Preprints
https://doi.org/10.5194/amt-2016-57
https://doi.org/10.5194/amt-2016-57
08 Mar 2016
 | 08 Mar 2016
Status: this preprint was under review for the journal AMT but the revision was not accepted.

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 Lu, Dongsheng Wang, Xiao-Bing Li, Zhanyong Wang, Ya Gao, and Zhong-Ren Peng

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.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Si-Jia Lu, Dongsheng Wang, Xiao-Bing Li, Zhanyong Wang, Ya Gao, and Zhong-Ren Peng
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Si-Jia Lu, Dongsheng Wang, Xiao-Bing Li, Zhanyong Wang, Ya Gao, and Zhong-Ren Peng
Si-Jia Lu, Dongsheng Wang, Xiao-Bing Li, Zhanyong Wang, Ya Gao, and Zhong-Ren Peng

Viewed

Total article views: 2,321 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,233 984 104 2,321 109 142
  • HTML: 1,233
  • PDF: 984
  • XML: 104
  • Total: 2,321
  • BibTeX: 109
  • EndNote: 142
Views and downloads (calculated since 08 Mar 2016)
Cumulative views and downloads (calculated since 08 Mar 2016)

Cited

Latest update: 14 Dec 2024
Download
Short summary
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. 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.