the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Numerical simulation of the impact of COVID-19 lockdown on tropospheric composition and aerosol radiative forcing in Europe
Simon F. Reifenberg
Anna Martin
Matthias Kohl
Sara Bacer
Zaneta Hamryszczak
Ivan Tadic
Lenard Röder
Daniel J. Crowley
Horst Fischer
Katharina Kaiser
Johannes Schneider
Raphael Dörich
John N. Crowley
Laura Tomsche
Andreas Marsing
Christiane Voigt
Andreas Zahn
Christopher Pöhlker
Bruna A. Holanda
Ovid Krüger
Ulrich Pöschl
Mira Pöhlker
Patrick Jöckel
Marcel Dorf
Ulrich Schumann
Jonathan Williams
Birger Bohn
Joachim Curtius
Hardwig Harder
Hans Schlager
Jos Lelieveld
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Our research explored changes in ozone levels in the northwest Pacific region over 30 years, revealing a significant increase in the middle-to-upper troposphere, especially during spring and summer. This rise is influenced by both stratospheric and tropospheric sources, which affect climate and air quality in East Asia. This work underscores the need for continued study to understand underlying mechanisms.
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.