Methane (CH4) emissions to the atmosphere from the oil and gas sector in Romania remain highly uncertain despite their relevance for the European Union’s goals to reduce greenhouse gas emissions. Measurements of CH4 isotopic composition can be used for source attribution, which is important in top-down studies of emissions from extended areas. We performed isotope measurements of CH4 in atmospheric air samples collected from an aircraft (24 locations) and ground vehicles (83 locations), around oil and gas production sites in Romania, with focus on the Romanian Plain. Ethane to methane ratios were derived at 412 locations of the same fossil fuel activity clusters. The resulting isotopic signals (δ13C and δ2H in CH4) covered a wide range of values, indicating mainly thermogenic gas sources (associated with oil production) in the Romanian Plain, mostly in Prahova county (δ13C from –67.8 ± 1.2 to –22.4 ± 0.04 ‰ Vienna Pee Dee Belmnite; δ2H from –255 ± 12 to –138 ± 11 ‰ Vienna Standard Mean Ocean Water) but also the presence of some natural gas reservoirs of microbial origin in Dolj, Ialomiţa, Prahova, and likely Teleorman counties. The classification based on ethane data was generally in agreement with the one based on CH4 isotopic composition and confirmed the interpretation of the gas origin. In several cases, CH4 enhancements sampled from the aircraft could directly be linked to the underlying production clusters using wind data. The combination of δ13C and δ2H signals in these samples confirms that the oil and gas production sector is the main source of CH4 emissions in the target areas. We found that average CH4 isotopic signatures in Romania are significantly lower than commonly used values for the global fossil fuel emissions. Our results emphasize the importance of regional variations in CH4 isotopes, with implications for global inversion modeling studies.

Large reductions of greenhouse gas (GHG) emissions to the atmosphere are required to mitigate ongoing climate change. The irreversible impacts of a global warming of more than 1.5°C above preindustrial levels were highlighted in a special report from the Intergovernmental Panel on Climate Change (IPCC, 2018). Limiting this increase to 1.5°C with a reasonably high probability requires not only net-zero emissions of carbon dioxide (CO2) by 2055 but also a reduction of methane (CH4) and black carbon emissions by 35% or more by 2050, relative to 2010 (IPCC, 2018). The European Union (EU) recently incorporated a net-zero emission objective for all GHGs by 2050 (European Green Deal; European Commission, 2019). In 2018, reported GHG emissions by EU countries (including the United Kingdom) were more than 4 billion tons CO2 equivalent, with a contribution of 11% from CH4 (European Environment Agency, 2020).

In 2019, the European Green Deal specially mentioned the necessity to “address the issue of energy-related methane emissions” (European Commission, 2019). Reported fugitive emissions from the extraction and handling of coal, oil, and natural gas were responsible for 12% of the EU’s total CH4 emissions in 2018 (Crippa et al., 2019). In the United States, fugitive CH4 from the natural gas supply chain was reported to be equivalent to total CO2 emissions generated by its combustion (Alvarez et al., 2018). This is due to the global warming potential of CH4 being 86 larger than the one of CO2 over a 20 years-time horizon, including carbon cycle feedbacks (IPCC, 2013). An increased focus on CH4 fugitive emissions is therefore particularly interesting for efficiently reducing GHG emissions.

GHG emissions are reported for each country using bottom-up approach (data-driven inventories), but top-down studies (atmospheric measurements and modeling) help verifying these estimates (Saunois et al., 2020). Romania is the fourth and third largest producer of crude oil and natural gas in the EU (including the United Kingdom), respectively (British Petroleum, 2020). It is especially relevant to investigate the CH4 emissions in Romania as this region is not as well covered by atmospheric measurements than Western Europe (Integrated Carbon Observation System Research Infrastructure, 2019). The ROmanian Methane Emissions from Oil & gas (ROMEO) project (Röckmann, 2020) aims to provide experimental quantification of methane emissions from oil and gas extraction activities. In this framework, the present work reports methane isotopic data of atmospheric air samples collected mainly in the Romanian Plain, a major oil–gas production region in Romania.

As described in more detail below, the measurements of CH4 isotopic composition (stable C and H isotope ratios) are widely used to characterize the sources of methane in atmospheric air samples (Levin et al., 1993; Tarasova et al., 2006; Röckmann et al., 2016; Townsend-Small et al., 2016; Zazzeri et al., 2016; Hoheisel et al., 2019; Lu et al., 2021), following genetic (thermogenic vs. microbial) CH4 isotopic categorization (Schoell, 1980; Milkov and Etiope, 2018). The ethane (C2H6) to methane (C2:C1) ratio is also frequently used in atmospheric studies (Lopez et al., 2017; Mielke-Maday et al., 2019; Maazallahi et al., 2020) as an additional proxy of the gas origin, since thermogenic and microbial gas have different molecular compositions: Ethane (as well as higher hydrocarbons) is abundant in thermogenic reservoirs, with or without oil, and is practically absent in microbial gas. We note, however, that also high maturity thermogenic gas can be “dry,” ethane-free (Schoell, 1983; Milkov and Etiope, 2018), and this may confuse the genetic attribution of the gas based only on the lack of ethane. The CH4 isotopic characterization can be used as tracer for the different sources in atmospheric transport models and inversions at different scales (Bousquet et al., 2006; Monteil et al., 2011; Houweling et al., 2017; Bergamaschi et al., 2018; Fujita et al., 2020) and therefore help improving the methane budget. More measurements of CH4 source isotopic composition reduce the uncertainties in the signatures assigned to the different sources and to the resulting emission estimates.

The present study combined CH4 isotopic and C2:C1 measurements in atmospheric air samples collected from aircraft and ground vehicles in different areas in Romania. From these measurements, we first determine the isotopic signature of CH4 emissions from oil and gas production in Romania. Then, we investigate whether we can attribute CH4 enhancements from aircraft measurements to the oil and gas extraction activities. Finally, we aim at providing further insight into formation processes of the fossil fuel reservoirs exploited in the Romanian Plain, based on both our results and previous literature.

### 2.1. Sampling procedure

The samples were taken during measurement surveys from an aircraft and from vehicles on the ground. The locations of all CH4 enhancements that were characterized regarding isotopic compositions and/or C2:C1 ratio are presented in Figure 1 and summarized in Table 1. An enhancement describes a noticeable (usually from 100 ppb) increase in χ(CH4) observed on a mobile analyzer. The target areas include important oil and gas basins and production sites in Romania.

Figure 1.

Target region and sampling locations during the ROmanian Methane Emissions from Oil & Gas campaign. (a) Overview of target regions where aerial raster flights were performed: P = Prahova, I = Ialomita, Te = Teleorman, O = Olt, D = Dolj, Tr = Transylvania, and M = Moldavia. The reservoir locations were provided by the National Agency for Mineral Resources (Georgescu, 2019). (b) Zoom on region P and its division in 9 clusters: P1 (with subcluster P1.1), P2, P3, P4, P5, P6, P7, P8, and P9. Blue squares: Locations of isotopically characterized χ(CH4) anomalies from aircraft (U: unknown source). Green circles: Locations of isotopically characterized χ(CH4) anomalies from ground vehicles. Red circles: Location of ground-based C2:C1 measurements. Yellow triangles: Previously sampled gas seeps and mud volcanoes (Baciu et al., 2018). © EuroGeographics for the administrative boundaries, OpenStreetMap contributors for the map image. DOI: https://doi.org/10.1525/elementa.2021.000092.f1

Figure 1.

Target region and sampling locations during the ROmanian Methane Emissions from Oil & Gas campaign. (a) Overview of target regions where aerial raster flights were performed: P = Prahova, I = Ialomita, Te = Teleorman, O = Olt, D = Dolj, Tr = Transylvania, and M = Moldavia. The reservoir locations were provided by the National Agency for Mineral Resources (Georgescu, 2019). (b) Zoom on region P and its division in 9 clusters: P1 (with subcluster P1.1), P2, P3, P4, P5, P6, P7, P8, and P9. Blue squares: Locations of isotopically characterized χ(CH4) anomalies from aircraft (U: unknown source). Green circles: Locations of isotopically characterized χ(CH4) anomalies from ground vehicles. Red circles: Location of ground-based C2:C1 measurements. Yellow triangles: Previously sampled gas seeps and mud volcanoes (Baciu et al., 2018). © EuroGeographics for the administrative boundaries, OpenStreetMap contributors for the map image. DOI: https://doi.org/10.1525/elementa.2021.000092.f1

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Table 1.

Overview and nomenclature of the target regions where methane isotopic signatures and C2:C1 ratios were determined and the number of source characterizations per region. DOI: https://doi.org/10.1525/elementa.2021.000092.t1

CH4 Isotopic SignaturesC2H6:CH4 Ratios
Region NameRegion IDRaster FlightsGround SurveysGround Surveys
Prahova P1 8 (4 + 4)a 14 81
P2  13 30
P3
P4  118
P5  29
P6   34
P7   28
P8   33
P9  15
Teleorman Te1
Te2  17
Ialomita 39
Dolj  11
Olt
Transylvania Tr
Moldavia
Others
Total 24 83 412
CH4 Isotopic SignaturesC2H6:CH4 Ratios
Region NameRegion IDRaster FlightsGround SurveysGround Surveys
Prahova P1 8 (4 + 4)a 14 81
P2  13 30
P3
P4  118
P5  29
P6   34
P7   28
P8   33
P9  15
Teleorman Te1
Te2  17
Ialomita 39
Dolj  11
Olt
Transylvania Tr
Moldavia
Others
Total 24 83 412

aFrom separate flights in the west and in the east (Figure 1).

We performed in situ measurements from a BN2 aircraft from the National Institute of Aerospace Research “ELIE CARAFOLI” (INCAS). Air samples were collected during 10 research flights on 9 days between October 2 and 17, 2019, over 7 regions of interest. The target areas were covered following a raster pattern (ca. 5 km width between the different legs), orientated perpendicular to the wind direction, and flying generally upwind. An example raster flight path is shown in Figure S1 of the supplementary material. The raster was generally flown at an altitude between 100 and 200 m above ground to be able to detect CH4 enhancements from surface sources. We used a cavity ring-down spectroscopy (CRDS) analyzer onboard the aircraft (GasScouter G4302, Picarro, Santa Clara, CA, USA), to detect concentration elevations for determining when to collect samples. Unfortunately, due to an instrument malfunction, the ethane mode of the G4302 instrument was not operational during the campaign, therefore the instrument only measured CH4 mole fractions (χ(CH4)), at a measurement frequency of 1 and only operated at strongly reduced precision (instrument noise on the χ(CH4) reading was approximately 200 ppb). Therefore, the CRDS analyzer was not used for quantification (another instrument was dedicated), but only to identify zones of CH4 enhancements and sampling, which was still possible for significant enhancements, despite the reduced precision.

The instrument drew air through a 1/4” o.d. Teflon line that was connected to an air inlet at the outside, on the top-left of the cockpit. A 10-m 1/2” o.d. Dekabon tube was mounted on the outflow of the G4302 analyzer as a buffer volume. At a flow rate of 2.2 L/min, this volume is flushed in 15 s, so after a signal was detected by the instrument, we had about 15 s to decide whether it was significant enough to take a sample. If so, we diverted the air in the buffer volume toward the sample receptacle (2 L Supel™-Inert Multi-Layer Foil sample bags, Sigma-Aldrich Co. LLC, Saint Louis, USA). In some cases, the raster pattern of the flights allowed us to cross a zone of enhanced χ(CH4) several times, and we collected several samples of the same suspected source. A total of 117 samples were taken from 31 CH4 enhancements. The average background χ(CH4) was 1975 ± 33 ppb, and CH4 mole fraction enhancements ranged from 30 to 300 ppb above background. We only retained the samples with more than 60 ppb CH4 above background and obtained CH4 isotopic signals for 24 source locations.

Ground-based surveys were performed on 16 days between September 30 and October 19, 2019, targeted on 6 regions of interest in the Romanian Plain. The 3 ground teams that collected samples for this study traveled by car or truck, measuring CH4 mole fractions using mobile analyzers (Ultraportable Greenhouse Gas Analyzer, Los Gatos Research, San Jose, CA, USA; GasScouter G4302 and G2201-i isotopic analysers, Picarro, Santa Clara, CA, USA; LI-7810 Trace Gas Analyzer, LI-COR, Lincoln, USA; Dual Laser Trace Gas Monitor, Aerodyne Research Inc., Billerica, USA). Once a CH4 enhancement (ca. >200 ppb above background) was identified, the vehicle stopped and ambient air was collected in sample bags (2 L Supel™_¢-Inert Multi-Layer Foil, Sigma-Aldrich Co. LLC, St. Louis, MO, USA; 3 L FlexFoil PLUS, SKC Inc., Eighty Four, PA, USA). One to three samples were taken for each χ(CH4) anomaly, and 1 or 2 background samples were taken every survey day, in each region. A total of 161 samples were taken during ground surveys from 84 different sites.

Measurements of ethane and methane were performed in two vehicles during ground surveys. The surveys were performed on 16 days from October 1 to 18, 2019. In 1 car, a second G4302 instrument sampled air through a 1/2” o.d. teflon tube from the roof top of a car and continuously measured CH4 and C2H6 at a frequency of about 1 Hz and a flow rate of 2.2 L/min. The noise was approximately 100 and 15 ppb around background level for CH4 and C2H6, respectively. The instrument was installed on the back seat of the vehicle, running either on an internal battery or an external battery supply. The instrument connected to a tablet via Wi-Fi, on which the measured mole fractions were displayed with a delay of 5 s.

