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Time-series analysis of the contributors and drivers of Zhejiang’s carbon emissions and intensity since China’s accession to the WTO

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Abstract

Carbon abatement efforts in China are penetrating to sub-national level. Zhejiang province, as the 4th wealthy region in China and important player in global market (e.g., textiles, cloth, petroleum, and chemical products), lacks in-depth study of its climate change mitigation efforts, especially after China’s accession to the WTO in 2001. This paper analyzed carbon emissions and intensity in Zhejiang province using most comprehensive and time-series dataset available to date since 2002. Its carbon emissions were growing at a declining speed, and carbon intensity was almost halved. The leading emitters largely agglomerate around Hangzhou Bay, close to Zhoushan Port and Shanghai Port. The growth in absolute emissions primarily arose from higher investment (323.1 Mt) and exports (280.6 Mt), while the slower growth was mainly due to efficiency improvements (− 245.7 Mt) stemming from energy and carbon abatement policies and inflows of emission-intensive products from the rest of China. Similarly, declined carbon intensity was mainly attributed to efficiency improvement. Major contributors were sector S13-Non-metallic minerals, S12-Chemicals, S26-Transport, storage and post, S07-Textiles, and S10-Paper. Economic restructuring played different roles on emissions and intensity during various development stages. Policy implications of the findings are discussed for future developments.

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Fig. 1

Source: ZJBS 2022. b Zhejiang’s carbon emissions and intensity, 1995–2020. Source: ZJBS, 2022; NBSC, 1996–2021

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Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. All data generated or analyzed during this study are included in this article.

Notes

  1. The literature review was done by the authors. Table 4 in the appendix lists the papers that conducted IOA or SDA.

  2. https://m.bjx.com.cn/mnews/20210824/1172003.shtml

References

  • Ang BW, Su B, Wang H (2016) A spatial-temporal decomposition approach to performance assessment in energy and emissions. Energy Economics 60:112–121

    Article  Google Scholar 

  • CSC (2021a) Outline of the 14th five-year plan (2021a-2025) for national economic and social development and the long-range objectives through the year 2035. http://www.gov.cn/xinwen/2021a-03/13/content_5592681.htm

  • CSC (2021b) Responding to climate change: China’s policies and actions. http://english.scio.gov.cn/m/whitepapers/2021b-10/27/content_77836502_3.htm

  • Dong G, Mao XQ, Zhou J, Zeng A (2013) Carbon footprint accounting and dynamics and the driving forces of agricultural production in Zhejiang Province, China. Ecol Econ 91:38–47

    Article  Google Scholar 

  • Dong G, Wang Z, Mao X (2018) Production efficiency and GHG emissions reduction potential evaluation in the crop production system based on emergy synthesis and nonseparable undesirable output DEA: a case study in Zhejiang Province, China. Plos One 13:e0206680

    Article  Google Scholar 

  • HUBS, 2021. Huzhou Statistical Yearbook 2021. Huzhou Bureau of Statistics.

  • HZBS (2021) Hangzhou Statistical Yearbook 2021. Hangzhou Bureau of Statistics

  • IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Intergovernmental Panel on Climate Change

  • JHBS (2021) **hua Statistical Yearbook 2021. **hua Bureau of Statistics

  • JXBS, 2021. Jiaxing Statistical Yearbook 2021. Jiaxing Bureau of Statistics.

  • Leontief W (1970) Environmental repercussions and the economic structure: an input-output approach. Rev Econ Stat 52:262–271

    Article  Google Scholar 

  • LSBS (2021) Lishui Statistical Yearbook 2021. Lishui Bureau of Statistics

  • NBBS (2021) Ningbo Statistical Yearbook 2021. Ningbo Bureau of Statistics

  • NBSC (2020) China Energy Statistical Yearbook 2020. National Bureau of Statistics of China

  • NBSC (2021) China Statistical Yearbook 2021. National Bureau of Statistics of China

  • Li YZ, Su B (2017) The impacts of carbon pricing on coastal megacities: a CGE analysis of Singapore. J Clean Prod 165:1239–1248

  • Li DR, Lei YL, Li L, Liu LN (2020) Study on industrial selection of counterpart cooperation between Jilin Province and Zhejiang Province in China from the perspective of low carbon. Environ Sci Pollut Res 27:16668–16676

    Article  CAS  Google Scholar 

  • Qing G, Luo Y, Huang W, Wang W, Yue Z, Wang J, Li Q, Jiang S, Sun S (2021) Driving factors of energy consumption in the developed regions of develo** countries: a case of Zhejiang Province, China. Atmosphere 12:1196

    Article  CAS  Google Scholar 

  • QZBS, 2021. Quzhou Statistical Yearbook 2021. Quzhou Bureau of Statistics.

  • Shan YL, Guan DB, Zheng HR, Ou JM, Li Y, Meng J, Mi ZF, Liu Z, Zhang Q (2018) Data Descriptor: China CO2 Emission Accounts 1997–2015. Sci Data 5

  • Su B, Ang BW (2010) Input-output analysis of CO2 emissions embodied in trade the effects of spatial aggregation. Ecol Econ 70:10–18

    Article  Google Scholar 

  • Su B, Ang BW (2012) Structural decomposition analysis applied to energy and emissions: some methodological developments. Energy Economics 34:177–188

    Article  Google Scholar 

  • Su B, Ang BW (2013) Input-output analysis of co2 emissions embodied in trade: competitive versus non-competitive imports. Energy Policy 56:83–87

    Article  Google Scholar 

  • Su B, Ang BW (2014) Attribution of changes in the generalized fisher index with application to embodied emission studies. Energy 69:778–786

