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Abstract

Particulate matter (PM2.5 and PM10) and ozone (O3) are the two major air pollutants in China in recent years. The fluctuations of PM2.5, PM10 and O3 strongly depend on the weather processes and anthropogenic emission. These processes may lead to the existence of short- and long-term memory behaviors in air pollutants. Hence, here we use the autoregressive parameter a of the first-order autoregressive process [AR (1)] to characterize the short-term memory effects of pollutants. We estimate the scaling exponent α using detrended fluctuation analysis (DFA) for the long-term memory effects of air pollutants (PM2.5, PM10, and O3) in summer and winter for different cities in China. Our results show that PM2.5, PM10, and O3 have strong short-term and long-term memory characteristics both in summer and winter. Furthermore, both the short- and long-term memory effects are stronger in winter than summer for most cities associated with stronger and longer persistent weather systems in winter. In general, the scaling exponent α of PM2.5 and PM10 are smaller for northern cities than those of southern cities in China. The long-term memory patterns of O3 are stronger in northern cities and weaker in southern cities in relative to those of PM2.5 and PM10 in winter. Our results show that the short- and long-term memory behaviors of air pollutions are dominated by the weather systems with different time scales.