Risk Assessment of Radioactive Elements in Atmospheric Dust Around Cement Stores in three States,Nigeria

Risk Assessment of Radioactive Elements in Atmospheric Dust Around Cement Stores in three States,Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Risk Assessment of Radioactive Elements in Atmospheric Dust Around Cement Stores in three States,Nigeria Ediagbonya Thompson Faraday, Emmanuel Oghenvovovwero Esi Emmanuel, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3981884/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This research investigates the numerous facts of radioactive elements, including their origins, how they impact various ecosystems, how they affect living beings as well as inanimate objects, how they can be quantified, and how they can be cleaned up. Samples were collected from Wuye Abuja, Guzape Abuja, Ore Ondo State, Ilado Ondo State, and Irele Ondo State, which are all locations in Nigeria. Each of these locations has a unique climate as well as other environmental characteristics. Ionizing radiation-emitting substances can be found in nature as well as be produced artificially. They have raised concerns because of their potential to harm nearby materials and living organisms. Obtaining a complete picture of how radioactive elements behave around the planet is the aim of this study. To understand how radioactive materials enter the environment, research examines both natural (such as uranium and thorium) and man-made (such as nuclear fallout) sources. For Samples A, B, C, D, and E, the mean concentrations of radium (Ra-226) are 185.20, 162.53, 142.28, 97.27, and 100.70, respectively. For Samples A, B, C, D, and E, the mean concentrations of uranium (U-238) are, respectively, 83.48, 84.60, 70.17, 47.57, and 48.07. Thorium (Th-232) average concentrations for Samples A, B, C, D, and E are 33.07, 26.86, 31.53, 26.40, and 27.60, respectively. While the mean potassium (K-40) concentrations for Samples A, B, C, D, and E are, respectively, 224.47, 115.70, 127.07, 62.30, and 78.33.Except for Uranium (U-238) with 84.60 in sample B, the results showed a significant difference in sample A. The highest values of Radium (Ra-226), Thorium (Th-232), and Potassium (K-40) were 185.20, 33.07, and 224.47, respectively. Radioactive element cement stores risk assessment Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Due to potential health dangers and negative effects on the ecosystem. The environmental occurrence of radioactive materials has garnered attention. These radioactive elements can be carried by and stored in dust, a common environmental component. To estimate the hazards of radiation exposure, comprehend environmental contamination, and ensure regulatory compliance, it is essential to identify radioactive components in dust (UNEP, 2015).Natural radioactive elements can be found everywhere, from geological formations to industrial processes. Radium, uranium, thorium, and radon gas are all naturally occurring sources that can be found in variable amounts in soil and rocks (UNSCEAR, 2000). Dust can contain radioactive elements due to human activities like construction, mining, and industrial procedures that release radioactive contaminants into the environment (IAEA, 2019).Dust, which is made up of microscopic airborne particles, both natural and manmade, can be found in many different places. (Ediagbonya et al.,2022;2020;2013;Goudie, 2018 ). In contrast to anthropogenic sources, which include activities like mining, construction, and transportation, rock weathering, volcanic eruptions, and wind erosion are examples of natural causes of dust. (Malm, 2003). Before settling on surfaces, dust particles can travel great distances after becoming suspended in the sky, including those close to industrial locations like cement storage facilities (Lyles et al., 2013 ).It is crucial to identify radioactive components in dust for a number of reasons. It addresses issues with radiation exposure and dust inhalation that are connected to health and safety. Radiation-related health problems, including cancer, may emerge from increased radiation exposure brought on by inhaling radioactive dust (WHO 2009). Exposure to radioactive elements may have detrimental impacts on one's health. How long and how much exposure influences the consequences differently. Acute exposure to high radiation levels can cause radiation sickness, which in some situations can be lethal. Long-term exposure to low amounts of radiation raises the risk of developing cancer, genetic defects, and other health problems. Environmental contamination can be caused by dust that contains radioactive materials. It poses threats to ecosystems and species when it settles into soil and water bodies, contaminating the two ( Ediagbonya et al 2020 2018;EC, 2018). This environmental influence can disturb natural systems and has important ecological ramifications. A crucial component of monitoring radioactive materials in dust is regulatory compliance. The release of radioactive elements into the environment is governed by laws and policies that have been created by numerous nations and international organizations (IAEA, 2014). The environment can become contaminated by radioactive substances, which could have harmful consequences. By contaminating soil, water, and air, radioactive isotopes can cause harm to plants, animals, and people. In addition, environmental pollution can Pollution lowers agricultural productivity, which has a detrimental effect on the economy and reducing biodiversity. These requirements apply to industrial operations in general, including cement storage facilities, therefore precise detection of radioactive elements in dust is crucial for compliance monitoring. The creation of effective methods to lower exposure hazards and environmental contamination, so protecting human health and the ecosystem, is made possible by identifying the sources and concentrations of radioactive elements in dust. A component of the environment known as dust, which is made up of tiny airborne particles, has the capacity to transport and store radioactive materials. The existence of these radioactive elements in dust has been the subject of extensive scientific investigation due to the potential consequences on industrial safety, human health, and the environment (Bossew et al., 2016). Dust can contain radioactive materials from both natural and man-made sources. Radon gas, radium, uranium, and thorium are some of the most prevalent naturally occurring radioactive elements (Ediagbonya ,2016; Ediagnoya etal.,2015;NORM) and can be found in variable proportions in soil and rocks (UNSCEAR, 2000). These substances contribute to the presence of these substances in dust because they are discharged into the surroundings as a result of processes like erosion and weathering. The spread of radioactive materials into the environment has been considerably aided by anthropogenic activity. For instance, mining can release radionuclides into the air, such as uranium and thorium, especially in areas with heavy mining activity. Radioactive contaminants are emitted into the atmosphere during production like nuclear power generation and some manufacturing operations (IAEA, 2019). The effects of radioactive dust components on the environment may be extensive. It is possible for soil and water to become contaminated when dust settles into these areas of the environment. Infiltrating radionuclides, such as those found in dust, can alter the radioactivity of soil and possibly result in soil pollution (European Commission [EC], 2018). The quality of the water and aquatic ecosystems may be impacted by dust that enters water bodies as well as its ability to spread water-borne pollution. Aquatic species may be at risk and the ecological balance may be upset by the introduction of radioactive elements into aquatic systems (International Atomic Energy Agency [IAEA, 2014]. This environmental impact emphasizes how crucial it is to keep an eye on and comprehend the presence of radioactive elements in dust, especially in areas where there are industrial and mining operations. MATERIAL AND METHODOLOGY STUDY AREA Nigeria's capital and seventh-most populated city is Abuja. Located in the Federal Capital Territory (FCT), this planned city was primarily constructed in the 1980s based on a master plan designed by International Planning Associates, a partnership of three American planning firms. The 400-meter (1,300-foot) Aso boulder, which was left behind by river erosion, serves as the geographic core of Abuja. There are three different weather patterns in the FCT each year. This has two seasons: a warm, humid one and a scorching, dry one. Due to the north-east trade wind, there is a brief period of harmony between the two; the primary features are dust haze and clear skies. It is thought that the rainy season lasts from April to October. At this time of year, daytime highs typically range from 28 to 30°C (82.4 to 86.0°F), while evening lows are roughly 22 to 23°C (73.4°F). During the dry season, daily highs of up to 40°C (104.0°F) and lows of as low as 15°C (59.0°F) are possible. In the afternoon, the temperature can soar well beyond 30°C (86.0°F), even on the coldest nights. The FCT's moderate height and gently undulating topography help to regulate the local weather. When compared to coastal locations with similar climates, such as Lagos, the city's inland location results in a noticeably higher diurnal temperature range. With its capital city of Ode Ondo, the Ondo Kingdom is a traditional nation with a five-century history. Akoko-Northeast, Akoko-Northwest, Akoko-Southwest, Akoko-Southeast, Akure-South, Akure-North, Ese-Odo, Idanre, Ifedore, Ilaje, Ile-Oluji-Okeigbo, Irele, Odigbo, Okitipupa, Ondo West, Ondo East, Ose, and Owo are among the 19 local government areas of the state. Nigeria's southwest geopolitical zone contains Ondo State. It was created out of the former Western State in 1976. Geographically speaking, the whole 14,788.723 square kilometres (km2) that makes up Ondo State are situated inside the tropical belt. The states of Ekiti and Kogi, Edo, Oyo, and Ogun, as well as the Atlantic Ocean, form the state's northern, eastern, western, and southern borders, respectively. Sample collection From cement storage facilities in Okitipupa, Oregon, and Abuja, Nigeria, dust samples were collected. The three-month period from February to April 2023, when the dust was estimated to be at its peak prevalence, was used for the collecting of soil samples. A soft plastic brush was used to carefully brush the topmost layer of dust at the cement store in order to collect the dust samples. The recovered dust was then placed in a dustpan and afterwards wrapped in polyethylene bags that had been acid-washed. Figure 1 and Table illustrates the study region Radiation Hazards The weighted total of the 238U, 232Th, and 40K activities is represented by the radium equivalent (Raeq) activity. It is predicated on the assumption that the radiation dosage rates produced by 1 Bq kg-1 of 238U, 0.7 Bq kg-1 of 232Th, and 13 Bq kg-1 of 40K are equivalent. (Avwiri and others, 2013). Detailed explanation of the various equation used for the computation of hazard risk had given by ( Veiga et al .,2006;Ediagbonya et al .,2020;2018) Table 1: Showing the coordinates of sample collection Figure 1 : showing sample locations ANALYSIS AND INSTRUMENTATION USING Co-Axial HpGe For radioactivity measurements, the calibration of the detector is a crucial component of gamma-ray spectroscopy. This is to guarantee that the energy and specific activity of the gamma ray spectra are correctly interpreted. In this paper, two types of calibration were performed. The first step, known as energy calibration, included allocating the proper channel numbers to the appropriate keV gamma ray energy peaks. The second, referred to as efficiency calibration, was to ascertain the detector's effectiveness in producing a spectrum with the specific setup at various energies. Efficiency is required to translate each photopeak's region into the radionuclide's activity. Utilising various known-energy gamma emitting sources is necessary for energy calibration. The IAEA provided the point sources of 241Am (59.54 keV), 60Co (1173.24 and 1332.49 keV), and 137Cs (661.66 