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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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Sparks MS, Farahbakhsh I, Anand M, Bauch CT, Conlon KC, East JD, Li T, Lickley M, Garcia-Menendez F, Monier E, Saari RK. Health and equity implications of individual adaptation to air pollution in a changing climate. Proc Natl Acad Sci U S A 2024; 121:e2215685121. [PMID: 38227646 PMCID: PMC10835109 DOI: 10.1073/pnas.2215685121] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 11/05/2023] [Indexed: 01/18/2024] Open
Abstract
Future climate change can cause more days with poor air quality. This could trigger more alerts telling people to stay inside to protect themselves, with potential consequences for health and health equity. Here, we study the change in US air quality alerts over this century due to fine particulate matter (PM2.5), who they may affect, and how they may respond. We find air quality alerts increase by over 1 mo per year in the eastern United States by 2100 and quadruple on average. They predominantly affect areas with high Black populations and leakier homes, exacerbating existing inequalities and impacting those less able to adapt. Reducing emissions can offer significant annual health benefits ($5,400 per person) by mitigating the effect of climate change on air pollution and its associated risks of early death. Relying on people to adapt, instead, would require them to stay inside, with doors and windows closed, for an extra 142 d per year, at an average cost of $11,000 per person. It appears likelier, however, that people will achieve minimal protection without policy to increase adaptation rates. Boosting adaptation can offer net benefits, even alongside deep emission cuts. New adaptation policies could, for example: reduce adaptation costs; reduce infiltration and improve indoor air quality; increase awareness of alerts and adaptation; and provide measures for those working or living outdoors. Reducing emissions, conversely, lowers everyone's need to adapt, and protects those who cannot adapt. Equitably protecting human health from air pollution under climate change requires both mitigation and adaptation.
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Affiliation(s)
- Matt S. Sparks
- Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ONN2L 3G1, Canada
| | - Isaiah Farahbakhsh
- School of Environmental Sciences, University of Guelph, Waterloo, ONN1G 2W1, Canada
| | - Madhur Anand
- School of Environmental Sciences, University of Guelph, Waterloo, ONN1G 2W1, Canada
| | - Chris T. Bauch
- Department of Applied Mathematics, University of Waterloo, Waterloo, ONN2L 3G, Canada
| | - Kathryn C. Conlon
- School of Medicine, Department of Public Health Sciences, University of California, Davis, CA95616
- School of Veterinary Medicine, Department of Medicine and Epidemiology, University of California, Davis, CA95616
| | - James D. East
- Department of Civil, Construction, and Environmental Engineering, North Carolina State University, Raleigh, NC27695
| | - Tianyuan Li
- Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ONN2L 3G1, Canada
| | - Megan Lickley
- Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA02139N
| | - Fernando Garcia-Menendez
- Department of Civil, Construction, and Environmental Engineering, North Carolina State University, Raleigh, NC27695
| | - Erwan Monier
- Department of Land, Air and Water Resources, University of California, Davis, CA95616
| | - Rebecca K. Saari
- Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ONN2L 3G1, Canada
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Liu M, Saari RK, Zhou G, Li J, Han L, Liu X. Recent trends in premature mortality and health disparities attributable to ambient PM 2.5 exposure in China: 2005-2017. Environ Pollut 2021; 279:116882. [PMID: 33756244 DOI: 10.1016/j.envpol.2021.116882] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 03/06/2021] [Accepted: 03/08/2021] [Indexed: 06/12/2023]
Abstract
In the past decade, particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5) has reached unprecedented levels in China and posed a significant threat to public health. Exploring the long-term trajectory of the PM2.5 attributable health burden and corresponding disparities across populations in China yields insights for policymakers regarding the effectiveness of efforts to reduce air pollution exposure. Therefore, we examine how the magnitude and equity of the PM2.5-related public health burden has changed nationally, and between provinces, as economic growth and pollution levels varied during 2005-2017. We derive long-term PM2.5 exposures in China from satellite-based observations and chemical transport models, and estimate attributable premature mortality using the Global Exposure Mortality Model (GEMM). We characterize national and interprovincial inequality in health outcomes using environmental Lorenz curves and Gini coefficients over the study period. PM2.5 exposure is linked to 1.8 (95% CI: 1.6, 2.0) million premature deaths over China in 2017, increasing by 31% from 2005. Approximately 70% of PM2.5 attributable deaths were caused by stroke and IHD (ischemic heart disease), though COPD (chronic obstructive pulmonary disease) and LRI (lower respiratory infection) disproportionately affected poorer provinces. While most economic gains and PM2.5-related deaths were concentrated in a few provinces, both gains and deaths became more equitably distributed across provinces over time. As a nation, however, trends toward equality were more recent and less clear cut across causes of death. The rise in premature mortality is due primarily to population growth and baseline risks of stroke and IHD. This rising health burden could be alleviated through policies to prevent pollution, exposure, and disease. More targeted programs may be warranted for poorer provinces with a disproportionate share of PM2.5-related premature deaths due to COPD and LRI.
