Distance education-sources and control of air pollution

Heinsohn, Robert Jennings

doi:10.1109/fie.1997.644899

Cited by 15 publications

(23 citation statements)

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“…The ground level of pollutant concentration is namely a continuous function along x and y and its distribution has an asymmetric bell-shape with a single maximum value. Such a maximum exists, since at locations to the stack the plume is still overhead and the ground-level concentration is zero, while at great distance from the stack the concentration approaches zero, as the plume becomes diluted with ambient air (see also Heinsohn and Kabel, 1999). Secondly, with a higher H the maximum concentration takes place farther from the stack along x and its value gets lower compared to the case with a lower one.…”

Section: Market Area Model With One Pollutermentioning

confidence: 97%

“…Although a clear-cut classification can hardly be made, dispersion in the vertical direction appears to be more distinctively affected by the buoyant turbulence caused by different atmospheric conditions (day or night, heat flux, thermal structure, etc. ), while dispersion in the horizontal plane is likely to be more significantly determined by molecular and eddy diffusion triggered by the prevailing wind (Csanady, 1972;Berljand, 1982;Baumbach, 1994;Heinsohn and Kabel, 1999;Koop and Tole, 2004). In the following the x-axis will always be oriented in the direction of wind, the z-axis is vertically upward, and the y-axis is transverse to the wind (i.e.…”

Section: Major Characteristics Of Gaussian Plume Modelmentioning

confidence: 99%

“…The greater the downwind distance x from the stack, the greater the vertical dispersion to the direction z and the lower the concentration (Turner, 1994). As the case for σ y we assume σ z = αx β (Zannetti, 1990;Turner, 1994;Heinsohn and Kabel, 1999). The terms N(H, σ 2 z )(z) and N(-H, σ 2 z )(z) determine the symmetrical distribution of pollutants in the z-direction.…”

Section: Major Characteristics Of Gaussian Plume Modelmentioning

confidence: 99%

“…Based on the empirically estimated Pasquill-Gifford horizontal dispersion parameters we asaerodynamic down-wash, causing higher concentrations in their immediate vicinity. sume σ y = ax b (Turner, 1994;Heinsohn and Kabel, 1999). The term N(0, σ 2 y )(y) determines the symmetrical distribution of pollutants in the y-direction.…”

Section: Major Characteristics Of Gaussian Plume Modelmentioning

confidence: 99%

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Shadow Market Area for Air Pollutants

Meintrup

Nam

2009

Environ Plann B Plann Des

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may AbstractThis study identifies the shadow market area of air pollutants based on the Gaussian plume model. Since pollutants are dispersed by wind, transport costs are irrelevant in its formation. Pollutant distribution on the ground level has an asymmetric bell-shape in the wind direction. Apart from the linear functions, the exponential and quadratic shadow price functions are considered for the compensation of health hazard of consumers, when the strict liability in the framework of Coase theorem applies. The shadow market area for pollutants is shell-shaped. This specific characteristic has an implication for market boundaries between polluters and their location decisions.

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Section: Market Area Model With One Pollutermentioning

confidence: 97%

Section: Major Characteristics Of Gaussian Plume Modelmentioning

confidence: 99%

Section: Major Characteristics Of Gaussian Plume Modelmentioning

confidence: 99%

Section: Major Characteristics Of Gaussian Plume Modelmentioning

confidence: 99%

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Shadow Market Area for Air Pollutants

Meintrup

Nam

2009

Environ Plann B Plann Des

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“…In deriving the model certain simplifying assumptions were made. Natural extensions of the model arise through relaxing some of these assumptions: for instance, a height dependent wind velocity could be included ( [12], p386, p413), or a height dependent diffusivity ( [13], p593) and, rather than using a point source, a more realistic term for the particle concentration at the chimney opening could be added.…”

Section: Discussionmentioning

confidence: 99%

Diffusion and convection of gaseous and fine particulate from a chimney

MacKay¹,

McKee²,

Mulholland³

2006

IMA Journal of Applied Mathematics

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Particle dispersion from a high chimney is considered and an expression for the subsequent concentration of the particulate deposited on the ground is derived. We consider the general case wherein the effects of both diffusion and convection on the steady state ground concentration of particulate are incorporated. Two key parameters emerge from this analysis: α, the ratio of diffusion to convection, and λ, the nondimensionalised surface mass transfer rate. We also solve the inverse problem of recovering these two parameters given the boundary concentration profile and provide an estimate of the concentration flux above the chimney stack.

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A MATLAB-based modeling and simulation program for dispersion of multipollutants from an industrial stack for educational use in a course on air pollution control

Fatehifar

Elkamel

Mohebbi

2006

Comput. Appl. Eng. Educ.

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In this article, a MATLAB program for a three-dimensional simulation of multipollutants (CO, NO x , SO 2 , and TH) dispersion from an industrial stack using a Multiple Cell Model is presented. The program verification was conducted by checking the simulation results against experimental data and Gaussian Model and better agreements were obtained in comparison with the Gaussian model. The effects of meteorological and stack parameters on dispersion of pollutants like, wind velocity, ambient air temperature, atmospheric stability, exit temperature, velocity, concentration, and stack height can be easily studied using the program. Several illustrations for reducing maximum ground level concentrations using the program are given. The program can simulate all industrial stacks and only needs meteorological data and stack parameters. The outputs from the program are presented in graphical form. The program was designed to be user friendly and computationally efficient through

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Distance education-sources and control of air pollution

Cited by 15 publications

References 0 publications

Shadow Market Area for Air Pollutants

Shadow Market Area for Air Pollutants

Diffusion and convection of gaseous and fine particulate from a chimney

A MATLAB-based modeling and simulation program for dispersion of multipollutants from an industrial stack for educational use in a course on air pollution control

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