Significance: Our 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.

Methane leakage regulations in the US and Canada have spurred the development of new technologies that promise faster and cheaper leak detection for the oil and natural gas industry. Here, we report results from the Stanford/EDF Mobile Monitoring Challenge – the first independent assessment of 10 vehicle-, drone-, and plane-based mobile leak detection technologies. Using single-blind controlled release tests at two locations, we analyze the ability of mobile technologies to detect, localize, and quantify methane emissions. We find that the technologies are generally effective at detecting leaks, with 6 of the 10 technologies correctly detecting over 90% of test scenarios (true positive plus true negative rate). All technologies demonstrated pad-level localization of leaks, while 6 of the 10 technologies could assign a leak to the specific piece of equipment in at least 50% of test scenarios. All systems tested here will require secondary inspection to identify leak locations for repair; thus, mobile leak detection technologies can act as a complement, and not a substitute, for currently used optical gas imaging systems. In general, emissions quantification needs improvement as most technologies were only able to generally provide order of magnitude emissions estimates. Improvements to quantification algorithms, reducing false positive detection rates, and identifying early applications will be critical for deployment at scale. Even as this study provides the first independent verification of the performance of mobile technologies, it only represents the first step in the road to demonstrating that these technologies will provide emissions reductions that are equivalent to existing regulatory approaches.

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 (R² = 0.75) and active gas well pad count (R² = 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.