Challenges in determining atmospheric organic aerosol volatility distributions using thermal evaporation techniques

Abstract

Volatility is one of the most important physical properties of organic aerosol (OA), as it determines the partitioning of its components between the vapor and particulate phases. Despite their atmospheric importance, multicomponent OA volatility estimates remain quite uncertain. This study combined thermodenuder (TD) and isothermal dilution measurements to characterize secondary OA (SOA) generated from the ozonolysis of a-pinene and cyclohexene. The SOA from both precursors evaporated similarly in the TD, but behaved quite differently when isothermally diluted by similar amounts. The a-pinene ozonolysis SOA evaporated by only 20% after 2 h of dilution by a factor of around 20, while 65% of the cyclohexene ozonolysis SOA evaporated at the same conditions. The volatility distributions were first estimated by fitting only the evaporation in the TD. This approach resulted in similar volatility distributions for the two systems. Then, the model was used to fit both the evaporation in the TD and the dilution chamber. This technique estimated drastically different volatility distributions with the a-pinene ozonolysis SOA consisting of mostly low-volatility compounds and the cyclohexene ozonolysis SOA consisting of mostly semi-volatile compounds. In the next stage of analysis, the model was updated to account for vapor-phase wall-losses occurring in the dilution chamber. This approach resulted in slightly less volatile SOA and provided some information about the losses of vapors to the walls, but the results were fairly uncertain. These results show the necessity of combining thermal measurements with other techniques to accurately estimate OA volatility.

α-Pinene, Limonene, and Cyclohexene Secondary Organic Aerosol Hygroscopicity and Oxidation Level as a Function of Volatility

“…The data analysis in this study utilizes the techniques described in Cain and Pandis (2017) and Cain et al (2020). Briefly, hygroscopicity was quantified with the hygroscopicity parameter, κ, and determined from activation diameters and water supersaturations from the CCNC (Petters and Kreidenweis, 2007).…”

“…Volatility distributions were estimated using a thermogram and areogram, which describe particle mass fraction remaining (MFR) as a function of TD temperature and dilution time respectively, and a mass transfer model (Riipenen et al, 2010;Karnezi et al, 2014). Full details on the volatility fitting process can be found in Cain et al (2020). Thermograms were corrected for size and temperature dependent losses, as specified in Cain and Pandis (2017).…”

“…The experimental setup combines the parallel TD and isothermal dilution measurements from Cain et al (2020) with the hygroscopicity and oxidation level measurements from Cain and Pandis (2017). A schematic of the experimental setup can be seen in Fig.…”

“…In this work, we extend the experimental technique of Cain and Pandis (2017) by adding isothermal dilution to the set of measurements. Cain et al (2020) showed that this addition can better constrain the SOA volatility distribution. The resulting method is then applied to SOA from the ozonolysis of α-pinene, limonene, and cyclohexene to examine the relationship between hygroscopicity, oxidation level, and volatility in these systems.…”

Response to Referee #1

“…The comment of Karnezi et al (2014) referred to a detailed volatility distribution in the Volatility-Basis-Set framework. We have recently shown (Louvaris et al, 2017;Cain et al, 2020) that the uncertainty of volatility classes (e.g. ELVOCs, LVOCs, SVOCs) is significantly less than the uncertainty of individual volatility bins.…”