TY - JOUR
AU - Kim,, Juyoul
AB - Abstract Mining and milling processes could cause potential radiological exposures to the public. The objective of this study was to estimate the off-site radiological doses expected to be received by the public as a result of uranium mining and milling activities at Mkuju River Project in the United Republic of Tanzania. MILDOS-AREA was used to estimate off-site doses along with RESRAD-OFFSITE for comparison and verification. Since the mining has not yet started, the conceptual scenario was chosen. Using the concept of the most exposed individual, the location of the nearest residence (receptor) was chosen at 2.5 km from the site with other receptors being the fence boundary and grazing area being at 1.0 and 1.8 km, respectively. Yellowcake stack (point source), ore pad and two tailing piles where each had an area of 2.5 × 105 m2 were chosen to be the source of radiological contamination. The radiological source term was obtained from the concentration of 226Ra and 232Th in soil obtained from the previous studies of environmental impact assessments. Meteorological and site-specific data were used for this analysis. The estimated total effective dose equivalent (TEDE) for the nearest residence which was calculated by MILDOSE-AREA ranged from 2.5 × 10−2 to 4.45 × 10−2 mSv/y during the operation of 13 y. The result of RESRAD-OFFSITE ranged from 7.19 × 10−2 mSv/y for the first year to 7.43 × 10−2 mSv/y in the final year. This implied all the estimated TEDEs were below the dose limit and dose constraint of 1 and 0.3 mSv/y, respectively, as suggested by the International Atomic Energy Agency. Hence, it was found that there was no potential radiological concern of uranium mining at Mkuju River Project. It was found that using MILDOS-AREA it is possible to estimate dose at different distances from the facility. Therefore, this study apart from estimating the off-site doses, it can be used for planning of public and social premises before the commencement of the project. That is the distance from the facility where the public should be located as well as other locations for social activities. INTRODUCTION Minerals of all kinds and raw materials of natural origin contain 238U, 235U, 232Th and their decay progeny, as well as 40K. In most cases, the concentrations of these radionuclides are insufficient to result in a radiological hazard. Hence, for radiation protection, they are not regarded as radioactive material. However, when the concentration of these radionuclides is significantly higher than the normal background levels, there may be a radiological concern for potential exposures and therefore need for regulatory measures(1). Also, mining and processing of these minerals from the earth’s crust may cause uneven distribution of these radionuclides in the materials along the process. Consequently, the concentration of these radionuclides in the materials along the process may be higher than in the original mineral ore (raw material)(2). According to the International Atomic Energy Agency (IAEA), the concentration of natural radionuclides of 238U, 235U and 232Th and their decay progeny, should not exceed 1 Bq/g and 10 Bq/g for 40K(1). The main source of human exposure from the natural source of radiation is radon and its short-lived decay products. Inhalation of the short-lived decay progeny of 222Rn causes exposure of the lung by being deposited to the walls of the bronchial tree. Hence, is said to be responsible for the lung cancer(3). According to the World Health Organization, radon is the second most important cause of lung cancer after smoking when talking of the general population(4). Mkuju River Project is an area with elevated uranium ore deposits which is viable for uranium mining. Hence, mining and milling activities in this area are expected to increase the potential public exposure. Therefore, there is a need to evaluate the radiological impact to the public living in the vicinity of the mining site. Various radiological studies have been conducted at the Mkuju River Project. Most of them were based on the determination of the pre-mining radiological baseline. Therefore, all of these studies did not consider the contribution of uranium mining and milling activities to radiological exposure of the public. Hence, this study is unique and important because it is aiming to address this discrepancy. The only study which addressed the impact of uranium mining is the environmental impact assessment (EIA). However, this study was conducted by the mining company responsible for the same project of mining at Mkuju. For regulatory purposes, there is a need to perform a different study apart from the EIA and compare the results. It is for this reason this study was conducted and the results can be used as a baseline for regulatory control purposes. It is unlikely for naturally occurring radiative materials (NORMs) to cause an exposure dose that exceeds 1 mSv/y to a member of the public. However, with these NORMs in a bulk form such as tailing piles and waste rocks, an individual can receive the dose that exceeds this limit(1). There are different types of uranium mining, namely in situ leach, open-cut and underground mining. In this project, open-pit mining is expected to be used to extract uranium from the ore. This is a surface mining technique that extracts minerals from an open pit in the ground. Mining activities will be performed through the mechanical excavation of the ore and therefore there will be no use of explosives. This mechanical excavation will be carried out with the use of heavy equipment such as the 7 m3 extractors and 90-tonne rigid haul trucks. The milling of uranium is expected to be carried out by scrubbing and acid leaching method. The scrubbing process will use water to remove ore materials while sulfuric acid will be added to extract uranium from mineral. The final product which is the yellowcake will be transported by track to Dar es Salaam or Mtwara port for export(5). Therefore, it is important to manage effectively the mining and milling facilities throughout the life cycle of the facility to maintain radiation safety and avoid health effects associated with uranium mining(6). The objectives of this study were to estimate the radiological off-site doses received by the public living close to the site as the result of mining and milling activities. This study is very important because will act as the baseline document to assist the regulatory body to implement its mandatory functions. This is because currently no offsite dose assessment has been done except the EIA. Also, since the EIA dose assessment was done using manual calculation, this study is the unique one using MILDOS-AREA computer software to calculate these off-site doses. Therefore, the results of the two methods will be compared. The summary of the previous studies that have been conducted at the Mkuju River Project together is presented in Table 1 together with their findings(7–11). Table 1 Previous studies cHonducted at Mkuju River Project. Study purpose . Findings . Reference . 1. Radioactivity levels of 226Ra, 232Th and 40K in soil and plants for estimation of transfer factors and effective dose A strong positive correlation (r) of 0.947 and 0.950 for 226Ra and 232Th, respectively, between values determined in soils and plants. That is, the distribution of radionuclides in soils is directly proportional to the corresponding radionuclides in plants Banzi et al.(7) 2 a) Natural radioactivity in Soil 226Ra (24.94–4200) Bq/kg 232Th (20.86–220) Bq/kg 40K (344.5–1466.10) Bq/kg Banzi et al.(8) b) Its contribution to population exposure Soils in the vicinity could pose a less radiological risk compared to concession soil 3 a) Natural radioactivity in Water Activity concentrations in water samples from the concession area was found to be higher in groundwater than in surface water. However, these values from each of the water sources were lower than the recommended maximum dose of 0.1 mSv/y Banzi et al.(9) b) Population human health risk The annual effective doses and carcinogenic risks related to exposure to water within and around the MRP were significantly below the recommended limits. Activity concentration ratios for 234U/238U and 226Ra/234U shows higher values in the vicinity of the project than within the concession area 4. Natural Radioactivity in soil and water from Likuyu Village, the neighborhood of Mkuju Uranium Deposit The mean concentration of 238U (51.7 Bq/kg) in soil were higher than the world average but within the world range. The mean concentration of 232Th is comparable to the world average Mazunga et al.(10) The radionuclide concentration of in water was comparable to the radionuclide concentration in the literature cited 5. EIA, The Mkuju River Project, Namtumbo (Radiological Assessment Report) Refer(11) Mantra Tanzania(11) Study purpose . Findings . Reference . 1. Radioactivity levels of 226Ra, 232Th and 40K in soil and plants for estimation of transfer factors and effective dose A strong positive correlation (r) of 0.947 and 0.950 for 226Ra and 232Th, respectively, between values determined in soils and plants. That is, the distribution of radionuclides in soils is directly proportional to the corresponding radionuclides in plants Banzi et al.