Arctic marine fish 'biotransformation toxicity' model for ecological risk assessment

Human health risk model for microplastic exposure in the Arctic region

Microplastics enriched with carcinogens like heavy metals, polycyclic aromatic hydrocarbons (PAHs), and their derivatives are ubiquitous in Arctic waters. They contaminate the local land and sea-based food sources, which is a significant health hazard. It is thus imperative to assess the risk posed by them to the nearby communities, which primarily rely on locally available food sources to meet their energy requirements. This paper proposes a novel ecotoxicity model to assess the human health risk posed by microplastics. The region's geophysical and environmental conditions affecting human microplastic intake, along with the human physiological parameters influencing biotransformation, are incorporated into the developed causation model. It investigates the carcinogenic risk associated with microplastic intake in humans via ingestion in terms of incremental excess lifetime cancer risk (IELCR). The model first evaluates microplastic intake and then uses reactive metabolites produced due to the interaction of microplastics with xenobiotic metabolizing enzymes to assess cellular mutations that result in cancer. All these conditions are mapped in an Object-Oriented Bayesian Network (OOBN) framework to evaluate IELCR. The study will provide a vital tool for formulating better risk management strategies and policies in the Arctic region, especially concerning Arctic Indigenous peoples.

A multi-criteria decision analysis model for ship biofouling management in the Baltic Sea

Biofouling of ship hulls form a vector for the introduction of non-indigenous organisms worldwide. Through increasing friction, the organisms attached to ships' hulls increase the fuel consumption, leading to both higher fuel costs and air emissions. At the same time, ship biofouling management causes both ecological risks and monetary costs. All these aspects should be considered case-specifically in the search of sustainable management strategies. Applying Bayesian networks, we developed a multi-criteria decision analysis model to compare biofouling management strategies in the Baltic Sea, given the characteristics of a ship, its operating profile and operational environment, considering the comprehensive environmental impact and the monetary costs. The model is demonstrated for three scenarios (SC1-3) and sub-scenarios (A-C), comparing the alternative biofouling management strategies in relation to NIS (non-indigenous species) introduction risk, eco-toxicological risk due to biocidal coating, carbon dioxide emissions and costs related to fuel consumption, in-water cleaning and hull coating. The scenarios demonstrate that by the careful consideration of the hull fouling management strategy, both money and environment can be saved. We suggest biocidal-free coating with a regular in-water cleaning using a capture system is generally the lowest-risk option. The best biocidal-free coating type and the optimal in-water cleaning interval should be evaluated case-specifically, though. In some cases, however, biocidal coating remains a justifiable option.

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.

Ecological risk simulation assessment in marine ecosystems of the Arctic shelf

This work elaborates an approach to the ecological risk model assessment in marine systems exposed to intense impacts and accompanying pollution. This approach was applied to the marine ecosystems of the Arctic shelf for two types of ecosystems, i.e. highly productive and low productive. The proposed method makes it possible to identify intervals in the increased ecological risk throughout the year and to calculate the allowable probability of anthropogenic impact depending on this. Variations in ecological risk throughout the year revealed periods of increased hazard and relatively favorable periods with a low risk probability. Performed calculation analysis refutes assumptions that in the Arctic shelf ecosystems with low productivity, a more intense anthropogenic impact is possible supposedly causing no significant damage. The proposed approach in the interdisciplinary aspect reveals possibility to harmonize ecological and economic requirements to ensure safe development of the marine system resources.

A food chain-based ecological risk assessment model for oil spills in the Arctic environment

This paper investigates the linkage between the acute impacts on apex marine mammals with polar cod responses to an oil spill. It proposes a Bayesian network-based model to link these direct and indirect effects on the apex marine mammals. The model predicts a recruitment collapse (for the scenarios considered), causing a higher risk of mortality of polar bears, beluga whales, and Narwhals in the Arctic region. Whales (adult and calves) were predicted to be at higher risk when the spill was under thick ice, while adult polar bears were at higher risk when the spill occurred on thin ice. A spill over the thick ice caused the least risk to whale and adult polar bears. The spill's timing and location have a significant impact on the animals in the Arctic region due to its unique sea ice dynamics, simple food web, and short periods of food abundance.

Bayesian Networks in Environmental Risk Assessment: A Review

Human activities both depend upon and have consequences on the environment. Environmental risk assessment (ERA) is a process of estimating the probability and consequences of the adverse effects of human activities and other stressors on the environment. Bayesian networks (BNs) can synthesize different types of knowledge and explicitly account for the probabilities of different scenarios, therefore offering a useful tool for ERA. Their use in formal ERA practice has not been evaluated, however, despite their increasing popularity in environmental modeling. This paper reviews the use of BNs in ERA based on peer-reviewed publications. Following a systematic mapping protocol, we identified studies in which BNs have been used in an environmental risk context and evaluated the scope, technical aspects, and use of the models and their results. The review shows that BNs have been applied in ERA, particularly in recent years, and that there is room to develop both the model implementation and participatory modeling practices. Based on this review and the authors' experience, we outline general guidelines and development ideas for using BNs in ERA. Integr Environ Assess Manag 2021;17:62-78. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Environmental effects of offshore produced water discharges: A review focused on the Norwegian continental shelf

