Development and Evaluation of an Airborne Measurement Platform for Assessing Regional Air Quality

Air pollutants, such as NOx (NO + NO2) and ozone (O3), have significant adverse effects on both human health and the environment. Their concentrations are typically monitored through ground-based networks, but such stationary measurements provide only a partial view of pollutant distribution, particularly within the planetary boundary layer (PBL), which extends up to approximately 1 km in altitude. This region is critical, e.g., for understanding pollutant transport from emission sources to impact zones, yet remains under-explored due to the technological and logistical demands of airborne measurement systems. This doctoral thesis examines the feasibility of using small, lightweight low-cost sensors, especially electrochemical sensors, for in situ trace gas measurements within the PBL, dependent on meteorological parameters, including temperature, humidity, and pressure. For this purpose, an unmanned aerial vehicle (UAV), collaboratively developed in the research project MesSBAR, and a Zeppelin NT were used as airborne platforms. These platforms were specifically chosen since their flight altitudes correspond to the typical heights of the PBL. A primary challenge lies in evaluating and ensuring the data quality of low-cost sensors, especially given the rapid environmental changes encountered during flight, which can affect sensor performance. To simulate these dynamic conditions in the laboratory, the Climatised Atmospheric Calibration Flow Tube System (CACTUS) was developed and its performance evaluated, enabling instrument characterization under controlled variations in temperature, relative humidity, air pressure, and pollutant concentrations. To realize these controlled conditions, high leak tightness is essential to minimize unwanted external influences and ensure the stability inside the system. CACTUS demonstrated a reliable performance in leak tightness, with a pressure increase of 0.21 hPa per hour (starting pressure of 800h Pa), corresponding to a calculated altitude change of 2 m per hour, confirming its suitability for drone-based applications. The system is capable of creating simulated atmospheres with temperatures and relative humidities ranging from −20 to 40 °C, and 0 to 95 %RH, respectively, while also providing the option to introduce air pollutants such as NOx, O3, particulate matter, and volatile organic compounds at atmospheric concentrations. Longitudinal temperature profiles demonstrated consistent distributions within ± 0.15 °C across the entire 140 cm flow tube length. To simulate the temperature changes experienced during a drone descent, a target gradient of ± 2 °C min-1, corresponding to a descent speed of 5 m s-1, was set. This gradient was achieved for heating and exceeded for cooling, reaching −4 °C min-1. Heating from −20 °C to 40 °C and cooling to −20 °C resulted in t90 values of 41 minutes and 21 minutes, respectively, where t90 refers to the time required for the temperature to reach 90 % of its final value. Humidity t90 values ranged from (308 ± 10) s to (840 ± 10) s (step changes of 10 %RH to 40 %RH). The t90 for pressure changes were found to range from (15 ± 4) s (50 hPa steps) to (84 ± 20) s (250 hPa steps). The system supports pressures down to 750 hPa, corresponding to altitudes of approximately 2.5 km, exceeding the 1 km target of the MesSBAR project. To determine the properties of electrochemical sensors for their application on UAVs and facilitating correction of electrochemical NO and NO2 sensor signals, models were developed using multiple linear regressions and evaluated using the Akaike Information Criterion, a statistical measure for model comparison, and the adjusted R2, a version of the coefficient of determination that accounts for the number of predictors in the model. It was observed that environmental influences on NO and NO2 sensors often act in opposite ways. Therefore, the summed signals of NO and NO2 measurements, i.e., NOx, were used to correct negative effects resulting from rapid changes in relative humidity. In addition, baseline estimation methods, including asymmetric least squares smoothing, were also applied and validated through both laboratory and in-flight field measurements using reference instruments. With these approaches, the increase in the PBL height, caused by solar heating of the ground and lower atmosphere, was successfully detected through consecutive vertical profile measurements with the UAV. Furthermore, deploying electrochemical sensors on a Zeppelin NT proved to be applicable to detect emissions from sources such as a lignite-fired power plant and a steel mill, highlighting the potential of electrochemical sensors for airborne measurements. This work successfully demonstrated that combining low-cost sensors with the MesSBAR UAV offers a promising approach for air quality measurements in the PBL, yielding reliable and valuable data validated against reference devices. Despite some challenges, such as stringent regulations and flight permission requirements - including the need for a transponder for altitudes > 300 m, which caused interference and increased noise in certain sensors due to its high-energy electromagnetic emissions (250 W), limiting UAV flights to a maximum altitude of 300 m - laboratory measurements simulating higher altitudes, along with Zeppelin flights at higher altitudes, confirmed the overall feasibility of the approach. The electrochemical sensors showed response times of approximately 30 seconds, which, while limiting maximum flight speed, still allowed for meaningful data collection and valuable insights into the spatio-temporal resolution of the measurements, such as the previously described increase in PBL height over time. The UAV’s battery life of approximately 15 minutes presented a constraint on flight parameters, but this was managed by adjusting ascent and descent speeds and replacing batteries in brief breaks, ensuring successful data acquisition. Moreover, practical solutions such as maintaining stable conditions with an enclosed measurement chamber and applying data-driven correction methods, such as asymmetric least squares smoothing and combining sensor signals, were effective in mitigating the impact of rapid environmental changes, like humidity variations, on sensor outputs. The capability to simulate flight-like conditions in the laboratory using CACTUS, along with the ability to conduct in situ measurements with low-cost sensors in the PBL via suitable airborne platforms, enhances the effectiveness of air pollutant monitoring. By integrating airborne platforms with low-cost sensors and applying the methods developed in this work, in situ monitoring within the PBL is brought closer to practical application, potentially bridging the observation gap between ground-based stations and higher-altitude measurements from aircraft and satellites.