Particle Absorption and Scatter

2006 ◽  
Author(s):  
Michael E. Thomas
Keyword(s):  
Unit Volume ◽  
Particle Number ◽  
Mie Scattering ◽  
Particle Number Density ◽  
Number Density ◽  
Shape Variation ◽  
Propagation Modeling ◽  
Total Particle Number ◽  
Total Particle ◽  
Unit Radius

Particles are composed of solids and/or liquids, thus the bulk optical properties of these media must be known before propagation modeling within a medium of suspended particles (called aerosols when in air) can begin. We return to our discussion of propagation in the atmosphere and oceans of the earth that began in Chapters 7 and 9, and we now include attenuation by small particles. Particles vary in size, shape, concentration, and composition. Size and concentration distributions are described in the following two sections. The composition of the most common particles is presented in the last section. Unfortunately, a representation of shape variation does not exist. As mentioned in Chapter 4 (Section 4.4.2 on Mie scattering), a collection of real aerosols will have a range of different radii. This is called a polydisperse medium. Various models are used to represent particle size distributions. One commonly used model for particle number density as a function of radius is the modified gamma distribution function, as given by . . . ρp(r) = Arα exp(−brγ), (10.1) . . . where A, b, α, and γ are empirically determined parameters. This function represents the number of particles per unit volume and unit radius as a function of radius r. The total particle number density is obtained by integrating ρp(r ) over all r.

scholarly journals Implementing growth and sedimentation of NAT particles in a global Eulerian model

2004 ◽  
Vol 4 (7) ◽  
pp. 1869-1883 ◽  
Author(s):  
M. M. P. van den Broek ◽  
J. E. Williams ◽  
A. Bregman
Keyword(s):  
Particle Number ◽  
Transport Model ◽  
Particle Diameter ◽  
Particle Growth ◽  
Particle Number Density ◽  
Lagrangian Model ◽  
Number Density ◽  
Model Study ◽  
Total Particle Number ◽  
Total Particle

Abstract. Here we present a concise and efficient algorithm to mimic the growth and sedimentation of Nitric Acid Trihydate (NAT) particles in the polar vortex in a state-of-the-art 3D chemistry transport model. The particle growth and sedimentation are calculated using the microphysical formulation of Carslaw et al. (2002). Once formed, NAT particles are transported in the model as tracers in the form of size-segregated quantities or size bins. Two different approaches were adopted for this purpose: one assuming a fixed particle number density ("FixedDens") and the other assuming a discrete set of particle diameter values ("FixedRad"). Simulations were performed for three separate 10-day periods during the 1999-2000 Arctic winter and compared to the results of an existing Lagrangian model study, which uses similar microphysics in a computationally more expensive method for the simulation of NAT particle growth. The resulting particle sizes for both our approaches compare favourably at 430K with those obtained from this previous model study, and also in-situ observations related to the size of large NAT particles. The particle growth is faster for "FixedDens" resulting in a difference in (de)nitrification by a factor of ~2 for all three simulation periods. Comparisons were made with a standard equilibrium approach and the differences in the redistribution of HNO3 were found to be substantial. For both approaches the performance of the algorithm is rather insensitive to both the number of size bins and the shape of the size distribution, and show a weak dependence on the prescribed total particle number density during the coldest period. This results in an increase of 7% for the "FixedRad" approach and 17% for the "FixedDens" approach when increasing the total particle number density by a factor of 2.5.

scholarly journals Impact of the Coronavirus Pandemic Lockdown on Atmospheric Nanoparticle Concentrations in Two Sites of Southern Italy

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 352
Author(s):  
Adelaide Dinoi ◽  
Daniel Gulli ◽  
Ivano Ammoscato ◽  
Claudia R. Calidonna ◽  
Daniele Contini
Keyword(s):  
Particle Number ◽  
Southern Italy ◽  
Time Intervals ◽  
Atmospheric Particle ◽  
Total Particle Number ◽  
Total Particle ◽  
Consequent Reduction ◽  
Containment Measures ◽  
Coronavirus Infection ◽  
The Impact

