Exploiting crowdsourced geographic information and GIS for assessment of air pollution exposure during active travel

Yeran Sun,Zhang Liu,Yashar Moshfeghi

doi:10.1016/j.jth.2017.06.004

Abstract

Improvement on assessment of air pollution exposure will enhance assessment of health risk-benefit when active travel (cycling and walking). Earlier studies assessed air pollution exposure according to travel time and city-level air pollution. The lack of spatially fine-grained travel data is a barrier to an accurate assessment of air pollution exposure. Due to a high-level spatial granularity, Strava Metro provides an opportunity to assessing air pollution exposure in combination with spatially varying air pollution concentrations. Strava Metro anonymized and aggregated a large volume of users’ traces to streets for each city. In this study, to explore the potential of crowdsourced geographic information in research of active travel and health, we used Strava Metro data and GIS technologies to assess air pollution exposure in Glasgow, UK. Particularly, we incorporated time of the trip to assess average inhaled dose of pollutant during a single cycling or pedestrian trip. Empirical results demonstrate that Strava Metro data provides an opportunity to an assessment of average air pollution exposure during active travel. Additionally, to demonstrate the potential of Strava Metro data in policy-making, we explored the spatial association of air pollution concentration and active travel. As a result, we identified areas that require investment priority, and finally offered implications for policies.

Highlights

Through enhancing physical activity, active travel produces health benefit (Forsyth et al, 2012; Oja et al, 1998, 2011; Pucher et al, 2010; Wen and Rissel, 2008)
Due to a high-level spatial granularity, Strava Metro provides an opportunity to assessing air pollution exposure in combination with spatially varying air pollution concentrations (Sun and Mobasheri, 2017)
Unlike Strava Metro data which has a large spatial coverage, average daily flow (AADF) data covers only 119 links across Glasgow. We matched those links with streets from the Strava Metro data based on spatial proximity (a 5-m threshold), road name, start junction name and end junction name

Summary

Introduction

Active travel (cycling or walking) produces health benefit (Forsyth et al, 2012; Oja et al, 1998, 2011; Pucher et al, 2010; Wen and Rissel, 2008). As outdoor physical activities cycling and walking are of risks, including traffic accidents and air pollution exposure (Weichenthal et al, 2011; de Nazelle et al, 2013; Hollingworth et al, 2014). Earlier studies assessed air pollution exposure according to travel time and city-level air pollution. In the era of Big Data, a large volume of cycling and walking traces generated by individuals are becoming potential data for studies of travel and health (Prins et al, 2014; Duncan et al, 2009; Dill, 2009; Griffin and Jiao, 2015; Sun and Mobasheri, 2017)

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Conclusion