Based on the statistical analysis of API （air pollution index）, the study improves the layout of the site in the downtown of Nanjing and the surroundings. Through selecting more relevant factors to establish the API...Based on the statistical analysis of API （air pollution index）, the study improves the layout of the site in the downtown of Nanjing and the surroundings. Through selecting more relevant factors to establish the API regression equation and making the inversion of API data in simulated sites, the interpolation values of API in both actual sites and simulated sites have been calculated. The methods include IDW （inverse distance weighting） interpolation, Spline interpolation, and Kriging interpolation Spherical model, Exponential model and the Gaussian model. Meanwhile, through the cross-validation to test the results of interpolation in different models or parameters, the study also obtains the best fit of the interpolation model or parameters. In addition, IDW p = 3, fitting coefficient of 0.644; Spline interpolation w = 1, the fitting coefficient of 0.972; Kriging interpolation, Gaussian, fitting coefficient of 0.684. The study indicates that in best fitting model, the parameters after in increasing the simulated site are not in line with the ones previous. The result shows that it is best to test different data separately and select the appropriate interpolation model, but not blindly use the same spatial interpolation. After the increasing of the stimulated site, the API estimated results in three interpolation methods are consistent with the spatial distribution trend. In the aspect of calculating the range, the improvement close the results between 3 interpolation methods and increase of the stimulated sites, and the values of Spline interpolation and Kriging interpolation is closer.展开更多
In this paper, a nonlinear mathematical model is proposed and analyzed to study the role of dissolved oxygen （DO）-dependent bacteria on biodegradation of one or two organic pollutant（s） in a water body. In the cas...In this paper, a nonlinear mathematical model is proposed and analyzed to study the role of dissolved oxygen （DO）-dependent bacteria on biodegradation of one or two organic pollutant（s） in a water body. In the case of two organic pollutant（s）, it is assumed that the one is fast degrading and the other is slow degrading and both are discharged into the water body from outside with constant rates. The density of bacteria is assumed to follow logistic model and its growth increases due to biodegradation of one or two organic pollutant（s） as well as with the increase in the concentration of DO. The model is analyzed using the stability theory of differential equations and by simulation. The model analysis shows that the concentration（s） of one or both organic pollutant（s） decrease（s） as the density of bacteria increases. It is noted that for very large density of bacteria, the organic pollutant（s） may be removed ahnost completely from the water body. It is found that simulation analysis confirms the analytical results. The results obtained in this paper are in line with the experimental observations published in literature.展开更多
文摘Based on the statistical analysis of API （air pollution index）, the study improves the layout of the site in the downtown of Nanjing and the surroundings. Through selecting more relevant factors to establish the API regression equation and making the inversion of API data in simulated sites, the interpolation values of API in both actual sites and simulated sites have been calculated. The methods include IDW （inverse distance weighting） interpolation, Spline interpolation, and Kriging interpolation Spherical model, Exponential model and the Gaussian model. Meanwhile, through the cross-validation to test the results of interpolation in different models or parameters, the study also obtains the best fit of the interpolation model or parameters. In addition, IDW p = 3, fitting coefficient of 0.644; Spline interpolation w = 1, the fitting coefficient of 0.972; Kriging interpolation, Gaussian, fitting coefficient of 0.684. The study indicates that in best fitting model, the parameters after in increasing the simulated site are not in line with the ones previous. The result shows that it is best to test different data separately and select the appropriate interpolation model, but not blindly use the same spatial interpolation. After the increasing of the stimulated site, the API estimated results in three interpolation methods are consistent with the spatial distribution trend. In the aspect of calculating the range, the improvement close the results between 3 interpolation methods and increase of the stimulated sites, and the values of Spline interpolation and Kriging interpolation is closer.
文摘In this paper, a nonlinear mathematical model is proposed and analyzed to study the role of dissolved oxygen （DO）-dependent bacteria on biodegradation of one or two organic pollutant（s） in a water body. In the case of two organic pollutant（s）, it is assumed that the one is fast degrading and the other is slow degrading and both are discharged into the water body from outside with constant rates. The density of bacteria is assumed to follow logistic model and its growth increases due to biodegradation of one or two organic pollutant（s） as well as with the increase in the concentration of DO. The model is analyzed using the stability theory of differential equations and by simulation. The model analysis shows that the concentration（s） of one or both organic pollutant（s） decrease（s） as the density of bacteria increases. It is noted that for very large density of bacteria, the organic pollutant（s） may be removed ahnost completely from the water body. It is found that simulation analysis confirms the analytical results. The results obtained in this paper are in line with the experimental observations published in literature.