The second vehicle was equipped with a Dual Laser Trace Gas Monitor, based on a tunable infrared laser direct absorption spectroscopy using a combined quantum cascade laser and interband cascade laser (Aerodyne Research Inc., Billerica, MA, USA). Air was sampled through an RVS central inlet at the front of the trailer with a diameter of 60 mm at 3-m height, from which a 1/4” polyethylene tube goes to the instrument. CH4 and C2H6 were measured continuously at a frequency of 1 Hz, with a flow rate of 6 L/min and a precision of 2.4 and 0.1 ppb, respectively. Precision is here reported as 3 times the standard deviation of 6-min constant concentration reading. The instrument was installed in the trailer, which was facilitated with infrastructure for electricity, a battery pack to run the mobile laboratory for 24 h, a router, and an air inlet. While driving, the measurements were displayed on a laptop, connected via Wi-Fi to the instrument with a delay of 5 s.

### 2.2. Isotope measurements

All samples were measured for χ(CH4), δ13C, and δ2H in CH4 at the Institute for Marine and Atmospheric Research Utrecht (IMAU) between October 8 and December 17, 2019. The analytical system is described in detail in Röckmann et al. (2016). The procedure is based on the extraction of CH4 from the other air components, followed by its conversion into CO2 or H2 before isotope measurement using isotopic ratio mass spectrometry (IRMS). Measurements of δ13C or δ2H were performed separately, using 10–60 mL of sample air, depending on the CH4 content. Each isotope measurement also returns a χ(CH4) value, because the signal intensity is proportional to the amount of extracted CH4. The system allows to process samples with χ(CH4) in the same order of magnitude as ambient air. Some higher concentration samples were diluted with pure N2 prior to measurement. Each sample was measured 2–4 times for both δ13C and δ2H, leading to an average uncertainty of 0.069 and 1.4 ‰, respectively, and of 5 ppb for χ(CH4).

All reported isotopic values are relative to international reference materials: Vienna Pee Dee Belmnite (V-PDB) for δ13C and Vienna Standard Mean Ocean Water (V-SMOW) for δ2H. To do so, the sample measurements were alternated with a reference cylinder of ambient air, containing 1970.0 ppb CH4 with δ13C = –48.072 (±0.0261) ‰ V-PDB and δ2H = –88.311 (±0.3371) ‰ V-SMOW. The mole fractions were determined after measurements with a G2301 Gas Concentration Analyzer, Picarro, Santa Clara, CA, USA (precision at 5 min < 0.22 ppb). To calibrate the reference cylinder against the international scale for isotope ratios, it was measured repetitively (20 times) in the IMAU lab, against 2 other gases previously measured at the Max Planck Institute in Jena, Germany (Sperlich et al., 2016). The calibration of the reference gas was done in September 2019.

### 2.3. Data analysis

#### 2.3.1. Calculation of isotopic source signatures

The Keeling (1958) plot method was applied to the isotopic data of each sampled χ(CH4) anomaly. It is a mass balance approach used to derive the isotopic signature of an emission source, which is added to a stable background. This translates to the following expressions:

$δm=cbg*(δbg−δS)(1/cm)+δS,$
1

where c is the mole fraction and δ is the isotopic signature (δ13C or δ2H) of background (bg), source (S), or measured (m) CH4. Thus, the source isotopic signature (δS) is given by the y-intercept of the regression line, when plotting δm against 1/cm.

A prerequisite for this approach is that the background mole fractions and the isotopic values of background and source are stable over the sampling time period of each peak. To account for potential changes in the background CH4 from 1 day and region to another, a sample of background air was taken for each measurement day and area. We assumed a stable background for each location, given that we used the background sampled on the same day and in the same region in each of the plots. In order to confirm that variations in the background do not cause significant biases, we also evaluated our results using the Miller–Tans method (Miller and Tans, 2003), which is suitable for calculating isotopic source signatures with a varying background, and found very similar source signatures.

For all linear regressions, the orthogonal distance regression (Boggs and Rogers, 1990) fitting method was used.

#### 2.3.2. Calculation of C2:C1 ratios

CH4 and C2H6 data were extracted from the in situ measurements from two survey vehicles when we detected significant CH4 enhancements in the vicinity of oil and gas facility locations reported by the regional operator. For each of these locations, we determined C2:C1 ratios from the slope of the linear regression between χ(C2H6) and χ(CH4) measured values when a minimum excess threshold for CH4 of 100 ppb above background was exceeded. C2:C1 ratios smaller than 0.0004 were set to 0.

#### 2.3.3. Definition and classification of CH4 sources

Methane origin is generally biotic (Hunt, 1996; Clayton, 2005), including (1) thermal degradation of organic matter in sedimentary rocks (thermogenic gas), (2) metabolic reactions by certain microorganisms (microbial gas), and (3) biomass burning (pyrogenic gas). In some geological environments, methane can also be generated by chemical reactions in the absence of organic matter (abiotic gas; Etiope and Sherwood Lollar, 2013; Etiope, 2017). Microbial gas generated in sedimentary rocks in petroleum systems is fossil (radiocarbon-free), so as thermogenic gas, and can also be categorized as “geological methane.” Modern microbial gas is generated in surface ecosystems (wetlands, marshes, rice paddies, etc.) and by animal enteric fermentation; this category is mostly referred to as “biological methane” (Schoell, 1983). Microbial CH4 generation may follow 2 metabolic pathways, methyl-type fermentation (anaerobic enteric fermentation, and to a larger extent in continental deposits and freshwater) and CO2 reduction (preferred pathway in marine environments; Whiticar, 1999).

Geological hydrocarbon gases can be “wet” or “dry,” indicating the presence or absence of C2+ alkanes (Etiope, 2017). Alkanes are generally present in thermogenic systems, with or without oil (liquid phase). Geological gas composition and CH4 isotope ratios are generally used to assess the origin of oil and gas associated methane. Milkov and Etiope (2018) compiled a global inventory of molecular and isotopic composition of natural gas from petroleum source rocks, reservoirs, and surface seeps and assessed the ranges of several variables corresponding to the various gas origins.

Natural gas is generally composed of a majority of CH4 (>70%), with C2H6 (1%–10%), along with heavier hydrocarbons (until C5–C9) in smaller amounts and traces of inorganic gases (Hunt, 1996; Clayton, 2005; Etiope, 2017). The relative ratios of these compounds in the emitted gas provide information on its origin. The ratio of methane (C1) over ethane (C2) plus propane (C3) is referred as Bernard ratio or C1/(C2+C3) (Bernard et al., 1976). Although we did not measure C3, the C2:C1 ratios already provide constraints on the Bernard ratio values. In addition, our new measurements were supplemented by data provided by the local oil and gas operator or the published literature. The operator provided hydrocarbon measurements at 14 sites, and Bernard ratios from another 13 sites were obtained from Filipescu and Huma (1979). Only 5 locations from these data sets are within our target regions and are compared with our measurements using figures 7 and 8 in Milkov and Etiope (2018). The operator also provided a classification of the oil density for the reservoirs we visited during our study.

It is important to consider that there are no published data on the CH4 isotopic composition of natural gas from oil and gas production in Romania; the only available isotopic data are from gas seeps in the Transylvanian (microbial gas) and Carpathian (thermogenic gas) basins, reported by Baciu et al. (2008), Etiope et al. (2009), Etiope et al. (2009a), and Baciu et al. (2018). We will compare our results also with these published signatures.

