Evidence map›Paper›PMID 39874691›Full record

ArticleJournal of environmental management2025

bneR: A collaborative workflow for air pollution exposure modeling and uncertainty characterization using the Bayesian Nonparametric Ensemble.

Jaime Benavides, Carlos Carrillo-Gallegos, Vijay Kumar, Sebastian T Rowland, Lawrence G Chillrud, Temilayo Adeyeye, John Paisley, Brent Coull, Daven K Henze, Randall V Martin and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of environmental management, 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
–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

12 authors.

Jaime BenavidesDepartment of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA. Electronic address: jap2312@cumc.columbia.edu.
Carlos Carrillo-GallegosDepartment of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
Vijay KumarDepartment of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.
Sebastian T RowlandDepartment of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA; PSE Healthy Energy, Oakland, CA, USA.
Lawrence G ChillrudDepartment of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA; Department of Electrical & Computer Engineering, Northwestern University, IL, USA.
Temilayo AdeyeyeBureau of Environmental and Occupational Epidemiology, New York State Department of Health, Albany, NY, USA; Department of Environmental Health Sciences, College of Integrated Health Sciences, University at Albany, SUNY, NY, USA.
John PaisleyDepartment of Electrical Engineering & Data Science Institute Columbia, Columbia University, New York, NY, USA.
Brent CoullDepartment of Biostatistics Harvard University Boston, MA, USA.
Daven K HenzeDepartment of Mechanical Engineering, University of Colorado, 1111 Engineering Drive, Boulder, CO, USA.
Randall V MartinDepartment of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA.
Arlene M FioreDepartment of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Lamont-Doherty Earth Observatory and Columbia University, Palisades, NY, USA.
Marianthi-Anna KioumourtzoglouDepartment of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.

Funding

True Metal fac coreP30ES009089 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MATTHEW S PERZANOWSKI · 1998 to 2026
$44.7M
Supplemental Training in Making Data FAIR and AI/ML ReadyT32ES007322 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Pam R Factor-Litvak, Allison Kupsco · 2000 to 2026
$12.1M
Integrating Air Pollution Prediction Models: Uncertainty Quantification and Propagation in Health StudiesR01ES030616 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI DOMINICI, FRANCESCA, KIOUMOURTZOGLOU, MARIANTHI-ANNA · 2020 to 2024
$3.1M
NIEHS NIH HHS P30 ES009089NIEHS NIH HHS R01 ES030616NIEHS NIH HHS T32 ES007322
6 · The paper itself

Abstract

backgroundAir pollution is a major public health threat globally. Health studies, regulatory actions, and policy evaluations typically rely on air pollutant concentrations from single exposure models, assuming accurate estimations and ignoring related uncertainty. We developed a modeling framework, bneR, to apply the Bayesian Nonparametric Ensemble (BNE) prediction model that combines existing exposure models as inputs to provide air pollution estimates and their spatio-temporal uncertainty.

methodsThe bneR modeling framework (1) harmonizes air pollutant datasets to use standardized inputs for the BNE algorithm; (2) applies the BNE algorithm to obtain the posterior predictive distribution of pollutant concentrations; and (3) generates visualizations. We applied bneR to estimate NO

resultsUsing bneR, we harmonized the spatial scale of four input NO

conclusionMeeting stakeholders and modelers allowed us to understand that efficient communication on how uncertainty is estimated and interpreted is a key feature for these communities to engage in using bneR and its data products.

Indexed as

Air PollutantsAir PollutionEnvironmental MonitoringBayes TheoremHumansNew YorkNitrogen DioxideUncertaintyAir PollutantsNitrogen DioxideAir pollutionCollaborativeModel ensembleNonparametric

Identifiers

PMID39874691
PMCPMC11997696

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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.