Wei Wang
8 Papers
1 Citations
Wei Wang is an academic researcher. The author has contributed to research in topics: Medicine & Air quality index. The author has an hindex of 1, co-authored 2 publications.
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Papers
Sector‐Based Top‐Down Estimates of NO x , SO2, and CO Emissions in East Asia
TL;DR: In this paper , a sector-based 4D-Var framework based on the GEOS-Chem adjoint model was developed to address the impacts of co-emissions and chemical interactions on top-down emission estimates.
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[Concentration Characteristics and Assessment of Model-Predicted Results of PM 2.5 in the Beijing-Tianjin-Hebei Region in Autumn and Winter]
Yuanyuan Zhu,Yu-Xiao Gao,Bing Liu,Xiao-Yan Wang,Lili Zhu,Rong Xu,Wei Wang,Jun-Nan Ding,Jian-Jun Li,Xiaoli Duan +9 more
- 08 Dec 2019
TL;DR: The models performed well in forecasting Zhangjiakou, Chengde, and Qinhuangdao, but by contrast overestimated in Tangshan, Shijiazhuang, Baoding, Beijing, and Tianjin, where the uncertainty of emission sources, measured and predicted meteorological data, and the atmospheric chemical reaction mechanism may be the main reasons for the overestimate.
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[Variations in Ozone Concentration in Seven Regions Under Different Temperature and Humidity Conditions].
Jing-da Liu,Chao He,Shu-Man Zhao,Jun Zhu,Wei Wang,Li-Li Wang,Yue-Si Wang +6 more
- 08 Oct 2023
TL;DR: Variations in ozone concentration in seven regions under different temperature and humidity conditions in China show a positive correlation with temperature and a nonlinear relationship with humidity.
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[Characteristics of Ozone Pollution, Meteorological Impact, and Evaluation of Forecasting Results Based on a Neural Network Model in Beijing-Tianjin-Hebei Region].
Yuanyuan Zhu,Bing Liu,Hai-Lin Gui,Jianjun Li,Wei Wang +4 more
- 08 Aug 2022
TL;DR: In this paper , the ozone concentration characteristics of 13 cities in Beijing-Tianjin-Hebei regions from 2016 to 2020 were analyzed based on ecological environment monitoring and meteorological observation data.
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[Comparison and Analysis of PM2.5 Forecast in Key Areas Based on the Neural Network Model and Numerical Model].
Yu-Xiao Gao,Wei Wang,Yongtai Huang,Xiaoyan Wang,Yuanyuan Zhu,Lili Zhu,Rong Xu,Jian-Jun Li +7 more
- 08 Feb 2022
TL;DR: In this paper , the PM2.5 forecast effects of the three methods were analyzed and evaluated, and the results showed that the performance of the short-term forecast based on the BP neural network was relatively good but was reduced in the medium and long term and systematically overestimated in four regions.
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