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Enhancements in the Techa River Dosimetry System

TRDS-2016D Code for Reconstruction of Deterministic Estimates of Dose From Environmental Exposures

Degteva, M.O.1; Napier, B.A.2; Tolstykh, E.I.1; Shishkina, E.A.1; Shagina, N.B.1; Volchkova, A.Yu.1; Bougrov, N.G.1; Smith, M.A.2; Anspaugh, L.R.3

doi: 10.1097/HP.0000000000001067
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Waterborne releases to the Techa River from the Mayak plutonium facility in Russia during 1949–1956 resulted in significant doses to persons living downstream. The dosimetry system Techa River Dosimetry System-2016D has been developed, which provides individual doses of external and internal exposure for the members of the Techa River cohort and other persons who were exposed to releases of radioactive material to the Southern Urals. The results of computation of individual doses absorbed in red bone marrow and extraskeletal tissues for the Techa River cohort members (29,647 persons) are presented, which are based on residence histories on the contaminated Techa River and the East Urals Radioactive Trace, which was formed in 1957 as a result of the Kyshtym Accident. Available 90Sr body-burden measurements and available information on individual household locations have been used for refinement of individual dose estimates. Techa River Dosimetry System-2016D-based dose estimates will be used for verification of risk of low-dose-rate effects of ionizing radiation in the Techa River cohort.

1Urals Research Center for Radiation Medicine, Chelyabinsk, Russia

2Battelle Pacific Northwest National Laboratory, Richland, WA

3Emeritus, Department of Radiology, University of Utah, Salt Lake City, UT.

The authors declare no conflicts of interest.

For correspondence contact Bruce A. Napier, Pacific Northwest National Laboratory, MS K7-68, P.O. Box 999, Richland, WA, or email at bruce.napier@pnnl.gov.

(Manuscript accepted 19 November 2018)

Online date: April 8, 2019

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INTRODUCTION

THE TECHA River was contaminated in 1949–1956 as a result of releases of radioactive materials by the Mayak plutonium facility (Degteva et al. 2012, 2016; Shagina et al. 2012). The maximum releases occurred in 1951, when significant accidental discharge entered the river. The releases resulted in external and internal exposure of about 30,000 persons who lived in downstream settlements. The members of the Techa River cohort (TRC) were exposed to chronic radiation over a wide range of doses but at low to moderate dose rates. An increase in both leukemia and solid cancers with radiation dose has been noted for the TRC (Davis et al. 2015; Krestinina et al. 2013; Schonfeld et al. 2013). The TRC is the focus of joint Russian/US dose reconstruction and epidemiological studies to address the question of whether there is a dose-rate reduction factor in the induction of stochastic effects by radiation (Napier 2014; Preston et al. 2017).

Estimates of dose for the cohort members have been calculated for many years with a set of computer codes known as the Techa River Dosimetry System (TRDS). Strategic goals for the TRDS are to (1) provide individual doses of external and internal exposure for the TRC members and other persons who were exposed to releases of wastes by Mayak, (2) verify and validate dose estimates to the extent possible, and (3) provide an appropriate description of the uncertainty for each estimate of individual dose. The more significant pathways for the TRC included external exposure due to proximity to the contaminated shoreline and radionuclide intakes (mainly 90Sr, 89Sr, and 137Cs) with the river water and local foodstuff. These pathways have been considered in the main TRDS code since 2000 (Degteva et al. 2000a and b, 2006; Napier et al. 2001). It should be noted that the methodology of retrospective dose assessment used in the TRDS is rather unique in the worldwide practice of environmental dose reconstruction, because the internal dose-reconstruction process is based primarily on a large number of measurements of radionuclide burden in humans (Degteva et al. 2000b, 2006). A radionuclide of major interest was 90Sr, and practically all known methods of 90Sr estimation in humans were used starting from 1951 in the study of the Techa River population. This extensive data set allowed for reconstruction of 90Sr intake functions (Tolstykh et al. 2011) and development of an age- and sex-specific biokinetic model for strontium in humans (Shagina et al. 2015).

