We present an algorithm for flagging sharply elevated values ("spikes") in a univariate time series, which we assume to be methane concentrations. This algorithm is used in the broader event detection, localization, and quantification framework to estimate background methane concentrations, determine when an emission is occurring, and isolate time steps in which a given sensor is recording a relevant signal.