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中国城市碳达峰路径及其驱动因素的结构分解 被引量:4
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作者 张兵兵 王捷 闫志俊 《中国人口·资源与环境》 CSSCI CSCD 北大核心 2023年第9期38-44,共7页
碳达峰和碳中和是生态文明建设整体布局的重要一环,是实现中国绿色低碳高质量发展的重要举措。该研究首先基于校准的夜间灯光数据,运用从上至下估算方法对中国267个地级及以上城市的碳排放量进行反演模拟测算;然后,综合运用高斯回归、... 碳达峰和碳中和是生态文明建设整体布局的重要一环,是实现中国绿色低碳高质量发展的重要举措。该研究首先基于校准的夜间灯光数据,运用从上至下估算方法对中国267个地级及以上城市的碳排放量进行反演模拟测算;然后,综合运用高斯回归、支持向量机、梯度提升等机器学习算法,科学预测各个城市的碳达峰路径;最后,运用拓展的广义迪氏指数方法对2000—2030年地级及以上城市碳排放演变的驱动因素进行分解,结果显示:①中国二氧化碳排放总量呈持续增长态势,各城市增速不同且差异较大,形成“发达城市高排量,欠发达城市低排量”的态势。②267个样本城市中,仅有苏州市、贵阳市等6个城市可以提前达峰或按期达峰,比重仅占2%;上海市、广州市、杭州市等252个城市将在2031—2034年达峰;北京市、珠海市等9个城市将长时期延期达峰。③运用拓展的广义迪氏指数进行结构分解后发现,能源消费规模、产出规模、固定资产投资规模等因素对各城市碳排放基本保持促增作用,而产出碳强度、投资碳强度等则基本保持促降作用。优化绿色低碳发展区域布局,推动低碳产业集群建设,兼顾城市“稳发展”与“促减排”是“双碳”目标有序推进的重要保障。 展开更多
关键词 碳达峰 节能减排 低碳转型 机器学习 广义迪氏指数
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Driving factors and spatio-temporal features underlying industrial SO_(2) emissions in“2+26”in North China and extended cities 被引量:2
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作者 Zhuang Miao Sicen Liu Xiaodong Chen 《Chinese Journal of Population,Resources and Environment》 2020年第4期296-318,共23页
As one of the largest global emitters of sulfur dioxide(SO_(2)),China faces increasing pressure to achieve sustainable economic and social development.Using panel data of 58 prefecture-level cities in North China betw... As one of the largest global emitters of sulfur dioxide(SO_(2)),China faces increasing pressure to achieve sustainable economic and social development.Using panel data of 58 prefecture-level cities in North China between 2003 and 2017,this paper considers the dynamic spatio-temporal characteristics of industrial SO_(2) emissions in the"2+26"in North China and extended cities in North China and decomposes the determinants of industrial SO_(2) emissions into eight effects using the Generalized Divisia Index Model(GDIM).The contributions of each effect on changes in emissions are assessed on regional,provincial,and prefectural levels,as well as according to various stages.The results indicate the following.First,industrial SO2 emissions in the"2+26"cities in North China and extended cities in North China exhibit spatial autocorrelation and agglomeration effects.Cities with high-high(HH)and low-low(LL)agglomeration patterns were concentrated in Shanxi and Henan provinces,respectively.Second,industrialization,energy consumption,and economic development were the main factors that increased industrial SO2 emissions,while technology,energy sulfur intensity,and economic sulfur intensity were the key factors that reduced them.Third,13 cities,induding Tangshan,were the most important regions where further emissions regulations need to be implemented.These cities were divided into three types and different corresponding measures for reducing their emissions are suggested.Based on the conclusions of this study,this paper puts forward some targeted policy recommendations for reducing industrial SO_(2) emissions according to different categories of cities. 展开更多
关键词 Industrial SO_(2)emissions Temporal and spatial distribution characteristics Generalized divisia index model(gdim) Factor decomposition
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中国钢铁行业碳排放:达峰情景与中和路径
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作者 张攀路 都沁军 +1 位作者 张凯旋 田文涛 《环境科学》 EI CAS CSCD 北大核心 2024年第11期6336-6343,共8页
首先采用广义迪氏指数分解法(GDIM)分析2001~2020年中国钢铁行业碳排放变化影响因素,进而借助蒙特卡洛模拟对2021~2035年碳排放演化趋势进行动态情景模拟,旨在探究钢铁行业未来的碳达峰情景以及行之有效的碳中和实施路径.结果表明:①经... 首先采用广义迪氏指数分解法(GDIM)分析2001~2020年中国钢铁行业碳排放变化影响因素,进而借助蒙特卡洛模拟对2021~2035年碳排放演化趋势进行动态情景模拟,旨在探究钢铁行业未来的碳达峰情景以及行之有效的碳中和实施路径.结果表明:①经济产出和粗钢产量是钢铁行业碳排放最主要的促增因素;在促降因素中,产出碳强度效果最为显著,其次为产量碳强度,吨钢能耗和能源产出率的促降效应尚不明显.②基准情景(BAU)、低碳情景(L)和强化情景(S)下钢铁行业均能实现碳达峰,达峰时间依次为2030年、2025年和2020年. 展开更多
关键词 钢铁行业 碳排放 广义迪氏指数分解法(gdim) 情景分析 蒙特卡洛模拟
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