Quantitative sampling using an Aerodyne aerosol mass spectrometer 1. Techniques of data interpretation and error analysis

TLDR

The aerosol mass spectrometer (AMS) can deliver high‑time‑resolution quantitative data on the composition and size of volatile and semivolatile fine airborne particles. This work develops and presents analytical and software tools for interpreting AMS data to produce meaningful quantitative results. The authors convert ion rates to mass concentrations using calibration data, correct for electron‑multiplier drift with gas‑phase response measurements, apply particle‑velocity calibration to transform TOF signals into aerodynamic‑diameter distributions, and quantify uncertainties through ion‑counting statistics and background variability. These methods are applied in a companion study to analyze AMS measurements from two UK cities at different times of year.

Abstract

The aerosol mass spectrometer (AMS), manufactured by Aerodyne Research, Inc., has been shown to be capable of delivering quantitative information on the chemical composition and size of volatile and semivolatile fine airborne particulate matter with high time resolution. Analytical and software tools for interpreting the data from this instrument and generating meaningful, quantitative results have been developed and are presented here with a brief description of the instrument. These include the conversion of detected ion rates from the quadrupole mass spectrometer during the mass spectrum (MS) mode of operation to atmospheric mass concentrations of chemical species (in μg m −3 ) by applying calibration data. It is also necessary to correct for variations in the electron multiplier performance, and a method involving the measurement of the instrument's response to gas phase signals is also presented. The techniques for applying particle velocity calibration data and transforming signals from time of flight (TOF) mode to chemical mass distributions in terms of aerodynamic diameter (d M /dlog( D a ) distributions) are also presented. It is also possible to quantify the uncertainties in both MS and TOF data by evaluating the ion counting statistics and variability of the background signal, respectively. This paper is accompanied by part 2 of this series, in which these methods are used to process and analyze AMS results on ambient aerosol from two U.K. cities at different times of the year.