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Characteristics of Fine Particles in an Urban Atmosphere—Relationships with Meteorological Parameters and Trace Gases

Author

Listed:
  • Tianhao Zhang

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China)

  • Zhongmin Zhu

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
    College Information Science and Engineering, Wuchang Shouyi University, Wuhan 430064, China)

  • Wei Gong

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
    Collaborative Innovation Center for Geospatial Technology, Wuhan 430079, China)

  • Hao Xiang

    (School of Public Health, Wuhan University, Wuhan 430071, China)

  • Ruimin Fang

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China)

Abstract

Atmospheric fine particles (diameter < 1 μm) attract a growing global health concern and have increased in urban areas that have a strong link to nucleation, traffic emissions, and industrial emissions. To reveal the characteristics of fine particles in an industrial city of a developing country, two-year measurements of particle number size distribution (15.1 nm–661 nm), meteorological parameters, and trace gases were made in the city of Wuhan located in central China from June 2012 to May 2014. The annual average particle number concentrations in the nucleation mode (15.1 nm–30 nm), Aitken mode (30 nm–100 nm), and accumulation mode (100 nm–661 nm) reached 4923 cm −3 , 12193 cm −3 and 4801 cm −3 , respectively. Based on Pearson coefficients between particle number concentrations and meteorological parameters, precipitation and temperature both had significantly negative relationships with particle number concentrations, whereas atmospheric pressure was positively correlated with the particle number concentrations. The diurnal variation of number concentration in nucleation mode particles correlated closely with photochemical processes in all four seasons. At the same time, distinct growth of particles from nucleation mode to Aitken mode was only found in spring, summer, and autumn. The two peaks of Aitken mode and accumulation mode particles in morning and evening corresponded obviously to traffic exhaust emissions peaks. A phenomenon of “repeated, short-lived” nucleation events have been created to explain the durability of high particle concentrations, which was instigated by exogenous pollutants, during winter in a case analysis of Wuhan. Measurements of hourly trace gases and segmental meteorological factors were applied as proxies for complex chemical reactions and dense industrial activities. The results of this study offer reasonable estimations of particle impacts and provide references for emissions control strategies in industrial cities of developing countries.

Suggested Citation

  • Tianhao Zhang & Zhongmin Zhu & Wei Gong & Hao Xiang & Ruimin Fang, 2016. "Characteristics of Fine Particles in an Urban Atmosphere—Relationships with Meteorological Parameters and Trace Gases," IJERPH, MDPI, vol. 13(8), pages 1-16, August.
  • Handle: RePEc:gam:jijerp:v:13:y:2016:i:8:p:807-:d:75705
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    References listed on IDEAS

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    2. Dorina Gabriela Karottki & Michal Spilak & Marie Frederiksen & Zorana Jovanovic Andersen & Anne Mette Madsen & Matthias Ketzel & Andreas Massling & Lars Gunnarsen & Peter Møller & Steffen Loft, 2015. "Indoor and Outdoor Exposure to Ultrafine, Fine and Microbiologically Derived Particulate Matter Related to Cardiovascular and Respiratory Effects in a Panel of Elderly Urban Citizens," IJERPH, MDPI, vol. 12(2), pages 1-20, February.
    3. Kim, Jaehoon & Kim, Sangsin, 2015. "2012년 국회법 개정의 효과 연구 [A Study on the Effect of the 2012 National Assembly Act Amendment]," KDI Research Monographs, Korea Development Institute (KDI), volume 127, number v:2015-03(k):y:2015:p:1-1.
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    Cited by:

    1. Tianhao Zhang & Gang Liu & Zhongmin Zhu & Wei Gong & Yuxi Ji & Yusi Huang, 2016. "Real-Time Estimation of Satellite-Derived PM 2.5 Based on a Semi-Physical Geographically Weighted Regression Model," IJERPH, MDPI, vol. 13(10), pages 1-13, September.
    2. Tianhao Zhang & Wei Gong & Wei Wang & Yuxi Ji & Zhongmin Zhu & Yusi Huang, 2016. "Ground Level PM 2.5 Estimates over China Using Satellite-Based Geographically Weighted Regression (GWR) Models Are Improved by Including NO 2 and Enhanced Vegetation Index (EVI)," IJERPH, MDPI, vol. 13(12), pages 1-12, December.

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