Category: Model Improvements Current & Ongoing Studies

  • The Salt Lake Regional Smoke, Ozone and Aerosol Study (SAMOZA)

    The University of Washington, Utah State University and the University of Montana will conduct a detailed study of ozone (O3) and fine particulate matter (PM2.5) in the Salt Lake Valley (SLV). Using new VOC observations, plus existing measurements of NOx, CO and PM2.5, they will use a variety of analyses to understand O3 formation and…

  • Improving Smoke Detection and Quantifying the Wildfire Smoke Impacts on Local Air Quality Using Modeling and Machine Learning Techniques

    Though it can be easy to tell that wildfire smoke has negative impacts on urban air quality, there is no tool to quantitatively measure wildfire impacts, nor to identify whether exceedance days are due to wildfire smoke or other emissions. The first scope of this work will develop a new plume rise model to estimate…

  • Improved Vegetation Data for the Biogenic Emission Inventory of Wasatch Front

    The goal of this project is to improve numerical predictions of regional ozone and aerosol distributions in the Wasatch Front by developing more accurate estimates of biogenic volatile organic carbon (BVOC) emissions for the urban areas within the Northern Wasatch Front. Specifically, this project will upgrade modeled MEGAN (Model of Emissions of Gasses and Aerosols…

  • Development of a WRF-based Urban Canopy Model for the Greater Salt Lake City Area

    Brigham Young University will conduct a two-year project that will utilize state-of-the-science meteorological modeling with land use descriptions of the Great Salt Lake area to characterize impacts of urban growth on local meteorological conditions. Model methodology and usage will be documented so air quality modelers can use existing or self-developed future results for additional urban…

  • Assessing Wintertime Ozone Prediction Sensitivity to Photochemical Mechanism

    Ramboll and the Utah State University – Bingham Research Center (BRC) will conduct a study to thoroughly investigate wintertime ozone prediction sensitivity in the Uinta Basin among two current photochemical mechanisms using a consistent modeling platform. Recent air quality modeling conducted by BRC using different modeling systems indicates that the Regional Atmospheric Chemistry Mechanism (RACM)…

  • Improving WRF/CMAQ Model Performance using Satellite Data Assimilation Technique for the Uintah Basin

    This study will test if satellite observations of vegetation and land use can be used to improve photochemical model performance in the Uintah basin. An improved model will help inform emission reduction strategies and regulatory action. Principal Investigators: Huy Tran, Trang Tran (USU) Funded by Science for Solutions Research Grant: $38,392

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