Silicon-containing secondary organic aerosols in ambient air (Si-SOA)

环境空气中的含硅二次有机气溶胶（Si-SOA）

• 批准号: NE/R005281/1
• 负责人: Zongbo Shi
• 金额: $ 5.13万
• 依托单位: University of Birmingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FR005281%2F1
• 关键词: Silicon; containing; secondary; organic; aerosols

This Pump-Priming project will initiate a new collaboration with a leading Chinese research group led by Prof Pingqing Fu at Institute of Atmospheric Physics (IAP-CAS). Our aim is to provide definitive evidence, for the first time, on the formation of silicon-containing secondary organic aerosols (Si-SOAs) via photochemical atmospheric processing by using the novel techniques at the IAP-CAS and the UoB. The wider project context is the oxidation of Si-containing volatile organic compounds (Si-VOCs), which are widely used in personal care products and industrial applications. Si-VOCs are the most abundant VOCs in indoor air and its concentration in Chinese megacities can be over 10 microgram per cubic meter (which is extremely high). Si-VOCs can be oxidised by hydroxyl radicals and form secondary organic aerosols (SOAs), which contributes to the regional haze pollution. Our current NERC project Sources and Emissions of Air Pollutants in a Chinese Megacity - AIRPOLL-Beijing (NE/N007190/1) (2016 - 2020) integrates recent modelling, flux measurements, satellite retrievals, tower vertical profile measurements, and chemical transport modelling to provide thorough understanding of the sources and emissions of air pollutants in Beijing, at unprecedented detail and accuracy. As part of this project awarded to the University of Birmingham, we analyzed the chemical composition of individual particles collected during the winter campaign (Nov-Dec 2016) and found that >50% the fine particles contain silicon with mass fraction > 0.01. This suggests that silicon may play an important role in the formation of fine particles, which cause widespread smog / haze and lead to adverse human health effects. We also discovered that silicon is present as a coating, rather than as a solid grain, in individual sulphur-rich particles collected downwind of Chinese megacities, suggesting that the silicon is not directly emitted from primary sources (i.e., formed in the atmosphere). These new findings promoted us to hypothesize that silicon in the secondary particles in ambient air is formed from chemical processing of gas phase Si-containing VOCs. Si-SOA project will rigorously test this hypothesis. To do this, we will apply a series of novel techniques to study silicon in fine particles for the first time. We will use STEM (Scanning Transmission Electron Microscopy) and NanoSIMS (Nanoscale Secondary Ion Mass Spectrometer) to speciate silicon in atmospheric fine particles and confirm whether silicon in individual secondary particles is present as organosilicon. If confirmed, thiswill provide "smoking gun" on the formation of silicon organic aerosol by atmospheric processing. We will also apply the ESI-HRMS (Electrospray ionisation - high resolution mass spectrometer) to identify Si-containing organic molecules in fine particles and then gas chromatography - mass spectrometer to quantify the concentration of Si-SOAs identified by ESI-HRMS in selected fine particle samples collected during the APHH-China campaigns. Si-SOA project will add value to the AIRPOLL-Beijing by confirming the presence and quantify the concentration of siloxane oxidation products in fine particles. It will provide a better understanding on the sources of secondary organic aerosols, a key objective of AIRPOLL-Beijing. The project will consist of PI / research staff exchanges to plan and carry out the experiments in detail, followed by discussions on publication(s). This proposal has been developed following discussions between SHI and FU at meetings in Beijing in May 2017, which was initiated by discovery of silicon as coating in individual secondary sulphate-rich particles and the detection of silicon in over 50% of individual fine particles (see above). In addition to the specific science goals, Si-SOA will nurture a developing collaboration between UK groups and leading Chinese researchers at IAP, with potential for future links.

