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Mathematical Problems in Engineering
Volume 2014, Article ID 462705, 8 pages
http://dx.doi.org/10.1155/2014/462705
Research Article

Allocating Tradable Emissions Permits Based on the Proportional Allocation Concept to Achieve a Low-Carbon Economy

1School of Business, University of Science and Technology of China, Hefei, Anhui 230026, China
2Department of Electronics and Information, Toyota Technological Institute, Nagoya 468-8511, Japan
3Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

Received 17 December 2013; Accepted 19 March 2014; Published 16 April 2014

Academic Editor: Xiaodong Lin

Copyright © 2014 Qianzhi Dai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A key issue within the emissions trading system is how tradable emissions permits (TEPs) are initially allocated among a set of entities. This study proposes an approach based on the proportional allocation concept to allocate TEPs among a set of decision making units (DMUs). We firstly deduce a TEP allocation set based on the rule that the TEPs allocated to DMUs should be proportional to their environmental contribution. We then obtain the allocation intervals of DMUs from the set, expressing the allocation as the convex combination between the upper and the lower bound. Finally, we define the satisfaction degree as the coefficient of the convex combination, and propose an algorithm based on the max-min fairness of satisfaction degrees to obtain a unique TEP allocation plan. To illustrate our approach, we provide the example of how TEPs are allocated among 30 provincial administrative regions in China. Our findings indicate that our allocation method can be helpful for achieving a saving in energy consumption and reducing emissions. In addition, from the data envelopment analysis perspective, the TEP allocation set can ensure that both each individual DMU and the organization as a whole become efficient under a common set of variable weights.