The quality of temporal information from daily burned area inputs was evaluated using a transport and chemistry experiment. Carbon monoxide emissions from boreal forest fires were estimated using burned area inputs with daily resolution. Averaging of emissions data to create 30-day aggregate data reduced the variance by 80%, indicating a substantial loss of information. Data from Russia, Canada, and Alaska were tested for periodicity to uncover systematic gaps in daily data. Some evidence of periodicity was found in data from Alaska, where temporal information came from fire mapping by the Alaskan Fire Service. Autocorrelation decayed rapidly and nearly monotonically for Canada and Russia, where temporal information came from Advanced Very High Resolution Radiometer (AVHRR) satellite observations. Daily data as well as 7-day and 30-day aggregates were used as input to the University of Maryland Atmospheric Chemistry and Transport Model, and output was compared with CO observations from the Cooperative Air Sampling Network (CASN); continuous measurements from Mace Head, Ireland; and total column CO retrievals from the Measurement of Pollution in the Troposphere (MOPITT) instrument. CASN flask measurements showed no sensitivity to high-frequency variability in the source, indicating the effectiveness of the filtering protocol at ensuring only well-mixed air masses are sampled in this data set. Differences between daily and 7-day simulations were too small for quantitative comparison in any of the data. For cases where the differences were substantial, simulations using daily and 7-day average sources agreed better with observations than 30-day average sources.