Vertical profiling of fine particulate matter and black carbon by using unmanned aerial vehicle in Macau, China

Sci Total Environ. 2020 Mar 20:709:136109. doi: 10.1016/j.scitotenv.2019.136109. Epub 2019 Dec 13.

Abstract

An unmanned aerial vehicle (UAV) equipped with miniature monitors was used to study the vertical profiles of PM2.5 (particulate matter with a ≤2.5-μm diameter) and black carbon (BC) in Macau, China, from the surface to 500 m above ground level (AGL). Twelve- and 11-day measurements were conducted during February and March 2018, respectively. In total, 46 flights were conducted between 05:00 and 06:00 AM Local Time (LT). The average concentrations of PM2.5 and BC were significantly lower in March (40.1 ± 17.9 and 2.3 ± 2.0 μg m-3, respectively) when easterly winds prevailed, compared with those in February (69.8 ± 35.7 and 3.6 ± 2.0 μg m-3, respectively) when northerly winds dominated. In general, PM2.5 concentrations decreased with height, with a vertical decrement of 0.2 μg m-3 per 10 m. BC concentrations exhibited diverse vertical profiles with an overall vertical decrement of 0.1 μg m-3 per 10 m. Meteorological analyses including back-trajectory analysis and atmospheric stability categorization revealed that both advection and convection transports may have notable influences on the vertical profiles of PM pollutants. The concentration of PM pollutants above the boundary layer was lower than that within the layer, thus exhibiting a sigmoid profile in some cases. In addition, the lighting of firecrackers and fireworks on February 16 (first day of the Chinese New Year) resulted in the elevated concentrations of PM2.5 and BC within 150 m AGL. The takeoff of a civil flight on February 10 may have resulted in a substantial increase in the PM2.5 concentrations from 80.8 (±2.1) μg m-3 at the ground level to 119.2 (±9.3) μg m-3 at a height of 330 m. Although the results are confined to a height of 500 m AGL, the current study provides a useful dataset for PM vertical distributions, complementing the spatiotemporal variations by ground-based measurements.

Keywords: Black carbon; PM(2.5); Particulate matter; Unmanned aerial vehicle; Vertical profile.