Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Lower test scores from wildfire smoke exposure


Wildfires have increased in frequency and severity over the past two decades, threatening to undo substantial air quality improvements. We investigate the relationship between wildfire smoke exposure and learning outcomes across the United States using standardized test scores from 2009–2016 for nearly 11,700 school districts and satellite-derived estimates of daily smoke exposure. Relative to a school year with no smoke, average cumulative smoke-attributable PM2.5 (surface particulate matter <2.5 μg m−3) exposure during the school year (~35 μg m−3) reduces test scores by ~0.15% of a standard deviation. These impacts are more pronounced among younger students and are observed across differing levels of economic disadvantage and racial/ethnic composition. Additionally, we project that smoke PM2.5 exposure in 2016 reduced discounted future earnings by nearly $1.7 billion ($111 per student). Roughly 80% of these costs are borne by disadvantaged districts. Our findings quantify a previously unaccounted for social cost of wildfire that is likely to worsen under a warming climate.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type



Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Spatiotemporal variation in wildfire smoke exposure and average test scores.
Fig. 2: Effect of wildfire smoke exposure on student test scores.
Fig. 3: Heterogeneous effects of school day smoke PM2.5 on test performance by grade, race/ethnicity and level of economic disadvantage.
Fig. 4: School day smoke PM2.5 effect on average test scores by district, and total effect on lost future earnings by economic disadvantage and racial/ethnic subgroup over time.

Similar content being viewed by others

Data availability

The weather data used in this study are available through the Parameter elevation Regressions on Independent Slopes Model (PRISM) Climate Group at Oregon State University ( Student test performance and district-level covariate data are available through the Stanford Education Data Archive (SEDA) ( School location and student population data are available through the National Center for Education Statistics (NCES). Fire perimeter data used to calculate the distance of school districts to fire perimeters are available through the National Interagency Fire Center (NIFC) ( Smoke plume annotations are available through the National Environmental Satellite, Data and Information Service (NESDIS) Hazard Mapping System (HMS) ( Daily gridded estimates of PM2.5 concentrations are available from Di et al. (2021) (; Processed data to replicate the results in the main text and Supplementary Information are available at

Code availability

The code to replicate the results and figures in the main text and supplementary material are available at


  1. Kitzberger, T., Falk, D. A., Westerling, A. L. & Swetnam, T. W. Direct and indirect climate controls predict heterogeneous early-mid 21st century wildfire burned area across western and boreal North America. PloS ONE 12, e0188486 (2017).

    Article  Google Scholar 

  2. Dennison, P. E., Brewer, S. C., Arnold, J. D. & Moritz, M. A. Large wildfire trends in the western United States, 1984–2011. Geophys. Res. Lett. 41, 2928–2933 (2014).

    Article  Google Scholar 

  3. Reid, C. E. et al. Critical review of health impacts of wildfire smoke exposure. Environ. Health Perspect. 124, 1334–1343 (2016).

    Article  Google Scholar 

  4. Aguilera, R., Corringham, T., Gershunov, A. & Benmarhnia, T. Wildfire smoke impacts respiratory health more than fine particles from other sources: observational evidence from Southern California. Nat. Commun. 12, 1493 (2021).

  5. Calderón-Garcidueñas, L. et al. Air pollution, cognitive deficits and brain abnormalities: a pilot study with children and dogs. Brain Cogn. 68, 117–127 (2008).

    Article  Google Scholar 

  6. Block, M. L. & Calderón-Garcidueñas, L. Air pollution: mechanisms of neuroinflammation and CNS disease. Trends Neurosci. 32, 506–516 (2009).

    Article  CAS  Google Scholar 

  7. Marcotte, D. E. Something in the air? Air quality and children’s educational outcomes. Econ. Educ. Rev. 56, 141–151 (2017).

    Article  Google Scholar 

  8. Künn, S., Palacios Temprano, J. F. & Pestel, N. Indoor Air Quality and Cognitive Performance Discussion Paper No. 12632 (IZA, 2019).

  9. Huang, J., Xu, N. & Yu, H. Pollution and performance: do investors make worse trades on hazy days? Manage. Sci. 66, 4455–4476 (2020).

    Article  Google Scholar 

  10. Chang, T. Y., Graff Zivin, J., Gross, T. & Neidell, M. The effect of pollution on worker productivity: evidence from call center workers in China. Am. Econ. J. Appl. Econ. 11, 151–172 (2019).

    Article  Google Scholar 

  11. Archsmith, J., Heyes, A. & Saberian, S. Air quality and error quantity: pollution and performance in a high-skilled, quality-focused occupation. J. Assoc. Environ. Resour. Econ. 5, 827–863 (2018).

    Google Scholar 

  12. La Nauze, A. & Severnini, E. Air Pollution and Adult Cognition: Evidence from Brain Training Working Paper 28785 (NBER, 2021).

  13. Ebenstein, A., Lavy, V. & Roth, S. The long-run economic consequences of high-stakes examinations: evidence from transitory variation in pollution. Am. Econ. J. Appl. Econ. 8, 36–65 (2016).

    Article  Google Scholar 

  14. Shier, V., Nicosia, N., Shih, R. & Datar, A. Ambient air pollution and children’s cognitive outcomes. Popul. Environ. 40, 347–367 (2019).

    Article  Google Scholar 

  15. Zhang, X., Chen, X. & Zhang, X. The impact of exposure to air pollution on cognitive performance. Proc. Natl Acad. Sci. USA 115, 9193–9197 (2018).

    Article  CAS  Google Scholar 

  16. Zivin, J. G., Liu, T., Song, Y., Tang, Q. & Zhang, P. The unintended impacts of agricultural fires: human capital in China. J. Dev. Econ. 147, 102560 (2020).

    Article  Google Scholar 

  17. Lai, W., Li, S., Li, Y. & Tian, X. Air pollution and cognitive functions: evidence from straw burning in China. Am. J. Agric. Econ. 104, 190–208 (2022).

    Article  Google Scholar 

  18. Laurent, J. G. C. et al. Associations between acute exposures to PM2.5 and carbon dioxide indoors and cognitive function in office workers: a multicountry longitudinal prospective observational study. Environ. Res. Lett. 16, 094047 (2021).

    Article  CAS  Google Scholar 

  19. Shehab, M. & Pope, F. Effects of short-term exposure to particulate matter air pollution on cognitive performance. Sci. Rep. 9, 8237 (2019).

  20. Carneiro, J., Cole, M. A. & Strobl, E. The effects of air pollution on students’ cognitive performance: evidence from Brazilian university entrance tests. J. Assoc. Environ. Resour. Econ. 8, 1051–1077 (2021).

    Google Scholar 

  21. Gao, X. et al. Short-term air pollution, cognitive performance and nonsteroidal anti-inflammatory drug use in the veterans affairs normative aging study. Nat. Aging 1, 430–437 (2021).

    Article  Google Scholar 

  22. Calderón-Garcidueñas, L. et al. Long-term air pollution exposure is associated with neuroinflammation, an altered innate immune response, disruption of the blood-brain barrier, ultrafine particulate deposition, and accumulation of amyloid β-42 and α-synuclein in children and young adults. Toxicol. Pathol. 36, 289–310 (2008).

    Article  Google Scholar 

  23. Fu, P., Guo, X., Cheung, F. M. H. & Yung, K. K. L. The association between PM2.5 exposure and neurological disorders: a systematic review and meta-analysis. Sci. Total Environ. 655, 1240–1248 (2019).

    Article  CAS  Google Scholar 

  24. Lu, W., Hackman, D. A. & Schwartz, J. Ambient air pollution associated with lower academic achievement among US children: a nationwide panel study of school districts. Environ. Epidemiol. 5, e174 (2021).

  25. Gilraine, M. Air Filters, Pollution and Student Achievement EdWorkingPapers (Annenberg Institute at Brown University, 2020);

  26. Liu, J. C. et al. Wildfire-specific fine particulate matter and risk of hospital admissions in urban and rural counties. Epidemiology 28, 77-85 (2017).

  27. Burke, M. et al. The changing risk and burden of wildfire in the United States. Proc. Natl Acad. Sci. USA 118, e2011048118 (2021).

  28. Marlon, J. R. et al. Long-term perspective on wildfires in the western USA. Proc. Natl Acad. Sci. USA 109, E535–E543 (2012).

