Investigating Vertical Distributions and Driving Factors of Black Carbon in the Atmospheric Boundary Layer Using Unmanned Aerial Vehicle Measurements in Shanghai, China

ATMOSPHERE(2023)

引用 0|浏览0
暂无评分
摘要
Black carbon (BC) is a significant component of fine particulate matter (PM2.5, with aerodynamic diameters <= 2.5 mu m), and its spatial distribution greatly affects the global radiation budget. However, the vertical distributions and key driving factors of BC in the atmospheric boundary layer, where BC is mostly concentrated, remain unclear. In this study, gradient measurements of BC were made using an unmanned aerial vehicle (UAV) platform from ground level to 500 m above ground level (AGL) during and after the 2016 G20 control period in Shanghai. Generally, vertical profiles of BC from local time (LT) 9 to 17 on all experimental days demonstrated an upward trend with increasing height. The BC emitted from chimneys was initially released at higher altitudes, resulting in the positive gradients of vertical BC profiles. Furthermore, with the progressive development of the boundary layer height from LT 9 to 15, the average concentration of BC per vertical profile decreased. However, meteorological conditions unfavorable for dispersions caused by particularly high temperatures, low wind speed, unfavorable boundary layer conditions, or especially high relative humidity, and hygroscopic growth owing to the extremely high relative humidity, led to an overall increase in vertical BC and ground-based PM2.5 and BC. Despite the impact of adverse meteorological conditions, emission control measures during the control period not only effectively decreased the BC concentration but also reduced the proportion of BC in PM2.5 in the atmospheric boundary layer. The results of this study can provide valuable observations for evaluating numerical model results and important implications for making control strategies of BC in the future.
更多
查看译文
关键词
unmanned aerial vehicle measurements,atmospheric boundary layer,black carbon
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要