Environmental Engineering Reference
In-Depth Information
8.6 A Mass Consistency Method for Air Quality
Modeling over Complex Terrain
Yongtao Hu, Aika Yano, and M. Talat Odman
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta,
GA 30332-0512
1. Introduction
Mass inconsistency in air quality models (AQMs) can be severe particularly over
complex terrain. Inconsistencies may originate from meteorological models or
may be introduced by using AQMs with grids, time steps, or finite difference forms
different from those of the driving meteorological model. Without correction,
inconsistencies may lead to instabilities or produce unrealistic air quality fields. In
the past, we developed a vertical winds adjustment method to deal with the mass
inconsistency [1]. That method we refer to as Method 1 here was strictly mass
conservative but required the use of the first-order accurate upwind scheme for
vertical advection. In an application to Central California, where the complexity of
the terrain is further emphasized by fine grid resolution (4 km), Method 1 resulted
in large trajectory deviations and high ozone concentrations near the surface
especially at night. Here we developed two new mass consistency methods for air
quality modeling over complex terrain.
2. Methodology
First, we replace the upwind scheme with the higher-order accurate Bott's scheme
[2] for vertical advection (Method 2). The non-linear flux limiters in this scheme
necessitate an iterative solution for vertical winds adjustment. Since the iterative
solution is assumed to have converged when a small tolerance is met, it is not
exact and may introduce very small mass conservation errors. Second, to deal with
large trajectory deviations resulting from the use of adjusted vertical winds instead
of the winds generated by meteorological models, we developed a hybrid method.
This method (Method 3) switches from vertical winds adjustment to concentration
renormalization, which is not mass conservative, whenever the required adjust-
ments to wind speed or direction exceed typical uncertainties associated with these
parameters. Method 3 provides a compromise between trajectory deviations and
mass conservation errors.
