|Year : 2016 | Volume
| Issue : 2 | Page : 50-56
Assessment of radiological risk parameters associated with some selected rivers around oil mineral producing sites in Abia state, Nigeria due to gross alpha and beta radiations
Paschal Ikenna Enyinna, Francis C Uzochukwu
Department of Physics, University of Port Harcourt, P.M.B. 5323, Port Harcourt, Rivers State, Nigeria
|Date of Web Publication||7-Oct-2016|
Paschal Ikenna Enyinna
Department of Physics, University of Port Harcourt, P.M.B. 5323, Port Harcourt, Rivers State
Source of Support: None, Conflict of Interest: None
Context: The study of gross alpha and beta radiation in environmental components and water bodies in particular is very crucial to the environmental, radiation and medical Physicist as this helps to promote good water quality and environmental hygiene.
Aim: This research work understudied the radiological risk parameters due to gross alpha and beta radiations associated with three selected rivers around crude oil production sites in Abia State, Nigeria.
Materials and Methods: Gross alpha and beta activities were computed for the three rivers based on analytical measurements carried out using a well-calibrated IN-20 model gas-flow proportional counter. Radiological risk parameters were computed from the activity concentrations which included; annual effective dose equivalent of radiation from ingested water (AEDE), annual gonadal dose equivalent (AGDE), and excess lifetime cancer risk (ELCR).
Results: The mean of the total AEDE due to the sum of alpha and beta radiations for the three rivers are 0.868 ± 0.221 mSv/y, 1.008 ± 0.156 mSv/y, and 0.917 ± 0.214 mSv/y; and are above the World Health Organization (WHO) permissible limit of 0.1 mSv/y. The mean of the total AGDE is 4.048 ± 1.063 mSv/y, 4.756 ± 0.739 mSv/y, and 4.295 ± 1.026 mSv/y; and are above the world average limit of 0.3 mSv/y. The mean of the total ELCR are (3.038 ± 0.774) × 10−3 , (3.529 ± 0.547) × 10−3 , and (3.210 ± 0.748) × 10−3 , and are above the world average limit of 0.29 × 10−3 .
Conclusion: Most values of ELCR computed in this work are >6.0 × 10−4 estimated to be the risk of fatal and weighted nonfatal health conditions over a lifetime (70 years) derived from the radiation dose of 0.1 mSv/y (WHO permissible limit for drinking water). Drinking water from these surveyed sources could impact negatively on the end users.
Keywords: Cancer risk, gonads, radiation doses, water ingestion
|How to cite this article:|
Enyinna PI, Uzochukwu FC. Assessment of radiological risk parameters associated with some selected rivers around oil mineral producing sites in Abia state, Nigeria due to gross alpha and beta radiations. J Radiat Cancer Res 2016;7:50-6
|How to cite this URL:|
Enyinna PI, Uzochukwu FC. Assessment of radiological risk parameters associated with some selected rivers around oil mineral producing sites in Abia state, Nigeria due to gross alpha and beta radiations. J Radiat Cancer Res [serial online] 2016 [cited 2020 Dec 3];7:50-6. Available from: https://www.journalrcr.org/text.asp?2016/7/2/50/191712
| Introduction|| |
Our environment is continuously bombarded by radiation from natural and artificial sources. Technologically enhanced naturally occurring radioactive materials are produced when radionuclides that occur naturally in ores, soils, water, or other natural materials are concentrated or exposed to the environment by industrial activities. The geologic formations that contain oil and gas deposits also contain naturally-occurring radionuclides and geologists have recognized their presence. 
Oil exploration involves the use of radiotracers. When oil is produced, it comes out with its associated natural radionuclides and induced radionuclides resulting from exploration activities. These lead to the enhancement of the background radiation level of oil producing environments. Due to incessant oil spillages and evacuation of oil produced waters into surrounding water bodies within oil producing communities, the background radiation level of oil producing environments becomes more enhanced. Oil spillages occur frequently in the Niger Delta Region of Nigeria which Abia State forms a part. Factors such as nature of radioactive contaminant, level of contamination, and extent of the spread of contaminants determine the magnitude of radiation hazard to human beings and the environment. 
