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

Sun, Y., Moshfeghi, Y. and Liu, Z. (2017) Exploiting crowdsourced geographic information and GIS for assessment of air pollution exposure during active travel. Journal of Transport and Health, 6 . pp. 93-104. ISSN 2214-1405

Full content URL: https://doi.org/10.1016/j.jth.2017.06.004

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Item Type:Article
Item Status:Live Archive


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.

Additional Information:cited By 19
Keywords:Crowdsourced geographic information, Strava Metro, Active travel, Air pollution exposure, Particulate matter
Subjects:F Physical Sciences > F891 Geographical Information Systems
Divisions:College of Science > School of Geography
ID Code:49391
Deposited On:19 May 2022 09:12

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