Aerosols chemical composition, light extinction, and source apportionment near a desert margin city, Yulin, China

PeerJ

article

Yali Lei¹  Zhenxing Shen¹  Zhuoyue Tang¹  Qian Zhang²  Jian Sun¹  Yongjing Ma³  Xiaoyan Wu³  Yiming Qin⁵  Hongmei Xu¹  Renjian Zhang⁶ 

[1] Department of Environmental Sciences and Engineering, Xi’an Jiaotong University;School of Environmental & Municipal Engineering, Xi’an University of Architecture and Technology;College of Atmospheric Sciences, Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province, Lanzhou University;State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry ,(LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences;School of Engineering and Applied Sciences, Harvard University;Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences

关键词: PM10/PM2.5;    Chemical species;    Light extinction;    Potential contribution source function;    Principal component analysis;    Yulin;   

DOI  :  10.7717/peerj.8447

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

Daily PM10and PM2.5 sampling was conducted during four seasons from December 2013 to October 2014 at three monitoring sites over Yulin, a desert margin city. PM10 and PM2.5 levels, water soluble ions, organic carbon (OC), and elemental carbon (EC) were also analyzed to characterize their chemical profiles. bext (light extinction coefficient) was calculated, which showed the highest in winter with an average of 232.95 ± 154.88 Mm−1, followed by autumn, summer, spring. Light extinction source apportionment results investigated (NH4)2SO4 and NH4NO3 played key roles in the light extinction under high RH conditions during summer and winter. Sulfate, nitrate and Ca2 + dominated in PM10/PM2.5 ions. Ion balance results illustrated that PM samples were alkaline, and PM10 samples were more alkaline than PM2.5. High SO42−/K+ and Cl−/K+ ratio indicated the important contribution of coal combustion, which was consistent with the OC/EC regression equation intercepts results. Principal component analysis (PCA) analyses results showed that the fugitive dust was the most major source of PM, followed by coal combustion & gasoline vehicle emissions, secondary formation and diesel vehicle emissions. Potential contribution source function (PSCF) results suggested that local emissions, as well as certain regional transport from northwesterly and southerly areas contributed to PM2.5 loadings during the whole year. Local government should take some measures to reduce the PM levels.

【 授权许可】

CC BY