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A Stepwise-Inference-Based Optimization System for Supporting Remediation of Petroleum-Contaminated Sites

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Abstract

Groundwater contamination by leakage and spill of petroleum hydrocarbons from underground storage tanks has been a major environmental concern. Among various remediation alternatives, the vacuum-enhanced free product recovery (VFPR) is an important technology to extract light nonaqueous-phase liquids (LNAPLs) from subsurface. However, efficient design of a VFPR system was challenging to practitioners, since the process of hydrocarbon removal is costly and time consuming. To address such a problem, an integrated study system for optimizing the VFPR process was developed through coupling a numerical modeling system, a multivariate regression technique and nonlinear optimization model into a general framework. A two-dimensional multiphase flow simulation system was provided for modeling VFPR processes. An iterative stepwise-inference regression (ISIR) method was advanced for establishing a linkage between remediation actions and system responses. A nonlinear optimization model embedded with ISIR was then established for generating desired operating conditions. The results from a case study demonstrated that the established optimization model could effectively analyze tradeoffs between various environmental and economical considerations, and provide effective decision supports for site remediation practices. Compared with the conventional stepwise-cluster analysis method, the proposed ISIR method was more efficient and reliable in approximating relationships between remediation actions and system responses, and could significantly enhance the robustness of optimization solutions.

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Acknowledgement

This research has been supported by the Natural Science and Engineering Research Council of Canada (155701) and the Major State Basic Research Development Program (2005CB724200) and (2006CB403307). The authors are extremely grateful to the editor and the anonymous reviewers for their insightful comments and suggestions.

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Authors and Affiliations

  1. Faculty of Engineering, University of Regina, Regina, SK, S4S 0A2, Canada

    X. S. Qin & G. H. Huang

  2. Chinese Research Academy of Environmental Science, No. 8 Dayangfang, Anwai, Beijing, 100012, P.R. China

    G. H. Huang

  3. Department of Chemical Engineering, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada

    A. Chakma

Authors
  1. X. S. Qin
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  2. G. H. Huang
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  3. A. Chakma
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Correspondence to G. H. Huang.

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Qin, X.S., Huang, G.H. & Chakma, A. A Stepwise-Inference-Based Optimization System for Supporting Remediation of Petroleum-Contaminated Sites. Water Air Soil Pollut 185, 349–368 (2007). https://doi.org/10.1007/s11270-007-9458-1

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  • DOI: https://doi.org/10.1007/s11270-007-9458-1

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