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

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 (ACEENA) 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 Published by Copernicus Publications on behalf of the European Geosciences Union. 7554 F. Gallo et al.: Identifying a regional aerosol baseline in the eastern North Atlantic 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 AAFNtot 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.

[1]  D. Bromwich,et al.  AWARE: The Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment , 2020, Bulletin of the American Meteorological Society.

[2]  M. Dubey,et al.  Atmospheric Radiation Measurement (ARM) Aerosol Observing Systems (AOS) for Surface-Based In Situ Atmospheric Aerosol and Trace Gas Measurements , 2019, Journal of Atmospheric and Oceanic Technology.

[3]  J. Kyrouac,et al.  Aerosol Observing System Surface Meteorology (AOSMET) Instrument Handbook , 2019 .

[4]  Li Chen,et al.  Estimation of background concentration of PM in Beijing using a statistical integrated approach , 2019, Atmospheric Pollution Research.

[5]  Sally McFarlane,et al.  Atmospheric Radiation Measurement (ARM) User Facility: ARM Mobile Facility Workshop Report , 2019 .

[6]  S. Martin,et al.  Urban pollution greatly enhances formation of natural aerosols over the Amazon rainforest , 2019, Nature Communications.

[7]  S. Martin,et al.  Observations of Manaus urban plume evolution and interaction with biogenic emissions in GoAmazon 2014/5 , 2018, Atmospheric Environment.

[8]  E. Luke,et al.  Marine boundary layer aerosol in the eastern North Atlantic: seasonal variations and key controlling processes , 2018, Atmospheric Chemistry and Physics.

[9]  C. Kuang,et al.  High summertime aerosol organic functional group concentrations from marine and seabird sources at Ross Island, Antarctica, during AWARE , 2018, Atmospheric Chemistry and Physics.

[10]  Graham R. Simpkins Aerosol–cloud interactions , 2018, Nature Climate Change.

[11]  B. Anderson,et al.  Take-off engine particle emission indices for in-service aircraft at Los Angeles International Airport , 2017, Scientific Data.

[12]  R. Wood,et al.  A Case Study in Low Aerosol Number Concentrations Over the Eastern North Atlantic: Implications for Pristine Conditions in the Remote Marine Boundary Layer , 2017 .

[13]  Lynn Hazan,et al.  Identification of spikes associated with local sources in continuous time series of atmospheric CO, CO 2 and CH 4 , 2017 .

[14]  Eduardo Brito de Azevedo,et al.  Short-term variability of gamma radiation at the ARM Eastern North Atlantic facility (Azores). , 2017, Journal of environmental radioactivity.

[15]  R. Wood,et al.  Low‐CCN concentration air masses over the eastern North Atlantic: Seasonality, meteorology, and drivers , 2017 .

[16]  M. Campagna,et al.  Environmental Exposure to Ultrafine Particles inside and nearby a Military Airport , 2016 .

[17]  G. Feingold,et al.  ARM’s Aerosol–Cloud–Precipitation Research (Aerosol Indirect Effects) , 2016 .

[18]  R. Ferrare,et al.  Aerosol Physical and Optical Properties and Processes in the ARM Program , 2016 .

[19]  Jian Wang,et al.  Influences of upwind emission sources and atmospheric processing on aerosol chemistry and properties at a rural location in the Northeastern U.S. , 2016 .

[20]  C. Kuang Condensation Particle Counter Instrument Handbook , 2016 .

[21]  G. Tselioudis,et al.  Cloud Regime Variability over the Azores and Its Application to Climate Model Evaluation , 2015 .

[22]  D. Rosenfeld,et al.  Extensive closed cell marine stratocumulus downwind of Europe—A large aerosol cloud mediated radiative effect or forcing? , 2015 .

[23]  K. Prather,et al.  Chemistry and related properties of freshly emitted sea spray aerosol. , 2015, Chemical reviews.

[24]  Patrick Minnis,et al.  Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment , 2015 .

[25]  P. Rasch,et al.  A physically based framework for modeling the organic fractionation of sea spray aerosol from bubble film Langmuir equilibria , 2014 .

[26]  L. Lee,et al.  Occurrence of pristine aerosol environments on a polluted planet , 2014, Proceedings of the National Academy of Sciences.

