Aerosol formation and growth rates from chamber experiments using Kalman smoothing

Abstract. Bayesian state estimation in the form of Kalman smoothing was applied to differential mobility analyser train (DMA-train) measurements of aerosol size distribution dynamics. Four experiments were analysed in order to estimate the aerosol size distribution, formation rate, and size-dependent growth rate, as functions of time. The first analysed case was a synthetic one, generated by a detailed aerosol dynamics model and the other three chamber experiments performed at the CERN CLOUD facility. The estimated formation and growth rates were compared with other methods used earlier for the CLOUD data and with the true values for the computer-generated synthetic experiment. The agreement in the growth rates was very good for all studied cases: estimations with an earlier method fell within the uncertainty limits of the Kalman smoother results. The formation rates also matched well, within roughly a factor of 2.5 in all cases, which can be considered very good considering the fact that they were estimated from data given by two different instruments, the other being the particle size magnifier (PSM), which is known to have large uncertainties close to its detection limit. The presented fixed interval Kalman smoother (FIKS) method has clear advantages compared with earlier methods that have been applied to this kind of data. First, FIKS can reconstruct the size distribution between possible size gaps in the measurement in such a way that it is consistent with aerosol size distribution dynamics theory, and second, the method gives rise to direct and reliable estimation of size distribution and process rate uncertainties if the uncertainties in the kernel functions and numerical models are known.

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Aerosol formation and growth rates from chamber experiments using Kalman smoothing

10.5194/acp-2021-99 ◽

2021 ◽

Author(s):

Matthew Ozon ◽

Dominik Stolzenburg ◽

Lubna Dada ◽

Aku Seppänen ◽

Kari E. J. Lehtinen

Keyword(s):

Size Distribution ◽

Growth Rates ◽

Numerical Models ◽

Formation Rate ◽

Kernel Functions ◽

The Other ◽

Aerosol Size Distribution ◽

Aerosol Formation ◽

Distribution Dynamics ◽

Kalman Smoothing

Abstract. Bayesian state estimation in the form of Kalman smoothing was applied to Differential Mobility Analyser Train (DMA-train) measurements of aerosol size distribution dynamics. Four experiments were analysed in order to estimate the aerosol size distribution, formation rate and size-dependent growth rate, as functions of time. The first analysed case was a synthetic one, generated by a detailed aerosol dynamics model, and the other three chamber experiments performed at the CERN CLOUD facility. The estimated formation and growth rates were compared with other methods used earlier for the CLOUD data and with the true values for the computer-generated synthetic experiment. The agreement in the growth rates was remarkably good for all studied cases. The formation rates matched also well, especially considering the fact that they were estimated from data given by two different instruments, the other being the Particle Size magnifier (PSM). The presented Fixed Interval Kalman Smoother (FIKS) method has clear advantages compared with earlier methods that have been applied to this kind of data. First, FIKS can reconstruct the size distribution between possible size gaps in the measurement in such a way that it is consistent with aerosol size distribution dynamics theory, and second, the method gives rise to direct and reliable estimation of size distribution and process rate uncertainties if the uncertainties in the kernel functions and numerical models are known.

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Modeling kinetic partitioning of secondary organic aerosol and size distribution dynamics: representing effects of volatility, phase state, and particle-phase reaction

Atmospheric Chemistry and Physics ◽

10.5194/acp-14-5153-2014 ◽

2014 ◽

Vol 14 (10) ◽

pp. 5153-5181 ◽

Cited By ~ 73

Author(s):

R. A. Zaveri ◽

R. C. Easter ◽

J. E. Shilling ◽

J. H. Seinfeld

Keyword(s):