Most radioactivity-related researches with regards to oil producing environments tend to concentrate more on detection, quantification, and analysis of gamma radiation emissions even in environments where alpha and beta emitters could be present. ,, Although gamma rays have the highest penetrating power when compared to other particle emissions, alpha, and beta particles may pose more danger when introduced to the human body because of their high ionizing nature relative to gamma rays. Radionuclides that are present in drinking water pose a good number of health hazards to humans especially when such waters are ingested. Consumption of water with high concentration of natural radionuclides could increase human's internal exposure to radiation as these radionuclides disintegrate with the emission of several alpha and beta particles which are grossly accountable for the overall radiation doses received from both natural and artificial radiation sources. 
Radiological risk assessment is an estimate of an individual's probability of a fatal cancer risk as a result of exposure to low-level doses of radiation. To effectively estimate the radiological risks arising from environmental components such as air, soil and water, certain radiological risk parameters ought to be computed. This research work is anchored on the computation and assessment of some radiological risk parameters associated with some oil producing communities in Abia State, Nigeria to account for the contribution of alpha and beta particles to the probability of exposure of their inhabitants to the risk of developing cancer during their lifetime. This practice will help to promote radiation protection.
| Materials and Methods|| |
This study was conducted around three selected oil mineral producing communities, namely, Owaza, Imo River Area, and Umorie. The surveyed oil communities are located in Ukwa West Local Government Area of Abia State, Nigeria. Abia State is made up of undulating terrain and low-lying plains. Ukwa West Local Government Area is covered by the alluvial coastal plains characterized by rain forest vegetation and abundance of oil mineral resources as well as large belts of wild and plantation palm trees. The surveyed area has two climatic seasons in a year; the rainy and the dry seasons. The rainy season begins in March and ends in October whereas the dry season begins in November and ends in February. The average annual rainfall is about 2200 mm. The hottest months are from January to March when the mean temperature is above 27°C. The relative humidity is high all through the year, reaching a maximum of above 90% during the rainy season. 
The oil wells in the surveyed area belong to the Eastern Division of Shell Petroleum Development Company, and they contribute about 5% of the total barrels of oil per day produced in the division.  Map showing this study area is presented in [Figure 1].
Twenty-one water samples (seven from each river) were collected from surface water bodies within the three selected oil producing communities (Owaza River, Imo River and Umorie River). The water samples were carefully prepared according to the International Atomic Energy Agency specifications for gross alpha and beta analyses. The water samples were collected in 1 L plastic containers (which were rinsed twice with the water samples) and immediately acidified with nitric acid solution (after each sample was collected) to reduce the pH, minimize precipitation and absorption by the walls of the container and to prevent the growth of microorganisms. The samples were properly corked and taken to the laboratory and kept for a minimum of 24 h before analyses. The samples collected were put in open beakers and heated moderately on electric hot plates (without stirring) for the purpose of evaporation. When the volume of the samples reduced to about 50 ml, they were transferred to a weighed petri dish for further evaporation to residual level using infrared lamp. The sample residues were transferred into counting planchets and allowed to dry completely. Then, the planchets containing the sample residues were stored in desiccators awaiting counting.  These samples were analyzed for gross alpha and beta activity using an IN-20 model gas-flow proportional counter at the Centre for Energy Research and Training, Ahmadu Bello University, Zaria, Nigeria. The IN-20 model gas-flow proportional counter is a low background multiple detector (manufactured by Eurisys Mesures in France) and consists of 100 mm thick stainless steel surrounded by 10 cm lead shield (to shield the detector from external radiation sources) and a slide-in-sample-carrier that contains the measurement detectors. It also consists of two chambers each with four channels which can be fitted with a planchet for holding the samples. The gas used in operating the detector is P-10 gas (argo: Methane gas mixed in the ratio of 90%:10%). Each sample was counted three times and the mean used in computing the activity. The operational modes used for the counting were the α-only mode for the alpha counting and the β (+α) mode for the beta counting. The count rate of each sample was automatically processed by the computer using the equation: 
where C(α,β) = the count rate (cpm) of the alpha or beta particle, R(α,β) = raw count of the alpha or beta particle, t = counting time (2700 s).
