Spatiotemporal Characteristics, Determinants and Scenario Analysis of CO2 Emissions in China Using Provincial Panel Data
文献类型：SCI/SSCI论文
| 作者 | Wang S. J.; Fang, C. L.; Li, G. D. |
| 发表日期 | 2015 |
| 关键词 | carbon-dioxide emissions greenhouse-gas emissions unit-root tests energy-consumption economic-growth decomposition analysis impact factors stirpat model cointegration analysis relative importance |
| 英文摘要 | This paper empirically investigated the spatiotemporal variations, influencing factors and future emission trends of China's CO2 emissions based on a provincial panel data set. A series of panel econometric models were used taking the period 1995-2011 into consideration. The results indicated that CO2 emissions in China increased over time, and were characterized by noticeable regional discrepancies; in addition, CO2 emissions also exhibited properties of spatial dependence and convergence. Factors such as population scale, economic level and urbanization level exerted a positive influence on CO2 emissions. Conversely, energy intensity was identified as having a negative influence on CO2 emissions. In addition, the significance of the relationship between CO2 emissions and the four variables varied across the provinces based on their scale of economic development. Scenario simulations further showed that the scenario of middle economic growth, middle population increase, low urbanization growth, and high technology improvement (here referred to as Scenario BTU), constitutes the best development model for China to realize the future sustainable development. Based on these empirical findings, we also provide a number of policy recommendations with respect to the future mitigation of CO2 emissions. |
| 出处 | Plos One |
| 卷 | 10 |
| 期 | 9 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 1932-6203 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/38934]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Wang S. J.,Fang, C. L.,Li, G. D.. Spatiotemporal Characteristics, Determinants and Scenario Analysis of CO2 Emissions in China Using Provincial Panel Data. 2015. |
入库方式： OAI收割
来源：地理科学与资源研究所
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