offering greater understanding of the impacts of transportation fuels on human health and opening the door to advanced air dispersion modeling of fuel life cycles.
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Affiliation(s)
- Christopher W Tessum
- Department of Civil Engineering, University of Minnesota, Minneapolis, Minnesota, USA
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Millet DB, Apel E, Henze DK, Hill J, Marshall JD, Singh HB, Tessum CW. Natural and anthropogenic ethanol sources inNorth America and potential atmospheric impacts of ethanol fuel use. Environ Sci Technol 2012; 46:8484-92. [PMID: 22731385 DOI: 10.1021/es300162u] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
We used an ensemble of aircraft measurements with the GEOS-Chem chemical transport model to constrain present-day North American ethanol sources, and gauge potential long-range impacts of increased ethanol fuel use. We find that current ethanol emissions are underestimated by 50% in Western North America, and overestimated by a factor of 2 in the east. Our best estimate for year-2005 North American ethanol emissions is 670 GgC/y, with 440 GgC/y from the continental U.S. We apply these optimized source estimates to investigate two scenarios for increased ethanol fuel use in the U.S.: one that assumes a complete transition from gasoline to E85 fuel, and one tied to the biofuel requirements of the U.S. Energy Indepence and Security Act (EISA). For both scenarios, increased ethanol emissions lead to higher atmospheric acetaldehyde concentrations (by up to 14% during winter for the All-E85 scenario and 2% for the EISA scenario) and an associated shift in reactive nitrogen partitioning reflected by an increase in the peroxyacetyl nitrate (PAN) to NO(y) ratio. The largest relative impacts occur during fall, winter, and spring because of large natural emissions of ethanol and other organic compounds during summer. Projected changes in atmospheric PAN reflect a balance between an increased supply of peroxyacetyl radicals from acetaldehyde oxidation, and the lower NO(x) emissions for E85 relative to gasoline vehicles. The net effect is a general PAN increase in fall through spring, and a weak decrease over the U.S. Southeast and the Atlantic Ocean during summer. Predicted NO(x) concentrations decrease in surface air over North America (by as much 5% in the All-E85 scenario). Downwind of North America this effect is counteracted by higher NO(x) export efficiency driven by increased PAN production and transport. From the point of view of NO(x) export from North America, the increased PAN formation associated with E85 fuel use thus acts to offset the associated lower NO(x) emissions.
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Affiliation(s)
- Dylan B Millet
- University of Minnesota, Minneapolis-St. Paul, Minnesota, USA.
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