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Carbon emission reduction analysis for cloud computing industry: Can carbon emissions trading and technology innovation help?

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  • Yu, Xianyu
  • Hu, Yuezhi
  • Zhou, Dequn
  • Wang, Qunwei
  • Sang, Xiuzhi
  • Huang, Kai

Abstract

The emerging cloud computing industry (CCI) has become an important source of carbon emissions; therefore, choosing an appropriate carbon emission reduction strategy is of key importance. Based on two important alternative carbon reduction strategies, namely carbon emissions trading (CET) and emission reduction technological innovation (ERTI), in this paper, a scenario-based simulation model of carbon emission reduction strategies is established for the CCI of China. Based on different derivative scenarios of CET and ERTI strategies, 22 carbon reduction strategy scenarios are designed and subjected to simulation analysis. Then, a slacks-based model that considers undesirable output is constructed and used to evaluate the comprehensive effect of proposed carbon reduction strategy scenarios. Based on the evaluation results of the strategy scenarios, a tolerant CET strategy scenario with a high free quota ratio and a low carbon trading price has the potential to reverse the increasing trend of carbon emissions. This tolerant strategy scenario can also achieve a more efficient carbon emission reduction result for the CCI in the long run. In terms of technology innovation, the strong promotion of installed zero‑carbon capacity and negative emission technology applications can effectively promote the reduction of carbon emissions. The results of this analysis show that the carbon emission reduction strategy with tolerant CET and strong ERTI will contribute to the healthy development of the CCI.

Suggested Citation

  • Yu, Xianyu & Hu, Yuezhi & Zhou, Dequn & Wang, Qunwei & Sang, Xiuzhi & Huang, Kai, 2023. "Carbon emission reduction analysis for cloud computing industry: Can carbon emissions trading and technology innovation help?," Energy Economics, Elsevier, vol. 125(C).
    • Handle: RePEc:eee:eneeco:v:125:y:2023:i:c:s014098832300302x
    DOI: 10.1016/j.eneco.2023.106804
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