Radioecology discussion post/response

Journal of Environmental Protection, 2014, 5, 181-192 Published Online February 2014 (http://www.scirp.org/journal/jep) http://dx.doi.org/10.4236/jep.2014.53022

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Radioecology: Why Bother?

Emily Amanda Caffrey*, Mary Elizabeth Leonard, Jonathan Bamberger Napier, Delvan Reed Neville, Kathryn Ann Higley

Department of Nuclear Engineering and Radiation Health Physics, Oregon State University, Corvallis, USA. Email: *[email protected] Received December 21st, 2013; revised January 19th, 2014; accepted February 15th, 2014 Copyright © 2014 Emily Amanda Caffrey et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In accordance of the Creative Commons Attribution License all Copyrights © 2014 are reserved for SCIRP and the owner of the intellectual property Emily Amanda Caffrey et al. All Copyright © 2014 are guarded by law and by SCIRP as a guardian.

ABSTRACT The importance of radioecology to the discussion of radioactive contamination is discussed here. This paper dis- cusses the history of radioecology, alongside the most recent developments in the science. It describes the need for more environmental data, and explains where the gaps in current knowledge lie. The calculation of radiation dose to wildlife along with the complications in performing such calculations is discussed. The paper also tackles the difficult question of the implications of radioecology on nuclear waste management and site decommissioning policies. From the beginnings of the science to today, radioecology is poised to be an important field of study as humans continue to rely on ionizing radiation to improve their lives. KEYWORDS Radioecology; Wildlife Dose Calculations; Nuclear Waste Disposal; Environmental Protection

1. Introduction: A Brief History of Radioecology

“Radioecology is the study of behavior and effects of radioactive elements in the environment. This can be broken into three subdivisions: radionuclide movement within ecological systems and accumulation within spe- cific ecosystems components such as soil, air, water, and biota; the effects of ionizing radiation on individual spe- cies, populations, communities, and ecosystems; and the use of radionuclides and ionizing radiation in studies of structure and function of ecosystems and their compo- nent subsystems” [1].

Radiation protection has historically focused on hu- mans as the object of protection standards. In 1977, the International Commission on Radiological Protection (ICRP) stated that “Radiation protection has historically been solely focused on human protection, with the rea- soning that… the level of safety required for the [radia- tion] protection of all human individuals is thought likely to be adequate to protect other species, although not nec- essarily individual members of these species. The Com- mission therefore believes that if man is adequately pro-

tected then other living things are also likely to be suffi- ciently protected” [2].

In 2008, ICRP recommendations shifted toward a new paradigm, one in which wildlife populations are consi- dered to be their own protection endpoint. This decision has raised numerous challenges for the scientific com- munity, and efforts are currently in progress to deepen the understanding of how radiation impacts non-human biota (NHB). With this new paradigm, evaluating radia- tion dose to biota in response to planned, existing, or emergency situations is of significant concern. As dose- response relationships are not currently well understood for NHB, it is imperative to make an accurate determina- tion of dose rates at which NHB are exposed.

This paper aims to place radioecology in the context of radiological contamination, with the intent to inform readers about this field of study and some of the ongoing work to improve radioprotection of the environment.

2. The Need for More Data 2.1. Controversy and Data Gaps There is confusion over appropriate endpoints of protec- *Corresponding author.

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tion. For humans, we are interested in reducing the life- time cancer risk to as low as reasonably achievable, a stochastic endpoint, as our radiation protection standards virtually rule out deterministic effects. The dose-response relationship for humans is assumed to be linear, with no threshold, meaning that any increase in dose is an in- crease in risk. The dose response relationship for NHB is unknown in many cases. Table 1 illustrates the differ- ences in human and ecological protection.

There is also a scarcity of long-term multigenerational studies for NHB. One study shows that bank voles living in the Chernobyl exclusion zone had levels chromosomal aberrations in bone marrow that remained constant with each generation, despite decreasing levels of dose. In addition, the percent mortality of their embryos increased with time [3], suggesting that chronic, low doses of radi- ation may be more detrimental to organism health than previously assumed.

