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

Abstract

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 (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 excellent agreement with standard instrumentation 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 as the ones demonstrated here can revolutionise health studies by providing highly resolved reliable exposure metrics at large scale to investigate the underlying mechanisms of the effects of air pollution on health.

Relationships between Fixed-Site Ambient Measurements of Nitrogen Dioxide, Ozone, and Particulate Matter and Personal Exposures in Grand Paris, France: The Mobilisense Study

“…Our study measured all the air pollutants on the 1st, 2nd, 5th, and 6th days (over a 6 days monitoring period). The performance of the PAMs was characterized in outdoor co-locations with reference instruments, as described in Appendix 1, adopting the methodology described by Chatzidiakou and colleagues in 2019 (Chatzidiakou et al, 2019). These co-locations also permitted us to derive calibration equations for air pollutant concentrations considering temperature and cross-sensitivity between gases (Appendix 1).…”

RGC-TBRS Personal Air Pollutant Exposure versus Health Condition and Perception Pilot Study for Young Asthmatics in Hong Kong (2019/2020)

“…In the portable sensor, PM pollutants are measured by a laser particle counter. The PM sensor can be calibrated based on the raw data (bin counts for a range of particle size bins) while accounting for meteorology factors [15]. Our sensor calibration can be performed seasonally to capture the seasonal variation of air pollution in HK (for more details, please refer to our sensor calibration report).…”

In situ drift correction for a low-cost NO2 sensor network

“…Several studies have already been working on network-specic solutions, such as reference site collocation, transfer standard collocation, remote network calibration, or a proxy model for this data quality issue, most of which recommended semi-regular adjustments to the calibrations to adjust for dri or seasonal bias. [9][10][11][12][13][14][15] This network management is an additional challenge on top of individual device calibration.…”