Research On Atmospheric Pollution Retrieval Of Road Network Based On Remote Sensing Technology

As China’s economy develops and technology improves,the transport infrastructure continues to improve and the road network expands rapidly,the air pollution caused by its fossil fuel combustion and vehicle emissions has become a more serious problem nowadays.Remote sensing,as a scientific,rapid and wide-scale monitoring tool,is widely used in the study of atmospheric pollution.Based on this background,this thesis carries out a research on the retrieval of air pollution gases in road networks with remote sensing technology,in which the Aerosol Optical Depth（AOD）and Nitrogen Dioxide（NO₂）are retrieved separately,and the spatial and temporal characteristics of pollution gases are studied in typical road network areas with the retrieval result.The main research work is as follows.（1）Study of AOD retrieval from high-resolution satellite data sources.Based on MODIS satellite products,Landsat-8 satellite products are used as the data source for AOD retrieval.The determination coefficient R² reaches 0.84 as verified by ground monitoring data,which indicates that the retrieval results have good spatial distribution characteristics and can be used to carry out air pollution research on road networks.（2）Spatial and temporal characteristics of the road network based on the AOD retrieval algorithm.The long time series AOD analysis of the road network is carried out by the MCD19A2 product.For the extended dark target algorithm,the surface reflectance interferes with the real value of road AOD,this thesis uses the"clean pixel"as the benchmark to calculate the"polluted pixel"to eliminate its influence.The experiment concluded that the development of the road network leads to an increase in the average value of regional AOD,and the road traffic volume is positively correlated with the road AOD value.（3）Research and improvement of Differential Optical Absorption Spectroscopy（DOAS）algorithm.Contents include:mapping of the modified gas molecular absorption cross section and optimising the fitting window according to the absorption peak characteristics;improving the processing of the Ring effect by the DOAS algorithm:in this thesis Ring effect is treated as a pseudo-absorption cross section and calculated;DOAS fitting methods,polynomial order optimization and other related configuration improvements.By comparing with TROPOMI level-2 data,the determination coefficient R² is highly correlated in the region of high and low NO₂ column density at 0.84,0.91,respectively.while the retrieval results of this thesis have an upward lift of 24%compared with the official product,which can be considered that the improved algorithm of this thesis has improved the official underestimation trend to a certain extent.（4）Research and traceability of NO₂ spatial and temporal characteristics of road networks based on the improved DOAS algorithm in this thesis.Through the characterization of NO₂ changes under the Covid-19 epidemic and NO₂ traceability analysis.the research find that the NO₂ column density in the road network decreased significantly under the impact of the epidemic,including a decrease of more than 200%at the beginning of the epidemic outbreak;in addition to vehicle exhaust emissions,industrial exhaust emissions and urban air pollution emission dispersion also have an impact on the NO₂ column density in the road network,and this impact is more pronounced when the traffic flow is low.Lastly,the retrieval of NO₂ under the airborne platform is carried out by the Small Whiskbroom Imager for trace gases monitori NG（SWING）,and the retrieval result of 30 m×30 m resolution is significantly improved compared with the satellite resolution of 5.5 km×3.5 km,which provides a strong data support for further refinement of NO₂ spatial and temporal characteristics.