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Article

Assessing the Radon Exposure Variability and Lifetime Health Effects across Indoor Microenvironments and Sub-Populations

1
Department of Nano, Chemical and Biological Engineering, Seokyeong University, Seoul 02713, Republic of Korea
2
Graduate School of Environmental & Chemical Engineering, Seokyeong University, Seoul 02713, Republic of Korea
*
Author to whom correspondence should be addressed.
Atmosphere 2024, 15(8), 927; https://doi.org/10.3390/atmos15080927 (registering DOI)
Submission received: 12 July 2024 / Revised: 28 July 2024 / Accepted: 31 July 2024 / Published: 3 August 2024
(This article belongs to the Section Air Quality and Human Health)

Abstract

:
To assess the health impacts of radon exposure over a lifetime, in the present study, the annual effective dose (AED) and cumulative excess lifetime cancer risk (ELCR-C) were evaluated by considering various indoor microenvironmental exposures based on age-specific time–activity patterns using Monte Carlo simulations. Significant regional variations in indoor radon concentrations across the Republic of Korea were observed, with the highest levels found in schools and single detached houses. Based on the standard annual total of 8760 h spent indoors and outdoors, the AED varied by age group and dwelling type, with the ELCR-C for single detached houses being approximately 1.36 times higher than that for apartments on average. The present study highlights the importance of comprehensive health risk assessments that consider differences across indoor environments and age groups, indicating that limited evaluations of specific sites or areas may distort actual exposure levels.

1. Introduction

Radon, a naturally occurring radioactive gas, is a significant contributor to the development of lung cancer, as evidenced by extensive research [1,2]. The World Health Organization (WHO) Handbook recommends maintaining an indoor environmental radon concentration below 100 Bq/m3 [3], and the International Agency for Research on Cancer (IARC), an organization under the WHO, classified radon as a carcinogen (Group 1) in 1988 [4]. Empirical studies reveal a direct correlation between radon exposure and increased lung cancer risk, suggesting the relationship is dose-dependent [5,6]. Interestingly, Darby et al. [6] found this correlation to be linear, persisting even at low radon levels.
The scope of radon research has evolved from focusing primarily on miners, due to their high exposure levels in underground mines, to encompassing broader demographics and habitats as urban growth has continued. This expansion reflects the need to understand varying risk profiles based on age, occupation, and residential environments, prompting more research in urban environments to assess public health impacts [7,8,9,10,11]. Investigations into radon distribution in child-centric facilities such as daycare centers, kindergartens, and schools have been conducted globally, recognizing that children’s higher metabolic rates make them more susceptible to pollutant harm [12,13,14,15,16,17,18]. Radon exposure is an important factor in the development of childhood leukemia, and increased radon exposure in children under 15 years of age is associated with an increased incidence of lung cancer [19,20,21,22].
Similarly, radon presence has been studied in university environments, including classrooms and labs, and extended to the exteriors of buildings to understand the potential exposure of young adults [23,24,25,26,27]. Hospital-based studies have considered the impact of architectural elements like windows on indoor radon levels, underscoring the role of building design in exposure [28]. The historical significance of radon exposure in subterranean workspaces has also been a focus, indicating occupational exposure trends [29,30,31,32,33]. In homes, where most time is spent, the research has consistently shown the need to understand radon behavior to ensure safe living conditions [34,35,36].
The broadening of radon research to encompass a range of indoor microenvironments and specific sub-populations has provided substantial insights into radon’s prevalence and its potential health effects on different age groups and occupational contexts [7,8,9,10]. However, the emphasis of existing research on specific or confined environments (localized areas) might not provide an accurate representation of the risk across the general population. Individuals encounter various environments throughout their lives, and while certain local environments may be more prevalent in certain age groups, cumulative exposure across diverse environments is the norm. This indicates there may be discrepancies between studies focused on specific environments and the complex reality of radon exposure.
To quantify the risks associated with radon exposure, excess lifetime cancer risk (ELCR) is often used [37]. ELCR provides a probabilistic estimate of the additional cancer risk over a lifetime attributable to radon exposure. A key component of the ELCR calculation is the annual effective dose (AED), which varies widely depending on regional and local environmental conditions, as well as age-specific time–activity patterns. Calculating the AED rather than relying solely on radon concentration allows for a more comprehensive assessment of actual exposure and health risks by accounting for various exposure pathways and individual behavior patterns, thereby introducing some uncertainty into the representative values.
However, most assessments rely on average values from specific local environments. Consequently, health impact assessments of radon exposure that focus on specific environments may lead to over- or under-estimations when compared to the complex spectrum of actual exposure, making the extent of this uncertainty challenging to ascertain. Within our current knowledge, comprehensive lifecycle studies on radon exposure and health impacts are scarce.
The main objective of the present work, therefore, was (i) to assess the variability in radon exposure in various indoor microenvironments and (ii) to evaluate the associated lifetime health risks across different sub-populations, taking into account the uncertainty caused by the variability.

2. Materials and Methods

2.1. Assessment of Radon Levels across Indoor Microenvironments

In the present study, the population was divided into a total of 8 age-based sub-groups according to daily life activities in the Republic of Korea: infancy, early childhood, school age (7–13 years), adolescence (14–18 years), youth, young adulthood, middle adulthood, and senior years (Table 1 and Figure S1 in the Supplementary Materials (SM)). The assessment spanned multiple microenvironments, notably residential areas including single detached and apartment houses, as well as daycare centers, schools, offices, transportation facilities, and other public facilities (indoor environments away from home) frequently accessed in daily life (Table 1). The distribution and representative values of radon concentration were calculated using measurement data from previous studies in the Republic of Korea: for houses [38], public facilities, daycare centers, mobile environments [39], and schools and offices [40] using nationwide government data; and for outdoor [41] and university environments [42] using data from prior research.

2.2. Calculating Annual Effective Dose (AED) and the Excess Lifetime Cancer Risk—Cumulative (ELCR-C)

In the present study, the AED estimation is based on the equation presented in UNSCEAR (2000) [43]. However, it has been modified to reflect the differences in exposure to various microenvironments according to age-specific time–activity patterns in the South Korean environment, as presented in Equation (1).
A E D m S v / y = i k { C R N ( i ) × F e q ( i ) × T ( i ) × D }  
where the following definitions apply:
  • i indexes these microenvironments.
  • CRN(i) (Bq/m3) is the radon concentration in the i-th microenvironment.
  • Feq(i) (dimensionless) is the equilibrium factor for the i-th microenvironment, reflecting the ratio between radon and radon daughter nuclides.
  • T(i) (h/y) is the time spent in the i-th microenvironment, incorporating the time–activity patterns of individuals within that environment.
  • D (9 nSv/h per Bq · h/m3) is the radon dose conversion coefficient [43,44].
For all microenvironments, CRN and Feq [45] were assessed using the Anderson–Darling test to determine appropriate distributions and representative values (Tables S1 and S2 in SM). The exposure time, T, was calculated based on the duration of stay in each local environment by age group, using the Korean Exposure Factors Handbook (Figure S1 in SM) [46,47].
The excess lifetime cancer risk from radon exposure was assessed using the cumulative approach as follows:
E L C R C = j = 0 r = 75 { A E D j × R F }  
where ELCR − C quantifies the additional risk of cancer over a lifetime due to exposure to radon, j means 0 to 75 years old and AED(j) is the age-specific annual effective dose of radon. In the present study, the RF (a nominal risk coefficient) was assumed to be same across all age groups at 5.5 × 10−2 per sievert (Sv−1) [48], as optimized values for each age group could not be found. The sum totals the risk across ages from birth to 75 years, reflecting the lifetime exposure to radon. To incorporate the uncertainties of the parameters, a Monte Carlo simulation approach was employed, executing 2,000,000 iterations to derive the final values.

3. Results and Discussion

3.1. Spatial and Microenvironment Variation in the Concentration

The present study focused on assessing radon exposure within various indoor microenvironments across the 17 cities and provinces of the Republic of Korea, emphasizing the variation between regions rather than specific locale evaluations (Figure 1). A significant contrast was observed in residential radon levels, with the highest regional average recorded at 131.87 Bq/m3, more than double the lowest average of 55.41 Bq/m3. Daycare centers reported disparities as well, with the highest radon concentration averaging 50.12 Bq/m3—almost twice the lowest average of 26.45 Bq/m3. Schools exhibited even more stark variations, with the highest average radon concentration at 160.62 Bq/m3, substantially exceeding the lowest average of 33.56 Bq/m3, resulting in a nearly five-fold difference. The trend continued in office environments, with the highest average concentration noted at 68.91 Bq/m3, markedly surpassing the lowest average of 27.71 Bq/m3 by more than double. For indoor environments away from home, the highest average radon concentration recorded was 35.36 Bq/m3, significantly above the lowest average of 20.45 Bq/m3, indicating substantial variability. Among the 136 pairs formed from 17 regions, statistically significant differences (p-value < 0.05) were observed across several facility types: 80.88% for single detached houses, 73.53% for apartment houses, 83.09% for daycare centers, 67.65% for schools, 63.24% for offices, and 77.94% for indoor environments away from home. These results suggest that significant variances are prevalent in most of the regional pairings. The variations in indoor radon concentrations across different regions are estimated to stem from the diverse geological and climatic features. Radon is a naturally occurring radioactive gas, about 80% of which is emitted from soil and about 10% from the atmosphere [1,2]. Radon in soil is known to be higher in granite and gneiss [49,50,51], and differences in temperature, wind speed, and humidity affect the degree of diffusion from the soil into indoor environments.
The spatial variation in radon levels, indicated by the coefficient of variation (CV), ranges from moderate to high across various environments. Specifically, schools exhibit the most variability (CV of 1.71), followed by single detached houses (CV of 1.19) and apartment houses (CV of 0.91). Offices show moderate variation (CV of 0.79), while indoor public spaces and daycare centers have the least variability, with CVs of 0.72 and 0.69, respectively. This suggests that radon concentrations are more uneven in educational and residential areas compared to other environments. It is interesting to note that environments with relatively higher levels of contamination also tend to have larger CVs. Furthermore, it is rational to think that schools and homes, which show such high levels and where people spend a significant amount of time, would have greater uncertainties in lifetime exposure assessments.
At the national scale, representative contamination levels for each microenvironment were expressed as the arithmetic means with error bars indicating the 5th and 95th percentile values, as shown in Figure 2. The arithmetic mean (geometric mean) by microenvironment was 95.71 (65.65) Bq/m3 for detached houses, 64.03 (51.31) Bq/m3 for apartments, 36.82 (30.25) Bq/m3 for daycare centers, 97.08 (64.93) Bq/m3 for schools, 41.63 (36.23) Bq/m3 for universities, 50.76 (42.38) Bq/m3 for offices, 22.94 (18.70) Bq/m3 for transportation facilities, and 23.30 Bq/m3 for outdoors [41]. These results indicate that radon concentrations were notably elevated in single detached houses and schools. Although these two environments did not significantly differ from each other in radon levels, significant disparities (p-value < 0.05) were found when comparing them with other studied microenvironments. In consideration of indoor environments away from home, the present study also differentiated radon exposure levels by age group, given the diversity of facility use across demographics (Table 1). The results showed arithmetic mean concentrations (geometric mean) of 27.59 (23.23) Bq/m3 for infants (<1 year), 29.15 (24.25) Bq/m3 for young children (1–6 years), 28.79 (23.96) Bq/m3 for youth (7–24 years), 28.76 (23.92) Bq/m3 for adults (25–64 years), and 29.44 (24.36) Bq/m3 for seniors (≥65 years). The young children and the senior groups exhibited slightly higher levels than other age groups, statistically significant at a p-value < 0.05.

3.2. Lifetime Radon Exposure and Health Effects

3.2.1. Annual Effective Dose (AED)

The AEDs calculated assuming 7000 h of exposure per year [38] in the scenario local environment were as follows: single detached houses, 2.53 mSv/y; apartment houses, 1.69 mSv/y; daycare centers, 1.00 mSv/y; schools, 2.63 mSv/y; university, 1.13 mSv/y; offices, 1.38 mSv/y; transportation facilities, 0.62 mSv/y; other indoor multi-use facilities, 0.79 mSv/y; and outdoors, 0.63 mSv/y. The commonly used exposure scenario of 7000 h per year in a single indoor environment significantly differs from the actual exposure that includes various indoor environments and outdoor activities over a full day (8760 h annually). This disparity particularly arises from a simplified model that only accounts for partial daily exposure in one type of indoor environment, while neglecting the diversity of age-related lifestyle activities (Figure S1 in SM). Consequently, such a scenario can lead to the underestimation and/or overestimation of true exposure levels.
For each population group, accounting 8760 h per year, the results were compared according to the type of housing. Figure 3 shows the AED for each population group as a stacked bar to show the differences between the population groups. The arithmetic mean ± standard deviation (geometric mean) of the AED for each population group in the single detached houses were associated with 2.77 ± 3.24 (1.87) mSv/y in the <1 age group, 2.57 ± 2.85 (1.83) mSv/y in the 1–6 age group, 2.79 ± 2.71 (2.10) mSv/y in the 7–13 age group, 2.77 ± 2.59 (2.11) mSv/y in the 14–18 age group, 2.34 ± 2.33 (1.77) mSv/y in the 19–24 age group, 2.41 ± 2.47 (1.80) mSv/y in the 25–39 age group, 2.40 ± 2.48 (1.79) mSv/y in the 40–64 age group, and 2.64 ± 3.00 (1.84) mSv/y in the 65+ age group. For the population in apartment houses, the AED was 1.91 ± 1.68 (1.47) mSv/y for the <1 age group, 1.83 ± 1.49 (1.46) mSv/y for the 1–6 age group, 2.13 ± 1.61 (1.73) mSv/y in the 7–13 age group, 2.18 ± 1.73 (1.77) mSv/y in the 14–18 age group, 1.74 ± 1.24 (1.46) mSv/y in the 19–24 age group, 1.78 ± 1.30 (1.47) mSv/y in the 25–39 age group, 1.76 ± 1.31 (1.45) mSv/y in the 40–64 age group, and 1.85 ± 1.56 (1.46) mSv/y in the 65+ age group. Consistent with observations from actual measurements indicating higher radon levels in single detached homes compared to apartments, the calculated AED was correspondingly greater for single detached residences. Excluding the pairs of the 1–6 age group and the 65+ age group and the pairs of the 19–24 age group and the 40–64 age group living in apartment housing, all other age groups across both housing types were found to have statistically significant differences (p-value < 0.05).
While reference levels for indoor radon vary by country, to protect public health, both Republic of Korea and the U.S. Environmental Protection Agency have set the level at 148 Bq/m3. Assuming 7000 h of radon exposure per year, this concentration converts to the AED of 2.98 mSv/y [52]. Exceeding this level requires radon mitigation actions. Despite assuming a higher exposure time (8760 h per year) in the scenario of this study, the AED calculated for South Korea is relatively lower on average compared to this reference level.
The sensitivity analysis of the variables used to derive AEDs for each population group was performed using Oracle Crystal Ball (edition version 11.1.2.3.0x64). Unlike other groups, children under one year of age have difficulties with spontaneous activity and therefore spend most of their time within homes and daycare centers. Consequently, their AED is greatly influenced by the amount of time they spend in residential environments and the duration of activities at daycare centers during the week. For the two populations that are typically considered students, 7–13 and 14–18 years old, radon levels at schools and the number of hours spent at schools during the week are highly influential. In the adult population (19 years and older), apart from the radon concentration in the home, the number of hours spent at home and at work during the week are very important. Based on these results, it can be observed that the activity time according to the characteristics of the population plays a crucial role in estimating the AED.

3.2.2. The Excess Lifetime Cancer Risk—Cumulative (ELCR-C)

In the present study, a new ELCR-C was calculated using Monte Carlo simulations by accumulating exposure across age groups over an entire lifespan of 75 years, unlike the traditional ELCR [38]. The ELCR-C was differentiated into two categories: individuals residing in single detached houses and those in apartments. It was assumed that each group would be exposed to various local environments over 75 years, with the time distribution adjusted according to the specific local exposure environments. The difference between single detached houses and apartment houses was statistically significant (p-value < 0.05), and as shown in Figure 4, the ELCR-C in single detached houses was 10.50 × 10−3 ± 4.71 (9.73 × 10−3) when expressed as an arithmetic mean ± standard deviation (geometric mean), with a value of 5.55 × 10−3 for the bottom 5th percentile and 18.81 × 10−3 for the top 95th percentile. The ELCR-C in apartment houses was 7.70 × 10−3 ± 2.51 (7.36 × 10−3). The bottom 5th percentile for apartment houses was 4.70 × 10−3 and the top 95th percentile was 12.26 × 10−3. On average, the ELCR-C for single detached houses was approximately 1.36 times higher than for apartment houses, and when comparing the values at the 95th percentile, it was about 1.53 times higher, indicating that the lifetime cancer risk is relatively higher in the scenario of living in single detached houses. Comparing the ELCRs in single-site environments with the ELCR-C in the present study, all of them were lower than the ELCR-C except for the ELCRs in single detached houses and schools (inset of Figure 4). This shows that calculating the carcinogenic hazard in a single localized environment without evaluating the whole life through various exposures in multiple environments may lead to underestimation.

4. Conclusions

In the present study, the annual effective dose (AED) and cumulative lifetime exposure assessment (ELCR-C) for radon were evaluated, considering various indoor microenvironmental exposures based on age-specific time–activity patterns. Our findings suggest that due to the significant spatial variability in radon concentrations across different microenvironments and differences in age-specific time–activity patterns, comprehensive health risk assessments that account for these variations should be considered. By identifying uncertainties, this approach enables decisions in public health policy to be made from a conservative perspective. Future research should continue to refine this cumulative risk assessment approach by integrating broader data sets and considering the full complexity of human–environment interactions over a lifetime.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/atmos15080927/s1: Figure S1: Active time of each age group by microenvironment: (a) weekday, (b) weekend; Table S1: Distributions and representative values of radon concentration in microenvironments by each age group; Table S2: Distributions of Feq in microenvironments by each age group.

Author Contributions

Concept and design: H.-S.K. and S.-Y.L. Data curation: H.-S.K. and S.-Y.L. Drafting of the manuscript: H.-S.K. and S.-Y.L. Critical revision of the manuscript for important intellectual content: H.-S.K. and S.-Y.L. Statistical analysis: H.-S.K., S.-Y.L. and S.-H.L. Obtainment of funding: H.-S.K. Validation and visualization: H.-S.K., S.-Y.L. and S.-H.L. Supervision: H.-S.K. All authors have read and agreed to the published version of the manuscript.

Funding

This present study was supported by KETI and the Korea Ministry of Environment (MOE) under the “Technology Development Project Linked to the Commercialization of Atmospheric Environment Management Technologies (contract numbers of 2021003400008)”.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. The data are not publicly available due to privacy.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Spatial variation in radon concentration levels by microenvironments in Republic of Korea: (a) single detached houses, (b) apartment houses, (c) daycare centers, (d) schools, (e) offices, and (f) other public facilities.
Figure 1. Spatial variation in radon concentration levels by microenvironments in Republic of Korea: (a) single detached houses, (b) apartment houses, (c) daycare centers, (d) schools, (e) offices, and (f) other public facilities.
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Figure 2. Radon representative concentration by microenvironments. The plus sign and error bars denote mean and 5th and 95th percentiles, respectively, except for outdoor*, which shows standard deviation.
Figure 2. Radon representative concentration by microenvironments. The plus sign and error bars denote mean and 5th and 95th percentiles, respectively, except for outdoor*, which shows standard deviation.
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Figure 3. Radon annual effective dose contribution by microenvironment: living in (a) single detached houses and (b) apartment houses.
Figure 3. Radon annual effective dose contribution by microenvironment: living in (a) single detached houses and (b) apartment houses.
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Figure 4. The excess lifetime cancer risk—cumulative over 75 years for residents of single detached (red) and apartment houses (blue), respectively.
Figure 4. The excess lifetime cancer risk—cumulative over 75 years for residents of single detached (red) and apartment houses (blue), respectively.
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Table 1. Indoor microenvironments in each age group.
Table 1. Indoor microenvironments in each age group.
Age GroupHome [38]
(n = 30,951)
Indoors Away from Home [39]
(n = 50,484)
Daycare Center [39]
(n = 13,998)
School [40]
(n = 2544)
Office [40]
(n = 1547)
Transportation Facilities [39]
(n = 2427)
<1Single detached/
apartment
Postpartum care center,
medical facility
Daycare center--Transportation facilities **
1–6Common facilities *,
private educational facility
7–18Common facilities,
Internet cafe,
private educational facility
Elementary school, middle school, high school
19–24University [42]Office
25–39Common facilities,
Internet cafe,
funeral hall,
private educational facility
40–64-
65 Common facilities,
senior care facility,
funeral hall
University
* Big market, library, bath house, art gallery, museum, indoor parking area, indoor sports facility, movie theater, medical facility, exhibition facility, and underground shopping center. ** Airport facility, passenger terminal, subway station, railway station, and port facility.
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Lee, S.-Y.; Lim, S.-H.; Kim, H.-S. Assessing the Radon Exposure Variability and Lifetime Health Effects across Indoor Microenvironments and Sub-Populations. Atmosphere 2024, 15, 927. https://doi.org/10.3390/atmos15080927

AMA Style

Lee S-Y, Lim S-H, Kim H-S. Assessing the Radon Exposure Variability and Lifetime Health Effects across Indoor Microenvironments and Sub-Populations. Atmosphere. 2024; 15(8):927. https://doi.org/10.3390/atmos15080927

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Lee, Soo-Yong, Sang-Hun Lim, and Hee-Seok Kim. 2024. "Assessing the Radon Exposure Variability and Lifetime Health Effects across Indoor Microenvironments and Sub-Populations" Atmosphere 15, no. 8: 927. https://doi.org/10.3390/atmos15080927

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