Evidence map›Paper›PMID 42254971›Full record

ArticleInnovation (Cambridge (Mass.))2026

Mitigating inequity risks in China's net-zero energy transition via an enhanced renewable-guided industrial spatial reconfiguration.

Zihua Yin, Xi Lu, Chris P Nielsen, Ryna Yiyun Cui, Yang Ou, Mengyao Han, Mai Shi, Ziwen Ruan, Jiaxing Wang, Yuqi Su and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Innovation (Cambridge (Mass.)), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Zihua YinState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China.
Xi LuState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China.
Chris P NielsenHarvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Ryna Yiyun CuiCenter for Global Sustainability, School of Public Policy, University of Maryland, College Park, MD 20742, USA.
Yang OuCollege of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
Mengyao HanInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Mai ShiState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China.
Ziwen RuanState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China.
Jiaxing WangState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China.
Yuqi SuState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China.
Chongyu ZhangState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China.
Shaoqing BianState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China.
Emily XingHarvard-China Project on Energy, Economy and Environment, Harvard University, Cambridge, MA 02138, USA.
Wenji ZhouSchool of Applied Economics, Renmin University of China, Beijing 100872, China.
Junjie LiEngineering Research Center of Clean and Low-carbon Technology for Intelligent Transportation, Ministry of Education, School of Environment, Beijing Jiaotong University, Beijing 100044, China.
Michael B McElroyHarvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Kebin HeState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The energy transition to net-zero carbon emissions may exacerbate regional inequities, impeding an orderly national transition and threatening global climate goals. This challenge might be particularly severe in China, as it simultaneously faces significant regional disparities, carbon-intensive industrial and energy structures, and a relatively short transition period. Yet, the inequity risks rooted in regional economic linkages among technologies and sectors during the energy transition remain insufficiently addressed. Here, we newly developed a sector-extended multi-regional input-output model of China with a detailed representation of power production technologies (multi-regional input-output table with a disaggregated power sector [MRIO-DPS]) and further coupled it with the global change analysis model with China provincial-level details (GCAM-China) to assess regional inequities and responses in China's carbon-neutral energy transition (CNET). By 2060, ∼40% of China's provinces (mainly economically underdeveloped) are projected to face gross domestic product (GDP) declines ranging from 0.2% to 15.8%, while more developed provinces are expected to see GDP growth of 0.2%-3.5% (CNET scenario). We propose industrial spatial reconfiguration as a countermeasure: relocating energy-intensive industries to renewable-rich provinces while expanding electricity transmission from these provinces to load centers (power transmission combined with industrial transfer [PTIT] scenario). Scenario analysis shows that this reconfiguration significantly narrows subnational inequities, reduces the number of provinces with GDP declines by 42%, and boosts national GDP by 0.06% and employment by 0.68 million in 2060.

Indexed as

carbon neutralityelectricity transmissionindustrial transferintegrated assessment modelingjust transition

Identifiers

PMID42254971
PMCPMC13237846

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.