Skip to main content

Advertisement

SpringerLink
Log in

Urban carbon emission intensity under emission trading system in a developing economy: evidence from 273 Chinese cities

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

The international community has generally recognized the key role of developing countries’ cities in reducing carbon emissions, an elemental way to mitigate climate change. However, few have empirically analyzed the impact of market-based instruments such as emission trading system on urban carbon emissions in developing economies. This paper examines the effect of China’s pilot carbon trading markets, the first emission trading system in developing economies, on cities’ carbon intensity. We also explore the mechanism by which the emission trading system achieves its influence. The PSM-DID method is used to analyze the panel data including China’s 273 prefecture-level cities from 2010 to 2016. The results illustrate that the emission trading system significantly decreased pilot cities’ carbon intensity and this effect endured; as time progressed, the reduction effect was increasing. Through mediating effect analysis, we find that the emission trading system reduced the carbon intensity via increasing the proportion of tertiary industry output value in GDP and decreasing the energy intensity. Overall, the empirical results suggest that the Chinese government should drive the establishment and improvement of a national carbon market, proactively adjust industry structure, and consider the possible influence caused by the potential energy rebound effect.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Notes

  1. https://www.csis.org/analysis/urbanization-opportunity-and-development

  2. The pilot cities Beijing and Tianjin are deleted after PSM matching, so the 34 cities in the experimental group come from five pilot areas.

References

  • Ağralı S, Üçtuğ FG, Türkmen BA (2018) An optimization model for carbon capture & storage/utilization vs. carbon trading: a case study of fossil-fired power plants in Turkey. J Environ Manag 215:305–315

    Google Scholar 

  • Ali R, Bakhsh K, Yasin MA (2019) Impact of urbanization on CO2 emissions in emerging economy: evidence from Pakistan. Sustain Cities Soc 48:101553

    Google Scholar 

  • Berkhout PH, Muskens JC, Velthuijsen JW (2000) Defining the rebound effect. Energy Policy 28(6-7):425–432

    Google Scholar 

  • Bertrand M, Duflo E, Mullainathan S (2004) How much should we trust differences-in-differences estimates? Q J Econ 119(1):249–275

    Google Scholar 

  • Chen J, Gao M, Li D, Song M (2020) Analysis of the rebound effects of fossil and nonfossil energy in China based on sustainable development. Sustain Dev 28(1):235–246

    CAS  Google Scholar 

  • Cheng B, Dai H, Wang P, Xie Y, Chen L, Zhao D, Masui T (2016) Impacts of low-carbon power policy on carbon mitigation in Guangdong Province, China. Energy Policy 88:515–527

    Google Scholar 

  • Cheng Z, Li L, Liu J (2019) The effect of information technology on environmental pollution in China. Environ Sci Pollut Res 26(32):33109–33124

    Google Scholar 

  • Del Prete D, Ghins L, Magrini E, Pauw K (2019) Land consolidation, specialization and household diets: evidence from Rwanda. Food Policy 83:139–149

    Google Scholar 

  • Diaz-Rainey I, Tulloch DJ (2018) Carbon pricing and system linking: lessons from the New Zealand emissions trading scheme. Energy Econ 73:66–79

    Google Scholar 

  • Dong F, Dai Y, Zhang S, Zhang X, Long R (2019) Can a carbon emission trading scheme generate the Porter effect? Evidence from pilot areas in China. Sci Total Environ 653:565–577

    CAS  Google Scholar 

  • Gouldson A, Colenbrander S, Sudmant A, Papargyropoulou E, Kerr N, McAnulla F, Hall S (2016) Cities and climate change mitigation: economic opportunities and governance challenges in Asia. Cities 54:11–19

    Google Scholar 

  • Han F, Xie R, Fang J, Liu Y (2018) The effects of urban agglomeration economies on carbon emissions: evidence from Chinese cities. J Clean Prod 172:1096–1110

    Google Scholar 

  • Han Y (2020) Impact of environmental regulation policy on environmental regulation level: a quasi-natural experiment based on carbon emission trading pilot. Environ Sci Pollut Res 27:23602–23615. https://doi.org/10.1007/s11356-020-08658-8

    Article  CAS  Google Scholar 

  • Hannum C, Cutler H, Iverson T, Keyser D (2017) Estimating the implied cost of carbon in future scenarios using a CGE model: the case of Colorado. Energy Policy 102:500–511

    Google Scholar 

  • ICAP (2020) Global carbon market progress: 2020. Annual report. Berlin: International Carbon Action Partnership (ICAP)

  • IPCC (2014) IPCC fifth assessment synthesis report. Intergovernmental panel on climate change

  • Lee K, Melstrom RT (2018) Evidence of increased electricity influx following the regional greenhouse gas initiative. Energy Econ 76:127–135

    Google Scholar 

  • Lin B, Jia Z (2019) What will China's carbon emission trading market affect with only electricity sector involvement? A CGE based study. Energy Econ 78:301–311

    Google Scholar 

  • Meng S, Siriwardana M, McNeill J, Nelson T (2018) The impact of an ETS on the Australian energy sector: an integrated CGE and electricity modelling approach. Energy Econ 69:213–224

  • National Bureau of Statistics (NBS) (2011-2017a) China electric power statistical yearbook. China Electric Power Press, Beijing

  • National Bureau of Statistics (NBS) (2011-2017b) China energy statistical yearbook. China Statistics Press, Beijing

  • National Bureau of Statistics (NBS) (2011-2017c) China statistical yearbook. China Statistics Press, Beijing

  • National Bureau of Statistics (NBS) (2011-2017d) China urban statistical yearbook. China Statistics Press, Beijing

  • Nong D, Meng S, Siriwardana M (2017) An assessment of a proposed ETS in Australia by using the MONASH-Green model. Energy Policy 281–291

  • Richter JL, Mundaca L (2013) Market behavior under the New Zealand ETS. Carbon Manag 4(4):423–438

    CAS  Google Scholar 

  • Saeidi SP, Sofian S, Saeidi P, Saeidi SP, Saaeidi SA (2015) How does corporate social responsibility contribute to firm financial performance? The mediating role of competitive advantage, reputation, and customer satisfaction. J Bus Res 68(2):341–350

    Google Scholar 

  • Shao S, Huang T, Yang L (2014) Using latent variable approach to estimate China’s economy-wide energy rebound effect over 1954–2010. Energy Policy 72:235–248

    Google Scholar 

  • Sorrell S, Gatersleben B, Druckman A (2020) The limits of energy sufficiency: a review of the evidence for rebound effects and negative spillovers from behavioural change. Energy Res Soc Sci 64:101439

    Google Scholar 

  • Su W, Liu Y, Wang S, Zhao Y, Su Y, Li S (2018) Regional inequality, spatial spillover effects, and the factors influencing city-level energy-related carbon emissions in China. J Geogr Sci 28(4):495–513

    Google Scholar 

  • Tang K, Hailu A (2020) Smallholder farms’ adaptation to the impacts of climate change: evidence from China’s Loess Plateau. Land Use Policy 91:104353

    Google Scholar 

  • Tang K, Hailu A, Kragt ME, Ma C (2016a) Marginal abatement costs of greenhouse gas emissions: broadacre farming in the Great Southern Region of Western Australia. Aust J Agric Resour Econ 60(3):459–475

    Google Scholar 

  • Tang K, Hailu A, Kragt ME, Ma C (2018) The response of broadacre mixed crop-livestock farmers to agricultural greenhouse gas abatement incentives. Agric Syst 160:11–20

    Google Scholar 

  • Tang K, Hailu A, Yang Y (2020a) Agricultural chemical oxygen demand mitigation under various policies in China: a scenario analysis. J Clean Prod 250:119513

    CAS  Google Scholar 

  • Tang K, He C, Ma C, Wang D (2019) Does carbon farming provide a cost-effective option to mitigate GHG emissions? Evidence from China. Aust J Agric Resour Econ 63(3):575–592

    Google Scholar 

  • Tang K, Kragt ME, Hailu A, Ma C (2016b) Carbon farming economics: what have we learned? J Environ Manag 172:49–57

    Google Scholar 

  • Tang K, Qiu Y, Zhou D (2020b) Does command-and-control regulation promote green innovation performance? Evidence from China's industrial enterprises. Sci Total Environ 712:136362

    CAS  Google Scholar 

  • Tang K, Xiong C, Wang Y, Zhou D (2020c) Carbon emissions performance trend across Chinese cities: evidence from efficiency and convergence evaluation. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-020-10518-4

  • Tang K, Yang L, Zhang J (2016) Estimating the regional total factor efficiency and pollutants’ marginal abatement costs in China: a parametric approach. Appl Energy 184:230–240

    CAS  Google Scholar 

  • UN DESA (2014) World urbanization prospects: the 2014 revision. United Nations Department of Economic and Social Affairs, Population Division

  • Wang H, Chen Z, Wu X, Nie X (2019) Can a carbon trading system promote the transformation of a low-carbon economy under the framework of the porter hypothesis? Empirical analysis based on the PSM-DID method. Energy Policy 129:930–938

    Google Scholar 

  • Weng Q, Xu H (2018) A review of China’s carbon trading market. Renew Sust Energ Rev 91:613–619

    Google Scholar 

  • Wu J, Ma C, Tang K (2019) The static and dynamic heterogeneity and determinants of marginal abatement cost of CO2 emissions in Chinese cities. Energy 178:685–694

    Google Scholar 

  • Xing L, Wei T, Zhuo Y, Li G (2020) Assessment of the optimal rebound effects from energy intensity reduction. J Clean Prod 251:119668

