Estimation of particle size distribution parameters in animal lungs

1971 ◽  
Vol 2 (4) ◽  
pp. 393-400 ◽  
Author(s):  
R.G Thomas
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Distribution Parameters

scholarly journals Aerosol particle size distribution in the stratosphere retrieved from SCIAMACHY limb measurements

2018 ◽  
Vol 11 (4) ◽  
pp. 2085-2100 ◽  
Author(s):  
Elizaveta Malinina ◽  
Alexei Rozanov ◽  
Vladimir Rozanov ◽  
Patricia Liebing ◽  
Heinrich Bovensmann ◽  
...  
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Aerosol Particle ◽  
Volcanic Eruptions ◽  
Stratospheric Aerosol ◽  
Solar Light ◽  
Data Set ◽  
Aerosol Particle Size ◽  
Distribution Parameters

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.

scholarly journals The Effect of Nature and Parameters of Particle Size Distribution of Graphite on Physical and Mechanical Properties of Polimer Composites based on Aromatic Poliamide

2016 ◽  
Vol 17 (4) ◽  
pp. 611-620
Author(s):  
H.O. Sirenko ◽  
L.M. Soltys ◽  
V.P. Svidersky ◽  
I.V. Sulyma
Keyword(s):  
Mechanical Properties ◽  
Particle Size ◽  
Wear Resistance ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Physical And Mechanical Properties ◽  
Aromatic Polyamide ◽  
Ash Content ◽  
Natural Graphite ◽  
Distribution Parameters

The resultsof studies of the effect of nature and parameters of particle size distribution of graphite on physical and mechanical properties of polymer composites based on aromatic polyamide fenіlon C-2. The particle size of the filler and polymer for the theoretical gamma-distribution parameters (perimeter, thickness and diameter) have different values. Found the influence of fillers (natural graphite different bands), which differed ash content (5-15% and 0,05-2,5%), moisture and grinding fineness (dispersion) on the wear resistance of the samples of the polymer composite. There is non-linear connectionbetween the intensity and parameters graphite particles distribution.

Investigation of the rheological, thermal, sensory properties, and particle size distribution of sesame paste white compound chocolate as influenced by the soy flour and emulsifier levels

2020 ◽  
Vol 16 (7) ◽  
Author(s):  
Abdul Fateh Hosseini ◽  
Mostafa Mazaheri-Tehrani ◽  
Samira Yeganehzad ◽  
Seyed Mohammad Ali Razavi
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Milk Powder ◽  
Skim Milk ◽  
Skim Milk Powder ◽  
Sensory Properties ◽  
Soy Flour ◽  
Distribution Parameters ◽  
Yield Values

AbstractThe impacts of replacing various levels of skim milk powder with soy flour (0%, 7%, and 14.5% w/w), as well as the quantity of emulsifier (mono-glyceride, 0 and 1.5% w/w) on particle size distribution, rheological, textural, thermal, and sensory properties of sesame paste white compound chocolate were studied. Enhancing the percentage of soy flour along with concurrent decrease of milk powder, increased particle size distribution parameters, as D90 increased from 9.33 to 16.6 (μm). The outcomes indicated that different contents of soy flour affected the hardness along with having greater impact on the samples containing emulsifier. Adding mono-glyceride to chocolate resulted in an excessive reduction in the hardness and also in particle size distribution parameters. Values of Casson plastic viscosity ranged from 2.46 to 5.8 (Pa.s), the Casson yield values and apparent viscosity varied between 9.95 and 111.72 (Pa), and 6.3 and 12.1(Pa.s), respectively. Moreover, analyzing the data demonstrated that soy flour had notable impact on the sensory properties of the samples. Also, soy flour and emulsifier could be manipulated for achieving the desirable rheological properties of sesame paste white compound chocolate.

scholarly journals Statistical estimation of stratospheric particle size distribution by combining optical modelling and lidar scattering measurements

2008 ◽  
Vol 8 (17) ◽  
pp. 5435-5448 ◽  
Author(s):  
J. Jumelet ◽  
S. Bekki ◽  
C. David ◽  
P. Keckhut
Keyword(s):  
Particle Size ◽  
Refractive Index ◽  
Standard Deviation ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Optical Model ◽  
Solid Particles ◽  
Spherical Particles ◽  
Lidar Measurements ◽  
Distribution Parameters

Abstract. A method for estimating the stratospheric particle size distribution from multiwavelength lidar measurements is presented. It is based on matching measured and model-simulated backscatter coefficients. The lidar backscatter coefficients measured at the three commonly used wavelengths 355, 532 and 1064 nm are compared to a precomputed look-up table of model-calculated values. The optical model assumes that particles are spherical and that their size distribution is unimodal. This inverse problem is not trivial because the optical model is highly non-linear with a strong sensitivity to the size distribution parameters in some cases. The errors in the lidar backscatter coefficients are explicitly taken into account in the estimation. The method takes advantage of the statistical properties of the possible solution cluster to identify the most probable size distribution parameters. In order to discard model-simulated outliers resulting from the strong non-linearity of the model, solutions farther than one standard deviation of the median values of the solution cluster are filtered out, because the most probable solution is expected to be in the densest part of the cluster. Within the filtered solution cluster, the estimation algorithm minimizes a cost function of the misfit between measurements and model simulations. Two validation cases are presented on Polar Stratospheric Cloud (PSC) events detected above the ALOMAR observatory (69° N – Norway). A first validation is performed against optical particle counter measurements carried out in January 1996. In non-depolarizing regions of the cloud (i.e. spherical particles), the parameters of an unimodal size distribution and those of the optically dominant mode of a bimodal size distribution are quite successfully retrieved, especially for the median radius and the geometrical standard deviation. As expected, the algorithm performs poorly when solid particles drive the backscatter coefficient. A small bias is identified in modelling the refractive index when compared to previous works that inferred PSC type Ib refractive indices. The accuracy of the size distribution retrieval is improved when the refractive index is set to the value inferred in the reference paper. Our results are then compared to values retrieved with another similar method that does not account for the effect of the measurements errors and the non-linearity of the optical model on the likelihood of the solution. The case considered is a liquid PSC observed over northern Scandinavia on January 2005. An excellent agreement is found between the two methods when our algorithm is applied without any statistical filtering of the solution cluster. However, the solution for the geometrical standard deviation appears to be rather unlikely with a value close to unity (σ≈1.04). When our algorithm is applied with solution filtering, a more realistic value of the standard deviation (σ≈1.27) is found. This highlights the importance of taking into account the non linearity of the model together with the lidar errors, when estimating particle size distribution parameters from lidar measurements.

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