Editorial Type:
Article
Article Type:
Research Article

The Impacts of Heat and Air Pollution on Mortality in the United States

Zeying Huang aDepartment of Agricultural, Food, and Resource Economics, Michigan State University, East Lansing, Michigan

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Jungmin Lim bDepartment of Economics, Pukyong National University, Busan, South Korea

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Mark Skidmore aDepartment of Agricultural, Food, and Resource Economics, Michigan State University, East Lansing, Michigan

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Online Publication:
26 Mar 2024
Print Publication:
01 Apr 2024
DOI:
https://doi.org/10.1175/WCAS-D-23-0001.1
Page(s):
275–301
Restricted access

Abstract

Extreme heat events stress the body and can result in fatalities, especially for those with underlying health problems. Air pollution is another threat to health and is an important confounder of extreme heat risks. However, previous empirical studies that have addressed the joint health impacts of air pollution and heat rarely considered the endogeneity and spillover effects of air pollution. To fill this research gap, this article investigates the interconnected impacts of extreme heat and fine particulate matter (PM2.5) on all-cause and cause-specific mortality. We correct the endogeneity of PM2.5 by applying the control function approach and explore transboundary externalities of all-source PM2.5 and wildfire-caused PM2.5. We use a county-year balanced panel dataset covering 2992 U.S. counties from 2001 through 2011. Results show that extreme heat and air pollution exacerbate each other and jointly increase mortality. Specifically, a 1-standard-deviation (SD) increase in the heat index results in 0.60% (95% confidence interval: 0.26%–0.97%), 2.14% (1.34%–2.94%), and 0.86% (0.41%–1.34%) more all-cause fatalities, fatalities from respiratory system diseases, and fatalities from circulatory system diseases, respectively. A 1-SD increase in PM2.5 results in 5.75% (3.61%–7.90%), 6.99% (3.01%–11.15%), and 2.93% (0.66%–5.28%) additional fatalities, respectively. Failure to consider the endogeneity of PM2.5 leads to a substantial underestimation of PM2.5 risk. In addition, our instrumental variable strategy offers evidence of spillover effects from PM2.5 and wildfires.

Significance Statement

This study illustrates how extreme heat events combined with air pollutants threaten health. This article investigates the interconnected impact of extreme heat and air pollution using data from 2992 United States counties over the 2001–11 period. Results indicate that extreme heat and air pollution jointly increase mortality. Results also show that wind-driven pollution from other counties and wildfires increase mortality.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Mark Skidmore, mskidmor@msu.edu

Abstract

Extreme heat events stress the body and can result in fatalities, especially for those with underlying health problems. Air pollution is another threat to health and is an important confounder of extreme heat risks. However, previous empirical studies that have addressed the joint health impacts of air pollution and heat rarely considered the endogeneity and spillover effects of air pollution. To fill this research gap, this article investigates the interconnected impacts of extreme heat and fine particulate matter (PM2.5) on all-cause and cause-specific mortality. We correct the endogeneity of PM2.5 by applying the control function approach and explore transboundary externalities of all-source PM2.5 and wildfire-caused PM2.5. We use a county-year balanced panel dataset covering 2992 U.S. counties from 2001 through 2011. Results show that extreme heat and air pollution exacerbate each other and jointly increase mortality. Specifically, a 1-standard-deviation (SD) increase in the heat index results in 0.60% (95% confidence interval: 0.26%–0.97%), 2.14% (1.34%–2.94%), and 0.86% (0.41%–1.34%) more all-cause fatalities, fatalities from respiratory system diseases, and fatalities from circulatory system diseases, respectively. A 1-SD increase in PM2.5 results in 5.75% (3.61%–7.90%), 6.99% (3.01%–11.15%), and 2.93% (0.66%–5.28%) additional fatalities, respectively. Failure to consider the endogeneity of PM2.5 leads to a substantial underestimation of PM2.5 risk. In addition, our instrumental variable strategy offers evidence of spillover effects from PM2.5 and wildfires.

Significance Statement

This study illustrates how extreme heat events combined with air pollutants threaten health. This article investigates the interconnected impact of extreme heat and air pollution using data from 2992 United States counties over the 2001–11 period. Results indicate that extreme heat and air pollution jointly increase mortality. Results also show that wind-driven pollution from other counties and wildfires increase mortality.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Mark Skidmore, mskidmor@msu.edu
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  • Aguilera, R., T. Corringham, A. Gershunov, and T. Benmarhnia, 2021: Wildfire smoke impacts respiratory health more than fine particles from other sources: Observational evidence from Southern California. Nat. Commun., 12, 1493, https://doi.org/10.1038/s41467-021-21708-0.

    • Search Google Scholar
    • Export Citation

  • Analitis, A., and Coauthors, 2014: Effects of heat waves on mortality: Effect modification and confounding by air pollutants. Epidemiology, 25, 15–22, https://doi.org/10.1097/EDE.0b013e31828ac01b.

    • Search Google Scholar
    • Export Citation

  • Anderson, B. G., and M. L. Bell, 2009: Weather-related mortality: How heat, cold, and heat waves affect mortality in the United States. Epidemiology, 20, 205–213, https://doi.org/10.1097/EDE.0b013e318190ee08.

    • Search Google Scholar
    • Export Citation

  • Anenberg, S. C., S. Haines, E. Wang, N. Nassikas, and P. L. Kinney, 2020: Synergistic health effects of air pollution, temperature, and pollen exposure: A systematic review of epidemiological evidence. Environ. Health, 19, 130, https://doi.org/10.1186/s12940-020-00681-z.

    • Search Google Scholar
    • Export Citation

  • Baccini, M., and Coauthors, 2008: Heat effects on mortality in 15 European cities. Epidemiology, 19, 711–719, https://doi.org/10.1097/EDE.0b013e318176bfcd.

    • Search Google Scholar
    • Export Citation

  • Banzhaf, H. S., and B. A. Chupp, 2010: Heterogeneous harm vs. spatial spillovers: Environmental federalism and US air pollution. NBER Working Paper 15666, 45 pp., https://doi.org/10.3386/w15666.

  • Barreca, A. I., 2012: Climate change, humidity, and mortality in the United States. J. Environ. Econ. Manage., 63, 19–34, https://doi.org/10.1016/j.jeem.2011.07.004.

    • Search Google Scholar
    • Export Citation

  • Barwick, P. J., S. Li, D. Rao, and N. B. Zahur, 2021: The healthcare cost of air pollution: Evidence from the world’s largest payment network. National Bureau of Economic Research Working Paper No. w24688, 79 pp., https://doi.org/10.3386/w24688.

  • Basu, R., and B. D. Ostro, 2008: A multicounty analysis identifying the populations vulnerable to mortality associated with high ambient temperature in California. Amer. J. Epidemiol., 168, 632–637, https://doi.org/10.1093/aje/kwn170.

    • Search Google Scholar
    • Export Citation

  • Bayer, P., N. Keohane, and C. Timmins, 2009: Migration and hedonic valuation: The case of air quality. J. Environ. Econ. Manage., 58, 1–14, https://doi.org/10.1016/j.jeem.2008.08.004.

    • Search Google Scholar
    • Export Citation

  • Breitner, S., K. Wolf, R. B. Devlin, D. Diaz-Sanchez, A. Peters, and A. Schneider, 2014: Short-term effects of air temperature on mortality and effect modification by air pollution in three cities of Bavaria, Germany: A time-series analysis. Sci. Total Environ., 485–486, 49–61, https://doi.org/10.1016/j.scitotenv.2014.03.048.

    • Search Google Scholar
    • Export Citation

  • Burkart, K., P. Canário, S. Breitner, A. Schneider, K. Scherber, H. Andrade, M. J. Alcoforado, and W. Endlicher, 2013: Interactive short-term effects of equivalent temperature and air pollution on human mortality in Berlin and Lisbon. Environ. Pollut., 183, 54–63, https://doi.org/10.1016/j.envpol.2013.06.002.

    • Search Google Scholar
    • Export Citation

  • Burke, M., A. Driscoll, S. Heft-Neal, J. Xue, J. Burney, and M. Wara, 2021: The changing risk and burden of wildfire in the United States. Proc. Natl. Acad. Sci. USA, 118, e2011048118, https://doi.org/10.1073/pnas.2011048118.

    • Search Google Scholar
    • Export Citation

  • Cameron, A. C., and P. K. Trivedi, 2013: Regression Analysis of Count Data. Cambridge University Press, 597 pp.

  • Chen, H., and Coauthors, 2017: Exposure to ambient air pollution and the incidence of dementia: A population-based cohort study. Environ. Int., 108, 271–277, https://doi.org/10.1016/j.envint.2017.08.020.

    • Search Google Scholar
    • Export Citation

  • Chen, S., Y. Chen, Z. Lei, and J.-S. Tan-Soo, 2021: Chasing clean air: Pollution-induced travels in China. J. Assoc. Environ. Resour. Econ., 8, 59–89, https://doi.org/10.1086/711476.

    • Search Google Scholar
    • Export Citation

  • Chen, X., and J. Ye, 2019: When the wind blows: Spatial spillover effects of urban air pollution in China. J. Environ. Plann. Manage., 62, 1359–1376, https://doi.org/10.1080/09640568.2018.1496071.

    • Search Google Scholar
    • Export Citation

  • Chen, X., S. Shao, Z. Tian, Z. Xie, and P. Yin, 2017: Impacts of air pollution and its spatial spillover effect on public health based on China’s big data sample. J. Cleaner Prod., 142, 915–925, https://doi.org/10.1016/j.jclepro.2016.02.119.

    • Search Google Scholar
    • Export Citation

  • Chen, Y., G. Zhi, Y. Feng, J. Fu, J. Feng, G. Sheng, and B. R. T. Simoneit, 2006: Measurements of emission factors for primary carbonaceous particles from residential raw-coal combustion in China. Geophys. Res. Lett., 33, L20815, https://doi.org/10.1029/2006GL026966.

    • Search Google Scholar
    • Export Citation

  • Chindapol, S., J. Blair, P. Osmond, and D. Prasad, 2017: A suitable thermal stress index for the elderly in summer tropical climates. Procedia Eng., 180, 932–943, https://doi.org/10.1016/j.proeng.2017.04.253.

    • Search Google Scholar
    • Export Citation

  • Creason, J., L. Neas, D. Walsh, R. Williams, L. Sheldon, D. Liao, and C. Shy, 2001: Particulate matter and heart rate variability among elderly retirees: The Baltimore 1998 PM study. J. Expo. Sci. Environ. Epidemiol., 11, 116–122, https://doi.org/10.1038/sj.jea.7500154.

    • Search Google Scholar
    • Export Citation

  • Dawson, J. P., B. J. Bloomer, D. A. Winner, and C. P. Weaver, 2014: Understanding the meteorological drivers of U.S. particulate matter concentrations in a changing climate. Bull. Amer. Meteor. Soc., 95, 521–532, https://doi.org/10.1175/BAMS-D-12-00181.1.

    • Search Google Scholar
    • Export Citation

  • De Sario, M., K. Katsouyanni, and P. Michelozzi, 2013: Climate change, extreme weather events, air pollution and respiratory health in Europe. Eur. Respir. J., 42, 826–843, https://doi.org/10.1183/09031936.00074712.

    • Search Google Scholar
    • Export Citation

  • Deschênes, O., 2014: Temperature, human health, and adaptation: A review of the empirical literature. Energy Econ., 46, 606–619, https://doi.org/10.1016/j.eneco.2013.10.013.

    • Search Google Scholar
    • Export Citation

  • Deschênes, O., and E. Moretti, 2009: Extreme weather events, mortality, and migration. Rev. Econ. Stat., 91, 659–681, https://doi.org/10.1162/rest.91.4.659.

    • Search Google Scholar
    • Export Citation

  • Deschênes, O., and M. Greenstone, 2011: Climate change, mortality, and adaptation: Evidence from annual fluctuations in weather in the US. Amer. Econ. J. Appl. Econ., 3, 152–185, https://doi.org/10.1257/app.3.4.152.

    • Search Google Scholar
    • Export Citation

  • D’Ippoliti, D., and Coauthors, 2010: The impact of heat waves on mortality in 9 European cities: Results from the EuroHEAT project. Environ. Health, 9, 37, https://doi.org/10.1186/1476-069X-9-37.

    • Search Google Scholar
    • Export Citation

  • Dittrich, R., and S. McCallum, 2020: How to measure the economic health cost of wildfires—A systematic review of the literature for northern America. Int. J. Wildland Fire, 29, 961–973, https://doi.org/10.1071/WF19091.

    • Search Google Scholar
    • Export Citation

  • EPA, 2019: Integrated Science Assessment (ISA) for particulate matter. EPA Final Rep. EPA/600/R-19/188, 1967 pp., https://ordspub.epa.gov/ords/eims/eimscomm.getfile?p_download_id=539935.

  • EPA, 2020: Policy assessment for the review of the National Ambient Air Quality standards for particulate matter. EPA-452/R-20-002, 534 pp., https://www.epa.gov/system/files/documents/2021-10/final-policy-assessment-for-the-review-of-the-pm-naaqs-01-2020.pdf.

  • Fann, N., S.-Y. Kim, C. Olives, and L. Sheppard, 2017: Estimated changes in life expectancy and adult mortality resulting from declining PM2.5 exposures in the contiguous United States: 1980–2010. Environ. Health Perspect., 125, 097003, https://doi.org/10.1289/EHP507.

    • Search Google Scholar
    • Export Citation

  • Fann, N., E. Coffman, A. Hajat, and S.-Y. Kim, 2019: Change in fine particle-related premature deaths among US population subgroups between 1980 and 2010. Air Qual. Atmos. Health, 12, 673–682, https://doi.org/10.1007/s11869-019-00686-9.

