Evidence map›Paper›PMID 41014621›Full record

ArticleEnvironmental science & technology2025

Advancing Air Pollution Exposure Models with Open-Vocabulary Object Detection and Semantic Segmentation of Street-View Images.

Zhendong Yuan, Jules Kerckhoffs, Pi-I Debby Lin, Esra Suel, Hao Li, Li Yi, Marcia Pescador Jimenez, Peter James, Kees de Hoogh, Gerard Hoek and 1 more

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Article in Environmental science & technology, 2025. 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
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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

11 authors.

Zhendong YuanInstitute for Risk Assessment Sciences, Utrecht University, Utrecht 3584 CM, Netherlands.ORCID 0000-0003-3326-5243
Jules KerckhoffsInstitute for Risk Assessment Sciences, Utrecht University, Utrecht 3584 CM, Netherlands.ORCID 0000-0001-9065-6916
Pi-I Debby LinDivision of Chronic Disease Research Across the Lifecourse (CoRAL), Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts 02215, United States.
Esra SuelCentre for Advanced Spatial Analysis (CASA), University College London, London W1T4TJ, United Kingdom.
Hao LiDepartment of Geography, National University of Singapore, Singapore 119077, Singapore.
Li YiDivision of Chronic Disease Research Across the Lifecourse (CoRAL), Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts 02215, United States.
Marcia Pescador JimenezDepartment of Epidemiology, Boston University School of Public Health, Boston, Massachusetts 02118, United States.
Peter JamesDepartment of Environmental Health, Harvard TH Chan School of Public Health, Harvard University, Boston, Massachusetts 02115, United States.
Kees de HooghSwiss Tropical and Public Health Institute, Allschwil 4123, Switzerland.ORCID 0000-0001-5974-2007
Gerard HoekInstitute for Risk Assessment Sciences, Utrecht University, Utrecht 3584 CM, Netherlands.
Roel VermeulenInstitute for Risk Assessment Sciences, Utrecht University, Utrecht 3584 CM, Netherlands.ORCID 0000-0003-4082-8163

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mobile monitoring campaigns combined with land use regression (LUR) models effectively capture fine-scale spatial variations in urban air pollution. However, traditional predictor variables often fail to capture the nuances of the built environment and undocumented emission sources. To address this, we developed a framework integrating customizable object-level and segmentation-level visual features from street-view images into stepwise regression and random-forest-based LUR models. Using 5.7 million mobile air pollution measurements (2019-2020) and 0.37 million street-view images (2008-2024), we mapped nitrogen dioxide (NO

Indexed as

Air PollutionEnvironmental MonitoringAir PollutantsNetherlandsNitrogen DioxideParticulate MatterAir PollutantsNitrogen DioxideParticulate Matterair pollutiondeep learningexposure assessmentland use regression (LUR)mobile sensingstreet-view imagevision-language model (VLM)vision-transformer models (ViT)

Identifiers

PMID41014621
PMCPMC12509304

What Socratic 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 Socratic graph.