A drone-based approach to enhance spatial insight into surrounding air pollutant distributions for healthier indoor environments

Abstract

Current investigations into the interplay between indoor and outdoor air quality in buildings often rely on limited measurements of a small subset of air pollutants taken outside the structure. Implicit in this methodology is the assumption of a homogeneous distribution of air pollutants around the building, a premise that may not accurately reflect real-world conditions. This study introduces a more accurate and consistent approach to comprehending air pollutant distributions around buildings through systematic measurements conducted using a drone platform equipped with essential air quality sensors. Employing a fully autonomous drone, the study adopts a parametric approach to collect numerous air pollutant measurements around buildings with unconventional shapes. The resulting air pollutant maps offer comprehensive insights into the spatial distribution of pollutants around the building. A detailed analysis, achieved by dividing the building surroundings into different zones, revealed that concentrations of NO2, CO, PM10, and PM2.5 on the inward facade of the ¾ torus-shaped building were 12.64%, 14.49%, 7.66%, and 15.77% higher, respectively, than in the other measured areas around the building. These findings highlight that air pollutants around the building are notably influenced by the building's geometry, challenging the assumption of homogeneity. Instead, pollutants tend to accumulate at specific points, underscoring the significance of considering these factors in air quality assessments. Furthermore, the noted uneven distribution of pollutants around the building has distinct effects on various sections within the structure, as revealed by indoor measurements. Bureaus on the inward facade, where higher levels of outdoor pollutants are measured, can exhibit up to 44% more indoor air pollutants than those on the other side. This study not only contributes to a nuanced understanding of air pollutant distributions but also showcases the superior potential of drone platforms in advancing such research.