Low-cost sensors have the potential to improve understanding of air quality in complex regions like oil and gas production basins. Regression methods have been used to quantify pollutants from sensor signals, but these methods have not been tested when sensors are moved to new sampling locations, away from model training locations. We use sensor data collected at multiple sites to test how well these field calibration methods perform when they are extended to new locations and times.