Advertisement

Structural decomposition analysis of embodied carbon in trade in the middle reaches of the Yangtze River

  • Zhijian Chen
  • Wen Ni
  • Lantian Xia
  • Zhangqi Zhong
Research Article
  • 14 Downloads

Abstract

The middle reaches of the Yangtze River are the first demonstration zone for low-carbon urbanization in the midwest regions of China, and the division of carbon emission reduction responsibility is an important aspect of construction of ecological civilization. In this paper, the embodied carbon emissions in trade are estimated by using an input–output model in the middle reaches of the Yangtze River, and then a structural decomposition analysis (SDA) model is further applied to conduct decomposition analysis on factors of embodied carbon changes. Our primary findings show the following: (1) Production-based CO2 emissions from Hubei and Hunan are higher than consumption-based CO2 emissions. There are situations in Jiangxi and Anhui where production-based CO2 emissions are both higher and lower than consumption-based CO2 emissions. However, inter-regional trade implied carbon is dominated by net inflows. Moreover, the inter-regional embodied carbon emissions in trade mainly flow out to relatively developed regions, such as Jiangsu and Shanghai. The inflow of embodied carbon in trade comes mainly from relatively backward economic development areas, such as Shaanxi and Inner Mongolia. (2) From the perspective of industry, industries in Jiangxi and Anhui are dominated by net inflow, whereas industries in Hunan and Hubei are dominated by net outflow. Meanwhile, industry in the middle reaches of the Yangtze River displays a high carbon-locked phenomenon. Specifically, the high carbon-locked outflow industries are mainly concentrated in the transportation and warehousing industry, agriculture, and the chemical industry, and the outflow provinces flow out mainly to Jiangsu, Guangdong, and other economically developed regions; high carbon-locked inflows are concentrated in metal smelting and rolling processing, food manufacturing and tobacco processing, and construction, and the provinces are mainly Hebei, Henan, and Inner Mongolia, where economic development is lacking. (3) Furthermore, the results of SDA decomposition indicate that scale effect is generally the most important factor leading to embodied carbon outflow. Meanwhile, the energy carbon emission effect, the energy intensity effect, and the structural effect are important factors—the inter-industry association effect mainly promotes the embodied carbon outflow. Consequently, based on the distinction between production and consumer responsibility, and from the perspective of scale effect and structural effect, the related policy suggests that consumers should be held responsible.

Keywords

Input–output model Embodied carbon emissions in trade SDA model Responsibility for reducing emission 

Notes

Funding information

This study received financial support from the National Natural Science Foundation of China (Nos. 41501133, 41801118), the Jiangxi Provincial Social Science Planning Fund Project (No. 15YJ36), the Natural Science Foundation of Jiangxi Province (No. 20171BAA218012), the China Postdoctoral Fund Project (No. 2016M592106), the Jiangxi Postdoctoral Daily Fund Project (No. 2016RC14), the Jiangxi Graduate Innovative Special Fund Project (No. YC2018-S260), and the Post-Doctoral Fund Program in Jiangxi Province (No. 2016KY25).