(7) 2 a) Natural radioactivity in Soil 226Ra (24.94–4200) Bq/kg 232Th (20.86–220) Bq/kg 40K (344.5–1466.10) Bq/kg Banzi et al.(8) b) Its contribution to population exposure Soils in the vicinity could pose a less radiological risk compared to concession soil 3 a) Natural radioactivity in Water Activity concentrations in water samples from the concession area was found to be higher in groundwater than in surface water. However, these values from each of the water sources were lower than the recommended maximum dose of 0.1 mSv/y Banzi et al.(9) b) Population human health risk The annual effective doses and carcinogenic risks related to exposure to water within and around the MRP were significantly below the recommended limits. Activity concentration ratios for 234U/238U and 226Ra/234U shows higher values in the vicinity of the project than within the concession area 4. Natural Radioactivity in soil and water from Likuyu Village, the neighborhood of Mkuju Uranium Deposit The mean concentration of 238U (51.7 Bq/kg) in soil were higher than the world average but within the world range. The mean concentration of 232Th is comparable to the world average Mazunga et al.(10) The radionuclide concentration of in water was comparable to the radionuclide concentration in the literature cited 5. EIA, The Mkuju River Project, Namtumbo (Radiological Assessment Report) Refer(11) Mantra Tanzania(11) Open in new tab Table 1 Previous studies cHonducted at Mkuju River Project. Study purpose . Findings . Reference . 1. Radioactivity levels of 226Ra, 232Th and 40K in soil and plants for estimation of transfer factors and effective dose A strong positive correlation (r) of 0.947 and 0.950 for 226Ra and 232Th, respectively, between values determined in soils and plants. That is, the distribution of radionuclides in soils is directly proportional to the corresponding radionuclides in plants Banzi et al.(7) 2 a) Natural radioactivity in Soil 226Ra (24.94–4200) Bq/kg 232Th (20.86–220) Bq/kg 40K (344.5–1466.10) Bq/kg Banzi et al.(8) b) Its contribution to population exposure Soils in the vicinity could pose a less radiological risk compared to concession soil 3 a) Natural radioactivity in Water Activity concentrations in water samples from the concession area was found to be higher in groundwater than in surface water. However, these values from each of the water sources were lower than the recommended maximum dose of 0.1 mSv/y Banzi et al.(9) b) Population human health risk The annual effective doses and carcinogenic risks related to exposure to water within and around the MRP were significantly below the recommended limits. Activity concentration ratios for 234U/238U and 226Ra/234U shows higher values in the vicinity of the project than within the concession area 4. Natural Radioactivity in soil and water from Likuyu Village, the neighborhood of Mkuju Uranium Deposit The mean concentration of 238U (51.7 Bq/kg) in soil were higher than the world average but within the world range. The mean concentration of 232Th is comparable to the world average Mazunga et al.(10) The radionuclide concentration of in water was comparable to the radionuclide concentration in the literature cited 5. EIA, The Mkuju River Project, Namtumbo (Radiological Assessment Report) Refer(11) Mantra Tanzania(11) Study purpose . Findings . Reference . 1. Radioactivity levels of 226Ra, 232Th and 40K in soil and plants for estimation of transfer factors and effective dose A strong positive correlation (r) of 0.947 and 0.950 for 226Ra and 232Th, respectively, between values determined in soils and plants. That is, the distribution of radionuclides in soils is directly proportional to the corresponding radionuclides in plants Banzi et al.(7) 2 a) Natural radioactivity in Soil 226Ra (24.94–4200) Bq/kg 232Th (20.86–220) Bq/kg 40K (344.5–1466.10) Bq/kg Banzi et al.(8) b) Its contribution to population exposure Soils in the vicinity could pose a less radiological risk compared to concession soil 3 a) Natural radioactivity in Water Activity concentrations in water samples from the concession area was found to be higher in groundwater than in surface water. However, these values from each of the water sources were lower than the recommended maximum dose of 0.1 mSv/y Banzi et al.(9) b) Population human health risk The annual effective doses and carcinogenic risks related to exposure to water within and around the MRP were significantly below the recommended limits. Activity concentration ratios for 234U/238U and 226Ra/234U shows higher values in the vicinity of the project than within the concession area 4. Natural Radioactivity in soil and water from Likuyu Village, the neighborhood of Mkuju Uranium Deposit The mean concentration of 238U (51.7 Bq/kg) in soil were higher than the world average but within the world range. The mean concentration of 232Th is comparable to the world average Mazunga et al.(10) The radionuclide concentration of in water was comparable to the radionuclide concentration in the literature cited 5. EIA, The Mkuju River Project, Namtumbo (Radiological Assessment Report) Refer(11) Mantra Tanzania(11) Open in new tab MATERIALS AND METHODS Study area Mkuju River uranium mine is located in southern Tanzania in Namtumbo district in Ruvuma region, between latitude 9° 59′50″ to 10° 07′15″ S and longitudes 36° 30′00″ to 36° 37′55″ E and is about 180 km from Songea town as shown in Figure 1. It is partially within Selous Game Reserve, a World Heritage site that is under the care of the Government of Tanzania and UNESCO. This area contains a large amount of uranium deposit viable for mining with an estimated 25 200 tU. The annual production capacity is estimated to be 1600 tU y−1 over a minimum period of 12 y. The weather in this area is of two major seasons of the year. The first is a rainy season, which starts in January and ends in April with an average rainfall of 70 mm and temperatures ranging from 11 to 29°C. The second is a dry season, which starts in May and ends in December with temperatures ranging from 14 to 37°C(5,7). The closest village (most exposed population) to the site was identified to be Likuyu-Seka Maganga, which is situated 53 km from the site. Analysis model Uranium mining and milling facilities disperse the radionuclides from the area of original contamination to the outside environment through different media such as atmosphere, surface water and groundwater. The concentration of these contaminants in these media can be converted into a radiation dose. To be able to estimate the dose in the outside environment, some computer analysis software has been developed. MILDOS-AREA and RESRAD-OFFSITE computer codes were selected for this study because they can model the dispersion of radionuclides and estimate the doses at the locations far from the area of contamination. These computer software models the transport of the contaminants from the primary contamination to an agricultural area, grazing area, a dwelling area, surface water and groundwater(12,13). Some similarities between MILDOS-AREA and RESRAD-OFFSITE codes include both having the capability to model area sources. They both can estimate the radiological dose outside the area of primary contamination. Also, they both use the Gaussian plume dispersion model to evaluate the downwind transport of the radionuclides from continuing releases from the source. However, there are some differences between MILDOS-AREA and RESRAD-OFFSITE codes. For example, while RESRAD-OFFSITE can estimate the excess cancer risk, MILDOS-AREA does not support that function. Also, RESRAD-OFFSITE considers surface water and groundwater pathways among others but MILDOS-AREA has no option for surface water and groundwater pathways. MILDOS-AREA uses dose conversion factors of International Commission on Radiological Protection 26 (ICRP 26), whereas the RESRAD-OFFSITE uses those of ICRP 60, 68 and 72. Figure 1 Open in new tabDownload slide Location of Mkuju River Project Figure 1 Open in new tabDownload slide Location of Mkuju River Project MILDOS-AREA In this study, the MILDOS-AREA computer code was used to calculate the off-site radiation dose within an 80 km radius. This computer code was developed by Argonne National Laboratories for US Nuclear Regulatory Commission (US NRC). This code is used to estimate the radiological impacts of airborne emissions from uranium mining and milling facilities. The license applicants and US NRC has been using this code routinely in different uranium recovery operations for radiological impact and compliance evaluation purposes(14). This computer software code is useful and includes support for ores containing 232Th and its daughter radionuclides as well as 238U and its daughter radionuclides(12). This computer code uses a Gaussian plume dispersion model to calculate radiological release and transport root from point sources and different area sources. The transport model included mechanisms such as radioactive decay, plume depletion by deposition, ingrowth of daughter radionuclides and re-suspension of deposited radionuclides. The considered pathways are inhalation; external exposure from ground shine; cloud immersion and ingestion of vegetables, meat and milk(14). Available to the code include the individual dose commitments, total individual dose commitments and annual population dose commitments. The conversion factors for calculations of the committed dose are derived from recommendations of the ICRP and it considers age-specific(15). This computer code is capable of estimating the dose received by various receptors with the largest source of emissions being stockpiles, tailings impoundments and uranium dryer stack(16). The dose calculation using the MILDOS-AREA code is more site-specific of the problem in hands, therefore enables the user to define the parameters of the location in a topic(12). MILDOS-AREA computer code has been used successfully in some areas in uranium mining and processing facilities for estimation of radiological impact resulting from uranium mining and milling operations. MILDOS-AREA uses Gaussian plume dispersion for both point and area sources to evaluate the downwind transport of these radionuclides in particulate form and radon gas from continuing releases from the source. The model considers dry and wet deposition as an important factor in the depletion of the plume(17). The dispersion of the materials modeled by MILDOS-AREA is represented by the simplified Gaussian time-dependent dispersion equation as follows. $$\begin{equation} {C}_a\left(i,x,y\right)=\frac{Q_{xi}}{\pi{\sigma}_y{\sigma}_z{u}_H}\exp \left[-\left(\frac{y^2}{2{\sigma^2}_y}+\frac{H^2}{2{\sigma^2}_z}\right)\right], \end{equation}$$(1) where, |${C}_a(i,x,y)$| = air concentration of radionuclide i at (x, y) from a release at (0, 0, |$H$|⁠) at time t after release (Bq/m3), |${Q}_{xi}$| = depleted source strength of nuclide i at distance x (Bq/s), |${\sigma}_y$| = horizontal dispersion coefficient (m), |${\sigma}_z$| = vertical dispersion coefficient (m), |$x$| = downwind receptor distance from the release point (m), |$y$| = crosswind distance from the plume centerline (m), |${u}_H$| = average wind speed at the effective release height (m/s), |$H$| = effective release height (m). For an individual receptor, the external dose is calculated by considering the exposure due to ground activity and airborne concentration taking into consideration both indoor and outdoor exposure. $$\begin{eqnarray} &&{D}_{\mathit{\operatorname{ext}},0}\left(x,{t}_j\right)={10}^{12}\left({F}_{in}{S}_{in}+{F}_{out}\right)\nonumber\\ &&\times\left(\ \sum_i\left[{DC}_{cld, io}{C}_{air}\left(i,x,{t}_j\right)+{DC}_{gnd, io}\ {C}_g\left(i,x,{t}_j\right)\right]\right) \end{eqnarray}$$(2) where, |${D}_{\mathit{\operatorname{ext}},0}(x,{t}_j)$| = external dose rate to organ o in individual from outside airborne and deposited activity at distance x and time step j (mSv/y), 1012 = unit conversion factor, |${F}_{in},{F}_{out}$| = indoor and outdoor occupancy fractions, respectively (unitless), |${S}_{in}$| = indoor shielding factor (unitless), |${C}_{air}(i,x,{t}_j)$|= total air concentration of radionuclide i during time step tj at distance x (Bq/m3), |${C}_g(i,x,{t}_j)$| = ground concentration of radionuclide i from a given source after time step j (Bq/m2), |${DC}_{cld, io}$| = external air immersion dose coefficient for radionuclide i in organ o (mSv/y/Bq/m3), |${DC}_{gnd, io}$| = external ground-shine dose coefficient for radionuclide i in organ o (mSv/y/Bq/m2). Inhalation doses are calculated by using the total air concentrations for particulates and radon and its progeny. For an individual in age group k for all particle sizes the total inhalation dose is calculated by using the following expression. $$\begin{equation} {D}_{inh, kop}\left(x,{t}_j\right)={10}^{12}{\sum}_P{\sum}_i{C}_{air}\ \left(i,p,x,{t}_j\right)\ {DC}_{inh, ikop} IR \end{equation}$$(3) where, |${D}_{inh, kop}(x,{t}_j)$| = inhalation dose rate to organ o in an individual in age group k from particulates from time step tj (mSv/y), 1012 = unit conversion factor, |${C}_{air}\ (i,p,x,{t}_j)=$| total air concentration of radionuclide i on particle size p during time step tj at distance x (Bq/m3), |${\mathrm{DC}}_{inh, ikop}$| = inhalation dose coefficient for radionuclide i, age group k, organ o and particle size p (mSv/Bq), IR = inhalation rate (7300 m3/y). Ingestion doses are calculated by using the concentration of radionuclides present in agriculture produce (vegetables), in meat and milk. For an individual, the annual radionuclide intake through ingestion is calculated as follows. $$\begin{eqnarray} {I}_k\left(i,x,{t}_j\right)&=&{U}_{mk}{C}_m\left(i,x\ {t}_j\right)+{U}_{bk}{C}_b\left(i,x\ {t}_j\right)\nonumber\\&&+{F}_{va}{U}_{vk}{\sum}_v{F}_{vck}{C}_V\left(i,x\ {t}_j\right) \end{eqnarray}$$(4) where, |${I}_k(i,x,{t}_j)$| = ingestion rate of radionuclide i by an individual in age group k during time step tj (Bq/y), |${U}_{mk},{U}_{bk}$| = milk (L/y) and meat (kg/y) ingestion rates for age group k, |${C}_m(i,x\ {t}_j)$|= average milk concentration for radionuclide i during time step tj (Bq/L), |${C}_b(i,x\ {t}_j)$| = average meat concentration for radionuclide i during time step tj (Bq/kg), |${F}_{va}$| = fraction of radionuclide activity remaining in vegetables after food preparation (unitless), |${U}_{vk}$| = vegetable ingestion rate for age group k (kg/y) (wet weight), |${F}_{vck}$| = fraction of vegetable category c consumed by age group k (unitless), |${C}_V(i,x\ {t}_j)$| = concentration of radionuclide i in vegetation type v during time step tj (Bq/kg) (wet weight). Therefore, the ingestion dose for an organ o from the radionuclide i is then calculated by the following expression. $$\begin{equation} {D}_{ing, ko}\left(i,x\ {t}_j\right)={I}_k\left(i,x\ {t}_j\right)\ {DC}_{ing, iko} \end{equation}$$(5) where, |${D}_{ing, ko}(i,x\ {t}_j)$| = ingestion dose rate to organ o from radionuclide i of an individual in age group k from time step tj (mSv/y), |${DC}_{ing, iko}$| = ingestion dose coefficient for radionuclide I in organ o of an individual in age group k (mSv/Bq ingested). RESRAD-OFFSITE The origin of the RESRAD Family is the RESRAD-ONSITE, which evaluates the radiological dose and excess cancer risk to an individual who is exposed as a result of residing or working in an area of contamination with radionuclides. RESRAD-ONSITE was developed in the 1980s and has undergone several improvements to meet user’s requirements. The RESRAD-OFFSITE came into use in the 1990s to complement the RESRAD-ONSITE which could not predict the exposure to a receptor located outside the area of primary contamination. Since its development, RESRAD-OFFSITE has been undergoing different changes to improve the code. These changes were associated with the addition of a new sub-model/model to predict better the transport of the radionuclides in different media. These improvements have allowed RESRAD-OFFSITE to assess various complex sites. RESRAD-OFFSITE considers nine exposure pathways. These include direct exposure from contamination in soil, inhalation of particulates, inhalation of short-lived radon progeny, ingestion of plant food, meat, milk, aquatic foods, water and soil. The primary contamination as a source of all releases assumed to be within a layer of soil. The individual exposure pathway considers contaminant release through the atmosphere, surface water and groundwater (13). RESRAD-OFFSITE calculates the radionuclide concentrations in different media involved in the environment as a function of time. This concentration is used to calculate the dose to the individual associated with that pathway. The individual pathway doses are summed to obtain the total dose. The total annual dose, D (t), received by a member of the critical population group at time t following the radiological survey of the site (mSv/y) is given by $$\begin{equation} D(t)={\sum}_{i=1,n}\sum_p{D}_{ip}(t), \end{equation}$$(6) where, |${D}_{ip}(t)$| is the annual dose received by a member of the critical population group starting at time t from the ith principal radionuclide transported through the pth environmental pathway, together with its associated decay products (mSv/y). D(t) is the sum of annual doses over all active pathways, p, and the number of principal radionuclide present, n. RESRAD-OFFSITE uses a Gaussian plume dispersion model to account for atmospheric transport release of radionuclides from the contaminated area to the atmosphere. Gaussian dispersion model for the discrete puff generated from a point source that is time-dependent with an effective release height H above the ground level can be represented by the following equation. $$\begin{align} &{C}_a\left(i,x,y,z,t\right)\nonumber\\ &\quad=\frac{Q_{xi}}{{\left(2\pi \right)}^{\frac{3}{2}}{\sigma^2}_y{\sigma}_z}{e}^{-\frac{r^2}{2{\sigma^2}_y}}\ \left({e}^{-\frac{{\left(z-H\right)}^2}{2{\sigma^2}_z}}+{e}^{-\frac{{\left(z+H\right)}^2}{2{\sigma^2}_z}}\right) \end{align}$$(7) where, Table 2 Receptor names and their distance from the site in MILDOS-AREA. Receptor name . X (km) . Y (km) . Fence boundary 1.0 0.2 Grazing area 1.8 0.5 Nearest residence 2.5 1.0 Receptor name . X (km) . Y (km) . Fence boundary 1.0 0.2 Grazing area 1.8 0.5 Nearest residence 2.5 1.0 Open in new tab Table 2 Receptor names and their distance from the site in MILDOS-AREA. Receptor name . X (km) . Y (km) . Fence boundary 1.0 0.2 Grazing area 1.8 0.5 Nearest residence 2.5 1.0 Receptor name . X (km) . Y (km) . Fence boundary 1.0 0.2 Grazing area 1.8 0.5 Nearest residence 2.5 1.0 Open in new tab Table 3 Name of the sources, dimensions and areas in MILDOS-AREA. Source . Area (m2) . Yellowcake stack Point source Ore Pad 2.5 × 105 Tailing 1 2.5 × 105 Tailing 2 2.5 × 105 Total Area 7.5 x105 Source . Area (m2) . Yellowcake stack Point source Ore Pad 2.5 × 105 Tailing 1 2.5 × 105 Tailing 2 2.5 × 105 Total Area 7.5 x105 Open in new tab Table 3 Name of the sources, dimensions and areas in MILDOS-AREA. Source . Area (m2) . Yellowcake stack Point source Ore Pad 2.5 × 105 Tailing 1 2.5 × 105 Tailing 2 2.5 × 105 Total Area 7.5 x105 Source . Area (m2) . Yellowcake stack Point source Ore Pad 2.5 × 105 Tailing 1 2.5 × 105 Tailing 2 2.5 × 105 Total Area 7.5 x105 Open in new tab Figure 2 Open in new tabDownload slide Conceptual diagram for locations and distances between the individual receptors and source. Figure 2 Open in new tabDownload slide Conceptual diagram for locations and distances between the individual receptors and source. |${C}_a(i,x,y,z,t)$| = is the concentration of radionuclide |$i$| at (x, y, z) at time t after release, from a release at (0, 0, H) (Bq/m3), |$x$| = downwind distance from the release point (m), y = crosswind distance from the plume centerline (m), z = vertical distance above the ground level (m), t = time since the release (s), |$H$| = effective release height (m), |${Q}_{xi}$| = depleted source strength of radionuclide i at a distance of x from the release (Bq), |${\sigma}_y$| = horizontal dispersion coefficient (m), |${\sigma}_z$| = vertical dispersion coefficient (m), r 2 = square of the distance from the center of the puff to the receptor location (m2). Input parameters MILDOS-AREA In this scenario, the conceptual site was designed and the receptor was chosen based on the concept of the most exposed individual. The individual receptors were assigned their locations based on the wind direction. That is the dominant wind direction at Mkuju is from E to W, so the assumption was to locate the most exposed individual at the location where the more radiological effect is anticipated because most of the radioactive dust through atmospheric dispersion must be transported through this direction. Table 2 illustrates the individual receptors and their distances from the sources. The sources of radioactive materials releases assumed in this conceptual scenario are indicated in Table 3, which include Yellowcake Stack,  Ore  Pad  and  two tailing piles. Figure 2 is the Table 4 The specific activity of radionuclides in the soil used in the calculation in MILDOS-AREA and RESRAD-OFFSITE(8). Radionuclide in the ore . . Specific activity (Bq/kg) . 238U 4.2 × 103 230Th 4.2 × 103 226Ra 4.2 × 103 210Pb 4.2 × 103 232Th 2.2 × 102 228Ra 2.2 × 102 228Th 2.2 × 102 Radionuclide in the ore . . Specific activity (Bq/kg) . 238U 4.2 × 103 230Th 4.2 × 103 226Ra 4.2 × 103 210Pb 4.2 × 103 232Th 2.2 × 102 228Ra 2.2 × 102 228Th 2.2 × 102 Open in new tab Table 4 The specific activity of radionuclides in the soil used in the calculation in MILDOS-AREA and RESRAD-OFFSITE(8). Radionuclide in the ore . . Specific activity (Bq/kg) . 238U 4.2 × 103 230Th 4.2 × 103 226Ra 4.2 × 103 210Pb 4.2 × 103 232Th 2.2 × 102 228Ra 2.2 × 102 228Th 2.2 × 102 Radionuclide in the ore . . Specific activity (Bq/kg) . 238U 4.2 × 103 230Th 4.2 × 103 226Ra 4.2 × 103 210Pb 4.2 × 103 232Th 2.2 × 102 228Ra 2.2 × 102 228Th 2.2 × 102 Open in new tab conceptual diagram of the receptors and their distances from the sources. The source term, which is the radionuclide, concentrations in the soil were obtained Table 5 Other input parameters in MILDOS-AREA. Item . Value . Reference . Drying operation  Yellowcake production rate (kg/d) 4971 Mantra Tanzania(11)  Fraction released to stack 0.001 Default value  Inside stack diameter (m) 1.2 Default value Plume rice  Momentum driven  Effluent exit velocity (m/s) 14.2 Default value Activity fractions  Thorium 0.005 Default value  Radium 0.005 Default value  Others 0.005 Default value Local meteorological parameters  Anemometer height (m) 10 Default value  Ambient temperature (K) 283 Default value  Mean annual afternoon mixing height (m) 1600 Default value Air dispersion calculations  Briggs urban height cutoff (m) 50 Default value  Area source grid block size (m) 5 Default value  Maximum distance for area source calculation (m) 1000 Default value Area source term  Concentration of 238U, 230Th, 226Ra and 210Pb (Bq/kg) 4200 Banzi et al.(8)  Concentration of 232Th, 228Ra and 228Th, (Bq/kg) 220 Banzi et al.(8)  222Rn release rate (Bq/m2-s) 4200 Banzi et al.(8)  220Rn release rate (Bq/m2-s) 220 Banzi et al.(8) Particulate erosion model  Tailing mass < 20 um (%) 3 Default value  Surface roughness Ht. (m) 0.1 Default value  Particle density (g/m3) 2400000 Default value  Water content (wt. %) 0.1 Default value  Salting particle diameter (m) 0.0003 Default value Food parameters  Vegetable production (kg/y) 1,840,000 Assumed1% of the county(19)  Vegetable consumption rate (adult) (kg/y) 57.67 Kinabo(20)  Meat production (kg/y) 899,346 Assumed 1% of the country(21)  Meat consumption rate (adult) (kg/y) 12 Wilson(21)  Milk consumption rate (adult) (kg/y) 45 Katjiuongua and Nelgen(22) Item . Value . Reference . Drying operation  Yellowcake production rate (kg/d) 4971 Mantra Tanzania(11)  Fraction released to stack 0.001 Default value  Inside stack diameter (m) 1.2 Default value Plume rice  Momentum driven  Effluent exit velocity (m/s) 14.2 Default value Activity fractions  Thorium 0.005 Default value  Radium 0.005 Default value  Others 0.005 Default value Local meteorological parameters  Anemometer height (m) 10 Default value  Ambient temperature (K) 283 Default value  Mean annual afternoon mixing height (m) 1600 Default value Air dispersion calculations  Briggs urban height cutoff (m) 50 Default value  Area source grid block size (m) 5 Default value  Maximum distance for area source calculation (m) 1000 Default value Area source term  Concentration of 238U, 230Th, 226Ra and 210Pb (Bq/kg) 4200 Banzi et al.(8)  Concentration of 232Th, 228Ra and 228Th, (Bq/kg) 220 Banzi et al.(8)  222Rn release rate (Bq/m2-s) 4200 Banzi et al.(8)  220Rn release rate (Bq/m2-s) 220 Banzi et al.(8) Particulate erosion model  Tailing mass < 20 um (%) 3 Default value  Surface roughness Ht. (m) 0.1 Default value  Particle density (g/m3) 2400000 Default value  Water content (wt. %) 0.1 Default value  Salting particle diameter (m) 0.0003 Default value Food parameters  Vegetable production (kg/y) 1,840,000 Assumed1% of the county(19)  Vegetable consumption rate (adult) (kg/y) 57.67 Kinabo(20)  Meat production (kg/y) 899,346 Assumed 1% of the country(21)  Meat consumption rate (adult) (kg/y) 12 Wilson(21)  Milk consumption rate (adult) (kg/y) 45 Katjiuongua and Nelgen(22) Open in new tab Table 5 Other input parameters in MILDOS-AREA. Item . Value . Reference . Drying operation  Yellowcake production rate (kg/d) 4971 Mantra Tanzania(11)  Fraction released to stack 0.001 Default value  Inside stack diameter (m) 1.2 Default value Plume rice  Momentum driven  Effluent exit velocity (m/s) 14.2 Default value Activity fractions  Thorium 0.005 Default value  Radium 0.005 Default value  Others 0.005 Default value Local meteorological parameters  Anemometer height (m) 10 Default value  Ambient temperature (K) 283 Default value  Mean annual afternoon mixing height (m) 1600 Default value Air dispersion calculations  Briggs urban height cutoff (m) 50 Default value  Area source grid block size (m) 5 Default value  Maximum distance for area source calculation (m) 1000 Default value Area source term  Concentration of 238U, 230Th, 226Ra and 210Pb (Bq/kg) 4200 Banzi et al.(8)  Concentration of 232Th, 228Ra and 228Th, (Bq/kg) 220 Banzi et al.(8)  222Rn release rate (Bq/m2-s) 4200 Banzi et al.(8)  220Rn release rate (Bq/m2-s) 220 Banzi et al.(8) Particulate erosion model  Tailing mass < 20 um (%) 3 Default value  Surface roughness Ht. (m) 0.1 Default value  Particle density (g/m3) 2400000 Default value  Water content (wt. %) 0.1 Default value  Salting particle diameter (m) 0.0003 Default value Food parameters  Vegetable production (kg/y) 1,840,000 Assumed1% of the county(19)  Vegetable consumption rate (adult) (kg/y) 57.67 Kinabo(20)  Meat production (kg/y) 899,346 Assumed 1% of the country(21)  Meat consumption rate (adult) (kg/y) 12 Wilson(21)  Milk consumption rate (adult) (kg/y) 45 Katjiuongua and Nelgen(22) Item . Value . Reference . Drying operation  Yellowcake production rate (kg/d) 4971 Mantra Tanzania(11)  Fraction released to stack 0.001 Default value  Inside stack diameter (m) 1.2 Default value Plume rice  Momentum driven  Effluent exit velocity (m/s) 14.2 Default value Activity fractions  Thorium 0.005 Default value  Radium 0.005 Default value  Others 0.005 Default value Local meteorological parameters  Anemometer height (m) 10 Default value  Ambient temperature (K) 283 Default value  Mean annual afternoon mixing height (m) 1600 Default value Air dispersion calculations  Briggs urban height cutoff (m) 50 Default value  Area source grid block size (m) 5 Default value  Maximum distance for area source calculation (m) 1000 Default value Area source term  Concentration of 238U, 230Th, 226Ra and 210Pb (Bq/kg) 4200 Banzi et al.(8)  Concentration of 232Th, 228Ra and 228Th, (Bq/kg) 220 Banzi et al.