Finally, there is a growing abundance of data to chal- lenge established paradigms. Several studies done by Møller and Mousseau in the Chernobyl region suggest that there may be population level effects at radiation doses below that which were previously assumed safe [4,5]. These studies challenge our belief that low levels of

radiation (e.g., a few multiples of background dose rates) are essentially harmless to NHB. They highlight the need for a coordinated research effort to both qualify the types of effects and quantify their level of damage. There is ongoing research that is attempting to assist in the evalua- tion of radiation dose received by NHB. Table 2 provides a qualitative summary of the available data on chronic radiation effects [6].

2.2. Source Validity It is generally taken as true that site specific analytical results are more representative of a location than generic data. Studies of analogues may be used for site analysis, but the information should be limited to parameter fitting [7]. Additionally, applying non site specific data can lead to less accurate results because radionuclide data is “in- fluenced by many factors associated with the properties of the radionuclide, the organism, and the ecosystem. As a result, individual measurements display a great deal of variability [8].

An analysis of the source term data for the biosphere sub-model of Yucca Mountain by Higley et al. [9] de- termined that, of 538 parameters, 139 were sourced from

Table 1. Differences in human vs. ecological protection.

Observation Unit Endpoint of Concern Dose-Response Relationship

Humans Individuals Lifetime cancer risk Established relationship

Ecological Scenario dependent: could be populations, communities, or

ecosystems

Species dependent: could be increased mortality, decreased

fecundity, other sub-lethal effects

Unknown in many cases: chronic low-levels of radiation exposure only, possibly radiation exposure

mixed with other toxins?

Table 2. Data availability for chronic and external gamma radiation effects.

Species Morbidity Mortality Reproductive Capacity Mutation

Amphibians Few None None Few

Aquatic Invertebrates Available Few Few Few

Aquatic Plants Few Few None None

Bacteria Few None None None

Birds None None Available Few

Crustaceans Few Few Few None

Fish Available Few Available Available

Fungi Few None None None

Insects Available Few Few Few

Mammals Available Available Available Few

Mollusks Few Few Few None

Moss/Lichens Few None None None

Plants Available Available Available Available

Reptiles None None None Few

Soil Fauna Few Few None Few

Zooplankton Few None Few None

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a peer reviewed article, 210 were from institutional pub- lications, 140 had no listed reference, and 49 were de- rived during the creation of the model by the authors [9]. Of the data required to build the model, 35% were either not sourced, or inferred by the authors of the perfor- mance assessment.

There are ways to fill data gaps for site assessments. Collection of samples of opportunity from locations rep- resentative of the site can fill gaps for specific locations [10,11]. Collection efforts, along with, rapid processing and analysis can provide data that is accurate for the site and applicable.

2.3. Distribution of Information When transfer (e.g., concentration ratio) data is collected, there are no guidelines for filling in data gaps. What is collected is at the discretion of the team of researchers completing the study. The possibilities for research are open ended, but tend to be focused in specific directions towards certain elements and species.

There are two ways to consider how data is available, the first is element specific. IAEA Technical Document 1616 [12] provides a sense of the distribution of element specific transfer data for longer lived artificial radionuc- lides. Of the 9370 records for root transfer, roughly sixty percent provided data on cesium, strontium, or cobalt. The other 36 elements shared the remaining forty percent though most sources quantified manganese, zinc, ameri- cium, neptunium, and curium. The focus is similar in tropical and subtropical environments, though fewer ra- dionuclides are cataloged. Of the data available, 47% is for cesium and strontium, 21% is for naturally occurring radionuclides, 16% provides data on cobalt, zinc, and manganese, with the remaining data pertaining to other radionuclides. Naturally occurring radionuclides show similar trends with the focus being on uranium and ra- dium with other elements having sparse associated trans- fer data.

The second methodology for transfer is by animal, but this too has data gaps. The number of listed references for human protein and milk sources was categorized in IAEA Technical Document 1616 [12]. The numbers of references for 37 elements are shown in the following table (Table 3) for beef, cow milk, sheep meat and milk, goat meat and milk, pork, poultry, eggs. Looking at the data, it is again apparent that cesium and strontium are better characterized in beef and cow milk than other ele- ments. Iodine transfer through cow milk is also well characterized. But when looking at meat and milk prod- ucts from goat and sheep, meats that are eaten throughout the world, but not considered part of the core western diet.

