Modeling the Black and Brown Carbon Absorption and Their Radiative Impact: The June 2023 Intense Canadian Boreal Wildfires Case Study
Paolo Tuccella, Ludovico Di Antonio, Andrea Di Muzio, Valentina Colaiuda, Raffaele Lidori, Laurent Menut, Giovanni Pitari, Edoardo Raparelli
- Year
- 2025
- Citations
- 8
- Access
- Open access
Abstract
Abstract Black carbon (BC) and brown carbon (BrC) are light‐absorbing aerosols with significant climate impacts, but their absorption properties and direct radiative effect (DRE) remain uncertain. We simulated BC and BrC absorption during the intense Canadian boreal wildfires in June 2023 using an enhanced version of CHIMERE chemical and transport model. The study focused on a domain extending from North America to Eastern Europe, including the Arctic up to 85°N. The enhanced model includes an update treatment for BC absorption enhancement and a BrC aging scheme accounting for browning and blanching through oxidation. Validation against Aerosol Robotic Network and satellite data showed the model accurately reproduced aerosol optical depth (AOD) at multiple wavelengths, both near wildfire sources and during transoceanic transport to Europe. Improvements were observed in simulations of absorbing aerosol optical depth (AAOD) compared with the baseline model. Significant enhancements were achieved in capturing the spatial distribution of aerosol absorption in areas affected by wildfire emissions. For June 2023, the regional all‐sky DRE attributed to Canadian wildfires was reduced from −2.1 W/m 2 in the control model to −1.9 W/m 2 in the enhanced model. This corresponded to an additional warming effect of +0.2 W/m 2 (+10%) due to the advanced treatment of BC and BrC absorption. These results indicate the importance of accurate aerosol absorption modeling in regional climate predictions, during large‐scale biomass burning events. They also highlight potential overestimations of cooling effects in traditional models, emphasizing the need of improved aerosol parameterization to better simulate the DRE and for evaluating the impacts of mitigation strategies.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992