Using Global Positioning Systems (GPS) and temperature data to generate time-activity classifications for estimating personal exposure in air monitoring studies: an automated method.

https://arctichealth.org/en/permalink/ahliterature257181
Source
Environ Health. 2014;13(1):33
Publication Type
Article
Date
2014
Author
Elizabeth Nethery
Gary Mallach
Daniel Rainham
Mark S Goldberg
Amanda J Wheeler
Author 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.
Source
Environ Health. 2014;13(1):33
Date
2014
Language
English
Publication Type
Article
Keywords
Adolescent
Air Pollutants - analysis
Child
Cities
Environmental Monitoring - methods
Female
Geographic Information Systems
Humans
Humidity
Male
Particulate Matter - analysis
Quebec
Temperature
Time Factors
Abstract
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.
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.
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.
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.
Notes
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PubMed ID
24885722 View in PubMed
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