scholarly journals The Oklahoma Dispersion Model: Using the Gaussian Plume Model as an Operational Management Tool for Determining Near-Surface Dispersion Conditions across Oklahoma

2008 ◽  
Vol 47 (2) ◽  
pp. 462-474 ◽  
Author(s):  
J. D. Carlson ◽  
Derek S. Arndt
Keyword(s):  
Environmental Protection Agency ◽  
Prescribed Burning ◽  
Dispersion Model ◽  
Management Tool ◽  
Weather Data ◽  
Gaussian Plume Model ◽  
Near Surface ◽  
Plume Model ◽  
Oklahoma Mesonet ◽  
Gaussian Plume

Abstract The Oklahoma Dispersion Model (ODM) represents a current innovative application of the classic Gaussian plume model in an operational setting. Utilizing a statewide mesoscale automated weather station network (the Oklahoma Mesonet) for current weather conditions and 60-h gridded Nested Grid Model (NGM) model output statistics (MOS) forecasts for future conditions, the ODM is an Internet-based management tool that can be used to qualitatively assess current and future atmospheric dispersion conditions across Oklahoma for near-surface releases of gases and small particulates. The ODM is designed to qualitatively assess concentrations at ground level near the plume centerline at downwind distances of up to 4000 m. The Gaussian plume model is used in conjunction with rural Briggs sigma-y and sigma-z coefficients to estimate horizontal and vertical dispersion. Pasquill stability class is calculated in two ways: for current conditions, Oklahoma Mesonet weather data are used in conjunction with algorithms recommended by the Environmental Protection Agency; for forecast conditions, the Turner method is used. A method is employed that breaks the atmosphere into six dispersion categories, ranging from excellent to very poor. The ODM generates both graphical and text output. Statewide colored maps showing current conditions for dispersion (dilution of plume) and transport (direction of plume movement) are generated every 15 and 5 min, respectively. Similar maps for future conditions are generated every 12 h using gridded 60-h NGM MOS forecasts. In addition to graphical output, tabular output for future conditions at specific MOS locations is available. The ODM has been used as a management tool in the agriculture and natural resources arenas in conjunction with prescribed burning (smoke), pesticide application, and odors associated with animal agriculture.

Optimization of Stack Emission Parameters Using Gaussian Plume Model

2012 ◽  
Vol 58 (2) ◽  
Author(s):  
Zairi Ali ◽  
Ubaidullah D. ◽  
M. N. Zahid ◽  
Kahar Osman
Keyword(s):  
Dispersion Model ◽  
Ground Level ◽  
Ambient Air ◽  
Quality Standard ◽  
Ease Of Use ◽  
Manufacturing Plant ◽  
Data Sampling ◽  
Gaussian Plume Model ◽  
Plume Model ◽  
Gaussian Plume

Numerical simulation is an economical way to control air pollution because of its consistency and ease of use compared to traditional data sampling method. The objective of this research is to develop a practical numerical algorithm to predict the dispersion of pollutant particles around a specific source of emission. The algorithm is tested with a rubber wood manufacturing plant. Gaussian-plume model were used as air dispersion model due to its simplicity and generic application. Results of this study show the concentrations of the pollutant particles on ground level reached approximately 90μg/m3, compared with other software. This value surpasses the limit of 50μg/m3 stipulated by the National Ambient Air Quality Standard (NAAQS) and Recommended Malaysian Guidelines (RMG) set by Environment Department of Malaysia. The manufacturing plant is advised to make a few changes with its emission parameters and adequate values are suggested. In general, the developed algorithm is proven to be able to predict particles distribution around emitted source with acceptable accuracy.

The Simulation of Release Consequence with a Modified Gaussian Plume Model

2016 ◽  
pp. 445-454
Author(s):  
Hongya Zhu ◽  
Xuanya Liu ◽  
Qingsong Wang ◽  
Jinhua Sun
Keyword(s):  
Gaussian Plume Model ◽  
Plume Model ◽  
Gaussian Plume

scholarly journals Estimation of Radioactivity Release Activity Using Non-Linear Kalman Filter-Based Estimation Techniques

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3985
Author(s):  
Victor M. Becerra ◽  
Vineet Vajpayee ◽  
Nils Bausch ◽  
T.V. Santhosh ◽  
Gopika Vinod ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Dose Rate ◽  
Gaussian Plume Model ◽  
Estimation Techniques ◽  
Plume Model ◽  
Dose Rates ◽  
Statistical Measures ◽  
Cubature Kalman Filter ◽  
Non Linear ◽  
Gaussian Plume

The estimation of radioactivity release following an accident in a nuclear power plant is crucial due to its short and long-term impacts on the surrounding population and the environment. In the case of any accidental release, the activity needs to be estimated quickly and reliably to effectively plan a rapid emergency response and design an appropriate evacuation strategy. The accurate prediction of incurred dose rate during normal or accident scenario is another important aspect. In this article, three different non-linear estimation techniques, extended Kalman filter, unscented Kalman filter, and cubature Kalman filter are proposed in order to estimate release activity and to improve the prediction of dose rates. Radionuclide release rate, average wind speed, and height of release are estimated using the dose rate monitors data collected in proximity of the release point. Further, the estimates are employed to improve the prediction of dose rates. The atmospheric dispersion phenomenon of radioactivity release is modelled using the Gaussian plume model. The Gaussian plume model is then employed for the calculation of dose rates. A variety of atmospheric and accident related scenarios for single source and multiple sources are studied in order to assess the efficacy of the proposed filters. Statistical measures have been used in order to validate the performance of the proposed approaches.

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