A time–scaling property of air pollution indices: a case study of Shanghai, China

This study used detrended fluctuation analysis (DFA) and multifractal method to characterize the temporal fluctuations of the three pollution indices (SO2, NO2 and PM10) and the daily air pollution indices (APIs) of Shanghai in China. The results show that the temporal scaling behaviors in all the four series exhibit two different power laws. In shorter temporal scaling, all the series indicate the similar persistence corresponding to the annual cycle. However, in longer temporal scaling, the trends are different for the four series, which reflect the different inherent dynamic nature of various pollutant series. Furthermore, we investigated the frequency–size distribution of the four series. Our findings suggest that SO2, NO2 and PM10 pollution is an example of a self–organized criticality (SOC) process. The results represent that it is different SOC behaviors that result in the differences of power–law relations in these four series. This work can be helpful to understand the complex dynamic characteristics of APIs that can contribute to developing advanced techniques for air pollution forecasting.