Multi-period Planning of Municipal Solid Waste Management: a Case Study in Qingdao

With the increase of population and the improvement of people's living standards, the amount of municipal solid waste (MSW) increases rapidly. It is a challenge for the cities in developing countries to deal with these MSW economically and environmentally. This paper proposed an integrated framework which combines the grey system theory and mathematical programming model to deal with MSW management. First, the factors affecting MSW generation are analyzed and screened out by grey correlation analysis. The factors with higher priority are selected to perform the regression analysis. The generation of MSW is predicted based on the grey model GM (1,1). Second, a multi-period planning model is proposed to optimize MSW management of Qingdao City, China. The model is formulated as mixed integer nonlinear programming (MINLP) model for the scenario with variable capacities of treatment plants and mixed integer linear programming (MILP) for the scenario with given capacities of treatment plants. Four different scenarios are considered: minimum cost scenario with and without variable capacities, minimum carbon emissions with and without variable capacities. The results indicate that the average cost of MSW treatment for the minimum cost scenario with and without variable capacities is 28.32$/t and 27.92 $/t, respectively. The average carbon emission for the minimum emission scenario with and without variable capacities is 0.751 t CO2/t MSW and 0.721 t CO2/t MSW, respectively. This shows the variable expansion capacities of disposal technologies could reduce the cost and carbon emission of MSW treatment compared with the scenario with given capacities. The findings are useful for the decision-maker to adopt effective policy for MSW management. It provides a systematic method for MSW management for other developing countries.