Evidence map›Paper›PMID 31534556›Full record

ArticleAtmospheric measurement techniques2019

Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments.

Lia Chatzidiakou, Anika Krause, Olalekan A M Popoola, Andrea Di Antonio, Mike Kellaway, Yiqun Han, Freya A Squires, Teng Wang, Hanbin Zhang, Qi Wang and 8 more

Abstract read
In one paragraph

Article in Atmospheric measurement techniques, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–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

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  11. Feasibility Study on the Use of NOSensors (Basel, Switzerland) · 2024
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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

18 authors.

Lia Chatzidiakou *Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK.
Anika Krause *Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK.
Olalekan A M PopoolaDepartment of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK.
Andrea Di AntonioDepartment of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK.
Mike KellawayAtmospheric Sensors Ltd, Bedfordshire, SG19 3SH, UK.
Yiqun HanMRC-PHE Centre for Environment & Health, Imperial College London and King's College London, London, W2 1PG, UK.
Freya A SquiresDepartment of Chemistry, University of York, York, YO10 5DD, UK.
Teng WangCollege of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
Hanbin ZhangMRC-PHE Centre for Environment & Health, Imperial College London and King's College London, London, W2 1PG, UK.
Qi WangCollege of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
Yunfei FanCollege of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
Shiyi ChenCollege of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
Min HuCollege of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
Jennifer K QuintNational Heart and Lung Institute, Imperial College London, SW3 6LR, UK.
Benjamin BarrattMRC-PHE Centre for Environment & Health, Imperial College London and King's College London, London, W2 1PG, UK.
Frank J KellyMRC-PHE Centre for Environment & Health, Imperial College London and King's College London, London, W2 1PG, UK.
Tong ZhuCollege of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
Roderic L JonesDepartment of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK.

Funding

Medical Research Council MR/L019744/1
6 · The paper itself

Abstract

The inaccurate quantification of personal exposure to air pollution introduces error and bias in health estimations, severely limiting causal inference in epidemiological research worldwide. Rapid advancements in affordable, miniaturised air pollution sensor technologies offer the potential to address this limitation by capturing the high variability of personal exposure during daily life in large-scale studies with unprecedented spatial and temporal resolution. However, concerns remain regarding the suitability of novel sensing technologies for scientific and policy purposes. In this paper we characterise the performance of a portable personal air quality monitor (PAM) that integrates multiple miniaturised sensors for nitrogen oxides (NO

Identifiers

PMID31534556
PMCPMC6751078

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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.