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China’s carbon emissions peaking pathway in the post-COVID-19 era

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Abstract

Several countries have weakened the carbon emission objectives to immediately revive the economy in the post-COVID-19 era. Therefore, it is a challenge worth addressing to readjust the economic development and carbon emissions after the COVID-19 pandemic. From the perspective of China’s carbon emissions, this study shapes a multi-objective dynamic optimization model based on the material capital input and R&D support aspects. The proposed model imitates China’s economic development, energy consumption, and carbon dioxide (CO2) emissions. The model provides theoretical suggestion for the government to revive economic development and reduce carbon emissions. In addition, this research paper compares the evolutionary path of carbon peak under the two scenarios. The first scenario requires maintaining the pre-epidemic development state and pace of carbon emission reduction, referred to as the baseline scenario (BS). The second scenario is termed the optimal scenario (OS) based on the model calculation. The study findings exhibit that China is not able to accomplish the 2030 CO2 emission peak objective, under the BS. However, China under the OS shall expectedly accomplish the 2030 carbon peak objective ahead of schedule, while the peak CO2 emissions shall be around 11.28 billion tons. Reportedly, at least 788 million tons of CO2 reduction contrasted with the BS. Furthermore, there is an 80.35% decline in energy intensity as compared to 2005. Consequently, the study results contribute theoretical guidance for the “green recovery” of China’s economy and the adjustment of carbon emission reduction’s path after the COVID-19 epidemic. Consistent with this, the research method also contributes to the theoretical research on carbon emissions at the national level while extending a new research perspective for the economic and environmental fields.

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Data Availability

The data that support the findings of this study are available from the corresponding author, [Shengyan Wang], upon reasonable request.

References

  • Ang BW, Liu FL et al (2003) Perfect decomposition techniques in energy and environmental analysis. Energy Policy 31(14):1561–1566

    Article  Google Scholar 

  • Beatriz Piderit, M, Vivanco F et al (2019) Net zero buildings-a framework for an integrated policy in Chile. Sustainability 11(5):1494. https://doi.org/10.3390/su11051494

  • Chen L, Msigwa G et al (2022) Strategies to achieve a carbon neutral society: a review. Environ Chem Lett 20(4):2277–2310

    Article  CAS  Google Scholar 

  • Chen Q, Wang Q et al (2023) Drivers and evolution of low-carbon development in China’s transportation industry: an integrated analytical approach. Energy 262:125614

    Article  CAS  Google Scholar 

  • Faubert, P, Bouchard S et al (2020) Achieving carbon neutrality for a future large greenhouse gas emitter in Quebec, Canada: a case study. Atmosphere 11(8):810. https://doi.org/10.3390/atmos11080810

  • He Y, Fu F et al (2021) Exploring the path of carbon emissions reduction in China’s industrial sector through energy efficiency enhancement induced by R&D investment. Energy 225:120208

    Article  CAS  Google Scholar 

  • Huang F, Zhou D et al (2019) Decomposition and attribution analysis of the transport sector’s carbon dioxide intensity change in China. Trans Res Part a: Policy Pract 119:343–358

    Google Scholar 

  • Jia S, Yang C et al (2022) Heterogeneous impact of land-use on climate change: study from a spatial perspective. Front Environ Sci 10:840603. https://doi.org/10.3389/fenvs

  • Leal Filho W, Setti AFF et al (2022) An overview of the interactions between food production and climate change. Sci Total Environ 838:156438. https://doi.org/10.1016/j.scitotenv.2022.156438

  • Li A, Zhang A et al (2017) Decomposition analysis of factors affecting carbon dioxide emissions across provinces in China. J Clean Prod 141:1428–1444

    Article  CAS  Google Scholar 

  • Li H, Qin Q (2019) Challenges for China’s carbon emissions peaking in 2030: a decomposition and decoupling analysis. J Clean Prod 207:857–865

    Article  Google Scholar 

  • Lin B, Benjamin NI (2017) Influencing factors on carbon emissions in China transport industry. A new evidence from quantile regression analysis. J Clean Prod 150:175–187

    Article  Google Scholar 

  • Lisitano IM, Biglia A et al (2018) Building for a zero carbon future: trade-off between carbon dioxide emissions and primary energy approaches. Energy Procedia 148:1074–1081

  • Liu M, Yang X et al (2023) Drivers of China’s carbon dioxide emissions: Based on the combination model of structural decomposition analysis and input-output subsystem method. Environ Impact Assess Rev 100:107043

    Article  Google Scholar 

  • Luo X and Lin T (2023) Probabilistic sea level rise hazard analysis based on the current generation of data and protocols. J Struct Eng 149(3):4022252

  • Maierhofer D, Roeck M et al (2022) Critical life cycle assessment of the innovative passive nZEB building concept ‘be 2226’ in view of net-zero carbon targets. Build Environ 223:109476

  • Matthews HD, Zickfeld K et al (2022) Temporary nature-based carbon removal can lower peak warming in a well-below 2 degrees C scenario. Commun Earth Environ 3(65). https://doi.org/10.1038/s43247-022-00391-z

  • Mi Z, Wei Y et al (2017) Socioeconomic impact assessment of China’s CO2 emissions peak prior to 2030. J Clean Prod 142:2227–2236

    Article  Google Scholar 

  • Pan X, Xu H et al (2021) Forecasting of industrial structure evolution and CO2 emissions in Liaoning Province. J Clean Prod 285:124870

