Developing effective air quality planning strategies through innovative multi-scale modelling

Expected outcome

Project results are expected to contribute to all of the following outcomes: public authorities obtain access to enhanced and innovative modelling capabilities to support air quality planning at various policy levels in a coherent way; society benefits from improved governance processes and effective air quality planning strategies, aiming at mitigating air pollution and reducing population exposure, as well as from far more targeted air pollution alerts; public authorities, including EU policy-makers and the EEA, receive faster, more comprehensive scientific evidence and tools, enabling more effective EU air quality policy implementation and providing citizens with reliable, detailed information and peak pollution warnings to reduce health impacts.

Scope

The air we breathe is often polluted, which can lead to serious health problems and even premature death. To address this public health issue, it is essential to understand how pollutants move and interact in the air at different scales, from regional to street level and at different time periods during the day or in different seasons. However, current models used to predict air quality have limitations, particularly in terms of their grid resolution levels and their limited ability to accurately capture the complex interactions between different scales. This can lead to uncertainties and inaccuracies in assessing and predicting air quality, making it challenging to develop and take effective measures to improve air quality. This topic aims to improve these capabilities by developing a chain of innovative integrated models, relatively easy to use and interpret, that can simulate the air quality situation in different scales and types of areas, including at ‘micro-scale’, and by integrating a temporal-scale dimension, also taking into account emissions into the ambient atmosphere from indoor environments. This should support the development of effective air quality planning strategies at various levels, ultimately helping to reduce air pollution and protect public health. Moreover, it should support the requirements in the revised Ambient Air Quality Directive as regards the development of Air Quality Roadmaps and Air Quality Plans, and for the design and planning of the network of monitoring stations. More specifically, proposals should: develop comprehensive multi-scale modelling chains possibly with two-way nesting capabilities (TRL 5), addressing air quality assessment, including spatial and temporal representativeness, and atmospheric processes of air pollution. Incorporate and improve urban canopy parameterization to better account for complex interactions between urban structures and air pollutants, including the role of urban vegetation in mitigating and/or fostering the formation and/or accumulation of specific air pollutants, with an emphasis on air pollutants with the highest health impacts; analyse the current limitations associated with the integration of different models and multiple spatial/ temporal scales in a single modelling system and develop methods to improve and integrate the existing air quality models and required input datasets (TRL 5); develop, configure and validate innovative micro-scale modelling systems at very high resolution with the aim of modelling and evaluating the impact of air quality measures to minimize, mitigate, and prevent exceedances at hotspot locations (TRL 5); provide guidelines for air quality modelling to support decision making to improve air quality at all scales, including by harmonizing different types of models within an integrated system, as well as promoting the use and development of multi-scale online modelling systems.

What this means for cities and regions

City and regional authorities responsible for air-quality plans under the revised Ambient Air Quality Directive. Topic budget €9.8 million; 2 grants expected; around €4.9 million per project. Opens 20 April 2027; closes 22 September 2027. Street-level modelling nests inside the Copernicus Atmosphere Monitoring Service and Sentinel-5P observations — a direct downstream use of EU space data.