Uncovering CO2 emission drivers under regional industrial transfer in China’s Yangtze River Economic Belt: a multi-layer LMDI decomposition analysis
Huijuan JIANG, Yong GENG, Xu TIAN, Xi ZHANG, Wei CHEN, Ziyan GAO
Uncovering CO2 emission drivers under regional industrial transfer in China’s Yangtze River Economic Belt: a multi-layer LMDI decomposition analysis
With the relocation of heavy industries moving from downstream region to upstream and midstream regions in the Yangtze River Economic Belt (YREB), it is critical to encourage coordinated low carbon development in different regions within the YREB. This paper uncovers the evolution of CO2 emissions in different regions within the YREB for the period of 2000–2017. It decomposes regional CO2 emission changes using the temporal and cross-regional three-layer logarithmic mean Divisia index (LMDI) method. Besides, it decomposes industrial CO2 emission changes using the temporal two-layer LMDI method. The research results show that economic growth is the major driver for regional CO2 emission disparities. The mitigation drivers, such as energy intensity and energy structure, lead to a more decreased CO2 emission in the downstream region than in the upstream and midstream regions. In addition, it proposes several policy recommendations based upon the local realities, including improving energy efficiency, optimizing energy structure, promoting advanced technologies and equipment transfers, and coordinating the development in the upstream, midstream and downstream regions within the YREB.
CO2 emission / multi-layer LMDI decomposition / industrial transfer / governance
[1] |
World Bank. World bank topics. 2018–09–16
|
[2] |
Wu R, Geng Y, Cui X, Gao Z, Liu Z. Reasons for recent stagnancy of carbon emissions in China’s industrial sectors. Energy, 2019, 172: 457–466
CrossRef
Google scholar
|
[3] |
National Development and Reform Commission (NDRC). Notice of the State Council on Issuing the Comprehensive Work Plan for Energy Saving and Emission Reduction in 12th Five-year Plan. Beijing: Statistics Press, 2011 (in Chinese)
|
[4] |
National Development and Reform Commission (NDRC). Notice of the State Council on Issuing the Comprehensive Work Plan for Energy Saving and Emission Reduction in 13th Five-Year Plan. Beijing: Statistics Press, 2016 (in Chinese)
|
[5] |
He J K. An analysis of China’s CO2 emission peaking target and pathways. Advances in Climate Change Research, 2014, 5(4): 155–161
CrossRef
Google scholar
|
[6] |
Zhang X, Geng Y, Shao S, Wilson J, Song X, You W. China’s non-fossil energy development and its 2030 CO2 reduction targets: the role of urbanization. Applied Energy, 2020, 261: 114353
CrossRef
Google scholar
|
[7] |
Ninpanit P, Malik A, Wakiyama T, Geschke A, Lenzen M. Thailand’s energy-related carbon dioxide emissions from production-based and consumption-based perspectives. Energy Policy, 2019, 133: 110877
CrossRef
Google scholar
|
[8] |
Steckel J C, Hilaire J, Jakob M, Edenhofer O. Coal and carbonization in sub-Saharan Africa. Nature Climate Change, 2020, 10(1): 83–88
CrossRef
Google scholar
|
[9] |
Oliver J, Janssens M G, Munteank M, Peters J. Trends in Global CO2 Emissions: 2015 Report. 2015, PBL Netherlands Environmental Assessment Agency
|
[10] |
Zhou S, Duan M, Yuan Z, Ou X. Peak CO2 emission in the region dominated by coal use and heavy chemical industries: a case study of Dezhou city in China. Frontiers in Energy, 2018, [Epub ahead of print] 10.1007/s11708-018-0558-y
|
[11] |
Chen J, Wang P, Cui L, Huang S, Song M. Decomposition and decoupling analysis of CO2 emissions in OECD. Applied Energy, 2018, 231: 937–950
CrossRef
Google scholar
|
[12] |
