A Particle-Grid Air Quality Modeling Approach

Abstract

A particle-grid air quality modeling approach that can incorporate chemistry is proposed as an alternative to the conventional PDE-grid air quality modeling. The particle trajectory model can accurately describe advection of air pollutants without introducing artificial diffusion, generating negative concentrations or distorting the concentration distributions. It also accurately describes the dispersion of emissions from point sources and is capable of retaining subgrid-scale information. Inhomogeneous turbulence necessitates use of a small timestep, say, 10 s to describe vertical dispersion of particles in convective conditions. A timestep as large as 200 s can be used to simulate horizontal dispersion. A time-splitting scheme can be used to couple the horizontal and vertical dispersion in a 3D simulation, and about 2000–3000 particles per cell of size 5 km × 5 km × 50 m is sufficient to yield a highly accurate simulation of 3D dispersion. Use of an hourly-averaged concentration further reduces the demand of particle per cell to 500.

The particle-grid method is applied to a system of ten reacting chemical species in a two-dimensioned rotating flow field with and without diffusion. A chemistry grid within which reactions are assumed to take place can be decoupled from the grid describing the flow field. Two types of chemistry grids are used to describe the chemical reactions: a fixed coarse grid and a moving (the advection case) or stationary (the advection plus diffusion case) fine grid. Two particle-number densities are also used: 256 and 576 particles per fixed coarse grid cell. The species mass redistributed back to the particle after each reaction step is assumed to be proportioned to the species mass in the particle before the reaction. The simulation results are very accurate, especially in the advection-chemistry case. Accuracy improves with the use of a fine grid. A higher particle-number density also reduces the concentration fluctuation in the cases involving diffusion.

We also show by examples that chemistry can lead to significantly different results from numerical methods for the diffusion equation (let alone the advection equation) which otherwise yield almost identical solutions. The absence of this difficulty in the particle-grid method further enhances its attractiveness.