Use of unmanned aerial systems for measuring particulate matter in the lower atmosphere in urban areas

Abstract

Air quality monitoring traditionally relies on ground stations and satellites, which may face limitations in capturing real-time data near pollution sources due to site complexity or physical barriers. To overcome these challenges, unmanned aerial vehicles (UAVs) equipped with air quality sensors offer new opportunities for comprehensive and rapid data collection in urban and industrial areas. In this study, we propose a novel approach by utilizing a UAV-based system to investigate the spatial distribution of particulate matter in the atmosphere. The monitoring site is strategically located at an intersection in Zagreb, known for its medium to high traffic density and its suitability for capturing the impact of vehicular emissions on air quality. It is essential to note that this assumption based on the observed conditions is not a precisely measured figure but rather an estimate based on observations and the context of the road. Traffic density may vary throughout the day, week, or year, depending on working hours, events, seasonal factors, and other influences affecting vehicular movement. The UAV is equipped with lightweight and low-cost sensors specifically designed for measuring airborne particles, ensuring accurate and reliable measurements. These sensors, integrated onto the UAV and placed on the upper side, minimize interference from propeller-generated airflow and turbulence, providing representative assessments of air quality conditions. By collecting precise data on the concentration of airborne particles, including PM1, PM2.5, and PM10, the study aims to gain insights into the spatial distribution of pollutants near the intersection and understand the potential impacts of traffic emissions on the surrounding environment. Additionally, the UAV's sensors can connect to smartphones or computers, enabling real-time data viewing and analysis, facilitating prompt adjustments and informed decision-making based on the current air quality conditions. The findings challenge the initial assumption as the concentration of particles does not decrease with increasing altitude, requiring further research to understand this phenomenon. Furthermore, future research will consider integrating meteorological data, such as temperature, humidity, air pressure, wind direction, and speed, from a nearby weather station. By analyzing the interplay between meteorological parameters and particle concentration, a comprehensive understanding of airborne particle dynamics can be achieved. This approach will contribute to the development of effective strategies for managing air quality, considering the complex interdependencies and factors influencing particle distribution in the air.