A particle grid air quality modeling approach that can incorporate chemistry is proposed as an alternative to the conventional partial differential equation (PDE) grid air quality modeling approach. In this approach, each particle is tagged with different species masses and particles in the same grid participate in chemical reactions. The approach is flexible and removes the advection and point source problems encountered in the PDE approach. For a typical grid size of 5 km × 5 km × 50 m used in the lowest layer of an urban air quality model, use of 2000–3000 particles of unequal masses per grid cell will yield a highly accurate grid‐averaged instantaneous concentration field that undergoes eddy diffusion for a period of about 1 day. Use of an hourly averaged concentration reduces the demand of particle per cell to about 500. Increasing the grid size also reduces the demand on the number of particles per cell. For the choice of our Lagrangian integral time scales, the time step must be small (10 s) for vertical dispersion simulation but can be large (200 s) for horizontal dispersion simulation. To reduce computation time, a time‐splitting scheme is, proposed to simulate the horizontal and vertical dispersion simulations in an alternating sequence. The present study also shows that the oft‐used second‐order‐accurate finite difference scheme for solving the diffusion equation tends to overpredict the peak of a sharply peaked concentration.
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