Empirical analysis of air quality in Shanghai based on multiple linear regression model

Abstract

In recent years, with the rapid development of social and economic development, scientific and technological progress, human production and living standards have achieved tremendous improvement, at the same time, a large number of exhaust gases and soot emissions have become important sources of pollution, industrial energy consumption and urban construction, etc. make China's air environment pollution problem increasingly serious. The air quality in China gradually presents regional pollution, especially in the Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei regions. This paper takes Shanghai as the research object and empirically analyzes the main influencing factors of its air quality, which can provide reference not only for managing the air quality of this city, but also for the air quality management of similar cities. This paper empirically investigates the influencing factors of air quality in Shanghai based on the Shanghai air quality monitoring data, including AQI (Air Quality Index) and PM2.5, PM10, NO2, CO, SO2 and O3 pollutant concentrations, released by the Shanghai Bureau of Ecology and Environment from January 2015 to October 2021. This paper uses the knowledge of econometrics to establish a multiple linear regression model with the help of RStudio, which is continuously estimated, tested and improved on the basis of the primary model to analyze the degree of influence of pollutants on AQI, and also to analyze the main pollutants affecting air quality by testing. The statistical results show that the primary air pollutants in Shanghai are O3 and NO2. Based on the analysis results, this paper puts forward corresponding suggestions about improving the air quality and protecting the ecological environment in Shanghai.