Anthropogenic radionuclides in Antarctic biota – dosimetrical considerations

Journal of Environmental Radioactivity 213 (2020) 106140

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Anthropogenic radionuclides in Antarctic biota – dosimetrical considerations K.M. Szufa a, b, *, J.W. Mietelski b, M.A. Olech c, d, A. Kowalska e, K. Brudecki b a

Institute of Physics, University of Silesia, 75 Pułku Piechoty 1, 41-500, Chorz� ow, Poland Institute of Nuclear Physics, Polish Academy of Sciences, Radzikowskiego152, 32-342, Krak� ow, Poland c Institute of Botany, Jagiellonian University, Kopernika 27, 31-501, Krak� ow, Poland d Institute of Biochemistry and Biophysics, Department of Antarctic Biology, Polish Academy of Sciences, Pawi� nskiego 5a, 02-109, Warszawa, Poland e Faculty of Geoengineering, Mining and Geology, Wrocław University of Science and Technology, Wybrze_ze S. Wyspia� nskiego 27, 50-370, Wrocław, Poland b

A R T I C L E I N F O

A B S T R A C T

Keywords: Cesium Strontium Americium Doses to biota The Antarctic

The article presents results of the research on artificial radionuclides (137Cs, 90Sr, 241Am) in the Antarctic environment. Samples of 12 species from the marine environment: Pygoscelis adeliae, Pygoscelis papua, Macro­ nectes giganteus, Pagodroma nivea, Catharacta antarctica, Leptonychotes weddellii, Mirounga leonina, Harpagifer antarcticus, Chaenocephalus aceratus, Nacella concinna, Himantothallus grandifolius, Iridaea cordata (bones, feathers, soft tissues, eggs’ shells of birds, bones, skin, fur of mammals, fish, mollusks’ soft tissues and shells, algae) and samples of 4 species from the terrestrial environment: Sanionia uncinata, Usnea antarctica, Usnea aurantiaco-atra, Deschampsia antarctica (mosses, lichens, grass) were investigated. Differences in the accumula­ tion of 137Cs between marine and terrestrial ecosystem were shown, which are mostly due to conservatism of mosses and lichens and active removal of cesium by animal body. Furthermore discrepancy between mosses and lichens in the radioceasium accumulation was statistically proven with the additional use of Neutron Activation Analysis. Moreover, the internal weighted dose rates assessment was prepared using the ERICA Tool. The dose rates were relatively low, not exceeding several dozen nGy/h. Nonetheless, one species – Pagodroma nivea, was significantly outstanding due to the highest weighted dose rate it is burdened with.

1. Introduction The Antarctic is the coldest and the windiest continent. Harsh environmental conditions have an influence on the low species diversity of both plants and animals. There are only two native species of vascular plants: Deschampsia antarctica and Colobanthus quitensis, the dominant organisms on the Antarctic land are mosses and lichens. They grow in places free of snow cover, which occupy about 2–5% of the Antarctic surface. The occurrence and diversity of marine mammals (seals and wheals) and birds (penguins and flying species) are dependent on food accessibility (Dodds, 2012; Olech, 2004). From the 1950s, as a result of an international consensus, the Ant­ arctic has been considered to be the common good of all humanity. It was expressed in the Antarctic Treaty (signed by 53 countries), docu­ ment that establishes freedom of scientific research in the Antarctic. The treaty completely forbids any actions with nuclear materials, nuclear weapons tests or radioactive waste storage. The entire article V in the

Antarctic Treaty is devoted to this issue (https://www.ats.aq). However, along with the sea currents and the air mass movement radioactive debris reach the Antarctic ecosystems. The origin of anthropogenic radionuclides found in domestic ecosystems is global fallout (Szufa et al., 2018; Mietelski et al., 2008, 2000, Giuliani el al. 2003, Jia et al., 2000, 1999; Godoy et al., 1998; Roos et al., 1994) with some distinctive traces of French nuclear tests on Polynesia (Szufa et al., 2018; Arienzo et al., 2016; Koide et al., 1985), and American satellite accident with radioisotope thermoelectric generator on board (238Pu input) (Thakur et al., 2017). The aim of this study was to investigate activity concentration of 90 Sr, 137Cs, 241Am in the Antarctic organisms from both terrestrial and marine ecosystems. 238,239þ240Pu results of the same sample set have been already published in Szufa et al. (2018) where plutonium ratios variances were described; on these basis sources of radioactive contamination in the Antarctic region were discussed. Second purpose of the present work was to estimate the weighted dose rates from internal

* Corresponding author. Institute of Physics, University of Silesia, 75 Pułku Piechoty 1, 41-500, Chorz� ow, Poland. E-mail address: [email protected] (K.M. Szufa). https://doi.org/10.1016/j.jenvrad.2019.106140 Received 10 April 2019; Received in revised form 4 November 2019; Accepted 12 December 2019 Available online 23 December 2019 0265-931X/© 2019 Elsevier Ltd. All rights reserved.