References

  1. Ang BW (1995) Decomposition methodology in industrial energy demand analysis. Energy 20(20):1081–1095CrossRefGoogle Scholar
  2. Cai QM, Chen Y, Xu HQ (2015) Study on the decomposition scheme of regional indicators under the dual control targets of carbon intensity and total quantity: a case study of Wenzhou City. China Energy 37(4):28–32Google Scholar
  3. Cansino JM, Román R, Ordóñez M (2016) Main drivers of changes in CO2, emissions in the Spanish economy: a structural decomposition analysis. Energy Policy 89:150–159CrossRefGoogle Scholar
  4. Casler SD, Rose A (1998) Carbon dioxide emissions in the U.S. economy: a structural decomposition analysis. Environ Resour Econ 11(3/4):349–363CrossRefGoogle Scholar
  5. CESY (2015) China energy statistical yearbook (2008–2015). China Statistical Publishing House, BeijingGoogle Scholar
  6. Chen GQ, Guo S, Shao L, Li JS, Chen ZM (2013) Three-scale input–output modeling for urban economy: carbon emission by Beijing 2007. Commun Nonlinear Sci Numer Simul 18(9):2493–2506CrossRefGoogle Scholar
  7. Chen ZJ, Wang Z, Song Y (2015) Spatial changing pattern of carbon dioxide emissions per capita and club convergence in China. J Arid Land Resour Environ 29(4):24–29Google Scholar
  8. Chen G, Hadjikakou M, Wiedmann T (2016) Urban carbon transformations: unravelling spatial and inter-sectoral linkages for key city industries based on multi-region input-output analysis. J Clean Prod (163):224–240CrossRefGoogle Scholar
  9. Chen MM, Wu SM, Lei YL, Li ST (2018) Study on embodied CO2 transfer between the Jing-Jin-Ji region and other regions in China: a quantification using an interregional input-output model. Environ Sci Pollut Res 25:14068–14082CrossRefGoogle Scholar
  10. Cheng YQ, Wang ZY, Zhang SZ et al (2014) Spatial econometric analysis of carbon emission intensity and its driving factors from energy consumption in China. Sci Geogr Sin 68(4):1418–1431Google Scholar
  11. CSY (2015) China statistical yearbook (2008–2015). China Statistical Publishing House, BeijingGoogle Scholar
  12. Deng JX, Liu X, Wang Z (2014) Characteristics analysis and factor decomposition based on the regional difference changes in China’s CO2 emission. J Nat Resour 29(2):189–200Google Scholar
  13. Du YH, Zhang WF (2012) Research on CO2 embodied in China’s export and its driving factors. J Int Trade (3):97–107Google Scholar
  14. Feng K, Davis SJ, Sun L, Li X, Guan D, Liu W, Liu Z, Hubacek K (2013) Outsourcing CO2 within China. Proc Natl Acad Sci U S A 110(28):11654–11659CrossRefGoogle Scholar
  15. Gao XJ, Shi Y, Zhang DF, Giorgi F (2012) Climate change in China in the 21st century as simulated by a high resolution regional climate model. Sci Bull 57(10):1188–1195CrossRefGoogle Scholar
  16. Ge YU (2009) Impacts of climate change on locust outbreaks in China’s history. Bull Chin Acad Sci 23(4):234–236Google Scholar
  17. Ge YU, Xue B, Wang S et al (2000) Lake records and LGM climate in China. Sci Bull 45(13):1158–1164CrossRefGoogle Scholar
  18. Ge Q, Wang H, Rutishauser T, Dai J (2015) Phenological response to climate change in China: a meta-analysis. Glob Chang Biol 21(1):265–274CrossRefGoogle Scholar
  19. Gu AL, Lv ZQ (2016) Effects of economic structure change on carbon emission of China: analysis based on IO-SDA model. Chin J Popul Resour Environ 26(3):37–45Google Scholar
  20. Guan D, Peters GP, Weber CL et al (2009) Journey to world top emitter: an analysis of the driving forces of China’s recent CO2 emissions surge. Geophys Res Lett 36(4):L04709CrossRefGoogle Scholar
  21. He JK, Chen WY, Wang ZY, Liu P, Wen ZG et al (2016) Climate change mitigation in China. Chin Sci Bull 61(10):1055–1062Google Scholar
  22. Huang R, Zhong ZQ, Song Y et al (2015) Measurements of regional sectoral embodied CO2 emissions: a case study of Beijing. Geogr Res 34(5):933–943Google Scholar
