Abstract. High-time-resolution measurements of in situ aerosol and cloud properties
provide the ability to study regional atmospheric processes that occur on
timescales of minutes to hours. However, one limitation to this approach is
that continuous measurements often include periods when the data collected
are not representative of the regional aerosol. Even at remote locations,
submicron aerosols are pervasive in the ambient atmosphere with many
sources. Therefore, periods dominated by local aerosol should be identified
before conducting subsequent analyses to understand aerosol regional
processes and aerosol–cloud interactions. Here, we present a novel method to
validate the identification of regional baseline aerosol data by applying a
mathematical algorithm to the data collected at the U.S. Department of
Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility in the
eastern 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 to
minutes. A second temporary supplementary facility (S1), located
∼0.75 km from C1, was deployed for ∼1 year
during the Aerosol and Cloud Experiments (ACE-ENA) campaign in 2017. First, we investigate the local aerosol at both locations. We associate
periods of high submicron number concentration (Ntot) in the fine-mode
condensation particle counter (CPC) and size distributions from the
Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) as a function of wind
direction using a meteorology sensor with local sources. Elevated
concentrations of Aitken-mode (< 100 nm diameter) particles were
observed in correspondence with the wind directions associated with airport
operations. At ENA, the Graciosa Airport and its associated activities were
found to be the main sources of high-concentration aerosol events at ENA,
causing peaks in 1 min Ntot that exceeded 8000 and
10 000 cm−3 at C1, in summer and winter, respectively, and 5000 cm−3 at S1 in summer. Periods with high Ntot not associated with
these wind directions were also observed. As a result, the diverse local
sources at ENA yielded a poor relationship between Ntot measurements
collected 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 the
wind direction was associated with the airport operations (west to northwest
and southeast to south at C1 and east to south at S1) were applied. The
meteorological masks removed 38.9 % of the data at C1 and 43.4 % at S1,
and they did not significantly improve the relationship between the two
sites (R2=0.18 with a slope =0.06±0.001). Due to the complexity of high-Ntot events observed at ENA, we develop
and validate a mathematical ENA Aerosol Mask (ENA-AM) to identify high-Ntot events using 1 min resolution data from the AOS CPC at C1 and
S1. After its parameterization and application, ENA-AM generated a high
correlation between Ntot in the summer at C1 and S1 (R2=0.87
with a slope =0.84±0.001). We identified the regional baseline at
ENA to be 428±228 cm−3 in the summer and 346±223 cm−3 in the winter. Lastly, we compared masked measurements from the
AOS with the ARM Aerial Facility (AAF) during flights over C1 in the summer
to understand submicron aerosol vertical mixing over C1. The high
correlation (R2=0.71 with a slope of 1.04±0.01) observed
between C1 and the AAF Ntot collected within an area of 10 km
surrounding ENA and at altitudes < 500 m indicated that the
submicron aerosol at ENA was well mixed within the first 500 m of the
marine boundary layer during the month of July during ACE-ENA. Our novel
method for determining a regional aerosol baseline at ENA can be applied to
other time periods and at other locations with validation by a secondary
site or additional collocated measurements.