赵留元,李子璇,吕沛诚,宋世杰,张英俊,张静,高宏,马建民,黄韬,毛潇萱.基于SPAMS的兰州市2018年冬季沙尘天气过程细颗粒物污染特征及来源研究[J].环境科学学报,2020,40(2):388-400
基于SPAMS的兰州市2018年冬季沙尘天气过程细颗粒物污染特征及来源研究
- Pollution characteristics and sources of atmospheric fine particulates during the period of 2018,winter dust weather in Lanzhou City based on SPAMS technology
- 基金项目：国家自然科学基金面上项目（No.41671460）；国家重点研发计划项目（No.2017YFC0212002）
- 赵留元
- 兰州大学资源环境学院甘肃省环境污染预警与控制重点实验室, 兰州 730000
- 李子璇
- 兰州大学资源环境学院甘肃省环境污染预警与控制重点实验室, 兰州 730000
- 宋世杰
- 兰州大学资源环境学院甘肃省环境污染预警与控制重点实验室, 兰州 730000
- 张英俊
- 甘肃省兰州生态环境监测中心, 兰州 730000
- 张静
- 甘肃省兰州生态环境监测中心, 兰州 730000
- 高宏
- 兰州大学资源环境学院甘肃省环境污染预警与控制重点实验室, 兰州 730000
- 马建民
- 北京大学城市与环境学院地表过程分析与模拟教育部重点实验室, 北京 100871
- 黄韬
- 兰州大学资源环境学院甘肃省环境污染预警与控制重点实验室, 兰州 730000
- 毛潇萱
- 兰州大学资源环境学院甘肃省环境污染预警与控制重点实验室, 兰州 730000
- 摘要：2018年11月22日-12月1日，兰州市经历了一次远距离传输的沙尘天气过程，为了解此次沙尘天气过程时段细颗粒物污染特征及其污染来源变化特征，本研究基于单颗粒气溶胶质谱仪（SPAMS）细颗粒物自动采集数据，并结合常规污染物自动监测数据和气象因子数据对沙尘天气前后及其过境期间细颗粒物化学组分及污染来源变化情况进行了分析，同时利用后向轨迹模型（HYSPLIT）研究了沙尘气溶胶的输送路径.研究结果表明：受沙尘天气过境影响，兰州市PM10浓度大幅升高，PM2.5/PM10最小值仅为0.13，SO2、NO2、CO质量浓度出现明显降低，而O3质量浓度在沙尘过境时有所升高；细颗粒物质量浓度与MASS数浓度变化趋势基本一致，细颗粒物的变化趋势可一定程度上反映大气细颗粒物的污染状况；利用自适应共振神经网络法分类后经人工合并将所采集到的细颗粒分为9类：OC、EC、HOC、OCEC、MD、HM、K、Na、LEV；所选时间段内SPAMS采集到的OC（24.8%）类颗粒物数量最多，沙尘过境时MD、LEV、Na类颗粒物占比不同程度增大，其余颗粒物占比减小；沙尘过境时扬尘源、生物质燃烧源、工业工艺源、餐饮及其它源贡献率增加，其中扬尘源增幅最大，而其余源贡献占比减小；后向轨迹HYSPLIT模型输送路径结果显示沙尘天气过程的起源地为塔克拉玛干沙漠，传输方向为经新疆的塔里木盆地塔克拉玛干沙漠进入青海中部，最后影响兰州地区.
- Abstract：From November 22 to December 1, 2018, a strong dust event occurred in Lanzhou. To gain insight into understanding the primary characteristics of fine particles and origins of this dust event, the chemical composition of sand dust and source-receptor relationships were investigated. A single particle mass aerosol spectrometer (SPAMS) was employed to collect concentration of fine particulate matter in the atmosphere before, after, and during the dust event. The criteria air pollutants and meteorological data were collected simultaneously from the official air quality monitoring stations in Lanzhou. The HYSPLIT model was used to trace the transport routes of dust aerosols from their potential source regions. Monitoring data revealed a sharp increase of PM10 concentrations with a minimum PM2.5/PM10 ratio of 0.13. Accordingly, decreasing concentration levels of SO2, NO2 and CO decreases and increasing O3 concentrations were observed. It was found that the trend of mass concentrations of fine particles were almost identical to that of MASS number, featuring primary pollution characteristics of fine particulate matters. In the present study, fine particulate matters were classified into nine categories by an adaptive resonance neural network method, these are OC, EC, HOC, OCEC, MD, HM, K, Na, and LEV. Among these compositions, OC contributed mostly to total particulate matter at 24.8% during the period of dust storm. MD, LEV, and Na exhibited most significant increase in particulate matters whereas the contribution of other particles to the total particulate matter declined when the dust storm passed over Lanzhou. The SPAMS measurements discerned that dust, biomass burning, industrial process, catering source, and other sources contributed increasingly to the dust storm, associated with decreasing contribution from other sources to the dust storm across the Lanzhou Valley. The HYSPLIT model retrieved source origins shows that the Taklimakan Desert was a major source of this sand storm. Originated from the Taklimakan Desert in the Tarim Basin, this dust storm moved over the central Qinghai Province along its route and reached Lanzhou area.
