Documentation of the Evaluation of CALPUFF and Other Long ...

In this study we expand the LRT model performance philosophy to include spatial,
correlation/scatter, bias, error and frequency distribution performance metrics.
In their regulatory use within the United States, LRT models are used to predict impacts of
criteria pollutants for national ambient air quality standards (NAAQS) and Prevention of
Significant Deterioration of Air Quality (PSD) Class I increments. Additionally, Federal Land
Management Agencies rely upon the same LRT models in the PSD program for estimates of
chemical transformation and removal to assess impacts on air quality related values (AQRV’s)
such as visibility and acid deposition. The chemistry of aerosol formation is highly dependent
upon the spatial and temporal variability of meteorology (e.g., relative humidity and
temperature) and precursors (e.g., ammonia).
Recognizing the need for developing an evaluation approach that reflects the intended
regulatory uses of LRT models, the model performance evaluation approach of Mosca et al.,
(1998) and Stohl et al., (1998) used in the ATMES‐II study and recommended by DATEM
(Draxler, Heffter and Rolph, 2002) was adopted for this study.
We have also included elements of the plume fitting evaluation approach of Irwin (1997) for
comparison with the results from the original 1998 tracer evaluation study (EPA, 1998a). The
Irwin model evaluation approach is only applicable when you have an arc of receptors at a
given distance downwind of the source so that a cross plume distribution and dispersion
statistics can be generated. Whereas, the ATMES‐II is more applicable when you have
receptors spread over a large region and can calculate statistical parameters related to the
predicted and observed distribution of the tracer concentrations. Accordingly, we use the Irwin
plume fitting statistical evaluation approach for the GP80 and SRL75 tracer experiments whose
receptors were defined along arcs at a given distance from the source and we used the ATMES‐
II statistical evaluation approach for the CAPTEX and ETEX tracer experiments that had
receptors that were defined across a broad area.
2.4.2 Irwin Plume Fitting Model Evaluation Approach
Irwin (1997) focused his evaluation of the CALPUFF modeling system on its ability to replicate
centerline concentrations and plume widths, with more emphasis placed upon these factors
than data such as modeled/observed plume azimuth, plume arrival time, and plume transit
time. The Great Plains and Savannah River tracer CALPUFF evaluations (EPA, 1998a) followed
the tracer evaluation methodology of the Idaho National Engineering Laboratory (INEL) tracer
study conducted on April 19, 1977 near Idaho Falls, Idaho (Irwin, 1997).
Irwin examined CALPUFF performance by calculating the cross‐wind integrated concentration
(CWIC), azimuth of plume centerline, and the second moment of tracer concentration (lateral
dispersion of the plume [σy]). The CWIC is calculated by trapezoidal integration across average
monitor concentrations along the arc. By assuming a Gaussian distribution of concentrations
along the arc, a fitted plume centerline concentration (Cmax) can be calculated by the following
equation:
Cmax = CWIC/[(2π) ½ σy] (2‐1)
The measure σy describes the extent of plume horizontal dispersion. This is important to
understanding differences between the various dispersion options available in the CALPUFF
modeling system. Additional measures for temporal analysis include plume arrival time and the
plume transit time on arc. Table 2‐2 summarizes the statistical metrics used in the Irwin fitted
Gaussian plume evaluation methodology.
14