A probabilistic evaluation of China’s energy-related carbon emission peak target

Zheng Li , Chenpeng Li , Yujuan Fang , Pei Liu , Ershun Du , Linwei Ma , Xiu Yang

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A probabilistic evaluation of China’s energy-related carbon emission peak target
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Abstract

In recent years, China has witnessed a surge in both its total primary energy consumption and its installed renewable energy capacity, which has had a profound impact on the nation’s carbon emissions. The future trajectories of energy consumption and renewable energy development are fraught with uncertainties, and these will critically influence the realization of China’s climate objectives, especially the goal of reaching a carbon peak. This research employs maximum likelihood estimation (MLE), in conjunction with Monte Carlo simulation and random sampling techniques, to assess the likelihood of China attaining its carbon peak and other climate targets under various scenarios. Additionally, it offers strategic policy recommendations to ensure the fulfillment of these environmental goals. In the baseline scenario, China must either surpass 4000 GW of installed non-fossil energy capacity before 2030 or maintain a total energy consumption below 6500 million tons of coal equivalent (Mtce) to align with its climate commitments. However, should the rate of reduction in energy intensity falter, leading to a total energy consumption exceeding 8250 Mtce before 2030, China may find it challenging to achieve all its climate ambitions.

Keywords

Uncertainty / Carbon peak / Probability / Monte Carlo simulation / Renewable energy

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Zheng Li, Chenpeng Li, Yujuan Fang, Pei Liu, Ershun Du, Linwei Ma, Xiu Yang. A probabilistic evaluation of China’s energy-related carbon emission peak target. Engineering DOI:10.1016/j.eng.2025.07.018

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