A Global Atmospheric Contaminant Transport Model Based on 3D Advection-Diffusion Equation

Abstract

To study the global air pollution concentration and evaluate the impact of regional pollution on whole earth, a global atmospheric contaminant transport model is established based on 3D advection-diffusion equation, which captures the processes of advection by wind and turbulent diffusion during atmospheric dispersion. The Eulerian finite difference method is employed for numerical solution of the proposed model. Then one-year aerosol transport on global scale is simulated using the proposed model, and the simulation results are verified against the real remote sensing data of NASA. It turns out that the simulated values of aerosol concentration are strongly correlated with the real values and the correlation coefficient is above 0.8 for sample point. Furthermore, the proposed model is used for predicting the next-year global atmospheric contaminant concentration by simulation. Compared with the related models on atmospheric contaminant transport, we propose a model in this paper with three appealing features: three-dimensional (3D), global scale, and targeted for aerosol transport simulation. In this paper, we present the global 3D atmospheric contaminant transport model and simulate the transport of aerosol around the world. This proposed model uses 3D space coordinates which can fully address the spread of pollutants in space. In this mode, the wind speed and turbulent diffusivity are considered. Furthermore, a comprehensive term is introduced into the model to take into account the factors of emission source, chemical conversion, dry deposition and wet scavenging. The parameters in the model are variables changing over time and space. For simulation purposes, the horizontal resolution of the model is 45 oo × , and the vertical direction is divided into 11 layers. We first simulate the aerosol diffusion in the world in one year. It turns out that the simulated global aerosol concentration distribution is consistent with the real aerosol concentration distribution. Actually, the simulated value has strong correlation with the real data, and the correlation coefficient is above 0.8 for sample point. We also predict the global aerosol concentration over next year. Hence, the proposed model in this paper can be a useful tool for predicting the global aerosol concentration. If we combine this model with more precise chemical patterns, the accuracy of the model can be improved and the proposed model can be further extended to study other atmospheric contaminants. The rest of paper is organized as follows. Section II introduces the proposed global atmospheric contaminant transport model based on 3D advection-diffusion equation. Numerical solution of the proposed model is given in Section III. Section IV presents and discusses the simulation results. Finally, conclusions are drawn in Section V.