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Attributing Atmospheric Methane to Anthropogenic Emission Sources David Allen Department of Chemical Engineering and Center for Energy and Environmental Resources University of Texas at Austin, Austin, Texas 78712, United States S Supporting Information *

ABSTRACT: 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.

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INTRODUCTION Methane is a greenhouse gas and increases in atmospheric methane concentration over the past 250 years have driven increased radiative forcing of the atmosphere. The Intergovernmental Panel on Climate Change1 reports that atmospheric mixing ratios of methane increased from 722 ± 25 ppb in 1750 to 1802 ± 2 ppb by 2011. The net increase in radiative forcing due to atmospheric methane concentrations observed in 2011, relative to the concentration estimated for the year 1750, is 0.48 ± 0.05 W/m2. Methane therefore accounts for 17% of the radiative forcing due to the concentration increases of all well-mixed greenhouse gases (2.83 ± 0.029 W/m2). In addition, total contributions of methane emissions to radiative forcing are larger than the contributions due to methane concentrations alone (0.97 ± 0.17 W/m2 vs 0.48 ± 0.05 W/m2), since emissions of methane lead to secondary production of other radiative forcing species.1 © XXXX American Chemical Society

Atmospheric methane is attributed to biogenic, geogenic, and anthropogenic sources.2 Among the biogenic and geogenic sources are wetlands, termites, and hydrates. Anthropogenic sources, which have emissions that are comparable in magnitude to biogenic and geogenic sources, include energy systems, rice and other agriculture, livestock operations, landfills, waste treatment, and biomass burning. In the United States, the Environmental Protection Agency (EPA) estimates that the largest sources of anthropogenic methane emissions are natural gas and petroleum systems, enteric fermentation (livestock), landfills, coal mining, and manure management.3 While methane emission source categories are well-known, there is significant uncertainty in the magnitude of methane emissions from various source categories, and significant effort Received: February 14, 2016

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attribute methane emissions to a source that dominates the emissions of that tracer.14 For example, ethane is often used to estimate the methane emissions that are attributable to oil and gas production, assuming that all of the observed ethane emissions are due to oil and gas operations. These approaches to interpreting top-down measurements must be employed with caution. One reason for exercising caution in interpreting source attributions that subtract a bottom-up emission estimate of a less significant source from a total emission estimate for a region is the uncertainty in the bottom-up inventories, which are incorporated into the emissions estimate of the more dominant source. If the average bottom-up estimates of the less significant sources are over- or underestimated, then the average emissions for the more dominant source will be under- or overestimated. Another reason for exercising caution is that some top-down measurements are instantaneous and only made at certain times of day (e.g., aircraft measurements), while the bottom-up information used to estimate source strengths that are being subtracted from regional totals are frequently annual estimates. Specifically, aircraft measurements of regional emissions are generally performed during the midafternoon when atmospheric mixing distributes emissions throughout the boundary layer. Some emission sources exhibit diurnal variability, and therefore inventories that are compared with observations made exclusively in the afternoon must be adjusted to account for diurnal variability. For example, emissions from livestock operations are a major methane source known to peak in the afternoon,15 and therefore using emission estimates based on annual average emission factors, as is sometimes done in analyzing regional data, will understate the contribution of these emissions. A case study of the potential impact of diurnal variability in emissions is provided by the detailed data available for the Barnett Shale region oil and gas production region in North Central Texas. This region’s methane emissions, while dominated by oil and gas production sources, are also influenced by livestock operations. Lyon et al.16 have estimated that methane emissions from 1 170 000 beef and dairy cattle in the region and the associated manure management operations totaled 11 900 (9 500−14 300) kg h−1 (approximately 16% of the methane emissions in the region), based on annual average emission factors used in the U.S. Environmental Protection Agency’s Greenhouse Gas Inventory.3 If it is assumed that afternoon emissions from livestock are roughly double the night-time emissions,15 then afternoon emissions will be approximately a third higher than the annual average, increasing the Barnett Shale afternoon emission estimate to 16 000 kg h−1. Other sources that may have diurnal variability include oil and natural gas supply chain sources that require operator activity such as some types of liquid unloadings and blowdowns, and any emissions that may be temperature sensitive. Using molecular tracers, such as ethane, as exclusive markers for a single source14 must also be done with caution. Other sources of the tracer (e.g., possible ethane emissions from manure management) may need to be accounted for in some regions. The problem of using top-down measurements to assess emission source strengths, including sources that have temporal variability and sources that have overlapping molecular tracers, is not a new problem in air quality management. Over the past 40 years, best practices have emerged to assess source strengths based on regional measurements of fine particulate matter and volatile organic compounds (VOCs). Many of these best

