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Journal of Environmental Accounting and Management 3(3) (2015) 275--283 | DOI:10.5890/JEAM.2015.09.006

Tao Xie$^{1}$,$^{2}$, Reti Hai$^{1}$, Xiangchun Quan$^{3}$, Anjie Li$^{3}$, Rui Liu$^{2}$, Yaxin Chen$^{2}$

$^{1}$ Beijing Engineering Research Center of Environmental Material for Water Purification, Beijing University of Chemical Technology, Beijing, China

$^{2}$ Institute of Resources and Environment Science, Mapuni, Beijing, China

$^{3}$ Key Laboratory of Water and Sediment Sciences of Ministry of Education/State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, China

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Abstract

Multi-criteria analysis was used to compare technology solutions for 3 Selection of soil remediation technologies for contaminated sites is difficult given the large number of technologies available and the economic, social, and environmental impacts of site remediation activities. In this paper, we take into account a multitude of consequences and analyze their impacts with multi-criteria utility theory. By establishing the AHPPROMETHEE II (Analytic Hierarchy Process-Preference Ranking Organization Method for Enrichment Evaluations II) method, an Environmental Decision Support System (EDSS) has been developed for the purpose of identifying optimum soil remediation approaches for contaminated site. In the EDSS, AHP is used to structure the decision problem and to attribute weights to the criteria, whereas PROMETHEE is used to obtain a final ranking of the proposed alternatives. In addition, the hierarchical decision tree was constructed according to 4 criteria, i.e., time and economic costs, technical levels, technical applicability and social benefits, 12 indicators, and 21 soil remediation alternatives. The system has been applied to a case study, in which the best option of soil remediation technology for the particular remediation goal could be achieved. The effectiveness and shortcomings of this system are also discussed.

Acknowledgments

This work was supported by a Grant from the National High-Tech Research and Development (863) Programme of China (No. 2009AA06A41803). The authors appreciate the helpful comments given by editors and anonymous reviewers over this paper.

References

1. [1]	Cai, Q.Y., Mo, C.H., Wu, Q.T., Katsoyiannis, A. and Zeng, Q.Y. (2008), The status of soil contamination by semivolatile organic chemicals (SVOCs) in China: A review, Science of the Total Environment 389(2-3): 209-224.

2. [2]	Geng, L.Q., Chen, Z., Chan, C.W. and Huang, G.H. (2001), An intelligent decision support system for management of petroleumcontaminated sites, Expert Systems with Applications 20(3): 251-260.

3. [3]	Liang, Y.T., Zhang, X, Wang, J and Li, G.H. (2012), Spatial variations of hydrocarbon contamination and soil properties in oil exploring fields across China, Journal of Hazardous Materials 241–242: 371-378.

4. [4]	Luo, C.L., Liu, C.P., Wang, Y., Liu, X., Li, F.B., Zhang, G. and Li, X.D. (2011), Heavy metal contamination in soils and vegetables near an e-waste processing site, south China, Journal of Hazardous Materials 186(1): 481-490.

5. [5]	Zhang, L.F., Dong, L., Shi, S.X., Zhou, L., Zhang, T. and Huang, Y.R. (2009), Organochlorine pesticides contamination in surface soils from two pesticide factories in Southeast China, Chemosphere 77(5): 628-633.

6. [6]	Scholz, R.W. and Schnabel, U. (2006), Decision making under uncertainty in case of soil remediation, Journal of Environmental Management 80(2): 132-147.

7. [7]	Turcksin, L., Bernardini, A. and Macharis, C. (2011), A combined AHP-PROMETHEE approach for selecting the most appropriate policy scenario to stimulate a clean vehicle fleet, Procedia - Social and Behavioral Sciences 20(0): 954-965.

