To assess the impact of interventions designed to reduce residential space heating demand, investigators must be armed with field-trial applicable techniques that accurately measure space heating energy use. This study assesses the feasibility of using a passive acoustic sensor to detect gas consumption events in domestic combination gas-fired boilers (C-GFBs). The investigation has shown, for the C-GFB investigated, the following events are discernible using a passive acoustic sensor: demand type (hot water or central heating); boiler ignition time; and pre-mix fan motor speed. A detection algorithm was developed to automatically identify demand type and burner ignition time with accuracies of 100% and 97% respectfully. Demand type was determined by training a naive Bayes classifier on 20 features of the acoustic profile at the start of a demand event. Burner ignition was determined by detecting low frequency (5–10 Hz) pressure pulsations produced during ignition. The acoustic signatures of the pre-mix fan and circulation-pump were identified manually. Additional work is required to detect burner duration, deal with detection in the presence of increased noise and expand the range of boilers investigated. There are considerable implications resulting from the widespread use of such techniques on improving understanding of space heating demand.