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Primary Standards, Reference Materials, and Uncertainty Analysis for the Measurement of Greenhouse Gases
by Mrs./Ms. Christina Cecelski, Dr. Blaza Toman, Dr. Juris Meija, Mrs./Ms. Fong-Ha Liu, Mrs./Ms. Kimberly Harris, Mrs./Ms. Jennifer Carney, Dr. Antonio Possolo


The National Institute of Standards and Technology (NIST, USA) has made great strides in advancing the measurement science that enables the production and certification of gas mixtures that serve as primary standards and as reference materials, which support measurements of atmospheric greenhouse gases (GHGs) qualified with rigorous evaluations of measurement uncertainty. We review contributions we have made in the certification of reference gas mixtures that include GHGs, and in the construction of calibration and analysis functions that play the role of key comparison (KC) reference functions, in KCs where the measurement results are mutually inconsistent. As part of our work-flow in the development of reference gas mixtures, we have developed and implemented new procedures that improve conventional data reduction techniques: for statistical model selection; construction of analysis functions that take into account the typically small numbers of replicated observations made at each calibration point; Monte Carlo uncertainty evaluation; and Bayesian methods to incorporate information accumulated in the course of our long history of development and characterization of reference gas mixtures. Motivated by needs arising in KCs organized by the Gas Analysis Working Group (GAWG) of the CCQM, we have developed innovations that promote an equitable inclusion of all participants, particularly when the measurement results submitted by the participants are mutually inconsistent, thereby helping to ensure the commutability of measurements of GHGs that are made across the globe. In particular, jointly with the National Research Council, Canada, and the National Measurement Institute, Australia, we have developed versions of errors-in-variables regression, used as KC reference functions for CCQM-GAWG KCs, that recognize dark uncertainty, which not only help harmonize the different results but also provide a quantifiable evaluation of collective performance of the community involved in the measurement of GHGs.

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Topic : Theme 2: Accuracy requirements for atmospheric composition measurements across economic sectors, and temporal and spatial scales.
Reference : T2-A1

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