Volatile organic compounds (VOCs) are a type of air pollutants that have adverse health impacts on the human body. Among monitoring instrumentation, the photoionization detector (PID) has become popular nowadays due to its cost-effectiveness and time-saving advantages compared to conventional tools like Gas Chromatography-Mass Spectrum (GC-MS). Previous studies have shown that the correlation between PID and GC-MS significantly decreases when transitioning from the laboratory to the field, indicating that meteorological factors greatly influence PID performance. The objective of this study is to identify and mitigate potential error sources through a calibration algorithm....[ Read more ]

Volatile organic compounds (VOCs) are a type of air pollutants that have adverse health impacts on the human body. Among monitoring instrumentation, the photoionization detector (PID) has become popular nowadays due to its cost-effectiveness and time-saving advantages compared to conventional tools like Gas Chromatography-Mass Spectrum (GC-MS). Previous studies have shown that the correlation between PID and GC-MS significantly decreases when transitioning from the laboratory to the field, indicating that meteorological factors greatly influence PID performance. The objective of this study is to identify and mitigate potential error sources through a calibration algorithm.

The PID was firstly characterized under various temperature (15°C - 35°C) and humidity (40% - 80%) conditions in an environmental chamber and a correction model was fitted based on the result. Absolute humidity (AH) is introduced as a function of T and RH to linearize the correction formula. To verify the algorithm derived in the lab, the instruments were installed at Shanghai Chemical Industry Park (SCIP) to continuous measure VOCs for three months.

The lab test shows that ranging from the lowest AH (0 g/m3) to the highest AH (30 g/m3), baseline voltage of PID increased about 20mV. The sensitivity is negatively related to AH. This shows the potential to diminish impact of humidity based on correction model.

Five co-pollutants are tested for interference effect. PID is sensitive for NO but not for NO₂. But ideally, both those two gases are supposed to influence PID response since their ionization energy is lower than the UV lamp. O₃, SO₂, and CO do not have significant influence on PID response.

Few studies tested the long-term drift of PID. In our field observation result, the long-term drift rate of baseline is around 0.0937 mV/day. This may because of VOC contamination on UV lamp. After correction, baseline is positive related to AH the same as the lab test, but the amplitude is only one-third of it in the lab. Maybe O₂ diminish the light intensity and reduce the humidity sensitivity.

MOCON PID is another brand PID which has same principle as Alphasense PID. But we found that its baseline drops about 20 mV within 40% - 65% RH. One of the critical structures inside the electrode may absorb vapor and influence the ion collection process. Beside the abnormal drop phenomenon, half of the sensors short circuited and go to very high voltage when RH is larger than 85% even the sensor is not contaminated. The condensation can be inhibited through pre-heat airflow when observe in the field.

In conclusion, humidity influence PID sensor in completely different ways. For different brands, their PIDs also encounter different type of difficulties. This study investigates the potential format of those impacts and discuss the availability of calibrating them with algorithm. This will be helpful for the development of real-time online VOC monitoring data processing.