There are known to be additional sources of environmental exposure for the TRC members, namely (1) an explosion in the radioactive waste-storage facility in 1957 (the so-called Kyshtym Accident) that formed the East Urals Radioactive Trace (EURT), and (2) the gaseous aerosol releases from Mayak from 1948–1972. For the EURT, detailed maps of soil contamination were published (Izrael 2013), and all data of monitoring of local foodstuffs, environmental samples, and human bone samples were normalized per unit of initial 90Sr deposition (Tolstykh et al. 2017). This allowed for the extension of the main TRDS code for the calculation of doses in the EURT area (Napier et al. 2013). Individual thyroid doses for TRC members exposed to atmospheric radioiodine releases were calculated in a separate computer program as described by Napier et al. (2017).

The latest version of the dosimetry system consists of both deterministic (TRDS-2016D providing point estimate) and stochastic (TRDS-2016MC including uncertainty) versions, which use the same basic equations and input data but are coded separately. TRDS-2016D is operating as a single code unified for the exposures on the Techa River and EURT areas.

This paper provides an overview of the TRDS-2016D system. The results of TRDS-2016D individual dose calculations are presented for the TRC members.

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MATERIALS AND METHODS

Basic equations for calculation of dose

The method being used for the TRDS-2016D dose calculations for exposure to radionuclides released into the Techa River and the EURT can be written as a single equation:

Here the upper lines represent the dose from the Techa River from internal exposures (first line) and external exposures (second line); the lower lines represent dose from exposure to fallout from the EURT from internal exposures (third line) and external exposures (fourth line). The individual components of eqn (1) are:

Do,Y,i = absorbed dose (Gy) in organ o accumulated through calendar year Y to individual i;

Y = the calculational end point for a particular individual (can vary according to the analyst’s wishes within the range 1950–2015);

bi = the year of birth of individual i;

y = year of environmental exposure (external irradiation and intake of nuclides). The minimum value of y in the summation is ymin = MAX{1950, bi, year of first moving to the Techa River or EURT area};

P = the end point of external exposure and intake of radionuclides for a particular individual (can vary within the range 1950–Y, P ≤ Y);

L = location (settlement) identifier;

My,L,i = fraction of year y spent in location L by individual i;

r = identifier of ingested radionuclide (89Sr, 90Sr, 95Zr, 95Nb, 103Ru, 106Ru, 137Cs, 144Ce);

τi = y − bi, the age of individual i in year y (years);

I*y,r,L = intake function (Bq) for year y, radionuclide r, and location L (function of age τ, related to y);

I* = I × ξi, where ξi is a modifier predetermined for individual i equal to 1 (i.e., the village average), IMRi (individual-to-model ratio), or HSRi (household-specific ratio), discussed below;

DFr,o,Y − y = conversion factor (Gy Bq−1) for dose accumulated in organ o in year Y − y from intake of radionuclide r in year y (function of age, related to y and sex, if applicable);

Y − y = time since intake, years;

Ao = conversion factor from absorbed dose in air to absorbed dose in organ o (function of age, related to y);

DRiv,L,y = absorbed dose in air near river shoreline at location L received in year y (Gy);

Rout/Riv,L = ratio of dose rate in air outdoors at homes to the dose rate by the river at location L;

Rin/out = ratio of dose rate in air indoors to that outdoors;

T1 = time spent on river bank relative to whole year (function of age, related to y);

T2 = time spent outdoors relative to whole year (function of age, related to y);

T3 = time spent indoors relative to whole year (function of age, related to y);

GSr,L = surface deposition of 90Sr (Bq m−2) at location L from fallout from the EURT;

δy = 0 or 1 depending on y. For the EURT, δy = 0 for y < 1957;

Er,y = intake function per unit surface deposition of 90Sr for EURT for year y, radionuclide r (function of age, related to y); and

DSr,y = absorbed dose in air (Gy) received in year y per unit deposition of 90Sr (Bq m−2) from fallout from the EURT.

