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.

Large-Scale Controlled Experiment Demonstrates Effectiveness of Methane Leak Detection and Repair Programs at Oil and Gas Facilities.

Most jurisdictions around the globe use leak detection and repair (LDAR) programs to find and fix methane leaks from oil and gas operations. In this work, we empirically evaluate the efficacy of LDAR programs using a large-scale, bottom-up, randomized controlled field experiment across ∼200 oil and gas sites in Red Deer, Canada. We find that tanks are the single largest source of emissions, contributing to nearly 60% of the total emissions. The average number of leaks at treatment sites that underwent repair reduced by ∼50% compared to the control sites. Although control sites did not see a reduction in the number of leaks, emissions reduced by approximately 36%, suggesting potential impact of routine maintenance activities to find and fix large leaks. By tracking tags on leaking equipment over time, we find a high degree of persistence; leaks that are repaired remain fixed in follow-up surveys, while non-repaired leaks remain emitting at a similar rate, suggesting that any increase in observed leak emissions following LDAR surveys are likely from new leaks. Our results show that a focus on equipment and sites that are prone to high emissions, such as tanks and oil sites, is key to cost-effective mitigation.

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.

Pipeline Availability Limits on the Feasibility of Global Coal-to-Gas Switching in the Power Sector.

Coal-to-gas switching in the power sector, as happening in the U.S., has been a key driver of near-term greenhouse gas emissions reductions. Can this success be replicated around the world? Here, we explore the limits of a global, plant-level, coal-to-gas transition arising from pipeline availability constraints. Globally, only 43% of coal capacity is within 14 km of a nearby pipeline, the median distance for recent coal-to-gas conversions. Furthermore, plant-to-pipeline distance distributions vary widely-only 30% of coal capacity in India is within 14 km of a nearby pipeline. Most global coal fleets are in the intermediate space of balancing two competing interests-having a young coal fleet with high "avoided" emissions potential through coal-to-gas switching but without access to low-cost gas resources. A global stocktake based on coal fleet age, pipeline access, and natural gas supply security suggests that a coal-to-gas transition in the power sector is unlikely to be a universal climate solution.

Multiscale Methane Measurements at Oil and Gas Facilities Reveal Necessary Frameworks for Improved Emissions Accounting.

Methane mitigation from the oil and gas (O&G) sector represents a key near-term global climate action opportunity. Recent legislation in the United States requires updating current methane reporting programs for oil and gas facilities with empirical data. While technological advances have led to improvements in methane emissions measurements and monitoring, the overall effectiveness of mitigation strategies rests on quantifying spatially and temporally varying methane emissions more accurately than the current approaches. In this work, we demonstrate a quantification, monitoring, reporting, and verification framework that pairs snapshot measurements with continuous emissions monitoring systems (CEMS) to reconcile measurements with inventory estimates and account for intermittent emission events. We find that site-level emissions exhibit significant intraday and daily emission variations. Snapshot measurements of methane can span over 3 orders of magnitude and may have limited application in developing annualized inventory estimates at the site level. Consequently, while official inventories underestimate methane emissions on average, emissions at individual facilities can be higher or lower than inventory estimates. Using CEMS, we characterize distributions of frequency and duration of intermittent emission events. Technologies that allow high sampling frequency such as CEMS, paired with a mechanistic understanding of facility-level events, are key to an accurate accounting of short-duration, episodic, and high-volume events that are often missed in snapshot surveys and to scale snapshot measurements to annualized emissions estimates.

New Technologies Can Cost Effectively Reduce Oil and Gas Methane Emissions, but Policies Will Require Careful Design to Establish Mitigation Equivalence.

Reducing methane emissions from oil and gas systems is a central component of US and international climate policy. Leak detection and repair (LDAR) programs using optical gas imaging (OGI)-based surveys are routinely used to mitigate fugitive emissions or leaks. Recently, new technologies and platforms such as planes, drones, and satellites promise more cost-effective mitigation than existing approaches. To be approved for use in LDAR programs, new technologies must demonstrate emissions mitigation equivalent to existing approaches. In this work, we use the FEAST modeling tool to (a) identify cost vs mitigation trade-offs that arise from using new technologies and (b) provide a framework for effective design of alternative LDAR programs. We identify several critical insights. First, LDAR programs can trade sensitivity for speed without sacrificing mitigation outcomes. Second, low sensitivity or high detection threshold technologies have an effective upper bound on achievable mitigation that is independent of the survey frequency. Third, the cost effectiveness of tiered LDAR programs using site-level detection technologies depends on their ability to distinguish leaks from routine venting. Finally, "technology equivalence" based on mitigation outcomes differs across basins and should be evaluated independently. The FEAST model will enable operators and regulators to systematically evaluate new technologies in next-generation LDAR programs.

