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Modeling Long-Term Patterns of Speciated Mercury Concentrations in Maryland Using CALPUFF
John Sherwell*
Maryland Power Plant Research Program (PPRP), 580 Taylor Ave.,
Tawes State Office Building, Annapolis, MD, 21401
Tom Wickstrom, Anand Yegnan, Mark Garrison
ERM, 350 Eagleview Blvd., Exton, PA 19341
Mark Castro, Chris Moore
University of Maryland Center for Environmental Science,
301 Braddock Rd., Frostburg, MD 21532
| The Maryland Department of Natural Resources,
Power Plant Research Program (PPRP) has provided support for the enhancement
of a monitoring site at the Piney Reservoir in western Maryland by adding
instrumentation (Tekran) that measures ambient speciated mercury on a
continuous basis. Since the Piney site is part of several monitoring networks,
a comprehensive set of concentration, deposition, and meteorological parameters
are measured there. Nearly two years of continuous, speciated mercury
concentrations are now available from the Piney site - elemental (HG0),
reactive (Hg2+) and particulate (HgP). These data display seasonal, diurnal,
and other patterns of mercury concentrations (including occasional large
peaks of Hg2+) that can contribute to an understanding of the relative
importance of local, regional, and global sources of mercury. PPRP has
developed a modified version of the CALPUFF Lagrangian model to estimate
mercury concentrations and deposition in Maryland. CALPUFF is capable
of creating detailed source contribution matrices of mercury concentrations
and deposition. While the CALPUFF model has demonstrated reasonably good
performance when compared to weekly mercury deposition network (MDN) measurements,
it has yet to be comprehensively evaluated with continuous concentrations.
Success in predicting mercury oncentrations is a necessary ingredient
for estimating dry deposition, which may play an extremely important (but
less-understood) role in mercury loading to watersheds and waterbodies
due to atmospheric input. PPRP is taking the first step in this evaluation
by comparing model predicted patterns with patterns measured at Piney.
To develop the model predictions, a 10-year meteorological data set is
used to examine the frequency and persistence of certain patterns. This
poster will compare the model predictions over a ten-year period to measurements
taken at Piney to provide insights into model performance related to speciated
concentrations.
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