PM2.5 Source Identification By Using Terahertz Time-domain Spectroscopy

In the past decades,city air pollution has become a global problem due to industrial expansion and traffic emissions.PM2.5(particulate matter with aerodynamic diameter less than 2.5 μm)is a major contributor to air pollution.Monitoring the concentration and identifying the sources of PM2.5 is an important guarantee for controlling pollution.It is important to develop monitoring instruments that can monitor PM2.5 concentrations and identify its sources.In this thesis,we verify qualitatively identifying PM2.5 samples collected in different environment including ordinary atmospheric environment,lampblack environment and the environment with an air conditioning exhaust fan by using the terahertz time-domain spectroscopy(THz-TDS).The results show that these linear relationships are different.The PCA results indicate that combining THz-TDS with statistical methods can identifying air pollutants in different environment.Principal component analysis was used to analyze the terahertz absorption spectra of the two different samples collected before and after the intensity limiting.It was found that terahertz technology combined with principal component analysis can distinguish PM2.5 samples from different sources.The SEM-EDS,ICP-MS and other methods were used to characterize the samples in different environments.It was found that the composition and content of PM2.5collected in different environment were different.According to the above content,we tentatively conclude that combining THz-TDS with statistical methods can serve as a contactless and efficient approach to identifying air pollutants in different environment.