The formation and evolution of secondary organic aerosol during summer in Xi'an: Aqueous phase processing in fog-rain days
Graphical abstract
Introduction
As a dominant component of fine particles, organic aerosol (OA) has important effects on air quality and human health (Watson, 2002; Jimenez et al., 2009; Pope et al., 2009; Shen et al., 2015; An et al., 2019). OA can be either emitted from primary sources (primary OA, POA) such as cooking, traffic, coal combustion, and biomass burning, or produced by gas-to-particle conversion in the atmosphere (secondary OA, SOA) (Xu et al., 2017). With the mitigation of POA, SOA is becoming more critical for urban air quality (Liu et al., 2010; Huang et al., 2014, Huang et al., 2019; Xu et al., 2019; Duan et al., 2020). However, compared to POA that is relatively well constrained, our understanding of SOA is still limited. Model simulations of SOA concentrations and oxidation states are still largely uncertain because of insufficient cognition of SOA formation and aging chemistry (Tsigaridis et al., 2014; Hu et al., 2017; Shrivastava et al., 2017; Xing et al., 2019).
SOA can be formed through gas-phase photochemical oxidation of volatile organic compounds (VOCs) with OH radicals, ozone (O3), or other atmospheric oxidants, followed by gas-particle partitioning onto preexisting particles (Donahue et al., 2006). SOA can also be formed in aqueous phase including wet aerosols, clouds and fogs through the further chemical processes of water-soluble VOCs or SOA produced from gas-phase photochemistry (Ervens et al., 2011, Ervens et al., 2014). A growing number of experiments and simulation studies have indicated that aqueous-phase processes are important but missing pathways for SOA formation (Lee et al., 2012; Gilardoni et al., 2016; Bikkina et al., 2017).
As ambient measurements of SOA are challenging, oxygenated organic aerosol (OOA) factors determined from OA source apportionment using positive matrix factorization (PMF) are often adopted as substitutes for SOA (Kondo et al., 2007; Xu et al., 2017). Numerous field measurements using aerosol chemical speciation monitor (ACSM) or aerosol mass spectrometer (AMS) have been conducted in China in recent years for the investigation of aqueous chemistry contributions to the formation and evolution of SOA (Hu et al., 2016; Sun et al., 2016; Wang et al., 2017; Xu et al., 2017; Huang et al., 2019; Kuang et al., 2020). For example, an aqueous-phase-processed SOA (aq-OOA) accounting for 12% of total OA was identified by Sun et al. (2016), which had a significant effect on increasing OA oxidation degree under high RH conditions. The results of Xu et al. (2017) indicated that the less oxidized-OOA (LO-OOA) was mainly formed through photochemical oxidation, while the more oxidized-OOA (MO-OOA) formation was dominantly affected by aqueous-phase chemistry. Kuang et al. (2020) further found rapid OOA formation in daytime during haze pollution period in winter, which was induced by the photochemical aqueous-phase chemistry. However, the major factors determining aqueous-phase SOA formation and coordinated effects of photochemistry and aqueous-phase chemistry on SOA formation under different meteorological conditions are still unclear. Meanwhile, previous studies were mainly conducted in North China Plain (NCP), while there is still a lack of research on the characterization of SOA formation in Guanzhong Basin (Elser et al., 2016; Wang et al., 2017; Zhong et al., 2020), which is one of the top three regions in China's air cleaning campaign.
A few studies using AMS or ACSM have been conducted in Xi'an, the most important city of the Guanzhong basin, and mainly focused on aerosol composition and sources during winter (Elser et al., 2016; Zhong et al., 2020). In contrast, online characterization of aerosol composition, sources and SOA formation mechanisms in Xi'an during summer with high atmospheric oxidation capacity has not yet been reported. Here, online measurements of PM2.5 composition in Xi'an during summer were conducted using a soot particle long-time-of-flight AMS (SP-LToF-AMS). The chemical composition and OA sources were analyzed, and the formation mechanisms and evolutions of SOA under different meteorological conditions were elucidated, with a focus on the aqueous-phase SOA contribution and formation processes.
Section snippets
Sampling
The measurement was performed from 22 June to 21 July 2019 at the campus of the Institute of Earth Environment, Chinese Academy of Sciences (34°23′N, 108°89′, 12 m above the ground level) in downtown Xi'an with surrounding residential, traffic, and commercial areas.
Online characterization of PM2.5 composition was conducted by the SP-LToF-AMS (Aerodyne Research Inc.) with a time resolution of 1 min, and the instrument description and operation were detailed in Onasch et al. (2012). As the
NR-PM2.5 composition in summertime Xi'an
The time variations of NR-PM2.5 composition, gas pollutants as well as RH and temperature during the summer campaign are shown in Fig. 1. The summary of average concentrations of each component and average values of individual parameters during different periods are also presented in Table 1. The mass concentration of NR-PM2.5 ranged from 1.3 μg m−3 to 82.9 μg m−3, with an average of 22.5 μg m−3, which was an order of magnitude lower than that measured in wintertime Xi'an (Elser et al., 2016).
Conclusion
High-resolution characterization of NR-PM2.5 was conducted using a SP-LToF-AMS during summer in Xi'an. An average NR-PM2.5 concentration of 22.5 μg m−3 was observed. OA showed a dominant contribution to NR-PM2.5, with an average mass fraction of 62%. In comparison, sulfate on average constituted 17% of NR-PM2.5, followed by nitrate (12%) and ammonium (8%). However, from non-fog-rain days to fog-rain days, the OA contribution decreased from 74% to 54%, while the nitrate contribution increased
CRediT authorship contribution statement
Jing Duan: Methodology, Data curation, Formal analysis, Writing – original draft, Writing – review & editing. Ru-Jin Huang: Conceptualization, Validation, Data curation, Writing – original draft, Writing – review & editing, Supervision, Project administration, Funding acquisition. Yifang Gu: Data curation. Chunshui Lin: Writing – review & editing. Haobin Zhong: Writing – review & editing. Ying Wang: Data curation. Wei Yuan: Writing – review & editing. Haiyan Ni: Writing – review & editing. Lu
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgement
This work was supported by the National Natural Science Foundation of China (NSFC) under Grant No. 41925015, 91644219, and 41877408, the Chinese Academy of Sciences (No. ZDBS-LY-DQC001, XDB40000000), and the Cross Innovative Team fund from the State Key Laboratory of Loess and Quaternary Geology (No. SKLLQGTD1801).
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