Memory Behaviors of Air Pollutions and Their Spatial Patterns in China

Particulate matter (PM_2.5 and PM₁₀) and ozone (O₃) are the two major air pollutants in China in recent years. The fluctuations of PM_2.5, 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 (PM_2.5, PM₁₀, and O₃) in summer and winter for different cities in China. Our results show that PM_2.5, 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 PM_2.5 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 PM_2.5 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.