Seasonal variations of some pollution indices in River Ekulu, Enugu, Nigeria.
Furthermore, an almost total lack of sewerage in most urban areas leaves industries no alternative but to discharge liquid effluents into surface waters. Urban water courses in developing countries are notoriously polluted with domestic wastes but the healths implications may be much more serious if certain types of industrial pollutant are also present (8.9). Hence, the lotic environment consisting of all inland waters had continued to be an avenue for dumping refuse from man's quest for industrialization, urbanization and improved economic and social conditions.
The problems arising from waste water discharge is on the increase in third world counties (10,11). In addition to these problems is the low cleaning capacity or the low waste loading capacity of the main outfalls in dry areas due to the fact that they carry seasonally widely varying amounts of wastes.
Water pollution control agencies usually prescribe that receiving waters must not be loaded so heavily that they will produce offensive odors or contain visible floating or settleable solids, oil or sludge deposits. The extent of pollution of surface water can be determined by such parameters as pH, BOD, DO, suspended solids (SS), dissolved solids (DS) etc. (12,13). Industrial activities are major sources of many of the wastes which have bearing on the water body purity because industrial processes produce excessive concentrations of dangerous chemical substances, dust and contaminated waters which ultimately enter the water courses.
Industries in Emene industrial estate, are known to discharge their wastes into Ekulu River (14,15). The ability of the stream to handle the wastes and regenerate itself or rid itself of the pollution is studied here in relation to seasons. The two prevalent seasons in Nigeria, rainy and dry seasons show difference in the volumetric flows or discharge of the river and hence the ease with which the contaminants were got rid of. The level or concentration of five of these pollutants were monitored in both seasons. These include BOD5, DO, Temperature, TSS and TDS.
Mapping the Sampling Locations
Four Sampling stations along the stretch of Ekulu River were mapped out as permanent sites for the collection of water samples and on site testing throughout the duration of the study. The first station was 200m above the entry point of major pollutants into river the second third and fourth location 600m and was 400m, 10,00m from the first point respectively, covering a distance of 1.2km,
Collection of Water Sample
Water sampling was by grab method. It was carried out at the depth of 0.762m from the surface (ie 0.6h where h = depth) in all the sampling locations. The samples were collected when it was known that the industries contributing effluents into the river were in operation. The samples were collected between 9.00am and 10.30am on each sampling day. The samples were collected in white polythene bottle, with rubber stopper under water.
The temperature of the river water were taken immediately before collection of the samples using a mercury in glass thermometer (range 0[degrees]-100[degrees]c) supplies by Philips Co.
Total Suspended Solids (TSS)
A 100ml of the water sample was filtered over a neighed filter paper (whatman. No 42) which had been over dried and stored in a desiccators. The residue with the filter paper was dried between 98[degrees]c and 1100[degrees]c, cooled and weighed the weight of the TSS was obtained by subtracting the weight of the filter paper from the weight of filter paper and the residue. The result was multiplied by a factor of 10 to express the result in mg/e or ppm.
Total Dissolved Solid Determinations
A 100ml of the water sample filtered in (vi) above was vaporized in weighed 250ml evaporating chib. The difference in weight constitutes the TDS. The value got was multiplied by a factor of 10 to express it in mg/e or ppm.
DO and [BOD.sub.5] Determinations
The determination of BOD5 was carried out as prescribed in literature using the aired modification method (18). After collection of the sample in a 300ml BOD bottle, it was fixed by introducing in quick succession 1ml KF solution, 2ml MnS[O.sub.4] solution and 2ml alkali iodide azide regent. The full bottle was corked to prevent am entrainment and mixed by inversion. Finally 2ml of conc. [H.sub.2]S[O.sub.4] was run down the neck of the bottle and the precipitate dissolved by inverting the bottle. The sample was transferred to the laboratory and the DO content determined as is described elsewhere. The sample was incubated for five days after which DO content determination was repeated.
