Uncertainty In Risk Assessment Research Articles

How evidence-based methodologies can help identify and reduce uncertainty in chemical risk assessment.

Evidence-based methodology, in particular systematic review, is increasingly being applied in environmental, public, and occupational health to increase the transparency, comprehensiveness, and objectivity of the processes by which existing evidence is gathered, assessed, and synthesized in answering research questions. This development is also changing risk assessment practices and will impact the assessment of uncertainties in the evidence for risks to human health that are posed by exposure to chemicals. The potential of evidence-based methodology for characterizing uncertainties in risk assessment has been widely recognized, while its contribution to uncertainty reduction is yet to be fully elucidated. We therefore present some key aspects of the evidence-based approach to risk assessment, showing how they can contribute to the identification and the assessment of uncertainties. We focus on the pre-specification of an assessment method­ology in a protocol, comprehensive search strategies, study selection using predefined eligibility criteria, critical appraisal of individual studies, and an evidence integration and uncertainty characterization process based on certainty of evi­dence frameworks that are well-established in health care research. We also provide examples of uncertainty in risk assessment and discuss how evidence-based methodology could address those. This perspective, which neither claims to be comprehensive nor complete, is intended to stimulate discussion of the topic and to motivate detailed exploration of how evidence-based methodology contributes to characterization of uncertainties, and how it will lead to uncertainty reduction in the conduct of health risk assessment.

A rodent thyroid-liver chip to capture thyroid toxicity on organ function level.

Endocrine disruption by environmental chemicals continues to be a concern for human safety. The rat, a widely used model organism in toxicology, is very sensitive to chemical-induced thyroid perturbation, e.g., histopathological alterations in thyroid tissue. Species differences in the susceptibility to thyroid perturbation lead to uncertainty in human safety risk assessments. Hazard identification and characterization of chemically induced thyroid perturbation would therefore benefit from in vitro models addressing different mechanisms of action in a single functional assay, ideally across species. We here introduce a rat thyroid-liver chip that enables simultaneous identification of direct and indirect (liver-mediated) thyroid perturbation on organ-level functions in vitro. A second manuscript describes our work toward a human thyroid-liver chip (Kühnlenz et al., 2022). The presented microfluidic model consisting of primary rat thyroid follicles and liver 3D spheroids maintains a tissue-specific phenotype for up to 21 days. More precisely, the thyroid model exhibits a follicular architecture expressing basolateral and apical markers and secretes T4. Likewise, liver spheroids retain hepatocellular characteristics, e.g., a stable release of albumin and urea, the presence of bile canalicular networks, and the formation of T4-glucuronide. Experiments with reference chemicals demonstrated proficiency to detect direct and indirect mechanisms of thyroid perturbation through decreased thyroid hormone secretion and increased gT4 formation, respectively. Prospectively this rat thyroid-liver chip model, together with its human counterpart, may support a species-specific quantitative in vitro to in vivo extrapolation to improve a data-driven and evidence-based human safety risk assessment with significant contributions to the 3R principles.

Effects of climate change on future energy production of Namakhvani HPP

Climate change may be considered relevant for hydropower production schemes all over the world. Despite this, the assessment of the impact of climate change on hydropower is uncertain and must be interpreted with that in mind. The paper focuses on the Namakhvani HPP (400 MW), a new project under development in the Rioni River, in Georgia. Using it as an example, the paper emphasizes the critical role that is played by uncertainty in climate impact risk assessments and explores the interpretation of simulation results, providing ways in which they can be transformed in actionable information for decision-making.

A Critical Review of the Availability, Reliability, and Ecological Relevance of Arctic Species Toxicity Tests for Use in Environmental Risk Assessment.

