A predictive thermodynamic framework of cloud droplet activation for chemically unresolved aerosol mixtures, including surface tension, non-ideality, and bulk–surface partitioning

Abstract This work presents a thermodynamically consistent framework that enables self-contained, predictive Köhler calculations of droplet growth and activation with considerations of surface adsorption, surface tension reduction, and non-ideal water activity for chemically complex and unresolved surface-active aerosol mixtures. The common presence of surface-active species in atmospheric aerosols is now well-established. However, the impacts of different effects driven by surface activity, in particular bulk–surface partitioning and resulting bulk depletion and/or surface tension reduction, on aerosol hygroscopic growth and cloud droplet activation remain to be generally established. Because specific characterization of key properties, including water activity and surface tension, remains exceedingly challenging for finite-sized activating droplets, a self-contained and thermodynamically consistent model framework is needed to resolve the individual effects of surface activity during droplet growth and activation. Previous frameworks have achieved this for simple aerosol mixtures, comprising at most a few well-defined chemical species. However, atmospheric aerosol mixtures and more realistic laboratory systems are typically chemically more complex and not well-defined (unresolved). Therefore, frameworks which require specific knowledge of the concentrations of all chemical species in the mixture and their composition-dependent interactions cannot be applied. For mixtures which are unresolved or where specific interactions between components are unknown, analytical models based on retrofitting can be applied, or the mixture can be represented by a proxy compound or mixture with well-known properties. However, the surface activity effects evaluated by such models cannot be independently verified. The presented model couples Köhler theory with the Gibbs adsorption and Szyszkowski-type surface tension equations. Contrary to previous thermodynamic frameworks, it is formulated on a mass basis to obtain a quantitative description of composition-dependent properties for chemically unresolved mixtures. Application of the model is illustrated by calculating cloud condensation nuclei (CCN) activity of aerosol particles comprising Nordic aquatic fulvic acid (NAFA), a chemically unresolved and strongly surface-active model atmospheric humic-like substance (HULIS), and NaCl, with dry diameters of 30–230 nm and compositions spanning the full range of relative NAFA and NaCl mixing ratios. For comparison with the model presented, several other predictive Köhler frameworks, with simplified treatments of surface-active NAFA, are also applied. Effects of NAFA surface activity are gauged via a suite of properties evaluated for growing and activating droplets. The presented framework predicts a similar influence of surface activity of the chemically complex NAFA on CCN activation as was previously shown for single, strong surfactants. Comparison to experimental CCN data shows that NAFA bulk–surface partitioning is well-represented by Gibbs adsorption thermodynamics. Contrary to several recent studies, no evidence of significantly reduced droplet surface tension at the point of activation was found. Calculations with the presented thermodynamic model show that throughout droplet growth and activation, the finite amounts of NAFA in microscopic and submicron droplets are strongly depleted from the bulk, due to bulk–surface partitioning, because surface areas for a given bulk volume are very large. As a result, both the effective hygroscopicity and ability of NAFA to reduce droplet surface tension are significantly lower in finite-sized activating droplets than in macroscopic aqueous solutions of the same overall composition. The presented framework enables the influence of surface activity on CCN activation for other chemically complex and unresolved aerosol mixtures, including actual atmospheric samples, to be systematically explored. Thermodynamic input parameters can be independently constrained from measurements, instead of being either approximated by a proxy or determined by retrofitting, potentially confounding several mechanisms influenced by surface activity

Managing urban traffic emissions with focus on people and atmospheric impacts

Abstract With a growing majority of the world’s population residing in cities, it is vital to advance a shift to low-emission urban mobility in order to mitigate climate change. Despite the fundamental role played by infrastructure, daily decisions and routines of individuals ultimately generate traffic. When people choose a conventionally fueled private car, it causes externalities detrimental for both individuals and the urban system as a whole: congestion, noise, greenhouse gas emissions, air pollution. Empirical studies show that the awareness of and exposure to those do not provide enough motivation for people to shift to more sustainable travel modes. Convenience overpowers environmental values. To break the habits and manage emissions, authorities must deploy incentives or sanctions — structural, regulative, economic, persuasive — that can increase the comparative advantage of low-carbon traffic modes. The potential of different initiatives to reduce traffic emissions is invaluable information for decision makers. Our contribution investigates the variety of possible ways to advance the desired shift, and highlights the importance, challenges, and key factors of high quality impact evaluations. A functional approach to test and evaluate traffic initiatives is multidisciplinary, with ways to quantify people’s behavior and preferences, traffic emerging from them, and the resulting atmospheric emissions. By shedding light on reliable approaches to reveal the real impacts of traffic initiatives, the efforts for climate change management may be reinforced

