Evaluating waste management alternatives by the multiple criteria approach

S. S. Chung, Chi Sun Poon

Research output: Journal article publicationJournal articleAcademic researchpeer-review

48 Citations (Scopus)

Abstract

in the past, justifications on decision making in the environmental (including waste management) field have always been qualitative and implicit in Hong Kong. The use of multiple criteria analysis (MCA) in waste management decision making has the advantage of rendering subjective and implicit decision making more objective and transparent. An additional merit of MCA is its ability to accommodate quantitative and qualitative data. In this paper the MCA approach is made use to find out the preferred waste management option(s) for Hong Kong (HK). Landfilling, waste to energy, composting and source separation of municipal solid waste (MSW) are analysed by the MCA, It is found that source separation is the most preferred option. Waste to energy is found to have a better overall performance than landfilling (with methane recovery). Composting of solid waste is found to be very land intensive and should only be used with care. Incineration without energy recovery is the least desirable option, Landfilling of solid waste although is not the best option, it is indispensable in a waste management system. Thus, it should only be practised in a limited extent. It is also demonstrated in this paper that dominance pairwise comparison is not sensitive to weighting differences. Thus, if decisive criteria exist, then they should be considered prior to the use of dominance pairwise comparison.
Original languageEnglish
Pages (from-to)189-210
Number of pages22
JournalResources, Conservation and Recycling
Volume17
Issue number3
DOIs
Publication statusPublished - 1 Jan 1996

Keywords

  • Composting
  • Decision making
  • Landfilling
  • Multiple criteria analysis
  • Municipal solid waste management
  • Source separation
  • Waste to energy

ASJC Scopus subject areas

  • Waste Management and Disposal
  • Economics and Econometrics

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