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In comparing observation based methane emission estimates for oil and gas well sites to routine emissions reported in inventories, the time scale of the measurement should match the time scale over which the inventoried emissions are estimated. Since many measurements are of relatively short duration (seconds to hours), a tool is needed to estimate emissions over these time scales rather than the annual totals reported in most emission inventories. This work presents a tool for estimating routine emissions from oil and gas well sites at multiple time scales; emissions at well sites vary over time due to changes in oil and gas production rates, operating practices and operational modes at the sites. Distributions of routine emissions (expected and inventoried) from well sites are generally skewed, and the nature and degree to which the distributions are skewed depends on the time scales over which emissions are aggregated. Abnormal emissions can create additional skew in these distributions. At very short time scales (emissions aggregated over 1 min) case study distributions presented in this work are both skewed and bimodal, with the modes depending on whether liquid storage tanks are flashing at the time of the measurement and whether abnormal emissions are occurring. At longer time scales (emissions aggregated over 1 day) distributions of routine emissions simulated in this work can have multiple modes if short duration, high emission rate events, such as liquid unloadings or large abnormal emissions, occur at the site. Multiple applications of the methane emission estimation tool (MEET), developed in this work, are presented. These results emphasize the importance of developing detailed emission inventories, which incorporate operational data, when comparing measurements to routine emissions. The model described in this work supports such comparisons and is freely available., Competing Interests: Declaration of competing interest The authors declare the following competing financial interest(s): This work was supported by the Collaboratory to Advance Methane Science (CAMS), a group of companies operating facilities in the natural gas supply chain., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Recent attention to methane emissions from oil and gas infrastructure has increased interest in comparing measurements with inventory emission estimates. While measurement methods typically estimate emissions over a few periods that are seconds to hours in length, current inventory methods typically produce long-term average emission estimates. This temporal mis-alignment complicates comparisons and leads to underestimates in the uncertainty of measurement methods. This study describes a new temporally and spatially resolved inventory emission model (MEET), and demonstrates the model by application to compressor station emissions - the key facility type in midstream natural gas operations The study looks at three common facility measurement methods: tracer flux methods for measuring station emissions, the use of ethane-methane ratios for source attribution of basin-scale estimates, and the behavior of continuous monitoring for leak detection at stations. Simulation results indicate that measurement methods likely underestimate uncertainties in emission estimates by failing to account for the variability in normal facility emissions and variations in ethane/methane ratios. A tracer-based measurement campaign could estimate emissions outside the 95% confidence interval of annual emissions 30% of the time, while ethane/methane ratios could be mis-estimated by as much as 50%. Use of MEET also highlights the need to improve data reporting from measurement campaigns to better capture the temporal and spatial variation in observed emissions., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Daniel Zimmerle reports financial support was provided by Collaboratory to Advance Methane Science. David T Allen reports a relationship with Exxon Mobil Upstream Research Company that includes: funding grants. David T Allen reports a relationship with National Institute for Clean and low Carbon Energy (NICE) that includes: funding grants. Daniel Zimmerle reports a relationship with Chevron Inc. that includes: funding grants. Daniel Zimmerle reports a relationship with BP Plc that includes: funding grants. Daniel Zimmerle reports a relationship with The Environmental Partnership (API) that includes: funding grants. Daniel Zimmerle reports a relationship with Renewable Natural Gas Coalition that includes: funding grants. Daniel Zimmerle reports a relationship with Environmental Defense Fund that includes: funding grants. David T Allen reports a relationship with Eastern Research Group that includes: funding grants. Felipe Cardoza-Saldana reports a relationship with Exxon Mobil Upstream Research Company that includes: employment. Daniel Zimmerle reports a relationship with Colorado Air Quality Enterprise Board, as Colorado State Agency that includes: board membership. Over the past five years, multiple authors have also worked on methane emission measurement projects that have been supported by multiple natural gas producers, developers of leak detection solutions, and the Environmental Defense Fund. Multiple co-authors have been active the funded research projects declared by the Corresponding Author (Zimmerle) and co-Author (Allen)., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Rapid response to underground natural gas leaks could mitigate methane emissions and reduce risks to the environment, human health and safety. Identification of large, potentially hazardous leaks could have environmental and safety benefits, including improved prioritization of response efforts and enhanced understanding of relative climate impacts of emission point sources. However, quantitative estimation of underground leakage rates remains challenging, considering the complex nature of methane transport processes. We demonstrate a novel method for estimating underground leak rates based on controlled underground natural gas release experiments at the field scale. The proposed method is based on incorporation of easily measurable field parameters into a dimensionless concentration number, ε, which considers soil and fluid characteristics. A series of field experiments was conducted to evaluate the relationship between the underground leakage rate and surface methane concentration data over varying soil and pipeline conditions. Peak surface methane concentrations increased with leakage rate, while surface concentrations consistently decreased exponentially with distance from the source. Deviations between the estimated and actual leakage rates ranged from 9% to 33%. A numerical modeling study was carried out by the TOUGH3 simulator to further evaluate how leak rate and subsurface methane transport processes affect the resulting methane surface profile. These findings show that the proposed leak rate estimation method may be useful for prioritizing leak repair, and warrant broader field-scale method validation studies. A method was developed to estimate fugitive emission rates from underground natural gas pipeline leaks. The method could be applied across a range of soil and surface covering conditions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

This study spatially and temporally aligns top-down and bottom-up methane emission estimates for a natural gas production basin, using multiscale emission measurements and detailed activity data reporting. We show that episodic venting from manual liquid unloadings, which occur at a small fraction of natural gas well pads, drives a factor-of-two temporal variation in the basin-scale emission rate of a US dry shale gas play. The midafternoon peak emission rate aligns with the sampling time of all regional aircraft emission studies, which target well-mixed boundary layer conditions present in the afternoon. A mechanistic understanding of emission estimates derived from various methods is critical for unbiased emission verification and effective greenhouse gas emission mitigation. Our results demonstrate that direct comparison of emission estimates from methods covering widely different timescales can be misleading., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)