Particle removal mass concentration

The major purpose of ambient particulate sampling is to obtain mass concentration and chemical composition data, preferably as a function of particle diameter. This information is valuable for a variety of problems effects on human health, identification of particulate matter sources, understanding of atmospheric haze, and particle removal processes. 

Mass concentration units for ambient measurements are mass (/xg) per unit volume (m ). Size classification involves the use of specially designed inlet configurations, e.g., PMjq sampling. To determine mass concentration, all the particles are removed from a known volume of air and their total mass is measured. This removal is accomplished by two techniques, filtration and impaction, described in Chapter 13. Mass measurements are made by pre-and postweighing of filters or impaction surfaces. To account for the absorption of water vapor, the filters are generally equilibrated at standard conditions T = 20°C and 50% relative humidity). 

Fig. 7-12 Schematic of an atmospheric aerosol size distribution. This shows the three mass modes, the main sources of mass for each mode, and the principal processes involved in inserting mass into and removing mass from each mode (m = mass concentration. Dp = particle diameter). (Reproduced with permission from K. T. Whitby and G. M. Sverdrup (1983). California aerosols their physical and chemical characteristics. In "The Character and Origin of Smog Aerosols" (G. M. Hidy, P. K. Mueller, D. Grosjean, B. R. Appel, and J. J. Wesolowski, eds), p. 483, John Wiley, New York.)...

Ash particles produced in coal combustion are controlled by passing the flue gases through electrostatic precipitators. Since most of the mass of particulate matter is removed by these devices, ash received relatively little attention as an air pollutant until it was shown that the concentrations of many toxic species in the ash particles increase as particle size decreases. Particle removal techniques become less efiective as particle size decreases to the 0.1-0.5 pm range, so that particles in this size range that escape contain disproportionately high concentrations of toxic substances. 

Removal of colloidal calcium phosphate (CCP) results in disintegration of the micelles into particles of mass 3 x 106 Da. The properties of the CCP-free system are very different from those of the normal milk system, e.g. it is sensitive to and precipitated by relatively low concentrations of Ca2 +, it is more stable to high temperatures, e.g. 140°C, and is not coagulable by rennets. Many of these properties can be restored, at least partially, by increased concentrations of calcium. 

Let us assume that turbulence in the tank keeps the suspended particle concentration homogeneous, but that at the bottom of the tank the particles can sink through some screen below which no water currents exist (Fig. 23.2 b). In the absence of any external particle fluxes or in situ production/removal of particles, the mass balance equation for suspended particle mass is given by equating the rate of change of particle mass in the water volume V with time with the rate of loss due to settling ... 

The results in Figure 4 yield a 50 50 ratio by mass when a smoothed approximation of P is used where the smoothing is performed in an attempt to remove particle refractive index as a necessary parameter. However, a better calculation, using the correct refractive index (1.545) of this particular rubber and the full Mie theory for spheres, yields a mass concentration ratio of 69 31 for the 1010nm 270nm sizes which is quite close to the 70 30 ratio of this blended sample. 

The mechanism of particle incorporation is treated extensively in the next section, but a generalized mechanism is given here to better comprehend the effects of the process parameters. Particle incorporation in a metal matrix is a two step process, involving particle mass transfer from the bulk of the suspension to the electrode surface followed by a particle-electrode interaction leading to particle incorporation. It can easily be understood that electrolyte agitation, viscosity, particle bath concentration, particle density etc affect particle mass transfer. The particle-electrode interaction depends on the particle surface properties, which are determined by the particle type and bath composition, pH etc., and the metal surface composition, which depends on the electroplating process parameters, like pH, current density and bath constituents. The particle-electrode interaction is in competition with particle removal from the electrode surface by the suspension hydrodynamics. 

In theory, the removal of fine particles by collision processes results in chemical concentrations in the air mass following an exponential decay law. In actual clouds, both collision and nucleation may contribute to particle removal, and their combined effects often are lumped into a single scavenging coefficient, A [T 3] ... 

The aerosol volume fraction. , is closely related to the mass concentration, which is usually determined by nitration. We assume the filter is ideal, removing all particles larger than single molecules. Then... 

Physically, relation [5.20] means that the mass concentration of aerosol particles below the cloud base decreases exponentially due to wet removal. 

The boundaries of the process selection regions are guidelines only they can be used for a preliminary assessment of technically feasible separation processes and pretreatment requirements (using particle size data). Lake waters typically contain low mass concentrations (< 10 mg/L) of particulates with number counts of 10 to 10 mL S and Zxv between 5 and 20 /xm (14,16,18). Thus direct filtration may satisfy particulate removal requirements. However, particulate concentrations in... 

The Raw Water Supply. The concentration of solid material was assumed to be 50 ppm by volume for the standard case. Particle density was assumed to be 2.65, representative of inorganic materials the corresponding mass concentration is about 132 mg/L. A particle size range from 0.3 to 30 /x.m was selected. There are few data to provide a base for this estimate. This range reflects a consideration that large particles will be removed effectively from the water source by natural processes, and that submicron particles can be present in surface water supplies even if not detected quantitatively by routine analysis for suspended solids. The particle size distribution throughout this size range was assumed to be described by the power-law distribution function (Equation 9) with = 4. This is consistent with the available data. 

Figure SB illustrates that head loss development is rapid for small particles but slow for large particles, since smaller particles contribute more surface area for the same mass concentration removed. Removal eflBciency (Figure 8A) is a more complex function of particle size. Submicron particles are removed eflFectively by Brownian diffusion even on a clean bed (t = 0), and large particles are removed effectively by settling and interception. For particles of about 1 /x.m in size, removal is least eflGcient (although still over 70% at f = 0 for the conditions considered), and a ripening period of about 1 hr is necessary to achieve 90% removal. These concepts are useful when considering the results and discussion that follow.

A review of the wastewater treatment literature suggests a number of research needs. Efforts to characterize alumina, ceria, and silica particles in both waste materials and natural water systems face difficult metrology challenges. There is a need for vahdated methodologies that can discriminate quantitatively between individual types of nanomaterials and evaluate concentration by size, number count, and mass concentration within real environmental matrices. The few published evaluations of alumina, ceria, and silica nanoparticle removal in wastewater treatment processes have primarily addressed removal in municipal-type biological wastewater treatment processes whereas relatively little information is available regarding alumina, ceria, and silica nanoparticle removal in the types of physicochemical treatment processes that are often used by fabs to pretreat wastewaters prior to discharge. 

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