Application of GIS and feedforward back-propagated ANN models for predicting the ecological and health risk of potentially toxic elements in soils in Northwestern Nigeria

Application of GIS and feedforward back-propagated ANN models for predicting the ecological and health risk of potentially toxic elements in soils in Northwestern Nigeria | 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 Application of GIS and feedforward back-propagated ANN models for predicting the ecological and health risk of potentially toxic elements in soils in Northwestern Nigeria Benjamin Odey Omang, Michael Ekuru Omeka, Enah Asinya Asinya, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2643106/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Sep, 2023 Read the published version in Environmental Geochemistry and Health → Version 1 posted 10 You are reading this latest preprint version Abstract Potentially toxic elements occur naturally in most geologic materials. However, recent anthropogenic disturbances such as ore mining have contributed significantly to their enrichment in soils. Their occurrence in soil may portend a myriad of related risks to the environment and biota. Most traditional soil quality evaluation methods involve comparing the background values of the elements to the established guideline values, which is often time-consuming and fraught with computational mistakes. As a result, in order to conduct a comprehensive and unbiased evaluation of soil quality and its effects on the ecosystem and human health, this research combined geochemical, numerical, and GIS data for a composite health risk zonation of the full study region. Furthermore, the multilayer perceptron artificial neural network was used to forecast the most important toxic components influencing soil quality (MLP-NN). Geochemical, statistical, and quantitative soil pollution evaluation (pollution index and ecological risk index) showed that apart from mining, the spread and association of trace elements and oxides occur as a consequence of surface environmental conditions (e.g., leaching, weathering, and organo-metallic complexation). The hazard quotients (HQs) and hazard index (HI) of all PTEs were greater than one. This indicates that residents (particularly children) are more susceptible to risks from toxic components ingestion than skin exposure and inhalation. Ingestion of As and Cr resulted in higher cancer risks and lifetime cancer risk levels (> 1.0E 04), with risk levels increasing towards the northeastern, western, and southeastern directions of the study area. The low modeling errors observed from the sum of square errors, relative errors, and coefficient of determination confirmed the efficiency of the MLP-NN in pollution load prediction. Based on the sensitivity analysis, Hg, Sr, Zn, Ba, As, and Zr showed the greatest influence on soil quality. Focus on remediation should therefore be placed on the removal of these elements from the soil Soil pollution Artificial neural network (ANN) Health risk assessment Ecological risk assessment Geographical information system (GIS) Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Full Text Additional Declarations No competing interests reported. Tables are available in Supplementary Files section. Supplementary Files supplentaryfile.docx Tables2.docx Cite Share Download PDF Status: Published Journal Publication published 04 Sep, 2023 Read the published version in Environmental Geochemistry and Health → Version 1 posted Editorial decision: Major revision 03 Aug, 2023 Reviews received at journal 02 Aug, 2023 Reviewers agreed at journal 31 May, 2023 Reviews received at journal 12 Apr, 2023 Reviewers agreed at journal 17 Mar, 2023 Reviewers agreed at journal 03 Mar, 2023 Reviewers invited by journal 02 Mar, 2023 Editor assigned by journal 02 Mar, 2023 Submission checks completed at journal 01 Mar, 2023 First submitted to journal 01 Mar, 2023 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. 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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-2643106","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":179969508,"identity":"59451b42-231e-4d58-bb9e-61d5af39a41d","order_by":0,"name":"Benjamin Odey Omang","email":"","orcid":"","institution":"University of Calabar","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"Odey","lastName":"Omang","suffix":""},{"id":179969509,"identity":"23ecff84-d338-4905-be68-579a01df4662","order_by":1,"name":"Michael Ekuru 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