Retrieval of high time resolution growth factor probability density function from a humidity-controlled fast integrated mobility spectrometer |
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| Authors: | Yang Wang Guangjie Zheng Steven R. Spielman Tamara Pinterich Susanne V. Hering Jian Wang |
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| Affiliation: | 1. Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, New York, USA;2. Center for Aerosol Science and Engineering, Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA;3. jian@wustl.edu;5. Aerosol Dynamics Inc, Berkeley, California, USA |
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| Abstract: | Hygroscopicity describes the tendency of aerosol particle to uptake water and is among the key parameters in determining the impact of atmospheric aerosols on global radiation and climate. A hygroscopicity tandem differential mobility analyzer (HTDMA) system is the most widely used instrument for determining the aerosol hygroscopic growth. Because of the time needed to scan the classifying voltage of the DMA, HTDMA measurement often requires a minimum of 30?min to characterize the particle hygroscopic growth at a single relative humidity for five to six different sizes. This slow speed is often inadequate for measurements onboard mobile platforms or when aerosols evolve rapidly. Recently, a humidity-controlled fast integrated mobility spectrometer (HFIMS) was developed for measuring the hygroscopic growth of particles. The measurement speed of the HFIMS is about one order of magnitude faster than that of the conventional HTDMA. In this work, a data inversion routine is developed to retrieve the growth factor probability density function (GF-PDF) of particles measured by the HFIMS. The inversion routine considers the transfer functions of the upstream DMA and the downstream water-based fast integrated mobility spectrometer (FIMS), and derives the GF-PDF that reproduces the measured responses of the HFIMS. The performance of the inversion routine is examined using ambient measurements with different assumptions for the spectral shape of the particle GF-PDF (multimodal lognormal or piecewise linear). The influences of the data inversion parameters and counting statistics on the inverted GF-PDFs were further investigated, and an approach to determine the optimized inversion parameters is presented.Copyright © 2019 American Association for Aerosol Research |
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