Aircraft-based mass balance estimate of methane emissions from offshore gas facilities in the Southern North Sea

Atmospheric methane (CH4) concentrations have more than doubled since the beginning of the industrial age, making CH4 the second most important anthropogenic greenhouse gas after carbon dioxide (CO2). The oil and gas sector represent one of the major anthropogenic CH4 emitters as it is estimated to account for 22 % of global anthropogenic CH4 emissions. An airborne field campaign was conducted in April&ndash;May 2019 to study CH4 emissions from offshore gas facilities in the Southern North Sea with the aim to derive emission estimates using a top-down (measurement-led) approach. We present CH4 fluxes for six UK and five Dutch offshore platforms/platform complexes using the well-established mass balance flux method. We identify specific gas production emissions and emission processes (venting/fugitive or flaring/combustion) using observations of co-emitted ethane (C2H6) and CO2. We compare our top-down estimated fluxes with a ship-based top-down study in the Dutch sector and with bottom-up estimates from a globally gridded annual inventory, UK national annual point-source inventories, and with operator-based reporting for individual Dutch facilities. In this study, we find that all inventories, except for the operator-based facility-level reporting, underestimate measured emissions, with the largest discrepancy observed with the globally gridded inventory. Individual facility reporting, as available for Dutch sites for the specific survey date, shows better agreement with our measurement-based estimates. For all sampled Dutch installations together, we find that our estimated flux of (122.7 &plusmn; 9.7) kg h-1 deviates by a factor 0.7 (0.35&ndash;12) from reported values (183.1 kg h-1). Comparisons with aircraft observations in two other offshore regions (Norwegian Sea and Gulf of Mexico) show that measured, absolute facility-level emission rates agree with the general distribution found in other offshore basins despite different production types (oil, gas) and gas production rates, which vary by two orders of magnitude. Therefore, mitigation is warranted equally across geographies.</p

Facility level measurement of offshore oil and gas installations from a medium-sized airborne platform : method development for quantification and source identification of methane emissions

Emissions of methane (CH4) from offshore oil and gas installations are poorly ground-truthed, and quantification relies heavily on the use of emission factors and activity data. As part of the United Nations Climate & Clean Air Coalition (UN CCAC) objective to study and reduce short-lived climate pollutants (SLCPs), a Twin Otter aircraft was used to survey CH4 emissions from UK and Dutch offshore oil and gas installations. The aims of the surveys were to (i) identify installations that are significant CH4 emitters, (ii) separate installation emissions from other emissions using carbon-isotopic fingerprinting and other chemical proxies, (iii) estimate CH4 emission rates, and (iv) improve flux estimation (and sampling) methodologies for rapid quantification of major gas leaks. In this paper, we detail the instrument and aircraft set-up for two campaigns flown in the springs of 2018 and 2019 over the southern North Sea and describe the developments made in both the planning and sampling methodology to maximise the quality and value of the data collected. We present example data collected from both campaigns to demonstrate the challenges encountered during offshore surveys, focussing on the complex meteorology of the marine boundary layer and sampling discrete plumes from an airborne platform. The uncertainties of CH4 flux calculations from measurements under varying boundary layer conditions are considered, as well as recommendations for attribution of sources through either spot sampling for volatile organic compounds (VOCs) /δ 13CCH4 or using in situ instrumental data to determine C2H6-CH4 ratios. A series of recommendations for both planning and measurement techniques for future offshore work within marine boundary layers is provided

Quantification and assessment of methane emissions from offshore oil and gas facilities on the Norwegian continental shelf

The oil and gas (O&G) sector is a significant source of methane (CH4) emissions. Quantifying these emissions remains challenging, with many studies highlighting discrepancies between measurements and inventory-based estimates. In this study, we present CH4 emission fluxes from 21 offshore O&G facilities collected in 10 O&G fields over two regions of the Norwegian continental shelf in 2019. Emissions of CH4 derived from measurements during 13 aircraft surveys were found to range from 2.6 to 1200 t yr−1 (with a mean of 211 t yr−1 across all 21 facilities). Comparing this with aggregated operator-reported facility emissions for 2019, we found excellent agreement (within 1σ uncertainty), with mean aircraft-measured fluxes only 16 % lower than those reported by operators. We also compared aircraft-derived fluxes with facility fluxes extracted from a global gridded fossil fuel CH4 emission inventory compiled for 2016. We found that the measured emissions were 42 % larger than the inventory for the area covered by this study, for the 21 facilities surveyed (in aggregate). We interpret this large discrepancy not to reflect a systematic error in the operator-reported emissions, which agree with measurements, but rather the representativity of the global inventory due to the methodology used to construct it and the fact that the inventory was compiled for 2016 (and thus not representative of emissions in 2019). This highlights the need for timely and up-to-date inventories for use in research and policy. The variable nature of CH4 emissions from individual facilities requires knowledge of facility operational status during measurements for data to be useful in prioritising targeted emission mitigation solutions. Future surveys of individual facilities would benefit from knowledge of facility operational status over time. Field-specific aggregated emissions (and uncertainty statistics), as presented here for the Norwegian Sea, can be meaningfully estimated from intensive aircraft surveys. However, field-specific estimates cannot be reliably extrapolated to other production fields without their own tailored surveys, which would need to capture a range of facility designs, oil and gas production volumes, and facility ages. For year-on-year comparison to annually updated inventories and regulatory emission reporting, analogous annual surveys would be needed for meaningful top-down validation. In summary, this study demonstrates the importance and accuracy of detailed, facility-level emission accounting and reporting by operators and the use of airborne measurement approaches to validate bottom-up accounting

Jlbox v1.1: A Julia-based multi-phase atmospheric chemistry box model

As our knowledge and understanding of atmospheric aerosol particle evolution and impact grows, designing community mechanistic models requires an ability to capture increasing chemical, physical and therefore numerical complexity. As the landscape of computing software and hardware evolves, it is important to profile the usefulness of emerging platforms in tackling this complexity. Julia is a relatively new programming language that promises computational performance close to that of Fortran, for example, without sacrificing the flexibility offered by languages such as Python. With this in mind, in this paper we present and demonstrate the initial development of a high-performance community mixed-phase atmospheric 0D box model, JlBox, written in Julia. In JlBox v1.1 we provide the option to simulate the chemical kinetics of a gas phase whilst also providing a fully coupled gas-particle model with dynamic partitioning to a fully moving sectional size distribution, in the first instance. JlBox is built around chemical mechanism files, using existing informatics software to parse chemical structures and relationships from these files and then provide parameters required for mixed-phase simulations. In this study we use mechanisms from a subset and the complete Master Chemical Mechanism (MCM). Exploiting the ability to perform automatic differentiation of Jacobian matrices within Julia, we profile the use of sparse linear solvers and pre-conditioners, whilst also using a range of stiff solvers included within the expanding ODE solver suite the Julia environment provides, including the development of an adjoint model. Case studies range from a single volatile organic compound (VOC) with 305 equations to a “full” complexity MCM mixed-phase simulation with 47 544 variables. Comparison with an existing mixed-phase model shows significant improvements in performance for multi-phase and mixed VOC simulations and potential for developments in a number of areas.ISSN:1991-9603ISSN:1991-959