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A decision analysis on powerline siting for a utility company

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A decision analysis on powerline siting for a utility company

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Copyright 1997
A DECISION ANALYSIS ON POWERLINE
SITING FOR A UTILITY COMPANY
by
Charles-Henri C. Tardivat
A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(Systems Management)
April 1997
Charles-Henri C. Tardivat
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UNIVERSITY O F SOU TH ERN CALIFORNIA
THE GRADUATE SCHOOL
UNIVERSITY PARK
LOS ANGELES. CALIFORNIA 9 0 0 0 7
This thesis, written by
C * A A L * S - fit ~ T a £ o iv 'A 'r ______
under the direction of hiA Thesis C om m ittee,
and approved by all its members, has been pre
sented to and accepted by the D ean of The
G raduate School, in partial fu lfillm ent of the
requirements for the degree of
/lA-zTgt} of jvv'gwce i*rsy ste m s MAisac
D ateM SX JLu.1291
THESIS COMMITTEE
Chairman
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Table of contents
List of figures - - - - - - - - - iv
List of tables - - - - - - - - - v
Acknowledgments - - - - - - - - vi
1 . Introduction
1.1 Purpose and scope of the report 1
1.2 Background on electromagnetic fields research - - 2
1.3 Overview of the report - - - - - 3
2. The transmission line decision
2.1 The utility’s decision problem - 3
2.2 Potential stakeholders and objectives - - - - 7
3. Stakeholders, objectives, and attributes
3.1 Stakeholders - - - - - - - 8
3.2 Objectives for each stakeholder group 9
3.3 Definition of the attributes - - - - - 12
4. Decision alternatives and strategies
4.1 Alternatives routes - - - - - - 18
4.2 EMF mitigation alternatives - - - - - 19
5. Decision tree - - - - - - - - 2 1
6. Performance of the alternatives
6.1 Health and safety
6.1.1 Cancers - - - - - - - 2 4
6.1.2 Number of serious injuries 32
6.2 Environment - - - - - - - 34
6.3 Social
6.3.1 Resident's fear - - - - - - 36
6.3.2 Construction disruption days 38
6.3.3 Visual degradation - - - - - 39
ii
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6.4 Economic
6.4.1 Change in property value - - - - 41
6.4.2 Costs - - - - - - - 4 2
6.5 Quality of service
6.5.1 Disruption of service - - - - - 43
6.5.2 Support of future development - 43
6.6 Probability parameters- - - - - - 44
7. Value model - - - - - - - - 4 5
8. Analysis - - - - - - - - - 4 7
9. Conclusion and insights - - - - - - - 59
10. References - - - - - - - - 6 2
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List of figures
Figure Page
1. Layout of the existing transmission line routes 4
2. Layout of proposed new 115 kV line routes 5
3. Mean-ends objective network - - - - - - 13
4. Combined hierarchy of the ends objective - - - - 14
5. Decision tree - - - - - - - - 22
6 . Ranges of values for variability used for
the exposure calculations - - - - - - 21
7. Dose-response function for an individual if there is a health effect - 29
8 . Equivalent estimated costs vs. routes for each EMF alternative - 52
9. Equivalent estimated costs vs. EMF alternative for each route - 52
10. Sensitivity analysis on the equivalent cost of a cancer 54
11. Sensitivity analysis on the base rate (BR) used to calculate the
incremental cancer risk - - - - - - 55
12. Two-way sensitivity analysis on the base rate (BR) and on the
equivalent cost of a cancer - - - - - - 55
13. Sensitivity analysis on the equivalent cost of a mile of environmental
disruption - - - - - - - - 5 6
14. Sensitivity analysis on the equivalent cost of a cancer 57
15. Sensitivity analysis on the base rate (BR) used to calculate the incremental
cancer risk - - - - - - - - 5 8
16. Sensitivity analysis on the price to be paid not to experience fear
for 5 years - - - - - - - - 5 9
IV
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List of tables
Table Page
1. Proposed alternatives - - - - - - - 6
2. List of the stakeholders considered in
the decision analysis - - - - - - - 8
3. Combined objectives elicited for each stakeholder group - - 10
4. Objectives and attributes - - - - - - 15
5. Incremental population risk due to EMF exposure
from transmission lines over 1 year - - - - - 30
6. Total number of serious injuries during the total
construction time - - - - - - - 34
7. Equivalent miles of environmental disruption due
to construction and transmission lines- - - - - 35
8. Total number of residents experiencing fear of EMF- - - 37
9. Number of total disruption days due to construction - - - 39
10. Equivalent miles of visual degradation 40
11. Total cost - - - - - - - - 42
12. Price-out table for all measures by all stakeholders
and decision analysts - - - - - - - 4 7
13. Alternatives by objectives matrix (consequences) 49
14. Total dollar amounts of all the objectives
for all the alternatives - - - - - - - 5 0
15. Ranking of the alternatives - - - - - - 51
v
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Acknowledgments
I would like to thank Professor Detlof von Winterfeldt as well as Dr. Ralph
Keeney for their insights and invaluable inputs, for their patience in guiding me to fully
understand the topic, and for providing feedback on my research. Despite their busy
schedules, they spent a great deal of time in reading several drafts of my thesis and other
writings and were both supportive, patient and encouraging advisors.