The intake function Iy,r,L is a complex, time-dependent function derived from a combination of data from tooth beta counting and the whole-body counter. The village average intake function Iy,r,L for each year y is calculated as:

Where

= 90Sr intake for adult residents of the reference settlement in year y (reference 90Sr intake function);

= 90Sr intake for other age groups relative to that for adults living in the reference settlement;

= ratio of 90Sr intake for location L to 90Sr intake for residents of the reference settlement; and

= ratio of radionuclide (r) to 90Sr intake for location L in year y.

The TRDS is designed as a modular database processor. That is, depending on the input data for an individual, various elements of several TRDS databases are combined to provide the dosimetric variables requested by the user. TRDS-2016D databases include information on time-dependent radionuclide intakes and absorbed doses in air for 41 settlements located along the Techa River downstream from the site of radioactive releases to the mouth of the river and 83 settlements located in the EURT area with initial deposition of 90Sr from 3.7 to 17,800 kBq m−2. The data for eight radionuclides (89Sr, 90Sr, 95Zr, 95Nb, 103Ru, 106Ru, 137Cs, and 144Ce) are considered, and each radionuclide has a separate table of age-dependent dose coefficients providing absorbed dose in organ o per unit intake. Organs considered in TRDS-2016D include: esophagus, stomach, small intestine, colon, rectosigmoid, lungs, breast, red bone marrow (RBM), thyroid, bladder, liver, spleen, kidneys, adrenals, pancreas, thymus, uterus, testes, ovaries, brain, muscle, and skin.

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Input data and output options

Requisite input requirements and output options for the TRDS-2016 computer program are shown in Fig. 1. As can be seen, the input data for each individual should include identification code (SN), birth year, sex, entire history of residence within the catchment area, and exit year (e.g., due to death, migration, or end of follow-up).

Fig. 1

Fig. 1

The TRDS-2016D code provides a number of output options (Fig. 1). The first option is doses for all members of the TRC computed with a common algorithm which uses village average parameters available in the system databases. Reconstruction of village average intake functions and absorbed doses in air used in TRDS-2016D was described earlier (Tolstykh et al. 2011, 2013, 2017; Degteva et al. 2015; Akleyev et al. 2017). Combining these village average data with the residence history and age of a particular person, the system produces an individualized scenario of external exposure and radionuclide intake, and then calculates corresponding external and internal doses from the Techa River and EURT. Other options provide refined estimates of individual doses from the Techa River in cases where there are additional data on individual exposure conditions.

The second option provides refined estimates of internal dose from the Techa River based on individual 90Sr body-burden measurements. The variation of 90Sr body burden within an age cohort in a village mainly depended on the source of drinking water for particular individuals (Napier et al. 2001). The coefficient of variation (CV) of age-standardized 90Sr body burdens is 0.7–0.8 in villages where the river was the only source of water supply; the CV is 1.8–2.3 for settlements with mixed sources of drinking water (river and wells). The intake functions for subjects who have had body-burden measurements can be adjusted by an individual-to-model ratio (IMR), which is determined as the average of the ratios of an individual’s 90Sr measurements to the respective reference-model values (Degteva et al. 2007). Assuming that those living in the same household would have had similar sources of drinking water and food, it is possible to assign them a household-specific ratio (HSR), which is determined as the average of IMRs for measured members of a household (Degteva et al. 2007). The IMR/HSR values have been calculated for 10,900 persons who have sufficient data and are kept in the IMR/HSR registry (Fig. 1). Thus, the second option replaces the village average intake with an IMR/HSR-adjusted value for these persons to provide them with refined estimates of internal dose.

The third option provides refined estimates of individual external dose calculated for the upper Techa residents accounting for the actual location of their residences with respect to the contaminated river shoreline. The level of external dose for a particular individual within an age cohort in a village is significantly decreased with distance of individual household from the contaminated shoreline (Napier et al. 2001). If the actual distances of individual residences from the river are not known, it is assumed that specific individuals could live in any house within the bounds of the village. The parameter Rout/Riv, L in eqn (1) is defined as the average for an entire village and could bear a significant uncertainty (Napier et al. 2001). Individual household-to-river ratios have been calculated for 2,014 residents of the upper Techa with known geolocation of their residences. These individual external registry data (Rhouse/Riv) are used in the third option to provide this group of subjects with refined estimates of external dose (Fig. 1).

