Correlation Analysis Between The Concentration Of The Near-surface Particulates And Aerosol Optical Depth In Dalian

Rapid industrialization and urbanization in China have led to extremely severe air pollution.The increasing of mass concentration of particulate pullutants in the near-surface causes increasing negative effects on human health,visibility and economic development.Against this backdrop,take a statistical of the concentration of the near-surface particulates that are PM_2.5?PM₁₀?SO₂?NO₂?CO and O₃,from June to December in2015 and from June to December in 2016 in Dalian.Base on ENVI software platform,inverted aerosol optical depth?or AOD?in Dalian area.Research the correlation between aerosol optical depth and concentration data of near-surface particulate pollutants PM_2.5?PM₁₀?SO₂?NO₂?CO and O₃ at 10 ground monitoring stations in Dalian by regression modeling.Used AOD as an independent variable,particle pollutants PM_2.5,PM₁₀,SO₂,NO₂,CO,and O₃ as dependent variables.Selected linear,logarithmic,cubic,exponential and index five types of functions in the SPSS software to research.By comparing the goodness of fit R² of the regression model,selected the best-fit model.Explored the relevance and feasibility of using remote sensing data to inverted aerosol optical depth to monitor atmospheric pollution.The results showed:2015.8,the best fitting model for aerosol optical depth and NO₂ is a cubic model,the goodness of fit R² is 0.685;2015.10,The best fitting model for aerosol optical depth and O₃ is an index model,the goodness of fit R² is 0.367;2015.11,Aerosol optical depth has a good correlation with PM_2.5.5 and PM₁₀,the best fitting models are cubic models,the goodness of fit R² for PM_2.5.5 is 0.801,the goodness of fit R² for PM₁₀0 is 0.845;2016.8,The best fitting model for aerosol optical depth and CO is a logarithmic model,the goodness of fit R² is 0.810;2016.10,The best fitting model for aerosol optical depth and SO₂ is an index model,the goodness of fit R² is 0.482.