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Affiliation(s)
- Ming Liu
- Department of Geography and Environmental Management, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada; School of Land Engineering, Chang'an University, Xi'an, Shaanxi, 710064, China.
| | - Rebecca K Saari
- Department of Geography and Environmental Management, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada; Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada.
| | - Gaoxiang Zhou
- Department of Geography and Environmental Management, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada; School of Information Engineering, China University of Geosciences, Beijing, 100083, China
| | - Jonathan Li
- Department of Geography and Environmental Management, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada; Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, FJ, 361005, China
| | - Ling Han
- Shaanxi Key Laboratory of Land Consolidation, School of Land Engineering, Chang'an University, Xi'an, Shaanxi, 710064, China
| | - Xiangnan Liu
- School of Information Engineering, China University of Geosciences, Beijing, 100083, China
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Hess JJ, Ranadive N, Boyer C, Aleksandrowicz L, Anenberg SC, Aunan K, Belesova K, Bell ML, Bickersteth S, Bowen K, Burden M, Campbell-Lendrum D, Carlton E, Cissé G, Cohen F, Dai H, Dangour AD, Dasgupta P, Frumkin H, Gong P, Gould RJ, Haines A, Hales S, Hamilton I, Hasegawa T, Hashizume M, Honda Y, Horton DE, Karambelas A, Kim H, Kim SE, Kinney PL, Kone I, Knowlton K, Lelieveld J, Limaye VS, Liu Q, Madaniyazi L, Martinez ME, Mauzerall DL, Milner J, Neville T, Nieuwenhuijsen M, Pachauri S, Perera F, Pineo H, Remais JV, Saari RK, Sampedro J, Scheelbeek P, Schwartz J, Shindell D, Shyamsundar P, Taylor TJ, Tonne C, Van Vuuren D, Wang C, Watts N, West JJ, Wilkinson P, Wood SA, Woodcock J, Woodward A, Xie Y, Zhang Y, Ebi KL. Guidelines for Modeling and Reporting Health Effects of Climate Change Mitigation Actions. Environ Health Perspect 2020; 128:115001. [PMID: 33170741 PMCID: PMC7654632 DOI: 10.1289/ehp6745] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 09/08/2020] [Accepted: 10/13/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers. OBJECTIVE The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions. METHODS An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies. RESULTS The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting. DISCUSSION This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice. https://doi.org/10.1289/EHP6745.
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Affiliation(s)
- Jeremy J. Hess
- Center for Health and the Global Environment, University of Washington, Seattle, Washington, USA
| | | | - Chris Boyer
- Center for Health and the Global Environment, University of Washington, Seattle, Washington, USA
| | | | - Susan C. Anenberg
- Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA
| | - Kristin Aunan
- CICERO Center for International Climate Research, Oslo, Norway
| | - Kristine Belesova
- Department of Public Health, Environments, and Society, London School of Hygiene & Tropical Medicine, London, UK
- Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Michelle L. Bell
- School of Forestry and Environmental Studies, Yale University, New Haven, Connecticut, USA
| | - Sam Bickersteth
- Rockefeller Foundation Economic Council on Planetary Health, Oxford, UK
| | | | - Marci Burden
- Center for Health and the Global Environment, University of Washington, Seattle, Washington, USA
| | - Diarmid Campbell-Lendrum
- Department of Environment Climate Change and Health, World Health Organization, Geneva, Switzerland
| | - Elizabeth Carlton
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado, Aurora, Colorado, USA
| | - Guéladio Cissé
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Francois Cohen
- Smith School for Enterprise and the Environment and Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, Oxford, UK
| | - Hancheng Dai
- Laboratory of Energy & Environmental Economics and Policy (LEEEP), College of Environmental Sciences and Engineering, Peking University, Beijing, China
- College of Environmental Sciences and Engineering, Peking University, Beijing, China
| | - Alan David Dangour
- Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Purnamita Dasgupta
- Environmental and Resource Economics Unit, Institute of Economic Growth, Delhi, India
| | | | - Peng Gong
- Department of Earth System Science, Tsinghua University, Beijing, China
| | - Robert J. Gould
- Center for Climate Change Communication, George Mason University, Fairfax, Virginia, USA
| | - Andy Haines
- Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Simon Hales
- Department of Public Health, University of Otago, Wellington, New Zealand
| | - Ian Hamilton
- UCL Energy Institute, University College London, London, UK
| | - Tomoko Hasegawa
- National Institute for Environmental Studies, Tsukuba, Japan
| | - Masahiro Hashizume
- Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
| | - Yasushi Honda
- Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan
| | - Daniel E. Horton
- Department of Earth and Planetary Sciences, Northwestern University, Evanston, Illinois, USA
| | | | - Ho Kim
- Department of Epidemiology and Biostatistics, School of Public Health, Seoul National University, Seoul, South Korea
| | - Satbyul Estella Kim
- Center for Climate Change Adaptation, National Institute for Environmental Studies, Tsukuba, Japan
| | - Patrick L. Kinney
- Department of Environmental Health, Boston University School of Public Health, Boston, USA
| | - Inza Kone
- Centre Suisse de Recherches Scientifiques en Côte d’Ivoire, Abidjan, Côte d’Ivoire
- Université Félix Houphouet-Boigny, Abidjan, Côte d’Ivoire
| | - Kim Knowlton
- Natural Resources Defense Council, New York, New York, USA
| | - Jos Lelieveld
- Max Planck Institute for Chemistry, Dept. of Atmospheric Chemistry, Mainz, Germany
| | | | - Qiyong Liu
- National Institute for Communicable Disease Control and Prevention, Beijing, China
| | - Lina Madaniyazi
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
- Department of Paediatric Diseases, Institute of Tropical Medicine, Nagasaki, Japan
| | - Micaela Elvira Martinez
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Denise L. Mauzerall
- Woodrow Wilson School of Public and International Affairs and the Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey, USA
| | - James Milner
- Department of Public Health, Environments, and Society, London School of Hygiene & Tropical Medicine, London, UK
| | | | - Mark Nieuwenhuijsen
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiologia y Salud Publica (CIBERESP), Barcelona, Spain
| | | | - Frederica Perera
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Helen Pineo
- Bartlett Faculty of the Built Environment, University College London, London, UK
| | - Justin V. Remais
- Division of Environmental Health Sciences, University of California, Berkeley, Berkeley, California, USA
| | - Rebecca K. Saari
- Civil and Environmental Engineering, University of Waterloo, Ontario, Canada
| | - Jon Sampedro
- Basque Centre for Climate Change (BC3), Leioa, Spain
| | - Pauline Scheelbeek
- Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK
- Department of Epidemiology & Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Heath, Boston, Massachusetts, USA
| | - Drew Shindell
- Nicholas School of the Environment, Duke University, Durham, North Carolina, USA
| | | | - Timothy J. Taylor
- European Centre for Environment and Human Health, University of Exeter Medical School, Truro, Cornwall, UK
| | - Cathryn Tonne
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiologia y Salud Publica (CIBERESP), Barcelona, Spain
| | - Detlef Van Vuuren
- PBL Netherlands Environmental Assessment Agency, The Hague, Netherlands
| | - Can Wang
- School of Environment, Tsinghua University, Beijing, China
| | - Nicholas Watts
- Institute for Global Health, University College London, London, UK
| | - J. Jason West
- Environmental Sciences & Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Paul Wilkinson
- Department of Public Health, Environments, and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Stephen A. Wood
- School of Forestry and Environmental Studies, Yale University, New Haven, Connecticut, USA
- The Nature Conservancy, New Haven, Connecticut, USA
| | - James Woodcock
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Alistair Woodward
- Epidemiology and Biostatistics, University of Auckland, Auckland, New Zealand
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing, China
- Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Beihang University, Beijing, China
| | - Ying Zhang
- School of Public Health, University of Sydney, New South Wales, Australia
| | - Kristie L. Ebi
- Center for Health and the Global Environment, University of Washington, Seattle, Washington, USA
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Mukherjee U, Saari RK, Bachmann C, Wang W. Multipollutant impacts to U.S. receptors of regional on-road freight in Ontario, Canada. J Air Waste Manag Assoc 2020; 70:1121-1135. [PMID: 32931377 DOI: 10.1080/10962247.2020.1781294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Revised: 05/29/2020] [Accepted: 06/01/2020] [Indexed: 06/11/2023]
Abstract
