Survey of the Ecological State of Eight Man-Made Lakes Within the City Limits of Freiburg, Germany

1992 ◽  
Vol 27 (2) ◽  
pp. 301-310
Author(s):  
Agnes G. Pulvermüller ◽  
Heidulf E. Müller

Abstract The survey of the ecological condition of eight lakes within the city limits of Freiburg included hydrochemical measurements and analyses (oxygen profiles, Secchi depth, pH, biochemical oxygen demand) together with biological parameters (chlorophyll a, phytoplanktonbiomass, Escherichia coli counts), as well as parasitic examinations. Only some of the investigated parameters are presented here. Seven of the eight lakes were found to be eutrophic. The process of eutrophication appears to be still in progress. One lake can be considered to be hypertrophic. Schistosome dermatitis was observed. The water quality in general was considered to be acceptable; suggestions to maintain or improve the water quality are made.

Author(s):  
H. Garba ◽  
C. A. Elanu

An assessment of the chemical characteristics of industrial and domestic wastewater discharges on seven parameters into Kaduna River on a bimonthly basis was carried out. PH, dissolved oxygen (DO), chloride, nitrite, chemical oxygen demand (COD), biochemical oxygen demand (BOD) and iron were analyzed to determine their concentration levels. From the analysis, the highest mean concentration of the parameters were 8.24 of pH, 7.7 mg/l of DO, 233.4 mg/l of chloride, 55.68 mg/l of COD, 27.95 mg/l of nitrite, 122.22 mg/l of BOD, and 17.05 mg/l of iron. After comparing with prescribed standards, it can be concluded that there is evidence of organic and inorganic accumulation of contaminants into River Kaduna.


2016 ◽  
Vol 47 (5) ◽  
pp. 1069-1085 ◽  
Author(s):  
Yung-Chia Chiu ◽  
Chih-Wei Chiang ◽  
Tsung-Yu Lee

The adaptive neuro fuzzy inference system (ANFIS) has been proposed to model the time series of water quality data in this study. The biochemical oxygen demand data collected at the upstream catchment of Feitsui Reservoir in Taiwan for more than 20 years are selected as the target water quality variable. The classical statistical technique of the Box-Jenkins method is applied for the selection of appropriate input variables and data pre-processing of using differencing is implemented during the model development. The time series data obtained by ANFIS models are compared to those obtained by autoregressive integrated moving average (ARIMA) and artificial neural networks (ANNs). The results show that the ANFIS model identified at each sampling station is superior to the respective ARIMA and ANN models. The R values at all sampling stations of the training and testing datasets are 0.83–0.98 and 0.81–0.89, respectively, except at Huang-ju-pi-liao station. ANFIS models can provide accurate predictions for complex hydrological processes, and can be extended to other areas to improve the understanding of river pollution trends. The procedure of input selection and the pre-processing of input data proposed in this study can stimulate the usage of ANFIS in other related studies.


2021 ◽  
Vol 5 (2) ◽  
pp. 112-116
Author(s):  
F., F. Akinola ◽  
M., O. Lasisi ◽  
B., S. Awe

Groundwater pollution has increased as a result of poor waste disposal practices in developing countries. The purpose of this study was to determine the levels of physicochemical parameters and heavy metal concentrations in order to investigate the impact of dumpsites on groundwater and soil quality in Erinfun community. Four (4) water samples were collected hand dug well and four (4) soil samples designated Ss1 to Ss4 were collected at distances of 10, 20, 30 and 40 m, respectively, away from the waste dumpsite. Physicochemical parameters and traces such as odour, colour, taste and temperature, as well as Biochemical Oxygen Demand, Chemical Oxygen Demand, Dissolve Oxygen, Total Dissolve Solid, pH, and chloride were measured in collected water samples. Collected soil samples were also analyzed for heavy metals such as Magnesium, Zinc, Iron, Chromium, and Lead. All the physical parameters of the water samples analysed were found not to be within the acceptable limit of World Health Organization and Nigerian Standard of Drinking Water Quality standards. The chemical constituents tested were within the acceptable limit of World Health Organization and Nigerian Standard of Drinking Water Quality except for the Biochemical Oxygen Demand, Chemical Oxygen Demand and Dissolve Oxygen of water samples 1 and 2, respectively. The concentration of trace metals in water sample test were within health limit except for Magnesium and Iron which has the highest concentrations in water sample 1 at 10 m away from dumpsite (61.00 mg/l and 0.46 mg/l). Consequently, open dumpsites are discouraged, and constructed standard landfills with appropriate monitoring guidelines are recommended.


