Description: This dataset contains CCN concentrations at five supersaturation levels, averaged to 1 min time resolution, measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern, using the model CCN-100 from Droplet Measurement Technologies (DMT, Boulder, USA). Detailed description of the measurement principle can be found in e.g. Roberts & Nenes (2005). 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., Submitted; Beck et al., 2022; Dada et al., 2022). The measurements were performed in 1-h cycles, with a 0.5 L/min sample flow and a 2 L/min make up flow, where the supersaturations 0.15, 0.2, 0.3, 0.5 and 1.0 % were measured. The supersaturation of 0.15 % is measured for 20 min, as it takes longer to equilibrate, and the remaining supersaturations were measured for 10 min each. The instrument was calibrated in July 2019 before the campaign, and in March and April 2020 during the campaign. Based on the inter-variability of the calculated supersaturation levels during these calibrations, we can expect values ranging from 0.15-0.20, 0.20-0.25, 0.29-0.33, 0.43-0.5, 0.78-1.0 % for the nominal supersaturations of 0.15, 0.2, 0.3, 0.5 and 1.0 %, respectively. The counting error for the CCNC is associated with the error in the optical counting of particles and is about 10 %. Data were removed during the cooling cycle (i.e., the time when the measurement cycle starts again and the temperature is cooled to set the lowest supersaturation), which corresponds roughly to the first 10 min of each hour (so 50 % of the 0.15 % supersaturation period). Additionally, the first minute of the transition between supersaturations was removed before averaging the data to 1 min time resolution. During some time periods, a difference pattern of mean and standard deviation of the measurements between even and odd hours was observed, most probably caused by a persistent pressure drop in the inlet lines, resulting in a proportional reduction of the concentration measurements. For correction, 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. The dataset contains a pollution mask for local pollution (predominantly exhaust from the Research Vessel Polarstern) with 0 indicating clean, and 1 indicating polluted periods (Beck et al., 2022; Beck et al., 2022).

Description: This dataset contains CCN concentrations at five supersaturation levels, averaged to 1 min time resolution, measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern, using the model CCN-100 from Droplet Measurement Technologies (DMT, Boulder, USA). Detailed description of the measurement principle can be found in e.g. Roberts & Nenes (2005). 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., Submitted; Beck et al., 2022; Dada et al., 2022). The measurements were performed in 1-h cycles, with a 0.5 L/min sample flow and a 2 L/min make up flow, where the supersaturations 0.15, 0.2, 0.3, 0.5 and 1.0 % were measured. The supersaturation of 0.15 % is measured for 20 min, as it takes longer to equilibrate, and the remaining supersaturations were measured for 10 min each. The instrument was calibrated in July 2019 before the campaign, and in March and April 2020 during the campaign. Based on the inter-variability of the calculated supersaturation levels during these calibrations, we can expect values ranging from 0.15-0.20, 0.20-0.25, 0.29-0.33, 0.43-0.5, 0.78-1.0 % for the nominal supersaturations of 0.15, 0.2, 0.3, 0.5 and 1.0 %, respectively. The counting error for the CCNC is associated with the error in the optical counting of particles and is about 10 %. Data were removed during the cooling cycle (i.e., the time when the measurement cycle starts again and the temperature is cooled to set the lowest supersaturation), which corresponds roughly to the first 10 min of each hour (so 50 % of the 0.15 % supersaturation period). Additionally, the first minute of the transition between supersaturations was removed before averaging the data to 1 min time resolution. During some time periods, a difference pattern of mean and standard deviation of the measurements between even and odd hours was observed, most probably caused by a persistent pressure drop in the inlet lines, resulting in a proportional reduction of the concentration measurements. For correction, 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. The dataset contains a pollution mask for local pollution (predominantly exhaust from the Research Vessel Polarstern) with 0 indicating clean, and 1 indicating polluted periods (Beck et al., 2022; Beck et al., 2022).

