scholarly journals Temporal and spatial distributions of precipitation on the Huang-Huai-Hai Plain during 1960–2019, China

2021 ◽  
Author(s):  
Minhua Ling ◽  
Hongbao Han ◽  
Xingling Wei ◽  
Cuimei Lv
Keyword(s):  
Spatial Distribution ◽  
Large Scale ◽  
Kendall Test ◽  
Winter Precipitation ◽  
Annual Precipitation ◽  
Temporal And Spatial Distribution ◽  
Global Pattern ◽  
The North ◽  
Variance Contribution ◽  
Temporal And Spatial

Abstract The Huang-Huai-Hai Plain is an important commercial grain production base in China. Understanding the temporal and spatial variations in precipitation can help prevent drought and flood disasters and ensure food security. Based on the precipitation data for the Huang-Huai-Hai Plain from 1960 to 2019, this study analysed the spatiotemporal distribution of total precipitation at different time scales using the Mann–Kendall test, the wavelet analysis, the empirical orthogonal function (EOF), and the centre-of-gravity model. The results were as follows: (1) The winter precipitation showed a significant upward trend on the Huang-Huai-Hai Plain, while other seasonal trends were not significant. (2) The precipitation on the Huang-Huai-Hai Plain shows a zonal decreasing distribution from southeast to northwest. (3) The application of the EOF method revealed the temporal and spatial distribution characteristics of the precipitation field. The cumulative variance contribution rate of the first two eigenvectors reached 51.5%, revealing two typical distribution fields, namely a ‘global pattern’ and a ‘north-south pattern’. The ‘global pattern’ is the decisive mode, indicating that precipitation on the Huang-Huai-Hai Plain is affected by large-scale weather systems. (4) The annual precipitation barycentres on the Huang-Huai-Hai Plain were located in Jining city and Taian city, Shandong Province, and the spatial distribution pattern was north-south. The annual precipitation barycentres tended to move southwest, but the trend was not obvious. The annual precipitation barycentre is expected to continue to shift to the north in 2020.

scholarly journals Investigations of temporal and spatial distribution of precursors SO<sub>2</sub> and NO<sub>2</sub> vertical columns in the North China Plain using mobile DOAS

2018 ◽  
Vol 18 (3) ◽  
pp. 1535-1554 ◽  
Author(s):  
Fengcheng Wu ◽  
Pinhua Xie ◽  
Ang Li ◽  
Fusheng Mou ◽  
Hao Chen ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Air Quality ◽  
North China Plain ◽  
North China ◽  
Emission Sources ◽  
Temporal And Spatial Distribution ◽  
Air Mass ◽  
The North ◽  
The North China Plain ◽  
Temporal And Spatial

Abstract. Recently, Chinese cities have suffered severe events of haze air pollution, particularly in the North China Plain (NCP). Investigating the temporal and spatial distribution of pollutants, emissions, and pollution transport is necessary to better understand the effect of various sources on air quality. We report on mobile differential optical absorption spectroscopy (mobile DOAS) observations of precursors SO2 and NO2 vertical columns in the NCP in the summer of 2013 (from 11 June to 7 July) in this study. The different temporal and spatial distributions of SO2 and NO2 vertical column density (VCD) over this area are characterized under various wind fields. The results show that transport from the southern NCP strongly affects air quality in Beijing, and the transport route, particularly SO2 transport on the route of Shijiazhuang–Baoding–Beijing, is identified. In addition, the major contributors to SO2 along the route of Shijiazhuang–Baoding–Beijing are elevated sources compared to low area sources for the route of Dezhou–Cangzhou–Tianjin–Beijing; this is found using the interrelated analysis between in situ and mobile DOAS observations during the measurement periods. Furthermore, the discussions on hot spots near the city of JiNan show that average observed width of polluted air mass is 11.83 and 17.23 km associated with air mass diffusion, which is approximately 60 km away from emission sources based on geometrical estimation. Finally, a reasonable agreement exists between the Ozone Monitoring Instrument (OMI) and mobile DOAS observations, with a correlation coefficient (R2) of 0.65 for NO2 VCDs. Both datasets also have a similar spatial pattern. The fitted slope of 0.55 is significantly less than unity, which can reflect the contamination of local sources, and OMI observations are needed to improve the sensitivities to the near-surface emission sources through improvements of the retrieval algorithm or the resolution of satellites.

Analysis of temporal and spatial distribution and change-points for annual precipitation in Kansas, USA

2015 ◽  
Vol 35 (13) ◽  
pp. 3879-3887 ◽  
Author(s):  
Vahid Rahmani ◽  
Stacy L. Hutchinson ◽  
John A. Harrington Jr ◽  
J. M. Shawn Hutchinson ◽  
Aavudai Anandhi
Keyword(s):  
Spatial Distribution ◽  
Change Points ◽  
Annual Precipitation ◽  
Temporal And Spatial Distribution ◽  
Temporal And Spatial

scholarly journals Study on Spatial Distribution Characteristics of Industrial Pollution Sources in 2008

2021 ◽  
Vol 257 ◽  
pp. 03012
Author(s):  
Kecheng Peng ◽  
Xiaoqun Cao ◽  
Wenlong Tian
Keyword(s):  
Spatial Distribution ◽  
Environmental Governance ◽  
Northern China ◽  
Pollutant Emissions ◽  
Distribution Characteristics ◽  
Temporal And Spatial Distribution ◽  
The North ◽  
Spatial Distribution Characteristics ◽  
Temporal And Spatial ◽  
The Difference

With the continuous development of China’s economy, the problems of pollutant emissions and environmental governance are gradually emerging. Based on the monthly data of man-made emission sources in Asia from the 2008 East Asia MIX emission inventory, this study analyzed the temporal and spatial distribution characteristics of air pollutants including PM2.5, PM10, CO, CO2, NOx, OC, etc., and explored the difference and variation law of material concentration distribution between designated special regions, as well as the possible impact of various atmospheric systems on them. Firstly, in most areas of China, the distribution of pollutants has obvious temporal and spatial differences, and the overall trend of pollutant concentration is higher in the north than in the south. The results show that the monthly variation trend of pollutants in India is significantly correlated with that in China. However, compared with the monthly trend in northern China, it is not particularly obvious.

Sign in / Sign up

Export Citation Format

Share Document