Size Distribution ◽

Rate Constant ◽

Secondary Organic Aerosol ◽

Organic Aerosol ◽

Diffusion Reaction ◽

Aerosol Size Distribution ◽

Particle Phase ◽

Distribution Dynamics ◽

Bulk Diffusivity ◽

New Framework

Abstract. This paper describes and evaluates a new framework for modeling kinetic gas-particle partitioning of secondary organic aerosol (SOA) that takes into account diffusion and chemical reaction within the particle phase. The framework uses a combination of (a) an analytical quasi-steady-state treatment for the diffusion–reaction process within the particle phase for fast-reacting organic solutes, and (b) a two-film theory approach for slow- and nonreacting solutes. The framework is amenable for use in regional and global atmospheric models, although it currently awaits specification of the various gas- and particle-phase chemistries and the related physicochemical properties that are important for SOA formation. Here, the new framework is implemented in the computationally efficient Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) to investigate the competitive growth dynamics of the Aitken and accumulation mode particles. Results show that the timescale of SOA partitioning and the associated size distribution dynamics depend on the complex interplay between organic solute volatility, particle-phase bulk diffusivity, and particle-phase reactivity (as exemplified by a pseudo-first-order reaction rate constant), each of which can vary over several orders of magnitude. In general, the timescale of SOA partitioning increases with increase in volatility and decrease in bulk diffusivity and rate constant. At the same time, the shape of the aerosol size distribution displays appreciable narrowing with decrease in volatility and bulk diffusivity and increase in rate constant. A proper representation of these physicochemical processes and parameters is needed in the next generation models to reliably predict not only the total SOA mass, but also its composition- and number-diameter distributions, all of which together determine the overall optical and cloud-nucleating properties.

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Size distribution dynamics reveal particle-phase chemistry in organic aerosol formation

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1307501110 ◽

2013 ◽

Vol 110 (29) ◽

pp. 11746-11750 ◽

Cited By ~ 111

Author(s):

M. Shiraiwa ◽

L. D. Yee ◽

K. A. Schilling ◽

C. L. Loza ◽

J. S. Craven ◽

...

Keyword(s):

Size Distribution ◽

Organic Aerosol ◽

Particle Phase ◽

Aerosol Formation ◽

Distribution Dynamics ◽

Phase Chemistry

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Secondary organic aerosol formation and transport — II. Predicting the ambient secondary organic aerosol size distribution

Atmospheric Environment Part A General Topics ◽

10.1016/0960-1686(93)90408-q ◽

1993 ◽

Vol 27 (15) ◽

pp. 2403-2416 ◽

Cited By ~ 103

Author(s):

Spyros N. Pandis ◽

Anthony S. Wexler ◽

John H. Seinfeld

Keyword(s):

Size Distribution ◽

Secondary Organic Aerosol ◽

Organic Aerosol ◽

Aerosol Size Distribution ◽

Aerosol Formation ◽

Secondary Organic Aerosol Formation

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Modeling kinetic partitioning of secondary organic aerosol and size distribution dynamics: representing effects of volatility, phase state, and particle-phase reaction

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-28631-2013 ◽

2013 ◽

Vol 13 (11) ◽

pp. 28631-28694 ◽

Cited By ~ 2

Author(s):

R. A. Zaveri ◽

R. C. Easter ◽

J. E. Shilling ◽

J. H. Seinfeld

Keyword(s):

Size Distribution ◽

Rate Constant ◽

Secondary Organic Aerosol ◽

Organic Aerosol ◽

Diffusion Reaction ◽

Aerosol Size Distribution ◽

Particle Phase ◽

Distribution Dynamics ◽

Bulk Diffusivity ◽

New Formulation

Abstract. This paper describes and evaluates a new formulation for modeling kinetic gas-particle partitioning of secondary organic aerosol (SOA) that takes into account diffusion and chemical reaction within the particle phase. The new formulation uses a combination of: (a) an analytical quasi-steady-state treatment for the diffusion-reaction process within the particle phase for fast-reacting organic solutes, and (b) a two-film theory approach for slow- and non-reacting solutes. The formulation is amenable for use in regional and global atmospheric models, although it currently awaits specification of the actual species and particle-phase reactions that are important for SOA formation. Here, the formulation is applied within the framework of the computationally efficient Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) to investigate the competitive growth dynamics of the Aitken and accumulation mode particles. Results show that the timescale of SOA partitioning and the associated size distribution dynamics depend on the complex interplay between organic solute volatility, particle-phase bulk diffusivity, and particle-phase reactivity (as exemplified by a pseudo-first-order reaction rate constant), each of which can vary over several orders of magnitude. In general, the timescale of SOA partitioning increases with increase in volatility and decrease in bulk diffusivity and rate constant. At the same time, the shape of the aerosol size distribution displays appreciable narrowing with decrease in volatility and bulk diffusivity and increase in rate constant. A proper representation of these physicochemical processes and parameters are needed in the next generation models to reliably predict not only the total SOA mass, but also its composition and number size distribution, all of which together determine its overall optical and cloud-nucleating properties.

