Evidence map›Paper›PMID 42230575›Full record

ArticleNature communications2026

National-level assessment of infrastructure-coupled roadside solar energy toward transportation decarbonization in China.

Zhaoyuan Wu, Jianxiao Wang, Lanyi Wei, Bo Li, Lin Chen, Lu Zhang, Daniel M Kammen, Gengyin Li, Ming Zhou, Jie Song

Abstract read
In one paragraph

Article in Nature communications, 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

10 authors.

Zhaoyuan Wu *State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China.ORCID http://orcid.org/0000-0002-9269-0082
Jianxiao Wang *National Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing, China.ORCID http://orcid.org/0000-0001-9871-5263
Lanyi WeiState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China.
Bo LiSchool of Electrical Engineering, Guangxi University, Nanning, Guangxi Zhuang Autonomous Region, China.ORCID http://orcid.org/0000-0001-7320-7297
Lin ChenInstitute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China.ORCID http://orcid.org/0009-0003-5318-6195
Lu ZhangCollege of Information and Electrical Engineering, China Agricultural University, Beijing, China.
Daniel M KammenEnergy and Resources Group, University of California Berkeley, Berkeley, CA, USA.ORCID http://orcid.org/0000-0003-2984-7777
Gengyin LiState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China.
Ming ZhouState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China. zhouming@ncepu.edu.cn.ORCID http://orcid.org/0000-0002-9226-0496
Jie SongNational Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing, China. jie.song@pku.edu.cn.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 52577106National Natural Science Foundation of China (National Science Foundation of China) 72422015National Natural Science Foundation of China (National Science Foundation of China) U22B20110
6 · The paper itself

Abstract

Decarbonizing transportation requires approaches that embed renewable generation into existing infrastructure. Here we show that roadside photovoltaic deployment along China's roads and railways can be quantified using a geospatial framework that links segmented transport corridors to meteorological grids. The approach maps 480,019 km of transport infrastructure to 4,133 meteorological grids and provides a scalable alternative to coarse regional averaging. Across all deployment scenarios, roadside photovoltaic systems could support 40.91-202.84 GW of installed capacity and generate 56.6-239.2 TWh of electricity annually. Under the baseline scenario, annual generation reaches about 100.6 TWh, equivalent to about 50% of current transport-sector electricity demand. The resulting carbon reduction reaches 33.62-143.97 Mt CO

Identifiers

PMID42230575
PMCPMC13392230

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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.