Group Contribution Approach To Predict the Refractive Index of Pure Organic Components in Ambient Organic Aerosol

Abstract

We introduce and assess a group contribution scheme by which the refractive index (RI) (λ = 589 nm) of nonabsorbing components common to secondary organic aerosols can be predicted from the molecular formula and chemical functionality. The group contribution method is based on representative values of ratios of the molecular polarizability and molar volume of different functional groups derived from data for a training set of 234 compounds. The training set consists of 106 nonaromatic compounds common to atmospheric aerosols, 64 aromatic compounds, and 64 compounds containing halogens; a separate group contribution model is provided for each of these three classes of compound. The resulting predictive model reproduces the RIs of compounds in the training set with mean errors of ±0.58, ±0.36, and ±0.30% for the nonaromatic, aromatic, and halogen-containing compounds, respectively. We then evaluate predictions from the group contribution model for compounds with no previously reported RI, comparing values with predictions from previous treatments and with measurements from single aerosol particle experiments. We illustrate how such comparisons can be used to further refine the predictive model. We suggest that the accuracy of this model is already sufficient to better constrain the optical properties of organic aerosol of known composition.

Complexity of Measuring and Representing the Hygroscopicity of Mixed Component Aerosol

“…The values of RI and density in the limit of pure solute (no water) are estimated using both methods 1 and 3, outlined above, with values for RI (1.464 and 1.463, respectively) and density (1.355 and 1.351 g·cm –3 , respectively) in good agreement. For fits to aqueous solutions, these values provide estimates for the subcooled melts, rather than the crystalline phase, and can be considerably less than the values for the corresponding pure solids. ,, A similar comparison is shown for mixture 7 in Figure S1, again with excellent agreement between the two methods across the entire MFS range.…”

Characterization of the Real Part of Dry Aerosol Refractive Index Over North America From the Surface to 12 km

“…Unlike the cumulative data set, the results indicate that a linear model can yield fairly good performance in predicting n for simple case studies, with adjusted R 2 values ranging between 0.45 and 0.96. Other work has shown that at least for the organic fraction of aerosol, models relying on quantitative structure‐property relationships (Redmond & Thompson, ) and group contribution approaches are promising (Cai et al, ). However, these methods require information about the aerosol that is difficult to obtain for the complex organic fraction of ambient aerosol with field measurements, such as molecular formula, chemical functionality, and density.…”

Sources and characteristics of size-resolved particulate organic acids and methanesulfonate in a coastal megacity: Manila, Philippines

“…MSA is produced predominantly from the oxidation of dimethylsulfide (DMS) emitted from oceans (Bates et al, 2004;Davis et al, 1998;Kerminen et al, 2017), but it also can be linked to biomass burning, urban, and agricultural emissions (Sorooshian et al, 2015). Sources of organic acids include primary emissions from biomass burning, biogenic activity, and the combustion of fossil fuels (Kawamura and Kaplan, 1987) and secondary formation via gas-to-particle conversion processes stemming from both biogenic (Carlton et al, 2006) and anthropogenic emissions (Sorooshian et al, 2007b). Secondary processing can include both aqueous-phase chemistry in clouds (Blando and Turpin, 2000;Ervens, 2018;Ervens et al, 2014;Hoffmann et al, 2019;Rose et al, 2018;Sareen et al, 2016;Warneck, 2005) and photo-oxidation of volatile organic compounds (VOCs) in cloud-free air (Andreae and Crutzen, 1997;Gelencsér and Varga, 2005).…”