ISSN: 2637-4668
Ezeilo FE1* and Eluozo SN2
Received: January 04, 2021 Published: January 21, 2021
Corresponding author: Ezeilo FE, Department of Civil Engineering, Rivers State University of Nkpolu Oroworukwo, Port Harcourt, Nigeria
DOI: 10.32474/TCEIA.2021.04.000181
Phosphorus as one of the microelement was observed to predominantly deposit in the study environment, this were experienced from physiochemical investigation carried out in the stream, the examination observed the predominant deposition of increased phosphorus in different station point of discharge, this implies that there are some significant factors causing such increase of the contaminant in the stream, the evaluation generated other parameters that could influenced the exponential state of the contaminant, such condition call for serious concern, thus thorough examination of these parameters that affect the growth rate of phosphorus in the stream, the transport of this microelement experienced increase in all the figures based on the points source of discharge monitored, derived model were applied to monitor the behaviour of phosphorus in the stream, this were carried out through model and simulation, the system monitored other influential parameters that pressured the growth rate of the contaminant at different point source, gradual growth rate to the optimum level were experienced based on the continuity process of phosphorus substance discharged in the stream, the study also observed other effect from phosphorus deposition at high rate in the stream, the substance were observed in the stream to increase rapid rate of microbes in the stream, an increase of Eutrophication in the stream expressed high rate of phosphorus in the environment, there various rates of concentration ranged from 0.000352718-0.437434594,0.00029158-0.361612598,0.00028183-0.331253401, 0.000263182- 0.316679675, 0.000235172-0.293114139, 0.000270628- 0.347346913, the derived simulation values were compared with experimental data, and both parameters developed best fits correlation, the study is imperative because it has monitored various rate of velocity that influenced dispersion of phosphorus substance in the stream, it has also expressed the rate of homogeneous velocity of flows as it has been through evaluated.
Keywords: Phosphorus; Transport dispersion coefficient velocity and flow
Preceding segments explain the pathogen pollution in various ambient water bodies and possible sources. Factors influencing pathogen continued existence and transport in ambient water bodies are of a huge interest Pathogen concentration in water bodies are influenced by many environmental factors. Scott et al. [1] several studies have been reviewed studies explaining the environmental factors impacts on pathogen survival are accessible Brookes et al. [2]; Fayer and Trout [3]; Gerba 4]; Hipsey et al. [5] Eluozo and Ezeilo [6]. The consequence of these factors has variation with season and these types of ambient water bodies Van Donsel et al. [7]; Gallagher and Spino [8]; Niemi [9] Eluozo and Ezeilo [10], Pandey [12]. Modeling In- Stream Escherichia coli Concentrations Graduate Dissertation Iowa state university pp 62-75. Other studies carried out such as for stream water, temperature is considered to be the governing factor in E. coli continued existence McFeters and Stuart [12] Eluozo and Ezeilo [13]; meanwhile, in the study of groundwater and reservoir, the existence of predators controls their survival Wcislo and Chrost [14]; Gordon and Toze [15]; John and Rose [16] Eluozo and Ezeilo [17], Eluozo and Amadi [18], Eluozo and Amadi [19]. In another development, solar radiation is considered to be the most significant factor that affect the survival of pathogens; more so, the effect may definitely vary with depth of water, including the of type water bodies, and type of pathogen Sinton et al. [20]. Sunlight For example, is an inactivation rates that definitely vary. These are from greatest to least, because they are: coliforms > enterococci > F-RNA phages > somatic coliphages Davies-Colley et al. [21]; Davies-Colley et al. [22]; Davies-Colley et al. [23] Eluozo and Afiibor [24] Eluozo and Afiibor [25]. Other research study carried out expressed the sunlight inactivation rate as: >enterococci > fecal coliforms > E. coli > somatic coliphages > F-RNA phages Sinton et al. [20], Eluozo [26].
Nomenclatures
C = Concentration
B = Fluid Density
K = Dispersions
A= Velocity of flow
D = Distance
Multiplying the equation through by C[x], we have:
Then Equation (2), we have:
Differentiate 2nd term on the left-hand side of (6) with respect to x, we have
Applying separation of variables, by dividing through by C(x) and cross multiply by dx, gives:
Taking exponent of both side of the equation
Standard laboratory experiment where performed to monitor Phosphorus a using the standard method for the experiment at different sample at different station, the water sample were collected in sequences base on specification stipulated at different locations, this samples collected at different location generated variations at different distance producing different Phosphorus concentration through physiochemical analysis, the experimental result were compared with the theoretical values for model validation [27,28].
Table 1-6 and Figure 1-6 explained the behavior of the microelement growth rate in the stream, the figures shows exponential growth rate, this implies that the point source of the microelement discharging into the river are in continues process, the discharge from human settlers in the environment continue to increase, the concentration in the stream cause higher rate of increase from the point source of discharge, the trend gradual increase from the point source to optimum rate, such condition were monitor in the environment in other to determine the rate of it deposition at distance of ninety meters, because of the gradual increase in the stream, this condition implies that the system are influenced by other significant parameters that should be part of the transport system, the growth rate of both phosphorus are basically on the conditions observed in the study environment, the stream experienced heterogeneous velocity at different locations, the shape of the stream and other environmental factor were observed to influence the velocity of flow, but the trend monitored the dispersion coefficient effect on the stream, the growth rate of the microelement explained the rate of velocity of flows and the variation of dispersion coefficients in the transport process, based on this factors exponential phase of phosphorus were predominantly observed in the study area, the predictive and experimental values developed the gradual increase with higher percentage of best fits correlation.
Phosphorus deposition in Eleme stream were monitor at different locations, this were to evaluate the rate of its concentration at different station point of discharge in the stream, the study evaluate this microelement based on it exponential growth rate in the stream, this cause for thorough study in other to determine their various rate of increase at the stream, the rate of concentration in some location generated Eutrophication in the stream, the variations from velocity of flow were observed to influenced the rate dispersion of phosphorus in the study environment, this on physical process shows the rate water hyacinth on the stream, this condition implies that constant discharge of the microelement will definitely generate high increase of microbes in the river thus developed microbial increase from these points of discharge, the study has definitely express various rates of discharge and it level of concentration at different point, such study expressed thorough evaluation of the factor that cause the increase of phosphorus transport in the stream, the study has expressed the fundamentals causes of exponential growth rate of contaminant in the stream, the application of one dimensional flow transport system has express the variation effect of dispersion at various point source discharge locations in the study area. The predictive and experimental values developed best fits correlations.
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