keV). The HpGe detector was exposed to the gamma emitting sources, and the gamma spectrum was captured for 1000 seconds. Plotting the channel counts against the gamma energies results in a linear curve. Throughout the experiment, this calibration is kept in the multichannel analyzer's memory. QUALITY CONTROL The most recent information may be required for studies conducted in multiple locations and for regulatory limitations for radioactive elements, both of which are subject to change. To mitigate radioactive exposure to the broader public and individuals lacking sufficient training, the sampling location was secured and access was limited to approved personnel only. To provide reliable readings, radiation detectors and measurement tools are routinely calibrated. To avoid contamination and leakage, radiation-resistant sample packing was used. RESULTS AND DISCUSSION Table 2 Spatial variation of Radionuclides concentration in Bq/kg at different sampling sites SAMPLE A SAMPLE B SAMPLE C SAMPLE D SAMPLE E P Ra-226 185.20 ± 1.15 162.53 ± 0.65 142.28 ± 0.26 97.27 ± 0.50 100.70 ± 0.4 < 0.001 U-238 83.48 ± 0.92 84.60 ± 0.30 70.17 ± 0.21 47.57 ± 0.35 48.07 ± 0.15 < 0.001 Th- 232 33.07 ± 0.46 26.86 ± 0.35 31.53 ± 0.21 26.40 ± 0.36 27.60 ± 0.30 < 0.001 K-40 224.47 ± 0.91 115.70 ± 0.98 127.07 ± 1.31 62.30 ± 0.46 78.33 ± 0.47 <0.001 Table 2 : demonstrates how radioactive concentrations in Bq/Kg vary spatially between different sample sites. Four different radionuclides (Th-232, U-238, K-40,and Ra-226) were measured at five different sampling locations (E,D,C,B, and A), and the mean values and standard deviation are shown in the table. The mean concentration of Ra-226 in Sample A is the greatest (185.20 1.15 Bq/kg), and it differs considerably from the means of Samples B, C, D, and E. The concentrations of U-238 follow a similar pattern, with Samples A and B having higher amounts than Samples C, D, and E, with significant differences indicated by superscripts. The greatest mean is seen in Sample A for Th-232, which is substantially different from Samples B and D but not from Samples C and E. In the K-40 category, where Sample A has a much higher mean than all other samples, followed by Samples B and C with lower concentrations, and Samples D and E with the lowest concentrations, the spatial variation is quite remarkable. These patterns among various radionuclides point to variable rates of radioisotope deposition or accumulation throughout the sampling sites, which may be explained by elements like the geological composition of the sample sites, the use of the land, or other environmental circumstances. The geological makeup of the area is one of the most important elements influencing regional variance in radioactive concentrations. There are various concentrations of naturally occurring radioactive elements in various geological formations. According to Smith ( 2018 ), areas with granite or shale bedrock typically have higher quantities of uranium and thorium, it may lead to increased levels of radioactivity in the soil and the environment around it.. Additionally, human activities have a significant impact on how geographic variations in radionuclide concentrations are shaped. Due to leaks, spills, or poor waste disposal, areas close to nuclear power stations, mining operations, and industrial sites handling radioactive materials may have higher levels of radionuclides (Johnson & Martinez, 2017 ). These small hotspots can have a big influence on the neighboring inhabitants and environment. Radionuclides can migrate about in an area due to natural processes such erosion, sedimentation, and groundwater flow. These procedures have the ability to move radionuclides away from their original source and alter the way concentrations are distributed in space. For instance, tidal impacts and sediment dynamics may cause fluctuations in radioactive concentrations in coastal regions (Brown & White, 2019 ). Radionuclide concentrations are also influenced by topographical factors like elevation, closeness to water bodies, and drainage patterns. While elevated places may have varying quantities of radionuclides due to geological causes, low-lying areas may accumulate radionuclides through water runoff. Additionally, being close to lakes or rivers might cause radionuclides to build up in sediments (Garcia et al., 2020 ). In areas with complicated topography, these fluctuations can be quite important. Spatial heterogeneity in radioactive concentrations can be further exacerbated by the type of plant and soil present. The propensity of some plants to absorb and store radionuclides from the soil causes concentrations to vary depending on the local flora (Smith & Green, 2021 ). The retention and movement of radionuclides within an ecosystem can also be influenced by soil characteristics like pH and organic matter concentration. Soils and rocks are the main sources of radiation on land because naturally occurring radionuclides such as 238U, 232Th, and 40K, which are the main sources of gamma radiation, can be found in volcanic structures and granite, salt, and phosphate-rich rocks (David, 2015 ),is the United Nations Scientific Committee on Effects of Radiation. ).[UNSCEAR, 2008] states the principal causes of external exposures are gamma emitting radionuclides, particularly those belonging to the 232Th, 238U, and 40K families that are found in trace amounts in soil. U decay subseries, which is occasionally taken into account in place of 238U [Bussa & Belayneh, 2020 ] .Ionising radiation's short- and long-term health effects are mostly caused by naturally occurring radionuclides (NOR), of which 226Ra makes up 98%. Reducing any long-term effects to a manageable level and preventing any immediate effects will be aided by monitoring the quarry sites. Research on outdoor exposure rely on measured values of radionuclide concentrations in sample soil or direct dose rate readings. These radioactive materials are principally responsible for producing gamma radiation, according to Lust and Realo ( 2012 ). The International Atomic Energy Agency (IAEA, 2019) released a technical report that states that the distribution of radionuclides throughout the geosphere is determined by the distribution of the geological media from which they are derived and the mechanisms that concentrate them at a specific location in a given media. Naturally Occurring Radioactive Material (NORM) is defined by the IAEA Safety Glossary [IAEA, 2019] as radioactive material that does not contain any detectable levels of radionuclides other than those that occur naturally. The precise definition of a significant amount of naturally occurring radionuclides would be governed by regulations. Among the industries that use NORMs are mining, quarrying, oil drilling, and water production. 2000, among others (Haileyesus) Depending on the concentration, people who live close to or inside quarrying sites may be at risk for health problems due to NORM. Calculating the radiological impact on the general public and workers who may be exposed to gamma radiation from terrestrial natural radionuclides requires the identification and assessment of the types, spatial distributions, and concentrations of radionuclides in rocks and soil. (EPA's guidance, EPA's Memo) (IAE, 2019) states that in some regions with granites and phosphate limestone, radionuclides can be found in all kinds of soils, rocks, and materials. Additionally, the rock matrix in these areas may contain radioactive minerals at concentrations much higher than background levels. The Australian Radiation Protection and Nuclear Safety Agency (ARPANSA) released survey results on NORM related to mining and found that, while most sampled mining operations did not have elevated NORM levels, samples of quarry products had higher radiation results than mines. Due to the potential for high radiation levels in granite and other rocks, particularly those in the uranium family, quarries are particularly notable for their radiation hazards (Alakhdar et al., 2023 ). Table 3 Spatial variation of risk indices in the different sampling sites SAMPLE A SAMPLE B SAMPLE C SAMPLE D SAMPLE E P Outdoor dose- Rate (nGy/h) 29.73 ± 0.12 27.35 ± 0.15 24.03 ± 0.11 15.33 ± 0.15 18.27 ± 0.17 < 0.001 Indoordose-Rate (nGy/h) 17.79 ± 0.08 15.22 ± 0.06 13.36 ± 0.06 8.74 ± 0.05 10.82 ± 0.07 < 0.001 Raeq (bq/kg) 149.45 ± 2.42 134.02 ± 1.26 118.84 ± 0.68 76.78 ± 0.36 79.64 ± 0.38 <0.001 deout (mSv/y) 2.14 ± 0.03 1.93 ± 0.02 1.71 ± 0.01 1.10 ± 0.01 1.14 ± 0.01 <0.001 dein (mSv/y) 1.28 ± 0.02 1.08 ± 0.01 0.95 ± 0.01 0.63 ± 0.01 0.67 ± 0.01 <0.001 aGEd (mSv) 3.41 ± 0.07 2.86 ± 0.03 2.55 ± 0.02 1.69 ± 0.02 1.82 ± 0.01 <0.001 ELcR 0.27 ± 0.01 0.22 ± 0.01 0.20 ± 0.00 0.13 ± 0.00 0.14 ± 0.00 <0.001 External Hazard Index (H_ex) 0.31 ± 0.01 0.27 ± 0.01 0.24 ± 0.00 0.17 ± 0.00 0.18 ± 0.00 <0.001 Internal Hazard Index (H_in) 0.31 ± 0.01 0.27 ± 0.01 0.24 ± 0.00 0.17 ± 0.00 0.18 ± 0.00 <0.001 Table 3 : demonstrates how risk indices vary spatially across several sampling sites. These risk indices offer information about possible radiation exposure and related health problems in each area. With Sample A having the highest mean value (29.730.12 nGy/h) and being substantially different from the means of Samples B, C, D, and E (a > b, c, d, e), the Outdoor Dose-Rate (nGy/h) displays a clear spatial pattern. Similarly, Sample A has the highest mean value for Indoor Dose-Rate (nGy/h), with substantial variances between each sample. Similar patterns can be seen in the computed Risk Activity Equivalent (Raeq) in Bq/kg, with Sample A having the highest mean value (149.452.42 Bq/kg) and being significantly different from all other samples. This shows that Sample A may have a radionuclide concentration that is significantly higher, increasing the radiation risk. The generated dose-related indices, including deout (mSv/y), dein (mSv/y), and AGED (mSv), show a consistent pattern with Sample A having the highest mean values, indicating a probable higher radiation exposure in comparison to the other samples. Similar tendencies can also be seen in the Effective Lifetime Cancer Risk (ELCR) and the Hazard Index (H_ex and H_in), with Sample A having the highest mean values and the largest deviations from the means of the other samples. The geographical location of a sampling site is one of the main factors causing spatial variation in risk indices. Coastal communities are especially vulnerable due to the threat of flooding and sea level rise (Smith, 2018 ). On the other hand, inland areas may have completely distinct risk profiles due to exposures from industrial or agricultural activities (Johnson, 2017 ). Land use and cover are other important factors (Turner, 2019 ). High population density urban regions frequently face increased threats from hazardous waste and air pollution. Factors like road congestion and industrial pollutants increase these hazards (Garcia et al., 2015). On the other hand, due to their patterns of land use, rural or agricultural areas may face dangers from pesticide use and soil contamination (Brown, 2016 ). Spatial variations in risk indices are largely influenced by climate and weather patterns. For instance, areas with significant precipitation may experience higher risks of water-borne toxins due to run-off and the contaminant's permeability to water bodies (Jones, 2020 ). In contrast, areas subject to drought may have increased risks of wildfires and the related air quality problems, this may have negative consequences for human health (Davis et al., 2019). Topography and elevation should also be considered.. According to Li et al. ( 2018 ), topographic characteristics like valleys can trap pollutants, resulting in poor air quality and increased health risks for locals. On the other hand, high elevation regions may face greater dangers from UV radiation exposure and extreme weather conditions (Wang, 2017 ). The variance in risk across space is significantly influenced by proximity to pollution sources. Due to the emissions and discharge from factories and power plants, sampling locations close to industrial regions may face greater levels of air and water pollution (Garcia et al., 2015). Similar risks are associated with traffic-related pollutants, such as fine particulate matter and volatile organic