|Title||Atmospheric characterization through fused mobile airborne and surface in situ surveys: methane emissions quantification from a producing oil field|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Ira Leifer, Christopher Melton, Marc L Fischer, Matthew Fladeland, Jason Frash, WarrenGore, Laura T Iraci, Jocette E Marrero, Ju-Mee Ryoo, Tomoaki Tanaka, Emma L Yates|
|Journal||Atmospheric Measurement Techniques|
|Pagination||1689 - 1705|
Methane (CH4) inventory uncertainties are large, requiring robust emission derivation approaches. We report on a fused airborne–surface data collection approach to derive emissions from an active oil field near Bakersfield, central California. The approach characterizes the atmosphere from the surface to above the planetary boundary layer (PBL) and combines downwind trace gas concentration anomaly (plume) above background with normal winds to derive flux. This approach does not require a well-mixed PBL; allows explicit, data-based, uncertainty evaluation; and was applied to complex topography and wind flows.In situ airborne (collected by AJAX – the Alpha Jet Atmospheric eXperiment) and mobile surface (collected by AMOG – the AutoMObile trace Gas – Surveyor) data were collected on 19 August 2015 to assess source strength. Data included an AMOG and AJAX intercomparison transect profiling from the San Joaquin Valley (SJV) floor into the Sierra Nevada (0.1–2.2 km altitude), validating a novel surface approach for atmospheric profiling by leveraging topography. The profile intercomparison found good agreement in multiple parameters for the overlapping altitude range from 500 to 1500 m for the upper 5 % of surface winds, which accounts for wind-impeding structures, i.e., terrain, trees, buildings, etc. Annualized emissions from the active oil fields were 31.3 ± 16 Gg methane and 2.4 ± 1.2 Tg carbon dioxide. Data showed the PBL was not well mixed at distances of 10–20 km downwind, highlighting the importance of the experimental design.
|Short Title||Atmos. Meas. Tech.|