Demonstrates improved waste collection efficiency in a flood-prone town, suggesting enhanced local solutions for urban waste challenges.
Municipal solid waste management (MSWM) remains a critical challenge in India due to rapid urbanisation, increasing waste volumes, and limited institutional capacity. Although urban local bodies (ULBs) allocate up to 80% of their MSWM budgets to collection and transport, inefficiencies persist due to unoptimised routes and poor alignment with local conditions. Most geographic information system (GIS)-based optimisation models remain top-down, failing to reflect on-the-ground realities and are rarely implementable. This study presents a participatory GIS-based routing methodology for decentralised MSWM system in a flood-prone town in Kerala, India. It integrates standard geospatial data with tacit knowledge from ULB officials and frontline sanitation workers through participatory mapping and ground-truthing, producing spatial layers on waste generation, transport conditions, flood-prone roads, and existing collection clusters, pick-up points, and storage facilities. Based on this, the study proposes operational changes, including new pick-up points, mini-material collection facilities (intermediary storage hubs), and a three-tier vehicle system tailored to local constraints. ArcGIS Network Analyst is used to identify optimal routes, incorporating flood-prone roads as network barriers. Compared to the current system, the optimised plan is flood-resilient and achieves a 32% reduction in travel distance, 35% cut in fuel use and emissions, and a 62% increase in collection capacity and 100% household coverage, along with better working conditions. The study offers a scalable framework that merges technical optimisation with context specificity, enabling ULBs in resource-constrained settings to co-produce climate-resilient transport solutions.
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Suresh et al. (2026) studied this question.
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