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Improved asthma outcomes observed in the vicinity of coal power plant retirement, retrofit and conversion to natural gas


Coal-fired power plants release substantial air pollution, which included over 60% of US sulfur dioxide emissions in 2014. Such air pollution may exacerbate asthma, but direct studies of the health impacts linked to power plant air pollution are rare. Here we take advantage of a natural experiment in Louisville, Kentucky, where one coal-fired power plant was retired and converted to natural gas, and three others installed SO2 emission control systems between 2013 and 2016. Dispersion modelling indicated that exposure to SO2 emissions from these power plants decreased after the energy transitions. We used several analysis strategies, which include difference-in-differences, first-difference and interrupted time-series modelling to show that the emissions control installations and plant retirements are associated with a reduced asthma disease burden related to hospitalizations and emergency room visits at the ZIP-code level, and to individual-level medication use as measured by digital medication sensors.

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Fig. 1: Power plant locations, emissions and exposure.
Fig. 2: Quarterly mean ZIP code-level HyADS exposure in Jefferson County.
Fig. 3: Quarterly ZIP-code-level counts of asthma hospitalizations and ERVs in Jefferson County.
Fig. 4: Spring 2015 coal-fired power plant events and counts of ZIP-code-level asthma hospitalization and ERVs.
Fig. 5: Monthly mean ZIP-code-level HyADS exposure from the Mill Creek power plant in Jefferson County, 2015–2017.
Fig. 6: Monthly average daily SABA use before and after the June 2016 Mill Creek SO2 scrubber installation.

Data availability

The ZIP-code-level asthma hospitalization and ERV data are available from the authors following the submission of an analysis proposal and written approval granted by the Louisville Metro Public Health and Wellness. The AIR Louisville monthly medication use data are considered Protected Health Information under the Health Insurance Portability and Accountability Act of 1996 (HIPAA) in the United States, and as such may be accessible from the authors for analysis only after specific written authorization of access following HIPAA guidelines and Institutional Review Board approval. We provide Jefferson County ZIP-code-level monthly HyADS estimates on GitHub at

Code availability

An R package is available on GitHub for running the HyADS model ( We also provide analysis code on GitHub at


  1. 1.

    IEA Statistics (International Energy Agency, 2018);

  2. 2.

    Massetti, E. et al. Environmental Quality and the US Power Sector: Air Quality, Water Quality, Land Use and Environmental Justice (Oak Ridge National Laboratory, 2017);–Environmental%20Quality%20and%20the%20U.S.%20Power%20Sector–Air%20Quality%2C%20Water%20Quality%2C%20Land%20Use%2C%20and%20Environmental%20Justice.pdf

  3. 3.

    Toxic Air: The Case for Cleaning Up Coal-Fired Power Plants (American Lung Association, 2011);

  4. 4.

    Zheng, X.-Y et al. Association between air pollutants and asthma emergency room visits and hospital admissions in time series studies: a systematic review and meta-analysis. PLoS ONE 10, e0138146 (2015).

    Google Scholar 

  5. 5.

    Orellano, P., Quaranta, N., Reynoso, J., Balbi, B. & Vasquez, J. Effect of outdoor air pollution on asthma exacerbations in children and adults: systematic review and multilevel meta-analysis. PLoS ONE 12, e0174050 (2017).

    Google Scholar 

  6. 6.

    Williams, A. M., Phaneuf, D. J., Barrett, M. A. & Su, J. G. Short-term impact of PM2.5 on contemporaneous asthma medication use: behavior and the value of pollution reductions. Proc. Natl Acad. Sci. USA 116, 5246–5253 (2019).

    Google Scholar 

  7. 7.

    Integrated Science Assessment for Oxides of Nitrogen-Health Criteria (US Environmental Protection Agency, 2016);

  8. 8.

    Integrated Review Plan for the Primary National Ambient Air Quality Standard for Sulfur Dioxide EPA-452/R-14-007 (US Environmental Protection Agency, 2014);

  9. 9.

