Monte Carlo Simulation–Aided Analytic Hierarchy Process Approach: Case Study of Assessing Preferred Non-Point-Source Pollution Control Best Management Practices
Publication: Journal of Environmental Engineering
Volume 139, Issue 5
Abstract
This paper presents an innovative Monte Carlo simulation—aided analytical hierarchy process (MC-AHP) approach by integrating the beta-PERT distribution, pairwise comparison, and Monte Carlo simulation. A case study related to non-point-source pollution management in southwest China is used to demonstrate the applicability of the proposed approach. Five alternative best management practices (BMPs) (i.e., constructed wetlands technology, conservation tillage, fertilizer and pesticide management, irrigation management, and livestock grazing management) are evaluated by experts using a number of criteria such as reliability, capital costs, and environmental benefits. Statistical analysis indicates that conservation tillage has the highest score (0.25–0.36) in most replications, and its overlap with the second-best alternative is statistically negligible. Constructed wetlands technology, along with fertilizer and pesticide management, are mostly found as the second- and third-best alternatives, with scores ranging from 0.18 to 0.28 and 0.17 to 0.25, respectively. Compared with the traditional analytic hierarchy process (AHP), the proposed MC-AHP approach addresses the uncertainty resulting from insufficient information and opinion difference in group decision-making problems.
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Acknowledgments
The research was supported by the National Natural Science Foundation of China (No. 51179070), Natural Science and Engineering Research Council of Canada, and United Nations Development Programme (UNDP) as well as the China International Center for Economic and Technical Exchanges (CICETE) of the Ministry of Commerce of China.
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Published In
Journal of Environmental Engineering
Volume 139 • Issue 5 • May 2013
Pages: 618 - 626
Copyright
© 2013 American Society of Civil Engineers.
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Received: Apr 14, 2012
Accepted: Oct 26, 2012
Published online: Oct 29, 2012
Published in print: May 1, 2013
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