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Secondary organic aerosol formation during June 2010 in Central Europe: measurements and modelling studies with a mixed thermodynamic-kinetic approach

Atmospheric Chemistry and Physics ◽

10.5194/acp-14-3831-2014 ◽

2014 ◽

Vol 14 (8) ◽

pp. 3831-3842 ◽

Cited By ~ 8

Author(s):

B. Langmann ◽

K. Sellegri ◽

E. Freney

Keyword(s):

Organic Carbon ◽

Size Distribution ◽

Atmospheric Chemistry ◽

Mass Concentration ◽

Three Dimensional ◽

Kinetic Approach ◽

Aerosol Size Distribution ◽

Aerosol Formation ◽

Organic Vapour ◽

Mass Concentrations

Abstract. Until recently secondary organic carbon aerosol (SOA) mass concentrations have been systematically underestimated by three-dimensional atmospheric-chemistry-aerosol models. With a newly proposed concept of aging of organic vapours, more realistic model results for organic carbon aerosol mass concentrations can be achieved. Applying a mixed thermodynamic-kinetic approach for SOA formation shifted the aerosol size distribution towards particles in the cloud condensation nuclei size range, thereby emphasising the importance of SOA formation schemes for modelling realistic cloud and precipitation formation. The additional importance of hetero-molecular nucleation between H2SO4 and organic vapours remains to be evaluated in three-dimensional atmospheric-chemistry-aerosol models. Here a case study is presented focusing on Puy-de-Dôme, France in June 2010. The measurements indicate a considerable increase in SOA mass concentration during the measurement campaign, which could be reproduced by modelling using a simplified thermodynamic-kinetic approach for SOA formation and increased biogenic volatile organic compound (VOC) precursor emissions. Comparison with a thermodynamic SOA formation approach shows a huge improvement in modelled SOA mass concentration with the thermodynamic-kinetic approach for SOA formation. SOA mass concentration increases by a factor of up to 6 accompanied by a slight improvement of modelled particle size distribution. Even though nucleation events at Puy-de-Dôme were rare during the chosen period of investigation, a weak event in the boundary layer could be reproduced by the model in a sensitivity study when nucleation of low-volatile secondary organic vapour is included. Differences in the model results with and without nucleation of organic vapour are visible in the lower free troposphere over several days. Taking into account the nucleation of organic vapour leads to an increase in accumulation mode particles due to coagulation and condensational growth of nucleation and Aitken mode particles.

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Estimated variability of below-cloud aerosol removal by rainfall for observed aerosol size distributions

Atmospheric Chemistry and Physics ◽

10.5194/acp-3-131-2003 ◽

2003 ◽

Vol 3 (1) ◽

pp. 131-143 ◽

Cited By ~ 117

Author(s):

C. Andronache

Keyword(s):

Size Distribution ◽

Field Experiments ◽

Numerical Models ◽

Aerosol Particles ◽

Rainfall Rate ◽

Aerosol Size Distribution ◽

Size Distributions ◽

Aerosol Mass Concentration ◽

Raindrop Size Distribution ◽

Cloud Scavenging

Abstract. Below-cloud scavenging (BCS) coefficients of aerosols by rainfall are estimated for reported aerosol size distributions measured during field experiments in various environments. The method employed is based on explicit calculations of the efficiency of collision between a raindrop and aerosol particles. Such BCS coefficients can be used in numerical models that describe: 1) the detailed evolution of aerosol size distribution and, 2) the evolution of total aerosol mass concentration. The effects of raindrop size distribution and aerosol size distribution variability on BCS coefficients are illustrated using observed data. Results show that BCS coefficient increases with rainfall rate and has a significant dependence on aerosol size distribution parameters. Thus, BCS is important for very small particles (with diameters less than 0.01 μm) and for coarse particles (with diameters larger than 2 µm). For rainfall rate R ~ 1 mm hr-1, the 0.5-folding time of these particles is of the order of one hour. It is shown that BCS is negligible for aerosol particles in the range [0.1-1] µm if compared with in-cloud scavenging rates for low and moderate rainfall rates ( R ~ 0.1-10 mm hr-1). The results indicate that a boundary layer aerosol size distribution with coarse mode is drastically affected very shortly after rain starts (in a fraction of one hour) and consequently, the below-cloud aerosol size distribution becomes dominated by particles in the accumulation mode.

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