Quantifying Regional Methane Emissions in the New Mexico Permian Basin with a Comprehensive Aerial Survey

Assessing the Progress of the Performance of Continuous Monitoring Solutions under a Single-Blind Controlled Testing Protocol

The recent regulatory spotlight on continuous monitoring (CM) solutions and the rapid development of CM solutions have demanded the characterization of solution performance through regular, rigorous testing using consensus test protocols. This study is the second known implementation of such a protocol involving single-blind controlled testing of 9 CM solutions. Controlled releases of rates (6-7100 g) CH4/h over durations (0.4-10.2 h) under a wind speed range of (0.7-9.9 m/s) were conducted for 11 weeks. Results showed that 4 solutions achieved method detection limits (DL90s) within the tested emission rate range, with all 4 solutions having both the lowest DL90s (3.9 [3.0, 5.5] kg CH4/h to 6.2 [3.7, 16.7] kg CH4/h) and false positive rates (6.9-13.2%), indicating efforts at balancing low sensitivity with a low false positive rate. These results are likely best-case scenario estimates since the test center represents a near-ideal upstream field natural gas operation condition. Quantification results showed wide individual estimate uncertainties, with emissions underestimation and overestimation by factors up to >14 and 42, respectively. Three solutions had >80% of their estimates within a quantification factor of 3 for controlled releases in the ranges of [0.1-1] kg CH4/h and > 1 kg CH4/h. Relative to the study by Bell et al., current solutions performance, as a group, generally improved, primarily due to solutions from the study by Bell et al. that were retested. This result highlights the importance of regular quality testing to the advancement of CM solutions for effective emissions mitigation.

Technological Maturity of Aircraft-Based Methane Sensing for Greenhouse Gas Mitigation

Methane is a major contributor to anthropogenic greenhouse gas emissions. Identifying large sources of methane, particularly from the oil and gas sectors, will be essential for mitigating climate change. Aircraft-based methane sensing platforms can rapidly detect and quantify methane point-source emissions across large geographic regions, and play an increasingly important role in industrial methane management and greenhouse gas inventory. We independently evaluate the performance of five major methane-sensing aircraft platforms: Carbon Mapper, GHGSat-AV, Insight M, MethaneAIR, and Scientific Aviation. Over a 6 week period, we released metered gas for over 700 single-blind measurements across all five platforms to evaluate their ability to detect and quantify emissions that range from 1 to over 1,500 kg(CH4)/h. Aircraft consistently quantified releases above 10 kg(CH4)/h, and GHGSat-AV and Insight M detected emissions below 5 kg(CH4)/h. Fully blinded quantification estimates for platforms using downward-facing imaging spectrometers have parity slopes ranging from 0.76 to 1.13, with R2 values of 0.61 to 0.93; the platform using continuous air sampling has a parity slope of 0.5 (R2 = 0.93). Results demonstrate that aircraft-based methane sensing has matured since previous studies and is ready for an increasingly important role in environmental policy and regulation.

Automatic detection of methane emissions in multispectral satellite imagery using a vision transformer

Curbing methane emissions is among the most effective actions that can be taken to slow down global warming. However, monitoring emissions remains challenging, as detection methods have a limited quantification completeness due to trade-offs that have to be made between coverage, resolution, and detection accuracy. Here we show that deep learning can overcome the trade-off in terms of spectral resolution that comes with multi-spectral satellite data, resulting in a methane detection tool with global coverage and high temporal and spatial resolution. We compare our detections with airborne methane measurement campaigns, which suggests that our method can detect methane point sources in Sentinel-2 data down to plumes of 0.01 km2, corresponding to 200 to 300 kg CH4 h-1 sources. Our model shows an order of magnitude improvement over the state-of-the-art, providing a significant step towards the automated, high resolution detection of methane emissions at a global scale, every few days.

Point Sensor Networks Struggle to Detect and Quantify Short Controlled Releases at Oil and Gas Sites

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.

