Evidence map›Paper›PMID 38316907›Full record

ArticleJournal of exposure science & environmental epidemiology2024

Representativeness of the US EPA PM monitoring site locations to the US population: implications for air pollution prediction modeling.

Meredith Pedde, Sara D Adar

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of exposure science & environmental epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Equity in the Distribution of Regulatory PMEnvironmental science & technology · 2025
    Article
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

2 authors.

Meredith PeddeDepartment of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA. mpedde@umich.edu.ORCID 0000-0003-2099-9221
Sara D AdarDepartment of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Air pollution prediction modeling establishes relationships between measurements and geographical and meteorological characteristics to infer concentrations at locations without measurements. Since air pollution monitors are limited in number, predictions may be generated for locations different than those used to train the model. The epidemiologic impacts of this potential mismatch hinge on whether the population resides in areas well-represented by monitoring sites. Here we quantify the fraction of the population with geographical characteristics not reflected by the 2000, 2010, and 2020 EPA PM

Indexed as

Air PollutantsAir PollutionEnvironmental ExposureEnvironmental MonitoringParticulate MatterUnited States Environmental Protection AgencyHumansModels, TheoreticalUnited StatesAir PollutantsParticulate MatterAir PollutionEnvironmental MonitoringExposure ModelingParticulate Matter

Identifiers

What OpenQuestion holds

Textmetadata
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.