Probability of Detection and Multi-Sensor Persistence of Methane Emissions from Coincident Airborne and Satellite Observations.

Abstract

Satellites are becoming a widely used measurement tool for methane detection and quantification. The landscape of satellite instruments with some methane point-source quantification capabilities is growing. Combining information across available sensor platforms could be pivotal for understanding trends and uncertainties in source-level emissions. However, to effectively combine information across sensors of varying performance levels, the probability of detection (POD) for all instruments must be well characterized, which is time-consuming and costly, especially for satellites. In August 2023, we timed methane-sensing aerial surveys from the Global Airborne Observatory (GAO) to overlap with observations from the NASA Earth Surface Mineral Dust Source Investigation (EMIT). We show how these coincident observations can be used to determine and verify the detection limits of EMIT and to develop and test a multisensor persistence framework. Under favorable conditions, the 90% POD at 3 for EMIT is 1060. We further derive a Bayesian model to infer probabilistically whether nondetected emissions were truly off, and we validate and show how this model can be used to assess the intermittency of emissions with GAO and EMIT. Time-averaged emission rates from persistent sources can be underestimated if POD is not characterized and if differences in POD across multisensor frameworks are not properly accounted for.