Climate Impacts of Hydrogen and Methane Emissions Can Considerably Reduce the Climate Benefits across Key Hydrogen Use Cases and Time Scales

Recent investments in "clean" hydrogen as an alternative to fossil fuels are driven by anticipated climate benefits. However, most climate benefit calculations do not adequately account for all climate warming emissions and impacts over time. This study reanalyzes a previously published life cycle assessment as an illustrative example to show how the climate impacts of hydrogen deployment can be far greater than expected when including the warming effects of hydrogen emissions, observed methane emission intensities, and near-term time scales; this reduces the perceived climate benefits upon replacement of fossil fuel technologies. For example, for blue (natural gas with carbon capture) hydrogen pathways, the inclusion of upper-end hydrogen and methane emissions can yield an increase in warming in the near term by up to 50%, whereas lower-end emissions decrease warming impacts by at least 70%. For green (renewable-based electrolysis) hydrogen pathways, upper-end hydrogen emissions can reduce climate benefits in the near term by up to 25%. We also consider renewable electricity availability for green hydrogen and show that if it is not additional to what is needed to decarbonize the electric grid, there may be more warming than that seen with fossil fuel alternatives over all time scales. Assessments of hydrogen's climate impacts should include the aforementioned factors if hydrogen is to be an effective decarbonization tool.

Temporal Variation and Persistence of Methane Emissions from Shallow Water Oil and Gas Production in the Gulf of Mexico

Methane emissions from the oil and gas supply chain can be intermittent, posing challenges for monitoring and mitigation efforts. This study examines shallow water facilities in the US Gulf of Mexico with repeat atmospheric observations to evaluate temporal variation in site-specific methane emissions. We combine new and previous observations to develop a longitudinal study, spanning from days to months to almost five years, evaluating the emissions behavior of sites over time. We also define and determine the chance of subsequent detection (CSD): the likelihood that an emitting site will be observed emitting again. The average emitting central hub in the Gulf has a 74% CSD at any time interval. Eight facilities contribute 50% of total emissions and are over 80% persistent with a 96% CSD above 100 kg/h and 46% persistent with a 42% CSD above 1000 kg/h, indicating that large emissions are persistent at certain sites. Forward-looking infrared (FLIR) footage shows many of these sites exhibiting cold venting. This suggests that for offshore, a low sampling frequency over large spatial coverage can capture typical site emissions behavior and identify targets for mitigation. We further demonstrate the preliminary use of space-based observations to monitor offshore emissions over time.

US oil and gas system emissions from nearly one million aerial site measurements

As airborne methane surveys of oil and gas systems continue to discover large emissions that are missing from official estimates1-4, the true scope of methane emissions from energy production has yet to be quantified. We integrate approximately one million aerial site measurements into regional emissions inventories for six regions in the USA, comprising 52% of onshore oil and 29% of gas production over 15 aerial campaigns. We construct complete emissions distributions for each, employing empirically grounded simulations to estimate small emissions. Total estimated emissions range from 0.75% (95% confidence interval (CI) 0.65%, 0.84%) of covered natural gas production in a high-productivity, gas-rich region to 9.63% (95% CI 9.04%, 10.39%) in a rapidly expanding, oil-focused region. The six-region weighted average is 2.95% (95% CI 2.79%, 3.14%), or roughly three times the national government inventory estimate5. Only 0.05-1.66% of well sites contribute the majority (50-79%) of well site emissions in 11 out of 15 surveys. Ancillary midstream facilities, including pipelines, contribute 18-57% of estimated regional emissions, similarly concentrated in a small number of point sources. Together, the emissions quantified here represent an annual loss of roughly US$1 billion in commercial gas value and a US$9.3 billion annual social cost6. Repeated, comprehensive, regional remote-sensing surveys offer a path to detect these low-frequency, high-consequence emissions for rapid mitigation, incorporation into official emissions inventories and a clear-eyed assessment of the most effective emission-finding technologies for a given region.

The Role of Emission Size Distribution on the Efficacy of New Technologies to Reduce Methane Emissions from the Oil and Gas Sector

Methane emissions from oil and gas operations exhibit skewed distributions. New technologies such as aerial-based leak detection surveys promise cost-effective detection of large emitters (greater than 10 kg/h). Recent policies such as the US Environmental Protection Agency (EPA) methane rule that allow the use of new technologies as part of leak detection and repair (LDAR) programs require a demonstration of equivalence with existing optical gas imaging (OGI) based LDAR programs. In this work, we illustrate the impact of emission size distribution on the equivalency condition between the OGI and site-wide survey technologies. Emission size distributions compiled from aerial measurements include significantly more emitters between 1 and 10 kg/h and lower average emission rates for large emitters compared to the emission distribution in the EPA rule. As a result, we find that equivalence may be achieved at lower site-wide survey frequencies when using technologies with detection thresholds below 10 kg/h, compared to the EPA rule. However, equivalence cannot be achieved with a detection threshold of 30 kg/h at any survey frequency, because most emitters across most US basins exhibit emission rates below 30 kg/h. We find that equivalence is a complex tradeoff among technology choice, design of LDAR programs, and survey frequency that can have more than one unique solution set.

