Atmospheric methane emissions from active natural gas production sites in normal operation were quantified using an inverse Gaussian method (EPA's OTM 33a) in four major U.S. basins/plays: Upper Green River (UGR, Wyoming), Denver-Julesburg (DJ, Colorado), Uintah (Utah), and Fayetteville (FV, Arkansas). In DJ, Uintah, and FV, 72-83% of total measured emissions were from 20% of the well pads, while in UGR the highest 20% of emitting well pads only contributed 54% of total emissions. The total mass of methane emitted as a percent of gross methane produced, termed throughput-normalized methane average (TNMA) and determined by bootstrapping measurements from each basin, varied widely between basins and was (95% CI): 0.09% (0.05-0.15%) in FV, 0.18% (0.12-0.29%) in UGR, 2.1% (1.1-3.9%) in DJ, and 2.8% (1.0-8.6%) in Uintah. Overall, wet-gas basins (UGR, DJ, Uintah) had higher TNMA emissions than the dry-gas FV at all ranges of production per well pad. Among wet basins, TNMA emissions had a strong negative correlation with average gas production per well pad, suggesting that consolidation of operations onto single pads may reduce normalized emissions (average number of wells per pad is 5.3 in UGR versus 1.3 in Uintah and 2.8 in DJ).

SignificanceOur results demonstrate that access to high-resolution spatiotemporal activity data and multiscale, contemporaneous measurements is critical to understanding oil- and gas-related methane emissions. Careful consideration of all factors influencing methane emissions—including temporal variation—is necessary in scientific and policy discussions to develop effective strategies for mitigating greenhouse gas emissions from natural gas infrastructure.

Divergence in recent oil and gas related methane emission estimates between aircraft studies (basin total for a midday window) and emissions inventories (annualized regional and national statistics) indicate the need for better understanding the experimental design, including temporal and spatial alignment and interpretation of results. Our aircraft-based methane emission estimates in a major U.S. shale gas basin resolved from west to east show (i) similar spatial distributions for 2 days, (ii) strong spatial correlations with reported NG production (R = 0.75) and active gas well pad count (R = 0.81), and (iii) 2× higher emissions in the western half (normalized by gas production) despite relatively homogeneous dry gas and well characteristics. Operator reported hourly activity data show that midday episodic emissions from manual liquid unloadings (a routine operation in this basin and elsewhere) could explain ∼1/3 of the total emissions detected midday by the aircraft and ∼2/3 of the west-east difference in emissions. The 22% emission difference between both days further emphasizes that episodic sources can substantially impact midday methane emissions and that aircraft may detect daily peak emissions rather than daily averages that are generally employed in emissions inventories. While the aircraft approach is valid, quantitative, and independent, our study sheds new light on the interpretation of previous basin scale aircraft studies, and provides an improved mechanistic understanding of oil and gas related methane emissions.

Methane, a key component of natural gas, is a potent greenhouse gas. A key feature of recent methane mitigation policies is the use of periodic leak detection surveys, typically done with optical gas imaging (OGI) technologies. The most common OGI technology is an infrared camera. In this work, we experimentally develop detection probability curves for OGI-based methane leak detection under different environmental and imaging conditions. Controlled single blind leak detection tests show that the median detection limit (50% detection likelihood) for FLIR-camera based OGI technology is about 20 g CH/h at an imaging distance of 6 m, an order of magnitude higher than previously reported estimates of 1.4 g CH/h. Furthermore, we show that median and 90% detection likelihood limit follows a power-law relationship with imaging distance. Finally, we demonstrate that real-world marginal effectiveness of methane mitigation through periodic surveys approaches zero as leak detection sensitivity improves. For example, a median detection limit of 100 g CH/h is sufficient to detect the maximum amount of leakage that is possible through periodic surveys. Policy makers should take note of these limits while designing equivalence metrics for next-generation leak detection technologies that can trade sensitivity for cost without affecting mitigation priorities.

Introduction The recent Intergovernmental Panel on Climate Change (IPCC) special report on global warming of 1.5°C highlighted the importance of reducing short-lived greenhouse gases like methane (Intergovernmental Panel on Climate Change, 2018). Methane, a major component of natural gas, has a global warming potential that is 36 times that of carbon dioxide over a 100-year period (Myhre, et al., 2013), and even higher over shorter time periods (Etminan, Myhre, Highwood, & Shine, 2016). Furthermore, methane emissions contribute to sea-level rise over much longer timescales than their atmospheric lifetimes (Zickfeld, Solomon, & Gilford, 2017). These consequences are troubling given that official methane emissions inventory in the US and Canada have been found to be systematically underestimated (Alvarez, et al.,