Study the effect of different shapes of plume rise on Gaussian plume models and its maximum in unstable conditions
<p>Exposure to radioactive pollutants such as Iodine-135 I135 seriously threatens public health and environmental balance. Monitoring and managing these pollutants require expensive economic equipment that is not suitable for low-income countries such as Egypt. Therefore, trying to derive a ma...
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| Main Authors: | , , , |
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| Format: | Book |
| Published: |
Open Journal of Analytical and Bioanalytical Chemistry - Peertechz Publications,
2023-05-30.
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| Online Access: | Connect to this object online. |
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| Summary: | <p>Exposure to radioactive pollutants such as Iodine-135 I135 seriously threatens public health and environmental balance. Monitoring and managing these pollutants require expensive economic equipment that is not suitable for low-income countries such as Egypt. Therefore, trying to derive a mathematical model that estimates the concentrations of these radioactive pollutants with high accuracy and a low relative error coefficient compared to the actually measured values is very important. Therefore a mathematical Gaussian model was received to estimate the concentrations of I135 emitted from the research nuclear reactor in the Inshas region in Egypt using different shapes of plume rise in unstable conditions.</p><p>A comparison between the derived model and its maximum values with observed concentrations data measuring on Egyptian Atomic Energy Authority for I135 in unstable conditions has been found. The derived model may be applied to estimate and predict the emissions of any radioactive pollutant for any similar area and similar type of used reactor, which provides high-precision technology with zero economic cost.</p><p>The statistical technique shows that the entire Gaussian model and its maximum inside a factor of two with observed concentration data achieved 98%. In addition, the statistics show that all the Gaussian plume models and their maximum have a correlation coefficient of about 0.95%. Also, the normalized mean square error. And the fraction bias. are near-zero values in all Gaussian models and their maximum. </p> |
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| DOI: | 10.17352/ojabc.000029 |