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采用西安市1997—2011年工业能耗数据和2010年各区县单位GDP能耗数据进行了碳排放量的估算,通过STIRPAT模型构建驱动因子分析模型。研究表明:(1)西安市1997—2011年各类碳排放量表现出总体上升的特征。(2)各区县碳排放量、碳排放产值、人均碳排放量、地均碳排放量呈现出明显的空间分异现象。Moran指数显示,西安市各区县碳排放量存在显著地空间正相关性。碳排放量的空间分布特征是:碳排放量较高的区县趋向于和碳排放量较高的区县集聚,碳排放量较低的区县趋向于和碳排放量较低的区县集聚。(3)STIRPAT模型表明:经济发展、人口规模、产业结构和技术水平对碳排放量影响程度不同,其中经济发展对碳排放量增加具有决定作用,产业结构优化对碳排放量增加具有抑制作用。
The carbon emissions were estimated by using industrial energy consumption data from 1997 to 2011 in Xi’an and energy consumption per unit GDP of all districts and counties in 2010, and a driving factor analysis model was constructed through STIRPAT model. The research shows that: (1) All kinds of carbon emissions in Xi’an from 1997 to 2011 show an overall increase. (2) The carbon emissions, the output value of carbon emissions, the per capita carbon emissions and the carbon emissions per capita in all districts show obvious spatial differentiation. The Moran index shows that there is a significant spatial positive correlation between carbon emissions in all districts and counties in Xi’an. The spatial distribution of carbon emissions is characterized by the fact that counties with higher carbon emissions tend to gather with counties with higher carbon emissions and that counties with lower carbon emissions tend to gather with districts with lower carbon emissions . (3) The STIRPAT model shows that economic development, population size, industrial structure and technology have different impacts on carbon emissions. Economic development plays a decisive role in increasing carbon emissions, and industrial structure optimization has an inhibitory effect on carbon emissions.