Impact of the High-Emission Event Duration and Sampling Frequency on the Uncertainty in Emission Estimates

Abstract

Short duration remote sensing measurements of methane emissions from oil and gas operations are being deployed at a large scale, but interpretation of these snapshot measurements is complex due to the spatial and temporal variability of methane emissions. The accuracy and precision of annual emission estimates extrapolated from short duration measurements depend on the measurement frequency and complexity of temporal emission patterns. This work examines sampling uncertainties associated with short duration measurements of varying frequencies for methane emissions from a group of sites representing the Barnett Shale region. Routine, frequent emissions are accurately captured with minimal bias through semiannual sampling; however, infrequent high-emission rate events increase the error associated with annual emission estimates, even under the assumption of no measurement uncertainty. If emission events have a duration of ≤1 week, monthly sampling has an estimated sampling error of >15%. For quarterly sampling with emission events that persist for ≤1 month, the sampling error is >30%. There is also negative bias associated with quarterly, semiannual, and annual sampling, which suggests infrequent campaigns may be systemically underestimating emissions. The sampling error increases as the duration of the high-emission events becomes shorter, making the temporal persistence of emission events an important factor in designing measurement protocols.