Study And Evaluation Of Quantitative Monitoring Of Atmospheric Particulate Matter In The Mining City Cluster From Remote Sensing Data

Mining cities are an important part of China’s urban agglomerations,and with the continuous development of mining cities,ecological and environmental pollution problems are becoming more and more prominent.In the study of urban air pollution,the pollutants that have a greater impact on air quality are atmospheric particulate matter,mainly PM_2.5 and PM₁₀,and the environmental impact of atmospheric particulate matter is particularly serious in mining cities due to their industrial characteristics,which is a key element of environmental management in such cities.The current research on atmospheric particulate matter pollution is mainly conducted in cities or regions,and there are fewer studies related to mining city clusters.In addition,since the ground monitoring network of air pollutants in China has been gradually built since 2014,the lack of ground monitoring data for air quality before2013 has caused difficulties in remote sensing estimation of atmospheric particulate matter.In this thesis,the MODIS multi-angle algorithm AOD product（MCD19A2）from NASA,relative humidity data,planetary boundary layer height data and relevant subsurface data are used as data sources for remote sensing estimation of atmospheric particulate matter mass concentrations in mining city clusters in eastern China for a long time series from 2005 to 2021,and combined with city yearbook statistics for mining city clusters for The comprehensive evaluation and analysis of the mining city clusters are carried out.The main research results are as follows:（1）Establishment of a virtual monitoring network for PM_2.5 and PM₁₀ mass concentration based on a chemical transport model with a proportionality equation.To solve the problem of missing data from ground stations before 2014,this study establishes a virtual mass concentration monitoring network based on the proportionality equation with simulated product data of AOD and PM_2.5 or PM₁₀,and applies the virtual monitoring network to the remote sensing estimation of atmospheric particulate matter pollution before June 2014.This virtual monitoring network is also used with the national environmental quality monitoring network in June 2014 and after to construct an integrated monitoring network for remote sensing estimation of atmospheric particulate matter.（2）Remote sensing estimation of PM_2.5 and PM₁₀ mass concentrations in mining city clusters for long time series.In this study,we use the established virtual monitoring network and integrated monitoring network to construct a generalized distance using latitude,longitude,time,and subsurface data,and an improved geo-temporal weighted regression model with AOD,relative humidity,and planetary boundary layer height data to perform remote sensing estimation of atmospheric particulate matter in mining city clusters in eastern China for a long time series.The estimation results show good correlation and accuracy compared with the ground-based national control site data.This validation result indicates that the algorithm has high reliability and stability.（3）Study on the spatial and temporal distribution of atmospheric particulate matter in mining city clusters over long time series.Using the estimation results in the study area,the temporal and spatial distribution patterns of atmospheric particulate matter in the mining city cluster and its surrounding areas are studied and analyzed.The air quality of the study area is analysed by comparing the spatial and temporal distribution patterns of two air pollutants,PM_2.5 and PM₁₀.（4）Comprehensive evaluation and analysis of mining city clusters.Using the PM_2.5 and PM₁₀ mass concentration data set calculated in this study,and in collaboration with the data in China’s city statistical yearbook,a comprehensive evaluation system of mining city clusters is established to analyze the air particulate pollution,air pollutant emissions and industrial structure of different types of mining cities in the study area,and to evaluate the transformation of different types of mining cities.