摘要
利用卡尔费休法可直接测定PM_(2.5)水分含量,方法精密度及准确度均较好.将该方法应用于北京市城区站点2020年全年的PM_(2.5)分析,结果显示PM_(2.5)水分浓度年均值为(5.0±4.1)μg/m^(3),在PM_(2.5)占比为(12.5±4.8)%,与PM_(2.5)质量浓度呈显著相关.水分质量浓度与PM_(2.5)的质量浓度月度及季节变化趋势基本一致.研究发现,随着空气污染加重,水分质量浓度及其在PM_(2.5)占比均呈上升趋势,二者相关性明显增强.可见污染发生时,水分增加有利于颗粒物吸湿增长从而推高污染水平,对PM_(2.5)的贡献同步增强.当沙尘污染发生时湿度处于同期较低水平,不利于细颗粒物的吸湿增长,水分质量浓度及其占比均处于较低水平.PM_(2.5)水分与二次离子及有机物均有很好的相关性,说明水分为气态污染物提供非均相转化载体,促进硝酸盐、硫酸盐、有机物的进一步生成.PM_(2.5)水分与地壳物质无相关性,证实地壳元素为一次源,不受水分影响.
Karl Fischer method can directly determine the water content of PM_(2.5)with good precision and accuracy.The method was applied to PM_(2.5)analysis of urban stations in Beijing in 2020,and the results showed that the annual average water concentration was(5.0±4.1)μg/m^(3),and the proportion of PM_(2.5)was(12.5±4.8)%,which was significantly correlated with PM_(2.5)mass concentration.The monthly and seasonal variation trended of water concentration and PM_(2.5)mass concentration were basically consistent.The study found that with the increase of air pollution,the water concentration and its proportion in PM_(2.5)both showed an increasing trend,and the correlation between them was significantly enhanced.It can be seen that when pollution occurred,the increase of water concentration was conducive to the increase of moisture absorption of particles,thus pushing up the pollution level and enhancing the contribution to PM_(2.5)simultaneously.When dust pollution occurred,the humidity was at a low level in the same period,which was not conducive to the growth of moisture absorption of fine particles,the water concentration and its proportion were at a low level.There was a good correlation between water,secondary ions and organic matter,indicating that water provided heterogeneous transformation carrier for gaseous pollutants and promotes the further generation of fine particles such as nitrate,sulfate and organic matter.There was no correlation between water and crustal material,which proved that crustal elements were primary sources and were not affected by water.
作者
陈圆圆
李珺琪
常淼
沈秀娥
刘保献
CHEN Yuan-yuan;LI Jun-qi;CHANG Miao;SHEN Xiu-e;LIU Bao-xian(Beijing Key Laboratory of Airborne Particulate Matter Monitoring Technology,Beijing Municipal Environmental Monitoring Center,Beijing 100048,China)
出处
《中国环境科学》
EI
CAS
CSCD
北大核心
2023年第1期70-76,共7页
China Environmental Science
基金
大气重污染成因与治理攻关项目(DQGG202101)。
