the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Automated identification of local contamination in remote atmospheric composition time series
Ivo Beck
Hélène Angot
Andrea Baccarini
Lubna Dada
Lauriane Quéléver
Tuija Jokinen
Tiia Laurila
Markus Lampimäki
Nicolas Bukowiecki
Matthew Boyer
Xianda Gong
Martin Gysel-Beer
Tuukka Petäjä
Jian Wang
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Airborne particles affect clouds, climate, and air quality, but it is difficult to determine how their chemical components are mixed within individual particles. We tested a method that estimates this mixing from water-uptake measurements using detailed computer simulations. The method works well in many cases, but can overestimate particle mixing when moderately water-attracting material exists in separate particle types. We then applied this uncertainty framework to long-term observations.
We present a novel version of an aerosol number size distribution instrument, showcasing its capability to measure particle number concentration and particle number size distribution between 1 and 12 nm. Our results show that the instrument agrees well with existing instrumentation and allows for both the accurate measurement of the smallest particles and overlap with more conventional aerosol number size distribution instruments.
hotspotsof interaction. Code and data are open access.