This study evaluated multiple commercially available continuous monitoring (CM) point sensor network (PSN) solutions under single-blind controlled release testing conducted at operational upstream and midstream oil and natural gas (O&G) sites. During releases, PSNs reported site-level emission rate estimates of 0 kg/h between 38 and 86% of the time. When non-zero site-level emission rate estimates were provided, no linear correlation between the release rate and the reported emission rate estimate was observed. The average, aggregated across all PSN solutions during releases, shows 5% of the mixing ratio readings at downwind sensors were greater than the site’s baseline plus two standard deviations. Four of seven total PSN solutions tested during this field campaign provided site-level emission rate estimates with the site average relative error ranging from −100% to 24% for solution D, −100% to −43% for solution E, −25% for solution F (solution F was only at one site), and −99% to 430% for solution G, with an overall average of −29% across all sites and solutions. Of all the individual site-level emission rate estimates, only 11% were within ±2.5 kg/h of the study team’s best estimate of site-level emissions at the time of the releases.

Methane (CH₄), a powerful greenhouse gas (GHG), has been identified as a key target for emission reduction in the Paris agreement, but it is not currently clear where efforts should be focused to make the greatest impact. Currently, activity data and standard emission factors (EF) are used to generate GHG emission inventories. Many of the EFs are globally uniform and do not account for regional variability in industrial or agricultural practices and/or regulation. Regional EFs can be derived from top–down emissions measurements and used to make bespoke regional GHG emission inventories that account for geopolitical and social variability. However, most large-scale top–down approaches campaigns require significant investment. To address this, lower-cost driving surveys (DS) have been identified as a viable alternative to more established methods. DSs can take top–down measurements of many emission sources in a relatively short period of time, albeit with a higher uncertainty. To investigate the use of a portable measurement system, a 2260 km DS was conducted throughout the Denver–Julesburg Basin (DJB). The DJB covers an area of 8000 km² north of Denver, CO and is densely populated with CH₄ emission sources, including oil and gas (O and G) operations, agricultural operations (AGOs), lakes and reservoirs. During the DS, 157 individual CH₄ emission sources were detected; 51%, 43% and 4% of sources were AGOs, O and G operations, and natural sources, respectively. Methane emissions from each source were quantified using downwind concentration and meteorological data and AGOs and O and G operations represented nearly all the CH₄ emissions in the DJB, accounting for 54% and 37% of the total emission, respectively. Operations with similar emission sources were grouped together and average facility emission estimates were generated. For agricultural sources, emissions from feedlot cattle, dairy cows and sheep were estimated at 5, 31 and 1 g CH₄ head⁻¹ h⁻¹, all of which agreed with published values taken from focused measurement campaigns. Similarly, for O and G average emissions for well pads, compressor stations and gas processing plants (0.5, 14 and 110 kg CH₄ facility⁻¹ h⁻¹) were in reasonable agreement with emission estimates from intensive measurement campaigns. A comparison of our basin wide O and G emissions to measurements taken a decade ago show a decrease of a factor of three, which can feasibly be explained by changes to O and G regulation over the past 10 years, while emissions from AGOs have remained constant over the same time period. Our data suggest that DSs could be a low-cost alternative to traditional measurement campaigns and used to screen many emission sources within a region to derive representative regionally specific and time-sensitive EFs. The key benefit of the DS is that many regions can be screened and emission reduction targets identified where regional EFs are noticeably larger than the regional, national or global averages.

This study evaluated multiple commercially available continuous monitoring (CM) point sensor network (PSN) solutions under single-blind controlled release testing conducted at operational upstream and midstream oil and natural gas (O&G) sites. During releases, PSNs reported site-level emission rate estimates of 0 kg/h between 38-86% of the time. When non-zero site-level emission rate estimates were provided, no linear correlation between release rate and reported emission rate estimate was observed. The average, aggregated across all PSN solutions during releases, shows 5% of mixing ratio readings at downwind sensors were greater than the site's baseline plus two standard deviations. Four of six total PSN solutions tested during this field campaign provided site-level emission rate estimates with the site average relative error ranging from -100% to 24% for solution D, -100% to -43% for solution E, -25% for solution F (solution F was only at one site), and -99% to 430% for solution G, with an overall average of -29% across all sites and solutions. Of all the individual site-level emission rate estimates, only 11% were within +/- 2.5 kg/h of the study team's best estimate of site-level emissions at the time of the releases.

Continuous Monitoring (CM) solutions have been identified as a method to address methane emissions at oil and gas (O&G) facilities, as these solutions can facilitate faster emission detection and repair compared to traditional survey methods. This study tested 13 CM solutions over 12 weeks using single-blind controlled testing. Controlled release rates ranged from 0.08 to 6.75 kg CH4/hr and lasted 18 minutes to 8 hours. Six solutions demonstrated 90 % method detection limits (DL90s) within the range of controlled releases, from 0.5 [0.3, 0.6] kg CH4/hr to 6.7 [5.9, 8.0] kg CH4/hr. Of the six solutions, four had False Positive (FP) rates between 7.8% and 14.0% (less than 15%), and four had False Negative rates (FN) of 8.0% to 34.1% (less than 50%). Compared with Ilonze et al., these results show retested solutions balancing method sensitivity with FP and FN rates. All scanning/imaging solutions had high localization (≥ 40%) precision and accuracy to the equipment unit. Eleven of the 13 solutions were tested for quantification. Single quantification estimates exhibited high relative quantification errors, outside the -90 % to 1000% range. The mean quantification error ranged from 33 [0.9, 66] %, 95% CI to 1326 [1003, 1648] %, 95 % CI for small emissions, between 0.1 and 1 kg CH4/hr, and from 3 [-20, 26] %, 95% CI to 3578 [-2832, 9988] %, 95% CI for larger emissions, greater than 1 kg CH4/hr. There were 3 and 9 solutions in the small and large emissions categories, respectively, that had less than 100% relative quantification error. Relative to previous studies, errors in quantification estimates decreased, as did FN and FP rates, with improved DL90s for two of the four retested solutions. These findings highlight that continuous, rigorous testing enhances solution performance, with notable improvements observed across multiple testing programs using the same test protocol.

Standardized controlled testing of advanced methane detection technologies (solutions) has been identified as a step in demonstrating the emissions mitigation equivalence between these solutions and existing regulatory-approved leak detection and repair methods (e.g., ground-based optical gas imaging [OGI] camera survey) in the US and Canada. In this study, 12 solutions consisting of 4 handheld OGI cameras, 4 advanced handheld systems, and 4 mobile (automobile- and drone-based) solutions were tested under a single-blind controlled testing protocol at different periods between 2021 and 2023 at an outdoor test facility that simulates emissions from a simple, onshore North American production oil and gas (O&G) facility. Three solutions were tested again 3–12 months after the first test, using the same test protocol and facility to assess how performance changed over time. Results showed that handheld OGI cameras had comparable or better performance in terms of lower 90% probability of detection (DL90), false positive and negative fractions, and higher equipment unit-level localization performance compared to other categories of solutions tested. Advanced handheld solutions had comparable performance with the OGI cameras across all metrics except false positive fraction (much higher), while mobile solutions generally had shorter survey durations compared to other solutions. For solutions that tested twice, the performance of 2 of 3 solutions generally improved, illustrating the benefit of regular, comprehensive testing in the development of solutions. The different value propositions inferred from the various categories of solutions tested suggest that mobile solutions can rapidly survey larger areas to inform more targeted, follow-up inspections with handheld solutions. While advanced handheld solutions can be as effective as OGI cameras, mobile solutions have some difficulties to overcome to make them directly comparable or need to have a different use case.