(8)  222Rn release rate (Bq/m2-s) 4200 Banzi et al.(8)  220Rn release rate (Bq/m2-s) 220 Banzi et al.(8) Particulate erosion model  Tailing mass < 20 um (%) 3 Default value  Surface roughness Ht. (m) 0.1 Default value  Particle density (g/m3) 2400000 Default value  Water content (wt. %) 0.1 Default value  Salting particle diameter (m) 0.0003 Default value Food parameters  Vegetable production (kg/y) 1,840,000 Assumed1% of the county(19)  Vegetable consumption rate (adult) (kg/y) 57.67 Kinabo(20)  Meat production (kg/y) 899,346 Assumed 1% of the country(21)  Meat consumption rate (adult) (kg/y) 12 Wilson(21)  Milk consumption rate (adult) (kg/y) 45 Katjiuongua and Nelgen(22) Open in new tab from the results of a previous study at the site. The radionuclides calculated in the soil were 226Ra and 232Th(8). The rest of the concentrations were estimated based on circular equilibrium whereby the concentration of the decay product is assumed to be equal to the concentration of the parent(18). Source term (specific activity of radionuclides) used in the calculation are summarized in Table 4(8) while the other input parameters used in MILDOS-AREA calculations are summarized in Table 5(8,11,19–22). The meteorological data such as wind speed and wind directions at Mkuju River site were collected from the website(23) for a period of 3 y from 2017 to 2020. These data were processed and the results of these processed meteorological data are presented in Figure 3 (the wind rose diagram). The food consumption data used in this study are summarized in Table 6 and Table 7(20,21). RESRAD-OFFSITE The site layout in RESRAD-OFFSITE was described in such a way that the area of primary contamination is equal to the area of the sources used in MILDOS-AREA scenario. Table 8 shows the dimensions of the area of primary contamination and Table 9 shows the location and coordinates of the areas affected by primary contamination. Table 10 shows all the other input parameters used in RESRAD-OFFSITE for this study. Out of nine exposure pathways considered in RESRAD-OFFSITE, only the following five pathways were considered in this scenario(1): Figure 3 Open in new tabDownload slide Wind rose diagram. Figure 3 Open in new tabDownload slide Wind rose diagram. Table 6 Consumption of meat and other livestock products in Tanzania(21). Product . 2005 . 2010 . Meat (kg) 11 12 Milk (liters) 39 43 Eggs (number) 53 75 Product . 2005 . 2010 . Meat (kg) 11 12 Milk (liters) 39 43 Eggs (number) 53 75 Open in new tab Table 6 Consumption of meat and other livestock products in Tanzania(21). Product . 2005 . 2010 . Meat (kg) 11 12 Milk (liters) 39 43 Eggs (number) 53 75 Product . 2005 . 2010 . Meat (kg) 11 12 Milk (liters) 39 43 Eggs (number) 53 75 Open in new tab Table 7 Trends in per capita supply of major foods groups (in g/per d)(20). Major food groups . Supply for human consumption in g/d . 1966–68 . 1973–75 . 1980–82 . 1987–89 . 1994–96 . 2001–2003 . Starchy roots 742 755 691 494 592 518 Cereals (excl.beer) 181 245 318 328 283 307 Fruit and vegetables 283 257 262 228 173 158 Other 149 152 280 211 203 191 Milk and eggs 87 75 71 67 62 72 Pulses, nuts, oilcrops 54 51 52 55 44 42 Meat and offals 32 30 30 33 31 30 Fish, seafood 28 33 32 42 26 19 Sweeteners 20 23 18 13 18 21 Vegetable oils 7 9 10 11 11 14 Animal fats 3 3 2 2 2 2 Major food groups . Supply for human consumption in g/d . 1966–68 . 1973–75 . 1980–82 . 1987–89 . 1994–96 . 2001–2003 . Starchy roots 742 755 691 494 592 518 Cereals (excl.beer) 181 245 318 328 283 307 Fruit and vegetables 283 257 262 228 173 158 Other 149 152 280 211 203 191 Milk and eggs 87 75 71 67 62 72 Pulses, nuts, oilcrops 54 51 52 55 44 42 Meat and offals 32 30 30 33 31 30 Fish, seafood 28 33 32 42 26 19 Sweeteners 20 23 18 13 18 21 Vegetable oils 7 9 10 11 11 14 Animal fats 3 3 2 2 2 2 Open in new tab Table 7 Trends in per capita supply of major foods groups (in g/per d)(20). Major food groups . Supply for human consumption in g/d . 1966–68 . 1973–75 . 1980–82 . 1987–89 . 1994–96 . 2001–2003 . Starchy roots 742 755 691 494 592 518 Cereals (excl.beer) 181 245 318 328 283 307 Fruit and vegetables 283 257 262 228 173 158 Other 149 152 280 211 203 191 Milk and eggs 87 75 71 67 62 72 Pulses, nuts, oilcrops 54 51 52 55 44 42 Meat and offals 32 30 30 33 31 30 Fish, seafood 28 33 32 42 26 19 Sweeteners 20 23 18 13 18 21 Vegetable oils 7 9 10 11 11 14 Animal fats 3 3 2 2 2 2 Major food groups . Supply for human consumption in g/d . 1966–68 . 1973–75 . 1980–82 . 1987–89 . 1994–96 . 2001–2003 . Starchy roots 742 755 691 494 592 518 Cereals (excl.beer) 181 245 318 328 283 307 Fruit and vegetables 283 257 262 228 173 158 Other 149 152 280 211 203 191 Milk and eggs 87 75 71 67 62 72 Pulses, nuts, oilcrops 54 51 52 55 44 42 Meat and offals 32 30 30 33 31 30 Fish, seafood 28 33 32 42 26 19 Sweeteners 20 23 18 13 18 21 Vegetable oils 7 9 10 11 11 14 Animal fats 3 3 2 2 2 2 Open in new tab Table 8 Dimensions of primary contamination in RESRAD-OFFISTE. Parameter . Value . X-Dimension of primary contamination 866 m Y-Dimension of primary contamination 866 m Area of primary contamination 7.5 × 105 m2 Parameter . Value . X-Dimension of primary contamination 866 m Y-Dimension of primary contamination 866 m Area of primary contamination 7.5 × 105 m2 Open in new tab Table 8 Dimensions of primary contamination in RESRAD-OFFISTE. Parameter . Value . X-Dimension of primary contamination 866 m Y-Dimension of primary contamination 866 m Area of primary contamination 7.5 × 105 m2 Parameter . Value . X-Dimension of primary contamination 866 m Y-Dimension of primary contamination 866 m Area of primary contamination 7.5 × 105 m2 Open in new tab Table 9 Location and coordinates of areas affected by primary contamination (m) in RESRAD-OFFSITE. Location . Small X-coordinates . Larger X- coordinates . Small Y-coordinates . Larger Y- coordinates . Fruits, grain, non-leafy vegetable plot 1100 1200 1000 1100 Leafy vegetable plot 1100 1200 1100 1200 Pasture, silage growing area 900 1000 950 1000 Grain fields 900 1000 900 950 Dwelling site 2500 2550 900 950 Location . Small X-coordinates . Larger X- coordinates . Small Y-coordinates . Larger Y- coordinates . Fruits, grain, non-leafy vegetable plot 1100 1200 1000 1100 Leafy vegetable plot 1100 1200 1100 1200 Pasture, silage growing area 900 1000 950 1000 Grain fields 900 1000 900 950 Dwelling site 2500 2550 900 950 Open in new tab Table 9 Location and coordinates of areas affected by primary contamination (m) in RESRAD-OFFSITE. Location . Small X-coordinates . Larger X- coordinates . Small Y-coordinates . Larger Y- coordinates . Fruits, grain, non-leafy vegetable plot 1100 1200 1000 1100 Leafy vegetable plot 1100 1200 1100 1200 Pasture, silage growing area 900 1000 950 1000 Grain fields 900 1000 900 950 Dwelling site 2500 2550 900 950 Location . Small X-coordinates . Larger X- coordinates . Small Y-coordinates . Larger Y- coordinates . Fruits, grain, non-leafy vegetable plot 1100 1200 1000 1100 Leafy vegetable plot 1100 1200 1100 1200 Pasture, silage growing area 900 1000 950 1000 Grain fields 900 1000 900 950 Dwelling site 2500 2550 900 950 Open in new tab Table 10 Other Input parameters in RESRAD-OFFSITE. Item . Value . Reference . Nuclide concentrations  226Ra (Bq/g) 4.2 Banzi et al.(8)  232Th (Bq/g) 0.22 Banzi et al.(8)  Distribution coefficients (cm3/g)  226Ra 70 Default value  232Th 60000 Default value Deposition velocities  Deposition velocity of respirable particulates (m/s)  226Ra 0.001 Default value  232Th 0.001 Default value Deposition velocities of all particulates  226Ra 0.001 Default value  232Th 0.001 Default value Soil-to-plant-transfer factors  226Ra (Bq/kg)/ (Bq/kg) 0.04 Default value  232Th (Bq/kg)/ (Bq/kg) 0.001 Default value Intake to animal product transfer factor  Meat  226Ra (Bq/kg)/(Bq/d) 0.001 Default value  232Th (Bq/kg)/(Bq/d) 0.0001 Default value Milk  226Ra (Bq/L)/ (Bq/d) 0.001 Default value  232Th (Bq/L)/ (Bq/d) 0.000005 Default value  Reporting Times (Years) 13 Mining duration  Area of primary contamination (m2) 760000 MILDOS Atmospheric transport  Release height (m) 1 Default value  Release flux (cal/s) 0 Default value  AM atmospheric mixing height (m) 400 Default value  PM atmospheric mixing height (m) 1600 Default value Livestock Feed Growing Area  Pasture silage (m2) 5000 Calculated  Grain (m2) 5000 Calculated Consumption rate  Drinking water (L/y) 510 Default values  Fruits, grain, non-leafy vegetables (kg/y) 57.67 Kinabo(20)  Leafy vegetables (kg/y) 57.67 Kinabo(20)  Meat (kg/y) 12 Wilson(21)  Milk (L/y) 45 Katjiuongua and Nelgen(22) Inhalation and External Gamma  Inhalation rate (m3/y) 5840 Default value  Mass loading of all particulates above primary contamination (g/m3) 0.0001 Default value  Respirable particulates as a fraction of total particulates 1 Default value  Indoor to outdoor dust concentration ratio 0.4 Default value  External gamma penetration factor 0.7 Default value Radon  Effective radon diffusion coefficient of cover (m2/s) 0.000002 Default value  Effective radon diffusion coefficient of contaminated zone (m2/s) 0.000002 Default value  Effective radon diffusion coefficient of floor (m2/s) 0.0000003 Default value  Effective radon diffusion coefficient of non-leafy veg fields, leafy vegetable field, pasture, livestock grain fields and offsite dwelling site (m2/s) 0.000002 Default value Item . Value . Reference . Nuclide concentrations  226Ra (Bq/g) 4.2 Banzi et al.