High population density is exposed with excess anthropogenic emissions impacting environment and health effects. Highly accurate and reliable air quality monitoring stations which have been established to continuously monitor the air pollution are expensive and complex in operation and maintenance. Dense deployment of low-cost air quality sensors in urban areas allows detecting the pollution hotspots in real-time. In this paper, we present data analysis of two identical low-cost sensors that measure meteorological variables, PM2.5 and CO2. The low-cost sensors were installed at a reference station. The results demonstrate that the sensors are consistent among themselves. When the sensors were compared with the reference station’s measurements, the sensors demonstrate adequate accuracy for meteorological variables. However, for PM2.5 and CO2, the sensors accuracies are not satisfactory, indicating that the sensors need to be calibrated or a proxy needs to be developed.
|Status||!!Accepted/In press - jun 2020|