Re-Analysis of Long-Term Aerosol Mass Spectrometer Data: Homogenizing 13 Years of Measurements

JULIETTE BROCHET, Hasna Chebaicheb, Yunjiang Zhang, Laura Cadeo, Valerie Gros, Philip Croteau, Olivier Favez, Jean-Eudes Petit, LSCE

     Abstract Number: 105
     Working Group: Instrumentation and Methods

Abstract
Since the early 2010s, the implementation of Aerosol Chemical Speciation Monitors (ACSM, Ng et al., 2011) has provided valuable information on the nature and temporal variability of non-refractory submicron aerosols worldwide. This led to the emergence of a growing number of long-term datasets, introducing new challenges in data treatment strategies. Indeed, such datasets often result from the juxtaposition of separate data processing periods, associated with the evolution of quality assurance/control guidelines and measurement procedures, which may lead to heterogeneous subsets and prevent a robust and relevant analysis of long-term features. Here, we present a re-analysis of the longest ACSM datasets worldwide from the SIRTA facility, located in the Paris region.

We will present and discuss the developed strategy towards homogeneous data processing, also considering the challenges related to long-term measurements. We highlight first the utmost importance of re-evaluating (relative) ion efficiency calibration values, as they directly impact concentrations, and discuss how to take their variability into account. Further data processing steps (m/z calibration, airbeam correction, ion transmission) will be discussed. Additionally, we present a long-term evaluation of the composition-dependent collection efficiency (CDCE) and discuss the interest and relevance of updating the parametrisation originally proposed by Middlebrook et al. (2011) regarding improved mass closure.

The impacts of this re-analysis are presented through a Mann-Kendall trend test (Collaud Coen et al., 2020), where results (both statistical significance and slope) are directly linked to the homogeneity of the dataset.