Shirato Shintaro, Iizuka Atsushi, Mizukoshi Atsushi, Noguchi Miyuki, Yamasaki Akihiro, Yanagisawa Yukio
Department of Environmental Systems, Institute of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8563, Japan.
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.
Int J Environ Res Public Health. 2015 Mar 10;12(3):2950-66. doi: 10.3390/ijerph120302950.
Continuous ambient air monitoring systems have been introduced worldwide. However, such monitoring forces autonomous communities to bear a significant financial burden. Thus, it is important to identify pollutant-monitoring stations that are less efficient, while minimizing loss of data quality and mitigating effects on the determination of spatiotemporal trends of pollutants. This study describes a procedure for optimizing a constant ambient air monitoring system in the Kanto region of Japan. Constant ambient air monitoring stations in the area were topologically classified into four groups by cluster analysis and principle component analysis. Then, air pollution characteristics in each area were reviewed using concentration contour maps and average pollution concentrations. We then introduced three simple criteria to reduce the number of monitoring stations: (1) retain the monitoring station if there were similarities between its data and average data of the group to which it belongs; (2) retain the station if its data showed higher concentrations; and (3) retain the station if the monitored concentration levels had an increasing trend. With this procedure, the total number of air monitoring stations in suburban and urban areas was reduced by 36.5%. The introduction of three new types of monitoring stations is proposed, namely, mobile, for local non-methane hydrocarbon pollution, and Ox-prioritized.
连续环境空气监测系统已在全球范围内推行。然而，这种监测给自治社区带来了巨大的经济负担。因此，识别效率较低的污染物监测站很重要，同时要尽量减少数据质量的损失，并减轻对污染物时空趋势判定的影响。本研究描述了一种优化日本关东地区固定环境空气监测系统的程序。通过聚类分析和主成分分析，将该地区的固定环境空气监测站在拓扑结构上分为四组。然后，利用浓度等值线图和平均污染浓度对各区域的空气污染特征进行了评估。接着，我们引入了三条简单的标准来减少监测站的数量：（1）如果监测站的数据与其所属组的平均数据相似，则保留该监测站；（2）如果其数据显示浓度较高，则保留该监测站；（3）如果监测浓度水平呈上升趋势，则保留该监测站。通过这一程序，城郊和市区空气监测站的总数减少了36.5%。建议引入三种新型监测站，即用于本地非甲烷烃污染的移动监测站和以氧化合物为优先监测对象的监测站。
