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An analysis of multifractal characteristics of API time series in Nanjing, China

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  • Shen, Chen-hua
  • Huang, Yi
  • Yan, Ya-ni

Abstract

This paper describes multifractal characteristics of daily air pollution index (API) records in Nanjing from 2001 to 2012. The entire daily API time series is first divided into 12 parts that serve as research objects, and the generalized Hurst exponent is calculated for each series. And then, the multifractal sources are analyzed and singularity spectra are shown. Next, based on a singularity spectrum, the multifractal-characteristics parameters (maximum exponent α0, spectrum width Δα, and asymmetry Δαas) are introduced. The results show that the fractality of daily API for each year is multifractal. The multifractal sources originate from both a broad probability density function and different long-range correlations with small and large fluctuations. The strength of the distribution multifractality is stronger than that of the correlation multifractality. The variation in the structure of API time series with increasing years is mainly related to long-range correlations. The structure of API time series in some years is richer. These findings can provide a scientific basis for further probing into the complexity of API.

Suggested Citation

  • Shen, Chen-hua & Huang, Yi & Yan, Ya-ni, 2016. "An analysis of multifractal characteristics of API time series in Nanjing, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 171-179.
    • Handle: RePEc:eee:phsmap:v:451:y:2016:i:c:p:171-179
    DOI: 10.1016/j.physa.2016.01.061
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    1. Ludescher, Josef & Bogachev, Mikhail I. & Kantelhardt, Jan W. & Schumann, Aicko Y. & Bunde, Armin, 2011. "On spurious and corrupted multifractality: The effects of additive noise, short-term memory and periodic trends," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(13), pages 2480-2490.
    2. Ramón E. López & Vinod Thomas & Yan Wang, 2008. "The Quality of Growth," World Bank Publications - Books, The World Bank Group, number 28198.
    3. Schumann, Aicko Y. & Kantelhardt, Jan W., 2011. "Multifractal moving average analysis and test of multifractal model with tuned correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(14), pages 2637-2654.
    4. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    5. Shen, Chen-hua & Li, Chao-ling & Si, Ya-li, 2015. "A detrended cross-correlation analysis of meteorological and API data in Nanjing, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 417-428.
    6. Hajian, S. & Movahed, M. Sadegh, 2010. "Multifractal Detrended Cross-Correlation Analysis of sunspot numbers and river flow fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4942-4957.
    7. Zebende, G.F. & Filho, A. Machado, 2009. "Cross-correlation between time series of vehicles and passengers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(23), pages 4863-4866.
    8. Chianca, C.V. & Ticona, A. & Penna, T.J.P., 2005. "Fourier-detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 357(3), pages 447-454.
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    Cited by:

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    5. Linan Sun & Antao Wang & Jiayao Wang, 2022. "Spatial Characteristics Analysis for Coupling Strength among Air Pollutants during a Severe Haze Period in Zhengzhou, China," IJERPH, MDPI, vol. 19(14), pages 1-19, July.
    6. Zhang, Jiao & Li, Youping & Liu, Chunqiong & Wu, Bo & Shi, Kai, 2022. "A study of cross-correlations between PM2.5 and O3 based on Copula and Multifractal methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    7. Yue-Hua Dai & Wei-Xing Zhou, 2017. "Temporal and spatial correlation patterns of air pollutants in Chinese cities," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-24, August.
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    10. Shen, Chenhua, 2019. "The influence of a scaling exponent on ρDCCA: A spatial cross-correlation pattern of precipitation records over eastern China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 579-590.

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