Understanding the evolution of U.S. residential housing inventory and their carbon storage contribution: Implications of alternate decay models and half-lives

Understanding the evolution of U.S. residential housing inventory and their carbon storage contribution: Implications of alternate decay models and half-lives | 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 Understanding the evolution of U.S. residential housing inventory and their carbon storage contribution: Implications of alternate decay models and half-lives Prakash Nepal, Ghanashyam Khanal, Sailesh Adhikari, Jeffrey Prestemon, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8725908/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 Over 90% of U.S. homes are wood-based, making the residential construction sector both a major consumer of wood products and an important carbon sink. Understanding its long-term dynamics is critical for economic planning and carbon mitigation. Current U.S. models typically apply an exponential decay function to estimate carbon stored in wood products. However, recent research suggests this may not accurately reflect the time dynamics of wood products in housing, which remain in use for extended periods before disposal. This study compares the projections of U.S. single-family, multifamily, and manufactured housing inventories and associated carbon stocks from 2022 to 2070 using the conventional exponential decay model and an alternative chi- squared decay model, combined with three half-live assumptions (short, base, and long). Results reveal substantial differences in projected outcomes: under exponential decay, U.S. housing inventory declines, depending on half-life assumption, by 3 to 19% relative to 2022 levels, while chi-squared decay shows reductions of 3 to 52%. In contrast, total carbon stocks in housing inventory increase in the exponential model with all three half-life assumptions (14% to 16% relative to 2022 levels) and the chi-squared decay model with base and long half-life assumptions (10 to 18%). However, they decrease slightly (1%) for the chi-squared decay model with the short half-life assumption. These findings highlight the housing sector’s role in carbon storage and calls for a need to empirically validate decay functions and half-life parameters using updated time series data to improve long-term projections of housing inventories and associated carbon stocks. Residential housing inventory Harvested wood products carbon Decay function Half-life Solid Wood Disposable Site 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-8725908","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":602077894,"identity":"0b3c4ad9-9ae2-4341-b0b2-392996f5c1a5","order_by":0,"name":"Prakash 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Understanding its long-term dynamics is critical for economic planning and carbon mitigation. Current U.S. models typically apply an exponential decay function to estimate carbon stored in wood products. However, recent research suggests this may not accurately reflect the time dynamics of wood products in housing, which remain in use for extended periods before disposal. This study compares the projections of U.S. single-family, multifamily, and manufactured housing inventories and associated carbon stocks from 2022 to 2070 using the conventional exponential decay model and an alternative chi- squared decay model, combined with three half-live assumptions (short, base, and long). Results reveal substantial differences in projected outcomes: under exponential decay, U.S. housing inventory declines, depending on half-life assumption, by 3 to 19% relative to 2022 levels, while chi-squared decay shows reductions of 3 to 52%. In contrast, total carbon stocks in housing inventory increase in the exponential model with all three half-life assumptions (14% to 16% relative to 2022 levels) and the chi-squared decay model with base and long half-life assumptions (10 to 18%). However, they decrease slightly (1%) for the chi-squared decay model with the short half-life assumption. 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