Kotli Sattian is a municipality located in the Rawalpindi District of Punjab, Pakistan. It is a subdivision of the Rawalpindi district. From a geographical perspective, it is surrounded on the east by the Jhelum River, on the southwest by the Soan River, and on the northwest by Murree [24]. In addition, Kotli Sattian is adjacent to Kahuta Tehsil to the south. Kotli Sattian is connected to the Kashmir Territory in the east via a bridge over the river Jhelum, as well as to the southwest. Moreover, it is located next to Islamabad. The maximum elevation is at Pofandi peak, located east of the Patriata spur, with an altitude above 7035 feet above sea level. The nadir is situated along the Jhelum River at Patton, at an elevation of 1587 feet relative to sea level. In seismically active regions, the geological setting plays a particularly amplifying role: fault zones serve as preferential pathways for radon migration due to their increased porosity and permeability [25], allowing radon to travel from deeper crustal sources toward the surface far more rapidly than diffusion through intact rock would permit [8]. Two main mechanisms of radon discharge from soil gas in active fault zones have been identified: diffusion and dispersion from permeable soil, and upwelling directly from fault planes, with higher concentrations and flux consistently observed at fault locations [26]. In the sub-Himalayan fold-and-thrust belt where Kotli Sattian is situated, the intersection of uranium-bearing metamorphic basement rocks and active seismic faults therefore represents a geologically favorable setting for elevated soil-gas radon, providing the fundamental geogenic context for the indoor concentrations measured in this study. Radon measurements were conducted in five villages, specifically Kamra, Bhattian, Paija, Thoon, and Chaffar. The study area map is given in Figure 1Figure 1 and the details of the houses are given in Table 1.

Figure 1. Study area map.

A total of twenty-five dwellings were chosen, and 5 dosimeters were carefully positioned in different spots within the houses across the five villages in the Kotli Sattian region. Five houses were chosen in every village as locations for dosimeter installation. Copper Wire was used to suspend the dosimeters at a height of 5 - 6 feet in each house. The houses in Bhattian, Paija, and Thoon were built using bricks, cement blocks, and concrete. The newly constructed dwellings for our inquiry were designated as these buildings. The houses in Chaffar and Kamra were categorized as old homes, built with mud and wood.

Table 1. Location details of houses selected for this study, Radon concentration and Annual Effective dose.

Radon dosimeters utilized for extended surveys must exhibit qualities such as small dimensions, cost-effectiveness, and ease of use. The sensitivity of a dosimeter depends on the choice of material, as well as the size and placement of the detector within the dosimeter. The dosimeter consists of a cylindrical plastic case with a radius of 3 cm and a height of 7.5 cm. These dosimeters have one side that is exposed, while the opposite side is sealed with a cap. The detector is affixed to the lid utilizing double-sided tape. The Radon dosimeters (Figure 2Figure 2) were obtained and calibrated in the Radiation Physics Laboratory (RPL) at COMSATS University Islamabad.

Figure 2. Closed and open view of dosimeter that consists of a cylindrical plastic bottle with detector fixed below the lid of the dosimeter.

The CR-39 is attached to the dosimeter cap using double-sided tape, assuring its strong fixation. The dosimeter was enclosed in a plastic bag that efficiently resists moisture and blocks the entry of particles of dust from the surrounding air. The dosimeter was installed for a period of sixty days. The CR-39 nuclear track detector was used for radon measurements because of its exceptional sensitivity, resilience to various environmental factors, and superior visual clarity. The selection was made to use CR-39 sheets with an average thickness of 0.9mm due to their robustness and ability to avoid detection of any markings on the rear surface by the image analyzer. The CR-39 sheets were accurately partitioned into rectangular segments measuring 4 cm in length and 2.5 cm in width using a laser cutter. A unique serial number was engraved on each detector to aid in identification. View and specifications of CR-39 detector are shown in Figure 3. Figure 3(a) shows a view of CR-39 detector used in our study while Figure 3(b) shows a schematic view of the dosimeter. Radon concentration was calculated by applying the conversion factor of dosimeter as 0.012 tracks∙cm⁻²∙h⁻¹ is equal to 1 Bq∙m⁻³.

Figure 3. (a) A View of CR-39 detector; (b) A View of dosimeter for this study.

