Dynamic assessment of exposure to air pollution using mobile phone data.

Tijs Neutens,Wouter Lefebvre,Nico Van de Weghe,Bart Dewulf,Carolien Beckx,Gerdy Seynaeve,Charlotte Vanpoucke

doi:10.1186/s12942-016-0042-z

Abstract

BackgroundExposure to air pollution can have major health impacts, such as respiratory and cardiovascular diseases. Traditionally, only the air pollution concentration at the home location is taken into account in health impact assessments and epidemiological studies. Neglecting individual travel patterns can lead to a bias in air pollution exposure assessments.MethodsIn this work, we present a novel approach to calculate the daily exposure to air pollution using mobile phone data of approximately 5 million mobile phone users living in Belgium. At present, this data is collected and stored by telecom operators mainly for management of the mobile network. Yet it represents a major source of information in the study of human mobility. We calculate the exposure to NO2 using two approaches: assuming people stay at home the entire day (traditional static approach), and incorporating individual travel patterns using their location inferred from their use of the mobile phone network (dynamic approach).ResultsThe mean exposure to NO2 increases with 1.27 μg/m3 (4.3 %) during the week and with 0.12 μg/m3 (0.4 %) during the weekend when incorporating individual travel patterns. During the week, mostly people living in municipalities surrounding larger cities experience the highest increase in NO2 exposure when incorporating their travel patterns, probably because most of them work in these larger cities with higher NO2 concentrations.ConclusionsIt is relevant for health impact assessments and epidemiological studies to incorporate individual travel patterns in estimating air pollution exposure. Mobile phone data is a promising data source to determine individual travel patterns, because of the advantages (e.g. low costs, large sample size, passive data collection) compared to travel surveys, GPS, and smartphone data (i.e. data captured by applications on smartphones).

Highlights

Exposure to air pollution can have major health impacts, such as respiratory and cardiovascular dis‐ eases
Hourly air pollution concentrations are preferably used over daily averages to maximise the level of detail when combining air pollution with individual travel patterns
This study shows that for epidemiological studies and exposure assessments, it is relevant to incorporate individual travel patterns to estimate the exposure to air pollution

Summary

Introduction

Exposure to air pollution can have major health impacts, such as respiratory and cardiovascular dis‐ eases. To assess individual travel patterns, often self-reported household travel surveys are used [26]. Major disadvantages of this approach are the large non-response rate [27], non-representative samples [28], and high costs [26]. Dewulf et al Int J Health Geogr (2016) 15:14 mathematical models of travel patterns can be used [18, 24, 29] This approach allows to draw more quantitative conclusions from a larger population size, but results are only valid for situations similar to those for which their initial parameters were estimated. Data collection with GPS or smartphone devices is often intensive for both researchers and participants, expensive and only a limited number of people can be tracked

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Discussion

Conclusion