Quantification of an alpha flux based radiological dose from seasonal exposure to ²²²Rn, ²²⁰Rn and their different EEC species

Abstract

This study summarizes the seasonal experimental data on the activity concentrations of indoor ²²²Rn (Radon), ²²⁰Rn (Thoron) and their progeny in Mansa and Muktsar districts of Punjab (India) using LR-115 solid state nuclear track detector based time integrated pin-hole cup dosimeters and deposition based progeny sensors for the assessment of radiological dose. The indoor ²²²Rn concentration was observed higher in the rainy and winter seasons while ²²⁰Rn concentration was observed higher in the winter season. However, Equilibrium Equivalent Concentrations (EECs) of ²²²Rn and ²²⁰Rn exhibited distinct seasonal behaviour unlike their parent nuclides. The average equilibrium factors for ²²²Rn (F_Rn) and ²²⁰Rn (F_Tn) were found 0.47 ± 0.1 and 0.05 ± 0.01, respectively. The annual arithmetic means of unattached fractions of ²²²Rn (${f}_{p}^{Rn}$) and ²²⁰Rn (${f}_{p}^{Tn}$) were found to be 0.09 ± 0.02 and 0.10 ± 0.02, respectively. The attachment rate (X_Rn) and attachment rate coefficients (β) of ²²²Rn progeny were also calculated to understand the proper behaviour of progeny species in the region. A new alpha flux based technique has been proposed and used for the assessment of absorbed dose rate and annual effective dose rate for radiation protection purpose.

Introduction

²²²Rn and ²²⁰Rn are naturally occurring radionuclides formed within the decay series of ²³⁸U and ²³²Th, respectively. Exhalation and emanation processes are responsible for the migration of ²²²Rn and ²²⁰Rn from its parent radionuclides (present in soil or building material) to indoor environment and thereby contributing radiological dose to mankind^1,2,3,4,5. In general, radioactive aerosols can be categorized as radioactive nuclides of cosmogenic origin (⁷Be, ²²Na and ³²P), ²²²Rn and ²²⁰Rn decay products aerosols (²¹⁸Po, ²¹⁶Po, ²¹⁴Po and ²¹²Po), aerosols associated with the high-energy accelerators (²⁴Na, ⁵²Mn and ⁷Be) and Fission product radionuclide aerosols (⁸⁹Sr, ¹³⁷Cs, ¹³¹I and ¹⁴⁰Ba). Among numerous sources of manmade and natural background radiation, a major part of the dose comes from α- emissions from decay products of ²²²Rn and ²²⁰Rn (1.26 mSv out of 2.4 mSv). These radionuclides tend to attach themselves to aerosol particles and then get deposited in the respiratory tract^6,7,8. Equilibrium factors of ²²²Rn (F_Rn) and ²²⁰Rn (F_Tn) have a vital role in dose assessment. In umpteen scientific reports and manuscripts, the F_Rn and F_Th in the indoor environment have often been reported to be 0.4 (for ²²²Rn) and 0.1 for ²²⁰Rn, however equilibrium factor (F) is varies with surrounding conditions⁶. The attached and unattached equilibrium equivalent concentrations (EECs), unattached fraction (f_p), attachment rate (X), aerosol concentration (Z) and dose conversion factors (DCFs) are other weighty parameters in lung dose assessment. The unattached fraction has higher tendency than attached fraction to absorb faster in the blood⁹. For a significant analysis, it is imperative to take into account all these parameters with appropriate seasonal behaviour of ²²²Rn, ²²⁰Rn and their progeny for the assessment of annual effective dose. The seasonal variations of these parameters are highly influenced by geology and climate of particular area. In present investigation, an effort is made to give a detailed analysis of geology, seasonal variations and climatic conditions of the studied area.

In Indian scenario, the seasonal variation data of F, f_p, X and EECs of ²²²Rn and ²²⁰Rn are very scanty and negligible emphasis has been given on these parameters in ²²²Rn/²²⁰Rn studies. The ²²⁰Rn measurements were also neglected in the past studies due to the assumption of small contribution of ²²⁰Rn to effective radiological dose. However, recent studies in some countries have unveiled that this assumption may not be entirely correct and ²²⁰Rn can still be a hazard since its progeny ²¹²Pb with a half - life of 10.6 h can accumulate to significant levels in breathing air^10,11. In this study, all parameters (X, f_p, F_Rn, F_Tn and Z) that influence the levels of ²²²Rn and ²²⁰Rn in an indoor environment have been evaluated. In the present work, an attempt has been made to study the seasonal variations of ²²²Rn, ²²⁰Rn and their EEC species along with the effects and correlation of divergent parameters in dose assessment.

In former studies, the discrepancy of dose conversion factors (DCFs) between epidemiological and dosimetric approach has not been resolved due to their different origins and sources. The dosimetric approach followed the path of Human Respiratory Tract Model (HRTM) with innumerable parameters as breathing frequency, tidal volume, aerosol parameters, unattached fraction and clearance rate. However, epidemiological approach used the data of atomic bomb survival, nuclear accident survival and uranium mine studies. The ICRP initiated with the dosimetric approach and considered the epithelium of the lung as a critical tissue for ²²²Rn exposure¹². In ICRP publication 26, committee distributed the tissue weighting factors for different tissues or organ in order to estimate the overall risk for a whole body irradiation¹³. A tissue weighting factor of 0.12 has been reserved for lungs. Instead of considering the tissue weighting factor, ICRP changed the radiation weighting factor of an alpha particle from 10 to 20^13,14. The UNSCEAR committee has also adopted the path of dosimetric approach (based on radiation weighting factor and tissue weighting factor for alpha exposure) with different indoor and outdoor occupancy factors¹⁵. In 1993, ICRP switched to the epidemiology approach of ²²²Rn exposure in mines (due to less uncertainty) and later biokinetic model (HRTM) for ²²²Rn gas has been developed so that effective doses arising from the inhalation of ²²²Rn gas can be calculated^16,17,18. In ICRP publication 115, the commission has concluded that ²²²Rn and its progeny should be treated in the same way as any other radionuclide within the system of protection and proposed that doses from ²²²Rn and its progeny should be calculated using ICRP biokinetic and HRTM (in order to calculate the doses to either organs or lungs)¹⁹. Further, ICRP revised the HRTM with major changes made to relate the clearance of deposited material by both particle transport and absorption into blood and provided new recommendation of data on systemic biokinetics, inhalation and ingestion for most of the elements^20,21. In the present manuscript, a different and direct alpha flux-based approach has been used to estimate the radiological dose from ²²²Rn exposure.

Geology, Climate and Seasons of Studied Area

Punjab is in north western India and has an area of 50, 362 square kilometers. Geologically, Punjab is formed by alluvial deposits of various rivers flowing in the region. The rocks of Aravalli – Delhi subgroup and the Malani igneous suite comprising greywacke, Ortho – quartzite carbonate sediments, calcareous shales and slates, high heat producing granites and felsites form the basement in the region^22,23,24,25. The scattered outcrops of the Aravali- Delhi Subgroup occur at Tosham (Haryana) just south of the study area i.e. Mansa and Muktsar Districts of Punjab (India) as shown in Fig. 1. The other geological parameters, area and population are given in Table 1 ^26,27.

Figure 1

Map of the investigated area of Punjab (India).

Table 1 Area, Population and average rainfall in Mansa and Muktsar districts.

The climate of Punjab is determined by the extreme hot and cold conditions. The Himalayas in North, Deserts of Rajasthan in south, three rivers and famous Indian monsoon influencing the climate and environment of Punjab. The seasons of Punjab can be categorized into summer, rainy, winter, pre -summer and post monsoon seasons. In Punjab, the summer season commences at the start of March. Punjab’s rainy season begins in last week of June monsoon. Three quarters of the total rainfall is concentrated during the three months of southwest monsoon winds and the rest comes during the winter months. There is a wide difference in the amount of rainfall experienced in east and west Punjab. The monthly average rainfall in the studied area has been shown in Table 1 and it has been seen that gap between October and November is a transitional period between monsoon and winter^26,27. The minimum temperature in studied area has been recorded in months of January – February and maximum in the month of June. The maximum temperature usually occurs in the months of May - June and during this period temperature remains greater than the 40–45 °C in studied area.

Materials and Methodology

The seasonal behaviour of ²²²Rn, ²²⁰Rn, unattached fraction and equilibrium factors of ²²²Rn and ²²⁰Rn have been studied in 42 villages of Mansa and Muktsar districts of Punjab (India). The acquired data points were processed on computer using IDW (Inverse Distance Weighted) algorithm on Arc map GIS (Geographical Information System) 10.3 software²⁸. The months of March to mid-June as summer, Second half June to mid-October as rainy and Second half October to February as winter were taken for the seasonal estimation of ²²²Rn, ²²⁰Rn and their daughter products²⁷. The ²²²Rn/²²⁰Rn based dosimeters and DRPS/DTPS were suspended in the way to 20 cm away from the adjacent walls.

Estimation of concentration of ²²²Rn and ²²⁰Rn

The ²²²Rn and ²²⁰Rn concentrations in the air were estimated by using a pin hole-cup dosimeter (Fig. 2). The gas enters through the bottom of the dosimeters in the lower chamber (²²²Rn + ²²⁰Rn chamber) and diffuses to upper chamber (²²²Rn chamber) through four pin holes (2 mm length and 1 mm diameter). The glass fiber filter (0.60 µm) paper has been used to stop the entry of progeny nuclides into the chamber as shown in Fig. 2. LR- 115 detector films (3 × 3 cm²) have been installed in both chambers of the dosimeter. The chambers are of cylindrical shape having a length of 4.1 cm and radius 3.1 cm. The dosimeters were deployed in the indoor environment for different seasons of a year. After stipulated time of exposure, LR-115 films were retrieved, chemically etched (2.5 N NaOH solution at 60 °C for 90 minutes) and track densities on LR-115 detectors were counted using the spark counter. The concentrations of ²²²Rn $\{{{\rm{C}}}_{{222}_{{\rm{Rn}}}}({\rm{Bq}}\,{{\rm{m}}}^{-3})\}$ and ²²⁰Rn ${\{C}_{{220}_{{\rm{Rn}}}}({\rm{Bq}}\,{{\rm{m}}}^{-3})\}$ gases were estimated by using Eqs (1) and (2) ²⁹.

$${C}_{{222}_{Rn}}(Bq\,{m}^{-3})=\frac{{T}_{R,1}-B}{\,t\,\times \,{k}_{R,1}}$$

(1a)

$${C}_{{222}_{Rn}}(Bq\,{m}^{-3})=\frac{{T}_{R,2}-B}{\,t\,\times \,{k}_{R,2}}$$

(1b)

$${C}_{{220}_{Rn}}(Bq\,{m}^{-3})=\frac{{T}_{T,1}-B}{\,t\,\times \,{k}_{T,1}}$$

(2a)

$${C}_{{220}_{Rn}}(Bq\,{m}^{-3})=\frac{{T}_{T,2}-B}{\,t\,\times \,{k}_{T,2}}$$

(2b)

where, k_R,1 {0.0172 Tracks cm⁻² (Bq m⁻³ d)⁻¹}, k_R,2 {0.0170 Tracks cm⁻² (Bq m⁻³ d)⁻¹}, k_T,1 {0.010 Tracks cm⁻² (Bq m⁻³ d)⁻¹} and k_T,2 {0.00052 Tracks cm⁻² (Bq m⁻³ d)⁻¹} are the calibration factors of ²²²Rn and ²²⁰Rn in the ‘²²²Rn + ²²⁰Rn’ and ‘²²²Rn’ chamber, respectively. T_R,1, T_R,2, T_T,1 and T_T,2 are the track densities (Tracks cm⁻²) in LR-115 detectors for the ‘²²²Rn + ²²⁰Rn’ and ‘²²²Rn’ chamber for ²²²Rn and ²²⁰Rn exposure respectively. B is the background track density in unexposed LR-115 detector.

Figure 2

Single entry Pin Hole Cup Dosimeter.

Estimation of Equilibrium Equivalent Concentrations of ²²²Rn and ²²⁰Rn (EERC/EETC)

The total unattached and attached EECs of ²²²Rn and ²²⁰Rn have been measured by DRPS and DTPS progeny sensors as shown in Fig. 3. Both DRPS and DTPS element was made up of LR- 115 (2.5 × 2.5 cm²) mounted with absorbers of appropriate thickness as shown in Fig. 3. The EEC has been estimated from the tracks registered on LR-115 films using sensitivity factors used in Eqs (3) and (4) ^30,31,32. The coarse (attached) fraction of progeny concentration was measured by the wire-mesh capped DTPS/DRPS (mounted with 200 mesh type wire screens) as shown in Fig. 4.

$$EETC(Bq\,{m}^{-3})=\frac{{T}_{T}-\,B}{t\times {S}_{T}}$$

(3)

$$EERC(Bq{m}^{-3})=\frac{{T}_{R}-\,B-({S}_{{T}^{\text{'}}}\times EETC(Bq{m}^{-3}))}{t\times {S}_{R}}$$

(4)

S_T’, S_T, and S_R are sensitivity factors of ²²⁰Rn progeny [0.09 Tracks cm⁻² d⁻¹{EERC (Bq m⁻³)}⁻¹] in DRPS, ²²⁰Rn progeny [0.94 Tracks cm⁻² d⁻¹{EERC (Bq m⁻³)}⁻¹] in DTPS and ²²²Rn progeny [0.09 Tracks cm⁻² d⁻¹{EERC (Bq m⁻³)}⁻¹] in DRPS, respectively. t is the exposure time period. B, T_T and T_R are the track densities estimated in unexposed background, DTPS and DRPS LR-115 films respectively. In wire-mesh capped progeny sensors, the sensitivity factors of ²²⁰Rn and ²²²Rn progeny are replaced by 0.33 Tracks cm⁻² d⁻¹{(EETC (Bq m⁻³)}⁻¹ and 0.04 Tracks cm⁻² d⁻¹ {EERC (Bq m⁻³)}^−1 32. Deposition based ²²²Rn progeny sensor and ²²⁰Rn progeny sensor have minimum detection limit of 1.0 Bq m⁻³ and 0.1 Bq m⁻³ respectively³³.

Figure 3

DRPS/ DTPS Sensor.

Figure 4

Wire mesh Capped DRPS/DTPS Sensor.

Theoretical Formalism

Attachment Rate and attachment coefficient

The activity size distribution f_a(d) of the radionuclides and the number size distribution Z(d) strongly depend on attachment process and a function of particle size. The following expression can be used to evaluate f_a(d)³⁴.

$${f}_{a}(d)=\beta (d)\frac{Z(d)}{{X}_{Rn}}$$

(5)

The function β(d) is attachment coefficient given by

$$\beta (d)=\frac{2\pi {D}_{0}d}{\frac{8{D}_{0}}{d{v}_{0}}+\,\frac{d}{2\delta }}$$

(6)

where, D₀ = 6.8 × 10⁻² cm²s⁻¹ is diffusion coefficient, v₀ = 1.72 × 10⁴ cm s⁻¹ is mean thermal velocity and δ = d/2 + l₀ with l₀ = 4.9 × 10⁻⁶ cm is mean free path of the unattached decay product cluster³⁴. Function Z(d) was normalized to unit aerosol concentration (N₀) as:

$$\int Z({d}_{{\rm{p}}}){\rm{d}}{d}_{{\rm{p}}}=1$$

(7)

Here, β(d) is the attachment coefficient of attached ²²²Rn progeny to aerosol and Z(d) represents aerosol concentration (cm⁻³). In the present investigation, the attachment rate of ²²²Rn (X_Rn) has been calculated from the measurement of unattached and attached activity concentrations of ²¹⁴Po as follows:

$${X}_{Rn}=\frac{EER{C}_{A}}{EER{C}_{U}}\times {\lambda }_{Rn}$$

(8)

The average attachment coefficient is defined as to be ratio of the attachment rate and aerosol number concentration given as

$$\beta =\frac{{X}_{Rn}}{{N}_{0}}=\frac{{\int }^{}\beta ({d}_{{\rm{p}}})\,Z({d}_{{\rm{p}}}){\rm{d}}{d}_{{\rm{p}}}}{{\int }^{}Z({d}_{{\rm{p}}}){\rm{d}}{d}_{{\rm{p}}}}$$

(9)

$${X}_{Rn}={\int }_{0}^{\infty }\,\beta (d)Z(d){\rm{d}}d$$

(10)

where, EERC_A, EERC_U and λ_Rn are attached activity concentration, unattached activity concentration and decay constant of ²¹⁴Po, respectively.

Equilibrium Factor (F _Rn, F _Tn)

Equilibrium factor for both ²²²Rn and ²²⁰Rn has been calculated using following equations:

$${F}_{Rn}=\frac{EER{C}_{A+U}}{{C}_{Rn}}$$

(11)

$${F}_{Tn}=\,\frac{EET{C}_{A+U}}{{C}_{Tn}}$$

(11a)

F_Rn and F_Tn are equilibrium factor for ²²²Rn and ²²⁰Rn, respectively. The EERC_A+U and EETC_A+U are total (attached + unattached) equilibrium equivalent concentrations of ²²²Rn and ²²⁰Rn progeny, respectively.

Results and Discussion

Seasonal variation of ²²²Rn and ²²⁰Rn

Prior to statistical analysis, the reliability of the data has been tested. The observed value of Kronbach alpha (=0.816 > 0.7) revealed that the data was statistically significant. Few outliers (cases with standardized residual greater than ±3 standard deviations) are found (Table 2) and further data have been tested for normality (Kolmogorov-Smirnov). A robust statistics has been used to study the descriptive analysis of the different radiological parameters and recorded the lower quartile (25%), median quartile (50%) and upper quartile (75%) using tukey’s Hinges and visualized by box - whisker plots as depicted in Figs 5 and 6. The mean, trimmed mean (5%), Inter-quartile range (IQR) corresponding to the dispersion, standard deviation (S.D.) and variance are also reported in Table 2. The asymmetry and tailness of the distribution is indicated by the skewness (S_k) and kurtosis (K) of the data. Relative variability has been analyzed by the absolute median deviation (AMD). All the above tests have been performed at 95% confidence interval and no missing values have been observed.

Table 2 Different statistical parameters of indoor ²²²Rn and ²²⁰Rn in Mansa and Muktsar districts (42 locations).

Figure 5

Seasonal Variation of ²²²Rn.

Figure 6

Seasonal Variation of ²²⁰Rn.

The descriptive statistics for seasonal variation of ²²²Rn concentration (C_Rn) and ²²⁰Rn concentration (C_Tn) in Mansa and Muktsar districts are given in Table 2. It is vivid that the overall mean C_Rn in three seasons was 45 Bq m⁻³ with high ²²²Rn concentration during rainy season (54 Bq m⁻³) and the lowest concentration in summer season (32 Bq m⁻³). The average C_Rn in rainy season is 1.1 fold higher than the winter season. The ratio of rainy to summer ²²²Rn level is 1.7 due to the variation of the soil moisture in different seasons. The soil moisture content is higher in the rainy season as compared to summer or winter season. The rainfall sealing the outer soil surface and elevate the negative pressure field in the room. The negative pressure field generated by the house is responsible for the transportation of soil gas from large distances. The overall mean of C_Tn was found to be 44 Bq m⁻³ across all seasons. The C_Tn was highest during winter season with mean value of 54 Bq m⁻³ and lowest concentration in summers season (34 Bq m⁻³). The seasonal variation of C_Rn is different as compared to C_Tn because of shorter diffusion length and half – life of ²²⁰Rn. As C_Tn is not affected by ventilation rate³⁵, even then C_Tn is higher in the winter season as compared to rainy and summer seasons.