The fourth option is the comparison and compilation of internal and external doses obtained for options 1, 2, and 3 to provide the best estimates for all cohort members with an indicator of individualization (e.g., IMR, HSR, distance of individual household from contaminated shoreline) (Fig. 1).

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RESULTS OF CALCULATIONS

Example case histories

Input data on residence histories and vital status dates for the TRC members were extracted from the Urals Research Center for Radiation Medicine database on 10 March 2017. The input file included satisfactory data on residence histories for 29,647 TRC members. All these people were born before the onset of the Techa River contamination and were first exposed to radiation in the 1950s.

Case history data for six example cases are shown in Table 1. The first two subjects lived in Metlino (the closest village to the release site, demolished in 1956) during the entire period of the releases and then were removed from the Techa River area. One of them (case 2) was additionally exposed in 1957–1960 in the EURT area with low 90Sr deposition. The third person (case 3) moved from the Techa River to the village Berdyanish in 1951 where he was exposed to accident-related fallout in September 1957 and urgently evacuated (together with other Berdyanish residents). The next two persons (cases 4 and 5) lived continuously since birth in villages of the middle Techa region during the period of major releases. The last person (case 6) came to live in a village located far from the release site after the period of major releases. Individual intakes for cases 1, 2, 4, and 5 can be adjusted by IMRs in accordance to their 90Sr body-burden measurements. External exposure scenarios for cases 1 and 2 can be refined in accordance to their household-to-river ratios.

Table 1

Table 1

Individual dose accumulation in RBM and muscle (as a sample of extraskeletal tissues) for the six example cases is shown in Fig. 2. As can be seen from Fig. 2, the RBM dose exceeds the dose absorbed in muscle for all cases. Most of the dose in extraskeletal tissues was accumulated before 1970 due to external exposure and 137Cs intakes. Individual muscle doses varied from 2 mGy for case 6 (a late arrival to lower reaches of the river) to 910 mGy for case 1 (living close to the release site during entire period of the release). RBM irradiation with 90Sr incorporated in bones continued for a longer period. Individual RBM doses varied from 34 mGy for case 5 (middle Techa, use of well water) to 3.18 Gy for case 4 (middle Techa, use of river water for drinking). The effect of EURT exposure is noticeable only for case 3 when the person, after a short residence on the river, migrated to a village that was heavily contaminated in 1957 as a result of the Kyshtym Accident. After the accident, his RBM dose increased 2 times and muscle dose increased 13.5 times (Fig. 2).

Fig. 2

Fig. 2

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Contributions of different exposure pathways

On average, the total RBM doses for adult permanent residents were about 1 Gy in the upper Techa region, about 0.5 Gy in the middle course of the river, and about 0.3 Gy in the lower reaches. To understand the nature of radiation exposure to members of the TRC, it is necessary to consider separately the contributions of different exposure pathways to the total RBM dose. The typical structure of the total RBM dose for different regions of the Techa River area is shown in Table 2. As can be seen from Table 2, the major dose-causing radionuclide was 90Sr, contributing 61–94% to the total dose. The contribution of 89Sr was about 2.5–3.2% and did not significantly change with distance from the release site. The percent contributions of external sources and internal 137Cs were highest in the upper Techa region (contributing 24% and 12%, respectively) and significantly decreased with distance (up to 0.6% and 1.9% in the lower Techa villages). The difference in contributions of 90Sr and 137Cs with distance can be explained by a 4-fold excess of sorption rate by bottom and floodplain soils for 137Cs in comparison with 90Sr (Shagina et al. 2012). As a result, the 137Cs-to-90Sr ratio in river water decreased with downstream distance.

Table 2

Table 2

RBM doses for the TRC members from separate exposure pathways (Techa internal, Techa external, EURT internal, EURT external) are shown in Table 3. As can be seen from Table 3, 29,618 members of the TRC were exposed due to their residence in Techa River villages, and 5,280 members of the TRC were exposed due to their residence in EURT villages. Average external dose from the Techa River was 57 times higher than from the EURT, and the average internal dose from the Techa River was 142 times higher than from the EURT. Thus, internal exposure of RBM, mainly due to 90Sr intake, was the dominant pathway for all TRC members.

