4.7 Article

Sectoral convergence analysis of China?s emissions intensity and its implications

Journal

ENERGY
Volume 262, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2022.125516

Keywords

Emission intensity; Convergence; Sectoral analysis; Scenario analysis; Bayesian hierarchical model

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This study examines the convergence of emission intensities in six major sectors among China's provinces and projects the impact of convergence on future CO2 emissions. The findings suggest that there is convergence in emission intensity across sectors, particularly in the industrial sector of underdeveloped provinces. Scenario analysis shows that promoting convergence can significantly reduce CO2 emissions.
China has committed to reduce emission intensity (CO2 emissions per unit of GDP) by 60-65% in 2030 compared to the level of 2005. Because the convergence of emission intensity is one of the important signs of a decline in emission intensity, we examined the beta-convergence and club convergence of emission intensities among China's 30 provinces for six major sectors from 1997 to 2018. In addition, to project the impacts of convergence on future CO2 emissions, we developed three scenarios (baseline scenario, club convergence scenario and the best convergence scenario) with the Bayesian hierarchical models. We find that six major sectors all show the absolute and conditional beta-convergence and support the existence of club convergence. The scenario analysis suggests that the club convergence and the best convergence scenarios can reduce 44.1% and 69.8% CO2 emissions in 2050 compared with the level of baseline scenario, respectively. These emission reductions are mainly from Industry of undeveloped provinces. The emission intensity convergence of Industry in Liaoning, Hebei and Shandong will account for more than 90% of the total emissions impact of regional convergence in the best convergence scenario.

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