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Health implications of model uncertainties related to carbonaceous aerosols

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Pozzer,  Andrea
Atmospheric Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

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Lelieveld,  Jos
Atmospheric Chemistry, Max Planck Institute for Chemistry, Max Planck Society;

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Citation

Paisi, N., Kushta, J., Pozzer, A., & Lelieveld, J. (2024). Health implications of model uncertainties related to carbonaceous aerosols. In EGU General Assembly 2024, Vienna, Austria & Online. doi:10.5194/egusphere-egu24-2061.


Cite as: https://hdl.handle.net/21.11116/0000-000F-540B-7
Abstract
In EGU General Assembly 2024, Vienna, Austria & Online

Exposure to fine particulate matter (PM2.5) leads to increased morbidity and excess mortality. Air quality models are powerful tools for air pollutants simulation and are useful for health impact applications. The impact of each PM2.5 component on human health is probably unequal due to the specific toxicity of each specie. Specifically, carbonaceous aerosols (e.g., black carbon and organic aerosols), which are emitted from combustion related sources have been widely assessed for their oxidative capacity and toxicity. The accuracy of air quality modeling is highly dependent on the input data and the representation of meteorology. Due to their complex formation pathways, organic aerosols have been consistently underestimated by several air quality models. Therefore, health impact studies that focus on these aerosols might underestimate their estimated health effect. In this study, the Weather Research and Forecasting Model, coupled with chemistry (WRF-Chem) is used to simulate PM2.5 and the carbonaceous species over Europe. We evaluate the model for its ability to represent accurate exposure levels of PM2.5 with a focus on organic aerosols, and how their modeling uncertainties can influence excess mortality estimates. We take into account the potentially increased contribution of carbonaceous aerosols to excess mortality through several assumptions on their specific toxicity.