Title

Environmental Performance Evaluation Of Large-Scale Municipal Solid Waste Incinerators Using Data Envelopment Analysis

Abstract

Limited to insufficient land resources, incinerators are considered in many countries such as Japan and Germany as the major technology for a waste management scheme capable of dealing with the increasing demand for municipal and industrial solid waste treatment in urban regions. The evaluation of these municipal incinerators in terms of secondary pollution potential, cost-effectiveness, and operational efficiency has become a new focus in the highly interdisciplinary area of production economics, systems analysis, and waste management. This paper aims to demonstrate the application of data envelopment analysis (DEA) - a production economics tool - to evaluate performance-based efficiencies of 19 large-scale municipal incinerators in Taiwan with different operational conditions. A 4-year operational data set from 2002 to 2005 was collected in support of DEA modeling using Monte Carlo simulation to outline the possibility distributions of operational efficiency of these incinerators. Uncertainty analysis using the Monte Carlo simulation provides a balance between simplifications of our analysis and the soundness of capturing the essential random features that complicate solid waste management systems. To cope with future challenges, efforts in the DEA modeling, systems analysis, and prediction of the performance of large-scale municipal solid waste incinerators under normal operation and special conditions were directed toward generating a compromised assessment procedure. Our research findings will eventually lead to the identification of the optimal management strategies for promoting the quality of solid waste incineration, not only in Taiwan, but also elsewhere in the world. © 2010 Elsevier Ltd.

Publication Date

7-1-2010

Publication Title

Waste Management

Volume

30

Issue

7

Number of Pages

1371-1381

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.wasman.2010.02.002

Socpus ID

77952674940 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/77952674940

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