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北方农牧交错区碳排放时空演变及减排路径

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农牧交错区在我国能源供给和生态格局中具有重要的战略地位,探究其碳排放时空变化特征有助于深入了解我国能源生产基地的历史碳排放信息,为推动区域节能降碳和制定差异化的减排政策提供数据参考,对实现低碳经济发展具有重要意义。基于土地利用、夜间灯光及省级能源消费碳排放数据构建碳排放空间化模型,运用全局莫兰指数(Moran's Ⅰ)和热点分析探究北方农牧交错区1995~2020年碳排放时空变化及聚集特征,并结合2010~2020年各城市的碳排放效率和减排潜力指数对城市分类后提出差异化的减排路径。结果表明:①多源数据构建的碳排放空间化模型在市级尺度的估算结果线性拟合R2可达0。92。②农牧交错区的碳排放总量从1995年的17 629。13万t增加到了 2020年的101 450。8万t;但碳排放强度和增长速度均有所降低,与能源结构调整和能源效率提升有关。在空间分布上,高碳排放城市随时间变化依次为大同、包头和榆林。③研究区碳排放在县域尺度上呈现显著的全局空间正相关,热点区主要分布在晋陕蒙交界处,冷点区在2010年后由延安扩展到了庆阳和固原。④各城市基于碳排放效率和减排潜力指数的差异,可划分为:"高效率高潜力型"、"低效率高潜力型"、"高效率低潜力型"和"低效率低潜力型"这4类来实施有针对性的减排策略。
Spatio-temporal Evolution of Carbon Emissions and Emission Reduction Paths in the Northern Farming-pastoral Ecotone
The farming-pastoral ecotone has an important strategic place in the energy supply and ecological layout of China.Thus,exploring the spatial and temporal variation characteristics of carbon emissions in this region will help to deeply understand the information on the historical carbon emissions in China's energy production bases and provide data references for the formulation of differentiated emission reduction policies and the promotion of regional energy-saving and carbon-reducing measures,which is of great significance for the realization of low-carbon economic development.This study constructed a spatialization model of carbon emissions based on land use,night lighting,and provincial energy consumption data;explored the spatiotemporal changes and aggregation characteristics of carbon emissions in the farming-pastoral ecotone from 1995 to 2020 using the global Moran's index and hotspot analysis;and then combined it with the slack-based measure model to calculate the carbon emission efficiency and emission reduction potential of each city from 2010 to 2020 and classify cities to propose a differentiated emission reduction path.The results showed that,firstly,the estimated results at the prefectural city level of the carbon emission spatialization model constructed in this study with multi-source data could reach an R2 of 0.92 for a linear fit.Secondly,the total carbon emissions in the farming-pastoral ecotone increased from 176.29 million tons in 1995 to 1 014.51 million tons in 2020.However,the carbon emission intensity and growth rate both decreased,which was related to adjusting the energy structure and improving energy efficiency.Regarding spatial distribution,the cities with high carbon emissions over time were Datong,Baotou,and Yulin in order.Thirdly,the carbon emissions in the study area showed a significant global spatial positive correlation at the county level,with the hot spots mainly located at the junction of Shanxi,Shaanxi,and Inner Mongolia,while the cold spots were extended from Yanan City to Qingyang and Guyuan City after 2010.Finally,based on the differences in carbon emission efficiency and reduction potential,cities could be classified into four types:"high-efficiency and high potential,""low-efficiency and high potential,""high-efficiency and low potential,"and"low-efficiency and low potential"to implement targeted emission reduction strategies.

carbon emissionsspatiotemporal variationsthe farming-pastoral ecotonenighttime light dataemission reduction potential

孙景妍、罗佳琪、杜国红、郭晋伟、汤媛媛、齐雁冰

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西北农林科技大学资源环境学院,杨凌 712100

碳排放 时空分布变化 农牧交错区 夜间灯光遥感 减排潜力

2025

环境科学
中国科学院生态环境研究中心

环境科学

北大核心
影响因子:1.913
ISSN:0250-3301
年,卷(期):2025.46(1)