Greenhouse Gas Emissions of Western Canadian Natural Gas: Proposed Emissions Tracking for Life Cycle Modeling.

Natural gas (NG) produced in Western Canada is a major and growing source of Canada's energy and greenhouse gas (GHG) emissions portfolio. Despite recent progress, there is still only limited understanding of the sources and drivers of Western Canadian greenhouse gas (GHG) emissions. We conduct a case study of a production facility based on Seven Generation Energy Ltd.'s Western Canadian operations and an upstream NG emissions intensity model. The case study upstream emissions intensity is estimated to be 3.1-4.0 gCO2e/MJ NG compared to current best estimates of British Columbia (BC) emissions intensities of 6.2-12 gCO2e/MJ NG and a US average estimate of 15 gCO2e/MJ. The analysis reveals that compared to US studies, public GHG emissions data for Western Canada is insufficient as current public data satisfies only 50% of typical LCA model inputs. Company provided data closes most of these gaps (∼80% of the model inputs). We recommend more detailed data collection and presentation of government reported data such as a breakdown of vented and fugitive methane emissions by source. We propose a data collection template to facilitate improved GHG emissions intensity estimates and insight about potential mitigation strategies.

"Good versus Good Enough?" Empirical Tests of Methane Leak Detection Sensitivity of a Commercial Infrared Camera.

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 CH4/h at an imaging distance of 6 m, an order of magnitude higher than previously reported estimates of 1.4 g CH4/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 CH4/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.

Are Optical Gas Imaging Technologies Effective For Methane Leak Detection?

Concerns over mitigating methane leakage from the natural gas system have become ever more prominent in recent years. Recently, the U.S. Environmental Protection Agency proposed regulations requiring use of optical gas imaging (OGI) technologies to identify and repair leaks. In this work, we develop an open-source predictive model to accurately simulate the most common OGI technology, passive infrared (IR) imaging. The model accurately reproduces IR images of controlled methane release field experiments as well as reported minimum detection limits. We show that imaging distance is the most important parameter affecting IR detection effectiveness. In a simulated well-site, over 80% of emissions can be detected from an imaging distance of 10 m. Also, the presence of "superemitters" greatly enhance the effectiveness of IR leak detection. The minimum detectable limits of this technology can be used to selectively target "superemitters", thereby providing a method for approximate leak-rate quantification. In addition, model results show that imaging backdrop controls IR imaging effectiveness: land-based detection against sky or low-emissivity backgrounds have higher detection efficiency compared to aerial measurements. Finally, we show that minimum IR detection thresholds can be significantly lower for gas compositions that include a significant fraction nonmethane hydrocarbons.

Wavelength independent normal incident quantum cascade detectors.

We demonstrate a novel technique for normal-incident absorption in intersubband infrared detectors by taking advantage of light scattering from the side-walls of a wet-etched mesa. We fabricate 'spiral' and 'hairpin' shaped quantum cascade detector at a peak wavelength of 6.6 µm, and compare their performance with a standard rectangular mesa. We achieve a peak responsivity of 6 mA/W for the spiral and 12 mA/W for the hairpin detectors at normal incidence, comparable to the 8.8 mA/W obtained for the mesa at 45 degree incidence. We obtain a background limited detectivity of about 3×1010 cmHz/W for the spiral and hairpin detectors at 80 K, compared to 3×108 cmHz/W for the standard mesa. This method to achieve normal incidence absorption is wavelength independent, and does not involve complicated fabrication procedures, paving the way for widespread use of intersubband detectors in sensor applications.

Comparing Natural Gas Leakage Detection Technologies Using an Open-Source "Virtual Gas Field" Simulator.

