Norwegian Radiation and Nuclear Safety Authority

Objective This position paper results from an International Union of Radioecology symposium aimed at identifying challenges to develop eco-centric and holistic approaches to understanding ionizing radiation impacts on ecosystems. An ecosystem approach is particularly relevant today not only because of the triple planetary crisis of climate change, biodiversity loss, and pollution, which make single-stressor approaches unrealistic, but because of renewed interest in nuclear power as a potential solution to transition away from fossil fuels. For example, there are proposals to site small modular reactors in remote and pristine areas. The focus of the symposium was to expand the boundaries of existing approaches in radioecology and look at issues like ecosystem complexity and multiple stressors, which complicate single-stressor approaches. Conclusions Discussion centered around existing tools for radiation protection e.g. Adverse Outcome Pathway (AOP) analysis, biomarkers, use of microcosms and mesocosms and modeling approaches. These approaches were discussed with emphasis on identifying gaps, boundaries, and where leaps into the unknown might be beneficial. Identified challenges with biomarker and AOP approaches were that the individual level is generally addressed while interrelatedness of ecosystem components is difficult to capture. Novel ideas suggested were to construct multiple-stressor AOPs which capture key interactions and consider time as a critical component, or to exploit ‘ecological network analysis’ metrics which have been extensively used in ecological science. Other discussions centered on complexity and chaos modeling. The use of microcosms, focused field studies, and harnessing ecosystem information and communication systems were suggested to bridge the gap between individual and population-level responses.

Radon and its progeny are major contributors to dose to the public. In high background radiation areas (HBRAs), the risk is increased. In the Fen igneous complex, Norway, significant outdoor levels of radon-220 (220Rn) have been observed and exhalation from the ground is a contributor. Such exhalation depends on many factors, including levels of radon-progenitors in the ground. Temporal variation in 220Rn exhalation rates is affected by weather parameters. We show large 220Rn exhalation rates at Fen complex and assess temporal variation, which is explained by weather parameters, especially by wind. Exhalation rates are calculated from measurement series in an exhalation container using different phases of accumulation. We find a bias depending on whether the linear phase of increase or the subsequent threshold phase is used, and show it is affected by whether air is sampled from the side or top valve of the container. However, in areas where progenitor levels in the ground are low, assessment of the linear phase may not be possible due to required period of measurement intervals.

Experience from earlier nuclear accidents has clearly shown the need for maintaining and developing appropriate modelling capabilities. Dealing with complex issues such as human exposure following a nuclear accident necessitates the implementation of a set of interconnected models such as FDMT. FDMT is an integrated module within the two main European decision support systems for radiological emergency preparedness, ARGOS and JRODOS, to simulate the transfer of radionuclides along terrestrial food chains and to predict their activity concentrations in foodstuffs. In order to make the module more fit-for-purpose, FDMT has been implemented in a new modelling platform (ECOLEGO) which provides a high degree of flexibility with regard to conducting developmental work. This paper presents improvements in FDMT further through either the incorporation of new models or further elaboration of existing ones, as well as updates in default parameters. Models have also been made more fit-for-purpose through consideration of regional-specific parameters. Specific improvements include modelling developments related to dry deposition, radioactive particle weathering, radiocaesium transfer influenced by soil characteristics and, for a region-specific case, animal uptake. In addition, the paper presents new pathways and parameters (and updated values) to be considered for making FDMT more adapted for Norwegian conditions. Overall, the improvements made in the present work should significantly reduce the uncertainties associated with the outputs of the FDMT models.

To enhance stakeholder engagement and foster the inclusion of interests of citizens in radiation protection research, a comprehensive online survey was developed within the framework of the European Partnership PIANOFORTE. This survey was performed in 2022 and presented an opportunity for a wide range of stakeholders to voice their opinions on research priorities in radiation protection for the foreseeable future. Simultaneously, it delved into pertinent issues surrounding general radiation protection. The PIANOFORTE e-survey was conducted in the English language, accommodating a diverse range of participants. Overall, 440 respondents provided their insights and feedback, representing a broad geographical reach encompassing 29 European countries, as well as Canada, China, Colombia, India, and the United States. To assess the outcomes, the Positive Matrix Factorization numerical model was applied, in addition to qualitative and quantitative assessment of individual responses, enabling the discernment of four distinct stakeholder groups with varying attitudes. While the questionnaire may not fully represent all stakeholders due to the limited respondent pool, it is noteworthy that approximately 70% of the participants were newcomers to comparable surveys, demonstrating a proactive attitude, a strong willingness to collaborate and the necessity to continuously engage with stakeholder groups. Among the individual respondents, distinct opinions emerged particularly regarding health effects of radiation exposure, medical use of radiation, radiation protection of workers and the public, as well as emergency and recovery preparedness and response. In cluster analysis, none of the identified groups had clear preferences concerning the prioritization of future radiation protection research topics.

