論文

査読有り
2009年

Probabilistic Estimation of Regional Dietary Exposure to Dioxins in Fish in Japan on the Basis of Market and Fish Distribution Network Data

HUMAN AND ECOLOGICAL RISK ASSESSMENT
  • Hongbin Cao
  • ,
  • Noriyuki Suzuki
  • ,
  • Takeo Sakurai

15
5
開始ページ
890
終了ページ
906
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1080/10807030903153113
出版者・発行元
TAYLOR & FRANCIS INC

Dietary consumption of fish is the greatest contributor to dioxin exposure of the general population in Japan. Unlike with other routes of exposure to dioxins, exposure via foodstuffs does not necessarily occur from local sources. Clarifying the distribution of fish from the catch area to local markets helps to control dioxin exposure from the head of the distribution chain down. We analyzed the data from 30 major central wholesale fish markets to determine both the market share of fish by catch area and the market share of major fish types in fish consumption markets. Probabilistic estimation of dietary exposure of the general population to dioxins in fish was conducted in seven regions in Japan. Probabilistic density functions (PDFs) were assigned to express the variability of data from monitoring of dioxin levels in fish by catch area or by fish type. From histograms of dioxin levels in fish by catch area, the mean and 5th to 95th percentile range of dietary exposure to dioxins in the region with the largest 95th percentile value were estimated, respectively, as 55.5 and 12.9-172.9 pg-TEQ/day. No statistically significant differences in dietary exposure to dioxins in fish were observed among the seven regions. Some specific coastal catch areas and some types of fish that had a greater impact than others on exposure were pinpointed for each region.

リンク情報
DOI
https://doi.org/10.1080/10807030903153113
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000271231700004&DestApp=WOS_CPL
URL
http://orcid.org/0000-0002-4263-3469
ID情報
  • DOI : 10.1080/10807030903153113
  • ISSN : 1080-7039
  • ORCIDのPut Code : 12342574
  • Web of Science ID : WOS:000271231700004

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