Siting of a central healthcare waste incinerator using GIS-based Multi Criteria Decision Analysis


Hariz H. A. , DÖNMEZ C. Ç. , SENNAROĞLU B.

JOURNAL OF CLEANER PRODUCTION, cilt.166, ss.1031-1042, 2017 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 166
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1016/j.jclepro.2017.08.091
  • Dergi Adı: JOURNAL OF CLEANER PRODUCTION
  • Sayfa Sayıları: ss.1031-1042

Özet

This research looks into the problem of poor healthcare waste management in Kenya. Most healthcare facilities lack enforcement of existing legislation for handling, and disposal of health care waste, an issue exacerbated by the fact that regulating bodies lack a systemized oversight plan of ensuring compliance. This paper suggests that setting up a centralized modern waste incinerator will facilitate in overcoming the problems outlined above. The study area for this study is Kilifi, a county which lies along the Kenyan Coast. The county has over 330 healthcare facilities. The main objective of this study was to identify a suitable area to build an incinerator to serve these facilities. A two stage analysis was employed to identify a suitable location. Geographical Information Systems (GIS) techniques were used to first screen the entire study area to eliminate unsuitable land that did not satisfy the eight economic, environmental and social criteria taken into account. In the second stage, Multi-Criteria Decision Analysis (MCDA) methods were used to analyse and rank the potential sites. From the GIS analysis, it was found that only around 8.2% of the land was suitable. From this spatial analysis, eight potential sites were identified. These sites were then ranked using three MCDA methods, namely, AHP, VIKOR and PROMETHEE. This study differs from previous studies that use the GIS-MCDA model, in that three MCDA methods each with a different mode of operation was used. This was for the sake of performing a comparison on the results and to determine if there would be significant differences especially with regard to the best ranked site. Interestingly, the methods all identified 'site 6', an area near the urban town of Malindi as the most suitable. The rest of the rankings were almost consistent across all three methods. (C) 2017 Elsevier Ltd. All rights reserved.