The amount of data for plants and animals that are not art of the western food chain is even sparser. A review of

pasture grazers by Brown et al. [13] showed that reindeer transfer factors accounted for more than 80 percent of the available values. Similar notes have been made on the availability of transfer factors for birds.

From both conceptual methodologies, the IAEA con- siders the amount of data for cesium and strontium to be acceptable and nearly adequate for uranium, radium, manganese and cobalt. These six elements have more than 500 listed references available; the other elements considered have not been studied to the same extent and do not have enough data points to be considered suffi- ciently categorized.

3. Determining Dose to Non-Human Biota: The Development of Computational Voxel Phantoms

Several approaches have been developed, tested and compared for the computation of radiation dose in non-human biota. The ICRP has developed a compre- hensive approach that includes the use of Reference Animals and Plants (RAPs) for the assessment of dose to NHB.

ICRP’s current approach to dosimetry calculations for NHB relies on simplified organism geometry. Organisms are modeled as ellipsoids made of homogeneous ICRU four-component soft tissue [14]. Some models also con- tain simple ellipsoidal organs that serve as targets for dosimetric calculations [15]. These rudimentary models are used to generate absorbed fractions that are in turn used to calculate dose conversion factors (DCFs) from radionuclides that are distributed uniformly throughout the organism. There are two scenarios that require con- siderations beyond that available with homogeneous models. The first is when comparing full body average dose rates for homogeneous and non-homogeneous dis- tributions of incorporated radionuclides and assessments of the uncertainties of the whole body doses due to those non-homogeneous sources. The second is when it is ne- cessary or prudent to estimate organ dose rates form ra- dionuclides that partition heterogeneously.

Voxel models are three dimensional models created from radiological imaging modalities (e.g. computed tomography and magnetic resonance imaging). These models allow radioecologists to calculated organ-specific DCFs from heterogeneously distributed radionuclides. Voxel models are more robust and easily defendable than the previously used ellipsoidal models.

Figure 1 shows the procedure for the creation of voxel phantoms. First, the organism of interest is obtained, and imaged using CT or MRI. The scans are loaded into software (3D Doctor in the case of the crab, flatfish, trout, bee, and earthworm that have been created to date) that allows the user to manipulate the images. Organs and other structures or tissues of interest are segmented, and

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Table 3. Number of available transfer coefficients for certain proteins and milk sources, data from IAEA Technical Docu- ment 1616 [14].

Element Beef Cow Milk Sheep Meat Sheep Milk Goat Meat Goat Milk Pork Poultry Egg

Ag No Data No Data 1 No Data No Data No Data No Data No Data No Data

Am 1 1 1 No Data No Data 2 No Data No Data 1

Ba 2 15 No Data 1 1 3 No Data 2 1

Be No Data 1 No Data No Data No Data No Data No Data No Data No Data

Ca 3 15 No Data Stable No Data 12 No Data 2 1

Cd 8 8 1 1 No Data 1 No Data 2 No Data

Ce No Data 6 1 No Data No Data 1 No Data No Data 1

Cl 1 No Data No Data No Data No Data No Data No Data No Data No Data

Co 4 4 2 2 No Data 1 No Data 2 2

Cr No Data 3 No Data 1 No Data 2 No Data No Data No Data

Cs 58 288 41 28 11 28 22 13 11

Fe 4 7 No Data Stable No Data Stable 1 No Data 2

I 5 104 1 7 No Data 24 2 3 4

La 3 No Data No Data No Data No Data No Data No Data No Data No Data

Mn 2 4 1 1 No Data Stable 1 2 3

Mo 1 7 No Data No Data No Data 4 No Data 1 3

Na 2 7 1 No Data No Data Stable No Data 1 2

Nb 1 1 No Data No Data 1 1 No Data 1 1

Ni No Data 2 No Data 1 No Data 2 No Data No Data No Data

Np No Data No Data No Data No Data No Data 1 No Data No Data No Data

P 1 Stable No Data Stable No Data Stable 1 No Data 1

Pb 5 15 2 Stable No Data No Data No Data No Data No Data

Po No Data 4 No Data No Data No Data 2 No Data 1 1

Pu 5 No Data 2 No Data No Data No Data No Data No Data 2

Ra 1 11 No Data No Data No Data No Data No Data No Data No Data

Ru 3 6 2 No Data No Data No Data 1 No Data 1

S No Data 1 3 Stable No Data 12 No Data No Data No Data

Sb 2 3 No Data No Data No Data No Data No Data No Data No Data

Se No Data 12 No Data No Data No Data 2 1 4 4

Sr 35 154 25 4 8 21 12 7 9

Te 1 11 No Data 1 1 1 No Data 1 1

Th 6 3 No Data No Data No Data No Data No Data No Data No Data

U 3 3 No Data No Data No Data 1 2 2 2

W No Data 7 No Data No Data No Data No Data No Data No Data No Data

Y No Data No Data No Data No Data 1 1 No Data No Data No Data

Zn 6 8 6 Stable No Data Stable 2 3 4

Zr 1 6 No Data No Data 1 1 No Data 1 1

a 3-dimensional model is created. 3D Doctor allows for the export of a boundary file, which specifies the coordi- nates of each segmented tissue on a three dimensional matrix grid. This file is imported into a program created by the Human Monitoring Laboratory called Voxelizer [16]. Finally, a lattice geometry is imported into the

Monte-Carlo N-Particle transport code, where absorbed fractions (AF; a unit-less number that quantifies the amount of energy deposited in a target organ from a source organ). The AF values are then used in radiation dose or DCF calculations, coupled with environmental concentration data. This dose calculation informs the

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Figure 1. Creating voxel phantoms.

decision-making process, such that environmental re- mediation, removal of wildlife, or other actions deemed necessary can be taken.

4. Implications for Nuclear Waste and Site Decommissioning Policies

4.1. Biosphere Models Performance assessments comprise the formal means by which the long-term safety of nuclear waste repositories is evaluated. In its peer review of the biosphere modeling program of the US Department of Energy’s Yucca Mountain site characterization project, the International Atomic Energy Agency states that an essential compo- nent of a performance assessment is the development and application of a methodology for assessing the potential impact of any future releases of radionuclides that may reach the surface environment, i.e. the biosphere [17]. Efforts to predict radiological doses to future human populations resulting from long-term geological disposal of radioactive wastes rely heavily on modeling software.

Modeling programs have been designed to predict movement of radionuclides in future environments (up to 1 × 106 y) [18-20]. Many performance assessments in- corporate a scenario of future human inhabitants living near a waste repository and irrigating crops with groundwater contaminated with radioactive isotopes in the absence of major geological disturbance or human intrusion into the repository [21].

Broadly speaking, the modeling process for radioac- tive waste internment or site decommissioning involves 1) construction of a conceptual model that describes the system and includes each of the important processes and their couplings, 2) translation of the conceptual model into a mathematical model and coding it into a computer program, 3) verification of the numerical correctness of the code, and 4) validation of the code’s applicability to the repository system to assess its predictive capabilities [22]. A sequential chain of codes is then constructed to model waste canister corrosion, waste dissolution, near- field diffusive transport of radionuclides, far-field diffu- sive transport of radionuclides, radionuclide release to

Organism

Structure ID

Voxelizer Lattice

Voxel Model Rendering

MCNP results

Environmental Source term

DOSE/DCF

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the biosphere, and uptake of radionuclides by humans, plants, or animals.

The last two components, release of radionuclides to the biosphere and their subsequent uptake by biota, are most relevant to the field of radioecology. Biosphere models must consider 1) radionuclide transport through many food chain pathways, such as deposition on soil and vegetation via irrigation water; 2) crop interception and retention; 3) radionuclide accumulation in soils as a result of long-term deposition by irrigation; 4) radionuc- lide leaching from the soil and retention mechanisms in root zones; 5) re-suspension of contaminated soil onto vegetation; 6) soil-to-plant uptake via roots; 7) transfer of radionuclides from feed to animal products; and 8) food ingestion rates of humans [23].

