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A Cluster Analysis of Constant Ambient Air Monitoring Data from the Kanto Region of Japan

Author

Listed:
  • Atsushi Iizuka

    (Research Center for Sustainable Science and Engineering, Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai, Miyagi 980-8577, Japan
    Department of Environmental Systems, Institute of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan)

  • Shintaro Shirato

    (Department of Environmental Systems, Institute of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan)

  • Atsushi Mizukoshi

    (Department of Environmental Systems, Institute of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan
    Tokyo Metropolitan Industrial Technology Research Institute, 2-4-10 Aomi, Koto-ku, Tokyo 135-0064, Japan)

  • Miyuki Noguchi

    (Department of Environmental Systems, Institute of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan
    Department of Materials and Life Science, Faculty of Science and Technology, Seikei University, 3-3-1 Kichijoji-kitamachi, Musashino, Tokyo 180-8633, Japan)

  • Akihiro Yamasaki

    (Department of Materials and Life Science, Faculty of Science and Technology, Seikei University, 3-3-1 Kichijoji-kitamachi, Musashino, Tokyo 180-8633, Japan)

  • Yukio Yanagisawa

    (Department of Environmental Systems, Institute of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan)

Abstract

This study demonstrates an application of cluster analysis to constant ambient air monitoring data of four pollutants in the Kanto region: NO x , photochemical oxidant (O x ), suspended particulate matter, and non-methane hydrocarbons. Constant ambient air monitoring can provide important information about the surrounding atmospheric pollution. However, at the same time, ambient air monitoring can place a significant financial burden on some autonomous communities. Thus, it has been necessary to reduce both the number of monitoring stations and the number of chemicals monitored. To achieve this, it is necessary to identify those monitoring stations and pollutants that are least significant, while minimizing the loss of data quality and mitigating the effects on the determination of any spatial and temporal trends of the pollutants. Through employing cluster analysis, it was established that the ambient monitoring stations in the Kanto region could be clustered topologically for NO x and O x into eight groups. From the results of this analysis, it was possible to identify the similarities in site characteristics and pollutant behaviors.

Suggested Citation

  • Atsushi Iizuka & Shintaro Shirato & Atsushi Mizukoshi & Miyuki Noguchi & Akihiro Yamasaki & Yukio Yanagisawa, 2014. "A Cluster Analysis of Constant Ambient Air Monitoring Data from the Kanto Region of Japan," IJERPH, MDPI, vol. 11(7), pages 1-12, July.
    • Handle: RePEc:gam:jijerp:v:11:y:2014:i:7:p:6844-6855:d:37784
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    Citations

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    Cited by:

    1. Emanoel L. R. Costa & Taiane Braga & Leonardo A. Dias & Édler L. de Albuquerque & Marcelo A. C. Fernandes, 2022. "Analysis of Atmospheric Pollutant Data Using Self-Organizing Maps," Sustainability, MDPI, vol. 14(16), pages 1-24, August.
    2. Shintaro Shirato & Atsushi Iizuka & Atsushi Mizukoshi & Miyuki Noguchi & Akihiro Yamasaki & Yukio Yanagisawa, 2015. "Optimized Arrangement of Constant Ambient Air Monitoring Stations in the Kanto Region of Japan," IJERPH, MDPI, vol. 12(3), pages 1-17, March.

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