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Abstract
Atmospheric aerosols are important drivers of Arctic climate change through aerosol-cloud-climate interactions. However, large uncertainties remain on the sources and processes controlling particle numbers in both fine and coarse modes. Here, we applied a receptor model and an explainable machine learning technique to understand the sources and drivers of particle numbers from 10 nm to 20 μm in Svalbard. Nucleation, biogenic, secondary, anthropogenic, mineral dust, sea salt and blowing snow aerosols and their major environmental drivers were identified. Our results show that the monthly variations in particles are highly size/source dependent and regulated by meteorology. Secondary and nucleation aerosols are the largest contributors to potential cloud condensation nuclei (CCN, particle number with a diameter larger than 40 nm as a proxy) in the Arctic. Nonlinear responses to temperature were found for biogenic, local dust particles and potential CCN, highlighting the importance of melting sea ice and snow. These results indicate that the aerosol factors will respond to rapid Arctic warming differently and in a nonlinear fashion.
Original language | English |
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Pages (from-to) | 11189-11198 |
Number of pages | 10 |
Journal | Environmental Science and Technology |
Volume | 56 |
Issue number | 16 |
Early online date | 25 Jul 2022 |
DOIs | |
Publication status | Published - 16 Aug 2022 |
Bibliographical note
Funding Information:This research was supported by the Natural Environment Research Council (grant no. NE/S00579X/1) and endorsed by the Surface Ocean-Lower Atmosphere Study (SOLAS). The authors acknowledge the staff of the Arctic Station Dirigibile Italia of the National Research Council of Italy for their support in measurements at the GVB station. The authors acknowledge the NOAA Air Resources Laboratory (ARL) for providing the HYSPLIT model used to analyze the back trajectories.
Publisher Copyright:
© 2022 The Authors. Published by American Chemical Society.
Keywords
- Arctic
- machine learning
- meteorology
- particle number concentration
- positive matrix factorization
- source apportionment
ASJC Scopus subject areas
- General Chemistry
- Environmental Chemistry
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SEANA - Shipping Emissions in the Arctic and North Atlantic Atmosphere
Harrison, R., Shi, Z. & Beddows, D.
Natural Environment Research Council
3/01/19 → 30/06/26
Project: Research