A provincial cost analysis of electric vehicle operation in China.

Bo Li, Mingxia Yang, Gang He, Guangchun Ruan, Jianxiao Wang, Xueqin Cui, Haiwang Zhong, Daniel M Kammen

Abstract read

In one paragraph

Article in iScience, 2025. 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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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

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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

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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.

Bo LiSchool of Electrical Engineering, Guangxi University, Nanning 530004, China.

Mingxia YangSchool of Electrical Engineering, Guangxi University, Nanning 530004, China.

Gang HeMarxe School of Public and International Affairs, Baruch College, City University of New York, New York, NY 10010, USA.

Guangchun RuanLaboratory for Information & Decision Systems, Massachusetts Institute of Technology, Boston, MA 02139, USA.

Jianxiao WangNational Engineering Laboratory for Big Data Analysis and Applications, Peking University, Beijing 100871, China.

Xueqin CuiCalifornia-China Climate Institute, University of California, Berkeley, Berkeley, CA 94709, USA.

Haiwang ZhongDepartment of Electrical Engineering, Tsinghua University, Beijing 100084, China.

Daniel M KammenDepartment of Civil and Systems Engineering (CASE), School of Advanced International Studies (SAIS), Johns Hopkins University, Baltimore, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The transition to all-electric driving is essential for achieving carbon reduction goals in China's transportation sector, which is significantly influenced by economic costs and emission reduction benefits. In this study, a comprehensive provincial assessment method is developed to quantify the levelized cost of operation (LCOO) for four electric vehicle (EV) types in China, revealing a complex interaction between geographical, economic, and technological factors. We find that the LCOO of EVs ranges from $1.36/100 km for private light-duty vehicles in the northwest region to $26.09/100 km for heavy-duty trucks in the northeast region. The results emphasize the significant disparities in the LCOO of EVs across vehicle types and regions while underscoring the relative importance of various cost components. With the widespread electrification of transportation, there is an urgent requirement for a comprehensive model to disaggregate and estimate the LCOO considering multiple factors, and formulate targeted strategies for expediting EV regional development.

Indexed as

applied scienceseconomicselectrical engineering

Identifiers

PMID41126893

DOI10.1016/j.isci.2025.113504

PMCPMC12538125

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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.