Description: This dataset contains CCN concentrations at five supersaturation levels, averaged to 1 min time resolution, measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern, using the model CCN-100 from Droplet Measurement Technologies (DMT, Boulder, USA). Detailed description of the measurement principle can be found in e.g. Roberts & Nenes (2005). 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., Submitted; Beck et al., 2022; Dada et al., 2022). The measurements were performed in 1-h cycles, with a 0.5 L/min sample flow and a 2 L/min make up flow, where the supersaturations 0.15, 0.2, 0.3, 0.5 and 1.0 % were measured. The supersaturation of 0.15 % is measured for 20 min, as it takes longer to equilibrate, and the remaining supersaturations were measured for 10 min each. The instrument was calibrated in July 2019 before the campaign, and in March and April 2020 during the campaign. Based on the inter-variability of the calculated supersaturation levels during these calibrations, we can expect values ranging from 0.15-0.20, 0.20-0.25, 0.29-0.33, 0.43-0.5, 0.78-1.0 % for the nominal supersaturations of 0.15, 0.2, 0.3, 0.5 and 1.0 %, respectively. The counting error for the CCNC is associated with the error in the optical counting of particles and is about 10 %. Data were removed during the cooling cycle (i.e., the time when the measurement cycle starts again and the temperature is cooled to set the lowest supersaturation), which corresponds roughly to the first 10 min of each hour (so 50 % of the 0.15 % supersaturation period). Additionally, the first minute of the transition between supersaturations was removed before averaging the data to 1 min time resolution. During some time periods, a difference pattern of mean and standard deviation of the measurements between even and odd hours was observed, most probably caused by a persistent pressure drop in the inlet lines, resulting in a proportional reduction of the concentration measurements. For correction, 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. The dataset contains a pollution mask for local pollution (predominantly exhaust from the Research Vessel Polarstern) with 0 indicating clean, and 1 indicating polluted periods (Beck et al., 2022; Beck et al., 2022).

Description: This dataset contains equivalent black carbon (eBC) concentrations, averaged to 10 min time resolution, measured during the year-long MOSAiC expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern, using a commercial aethalometer (model AE33, Magee Scientific, Berkeley, USA). 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. The inlet flow, of 2 liters per minute, was verified biweekly. The dual spot technology of the instrument allowed for a real-time compensation of what is known as the loading effect (Drinovec et al., 2015). Optical absorption was measured at 7 different wavelengths simultaneously, with a 1 second time resolution. We used the absorption at 880 nm (channel 6) to derive eBC, using a mass absorption cross-section value of 7.77 m2g-1. The switching valve caused concentration spikes to be observed at the full hours, hence data points within ± 2 minutes of the full hours are removed. The dataset was averaged to 1 minute time resolution (original time resolution is 1 second) to reduce the largest part of the instrument's noise, and outliers of more than 3 times the standard deviation of an hourly moving window were removed from the 1 minute averaged dataset. During some times for which the switching valve mechanism was on, varying patterns of increased mean and standard deviation of the measurements were observed, due to a pressure drop in the inlet lines. We corrected it by taking the arithmetic means of the data points during interstitial inlet measurements and the two adjacent hours of total inlet measurements, subtracting these two values and adding this difference to the data points of the interstitial inlet measurements. Finally, the data were averaged to 10 minutes time resolution. Based on a visual inspection of the entire dataset, we removed periods of strong noise and intense negative spikes. These artifacts may have emerged from the averaging of the initially noisy 1 second time resolution dataset and/or from the dual spot compensation which may lead to the presence of strong negative outliers right after a large positive outlier. Data collected between June 3rd and June 9th were discarded as Polarstern was within Svalbard's 12 nautical miles zone. The aethalometer dataset was further cleaned for disturbing pollution emissions from local research activities (e.g., exhaust by Polarstern's engine and vents, skidoos, on-ice diesel generators) using a preexisting pollution mask developed by Beck et al. (2022a), where a multi-step pollution detection algorithm was applied on the interstitial CPC dataset at 1 minute time resolution (Beck et al., 2022b). This pollution mask was converted to 10 minutes time resolution by setting a condition where, if more than 1 data point is polluted in a 10 minutes moving window, the entire 10 minutes period is defined as polluted. The resulting flag “Flag_pollution” should be equal to 0 to retain un-polluted data points only.

