Characterization of distinct Arctic aerosol accumulation modes and their sources

10 pages, 4 figures, 1 table, supplementary data https://doi.org/10.1016/j.atmosenv.2018.03.060 In this work we use cluster analysis of long term particle size distribution data to expand an array of different shorter term atmospheric measurements, thereby gaining insights into longer term patterns...

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Bibliographic Details
Published in:Atmospheric Environment
Main Authors: Lange, R., Dall'Osto, Manuel, Skov, Henrik, Nøjgaard, Jacob Klenø, Nielsen, I.E., Beddows, D.C.S., Simó, Rafel, Harrison, Roy M., Massling, Andreas
Other Authors: Ministerio de Economía y Competitividad (España), European Commission, Natural Environment Research Council (UK), Danish Environmental Protection Agency, Nordic Centre of Excellence (Norway), Villum Fonden
Format: Article in Journal/Newspaper
Language:unknown
Published: Elsevier 2018
Subjects:
CCN
Online Access:http://hdl.handle.net/10261/167331
https://doi.org/10.1016/j.atmosenv.2018.03.060
https://doi.org/10.13039/501100000270
https://doi.org/10.13039/501100000780
https://doi.org/10.13039/501100003329
https://doi.org/10.13039/100008398
Description
Summary:10 pages, 4 figures, 1 table, supplementary data https://doi.org/10.1016/j.atmosenv.2018.03.060 In this work we use cluster analysis of long term particle size distribution data to expand an array of different shorter term atmospheric measurements, thereby gaining insights into longer term patterns and properties of Arctic aerosol. Measurements of aerosol number size distributions (9–915 nm) were conducted at Villum Research Station (VRS), Station Nord in North Greenland during a 5 year record (2012–2016). Alongside this, measurements of aerosol composition, meteorological parameters, gaseous compounds and cloud condensation nuclei (CCN) activity were performed during different shorter occasions. K-means clustering analysis of particle number size distributions on daily basis identified several clusters. Clusters of accumulation mode aerosols (main size modes > 100 nm) accounted for 56% of the total aerosol during the sampling period (89–91% during February–April, 1–3% during June–August). By association to chemical composition, cloud condensation nuclei properties, and meteorological variables, three typical accumulation mode aerosol clusters were identified: Haze (32% of the time), Bimodal (14%) and Aged (6%). In brief: (1) Haze accumulation mode aerosol shows a single mode at 150 nm, peaking in February–April, with highest loadings of sulfate and black carbon concentrations. (2) Accumulation mode Bimodal aerosol shows two modes, at 38 nm and 150 nm, peaking in June–August, with the highest ratio of organics to sulfate concentrations. (3) Aged accumulation mode aerosol shows a single mode at 213 nm, peaking in September–October and is associated with cloudy and humid weather conditions during autumn. The three aerosol clusters were considered alongside CCN concentrations. We suggest that organic compounds, that are likely marine biogenic in nature, greatly influence the Bimodal cluster and contribute significantly to its CCN activity. This stresses the importance of better characterizing the marine ...