Inhomogeneity in the lung impairs gas exchange and can be an early marker of lung disease. We hypothesised that highly precise measurements of gas exchange contain sufficient information to quantify many aspects of the inhomogeneity non-invasively. Our aim was to explore whether one parameterization of lung inhomogeneity could both fit such data and provide reliable parameter estimates. A mathematical model of gas exchange in an inhomogeneous lung was developed, containing inhomogeneity parameters for compliance, vascular conductance and deadspace, all relative to lung volume. Inputs were respiratory flow, cardiac output, and the inspiratory and pulmonary arterial gas compositions. Outputs were expiratory and pulmonary venous gas compositions. All values were specified every 10 ms. Some parameters were set to physiologically plausible values. To estimate the remaining unknown parameters and inputs, the model was embedded within a non-linear estimation routine to minimise the deviations between model and data for CO2, O2 and N2 flows during expiration. Three groups, each of six individuals, were studied: young (20--30 yr); old (70--80 yr); and patients with mild to moderate chronic obstructive pulmonary disease (COPD). Each participant undertook a 15 min measurement protocol six times. For all parameters reflecting inhomogeneity, highly significant differences were found between the three participant groups (p<0.001, ANOVA). Intraclass correlation coefficients were 0.96, 0.99 and 0.94 for the parameters reflecting inhomogeneity in deadspace, compliance and vascular conductance, respectively. We conclude that, for the particular participants selected, highly repeatable estimates for parameters reflecting inhomogeneity could be obtained from non-invasive measurements of respiratory gas exchange.