During the new coronavirus infection outbreak, the application of strict containment measures entailed a decrease in most human activities, with the consequent reduction of anthropogenic emissions into the atmosphere. In this study, the impact of lockdown on atmospheric particle number concentrations and size distributions is investigated in two different sites of Southern Italy: Lecce and Lamezia Terme, regional stations of the GAW/ACTRIS networks. The effects of restrictions are quantified by comparing submicron particle concentrations, in the size range from 10 nm to 800 nm, measured during the lockdown period and in the same period of previous years, from 2015 to 2019, considering three time intervals: prelockdown, lockdown and postlockdown. Different percentage reductions in total particle number concentrations are observed, −19% and −23% in Lecce and −7% and −4% in Lamezia Terme during lockdown and postlockdown, respectively, with several variations in each subclass of particles. From the comparison, no significant variations of meteorological factors are observed except a reduction of rainfall in 2020, which might explain the higher levels of particle concentrations measured during prelockdown at both stations. In general, the results demonstrate an improvement of air quality, more conspicuous in Lecce than in Lamezia Terme, during the lockdown, with a differed reduction in the concentration of submicronic particles that depends on the different types of sources, their distance from observational sites and local meteorology.

Experimentally determined particle number density statistics in an industrial-scale, pulverized-coal-fired boiler

1993 ◽  
Vol 7 (6) ◽  
pp. 842-851 ◽  
Author(s):  
M. Queiroz ◽  
M. P. Bonin ◽  
J. S. Shirolkar ◽  
R. W. Dawson
Keyword(s):  
Particle Number ◽  
Particle Number Density ◽  
Pulverized Coal ◽  
Industrial Scale ◽  
Number Density

The next step in precipitation polymerization of N-isopropylacrylamide: particle number density control by monochain globule surface charge modulation

2016 ◽  
Vol 7 (32) ◽  
pp. 5123-5131 ◽  
Author(s):  
O. L. J. Virtanen ◽  
M. Brugnoni ◽  
M. Kather ◽  
A. Pich ◽  
W. Richtering
Keyword(s):  
Particle Size ◽  
Robust Control ◽  
Surface Charge ◽  
Particle Number ◽  
Particle Number Density ◽  
Precipitation Polymerization ◽  
Number Density ◽  
Density Control ◽  
Charge Modulation

Many applications of poly(N-isopropylacrylamide) microgels necessitate robust control over particle size.

Effect of Particle Number Density on Wave Dispersion in a Two-Dimensional Yukawa System

2017 ◽  
Vol 34 (7) ◽  
pp. 075203
Author(s):  
Rang-Yue Zhang ◽  
Yan-Hong Liu ◽  
Feng Huang ◽  
Zhao-Yang Chen ◽  
Chun-Yan Li
Keyword(s):  
Particle Number ◽  
Wave Dispersion ◽  
Particle Number Density ◽  
Two Dimensional ◽  
Number Density

scholarly journals Vertical marine snow distribution in the stratified, hypersaline, and anoxic Orca Basin (Gulf of Mexico)

Elem Sci Anth ◽  
2019 ◽  
Vol 7 ◽  
Author(s):  
Arne Diercks ◽  
Kai Ziervogel ◽  
Ryan Sibert ◽  
Samantha B. Joye ◽  
Vernon Asper ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Gulf Of Mexico ◽  
Particle Number ◽  
Sea Surface ◽  
Marine Snow ◽  
Particle Volume ◽  
Total Particle Number ◽  
Total Particle ◽  
Snow Distribution ◽  
Orca Basin

