||Wright-Patterson AFB, OH 454337542
Methane emissions have a devastating effect on the atmosphere. Methane has been shown to be a far more effective greenhouse gas than carbon dioxide. Methane emissions sensing and modeling is very important to understanding source apportionment and aids in developing policies and technologies to control emissions. There are two main methods in methane inventorying and apportionment: atmospheric sampling and modeling (top down) and source sampling and modeling (bottom up). The source sampling and modeling lends itself better to apportionment, but there are disparities in taking relatively few samples and relying on ranges of assumptions in the models. More sampling data from sources refine the models, but the spatial and temporal distribution of source emissions precludes exhaustive study. It is time-consuming and expensive to have environmental scientists in the field collecting data.
Unmanned aerial vehicles (UAVs) offer an opportunity for source emissions sampling at remote sites, which extends the capacity of the field environmental scientist, However, there are several research questions to resolve to enable using the sampling data in source emissions modeling:(1) effects of “prop wash” on sampling measurements and techniques to employ UAVs to minimize adverse effects, (2) payload tradeoff to achieve sufficient measurement resolution/limit of detection, and (3) georeferencing and flight velocity/sensor response time error resolution.
Eninger RM, Johnson RL: Unmanned Aerial Systems in Occupational Hygiene--Learning from Allied Disciplines. Annals of Occupational Hygiene: mev041, 2015
Subramanian R, et al: Methane emissions from natural gas compressor stations in the transmission and storage sector. Measurements and comparisons with the EPA greenhouse gas reporting program protocol. Environmental Science & Technology 49(5): 3252-3261, 2015
UAV; Remote sensing; Methane; Environmental; Unmanned aerial systems; Unmanned aerial vehicles;