Advancements in the incorporation of complex soot morphology within atmospheric sciences

Soot, also commonly known as black carbon (BC) aerosol, is an important short-lived climate forcer. Although global anthropogenic BC emissions from fossil fuel combustion are expected to decrease, BC remains a significant concern in air pollution hotspots in Asia and Africa. Estimates of the global black carbon direct radiative forcing are still subject to considerable uncertainties, ranging from 0.20 to 0.42 Wm⁻². To reduce these uncertainties, it is crucial to improve the representation of the complex soot morphology in simulations of their optical properties and global models. We have investigated various aspects of the optical properties of morphologically complex soot particles, including field and laboratory measurements, and optical simulations of BC as ‘realistic’ fractal aggregates. Investigations conducted in Delhi, a highly polluted urban environment in Asia, confirmed that fractal morphology is important in reducing the overestimation of aerosol light absorption by commonly used light simulation models by 10 to 80%.

To address the computationally expensive nature of fractal simulations, we propose a new metric known as the morphology index (MI). Additionally, to reduce the computational burden of optical simulations of fractal BC particles, we developed a fast and accurate machine learning-based tool for predicting the optical properties of BC fractal aggregates. We have highlighted the importance of the lack of representation of complex soot particles in global models, and offer methods to facilitate their integration into the atmospheric science community.