Analysis of Methane Loss Rate in the Atmosphere over Iran: A Regional Computational Study Using CAMS and ERA5 Data (Mar 2024 – Feb 2025)

Analysis of Methane Loss Rate in the Atmosphere over Iran: A Regional Computational Study Using CAMS and ERA5 Data (Mar 2024 – Feb 2025) | 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 Analysis of Methane Loss Rate in the Atmosphere over Iran: A Regional Computational Study Using CAMS and ERA5 Data (Mar 2024 – Feb 2025) Pedram Hamidi Rad, Bijan Hejazi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7880726/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Methane is the second most potent anthropogenic greenhouse gas, making the accurate quantification of its atmospheric sink vital for regional climate modeling. This study presents a high-resolution, time-dependent computational analysis of the primary CH 4 ​ chemical sink (reaction with the hydroxyl radical, OH·) over the Iranian plateau and surrounding territories from March 2024 to February 2025. The analysis utilizes 3-hourly, 0.4°×0.4° spatial resolution data for CH 4 ​ column-averaged molar fraction, temperature (t2m), and humidity (d2m) derived from the Copernicus Atmosphere Monitoring Service (CAMS) and ERA5 reanalysis datasets. The CH 4 ​ loss rate is calculated using the standard kinetic rate law with a temperature-dependent rate coefficient, while OH· concentration is estimated empirically based on relative humidity (RH). The results show a mean annual CH 4 ​ loss rate of 1.5502×10 5 molecule⋅cm − 3 ⋅s − 1 across Iran. Spatially, the highest loss rates are consistently found over the humid Caspian Sea and Persian Gulf coastlines. Temporally, the loss rate exhibits a strong seasonal cycle, with the peak occurring in spring and autumn (November/March), which is counter-intuitive to peak temperature seasons. This temporal pattern is attributed to the governing influence of Relative Humidity (RH) on the empirically estimated OH· concentration, which dominates the Arrhenius temperature dependence. The study provides critical, highly resolved regional data for improving national CH 4 ​ budget models. Methane Sink Hydroxyl Radical (OH·) Atmospheric Chemistry CH4​ Budget Relative Humidity (RH) ERA5 Reanalysis CAMS Data Iran Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 25 Nov, 2025 Reviews received at journal 24 Nov, 2025 Reviews received at journal 23 Nov, 2025 Reviewers agreed at journal 08 Nov, 2025 Reviewers agreed at journal 04 Nov, 2025 Reviewers invited by journal 02 Nov, 2025 Editor assigned by journal 17 Oct, 2025 Submission checks completed at journal 17 Oct, 2025 First submitted to journal 16 Oct, 2025 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. 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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-7880726","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":531017907,"identity":"a9e53808-9c91-4a43-8c5c-2d1387fb6b29","order_by":0,"name":"Pedram Hamidi 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2025)","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"theoretical-and-applied-climatology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"taac","sideBox":"Learn more about [Theoretical and Applied Climatology](https://www.springer.com/journal/704)","snPcode":"704","submissionUrl":"https://submission.nature.com/new-submission/704/3","title":"Theoretical and Applied Climatology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Methane Sink, Hydroxyl Radical (OH·), Atmospheric Chemistry, CH4​ Budget, Relative Humidity (RH), ERA5 Reanalysis, CAMS Data, Iran","lastPublishedDoi":"10.21203/rs.3.rs-7880726/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7880726/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMethane is the second most potent anthropogenic greenhouse gas, making the accurate quantification of its atmospheric sink vital for regional climate modeling. This study presents a high-resolution, time-dependent computational analysis of the primary CH\u003csub\u003e4\u003c/sub\u003e​ chemical sink (reaction with the hydroxyl radical, OH\u0026middot;) over the Iranian plateau and surrounding territories from March 2024 to February 2025. The analysis utilizes 3-hourly, 0.4\u0026deg;\u0026times;0.4\u0026deg; spatial resolution data for CH\u003csub\u003e4\u003c/sub\u003e​ column-averaged molar fraction, temperature (t2m), and humidity (d2m) derived from the Copernicus Atmosphere Monitoring Service (CAMS) and ERA5 reanalysis datasets. The CH\u003csub\u003e4\u003c/sub\u003e​ loss rate is calculated using the standard kinetic rate law with a temperature-dependent rate coefficient, while OH\u0026middot; concentration is estimated empirically based on relative humidity (RH). The results show a mean annual CH\u003csub\u003e4\u003c/sub\u003e​ loss rate of 1.5502\u0026times;10\u003csup\u003e5\u003c/sup\u003e molecule\u0026sdot;cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e\u0026sdot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e across Iran. Spatially, the highest loss rates are consistently found over the humid Caspian Sea and Persian Gulf coastlines. Temporally, the loss rate exhibits a strong seasonal cycle, with the peak occurring in spring and autumn (November/March), which is counter-intuitive to peak temperature seasons. This temporal pattern is attributed to the governing influence of Relative Humidity (RH) on the empirically estimated OH\u0026middot; concentration, which dominates the Arrhenius temperature dependence. The study provides critical, highly resolved regional data for improving national CH\u003csub\u003e4\u003c/sub\u003e​ budget models.\u003c/p\u003e","manuscriptTitle":"Analysis of Methane Loss Rate in the Atmosphere over Iran: A Regional Computational Study Using CAMS and ERA5 Data (Mar 2024 – Feb 2025)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-21 02:43:57","doi":"10.21203/rs.3.rs-7880726/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-25T08:48:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-24T08:40:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-23T20:04:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"193264768072301839448555534995327375955","date":"2025-11-08T19:12:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13586533619471588525434532582119624669","date":"2025-11-05T01:00:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-02T21:09:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-17T06:36:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-17T06:31:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"Theoretical and Applied Climatology","date":"2025-10-16T20:01:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"theoretical-and-applied-climatology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"taac","sideBox":"Learn more about [Theoretical and Applied Climatology](https://www.springer.com/journal/704)","snPcode":"704","submissionUrl":"https://submission.nature.com/new-submission/704/3","title":"Theoretical and Applied Climatology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0a479fea-7552-482e-89e3-def46685de7a","owner":[],"postedDate":"October 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-02-17T15:58:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-21 02:43:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7880726","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7880726","identity":"rs-7880726","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}