Differences in Regional Home Heating Behavior in Three U.S. Cities Revealed by Ground‐Based Sensor Network

Abstract Home heating preferences vary dramatically with regional climate. The temperature at which residents turn on natural gas home heating systems (critical temperature) varies by as much as 25°C from the northern to southern United States (U.S.). Here we derive temperature dependent CO 2 emissions in three U.S. cities using a dense ground‐based CO 2 observation network. A Bayesian inverse modeling methodology is used to update a 1‐km emission inventory in each of the three cities. This method is able to correctly identify the critical temperature of home heating even when this information is withheld from the prior inventory, as verified by natural gas distribution data. Variance in regional heating practices has not been previously demonstrated with ground‐based networks of CO 2 observations. This result provides evidence that a Bayesian inverse modeling framework is sensitive to emissions of the home heating sector.