  Drift is a significant issue that undermines the reliability of gas sensors.
This paper introduces a probabilistic model to distinguish between
environmental variation and instrumental drift, using low-cost non-dispersive
infrared (NDIR) CO2 sensors as a case study. Data from a long-term field
experiment is analyzed to evaluate both sensor performance and environmental
changes over time. Our approach employs importance sampling to isolate
instrumental drift from environmental variation, providing a more accurate
assessment of sensor performance. The results show that failing to account for
environmental variation can significantly affect the evaluation of sensor
drift, leading to improper calibration processes.
