Name
Abstract | ||
|---|---|---|
Based on the STIRPAT model and spatial autoregressive models, this paper investigates the energy-related CO2 emissions of 30 provinces in China from 2000 to 2006 and the underlying driving forces. The result shows that there exists spatial interdependence of the provincial CO2 emission, and the energy intensity, population growth and economic development level are the main contributors to CO2 emissions, while urbanization is not an inevitable factor. We also find that the provincial CO2 emissions show the pattern of spatial dependence and spatial heterogeneity at the same time, which means that we must take into account the spatial interaction mechanism when adopt the proactive policies and measures regarding environmental protection and energy consumption. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CSO.2009.147 | CSO (2) |
Keywords | Field | DocType |
co2,economic development level,carbon compounds,co2 emission,energy-related carbon dioxide emission,stirpat model,energy intensity,air pollution,spatial dependence,china,spatial autoregressive models,ad 2000 to 2006,provincial carbon dioxide emissions,environmental protection,spatial econometric analysis,spatial interaction mechanism,spatial autoregressive model,spatial interdependence,environmental management,emission contributors,energy consumption,atmospheric composition,population growth,atmospheric boundary layer,spatial heterogeneity,driving forces,provincial co2 emissions,time series analysis,spatial econometrics,technology management,petroleum,time measurement,pattern analysis,economic development,econometrics,environmental economics,carbon dioxide | Autoregressive model,Urbanization,Spatial dependence,Mathematical optimization,Energy intensity,Computer science,Population growth,Economic geography,China,Economy,Spatial heterogeneity,Energy consumption | Conference |
Volume | ISBN | Citations |
2 | 978-0-7695-3605-7 | 0 |
PageRank | References | Authors |
0.34 | 1 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junjie Ma | 1 | 148 | 15.24 |
| Xia Liu | 2 | 0 | 0.34 |
| Jianxin You | 3 | 107 | 5.06 |
| Maolin Zhang | 4 | 0 | 1.69 |