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

Foulds, Amy; Allen, Grant; Shaw, Jacob T.; Bateson, Prudence; Barker, Patrick A.; Huang, Langwen; Pitt, Joseph R.; Lee, James D; Wilde, Shona E.; Dominutti, Pamela; Purvis, Ruth M.; Lowry, David; France, James L.; Fisher, Rebecca E.; Fiehn, Alina; Pühl, Magdalena; Bauguitte, Stéphane Jean-Bernard; Conley, Stephen A.; Smith, Mackenzie L.; Lachlan-Cope, Tom; Pisso, Ignacio; Schwietzke, Stefan

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.

2022

Quantification Approaches in Non-Target LC/ESI/HRMS Analysis: An Interlaboratory Comparison

Malm, Louise; Liigand, Jaanus; Aalizadeh, Reza; Alygizakis, Nikiforos; Ng, Kelsey; Fro̷kjær, Emil Egede; Nanusha, Mulatu Yohannes; Hansen, Martin; Plassmann, Merle; Bieber, Stefan; Letzel, Thomas; Balest, Lydia; Abis, Pier Paolo; Mazzetti, Michele; Kasprzyk-Hordern, Barbara; Ceolotto, Nicola; Kumari, Sangeeta; Hann, Stephan; Kochmann, Sven; Steininger-Mairinger, Teresa; Soulier, Coralie; Mascolo, Giuseppe; Murgolo, Sapia; Garcia-Vara, Manuel; López de Alda, Miren; Hollender, Juliane; Arturi, Katarzyna; Coppola, Gianluca; Peruzzo, Massimo; Joerss, Hanna; van der Neut-Marchand, Carla; Pieke, Eelco N.; Gago-Ferrero, Pablo; Gil-Solsona, Ruben; Licul-Kucera, Viktória; Roscioli, Claudio; Valsecchi, Sara; Luckute, Austeja; Christensen, Jan H.; Tisler, Selina; Vughs, Dennis; Meekel, Nienke; Talavera Andújar, Begoña; Aurich, Dagny; Schymanski, Emma L.; Frigerio, Gianfranco; Macherius, André; Kunkel, Uwe; Bader, Tobias; Rostkowski, Pawel; Gundersen, Hans; Valdecanas, Belinda; Davis, W. Clay; Schulze, Bastian; Kaserzon, Sarit; Pijnappels, Martijn; Esperanza, Mar; Fildier, Aurélie; Vulliet, Emmanuelle; Wiest, Laure; Covaci, Adrian; Macan Schönleben, Alicia; Belova, Lidia; Celma, Alberto; Bijlsma, Lubertus; Caupos, Emilie; Mebold, Emmanuelle; Le Roux, Julien; Troia, Eugenie; de Rijke, Eva; Helmus, Rick; Leroy, Gaëla; Haelewyck, Niels; Chrastina, David; Verwoert, Milan; Thomaidis, Nikolaos S.; Kruve, Anneli

Nontargeted screening (NTS) utilizing liquid chromatography electrospray ionization high-resolution mass spectrometry (LC/ESI/HRMS) is increasingly used to identify environmental contaminants. Major differences in the ionization efficiency of compounds in ESI/HRMS result in widely varying responses and complicate quantitative analysis. Despite an increasing number of methods for quantification without authentic standards in NTS, the approaches are evaluated on limited and diverse data sets with varying chemical coverage collected on different instruments, complicating an unbiased comparison. In this interlaboratory comparison, organized by the NORMAN Network, we evaluated the accuracy and performance variability of five quantification approaches across 41 NTS methods from 37 laboratories. Three approaches are based on surrogate standard quantification (parent-transformation product, structurally similar or close eluting) and two on predicted ionization efficiencies (RandFor-IE and MLR-IE). Shortly, HPLC grade water, tap water, and surface water spiked with 45 compounds at 2 concentration levels were analyzed together with 41 calibrants at 6 known concentrations by the laboratories using in-house NTS workflows. The accuracy of the approaches was evaluated by comparing the estimated and spiked concentrations across quantification approaches, instrumentation, and laboratories. The RandFor-IE approach performed best with a reported mean prediction error of 15× and over 83% of compounds quantified within 10× error. Despite different instrumentation and workflows, the performance was stable across laboratories and did not depend on the complexity of water matrices.