Extension of Methane Emission Rate Distribution for Permian Basin Oil and Gas Production Infrastructure by Aerial LiDAR

Aerial LiDAR measurements at 7474 oil and gas production facilities in the Permian Basin yield a measured methane emission rate distribution extending to the detection sensitivity of the method, 2 kg/h at 90% probability of detection (POD). Emissions are found at 38.3% of facilities scanned, a significantly higher proportion than reported in lower-sensitivity campaigns. LiDAR measurements are analyzed in combination with measurements of the heavy tail portion of the distribution (>600 kg/h) obtained from an airborne solar infrared imaging spectrometry campaign by Carbon Mapper (CM). A joint distribution is found by fitting the aligned LiDAR and CM data. By comparing the aerial samples to the joint distribution, the practical detection sensitivity of the CM 2019 campaign is found to be 280 kg/h [256, 309] (95% confidence) at 50% POD for facility-sized emission sources. With respect to the joint model distribution and its confidence interval, the LiDAR campaign is found to have measured 103.6% [93.5, 114.2%] of the total emission rate predicted by the model for equipment-sized emission sources (∼2 m diameter) with emission rates above 3 kg/h, whereas the CM 2019 campaign is found to have measured 39.7% [34.6, 45.1%] of the same quantity for facility-sized sources (150 m diameter) above 10 kg/h. The analysis is repeated with data from CM 2020-21 campaigns with similar results. The combined distributions represent a more comprehensive view of the emission rate distribution in the survey area, revealing the significance of previously underreported emission sources at rates below the detection sensitivity of some emissions monitoring campaigns.

Blue and green ammonia production: A techno-economic and life cycle assessment perspective

Blue and green ammonia production have been proposed as low-carbon alternatives to emissions-intensive conventional ammonia production. Although much attention has been given to comparing these alternatives, it is still not clear which process has better environmental and economic performance. We present a techno-economic analysis and full life cycle assessment to compare the economics and environmental impacts of blue and green ammonia production. We address the importance of time horizon in climate change impact comparisons by employing the Technology Warming Potential, showing that methane leakage can exacerbate the climate change impacts of blue ammonia in short time horizons. We represent a constrained renewable electricity availability scenario by comparing the climate change impact mitigation efficiency per kWh of renewable electricity. Our work emphasizes the importance of maintaining low natural gas leakage for sustainability of blue ammonia, and the potential for technological advances to further reduce the environmental impacts of photovoltaics-based green ammonia.

Toward Multiscale Measurement-Informed Methane Inventories: Reconciling Bottom-Up Site-Level Inventories with Top-Down Measurements Using Continuous Monitoring Systems

Government policies and corporate strategies aimed at reducing methane emissions from the oil and gas sector increasingly rely on measurement-informed, site-level emission inventories, as conventional bottom-up inventories poorly capture temporal variability and the heavy-tailed nature of methane emissions. This work is based on an 11-month methane measurement campaign at oil and gas production sites. We find that operator-level top-down methane measurements are lower during the end-of-project phase than during the baseline phase. However, gaps persist between end-of-project top-down measurements and bottom-up site-level inventories, which we reconcile with high-frequency data from continuous monitoring systems (CMS). Specifically, we use CMS to (i) validate specific snapshot measurements and determine how they relate to the temporal emission profile of a given site and (ii) create a measurement-informed, site-level inventory that can be validated with top-down measurements to update conventional bottom-up inventories. This work presents a real-world demonstration of how to reconcile CMS rate estimates and top-down snapshot measurements jointly with bottom-up inventories at the site level. More broadly, it demonstrates the importance of multiscale measurements when creating measurement-informed, site-level emission inventories, which is a critical aspect of recent regulatory requirements in the Inflation Reduction Act, voluntary methane initiatives such as the Oil and Gas Methane Partnership 2.0, and corporate strategies.

