Keywords
ClairCity, air quality modelling, air pollution reduction, citizens engagement, European cities
Start Date
15-9-2020 11:00 AM
End Date
15-9-2020 11:20 AM
Abstract
ClairCity is a research project funded by the EU Horizon 2020 programme, which aims at improving future air quality and carbon policies in European cities by initiating new modes of engaging citizens, stakeholders and policymakers. ClairCity assessed environmental, health and economic impacts, through a quantification framework. This framework consists of an integrated urban module based on the household and dwelling characteristics, emission data (road transport, industrial and residential), air quality patterns and related population exposure, health-related impacts and costs, and carbon footprint estimates. The ClairCity framework contributed to apportion air pollution not only by technology, but also by citizens’ behaviour, considering the baseline as well as future scenarios translating the expectations of citizens and local experts. A distinct final Unified Policy Scenario was designed for each of the six pilot cases of the ClairCity project. For the urban area of Bristol, the final Unified Scenario will lead to a maximum reduction of 87% of the NO2 concentrations in 2050, and a maximum reduction of 57% of the PM2.5 concentrations. For the Aveiro region, another pilot case of ClairCity, a distinct Unified Policy Scenario was designed, leading to a maximum reduction of 84% of the NO2 concentrations in 2050, and a maximum reduction of only 17% of the PM2.5 concentrations. The slight decrease of the PM2.5 concentrations is mainly associated with the lack of measures focusing on the citizens’ practices of wood burning for residential heating. In conclusion, the overall air quality will significantly improve in 2050 with the implementation of the Unified Scenarios over the six pilot cases of the ClairCity project. In each pilot NO2, PM10 and PM2.5 concentrations will distinctly decrease depending on the current air quality status of each city and on the distinct levels of ambition of the scenarios.
Modelling the impact of citizens-led scenarios on air quality in European urban areas
ClairCity is a research project funded by the EU Horizon 2020 programme, which aims at improving future air quality and carbon policies in European cities by initiating new modes of engaging citizens, stakeholders and policymakers. ClairCity assessed environmental, health and economic impacts, through a quantification framework. This framework consists of an integrated urban module based on the household and dwelling characteristics, emission data (road transport, industrial and residential), air quality patterns and related population exposure, health-related impacts and costs, and carbon footprint estimates. The ClairCity framework contributed to apportion air pollution not only by technology, but also by citizens’ behaviour, considering the baseline as well as future scenarios translating the expectations of citizens and local experts. A distinct final Unified Policy Scenario was designed for each of the six pilot cases of the ClairCity project. For the urban area of Bristol, the final Unified Scenario will lead to a maximum reduction of 87% of the NO2 concentrations in 2050, and a maximum reduction of 57% of the PM2.5 concentrations. For the Aveiro region, another pilot case of ClairCity, a distinct Unified Policy Scenario was designed, leading to a maximum reduction of 84% of the NO2 concentrations in 2050, and a maximum reduction of only 17% of the PM2.5 concentrations. The slight decrease of the PM2.5 concentrations is mainly associated with the lack of measures focusing on the citizens’ practices of wood burning for residential heating. In conclusion, the overall air quality will significantly improve in 2050 with the implementation of the Unified Scenarios over the six pilot cases of the ClairCity project. In each pilot NO2, PM10 and PM2.5 concentrations will distinctly decrease depending on the current air quality status of each city and on the distinct levels of ambition of the scenarios.
Stream and Session
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