Natural radioactivity measurements and evaluation of radiological hazards in the soil of an iron beneficiation plant in China

Abstract

The specific activities of natural radionuclides, ²³²Th, ²²⁶Ra, and ⁴⁰K, in a Chinese iron beneficiation plant and surrounding soil were analyzed with the high purity germanium gamma (HPGe) spectrometer in this study. Average specific activities of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K lower than the Chinese averages. To assess radiation impact, various indicators, radium equivalent index (Ra_eq), absorbed dose rate (D_R), annual effective dose (AED), excess lifetime cancer risk (ELCR), external hazard index (H_ex), internal hazard index (H_in) and activity utilization index (AUI), were calculated. Mean values were below international limits, indicating no significant health hazards for the local population. Statistical analyses, including skewness and kurtosis calculations, along with techniques like frequency distribution, Pearson's correlation analysis, box plots and cluster analysis, were applied to comprehensively assess distribution patterns and interrelationships among radiological parameters. In summary, there are no potential health hazards associated with the soil in the study region for people.

KEYWORDS:

• Iron ore
• waste residue
• radioactivity
• soil
• radiation hazard indicators

1. Introduction

The raw iron ore used by a Chinese iron beneficiation plant is accompanied by radioactive elements [1]. The beneficiation process adopts the conventional two-stage crushing, two-stage grinding stone and two-stage magnetic separation fine screening process. Prior to mineral processing, the natural radioactivity of the surroundings is in a balanced state and remains unchanged during the processing stages. However, after processing, during the process of storage and waste disposal natural radionuclides in raw materials will be discharged into the environment along with the generated dust, waste residue and wastewater, causing internal and external radioactive exposure to workers [2,3]. Naturally occurring radioactive materials (NORM) refer to natural radionuclides, predominantly ²³⁸U, ²³²Th, ²²⁶Ra, ⁴⁰K and others, which arise from natural processes rather than human activities. They are ubiquitously present in various components of the natural environment, such as rocks, soil, water, atmosphere, as well as flora and fauna [4–6]. NORM that have been concentrated or exposed to the accessible environment as a result of human activities such as manufacturing, mineral extraction, or water processing are called Technologically Enhanced Naturally Occurring Radioactive Material (TENORM) [7,8]. The radioactive pollution of TENORM is mainly distributed in the process of mining, beneficiation, smelting and use of mineral products. Raw materials used by mineral processing enterprises contain certain natural radionuclides. During the processing, some of radionuclides will be transferred and accumulated, making the radioactive contents of some products or waste much higher than the background level of natural radioactivity, causing certain environmental pollution [9,10].

In the iron ore processing and smelting process, a large amount of waste slag accumulates in outdoor pits on the factory premises. Due to the fact that the factory has not taken any measures to treat these slag heaps, they are simply left exposed in the outdoor environment, posing a potential safety hazard. Proper disposal of radioactive waste is crucial for ensuring the factory's safety, environmental protection and human health. Inadequate disposal can lead to significant safety hazards, including potential loss of life and property, damage to the environment, and serious social consequence. Humans are exposed to ionizing radiation from natural radionuclides and artificial ones in the environment. According to the data of World Nuclear Association (WNA), natural radionuclides account for approximately 85% of the ionizing radiation dose received by the general public annually. Among them, the most prominent ones are radionuclides of the uranium and thorium series and ⁴⁰K. Soil is an important environmental medium for sustaining life and also serves as an effective indicator of radionuclide pollution [11]. Radionuclides in soil pose the potential threat to the ecological environment and harm human health through various absorption routes, such as direct ingestion, skin contact and ingestion through the soil-food chain and inhalation [12,13]. In order to ascertain the impact of the slag heaps on the surrounding environment within the factory, a comprehensive analysis of natural radioactive nuclides in the soil and a radioactive hazard assessment will be conducted, which will serve as foundational data for the subsequent management of the slag heaps.

It is crucial to evaluate activity concentration through radiological assessment for the monitoring and assessment of radioactive hazards, which provides the foundation for establishing standards and guidelines that are imperative for effective environmental management and remediation efforts [14]. Research on the sources and behaviour of natural radioactive nuclides has been extensive [15–17], encompassing analyses of their spatial distribution in soil and investigations into the effects of associated radioactive ores like iron and phosphate ores on the soil [1,18–21]. This research work aims to determine the activity concentrations and distribution of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K in soil samples collected from an iron ore beneficiation plant in China. It also aims to assess the radium equivalent index (Ra_eq), absorbed dose rate (D_R), annual effective dose (AED), excess lifetime cancer risk (ELCR), external hazard index (H_ex), internal hazard index (H_in) and activity utilization index (AUI). The data collected in this study can be added to the natural radioactivity level database, providing information about the activity concentration distribution of natural radioactive nuclides and the radiation doses received by individuals in contact with this environment. Simultaneously, the findings of this study can furnish regulatory authorities with more precise and effective regulatory approaches, and furnish scientifically grounded, objective, and impartial foundational data and justification for establishing industry threshold standards and related policies.

2. Materials and methods

2.1. Study area

The study area is located in a Chinese iron beneficiation plant, which is located at a mountainous and hilly landform. The northern part is an eroded structural terrain with an altitude of more than 1000 m. The central part is mountainous and hilly with moderate cuts, which is a stage-like landform with successively lower structures. From the south to the sea coast, it gradually becomes an undulating banded plain with low hills with a width of tens of kilometers. Due to the characteristics of the landform, there are a large number of mineral resources in the area. There are many villages around the factory, so the development and utilization of mineral resources would inevitably have an impact on the surrounding environment and individuals.