Tiered Leak Detection and Repair Programs at Simulated Oil and Gas Production Facilities: Increasing Emission Reduction by Targeting High-Emitting Sources

Distributions of methane emission rates originating from oil and gas production facilities are highly skewed and span 6-8 orders of magnitude. Traditional leak detection and repair programs have relied on surveys with handheld detectors at intervals of 2 to 4 times a year to find and fix emissions; however, this approach may lead unintended emissions to be active for the same interval independently of their magnitude. In addition, manual surveys are labor intensive. Novel methane detection technologies offer opportunities to further reduce emissions by quickly detecting the high-emitters, which account for a disproportionate fraction of total emissions. In this work, combinations of methane detection technologies with a focus of targeting high-emitting sources were simulated in a tiered approach for facilities representative of the Permian Basin, a region with skewed emission rates where emissions above 100 kg/h account for 40-80% of production site-wide total emissions, which include sensors on satellites, aircraft, continuous monitors, and optical gas imaging (OGI) cameras, with variations on survey frequency, detection thresholds, and repair times. Results show that strategies that quickly detect and fix high-emitting sources while decreasing the frequency of OGI inspections, which find the smaller emissions, achieve higher reductions than quarterly OGI and, in some cases, reduce emissions further than monthly OGI.

Cost and Life Cycle Emissions of Ethanol Produced with an Oxyfuel Boiler and Carbon Capture and Storage

Decarbonization of transportation fuels represents one of the most vexing challenges for climate change mitigation. Biofuels derived from corn starch have offered modest life cycle greenhouse gas (GHG) emissions reductions over fossil fuels. Here we show that capture and storage of CO₂ emissions from corn ethanol fermentation achieves ∼58% reduction in the GHG intensity (CI) of ethanol at a levelized cost of 52 $/tCO₂e abated. The integration of an oxyfuel boiler enables further CO₂ capture at modest cost. This system yields a 75% reduction in CI to 15 gCO₂e/MJ at a minimum ethanol selling price (MESP) of $2.24/gallon ($0.59/L), a $0.31/gallon ($0.08/L) increase relative to the baseline no intervention case. The levelized cost of carbon abatement is 84 $/tCO₂e. Sensitivity analysis reveals that carbon-neutral or even carbon-negative ethanol can be achieved when oxyfuel carbon capture is stacked with low-CI alternatives to grid power and fossil natural gas. Conservatively, fermentation and oxyfuel CCS can reduce the CI of conventional ethanol by a net 44-50 gCO₂/MJ. Full implementation of interventions explored in the sensitivity analysis would reduce CI by net 79-85 gCO₂/MJ. Integrated oxyfuel and fermentation CCS is shown to be cost-effective under existing U.S. policy, offering near-term abatement opportunities.

Single-blind validation of space-based point-source detection and quantification of onshore methane emissions

Satellites are increasingly seen as a tool for identifying large greenhouse gas point sources for mitigation, but independent verification of satellite performance is needed for acceptance and use by policy makers and stakeholders. We conduct to our knowledge the first single-blind controlled methane release testing of satellite-based methane emissions detection and quantification, with five independent teams analyzing data from one to five satellites each for this desert-based test. Teams correctly identified 71% of all emissions, ranging from 0.20 [0.19, 0.21] metric tons per hour (t/h) to 7.2 [6.8, 7.6] t/h. Three-quarters (75%) of quantified estimates fell within ± 50% of the metered value, comparable to airplane-based remote sensing technologies. The relatively wide-area Sentinel-2 and Landsat 8 satellites detected emissions as low as 1.4 [1.3, 1.5, 95% confidence interval] t/h, while GHGSat's targeted system quantified a 0.20 [0.19, 0.21] t/h emission to within 13%. While the fraction of global methane emissions detectable by satellite remains unknown, we estimate that satellite networks could see 19-89% of total oil and natural gas system emissions detected in a recent survey of a high-emitting region.

Origins of Oil and Gas Sector Methane Emissions: On-Site Investigations of Aerial Measured Sources

Success in reducing oil and gas sector methane emissions is contingent on understanding the sources driving emissions, associated options for mitigation, and the effectiveness of regulations in achieving intended outcomes. This study combines high-resolution, high-sensitivity aerial survey data with subsequent on-site investigations of detected sources to examine these points. Measurements were performed in British Columbia, Canada, an active oil- and gas-producing province with modern methane regulations featuring mandatory three times per year leak detection and repair (LDAR) surveys at most facilities. Derived emission factors enabled by source attribution show that significant methane emissions persist under this regulatory framework, dominated by (i) combustion slip (compressor exhaust and also catalytic heaters, which are not covered in current regulations), (ii) intentional venting (uncontrolled tanks, vent stacks or intentionally unlit flares, and uncontrolled compressors), and (iii) unintentional venting (controlled tanks, unintentionally unlit/blown out flares, and abnormally operating pneumatics). Although the detailed analysis shows mitigation options exist for all sources, the importance of combustion slip and the persistently large methane contributions from controlled tanks and unlit flares demonstrate the limits of current LDAR programs and the critical need for additional monitoring and verification if regulations are to have the intended impacts, and reduction targets of 75% and greater are to be met.

