International Journal of Environmental Science and Development

Abstract—The disposal of daily waste in landfills is the prevailing method of waste management today. Landfill sites are significant sources of pollution, affecting land, air, and water. Particularly detrimental are the impacts on individuals residing near these sites, with increased risks of adverse health effects such as low birth weight, birth defects, and certain cancers. This study aimed to develop a predictive model for assessing environmental and health impacts in communities neighboring 80 landfill sites across Ubon Ratchathani province, Thailand. Local government organizations supervise these sites in 21 districts. The study employed data-driven predictive methods to anticipate future scenarios, considering four key factors: Cleanliness Index (CI), Environmental Impact Index (I), Waste Production Rate at Any Time (Pw), and Sub-district Level Community Health Problems (HP). Relationships between these factors were analyzed using multiple linear regression with the “enter” method. Additionally, the study aimed to establish a spatial web platform for forecasting impacts and providing recommendations for effective implementation utilizing GIS software. Findings revealed positive associations between CI, Pw, and I with environmental and health impacts, while health problems (HP) at the sub-district level were negatively correlated. Although not statistically significant at the 0.05 significance level, these four variables are considered crucial factors influencing landfill site quality. Assessment of impact levels indicated that 63 sites experienced a high level (78.75%), while the remaining 17 sites (21.25%) had a medium level of impact. GIS-formatted maps were created to develop a geographic web application for predicting environmental and health consequences near landfill sites. This study offers valuable insights into factors influencing landfill site consequences, guiding mitigation efforts and policy decisions.

Keywords—prediction model, landfill Sites, environmental, multiple linear regression, spatial web

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Cite: Surasak Suksai and Phatcharee Srikuta, "Cultivating Sustainable Communities: An Advanced Prediction Model for Assessing Environmental and Health Impacts in the Vicinity of Landfill Sites via Multiple Linear Regression and Spatial Web," International Journal of Environmental Science and Development vol. 15, no. 4, pp. 211-217, 2024.

Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).