Uncertainty quantification of CO2 emissions from China's civil aviation industry to 2050

Lishan Yang; Yu-Jie Hu; Honglei Wang; Chengjiang Li; Bao-Jun Tang; Binli Wang; Hefu Cui

doi:10.1016/j.jenvman.2023.117624

Uncertainty quantification of CO₂ emissions from China's civil aviation industry to 2050

J Environ Manage. 2023 Jun 15:336:117624. doi: 10.1016/j.jenvman.2023.117624. Epub 2023 Mar 1.

Authors

Lishan Yang¹, Yu-Jie Hu², Honglei Wang³, Chengjiang Li¹, Bao-Jun Tang⁴, Binli Wang¹, Hefu Cui⁵

Affiliations

¹ School of Management, Guizhou University, Guiyang, Guizhou, 550025, China.
² School of Management, Guizhou University, Guiyang, Guizhou, 550025, China; Research Centre for Karst Region Development Strategy, Guizhou University, Guiyang, 550025, China. Electronic address: yjhu@gzu.edu.cn.
³ School of Management, Guizhou University, Guiyang, Guizhou, 550025, China; Key Laboratory of "Internet+" Collaborative Intelligent Manufacturing in Guizhou Provence, Guiyang, Guizhou, 550025, China.
⁴ School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China; Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China.
⁵ COMAC Beijing Aircraft Technology Research Institute, Beijing, 102211, China.

PMID: 36868152
DOI: 10.1016/j.jenvman.2023.117624

Abstract

To mitigate aviation's carbon emissions of the aviation industry, the following steps are vital: accurately quantifying the carbon emission path by considering uncertainty factors, including transportation demand in the post-COVID-19 pandemic period; identifying gaps between this path and emission reduction targets; and providing mitigation measures. Some mitigation measures that can be employed by China's civil aviation industry include the gradual realization of large-scale production of sustainable aviation fuels and transition to 100% sustainable and low-carbon sources of energy. This study identified the key driving factors of carbon emissions by using the Delphi Method and set scenarios that consider uncertainty, such as aviation development and emission reduction policies. A backpropagation neural network and Monte Carlo simulation were used to quantify the carbon emission path. The study results show that China's civil aviation industry can effectively help the country achieve its carbon peak and carbon neutrality goals. However, to achieve the net-zero carbon emissions goal of global aviation, China needs to reduce its emissions by approximately 82%-91% based on the optimal emission scenario. Thus, under the international net-zero target, China's civil aviation industry will face significant pressure to reduce its emissions. The use of sustainable aviation fuels is the best way to reduce aviation emissions by 2050. Moreover, in addition to the application of sustainable aviation fuel, it will be necessary to develop a new generation of aircraft introducing new materials and upgrading technology, implement additional carbon absorption measures, and make use of carbon trading markets to facilitate China's civil aviation industry's contribution to reduce climate change.

Keywords: Back propagation neural network; China'S civil aviation; Emission reduction pathway; Monte Carlo simulation; Uncertainty quantification.

MeSH terms

Aviation*
COVID-19* / prevention & control
Carbon / analysis
Carbon Dioxide / analysis
China
Economic Development
Humans
Pandemics
Uncertainty

Substances

Carbon Dioxide
Carbon