Although they are highly complex, these models by necessity include hypotheses, assumptions, and simplifi- cations. Biosphere models are generally based on empir- ically determined bio-concentration factors, which pre- dict radionuclide concentrations in plants and animals based on their concentrations in the environment (soil, water) or an animal’s diet. Concentration ratio (CR) is the ratio of radionuclide concentration in plant or animal tissue to the radionuclide’s concentration in the sur- rounding medium (soil, water). Transfer coefficients, also known as transfer factors, relate radionuclide con- centrations in an animal’s diet to radionuclide concentra- tions in foods produced from the animal.

The most minimal acceptable model of radionuclide uptake by vegetation is illustrated by Robertson et al. in their review of plant and animal transfer factors used in performance assessment models [23]. The model con- tains two components: the plant uptake of radionuclides deposited on plant material above ground, and plant up- take of radionuclides through roots. Equation (1) below shows how concentration of a radionuclide from deposi- tion is calculated for a plant at the time of harvest. It is the sum of deposition of the radionuclide directly onto plant surfaces from the air, deposition from re-suspended soil material, and deposition from irrigation water:

( ) [ ( ) ) ( ) ( )( )

dci yr id dc iw wc

ci yr c di dc wi ic c

λeiTgc2.74E 3 c c ei

C T R R

3.15E7C T RF V R M

TV B 1 e λ− −

= Γ + Γ

+ Γ + ∗ Γ   ∗ ∗ −  

(1) where:

Cdci(Tyr) = concentration of radionuclide i on plant type c at harvest from deposition processes for a one-year period (Bq/kg wet weight)

Tyr = one-year exposure period (y) Rid = constant dry deposition rate of radionuclide i

(Bq/m2y)

Riw = constant wet deposition rate of radionuclide i (Bq/m2y)

Γdc = interception fraction from airborne dry deposi- tion for plant type c (dimensionless)

Γwc = interception fraction for airborne wet deposition to plant type c (dimensionless)

Cci(Tyr) = average concentration of radionuclide i in farmland soil for crop type c for the current one-year period (Bq/m2)

RFc = re-suspension factor for crop soil (m −1)

Vdi = deposition velocity of radionuclide i (m/s) Γic = interception fraction for irrigation deposition to

plant type c (dimensionless), generally equal to Γwc Mc = fraction of the year irrigation takes place for

plant type c TVc = translocation factor for plant type c (dimen-

sionless) Bc = total standing biomass for plant type c (kg wet

weight/m2) λei = effective loss rate constant from plant surfaces

representing weathering and radioactive decay for radio- nuclide i (y−1)

λei = λwi + λI λwi = weathering rate constant for crops for radionuc-

lide i (y−1) Tgc = crop growing period for plant type c (days) 3.15E7 = units conversion factor (sec/y) 2.74E−3 = units conversion factor (y/d) Equation (2) illustrates how concentration of a radio-

nuclide in a plant due to root uptake is calculated:

( ) ( ) 1rci yr ci yr vci cC T C T B f P−= ∗ ∗ (2) where:

Crci(Tyr) = concentration of radionuclide i in crop type c from root uptake pathways for a 1-year period (Bq/kg wet plant)

Bvci = concentration ratio for plant type c (Bq/kg dry plant per Bq/kg dry soil)

fc = dry-to-wet ratio for plant type c (kg dry plant/kg wet plant)

P = areal soil density (kg dry soil/m2) The total radionuclide concentration in the plant at the

time of harvest is the sum of radionuclide contributions by deposition and root uptake is described by Equation (3):

( ) ( ) ( )hci yr dci yr rci yrC T C T C T= + (3) where:

Chci(Tyr) is the concentration of radionuclide i in plant type c at harvest for a one-year period (Bq/kg wet plant), and other terms are as previously defined.