2.2. Collection and preparation of samples

Radiation environmental monitoring should be conducted for enterprises involved in the extraction, beneficiation, and smelting of radioactive minerals in accordance with Chinese national standard HJ 61-2021 “Technical specification for radiation environmental monitoring”. This includes monitoring of radioactive nuclides such as ²³⁸U, ²³²Th and ²²⁶Ra in the soil within 3–5 km around the factory area [22]. Therefore, based on this standard, the current study established five monitoring points in four directions of the beneficiation plant and near the tailings pond. Additionally, 28 villages with dense populations and long-term residency within 3 km of the factory were selected as monitoring sites, as shown in Figure 1. Soil samples were collected at these monitoring sites to analyze the activity concentrations of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K, and to evaluate the long-term health effects of the beneficiation plant's operations on the surrounding residents.

Figure 1. Schematic diagram of soil sampling points.

Soil site selection, sample collection and sample processing were conducted based on the HJ/T 166-2004 “The technical specification for soil environmental monitoring” in this study [23]. The soil site selection was carried out using a systematic random approach, dividing the monitoring area into four equal sections. Within each grid, a sampling point was designated, and 5 soil surface samples were collected using the “cloverleaf” sampling method. Topsoil was collected at a depth of 10 cm from the surface. Debris like stones and roots collected from various points in the soil was cleared, mixed on-site, and a 2–3 kg sample was taken, sealed in a double-layered plastic bag, and then placed in a cloth bag of the same size for storage. The soil samples, after removing weeds and gravel, were dried at 100 °C until reaching the constant weight [24]. Subsequently, they were crushed, sieved through a sieve with a mesh size of 0.25 mm, weighed, and transferred into 75 × 70 cm sample boxes, which is consistent in size with the standard source of the calibrated gamma spectrometer [24]. All samples were sealed and placed for at least 30 days to achieve the secular equilibrium between ²²⁶Ra and its progeny [24,25]. The samples were collected from the four directions of the beneficiation plant are labelled with the corresponding directions as identifiers: S, N, W and E. The samples gathered near the tailings pond are identified as NTP. The soil samples collected from the 28 villages around the factory are numbered in sequence starting from V1 to V28 according to the order of the villages.

2.3. Radioactivity measurements

The analysis of natural isotopes ²³²Th, ²²⁶Ra and ⁴⁰K in soil samples was based on the Chinese national standard GB/T 11743-2013 “Determination of radionuclides in soil by gamma spectrometry” [24]. ORTEC GEM30P4-76 high purity germanium gamma spectrometer was used to analyze the samples [26]. The detector has a relative efficiency of 30% and an energy resolution of 1.99 keV for 1332.25 keV gamma energy of ⁶⁰Co. The detector was calibrated using a standard sample (8NTR/015) which contains a number of radioactive nuclides of ²¹⁴Am, ²³⁸U, ²²⁶Ra, ²³⁵U, ²³²Th, ⁴⁰K, ⁶⁰Co and ¹³⁷Cs. The detector is surrounded by a shield made of 10 cm thick lead to reduce the background radiation level of the system and internally filled with 1 mm thick copper plates to reduce the X-ray emissions from cosmic radiation interacting with lead. “Gamma Vision” software was used to analyze the spectral data.

The prepared samples were placed at the central position of the probe for measurement. The background radioactive intensity was measured for 86,400 s, using an empty Marinelli cup. The samples were then measured at a record time of 86,400 s. After that, the background count was subtracted from the spectrum of the sample. The activity concentrations of ⁴⁰K were calculated directly by its gamma spectra 1460.83 keV. ²³²Th activity concentration was determined from the gamma peak energies of ²⁰⁸Tl at 583.19 keV and ²²⁸Ac at 911.20 keV. ²³⁸U measurements were based on the weighted mean of the photo peaks of ²³⁴Th (63.29 and 92.8 keV), while ²²⁶Ra stem from the determinations of ²¹⁴Pb at 351.92 keV and ²¹⁴Bi at 609.31 keV [27,28].

The absolute efficiency is obtained from using the efficiency curve for the standard source through Equation (1) [24]: (1) $\begin{array}{r}\ln \epsilon =\sum _{i=0}^{n-1}{a}_i{(\ln E_r)}^i\end{array}$(1) where ε is the efficiency value. a_i is the best appropriate parameter determined by the synthesis algorithm. E_γ is energy. The efficiency values were used to calculate the activity concentration of ²³²Th, ²²⁶Ra and ⁴⁰K.

According to the efficiency curve method, the activity concentration of radioactive nuclides in soil samples is calculated using Equation (2) [24]: (2) $\begin{array}{r}{Q}_j=\frac{A_{ji}-A_{jib}}{P_{ji}{\eta }_{i}W{D}_j}\end{array}$(2) where η_i represents the efficiency value for the i^th full absorption peak of the gamma ray. P_ji denotes the emission probability of the j^th nuclide emitting the i^th gamma ray. A_ji (s⁻¹) represents the net peak area counting rate of the i^th characteristic peak of the j^th nuclide in the measured sample. A_jib (s⁻¹) corresponds to the background net peak area counting rate of the characteristic peak corresponding to A_ji. W (kg) is the net weight of the measured sample. D_j is the decay correction factor for the j^th nuclide to the time of sampling.

2.4. Radiological hazard indices

2.4.1. Radium equivalent index (Ra_eq)

A common radiation index was introduced to represent the activity levels of ²³²Th, ²²⁶Ra and ⁴⁰K [29]. The safe limit Ra_eq is 370 Bq kg⁻¹ [30]. The mathematical definition of the radium equivalent index (Ra_eq) is as follows [31]: (3) $\begin{array}{r}R{a}_{eq}=1.43A_{Th}+A_{Ra}+0.077A_K\end{array}$(3) where Ra_eq (Bq kg⁻¹) is the radium equivalent index. A_Th, A_Ra and A_K (Bq kg⁻¹) are the activity concentrations of ²³²Th, ²²⁶Ra and ⁴⁰K, respectively.

2.4.2. Absorbed dose rate (D_R)

According to the specific activity values of ²³²Th, ²²⁶Ra and ⁴⁰K in the soil, the absorbed dose rate of γ-ray at 1 m above the ground was calculated. It is recommended that the acceptable total absorbed dose rate for the workers in the area should not exceed the global average level of 57 nGy h⁻¹ [30]. It can be calculated by using the Equation (4) [30,32]. (4) $\begin{array}{r}{D}_R=0.604A_{Th}+0.462A_U+0.0417A_K\end{array}$(4) where D_R (nGy h⁻¹) is the absorbed dose rate. According to UNSCEAR and the European Commission, the conversion factors for converting the activity concentration, A_Th, A_U and A_K to ADR are 0.604, 0.462 and 0.0417, respectively [30].

2.4.3. Annual effective dose (AED)

AED is defined as the radioactive coefficient used to judge the degree of impact of absorbed dose on health, in the unit of μSv y⁻¹. The recommended AED limit for public exposure is 1 mSv y⁻¹ [33]. The annual effective equivalent dose is calculated by the Equation (5) [34]: (5) $\begin{array}{r}AED=D_R\times T\times CF\times {10}^{-3}\end{array}$(5) where AED (μSv y⁻¹) is the annual effective dose. D_R (nGy h⁻¹) is absorbed dose rate. The conversion factor (CF) is assigned a value of 0.7 Sv Gy⁻¹. T (h) is the annual exposure time of people outdoors (outdoor occupancy factor p = 0.2, T = 24 × 365 × 0.2 = 1752h) [30].

2.4.4. Excess lifetime cancer risk (ELCR)

ELCR is defined as the cancer risk of people with long-term exposure to carcinogens. UNSCEAR reported that the worldwide average limit value was 0.29 × 10⁻³ [30,35]. The ELCR can be estimated using Equation (6) [31]: (6) $\begin{array}{r}ELCR=AED\times DL\times RF\times {10}^{-6}\end{array}$(6) where ELCR is the excess lifetime cancer risk. AED, DL and RF are the effective annual dose (μSv y⁻¹), life span (70 years) and risk factor (0.05 Sv⁻¹), respectively.

2.4.5. External and internal hazard index (H_ex, H_in)

H_ex reflects the ionizing hazard of external natural γ-ray radiation. What’s more, there is also the H_in, to ensure that the effective dose of the radiation is not beyond the limits is 1 mSv y⁻¹ [36]. Only when the values of H_ex and H_in are both no more than 1, can radiation hazards be insignificant. The H_ex and H_in can be calculated by using Equations (7) and (8), as follows [31]: (7) $\begin{array}{rl}{H}_{ex}& =\frac{A_{Th}}{259}+\frac{A_{Ra}}{370}+\frac{A_K}{4810}\le 1\end{array}$(7) (8) $\begin{array}{rl}{H}_{in}& =\frac{A_{Th}}{259}+\frac{A_{Ra}}{185}+\frac{A_K}{4810}\le 1\end{array}$(8)

2.4.6. Activity utilization index (AUI)

The activity utilization index (AUI) reflects the air dose rate of the combination of ²³²Th, ²²⁶Ra and ⁴⁰K. The recommended acceptable activity utilization index limit is 1 [30]. Based on appropriate conversion factors and the specific activities of the radionuclides, the AUI can be calculated according to Equation (9) [32], as follows: (9) $\begin{array}{r}AUI=\frac{A_{Th}}{50}{f}_{Th}+\frac{A_{Ra}}{50}{f}_{Ra}+\frac{A_K}{500}{f}_K\end{array}$(9) where AUI is the activity utilization index. A_Th, A_Ra and A_K (Bq kg⁻¹) are the activity concentrations of ²³²Th, ²²⁶Ra and ⁴⁰K, respectively. Also, (f_Th= 0.604), (f_Ra= 0.462) and (f_K= 0.0417) are the respective fractional contributions from the actual activities of these radionuclides to the total gamma radiation dose rate in the air [30].

