Carbon Emission Prediction and Peaking Pathways from the Perspective of New Energy Substitution

DOI

10.2991/978-94-6239-825-2_10How to use a DOI?

Keywords

carbon emission prediction; ridge regression; scenario analysis; new energy substitution

Abstract

Under the constraints of the “dual carbon” goals, accurately predicting regional carbon emission trends and identifying key driving factors is the foundation for formulating differentiated emission reduction policies. Taking Heilongjiang Province, a typical old industrial base, as the research object, this paper constructs a carbon emission prediction model incorporating three core variables-per capita GDP, share of tertiary industry, and energy intensity-based on energy consumption and socio-economic development data from 2010 to 2024. To address severe multicollinearity among the variables, the ridge regression method is employed for parameter estimation, and the prediction results are coupled with three scenarios with different speeds of new energy substitution. The ridge regression model achieves R² values of 0.9969 and 0.7652 on the training set and test set, respectively, with the test set MAPE of 2.35%, indicating that although the sample size is limited, the model maintains reasonable extrapolation capability for out-of-sample predictions. Energy intensity is the most important factor driving carbon emission increases in Heilongjiang (standardized coefficient 1.0016), followed by per capita GDP (1.9930), while the share of tertiary industry has a weak and anomalously positive effect (0.0402), suggesting that the emission reduction dividends from industrial structure upgrading have not yet materialized. Scenario projections indicate that even under the low-carbon fast transition scenario, carbon emissions in Heilongjiang continue to rise and cannot peak before 2030; however, accelerating the substitution of new energy for traditional fossil fuels could reduce the peak level by about 3.6%. This paper emphasizes that new energy capacity expansion and energy efficiency improvement are the key levers to break the “high-carbon lock-in” of Heilongjiang. It is recommended to incorporate the new energy substitution rate into the provincial carbon peaking assessment system and implement differentiated energy use constraints for heavy industrial sectors.

Copyright

© 2026 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  - Aixuan Liu
AU  - Yuemeng Wang
AU  - Meng Han
AU  - He Li
PY  - 2026
DA  - 2026/11/10
TI  - Carbon Emission Prediction and Peaking Pathways from the Perspective of New Energy Substitution
BT  - Proceedings of the 2026 5th International Conference on Public Service, Economic Management and Sustainable Development (PESD 2026)
PB  - Atlantis Press
SP  - 93
EP  - 100
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-825-2_10
DO  - 10.2991/978-94-6239-825-2_10
ID  - Liu2026
ER  -