With fast development, it is not easy for China to achieve carbon reduction targets only by traditional command and control measures (e.g., the measures for energy-efficiency). Carbon tax is advocated as one effective complementary measure and has high possibility to be implemented for China’s future low carbon development. Under such a circumstance, this paper aims at forecasting the possible impact of carbon tax on both carbon reduction and economic loss of 30 Chinese provinces. A 30-Chinese-province CGE (Computational general equilibrium) model has been developed to conduct the provincial evaluation, and seven scenarios including Business-as-Usual (BaU) scenario and six carbon tax scenarios with carbon price from 20 USD/ton to 120 USD/ton up to 2030 are set. The results show that China’s industrial CO₂ will be reduced from 12.2 billion tons under BaU scenario to 10.4 billion tons, 9.3 billion tons, 8.5 billion tons, 7.9 billion tons, 7.4 billion tons and 7.0 billion tons under scenarios of TAX20, TAX40, TAX60, TAX80, TAX100 and TAX120 in 2030, respectively. Electricity, Metal and Chemicals sectors have high reduction potentials and are priority sectors for carbon tax policy. Provincial disparity analysis demonstrates that coal production/consumption and total energy consumption are key factors to affect carbon tax effect on CO₂ reduction, and Inner Mongolia, Shandong, Shanxi and Hebei have the largest industrial CO₂ reduction potentials after levying carbon tax. However, the implementation of carbon tax will impede economic development for all provinces. Therefore, the concept of carbon tax efficiency is further proposed in order to evaluate the effectiveness of carbon tax by considering both CO₂ reduction and GDP loss. Policy suggestions indicate that provinces of Shanxi, Inner Mongolia, Hebei and Anhui should be set priority when implementing carbon tax policy in China, and carbon price should be no more than 50 USD/ton.

Exploring impact of carbon tax on China’s CO 2 reductions and provincial disparities.pdf