Automated UAV-based real-time air quality monitoring and activity-level emission attribution at construction sites

Construction activities generate spatially and temporally variable pollutant emissions that are difficult to characterize using conventional stationary monitoring. This paper evaluates an automated unmanned aerial vehicle (UAV)-based framework for real-time air-quality monitoring at construction sites, integrating pollutant sensing, LoRa communication, GPS-referenced measurements, and real-time visualization. Field experiments evaluated sensor performance, communication reliability, UAV deployment, and pollutant monitoring under construction-site conditions. Measurements collected during UAV flights were synchronized with timestamps and spatial information on construction machinery to examine associations between observed pollutant concentrations and ongoing construction activities. Field results demonstrated spatial and temporal variations in particulate and gaseous pollutants across monitored construction operations. The framework provides spatially and temporally resolved pollutant information that can be associated with documented construction activities and machinery locations. These capabilities demonstrate its potential to support construction environmental management through localized pollutant identification, targeted mitigation, worker-exposure awareness, and data-informed planning.