    • Search Google Scholar
    • Export Citation

  • Freeman, A. M., III, J. A. Herriges, and C. L. Kling, 2014: The Measurement of Environmental and Resource Values: Theory and Methods. 3rd ed. Routledge, 478 pp.

  • Gabriel, K. M. A., and W. R. Endlicher, 2011: Urban and rural mortality rates during heat waves in Berlin and Brandenburg, Germany. Environ. Pollut., 159, 2044–2050, https://doi.org/10.1016/j.envpol.2011.01.016.

    • Search Google Scholar
    • Export Citation

  • Gold, D. R., and Coauthors, 2000: Ambient pollution and heart rate variability. Circulation, 101, 1267–1273, https://doi.org/10.1161/01.CIR.101.11.1267.

    • Search Google Scholar
    • Export Citation

  • Gordon, C. J., 2003: Role of environmental stress in the physiological response to chemical toxicants. Environ. Res., 92 (1), 1–7, https://doi.org/10.1016/S0013-9351(02)00008-7.

    • Search Google Scholar
    • Export Citation

  • Hajian Tilaki, K., 2012: Methodological issues of confounding in analytical epidemiologic studies. Caspian J. Intern. Med., 3, 488–495.

    • Search Google Scholar
    • Export Citation

  • Hammer, M. S., and Coauthors, 2020: Global estimates and long-term trends of fine particulate matter concentrations (1998–2018). Environ. Sci. Technol., 54, 7879–7890, https://doi.org/10.1021/acs.est.0c01764.

    • Search Google Scholar
    • Export Citation

  • Hayhoe, K., and Coauthors, 2018: Our changing climate. Impacts, Risks, and Adaptation in the United States: The Fourth National Climate Assessment, Vol. II, D. R. Reidmiller et al., Eds., U.S. Global Change Research Program, 72–144.

  • Heal, G., and J. Park, 2016: Reflections—Temperature stress and the direct impact of climate change: A review of an emerging literature. Rev. Environ. Econ. Policy, 10, 347–362, https://doi.org/10.1093/reep/rew007.

    • Search Google Scholar
    • Export Citation

  • Hernandez, G., T.-A. Berry, S. L. Wallis, and D. Poyner, 2017: Temperature and humidity effects on particulate matter concentrations in a sub-tropical climate during winter. Proceedings of International Conference of the Environment, Chemistry and Biology, L. Juan, Ed., 41–49, https://www.researchbank.ac.nz/handle/10652/4299.

  • Hoek, G., R. M. Krishnan, R. Beelen, A. Peters, B. Ostro, B. Brunekreef, and J. D. Kaufman, 2013: Long-term air pollution exposure and cardio-respiratory mortality: A review. Environ. Health, 12, 43, https://doi.org/10.1186/1476-069X-12-43.

    • Search Google Scholar
    • Export Citation

  • Huang, W., H. Kan, and S. Kovats, 2010: The impact of the 2003 heat wave on mortality in Shanghai, China. Sci. Total Environ., 408, 2418–2420, https://doi.org/10.1016/j.scitotenv.2010.02.009.

    • Search Google Scholar
    • Export Citation

  • Institute for Health Metrics and Evaluation, 2013: United States physical activity and obesity prevalence by county 2001–2011. IHME, accessed 23 September 2020, https://doi.org/10.6069/5E84-HD26.

  • Institute for Health Metrics and Evaluation, 2014: United States smoking prevalence by county 1996–2012. IHME, accessed 23 September 2020, https://doi.org/10.6069/H6ZD-KX77.

  • Jacob, D. J., and D. A. Winner, 2009: Effect of climate change on air quality. Atmos. Environ., 43, 51–63, https://doi.org/10.1016/j.atmosenv.2008.09.051.

    • Search Google Scholar
    • Export Citation

  • Jeffery, P. K., 1999: Effects of cigarette smoke and air pollutants on the lower respiratory tract. Air Pollution and Health, Elsevier, 219–268.

  • Jhun, I., N. Fann, A. Zanobetti, and B. Hubbell, 2014: Effect modification of ozone-related mortality risks by temperature in 97 US cities. Environ. Int., 73, 128–134, https://doi.org/10.1016/j.envint.2014.07.009.

    • Search Google Scholar
    • Export Citation

  • Karlsson, M., and N. R. Ziebarth, 2018: Population health effects and health-related costs of extreme temperatures: Comprehensive evidence from Germany. J. Environ. Econ. Manage., 91, 93–117, https://doi.org/10.1016/j.jeem.2018.06.004.

