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Article | Open Access | Online First

Tracking greenhouse gas emissions in Chinese value chains with an interprovincial input–output model

Alun Gu1( )Xiaoyu Zhou1Qiaowen Chen2Yahong Dong3
Institute of Energy, Environment and Economy, Tsinghua University, Beijing 100084, China
School of Management, China Institute for Studies in Energy Policy, Xiamen University, Xiamen 361005, China
Macau Environmental Research Institute, Macau University of Science and Technology, Macao 999078, China
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Abstract

China’s carbon emission growth patterns exhibit marked regional differences, mainly caused by heterogeneities in initial resource endowment, economic scale, industrial structure, development stage, and international connections. To better characterize embodied greenhouse gas (GHG) emission patterns and their importance for interprovincial and industrial value chains in China, we analyzed the temporal and regional-scale spatial relationships between value-added and production-based GHG emissions in domestic value chains in 2012, 2015, and 2017 using an interprovincial input–output framework and accounting for interprovincial economic development correlations. The results demonstrate a gradually increasing flow of value-added GHG emissions within interprovincial value chains in the current interprovincial economic context. Within Chinese national value chains, the value-added emissions increased in Beijing–Tianjin and coastal areas, concurrently with decreasing local production-based emissions. Additionally, temporal evolution of provincial statuses and roles occurred within the value chains. Specifically, the roles of Shandong and Guangdong Provinces gradually evolved from suppliers to consumers of value-added emissions, indicating upgraded industries. Finally, the analysis of value-added industrial emissions showed partial decoupling between provinces, induced by the transformation and development of specific industries, emphasizing the need for close monitoring of industrially produced value-added GHG emissions in some provinces.

References

[1]
IEA, CO2 emissions from fuel combustion. 2020. http://www.iea.org/t&c/termsandconditions/
[2]
Progress on the Implementation of China′s Nationally Determined Contributions. (2022). (In Chinese). Available on https://www.gov.cn/xinwen/2022-11/12/5726372/files/b01ead68146e4dc293b1b4463be2eb20.pdf.
[3]
Xinhua Net. Xi Jinping delivered an important speech in the general debate of the 75th session of the United Nations General Assembly [EB/OL]. (2020-09-22). http://www.gov.cn/xinwen/2020-09/22/content_5546168.htm.
[4]
Xinhua News Agency. Proposals of the central committee of the communist party of China (CPC) on the formulation of the 14th Five-Year Plan (2021–2025) for national economic and social development and long-range objectives through the Year 2035 [EB/OL]. (2020-11-03). http://www.gov.cn/zhengce/2020-11/03/content_5556991.htm.
[5]

Liu, Z., Davis, S. J., Feng, K., et al. (2016). Targeted opportunities to address the climate–trade dilemma in China. Nature Climate Change, 6: 201–206.

[6]
Deng, R., Yang, G. (2018). Does interregional trade lead to interregional carbon emissions transfer? An empirical analysis based on interregional input-output tables from 2002 to 2012. Journal of Nanjing University of Finance and Economics, 2018(3): 1–11. (In Chinese).
[7]
Solomon, S., Qin, D. H., Manning, M., et al. (2007). Technical summary. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Solomon, S., Qin, D., Manning, M., et al. Eds. Cambridge University Press.
[8]
Stock, T., Qin, D. H., Plattner, G., et al. (2013). Technical summary. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Stock, T., Qin, D. H., Plattner, G., et al. Eds. Cambridge University Press.
[9]
CCSP. (2007). Synthesis and assessment product 2.1: Scenarios of greenhouse gas emissions and atmospheric concentrations (Part A) and review of integrated scenario development and application (Part B). Report. Climate Change Science Program and the Subcommittee on Global Change Research. Department of Energy, Office of Biological & Environmental Research, Washington DC, USA.
[10]
Weyant, J. P. (2009). EMF 22: Climate change control scenarios. In: Energy Modeling Forum, Stanford University, Stanford, California, USA.
[11]
Hu, J. T. (2012). Advance firmly along the path of socialism with Chinese characteristics and strive for the moderate prosperity in all respects: Report to the 18th National Congress of the Communist Party of China. Beijing: People’s Publishing House.
[12]
Xi, J. P. (2017). Secure a decisive victory in building a moderately prosperous society in all respects and win the great victory of socialism with Chinese characteristics in the new era: Report at the 19th National Congress of the Communist Party of China. Beijing: People’s Publishing House.
[13]
Department of Climate Change. National development and reform commission, People’s Republic of China. (2015). Enhanced actions on climate change: China’s intended nationally determined contributions. (In Chinese).
[14]
Krugman, P. (1995). Chapter 24 Increasing returns, imperfect competition and the positive theory of international trade. In: Handbook of International Economics. Amsterdam: Elsevier, 1243–1277.
[15]
Pan, W. Q., Li, G. Q. (2018). National value chain and global value chain in Chinese regions: Regional interaction and value-added gains. Economic Research Journal, 53(3): 171–186.
[16]
Zhang, S. J. (2009). Global value chain and national value chain-new method based on input-output table. Journal of International Trade, (4): 108–113.
[17]
Zhang, S. J., Liu, Z. B. (2013). Whether domestic value chains are linked to global value chains? An empirical analysis based on a simultaneous equation model. Journal of International Trade, 2013(2): 14–27.
[18]
Deng, G. Y. (2019). Research on the accounting and network characteristics of value added in China’s trade under global value chains. Journal of Capital University of Economics and Business, 21(5): 34–44.
[19]

