(BRAVO) Study: Final Report. - Desert Research Institute

Final Report — September 2004
• The synthesized CMAQ results are closer to the original CMAQ model estimates
than those of synthesized REMSAD were to regular REMSAD results.
Therefore, the CMAQ source attributions required smaller bias corrections, and
relied less on the regression analysis to fit the observed data.
• The synthesized CMAQ results compare better to the observed data.
9.13 Conclusions Concerning Performance of the Source Attribution Methods
The many analyses of model performance discussed here produced the not-surprising
conclusion that the meteorological and air quality models ultimately used for source
apportionment in the BRAVO Study performed pretty much within the norms of state-of-the
art model performance. Most of the methods were able to estimate the average – over the
study area and over the period of the study – sulfate concentrations and, to a lesser degree,
the SO 2 concentrations. The models that provided finer spatial and temporal resolution were
less successful at capturing all of the day-to-day details of concentration variation, especially
for SO 2 and for peaks in either sulfate or SO 2 . The REMSAD and CMAQ air pollution
models both overestimated sulfur concentrations in the eastern part of the study area. CMAQ
used measurement-scaled REMSAD outputs to provide boundary conditions, which adjusted
for this overestimate in the REMSAD inputs to CMAQ, so the CMAQ overestimation should
be relatively independent of the REMSAD bias.
Quantitatively, the MM5 wind fields used for the modeling and trajectory analyses
tended to estimate hourly-average wind direction within 30 degrees (mean absolute error)
and speed within 2 m/s (RMS error). Long-term biases were better than 10 degrees and 0.5
m/s, except that wind speeds aloft were slightly worse. The better long-term statistics
provide a first indication of why the trajectory methods and air quality models performed
better on average than on any particular day. The EDAS wind fields used for some of the
trajectory analyses appeared to be comparable in quality to those of MM5.
The MM5 meteorological model outputs, when processed by the REMSAD model,
tended to overestimate precipitation in the BRAVO Study area and cloud cover along the
Texas-Mexico border.
Accurately simulating the narrow perfluorocarbon tracer plumes was expected to be
challenging, and it turned out to be so. Performance for the tracer that traveled the longest
distance, from northeast Texas, could not be evaluated reliably by any of the methods
because the measured sample concentrations were so small. For the other tracers, none of the
methods could consistently reproduce the day-to-day variation of the tracer signals, but most
methods had some success some of the time. Both the REMSAD and CMAQ models
performed the best for the Eagle Pass and San Antonio tracers, and not as well for the tracer
released from the more distant Houston. Both returned the highest coefficients of
determination, r 2 , for the San Antonio tracer, with the best r 2 = 0.4 obtained by CMAQ.
Several of the methods were able to attribute the tracers to their sources with varying
degrees of accuracy. For the Tracer Mass Balance (TrMB) method, the combination of the
HYSPLIT trajectory model and EDAS winds performed relatively well at attributing the
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