Factorial-Based Inexact Stochastic Fuzzy Chance Constraint Programming Framework for Municipal Solid Waste Management with GHG Emission Trading: Analysis of Multilevel Parametric Interactions

This study proposes a factorial inexact stochastic fuzzy chance constraint programming framework for dealing with uncertainties in municipal solid waste management under consideration of greenhouse gas (GHG) emission trading. It can reflect uncertainties expressed as fuzzy, interval, and random vari...

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Bibliographic Details
Published in:Water, air, and soil pollution Vol. 227; no. 10; pp. 1 - 383
Main Authors: Ma, Xiaolin, Ma, Chi, Liu, Hongyu
Format: Journal Article
Language:English
Published: Cham Springer International Publishing 01.10.2016
Springer Nature B.V
Subjects:
Analysis
Atmospheric Protection/Air Quality Control/Air Pollution
Carbon dioxide
Climate change
Climate Change/Climate Change Impacts
Composting
credit
Decision making
Earth and Environmental Science
Emissions
Emissions control
Emissions trading
Environment
Environmental monitoring
Fuzzy sets
Greenhouse effect
greenhouse gas emissions
Greenhouse gases
Hydrogeology
Incinerators
Linear programming
Mathematical programming
Methods
Municipal solid waste
Optimization techniques
purchasing
Random variables
Soil Science & Conservation
Solid waste disposal
Solid waste management
Stochastic models
Stochasticity
Studies
uncertainty
Waste disposal
Waste management
Water Quality/Water Pollution
Parameter interaction
GHG emission
Multiple uncertainties
Decision making
Municipal solid waste
ISSN:0049-6979, 1573-2932
Online Access:Get full text
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Summary:This study proposes a factorial inexact stochastic fuzzy chance constraint programming framework for dealing with uncertainties in municipal solid waste management under consideration of greenhouse gas (GHG) emission trading. It can reflect uncertainties expressed as fuzzy, interval, and random variables and generate desired management strategies for minimizing the integrated cost for solid waste disposal and purchasing GHG emission credit. Moreover, multilevel factorial analysis is conducted to reveal the main and interactive effects of uncertain parameters. The results show that effective waste allocation schemes can be obtained to meet the waste disposal demands and GHG emission requirements under different α -cut levels. The changes in the fuzzy confidence level have impacts on the waste allocation schemes, especially for the waste flow to the incinerator. The disposal cost differs across the three levels of 0.3, 0.5, and 0.7 for incinerator capacity constraint when the fuzzy confidence level of composting capacity constraint is equal to 0.5, implying the existence of the interaction between uncertainties in the incinerator and composting facility. Comparison between the waste management practices with and without considering GHG emission requirements indicates that the purchase of GHG emission credits would contribute about 10 % to the total cost, which would not be influenced significantly by the α -cut level.
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ISSN:0049-6979
1573-2932
DOI:10.1007/s11270-016-3034-5