Consequently, the gross alpha and beta activity were computed using the formula: 
Where, A(α,β) = Activity concentration of alpha or beta (Bq/L)
C(α,β) = Count rate of alpha or beta particle (cpm)
B(α,β) = Background count rate of alpha or beta particle (cpm)
U(α,β) = Unit coefficient of alpha or beta particle (1.67 × 10−2 , conversion, factor from cpm to cps, where 1 cps = 1 Bq)
Ce (α,β) = Channel efficiency for alpha or beta counting
Se (α,β) = Sample efficiency for alpha or beta counting
S v = Sample volume (litre).
Methods of computation of radiological risk parameters
The following radiological risk parameters which are used to quantify the health impacts associated with exposure to environmental radiation were computed for gross alpha and gross beta radiations; annual effective dose equivalent (AEDE), annual gonadal dose equivalent (AGDE), and excess lifetime cancer risk (ELCR). The variables used for calculation of Radiological risk parameters are based on the report of the International Commission on Radiological Protection ([ICRP], Publication 119). 
Annual effective dose equivalent
The AEDE due to ingestion of water is the quantity of ionizing radiation a person may receive in a year because of the intake of water according to protection guidelines. The formula for computation of AEDE for gross alpha or gross beta radiation received by people is given as: 
AEDE (α,β) = A(α,β) × WC × F1D (3)
The sum of AEDE for gross alpha and gross beta radiation is given as:
where A(α,β) is the activity concentrations of gross alpha and gross beta in Bq/L, WC is the water consumed by a person in a year (We have assumed that standard water consumption for a normal adult is approximately 2 L a day which approximates to 730 L in a year)  and F1D (α,β) is the activity to dose ingestion conversion factor (for gross alpha and beta radiations).
In this work, we have assumed that the major contributor to AEDE due to ingestion of water from gross alpha radiation is radium-226, and the major contributors to the gross beta activities are lead-210 and radium-228.  We, therefore, used the activity to dose conversion factor (FID ) for radium-226 (2.8 × 10−4 mSv/y) for gross alpha radiation and the activity to dose conversion factor for radium-228 and lead-210 (6.7 × 10−4 mSv/y) for gross beta radiation.  We made these assumptions based on the fact that there are four natural isotopes of radium. Radium-226 (half-life of 1600 years) is the most common and is generated in the decay series of uranium-238, and its decay emits alpha particles. Radium-228 (half-life of 6.7 years) is the next most common and is generated in the decay series of thorium-232 and its decay emits beta particles. 
Annual gonadal dose equivalent
AGDE measures the dose of gross alpha and gross beta received by the gonadal surface cells as a result of exposure to radiation. 
The computation of AGDE for gross alpha or gross beta is given by the formula: 
The sum of AGDE for gross alpha and gross beta radiation is given as:
where R.W.F. is the radiation weighting factor and T.W.F. is the tissue weighting factor. R.W.F. for α activity is 20, and for β activity, it is given as 1. For gonads, T.W.F. is 0.20 (for α, and β-activity). 
Excess lifetime cancer risk
ELCR is the probability of developing cancer over a lifetime at a given exposure level.  In this work, 70 years were considered as the average duration of life for humans. ELCR for gross alpha or gross beta was calculated using the formula: 
where DL is the average duration of life (estimated to be 70 years), and RF is Risk Factor (Sv−1 ), which is fatal cancer risk per Sievert. For stochastic effects, the ICRP uses RF as 0.05/Sv (equivalent to 5 × 10−5 /[mSv]) for the public. 
All the data analyses were performed using MINITAB (Release 14) statistical software (manufactured by Minitab Inc. with headquarters in State College, Pennsylvania, USA). We used this software in computing the sample mean (Sm ), standard error of the mean (SEM), standard deviation (σ), and t-test based on equations (9), (10), (11), and (12), respectively.
