A comprehensive SERS, SEM and EDX study of individual atmospheric PM2.5 particles in Chengdu, China

被引:10
|
作者
Li, Dongxian [1 ,2 ,3 ,4 ]
Yue, Weisheng [1 ,3 ,4 ]
Gong, Tiancheng [1 ,3 ,4 ]
Gao, Ping [1 ,3 ,4 ]
Zhang, Tao [1 ,3 ]
Luo, Yunfei [1 ,3 ,4 ]
Wang, Changtao [1 ,3 ,4 ]
机构
[1] Chinese Acad Sci, Inst Opt & Elect, POB 350, Chengdu 610209, Peoples R China
[2] Univ Elect Sci & Technol China, Sch Optoelect Sci & Engn, Chengdu 610054, Peoples R China
[3] Chinese Acad Sci, Natl Key Lab Opt Field Manipulat Sci & Technol, POB 350, Chengdu 610209, Peoples R China
[4] Univ Chinese Acad Sci, Sch Optoelect, Beijing 100049, Peoples R China
基金
中国国家自然科学基金;
关键词
PM2; 5; pollution; Compounds and elements; Surface-enhanced Raman spectroscopy; Molecular analysis; Elemental analysis; Morphology analysis; ENHANCED RAMAN-SPECTROSCOPY; FINE PARTICULATE MATTER; CHEMICAL-CHARACTERIZATION; SOURCE IDENTIFICATION; MICRO-RAMAN; AMBIENT AIR; SURFACE; PM10; CITY; IMPACT;
D O I
10.1016/j.scitotenv.2023.163668
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Characterization of atmospheric fine particulate matter (PM2.5) in large cities has important implications for the study of their sources and formation mechanisms, as well as in developing effective measures to control air pollution. Herein, we report a holistic physical and chemical characterization of PM2.5 by combining surface-enhanced Raman scattering (SERS) with scanning electron microscopy (SEM) and electron-induced X-ray spectroscopy (EDX). PM2.5 particles were collected in a suburban area of Chengdu, a large city in China with a population over 21 million. A special SERS chip composed of inverted hollow Au cone (IHAC) arrays was designed and fabricated to allow direct loading of PM2.5 par-ticles. SERS and EDX were used to reveal the chemical composition, and particle morphologies were analyzed from SEM images. SERS data of atmospheric PM2.5 indicated qualitatively the presence of carbonaceous particulate matter, sulfate, nitrate, metal oxides and bioparticles. The EDX showed the presence of the elements C, N, O, Fe, Na, Mg, Al, Si, S, K, and Ca in the collected PM2.5. Morphology analysis showed that the particulates were mainly in the form of floc-culent clusters, spherical, regular crystal shaped or irregularly shaped particles. Our chemical and physical analyses also revealed that the main sources of PM2.5 are automobile exhaust, secondary pollution caused by photochemical re-actions in the air, dust, emission from nearby industrial exhaust, biological particles, other aggregated particles, and hygroscopic particles. SERS and SEM data collected during three different seasons showed that carbon-containing par-ticles are the principal sources of PM2.5. Our study demonstrates that the SERS based technique, when combined with standard physicochemical characterization methods, is a powerful analytical tool to determine the sources of ambient PM2.5 pollution. Results obtained in this work may be valuable to the prevention and control of PM2.5 pollution in air.
引用
收藏
页数:9
相关论文
共 50 条
  • [31] Characterization of PM2.5 in the ambient air of Shanghai city by analyzing individual particles
    Yue, Weisheng
    Lia, Xiaolin
    Liu, Jiangfeng
    Li, Yan
    Yu, Xiaohan
    Deng, Biao
    Wan, Tianmin
    Zhang, Guilin
    Huang, Yuying
    He, Wei
    Hua, Wei
    Shao, Longyi
    Li, Weijun
    Yang, Shushen
    SCIENCE OF THE TOTAL ENVIRONMENT, 2006, 368 (2-3) : 916 - 925
  • [32] Characterization of PM2.5 Carbonaceous Particles with a High-Efficiency SEM: A Case Study at a Suburban Area of Xi’an
    Meixia Wang
    Tafeng Hu
    Feng Wu
    Jing Duan
    Yingpan Song
    Yuqing Zhu
    Chenxin Xue
    Ningning Zhang
    Daizhou Zhang
    Aerosol Science and Engineering, 2021, 5 : 70 - 80
  • [33] Characterization of PM2.5 Carbonaceous Particles with a High-Efficiency SEM: A Case Study at a Suburban Area of Xi'an
    Wang, Meixia
    Hu, Tafeng
    Wu, Feng
    Duan, Jing
    Song, Yingpan
    Zhu, Yuqing
    Xue, Chenxin
    Zhang, Ningning
    Zhang, Daizhou
    AEROSOL SCIENCE AND ENGINEERING, 2021, 5 (01) : 70 - 80
  • [34] Refined Source Apportionment of Atmospheric PM2.5 in a Typical City in Northwest China
    Wang, Yiting
    Zhang, Yong
    Li, Xia
    Cao, Junji
    AEROSOL AND AIR QUALITY RESEARCH, 2021, 21 (01) : 1 - 11
  • [35] Atmospheric conditions and composition that influence PM2.5 oxidative potential in Beijing, China
    Campbell, Steven J.
    Wolfer, Kate
    Utinger, Battist
    Westwood, Joe
    Zhang, Zhi-Hui
    Bukowiecki, Nicolas
    Steimer, Sarah S.
    Vu, Tuan V.
    Xu, Jingsha
    Straw, Nicholas
    Thomson, Steven
    Elzein, Atallah
    Sun, Yele
    Liu, Di
    Li, Linjie
    Fu, Pingqing
    Lewis, Alastair C.
    Harrison, Roy M.
    Bloss, William J.
    Loh, Miranda
    Miller, Mark R.
    Shi, Zongbo
    Kalberer, Markus
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2021, 21 (07) : 5549 - 5573
  • [36] Temporal and spatial distribution characteristics of atmospheric PM2.5 concentrations in Guiyang, China
    Sun, Rongguo
    Fan, Li
    Chen, Zhuo
    Nature Environment and Pollution Technology, 2019, 18 (02) : 663 - 671
  • [37] Individual exposure of graduate students to PM2.5 and black carbon in Shanghai, China
    Lei, Xiaoning
    Xiu, Guangli
    Li, Bo
    Zhang, Kun
    Zhao, Mengfei
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2016, 23 (12) : 12120 - 12127
  • [38] Characteristics and source apportionment of PM2.5 during persistent extreme haze events in Chengdu, southwest China
    Li, Lulu
    Tan, Qinwen
    Zhang, Yuanhang
    Feng, Miao
    Qu, Yu
    An, Junling
    Liu, Xingang
    ENVIRONMENTAL POLLUTION, 2017, 230 : 718 - 729
  • [39] Individual exposure of graduate students to PM2.5 and black carbon in Shanghai, China
    Xiaoning Lei
    Guangli Xiu
    Bo Li
    Kun Zhang
    Mengfei Zhao
    Environmental Science and Pollution Research, 2016, 23 : 12120 - 12127
  • [40] Characteristics and source apportionment of PM2.5 during persistent extreme haze events in Chengdu, southwest China
    Li, Lulu
    Tan, Qinwen
    Zhang, Yuanhang
    Feng, Miao
    Qu, Yu
    An, Junling
    Liu, Xingang
    Environmental Pollution, 2017, 230 : 718 - 729