2.5. Geo-spatial analysis

With ArcGIS10.6, Kriging spatial interpolation method was used to generate the spatial distribution map of natural radionuclides in the soil of the study area. Utilizing this method, spatial analyses were conducted on prepared maps. The distribution area was assessed for concentrations of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K. Employing the Kriging technique, an experimental variogram model was developed based on data collected from the research area. Spatial transformation was implemented to identify the optimal model for utilization along with the parameters of the generated maps [37]. The ordinary Kriging formula is represented as follows: (10) $\begin{array}{r}Z(S_0)=\sum _{i=1}^N{\lambda }_{i}Z(S_i)\end{array}$(10) where Z(S_i) represents the recorded value at the specific location (i^th), λ_i signifies the unspecified weight assigned to the recorded value at the same location (i^th) and S₀ denotes the target estimation location.

The Kriging interpolation method becomes feasible by moving data into the GIS context. Consequently, analyses can be carried out in regions lacking data.

2.6. Multivariate statistical methods

IBM SPSS Statistics is a comprehensive statistical software package created by IBM, designed for tasks such as data management, advanced analytics, multivariate analysis, business intelligence and even criminal investigation. The statistical analysis of multiple variables was executed using IBM SPSS version 23 software, resulting in the generation of box plots based on experimental data.

3. Results and discussions

3.1. Activity concentrations of natural radionuclides in soil samples

The analysis results of specific activities of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K are shown in Table 1. The specific activities of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K in the factory area soil were 11.0 ± 0.7–14.2 ± 0.9, 41.9 ± 2.6–51.2 ±3.2, 12.2 ± 0.8–23.8 ± 1.5, 620.9 ± 39.3–658.8 ±41.7 Bq kg⁻¹, respectively. The specific activities of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K in the non-factory area soil are 8.7 ± 0.5–12.8 ± 0.8, 35.6 ± 2.2–51.6 ± 3.3, 8.3 ± 0.5–11.7 ± 0.7, 487.1 ± 30.8–609.0 ± 38.5 Bq kg⁻¹, respectively. The specific activities of radionuclides in the soil of the factory area were higher than those in the non-factory area, but all within the range of natural radioactivity levels in Chinese soil, and the ranges of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K are 1.8–520.0, 1.0–437.8, 2.4–425.8, 11.5–2185.2 Bq kg⁻¹, respectively [38].

Table 1. Specific activities of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K in soil samples.

		Country of origin Activity concentration (Bq kg^−1)
Sample No.	Sample codes	^238U	^232Th	^226Ra	^40K
1	N	11.0 ± 0.7	49.7 ± 3.1	12.2 ± 0.8	656.6 ± 41.5
2	S	14.2 ± 0.9	51.2 ± 3.2	20.8 ± 1.3	626.6 ± 40.1
3	W	11.7 ± 0.7	43.8 ± 2.8	15.2 ± 1.0	658.8 ± 41.7
4	E	11.9 ± 0.8	41.9 ± 2.6	14.1 ± 0.9	620.9 ± 39.3
5	NTP	11.9 ± 0.8	45.9 ± 2.9	23.8 ± 1.5	644.3 ± 40.8
6	V1	12.5 ± 0.8	36.8 ± 2.3	8.8 ± 0.6	553.5 ± 35.0
7	V2	12.4 ± 0.8	38.2 ± 2.4	8.7 ± 0.5	572.6 ± 36.2
8	V3	11.0 ± 0.7	42.9 ± 2.7	10.6 ± 0.7	547.9 ± 34.6
9	V4	9.8 ± 0.6	45.3 ± 2.9	10.6 ± 0.7	504.6 ± 31.9
10	V5	8.7 ± 0.5	40.6 ± 2.6	9.9 ± 0.6	513.9 ± 32.5
11	V6	9.4 ± 0.6	39.2 ± 2.5	10.7 ± 0.7	564.7 ± 35.7
12	V7	10.4 ± 0.7	38.7 ± 2.4	9.2 ± 0.6	487.1 ± 30.8
13	V8	10.7 ± 0.7	40.0 ± 2.5	10.4 ± 0.7	541.0 ± 34.2
14	V9	10.6 ± 0.7	43.9 ± 2.8	9.0 ± 0.6	502.5 ± 31.8
15	V10	10.9 ± 0.7	51.6 ± 3.3	11.0 ± 0.7	565.8 ± 35.8
16	V11	9.4 ± 0.6	41.1 ± 2.6	9.7 ± 0.6	506.3 ± 32.0
17	V12	10.3 ± 0.7	37.3 ± 2.4	10.8 ± 0.7	568.5 ± 36.0
18	V13	11.6 ± 0.7	40.0 ± 2.5	8.7 ± 0.6	572.6 ± 36.2
19	V14	9.6 ± 0.6	41.2 ± 2.6	11.7 ± 0.7	557.4 ± 35.3
20	V15	9.0 ± 0.6	35.6 ± 2.2	8.3 ± 0.5	562.6 ± 35.6
21	V16	10.9 ± 0.7	37.0 ± 2.3	9.6 ± 0.6	522.1 ± 33.0
22	V17	12.8 ± 0.8	42.8 ± 2.7	10.9 ± 0.7	503.1 ± 31.8
23	V18	10.0 ± 0.6	42.8 ± 2.7	10.7 ± 0.7	582.6 ± 36.8
24	V19	9.9 ± 0.6	39.0 ± 2.5	9.3 ± 0.6	512.4 ± 32.4
25	V20	8.7 ± 0.5	38.0 ± 2.4	9.6 ± 0.6	489.2 ± 30.9
26	V21	10.3 ± 0.6	40.2 ± 2.5	9.2 ± 0.6	570.2 ± 36.1
27	V22	12.4 ± 0.8	40.1 ± 2.5	9.6 ± 0.6	525.1 ± 33.2
28	V23	9.8 ± 0.6	39.9 ± 2.5	8.7 ± 0.6	526.5 ± 33.3
29	V24	10.2 ± 0.6	41.0 ± 2.6	9.7 ± 0.6	581.8 ± 36.8
30	V25	9.4 ± 0.6	42.9 ± 2.7	10.5 ± 0.7	533.1 ± 33.7
31	V26	10.7 ± 0.7	47.1 ± 3.0	10.2 ± 0.6	550.7 ± 34.8
32	V27	9.6 ± 0.6	44.1 ± 2.8	11.2 ± 0.7	499.5 ± 31.6
33	V28	11.0 ± 0.7	46.0 ± 2.9	11.3 ± 0.7	609.0 ± 38.5
Min		8.7	35.6	8.3	487.1
Max		14.2	51.6	23.8	658.8
Ave.		10.7	42.0	11.1	555.6

