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. High-time-resolution measurements of in situ aerosol and cloud propertiesprovide the ability to study regional atmospheric processes that occur ontimescales of minutes to hours. However, one limitation to this approach isthat continuous measurements often include periods when the data collectedare not representative of the regional aerosol. Even at remote locations,submicron aerosols are pervasive in the ambient atmosphere with manysources. Therefore, periods dominated by local aerosol should be identifiedbefore conducting subsequent analyses to understand aerosol regionalprocesses and aerosol–cloud interactions. Here, we present a novel method tovalidate the identification of regional baseline aerosol data by applying amathematical algorithm to the data collected at the U.S. Department ofEnergy's (DOE) Atmospheric Radiation Measurement (ARM) user facility in theeastern North Atlantic (ENA). The ENA central facility (C1) includes an aerosol observing system (AOS) for the measurement of aerosol physical,optical, and chemical properties at time resolutions from seconds tominutes. A second temporary supplementary facility (S1), located∼0.75 km from C1, was deployed for ∼1 yearduring the Aerosol and Cloud Experiments (ACE-ENA) campaign in 2017. First, we investigate the local aerosol at both locations. We associateperiods of high submicron number concentration (Ntot) in the fine-modecondensation particle counter (CPC) and size distributions from theUltra-High Sensitivity Aerosol Spectrometer (UHSAS) as a function of winddirection using a meteorology sensor with local sources. Elevatedconcentrations of Aitken-mode (&lt; 100 nm diameter) particles wereobserved in correspondence with the wind directions associated with airportoperations. At ENA, the Graciosa Airport and its associated activities werefound to be the main sources of high-concentration aerosol events at ENA,causing peaks in 1 min Ntot that exceeded 8000 and10 000 cm−3 at C1, in summer and winter, respectively, and 5000 cm−3 at S1 in summer. Periods with high Ntot not associated withthese wind directions were also observed. As a result, the diverse localsources at ENA yielded a poor relationship between Ntot measurementscollected at C1 and S1 (R2=0.03 with a slope =0.05±0.001). As a first approach to mask these events, the time periods when thewind direction was associated with the airport operations (west to northwestand southeast to south at C1 and east to south at S1) were applied. Themeteorological masks removed 38.9 % of the data at C1 and 43.4 % at S1,and they did not significantly improve the relationship between the twosites (R2=0.18 with a slope =0.06±0.001). Due to the complexity of high-Ntot events observed at ENA, we developand validate a mathematical ENA Aerosol Mask (ENA-AM) to identify high-Ntot events using 1 min resolution data from the AOS CPC at C1 andS1. After its parameterization and application, ENA-AM generated a highcorrelation between Ntot in the summer at C1 and S1 (R2=0.87with a slope =0.84±0.001). We identified the regional baseline atENA to be 428±228 cm−3 in the summer and 346±223 cm−3 in the winter. Lastly, we compared masked measurements from theAOS with the ARM Aerial Facility (AAF) during flights over C1 in the summerto understand submicron aerosol vertical mixing over C1. The highcorrelation (R2=0.71 with a slope of 1.04±0.01) observedbetween C1 and the AAF Ntot collected within an area of 10 kmsurrounding ENA and at altitudes &lt; 500 m indicated that thesubmicron aerosol at ENA was well mixed within the first 500 m of themarine boundary layer during the month of July during ACE-ENA. Our novelmethod for determining a regional aerosol baseline at ENA can be applied toother time periods and at other locations with validation by a secondarysite or additional collocated measurements.

atmospheric chemistry and physics

Identifying a regional aerosol baseline in the eastern North Atlantic using collocated measurements and a mathematical algorithm to mask high-submicron-number-concentration aerosol events