Pollution mask for the continuous corrected particle number concentration data in 1 min resolution, measured in the Swiss aerosol container during MOSAiC 2019/2020

• Main Authors: Beck, Ivo Fabio, Quéléver, Lauriane, Laurila, Tiia, Jokinen, Tuija, Baccarini, Andrea, Angot, Hélène, Schmale, Julia
• Format: Text
• Language: English
• Published: EPFL Infoscience 2023
• Subjects: Arctic; Beck; Swiss Polar Institute
• Online Access: http://infoscience.epfl.ch/record/300259; https://doi.org/10.1594/pangaea.941335

This dataset contains a pollution flag in 1 min time resolution. It is derived by the pollution detection algorithm (PDA) based on the corrected particle number concentration data (DOI upcoming) measured during the year long MOSAiC expedition from October 2019 to September 2020. With pollution, we refer to emission from the exhaust of the ship stack, snow groomers, diesel generators, ship vents, helicopters and other. Pollution hence reflects locally emitted particles and trace gases, which are not representative of the central Arctic ambient concentrations. The PDA identifies and flags periods of polluted data in the particle number concentration dataset five steps. The first and most important step identifies polluted periods based on the gradient (time-derivative) of a concentration over time. If this gradient exceeds a given threshold, data are flagged as polluted. Further pollution identification steps are a simple concentration threshold filter, a neighboring points filter (optional), a median and a sparse data filter (optional). The detailed methodology of the derivation of the pollution flag is described in Beck et al. (Atmos. Meas. Tech., in prep). A description and download link to the used particle number concentration dataset can be found here: doi:10.1594/PANGAEA.941886. The code of the PDA can be found on Zenodo (Beck et al., 2021; doi:10.5281/zenodo.5761101).Participation of the Swiss Container was co-financed by the Swiss Polar Institute and University of Helsinki. This dataset contains a pollution flag in 1 min time resolution and the corresponding particle number concentration data (doi:10.1594/PANGAEA.941886). The data columns include Event, Time, Latitude, Longitude, Particle number concentration and a pollution flag to indicate polluted periods (0=not polluted, 1=polluted). The pollution flag is derived from the Pollution Detection Algorithm (PDA), a python-based open access script to automatically detect contamination in remote atmospheric time series (Beck et al., Atmos. Meas. Tech., in ...