Inter-comparison of four different carbon monoxide measurement techniques and evaluation of the long-term carbon monoxide time series of Jungfraujoch

Abstract

Abstract. Despite the importance of carbon monoxide (CO) for the overall oxidative capacity of the atmosphere, there is still considerable uncertainty in ambient measurements of CO. To address this issue, an inter-comparison between four different measurement techniques was made over a period of two months at the high-alpine site Jungfraujoch (JFJ), Switzerland. The measurement techniques were Nondispersive Infrared Absorption (NDIR), Vacuum UV Resonance Fluorescence (VURF), gas chromatographic separation with a mercuric oxide reduction detector (GC/HgO), and gas chromatographic separation followed by reduction on a nickel catalyst and analysis by a flame ionization detector (GC/FID). The agreement among all techniques was better than 2% for one-hourly averages, which confirmed the suitability of the NDIR method for CO measurements even at remote sites. The inter-comparison added to the validation of the 12-year record (1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007) of continuous CO measurements at JFJ. To date this is one of the longest time series of continuous CO measurements in the free troposphere over Central Europe. This data record was further investigated with a focus on trend analysis. A significant negative trend was observed at JFJ showing a decrease of 21.4±0.3% over the investigated period, or an average annual decrease of 1.78%/yr (2.65±0.04 ppb/yr). These results were compared with emission inventory data reported to the Longrange Transboundary Air Pollution (LRTAP) Convention. It could be shown that long range transport significantly influences the CO levels observed at JFJ, with air masses of non-European origin contributing at least one third of the observed mole fractions.

Robust extraction of baseline signal of atmospheric trace species using local regression

“…1, the scale parameter σ is an upper limit for the precision of the instrument. However, the obtained value for σ is considerably larger than the random uncertainty of the NDIR instrument (4.2 ppb), which was determined from the standard deviation of repeated zero air measurements (Zellweger et al, 2009). The larger scale parameter σ might be a consequence of the deviations from the concept of background conditions mentioned above: the relatively short lifetime of CO mainly due to oxidation by OH leads to a latitudinal gradient for CO, and therefore to a dependence of the background concentration at Jungfraujoch on the air mass origin.…”

“…2). It has been shown by Zellweger et al (2009) that the negative trend of CO at Jungfraujoch is the HFC-152a background at Jungfraujoch was higher than at Mace Head, most likely because of the closer proximity of the Jungfraujoch to major source regions (Greally et al, 2007;Reimann et al, 2008). Since about 2008, the HFC152a background concentration at Jungfraujoch has been declining (probably due to stabilizing emissions) and again very close to the background concentration at Mace Head.…”

“…The average annual change for the 1996 to 2009 period as determined from the REBS filtered data is −2.2 ± 1.1 ppb yr −1 ; data filtering using the smooth curve fit results in −2.5 ± 1.1 ppb yr −1 , a slightly larger, although not statistically significant, decrease of background CO (see also the study by Zellweger et al (2009) for a discussion of the trend of CO at Jungfraujoch for the 1996 to 2007 period). Note that the linear negative trend of unfiltered hourly CO measurements for this time period is considerably larger (−2.9 ± 1.3 ppb yr −1 ) due to more severe and more frequent pollution events during the first years of the considered time period (see Fig.…”

“…The detection limit for individual 1 min values is 20 ppb; the overall measurement uncertainty was estimated to be ±5 % (1σ ) . In Zellweger et al (2009) different CO measurement techniques were compared during a field campaign at JFJ. It was confirmed that the NDIR method is suitable for CO measurements at this site.…”

“…Hence, data filtering is often an essential part of the analysis of data from those sites. For example, data filtering was applied for trend estimations (Thoning et al, 1989;Novelli et al, 1998;Schuepbach et al, 2001;Novelli et al, 2003;Zellweger et al, 2009), for evaluation of source regions and corresponding emission estimates Cox et al, 2005;Reimann et al, 2005;Greally et al, 2007), as well as for modeling of long-range transport of trace gases Balzani Lööv et al, 2008).…”