2014年1月北京市大气重污染过程单颗粒物特征分析

利用在线单颗粒物气溶胶质谱仪(SPAMS)对2014年1月北京市典型大气重污染过程进行了连续监测,分析了具有正负离子质谱信息的颗粒物共2248225个.同时,利用ART-2a神经网络分类方法并结合Matlab统计分析,将具有质谱信息的颗粒物归为10类,分别为:矿尘类颗粒物(Dust)、元素碳颗粒物(EC)、有机碳颗粒物(OC)、元素碳和有机碳混合颗粒物(ECOC)、钠钾颗粒物(NaK)、富钾颗粒物(K)、含氮有机物(KCN)、高分子有机物(MOC,Macromolecular OC)、多环芳烃类颗粒物(PAHs)和重金属类颗粒物(Metal).结合PM_2.5质量浓度数据和HYSPLIT 4.0后向轨迹模型结果,将观测时间段划分为3个典型污染过程和1个清洁过程.结果显示,重污染期间OC、MOC和PAHs为最主要的颗粒物类型.最后,本文还比对分析了污染过程和清洁期间颗粒物的混合状态,结果表明,污染过程中硫酸盐和硝酸盐较清洁期间更容易与碳质颗粒物结合.

Single particle analysis during heavy air pollution episodes in January 2014 in Beijing

To investigate the composition and possible sources of particles in Beijing, a single particle mass spectrometer (single particle aerosol mass spectrometry, SPAMS) was deployed to measure changes of single particle species and sizes in Beijing in January 2014. A total of 2,248,225 particles with both positive and negative spectrums were collected and characterized in combination with the ART-2a neural network algorithm. Ten types of particles were classified as dust particles (Dust), elemental carbon(EC), organic carbon(OC), EC and OC combined particles(ECOC), K-Na containing particles(NaK), K-containing particles (K), organic nitrogen and potassium containing particles(KCN), macromolecular organic carbon(MOC), polycyclic aromatic hydrocarbons(PAHs), metal-containing particles(Metal). Three haze pollution episodes and one clean period were observed based on PM_2.5 mass concentration and back trajectory results from Hysplit-4 models. OC, MOC and PAHs were the major components of single particles during the three haze pollution periods, which showed obviously higher abundance compared with clean periods. Results from the mixing state of secondary species with different types of aged particles showed that sulfate and nitrate were more easily mixed with carbon-containing particles during haze pollution events than in clean periods.