Development and Validation of a UAV Based System for Air Pollution Measurements

Area of Science:

• Environmental Science
• Atmospheric Science
• Robotics Engineering

Background:

• Air quality monitoring near pollution sources is challenging due to complex environments and moving sites.
• Small Unmanned Aerial Vehicles (UAVs) present a novel solution for atmospheric and air pollution studies.
• Optimal sensor placement is critical for representative data collection on UAVs.

Purpose of the Study:

• To determine the best mounting location for gas sensors and a Particle Number Concentration (PNC) monitor on a hexacopter UAV.
• To develop a UAV system for effective measurement of point source emissions.
• To provide guidelines for developing UAV systems for real-world air quality data collection.

Main Methods:

• Assessed hexacopter airflow dynamics, including downwash and upwash effects, by measuring air speed.
• Evaluated the performance of CO₂, CO, NO₂, NO gas sensors, and a PNC monitor (DISCmini) using a diesel engine emission source.
• Employed a Linear Regression model to analyze the impact of sensor position on pollutant concentration measurements.

Main Results:

• Air speed mapping identified sensor placement alongside the UAV as optimal, minimizing propeller downwash interference.
• UAV propeller wash caused a dispersion effect, reducing measured gas and particulate matter concentrations in real-time.
• Sensor position relative to the UAV center significantly affected pollutant concentration readings.

Conclusions:

• Mounting sensors alongside the UAV is recommended for accurate air quality measurements.
• UAV propeller wash disperses emissions, a factor to consider in data analysis.
• Guidelines are established for developing effective UAV-based air pollution monitoring systems.