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Journal of Environmental Radioactivity 213 (2020) 106140

exposition resulted from the accumulation of 90Sr, 137Cs, 238,239þ240Pu and 241Am in the Antarctic biota. To achieve these goals, different Antarctic matrices were analyzed using alpha and gamma spectrometry and liquid scintillation counter. Dosimetric calculations where per­ formed with the ERICA Tool (Brown et al., 2008).

calcium oxalates containing plutonium and americium isotopes at pH~3 and containing strontium isotopes at pH~6 were performed. The pro­ cedure is described in detail in Mietelski et al. (2011, 2006). The rest of samples were mineralized using concentrated hydrofluoric, nitric, hy­ drochloric and boric acids (Mietelski and Wąs, 1995). Plutonium was extracted using anion exchange chromatography using Dowex 1 � 8 resin (Sigma-Aldrich) (Mietelski et al., 2016; Łokas et al., 2010; Mie­ telski and Wąs, 1995) which was preceded by adjustment to the þ4 oxidation state of Pu (La Rosa et al., 1992). Subsequent separation of strontium directly from the Dowex 1 � 8 effluents (in 8 M HNO3 in case of samples free of phosphates), or prepared from the oxalates (pH~6 fraction) by decomposition in concentrated HNO3 diluted then to 4 M HNO3, took place on column filled with Sr-Resin (Eichrom). Wider description of this method has been published already in Gaca et al. (2006), Mietelski et al. (2016, 2011, 2006), Łokas et al. (2010). Prior to americium separation using Dowex 1 � 8 resin and methanol-acid so­ lutions the samples were pre-concentrated by subsequent oxalates and iron hydroxides precipitation according to the procedure described by Holm et al. (1979) with our small modifications (Mietelski et al., 2016). Plutonium and americium spectrometric sources were prepared by the NdF3 micro coprecipitation method (Sill, 1987) using 100 nm pore diameter membrane filters (Eichrom) and measured using different alpha spectrometers (Silena Alpha Quattro, Ortec Alpha Duo or Can­ berra 7401). The acquisition time was around 7 days, the background count rate for given peak was estimated on the basis of averaged blank sample results analyzed in parallel (one blank for each twelve samples). Effluents containing strontium were purified from lead tracers (Gaca et al., 2006); samples’ volumes were adequately reduced, mixed with Gold Star LT2 scintillation cocktail and measurements using Wallac 1414 Guardian LSC spectrometer were performed. Recovery of 85Sr was determined using HPGe low background gamma spectrometer (Mie­ telski et al., 2016, 2011; Łokas et al., 2010).

2. Material and methods Research material comprises fifty nine samples from the marine environment and forty nine samples from the terrestrial environment (see Table 1) which was gathered between 1980 and 2015 during series of Polish Academy of Sciences expeditions. More information about the samples may be found in Szufa et al. (2018) (supplementary data), where 238,239þ240Pu concentrations were published. Animals’ samples were collected post mortem. The organisms were not harvested in fresh nor frozen state; dry animal remains had been collected as it facilitated further transport and storage. In most cases samples originate from King George Island (South Shetland Islands), the rest were obtained on Deception Island (South Shetland Islands), Penguin Island (South Shetland Islands), Peter I Is­ land, Antarctic Peninsula and the continental Antarctic (Schirmacher Oasis) (Figs. 1 and 2). 2.1. Measurements and radiochemical procedure 137

Cs measurements were performed using low-background gamma spectrometer with three HPGe detectors shielded with 10 cm of lead with inner lining of 2 mm cadmium and 20 mm of pure copper (10% efficiency, FWHM ¼ 1.9 keV at 1332 keV by Silena, 15 and 25% relative efficiency, 2.3. keV FWHM at 1332 keV the latest both manufactured by in Institute of Nuclear Physics workshop). Full energy peak efficiency calibration routinely used in our laboratory and positively verified in the number of intercomparison exercises was applied in 137Cs activity determination. Time of measure was about 4 days. Terrestrial samples were prepared by 24 h drying at 75 � C and later homogenization. Marine samples were ashed at 400 � C, and then if needed, bones and soft tissues were separated (for mammals and birds samples). More information about measurement and sample treatment may be found elsewhere (Mietelski et al., 2008, 2000). The Laboratory belongs to ALMERA network (Osvath et al., 2016) and has introduced ISO 1702 standards accreditation by Polish Accreditation Center. After determining 137Cs concentrations 90Sr, 238,239þ240Pu, 241Am where chemically separated using combined sequential method (Mie­ telski et al., 2016; Łokas et al., 2010). All samples were ashed at 600 � C, then tracers: 85Sr, 242Pu, Am243 were added. Bones, eggs shells and mollusks shells were dissolved in 9 M HCl. Subsequently precipitation of

2.2. Internal weighted dose rate estimation The internal weighted dose rates were calculated using the ERICA Tool (version 1.2 available from www.erica-tool.com/erica/download/, download February 2018). The ERICA dose assessment approach is based on dose conversion coefficients (DCC) (DCCint for the internal dose rate, DCCext for the external dose rate - not analyzed in the present article) which are defined as absorbed dose rates (mGy/h) per unit ac­ tivity concentration in organism (Bq/kg fw) (or medium (Bq/kg dw) for external exposition). Weighted dose rates are estimated by the imple­ mentation of the weighting factors: 10 for alpha, 3 for low energy beta (Eβ<10 keV) and 1 for beta (Eβ>10 keV) and gamma radiation (Brown et al., 2008; Ulanovsky et al., 2008). Despite the application of the ra­ diation weight coefficients, Gy is still the valid unit for doses to non-human biota, unlike in radiological protection of human where Sv was introduced (ICRP, 2017). In this assessment Tier 2 was applied (Brown et al., 2008). The Erica assessment gives a possibility to perform in a three-tiered pattern, ac­ cording to level of concern, with the highest level–Tier 3–being the most specific and complex. Tier 2 allows entering biota activity concentra­ tions and creating new reference organism in contrary to Tier 1 which is the most conservative and least flexible (Brown et al., 2008). The default reference organisms were used for the geometries and dimensions of moss (lichen and bryophytes), lichen (lichen and bryophytes), grass (grasses and herbs), algae (macroalgae) and mollusk (bivalve mollusk). The rest of reference organisms were created as user defined organisms (the add organism function is available on Tier 2 and 3), the dimensions of these are presented in Table 2. The input data for the ERICA Tool was mean activity concentrations of 90Sr, 137Cs, 238,238þ240Pu, 241Am in each species. The DCCint are the same for both plutonium isotopes 239Pu and 240Pu, so the radiation hazard will be equal for both radioisotopes. Consequently, as 239Pu and 240 Pu cannot be separated in alpha radiation spectrum (Eα ~ 5160 keV

