the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Optical properties of coated black carbon aggregates: numerical simulations, radiative forcing estimates, and size-resolved parameterization scheme
Baseerat Romshoo
Thomas Müller
Sascha Pfeifer
Jorge Saturno
Andreas Nowak
Krzysztof Ciupek
Paul Quincey
Alfred Wiedensohler
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Through the use of our machine-learning-based optical model, realistic BC morphologies can be incorporated into atmospheric science applications that require highly accurate results with minimal computational resources. The results of the study demonstrate that the predictions of single-scattering albedo (ω) and mass absorption cross-section (MAC) were improved over the conventional Mie-based predictions when using the machine learning method.
Through the use of our machine-learning-based optical model, realistic BC morphologies can be incorporated into atmospheric science applications that require highly accurate results with minimal computational resources. The results of the study demonstrate that the predictions of single-scattering albedo (ω) and mass absorption cross-section (MAC) were improved over the conventional Mie-based predictions when using the machine learning method.
real-world laboratoryconditions was conducted. We found that measured black carbon (eBC) and particulate matter (PM) in rural shallow terrain depressions with residential wood burning could be much greater than predicted by models. The exceeding levels are a cause for concern since similar conditions can be expected in numerous hilly and mountainous regions across Europe, where approximately 20 % of the total population lives.