We conclude that a mathematical model of a catalytic filter in series with a gas sensor can be used to optimize its design parameters when coupled with a probabilistic model of (i) measurement noise and (ii) gas compositions in the sensing environment. Particularly, Fig. shows the residence time of gas in the filter must be carefully tuned to minimize the expected error in the predicted partial pressure of the analyte, to balance corruption of the predicted gas composition by variance in (i) the interferent concentration and (ii) measurement noise. Generally, mathematical models of catalytically filtered gas sensors could be useful for screening catalysts, recognition elements for the sensor, operating temperatures, and residence times of gas in the filter. This is in line with recent efforts to computationally-design (non-filtered) gas sensors .