Évaluation des performances d’un analyseur à faible coût pour la mesure des aérosols (PM10) dans l’écosystème de savane humide de la station géophysique de LAMTO, Côte d’Ivoire

Abstract

The present study aims to evaluate the performance of the low-cost AirQino sensor for measuring PM10 particle concentrations in a humid savannah environment at the Lamto geophysical station (Côte d'Ivoire). A 40-day measurement campaign was conducted in co-location with a reference instrument (TEOM). The raw results show a moderate and significant correlation between AirQino and TEOM measurements (r = 0.51; R² = 0.26), with a tendency to underestimate concentrations (NMB = -34.3%). The root mean square error (RMSE = 12.15 µg/m³) and the mean absolute error (MAE = 8.51 µg/m³) highlight significant data variability. The coefficient of variation of the mean absolute error (CVMAE = 45.2%) indicates limited accuracy, a phenomenon that is likely influenced by high relative humidity. To address these biases, several multivariate calibration models were tested. The most effective models (Model 1 and Model 2), which include meteorological variables (T, RH) and pollutants (CO, NO₂, O₃), significantly enhanced performance (r = 0.77; R² = 0.60; RMSE reduced to 7.57 µg/m³; CVMAE ≈ 28%; bias ≈ 0%). These findings confirm the vital role of environmental factors in measurement accuracy. Therefore, although AirQino cannot replace reference instruments without prior calibration, it provides a reliable alternative for spatiotemporal PM10 monitoring, as long as it is calibrated to the local environment using suitable models. Keywords: AirQino; Low-cost sensor; Lamto; PM10; Humid savanna; Multivariate calibration.