Waste management is a significant challenge for India. The Indian waste landscape is changing rapidly as the population grows, the composition of the waste generated evolves, the extent of waste segmentation changes, and the technologies available to collect and process waste improve. Municipal solid waste management systems in India will need to adapt to changing consumer behavior.
Our research focuses on helping Indian cities improve collection, transportation, and treatment of waste by developing a GIS-based decision support tool that assesses the cost effectiveness and efficiency of collection strategies, treatment technologies, and system configurations, and then optimizes system design. This will enable designers to identify a waste management system architecture that considers the unique elements of a city, including the demographics, waste composition, scale, existing infrastructure for waste collection and treatment, and potential for implementing new technologies.
To characterize and quantify municipal waste generation, we conducted waste audits in six pilot neighborhoods in the mid-sized industrial city of Muzaffarnagar, Uttar Pradesh, spanning different socio-economic groups. We have also conducted a pilot project to understand the behavioral incentives that work best in encouraging households to segregate their food waste. These efforts will provide additional data with which to test and develop the GIS-based decision support tool.
In the case of Muzaffarnagar, the tool has been used to identify waste system configurations which can reduce costs by 5% while increasing waste system coverage by 20%. We have also been able to identify an ideal scenario which reconciles the conflicting objectives of minimum cost and maximum employment within the system (cost-labor tradeoff). The best compromise solution was at the system configuration where a 10% increase in costs corresponded to a 500% increase in employment.