Constructing a Spatially Resolved Methane Emission Inventory for the Barnett Shale Region

Methods for Spatial Extrapolation of Methane Measurements in Constructing Regional Estimates from Sample Populations

Methane emission estimates for oil and gas facilities are typically based on estimates at a subpopulation of facilities, and these emission estimates are then extrapolated to a larger region or basin. Basin-level emission estimates are then frequently compared with basin-level observations. Methane emissions from oil and gas systems are inherently variable and intermittent, which make it difficult to determine whether a sample population is sufficiently large to be representative of a larger region. This work develops a framework for extrapolation of emission estimates using the case study of an operator in the Green River Basin. This work also identifies a new metric, the capture ratio, which quantifies the extent to which sources are represented in the sample population, based on the skewness of emissions for each source. There is a strong correlation between the capture ratio and extrapolation error, which suggests that understanding source-level emissions distributions can mitigate error when sample populations are selected and extrapolating measurements. The framework and results from this work can inform the selection and extrapolation of site measurements when developing methane emission inventories and establishing uncertainty bounds to assess whether inventory estimates are consistent with independent large spatial-scale observations.

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.

Assessing the Relative Importance of Satellite-Detected Methane Superemitters in Quantifying Total Emissions for Oil and Gas Production Areas in Algeria

Methane emissions from oil and gas production provide an important contribution to global warming. We investigate 2020 emissions from the largest gas field in Algeria, Hassi R'Mel, and the oil-production-dominated area Hassi Messaoud. We use methane data from the high-resolution (20 m) Sentinel-2 instruments to identify and estimate emission time series for 11 superemitters (including 10 unlit flares). We integrate this information in a transport model inversion that uses methane data from the coarser (7 km × 5.5 km) but higher-precision TROPOMI instrument to estimate emissions from both the 11 superemitters (>1 t/h individually) and the remaining diffuse area source (not detected as point sources with Sentinel-2). Compared to a bottom-up inventory for 2019 that is aligned with UNFCCC-reported emissions, we find that 2020 emissions in Hassi R'Mel (0.16 [0.11-0.22] Tg/yr) are lower by 53 [24-73]%, and emissions in Hassi Messaoud (0.22 [0.13-0.28] Tg/yr) are higher by 79 [4-188]%. Our analysis indicates that a larger fraction of Algeria's methane emissions (∼75%) come from oil production than national reporting suggests (5%). Although in both regions the diffuse area source constitutes the majority of emissions, relatively few satellite-detected superemitters provide a significant contribution (24 [12-40]% in Hassi R'Mel; 49 [27-71]% in Hassi Messaoud), indicating that mitigation efforts should address both. Our synergistic use of Sentinel-2 and TROPOMI can produce a unique and detailed emission characterization of oil and gas production areas.

Reconciling a national methane emission inventory with in-situ measurements

Reconciling top-down and bottom-up country-level greenhouse gas emission estimates remains a key challenge in the MRV (Monitoring, Reporting, Verification) paradigm. Here we propose to independently quantify cumulative emissions from a significant number of methane (CH4) emitters at national level and derive robust constraints for the national inventory. Methane emissions in Cyprus, an insular country, stem primarily from waste and agricultural activities. We performed 24 intensive survey days of mobile measurements of CH4 from October 2020 to September 2021 at emission 'hotspots' in Cyprus accounting together for about 28 % of national CH4 emissions. The surveyed areas include a large active landfill (Koshi, 8 % of total emissions), a large closed landfill (Kotsiatis, 18 %), and a concentrated cattle farm area (Aradippou, 2 %). Emission rates for each site were estimated using repeated downwind transects and a Gaussian plume dispersion model. The calculated methane emissions from landfills of Koshi and Kotsiatis (25.9 ± 6.4 Gg yr-1) and enteric fermentation of cattle (10.4 ± 4.4 Gg yr-1) were about 129 % and 40 % larger, respectively than the bottom-up sectorial annual estimates used in the national UNFCCC inventory. The parametrization of the Gaussian plume model dominates the uncertainty in our method, with a typical 21 % uncertainty. Seasonal variations have little influence on the results. We show that using an ensemble of in situ measurements targeting representative methane emission hotspots with consistent temporal and spatial coverage can contribute to the monitoring and validation of national bottom-up emission inventories.

A Gridded Inventory of Annual 2012-2018 U.S. Anthropogenic Methane Emissions

Nationally reported greenhouse gas inventories are a core component of the Paris Agreement's transparency framework. Comparisons with emission estimates derived from atmospheric observations help identify improvements to reduce uncertainties and increase the confidence in reported values. To facilitate comparisons over the contiguous United States, we present a 0.1° × 0.1° gridded inventory of annual 2012-2018 anthropogenic methane emissions, allocated to 26 individual source categories, with scale-dependent error estimates. Our inventory is consistent with the U.S. Environmental Protection Agency (EPA) Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI), submitted to the United Nations in 2020. Total emissions and patterns (spatial/temporal) reflect the activity and emission factor data underlying the GHGI, including many updates relative to a previous gridded version of the GHGI that has been extensively compared with observations. These underlying data are not generally available in global gridded inventories, and comparison to EDGAR version 6 shows large spatial differences, particularly for the oil and gas sectors. We also find strong regional variability across all sources in annual 2012-2018 spatial trends, highlighting the importance of understanding regional- and facility-level activities. Our inventory represents the first time series of gridded GHGI methane emissions and enables robust comparisons of emissions and their trends with atmospheric observations.

Informing Methane Emissions Inventories Using Facility Aerial Measurements at Midstream Natural Gas Facilities

Increased interest in greenhouse gas (GHG) emissions, including recent legislative action and voluntary programs, has increased attention on quantifying and ultimately reducing methane emissions from the natural gas supply chain. While inventories used for public or corporate GHG policies have traditionally utilized bottom-up (BU) methods to estimate emissions, the validity of such inventories has been questioned. Therefore, there is attention on utilizing full-facility measurements using airborne, satellite, or drone (top-down (TD)) techniques to inform, improve, or validate inventories. This study utilized full-facility estimates from two independent TD methods at 15 midstream natural gas facilities in the U.S.A., which were compared with a contemporaneous daily inventory assembled by the facility operator, employing comprehensive inventory methods. Estimates from the two TD methods statistically agreed in 2 of 28 paired measurements. Operator inventories, which included extensions to capture sources beyond regular inventory requirements and integration of local measurements, estimated significantly lower emissions than the TD estimates for 40 of 43 paired comparisons. Significant disagreement was observed at most facilities, both between the two TD methods and between the TD estimates and operator inventory. These findings have two implications. First, improving inventory estimates will require additional on-site or ground-based diagnostic screening and measurement of all sources. Second, the TD full-facility measurement methods need to undergo further testing, characterization, and potential improvement specifically tailored for complex midstream facilities.

