ABSTRACT For olfactory sensors, clear differentiation of complex odour samples requires diverse information. To obtain such information, hardware modifications, such as introducing additional channels with different physical/chemical properties, are usually needed. In this study, we present a new approach to augmenting the sensing signals of an olfactory sensor by modulating the flow rate of the carrier gas. The headspace vapour of complex odours is measured using a sensing system of nanomechanical sensor (Membrane-type Surface stress Sensor, MSS). The resulting data set is quantitatively evaluated using the Davies-Bouldin index (DBI) of principal component analysis (PCA). The increasing number of sensing signals obtained at different gas flow rates leads to a decrease in the DBI, achieving better cluster separation between different odours. Such gas flow effects can be attributed to several factors, including the sample evaporation and the equilibrium of the gas-liquid and gas-solid interfaces. Proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS) experiments reveal that the compositions of odour samples vary with the different gas flow rates. It is demonstrated that a simple technique for modulating gas flow rates can significantly improve the differentiation performance of complex odours, providing an additional degree of freedom in olfactory sensing.