The adsorption behavior at the water-air interface and volumetric properties of aqueous solutions of Triton X-100 and propanol mixtures at constant Triton X-100 concentrations equal to I X 10(-7), 1 x 10(-6), 1 x 10(-5), 1 x 10(-4), 6 x 10(-4), and 1 x 10(-3) M, respectively, in the propanol concentration range from 0 to 6.69 M were investigated by Surface tension, viscosity, and density measurements of solutions. The obtained values of the surface tension as a function of propanol concentration were compared with those Calculated from the Fainerman and Miller equation. On this basis it was stated that the Fainerman and Miller equation is useful for prediction of surface tension only in the concentration range of Triton X-100 corresponding to its unsaturated monolayer in the absence of propanol. Using the measured values of the surface tension in the Gibbs equation, the Surface excess concentration of Triton X-100 and propano[ was Calculated, and it was stated that in the case of propanol the most reliable Values of its excess concentration were obtained if its activity were taken into account instead of concentration in the bulk phase. The values of the Surface excess concentration were applied in different approaches for determination of the standard free energy of adsorption. The calculated values of the standard free energy of adsorption were compared with those for individual components of the studied mixtures deduced on the basis of the tail-water and tail-air interfacial tension. Beside the surface properties of the Triton X-100 and-propanol mixtures their volumetric properties were established and it was found that the micellization Process of Triton X-100 Occurred only at a low propanol concentration at which it is present in the monomeric form. The possibility of propanol aggregates formation was deduced from the viscosity and density changes in relation to propanol concentration. From the density data it was also deduced that the apparent molar volume for aqueous Solutions of the Triton X-100 and propanol mixtures can be predicted from the data of their individual components. (C) 2009 Elsevier Inc. All rights reserved.