中文关键词气溶胶化学组分在线监测仪(ACSM)非难熔性PM₁(NR-PM₁)化学组分潜在源贡献分析(PSCF)法气象-空气质量模式(WRF-CAMx)PM_2.5传输通量 英文关键词Aerosol Chemical Speciation Monitor (ACSM)non-refractory submicron aerosols (NR-PM₁)chemical componentspotential source contribution function (PSCF) methodmeteorology-air quality coupling model system (WRF-CAMx)PM_2.5 transport flux

作者	单位	E-mail
张晗宇	北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124	zhy2016@emails.bjut.edu.cn
程水源	北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124	bjutpaper@gmail.com
姚森	北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124
王晓琦	北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124
张俊峰	北京工业大学环境与能源工程学院, 区域大气复合污染防治北京市重点实验室, 北京 100124

中文摘要 本研究采用气溶胶化学组分在线监测仪（ACSM）对北京地区2016年10月15日~11月15日期间非难熔性PM₁（NR-PM₁）化学组分进行实时连续在线观测，探讨了NR-PM₁化学组分的演变特征；运用潜在源贡献分析（PSCF）法和气象-空气质量模式（WRF-CAMx）识别了北京PM_2.5潜在污染源区和传输路径，揭示了PM_2.5净传输通量的垂直分布特征.结果表明，北京秋季NR-PM₁和PM_2.5质量浓度分别为（59.16±57.05）μg·m^-3和（89.82±66.66）μg·m^-3，其中NR-PM₁平均占PM_2.5的（70.31±22.28）%.整个观测期间，有机物（Org）、硝酸盐（NO₃^-）、硫酸盐（SO₄^2-）、铵盐（NH₄⁺）和氯化物（Chl）分别占NR-PM₁总质量浓度的（42.75±11.35）%、（21.27±7.72）%、（19.11±7.08）%、（12.19±2.64）%和（4.68±3.24）%，不同化学组分的日变化特征存在明显差异.对北京秋季NR-PM₁污染影响较大的潜在源区主要集中在河北南部、河南东北部及山东西部，重污染期间保定、北京南部及廊坊等城市对NR-PM₁贡献较大.WRF-CAMx模拟结果表明，PM_2.5总的净传输通量呈现出显著的垂直分布特征.整个观测期间，毗邻城市主要向北京输入PM_2.5，净通量最大出现在海拔600~1000 m；而重污染前期外来源输送PM_2.5主要位于高空，直到污染最严重的11月5日，PM_2.5转为近地面传输，说明高空和近地面传输是影响北京秋季PM_2.5重污染形成的重要因素.同时鉴别出了两种传输路径，即西南-东北方向（保定→北京→承德）和西北-东南方向（张家口→北京→廊坊北→天津）. 英文摘要 In this study, the Aerosol Chemical Speciation Monitor (ACSM) was used to conduct real-time and continuous comprehensive observation of chemical components in non-refractory submicron aerosols (NR-PM₁) from October 15 to November 15, 2016. In addition to that, the evolution characteristics of NR-PM₁ chemical components were discussed. The potential source contribution function (PSCF) method and a meteorology-air quality coupling model system (WRF-CAMx) were applied to identify the potential PM_2.5 emission sources and transport path in Beijing, and the vertical distribution characteristics of PM_2.5 net transport flux. The results indicate that the monthly average mass concentrations of NR-PM₁ and PM_2.5 were (59.16±57.05) μg·m^-3 and (89.82±66.66) μg·m^-3, respectively. On average, NR-PM₁ accounted for (70.31±22.28)% of PM_2.5. During the whole study period, Org, NO₃^-, SO₄^2-, NH₄⁺, and Chl represented (42.75±11.35)%, (21.27±7.72)%, (19.11±7.08)%, (12.19±2.64)%, and (4.68±3.24)% of NR-PM₁, respectively. The diurnal variation characteristics of different chemical components were disparate. The high potential source areas were mainly located in southern Hebei, northeastern Henan, and western Shandong provinces during the whole study period. During the haze episode, the potential regions of higher contribution were concentrated in Baoding, southern Beijing, and Langfang. The simulation results of WRF-CAMx showed that the vertical distribution characteristics of PM_2.5 net flux varied with different altitudes. The adjacent cities mainly export PM_2.5 to Beijing, and the PM_2.5 net fluxes mainly occurred at 600-800 m during the whole study period. PM_2.5 in Beijing from external sources mainly occurred in high altitudes during the early stage of the heavy pollution episode. Then it turned to near-ground transport until November 5, when the pollution was the most severe. This indicated that high-altitude and near-ground transport both played an essential role in the formation of heavy PM_2.5 pollution in Beijing during the autumn. Moreover, two important transport pathways were identified:the southwest-northeast pathway (Baoding→Beijing→Chengde) and the northwest-southeast pathway (Zhangjiakou→Beijing→Langfang-south→Tianjin).

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