With Green Paths routing tool you may compare routes from the shortest to the least polluted ones and choose your own optimal way. You can also see how long time would you spend in different environmental exposure zones. You can use the tool either via an English or Finnish mobile-friendly interface either prior to or during the trips. As a frequent user, you might like to add the browser link to your smartphone home screen! Give it a try: green-paths.web.app
We usually make several trips and experience different travel environments every day. During daily travel, we sense the surrounding environment with all our senses: see the views, hear the sounds or smell the air. This environmental exposure may affect our health and wellbeing in different ways. On one hand, fresh air, quietness, and greenery have been shown to bring travel satisfaction and even health benefits. On the other hand, air pollution and excessive noise may cause physical and mental health problems such as respiratory infections, cardiovascular disease, stress, or even premature death in the worst cases.
Route planners that take into consideration the quality of the travel environment help to avoid harmful exposure, increase health-benefiting encounters with the environment, and thus help to achieve a more satisfying travel experience. This, in turn, supports the use of active travel modes and sustainable transportation.
Inspired by the idea that pleasant routes improve the travel experience by allowing positive interaction with the urban environment, we at the Digital Geography Lab have developed the Green Paths routing tool.
Green Paths routing tool optimises route suggestions per trip length and exposure level to air pollution, traffic noise, and street-level greenery. We derive near real-time air quality data from the FMI-ENFUSER modelling system developed by the Finnish Meteorological Institute (FMI). We deploy the experimental and novel Air Quality Index 2.0, which is a composite measure of the latest hourly levels of nitrogen dioxide (NO2), coarse particles (PM10), fine particles (PM2.5), black carbon (BC), ozone (O3), sulphur dioxide (SO2), and the lung deposited surface area (LDSA). While Air Quality Index is originally a scale attribute, for communication purposes its values are divided into five classes, ranging from the least polluted class “good” (AQI=1) to the most polluted class “very poor” (AQI=5). The index value is assigned based on the pollutant representing the poorest air quality class.
FMI-ENFUSER modelling system deploys historic and real-time air quality measurement data from fixed-site monitoring stations and combines it with data on weather conditions, emissions from traffic and fuel burning, and detailed land use. The spatial resolution of the model output used in the Green Paths routing tool is 13 x 13 m. You may find the latest air quality maps modelled by the FMI-ENFUSER official version (AQI 1.0) under the website of Helsinki Region Environmental Services Authority. More information on the air quality map can be found here.
Traffic noise data is based on an assessment and modelling conducted in the Helsinki Metropolitan Area in 2017 in the cooperation of the respective municipalities and the Finnish Transport Infrastructure Agency. The modelling was done in accordance with the EU Environmental Noise Directive, and the data can be launched from the website of the Finnish Environmental Institute (CC BY 4.0). The methodology is described in the Helsinki Region Infoshare website along with open access data from Helsinki. The data represents typical day-evening-night-time noise levels from the road and rail traffic (A-weighted equivalent continuous sound pressure level, Lden), which is an indicator for noise annoyance. Different noise sources are combined based on the highest typical noise value in each location. The data are arranged as 5db ranges.
We use Green View Index (GVI) for reflecting the amount of green vegetation that is visible at the street level. The GVI data for Helsinki are provided by Toikka et al. (2020) (CC BY 4.0). The data set is developed based on street view imagery and land cover data in the immediate buffer zone of the street segments. For streets and paths where no street view imagery is available, only land cover data about higher than 2m vegetation is used. The GVI is arranged on a scale from 0 to 1 (no vegetation ... full vegetation).
Street and path network data are fetched from OpenStreetMap (OSM) which is a collaborative open-source geodata project (CC-BY-SA 2.0). We deploy walking and cycling routes within the Helsinki capital region. We use OpenTripPlanner to transform OSM data to a graph model suitable for solving multimodal routing problems. The environmental data are joined with the street network graph to enable exposure-optimised routing.
The key elements of the Green Paths routing tool are accessing and pre-processing environmental and street/path network data, defining cost functions for environmental exposures, and optimising routes based on both distance and projected environmental costs by pollutants.
We utilise graph-based least-cost path analysis (LCPA) with Dijkstra’s algorithm for finding the shortest and most pleasant routes. Environmental cost functions are defined separately for air pollution, traffic noise, and street-level greenery to calculate appropriate exposure-based costs for LCPA. In order to suit different situations and sensitivities to pollutants, our route optimisation returns a selection of exposure-optimised routes in addition to the shortest path. Hence, you as the user can make your own decision on a desirable travel-time versus exposure trade-off.
Each route is equipped with the data on how long time you would spend in different exposure zones and compares the exposure durations between the shortest and the alternative route. Green Paths tool also visualises exposure levels by colours, making it intuitive to make travel choices by just comparing different routes on the map.
We support open science and have made the codes public to ensure transparency and support further developments. We encourage the replication of the source code or the use of Green Paths output data via an API in any other application it may advance.
The routing software is published in Zenodo: https://doi.org/10.5281/zenodo.5409403. All codes are accessible from the Digital Geography Lab's GitHUB repository. We appreciate it if you give reference to the original software when applying the codes of Green Paths development elsewhere.
For now, the tool is developed as a proof of concept by advancing its features and functionalities in time. It should be considered as a demonstration of environmentally sensitive routing based on spatially explicit and advancing open access data sets, and it is thus not guaranteed to work smoothly at all times.
The software and user interface is developed by Joose Helle. The Green Paths team involves Joose Helle, Age Poom, Elias Willberg, Tuomas Väisänen and Tuuli Toivonen from the Digital Geography Lab of the University of Helsinki. The development is part of the Urban Innovation Action HOPE – Healthy Outdoor Premises for Everyone and is co-financed by the European Regional Development Fund.
Joose Helle, joose.helle (a) helsinki.fi, Green Paths software development
Age Poom, age.poom (a) helsinki.fi, Green Paths coordination, environmental exposure research