There is a pressing need to understand the impact of contaminants on Arctic ecosystems; however, most toxicity tests are based on temperate species, and there are issues with reliability and relevance of bioassays in general. Together this may result in an underestimation of harm to Arctic organisms and contribute to significant uncertainty in risk assessments. To help address these concerns, a critical review to assess reported effects for these species, quantify methodological and endpoint relevance gaps, and identify future research needs for testing was performed. We developed uniform criteria to score each study, allowing an objective comparison across experiments to quantify their reliability and relevance. We scored a total of 48 individual studies, capturing 39 tested compounds, 73 unique Arctic test species, and 95 distinct endpoints published from 1975 to 2021. Our analysis shows that of 253 test substance and species combinations scored (i.e., a unique toxicity test), 207 (82%) failed to meet at least one critical study criterion that contributes to data reliability for use in risk assessment. Arctic‐focused toxicity testing needs to ensure that exposures can be analytically confirmed, include environmentally realistic exposure scenarios, and report test methods more thoroughly. Significant data gaps were identified as related to standardized toxicity testing with Arctic species, diversity of compounds tested with these organisms, and the inclusion of ecologically relevant sublethal and chronic endpoints assessed in Arctic toxicity testing. Overall, there needs to be ongoing improvement in test conduction and reporting in the scientific literature to support effective risk assessments in an Arctic context. Environ Toxicol Chem 2022;41:46–72. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Sensitivity of a Model Reptile, the Common Snapping Turtle (Chelydra serpentina), to In Ovo Exposure to 2,3,7,8-Tetrachlorodibenzo-p-Dioxin and Other Dioxin-Like Chemicals.

Reptiles represent the least-studied group of vertebrates with regards to ecotoxicology and no empirical toxicity data existed for dioxin-like chemicals (DLCs). This lack of toxicity data represents a significant uncertainty in ecological risk assessments of this taxon. Therefore, the present study assessed early-life sensitivity to select DLCs and developed relative potencies in the common snapping turtle (Chelydra serpentina) as a model reptile. Specifically, survival to hatch and incidence of pathologies were assessed in common snapping turtle exposed in ovo to serial concentrations of the prototypical reference congener 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), and three other DLCs of environmental relevance, namely, 2,3,4,7,8-pentachlorodibenzofuran (PeCDF), 2,3,7,8-tetrachlorodibenzofuran (TCDF), and 3,3',4,4',5-pentachlorobiphenyl (PCB 126). In ovo exposure to TCDD, PeCDF, TCDF, and PCB 126 caused a dose-dependent increase in early-life mortality, with median lethal doses (LD50s) of 14.9, 11.8, 29.6, and 185.9 pg/g-egg, respectively. Except for abnormal vasculature development, few pathologies were observed. Based on the measured LD50, common snapping turtle is more sensitive to TCDD in ovo than other species of oviparous vertebrates investigated to date. The potencies of PeCDF, TCDF, and PCB 126 relative to TCDD were 1.3, 0.5, and 0.08, respectively. These relative potencies are within an order of magnitude of World Health Organization (WHO) TCDD-equivalency factors (TEFs) for both mammals and birds supporting these TEFs as relevant for assessing ecological risk to reptiles. The great sensitivity to toxicities of the common snapping turtle, and potentially other species of reptiles, suggests a clear need for further investigation into the ecotoxicology of this taxon. Environ Toxicol Chem 2022;41:175-183. © 2021 SETAC.

Refining health risk assessment for determining arsenic and cadmium safety limits in an herbal medicine and its cultivation soils

The contents of arsenic (As) and cadmium (Cd) in the herbal medicine Panax notoginseng (PN) have attracted public attention for the safe use of PN. Species-specific safety limits for As and Cd based on health risk assessment are an effective measure for the safety of PN consumption. To decrease the uncertainty of risk assessment, the gastrointestinal bioaccessibilities of As and Cd in PN, the influence of pharmaceutical processes, and individual variations in the dosage and duration of PN preparations were introduced for probabilistic health risk estimation. The As and Cd concentrations in PN materials from three major medicinal material markets were in the ranges of 0.11–1.26 and 0.07–1.97 mg/kg, respectively. The gastrointestinal bioaccessibilities of As and Cd in PN determined by an in vitro experiment were 64.7 ± 3.9% and 84.1 ± 10.1%, respectively. There was almost no noncarcinogenic health risk; however, long-term consumption of the PN preparation may induce 3.53% of consumers to have carcinogenic risks exceeding 1 × 10−4. The safety limits of As and Cd in PN were then determined to be 1.5 and 3.6 mg/kg, respectively, based on this acceptable carcinogenic risk level. Furthermore, the bioaccumulation of As and Cd in PN and their impacts on pharmaceutical components were studied based on our investigation in 19 PN plantations in major production areas. The safety limits of As and Cd in the soils were thus determined to be 5.5 and 7.3 mg/kg, respectively. The establishment of species-specific safety limits for commonly used herbal medicine was proposed because current standards cannot ensure the safe usage of PN.

Representing Uncertainty in Physical Security Risk Assessment

The importance of (physical) security is increasingly acknowledged by society and the scientific community. In light of increasing terrorist threat levels, numerous security assessments of critical infrastructures are conducted in practice and researchers propose new approaches continuously. While practical security risk assessments (SRA) use mostly qualitative methods, most of the lately proposed approaches are based on quantitative metrics. Due to little evidence of actual attacks, both qualitative and quantitative approaches suffer from the fundamental problem of inherent uncertainties regarding threats and capabilities of security measures as a result from vague data or the usage of expert knowledge. In quantitative analysis, such uncertainties may be represented by, e.g., probability distributions to reflect the knowledge on security measure performance available. This paper focuses on the impact of these uncertainties in security assessment and their consideration in system design. We show this influence by comparing the results of a scalar evaluation that does not take into account uncertainties and another evaluation based on distributed input values. In addition, we show that the influence is concentrated on certain barriers of the security system. Specifically, we discuss the robustness of the system by conducting quantitative vulnerability assessment as part of the SRA process of an airport structure example. Based on these results, we propose the concept of a security margin. This concept accounts for the uncertain knowledge of the input parameters in the design of the security system and minimizes the influence of these uncertainties on the actual system performance. We show how this approach can be used for vulnerability assessment by applying it to the initially assessed configuration of the airport structure. The results of this case study support our assumptions that the security margin can help in targeted uncertainty consideration leading to reduced system vulnerability.

Development of a Bayesian network for probabilistic risk assessment of pesticides.

Conventional environmental risk assessment of chemicals is based on a calculated risk quotient, representing the ratio of exposure to effects of the chemical, in combination with assessment factors to account for uncertainty. Probabilistic risk assessment approaches can offer more transparency by using probability distributions for exposure and/or effects to account for variability and uncertainty. In this study, a probabilistic approach using Bayesian network modeling is explored as an alternative to traditional risk calculation. Bayesian networks can serve as meta-models that link information from several sources and offer a transparent way of incorporating the required characterization of uncertainty for environmental risk assessment. To this end, a Bayesian network has been developed and parameterized for the pesticides azoxystrobin, metribuzin, and imidacloprid. We illustrate the development from deterministic (traditional) risk calculation, via intermediate versions, to fully probabilistic risk characterization using azoxystrobin as an example. We also demonstrate the seasonal risk calculation for the three pesticides. Integr Environ Assess Manag 2022;18:1072-1087. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Taxonomic Chauvinism in Pesticide Ecotoxicology.

Taxonomic Chauvinism in Pesticide Ecotoxicology.

Geographic delay characterization of railway systems

Railway systems provide pivotal support to modern societies, making their efficiency and robustness important to ensure. However, these systems are susceptible to disruptions and delays, leading to accumulating economic damage. The large spatial scale of delay spreading typically make it difficult to distinguish which regions will ultimately affected from an initial disruption, creating uncertainty for risk assessment. In this paper, we identify geographical structures that reflect how delay spreads through railway networks. We do so by proposing a graph-based, hybrid schedule and empirical-based model for delay propagation and apply spectral clustering. We apply the model to four European railway systems: the Netherlands, Germany, Switzerland and Italy. We characterize these geographical delay structures in the railway systems of these countries and interpret these regions in terms of delay severity and how dynamically disconnected they are from the rest. The method also allows us to point out important differences between these countries’ railway systems. For practitioners, such geographical characterization of railways provides natural boundaries for local decision-making structures and risk assessment.

Effects of communicating uncertainty descriptions in hazard identification, risk characterization, and risk protection.

Uncertainty is a crucial issue for any risk assessment. Consequently, it also poses crucial challenges for risk communications. Many guidebooks advise reporting uncertainties in risk assessments, expecting that the audience will appreciate this disclosure. However, the empirical evidence about the effects of uncertainty reporting is sparse and inconclusive. Therefore, based on examples of potential health risks of electromagnetic fields (EMF), three experiments were conducted analysing the effects of communicating uncertainties separately for hazard identification, risk characterisation and risk protection. The setups aimed to explore how reporting and how explaining of uncertainty affects dependent variables such as risk perception, perceived competence of the risk assessors, and trust in risk management. Each of the three experiments used a 2x2 design with a first factor presenting uncertainty descriptions (as used in public controversies on EMF related health effects) or describing a certainty conditions; and a second factor explaining the causes of uncertainties (by pointing at knowledge gaps) or not explaining them. The study results indicate that qualitative uncertainty descriptions regarding hazard identification reduce the confidence in the professional competencies of the assessors. In contrast, a quantitative uncertainty description in risk characterisation–regarding the magnitude of the risk–does not affect any of the dependent variables. Concerning risk protection, trust in exposure limit values is not affected by qualitative uncertainty information. However, the qualitative description of uncertainty regarding the adequacy of protection amplifies fears. Furthermore, explaining this uncertainty results in lower text understandability.

