Evidence map›Paper›PMID 42611482›Full record

ArticleEnvironmental science & technology2026

Resource and Climate Implications of China's Passenger Vehicle Fleet Transition to 2050.

Fanran Meng, Yiling Xiong, Hannes Gauch, Wei Ow, Xin Sun, Yi Feng, Shaojun Zhang, Jonathan M Cullen

Abstract read
In one paragraph

Article in Environmental science & technology, 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

8 authors.

Fanran MengSchool of Chemical, Materials and Biological Engineering, University of Sheffield, Mappin Street, SheffieldS1 3JD, United Kingdom.ORCID 0000-0002-9014-1231
Yiling XiongSchool of Chemical, Materials and Biological Engineering, University of Sheffield, Mappin Street, SheffieldS1 3JD, United Kingdom.
Hannes GauchDepartment of Engineering, University of Cambridge, CambridgeCB2 1PZ, United Kingdom.
Wei OwDepartment of Engineering, University of Cambridge, CambridgeCB2 1PZ, United Kingdom.
Xin SunChina Automotive Technology and Research Center Company, Ltd., No. 68 East Xianfeng Road, Dongli District, Tianjin300300, China.
Yi FengChina Automotive Technology and Research Center Company, Ltd., No. 68 East Xianfeng Road, Dongli District, Tianjin300300, China.
Shaojun ZhangState Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing100084, P. R. China.ORCID 0000-0002-2176-6174
Jonathan M CullenDepartment of Engineering, University of Cambridge, CambridgeCB2 1PZ, United Kingdom.

Funding

Royal Society ICA\R1\231046Saudi Aramco NA
6 · The paper itself

Abstract

China's rapid expansion and electrification of its passenger vehicle fleet will strongly influence global resource demand and greenhouse gas emissions. Yet existing projections rarely capture the complex, coupled effects of vehicle- and battery-related variables alongside fleet growth and decarbonization pathways. Here, we develop a bottom-up fleet stock model with exogenously specified powertrain adoption pathways to quantify China's passenger vehicle stock and its greenhouse gas, energy, and material demand through 2050. The model is parametrized with China-specific data, evaluated against recent fleet statistics, and complemented by Monte Carlo, Sobol, and reference-scenario sensitivity analyses. We project that China's passenger vehicle stock increases from 218 million in 2019 to 360-520 million by 2050, while life cycle greenhouse gas emissions, energy use, and material demand generally peak around 2035-2040 before stabilizing or declining. Depending on future behavioral and technological pathways, final energy demand and life-cycle greenhouse gas emissions range from approximately 53% below to 122-153% above the reference scenario. Sobol analysis shows that rebound effects account for 50-73% of output variance, followed by passenger travel demand (23-29%), whereas the timing of internal combustion engine phase-out contributes less than 0.5%. These findings demonstrate that a sustainable transport transition in China requires coordinated action on demand management, vehicle efficiency, electricity decarbonization, and material stewardship.

Indexed as

ClimateVehicle EmissionsChinaGreenhouse GasesModels, TheoreticalGreenhouse GasesVehicle EmissionsFleet electrificationGreenhouse gas emissionMaterial demandSobol analysisVehicle stock

Identifiers

PMID42611482
PMCPMC13492275

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.