Kai Shi 1,2, Chunqiong Liu2, Yi Huang3

  • 1 Key Laboratory of Ecotourism in Hunan Province, Jishou University, Jishou, Hunan 416000, China
  • 2 College of Biology & Environmental Sciences, Jishou University, Jishou, Hunan 416000, China
  • 3 College of Mathematics & Statistics, Jishou University, Jishou Hunan 416000, China

Received: May 23, 2014
Revised: July 12, 2014
Accepted: October 16, 2014
Download Citation: ||https://doi.org/10.4209/aaqr.2014.05.0091 

  • Download: PDF


Cite this article:
Shi, K., Liu, C. and Huang, Y. (2015). Multifractal Processes and Self-Organized Criticality of PM2.5 during a Typical Haze Period in Chengdu, China. Aerosol Air Qual. Res. 15: 926-934. https://doi.org/10.4209/aaqr.2014.05.0091


HIGHLIGHTS

  • The evolution of PM2.5 concentrations in haze period exhibits multifractal nature.
  • The major source of multifractality is long-range correlation.
  • A novel PM2.5 evolution model was developed based on the critical phenomena.
  • The new model can give a good prediction of the statistical features of PM2.5.
  • The evolutional rule of PM2.5 is a self-organized critical state transition process.

 

ABSTRACT


Scaling and multifractal properties of the hourly PM2.5 average concentration series at the four air monitoring stations of Chengdu (southwestern China) were explored by using a multifractal detrended fluctuation analysis method, during a typical haze episode (from 1 March to 17 March, 2013). Using shuffling procedure and phase randomization procedure, the major sources of multifractality in these PM2.5 series are studied. The results show that the multifractality nature of PM2.5 series is mainly due to long-range correlation. At the same time, the non-Gaussian probability distributions also partly contribute to the multifractal behaviour. The scale-free power laws behaviours are found to govern the cumulative distributions statistics for PM2.5 concentration fluctuations. The temporal evolutions of the multifractality were investigated by the approach of a sliding window. Further, we attempt to find the answers to the following questions: how does long-range correlation and power-law distribution in PM2.5 evolution emerge? It is inviting to do it in a self-organized criticality (SOC) framework, which was specially designed to model the dynamics of complex systems. A novel PM2.5 evolution model is developed on the bases of SOC theory. The model displays robust power law behaviour in certain dynamical region. The self-organized criticality properties of PM2.5 evolution are discussed. This SOC behaviour is related to a statistically steady state that implies the presence of long-range correlation and power-law distribution in PM2.5 evolution during the haze period. It is the stability of SOC that causes the haze period to be sustained for a long time in Chengdu.


Keywords: PM2.5; Multifractal; Long-range correlation; Power-law distribution; Self-organized criticality


Impact Factor: 2.735

5-Year Impact Factor: 2.827


SCImago Journal & Country Rank

Enter your email below to receive latest published articles in your field.