Forecasting CO₂ Emission Using ARIMA Modelling

DOI

10.2991/978-94-6463-829-5_3How to use a DOI?

Keywords

ARIMA; CO2 emission; data analysis; prediction; time series

Abstract

CO2 emission is a widely challenging problem in economics, energy and environment, which has an impact on carbon price. This work utilizes ARIMA-based models to analyse the CO2 emission prediction. We provide an useful model for CO2 emission time series and forecast the emission volume in 2024~2028. We first remove some outliers and scale the data. Then, use R to do some tests for white noise and stationary with Ljung-Box test and ADF test. Next, we choose the nuisance parameters by AIC criterion and built ARIMA(4,2,3) for analysing and prediction. Finally, evaluate this model using MAE and MAPE as well as some residual analysis plots. The numeric results indicate a good performance in fitting and prediction.

Copyright

© 2025 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  - Yiyao Yin
PY  - 2025
DA  - 2025/08/28
TI  - Forecasting CO₂ Emission Using ARIMA Modelling
BT  - Proceedings of the 2025 International Conference on Chemical Engineering and Biological Science (CEBS 2025)
PB  - Atlantis Press
SP  - 15
EP  - 23
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-829-5_3
DO  - 10.2991/978-94-6463-829-5_3
ID  - Yin2025
ER  -