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Prediction of soil organic carbon partition coefficients by soil column liquid chromatography

机译:土柱有机色谱法预测土壤有机碳分配系数

摘要

To avoid the limitation of the widely used prediction methods of soil organic carbon partition coefficients (K-OC) from hydrophobic parameters, e.g., the n-octanol/water partition coefficients (K-OW) and the reversed phase high performance liquid chromatographic (RP-HPLC) retention factors, the soil column liquid chromatographic (SCLC) method was developed for K-OC prediction. The real soils were used as the packing materials of RP-HPLC columns, and the correlations between the retention factors of organic compounds on soil columns (k(soil)) and K-OC measured by batch equilibrium method were studied. Good correlations were achieved between k(soil) and K-OC for three types of soils with different properties. All the square of the correlation coefficients (R-2) of the linear regression between log k(soi) and log K-OC were higher than 0.89 with standard deviations of less than 0.21. In addition, the prediction of K-OC from K-OW and the RP-HPLC retention factors on cyanopropyl (CN) stationary phase (k(CN)) was comparatively evaluated for the three types of soils. The results show that the prediction of K-OC from k(CN) and K-OW is only applicable to some specific types of soils. The results obtained in the present study proved that the SCLC method is appropriate for the K-OC prediction for different types of soils, however the applicability of using hydrophobic parameters to predict K-OC largely depends on the properties of soil concerned. (C) 2004 Elsevier B.V. All rights reserved.
机译:为避免广泛使用的基于疏水参数的土壤有机碳分配系数(K-OC)预测方法的局限性,例如正辛醇/水分配系数(K-OW)和反相高效液相色谱(RP) -HPLC)保留因子,开发了土壤柱液相色谱(SCLC)方法进行K-OC预测。以实际土壤为RP-HPLC色谱柱的填充材料,研究了有机化合物在土壤色谱柱上的保留因子(k(soil))与K-OC之间的相关性。对于三种性质不同的土壤,k(土壤)和K-OC之间具有良好的相关性。 log k(soi)和log K-OC之间的线性回归相关系数(R-2)的所有平方均大于0.89,标准偏差小于0.21。此外,比较评估了三种土壤在氰基丙基(CN)固定相(k(CN))上从K-OW预测K-OC和RP-HPLC保留因子。结果表明,从k(CN)和K-OW预测K-OC仅适用于某些特定类型的土壤。在本研究中获得的结果证明,SCLC方法适用于不同类型土壤的K-OC预测,但是使用疏水性参数预测K-OC的适用性在很大程度上取决于相关土壤的性质。 (C)2004 Elsevier B.V.保留所有权利。

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