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| Titel |
Peak-fitting and integration imprecision in the Aerodyne aerosol mass spectrometer: effects of mass accuracy on location-constrained fits |
| VerfasserIn |
J. C. Corbin, A. Othman, J. D. Allan, D. R. Worsnop, J. D. Haskins, B. Sierau, U. Lohmann, A. A. Mensah |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 8, no. 11 ; Nr. 8, no. 11 (2015-11-03), S.4615-4636 |
| Datensatznummer |
250116673
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| Publikation (Nr.) |
 copernicus.org/amt-8-4615-2015.pdf |
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| Zusammenfassung |
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 peak-integration 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, σh. It is shown that the major
contributors to σh 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 σh and thus the
peak-integration imprecision. The estimated σh 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 n1). 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 n0.5) at high signals. The previous HR-AMS
uncertainty model therefore underestimates the overall fitting imprecision
even for well-resolved 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 σh, while significantly reducing the
sensitivity of σh to the unknown, ion-specific m/z-calibration
biases. Thus, with only the measured 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. |
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