Development of a Decision Making Framework for Solid Waste Management Using GIS-based Site Selection and an Economic Comparison

  • Author / Creator
    Khan, Md. Mohib-Ul-Haque
  • The management of municipal solid waste (MSW) is one of the major challenging issues for various global jurisdictions. MSW generation and disposal rates are increasing worldwide along with increased population and urbanization. Limited landfill capacity and long-term environmental issues associated with landfilling (e.g., landfill gas emission and leachate generation) have led to a need to consider sustainable alternatives for MSW use and disposal.
    Two of the most important issues associated with waste conversion facility building are optimal site location and economic feasibility. The overall objective of this research is to: (1) develop a methodology for waste conversion facility site selection and (2) create a generic decision-making model that can be used by county planners to make waste conversion facility decisions incorporating economic and social parameters. Siting a solid waste-to-energy (WTE) facility requires an assessment of solid waste availability as well as compliance with environmental, social, and economic factors. There are some important parameters (e.g., location and amount of available waste, soil type, etc.) that should be considered when siting WTE facilities. These parameters do not have equal weight. In the first part of this study, six different waste management scenarios were studied with three different weights used. The analytic hierarchy process (AHP) was used to assign weights to the parameters. Both waste availability amount-dependent and waste availability amount-independent studies were carried out. The purpose of the second part of this study is to develop a framework to help compare the costs of different waste management scenarios. A user-friendly model was developed that allows the user to input different waste availability details and other variables (i.e., cost of biofuel, cost of electricity, etc.). Ten waste management scenarios were compared based on either gate fee or internal rate of return. These scenarios are: (i) gasification (producing biofuel), (ii) gasification (producing electricity), (iii) anaerobic digestion, (iv) composting, (v) new landfill, (vi) gasification (producing biofuel) integrated with anaerobic digestion, (vii) gasification (producing electricity) integrated with anaerobic digestion, (viii) gasification (producing biofuel) integrated with composting, and (ix) gasification (producing electricity) integrated with composting. A sensitivity analysis was conducted to assess the impact of changes in the values of different parameters.
    For this research, a case study of Parkland County was conducted. For this case study, at 10% IRR and a waste availability of 25,000-50,000 tonne/year, composting is the cheapest solution (77 -86 $/tonne gate fee), and for a waste availability of 50,000-150,000 tonne/year, a gasification (producing electricity) facility integrated with composting is the cheapest solution with a gate fee of 42 -77 $/tonne. Moreover, as incentives (from government or other parties) increase for waste-to-energy scenarios, these scenarios become cheaper. As capital investment incentives increase, the facility owner’s capital investment decreases.

  • Subjects / Keywords
  • Graduation date
    Fall 2015
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
  • Institution
    University of Alberta
  • Degree level
  • Department
  • Specialization
    • Engineering Management
  • Supervisor / co-supervisor and their department(s)
  • Examining committee members and their departments
    • Kumar, Amit (Mechanical Engineering)
    • Tian, Zhigang (Will) (Mechanical Engineering)
    • Gupta, Rajendra (Chemical and Materials Engineering)