The results of this study are compared with these in other countries shown in Table 2. The activity concentrations of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K in soil samples were compared with several countries including Vietnam, Bangladesh, Ghana, Malaysia, India, Mumbai, Cameroon, Togo, Thailand, Egypt, Tunisia, Jordan, etc. In this study, the average values of ²³⁸U and ²²⁶Ra were lower than in other countries. The average value of ²³²Th was lower than in all countries except Vietnam, Ghana, Mumbai, Egypt, Tunisia and Jordan. The average value of ⁴⁰K was higher than in all countries except Bangladesh and Cameroon. According to the results of this study, it can be observed that the average activity concentrations of ²³⁸U, ²³²Th and ²²⁶Ra in soil samples were lower than the global average values (which are 33, 45 and 32 Bq kg⁻¹ respectively), except for 40 K (420 Bq kg⁻¹) [30]. This could be attributed to agricultural activities in the study area, including agricultural land use and wastewater discharge [51]. There are numerous villages and farmlands surrounding this area, and domestic wastewater from these villages is directly discharged into the surrounding environment without treatment. Additionally, potassium generated from agricultural land use and fertilization processes infiltrates the soil through surface runoff [52].

Table 2. Comparison of average specific activities in soils in the study area with those reported by other researchers in different countries.

	Activity Concentration (Bq kg^−1)
Location	^238U	^232Th	^226Ra	^40K	Type	Reference
Vietnam	NG^a	36	30	331	Quarry towns	[39]
Bangladesh	65.9	83.17	NG	946.9	Naturally	[40]
Ghana	NG	31	27	132	Quarry towns	[41]
Malaysia (Langkawi Island)	NG	4.5-1272	8.3-2411	61-136	Naturally	[42]
Malaysia (Penang Island)	NG	9-5622	8-2641	68-495	Naturally	[43]
India	NG	203.74	53.36	479.19	Naturally	[44]
Mumbai	161	20	169	172	Phosphate fertilizer plant	[9]
Cameroon	99	157	125	671	Bauxite mining	[45]
Togo	158.6	47.8	173	30.1	Phosphate ore mining	[46]
Thailand	103	103	64	494	Coal-based power plant	[47]
Egypt	947	39.1	1469	152.5	Phosphate rocks	[48]
Tunisia	221.3	39.1	236	35.4	Phosphate treatment plants	[49]
Jordan	NG	35.5	29.0	265.7	Naturally	[50]
China	10.7	42.0	11.1	555.6	Iron beneficiation plant	This research
China Average	39.5	49.1	36.5	580.0	Naturally	[38]
Worldwide Average	33	45	32	420	Naturally	[30]

^a Not given.

The Geo-Spatial distribution of natural radionuclides in the soil of the study area is shown in Figures 2–5. It can be found that the specific activities diffused from the factory area to the surrounding area, and the specific activities in the factory area were obviously higher than those in the non-factory area. Natural radionuclides are enriched in waste residues during processing, and these waste residues are piled up in the open air in the factory area, so there is a risk of release to the environment, affecting the surrounding ecological environment [39,41]. In addition, the specific activities are related to correlated with the elements, chemical and geological properties of the soil. Leaching, surface erosion and plant uptake are also major factors affecting the distribution of radionuclides [53,54].

Figure 2. Geo-Spatial distribution of ²³⁸U in the soils of the study area.

Figure 3. Geo-Spatial distribution of ²³²Th in the soils of the study area.

Figure 4. Geo-Spatial distribution of ²²⁶Ra in the soils of the study area.

Figure 5. Geo-Spatial distribution of ⁴⁰K in the soils of the study area.

3.2. Radiological health risk assessment

To evaluate the radiation hazards of ionizing radiation released from natural radionuclides in soil samples, radiation hazard indicators were calculated. Radiation hazards evaluation is important for the purpose of environmental protection studies because soil would have a continuous impact on the residents. The results are shown in Table 3.

Table 3. Radiation hazard indicators in soil samples.

