两种典型污染时段鹤山市大气细颗粒污染特征及来源

PM_2.5和O₃浓度超标是我国大气污染的主要特征，研究两种典型污染时段的细颗粒化学组成、混合状态和来源对治理大气污染具有重要意义.2016年11月10—20日广东省鹤山市先后出现了PM_2.5和O₃超标的污染事件.污染期间，采用SPAMS（单颗粒气溶胶质谱仪）对细颗粒进行实时采样分析，共采集到有正负化学组成信息的颗粒422 944个，占总颗粒数的19.2%.基于单颗粒质谱数据特征，使用自适应共振神经元网络算法（ART-2a），对单颗粒数据进行自适应分类.颗粒物划分为OC（有机碳）、EC（元素碳）、ECOC（元素-有机碳混合）、HOC（高分子有机碳）、Pb-rich（富铅）、Si-rich（富硅）、LEV（左旋葡聚糖）、K-Secondary（钾二次）、Na-rich（海盐）和HM（重金属）颗粒共10类.结果表明:两个PM_2.5污染时段EC颗粒和K-Secondary颗粒的占比高，EC颗粒分别占46.5%和61.1%，K-Secondary颗粒分别占14.3%和10.3%；O₃污染时段EC颗粒占比（39.4%）最高，其次是OC颗粒占比17.0%；两种污染时段OC组分与HSO₄-和NO₃-的混合程度都有明显的上升，说明污染有利于有机气溶胶的老化.由源解析结果可知，PM_2.5污染时段，细颗粒主要来源于燃煤、机动车尾气和扬尘，而O₃污染时段细颗粒主要来源于燃煤、生物质燃烧和扬尘；此外，两种污染时段燃煤源对细颗粒的贡献都有较大提升.研究显示，控制燃煤源的排放对污染物的降低有着重要影响. 

Chemical Composition and Source Apportionment of Single Particles during Two Typical Pollution Events in Heshan City

High concentrations of fine particulate matter (PM_2.5) and ozone (O₃) are main characteristic of air pollution in China. It is of great significance to study the chemical composition, mixing state and source of ambient particles for reducing air pollution. A single particle aerosol time-of-flight mass spectrometer (SPAMS) was used to analyze single particles in Heshan City from 10^th-20^th, November, 2016. A total of 422,944 particles (19.2% of the total particle number) were detected with positive and negative ion spectra. Based on mass spectral features of particles, the particles were classified into ten types including organic carbon (OC), elemental carbon (EC), ECOC, high molecular OC (HOC), Pb-rich, Si-rich, levoglucosan (LEV), K-rich, Na-rich and heavy metal (HM) particles. EC particles were the most abundant species in two PM_2.5 events (46.5% and 61.1%) and one O₃ pollution event (39.4%), while K-Secondary particles (14.3% and 10.3%) and OC particles (17.0%) were the second abundant species in PM_2.5 pollution events and in O₃ pollution event, respectively. More OC particles were found to be internally mixed with HSO₄^- and NO₃^- in polluted days than in clean days, suggesting a more aged state of OC particles in pollution events. The source apportionment showed that the particles in PM_2.5 pollution events could be mainly from coal combustion, vehicle exhaust and dust, while the particles in O₃ pollution events are most likely from coal combustion, biomass burning and dust. Besides, coal combustion had an increased contribution to fine particles both in two kinds of pollution events.