    Google Scholar 

  • Yang L, Tang K, Wang Z, An H, Fang W (2017) Regional eco-efficiency and pollutants' marginal abatement costs in China: a parametric approach. J Clean Prod 167:619–629

    Google Scholar 

  • Yang L, Yang Y, Zhang X, Tang K (2018) Whether China's industrial sectors make efforts to reduce CO2 emissions from production? A decomposed decoupling analysis. Energy 160:796–809

    Google Scholar 

  • Zang J, Wan L, Li Z, Wang C, Wang S (2020) Does emission trading scheme have spillover effect on industrial structure upgrading? Evidence from the EU based on a PSM-DID approach. Environ Sci Pollut Res 27:12345–12357

    Google Scholar 

  • Zhang W, Zhang N, Yu Y (2019a) Carbon mitigation effects and potential cost savings from carbon emissions trading in China's regional industry. Technol Forecast Soc Chang 141:1–11

    Google Scholar 

  • Zhang K, Xu D, Li S, Zhou N, Xiong J (2019b) Has China’s pilot emissions trading scheme influenced the carbon intensity of output? Int J Environ Res Public Health 16(10):1854

    CAS  Google Scholar 

  • Zhang H, Duan M, Deng Z (2019c) Have China’s pilot emissions trading schemes promoted carbon emission reductions? The evidence from industrial sub-sectors at the provincial level. J Clean Prod 234:912–924

    Google Scholar 

  • Zhang YJ, Wei YM (2010) An overview of current research on EU ETS: evidence from its operating mechanism and economic effect. Appl Energy 87(6):1804–1814

    Google Scholar 

  • Zhang Y, Zhang J (2019) Estimating the impacts of emissions trading scheme on low-carbon development. J Clean Prod 238:117913

    CAS  Google Scholar 

  • Zhao H, Geng G, Zhang Q et al (2019) Inequality of household consumption and air pollution-related deaths in China. Nat Commun 10(1):1–9

    Google Scholar 

  • Zheng J, Mi Z, Coffman DM, Milcheva S, Shan Y, Guan D, Wang S (2019) Regional development and carbon emissions in China. Energy Econ 81:25–36

    Google Scholar 

  • Zhou B, Zhang C, Song H, Wang Q (2019a) How does emission trading reduce China’s carbon intensity? An exploration using a decomposition and difference-in- differences approach. Sci Total Environ 676:514–523

    CAS  Google Scholar 

  • Zhou D, Liang X, Zhou Y, Tang K (2020) Does emission trading boost carbon productivity? Evidence from China’s pilot emission trading scheme. Int J Environ Res Public Health 17(15):5522

    CAS  Google Scholar 

  • Zhou D, Zhou F, Wang X (2019b) Impact of low-carbon pilot policy on the performance of urban carbon emissions and its mechanism. Resour Sci 41(3):546–556

    Google Scholar 

Download references

Funding

This research was supported by the Humanities and Social Science Fund of Ministry of Education of China (20YJCZH144, 20YJC790191), Guangdong Basic and Applied Basic Research Foundation (2019A1515010884), Natural Science Foundation of Guangdong Province (2018A030310025, 2018A030310044), and Pearl River Talents Plan of Guangdong Province (20170133).

Author information

Authors and Affiliations

  1. School of Economics and Trade, Guangdong University of Foreign Studies, Guangzhou, 510006, China

    Kai Tang

  2. Department of Accounting and Finance, Lancaster University, Lancaster, LA1 4YW, UK

    Yichun Liu

  3. School of Mathematics and Statistics, Guangdong University of Foreign Studies, Guangzhou, 510006, China

    Di Zhou

  4. School of Business, Guangdong University of Foreign Studies, Guangzhou, 510006, China

    Yuan Qiu

Authors
  1. Kai Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yichun Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Di Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuan Qiu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: Kai Tang, Yichun Liu, and Di Zhou; methodology: Yichun Liu and Di Zhou; formal analysis and investigation: Kai Tang and Yichun Liu; writing—original draft preparation: Kai Tang, Yichun Liu, Di Zhou, and Yuan Qiu; writing—review and editing: Kai Tang and Yuan Qiu; funding acquisition: Kai Tang and Di Zhou; resources: Kai Tang and Di Zhou; supervision: Kai Tang.

Corresponding author

Correspondence to Di Zhou.

Ethics declarations

Competing interests

The authors declare that they have no competing interests.

Ethical approval

Not applicable

Consent to participate

Not applicable

Consent to publish

Not applicable

Additional information

Responsible Editor: Nicholas Apergis

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

Table 6 List of the 34 cities in the pilot areas
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tang, K., Liu, Y., Zhou, D. et al. Urban carbon emission intensity under emission trading system in a developing economy: evidence from 273 Chinese cities. Environ Sci Pollut Res 28, 5168–5179 (2021). https://doi.org/10.1007/s11356-020-10785-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-020-10785-1

Keywords

Search

Navigation