GPS-based microenvironment tracker (MicroTrac) model to estimate time–location of individuals for air pollution exposure assessments: Model evaluation in central North Carolina

Abstract

A critical aspect of air pollution exposure assessment is the estimation of the time spent by individuals in various microenvironments (ME). Accounting for the time spent in different ME with different pollutant concentrations can reduce exposure misclassifications, while failure to do so can add uncertainty and bias to risk estimates. In this study, a classification model, called MicroTrac, was developed to estimate time of day and duration spent in eight ME (indoors and outdoors at home, work, school; inside vehicles; other locations) from global positioning system (GPS) data and geocoded building boundaries. Based on a panel study, MicroTrac estimates were compared with 24-h diary data from nine participants, with corresponding GPS data and building boundaries of home, school, and work. MicroTrac correctly classified the ME for 99.5% of the daily time spent by the participants. The capability of MicroTrac could help to reduce the time–location uncertainty in air pollution exposure models and exposure metrics for individuals in health studies.

Benefits of Mobile Phone Technology for Personal Environmental Monitoring

“…The performance of the map-matching algorithm to determine the time spent at home or work has been shown to be very sensitive and precise, which is consistent with previous research [42,45-47]. Another relevant point in this study is the confirmation that a combined use of the mobile phone–based CalFit and the map-matching algorithm provides a better performance to identify the in-transit microenvironments than previous approaches using only GPS trackers [45,46].…”

“…Another relevant point in this study is the confirmation that a combined use of the mobile phone–based CalFit and the map-matching algorithm provides a better performance to identify the in-transit microenvironments than previous approaches using only GPS trackers [45,46]. However, our in-transit results, which include all travel modes, are still poor in comparison with those focused on the restrictive definition of in-transit microenvironment (ie, mainly in-vehicle mode) [42,47]. On the other hand, and in agreement with previous literature [41], it is still a challenge to distinguish between places that are very close to each other and to detect very short trips (eg, <10 minutes).…”

“…This difference could be explained because Michael and colleagues had more car measurements in suburban areas, where there are lower barriers for satellite coverage if compared with urban or forest areas. However, we cannot disentangle to what extent these differences could be a result of the placement of the device [42] (in this study, mobile phones were worn on the lower abdomen and the GPS tracker on the left hip), signal problem (lack of Wi-Fi signal during intercity trips), or a real mobile phone technical weakness (such as limitations on GPS antenna, digital interface, or GPS chipset built in the mobile phone).…”

Personal day-time exposure to ultrafine particles in different microenvironments

“…In panel studies estimating the individual (personal) exposure by using time-weighted pollutant concentrations in each microenvironment without measurements such imprecise information leads to uncertainty and bias to risk estimates. To address the limitations of diaries the use of GPS logger for collecting personal time-location information was recommended recently (Breen et al, 2014). It reduces the errors arising from manual recording and coding.…”

Applications of GPS-tracked personal and fixed-location PM2.5 continuous exposure monitoring

“…While outdoor monitors provide useful information regarding ambient pollution levels, they do not accurately estimate individuals' daily exposures. Particulate levels vary a great deal in local areas (microclimates), depending on the density of transmission sources, weather, and altitude (Gulliver and Briggs, 2004;Zuurbier et al, 2010;Zuurbier et al, 2011;Breen et al, 2014). Even for individuals who live at the same residence, exposure can differ by more than 30% in a single day (Dons, Int Panis et al, 2011).…”