Table 3

Table 3

The contributions of external and internal exposures to absorbed dose for selected extraskeletal tissues of TRC members are illustrated in Fig. 3. As can be seen, median doses from external exposure are lower than those from internal exposure for all organs considered. Nevertheless, for a group of TRC members with the highest levels of dose, the contribution of external exposure exceeds the contribution of internal exposure. This results in a slight excess of the cohort average value of the external dose over the internal dose; specifically, 30 vs. 29 mGy for stomach and 31 vs. 19 mGy for lungs. The major pathways for these organs were external exposure and intake of 137Cs.

Fig. 3

Fig. 3

It should be noted that the TRC members, in addition to exposures from the Techa River and EURT, were exposed to atmospheric radioiodine releases from the Mayak stack. Individual thyroid doses to TRC members from the Techa River and the EURT were calculated using the TRDS-2016D code. Then, for TRC members exposed to atmospheric radioiodine releases, individual thyroid doses were calculated with the CiderF computer code (Eslinger and Napier 2013) as described by Napier et al. (2017). The summation of the results showed that the 131I contribution was 75–99% of the total thyroid dose for the TRC members. The highest thyroid doses were received by persons born in 1947–1949 and living for several years in the village of Metlino, the closest downwind village to Mayak. Thus, the major pathway for the thyroid exposure of the TRC members was intake of 131I.

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Distributions of individual organ doses in the TRC

Table 4 shows parameters of the distributions of individual doses absorbed in different organ/tissues of the TRC members. As can be seen, dose distribution through the human body was uneven, with average doses of 50–60 mGy for most extraskeletal tissues, 80–100 mGy for the colon wall, about 200 mGy for the thyroid, and 350 mGy for RBM.

Table 4

Table 4

Individual dose values in the TRC varied over a wide range. About 10% of the TRC members received doses less than 2 mGy to extraskeletal tissues, less than 10 mGy to the thyroid, and less than 60 mGy to RBM (Table 4). As a rule, these people came to the Techa River after the end of the major releases and lived away from the release site. At the same time, the other 10% of the TRC received doses exceeding 100 mGy to a majority of extraskeletal tissues, 200 mGy to the colon wall, 400 mGy to the thyroid, and 900 mGy to RBM (Table 4). Maximum doses (about 1 Gy to a majority of extraskeletal tissues, 2 Gy to the colon wall, and 7 Gy to the thyroid and RBM) were estimated for persons who spent their childhood and adolescence in the upper Techa region and for which individual data were available on high body burdens and close location of their residence places to the contaminated floodplain. It should be noted that median dose in all cases is significantly lower than the average value, and thus the distributions of individual doses are strongly asymmetrical.

Individual dose estimates were provided to epidemiologists working on a companion project developing subsequent risk assessments of long-term effects. Epidemiological studies in the Techa River cohort are internationally recognized as an important source of information on the influence of radiation dose and dose rate on health effects (Ruhm et al. 2015).

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DISCUSSION

The reliability of dose estimates depends mainly on the completeness and quality of the basic primary data and reliability of models that describe radionuclide behavior in the environment and humans. A previous version of the dosimetry system, TRDS-2009, was used to estimate dose-related increases in risks of leukemia and solid cancers in the TRC (Davis et al. 2015; Krestinina et al. 2013; Schonfeld et al. 2013). Since 2009, the TRDS databases have been significantly updated on the basis of extensive analysis of historical data on environmental contamination and internal contamination of humans with the use of model calculations.

Special attention is paid to 90Sr, the most significant radionuclide in terms of RBM dose. The reconstruction of internal dose relies strongly on the results of measurements of 90Sr in residents of the Urals region. These data include the results of post mortem measurements of 90Sr in bone samples, as well as extensive in vivo measurements of tooth beta activity and 90Sr body burdens (Degteva et al. 1998). The data set on in vivo 90Sr measurements is critical to the success of efforts to provide individual doses and their uncertainties. The data on 90Sr measurements in teeth of residents along the Techa River were used for reconstruction of age-dependent 90Sr intake functions (Tolstykh et al. 2011). An improved age- and sex-dependent biokinetic model for strontium was developed (Shagina et al. 2015) to provide a link between ingested amount of radionuclide and time-dependent 90Sr body burdens.

