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Asymmetric multifractal detrending moving average analysis in time series of PM2.5 concentration

Author

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  • Zhang, Chen
  • Ni, Zhiwei
  • Ni, Liping
  • Li, Jingming
  • Zhou, Longfei

Abstract

In this paper, we propose the asymmetric multifractal detrending moving average analysis (A-MFDMA) method to explore the asymmetric correlation in non-stationary time series. The proposed method is applied to explore the asymmetric correlation of PM2.5 daily average concentration with uptrends or downtrends in China. In addition, shuffling and phase randomization procedures are applied to detect the sources of multifractality. The results show that existences of asymmetric correlations, and the asymmetric correlations are multifractal. Further, the multifractal scaling behavior in the Chinese PM2.5 is caused not only by long-range correlation but also by fat-tailed distribution, but the major source of multifractality is fat-tailed distribution.

Suggested Citation

  • Zhang, Chen & Ni, Zhiwei & Ni, Liping & Li, Jingming & Zhou, Longfei, 2016. "Asymmetric multifractal detrending moving average analysis in time series of PM2.5 concentration," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 322-330.
    • Handle: RePEc:eee:phsmap:v:457:y:2016:i:c:p:322-330
    DOI: 10.1016/j.physa.2016.03.072
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    6. Milena Kojić & Petar Mitić & Marko Dimovski & Jelena Minović, 2021. "Multivariate Multifractal Detrending Moving Average Analysis of Air Pollutants," Mathematics, MDPI, vol. 9(7), pages 1-17, March.

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