This work describes the development and validation of new Primary Reference Materials (PRMs) for trace impurities in carbon dioxide (CO 2), addressing a key metrological gap for carbon capture, utilisation, and storage (CCUS) applications. CO 2 streams captured from industrial sources inevitably contain impurities such as water, sulfur oxides, nitrogen oxides, hydrogen, and hydrocarbons. Accurate and traceable quantification of these species is essential to protect transport infrastructure, ensure compliance with project specifications, and enable safe long-term geological storage. International and project-specific guidelines, including ISO/TR 27913, Porthos, and Northern Lights, define stringent impurity limits, underscoring the need for reliable gas standards for calibration and validation of analytical instruments. Binary and multi-component PRMs were prepared by VSL, NPL, CMI, IPQ, and SINTEF ER using ISO 6142-1 gravimetric methods. The mixtures covered sulfur dioxide, hydrogen sulfide, nitrogen dioxide, nitrous oxide, water, dimethyl sulfide, ethanol, and non-condensable gases (N 2, Ar, H 2, O 2, CH 4, and CO) at amount fractions relevant to CCUS specifications. In parallel, dynamic preparation systems and a portable trace gas generator were validated as alternative approaches for producing low-level mixtures of reactive species such as ammonia. PRM stability was investigated over a two-year period. Sulfur dioxide, hydrogen sulfide, dimethyl sulfide, ethanol, and nitrous oxide demonstrated stability within their expanded uncertainties. In contrast, sulfur dioxide, nitrogen dioxide, and nitric oxide in multi-component mixtures exhibited significant degradation, indicating pronounced reactivity and wall effects. Dynamic dilution systems developed by VSL and NPL produced mixtures consistent with static PRMs within 1–5%, while the portable trace gas generator achieved ammonia generation in CO 2 with a relative uncertainty of approximately 2%. These results establish a robust metrological basis for impurity analysis in CO 2. The PRMs developed within MetCCUS provide traceable calibration capabilities aligned with European CO 2 quality specifications, supporting reliable monitoring and safe operation of CCUS infrastructure.
The proliferation of nanotechnology faces a critical bottleneck: the lack of comparable and reliable nanoscale dimensional measurements across diverse instruments and laboratories that undermines reproducibility and innovation in nanoscale materials, devices and systems. In this work, we show that the periodicity of nanostructures obtained through self-assembled block copolymer templating can be exploited as a universal traceable measurand for nanoscale metrology. Overcoming main challenges of nanoscale metrology - i.e., method-dependent dimensional definitions, probe-sample interaction effects, and technique-specific artifacts - we demonstrate through traceable measurements and a worldwide international comparison that the periodicity of these reference materials enables the establishment of a technique-agnostic reference value that can be used for instrument calibration and for the detection/correction of measurement artifacts. The reliability, stability and biocompatibility of these reference materials enable the realization of nanoscale rulers allowing the generation of traceable, machine learning-ready data as required for data-driven advancement of nanoscience and nanotechnology.
Integrating spectral data (spectral responsivities of photometers or spectral distributions of light sources) to calculate integrated quantities such as tristimulus values is straightforward at first sight. However, estimating the measurement uncertainty of these integrated quantities is challenging. When calculating integrated photometric quantities, some uncertainty contributions from the spectral data transfer to the final results, some ‘cancel out’, some ‘average out’ and others increase or decrease their weight by correlation. The spectral data are usually assumed to be uncorrelated when deriving other quantities by integration, which is typically not justified. A method called the framework approach, applying orthogonal basis functions and Monte Carlo simulations, is introduced. This approach shows that neglecting partial spectral correlations may lead to a significant underestimation of the measurement uncertainty of integrated quantities. Furthermore, this paper shows how information about spectral error correlation structures can be used to obtain better estimations of the measurement uncertainty.
This paper presents an approach to assess the measurement uncertainty of luminance measurements obtained by imaging luminance measurement devices (ILMDs). A common strategy for users doing measurements in photometry is to characterise and correct for residual errors, that in this domain are often significant. To apply this strategy to measurements with ILMDs leads to issues because the user only has limited knowledge on the device internals and the effort for such characterisations would exceed the capabilities of most users. To illustrate this, the complexity of the devices' internal operation is shown, and tasks of the manufacturer to build and adjust an ILMD based on a camera system are outlined. From this we concluded, that for most users, the best approach is to assume that all significant effects have been corrected for by the manufacturer, and only the remaining uncertainties need to be estimated. An example is given for this estimation and for the handling of correlations between measurements.
The European project EPM SRT-v01 - MetCCUS (Metrology for Carbon Capture Utilization and Storage) is the first metrology project within the scope of CCUS (Carbon Capture Utilization and Storage), which, in the European ecological pact, European Commission’s Green Deal, is listed as one of the priority areas to achieve a reduction in greenhouse gas emissions by 55 % by 2030 and carbon neutrality by 2050. This project, financed by EURAMET, aims to respond to the metrological challenges identified by the industry and aims to provide the primary standards, methods, good practice guides that will support the necessary measurements. This study successfully characterized four bicomponent mixtures: SO2 in CO2 matrix (two mixtures) and H2S in CO2 matrix (two mixtures) and four multicomponent mixtures SO2+CO+O2 in CO2 (two mixtures) and H2S+CO+CH4+O2 in CO2 matrix (two mixtures) within a cylinder under a pressure of approximately 40 bar, and it entailed a stability study. The stability study was conducted over one year, employing statistical evaluation using the Normalized Error (En) function in accordance with the international standard ISO 13528:2022 for statistical methods.
