资源环境科技发展态势分析平台

Hygroscopicity plays crucial roles in determining aerosol optical properties and aging processes in the atmosphere. We investigated submicron aerosol hygroscopicity and composition by connecting an aerosol time-of-flight mass spectrometer (ATOFMS) in series to a hygroscopic tandem differential mobility analyzer (HTDMA), to characterize hygroscopicity and composition of ambient aerosols in Shanghai, China. The HTDMA-ATOFMS data suggested that particle types, including biomass burning, elemental carbon (EC), dust/ash, organic particles, cooking particles and sea salt, were shown to have distinct hygroscopicity distributions. Peak intensities in particle spectra were found to be nonlinearly correlated with hygroscopicity, and the correlations were variant with particle types. Based on the measured hygroscopicity-composition relations, we developed a statistical method to estimate ambient particle hygroscopicity just from their mass spectra. The method was applied to another ambient ATOFMS dataset sampled from 12 to 28 September 2012 in Shanghai. The estimated hygroscopicity suggested that ambient particles were present in three apparent hygroscopicity modes, whose growth factors peaked at 1.05, 1.42 and 1.60 (85 % relative humidity, RH). The estimated growth factor (GF) were divided into four bins as < 1.1, 1.1-1.3, 1.3-1.5 and > 1.5 to represent the nearly hydrophobic (NH), less-hygroscopic (LH), more-hygroscopic (MH) and sea salt (SS) modes. Number contributions of particle types to hygroscopicity modes showed consistent results with the HTDMA-ATOFMS experiment. Based on the combined information on particle composition, hygroscopicity, air mass back trajectories and ambient pollutant concentrations, we inferred that the NH, LH, MH and SS modes were characterized by primary organic aerosol (POA) / EC, secondary organic aerosol (SOA), secondary inorganic aerosol (SIA) and salt compositions, respectively. The proposed method would provide additional information to the study of particle mixing states, source identification and visibility variation.