Development of a Portable Calibration Chamber for PM Sensors Equipped with Wireless Connectivity Controlled by a Graphical Interface in Python

The health impact of air pollutants has generated a trend in the design and manufacture of portable, personal and fixed PM monitoring systems to help reduce exposure to air pollutants. However, these devices still need to be improved and properly evaluated to compete with environmental monitors in the market. In this work, a test chamber with controlled environmental conditions and wireless connectivity is developed for the evaluation of low-cost portable and personal PM sensors. The developed system ensures rapid evaluation tests ranging from seconds to hours to corroborate prolonged operation and correct calibration. The system is controlled by a Python-based graphical user interface (GUI) and monitors PM concentration, altitude, relative humidity, atmospheric pressure, illuminance, and temperature measurements. Fifty measurement tests with a duration of 10 min each were conducted to ensure robust performance and data transfer. Subsequently, four calibration tests were conducted using two SENSIRION SPS30 (SPS A and SPS B) personal PM sensors and two PMS5003 (PMS A and PMS B) personal PM sensors. The Prana Air PAS-OUT-01 sensor served as the reference to calculate the correlations and the descriptive statistics between each sensor to be calibrated. A contamination source was employed utilizing a monodispersed aerosol generator for 0.46 µm latex polystyrene particle atomization. Linear regression was applied during the calibration to determine the calibration coefficients, which were then used to adjust the sensor readings in the respective code and descriptive statistics of the sensor calibration tests were calculated. For the PMS5003 sensors, the Pearson correlation coefficients (r) after calibration were PMS A: 0.9870 and PMS B: 0.9898 compared to their uncalibrated values of PMS A: 0.9828 and PMS B: 0.9863. In contrast, the uncalibrated SPS A sensor initially had a correlation of 0.9939, which slightly decreased to 0.9917 after calibration. Meanwhile, the uncalibrated SPS B sensor showed a correlation of 0.9422, which improved to 0.9715 after calibration.