The mean and median values of ²²²Rn and ²²⁰Rn are indicated that the distribution is normal and can be justified by skewness (S_K), kurtosis values (range between −2 and +2) as given in Table 2. The Q -Q plots (probability plots) have been used to confirm the statistical distribution of data around their mean. Figure 7 demonstrates normal Q-Q plots of C_Rn and C_Tn during rainy, winter and summer seasons. During rainy season, ²²²Rn has normal distribution (S_K = −0.21) while ²²⁰Rn is rightly skewed (S_K = 0.49). In winter season, both ²²²Rn (S_K = 0.42) and ²²⁰Rn (S_K = 0.61) appears to be rightly skewed, with more variation seen in ²²⁰Rn distribution. In summer season, ²²²Rn has normal spread with an outlier (S_K = −0.01), however, ²²⁰Rn is rightly skewed (S_K = 0.21). The results from these Q-Q plots are corroborating with box-plots. The Q-Q plots of C_Rn and C_Tn lie on a straight diagonal line with minimal deviations indicating normality. Tests of normality (Kolmogorov-Smirnov test) showed that C_Rn and C_Tn in three seasons follow normal distributions and have a further possibility to proceed with parametric statistics.

Figure 7

Q-Q Plots for ²²²Rn and ²²⁰Rn.

Figures 5 and 6 revealed the box-plots of C_Rn and C_Tn in three seasons (range of data, R) and it has been found that variation in C_Rn was less as compared to C_Tn as indicated by size of the boxes. ²²²Rn has less spread of data than ²²⁰Rn, with smallest box being that of summer season (IQR = 10, R = 38) and ²²⁰Rn has widest distribution during winter season (IQR = 49, R = 108). The only one outlier in the overall data has been found in summer season for ²²²Rn. The median values of C_Rn in three seasons are nearly in the middle of their boxes. For C_Rn the median values are shifted towards 3^rd and 1^st quartiles in summer and winter seasons, respectively. However, the amount of data on both sides of the boxes is largely unequal for C_Tn than C_Rn.

Seasonal Variation for EEC of ²²²Rn and ²²⁰Rn progeny

Unlike their parent nuclides, the seasonal demeanor of progenies for ²²²Rn and ²²⁰Rn has shown distinct consequences in the studied region as given in Table 2. During the rainy season, the average EERC_A+U and EETC_A+U were 22 Bq m⁻³ and 1.7 Bq m⁻³. In winter and summer seasons, the average EERC_A+U and EETC_A+U were 24 Bq m⁻³, 1.8 Bq m⁻³ and 15 Bq m⁻³, 1.6 Bq m⁻³ respectively. In winter season the average EERC_A and EETC_A (Equilibrium equivalent concentration of attached ²²⁰Rn progeny) in the studied region was 22 Bq m⁻³ and 1.6 Bq m⁻³ respectively. During summer and rainy season, the average EERC_A and EETC_A (Equilibrium equivalent concentration of attached ²²⁰Rn progeny) was 15 Bq m⁻³, 1.5 Bq m⁻³ and 20 Bq m⁻³, 1.7 Bq m⁻³ respectively.

Statistically, the 5% trimmed mean value and the mean value of EERC in rainy, winter and summer season indicated no outliers (<Q1–1.5 * IQR; >Q3 + 1.5 * IQR) in the data. The EETC also has a normal distribution in different seasons as explained by descriptive statistics (S_k, K and IQR) in Table 2. The box-whisker plots revealed more data spread in EERC as compared to EETC (Figs 8 and 9). In general, 95% attached EEC present in the indoor atmosphere and the seasonal behaviour of total EEC (EERC_A+U and EETC_A+U) relies on attached EEC. The EERC_A was greater in winter season as compared to rainy or summer season due to the poor ventilation in the winter season and faster formation process of attached progeny aerosols as shown in Figs 10 and 11. The aerosol concentration increases with the decrease of temperature in the winter season (India)³⁶. The higher aerosol concentration in winter season tends to increase the ²²²Rn and ²²⁰Rn attached progeny concentration in the winter season. However, a seasonal pattern for EETC_A+U and EETC_U has been not observed in the studied region.

Figure 8

Seasonal Variation of EEC of ²²²Rn.

Figure 9

Seasonal Variation of EEC of ²²⁰Rn.

Figure 10

Attached and unattached seasonal variation of EEC of ²²²Rn.

Figure 11

Attached and unattached seasonal variation of EEC of ²²⁰Rn.

Pearson correlation analysis has been performed to determine the interrelation between the ²²²Rn, ²²⁰Rn and their attached/unattached EEC in different seasons. A significant and positive correlation has been observed between ²²²Rn, ²²⁰Rn and different seasons respectively (Table 3). This suggests that ²²²Rn and ²²⁰Rn separately varied during three seasons with no impact on each other and have an influence on their respective concentrations. ²²²Rn concentrations during the three seasons was significantly associated with attached and unattached EEC of ²²²Rn (r = 0.37–0.72, p < 0.05). However, there was no relationship between ²²⁰Rn and EEC of ²²⁰Rn.

Table 3 Correlation coefficient of ²²²Rn and ²²⁰Rn activity concentration among different seasons.

Seasonal variation of Equilibrium factor for ²²²Rn and ²²⁰Rn

From the last few decades, UNSCEAR specified the value of 0.4 for ²²²Rn and 0.02 for ²²⁰Rn^37,38. For an accurate dose assessment, it is necessary to estimate the equilibrium factor of each dwelling due to different ventilation conditions and building material. The equilibrium factor for ²²²Rn (F_Rn) and ²²⁰Rn (F_Tn) has been calculated season- wise. The F_Rn during rainy, winter and summer seasons was 0.42 ± 0.15, 0.51 ± 0.14 and 0.49 ± 0.15 respectively. It has been observed that F_Rn was lower in the rainy season due to higher C_Rn and lower EERC_A+U in the same season. The overall arithmetic means of F_Rn and F_Tnwas 0.47 ± 0.04 and 0.05 ± 0.01, respectively. The F_Tnduring rainy, winter and summer seasons was 0.04 ± 0.03, 0.05 ± 0.03 and 0.05 ± 0.04, respectively. Due to the much smaller value of F_Tn, a proper relation has not been observed seasonally. However, F_Rn varies in different indoor environments due to variation in environmental parameters (ventilation rate, temperature etc). Further, it is worth highlighting that F_Tn varies in the same indoor environment due to the fact of ²²⁰Rn gas is not uniformly distributed in a room but ²²⁰Rn progeny having relatively high half-life is uniformly distributed³⁹. Hence, it is problematic to define season wise F_Tn due to the difference in physical properties of ²²⁰Rn and its progeny.

Seasonal variation of Unattached Fraction for ²²²Rn (${{\boldsymbol{f}}}_{{\boldsymbol{p}}}^{{\boldsymbol{R}}{\boldsymbol{n}}}$), ²²⁰Rn (${{\boldsymbol{f}}}_{{\boldsymbol{p}}}^{{\boldsymbol{T}}{\boldsymbol{n}}}$)

Most of the unattached ²²²Rn and ²²⁰Rn progeny is deposited in the respiratory tract during breathing whereas 80% of the attached progenies get exhaled without deposition⁴⁰. So, the estimation of unattached fraction is necessary for accurate dose assessment. The unattached fractions for ²²²Rn (${f}_{p}^{Rn}$) and ²²⁰Rn (${f}_{P}^{Th}$) have been calculated (using Eq. 12, 12a) season wise.

$${f}_{p}^{Rn}=\frac{EER{C}_{U}}{EER{C}_{A+U}}$$

(12)

$${f}_{P}^{Tn}=\frac{EET{C}_{U}}{EET{C}_{A+U}}$$

(12a)

It has been found that unattached fraction is slightly higher in summer season as compared to winter and rainy seasons. However total EERC_A+U and EETC_A+U were higher in the winter season, but ${f}_{p}^{Rn}$ and ${f}_{p}^{Tn}$ are lower in the winter season. In the winter season, the aerosol concentration is higher which is attributed to high values of attached progeny in the dwellings. The aerosol concentration decreases during rainfall in India³⁶. The EECs for ²²²Rn and ²²⁰Rn are lower in summer season due to good ventilation and higher exchange rate between indoor and outdoor environments. The overall arithmetic means (rainy, winter and summer seasons) of ${f}_{p}^{Rn}$ and ${f}_{p}^{Tn}$ were 0.09 ± 0.02 and 0.10 ± 0.03, respectively. A relation ${f}_{p}^{Rn}=400/Z$ has been used to calculate the aerosol concentration (Z) from the unattached fraction of ²²²Rn for the estimation of attachment coefficient^21,41. In the past studies, the aerosol concentration for a residential environment was considered to be 10,000 cm⁻³ with ${f}_{p}^{Rn}=0.07$ for an indoor environment⁴². UNSCEAR suggested a central value of 0.05 (in homes) for f_p and it can vary by a factor of 2 depending on air filtration and local source¹⁵. The observation for ${f}_{p}^{Rn}$ in the present manuscript is in agreement with literature (Table 4).

Table 4 Comparison of F_Rn, ${f}_{p}^{Rn}$ and β with previously published values.

