2022 article

Microenvironment Tracker (MicroTrac) model to estimate time-location of individuals for air pollution exposure assessments: model evaluation using smartphone data

Breen, M. S. S., Xu, Y., Frey, H. C., Breen, M., & Isakov, V. (2022, December 16). JOURNAL OF EXPOSURE SCIENCE AND ENVIRONMENTAL EPIDEMIOLOGY.

By: M. Breen*, Y. Xu *, H. Frey  n, M. Breen * & V. Isakov*

author keywords: Smartphone; GPS; Microenvironment; exposure assessment; Air pollution
MeSH headings : Humans; Smartphone; Air Pollution / analysis; Air Pollutants / analysis; Time; Environmental Pollutants; Environmental Exposure / analysis; Environmental Monitoring / methods
TL;DR: This study demonstrates the extended capability of using ubiquitous smartphone data with MicroTrac to help reduce time-location uncertainty in air pollution exposure models for epidemiologic and exposure field studies. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Source: Web Of Science
Added: January 9, 2023

{"Label"=>"BACKGROUND"} A critical aspect of air pollution exposure assessments is determining the time spent in various microenvironments (ME), which can have substantially different pollutant concentrations. We previously developed and evaluated a ME classification model, called Microenvironment Tracker (MicroTrac), to estimate time of day and duration spent in eight MEs (indoors and outdoors at home, work, school; inside vehicles; other locations) based on input data from global positioning system (GPS) loggers. {"Label"=>"OBJECTIVE"} In this study, we extended MicroTrac and evaluated the ability of using geolocation data from smartphones to determine the time spent in the MEs. {"Label"=>"METHOD"} We performed a panel study, and the MicroTrac estimates based on data from smartphones and GPS loggers were compared to 37 days of diary data across five participants. {"Label"=>"RESULTS"} The MEs were correctly classified for 98.1% and 98.3% of the time spent by the participants using smartphones and GPS loggers, respectively. {"Label"=>"SIGNIFICANCE"} Our study demonstrates the extended capability of using ubiquitous smartphone data with MicroTrac to help reduce time-location uncertainty in air pollution exposure models for epidemiologic and exposure field studies.