論文

2006年10月4日

化学物質のリスク評価のための水系暴露解析モデル

資源と素材 : 資源・素材学会誌
  • 石川 百合子
  • ,
  • 東海 明宏

122
9
開始ページ
433
終了ページ
441
記述言語
日本語
掲載種別
DOI
10.2473/shigentosozai.122.433
出版者・発行元
The Mining and Materials Processing Institute of Japan

The AIST-SHANEL (AIST-Standardized Hydrology-based AssessmeNt tool for chemical Exposure Load) software was developed to estimate detailed and accurate exposure predictions of concentrations of chemicals at watershed areas for use within chemical risk assessment and management in Japan. This software covers the area more than 50% population in Japan. The main technical focus is on the temporal and spatial fate of chemicals in surface water, together with emissions from point sources of various industry and sewage treatment plants and non-point sources of households and agricultural land. Therefore, it is necessary to account for spatial and temporal distributions in exposure concentrations of chemicals with chemical emissions and river discharge. For estimating concentrations of chemicals in surface water on the 1km scale per day or month, a given watershed area was segmented into 1km grids, including 3 compartments of surface water, sediment, surface soil. The exposure concentrations in the watershed area were predicted based on the river discharge and the emission amounts of chemicals at each grid. The discharge was estimated from precipitation amounts in the watershed area. The emission amounts of chemicals based on the PRTR in Japan were allocated to 1km grids within the watershed area using industrial manufacture data, sewerage area data and land use data. The attenuation mechanisms included advection, diffusion, sorption/desorption, settling and resuspension of suspended solids, diffusive exchange between compartments, and biodegradation. Required input parameters in this model were emission data, sewage removal rate and basic chemical-specific properties for the chemical of interest. Here this model was applied to Tama River and predicted the exposure concentrations of some representative chemicals, for example 4-nonylphenol, in terms of ecological risk and risk reduction measures. In this way, this model will enables us to conduct ecological risk assessment in aquatic systems and will be expected as chemical risk assessment tool.

リンク情報
DOI
https://doi.org/10.2473/shigentosozai.122.433
CiNii Articles
http://ci.nii.ac.jp/naid/10018779358
CiNii Books
http://ci.nii.ac.jp/ncid/AN10062646
URL
http://id.ndl.go.jp/bib/8528950
URL
https://jlc.jst.go.jp/DN/JALC/00285429299?from=CiNii
ID情報
  • DOI : 10.2473/shigentosozai.122.433
  • ISSN : 0916-1740
  • CiNii Articles ID : 10018779358
  • CiNii Books ID : AN10062646

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