Using size-based classifiers in tandem to calibrate and infer mixing state with an aerosol mass spectrometer

The aerosol mass spectrometer (AMS) is widely used to characterize physical and chemical properties of aerosols. This work focuses on both the calibration of the AMS and its use for aerosol characterization. Conventional AMS calibration requires ionization efficiency (IE) and particle time of flight (pToF) measurements using mobility classified (dm) aerosols generated by a differential mobility analyzer (DMA). However, DMA-based calibration is susceptible to multiple charging artifacts, introducing limits in size selection (since selecting smaller particles magnifies the artifacts), signal intensity and calibration accuracy. Here, we present an alternative calibration approach using an aerodynamic aerosol classifier (AAC), which selects truly monodisperse particles based on aerodynamic diameter (da). Because the AMS measures vacuum aerodynamic diameter (dva), AAC classification provides a more direct physical comparison. We then evaluated the relationship between da and dva alongside dm to quantify the AMS response to four different aerosol materials: polyethylene glycol, ammonium nitrate, ammonium sulfate and fulvic acid, over size ranges of ~30 – 800 nm. In the second part of this work, we operated AMS in tandem with both AAC and DMA to establish a bidimensional (2D) space combining equivalent properties from all three instruments. This enables the derivation of 2D effective density with chemical information as a new constraint to better define the aerosol mixing state. The AAC-based classification enables a more robust AMS calibration and combining effective density with chemical speciation provides a new 2D framework for understanding complex aerosol mixture.