2021 ◽  
Author(s):  
M. M. Majedul Islam ◽  
Md. Atikul Islam

Abstract Faecal contamination of surface water sources is an important water quality issue worldwide. Although quite a few studies exist on surface water faecal contamination and variability of indicator bacteria, most of the studies have been based on larger river basins and in temperate region. The variability is relatively unknown in local scale and in tropical developing countries. In this study we assess how anthropogenic and environmental factors affect faecal contamination and physicochemical parameters in Rupsha and Bhairab rivers around Khulna city, Bangladesh. Water samples were collected from six locations of the rivers during a wet and dry period in 2018 to measure Escherichia coli (E. coli) concentrations. Water physicochemical parameters—temperature, turbidity, pH, dissolved oxygen, biochemical oxygen demand and chemical oxygen demand were also measured. Higher concentrations of E. coli were found in the sampling sites located near the densely populated urban area compared to the downstream site, which receives fewer amounts of discharges from sewer drains. All the E. coli samples violated bathing water quality standards. E. coli concentrations were found to be correlated positively with precipitation and turbidity. A linear regression model was applied, that explains large part of the variation in E. coli concentration (R2 = 0.42). Water quality index assessment was also ranked the water quality as ‘poor’ category; indicate that the water is unsuitable for uses in domestic and recreational purposes and high health risks involved with the water use. The study findings highlight the problem of untreated sewage discharge into the rivers. Implementation of sewage treatment plant with adequate capacity is highly recommended.


2021 ◽  
Vol 26 (3) ◽  
pp. 75-84
Author(s):  
E. V. Tekanova ◽  
◽  
E. M. Makarova ◽  
N. M. Kalinkina ◽  
◽  
...  

Introduction. The Lososinka River is an urban tributary of Lake Onego, the lower reaches of which flow through the territory of Petrozavodsk city, receiving untreated drains of the city’s storm sewers. The river enters the Petrozavodsk Bay of Lake Onego, which is used as a source of public drinking water supply in the city. Methods. During the 2015 open water period, the oxygen concentration, total iron, color, pH, total suspended matter, biochemical oxygen demand (BOD5), content of oil products, and dichromate chemical oxygen demand were measured by standard methods in the water of the background and urban areas of the Lososinka River. Results. In the river water, high values of water color (132 mg/l Cr-Co), total iron (1.5 mg/l), dichromate chemical oxygen demand (23 mgO/l) were revealed, which is associated with the geochemical peculiarities of the surface waters in Karelia, enriched in the humic matter. Seasonal increases in the concentrations of these indicators were associated with floods. The oxygen saturation of the water reached 90% due to the fast current and riffles. The indicators of water pollution include total phosphorous (60 μg/l), mineral phosphorous (40 μg/l), BOD5 (1.5 mgO2/l), suspended matter (25.5 mg/l), and content of oil products (0.02 mg/l). Seasonal changes in these indicators were not associated with the hydrological regime of the river. In the storm sewers of the city, the maximum permissible concentrations for BOD5 are exceeded by 4 times, and for oil products — by 15 times. The Kruskal–Wallis test showed that all the studied chemical indicators in the urban and background areas of the river do not have significant differences. Conclusion. Water quality in the Lososinka River is considered satisfactory in terms of most of the studied parameters. According to the total iron content, the water is characterized as polluted, and according to water color, the river water is classified as dirty. The maximum permissible concentrations for total iron in the background and urban areas of the river were exceeded by 10 times. The standards for water quality adopted in the Russian Federation and the maximum permissible concentrations for total iron and water color are inapplicable for the water bodies in Karelia with high background values of these indicators. The trophic status of the river corresponds to the eutrophic state. Good saturation of the river water with oxygen hinders water pollution in the city territory due to self-purification processes.


2017 ◽  
Vol 1 (1) ◽  
pp. 25
Author(s):  
Jazmin Salguero ◽  
Jhonny Valverde Flores

The dumping of domestic and industrial wastewater is one of the major problems facing rivers, the high level of pollution directly affects aquatic and plant life. Producers living near to the Chillon River use these waters to irrigate their farms, many of the food products are taken to shopping centers in the city and then consumed by the population. Due to this reason, this research aims to reduce or eliminate pollutants by measuring the Biochemical Oxygen Demand (BOD); since it is considered as a test of great value in the analysis of sewage effluent or highly contaminated. The results show that the mean initial sample was 173 mg/L. after treatment at 15 minutes with air Micro Nanobubbles was obtained 53 mg/L and with ozone Micro Nanobubbles was obtained 53 mg/L. The best obtained efficiency was 69.36%


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