Mousavi B, Lopez N S A, Biona J B M, Chiu A S F, Blesl M. Driving forces of Iran’s CO2 emissions from energy consumption: an LMDI decomposition approach. Applied Energy, 2017, 206: 804–814
CrossRef
Google scholar
|
[13] |
Wang H, He J. China’s pre-2020 CO2 emission reduction potential and its influence. Frontiers in Energy, 2019, 13(3): 571–578
CrossRef
Google scholar
|
[14] |
Lopez N S, Chiu A S, Biona J B. Decomposing drivers of transportation energy consumption and carbon dioxide emissions for the Philippines: the case of developing countries. Frontiers in Energy, 2018, 12(3): 389–399
CrossRef
Google scholar
|
[15] |
Fujii M, Fujita T, Dong L, Lu C, Geng Y, Behera S K, Park H S, Chiu A S F. Possibility of developing low-carbon industries through urban symbiosis in Asian cities. Journal of Cleaner Production, 2016, 114: 376–386
CrossRef
Google scholar
|
[16] |
Kuramochi T. Assessment of midterm CO2 emissions reduction potential in the iron and steel industry: a case of Japan. Journal of Cleaner Production, 2016, 132: 81–97
CrossRef
Google scholar
|
[17] |
Song X, Geng Y, Li K, Zhang X, Wu F, Pan H, Zhang Y. Does environmental infrastructure investment contribute to emissions reduction? A case of China. Frontiers in Energy, 2020, 14(1): 57–70
CrossRef
Google scholar
|
[18] |
Song M, Guo X, Wu K, Wang G. Driving effect analysis of energy-consumption carbon emissions in the Yangtze River Delta region. Journal of Cleaner Production, 2015, 103: 620–628
CrossRef
Google scholar
|
[19] |
Hao H, Geng Y, Hang W. GHG emissions from primary aluminum production in China: regional disparity and policy implications. Applied Energy, 2016, 166: 264–272
CrossRef
Google scholar
|
[20] |
Li A, Zhang A, Zhou Y, Yao X. Decomposition analysis of factors affecting carbon dioxide emissions across provinces in China. Journal of Cleaner Production, 2017, 141: 1428–1444
CrossRef
Google scholar
|
[21] |
Gu S, Fu B, Thriveni T, Fujita T, Ahn J W. Coupled LMDI and system dynamics model for estimating urban CO2 emission mitigation potential in Shanghai, China. Journal of Cleaner Production, 2019, 240: 118034
CrossRef
Google scholar
|
[22] |
Zheng J, Mi Z, Coffman D M, Milcheva S, Shan Y, Guan D, Wang S. Regional development and carbon emissions in China. Energy Economics, 2019, 81: 25–36
CrossRef
Google scholar
|
[23] |
Liang W, Gan T, Zhang W. Dynamic evolution of characteristics and decomposition of factors influencing industrial carbon dioxide emissions in China: 1991–2015. Structural Change and Economic Dynamics, 2019, 49: 93–106
CrossRef
Google scholar
|
[24] |
Xu S C, He Z X, Long R Y. Factors that influence carbon emissions due to energy consumption in China: decomposition analysis using LMDI. Applied Energy, 2014, 127: 182–193
CrossRef
Google scholar
|
[25] |
Tian X, Bai F, Jia J, Liu Y, Shi F. Realizing low-carbon development in a developing and industrializing region: impacts of industrial structure change on CO2 emissions in southwest China. Journal of Environmental Management, 2019, 233: 728–738
CrossRef
Google scholar
|
[26] |
Chen J, Yuan H, Tian X, Zhang Y, Shi F. What determines the diversity of CO2 emission patterns in the Beijing-Tianjin-Hebei region of China? An analysis focusing on industrial structure change. Journal of Cleaner Production, 2019, 228: 1088–1098
CrossRef
Google scholar
|
[27] |
Xu X, Yang G, Tan Y, Zhuang Q, Tang X, Zhao K, Wang S. Factors influencing industrial carbon emissions and strategies for carbon mitigation in the Yangtze River Delta of China. Journal of Cleaner Production, 2017, 142: 3607–3616
CrossRef
Google scholar
|
[28] |
Chen L, Xu L, Yang Z. Accounting carbon emission changes under regional industrial transfer in an urban agglomeration in China’s Pearl River Delta. Journal of Cleaner Production, 2017, 167: 110–119
CrossRef
Google scholar