(8)  232Th (Bq/g) 0.22 Banzi et al.(8)  Distribution coefficients (cm3/g)  226Ra 70 Default value  232Th 60000 Default value Deposition velocities  Deposition velocity of respirable particulates (m/s)  226Ra 0.001 Default value  232Th 0.001 Default value Deposition velocities of all particulates  226Ra 0.001 Default value  232Th 0.001 Default value Soil-to-plant-transfer factors  226Ra (Bq/kg)/ (Bq/kg) 0.04 Default value  232Th (Bq/kg)/ (Bq/kg) 0.001 Default value Intake to animal product transfer factor  Meat  226Ra (Bq/kg)/(Bq/d) 0.001 Default value  232Th (Bq/kg)/(Bq/d) 0.0001 Default value Milk  226Ra (Bq/L)/ (Bq/d) 0.001 Default value  232Th (Bq/L)/ (Bq/d) 0.000005 Default value  Reporting Times (Years) 13 Mining duration  Area of primary contamination (m2) 760000 MILDOS Atmospheric transport  Release height (m) 1 Default value  Release flux (cal/s) 0 Default value  AM atmospheric mixing height (m) 400 Default value  PM atmospheric mixing height (m) 1600 Default value Livestock Feed Growing Area  Pasture silage (m2) 5000 Calculated  Grain (m2) 5000 Calculated Consumption rate  Drinking water (L/y) 510 Default values  Fruits, grain, non-leafy vegetables (kg/y) 57.67 Kinabo(20)  Leafy vegetables (kg/y) 57.67 Kinabo(20)  Meat (kg/y) 12 Wilson(21)  Milk (L/y) 45 Katjiuongua and Nelgen(22) Inhalation and External Gamma  Inhalation rate (m3/y) 5840 Default value  Mass loading of all particulates above primary contamination (g/m3) 0.0001 Default value  Respirable particulates as a fraction of total particulates 1 Default value  Indoor to outdoor dust concentration ratio 0.4 Default value  External gamma penetration factor 0.7 Default value Radon  Effective radon diffusion coefficient of cover (m2/s) 0.000002 Default value  Effective radon diffusion coefficient of contaminated zone (m2/s) 0.000002 Default value  Effective radon diffusion coefficient of floor (m2/s) 0.0000003 Default value  Effective radon diffusion coefficient of non-leafy veg fields, leafy vegetable field, pasture, livestock grain fields and offsite dwelling site (m2/s) 0.000002 Default value Open in new tab Table 10 Other Input parameters in RESRAD-OFFSITE. Item . Value . Reference . Nuclide concentrations  226Ra (Bq/g) 4.2 Banzi et al.(8)  232Th (Bq/g) 0.22 Banzi et al.(8)  Distribution coefficients (cm3/g)  226Ra 70 Default value  232Th 60000 Default value Deposition velocities  Deposition velocity of respirable particulates (m/s)  226Ra 0.001 Default value  232Th 0.001 Default value Deposition velocities of all particulates  226Ra 0.001 Default value  232Th 0.001 Default value Soil-to-plant-transfer factors  226Ra (Bq/kg)/ (Bq/kg) 0.04 Default value  232Th (Bq/kg)/ (Bq/kg) 0.001 Default value Intake to animal product transfer factor  Meat  226Ra (Bq/kg)/(Bq/d) 0.001 Default value  232Th (Bq/kg)/(Bq/d) 0.0001 Default value Milk  226Ra (Bq/L)/ (Bq/d) 0.001 Default value  232Th (Bq/L)/ (Bq/d) 0.000005 Default value  Reporting Times (Years) 13 Mining duration  Area of primary contamination (m2) 760000 MILDOS Atmospheric transport  Release height (m) 1 Default value  Release flux (cal/s) 0 Default value  AM atmospheric mixing height (m) 400 Default value  PM atmospheric mixing height (m) 1600 Default value Livestock Feed Growing Area  Pasture silage (m2) 5000 Calculated  Grain (m2) 5000 Calculated Consumption rate  Drinking water (L/y) 510 Default values  Fruits, grain, non-leafy vegetables (kg/y) 57.67 Kinabo(20)  Leafy vegetables (kg/y) 57.67 Kinabo(20)  Meat (kg/y) 12 Wilson(21)  Milk (L/y) 45 Katjiuongua and Nelgen(22) Inhalation and External Gamma  Inhalation rate (m3/y) 5840 Default value  Mass loading of all particulates above primary contamination (g/m3) 0.0001 Default value  Respirable particulates as a fraction of total particulates 1 Default value  Indoor to outdoor dust concentration ratio 0.4 Default value  External gamma penetration factor 0.7 Default value Radon  Effective radon diffusion coefficient of cover (m2/s) 0.000002 Default value  Effective radon diffusion coefficient of contaminated zone (m2/s) 0.000002 Default value  Effective radon diffusion coefficient of floor (m2/s) 0.0000003 Default value  Effective radon diffusion coefficient of non-leafy veg fields, leafy vegetable field, pasture, livestock grain fields and offsite dwelling site (m2/s) 0.000002 Default value Item . Value . Reference . Nuclide concentrations  226Ra (Bq/g) 4.2 Banzi et al.(8)  232Th (Bq/g) 0.22 Banzi et al.(8)  Distribution coefficients (cm3/g)  226Ra 70 Default value  232Th 60000 Default value Deposition velocities  Deposition velocity of respirable particulates (m/s)  226Ra 0.001 Default value  232Th 0.001 Default value Deposition velocities of all particulates  226Ra 0.001 Default value  232Th 0.001 Default value Soil-to-plant-transfer factors  226Ra (Bq/kg)/ (Bq/kg) 0.04 Default value  232Th (Bq/kg)/ (Bq/kg) 0.001 Default value Intake to animal product transfer factor  Meat  226Ra (Bq/kg)/(Bq/d) 0.001 Default value  232Th (Bq/kg)/(Bq/d) 0.0001 Default value Milk  226Ra (Bq/L)/ (Bq/d) 0.001 Default value  232Th (Bq/L)/ (Bq/d) 0.000005 Default value  Reporting Times (Years) 13 Mining duration  Area of primary contamination (m2) 760000 MILDOS Atmospheric transport  Release height (m) 1 Default value  Release flux (cal/s) 0 Default value  AM atmospheric mixing height (m) 400 Default value  PM atmospheric mixing height (m) 1600 Default value Livestock Feed Growing Area  Pasture silage (m2) 5000 Calculated  Grain (m2) 5000 Calculated Consumption rate  Drinking water (L/y) 510 Default values  Fruits, grain, non-leafy vegetables (kg/y) 57.67 Kinabo(20)  Leafy vegetables (kg/y) 57.67 Kinabo(20)  Meat (kg/y) 12 Wilson(21)  Milk (L/y) 45 Katjiuongua and Nelgen(22) Inhalation and External Gamma  Inhalation rate (m3/y) 5840 Default value  Mass loading of all particulates above primary contamination (g/m3) 0.0001 Default value  Respirable particulates as a fraction of total particulates 1 Default value  Indoor to outdoor dust concentration ratio 0.4 Default value  External gamma penetration factor 0.7 Default value Radon  Effective radon diffusion coefficient of cover (m2/s) 0.000002 Default value  Effective radon diffusion coefficient of contaminated zone (m2/s) 0.000002 Default value  Effective radon diffusion coefficient of floor (m2/s) 0.0000003 Default value  Effective radon diffusion coefficient of non-leafy veg fields, leafy vegetable field, pasture, livestock grain fields and offsite dwelling site (m2/s) 0.000002 Default value Open in new tab Direct radiation from the soil When radioactive materials dispersed into the atmosphere, some amount/concentration remain in the atmosphere while other amount deposit to the ground. The deposited radionuclides can be a source of exposure to the public through external radiation by gamma. And, the soil content can be a source of external radiation exposure depending on the activity of the soil. In this particular study, this exposure scenario is a possible case(2). Radon Due to the presence of 226Ra in the ore, there is a continuous emission of radon (222Rn) gas, which is a radionuclide daughter of 226Ra. This escaping radon from the ore crust and ore dust can be inhaled by the public and become a source exposure by internal radiation exposure. In this study, this type of exposure case was anticipated(3). Inhalation Exposure by inhalation can result from breathing air dust (contaminated air with particulate matters). In this study, this mode of exposure was regarded as the potential exposure pathway because mining and milling activities are primarily involving processes such as excavation, transporting, milling, drying, etc. In all the mentioned processes, there is the transportation of dust through the atmosphere depending on other factors like wind speed, stability and other meteorological factors(4). Meat ingestion Grazing of animals into the pasture contaminated with radionuclides can result in the meat being contaminated with radionuclide and hence, become a source of public exposure through the ingestion of meat. Therefore, in this study, this source of exposure was considered because grazing activities were anticipated(5). Milk ingestion Like for meat, when animals are grazed into the pasture contaminated with radionuclides, there is a possibility for the milk from those animals to be contaminated with the radionuclides. Therefore, due to the presence of grazing areas and the presence of animals near the mining site, this exposure scenario was considered. In this study, since the operation is yet to start and no enough information about the expected site, a conceptual site was assumed for the mining facility (site). Also, it was assumed that RESRAD-OFFSITE does not consider surface and groundwater pathways. The reason for neglecting them was because MILDOS-AREA does not account for these pathways. Therefore, in the analysis of RESRAD-OFF, these pathways were deactivated to be able to make a reasonable comparison between the two codes. In both computer codes, the distance from the contamination area to the receptor was kept the same. Since there was no food consumption data for the local community, it was assumed that food consumption rates of