Linear Regression Model for Predicting Daily PM2.5 Using VIIRS-SNPP and MODIS-Aqua AOT

International Conference On Tropical Meteorology And Atmospheric Sciences

生态环境科学;原子能学

Cholianawati, N.^1 ; Cahyono, W.E.^1 ; Indrawati, A.^1 ; Indrajad, A.^1

Indonesia National Institute of Aeronautics and Space (LAPAN), Bandung, Indonesia^1

关键词: Aerosol optical thickness;    Aqua satellites;    Linear regression models;    MODIS;    MODIS sensors;    Particle concentrations;    SNPP;    VIIRS;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/303/1/012039/pdf
DOI  :  10.1088/1755-1315/303/1/012039

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Small-sized particulates (PM2.5) are very dangerous if inhaled by humans. The measurement of the particle concentration is carried out by the highly variable AQMS. Several studies have shown a positive relationship between aerosol optical thickness to surface PM2.5. The study aims to predict PM2.5 from Aerosol Optical Thickness using Linear Regression Model in Indonesia. The aerosol optical thickness is obtained from the VIIRS sensor on the SNPP satellite and from the MODIS sensor on the Aqua satellite. Linear regression model for predicting daily PM2.5 using AOT VIIRS SNPP is PM2.5=56.683∗AOT-3.807 with r=0.7. Linear regression model for predicting daily PM2.5 using AOT MODIS-Aqua is PM2.5=104.3∗AOT+1.0118 with r=0.7.