RESUMEN
Atmospheric aerosols are a significant public health hazard and have substantial impacts on the climate. Secondary organic aerosols (SOAs) have been shown to phase separate into a highly viscous organic outer layer surrounding an aqueous core. This phase separation can decrease the partitioning of semi-volatile and low-volatile species to the organic phase and alter the extent of acid-catalyzed reactions in the aqueous core. A new algorithm that can determine SOA phase separation based on their glass transition temperature (T g), oxygen to carbon (O : C) ratio and organic mass to sulfate ratio, and meteorological conditions was implemented into the Community Multiscale Air Quality Modeling (CMAQ) system version 5.2.1 and was used to simulate the conditions in the continental United States for the summer of 2013. SOA formed at the ground/surface level was predicted to be phase separated with core-shell morphology, i.e., aqueous inorganic core surrounded by organic coating 65.4 % of the time during the 2013 Southern Oxidant and Aerosol Study (SOAS) on average in the isoprene-rich southeastern United States. Our estimate is in proximity to the previously reported ~ 70 % in literature. The phase states of organic coatings switched between semi-solid and liquid states, depending on the environmental conditions. The semi-solid shell occurring with lower aerosol liquid water content (western United States and at higher altitudes) has a viscosity that was predicted to be 102-1012 Pa s, which resulted in organic mass being decreased due to diffusion limitation. Organic aerosol was primarily liquid where aerosol liquid water was dominant (eastern United States and at the surface), with a viscosity < 102 Pa s. Phase separation while in a liquid phase state, i.e., liquid-liquid phase separation (LLPS), also reduces reactive uptake rates relative to homogeneous internally mixed liquid morphology but was lower than aerosols with a thick viscous organic shell. The sensitivity cases performed with different phase-separation parameterization and dissolution rate of isoprene epoxydiol (IEPOX) into the particle phase in CMAQ can have varying impact on fine particulate matter (PM2.5) organic mass, in terms of bias and error compared to field data collected during the 2013 SOAS. This highlights the need to better constrain the parameters that govern phase state and morphology of SOA, as well as expand mechanistic representation of multiphase chemistry for non-IEPOX SOA formation in models aided by novel experimental insights.
RESUMEN
Fine particulate matter (PM2.5) is known to have an adverse impact on public health and is an important climate forcer. Secondary organic aerosol (SOA) contributes up to 80% of PM2.5 worldwide and multiphase reactions are an important pathway to form SOA. Aerosol-phase state is thought to influence the reactive uptake of gas-phase precursors to aerosol particles by altering diffusion rates within particles. Current air quality models do not include the impact of diffusion-limiting organic coatings on SOA formation. This work examines how α-pinene-derived organic coatings change the predicted formation of SOA from the acid-catalyzed multiphase reactions of isoprene epoxydiols (IEPOX). A box model, with inputs provided from field measurements taken at the Look Rock (LRK) site in Great Smokey Mountains National Park during the 2013 Southern Oxidant and Aerosol Study (SOAS), was modified to incorporate the latest laboratory-based kinetic data accounting for organic coating influences. Including an organic coating influence reduced the modeled reactive uptake when relative humidity was in the 55-80% range, with predicted IEPOX-derived SOA being reduced by up to 33%. Only sensitivity cases with a large increase in Henry's Law values of an order of magnitude or more or in particle reaction rates resulted in the large statistically significant differences form base model performance. These results suggest an organic coating layer could have an impact on IEPOX-derived SOA formation and warrant consideration in regional and global scale models.