Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China.
Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China.
Sci Total Environ. 2021 Feb 20;756:144135. doi: 10.1016/j.scitotenv.2020.144135. Epub 2020 Nov 26.
Owing to a lack of vertical observations, the impacts of black carbon (BC) on radiative forcing (RF) have typically been analyzed using ground observations and assumed profiles. In this study, a UAV platform was used to measure high-resolution in-situ vertical profiles of BC, fine particles (PM), and relevant meteorological parameters in the boundary layer (BL). Further, a series of calculations using actual vertical profiles of BC were conducted to determine its impact on RF and heating rate (HR). The results show that the vertical distributions of BC were strongly affected by atmospheric thermodynamics and transport. Moreover. Three main types of profiles were revealed: Type I, Type II, Type III, which correspond to homogenous profiles (HO), negative gradient profiles (NG), and positive gradient profiles (PG), respectively. Types I and II were related to the diurnal evolution of the BL, and Type III was caused by surrounding emissions from high stacks and regional transport. There were no obvious differences in RF calculated for HO profiles and corresponding surface BC concentrations, unlike for NG and PG profiles. RF values calculated using surface BC concentrations led to an overestimate of 13.2 W m (27.5%, surface) and 18.2 W m (33.4%, atmosphere) compared to those calculated using actual NG profiles, and an underestimate of approximately 15.4 W m (35.0%, surface) and 16.1 W m (29.9%, atmosphere) compared to those calculated using actual PG profiles. In addition, the vertical distributions of BC HR exhibited clear sensitivity to BC profile types. Daytime PG profiles resulted in a positive vertical gradient of HR, which may strengthen temperature inversion at high altitudes. These findings indicate that calculations that use BC surface concentrations and ignore the vertical distribution of BC will lead to substantial uncertainties in the effects of BC on RF and HR.
由于缺乏垂直观测，通常使用地面观测和假设廓线来分析黑碳 (BC) 对辐射强迫 (RF) 的影响。在这项研究中，使用无人机平台测量了边界层 (BL) 中 BC、细颗粒物 (PM) 和相关气象参数的高分辨率原位垂直廓线。此外，还使用实际的 BC 垂直廓线进行了一系列计算，以确定其对 RF 和加热率 (HR) 的影响。结果表明，BC 的垂直分布强烈受到大气热力学和输送的影响。此外，揭示了三种主要的廓线类型：I 型、II 型和 III 型，分别对应于均匀廓线 (HO)、负梯度廓线 (NG) 和正梯度廓线 (PG)。I 型和 II 型与 BL 的日变化有关，而 III 型则是由周围高烟囱排放和区域输送引起的。对于 HO 廓线和相应的表面 BC 浓度计算的 RF 没有明显差异，而对于 NG 和 PG 廓线则不同。与使用实际 NG 廓线计算的 RF 值相比，使用表面 BC 浓度计算的 RF 值高估了 13.2 W m （27.5%，表面）和 18.2 W m （33.4%，大气），而与使用实际 PG 廓线计算的 RF 值相比，低估了约 15.4 W m （35.0%，表面）和 16.1 W m （29.9%，大气）。此外，BC HR 的垂直分布对 BC 廓线类型表现出明显的敏感性。白天 PG 廓线导致 HR 出现正垂直梯度，这可能会加强高空温度逆温。这些发现表明，使用 BC 表面浓度且忽略 BC 垂直分布的计算会导致 BC 对 RF 和 HR 的影响产生重大不确定性。
