Black carbon (BC) emissions from gas flaring in the oil and gas industry are postulated to have critical impacts on climate and public health, but actual emission rates remain poorly characterized. This paper presents in situ field measurements of BC emission rates and flare gas volume-specific BC yields for a diverse range of flares. Measurements were performed during a series of field campaigns in Mexico and Ecuador using the sky-LOSA optical measurement technique, in concert with comprehensive Monte Carlo-based uncertainty analyses. Parallel on-site measurements of flare gas flow rate and composition were successfully performed at a subset of locations enabling direct measurements of fuel-specific BC yields from flares under field conditions. Quantified BC emission rates from individual flares spanned more than 4 orders of magnitude (up to 53.7 g/s). In addition, emissions during one notable ∼24-h flaring event (during which the plume transmissivity dropped to zero) would have been even larger than this maximum rate, which was measured as this event was ending. This highlights the likely importance of superemitters to global emission inventories. Flare gas volume-specific BC yields were shown to be strongly correlated with flare gas heating value. A newly derived correlation fitting current field data and previous lab data suggests that, in the context of recent studies investigating transport of flare-generated BC in the Arctic and globally, impacts of flaring in the energy industry may in fact be underestimated.

No abstract

No abstract

We present a new framework for incorporating aerial measurements into comprehensive oil and gas sector methane inventories that achieves robust, independent quantification of measurement and sample size uncertainties, while providing timely source-level insights beyond what is possible in current official inventories. This “hybrid” inventory combines top-down, multi-pass aerial measurements with bottom-up estimates of unmeasured sources leveraging continuous probability of detection and quantification models for a chosen aerial technology. Notably, the combined Monte Carlo and “mirror-match” bootstrapping technique explicitly considers skewed source distributions and finite facility populations that have not been previously addressed. The protocol is demonstrated to produce a comprehensive upstream oil and gas sector methane inventory for British Columbia, Canada, which while approximately 1.7 times higher than the most recent official bottom-up inventory, reveals a lower methane intensity of produced natural gas (< 0.5%) than comparable estimates for several other regions. Finally, the developed method and data are used to upper bound the potential influence of source variability/intermittency on the overall inventory, directly addressing an open question in the literature. Results demonstrate that even for an extreme case, variability/intermittency effects can be addressed by sample size and survey design and have a minor impact on overall inventory uncertainty.

Critical mitigation of methane emissions from the oil and gas (OG) sector is hampered by inaccurate official inventories and limited understanding of contributing sources. Here we present a framework for incorporating aerial measurements into comprehensive OG sector methane inventories that achieves robust, independent quantification of measurement and sample size uncertainties, while providing timely source-level insights. This hybrid inventory combines top-down, source-resolved, multi-pass aerial measurements with bottom-up estimates of unmeasured sources leveraging continuous probability of detection and quantification models for a chosen aerial technology. Notably, the technique explicitly considers skewed source distributions and finite facility populations that have not been previously addressed. The protocol is demonstrated to produce a comprehensive upstream OG sector methane inventory for British Columbia, Canada, which while approximately 1.7 times higher than the most recent official bottom-up inventory, reveals a lower methane intensity of produced natural gas (<0.5%) than comparable estimates for several other regions. Finally, the method and data are used to upper bound the potential influence of source variability/intermittency, directly addressing an open question in the literature. Results demonstrate that even for an extreme case, variability/intermittency effects can be addressed by sample size and survey design and have a minor impact on overall inventory uncertainty.

Thorough understanding of probabilities of detection (POD) and quantification uncertainties is fundamentally important when applying aerial measurement technologies as part of alternative means of emission limitation (AMEL) or alternate fugitive emissions management programs (Alt-FEMP), as part of monitoring, reporting, and verification (MRV) efforts, and in surveys designed to support measurement-based emissions inventories and mitigation tracking. This paper presents a robust framework for deriving continuous probability of detection functions and quantification uncertainty models for aerial measurement techniques based on controlled release data. Using extensive fully- and semi-blinded controlled release experiments to test Bridger Photonics Inc.’s Gas Mapping LiDAR (GML), as well as available release data for Kairos LeakSurveyor and NASA/JPL AVIRIS-NG technologies, robust POD functions are derived that enable calculation of detection probability for any given source rate, wind speed, and flight altitude. Uncertainty models are separately developed that independently address measurement bias, bias variability, and measurement precision, allowing for a distribution of the true source rate to be directly calculated from the source rate estimated by the technology. Derived results demonstrate the potential of all three technologies in methane detection and mitigation, and the developed methodology can be readily applied to characterize other techniques or update POD and uncertainty models following future controlled release experiments. Finally, the analyzed results also demonstrate the importance of using controlled release data from a range of sites and times to avoid underestimating measurement uncertainties.

Researchers from myriad fields frequently seek to quantify and classify concentrations of carbonaceous aerosols as organic carbon (OC) or elemental carbon (EC). This is commonly accomplished using thermal-optical OC/EC analyzers (TOAs), which enable measurement via controlled thermal pyrolysis and oxidation under specific temperature protocols and within constrained atmospheres. Several commercial TOAs exist, including a semi-continuous instrument that enables on-line analyses in the field. This instrument employs an in-test calibration procedure that requires relatively frequent calibration. This article details a calibration protocol for this semi-continuous TOA and presents an open-source software tool for data analysis and rigorous Monte Carlo quantification of uncertainties. Notably, the software tool includes novel means to correct for instrument drift and identify and quantify the uncertainty in the OC/EC split point. This is a significant improvement on the uncertainty estimation in the manufacturer's software, which ignores split point uncertainty and otherwise uses fixed equations for relative and absolute errors (generally leading to underestimated uncertainties and often yielding non-physical results as demonstrated in several example data sets). The demonstrated calibration protocol and new software tool enabling accurate quantification of combined uncertainties from calibration, repeatability, and OC/EC split point are shared with the intent of assisting other researchers in achieving better measurements of OC, EC, and total carbon mass in aerosol samples. Video Link The video component of this article can be found at https://www.jove.com/video/59742/ 1) have been suggested to be the key component of PM responsible for adverse health effects and outcomes 2,3,4. Particulate carbon in the atmosphere is a critical climate pollutant, where different carbonaceous species are known to have variable, even opposite, impacts. Black carbon is potentially the second strongest direct radiative forcer in the earth's atmosphere 5,6,7,8. When deposited on snow and ice, black carbon also reduces the reflectivity of the arctic landscape, enhancing the absorption of sunlight, and increasing the rate of melt 9,10,11,12. Contrastingly, hygroscopic organic carbon particles act as cloud condensation nuclei, increasing the mean reflectivity of earth, and causing a cooling effect 13. Accurate classification of sampled carbonaceous material and concurrent quantification of measurement uncertainties are thus essential aspects of particulate matter measurements. Differentiating between organic and elemental carbon in a particulate-laden sample can be achieved using a thermal-optical analysis 14. Commercial, laboratory-based systems for thermal-optical carbon analyses have been created 15,16,17 including an on-line, semi-continuous analyzer 18 that enables the execution of thermal-optical analyses in the field. The present work describes a detailed procedure for calibrating this latter OCEC instrument (see Table of Materials) ...

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