Variation of attachment rate (X _Rn) and attachment coefficient (β) of ²²²Rn

While studying the seasonal behaviour of attached and unattached progeny, it is necessary to discuss the attachment rate and attachment coefficient. The X_Rn and β have been calculated using Eqs (5–10). The X_Rn in the studied area is 64 h⁻¹ in winter, 38 h⁻¹ in summer and 47 h⁻¹ in rainy season. Attachment coefficient is defined as the attachment rate per unit aerosol concentration. In past studies, the ratio ${X}_{Rn}/Z$ was denoted as the average attachment coefficient (β)³⁴. The attachment rate coefficient increases with AMAD (Activity median aerodynamic diameter) and larger AMAD describes aerosols with a larger diameter which induce increasing attachment rate⁴². The value of β is slightly greater in winter (0.010 cm³h⁻¹) than summer (0.009 cm³h⁻¹). The average calculated attachment rate coefficient is greater than 0.005 cm³h⁻¹ as reported by Porstendorfer⁴³ and almost equal to 1.45 × 10⁻⁹ m³h⁻¹ given by Stevanovic et al.⁴⁴. The average estimated F_Rn, X_Rn and β are concerned as per the values given by other investigators in Table 4. A positive correlation (R² = 0.4) has been observed between F_Rn and X_Rn (h⁻¹) and the best fit is shown in Fig. 12. A correlation between ${f}_{p}^{Rn}$ and F_Rn has been already studied in the past studies^45,46.

Figure 12

Relation between X_Rn (h⁻¹) and F_Rn.

Estimation of absorbed dose rate {D _ab(nGyh ⁻¹)} and Effective dose

As ICRP adopted DCF’s of 5 mSv WLM⁻¹ and 4 mSv WLM⁻¹ for homes and mines and later recommended 3.8 mSv WLM^−1 16. The variation of DCF’s for ²²²Rn, estimated from epidemiological studies and dosimetric approach varied from 3.8–9.5 mSv WLM^−1 16. The dosimetric evaluation of the absorbed dose to the bronchial epithelium per unit exposure varied from 5–25 nGy (Bq h m⁻³)⁻¹ with an average central value of 9 nGy (Bq h m⁻³)⁻¹ reported by UNCEAR¹⁵. In the present manuscript, direct energy deposition rate (alpha fluence), D_ab (nGyh⁻¹) and effective dose have been estimated from total EEC. The energy deposition rate in bronchial epithelium has been calculated using Eq. (13).

$${D}_{ab}(nGy{h}^{-1})=\frac{{\rm{\Phi }}({\rm{\alpha }}c{m}^{-2}{s}^{-1})\times {\rm{Energy}}({\rm{Mev}}\,{{\rm{\alpha }}}^{-1})\times 1.6\times {10}^{-6}({\rm{erg}}{({\rm{Mev}})}^{-1}}{{R}_{t}(cm)\times {\rho }_{t}(gram{(cm)}^{-3})\times 100(erg{(gram)}^{-1})/rad}$$

(13)

Where Φ (αcm⁻²s⁻¹) is an alpha flux, R_t = Range of α- Particle in tissue, ρ_t = Density of tissue. A 50% of this flux has been taken due geometry consideration of basal and secretory cells. For the indoor environment, an occupancy factor of 0.8 has been used to calculate the total dose¹⁶.

The absorbed dose rate for lungs (D_lung(nGy h⁻¹)), for trachea- bronchial region (D_TB(nGy h⁻¹)) and for the pulmonary region (D_P(nGy h⁻¹)) have been estimated for comparison using UNSCEAR report using Eqs (14–16) ⁴⁷.

$${D}_{lung}(nGy\,{h}^{-1})=0.04\times {222}_{Rn}(Bq{m}^{-3})$$

(14)

$${D}_{TB}(nGy\,{h}^{-1})=7\times EERC(Bq{m}^{-3})$$

(15)

$${D}_{P}(nGy\,{h}^{-1})=0.9\times EERC(Bq{m}^{-3})$$

(16)

$$F={C}_{Rn}\times \frac{{F}_{Rn}}{3700}\times \frac{time}{170}\times DCF$$

(17)

The D_ab(nGyh⁻¹) in the studied area varied from 32 nGyh⁻¹ to 121 nGyh⁻¹ with an average value of 60 nGyh⁻¹. In UNSCEAR 1988 report⁴⁷, the D_lung(nGyh⁻¹) was estimated from ²²²Rn, D_TB(nGyh⁻¹) and D_P(nGyh⁻¹) was estimated from EEC as given in Eqs (14–16) respectively. These results showed a huge gap between these two approaches and in the same report, it was further assumed that bronchial dose is better related to ²²²Rn gas concentration directly instead of from total EEC. However, in the later reports of UNSCEAR, a previous DCF of 5.7 mSv WLM⁻¹ (based on EEC) has been considered for the estimation of radiological dose. In the present manuscript, D_ab(nGyh⁻¹) is floating in between both approaches. A comparison between these doses has beengiven in Table 5. The calculated D_ab(nGyh⁻¹) shows similar variance as reported by UNSCEAR (2000) report for indoor gamma exposure rate⁶. The effective dose in the studied area varied from 1.9 mSv a⁻¹ to 7 mSv a⁻¹ with an average of 3.4 mSv a⁻¹ respectively. The calculated effective dose is in consent with past studies and these different doses have been calculated using Eq. (17) from DCFs discussed in different model asreported in Table 6. The calculated dose is greater than epidemiological approach dose and almost similar to the dosimetric dose model (DCF of 15 mSv a⁻¹)⁴⁸.

