scholarly journals Influence of the dry aerosol particle size distribution and morphology on the cloud condensation nuclei activation. An experimental and theoretical investigation

2020 ◽  
Vol 20 (7) ◽  
pp. 4209-4225 ◽  
Author(s):  
Junteng Wu ◽  
Alessandro Faccinetto ◽  
Symphorien Grimonprez ◽  
Sébastien Batut ◽  
Jérôme Yon ◽  
...  

Abstract. Combustion and other high-temperature processes frequently result in the emission of aerosols in the form of polydisperse fractal-like aggregates made of condensed-phase nanoparticles (soot for instance). If certain conditions are met, the emitted aerosol particles are known to evolve into important cloud condensation nuclei (CCN) in the atmosphere. In this work, the hygroscopic parameter κ of complex morphology aggregates is calculated from the supersaturation-dependent activated fraction Fa=Fa(SS) in the frame of κ-Köhler theory. The particle size distribution is approximated with the morphology-corrected volume equivalent diameter calculated from the electrical mobility diameter by taking into account the diameter of the primary particle and the fractal dimension of the aggregate experimentally obtained from transmission electron microscopy measurements. Activation experiments are performed in water supersaturation conditions using a commercial CCN-100 condensation nuclei counter. The model is tested in close-to-ideal conditions of size-selected, isolated spherical particles (ammonium sulfate nanoparticles dispersed in nitrogen), then with complex polydisperse fractal-like aggregates (soot particles activated by exposure to ozone with κ as low as 5×10-5) that represent realistic anthropogenic emissions in the atmosphere.

2012 ◽  
Vol 12 (10) ◽  
pp. 4449-4476 ◽  
Author(s):  
G. W. Mann ◽  
K. S. Carslaw ◽  
D. A. Ridley ◽  
D. V. Spracklen ◽  
K. J. Pringle ◽  
...  

Abstract. In the most advanced aerosol-climate models it is common to represent the aerosol particle size distribution in terms of several log-normal modes. This approach, motivated by computational efficiency, makes assumptions about the shape of the particle distribution that may not always capture the properties of global aerosol. Here, a global modal aerosol microphysics module (GLOMAP-mode) is evaluated and improved by comparing against a sectional version (GLOMAP-bin) and observations in the same 3-D global offline chemistry transport model. With both schemes, the model captures the main features of the global particle size distribution, with sub-micron aerosol approximately unimodal in continental regions and bi-modal in marine regions. Initial bin-mode comparisons showed that the current values for two size distribution parameter settings in the modal scheme (mode widths and inter-modal separation sizes) resulted in clear biases compared to the sectional scheme. By adjusting these parameters in the modal scheme, much better agreement is achieved against the bin scheme and observations. Annual mean surface-level mass of sulphate, sea-salt, black carbon (BC) and organic carbon (OC) are within 25% in the two schemes in nearly all regions. Surface level concentrations of condensation nuclei (CN), cloud condensation nuclei (CCN), surface area density and condensation sink also compare within 25% in most regions. However, marine CCN concentrations between 30° N and 30° S are systematically 25–60% higher in the modal model, which we attribute to differences in size-resolved particle growth or cloud-processing. Larger differences also exist in regions or seasons dominated by biomass burning and in free-troposphere and high-latitude regions. Indeed, in the free-troposphere, GLOMAP-mode BC is a factor 2–4 higher than GLOMAP-bin, likely due to differences in size-resolved scavenging. Nevertheless, in most parts of the atmosphere, we conclude that bin-mode differences are much less than model-observation differences, although some processes are missing in these runs which may pose a bigger challenge to modal schemes (e.g., boundary layer nucleation and ultra-fine sea-spray). The findings here underline the need for a spectrum of complexity in global models, with size-resolved aerosol properties predicted by modal schemes needing to be continually benchmarked and improved against freely evolving sectional schemes and observations.


Author(s):  
Steven L. Alderman ◽  
Chen Song ◽  
Serban C. Moldoveanu ◽  
Stephen K. Cole

AbstractThe relatively volatile nature of the particulate matter fraction of e-cigarette aerosols presents an experimental challenge with regard to particle size distribution measure-ments. This is particularly true for instruments requiring a high degree of aerosol dilution. This was illustrated in a previous study, where average particle diameters in the 10-50 nm range were determined by a high-dilution, electrical mobility method. Total particulate matter (TPM) masses calculated based on those diameters were orders of magnitude smaller than gravimetrically determined TPM. This discrepancy was believed to result from almost complete particle evaporation at the dilution levels of the electrical mobility analysis. The same study described a spectral transmission measurement of e-cigarette particle size in an undiluted state, and reported particles from 210-380 nm count median diameter. Observed particle number concentrations were in the 10Described here is a study in which e-cigarette aerosols were collected on Cambridge filters with adsorbent traps placed downstream in an effort to capture any material passing through the filter. Amounts of glycerin, propylene glycol, nicotine, and water were quantified on the filter and downstream trap. Glycerin, propylene glycol, and nicotine were effciently captured (> 98%) by the upstream Cambridge filter, and a correlation was observed between filtration efficiency and the partial vapor pressure of each component. The present analysis was largely inconclusive with regard to filter efficiency and particle-vapor partitioning of water. [Beitr. Tabakforsch. Int. 26 (2014) 183-190]


2021 ◽  
Author(s):  
Pak Lun Fung ◽  
Martha Arbayani Zaidan ◽  
Ola Surakhi ◽  
Sasu Tarkoma ◽  
Tuukka Petäjä ◽  
...  

Abstract. In air quality research, often only particle mass concentrations as indicators of aerosol particles are considered. However, the mass concentrations do not provide sufficient information to convey the full story of fractionated size distribution, which are able to deposit differently on respiratory system and cause various harm. Aerosol size distribution measurements rely on a variety of techniques to classify the aerosol size and measure the size distribution. From the raw data the ambient size distribution is determined utilising a suite of inversion algorithms. However, the inversion problem is quite often ill-posed and challenging to invert. Due to the instrumental insufficiency and inversion limitations, models for fractionated particle size distribution are of great significance to fill the missing gaps or negative values. The study at hand involves a merged particle size distribution, from a scanning mobility particle sizer (NanoSMPS) and an optical particle sizer (OPS) covering the aerosol size distributions from 0.01 to 0.42 μm (electrical mobility equivalent size) and 0.3 μm to 10 μm (optical equivalent size) and meteorological parameters collected at an urban background region in Amman, Jordan in the period of 1st Aug 2016–31st July 2017. We develop and evaluate feed-forward neural network (FFNN) models to estimate number concentrations at particular size bin with (1) meteorological parameters, (2) number concentration at other size bins, and (3) both of the above as input variables. Two layers with 10–15 neurons are found to be the optimal option. Lower model performance is observed at the lower edge (0.01 


Author(s):  
S. Cazares ◽  
J. A. Barrios ◽  
C. Maya ◽  
G. Velásquez ◽  
M. Pérez ◽  
...  

Abstract An important physical property in environmental samples is particle size distribution. Several processes exist to measure particle diameter, including change in electrical resistance, blocking of light, the fractionation of field flow and laser diffraction (these being the most commonly used). However, their use requires expensive and complex equipment. Therefore, a Digital Microscopic Imaging Application (DMIA) method was developed adapting the algorithms used in the Helminth Egg Automatic Detector (HEAD) software coupled with a Neural Network (NN) and Bayesian algorithms. This allowed the determination of particle size distribution in samples of waste activated sludge (WAS), recirculated sludge (RCS), and pretreated sludge (PTS). The recirculation and electro-oxidation pre-treatment processes showed an effect in increasing the degree of solubilization (DS), decreasing particle size and breakage factor with ranges between 44.29%, and 31.89%. Together with a final NN calibration process, it was possible to compare results. For example, the 90th percentile of Equivalent Diameter (ED) value obtained by the DMIA with the corresponding result for the laser diffraction method. DMIA values: 228.76 μm (WAS), 111.18 μm (RCS), and 84.45 μm (PTS). DMIA processing has advantages in terms of reducing complexity, cost and time, and offers an alternative to the laser diffraction method.


