Mass balances of major chemical constitutents in Bohai Sea water I. Sources

1994 ◽  
Vol 12 (1) ◽  
pp. 71-77 ◽  
Author(s):  
Li Yue
Keyword(s):  
Bohai Sea ◽  
Sea Water ◽  
Mass Balances ◽  
Major Chemical

Design Considerations for Space Mission Washwater Processing by Reverse Osmosis

1973 ◽  
Vol 95 (4) ◽  
pp. 1030-1038
Author(s):  
G. W. Wells ◽  
W. Wong ◽  
D. F. Putnam
Keyword(s):  
Reverse Osmosis ◽  
Chemical Constituents ◽  
Theoretical Estimate ◽  
Space Mission ◽  
Wash Water ◽  
Personal Hygiene ◽  
Published Data ◽  
Mass Balances ◽  
Major Chemical ◽  
The Impact

Reverse osmosis (RO) is shown to be a promising method of reclaiming wash water. The amounts of wash water and cleansing agent required for showering, personal hygiene, housekeeping, dish washing, laundry, and experiment purposes are presented and the impact of clothing types and laundry schedule are discussed. A theoretical estimate of the contaminants found in wash water is made based on published data for sebum, sweat, and other body excretions. An analytical method for calculating mass balances in a reverse osmosis recycle system is presented and concentrations of the major chemical constituents expected in the RO feed, product and brine streams are projected.

scholarly journals SHALLOW BATHYMETRY ESTIMATION BASED ON LANDSAT 8 REMOTELY SENSED DATAAT BOHAI SEA

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 941-943
Author(s):  
D. J. Zhang ◽  
J. Zhan ◽  
C. X. Wang ◽  
G. Q. Zhou
Keyword(s):  
Water Depth ◽  
Bohai Sea ◽  
Sea Water ◽  
Absolute Error ◽  
Inversion Method ◽  
Band Model ◽  
Landsat 8 ◽  
Ocean Monitoring ◽  
The Relationship ◽  
Monitoring And Measurement

Abstract. Bathymetry is a key variable in ocean monitoring and measurement research. It becomes more and more important for development of rapid method to invert shallow sea water depth. In this study, a water depth inversion method based on multi-band model is established to analyze the relationship between different bands of Landsat 8 OLI multi-spectral and measured data. The average absolute error of the model is 1.48m at 10–20m water depth and the average relative error is 13.12%. The water depth inversion accuracy under normal conditions are achieved, indicating that the model will have a promising practical application in the future.

scholarly journals The Yellow Sea Warm Current flushes the Bohai Sea microbial community in winter

2020 ◽  
Vol 71 (12) ◽  
pp. 1616
Author(s):  
Caixia Wang ◽  
Yibo Wang ◽  
Pengyuan Liu ◽  
Lin Wu ◽  
James S. Paterson ◽  
...  
Keyword(s):  
Yellow Sea ◽  
Bohai Sea ◽  
Heterotrophic Bacteria ◽  
Cold Water ◽  
Sea Water ◽  
The Yellow Sea ◽  
Effect Of Temperature ◽  
Yellow Sea Warm Current ◽  
Warm Current ◽  
The Bohai Sea

The effect of the Yellow Sea Warm Current (YSWC) on virio- and bacterioplankton communities in the Bohai Sea is unknown. In this study, the composition and dynamic changes of virio- and bacterioplankton at the entrance of the Bohai Sea were measured to determine the influence of the YSWC on those communities and vice versa. In the Bohai Strait, there were east to west gradients of water chemistry and hydrology. The turbulent mixing between the deep north-western ‘warm’ current, which is 9°C, and the cold, nutrient-rich Bohai Sea water at 7–8°C appears to stimulate the abundance of both viruses and heterotrophic bacteria, with numbers at the junction of ‘warm’ and cold water being almost 10-fold greater than in the low-thermohaline areas, and peaking where the temperature is the highest. The average viral and bacterial abundances in the north-eastern area are much higher than in the south-western area. It proved that the YSWC entered the Bohai Sea with poor biomass and exited with rich biomass, which, in turn, enriches the Yellow Sea microbial loop. Our results showed the dramatic effect of temperature rise and increasing eutrophication on microbial abundance and marine microbial communities.

Spectral similarity algorithm-based image classification for oil spill mapping of hyperspectral datasets

2020 ◽  
Author(s):  
Deepthi ◽  
Tessamma Thomas
Keyword(s):  
Oil Spill ◽  
Bohai Sea ◽  
Sea Water ◽  
Hybrid Algorithms ◽  
Chi Square ◽  
Spectral Similarity ◽  
Spectral Discrimination ◽  
Similarity Algorithm ◽  
Hyperion Image ◽  
Better Than

In remote sensing, the compositional information of part of the earth’s surface is statistically evaluated by comparing known field or library spectra with the unknown image spectra, known as spectral matching or spectral similarity analysis. In this research, hybrid spectral similarity algorithms developed based on chi-square distance (CHI or χ2) are used to retrieve useful information from the Hyperion hyperspectral oil spill image covering the area near Liaodong Bay of the Bohai Sea, China. In order to evaluate the discriminability of spectral similarity algorithms, a pixel-level matching is carried out between the reference vectors, viz. Oil Slick (O), Sheen (H), Sea Water (S) and Ship Track (T), collected visually from known areas in the image. The hybrid spectral similarity algorithms are statistically assessed for their performance using the spectral discriminatory measures (i) relative spectral discriminatory power (RSDPW), (ii) relative spectral discriminatory probability (RSDPB) and (iii) relative spectral discriminatory entropy (RSDE). Additionally, the selected hybrid algorithms are used on the Hyperion image subset to perform a pixel-based classification. Classification results revealed that the CHI-based hybrid algorithms performed better than all other hybrid spectral similarity methods. Therefore, the CHI-based hybrid algorithms demonstrated their superior spectral discrimination capacity to classify marine spectral classes for oil spill mapping from the hyperspectral dataset.

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