title: Integrating smart-phone based momentary location tracking with fixed site air quality monitoring for personal exposure assessment.
abstract: Epidemiological studies investigating relationships between environmental exposures from air pollution and health typically use residential addresses as a single point for exposure, while environmental exposures in transit, at work, school or other locations are largely ignored. Personal exposure monitors measure individuals' exposures over time; however, current personal monitors are intrusive and cannot be operated at a large scale over an extended period of time (e.g., for a continuous three months) and can be very costly. In addition, spatial locations typically cannot be identified when only personal monitors are used. In this paper, we piloted a study that applied momentary location tracking services supplied by smart phones to identify an individual's location in space-time for three consecutive months (April 28 to July 28, 2013) using available Wi-Fi networks. Individual exposures in space-time to the traffic-related pollutants Nitrogen Oxides (NOX) were estimated by superimposing an annual mean NOX concentration surface modeled using the Land Use Regression (LUR) modeling technique. Individual's exposures were assigned to stationary (including home, work and other stationary locations) and in-transit (including commute and other travel) locations. For the individual, whose home/work addresses were known and the commute route was fixed, it was found that 95.3% of the time, the individual could be accurately identified in space-time. The ambient concentration estimated at the home location was 21.01 ppb. When indoor/outdoor infiltration, indoor sources of air pollution and time spent outdoors were taken into consideration, the individual's cumulative exposures were 28.59 ppb and 96.49 ppb, assuming a respective indoor/outdoor ratio of 1.33 and 5.00. Integrating momentary location tracking services with fixed-site field monitoring, plus indoor-outdoor air exchange calibration, makes exposure assessment of a very large population over an extended time period feasible.
authors.affiliation: Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley 94720-7360, United States. Electronic address: jasonsu@berkeley.edu.
authors.forename: Jason G
authors.initials: JG
authors.lastname: Su
authors.affiliation: Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley 94720-7360, United States.
authors.forename: Michael
authors.initials: M
authors.lastname: Jerrett
authors.affiliation: Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley 94720-7360, United States.
authors.forename: Ying-Ying
authors.initials: YY
authors.lastname: Meng
authors.affiliation: Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley 94720-7360, United States.
authors.forename: Melissa
authors.initials: M
authors.lastname: Pickett
authors.affiliation: Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley 94720-7360, United States.
authors.forename: Beate
authors.initials: B
authors.lastname: Ritz
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000706:statistics & numerical data*; D040421:Cell Phone; D004781:Environmental Exposure / Q000706:statistics & numerical data*; D004784:Environmental Monitoring / Q000295:instrumentation* / Q000379:methods; D006801:Humans
chemical_list: D000393:Air Pollutants
keywords: Fixed site monitoring; Land use regression; Momentary location tracking; Personal exposure; Smart phone; Traffic-related air pollution