摘要
为了探讨京津冀地区冬季背景大气中气溶胶化学组分特征及其来源分布,使用GRIMM 180、单颗粒黑碳光度计(SP2)和高分辨率飞行时间气溶胶质谱仪(HR-TOF-AMS)观测了海坨山2020年12月28日至2021年2月3日PM和化学组分,结合气象数据和HYSPLIT模式,计算了潜在源贡献因子(PSCF)和浓度权重轨迹(CWT),分析了不同污染过程下PM和气溶胶化学组分的时间演变特征及其潜在来源.结果表明,海坨山冬季沙尘过程主要影响PM_(10)和PM_(2.5),对PM_(1)的影响较小;而霾污染正好相反,主要影响PM_(1).化学组分在干净天和霾污染中占PM_(1)的比例分别为85.0%和73.4%,而在沙尘天仅占PM_(1)的47.4%.霾污染过程中NO^(-)_(3)的质量浓度最大,占PM_(1)的25.2%;在干净天和沙尘天黑碳(BC)的质量浓度最大,占PM_(1)的24.1%和12.8%.BC气溶胶的中值直径在干净天、沙尘天和霾污染中分别为209.7、207.5和204.7 nm.D_(p)/D_(c)在霾污染中最大,为2.15,分别是沙尘天和干净天的1.38和1.39倍.不同过程下PM和气溶胶化学组分的日变化特征不同.PM_(10)和PM_(2.5)的日变化在干净天和沙尘天为夜间高白天低,在霾污染为单峰型分布,峰值位于14:00.化学组分日变化在干净天为单峰型分布,在沙尘天和霾污染过程为双峰型分布.不同过程下BC的包裹层成分不同.BC的包裹层在干净天主要是NH_(4)NO_(3),在沙尘天主要是(NH_(4))_(2)SO_(4),在霾污染天主要是有机物.不同过程中PM_(1)及其化学组分的潜在来源分布不同.潜在源区高值区在沙尘天主要集中在西南部的北京-保定-石家庄-阳泉一带,在霾污染天主要集中在观测点周边的延庆、怀来和昌平一带.
In order to investigate the chemical composition and source apportionment of aerosols during winter in the Beijing-Tianjin-Heibei region,the particular matter(PM)and aerosol chemical composition at Mt.Haituo were observed by using a GRIMM 180,a single-particle soot photometer(SP2),and a high-resolution time-of-flight aerosol mass spectrometer(HR-TOF-AMS)from December 28,2020 to February 3,2021.Combining these observations with meteorological data and the HYSPLIT model,we calculated the potential source contribution factor(PSCF)and concentration weighted trajectory(CWT)and analyzed the temporal evolution and potential sources apportionment of PM and aerosol chemical composition under different pollution processes.The results showed that the dust storm process mainly affected PM_(10) and PM_(2.5) in Mt.Haituo during the winter and had a small impact on PM_(1);by contrast,haze pollution mainly affected PM_(1).Chemical components of aerosol accounted for 85.0%and 73.4%of PM_(1)on clean and haze days,respectively,but only 47.4%of PM_(1) in dust storm processes.NO^(-)_(3) was the chemical component with the largest mass concentration in haze,accounting for 25.2%of PM_(1);black carbon(BC)had the largest mass concentration on clean and dust storm days,accounting for 24.1%and 12.8%of PM_(1),respectively.The median diameters of BC were 209.7,207.5,and 204.7 nm on clean,dust storm,and haze days,respectively.D_(p)/D_(c) was 2.15 in haze pollution,which was 1.38 and 1.39 times that on dust storm and clean days,respectively.Diurnal variations in PM and aerosol chemical components were different during the different processes.PM_(10) and PM_(2.5) had high mass concentrations at night and low mass concentrations during the daytime on clean and dust storm days and had a unimodal distribution with a peak at 14:00 in haze.Diurnal variations in chemical composition had a unimodal distribution on clean days and a bimodal distribution on dust storm and haze days.The chemical compositions of the BC coating layer were different under different processes.The coating layers of BC were mainly NH_(4)NO_(3),(NH_(4))_(2)SO_(4),and organic matter on the clean,dust storm,and haze days,respectively.The distribution of potential sources of PM_(1)and its chemical components were different under different processes.The high-value area of the potential sources was mainly concentrated in the Beijing-Baoding-Shijiazhuang-Yangquan area in the southwestern portion of the site during dust storms and was mainly concentrated in Yanqing,Huailai,and Changping in the areas around the site during haze.
作者
赵德龙
王飞
刘丹彤
田平
盛久江
周嵬
肖伟
杜远谋
卢俐
黄梦宇
何晖
丁德平
ZHAO De-long;WANG Fei;LIU Dan-tong;TIAN Ping;SHENG Jiu-jiang;ZHOW Wei;XIAO Wei;DU Yuan-mou;LU Li;HUANG Meng-yu;HE Hui;DING De-ping(Beijing Weather Modification Office,Beijing 100089,China;China Field Experiment Base of Cloud and Precipitation Research in North China,China Meteorological Administration,Beijing 101200,China;Beijing Key Laboratory of Cloud,Precipitation and Atmospheric Water Resources,Beijing 101200,China;Department of Atmospheric Sciences,School of Earth Sciences,Zhejiang University,Hangzhou 310027,China;Beijing Meteorological Information Center,Beijing 100089,China)
出处
《环境科学》
EI
CAS
CSCD
北大核心
2022年第1期46-60,共15页
Environmental Science
基金
国家重点研发计划项目(2016YFA0602001)。
