中国地理科学 ›› 2016, Vol. 26 ›› Issue (5): 656-669.doi: 10.1007/s11769-016-0823-0

• 论文 • 上一篇    下一篇

Carbon Emission Trends of Manufacturing and Influencing Factors in Jilin Province, China

YU Chao1,2, MA Yanji1   

  1. 1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • 收稿日期:2015-06-05 修回日期:2015-09-28 出版日期:2016-10-27 发布日期:2016-08-25
  • 通讯作者: MA Yanji.E-mail:mayanji@iga.ac.cn E-mail:mayanji@iga.ac.cn
  • 基金资助:

    Under the auspices of National Natural Science Foundation of China (No. 41371135);Jilin Province Science and Technology Guide Plan Soft Science Project (No. 20120635)

Carbon Emission Trends of Manufacturing and Influencing Factors in Jilin Province, China

YU Chao1,2, MA Yanji1   

  1. 1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2015-06-05 Revised:2015-09-28 Online:2016-10-27 Published:2016-08-25
  • Contact: MA Yanji.E-mail:mayanji@iga.ac.cn E-mail:mayanji@iga.ac.cn
  • Supported by:

    Under the auspices of National Natural Science Foundation of China (No. 41371135);Jilin Province Science and Technology Guide Plan Soft Science Project (No. 20120635)

摘要:

This paper constructed a carbon emission identity based on five factors: industrial activity, industrial structure, energy intensity, energy mix and carbon emission parameter, and analyzed manufacturing carbon emission trends in Jilin Province at subdivided industrial level through Log-Mean Divisia Index (LMDI) method. Results showed that manufacturing carbon emissions of Jilin Province increased 1.304×107 t by 66% between 2004 and 2010. However, 2012 was a remarkable year in which carbon emissions decreased compared with 2011, the first fall since 2004. Industrial activity was the most important factor for the increase of carbon emissions, while energy intensity had the greatest impact on inhibiting carbon emission growth. Despite the impact of industrial structure on carbon emissions fluctuated, its overall trend inhibited carbon emission growth. Further, influences of industrial structure became gradually stronger and surpassed energy intensity in the period 2009-2010. These results conclude that reducing energy intensity is still the main way for carbon emission reduction in Jilin Province, but industrial structure can not be ignored and it has great potential. Based on the analyses, the way of manufacturing industrial structure adjustment for Jilin Province is put forward.

关键词: manufacturing, carbon emissions, influencing factors, Log-Mean Divisia Index (LMDI), industrial structure adjustment, Jilin Province, China

Abstract:

This paper constructed a carbon emission identity based on five factors: industrial activity, industrial structure, energy intensity, energy mix and carbon emission parameter, and analyzed manufacturing carbon emission trends in Jilin Province at subdivided industrial level through Log-Mean Divisia Index (LMDI) method. Results showed that manufacturing carbon emissions of Jilin Province increased 1.304×107 t by 66% between 2004 and 2010. However, 2012 was a remarkable year in which carbon emissions decreased compared with 2011, the first fall since 2004. Industrial activity was the most important factor for the increase of carbon emissions, while energy intensity had the greatest impact on inhibiting carbon emission growth. Despite the impact of industrial structure on carbon emissions fluctuated, its overall trend inhibited carbon emission growth. Further, influences of industrial structure became gradually stronger and surpassed energy intensity in the period 2009-2010. These results conclude that reducing energy intensity is still the main way for carbon emission reduction in Jilin Province, but industrial structure can not be ignored and it has great potential. Based on the analyses, the way of manufacturing industrial structure adjustment for Jilin Province is put forward.

Key words: manufacturing, carbon emissions, influencing factors, Log-Mean Divisia Index (LMDI), industrial structure adjustment, Jilin Province, China