Carbon neutrality planning based on time series analysis and hybrid supervision

DOI

10.2991/978-94-6463-415-0_19How to use a DOI?

Keywords

ARIMA model; AHP-TOPSIS evaluation method; Carbon Neutrality Pathway

Abstract

With the rapid development of industrialization and urbanization, the problem of climate change is becoming increasingly serious, and it has become crucial for China, to reduce greenhouse gas emissions and achieve carbon neutrality as an important contributor to global climate change. First, the ARIMA model was used to predict the energy consumption structure of each province in the coming years. The model predicted the energy consumption structure and obtained significant prediction accuracy with an average R-squared value of 0.83, which was better than the control group methods such as LSTM, BP, and RNN. Second, this study established a low-carbon situation evaluation system based on the AHP-TOPSIS evaluation method. Using the AHP-TOPSIS method enabled the quantification of regional low-carbon efforts by assigning weights to renewable and non-renewable energy sources, with coal having the highest weight at 48.264% and the lowest weight being wind energy at only 4.245%. Then, this study predicted the trend of carbon emission, assessed the carbon emission, and proposed a low-carbon optimization strategy. Through these methods and strategies, this study provided a scientific basis and decision support for China’s carbon neutrality pathway planning. This study provides theoretical and practical support for China to achieve its carbon neutrality goal, but it still needs to be continuously improved. It is believed that with the joint efforts of all parties, China’s carbon neutrality pathway planning will become more scientific and effective and contribute to the solution of global climate change.

Copyright

© 2024 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  - Weihao Hong
PY  - 2024
DA  - 2024/05/14
TI  - Carbon neutrality planning based on time series analysis and hybrid supervision
BT  - Proceedings of the 2023 9th International Conference on Advances in Energy Resources and Environment Engineering (ICAESEE 2023)
PB  - Atlantis Press
SP  - 178
EP  - 184
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-415-0_19
DO  - 10.2991/978-94-6463-415-0_19
ID  - Hong2024
ER  -