    • Search Google Scholar
    • Export Citation

  • Katsouyanni, K., and Coauthors, 2001: Confounding and effect modification in the short-term effects of ambient particles on total mortality: Results from 29 European cities within the APHEA2 project. Epidemiology, 12, 521–531, https://doi.org/10.1097/00001648-200109000-00011.

    • Search Google Scholar
    • Export Citation

  • Khawand, C., 2015: Air quality, mortality, and perinatal health: Causal evidence from wildfires. Department of Economics, Michigan State University, 61 pp., https://ideas.repec.org/jmp/2015/pkh318.pdf.

  • Knol, M. J., and T. J. VanderWeele, 2012: Recommendations for presenting analyses of effect modification and interaction. Int. J. Epidemiol., 41, 514–520, https://doi.org/10.1093/ije/dyr218.

    • Search Google Scholar
    • Export Citation

  • Knowlton, K., M. Rotkin-Ellman, G. King, H. G. Margolis, D. Smith, G. Solomon, R. Trent, and P. English, 2009: The 2006 California heat wave: Impacts on hospitalizations and emergency department visits. Environ. Health Perspect., 117, 61–67, https://doi.org/10.1289/ehp.11594.

    • Search Google Scholar
    • Export Citation

  • Kochi, I., G. H. Donovan, P. A. Champ, and J. B. Loomis, 2010: The economic cost of adverse health effects from wildfire-smoke exposure: A review. Int. J. Wildland Fire, 19, 803–817, https://doi.org/10.1071/WF09077.

    • Search Google Scholar
    • Export Citation

  • Kovats, R. S., and S. Hajat, 2008: Heat stress and public health: A critical review. Annu. Rev. Public Health, 29, 41–55, https://doi.org/10.1146/annurev.publhealth.29.020907.090843.

    • Search Google Scholar
    • Export Citation

  • Lavaine, E., 2015: An econometric analysis of atmospheric pollution, environmental disparities and mortality rates. Environ. Resour. Econ., 60, 215–242, https://doi.org/10.1007/s10640-014-9765-0.

    • Search Google Scholar
    • Export Citation

  • Li, J., and Coauthors, 2017: Modification of the effects of air pollutants on mortality by temperature: A systematic review and meta-analysis. Sci. Total Environ., 575, 1556–1570, https://doi.org/10.1016/j.scitotenv.2016.10.070.

    • Search Google Scholar
    • Export Citation

  • Lim, J., and M. Skidmore, 2020: Heat vulnerability and heat island mitigation in the United States. Atmosphere, 11, 558, https://doi.org/10.3390/atmos11060558.

    • Search Google Scholar
    • Export Citation

  • Lin, S., M. Luo, R. J. Walker, X. Liu, S.-A. Hwang, and R. Chinery, 2009: Extreme high temperatures and hospital admissions for respiratory and cardiovascular diseases. Epidemiology, 20, 738–746, https://doi.org/10.1097/EDE.0b013e3181ad5522.

    • Search Google Scholar
    • Export Citation

  • Liu, J. C., and Coauthors, 2017: Wildfire-specific fine particulate matter and risk of hospital admissions in urban and rural counties. Epidemiology, 28, 77–85, https://doi.org/10.1097/EDE.0000000000000556.

    • Search Google Scholar
    • Export Citation

  • Luber, G., and M. McGeehin, 2008: Climate change and extreme heat events. Amer. J. Prev. Med., 35, 429–435, https://doi.org/10.1016/j.amepre.2008.08.021.

    • Search Google Scholar
    • Export Citation

  • Luechinger, S., 2010: Life satisfaction and transboundary air pollution. Econ. Lett., 107, 4–6, https://doi.org/10.1016/j.econlet.2009.07.007.

    • Search Google Scholar
    • Export Citation

  • McGeehin, M. A., and M. Mirabelli, 2001: The potential impacts of climate variability and change on temperature-related morbidity and mortality in the United States. Environ. Health Perspect, 109, 185–189, https://doi.org/10.1289/ehp.109-1240665.

    • Search Google Scholar
    • Export Citation

  • Miller, N., D. Molitor, and E. Zou, 2017: Blowing smoke: Health impacts of wildfire plume dynamics. Environmental and Resource Economics at the University of Illinois, 35 pp., https://static1.squarespace.com/static/56034c20e4b047f1e0c1bfca/t/59e2e4fe0100271556d54e1a/1508041986866/smoke_MMZ_201710.pdf.

  • Mocko, D., and NASA/GSFC/HSL, 2012: NLDAS primary forcing data L4 monthly 0.125 × 0.125 degree V002. 2012. Goddard Earth Sciences Data and Information Services Center, accessed 7 February 2021, https://doi.org/10.5067/Z62LT6J96R4F.