the local community were the same as Tanzania’s average food consumption. In MILDOS-AREA, it was assumed four sources of radiation contamination (ore pad, 2 tailing piles and yellow cake stack). The reason for this assumption is that there was no enough information about the expected sources for the facility. Therefore, decided to select sources that are general that can be found at any mining facility. Other specific assumptions can be found in Tables 5 and 10. RESULTS AND DISCUSSION MILDOS-AREA The results of the total effective dose equivalent (TEDE) per year for the 13 y of exposures at each location are indicated in Figure 4. The reporting period was made for 13 y because the mining operations are expected to run for 13 y. Therefore, the value reported each year is the maximum value at each receptor. This figure shows an increasing trend in the TEDEs at each receptor location. This increase is due to an uneven distribution of these radionuclides in the ore where the concentration is higher than the background. Each year, a different value of dose is recorded at each receptor because the receptors were located at a different distance from the source. Therefore, they receive different doses. From this figure, the maximum dose at each receptor location is below the recommended dose limit and dose constraint i.e. <1 mSv/y and 0.3 mSv/y, respectively, as suggested by IAEA. This implies that the real exposed individual at a far location from the site (53 km) will receive a negligible radiological impact from mining and milling operations. Figure 5 represents the plot of different pathways that contribute to the off-site dose together with their respective doses. These pathways include ground-shine, cloud-shine, inhalation, plant ingestion, meat ingestion and milk ingestion. The TEDEs indicated in these pathways are the sum of doses accumulated for 13 y. These results indicate that the inhalation pathway is the potential pathway because it contributes a significant amount of the TEDE (1.2 × 10−1 mSv) compared to the rest of the pathways i.e. almost 99% of the TEDE is contributed by the inhalation pathway. The reason for this big difference might be because most of the operations are involving dispersing and transporting dust in which radon and particulates are emitted into the atmosphere. The processes like excavation, transporting, drying and packaging are likely to produce more dust into the atmosphere. Also, the increase of the accumulated radioactive materials to the tailings is considered as one of the sources of atmospheric dust increasing. On the other hand, the small values of other pathways may be due to the low consumption rates of food i.e. the low consumption of vegetables, meat and milk compared to the world Figure 4 Open in new tabDownload slide Maximum total effective dose equivalent at each receptor location estimated by MILDOS-AREA. Figure 4 Open in new tabDownload slide Maximum total effective dose equivalent at each receptor location estimated by MILDOS-AREA. Figure 5 Open in new tabDownload slide Receptor doses according to different pathways estimated by MILDOS-AREA. Figure 5 Open in new tabDownload slide Receptor doses according to different pathways estimated by MILDOS-AREA. Figure 6 Open in new tabDownload slide Maximum organ doses estimated by MILDOS-AREA. Figure 6 Open in new tabDownload slide Maximum organ doses estimated by MILDOS-AREA. average. The consumption rate for these foods is 57.67, 12 and 45 kg/y for vegetables, meat and milk, respectively(20,21,22). Hence, the contribution of these pathways is very small compared to the inhalation dose, which is the dominant pathway. For the case of organ doses, MILDOS-AREA considers four organs which are bone, lung, liver and kidney. These are the main organs in the human body that have a direct association with uranium. Maximum doses for each of these organs accumulated for 13 y are indicated in Figure 6, with the lung having the highest amount of dose (1.15 × 10−1 mSv) compared to the rest of the organs. This is because the lungs are highly affected by the inhalation pathway and from Figure 5 it was found that the inhalation pathway was the dominant pathway contributing ~99% of TEDE. The inhalation of radon causes the maximum exposure of the lungs because the radon decay progenies are deposited into the lungs. Apart from radon, inhalation dose is contributed by the particulates coming from the emitted dust. Therefore, the total inhalation dose is due to radon gas coming from radium and the particulates dust. The second organ to receive the highest dose after the lung is the bone. This dose is contributed by uranium since uranium tends to deposit in the bone. When uranium is absorbed in the body, 66% of it is found in the bone where it can remain for a long time, having a half-life of 70–200 d in bones(24,25). Although most of the uranium is deposited in bone, no evidence is suggesting the health damage of the bones after human ingestion or inhalation of uranium materials. However, after entering the human body, uranium targets the kidney where it can cause kidney damage(22). The liver received the least organ dose compared to the rest of the organs. The meteorological conditions such as wind speed and wind direction have an influence on the results of the doses at a different location. Therefore, it is anticipated that the doses in 16-wind directions will be different depending on the wind speed. However, this study considered receptors being only in one direction i.e. the direction which is mostly affected by the dominant wind. The direction of the dominant wind is from E to W and the dominant wind speed class is >5 m/s as shown in Figure 3. The study did not consider receptors in other directions (this was the hypothetical scenario for the receptors). Therefore, the impact on other directions of the wind was not determined. RESRAD-OFFSITE Figure 7 shows the TEDE for the 13 y calculated using RESRAD-OFFSITE. The doses in this figure are the summed TEDE from all pathways and show the trend of TEDE for 13 y of exposure. These doses were contributed by the direct radiation from the soil, radon, inhalation, meat ingestion and milk ingestion. The maximum TEDE contributed by direct radiation from the soil was 1.4 × 10−2 mSv/y while radon, inhalation, meat ingestion and milk ingestion were 6.0 × 10−2, 8.3 × 10−5, 6.0 × 10−6 and 4.0 × 10−6 mSv/y, respectively. Therefore, this shows that a large amount of the TEDE was contributed by the radon pathway followed by direct radiation from the soil pathway. The contribution of meat and milk ingestion was very small compared to radon and direct radiation from the soil. Figure 7 Open in new tabDownload slide Total effective dose equivalent with time estimated by RESRAD-OFFSITE. Figure 7 Open in new tabDownload slide Total effective dose equivalent with time estimated by RESRAD-OFFSITE. Comparison of MILDOS-AREA and RESRAD-OFFSITE Figure 8 represents the comparison of the results of the calculations using different methods. That is calculations using MILDOS-AREA and RESRAD-OFFSITE, and they are plotted in the same figure with the reference standard (dose constraints) and the EIA results (the maximum value). From this figure, the maximum (TEDE) calculated by MILDOS-AREA was 4.45 × 10−2 mSv/y while the maximum TEDE calculated by RESRAD-OFFSITE was 7.43 × 10−2 mSv/y. Since the two codes used different dose conversion factors, it was anticipated to be some differences in the results. While MILDOS-AREA used ICRP 26 dose conversion factors, RESRAD-OFFSITE used ICRP 60/72 dose coefficients. For example, while the external dose coefficients used in ICRP 26 for 226Ra, 222Rn, 238U and 232Th were 8.58 × 10−3, 6.36 × 10−4, 2.79 × 10−5 and 1.41 × 10−4 mSv/y/Bq/g, respectively, the ICRP 60 external dose coefficients for the same radionuclides above were 7.88 × 10−3, 5.91 × 10−4, 2.15 × 10−5 and 1.23 × 10−4 mSv/y/Bq/g, respectively. For inhalation exposure, the dose coefficients used in ICRP 26 for 226Ra and its progeny, 238U and 232Th were 2.32 × 10−3, 3.19 × 10−2 and 4.43 × 10−1 mSv/Bq, respectively, while the ICRP 60 inhalation dose coefficients for the same radionuclides above were 9.53 × 10−3, 8.0 × 10−3 and 1.10 × 10−1 mSv/Bq, respectively. Also, for the case of exposure due to ingestion, the dose coefficients used in ICRP 26 for 226Ra and its progeny, 238U and 232Th were 3.57 × 10−4, 6.89 × 10−5 and 7.38 × 10−4 mSv/Bq, respectively, while the ICRP 60 ingestion dose coefficients for the same radionuclides above were 2.80 × 10−4, 4.5 × 10−5 and 2.3 × 10−4 mSv/Bq, respectively(13). Based on the above facts of dose coefficients, MILDOS-AREA was expected to estimate higher doses than RESRAD-OFFSITE because ICRP 26 dose coefficients are higher than those of the corresponding dose coefficients from ICRP 60. Along with different dose conversion factors, these two codes used different release, dispersion and deposition models. While RESRAD-OFFSITE considered both dry and wet deposition, MILDOS-AREA considered only dry deposition. RESRAD-OFFSITE calculated the source term (release rate) using the average mass loading, deposition velocity, average concentration and source area, while MILDOS-AREA used windblown particle emission. Also, while the soil concentration in RESRAD-OFFSITE was