Evidence map›Paper›PMID 42903711›Full record

ArticleEnvironment & health (Washington, D.C.)2026

Driving Scenarios Strongly Influence Tire Additive Accumulation in Road Dust: First Field Evidence from China's Urban Roads.

Pinjie Su, Jie Shen, Zihan Wang, Chenxi Huo, Jiefeng Liang, Guangbo Qu, Runzeng Liu

Abstract read
In one paragraph

Article in Environment & health (Washington, D.C.), 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

7 authors.

Pinjie SuShandong Key Laboratory of Environmental Processes and Health, School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China.
Jie ShenShandong Key Laboratory of Environmental Processes and Health, School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China.
Zihan WangShandong Key Laboratory of Environmental Processes and Health, School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China.
Chenxi HuoShandong Key Laboratory of Environmental Processes and Health, School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China.
Jiefeng LiangShandong Key Laboratory of Environmental Processes and Health, School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China.
Guangbo QuState Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.ORCID https://orcid.org/0000-0002-5220-7009
Runzeng LiuShandong Key Laboratory of Environmental Processes and Health, School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China.ORCID https://orcid.org/0000-0002-0219-8052

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tire additives (TAs) are of growing concern due to their widespread occurrence and potential toxicity. However, the role of driving scenarios in modulating their release remains poorly understood. This study examined a broad range of TAs in road dust collected from two typical urban road scenarios in China. A total of 138 TAs were detected, including 14 compounds reported in road dusts for the first time. Driving scenarios strongly influenced the TA concentrations and composition. On urban roads, crossroads (characterized by frequent braking, turning, and stop-and-go traffic) exhibited higher TA concentrations (median: 5.46 × 10

Indexed as

driving scenarioshealth risknew pollutantsroad dusttire additive emission

Identifiers

PMID42903711
PMCPMC13681437

What OpenQuestion holds

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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.