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.

Population groups in vulnerable situations are disproportionally affected by air pollution. Proposals should consider the vulnerability dimension (e.g. for children, older people, women, people with lower socio-economic status, people with underlying health conditions) when approaching different scale analyses and provide recommendations on whether and how links could be made with data on social and spatial inequalities related to air pollution exposure and benefits of mitigation measures in developing inclusive air quality plans and in urban planning.

Where relevant, activities should build and expand on the results of past and ongoing research projects and initiatives with a relevant air quality monitoring and/or modelling component to share experiences, reach synergies and avoid duplication. These could include projects funded under H2020 and Horizon Europe as well as under LIFE strategic integrated projects for clean air, such as LIFE PREPAIR and LIFE Malopolska.

Proposals are encouraged to consider, where relevant, the data, expertise and services offered by European research infrastructures in the environment domain, such as ACTRIS. Concrete efforts should be made to ensure that the data produced is FAIR (Findable, Accessible, Interoperable and Re-usable).

Proposals should, where possible, build on results of and cooperate with AQUILA and FAIRMODE communities and pave the way for the possible transition of the project outcomes into the Copernicus Atmosphere Monitoring Service. This topic is part of the EC-ESA Earth System Science Initiative, and projects should collaborate with related projects funded by ESA’s FuturEO programme and should towards this end include sufficient means and resources for effective coordination.

The Joint Research Centre (JRC) may participate as a member of the consortium selected for funding. In particular, the JRC could, as relevant, promote and support the harmonised use of scientifically sound air quality modelling approaches and help identify best practices in the area. In this regard, JRC would also usefully facilitate interaction with the JRC-chaired Forum for Air quality Modelling (FAIRMODE).

International cooperation is encouraged.