4.7 Article

Regional carbon imbalance within China: An application of the Kaya-Zenga index

Journal

JOURNAL OF ENVIRONMENTAL MANAGEMENT
Volume 262, Issue -, Pages -

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2020.110378

Keywords

Carbon emissions; Carbon intensity; Carbon imbalance; Kaya-Zenga index; Scenario analysis; China

Funding

  1. National Natural Science Foundation of China [71922015, 71773075, 71525006, 71533004]
  2. Cheung Kong Scholars Program
  3. Major Project of National Social Science Foundation of China [18ZDA051]
  4. Shanghai Philosophy and Social Science Fund Project [2019BJB001]
  5. Shanghai Post-doctoral Excellence Program
  6. Two Service Action Plans of Shanghai University of Finance and Economics [2019110191]
  7. National Top-Notch Young Talent Support Program of China
  8. Shanghai Leading Talent Project

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Considering the enlarging inter-provincial disparities in China as regards carbon emissions and carbon intensity (carbon emissions per unit gross domestic product), this paper is the first study to investigate the inter-provincial carbon imbalance by constructing and employing the Kaya-Zenga index. We use China's panel data of provincial-level carbon emissions over 1995-2016 to quantitatively measure the levels of inter-provincial imbalance and polarization in carbon emissions and carbon intensity. Further, we decompose the Kaya-Zenga index into different contributing factors both regionally and structurally and perform a scenario analysis to identify the corresponding regionally differentiated countermeasures regarding carbon emission reduction. The results show that the imbalance in carbon emissions is mainly caused by imbalances in population scale and income level, while the imbalance in carbon intensity predominantly results from imbalances in energy efficiency and energy mix. In addition, for heavy manufacturing provinces, the respective emission-reduction strategy should aim at lowering energy intensity through local technology improvement and inter-regional technology transfer. For light manufacturing and high technology provinces, carbon emission reduction is harder to be achieved; however, a mix of policies of improving energy efficiency, optimizing energy mix, and industrial upgrading should be implemented. The results of the scenario analysis indicate that reducing imbalance in carbon intensity under different scenarios can lead to a substantial reduction in carbon emissions (up to 10%).

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