Sample No.	Sample codes	Raeq (Bq kg^−1)	DR (nGy h^−1)	AED (μSv y^−1)	ELCR (10^−3)	Hex	Hin	AUI
1	N	133.8	62.5	76.6	0.3	0.4	0.4	0.8
2	S	142.3	63.6	78.0	0.3	0.4	0.4	0.9
3	W	128.6	59.3	72.8	0.3	0.3	0.4	0.7
4	E	121.8	56.7	69.5	0.2	0.3	0.4	0.7
5	NTP	139.0	60.1	73.7	0.3	0.4	0.4	0.8
6	V1	104.0	51.1	62.6	0.2	0.3	0.3	0.6
7	V2	107.4	52.7	64.6	0.2	0.3	0.3	0.6
8	V3	114.1	53.8	66.0	0.2	0.3	0.3	0.7
9	V4	114.2	52.9	64.9	0.2	0.3	0.3	0.7
10	V5	107.5	50.0	61.3	0.2	0.3	0.3	0.6
11	V6	110.2	51.6	63.2	0.2	0.3	0.3	0.6
12	V7	102.0	48.5	59.5	0.2	0.3	0.3	0.6
13	V8	109.3	51.7	63.4	0.2	0.3	0.3	0.6
14	V9	110.5	52.4	64.2	0.2	0.3	0.3	0.7
15	V10	128.4	59.8	73.3	0.3	0.3	0.4	0.8
16	V11	107.5	50.3	61.7	0.2	0.3	0.3	0.6
17	V12	107.9	51.0	62.5	0.2	0.3	0.3	0.6
18	V13	110.0	53.4	65.5	0.2	0.3	0.3	0.6
19	V14	113.5	52.6	64.5	0.2	0.3	0.3	0.7
20	V15	102.5	49.1	60.2	0.2	0.3	0.3	0.6
21	V16	102.7	49.2	60.3	0.2	0.3	0.3	0.6
22	V17	110.8	52.7	64.7	0.2	0.3	0.3	0.7
23	V18	116.8	54.8	67.2	0.2	0.3	0.3	0.7
24	V19	104.5	49.5	60.7	0.2	0.3	0.3	0.6
25	V20	101.6	47.4	58.1	0.2	0.3	0.3	0.6
26	V21	110.6	52.8	64.8	0.2	0.3	0.3	0.6
27	V22	107.4	51.8	63.6	0.2	0.3	0.3	0.6
28	V23	106.3	50.6	62.0	0.2	0.3	0.3	0.6
29	V24	113.1	53.7	65.9	0.2	0.3	0.3	0.6
30	V25	112.9	52.5	64.4	0.2	0.3	0.3	0.7
31	V26	120.0	56.4	69.1	0.2	0.3	0.4	0.7
32	V27	112.7	51.9	63.7	0.2	0.3	0.3	0.7
33	V28	124.0	58.3	71.5	0.3	0.3	0.4	0.7
Min		101.6	47.4	58.1	0.2	0.3	0.3	0.6
Max		142.3	63.6	78.0	0.3	0.4	0.4	0.9
Ave.		113.9	53.5	65.6	0.2	0.3	0.3	0.7
World wide safe limit		370	57	1000	1.45	1	1	1

The D_R of in the factory was 56.7–63.6 nGy h⁻¹, with an average of 60.4 nGy h⁻¹. The D_R of non-factory samples was 47.4–59.8 nGy h⁻¹, with an average of 52.2 nGy h⁻¹. The value of D_R is the highest at sampling point S on the south side of the factory area, and the lowest at sampling point V20 in the non-factory area. The largest contribution to D_R is ²³²Th (48%), followed by ⁴⁰K (43%) and ²³⁸U (9%). The average value of D_R in this region is lower than the world average of 57 nGy h⁻¹ [30].

Relying solely on the dose rate (D_R) may not provide a comprehensive reflection of the radiation hazard level. It is necessary to combine it with other hazard indices to collectively assess the situation [55]. The study area is located in a rural area, where people mainly make a living by farming. Therefore, people are mainly affected by the soil from outdoors. The AED is estimated by the absorbed dose rate and the conversion coefficient of the effective dose and the outdoor occupancy factor. The AED of the factory samples was 69.5–78.0 μSv y⁻¹, with an average of 74.1 μSv y⁻¹. The AED of the non-factory samples was 58.1–73.3 μSv y⁻¹, with an average of 64.0 μSv y⁻¹. The factory area is significantly higher than the non-factory area. However, these values are all lower than the maximum allowable limit of 1 mSv y⁻¹ recommended by ICRP [33].

The ELCR in the factory area is 0.3 × 10⁻³. The ELCR of non- factory samples were 0.2 × 10⁻³ to 0.3 × 10⁻³, with an average value of 0.2 × 10⁻³. The ELCR is the highest at the sampling points on the south side of the factory area, and the values in non-factory area were all lower than those in the factory area. These values are all lower than the world average of 1.45 × 10⁻³ [30].

The Ra_eq in the factory area was 121.8–142.3 Bq kg⁻¹, with an average of 133.1 Bq kg⁻¹. The Ra_eq of non-factory soil samples ranged from 101.6 to 128.4 Bq kg⁻¹, with an average of 110.4 Bq kg⁻¹. For Ra_eq, the sampling point S on the south side of the factory area is the highest, and the sampling point V20 in the non-factory area is the lowest. The largest contribution to Ra_eq is ²³²Th (53%), followed by ⁴⁰K (38%) and ²²⁶Ra (9%). The average value of Ra_eq in this region is lower than the world average of 370 Bq kg⁻¹ [30].

