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Characterising low-cost sensors in highly portable platforms to quantify personal exposure in diverse environments
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 addre...
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Published in: | Atmospheric measurement techniques 2019-08, Vol.12 (8), p.4643-4657 |
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Main Authors: | , , , , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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 (NOx), carbon monoxide (CO), ozone
(O3) and particulate matter (PM) measurements along with temperature,
relative humidity, acceleration, noise and GPS sensors. Overall, the air
pollution sensors showed high reproducibility (mean R‾2=0.93, min–max: 0.80–1.00) and excellent agreement with
standard instrumentation (mean R‾2=0.82, min–max: 0.54–0.99) in outdoor, indoor and commuting
microenvironments across seasons and different geographical settings. An
important outcome of this study is that the error of the PAM is
significantly smaller than the error introduced when estimating personal
exposure based on sparsely distributed outdoor fixed monitoring stations.
Hence, novel sensing technologies such as the ones demonstrated here can
revolutionise health studies by providing highly resolved reliable exposure
metrics at a large scale to investigate the underlying mechanisms of the
effects of air pollution on health. |
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ISSN: | 1867-8548 1867-1381 1867-8548 |
DOI: | 10.5194/amt-12-4643-2019 |