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Articles

Incentive equilibrium strategies of transboundary industrial pollution control under emission permit trading

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Pages 107-134 | Received 03 Jul 2018, Accepted 11 Mar 2019, Published online: 09 Apr 2019
 

Abstract

In this paper, we investigate the incentive equilibrium strategies of two neighboring regions facing transboundary industrial pollution under abatement investment and emission permits trading in a differential game setting. Our paper can be viewed as an extension of the work of Yeung [2007. Dynamically consistent cooperative solution in a differential game of transboundary industrial pollution. Journal of Optimization Theory and Applications, 134, 143–160] in the context of the transboundary industrial pollution. Compared with the work of Yeung [2007. Dynamically consistent cooperative solution in a differential game of transboundary industrial pollution. Journal of Optimization Theory and Applications, 134, 143–160], our research significant features (i) introduce the emission permits trading into the transboundary industrial pollution control;(ii) take into account the pollution abatement investment; (iii) examine the incentive equilibrium strategies of transboundary industrial pollution control; and (iv) design an allocation mechanism for regions’ cooperative profits. Furthermore, we illustrate the results of the paper with a numerical example. The utility of this paper is how to make incentive equilibrium strategies in a situation where the neighboring regions facing transboundary industrial pollution under abatement investment and emission permits trading in a differential game setting.

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Acknowledgements

The authors thank the editor and the anonymous referee for their careful reading and their valuable comments on the first version of this paper. Any remaining errors are our responsibility.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by the National Natural Science Foundation of China [grant number 71373263] and [grant number 71673275].

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