Research on the spatiotemporal distribution characteristics of the CO 2 gas concentration and water–gas interface exchange flux in deep and large reservoirs in the upper reaches of the Yellow River

Research on the spatiotemporal distribution characteristics of the CO 2 gas concentration and water–gas interface exchange flux in deep and large reservoirs in the upper reaches of the Yellow River | 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 Research on the spatiotemporal distribution characteristics of the CO 2 gas concentration and water–gas interface exchange flux in deep and large reservoirs in the upper reaches of the Yellow River Wei Wu, Zhuo Hou, Chen Li, Hang Chen, Lei Ren, Sheng Xu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5300918/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 Greenhouse gas (GHG) emissions has become one of the most important concerns, and relatively few systematic studies have been conducted on the source‒sink relationships of GHGs and their influencing factors in deep reservoirs. To characterize the dissolved CO 2 in the water column at different periods in deep and large reservoirs and to reveal CO 2 exchange processes at the water‒gas interface, three typical deep and large reservoirs in the upper Yellow River section of the Longyangxia‒Liujiaxia River, namely, Longyangxia, Lijiaxia, and Liujiaxia, were selected as the study objects, and the hydrochemical equilibrium method and thin boundary layer diffusion model (TBL model) were adopted to estimate the CO 2 dissolved concentration ( p CO 2 ) and interfacial exchange flux ( F CO 2 ). The results revealed that (1) the mean values of p CO 2 in the Long-Liu reservoirs in the upper reaches of the Yellow River were 765.00 ± 385.58 µatm (stratification period) and 739.00 ± 305.01 µatm (mixing period), and the mean values of F CO 2 were 12.27 ± 15.13 mmol/(m 2 ·d) (stratification period) and 9.11 ± 8.01 mmol/(m 2 ·d) (mixing period). (2) Influenced by the carbonate balance of the water column, p CO 2 was regulated mainly by water temperature (WT), dissolved oxygen (DO), alkalinity (Talk) and DOC. (3) The p CO 2 and F CO 2 values of three typical deep and large reservoirs in the upper Long-Liu section of the Yellow River had obvious spatial and seasonal variations, and all of them were manifested as sources of atmospheric CO 2 . This study provide theoretical support for the study of greenhouse gas emissions from reservoir aquatic ecosystems under the influence of hydropower development. deep and large reservoirs CO2 partial pressure CO2 exchange flux thin boundary layer diffusion model water‒gas interface 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-5300918","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":381621181,"identity":"8bcca617-68b8-46a6-bd16-a3ee1d975ddf","order_by":0,"name":"Wei Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuElEQVRIiWNgGAWjYLCChAoog4d4LWeABBtJWhjbSNFicCPH8MHDeYflDe43MD5428Ygb06EFmODxG1phhuOMTAbzm1jMNzZQECL2Y3cbRKJ22wYgVrYpHnbGBIMDhDWsv1H4hwJe6AW9t/EatnGkNhgkwiyhZkoLfZn3n+WSDiWljzzWGKz5JxzEoYbCGmRbE9L/Pij5rBt3+HDBz+8KbORJ2gLEmBsABISxKsfBaNgFIyCUYAbAAAJkUDi6x1XSwAAAABJRU5ErkJggg==","orcid":"","institution":"Xi'an University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Wei","middleName":"","lastName":"Wu","suffix":""},{"id":381621182,"identity":"908a758c-0f5b-46d4-a5ab-d8cd13758a63","order_by":1,"name":"Zhuo Hou","email":"","orcid":"","institution":"Xi'an University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Zhuo","middleName":"","lastName":"Hou","suffix":""},{"id":381621183,"identity":"b5a04abd-dc6a-4a73-a9f6-98febfb5b020","order_by":2,"name":"Chen Li","email":"","orcid":"","institution":"Xi'an University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Li","suffix":""},{"id":381621184,"identity":"e0f4c9e7-bb3e-4bf6-9e6b-58f345fa4c66","order_by":3,"name":"Hang Chen","email":"","orcid":"","institution":"Xi'an University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Hang","middleName":"","lastName":"Chen","suffix":""},{"id":381621185,"identity":"9bfaff76-8fbd-403c-92a6-1d113e6bb53c","order_by":4,"name":"Lei Ren","email":"","orcid":"","institution":"Xi'an University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Ren","suffix":""},{"id":381621186,"identity":"98ed5e0f-82ff-4ae6-9bd4-46284ad33eb0","order_by":5,"name":"Sheng Xu","email":"","orcid":"","institution":"Xi'an University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Sheng","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2024-10-21 03:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5300918/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5300918/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":76024375,"identity":"a84d8d04-65ba-4a43-ab55-8ba6168cd494","added_by":"auto","created_at":"2025-02-11 14:17:04","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1134234,"visible":true,"origin":"","legend":"","description":"","filename":"manuscriptWeiWu.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5300918/v1_covered_8a363aa3-6f61-4e7a-b554-04453c3bb53a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Research on the spatiotemporal distribution characteristics of the CO 2 gas concentration and water–gas interface exchange flux in deep and large reservoirs in the upper reaches of the Yellow River","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"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":"deep and large reservoirs, CO2 partial pressure, CO2 exchange flux, thin boundary layer diffusion model, water‒gas interface","lastPublishedDoi":"10.21203/rs.3.rs-5300918/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5300918/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGreenhouse gas (GHG) emissions has become one of the most important concerns, and relatively few systematic studies have been conducted on the source‒sink relationships of GHGs and their influencing factors in deep reservoirs. To characterize the dissolved CO\u003csub\u003e2\u003c/sub\u003e in the water column at different periods in deep and large reservoirs and to reveal CO\u003csub\u003e2\u003c/sub\u003e exchange processes at the water‒gas interface, three typical deep and large reservoirs in the upper Yellow River section of the Longyangxia‒Liujiaxia River, namely, Longyangxia, Lijiaxia, and Liujiaxia, were selected as the study objects, and the hydrochemical equilibrium method and thin boundary layer diffusion model (TBL model) were adopted to estimate the CO\u003csub\u003e2\u003c/sub\u003e dissolved concentration (\u003cem\u003ep\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e) and interfacial exchange flux (\u003cem\u003eF\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e). The results revealed that (1) the mean values of \u003cem\u003ep\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e in the Long-Liu reservoirs in the upper reaches of the Yellow River were 765.00\u0026thinsp;\u0026plusmn;\u0026thinsp;385.58 \u0026micro;atm (stratification period) and 739.00\u0026thinsp;\u0026plusmn;\u0026thinsp;305.01 \u0026micro;atm (mixing period), and the mean values of \u003cem\u003eF\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e were 12.27\u0026thinsp;\u0026plusmn;\u0026thinsp;15.13 mmol/(m\u003csup\u003e2\u003c/sup\u003e\u0026middot;d) (stratification period) and 9.11\u0026thinsp;\u0026plusmn;\u0026thinsp;8.01 mmol/(m\u003csup\u003e2\u003c/sup\u003e\u0026middot;d) (mixing period). (2) Influenced by the carbonate balance of the water column, \u003cem\u003ep\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e was regulated mainly by water temperature (WT), dissolved oxygen (DO), alkalinity (Talk) and DOC. (3) The \u003cem\u003ep\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e and \u003cem\u003eF\u003c/em\u003eCO\u003csub\u003e2\u003c/sub\u003e values of three typical deep and large reservoirs in the upper Long-Liu section of the Yellow River had obvious spatial and seasonal variations, and all of them were manifested as sources of atmospheric CO\u003csub\u003e2\u003c/sub\u003e. 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