| Title | Economic, environmental and social optimization of solid waste management in the context of circular economy |
|---|---|
| ID_Doc | 2870 |
| Authors | Rathore, P; Sarmah, SP |
| Title | Economic, environmental and social optimization of solid waste management in the context of circular economy |
| Year | 2020 |
| Published | |
| Abstract | Rapid growth in population and urbanization is increasing the generation of solid waste as well as demand for natural resources. Moreover, increasing demand and fixed available quantity of natural resources are making the problem more complex and challenging. It has been identified that; the concept of the circular economy can provide the solution to the problem. This study examines the economic, environmental, and social feasibility of circular economy in municipal solid waste (MSW) management. This study proposes a concept for the utilization of collected organic MSW by converting it into biogas and then use it as a fuel in a thermal power plant (TPP) to reduce the burden on coal mines. A mixed-integer non-linear programme (MINLP) model is formulated for the minimization of the total cost which is the sum up of (i) functioning cost, (ii) transportation cost, (iii) hiring cost, (iv) environmental cost, (v) social cost, and (vi) penalty cost. The proposed system is validated by a case study on a city Bilaspur, India. Developed model is evaluated for two scenarios: (i) present scenario, in which desegregated MSW is collected from sources and dispose it to landfill, and TPP gets its fuel only from coal mine; and (ii) proposed scenario, in which collected organic MSW is sent to biogas plant and from there, biogas is transported to TPP as a fuel. The model is solved for both the scenarios and identifies that the proposed system is performing better. It is reducing the total cost of the present system by around INR 30,462,326 per day which is consists of a reduction in functioning, transportation, environmental and social cost by INR 225580, 30120443, 113905 and 2397. In addition to that, it is also reducing the carbon emission by 186.43 tonnes daily. Further, sensitivity analysis is performed by varying the collection efficiency and TPP capacity parameter for testing the fitness of the model globally and in different cities. From the analysis, it is identified that the model is globally implementable and best suited for cities having low TPP capacity. |
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