Produced water (PW), a large byproduct of offshore oil and gas extraction, is reinjected to formations or discharged to the sea after treatment. The discharges contain dispersed crude oil, polycyclic aromatic hydrocarbons (PAHs), alkylphenols (APs), metals, and many other constituents of environmental relevance. Risk-based regulation, greener offshore chemicals and improved cleaning systems have reduced environmental risks of PW discharges, but PW is still the largest operational source of oil pollution to the sea from the offshore petroleum industry. Monitoring surveys find detectable exposures in caged mussel and fish several km downstream from PW outfalls, but biomarkers indicate only mild acute effects in these sentinels. On the other hand, increased concentrations of DNA adducts are found repeatedly in benthic fish populations, especially in haddock. It is uncertain whether increased adducts could be a long-term effect of sediment contamination due to ongoing PW discharges, or earlier discharges of oil-containing drilling waste. Another concern is uncertainty regarding the possible effect of PW discharges in the sub-Arctic Southern Barents Sea. So far, research suggests that sub-arctic species are largely comparable to temperate species in their sensitivity to PW exposure. Larval deformities and cardiac toxicity in fish early life stages are among the biomarkers and adverse outcome pathways that currently receive much attention in PW effect research. Herein, we summarize the accumulated ecotoxicological knowledge of offshore PW discharges and highlight some key remaining knowledge needs.

Effects of pollution on marine organisms

This review covers selected 2019 articles on the biological effects of pollutants, including human physical disturbances, on marine and estuarine plants, animals, ecosystems, and habitats. The review, based largely on journal articles, covers field, and laboratory measurement activities (bioaccumulation of contaminants, field assessment surveys, toxicity testing, and biomarkers) as well as pollution issues of current interest including endocrine disrupters, emerging contaminants, wastewater discharges, marine debris, dredging, and disposal. Special emphasis is placed on effects of oil spills and marine debris due largely to the 2010 Deepwater Horizon oil blowout in the Gulf of Mexico and proliferation of data on the assimilation and effects of marine debris microparticulates. Several topical areas reviewed in the past (e.g., mass mortalities ocean acidification) were dropped this year. The focus of this review is on effects, not on pollutant sources, chemistry, fate, or transport. There is considerable overlap across subject areas (e.g., some bioaccumulation data may be appeared in other topical categories such as effects of wastewater discharges, or biomarker studies appearing in oil toxicity literature). Therefore, we strongly urge readers to use keyword searching of the text and references to locate related but distributed information. Although nearly 400 papers are cited, these now represent a fraction of the literature on these subjects. Use this review mainly as a starting point. And please consult the original papers before citing them.

Risk assessment of Arctic aquatic species using ecotoxicological biomarkers and Bayesian network

The risk to Arctic aquatic species due to accidental oil spills is not well studied. One of the key reasons for this limitation is the lack of understanding of the dose-response relations for the species in the Arctic region. The present study addresses this knowledge gap. It proposes a new approach to develop dose-response curves for Arctic aquatic species. The application of the approach is demonstrated using the estimation of mortality risk in Boreogadus saida (polar cod) due to exposure from polycyclic aromatic hydrocarbons (PAH). The proposed approach considers the toxicity mechanism in Arctic species (i.e. polar cod) and regional environmental factors, and models these as a belief-based Bayesian Network (BN). The BN model integrates diverse ecotoxicology biomarker data types and predicts the cell death probability due to exposure to a toxicant (PAH in crude oil). The input data and results from the model were verified using data available in the literature. Seasonal sea ice played a major role in containing PAH exposure and subsequent risk to polar cod. However, the physiological factors, such as presence of higher Phase II activity, and higher oxyradical scavenging ability, had greater impact on PAH risk mitigation.

Implications of Trophic Variability for Modeling Biomagnification of POPs in Marine Food Webs in the Svalbard Archipelago

The occurrence of persistent organic pollutants (POPs) in the Arctic has been of constant concern, as these chemicals cause reproductive effects and mortality in organisms. The Arctic acts as a chemical sink, which makes this system an interesting case for bioaccumulation studies. However, as conducting empirical studies for all Arctic species and POPs individually is unfeasible, in silico methods have been developed. Existing bioaccumulation models are predominately validated for temperate food chains, and do not account for a large variation in trophic levels. This study applies Monte Carlo simulations to account for variability in trophic ecology on Svalbard when predicting bioaccumulation of POPs using the optimal modeling for ecotoxicological applications (OMEGA) bioaccumulation model. Trophic magnification factors (TMFs) were calculated accordingly. Comparing our model results with monitored POP residues in biota revealed that, on average, all predictions fell within a factor 6 of the monitored POP residues in biota. Trophic variability did not affect model performance tremendously, with up to a 25% variability in performance metrics. To our knowledge, we were the first to include trophic variability in predicting biomagnification in Arctic ecosystems using a mechanistic biomagnification model. However, considerable amounts of data are required to quantify the implications of trophic variability on biomagnification of POPs in Arctic food webs.