The ability to characterize adsorption equilibria accurately is important in a number of physico-chemical processes, more especially in the purification of drinking water and industrial wastewater by activated carbon adsorption. One of the best-known relations to describe single-solute adsorption equilibria is the Langmuir isotherm, usually expressed in the linear form by plotting the reciprocal adsorption capacity ( 1 Γ ) against the reciprocal equilibrium concentration of the solute ( 1 C ), following the equation: 1 Γ = 1 Γ ∞ + K −1 Γ ∞ 1 C Equilibrium parameters of the Langmuir isotherm, Γ ∞ (ultimate quantity of substance adsorbed by unit weight of adsorbent) and K (equilibrium constant for adsorption), are then determined respectively from the intercept on the 1 Γ axis and from the slope K −1 Γ ∞ of the straight line. However, this common model of adsorption equilibrium is frequently applied as a convenient empirical representation of experimental data, without implying the signification of isotherm parameters for a particular solute, or their variation when competitive or mutual adsorption occurs in multi-component systems. In this work, a graphical representation of a new linear form of the Langmuir equation, for single-solute adsorption, is presented. Since there is a mathematical similarity between the Langmuir equation and the Michaelis-Menten equation used to describe enzyme kinetics, we propose to extend, to adsorption equilibrium studies, a recent description of a particular method of plotting enzyme kinetic results, developed and called “direct linear plot” by Eisenthal and Cornish-Bowden (1974). For a single-solute adsorption equilibrium, the Langmuir equation: Γ= Γ ∞KC 1+KC = Γ ∞C K −1+C can be rearranged to show the dependance of Γ ∞ on K −1, giving the relation: Γ ∞=Γ+ Γ C K −1 . In this linear form of the Langmuir equation, intercept on the vertical axis is obtained when K −1 = 0, at Γ = Γ ∞, and intercept on the horizontal K −1 axis is obtained when Γ ∞ = 0, at K −1 = − C. If observed Γ values are plotted on the vertical Γ ∞ axis and experimental C values plotted on a negative horizontal K −1 axis, then straight lines drawn through the corresponding Γ and C points have a slope Γ C . For several observations of Γ providing an adsorption isotherm, corresponding straight lines should intersect at a common point, the co-ordinates of which give the only values of equilibrium parameters, Γ ∞ and K −1, that satisfy all observations (Fig. 1). Previous experimental results (Lafrance et al., 1983) concerning the static adsorption, on powdered activated carbon, of micromolar quantities of 2-naphtol alone (Fig. 2) and in presence of increasing concentration of sodium dodecyl sulphate (SDS) (Fig. 3), are presented by the method of “direct linear plots”. It can be seen from this representation that: 1. (1) In a real experiment computing many values of Γ (or one adsorption isotherm), the point of intersection of corresponding straight lines gives, without calculation, a satisfactory evaluation of Γ ∞ and K −1, in comparison with results obtained from the classical Langmuir isotherm (the latter being indicated by circles on graphs); 2. (2) for a particular adsorption isotherm, the scattering of the intersection point provides a clear representation of experimental errors and/or the validity of the linear form of the Langmuir equation to describe experimental data; 3. (3) a qualitative and quantitative picture of the variation of equilibrium parameters for 2-naphtol in the presence of an increasing concentration of SDS (indicated by the shifting of the intersection point), shows the effect of a multi-component system on the adsorptive capacity and affinity of the carbon for a particular solute; and 4. (4) if we assume the linearity of the classical Langmuir isotherm, “direct linear plots” can focus attention directly on values of equilibrium parameters ( Γ ∞ and K −1 ), as a function of system characteristics. The study of the variation of these equilibrium parameters, should be helpful to identified adsorption mechanisms involved in multi-component systems.