  23. Huang GH, Liu CJ, Xu ZH (2018) Carbon emission reduction potential and low-carbon development strategy in Yangtez River Economic Belt. Resour Environ Yangtze Basin 27(4):695–704Google Scholar
  24. IPCC (2006) IPCC Guidelines for National Greenhouse Gas Inventories. Available at www.ipcc-nggip.iges.or.jp/public/2006gl/index.html,2017-04-23
  25. Jiang H (2016) Implied carbon in trade between BRIC countries based on input- output modeling and structural decomposition. Resour Sci 38(12):2326–2337Google Scholar
  26. Kim YG, Yoo J, Oh W (2015) Driving forces of rapid CO2, emissions growth: a case of Korea. Energy Policy 82(1):144–155CrossRefGoogle Scholar
  27. Li H, Mu H, Zhang M, Li N (2011) Analysis on influence factors of China’s CO emissions based on Path–STIRPAT model. Energy Policy 39(11):6906–6911CrossRefGoogle Scholar
  28. Li L, Lei YL, He CY, Wu SM, Chen JB (2017) Study on the CO2 emissions embodied in the trade of China’s steel industry-based on the input-output model. Nat Hazards 86(3):989–1005CrossRefGoogle Scholar
  29. Li L, Lei YL, Wu SM, He CY, Chen JB, Yan D (2018) Impacts of city size change and industrial structure change on CO2 emissions in Chinese cities. J Clean Prod.  https://doi.org/10.1016/j.jclepro.05.208
  30. Lu WB, Qiu TT, Du L (2013) A study on influence factors of carbon emissions under different economic growth stages in China. Econ Res J (4):106–118Google Scholar
  31. Mi Z, Meng J, Guan D, Shan Y, Song M, Wei YM, Liu Z, Hubacek K (2017) Chinese CO2 emission flows have reversed since the global financial crisis. Nat Commun 8(1):1712CrossRefGoogle Scholar
  32. Minx JC, Baiocchi G, Peters GP, Weber CL, Guan D, Hubacek K (2011) A “Carbonizing Dragon”: China’s fast-growing CO2 emissions revisited. Environ Sci Technol 45(21):9144–9153CrossRefGoogle Scholar
  33. Pang J, Zhang JZ (2014) Carbon emissions embodied in Sino-EU trade and the influence factors: an analysis based on MRIO model and LMDI method. Int Econ Trade Res 30(11):51–65Google Scholar
  34. Peng SJ, Zhang WC, Song CW (2015) China’s production-based and consumption-based carbon emissions and their determinants. Econ Res J (1):168–182Google Scholar
  35. Peters GP, Weber CL, Guan D, Hubacek K (2007) China’s growing CO2 emissions: a race between increasing consumption and efficiency gains. Environ Sci Technol 41(17):5939–5944CrossRefGoogle Scholar
  36. Qi SJ, Zhang YB (2013) Research on the influencing factors and reduction strategies of carbon emission of construction industry in China. Soft Sci 27(6):39–43Google Scholar
  37. Román-Collado R, Colinet MJ (2018) Is energy efficiency a driver or an inhibitor of energy consumption changes in Spain? Two decomposition approaches ☆. Energy Policy 115:409–417CrossRefGoogle Scholar
  38. Rose A, Casler S (1996) Input-output structural decomposition analysis: a critical appraisal. Econ Syst Res 8(1):33–62CrossRefGoogle Scholar
  39. Su B, Ang BW (2012) Structural decomposition analysis applied to energy and emissions: some methodological developments. Energy Econ 34(1):177–188CrossRefGoogle Scholar
  40. Su B, Ang BW (2014) Input–output analysis of CO2, emissions embodied in trade: a multi-region model for China. Ecol Econ 71(24):42–53Google Scholar
  41. Su B, Ang BW (2017) Multiplicative structural decomposition analysis of aggregate embodied energy and emission intensities. Energy Econ:65Google Scholar
  42. Su B, Ang BW, Low M (2013) Input-output analysis of CO2 emissions embodied in trade and the driving forces: processing and normal exports. Ecol Econ 88:119–125CrossRefGoogle Scholar
  43. Su B, Ang BW, Li Y (2017) Input-output and structural decomposition analysis of Singapore’s carbon emissions. Energy Policy 105:484–492CrossRefGoogle Scholar
  44. Sun C, Ma T, Xu M (2018) Exploring the prospects of cooperation in the manufacturing industries between India and China: a perspective of embodied energy in India-China trade. Energy Policy 113:643–650CrossRefGoogle Scholar
