Probabilistic study assesses China’s energy-related carbon emission peak target
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The research diagram for this study.
view moreCredit: Zheng Li, Chenpeng Li et al.
A new study published in Engineering provides a probabilistic evaluation of China’s ability to reach its energy-related carbon emission peak and related climate targets by 2030, accounting for uncertainties in total energy consumption and non-fossil energy development. Conducted by researchers from Tsinghua University, the analysis uses maximum likelihood estimation, Monte Carlo simulation, and random sampling to quantify the likelihood of goal achievement across different policy scenarios, without overstatement of outcomes.
The research notes that China has seen rapid growth in both primary energy consumption and renewable energy installed capacity, which jointly shape national carbon emission trends. Future pathways in these two areas carry substantial uncertainty, directly affecting the delivery of climate pledges including peaking carbon emissions before 2030, cutting CO₂ emissions per unit of GDP by more than 65% from 2005 levels by 2030, and raising the share of non-fossil fuels in primary energy consumption to around 25%. The study models uncertainties in economic growth, energy intensity reduction, and the deployment of wind, solar, nuclear, hydropower, and offshore wind power, treating solar and onshore wind as high-uncertainty variables while setting deterministic projections for other low-uncertainty non-fossil sources.
Under the baseline energy intensity scenario, China needs to either exceed 4000 GW of installed non-fossil energy capacity before 2030 or keep total energy consumption below 6500 million tons of coal equivalent (Mtce) to meet its climate commitments. The analysis covers four renewable energy policy scenarios, showing that stronger policy support for wind and solar raises the probability of peaking emissions on time, with diminishing marginal returns in probability gains beyond moderate ambition levels. The study also finds that achieving the GDP-linked carbon intensity target is more stringent than meeting the non-fossil energy share target, and that success in the former typically ensures fulfillment of the latter.
A slowdown in energy intensity reduction poses notable risks. If total energy consumption exceeds 8250 Mtce before 2030 due to weaker efficiency gains, it will become difficult for China to achieve all its climate goals within the studied uncertainty ranges. The framework calculates millions of sub-scenarios to map the combined effects of energy demand and non-fossil energy expansion, offering targeted policy suggestions including phased non-fossil capacity planning, region-specific technological innovation, and coordinated governance linking energy management and socioeconomic development to stabilize progress toward climate targets.
The findings offer a data-driven reference for balancing energy security, economic development, and decarbonization as China advances its dual-carbon objectives amid global energy transition challenges.
The paper “A Probabilistic Evaluation of China’s Energy-Related Carbon Emission Peak Target,” is authored by Zheng Li, Chenpeng Li, Yujuan Fang, Pei Liu, Ershun Du, Linwei Ma, Xiu Yang. Full text of the open access paper: https://doi.org/10.1016/j.eng.2025.07.018. For more information about Engineering, visit the website at https://www.sciencedirect.com/journal/engineering.
Journal
Engineering
Article Title
A Probabilistic Evaluation of China’s Energy-Related Carbon Emission Peak Target
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