Improved AIOMFAC model parameterisation of the temperature dependence of activity coefficients for aqueous organic mixtures

Abstract

Abstract. This study presents a new, improved parameterisation of the temperature dependence of activity coefficients in the AIOMFAC (Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients) model applicable for aqueous as well as water-free organic solutions. For electrolyte-free organic and organic-water mixtures the AIOMFAC model uses a group-contribution approach based on UNIFAC (UNIversal quasi-chemical Functional-group Activity Coefficients). This group-contribution approach explicitly accounts for interactions among organic functional groups and between organic functional groups and water. The previous AIOMFAC version uses a simple parameterisation of the temperature dependence of activity coefficients, aimed to be applicable in the temperature range from ∼ 275 to ∼ 400 K. With the goal to improve the description of a wide variety of organic compounds found in atmospheric aerosols, we extend the AIOMFAC parameterisation for the functional groups carboxyl, hydroxyl, ketone, aldehyde, ether, ester, alkyl, aromatic carbon-alcohol, and aromatic hydrocarbon to atmospherically relevant low temperatures. To this end we introduce a new parameterisation for the temperature dependence. The improved temperature dependence parameterisation is derived from classical thermodynamic theory by describing effects from changes in molar enthalpy and heat capacity of a multi-component system. Thermodynamic equilibrium data of aqueous organic and water-free organic mixtures from the literature are carefully assessed and complemented with new measurements to establish a comprehensive database, covering a wide temperature range (∼ 190 to ∼ 440 K) for many of the functional group combinations considered. Different experimental data types and their processing for the estimation of AIOMFAC model parameters are discussed. The new AIOMFAC parameterisation for the temperature dependence of activity coefficients from low to high temperatures shows an overall improvement of 28 % in comparison to the previous model version, when both versions are compared to our database of experimentally determined activity coefficients and related thermodynamic data. When comparing the previous and new AIOM-FAC model parameterisations to the subsets of experimental data with all temperatures below 274 K or all temperatures above 322 K (i.e. outside a 25 K margin of the reference temperature of 298 K), applying the new parameterisation leads to 37 % improvement in each of the two temperature ranges considered. The new parameterisation of AIOMFAC agrees well with a large number of experimental data sets. Larger model-measurement discrepancies were found particularly for some of the systems containing multi-functional organic compounds. The affected systems were typically also poorly represented at room temperature and further improvements will be necessary to achieve better performance of AIOM-FAC in these cases (assuming the experimental data are reliable). The performance of the AIOMFAC parameterisation is typically better for system...

Diffusivity measurements of volatile organics in levitated viscous aerosol particles

“…As activity coefficients of organics are generally only weakly temperature dependent (Ganbavale et al, 2015), we assume γ PEG to be constant over the investigated temperature range of 8-19.5 • C. We determine γ PEG at high RH by freely adjusting its value in the diffusion model to reproduce the experimental radius curve presented in Fig. 4a (red) while D PEG was set to a constant value of 1.0 × 10 −9 cm 2 s −1 .…”

Development of an inorganic and organic aerosol model (CHIMERE 2017<i>β</i> v1.0): seasonal and spatial evaluation over Europe

“…Each surrogate can be hydrophilic (condense only into the aqueous phase of particles), hydrophobic (condense only into the organic phases of particles) or both. Activity coefficients are computed with the UNIFAC (UNIversal Functional group Activity Coefficient; Fredenslund et al, 1975) thermodynamic model for short-range interactions and with the Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients (AIOMFAC) parameterization for medium-and long-range interactions between electrolytes and organic compounds (Zuend et al, 2008(Zuend et al, , 2011Zuend and Seinfeld, 2012;Ganbavale et al, 2015).…”

Treatment of non-ideality in the SPACCIM multiphase model – Part 1: Model development

“…Due to the limitations regarding the lack of experimental data, and the ability to treat the organic-electrolyte mixtures of atmospheric relevance at various complexities, predictions are improved considerably while using extended interaction parameters. In future, the database will be extended with new parameters of recent studies (Zuend et al, 2011;Mohs and Gmehling, 2013;Ganbavale et al, 2015) within this activity coefficient module. First test simulations with the advanced SPACCIM have demonstrated the applicability of SpactMod within the model framework.…”

“…AIOMFAC is based on the LIFAC group-contribution model (Yan et al, 1999) and yet is modified in many respects to better represent relevant species, reference states, and the relative humidity range of the atmosphere. Recently, Zuend et al (2011), Mohs and Gmehling (2013) and Ganbavale et al (2015) proposed revised and extended parameterizations for mixtures containing various organic functional groups, water and inorganic ions.…”

“…While the interactions between inorganic compounds are relatively well known, interactions between organic components as well as organic-electrolyte mixtures comprised in complex multiphase systems have remained elusive for some time, due to the large number of organic species with highly variable properties available in the gas phase and in ambient particles. Starting with the more conceptual paper of Clegg et al (2001), several approaches for the treatment of organic-inorganic mixtures in ambient particles were developed and incorporated into thermodynamic models (e.g., Ming and Russell, 2002;Topping et al, 2005b;Erdakos et al, 2006;Metzger et al, 2006;Clegg et al, 2008;Zaveri et al, 2008;Zuend et al, 2008Zuend et al, , 2011Ganbavale et al, 2015). Raatikainen and Laaksonen (2005) have compared different activity coefficient models, and four models were extended by fitting new parameters for aqueous organic-electrolyte solutions.…”