Abstract

Mobile phones have a large spectrum of applications, aiding in risk prevention and improving health and wellbeing of their owners. So far, however, they have not been used for direct assessment of personal exposure to air pollution. In this study, we comprehensively evaluated the first, and the only available, mobile phone—BROAD Life—equipped with air pollution sensors (PM2.5 and VOC), to answer the question whether this technology is a viable option in the quest of reducing the burden of disease to air pollution. We tested its performance, applicability and suitability for the purpose by subjecting it to varied concentrations of different types of aerosol particles (cigarette smoke, petrol exhaust and concrete dust) and formaldehyde under controlled laboratory conditions, as well as to ambient particles during field measurements. Six reference instruments were used in the study: AEROTRAK Optical Particle Counter (OPC model number 9306), DustTrak, Aerodynamic Particle Counter (APS), Scanning Mobility Particle Sizer (SMPS), Tapered Element Oscillating Microbalance (TEOM) and Formaldehyde Analyser. Overall, we found that the phone’s response was linear at higher particle number concentrations in the chamber, above 5 and 10 μg m-3, for combustion and concrete dust particles, respectively, and for higher formaldehyde concentrations, making it potentially suitable for applications in polluted environments. At lower ambient concentrations of particles around 10 ug m-3 and 20 μg m-3 for PM2.5 and PM10, respectively, the phone’s response was below its noise level, suggesting that it is not suitable for ambient monitoring under relatively clean urban conditions. This mobile phone has a number of limitations that may hinder its use in personal exposure and for continuous monitoring. Despite these limitations, it may be used for comparative assessments, for example when comparing outcomes of intervention measures or local impacts of air pollution sources. It should be kept in mind, however, that a mobile phone measuring air quality alone cannot as such 'reduce the burden of disease to air pollution, as knowing ambient concentrations is only one of the building block in this quest. As long as individuals cannot avoid exposure e.g. in urban areas, knowing concentrations is not sufficient to reduce potential adverse effects. Yet, there are many situations and microenvironments, which individuals could avoid knowing the concentrations and also being aware of the risk caused by exposure to them. This includes for example to proximity to vehicle emissions, either for social purposes (e.g. street cafes) or exercising (e.g. walking or jogging along busy roads)or indoor environments affected by combustion emissions (smoking, candle burning, open fire).

Highlights

  • Human contact with air pollution is quantified in terms of exposure, which is a function of concentration of the specific pollutants and time when people are subjected to them [1]

  • The phone is lowpower, battery-operated, a data-logging device that weighs approximately 200 grams and has dimensions 137 × 78 × 25 mm. Imbedded in it are six sensors used for the detection of PM, volatile organic compound (VOC), temperature, relative humidity (RH), ultraviolet (UV) radiation and electromagnetic radiation (EMR)

  • Particle size distributions measured by the Scanning Mobility Particle Sizer (SMPS) for the combustion particles and by APS for concrete dust are presented in Figs 1 and 2, respectively

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Summary

Introduction

Human contact with air pollution is quantified in terms of exposure, which is a function of concentration of the specific pollutants and time when people are subjected to them [1]. The need for high resolution air quality data, technological advances in high-tech device miniaturization, and the growing demand for knowledge and information on personal exposure by citizens, have a potential to shift the paradigm from conventional fixed location to mobile air pollution monitoring [3,4,5,6,7]. Mobile air sensing and monitoring devices with potential application in personal exposure monitoring at high temporal, and high spatial resolution, are emerging [8,9,10]. The application of air sensor networks, such as wireless distributed networks of sensors to collect and disseminate real time air quality data have been designed and trailed [14,15,16,17,18]

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