  • Neumann, J. E., and Coauthors, 2021: Estimating PM2.5-related premature mortality and morbidity associated with future wildfire emissions in the western US. Environ. Res. Lett., 16, 035019, https://doi.org/10.1088/1748-9326/abe82b.

    • Search Google Scholar
    • Export Citation

  • NLDAS, 2012a: Daily air temperatures and heat index, years 1979–2011. NLDAS, accessed 17 November 2019, https://wonder.cdc.gov/NASA-NLDAS.html.

  • NLDAS, 2012b: Daily precipitation, years 1979–2011. NLDAS, accessed 13 August 2019, https://wonder.cdc.gov/NASA-precipitation.html.

  • O’Neill, M. S., S. Hajat, A. Zanobetti, M. Ramirez-Aguilar, and J. Schwartz, 2005: Impact of control for air pollution and respiratory epidemics on the estimated associations of temperature and daily mortality. Int. J. Biometeor., 50, 121–129, https://doi.org/10.1007/s00484-005-0269-z.

    • Search Google Scholar
    • Export Citation

  • Park, A. K., Y. C. Hong, and H. Kim, 2011: Effect of changes in season and temperature on mortality associated with air pollution in Seoul, Korea. J. Epidemiol. Community Health, 65, 368–375, https://doi.org/10.1136/jech.2009.089896.

    • Search Google Scholar
    • Export Citation

  • Pascal, M., V. Wagner, A. Alari, M. Corso, and A. Le Tertre, 2021: Extreme heat and acute air pollution episodes: A need for joint public health warnings? Atmos. Environ., 249, 118249, https://doi.org/10.1016/j.atmosenv.2021.118249.

    • Search Google Scholar
    • Export Citation

  • Peterson, G. C. L., C. Hogrefe, A. E. Corrigan, L. M. Neas, R. Mathur, and A. G. Rappold, 2020: Impact of reductions in emissions from major source sectors on fine particulate matter-related cardiovascular mortality. Environ. Health Perspect., 128, 017005, https://doi.org/10.1289/EHP5692.

    • Search Google Scholar
    • Export Citation

  • Pope, C. A., III, and D. W. Dockery, 2006: Health effects of fine particulate air pollution: Lines that connect. J. Air Waste Manage. Assoc., 56, 709–742, https://doi.org/10.1080/10473289.2006.10464485.

    • Search Google Scholar
    • Export Citation

  • Pye, H. O. T., C. K. Ward-Caviness, B. N. Murphy, K. W. Appel, and K. M. Seltzer, 2021: Secondary organic aerosol association with cardiorespiratory disease mortality in the United States. Nat. Commun., 12, 7215, https://doi.org/10.1038/s41467-021-27484-1.

    • Search Google Scholar
    • Export Citation

  • Rai, M., and Coauthors, 2023: Heat-related cardiorespiratory mortality: Effect modification by air pollution across 482 cities from 24 countries. Environ. Int., 174, 107825, https://doi.org/10.1016/j.envint.2023.107825.

    • Search Google Scholar
    • Export Citation

  • Rainham, D. G. C., and K. E. Smoyer-Tomic, 2003: The role of air pollution in the relationship between a heat stress index and human mortality in Toronto. Environ. Res., 93, 9–19, https://doi.org/10.1016/S0013-9351(03)00060-4.

    • Search Google Scholar
    • Export Citation

  • Ren, C., G. M. Williams, and S. Tong, 2006: Does particulate matter modify the association between temperature and cardiorespiratory diseases? Environ. Health Perspect., 114, 1690–1696, https://doi.org/10.1289/ehp.9266.

    • Search Google Scholar
    • Export Citation

  • Sarwar, S., D. Streimikiene, R. Waheed, and Z. Mighri, 2021: Revisiting the empirical relationship among the main targets of sustainable development: Growth, education, health and carbon emissions. Sustainable Dev., 29, 419–440, https://doi.org/10.1002/sd.2156.

    • Search Google Scholar
    • Export Citation

  • Schlenker, W., and W. R. Walker, 2016: Airports, air pollution, and contemporaneous health. Rev. Econ. Stud., 83, 768–809, https://doi.org/10.1093/restud/rdv043.

    • Search Google Scholar
    • Export Citation

  • Scortichini, M., M. De Sario, F. K. De’Donato, M. Davoli, P. Michelozzi, and M. Stafoggia, 2018: Short-term effects of heat on mortality and effect modification by air pollution in 25 Italian cities. Int. J. Environ. Res. Public Health, 15, 1771, https://doi.org/10.3390/ijerph15081771.

