4.7 Article

Characterization of submicron aerosol volatility in the regional atmosphere in Southern China

期刊

CHEMOSPHERE
卷 236, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chemosphere.2019.124383

关键词

Volatility; TD-AMS; PMF; CMB; Organic aerosol

资金

  1. National Natural Science Foundation of China [41622304, 91744202]
  2. Science and Technology Plan of Shenzhen Municipality [JCYJ20170412150626172]

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The volatility of atmospheric aerosols greatly influences the gas-particle partitioning, chemical mechanisms and lifetime of aerosols. Due to the complex composition, the volatility of organic aerosol is one of the major sources of uncertainty in measuring and modeling ambient aerosols. Despite high aerosol loading in the atmosphere in China, especially in winter, few field measurements were conducted targeting the volatility of ambient organic aerosol (OA). With the deployment of a thermodenuder-aerosol mass spectrometer (TD-AMS) system, the volatility of non-refractory submicron aerosols (NR-PM1) were measured on an island near the coastal line for the regional air in wintertime in southern China. NO3- and Cl- showed the highest volatility in the NR-PM1 chemical species, while SO42- showed the least volatility. Organic aerosol showed a moderate volatility, evaporating at a stable rate (0.57% C-1) at temperatures lower than 150 degrees C and keeping a stable volatility when its loading increases, which could be an advantage for parameterization of OA in air quality models. Based on both positive matrix factorization and chemical mass balance modeling of OA composition, biomass burning OA was found to be the most volatile factor, followed by hydrocarbon-like OA and more-oxidized oxygenated OA. By summarizing the OA volatility measured in this study and in the literature, we found that the volatilities of different OA factors at different locations do not have a clear relationship with the OA oxidation state, possibly due to the vague understanding of local OA aging mechanisms and mixing states. (C) 2019 Elsevier Ltd. All rights reserved.

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