A Clean Air Journey Planner for pedestrians using high resolution near real time air quality data

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Date
2020-07
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Mcode
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Language
en
Pages
8
44-51
Series
Proceedings of the 2020 16th International Conference on Intelligent Environments, IE 2020
Abstract
Air pollution is a severe health issue. In urban environments, traffic is the main pollution source. Pollution disperses from main roads to the environment depending on weather conditions and city structure. Given dense air quality data, one could create routes that optimize journeys to avoid polluted air. We provide a methodology for this, and have implemented a Clean Air Journey Planner for the City of Helsinki. We have done this by modifying the existing Open Source journey planner (the Digitransit platform), extended by integrating high resolution (13m grid size) air quality data generated hourly with the ENFUSER dissipation model by the Finnish Meteorological Institute. The Planner is suited for pedestrians and allows citizens to find routes with less pollution. It is the first to utilize near real time updated high resolution air quality data directly in the routing core of a widely used Open Source journey planner.
Description
| openaire: EC/H2020/732240/EU//SynchroniCity
Keywords
air quality, ENFUSER, pollution avoidance, route planning
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Citation
Nurminen, A, Malhi, A, Johansson, L & Framling, K 2020, A Clean Air Journey Planner for pedestrians using high resolution near real time air quality data . in C A Iglesias, J I Moreno & D Rivera (eds), Proceedings of the 2020 16th International Conference on Intelligent Environments, IE 2020 ., 9155068, IEEE, pp. 44-51, International Conference on Intelligent Environments, Madrid, Spain, 20/07/2020 . https://doi.org/10.1109/IE49459.2020.9155068