    • Search Google Scholar
    • Export Citation

  • Short, K. C., 2017: Spatial wildfire occurrence data for the United States, 1992–2015 [FPA_FOD_20170508]. 4th ed. Forest Service Research Data Archive, accessed 6 May 2019, https://doi.org/10.2737/RDS-2013-0009.4.

  • Stafoggia, M., J. Schwartz, F. Forastiere, and C. Perucci, 2008: Does temperature modify the association between air pollution and mortality? A multicity case-crossover analysis in Italy. Amer. J. Epidemiol., 167, 1476–1485, https://doi.org/10.1093/aje/kwn074.

    • Search Google Scholar
    • Export Citation

  • Steadman, R. G., 1979: The assessment of sultriness. Part I: A temperature-humidity index based on human physiology and clothing science. J. Appl. Meteor. Climatol., 18, 861–873, https://doi.org/10.1175/1520-0450(1979)018<0861:TAOSPI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Steadman, R. G., 1984: A universal scale of apparent temperature. J. Climate Appl. Meteor., 23, 1674–1687, https://doi.org/10.1175/1520-0450(1984)023<1674:AUSOAT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Stone, S. L., and Coauthors, 2019: Wildfire Smoke: A Guide for Public Health Officials. US Environmental Protection Agency, 88 pp.

  • Stott, P. A., and Coauthors, 2016: Attribution of extreme weather and climate-related events. Wiley Interdiscip. Rev.: Climate Change, 7, 23–41, https://doi.org/10.1002/wcc.380.

    • Search Google Scholar
    • Export Citation

  • Tai, A. P. K., L. J. Mickley, and D. J. Jacob, 2010: Correlations between fine particulate matter (PM2.5) and meteorological variables in the United States: Implications for the sensitivity of PM2.5 to climate change. Atmos. Environ., 44, 3976–3984, https://doi.org/10.1016/j.atmosenv.2010.06.060.

    • Search Google Scholar
    • Export Citation

  • Tan Soo, J.-S., 2018: Valuing air quality in Indonesia using households’ locational choices. Environ. Resour. Econ., 71, 755–776, https://doi.org/10.1007/s10640-017-0182-z.

    • Search Google Scholar
    • Export Citation

  • U.S. Bureau of Economic Analysis, 2020a: CAGDP1 gross domestic product (GDP) summary by county and metropolitan area. Accessed 13 July 2020, https://apps.bea.gov/itable/iTable.cfm?ReqID=70&step=1.

  • U.S. Bureau of Economic Analysis, 2020b: CAINC30 economic profile by county and metropolitan area. Accessed 27 December 2020, https://apps.bea.gov/itable/iTable.cfm?ReqID=70&step=1.

  • U.S. Bureau of Labor Statistics, 2021: Consumer price index retroactive series using current methods (R-CPI-U-RS). Accessed 13 February 2021, https://www.bls.gov/cpi/research-series/r-cpi-u-rs-home.htm.

  • U.S. Census Bureau, 2000a: Census GCT-PH1 population, housing units, area, and density: 2000—county—census tract. Accessed 10 February 2020, https://factfinder.census.gov/.

  • U.S. Census Bureau, 2000b: Census P002 urban and rural. Accessed 5 February 2020, https://factfinder.census.gov/.

  • U.S. Census Bureau, 2010a: TIGER/Line shapefiles. Accessed 11 February 2021, https://www2.census.gov/geo/tiger/TIGER2010.

  • U.S. Census Bureau, 2010b: Intercensal estimates of the resident population by five-year age groups and sex for counties: April 1, 2000 to July 1, 2010. Accessed 15 September 2020, https://www.census.gov/data/datasets/time-series/demo/popest/intercensal-2000-2010-counties.html.

  • U.S. Census Bureau, 2010c: Census GCT-PH1 population, housing units, area, and density: 2010—United States—county; and for Puerto Rico. Accessed 17 February 2020, https://factfinder.census.gov/.

  • U.S. Census Bureau, 2010d: Census P2 urban and rural. Accessed 5 February 2020, https://factfinder.census.gov/.

  • U.S. Census Bureau, 2019a: Annual county resident population estimates by age, sex, race, and Hispanic origin: April 1, 2010 to July 1, 2019. Accessed 13 August 2020 https://www.census.gov/data/datasets/time-series/demo/popest/2010s-counties-detail.html.

  • U.S. Census Bureau, 2019b: Small Area Income and Poverty Estimates (SAIPE) program online database. Accessed 11 February 2020, https://www.census.gov/programs-surveys/saipe/data/datasets.html.

  • U.S. Department of Health and Human Services, CDC, and National Center for Health Statistics, 2018: Underlying cause of death 1999–2017. Accessed 9 January 2020, https://wonder.cdc.gov/ucd-icd10.html.

