Satellite Measurements Aid Uinta Basin Air Quality Research
Lower Methane in Uinta Basin Oilfield During Winter 2020
We examined data from the TROPOspheric Monitoring Instrument (TROPOMI) instruments onboard the Sentinel – 5P satellite platform for the distribution of methane total atmospheric column concentration over the Uinta Basin in winters 2019 and 2020. As shown in the figure, during January through March, methane concentration over the oil field (west of Ouray – OU) was lower in 2020 than in 2019, but methane over the gas field (east of OU) was higher in 2020 than in 2019. The reason for these differences is not yet entirely clear. Oil production declined during winter 2020, but meteorological conditions were different also. Persistent inversion conditions in 2019 led to elevated winter ozone, while 2020 inversions were accompanied by cloud cover and lower ozone. While methane's contribution to wintertime ozone is low, methane is a reasonable surrogate for ozone-producing organic compound concentrations in the atmosphere.
TROPOMI data products include methane, carbon monoxide, formaldehyde, and nitrogen dioxide. These data are providing insights into meteorological and chemical changes in the Uinta Basin atmosphere and will be used to validate photochemical model outputs. Furthermore, in combination with measurements of the atmospheric boundary layer using instruments such as met towers, SODAR, and LiDAR that will be carried out over the next two winters by BLM, these TROPOMI data products can be used to deduce Basin-wide emission rates, leading to improvements to emissions inventories.
Atmospheric total column of methane concentration (in ppb) over the Uinta Basin on average over the period January – March 2019 and 2020, as observed from SENTINEl-5P satellite (TROPOMI). The blob in cyan south of Gusher (GU) and east of Ouray (OU) in 2020 is caused by insufficient TROPOMI data and should be disregarded.
Incorporation of Satellite Data Improves Snow Cover in Photochemical Models
We have completed work to improve meteorological (WRF) and photochemical (CAMx) model performance in simulating surface albedo and snow cover using a novel MODIS satellite data assimilation technique. The main finding for a model episode in winter 2011 is that assimilation of MODIS data to WRF greatly improves WRF’s accuracy in simulating snow characteristics, not only in the Basin, but in all areas of the model domain, including the Wasatch Front. Decay of snow depth and snow cover in WRF is also less with MODIS data assimilation in comparison with a regular simulation. However, no significant improvements in WRF performance were found for other quantities, such as mixing height or wind fields. Furthermore, higher snow albedo in WRF as obtained from the MODIS data assimilation did not, in general, result in higher photolysis rates in CAMx, due to how the model calculates snow albedo and its assumption on snow age. Nevertheless, from this study we have developed a methodological approach to improve WRF performance in simulating snow characteristics which, prior to this study, required manual corrections and best guesses from modelers. This study was financially supported by Utah DAQ.
Comparison of ozone photolysis rates simulated by CAMx at Ouray (OU) in a standard simulation (REF) and with snow albedo assimilated from MODIS. Ozone photolysis rates are higher in MODIS than in REF if snow is left aging over an extended period, but becomes lower when there is fresh snow in the model, which is indicated by the green vertical bar.