compounds, for areas located close to major transportation corridors (Zhang, 2019 ). Geographical heterogeneity in risk indices is also influenced by demographic factors. Exposure and vulnerability may vary depending on the population density and composition at a sampling site. Due to different socioeconomic and environmental conditions, vulnerable individuals, such as children, the elderly, and low-income communities, may be at higher risk (Clark, 2020 ). This emphasises how critical it is to take social inequalities into account when evaluating and managing risks. Additionally important factors of risk variance are local laws and policies. Risk profiles among sample sites can range significantly depending on whether environmental rules are in place and if they are being followed. Sites in locations with loose restrictions might be exposed to more contaminants, whilst those in regions with strict rules might be at a lesser risk (EPA, 2021 ). Last but not least, historical variables like previous land use, industrial operations, and pollution events may have left a long-lasting contamination that still has an impact on risk indices. Due to contaminants and lingering pollutants, sampling locations with a mining or industry background may present higher hazards (Huang et al., 2017). Table 4 The findings were compared with those of other investigations using a soil sample in Ba/Kg. Area Radionuclides Concentration (BqKg − 1 ) Reference Abeokuta, Ogun state 40K 261.29 ± 36.84 (Ekhaguere et al, 2019 ) 226Ra 30.87 ± 6.81 232Th 238U 47.10 ± 11.95 46.5 Southwestern cities 40K 393.73 (Ibikunle et al, 2019 ) 226Ra 52.91 232Th 238U 76.79 19.72 Delta state 40K 413.64 ± 21.22 (Ononugbo et al, 2019) 226Ra 54.43 ± 3.22 232Th 238 U 561.67 ± 2.21 61.74 Ile-Ife, Osun state 40K 270.14 ± 61.79 (Oluyide et al, 2019 ) 226Ra 12.14 ± 4.17 232Th 238U 23.23 ± 7.67 23.72 Coastal area, Akwa Ibom state 40K 145 ± 6 (Akpan et al, 2020 ) 226Ra 23 ± 3 232Th 238U 36 ± 2 45.1 Sample A 40K 224.47 ± 0.91 This study 226Ra 185.20 ± 1.15 232Th 238U 33.07 ± 0.46 83.48 ± 0.92 Sample B 40K 115.70 ± 0.98 This study 226Ra 162.53 ± 0.65 232Th 238U 26.86 ± 0.35 84.60 ± 0.30 Sample C 40K 127.07 ± 1.31 This study 226Ra 142.28 ± 0.21 232Th 238U 29.05 ± 3.68 70.17 ± 0.21 Table 4 presents a comparison between the results of this study and other research that used Ba/Kg soil sample measurements. The results of this investigation can be compared to those of previous research conducted in Nigeria (Gbadamosi et al., 2017 ; Ibikunle et al., 2019 ; Oluyide et al., 2019 ; Ogunyele et al., 2020 ; Aleksakhin 2009 ; Akingboye et al., 2021 ). The activity concentrations that were found were lower than the global average. To reduce radioactive buildup, extended occupational exposure should be avoided. Figure 1 : demonstrates the dataset of Ra-226 (n = 15)'s normality, which was determined using an ogive's cumulative frequency curve. The cumulative distribution of the data is depicted visually by the normalcy curve. Ra-226 concentrations are mostly centered on the mean, and as they get closer to the upper and lower tails of the distribution, their cumulative frequency gradually rises. This pattern shows that the data follows a normal distribution, in which the majority of observations are centered on the mean and the frequency gradually declines as we move away from the mean. These results provide credence to the supposition that the radionuclide concentration is normal. Due to its possible effects on health and safety, the radionuclide Ra-226 is of interest in a number of environmental and radiological research (EPA, 2021 ). Figure 2 : demonstrates the U-238 dataset's (n = 15) normality, which was determined using an ogive's cumulative frequency curve. The cumulative distribution of the data is depicted visually by the normalcy curve. Due to its skewed distribution, the majority of the U-238 concentration did not cluster around the mean. This pattern indicates that the data differs from a normal distribution, in which the majority of observations are centered on the mean. Since the points diverged from the typical systematic pattern, it raises the possibility of non-normality, necessitating more investigation or data manipulations for statistical tests that rely on normality. Figure 3 : demonstrates the Th-232 dataset's (n = 15) normality, which was determined using an ogive's cumulative frequency curve. The cumulative distribution of the data is depicted visually by the normalcy curve. Due to its skewed distribution, the Th-238 concentration distribution did not cluster around the mean. This pattern indicates that the data differs from a normal distribution, in which the majority of observations are centered around the mean. Since the points diverged from the typical systematic pattern, it raises the possibility of non-normality, necessitating more investigation or data manipulations for statistical tests that rely on normality. Figure 4 : demonstrates the K-40 dataset's (n = 15) normality, which was determined using an ogive's cumulative frequency curve. The cumulative distribution of the data is depicted visually by the normalcy curve. Due to its skewed distribution, the majority of the K-40 concentration did not cluster around the mean. This pattern indicates that the data differs from a normal distribution, in which the majority of observations are centred around the mean. Since the points diverged from the typical systematic pattern, it raises the possibility of non-normality, necessitating more investigation or data manipulations for statistical tests that rely on normality. CONCLUSION The 226Ra, 238U, 232Th, and 40K radioactivity concentrations at five sites were computed. The inquiry was examined to see how the findings compared to IAEA guidelines and those of other studies of a similar nature. The highest value was found in sample B's 238U, whereas samples B, C, D, and E all had higher activity concentrations for 226Ra, 232Th, and 40K. Nevertheless, it was discovered that every radionuclide's value fell outside of the advised range.Despite these findings, the study recommends regular site inspections and assessments in order to guarantee the public's safety as well as the safety of the quarry personnel. The distribution of radionuclides in the environment must be understood for the objectives of environmental protection and monitoring. A rise in naturally occurring radioactive materials could result from human activities such as mining, farming, and drilling for crude oil. This could then induce a redistribution of radionuclides in the environment, which could pose health risks. An appropriate indicator of potentially significant radioactive element deposits in Nigeria, primordial radionuclide concentrations and their presence in a given area can be utilised for radioactive dating. Declarations Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data availability Data will be made available on request. Funding information Partially funded by the institution Consent to publish We give our consent to publish the manuscript Acknowledgments We thank the university management for providing the enabled environment in carrying the research References Akingboye A.S., Ogunyele A.C., Jimoh. (2021) Radioactivity, radiogenic heat production and environmental radiation risk of the basement complex rocks of Akungba-Akoko, southwestern Nigeria: insights from in situ gamma-ray spectrometry. Environ Earth Sci 80:228. https:// doi. org/ 10. 1007/ s12665- 021- 09516-7 Akpan A.E., Ebong E.D., Ekwok S.E., Eyo J.O. (2020) Assessment of radionuclide distribution and associated radiological hazards for soils and beach sediments of Akwa Ibom Coastline, southern Nigeria. Arab J Geosci 13(15):1–12. https://d oi.org/1 0 .1007 / s12517- 020- 05727-7 Alakhdar, E.M., Alhuweemdi, S.O., Hweeth, A.M. (2023). “The Impact of Urban Expansion and Quarry on the Vegetation Cover around Al - Khoums City - Libya,” 12 (5) 1887–1890, https://doi.org/10.21275/SR23522153623. Aleksakhin R.M (2009) radioactive contamination as a type of soil degradation. Eurasian Soil Sci 42:1386. https://d oi.org/1 0 .1134 / S1064 22930 91200 96 Avwiri.,G.O., Osimobi,J.C., AgbalagbaE.O (2012). Evaluation of Radiation Hazard Indices and Excess Lifetime Cancer Risk Due to Natural Radioactivity in soil profile of Udi and Ezeagu Local Government Areas of Enugu State, Nigeria. Comprehensive J. of Environmental and Earth Sci. 1(1): 1 – 10. Brown, A. (2016). "Assessing Agricultural Contamination in Rural Communities." Environmental Science Journal, 45(2), 112-125. Brown, J., & White, S. (2019). Tidal Influences on the Spatial Distribution of Radionuclide Concentrations in Coastal Sediments. Marine Environmental Science, 30(4), 415-430. Bussa N., Belayneh, A. (2020). Long-standing herbal medicinal traditions from the prehistoric harar town and the surroundings, eastern Ethiopia, J. Ayurvedic Herb. Med. 6 (3) 154–172, https://doi.org/10.31254/jahm.2020.6311. Clark, J. (2020). "Vulnerability Assessment of High-Density Urban Areas." Environmental Health Perspectives, 128(7), 076543. Darby, S., Hill, D., Auvinen, A., Barros-Dios, J. M., Baysson, H., Bochicchio, F., & Tirmarche, M. (2005). Radon in homes and risk of lung cancer: collaborative analysis of individual data from 13 European case-control studies. BMJ, 330(7485), 223. David, O., (2015). “Radiation Exposure to Natural Radioactivity in Crude Oil and Petroleum Waste from Oil Fields in Ghana; Modelling, Risk Assessment and Regulatory Control, 2015 [Online]. Available: http://ugspace.ug.edu.gh. EC (European Commission). (2018). Radiation Protection No. 179 - Protection of the Environment from Ionizing Radiation. Retrieved from https://ec.europa.eu/energy/sites/default/files/documents/179.pdf Ediagbonya T.F (2016) Enrichment factor of atmospheric trace metals using Zirconium Titanium,Iron and Copper as reference element.Nigeria journal of Technology 35 (4):785-795 Ediagbonya, T. F., Oyinlusi O. C Okungbowa E.G and Uche I. J (2022) Environmental and Human Health risk assessments of polycyclic aromatic hydrocarbons in particulate matter in okitipupa, Ondo State, Nigeria Environmental Monitoring and Assessment 194,(9):556 Ediagbonya, T. F., Okungbowa E.G and Titilayo O (2020). Background study of natural radioactive in soil. Journal of Chemical Society of Nigeria 45 (2) :290-298 Ediagbonya, T. F., Ukpebor, E. E and Okiemien, F. E.,Akojivi ,V.O (2013)Selected trace metals analysis of Total suspended particulate matter in rural area in Edo state,Nigeria. GreenerJournal of Environmental Management and Public Health 2(2): 91-98 Ediagbonya, T.F and Gbolahan O. I (2018). Determination of radioactive isotopes and some physio-chemical parameters in five different rivers in South-South Ondo State, Nigeria. International Journal of Low Radiation 11(1): 45- 65 Ediagbonya, T.F.Ukpebor, E.E .; Okieimen, F.E .(2015)Source identification of trace metal in total suspended particulate matter Int. J. Chem. Sci. 7: (1): 37-45 Ekhaguere OA, Alatise OO, Oyeyemi KD (2019) Assessment of natural radionuclides in a fertilized farmland in Abeokuta, Nigeria: implications for environmental radioactivity evaluation and monitoring. J Phys Conf Ser 1299(1):012093. https:// doi. org/ 10. 1088/ 1742- 6596/ 1299/1/ 012093 EPA (2021). "Environmental Regulations and Their Impact on Risk Indices." Environmental Protection Agency, Retrieved from EPA.gov. Garcia, M., Smith, J., Johnson, A. (2020). Influence of Terrain and Elevation on Radionuclide Concentrations in a Mountainous Region. Geophysical Research Letters, 47(8), e2020GL089764. Gbadamosi MR, Banjoko OO, Abudu KA, Ogunbanjo OO, Ogunneye AL (2017) Radiometric evaluation of excessive lifetime cancer probability due to naturally occurring radionuclides in wastes dumpsites soils in Agbara, Southwest, Nigeria. J Assoc Arab Univ Basic Appl Sci 24:315–324. https:// doi. org/ 10. 1016/j. jaubas. 2017. 06. 