三亚市大气VOCs污染特征、臭氧生成潜势及来源解析

为探究热带地区环境空气中挥发性有机物(VOCs)的污染特征，利用三亚市2019年VOCs在线监测数据，全面分析了VOCs的污染特征、来源以及对O₃的影响.结果表明:①总挥发性有机物(TVOCs)日均体积分数范围为2.05×10-9~19.74×10-9，且以烷烃(71.4%)和烯烃(20.5%)为主.②VOCs优势物种丙烷、正丁烷、乙烷、异丁烷、乙烯、乙炔、苯和甲苯的体积分数日变化均呈早晚双峰的特征；φ(异戊二烯)呈白天显著高于夜间的特征，其季节性变化规律与光照变化基本一致.③对臭氧生成潜势(OFP)贡献最大的是烯烃(70.6%)，其中异戊二烯的OFP贡献率(41.9%)最大，其次是烷烃(19.9%).④春夏季φ(NO₂)和φ(VOCs)均较低，难以通过光化学反应生成较高的φ(O₃)，秋冬季φ(O₃)显著升高主要与东北方向污染物传输有关.⑤正交矩阵因子模型(PMF)解析结果表明，VOCs来源分别为交通源(46.52%)、溶剂使用源(18.25%)、植物源(12.36%)、工业源(11.99%)和燃烧源(10.88%).研究显示，三亚市环境空气中φ(VOCs)受交通源排放影响较大，应加强管制以削减环境空气中VOCs活性较大的物种，从而减少O₃的生成. 

Pollution Characterization,Ozone Formation Potential and Source Apportionment of Ambient VOCs in Sanya,China

Utilizing the online monitoring data of volatile organic compounds (VOCs) in Sanya in 2019, the pollution characteristics and sources of VOCs, and the effects of VOCs on O₃ were comprehensively analyzed to investigate the pollution characteristics of VOCs in the ambient air in tropical regions. The results showed that: (1) The daily average mixing ratio of total volatile organic compounds (TVOCs) ranged from 2.05×10-9 to 19.74×10-9, and the composition was dominated by alkanes (71.4%) and olefins (20.5%). (2) The diurnal variations mixing ratio of dominant VOCs species such as propane, n-butane, isobutane, ethane, ethylene, acetylene, benzene and toluene, showed obvious bimodal distribution in the morning and evening. The diurnal variations mixing ratio of isoprene was significantly higher during the day than at night, and the seasonal variation was basically consistent with the changes of light. (3) The greatest contribution to ozone formation potential (OFP) was alkenes (70.6%), of which isoprene contributed the most (41.9%), followed by alkanes (19.9%). (4) The concentration of VOCs and NO₂ in spring and summer was low, and it was difficult to generate high concentration of O₃ through photochemical reaction. The significant increase in O₃ concentration in autumn and winter was mainly related to the transmission of pollutants in the northeast. (5) Six sources were extracted by positive matrix factorization (PMF) model: traffic source (46.52%), solvent usage source (18.25%), plant source (12.36%), industrial source (11.99%) and combustion source (10.88%). Overall, the concentration of ambient VOCs in Sanya was strongly influenced by traffic sources, and the control of VOCs emitted from motor vehicles should be strengthened to reduce the active components of atmospheric VOCs in Sanya, thereby reducing the generation of O₃.