3.4.2.8 Proximity to high voltage power line
Power lines are considered a noticeable source of electromagnetic
pollution to which extended exposure to some specific frequencies may result in
cancer, birth defects, decreased immunity to disease, even new sicknesses
(Michrowski 1991). A study conducted by Fews et al. (1999) observed an
increased exposure to pollutant aerosols under high voltage power line. But
another study conducted by Draper et al. (2005) and leading to the conclusion
of association between the proximity of birth residence to high voltage power
lines and children with leukemia (e.g.) has been the occasion of much debate
(Day et al. 2005).
The delineation of this hazard was built on a uniform buffer of
500 meters from the power cables (line geometry) and 1000 meters around the
distribution centers (point geometry). The distance ranges considered are
shown in the Table 8.
Table 8: Distance to High
Voltage Power Lines and Vulnerability level
|
Distance to Lines (in meters)
|
Distance to Centers
|
Vulnerability Level
|
|
0 - 150
|
0 - 300
|
4
|
|
151 - 300
|
301 - 500
|
3
|
|
301 - 400
|
501 - 700
|
2
|
|
> 400
|
> 700
|
1
|
Both distances were combined using the max function within the
single output Map Algebra tool. In areas where the two grids intersect, the max
function assigns the greatest value to the output grid. The use of this tool
was necessary to put in evidence extreme cases of risk.
3.4.3 Linear Combination of
the Variables
The Expert Opinion survey was conducted with the participation of
ten local professionals having a certain familiarity with health and
environmental issues in the study area. The respondents comprised 5
professionals in public health, 2 in environment, 2 economists and one
agronomist. They were requested to assign a score from 1 to 9 (with 1 being
very low and 9 very high) in order to rank the relative importance of the
environmental variables of the model (see results in Table 15 of Appendix A).
The ten scores were summed for each factor and divided by the total scores for
all the factors. This provided a normalized weight comprised between 0 and 1.
Hereafter this approach will be referred to Expert Opinion Weighting (EOW).
The second weighting approach assumed equal influence of the
factors on health risks and assigned the same weight of 1/9 to each. The last
weighting scheme was based on our own perception of the spatial extent and
intensity of the different hazards of the model. Henceforth, either of these
designations will be used for this approach: Own weighting or personalized
weighting. Finally, to put in evidence those areas exposed uniquely to high
risks for any factor, the maximum combination was applied. The max operator is
a local function within the Spatial Analyst tools, which uses several input
rasters to calculate the highest value on a cell-by-cell basis within the
Analysis window.
Further the linear regression technique was used to validate the
rationale under the Expert Opinion weighting and the personalized (own)
weighting scheme. The intent was to discover the degree of correlation existing
between the assigned coefficient in these two schemes and the factors in terms
of area covered and the proportion of high and very high risks.
| 
