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SUMMARY:Improving Particle Dry Deposition Models with Representative Measur
 ements
LOCATION:Chemistry A101
TZID:America/Denver
DTSTART:20251029T160000
UID:2026-05-18-22-38-10@natsci.colostate.edu
DTSTAMP:20260518T223810
Description:About the seminar:\n\nAerosol effects in the atmosphere dominat
 e uncertainty in climate predictions and are controlled by particle concen
 trations. These concentrations\, in turn\, depend on removal processes\, w
 ith dry deposition contributing the largest uncertainty. The complexity o
 f dry deposition—driven by both particle characteristics and meteorologi
 cal conditions—makes it difficult to model accurately. This seminar eval
 uates one foundational dry deposition model and two subsequent updates de
 veloped for needleleaf forest conditions. While these models improve physi
 cal representation for that surface type\, limited observations across oth
 er environments (e.g.\, water\, ice\, and grass) hinder broader evaluation
 . This highlights the need for meteorologically representative measurement
 s to better constrain model performance across different surfaces. 4:00 p
 m
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