Risk Assessment of Indian Landfill Contaminants using Trapezoidal Neutrosophic Fuzzy Numbers and Fuzzy Inference System

Objectives: To evaluate and prioritize Indian landfills according to the health risks, they pose to people, taking into account the contamination brought on by heavy metals and their physicochemical pollutants. Methods: A hybrid method integrating Trapezoidal Neutrosophic Fuzzy Numbers with Mamdani- Fuzzy Inference System was used to analyse twelve landfill sites based on their heavy mental and indicator presence in each landfill sites. To obtain a comparative risk ranking from transformed fuzzy output a score function was applied. Python code was implemented, the comparison of risk scores was done among the twelve landfill sites. Findings: Ghazipur was identified as the site with the highest risk by the assessment, with a risk score of 0.5813, followed by Narela- Bawana, Hyderabad, Gurgoan, Kadapa, Ariyamangalm, Okhla, Kodungaiyur, Silchar, Perungudi, Raipur and Ahmedabad. Significant health risks were indicated by the other sites, which also displayed notable high scores. The model's ability to handle ambiguous environmental data allowed for a more accurate assessment of landfill risk, as demonstrated by the results. The results enabled clear differentiation and comparative prioritization among the rank-based interpretation of landfill sites. The findings offer a scalable and quantitative method. With limited data, this framework offers practical insights to direct waste management and environmental health policies. Novelty: An integrated model for evaluating landfill health risk ranking that uses rule-based and neutrosophic score-driven site prioritization to improve decision-making with incomplete and uncertain environmental data. 2020 Mathematics Subject Classification: 90B50, 90C70. Keywords: Metal Contaminants, Trapezoidal Neutrosophic Fuzzy Numbers, Risk Assessment, Fuzzy Inference System, Environmental Uncertain Data