Abstract
Optical particle counters (OPCs) are common tools for the in situ measurement of aerosol particle number size distributions. As the actual quantity measured by OPCs is the intensity of light scattered by individual particles, it is necessary to translate the distribution of detected scattering signals into the desired information, i.e., the distribution of particle sizes. A crucial part in this challenge is the modeling of OPC response and the calibration of the instrument in other words, establishing the relation between instrumentspecific particle scattering cross-section and measured signal amplitude. To date, existing methods lack a comprehensive parametrization of OPC response, particularly regarding the instrument-induced broadening of signal amplitude distributions. This deficiency can lead to significant size distribution biases. We introduce an advanced OPC response model including a simple parametrization of the broadening effect and a self-consistent way to evaluate calibration measurements using a Markov chain Monte Carlo (MCMC) method. We further outline how to consistently derive particle number size distributions with realistic uncertainty estimates within this new framework. Based on measurements of particle standards for two OPCs, the Grimm model 1.129 (SkyOPC) and the DMT Passive Cavity Aerosol Spectrometer Probe (PCASP), we demonstrate that residuals between measured and modeled response can be substantially reduced when using the new approach instead of existing methods. More importantly, for the investigated set of measurements only the new approach yields results that conform with the true size distributions within the range of model uncertainty. The presented innovations will help improving the accuracy of OPC-derived size distributions and the assessment of their precision.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Physik |
Themengebiete: | 500 Naturwissenschaften und Mathematik > 530 Physik |
URN: | urn:nbn:de:bvb:19-epub-54005-3 |
ISSN: | 1867-1381 |
Sprache: | Englisch |
Dokumenten ID: | 54005 |
Datum der Veröffentlichung auf Open Access LMU: | 14. Jun. 2018, 09:54 |
Letzte Änderungen: | 04. Nov. 2020, 13:33 |