On-road freight is a significant source of air pollutant and greenhouse gas emissions. The resulting economic damages can cross borders through processes of atmospheric fate and transport, regardless of whether that freight serves local or regional demand. Understanding patterns of freight demand and atmospheric processes can thus inform inter-jurisdictional efforts to mitigate multipollutant damages. We quantify how different freight trips across 49 census divisions in the Province of Ontario, Canada create an economic burden on downwind US receptors. We apply an integrated modeling approach combining a travel demand model, a mobile emissions simulator, and marginal damages from emissions. Economic damages include the increased risk of premature death from PM2.5 related to primary PM2.5 (represented by damages from inert primary PM2.5), NOX, SO2, and NH3, and the global effects of climate change from greenhouse gases (CO2, CH4, N2O). Over 90% of the $1.4 billion (2010USD) in transboundary air pollutant damages at US receptors result from regional freight demand across Ontario in 2012. A single major freight corridor, the ON-401 expressway, contributes more than half of all damages. Most of these damages impact the states situated to the south and east of the province. Mean estimates of annual damages range from millions to tens of millions (2010USD) across major eastern metropolitan areas including New York, Boston, Philadelphia, and D.C. Most of these damages result from NOX, which constitutes 95% of inorganic PM2.5-related pollutant emissions by mass. Thus, targeting NOx from freight movements along the ON-401 expressway could avoid millions to tens of millions of damages annually in eastern US cities. These results indicate that local green freight policies may be unable to address the environmental burden at cross-border receptors. Cooperation is needed among local, provincial, and federal governments to encourage policies targeting the most harmful emissions along routes servicing regional freight demands. Implications: On-road freight movement in Ontario can yield billions of dollars in annual economic damages to US residents through its effects on air pollution and climate change. We use an integrated modeling approach combining an on-road freight travel demand, mobile emissions, and marginal damages of emissions to quantify and study these economic damages. Regional freight contributes approximately 90% of damages, with one major freight corridor, the ON-401 expressway, contributing 59%. Most damages derive from emissions of NOx and amount to millions to tens of millions of dollars in annual damages across major Eastern US cities. Thus, targeting NOx from freight movements along the ON-401 expressway could avoid millions of damages annually in eastern US cities.
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Affiliation(s)
- Ushnik Mukherjee
- Civil and Environmental Engineering, University of Waterloo , Waterloo, ON, Canada
| | - Rebecca K Saari
- Civil and Environmental Engineering, University of Waterloo , Waterloo, ON, Canada
| | - Chris Bachmann
- Civil and Environmental Engineering, University of Waterloo , Waterloo, ON, Canada
| | - Wilson Wang
- Civil and Environmental Engineering, University of Waterloo , Waterloo, ON, Canada
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Saari RK, Mei Y, Monier E, Garcia-Menendez F. Effect of Health-Related Uncertainty and Natural Variability on Health Impacts and Cobenefits of Climate Policy. Environ Sci Technol 2019; 53:1098-1108. [PMID: 30624913 DOI: 10.1021/acs.est.8b05094] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Climate policy can mitigate health risks attributed to intensifying air pollution under climate change. However, few studies quantify risks of illness and death, examine their contribution to climate policy benefits, or assess their robustness in light of natural climate variability. We employ an integrated modeling framework of the economy, climate, air quality, and human health to quantify the effect of natural variability on U.S. air pollution impacts under future climate and two global policies (2 and 2.5 °C stabilization scenarios) using 150 year ensemble simulations for each scenario in 2050 and 2100. Climate change yields annual premature deaths related to fine particulate matter and ozone (95CI: 25 000-120 000), heart attacks (900-9400), and lost work days (3.6M-4.9M) in 2100. It raises air pollution health risks by 20%, while policies avert these outcomes by 40-50% in 2050 and 70-88% in 2100. Natural variability introduces "climate noise", yielding some annual estimates with negative cobenefits, and others that reach 100% of annual policy costs. This "noise" is three times the magnitude of uncertainty (95CI) in health and economic responses in 2050. Averaging five annual simulations reduces this factor to two, which is still substantially larger than health-related uncertainty. This study quantifies the potential for inaccuracy in climate impacts projected using too few annual simulations.
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Affiliation(s)
- Rebecca K Saari
- Civil and Environmental Engineering , University of Waterloo , 200 University Avenue West , Waterloo , Ontario , Canada , N2L 3G1
| | - Yufei Mei
- Civil and Environmental Engineering , University of Waterloo , 200 University Avenue West , Waterloo , Ontario , Canada , N2L 3G1
| | - Erwan Monier
- Joint Program on the Science and Policy of Global Change , Massachusetts Institute of Technology , Cambridge , Massachusetts 02139 , United States
| | - Fernando Garcia-Menendez
- Department of Civil, Construction and Environmental Engineering , North Carolina State University , Raleigh , North Carolina 27695 , United States
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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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Abstract
Low-income households may be disproportionately affected by ozone pollution and ozone policy. We quantify how three factors affect the relative benefits of ozone policies with household income: (1) unequal ozone reductions; (2) policy delay; and (3) economic valuation methods. We model ozone concentrations under baseline and policy conditions across the full continental United States to estimate the distribution of ozone-related health impacts across nine income groups. We enhance an economic model to include these impacts across household income categories, and present its first application to evaluate the benefits of ozone reductions for low-income households. We find that mortality incidence rates decrease with increasing income. Modeled ozone levels yield a median of 11 deaths per 100 000 people in 2005. Proposed policy reduces these rates by 13%. Ozone reductions are highest among low-income households, which increases their relative welfare gains by up to 4% and decreases them for the rich by up to 8%. The median value of reductions in 2015 is either $30 billion (in 2006 U.S. dollars) or $1 billion if reduced mortality risks are valued with willingness-to-pay or as income from increased life expectancy. Ozone reductions were relatively twice as beneficial for the lowest- compared to the highest-income households. The valuation approach affected benefits more than a policy delay or differential ozone reductions with income.
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Affiliation(s)
| | - Tammy M Thompson
- CSU Cooperative Institute for Research in the Atmosphere , 1375 Campus Delivery, Fort Collins, Colorado 80523, United States
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Thompson TM, Rausch S, Saari RK, Selin NE. Air quality co-benefits of subnational carbon policies. J Air Waste Manag Assoc 2016; 66:988-1002. [PMID: 27216236 DOI: 10.1080/10962247.2016.1192071] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2016] [Accepted: 05/16/2016] [Indexed: 05/19/2023]
Abstract
UNLABELLED To mitigate climate change, governments ranging from city to multi-national have adopted greenhouse gas (GHG) emissions reduction targets. While the location of GHG reductions does not affect their climate benefits, it can impact human health benefits associated with co-emitted pollutants. Here, an advanced modeling framework is used to explore how subnational level GHG targets influence air pollutant co-benefits from ground level ozone and fine particulate matter. Two carbon policy scenarios are analyzed, each reducing the same total amount of GHG emissions in the Northeast US: an economy-wide Cap and Trade (CAT) program reducing emissions from all sectors of the economy, and a Clean Energy Standard (CES) reducing emissions from the electricity sector only. Results suggest that a regional CES policy will cost about 10 times more than a CAT policy. Despite having the same regional targets in the Northeast, carbon leakage to non-capped regions varies between policies. Consequently, a regional CAT policy will result in national carbon reductions that are over six times greater than the carbon reduced by the CES in 2030. Monetized regional human health benefits of the CAT and CES policies are 844% and 185% of the costs of each policy, respectively. Benefits for both policies are thus estimated to exceed their costs in the Northeast US. The estimated value of human health co-benefits associated with air pollution reductions for the CES scenario is two times that of the CAT scenario. IMPLICATIONS In this research, an advanced modeling framework is used to determine the potential impacts of regional carbon policies on air pollution co-benefits associated with ground level ozone and fine particulate matter. Study results show that spatially heterogeneous GHG policies have the potential to create areas of air pollution dis-benefit. It is also shown that monetized human health benefits within the area covered by policy may be larger than the model estimated cost of the policy. These findings are of particular interest both as U.S. states work to develop plans to meet state-level carbon emissions reduction targets set by the EPA through the Clean Power Plan, and in the absence of comprehensive national carbon policy.
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Affiliation(s)
- Tammy M Thompson
- a MIT Joint Program on the Science and Policy of Global Change , Cambridge , MA , USA
- b Cooperative Institute for Research in the Atmosphere , Colorado State University , Fort Collins , CO , USA
| | - Sebastian Rausch
- a MIT Joint Program on the Science and Policy of Global Change , Cambridge , MA , USA
- c Department of Management , Technology, and Economics, ETH Zurich (Swiss Federal Institute of Technology) , Zurich , Switzerland
| | - Rebecca K Saari
- d Institute for Data, Systems, and Society , Massachusetts Institute of Technology , Cambridge , MA , USA
- e Department of Civil and Environmental Engineering , University of Waterloo , Waterloo , Ontario , Canada
| | - Noelle E Selin
- d Institute for Data, Systems, and Society , Massachusetts Institute of Technology , Cambridge , MA , USA
- f Department of Earth , Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology , Cambridge , MA , USA
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Garcia-Menendez F, Saari RK, Monier E, Selin NE. U.S. Air Quality and Health Benefits from Avoided Climate Change under Greenhouse Gas Mitigation. Environ Sci Technol 2015; 49:7580-8. [PMID: 26053628 DOI: 10.1021/acs.est.5b01324] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
We evaluate the impact of climate change on U.S. air quality and health in 2050 and 2100 using a global modeling framework and integrated economic, climate, and air pollution projections. Three internally consistent socioeconomic scenarios are used to value health benefits of greenhouse gas mitigation policies specifically derived from slowing climate change. Our projections suggest that climate change, exclusive of changes in air pollutant emissions, can significantly impact ozone (O3) and fine particulate matter (PM2.5) pollution across the U.S. and increase associated health effects. Climate policy can substantially reduce these impacts, and climate-related air pollution health benefits alone can offset a significant fraction of mitigation costs. We find that in contrast to cobenefits from reductions to coemitted pollutants, the climate-induced air quality benefits of policy increase with time and are largest between 2050 and 2100. Our projections also suggest that increasing climate policy stringency beyond a certain degree may lead to diminishing returns relative to its cost. However, our results indicate that the air quality impacts of climate change are substantial and should be considered by cost-benefit climate policy analyses.
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Affiliation(s)
- Fernando Garcia-Menendez
- †Joint Program on the Science and Policy of Global Change, ‡Engineering Systems Division, and §Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Rebecca K Saari
- †Joint Program on the Science and Policy of Global Change, ‡Engineering Systems Division, and §Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Erwan Monier
- †Joint Program on the Science and Policy of Global Change, ‡Engineering Systems Division, and §Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Noelle E Selin
- †Joint Program on the Science and Policy of Global Change, ‡Engineering Systems Division, and §Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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Saari RK, Selin NE, Rausch S, Thompson TM. A self-consistent method to assess air quality co-benefits from U.S. climate policies. J Air Waste Manag Assoc 2015; 65:74-89. [PMID: 25946960 DOI: 10.1080/10962247.2014.959139] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
Air quality co-benefits can potentially reduce the costs of greenhouse gas mitigation. However, whereas many studies of the cost of greenhouse gas mitigation model the macroeconomic welfare impacts of mitigation, most studies of air quality co-benefits do not. We employ a U.S. computable general equilibrium economic model previously linked to an air quality modeling system and enhance it to represent the economy-wide welfare impacts of fine particulate matter. We present a first application of this method to explore the efficiency and distributional implications of a Clean Energy Standard (CES) and a Cap and Trade (CAT) program that both reduce CO₂emissions by 10% in 2030 relative to 2006. We find that co-benefits from fine particulate matter reduction (median $6; $2 to $10/tCO₂) completely offset policy costs by 110% (40% to 190%), transforming the net welfare impact of the CAT into a gain of $1 (-$5 to $7) billion 2005$. For the CES, the corresponding co-benefit (median $8; $3 to $14/tCO₂) is a smaller fraction (median 5%; 2% to 9%) of its higher policy cost. The eastern United States garners 78% and 71% of co-benefits for the CES and CAT, respectively. By representing the effects of pollution-related morbidities and mortalities as an impact to labor and the demand for health services, we find that the welfare impact per unit of reduced pollution varies by region. These interregional differences can enhance the preference of some regions, such as Texas, for a CAT over a CES, or switch the calculation of which policy yields higher co-benefits, compared with an approach that uses one valuation for all regions. This framework could be applied to quantify consistent air quality impacts of other pricing instruments, subnational trading programs, or green tax swaps.
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Affiliation(s)
- Rebecca K Saari
- a Engineering Systems Division , Massachusetts Institute of Technology , Cambridge , MA , USA
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