[27]  Patrick Minnis,et al.  A 19-Month Record of Marine Aerosol-Cloud-Radiation Properties Derived from DOE ARM Mobile Facility Deployment at the Azores. Part I: Cloud Fraction and Single-Layered MBL Cloud Properties , 2014 .

[28]  Timothy Logan,et al.  Aerosol properties and their influences on marine boundary layer cloud condensation nuclei at the ARM mobile facility over the Azores , 2014 .

[29]  S. Sherwood,et al.  Climate Effects of Aerosol-Cloud Interactions , 2014, Science.

[30]  Gayle S. W. Hagler,et al.  Mobile air monitoring data-processing strategies and effects on spatial air pollution trends , 2013 .

[31]  G. Mann,et al.  Large contribution of natural aerosols to uncertainty in indirect forcing , 2013, Nature.

[32]  Jimmy W. Voyles,et al.  The Arm Climate Research Facility: A Review of Structure and Capabilities , 2013 .

[33]  E. Luke,et al.  Marine Boundary Layer Cloud Observations in the Azores , 2012 .

[34]  J. Schneider,et al.  Design of a mobile aerosol research laboratory and data processing tools for effective stationary and mobile field measurements , 2012 .

[35]  Vlad Isakov,et al.  Field investigation of roadside vegetative and structural barrier impact on near-road ultrafine particle concentrations under a variety of wind conditions. , 2012, The Science of the total environment.

[36]  S. Reimann,et al.  The determination of a "regional" atmospheric background mixing ratio for anthropogenic greenhouse gases: A comparison of two independent methods , 2011 .

[37]  K. Bowman,et al.  The influence of boreal biomass burning emissions on the distribution of tropospheric ozone over North America and the North Atlantic during 2010 , 2011 .

[38]  Stefan Reimann,et al.  Robust extraction of baseline signal of atmospheric trace species using local regression , 2010 .

[39]  D. R. Worsnop,et al.  Evolution of Organic Aerosols in the Atmosphere , 2009, Science.

[40]  Yong Cai,et al.  Performance characteristics of the ultra high sensitivity aerosol spectrometer for particles between 55 and 800 nm: Laboratory and field studies , 2008 .

[41]  Philip B. Russell,et al.  International Consortium for Atmospheric Research on Transport and Transformation (ICARTT): North America to Europe—Overview of the 2004 summer field study , 2006 .

[42]  Richard C. Miake-Lye,et al.  Particulate Emissions from in-use Commercial Aircraft , 2005 .

[43]  Reto Knutti,et al.  Climate Forcing by Aerosols--a Hazy Picture , 2003, Science.

[44]  M. Maricq,et al.  Signature size distributions for diesel and gasoline engine exhaust particulate matter , 2001 .

[45]  Chang-Yu Wu,et al.  Combustion Aerosols: Factors Governing Their Size and Composition and Implications to Human Health , 2000, Journal of the Air & Waste Management Association.

[46]  Stuart A. Penkett,et al.  Preface [to special section on North Atlantic Regional Experiment (NARE II)] , 1998 .

[47]  B. Hayden,et al.  The North Atlantic subtropical anticyclone , 1997 .

[48]  C. Bretherton,et al.  The Atlantic Stratocumulus Transition Experiment - ASTEX , 1995 .

[49]  M. H. Smith,et al.  Physicochemical properties of aerosols over the northeast Atlantic: Evidence for wind‐speed‐related submicron sea‐salt aerosol production , 1993 .

[50]  P F Velleman,et al.  Robust nonlinear data smoothers: Definitions and recommendations. , 1977, Proceedings of the National Academy of Sciences of the United States of America.

[51]  J. Tukey,et al.  The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data , 1974 .

[52]  Li Chen,et al.  Background concentrations of PMs in Xinjiang, West China: An estimation based on meteorological filter method and Eckhardt algorithm , 2019, Atmospheric Research.

[53]  Lunche Wang,et al.  Long-term observations of aerosol optical properties at Wuhan, an urban site in Central China , 2015 .

[54]  Aonghus McNabola,et al.  Analysis of the relationship between urban background air pollution concentrations and the personal exposure of office workers in Dublin, Ireland, using baseline separation techniques , 2011 .

[55]  Vladimir Nikora,et al.  Despiking Acoustic Doppler Velocimeter Data , 2002 .

[56]  Liu Xinwu This is How the Discussion Started , 1981 .