Abstract

Henry's law constants, H, of volatile organic compounds are often determined using static headspace gas chromatography. From the methodology of this approach, the experimental data are expected to conform to a nonlinear function and can, accordingly, be analyzed by a nonlinear regression procedure. Alternatively, the data can be transformed to a linear function and subsequently analyzed by linear regression. A series of computer simulations was used to demonstrate the need to employ appropriate statistical weighting factors in carrying out regression analysis of experimental data. These simulations were based on error-dispersed, realistic data sets for a wide range of H input values, and were analyzed using unweighted and weighted, nonlinear and linear regression methods. For a given data set, nonlinear and linear regression analyses, when both unweighted, return different H values. This disparity is sharply reduced when weighted regression methods are used. The regression results for H (and standard devi...

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