An integrated approach for modeling uncertainty in human health risk assessment.

A human health risk assessment (HHRA) will not remain simple and straightforward when it involves multiple uncertain input variables. Uncertainties in HHRA result from the unavailability and subjectivity of input variables. Though several studies have performed HHRA, the quantification of uncertainty in HHRA under a situation of data scarcity and the simultaneous application of random and non-random input variables have rarely been reported. The present study proposes an integrated hybrid health risk modeling framework involving the concurrent treatment of random and non-random input variables and estimating the uncertainties linked to the input variables in HHRA. The proposed framework presents the flexibility to classify the input variables into fuzzy and probabilistic categories, based on their data availability and provenience nature. The framework is demonstrated over the Turbhe sanitary landfill in Navi Mumbai, India, where the fate and transport of heavy metals in leachate are investigated through LandSim modeling. The present study considers the LandSim-simulated heavy metal concentration and body weight as a random variable and water intake, exposure duration, frequency, bioavailability, and average time as fuzzy variables. Further, the uncertainties in the non-carcinogenic human health risk have been quantified using Monte Carlo simulations, followed by a comprehensive multivariate sensitivity analysis of the proposed framework. High health risk at Turbhe is estimated for the male and female population. This study presents the first effort to quantify the non-carcinogenic human health risks from leachate-contaminated groundwater considering the health risk input variables as non-deterministic. The proposed framework is generic and applicable to any landfill site and will remain unaltered when integrated health risk assessment and uncertainty assessment are performed for the landfill.

Options for reducing uncertainty in impact classification for alien species

AbstractImpact assessment is an important and cost‐effective tool for assisting in the identification and prioritization of invasive alien species. With the number of alien and invasive alien species expected to increase, reliance on impact assessment tools for the identification of species that pose the greatest threats will continue to grow. Given the importance of such assessments for management and resource allocation, it is critical to understand the uncertainty involved and what effect this may have on the outcome. Using an uncertainty typology and insects as a model taxon, we identified and classified the causes and types of uncertainty when performing impact assessments on alien species. We assessed 100 alien insect species across two rounds of assessments with each species independently assessed by two assessors. Agreement between assessors was relatively low for all three impact classification components (mechanism, severity, and confidence) after the first round of assessments. For the second round, we revised guidelines and gave assessors access to each other’s assessments which improved agreement by between 20% and 30% for impact mechanism, severity, and confidence. Of the 12 potential reasons for assessment discrepancies identified a priori, 11 were found to occur. The most frequent causes (and types) of uncertainty (i.e., differences between assessment outcomes for the same species) were as follows: incomplete information searches (systematic error), unclear mechanism and/or extent of impact (subjective judgment due to a lack of knowledge), and limitations of the assessment framework (context dependence). In response to these findings, we identify actions that may reduce uncertainty in the impact assessment process, particularly for assessing speciose taxa with diverse life histories such as Insects. Evidence of environmental impact was available for most insect species, and (of the non‐random original subset of species assessed) 14 of those with evidence were identified as high impact species (with either major or massive impact). Although uncertainty in risk assessment, including impact assessments, can never be eliminated, identifying, and communicating its cause and variety is a first step toward its reduction and a more reliable assessment outcome, regardless of the taxa being assessed.

FMEA Using the Normalized Projection-Based TODIM-PROMETHEE II Model for Blood Transfusion

Failure mode and effect analysis (FMEA) is a forceful way for preventing the occurrence of possible damages before the process of management activities, which is widely utilized in various fields. However, experts’ bounded rationality, imprecise risk assessments and unobjective risk factors’ weights are prominent challenges existed in the conventional FMEA model. Thus, to better meet the challenges and further improve the performance of FMEA, this paper constructs a novel FMEA model for risk ranking by integrating the TODIM with the PROMETHEE II technique under q-rung orthopair fuzzy environment. Considering the fuzziness and uncertainty in risk assessments, q-rung orthopair fuzzy sets (q-ROFSs) are utilized to assist experts in describing their actual opinions concerning each failure modes flexibly and freely. Further, based on the proposed normalized projection model for q-ROFSs, a comprehensive criteria weighting determination method is employed for obtaining the optimal weights and a novel distance measurement of q-ROFSs is also further presented. Subsequently, the integrated TODIM-PROMETHEE II technique is developed for ranking failure modes, which has the ability of considering risk aversion behavior of experts. After that, the detailed steps are depicted via a representative case in blood transfusion. Finally, the comparative analysis is conducted to verify the stable and superiority of the FMEA method proposed in this paper. The proposed method under q-ROF environment can solve some cases which the traditional FMEA technique cannot, as well as helping experts to express their opinions flexibly, which improves the implementation accuracy of the FMEA.

