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UAS-Based Aerial Measurements to Calibrate Plume Dispersion Models: The “Alaska Plume Project”
Citation:
Gullett, B. UAS-Based Aerial Measurements to Calibrate Plume Dispersion Models: The “Alaska Plume Project”. PI-Initiated briefing, NA - Virtual Meeting, NC, July 20, 2022.
Impact/Purpose:
This presentation discusses emission measurements of plumes relating to air quality. An upcoming project, with multiple partners, will conduct emission measurements using instruments carried aloft by an unmanned aircraft system as well as ground-based measurements. These plume measurements will, likely for the first time, provide plume concentration data that can be used to improve dispersion model predictions. This could have significant impact on on-scene assessments of worker risk and downwind population exposure.
Description:
This multiagency project, with funding and participation from NOAA, EPA, DOI/BSEE, USGS, and USCG, will conduct sampling of a burning oil plume (although other sources are applicable) in Alaska to provide NOAA with data for near-source dispersion model calibration. This is a first-of-its-kind effort: probing a near-source plume using an unmanned aircraft system (UAS, or drone) for spatial and temporal plume concentrations to feed into a dispersion model. The resulting calibrations (improvements) of the model will further the ability of On-Scene Coordinators (OSCs) to predict worker and downwind populace exposure from emergency responses as well as developing dispersion modeling science. The base project is anticipated to gather first data in August '22 near Fairbanks, Alaska. These data will be put into NOAA dispersion models to calibrate the model fit of the actual data. Participation by the USCG and EPA researchers can assist in modernization of the USCG/NOAA Special Monitoring of Applied Response Technologies (SMART) technologies and methods used to respond to monitoring air quality during emergency responses. As this is the first of its kind effort and the number of anticipated burns (5) and plume duration will be limited, we expect a steep learning curve suggesting follow-up plume measurements on the same or other candidate sources (e.g., landfills, wildland fires). The ultimate, out-year goal of this effort is a UAS-based system and model that can be used by OSCs at emergency responses. Development of this modeling capability will parallel the Agency's adoption and use of UAS for emergency responses, provide more accurate plume path information into regional dispersion models, and improve general dispersion modeling science.