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

International Journal of Environmental Research and Public Health

Atsushi Iizuka³  Shintaro Shirato²  Atsushi Mizukoshi²  Miyuki Noguchi²  Akihiro Yamasaki¹ 

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

关键词: cluster analysis;    constant ambient air monitoring;    Kanto region;    NO_x;    O_x;    non-methane hydrocarbon;    suspended particulate matter;   

DOI  :  10.3390/ijerph110706844

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.