Modelling the speciation pattern of metals in Ondo coastal water with geochemical model – PHREEQCI

2012 ◽  
Vol 7 (3) ◽  
Author(s):  
Foluso O. Agunbiade ◽  
Bamidele I. Olu-Owolabi ◽  
Kayode O. Adebowale
Keyword(s):  
Coastal Water ◽  
Toxic Metals ◽  
Quality Parameters ◽  
Geochemical Model ◽  
Free Ion ◽  
Speciation Modelling ◽  
High Alkalinity ◽  
Ondo State ◽  
Fe Hydroxide ◽  
Ion Species

The speciation pattern of ten metals was studied in the coastal water of Ondo State, Nigeria using geochemical modelling software (PHREEQCI). The metals classified as macronutrients – Na, Ca, K, Mg; micronutrients – Fe, Cu, Mn, Zn; toxic metals – Cd, Pb were evaluated along with other general water quality parameters from ten sampling sites. The results served as input data for the modelling. The outcomes of the water speciation modelling revealed that the macronutrient metals exist as free ions which aid the reduction of free ion species of toxic metals. The micronutrients exist as neutral or complex salts which are less toxic according to free ion activity model theory. The self purification capacity of the coastal water was aided by the abundant formation of Fe-hydroxide precipitates; high alkalinity; pH; salinity of the coastal water which are responsible for the reduction of free ion specie of Pb and its ecotoxicity but increased the concentration of toxic Cd chloride species. Therefore, the prevailing biogeochemistry of the coast enhances demobilization of the metal contaminants and favours the reduction of their toxicity except Cd.

Influence of Seawater to the River Water Quality in Kalibuntung Estuary Southeastern Coast of Surabaya City Indonesia

2017 ◽  
Vol 862 ◽  
pp. 107-114
Author(s):  
Wahyudi ◽  
Suntoyo ◽  
Sholihin
Keyword(s):  
Water Quality ◽  
River Water ◽  
Coastal Water ◽  
Organic Waste ◽  
Water Movement ◽  
High Tide ◽  
River Mouth ◽  
Quality Parameters ◽  
Coastal Aquaculture ◽  
Nitrite Nitrate

This study reports distribution of water quality parameters, i.e. salinity, nitrite, nitrate, and phosphate of the Kalibuntung estuary in the southeastern Surabaya coastal area. The study was conducted over 34 sampling points in the river channel, river mouth, and in the coastal water of the Kalibuntung estuary. The result shows that the minimum salinity of (2-4 ppt) reached 3,000 m far from the coastline to upper strem. The maximum salinity of 28.60 ppt found in the coastal water, about 1,000 m seaward from coastline. Based on the numerical modeling analyses, distribution of salinity followed the water movement of eeb-flood currents cycles due to tidal fluctuation. The result obviously revealed that during flood current, water mass from the sea moves to the upper river, on the other hand, during eeb current more volume of river water flows to the sea. It is indicated by salinity values in the river mouth, which reached 27 ppt during high tide and < 20 ppt during low tide. Concentration of ammonia ranging from 0.42 mg/l in the lower part close to the river mouth, up to 6.13 mg/l in the uppermost of the river. This indicated that the river is heavily polluted by organic waste. Concentration of phosphate range from 0.06 to 0.43 mg/l. Its concentration decrease seaward, it is distributed to a distance of 3,000 m fom the river mouth. The river water of Kalibuntung estuary is not permitted to be used as a drinking water, and also it is not feasible for coastal aquaculture. Only in the lower part of the study area where it close to the rivermouth, its water can be used as a source of the coastal aquaculture. This research also found that the river water of the study area has already heavily polluted by organic waste, which it might come from domestic waste, agriculture or fertilizer for fishpond, or industrial organic waste.

scholarly journals Levels of Some Selected Heavy Metals in Groundwater in Ebubu Community, Eleme, Rivers State, Nigeria

2019 ◽  
pp. 1-5
Author(s):  
Sokpuwu Ikubor Austin ◽  
Keyword(s):  
Heavy Metals ◽  
Toxic Metals ◽  
Water Samples ◽  
Quality Parameters ◽  
Mean Value ◽  
Polluted Water ◽  
Periodic Analysis ◽  
Rivers State ◽  
Standard Techniques ◽  
Drinking Purpose

This study was carried out to assess the level of the presence of some selected heavy metals in borehole-drinking water of Ebubu community in Eleme between June and August. Water samples were collected from ten (10) functional boreholes using standard techniques. The levels of the heavy metals in the study area were found to be in the order: cadmium (0.361±0.381 mg/L), > lead (0.117±0.056 mg/L) > nickel (0.042±0.0281 mg/L) > cobalt (0.010±0.009 mg/L) in the water samples. These values were above the WHO and NIS limits. The water quality parameters varied across the sampling periods (June and August); apart from Cd whose mean value was higher during the month of June, but lower during the month of August, all other toxic metals (Ni, Pb, and Co). The groundwater from the community is therefore, unsafe for drinking purpose due to elevated levels of toxic metals. In light of these findings, periodic analysis of samples from boreholes is inevitable. Such analysis will reveal pollution status of groundwater in this area and to determine the best method for water treatment, to intimate consumers and other users of the groundwater, and also to safeguard their health against the subsequent impact that may arise from drinking polluted water

scholarly journals Assessment of Seasonal and Spatial Variations of Coastal Water Quality Using Multivariate Statistical Techniques

2021 ◽  
Vol 9 (11) ◽  
pp. 1292
Author(s):  
Mohamad Alkhalidi ◽  
Abdalrahman Alsulaili ◽  
Badreyah Almarshed ◽  
Majed Bouresly ◽  
Sarah Alshawish
Keyword(s):  
Water Quality ◽  
Coastal Water ◽  
Pearson Correlation ◽  
Chlorophyll Concentration ◽  
Principal Component ◽  
Quality Parameters ◽  
Statistical Techniques ◽  
Principal Component Factor Analysis ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical

This study investigates the seasonal and spatial trends in Kuwait’s coastal water’s physical, chemical, and biological parameters by applying multivariate statistical techniques, including cluster analysis (CA), principal component/factor analysis (PCA/FA), and the Pearson correlation (PC) method to the average daily reading of water quality parameters from fifteen stations over one year. The investigated parameters are pH, turbidity, chlorophyll-a, conductivity, dissolved oxygen (DO), phycoerythrin, salinity, and temperature. The results show that the coastal water of Kuwait is subjected to high environmental pressure due to natural and human interferences. During 2017, the DO levels were below the threshold limit, and at the same time, the water temperature and salinity were very high, causing a series of fish death events. CA resulted in three different regions based on the turbidity, including high, moderate, and low regions, and three seasons (winter, summer, and autumn). Spring is very short and overlaps with winter and summer. PCA/FA applied on the datasets assisted in extracting and identifying parameters responsible for the variations in the seasons and regions obtained from CA. Additionally, Pearson’s correlation resulted in a strong positive relation between chlorophyll and phycoerythrin in 7 out of the 15 stations. However, at high turbidity regions (stations 1 and 2), chlorophyll concentration was low. Additionally, the negative correlation between DO and temperature was observed at stations with rare human activities.

scholarly journals Sewage-specific enterococcal bacteriophages and multiple water quality parameters for coastal water quality assessment

2018 ◽  
Vol 79 (5) ◽  
pp. 799-807 ◽  
Author(s):  
Akechai Kongprajug ◽  
Namfon Booncharoen ◽  
Kanyaluck Jantakee ◽  
Natcha Chyerochana ◽  
Skorn Mongkolsuk ◽  
...  
Keyword(s):  
Water Quality ◽  
Multivariate Analysis ◽  
Coastal Water ◽  
Principal Component ◽  
Water Quality Assessment ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Quality Monitoring ◽  
Biological Parameters ◽  
Coastal Water Quality

Abstract Coastal water quality is deteriorating worldwide. Water quality monitoring is therefore essential for public health risk evaluation and the management of water bodies. This study investigated the feasibility of using bacteriophages of Enterococcus faecalis as sewage-specific faecal indicators, together with physicochemical (dissolved oxygen, pH, temperature and total suspended solids) and biological parameters, to assess coastal water quality using multivariate analysis incorporating non-detects. The principal component and cluster analyses demonstrated that coastal water quality was mostly influenced by biological parameters, including Escherichia coli and total coliforms, which were found in all 31 sampling sites, and enterococci, which was found in all but two sampling sites. The enterococcal bacteriophages AIM06 and SR14 were detected in 17 and 18 samples at concentrations up to 1,815 and 2,790 PFU/100 mL, respectively. Both bacteriophages co-presented in approximately 80% of phage-positive samples, and the concentrations at each site were not significantly different. Overall, either bacteriophage could be used to differentiate high- and low-level coastal water pollution, as grouped by cluster analysis. This study is the first to investigate the suitability of sewage-specific bacteriophages of E. faecalis for monitoring coastal water quality and emphasises the importance of a multivariate analysis with non-detects to facilitate coastal water quality monitoring and management.

scholarly journals Neural Network Implementations on the coastal water quality of Manora channel for the years 1996 to 2014.

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Water Quality ◽  
Coastal Water ◽  
Environmental Quality ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
The Other ◽  
Water Quality Parameters ◽  
National Environmental

Neural Networks is an Important Part of Computational Intelligence, Systems Theory and Signal Processing and finds numerous important applications in Science and Engineering. Sea water quality contaminates due to the severe untreated domestic, sewage and industrial pollutants. Presence of ammonia in seawater causes the deterioration of coastal water in terms of diminution of oxygen levels which suffocates the marine lives, fishes and mangroves. Industrial, sewage and domestic effluents carried by Lyari River contaminate the Manora channel, Karachi. The aim of study is to make the clear and transparent step-wise use of Artificial Neural Networks for the data driven water quality parameters models of Manora channel (Lyari river outfall zone N 24-51-26, E 66-58-01), Karachi (Pakistan) as well as to compare the pollutant contaminant ratio with the national environmental quality standard limits and other sampling sites of Manora channel and southern east Karachi coast. In this study, Manora channel Physico-chemical water quality parameters are assessed by using Artificial Neural Network taking Biochemical Oxygen Demand (BOD), chemical oxygen Demand (COD), Bicarbonates, potential Hydrogen(pH) , Chloride(Cl) as input and Ammonia(NH3)as output. Mean Square Error and R square are used for the model assessments statistical metrics. The computational work has been done by using R-studio. This is also found that Manora channel has the contaminated level of ammonia along the other sampling stations of both southern Karachi coast (N 24-47-03 E 67-08-39) as well as the other sampling site of Manora channel Karachi coast (N 24-50-15, E 66-58-01). In spite of all contamination Ammonia is found to be within National Environmental Quality Standards limits of Pakistan.

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