    Ramadour, M. et al. Prevalence of asthma and rhinitis in relation to long-term exposure to gaseous air pollutants. Allergy 55, 1163–1169 (2000).

    Google Scholar 

  10. 10.

    Guarnieri, M. & Balmes, J. R. Outdoor air pollution and asthma. Lancet 383, 1581–1592 (2014).

    Google Scholar 

  11. 11.

    Deger, L. et al. Active and uncontrolled asthma among children exposed to air stack emissions of sulphur dioxide from petroleum refineries in Montreal, Quebec: a cross-sectional study. Can. Respir. J. 19, 97–102 (2012).

    Google Scholar 

  12. 12.

    Charpin, D. et al. Respiratory symptoms and air pollution changes in children: the Gardanne Coal-Basin Study. Arch. Environ. Health 43, 22–27 (1988).

    Google Scholar 

  13. 13.

    Schenker, M. B., Speizer, F. E., Samet, J. M., Gruhl, J. & Batterman, S. Health effects of air pollution due to coal combustion in the Chestnut Ridge Region of Pennsylvania: results of cross-sectional analysis in adults. Arch. Environ. Health 38, 325–330 (1983).

    Google Scholar 

  14. 14.

    Dubnov, J. et al. Estimating the effect of air pollution from a coal-fired power station on the development of children’s pulmonary function. Environ. Res. 103, 87–98 (2007).

    Google Scholar 

  15. 15.

    Cohen, A. A., Bromberg, S., Buechley, R. W., Heiderscheit, L. T. & Shy, C. M. Asthma and air pollution from a coal-fueled power plant. Am. J. Public Health 62, 1181–1188 (1972).

    Google Scholar 

  16. 16.

    Smargiassi, A. et al. Risk of asthmatic episodes in children exposed to sulfur dioxide stack emissions from a refinery point source in Montreal, Canada. Environ. Health Perspect. 117, 653 (2009).

    Google Scholar 

  17. 17.

    Rodriguez-Villamizar, L. A., Rosychuk, R. J., Osornio-Vargas, A., Villeneuve, P. J. & Rowe, B. H. Proximity to two main sources of industrial outdoor air pollution and emergency department visits for childhood asthma in Edmonton, Canada. Can. J. Public Health 108, e523–e529 (2017).

    Google Scholar 

  18. 18.

    Middleton, N., Kolokotroni, O., Lamnisos, D., Koutrakis, P. & Yiallouros, P. K. Prevalence of asthma and respiratory symptoms in 15–17-year-old Greek-Cypriots by proximity of their community of residence to power plants: Cyprus 2006–07. Public Health 128, 288–296 (2014).

    Google Scholar 

  19. 19.

    Liu, X., Lessner, L. & Carpenter, D. O. Association between residential proximity to fuel-fired power plants and hospitalization rate for respiratory diseases. Environ. Health Perspect. 120, 807–810 (2012).

    Google Scholar 

  20. 20.

    Form EIA-860 (US Energy Information Administration, 2019);

  21. 21.

    Humphreys, D. K., Panter, J., Sahlqvist, S., Goodman, A. & Ogilvie, D. Changing the environment to improve population health: a framework for considering exposure in natural experimental studies. J. Epidemiol. Community Health 70, 941–946 (2016).

    Google Scholar 

  22. 22.

    Rich, D. Q. Accountability studies of air pollution and health effects: lessons learned and recommendations for future natural experiment opportunities. Environ. Int. 100, 62–78 (2017).

    Google Scholar 

  23. 23.

    Zigler, C. M. & Dominici, F. Point: clarifying policy evidence with potential-outcomes thinking—beyond exposure–response estimation in air pollution epidemiology. Am. J. Epidemiol. 180, 1133–1140 (2014).

    Google Scholar 

  24. 24.

    Pope, C. A. 3rd Respiratory disease associated with community air pollution and a steel mill, Utah Valley. Am. J. Public Health 79, 623–628 (1989).

    Google Scholar 

  25. 25.

    Clancy, L., Goodman, P., Sinclair, H. & Dockery, D. W. Effect of air-pollution control on death rates in Dublin, Ireland: an intervention study. Lancet 360, 1210–1214 (2002).

    Google Scholar 

  26. 26.

    Friedman, M. S., Powell, K. E., Hutwagner, L., Graham, L. M. & Teague, W. G. Impact of changes in transportation and commuting behaviors during the 1996 Summer Olympic Games in Atlanta on air quality and childhood asthma. J. Am. Med. Assoc. 285, 897–905 (2001).

    Google Scholar 

  27. 27.

    Li, Y., Wang, W., Kan, H., Xu, X. & Chen, B. Air quality and outpatient visits for asthma in adults during the 2008 Summer Olympic Games in Beijing. Sci. Total. Environ. 408, 1226–1227 (2010).

    Google Scholar 

  28. 28.

    Deschenes, O., Greenstone, M. & Shapiro, J. S. Defensive investments and the demand for air quality: evidence from the NOx budget program. Am. Econ. Rev. 107, 2958–2989 (2017).

    Google Scholar 

  29. 29.

    National Emissions Inventory (US Environmental Protection Agency, 2011);

  30. 30.

    Henneman, L. R. F., Choirat, C., Ivey, C. E., Cummiskey, K. & Zigler, C. M. Characterizing population exposure to coal emissions sources in the United States using the HyADS model. Atmos. Environ. 203, 271–280 (2019).

    Google Scholar 

  31. 31.

    Henneman, L. R. F., Mickley, L. J. & Zigler, C. M. Air pollution accountability of energy transitions: the relative importance of wind fields and emissions in exposure changes. Environ. Res. Lett. 14, 115003 (2019).

    Google Scholar 

  32. 32.

    Zein, J. G. et al. Impact of age and sex on outcomes and hospital cost of acute asthma in the United States, 2011-2012. PLoS ONE 11, e0157301 (2016).

    Google Scholar 

  33. 33.

    Patel, M. et al. Metrics of salbutamol use as predictors of future adverse outcomes in asthma. Clin. Exp. Allergy 43, 1144–1151 (2013).

    Google Scholar 

  34. 34.

    Prieto-Parra, L. et al. Air pollution, PM2.5 composition, source factors, and respiratory symptoms in asthmatic and nonasthmatic children in Santiago, Chile. Environ. Int 101, 190–200 (2017).

    Google Scholar 

  35. 35.

    Schildcrout, J. S. et al. Ambient air pollution and asthma exacerbations in children: an eight-city analysis. Am. J. Epidemiol. 164, 505–517 (2006).

    Google Scholar 

  36. 36.

    U.S. Environmental Protection Agency. Federal Registrar. Primary National Ambient Air Quality Standard for Sulfur Dioxide, Final Rule, 40 CFR Parts 50, 53, and 58., <> (2010).

  37. 37.

    Gowers, A. M. et al. Does outdoor air pollution induce new cases of asthma? Biological plausibility and evidence; a review. Respirology 17, 887–898 (2012).

    Google Scholar 

  38. 38.

    Johns, D. O. & Linn, W. S. A review of controlled human SO2 exposure studies contributing to the US EPA integrated science assessment for sulfur oxides. Inhal. Toxicol. 23, 33–43 (2011).

    Google Scholar 

  39. 39.

    Li, R. et al. Effect of sulfur dioxide on inflammatory and immune regulation in asthmatic rats. Chemosphere 112, 296–304 (2014).

    Google Scholar 

  40. 40.

    Amster, E. D., Haim, M., Dubnov, J. & Broday, D. M. Contribution of nitrogen oxide and sulfur dioxide exposure from power plant emissions on respiratory symptom and disease prevalence. Envrion. Pollut. 186, 20–28 (2014).

    Google Scholar 

  41. 41.

    Anenberg, S. C. et al. Estimates of the global burden of ambient PM2.5, ozone, and NO2 on asthma incidence and emergency room visits. Environ. Health Perspect. 126, 107004 (2018).

    Google Scholar 

  42. 42.

    Achakulwisut, P., Brauer, M., Hystad, P. & Anenberg, S. C. Global, national, and urban burdens of paediatric asthma incidence attributable to ambient NO2 pollution: estimates from global datasets. Lancet Planet Health 3, e166–e178 (2019).

    Google Scholar 

  43. 43.

    Dominici, F., Greenstone, M. & Sunstein, C. R. Particulate matter matters. Science 344, 257–259 (2014).

    Google Scholar 

  44. 44.

    Cushing, L., Morello-Frosch, R., Wander, M. & Pastor, M. The haves, the have-nots, and the health of everyone: the relationship between social inequality and environmental quality. Annu. Rev. Public Health 36, 193–209 (2015).

    Google Scholar 

  45. 45.

    Baltrus, P. et al. Individual and county level predictors of asthma related emergency department visits among children on Medicaid: a multilevel approach. J. Asthma 54, 53–61 (2017).

    Google Scholar 

  46. 46.

    Craig, P., Katikireddi, S. V., Leyland, A. & Popham, F. Natural experiments: an overview of methods, approaches, and contributions to public health intervention research. Annu. Rev. Public Health 38, 39–56 (2017).

    Google Scholar 

  47. 47.

    Barrett, M. et al. AIR Louisville: addressing asthma with technology, crowdsourcing, cross-sector collaboration, and policy. Health Affairs 37, 525–534 (2018).

    Google Scholar 

  48. 48.

    Anderson, H. R., Favarato, G. & Atkinson, R. W. Long-term exposure to outdoor air pollution and the prevalence of asthma: meta-analysis of multi-community prevalence studies. Air Qual. Atmos. Health 6, 57–68 (2013).

    Google Scholar 

  49. 49.

    2016 National Health Interview Survey (NHIS) Data (US Centers for Disease Control & Prevention, 2016);

  50. 50.

    Air Markets Program Data (US Environmental Protection Agency, 2018);

  51. 51.

    Stein, A. et al. NOAA’s HYSPLIT atmospheric transport and dispersion modeling system. Bull. Am. Meteorol. Soc. 96, 2059–2077 (2015).

    Google Scholar 

  52. 52.

    Henneman, L. R. F., Dedoussi, I. C., Casey, J. A., Choirat, C. & Zigler, C. M. Comparisons of simple and complex methods for quantifying exposure to point source air pollution emissions. J. Expo. Sci. Environ. Epidemiol. (2020).

  53. 53.

    Henneman, L. R. F., Choirat, C. & Zigler, C. M. Accountability assessment of health improvements in the United States associated with reduced coal emissions between 2005 and 2012. Epidemiology 30, 477–485 (2019).

    Google Scholar 

  54. 54.

    Mill Creek Station Wins 2016 Project of the Year Award (Louisville Gas & Electric, 2017);

  55. 55.

    Manson, S., Schroeder, J., Riper, D. V. & Ruggles, S. IPUMS National Historical Geographic Information System: Version 13.0 (IPUMS, 2018);

  56. 56.

    Gottlieb, D. J., Beiser, A. S. & O’Connor, G. T. Poverty, race, and medication use are correlates of asthma hospitalization rates: a small area analysis in Boston. Chest 108, 28–35 (1995).

    Google Scholar 

  57. 57.

    Air Data Pre-generated Data Files (US Environmental Protection Agency)

  58. 58.

    Merchant, R. K., Inamdar, R. & Quade, R. C. Effectiveness of population health management using the propeller health asthma platform: a randomized clinical trial. J. Allergy Clin. Immunol. Pract. 4, 455–463 (2016).

    Google Scholar 

  59. 59.

    Van Sickle, D., Magzamen, S., Truelove, S. & Morrison, T. Remote monitoring of inhaled bronchodilator use and weekly feedback about asthma management: an open-group, short-term pilot study of the impact on asthma control. PLoS ONE 8, e55335 (2013).

    Google Scholar 

  60. 60.

    National Centers for Environmental Information, Weather and Climate Data (National Oceanic and Atmospheric Administration, accessed 13 February 2017);

  61. 61.

    CDC’s Social Vulnerability Index (SVI) (US Centers for Disease Control & Prevention, 2016);

  62. 62.

