The impact of regional convergence in energy-intensive industries on China 's CO 2 emissions and emission goals

article
In order to respond to climate change, China has committed to reduce national carbon intensity by 40-45% in 2020 and 60-65% in 2030, relative to 2005. Given that energy-intensive industries represent 80% of total CO 2 emissions in China and that China is a large and diverse country, this paper aims to investigate the potential contribution of regional convergence in energy-intensive industries to CO 2 emissions reduction and to meeting China 's emissions goals. To the best of our knowledge this matter has never been explored before. Using panel data from 2001 to 2015, we build three scenarios of future carbon intensities: business as usual (BAU), frontier (based on the directional distance function, in which all regions reach the efficiency frontier) and best available technology (BAT, in which all regions adopt the lowest-emitting technology). The frontier and BAT scenarios represent a weak and a strong form of regional convergence, respectively, and the BAU assumes that it develops following historical patterns. We then use the Kaya identity to estimate CO 2 emissions up to 2030 under the three scenarios. Our results are as follows: (1) Under BAU, the CO 2 emissions of energy-intensive industries increase from 7382.8 Mt in 2015 to 8127.6 Mt in 2030. Under the frontier scenario the emissions in 2030 are 44.23% lower than under business as usual, while under the BAT scenario this value becomes 84.81%. Electricity and ferrous metals are the sectors that most contribute to the reduction potential. (2) Even under BAU the carbon intensity of energy-intensive industries as a whole and all of its constituent sub-sectors except for electricity will decrease by more than the nationally-mandated averages. (3) Regional convergence could help the energy-intensive industries peak its CO 2 emissions before 2030, while under BAU the absolute emissions of the energy-intensive industries keep increasing. A© 2019 The Author(s)
TNO Identifier
862370
ISSN
01409883
Source
Energy Economics, 80, pp. 512-523.
Pages
512-523