Prediction of Carbon Peak in Shaanxi Province and Its Cities
- DOI
- 10.2991/978-94-6463-200-2_97How to use a DOI?
- Keywords
- peak carbon dioxide emissions; environmental kuznets curve; Shaanxi province
- Abstract
Shaanxi Province is an important energy province in China. There are great differences among different regions in resource endowment, industrial advantages and economic development level. Predicting the peak value is conducive to the early realization of the carbon peak goal in Shaanxi Province and the overall green transformation of economic and social development. On this basis, the IPCC method was used to calculate the carbon emissions of Shaanxi Province and other cities, and the EKC method was used to predict the peak carbon emissions. The results showed that:(1) CO2 emissions in Shaanxi Province showed an upward trend from 2011 to 2020, reaching 276,037,500 tons in 2020, in which coal accounted for the largest proportion of CO2 emissions. The largest carbon emission is Yulin City, the least is Ankang City. (2) Shaanxi Province will reach its carbon emission peak in 2033. With the exception of Xi 'an, Tongchuan and Shangluo, all cities will reach their carbon peak by 2030. The earliest peak is Weinan City, the latest is Tongchuan City.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Weixian Xue AU - Liangmin Wang PY - 2023 DA - 2023/07/26 TI - Prediction of Carbon Peak in Shaanxi Province and Its Cities BT - Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023) PB - Atlantis Press SP - 938 EP - 945 SN - 2589-4919 UR - https://doi.org/10.2991/978-94-6463-200-2_97 DO - 10.2991/978-94-6463-200-2_97 ID - Xue2023 ER -