Table 1 Research material: species with short description of samples. marine ecosystem Himantothallus grandifolius (algae): thallus Iridaea cordata (algae): thallus Pygoscelis adeliae (penguin): bones, feathers, soft tissues, egg shells Pygoscelis papua (penguin): feathers Macronectes giganteus (flying bird): bones, feathers, soft tissues Pagodroma nivea (flying bird): bones, feathers, soft tissues Catharacta antarctica (flying bird): bones, feathers, soft tissues Leptonychotes weddellii (seal): bones, skin and fur Mirounga leonina (seal): bones, skin and fur Nacella concinna (mollusc): soft tissue, shells Harpagifer antarcticus (fish) Chaenocephalus aceratus (fish) terrestrial ecosystem Sanionia uncinata (moss) Usnea antarctica (lichen) Usnea aurantiaco-atra (lichen) Deschampsia antarctica (grass)

2

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Journal of Environmental Radioactivity 213 (2020) 106140

Fig. 1. Places of samples collection: A– Schirmacher Oasis, B – King George Island, C – Deception Island, D– Antarctic Peninsula (Brown Station), E Peter I Island. Locations of prior expeditions (referred in the paper): B – Mietelski et al. (2000), 2008, B&C (South Shetland Islands) – Schuller et al. (2002), Godoy et al. (1998), Baeza et al. (1994), Roos et al. (1994), F –Desideri et al. (2003), Giuliani et al. (2003), Jia et al. (2000), 1999, Marzano et al. (2000), Godoy et al. (1998).

Fig. 2. Places of samples collection on King George Island.

Pu, Eα ~ 5170 keV for 240Pu, peaks in spectrum overlap), Pu concentrations were used for the calculation, applied into the program as 239Pu concentration. Due to that the data set included censored data (results below the detection limit) activity concentration means were calculated using proper estimating summary statistics for censored data (Wood et al., 2011) or the substitution method – replacing

for

239

the LOD value with LOD/2 value. When a data set contained no more than 80% of measurements below the limit of detection the adequate estimating summary statistics for censored data were used to calculate the mean value. In other cases the substitution method was used and arithmetic mean was calculated. The results of the average concentra­ tion of radionuclides were then converted to the concentrations on basis

230þ240

3

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Journal of Environmental Radioactivity 213 (2020) 106140 90

Sr fallout resulted from the nuclear tests has been deposited within the Southern Hemisphere (UNSCEAR, 1982) and Chernobyl fallout does not affect the Antarctic area (Schuller et al., 2002). The average concentration of 90Sr in the research material from the marine environment is 9.49 Bq/kg and standard deviation on the mean is 3.93 Bq/kg. The lowest concentration: 1.75 � 0.56 Bq/kg was ob­ tained in feathers from Macronectes giganteus (southern giant petrel) body, the highest: 46.41 � 2.46 Bq/kg in Pagodroma nivea (snow petrel) wing (soft tissues and bones). These results correspond with data pub­ lished so far (Jia et al., 2000; Mietelski et al., 2008). In the Ross Sea (mark F on Fig. 1) strontium concentrations in algae were between 3 and 9 Bq/kg dw (Jia at al. 2000) or below the detection limit (Desideri et al., 2003). However, in the algae from the Admiralty Bay (indenting the southern coast of King George Island, point 23 on Fig. 2) concentration of 90Sr ranges from 0.8 to 3.8 Bq/kg (Mietelski et al., 2008). Similar level of 90Sr was discovered by Mietelski et al. (2008) in Nacella concinna, Antarctic birds and mammals. The average concentration of 90Sr in the terrestrial matrices is equal to 3.98 Bq/kg with standard deviation of the mean 0.47 Bq/kg. This result is representative for the two main groups constituting the terrestrial ecosystem in this work: mosses with the average concentra­ tion of 90Sr 3.99 Bq/kg with standard deviation of the mean 0.86 Bq/kg and lichens with the average concentration 3.97 Bq/kg and standard deviation of the mean 0.53 Bq/kg. Minimal concentration in all terres­ trial samples: 0.83 � 0.22 Bq/kg was discovered in Usnea antarctica sample, maximal (9.76 � 1.31 Bq/kg) was measured in moss sample. These results are similar to data published so far (Mietelski et al., 2008, Desideri et al., 2003, Guliani et al. 2003; Jia et al., 2000, 1999). Among marine samples, concentration of 137Cs above the detection limit was detected only in two samples: in soft tissues and feathers from wing of snow petrel and in bones of Pagodroma nivea (different indi­ vidual). Such a result may be explained by the intensive washout by sea waters and the effective removal of radiocesium by living organisms, the ecological half-life of 137Cs is considered to be shorter than two years (Tanaka et al., 2018; Matsumoto et al., 2015; Iwata et al., 2013). Therefore, it is problematic for the results obtained to refer to the literature data (Mietelski et al., 2008, Desideri et al., 2003, Guliani et al. 2003; Jia et al., 2000, 1999) reporting 137Cs in Antarctic marine ecosystem. Nevertheless, those two values are comparable with cesium levels in Antarctic birds described by Mietelski et al. (2008). The mean concentration of 137Cs in terrestrial samples was 13.12 Bq/ kg with standard deviation of the mean 2.29 Bq/kg. The highest level of 137 Cs: 32.8 � 2.3 Bq/kg was found in moss sample, minimal value: 0.37 � 0.09 Bq/kg was detected in Usnea aurantiaco-atra sample. The mean result for the bryophyte samples was 16.54 Bq/kg (SDM 2.82 Bq/kg). The range of 137Cs concentrations in mosses is comparable with some literature data, especially Mietelski et al. (2000) and Godoy et al. (1999). The average concentration of radiocesium in lichens was 6.32 Bq/kg, with standard deviation of the mean 3.01 Bq/kg. It can be noticed that concentrations of cesium 137 are lower in lichen than in moss samples. The average value among bryophytes is slightly more than 2.5 times higher; the minimum concentration in mosses is nearly twice as high as the lowest result of 137Cs in lichens, similar trend applies to maximal results. As the majority of moss and lichen samples were collected on the same or nearby places (see Fig. 2 and Table 4) it can be assumed that the local variations in radiocesium fallout do not affect the results obtained. Data presented by Ross et al. (1994), who examined the deposition of 137Cs over the Antarctic, and Godoy et al. (1998) show analogous tendency. Obtained discrepancies between the results of 137Cs for mosses and lichens were statistically tested. At the 5% significance level, statistically significant result was obtained (p ¼ 0.0469). Some of the samples were examined using Neutron Activation Analysis (NAA); concentration of stable cesium (mg/kg) in mosses (Sanionia uncinata) and lichens (Usnea �z et al., 2018). antarctica, Usnea aurantiaco-atra) were analyzed (Mro These results also showed significant difference between mosses and