003 Goudie, A. (2018). Dust in the Wind: Long-range Transport of Dust in the Atmosphere and Its Implications for Global Public and Environmental Health. Global Health Action, 11(1), 1494902. Goudie, A. S. (2018). Dust storms: Recent developments. Journal of Environmental Management, 212, 411-417. Haileyesus W., Sintayehu Z., Heldal T. (2000). Building stone of central and southern Ethiopia: deposits and resource potential, NGU-BULL 436,175[Online]. Available: www.chariotinternational.com/priceListTiles.htm. Huang, S. (2017). "Legacy Contamination and Health Risks in Former Mining Sites." Journal of Environmental Science, 28(5), 831-843. IAEA (International Atomic Energy Agency). (2014). Environmental and Source Monitoring for Purposes of Radiation Protection. Retrieved from https://www-pub.iaea.org/MTCD/Publications/PDF/Pub1503web-12932606.pdf Ibikunle SB, Arogunjo AM, Ajayi OS (2019) Characterization of radiation dose and soil-to-plant transfer factor of natural radionuclides in some cities from south-western Nigeria and its effect on man. Sci Afr 3:e00062. https:// doi. org/ 10. 1016/j. sciaf. 2019. e00062 International Atomic Energy Agency [IAEA]. (2019). Environmental Impact Assessment for Uranium Mine Development. IAEA Safety Standards Series No. SSG-16. International Atomic Energy Agency. International Atomic Energy Agency [IAEA]. (2019). Radiation Protection and Safety of Radiation Sources: International Basic Safety Standards: General Safety Requirements Part 3. IAEA. International Atomic Energy Agency [IAEA]. (2019). Radioecology for Ecosystems: Biological Approaches to the Assessment of Radioactivity in Real Ecosystems. IAEA Technical Reports Series No. 481. International Atomic Energy Agency. International Commission on Radiological Protection [ICRP]. (2007). The 2007 Recommendations of the International Commission on Radiological Protection. ICRP Publication 103. Annals of the ICRP, 37(2-4). Johnson, D., & Martinez, E. (2017). Radionuclide Contamination in the Vicinity of a Uranium Mining Site: A Case Study in Western USA. Environmental Research, 55(2), 187-201. Johnson, R. (2017). "Industrial Activities and Environmental Risks in Inland Areas." Journal of Environmental Management, 204, 598-607. Jones, P. (2020). "Climatic Factors and Waterborne Contaminants." Water Research, 75(3), 124-135. Li, T., R.M. Horton, D.A. Bader, F. Liu, Q. Sun, and P.L. Kinney (2018). "Topography and Air Quality in Valley Regions." Atmospheric Environment, 182, 89-97. Lust, M., Realo, E. (2012). Ehitusmaterjalides leiduvatest looduslikest radionukliididest p˜ohjustatud elanikudoosi hinnang, Proc. Est. Acad. Sci. 61 (2) 107–112, https://doi.org/10.3176/proc.2012.2.03. Lyles, B. F., Tchounwou, P. B., & Collette, T. W. (2013). Windblown dust deposition on the external surfaces of industrial storage tanks: an environmental radiological health risk assessment. International Journal of Environmental Research and Public Health, 10(5), 1904-1924. Ogunyele AC, Obaje SO, Akingboye AS, Adeola AO, Babalola AO, Olufunmilayo AT (2020) Petrography and geochemistry of Neoproterozoic charnockite–granite association and metasedimentary rocks around Okpella, southwestern Nigeria. Arab J Geosci 13:780. https:// doi. org/ 10. 1007/ s12517- 020- 05785-x Oluyide SO, Tchokossa P, Akinyose FC, Orosun MM (2019) Assessment of radioactivity levels and transfer factor of natural radionuclides around iron and steel smelting company located in Fashina village, Ile-ife, Osun state, Nigeria. Facta Universitatis, Series: Working and Living Environmental Protection, pp 241–256 Ononugbo CP, Amah OS (2019) Radioactivity concentrations and their radiological significance in sediments of some communities in Andoni, Rivers State, Nigeria. Asian J Adv Res Rep. https://d oi. org/ 10. 9734/ ajarr/ 2019/ v6i33 0151 Smith, A., Johnson, B., & White, C. (2018). Spatial Variation of Radionuclide Concentrations in Appalachian Soils. Environmental Science Journal, 42(3), 321-335. Smith, D. (2018). "Coastal Vulnerabilities and Climate Change Risks." Nature Climate Change, 7(3), 205-211. Smith, R., & Green, L. (2021). Effects of Tree Species on the Spatial Distribution of Radionuclide Concentrations in Forest Soils. Journal of Environmental Ecology, 40(5), 621-635. Turner, L. (2019). "Urbanization and Risk Factors in Dense Developments." Urban Studies, 36(4), 498-513. UNEP (United Nations Environment Programme). (2015). Radiological Assessment Reports Series - Assessment of Radionuclides in Food and the Environment. Retrieved from https://www.iaea.org/publications/108 United Nations Scientific Committee on the Effects of Atomic Radiation [UNSCEAR]. (2000). Sources and Effects of Ionizing Radiation: United Nations Scientific Committee on the Effects of Atomic Radiation: UNSCEAR 2000 Report, Vol. 1, Annex B. Sources. United Nations. Veiga.,R.G., Sanches.,H., Anjos.,R.M., Macario.,K., Bastos .,J., Iguatemy., M.,.Aguitar.,J.G Santos.,M.A., Mosquera., B.,.Carvaiho.,C., Baptista., M.,Umisedo ,N.K(2006) Measurement of natural radioactivity in Brazilizn beach sands. Radiation Measurements. 41: 189-196. Wang, Y. (2017). "High-Elevation Areas and Their Unique Risk Profiles." Mountain Research, 22(1), 45-58. Zhang, H. (2019). "Transportation-Related Pollution and Risks Near Highways." Transportation Research, 42(5), 763-774. Additional Declarations No competing interests reported. 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Faraday","email":"data:image/png;base64,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","orcid":"","institution":"Olusegun Agagu University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Ediagbonya","middleName":"Thompson","lastName":"Faraday","suffix":""},{"id":275316203,"identity":"05daf7e0-8cbd-4a86-a7dd-3749eaecb6d2","order_by":1,"name":"Emmanuel Oghenvovovwero Esi Emmanuel","email":"","orcid":"","institution":"Dennis Osadebay University","correspondingAuthor":false,"prefix":"","firstName":"Emmanuel","middleName":"Oghenvovovwero Esi","lastName":"Emmanuel","suffix":""},{"id":275316204,"identity":"693a97c8-ef45-4301-9117-bb3996ce253f","order_by":2,"name":"Sabastine Dekas Francis","email":"","orcid":"","institution":"Olusegun Agagu University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Sabastine","middleName":"Dekas","lastName":"Francis","suffix":""},{"id":275316205,"identity":"2b76ff8f-4520-4277-a50f-70d7dc7e0dad","order_by":3,"name":"Oziegbe Friday Elumah","email":"","orcid":"","institution":"Federal University of Petroleum Resources","correspondingAuthor":false,"prefix":"","firstName":"Oziegbe","middleName":"Friday","lastName":"Elumah","suffix":""},{"id":275316206,"identity":"58341428-4a25-421e-a500-cc4c29f2f71b","order_by":4,"name":"Adelani Gabriel Timilehin","email":"","orcid":"","institution":"Olusegun Agagu University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Adelani","middleName":"Gabriel","lastName":"Timilehin","suffix":""}],"badges":[],"createdAt":"2024-02-23 13:03:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3981884/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3981884/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51829806,"identity":"ea887706-0107-4eca-a461-198e82e64e76","added_by":"auto","created_at":"2024-02-29 18:04:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1423862,"visible":true,"origin":"","legend":"\u003cp\u003eshowing sample locations\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3981884/v1/4b8f2c53984ad9e99387e5df.png"},{"id":51829803,"identity":"b7ad0dd4-04dc-44d0-97b9-f738878a4558","added_by":"auto","created_at":"2024-02-29 18:04:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":19835,"visible":true,"origin":"","legend":"\u003cp\u003eFIGURE 1: Normality Plot for R-226\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3981884/v1/7c25e907ef8e1006185f142d.png"},{"id":51830180,"identity":"0952bda8-d8db-4fa7-88af-e17eb884a566","added_by":"auto","created_at":"2024-02-29 18:12:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":19395,"visible":true,"origin":"","legend":"\u003cp\u003eFIGURE 2: NORMALITY PLOT FOR U-238\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3981884/v1/bec3a707b45a657d1404ce3b.png"},{"id":51829804,"identity":"c30cb021-a208-4430-a91e-5509f941edd9","added_by":"auto","created_at":"2024-02-29 18:04:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":18506,"visible":true,"origin":"","legend":"\u003cp\u003eFIGURE 3: NORMALITY PLOT FOR Th-232\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3981884/v1/4e5fabc83664512fda991d0f.png"},{"id":51829807,"identity":"3a50f231-7abf-4ee3-ac6a-de59d93f1a09","added_by":"auto","created_at":"2024-02-29 18:04:41","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":133458,"visible":true,"origin":"","legend":"\u003cp\u003eFIGURE 4: NORMALITY PLOT FOR K-40\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3981884/v1/3cedffce4fa251a5381238b9.png"},{"id":53077635,"identity":"449d9e0a-6ea9-481d-87c7-d14c848fba3f","added_by":"auto","created_at":"2024-03-20 10:02:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2106645,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3981884/v1/fd3ecf59-1dd5-4358-ab71-238f4d5f62d8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Risk Assessment of Radioactive Elements in Atmospheric Dust Around Cement Stores in three States,Nigeria","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eDue to potential health dangers and negative effects on the ecosystem. The environmental occurrence of radioactive materials has garnered attention. These radioactive elements can be carried by and stored in dust, a common environmental component. To estimate the hazards of radiation exposure, comprehend environmental contamination, and ensure regulatory compliance, it is essential to identify radioactive components in dust (UNEP, 2015).Natural radioactive elements can be found everywhere, from geological formations to industrial processes. Radium, uranium, thorium, and radon gas are all naturally occurring sources that can be found in variable amounts in soil and rocks (UNSCEAR, 2000). Dust can contain radioactive elements due to human activities like construction, mining, and industrial procedures that release radioactive contaminants into the environment (IAEA, 2019).Dust, which is made up of microscopic airborne particles, both natural and manmade, can be found in many different places. (Ediagbonya et al.,2022;2020;2013;Goudie, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In contrast to anthropogenic sources, which include activities like mining, construction, and transportation, rock weathering, volcanic eruptions, and wind erosion are examples of natural causes of dust. (Malm, 2003). Before settling on surfaces, dust particles can travel great distances after becoming suspended in the sky, including those close to industrial locations like cement storage facilities (Lyles et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).It is crucial to identify radioactive components in dust for a number of reasons. It addresses issues with radiation exposure and dust inhalation that are connected to health and safety. Radiation-related health problems, including cancer, may emerge from increased radiation exposure brought on by inhaling radioactive dust (WHO 2009). Exposure to radioactive elements may have detrimental impacts on one's health. How long and how much exposure influences the consequences differently. Acute exposure to high radiation levels can cause radiation sickness, which in some situations can be lethal. Long-term exposure to low amounts of radiation raises the risk of developing cancer, genetic defects, and other health problems. Environmental contamination can be caused by dust that contains radioactive materials. It poses threats to ecosystems and species when it settles into soil and water bodies, contaminating the two ( Ediagbonya et al \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e 2018;EC, 2018). This environmental influence can disturb natural systems and has important ecological ramifications. A crucial component of monitoring radioactive materials in dust is regulatory compliance. The release of radioactive elements into the environment is governed by laws and policies that have been created by numerous nations and international organizations (IAEA, 2014). The environment can become contaminated by radioactive substances, which could have harmful consequences. By contaminating soil, water, and air, radioactive isotopes can cause harm to plants, animals, and people. In addition, environmental pollution can Pollution lowers agricultural productivity, which has a detrimental effect on the economy and reducing biodiversity. These requirements apply to