Air pollution has a significant impact on the use of solar energy. On the one hand, the polluted environment directly reduces the intensity of solar radiation, on the other hand, pollution of the environment will also reduce the life of the equipment. Therefore, mastering the dynamic characteristics of the atmospheric environment has certain guiding significance for the efficient utilization of solar energy. In this study, the concentrations of particulate matter, CO, SO2 and NO2 from Tianyun big data website are analyzed to obtain the general characteristics of particulate pollution in Wuhan. At the same time, a long-period sampling atmospheric particulate matter sampler in the Huangjiahu area of Wuhan has been used, and experimental analysis of the physical and chemical characteristics of the samples has been obtained. The results show that both PM2.5 and PM10 show obvious seasonal changes, and the concentration of the four anions during the sampling period is SO42− > NO3− > Cl− > F−. During the sampling period, atmospheric particulate matter is mainly composed of organic matter, inorganic anions and oxides of more than 20 elements. The results of the enrichment factor analysis show that elements such as Br, Pb, Sb and Zn are the main enriched elements during the sampling period. The enrichment factors of these elements are 246.43 ± 168.81, 133.28 ± 115.03, 403.305 ± 396.18 and 90.67 ± 67.01, respectively. The high enrichment of these elements also reflects the contribution of motor vehicle exhaust emission during the sampling period. Traffic source is the main emission source in the Huangjiahu area of Wuhan. This research has a certain guiding significance for many industries such as energy utilization, environmental monitoring, health care, transportation and so on.
A high voltage electrostatic filter for particulate matter PM2.5 capture applied in motor vehicle exhaust system