The H_ex range of the factory soil samples is 0.3–0.4, the average value is 0.4, and the H_in is 0.4. The H_ex of non-factory soil samples is 0.3, the H_in range is 0.3–0.4, and the average value is 0.3. The H_ex and H_in in the factory area were significantly higher than those in the non-factory area. The largest contribution to H_ex is ²³²Th (53%), followed by ⁴⁰K (38%) and ²²⁶Ra (9%). And for H_in, the largest contribution is ²³²Th (48%), followed by ⁴⁰K (34%) and ²²⁶Ra (17%). These values are all lower than the UNSCEAR recommendation of 1 [30].

The AUI in the factory area was 0.7–0.9, with an average value of 0.8. The AUI of non-factory samples was 0.6–0.8, with an average value of 0.6. The AUI was the highest at the sampling point S on the south side of the factory area, and the values of soil samples in the factory area were significantly higher than those in the non-factory area samples. The largest contribution to AUI was ²³²Th (78%), followed by ²²⁶Ra (15%) and ⁴⁰K (7%). The average AUI for the region is below the world average of 1 [30].

3.3. Statistical analysis

3.3.1. Basic statistics

Radiation measurement results in this study were statistically examined in order to get the most accurate conclusion on the significance and type of natural radionuclides in the soil of a Chinese iron beneficiation plant. It is shown in Table 4 that the descriptive statistics of activity concentration of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K. The central tendency and variation of the data are described using the arithmetic averages and the standard deviations of the activity concentrations of NORMs in all of the soil samples. Skewness of radionuclides ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K is positive, indicating an asymmetric distribution around the mean. Kurtosis serves as a measure to evaluate the prominence of a probability distribution for a real-valued random variable. By comparing it with a standard distribution, kurtosis characterizes the degree of prominence or flatness in a distribution. A positive kurtosis value indicates a distribution with a relatively sharp peak, while a negative kurtosis value signifies a flatter distribution. In this particular investigation, the kurtosis values for ⁴⁰K (−0.3) indicated a flattened distribution, while the positive kurtosis values of ²³⁸U (0.3), ²³²Th (0.3) and ²²⁶Ra (8.6) pointed to distributions with relatively pronounced peaks [31].

Table 4. Descriptive statistics of activity concentration of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K in soil samples.

	^238U	^232Th	^226Ra	^40K
Mean	10.7	42.0	11.1	555.6
Median	10.6	41.1	10.4	553.5
Standard Deviation	1.3	4.0	3.3	48.0
Variance	1.6	16.1	10.7	2301.7
Skewness	0.7	0.8	2.8	0.6
Kurtosis	0.3	0.3	8.6	−0.3
Range	5.5	16.0	15.5	171.7
Minimum	8.7	35.6	8.3	487.1
Maximum	14.2	51.6	23.8	658.8

3.3.2. Box plot

Figure 6 illustrates the Box plot showcasing the distribution of activity concentrations for ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K. The median is positioned close to the centre of the boxes for ²³⁸U, ²³²Th and ⁴⁰K, indicating a symmetrical and normally distributed data set. However, in the case of ²²⁶Ra, the median is positioned nearer to the upper part of the box, indicating a skewed distribution [34]. The outliers 2, 3, 4 and 5 observed in the boxplot of ²³²Th and ²²⁶Ra correspond to sampling points within the factory area, namely points S, W, E and NTP. This is attributed to the prolonged processing and production of associated radioactive iron ore within the factory premises, resulting in higher levels of radioactive nuclides such as ²³²Th and ²²⁶Ra in the soil environment compared to areas outside the factory. As for the outlier 15 in the boxplot of ²³²Th, it corresponds to the sampling point V10 within the non-factory area. This point is located less than 300 m from the factory. It is possible that during the transportation of ore or slag, there may have been instances of spillage, leading to higher levels of ²³²Th in the soil sample at V10 compared to other areas.

Figure 6. Box plots of the results on ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K activity concentrations in the soil samples.

3.3.3. Frequency distribution and Q-Q plot

The analysis of frequency distribution and Quantile-quantile (Q-Q) plots for activity concentrations of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K was conducted, and the corresponding histograms are presented in Figures 7–10. The activity concentration distribution of ⁴⁰K follows a normal distribution (bell-shaped), whereas the distributions of ²³⁸U, ²³²Th and ²²⁶Ra exhibit a log-normal pattern with some level of multimodality. This presence of multiple modes signifies the intricate nature of radionuclides within soil samples. The Q-Q plots depicted in Figures 7–10 reveal that the points align approximately along the 45-degree reference line, suggesting that the distributions can be reasonably assumed to be normal.

Figure 7. Frequency distribution and Quantile-quantile (Q-Q) plots of the activity concentrations for ²³⁸U of the investigated soil samples.

Figure 8. Frequency distribution and Quantile-quantile (Q-Q) plots of the activity concentrations for ²³²Th of the investigated soil samples.

Figure 9. Frequency distribution and Quantile-quantile (Q-Q) plots of the activity concentrations for ²²⁶Ra of the investigated soil samples.

Figure 10. Frequency distribution and Quantile-quantile (Q-Q) plots of the activity concentrations for ⁴⁰K of the investigated soil samples.