To examine associations of neighborhood greenery, air pollution and walkability with cardiometabolic disease in adults aged ≥45 years in the Frankston-Mornington Peninsula region, Victoria, Australia. A cross-sectional, ecological study design was used. We assessed mean annual neighborhood greenery using the Normalized Difference Vegetation Index; air pollution (fine particulate matter of diameter ≤2.5 μm [PM2.5] and NO2) using land-use regression models; and walkability using Walk Score (possible values 0-100). Medically diagnosed diabetes (~95% type-2), heart disease and stroke were self-reported in the Australian Census (2021). Multivariable regression was used to model associations between environmental exposures and area-level (neighborhood) cardiometabolic disease prevalence (age group ≥45 years), with socioeconomic status, age and sex as covariates. Air pollution was examined as a mediator of associations between greenery and disease prevalence. Our sample comprised 699 neighborhoods with the following mean (SD) values: Normalized Difference Vegetation Index 0.47 (0.09), PM2.5, 8.5 (0.6) μg/m3 and NO2, 5.2 (1.6) ppb. Disease prevalences were: heart disease, mean 8.9% (4.5%); diabetes, mean 10.3% (4.7%); and stroke, median 1.2% (range 0-10.9%). Greenery was negatively associated with diabetes (β = -5.85, 95% CI -9.53, -2.17) and stroke prevalence (β = -1.26, 95% CI -2.11, -0.42). PM2.5 and NO2 were positively associated with diabetes (β = 1.59, 95% CI 1.00, 2.18; β = 0.42, 95% CI 0.22, 0.62) and stroke prevalence (β = 0.15, 95% CI 0.01, 0.29; β = 0.06, 95% CI 0.01, 0.10). The association between greenery and diabetes was partially mediated by PM2.5 (mediated effect -5.38, 95% CI -7.84, -3.03). Greenery and air pollutants were associated with lower and higher prevalence, respectively, of self-reported diabetes and, to a lesser extent, stroke. These ecological findings require further exploration with stronger, longitudinal study designs to inform public health policy and directions. Geriatr Gerontol Int 2024; 24: 208-214.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Earth's global climate system is vast, complex, and intricately interrelated. Many areas are influenced by global-scale phenomena, including the "triple dip" La Niña conditions that

Adequate information on external exposure is often a limiting factor in ecological risk assessments because of a lack of exposure data for free-ranging animals as they interact with a heterogeneous distribution of contaminants. Instead, most wildlife exposure data are estimated from model simulations. However, empirical exposure data are rarely available to verify model results, or to test fundamental assumptions inherent in exposure assessments. We used novel, GPS-coupled radiation dosimeters on reindeer (Rangifer tarandus) to quantify their external exposure for five months in a Chernobyl fallout affected mountainous area of Norway. The exposure data were then used to test a fundamental assumption in screening-level risk assessments: Mean soil contaminant concentrations can be used to conservatively estimate chronic external exposures to representative animals. External exposure and GPS coordinates were obtained hourly and compared to model simulations of exposure based on airborne surveys of 137Cs soil contamination. Our objectives were to determine 1) if modelled dose estimates based on mean 137Cs soil concentrations were conservative, and 2) if modelled dose estimates could be improved by adjusting for spatial–temporal heterogeneity of contaminants using 137Cs concentrations within reindeers’ GPS-defined home ranges and core areas. We found that external exposure modelled from mean soil contaminant concentrations underestimated exposure by 70% compared to empirical measurements from GPS-dosimeter collars worn on individual animals. Using area-weighted mean contaminant levels within the animals’ home range improved the model estimates, but still underestimated the field dosimeter data by 53%. The best estimate of external exposure was obtained when high-use areas within their home range, along with spatial heterogeneity of the contaminant, was accounted for by using area-weighted mean soil contaminant levels within GPS-derived core areas. Accounting for temporal use of core areas within animals’ home range provided a 24% improvement. A comparison of our analyses to similar work performed on Chernobyl wolves found the two studies concur that risk assessors should be cautious in relying on the paradigm of using averaged soil contaminant levels to provide conservative estimates of external exposure to representative individuals. Results of modelled external exposure based on mean soil contaminant concentrations could misguide assessors and cause inappropriate management decisions.

Barium (Ba) in recent marine sediments can originate from natural and anthropogenic sources including discharges from the oil and gas industry. In this study, we use data from the Norwegian and Barents Seas to assess whether Ba in recent marine sediments has increased due to these discharges. To account for Ba in detrital material, we normalise all samples with respect to aluminosilicate by calculating an enrichment factor. We use statistical modelling to control for parameters related to sedimentation. We present results that suggest increased Ba levels in recent sediments that coincide with the timing of hydrocarbon drilling and production. This is supported by geographical differences on a large scale that relate to proximity to hydrocarbon drilling and production. Among 243 sampling stations, we identify 73 locations exhibiting enrichment of Ba in the upper 6 of sediment. At these locations, Ba is 1.55 to 3.55 times higher than the levels that can be expected from the shale average when Ba in detrital matter is accounted for. Excess Ba is reported in sediment surface samples in areas important to fisheries like the Lofoten area and the western Barents Sea.