In the Philippines, where 80% of air pollution comes from vehicle emissions, air quality stations have limited coverage, making efficient monitoring crucial for tracking pollutant exposure. This study proposes a mobile monitoring system to provide more comprehensive air quality data across the University of the Philippines Diliman Campus (UPD). The system is installed in E-trikes due to their zero tailpipe emissions. It comprises an indoor and outdoor node equipped with sensors to measure PM2.5, PM10, CO2, temperature, humidity, VOC index. A TTGO LORA32 microcontroller collected, processed and transmitted sensor data with a Micro SD Card backup. GPS modules were included for both nodes, and the outdoor node featured a wind anemometer. Results were visualized in a Grafana-based web application with time series and heatmaps. The indoor node consumed more power due to frequent transmission. Data was analyzed and visualized by comparing air quality parameters against established safety thresholds, ranging from safe to dangerous levels. High pollutant levels were observed near busy roads, jeepney waiting sheds and residential halls, while the Academic Oval showed better air quality.
Tolentino et al. (Fri,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: