The NEBA rationale has been widely used to assess spill response strategy effectiveness, identify potentially impacted areas, and estimate associated environmental and socioeconomic impacts during many phases of environmental and emergency management. These include permitting and regulatory actions, contingency planning, and emergency response.  Lunel and Baker (IOSC 1999) illustrated varying uses of NEBA to support strategic, tactical, and operational decision making.   SINTEF has demonstrated phased approaches to NEBA use, during planning and response, noting that “NEBA… is a continuous evaluation process that is to be repeated during an incident in the light of new information concerning the behaviour of spilt oil, the overall environmental impact, and/or the effectiveness of the activated response technique ” (Schallier et al. 2004).  In Russia, NEBA is required by regulation as a condition for dispersant use.  Norway requires use of the similar NEDRA process for oil spill response planning. While not a formalized legal requirement in the U.S., NEBA has been used in Area Contingency Planning, and in some cases has resulted in pre-authorization of dispersant use by Federal On-Scene Coordinators for certain spill types and locations (Addassi et al. 2005).  The following description of NEBA concepts, historical uses and case studies illustrate some of the potential benefits of using NEBA for contingency planning and emergency response to oil spills in the Arctic environment.

Figure 9- 3. Decision tree illustrating the NEBA process [Source: Merlin (CEDRE) and Lee (COOGER)]

A number of relatively objective analytical tools have been developed to support the process of estimating the effectiveness of potential response strategies and the fate and effect of spilled oil.  Reviews of field trials and/or case histories are also available, which help to serve as a basis for decision making, and for verifying model outputs.  

Lunel and Baker (IOSC 1999) reviewed case histories of well-studied oil spills, including the Braer (1993), Exxon Valdez (1989) and Sea Empress (1996) and developed tables that could be used to produce quantitative estimates of oil fate and effect for NEBA analyses (including ecological and socioeconomic sensitivity tables).  They demonstrated the potential use of historical data for three levels of NEBA – strategic, tactical, and operational, which corresponded roughly to tier 3, 2, and 1 spill respectively. 

French and Shuttenberg (1999) demonstrated the ability to use the Spill Impact Model Analysis Package (SIMAP) to predict impacts of a scenario based on the well-studied North Cape Oil Spill.  In the North Cape spill, oil dispersion occurred as a result of high wave energy, not chemical dispersants, but the model was capable of predicting either.  The SIMAP model includes an oil physical fates model; a biological effects model; input tools for oil physical, chemical and toxicological data; input tools for environmental, geographical, and biological data; a response module to analyze effects of response strategies, and export and graphical visualization tools. 

SINTEF uses the Oil Spill Contingency and Response (OSCAR) mathematical model to support NEBA activities.  OSCAR consists of a three-dimensional numerical model of the physical and chemical behavior and fate of spilled oil, and an oil spill response simulator for various mechanical recovery and dispersant application systems.  Prediction of oil spill fate and effect is particularly difficult in ice infested waters, but the OSCAR model showed promise during field trials conducted in the Barents Sea in 2009. Further modeling research at SINTEF is underway to develop coupled ice-ocean-oil models.  With regards to modeling ecological impact, by implementing models of biological resources (statistical distribution in time and space) into the OSCAR model system, it is also possible to perform dynamic modelling of the oil exposure to relevant marine organisms in the water column (e.g. fish eggs and larvae) and sea birds on the surface.  This has become an important tool for predicting realistic effects (acute toxicity) and losses of populations of analysing various oil spill scenarios/response options. 

The use of any of these tools to support use of NEBA in contingency planning requires that realistic scenarios are utilized and that response methods evaluated are actually available and feasible for the area being studied.

Assessing the potential ecological and socioeconomic impacts and recovery rates is inherently more subjective.  Natural resource distributions are particularly sensitive to temporal and geographic influences.  Socioeconomic impacts result from damages to natural resources, and may include loss of subsistence hunting and fishing, reduction in tourism, and reduced “sense of well-being” due to perceived environmental tainting.  The recovery rates from these types of impacts are dependent upon many factors that are highly location dependent and difficult to quantify.  As a result, it is often necessary to rely on local knowledge and expertise to predict the relative magnitude of these variables during NEBA studies.  In doing so, it is extremely important that all potentially affected stakeholders are identified and provided opportunities for involvement.  For NEBA results to be successfully used in contingency planning, stakeholders must reach consensus on the magnitude and relative importance of potential ecological and socioeconomic impacts for the range of spill scenarios considered.  This can be extremely difficult since the value assigned to environmental resources is likely to vary widely, depending on the extent of use or value of those resources by different stakeholder groups.  Even if individuals representing varying stakeholder groups reach consensus during the NEBA process, other members of the community may not understand and accept the decisions reached and support spill response decisions made during an incident.  Broad acceptability requires an effective outreach and communication strategy and frequent re-evaluations in order to determine any changes over time in response capabilities and technologies or resource dynamics and valuations.

Despite the semi-quantitative nature of resource valuations, some tools have been developed to assist with more objective analysis.  Some of the previously discussed models, such as SIMAP and OSCAR do contain biological assessment algorithms.  Aps et al. (2007, 2009) demonstrated that Bayesian inference networks, which capture uncertainties in terms of probabilities, can be very useful in supporting ecosystem consequence analyses by providing decision makers with more objective numerical estimates to weigh alternatives against each other. Bayesian networks were shown to be useful in integrating surveillance data, mathematical simulation results, and ecological sensitivity GIS maps during ECA analyses (Aps et al. 2007, 2009).

NEBA can be an effective means of generating valuable discussions around the potentially disparate views of industry, academia, government regulators, and local stakeholders, even if consensus is not reached.  This was illustrated in 2011 during a Workshop on Dispersant Use in the Canadian Beaufort Sea that was conducted as part of a multi-year Beaufort Regional Environmental Assessment (BREA).  The workshop included simplified NEBAs addressing the potential benefits of dispersant use in three different scenarios.  Over 50 persons from stakeholders including Inuvialuit communities, government agencies, and the oil industry were involved.  The participants did not necessarily reach consensus on the desirability of dispersant use, but each of the major stakeholder groups did present valuable perspectives on the path forward for future planning activities.