    Article  Google Scholar 

  • Su B, Ang BW (2017) Multiplicative structural decomposition analysis of aggregate embodied energy and emission intensities. Energy Economics 65:137–147

    Article  Google Scholar 

  • Su B, Huang HC, Ang BW, Zhou P (2010) Input-output analysis of CO2 emissions embodied in trade: the effects of sector aggregation. Energy Econ 32:166–175

  • SXBS (2021) Shaoxing Statistical Yearbook 2021. Shaoxing Bureau of Statistics

  • TZBS (2021) Taizhou Statistical Yearbook 2021. Taizhou Bureau of Statistics

  • UNFCCC (2021a) China’s achievements, new goals and new measures for nationally determined contributions. United Nations Framework Convention on Climate Change

  • UNFCCC (2021b) United Nations climate change annual report 2020. United Nations Framework Convention on Climate Change

  • Wang F, Xu H (2021) Decoupling elasticity of carbon emissions and economic growth of transportation industry in Zhejiang Province and its influencing factors. J Environ Prot Ecol 22:750–759

    Google Scholar 

  • Weber CL, Peters GP, Guan D, Hubacek K (2008) The contribution of chinese exports to climate change. Energy Policy 36:3572–3577

    Article  Google Scholar 

  • WTO (2021) World trade statistical review 2021. World Trade Organization

  • Wu CF, Li G, Yue WZ, Lu RC, Lu ZW, You HY (2015) Effects of endogenous factors on regional land-use carbon emissions based on the grossman decomposition model: a case study of Zhejiang Province, China. Environ Manage 55:467–478

    Article  Google Scholar 

  • Wu X, Del Valle TM, Zheng L, Shi Y, Du Y, Luo W (2021) Temporal changes in sectoral carbon productivity and corresponding driving factors: implications for carbon governance in Zhejiang Province. Journal of Chinese Governance.

  • WZBS (2021) Wenzhou Statistical Yearbook 2021. Wenzhou Bureau of Statistics

  • **a CY, Li Y, Ye YM, Shi Z, Liu JM (2017) Decomposed driving factors of carbon emissions and scenario analyses of low-carbon transformation in 2020 and 2030 for Zhejiang Province. Energies 10:1747

    Article  Google Scholar 

  • Yan JN, Su B (2020) What drive the changes in China’s energy consumption and intensity during 12th five-year plan period? Energy Policy 140:111383

    Article  Google Scholar 

  • Yang LX, **a H, Zhang XL, Yuan SF (2018) What matters for carbon emissions in regional sectors? A China study of extended STIRPAT model. J Clean Prod 180:595–602

    Article  Google Scholar 

  • ZDRC (2021) Zhejiang’s 14th five-year plan for climate change. https://fzggw.zj.gov.cn/art/2021/6/16/art_1229123366_2302792.html.

  • Zheng S, Shan JM, Singh RP, Wu YZ, Pan JC, Wang YS, Lichtfouse E (2020) High spatio-temporal heterogeneity of carbon footprints in the Zhejiang Province, China, From 2005 to 2015: implications for climate change policies. Environ Chem Lett 18:931–939

    Article  CAS  Google Scholar 

  • Zhu E, Deng J, Zhou M, Gan M, Jiang R, Wang K, Shahtahmassebi A (2019) Carbon emissions induced by land-use and land-cover change from 1970 to 2010 in Zhejiang, China. Sci Total Environ 646:930–939

  • ZJBS (2022) Zhejiang Statistical Yearbook 2022. Zhejiang Bureau of Statistics

  • ZPG (2010) Zhejiang’s strategies to tackle climate change. https://www.zj.gov.cn/art/2012/8/17/art_1229621583_64009.html

  • ZSBS (2021) Zhoushan Statistical Yearbook 2021.Zhoushan Bureau of Statistics

Download references

Funding

The authors are grateful for financial supports from the National Natural Science Foundation of China (No. 72004200), the National Key Research and Development Program of China (No. 2020YFA0608604), and the Zhejiang Provincial Philosophy and Social Sciences Planning Project (No. 21YJRC05-1YB).

Author information

Authors and Affiliations

  1. School of Public Affairs, Zhejiang University, Hangzhou, 310058, People’s Republic of China

    Yingzhu Li & Yingchao Lin

  2. Energy Studies Institute, National University of Singapore, Singapore, 119620, Singapore

    Bin Su

  3. Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, 117576, Singapore

    Bin Su

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  1. Yingzhu Li
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  2. Yingchao Lin
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  3. Bin Su
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Contributions

All authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by Yingzhu Li, Yingchao Lin, and Bin Su. The first draft of the manuscript was written by Yingzhu Li, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Bin Su.

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Appendices

Appendix 1. Selected literature review

See Table 4

Table 4 IOA and SDA studies on carbon emissions in Chinese provinces or multiplicities
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Appendix 2. Sectoral classifications

See Table 5

Table 5 Sectoral classifications
Full size table

Appendix 3. Additive total emission intensity effect by sector

See Tables 6 and 7

Table 6 The additive total emission intensity effect by sector from the production side (Mt-CO2)
Full size table
Table 7 The additive total emission intensity effect by sector from the consumption side (Mt-CO2)
Full size table

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Li, Y., Lin, Y. & Su, B. Time-series analysis of the contributors and drivers of Zhejiang’s carbon emissions and intensity since China’s accession to the WTO. Environ Sci Pollut Res 30, 46913–46932 (2023). https://doi.org/10.1007/s11356-023-25550-3

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