Table 2 Reference organisms created by the add organism function in the ERICA Tool. Animals’ characteristic chosen according to De Roy et al., (2013), Soper (2008), Riffenburgh (2007) and Jefferson et al., (1993). Organism

dimensions [cm]

mass [kg]

Pygoscelis adeliae Pygoscelis papua Macronectes giganteus Pagodroma nivea Catharacta antarctica Mirounga leonina Leptonychotes weddellii Harpagifer antarcticus Chaenocephalus aceratus

70 � 40 � 40 90 � 40 � 40 90 � 30 � 30 30 � 20 � 20 60 � 20 � 20 400 � 100 � 100 300 � 90 � 90 8�4�3 50 � 20 � 20

3.5 6 5.4 0.25 2.3 1000 400 0.2 3.7

Table 3 Data on the deposition of 90Sr, 137Cs, Northern Hemisphere perspective.

241

Am in terms of Bq/m2, Southern vs.

Southern Hemisphere

Northern Hemisphere

Reference

0.54⋅103 0.35⋅103 (60� –70� ) 0.22⋅103 (70� –80� ) 0.08⋅103 (80� –90� )

2.14⋅103 1.74⋅103 (60� –70� ) 0.68⋅103 (70� –80� ) 0.26⋅103 (80� –90� )

Integrated deposition density through 1980, UNSCEAR, 1982

137

0.86⋅103 0.56⋅103 (60� –70� ) 0.35⋅103 (70� –80� ) 0.13⋅103(80� –90� )

3.42⋅103 2.78⋅103(60� –70� ) 1.09⋅103 (70� –80� ) 0.42⋅103 (80� –90� )

Integrated deposition density through 1980, UNSCEAR, 1982

241

4.2 7.0 (40� –50� ) 0.56 � 2.25 (King George Island)

17 25 (40� –50� ) 3.18 � 11.3 (Greenland)

Integrated deposition density þ 241Pu decay through 1980, UNSCEAR, 1982 Ross et al. 1994 Eriksson et al. (2014)

90

Sr

Cs

Am

of initial mass by means of the initial mass to ashes or dry mass ratios (calculated at the measurement preparation stage). Values obtained in this way were used to determine the weighted dose rate. It should be mentioned, that the ERICA Tool assumes that the input data will be on basis of fresh mass, meanwhile, the initial weight of the samples is not the same as the fresh mass. The research material at the initial stage was already somewhat dried up; the remains of the animals were obtained post mortem, when some of water had already evaporated from organ­ ism. Therefore, the presented dose rate assessment is burdened with an overestimation, or in other words, the dose rates are characterized by high conservatism. This remark also applies to the terrestrial samples; due to the long storage time (the oldest sample was collected in 1980) water loss rate is difficult to estimate. 3. Results and discussion 3.1. Concentrations of

90

Sr,

137

Cs,

241

Am

90

Sr, 137Cs, 241Am activity concentrations in marine samples are presented on basis of ash weight, in terrestrial samples of dry weight. All results obtained are presented in Tables 4 and 5. Radioactive decay correction was applied (activities were calculated for the day of the sampling). The summery statistics described below (in subsection 3.1): the arithmetic mean and the standard deviation of the mean were calculated on basis of results above detection limits. Before presenting the results obtained it may be beneficial to intro­ duce the reader to a bigger and comparative perspective showing a difference between the Southern and the Northern Hemisphere in terms of deposition data. Brief comparison is presented in Table 3. It is also worth to keep in mind that, approximately 25% of the global 137Cs and 4

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Journal of Environmental Radioactivity 213 (2020) 106140

Table 4 137 Cs, 90Sr, 241Am concentrations (Bq/kg), collection place (codes accordingly to maps in Figs. 1 and 2) and sampling date of marine samples; B- algae, H – Harpagifer antarcticus, CH – Chaenocephalus aceratus, MT – Mirounga leonina (skin and fur), NM – nacella concinna (soft tissue), NS – N.concinna (shells), WB –Leptonychotes weddellii (bone), WT –L. weddellii (skin and fur), PE – Pygoscelis adeliae (egg shells), AB – Pygoscelis adeliae (bones), AT – P.adeliae (feathers and soft tissues), CB –Catharacta antarctica (bones), CT –C.antarctica (feathers and soft tissues), GB –Macronectes giganteus (bones), GT –M.giganteus (feathers and soft tissues), NB – Pagodroma nivea (bones), NT – P.nivea (feathers and soft tissues), N – P.nivea (wing), PF – Pygoscelis papua (feathers after moulting). sample

