This thesis aims to develop and implement a real-time air quality monitoring system using an onboard UAV-based measurement platform to assess air quality over the area surrounding the Al-Doura power plant in Baghdad, Iraq.

The study also involves measuring pollutant concentrations and comparing them with international standards (WHO, US EPA) as well as local regulations. Geographic Information System (GIS) tools were employed to map the spatial distribution of pollutants and to identify air pollution hotspots. Additionally, the study examined the Air Quality Index (AQI) as a tool to evaluate pollution levels, which helped in tracking seasonal and geographical variations in air quality.

A DJI Phantom 4 Pro drone equipped with a calibrated, low-cost sensor array (CO, CO₂, SO₂, NO₂, PM₂.₅, VOCs) was employed in this study. Air sampling was conducted at various altitudes using the UAV, fixed ground stations, and a mobile monitoring vehicle during both the dry and wet seasons. Data collection for each pollutant followed the time intervals specified by the United States Environmental Protection Agency (US EPA). The results indicated that concentrations of certain pollutants exceeded permissible limits in multiple locations—for example, CO (27 ppm) and NO₂ (670 ppb). ANOVA analyses revealed statistically significant differences between sites and seasons. UAV-based AQI measurements for CO₂ and NO₂ classified them as ‘very unhealthy.’ In contrast, O₃ levels across all sites remained within the ‘good’ category, with AQI values of 10–11, corresponding to safe concentrations below 11.7 ppb. GIS-based maps clearly illustrated dispersion patterns and concentration gradients across the study area. The findings confirm that the Al-Doura region is experiencing environmental pollution. Moreover, the integration of UAVs with spatial analysis tools proved to be a scientifically reliable and effective approach for assessing environmental conditions in unmonitored industrial areas.

Final Grade: Very Good