Allocating CO2 allowances to emitters in China: A multi-objective decision approach. (October 2018)

• Record Type: Journal Article
• Authors: Zhu, Bangzhu; Jiang, Mingxing; He, Kaijian; Chevallier, Julien; Xie, Rui
• Is Part Of: Energy policy. Volume 121(2018)
• Page Start: 441
• Page End: 451
• Publication Date: 2018-10
• Subjects: Q57 -- N55 -- 044; China CO2 allowance allocation -- Major industries -- Multi-objective decision analysis -- Fairness -- Efficiency -- Feasibility; Energy policy -- Periodicals; Politique énergétique -- Périodiques; Electronic journals; 333.79
• DOI: 10.1016/j.enpol.2018.07.002
• Languages: English
• ISSNs: 0301-4215

Abstract

Abstract: China CO2 allowance (CHA) allocation for emitters is one of the pivotal issues to build the effective national carbon market. In this study, we propose a multi-objective decision approach, incorporating the principles of fairness, efficiency, and feasibility, to allocate the CHAs to emitters from the industry perspective. Taking Guangdong, China as an example, we employ the proposed approach for allocating the CHAs to six major industries of petrochemical, chemical, cement, steel, nonferrous metals, and electricity power by 2030. The empirical results show that there are significant conflicts between principles. The proposed approach can not only effectively eliminate the defects of single-object models to make the allocation results more reasonable and acceptable, but also achieve optimal allocation options under various decision preferences. The power industry has the highest CHA and petrochemical industry has the lowest one, and petrochemical, chemical, and steel industries have the greatest potential to reduce carbon intensity. Single-factor sensitivity analysis shows that the CHA/10 4 Yuan added value (TY) of the industry with lower emissions is more sensitive to the changes of physical capital stock but received fewer impacts from the changes of emissions cap for six industries. Highlights: Allocation criteria in the Chinese ETS. Efficiency vs. fairness vs. feasibility principles. Multi-objective decision approach. Case-study of the Guangdong province.