    Angrist, J. D. & Pischke, J.-S. Mostly Harmless Econometrics: An Empiricist’s Companion (Princeton Univ. Press, 2009).

  63. 63.

    Glymour, M. & Greenland, S. in Modern Epidemiology 3rd edn (eds Rothman, K. J., Greenland, S. & Lash, T. L.) 183–209 (Lippincott Williams and Wilkins, 2008).

  64. 64.

    Pope, C. A. 3rd, Ezzati, M. & Dockery, D. W. Fine-particulate air pollution and life expectancy in the United States. N. Engl. J. Med. 360, 376–386 (2009).

    Google Scholar 

  65. 65.

    Abadie, A., Athey, S., Imbens, G. W. & Wooldridge, J. When Should You Adjust Standard Errors for Clustering? (NBER, 2017);

  66. 66.

    Armstrong, B. G., Gasparrini, A. & Tobias, A. Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis. BMC Med. Res. Methodol. 14, 122 (2014).

    Google Scholar 

  67. 67.

    Bernal, J. L., Cummins, S. & Gasparrini, A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int. J. Epidemiol. 46, 348–355 (2017).

    Google Scholar 

  68. 68.

    Petersen, I., Douglas, I. & Whitaker, H. Self controlled case series methods: an alternative to standard epidemiological study designs. Br. Med. J. 354, i4515 (2016).

    Google Scholar 

  69. 69.

    Brumback, B. A. et al. Transitional regression models, with application to environmental time series. J. Am. Stat. Assoc. 95, 16–27 (2000).

    Google Scholar 

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We acknowledge the network of local partners that made the AIR Louisville program possible, which include the Center for Healthy Air, Water and Soil, Louisville Metro, the Community Foundation of Louisville and all the AIR Louisville participants. Partners within the Louisville Metro Government include G. Fischer, the Office of Civic Innovation, Louisville Metro Department of Public Health and Wellness, the Office of Sustainability, the Office of Advanced Planning, the Louisville Jefferson County Information Consortium and Louisville Forward. Specifically, K. Talley, M. King and R. Hamilton of the Air Pollution Control District provided critical information and review of this manuscript. We also thank P. Tarini and O. Wójcik at the Robert Wood Johnson Foundation for helpful guidance throughout the project. The main funding for the project was provided by the Robert Wood Johnson Foundation. Support was also provided by the Foundation for a Healthy Kentucky, Norton Healthcare Foundation, Owsley Brown Charitable Foundation, the American Lung Association, the National Institute of Environmental Health Sciences (J.A.C., K99/R00 ES027023; A.M.N, K99/R00 ES027511; C.Z., R01 ES026217) and the USEPA (C.Z., EPA 83587201). The contents of this work are solely the responsibility of the grantee and do not necessarily represent the official views of the USEPA or the Robert Wood Johnson Foundation. Further, the USEPA does not endorse the purchase of any commercial products or services mentioned in the publication.

Author information




J.A.C., T.S. and M.A.B. secured funding for the study. J.A.C., J.G.S., L.R.F.H., C.Z., A.M.N., R.C., S.S.M., Y.-T.C., J.S. and M.A.B. designed the study and provided exposure and outcome data. J.A.C. and A.M.N. carried out the statistical analyses. J.A.C., J.G.S., L.R.F.H., C.Z., A.M.N., R.C., R.G., Y.-T.C., L.K., S.S.M., V.C., G.S., T.S., J.S. and M.A.B. reviewed and critically revised the manuscript.

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Correspondence to Joan A. Casey.

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Competing interests

M.A.B., R.G. and L.K. are salaried employees of Propeller Health and J.G.S. receives limited funding from Propeller Health to conduct analyses.

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Supplementary Information

Supplementary Figs. 1–11, Tables 1–5, Notes 1 and 2, and refs. 1–3.

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Casey, J.A., Su, J.G., Henneman, L.R.F. et al. Improved asthma outcomes observed in the vicinity of coal power plant retirement, retrofit and conversion to natural gas. Nat Energy 5, 398–408 (2020).

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