1. Development of a community-based participatory network for integrated solid waste management By: Y.P. Cai, G.H. Huang, Q. Tan & G.C. Li EVSE, Faculty of Engineering University of Regina April, 2008

2. Content 1. Introduction 2. Methodology 3. A Hypothetical Case Study 4. Application 5. Expected results

3. 1. Introduction (1) Increasing concerns over municipal solid waste… !!! The situation will be even worse due to: urbanization, population growth, economic development and change of life style…, especially in many developing countries.

4. 1. Introduction (2) In order to deal with waste related problems… A number of concepts, processes, factors as well as their interactions should be considered. Multiple concepts and ideas

5. 1. Introduction (3) Multiple processes and facilities Waste can be recycled, composted, incinerated, or landfilled.

6. 1. Introduction (4) Multiple stakeholders and interest groups Different stakeholder have different opinions on solid waste problems Local community and residents  objection to waste treatment facilities Government  financial budget and environmental protection Managers  minimizing costs and maximizing benefits …

7. 1. Introduction (5) Therefore, Identification of desirable waste-flow-allocation patterns under uncertainty has received considerable attention … Thus, several challenges will be faced by decision makers… How to make tradeoffs between various objectives? How to identify the most acceptable decision alternatives among various interest groups and stakeholders? How to examine the complex interactions between social development, environmental protection, and economic investment? How to communicate the uncertain and conflicting information from different stakeholders into the process of decision making? How to identify optimal schemes for waste transport and treatment, as well as capacity expansion patterns for relevant facilities within a short- or long-term? How to locate waste treatment facilities in a community of a large-scale region?

8. 2. Methodology (1) Thus, identify science-based schemes for solid waste management under uncertainty is desired… i.e., low economic cost, low environmental impacts high social acceptability high sustainability flexible, applicable and robust… For dealing with such problems, optimization models are effective…

9. Previously, dealing with waste management system in deterministic manner LP MIP DP -- Linear programming ( LP ) -- Mixed integer programming ( MIP ) -- Dynamic programming ( DP ) 2. Methodology (2) They cannot: (a) reflect uncertainty, (b) handle interactions between parameters, and (c) be applicable to real-world cases

10. Also, dealing with waste management system under uncertainty 2. Methodology (3) -- Fuzzy linear programming (FLP) -- Stochastic linear programming (SLP) -- Interval linear Programming (ILP) And their hybrid, e.g.,: -- Interval integer programming (IIP) -- Interval fuzzy linear programming (IFLP) -- Fuzzy integer programming (FIP) Till now, there are more hybrid methods…

11. ● direct communication of uncertainties ● reflection of different uncertainty types ● reasonable computational requirements ● flexibility of results interpretation ● generation of decision alternatives ● applicable to practical problems 2. Methodology (4) A number of advantages can be identified with such inexact programming However, an individual deterministic/inexact modeling method can hardly deal with waste related problems in a systematic manner, can hardly take public opinions into consideration, especially in various communities of a region…

12. 2. Methodology (5) Thus, major theme of this research focus on: ● An inexact fuzzy stochastic programming model ● Multi-criteria decision analysis ● Public participation and community involvement ● Policy analysis An integrated framework can be established for effectively addressing problems related to solid waste in communities…

13. 2. Methodology (6) General framework…

14. 2. Methodology (7) 2.1. An inexact programming model: OOrOOr Relevant parameters ( fuzzy- stochastic distribution )

15. 2. Methodology (8) 2.2. MCDA methods: SAW (simple additive weighting) ELECTRE (elimination and choice translating reality) TOPSIS (technique ordered preference by similarity to the ideal solution)

16. 2. Methodology (9) 2.3. Public participation and community involvement :

17. 2. Methodology (10) 2.4. Policy analysis: comprehensive questionnaire survey

18. 3. A Hypothetical Case Study Residue Landfill W-T-E Facility Community 2 Community 1 Community 33 MSW

19. 4. Application in the future study Community 1

20. 5. Expected Result... Plan of capacity expansion Capacity (t/wk) Existing Landfill 19962000 2005 2010 2025 Composting facility Recycling facility 2015 2020 500 [45 49] [161 182] [430 434] [622 626] [511 532] [861 882]

21. Plan of waste flow allocation

22. Thank you very much