Narrow Results

It seems evident that the understanding of the complex temporal evolution dynamic characteristics of air pollution indexes (APIs) can contribute to developing advanced techniques for air pollution forecasting. In this work, monofractal and multifractal methods have been successfully used to characterize the temporal fluctuations of APIs in Shanghai. It shows that APIs in Shanghai are characterized by scale invariance, long range dependence and multifractal scaling. Introducing a kind of variable window sizes method, we analyze the temporal evolution of the monofractal and multifractal behaviors of APIs. Some information about the temporal evolution dynamics of APIs is revealed. Our study suggests that the variable window sizes method can be help the analysis of air pollution time series temporal evolution dynamical mechanisms. This work could play an important role in the research of air pollution.

Based on daily visibility data obtained from 1980–2002 and air pollution index data from 2001–2004 in Xi'an, long-term variations and relationships for daily horizontal extinction coefficient and mass concentration of PM₁₀ have been evaluated. A decreasing trend was found in horizontal extinction coefficient during the past 23 years, with higher values observed in 1980s relative to 1990s, and the highest and lowest values in winter and summer, respectively. Significant correlation and similar seasonal variations existed between horizontal extinction coefficient and PM₁₀ concentration, suggesting the high influence of PM₁₀ to the visibility drop at a site in the Guanzhong Plain of central China during the past two decades.