Measurements of atmospheric aerosol vertical distribution above North China Plain using hexacopter

2019 ◽  
Vol 665 ◽  
pp. 1095-1102 ◽  
Author(s):  
Yishu Zhu ◽  
Zhijun Wu ◽  
Yonghee Park ◽  
Xiaobo Fan ◽  
Dong Bai ◽  
...  
2021 ◽  
Author(s):  
Hao Luo ◽  
Li Dong ◽  
Yichen Chen ◽  
Yuefeng Zhao ◽  
Delong Zhao ◽  
...  

Abstract. Aerosol-planetary boundary layer (PBL) interaction has been proposed as a key mechanism for stabilizing the atmosphere and exacerbating surface air pollution. Although the understanding of this process has progressed enormously, its magnitude and impact remain uncertain and vary widely concerning aerosol types, vertical distributions, synoptic conditions, etc. In this study, our primary interest is to distinguish the aerosol-PBL interaction of absorbing and scattering aerosols under contrasting synoptic patterns and aerosol vertical distributions. Detailed in-situ aircraft (KingAir-350) measurements and online coupled model Weather Research and Forecasting with Chemistry (WRF-Chem) simulations are explored over the North China Plain (NCP). Furthermore, a long-term PBL stability trend from 1980 to 2020 over the NCP is also investigated. The aircraft measurements and surface observations show that the surface air pollution over the Baoding City on 3 January is heavier than that on 4 January, 2020. In addition, the aerosols are restricted to the low layer on 3 January, whereas the aerosols mix more homogeneous upwards on 4 January. Thereupon, we focus on the two days with distinct synoptic circumstances, PBL stability, and aerosol vertical distributions over the NCP. According to the WRF-Chem modelling, the synoptic pattern over the Baoding City differs between the two days. The prevailing wind direction is opposite with a southwest wind on 3 January and a northeast wind on 4 January. The results indicate that the synoptic condition may affect the PBL thermal structure, thus affecting the aerosol vertical distribution. Additionally, the sensitive numerical experiments reveal that the light-absorbing and light-scattering aerosols have different effects on altering the PBL thermal structure. The inhibition effect of scattering aerosols on the PBL appears to be independent of the aerosol height distribution and solely depends on its concentration. However, aerosol-PBL feedback of absorbing aerosols is highly dependent on its vertical distribution. Our analysis highlights that we should principally concentrate on controlling the emissions of scattering aerosols under the stable stratification while cooperating to control the emissions of scattering and absorbing aerosols in an unstable stratification. Moreover, the long-term inter-annual variation in PBL stability shows a strong correlation with the East Asian Winter Monsoon, which seems to be valuable in determining which pollutants to target in different monsoon years and attaining more precise air pollution control. Based on the numerical simulations and observational constraints, a concept scheme description has been concluded to deepen our recognition of the interactions between thermodynamic stability and aerosols within the PBL over the NCP region.


Author(s):  
Min Xue ◽  
Jianzhong Ma ◽  
Guiqian Tang ◽  
Shengrui Tong ◽  
Bo Hu ◽  
...  

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 46
Author(s):  
Gangqiang Zhang ◽  
Wei Zheng ◽  
Wenjie Yin ◽  
Weiwei Lei

The launch of GRACE satellites has provided a new avenue for studying the terrestrial water storage anomalies (TWSA) with unprecedented accuracy. However, the coarse spatial resolution greatly limits its application in hydrology researches on local scales. To overcome this limitation, this study develops a machine learning-based fusion model to obtain high-resolution (0.25°) groundwater level anomalies (GWLA) by integrating GRACE observations in the North China Plain. Specifically, the fusion model consists of three modules, namely the downscaling module, the data fusion module, and the prediction module, respectively. In terms of the downscaling module, the GRACE-Noah model outperforms traditional data-driven models (multiple linear regression and gradient boosting decision tree (GBDT)) with the correlation coefficient (CC) values from 0.24 to 0.78. With respect to the data fusion module, the groundwater level from 12 monitoring wells is incorporated with climate variables (precipitation, runoff, and evapotranspiration) using the GBDT algorithm, achieving satisfactory performance (mean values: CC: 0.97, RMSE: 1.10 m, and MAE: 0.87 m). By merging the downscaled TWSA and fused groundwater level based on the GBDT algorithm, the prediction module can predict the water level in specified pixels. The predicted groundwater level is validated against 6 in-situ groundwater level data sets in the study area. Compare to the downscaling module, there is a significant improvement in terms of CC metrics, on average, from 0.43 to 0.71. This study provides a feasible and accurate fusion model for downscaling GRACE observations and predicting groundwater level with improved accuracy.


Author(s):  
Weiqi Xu ◽  
Chun Chen ◽  
Yanmei Qiu ◽  
Conghui Xie ◽  
Yunle Chen ◽  
...  

Organic aerosol (OA), a large fraction of fine particles, has a large impact on climate radiative forcing and human health, and the impact depends strongly on size distributions. Here we...


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