Petroleum-contaminated groundwater remediation systems design: A data envelopment analysis based approach

  • Authors:
  • Xiaodong Zhang;Guo H. Huang;Qianguo Lin;Hui Yu

  • Affiliations:
  • Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, Canada S4S 0A2;Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, Canada S4S 0A2 and Chinese Research Academy of Environmental Science, Beijing Normal ...;Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, Canada S4S 0A2;Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Saskatchewan, Canada S4S 0A2

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2009

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Abstract

Groundwater contamination is one of important environmental problems at petroleum-related sites, which is causing more and more attention. It can bring serious adverse effects on the environment and human health. Design of a groundwater remediation system is desired for supporting the management of petroleum-contaminated sites. Due to high remediation cost and extensive alternatives, efficient remediation design needs to be determined. Data envelopment analysis (DEA) is an approach to measure the relative efficiencies of decision-making units (DMUs) with multiple inputs and multiple outputs without underlying assumptions. However, few of these studies were applied to the design of groundwater remediation systems, where efficient alternatives for remediation systems design need to be determined. This paper proposes a hybrid decision support approach based on data envelopment analysis to determine the most preferable design alternatives for groundwater remediation systems. The total remediation system cost, amount of additional wells, and manpower requirements will be employed as the input variables, while the removal efficiency and technical feasibility as the output variables. The proposed approach will be applied to a case study of designing a groundwater remediation system at a petroleum-contaminated site in western Canada. The most preferable design alternative can be obtained to provide effective decision support for cleaning up the contaminated site.