Koopman, R., Wang, Z., Wei, S. J. (2014). Tracing value-added and double counting in gross exports. American Economic Review, 104: 459–494.

[20]

Li, G., Pan, W. (2016). How do domestic value chains embed into global value chains? Perspective from value added. China Industrial Economy, 7: 10–22.

[21]

Liu, H., Liu, W., Fan, X., et al. (2015). Carbon emissions embodied in value added chains in China. Journal of Cleaner Production, 103: 362–370.

[22]

Mi, Z., Meng, J., Green, F., et al. (2018). China’s “exported carbon” peak: Patterns, drivers, and implications. Geophysical Research Letters, 45: 4309–4318.

[23]
Meng, B., Peters, G. P., Wang, Z., et al. (2018). Tracing CO2 emissions in global value chains. Energy Economics, 73: 24–42.
[24]

Zhan, L., Lei, Y., Li, L., et al. (2019). Interprovincial transfer of ecological footprint among the region of Jing-Jin-Ji and other provinces in China: A quantification based on MRIO model. Journal of Cleaner Production, 225: 304–314.

[25]
Yuan, L. (2017). Research on coordinated development of regional economy in Jiangsu Province from a value chain division perspective. Dissertation. Nanjing University of Finance and Economics.
[26]
Zheng, K. (2019). Research on transfer of embedded carbon emissions in trade and coordinated carbon reduction in Beijing-Tianjin-Hebei region. Dissertation. Capital University of Economics and Business.
[27]

Johnson, R. C., Noguera, G. (2012). Accounting for intermediates: Production sharing and trade in value added. Journal of International Economics, 86: 224–236.

[28]
Xie, H. (2018). Research on the impact of the embedment of global value chains on China’s carbon emissions and productivity. Dissertation. Chongqing University.
[29]

Timmer, M. P., Erumban, A. A., Los, B., et al. (2014). Slicing up global value chains. Journal of Economic Perspectives, 28: 99–118.

[30]

Liang, S., Qu, S., Zhu, Z. et al. (2017). Income-based greenhouse gas emissions of nations. Environmental Science & Technology, 51: 346–355.

[31]
Lu, P. P., Gong, W. P. (2015). Review on research progress of carbon emissions embodied of measurement method in international trade. Review of Industrial Economics, (6): 82–90.
[32]
Xiang, S. J., Wen, T. (2014). Re-measurement of embodied carbon emissions in China’s foreign trade: Based on the perspective of statistics on new value-added trade. International Economics and Trad Research, 30(12):17–29.
[33]

Leontief, W. (1970). Environmental repercussions and the economic structure: An input−output approach. The Review of Economics and Statistics, 52: 262.

[34]
Wang, X. L., Ren, C. Y. (2018). Embodied carbon emission calculating based upon MRIO model in Northwest China. China Coal, 44(8): 11–16.
[35]

Liu, H., Fan, X. (2017). Value-added-based accounting of CO2 emissions: A multi-regional input-output approach. Sustainability, 9: 2220.

[36]

Zheng, H., Zhang, Z., Wei, W., et al. (2020). Regional determinants of China’s consumption-based emissions in the economic transition. Environmental Research Letters, 15: 074001.

[37]
IPCC. (2006). IPCC Guidelines for national greenhouse gas inventories, Institute for Global Environmental Strategies (IGES).
[38]
National Development and Reform Commission’s Department of Climate Change. (2014). Research on China’s Greenhouse Gases Inventory: 2005. China Environmental Press.
Energy and Climate Management
Cite this article:
Gu A, Zhou X, Chen Q, et al. Tracking greenhouse gas emissions in Chinese value chains with an interprovincial input–output model. Energy and Climate Management, 2024, https://doi.org/10.26599/ECM.2024.9400001

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Received: 04 September 2023
Revised: 19 December 2023
Accepted: 19 February 2024
Published: 18 April 2024
© The author(s) 2024.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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