An Approach to Improve Distribution Efficiency for the Deployment of Air Quality Monitoring Devices

An Approach to Improve Distribution Efficiency for the Deployment of Air Quality Monitoring Devices | 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 An Approach to Improve Distribution Efficiency for the Deployment of Air Quality Monitoring Devices Pritisha Sarkar, Munsi Yusuf Alam, Mousumi Saha, Arup Roy, Saurav Mallik, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3897355/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Effective air quality monitoring is crucial for understanding and mitigating the adverse impacts of pollution. This research confronts the challenges of obtaining precise data and identifying sources of pollution. It achieves this by introducing an effective algorithm for the deployment of air quality monitoring devices (AQMDs), thereby enhancing the efficiency of their distribution. Our study initiates by verifying current setups of AQMD, which have a limited number of pre-installed devices. This algorithm considers the spatial distribution of pollution sources to minimize the capital and operational costs associated with AQMD installation. It utilizes a dataset that spans 11 months and covers 759.13 km² of Delhi and 75 km² of Durgapur. The proposed algorithm demonstrates its efficacy by achieving an accuracy rate of 90% − 95% in predicting air quality. By strategically selecting monitoring locations based on the distribution of pre- installed AQMDs and existing pollution sources, the algorithm significantly reduces unnecessary costs while maximizing data coverage for comprehensive testing and analysis. This research contributes to optimizing air quality monitoring networks, facilitating better decision-making for pollution control and resource allocation. The outcomes bear significance for urban planners, policymakers, and environmental researchers who are in search of cost-effective solutions to address air pollution challenges in affected areas. Outdoor air pollution Air quality monitoring device Ideal placement Spatial-temporal factor Full Text Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revisions 09 Mar, 2025 Reviewers agreed at journal 01 Aug, 2024 Reviewers invited by journal 01 Aug, 2024 Editor assigned by journal 24 Jan, 2024 First submitted to journal 24 Jan, 2024 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-3897355","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":334930498,"identity":"c13e3fa8-65b8-4c60-ba87-063f8c046230","order_by":0,"name":"Pritisha Sarkar","email":"","orcid":"","institution":"National Institute of Technology Durgapur","correspondingAuthor":false,"prefix":"","firstName":"Pritisha","middleName":"","lastName":"Sarkar","suffix":""},{"id":334930499,"identity":"19d6c063-2091-4645-937d-5622f68b54fb","order_by":1,"name":"Munsi Yusuf Alam","email":"","orcid":"","institution":"Budge Budge Institute of 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