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A predictive group-contribution model for the viscosity of aqueous organic aerosol

机译:用于含水气溶胶水溶液粘度的预测群贡献模型

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The viscosity of primary and secondary organic aerosol (SOA) has important implications for the processing of aqueous organic aerosol phases in the atmosphere, their involvement in climate forcing, and transboundary pollution. Here we introduce a new thermodynamics-based group-contribution model, which is capable of accurately predicting the dynamic viscosity of a mixture over several orders of magnitude (~10-3 to 1012Pa?s) as a function of temperature and mixture composition, accounting for the effect of relative humidity on aerosol water content. The mixture viscosity modelling framework builds on the thermodynamic activity coefficient model AIOMFAC (Aerosol Inorganic–Organic Mixtures Functional groups Activity Coefficients) for predictions of liquid mixture non-ideality, including liquid–liquid phase separation, and the calorimetric glass transition temperature model by DeRieux et?al. (2018) for pure-component viscosity values of organic components. Comparing this new model with simplified modelling approaches reveals that the group-contribution method is the most accurate in predicting mixture viscosity, although accurate pure-component viscosity predictions (and associated experimental data) are key and one of the main sources of uncertainties in current models, including the model presented here. Nonetheless, we find excellent agreement between the viscosity predictions and measurements for systems in which mixture constituents have a molar mass below 350?g?mol?1. As such, we demonstrate the validity of the model in quantifying mixture viscosity for aqueous binary mixtures (glycerol, citric acid, sucrose, and trehalose), aqueous multicomponent mixtures (citric acid plus sucrose and a mixture of nine dicarboxylic acids), and aqueous SOA surrogate mixtures derived from the oxidation of α-pinene, toluene, or isoprene. We also use the model to assess the expected change in SOA particle viscosity during idealized adiabatic air parcel transport from the surface to higher altitudes within the troposphere. This work demonstrates the capability and flexibility of our model in predicting the viscosity for organic mixtures of varying degrees of complexity and its applicability for modelling SOA viscosity over a wide range of temperatures and relative humidities.
机译:初级和二级有机气溶胶(SOA)的粘度对大气中的有机气溶胶阶段加工,其参与气候迫使和跨界污染的过程具有重要意义。在这里,我们介绍了一种新的基于热力学的基础贡献模型,其能够以温度和混合物组成的函数,准确地预测混合物的动态粘度(〜10-3至1012PaΔs),核算相对湿度对气溶胶含水量的影响。混合物粘度建模框架在热力学活性系数模型AIOMFAC(气溶胶无机 - 有机混合物官能团活性系数)上构建,用于预测液体混合物的非理想性,包括液液相分离,以及Derieux等的热玻璃化转变温度模型?al。 (2018)对于有机组分的纯组分粘度值。通过简化的建模方法比较这一新模型揭示了组贡献方法是预测混合粘度最准确的,尽管准确的纯组分粘度预测(以及相关的实验数据)是当前模型中的关键和主要不确定性的主要原因之一,包括这里呈现的模型。尽管如此,我们在混合物成分的粘度预测和测量之间找到了良好的一致性,其中混合成分的摩尔质量在350〜g?摩尔·1以下。因此,我们证明了模型在量化含水二元混合物(甘油,柠檬酸,蔗糖和海藻糖)的混合粘度方面的有效性,水性多组分混合物(柠檬酸加蔗糖和九二羧酸的混合物),以及SOA水溶液衍生自α-甲烯,甲苯或异戊二烯的替代混合物。我们还使用该模型在理想化的绝热空气包裹运输期间从表面到对流层内的更高海拔地区评估SOA颗粒粘度的预期变化。这项工作展示了我们模型的能力和灵活性在预测不同程度的复杂性的有机混合物的粘度及其在广泛的温度和相对湿度范围内建模SOA粘度的适用性。

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