Three-dimensional distribution of fine particulate matter concentrations and synchronous meteorological data measured by an unmanned aerial vehicle (UAV) in Yangtze River Delta, China
Si-Jia Lu1, Dongsheng Wang1, Xiao-Bing Li1, Zhanyong Wang1, Ya Gao1, and Zhong-Ren Peng1,21Center for UAV Application and ITS Research, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China 2Department of Urban and Regional Planning, University of Florida, Gainesville, FL 32611-5706, USA
Received: 20 Feb 2016 – Accepted for review: 29 Feb 2016 – Discussion started: 08 Mar 2016
Abstract. Three-dimensional distribution of fine particulate matter (PM2.5) and meteorological factors are of great importance to clarify the formation mechanism of haze pollution and to help forecast atmospheric pollution under different meteorological conditions. The objective of this study was to measure PM2.5 concentrations and meteorological data at 300–1000 m altitude using an unmanned aerial vehicle (UAV) equipped with mobile instruments. The study was conducted in a 4 × 4 km2 space in Lin'an, Yangtze River Delta (YRD), China. The UAV was operated repeatedly for four times in one day along the designed route spirally from the ground to 1000 m altitude with a total of 8 layers and a 100 m interval between two adjacent layers for five days from 21th August 2014 to 2nd February 2015. PM2.5, air temperature, relative humidity, dew point temperature and air pressure were measured during the data collection. The study results indicated that the PM2.5 concentrations decreased with altitude at 300–1000 m and the variations of PM2.5 with altitude in morning flights were much bigger than in afternoon flights. Besides, the PM2.5 concentration levels in morning flights were generally lower than in afternoon flights. PM2.5 concentrations were positively correlated with dew point temperature and pressure, but positively correlated with relative humidity only on pollution days in autumn or winter. The vertical gradient of PM2.5 concentrations was small in pollution days compared with on clean days. These findings provide the key theoretical foundation for PM2.5 pollution forecast and environmental management.
Lu, S.-J., Wang, D., Li, X.-B., Wang, Z., Gao, Y., and Peng, Z.-R.: Three-dimensional distribution of fine particulate matter concentrations and synchronous meteorological data measured by an unmanned aerial vehicle (UAV) in Yangtze River Delta, China, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2016-57, 2016.