机构地区:[1]湖南科技大学建筑与城乡规划学院,湘潭411201 [2]湖南科技大学生命科学学院,湘潭411201
出 处:《生态学报》2017年第7期2476-2487,共12页Acta Ecologica Sinica
基 金:教育部人文社科项目(14YJAZH050);湖南省社会科学基金项目(14YBA170)
摘 要:研究碳排放时空格局演变及其影响因素对指导碳减排具有重要意义。利用2008—2013年湖南省14地市规模以上工业企业终端能源消费数据,运用IPCC提供的参考方法和对数平均迪氏指标分解模型(Logarithmic Mean Divisia Index,LMDI)对湖南市域碳排放量、人均碳排放量、碳排放强度的时空格局及碳排放量变化的影响因素进行了研究。结果表明:1)2008—2013年湖南市域碳排放量随时间变化趋势不一,大致呈3种类型变化;累积碳排放量居前3位的市域依次是娄底、岳阳和湘潭,三者累积碳排放量占全省同期的48.92%,而吉首、张家界和怀化3市的累积碳排放量合计仅占全省的2.59%。2)湖南市域能源消费碳排放量、人均碳排放量存在相似的空间差异,二者均表现为东高西低的格局,且具有较强的相关性,碳排放量高的市域,人均碳排放量也较高;2008—2013年湖南市域碳排放强度呈下降趋势,属于低强度区的市域由2008年的4个增加到2013年的7个,碳排放强度的空间分布与市域产业类型有关。3)能源结构、能源强度对碳排放的增长主要起抑制作用,但能源结构的贡献很小,碳排放量的降低主要是由能源强度引起的;经济发展是碳排放增长的最主要因素,在2008—2010年和2011—2013年两个时段其累积贡献值分别为74.285和27.579;人口规模对碳排放的驱动较小,在2011—2013年对碳排放增加产生的累积贡献值仅为2.252。湖南当前及未来碳减排的重点是加快发展清洁能源与提高能效并重,优化能源结构和促进产业结构升级,从战略层面促进湖南"四大区域"协调发展。To reduce carbon emission, there is a need to explore the spatio-temporal evolution patterns of carbon emissions and the factors that influence this process. The terminal energy consumption data of industrial enterprises above a designated size in 14 cities in Hunan Province, China, from 2008 to 2013, were used to study the temporal-spatial patterns and the factors influencing carbon emissions, per capita carbon emissions, and carbon emission intensity at the city scale in Hunan Province. These factors were analyzed using the reference approach provided by the IPCC and the Logarithmic Mean Divisia Index (LMDI). The results showed that 1) from 2008 to 2013, different cities had different carbon emission growth trends, which could be classified into three categories. The top three cities for cumulative carbon emissions were Loudi, Yueyang, and Xiangtan, and their total cumulative carbon emissions accounted for 48.92% of the province's total carbon emissions over the study period. In contrast, the total cumulative carbon emissions from Jishou, Zhangjiajie, and Huaihua accounted for only 2.59%. 2) The city-level carbon emissions and per capita carbon emissions in the eastern cities were higher than those in the western cities of Hunan Province. Furthermore, carbon emissions and per capita emissions were strongly correlated. The cities with high carbon emissions had higher per capita carbon emissions. However, carbon emission intensities from each city in Hunan Province decreased over the period, and the number of cities classified as being in a low-carbon-emission intensity region increased from four in 2008 to seven in 2013. The spatial distribution of carbon emission intensity was related to the type of industry in the city. 3) The energy structure and energy intensity factors could reduce carbon emission growth, but the energy structure contribution was very small and the reduction in carbon emissions was mainly caused by energy intensity. Economic development had the strongest positive impact on carbo
分 类 号:F426.2[经济管理—产业经济] X24[环境科学与工程—环境科学]
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