Authors: Yannan Zhou*, Institute of Geographic Sciences and Natural Research, CAS, Yu Yang, Institute of Geographic Sciences and Natural Research, CAS
Topics: China, Energy, Environment
Keywords: carbon dioxide intensity, spatial dependence, spatial auto-regressive models, direct effect, indirect effect
Session Type: Poster
Start / End Time: 1:10 PM / 2:50 PM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: Download
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-targeted 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. However, they are more direct and contained affecting residents within the region for the Middle Yangtze River, South, North and East Coasts.