摘要
据2006-2015年间制造业能源消费数据核算中国大陆30个省(除港澳台、西藏外)的制造业碳排放,并依据要素密集度将制造业划分为资金、技术、劳动力密集型3类。在分析制造业以及不同类型制造业碳排放时空演变基础上,运用Kaya模型将碳排放驱动因素划分为经济规模、产业结构、能源强度、能源碳强度4个方面,并运用LMDI-I分解模型定量分析碳排放的驱动因素。结果表明:除北京外,其余省域制造业碳排放均呈现不同程度的增长;资金密集型制造业碳增长最高,其次是技术、劳动力密集型制造业;经济规模扩大是导致各省、各类型制造业碳增长的首要因素;产业结构调整、能源强度与能源碳强度的变化在各省、各类型制造业碳排放中呈现双向效应,且作用强度差异显著。因此,在未来,各省、各类型制造业碳减排措施应各有侧重。
This paper is based on the energy consumption data of manufacturing industries from 2006 to 2015 to determine the carbon emissions in 30 provinces of China(except for Hong Kong,Macao,Taiwan,and Tibet because of data shortage).According to the degree of factory intensity,the manufacturing industry was divided into three categories:capital,technology,and labor-intensive.Based on the analysis of the temporal-spatial evolution characteristics of carbon emissions in the manufacturing industry and the different types of manufacturing industry,this study used the Kaya model to divide the driving factors of carbon emissions into four aspects: economic scale,industrial structure,energy intensity,and energy-carbon intensity.Then,the LMDI-I decomposition model was used to quantitatively analyze the driving factors of carbon emissions.The research results show that in addition to Beijing City,the carbon emissions of the manufacturing industry in other provinces showed a growth trend;the carbon emission increment is the highest in capital-intensive manufacturing industries,followed by the technology and labor-intensive manufacturing industries.The effect of expansions of economic scale is a main factor for all provinces and the carbon emissions of various manufacturing industries are increasing.The industrial structure adjustment,energy intensity,and energy-carbon intensity changes have two-way effects on the carbon emissions of all types of manufacturing industries in different provinces and the intensities of the effect are significantly different.Therefore,in the future,the cut-in points of carbon emission reduction in manufacturing industries in different provinces and industries should be different.
作者
王霞
张丽君
秦耀辰
张晶飞
WANG Xia;ZHANG Li-jun;QIN Yao-chen;ZHANG Jing-fei(College of Environment and Planning,Henan University,Kaifeng 475004,Henan,China;Key Laboratory of Geospatial Technology for Middle and Lower Yellow Region,Henan University,Kaifeng 475004,Henan,China)
出处
《干旱区地理》
CSCD
北大核心
2020年第2期536-545,共10页
Arid Land Geography
基金
国家自然科学基金项目(41501588,41671536)
中国博士后基金项目(2016M600575)
河南省哲学社会科学规划项目(2014CJJ065)资助。
