the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Absorption instruments inter-comparison campaign at the Arctic Pallas station
John Backman
Henri Servomaa
Aki Virkkula
Maria I. Gini
Konstantinos Eleftheriadis
Thomas Müller
Sho Ohata
Yutaka Kondo
Antti Hyvärinen
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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.