Vertical profiling of atmospheric air pollutants in rural India: A case study on particulate matter (PM10/PM2.5/PM1), carbon dioxide, and formaldehyde

Abstract

Particulate matter is one of the major air pollutants that challenge the environment and human health. In this study, we used an unmanned aerial vehicle associated with smart, low-cost sensors to record the vertical profiles of particulate matters (PM10/PM2.5/PM1), carbon dioxide, and formaldehyde in a rural area of southern India. Our study covered the surface to 60 m above the ground level compiling data over twenty days of measurements in March 2021. A total of thirty flights were performed in the five selected locations. The data show a decrease in air pollutant concentration with increasing height from the surface. However, statistical data analysis through CHAID Decision Trees and 3-D visualization of the relationship between the pollutants and the height, RH, and temperature show that the concentration of pollutants is more strongly influenced by the location and meteorological parameters rather than the height from the surface. We infer that transport through both advection and convection influences the vertical distribution of air pollutants as inferred from meteorological analysis, including back trajectories using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT4) model. The long-range transport of air mass could also contribute to the high concentration values of particulate matters, as found through the five-day air mass backward trajectory analysis. Although the observed data sets are confined to a height of 60 m AGL, the results from this study provide insights into the vertical distribution of air pollutants, complementing ground-based measurement variations with different spacing and timing.