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Spatiotemporal Changes in PM 2.5 and Their Relationships with Land-Use and People in Hangzhou

Author

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  • Li Tian

    (Qianyanzhou Ecological Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Wei Hou

    (China Institute of Surveying and Mapping Science, Beijing 100830, China)

  • Jiquan Chen

    (Department of Geography, Environment and Spatial Sciences and Center for Global Change and Earth Observations, Michigan State University, East Lansing, MI 48824, USA)

  • Chaonan Chen

    (College of Environment and Planning, Henan University, Kaifeng 475004, China)

  • Xiaojun Pan

    (The Second Surveying and Mapping Institute of Zhejiang Province, Hangzhou 310012, China)

Abstract

Increases in the extent and level of air pollution in Chinese cities have become a major concern of the public and burden on the government. While ample literature has focused on the status, changes and causes of air pollution (particularly on PM 2.5 and PM 10 ), significantly less is known on their effects on people. In this study we used Hangzhou, China, as our testbed to assess the direct impact of PM 2.5 on youth populations that are more vulnerable to pollution. We used the ground monitoring data of air quality and Aerosol optical thickness (AOT) product from the Moderate Resolution Imaging Spectroradiometer (MODIS) for the spatiotemporal changes of PM 2.5 by season in 2015. We further explored these distributions with land cover, population density and schools (kindergarten, primary school and middle school) to explore the potential impacts in seeking potential mitigation solutions. We found that the seasonal variation of PM 2.5 concentration was winter > spring > autumn > summer. In Hangzhou, the percentage of land area exposed to PM 2.5 > 50 µg m −3 accounted for 59.86% in winter, 56.62% in spring, 40.44% in autumn and 0% in summer, whereas these figures for PM 2.5 of <35 µg m −3 were 70.01%, 5.28%, 5.17%, 4.16% in summer, winter, autumn and spring, respectively. As for land cover, forest experienced PM 2.5 of 35–50 µg m −3 (i.e., lower than those of other cover types), likely due to the potential filtering and absorption function of the forests. More importantly, a quantitative index based on population-weighted exposure level ( pwel ) indicated that only 9.06% of the population lived in areas that met the national air quality standards. Only 1.66% (14,055) of infants and juveniles lived in areas with PM 2.5 of <35 µg m −3 . Considering the legacy effects of PM 2.5 over the long-term, we highly recommend improving the monitoring systems for both air quality and people (i.e., their health conditions), with special attention paid to infants and juveniles.

Suggested Citation

  • Li Tian & Wei Hou & Jiquan Chen & Chaonan Chen & Xiaojun Pan, 2018. "Spatiotemporal Changes in PM 2.5 and Their Relationships with Land-Use and People in Hangzhou," IJERPH, MDPI, vol. 15(10), pages 1-14, October.
  • Handle: RePEc:gam:jijerp:v:15:y:2018:i:10:p:2192-:d:174124
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    References listed on IDEAS

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    1. J. Lelieveld & J. S. Evans & M. Fnais & D. Giannadaki & A. Pozzer, 2015. "The contribution of outdoor air pollution sources to premature mortality on a global scale," Nature, Nature, vol. 525(7569), pages 367-371, September.
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    Cited by:

    1. Liang Zhang & Xianfan Shu & Jiaojiao Luo, 2022. "The Formation of a Polycentric City in Transitional China in a Three-Level Analysis Framework: The Case Study of Hangzhou," Land, MDPI, vol. 11(11), pages 1-17, November.
    2. Huanfeng Shen & Man Zhou & Tongwen Li & Chao Zeng, 2019. "Integration of Remote Sensing and Social Sensing Data in a Deep Learning Framework for Hourly Urban PM 2.5 Mapping," IJERPH, MDPI, vol. 16(21), pages 1-18, October.
    3. Ruiling Sun & Yi Zhou & Jie Wu & Zaiwu Gong, 2019. "Influencing Factors of PM 2.5 Pollution: Disaster Points of Meteorological Factors," IJERPH, MDPI, vol. 16(20), pages 1-31, October.

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