  • U.S. Department of Health and Human Services, CDC, and National Center for Health Statistics, 2020: Underlying cause of death 1999–2019. Accessed 11 February 2021, https://wonder.cdc.gov/ucd-icd10.html.

  • U.S. Global Change Research Program, 2019: Heat waves. USGCRP, accessed 19 November 2019, https://www.globalchange.gov/browse/indicators/us-heat-waves.

  • VanderWeele, T. J., 2009: On the distinction between interaction and effect modification. Epidemiology, 20, 863–871, https://doi.org/10.1097/EDE.0b013e3181ba333c.

    • Search Google Scholar
    • Export Citation

  • van Donkelaar, A., R. V. Martin, C. Li, and R. T. Burnett, 2019: Regional estimates of chemical composition of fine particulate matter using a combined geoscience-statistical method with information from satellites, models, and monitors. Environ. Sci. Technol., 53, 2595–2611, https://doi.org/10.1021/acs.est.8b06392.

    • Search Google Scholar
    • Export Citation

  • Williams, A. M., and D. J. Phaneuf, 2019: The morbidity costs of air pollution: Evidence from spending on chronic respiratory conditions. Environ. Resour. Econ., 74, 571–603, https://doi.org/10.1007/s10640-019-00336-9.

    • Search Google Scholar
    • Export Citation

  • Wooldridge, J. M., 2010: Econometric Analysis of Cross Section and Panel Data. MIT Press, 741 pp.

  • Wooldridge, J. M., 2015: Control function methods in applied econometrics. J. Hum. Resour., 50, 420–445, https://doi.org/10.3368/jhr.50.2.420.

    • Search Google Scholar
    • Export Citation

  • Wrenn, D. H., H. A. Klaiber, and D. A. Newburn, 2017: Confronting price endogeneity in a duration model of residential subdivision development. J. Appl. Econ., 32, 661–682, https://doi.org/10.1002/jae.2546.

    • Search Google Scholar
    • Export Citation

  • Wuebbles, D. J., D. W. Fahey, K. A. Hibbard, D. J. Dokken, B. C. Stewart, and T. K. Maycock, 2017: Climate science special report: Fourth national climate assessment, volume I. U.S. Global Change Research Program, 470 pp., https://doi.org/10.7930/J0J964J6.

  • Xia, Y., and Coauthors, 2012: Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products. J. Geophys. Res., 117, D03109, https://doi.org/10.1029/2011JD016048.

    • Search Google Scholar
    • Export Citation

  • Xu, B., T. Yao, X. Liu, and N. Wang, 2006: Elemental and organic carbon measurements with a two-step heating-gas chromatography system in snow samples from the Tibetan Plateau. Ann. Glaciol., 43, 257–262, https://doi.org/10.3189/172756406781812122.

    • Search Google Scholar
    • Export Citation

  • Yang, D., and Coauthors, 2021: Associations between fine particulate matter constituents and hospital outpatient and emergency room visits in Shanghai, China. Atmos. Environ., 261, 118606, https://doi.org/10.1016/j.atmosenv.2021.118606.

    • Search Google Scholar
    • Export Citation

  • Yang, J., and B. Zhang, 2018: Air pollution and healthcare expenditure: Implication for the benefit of air pollution control in China. Environ. Int., 120, 443–455, https://doi.org/10.1016/j.envint.2018.08.011.

    • Search Google Scholar
    • Export Citation

  • Yu, X., X. Lei, and M. Wang, 2019: Temperature effects on mortality and household adaptation: Evidence from China. J. Environ. Econ. Manage., 96, 195–212, https://doi.org/10.1016/j.jeem.2019.05.004.

    • Search Google Scholar
    • Export Citation

  • Zhang, H., Y. Wang, T.-W. Park, and Y. Deng, 2017: Quantifying the relationship between extreme air pollution events and extreme weather events. Atmos. Res., 188, 64–79, https://doi.org/10.1016/j.atmosres.2016.11.010.

    • Search Google Scholar
    • Export Citation

  • Zheng, S., J. Cao, M. E. Kahn, and C. Sun, 2014: Real estate valuation and cross-boundary air pollution externalities: Evidence from Chinese cities. J. Real Estate Finance Econ., 48, 398–414, https://doi.org/10.1007/s11146-013-9405-4.

    • Search Google Scholar
    • Export Citation

  • Zheng, S., X. Zhang, W. Sun, and C. Lin, 2019: Air pollution and elite college graduates’ job location choice: Evidence from China. Ann. Reg. Sci., 63, 295–316, https://doi.org/10.1007/s00168-019-00939-6.

    • Search Google Scholar
    • Export Citation
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