The application of Raman spectroscopy combined with multivariable analysis on source apportionment of atmospheric black carbon aerosols

Yiqing Feng; Lei Liu; Yang Yang; Yue Deng; Kejian Li; Hanyun Cheng; Xu Dong; Weijun Li; Liwu Zhang

doi:10.1016/j.scitotenv.2019.05.367

The application of Raman spectroscopy combined with multivariable analysis on source apportionment of atmospheric black carbon aerosols

Sci Total Environ. 2019 Oct 1:685:189-196. doi: 10.1016/j.scitotenv.2019.05.367. Epub 2019 May 28.

Authors

Yiqing Feng¹, Lei Liu², Yang Yang³, Yue Deng³, Kejian Li³, Hanyun Cheng³, Xu Dong³, Weijun Li⁴, Liwu Zhang⁵

Affiliations

¹ Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China.
² Department of Atmospheric Sciences, School of Earth Sciences, Zhejiang University, Hangzhou 310027, PR China; Environment Research Institute, Shandong University, Qingdao 266237, PR China.
³ Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, PR China.
⁴ Department of Atmospheric Sciences, School of Earth Sciences, Zhejiang University, Hangzhou 310027, PR China.
⁵ Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, PR China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, PR China. Electronic address: zhanglw@fudan.edu.cn.

PMID: 31174116
DOI: 10.1016/j.scitotenv.2019.05.367

Abstract

Source apportionment studies become increasingly crucial for black carbon (BC) in atmospheric particulate matters given its linkage with adverse public health and climate impacts. In this work, a facile and rapid method using Raman spectra combined with stepwise discriminant analysis (SDA) was proposed to identify and quantify the contributions of atmospheric BC sources. Four BC samples from biomass burning, coal combustion, gasoline and diesel vehicle emission were characterized by Raman spectra. The SDA model was established based on 10 parameters with significant differences (p < 0.05), giving an accuracy of 83% with a cross-validation rate of 80%. Utilizing four suggested discriminant variables from SDA model, vehicle emission was predicted as the dominant contributor to ambient BC particles, among which gasoline contributed much higher than diesel at an urban road intersection in Shanghai, China. This new method shows great potential to classify and investigate the sources of atmospheric BC aerosols and provide more effective information on air pollution control measures.

Keywords: Black carbon aerosols; Raman; Source apportionment; Stepwise discriminant analysis.