The [BOD.sub.5] in mg/l or ppm was estimated for the diluted sample thins [BOD.sub.5]; mg/1 = [[D.sub.1]-[D.sub.2]]/P
[D.sub.1] = DO of diluted sample after preparation
[D.sub.2] = DO of diluted sample after 5days incubation
P = Decimal fraction of sample used and is given by
P = [ml of dilution water + ml of sample]/ml of sample
Result and Discussion
The results obtained is presented and table 1 and 2 below
Inspection of the values of the temperature of the water sample showed that rainy season temperatures of Ekulu River were higher than dry season ones. Thin disparity may be attributed to two reasons namely: (i) evaporation which is higher in dry seasons and (ii) cold harmattan winds which prevail at this time of the year. As temperature increases in streams, both oxygen consumption and heat rate increase in aquatic life hence more oxygen is needed at higher temperatures for higher metabolic rate. Also disease resistance in aquatic life is linked to temperature as increase in temperature increase the rate of microbial activity and decrease the ability to resist diseases.
TSS and TDS
The total suspended solids (TSS) are higher during dry season than rainy season. Thin may be accounted for by the fact that during dry seasons, there is increased evaporation and reduced discharge rate and than TSS tend to concentrate following efficient discharges.
Also total dowered solid (TDS) was higher in dry season than rainy season for probably for same reason as above. Suspended Solids (SS) no matter how small are objectionable in rivers.
Dissolved Oxygen (DO)
The dissolved oxygen is one of the most popular index of river contamination because it is affected by virtually all the pollution indices. Result of the analysis shows that rainy season values of DO are higher than dry seasons which can be attributed to availability of factors favoring re-aeration of the river.
Biochemical Oxygen Aemand (BOD)
[BOD.sub.5] analysis showed that the values were higher in dry season, than rainy seasons. However the BOD5 laved of the river is within the limit set by Federal Environmental Protection Agency (FEPA), Nigeria as interim effluent guidelines but in excess of the limit set by WHO as standard for portable rate.
The seasonal variation of these parameters were subjected to time series analysis using least square method to ascertain which set were higher and by how much. If the variable X represent the independent variable of the series, such as distance and Y represents the value of the dependent variable, (eg temperature), linear trend is written as.
Y = a+bx where a and b are constants whose values were obtained using normal equations. The result of the series analysis yield time series normal equation characteristic of Ekulu river stretch studied.
(a) Temperature Y = 26.07 x 0.32x (dry season). Y = 27.04 x 0.05x (rainy season).
(b) TDS Y = 29.07 x 10.34x (rainy season) Y = 43.31 x 10.34x (dry season)
(c) TSS Y = 48.27 x 3.62x (rainy season) Y = 58.85 x 2.95 x (dry season)
(d) DO Y = 6.62-0.30 x (rainy season) Y = 6.43-0.27 x (dry season)
(e) [BOD.sub.5] Y = 2.74 x 0.35 x (rainy season) Y = 3.03 x 0.51 x (dry season)
Result of these time series analysis show that rainy season temperature is higher than dry season temperature by 0.97[degrees]c(at x=0; station 1) and 200m distance of charge in temperature in dry season (5-value) is higher than temperature of rainy season by 0.27[degrees]c. As for TDS, dry season set is higher than rainy season set by 14.24mg/l at (x=0) and dry season set higher than rainy season by 7.72mg/l per 200m change in distance. Dry season TSS was higher than rainy season set by 8.58mg/l (at x=0) and rate of charge of TSS is higher in rainy season (b=3.62) than in dry season (b=2.95).
Comparing the two trend equations of DO (rainy and dry season sets) on observer that rainy season set is higher than dry season set by 0.19mg/l and rate of charge differ by 0.03.
The dry season [BOD.sub.5] is higher than that of rainy season by 0.29mg/l when considered at (x=0) Also, the [BOD.sub.5] increase per unit distance (200m) is higher in dry season than rainy season.
Implications of the Study
The result of the study has a far reaching implications. The river series as a dump site for the industrial wastes from Emene industrial estate, domestic wastes, such reuse and Landry; non-point source agricultural wastes and others. With the result, it is established hat the rivers assimilation capacity is higher in rainy season. The extent of pollution of the river ought to be monitored to avoid excessive endangering the flora and fauna and the inhabitants that depend on the river down stream as a source for domestic water supply. The onus lies on the shoulders. Of the environment at protection agency and the stake holder who hold clean environment dear and indispensable.
