Transition Pathways for Carbon Peaking in Mountainous Megacities: A Multi-Scenario Simulation in Chongqing, China

Transition Pathways for Carbon Peaking in Mountainous Megacities: A Multi-Scenario Simulation in Chongqing, China | 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 Article Transition Pathways for Carbon Peaking in Mountainous Megacities: A Multi-Scenario Simulation in Chongqing, China Lijun Liang, Mengze Ma, Jianglin Feng This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8209106/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted 13 You are reading this latest preprint version Abstract This research addresses several challenges, including the lack of comprehensive regional structural variables in carbon peak pathways for mountainous cities, limited policy flexibility in scenario design, and a deficiency of case studies focused on western China, by selecting Chongqing as a representative case. Utilizing the STIRPAT model, the study conducts a thorough assessment of critical regional factors such as industrial structure, energy intensity, and energy mix. To enhance the accuracy of parameter estimation, ridge regression is employed with data sourced from the China Emissions Accounting and Data System (CEADS). Seven multi-scenario combinations are developed to forecast carbon emission trajectories from 2023 to 2050. The results reveal that: ( 1 ) population size, industrial structure, and energy structure are the principal determinants of Chongqing’s carbon emissions, with population size exerting the most pronounced marginal impact; ( 2 ) under the baseline scenario, carbon emissions are projected to increase, reaching a peak of 208.009 million tons of CO₂ in 2037; conversely, the “Low Growth + Efficient Carbon Reduction” scenario, characterized by accelerated improvements in energy intensity and intensified industrial restructuring, could advance the peak to 2035 at 202.040 million tons, representing a reduction of approximately 2.9% relative to the baseline; and ( 3 ) the “Low Growth + Smart-Driven + High-Efficiency Decarbonization” pathway emerges as the most effective strategy for achieving carbon emission peaking and promoting clean production in Chongqing and comparable regions. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Environmental social sciences Social science/Environmental studies Scientific community and society/Geography Social science/Geography Carbon emissions peaking STIRPAT model Mountainous cities Multi-scenario analysis Emission reduction pathways Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 18 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 13 Jan, 2026 Reviews received at journal 12 Jan, 2026 Reviewers agreed at journal 05 Jan, 2026 Reviewers agreed at journal 05 Jan, 2026 Reviews received at journal 02 Jan, 2026 Reviews received at journal 02 Jan, 2026 Reviewers agreed at journal 31 Dec, 2025 Reviewers agreed at journal 31 Dec, 2025 Reviewers invited by journal 24 Dec, 2025 Editor invited by journal 16 Dec, 2025 Editor assigned by journal 27 Nov, 2025 Submission checks completed at journal 27 Nov, 2025 First submitted to journal 26 Nov, 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. 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-8209106","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":565626225,"identity":"f6bfc4dd-d52d-4456-a199-9a1a9478cc8a","order_by":0,"name":"Lijun 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China","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Carbon emissions peaking, STIRPAT model, Mountainous cities, Multi-scenario analysis, Emission reduction pathways","lastPublishedDoi":"10.21203/rs.3.rs-8209106/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8209106/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis research addresses several challenges, including the lack of comprehensive regional structural variables in carbon peak pathways for mountainous cities, limited policy flexibility in scenario design, and a deficiency of case studies focused on western China, by selecting Chongqing as a representative case. Utilizing the STIRPAT model, the study conducts a thorough assessment of critical regional factors such as industrial structure, energy intensity, and energy mix. To enhance the accuracy of parameter estimation, ridge regression is employed with data sourced from the China Emissions Accounting and Data System (CEADS). Seven multi-scenario combinations are developed to forecast carbon emission trajectories from 2023 to 2050. The results reveal that: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) population size, industrial structure, and energy structure are the principal determinants of Chongqing\u0026rsquo;s carbon emissions, with population size exerting the most pronounced marginal impact; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) under the baseline scenario, carbon emissions are projected to increase, reaching a peak of 208.009\u0026nbsp;million tons of CO₂ in 2037; conversely, the \u0026ldquo;Low Growth\u0026thinsp;+\u0026thinsp;Efficient Carbon Reduction\u0026rdquo; scenario, characterized by accelerated improvements in energy intensity and intensified industrial restructuring, could advance the peak to 2035 at 202.040\u0026nbsp;million tons, representing a reduction of approximately 2.9% relative to the baseline; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) the \u0026ldquo;Low Growth\u0026thinsp;+\u0026thinsp;Smart-Driven\u0026thinsp;+\u0026thinsp;High-Efficiency Decarbonization\u0026rdquo; pathway emerges as the most effective strategy for achieving carbon emission peaking and promoting clean production in Chongqing and comparable regions.\u003c/p\u003e","manuscriptTitle":"Transition Pathways for Carbon Peaking in Mountainous Megacities: A Multi-Scenario Simulation in Chongqing, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-26 10:04:58","doi":"10.21203/rs.3.rs-8209106/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-13T07:11:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-12T13:52:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"102188715298103334162206330704547566073","date":"2026-01-05T13:45:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"138820663893899148978946001054624787979","date":"2026-01-05T06:49:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-02T14:05:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-02T09:23:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"311364389150858667106321198420907392750","date":"2025-12-31T06:54:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"134842405479111859673750280050971336288","date":"2025-12-31T06:24:39+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-24T12:49:33+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-16T19:07:09+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-28T04:20:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-28T04:18:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-11-26T05:57:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7963ad82-d0c5-4125-bd4b-38c6dafaf1f5","owner":[],"postedDate":"December 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":60219301,"name":"Earth and environmental sciences/Environmental sciences"},{"id":60219302,"name":"Earth and environmental sciences/Environmental social sciences"},{"id":60219303,"name":"Social science/Environmental studies"},{"id":60219304,"name":"Scientific community and society/Geography"},{"id":60219305,"name":"Social science/Geography"}],"tags":[],"updatedAt":"2026-03-23T16:00:51+00:00","versionOfRecord":{"articleIdentity":"rs-8209106","link":"https://doi.org/10.1038/s41598-026-44711-1","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-03-18 15:58:15","publishedOnDateReadable":"March 18th, 2026"},"versionCreatedAt":"2025-12-26 10:04:58","video":"","vorDoi":"10.1038/s41598-026-44711-1","vorDoiUrl":"https://doi.org/10.1038/s41598-026-44711-1","workflowStages":[]},"version":"v1","identity":"rs-8209106","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8209106","identity":"rs-8209106","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}