Abstract:The modeling of atmospheric dispersion is the mathematical simulation of how pollutants are dispersed in the atmosphere. Based on the advection-diffusion equations describing the dispersion of pollutants, dispersal models are widely used to give a spatial variability of pollutants emitted mainly by agricultural activities and industrial facilities. In this context, an analytical model is presented to study the dispersion of pollutants in the atmospheric boundary layer. The solution procedure is based on dividi… Show more
“…The calculated values are mostly within the range of acceptable model performance for both formulations of the vertical eddy diffusivity. Furthermore, Table 1 indicates that similar results are obtained compared to other analytical procedures, previously published in the literature [9,12,15,19].…”
Section: Validation and Experimental Datasupporting
confidence: 77%
“…The calculated values are mostly within the range of acceptable model performance for both formulations of the vertical eddy diffusivity. Furthermore, Table 1 indicates that similar results are obtained compared to other analytical procedures, previously published in the literature [9, 12, 15, 19]. Figure 1 Scatter plot of observed and predicted crosswind-integrated concentrations of the Copenhagen (top panel) and the Prairie Grass experiments (bottom panel).…”
Section: Validation and Experimental Datasupporting
We develop a new analytical solution of a three-dimensional atmospheric pollutant dispersion. The main idea is to subdivide vertically the planetary boundary layer into sub-layers, where the wind speed and eddy diffusivity assume average values for each sub-layer. Basically, the model is assessed and validated using data obtained from the Copenhagen diffusion and Prairie Grass experiments. Our findings show that there is a good agreement between the predicted and observed crosswind-integrated concentrations. Moreover, the calculated statistical indices are within the range of acceptable model performance.
“…The calculated values are mostly within the range of acceptable model performance for both formulations of the vertical eddy diffusivity. Furthermore, Table 1 indicates that similar results are obtained compared to other analytical procedures, previously published in the literature [9,12,15,19].…”
Section: Validation and Experimental Datasupporting
confidence: 77%
“…The calculated values are mostly within the range of acceptable model performance for both formulations of the vertical eddy diffusivity. Furthermore, Table 1 indicates that similar results are obtained compared to other analytical procedures, previously published in the literature [9, 12, 15, 19]. Figure 1 Scatter plot of observed and predicted crosswind-integrated concentrations of the Copenhagen (top panel) and the Prairie Grass experiments (bottom panel).…”
Section: Validation and Experimental Datasupporting
We develop a new analytical solution of a three-dimensional atmospheric pollutant dispersion. The main idea is to subdivide vertically the planetary boundary layer into sub-layers, where the wind speed and eddy diffusivity assume average values for each sub-layer. Basically, the model is assessed and validated using data obtained from the Copenhagen diffusion and Prairie Grass experiments. Our findings show that there is a good agreement between the predicted and observed crosswind-integrated concentrations. Moreover, the calculated statistical indices are within the range of acceptable model performance.
Modeling pollutant transport in heterogeneous media is an important task of hydrology. Pollutant transport in a non-homogeneous environment typically exhibits non-local transport dynamics, whose efficient characterization requires a parsimonious model with the non-local feature. This study encapsulates the non-local transport characteristic of pollutants into the peridynamic differential operator (PDDO) and develops a PDDO-based model for quantifying the observed pollutant non-local transport behavior. The simulation results show that the proposed model can describe pollutant non-local transport behavior in various heterogeneous media. The non-local nature of pollutant transport can be adjusted by pre-defined weight function w(|ξ|) and horizon Hx. Applications show that the PDDO-based model can better capture pollutant non-local transport behavior than the classical advection–diffusion equation (ADE) model, especially for quantifying the tail of the experimental data late. Analyses further reveal that the PDDO-based model can characterize both normal (Fickian) and anomalous (Lévy) diffusion regimes.
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