industrial operations in general, including cement storage facilities, therefore precise detection of radioactive elements in dust is crucial for compliance monitoring. The creation of effective methods to lower exposure hazards and environmental contamination, so protecting human health and the ecosystem, is made possible by identifying the sources and concentrations of radioactive elements in dust. A component of the environment known as dust, which is made up of tiny airborne particles, has the capacity to transport and store radioactive materials. The existence of these radioactive elements in dust has been the subject of extensive scientific investigation due to the potential consequences on industrial safety, human health, and the environment (Bossew et al., 2016). Dust can contain radioactive materials from both natural and man-made sources. Radon gas, radium, uranium, and thorium are some of the most prevalent naturally occurring radioactive elements (Ediagbonya ,2016; Ediagnoya etal.,2015;NORM) and can be found in variable proportions in soil and rocks (UNSCEAR, 2000). These substances contribute to the presence of these substances in dust because they are discharged into the surroundings as a result of processes like erosion and weathering. The spread of radioactive materials into the environment has been considerably aided by anthropogenic activity. For instance, mining can release radionuclides into the air, such as uranium and thorium, especially in areas with heavy mining activity. Radioactive contaminants are emitted into the atmosphere during production like nuclear power generation and some manufacturing operations (IAEA, 2019). The effects of radioactive dust components on the environment may be extensive. It is possible for soil and water to become contaminated when dust settles into these areas of the environment. Infiltrating radionuclides, such as those found in dust, can alter the radioactivity of soil and possibly result in soil pollution (European Commission [EC], 2018). The quality of the water and aquatic ecosystems may be impacted by dust that enters water bodies as well as its ability to spread water-borne pollution. Aquatic species may be at risk and the ecological balance may be upset by the introduction of radioactive elements into aquatic systems (International Atomic Energy Agency [IAEA, 2014]. This environmental impact emphasizes how crucial it is to keep an eye on and comprehend the presence of radioactive elements in dust, especially in areas where there are industrial and mining operations.\u003c/p\u003e"},{"header":"MATERIAL AND METHODOLOGY","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSTUDY AREA\u003c/h2\u003e \u003cp\u003eNigeria's capital and seventh-most populated city is Abuja. Located in the Federal Capital Territory (FCT), this planned city was primarily constructed in the 1980s based on a master plan designed by International Planning Associates, a partnership of three American planning firms. The 400-meter (1,300-foot) Aso boulder, which was left behind by river erosion, serves as the geographic core of Abuja. There are three different weather patterns in the FCT each year. This has two seasons: a warm, humid one and a scorching, dry one. Due to the north-east trade wind, there is a brief period of harmony between the two; the primary features are dust haze and clear skies. It is thought that the rainy season lasts from April to October. At this time of year, daytime highs typically range from 28 to 30\u0026deg;C (82.4 to 86.0\u0026deg;F), while evening lows are roughly 22 to 23\u0026deg;C (73.4\u0026deg;F). During the dry season, daily highs of up to 40\u0026deg;C (104.0\u0026deg;F) and lows of as low as 15\u0026deg;C (59.0\u0026deg;F) are possible. In the afternoon, the temperature can soar well beyond 30\u0026deg;C (86.0\u0026deg;F), even on the coldest nights. The FCT's moderate height and gently undulating topography help to regulate the local weather. When compared to coastal locations with similar climates, such as Lagos, the city's inland location results in a noticeably higher diurnal temperature range. With its capital city of Ode Ondo, the Ondo Kingdom is a traditional nation with a five-century history. Akoko-Northeast, Akoko-Northwest, Akoko-Southwest, Akoko-Southeast, Akure-South, Akure-North, Ese-Odo, Idanre, Ifedore, Ilaje, Ile-Oluji-Okeigbo, Irele, Odigbo, Okitipupa, Ondo West, Ondo East, Ose, and Owo are among the 19 local government areas of the state. Nigeria's southwest geopolitical zone contains Ondo State. It was created out of the former Western State in 1976. Geographically speaking, the whole 14,788.723 square kilometres (km2) that makes up Ondo State are situated inside the tropical belt. The states of Ekiti and Kogi, Edo, Oyo, and Ogun, as well as the Atlantic Ocean, form the state's northern, eastern, western, and southern borders, respectively.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample collection\u003c/h3\u003e\n\u003cp\u003eFrom cement storage facilities in Okitipupa, Oregon, and Abuja, Nigeria, dust samples were collected. The three-month period from February to April 2023, when the dust was estimated to be at its peak prevalence, was used for the collecting of soil samples. A soft plastic brush was used to carefully brush the topmost layer of dust at the cement store in order to collect the dust samples. The recovered dust was then placed in a dustpan and afterwards wrapped in polyethylene bags that had been acid-washed. Figure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and Table illustrates the study region\u003c/p\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eRadiation Hazards\u003c/h2\u003e\n \u003cp\u003eThe weighted total of the 238U, 232Th, and 40K activities is represented by the radium equivalent (Raeq) activity. It is predicated on the assumption that the radiation dosage rates produced by 1 Bq kg-1 of 238U, 0.7 Bq kg-1 of 232Th, and 13 Bq kg-1 of 40K are equivalent. (Avwiri and others, 2013). Detailed explanation of the various equation used for the computation of hazard risk had given by ( Veiga et al .,2006;Ediagbonya et al .,2020;2018)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;1: Showing the coordinates of sample collection\u003c/strong\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1709207590.png\"\u003e\u003cbr\u003e\u003c/h2\u003e\n \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n \u003cdiv id=\"Sec10\" class=\"Section4\"\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e : showing sample locations\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eANALYSIS AND INSTRUMENTATION USING Co-Axial HpGe\u003c/h2\u003e\n \u003cp\u003eFor radioactivity measurements, the calibration of the detector is a crucial component of gamma-ray spectroscopy. This is to guarantee that the energy and specific activity of the gamma ray spectra are correctly interpreted. In this paper, two types of calibration were performed. The first step, known as energy calibration, included allocating the proper channel numbers to the appropriate keV gamma ray energy peaks. The second, referred to as efficiency calibration, was to ascertain the detector\u0026apos;s effectiveness in producing a spectrum with the specific setup at various energies. Efficiency is required to translate each photopeak\u0026apos;s region into the radionuclide\u0026apos;s activity. Utilising various known-energy gamma emitting sources is necessary for energy calibration. The IAEA provided the point sources of 241Am (59.54 keV), 60Co (1173.24 and 1332.49 keV), and 137Cs (661.66 keV). The HpGe detector was exposed to the gamma emitting sources, and the gamma spectrum was captured for 1000 seconds. Plotting the channel counts against the gamma energies results in a linear curve. Throughout the experiment, this calibration is kept in the multichannel analyzer\u0026apos;s memory.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eQUALITY CONTROL\u003c/h2\u003e\n \u003cp\u003eThe most recent information may be required for studies conducted in multiple locations and for regulatory limitations for radioactive elements, both of which are subject to change. To mitigate radioactive exposure to the broader public and individuals lacking sufficient training, the sampling location was secured and access was limited to approved personnel only. To provide reliable readings, radiation detectors and measurement tools are routinely calibrated. To avoid contamination and leakage, radiation-resistant sample packing was used.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSpatial variation of Radionuclides concentration in Bq/kg at different sampling sites\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSAMPLE A\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSAMPLE B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSAMPLE C\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSAMPLE D\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSAMPLE E\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRa-226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e185.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e162.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e142.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e97.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e100.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eU-238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e83.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e84.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e70.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e47.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e48.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTh- 232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e33.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e26.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e26.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e27.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK-40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e224.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e115.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e127.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e62.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e78.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e: demonstrates how radioactive concentrations in Bq/Kg vary spatially between different sample sites. Four different radionuclides (Th-232, U-238, K-40,and Ra-226) were measured at five different sampling locations (E,D,C,B, and A), and the mean values and standard deviation are shown in the table. The mean concentration of Ra-226 in Sample A is the greatest (185.20 1.15 Bq/kg), and it differs considerably from the means of Samples B, C, D, and E. The concentrations of U-238 follow a similar pattern, with Samples A and B having higher amounts than Samples C, D, and E, with significant differences indicated by superscripts. The greatest mean is seen in Sample A for Th-232, which is substantially different from Samples B and D but not from Samples C and E. In the K-40 category, where Sample A has a much higher mean than all other samples, followed by Samples B and C with lower concentrations, and Samples D and E with the lowest concentrations, the spatial variation is quite remarkable. These patterns among various radionuclides point to variable rates of radioisotope deposition or accumulation throughout the sampling sites, which may be explained by elements like the geological composition of the sample sites, the use of the land, or other environmental circumstances. The geological makeup of the area is one of the most important elements influencing regional variance in radioactive concentrations. There are various concentrations of naturally occurring radioactive elements in various geological formations. According to Smith (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), areas with granite or shale bedrock typically have higher quantities of uranium and thorium, it may lead to increased levels of radioactivity in the soil and the environment around it.. Additionally, human activities have a significant impact on how geographic variations in radionuclide concentrations are shaped. Due to leaks, spills, or poor waste disposal, areas