    Article  CAS  Google Scholar 

  29. Westerling, A. L., Hidalgo, H. G., Cayan, D. R. & Swetnam, T. W. Warming and earlier spring increase western U.S. forest wildfire activity. Science 313, 940–943 (2006).

    Article  CAS  Google Scholar 

  30. Colmer, J., Hardman, I., Shimshack, J. & Voorheis, J. Disparities in PM2.5 air pollution in the United States. Science 369, 575–578 (2020).

    Article  CAS  Google Scholar 

  31. Chan, W. R., Joh, J. & Sherman, M. H. Analysis of air leakage measurements of US houses. Energy Build. 66, 616–625 (2013).

    Article  Google Scholar 

  32. Liang, Y. et al. Wildfire smoke impacts on indoor air quality assessed using crowdsourced data in California. Proc. Natl Acad. Sci. USA (2021).

  33. Park, R. J., Goodman, J., Hurwitz, M. & Smith, J. Heat and learning. Am. Econ. J. Econ. Policy 12, 306–339 (2020).

    Article  Google Scholar 

  34. Park, R. J., Behrer, A. P. & Goodman, J. Learning is inhibited by heat exposure, both internationally and within the United States. Nat. Hum. Behav. 5, 19–27 (2021).

    Article  Google Scholar 

  35. Tessum, C. W. et al. Inequity in consumption of goods and services adds to racial–ethnic disparities in air pollution exposure. Proc. Natl Acad. Sci. USA 116, 6001–6006 (2019).

    Article  CAS  Google Scholar 

  36. Su, J. G., Jerrett, M., Morello-Frosch, R., Jesdale, B. M. & Kyle, A. D. Inequalities in cumulative environmental burdens among three urbanized counties in California. Environ. Int. 40, 79–87 (2012).

    Article  CAS  Google Scholar 

  37. Lipfert, F. Air pollution and poverty: does the sword cut both ways? J. Epidemiol. Community Health 58, 2-3 (2004).

  38. Legot, C., London, B. & Shandra, J. Environmental ascription: high-volume polluters, schools, and human capital. Organ. Environ. 23, 271–290 (2010).

    Article  Google Scholar 

  39. Di, Q. et al. An ensemble-based model of PM2.5 concentration across the contiguous United States with high spatiotemporal resolution. Environ. Int. 130, 104909 (2019).

    Article  CAS  Google Scholar 

  40. Di, Q. et al. Daily and Annual PM2.5 Concentrations for the Contiguous United States, 1-km Grids, v1 (2000–2016) (NASA, 2021);

  41. PRISM Gridded Climate Data 2019 (Oregon State University PRISM Climate Group, accessed 2 March 2020);

  42. Bertrand, M., Duflo, E. & Mullainathan, S. How much should we trust differences-in-differences estimates? Q. J. Econ. 119, 249–275 (2004).

    Article  Google Scholar 

  43. Abadie, A., Athey, S., Imbens, G. W. & Wooldridge, J. Clustering as a Design Problem Working paper (MIT Economics, 2016);

  44. Blattman, C., Green, D. P., Ortega, D. & Tobón, S. Place-based interventions at scale: the direct and spillover effects of policing and city services on crime. J. Eur. Econ. Assoc. 19, 2022–2051 (2021).

    Article  Google Scholar 

  45. Mullen, C., Grineski, S. E., Collins, T. W. & Mendoza, D. L. Effects of PM2.5 on third grade students’ proficiency in math and english language arts. Int. J. Environ. Res. Public Health 17, 6931 (2020).

    Article  Google Scholar 

  46. Brockmeyer, S. & d’Angiulli, A. How air pollution alters brain development: the role of neuroinflammation. Transl. Neurosci. 7, 24–30 (2016).

    Article  CAS  Google Scholar 

  47. Burke, M. et al. Exposures and Behavioral Responses to Wildfire Smoke Working Paper 29380 (NBER, 2021).

  48. Chetty, R., Friedman, J. N. & Rockoff, J. E. Measuring the impacts of teachers II: teacher value-added and student outcomes in adulthood. Am. Econ. Rev. 104, 2633–79 (2014).

