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

Authors :
Antti Nurminen
Lasse Johansson
Avleen Malhi
Kary Främling
Iglesias, Carlos A.
Moreno, Jose Ignacio
Rivera, Diego
Adj. Prof. Främling Kary group
Department of Computer Science
Finnish Meteorological Institute
Aalto-yliopisto
Aalto University
Source :
Intelligent Environments, 2020 16th International Conference on Intelligent Environments (IE)
Publication Year :
2020
Publisher :
IEEE, 2020.

Abstract

openaire: EC/H2020/732240/EU//SynchroniCity 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.

Details

ISBN :
978-1-72816-158-7
ISBNs :
9781728161587
Database :
OpenAIRE
Journal :
2020 16th International Conference on Intelligent Environments (IE)
Accession number :
edsair.doi.dedup.....cbd6adf567ebc08c0133f5d7a9a934ed
Full Text :
https://doi.org/10.1109/ie49459.2020.9155068