We propose a program of work that will enhance applications of EPA's Community Multiscale Air Quality (CMAQ) Model, which will be considered as the Decision Support Tool in this application of NASA Earth Science Research Results. We will enhance the application of CMAQ through linkages with NASA satellite data products and with NASA-generated model algorithms. CMAQ is run for operational air quality forecasts by NOAA, run by EPA for national air quality assessments, and run by state agencies for air quality planning. In all applications of CMAQ accurate emissions inventories are necessary for making accurate air quality estimates. Natural sources of NOx (soil and lightning) are currently either crudely represented or not included in inventories used in CMAQ. The air quality impacts of large changes in power plant NOx emissions that have been mandated under EPA's SIP Call have been estimated with national assessments run with CMAQ. However, EPA is required to demonstrate the resulting improvement in air quality through monitoring activities. We anticipate that tropospheric NO2 from the OMI instrument on NASA's Aura satellite can be used in conjunction with CMAQ to both refine estimates of natural source emissions of NOx and to monitor air quality improvements associated with anthropogenic emissions reductions. We will begin by adapting an existing algorithm for lightning NOx emissions for use in CMAQ. We have developed this algorithm under previous NASA funding for the Global Modeling Initiative (GMI). The algorithm ensures that lightning emissions are input to the model in the same locations and times for which the model contains deep convection, and that the emissions are input using a realistic vertical profile. Testing will first be conducted using observations of lightning flash rates from the National Lightning Detection Network and the OTD/LIS satellite-derived lightning climatology. Resulting NOx mixing ratios from CMAQ will be evaluated against aircraft measurements from the NASA Tropospheric Chemistry Program's INTEX-NA experiment in the summer of 2004. The longer-term evaluation of the lightning emissions will be conducted using the OMI data. Soil NO emissions are likely underestimated in current emissions inventories used in CMAQ. OMI NO2 data from regions of cropland with low population density and distant from major point sources will be analyzed, and soil emissions will be adjusted in CMAQ simulations such that the model matches the tropospheric column NO2 from OMI. Substantial NOx emissions reductions have been taking place at eastern and central US electrical generating plants since 2003. Much of the power plant emissions are transported either in the upper portion of the boundary layer or above the boundary layer top. Therefore, satellite data would appear to be the tool that would allow more comprehensive assessment of the results of the emission reductions than would surface monitoring alone. EPA has begun an Advanced Monitoring Initiative project along these lines using SCIAMACHY NO2 data. We will contribute to the EPA activity by employing a methodology for use of the OMI data in examining the air quality impacts of the emissions reductions. The method will consist of using CMAQ simulations to define regions of influence downwind of the sources undergoing emissions reductions. OMI data will be analyzed in the regions of influence defined by CMAQ for time periods before and after emission reduction occurs, such that we can determine the magnitude of improvement in air quality. EPA-mandated Tier II mobile source NOx emissions reductions of 5% per year on new vehicles began in 2002 and will continue to 2010. We will use the same technique designed above for employing OMI data to evaluate air quality improvements in major metropolitan areas (e.g., Baltimore-Washington area and others) resulting from these motor vehicle emissions reductions.