Correlation Analysis between Meteorological Factors and Pollutants Based on Copula Theory

Abstract

In recent years, the continuous acceleration of industrial and agricultural production has aggravated the deterioration of the environment and seriously affected people’s health. Gas pollutant index has become an important indicator to measure air quality. Taking a region of China as the study subject, this paper firstly uses the monitoring data of air pollutants in 5 years and meteorological data (rainfall, temperature and wind speed) of meteorological observation stations in the same period. Then, the autocorrelation function is selected to analyze the autocorrelation of pollutants, and on this basis, the significant correlation level between meteorological factors and pollutants is analyzed by Copula theory. The results show that the ACF values of pollutants are all higher than 0.6, which means that the autocorrelation of pollutants within 2 hours is relatively significant. PM2.5 has a significant negative correlation with wind speed in four seasons, but a low correlation with rainfall. SO2 is negatively correlated with most of the three meteorological factors. In addition, the study also finds that there are significant differences in the impact of meteorological factors on pollutants at different time scales. This paper proposes a correlation analysis method between meteorological factors and pollutants, which provides corresponding support and guarantee for China’s economic and environmental protection policies.