A new framework for assessing the sustainability of municipal solid waste treatment techniques applying multi-criteria decision analysis.

Autor: Omran, I. I., Al-Saati, N. H., Salman, A. A., Hashim, K.
Předmět:
Zdroj: International Journal of Environmental Science & Technology (IJEST); Sep2023, Vol. 20 Issue 9, p9683-9692, 10p
Abstrakt: In this study, a new multi-criteria decision analysis (MCDA) framework was designed and adopted for assessing the sustainability of solid waste treatment techniques (six treatment techniques) in urban areas of Baghdad (the capital of Iraq). A questionnaire has been developed that contains the four dimensions of sustainability (environmental, economic, social, and technical) and their indicators. These indicators have been studied, analyzed, and evaluated by a group of specialists working on solid waste management. Then the data were modelled adopting the weighted sum model (WSM), weighted product model (WPM) and technique for order preference by similarity to ideal solution (TOPSIS). The main results of the study clearly showed that the sustainability of municipal solid waste treatment in the city of Baghdad is directly related to the four dimensions in variable proportions (weights), and the environmental dimension gained the largest impact (46.9%) while the technical dimension gained the least impact (16.1%) on sustainability. By analyzing the questionnaire data according to the designed framework with reference to the three methods of MCDA (WSM, WPM, and TOPSIS) and in the presence of three Scenarios of the multi-criteria weights, Recycling by Source-Separation (RSS) Technique gained the highest score (0.896) which means that it is the best alternative, while Anaerobic Digestion Technique (AD) gained the lowest score (0.397) which means that it is the worst alternative, other scores are (0.874) for material recycling facility (MRF) Technique, (0.84) for Landfill Technique, (0.813) for Composting Technique, and (0.584) for mass-burn incineration (MBI) Technique. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index