• A new online tool developed by the Barcelona Supercomputing Center allows visualizing and downloading uncertainty in Barcelona's urban air quality simulations.
• Two co-creation workshops ensured the uncertAIR tool's design was intuitive and met the diverse needs of users.
• The platform is aimed to provide public administration, businesses, and researchers with vital air quality data for policymaking, planning, and analysis.

The Earth System Services (ESS) group at the Earth Sciences Department of the Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC-CNS) has recently launched the uncertAIR online tool. It has been designed to report uncertainty in urban air quality simulations, aiming to provide the necessary tools to calculate and communicate the uncertainty of the air quality model in ​​Barcelona’s inner-city area. The outcome is an interactive platform that allows users to visualize and download Barcelona’s air quality data.

The shiny app has been developed by Álvaro Criado, Antonia Frangeskou and Diana Urquiza from the ESS group at BSC and has been funded by the Barcelona City Council.

“To ensure the tool meets the needs of diverse users, including policymakers, researchers, social agents, NGOs, and private companies, two co-creation workshops were held, along with several interviews with potential users”, commented Cristina Carnerero, one of the main project leaders, a member of the ESS group of the BSC. The first workshop focused on identifying the various needs users might have when consulting air quality data. In the second workshop, participants were able to test the tool to ensure it met their requirements, that the interface was intuitive and easy to use, and that all functionalities worked as expected. She added: “This co-creation approach helped develop a functional, user-friendly and visually appealing online tool that makes critical information about air pollution in Barcelona easily accessible and understandable.”

The platform’s main feature is an interactive dashboard, where users can visualize results overlaid on a city map and download the data for further analysis. The dashboard also allows for selecting the variable of interest (concentration, uncertainty or probability of exceedance of legal thresholds). Users can choose the spatial resolution, the year of interest and the averaging period (annual or daily averages). Additionally, different layers of city features and points of interest, such as parks, health centres, and schools, can be overlaid on the map. The platform offers two different resolutions to meet the needs of different levels of users: high-resolution (20 m x 20 m) annual averages and lower-resolution (census areas) data for both annual and daily averages. To better communicate the concept of uncertainty in air quality simulations, the platform allows selecting, in addition to the simulated concentration of the air pollutant and the associated uncertainty, the probability of exceeding the legal annual limit value. The website also provides a glossary and methodology section to help non-expert users understand these concepts and place them in the context of the current and future air quality guidelines and legislation.

The uncertAIR platform has been made available to the public administration for policy-making, to social actors and the public for providing vital information on the risks of public exposure to poor air quality, to the urban planning and air quality companies business sectors for probabilistic air quality information, and to the scientific community for estimating and communicating uncertainty when publishing new simulation results.

Jan Mateu, leader of the air quality team at the BSC-ESS group and co-PI of the project, stated: “uncertAIR leverages the in-depth knowledge of atmospheric chemistry and local emissions developed over more than a decade in the BSC's Earth Science Department. For the first time, we have scientifically formalised model uncertainties and made them publicly available because we believe this is an asset when analysing air quality data.”