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River biological oxygen demand

Fig. 5 Main contamination sources identified by PCA for sediments, fish, and suface water in the Ebro River basin, and explained variances for each principal component. Variable identification. Organic compounds in sediments 1, summatory of hexachlorocyclohexanes (HCHs) 2, summa-tory of DDTs (DDTs) 3, hexachlorobenzene (HCB) 4, hexachlorobutadiene (HCBu) 5, summatory of trichlorobenzenes (TCBs) 6, naphthalene 7, fluoranthene 8, benzo(a)pyrene 9, benzo(b) fluoranthene 10, benzo(g,h,i)perylene 11, benzo(k)fluoranthene 12, indene(l,2,3-cd)pyrene. Organic compounds in fish 1, hexachlorobenzene (HCB) 2, summatory of hexachlorocyclohexanes (HCHs) 3, o,p-DDD 4, o,p-DDE 5, o,p-DDT 6, p,p-DDD 7, />,/>DDE 8, />,/>DDT 9, summatory of DDTs (DDTs) 10, summatory of trichlorobenzenes (TCBs) 11, hexachlorobutadiene (HCBu) 12, fish length. Physico-chemical parameters in water 1, alkalinity 2, chlorides 3, cyanides 4, total coliforms 5, conductivity at 20°C 6, biological oxygen demand 7, chemical oxygen demand 8, fluorides 9, suspended matter 10, total ammonium 11, nitrates 12, dissolved oxygen 13, phosphates 14, sulfates 15, water temperature 16, air temperature... Fig. 5 Main contamination sources identified by PCA for sediments, fish, and suface water in the Ebro River basin, and explained variances for each principal component. Variable identification. Organic compounds in sediments 1, summatory of hexachlorocyclohexanes (HCHs) 2, summa-tory of DDTs (DDTs) 3, hexachlorobenzene (HCB) 4, hexachlorobutadiene (HCBu) 5, summatory of trichlorobenzenes (TCBs) 6, naphthalene 7, fluoranthene 8, benzo(a)pyrene 9, benzo(b) fluoranthene 10, benzo(g,h,i)perylene 11, benzo(k)fluoranthene 12, indene(l,2,3-cd)pyrene. Organic compounds in fish 1, hexachlorobenzene (HCB) 2, summatory of hexachlorocyclohexanes (HCHs) 3, o,p-DDD 4, o,p-DDE 5, o,p-DDT 6, p,p-DDD 7, />,/>DDE 8, />,/>DDT 9, summatory of DDTs (DDTs) 10, summatory of trichlorobenzenes (TCBs) 11, hexachlorobutadiene (HCBu) 12, fish length. Physico-chemical parameters in water 1, alkalinity 2, chlorides 3, cyanides 4, total coliforms 5, conductivity at 20°C 6, biological oxygen demand 7, chemical oxygen demand 8, fluorides 9, suspended matter 10, total ammonium 11, nitrates 12, dissolved oxygen 13, phosphates 14, sulfates 15, water temperature 16, air temperature...
Regression analysis in time series analysis is a very useful technique if an explanatory variable is available. Explanatory variables may be any variables with a deterministic relationship to the time series. VAN STRATEN and KOUWENHOVEN [1991] describe the dependence of dissolved oxygen on solar radiation, photosynthesis, and the respiration rate of a lake and make predictions about the oxygen concentration. STOCK [1981] uses the temperature, biological oxygen demand, and the ammonia concentration to describe the oxygen content in the river Rhine. A trend analysis of ozone data was demonstrated by TIAO et al. [1986]. [Pg.219]

Fig. 8-6. Multivariate correlation coefficients between the sampling points on the river Saale for the water components nitrate and ammonium and the collective parameters conductivity, total hardness, dissolved oxygen, biological oxygen demand, and chemical oxygen demand... Fig. 8-6. Multivariate correlation coefficients between the sampling points on the river Saale for the water components nitrate and ammonium and the collective parameters conductivity, total hardness, dissolved oxygen, biological oxygen demand, and chemical oxygen demand...
Biochemical oxygen demand (BOD) is arguably the oldest total parameter used for the characterization of water quality. It was introduced in the first decade of the twentieth century as a test for the organic pollution of rivers. BOD is the amount of oxygen in mg L 1 required for the oxidation of the organic matter contained in water by biological action under standardized test conditions (usually a temperature of 20°C and an incubation time of 5 days).8 9 The test is often used to evaluate the efficiency of wastewater treatment processes. [Pg.224]

Interpretation of the hierarchical dendrogram for the clustering of chemical variables shows clearly that three major clusters are formed. One of them shows up the close relation between nitrite content and oxygen content in the river water. This is an important indicator regarding the processes involving oxygen demand and oxidation, which are important in biological transformations. The... [Pg.374]


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