affected by mixing in the surface layer, erosion and leaching, the soil concentration in MILDOS-AREA was affected by the constant deposition and environmental loss. RESRAD-OFFSITE used different selected areas to calculate the average air concentration and deposition, while MILDOS-AREA calculated air concentration and deposition at a specific receptor location. Moreover, while RESRAD-OFFSITE assumed a finite volume source with uniform concentration to calculate the external pathway dose, MILDOS-AREA assumed an infinite surface source(26). The calculated results fall below the dose constraint recommended by the IAEA of 0.3 mSv/y(1) as can be seen in Figure 8. On the other hand, the calculated results together with the results of EIA(11) seem to have a value very close as can be seen in Figure 8. This indicates that the results from MILDOS-AREA and RESRAD-OFFSITE can be trusted. The comparison helps to have confidence that the calculated results using a particular method or procedure is correct or not. Therefore, from the calculated results it can be said that MILDOS-AREA and RESRAD-OFFSITE have shown similar results and therefore the results can be trusted. Figure 8 Open in new tabDownload slide Comparison of calculated doses with IAEA dose constraint and EIA dose at Mkuju River Project. Figure 8 Open in new tabDownload slide Comparison of calculated doses with IAEA dose constraint and EIA dose at Mkuju River Project. CONCLUSIONS The objective of this study was to estimate the radiological off-site doses received by the public living close to the Mkuju River Project site as a result of mining and milling activities and identify the potential pathway responsible for radiological exposure. The MILDOSE-AREA and RESRAD-OFFSITE codes were used to assess radiological impacts associated with radioactive emissions from uranium mining and milling at Mkuju River. The dose obtained from the results of the two computer codes were below the public dose limit and the dose constraint. The comparison was made between the calculated results of MILDOS-AREA, and RESRAD-OFFSITE and the two were compared with the dose constraint and also to the EIA results previously done at Mkuju. The estimated maximum TEDE for the nearest residence calculated by MILDOS-AREA ranges from 2.5 × 10−2 mSv/y for the first year after the start of mining to 4.45 × 10−2 mSv/y after thirteen years of mining. The result of RESRAD-OFFSITE ranges from 7.19 × 10−2 mSv/y for the first year to 7.43 × 10−2 mSv/y after 13 y. This shows that all the calculated results are below the dose limit and dose constraint of 1.0 mSv/y and 3.0 × 10−1 mSv/y, respectively, as recommended by the IAEA. Also, all the TEDEs at each receptor location are below the recommended dose limit. Since the nearest residence location distance of 2.5 km was chosen based on the assumption of the most exposed individual (conservatism) and no residence at this location, this implies that the real exposed individual at a far distance (53 km) from the Mkuju River Project site will receive negligible radiological impact from mining and milling activities. FUNDING SOURCES This research was supported by the 2020 Research Fund of the KEPCO International Nuclear Graduate School (KINGS), the Republic of Korea. References 1. International Atomic Energy Agency . Exposure of the Public from Large Deposits of Mineral Residues . ( Vienna : International Atomic Energy Agency ) ( 2011 ). Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 2. International Atomic Energy Agency . Assessing the Need for Radiation Protection Measures in Work Involving Minerals and Raw Materials . ( Vienna : Internat. Atomic Energy Agency ) ( 2006 ). Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 3. United Nations . Sources and Effects of Ionizing Radiation: United Nations Scientific Committee on the Effects of Atomic Radiation: UNSCEAR 2000 Report to the General Assembly, with Scientific Annexes . ( New York : United Nations ) ( 2000 ). Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 4. World Health Organization . WHO Handbook on Indoor Radon: A Public Health Perspective. Geneva . ( Switzerland : World Health Organization ) ( 2009 ). Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 5. Mantra Tanzania Limited . Environmental and Social Impact Assessment for the Proposed Uranium Mining Project, Version 3, Volume 1: Annexure II . ( 2012 ). 6. OECD . Managing Environmental and Health Impacts of Uranium Mining . (Paris, France: OECD Publishing ) ( 2014 ). Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 7. Banzi , F. , Msaki , P. and Mohammed , N. Assessment of radioactivity of Ra-226, Th-232 and K-40 in soil and plants for estimation of transfer factors and effective dose around Mkuju river project, Tanzania . Mining of Mineral Deposits, 11 ( 2017 ). doi: 10.15407/mining11.03.093 . 8. Banzi , F. P. , Msaki , P. K. and Mohammed , N. K. Assessment of natural radioactivity in soil and its contribution to population exposure in the vicinity of Mkuju River uranium project in Tanzania . Expert Opin. Environ. Biol. 06 ( 01 ) ( 2017 ). doi: 10.4172/2325-9655.1000140 . Google Scholar OpenURL Placeholder Text WorldCat Crossref 9. Banzi , F. P. , Msaki , P. K. and Mohammed , N. K. Natural radioactivity in water and its potential human health risk in the vicinity of Mkuju River uranium project in Tanzania . International Journal of Environmental Protection and Policy 4 ( 5 ) ( 2016 ). doi: 10.11648/j.ijepp.20160405.11 . 10. Mohammed , N. K. and Mazunga , M. S. Natural radioactivity in soil and water from Likuyu Village in the Neighborhood of Mkuju uranium deposit . International Journal of Analytical Chemistry. 2013 , 501856. ( 2013 ). doi: 10.1155/2013/501856 . 11. Mantra Tanzania Limited . Environmental and social impact assessment for the proposed uranium mining project version 3 . ( 2012 ). 12. Kamboj , S. , Biwer , B. M., Lepoire , D. and Chang , Y.-S. Technical manual and User’s guide for MILDOS-AREA version 4 . USA: Argonne National Laboratory, ( 2016 ). 13. Gnanapragasam , E. , Cheng , J.-J., LePoire , D., Kamboj , S. and Wang , C. User’s manual for RESRAD-OFFSITE code version 4 , 544 USA: Argonne National Laboratory, ( 2020 ). 14. Kleinfelder West, Inc. , MILDOS-AREA assessment of off-site radiation doses . ( 2009 ). http://recycle4colorado.ipower.com/ ( accessed July 15, 2020 ). 15. Yuan , Y. C. , Wang , J. H. C. and Zielen , A. MILDOS-AREA: an enhanced version of MILDOS for large-area sources , ANL/ES-161, 5950391 . ( 1989 ). doi: 10.2172/5950391 . 16. Energy Fuels Resources (USA) Inc. , Evaluation of the radiological characteristics of uranium mine waste rock . ( 2014 ). https://eplanning.blm.gov/public_projects/nepa/54345/73737/81007/Appendix_E_-_Radiological_Characteristics_of_U_Mine_Waste_Rock.pdf ( accessed July 15, 2020 ). 17. Two Lines, Inc. Estimated Radiation Doses To Members of the Public from the Lost Creek Project Including the Eastern Expansion . ( Colorado : Sweetwater County, Wyoming ) ( 2017 ). Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 18. Junior , D. , Pereira , W. and Rocha , R. Environmental impact of uranium mining and milling in Caetite . (2002). Available: http://www.researchgate.net/publication/256088037_Environmental_Impact_of_Uranium_Mining_and_Milling_in_Caetite. 19. Economic and Social Research Foundation . Strengthening micro-Enterprises in Tanzania: the case of small-scale vegetable farmers in Arusha . ( 2010 ). http://www.tzonline.org/pdf/microenteprise.pdf (accessed June 15, 2020). 20. Kinabo , J. Nutrition country profile United Republic of Tanzania , 48 ( 2008 ). http://bvsper.paho.org/texcom/nutricion/tza.pdf (accessed June 16, 2020). 21. Wilson , R. T. The red meat value chain in Tanzania . Anim. Husb. Dairy Vet. Sci. 2 ( 1 ) ( 2018 ). doi: 10.15761/AHDVS.1000127 . Google Scholar OpenURL Placeholder Text WorldCat Crossref 22. Katjiuongua , H. and Nelgen , S, Tanzania Smallholder Dairy Value Chain Development: Situation Analysis and Trends ILRI Project Report, Nairobi . ( 2014 ). [Online]. Available : https://cgspace.cgiar.org/bitstream/handle/10568/68513/PR_Tanzania.pdf?sequence=1&isAllowed=y. ( accessed June 15, 2020 ) 23. OGIMET. OGIMET synop based daily summary by state , OGIMET . http://www.ogimet.com/ (accessed May 7, 2020). 24. Agency for Toxic Substances and Disease Registry , Public health statement uranium . ( 2013 ). https://www.atsdr.cdc.gov/ ( accessed July 17, 2020 ). 25. Kurttio , P. , Komulainen , H., Leino , A., Salonen , L., Auvinen , A. and Saha , H. Bone as a possible target of chemical toxicity of natural uranium in drinking water . 113 , 6 ( 2004 ). 26. S. Cohen & Associates . Risk Assessment Revision for 40 CPR Part 61 Subpart W–Radon Emissions from Operating Mill Tailings . ( Vienna : U.S. Environmental Protection Agency ) ( 2010 ). Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC © The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
TI - POTENTIAL ENVIRONMENTAL HAZARD TO THE PUBLIC FROM THE OPERATION OF URANIUM MINING AND MILLING FACILITY
JF - Radiation Protection Dosimetry
DO - 10.1093/rpd/ncaa195
DA - 2020-12-30
UR - https://www.deepdyve.com/lp/oxford-university-press/potential-environmental-hazard-to-the-public-from-the-operation-of-pNeBSkqQoT
SP - 75
EP - 88
VL - 192
IS - 1
DP - DeepDyve
ER -