137

B1 B2 B3 B7 B8 B9 H1 CH1 MT1 NM1 NS1 WB2 WT1 WT2 PE1 PE2 PE4 AB1 AB2 AB4 AB5 AB6 AB7 AB8 AB9 CB1 CB2 CB3 CB4 GB2 GB3 GB4 GB5 NB1 NB2 NB4 AT1 AT2 AT3 AT4 AT5 AT6 AT7 AT8 CT1 CT2 CT3 CT4 GT1 GT2 GT3 GT4 GT5 N3 NT1 NT2 PF1 PF2 PF3

<80.9 <87.5 <65.4 <5.66 <1.11 <2.92 <28 <30.3 <2.53 <4.15 <0.78 <11.1 <5.12 <41.3 <1.36 <0.87 <1.74 <2.33 <4.77 <0.43 <3.24 <2.17 <0.92 <1.38 <0.41 <2.41 <2.85 <3.67 <12.2 <5.49 <0.64 <0.85 <3.06 <3.88 <4.06 6.76 � 2.68 <71.4 <108 <2.69 <15 <13.8 <2.72 <3.5 <21.6 <5.44 <14.7 <13.6 <25.9 <5.83 <24.3 <6.79 <8.2 <16.9 <28.9 <7.66 18.6 � 3.4 <39.2 <60.6 <57.2

Cs

90

241

Sr

<1.72 <2.02 3.73 � 2.2 <1.47 <1.05 <1.24 <5.52 <6.34 <1.72 <1.69 <0.84 <1.17 <1.86 <9.78 <0.07 <1.9 <1.29 <2.23 <3.75 N/A 2.89 � 0.5 <1.02 <0.7 <0.58 <0.52 <2.52 <0.74 <1.35 <1.37 2.18 � 0.46 <7.74 <1.42 N/A 5.02 � 0.74 <0.79 10.12 � 0.56 <3.67 <7.55 <0.63 <1.22 <1.17 N/A 2.67 � 0.24 <2.15 <2.46 <2.02 <1.56 <1.69 1.75 � 0.56 <3.72 2.85 � 3.02 <1.42 <1.48 46.41 � 2.46 <1.91 11.92 � 0.74 14.85 � 2.67 <7.15 <12.06

Am

<0.004 0.092 � 0.018 0.041 � 0.005 0.15 � 0.02 0.011 � 0.002 <0.02 <0.12 <0.08 <0.04 <0.019 0.029 � 0.004 <0.017 <0.03 <0.17 <0.002 N/A <0.005 <0.028 0.008 � 0.001 <0.002 0.04 � 0.01 <0.01 <0.055 0.016 � 0.003 <0.023 <0.046 <0.007 <0.019 <0.017 <0.022 <0.002 <0.004 <0.22 <0.039 0.13 � 0.02 0.25 � 0.02 <0.12 <0.09 0.016 � 0.004 0.016 � 0.002 0.017 � 0.004 <0.015 <0.011 N/A <0.095 N/A <0.024 <0.028 <0.018 <0.018 0.033 � 0.003 <0.006 <0.025 2.384 � 0.179 <0.019 0.33 � 0.03 <0.08 <0.21 <0.27

sampling place

sampling date

B. 1 B. 1 B. 1 B. 1 B. 1 B. 1 B. 23 B.23 B. 6 B. 2 B. 2 B. 3 B. 3 B. 3 B. 5 B. 5 B. 3 B. 8 B. 8 B. 8 B. 11 B. 3 B. 3 B. 3 B. 3 B. 3 B. 14 B. 4 B. 18 B. 5 B. 3 B. 3 B. 19 A A A B. 8 B. 8 B. 8 B. 8 B. 11 B. 3 B. 3 B. 3 B. 3 B. 14 B. 4 B. 18 B. 5 B. 5 B. 5 B. 5 B. 19 A A A B. 5 B. 5 B. 5

20.12.2006 20.12.2006 20.12.2006 20.12.2006 20.12.2006 20.12.2006 08.02.2002 08.02.2002 21.01.2007 10.02.2009 10.02.2009 31.12.2008 31.12.2008 31.12.2008 22.02.2010 29.12.2008 22.02.2010 10.01.2006 10.01.2006 10.01.2006 22.02.2010 03.02.2010 03.02.2010 03.02.2010 15.02.2002 04.01.2015 19.12.2005 09.01.2006 22.02.2009 09.01.2006 09.01.2006 09.01.2006 01.02.2010 21.01.2004 21.01.2004 21.01.2004 10.01.2006 10.01.2006 10.01.2006 10.01.2006 22.02.2010 03.02.2010 03.02.2010 03.02.2010 04.01.2015 19.12.2005 09.01.2006 22.02.2009 09.01.2006 09.01.2006 09.01.2006 09.01.2006 01.02.2010 21.01.2004 21.01.2004 21.01.2004 20.02.2006 06.02.2007 22.02.2010

One may notice, that the activity concentrations of 90Sr in some cases is higher than activity of 137Cs, which is in the contrast to previous re­ searches like Jia et al. (2000, 1999) or Marzano et al. (2000). Firstly, it must be noted, that for the many samples 137Cs detection limits are high, which is mostly caused by the small masses of the samples; e.g. maximal mass of feathers after ashing do not exceed 0.03 kg, when minimal sample mass was 0.001 kg. As a consequence, high levels of the

lichens at the 5% significance level (p ¼ 0.015). Therefore, it can be argued that the differences between 137Cs (or cesium in general) accu­ mulation by Usnea antarctica, Usnea aurantiaco-atra species and Sanionia uncinata species result from the individual characteristics of these spe­ cies. Nevertheless, it should be added that Sanionia uncinata grows on soil and contamination with its particles may also affect the results ob­ tained; Usnea grows on rocks and stones (Olech, 2004; Ochyra, 1998). 5

