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Significant Contribution of Organics to Aerosol Liquid Water Content In Atmos. Chem. Phys., 20, 901–914, 2020 https://doi.org/10.5194/acp-20-901-2020 © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. Significant contribution of organics to aerosol liquid water content in winter in Beijing, China Xiaoai Jin1, Yuying Wang2, Zhanqing Li3, Fang Zhang1, Weiqi Xu4,5, Yele Sun4,5, Xinxin Fan1, Guangyu Chen6, Hao Wu1, Jingye Ren1, Qiuyan Wang2, and Maureen Cribb3 1State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China 2Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing 210044, China 3Earth System Science Interdisciplinary Center, Department of Atmospheric and Oceanic Science, University of Maryland, College Park, College Park, MD, USA 4State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China 5College of Earth Sciences and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China 6Zhejiang Windey Co., Ltd., Hangzhou 310012, China Correspondence: Zhanqing Li ([email protected]) and Yuying Wang ([email protected]) Received: 28 May 2019 – Discussion started: 31 July 2019 Revised: 21 November 2019 – Accepted: 29 November 2019 – Published: 23 January 2020 Abstract. The aerosol liquid water (ALW) content (ALWC), (R2 D 0:66, 0.56 and 0.60, respectively). We further noted an important component of atmospheric particles, has a sig- that accumulation mode particles play a key role in deter- nificant effect on atmospheric optical properties, visibility mining ALWC, dominating among all the aerosol modes. and multiphase chemical reactions. In this study, ALWC is ALWC is an exponential function of ambient relative humid- determined from aerosol hygroscopic growth factor (GF) and ity (RH), whose strong diurnal variation influence the diurnal particle number size distribution (PNSD) measurements and variation of ALWC. However, there is a 3 h lag between the is also simulated by ISORROPIA II, a thermodynamic equi- extremes of ALWC and RH values, due to the diurnal vari- librium model, with measured aerosol chemical composition ations in PNSD and aerosol chemical composition. Finally, data taken at an urban site in Beijing from 8 November to a case study reveals that ALWCOrg plays an important role 15 December 2017. Rich measurements made during the ex- in the formation of secondary aerosols through multiphase periment concerning virtually all aerosol properties allow us reactions at the initial stage of a heavy-haze episode. not only to derive the ALWC but also to study the contri- butions by various species for which little has been done in this region. The simulated ALWC including the contribution of organics and the calculated ALWC are highly correlated (coefficient of determination R2 D 0:92). The ALWC con- 1 Introduction tributed by organics (ALWCOrg) accounts for 30% ± 22% of the total ALWC during the sampling period. These re- China has experienced rapid economic developments during sults suggest a significant contribution of organics to ALWC, the past few decades, resulting in frequent heavy-haze events. which is rather different from previous studies that showed Severe air pollution may harm human health and affect the negligible contributions by organics. Our results also show regional climate through aerosol direct and indirect radiation that ALWC correlates well with the mass concentrations effects (Li et al., 2016; Wu et al., 2016; Wei et al., 2019a, of sulfate, nitrate, and secondary organic aerosols (SOAs) b). However, air pollution formation mechanisms and aerosol climate effects remain highly uncertain due to the complex Published by Copernicus Publications on behalf of the European Geosciences Union. 902 X. Jin et al.: Significant contribution of organics to aerosol liquid water content in winter in Beijing physical and chemical processes involved (Tao et al., 2012; thermodynamic model (Nenes et al., 1998), Aerosol Inorgan- Wang et al., 2014). ics Model (Wexler and Clegg, 2002), the Simulating Compo- Aerosol liquid water (ALW), a component of atmospheric sition of Atmospheric Particles in Equilibrium model (Kim particles in the atmosphere, exists universally and plays an et al., 1993), and the Gibbs Free Energy Minimization model important role in many atmospheric physical and chemical (Ansari and Pandis, 1999) with aerosol chemical composi- processes (Nguyen et al., 2016). For example, ALW can tion information as an input. influence aerosol optical properties, resulting in increased ALWC mostly depends on aerosol PNSD, chemical com- extinction coefficients, lowered atmospheric visibilities, en- position and ambient RH. Hodas et al. (2014) reported that hanced aerosol optical depths (AODs) and changes in the di- ALWC in the Po Valley in Italy was driven by locally formed rect climatic effect of aerosols (Dougle et al., 1996; Adams anthropogenic nitrates. The implications for the lifetimes of and Seinfeld, 2001; Liao et al., 2005; Seinfeld and Pan- water-soluble organic compounds and its potential