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

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.