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Spatial and Temporal Variations of PM 2.5 and Its Relation to Meteorological Factors in the Urban Area of Nanjing, China

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  • Tao Chen

    (Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China)

  • Jun He

    (Nanjing Information Center, Nanjing 210019, China)

  • Xiaowei Lu

    (School of the Environment, Nanjing University, Nanjing 210023, China)

  • Jiangfeng She

    (Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China)

  • Zhongqing Guan

    (Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China)

Abstract

The serious air pollution problem has aroused widespread public concerns in China. Nanjing city, as one of the famous cities of China, is faced with the same situation. This research aims to investigate spatial and temporal distribution characteristics of fine particulate matter (PM 2.5 ) and the influence of weather factors on PM 2.5 in Nanjing using Spearman-Rank analysis and the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) method. Hourly PM 2.5 observation data and daily meteorological data were collected from 1 April 2013 to 31 December 2015. The spatial distribution result shows that the Maigaoqiao site suffered the most serious pollution. Daily PM 2.5 concentrations in Nanjing varied from 7.3 μg/m 3 to 336.4 μg/m 3 . The highest concentration was found in winter and the lowest in summer. The diurnal variation of PM 2.5 increased greatly from 6 to 10 a.m. and after 6 p.m., while the concentration exhibited few variations in summer. In addition, the concentration was slightly higher on weekends compared to weekdays. PM 2.5 was found to exhibit a reversed relation with wind speed, relative humidity, and precipitation. Although temperature had a positive association with PM 2.5 in most months, a negative correlation was observed during the whole period. Additionally, a high concentration was mainly brought with the wind with a southwest direction and several relevant factors are discussed to explain the difference of the impacts of diverse wind directions.

Suggested Citation

  • Tao Chen & Jun He & Xiaowei Lu & Jiangfeng She & Zhongqing Guan, 2016. "Spatial and Temporal Variations of PM 2.5 and Its Relation to Meteorological Factors in the Urban Area of Nanjing, China," IJERPH, MDPI, vol. 13(9), pages 1-16, September.
    • Handle: RePEc:gam:jijerp:v:13:y:2016:i:9:p:921-:d:78290
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    1. Ru-Jin Huang & Yanlin Zhang & Carlo Bozzetti & Kin-Fai Ho & Jun-Ji Cao & Yongming Han & Kaspar R. Daellenbach & Jay G. Slowik & Stephen M. Platt & Francesco Canonaco & Peter Zotter & Robert Wolf & Sim, 2014. "High secondary aerosol contribution to particulate pollution during haze events in China," Nature, Nature, vol. 514(7521), pages 218-222, October.
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    Cited by:

    1. Mengjie Wang & Yanjun Wang & Fei Teng & Shaochun Li & Yunhao Lin & Hengfan Cai, 2022. "Estimation and Analysis of PM 2.5 Concentrations with NPP-VIIRS Nighttime Light Images: A Case Study in the Chang-Zhu-Tan Urban Agglomeration of China," IJERPH, MDPI, vol. 19(7), pages 1-18, April.
    2. Chengming Li & Zhaoxin Dai & Lina Yang & Zhaoting Ma, 2019. "Spatiotemporal Characteristics of Air Quality across Weifang from 2014–2018," IJERPH, MDPI, vol. 16(17), pages 1-15, August.
    3. Huilin Yang & Rui Yao & Peng Sun & Chenhao Ge & Zice Ma & Yaojin Bian & Ruilin Liu, 2023. "Spatiotemporal Evolution and Driving Forces of PM 2.5 in Urban Agglomerations in China," IJERPH, MDPI, vol. 20(3), pages 1-15, January.
    4. Tianjun Lu & Yisi Liu & Armando Garcia & Meng Wang & Yang Li & German Bravo-villasenor & Kimberly Campos & Jia Xu & Bin Han, 2022. "Leveraging Citizen Science and Low-Cost Sensors to Characterize Air Pollution Exposure of Disadvantaged Communities in Southern California," IJERPH, MDPI, vol. 19(14), pages 1-16, July.
    5. Wei Xue & Qingming Zhan & Qi Zhang & Zhonghua Wu, 2019. "Spatiotemporal Variations of Particulate and Gaseous Pollutants and Their Relations to Meteorological Parameters: The Case of Xiangyang, China," IJERPH, MDPI, vol. 17(1), pages 1-23, December.
    6. Lilin Xiong & Jie Li & Ting Xia & Xinyue Hu & Yan Wang & Maonan Sun & Meng Tang, 2018. "Risk Reduction Behaviors Regarding PM 2.5 Exposure among Outdoor Exercisers in the Nanjing Metropolitan Area, China," IJERPH, MDPI, vol. 15(8), pages 1-13, August.
    7. Haiou Yang & Wenbo Chen & Zhaofeng Liang, 2017. "Impact of Land Use on PM 2.5 Pollution in a Representative City of Middle China," IJERPH, MDPI, vol. 14(5), pages 1-14, April.

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