Using the QICAR Model to Correlate Metal Ion Characteristics with Toxicity Order Numbers |
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Authors: | Yu Li Xiao-Li Li Xian-Yuan Du Meng Wang Jing Xin Yan Hu |
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Affiliation: | MOE Key Laboratory of Regional Energy Systems Optimization, Research Academy of Energy and Environmental Studies , North China Electric Power University , Beijing , China |
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Abstract: | The quantitative ion character–activity relationship (QICAR) was used to correlate nine ion characteristics with ion toxicity order numbers (TON) in 19 metals. A multi-parameter regression model was used to simulate the metals toxicity order numbers after minimization of the multicollinearity among the ion characteristics using principal component analysis (PCA). The toxicity order numbers of the metals increased with the positively correlated variables AN, Xm 2r, AN/ΔIP, AW, and Xm , and decreased with the negatively correlated variables ΔE 0, |logK OH|, AR/AW, and σ P . The regression model provided high prediction ability, with Nash-Suttcliffe simulation efficiency coefficients (NSC) of 0.93 for the modeling phase and 0.87 for the testing phases. The model may be successfully employed to predict the stability constants and metal toxicity and used as a first step in the further risk assessment modeling. |
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Keywords: | quantitative ion character–activity relationship metal ion characteristic metal toxicity order number principal component analysis principal component regression |
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