Improving solubility and activity estimates of multifunctional atmospheric organics by selecting conformers in COSMOtherm

Abstract We estimated aqueous solubilities and activity coefficients of atmospherically relevant highly oxidized multifunctional organic compounds in binary mixtures with water at temperatures between 278.15 and 338.15 K, using the COSMOtherm program. Physicochemical properties of organic aerosol constituents are needed in the modeling of atmospheric aerosol processes. As experimental data are often impossible to obtain, reliable estimates from theoretical approaches are a promising path to fill this gap. We investigated the effect of intramolecular hydrogen bonds on the estimation of these condensed-phase properties, attempting to improve the agreement between experimental and estimated values. Citric, tartaric, malic, and maleic acids, which are often used in atmospheric models as representatives of oxidized compounds, were selected to benchmark our calculations. In addition, we estimated aqueous solubilities and activity coefficients of α-pinene-derived organosulfates and highly oxidized isoprene-derived organic compounds, for which no experimental data are available. Our results indicate that the absolute aqueous solubility and activity coefficient estimates of citric, tartaric, malic, and maleic acids, and likely other multifunctional organics, can be improved significantly by selecting conformers on the basis of their intramolecular hydrogen bonding in COSMOtherm calculations

Composition dependent density of ternary aqueous solutions of ionic surfactants and salts:capturing the effect of surfactant micellization in atmospheric droplet model solutions

Abstract Surfactants exist in atmospheric aerosols mixed with inorganic salts and can significantly influence the formation of cloud droplets due to bulk–surface partitioning and surface tension depression. To model these processes, we need continuous parametrizations of the concentration dependent properties of aqueous surfactant–salt solutions for the full composition range from pure water to pure surfactant or salt. We have developed density functions based on the pseudo-separation method and Young’s mixing rule for apparent partial molal volumes for solutions that mimic atmospheric droplets of marine environments. The developed framework requires only model parameters from binary water–salt and water–surfactant systems and includes the effect of salinity on micellization with composition-dependent functions for the critical micelle concentration (CMC). We evaluate different models and data available in the literature to find the most suitable representations of the apparent partial molal volume of sodium chloride (NaCl) in aqueous solutions and the CMC of selected atmospheric and model surfactants in pure water and aqueous NaCl solutions. We compare model results to experimental density data, available in the literature and obtained from additional measurements, for aqueous solutions containing one of the ionic surfactants sodium octanoate, sodium decanoate, sodium dodecanoate or sodium dodecylsulfate mixed with NaCl in different relative ratios. Our model follows the experimental trends of increasing densities with increasing surfactant concentrations or increasing surfactant–salt mixing ratios both, below and above the CMC, capturing the effect of the inorganic salt on the surfactant micellization

The atmospheric impacts of initiatives advancing shifts towards low-emission mobility:a scoping review

Abstract In an urban environment, people’s daily traffic choices are reflected in emissions and the resulting local air composition, or air quality. Traffic contributes to the emissions of both carbon dioxide (CO₂), affecting climate, and particulate matter (PM), affecting atmospheric chemistry and human health. While the development of city infrastructure is not in the hands of individuals, it is their transport mode choices that constitute traffic. In this scoping review we analyse 108 initiatives from around the world potentially influencing individual travel behaviour and producing changes in the shares of different transport modes (modal shifts). The targets, types and techniques of initiatives are identified. Examples of economic, regulative, structural and persuasive initiatives are included. Special focus is on whether the impacts on CO₂ emissions, PM emissions and/or PM concentrations have been quantitatively evaluated, and on the quality and results of the evaluations. We observe that a variety of targets can motivate actions that lead to modal shifts and emission reductions. The results indicate that the level of atmospheric evaluations is low: absolute or relative changes in emissions and/or concentrations had been evaluated for only 31% (N = 34) of the reviewed initiatives, with substantial heterogeneity in quality. Sanctions, such as congestion charge and restrictions, have more likely been evaluated in peer reviewed analyses than incentives. Scientific evaluations of impacts on ambient PM concentrations are especially scarce (N = 4), although Air Quality is the primary target of 13% of actions and secondary target for at least 12%. We discuss the determinants of success and failure, when it comes to different types of initiatives, emission reductions and evaluations. A high-quality evaluation of atmospheric impacts captures the following: correct data about the modal shift (rate and direction), exclusion of external factors affecting the shift and emissions, and possible indirect impacts of the shift

Qu­antitative alignment parameter estimation for analyzing X-ray photoelectron spectra