Dosimeters were set at head heights in five houses of each community in Kotli Sattian. After a duration of 60 days, the dosimeters were retrieved and carefully transported back to the laboratory without any contamination. The detectors were removed from the dosimeter to receive etching. The CR-39 detectors underwent etching in a 6-molar solution (6M) of NaOH at a temperature of 70˚C for a duration of three hours (Figure 4Figure 4). Following the etching process, the CR-39 samples were removed from the solution, rinsed with pure water, and dried flat using tissue wipes to eliminate the etchant and etch products from the detector’s surface.

The average number of tracks accumulated during a 60-day period was determined by counting the average number of tracks in a CR-39 detector under x10 magnification, using 20 - 25 fields of view. The track density was calculated by multiplying the calibration of the microscope (×10) by the average number of tracks observed in each field of view. The track density per hour was determined by translating the exposure time into hours. The radon concentration was determined by utilizing the given equation.

The conversion factor of dosimeter used is 0.012 tracks∙cm⁻²∙h⁻¹.

Figure 4. (a) Installed dosimeter in the house; (b) Etching of the Cr-39 detector for track counting.

The mean radon concentrations across the five villages, alongside average track densities and annual effective doses, are summarised in Table 2, and the spatial distribution of radon activity is illustrated through Inverse Distance Weighting (IDW) interpolation in Figure 5Figure 5. At the village level, the highest mean radon concentration was recorded in Chaffar (51.85 ± 40.53 Bq∙m⁻³), followed by Thoon (50.53 ± 48.10 Bq∙m⁻³), Paija (45.50 ± 25.91 Bq∙m⁻³), Kamra (37.78 ± 26.38 Bq∙m⁻³), and the lowest in Bhattian (33.10 ± 11.29 Bq∙m⁻³). The large standard deviations observed particularly in Chaffar (CV = 78.2%) and Thoon (CV = 95.2%) indicate substantial intra-village variability in radon concentrations. Indoor radon concentration can vary highly from place to place, and even from room to room within the same dwelling, as it is influenced by geological, building-related, meteorological, and socio-economic factors acting simultaneously [32][33]. Among these contributors, geological factors are the most variable, while ventilation variation among houses is generally responsible for radon variations comparable to those introduced by building materials, and is more significant at lower ventilation rates. In Chaffar specifically, the wide range from 13.77 Bq∙m⁻³ (H23) to 99.61 Bq∙m⁻³ (H25) within the same village reflects the local heterogeneity of soil radon potential, which even within a relatively homogeneous area can exert a strong influence on indoor concentrations [34]. In contrast, Bhattian exhibited the lowest inter-house variability (CV = 34.1%), with values ranging narrowly from 23.61 to 52.34 Bq∙m⁻³, suggesting a more homogeneous sub-surface radon source in that locality.

The elevated concentrations in Chaffar and Thoon, despite belonging to different construction categories (old mud/wood and new concrete respectively), point to geology as the dominant driver over building material type in these cases. The physical and chemical properties of soil, including porosity and permeability, significantly affect the migration and release of radon from underground sources into the indoor environment [34]. The presence of faults allows for the migration of radon gas from deeper geological origins, favouring its entry into homes; high radon emissions are more likely to be found in permeable soils such as sandy or gravelly soils, whereas fine soils act as a natural barrier to the upward movement of gas [34]. Kotli Sattian lies in a tectonically active zone of the sub-Himalayan fold-and-thrust belt, where permeable fractured geology facilitates vertical radon transport irrespective of surface construction type. Geological characteristics and meteorological parameters present synergistic effects on indoor radon levels, and indoor radon concentrations are reportedly more sensitive to meteorological parameters than to building characteristics alone [35][36]. A review of 31 indoor radon studies from different countries revealed a weighted mean indoor radon concentration of 178 Bq∙m⁻³ with a standard deviation of 193 Bq∙m⁻³, underscoring the extent to which local geological and meteorological conditions drive variability between regions [36].

Table 2. Averages track densities, mean radon concentrations and annual effective doses in five villages of Kotli Sattian, Pakistan.

In radiation protection, the annual effective dose is expressed in units of mSv∙y⁻¹ and is utilized to evaluate the quantity of radiation exposure and radionuclide intake for the public and workers. The following equation is employed to estimate the average annual effective dose of radon to the Kotli Sattian population that is caused by indoor radon:

The variables in the equation are as follows: H is the annual effective dose, C represents the indoor radon concentration in Bq∙m⁻³, F is the adjustment factor with a value of 0.4 for indoor measurement, O is the occupancy factor with a value of 0.8 for indoor measurement, T represents the number of hours in a year 8784 h∙y⁻¹, and D is the dose conversion factor with a value of 0.9 nSv∙Bq⁻¹∙m⁻³∙h⁻¹ (0.9) [22][37].