We present a tool for modeling the performance of methane leak detection and repair programs that can be used to evaluate the effectiveness of detection technologies and proposed mitigation policies. The tool uses a two-state Markov model to simulate the evolution of methane leakage from an artificial natural gas field. Leaks are created stochastically, drawing from the current understanding of the frequency and size distributions at production facilities. Various leak detection and repair programs can be simulated to determine the rate at which each would identify and repair leaks. Integrating the methane leakage over time enables a meaningful comparison between technologies, using both economic and environmental metrics. We simulate four existing or proposed detection technologies: flame ionization detection, manual infrared camera, automated infrared drone, and distributed detectors. Comparing these four technologies, we found that over 80% of simulated leakage could be mitigated with a positive net present value, although the maximum benefit is realized by selectively targeting larger leaks. Our results show that low-cost leak detection programs can rely on high-cost technology, as long as it is applied in a way that allows for rapid detection of large leaks. Any strategy to reduce leakage should require a careful consideration of the differences between low-cost technologies and low-cost programs.

II-VI Quantum Cascade emitters in the 6-8µm range.

We present the growth and characterization of ZnCdSe/ZnCdMgSe quantum cascade (QC) heterostructures grown by molecular beam epitaxy (MBE) and designed to operate at 6-8µm. These structures utilize the better-understood ZnCdMgSe with InP lattice matched compositions yielding a bandgap of 2.80 eV as compared to previous work which used ZnCdMgSe compositions with bandgaps at 3.00 eV. Grown structures posses good structural and optical properties evidenced in X-ray diffraction and photoluminescence studies. Fabricated mesa devices show temperature dependent I-V measurements with differential resistance of 3.6 Ω, and a turn on voltage of 11V consistent with design specifications. Electroluminescence was observed in these devices up to room temperature with emission centered at 7.1 µm and line widths of ∼16%(ΔE/E) at 80K. The results show that these are well-behaved electroluminescent structures. Addition of waveguide layers and further improvements in well barrier interfaces are being pursued in efforts to demonstrate lasing.

ZnCdSe/ZnCdMgSe quantum well infrared photodetector.

We report the design, fabrication and characterization of a II-VI Zn(0.51)Cd(0.49)Se / Zn_{0.45(Cd)0.42(Mg)(0.13)Se-based quantum well infrared photodetector (QWIP) with a bound to quasi-bound transition centered at 8.7 µm. The good growth quality of the epitaxial layers was verified by x-ray diffraction measurements. Absorption and photocurrent measurements yield results consistent with conventional III-V QWIPs. Photocurrent measurements reveal an exponential decrease with temperature. In addition, we also observe more than 4 orders of magnitude increase in photocurrent with applied bias. By compensating the drop in temperature performance with an increase in applied bias, we achieve an operating temperature of up to 140K and a responsivity of 1-10 µA/W.}

The US role in securing the European Union's near-term natural gas supply.

The European Union's plan to phase out Russian natural gas imports by 2027 rests partly on increasing near-term imports of US liquefied natural gas. This will require a coordinated policy response that includes securing supplies from major exporters, global diplomacy, expanding import capacity, and alignment with Europe's climate goals.

Closing the methane gap in US oil and natural gas production emissions inventories.

Methane (CH4) emissions from oil and natural gas (O&NG) systems are an important contributor to greenhouse gas emissions. In the United States, recent synthesis studies of field measurements of CH4 emissions at different spatial scales are ~1.5-2× greater compared to official greenhouse gas inventory (GHGI) estimates, with the production-segment as the dominant contributor to this divergence. Based on an updated synthesis of measurements from component-level field studies, we develop a new inventory-based model for CH4 emissions, for the production-segment only, that agrees within error with recent syntheses of site-level field studies and allows for isolation of equipment-level contributions. We find that unintentional emissions from liquid storage tanks and other equipment leaks are the largest contributors to divergence with the GHGI. If our proposed method were adopted in the United States and other jurisdictions, inventory estimates could better guide CH4 mitigation policy priorities.

Phased-array sources based on nonlinear metamaterial nanocavities.

Coherent superposition of light from subwavelength sources is an attractive prospect for the manipulation of the direction, shape and polarization of optical beams. This phenomenon constitutes the basis of phased arrays, commonly used at microwave and radio frequencies. Here we propose a new concept for phased-array sources at infrared frequencies based on metamaterial nanocavities coupled to a highly nonlinear semiconductor heterostructure. Optical pumping of the nanocavity induces a localized, phase-locked, nonlinear resonant polarization that acts as a source feed for a higher-order resonance of the nanocavity. Varying the nanocavity design enables the production of beams with arbitrary shape and polarization. As an example, we demonstrate two second harmonic phased-array sources that perform two optical functions at the second harmonic wavelength (∼5 µm): a beam splitter and a polarizing beam splitter. Proper design of the nanocavity and nonlinear heterostructure will enable such phased arrays to span most of the infrared spectrum.