Modeling Municipal Solid Waste Management System under Uncertainty

Abstract

In this study, a dynamic inexact waste management (DIWM) model is developed for identifying optimal waste-flow-allocation and facility-capacity-expansion strategies under uncertainty and is based on an inexact scenario-based probabilistic programming (ISPP) approach. The DIWM model can handle uncertainties presented as interval values and probability distributions, and it can support assessing the risk of violating system constraints. Several violation levels for facility-capacity and waste-diversion constraints are examined. Solutions associated with different risks of constraint violation were generated. The modeling results are valuable for supporting the planning of the study city's municipal solid waste (MSW) management practices, the long-term capacity expansion for waste management system, and the identification of desired policies regarding waste diversion. Sensitivity analyses are also undertaken to demonstrate that the violations of different constraints have varied effects on the planning of waste-flow allocation, facility expansion, and waste management cost.

Composting kinetics in full-scale mechanical–biological treatment plants

“…The dependence of composting rate on oxygen concentration in the free air space has been commonly modelled by a Monod type equation (Bertoni et al, 1997;Bongochgetsakul and Ishida, 2008;Cronjé et al, 2004;Haug, 1993;Kim et al, 2000;Li et al, 2002;Petric and Selimbasic, 2008;Qin et al, 2007;Stombaugh and Nokes, 1996;Tollner et al, 1998;Xi et al, 2005Xi et al, , 2008Yu et al, 2009). Richard (1997), Richard and Walker (1999) and carried out detailed experimental work that analyzed the dependence of reaction rate on oxygen.…”

Examining the effectiveness of municipal solid waste management systems: An integrated cost–benefit analysis perspective with a financial cost modeling in Taiwan

“…From the recent literature, several types of accounting systems for MSW management have been established on the basis of economic values, physical quantities, emergy, and resource-driven units. Economic accounting systems for MSW management deal with the cash flows of waste treatment facilities (Chang et al, 1993;Chang and Wang, 1995;Daskalopoulos et al, 1998;Weng and Chang, 2001;Wu et al, 2006;Chang and Davila, 2007;Xu et al, 2009;Li and Huang, 2010). The physical accounting systems for MSW management estimate the material flows of a system with an extension of life cycle cost (LCC) analysis (Jasch, 2003;Eriksson et al, 2005;Carlsson-Reich, 2005;Nakamura and Kondo, 2006;Khoo, 2009;Guinée et al, 2011).…”

“…Alternatively, the analysis of the financial cost structure involving the related influencing factors with the existing financial data would be a preliminary and relatively rapid approach to examine the cost-effectiveness of the MSW management systems (Chang et al, 1993;Chang and Wang, 1995;Daskalopoulos et al, 1998;Weng and Chang, 2001;Wu et al, 2006;Hogg and Eunomia Research & Consulting, 2006;Chang and Davila, 2007;Xu et al, 2009;Li and Huang, 2010). Besides, the information of the required financial costs of MSW management systems is quite essential for the municipalities to make precise budget plans.…”

Air Space in Composting Research: A Literature Review

“…Another example of FAS application in composting modelling is described by Li et al (2002). In this study, the authors incorporated the FAS correction term (Haug 1993) Monte Carlo simulation and factorial design to analyze how temperature, moisture content, oxygen concentration, and FAS (considered as uncertain parameters) affect composting modelling process.…”