|
[29] |
Liao C, Wang S, Zhang Y, Song D, Zhang C. Driving forces and clustering analysis of provincial-level CO2 emissions from the power sector in China from 2005 to 2015. Journal of Cleaner Production, 2019, 240: 118026
CrossRef
Google scholar
|
[30] |
Geng Y, Zhao H, Liu Z, Xue B, Fujita T, Xi F. Exploring driving factors of energy-related CO2 emissions in Chinese provinces: a case of Liaoning. Energy Policy, 2013, 60: 820–826
CrossRef
Google scholar
|
[31] |
Shan Y, Liu J, Liu Z, Xu X, Shao S, Wang P, Guan D. New provincial CO2 emission inventories in China based on apparent energy consumption data and updated emission factors. Applied Energy, 2016, 184: 742–750
CrossRef
Google scholar
|
[32] |
Zheng X, Wang R, He Q. A city-scale decomposition and decoupling analysis of carbon dioxide emissions: a case study of China. Journal of Cleaner Production, 2019, 238: 117824
CrossRef
Google scholar
|
[33] |
Shao S, Yang L, Gan C, Cao J, Geng Y, Guan D. Using an extended LMDI model to explore techno-economic drivers of energy-related industrial CO2 emission changes: a case study for Shanghai (China). Renewable & Sustainable Energy Reviews, 2016, 55: 516–536
CrossRef
Google scholar
|
[34] |
Liu Z, Liang S, Geng Y, Xue B, Xi F, Pan Y, Zhang T, Fujita T. Features, trajectories and driving forces for energy-related GHG emissions from Chinese mega cites: the case of Beijing, Tianjin, Shanghai and Chongqing. Energy, 2012, 37(1): 245–254
CrossRef
Google scholar
|
[35] |
Gao Z, Geng Y, Wu R, Chen W, Wu F, Tian X. Analysis of energy-related CO2 emissions in China’s pharmaceutical industry and its driving forces. Journal of Cleaner Production, 2019, 223: 94–108
CrossRef
Google scholar
|
[36] |
Wang Y, Zhu Q, Geng Y. Trajectory and driving factors for GHG emissions in the Chinese cement industry. Journal of Cleaner Production, 2013, 53: 252–260
CrossRef
Google scholar
|
[37] |
Shao S, Liu J, Geng Y, Miao Z, Yang Y. Uncovering driving factors of carbon emissions from China’s mining sector. Applied Energy, 2016, 166: 220–238
CrossRef
Google scholar
|
[38] |
National Development and Reform Commission (NDRC). Guiding Opinions of the State Council on Relying on Golden Waterways to Promote the Development of the Yangtze River Economic Belt. 2014
|
[39] |
Ren F R, Tian Z, Shen Y T, Chiu Y H, Lin T Y. Energy, CO2, and AQI efficiency and improvement of the Yangtze River Economic Belt. Energies, 2019, 12(4): 647
CrossRef
Google scholar
|
[40] |
Tian Z, Ren F R, Xiao Q W, Chiu Y H, Lin T Y. Cross-regional comparative study on carbon emission efficiency of China’s Yangtze River Economic Belt based on the meta-frontier. International Journal of Environmental Research and Public Health, 2019, 16(4): 619
CrossRef
Google scholar
|
[41] |
Tang D, Zhang Y, Bethel B J. An analysis of disparities and driving factors of carbon emissions in the Yangtze River Economic Belt. Sustainability, 2019, 11(8): 2362
CrossRef
Google scholar
|
[42] |
Zhang X, Zhao X, Jiang Z, Shao S. How to achieve the 2030 CO2 emission-reduction targets for China’s industrial sector: retrospective decomposition and prospective trajectories. Global Environmental Change, 2017, 44: 83–97
CrossRef
Google scholar
|
[43] |
Mi Z, Meng J, Green F, Coffman D M, Guan D. China’s “exported carbon” peak: patterns, drivers, and implications. Geophysical Research Letters, 2018, 45(9): 4309–4318
CrossRef
Google scholar
|
[44] |
Zhang S, Li H, Zhang Q, Tian X, Shi F. Uncovering the impacts of industrial transformation on low-carbon development in the Yangtze River Delta. Resources, Conservation and Recycling, 2019, 150: 104442
CrossRef
Google scholar
|
[45] |
Zhao X, Ma Q, Yang R. Factors influencing CO2 emissions in China’s power industry: co-integration analysis. Energy Policy, 2013, 57: 89–98