Unravelling the Importance of Uncertainties in Global-Scale Coastal Flood Risk Assessments under Sea Level Rise

Global scale assessments of coastal flood damage and adaptation costs under 21st century sea-level rise are associated with a wide range of uncertainties, including those in future projections of socioeconomic development (shared socioeconomic pathways (SSP) scenarios), of greenhouse gas concentrations (RCP scenarios), and of sea-level rise at regional scale (RSLR), as well as structural uncertainties related to the modelling of extreme sea levels, data on exposed population and assets, and the costs of flood damages, etc. This raises the following questions: which sources of uncertainty need to be considered in such assessments and what is the relative importance of each source of uncertainty in the final results? Using the coastal flood module of the Dynamic Interactive Vulnerability Assessment modelling framework, we extensively explore the impact of scenario, data and model uncertainties in a global manner, i.e., by considering a large number (>2000) of simulation results. The influence of the uncertainties on the two risk metrics of expected annual damage (EAD), and adaptation costs (AC) related to coastal protection is assessed at global scale by combining variance-based sensitivity indices with a regression-based machine learning technique. On this basis, we show that the research priorities in terms of future data/knowledge acquisition to reduce uncertainty on EAD and AC differ depending on the considered time horizon. In the short term (before 2040), EAD uncertainty could be significantly decreased by 25 and 75% if the uncertainty of the translation of physical damage into costs and of the modelling of extreme sea levels could respectively be reduced. For AC, it is RSLR that primarily drives short-term uncertainty (with a contribution ~50%). In the longer term (>2050), uncertainty in EAD could be largely reduced by 75% if the SSP scenario could be unambiguously identified. For AC, it is the RCP selection that helps reducing uncertainty (up to 90% by the end of the century). Altogether, the uncertainty in future human activities (SSP and RCP) are the dominant source of the uncertainty in future coastal flood risk.

Insurance and the temporality of climate ethics: Accounting for climate change in US flood insurance

How is knowledge about future climate change operationalized in governance of the present? This paper addresses this question by examining efforts to repurpose the US National Flood Insurance Program (NFIP) for climate change adaptation. Policymakers and officials initially imagined the challenge to be principally a technical one of accounting for uncertainty in risk assessments and insurance tools. But the conduct and outcome of their efforts reflected instead politically charged normative tensions related to the temporality of climate ethics. NFIP policyholders, constituted as a ‘risk public’ by the instruments of flood insurance, exposed these tensions in mobilizations targeting practices of risk governance. The case shows that practices of ‘accounting for’ climate change and governing it through insurance work out—in however tentative or provisional a fashion—larger moralized disputes over the distribution of burdens, benefits and responsibilities over time.

A Case Study of Flood Risk Evaluation Based on Emergy Theory and Cloud Model in Anyang Region, China

With the progression of climate change, the intensity and frequency of extreme rainfall have increased in many parts of the world, while the continuous acceleration of urbanization has made cities more vulnerable to floods. In order to effectively estimate and assess the risks brought by flood disasters, this paper proposes a regional flood disaster risk assessment model combining emergy theory and the cloud model. The emergy theory can measure many kinds of hazardous factor and convert them into unified solar emergy (sej) for quantification. The cloud model can transform the uncertainty in flood risk assessment into certainty in an appropriate way, making the urban flood risk assessment more accurate and effective. In this study, the flood risk assessment model combines the advantages of the two research methods to establish a natural and social dual flood risk assessment system. Based on this, the risk assessment system of the flood hazard cloud model is established. This model was used in a flood disaster risk assessment, and the risk level was divided into five levels: very low risk, low risk, medium risk, high risk, and very high risk. Flood hazard risk results were obtained by using the entropy weight method and fuzzy transformation method. As an example for the application of this model, this paper focuses on the Anyang region which has a typical continental monsoon climate. The results show that the Anyang region has a serious flood disaster threat. Within this region, Linzhou County and Anyang County have very high levels of risk for flood disaster, while Hua County, Neihuang County, Wenfeng District and Beiguan District have high levels of risk for flood disaster. These areas are the core urban areas and the economic center of local administrative regions, with 70% of the industrial clusters being situated in these regions. Only with the coordinated development of regional flood control planning, economy, and population, and reductions in the uncertainty of existing flood control and drainage facilities can the sustainable, healthy and stable development of the region be maintained.

