論文

査読有り
2011年10月

Spatiotemporal trend analysis of recent river water quality conditions in Japan

JOURNAL OF ENVIRONMENTAL MONITORING
  • Pingping Luo
  • ,
  • Bin He
  • ,
  • Kaoru Takara
  • ,
  • Bam H. N. Razafindrabe
  • ,
  • Daniel Nover
  • ,
  • Yosuke Yamashiki

13
10
開始ページ
2819
終了ページ
2829
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1039/c1em10339c
出版者・発行元
ROYAL SOC CHEMISTRY

In order to promote pollutant monitoring and preservation of water resources, we evaluate the spatiotemporal trends in recent water quality conditions in Japanese rivers. Trend analysis is conducted on the 92 major rivers in Japan using the available water quality data recorded from 1992 to 2005 and the characteristics of major pollutants in these rivers are analyzed. Spatial and temporal analysis of trends for six water quality indicators is conducted using the Mann Kendall test, a non-parametric statistical method. The indicators analyzed are biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), total nitrogen (TN), total phosphorus (TP) and pH. The majority of sampling locations monitoring BOD, COD, TN and TP show trends toward decreasing concentrations over time. Many sampling locations show increasing DO concentrations. Our results show that water quality in Japanese rivers has improved dramatically over the past decade, although there are still problems in some places, most notably in the Hokkaido, Kanto, Kinki and Kyushu regions. The improvements seen in water quality appear to be the result of improved wastewater treatment and other water quality improvement efforts achieved through government initiative.

リンク情報
DOI
https://doi.org/10.1039/c1em10339c
CiNii Articles
http://ci.nii.ac.jp/naid/120004398113
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/21842064
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000295579000018&DestApp=WOS_CPL
ID情報
  • DOI : 10.1039/c1em10339c
  • ISSN : 1464-0325
  • CiNii Articles ID : 120004398113
  • PubMed ID : 21842064
  • Web of Science ID : WOS:000295579000018

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