TY - JOUR
T1 - A statistical approach to the prediction of the possible presence of pollutant chemicals in the environment
AU - Ikeda, Masayuki
AU - Koizumi, Akio
AU - Kasahara, Miyuki
AU - Watanabe, Takao
AU - Nakatsuka, Haruo
AU - Sekita, Yasuyoshi
PY - 1987/9
Y1 - 1987/9
N2 - In the present study, trials were performed to examine the applicability of Hayashi's theory of quantification (second type) to prediction of the possible presence (i.e., detection) or absence (nondetection) of a given chemical in the environment. The dependent variables employed were the results of a nationwide environmental monitoring on pollutant chemicals conducted by the Environment Agency of Japan. When 102 chemicals were analyzed utilizing five factors as independent variables-annual production, use pattern, n-octanol/water partition coefficient (P o w), water solubility, and biodegradability-it was found that production, use pattern, and P o w are the major contributing factors in the prediction. Further studies with 186 chemicals utilizing these three factors as the independent variables showed that, through the combined evaluation of the results of analyses with three pairs out of the three variables, the absence of a chemical in the environment at an analytically meaningful level can be predicted with a success rate of 94.4%. The rate for the presence was 76.4%.
AB - In the present study, trials were performed to examine the applicability of Hayashi's theory of quantification (second type) to prediction of the possible presence (i.e., detection) or absence (nondetection) of a given chemical in the environment. The dependent variables employed were the results of a nationwide environmental monitoring on pollutant chemicals conducted by the Environment Agency of Japan. When 102 chemicals were analyzed utilizing five factors as independent variables-annual production, use pattern, n-octanol/water partition coefficient (P o w), water solubility, and biodegradability-it was found that production, use pattern, and P o w are the major contributing factors in the prediction. Further studies with 186 chemicals utilizing these three factors as the independent variables showed that, through the combined evaluation of the results of analyses with three pairs out of the three variables, the absence of a chemical in the environment at an analytically meaningful level can be predicted with a success rate of 94.4%. The rate for the presence was 76.4%.
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U2 - 10.1016/0273-2300(87)90039-0
DO - 10.1016/0273-2300(87)90039-0
M3 - Article
C2 - 3685461
AN - SCOPUS:0023402711
VL - 7
SP - 321
EP - 336
JO - Regulatory Toxicology and Pharmacology
JF - Regulatory Toxicology and Pharmacology
SN - 0273-2300
IS - 3
ER -