the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The impact of temperature inversions on black carbon and particle mass concentrations in a mountainous area
Griša Močnik
Honey Dawn C. Alas
Andrea Cuesta-Mosquera
Luka Drinovec
Asta Gregorič
Matej Ogrin
Kay Weinhold
Irena Ježek
Thomas Müller
Martin Rigler
Maja Remškar
Dominik van Pinxteren
Hartmut Herrmann
Martina Ristorini
Maik Merkel
Miha Markelj
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.
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Clouds over the Southern Ocean are crucial to Earth's energy balance, but understanding the factors that control them is complex. Our research examines how weather patterns affect tiny particles called cloud condensation nuclei (CCN), which influence cloud properties. Using data from Kennaook / Cape Grim, we found that winter air from Antarctica brings cleaner conditions with lower CCN, while summer patterns from Australia transport more particles. Precipitation also helps reduce CCN in winter.
Cited articles
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.
real-world laboratoryconditions...