Assessing air quality's impact on human health involves monitoring pollutant concentrations such as NO2, O3, CO, SO2, and particulate matter. While high-income countries rely on expensive reference instruments, low-income nations face technological limitations. This study explores the potential of low-cost scientific devices as a viable solution for these regions. The research focuses on evaluating the reliability of low-cost NO2 sensors and consistency across five identical sensors. Calibration tests in controlled settings reveal a linear model with high coefficients of determination, contrasting with lower coefficients observed during field tests. Variability in intercepts and slopes is evident across time and campaign contexts. Time series analysis using low-cost NO2 sensors showed that many of the tall peaks atop a fluctuating baseline correlates with peaks identified by reference instruments. Additionally, NO gas sensors are also able to identify pollution peaks in monitoring campaigns. Therefore, such affordable sensors provide valuable insights into pollutant concentration trends, offering indicative magnitude information. However, improving calibration and reliability of these sensors necessitates further research.
