Identification of the Safe Variation Limits for the Optimization of the Measurements in Low-Cost Electrochemical Air Quality Sensors

Abstract

Nowadays, the study of air quality has become an increasingly prominent field of research, particularly in large urban centers, given its significant impact on human health. In many countries, government departments and research centers use official high-cost scientific instruments to monitor air quality in their regions. Meanwhile, concerned citizens interested in studying the air quality of their local areas often employ low-cost air quality sensors for monitoring purposes. The optimization and evaluation of low-cost sensors have been a field of research by many research groups. This paper presents an extensive study to identify the safe percentage change limits that low-cost electrochemical air quality sensors can have, in order to optimize their measurements. For this work, three low-cost air quality monitoring stations were used, which include an electrochemical sensor for nitrogen dioxide (NO2) (Alphasense NO2-B43F) and an electrochemical sensor for ozone (O3) (Alphasense OX-B431). The aim of this work is to explore the variance of the aforementioned sensors and how this variability can be used to optimize the measurements of low-cost electrochemical sensors, closer to real ones. The analysis is conducted by employing diagrams, boxplot and violin curves of the groups of sensors used, with satisfactory results.

Nonlinear Regression Approach as a Correction Factor of Measurements of Low-Cost Electrochemical Air Quality Sensors

“…The design and implementation of the low-cost gas quality monitoring stations were carried out by the Electronic Devices and Materials Research Laboratory (EDML) of the Department of Electrical and Electronics Engineering of the University of West Attica in Greece. Details of the monitoring stations' design and implementation can be found in previous works [15,35]. The stations were installed at the same place, near to official instrumentation from the Ministry of Environment and Energy of Greece (PERPA) [45] at a height of 6-8 m. The monitoring stations were installed in Athens city center and installation details regarding the locations, the sampling rate and the official instrumentation used for the on-site measurements are presented in [33].…”

“…However, their application requires a large amount of data for training each model [31,32]. The simplest correction methods are presented by the Kalman filtering [33] and LASSO regression [34] approaches, as well as the measurements variation limits [35] approach. According to manufacturers, the lifetime of low-cost electrochemical sensors is set at 1 to 2 years, and during its operation the change in sensor response is referred to as aging [36,37].…”

Investigation of LASSO Regression Method as a Correction Measurements’ Factor for Low-Cost Air Quality Sensors

“…The research group [23] proposes a method for the calibration of portable gas sensors for accurate measurement of O 3 and NO 2 by utilizing linear regression, least squares, and major axis linear regression. In the research work [24], the method of correcting measurements according to the quantitative variation in low-cost sensor measurements using linear regression is proposed.…”