Air Pollution Monitoring via Wireless Sensor Networks: The Investigation and Correction of the Aging Behavior of Electrochemical Gaseous Pollutant Sensors

Abstract

The continuously growing human activity in large and densely populated cities pollutes air and consequently puts public health in danger. This is why air quality monitoring is necessary in all urban environments. However, the creation of dense air monitoring networks is extremely costly because it requires the usage of a great number of air monitoring stations that are quite expensive. Instead, the usage of wireless sensor networks (WSNs) that incorporate low-cost electrochemical gas sensors provides an excellent alternative. Actually, sensors of this kind that are recommended for low-cost air quality monitoring applications may provide relatively precise measurements. However, the reliability of such sensors during their operational life is questionable. The research work presented in this article not only experimentally examined the correlation that exists between the validity of the measurements obtained from low-cost gas sensors and their aging, but also proposes novel corrective formulae for gas sensors of two different types (i.e., NO2, O3), which are aimed at alleviating the impact of aging on the accuracy of measurements. The following steps were conducted in order to both study and lessen the aging of electrochemical sensors: (i) a sensor network was developed to measure air quality at a place near official instruments that perform corresponding measurements; (ii) the collected data were compared to the corresponding recordings of the official instruments; (iii) calibration and compensation were performed using the electrochemical sensor vendor instructions; (iv) the divergence between the datasets was studied for various periods of time and the impact of aging was studied; (v) the compensation process was re-evaluated and new compensation coefficients were produced for all periods; (vi) the new compensation coefficients were used to shape formulae that automatically calculate the new coefficients with respect to the sensors’ aging; and (vii) the performance of the overall procedure was evaluated through the comparison of the final outcomes with real data.