Toward integrative management advice of water quality, oil spills, and fishery in the Gulf of Finland: a Bayesian approach

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.

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).

Incorporating stakeholders' values into environmental decision support: A Bayesian Belief Network approach

Participatory modelling increases the transparency of environmental planning and management processes and enhances the mutual understanding among different parties. We present a sequential probabilistic approach to involve stakeholders' views in the formal decision support process. A continuous Bayesian Belief Network (BBN) model is used to estimate population parameters for stakeholder groups, based on samples of individual value judgements. The approach allows quantification and visualization of the variability in views among and within stakeholder groups. Discrete BBN is populated with these parameters, to summarize and visualize the information and to link it to a larger decision analytic influence diagram (ID). As part of ID, the resulting discrete BBN element serves as a distribution-form decision criteria in probabilistic evaluation of alternative management strategies, to help find a solution that represents the optimal compromise in the presence of potentially conflicting objectives. We demonstrate our idea using example data from the field of marine spatial planning. However, this approach is applicable to many types of management cases. We suggest that by advancing the mutual understanding and concrete participation this approach can further facilitate the stakeholder involvement also during the various stages of the environmental management process.

Cost-Effective Marine Protection--A Pragmatic Approach

This paper puts forward a framework for probabilistic and holistic cost-effectiveness analysis to provide support in selecting the least-cost set of measures to reach a multidimensional environmental objective. Following the principles of ecosystem-based management, the framework includes a flexible methodology for deriving and populating criteria for effectiveness and costs and analyzing complex ecological-economic trade-offs under uncertainty. The framework is applied in the development of the Finnish Programme of Measures (PoM) for reaching the targets of the EU Marine Strategy Framework Directive (MSFD). The numerical results demonstrate that substantial cost savings can be realized from careful consideration of the costs and multiple effects of management measures. If adopted, the proposed PoM would yield improvements in the state of the Baltic Sea, but the overall objective of the MSFD would not be reached by the target year of 2020; for various environmental and administrative reasons, it would take longer for most measures to take full effect.

A Bayesian network for assessing the collision induced risk of an oil accident in the Gulf of Finland

The growth of maritime oil transportation in the Gulf of Finland (GoF), North-Eastern Baltic Sea, increases environmental risks by increasing the probability of oil accidents. By integrating the work of a multidisciplinary research team and information from several sources, we have developed a probabilistic risk assessment application that considers the likely future development of maritime traffic and oil transportation in the area and the resulting risk of environmental pollution. This metamodel is used to compare the effects of two preventative management actions on the tanker collision probabilities and the consequent risk. The resulting risk is evaluated from four different perspectives. Bayesian networks enable large amounts of information about causalities to be integrated and utilized in probabilistic inference. Compared with the baseline period of 2007-2008, the worst-case scenario is that the risk level increases 4-fold by the year 2015. The management measures are evaluated and found to decrease the risk by 4-13%, but the utility gained by their joint implementation would be less than the sum of their independent effects. In addition to the results concerning the varying risk levels, the application provides interesting information about the relationships between the different elements of the system.

Scientific support by the BONUS+ projects for the sustainability of the Baltic Sea Region: the case of the HELCOM Baltic Sea Action Plan

The synthesis of the BONUS+ research is introduced. The HELCOM Baltic Sea Action Plan is examined as a case to illustrate the potentials and challenges in building the science-policy making interface on a macro regional level. The projects address environmental challenges in the Baltic Sea as defined by the Baltic Sea Action Plan, or consider the environmental governance and decision making within the Baltic Sea context in general. Eutrophication, biodiversity, hazardous substances, maritime activities, and the environment governance are addressed, as are cross cutting issues, such as the impact of climate change, maritime spatial planning and impacts of future development on ecosystem services. The projects contributed to relevant policy developments: 37 consultations carried out at EU level, 49 modifications to policy documents and action plans, 153 suggestions for the efficacy of pertinent public policies and governance, and in 570 occasions, scientists working in BONUS+ projects served as members or observers in scientific and stakeholder committees.