Fractal aggregates in the atmosphere

Lushnikov, A.A.; Гвишиани, А. Д.; Lyubovtseva, Yu. S.

doi:10.2205/2013es000531

Cited by 3 publications

(3 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The attempts of modelling this important and still enigmatic process also appeared rather long ago. Here we avoid the long history of this problem and cite only the last models appeared in the XXI century: [Barret and Clement, 1991;Clement and Ford, 1999;Clement et al, 2006;Adams et al, 2002;Korhonen et al, 2003;Lehtinen and Kulmala, 2003;Easter et al, 2004;Anttila et al, 2004;Korhonen et al, 2004;Grini et al, 2005;Lushnikov et al, 2013aLushnikov et al, , 2013bLushnikov et al, 2014;Elperin et al, 2013;Stolzenberg et al, 2005;Spracklen et al, 2006]. The extensive earlier citations can be found in the above listed papers.…”

Section: Nucleation Bursts In the Atmospherementioning

confidence: 99%

Formation of aerosols in the lower troposphere

Lushnikov¹,

Zagaynov²,

Lyubovtseva³

2017

Russ. J. Earth Sci.

Self Cite

View full text Add to dashboard Cite

This paper overviews the observations of aerosol events in the atmosphere in view of a simple linear model of the formation of nanoaerosols in the atmosphere. The model includes three input functions: the rate of formation of the smallest (1.5 nm in diameter) particles by nucleation, the particle growth rate, and the coagulation sink of newly born particles. Neglecting the self-coagulation of newly born particles (this process is slow) simplifies the growth equation describing time evolution of the particle size distribution. This equation becomes linear and is solved exactly. The most remarkable feature of our consideration is that the particle size distribution can be presented as a superposition of different growth regimes. In particular, if the source-enhanced particle growth is combined with the free regime, the latter produces a running wave that moves to the right along the size axis giving the picture very similar to that observed during the nucleation events. The source-enhanced regime alone can also produce the wave moving to the right but the picture is much less expressive. Another possibility discussed here is an abrupt change in the particle source intensity because of increasing the condensation sink. The source stops producing fresh particles and the whole particle distribution begins to shift to the right along the particle size axis. Similar picture is observed if the nucleation process goes at nighttime and stops at daytime. In this case the particles accumulated during the night grow in the free regime at daytime by condensing the low volatile substances formed in photochemical reactions. The particle size spectra are found for different sets of the parameters. Possible scenarios of nucleation bursts are discussed.

show abstract

Section: Nucleation Bursts In the Atmospherementioning

confidence: 99%

Formation of aerosols in the lower troposphere

Lushnikov¹,

Zagaynov²,

Lyubovtseva³

2017

Russ. J. Earth Sci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The importance of the morphology of dust particles on the early Earth's radiation environment is studied in [16]. Fractal structures of particulate matter have been analyzed in the context of the global threat to public health [17][18][19], and in relation to the warming effects in the Earth's atmosphere in [20,21].…”

Section: Introductionmentioning

confidence: 99%

The importance of the local structure of fractal aggregates

Botet,

Rannou,

Tazaki

2024

J. Phys. A: Math. Theor.

View full text Add to dashboard Cite

The pair correlation function, g(r), is a fundamental descriptor of the inner structure of fractal aggregates of monomers. It provides a natural tool for studying physical properties involving two-point interaction (e.g. optics of aggregates). Several domains of distances between pairs of monomers have been identified. The fractal domain (in which g(r) is a power-law) is generally dominant for large aggregates. We show here that the local behaviour of g(r) – involving monomers tangent to a given monomer – is necessary for most of the quantitative applications, even if that local domain is not directly related to fractal morphology. We derive a simple generic pair correlation function for fractal aggregates, depending on three structural parameters only: the fractal dimension, df ; the prefactor, kf ; the local mean coordination number, Z̅. Unlike the fractal dimension, the prefactor and the mean coordination number are not universal since they depend on many parameters of the generation process. We discuss the impact of the definite shape of g(r) on the aggregate structure factor profile (a measurable quantity through small-angle X-ray scattering). Improvement from the new g(r) shape is also illustrated deriving an analytical expression of the geometric cross section, G, of aggregates for fractal dimension < 2. Accuracy is checked by comparing with numerical data from aggregates of fractal dimension df = 1.9. On the up-to-date analytical expression of G, the contributions of the short- and long-range behaviours of g(r) are well separated, and it is clear that the local behaviour of the pair correlation function is required to obtain accurate values of the geometric cross section. Thus, in addition to the fractal structure of aggregates, the local structure of aggregates (to which the prefactor kf and the g(r) divergence at short distances are related) also appears important to accurately describe their physical features.

show abstract

“…Experimental techniques used to investigate irregularly shaped structures included light scattering and transmission electron microscopy (TEM) (Lin et al 1990;Puri et al 1993;Wentzel et al 2003). Researchers have found that atmospheric agglomerates (for, e.g., soot and fly ash) grow mainly by cluster-cluster coagulation and reveal self-similarity; hence, they can be called fractal-like structures that follow the rules of power law scaling (Lee et al 2003;Zhu et al 2005;Lushnikov et al 2013). Thus, the introduction of fractal geometry enabled a convenient and effective mathematical description of structures like particulate matter agglomerates and provided a way to parameterize aerosol properties.…”

Section: Introductionmentioning

confidence: 99%

Introduction of fractal-like agglomerates to the algorithm for calculating surface area concentrations of PM1

Bełkowska-Wołoczko

2018

Air Qual Atmos Health

View full text Add to dashboard Cite

A method of estimating, in urban indoor environments, human exposure to particulate matter with aerodynamic diameter of less than 1 μm (PM1, also referred in the literature as fine-mode or nanometer (nm) particulate matter) is proposed. It defines a measure of exposure as a surface area concentration of PM1 and the means of its calculation. The calculation algorithm was constructed using statistical parameters of particulate matter lognormal distribution, with the use of Hatch-Choate equations and the Maynard method, and extended by the accumulation stage physics of PM1 fraction, including Eggersdorfer's and Pratsinis's findings. Introduction of structure and dynamics of fractal-like agglomerates into the calculation algorithm significantly increased estimation accuracy of surface area concentrations, in relation to the standard Maynard method, which calculates surface area concentrations of only spherical particles.

show abstract

Fractal aggregates in the atmosphere

Cited by 3 publications

References 39 publications

Formation of aerosols in the lower troposphere

Formation of aerosols in the lower troposphere

The importance of the local structure of fractal aggregates

Introduction of fractal-like agglomerates to the algorithm for calculating surface area concentrations of PM1

Contact Info

Product

Resources

About