Analysis and Prediction Research on the Pollution Characteristics of Atmospheric Particulate Matter in Aral City based on SARIMA Model
In order to understand the pollution status of atmospheric particulate matter PM10 and PM2.5 in recent years in Alar City,and adjust the air pollution control strategies,this work collected the monitoring data of atmospheric particulate matter PM10 and PM2.5 in Alar City from 2017 to 2023,and constructed a seasonal autoregressive integrated moving average(SARI-MA)model to systematically analyzes the variation characteristics of the concentration of atmospheric particulate matter PM10 and PM2.5 in Alar City,and predict their future trends.The results show that the mass concentrations of atmospheric particu-late matter PM10 and PM2.5 in Alar City are relatively high and exhibit significant seasonal variations.The optimized models for atmospheric particulate matter PM10 and PM2.5,automatically selected by the SPSSAU software,are SARIMA(0,0,0)(2,0,0)12 and SARIMA(1,0,0)(3,0,0)12,respectively.By applying the optimized models to fit and compare the monthly avera-ges of atmospheric particulate matter PM10 and PM2.5 in Alar City in 2023,it was found that the overall relative error is within 15%,to some extent reflecting the good fitting effect of the model.The application of the optimized models to predict the mass concentrations of atmospheric particulate matter PM10 and PM2.5 in Alar City in 2024 revealed a good agreement between the predicted values and the measured values from January to June 2024,further demonstrating the accuracy of the model.The a-bove research results indicate that SARIMA(0,0,0)(2,0,0)12 and SARIMA(1,0,0)(3,0,0)12 can be used to predict the pollution status of atmospheric particulate matter in Alar City,providing technical reference for environmental regulation strate-gies for atmospheric particulate matter pollution in Alar City.
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