Category: Model Improvements Current & Ongoing Studies

Air quality models are used to predict atmospheric conditions in the future. They are based on meteorological conditions, chemistry mechanisms, and inventories of reported emissions. Models are tested for correctness by comparing their results to observed atmospheric characteristics, such as PM2.5 concentrations during high pollution periods in the past. The following studies show various ways in which models are being improved to better reflect observations of the atmosphere in Utah.

Current & Recently Completed Studies

Image: WRF 2-m air temperature and wind velocity predictions on 10-km grid for northern Utah at 4:00 am April 12, 2017 (left) and 4:00 am April 13, 2017 (right).

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 growth and air pollutant assessments.

  • Principal Investigator: Bradley Adams (BYU)
  • Funded by Science for Solutions Research Grant: $59,411
Read More
Image: Observed ozone concentrations at Ouray and Vernal during January – March 2013. Time in MST.

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) produces much higher ozone concentrations than the Carbon Bond (CB) mechanisms. Ramboll and the BRC will comprehensively test and understand RACM2 performance in simulating wintertime ozone in the Uinta Basin relative to the CB version 6 (CB6) mechanism currently implemented in the CAMx air quality model used by the Utah Division of Air Quality.

  • Principal Investigators: Greg Yarwood (Ramboll), Seth Lyman (Utah State University)
  • Funded by Science for Solutions Research Grant: $98,048
Read More
Model Map Graphic

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
Read More