3.3.4. Pearson’s correlation coefficient analysis

Pearson's correlation coefficient analysis was employed to assess the interrelationships and their strengths among pairs of variables, as detailed in Table 5. Notably, a substantial correlation was observed between ²³²Th and ²²⁶Ra (r = 0.549), which can be attributed to their shared natural origins [56]. Additionally, the calculated correlations involving Ra_eq, D_R, AED, ELCR, H_ex, H_in and AUI demonstrated a perfectly positive linear relationship. This signifies a high degree of association among these parameters, with strong correlations extending to ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K.

Table 5. Pearson’s correlation matrix between radioactive variables of the investigated soil samples.

Variables	^238U	^232Th	^226Ra	^40K	Raeq	DR	AED	ELCR	Hex	Hin	AUI
^238U	1	0.320	0.467	0.452	0.478	0.562	0.563	0.409	0.421	0.437	0.431
^232Th	0.320	1	0.549	0.418	0.863	0.855	0.856	0.720	0.555	0.738	0.903
^226Ra	0.467	0.549	1	0.626	0.829	0.709	0.709	0.682	0.773	0.662	0.735
^40K	0.452	0.418	0.626	1	0.773	0.814	0.813	0.711	0.582	0.731	0.513
Raeq	0.478	0.863	0.829	0.773	1	0.973	0.973	0.855	0.747	0.865	0.901
DR	0.562	0.855	0.709	0.814	0.973	1	1.000	0.846	0.684	0.871	0.860
AED	0.563	0.856	0.709	0.813	0.973	1.000	1	0.846	0.684	0.870	0.860
ELCR	0.409	0.720	0.682	0.711	0.855	0.846	0.846	1	0.671	0.833	0.731
Hex	0.421	0.555	0.773	0.582	0.747	0.684	0.684	0.671	1	0.559	0.696
Hin	0.437	0.738	0.662	0.731	0.865	0.871	0.870	0.833	0.559	1	0.725
AUI	0.431	0.903	0.735	0.513	0.901	0.860	0.860	0.731	0.696	0.725	1

3.3.5. Cluster analysis

Cluster analysis (CA) was executed to explore the resemblances among radiological parameters, as depicted in Figure 11. The dendrogram visually presents clusters with shared characteristics. In this study, the average linkage method was utilized to quantify the distance between clusters. This method hinges on the smallest average distance value between clusters, akin to the single and full link techniques. Within the dendrogram, all 7 radiological parameters were categorized into two clusters. Cluster 1 encompasses parameters (²³⁸U, ²³²Th and ²²⁶Ra) that exhibit high similarity. This suggests that the radioactivity in soil samples primarily hinges on the activity concentrations of ²³⁸U, ²³²Th and ²²⁶Ra [57]. Meanwhile, Cluster II encompasses ⁴⁰K at a considerable Euclidean distance. Within the dendrogram, it's evident that D_R, AED and Ra_eq were predominantly influenced by ⁴⁰K.

Figure 11. Dendrogram shows the clustering of radiological parameters.

This study reveals the distribution and concentration of natural radioactive materials in specific environments, providing valuable data for environmental protection and human health. It aids in the formulation of more targeted protective measures and policies, thereby advancing sustainable development and public health management on a global scale. Additionally, it contributes to the accumulation and development of scientific knowledge, offering crucial reference for similar research in other regions and on different types of mineral resources, enriching the theoretical framework in the field of radiological studies. Finally, the achievements and experiences of this study can be shared for international cooperation, strengthening the collective understanding and response to environmental issues worldwide. Overall, this specific research not only contributes to solving localized problems but also provides valuable knowledge and resources for global scientific research and practical applications.

4. Conclusion

The specific activities and radiation hazard indicators in the factory area were higher than those in the non-factory area. The largest contribution to environmental pollution and health hazards was ²³²Th, potentially due to the enrichment of radionuclides in the waste slag generated during iron ore processing. There is a risk of release during the transportation of waste residues to open dumps, resulting in higher radioactivity in the factory area than in non-factory areas. The specific activities of ²³⁸U, ²³²Th, ²²⁶Ra and ⁴⁰K were all lower than the Chinese average. All radiation hazard indicators were lower than the world average. Therefore, people in the study area face no significant health risk from the presence of natural radionuclides of this area. This study serves as an initial assessment of the inherent specific activities in the study region, and it is advisable to maintain ongoing surveillance of the spatial fluctuations in specific activities going forward. From a statistical standpoint, the presence of a lognormal distribution in ²³⁸U, ²³²Th and ²²⁶Ra, coupled with multimodality, highlights the intricate nature of the sediment's attributes. The findings from Pearson’s correlation coefficient analysis underscore a significant correlation between ²³²Th and ²²⁶Ra. Cluster analysis (CA) further reveals that D_R, AED and Ra_eq are predominantly influenced by the presence of ⁴⁰K.

The findings of this study can serve as a foundational reference point for future research endeavours, while the data collected in this investigation holds potential value for the development of radioactivity mapping. The insights derived from this study were designed to contribute to the identification of sources of radionuclides, understanding their distribution patterns, and assessing potential public health risks associated with them.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Scientific Research Business Fee Project of Heilongjiang Provincial Scientific Research Institutes (CZKYF2021-2-B003), Ecological Environment Protection Scientific Research Project in Heilongjiang Province (HST2022H001), Youth Innovation Fund Project of Heilongjiang Academy of Sciences (CXMS2023YZNY01 and CXMS2023YZNY02).