    Article  Google Scholar 

  49. Deryugina, T., Heutel, G., Miller, N. H., Molitor, D. & Reif, J. The mortality and medical costs of air pollution: evidence from changes in wind direction. Am. Econ. Rev. 109, 4178–4219 (2019).

    Article  Google Scholar 

  50. Sunyer, J. et al. Traffic-related air pollution and attention in primary school children: short-term association. Epidemiology 28, 181–189 (2017).

  51. Currie, J., Hanushek, E. A., Kahn, E. M., Neidell, M. & Rivkin, S. G. Does pollution increase school absences? Rev. Econ. Stat. 91, 682–694 (2009).

    Article  Google Scholar 

  52. Holm, S. M., Miller, M. D. & Balmes, J. R. Health effects of wildfire smoke in children and public health tools: a narrative review. J. Expo. Sci. Environ. Epidemiol. 31, 1–20 (2021).

    Article  Google Scholar 

  53. Mohai, P., Kweon, B.-S., Lee, S. & Ard, K. Air pollution around schools is linked to poorer student health and academic performance. Health Aff. 30, 852–862 (2011).

    Article  Google Scholar 

  54. Klein, M., Sosu, E. M. & Dare, S. School absenteeism and academic achievement: does the reason for absence matter? AERA Open 8, 23328584211071115 (2022).

    Article  Google Scholar 

  55. Heft-Neal, S., Driscoll, A., Yang, W., Shaw, G. & Burke, M. Associations between wildfire smoke exposure during pregnancy and risk of preterm birth in California. Environ. Res. 203, 111872 (2022).

    Article  CAS  Google Scholar 

  56. Burnett, R. et al. Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter. Proc. Natl Acad. Sci. USA 115, 9592–9597 (2018).

    Article  CAS  Google Scholar 

  57. Brey, S. J., Ruminski, M., Atwood, S. A. & Fischer, E. V. Connecting smoke plumes to sources using hazard mapping system (hms) smoke and fire location data over North America. Atmos. Chem. Phys. 18, 1745–1761 (2018).

    Article  CAS  Google Scholar 

  58. Reardon, S. F. et al. Stanford Education Data Archive (version 4.0) (Stanford Libraries, 2021);

  59. Fahle, E. M. et al. Stanford Education Data Archive Technical Documentation Version 4.0 (Stanford Libraries, 2021).

  60. Reardon, S. F. Educational opportunity in early and middle childhood: using full population administrative data to study variation by place and age. RSF 5, 40–68 (2019).

    Article  Google Scholar 

  61. Bergé, L. Efficient Estimation of Maximum Likelihood Models with Multiple Fixed-effects: the R Package FENmlm Discussion Papers (CREA, University of Luxembourg, 2018).

  62. Wildland Fire Management Research, Development, & Application program data team. Interagency Fire Perimeter History - All Years (National Interagency Fire Center, accessed 30 January 2021);

  63. Wong, S. D., Broader, J. C. & Shaheen, S. A. Review of California Wildfire Evacuations from 2017 to 2019 (UC Berkeley Institute of Transportation Studies, 2020).

  64. Radeloff, V. C. et al. The wildland–urban interface in the United States. Ecol. Appl. 15, 799–805 (2005).

    Article  Google Scholar 

Download references


We thank the ECHOLab at Stanford University and the Exploring the ‘Hidden Burden’ of Climate Change and Pollution on Mental Health and Conflict session at American Geophysical Union 2020 for helpful discussions and comments. M.B. thanks the Robert Wood Johnson Foundation (ID No. 76555) for funding. J.W. gratefully acknowledges partial funding from Stanford Data Science for this work. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations



J.W. and M.B. contributed to the conception and design of the study. J.W. conducted data extraction and econometric analysis. J.W. and M.B. analysed the results and wrote the paper.

Corresponding author

Correspondence to Jeff Wen.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Sustainability thanks Tarik Benmarhnia, Caroline Gao, Fay Johnston and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Note, Figs. 1–6 and Tables 1–4.

Reporting Summary

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wen, J., Burke, M. Lower test scores from wildfire smoke exposure. Nat Sustain 5, 947–955 (2022).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing