DOI: 10.1594/pangaea.981399
title: Mass concentration of submicron particulate methanesulfonic acid (MSA) measured in the Swiss container during MOSAiC 2019/2020

description: This dataset contains the mass concentration of submicron particulate methanesulfonic acid (MSA) measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to July 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern, using a commercial Aerodyne Research Inc. High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS). The instrument was located behind an automated valve, which switched hourly between a total and an interstitial air inlet, with upper cutoff sizes of 40 and 1 µm respectively (Heutte et al. (2023), Beck et al. (2022), and Dada et al. (2022)). Ambient air was hence sampled alternately every hour from the total and interstitial inlets into an aerodynamic lens with a 1 µm critical orifice and a flow of 0.07 L/min.All data were processed using SQUIRREL v1.65B and PIKA v1.25B within the IGOR Pro v9.00 software. This was done separately for the three distinct periods of available measurements, October to December 2019, March to May, and June to July 2020, as the instrument was each time in a different state (after long down times related to turbo pump failures). A general description of the instrument and of the calibrations for bulk species quantification can be found in Heutte et al. (2023) and the bulk submicron aerosol chemical composition from the AMS can be downloaded at doi:10.1594/PANGAEA.961009.The mass concentration of particulate methanesulfonic acid was determined using the calibrated signal of the CH3SO2+ fragment at the mass-to-charge ratio (m/z) 79 and following the method outlined by Hodshire et al. (2019). The calibration factor applied to the CH3SO2+ ion fragment was equal to 12.1.We applied two corrections. First, the switching valve caused data distortion, observed at every full hour (i.e., when the valve turns and the ambient sampling changes from one inlet to another, there is a brief moment with under-pressure in the inlet lines). Consequently, all data points within ± 2 min of the full hours were removed. Second, during some periods when the inlet switching valve was activated, we observed a difference pattern of mean and standard deviation of the measurements between even and odd hours, most probably caused by a persistent pressure drop in the inlet lines, resulting in a proportional reduction of the concentration measurements. The 1-h arithmetic mean of interstitial inlet measurements and the mean of the two adjacent hours of total inlet measurements were subtracted, and the resulting difference was added as a constant to the data points of the interstitial inlet measurements.This dataset contains a pollution flag ("Flag, pollution") to flag datapoints that were identified as directly influenced by fresh local pollution (e.g., Polarstern exhaust, on-ice diesel generators, skidoos), where a flag equal to 0 indicates clean data and 1 indicates polluted data. The identification method, based on the cosine similarity of the measured mass spectra with a known reference polluted spectrum, is described in Dada et al. (2022). Additionally, a sparse filter with a moving window spanning 60 datapoints (approx. 1h30) was applied to define as entirely polluted periods where more than 60% of the points were already classified as polluted by the cosine similarity method.
description: We encourage data users to refer to Heutte et al. (2023) for a more detailed description of the data acquisition, data processing and corrections applied.We thank the Laboratory for Atmospheric Chemistry at the Paul Scherrer Institute for providing the instrument and expertise.We extracted 90 sec time resolution positional data from the following datasets: Rex (2020), Haas (2020), Kanzow (2020) and Rex (2021ab).