has gone into making direct and indirect measurements of anthropogenic methane emissions, especially in regions with significant oil and gas operations. Some measurements of methane emissions have been made directly at the emission sources. These source measurements are typically done at a relatively small fraction of sources that are selected to be representative of regional or national populations. Results from the sampled sources are then extrapolated to estimate emissions from larger populations. For example, emissions from several hundred natural gas wells have been used to estimate the emissions from the half-million natural gas wells in the United States.4−6 This approach is generally referred to as a “bottomup” analysis. The difficulty with “bottom-up” approaches is obtaining a representative sample from large, diverse populations. Allen7 has described some of the challenges associated with bottom-up analyses for natural gas sources. Alternative, but indirect, approaches involve inferring methane emissions based on measured or inferred ambient concentrations of methane. Atmospheric concentrations of methane measured or inferred from ground, aircraft, and satellite platforms can be used to infer (using atmospheric models and assumptions) total methane emissions in a region in a process referred to as a “top-down” analysis.8−12 For example, for aircraft measurements, the difference between average concentrations of methane upwind and downwind of a region can be used, with the ventilation rate of the region, to estimate regional emissions. Recent reviews have concluded, based on top-down assessments, that bottom-up inventories underestimate or omit sources of methane emissions. For example, Brandt et al.13 estimate missing or underestimated sources of methane emissions in the US national emission inventory total 14 Tg/ year (7−21 Tg/year), approximately 50% (25%−100%) of the total anthropogenic emissions for the United States. Identifying which sources are responsible for the missing or underestimated emissions requires methods for attributing atmospheric methane concentrations from top-down measurements to specific sources. This Account will describe the methods that are being used and those that could be used in attributing regional emission estimates for methane to specific sources. The data required for these analyses, which will also be described, are molecular and isotopic characterizations of sources. The application of these methods to the challenges of methane source attribution will be illustrated, to the extent possible, with data from recent field studies.

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METHODS FOR ATTRIBUTING ATMOSPHERIC METHANE TO EMISSION SOURCES Top-down studies, particularly those done from aircraft, use atmospheric concentrations of methane and other chemical species and wind field data to estimate a total methane emission rate for a region. When these top-down studies are performed in a region in which one source dominates, bottom-up estimates of other emission sources are sometimes subtracted from the total emissions to arrive at estimates of the emissions of the dominant emission source for the region.10 For example, in regions where oil and gas emission sources dominate, emissions from sources such as enteric fermentation from animals are often estimated using bottom-up methods (e.g., multiplying counts of animals by an annual average emission factor for methane emissions) and subtracted from an estimate of total emissions to arrive at an estimate for emissions from oil and gas sources. In other cases, a molecular tracer is used to B

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Among the advantages of the CMB approach are the use of measurements of multiple chemical species to attribute sources and the ability to characterize, with statistical rigor, the extent to which multiple measurements provide a consistent picture of relative source strengths. The method provides a characterization of relative source strengths over the time scale of the measurements used in the analysis, and consequently if there are temporal variations in emission rates or wind trajectories, the estimated source strengths at a measurement site would vary for measurements made at different times. Because of the widespread use of the CMB approach in source allocation for particulate matter and VOCs, the US EPA provides free software for implementing the tool20 and maintains an extensive database, SPECIATE,21 that provides default gas and particle phase emission composition profiles for thousands of emission sources. To the author’s knowledge, the CMB approach has not yet been applied to the analysis of top-down emission data in methane source attribution; however, as shown in Table 1, a combination of molecular and isotopic

practices rely on the chemical mass balance method. The chemical mass balance (CMB) method was originally developed to resolve sources of ambient aerosols observed at a downwind receptor location,17 and the CMB method has been widely used for this purpose. In the last 40 years, the CMB method has also been used to resolve sources of ambient hydrocarbons in many urban areas.18 When used to resolve sources of hydrocarbons, the CMB models solve a set of species specific mass balances, which relate the concentration of the hydrocarbon observed at a receptor site to the linear sum of the contributions of the hydrocarbon from its sources: J

Ci =

∑ FijSCj + εi j=1

where Ci is the measured concentration of species i at the receptor site, Fij is the measured mass fraction of species i in the source profile of emissions from source j, SCj is the source contribution of hydrocarbon from source j, and εi is the difference between the observed concentration and the predicted concentration based on a linear combination of sources. In performing source attribution, the source profiles (Fij) are known, based on source specific measurements. If the number of species measured is greater than the number of sources, then the relative source strengths (SCj) are calculated by minimizing some measure of the differences between the observed concentrations and the concentrations predicted based on a linear combination of sources. For example, if observed concentrations have different levels of uncertainty, a weighted, squared difference between predictions and observations can be minimized: Minimize:

