China's carbon dioxide emission and driving factors: A spatial analysis. (20th February 2019)

• Record Type: Journal Article
• Authors: Yang, Yu; Zhou, Yannan; Poon, Jessie; He, Ze
• Is Part Of: Journal of cleaner production. Volume 211(2019)
• Page Start: 640
• Page End: 651
• Publication Date: 2019-02-20
• Subjects: Carbon dioxide intensity -- Spatial dependence -- Spatial autoregressive models -- Direct effect -- Indirect effect; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2018.11.185
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: A burgeoning literature is emerging on China's high levels of carbon dioxide (CO2 ) emission. Yet policies remain elusive in part because of conflictual empirical findings and insufficient attention to China's complex spatial terrain. This paper conducts a spatial analysis of China's CO2 intensity (CEI) based on six major drivers, and shows that region-targetted strategies may be more effective in tackling CEI. Specifically, results from spatial autoregressive models indicate that drivers vary significantly across regions: changing the energy production mix through alternative sources of energy is likely to have a stronger effect on the Northwest and Middle Yangtze River but it is less effective for the South and East Coasts. Changes in population, urbanization, industrial structure and technology are more likely to lead to CEI reduction for South and East Coasts. Moreover at the regional level, spatial effects are more indirect and widespread spilling over to neighboring regions for the Middle Yellow River and Northeast. But they are more direct and contained affecting residents within the region for the Middle Yangtze River, South, North and East Coasts. Highlights: A spatial analysis of CO2 intensity based on six major drivers is conducted. Region-targeted strategies are more effective in tackling CO2 intensity. Driving factors vary significantly across regions. Spatial econometrics show both positive and negative spatial dependence effects.