Direct links between hygroscopicity and mixing state of ambient aerosols: estimating particle hygroscopicity from their single-particle mass spectra

Xinning Wang,Lei Zhu,Xingnan Ye,Chongxuan Liu,Tzung-May Fu,Xin Yang,Xiaofei Wang,Jianmin Chen

doi:10.5194/acp-20-6273-2020

Abstract

Abstract. 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.

Highlights

Atmospheric particles have critical impacts on climate and the environment
The majority of particles were eventually classified into nine types including biomass, fresh elemental carbon (EC), aged EC, dust/ash, high-mass organic carbon (HMOC), amine-rich, ammonium and organic carbon (OC), cooking and sea salt
Since the total number of detected particles in growth factor (GF) bins was not equal (Table 1), we present the particle numbers normalized by the total numbers to indicate their detection probability in each GF bin (Fig. 2)

Summary

Introduction

Atmospheric particles have critical impacts on climate and the environment. They affect climate by directly interacting with sunlight and changing the energy balance of Earth’s atmosphere (Facchini et al, 1999; Lohmann and Feichter, 2005). Aerosol particles act as cloud condensation nuclei or ice nuclei and impact cloud formation (Lohmann and Feichter, 2005). Aerosol particles provide surfaces for heterogeneous reactions to occur and act as the sink for many atmospheric reactions (Gard et al, 1998; Qiu and Zhang, 2013), which are of significance to air quality, visibility and human health. In atmospheric conditions the hygroscopic growth transforms particles into microdroplets and their optical effects are al-

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Results

Conclusion