这个泵启动项目将与中国大气物理研究所（IAP-CAS）的傅平青教授领导的中国领先研究小组展开新的合作。我们的目标是通过使用IAP-CAS和UoB的新技术，首次提供关于通过光化学大气处理形成含硅二次有机气溶胶（Si-SOA）的确切证据。更广泛的项目背景是含硅挥发性有机化合物（Si-VOC）的氧化，这些化合物广泛用于个人护理产品和工业应用。Si-VOCs是室内空气中最丰富的VOCs，在中国特大城市的浓度可超过10微克/立方米（非常高）。Si-VOCs可被羟基自由基氧化，形成二次有机气溶胶（SOAs），对区域灰霾污染有贡献。我们目前的NERC项目“中国特大城市空气污染物的来源和排放- AIRPOLL-Beijing（NE/N 007190/1）（2016 - 2020）”整合了最新的建模、通量测量、卫星反演、塔垂直剖面测量和化学传输建模，以前所未有的细节和准确度全面了解北京空气污染物的来源和排放。作为授予伯明翰大学的该项目的一部分，我们分析了冬季活动（2016年11月至12月）期间收集的单个颗粒的化学成分，发现>50%的细颗粒含有质量分数> 0.01的硅。这表明硅可能在细颗粒物的形成中起重要作用，细颗粒物会导致广泛的烟雾/霾，并对人类健康产生不利影响。我们还发现，在中国特大城市下风处收集的个别富硫颗粒中，硅是以涂层而不是固体颗粒的形式存在的，这表明硅不是直接从主要来源排放的（即，在大气中形成）。这些新发现促使我们假设环境空气中二次颗粒物中的硅是由气相含硅VOCs的化学加工形成的。Si-SOA项目将严格检验这一假设。为此，我们将首次应用一系列新技术来研究细颗粒中的硅。我们将使用STEM（扫描透射电子显微镜）和NanoSIMS（纳米二次离子质谱仪）对大气细颗粒物中的硅进行形态分析，并确认单个二次颗粒物中的硅是否以有机硅的形式存在。如果得到证实，这将为大气处理形成硅有机气溶胶提供“确凿证据”。我们还将应用ESI-HRMS（电喷雾电离-高分辨率质谱仪）来识别细颗粒中的含硅有机分子，然后应用气相色谱-质谱仪来量化在APHH-China活动期间收集的选定细颗粒样品中通过ESI-HRMS识别的Si-SOA浓度。Si-SOA项目将通过确认细颗粒中硅氧烷氧化产物的存在并量化其浓度来为AIRPOLL-北京项目增加价值。它将使人们更好地了解二次有机气溶胶的来源，这是AIRPOLL-北京的一个关键目标。该项目将包括PI /研究人员交流，以详细计划和实施实验，然后讨论出版物。该提案是在2017年5月在北京举行的会议上SHI和FU之间的讨论之后制定的，该会议是由发现硅作为单个二次富硫酸盐颗粒的涂层以及在超过50%的单个细颗粒中检测到硅而发起的（见上文）。除了具体的科学目标外，Si-SOA还将促进英国团体与IAP的中国领先研究人员之间的合作，并有可能在未来建立联系。

项目成果

Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns.

• DOI: 10.1126/sciadv.abd6696
• 发表时间: 2021-01
• 期刊: Science advances
• 影响因子: 13.6
• 作者: Shi Z;Song C;Liu B;Lu G;Xu J;Van Vu T;Elliott RJR;Li W;Bloss WJ;Harrison RM
• 通讯作者: Harrison RM

Simultaneous measurements of urban and rural particles in Beijing - Part 1: Chemical composition and mixing state

• DOI: 10.5194/acp-20-9231-2020
• 发表时间: 2020-08-05
• 期刊: ATMOSPHERIC CHEMISTRY AND PHYSICS
• 影响因子: 6.3
• 作者: Chen, Yang;Cai, Jing;Yang, Fumo
• 通讯作者: Yang, Fumo

Attribution of Air Quality Benefits to Clean Winter Heating Policies in China: Combining Machine Learning with Causal Inference.

• DOI: 10.1021/acs.est.2c06800
• 发表时间: 2023-11-21
• 期刊: ENVIRONMENTAL SCIENCE & TECHNOLOGY
• 影响因子: 11.4
• 作者: Song, Congbo;Liu, Bowen;Cheng, Kai;Cole, Matthew A.;Dai, Qili;Elliott, Robert J. R.;Shi, Zongbo
• 通讯作者: Shi, Zongbo

An evaluation of source apportionment of fine OC and PM 2.5 by multiple methods: APHH-Beijing campaigns as a case study

多种方法对精细 OC 和 PM 2.5 源解析的评估：以 APHH-北京活动为例

• DOI: 10.48350/155723
• 发表时间: 2021
• 作者: Xu J