Abstract The interpretation of X-ray photoelectron spectroscopy (XPS) data relies on measurement models that depend on several parameters, including the photoelectron attenuation length and X-ray photon flux. However, some of these parameters are not known, because they are not or cannot be measured. The unknown geometrical parameters can be lumped together in a multiplicative factor, the alignment parameter. This parameter characterizes the ability of the exciting light to interact with the sample. Unfortunately, the absolute value of the alignment parameter cannot be measured directly, in part because it depends on the measurement model. Instead, a proxy for the experimental alignment is often estimated, which is closely related to the alignment parameter. Here, a method for estimating the absolute value of the alignment parameter based on the raw XPS spectra (i.e. non-processed photoelectron counts), the geometry of the sample and the photoelectron attenuation length is presented. The proposed parameter estimation method enables the quantitative analysis of XPS spectra using a simplified measurement model. All computations can be executed within the open and free Julia language framework PROPHESY. To demonstrate feasibility, the alignment parameter estimation method is first tested on simulated data with known acquisition parameters. The method is then applied to experimental XPS data and a strong correlation between the estimated alignment parameter and the typically used alignment proxy is shown

Model for estimating activity coefficients in binary and ternary ionic surfactant solutions

Abstract We introduce the CMC based Ionic Surfactant Activity model (CISA) to calculate activity coefficients in ternary aqueous solutions of an ionic surfactant and an inorganic salt. The surfactant can be either anionic or cationic and in the present development, the surfactant and inorganic salts share a common counterion. CISA incorporates micellization into the Pitzer–Debye–Hückel (PDH) framework for activities of mixed electrolyte solutions. To reduce computing requirements, a parametrization of the critical micelle concentration (CMC) is used to estimate the degree of micellization instead of explicit equilibrium calculations. For both binary and ternary systems, CISA only requires binary experimentally-based parameters to describe water–ion interactions and temperature–composition dependency of the CMC. The CISA model is intended in particular for atmospheric applications, where higher-order solution interaction parameters are typically not constrained by experiments and the description must be reliable across a wide range of compositions. We evaluate the model against experimental activity data for binary aqueous solutions of ionic surfactants sodium octanoate and sodium decanoate, as common components of atmospheric aerosols, and sodium dodecylsulfate, the most commonly used model compound for atmospheric surfactants. Capabilities of the CISA model to describe ternary systems are tested for the water–sodium decanoate–sodium chloride system, a common surrogate for marine background cloud condensation nuclei and to our knowledge the only atmospherically relevant system for which ternary activity data is available. For these systems, CISA is able to provide continuous predictions of activity coefficients both below and above CMC and in all cases gives an improved description of the water activity above the CMC, compared to the alternative model of Burchfield and Wolley [J. Phys. Chem., 88(10), 2149–2155 (1984)]. The water activity is a key parameter governing the formation and equilibrium growth of cloud droplets. The CISA model can be extended from the current form to include the effect of other inorganic salts with the existing database of binary PDH parameters and using appropriate mixing rules to account for ion specificity in the micellization process

Cloud droplet activation of organic–salt mixtures predicted from two model treatments of the droplet surface

Abstract The droplet surface plays important roles in the interaction between organic aerosols with clouds and climate. Surface active organic compounds can partition to the droplet surface, depleting solute from the droplet bulk or depressing the droplet surface tension. This may in turn affect the shape of the droplet growth curve, threshold of aerosol activation into cloud droplets, as well as activated droplet size distributions, and cloud radiative effects. In this work, a new monolayer model along with a traditional Gibbs adsorption isotherm model were used in conjunction with equilibrium Köhler theory to predict CCN activation of both simple and complex surface active model aerosol systems. For the surface active aerosol considered, the monolayer droplet model produces similar results to the Gibbs model as well as comparable results to CCN measurements from literature, even for systems where specific molecular identities and aqueous properties are unknown. The monolayer model is self-contained, fully prognostic, and provides a versatile, conceptually simple, yet physically-based model for understanding the role of organic surfactants in cloud droplet formation

Inversion model for extracting chemically resolved depth profiles across liquid interfaces of various configurations from XPS data:PROPHESY

Abstract PROPHESY, a technique for the reconstruction of surface-depth profiles from X-ray photoelectron spectroscopy data, is introduced. The inversion methodology is based on a Bayesian framework and primal-dual convex optimization. The acquisition model is developed for several geometries representing different sample types: plane (bulk sample), cylinder (liquid microjet) and sphere (droplet). The methodology is tested and characterized with respect to simulated data as a proof of concept. Possible limitations of the method due to uncertainty in the attenuation length of the photo-emitted electron are illustrated