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Table 5 137 Cs, 90Sr, 241Am concentrations (Bq/kg), collection place (codes accordingly to maps in Figs. 1 and 2) and sampling date of terrestrial samples; SU – Sanionia uncinata; UA – Usnea antarctica, UA … A – Usnea aurantiaco-atra; D – Deschamsia antarctica. sample

137

90

SU1 SU4 SU7 SU8 SU12 SU14 SU16 SU18 SU20 SU25 SU28 SU29 SU30 SU32 SU33 SU34 SU35 SU36 SU37 SU38 SU39 SU40 SU41 SU42 SU43 SU44 SU45 UA1 UA3 UA4 UA6A UA7A UA8A UA9 UA10 UA11 UA12 UA13 UA14 UA15A UA16 UA17A UA18 UA20 UA21A UA22A UA23 UA24 D1

32.8 � 2.3 <6.77 <3.68 7.75 � 0.60 <27 <1.18 19.8 � 0.9 <1.84 16.8 � 1.5 <12.1 <5.39 <6.77 <8.27 <6.72 <8.56 5.61 � 1.10 4.83 � 1.05 18.4 � 1.2 <1.68 28.6 � 2.5 17.7 � 2.9 7.32 � 1.91 <1.64 <7.33 22.4 � 3.3 <11.29 <5.73 <1.68 <1.17 <0.92 <5.84 <0.71 <1.63 <6.58 <4.23 <7.68 <6.27 3.08 � 1.21 <0.44 0.3 � 0.09 <1.7 <1.64 <1.26 6.94 � 1.47 <21.8 <2.20 <0.46 17.6 � 5.3 9.52 � 2.25

<1.62 9.15 � 1.85 1.19 � 0.38 3.69 � 0.36 6.54 � 1.25 3 � 0.59 4.16 � 0.64 0.96 � 0.22 1.66 � 0.27 9.76 � 1.31 <0.1 <1.86 1.62 � 0.19 <2.06 <2.92 <0.78 <0.71 <0.46 <1.17 N/A <1.16 <1.38 N/A <0.39 <1.17 2.68 � 0.2 3.47 � 0.67 2.94 � 0.28 3.06 � 0.34 7.42 � 0.42 1.01 � 0.29 <0.34 <0.69 <1.78 4.02 � 0.58 3.59 � 0.42 4 � 1.05 <1.07 <1.08 1.66 � 0.16 6.33 � 0.84 6.86 � 0.38 2.34 � 0.26 0.83 � 0.22 <7.26 5.58 � 0.27 4.28 � 0.35 5.61 � 0.32 <0.71

Cs

Sr

241

sampling place

sampling date

0.62 � 0.08 1.66 � 0.20 <0.059 0.06 � 0.02 0.28 � 0.06 <0.42 0.31 � 0.08 <0.35 0.22 � 0.02 0.28 � 0.04 <0.003 0.08 � 0.01 0.09 � 0.01 <0.3 N/A <0.016 <0.052 0.030 � 0.006 N/A N/A <0.051 <0.1 <0.064 0.091 � 0.015 0.26 � 0.03 0.57 � 0.06 0.14 � 0.05 0.35 � 0.02 0.18 � 0.02 0.23 � 0.02 0.58 � 0.06 0.28 � 0.03 1.24 � 0.09 0.10 � 0.02 0.19 � 0.02 <0.36 0.099 � 0.014 0.15 � 0.01 N/A 0.19 � 0.02 0.36 � 0.05 0.11 � 0.01 0.35 � 0.04 0.096 � 0.009 1.87 � 0.19 1.08 � 0.17 0.78 � 0.06 0.16 � 0.02 <0.019

B. 19 B. 13 B. 17 B. 14 B. 19 C B. 22 B. 15 B. 24 B. 24 C B. 15 B. 7 B. 20 B. 5 B. 21 B. 19 B. 18 B. 10 B. 19 B. 28 B. 9 B. 5 B. 21 B. 5 E B. 29 B. 16 B. 20 B. 12 B. 24 D B. 25 B. 28 B. 7 B. 26 B. 24 B. 21 B. 5 B. 14 B. 19 B. 24 B. 15 D B. 27 B. 9 B. 9 D B. 19

01.01.2007 16.02.2005 10.01.2007 19.12.2005 01.01.2007 10.02.2006 15.12.2005 03.01.2007 26.12.2005 16.02.2006 01.02.2006 18.12.2005 10.01.2006 05.01.2007 14.02.2002 04.01.2007 31.12.2006 23.01.2009 06.02.2006 01.01.2007 08.01.2002 26.01.2002 14.03.2015 24.01.2002 14.02.2002 12.12.2006 21.12.2007 15.12.2005 05.01.2007 07.12.2005 16.02.2006 12.12.2006 28.01.2007 16.02.2006 10.01.2006 11.03.2006 16.02.2006 04.01.2007 14.02.2002 19.12.2005 15.02.2006 26.12.2005 17.12.2005 12.12.2006. 16.02.1980 26.01.2002 26.01.2002 12.12.2006 26.12.2006

