Future regulatory actions for mitigating PM2.5 concentrations will rely, to some extent, on results from large-scale atmospheric models. The most efficient approach to evaluating regulatory actions is to use an integrated approach that examines multiple air quality impacts simultaneously. This is because of the strong linkage between PM2.5 levels, visibility degradation, ozone and acidic deposition. Thus, regional modeling of the impacts on PM2.5 levels from proposed emission reductions should be evaluated in terms of computed impacts not only on PM2.5 levels, but on ozone and acidic deposition as well.

TVA is an active participant in the only ongoing assessment of this type, which is being done for the Southern Appalachian Mountains Initiative (SAMI) as part of its integrated assessment in the southeastern United States. SAMI, with its focus on protecting PSD Class I areas, is using a model called URM that can examine all the aforementioned phenomena at once. In addition, URM has the capability, which SAMI intends to use, of efficiently examining the sensitivity of model outputs to changes in emissions across the entire modeling domain. Finally, SAMI will use URM to test various emission management options (EMOs) for mitigating impacts in the southern Appalachians. These EMOs will include controls on various source sectors, including energy.

Under collaboration with DOE, results from the episodic and sensitivity runs of URM will be analyzed by TVA to provide DOE with information on how different air quality parameters, including PM2.5, vary with changes in different source sectors (e.g., large point sources, low-level area sources, mobile sources, etc.) This modeling will examine large-scale changes, thereby giving a scope to the results that will be applicable to a large part of the eastern U.S. In addition, SAMI will use actual and future-year emissions data as part of its analysis, giving information that is relevant to current and anticipated future emission scenarios.

In order to build upon the SAMI modeling effort, the regional air quality model recently developed by EPA (Models-3) will also be evaluated under this task. Models-3 and URM will each be run for one or two base cases (depending on the feasibility of converting the existing SAMI data to the Models-3 format), and the predicted PM2.5 and ozone levels from the two models in the eastern U.S. would be compared. Several emission control strategies proposed by SAMI will be simulated for the base case(s) and the consistency between the two models will be evaluated.

Nitrogen Deposition Modeling
A modeling exercise will be performed to predict the effect of various NOx reduction strategies on nitrogen deposition and saturation in the Noland Divide Watershed (NDW) over a long period of time. Since a wealth of historical data has been developed in previous work, this existing database will be used to check the accuracy of the model outputs. Using the specific deposition and site characteristics data from NDW and Clingman's Dome, the modeling will provide a fairly comprehensive temporal analysis to predict how long it will take for any environmentally significant change to be detected. Because of the high nitrogen deposition rates in the watershed, it offers a unique advantage, in that even small changes are more likely to be apparent. This will be a highly-leveraged study with funding provided by numerous other organizations besides DOE and TVA.