CrossRef
Google scholar
|
[46] |
Lin B, Fei R. Regional differences of CO2 emissions performance in China’s agricultural sector: a Malmquist index approach. European Journal of Agronomy, 2015, 70: 33–40
CrossRef
Google scholar
|
[47] |
Liu Z, Geng Y, Dong H, Wilson J, Micic T, Wu R, Cui X, Qian Y, You W, Sun H. Efficient distribution of carbon emissions reduction targets at the city level: a case of Yangtze River Delta region. Journal of Cleaner Production, 2018, 172: 1711–1721
CrossRef
Google scholar
|
[48] |
Li K, Lin B. Economic growth model, structural transformation, and green productivity in China. Applied Energy, 2017, 187: 489–500
CrossRef
Google scholar
|
[49] |
National Development and Reform Commission (NDRC). Outline of the Yangtze River Economic Belt Development Plan. 2016, General office of the State Council of China
|
[50] |
Intergovernmental Panel on Climate Change (IPCC). 2006 Intergovernmental Panel on Climate Change Guidelines for National Greenhouse Gas Inventories. 2006
|
[51] |
Jeong K, Kim S. LMDI decomposition analysis of greenhouse gas emissions in the Korean manufacturing sector. Energy Policy, 2013, 62: 1245–1253
CrossRef
Google scholar
|
[52] |
Ang B W, Wang H. Index decomposition analysis with multidimensional and multilevel energy data. Energy Economics, 2015, 51: 67–76
CrossRef
Google scholar
|
[53] |
Ang B W, Liu F L. A new energy decomposition method: perfect in decomposition and consistent in aggregation. Energy, 2001, 26(6): 537–548
CrossRef
Google scholar
|
[54] |
Wu L, Kaneko S, Matsuoka S. Driving forces behind the stagnancy of China’s energy-related CO2 emissions from 1996 to 1999: the relative importance of structural change, intensity change and scale change. Energy Policy, 2005, 33(3): 319–335
CrossRef
Google scholar
|
[55] |
Ang B W, Zhang F Q. Inter-regional comparisons of energy-related CO2 emissions using the decomposition technique. Energy, 1999, 24(4): 297–305
CrossRef
Google scholar
|
[56] |
Li A, Hu M, Wang M, Cao Y. Energy consumption and CO2 emissions in eastern and central China: a temporal and a cross-regional decomposition analysis. Technological Forecasting and Social Change, 2016, 103: 284–297
CrossRef
Google scholar
|
[57] |
Zhang F Q, Ang B W. Methodological issues in cross-country/region decomposition of energy and environment indicators. Energy Economics, 2001, 23(2): 179–190
CrossRef
Google scholar
|
[58] |
National Bureau of Statistics of China (NBSC). Industrial Classification for National Economic Activities (GB/T 4754–2017). Beijing: China Statistics Press, 2017 (in Chinese)
|
[59] |
Tian Y, Xiong S, Ma X, Ji J. Structural path decomposition of carbon emission: a study of China’s manufacturing industry. Journal of Cleaner Production, 2018, 193: 563–574
CrossRef
Google scholar
|
[60] |
Luo L, Zhao F. Optimization of industrial layout and high-quality development of the Yangtze River Economic Belt: based on the perspective of industrial transfer between regions. Reform, 2019, 2: 27–36 (in Chinese)
|
[61] |
Li L, Ma Y. Spatial-temporal pattern evolution of manufacturing geographical agglomeration and influencing factors of old industrial base: a case of Jilin province, China. Chinese Geographical Science, 2015, 25(4): 486–497
CrossRef
Google scholar
|
[62] |
Ang B W, Xu X Y, Su B. Multi-country comparisons of energy performance: the index decomposition analysis approach. Energy Economics, 2015, 47: 68–76
CrossRef
Google scholar
|
[63] |
Guan D, Liu Z, Geng Y, Lindner S, Hubacek K. The gigatonne gap in China’s carbon dioxide inventories. Nature Climate Change, 2012, 2(9): 672–675
CrossRef
Google scholar
|
[64] |
