Peak-fitting and integration imprecision in the Aerodyne aerosol mass spectrometer: effects of mass accuracy on location-constrained fits

Abstract

Abstract. The errors inherent in the fitting and integration of the pseudo-Gaussian ion peaks in Aerodyne high-resolution aerosol mass spectrometers (HR-AMSs) have not been previously addressed as a source of imprecision for these or similar instruments. This manuscript evaluates the significance of this imprecision and proposes a method for their estimation in routine data analysis.In the first part of this work, it is shown that peakintegration errors are expected to scale linearly with peak height for the constrained-peak-shape fits performed in the HR-AMS. An empirical analysis is undertaken to investigate the most complex source of peak-integration imprecision: the imprecision in fitted peak height, σ h . It is shown that the major contributors to σ h are the imprecision and bias inherent in the m/z calibration, both of which may arise due to statistical and physical non-idealities of the instrument. A quantitative estimation of these m/z-calibration imprecisions and biases show that they may vary from ion to ion, even for ions of similar m/z.In the second part of this work, the empirical analysis is used to constrain a Monte Carlo approach for the estimation of σ h and thus the peak-integration imprecision. The estimated σ h for selected well-separated peaks (for which m/z-calibration imprecision and bias could be quantitatively estimated) scaled linearly with peak height as expected (i.e. as n 1 ). In combination with the imprecision in peak-width quantification (which may be easily and directly estimated during quantification), peak-fitting imprecisions therefore dominate counting imprecisions (which scale as n 0.5 ) at high signals. The previous HR-AMS uncertainty model therefore underestimates the overall fitting imprecision even for wellresolved peaks. We illustrate the importance of this conclusion by performing positive matrix factorization on a synthetic HR-AMS data set both with and without its inclusion.In the third part of this work, the Monte Carlo approach is extended to the case of an arbitrary number of overlapping peaks. Here, a modification to the empirically constrained approach was needed, because the ion-specific m/z-calibration bias and imprecision can generally only be estimated for well-resolved peaks. The modification is to simply overestimate the m/z-calibration imprecision in all cases. This overestimation results in only a slight overestimate of σ h , while significantly reducing the sensitivity of σ h to the unknown, ion-specific m/z-calibration biases. Thus, with only the meaPublished by Copernicus Publications on behalf of the European Geosciences Union. J. C. Corbin et al.: AMS peak-integration errorssured data and an approximate estimate of the order of magnitude of m/z-calibration biases as input, conservative and unbiased estimates of peak-integration imprecisions may be obtained for each peak in any ensemble of overlapping peaks.

Applications and limitations of constrained high-resolution peak fitting on low resolving power mass spectra from the ToF-ACSM

“…However, (ii) and (iii) are worth consideration as they can significantly degrade calibration accuracy. We note that Corbin et al (2015) demonstrate that the AMS calibration can also contain biases that are of similar magnitude as the imprecision; consideration of their sources is, however, outside the scope of this paper. Finally, it is emphasised that this discussion pertains to fitted peaks and these effects would not introduce appreciable error in integrated isobaric peak intensities (processing of the fullresolution mass spectra to centroid, or "stick", spectra based on unit-mass resolution integration boundaries).…”

“…In the constrained peak-fitting procedure employed during ToF-ACSM and AMS analysis, the accuracy and precision of the mass calibration are of critical importance, because the fitting is performed in time-offlight space and the position of the fitted peaks held constant using fixed mass-to-charge values. In consequence, an imperfect mass calibration introduces imprecision in the fitted peak intensities, particularly for weaker signals in the presence of larger neighbours , although imprecision in the fitted intensity is a significant source of error even for isolated peaks (Corbin et al, 2015). In practice, the precision of the mass calibration is limited principally by (i) the spectrometer resolving power, for wider calibrant peaks have a less well-defined centroid position, (ii) counting statistics for the calibrant ions, and, non-ideally, (iii) the influence of neighbouring ions on assessment of calibrant peak position.…”

“…Careful calibrant selection, fitting of a sub-range and/or use of more complicated ToF/mass relationships may increase accuracy to below 10 ppm, but during normal operation the user should expect mass axis biases of around 10-20 and 50-100 ppm in the lower and upper regions of the MS respectively. Fitted peak intensities should be evaluated accordingly (see Corbin et al, 2015, for a detailed discussion on the influence of calibration bias on fitted peak intensity).…”

“…This paper addresses the question of what extra information can be obtained by fitting the MS peaks. Recently, the uncertainty on fitted peak intensity associated with the constrained peak-fitting procedure employed by the AMS community has been explored and parameterisations for calculation of the precision reported (Corbin et al, 2015;Cubison and Jimenez, 2015). These are used, together with the appropriate sensitivity analyses, to assess the confidence in the peak-fitting results and draw conclusions on the appropriateness of applying peak fitting for retrieval of overlapping ion peak intensities for a range of example scenarios measured with a ToF-ACSM.…”

Insights into organic-aerosol sources via a novel laser-desorption/ionization mass spectrometry technique applied to one year of PM<sub>10</sub> samples from nine sites in central Europe

“…(3) (σ PMF,m/z , for a single mass spectrum). The need for and applicability of such an error model has been demonstrated by Corbin et al (2015) for MS-PMF. We obtained the two error terms by fitting Eq.…”