Evidence map›Paper›PMID 42562835›Full record

ArticleScientific reports2026

Assessment and pathways of the energy production revolution in the Yellow River Basin, China towards carbon peaking: a machine learning approach.

Jian Xu, Jie Song, Yifan Yan, Ziwei Jia, Yanghong Lu, Mengna Li

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Jian Xu *School of Management, Xi'an University of Science and Technology, Xi'an, 710054, Shaanxi, China. jxu@xust.edu.cn.
Jie Song *School of Management, Xi'an University of Science and Technology, Xi'an, 710054, Shaanxi, China.
Yifan YanSchool of Management, Xi'an University of Science and Technology, Xi'an, 710054, Shaanxi, China.
Ziwei JiaSchool of Management, Xi'an University of Science and Technology, Xi'an, 710054, Shaanxi, China.
Yanghong LuSchool of Management, Xi'an University of Science and Technology, Xi'an, 710054, Shaanxi, China.
Mengna LiSchool of Management, Xi'an University of Science and Technology, Xi'an, 710054, Shaanxi, China.

Funding

The Humanities and Social Sciences Research Fund of the Ministry of Education 22YJA630100The Social Science Foundation of Shaanxi Province 2021R039
6 · The paper itself

Abstract

Under the dual pressure of global warming and the energy crisis, the energy production revolution is central to achieving China's carbon peaking and carbon neutrality goals. The Yellow River Basin, a strategically vital region for national energy supply, plays a critical role in this transition, with its progress directly impacting energy security and ecological sustainability. This study develops an energy production revolution index (EIT) based on four dimensions-cleanliness, low-carbonization, security, and efficiency. We employ a stacking ensemble model and a Lasso-based extended STIRPAT-ridge regression model, combined with scenario analysis, to predict the trends in the effects of the energy production revolution and carbon emissions in the basin from 2025 to 2045. The findings reveal that: (1) From 2010 to 2023, the EIT index for the entire basin, hydro-rich provinces, wind-rich provinces, and PV-rich provinces increased from 55.0 to 65.5, from 72.9 to 85.2, from 45.2 to 53.6, and from 46.8 to 57.6, respectively. All exhibit a continuous upward trend, yet a considerable gap remains compared to the Excellent level. (2) Against the backdrop of carbon peaking, the optimal pathways for the energy production revolution in the entire basin and the three types of major provinces exhibit heterogeneity. The structural synergy scenario proves most effective for the entire basin and wind-rich provinces, while a foundational innovation scenario is optimal for hydro-rich and PV-rich provinces. Projected carbon peaking years are 2028-2030 for the entire basin and hydro-rich provinces, and 2027-2029 for wind-rich and PV-rich provinces. By 2045, under the optimal pathways, the EIT index for the entire basin, hydro-rich, wind-rich, and PV-rich provinces is projected to reach 90.5, 98.4, 83.0, and 89.8, respectively, with the former two reaching the Excellent level and the latter two reaching the Good level.(3) Significant spatial disparities in carbon emission trajectories and transition effectiveness exist among the nine provinces within the basin. Finally, a practical pathway is developed for the basin-wide energy production revolution, supporting the Yellow River Basin's timely carbon peaking goals.

Identifiers

PMID42562835
PMCPMC13447845

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