An Interval-Fuzzy Emissions Reduction Optimization Model for Regional Water Pollutant Total Amount Control

Article Preview

Abstract:

Combining environment policies of structure emissions reduction, engineering emissions reduction and management emissions reduction, this paper uses an interval-fuzzy linear programming and builds an optimization model for total amount control of regional water pollution, on account of severe water pollution condition. The developed model is applied to a case of Hunan Province to validate its validity and reliability. The optimal result demonstrated that the emission reduction of COD and NH3-N are [43.39, 47.57] and [7.05, 7.64] (104 tons), and the optimal total costs of reduction is [35.11, 37.35] (billion yuan), which decreases 6.32~11.20% than the existed recommended scheme (39.87 billion yuan). This method can be used for providing technical support and thus achieves the 12th Five-year goals of the environment protection plan more effectively.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

497-500

Citation:

Online since:

April 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] C.F. Yang, Perfect environmental policy system and control environmental pollution situation, China Environmental Protection Industry. 2 (2011) 19-22.

Google Scholar

[2] Z.G. Liu, J.C. Shang, J.X. Jiang, Study on the total control models of regional environment, Journal of Northeast Normal Un. 2 (1997) 116-121.

Google Scholar

[3] J.N. Wang, R.S. Tian, S.Z. Wu, Z.F. Dong, A road map of the pollutants emission total amount control for china in the 12th five year period, China Population Resources and Environment. 20 (2010) 70-74.

Google Scholar

[4] Y. Li, Z. Li, Z. Sun, J.Y. Wen, Application of interval optimization model for total amount control and emissions trading of regional pollutants: 2012 The 2nd International Conference on Remote Sensing, Environment and Transportation Engineering (IEEE Press, NY, 2012).

DOI: 10.1109/rsete.2012.6260406

Google Scholar

[5] G.H. Huang, B.W. Baetz, G.G. Patry, Grey fuzzy integer programming: an application to regional waste management planning under uncertainty, SEPS. 29 (1995) 17-38.

DOI: 10.1016/0038-0121(95)98604-t

Google Scholar

[6] N.B. Chang, Y.L. Chen, S.F. Wang, A fuzzy interval multiobjective mixed integer programming approach for the optimal planning of solid waste management systems, Fuzzy Set Syst. 89 (1997) 35-59.

DOI: 10.1016/s0165-0114(96)00086-3

Google Scholar

[7] Heinrich Rommelfanger, Fuzzy linear programming and applications, Eur J Oper Res. 92 (1996) 512-527.

Google Scholar

[8] J.Y. Wen, Y. Hu, Z. Sun, Z. Li and Y. Li: The 2nd/2012 International Conference on Energy, Environment and Sustainable Development, Jilin, China, (2012), in press.

Google Scholar

[9] Information on http://www.mep.gov.cn

Google Scholar