In thermogenic deposits, an increase in δ13C and δ2H in CH4 is correlated with the maturity of the source rocks (degree of degradation of organic matter; Schoell, 1980). Regarding the hydrocarbon composition, C2+ content initially increases from low maturity (wet gas, associated with oil), evolving into a drier gas, with less or no C2+ hydrocarbons at high maturity. Microbially formed CH4 is also dry and contains little or no C2+ hydrocarbons, but is significantly more depleted in 13C, and generally occurs in shallower deposits (Rice and Claypool, 1981; Whiticar, 1999). While mixing of different gases can change the isotopic CH4 composition of the original end members, gas migration among reservoirs and to the surface, being substantially advective, does not modify the isotopic CH4 ratio. Migration can, however, modify the C1:C2+ ratio, through molecular fractionation (Etiope et al., 2009). This hypothesis will be discussed in relation with our results and interpretation.

### 3.1. Overview of results

The isotopic source signatures at 83 locations related to oil and gas production are shown in Figure 2. One additional location was characterized: CH4 enhancements from cattle grazing in an open field. The isotopic signals related to fossil fuel operations range between –67.8 and –22.4 ‰ V-PDB for δ13C and from –259 to –138 ‰ V-SMOW for δ2H. The distinction between geological gas emissions and modern microbial sources is possible through the δ2H signatures: While δ13C values are similar for modern and fossil microbial gas, the δ2H values are generally lower for modern gas, which derives from fermentation pathway (Figure 2a). Although sampled at different locations (Figure 1), there is a good agreement between our results and the literature values from Baciu et al. (2018), who mainly sampled natural gas seeps in north Buzu, Vrancea, Gorj, and in Transylvania (δ13C from –67.4 to –29.0 ‰ V-PDB and δ2H from –228 to –145 ‰ V-SMOW; Figure 2a and b).

Figure 2.

Dual isotope plots of the isotopic source signatures and C2:C1 ratios. (a) Isotopic signatures from flight samples (squares, n = 24), including above Transylvania (yellow squares) and ground samples around oil (circles, n = 57) and gas (diamonds, n = 17)-related facilities. Additional samples were taken from gas leaks (red diamonds, n = 2) and ruminants (green triangle, n = 1). Values are compared with isotopic ranges from literature on Romanian geological sources (dotted black line; Baciu et al., 2018) and from natural gas formation pathways as in Milkov and Etiope (2018). MC = microbial CO2 reduction; MF = microbial fermentation; MS = secondary microbial; TH = thermogenic; AB = abiotic. The ambient value is an average from the flight samples with χ(CH4) < 2000 ppb (n = 10). (b) Same data, now overlain with reported source signature ranges from the literature (Sherwood et al., 2017). FF = fossil fuel; BB = biomass burning; WST = waste; AGR = agriculture. (c) C2:C1 ratios per type of source as classified by the operator (oil productions sites, n = 340; gas production sites, n = 62; other2 sites, n = 82), compared to typical ranges in CH4 from M = microbial, TD = thermogenic dry, and TW = thermogenic wet gas. DOI: https://doi.org/10.1525/elementa.2021.000092.f2

Figure 2.

Dual isotope plots of the isotopic source signatures and C2:C1 ratios. (a) Isotopic signatures from flight samples (squares, n = 24), including above Transylvania (yellow squares) and ground samples around oil (circles, n = 57) and gas (diamonds, n = 17)-related facilities. Additional samples were taken from gas leaks (red diamonds, n = 2) and ruminants (green triangle, n = 1). Values are compared with isotopic ranges from literature on Romanian geological sources (dotted black line; Baciu et al., 2018) and from natural gas formation pathways as in Milkov and Etiope (2018). MC = microbial CO2 reduction; MF = microbial fermentation; MS = secondary microbial; TH = thermogenic; AB = abiotic. The ambient value is an average from the flight samples with χ(CH4) < 2000 ppb (n = 10). (b) Same data, now overlain with reported source signature ranges from the literature (Sherwood et al., 2017). FF = fossil fuel; BB = biomass burning; WST = waste; AGR = agriculture. (c) C2:C1 ratios per type of source as classified by the operator (oil productions sites, n = 340; gas production sites, n = 62; other2 sites, n = 82), compared to typical ranges in CH4 from M = microbial, TD = thermogenic dry, and TW = thermogenic wet gas. DOI: https://doi.org/10.1525/elementa.2021.000092.f2

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C2:C1 ratios were obtained at 412 facilities, including 340 oil and 62 gas production facilities. Results for all sites are presented in Figures 2c and S2. Commonly used natural gas classification distinguishes between wet gas (C2:C1 > 0.1), thermogenic dry gas (C2:C1 < 0.1), and microbial dry gas (C2:C1 < 0.001; Clayton, 2005; Etiope, 2017). All C2:C1 ratios ranged from 0 to 0.91, therefore representing different types of natural gas, without a clear distinction between oil and gas production sites.

In Figure 3, we classified the ground surface δ13C isotopic signals depending on the exploitation of oil or gas, as reported by the operator for each site. We compare them with signatures observed from leaks in the natural gas distribution network and ruminants that we also sampled during our campaign. The δ13C of the natural gas from the network falls in the range of most sampled gas extraction facilities (in regions D, I, and P2). The δ13C from the ruminants (–61.6 ± 0.4 ‰) falls in the same range of values, which are typical of microbial CH4 formation. The most depleted δ13C signals measured at oil wells, with values < –50 ‰ V-PDB, can occur in the case of very early mature thermogenic formations, when thermogenic gas is mixed with adjacent microbial formations or when secondary microbial CH4 is produced. The distinction shown in Figure 3 is further discussed below, along with the analysis of the data from the different regions.

Figure 3.

δ13C in CH4 source signatures from surface samples. Histogram of δ13C-CH4 source signatures from samples around oil and gas facilities, compared with other sampled source signatures. Gas leaks (red points) were sampled from a leaky pipeline along a rural road (area P2, 44.949135° N, 25.77005° E) and in a residential area (Filipeştii de Târg, area P2, 44.963822° N, 25.794138° E). Ruminants (green point) were sampled in a grass field in region Te2 (44.362855° N, 25.321468° E). Values specified on the vertical lines are the means of each gas and oil extraction data and the mean of two modes of the oil extraction data. DOI: https://doi.org/10.1525/elementa.2021.000092.f3

Figure 3.

δ13C in CH4 source signatures from surface samples. Histogram of δ13C-CH4 source signatures from samples around oil and gas facilities, compared with other sampled source signatures. Gas leaks (red points) were sampled from a leaky pipeline along a rural road (area P2, 44.949135° N, 25.77005° E) and in a residential area (Filipeştii de Târg, area P2, 44.963822° N, 25.794138° E). Ruminants (green point) were sampled in a grass field in region Te2 (44.362855° N, 25.321468° E). Values specified on the vertical lines are the means of each gas and oil extraction data and the mean of two modes of the oil extraction data. DOI: https://doi.org/10.1525/elementa.2021.000092.f3

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### 3.2. Analysis per region

We can distinguish the CH4 isotopic signatures from the different geographical clusters we covered; our results for each of them are shown in Figure 4. The C2:C1 ratios are not available for the exact same locations than the CH4 isotopic signatures because they were obtained by different survey teams, but we can compare them on the cluster scale. The geographical distribution of the isotopic signatures and C2:C1 ratios is shown in the supplementary material (Figure S2). We evaluated the clusters with coinciding measurements of isotopic and C2:C1 ratios in Figure 5. Because we measured only ethane and methane (C2 and C1), we only report maximal values of Bernard ratios.

Figure 4.

Distribution of all CH4 isotopic composition results determined from ground samples per cluster. (a) C2:C1 ratios derived from all CH4 enhancements measured when driving in clusters of oil and gas extraction activities. (b) δ13C-CH4 and (c) δ2H-CH4 isotopic source signatures of CH4 enhancements sampled with the survey vehicles in the targeted clusters. DOI: https://doi.org/10.1525/elementa.2021.000092.f4

Figure 4.

Distribution of all CH4 isotopic composition results determined from ground samples per cluster. (a) C2:C1 ratios derived from all CH4 enhancements measured when driving in clusters of oil and gas extraction activities. (b) δ13C-CH4 and (c) δ2H-CH4 isotopic source signatures of CH4 enhancements sampled with the survey vehicles in the targeted clusters. DOI: https://doi.org/10.1525/elementa.2021.000092.f4

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Figure 5.

Bernard plot of the measurement results aggregated per cluster. Maximal Bernard ratio values with respect to δ13C-CH4 source signatures from measurements in the same clusters, around oil (circles) and gas (diamonds) facilities. Values are compared with genetic ranges from Milkov and Etiope (2018). MC = microbial CO2 reduction; MF = microbial fermentation; MS = secondary microbial; TH = thermogenic; AB = abiotic. The geographical locations of each clusters are shown in Figures 1 and 4. DOI: https://doi.org/10.1525/elementa.2021.000092.f5

Figure 5.

Bernard plot of the measurement results aggregated per cluster. Maximal Bernard ratio values with respect to δ13C-CH4 source signatures from measurements in the same clusters, around oil (circles) and gas (diamonds) facilities. Values are compared with genetic ranges from Milkov and Etiope (2018). MC = microbial CO2 reduction; MF = microbial fermentation; MS = secondary microbial; TH = thermogenic; AB = abiotic. The geographical locations of each clusters are shown in Figures 1 and 4. DOI: https://doi.org/10.1525/elementa.2021.000092.f5

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Additional measurements from the regional operator and the literature allowed to characterize the CH4 formation processes in the different oil or gas reservoirs in more detail. All the complementary data are presented in the supplementary material (Table S1, Figures S1, S3, and S4).

Most samples were collected in the district of Prahova (region P). The ranges of isotopic values and C2:C1 ratios in the clusters P1, P2, and P4 are very wide, which corresponds to a heterogenous thermal maturity of the oil reservoirs that are being processed there (Figure 4). Similar heterogeneity is also found in the clusters P6 and P7, showing C2:C1 ratios from 0.0021 to 0.61. However, we identified four clusters with comparatively consistent results:

• P2: δ13C values < –59 ‰ were measured around two natural gas facilities of the area. Five χ(CH4) enhancements near gas wells were measured in cluster P2, with C2:C1 < 0.002. Such values provide evidence for the presence of natural gas of microbial origin (Figure 5). Nearby oil extraction facilities in region P2 have higher C2:C1 ratios, and higher δ13C-CH4 values, typical for associated gas of thermogenic origin (Figure 5). Our measurements support the presence of multiple origins of the fossil fuel deposits in this cluster.

• P5: The hilly region east of Târgovişte (labelled P5) hosts a cluster of oil extraction facilities with well-defined isotopic composition of the emitted gas: δ13C between –50.6 and –37.3 ‰ V-PDB, δ2H between –251 and –199 ‰ V-SMOW. The relatively high C2:C1, between 0.056 and 0.37, confirms the presence of only wet thermogenic gas in the exploited reservoir.

• P9: This cluster displays the highest CH4 enhancements (χ(CH4) > 106 ppb) with particularly enriched and highly consistent isotopic signals from oil installations (n = 16): average δ13C = –36.8 ± 2.2 ‰ and δ2H = –160 ± 10 ‰. No other gas composition measurements was made in this region.

• P1.1: In this subregion of P1, the isotopic signatures suggest an intermediate maturity thermogenic or secondary microbial formation (δ13C from –51.0 to –41.4 ‰ and δ2H from –221 to –185 ‰; Figure S4). We obtained C2:C1 values > 0.02 for most locations in this cluster (41 of 45), indicating a relatively large ethane proportion (Bernard ratio < 50). These locations were nearby oil extraction and production facilities, which confirm the presence of wet gas of thermogenic origin (Figure 5). A Bernard ratio of 11.9 was reported by the operator for an installation 10 km away from this cluster. Subsurface measurements within the cluster (Filipescu and Huma, 1979) show a reservoir of oil with Bernard ratios from 9 to 18 at ca. 2,000-m depth, also consistent with our surface measurements. Therefore, most deposits in this region are likely from thermogenic CH4 formation, but can also be of secondary microbial origin.

The CH4 isotopic signatures we measured in the Dolj and Ialomita districts (regions D and I) are well defined (Figure 4), with relatively enriched δ2H and depleted δ13C, especially in Dolj. In this region, all facilities are associated with gas and condensed gas extraction plants. The same is true for the facilities with the lowest δ13C values sampled in Ialomita. The δ13C-CH4 signatures we obtained were < –57 ‰ for 11 of the 12 sampled locations in these two regions. Values of δ13C < –60 ‰ suggest the presence of dry gas with microbial origin (CO2 reduction pathway), as it is found in Transylvania (see the results of aircraft samples). Additional data support the hypothesis of the microbial origin of the extracted natural gas in regions in Dolj and Ialomita:

• Dolj (D): For a borehole southeast of Craiova, Filipescu and Huma (1979) mentioned shallow deposits of dry gas (ca. 30 km from the sampled sites, 200- to 300-m deep), with Bernard ratios > 3,000. This would confirm the presence of large microbial gas reservoirs, in this region of major natural gas production.

• Ialomita (I): Some facilities in Ialomita are related to oil extraction, from where we sampled CH4 with isotopic signatures showing a thermogenic origin. The distinction with gas facilities is confirmed by the C2:C1 results of this cluster: The values range from 0 to 0.76, with C2:C1 from 0 to 0.002 only found around gas installations and the higher ratios found around oil installations (Figure 5). Filipescu and Huma (1979) reported a vertical gas composition profile in the vicinity of the cluster where we carried out measurements, nearby the sampled cluster showing the presence of dry gas overlying associated gas with increasing C2 and C3 content (Bernard ratios of ca. 376 and 76 at –1,200 and –2,000 m, respectively). The gas sampled by the operator likely corresponds to this deeper layer of associated gas (Bernard ratio of 47). Thus, we conclude on microbial dry gas overlying oil deposits from our measurements in Ialomita; and this hypothesis matches the gas composition data.

