Database of methane (CH4) abundance and its stable carbon isotope (d13CH4) composition from atmospheric measurements

Database of methane (CH₄) and its stable carbon isotope (d¹³CH₄) from atmospheric measurements compiled for the study of "Estimating Emissions of Methane Consistent with Atmospheric Measurements of Methane and of d¹³CH₄ of Methane"

Authors

Xin Lan*, Edward Dlugokencky, Sylvia Englund Michel^#, Sourish Basu, Kenneth Schuldt, John Mund, Shuji Aoki, Alcide "Giorgio" di Sarra, Alex Vermeulen, Arlyn Andrews, Armin Jordan, Bianca Baier, Casper Labuschagne, Catherine Lund Myhre, Colm Sweeney, Dagmar Kubistin, Dan Smale, Doug Worthy, Emilio Cuevas, Francesco Apadula, Gordon Brailsford, Haeyoung Lee, Heiko Moosen, Hinrich Schaefer, Hsiang Jui, Jaroslaw Necki, Jgor Arduini, John Miller, John Moncrieff, Juha Hatakka, Karin Uhse, Kathryn McKain, Laszlo Haszpra, Luciana Gatti, Ludwig Ries, Martin Steinbacher, Martina Schmidt, Michel Ramonet, Mikhail Arshinov, Motoki Sasakawa, Nina Paramonova, Peter Bergamaschi, Ray Langenfelds, Seung-Yeon Kim, Shinji Morimoto, Shinya Takatsuji, Sylvia Nichol, Taku Umezawa, Tatiana Di Iorio, Teruo Kawasaki

* Primary contact for CH₄ data: xin.lan@noaa.gov

^# Primary contact for d¹³CH₄ data: sylvia.michel@colorado.edu

In our inverse modeling project, we used an extensive atmospheric measurement database to best inform global CH₄ emissions. To maximize the spatiotemporal coverage of in-situ CH₄ and d¹³CH₄ data, we compiled a new atmospheric measurement database by harmonizing measurements from NOAA/INSTAAR (Institute of Arctic and Alpine Research of University of Colorado Boulder) with another 29 research laboratories around the world. All CH₄ data were quality checked, converted to a common CH₄ standard scale (the World Meteorological Organization X2004A scale maintained by NOAA (Dlugokencky et al., 2005)), and assigned with lab-specific measurement uncertainty. We converted all data to the WMO X2004A scale by applying a scale multiplier to data that were not on WMO X2004A scale. We used an inversion scheme that requires a measurement uncertainty for each observation. Although uncertainties had been assigned to NOAA/GML CH₄ data, many data sets shared for this project had not. So, we applied the same fundamental approach used for NOAA/GML uncertainties to other data sets.

For GML data, uncertainties are calculated for each measurement based on analytical repeatability, reproducibility, our ability to propagate the WMO CH₄ mole fraction standard scale, and additional terms, if necessary. Analytical repeatability, or short-term measurement noise (sometimes called precision), is assessed through a number of methods, but most commonly as the standard deviation of the mean of multiple measurements of natural air from a cylinder. It varies with analytical instrument from 0.3 to 2.3 ppb (all uncertainties are given as 68% confidence intervals). Propagation of the scale is based on the reproducibility determined for scale propagation in our calibration laboratory. It has a fixed value of 0.5 ppb based on repeat calibrations of the same cylinder at least one year after the first. Reproducibility is based on long-term variations in measurements of target cylinders, typically ~0.3 ppb. The three terms are added in quadrature (square root of the sum of the squares) to estimate the measurement uncertainty at 68% confidence interval.

For non-GML measurements, we used the uncertainty assigned by the data provider (if available), or we estimated uncertainties using the same approach used for GML measurements. Uncertainty terms were assessed from publicly available information (publications, meta data, etc.), if available, or from an informed guess based on GML experience with the analytical method used. These uncertainties include additional terms as necessary (e.g., for internal scale propagation, conversion from a different scale, etc.).

