1.6 What Can ERA Acute Results Be Used for?
15
of oil brings the impact into the next impact category. Using the continuous function in
ERA Acute will mitigate this shortcoming and is especially useful for comparing risk
between alternative cases and solutions, such as for SIMAs. Although in some cases
a category-based method may result in higher impact for a small spill, a continuous
function will be more sensitive to subtle changes in exposure. ERA Acute is therefore
expected to be more suitable for analyzing efficiency of mitigation of smaller spills
than a category-based method, which is especially important in environmentally
sensitive areas.
Because ERA Acute quantitatively evaluates the impact and risk in grid cells, risk
assessors can view results in maps at various assessment steps using a geographical
information system for any region globally. An ERA Acute environmental risk map
for a VEC can show where the risk is high or low, for example by showing average
population loss from all simulations or by highlighting the worst case by showing
maximum population loss. The environmental risk assessor can identify areas of
high risk for use in decision support and spill response planning, independently
of the region. All georeferenced results are useful for strategic use of geographic
information in risk management and planning.
For detailed studies of scenario impacts, analysis endpoints can be plotted against
frequencies in risk matrixes. Since many spill simulations have been carried out for
each spill scenario, a probability distribution is obtained of different outcomes in
terms of environmental damage. The various impact and recovery time endpoints in
ERA Acute can be categorized according to level of seriousness and the probability
for defined categories of environmental damage can be calculated, e.g. “minor”,
“moderate”, “serious” etc. These severity categories are subjective, based on operator
preferences or industry standards where relevant (see Chap. 2 for more detail). The
applications of the methodology are discussed in Chap. 2.
1.7 Model Sensitivity and Uncertainty Issues
As a quantitative impact and restoration model, The ERA Acute methodology
attempts to describe in mathematical terms the magnitude and duration of the impact
from an accidental oil spill. The ability of such a model to accurately quantify the
relationship between the exposure and the impact in terms of mortality depends on
our understanding of underlying mechanisms of harmful action and how well these
can be implemented into mathematical functions. In developing such models, there
are numerous decisions to be made, regarding e.g. complexity versus data availability, simplification versus inaccuracy etc. It has been a major goal of the project
to develop a model that could be used robustly if there is a low availability of data
on presence of resources, but also to be able to utilize high-quality data where these
are available.
As a model that uses data on resource presence and exposure-parameters from oil
drift simulations to determine exposure and lethality probabilities (denoted p exp and
p let , described in Chap. 3), the model is naturally sensitive to these and other inputs.
15
of oil brings the impact into the next impact category. Using the continuous function in
ERA Acute will mitigate this shortcoming and is especially useful for comparing risk
between alternative cases and solutions, such as for SIMAs. Although in some cases
a category-based method may result in higher impact for a small spill, a continuous
function will be more sensitive to subtle changes in exposure. ERA Acute is therefore
expected to be more suitable for analyzing efficiency of mitigation of smaller spills
than a category-based method, which is especially important in environmentally
sensitive areas.
Because ERA Acute quantitatively evaluates the impact and risk in grid cells, risk
assessors can view results in maps at various assessment steps using a geographical
information system for any region globally. An ERA Acute environmental risk map
for a VEC can show where the risk is high or low, for example by showing average
population loss from all simulations or by highlighting the worst case by showing
maximum population loss. The environmental risk assessor can identify areas of
high risk for use in decision support and spill response planning, independently
of the region. All georeferenced results are useful for strategic use of geographic
information in risk management and planning.
For detailed studies of scenario impacts, analysis endpoints can be plotted against
frequencies in risk matrixes. Since many spill simulations have been carried out for
each spill scenario, a probability distribution is obtained of different outcomes in
terms of environmental damage. The various impact and recovery time endpoints in
ERA Acute can be categorized according to level of seriousness and the probability
for defined categories of environmental damage can be calculated, e.g. “minor”,
“moderate”, “serious” etc. These severity categories are subjective, based on operator
preferences or industry standards where relevant (see Chap. 2 for more detail). The
applications of the methodology are discussed in Chap. 2.
1.7 Model Sensitivity and Uncertainty Issues
As a quantitative impact and restoration model, The ERA Acute methodology
attempts to describe in mathematical terms the magnitude and duration of the impact
from an accidental oil spill. The ability of such a model to accurately quantify the
relationship between the exposure and the impact in terms of mortality depends on
our understanding of underlying mechanisms of harmful action and how well these
can be implemented into mathematical functions. In developing such models, there
are numerous decisions to be made, regarding e.g. complexity versus data availability, simplification versus inaccuracy etc. It has been a major goal of the project
to develop a model that could be used robustly if there is a low availability of data
on presence of resources, but also to be able to utilize high-quality data where these
are available.
As a model that uses data on resource presence and exposure-parameters from oil
drift simulations to determine exposure and lethality probabilities (denoted p exp and
p let , described in Chap. 3), the model is naturally sensitive to these and other inputs.