Ambient Aerosol Is Physically Larger on Cloudy Days in Bondville, Illinois

• Published in: ACS Earth and Space Chemistry
• Main Authors: Flesch, Madison M., Christiansen, Amy E., Burns, Alyssa M., Ghate, Virendra P., Carlton, Annmarie G.
• Format: Text
• Language: English
• Published: American Chemical Society 2022
• Subjects: Aerosol Robotic Network
• Online Access: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9761781/; https://doi.org/10.1021/acsearthspacechem.2c00207

[Image: see text] Particle chemical composition affects aerosol optical and physical properties in ways important for the fate, transport, and impact of atmospheric particulate matter. For example, hygroscopic constituents take up water to increase the physical size of a particle, which can alter the extinction properties and atmospheric lifetime. At the collocated AERosol RObotic NETwork (AERONET) and Interagency Monitoring of PROtected Visual Environments (IMPROVE) network monitoring stations in rural Bondville, Illinois, we employ a novel cloudiness determination method to compare measured aerosol physicochemical properties on predominantly cloudy and clear sky days from 2010 to 2019. On cloudy days, aerosol optical depth (AOD) is significantly higher than on clear sky days in all seasons. Measured Ångström exponents are significantly smaller on cloudy days, indicating physically larger average particle size for the sampled populations in all seasons except winter. Mass concentrations of fine particulate matter that include estimates of aerosol liquid water (ALW) are higher on cloudy days in all seasons but winter. More ALW on cloudy days is consistent with larger particle sizes inferred from Ångström exponent measurements. Aerosol chemical composition that affects hygroscopicity plays a determining impact on cloudy versus clear sky differences in AOD, Ångström exponents, and ALW. This work highlights the need for simultaneous collocated, high-time-resolution measurements of both aerosol chemical and physical properties, in particular at cloudy times when quantitative understanding of tropospheric composition is most uncertain.