We used d¹³CH₄ data from INSTAAR as well as other isotope laboratories making precise measurements of atmospheric CH₄ with isotope ratio mass spectrometers. The INSTAAR d¹³CH₄ data were measured in a subset of air samples collected from NOAA/GML's Global Greenhouse Gas Reference Network (GGGRN). Because different labs have independent ties to primary reference materials which do not agree, we calculated offsets to bring the d¹³CH₄ data onto the INSTAAR realization of the Vienna Pee Dee Belemnite (VPDB) scale (Miller et al., 2002). These offsets were based on measurements of air directly from cylinders, flasks filed with air from cylinders, or co-located sample data, and are all described in Umezawa et al. (2018). When there was not a direct comparison, e.g., between INSTAAR and NIES, or INSTAAR and NIPR, we used comparisons between each of these labs and the Institute for Marine and Atmospheric research Utrecht (IMAU). Each comparison has an uncertainty associated with it, which were combined in quadrature to account for uncertainty in the offset correction. The total uncertainty on assimilated d¹³CH₄ measurements was typically less than 0.15‰.

Product information:

Datasets for CH₄ include CH₄ Info. Note that to bring all CH₄ data to the WMO X2004A scale, multiply the "value" in the Variables field by the "ch4_scale_multiplier" in the Global Attributes for each nc file.
Datasets for d¹³CH₄ include d¹³CH₄ Info. Note that to bring all d¹³CH₄ data to the INSTAAR scale, subtract the "ch4c13_scale_offset" in the Global Attributes from the "value" in the Variables field for each nc file.

References of datasets included in this database:

Lan, X., E.J. Dlugokencky, J.W. Mund, A.M. Crotwell, M.J. Crotwell, E. Moglia, M. Madronich, D. Neff and K.W. Thoning (2022), Atmospheric Methane Dry Air Mole Fractions from the NOAA GML Carbon Cycle Cooperative Global Air Sampling Network, 1983-2021, Version: 2022-07-28, https://doi.org/10.15138/VNCZ-M766

Lan, X., Dlugokencky, E.J., A.M. Crotwell, K.W. Thoning, and J.W. Mund (2022), Atmospheric methane from quasi-continuous measurements at Barrow, Alaska and Mauna Loa, Hawaii, 1986-2021, Version: 2022-03, https://doi.org/10.15138/ve0c-be70

Michel, E. S., B. H. Vaughn, P. Tans, K. Thoning, X. Lan. Atmospheric d13C-CH4 data from the Institute of Arctic and Alpine Research (INSTAAR) at the University of Colorado, Boulder in cooperation with NOAA Global Monitoring Laboratory, 2021, https://doi.org/10.15138/79jq-qc24

Sasakawa, M., T. Machida, K. Ishijima, M. Arshinov, P. K. Patra, A. Ito, S. Aoki, and V. Petrov. "Temporal characteristics of CH4 vertical profiles observed in the West Siberian Lowland over Surgut from 1993 to 2015 and Novosibirsk from 1997 to 2015." Journal of Geophysical Research: Atmospheres 122, no. 20 (2017): 11-261. https://doi.org/10.1002/2017JD026836

Sasakawa, M., K. Shimoyama, T. Machida, N. Tsuda, H. Suto, M. Arshinov, D. Davydov et al. "Continuous measurements of methane from a tower network over Siberia." Tellus B: Chemical and Physical Meteorology 62, no. 5 (2010): 403-416. https://doi.org/10.1111/j.1600-0889.2010.00494.x

Fair Use Statement

This database is made freely available to the scientific community and is intended to stimulate and support global methane cycle and other modeling studies. We rely on the ethics and integrity of the user to assure that the authors receive fair credit for their work. Fair credit will depend on the nature of the work and the requirements of the institutions involved. Your use of this database implies an agreement to contact the database co-authors to discuss the nature of the work and the appropriate level of acknowledgement. If the database is essential to the work, or if an important result or conclusion depends on the database, co-authorship may be appropriate.
This should be discussed with the co-authors at an early stage in the work. Contacting the co- authors is not optional; if you use the database, you must contact the co-authors. A co-author email distribution list is provided during the database download process, which generates an automated e-mail to the user containing all relevant information.

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