Using smartphones to collect time–activity data for long-term personal-level air pollution exposure assessment

Because of the spatiotemporal variability of people and air pollutants within cities, it is important to account for a person’s movements over time when estimating personal air pollution exposure. this study aimed to examine the feasibility of using smartphones to collect personal-level time–activity data. using skyhook wireless’s hybrid geolocation module, we developed “apolux” (air, pollution, exposure), an androidtm smartphone application designed to track participants’ location in 5-min intervals for 3 months. from 42 participants, we compared apolux data with contemporaneous data from two self-reported, 24-h time–activity diaries. about three-fourths of measurements were collected within 5 min of each other (mean=74.14%), and 79% of participants reporting constantly powered-on smartphones (n=38) had a daily average data collection frequency of <10 min. apolux’s degree of temporal resolution varied across manufacturers, mobile networks, and the time of day that data collection occurred. the discrepancy between diary points and corresponding apolux data was 342.3 m (euclidian distance) and varied across mobile networks. this study’s high compliance and feasibility for data collection demonstrates the potential for integrating smartphone-based time–activity data into long-term and large-scale air pollution exposure studies.