Spatio-temporal evolution and influencing factors of aggregate carbon intensity of electricity generation in China's cities
The power sector is a critical industry in China's efforts to attain its carbon peaking and carbon neutrality targets.Analyzing the spatio-temporal pattern and influencing factors of the aggregate carbon intensity(ACI)of electricity generation at the city scale is of great significance for refining electricity emission reduction policies and guiding regional collaborative carbon reduction.This study utilizes micro-level data from 21543 power plants with a capacity of 6000 kW or above,in combination with multiple sources of statistical data related to energy,economy,and society,to calculate ACI of electricity generation in China's cities in 2003,2010,and 2017.Exploratory spatial data analysis,IDA-LMDI decomposition,and STIRPAT modeling are employed to reveal the spatio-temporal patterns and influencing factors.The findings show that:(1)From 2003 to 2017,the ACI of China's electricity generation sector exhibited a notable decline,albeit with a trend of increasing internal differences.Significant spatial differentiation was observed at city scale,with the northeast half of the Bole-Taipei Line maintaining higher levels than the southwest half over an extended period.The degree of spatial agglomeration also increased significantly during this period,with Northeast and North China identified as regions of particular concern in the decline of ACI.(2)The thermal efficiency was the dominant factor in the decline of ACI in the early stage,whereas the electricity generation structure became increasingly influential in the later period.Meanwhile,other power system factors exhibited less influence,though significant spatial differences were observed.(3)The impact of diverse socio-economic determinants on ACI fluctuated over time,engendering modifications in the attributes of the power system through their interactions with the intricate network of power demand,policy,technology,and clean energy expansion opportunities.(4)An inverted U-shaped correlation was observed between ACI and per capita GDP in 2003 and 2010,which transformed into a linear positive association in 2017.This shift can be attributed to the swift emergence of renewable electricity that have challenged the traditional interpretive framework of the Environmental Kuznets Curve hypothesis,which was previously applicable only to thermal power generation.In the future,endeavors aimed at reducing emissions in the electricity sector must comprehensively acknowledge the spatial heterogeneity and sustain attention towards the ramifications of abrupt shifts arising from emerging technologies on the conventional theoretical framework.
NETL
NSTL
万方数据