American Chemical Society (ACS)

2024

Quantification of Element Mass Concentrations in Ambient Aerosols by Combination of Cascade Impactor Sampling and Mobile Total Reflection X-ray Fluorescence Spectroscopy

Seeger, Stefan; Osan, Janos; Czömpöly, Ottó; Gross, Armin; Stosnach, Hagen; Stabile, Luca; Ochsenkuehn-Petropoulou, Maria; Tsakanika, Lamprini Areti; Lymperopoulou, Theopisti; Goddard, Sharon; Fiebig, Markus; Gaie-Levrel, Francois; Kayser, Yves; Beckhoff, Burkhard

MDPI

2021

Quantification of Global Ammonia Sources constrained by a Bayesian Inversion Technique (COMBAT)

Evangeliou, Nikolaos; Eckhardt, Sabine; Balkanski, Yves; Stohl, Andreas

2018

Quantification of microplastic in fillet and organs of farmed and wild salmonids - a comparison of methods for detection and quantification - SALMODETECT

Gomiero, Alessio; Haave, Marte; Bjorøy, Ørjan; Herzke, Dorte; Kögel, Tanja; Nikiforov, Vladimir; Øysæd, Kjell Birger

Microplastic (MP) is of growing concern to environmentaland humanhealth. Thisstudy investigated three analytical approachesto measure MPin tissues of salmonids. The studyaimed to 1) determine and demonstrate the sensitivity of current analytical methods for MP in salmon tissues for the three different quantitative methods, 2) compare the utility of the different methods in terms of cost, time and sensitivity 3) quantify MP in a relevant selection of tissues of farmedand wildsalmon in order to establish likely indicator organs for future documentation purposes. We here present the results, compare themethodsand discuss uncertainties and needs for further method development.

NORCE

2020

Quantification of sources of PCBs to the atmosphere in urban areas: A comparison of cities in North America, Western Europe and former Yugoslavia.

Gasic, B.; MacLeod, M.; Klanova, J.; Scheringer, M.; Ilic, P.; Lammel, G.; Pajovic, A.; Breivik, K.; Holoubek, I.; Hungerbühler, K.

2010

Quantifying black carbon from biomass burning by means of levoglucosan - a one year time series at the Arctic observatory Zeppelin.

Yttri, K. E.; Myhre, C.L.; Eckhardt, S.; Fiebig, M.; Dye, C.; Hirdman, D.; Ström, J.; Klimont, Z.; Stohl, A.

2014

Quantifying CH4 leaks from the Nordstream pipelines using ICOS data: updated estimates using the FLEXPART Lagrangian particle dispersion model

Pisso, Ignacio; Platt, Stephen Matthew; Schmidbauer, Norbert; Eckhardt, Sabine; Evangeliou, Nikolaos; Thompson, Rona Louise; Cassiani, Massimo

2023

Quantifying effect of traffic measures using individual exposure modeling. NILU F

Clench-Aas, J.; Bartonova, A.; Klæboe, R.; Kolbenstvedt, M.

1999

Quantifying methane emissions from the Arctic Ocean seabed to the atmosphere.

Platt, S.; Pisso, I.; Schmidbauer, N.; Hermansen, O.; Silyakova, A.; Ferré, B.; Vadakkepuliyambatta, S.; Myhre, G.; Mienert, J.; Stohl, A.; Myhre, C.L.

2016

Quantifying subnational CO2 emissions by assimilating regional measurements in a global high-resolution inverse model

Nayagam, Lorna Raja; Maksyutov, Shamil; Oda, Tomohiro; Janardanan, Rajesh; Yoshida, Yukio; Trisolino, Pamela; Zeng, Jiye; Kaiser, Johannes; Matsunaga, Tsuneo

2024

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