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.