Quantification of natural gas and other hydrocarbons from production sites in northern West Virginia using tracer flux ratio methodology

Tracer flux ratio (TFR) methodology performed downwind of 15 active oil and natural gas production sites in Ohio County, West Virginia sought to quantify air pollutant emissions over two weeks in April 2018. In coordination with a production company, sites were randomly selected depending on wind forecasts and nearby road access. Methane (CH4), ethane (C2H6), and tracer gas compounds (acetylene and nitrous oxide) were measured via tunable infrared direct absorption spectroscopy. Ion signals attributed to benzene (C6H6) and other volatile gases (e.g., C7 - C9 aromatics) were measured via proton-transfer reaction time-of-flight mass spectrometry. Short-term whole facility emission rates for 12 sites are reported. Results from TFR were systematically higher than the sum of concurrent on-site full flow sampler measurements, though not all sources were assessed on-site in most cases. In downwind plumes, the mode of the C2H6:CH4 molar ratio distribution for all sites was 0.2, which agreed with spot sample analysis from the site operator. Distribution of C6H6:CH4 ratios was skew but values between 1 and 5 pptv ppbv-1 were common. Additionally, the aromatic profile has been attributed to condensate storage tank emissions. Average ratios of C7 - C9 to C6H6 were similar to other literature values reported for natural gas wells.

Recent Advances Toward Transparent Methane Emissions Monitoring: A Review

Given that anthropogenic greenhouse gas (GHG) emissions must be immediately reduced to avoid drastic increases in global temperature, methane emissions have been placed center stage in the fight against climate change. Methane has a significantly larger warming potential than carbon dioxide. A large percentage of methane emissions are in the form of industry emissions, some of which can now be readily identified and mitigated. This review considers recent advances in methane detection that allow accurate and transparent monitoring, which are needed for reducing uncertainty in source attribution and evaluating progress in emissions reductions. A particular focus is on complementary methods operating at different scales with applications for the oil and gas industry, allowing rapid detection of large point sources and addressing inconsistencies of emissions inventories. Emerging airborne and satellite imaging spectrometers are advancing our understanding and offer new top-down assessment methods to complement bottom-up methods. Successfully merging estimates across scales is vital for increased certainty regarding greenhouse gas emissions and can inform regulatory decisions. The development of comprehensive, transparent, and spatially resolved top-down and bottom-up inventories will be crucial for holding nations accountable for their climate commitments.

Evaluating the detectability of methane point sources from satellite observing systems using microscale modeling

This study evaluates the efficacy of current satellite observing systems to detect methane point sources from typical oil and gas production (O&G) facilities using a novel very high-resolution methane concentration dataset generated using a microscale model. Transport and dispersion of typical methane emissions from seven well pads were simulated and the column enhancements for pseudo satellite pixel sizes of 3, 1, and 0.05 km were examined every second of the 2-h simulations (7200 realizations). The detectability of plumes increased with a pixel resolution, but two orders of magnitude change in emission rates at the surface results only in about 0.4%, 1.6%, and 47.8% enhancement in the pseudo-satellite retrieved methane column at 3, 1, and 0.05 km, respectively. Average methane emission rates estimated by employing the integrated mass enhancement (IME) method to column enhancements at 0.05 km showed an underestimation of the mean emissions by 0.2-6.4%. We show that IME derived satellite-based inversions of methane emissions work well for large persistent emission sources (e.g., super emitters), however, the method is ill-suited to resolve short-term emission fluctuations (< 20 min) in typical well site emissions due to the limitations in satellite detection limits, precision, overpass timing, and pixel resolution.

Methane emissions from US low production oil and natural gas well sites

Eighty percent of US oil and natural gas (O&G) production sites are low production well sites, with average site-level production ≤15 barrels of oil equivalent per day and producing only 6% of the nation's O&G output in 2019. Here, we integrate national site-level O&G production data and previously reported site-level CH4 measurement data (n = 240) and find that low production well sites are a disproportionately large source of US O&G well site CH4 emissions, emitting more than 4 (95% confidence interval: 3-6) teragrams, 50% more than the total CH4 emissions from the Permian Basin, one of the world's largest O&G producing regions. We estimate low production well sites represent roughly half (37-75%) of all O&G well site CH4 emissions, and a production-normalized CH4 loss rate of more than 10%-a factor of 6-12 times higher than the mean CH4 loss rate of 1.5% for all O&G well sites in the US. Our work suggests that achieving significant reductions in O&G CH4 emissions will require mitigation of emissions from low production well sites.

Tropical methane emissions explain large fraction of recent changes in global atmospheric methane growth rate

Large variations in the growth of atmospheric methane, a prominent greenhouse gas, are driven by a diverse range of anthropogenic and natural emissions and by loss from oxidation by the hydroxyl radical. We used a decade-long dataset (2010–2019) of satellite observations of methane to show that tropical terrestrial emissions explain more than 80% of the observed changes in the global atmospheric methane growth rate over this period. Using correlative meteorological analyses, we show strong seasonal correlations (r = 0.6–0.8) between large-scale changes in sea surface temperature over the tropical oceans and regional variations in methane emissions (via changes in rainfall and temperature) over tropical South America and tropical Africa. Existing predictive skill for sea surface temperature variations could therefore be used to help forecast variations in global atmospheric methane.

Methane is a powerful greenhouse gas with emissions that are challenging to constrain. Here the authors use 10 years of satellite observations and show tropical terrestrial emissions account for 80% of observed global methane increases.