  45. Vause J, Gao L, Shi L, Zhao J (2013) Production and consumption accounting of CO2, emissions for Xiamen, China. Energy Policy 60(6):697–704CrossRefGoogle Scholar
  46. Wang LL, Wang Y, Mao GZ et al (2012) Structure decomposition analysis of embodied carbon emissions for China’s international trade. Resour Sci 34(12):162–169Google Scholar
  47. Wang P, Wu W, Zhu B, Wei Y (2013) Examining the impact factors of energy-related CO2, emissions using the STIRPAT model in Guangdong Province, China. Appl Energy 106(11):65–71CrossRefGoogle Scholar
  48. Wang CJ, Zhang XL, Zhang HO et al (2016) Influencing mechanism of energy-related carbon emissions in Xinjiang based on IO-SDA model. Sci Geogr Sin 71(3):1105–1118Google Scholar
  49. Wang H, Ang BW, Su B (2017) Multiplicative structural decomposition analysis of energy and emission intensities: some methodological issues. Energy 123:47–63CrossRefGoogle Scholar
  50. Wu CY, Huang XJ, Chuai XW et al (2015a) Analysis of industrial structure adjustment and carbon reduction potential in Jiangsu Province: based on EIO-LCA model. Chin J Popul Resour Environ 25(4):43–51Google Scholar
  51. Wu C, Huang X, Yang H et al (2015b) Embodied carbon emissions of foreign trade under the global financial crisis: a case study of Jiangsu province, China. J Renew Sustain Energy 7(4):10288–10293Google Scholar
  52. Wu SM, Lei YL, Li ST, Li L (2018) Chinese provinces’ CO2 emissions embodied in imports and exports. Earth’s Future 6:867–881CrossRefGoogle Scholar
  53. Xi F, Geng Y, Chen X, Zhang Y, Wang X, Xue B, Dong H, Liu Z, Ren W, Fujita T, Zhu Q (2011) Contributing to local policy making on GHG emission reduction through inventorying and attribution: a case study of Shenyang, China. Energy Policy 39(10):5999–6010CrossRefGoogle Scholar
  54. Xu Y, Dietzenbacher E (2014) A structural decomposition analysis of the emissions embodied in trade. Ecol Econ 101(5):10–20CrossRefGoogle Scholar
  55. Zhang Y, Tang HY (2015) Research on China’s CO2 emissions embodied in trading and responsibility sharing: an example measurement from perspective of industrial chain. J Int Trade (4):148–156Google Scholar
  56. Zhang ZK, Guo JE, Anniwaer AMT (2011) Determination of each province’s carbon dioxide reduction target based on embodied carbon dioxide emissions. Chin J Popul Resour Environ 21(12):15–21Google Scholar
  57. Zhang Z, Guo J, Hewings GJ (2014) The effects of direct trade within China on regional and national CO2 emissions. Energy Econ 46:161–175CrossRefGoogle Scholar
  58. Zhang XY, Chen DJ, Zhu B et al (2016) A new eco-compensation mechanism for iron ore extraction based on multi-region input-output analysis. China Environ Sci 36(11):3449–3455Google Scholar
  59. Zhao YH, Liu Y (2015) Carbon emissions embodied in Russia’s foreign trade: an analysis based on input–output model. Int Bus (3):24–34Google Scholar
  60. Zhao YH, Tian Y, Liu Y (2014) Input-output analysis of carbon emissions embodied in India’s foreign trade. J Int Trade (10):77–87Google Scholar
  61. Zhong ZQ, He LY, Wang Z (2017) Geographic sources and the structural decomposition of emissions embodied in trade by Chinese megacities: the case of Beijing, Tianjin, Shanghai, and Chongqing. J Clean Prod 158:59–72CrossRefGoogle Scholar
  62. Zhong ZQ, Jiang L, Zhou P (2018) Transnational transfer of the emissions embodied in trade: characteristics and determinants from a spatial perspective. Energy 147:858–875CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Zhijian Chen
    • 1
  • Wen Ni
    • 1
  • Lantian Xia
    • 2
  • Zhangqi Zhong
    • 3
  1. 1.School of Economics and ManagementEast China Jiaotong UniversityNanchangChina
  2. 2.Faculty of International Tourism and ManagementCity University of MacauMacauChina
  3. 3.School of EconomicsZhejiang University of Finance & EconomicsHangzhouChina

Personalised recommendations