Investigating the Role of Meteorological Factors in the Vertical Variation in PM2.5 by Unmanned Aerial Vehicle Measurement
| Autor: | Zhanyong Wang, Ya Gao, Bai Li, Zhong-Ren Peng, Dongsheng Wang, Xiao-Bing Li, Si-Jia Lu |
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| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Aerosol and Air Quality Research. 19:1493-1507 |
| ISSN: | 2071-1409 1680-8584 |
| DOI: | 10.4209/aaqr.2018.07.0266 |
| Popis: | Clarifying the effects of meteorology on the vertical variation in PM2.5 is critical to understanding the formation of haze. We investigated the PM2.5 and synchronous meteorological variations in a three-dimensional space by measuring them with a lightweight unmanned aerial vehicle (UAV) equipped with portable monitors. Our field campaign was conducted on 5 separate days selected between August 2014 and February 2015 at altitudes ≤ 1000 m above a 4 × 4 km2 area in Lin’an, China. The UAV measurement was performed 4 times on each of the selected days, and every flight followed a designed spiral route from ground level up to an altitude of 1000 m. The PM2.5 mass concentration and meteorological factors, viz., the air temperature, relative humidity, dew point temperature and air pressure, were sampled at three-dimensional spatial locations during each flight. The measurements indicate that the PM2.5 distribution is more homogeneous horizontally than vertically. The PM2.5 concentration also decreases as the height increases; furthermore, it exhibits obvious stratification in the morning but more homogeneity in the afternoon. The concentrations above 500 m slightly rise in the afternoon , especially on days that display more stratification. The vertical gradient of the concentrations shows a decrease from the morning to the afternoon, which is smaller during winter than summer and autumn. Meteorologically induced changes in the planetary boundary layer height and inversion layer also significantly affect the PM2.5 variation in the lower troposphere. Our results serve as a reference for analyzing and forecasting PM2.5 pollution and provide a basis for smarter and more targeted air pollution management and governance. |
| Databáze: | OpenAIRE |
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