The Teleorman region (Te) can be divided into west and east subareas (respectively, Te1 and Te2), separated by the river Teleorman, based on the isotopic signatures:

• Te1: This subcluster is characterized by the heaviest isotopic signatures found in this study, sampled around both oil and gas extraction facilities (n = 4): average δ13C = –28.1 ± 4.2 and δ2H = –149 ± 11 ‰ (Figure 4). These values correspond to very late maturity thermogenic gas (Figure 2a). The Bernard ratio reported by the operator for a close-by facility is between the values reported in Filipescu and Huma (1979), from associated gas at two different depths. Filipescu and Huma (1979) also reported the presence of nonassociated gas in the deepest layers (>2,000 m below surface), with a Bernard ratio of 452. Therefore, the facilities we sampled are likely to reach the deepest formations of high maturity deposits, at the stage where dry gas formation starts to occur.

• Te2: CH4 from oil wells (n = 5) was more isotopically depleted, especially in 13C: average δ13C = –54.6 ± 4.4 ‰ and δ2H = –199 ± 6 ‰ (Figure 4). This suggests an intermediate maturity thermogenic, secondary microbial, or mixed (with primary microbial gas) origin of the CH4. The origin cannot be further constrained by the large range of measured C2:C1 ratios (Figure 5). Low δ13C values (–58 ‰ and lower) usually indicate microbial CH4 and were measured at two oil wells. C2:C1 ratios from our surface measurements indicate relatively low ethane amounts (values from 0 to 0.08, n = 17), in agreement with Bernard ratios between 10 and 300 reported for one facility in the region by Filipescu and Huma (1979). However, the values reflect a certain heterogeneity, confirmed by the variations in δ13C by up to 10 ‰, and the presence of different densities in the oil deposits: from medium to heavy, compared to only light deposits in Te1. Here, the hypothesis of mixed gas origins is the most likely, including the presence of microbial dry CH4 reservoirs alongside wet gas reservoirs.

### 4.1. Isotopic signals from aircraft samples

Although the χ(CH4) excess above background was much lower than what was observed by the surface vehicles, we could characterize the isotopic source signals of 24 locations. The Keeling plots were rejected if:

• (1) the excess χ(CH4) above background was <60 ppb (based on IRMS measurements), and

• (2) the r2 of the regression fit was <0.5 for δ13C and δ2H.

All accepted Keeling plots are available in the Supplementary Material (Figure S5), as well as the resulting source signals (Table S2).

The map in Figure 6 shows the resulting isotopic signatures of the χ(CH4) anomalies sampled from the aircraft. They are compared with typical ranges of CH4 isotopic source signatures in Figure 4. δ13C ranged from –64.6 to –35.8 ‰ V-PDB, and δ2H from –404 to –127 ‰ V-SMOW, and the majority of them correspond to the emissions from fossil fuel extraction (Figure 2b). Based on the wind direction for each flight day and of the recorded altitudes, we could link 18 CH4 enhancements to underlying oil and gas extraction facilities and 6 to “unknown sources” (Figures 2 and 6). The CH4 enhancements of unknown origin sampled in the aircraft had the most depleted isotopic values: δ13C between –64.6 and –54.9 ‰ and δ2H between –404 and –239 ‰ and were generally observed at higher altitudes (up to 2,000 m above ground, Table S2) and outside the oil and gas production clusters. These isotope ranges correspond to CH4 from microbial fermentation processes (Figure 2), therefore likely coming from agriculture activities, waste management, or natural wetlands. The CH4 enhancements could, for example, be advected from densely populated areas (urban) or large agriculture facilities. Waste and agriculture emissions of biogenic origin account for 33% and 40%, respectively, of the 2015 CH4 anthropogenic emissions in Romania (Crippa et al., 2019). In comparison, fossil fuels fugitive emissions were estimated at 21%. Measurements carried out in the city of Bucharest (Fernandez et al., 2022) showed that biogenic emissions, especially from urban wastewater, were surprisingly widespread, much more than in other European cities.

Figure 6.

Isotopic signals derived from aircraft samples. Results of CH4 isotopic source signals for all enhancements sampled from the aircraft, related to oil and gas extraction activities or from unknown sources (U). (a) δ2H in CH4. (b) δ13C in CH4. DOI: https://doi.org/10.1525/elementa.2021.000092.f6

Figure 6.

Isotopic signals derived from aircraft samples. Results of CH4 isotopic source signals for all enhancements sampled from the aircraft, related to oil and gas extraction activities or from unknown sources (U). (a) δ2H in CH4. (b) δ13C in CH4. DOI: https://doi.org/10.1525/elementa.2021.000092.f6

Close modal

Most other isotopic signals determined on samples collected from the aircraft were in the range of signatures sampled from the oil and gas extraction facilities on the ground (Figure 2). Without considering the CH4 enhancements of unknown origins, the average δ2H signal was –196 ‰ V-SMOW. Most of the emissions from oil and gas facilities we characterized from ground sampling are in the Prahova region. It is also the area where most samples were taken from the aircraft, because of the location of the airfield. However, the wind often advected emissions from region O (Figure 7), where very few ground measurements were made. The relative enrichment in deuterium isotopes in the samples from the aircraft confirms the fossil fuel origin of the responsible CH4 emissions.

Figure 7.

Isotopic signals from the aircraft linked with the ones from the ground surface. Isotopic source signatures determined from aircraft samples (squares) and the suspected emission sources sampled from the ground (circles), when the wind directions (arrows) were matching: in west of Teleorman (Te, dark blue), north of Prahova (P, red), and Ialomita (I, green). No clear agreement was found in north of Prahova (P9, yellow), Olt and east of Teleorman (O and Te, wite). Note that the wind direction is irrelevant in Ialomita because the aircraft circled around the facility cluster during the sampling. The reservoir locations were provided by the National Agency for Mineral Resources (Georgescu, 2019). The isotopic signals are shown on a dual isotope plot (bottom-right) with isotopic ranges of geological formation pathways from Milkov and Etiope (2018). DOI: https://doi.org/10.1525/elementa.2021.000092.f7

Figure 7.

