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Inverse modelling of Kohler theory - Part 1: A response surface analysis of CCN spectra with respect to surface-active organic species
Stockholm University, Faculty of Science, Department of Environmental Science and Analytical Chemistry. University of Oxford, UK.
Stockholm University, Faculty of Science, Department of Environmental Science and Analytical Chemistry. University of Oxford, UK.
Number of Authors: 42016 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 16, no 17, p. 10941-10963Article in journal (Refereed) Published
Abstract [en]

In this study a novel framework for inverse modelling of cloud condensation nuclei (CCN) spectra is developed using Kohler theory. The framework is established by using model-generated synthetic measurements as calibration data for a parametric sensitivity analysis. Assessment of the relative importance of aerosol physicochemical parameters, while accounting for bulk-surface partitioning of surface-active organic species, is carried out over a range of atmospherically relevant supersaturations. By introducing an objective function that provides a scalar metric for diagnosing the deviation of modelled CCN concentrations from synthetic observations, objective function response surfaces are presented as a function of model input parameters. Crucially, for the chosen calibration data, aerosol-CCN spectrum closure is confirmed as a well-posed inverse modelling exercise for a subset of the parameters explored herein. The response surface analysis indicates that the appointment of appropriate calibration data is particularly important. To perform an inverse aerosol-CCN closure analysis and constrain parametric uncertainties, it is shown that a high-resolution CCN spectrum definition of the calibration data is required where single-valued definitions may be expected to fail. Using Kohler theory to model CCN concentrations requires knowledge of many physicochemical parameters, some of which are difficult to measure in situ on the scale of interest and introduce a considerable amount of parametric uncertainty to model predictions. For all partitioning schemes and environments modelled, model output showed significant sensitivity to perturbations in aerosol log-normal parameters describing the accumulation mode, surface tension, organic : inorganic mass ratio, insoluble fraction, and solution ideality. Many response surfaces pertaining to these parameters contain well-defined minima and are therefore good candidates for calibration using a Monte Carlo Markov Chain (MCMC) approach to constraining parametric uncertainties. A complete treatment of bulk-surface partitioning is shown to predict CCN spectra similar to those calculated using classical Kohler theory with the surface tension of a pure water drop, as found in previous studies. In addition, model sensitivity to perturbations in the partitioning parameters was found to be negligible. As a result, this study supports previously held recommendations that complex surfactant effects might be neglected, and the continued use of classical Kohler theory in global climate models (GCMs) is recommended to avoid an additional computational burden. The framework developed is suitable for application to many additional composition-dependent processes that might impact CCN activation potential. However, the focus of this study is to demonstrate the efficacy of the applied sensitivity analysis to identify important parameters in those processes and will be extended to facilitate a global sensitivity analysis and inverse aerosol-CCN closure analysis.

Place, publisher, year, edition, pages
2016. Vol. 16, no 17, p. 10941-10963
National Category
Earth and Related Environmental Sciences
Research subject
Applied Environmental Science
Identifiers
URN: urn:nbn:se:su:diva-135205DOI: 10.5194/acp-16-10941-2016ISI: 000383963200001OAI: oai:DiVA.org:su-135205DiVA, id: diva2:1047058
Available from: 2016-11-16 Created: 2016-11-01 Last updated: 2022-03-23Bibliographically approved
In thesis
1. Modelling the effects of organic aerosol phase partitioning processes on cloud formation
Open this publication in new window or tab >>Modelling the effects of organic aerosol phase partitioning processes on cloud formation
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Atmospheric aerosols particles may act as cloud condensation nuclei (CCN) that provide sites for condensation of water vapour for the formation of cloud droplets, called cloud droplet activation. Whether aerosol particles are CCN is determined by their size, composition and the ambient humidity. Cloud macrophysical properties together with the size and number concentration of droplets determine the optical properties of liquid phase clouds. Clouds are an important component in the Earth's radiation balance and aerosol-cloud interactions (ACI) are associated with the largest uncertainty in estimates made of anthropogenic radiative forcing in earth system models.

To constrain ACI and reduce uncertainties, an improvement in our understanding of CCN activation is required. Owing to its complex phase structure and chemical heterogeneity, the organic fraction of atmospheric aerosol introduces significant challenges in developing an exact description of cloud formation. In this thesis, a cloud parcel model is employed to systematically address parametric and process uncertainties in estimates of cloud droplet sizes and number concentrations (CDNC). To do so, the unified framework for organic aerosol (UFO) scheme was developed and embedded into the cloud parcel model, ICPM-UFO. The ICPM-UFO simulates partitioning of organic mass between the gas and aqueous bulk and surface phases, thereby providing means to theoretically diagnose changes in droplet nucleating potential of aerosol particles due to organic aerosol mass transfer processes.

Partitioning of surface active organic aerosol mass from the bulk particle phase to the surface phase results in a lowered, size-dependent surface tension that enhances activation potential of CCN and therefore simulated CDNC. A large fraction of organic aerosol constituents exist partitioned across particle and gas phases and simulation of cloud formation events show this semi-volatile organic mass to condense to the particle phase as humidity increases through the cloud base. This additional particle phase mass may be partially soluble. The more soluble component increases the activation potential by lowering the water activity, while the less soluble but more surface active component also increases the activation potential by further lowering of the surface tension. The compounding effects of the gas-particle and bulk-surface partitioning processes result in significant changes in CCN concentrations and CDNC for simulation on boreal aerosol. These results exhibit a significant over prediction of typical boreal CCN concentrations relative to in-situ measurements, though further sensitivity analysis with respect to the soluble fraction and surface phase description may be advantageous. Based on multivariate statistical approaches applied, resolution of the surface phase in cloud formation parameterisations within climate models is however not currently recommended.

Theoretical description of both partitioning processes require prescription of input parameters that are challenging to measure in-situ. These parameters include: SVOC volatility and enthalpy of vaporisation and organic component surface tension and film thickness. Further work using the inverse modelling framework established herein is recommended to provide estimation of these parameters while simultaneously matching simulated CDNC and/or CCN concentrations with observational data. It is envisaged that such an investigation will also yield insights into structural uncertainties associated with the choice of surface phase model - a point of contention both within this thesis and the wider literature.  

Place, publisher, year, edition, pages
Stockholm: Department of Environmental Science, Stockholm University, 2020. p. 52
Keywords
Cloud droplet activation, organic aerosol, cloud parcel modelling, Köhler theory, Sensitivity and Uncertainty analysis
National Category
Meteorology and Atmospheric Sciences
Research subject
Applied Environmental Science
Identifiers
urn:nbn:se:su:diva-182598 (URN)978-91-7911-222-6 (ISBN)978-91-7911-223-3 (ISBN)
Public defence
2020-09-11, digitally via conference (Zoom), public link at https://www.aces.su.se/, Stockholm, 13:00 (English)
Opponent
Supervisors
Note

At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 4: Manuscript.

Available from: 2020-08-19 Created: 2020-06-16 Last updated: 2022-02-26Bibliographically approved

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Lowe, SamuelPartridge, Daniel G.

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