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Evaluation of Composition-Dependent Collection Efficiencies for the Aerodyne...

Middlebrook, A. M., R. Bahreini, J. Jimenez-Palacios, and M. R. Canagaratna (2012), Evaluation of Composition-Dependent Collection Efficiencies for the Aerodyne Aerosol Mass Spectrometer using Field Data, Aerosol Science and Technology, 46, 258-271, doi:10.1080/02786826.2011.620041.
Abstract: 

In recent years, Aerodyne aerosol mass spectrometers (AMS) have been used in many locations around the world to study the size-resolved, nonrefractory chemical composition of ambient particles. In order to obtain quantitative data, the mass or (number) of particles detected by the AMS relative to the mass (or number) of particles sampled by the AMS, i.e., the AMS collection efficiency (CE) must be known. Previous studies have proposed and used parameterizations of the AMS CE based on the aerosol composition and sampling line relative humidity. Here, we evaluate these parameterizations by comparing AMS mass concentrations with independent measurements of fine particle volume or particle-into-liquid sampler (PILS) ion chromatography measurements for 3 field campaigns with different dominant aerosol mixtures: (1) acidic sulfate particles, (2) aerosol containing a high mass fraction of ammonium nitrate, and (3) aerosol composed of primarily biomass burning emissions. The use of the default CE of 0.5 for all campaigns resulted in 81–90% of the AMS speciated and total mass concentrations comparing well with fine particle volume or PILS measurements within experimental uncertainties, with positive biases compared with a random error curve. By using composition-dependent CE values (sometimes as a function of size) which increased the CE for the above aerosol types, the fraction of data points within the measurement uncertainties increased to more than 92% and the mass concentrations decreased by ~5–15% on an average. The CE did not appear to be significantly dependent on changes in organic mass fraction although it was substantial in the 3 campaigns (47, 30, and 55%).

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Research Program: 
Tropospheric Composition Program (TCP)