    Article  CAS  Google Scholar 

  • Quan C, Cheng X et al (2020) Analysis on the influencing factors of carbon emission in China’s logistics industry based on LMDI method. Sci Total Environ 734:138473

    Article  CAS  Google Scholar 

  • Shan H (2008) Reestimating the capital stock of China: 1952~2006. J Quant Technol Econ 25(10):17–31

  • Sterman J, Moomaw W et al (2022) Does wood bioenergy help or harm the climate? Bull Atomic Sci 78(3):128–138

    Article  Google Scholar 

  • Sun L, Cui H et al (2022) Will China achieve its 2060 carbon neutral commitment from the provincial perspective? Adv Clim Chang Res 13(2):169–178

    Article  Google Scholar 

  • Varga J, Roeger W et al (2022) E-QUEST: a multisector dynamic general equilibrium model with energy and a model-based assessment to reach the EU climate targets. Econ Model 114:105911

  • Wang Z, Yang Y (2016) Features and influencing factors of carbon emissions indicators in the perspective of residential consumption: evidence from Beijing, China. Ecol Ind 61:634–645

    Article  CAS  Google Scholar 

  • Wu L, Zhao H et al (2022) Understanding of the effect of climate change on tropical cyclone intensity: a review. Adv Atmos Sci 39(2):205–221

    Article  Google Scholar 

  • Xin D, Ahmad M et al (2022) Impact of innovation in climate change mitigation technologies related to chemical industry on carbon dioxide emissions in the United States. J Clean Prod 379:134746

  • Xu S, He Z et al (2014) Factors that influence carbon emissions due to energy consumption in China: decomposition analysis using LMDI. Appl Energy 127:182–193

    Article  CAS  Google Scholar 

  • Yan M, Sun H et al (2022) Driving factors and key emission reduction paths of Xinjiang industries carbon emissions: an industry chain perspective. J Clean Prod 374:133879

    Article  CAS  Google Scholar 

  • Yang H, Li X et al (2021) Using system dynamics to analyse key factors influencing China’s energy-related CO2 emissions and emission reduction scenarios. J Clean Prod 320:128811

    Article  CAS  Google Scholar 

  • Yu S, Zhang Q et al (2023) Development of an extended STIRPAT model to assess the driving factors of household carbon dioxide emissions in China. J Environ Manage 325:116502

    Article  CAS  Google Scholar 

  • Yu S, Zheng S et al (2018) China can peak its energy-related carbon emissions before 2025: evidence from industry restructuring. Energy Econ 73:91–107

    Article  Google Scholar 

  • Zeng N, Jiang K et al (2022) The Chinese carbon-neutral goal: challenges and prospects. Adv Atmos Sci 39(8):1229–1238

    Article  Google Scholar 

  • Zeng Q, Ma F et al (2022) Policy uncertainty and carbon neutrality: evidence from China. Finance Res Lett 47:102771

  • Zhang S, Wang K et al (2021) Policy recommendations for the zero energy building promotion towards carbon neutral in Asia-Pacific Region. Energy Policy 159:112661

  • Zhang Y, Zhang X et al (2022) Robust optimization-based dynamic power generation mix evolution under the carbon-neutral target. Resour Conserv Recycl 178:106103

  • Zhang Y, Da Y (2015) The decomposition of energy-related carbon emission and its decoupling with economic growth in China. Renew Sustain Energy Rev 41:1255–1266

    Article  Google Scholar 

  • Zhao J, Jiang Q et al (2022) How does industrial structure adjustment reduce CO2 emissions? Spatial and mediation effects analysis for China. Energy Econ 105:105704

    Article  Google Scholar 

  • Zhou X, Zhang M et al (2017) A comparative study on decoupling relationship and influence factors between China’s regional economic development and industrial energy–related carbon emissions. J Clean Prod 142:783–800

    Article  CAS  Google Scholar 

  • Zhu Y, Wang Z (2014) Optimal R&D investment path for China to fulfill its emission intensity target and the corresponding economic growth path. Geogr Res 33(8):1406–1416

    Google Scholar 

  • Zou C, Xiong B et al (2021) The role of new energy in carbon neutral. Pet Explor Dev 48(2):480–491

    Article  Google Scholar 

Download references

Acknowledgements

The authors are grateful to the editors and reviewers for their helpful comments and suggestions.

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Authors and Affiliations

  1. School of Economics and Management, North China Electric Power University, Changping, Beijing, 102206, China

    Da Liu, Shengyan Wang, Xudong Zhao & Jiaying Wang

  2. Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University), Changping, Beijing, 102206, China

    Da Liu, Shengyan Wang, Xudong Zhao & Jiaying Wang

Authors
  1. Da Liu
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  2. Shengyan Wang
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  3. Xudong Zhao
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  4. Jiaying Wang
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Contributions

Da Liu: conceptualization, methodology. Shengyan Wang: formal analysis, data curation, writing—original draft. Xudong Zhao: software, visualization. Jiaying Wang: writing- reviewing and editing.

Corresponding author

Correspondence to Shengyan Wang.

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Responsible Editor: V.V.S.S. Sarma

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Liu, D., Wang, S., Zhao, X. et al. China’s carbon emissions peaking pathway in the post-COVID-19 era. Environ Sci Pollut Res 30, 100959–100978 (2023). https://doi.org/10.1007/s11356-023-29400-0

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