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Identification of water quality and benthos characteristics in Daya Bay, China, from 2001 to 2004

Wang Y-S., Sun C-C., Lou Z-P., Wang H., Mitchell B.G., Wu M-L., Sun Z-X.

Oceanological and Hydrobiological Studies

2011

Vol. 40, No.1

82-95

Physicochemical and benthos data were collected from 12 marine monitoring stations in Daya Bay, during 2001-2004. 12 stations in Daya Bay could be grouped into three clusters: cluster I consisted of stations in the southern part of Daya Bay (stations S1, S2 and S6); cluster II consisted of stations in the cage culture areas (stations S3, S4, S5 and S8); cluster III consisted of stations in the southwest, the middle and the northeast of the Bay (stations S7, S9, S10, S11 and S12). Calculation with bivariate correlations between benthos and major physicochemical factors showed that the density of benthos in all stations correlated positively with temperature, DO, pH, NH4-N, SiO3-Si, SiO3-Si /PO4-P and chlorophyll a and was negatively correlated with salinity, Secchi, COD, NO3-N, NO2-N, TIN, PO4-P, TIN/PO4-P and BOD5. Factor analysis showed that there were high positive loading salinity, Secchi and NH4-N of three clusters. Results revealed that temperature, DO, pH, SiO3-Si and SiO3-Si/PO4-P and chlorophyll a could also play an important role in determining the biomass of benthos in Daya Bay, especially near the Nuclear Power Plants, in the southern part and in the cage culture areas.

Demonstration of a new indicator for studying upwelling in the northern South China Sea

Lin L., Wang Y-S., Sun C-C., Li N., Wang H., Mitchell B.G., Wu M-L., Song H., Wu J-F.

Oceanologia

2011

No. 53 (2)

605-622

In order to demonstrate that silicate can be used as an indicator to study upwelling in the northern South China Sea, hierarchical cluster analysis (CA) and principle component analysis (PCA) were applied to analyse the metrics of the data consisting of 14 physical-chemical-biological parameters at 32 stations. CA categorized the 32 stations into two groups (low and high nutrient groups). PCA was applied to identify five Principal Components (PCs) explaining 78.65% of the total variance of the original data. PCA found important factors that can describe nutrient sources in estuarine, upwelling, and non-upwelling areas. PC4, representing the upwelling source, is strongly correlated to silicate (SiO3-Si). The spatial distribution of silicate from the surface to 200 m depth clearly showed the upwelling regions, which is also supported by satellite observations of sea surface temperature.

Two models for absorption by coloured dissolved organic matter (CDOM)

Schwarz J. N., Kowalczuk P., Kaczmarek S., Cota G. F., Mitchell B. G., Kahru M., Chavez F. P., Cunningham A., McKee D., Gege P., Kishino M., Phinney D. A., Raine R.

Oceanologia

2002

No. 44 (2)

209-241

The standard exponential model for CDOM absorption has been applied to data from diverse waters. Absorption at 440 nm (ag440) ranged between close to zero and 10 m-1, and the slope of the semilogarithmic absorption spectrum over a minimum range of 400 to 440 nm (s440) ranged between < 0.01 and 0.04 nm-1. No relationship was found between ag440 or s440 and salinity. Except in the southern Baltic, s440 was found to have a broad distribution (0.0165 š 0.0035), suggesting that it should be introduced as an additional variable in bio-optical models when ag440 is large. An alternative model for CDOM absorption was applied to available high quality UV-visible absorption spectra from the Wisla river (Poland). This model assumes that the CDOM absorption spectrum comprises distinct Gaussian absorption bands in the UV, similar to those of benzene. Five bands were fit to the data. The mean central energy of all bands was higher in early summer (E~7.2, 6.6, 6.4, 6.2 and 5.5 eV or 172, 188, 194, 200 and 226 nm) than in winter. The higher energy bands were found to decay in both height and width with increasing salinity, while lower energy bands broadened with increasing salinity. s440 was found to be correlated with shape parameters of the bands centred at 6.4 and 5.5 eV. While the exponential model is convenient for optical modelling and remote sensing applications, these results suggest that the Gaussian model offers a deeper understanding of chemical interactions affecting CDOM molecular structure.