Spatiotemporal Graph Convolution Multifusion Network for Urban Vehicle Emission Prediction

Urban vehicle emission prediction can help the regulation of vehicle pollution and traffic control. However, it is hard to predict the spatiotemporal variation of vehicle emission because of the spatial interactions and temporal correlations between different road segments as well as the high nonlinearity and complexity of vehicle emission variation. The existing methods solve the problem by splitting the region into standard segments or grids based on conventional deep learning methods, without considering that urban vehicle emission varies by graph-structured traffic road network and depends on many complex external environment factors. To address these issues, a spatiotemporal graph convolution multifusion network (ST-MFGCN) is proposed to leverage the graph structural properties as the inherent connectivity of road network for urban vehicle emission prediction, which can capture the vehicle emission spatiotemporal variation patterns and learn the effects of complex environmental factors. The proposed model consists of three parts: 1) a spatiotemporal graph convolution module to capture spatiotemporal dependencies by merging closeness, period, and trend sequences with temporal convolution as well as graph convolution is introduced to model the spatial dependencies; 2) an external factor component to divide multisource external factors into global and individual external features; and 3) a general fusion component to merge the spatiotemporal patterns and the external features as well as fit the mutation of emission measurement data by multifusion strategy. Finally, the proposed model is evaluated on the practical monitoring data of vehicle emission data in Hefei, and the results demonstrate that our proposed model can predict regional vehicle emissions effectively.

Coupled Air Quality and Boundary-Layer Meteorology in Western U.S. Basins during Winter: Design and Rationale for a Comprehensive Study

Wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical-meteorological interactions that drive high pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in Western U.S. basins. Approximately 120 people participated, representing 50 institutions and 5 countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary-layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological-chemical linkages outlined here, nor to validate complex processes within coupled atmosphere-chemistry models.

Satellite-based survey of extreme methane emissions in the Permian basin

Industrial emissions play a major role in the global methane budget. The Permian basin is thought to be responsible for almost half of the methane emissions from all U.S. oil- and gas-producing regions, but little is known about individual contributors, a prerequisite for mitigation. We use a new class of satellite measurements acquired during several days in 2019 and 2020 to perform the first regional-scale and high-resolution survey of methane sources in the Permian. We find an unexpectedly large number of extreme point sources (37 plumes with emission rates >500 kg hour^-1), which account for a range between 31 and 53% of the estimated emissions in the sampled area. Our analysis reveals that new facilities are major emitters in the area, often due to inefficient flaring operations (20% of detections). These results put current practices into question and are relevant to guide emission reduction efforts.

Projecting the Temporal Evolution of Methane Emissions from Oil and Gas Production Basins

The methane emission intensity (methane emitted/gas produced or methane emitted/methane produced) of individual unconventional oil and gas production sites in the United States has a characteristic temporal behavior, exhibiting a brief period of decrease followed by a steady increase, with intensities after 10 years of production reaching levels that are 2-10 times the 10 year production-weighted average. Temporal patterns for methane emission intensity for entire production regions are more complex. Historical production data and facility data were used with a detailed basin-wide methane emission model to simulate the collective behavior of tens of thousands of wells and associated midstream facilities. For production regions with few to no new wells being brought to production, and existing wells having reached a mature stage, as in the Barnett Shale production region in north central Texas, the methane emission intensity gradually increases, as natural gas production decreases faster than emissions decrease, following the general pattern exhibited by individual wells. In production regions that are rapidly evolving, either with large numbers of new wells being put into production or with the introduction of source-specific regulations, the behavior is more complex. In the Eagle Ford Shale, which has had both a large number of new wells and the introduction of source-specific regulations, the methane emission intensity stays within relatively narrow bounds but the distribution of sources varies. As source distributions vary, basin-wide propane-to-methane and ethane-to-methane emission ratios vary, impacting methods used in source attribution.

Methane Exhaust Measurements at Gathering Compressor Stations in the United States

Unburned methane entrained in exhaust from natural gas-fired compressor engines ("combustion slip") can account for a substantial portion of station-level methane emissions. A novel in-stack, tracer gas method was coupled with Fourier transform infrared (FTIR) species measurements to quantify combustion slip from natural gas compressor engines at 67 gathering and boosting stations owned or managed by nine "study partner" operators in 11 U.S. states. The mean methane emission rate from 63 four-stroke, lean-burn (4SLB) compressor engines was 5.62 kg/h (95% CI = 5.15-6.17 kg/h) and ranged from 0.3 to 12.6 kg/h. The mean methane emission rate from 39 four-stroke, rich-burn (4SRB) compressor engines was 0.40 kg/h (95% CI = 0.37-0.42 kg/h) and ranged from 0.01 to 4.5 kg/h. Study results for 4SLB engines were lower than both the U.S. EPA compilation of air pollutant emission factors (AP-42) and Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI) by 8 and 9%, respectively. Study results for 4SRB engines were 43% of the AP-42 emission factor and 8% of the GHGI emission factor, the latter of which does not distinguish between engine types. Total annual combustion slip from the U.S. natural gas gathering and boosting sector was modeled using measured emission rates and compressor unit counts from the U.S. EPA Greenhouse Gas Reporting Program. Modeled results [328 Gg/y (95% CI = 235-436 Gg/y) of unburned methane] would account for 24% (95% CI = 17-31%) of the 1391 Gg of methane emissions for "Gathering and Boosting Stations", or 6% of the net emissions for "Natural Gas Systems" (5598 Gg) as reported in the 2020 U.S. EPA GHGI. Gathering and boosting combustion slip emissions reported in the 2020 GHGI (374 Gg) fall within the uncertainty of this model.

Hazardous substances as the dominant non-methane volatile organic compounds with potential emissions from liquid storage tanks during well fracturing: A modeling approach

Chemical additives used in hydraulic fracturing fluids (HFFs) are made up of various organic compounds that are potential human carcinogens. To estimate the emissions from these organic constituents in on-site liquid storage tanks, studies were performed using the AP-42 model on data collected from 72,023 wells put into production using hydraulic fracturing between 2008 and 2014 in the United States. Results show that a total of 8.11 × 10⁵ kg volatile organic compounds (VOCs) were potentially emitted from liquid storage tanks during fracturing operations, which was relatively low compared to other sources/activities in well fracturing. The median well emission roughly increased from 0.110 to 0.786 kg per well in 2008 and 2014, respectively, and was primarily due to the increase in the volume of chemical additives for fracturing one well. Of NMVOC emissions, 95.1% was contributed by 60 compounds listed on the priority list of hazardous substances defined by the Agency for Toxic Substances & Disease Registry (ATSDR), while 16.7% was caused by 15 carcinogenic compounds. Specially, methanol, formaldehyde, 2-propanol, and ethanol accounted for 55.5%, 16.6%, 11.7%, and 8.31% of NMVOC emissions. Our study highlights methanol, formaldehyde, 2-propanol, and ethanol as the targeted compounds for reducing organic emissions and occupational inhalation exposures related to storage tank operations.

The greenhouse gas effects of increased US oil and gas production

Increased oil and natural gas production in the United States has decreased domestic natural gas prices and global oil prices. The resulting greenhouse gas (GHG) impacts have received substantial attention, with most focus on natural gas and relatively little on oil. In this paper, I provide an estimate of how increased production affects these emissions through changes in the US energy mix, methane emissions, and—crucially—global oil prices. Under a high oil and gas production scenario, US GHG emissions in 2030 are 100–600 million metric tons of carbon dioxide equivalent (2–10%) higher than under a low production scenario. Under the high production scenario, lower global oil prices and increased consumption raise non-US carbon dioxide emissions by 450–900 million metric tons relative to a low production scenario in 2030. These estimates assume that OPEC does not strategically reduce production to offset U.S. gains.

Methane Emission Estimates by the Global High-Resolution Inverse Model Using National Inventories

We present a global 0.1° × 0.1° high-resolution inverse model, NIES-TM-FLEXPART-VAR (NTFVAR), and a methane emission evaluation using the Greenhouse Gas Observing Satellite (GOSAT) satellite and ground-based observations from 2010–2012. Prior fluxes contained two variants of anthropogenic emissions, Emissions Database for Global Atmospheric Research (EDGAR) v4.3.2 and adjusted EDGAR v4.3.2 which were scaled to match the country totals by national reports to the United Nations Framework Convention on Climate Change (UNFCCC), augmented by biomass burning emissions from Global Fire Assimilation System (GFASv1.2) and wetlands Vegetation Integrative Simulator for Trace Gases (VISIT). The ratio of the UNFCCC-adjusted global anthropogenic emissions to EDGAR is 98%. This varies by region: 200% in Russia, 84% in China, and 62% in India. By changing prior emissions from EDGAR to UNFCCC-adjusted values, the optimized total emissions increased from 36.2 to 46 Tg CH4 yr−1 for Russia, 12.8 to 14.3 Tg CH4 yr−1 for temperate South America, and 43.2 to 44.9 Tg CH4 yr−1 for contiguous USA, and the values decrease from 54 to 51.3 Tg CH4 yr−1 for China, 26.2 to 25.5 Tg CH4 yr−1 for Europe, and by 12.4 Tg CH4 yr−1 for India. The use of the national report to scale EDGAR emissions allows more detailed statistical data and country-specific emission factors to be gathered in place compared to those available for EDGAR inventory. This serves policy needs by evaluating the national or regional emission totals reported to the UNFCCC.

Open-path cavity ring-down methane sensor for mobile monitoring of natural gas emissions

We present the design, development, and testing results of a novel laser-based cavity ring-down spectroscopy (CRDS) sensor for methane detection. The sensor is specifically oriented for mobile (i.e. vehicle deployed) monitoring of natural gas emissions from oil and infrastructure. In contrast to most commercial CRDS sensors, we employ an open-path design which allows higher temporal response and a lower power and mass package more suited to vehicle integration. The system operates in the near-infrared (NIR) at 1651 nm with primarily telecom components and includes cellular communication for wireless data transfer. Along with basic sensor design and lab testing, we present results of field measurements showing performance over a range of ambient conditions and examples of methane plume detection.

Use of Light Alkane Fingerprints in Attributing Emissions from Oil and Gas Production

Spatially resolved emission inventories were used with an atmospheric dispersion model to predict ambient concentrations of methane, ethane, and propane in the Eagle Ford oil and gas production region in south central Texas; predicted concentrations were compared to ground level observations. Using a base case inventory, predicted median propane/ethane concentration ratios were 106% higher (95% CI: 83% higher-226% higher) than observations, while median ethane/methane concentration ratios were 112% higher (95% CI: 17% higher-228% higher) than observations. Predicted median propane and ethane concentrations were factors of 6.9 (95% CI: 3-15.2) and 3.4 (95% CI: 1.4-9) larger than observations, respectively. Predicted median methane concentrations were 7% higher (95% CI: 39% lower-37% higher) than observations. These comparisons indicate that sources of emissions with high propane/ethane ratios (condensate tank flashing) were likely overestimated in the inventories. Because sources of propane and ethane emissions are also sources of methane emissions, the results also suggest that sources of emissions with low ethane/methane ratios (midstream sources) were underestimated. This analysis demonstrates the value of using multiple light alkanes in attributing sources of methane emissions and evaluating the performance of methane emission inventories for oil and natural gas production regions.

Importance of Superemitter Natural Gas Well Pads in the Marcellus Shale

A large-scale study of methane emissions from well pads was conducted in the Marcellus shale (Pennsylvania), the largest producing natural gas shale play in the United States, to better identify the prevalence and characteristics of superemitters. Roughly 2100 measurements were taken from 673 unique unconventional well pads corresponding to ∼18% of the total population of active sites and ∼32% of the total statewide unconventional natural gas production. A log-normal distribution with a geometric mean of 2.0 kg h^-1 and arithmetic mean of 5.5 kg h^-1 was observed, which agrees with other independent observations in this region. The geometric standard deviation (4.4 kg h^-1) compared well to other studies in the region, but the top 10% of emitters observed in this study contributed 77% of the total emissions, indicating an extremely skewed distribution. The integrated proportional loss of this representative sample was equal to 0.53% with a 95% confidence interval of 0.45-0.64% of the total production of the sites, which is greater than the U.S. Environmental Protection Agency inventory estimate (0.29%), but in the lower range of other mobile observations (0.09-3.3%). These results emphasize the need for a sufficiently large sample size when characterizing emissions distributions that contain superemitters.

Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study

Greenhouse gas emissions mitigation requires understanding the dominant processes controlling fluxes of these trace gases at increasingly finer spatial and temporal scales. Trace gas fluxes can be estimated using a variety of approaches that translate observed atmospheric species mole fractions into fluxes or emission rates, often identifying the spatial and temporal characteristics of the emission sources as well. Meteorological models are commonly combined with tracer dispersion models to estimate fluxes using an inverse approach that optimizes emissions to best fit the trace gas mole fraction observations. One way to evaluate the accuracy of atmospheric flux estimation methods is to compare results from independent methods, including approaches in which different meteorological and tracer dispersion models are used. In this work, we use a rich data set of atmospheric methane observations collected during an intensive airborne campaign to compare different methane emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, USA. We estimate emissions based on a variety of different meteorological and dispersion models. Previous estimates of methane emissions from this region relied on a simple model (a mass balance analysis) as well as on ground-based measurements and statistical data analysis (an inventory). We find that in addition to meteorological model choice, the choice of tracer dispersion model also has a significant impact on the predicted down-wind methane concentrations given the same emissions field. The dispersion models tested often underpredicted the observed methane enhancements with significant variability (up to a factor of 3) between different models and between different days. We examine possible causes for this result and find that the models differ in their simulation of vertical dispersion, indicating that additional work is needed to evaluate and improve vertical mixing in the tracer dispersion models commonly used in regional trace gas flux inversions.