A cursory review of the equations for plant radionuc- lide uptake reveals the complexities inherent to evaluat- ing radionuclide concentrations in crops. The equations

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describing radionuclide concentrations in animals used for foodstuffs are no less complex. Transfer factors are often element and species specific. For example, a trans- fer coefficient calculated for 99Tc cannot be used inter- changeably with one calculated for 137Cs, as these ele- ments have different chemical and physiological proper- ties. One cannot assume that a transfer coefficient calcu- lated for 90Sr in beef is applicable to 90Sr in chicken. Calculation of transfer coefficients must also take into consideration each of the following variables: mode of absorption (gastrointestinal, inhalation, etc.); homeostatic control mechanisms that may cause variation in transfer coefficients over a wide range of conditions (for example, if calcium and strontium are under homeostatic control with regard to their concentrations in milk, estimates of strontium intake by the animal may not allow accurate determination of strontium concentration in the milk); equilibration of radionuclides in animal tissues; the ef- fects of a radionuclide’s chemical form, generally asso- ciated with solubility, on rates of absorption; isotopic effects of radionuclides lacking stable isotope carriers (such as technetium and plutonium); interference of die- tary components such as fiber; age of the animal; varia- tions in geography; and other variables such as soil in- gestion by the animal [23].

4.2. Missing Data In the absence of solid experimental, observational, or theoretical support, performance assessment model pa- rameters are generally selected to yield conservative re- sults. Erring on the side of caution is preferable to unde- restimating dose to biota; however, this approach almost certainly overestimates risk in some cases. With regard to waste repository performance assessments, regulatory decisions and allocation of resources should rely on ex- perimentally determined model input values whenever possible. Recent investigations have revealed significant data gaps in the parameters used for modeling radionuc- lide uptake by both plants and animals [9,24,25]. Con- centration ratios and transfer coefficients for 137Cs and 90Sr have been experimentally determined for many plant and animal species, due to the predominance of these isotopes in releases from atmospheric testing and events at Chernobyl in 1986 and the Fukushima Daiichi plant in 2011. However, data for determining biosphere concen- trations of many other components of high-level nuclear waste are either incomplete or lack empirical support.

Figure 2 and Table 2 show the number of available data sources for concentration ratios and transfer factors [14]. In their 2011 review of the parameters selected for a recent performance assessment, Higley et al. determined that of the 538 parameters examined, 139 (26%) refe- renced at least one peer-reviewed article. 210 (39%) re- ferenced an institutional publication. 140 (26%) had no

references, and 49 (9%) were justified or derived inter- nally by the case study’s authors. Gaps in compendia of experimentally determined values have not prevented predictions for radionuclide transfer among wide-ranging species and environments. This is problematic, because such predictions may be made using data obtained from chemical analogues (e.g. iodide in place of chloride based on both being halogens) or altogether dissimilar chemical species. In other cases, informed judgment re- garding use of data is relegated to appendices, and the uncertainty surrounding use of estimates or surrogates may go unacknowledged.

Figure 3 is output from the Yucca Mountain Project Performance Assessment (YMPPA), which shows the annual predicted dose contributions from various radio- nuclides up to one million years following repository closure under nominal conditions [26]. Major contribu- tors to biosphere concentrations one million years post repository closure are 99Tc, 237Np, 233U, 129I, 242Pu, and 36Cl. These radionuclides are also predicted to contribute the majority of dose to a reasonably maximally exposed individual (RMEI) over the same time frame.

A great deal of work has been done over the past ten years to establish site-specific concentration ratios and transfer factors for many of the long-lived radionuclides identified in the YMPPA. Napier et al. performed soil-to- plant uptake studies for 99Tc, 238Pu, and 241Am using soils and groundwater collected from sites in the northwest, southeast, and southwest United States [27]. Concentra- tion ratios were determined for onions, potatoes, alfalfa, and corn grown in each soil type and irrigated with groundwater from the corresponding source. Compari- sons between the site-specific concentration ratios and their generic counterparts contained in existing compen- dia led the authors to conclude that “Generic concentra- tion ratios are of limited use in site-specific dose analy- sis”. In addition, the assumption that a plant will exhibit linear uptake of a nutritional element or its analog may not be valid. For example, CRs determined for 99Tc were very high—as much as several hundred, depending on the combination of soil and plant. Technetium can mimic sulfur physiologically, and in its most common far-field oxidation state (+7), it is highly water soluble. Regional variations in soil-to-plant uptake must be addressed with site-specific determinations of CR and transfer factors in order to reduce uncertainty in dose predictions. Soil-to- plant uptake studies performed for 237Np and 125I in al- falfa, corn, and potatoes led to similar conclusions [19]. Soil and groundwater samples were obtained from sites in the northwest, southeast, and southwest United States and used to grow crops of each type. Significant differ- ences in iodine uptake were observed between plant spe- cies and crop types. The CRs generated by the study for both 237Np and 125I were substantially larger than the ge-

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Figure 2. Data sources for determining concentration ratio by element (data from IAEA TECDOC 1616) [14].

Figure 3. Contributions to total mean annual dose to a RMEI from individual radionuclides over 1 × 106 years, based on nominal conditions (no geological disturbance or human intrusion into the repository). A RMEI would rely exclusively on contaminated groundwater pumped to the surface for irrigation of crops and watering of livestock. Data from [28].

neric CRs typically used in performance assessments. Both studies underscore the requirement of site-specific data for meaningful dose analysis near waste repositories

and decommissioned sites. 36Cl is a major isotope of concern in the YMPPA, and

a close examination of CR and TF literature for 36Cl illu-

After TECDOC 1616: Number of Records of Soil: Plant Transfer Factors for Artificial Radionuclides 0 500 1000 1500 2000 2500 3000 3500

Cs Sr Co Mn Zn Am Np Cm I Cl Ce Ni Pu Ru Tc Pm Sb Cd La Fe Ag Y Ca Zr Cr Na Ba Nb P Eu Cu Te Se

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strates some of the problems associated with many model input values currently in use. This isotope is a neutron activation product of 35Cl, which is present in small quantities in graphite, cladding, nuclear fuel, and other sources. It is persistent, with a half-life of just over 300,000 years, and it is highly mobile in the environment as chloride anion. In a comprehensive literature review for this isotope, no studies were found that addressed foliar interception of 36Cl by crops irrigated with groundwater containing it [28]. Only scattered data was obtained for foliar absorption of 36Cl. The data that was obtained was of questionable pedigree. In “A Compen- dium of Transfer Factors for Agricultural and Animal Products” (PNNL-13421), Staven et al. list a CR of 70 for chlorine in leafy vegetables based on root uptake [25]. The primary reference given for this value is an older report that indicates the CR was obtained indirectly by assuming an average chloride soil concentration of 100 ppm, while the reported range of concentrations in plants was 2000 to 23,000 ppm [29]. This estimate was in- cluded because the values calculated based on empirical data were judged to be unusable. A CR of 2.1 in sweet clover was obtained from Furr et al. [30], while other studies report CR values between 18 and 377, depending on soil and plant type [31,32].

The compendia of generic concentration ratios and transfer factors currently in use have significant gaps and inadequacies. For many of the longest-lived components of nuclear waste, very little data exists. Generic CR and TF values that are available for these radionuclides are frequently characterized by high uncertainties and dubi- ous pedigrees. Experimentally determined site-specific CR and TF values for several sites in the US have been published recently. While their uncertainties are gener- ally lower, they are by definition best suited for site-spe- cific modeling. Significant differences in uptake result

from physical and chemical differences among soils and water sources. Dose assessments performed with model- ing software—whether they are for waste repositories, decommissioned sites, or emergency response—should rely on high-quality and experimentally determined input values. Much work remains to be done to increase the quantity and quality of CR and TF data used in modeling applications. This can only be accomplished with robust radionuclide uptake studies.

5. Why Does It All Matter? Ultimately, to ensure protection of the ecosystems which receive anthropogenic radioactivity releases, we must have the tools to determine what doses are being deli- vered and the knowledge of what doses produce the endpoints of concern.

How well can we determine absorbed dose to NHB that exist in spatially and temporally varying radiation fields? The endpoints of concern are a matter of two va- riables: how sensitive is a given organism, and what level of deleterious effects is acceptable? The most sensitive taxa (e.g. mammals, birds) have many regulations in place that focus on preventing individual level effects. Sessile organisms are among the easiest organisms for which to calculate dose. However, they are also generally far more radio-resistant than other organisms, with the exception of trees (see Figure 4). This means that to meet guidelines in a radioecology protection program with endpoints similar to other environmental protection programs, we must be able to accurately determine doses and dose rates for mobile organisms moving through a spatially (and often, temporally) varying radiation field, with likewise varying contamination levels.

This introduces challenges that to date have been ad- dressed to some degree. The simplest of these operate

Figure 4. Ranges of observed lethal dose thresholds for various taxa in cGy [1].

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simply via CRs as discussed earlier, to convert a soil measurement into estimated contamination levels of all organisms in the vicinity. This simplified approach is easily extended to apply to temporal variation, as organ- isms are simply assumed to instantaneously reach the published CRs. With the orders of magnitude variation in CRs and the need for site-specific calculations, this ap- proach leaves such a great deal of uncertainty that trans- lates into far more stringent regulations on environmental contamination than may truly be necessary to protect the ecosystem in question.

The next higher approach is to apply a network model for the food web and various medium-to-organism trans- fers. This is ideal for temporal variability as the transfer model already incorporates rate terms. The POSEIDONR model [30] has accurately predicted organism concentra- tions using this approach for the area around Fukushima, Japan, including the increased biota concentrations in 2012 that surprised many other researchers. Spatial va- riability here is addressed by using physical compart- ments large enough that all organisms may be treated as sessile with respect to that compartment. Mammals and birds, being the likely drivers of endpoints of concern, throw a wrench into the works with the large-compart- ment approach. The large spatial movements associated with many birds, marine mammals, and some terrestrial mammals extending beyond the range where physical compartments are still small enough to describe the phys- ical processes that produce spatial contamination patterns. In the marine environment, even reptiles and fish can have spatial movements greater than the size of features in the radiation or contamination distribution. When we speak of reproductive impacts, fish may be the most sen- sitive taxa in the marine environment [33], making a so- lution to their migration patterns especially pertinent to marine ecosystem protection.

Presently, our regulatory restrictions are based more loosely on population level effects, which introduce con- siderable leeway in the level of spatial variability detail we need. Rather than needing to describe movement pat- terns of individuals, we simply need a spatial occupation factor description. This is much easier to determine via routine surveys of the number of organisms present at each site, whereas individual level protection necessitates individual level movement description (e.g. radio tag studies). Determining external doses through such an approach is entirely feasible, but internal dose assess- ment is more challenging. CRs have large uncertainties but are easy to apply, which is why they remain a part of practices today. Food-web transfer models with spatial patterns for each species in the web would necessitate models that track spatially distinct communities that may be grazed by more mobile predators. However, with data on diet, transfer factors, and biological half-lives such an

approach is computationally possible. Doing so for an individual-level protection scheme would not, but a combination of these approaches (individual level for species of concern, population level for other food web components) may very well be with sufficient movement pattern description, be in the form of a function or as a randomly sampled collection of real-life recorded spatial movements.

Our measure of dose to wildlife remains fairly simplis- tic. In humans, we have substantial medical data upon which to weight exposures to different organs as well as weight different types and energies of radiation. Human protection focuses on stochastic effects (mainly cancer) associated with acute exposures. NHB protection de- pends on chronic exposures that produce largely deter- ministic effects. While there has been much written on the topic, we do not yet have a consensus on the appro- priate NHB weighting factors to use for different radia- tion types and energies [34].

The field of radioecology is rapidly expanding, its re- levance to humans becoming more apparent as humans continue to rely on the use of ionizing radiation to im- prove their lives. From handling spent fuel or decommis- sioning of former nuclear power plants to medical iso- topes and industrial radiography sources, we have a mul- titude of potential environmental consequences to con- sider from these uses. Radioecology aims to ensure we reap all the uses we’ve found for these technologies without sacrificing related ecosystems in the process.

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