Abstract Title: | Sustainability impact assessment of Low Emissions Zones in cities integrating hyperlocal air quality measurements and artificial intelligence models |
Presenter Name: | Ms Iris Cuevas Martínez |
Co-authors: | Mr Eduardo Illueca Fernández Mr Alejandro Pujante Pérez Dr Antonio Jesús Jara Valera |
Company/Organisation: | Libelium |
Country: | Spain |
Abstract Information :
Low Emission Zones are a key research topic because of the new regulation requiring cities to implement them, implying a big inversion and might importune the citizens, and it is not guaranteed that the measures will improve air quality in the city, since restricting an area might just produce the traffic to move to another zone, leaving air quality in the same state or even in a worse condition. That is why it is important to make sure that they will have the expected outcome. With this purpose, we propose a simulation tool that would allow the user to select where to implement the Low Emissions Zone and the measures to be taken and predicts the effect these measures would have in the traffic and in the global air quality of the city. To achieve this, the tool uses traffic models that take into account the traffic demand. Those models are used to predict the traffic that would result after the application of the measures, which then should be translated into emissions by calculating the pollutants that the expected vehicles that would circulate after the implementation of the LEZ would produce. We consider that to measure the impact of a Low Emissions Zone it is important to take into account the global air quality situation in the city and not just the traffic emissions or the air quality in the concrete zone of application of the measures. That is why we integrate dispersion models that, taking as an input the traffic emissions and air quality data, are able to predict pollutant propagation and allow the user to see the whole picture of air quality within the city. One of the more renowned dispersion models is CHIMERE, but it is a big-scale model that is not suitable to try to measure impact in the level of detail that we would like. That is why we developed a low-scale dispersion model with the cities topology in mind that bases on the street canyon effect that is observed in narrow streets in cities. The solution proposed has been validated in 7 european cities, and also presents the user with decision helping information, which consists of the current air quality and traffic status of the city and an estimated impact index that predicts the effect that implementing a Low Emission Zone in that area would have in the global air quality of the city.