Prediction of Carbon Peak Time in Jiangxi Province Based on Random Forest Model

DOI

10.2991/978-94-6463-030-5_153How to use a DOI?

Keywords

Carbon Emission; Scenario Analysis; Random Forest Model; Jiangxi Province

Abstract

The trend of global warming is irresistible, and achieving carbon peaking and carbon neutrality as soon as possible is widely believed to be one of the main ways to solve climate warming. In the 14th Five-Year Plan announced by China, it is again emphasized that China will achieve carbon peak before 2030 and achieve carbon neutrality around 2060. This paper adopts the prediction method of random forest and sets three different scenarios, including the baseline scenario, the energy optimization scenario and the low-carbon scenario. Predict whether Jiangxi Province can reach its carbon peak by 2030 under different scenarios. The forecast results show that under the baseline scenario, Jiangxi Province will achieve carbon peaking in 2029, under the energy optimization scenario, Jiangxi Province will achieve carbon peaking in 2028, and under the low-carbon scenario, Jiangxi Province will achieve carbon peaking in 2026. By continuously optimizing the influencing factors of carbon emissions, Jiangxi Province will gradually advance the carbon peak time.

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.

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TY  - CONF
AU  - Dandan Cao
PY  - 2022
DA  - 2022/12/20
TI  - Prediction of Carbon Peak Time in Jiangxi Province Based on Random Forest Model
BT  - Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)
PB  - Atlantis Press
SP  - 1529
EP  - 1535
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-030-5_153
DO  - 10.2991/978-94-6463-030-5_153
ID  - Cao2022
ER  -