TY - JOUR
T1 - Opportunities for low-carbon socioeconomic transition during the revitalization of Northeast China
T2 - Insights from Heilongjiang province
AU - Chen, Weiming
AU - Lei, Yalin
AU - Wu, Sanmang
AU - Li, Li
N1 - Publisher Copyright:
© 2019
PY - 2019/9/15
Y1 - 2019/9/15
N2 - The Strategies of Reviving the Old Industrial Bases provide opportunities for low-carbon transition in Northeast China, which is one of the earliest regions to industrialize and the largest rustbelt in China, but study on the impacts of its socioeconomic factors on CO2 emissions is still in short, though it is essential for guiding the pathways to achieve low-carbon socioeconomic transition. We adopted the structural decomposition analysis (SDA) to identify the main contributors to emissions increase in Heilongjiang province during 2002–2012, which is the heartland of Northeast revitalization. The results show that the increase in CO2 emissions was mainly driven by growth in per-capita final demand, which generated 203.8 Mt (153.6%) upstream CO2 emissions between 2002 and 2012. Changes in production structure and final demand structure had smaller impacts on CO2 emissions increase (36.1 Mt and 27.0 Mt). However, the positive influences were largely overwhelmed by change in emission intensity, which avoided 135.4 Mt (−102%) CO2 emissions. Therefore, appropriate measures related to energy structure optimization and efficiency improvement should be implemented. Especially, increasing the proportion of wind, solar and biomass energy in Heilongjiang, where renewable energy is abundant, would reduce the CO2 emissions significantly. In addition, domestic export took the lead position in driving the CO2 emissions in Heilongjiang, accounting for 37.6%–43.1% annual emissions between 2002 and 2012. Thus, some financial instrument, such as tax relief for less carbon intensive exports could be adopted to prompt upstream suppliers to decarbonize their production processes.
AB - The Strategies of Reviving the Old Industrial Bases provide opportunities for low-carbon transition in Northeast China, which is one of the earliest regions to industrialize and the largest rustbelt in China, but study on the impacts of its socioeconomic factors on CO2 emissions is still in short, though it is essential for guiding the pathways to achieve low-carbon socioeconomic transition. We adopted the structural decomposition analysis (SDA) to identify the main contributors to emissions increase in Heilongjiang province during 2002–2012, which is the heartland of Northeast revitalization. The results show that the increase in CO2 emissions was mainly driven by growth in per-capita final demand, which generated 203.8 Mt (153.6%) upstream CO2 emissions between 2002 and 2012. Changes in production structure and final demand structure had smaller impacts on CO2 emissions increase (36.1 Mt and 27.0 Mt). However, the positive influences were largely overwhelmed by change in emission intensity, which avoided 135.4 Mt (−102%) CO2 emissions. Therefore, appropriate measures related to energy structure optimization and efficiency improvement should be implemented. Especially, increasing the proportion of wind, solar and biomass energy in Heilongjiang, where renewable energy is abundant, would reduce the CO2 emissions significantly. In addition, domestic export took the lead position in driving the CO2 emissions in Heilongjiang, accounting for 37.6%–43.1% annual emissions between 2002 and 2012. Thus, some financial instrument, such as tax relief for less carbon intensive exports could be adopted to prompt upstream suppliers to decarbonize their production processes.
KW - CO emissions
KW - Heilongjiang province
KW - Input-output model
KW - Low-carbon transition
KW - Structural decomposition analysis (SDA)
UR - http://www.scopus.com/inward/record.url?scp=85066040823&partnerID=8YFLogxK
U2 - 10.1016/j.scitotenv.2019.05.232
DO - 10.1016/j.scitotenv.2019.05.232
M3 - Article
C2 - 31141742
AN - SCOPUS:85066040823
SN - 0048-9697
VL - 683
SP - 380
EP - 388
JO - Science of the Total Environment
JF - Science of the Total Environment
ER -