中文关键词
碳排放县级尺度时空格局空间自相关重庆市 | 英文关键词CO2 emissionscounty levelspatiotemporal dynamicsspatial autocorrelationChongqing |
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| 中文摘要 |
| 碳排放具有明显的时间和空间分布特征，研究区域碳排放时空格局动态特征可为制定合理的碳减排政策和措施提供重要的依据.本文以重庆为例，基于其38个区县的碳排放数据，利用空间统计、空间自相关和位序-规模法则探讨了其县级尺度碳排放的区域差异和空间格局演变特征.结果表明，重庆市各区县都经历了快速的碳排放增长过程，但碳排放的二元空间分布结构并没有改变；重庆市县级尺度碳排放全局Moran's I指数呈现出波浪式的降低趋势，主城区区县在中心相互辐射，形成一个碳排放HH中心；位序-规模法则分析结果则表明重庆市县级尺度碳排放基本属于首位型分布，1997~2012年区县碳排放规模分布趋于分散的力量均大于趋于集中的力量；1997和2012年，第二产业比例和城市化率成为影响重庆市碳排放的最重要的因素，人口与碳排放的相关关系却并不显著. |
| 英文摘要 |
| China's CO2 emissions present obvious temporal and spatial distribution characteristics. Therefore, the study of spatiotemporal dynamics of CO2 emissions could provide useful information for the government and policy-makers on viable CO2 emissions mitigation in China. Using Chongqing as a case study, we investigated the spatiotemporal dynamics of CO2 emissions at the county level (38 counties) from 1997 to 2012.The mathematical statistical method, spatial autocorrelation, and rank size rule were employed to evaluate the CO2 emissions change in detail. The results showed that all of the counties in Chongqing have experienced a rapid growth of CO2 emissions, but the two dimensional structure of CO2 emissions has not changed. The Global Moran's I clearly decreases with a small fluctuation, and these values gradually decrease from 0.56 in 1997 to 0.40 in 2012.In addition, the HH clusters are concentrated in some counties in the downtown areas. Based on the rank size rule analysis, the slope values q decrease from -1.35 in 1997 to -0.88 in 2012, indicating a clear scattered pattern of CO2 emissions in Chongqing at the county level. It has also been proven that the proportion of second industries and the urbanization rate are more important impact factors for CO2 emissions than the population. |
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https://www.hjkx.ac.cn/hjkx/ch/reader/create_pdf.aspx?file_no=20180654&flag=1&journal_id=hjkx&year_id=2018