Urbanization and population growth are solely responsible factors for the increase in the quantity of solid waste. Additionally, changes in lifestyle patterns, a shift from biodegradable to non‐degradable waste, and industrialization have led to an increase in the toxicity of solid waste. These factors have left solid waste as a major cause of environmental degradation today. Thus, this study underscores the necessity of intelligent waste management systems in addition to attempting to address the municipal solid waste issue in the city. A total of 129 samples were collected from 30 locations, with findings indicating significant variability in waste types and quantities. Maximum waste generation was observed at Gandhi Nagar (14.41 kg), while Shastri Nagar exhibited the highest proportion of food waste (87.15%). Plastic waste peaked at Domana (66.29%), and vegetable waste was predominant in Sunjwan (76.17%). Further, moisture content (M.C.) analysis revealed high organic content in waste streams, with levels exceeding 76% in some locations, advocating for composting as an effective management strategy. In addition, this study integrates solid waste characterization with spatial interpolation using the inverse distance weighted (IDW) technique (QGIS) to generate high‐resolution waste distribution maps across Jammu city. The approach combines with field‐based data analysis, statistical validation ( R 2 = 0.97), and a regression study to identify spatial hotspots and key predictors of waste generation, providing a data‐driven solution for optimized and area‐specific solid waste management planning. These findings offer actionable insights for improving waste management systems in Jammu city, fostering sustainability, and reducing environmental hazards.
Alam et al. (Thu,) studied this question.