YU Chao, MA Yanji. Carbon Emission Trends of Manufacturing and Influencing Factors in Jilin Province, China[J]. Chinese Geographical Science, 2016, 26(5): 656-669. doi: 10.1007/s11769-016-0823-0
Citation: YU Chao, MA Yanji. Carbon Emission Trends of Manufacturing and Influencing Factors in Jilin Province, China[J]. Chinese Geographical Science, 2016, 26(5): 656-669. doi: 10.1007/s11769-016-0823-0

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

doi: 10.1007/s11769-016-0823-0
Funds:  Under the auspices of National Natural Science Foundation of China (No. 41371135);Jilin Province Science and Technology Guide Plan Soft Science Project (No. 20120635)
More Information
  • Corresponding author: MA Yanji.E-mail:mayanji@iga.ac.cn
  • Received Date: 2015-06-05
  • Rev Recd Date: 2015-09-28
  • Publish Date: 2016-10-27
  • 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.
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Carbon Emission Trends of Manufacturing and Influencing Factors in Jilin Province, China

doi: 10.1007/s11769-016-0823-0
Funds:  Under the auspices of National Natural Science Foundation of China (No. 41371135);Jilin Province Science and Technology Guide Plan Soft Science Project (No. 20120635)
    Corresponding author: MA Yanji.E-mail:mayanji@iga.ac.cn

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.

YU Chao, MA Yanji. Carbon Emission Trends of Manufacturing and Influencing Factors in Jilin Province, China[J]. Chinese Geographical Science, 2016, 26(5): 656-669. doi: 10.1007/s11769-016-0823-0
Citation: YU Chao, MA Yanji. Carbon Emission Trends of Manufacturing and Influencing Factors in Jilin Province, China[J]. Chinese Geographical Science, 2016, 26(5): 656-669. doi: 10.1007/s11769-016-0823-0
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