Intercomparison of atmospheric trace gas dispersion models: Barnett Shale case study

Greenhouse gas emissions mitigation requires understanding the dominant processes controlling fluxes of these trace gases at increasingly finer spatial and temporal scales. Trace gas fluxes can be estimated using a variety of approaches that translate observed atmospheric species mole fractions into fluxes or emission rates, often identifying the spatial and temporal characteristics of the emission sources as well. Meteorological models are commonly combined with tracer dispersion models to estimate fluxes using an inverse approach that optimizes emissions to best fit the trace gas mole fraction observations. One way to evaluate the accuracy of atmospheric flux estimation methods is to compare results from independent methods, including approaches in which different meteorological and tracer dispersion models are used. In this work, we use a rich data set of atmospheric methane observations collected during an intensive airborne campaign to compare different methane emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, USA. We estimate emissions based on a variety of different meteorological and dispersion models. Previous estimates of methane emissions from this region relied on a simple model (a mass balance analysis) as well as on ground-based measurements and statistical data analysis (an inventory). We find that in addition to meteorological model choice, the choice of tracer dispersion model also has a significant impact on the predicted down-wind methane concentrations given the same emissions field. The dispersion models tested often underpredicted the observed methane enhancements with significant variability (up to a factor of 3) between different models and between different days. We examine possible causes for this result and find that the models differ in their simulation of vertical dispersion, indicating that additional work is needed to evaluate and improve vertical mixing in the tracer dispersion models commonly used in regional trace gas flux inversions.

Methane Emissions from Natural Gas Production Sites in the United States: Data Synthesis and National Estimate

We used site-level methane (CH₄) emissions data from over 1000 natural gas (NG) production sites in eight basins, including 92 new site-level CH₄ measurements in the Uinta, northeastern Marcellus, and Denver-Julesburg basins, to investigate CH₄ emissions characteristics and develop a new national CH₄ emission estimate for the NG production sector. The distribution of site-level emissions is highly skewed, with the top 5% of sites accounting for 50% of cumulative emissions. High emitting sites are predominantly also high producing (>10 Mcfd). However, low NG production sites emit a larger fraction of their CH₄ production. When combined with activity data, we predict that this creates substantial variability in the basin-level CH₄ emissions which, as a fraction of basin-level CH₄ production, range from 0.90% for the Appalachian and Greater Green River to >4.5% in the San Juan and San Joaquin. This suggests that much of the basin-level differences in production-normalized CH₄ emissions reported by aircraft studies can be explained by differences in site size and distribution of site-level production rates. We estimate that NG production sites emit total CH₄ emissions of 830 Mg/h (95% CI: 530-1200), 63% of which come from the sites producing <100 Mcfd that account for only 10% of total NG production. Our total CH₄ emissions estimate is 2.3 times higher than the U.S. Environmental Protection Agency's estimate and likely attributable to the disproportionate influence of high emitting sites.

Temporal variability largely explains top-down/bottom-up difference in methane emission estimates from a natural gas production region

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.

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.

Development of a Fuel-Based Oil and Gas Inventory of Nitrogen Oxides Emissions

In this study, we develop an alternative Fuel-based Oil and Gas inventory (FOG) of nitrogen oxides (NO _x) from oil and gas production using publicly available fuel use records and emission factors reported in the literature. FOG is compared with the Environmental Protection Agency's 2014 National Emissions Inventory (NEI) and with new top-down estimates of NO _x emissions derived from aircraft and ground-based field measurement campaigns. Compared to our top-down estimates derived in four oil and gas basins (Uinta, UT, Haynesville, TX/LA, Marcellus, PA, and Fayetteville, AR), the NEI overestimates NO _x by over a factor of 2 in three out of four basins, while FOG is generally consistent with atmospheric observations. Challenges in estimating oil and gas engine activity, rather than uncertainties in NO _x emission factors, may explain gaps between the NEI and top-down emission estimates. Lastly, we find a consistent relationship between reactive odd nitrogen species (NO _y) and ambient methane (CH₄) across basins with different geological characteristics and in different stages of production. Future work could leverage this relationship as an additional constraint on CH₄ emissions from oil and gas basins.

Discrepancies and Uncertainties in Bottom-up Gridded Inventories of Livestock Methane Emissions for the Contiguous United States

In this analysis we used a spatially explicit, simplified bottom-up approach, based on animal inventories, feed dry matter intake, and feed intake-based emission factors to estimate county-level enteric methane emissions for cattle and manure methane emissions for cattle, swine, and poultry for the contiguous United States. Overall, this analysis yielded total livestock methane emissions (8916 Gg/yr; lower and upper 95% confidence bounds of ±19.3%) for 2012 (last census of agriculture) that are comparable to the current USEPA estimates for 2012 and to estimates from the global gridded Emission Database for Global Atmospheric Research (EDGAR) inventory. However, the spatial distribution of emissions developed in this analysis differed significantly from that of EDGAR and a recent gridded inventory based on USEPA. Combined enteric and manure methane emissions from livestock in Texas and California (highest contributors to the national total) in this study were 36% lesser and 100% greater, respectively, than estimates by EDGAR. The spatial distribution of emissions in gridded inventories (e.g., EDGAR) likely strongly impacts the conclusions of top-down approaches that use them, especially in the source attribution of resulting (posterior) emissions, and hence conclusions from such studies should be interpreted with caution.

Comparisons of Airborne Measurements and Inventory Estimates of Methane Emissions in the Alberta Upstream Oil and Gas Sector

Airborne measurements of methane emissions from oil and gas infrastructure were completed over two regions of Alberta, Canada. These top-down measurements were directly compared with region-specific bottom-up inventories that utilized current industry-reported flaring and venting volumes (reported data) and quantitative estimates of unreported venting and fugitive sources. For the 50 × 50 km measurement region near Red Deer, characterized by natural gas and light oil production, measured methane fluxes were more than 17 times greater than that derived from directly reported data but consistent with our region-specific bottom-up inventory-based estimate. For the 60 × 60 km measurement region near Lloydminster, characterized by significant cold heavy oil production with sand (CHOPS), airborne measured methane fluxes were five times greater than directly reported emissions from venting and flaring and four times greater than our region-specific bottom up inventory-based estimate. Extended across Alberta, our results suggest that reported venting emissions in Alberta should be 2.5 ± 0.5 times higher, and total methane emissions from the upstream oil and gas sector (excluding mined oil sands) are likely at least 25-50% greater than current government estimates. Successful mitigation efforts in the Red Deer region will need to focus on the >90% of methane emissions currently unmeasured or unreported.

