长三角代表性城市大气细颗粒样品的采集及其表征与解析

To assess adverse health effects of fine particulate matter (PM2.5) in the ambient atmosphere, a large number of field-collected PM2.5 samples and their chemical compositions are needed. This project aims to create a network that continuously collects PM2.5 samples in typically PM2.5/photochemical smog polluted cities in Yangtze River Delta regions (Shanghai, Nanjing and Hangzhou) and to establish a quality controlled standard method for PM2.5 sampling and analysis. Samples are collected by using PM2.5 samplers. Online and offline analysis tools, including X-Ray fluorescence, ICP-MS, Quadrupole GC-MS, DESI-MS, will be employed to characterize the key chemical components of PM2.5, such as typical heavy metals (including Pb, As, Cr), polycyclic aromatic hydrocarbons with their Nitro-derivatives, and others. Those components are of high importance since they were found to be of potentional biological toxicity. The obtained chemical information together with PM2.5 samples collected from typical anthropogenic emission sources (including industrial boiler/furnace, residential combustion, open biomass burning, vehicles and ships) will be used to make semi-quantitative source appointments for the biological toxic components of PM2.5 samples via receptor models. All collected samples will be evaluated to set up a PM2.5 fingerprint and sample library, which will be the first one in China for typical polluted regions. Abundant PM2.5 samples and their key chemical components obtained in this project will be shared with other groups (at least 15) in the “Atmospheric Fine Particulate Matters and Their Health Effects” project for their health risk researches.

科学评估细颗粒物（PM2.5）的人群不良健康效应，需要使用大量实际大气颗粒物及其化学组成等信息。本课题采用大气颗粒物采样器在颗粒物与光化学烟雾同时污染为特征的长三角代表性城市（上海、南京和杭州）进行规范化连续采集大气PM2.5样品；采用在线X-射线荧光法、离线ICP-MS、四级杆GC-MS、DESI-MS等分析手段进行在线和离线表征PM2.5中Pb、As、Cr等典型重金属、多环芳烃及其硝基衍生物等可能的生物毒性关键化学组分；利用所采集的大气样品和典型人为源（工业锅炉和窑炉、民用燃烧、开放生物质、机动车和船舶等）末端排放PM2.5的表征信息，采用受体模型解析PM2.5的生物毒性成分来源。利用采集的样品，建立我国首个代表性区域PM2.5指纹图谱与样品库，并为获得基金委重大计划“大气细颗粒物的毒理与健康效应”资助的至少15个课题组的健康效应研究提供充足的PM2.5样品与关键化学组成信息。

本项目利用采集的大气颗粒物样品，建立我国首个代表性区域PM2.5指纹图谱与样品库（有效存储体积56 m3），并为获得基金委重大计划“大气细颗粒物的毒理与健康效应”资助的多个课题组的健康效应研究提供充足的PM2.5样品与关键化学组成信息。样品库收集的样品包括1408个来自长三角代表性城市（上海、南京和杭州等）的大气PM2.5样品和147个排放源（包括火力发电、工业锅炉、民用燃烧、垃圾焚烧、开放生物质、机动车和船舶等）的颗粒物样品。.针对大气气溶胶中有机组分难以识别的难题，发展并建立代表性细颗粒物样品的指纹图谱识别技术。结合GC×GC-TOF-MS和LC-QTOF-MS联合识别技术在弱极性和极性有机物非靶标分析方面的优势，探索出了关键有机毒性组分的指纹图谱识别技术，形成“源样品来源信息+常规化学组分含量+定量/半定量有机指纹图谱信息”的电子信息档案。指纹图谱识别技术成功实现了对气溶胶中水溶性有机组分的指纹图谱识别，对类腐殖质（HULIS）化学成分的识别能力从过去几十种提升到1246种。按照有机物碳骨架确定出芳香族是HULIS中最主要成分（燃煤样品占比34.5−70.0%）结构分为芳香族。此外，指纹图谱技术成功应用于识别中等和半挥发性有机物（I/SVOCs）的指纹图谱结构。将过去未识别的组分比例从67-95%的占比降低到<2%。基于指纹解析结果，可以对识别出来的有机分子精准计算其有效饱和浓度，揭示出指纹解析后的I/SVOCs的SOA产量比基于传统靶向分析所预测的SOA产量提高了63%至81%。.此外，基于所收集排放源样品的系统研究开展毒理研究。结果表明非完全燃烧源PM2.5毒性效应（包括基于二硫苏糖醇DTT消耗计算出的氧化潜势和基于细胞存活率计算出的IC20值）显著高于近似完全燃烧源。典型人为源排放PM2.5氧化潜势排序为：船舶重油（HFO）燃烧> 民用生物质燃烧 > 船舶轻质柴油（DO）燃烧> 民用燃煤 > 垃圾散烧 > 机动车 > 垃圾焚烧厂 > 燃煤电厂。.本项目顺利完成，研究成果形成专利17件，完成发表标注SCI 论文48篇，包括一篇发表在Nature energy（IF>60）上, 提出基于气溶胶人群暴露健康风险的污染防控新机制。