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A New Inferential Deposition Model for Use in Network Operations

Donna Schwede*
NOAA/ARL/ASMD, MD E243-04, Research Triangle Park, NC 27711

Gary Lear
Clean Air Markets Division, Office of Air and Radiation, U.S. Environmental Protection Agency


The Clean Air Status and Trends Network (CASTNET) is operated by the Clean Air Markets Division (CAMD) of the Office of Air Programs and the National Park Service to monitor concentration and dry deposition of sulfur and nitrogen species and ozone at sites across the country to assess long-term trends in air quality and environmental protection resulting from regulatory policies and emission reductions required under the Clean Air Act. CASTNET is considered the primary source for estimates of dry acidic deposition and is vital to the Agencies efforts in the protection of terrestrial and aquatic ecosystems. Additionally, concentration measurements from CASTNET are important to air programs in the development of SIPs and the evaluation of air quality models such as CMAQ.

Since measurements of dry deposition flux are costly, CASTNET uses an inferential method to obtain these estimates whereby model-determined deposition velocities are paired with network measured concentrations. The model currently used for determining the deposition velocity is the Multilayer Model (MLM). A contractor runs the model using a Visual Basic interface and station specific site characteristics, meteorology and plant information. The deposition estimates along with measured concentrations and computed fluxes are maintained in a database. The database is provided to EPA and posted to their website for public access. The public does not have access to the interface.

Previous evaluations of the MLM showed good overall model performance, but indicated some potential areas for improvement. To address these areas, the Multilayer Biochemical (MLBC) model was developed which includes a state-of-the-science biochemical stomatal resistance model. Additional modifications were made to the water stress function, cuticular resistance, and soil surface resistance. The MLBC model was evaluated against several field studies and showed slightly better overall performance compared to the MLM and captured diurnal cycles better. EPA initiated an effort to adapt the research version of the MLBC model for use with CASTNET data. Beta versions of the revised model, MLBCNet, supporting databases, and the new Python interface for running the model have been completed. An overview of MLBCNet, the interface, and associated data is presented. MLBCNet was run for several CASTNET sites and comparisons of the deposition velocities from MLBCNet with those from the MLM model are provided.

Note: In partnership with the U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory.