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CLOUDMAP focuses on understanding aerosol particle formation by creating a mass spectral library of atmospheric compounds. Using computational methods and machine learning, it aims to enhance compound identification from aerosol samples, contributing to climate change mitigation and improved air quality.
Global warming and air pollution are urgent challenges facing humanity.
Atmospheric aerosol particles contribute to both by affecting air quality, cloud formation, and the absorption and reflection of sunlight.
Increasingly, the atmosphere is shaped by organic rather than inorganic chemistry.
While initiatives like the European Green Deal have reduced inorganic emissions, volatile organic compounds (VOCs) from biogenic and anthropogenic sources are on the rise.
These VOCs react to form oxidized…
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