Author:
Yuan Xuan,Song Jiawei,Zeng Nan,Guo Jun,Ma Hui
Abstract
Determining the composition, particle size distribution and concentration changes of suspended particulate matter in the atmosphere is important for evaluating the quality of air and its impact on public health. The scattering and absorption of light by suspended particulate matter can change the polarization state of light, which can be used to extract characteristic information of measured particles. Firstly, we use our previously developed multi-angle simultaneous polarization measurement device to monitor the particulate matter around Dianshan Lake, Shanghai, and obtain high-throughput, high-dimensional Stokes data for nearly 1 month. The correlation between the Stokes data measured and the reference concentrations of five suspended particulate matter (Si, K, Fe, Ca, and Zn) was analyzed using the Periodical canonical correlation analysis (PCCA) method. The study shows a strong correlation between the three Stokes vectors and the concentrations of two types of suspended particulate matter in the atmosphere. Moreover, a prediction model for the concentration change of suspended particles was proposed by combining the locally weighted linear regression (LWLR) and the auto regressive moving average (ARMA) model. The prediction results on the concentration change of K and Fe in the atmosphere verified the validity of our method. The research in this work offers the possibility of continuous analysis and prediction of atmospheric suspended particulate matter in real environments.
Subject
General Environmental Science
Cited by
1 articles.
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