Table 3 presents the annual effective dose for each individual residence. At the household level, the maximum annual effective dosage was observed in H10, Thoon (0.343 mSv∙y⁻¹), associated with the peak individual radon concentration of 135.76 Bq∙m⁻³, whereas the minimum was noted in H23, Chaffar (0.035 mSv∙y⁻¹), linked to the lowest concentration of 13.77 Bq∙m⁻³. The computed mean annual effective doses at the village level are shown in Table 2. The highest mean annual effective dosage was reported in Chaffar (0.13 mSv∙y⁻¹) and Thoon (0.13 mSv∙y⁻¹), followed by Paija (0.11 mSv∙y⁻¹) and Kamra (0.10 mSv∙y⁻¹), with the lowest observed in Bhattian (0.08 mSv∙y⁻¹). The mean yearly effective dosage for all 25 residences in Kotli Sattian was determined to be 0.11 mSv∙y⁻¹.

All annual effective dose levels documented in this study are below the recommended public exposure action level of 1 mSv∙y⁻¹, as specified by ICRP, US-EPA, and WHO, demonstrating that radon-related radiation exposure in Kotli Sattian remains within internationally recognized limits. This finding aligns with similar research conducted in Pakistan. A research in the Murree region, adjacent to the current study area, showed a mean annual effective dosage of 0.733 mSv∙y⁻¹ [38], exceeding our values, possibly due to the varying geological sub-zones within the larger Murree formation. Research in the Punjab Province of Pakistan indicated mean annual effective doses of 1.39 ± 0.78 mSv∙y⁻¹ [39], whereas significantly elevated values of 3.5 - 5.1 mSv∙y⁻¹ were observed in the Hazara Division [40], highlighting the impact of uranium-rich geology and diminished winter ventilation in those areas. In the sub-Himalayan area of Kotli, Azad Jammu and Kashmir, which possesses geological characteristics directly comparable to Kotli Sattian, the mean annual effective dosage was 1.8 mSv∙y⁻¹, due to the uranium-bearing geological formations present in the region [32]. The relatively low doses in Kotli Sattian indicate that, despite the seismically active environment, the local geology does not yield uranium-rich rocks at a concentration adequate to generate harmful indoor radon levels under present conditions.

It is important to acknowledge that the dosage numbers presented are derived from a singular 60-day assessment window and do not account for seasonal fluctuations. Indoor radon levels are generally heightened during winter months owing to less ventilation and greater pressure differentials between indoor air and soil gas [32]. Future research should use year-round data to comprehensively characterize the annual dosage load on the population of Kotli Sattian.

The Excess Lifetime Cancer Risk (ELCR) measures the increased likelihood of getting terminal cancer during an individual’s lifetime as a result of prolonged exposure to indoor radon. It is computed as:

where E is the annual effective dose (mSv∙y⁻¹); DL is the life expectancy of Pakistan = 67.1 years [41]; and RF is the ICRP fatal cancer risk coefficient = 5 × 10⁻⁵ mSv⁻¹ (i.e. 0.05 Sv⁻¹) [42]. The calculated ELCR values for all five villages of Kotli Sattian are presented in Table 3. The overall mean ELCR across the study area was 0.3703 × 10⁻³. At the village level, the highest ELCR was recorded in Chaffar (0.4388 × 10⁻³), followed by Thoon (0.4277 × 10⁻³), Paija (0.3851 × 10⁻³), Kamra (0.3198 × 10⁻³), and the lowest in Bhattian (0.2801 × 10⁻³). The ICRP Publication 103 [42] defines an acceptable ELCR range of 0.29 × 10⁻³to 1.45 × 10⁻³ for the general public from a single source. Four of the five villages (Kamra, Thoon, Paija, and Chaffar) fall within this range. Bhattian recorded an ELCR of 0.2801 × 10⁻³, marginally below the lower bound, consistent with it having the lowest mean radon concentration in the study (33.10 Bq∙m⁻³). The overall mean ELCR of 0.3703 × 10⁻³ is well within the acceptable range, confirming that the population of Kotli Sattian does not face an elevated lifetime cancer risk from indoor radon under current conditions.

