Spatiotemporal Analysis of Air Pollution Using GIS and Geographically Weighted Regression: A Case Study in the Eastern Marmara Basin, Türkiye

Spatiotemporal Analysis of Air Pollution Using GIS and Geographically Weighted Regression: A Case Study in the Eastern Marmara Basin, Türkiye | 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 Spatiotemporal Analysis of Air Pollution Using GIS and Geographically Weighted Regression: A Case Study in the Eastern Marmara Basin, Türkiye Arzu Erener, Arif Çağdaş Aydınoğlu, Ali Doğan Gümüşsoy This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8898850/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 Natural hazards and environmental risks, including air pollution, pose significant threats to human health and urban sustainability, underscoring the need for comprehensive spatial databases to support effective monitoring and management. This study presents a framework for constructing a district-level environmental hazard database for PM₁₀ (particulate matter with an aerodynamic diameter of 10 µm or less) concentrations in Eastern Marmara Basin, Türkiye, from 2014 to 2024, highlighting the challenges posed by high-volume, heterogeneous data. Meteorological, land-use, and topographic variables were integrated into a Geographic Information Systems (GIS) framework to create a spatially explicit database for analysis. Geographically Weighted Regression (GWR) was applied to assess the spatially varying influences of these variables on PM₁₀ levels. Results indicate that meteorological factors are the dominant drivers of PM₁₀ variability, while land use and topography exert moderate but locally significant effects. Local R² values reveal spatial heterogeneity and identify hotspots where pollutant levels are most sensitive to environmental and anthropogenic drivers. This approach demonstrates a replicable GIS-based methodology for building environmental hazard databases to support risk assessment and evidence-based decision-making. PM₁₀ Air Pollution Environmental Hazard Database Geographically Weighted Regression GIS Big Data Full Text Additional Declarations No competing interests reported. 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-8898850","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":594983029,"identity":"c3c17064-7c35-4947-8140-247a788877c8","order_by":0,"name":"Arzu Erener","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIie3Rv0rEMBzA8fwIpEu9W3MI7Su0HPgH8e5VchTqLMJRQTAg5JaKa8WXiE9gpdAuoXNvUbt0PjcXxVx1sz06OuS7/LJ8+IUEIZPpnwc13w4L9CDDCPZbgn+JPYCQyQ9pz/1k/FA0FEUvzqF121wm0cwdY8zRZpmh+X7aSWjJQorUxfQ4Lg7WUgX+/Q1wSMoM2SPWvUahnIJgC1mFZF2LFGQGHO8JTXpu5ioQFL7YtXxtyLkm86ct+dxBPIUJBc6YVxECjyJdSP1iGHYQXxF8xHLmSxXiSaKCINFbnuPyzLZVN3GUVVebK+Z6RQ7vcTQ7vVut6reP5Yljxd2k7c/LpGjYT5pMJpOpp29BsVg3D+U3JgAAAABJRU5ErkJggg==","orcid":"","institution":"Kocaeli University","correspondingAuthor":true,"prefix":"","firstName":"Arzu","middleName":"","lastName":"Erener","suffix":""},{"id":594983030,"identity":"46d71517-ed2c-4e53-9e98-80b05ceb523a","order_by":1,"name":"Arif Çağdaş Aydınoğlu","email":"","orcid":"","institution":"Gebze Technical University","correspondingAuthor":false,"prefix":"","firstName":"Arif","middleName":"Çağdaş","lastName":"Aydınoğlu","suffix":""},{"id":594983032,"identity":"bdd6bfb5-6811-442c-9801-2e0ef8604d1d","order_by":2,"name":"Ali Doğan Gümüşsoy","email":"","orcid":"","institution":"Gebze Technical University","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"Doğan","lastName":"Gümüşsoy","suffix":""}],"badges":[],"createdAt":"2026-02-17 08:08:57","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8898850/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8898850/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104400472,"identity":"06a7e6bf-cee1-47f7-a924-27b07807b8f6","added_by":"auto","created_at":"2026-03-11 12:10:04","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1944180,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptAirPollutionErener.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8898850/v1_covered_d00baf5a-087a-4b5c-98fa-a7ee841b07e5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Spatiotemporal Analysis of Air Pollution Using GIS and Geographically Weighted Regression: A Case Study in the Eastern Marmara Basin, Türkiye","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"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":"PM₁₀, Air Pollution, Environmental Hazard Database, Geographically Weighted Regression, GIS, Big Data","lastPublishedDoi":"10.21203/rs.3.rs-8898850/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8898850/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNatural hazards and environmental risks, including air pollution, pose significant threats to human health and urban sustainability, underscoring the need for comprehensive spatial databases to support effective monitoring and management. This study presents a framework for constructing a district-level environmental hazard database for PM₁₀ (particulate matter with an aerodynamic diameter of 10 \u0026micro;m or less) concentrations in Eastern Marmara Basin, T\u0026uuml;rkiye, from 2014 to 2024, highlighting the challenges posed by high-volume, heterogeneous data. Meteorological, land-use, and topographic variables were integrated into a Geographic Information Systems (GIS) framework to create a spatially explicit database for analysis. Geographically Weighted Regression (GWR) was applied to assess the spatially varying influences of these variables on PM₁₀ levels. Results indicate that meteorological factors are the dominant drivers of PM₁₀ variability, while land use and topography exert moderate but locally significant effects. Local R\u0026sup2; values reveal spatial heterogeneity and identify hotspots where pollutant levels are most sensitive to environmental and anthropogenic drivers. This approach demonstrates a replicable GIS-based methodology for building environmental hazard databases to support risk assessment and evidence-based decision-making.\u003c/p\u003e","manuscriptTitle":"Spatiotemporal Analysis of Air Pollution Using GIS and Geographically Weighted Regression: A Case Study in the Eastern Marmara Basin, Türkiye","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-02 18:02:39","doi":"10.21203/rs.3.rs-8898850/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":"6c5df7e0-d9f0-4d96-998e-971950294820","owner":[],"postedDate":"March 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-08T06:10:36+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-02 18:02:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8898850","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8898850","identity":"rs-8898850","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}