Crustal Thickness andVp/Vsin the Northeast China-North China Region and Its Geological Implication

2014 ◽  
Vol 57 (2) ◽  
pp. 166-176 ◽  
Author(s):  
GAO Yan-Guang ◽  
LI Yong-Hua
Keyword(s):  
Northeast China ◽  
North China ◽  
Crustal Thickness ◽  
North China Region ◽  
China Region ◽  
Geological Implication

scholarly journals Understanding meteorological influences on PM<sub>2.5</sub> concentrations across China: a temporal and spatial perspective

2018 ◽  
Vol 18 (8) ◽  
pp. 5343-5358 ◽  
Author(s):  
Ziyue Chen ◽  
Xiaoming Xie ◽  
Jun Cai ◽  
Danlu Chen ◽  
Bingbo Gao ◽  
...  
Keyword(s):  
North China ◽  
Meteorological Factors ◽  
Mapping Method ◽  
National Scale ◽  
The North ◽  
Spatial Differences ◽  
Meteorological Influences ◽  
Temporal And Spatial ◽  
North China Region ◽  
China Region

Abstract. With frequent air pollution episodes in China, growing research emphasis has been put on quantifying meteorological influences on PM2.5 concentrations. However, these studies mainly focus on isolated cities, whilst meteorological influences on PM2.5 concentrations at the national scale have not yet been examined comprehensively. This research employs the CCM (convergent cross-mapping) method to understand the influence of individual meteorological factors on local PM2.5 concentrations in 188 monitoring cities across China. Results indicate that meteorological influences on PM2.5 concentrations have notable seasonal and regional variations. For the heavily polluted North China region, when PM2.5 concentrations are high, meteorological influences on PM2.5 concentrations are strong. The dominant meteorological influence for PM2.5 concentrations varies across locations and demonstrates regional similarities. For the most polluted winter, the dominant meteorological driver for local PM2.5 concentrations is mainly the wind within the North China region, whilst precipitation is the dominant meteorological influence for most coastal regions. At the national scale, the influence of temperature, humidity and wind on PM2.5 concentrations is much larger than that of other meteorological factors. Amongst eight factors, temperature exerts the strongest and most stable influence on national PM2.5 concentrations in all seasons. Due to notable temporal and spatial differences in meteorological influences on local PM2.5 concentrations, this research suggests pertinent environmental projects for air quality improvement should be designed accordingly for specific regions.

Comparison of the Kriging and neural network methods for modeling foF2 maps over North China region

2015 ◽  
Vol 56 (1) ◽  
pp. 38-46 ◽  
Author(s):  
Chunhua Jiang ◽  
Chen Zhou ◽  
Jing Liu ◽  
Ting Lan ◽  
Guobin Yang ◽  
...  
Keyword(s):  
Neural Network ◽  
North China ◽  
Network Methods ◽  
North China Region ◽  
China Region

Transfers of embodied PM2.5 emissions from and to the North China region based on a multiregional input-output model

2018 ◽  
Vol 235 ◽  
pp. 381-393 ◽  
Author(s):  
Xue Yang ◽  
Wenzhong Zhang ◽  
Jie Fan ◽  
Jianhui Yu ◽  
Hongyan Zhao
Keyword(s):  
North China ◽  
Input Output ◽  
The North ◽  
North China Region ◽  
China Region ◽  
Pm2.5 Emissions

scholarly journals Forward Modeling Research of Gravity Data Offset in North China Region

2019 ◽  
Vol 04 (02) ◽  
pp. 79-88
Author(s):  
Dandan Li ◽  
Xingong Tang ◽  
Shuai Hou ◽  
Kui Xiang
Keyword(s):  
North China ◽  
Gravity Data ◽  
Forward Modeling ◽  
North China Region ◽  
China Region
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