Table 3.Village-level radon concentration, annual effective dose, Excess Lifetime Cancer Risk (ELCR), and Lung Cancer Risk (LCR).

Radon exposure carries a specific, well-characterised risk for lung cancer the primary radiological health outcome of concern. The WHO estimates that radon accounts for 3% - 14% of all lung cancers nationally, depending on mean indoor radon concentration and smoking prevalence [18]. The radon-specific lung cancer risk (LCR) is calculated as:

where C is the mean indoor radon concentration (Bq∙m⁻³), and 1.16 × 10⁻⁴ is the WHO lifetime lung cancer risk coefficient per unit radon concentration [18][43].

The LCR values for all five villages are presented alongside the ELCR values in Table 3. The overall mean LCR was 5.075 × 10⁻³ (approximately 507 cases per 100,000 persons). The highest village-level LCR was recorded in Chaffar (6.014 × 10⁻³) and the lowest in Bhattian (3.839 × 10⁻³). All village LCR values fall within the US-EPA acceptable carcinogenic risk range of 1 × 10⁻⁶ to 1 × 10⁻⁴. ICRP Publication 115 [44] reports that each 100 Bq∙m⁻³ increase in radon concentration raises lung cancer risk by 16% a relationship that amplifies considerably in smokers. Given that adult male smoking prevalence in Pakistan is around 45.5% [45], targeted public health messaging combining radon awareness with smoking cessation would be the most effective risk-reduction strategy to mitigate lung cancer cases for this population. Radon gas measurements also help in a better prediction of seismic events and they should be monitored continually in the seismically active regions of Pakistan [25].

In this section, Table 4 compares the study’s average indoor radon concentration (43.75 ± 31.04 Bq∙m⁻³) to data from different countries. Numerous countries show average indoor radon levels lower than those measured in Kotli Sattian. In Haryana, India, 91 dwellings had an average of 22 Bq∙m⁻³, with values ranging from 9 to 94 Bq∙m⁻³. Libya had an average of 29 Bq∙m⁻³ (range from 5 to 54 Bq∙m⁻³), while Saudi Arabia had an average of 31 Bq∙m⁻³. The data from arid and semi-arid geological environments with sandy and limestone substrates show slightly lower radon emanation compared to the folded metamorphic and sedimentary phases beneath Kotli Sattian. The average indoor radon concentration in the United States is around 50 Bq∙m⁻³, which is consistent with the findings of this study. Numerous investigations show mean radon concentrations that are consistent with the current findings. A preliminary survey of 800 houses in Beijing, China, revealed a mean of 42 Bq∙m⁻³ with a range of 12 - 119 Bq∙m⁻³, which closely matched our results in both mean and range. Western Iran (Aleshtar) had an average of 43 Bq∙m⁻³, while Kilis, Osmaniye, and Antakya, Türkiye, reported averages ranging from 40 to 51 Bq∙m⁻³. Several analogous mountainous and seismically active places have elevated indoor radon levels. The Kathmandu Valley in Nepal, a comparable sub-Himalayan seismic zone, had an average of 67 Bq m^-3 across 50 households, with values reaching 135 Bq∙m⁻³, while earthquake-affected Gorkha had averages as high as 104 Bq∙m⁻³. Iraq had an average of 63 Bq∙m⁻³. Bingöl Province, Türkiye, located on the Anatolian fault system, recorded a mean of 103 Bq∙m⁻³, more than doubling our values, which is consistent with the region’s high seismicity and uranium-rich basement geology. Indonesia (Bangka Island) recorded a mean of 56 Bq∙m⁻³, whereas Bangladesh (Dhaka) reported 63 Bq∙m⁻³. The higher values in Nepal and eastern Türkiye when compared to Kotli Sattian are instructive; both places are sub-Himalayan or Alpide belt fault zones with similar tectonic properties. This suggests that local geological makeup, rather than tectonic context, is the primary factor affecting Kotli Sattian’s unusually low concentrations. Kotli Sattian falls within the global average for indoor radon levels in residential areas, with a mean concentration of 43.75 Bq∙m⁻³ and a range of 13.77 - 135.76 Bq∙m⁻³. This international comparison confirms that radon levels in Kotli Sattian provide no significant public health concern when compared to global standards; however, continuing monitoring is recommended due to the area’s seismic activity and aged housing structures.

Table 4.Comparison of indoor radon concentration in Kotli Sattian with worldwide studies.