Using the Quarterly Compound Fractional Grey Model to Predict the Air Quality in 22 Cities of China

Abstract

The rapid development of industrialization leads to more and more serious air pollution, which affects human health and sustainable development of society. Predicting air quality is an important link in preventing air pollution and improving the atmospheric environment. In this paper, 22 cities of China with poor air quality in recent years are selected as the research objects. A quarterly compound accumulation grey model is used to predict the concentrations of PM2.5, PM10, SO2, and NO2 in the 22 cities. Two parameters are introduced into the model to optimize the accumulation method of the grey model. Also, seasonal factors are introduced to better simulate air quality. The forecasting results show that air quality in these cities, although varies widely on a quarterly basis, tends to decline overall. The concentrations of PM2.5 and PM10 in most cities will still exceed the standard in the next few years, especially in the first and fourth quarters of each year. The prediction results can provide reference for relevant departments.