We present a complete description of the depth distribution of marine snow in Orca Basin (Gulf of Mexico), from sea surface through the pycnocline to within 10 m of the seafloor. Orca Basin is an intriguing location for studying marine snow because of its unique geological and hydrographic setting: the deepest ~200 m of the basin are filled with anoxic hypersaline brine. A typical deep ocean profile of marine snow distribution was observed from the sea surface to the pycnocline, namely a surface maximum in total particle number and midwater minimum. However, instead of a nepheloid (particle-rich) layer positioned near the seabed, the nepheloid layer in the Orca Basin was positioned atop the brine. Within the brine, the total particle volume increased by a factor of 2–3 while the total particle number decreased, indicating accumulation and aggregation of material in the brine. From these observations we infer increased residence time and retention of material within the brine, which agrees well with laboratory results showing a 2.2–3.5-fold reduction in settling speed of laboratory-generated marine snow below the seawater-brine interface. Similarly, dissolved organic carbon concentration in the brine correlated positively with measured colored dissolved organic matter (r2 = 0.92, n = 15), with both variables following total particle volume inversely through the pycnocline. These data indicate the release of dissolved organic carbon concomitant with loss in total particle volume and increase in particle numbers at the brine-seawater interface, highlighting the importance of the Orca Basin as a carbon sink.

scholarly journals Urban aerosol size distributions over the Mediterranean city of Barcelona, NE Spain

2012 ◽  
Vol 12 (7) ◽  
pp. 16457-16492 ◽  
Author(s):  
M. Dall'Osto ◽  
D.C.S. Beddows ◽  
J. Pey ◽  
S. Rodriguez ◽  
A. Alastuey ◽  
...  
Keyword(s):  
Particle Number ◽  
Number Concentration ◽  
Aerosol Size Distribution ◽  
Time Variability ◽  
Small Contribution ◽  
Particle Number Concentration ◽  
Size Distributions ◽  
Total Particle Number ◽  
Total Particle ◽  
One Year

Abstract. Differential mobility particle sizer (DMPS) aerosol concentrations (N13–800) were collected over a one-year-period (2004) at an urban background site in Barcelona, North-Eastern Spain. Quantitative contributions to particle number concentrations of the nucleation (33–38%), Aitken (39–49%) and accumulation mode (18–22%) were estimated. We examined the source and time variability of atmospheric aerosol particles by using both K-means clustering and Positive Matrix Factorization (PMF) analysis. Performing clustering analysis on hourly size distributions, nine K-means DMPS clusters were identified and, by directional association, diurnal variation and relationship to meteorological and pollution variables, four typical aerosol size distribution scenarios were identified: traffic (69% of the time), dilution (15% of the time), summer background conditions (4% of the time) and regional pollution (12% of the time). According to the results of PMF, vehicle exhausts are estimated to contribute at least to 62–66% of the total particle number concentration, with a slightly higher proportion distributed towards the nucleation mode (34%) relative to the Aitken mode (28–32%). Photochemically induced nucleation particles make only a small contribution to the total particle number concentration (2–3% of the total), although only particles larger than 13 nm were considered in this study. Overall the combination of the two statistical methods is successful at separating components and quantifying relative contributions to the particle number population.

Simulation of Multi-Phase Glass-Melt Flows in a Glass Melter

2001 ◽  
Author(s):  
S. L. Chang ◽  
C. Q. Zhou ◽  
B. Golchert ◽  
M. Petrick
Keyword(s):  
Heat Transfer ◽  
Molten Glass ◽  
Transfer Rate ◽  
Liquid Glass ◽  
Particle Number ◽  
Particle Number Density ◽  
Number Density ◽  
Melt Flow ◽  
Glass Melter ◽  
Multi Phase