We performed a t-test at 95% confidence interval (CI) so as to obtain the interval estimates for the sample mean (IESM) because, for each location, our sample size is n = 7 ˂ 30. This test was carried out to reduce the level of uncertainty of the calculated mean which was based on a relatively small sample size. The IESM was calculated using:
IESM = Sm ± t (SEM) (12)
where t is the t-table value for "n − 1" degrees of freedom.
| Results|| |
The results of radiological risk parameters conducted on water samples collected from three rivers around some oil producing communities in Abia State, Nigeria, due to gross alpha, gross beta, and sum of the two radiations have been presented in [Table 1], [Table 2], [Table 3]. Summary of the results of statistical analyses of radiological risk parameters for the surveyed samples has been presented in [Table 4]. Furthermore, bar charts showing the comparisons between the radiological risk parameters (due to the sum of gross alpha and beta) and the standard permissible limits have been presented in [Figure 2], [Figure 3], [Figure 4]. The correlation between risk parameters due to alpha and beta radiations have also been presented in [Figure 5], [Figure 6], [Figure 7].
|Figure 2: Maximum and mean values of annual effective dose equivalentá,â compared with standard (0.1 mSv/y)|
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|Figure 3: Maximum and mean values of annual gonadal dose equivalentá,â compared with standard (0.3 mSv/y)|
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|Figure 4: Maximum and mean values of excess lifetime cancer riskα,β compared with standard (0.29 × 10−3)|
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|Figure 5: Correlation between annual effective dose equivalent from alpha and beta radiations for the surveyed areas|
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|Figure 6: Correlation between annual gonadal dose equivalent from alpha and beta radiations for the surveyed areas|
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|Figure 7: Correlation between excess lifetime cancer risk from alpha and beta radiations for the surveyed areas|
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|Table 1: Annual effective dose equivalent for gross alpha, gross beta, and sum of gross alpha and beta radiations |
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|Table 2: Annual gonadal dose equivalent for gross alpha, gross beta, and sum of gross alpha and beta radiations |
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|Table 3: Excess lifetime cancer risk for gross alpha, gross beta, and sum of gross alpha and beta radiations |
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|Table 4: Summary of the statistical analyses of radiological risk parameters for the surveyed samples |
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| Discussion|| |
[Table 1] and [Table 4] show that the combined AEDE due to gross alpha and gross beta radiations (AEDE T[α,β] ) in water samples from Owaza River ranged between 0.015 mSv/y and 1.718 mSv/y with a mean of 0.868 ± 0.221 mSv/y and a range of Sm of 0.327-1.409 mSv/y computed at 95% CI. AEDE T(α,β) in water samples from Imo River ranged between 0.549 mSv/y and 1.5 mSv/y with a mean of 1.008 ± 0.156 mSv/y and a range of Sm of 0.626-1.391 mSv/y computed at 95% CI. AEDE T(α,β) in water samples from Umorie River ranged between 0.058 and 1.652 mSv/y with a mean of 0.917 ± 0.214 mSv/y and a range of Sm of 0.394-1.440 mSv/y computed at 95% CI. These results show that AEDE T(α,β) for most of the sampled points are higher than the permissible limit of 0.1 mSv/y,  with the exceptions of OWR5 and UMR7 whose total AEDE are 0.015 mSv/y and 0.058 mSv/y respectively. However, the mean values of AEDE T(α,β) for each of the three surveyed rivers [presented in [Table 4] are all higher than the permissible limit. These results are comparable with the results which were computed to be 0.291 and 0.728 mSv/y (for the sum of alpha and beta) for borehole and well water in mining areas of Plateau State.  [Figure 2] shows a bar chart comparing the maximum calculated values of AEDE T(α,β) for the surveyed water samples and their mean values with permissible limit of 0.1 mSv/y. From the bar chart, the maximum and mean values are all above permissible limit. People who drink water from these rivers may likely be impacted negatively.
