Application of Assessment Models for Health Risk and Pollution From Surface Water From Okumpi River in Nwangele, Imo State, Nigeria


 The study targets at examining the pollution assessment and environmental health effects of surface water from Okumpi River. Ten surface water samples were collected randomly both in wet and dry seasons within the river that was assessed. The models used for assessment include contamination factor (Cf), pollution load index (PLI), water quality index, dermal and absorption exposure dose, hazard quotient (HQ), hazard index (HI) and carcinogenic risk (CR). The mean and standard deviation pH value in the present study during the wet and dry seasons varied from 6.21±0.22 - 5.75±0.41. The mean and standard deviation EC in the current study ranges between 219.15±12.20 - 193.30±14.81 μS/cm for wet and dry seasons which are found to be in line with the WHO standard used. The mean and standard deviation of DO for this study during the wet and dry seasons were found to be 10.03±0.58 - 6.47±0.41 (mg/L). TDS for wet and dry seasons ranges from 374.79±5.33 - 121.65±6.33 mg/L. The colour of the water samples at both seasons were lower than the permissible limit 9.60±0.89 - 11.20±3.11 PCU against 15 PCU used as the standard. The nitrate [9.05±1.08 - 8.09±1.57], sulphate [3.91±0.51 - 3.73±0.46] and phosphate [82.78±3.86 - 81.76±3.32] in this present study for wet and dry season were all found to be below the standard of WHO for safe drinking water. Among all the heavy metals studied, Iron [1.28±0.01 - 0.37±0.01 (mg/L)] and Nickel [0.98±0.04 - 1.03±0.04 (mg/L)] were found more in the study in wet and dry seasons while cadmium was not detected in both seasons. Nickel showed high contamination factor of 48.24 – 42.40 in wet and dry season while cupper showed the least contamination factor of 0.012 – 0.008 in wet and dry season. The study has revealed that the surface water is not suitable for drinking purposes as seen by the high water quality index which the calculated value gave 1205.56-1236.26 for wet season and dry season which is > 300. The Hazard quotient via ingestion and Hazard quotient via dermal has a reduction in the order of lead > nickel > iron > manganese > copper > zinc and lead > zinc > nickel > copper > iron > manganese > cadmium, in cooperation in children and adults in wet season, correspondingly. The Hazard quotient via ingestion and Hazard quotient via dermal has a decrease in the following order of nickel > lead > manganese > copper > iron > zinc and lead >zinc > nickel > copper > manganese > iron > for both children and adults in dry season, respectively. Lead possess carcinogenic risk for the inhabitants of this area due to the value of the carcinogenic risk n wet season of 4.05E-4 in adult and 1.55E-3 in children, in dry season of 2.57E-4 in adult and 9.88E-4 in children, against the standard set by the USEPA of 10-6 – 10-4. The water pollution monitoring agency of this area should regularly check the water quality assessment of this river and should suggest treatment through filtration, boiling and the use of additives in order to reduce the risk of water related problems.


Introduction
Man and its environment are blessed with the most fundamental yet least expensive asset of earth, which are found all over. Notwithstanding, because of botch and less undertaking conduct of man, the most valuable asset has been severally been contaminated with physiochemical tracer and through anthropogenic exercises (Ihenetu et al., 2020). Water pollution transpires when water is adulterated with chemicals and foreign bodies that are destructive to animals, plants and humans. Water pollutants take account of chemical contamination which comes from waste places and sites, chemical wastes from industrial discharges, also heavy metals and materials such as lead and mercury, food processing waste, sewage waste, pesticides and fertilizers (Gannon et al., 2007). In rural areas, the major source of water pollution can be directed to anthropogenic activates and runoff from agricultural farm lands surrounding the rivers. Most works done by researchers are mostly concentrated on the urban areas meanwhile the source of domestic and livelihood of rural people are based in these surface water which they consume without the prior knowledge of the water quality. Water pollution is a severe ecological menace. When contaminated water is taken, it poses a very harmful to animal health and human. When toxic constituents dissolve in bodies of water of every type such as oceans, lakes and rivers, the water becomes polluted. They reduce the quality of water over interval. This results in devastating effects to aquatic ecosystems. Pollutants always contaminate the groundwater, which stances a serious danger to households that use the contaminated water (Jinwal and Dixit, 2008). Surface waters include streams, reservoirs, lakes, rivers, and wetlands. Surface water comes mostly from rainfall and is an amalgamation of the surface run-off and ground water. (Bernice et al., 2013). Unintended urbanization and population progression are among some of the home made and domestic activities accountable for pollution of water bodies. Stream flow varies in response to climatic factors and human activities (Owa, 2013). Anudike et al., (2019) worked on the Water quality assessment of Nwangele River in Imo State, Nigeria and found out that the river is slightly polluted and the present river studied has a flow with Nwangele River. Ubuoh et al., (2013) researched on the effectiveness of water quality index in Izombe in Imo state of Nigeria. The scientific research was done in Region where gas flaring is unremitting in order to establish pollution level in rainwater and boreholes as they are seen as the two major foundations of water supply in the area. The concentration of pollution among the sampled water resources was achieved by comparing the outcome of physicochemical tracers with that of WHO standards for drinking water. This research work frames a benchmark for the assessment of water quality in Okumpi River situated in Nwangele Local Government area of Imo state Nigeria since no work has been done in this river for physicochemical and health risk assessment. The objective of this work is to survey the physiochemical attributes and human health assessment because of heavy metals in surface waters sources in the study area.

Study Area
The study area is Okumpi River located in Nwangele Local Government area of Imo State. The geology of Nwangele area comprises of plain soil which is about 0.05-2.0 mm in size and it is somewhat porous, deep and highly leached. Geographically, the area falls between coordinates of latitude 5.7358785479-5.7410154879 and longitude 7.12223658951-7.12874785412. The major occupation in these areas include farming, fishing with few traders. The activities carried out in these rivers include washing of cloths, fishing, washing and fermentation of agricultural products, washing of kitchen utensils, bathing etc. Nwangele is in the tropical rainforest zone and it has two distinctive seasonal variation which are the wet and dry the seasons. Figure 1 below shows the map of the sampling point and the study area. The wet season twitches from April through October with topmost incidence between June and September while the dry season launches in November through March annually.

Sample Collection
Ten surface water samples were collected randomly both in wet and dry seasons within the river that was assessed. Sampling in this area was carried out for both dry and wet seasons and specified as Okw and Okd respectively. 500mL polyethylene sample containers were used to collect water samples from the River. In the sampling point, the containers were rinsed three times with water at the sampling point before the collection of the samples. The water samples were collected according to the method used by Ihenetu et al., (2019).

Instrumentation
The electrical conductivity was measured using the HANNA HI8733 EC METER in µS/cm, the pH was measured using JENWAY 3510pH METER, the DO concentration of the surface water samples were established using a Jen-way 9071 digital oxygen analyzer, colour and anion determination were done using Multiparameter bench photometer HI 82300 by HANNA Instruments. TDS were determined using Groline TDS meter by HANNA Instruments. Calcium, sodium, potassium, iron, copper, cadmium, Nikel, Manganese, Zinc, and lead, in the respective surface water samples was determined using Perkins Elmer AAnalyst 400 Atomic Absorption Spectrophotometer (WHO, 2004).

Data Analysis
The data were assessed for their mean and standard deviation. The data were used to calculate the pollution index models and contamination also Spear-manʼs correlation coefficient, water quality index (WQI) analysis and health risk assessment were calculated.

Quality control
Reagents used throughout the experiments were of high quality analytical grade, which was purchased from BDH Chemical Ltd, UK, and Sigma-Aldrich Chemie GmbH, Germany. Detergents and deionized water were used to wash the glassware and sample bottles. They were soaked overnight with a solution of 10% HNO3 in a 1% HCl solution, followed by rinsing with deionized water. Similarly, the reagents that were used for the determination of anion concentrations with the Hanna Hi 83,200 Instrument were obtained from Hanna Instruments. The instrument (Agilent 240FS AA) used for the determination of the concentrations of metallic elements in the samples has high sensitivity-typically > 0.9 absorbance with a precision of < 0.5% RSD from ten-second integrations for 5 mg/L Cu standard.

Results and Discussion
Physicochemical parameters of surface water

0.01
Temperature of water centers on its proposed usage. The temperature of surface water, conferring to the standards used falls within 20-30 0 C (WHO, 2006). The temperature degree examined for the wet season and dry seasons where observed to be within the WHO and NSDWQ standards. Nevertheless the dry season in the study revealed a minor upsurge in temperature which possibly will be due to the current weather condition of the environment at the location of study. Decrease and increase in temperature level is one of the notable importance feature of seasonal variation and weather change. Dissolve oxygen is the oxygen present in dissolve form in water bodies (Ibe et al., 2019). Its decrease is ominously affected by runoff from agricultural farm lands and soils encompassing nitrogen and phosphate compounds or the death and decay of marine life forms leading to the release of nitrogen compound directly to the water body subsequently causing decrease in dissolve oxygen. According to WHO standard, the dissolve oxygen for all points during the wet season were found to be low in relation to dry season, the DO is found to be lesser than the standards for dry season but slightly higher during the wet season [10.03±0.58 -6.47±0.41 (mg/L)]. The thin increase in DO and pH during the wet season can be studied in line with the affectation by similar anthropogenic activities. Interrelated results were noticed for Nworie River (Duru and Nwanekwu, 2012). The EC can critically affect the taste of water. The EC in this study falls between 219.15±12.20 -193.30±14.81 μS/cm in wet and dry season. The values obtained were contained by the WHO standard for risk-free drinking water. The pH value in this study for the two seasons varied from 6.21±0.22 -5.75±0.41 μS/cm which shows a little acidity which were not in agreement to the standard pH (6.50-8.50) recorded by WHO (2004WHO ( , 2006 guidelines for safe drinking water. In this present study, the TDS for the wet and dry season fall between 374.79±5.33 -121.65±6.33 mg/L. This might perhaps will be a suggestion of normal pollution from overflow of soils within the study area. The colour of the water samples at all the sampling sites were lower than the allowable (9.60±0.89 -11.20±3.11 PCU  (Ihenetu et al., 2020). Calcium, sodium and potassium as found from the current study in both seasons are below the WHO standard.  The iron level was high during the wet season and this might be as a result of iron coagulants and also due to the fact that most mineral sediment on the soil may have high level of iron. (Macdonald and Christopher, 2011). Copper is an essential nutrient, however, it can also be a contaminant if seen in higher concentration. The low level of copper in this present study is in line with the result observed in Nwangele River (Anudike et al., 2019) and in River Nworie (Duru and Nwanekwu, 2012). With regards to WHO standard for household and drinking water value for Mn, all points for wet season showed low level of Mn. If Mn is found higher in water, it can constitute an irritation with a characteristic metallic taste and discoloration properties (Ugwu, 2016). The level of zinc observed in this present study are below the standard used for checking the level of good water quality unlike lead which is higher during the dry season on this present study (0.1 mg/L), this might be due to the disbanding of lead from the soil.

Correlation coefficient matrix
A substantial positive correlation (r > 0.5) was observed between some of the metals, and anions parameters. The coefficient of relationship is shown in Table 2 Once the correlation is seen positive, the foundation of contamination of the positively linked metals is alike while negative correlation recommend dissimilar/different bases of contamination. Notable pollution can be through washing of engine cars, tricycles and motor cycles at the river. Some of the relationship shown by the metals has been examined by (Verla et al., 2018).

Chemometric Analysis
Contamination factor: The contamination factor were employed to check the rate of individual metal contamination in the water samples. Contamination factor were calculated with the formula below.

=
(1) Where Cf signify contamination factor, Cmetal represent the concentration of heavy metal and Cbackground signify the background value of metal. WHO recommendations for safe drinking water are taken as the background values for water sample. Very high contamination Pollution load index (PLI): The suggested pollution load index through Tomlinson for identifying pollution levels in soil were applied to the water samples to identify the concentration of contamination of heavy metal in the diverse locations. The PLI estimates the metal concentration status and give an idea of the various actions that can be taken to curb the issue (Naruka and Sharma, 2017). Researchers have estimated the pollution load index using equation 3.

Water quality index (WQI)
WQI is an arithmetic expression used to transmute large number of adjustable data into a single number, which signify the water quality level. The WQI is developed from the following formula conferring to Duru et al., 2017.
Where: where, Wi is equal to the comparative weight, wi is equal to the weight of every single parameter and n is the number of parameters. Water quality evaluation may be developed conferring to Bordalo et al., 2006. = × 100 (4) Where qi is the quality ranking, Ci is the concentration of each chemical parameter in every single water sample in mg/L, and Si is the WHO drinking water quality standard. To work out the WQI, the SI was established for each chemical parameter, which is then used to determine the WQI using Equation 5 and 6. The overhead equation becomes: SIi is the sub-index of ith parameter, qi is the rating based on concentration of ith parameter and n is the number of parameters. The benchmark values were acquired from World Health Organization (WHO) standard for drinking water, 2007. The following point out the arrangement of (WQI) and the quality of water WQI  From the results obtained and presented on the Figure 4 above for wet and dry season, all are above the estimated level for good drinking water quality which showed that selected water supplies in this studied area are severely polluted with physicochemical tracers for the reason that the calculated value 1205.56 for wet and 1236.26 for dry season. Various activities around the sampling point might have contaminated the rivers in an intense way.

