ALBERT

Beschreibung: The performance of 20 European laboratories involved in long-term non-methane hydrocarbon (NMHC) measurements within the framework of Global Atmosphere Watch (GAW) and European Monitoring and Evaluation Programme (EMEP) was assessed with respect to the ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) and GAW data quality objectives (DQOs). Compared to previous intercomparisons the DQOs of ACTRIS are much more demanding with deviations to a reference value of less than 5% and repeatability of better than 2% for mole fractions above 0.1 nmol mol−1. The participants were asked to measure both a 30 component NMHC mixture in nitrogen (NMHC_N2) at approximately 1 nmol mol−1 and whole air (NMHC_air), following a standardised operation procedure including zero- and calibration gas measurements. Furthermore, they had to report details on their instruments and they were asked to assess measurement uncertainties. The NMHCs were analysed either by gas chromatography-flame ionisation detection or gas chromatography-mass spectrometer methods. Most systems performed well for the NMHC_N2 measurements (88% of the reported values were within the GAW DQOs and even 58% within the ACTRIS DQOs). For NMHC_air generally more frequent and larger deviations to the assigned values were observed compared to NMHC_N2 (77% of the reported values were within the GAW DQOs, but only 48% within the ACTRIS DQOs). Important contributors to the poorer performance in NMHC_air compared to NMHC_N2 were a more complex matrix and a larger span of NMHC mole fractions (0.03–2.5 nmol mol−1). Issues, which affected both NMHC mixtures, are the usage of direct vs. two-step calibration, breakthrough of C2–C3 hydrocarbons, blank values in zero-gas measurements (especially for those systems using a Nafion® Dryer), adsorptive losses of aromatic compounds, and insufficient chromatographic resolution. Essential for high-quality results are experienced operators, a comprehensive quality assurance and quality control, well characterised systems, and sufficient man-power to operate the systems and evaluate the data.