A more accurate reconstruction of radionuclide releases into the Techa River was performed based on recently available archive materials regarding liquid radioactive waste storage and reprocessing at the Mayak facility (Degteva et al. 2012, 2016). Verified values of the source-term parameters were used for subsequent modeling of radionuclide transport along the Techa River and radionuclide deposition in flooded areas (Shagina et al. 2012). The outputs of the Techa River model show good agreement with historical measurements of water and soil contamination, as well as with 90Sr concentration in water (Tolstykh et al. 2011) based on 90Sr measurements in teeth (Shagina et al. 2012; Degteva et al. 2016). The model outputs provided concentrations of all source-term radionuclides in the river water and were used for estimation of the intake of non-90Sr radionuclides. Also included in the model output were concentrations of radionuclides on the shoreline and in floodplain soils. This allowed estimation of 137Cs transfer from floodplain soil to grass and cow’s milk and verification of dietary 137Cs intake (Tolstykh et al. 2013).

External dose rates in air were derived from radionuclide contents of the floodplain as calculated from the Techa River transport model and coefficients obtained by Monte Carlo simulations of air kerma (Shishkina et al. 2016). Modeled values were in agreement with the archival measurements of exposure rate carried out on the Techa River banks in the 1950s (Degteva et al. 2017). TRDS-based estimates of integral air kerma were validated using the luminescence measurements of anthropogenic dose in bricks from old buildings located on the Techa River banks (Hiller et al. 2017). To convert air kerma to doses in different organs, age-dependent coefficients were estimated (Shishkina et al. 2018). External dose estimates for residents along the Techa River were validated by electron paramagnetic resonance (EPR) measurements of teeth and fluorescent in situ hybridization (FISH) measurements of chromosome translocations (Degteva et al. 2015, 2017; Shishkina et al. 2016).

These improvements yielded substantial changes in the estimates of doses. Comparison with the previous dose estimates has shown that TRDS-2016D estimates have a good correlation with TRDS-2009 estimates (R = 0.95) but are on average 18% lower for RBM and about 30% higher for extraskeletal tissues. This is due mainly to the revision of radionuclide concentrations in the Techa River water and floodplain obtained with more detailed data on Mayak releases using an improved model of radionuclide transport along the river. The differences in individual dose values reflect the inclusion of household-specific external dose estimation, updates of residence history data and vital status dates (made after 2009), and updates of the IMR and HSR registries.

When estimation of radiation doses is based on historical reconstructions, many determinants of dose may be uncertain. The uncertainties in the TRDS are estimated using a two-dimensional Monte Carlo dosimetry system that incorporates shared and unshared uncertainties and acknowledges Berkson and classical types of uncertainties (Napier et al. 2013). A stochastic version (TRDS-2016MC) has been developed, which uses the same basic equations and input data as TRDS-2016D but is coded separately. This provides the project with the opportunity for comparative analyses for quality assurance, as well as providing the end users of dose estimates with various options for analysis. A description of TRDS-2016MC with results of stochastic estimates of individual dose will be the topic of a future paper.

TRDS-2016 is operating as a unified system for calculating exposures on the Techa River and in the EURT areas and can be used in the future for individual dose calculations in the combined Techa River plus EURT cohort. Analysis of cancer and leukemia incidence and mortality in the combined cohort will provide more data on low dose-rate effects on humans and could be useful for the purpose of radiological protection.

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CONCLUSION

The TRDS-2016D dosimetry system was developed to provide individual doses of external and internal exposure for the Techa River cohort members and other persons who were exposed to environmental releases of radioactive material in the Southern Urals. The results of the computations of individual doses absorbed in red bone marrow and extraskeletal tissues for the TRC members (29,647 persons) are presented, which are based on residence histories on the Techa River and East Urals Radioactive Trace (EURT), available body-burden measurements, and available information on individual household locations. TRDS-2016-based dose estimates will be used for verification of the risk of long-term effects.

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Acknowledgments

This work has been supported by the US Department of Energy’s Office of Health Studies and the Federal Department of the Ministry of Health of the Russian Federation. The authors thank the following persons for their technical assistance in this project: Olga Kozyreva, Victor Krivoschapov, Elena Tokareva, and Boris Akhramenko.

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Napier BA, Eslinger PW, Tolstykh EI, Vorobiova MI, Tokareva EE, Akhramenko BN, Krivoschapov VA, Degteva MO. Calculations of individual doses for Techa River Cohort members exposed to atmospheric radioiodine from Mayak releases. J Environ Radioact 178-179:156–167; 2017. DOI 10.1016/j.jenvrad.2017.08.013.
Preston DL, Sokolnikov ME, Krestinina LY, Stram DO. Estimates of radiation effects on cancer risks in the Mayak worker, Techa River and atomic bomb survivor studies. Radiat Protect Dosim 173:26–31; 2017. DOI 10.1093/rpd/ncw316.
Ruhm W, Woloschak GE, Shore RE, Azizova TV, Grosche B, Niwa O, Akiba S, Ono T, Suzuki K, Iwasaki T, Ban N, Kai M, Clement CH, Bouffler S, Toma H, Hamada N. Dose and dose-rate effects of ionizing radiation: a discussion in the light of radiological protection. Radiat Environ Biophys 54:379–401; 2015. DOI 10.1007/s00411-015-0613-6.
Schonfeld SJ, Krestinina LY, Epifanova SB, Degteva MO, Akleyev AV, Preston DL. Solid cancer mortality in the Techa River Cohort (1950–2007). Radiat Res 179:183–189; 2013. DOI 10.1667/RR2932.1.
Shagina NB, Vorobiova MI, Degteva MO, Peremyslova LM, Shishkina EA, Anspaugh LR, Napier BA. Reconstruction of the contamination of the Techa River in 1949–1951 as a result of releases from the “MAYAK” Production Association. Radiat Environ Biophys 51:349–366; 2012. DOI 10.1007/s00411-012-0414-0.
Shagina NB, Tolstykh EI, Degteva MO, Anspaugh LR, Napier BA. Age and gender specific biokinetic model for strontium in humans. J Radiol Protect 35:87–127; 2015. DOI 10.1088/0952-4746/35/1/87.
Shishkina EA, Volchkova AY, Degteva MO, Napier BA. Evaluation of dose rates in the air at non-uniform vertical distribution of gamma-emitting radionuclides in different types of soil. Radiat Safety Problems 3:43–52; 2016 (in Russian).
Shishkina EA, Volchkova AY, Degteva MO, Napier BA. Dose coefficients to convert air kerma into organ dose rate values for people of different ages externally exposed to 137Cs in soil. Radiat Safety Problems 89:36–47; 2018 (in Russian).
Tolstykh EI, Degteva MO, Peremyslova LM, Shagina NB, Shishkina EA, Krivoschapov VA, Anspaugh LR, Napier BA. Reconstruction of long-lived radionuclide intakes for Techa riverside residents: strontium-90. Health Phys 101:28–47; 2011. DOI 10.1097/HP.0b013e318206d0ff.
Tolstykh EI, Degteva MO, Peremyslova LM, Shagina NB, Vorobiova MI, Anspaugh LR, Napier BA. Reconstruction of long-lived radionuclide intakes for Techa riverside residents: 137Cs. Health Phys 104:481–498; 2013. DOI 10.1097/HP.0b013e318285bb7a.
Tolstykh EI, Peremyslova LM, Degteva MO, Napier BA. Reconstruction of radionuclide intakes for the residents of East Urals Radioactive Trace (1957–2011). Radiat Environ Biophys 56:27–45; 2017. DOI 10.1007/s00411-016-0677-y.
Keywords:

accidents, nuclear; contamination, environmental; dose reconstruction; dosimetry

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