Allocation of carbon dioxide emission permits with the minimum cost for Chinese provinces in big data environment

Abstract

The environmental problem and global warming have drawn many governments’ attention. In order to solve the problem, reasonable allocation of carbon dioxide emission (CDE) permits is an important issue because it sets the targets for the decision making units to control the amount of carbon dioxide emission. In this paper, a new data envelopment analysis approach is proposed to evaluate the efficiency of decision making units in a big data environment and set the carbon dioxide emission permits for each decision making unit with the minimum costs. Comparing with the previous works on carbon dioxide emission permits allocation, we firstly allocate the amount of carbon dioxide emission permits taking account into the cost each decision making unit should take to achieve its target. Moreover, two kinds of linear programming problems are developed under efficiency invariance principle and efficiency changeability principle respectively. As the allocation of carbon dioxide emission permits causes the minimum cost, the decision making units are more easily to accept the allocation alternative. Finally, our approach is applied to the carbon dioxide emission permits allocation among Chinese provinces. The results show that the approach can well allocate the CDE permits with the minimum cost, and also reveal the relationship between the marginal cost of reducing CDE permits and the adjustment on them.