中国主要背景区域冬季大气PM2.5中非极性有机化合物组成及来源解析

本研究于2019年12月至2020年1月在5个区域大气本底站：临安、金沙、龙凤山、上甸子和瓦里关，同步采集了PM_2.5样品，分析了其中的非极性有机物：多环芳烃、正构烷烃和藿烷类化合物。结果表明，上甸子和龙凤山的多环芳烃平均浓度显著高于其他站点，分别为35.2±25.6 ng/m³和27.5±16.8 ng/m³；藿烷类物质的浓度在上甸子和临安出现高值，分别为2.72±1.78 ng/m³和2.47±0.990 ng/m³；正构烷烃浓度以临安最高，为86.7±40.6 ng/m³。对各站点多环芳烃和藿烷类化合物采用比值法，正构烷烃采用主峰碳数（C_max）、碳优势指数（carbon preference index，CPI）和植物蜡贡献率（% Wax C_n），结合主成分分析-多元线性回归模型（PCA/MLR）综合进行源解析。结果显示采样期间除瓦里关外，其余站点燃烧源均以化石燃料源为主，贡献率分别为临安（94.9%） > 金沙（75.3%） > 龙凤山（74.7%） > 上甸子（62.5%） > 瓦里关（35.6%）。后向轨迹聚类分析（HYSPLIT）和潜在源贡献因子分析法（PSCF）表明各站点主要受到外来传输气团的影响，并查明了各站点的潜在污染源区。对背景站点的研究表明，东北地区和京津冀地区PM_2.5中非极性有机物来源相似，京津冀地区的生物质燃烧源贡献率高于东北地区；长江中下游地区化石燃料贡献率显著高于生物质燃烧；华中地区燃煤和交通排放源排放贡献率均低于长江三角洲地区；青藏高原地区生物质燃烧贡献率远高于其他地区。

Composition and Source Apportionment of Non-polar Organic Compounds in PM2.5 in Winter in Major Background Regions of China

Non-polar organic compounds (NPOCs) are important components of atmospheric fine particulate species, which widely detected in atmospheric fine particulates PM_2.5. It is an effective source apportionment method to use NPOCs as molecular markers for particulate matter source apportionment. In order to understand the influence and difference of human activities on PM_2.5 organic components in regional atmosphere, in this study, from December 2019 to January 2020, PM_2.5 samples were collected simultaneously at five regional atmospheric background stations:Lin''an (LA), Jinsha (JS), Longfengshan (LFS), Shangdianzi (SDZ) and Waliguan (WLG), and the non-polar organic compounds including polycyclic aromatic hydrocarbons (PAHs), n-alkanes and hopanes were analyzed by gas chromatography mass spectrometry (GC-MS). Results show that n-alkanes were the main components, followed by polycyclic aromatic hydrocarbons and hopanes. The highest concentrations of PAHs and hopanes were 35.2±25.6 ng/m³ and 2.72±1.78 ng/m³ in SDZ, and 86.7±40.6 ng/m³ in LA. The ratio method was used for PAHs and hopanes, and the main peak carbon number (C_max), carbon preference index and %Wax C_n of n-alkanes were used for source apportionment combined with PCA/MLR model. The results show that fossil fuel sources are the main combustion sources, and the contribution rates are LA(94.9%) > JS(75.3%) > LFS(74.7%) > SDZ(62.5%) > WLG(35.6%). Backward trajectory cluster analysis and potential source contribution function show that each station is mainly affected by the external transport air mass, and the potential pollution source areas of each station are identified. The research on background sites shows that the sources of non-polar organic matter in PM_2.5 in Northeast China and Beijing-Tianjin-Hebei region are similar, and the contribution rate of biomass combustion source in Beijing-Tianjin-Hebei region is higher than that in Northeast China; the contribution rate of fossil fuel in the middle and lower reaches of the Yangtze River region is significantly higher than that of biomass combustion; the contribution rate of coal combustion and traffic emission source in Central China region is lower than that in Yangtze River Delta region; and the contribution rate of biomass combustion in Qinghai-Tibet plateau region is much higher than that of other regions.