Stock price reaction to the drug development setbacks in the pharmaceutical industry.

Investments in pharmaceutical companies remain challenging due to the inherent uncertainties of risk assessment. Our paper aims to assess the impact of the drug development setbacks (DDS) on the stock price of pharmaceutical companies while taking into account the company's financial situation, pipeline size and trend of the stock price before the DDS. The model-based clustering based on finite Gaussian mixture modeling was employed to identify the clusters of pharmaceutical companies with homogenous parameters. An artificial neural network was constructed to aid the prediction of the positive mean rate of return 120days after the DDS. Our results reveal that a higher pipeline size and a lower rate of return before the DDS, as well as a lower ratio of the market value of the equity and the book value of the total liabilities, are associated with a positive mean rate of return 120days after the DDS. In general, the DDS have a negative impact on the company's stock price, but this risk can be minimized by investors choosing the companies that satisfy certain criteria. Graphical abstract The higher pipeline size(spip) and lower rate of return before (srr) the drug development setback (DDS) and the Market Value of Equity/Book Value of Total Liabilities ratio (sx4) are associated with a positive mean rate of return 120days after the DDS.

Simple method based on sensitivity coefficient for stochastic uncertainty analysis in probabilistic risk assessment

For the analysis of stochastic uncertainty in probabilistic risk assessment, a simple method based on the sensitivity coefficient was developed. The sensitivity coefficient can be defined as the importance of the parameter included in the risk assessment model to the output such as the probability of the target event. When the contribution of the parameter to the output is assumed to be linear, the sensitivity coefficient equals Fussell-Vesely importance. The present method does not require a lot of calculation cost and can treat the covariance of the parameters included in the risk assessment directly. The result obtained by the present method was compared with that obtained by other methods such as the Monte Carlo method in the analysis of the simple fault tree model. The results of the present method agree well with Monte Carlo method in the analysis of the fault tree model with β factor method and that with the Multiple Greek Letter method.

Distribution and transfer of naturally occurring radionuclides and 137Cs in the freshwater system of the Plitvice Lakes, Croatia, and related dose assessment to wildlife by ERICA Tool.

The aim of this study was to investigate the natural radioactivity of Plitvice Lakes, under the assumption that due to its status as a National Park, the area can be considered an example of a natural freshwater system. Also, considering the transfer parameter data as the largest source of uncertainty in radiological risk assessments, the impact of site-specific data on dose rate assessment, as opposed to currently available data, was investigated. The study included gamma and alpha spectrometric measurements of 238U, 226Ra, 210Pb, 228Ra, and 40K in water, sediment, and fish samples, as well as 137Cs due to the coinciding of the study with the Fukushima accident. The content of naturally occurring radionuclides significantly varied in sediments of different Lakes, probably as a reflection of the different underlying geology of the area. Also, the 210Pb distribution in sediments indicated an up to 312 Bq kg-1 of the allochthonous contribution of this radionuclide at the beginning of the Lake's watercourse, which probably entered into the lake system by the major inlet river with its steady decrease along downstream lakes. Low 40K activity concentrations (27.5 ± 20.1 mBq L-1) in the Lake's waters might be one of the causes of increased 137Cs activity concentrations in fish samples (1.5 ± 0.4 Bq kg-1), which was found to be an order of magnitude higher than average values for different fish species from other Croatian freshwater systems (0.2 ± 0.1 Bq kg-1). A temporary increase of 137Cs activity concentrations was measured in water samples collected immediately after the Fukushima accident. Calculated site-specific sediment/water distribution coefficients and fish/water concentration ratios for radium and caesium were on average lower than generic ones found in the literature. Background dose rate assessments performed by the ERICA Tool indicated a profound impact of different input data on assessment results with water activity concentrations resulting in significantly higher dose rates (0.1-67 μGy h-1) in comparison to sediment activity concentrations (0.03-9 μGy h-1). An incremental dose rate due to 137Cs was found to be in the range of < 0.001-0.023 μGy h-1 which, in comparison to background dose rates, can be considered negligible.