Abstract. The monosaccharide anhydrides (MAs) levoglucosan, galactosan and mannosan are products of incomplete combustion and pyrolysis of cellulose and hemicelluloses, and are found to be major constituents of biomass burning (BB) aerosol particles. Hence, ambient aerosol particle concentrations of levoglucosan are commonly used to study the influence of residential wood burning, agricultural waste burning and wildfire emissions on ambient air quality. A European-wide intercomparison on the analysis of the three monosaccharide anhydrides was conducted based on ambient aerosol quartz fiber filter samples collected at a Norwegian urban background site during winter. Thus, the samples' content of MAs is representative for BB particles originating from residential wood burning. The purpose of the intercomparison was to examine the comparability of the great diversity of analytical methods used for analysis of levoglucosan, mannosan and galactosan in ambient aerosol filter samples. Thirteen laboratories participated, of which three applied high-performance anion-exchange chromatography (HPAEC), four used high-performance liquid chromatography (HPLC) or ultra-performance liquid chromatography (UPLC) and six resorted to gas chromatography (GC). The analytical methods used were of such diversity that they should be considered as thirteen different analytical methPublished by Copernicus Publications on behalf of the European Geosciences Union. K. E. Yttri et al.: An intercomparison study of analytical methods used for quantificationods. All of the thirteen laboratories reported levels of levoglucosan, whereas nine reported data for mannosan and/or galactosan. Eight of the thirteen laboratories reported levels for all three isomers.The accuracy for levoglucosan, presented as the mean percentage error (PE) for each participating laboratory, varied from −63 to 20 %; however, for 62 % of the laboratories the mean PE was within ±10 %, and for 85 % the mean PE was within ±20 %. For mannosan, the corresponding range was −60 to 69 %, but as for levoglucosan, the range was substantially smaller for a subselection of the laboratories; i.e. for 33 % of the laboratories the mean PE was within ±10 %. For galactosan, the mean PE for the participating laboratories ranged from −84 to 593 %, and as for mannosan 33 % of the laboratories reported a mean PE within ±10 %.The variability of the various analytical methods, as defined by their minimum and maximum PE value, was typically better for levoglucosan than for mannosan and galactosan, ranging from 3.2 to 41 % for levoglucosan, from 10 to 67 % for mannosan and from 6 to 364 % for galactosan. For the levoglucosan to mannosan ratio, which may be used to assess the relative importance of softwood versus hardwood burning, the variability only ranged from 3.5 to 24 %.To our knowledge, this is the first major intercomparison on analytical methods used to quantify monosaccharide anhydrides in ambient aerosol filter samples conducted and reported in the scientific literature. The results show ...
Image quality metrics have become more and more popular in the image processing community. However, so far, no one has been able to define an image quality metric well correlated with the percept for overall image quality. One of the causes is that image quality is multi-dimensional and complex. One approach to bridge the gap between perceived and calculated image quality is to reduce the complexity of image quality, by breaking the overall quality into a set of quality attributes. In our research we have presented a set of quality attributes built on existing attributes from the literature. The six proposed quality attributes are: sharpness, color, lightness, artifacts, contrast, and physical. This set keeps the dimensionality to a minimum. An experiment validated the quality attributes as suitable for image quality evaluation. The process of applying image quality metrics to printed images is not straightforward, because image quality metrics require a digital input. A framework has been developed for this process, which includes scanning the print to get a digital copy, image registration, and the application of image quality metrics. With quality attributes for the evaluation of image quality and a framework for applying image quality metrics, a selection of suitable image quality metrics for the different quality attributes has been carried out. Each of the quality attributes has been investigated, and an experimental analysis carried out to find the most suitable image quality metrics for the given quality attributes. For the many attributes metrics based on structural similarity are the the most suitable, while for other attributes further evaluation is required.
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