Table 5 Absorbed dose rates (D_ab(nGyh⁻¹)) in Mansa and Muktsar districts.

Table 6 Estimation of effective dose in Mansa and Muktsar districts.

Conclusion

Different statistical tools used in the present study reveal the normal distribution of ²²²Rn and ²²⁰Rn in three seasons of a year. The indoor ²²²Rn concentration is the highest in rainy and winter seasons and the lowest in summer season. However, ²²⁰Rn concentration is the highest in winter season and demonstrated the distinct seasonal behavior a part from that of ²²²Rn. A large spatial variation in the activity concentrations of indoor ²²²Rn was found in Sardoolgarh and Behniwala villages. The activity concentration of indoor ²²⁰Rn was found relatively high in Kulrian and Ahlupur villages of Mansa district. The activity concentrations of natural radionuclides (²²⁶Ra and ²³²Th) in soil of these villages are reported to be higher than corresponding world average values of ²²⁶Ra (35 Bq kg⁻¹) and ²³²Th (45 Bq kg⁻¹)². The high values of ²²⁶Ra in soil (or high indoor ²²²Rn concentration) may be attributed to presence of uranium bearing rocks, such as granitic rocks, carbonate sediments and calcareous shales in vicinity of Tosham ring (south of Mansa district)^22,23,24,25. The observed pattern of seasonal variation in different parameters is not in agreement with the past studies (due to imperfect selection of seasons and directly used bare mode LR-115 as detector)⁴⁹. In general, indoor ²²²Rn and ²²⁰Rn concentration in the studied area are lower than the recommended action level of 200–300 Bq m^−3 7. The attached EEC of ²²²Rn (EERC_A) is high in winter season as compared to other seasons due to faster formation process of attached progeny aerosols and poor ventilation in winter.

The calculated values of F_Rn (0.47 ± 0.04) and F_Tn (0.05 ± 0.01) in the studied area are slightly greater than those given by UNSCEAR and ICRP^21,37,38. The calculated value of F_Rn is slightly higher in summer season as compared to rainy and winter seasons. Due to the very smaller value of F_Tn, a proper seasonal relation has not been observed for F_Tn. The overall arithmetic means (rainy, winter and summer seasons) of unattached fraction for ²²²Rn and ²²⁰Rn (${f}_{p}^{Rn}\,$and $\,{f}_{p}^{Th}$) were 0.09 ± 0.02 and 0.10 ± 0.02, respectively. The ${f}_{p}^{Rn}$ and $\,{f}_{p}^{Th}$ are lower in winter season as compared to rainy and summer seasons due to the higher value of attached EEC present in the winter season. Positive and significant correlations have been observed among equilibrium factor of ²²²Rn (F_Rn), ${f}_{p}^{Rn}\,$and X_Rn (h⁻¹). Both ${f}_{p}^{Rn}$ and X_Rn (h⁻¹) having a converse behaviour with F_Rn. Equilibrium factor of ²²²Rn (F_Rn) is an important parameter that have correlation with an unattached fraction (${f}_{p}^{Rn}$), attachment rate (X_Rn) and aerosol concentration (Z).

The average D_ab (nGyh⁻¹) (absorbed dose) in the studied area is 60 nGyh⁻¹ that minimizes the gap to estimate the absorbed dose rate from ²²²Rn and EEC approach, as given in UNSCEAR¹⁵. The annual effective dose rate in the studied region is 3.4 mSv a⁻¹. Figure 13 shows that there is significant contribution of ²²⁰Rn to total inhalation dose which suggests that simultaneous measurements of ²²²Rn and ²²⁰Rn are important for an accurate dose assessment. The calculated value of effective dose in the present investigation is greater than that reported by UNSCEAR³⁷ and Marsh et al.⁴⁵ approach. However, it is almost equal to dose given by Nikezic et al.⁴⁸. The estimated dose is greater than average worldwide dose of 1.26 mSv a⁻¹ for ²²²Rn^46,50. The present approach followed dosimetric approach rather than epidemiological approach. The dose estimated in the present study is 3.8 fold higher than epidemiological approach. This discrepancy may be due to the use of revised alpha radiation weighting factor in the previous report of ICRP and mostly dosimetric models except ICRP 24 were developed after 1980^13,14. The other aspect of this discrepancy may be unregistered cancer cases under epidemiological approach. This discrepancy can be solved to deploy long-term measurements of both approaches in active mines rather to assumed previous epidemiological based unregistered data in official reports.

Figure 13

Annual effective doses due to ²²²Rn and ²²⁰Rn.