Am

detection limit are even higher then 90Sr results, thus it is doubtful that this trend would point to some processes occurring in the environment. Regarding to the bone samples it is a well-known fact that strontium as a calcium analog easily accumulates in the bones. In the case of mosses and lichens, similar differences between 90Sr and 137Cs content were also observed by Mietelski et al. (2008). Jia et al. (2000, 1999) and Marzano et al. (2000) investigated biota from the different and remote Antarctic places than these analyzed in the present paper and by Mietelski et al. (2008), therefore the observed discrepancies may indicate the local variances in 90Sr deposition. The average concentration of 241Am in samples from the marine environment is 0.31 Bq/kg; standard deviation of the mean is equal to 0.16 Bq/kg. The range of results obtained is wide: from 0.008 � 0.001 Bq/kg in bones of Pygoscelis adeliae to 2.38 � 0.18 Bq/kg in the wing of Pagodroma nivea. Desideri et al. (2003), Giuliani et al. (2003) and Jia et al. (2000) presented similar results for the Antarctic marine samples. The average 241Am concentration in terrestrial samples is equal to 0.40 Bq/kg with standard deviation of the mean 0.08 Bq/kg. Maximal result was 1.87 � 0.19 Bq/kg and minimal was 0.030 � 0.006 Bq/kg. In

the moss group the mean and standard deviation of the mean were 0.39 Bq/kg and 0.12 Bq/kg, respectively. The lichen group is characterized by the average concentration of amercium at the level of 0.46 Bq/kg with standard deviation of the mean 0.12 Bq/kg. Desideri et al. (2003), Giuliani et al. (2003), and Jia et al. (2000, 1999) received slightly lower and less varied concentrations of 241Am in terrestrial samples. However, data presented by Mietelskiet et al. (2000) are comparable with the 241 Am results range in the present work. 3.2. Internal weighted dose rates The input data for the ERICA Tool in the form of average concen­ trations of 90Sr, 137Cs, 238,239þ240Pu and 241Am in analyzed species, obtained using summary statistics for censored data (or the substitution method when appropriate), were used to calculate the internal weighted dose rates. Data are presented in Tables 6 and 7. Figs. 3 and 4 show the estimated internal weighted dose rates (nGy/h). The internal weighted dose rate in the marine environment varies from 0.03 nGy/h (Mirounga leonina 238Pu) to 9.53 nGy/h (Pagodroma 6

K.M. Szufa et al.

Journal of Environmental Radioactivity 213 (2020) 106140

Table 6 Concentrations of 90Sr, 137Cs, tions in marine ecosystem.

238,239þ240

Species

90

Pygoscelis adeliae Pygoscelis papua Macronectes giganteus Pagodroma nivea Catharacta antarctica Leptonychotes weddellii Mirounga leonina Nacella concinna Harpagifer antarcticus Chaenocephalus aceratus Algae

0.36 1.48 0.45 5.88 0.20 0.51 0.15 0.20 1.38 0.61 0.31

Sr

Table 7 Concentrations of 90Sr, 137Cs, tions in terrestrial ecosystem. species

90

Mosses Lichens Vascular plant

2.88 2.97 0.33

Sr

137

238

239þ240

2.99 4.43 1.50 2.72 1.19 2.27 0.21 0.39 7.00 2.90 5.06

0.002 0.005 0.0009 0.034 0.002 0.003 0.001 0.001 0.009 0.005 0.007

0.012 0.002 0.005 0.32 0.007 0.005 0.0008 0.001 0.008 0.004 0.045

Cs

238,239þ240

137

Cs

10.1 2.41 8.7

of Antarctica), which could indicate that this place may be more contaminated than other sampling points. Apart from P. nivea, the rest of research material was collected in other places than Schirmacher Oasis; and consequently it is difficult to verify this hypothesis. In addition, the species migrates during the Antarctic winter to distant areas (Soper, 2008; Riffenburgh, 2007), thus it seems that the “place of the collection” factor does not provide an explanation for intense radionuclide accu­ mulation. Moreover, taking into account that the radioisotopes were found in the bones of Pagodorma nivea, and knowing that plutonium is not removed from bones for years (Brudecki et al., 2014), the assump­ tion, that samples may be superficially contaminated in Schirmacher Oasis may lead to the false conclusions. In the present assessment, the organism least exposed to radioactive hazard associated with man-made radionuclides is Catharacta antarctica burdened with the total internal weighted dose rate 0.75 nGy/h. It should be put forward that in this case, besides 239þ240Pu, the input data were LOD/2 values, and hence this result is an approximation with unknown uncertainty. The same problem applies to Pygoscelis papua, seals, fishes and mollusk. One general remark must be put forward here; there are sparse data published that can be used for the discussion of the dosimetrical results obtained. Especially, there are no articles about internal doses for the Antarctic biota, thus information about other parts of the world has to be used. Baeza et al. (1994) published study on the effective dose equiva­ lent rate (presented in nSv/h) on Livingstone Island (South Shetland Islands) researched using proportional counter, but such data cannot be adopted for the comparison in the present article, in particular from the methodological point of view. Similarly low dose rates from the internal and external exposure were calculated for the marine organisms off the coast of the Korean Peninsula after the Fukushima accident (Keum et al., 2013). Research conducted in China also showed a low radiation risk (internal and external) in the marine ecosystem; those results were also obtained with the ERICA Tool (Li et al., 2015). In Barents and Kara Arctic seas the internal dose rate from artificial radionuclides to marine biota is 20 � 10 9 � 30 � 10 9Gy/d (0.83 � 10 9 � 1.25 � 10 9μGy/h) (Kryshev et al., 2001). In the Yellow Sea the dose rate for fish caused by the in­ ternal 137Cs exposure ranges from one hundredth to several thousandths nGy/h (Yang et al., 2015). In the Antarctic terrestrial ecosystem the internal weighted dose rate range is 0.17 nGy/h (grass, 90Sr) � 23 nGy/h (lichen, 239þ240Pu). The total internal weighted dose rates for moss, lichen and grass are 24 nGy/ h, 41 nGy/h, 7 nGy/h respectively. Despite small differences in the ac­ tivity concentrations of 90Sr, 238,239þ240Pu, 241Am and almost doubled accumulation rate of 137Cs by mosses in relation to lichens, the latter

