Data-driven modeling of environmental factors influencing Arctic methanesulfonic acid aerosol concentrations

Jakob Boyd Pernov, William H. Aeberhard, Michele Volpi, Eliza Harris, Benjamin Hohermuth, Sakiko Ishino, Ragnhild B. Skeie, Stephan Henne, Ulas Im, Patricia K. Quinn, Lucia M. Upchurch, and Julia Schmale

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Cumulative views and downloads (calculated since 14 Nov 2024)

Month	HTML	PDF	XML	Total
Nov 2024	83	30	6	119
Dec 2024	43	11	4	58
Jan 2025	34	18	1	53
Feb 2025	31	10	3	44
Mar 2025	26	13	3	42
Apr 2025	36	7	2	45
May 2025	24	12	0	36
Jun 2025	32	6	6	44

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Latest update: 27 Jun 2025

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Short summary

Particulate methanesulfonic acid (MSA_p) is vital for the Arctic climate system. Numerical models struggle to reproduce the MSA_p seasonal cycle. We evaluate three numerical models and one reanalysis product’s ability to simulate MSA_p. We develop data-driven models for MSA_p at four Arctic stations. The data-driven models outperform the numerical models and reanalysis product and identified precursor source-, chemical-processing-, and removal-related features as being important for modeling MSA_p.