Analysis and Prediction of Atmospheric Environmental Quality Based on the Autoregressive Integrated Moving Average Model (ARIMA Model) in Hunan Province, China

Abstract

Based on the panel data of atmospheric environmental pollution in Hunan Province from 2016 to 2023, the autoregressive integrated moving average model (ARIMA) is introduced to evaluate and predict the current status of atmospheric environmental quality in Hunan Province of China, and the constructed ARIMA model has an excellent prediction effect on the atmospheric environmental quality in Hunan Province. The following conclusions are obtained through the prediction and analysis based on the ARIMA model: (1) the atmospheric environmental quality in Hunan Province shows a year-on-year improvement trend; (2) the ARIMA model prediction method is reliable and effective and can accurately analyze and predict the concentrations of air pollutants (PM2.5, PM10, SO2, and CO) and atmospheric environmental quality, and the prediction results show that the outdoor air quality of Hunan Province will improve gradually each year from 2024 to 2028; (3) this study contributes a better understanding of the ambient air quality in Hunan Province during 2016–2023 and provides good forecasting results for air pollutants during the period of 2024–2028.