8. [8]

   Sourdis, I., Strydis, C., Armato, A., Bouganis, C.S., Falsafi, B., Gaydadjiev, G.N., Isaza, S., Malek, A., Mariani, R., Pnevmatikatos, D., Pradhan, D.K., Rauwerda, G., Seepers, R.M., Shafik, R.A., Sunesen, K., Theodoropoulos, D., Tzilis, S. and Vavouras, M. (2013), DeSyRe: On-demand system reliability, Microprocessors and Microsystems 37(8, Part C): 981-1001.

9. [9]	Stezar, I. C., Pizzol, L., Critto, A., Ozunu, A. and Marcomini, A. (2013), Comparison of risk-based decision-support systems for brownfield site rehabilitation: DESYRE and SADA applied to a Romanian case study, Journal of Environmental Management 131: 383-393.

10. [10]	Stewart, R.N. and Purucker, S.T. (2011), An environmental decision support system for spatial assessment and selective remediation, Environmental Modelling and Software 26(6): 751-760.

11. [11]	Jiang, D., Lu, M.X., Li, F.S., Zhou, Y.Y. and Gu, Q.B. (2011), Review on Current Application of Decision Support Systems for Contaminated Site Management, Environmental Science and Technology 34(3): 170-174 (in Chinese).

12. [12]	Sorvari, J. and Seppälä, J. (2010), A decision support tool to prioritize risk management options for contaminated sites, Science of the Total Environment 408(8): 1786-1799.

13. [13]	Rodrigues, S.M., Pereira, M.E., da Silva, E. Ferreira, Hursthouse, A.S. and Duarte, A.C. (2009), A review of regulatory decisions for environmental protection: Part II—The case-study of contaminated land management in Portugal, Environment International 35(1): 214-225.

14. [14]	Li, A.J., Quan, X.C., Wang, Y., Tao, K. and Gu, L.Y. (2012), Selection of contaminated site soil remediation technology based on PROMETHEE II, Chinese Journal of Environmental Engineering 6(10): 3767-3773 (in Chinese).

15. [15]	Saaty, R.W. (1987), The analytic hierarchy process - what it is and how it is used, Mathematical Modelling 9(3–5): 161-176.

16. [16]	Saaty, T.L. (1990), How to make a decision: The analytic hierarchy process, European Journal of Operational Research 48(1): 9-26.

17. [17]	Brans, J.P., Vincke, Ph and Mareschal, B. (1986), How to select and how to rank projects: The Promethee method, European Journal of Operational Research 24(2): 228-238.

18. [18]	Macharis, C., Springael, J., De Brucker, K. and Verbeke, A. (2004), PROMETHEE and AHP: The design of operational synergies in multicriteria analysis.: Strengthening PROMETHEE with ideas of AHP, European Journal of Operational Research 153(2): 307- 317.

19. [19]	Khan, F.I., Husain, T and Hejazi, R (2004), An overview and analysis of site remediation technologies, Journal of Environmental Management 71(2): 95-122.

20. [20]	USEPA (2004), Treatment Technologies for Site Cleanup: Annual Status Report, Washington D.C., 11th Ed.

21. [21]	Gu, Q.B., Guo, G.L., Zhou, Y.Y., Yan, Z.G. and Li, F.S. (2008), Classification, application and selection of contaminated site remediation technology: An overview., Research of Environmental Sciences 21(2): 197-202 (in Chinese).

22. [22]	Peter, J.M., Walter, J.W. and Amy, F.L. (1994), Remediation Technologies Screening Matrix and Reference Guide, Roy F. Weston, Inc., West Chester, 2nd Ed.

23. [23]	Wang, Y. (2011), The Decision Support System for the Remediation of Contaminated Sites, Bachelor Thesis, Beijing Normal University (in Chinese).

24. [24]	Ma, G.J. and Garbers-Craig, A.M. (2006), A review on the characteristics, formation mechanisms and treatment processes of Cr(VI) - containing pyrometallurgical wastes, Journal of South Africa Institute of Mining and Metallurgy 106(11): 753-763.