Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Summer 2017
Eastern North Atlantic (ENA) Aerosol Mask (ENA-AM) is a mask developed to isolate high concentration aerosol events and identify the regional baseline in one minute time resolution CPC measurements collected at ENA central site during summer 2017(July 22 to August 20). ENA-AM is based on the statist...
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ftosti:oai:osti.gov:1579567 2023-07-30T04:05:13+02:00 Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Summer 2017 Gallo, Francesca Aiken, Allison 2020-02-04 application/pdf http://www.osti.gov/servlets/purl/1579567 https://www.osti.gov/biblio/1579567 https://doi.org/10.5439/1579567 unknown http://www.osti.gov/servlets/purl/1579567 https://www.osti.gov/biblio/1579567 https://doi.org/10.5439/1579567 doi:10.5439/1579567 54 Environmental Sciences 2020 ftosti https://doi.org/10.5439/1579567 2023-07-11T09:38:31Z Eastern North Atlantic (ENA) Aerosol Mask (ENA-AM) is a mask developed to isolate high concentration aerosol events and identify the regional baseline in one minute time resolution CPC measurements collected at ENA central site during summer 2017(July 22 to August 20). ENA-AM is based on the statistically different behavior of adjacent data points during background and pollution peaks measurements. Measurements that differ by more than α times the standard deviation (σm) of the data below the median plus the two points after are masked by ENA-AM. Other/Unknown Material North Atlantic SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
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Open Polar |
collection |
SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
op_collection_id |
ftosti |
language |
unknown |
topic |
54 Environmental Sciences |
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54 Environmental Sciences Gallo, Francesca Aiken, Allison Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Summer 2017 |
topic_facet |
54 Environmental Sciences |
description |
Eastern North Atlantic (ENA) Aerosol Mask (ENA-AM) is a mask developed to isolate high concentration aerosol events and identify the regional baseline in one minute time resolution CPC measurements collected at ENA central site during summer 2017(July 22 to August 20). ENA-AM is based on the statistically different behavior of adjacent data points during background and pollution peaks measurements. Measurements that differ by more than α times the standard deviation (σm) of the data below the median plus the two points after are masked by ENA-AM. |
author |
Gallo, Francesca Aiken, Allison |
author_facet |
Gallo, Francesca Aiken, Allison |
author_sort |
Gallo, Francesca |
title |
Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Summer 2017 |
title_short |
Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Summer 2017 |
title_full |
Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Summer 2017 |
title_fullStr |
Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Summer 2017 |
title_full_unstemmed |
Eastern North Atlantic Aerosol Mask (ENA-AM) with the Condensation Particle Counter (CPC) at Central Facility (C1) during Summer 2017 |
title_sort |
eastern north atlantic aerosol mask (ena-am) with the condensation particle counter (cpc) at central facility (c1) during summer 2017 |
publishDate |
2020 |
url |
http://www.osti.gov/servlets/purl/1579567 https://www.osti.gov/biblio/1579567 https://doi.org/10.5439/1579567 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
http://www.osti.gov/servlets/purl/1579567 https://www.osti.gov/biblio/1579567 https://doi.org/10.5439/1579567 doi:10.5439/1579567 |
op_doi |
https://doi.org/10.5439/1579567 |
_version_ |
1772816989475045376 |