THERMAL SCIENCE

International Scientific Journal

Xin Zhang

,

Yuesheng Fan

,

Shuxuan Wei

,

Huan Wang

,

Jiaxin Zhang

FRACTAL APPROACH TO CONCENTRATION DISTRIBUTION OF ATMOSPHERIC FINE PARTICLE SIZES

ABSTRACT
With the increase of particulate pollution in the atmosphere, it becomes extremely significant to understand the overall distribution characteristics of particulates and their adsorption of toxic gases for the source analysis and precise controlling of atmospheric particulate matters. The fractal theory was adopted to analyze particle sizes distribution characteristics in Xi’an city, China. Results showed the fractal dimension of particulate matters distribution ranged from 4.32-4.83, with an average fractal dimension of 4.54. A higher fractal dimension predicts a higher concentration of fine particles. Additionally the effects of outdoor temperature, humidity, and wind speed on the fractal dimension were also studied experimentally
KEYWORDS
atmospheric particles, concentration, distribution, fractal theory, fractal dimension
PAPER SUBMITTED: 2020-03-01
PAPER REVISED: 2020-06-18
PAPER ACCEPTED: 2020-06-18
PUBLISHED ONLINE: 2021-01-31
DOI REFERENCE: https://doi.org/10.2298/TSCI200301031Z
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2021, VOLUME 25, ISSUE Issue 2, PAGES [1337 - 1343]
REFERENCES
  1. Filonchyk, M., et al., Emporal and Spatial Variation of Particulate Matter and Its Correlation with Other Criteria of Air Pollutants in Lanzhou, China, In Spring-Summer periods, Atmospheric Pollution Research, 9 (2018), 12, pp. 1100-1110
  2. Gholampour, A., et al., Exposure and Health Impacts of Outdoor Particulate Matter in Two Urban and Industrialized Area of Tabriz, Iran, Journal of Environmental Health Science and Engineering, 12 (2014), 1, 27
  3. Fan, X. Y., et al., More Obvious Air Pollution Impacts on Variations in Bacteria Than Fungi and Their co-Occurrences with Ammonia-Oxidizing Microorganisms in PM2.5, Environmental Pollution, 251 (2019), Aug., pp. 668-680
  4. Cakmak, S., et al., Metal Composition of Fine Particulate Air Pollution and Acute Changes in Cardiorespiratory Physiology, Environmental Pollution, 189 (2014), Mar., pp. 208-214
  5. Xu, C. W., et al., The 2019-nCoV Epidemic Control Strategies and Future Challenges of Building Healthy Smart Cities, Indoor and Built Environment, 29 (2020), 5, pp. 639-644
  6. Xu, Y., et al., Spatial and Temporal Variations in Criteria Air Pollutants in Three Typical Terrain Regions in Shaanxi, China, during 2015, Air Quality Atmosphere and Health, 11 (2018), 1, pp. 95-109
  7. Lee, G., et al., Dominance of Large-Scale Atmospheric Circulations in Long-Term Variations of Winter PM(10 ) concentrations over East Asia, Atmospheric Research, 238 (2020), 104871
  8. Zhao, B., Impact of Energy Structure Adjustment on Air Quality: A Case Study in Beijing, China, Frontiers of Environmental Science and Engineering, 5 (2011), 3, pp. 378-390
  9. Zhou, Q. L., et al., Application of Geographically Weighted Regression (GWR) in the Analysis of the Cause of Haze Pollution in China, Atmospheric Pollution Research, 10 (2019), 2, pp. 935-946
  10. Dai, C. H., et al., Particulate Pollution Status and Its Characteristics during 2015 - 2016 in Hunan, China, Atmospheric Pollution Research, 10 (2019), 3, pp. 739-748
  11. Shang, T., et al., Trapping Efficiency Model of Fibrous DPF Based on Fractal Theory (in Chinese), Journal of Jilin University (Engineering and Technology Edition), 42 (2012), 2, pp. 397-402
  12. Li, W. F., et al., Characteristics of Major PM2.5 Components during Winter in Tianjin, China, Aerosol and Air Quality Research, 9 (2009), 1, pp. 105-119
  13. Lai, S. C., et al., Characterization of PM2.5 and the Major Chemical Components During a 1-Year Campaign in Rural Guangzhou, Southern China, Atmospheric Research, 167 (2016), Jan., pp. 208-215
  14. Wu, L. F., Xu, Z. C., Analyzing the Air Quality of Beijing, Tianjin, and Shijiazhuang Using Grey Verhulst Model, Air Quality, Atmosphere & Health, 12 (2019), 12, pp. 1419-1426
  15. Wang, J., et al., Contamination Characteristics and Possible Sources of PM10 and PM2.5 in Different Functional Areas of Shanghai, China, Atmospheric Environment, 68 (2013), Apr., pp. 221-229
  16. Deng, S. Y., et al. Global Well-Posedness of a Class of Dissipative Thermoelastic Fluids Based on Fractal Theory and Thermal Science Analysis, Thermal Science, 23 (2019), 4, pp. 2461-2469
  17. He, J. H., Ain, Q. T., New Promises and Future Challenges of Fractal Calculus: From Two-Scale ThermoDynamics to Fractal Variational Principle, Thermal Science, 24 (2020), 2, pp. 659-681
  18. Yang, S.S., et al. Fractal Dimensions of Size Distribution of PM10 in Shanghai (in Chinese), China Environmental Science, 27 (2007), 5, pp. 594-598.
  19. Zhang, H. L., Experimental Study of Filters of Different Grades on Outdoor Airborne Particulate Matter (in Chinese), M. Sc. thesis, Xi'an University of Architecture and Technology, Xi'an China, 2018
  20. Babayemi, J. O., Overview of Environmental Hazards and Health Effects of Pollution in Developing Countries: a Case Study of Nigeria, Environment Quality Management, 26 (2016), 1, pp. 51-71
  21. Shao, L. Y., et al., Fractal Dimensions of Size Distribution of Airbome Inhalable Particulates (PM10) in Beijing (in Chinese), Journal of China University of Mining and Technology, 37 (2008), 3, pp. 407-411.
  22. Xie, Y. X., et al., Fractal Characteristic of Atmospheric Particulate Matters, Word Sci-Tech R&D, 26 (2004), 6, pp. 24-28
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Fractal approach to concentration distribution of atmospheric fine particle sizes

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence