摘要
中国的碳减排约束目标已从单一的碳排放强度目标逐渐过渡到强度与总量双控目标。运用空间计量模型分析碳排放的空间集群效应,探究产生碳排放区域差异的影响因素。结果表明,经济的快速发展是碳排放总量不断增长的主要影响因素,能源消费和比重是碳排放的直接来源,人口增加对碳排放的影响相对较弱,产业结构调整对于碳排放总量具有较为显著的正向影响。据此,选取区域GDP、人口规模、产业结构、万元地区生产总值能耗和能源消费结构作为碳排放的影响因素,建立PSO-BP神经网络模型,进一步对2020~2030年中国30个省市自治区(不含西藏和港澳台地区)的碳排放总量与强度进行预测。研究发现,在基准情景与低碳情景下,中国各省区基本能够在2030年实现碳排放强度下降60%~65%的低碳减排目标,部分沿海发达地区可率先在2021~2025年完成碳达峰,部分欠发达在低碳情景下达峰依然晚于2030年,但增长率持续减小近零增长,有望在2035年之前实现达峰。中国要利用好碳排放权交易系统,合理设计排放配额;要对重点领域和行业依据规划方案明确减排目标;鼓励建立"达峰先锋城市联盟",在提前完成达峰目标的同时带动其他地区;设立监督追踪体系,保障达峰与强度目标得以有效实现。
China′s carbon emission reduction constraint target has gradually shifted from a single carbon intensity target to a dual control target of intensity and total emissions.Spatial econometric model was used to analyze the spatial clustering effect of carbon emissions and explore the influencing factors of regional differ-ences in carbon emissions.The results showed that the rapid economic development is the main factor influ-encing the continuous growth of the total carbon emissions,the energy consumption and proportion are the direct sources of carbon emissions,the population increase has a relatively small impact on carbon emissions,and the industrial structure adjustment has a significant positive impact on the total carbon emissions.There-fore,regional GDP,population size,industrial structure,energy consumption per ten-thousand-yuan regional GDP and energy consumption structure were selected as the influencing factors of carbon emissions,and a PSO-BP neural network model was established to further predict the total amount and intensity of carbon emissions in 30 provinces and autonomous regions(excluding Tibet and Hong Kong,Macao and Taiwan regions) in China from 2020 to 2030.It was found that in the benchmark scenario and low carbon scenario,all the provinces and regions in China can basically achieve the low carbon emission target of reducing carbon intensity by 60% to 65% by 2030.Some developed coastal areas may take the lead in peaking carbon dioxide emissions by 2021 to 2025,and some less developed areas may peak the emissions later than 2030 in low carbon scenario,but the growth rate continues to decrease to near-zero growth,and they are expected to peak the emissions by 2035.China should make good use of the carbon emissions trading system and rationally design the emission allowances,specify the emission reduction targets for key areas and industries according to the planning scheme,encourage the establishment of Alliance of Peaking Pioneer Cities of China to bring along other regions while peaking the emissions ahead of schedule,and establish a monitoring and tracking system to ensure that the peaking and intensity targets can be effectively achieved.
作者
范德成
张修凡
Fan Decheng;Zhang Xiufan(School of Economics and Management,Harbin Engineering University,Harbin Heilongjiang 150001)
出处
《中外能源》
2021年第8期11-19,共9页
Sino-Global Energy
基金
国家社会科学基金重点项目“基于产业组织理论的产业技术创新动力机制研究”(编号:19AGL007)
黑龙江省哲学社会科学研究规划项目(编号:18GLD291)的资助。
关键词
碳排放
能源结构
产业结构
碳排放强度
低碳情景
碳达峰
carbon emissions
energy structure
industrial structure
carbon emission intensity
low-carbon scenario
peak carbon dioxide emissions
作者简介
范德成,哈尔滨工程大学经济管理学院教授、博士生导师,2003年获得哈尔滨工程大学管理科学与工程专业博士学位,主要研究方向为产业技术创新;通讯作者:张修凡。E-mail:zhangxiufan@hrbeu.edu.cn。