Gregg J S, Andres R J. A method for estimating the temporal and spatial patterns of carbon dioxide emissions from national fossil-fuel consumption. Tellus. Series B, Chemical and Physical Meteorology, 2008, 60(1): 1–10
CrossRef
Google scholar
|
[65] |
Liu Z, Geng Y, Lindner S, Guan D. Uncovering China’s greenhouse gas emission from regional and sectoral perspectives. Energy, 2012, 45(1): 1059–1068
CrossRef
Google scholar
|
[66] |
Wang Z, Yin F, Zhang Y, Zhang X. An empirical research on the influencing factors of regional CO2 emissions: evidence from Beijing city, China. Applied Energy, 2012, 100: 277–284
CrossRef
Google scholar
|
[67] |
Liu Z, Guan D, Wei W, Davis S J, Ciais P, Bai J, Peng S, Zhang Q, Hubacek K, Marland G, Andres R J, Crawford-Brown D, Lin J, Zhao H, Hong C, Boden T A, Feng K, Peters G P, Xi F, Liu J, Li Y, Zhao Y, Zeng N, He K. Reduced carbon emission estimates from fossil fuel combustion and cement production in China. Nature, 2015, 524(7565): 335–338
CrossRef
Google scholar
|
[68] |
Shan Y, Guan D, Zheng H, Ou J, Li Y, Meng J, Mi Z, Liu Z, Zhang Q. China CO2 emission accounts 1997–2015. Scientific Data, 2018, 5(1): 170201
CrossRef
Google scholar
|
[69] |
Shan Y, Huang Q, Guan D, Hubacek K. China CO2 emission accounts 2016–2017. Scientific Data, 2020, 7(1): 54
CrossRef
Google scholar
|
[70] |
National Bureau of Statistics of China (NBSC). China Energy Statistical Yearbooks (2000–2017). Beijing: China Statistics Press, 2018 (in Chinese)
|
[71] |
National Bureau of Statistics of China (NBSC). China Statistical Yearbooks (2000–2017). Beijing: China Statistics Press, 2018 (in Chinese)
|
[72] |
Shan Y, Guan D, Liu J, Mi Z, Liu Z, Liu J, Schroeder H, Cai B, Chen Y, Shao S, Zhang Q. Methodology and applications of city level CO2 emission accounts in China. Journal of Cleaner Production, 2017, 161: 1215–1225
CrossRef
Google scholar
|
[73] |
Wang M, Feng C. Using an extended logarithmic mean Divisia index approach to assess the roles of economic factors on industrial CO2 emissions of China. Energy Economics, 2018, 76: 101–114
CrossRef
Google scholar
|
[74] |
Akbostancı E, Tunç G I, Türüt-Aşık S. Drivers of fuel based carbon dioxide emissions: the case of Turkey. Renewable & Sustainable Energy Reviews, 2018, 81: 2599–2608
CrossRef
Google scholar
|
[75] |
Wen L, Li Z. Provincial-level industrial CO2 emission drivers and emission reduction strategies in China: combining two-layer LMDI method with spectral clustering. Science of the Total Environment, 2020, 700: 134374
CrossRef
Google scholar
|
[76] |
Zhao X, Zhang X, Shao S. Decoupling CO2 emissions and industrial growth in China over 1993–2013: the role of investment. Energy Economics, 2016, 60: 275–292
CrossRef
Google scholar
|
[77] |
Zhu X, Zou J, Feng C. Analysis of industrial energy-related CO2 emissions and the reduction potential of cities in the Yangtze River Delta region. Journal of Cleaner Production, 2017, 168: 791–802
CrossRef
Google scholar
|
[78] |
Kopidou D, Diakoulaki D. Decomposing industrial CO2 emissions of Southern European countries into production- and consumption-based driving factors. Journal of Cleaner Production, 2017, 167: 1325–1334
CrossRef
Google scholar
|
[79] |
Wang M, Feng C. Understanding China’s industrial CO2 emissions: a comprehensive decomposition framework. Journal of Cleaner Production, 2017, 166: 1335–1346
CrossRef
Google scholar
|
[80] |
Xiao S, Dong H, Geng Y, Tian X, Liu C, Li H. Policy impacts on Municipal Solid Waste management in Shanghai: a system dynamics model analysis. Journal of Cleaner Production, 2020, 262: 121366
CrossRef
Google scholar
|
[81] |
Dong H, Geng Y, Yu X, Li J. Uncovering energy saving and carbon reduction potential from recycling wastes: a case of Shanghai in China. Journal of Cleaner Production, 2018, 205: 27–35
CrossRef
Google scholar
|
/
〈 | 〉 |