Variability in Spatially and Temporally Resolved Emissions and Hydrocarbon Source Fingerprints for Oil and Gas Sources in Shale Gas Production Regions

A gridded inventory for emissions of methane, ethane, propane, and butanes from oil and gas sources in the Barnett Shale production region has been developed. This inventory extends previous spatially resolved inventories of emissions by characterizing the overall variability in emission magnitudes and the composition of emissions at an hourly time resolution. The inventory is divided into continuous and intermittent emission sources. Sources are defined as continuous if hourly averaged emissions are greater than zero in every hour; otherwise, they are classified as intermittent. In the Barnett Shale, intermittent sources accounted for 14-30% of the mean emissions for methane and 10-34% for ethane, leading to spatial and temporal variability in the location of hourly emissions. The combined variability due to intermittent sources and variability in emission factors can lead to wide confidence intervals in the magnitude and composition of time and location-specific emission inventories; therefore, including temporal and spatial variability in emission inventories is important when reconciling inventories and observations. Comparisons of individual aircraft measurement flights conducted in the Barnett Shale region versus the estimated emission rates for each flight from the emission inventory indicate agreement within the expected variability of the emission inventory for all flights for methane and for all but one flight for ethane.

Spatiotemporal Variability of Methane Emissions at Oil and Natural Gas Operations in the Eagle Ford Basin

Methane emissions from oil and gas facilities can exhibit operation-dependent temporal variability; however, this variability has yet to be fully characterized. A field campaign was conducted in June 2014 in the Eagle Ford basin, Texas, to examine spatiotemporal variability of methane emissions using four methods. Clusters of methane-emitting sources were estimated from 14 aerial surveys of two ("East" or "West") 35 × 35 km grids, two aircraft-based mass balance methods measured emissions repeatedly at five gathering facilities and three flares, and emitting equipment source-types were identified via helicopter-based infrared camera at 13 production and gathering facilities. Significant daily variability was observed in the location, number (East: 44 ± 20% relative standard deviation (RSD), N = 7; West: 37 ± 30% RSD, N = 7), and emission rates (36% of repeat measurements deviate from mean emissions by at least ±50%) of clusters of emitting sources. Emission rates of high emitters varied from 150-250 to 880-1470 kg/h and regional aggregate emissions of large sources (>15 kg/h) varied up to a factor of ∼3 between surveys. The aircraft-based mass balance results revealed comparable variability. Equipment source-type changed between surveys and alterations in operational-mode significantly influenced emissions. Results indicate that understanding temporal emission variability will promote improved mitigation strategies and additional analysis is needed to fully characterize its causes.

Methane emissions from the Marcellus Shale in southwestern Pennsylvania and northern West Virginia based on airborne measurements

Natural gas production in the U.S. has increased rapidly over the past decade, along with concerns about methane (CH₄) leakage (total fugitive emissions), and climate impacts. Quantification of CH₄ emissions from oil and natural gas (O&NG) operations is important for establishing scientifically sound, cost-effective policies for mitigating greenhouse gases. We use aircraft measurements and a mass balance approach for three flight experiments in August and September 2015 to estimate CH₄ emissions from O&NG operations in the southwestern Marcellus Shale region. We estimate the mean ± 1σ CH₄ emission rate as 36.7 ± 1.9 kg CH₄ s^-1 (or 1.16 ± 0.06 Tg CH₄ yr^-1) with 59% coming from O&NG operations. We estimate the mean ± 1σ CH₄ leak rate from O&NG operations as 3.9 ± 0.4% with a lower limit of 1.5% and an upper limit of 6.3%. This leak rate is broadly consistent with the results from several recent top-down studies but higher than the results from a few other observational studies as well as in the U.S. Environmental Protection Agency CH₄ emission inventory. However, a substantial source of CH₄ was found to contain little ethane (C₂H₆), possibly due to coalbed CH₄ emitted either directly from coalmines or from wells drilled through coalbed layers. Although recent regulations requiring capture of gas from the completion venting step of the hydraulic fracturing appear to have reduced losses, our study suggests that for a 20 year time scale, energy derived from the combustion of natural gas extracted from this region will require further controls before it can exert a net climate benefit compared to coal.

Super-emitters in natural gas infrastructure are caused by abnormal process conditions

Effectively mitigating methane emissions from the natural gas supply chain requires addressing the disproportionate influence of high-emitting sources. Here we use a Monte Carlo simulation to aggregate methane emissions from all components on natural gas production sites in the Barnett Shale production region (Texas). Our total emission estimates are two-thirds of those derived from independent site-based measurements. Although some high-emitting operations occur by design (condensate flashing and liquid unloadings), they occur more than an order of magnitude less frequently than required to explain the reported frequency at which high site-based emissions are observed. We conclude that the occurrence of abnormal process conditions (for example, malfunctions upstream of the point of emissions; equipment issues) cause additional emissions that explain the gap between component-based and site-based emissions. Such abnormal conditions can cause a substantial proportion of a site's gas production to be emitted to the atmosphere and are the defining attribute of super-emitting sites.

Unconventional oil and gas development and risk of childhood leukemia: Assessing the evidence

The widespread distribution of unconventional oil and gas (UO&G) wells and other facilities in the United States potentially exposes millions of people to air and water pollutants, including known or suspected carcinogens. Childhood leukemia is a particular concern because of the disease severity, vulnerable population, and short disease latency. A comprehensive review of carcinogens and leukemogens associated with UO&G development is not available and could inform future exposure monitoring studies and human health assessments. The objective of this analysis was to assess the evidence of carcinogenicity of water contaminants and air pollutants related to UO&G development. We obtained a list of 1177 chemicals in hydraulic fracturing fluids and wastewater from the U.S. Environmental Protection Agency and constructed a list of 143 UO&G-related air pollutants through a review of scientific papers published through 2015 using PubMed and ProQuest databases. We assessed carcinogenicity and evidence of increased risk for leukemia/lymphoma of these chemicals using International Agency for Research on Cancer (IARC) monographs. The majority of compounds (>80%) were not evaluated by IARC and therefore could not be reviewed. Of the 111 potential water contaminants and 29 potential air pollutants evaluated by IARC (119 unique compounds), 49 water and 20 air pollutants were known, probable, or possible human carcinogens (55 unique compounds). A total of 17 water and 11 air pollutants (20 unique compounds) had evidence of increased risk for leukemia/lymphoma, including benzene, 1,3-butadiene, cadmium, diesel exhaust, and several polycyclic aromatic hydrocarbons. Though information on the carcinogenicity of compounds associated with UO&G development was limited, our assessment identified 20 known or suspected carcinogens that could be measured in future studies to advance exposure and risk assessments of cancer-causing agents. Our findings support the need for investigation into the relationship between UO&G development and risk of cancer in general and childhood leukemia in particular.

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.

Gridded National Inventory of U.S. Methane Emissions

We present a gridded inventory of US anthropogenic methane emissions with 0.1° × 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 US Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissions and Sinks (GHGI) for 2012. The EPA inventory is available only as national totals for different source types. We use a wide range of databases at the state, county, local, and point source level to disaggregate the inventory and allocate the spatial and temporal distribution of emissions for individual source types. Results show large differences with the EDGAR v4.2 global gridded inventory commonly used as a priori estimate in inversions of atmospheric methane observations. We derive grid-dependent error statistics for individual source types from comparison with the Environmental Defense Fund (EDF) regional inventory for Northeast Texas. These error statistics are independently verified by comparison with the California Greenhouse Gas Emissions Measurement (CALGEM) grid-resolved emission inventory. Our gridded, time-resolved inventory provides an improved basis for inversion of atmospheric methane observations to estimate US methane emissions and interpret the results in terms of the underlying processes.

Methane Leaks from Natural Gas Systems Follow Extreme Distributions

Future energy systems may rely on natural gas as a low-cost fuel to support variable renewable power. However, leaking natural gas causes climate damage because methane (CH₄) has a high global warming potential. In this study, we use extreme-value theory to explore the distribution of natural gas leak sizes. By analyzing ∼15 000 measurements from 18 prior studies, we show that all available natural gas leakage data sets are statistically heavy-tailed, and that gas leaks are more extremely distributed than other natural and social phenomena. A unifying result is that the largest 5% of leaks typically contribute over 50% of the total leakage volume. While prior studies used log-normal model distributions, we show that log-normal functions poorly represent tail behavior. Our results suggest that published uncertainty ranges of CH₄ emissions are too narrow, and that larger sample sizes are required in future studies to achieve targeted confidence intervals. Additionally, we find that cross-study aggregation of data sets to increase sample size is not recommended due to apparent deviation between sampled populations. Understanding the nature of leak distributions can improve emission estimates, better illustrate their uncertainty, allow prioritization of source categories, and improve sampling design. Also, these data can be used for more effective design of leak detection technologies.

Estimating Emissions of Toxic Hydrocarbons from Natural Gas Production Sites in the Barnett Shale Region of Northern Texas

Oil and natural gas operations have continued to expand and move closer to densely populated areas, contributing to growing public concerns regarding exposure to hazardous air pollutants. During the Barnett Shale Coordinated Campaign in October, 2013, ground-based whole air samples collected downwind of oil and gas sites revealed enhancements in several potentially toxic volatile organic compounds (VOCs) when compared to background values. Molar emissions ratios relative to methane were determined for hexane, benzene, toluene, ethylbenzene, and xylene (BTEX compounds). Using methane leak rates measured from the Picarro mobile flux plane (MFP) system and a Barnett Shale regional methane emissions inventory, the rates of emission of these toxic gases were calculated. Benzene emissions ranged between 51 ± 4 and 60 ± 4 kg h^-1. Hexane, the most abundantly emitted pollutant, ranged from 642 ± 45 to 1070 ± 340 kg h^-1. While observed hydrocarbon enhancements fall below federal workplace standards, results may indicate a link between emissions from oil and natural gas operations and concerns about exposure to hazardous air pollutants. The larger public health risks associated with the production and distribution of natural gas are of particular importance and warrant further investigation, particularly as the use of natural gas increases in the United States and internationally.

Direct and Indirect Measurements and Modeling of Methane Emissions in Indianapolis, Indiana

This paper describes process-based estimation of CH4 emissions from sources in Indianapolis, IN and compares these with atmospheric inferences of whole city emissions. Emissions from the natural gas distribution system were estimated from measurements at metering and regulating stations and from pipeline leaks. Tracer methods and inverse plume modeling were used to estimate emissions from the major landfill and wastewater treatment plant. These direct source measurements informed the compilation of a methane emission inventory for the city equal to 29 Gg/yr (5% to 95% confidence limits, 15 to 54 Gg/yr). Emission estimates for the whole city based on an aircraft mass balance method and from inverse modeling of CH4 tower observations were 41 ± 12 Gg/yr and 81 ± 11 Gg/yr, respectively. Footprint modeling using 11 days of ethane/methane tower data indicated that landfills, wastewater treatment, wetlands, and other biological sources contribute 48% while natural gas usage and other fossil fuel sources contribute 52% of the city total. With the biogenic CH4 emissions omitted, the top-down estimates are 3.5-6.9 times the nonbiogenic city inventory. Mobile mapping of CH4 concentrations showed low level enhancement of CH4 throughout the city reflecting diffuse natural gas leakage and downstream usage as possible sources for the missing residual in the inventory.

Attributing Atmospheric Methane to Anthropogenic Emission Sources

Methane is a greenhouse gas, and increases in atmospheric methane concentration over the past 250 years have driven increased radiative forcing of the atmosphere. Increases in atmospheric methane concentration since 1750 account for approximately 17% of increases in radiative forcing of the atmosphere, and that percentage increases by approximately a factor of 2 if the effects of the greenhouse gases produced by the atmospheric reactions of methane are included in the assessment. Because of the role of methane emissions in radiative forcing of the atmosphere, the identification and quantification of sources of methane emissions is receiving increased scientific attention. Methane emission sources include biogenic, geogenic, and anthropogenic sources; the largest anthropogenic sources are natural gas and petroleum systems, enteric fermentation (livestock), landfills, coal mining, and manure management. While these source categories are well-known, there is significant uncertainty in the relative magnitudes of methane emissions from the various source categories. Further, the overall magnitude of methane emissions from all anthropogenic sources is actively debated, with estimates based on source sampling extrapolated to regional or national scale ("bottom-up analyses") differing from estimates that infer emissions based on ambient data ("top-down analyses") by 50% or more. To address the important problem of attribution of methane to specific sources, a variety of new analytical methods are being employed, including high time resolution and highly sensitive measurements of methane, methane isotopes, and other chemical species frequently associated with methane emissions, such as ethane. This Account describes the use of some of these emerging measurements, in both top-down and bottom-up methane emission studies. In addition, this Account describes how data from these new analytical methods can be used in conjunction with chemical mass balance (CMB) methods for source attribution. CMB methods have been developed over the past several decades to quantify sources of volatile organic compound (VOC) emissions and atmospheric particulate matter. These emerging capabilities for making measurements of methane and species coemitted with methane, rapidly, precisely, and at relatively low cost, used together with CMB methods of source attribution can lead to a better understanding of methane emission sources. Application of the CMB approach to source attribution in the Barnett Shale oil and gas production region in Texas demonstrates both the importance of extensive and simultaneous source testing in the region being analyzed and the potential of CMB method to quantify the relative strengths of methane emission sources.