influence dis, 2006). Secondary aerosols (SAs) are considered to be on SOA formation were also discussed. Another study also the main source of particulate pollution during heavy-haze revealed that ALWC in Beijing was driven by secondary in- events in China (Huang et al., 2014). Many studies now high- organic aerosols (SIAs; Wu et al., 2018). Most previous stud- light the significance of aerosol liquid water content (ALWC) ies have focused on the interaction between inorganic salts in the formation of SA through chemical reactions (e.g., and ALWC, but the impact of organic species on ALWC has Arellanes et al., 2006; Wang et al., 2016; Cheng et al., 2016). been ignored to our knowledge (Blando et al., 2001; Surratt This is because ALW can dilute the absolute concentration et al., 2007; Hennigan et al., 2008; Carlton et al., 2013). A of solutes, adjust aerosol acidity and serve as a reactant, re- thorough understanding of the association of ALWC with or- sulting in increases in trace gas (e.g., N2O5 and HO2) up- ganic aerosols in the atmosphere is lacking. take coefficients (Wahner et al., 1998; Bertram et al., 2009; In this study, ALWC is calculated using the indirect Abbatt et al., 2012). H. Wang et al. (2017) found that the method (2) and simulated using the ISORROPIA II model, uptake coefficient of N2O5 can be high, which is related to i.e., indirect method (4), discussed previously. The effects of high ALWC in Beijing, thereby increasing the formation of inorganic aerosols, organic aerosols, PNSD and ambient RH nitrates. ALW can also speed up the aqueous phase chemical on ALWC are then investigated separately. We demonstrate reaction by serving as a reactor for the transformation of SO2 the significant contribution of organics to ALWC in Beijing to sulfate (Zheng et al., 2015; Wang et al., 2016; Cheng et al., and provide evidence that the ALW contributed by organics 2016). Some studies have found that ALWC can facilitate serves as a reactor for sulfate and SOA formation. the formation of secondary organic aerosols (SOAs) through aqueous-phase chemistry and photochemistry (Blando and Turpin, 2001; Surratt et al., 2007; Hennigan et al., 2008; 2 Data and measurements Song et al., 2019). Furthermore, observations in Beijing have 2.1 Sampling site shown that aqueous-phase processes play a dominant role in the additional formation of oxidized SOAs (Xu et al., 2017). The Air Pollution and Human Health (APHH) winter field Overall, investigating the formation of SA and haze in north- campaign took place from 8 November to 15 December 2016 ern China requires an examination of ALWC and its factors at the Chinese Academy of Sciences’ Institute of Atmo- including aerosol particle number size distribution (PNSD), spheric Physics Tower Branch in Beijing. Beijing is located aerosol chemical composition and ambient related humidity in the northwestern part of the North China Plain, which (RH) in this region. has experienced rapid economic developments during the last However, directly measuring real-time ALWC is not feasi- few decades. A large amount of gaseous precursors and other ble yet because of technical limitations (Kuang et al., 2018). air pollutants are emitted in this region every year, caus- Four indirect methods have been proposed to calculate real- ing serious air pollution problems. The sampling site is lo- time ALWC: (1) the aerosol PNSD under dry conditions and cated in the northwestern urban area of Beijing (39.97◦ N, ambient RH conditions are first measured, then ALWC is cal- 116.37◦ E), between the northern 3rd and 4th Ring Roads culated as the difference between dry and ambient aerosol and surrounded by restaurants. Traffic and cooking emis- volumes (Stanier et al., 2004); (2) the increased aerosol vol- sions are thus the main pollutants at the site. Aerosols at ume due to water uptake (i.e., ALWC) is calculated accord- this site can, therefore, represent anthropogenic aerosols in ing to the measured dry PNSD, size-dependent aerosol hy- highly polluted areas well. Sun et al. (2013) and Y. Wang et groscopicity and ambient RH (Kitamori et al., 2009; Bian et al. (2017) provide more detailed descriptions of the sampling al., 2014; Tan et al., 2017); (3) the dry and ambient aerosol site. volumes are first estimated using the measured aerosol op- tical enhancement and Ångström exponent, then ALWC is 2.2 Instrumentation calculated as the difference between dry and ambient aerosol volumes (Kuang et al., 2018); and (4) ALWC is simulated Sampling instruments used during the field campaign in- using thermal equilibrium models such as the ISORROPIA cluded a scanning mobility particle sizer (SMPS) equipped Atmos. Chem. Phys., 20, 901–914, 2020 www.atmos-chem-phys.net/20/901/2020/ X. Jin et al.: Significant contribution of organics to aerosol liquid water content in winter in Beijing 903 with a long differential mobility analyzer (DMA; model 3 Method 3081A, TSI) and a condensation particle counter (CPC; model 3772, TSI).
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