Understanding Sources and Drivers of Size-Resolved Aerosol in the High Arctic Islands of Svalbard Using a Receptor Model Coupled with Machine Learning

Bibliographic Details
Published in:Environmental Science & Technology
Main Authors: Song, Congbo, Becagli, Silvia, Beddows, David C. S., Brean, James, Browse, Jo, Dai, Qili, Dall’Osto, Manuel, Ferracci, Valerio, Harrison, Roy M., Harris, Neil, Li, Weijun, Jones, Anna E., Kirchgäßner, Amélie, Kramawijaya, Agung Ghani, Kurganskiy, Alexander, Lupi, Angelo, Mazzola, Mauro, Severi, Mirko, Traversi, Rita, Shi, Zongbo
Other Authors: Natural Environment Research Council
Format: Article in Journal/Newspaper
Language:English
Published: American Chemical Society (ACS) 2022
Subjects:
Svalbard
Online Access:http://dx.doi.org/10.1021/acs.est.1c07796
https://pubs.acs.org/doi/pdf/10.1021/acs.est.1c07796
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spelling cracsoc:10.1021/acs.est.1c07796 2024-09-15T18:38:14+00:00 Understanding Sources and Drivers of Size-Resolved Aerosol in the High Arctic Islands of Svalbard Using a Receptor Model Coupled with Machine Learning Song, Congbo Becagli, Silvia Beddows, David C. S. Brean, James Browse, Jo Dai, Qili Dall’Osto, Manuel Ferracci, Valerio Harrison, Roy M. Harris, Neil Li, Weijun Jones, Anna E. Kirchgäßner, Amélie Kramawijaya, Agung Ghani Kurganskiy, Alexander Lupi, Angelo Mazzola, Mauro Severi, Mirko Traversi, Rita Shi, Zongbo Natural Environment Research Council 2022 http://dx.doi.org/10.1021/acs.est.1c07796 https://pubs.acs.org/doi/pdf/10.1021/acs.est.1c07796 en eng American Chemical Society (ACS) https://creativecommons.org/licenses/by/4.0/ Environmental Science & Technology volume 56, issue 16, page 11189-11198 ISSN 0013-936X 1520-5851 journal-article 2022 cracsoc https://doi.org/10.1021/acs.est.1c07796 2024-09-05T04:08:30Z Article in Journal/Newspaper Svalbard ACS Publications Environmental Science & Technology 56 16 11189 11198
institution Open Polar
collection ACS Publications
op_collection_id cracsoc
language English
author2 Natural Environment Research Council
format Article in Journal/Newspaper
author Song, Congbo
Becagli, Silvia
Beddows, David C. S.
Brean, James
Browse, Jo
Dai, Qili
Dall’Osto, Manuel
Ferracci, Valerio
Harrison, Roy M.
Harris, Neil
Li, Weijun
Jones, Anna E.
Kirchgäßner, Amélie
Kramawijaya, Agung Ghani
Kurganskiy, Alexander
Lupi, Angelo
Mazzola, Mauro
Severi, Mirko
Traversi, Rita
Shi, Zongbo
spellingShingle Song, Congbo
Becagli, Silvia
Beddows, David C. S.
Brean, James
Browse, Jo
Dai, Qili
Dall’Osto, Manuel
Ferracci, Valerio
Harrison, Roy M.
Harris, Neil
Li, Weijun
Jones, Anna E.
Kirchgäßner, Amélie
Kramawijaya, Agung Ghani
Kurganskiy, Alexander
Lupi, Angelo
Mazzola, Mauro
Severi, Mirko
Traversi, Rita
Shi, Zongbo
Understanding Sources and Drivers of Size-Resolved Aerosol in the High Arctic Islands of Svalbard Using a Receptor Model Coupled with Machine Learning
author_facet Song, Congbo
Becagli, Silvia
Beddows, David C. S.
Brean, James
Browse, Jo
Dai, Qili
Dall’Osto, Manuel
Ferracci, Valerio
Harrison, Roy M.
Harris, Neil
Li, Weijun
Jones, Anna E.
Kirchgäßner, Amélie
Kramawijaya, Agung Ghani
Kurganskiy, Alexander
Lupi, Angelo
Mazzola, Mauro
Severi, Mirko
Traversi, Rita
Shi, Zongbo
author_sort Song, Congbo
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_short Understanding Sources and Drivers of Size-Resolved Aerosol in the High Arctic Islands of Svalbard Using a Receptor Model Coupled with Machine Learning
title_full Understanding Sources and Drivers of Size-Resolved Aerosol in the High Arctic Islands of Svalbard Using a Receptor Model Coupled with Machine Learning
title_fullStr Understanding Sources and Drivers of Size-Resolved Aerosol in the High Arctic Islands of Svalbard Using a Receptor Model Coupled with Machine Learning
title_full_unstemmed Understanding Sources and Drivers of Size-Resolved Aerosol in the High Arctic Islands of Svalbard Using a Receptor Model Coupled with Machine Learning
title_sort understanding sources and drivers of size-resolved aerosol in the high arctic islands of svalbard using a receptor model coupled with machine learning
publisher American Chemical Society (ACS)
publishDate 2022
url http://dx.doi.org/10.1021/acs.est.1c07796
https://pubs.acs.org/doi/pdf/10.1021/acs.est.1c07796
genre Svalbard
genre_facet Svalbard
op_source Environmental Science & Technology
volume 56, issue 16, page 11189-11198
ISSN 0013-936X 1520-5851
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.1021/acs.est.1c07796
container_title Environmental Science & Technology
container_volume 56
container_issue 16
container_start_page 11189
op_container_end_page 11198
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