Pu (Bq/kg) used for dose rate estima­ Pu

Pu

241

Am

0.004 0.016 0.005 0.24 0.004 0.009 0.004 0.002 0.89 0.008 0.013

Pu (Bq/kg) used for dose rate estima­ 238

Pu

0.08 0.13 0.03

239þ240

0.44 0.76 0.15

Pu

241

Am

0.20 0.40 0.009

nivea 239þ240Pu). Because LOD/2 values have been introduced in the calculations, which for alpha and beta emitters depend on the chemical recovery, it is difficult to identify the radioisotope that would cause the highest radioactive burden. However, since 239þ240Pu was the most frequently detected isotope in the marine research material (see Szufa et al., 2018) it can be identified as a main contributor to the radiological hazard in the Antarctic marine ecosystem. Certainly, snow petrel (Pagodroma nivea) can be indicated as an organism which is burdened with the highest dose rate (total internal weighted dose rate: 22 nGy/h). When analyzing activity concentrations of the artificial radionuclides in the marine organisms, one can note that P. nivea accumulates more ra­ dionuclides than other organisms, it results in higher internal weighted dose rates. The observed phenomena may indicate that P. nivea is a species of the Antarctic birds particularly exposed to contamination. However, research on the presence of mercury in the trophic chain in the Antarctic marine environment did not proof this (Bargagli et al., 1998). Snow petrels are predators and scavengers, often follow research vessels that can feed on waste from them (Soper, 2008; Riffenburgh, 2007). It is therefore likely that their diet is the source of these contaminations, especially that radioactive debris was found in the bone samples. All snow petrel samples were collected in Schirmacher Oasis (the continent

Fig. 3. Dose rates for Antarctic marine organisms. 7

K.M. Szufa et al.

Journal of Environmental Radioactivity 213 (2020) 106140

Fig. 4. Absorbed dose rates for Antarctic terrestrial organisms.

species receives higher doses. This is due to alpha emitters which cause the highest radiation burden. The aforementioned weighting factor of alpha radiation used in the ERICA tool for calculating the total weighted dose rate is equal to 10. Thus, initially small differences are finally multiplied. In comparison with the alpha emitters, the impact of 137Cs on mosses and lichens is much less significant, despite the contribution of beta radiation, which is emitted during the decay of cesium nucleus. In other parts of the world, the dose rates for terrestrial biota differ from those obtained in the present article. In western Serbia, the dose rate for mosses and lichens caused by 137Cs is three orders of magnitude higher. Birds from Serbia, as a result of the internal exposure to 137Cs � �c and Dragovi�c, 2018). In Upper Silesia, receive 1.07 � 10 2μGy/h (Cuji a mining region in Poland, radiation burden caused by NORM (Naturally Occurring Radioactive Materials) for vascular plants is even higher: 0.21 � 2.63 μGy/h (Michalik, 2008). The game animals in Finland due to the internal exposure to 137Cs receive from a few hundredths to several μGy/h (Vetikko and Kostiainen, 2013). These results are three orders of magnitude higher than these from the present paper. Taking into consideration that 137Cs is actively removed from animal organ­ isms, and in mosses and lichens is passively accumulated with possible washing out by precipitation as the main removal pathway, the differ­ ence is very large. Moreover, this discrepancy caused by 137Cs contri­ bution is a consequence of the Chernobyl contamination influence in Europe, which is not found in the Antarctic areas (Schuller et al., 2002).

taken into the consideration in the use of these species as bioindicators in the environmental monitoring. The internal weighted dose rates to the Antarctic marine and terrestrial biota from 90Sr, 137Cs, 238,239þ240Pu and 241Am were deter­ mined using the ERICA Tool. In the preparation of the input data for dosimetrical assessment, summary statistics for censored data were used, so far rarely introduced into radioecological research. Due to large number of the results below the detection limit, study of the marine ecosystem is not precise enough. Estimates for the terrestrial environ­ ment are based on the data containing higher number of results above LOD, therefore it represents greater precision. In both assessments the dose rates were relatively low, not exceeding 41 nGy/h (total internal weighted dose rate). The organism in the marine ecosystem, which is burdened with the highest weighted dose rate, is Pagodroma nivea (snow petrel). It may be a result of the life style of this bird, which is scavenger and predator, also feeds on waste from ships sailing in the Antarctic waters. Despite the small differences between mosses and li­ chens in the activity concentrations of Sr, Pu and Am and approximately two times higher accumulation of Cs by moss, lichens receive a higher dose. This is a result of the impact of alpha emitters, which contribution to the weighted dose rate is the largest (the weighting factor for alpha radiation used for calculations is 10). The radioisotopes accumulation data, and in particular the dosimetrical assessments which have not been carried out for the Antarctic ecosystems so far, constitutes a specific “zero-point” data set, which may be crucial in case of a new radioactive contaminations in the local environment.

4. Conclusions

Declaration of competing interestCOI

Activity concentrations of 137Cs, 90Sr and 241Am in 12 species sam­ ples from the Antarctic marine ecosystem: Pygoscelis adeliae, Pygoscelis papua, Macronectes giganteus, Pagodroma nivea, Catharacta antarctica, Leptonychotes weddellii, Mirounga leonina, Nacella concinna, Harpagifer antarcticus, Chaenocephalus aceratus, Himantothallus grandifolius, Iridaea cordata and 4 species samples from the Antarctic terrestrial ecosystem: Sanionia uncinata, Usnea antarctica, Usnea aurantiaco-atra, Deschampsia antarctica were examined. There were observed differences between the marine and terrestrial environment in the accumulation of artificial radionuclides, especially on the basis of 137Cs. Mosses and lichens are considered as conservative organisms accumulating pollution from the air, whereas marine organisms especially birds, mammals and fishes actively remove radiocesium with accompanying wash out by sea wa­ ters. For these reasons, 137Cs was more often detected in terrestrial vegetation samples. Furthermore, statistically significant difference in the accumulation of 137Cs by mosses Sanionia uncinata and lichens Usnea antarctica and Usnea aurantiaco-atra was discovered. The trend was confirmed by Neutron Activation Analysis by means of which the accumulation of stable cesium was examined. This achievement can be

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