Table 1. Molecular and Isotopic Tracer Species Present in Major Anthropogenic Methane Emission Sourcesa sources animal operations

species methane methane δ13C/12C methane δD-CH4 ethane propane butane pentane ethanol, propanol

I

∑ wiεi 2 i=1

where wi is the weighting factor for the difference between the observed concentration and the predicted concentration based on a linear combination of sources. The assumptions associated with applying this CMB process to source allocation are as follows:19 (i) the compositions of source emissions are constant over the period of sampling; (ii) chemical species are nonreactive; (iii) all sources with a potential for significantly contributing to the observed concentrations have been identified; (iv) source compositions are linearly independent; (v) the number of sources is less than or equal to the number of observed chemical species; (vi) measurement uncertainties are random, uncorrelated, and normally distributed. If applied to the problem of attributing sources to emissions estimated in top-down studies, the CMB approach would relate the emissions observed for a region to a linear sum of the contributions of multiple sources

enteric fermentation

manure management

coal seam gas

√ √

√ √

√ √

√ √

√ √

√

√

√

√

√

√ √ √ √ √

√

√ (?)b

√ √ √ √

landfills

a

Descriptions of measurement methods provided in Supporting Information. bSee text.

tracers can provide the data necessary to apply the method. The following sections describe data available on molecular and isotopic tracers of major methane emission sources and provide a case study of the potential application of the method in the Barnett Shale oil and gas production region in north central Texas.

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MOLECULAR AND ISOTOPIC TRACERS OF METHANE SOURCES Major anthropogenic sources of methane emissions include energy systems, livestock operations, landfills, and wastewater treatment. Many of these methane sources are also sources of other alkane emissions, including ethane (C2), propane (C3), butanes (C4), and pentanes (C5) (collectively C2−C5 hydrocarbons), as well as other species, and these species can be used in CMB analyses for methane source attribution. In addition, high precision and fast response instruments are now commercially available for quantifying methane isotopes. Since the relative abundance of deuterium and 13C varies among methane sources, these new measurement capabilities now allow methane isotopes to also be used as source tracers.

J

Ei =

natural gas supply chain sources

∑ Fij ECj + εi′ j=1

where Ei is the emission rate of species i for the region, Fij is the measured mass fraction of species i in the source profile of emissions from source j, and ECj is the emission contribution of hydrocarbon from source j. C

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0.009, respectively, and methane isotope δ13C and δD values of −56.3‰ and −283‰, respectively.

Animal Operations

Emissions from animal operations include enteric fermentation, manure handling, wastewater management, and manure disposal. Enteric fermentation is generally assumed to lead to emissions of negligible quantities of C2−C5 alkanes. In contrast, manure management can lead to a variety of C2− C5 alkanes and other molecular species. For example, in the US EPA SPECIATE database,21 the source profile for animal waste decomposition, based on engineering estimates and literature surveys, is given as 70% methane, 20% ethane, 2% acetone, 2% ethanol, 2% 2-propanol, 2% propylacetate, 1% ethylamine, and 1% trimethylamine, but the profile is highly sensitive to whether the decomposition is aerobic or anaerobic. Similarly, source profiles for final disposition of the manure (e.g., land application, combustion) will be highly dependent on site specific processes. Site specific profiles for a region improve source attribution. Data from the Barnett Shale oil and gas production region in north central Texas provide a case study of regional source characterization. Townsend-Small et al.22 report seven site source profiles for a combination of beef and dairy operations; collectively these sources had average background corrected C2/C1, C3/C1, C4/C1, and C5/C1 molar ratios of 0.017, 0.010, 0.005 and 0.002, respectively (mass ratios of 0.032, 0.028, 0.018 and 0.009, respectively). Spatial variability in emission source profiles for animal operations in the Barnett Shale region is described in more detail in Supporting Information. In addition to molecular tracers, isotopic tracers of methane emissions from livestock operations can also be used in CMB analyses. 13C content is frequently reported as δ13C, where δ13C (in parts per thousand, ‰) is defined as 13

13

12

13

Landfill Gas

In contrast to animal operations, where a variety of molecular tracers are present in measurable concentrations, landfill gas is primarily composed of methane and carbon dioxide. In the most recent (2008) draft US EPA guidance on estimating landfill emissions (referred to as AP-42),23 uncontrolled landfill gas (LFG) is assigned a composition of approximately equal volumes of CO2 and CH4, together with trace amounts of nonmethane organic compounds, totaling 838 ppmv, which can be used in source signatures. Only a few trace species average over 10 ppmv (1,2-dichloroethene, carbon monoxide, hydrogen sulfide, propane, and toluene). Average ethane concentration is listed as 9 ppmv, which is a significant change from the fifth edition of AP-42,24 which listed ethane as present in LFG at 889 ppmv. These profiles overall suggest a C2/C1 ratio in LFG of 0.001 or less. For the Barnett Shale region, Townsend-Small et al.22 report eight site specific source profiles for landfills; collectively these sources had average background corrected C2/C1 molar ratios of 0.002 (mass ratio of 0.004) with much lower ratios of C3 and higher hydrocarbons to methane. Isotopic compositions are reported as −54.8‰ for δ13C and −260‰ for δD, compared with average background values of −47.9‰ and −114‰. Collectively, these results suggest a source fingerprint for landfill gas in the Barnett Shale that has a C2/C1 mass ratio of 0.004 and methane isotope δ13C and δD values of −54.8‰ and −260‰, respectively. Natural Gas Sources

