scholarly journals Intercomparison of Multiple Satellite Aerosol Products against AERONET over the North China Plain

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 480 ◽  
Author(s):  
Fan ◽  
Xia ◽  
Chen
Keyword(s):  
North China Plain ◽  
North China ◽  
Sampling Rate ◽  
The Other ◽  
Wide Field ◽  
Advantages And Disadvantages ◽  
The North ◽  
The North China Plain ◽  
Data Volume ◽  
Better Than

In this study, using Aerosol Robotic Network aerosol optical depth (AOD) products at three stations in the North China Plain (NCP)—a heavily polluted region in China—the AOD products from six satellite-borne radiometers: the Moderate Resolution Imagining Spectroradiometer (MODIS), the Multiangle Imaging Spectroradiometer (MISR), Ozone Mapping Imaging (OMI), the Visible Infrared Imaging Radiometer (VIIRS), the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), and Polarization and Directionality of the Earth’s Reflectances (POLDER), were thoroughly validated, shedding new light on their advantages and disadvantages. The MODIS Deep Blue (DB) products provide more accurate retrievals than the MODIS Dark Target (DT) and other satellite products at the Beijing site (BJ,a megacity), with higher correlations with AERONET (R > 0.93), lower mean absolute bias (MB < 0.012), and higher percentages (>68%) falling within the expected error (EE). All MODIS DT and DB products perform better than the other satellite products at the Xianghe site (XH, a suburb). The MODIS/Aqua DT products at both 3-km and 10-km resolutions performed better than the other space-borne AOD products at the Xinglong site (XL, a rural area at the top of a mountain). MISR, VIIRS, and SeaWiFS tend to underestimate high AOD values and overestimate AOD values under very low AOD conditions in the NCP. Both OMI and POLDER significantly underestimate the AOD. In terms of data volume, MISR with the limited swath width of 380 km has less data volume than the other satellite sensors. MODIS products have the highest sampling rate, especially the MODIS DT and DB merged products, and can be used for various climate study and air-quality monitoring.

scholarly journals Analysis of a winter regional haze event and its formation mechanism in the North China Plain

2013 ◽  
Vol 13 (11) ◽  
pp. 5685-5696 ◽  
Author(s):  
X. J. Zhao ◽  
P. S. Zhao ◽  
J. Xu ◽  
W. Meng, ◽  
W. W. Pu ◽  
...  
Keyword(s):  
North China Plain ◽  
North China ◽  
The Other ◽  
Plain Area ◽  
The North ◽  
The North China Plain ◽  
Secondary Formation ◽  
Regional Haze ◽  
Haze Episode ◽  
Haze Days

Abstract. A regional haze episode occurred in the Beijing, Tianjin and Hebei province (BTH) area in the North China Plain (NCP) from 16 to 19 January 2010. Data were collected and analyzed during the time frame of 14 through 23 January 2010 to include the haze event. The increase of secondary inorganic pollutants (SO42−, NO3−, NH4+) in PM2.5 was observed simultaneously at four sites, especially in the plain area of the BTH, which could be identified as a common characteristic of pollution haze in east China. The sulfate and nitrate in PM2.5 were mainly formed through the heterogeneous reaction process in the urban area. The organic matter (OM) increased more significantly at the Chengde (CD) site than the other three sites in the plain area. The secondary organic aerosols only existed during haze days at CD but in both haze and non-haze days at the other three sites, which suggested the greater regional impact of secondary formation process during the haze episode. The secondary formation of aerosol was one important formation mechanism of haze. The strong temperature inversion and descending air motions in the planetary boundary layer (PBL) allowed pollutants to accumulate in a shallow layer. The weak surface wind speed produced high pollutants concentration within source regions. The accumulation of pollutants was one main factor in the haze formation. The enhanced southwest wind in the last period of this episode transported pollutants to the downwind area and expanded the regional scope of the haze.

ROx Budgets and O3 Formation during Summertime at Xianghe Suburban Site in the North China Plain

2021 ◽  
Author(s):  
Min Xue ◽  
Jianzhong Ma ◽  
Guiqian Tang ◽  
Shengrui Tong ◽  
Bo Hu ◽  
...  
Keyword(s):  
North China Plain ◽  
North China ◽  
The North ◽  
The North China Plain ◽  
Suburban Site

scholarly journals Improving the Resolution and Accuracy of Groundwater Level Anomalies Using the Machine Learning-Based Fusion Model in the North China Plain

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 46
Author(s):  
Gangqiang Zhang ◽  
Wei Zheng ◽  
Wenjie Yin ◽  
Weiwei Lei
Keyword(s):  
Machine Learning ◽  
Data Fusion ◽  
Groundwater Level ◽  
North China Plain ◽  
North China ◽  
Gradient Boosting ◽  
Fusion Model ◽  
The North ◽  
The North China Plain ◽  
Prediction Module

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.

scholarly journals The water-saving potential of using micro-sprinkling irrigation for winter wheat production on the North China Plain

2021 ◽  
Vol 20 (6) ◽  
pp. 1687-1700
Author(s):  
Li-chao ZHAI ◽  
Li-hua LÜ ◽  
Zhi-qiang DONG ◽  
Li-hua ZHANG ◽  
Jing-ting ZHANG ◽  
...  
Keyword(s):  
Winter Wheat ◽  
North China Plain ◽  
North China ◽  
Water Saving ◽  
Wheat Production ◽  
The North ◽  
The North China Plain

scholarly journals Corrigendum to “Folate content analysis of wheat cultivars developed in the North China Plain” [289 (2019) 377–383]

2021 ◽  
Vol 351 ◽  
pp. 129349
Author(s):  
Bisma Riaz ◽  
Qiuju Liang ◽  
Xing Wan ◽  
Ke Wang ◽  
Chunyi Zhang ◽  
...  
Keyword(s):  
Content Analysis ◽  
North China Plain ◽  
North China ◽  
Wheat Cultivars ◽  
The North ◽  
The North China Plain
Sign in / Sign up

Export Citation Format

Share Document