Description: This dataset contains the bulk size-resolved chemical composition and mass concentration of non-refractory submicron aerosols (NR-PM1) measured during the MOSAiC expedition from October 2019 to July 2020. These include the mass concentrations of sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), chloride (Chl), and organics (Org). The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern, using a commercial High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS, Aerodyne Research, Inc.). One can refer to existing literature (e.g., DeCarlo et al. (2006) and Canagaratna et al. (2007)) for detailed description, functioning principles and field deployment procedures of the 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. (Submitted), 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). Regular on-site calibrations using monodisperse, number concentration-defined, ammonium nitrate (NH4NO3) and ammonium sulfate ((NH4)2SO4) particles were performed to determine the ionization efficiency of NO3- and relative ionization efficiencies of NH4+ and SO42- (Jimenez et al. (2003) and Allan et al. (2003)). An airbeam correction factor was applied to the dataset, along with a time and composition-dependent collection efficiency (CDCE, Middlebrook et al. (2012)). Several times per month, zero measurements were performed using High-Efficiency Particulate Absorbing (HEPA) filters. These were used to (1) adapt the AMS fragmentation table for air fragmentation patterns (in post processing), and (2) compute the detection limits (DL) for the main aerosol chemical species (SO42-, NO3-, NH4+, Chl, and Org) as 3 times the standard deviation from the mean species concentration during filter measurements. At the instrument's native time resolution of 90 s, the DL are equal to (for Oct-Dec, Mar-May, and Jun-Jul, respectively) 0.017, 0.102, and 0.084 µg/m3 for SO42-, 0.011, 0.069 and 0.152 µg/m3 for NO3-, 0.001, 0.027 and 0.261 µg/m3 for NH4+, 0.055, 0.055 and 0.071 µg/m3 for Chl, and 0.284, 0.718 and 1.029 µg/m3 for Org. A mass closure analysis was performed between the total NR-PM1 calculated from the AMS and aethalometer and the one approximated from the mobility diameter (dm) measured by the Scanning Mobility Particle Sizer (SMPS) located in a neighboring container. The mass closure analysis was performed independently for the three periods (Oct-Dec, Mar-May and Jun-Jul) and yielded the following scaling factors: 3.77, 0.65 and 0.35 for the three respective periods. These scaling factors are not applied by default on the AMS timeseries, and the user is left with the decision to apply them or compute new ones. The following periods were removed from the dataset: when the airbeam correction factor was larger than 2 or smaller than 0, outliers (defined as more than 3 times the standard deviation of half an hour moving average, that constitute 〈 1 % of the whole dataset), all calibrations, periods when a HEPA filter was placed in front of the instrument, and data non-representative of ambient conditions (e.g. container air). 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. Finally, the dataset also contains a quality flag for the ammonium timeseries ("Flag_NH4"), as turbo pump failures rendered ammonium measurements very noisy. A value of 1 indicates a quality assured measurement, while a value of 0 indicates a "bad" measure of NH4+ (basically all data after May 24th 2020).

Description: This dataset contains particle number size distributions between 1.06-16.1 μm (aerodynamic diameter) and total concentration averaged to 1 min time resolution, measured with a commercial Aerodynamic Particle Sizer spectrometer (APS model 3321, TSI Incorporated, Minnesota, USA) during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern.

