Quantifying population exposure to air pollution using individual mobility patterns inferred from mobile phone data.
M M Nyhan1,2,3, I Kloog4, R Britter5
1Department of Environmental Health, Harvard School of Public Health, Harvard University, Boston, MA, 02115, USA. nyhan@hsph.harvard.edu.
Journal of Exposure Science & Environmental Epidemiology
|April 28, 2018
Summary
Mobile phone data refines air pollution exposure assessment for large populations. Ignoring daily mobility, like commuting, can miscalculate health effects from fine particulate matter (PM2.5).
Area of Science:
- Environmental epidemiology
- Public health
- Geospatial analysis
Background:
- Accurate assessment of population-level air pollution exposure is crucial for environmental epidemiology.
- Mobile device data offers novel opportunities to track human mobility patterns.
- Existing exposure assessment methods often overlook individual daily movement patterns.
Purpose of the Study:
- To evaluate the utility of mobile device data for refining air pollution exposure estimates in large populations.
- To compare exposure metrics that incorporate daily mobility versus residence-only data.
- To investigate the impact of mobility patterns on exposure misclassification.
Main Methods:
- Utilized cellular network data to infer home and work locations for over 400,000 mobile phone users.
- Developed a spatiotemporal model combining Aerosol Optical Depth and Land Use Regression to predict PM2.5 concentrations.
- Assigned individual PM2.5 exposures based on modeled concentrations at both home and work locations.
Main Results:
- Demonstrated the feasibility of quantifying individual air pollution exposures using mobile device data at an unprecedented scale.
- Found a bias of 0.91 in mean annual PM2.5 exposures when using residence-only data compared to a mobility-inclusive metric.
- Highlighted that neglecting daily mobility can lead to significant misclassification in health effect estimates.
Conclusions:
- Mobile device data enables more accurate and granular assessment of population air pollution exposure.
- Incorporating daily mobility patterns is essential for reducing exposure misclassification in epidemiological studies.
- The proposed framework can significantly advance environmental epidemiological research by improving exposure assessment.
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