According to the World Health Organisation, air pollution is the number one environmental threat to public health. In Barcelona, the only two measuring stations close to traffic routes recurrently exceed the legislated limits of annual average pollution. To characterise and minimise the exposure of citizens, the use of numerical models in combination with observational data become fundamental tools. Despite recent efforts, air quality modelling at the microscale (street staircase) presents a significant uncertainty associated with the limited number of traffic and air quality observations. Away from the measurement points and outside the conditions under which a model has been calibrated, this uncertainty increases significantly. The aim of this proposal is to co-develop a tool for reporting uncertainty in air quality simulations that supports and provides evidence for planning and management policies. The spatial distribution of uncertainty is key to interpreting modelling results: it allows prioritisation of regions to be monitored in future measurement campaigns and enables robust identification of vulnerable regions. In addition, it allows complementing health impact studies and urban planning in order to incorporate uncertainty in the analysis of their respective results. Currently, there are three air quality modelling systems at the microscale in the Barcelona region. To guarantee the applicability of the tool, a reproducible and transversal methodology is proposed for all the current systems, based on the post-processing of the models using geostatistical techniques. The co-design of this tool includes relevant social agents of the city, representatives of the public administration and industry, as well as a multidisciplinary scientific team in order to co-define the information layers and visualisation resources necessary to respond to the needs of the users.
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