title: Using Global Positioning Systems (GPS) and temperature data to generate time-activity classifications for estimating personal exposure in air monitoring studies: an automated method.
abstract: BACKGROUND
  Personal exposure studies of air pollution generally use self-reported diaries to capture individuals' time-activity data. Enhancements in the accuracy, size, memory and battery life of personal Global Positioning Systems (GPS) units have allowed for higher resolution tracking of study participants' locations. Improved time-activity classifications combined with personal continuous air pollution sampling can improve assessments of location-related air pollution exposures for health studies.
  
  
  METHODS
  Data was collected using a GPS and personal temperature from 54 children with asthma living in Montreal, Canada, who participated in a 10-day personal air pollution exposure study. A method was developed that incorporated personal temperature data and then matched a participant's position against available spatial data (i.e., road networks) to generate time-activity categories. The diary-based and GPS-generated time-activity categories were compared and combined with continuous personal PM2.5 data to assess the impact of exposure misclassification when using diary-based methods.
  
  
  RESULTS
  There was good agreement between the automated method and the diary method; however, the automated method (means: outdoors = 5.1%, indoors other =9.8%) estimated less time spent in some locations compared to the diary method (outdoors = 6.7%, indoors other = 14.4%). Agreement statistics (AC1 = 0.778) suggest 'good' agreement between methods over all location categories. However, location categories (Outdoors and Transit) where less time is spent show greater disagreement: e.g., mean time "Indoors Other" using the time-activity diary was 14.4% compared to 9.8% using the automated method. While mean daily time "In Transit" was relatively consistent between the methods, the mean daily exposure to PM2.5 while "In Transit" was 15.9 μg/m3 using the automated method compared to 6.8 μg/m3 using the daily diary.
  
  
  CONCLUSIONS
  Mean times spent in different locations as categorized by a GPS-based method were comparable to those from a time-activity diary, but there were differences in estimates of exposure to PM2.5 from the two methods. An automated GPS-based time-activity method will reduce participant burden, potentially providing more accurate and unbiased assessments of location. Combined with continuous air measurements, the higher resolution GPS data could present a different and more accurate picture of personal exposures to air pollution.
authors.affiliation: Water and Air Quality Bureau, HECSB, Health Canada, 269 Laurier Avenue West, AL 4903C, Ottawa, Ontario K1A 0 K9, Canada. elizabeth.nethery@gmail.com.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Nethery
authors.forename: Gary
authors.initials: G
authors.lastname: Mallach
authors.forename: Daniel
authors.initials: D
authors.lastname: Rainham
authors.forename: Mark S
authors.initials: MS
authors.lastname: Goldberg
authors.forename: Amanda J
authors.initials: AJ
authors.lastname: Wheeler
mesh_terms: D000293:Adolescent; D000393:Air Pollutants / Q000032:analysis*; D002648:Child; D002947:Cities; D004784:Environmental Monitoring / Q000379:methods*; D005260:Female; D040362:Geographic Information Systems; D006801:Humans; D006813:Humidity; D008297:Male; D052638:Particulate Matter / Q000032:analysis*; D011792:Quebec; D013696:Temperature; D013997:Time Factors
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter