嘉善冬季PM2.5化学组分特征及来源分析

张颖龙, 李莉, 宋刘明, 王翡, 赵欢欢, 吴伟超, 唐倩, 潘晨, 陈昊. 嘉善冬季PM2.5化学组分特征及来源分析[J]. 环境化学, 2021, (3): 754-764. doi: 10.7524/j.issn.0254-6108.2020062303
引用本文: 张颖龙, 李莉, 宋刘明, 王翡, 赵欢欢, 吴伟超, 唐倩, 潘晨, 陈昊. 嘉善冬季PM2.5化学组分特征及来源分析[J]. 环境化学, 2021, (3): 754-764. doi: 10.7524/j.issn.0254-6108.2020062303
ZHANG Yinglong, LI Li, SONG Liuming, WANG Fei, ZHAO Huanhuan, WU Weichao, TANG Qian, PAN Chen, CHEN Hao. Chemical components characteristic and source apportionment of PM2.5 during winter in Jiaxing[J]. Environmental Chemistry, 2021, (3): 754-764. doi: 10.7524/j.issn.0254-6108.2020062303
Citation: ZHANG Yinglong, LI Li, SONG Liuming, WANG Fei, ZHAO Huanhuan, WU Weichao, TANG Qian, PAN Chen, CHEN Hao. Chemical components characteristic and source apportionment of PM2.5 during winter in Jiaxing[J]. Environmental Chemistry, 2021, (3): 754-764. doi: 10.7524/j.issn.0254-6108.2020062303

嘉善冬季PM2.5化学组分特征及来源分析

    通讯作者: 潘晨, E-mail: arthur_pc@163.com
  • 基金项目:

    国家自然科学基金(41805120,41905099)资助.

Chemical components characteristic and source apportionment of PM2.5 during winter in Jiaxing

    Corresponding author: PAN Chen, arthur_pc@163.com
  • Fund Project: Supported by the National Natural Science Foundation of China (41805120, 41905099).
  • 摘要: 为研究嘉兴地区嘉善冬季污染时段和清洁时段PM2.5化学组分特征,结合气象数据对2019年1月嘉兴市嘉善县善西超级站在线自动监测PM2.5及化学组分数据、气态污染物(NO2和SO2)进行了分析.结果表明,2019年1月嘉善善西超级站污染时段PM2.5浓度(97.18 μg·m-3)为清洁时段(36.77 μg·m-3)的2.6倍.污染时段水溶性离子浓度(41.58 μg·m-3)较清洁时段(19.82 μg·m-3)高21.76 μg·m-3,但占比有所降低,含碳组分比例增加.OC/EC比值为3.93,可能受到燃煤及机动车排放的共同影响.低风速及高湿有利于NO2和SO2等气态污染物进行二次转化,污染时段硫转化率和氮转化率均比清洁时段高,分别增高7.93%和54.11%,说明NOx向硝酸盐二次转化较为明显,导致颗粒物浓度升高.聚类分析结果显示67.34%气流来自北方,且相应的气流轨迹上污染物浓度比周边高,说明污染物存在一定的长距离输送.结合风玫瑰图可以看出,污染主要为本地及其周边的输送,污染物的长距离输送在短时会使污染浓度突增.因此,在重点关注本地及周边污染的同时,偏北气流下的污染物区域输送不可忽视.
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嘉善冬季PM2.5化学组分特征及来源分析

    通讯作者: 潘晨, E-mail: arthur_pc@163.com
  • 1. 浙江省嘉兴生态环境监测中心, 嘉兴, 314000;
  • 2. 嘉兴市气象局, 嘉兴, 314000;
  • 3. 浙江省生态环境监测中心, 杭州, 310012;
  • 4. 江苏省气象台, 南京, 210008
基金项目:

国家自然科学基金(41805120,41905099)资助.

摘要: 为研究嘉兴地区嘉善冬季污染时段和清洁时段PM2.5化学组分特征,结合气象数据对2019年1月嘉兴市嘉善县善西超级站在线自动监测PM2.5及化学组分数据、气态污染物(NO2和SO2)进行了分析.结果表明,2019年1月嘉善善西超级站污染时段PM2.5浓度(97.18 μg·m-3)为清洁时段(36.77 μg·m-3)的2.6倍.污染时段水溶性离子浓度(41.58 μg·m-3)较清洁时段(19.82 μg·m-3)高21.76 μg·m-3,但占比有所降低,含碳组分比例增加.OC/EC比值为3.93,可能受到燃煤及机动车排放的共同影响.低风速及高湿有利于NO2和SO2等气态污染物进行二次转化,污染时段硫转化率和氮转化率均比清洁时段高,分别增高7.93%和54.11%,说明NOx向硝酸盐二次转化较为明显,导致颗粒物浓度升高.聚类分析结果显示67.34%气流来自北方,且相应的气流轨迹上污染物浓度比周边高,说明污染物存在一定的长距离输送.结合风玫瑰图可以看出,污染主要为本地及其周边的输送,污染物的长距离输送在短时会使污染浓度突增.因此,在重点关注本地及周边污染的同时,偏北气流下的污染物区域输送不可忽视.

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