Abstract A typical glass furnace consists of a combustion space and a melter. The intense heat, generated from the combustion of fuel and air/oxygen in the combustion space, is transferred mainly by radiation to the melter where the melt sand and cullet (scrap glass) are melted, creating molten glass. The melter flow is a complex multi-phase flow including solid batches of sand/cullet and molten glass. Proper modeling of the flow patterns of the solid batch and liquid glass is a key to determining the glass quality and furnace efficiency. A multi-phase CFD code has been developed to simulate glass melter flow. It uses an Eulerian approach for both the solid batch and the liquid glass-melt flows. The mass, momentum, and energy conservation equations of the batch flow are used to solve for local batch particle number density, velocity, and temperature. In a similar manner, the conservation equations of mass, momentum, and energy of the glass-melt flow are used to solve for local liquid molten glass pressure, velocity, and temperature. The solid batch is melted on the top by the heat from the combustion space and from below by heat from the glass-melt flow. The heat transfer rate from the combustion space is calculated from a radiation model calculation while the heat transfer rate from the glass-melt flow to the solid batch is calculated from a model based on local particle number density and glass-melt temperature. Energy and mass are balanced between the batch and the glass-melt. Batch coverage is determined from local particle number density and velocity. A commercial-scale glass melter has been simulated at different operating/design conditions.

scholarly journals Diffusion of Particles, Heat and Magnetic Fields in Compressible Turbulent Media

1991 ◽  
Vol 130 ◽  
pp. 71-74
Author(s):  
A.Z. Dolginov ◽  
N.A. Silant’ev
Keyword(s):  
Magnetic Field ◽  
Magnetic Fields ◽  
Vector Fields ◽  
Particle Number ◽  
Particle Number Density ◽  
Turbulent Diffusivity ◽  
Number Density ◽  
Scalar And Vector Fields ◽  
Kinetic Coefficients ◽  
The Magnetic Field

AbstractA new method for the calculation of kinetic coefficients is presented. This method allows us to obtain the distribution of scalar and vector fields (such as the temperature, the admixture particle number density and the magnetic field) in turbulent cosmic media with any value of S = u0т0/R0. The explicit expression for the “turbulent” diffusivity DT is obtained. In some cases DT becomes negative, implying the clustering of the admixture particles in patches (a local increase of the temperature and magnetic fields). The magnetic α-effect is considered for the case S ~ 1.

scholarly journals Long-Term Characterization of Submicron Atmospheric Particles in an Urban Background Site in Southern Italy

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 334 ◽  
Author(s):  
Adelaide Dinoi ◽  
Marianna Conte ◽  
Fabio M. Grasso ◽  
Daniele Contini
Keyword(s):  
Particle Number ◽  
Meteorological Parameters ◽  
Particle Diameter ◽  
Number Concentration ◽  
Total Particle Number ◽  
Total Particle ◽  
Late Evening ◽  
20 Nm

Continuous measurements of particle number size distributions in the size range from 10 nm to 800 nm were performed from 2015 to 2019 at the ECO Environmental-Climate Observatory of Lecce (Global Atmosphere Watch Programme/Aerosol, Clouds and Trace Gases Research Infrastructure (GAW/ACTRIS) regional station). The main objectives of this work were to investigate the daily, weekly and seasonal trends of particle number concentrations and their dependence on meteorological parameters gathering information on potential sources. The highest total number concentrations were observed during autumn-winter with average values nearly twice as high as in summer. More than 52% of total particle number concentration consisted of Aitken mode (20 nm < particle diameter (Dp) < 100 nm) particles followed by accumulation (100 nm < Dp < 800 nm) and nucleation (10 nm < Dp < 20 nm) modes representing, respectively, 27% and 21% of particles. The total number concentration was usually significantly higher during workdays than during weekends/holidays in all years, showing a trend likely correlated with local traffic activities. The number concentration of each particle mode showed a characteristic daily variation that was different in cold and warm seasons. The highest concentrations of the Aitken and accumulation particle mode were observed in the morning and the late evening, during typical rush hour traffic times, highlighting that the two-particle size ranges are related, although there was significant variation in the number concentrations. The peak in the number concentrations of the nucleation mode observed in the midday of spring and summer can be attributed to the intensive formation of new particles from gaseous precursors. Based on Pearson coefficients between particle number concentrations and meteorological parameters, temperature, and wind speed had significant negative relationships with the Aitken and accumulation particle number concentrations, whereas relative humidity was positively correlated. No significant correlations were found for the nucleation particle number concentrations.

Sign in / Sign up

Export Citation Format

Share Document