Characterizing On-Road CO

Hongmei Zhao, Zhaowen Han, Lijun Cheng, Yuxuan Lyu, Tian Luo

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 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

5 authors.

Hongmei ZhaoCollege of Transport & Communications, Shanghai Maritime University, Shanghai 201306, China.ORCID 0009-0006-6137-6222

Zhaowen HanCollege of Transport & Communications, Shanghai Maritime University, Shanghai 201306, China.

Lijun ChengSchool of Economics & Management, Shanghai Maritime University, Shanghai 201306, China.ORCID 0009-0001-8612-1641

Yuxuan LyuCollege of Transport & Communications, Shanghai Maritime University, Shanghai 201306, China.

Tian LuoAlibaba Business School, Hangzhou Normal University, Hangzhou 311121, China.

Funding

the National Natural Science Foundation of China and Zhejiang Provincial Nat-ural Science Foundation of China No.42507155 and No. LQN25G010006

6 · The paper itself

Abstract

Heavy-duty vehicles (HDVs) are major greenhouse gas emitters, and liquefied natural gas (LNG)-powered HDVs have emerged as a promising low-carbon alternative. However, their real-world emission performance and mitigation potential remain insufficiently studied, necessitating the characterization of LNG container trucks' on-road CO

Indexed as

LNG container truckmachine learningportable emission measurement system (PEMS)real-world emission

Identifiers

PMID41902036

DOI10.3390/s26061868

PMCPMC13030758

What OpenQuestion holds

Textmetadata

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.