Description: This dataset contains aerosol optical absorption coefficients at seven different wavelengths (babs(λ)), averaged to 10 min time resolution, measured during the year-long MOSAiC expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern, using a commercial aethalometer (model AE33, Magee Scientific, Berkeley, USA). 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. The inlet flow, 2 liters per minute, was verified biweekly. The dual spot technology of the instrument allowed for a real-time compensation of what is known as the loading effect (Drinovec et al., 2015). The instrument reports equivalent black carbon (eBC) mass concentrations at seven different wavelengths (370, 470, 520, 590, 660, 880, and 950 nm), computed from the measured light attenuation at each wavelength on the filter (equation (16) in Drinovec et al., 2015), with a 1 sec time resolution. The data obtained at 880 nm (channel 6: BC6) is the standard for reporting eBC concentrations (Drinovec et al., 2015), and are reported in Heutte et al. (2022). Here, we report the aerosol optical absorption coefficients at all seven wavelengths mentioned above, where the eBC (λ) concentrations were converted to optical absorption coefficients by multiplying them by the default mass absorption cross-section values of 18.47, 14.54, 13.14, 11.58, 10.35, 7.77, and 7.19 m2g-1 for the wavelengths 370, 470, 520, 590, 660, 880, and 950 nm, respectively. These optical absorption coefficients can be used for source apportionment or for the computation of the Absorption Ångström Exponent (AAE, Helin et al., 2021). The switching valve caused concentration spikes to be observed at the full hour, hence data points within ± 2 min of the full hour are removed. The dataset was averaged to 1 min time resolution (original time resolution is 1 second) to reduce the largest part of the instrument's noise, and outliers of more than 3 times the standard deviation of an hourly moving window were removed from the 1-minute averaged dataset. During some times for which the switching valve mechanism was on, varying patterns of increased mean and standard deviation of the measurements were observed, due to a pressure drop in the inlet lines. We corrected it by taking the arithmetic means of the datapoints during interstitial inlet measurements and the two adjacent hours of total inlet measurements, subtracting these two values and adding this difference to the data points of the interstitial inlet measurements. Finally, the data were averaged to 10 min time resolution. Based on a visual inspection of the entire dataset, we removed periods of strong noise and intense negative spikes. These artifacts may have emerged from the averaging of the initially noisy 1 second time resolution dataset and/or from the dual spot compensation which may lead to the presence of strong negative outliers right after a large positive outlier. Data collected between June 3rd and June 9th were discarded as Polarstern was within Svalbard's 12 nautical miles zone. The aethalometer dataset was further cleaned for disturbing pollution emissions from local research activities (e.g., exhaust by Polarstern's engine and vents, skidoos, on-ice diesel generators) using a preexisting pollution mask developed by Beck et al. (2022a), where a multi-step pollution detection algorithm was applied on the interstitial CPC dataset at 1 min time resolution (Beck et al., 2022b). This pollution mask was converted to 10 min time resolution by setting a condition where, if more than 1 data point is polluted in a 10 min moving window, the entire 10 min period is defined as polluted. The resulting flag "Flag_pollution" should be equal to 0 to retain un-polluted data points only.

Description: This dataset contains CCN concentrations at five supersaturation levels, averaged to 1 min time resolution, measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern, using the model CCN-100 from Droplet Measurement Technologies (DMT, Boulder, USA). Detailed description of the measurement principle can be found in e.g. Roberts & Nenes (2005). 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., Submitted; Beck et al., 2022; Dada et al., 2022). The measurements were performed in 1-h cycles, with a 0.5 L/min sample flow and a 2 L/min make up flow, where the supersaturations 0.15, 0.2, 0.3, 0.5 and 1.0 % were measured. The supersaturation of 0.15 % is measured for 20 min, as it takes longer to equilibrate, and the remaining supersaturations were measured for 10 min each. The instrument was calibrated in July 2019 before the campaign, and in March and April 2020 during the campaign. Based on the inter-variability of the calculated supersaturation levels during these calibrations, we can expect values ranging from 0.15-0.20, 0.20-0.25, 0.29-0.33, 0.43-0.5, 0.78-1.0 % for the nominal supersaturations of 0.15, 0.2, 0.3, 0.5 and 1.0 %, respectively. The counting error for the CCNC is associated with the error in the optical counting of particles and is about 10 %. Data were removed during the cooling cycle (i.e., the time when the measurement cycle starts again and the temperature is cooled to set the lowest supersaturation), which corresponds roughly to the first 10 min of each hour (so 50 % of the 0.15 % supersaturation period). Additionally, the first minute of the transition between supersaturations was removed before averaging the data to 1 min time resolution. During some time periods, a difference pattern of mean and standard deviation of the measurements between even and odd hours was observed, most probably caused by a persistent pressure drop in the inlet lines, resulting in a proportional reduction of the concentration measurements. For correction, 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. The dataset contains a pollution mask for local pollution (predominantly exhaust from the Research Vessel Polarstern) with 0 indicating clean, and 1 indicating polluted periods (Beck et al., 2022; Beck et al., 2022).

