Dispersion Coefficients for Gaussian Puff Models

• Published in: Boundary-layer meteorology Vol. 139; no. 3; pp. 487 - 500
• Main Authors: Cao, Xiaoying, Roy, Gilles, Hurley, William J., Andrews, William S.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.06.2011; Springer; Springer Nature B.V
• Subjects: Analysis; Atmospheric Protection/Air Quality Control/Air Pollution; Atmospheric Sciences; Convection, turbulence, diffusion. Boundary layer structure and dynamics; Correlation coefficient; Dispersion; Earth and Environmental Science; Earth Sciences; Earth, ocean, space; Exact sciences and technology; External geophysics; Field tests; Hostages; Meteorology; Neural networks; Normal distribution; Toy industry; Puff dispersion coefficients; Artificial neural network; Multi-variable regression; Gaussian puff model; models; Atmospheric condition; Non linear regression; Linear regression; neural networks; Gaussian distribution; Dispersion coefficient; Multiple linear regression; Multiple regression; Mean square error; transient phenomena; correlation coefficient; Power law; stability; Concentration distribution

The Gaussian distribution is a good approximation for transient (instantaneously released) puff concentration distributions within a short period of time after release. Artificial neural network (ANN) models for puff dispersion coefficients were developed, based on observations from field experiment...