Bayesian Vector Autoregression Analysis of Chinese Coal-Fired Thermal Power Plants

Ning Zhang, Haisheng Li

Research output: Contribution to journalArticlepeer-review

Abstract

Considering the dataset of information related to Chinese coal-fired thermal power plants during the 2005–2017 period, we initially investigated the orthogonalized response of the carbon emission to energy consumption and power generation by using Bayesian vector autoregressions and feedback solutions for impulse control technology. The results showed that the effects of energy consumption and power generation on carbon emissions were significant. The Chinese government has launched a program aimed at curbing carbon emission peaks and neutralizing or decreasing carbon emissions. The causal relationship concludes that China still needs further investment in emission abatement, improvement related to the level of openness to the outside world, and the strengthening of the construction of green zones for industrial transfer to mitigate carbon emissions.

Original languageEnglish
Article number8447
JournalSustainability (Switzerland)
Volume16
Issue number19
DOIs
Publication statusPublished - 2024 Oct

Bibliographical note

Publisher Copyright:
© 2024 by the authors.

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Environmental Science (miscellaneous)
  • Energy Engineering and Power Technology
  • Hardware and Architecture
  • Computer Networks and Communications
  • Management, Monitoring, Policy and Law

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