close to nuclear power stations, mining operations, and industrial sites handling radioactive materials may have higher levels of radionuclides (Johnson \u0026amp; Martinez, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These small hotspots can have a big influence on the neighboring inhabitants and environment. Radionuclides can migrate about in an area due to natural processes such erosion, sedimentation, and groundwater flow. These procedures have the ability to move radionuclides away from their original source and alter the way concentrations are distributed in space. For instance, tidal impacts and sediment dynamics may cause fluctuations in radioactive concentrations in coastal regions (Brown \u0026amp; White, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Radionuclide concentrations are also influenced by topographical factors like elevation, closeness to water bodies, and drainage patterns. While elevated places may have varying quantities of radionuclides due to geological causes, low-lying areas may accumulate radionuclides through water runoff. Additionally, being close to lakes or rivers might cause radionuclides to build up in sediments (Garcia et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In areas with complicated topography, these fluctuations can be quite important. Spatial heterogeneity in radioactive concentrations can be further exacerbated by the type of plant and soil present. The propensity of some plants to absorb and store radionuclides from the soil causes concentrations to vary depending on the local flora (Smith \u0026amp; Green, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The retention and movement of radionuclides within an ecosystem can also be influenced by soil characteristics like pH and organic matter concentration. Soils and rocks are the main sources of radiation on land because naturally occurring radionuclides such as 238U, 232Th, and 40K, which are the main sources of gamma radiation, can be found in volcanic structures and granite, salt, and phosphate-rich rocks (David, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e),is the United Nations Scientific Committee on Effects of Radiation. ).[UNSCEAR, 2008] states the principal causes of external exposures are gamma emitting radionuclides, particularly those belonging to the 232Th, 238U, and 40K families that are found in trace amounts in soil. U decay subseries, which is occasionally taken into account in place of 238U [Bussa \u0026amp; Belayneh, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e] .Ionising radiation's short- and long-term health effects are mostly caused by naturally occurring radionuclides (NOR), of which 226Ra makes up 98%. Reducing any long-term effects to a manageable level and preventing any immediate effects will be aided by monitoring the quarry sites. Research on outdoor exposure rely on measured values of radionuclide concentrations in sample soil or direct dose rate readings. These radioactive materials are principally responsible for producing gamma radiation, according to Lust and Realo (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The International Atomic Energy Agency (IAEA, 2019) released a technical report that states that the distribution of radionuclides throughout the geosphere is determined by the distribution of the geological media from which they are derived and the mechanisms that concentrate them at a specific location in a given media. Naturally Occurring Radioactive Material (NORM) is defined by the IAEA Safety Glossary [IAEA, 2019] as radioactive material that does not contain any detectable levels of radionuclides other than those that occur naturally. The precise definition of a significant amount of naturally occurring radionuclides would be governed by regulations. Among the industries that use NORMs are mining, quarrying, oil drilling, and water production. 2000, among others (Haileyesus) Depending on the concentration, people who live close to or inside quarrying sites may be at risk for health problems due to NORM. Calculating the radiological impact on the general public and workers who may be exposed to gamma radiation from terrestrial natural radionuclides requires the identification and assessment of the types, spatial distributions, and concentrations of radionuclides in rocks and soil. (EPA's guidance, EPA's Memo) (IAE, 2019) states that in some regions with granites and phosphate limestone, radionuclides can be found in all kinds of soils, rocks, and materials. Additionally, the rock matrix in these areas may contain radioactive minerals at concentrations much higher than background levels. The Australian Radiation Protection and Nuclear Safety Agency (ARPANSA) released survey results on NORM related to mining and found that, while most sampled mining operations did not have elevated NORM levels, samples of quarry products had higher radiation results than mines. Due to the potential for high radiation levels in granite and other rocks, particularly those in the uranium family, quarries are particularly notable for their radiation hazards (Alakhdar et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSpatial variation of risk indices in the different sampling sites\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSAMPLE A\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSAMPLE B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSAMPLE C\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSAMPLE D\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSAMPLE E\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutdoor dose- Rate (nGy/h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e29.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e27.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e24.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e15.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e18.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndoordose-Rate (nGy/h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e17.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e15.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e13.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e8.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e10.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRaeq (bq/kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e149.45\u0026thinsp;\u0026plusmn;\u0026thinsp;2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e134.02\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e118.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e76.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e79.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edeout (mSv/y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e1.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e1.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edein (mSv/y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eaGEd (mSv)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e1.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e1.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eELcR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExternal Hazard Index (H_ex)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternal Hazard Index (H_in)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e: demonstrates how risk indices vary spatially across several sampling sites. These risk indices offer information about possible radiation exposure and related health problems in each area. With Sample A having the highest mean value (29.730.12 nGy/h) and being substantially different from the means of Samples B, C, D, and E (a\u0026thinsp;\u0026gt;\u0026thinsp;b, c, d, e), the Outdoor Dose-Rate (nGy/h) displays a clear spatial pattern. Similarly, Sample A has the highest mean value for Indoor Dose-Rate (nGy/h), with substantial variances between each sample. Similar patterns can be seen in the computed Risk Activity Equivalent (Raeq) in Bq/kg, with Sample A having the highest mean value (149.452.42 Bq/kg) and being significantly different from all other samples. This shows that Sample A may have a radionuclide concentration that is significantly higher, increasing the radiation risk. The generated dose-related indices, including deout (mSv/y), dein (mSv/y), and AGED (mSv), show a consistent pattern with Sample A having the highest mean values, indicating a probable higher radiation exposure in comparison to the other samples. Similar tendencies can also be seen in the Effective Lifetime Cancer Risk (ELCR) and the Hazard Index (H_ex and H_in), with Sample A having the highest mean values and the largest deviations from the means of the other samples. The geographical location of a sampling site is one of the main factors causing spatial variation in risk indices. Coastal communities are especially vulnerable due to the threat of flooding and sea level rise (Smith, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). On the other hand, inland areas may have completely distinct risk profiles due to exposures from industrial or agricultural activities (Johnson, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Land use and cover are other important factors (Turner, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). High population density urban regions frequently face increased threats from hazardous waste and air pollution. Factors like road congestion and industrial pollutants increase these hazards (Garcia et al., 2015). On the other hand, due to their patterns of land use, rural or agricultural areas may face dangers from pesticide use and soil contamination (Brown, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Spatial variations in risk indices are largely influenced by climate and weather patterns. For instance, areas with significant precipitation may experience higher risks of water-borne toxins due to run-off and the contaminant's permeability to water bodies (Jones, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In contrast, areas subject to drought may have increased risks of wildfires and the related air quality problems, this may have negative consequences for human health (Davis et al., 2019). Topography and elevation should also be considered.. According to Li et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), topographic characteristics like valleys can trap pollutants, resulting in poor air quality and increased health risks for locals. On the other hand, high elevation regions may face greater dangers from UV radiation exposure and extreme weather conditions (Wang, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The variance in risk across space is significantly influenced by proximity to pollution sources. Due to the emissions and discharge from factories and power plants, sampling locations close to industrial regions may face greater levels of air and water pollution (Garcia et al., 2015). Similar risks are associated with traffic-related pollutants, such as fine particulate matter and volatile organic compounds, for areas located close to major transportation corridors (Zhang, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Geographical heterogeneity in risk indices is also influenced by demographic factors. Exposure and vulnerability may vary depending on the population density and composition at a sampling site. Due to different socioeconomic and environmental conditions, vulnerable individuals, such as children, the elderly, and low-income communities, may be at higher risk (Clark, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This emphasises how critical it is to take social inequalities into account when evaluating and managing risks. Additionally important factors of risk variance are local laws and policies. Risk profiles among sample sites can range significantly depending on whether environmental rules are in place and if they are being followed. Sites in locations with loose restrictions might be exposed to more contaminants, whilst those in regions with strict rules might be at a lesser risk (EPA, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Last but not least, historical variables like previous land use, industrial operations, and pollution events may have left a long-lasting contamination that still has an impact on risk indices. Due to contaminants and lingering pollutants, sampling locations with a mining or industry background may present higher hazards (Huang et al., 2017).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe findings were compared with those of other investigations using a soil sample in Ba/Kg.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArea\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRadionuclides\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConcentration (BqKg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbeokuta, Ogun state\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e261.29\u0026thinsp;\u0026plusmn;\u0026thinsp;36.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(Ekhaguere et al, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226Ra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.87\u0026thinsp;\u0026plusmn;\u0026thinsp;6.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e232Th\u003c/p\u003e \u003cp\u003e238U\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.10\u0026thinsp;\u0026plusmn;\u0026thinsp;11.95\u003c/p\u003e \u003cp\u003e46.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouthwestern cities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e393.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(Ibikunle et al, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226Ra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e232Th\u003c/p\u003e \u003cp\u003e238U\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.79\u003c/p\u003e \u003cp\u003e19.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelta state\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e413.64\u0026thinsp;\u0026plusmn;\u0026thinsp;21.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(Ononugbo et al, 2019)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226Ra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.43\u0026thinsp;\u0026plusmn;\u0026thinsp;3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e232Th\u003c/p\u003e \u003cp\u003e238 U\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e561.67\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21\u003c/p\u003e \u003cp\u003e61.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIle-Ife, Osun state\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e270.14\u0026thinsp;\u0026plusmn;\u0026thinsp;61.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(Oluyide et al, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226Ra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.14\u0026thinsp;\u0026plusmn;\u0026thinsp;4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e232Th\u003c/p\u003e \u003cp\u003e238U\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.23\u0026thinsp;\u0026plusmn;\u0026thinsp;7.67\u003c/p\u003e \u003cp\u003e23.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoastal area, Akwa Ibom state\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e145\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(Akpan et al, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226Ra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e232Th\u003c/p\u003e \u003cp\u003e238U\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003cp\u003e45.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e224.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThis study\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226Ra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e185.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e232Th\u003c/p\u003e \u003cp\u003e238U\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003cp\u003e83.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThis study\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226Ra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e162.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e232Th\u003c/p\u003e \u003cp\u003e238U\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003cp\u003e84.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThis study\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e226Ra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e142.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e232Th\u003c/p\u003e \u003cp\u003e238U\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.05\u0026thinsp;\u0026plusmn;\u0026thinsp;3.68\u003c/p\u003e \u003cp\u003e70.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents a comparison between the results of this study and other research that used Ba/Kg soil sample measurements. The results of this investigation can be compared to those of previous research conducted in Nigeria (Gbadamosi et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ibikunle et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Oluyide et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ogunyele et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Aleksakhin \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Akingboye et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The activity concentrations that were found were lower than the global average. To reduce radioactive buildup, extended occupational exposure should be avoided.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: demonstrates the dataset of Ra-226 (n\u0026thinsp;=\u0026thinsp;15)'s normality, which was determined using an ogive's cumulative frequency curve. The cumulative distribution of the data is depicted visually by the normalcy curve. Ra-226 concentrations are mostly centered on the mean, and as they get closer to the upper and lower tails of the distribution, their cumulative frequency gradually rises. This pattern shows that the data follows a normal distribution, in which the majority of observations are centered on the mean and the frequency gradually declines as we move away from the mean. These results provide credence to the supposition that the radionuclide concentration is normal. Due to its possible effects on health and safety, the radionuclide Ra-226 is of interest in a number of environmental and radiological research (EPA, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e: demonstrates the U-238 dataset's (n\u0026thinsp;=\u0026thinsp;15) normality, which was determined using an ogive's cumulative frequency curve. The cumulative distribution of the data is depicted visually by the normalcy curve. Due to its skewed distribution, the majority of the U-238 concentration did not cluster around the mean. This pattern indicates that the data differs from a normal distribution, in which the majority of observations are centered on the mean. Since the points diverged from the typical systematic pattern, it raises the possibility of non-normality, necessitating more investigation or data manipulations for statistical tests that rely on normality.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e: demonstrates the Th-232 dataset's (n\u0026thinsp;=\u0026thinsp;15) normality, which was determined using an ogive's cumulative frequency curve. The cumulative distribution of the data is depicted visually by the normalcy curve. Due to its skewed distribution, the Th-238 concentration distribution did not cluster around the mean. This pattern indicates that the data differs from a normal distribution, in which the majority of observations are centered around the mean. Since the points diverged from the typical systematic pattern, it raises the possibility of non-normality, necessitating more investigation or data manipulations for statistical tests that rely on normality.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e: demonstrates the K-40 dataset's (n\u0026thinsp;=\u0026thinsp;15) normality, which was determined using an ogive's cumulative frequency curve. The cumulative distribution of the data is depicted visually by the normalcy curve. Due to its skewed distribution, the majority of the K-40 concentration did not cluster around the mean. This pattern indicates that the data differs from a normal distribution, in which the majority of observations are centred around the mean. Since the points diverged from the typical systematic pattern, it raises the possibility of non-normality, necessitating more investigation or data manipulations for statistical tests that rely on normality.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThe 226Ra, 238U, 232Th, and 40K radioactivity concentrations at five sites were computed. The inquiry was examined to see how the findings compared to IAEA guidelines and those of other studies of a similar nature. The highest value was found in sample B's 238U, whereas samples B, C, D, and E all had higher activity concentrations for 226Ra, 232Th, and 40K. Nevertheless, it was discovered that every radionuclide's value fell outside of the advised range.Despite these findings, the study recommends regular site inspections and assessments in order to guarantee the public's safety as well as the safety of the quarry personnel. The distribution of radionuclides in the environment must be understood for the objectives of environmental protection and monitoring. A rise in naturally occurring radioactive materials could result from human activities such as mining, farming, and drilling for crude oil. This could then induce a redistribution of radionuclides in the environment, which could pose health risks. An appropriate indicator of potentially significant radioactive element deposits in Nigeria, primordial radionuclide concentrations and their presence in a given area can be utilised for radioactive dating.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding information\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePartially funded by the institution \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe give our consent to publish the manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the university management for providing the enabled environment in carrying the research\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAkingboye A.S., Ogunyele A.C., Jimoh. (2021) Radioactivity, radiogenic heat production and environmental radiation risk of the basement complex rocks of Akungba-Akoko, southwestern Nigeria: insights from in situ gamma-ray spectrometry. Environ Earth Sci 80:228. https:// doi. org/ 10. 1007/ s12665- 021- 09516-7\u003c/li\u003e\n\u003cli\u003eAkpan A.E., Ebong E.D., Ekwok S.E., Eyo J.O. (2020) Assessment of radionuclide distribution and associated radiological hazards for soils and beach sediments of Akwa Ibom Coastline, southern Nigeria. Arab J Geosci 13(15):1\u0026ndash;12. https://d oi.org/1 0 .1007 / s12517- 020- 05727-7\u003c/li\u003e\n\u003cli\u003eAlakhdar, E.M., Alhuweemdi, S.O., Hweeth, A.M. (2023). \u0026ldquo;The Impact of Urban Expansion and Quarry on the Vegetation Cover around Al - Khoums City - Libya,\u0026rdquo; 12 (5) 1887\u0026ndash;1890, https://doi.org/10.21275/SR23522153623.\u003c/li\u003e\n\u003cli\u003eAleksakhin R.M (2009) radioactive contamination as a type of soil degradation. Eurasian Soil Sci 42:1386. https://d oi.org/1 0 .1134 / S1064 22930 91200 96\u003c/li\u003e\n\u003cli\u003eAvwiri.,G.O., Osimobi,J.C., AgbalagbaE.O (2012). Evaluation of Radiation Hazard Indices and Excess Lifetime Cancer Risk Due to Natural Radioactivity in soil profile of Udi and Ezeagu Local Government Areas of Enugu State, Nigeria. Comprehensive J. of Environmental and Earth Sci. 1(1): 1 \u0026ndash; 10.\u003c/li\u003e\n\u003cli\u003eBrown, A. (2016). \u0026quot;Assessing Agricultural Contamination in Rural Communities.\u0026quot; Environmental Science Journal, 45(2), 112-125.\u003c/li\u003e\n\u003cli\u003eBrown, J., \u0026amp; White, S. (2019). Tidal Influences on the Spatial Distribution of Radionuclide Concentrations in Coastal Sediments. Marine Environmental Science, 30(4), 415-430.\u003c/li\u003e\n\u003cli\u003eBussa N., Belayneh, A. (2020). Long-standing herbal medicinal traditions from the prehistoric harar town and the surroundings, eastern Ethiopia, J. Ayurvedic Herb. Med. 6 (3) 154\u0026ndash;172, https://doi.org/10.31254/jahm.2020.6311.\u003c/li\u003e\n\u003cli\u003eClark, J. (2020). \u0026quot;Vulnerability Assessment of High-Density Urban Areas.\u0026quot; Environmental Health Perspectives, 128(7), 076543. \u003c/li\u003e\n\u003cli\u003eDarby, S., Hill, D., Auvinen, A., Barros-Dios, J. M., Baysson, H., Bochicchio, F., \u0026amp; Tirmarche, M. (2005). Radon in homes and risk of lung cancer: collaborative analysis of individual data from 13 European case-control studies. BMJ, 330(7485), 223.