Environmental Engineering Reference
In-Depth Information
procedure and a numerical example are proposed
further in this chapter.
This selection of indicators is intended to
represent the most commonly reported environ-
mental impacts and objectives at airports through-
out the world. Users should adapt the selection
of indicators to the particular needs of their proj-
ect. They should also be aware that limited
knowledge is currently available for the calcula-
tion of most indicators presented in this section.
As a consequence, it should be expected that
initial implementations will rely on primarily
qualitative scoring. This tentative set should
therefore be refined and adjusted by end-users
depending upon the data available to them and
upon the scope of their project. Further research
should ensure the relevance of such indicators
and establish protocols for computing relevant
data. Indicators should also evolve toward being
mutually preference-independent to avoid any
bias in the MCA. This set of indicators is pre-
sented for illustrative purposes only and should
be optimized as far as mutual independence is
concerned.
The outcome of this process is a decision
matrix
A
containing
S
ij
scores that represent the
physical performance of alternative
A
i
toward the
objectives assessed by criteria
C
j
.
The final matrix
includes both, utility-based and cost-based criteria
(Table 6, Box 1).
Estimation of Quantitative and
Qualitative Scores Using Utility
Functions
A utility function describing a preference score
is applied at the scoring step. To handle quantita-
tive values for which a mitigation cost may not
be assessed as well as qualitative values, this
procedure converts the actual performance of a
criterion to an artificial performance value that
is dimensionless. The scale uses the same range
of numerical values for all criteria, resulting in
a uniform utility function. At the weighting step,
the individual artificial performance values are
multiplied by weights for the computation of
an overall score for all criteria based on utility.
These weights may be determined arbitrarily or
with aggregated expert judgment using pairwise
comparisons.
Quantitative scores that do not have a mea-
surable mitigation cost function are computed
using this procedure and lead to the
S
ij
scores in
decision matrix
A
, whereas the qualitative scores
are computed in a different manner. Qualitative
scores typically represent experts' judgments on
the performance of each alternative
A
i
toward each
qualitative criterion
C
j
. Such scores are obtained
by assessing the relative benefit and negative im-
pacts of each proposal and the scale of its effect.
A utility function addresses these utility-based
quantitative and qualitative scores and converts
the values of real and physical performance
S
ij
into a uniform and artificial performance
U
ij
with
no dimension. This resolves the issue of incom-
mensurable units. Two types of utility functions
are presented below.
Estimation of Quantitative Scores
Each quantitative criterion requires a specific
procedure for the computation of its score. From
a governance perspective, end-users should ensure
that stakeholders understand and acknowledge
such procedures. The accuracy of the scoring
process is again very much dependent on data
availability and required sophistication. In initial
implementation phases, we recommend end-users
to focus on indicators that address issues already
documented in preliminary impact assessments.
Such studies often provide data on issues such
as noise, GHGs, land use, traffic, population, air
quality, water quality, historic resources, wildlife,
wetlands, hazards, and human health. The nature
of the method enables and encourages interaction
between the evaluation process and environmental
impact assessments.
