Formation Of Organic Aerosol Through Cloud Chemistry
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Quantifying Secondary Organic Aerosol (SOA) Formed Through Cloud Chemistry and Cloud Droplet Evaporation
Author | : Diana L. Ortiz-Montalvo |
Publisher | : |
Total Pages | : 226 |
Release | : 2013 |
Genre | : Atmospheric aerosols |
ISBN | : |
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Secondary organic aerosol (SOA) is a substantial contributor to atmospheric organic particulate matter; however, its formation via aqueous oxidation reactions is only beginning to be understood. Although the aqueous organic chemistry that drives SOA formation in clouds (SOACld) has now been incorporated into a few photochemical transport models, it is yet unknown to what extent the newly formed organic material remains in the particle-phase after droplet evaporation. This work investigates SOA formation through cloud water chemistry and droplet evaporation. Aqueous hydroxyl radical oxidation and droplet evaporation experiments were conducted using precursors commonly found in cloud water: glycolaldehyde, methylglyoxal, and glyoxal. A new method was used to measure the volatility of the product mixture. The effective vapor pressure, enthalpy of vaporization, and mass yields of SOACld were determined. Aqueous oxidation produced carboxylic acids and oligomers (i.e., small polymers), which are major constituents of atmospheric aerosols. Enhanced yields (e.g., ~50-80% yields from glycolaldehyde) provide evidence for additional chemistry during droplet evaporation. The overall vapor pressure and enthalpy of vaporization of SOACld were ~1E-07 atm and ~70 kJ/mol, respectively, similar to the mix of organic acids identified. Lastly, a substantial decrease in volatility (~ 1E-08 - 1E-16 atm) was observed when glyoxal SOACld products were exposed to sufficient ammonia to form organic salts. These results provide an important insight on the effects that cloud droplet evaporation and neutralization have on SOA formation through cloud processing. This work furthers our understanding of SOACld formation, and provides measurements that are needed for accurate prediction of SOA in global and regional air quality models.