School of Architecture and Urban Planning, Guangdong University of Technology, Guangzhou 510090, China; Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518034, China.
School of Architecture and Urban Planning, Guangdong University of Technology, Guangzhou 510090, China.
Sci Total Environ. 2022 Apr 20;818:151690. doi: 10.1016/j.scitotenv.2021.151690. Epub 2021 Nov 16.
Carbon intensity (CI) is a valuable indicator of the balances struck by the world's governments between economic growth and environmental issues. This study investigates spatiotemporal variations in the CI levels related to energy consumption, as well as the spatial heterogeneity of its driving forces, in 208 countries globally during 2000-2018. To do this, we obtained data from the International Energy Agency (IEA) and the World Bank, employing methods of exploratory spatial data analysis (ESDA) and standard deviation ellipse (SDE) in order to analyze CI's spatiotemporal variations. We also performed a geographically weighted regression (GWR) analysis to determine the spatial heterogeneity of CI and the strength of its influencing factors. Our results reveal that: (1) Carbon emissions from energy consumption increased, while CI decreased globally, with the CI of most countries and regions declining significantly. (2) Global CI evidenced a heterogeneous spatial distribution, with higher-value areas concentrated in Asia and lower-value areas in Africa and Western Europe; obvious spatial agglomeration was also presented, especially with respect to High-High and Low-Low agglomerations, and the gravity center point moved from the northeast to the southwest. (3) The 8 influencing factors investigated in this study all had effective explanatory power in relation to CI globally. These factors showed significant spatial heterogeneity, and energy structure was the only factor to have a fully positive influence on CI, while foreign direct investment, foreign trade openness, industrial structure, total population, and energy intensity, mainly exerted a positive influence, and the urbanization rate and GDP per capita exerted a negative influence. By clarifying the spatiotemporal variations characteristics of global CI and the spatial heterogeneity of its influencing factors, this study provides a targeted reference for reducing CI and promoting sustainable development, globally.
碳强度(CI)是衡量世界各国政府在经济增长与环境问题之间取得平衡的重要指标。本研究调查了 2000-2018 年间全球 208 个国家与能源消费相关的 CI 水平的时空变化,以及其驱动因素的空间异质性。为此,我们从国际能源署(IEA)和世界银行获取数据,采用探索性空间数据分析(ESDA)和标准差椭圆(SDE)方法,分析 CI 的时空变化。我们还进行了地理加权回归(GWR)分析,以确定 CI 的空间异质性及其影响因素的强度。结果表明:(1)全球能源消费的碳排放量增加,而 CI 则下降,大多数国家和地区的 CI 显著下降。(2)全球 CI 表现出异质的空间分布,高值区集中在亚洲,低值区集中在非洲和西欧;还呈现出明显的空间集聚,特别是在高-高和低-低集聚方面,重心从东北向西南移动。(3)本研究调查的 8 个影响因素对全球 CI 均具有有效的解释力。这些因素表现出显著的空间异质性,其中能源结构对 CI 具有完全正向影响,而外国直接投资、对外贸易开放度、产业结构、总人口和能源强度主要产生正向影响,城市化率和人均 GDP 则产生负向影响。本研究阐明了全球 CI 的时空变化特征及其影响因素的空间异质性,为全球降低 CI 和促进可持续发展提供了有针对性的参考。