Temporal Modeling and Analysis to the Variations and Trending of Haze in China

Abstract

Abstract The country's rapid industrialization and urbanization have aggravated air pollution. Especially in recent years, the haze problem in China has attracted increasing attention from government officials, industry leaders, academic researchers and the public. To this end, five typical Chinese cities were picked to analyze and reveal the haze evolution so that providing prior knowledge for multiple regions of China. Time series data of Particulate Matter 2.5, i.e., PM2.5, which is deemed as the major contributor to haze formation, are investigated for haze trending and variation analyses. Additionally, the main variables which are closely related to the concentration of PM2.5, including both meteorological and chemical factors, are identified. The daily and monthly averages of PM2.5 concentrations are evaluated and analyzed in terms of time series analysis methods, including the seasonal decomposition and Auto-regression Integrated Moving Average (ARIMA) methods. More importantly, qualitative analysis about the influence of Chinese policies on atmospheric environment and air pollution control are discussed.