Optimization of Municipal Solid Waste Management in Morocco Using Fuzzy TOPSIS: A Multi-Criteria Evaluation in the Rabat-Salé-Kénitra Region (Morocco)
Więcej
Ukryj
1
1: Civil Engineering and Environment Laboratory (LGCE), Materials Water and Environment team, Higher School of Technology of Mohammed V University in Rabat, MA11060 Sale, Morocco.
2: Doctoral Studies Center of Engineering Sciences and Techniques, Mohammadia School of Engineers (EMI), Mohammed V University of Rabat, Av. Ibn Sina, B.P. 765, Rabat-Agdal, 10090, Morocco.
2
1: Civil Engineering and Environment Laboratory (LGCE), Materials Water and Environment team, Higher School of Technology of Mohammed V University in Rabat, MA11060 Sale, Morocco. 2: Doctoral Studies Center of Engineering Sciences and Techniques, Mohammadia School of Engineers (EMI), Mohammed V University of Rabat, Av. Ibn Sina, B.P. 765, Rabat-Agdal, 10090, Morocco.
Autor do korespondencji
rahma EL HALLAB
1: Civil Engineering and Environment Laboratory (LGCE), Materials Water and Environment team, Higher School of Technology of Mohammed V University in Rabat, MA11060 Sale, Morocco.
2: Doctoral Studies Center of Engineering Sciences and Techniques, Mohammadia School of Engineers (EMI), Mohammed V University of Rabat, Av. Ibn Sina, B.P. 765, Rabat-Agdal, 10090, Morocco.
SŁOWA KLUCZOWE
DZIEDZINY
STRESZCZENIE
Sustainable municipal solid waste (MSW) management is a major challenge for local authorities in Morocco. This study applies the Fuzzy TOPSIS multi-criteria method to evaluate and rank seven MSW management scenarios for the prefectures of Rabat, Salé, and Skhirat-Témara in Morocco. The evaluation is based on 16 sub-criteria classified into five categories: institutional, social, environmental, economic, and technical. The study was based on the results of a survey conducted among experts with knowledge of MSW management (Regional Council, Regional Territorial Administration, Regional Department of the Environment). The survey data was then analyzed in the form of linguistic scales converted into triangular fuzzy numbers. The aggregated decision matrix was normalized, weighted, and compared to ideal positive and negative solutions according to the Fuzzy TOPSIS algorithm, allowing the calculation of a proximity coefficient for each alternative. The results obtained indicate that alternative A7, corresponding to mechanical-biological treatment (MBT) coupled with energy recovery and composting, is the most efficient, with a proximity coefficient of 0.9767. It is followed by alternative A6 (sorting, composting, and energy recovery) with a score of 0.7275, then by alternative A5 (mechanical sorting and composting) with 0.6991. The other scenarios perform less well and are ranked in the following order: A3 (simple mechanical sorting, 0.4920), A4 (mechanical sorting, recycling, and landfill, 0.2914), A2 (sorting at source and selective collection, 0.2961), and finally A1 (collection and controlled landfill, 0.2390).