An Assessment on Accuracy of GC-MS AIQS-DB Method in River Water Monitoring
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- MIHO Saori
- Faculty of Environment and Information Sciences, Yokohama National University
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- KAMEYA Takashi
- Faculty of Environment and Information Sciences, Yokohama National University Institute of Advanced Sciences, Yokohama National University
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- KOBAYASHI Takeshi
- Faculty of Environment and Information Sciences, Yokohama National University
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- FUJIE Koichi
- Institute of Advanced Sciences, Yokohama National University
Bibliographic Information
- Other Title
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- 河川水モニタリングにおけるGC-MS AIQS-DB法の同定定量精度の評価
Abstract
<p>Four indexes related to quantification accuracy and three indexes related to identification accuracy were investigated to clarify the reasons of their accuracy decrease in the simultaneous measuring using the GC-MS AIQS-DB method. Seven items concerning (1) the variation of quantification value in repeated measurement, (2) the lower limit of quantification value, (3) the change of quantification value effected by coexisting substance, (4) the recovery ratio in solid phase extraction, (5) the change of retention time, (6) the decrease of peak similarity and (7) the decrease of S/N ratio were ranked and scored based on the measurement results for 280 chemicals registered in the Japanese PRTR Law. As the result, it was found that 134 chemicals have the accuracy level enough for a screening evaluation, and that 105 chemicals were required detailed examinations to clarify the reasons of decrease in quantification accuracy and the identification accuracy. The comprehensive assessment matrix consisting of quantification accuracy and identification accuracy presented in this study shows the level and the cause of accuracy decrease. Therefore, it makes possible to assess the analysis accuracy as well as the detection of the large amount of monitoring data of simultaneous measuring using GC-MS AIQS-DB.</p>
Journal
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- ENVIRONMENTAL SCIENCE
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ENVIRONMENTAL SCIENCE 33 (5), 90-102, 2020-09-30
SOCIETY OF ENVIRONMENTAL SCIENCE, JAPAN
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Details 詳細情報について
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- CRID
- 1390004222629247232
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- NII Article ID
- 130007919243
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- ISSN
- 18845029
- 09150048
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- Text Lang
- ja
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed