Annukka Lehikoinen (MSc), University of Helsinki (Environmental Sciences) *******
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1 Evaluation of the Traffic Increase in the Gulf of Finland During the Years and the Effect of the Increase on the Environment and Traffic Chain Activities Annukka Lehikoinen (MSc), University of Helsinki (Environmental Sciences) ******* Co-authors: Emilia Luoma & Sakari Kuikka (University of Helsinki), Maria Hänninen (Aalto University) and Jenni Storgård (University of Turku)
2 Problem description The Gulf of Finland (GoF), eastern Baltic Sea: The world s largest brackish water pool Low biodiversity, unique ecosystem Particularly Sensitive Sea-Area status (IMO) Maritime traffic, especially oil transportation, is growing rapidly A major oil accident could have severe environmental consequences Increasing need to assess alternative preventive strategies in oil spill risk management actions is evident (in addition and compared to post-accidental oil-recovery)
3 MIMIC project MIMIC: Minimizing risks of maritime oil transport by using holistic safety strategies (05/ /2013) Studies the risks related to the maritime oil transport in the GoF from a multi-disciplinary perspective Consortium: Kotka Maritime Research Association, University of Turku, Kymenlaakso University of Applied Sciences, Aalto University, University of Helsinki, Tallinn University of Technology, University of Tartu, Swedish Meteorological and Hydrological Institute, Finnish Environment Institute Funding: The Central Baltic INTERREG IV A Programme , Centre for Economic Development, Transport and the Environment for Southwest Finland, City of Kotka, Kotka-Hamina Regional Development Company, Cursor Oy & project consortium
4 Research aims To integrate the knowledge from earlier projects and new information on the less studied aspects of maritime accidents To study and compare the effect of different management actions to avoid accidents, giving insight to the cost-effectiveness of these measures To create an integrative risk and decision analysis model that will gather information and forecasts concerning the maritime traffic, oil transport, oil combating and accidents, not forgetting their likely environmental consequences (WP5)
5 Environmental risk assessment context: DPSIR-approach Responses According to the instruments, should we react? Drivers Needs behind the pressures How much certain level of need creates pressure? What to do to manage the system (and what part of it)? Impacts Instruments to assess the harm How harmful the effects are seen? (How we valuate them?) Pressures causing harm in the system States Harm caused by the pressure How / to what degree the system is affected by the pressures?
6 Method: Bayesian networks as integrative analysis tool Probabilistic, causal networks which can be used for the analysis of complex systems, taking into account the uncertainty holistically on each level, E.g.: Forecast-related uncertainty Model uncertainty Environmental randomnes Data-related uncertainty Help in processing the entities that are too complex for human brains alone Enable integration of different types and forms of knowledge to chains of inference Statistics and forecasts Models and simulations Both qualitative and quantitative correlations and causalities
7 MIMIC model elements
8 Background: SAFGOF -model Bio-tieteellinen tiedekunta / Henkilön nimi / Esityksen nimi 8
9 Valuation approaches A) Tanker collision risk : Theoretical expected value for the collisions / year Tanker other vessel + Tanker tanker collisions B) Leak risk : Theoretical expected value for the collisions that lead to oil leakage / year A * p(collision leads to leakage) C) Oil risk 1 : Theoretical expected value for the amount of oil that ends to the sea yearly (t / year) B * p(spill size) D) Oil risk 2 : Theoretical expected value for the amount of oil that will stay in the ecosystem after the open sea oil recovery (t / year) C * (1 (p(recovery efficiency%) + p(evaporation%))
10 Example results Due to the growing amount of traffic, there is a large increase in the risk level from year 2008 to The average risk level, regardless of the risk approach used, is likely to triple from the year 2008 to 2015 in every area. The area in the eastern part of GoF (C3) has the largest risk.
11 The most optimal decision to decrease risk is naturally implementing both the more effective VTS alarm and the compulsory piloting management actions in the GoF. With the implementation of these, it is possible to decrease the magnitude of the risk by about 18 % (mean, range %) regardless of the risk approach and traffic scenario used
12 Map user-interface for the evaluation of spatial risk Components: Light version of the SAFGOF model SpillMod oil drifting simulations for 180 alternative accident scenarios Weather statistics for 6 years -> 1080 simulations in total OILECO software for the spatial prioritization of the coastal oil recovery Data and valuation system for the threatened species
13 Risk in cell X = P(X will be oiled) * conservation value index of X Oil type: heavy Traffic: 2008 Hot spot: C3
14 Example results Within the area C3 probability of an oil accident ( Leak risk ) is 2-3-fold compared to C4 When taking into account the spatial valuation what comes to the known threatened species occurrences and their conservation values, the risk proneness of C4 is 7-fold compared to C3!
15 Conclusions and discussion According to our results in the former project SAFGOF, the risk of a major oil accident in the GoF is going to remarkably increase in the near future. In project MIMIC we are analysing the situation in years 2020 and 2030 and taking into account a variety of accident types and valuation approaches not forgetting the costs of the management actions analysed. It seems that the risks of oil transportations in the GoF vary a lot in time and space (Risk = P*Harm). The magnitude of the relative differences between the valuation approaches will be studied further in MIMIC. What comes to the risk management, should we actually focus on different things in different parts of the GoF? What are the values that the society is willing to weight most? After several valuating approaches have been tested: does the weighting actually affect to the final ranking order of the management actions?
16 Authors wish to thank the MIMIC financers! Kotka Maritime Research Centre Heikinkatu 7, Kotka 16
17 and the SAFGOF financers!
18 Thank you for your attention! Contact:
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