Emissions from oil and gas operations in the United States and their air quality implications

The energy supply infrastructure in the United States has been changing dramatically over the past decade. Increased production of oil and natural gas, particularly from shale resources using horizontal drilling and hydraulic fracturing, made the United States the world's largest producer of oil and natural gas in 2014. This review examines air quality impacts, specifically, changes in greenhouse gas, criteria air pollutant, and air toxics emissions from oil and gas production activities that are a result of these changes in energy supplies and use. National emission inventories indicate that volatile organic compound (VOC) and nitrogen oxide (NOx) emissions from oil and gas supply chains in the United States have been increasing significantly, whereas emission inventories for greenhouse gases have seen slight declines over the past decade. These emission inventories are based on counts of equipment and operational activities (activity factors), multiplied by average emission factors, and therefore are subject to uncertainties in these factors. Although uncertainties associated with activity data and missing emission source types can be significant, multiple recent measurement studies indicate that the greatest uncertainties are associated with emission factors. In many source categories, small groups of devices or sites, referred to as super-emitters, contribute a large fraction of emissions. When super-emitters are accounted for, multiple measurement approaches, at multiple scales, produce similar results for estimated emissions. Challenges moving forward include identifying super-emitters and reducing their emission magnitudes. Work done to date suggests that both equipment malfunction and operational practices can be important. Finally, although most of this review focuses on emissions from energy supply infrastructures, the regional air quality implications of some coupled energy production and use scenarios are examined. These case studies suggest that both energy production and use should be considered in assessing air quality implications of changes in energy infrastructures, and that impacts are likely to vary among regions.

IMPLICATIONS

The energy supply infrastructure in the United States has been changing dramatically over the past decade, leading to changes in emissions from oil and natural gas supply chain sources. In many source categories along these supply chains, small groups of devices or sites, referred to as super-emitters, contribute a large fraction of emissions. Effective emission reductions will require technologies for both identifying super-emitters and reducing their emission magnitudes.

Aerial Surveys of Elevated Hydrocarbon Emissions from Oil and Gas Production Sites

Oil and gas (O&G) well pads with high hydrocarbon emission rates may disproportionally contribute to total methane and volatile organic compound (VOC) emissions from the production sector. In turn, these emissions may be missing from most bottom-up emission inventories. We performed helicopter-based infrared camera surveys of more than 8000 O&G well pads in seven U.S. basins to assess the prevalence and distribution of high-emitting hydrocarbon sources (detection threshold ∼ 1-3 g s(-1)). The proportion of sites with such high-emitting sources was 4% nationally but ranged from 1% in the Powder River (Wyoming) to 14% in the Bakken (North Dakota). Emissions were observed three times more frequently at sites in the oil-producing Bakken and oil-producing regions of mixed basins (p < 0.0001, χ(2) test). However, statistical models using basin and well pad characteristics explained 14% or less of the variance in observed emission patterns, indicating that stochastic processes dominate the occurrence of high emissions at individual sites. Over 90% of almost 500 detected sources were from tank vents and hatches. Although tank emissions may be partially attributable to flash gas, observed frequencies in most basins exceed those expected if emissions were effectively captured and controlled, demonstrating that tank emission control systems commonly underperform. Tanks represent a key mitigation opportunity for reducing methane and VOC emissions.

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.

A Mobile Sensing Approach for Regional Surveillance of Fugitive Methane Emissions in Oil and Gas Production

This paper addresses the need for surveillance of fugitive methane emissions over broad geographical regions. Most existing techniques suffer from being either extensive (but qualitative) or quantitative (but intensive with poor scalability). A total of two novel advancements are made here. First, a recursive Bayesian method is presented for probabilistically characterizing fugitive point-sources from mobile sensor data. This approach is made possible by a new cross-plume integrated dispersion formulation that overcomes much of the need for time-averaging concentration data. The method is tested here against a limited data set of controlled methane release and shown to perform well. We then present an information-theoretic approach to plan the paths of the sensor-equipped vehicle, where the path is chosen so as to maximize expected reduction in integrated target source rate uncertainty in the region, subject to given starting and ending positions and prevailing meteorological conditions. The information-driven sensor path planning algorithm is tested and shown to provide robust results across a wide range of conditions. An overall system concept is presented for optionally piggybacking of these techniques onto normal industry maintenance operations using sensor-equipped work trucks.

Reconciling divergent estimates of oil and gas methane emissions

Published estimates of methane emissions from atmospheric data (top-down approaches) exceed those from source-based inventories (bottom-up approaches), leading to conflicting claims about the climate implications of fuel switching from coal or petroleum to natural gas. Based on data from a coordinated campaign in the Barnett Shale oil and gas-producing region of Texas, we find that top-down and bottom-up estimates of both total and fossil methane emissions agree within statistical confidence intervals (relative differences are 10% for fossil methane and 0.1% for total methane). We reduced uncertainty in top-down estimates by using repeated mass balance measurements, as well as ethane as a fingerprint for source attribution. Similarly, our bottom-up estimate incorporates a more complete count of facilities than past inventories, which omitted a significant number of major sources, and more effectively accounts for the influence of large emission sources using a statistical estimator that integrates observations from multiple ground-based measurement datasets. Two percent of oil and gas facilities in the Barnett accounts for half of methane emissions at any given time, and high-emitting facilities appear to be spatiotemporally variable. Measured oil and gas methane emissions are 90% larger than estimates based on the US Environmental Protection Agency's Greenhouse Gas Inventory and correspond to 1.5% of natural gas production. This rate of methane loss increases the 20-y climate impacts of natural gas consumed in the region by roughly 50%.