2007 ◽  
Vol 534-536 ◽  
pp. 1621-1624
Author(s):  
Yuto Amano ◽  
Takashi Itoh ◽  
Hoshiaki Terao ◽  
Naoyuki Kanetake

For precise property control of sintered products, it is important to know the powder characteristics, especially the packing density of the powder. In a previous work, we developed a packing simulation program that could make a packed bed of spherical particles having particle size distribution. In order to predict the packing density of the actual powder that consisted of nonspherical particles, we combined the packing simulation with a particle shape analysis. We investigated the influence of the particle size distribution of the powder on the packing density by executing the packing simulation based on particle size distributions of the actual milled chromium powders. In addition, the influence of the particle shape of the actual powder on the packing density was quantitatively analyzed. A prediction of the packing density of the milled powder was attempted with an analytical expression between the particle shape of the powder and the packing simulation. The predicted packing densities were in good agreement with the actual data.


2018 ◽  
Vol 11 (4) ◽  
pp. 2085-2100 ◽  
Author(s):  
Elizaveta Malinina ◽  
Alexei Rozanov ◽  
Vladimir Rozanov ◽  
Patricia Liebing ◽  
Heinrich Bovensmann ◽  
...  

Abstract. Information about aerosols in the Earth's atmosphere is of a great importance in the scientific community. While tropospheric aerosol influences the radiative balance of the troposphere and affects human health, stratospheric aerosol plays an important role in atmospheric chemistry and climate change. In particular, information about the amount and distribution of stratospheric aerosols is required to initialize climate models, as well as validate aerosol microphysics models and investigate geoengineering. In addition, good knowledge of stratospheric aerosol loading is needed to increase the retrieval accuracy of key trace gases (e.g. ozone or water vapour) when interpreting remote sensing measurements of the scattered solar light. The most commonly used characteristics to describe stratospheric aerosols are the aerosol extinction coefficient and Ångström coefficient. However, the use of particle size distribution parameters along with the aerosol number density is a more optimal approach. In this paper we present a new retrieval algorithm to obtain the particle size distribution of stratospheric aerosol from space-borne observations of the scattered solar light in the limb-viewing geometry. While the mode radius and width of the aerosol particle size distribution are retrieved, the aerosol particle number density profile remains unchanged. The latter is justified by a lower sensitivity of the limb-scattering measurements to changes in this parameter. To our knowledge this is the first data set providing two parameters of the particle size distribution of stratospheric aerosol from space-borne measurements of scattered solar light. Typically, the mode radius and w can be retrieved with an uncertainty of less than 20 %. The algorithm was successfully applied to the tropical region (20° N–20° S) for 10 years (2002–2012) of SCIAMACHY observations in limb-viewing geometry, establishing a unique data set. Analysis of this new climatology for the particle size distribution parameters showed clear increases in the mode radius after the tropical volcanic eruptions, whereas no distinct behaviour of the absolute distribution width could be identified. A tape recorder, which describes the time lag as the perturbation propagates to higher altitudes, was identified for both parameters after the volcanic eruptions. A quasi-biannual oscillation (QBO) pattern at upper altitudes (28–32 km) is prominent in the anomalies of the analysed parameters. A comparison of the aerosol effective radii derived from SCIAMACHY and SAGE II data was performed. The average difference is found to be around 30 % at the lower altitudes, decreasing with increasing height to almost zero around 30 km. The data sample available for the comparison is, however, relatively small.


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