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Understanding sources and drivers of size-resolved aerosol ..:

Song, Congbo ; Becagli, Silvia ; Beddows, David C. S...
Song C, Becagli S, Beddows DCS, et al., (2022) Understanding sources and drivers of size-resolved aerosol in the High Arctic islands of Svalbard using a receptor model coupled with machine learning, Environmental Science and Technology, Volume 56, Issue 16, 16 August 2022, pp. 11189–11198. , 2022

Link: https://doi.org/10.1021/acs.est.1c07796

RT Journal
T1 <Title>Understanding sources and drivers of size-resolved aerosol in the High Arctic islands of Svalbard using a receptor model coupled with machine learning</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftcranfield:oai:dspace.lib.cranfield.ac.uk:1826_18310&Exemplar=1&LAN=DE
				
A1 Song, Congbo
A1 Becagli, Silvia
A1 Beddows, David C. S
A1 Brean, James
A1 Browse, Jo
A1 Dai, Qili
A1 Dall'Osto, Manuel
A1 Ferracci, Valerio
A1 Harrison, Roy M
A1 Harris, Neil R. P
A1 Li, Weijun
A1 Jones, Anna E
A1 Kirchgäßner, Amelie
A1 Kramawijaya, Agung Ghani
A1 Kurganskiy, Alexander
A1 Lupi, Angelo
A1 Mazzola, Mauro
A1 Severi, Mirko
A1 Traversi, Rita
A1 Shi, Zongbo
PB American Chemical Society
YR 2022
K1 Arctic
K1 source apportionment
K1 positive matrix factorization
K1 machine learning
K1 particle number concentration
K1 meteorology
JF Song C, Becagli S, Beddows DCS, et al., (2022) Understanding sources and drivers of size-resolved aerosol in the High Arctic islands of Svalbard using a receptor model coupled with machine learning, Environmental Science and Technology, Volume 56, Issue 16, 16 August 2022, pp. 11189–11198
LK http://dx.doi.org/https://doi.org/10.1021/acs.est.1c07796
DO https://doi.org/10.1021/acs.est.1c07796
SF ELIB - SuUB Bremen

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