[Table 2] and [Table 4] show that AGDE T(α,β) in water samples from Owaza River ranged between 0.057 and 8.212 mSv/y with a mean of 4.048 ± 1.063 mSv/y and a range of Sm of 1.446-6.650 mSv/y computed at 95% CI. AGDE T(α,β) in water samples from Imo River ranged between 2.716 and 7.112 mSv/y with a mean of 4.756 ± 0.739 mSv/y and a range of Sm of 2.948- 6.564 mSv/y computed at 95% CI. AGDE T(α,β) in water samples from Umorie River ranged between 0.270 and 7.845 mSv/y with a mean of 4.295 ± 1.026 mSv/y and a range of Sm of 1.785-6.805 mSv/y computed at 95% CI. The mean values of AGDE T(α,β) for each of the sampled locations presented in [Table 4] show that apart from OWR5 and UMR7, other points recorded high values of AGDE that exceeded the world average limit of 0.3 mSv/y.  The maximum and mean values of AGDE T(α,β) compared with the standard are presented in the bar chart of [Figure 3]. These values are higher than the world standard of 0.3 mSv/y. These results imply that consumption of water from the surveyed sources could have possible negative impacts on the users.
[Table 3] and [Table 4] show that ELCR T(α,β) in water samples from Owaza River ranged between 0.052 × 10−3 and 6.014 × 10−3 with a mean of (3.038 ± 0.774) × 10−3 and a range of Sm of (1.143-4.933) × 10−3 computed at 95% CI. ELCR T(α,β) in water samples from Imo River ranged between 1.922 × 10−3 and 5.251 × 10−3 with a mean of (3.529 ± 0.547) × 10−3 and a range of Sm of (2.190-4.868) × 10−3 computed at 95% CI. ELCR T(α,β) in water samples from Umorie River ranged between 0.203 × 10−3 and 5.783 × 10−3 with a mean of (3.210 ± 0.748) × 10−3 and a range of Sm of (1.380-5.041) × 10−3 computed at 95% CI. The mean values of ELCR T(α,β) for the three surveyed rivers showed higher values than the world permissible limit of 0.29 × 10−3 for ELCR due to alpha and beta rays. All the sampled points except OWR5 and UMR7 recorded ELCR values that are higher than the world average of 0.29 × 10−3 .  Most values of ELCR computed in this work are greater than 6.0 × 10−4 estimated to be the risk of fatal and weighted nonfatal conditions over a lifetime (70 years) derived from the radiation dose of 0.1 mSv/y (which has been stated earlier as the World Health Organization [WHO] permissible limit for drinking water).  Drinking water from these surveyed sources could enhance one's probability of developing fatal and nonfatal health conditions (cancer and other hereditary effects). However, let us note that studies on radiation-induced cancer at low dose rates through the use of a simple proportional relationship between increments of dose and increased risk is a positive scientific assumption but with its associated uncertainties.  [Figure 4] compares the maximum and mean values of ELCR T(α,β) for the sample locations with the world average. The Figure shows that the maximum values of ELCR T(α,β) which correspond to OWR4, IMR1, and UMR1, and their mean values are higher than the world average.
The ranges of the mean of radiological risk parameters in water samples for the three surveyed rivers computed at 95% CI presented above tell us what the range of the true mean ought to be to reduce the level of uncertainty of the calculated mean which was based on a relatively small sample size (n = 7) for each of the surveyed areas. This range gives us an idea of the margin of error involved in using our small sample size to compute the mean of the sample distribution.
The linear regression models of [Figure 5], [Figure 6], [Figure 7] are used to compare the relationship between the alpha and beta rays computed for the sampled points. The R2 (determination coefficient) values for the three linear regression plots are all <0.5 implying a weak correlation between the two radiating particles. Since there is a weak correlation between the trend of emissions of alpha and beta radiations from the surveyed sources, it is recommended that one computes independently the radiological risk parameters associated with the alpha and beta rays to ascertain their total radiological contributions.
| Conclusion|| |
Three radiological risk parameters (due to the sum of gross alpha and beta radiations) have been computed for water samples collected from three rivers around some selected oil producing areas of Abia State. All the computed radiological risk parameters except two sampled points are above the world average limits and the WHO permissible limit for ingested water (0.1 mSv/y).  Drinking water from these surveyed sources could impact negatively on the health status of the end users. It is therefore very important that during radiological studies, apart from the assessment of the gamma rays, the impact of alpha and beta rays should also be understudied because of their relatively high ionization potentials. All water bodies around oil producing areas should be radiologically screened periodically before consumption to ensure that they are not radiologically overburdened due to crude oil pollution.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7]
[Table 1], [Table 2], [Table 3], [Table 4]