Assessment of health risk
Dermal and ingestion exposure, Hazard quotient (HQ), Hazard Indices (HI) Health risk through human exposure to these metals contamination can be either by means of dermal ingestion, inhalation or absorption, which are the normal contact passageways to the water. Subsequently all the River studied in this research are continually used by the people for the most part of their domestic activities and recreational activities. The calculation of health risk was calculated using equation 7 and 8 according to the USEPA risk estimation method (USEPA 1989).
Exping represents the exposure dose via ingestion of water (mg/kg/day); Expderm represents the exposure dose via dermal absorption (mg/kg/day); Cwater: show the average level of the estimated metals in water (μg/L); IR shows the ingestion level in this study (2.2 L/day for adults; 1.8 L/day for children); EF shows the exposure frequency (365 days/year); ED shows the exposure duration (70 years for adults; and 6 years for children); BW show the average body weight (70 kg for adults; 15 kg for children); AT shows the averaging time (365 days/year × 70 years for an adult; 365 days/year × 6 years for a child); SA shows the exposed skin area (18,000 cm2 for adults; 6600 cm2 for children); Kp shows the dermal permeability coefficient in water, (cm/h), 0.001 for Cu, Mn, Fe and Cd, whereas 0.0006 for Zn; 0.0001 for Ni; and 0.004 for Pb; ET shows the exposure time (0.58 h/day for adults; 1 h/day for children) and CF shows the unit conversion factor (0.001 L/cm3) (USEPA, 2009). Potential non-carcinogenic risks in line for exposure of heavy metals were established by evaluating the calculated contaminant exposures from each exposure path (ingestion and dermal) with the proposal dose (USEPA, 1989) using equation 9 below adequate to obtain hazard quotient (HQ) toxicity potential of an average daily intake to reference dose for an individual via the two fold pathways.
Where RfDing/derm represents the ingestion and dermal toxicity recommendation dose (mg/kg/day). The RfDderm and RfDing values were gotten from the literature (Wu et al., 2009). An HQ under 1 is presumed to be safe and taken as substantial non-carcinogenic (USEPA, 2019). The hazard index (HI) was calculated using the formula in equation 10 Where HIing/derm is hazard index through dermal contact or ingestion.

HQ) and cumulative hazard indices (HI) for each heavy metal present in wet and dry season for Adult and Children
The dermal and ingestion exposure calculated in table 5 were used to determine the hazard quotient in table 6. The hazard quotient (HQ) was determined and both HQderm and HQing in the two seasons for all the trace metals checked in the research were less than one (1) as demonstrated in Table 6 for adults and children. This demonstrates there is practically no adversative health impact expected to be enacted by any of these metals when the surface water is utilized. The HQing and HQderm diminished in the order of lead > zinc > copper > iron > nickel > manganese and lead > iron > nickel >copper > zinc > manganese > cadmium, for both children and adults in wet season, respectively. HQin and HQderm diminished in the order of nickel > lead > manganese > copper > zinc > iron and lead >zinc > nickel > copper > manganese > iron > for both children and adults in dry season, respectively. Nevertheless, it has been recommended that estimated HQ values for metals > 1 for children should not be disregarded (Giandomenico et al., 2017;Sudsandee et al., 2017), probably because, children are vastly disposed to pollutants (Sudsandee et al. 2017). The major sources of non-carcinogenic health risk in both passageways were Pb, Zn and Ni. The estimated total HQ values were less than one as seen in table 6.

Chronic daily intake (CDI) and Carcinogenic risk (CR)
The carcinogenic risk (CRing) shows an incremental chance that an individual will develop cancer during his lifetime inferable from revelation under characterized conditions were computed for the selected metals in this current examination (Wu et al. 2009;Ibe et al., 2020). The chronic daily consumption of heavy metals through ingestion was computed using equation 11.
Where Cwater represents the concentration of trace metal in water in (mg/L), DI imply the, average daily intake of water (2.2 L per day for adults; 1.8 L per day for children) and BW shows the whole body weight (70 kg for adults; 15 kg for children), correspondingly (Yonglong et al. 2015). The cancer risk (CR) was calculated using the formula in equation 12 below: Where SFing represent the cancer slop factor. The SFing for Pb is 8.5 mg/kg/day (USEPA 1989(USEPA , 2005Naveedullah et al., 2010;Ibe et al., 2020).  (Table 7). This suggests that the surface water assumes less health threats to both adults and children via the pathways, however procedures ought to be made to circumvent accumulation of heavy metals that possibly will pose health problems especially in children.

Conclusion
The current study has uncovered that some actual appearance of surface water from Okumpi River during the wet and dry season are not in line with WHO guidelines. The study has shown additionally that the pH of all the sampling point are acidic. Phosphate apparently is a bit high in all the sampling point at various season and this can be related with high utilization of more phosphate grounded fertilizer on farm lands surrounding the Rivers. The current study has uncovered that the surface waters are profoundly contaminated with Fe, Ni, Pb, also this current study has shown that the surface water is not suitable for drinking purposes as revealed by the high water quality index (> 300).

Recommendation
With regard to the results on the present study, the following recommendations are made: 1. The water resources monitoring in the Nwangele Local Government area ought to be done regularly in order to assess pollution levels in order to check the spread of water related complications especially in Okumpi River.
2. In a circumstance of uncertain water quality, treatment is suggested through filtration, boiling and the use of additive (alum, liming, chlorine), thereby reducing the risk of water-related problems.