中国省际不同土地利用类型电力碳足迹的时空分析OACSTPCD
Electricity carbon footprint of different land use types in China
利用土地利用类型与能源消费项目的对应关系,对 2003-2020年中国省际不同土地利用方式的电力碳排放、电力碳足迹、电力碳赤字进行计算与时空分析,并借助空间自相关模型分析电力碳赤字的空间关联特征.结果表明:全国电力碳排放量增长速率持续放缓,空间上呈现东高西低、南高北低的特征.电力碳足迹增速表现为先急后缓的降低态势,且各土地利用类型的电力碳足迹增长为收敛趋势;电力碳足迹重心逐渐由东南向西北扩散转移,北方地区内部差异相较于南方持续扩大.电力碳赤字范围持续扩大,其空间关联性为逐渐强化的正相关,低—低集聚区(LL)和高—高集聚区(HH)是主要局部空间自相关类型.随空间相互作用增强,电力碳赤字区际差距缩小.
The spatial-temporal differentiation of electricity carbon emission and the carbon footprint,along with the spatial agglomeration characteristics of the carbon deficit in electricity consumption,can be measured based on the correlation between land use types and energy consumption.This measurement,using data on electricity consumption and land from 2003 to 2020,is a valuable reference for formulating reasonable and differential emission reduction policies.It can help achieve carbon neutrality and peaking carbon goals.The results indicate that the growth rate of national electricity carbon emissions is continuing to slow down,showing spatial patterns of high east and low west,high south and low north.The growth rate of the carbon footprint is characterized by a rapid initial reduction,followed by a slower rate of reduction.Additionally,the carbon footprint of electricity by land use type shows a trend towards convergence.The center of gravity of the carbon footprint is gradually shifting from southeast to northwest,and the northern internal differences have been increasing compared to the south.The scope of the carbon deficit in electricity consumption is continuing to expand.As spatial interactions have increased,the positive correlation between spatial correlation has been strengthened,and the inter-regional gap in the carbon deficit in electricity consumption is narrowing.The main local spatial auto-correlation types are low-low and high-high agglomeration areas.
许淑婷;殷海萍
辽宁师范大学地理科学学院,大连 116029
环境科学
电力碳足迹土地利用类型碳排放空间集聚
electricitycarbon footprintland use typescarbon emissionspatial agglomeration
《环境保护科学》 2024 (001)
59-66 / 8
国家自然科学基金项目(41771132);辽宁省哲学社会科学青年人才培养对象委托课题(2022lslqnrcwtkt-38)
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