| The process of urbanization and industrialization makes the pollution caused by aerosols often occur.With people’s growing awareness of environmental protection,great importance has been attached to the treatment of aerosol pollution,so as the detection of aerosol pollutants.Aerosols detection has high requirements for timeliness and accuracy.Traditional offline detection techniques such as gas chromatography-mass spectrometry and ion chromatography are complex and time-consuming,which failed to achieve real-time detection.In this study,liquid aerosols from typical online sources are identified based on Laser-induced breakdown spectroscopy(LIBS)technique.The necessary information of the organic matter molecular spectrum and particulate was obtained via laser Raman spectroscopy technique and single particle aerosol mass spectrometry(SPAMS)technique.What is more,the traditional spectral analysis method is combined with machine learning to establish an algorithm model to realize the quantitative analysis or traceability of liquid aerosol.The specific research contents are as follows:(1)To realize Water vapor content and soluble ions detection of aerosols,LIBS technology is used to identify for atmospheric water vapor from natural sources.By collecting the spectrum of air at different humidity,the quantitative relationship between relative humidity and spectral intensity of H atoms and O atoms is studied and a humidity regression model based on the principal component regression algorithm is set up.Then,the wet air spectra from different water vapor sources are collected and analysis based on the principal component analysis algorithm is conducted.Moreover,sodium ions and magnesium ions in water vapor are taken as samples,the standard calibration curve and detection limit are determined using the internal standard method.(2)Using the pesticide aerosol as an example,liquid aerosols,which have organic matters as their primary component,are recognized by LIBS.Molecular spectral information is obtained assisted by using laser Raman spectroscopy.In order to better analyze the LIBS spectra of pesticides,the pesticide aerosol samples and the powder tablet samples of deltamethrin,the main component of pesticides,were tested online in the atmospheric environment.Meanwhile,laser Raman spectroscopy was adopted to detect pesticide droplets,and the spectral fingerprint of the molecular spectra was obtained to support LIBS detection.(3)Taking the aerosol of cigarettes as examples,LIBS and SPAMS were used to detect the mainstream smoke aerosol of cigarettes and e-cigarettes,and the elemental composition information and particulate matter information are obtained.In addition,the spectral of exhaled smoke from smokers was tested in air,and the spectral change of the smoking process was determined by analyzing the intensity of line C(C I 246.7 nm).Finally,a machine learning model based on some spectral features of the source of aerosol was established to realize the source identification of aerosol with complex composition.In this paper,typical atmospheric liquid aerosols are detected online based on LIBS,and traditional analytical methods are combined with machine learning for rapid and accurate analysis of spectral data.The above research work provides technical support and new ideas for the online detection of liquid aerosol,which is of great value to the source analysis of atmospheric pollutants. |
