Evidence map›Paper›PMID 36623253›Full record

ArticleEnvironmental science & technology2023

Investigating Use of Low-Cost Sensors to Increase Accuracy and Equity of Real-Time Air Quality Information.

Ellen M Considine, Danielle Braun, Leila Kamareddine, Rachel C Nethery, Priyanka deSouza

Open access · greenAbstract read
In one paragraph

Article in Environmental science & technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.4field-weighted citation impact, top 7% of its field
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

5 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Ambient PMCurrent environmental health reports · 2026
    Review
  3. Equity in the Distribution of Regulatory PMEnvironmental science & technology · 2025
    Article
  4. Article
  5. 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

5 authors at 2 institutions in 1 country.

Ellen M ConsidineDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States.ORCID 0000-0002-7132-2862
Danielle BraunDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States.
Leila KamareddineDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States.
Rachel C NetheryDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States.
Priyanka deSouzaDepartment of Urban and Regional Planning, University of Colorado Denver, Denver, Colorado 80202, United States.ORCID 0000-0002-2618-4050
Harvard University · USUniversity of Denver · US

Funding

GRADUATE TRAINING IN BIOSTATISTICST32ES007142 · NIEHS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Brent Andrew Coull · 1985 to 2026
$11.9M
Causal machine learning methods for studying the effects of environmental exposures on childhood cancer using natural experimentsK01ES032458 · NIEHS · HARVARD SCHOOL OF PUBLIC HEALTH · PI NETHERY, RACHEL C · 2021 to 2023
$417k
NIEHS NIH HHS K01 ES032458NIEHS NIH HHS T32 ES007142
6 · The paper itself

Abstract

U.S. Environmental Protection Agency (EPA) air quality (AQ) monitors, the "gold standard" for measuring air pollutants, are sparsely positioned across the U.S. Low-cost sensors (LCS) are increasingly being used by the public to fill in the gaps in AQ monitoring; however, LCS are not as accurate as EPA monitors. In this work, we investigate factors impacting the differences between an individual's true (unobserved) exposure to air pollution and the exposure reported by their nearest AQ instrument (which could be either an LCS or an EPA monitor). We use simulations based on California data to explore different combinations of hypothetical LCS placement strategies (e.g., at schools or near major roads), for different numbers of LCS, with varying plausible amounts of LCS device measurement errors. We illustrate how real-time AQ reporting could be improved (or, in some cases, worsened) by using LCS, both for the population overall and for marginalized communities specifically. This work has implications for the integration of LCS into real-time AQ reporting platforms.

Indexed as

air qualitydecision-makingenvironmental justiceinformation accesslow-cost sensors

Identifiers

PMID36623253
PMCPMC10329730
OpenAlexW4313892918

What OpenQuestion holds

Textmetadata
LicenceTDM
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.