Description: This dataset contains CCN concentrations at five supersaturation levels, averaged to 1 min time resolution, measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern, using the model CCN-100 from Droplet Measurement Technologies (DMT, Boulder, USA). Detailed description of the measurement principle can be found in e.g. Roberts & Nenes (2005). 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., Submitted; Beck et al., 2022; Dada et al., 2022). The measurements were performed in 1-h cycles, with a 0.5 L/min sample flow and a 2 L/min make up flow, where the supersaturations 0.15, 0.2, 0.3, 0.5 and 1.0 % were measured. The supersaturation of 0.15 % is measured for 20 min, as it takes longer to equilibrate, and the remaining supersaturations were measured for 10 min each. The instrument was calibrated in July 2019 before the campaign, and in March and April 2020 during the campaign. Based on the inter-variability of the calculated supersaturation levels during these calibrations, we can expect values ranging from 0.15-0.20, 0.20-0.25, 0.29-0.33, 0.43-0.5, 0.78-1.0 % for the nominal supersaturations of 0.15, 0.2, 0.3, 0.5 and 1.0 %, respectively. The counting error for the CCNC is associated with the error in the optical counting of particles and is about 10 %. Data were removed during the cooling cycle (i.e., the time when the measurement cycle starts again and the temperature is cooled to set the lowest supersaturation), which corresponds roughly to the first 10 min of each hour (so 50 % of the 0.15 % supersaturation period). Additionally, the first minute of the transition between supersaturations was removed before averaging the data to 1 min time resolution. During some time periods, a difference pattern of mean and standard deviation of the measurements between even and odd hours was observed, most probably caused by a persistent pressure drop in the inlet lines, resulting in a proportional reduction of the concentration measurements. For correction, 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. The dataset contains a pollution mask for local pollution (predominantly exhaust from the Research Vessel Polarstern) with 0 indicating clean, and 1 indicating polluted periods (Beck et al., 2022; Beck et al., 2022).

Description: This dataset contains CCN concentrations at five supersaturation levels, averaged to 1 min time resolution, measured during the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-deck of Research Vessel Polarstern, using the model CCN-100 from Droplet Measurement Technologies (DMT, Boulder, USA). Detailed description of the measurement principle can be found in e.g. Roberts & Nenes (2005). 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., Submitted; Beck et al., 2022; Dada et al., 2022). The measurements were performed in 1-h cycles, with a 0.5 L/min sample flow and a 2 L/min make up flow, where the supersaturations 0.15, 0.2, 0.3, 0.5 and 1.0 % were measured. The supersaturation of 0.15 % is measured for 20 min, as it takes longer to equilibrate, and the remaining supersaturations were measured for 10 min each. The instrument was calibrated in July 2019 before the campaign, and in March and April 2020 during the campaign. Based on the inter-variability of the calculated supersaturation levels during these calibrations, we can expect values ranging from 0.15-0.20, 0.20-0.25, 0.29-0.33, 0.43-0.5, 0.78-1.0 % for the nominal supersaturations of 0.15, 0.2, 0.3, 0.5 and 1.0 %, respectively. The counting error for the CCNC is associated with the error in the optical counting of particles and is about 10 %. Data were removed during the cooling cycle (i.e., the time when the measurement cycle starts again and the temperature is cooled to set the lowest supersaturation), which corresponds roughly to the first 10 min of each hour (so 50 % of the 0.15 % supersaturation period). Additionally, the first minute of the transition between supersaturations was removed before averaging the data to 1 min time resolution. During some time periods, a difference pattern of mean and standard deviation of the measurements between even and odd hours was observed, most probably caused by a persistent pressure drop in the inlet lines, resulting in a proportional reduction of the concentration measurements. For correction, 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. The dataset contains a pollution mask for local pollution (predominantly exhaust from the Research Vessel Polarstern) with 0 indicating clean, and 1 indicating polluted periods (Beck et al., 2022; Beck et al., 2022).