Assessment of Leached Heavy Metals From Construction and Demolition Waste

Assessment of Leached Heavy Metals From Construction and Demolition Waste | 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 Assessment of Leached Heavy Metals From Construction and Demolition Waste Francis Agyapong, Bennetta Koomson, Samuel Kwofie, Solomon Senyo Robert Gidigasu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8653142/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Construction and Demolition Waste (CDW) presents significant environmental concerns due to heavy metals leaching into soils and groundwater. This study examines the concentrations and spatial migration patterns of heavy metals leached from CDW at a construction site in Kumasi, Ghana. Samples of CDW and underlying soil were collected and analyzed for heavy metals, including lead (Pb), arsenic (As), zinc (Zn), copper (Cu), manganese (Mn), and cadmium (Cd). The study finds that the CDW mainly consists of sand, which helps leachate move easily. Inverse Distance Weighting (IDW) interpolation and Radial Basis Function (RBF) neural network modeling were used to predict the spread of contaminants vertically and horizontally. Results show that Cu, Zn, and Mn have higher mobility, while Pb and As tend to stay localized. The mobility raises environmental risks such as soil degradation and threats to plant and microbial life. The study recommends regulatory reforms, sustainable construction practices, and chemical stabilization to reduce the environmental impacts of CDW leachates. heavy metals Interpolation modelling construction waste Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 24 Mar, 2026 Editor assigned by journal 21 Mar, 2026 Submission checks completed at journal 21 Mar, 2026 First submitted to journal 20 Jan, 2026 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-8653142","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":611637450,"identity":"bb3ccabd-ccb9-4c95-8d92-d0f701b1a22e","order_by":0,"name":"Francis 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