Decadal Reversal of Global Surface Ozone Pollution

Decadal Reversal of Global Surface Ozone Pollution | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Decadal Reversal of Global Surface Ozone Pollution Jing Wei, Zhanqing Li, Zeyu Yang, Xiong Liu, Jun Wang, Ke Li, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8336189/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Ambient ozone (O 3 ) pollution poses a critical threat to global environmental and public health. We reconstructed two decades (2000–2021) of historical daily surface O 3 concentrations across global land from space using deep learning. 91% of land area exceeded the World Health Organization (WHO) air quality guideline (AQG) for annual maximum daily 8-hour average (MDA8) O 3 concentrations of 30 ppb, affecting 90% of the world’s population. 96% of the land area and the entire population experienced exceedances of the WHO daily AQG level (50 ppb). We identified decadal trend reversals in population-weighted O 3 concentrations across 90% of countries, with turning points clustered around 2011; 74% followed a distinct “decline–increase” trajectory. While over half of land areas showed significant declines in exceedance days prior to 2011, these improving trends reversed sharply thereafter, affecting 71% of the global population and indicating a widespread reversal in acute O 3 exposure. A parallel reversal pattern was observed in mortality trends attributable to long-term O 3 exposure, with a rising health burden linked to deteriorating O 3 pollution in most nations. Explainable artificial intelligence analysis reveals that this trend reversal reflects a global rebalancing of driving factors. Meteorological factors continue to explain most variance (68%). Anthropogenic influences have grown in over half of the countries since the turning points. These findings call for strengthened precursor controls in densely populated regions and enhanced climate adaptation in areas where atmospheric conditions dominate O 3 levels. Atmospheric Sciences Surface ozone Deep learning Trend reversal Air quality Mortality burden Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8336189","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":558802355,"identity":"68d668ad-bf81-4bc2-acf8-a9a6afbaf6bd","order_by":0,"name":"Jing 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Pollution\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Peking University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Surface ozone, Deep learning, Trend reversal, Air quality, Mortality burden","lastPublishedDoi":"10.21203/rs.3.rs-8336189/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8336189/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAmbient ozone (O\u003csub\u003e3\u003c/sub\u003e) pollution poses a critical threat to global environmental and public health. We reconstructed two decades (2000\u0026ndash;2021) of historical daily surface O\u003csub\u003e3\u003c/sub\u003e concentrations across global land from space using deep learning. 91% of land area exceeded the World Health Organization (WHO) air quality guideline (AQG) for annual maximum daily 8-hour average (MDA8) O\u003csub\u003e3\u003c/sub\u003e concentrations of 30 ppb, affecting 90% of the world\u0026rsquo;s population. 96% of the land area and the entire population experienced exceedances of the WHO daily AQG level (50 ppb). We identified decadal trend reversals in population-weighted O\u003csub\u003e3\u003c/sub\u003e concentrations across 90% of countries, with turning points clustered around 2011; 74% followed a distinct \u0026ldquo;decline\u0026ndash;increase\u0026rdquo; trajectory. While over half of land areas showed significant declines in exceedance days prior to 2011, these improving trends reversed sharply thereafter, affecting 71% of the global population and indicating a widespread reversal in acute O\u003csub\u003e3\u003c/sub\u003e exposure. A parallel reversal pattern was observed in mortality trends attributable to long-term O\u003csub\u003e3\u003c/sub\u003e exposure, with a rising health burden linked to deteriorating O\u003csub\u003e3\u003c/sub\u003e pollution in most nations. Explainable artificial intelligence analysis reveals that this trend reversal reflects a global rebalancing of driving factors. Meteorological factors continue to explain most variance (68%). Anthropogenic influences have grown in over half of the countries since the turning points. These findings call for strengthened precursor controls in densely populated regions and enhanced climate adaptation in areas where atmospheric conditions dominate O\u003csub\u003e3\u003c/sub\u003e levels.\u003c/p\u003e","manuscriptTitle":"Decadal Reversal of Global Surface Ozone Pollution","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-12 09:23:56","doi":"10.21203/rs.3.rs-8336189/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4338fc11-fa04-460d-afc3-74c43872c010","owner":[],"postedDate":"December 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59541485,"name":"Atmospheric Sciences"}],"tags":[],"updatedAt":"2025-12-12T09:23:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-12 09:23:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8336189","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8336189","identity":"rs-8336189","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}