 Agunwamba, J.C. (2001) Waste Engineering and Management Tools. Immaculate Publications. Enugu pp 412-431
 Krantz, David and Kifferson Brad. (2001) Global water pollution. Water pollution and society 2. 1 pp5-6.
 Doppe, Wayne and Hurst Rence. (1997) Water pollution. Water quality international 5.I pp 139-43
 USEPA: United State Env. Protect. Agency publication Washington D.C. (1996)253.
 Mac Donnell L.T. (1996) Water Quality. Land water Rev.31 2 pp329-348.
 Terry L.A, (1996) Water pollution. Water Quality Int.4, 1 pp 19-29
 FEPA: (1991) Guidelines and standards for Environmental control in Nigeria. Lagos pp 3-11
 Richman, M. (1997) Ind. water pollution, waste water. 52 pp 2 4-29
 Lindsey, T. Neese, S and Thamos, D. (1996) pollution prevention. Water Quality Int. 4 1 pp 32-36
 Orth, H and Prugge. E. A. (1980) in Regis Kano in Nigeria. Wasserwritschaft 70. 402-406
 Awake, (1988) Pollution, the Relentles killer. Watch tower Bible and Tract society, New York may 8 p.4
 Agayi, S.O and Osibanjo. O. (1981) Pollution studies on Nigeria Rivers 11. water Quality of some Nigeria Rivers. Environmental Research, 18, 795
 Gannon, R.N, Osmond D.L; et.al. (1996) Agricultural water Quality. Water Resources Bull. 322 pp 437-450.
 Cheremisinoff, P.N and Morresi, A.C (1977) Environmental Assessment and Impact statement handbook. Ann Habor Sc. USA. 137.
 Ayinlai, P. (1985) Protecting Environment from Industrial pollution. Dail Times. 28/8/85; p 8.
 ASTM (1959) manual on Industrial water and Industrial waste water 2nd Ed. Philadelphia 74.
 ASTM. (1971) Standard methods D.5 12-72
 APHA. (1956). Standard methods for the Examination of water and waste water. New York.
Nwachukwu R. Ekere
Dept. of Pure & Industrial Chemistry, University of Nigeria, Nsukka
Table 1: Result of Seasonal Measurement of Pollution Indices. Parameter Station 1 200m Station 2 from outfall 400m Temp. [degrees]C Rainy season 27.05 27.10 Dry season 26.01 26.40 TSS. mg/l Dry season 63.00 65.20 Rainy season 43.30 59.10 TDS. mg/l Rainy season 26.90 33.50 Dry season 40.00 54.50 DO. mg/l Rainy season 6.71 6.21 Dry season 6.50 6.10 [BOD.sub.5] x mg/l Rainy season 2.17 3.10 Dry season 3.00 3.50 Parameter Station 3 Station 4 600m 1000m Temp. [degrees]C Rainy season 27.10 27.20 Dry season 26.90 27.00 TSS. mg/l Dry season 63.50 63.40 Rainy season 56.00 56.40 TDS. mg/l Rainy season 37.20 34.40 Dry season 72.10 68.66 DO. mg/l Rainy season 5.79 5.80 Dry season 5.80 5.70 [BOD.sub.5] x mg/l Rainy season 3.80 4.02 Dry season 4.20 4.45 Table 2: t-terts for pollution parameters measured as a function of season, at 95% confidence level. Parameter Dry Season (D) Rainy season(D) Temp 26.66 (0.2826) 27.03 (0.1180) DO 6.02 (0.3836) 6.29 (0.2112) TSS 57.0360 (5.1316) 57.96 (4.1827) TDS 60.02 (8.8316) 29.03 (4.0932 BOD5 3.829 (0.8932) 2.867 (0.8412) Parameter T-calculated Table Temp 6.440 2.131 DO 2.643 2.131 TSS 2.9662 2.131 TDS 12.569 2.131 [BOD.sub.5] 3.0367 2.131
|Printer friendly Cite/link Email Feedback|
|Author:||Ekere, Nwachukwu R.|
|Publication:||International Journal of Applied Chemistry|
|Date:||Jan 1, 2011|
|Previous Article:||Green approach for the synthesis of Ag-nanoparticles and their catalytic properties in the presence of [K.sub.2]C[O.sub.3].|
|Next Article:||Study of anti-nutritive factors in some new varieties of oil seeds.|