Reconciling Multiple Methane Detection and Quantification Systems at Oil and Gas Tank Battery Sites

Emission rates were estimated for >100 oil and gas production sites with significant liquid-handling equipment (tank battery sites) in the Permian Basin of west Texas. Emission estimates based on equipment counts and emission factors, but not accounting for large uninventoried emission events, led to ensemble average emission rates of 1.8-3.6 kg/h per site. None of the site-specific emission estimates for individual sites, based on equipment counts, exceeded 10 kg/h. On-site drone-based emission measurements led to similar emission estimates for inventoried sources. Multiple aircraft measurement platforms were deployed and reported emissions exceeding 10 kg/h at 14-27% of the sites, and these high-emission rate sites accounted for 80-90% of total emissions for the ensemble of sites. The aircraft measurement systems were deployed asynchronously but within a 5 day period. At least half of the sites with emission rates above 10 kg/h detected by aircraft had emissions that did not persist at a level above 10 kg/h for repeat measurements, suggesting typical high-emission rate durations of a few days or less for many events. The two aircraft systems differed in their estimates of total emissions from the ensembles of sites sampled by more than a factor of 2; however, the normalized distributions of emissions for sites with emission rates of >10 kg/h were comparable for the two aircraft-based methods. The differences between the two aircraft-based platforms are attributed to a combination of factors; however, both aircraft-based emission measurement systems attribute a large fraction of emissions to sites with an emission rate of >10 kg/h.

Methane Emissions from Natural Gas Gathering Pipelines in the Permian Basin

The rapid reduction of methane emissions, especially from oil and gas (O&G) operations, is a critical part of slowing global warming. However, few studies have attempted to specifically characterize emissions from natural gas gathering pipelines, which tend to be more difficult to monitor on the ground than other forms of O&G infrastructure. In this study, we use methane emission measurements collected from four recent aerial campaigns in the Permian Basin, the most prolific O&G basin in the United States, to estimate a methane emission factor for gathering lines. From each campaign, we calculate an emission factor between 2.7 (+1.9/-1.8, 95% confidence interval) and 10.0 (+6.4/-6.2) Mg of CH₄ year^-1 km^-1, 14-52 times higher than the U.S. Environmental Protection Agency's national estimate for gathering lines and 4-13 times higher than the highest estimate derived from a published ground-based survey of gathering lines. Using Monte Carlo techniques, we demonstrate that aerial data collection allows for a greater sample size than ground-based data collection and therefore more comprehensive identification of emission sources that comprise the heavy tail of methane emissions distributions. Our results suggest that pipeline emissions are underestimated in current inventories and highlight the importance of a large sample size when calculating basinwide pipeline emission factors.

Reduction of Signal Drift in a Wavelength Modulation Spectroscopy-Based Methane Flux Sensor

Accurately quantifying unsteady methane venting from key oil and gas sector sources such as storage tanks and well casing vents is a critical challenge. Recently, we presented an optical sensor to meet this need that combines volume fraction and Doppler shift measurements using wavelength modulation spectroscopy with 2f harmonic detection to quantify mass flux of methane through a vent line. This paper extends the previous effort through a methodical component-by-component investigation of potential sources of thermally-induced measurement drift to guide the design of an updated sensor. Test data were analyzed using an innovative signal processing technique that permitted quantification of background wavelength modulation spectroscopy signal drift linked to specific components, and the results were successfully used to design a drift-resistant sensor. In the updated sensor, background signal strength was reduced, and stability improved, such that the empirical methane-fraction dependent velocity correction necessary in the original sensor was no longer required. The revised sensor improves previously reported measurement uncertainties on flow velocity from 0.15 to 0.10 m/s, while markedly reducing thermally-induced velocity drift from 0.44 m/s/K to 0.015 m/s/K. In the most general and challenging application, where both flow velocity and methane fraction are independently varying, the updated design reduces the methane mass flow rate uncertainty by more than a factor of six, from ±2.55 kg/h to ±0.40 kg/h. This new design also maintains the intrinsic safety of the original sensor and is ideally suited for unsteady methane vent measurements within hazardous locations typical of oil and gas facilities.