Sectoral convergence analysis of China's emissions intensity and its implications. (1st January 2023)
- Record Type:
- Journal Article
- Title:
- Sectoral convergence analysis of China's emissions intensity and its implications. (1st January 2023)
- Main Title:
- Sectoral convergence analysis of China's emissions intensity and its implications
- Authors:
- Zheng, Shenglin
Yuan, Rong - Abstract:
- Abstract: 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 β -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 β -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. Highlights: We examine the sectoral convergence of emission intensities in China. We develop three scenarios to project the impact of convergence on emissions. China's six sectors all show the regional convergence in the emissions intensity. The convergence scenario canAbstract: 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 β -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 β -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. Highlights: We examine the sectoral convergence of emission intensities in China. We develop three scenarios to project the impact of convergence on emissions. China's six sectors all show the regional convergence in the emissions intensity. The convergence scenario can reduce more than 44.1% emissions in 2050. The emission reductions are mainly from Industry of undeveloped provinces. … (more)
- Is Part Of:
- Energy. Volume 262:Part B(2023)
- Journal:
- Energy
- Issue:
- Volume 262:Part B(2023)
- Issue Display:
- Volume 262, Issue B (2023)
- Year:
- 2023
- Volume:
- 262
- Issue:
- B
- Issue Sort Value:
- 2023-0262-NaN-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-01-01
- Subjects:
- Emission intensity -- Convergence -- Sectoral analysis -- Scenario analysis -- Bayesian hierarchical model
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2022.125516 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
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