the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Importance of size representation and morphology in modelling optical properties of black carbon: comparison between laboratory measurements and model simulations
Baseerat Romshoo
Mira Pöhlker
Alfred Wiedensohler
Sascha Pfeifer
Jorge Saturno
Andreas Nowak
Krzysztof Ciupek
Paul Quincey
Konstantina Vasilatou
Michaela N. Ess
Maria Gini
Konstantinos Eleftheriadis
Chris Robins
François Gaie-Levrel
Thomas Müller
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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.
We compared near real-time and benchtop XRF spectrometers measuring trace elements in airborne particles across three European cities. Results show filter material dictates accuracy: Teflon yielded strong inter-instrument agreement, while quartz caused systematic attenuation errors for light elements. Because empirical corrections left residual biases, using optimal substrates—preferably Teflon—is essential for accurately tracking pollution sources.
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.
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Aitken mode). Our study provides a general framework to estimate under which aerosol and cloud conditions Aitken mode particles affect clouds.