Modeling of RO/NF membrane rejections of PhACs and organic compounds: a statistical analysis

Drinking Water Engineering and Science

V.Yangali-Quintanilla¹  M.Kennedy¹  G.Amy¹  T.-U.Kim¹ 

DOI  :  10.5194/dwes-1-7-2008

学科分类：工程和技术（综合）

来源: Copernicus Publications

【 摘 要 】

Rejections of pharmaceutical compounds (Ibuprofen, Diclofenac, Clofibricacid, Naproxen, Primidone, Phenacetin) and organic compounds (Dichloroaceticacid, Trichloroacetic acid, Chloroform, Bromoform, Trichloroethene,Perchloroethene, Carbontetrachloride, Carbontetrabromide) by NF (Filmtec,Saehan) and RO (Filmtec, Saehan, Toray, Koch) membranes were studied.Chloroform presented the lowest rejection due to small molar volume,equivalent width and length. Diclofenac and Primidone showed high rejectionsrelated to high molar volume and length. Dichloroacetic acid andTrichloroacetic acid presented good rejections caused by charge exclusioninstead of steric hindrance mechanism influencing rejection. Bromoform andTrichloroethene showed low rejections due to small length and equivalentwidth. Carbontetrabromide, Perchloroethene and Carbontetrachloride withhigher equivalent width than BF and TCE presented better rejections. Aqualitative analysis of variables using Principal Component Analysis wassuccessfully implemented for reduction of physical-chemical compoundproperties that influence membrane rejection of PhACs and organic compounds.Properties such as dipole moment, molar volume,hydrophobicity/hydrophilicity, molecular length and equivalent width werefound to be important descriptors for simulation of membrane rejection. Formembranes used in the experiments, we may conclude that charge repulsion wasan important mechanism of rejection for ionic compounds. After analysis withMultiple Linear Regression, we also may conclude that membrane rejection ofneutral compounds was well predicted by molar volume, length, equivalentwidth, hydrophobicity/hydrophilicity and dipole moment. Molecular weight wasa poor descriptor variable for rejection modelling. We were able to provideacceptable statistical significance for important results.

【 授权许可】

Unknown