Isotopic signals from the aircraft linked with the ones from the ground surface. Isotopic source signatures determined from aircraft samples (squares) and the suspected emission sources sampled from the ground (circles), when the wind directions (arrows) were matching: in west of Teleorman (Te, dark blue), north of Prahova (P, red), and Ialomita (I, green). No clear agreement was found in north of Prahova (P9, yellow), Olt and east of Teleorman (O and Te, wite). Note that the wind direction is irrelevant in Ialomita because the aircraft circled around the facility cluster during the sampling. The reservoir locations were provided by the National Agency for Mineral Resources (Georgescu, 2019). The isotopic signals are shown on a dual isotope plot (bottom-right) with isotopic ranges of geological formation pathways from Milkov and Etiope (2018). DOI: https://doi.org/10.1525/elementa.2021.000092.f7

Close modal

The three χ(CH4) anomalies observed above Transylvania show relatively low δ13C values ( –63.2 ± 0.1, –62.3 ± 1.3, and –58.2 ± 1.3 ‰), typical of microbial CH4 gas (Figure 2a), and δ2H of –273 ± 26, –223 ± 20 and –188 ± 13 ‰. δ2H values >–250 ‰ are typical for the CO2 reduction pathway rather than fermentation (Milkov and Etiope, 2018) and are consistent with the isotopic data reported for gas seeps in the same basin (Baciu et al., 2018). Therefore, we likely sampled CH4 sources of microbially formed natural gas reservoirs at the two locations with δ2H > –250 ‰. This is confirmed by the relatively depleted δ13C values that we also found in natural gas leaks sampled on the ground. The presence of microbial gas reservoirs in Transylvania has been documented, for example, by Filipescu and Huma (1979), Pawlewicz (2005), and Baciu et al. (2018). The CH4 source of the third enhancement intercepted by the aircraft is more likely to be from agriculture or waste from urban settlements in the area.

Figure 7 shows the CH4 enhancements sampled from the aircraft that we could link to emissions sampled from the ground based on the wind directions. In Te1 and I regions, the isotopic signal from the aircraft compares well with signatures from the oil installations below, and we can confidently identify the oil and gas activities in the underlying clusters as the source of the CH4 enhancements observed from the aircraft. The distinct isotopic signatures measured in region Te1 (relatively enriched in heavy isotopes; see results from ground surface samples) are also found in the aircraft samples (Figure 7). In Prahova, we show the results of 2 of 8 CH4 enhancements observed from the aircraft, where the wind clearly came from clusters of oil and gas installations where we also sampled on the ground. Also here, the isotopic signals derived from the aircraft samples agree fall in the range of the ones observed at the ground, although this is a region with heterogenous isotopic signatures, which makes it difficult to precisely link a specific cluster to the isotopic signals from the aircraft (Figure 7).

The largest χ(CH4) anomalies observed from the aircraft were when flying above Ialomita, with values of 300 and 400 ppb above background. The underlying oil and gas cluster was visited several times by ground vehicles. The two locations with the lowest δ13C (–60.9 ± 0.032 and –67.8 ± 1.18 ‰) correspond to gas installations and the others are oil wells or processing plants. The CH4 enhancements observed from the aircraft likely originate from a specific processing plant (oil deposit, gas compression, and others) that was circled at low altitude. This facility was sampled two times from the ground with δ13C values of –48.5 ± 0.45 and –56.5 ± 0.13 ‰. The δ13C signals from the aircraft are in a similar range: –57.0 ± 0.22 and –51.4 ± 0.17 ‰. The range of isotopic values from this particular site suggests the presence of several CH4 sources, reflecting the different activities (storage, extraction, and gas recovery) and potential temporal variability (discussed in Section 5).

### 4.2. Implications of the aircraft results

CH4 enhancements were observed during each raster flight above the target areas (Figure 1), which include dense clusters of oil and gas installations. The isotopic signatures confirmed that the sampled emissions originate from the underlying oil and gas extraction activities. The total emissions from fossil fuel extraction clusters can be estimated from aircraft measurements, for example, using a mass balance approach (Hiller et al., 2014; Karion et al., 2015; Peischl et al., 2016; Schwietzke et al., 2017; Fiehn et al., 2020). Top-down approaches often rely on the use of regional-scale transport models in order to evaluate reported emission inventories (Xiao et al., 2008; Henne et al., 2016). Information on the CH4 isotopic signatures of the observed enhancements from the aircraft can be used for source attribution (Fisher et al., 2017), to constrain the measurement-based quantifications, and to verify model simulations on the origin of the emissions.

Previous studies used CH4 isotopic source signatures to constrain the CH4 budget globally (Schaefer et al., 2016; Schwietzke et al., 2016; Worden et al., 2017) and regionally (Röckmann et al., 2016; Bergamaschi et al., 2018; Menoud et al., 2020a). Mean isotopic values assigned to fossil fuel related emissions in the literature range between –37 and –44 ‰ for δ13C-CH4 (Schaefer et al., 2016; Schwietzke et al., 2016; Worden et al., 2017; Menoud et al., 2020b), and around –175 ‰ for δ2H-CH4 (Lu et al., 2021; Menoud et al., 2021), the latter being based on a substantially smaller sample size. For the specific case of the Romanian Plain, we suggest the use of average values from aircraft measurements made in this study: δ13C = –49.7 ± 6.4 ‰ and δ2H = –189 ± 38 ‰, from identified, mainly oil-related, fossil fuel activities. The average values from ground measurements around fossil fuel production sites in this study are δ13C = –46.0 ± 11.2 ‰ and δ2H = –188 ± 28 ‰, and within the range of uncertainty of the aircraft values.

The average isotopic signatures from our study do not take into account emissions from the production of natural gas in Transylvania and the distribution network. From the flight covering part of Transylvania, we found more depleted δ13C signatures than in the Romanian Plain, but we didn’t collect data on CH4 emissions samples on the ground. Regarding the gas network, Fernandez et al. (2022) measured significant emissions in Bucharest and with also a relatively depleted δ13C isotopic signature (confirmed by our measurements of two gas leaks; Figure 3). Therefore, the δ13C value for CH4 emissions from all fossil fuel activities in Romania is likely to be lower than the –49.7 ‰ suggested above and further different to the global values commonly assigned.

The χ(CH4) anomalies we observed from the aircraft were not all related to emissions from the oil and gas sector. The samples of “unknown” origin we collected from the aircraft, and 1 sample above Transylvania, had a distinct isotopic signal, with δ2H < –250 ‰, that corresponds to CH4 of microbial fermentation origin (Figure 2). Indeed, there are many other sources of CH4 emissions in Romania. According to the EDGAR v5.0 inventory (Crippa et al., 2019), the main anthropogenic CH4 sources in Romania in 2015 were the agriculture sector (40% of total emissions, including manure management) and waste management (33% of total emissions). Microbial fermentation can also occur in stagnant freshwater; therefore, lakes, swamps, and bogs are potential natural sources, in addition to the well-established natural gas seeps and mud volcanoes (Etiope et al., 2011). Future measurements could be targeted at constraining emissions from nonfossil fuel sources.

Schwietzke et al. (2017) emphasized the influence of episodic release from fossil fuel extraction or processing sites on atmospheric measurements. In this study, this was illustrated by the 2 flights performed over Ialomita (region I; on October 11 and 14, 2019), where the emissions very likely originated from the same facility that was circled by the aircraft (Figure 7). The isotopic signatures were δ13C = –57.0 ± 0.22 ‰ and δ2H = –131 ± 15 ‰ on the 11th, and δ13C = –51.4 ± 0.17 ‰ and δ2H = –176 ± 14 ‰ on the 14th. The results are statistically different, which reflects the diversity of releases, even from 1 localized facility. To evaluate the emissions from our target regions more precisely, it is necessary to combine data from several flights performed on several days and at different seasons.

The ground surface results show that we can determine the origin of emitted natural gas based on CH4 isotopic measurements at the surface. Whereas the signatures in some clusters show consistent signatures, results from other regions were very heterogenous (P1, P2, and P4; Figure 4). The C2:C1 ratios we measured are generally in agreement with the CH4 isotopic signatures. To support our conclusions, further measurements at the extraction and processing facilities would be beneficial, not only for gathering more data on the hydrocarbon composition but also to account for the different types of emissions that come from one facility. Cardoso-Saldaña et al. (2021) showed that the C2:C1 ratios are generally higher in storage tank emissions. There are also variations in the CH4 emissions of a facility because of the presence of different sources, for example, storage tanks do not emit continuously. Our approach of measuring the CH4 enhancements downwind of the facilities is sensitive to the variations in sources and their composition.

The analysis of other variables, especially total hydrocarbon contents, CO2 contents, and the isotopic composition of CO2 and C2H6 (Milkov, 2011; Milkov and Etiope, 2018), could help to further reduce the uncertainties in the origin of the gas emissions we investigated here. Nevertheless, we showed that atmospheric measurements allowed to draw conclusions on the geological origin of exploited gas reservoirs in the subsurface.

As part of the ROMEO project, we characterized CH4 emissions from 83 oil and gas production sites for source isotopic signatures and 412 for C2:C1 ratios. The δ13C and δ2H isotopic signatures were also determined at 24 locations sampled from an aircraft. Our data show that over the target areas, most CH4 significant enhancements that were encountered originated from the underlying oil and gas production activities. Thus, CH4 emissions from oil and gas extraction activities are the main emission source for such large point sources within our target areas. The CH4 isotopic composition over a certain area can sometimes be heterogeneous, but the distinction from other source categories than from oil and gas was still possible. This possibility of source attribution will support the quantitative interpretation of top-down emission estimates based on high-precision methane measurements that were also carried out on these and other flights in the same region.

Our results allow to characterize the origin of natural gas in several regions from atmospheric measurements. Both isotopic signatures and C2:C1 ratios indicated that most visited sites, related to oil production, emitted thermogenic gas. We also identified some microbial reservoirs, especially around gas production sites. New findings include the presence of microbial gas in at least four production areas of the Romanian Plain, located in the counties of Prahova, Ialomita, Dolj, and Teleorman. We also confirmed the presence of microbial, CH4 emissions due to the production of natural gas in Transylvania.

The average isotopic signatures for CH4 emissions from fossil fuel production over the Romanian Plain were –49.7 ± 6.4 ‰ V-PDB for δ13C and –189 ± 38 ‰ V-SMOW for δ2H, based on the measurements from the aircraft. The δ13C value possibly overestimates the average δ13C from fossil fuel activities in the whole country of Romania because it does not include emissions from natural gas production in Transylvania but is already lower than commonly used values for global fossil fuel emissions (Schwietzke et al., 2016). The global database of gas composition data made by Sherwood et al. (2017) did not include measurements made in Romania. Yet it is not the only place with relatively depleted δ13C-CH4 values in geological deposits: The database as well as recently published studies (Zazzeri et al., 2016; Lu et al., 2021) reported δ13C values < –60 ‰ V-PDB in emitted CH4 from coal or conventional gas exploitation in the United States, Australia, Poland, Japan, and other countries. Therefore, it is crucial to take into account the geographical variability of isotopic signatures when they are used to constrain the global or regional CH4 budget.

All of the data used in this study are publicly available on a Zenodo repository (https://doi.org/10.5281/zenodo.6319952).

• Table S1. Gas composition data measured at several extraction facilities by the operator in the regions where measurements were also carried out in this study.

• Table S2. Isotopic source signals of all χ(CH4) anomalies sampled from the aircraft and considered significant (excess χ(CH4) < 60 ppb and r2 < 0.5).

• Figure S1. Example of flight pattern.

• Figure S2. Results from ground surface sampling around oil and gas facilities in regions P and Te2.

• Figure S3. Gas composition data in the Romanian Plain.

• Figure S4. Genetic diagrams of gas molecular and isotopic compositions, per cluster.

• Figure S5. Keeling plots of all sampled CH4 enhancements from the aircraft.

We specially thank all other members of the ROmanian Methane Emissions from Oil & Gas team for their help during the campaign: Huilin Chen, Dominik Brunner, Oana Pîrvu, Mackenzie Smith, Niall Armstrong, Patryk Lakomiec, Sylvia Walter, Aurel Constantin, Sebastian Iancu, Alex Nica, Sorin Ghemulet, Constantin Visoiu, Cristian Pop, Alexandru Pana, Alexandru Tudor, Mihai Profir, Alin Scarlat, Lucian Cusa, Marius Corbu, Georgiana Grigoras, Sorin Vajaiac, Denisa Moaca, Vincent Edjabou, Julia Wietzel, Jaroslaw Necki, Pawel Jagoda, Jakub Baryzel, Andrei Radovici, Horatiu Stefanie, Alexandru Mereuta, Artur Ionescu, and Daniel Zavala-Araiza.

These surveys were funded by the ROmanian Methane Emissions from Oil & Gas project, funded by the Climate and Clean Air Coalition (CCAC) of UNEP under grant number PCA/CCAC/UU/DTIE19-EN652. This research project has also received funding from the European Union’s Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie Grant Agreement 722479 (MEMO2, https://h2020-memo2.eu).

The authors have no competing interests, as defined by Elementa, that might be perceived to influence the research presented in this article.

Contributed to conception and design: MM, TR.

Contributed to acquisition of data: MM, CV, HM, AH, IV, PB, AD, PK, MA, AC, CB, CS, MS, TR.

Contributed to analysis and interpretation of data: MM, CV, HM, GE, CB, TR.

Approved the submitted version for publication: MM, CV, HM, AH, IV, PB, AD, PK, SS, MA, AC, GE, CB, CS, MS, TR.

1.

Standard error of the mean.

2.

Includes disposal injection, power generator, and other.

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How to cite this article: Menoud, M, van der Veen, C, Maazallahi, H, Hensen, A, Velzeboer, I, van den Bulk, P, Delre, A, Korben, P, Schwietzke, S, Ardelean, M, Calcan, A, Etiope, G, Baciu, C, Scheutz, C, Schmidt, M, Röckmann, T. 2022. CH4 isotopic signatures of emissions from oil and gas extraction sites in Romania. Elementa: Science of the Anthropocene 10(1). DOI: https://doi.org/10.1525/elementa.2021.000092

Domain Editor-in-Chief: Detlev Helmig, Boulder AIR LLC, Boulder, CO, USA

Guest Editor: Arvind P. Ravikumar, The University of Texas at Austin, Austin, TX, USA

Knowledge Domain: Atmospheric Science

Part of an Elementa Forum: Oil and Natural Gas Development: Air Quality, Climate Science, and Policy

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.