TY - JOUR
T1 - Classification and source analysis of low-altitude aerosols in Beijing using fluorescence–Mie polarization lidar
AU - Zhang, Yinchao
AU - Sun, Zhuoran
AU - Chen, Siying
AU - Chen, He
AU - Guo, Pan
AU - Chen, Su
AU - He, Jinxi
AU - Wang, Jiaqi
AU - Nian, Xuan
N1 - Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2021/1/15
Y1 - 2021/1/15
N2 - The types of aerosols are essential for estimating radiative forcing effects, improving the lidar retrieval algorithms, and identifying aerosol sources. However, it is difficult to categorize the aerosols with similar optical properties based on lidar techniques. In this study, an approach was proposed to distinguish desert dust (DD), mineral dust (MD), air pollution aerosols (APA), and their mixtures (DD&MD, DD&APA, MD&APA, DD&MD&APA). We established the fluorescence–Mie polarization lidar (FMPL) system to categorize three types of main aerosols using the customized fluorescence-to-Mie ratio (FMR) and volume depolarization ratio (VDR) in the experiments from September 2017 to December 2018. Then, the mixture of the aerosols was classified by combining backward trajectory analysis. The feasibility of this method was verified through five typical cases in the paper, and it is proved that the method could be employed to study air pollution issues based on FMPL, which could provide references for the meteorological investigation.
AB - The types of aerosols are essential for estimating radiative forcing effects, improving the lidar retrieval algorithms, and identifying aerosol sources. However, it is difficult to categorize the aerosols with similar optical properties based on lidar techniques. In this study, an approach was proposed to distinguish desert dust (DD), mineral dust (MD), air pollution aerosols (APA), and their mixtures (DD&MD, DD&APA, MD&APA, DD&MD&APA). We established the fluorescence–Mie polarization lidar (FMPL) system to categorize three types of main aerosols using the customized fluorescence-to-Mie ratio (FMR) and volume depolarization ratio (VDR) in the experiments from September 2017 to December 2018. Then, the mixture of the aerosols was classified by combining backward trajectory analysis. The feasibility of this method was verified through five typical cases in the paper, and it is proved that the method could be employed to study air pollution issues based on FMPL, which could provide references for the meteorological investigation.
KW - Air pollution aerosols
KW - Desert dust
KW - Laser-induced fluorescence
KW - Lidar
KW - Mineral dust
KW - Volume depolarization ratio
UR - http://www.scopus.com/inward/record.url?scp=85090695054&partnerID=8YFLogxK
U2 - 10.1016/j.optcom.2020.126417
DO - 10.1016/j.optcom.2020.126417
M3 - Article
AN - SCOPUS:85090695054
SN - 0030-4018
VL - 479
JO - Optics Communications
JF - Optics Communications
M1 - 126417
ER -