\u003c/li\u003e\n\u003cli\u003eDavid, O., (2015). \u0026ldquo;Radiation Exposure to Natural Radioactivity in Crude Oil and Petroleum Waste from Oil Fields in Ghana; Modelling, Risk Assessment and Regulatory Control, 2015 [Online]. Available: http://ugspace.ug.edu.gh. \u003c/li\u003e\n\u003cli\u003eEC (European Commission). (2018). Radiation Protection No. 179 - Protection of the Environment from Ionizing Radiation. Retrieved from https://ec.europa.eu/energy/sites/default/files/documents/179.pdf\u003c/li\u003e\n\u003cli\u003eEdiagbonya T.F (2016) Enrichment factor of atmospheric trace metals using Zirconium Titanium,Iron and Copper as reference element.Nigeria journal of Technology 35 (4):785-795\u003c/li\u003e\n\u003cli\u003eEdiagbonya, T. F., Oyinlusi O. C Okungbowa E.G and Uche I. J (2022) Environmental and Human Health risk assessments of polycyclic aromatic hydrocarbons in particulate matter in okitipupa, Ondo State, Nigeria \u003cem\u003eEnvironmental Monitoring and Assessment \u003c/em\u003e194,(9):556 \u003c/li\u003e\n\u003cli\u003eEdiagbonya, T. F., Okungbowa E.G and Titilayo O (2020). Background study of natural radioactive in soil.\u003cem\u003e Journal of Chemical Society of Nigeria \u003c/em\u003e45 (2) :290-298\u003c/li\u003e\n\u003cli\u003eEdiagbonya, T. F., Ukpebor, E. E and Okiemien, F. E.,Akojivi ,V.O (2013)Selected trace metals analysis of Total suspended particulate matter in rural area in Edo state,Nigeria. GreenerJournal of Environmental Management and Public Health 2(2): 91-98\u003c/li\u003e\n\u003cli\u003eEdiagbonya, T.F and Gbolahan O. I (2018). Determination of radioactive isotopes and some physio-chemical parameters in five different rivers in South-South Ondo State, Nigeria. \u003cem\u003eInternational Journal of Low Radiation\u003c/em\u003e 11(1): 45- 65\u003c/li\u003e\n\u003cli\u003eEdiagbonya, T.F.Ukpebor, E.E .; Okieimen, F.E .(2015)Source identification of trace metal in total suspended particulate matter Int. J. Chem. Sci. 7: (1): 37-45\u003c/li\u003e\n\u003cli\u003eEkhaguere OA, Alatise OO, Oyeyemi KD (2019) Assessment of natural radionuclides in a fertilized farmland in Abeokuta, Nigeria: implications for environmental radioactivity evaluation and monitoring. J Phys Conf Ser 1299(1):012093. https:// doi. org/ 10. 1088/ 1742- 6596/ 1299/1/ 012093\u003c/li\u003e\n\u003cli\u003eEPA (2021). \u0026quot;Environmental Regulations and Their Impact on Risk Indices.\u0026quot; Environmental Protection Agency, Retrieved from EPA.gov.\u003c/li\u003e\n\u003cli\u003eGarcia, M., Smith, J., Johnson, A. (2020). Influence of Terrain and Elevation on Radionuclide Concentrations in a Mountainous Region. Geophysical Research Letters, 47(8), e2020GL089764.\u003c/li\u003e\n\u003cli\u003eGbadamosi MR, Banjoko OO, Abudu KA, Ogunbanjo OO, Ogunneye AL (2017) Radiometric evaluation of excessive lifetime cancer probability due to naturally occurring radionuclides in wastes dumpsites soils in Agbara, Southwest, Nigeria. J Assoc Arab Univ Basic Appl Sci 24:315\u0026ndash;324. https:// doi. org/ 10. 1016/j. jaubas. 2017. 06. 003\u003c/li\u003e\n\u003cli\u003eGoudie, A. (2018). Dust in the Wind: Long-range Transport of Dust in the Atmosphere and Its Implications for Global Public and Environmental Health. Global Health Action, 11(1), 1494902.\u003c/li\u003e\n\u003cli\u003eGoudie, A. S. (2018). Dust storms: Recent developments. Journal of Environmental Management, 212, 411-417.\u003c/li\u003e\n\u003cli\u003eHaileyesus W., Sintayehu Z., Heldal T. (2000). Building stone of central and southern Ethiopia: deposits and resource potential, NGU-BULL 436,175[Online]. Available: www.chariotinternational.com/priceListTiles.htm. \u003c/li\u003e\n\u003cli\u003eHuang, S. (2017). \u0026quot;Legacy Contamination and Health Risks in Former Mining Sites.\u0026quot; Journal of Environmental Science, 28(5), 831-843.\u003c/li\u003e\n\u003cli\u003eIAEA (International Atomic Energy Agency). (2014). Environmental and Source Monitoring for Purposes of Radiation Protection. Retrieved from https://www-pub.iaea.org/MTCD/Publications/PDF/Pub1503web-12932606.pdf\u003c/li\u003e\n\u003cli\u003eIbikunle SB, Arogunjo AM, Ajayi OS (2019) Characterization of radiation dose and soil-to-plant transfer factor of natural radionuclides in some cities from south-western Nigeria and its effect on man. Sci Afr 3:e00062. https:// doi. org/ 10. 1016/j. sciaf. 2019. e00062\u003c/li\u003e\n\u003cli\u003eInternational Atomic Energy Agency [IAEA]. (2019). Environmental Impact Assessment for Uranium Mine Development. IAEA Safety Standards Series No. SSG-16. International Atomic Energy Agency.\u003c/li\u003e\n\u003cli\u003eInternational Atomic Energy Agency [IAEA]. (2019). Radiation Protection and Safety of Radiation Sources: International Basic Safety Standards: General Safety Requirements Part 3. IAEA.\u003c/li\u003e\n\u003cli\u003eInternational Atomic Energy Agency [IAEA]. (2019). Radioecology for Ecosystems: Biological Approaches to the Assessment of Radioactivity in Real Ecosystems. IAEA Technical Reports Series No. 481. International Atomic Energy Agency.\u003c/li\u003e\n\u003cli\u003eInternational Commission on Radiological Protection [ICRP]. (2007). The 2007 Recommendations of the International Commission on Radiological Protection. ICRP Publication 103. Annals of the ICRP, 37(2-4).\u003c/li\u003e\n\u003cli\u003eJohnson, D., \u0026amp; Martinez, E. (2017). Radionuclide Contamination in the Vicinity of a Uranium Mining Site: A Case Study in Western USA. Environmental Research, 55(2), 187-201.\u003c/li\u003e\n\u003cli\u003eJohnson, R. (2017). \u0026quot;Industrial Activities and Environmental Risks in Inland Areas.\u0026quot; Journal of Environmental Management, 204, 598-607.\u003c/li\u003e\n\u003cli\u003eJones, P. (2020). \u0026quot;Climatic Factors and Waterborne Contaminants.\u0026quot; Water Research, 75(3), 124-135.\u003c/li\u003e\n\u003cli\u003eLi, T., R.M. Horton, D.A. Bader, F. Liu, Q. Sun, and P.L. Kinney (2018). \u0026quot;Topography and Air Quality in Valley Regions.\u0026quot; Atmospheric Environment, 182, 89-97.\u003c/li\u003e\n\u003cli\u003eLust, M., Realo, E. (2012). Ehitusmaterjalides leiduvatest looduslikest radionukliididest p\u0026tilde;ohjustatud elanikudoosi hinnang, Proc. Est. Acad. Sci. 61 (2) 107\u0026ndash;112, https://doi.org/10.3176/proc.2012.2.03. \u003c/li\u003e\n\u003cli\u003eLyles, B. F., Tchounwou, P. B., \u0026amp; Collette, T. W. (2013). Windblown dust deposition on the external surfaces of industrial storage tanks: an environmental radiological health risk assessment. International Journal of Environmental Research and Public Health, 10(5), 1904-1924.\u003c/li\u003e\n\u003cli\u003eOgunyele AC, Obaje SO, Akingboye AS, Adeola AO, Babalola AO, Olufunmilayo AT (2020) Petrography and geochemistry of Neoproterozoic charnockite\u0026ndash;granite association and metasedimentary rocks around Okpella, southwestern Nigeria. Arab J Geosci 13:780. https:// doi. org/ 10. 1007/ s12517- 020- 05785-x\u003c/li\u003e\n\u003cli\u003eOluyide SO, Tchokossa P, Akinyose FC, Orosun MM (2019) Assessment of radioactivity levels and transfer factor of natural radionuclides around iron and steel smelting company located in Fashina village, Ile-ife, Osun state, Nigeria. Facta Universitatis, Series: Working and Living Environmental Protection, pp 241\u0026ndash;256\u003c/li\u003e\n\u003cli\u003eOnonugbo CP, Amah OS (2019) Radioactivity concentrations and their radiological significance in sediments of some communities in Andoni, Rivers State, Nigeria. Asian J Adv Res Rep. https://d oi. org/ 10. 9734/ ajarr/ 2019/ v6i33 0151\u003c/li\u003e\n\u003cli\u003eSmith, A., Johnson, B., \u0026amp; White, C. (2018). Spatial Variation of Radionuclide Concentrations in Appalachian Soils. Environmental Science Journal, 42(3), 321-335.\u003c/li\u003e\n\u003cli\u003eSmith, D. (2018). \u0026quot;Coastal Vulnerabilities and Climate Change Risks.\u0026quot; Nature Climate Change, 7(3), 205-211.\u003c/li\u003e\n\u003cli\u003eSmith, R., \u0026amp; Green, L. (2021). Effects of Tree Species on the Spatial Distribution of Radionuclide Concentrations in Forest Soils. Journal of Environmental Ecology, 40(5), 621-635.\u003c/li\u003e\n\u003cli\u003eTurner, L. (2019). \u0026quot;Urbanization and Risk Factors in Dense Developments.\u0026quot; Urban Studies, 36(4), 498-513.\u003c/li\u003e\n\u003cli\u003eUNEP (United Nations Environment Programme). (2015). Radiological Assessment Reports Series - Assessment of Radionuclides in Food and the Environment. Retrieved from https://www.iaea.org/publications/108\u003c/li\u003e\n\u003cli\u003eUnited Nations Scientific Committee on the Effects of Atomic Radiation [UNSCEAR]. (2000). Sources and Effects of Ionizing Radiation: United Nations Scientific Committee on the Effects of Atomic Radiation: UNSCEAR 2000 Report, Vol. 1, Annex B. Sources. United Nations.\u003c/li\u003e\n\u003cli\u003eVeiga.,R.G., Sanches.,H., Anjos.,R.M., Macario.,K., Bastos .,J., Iguatemy., M.,.Aguitar.,J.G Santos.,M.A., Mosquera., B.,.Carvaiho.,C., Baptista., M.,Umisedo ,N.K(2006) Measurement of natural radioactivity in Brazilizn beach sands. Radiation Measurements. 41: 189-196. \u003c/li\u003e\n\u003cli\u003eWang, Y. (2017). \u0026quot;High-Elevation Areas and Their Unique Risk Profiles.\u0026quot; Mountain Research, 22(1), 45-58.\u003c/li\u003e\n\u003cli\u003eZhang, H. (2019). \u0026quot;Transportation-Related Pollution and Risks Near Highways.\u0026quot; Transportation Research, 42(5), 763-774.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Radioactive element, cement stores, risk assessment","lastPublishedDoi":"10.21203/rs.3.rs-3981884/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3981884/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis research investigates the numerous facts of radioactive elements, including their origins, how they impact various ecosystems, how they affect living beings as well as inanimate objects, how they can be quantified, and how they can be cleaned up. Samples were collected from Wuye Abuja, Guzape Abuja, Ore Ondo State, Ilado Ondo State, and Irele Ondo State, which are all locations in Nigeria. Each of these locations has a unique climate as well as other environmental characteristics. Ionizing radiation-emitting substances can be found in nature as well as be produced artificially. They have raised concerns because of their potential to harm nearby materials and living organisms. Obtaining a complete picture of how radioactive elements behave around the planet is the aim of this study. To understand how radioactive materials enter the environment, research examines both natural (such as uranium and thorium) and man-made (such as nuclear fallout) sources. For Samples A, B, C, D, and E, the mean concentrations of radium (Ra-226) are 185.20, 162.53, 142.28, 97.27, and 100.70, respectively. For Samples A, B, C, D, and E, the mean concentrations of uranium (U-238) are, respectively, 83.48, 84.60, 70.17, 47.57, and 48.07. Thorium (Th-232) average concentrations for Samples A, B, C, D, and E are 33.07, 26.86, 31.53, 26.40, and 27.60, respectively. While the mean potassium (K-40) concentrations for Samples A, B, C, D, and E are, respectively, 224.47, 115.70, 127.07, 62.30, and 78.33.Except for Uranium (U-238) with 84.60 in sample B, the results showed a significant difference in sample A. The highest values of Radium (Ra-226), Thorium (Th-232), and Potassium (K-40) were 185.20, 33.07, and 224.47, respectively.\u003c/p\u003e","manuscriptTitle":"Risk Assessment of Radioactive Elements in Atmospheric Dust Around Cement Stores in three States,Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-29 18:04:35","doi":"10.21203/rs.3.rs-3981884/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1f9375b1-141b-4f00-b9b1-d4b516b17216","owner":[],"postedDate":"February 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-20T09:54:20+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-29 18:04:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3981884","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3981884","identity":"rs-3981884","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}