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Adv."],"published-print":{"date-parts":[[2026,5,1]]},"abstract":"<jats:p>\n                    Fire smoke pollution is an emerging health risk factor, yet prior studies have focused mostly on fine particulate matter (PM\n                    <jats:sub>2.5<\/jats:sub>\n                    ) and neglected the health impacts from other pollutants, most notably ozone (O\n                    <jats:sub>3<\/jats:sub>\n                    ). Here, we quantify changes in ground-level O\n                    <jats:sub>3<\/jats:sub>\n                    concentrations during smoke episodes across the contiguous US using surface air quality measurements, satellite data, and machine learning models. After correcting for meteorological variability, smoke contribution to daily ground-level O\n                    <jats:sub>3<\/jats:sub>\n                    can reach up to 6.9 parts per billion (16% increase relative to nonsmoke days) at certain US monitoring locations, averaged over all smoke days from 2006 to 2023. Smoke O\n                    <jats:sub>3<\/jats:sub>\n                    patterns are poorly correlated with smoke PM\n                    <jats:sub>2.5<\/jats:sub>\n                    patterns, demonstrating that their health impacts do not necessarily coincide in space and time. We estimate that smoke O\n                    <jats:sub>3<\/jats:sub>\n                    can lead to 2045 annual excess deaths (95% confidence interval: 1325 to 2755) averaged across 2006 to 2023 using established exposure-response functions of all-source O\n                    <jats:sub>3<\/jats:sub>\n                    exposure. The increasing mortality due to smoke O\n                    <jats:sub>3<\/jats:sub>\n                    partially offset the observed declining trend in nonsmoke O\n                    <jats:sub>3<\/jats:sub>\n                    mortality. Over the study period, estimated deaths from smoke O\n                    <jats:sub>3<\/jats:sub>\n                    were equivalent to 15.8% of smoke PM\n                    <jats:sub>2.5<\/jats:sub>\n                    mortality, and this proportion reached 61.5% in 2023.\n                  <\/jats:p>","DOI":"10.1126\/sciadv.aec2903","type":"journal-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T17:58:27Z","timestamp":1777485507000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark","source":"Crossref","is-referenced-by-count":2,"title":["Growing impacts of fire smoke on ozone pollution and associated mortality burden in the United States"],"prefix":"10.1126","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-6111-3033","authenticated-orcid":true,"given":"Yangmingkai","family":"Li","sequence":"first","affiliation":[{"name":"School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6895-8464","authenticated-orcid":true,"given":"Xiaomeng","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Environmental Sciences, Rutgers, The State University of New Jersey, New Brunswick, NJ, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0451-3439","authenticated-orcid":true,"given":"Makoto","family":"Kelp","sequence":"additional","affiliation":[{"name":"Doerr School of Sustainability, Stanford University, Stanford, CA, USA."},{"name":"Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8820-909X","authenticated-orcid":true,"given":"Haitong Z.","family":"Sun","sequence":"additional","affiliation":[{"name":"Centre for Sustainable Medicine (CoSM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore."},{"name":"Saw Swee Hock School of Public Health, National University of Singapore, Singapore 117549, Singapore."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5224-570X","authenticated-orcid":true,"given":"Minghao","family":"Qiu","sequence":"additional","affiliation":[{"name":"School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY, USA."},{"name":"Program in Public Health, Stony Brook University, Stony Brook, NY, 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Liang E. Meyerson A. Rawal D. Fink O. Francon B. Raju H. Shahrzad A. Navruzyan N. Duffy B. Hodjat \u201cEvolving deep neural networks \u201d in Artificial Intelligence in the Age of Neural Networks 826 and Brain Computing R. Kozma C. Alippi Y. Choe F. C. Morabito Eds. (Academic Press ed. 2 2023) pp. 269\u2013287.","DOI":"10.1016\/B978-0-323-96104-2.00002-6"},{"key":"e_1_3_2_77_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.est.0c01791"},{"key":"e_1_3_2_78_2","doi-asserted-by":"publisher","DOI":"10.1021\/acsestair.4c00151"},{"key":"e_1_3_2_79_2","first-page":"4768","article-title":"A unified approach to interpreting model predictions","volume":"30","author":"Lundberg S. M.","year":"2017","unstructured":"S. M. Lundberg, S.-I. Lee, A unified approach to interpreting model predictions. Adv. Neural Inf. Proces. Syst. 30, 4768\u20134777 (2017).","journal-title":"Adv. Neural Inf. Proces. 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