Emissions from natural gas production sources can vary widely in their molecular composition, depending on the gas to oil ratio of the produced gas and liquid, as well as other parameters. For example, for the Barnett Shale, TownsendSmall et al.22 report seven site total source profiles for compressor stations (for sites where wind speeds during sampling exceeded threshold levels); collectively these sources had average background corrected C2/C1, C3/C1, C4/C1, and C5/C1 molar ratios of 0.085, 0.035, 0.011, and 0.004, respectively, but the range of C2/C1 background corrected molar ratios ranged from 0.02 to more than 0.2. Nevertheless, average C2/C1 and C3/C1 ratios for a region can be estimated, and Townsend-Small report C2/C1 molar ratios in the range of 0.06−0.07 for upstream natural gas sites in the Barnett Shale and 0.13 for oil well sites (0.11−0.13 mass ratio for gas sites and 0.24 for oil sites). Molar C3/C1 ratios for gas and oil sites are reported as 0.02 and 0.06 (0.05 and 0.16 by mass), respectively. Assuming that oil wells represent about 10% of the oil and gas well site methane emissions in the region16 suggests approximate regional average C2/C1 and C3/C1 mass ratios of 0.13 and 0.07 for combined oil and gas operations, respectively. Methane isotopes can also be used as source tracers for natural gas emissions; however, like molecular tracers, the relative abundance of isotopic tracers will vary from site to site in a natural gas production region. Townsend-Small et al.22 report a range of values for δ13C (−42‰ to −55‰) and δD (−119‰ to −208‰), for oil and gas sites, with central estimates of 47−48‰ for δ13C and 138−177‰ for δD. Townsend-Small et al.22 also report that that the isotopic abundance is correlated with molecular composition of produced gas, explaining much of the variability. Therefore, in the same way that average C2/C1 and C3/C1 ratios can be

12

δ C(‰) = {[( C/ C)sample /( C/ C)standard ] − 1} × 1000

where the standard is typically chosen as a geological sample, the Pee Dee Belemnite (PDB), which has a very high 13C/12C ratio (13C/12Cstandard is 0.011237). Since the standard has a high 13 C/12C ratio, most samples have a negative value of δ13C. For the Barnett Shale region, Townsend-Small et al.22 report δ13C source profiles for the same combination of beef and dairy operations for which they report C2−C5 alkanes. The value of δ13C at the source is determined using a Keeling plot, in which methane δ13C values for samples containing varying fractions of source and background methane are plotted against the inverse of the methane concentration. The intercept of the plot at zero inverse methane concentration provides the estimate of the source δ13C. Townsend-Small et al.22 report an average δ13C value for the sum of all methane emissions, detected downwind of multiple livestock sites, of −56.3‰ (precision of measurement reported as ±0.2‰), compared with an average δ13C value in background air of −47.9‰. Similarly, deuterium content is reported as δD, expressed in parts per thousand (‰), relative to a Vienna standard mean ocean water standard (VSMOW). Townsend-Small et al.22 report a δD value for methane emissions from livestock operations in the Barnett Shale of −283‰ (precision of measurement reported as ±4‰), compared with an average δD value in background air of −114‰. Collectively, these results suggest a source fingerprint for animal operations in the Barnett Shale that has C2/C1, C3/C1, C4/C1, and C5/C1 mass ratios of 0.032, 0.028, 0.018, and D

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Accounts of Chemical Research reported for a region, emission weighted δ13C and δD can be developed for natural gas sources. If an emission weighted C2/ C1 ratio of 0.13 (the value obtained based on both source sampling and estimates from VOC inventories) is used to predict δ13C and δD for the Barnett Shale, the estimates for δ13C and δD are −46‰ and −140‰, respectively. Collectively, these results suggest a source fingerprint for oil and gas operations in the Barnett Shale that has a C2/C1 mass ratio of 0.13 and methane isotope δ13C and δD values of −46‰ and −140‰, respectively.

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and the assumption that all of the ethane is attributed to oil and gas operations, can lead to relatively large differences between source attributions (79% vs 61% for oil and gas sources for topdown and bottom-up approaches). Including more molecular tracer species or isotope information and applying the CMB analysis approach could reduce these uncertainties. Table 2 Table 2. Molecular and Isotopic Source Profiles (by Mass) for the Barnett Shale Region, Normalized by Methane Content of Source

APPLYING THE CMB METHOD AND MOLECULAR AND ISOTOPIC TRACERS TO METHANE SOURCE ATTRIBUTION

species methane methane fraction with 13Ca methane fraction with Db ethane (mass ratio)

Barnett Shale Case Study Using Current Data

Studies performed in the Barnett Shale oil and gas production region provide one of the richest data sets available for comparing top-down emission estimates and bottom-up emission inventories, as well as for testing source attribution methods. Both bottom-up and top-down approaches have led to very similar total methane emission estimates for the region with aircraft-based, top-down measurements leading to an estimated emission rate of 76 000 ± 13 000 kg/h11 and bottomup estimates, based on measurements at hundreds of sites, extrapolated to a region wide total of 72 300 (63 400−82 400) kg/h.16 The total top-down and bottom-up emission estimates for methane are even closer if time-of-day emission corrections are included in the bottom-up inventory. For example, if livestock emissions during the afternoon hours, when aircraft flights are conducted, are assumed to increase by 33% relative to average emissions,15 total region wide bottom-up emissions would increase to 76 000 kg/h, identical to the top-down estimate. Top-down and bottom-up emission estimates for ethane are also in reasonable agreement. Aircraft-based top-down emission estimates totaled 6600 ± 200 kg/h.14 Bottom-up ethane emission estimation methods for oil and gas sources, based on methane emissions of 48 400 kg/h and an average methane to ethane (C2/C1) mass ratio of 0.13, lead to an estimate of 6000 kg/h from oil and gas emissions. Added to this is an estimated 500 kg/h of ethane from livestock operations based on the bottom-up methane emissions estimated by Lyon et.al,16 increased by 33% to account for time of day effects and measured source profiles (C2/C1 mass ratio of 0.032).22 This total for the region (6500 kg/h) is consistent with the total ethane emission estimate based on top-down measurements (6600 ± 200 kg/h). While total methane and ethane emissions using the topdown and bottom-up approaches were similar, the attribution of methane emission sources exhibited differences. The topdown estimate of emissions from oil and gas operations was 60 000 ± 11 000 (79% of total top-down emission estimate), based on an assumption that all of the ethane emissions quantified in the top-down measurements originated from oil and gas sources14 and that, on average, the C2/C1 emissions ratio for the region’s oil and gas operations was 0.11 (mass basis). In contrast, a bottom-up emissions estimate for the region led to an estimate of 46 200 kg/h of methane from oil and gas operations (48 400 kg/h including other minor geogenic sources), which is 61−63% of the region’s emissions. Relatively small differences in the average C2/C1 mass ratio (0.13 vs 0.11) in the source profile for oil and gas emissions,

oil and gas supply chain sources 1 0.01072 (−46‰) 134 × 10−6 (−140‰) 0.13 or 0.11c

animal operations 1 0.01060 (−56.3‰) 112 × 10−6 (−283‰) 0.032 or 0c

landfills 1 0.01062 (−54.8‰) 115 × 10−6 (−260‰) 0.004 or 0c

Methane fraction with 13C equals (1 + δ13C/1000) × 0.011237. Methane fraction with D equals (1 + δD/1000) × (155.76 × 10−6). c Ethane to methane ratios of 0.13, 0.032, and 0.004 are based on source sampling and account for all ethane and methane based on methane emission rates of 48 400 kg h−1 from oil and gas and other geogenic sources, 16 000 kg h−1 from livestock, and 11 300 kg h−1 from landfills. Ethane ratios of 0.11, 0, and 0 were used to derive methane source strengths of 60 000 kg h−1 from oil and gas sources, and the remainder was assumed to be evenly split between landfill and animal operations (8000 kg h−1 each). a b

shows data on both isotopic tracer concentrations and higher hydrocarbon tracers that have been collected for methane sources in the Barnett Shale region and that were summarized in the previous section. These data can be used to compare the two different estimates for source strength that emerged from the Barnett Shale studies, both of which account for the total regional methane and ethane emissions. Assuming ethane to methane ratios of 0.13, 0.032, and 0.004 for oil and gas, animal operation, and landfill sources (based on source sampling) and bottom-up methane emission rates of 48 400 kg h−1 from oil and gas and other geogenic sources, 16 000 kg h−1 from livestock, and 11 300 kg h−1 from landfills (Lyon et al., 2015), leads to estimates of methane fractions in the emissions containing 13C and D of 0.01067 and 126.3 × 10−6, respectively. In contrast, assuming ethane to methane ratios of 0.11, 0, and 0 for oil and gas, animal operation, and landfill sources and methane emission rates of 60 000 kg h−1 from oil and gas and other geogenic sources, 8000 kg h−1 from livestock, and 8000 kg h−1 from landfills14 leads to estimates of methane fractions in the emissions containing 13C and D of 0.01070 and 129.8 × 10−6, respectively. The differences in deuterium ratios in the aggregated methane emissions for the two scenarios (corresponding to δD values of −189‰ for 126.3 × 10−6 and −167‰ for 129.8 × 10−6) is a factor of 5 larger than the reported uncertainty range (±4‰) for δD (see Supporting Information) and therefore could distinguish between these two scenarios. While average downwind measurements of 13C and D have not yet been published for the Barnett Shale region, the measurements are feasible and the analyses presented here illustrate the potential value of the CMB approach in the Barnett Shale oil and gas production region. The CMB method could also be productively employed, together with molecular tracer and isotope measurements, in other production regions E

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Accounts of Chemical Research where oil and gas operations are colocated with livestock and poultry operations, landfills, and coal seam gas operations or natural gas seeps.

overlap in molecular tracers between sources, the ability to characterize the extent to which multiple measurements provide a consistent picture of relative source strengths, and the ability to estimate source strengths from top-down data without having to employ bottom-up emission estimates. The method requires source profiles for major sources, and these source profiles may vary both within and between regions. This means that for studies that seek to be precise and accurate in source attribution, some local source sampling is necessary. While this may be viewed as a limitation of the CMB method, source profiles are also needed for current source attribution methods, although sometimes these are assumed implicitly (e.g., ignoring ethane emissions from manure management).

Barnett Shale Case Study Using Spatially Resolved Data

While the CMB approach, based on regionally averaged source profiles, can reduce uncertainties in source attributions, the use of spatially resolved source profiles could provide even more refinement to source attributions. Consider, as an example, the development of spatially resolved molecular tracers for oil and gas emissions in the Barnett Shale. Zavala25 has developed spatially resolved C2/C1 and C3/C1 ratios for the Barnett Shale based on data available in detailed VOC emission inventories. VOC emissions, by regulation, include propane emissions, but ethane and methane emissions are excluded based on the low atmospheric reactivity of methane and ethane relative to other VOCs. Zavala-Araiza25 used data on the fraction of VOCs in produced gas, and a site by site inventory of VOC emissions for the Barnett Shale to produce emission weighted C2/C1 and C3/C1 ratios for Barnett Shale oil and gas emissions. Because this approach uses well-developed VOC inventories to estimate C2/C1 and C3/C1 ratios, it is potentially applicable to other regions, as well. Spatial mappings of C2/C1 and C3/C1 ratios for the Barnett Shale are shown in Supporting Information. Spatial variability of emission compositions highlights the importance of developing weighted average source fingerprints in oil and gas production regions. The emission weighted average mass ratios of C2/C1 and C3/C1 for the Barnett Shale, developed using this approach, are 0.13 and 0.10, respectively. This C2/ C1 estimate is the same as the average based on source sampling.22 The C3/C1 ratio is higher than the source sampling average.22 Just as methane to ethane ratios vary spatially for oil and gas operations, the ratios for animal operations also vary spatially in the Barnett Shale. The spatial variation is driven by differences in the ratio of manure management emissions to enteric fermentation emissions for beef and dairy cattle and varying ratios of beef to dairy cattle. Details are provided in Supporting Information. County specific C2/C1 mass ratios range from a low of 0.008 for counties dominated by beef cattle to a high of 0.086 in a county with comparable numbers of beef and dairy cattle. The emission-weighted average C2/C1 ratio for the entire region (0.034 by mass) is similar to the average for source sampling (0.032 by mass).22 Once again, the spatial heterogeneity observed in the methane to ethane ratios illustrate that if molecular source profiles are used to attribute emissions to sources, careful attention must be paid to the regions sampled. To summarize the Barnett Shale case study, use of just ethane as a molecular tracer for methane emission sources produces a variety of estimates of source strengths, depending on the assumptions made in the analysis. Adding isotope measurements into the analysis and using a CMB analysis framework has the potential to effectively distinguish among the various region-wide source attributions. The CMB method could also be used for subregional analyses, if spatially resolved source profiles and upwind and downwind isotope and tracer measurements are available. The advantages of the CMB method for source attribution, compared with current methods of attributing sources, are the use of measurements of multiple chemical species and isotopes to attribute sources, the ability to quantitatively account for

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.accounts.6b00081. Emissions from oil and natural gas operations and beef and dairy cattle operations in the Barnett Shale region and measurements for methane, methane isotopes, and ethane (PDF)

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AUTHOR INFORMATION

Notes

The authors declare the following competing financial interest(s): Funding to perform the analyses reported here was provided by ExxonMobil Upstream Research Company. In addition, the author has served as chair of the Environmental Protection Agency’s Science Advisory Board (2012−2015; in this role, he was a paid Special Governmental Employee); he serves as a journal editor for the American Chemical Society, and he has done work as a consultant for multiple companies, including Eastern Research Group, ExxonMobil, and Research Triangle Institute. Over the past three years, he has also worked on methane emission measurement projects that have been supported by multiple natural gas producers and Environmental Defense Fund. Biography Dr. David Allen is the Gertz Regents Professor of Chemical Engineering and the Director of the Center for Energy and Environmental Resources at the University of Texas at Austin. Dr. Allen has led multiple air quality measurement studies. From 2012 through 2015, with support from Environmental Defense Fund and a group of natural gas producers, he led a team measuring methane emissions from natural gas production sites. He has served on a variety of governmental advisory panels and from 2012 to 2015 chaired the Environmental Protection Agency’s Science Advisory Board.

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ACKNOWLEDGMENTS Funding to perform the analyses reported here was provided by ExxonMobil Upstream Research Company. REFERENCES

(1) Intergovernmental Panel on Climate Change (IPCC). Fifth Assessment Report, Workgroup I, Chapter 8, Intergovernmental Panel on Climate Change, Geneva, 2014. (2) Intergovernmental Panel on Climate Change (IPCC). Fifth Assessment Report, Workgroup III, Chapter 5, Intergovernmental Panel on Climate Change, Geneva, 2014.

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DOI: 10.1021/acs.accounts.6b00081 Acc. Chem. Res. XXXX, XXX, XXX−XXX

Article

Accounts of Chemical Research (3) U.S. Environmental Protection Agency. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990−2013, EPA 430-R-14003, April 2015. (4) Allen, D. T.; Torres, V. M.; Thomas, J.; Sullivan, D.; Harrison, M.; Hendler, A.; Herndon, S. C.; Kolb, C. E.; Fraser, M.; Hill, A. D.; Lamb, B. K.; Miskimins, J.; Sawyer, R. F.; Seinfeld, J. H. Measurements of Methane Emissions at Natural Gas Production Sites in the United States. Proc. Natl. Acad. Sci. U. S. A. 2013, 110, 17768−17773. (5) Allen, D. T.; Pacsi, A.; Sullivan, D.; Zavala-Araiza, D.; Harrison, M.; Keen, K.; Fraser, M.; Hill, A. D.; Sawyer, R. F.; Seinfeld, J. H. Methane Emissions from Process Equipment at Natural Gas Production Sites in the United States: Pneumatic Controllers. Environ. Sci. Technol. 2015, 49, 633−640. (6) Allen, D. T.; Sullivan, D.; Zavala-Araiza, D.; Pacsi, A.; Harrison, M.; Keen, K.; Fraser, M.; Hill, A. D.; Lamb, B. K.; Sawyer, R. F.; Seinfeld, J. H. Methane Emissions from Process Equipment at Natural Gas Production Sites in the United States: Liquid Unloadings. Environ. Sci. Technol. 2015, 49, 641−648. (7) Allen, D. T. Methane Emissions from Natural Gas Production and Use: Reconciling Bottom-Up and Top-Down Measurements. Curr. Opin. Chem. Eng. 2014, 5, 78−83. (8) Zavala-Araiza, D.; Sullivan, D. W.; Allen, D. T. Atmospheric hydrocarbon emissions and concentrations in the Barnett Shale natural gas production region. Environ. Sci. Technol. 2014, 48, 5314−5321. (9) Petron, G.; Frost, G.; Miller, B. R.; Hirsch, A. I.; Montzka, S. A.; Karion, A.; Trainer, M.; Sweeney, C.; Andrews, A. E.; Miller, L.; kofler, J.; Bar-Ilan, A.; Dlugokencky, E. J.; Patrick, L.; Moore, C. T.; Ryerson, T. B.; Siso, C.; Kolodzey, W.; Lang, P. M.; Conway, T.; Novelli, P.; Masarie, K.; Hall, B.; Guenther, D.; Kitzis, D.; Miller, J.; Welsh, D.; Wolfe, D.; Neff, W.; Tans, P. Hydrocarbon Emissions Characterization in the Colorado Front Range: A Pilot Study. J. Geophys. Res. 2012, 117 (D4), D04304. (10) Peischl, J.; Ryerson, T. B.; Aikin, K. C.; de Gouw, J. A.; Gilman, J. P.; Holloway, J. S.; Lerner, B. M.; Nadkarni, R.; Neuman, J. A.; Nowak, J. B.; Trainer, M.; Warneke, C.; Parrish, D. D. Quantifying atmospheric methane emissions from the Haynesville, Fayetteville, and northeastern Marcellus shale gas production regions. J. Geophys. Res. Atmos. 2015, 120, 2119−2139. (11) Karion, A.; Sweeney, C.; Kort, E. A.; Shepson, P. B.; Brewer, A.; Cambaliza, M.; Conley, S. A.; Davis, K.; Deng, A.; Hardesty, M.; Herndon, S. C.; Lauvaux, T.; Lavoie, T.; Lyon, D.; Newberger, T.; Petron, G.; Rella, C.; Smith, M.; Wolter, S.; Yacovitch, T. I.; Tans, P. Aircraft-based Estimate of Total Methane Emissions from the Barnett Shale Region. Environ. Sci. Technol. 2015, 49, 8124−8131. (12) Kort, E. A.; Frankenberg, C.; Costigan, K. R.; Lindenmaier, R.; Dubey, M. K.; Wunch, D. Four Corners: The largest US methane anomaly viewed from space. Geophys. Res. Lett. 2014, 41, 6898−6903. (13) Brandt, A. R.; Heath, G. A.; Kort, E. A.; O’Sullivan, F.; Pétron, G.; Jordaan, S. M.; Tans, P.; Wilcox, J.; Gopstein, A. M.; Arent, D.; Wofsy, S.; Brown, N. J.; Bradley, R.; Stucky, G. D.; Eardley, D.; Harriss, R. Methane Leaks from North American Natural Gas Systems. Science 2014, 343, 733−735. (14) Smith, M. L.; Kort, E. A.; Karion, A.; Sweeney, C.; Herndon, S. C.; Yacovitch, T. I. Airborne Ethane Observations in the Barnett Shale: Quantification of Ethane Flux and Attribution of Methane Emissions. Environ. Sci. Technol. 2015, 49, 8158−8166. (15) Leytem, A. B.; Dungan, R. S.; Bjorneberg, D. L.; Koehn, A. C. Emissions of Ammonia, Methane, Carbon Dioxide, and Nitrous Oxide from Dairy Cattle Housing and Manure Management Systems. J. Environ. Qual. 2011, 40, 1383−1394. (16) Lyon, D. R.; Zavala-Araiza, D.; Alvarez, R. A.; Harriss, R.; Palacios, V.; Lan, X.; Talbot, R.; Lavoie, T.; Shepson, P.; Yacovitch, T. I.; Herndon, S. C.; Marchese, A. J.; Zimmerle, D.; Robinson, A. L.; Hamburg, S. P. Constructing a Spatially Resolved Methane Emission Inventory for the Barnett Shale Region. Environ. Sci. Technol. 2015, 49, 8147−8157. (17) Friedlander, S. K. Chemical element balances and identification of air pollution sources. Environ. Sci. Technol. 1973, 7, 235−240.

(18) Watson, J. G.; Chow, J. C.; Fujita, E. M. Review of volatile organic compound source apportionment by chemical mass balance. Atmos. Environ. 2001, 35, 1567−1584. (19) Watson, J. G. Protocol for applying and validating the CMB model for PM2.5 and VOC, Report to the US EPA, EPA-451/R-04001, December 2004. (20) U.S. Environmental Protection Agency. Chemical Mass Balance (CMB) Model, available at http://www.epa.gov/ttn/scram/receptor_ cmb.htm, accessed August, 2015. (21) U.S. Environmental Protection Agency. SPECIATE, version 4.4, available at http://www.epa.gov/ttn/chief/software/speciate/, accessed August, 2015. (22) Townsend-Small, A.; Marrero, J. E.; Lyon, D. R.; Simpson, I. J.; Meinardi, S.; Blake, D. R. Integrating Source Apportionment Tracers into Bottom-up Inventory of Methane Emissions in the Barnett Shale Hydraulic Fracturing Region. Environ. Sci. Technol. 2015, 49, 8175− 8182. (23) U.S. Environmental Protection Agency, Emissions Factors & AP 42, Compilation of Air Pollutant Emission Factors, Draft Chapter 2.4, Municipal Solid Waste Landfills, October 2008, http://www.epa.gov/ ttn/chief/ap42/ch02/index.html, accessed August, 2015. (24) U.S. Environmental Protection Agency, Emissions Factors & AP 42, Compilation of Air Pollutant Emission Factors, Final Section Chapter 2.4 Municipal Solid Waste Landfills, November 1998, http:// www.epa.gov/ttn/chief/ap42/ch02/index.html, accessed August, 2015. (25) Zavala-Araiza, D. Ph.D. Thesis, University of Texas at Austin, 2014.

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DOI: 10.1021/acs.accounts.6b00081 Acc. Chem. Res. XXXX, XXX, XXX−XXX