I would also like to thank Professor William Petak for his valuable feedback and
insight from a different perspective. He inspired and encouraged me and was very
supportive throughout my graduate career.
Professor R. John deserves thanks for his contribution to my thesis work and for
his service as a committee member of this dissertation.
I would like to thank J. Adams for his insight and his patience in answering my
numerous questions about electromagnetic fields and its concepts. He spent a great deal
of time in going over my calculations and various estimates of field strength (miligaus
levels) for the different alternatives.
Special thanks go to my family and especially my father without whom none of this
would of ever been possible. Thank you for the education and the opportunity you have
given me.
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1. Introduction
1.1 Purpose and scope of the report
Transmission lines provide the most reliable and cost-effective means to transmit electricity from
generating stations to distribution centers. When population growth is expected in an area, a utility
company often has to develop new transmission lines or reconfigure existing ones in order to be able to
meet the future demand. But even if there is a clear need for new transmission lines, there often exists
opposition to the project resulting in long delays and economic losses. Residents and environmental
groups are very concerned with the potential negative consequences associated with new transmission
lines. Reasons for this concern are possible reductions in property values, aesthetic impacts and health
risks (e.g., Gregory & von Winterfeldt, 1996). Recent research indicating the possibility that exposure to
electromagnetic fields from transmission lines may be associated with cancer promotion has increased
these concerns (Nair et al., 1989; National Institute of Environmental Health Sciences, 1995: Savitz.
1992).
Decision analysis is a methodology for aiding organizations like utility companies in making
complex decisions (Keeney & Raiffa, 1976; von Winterfeldt & Edwards, 1986). It is especially useful
when the decision consequences are uncertain, when there are multiple decision objectives, and when
stakeholders involved in or affected by the decision disagree. This report provides an application and
illustration of decision analysis to the problem of siting and configuring a transmission line.
For the purpose of this report, we will consider the case of a rural area which has presently a 33
kV distribution line that needs to be upgraded to a 115 kV line in order to meet projected electricity
demand in the area reliably. While the problem was derived from a real problem of a utility company, it
was changed to a somewhat simplified and more generic problem in order to better illustrate the use of
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decision analysis. No specific references to the utility company or the stakeholders involved in this project
will be made.
1.2 Background on electromagnetic fields research
Over the past fifteen years, there has been an increasing interest in the association of
electromagnetic fields (EMFs) with potential health effects, including leukemia and brain cancer. Several
biological and epidemiological studies were conducted in the past two decades, but the results are still
inconclusive. In particular, no clear causal mechanism has yet been identified by which EMFs may
promote cancer. Of fourteen residential studies that examined childhood cancer, eight found some
association between exposure to EMF and childhood cancer. Of eight adult residential studies, only two
found significant associations of health effects with EMF exposure. Out of these twenty-two studies, only
four correlated health effects with direct measures of EMF exposure, and only two of the four found
statistically significant effects (National Institute of Environmental Health Sciences, 1995).
Biological studies of the effects of EMF exposure on cells, tissues, and whole animals have also
been largely inconclusive (Anderson, 1993; Nair et al., 1989; Sagan, 1992). While biological responses of
EMF exposure can be demonstrated in the laboratory on the cellular and hormonal level, the relationship
between these responses and health effects remains unclear.
While the research remains inconclusive, there is an increasing concern about EMF exposure and
the possible health effects that it may cause (Florig, 1992). The government as well as utility companies
have already responded to the uncertainty associated with EMF. Examples are standards for limiting
EMF exposure near new transmission lines and changes in the configuration of transmission lines to
reduce fields (Southern California Edison, 1994).
2
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1.3 Overview of the report
This report will first describe the decision problem that a utility faces when siting and
configuring a transmission line in a rural area (chapter 2). Chapter 3 lists the stakeholders involved in
this problem, as well as their objectives and the measures used to quantify them in the decision analysis.
Chapter 4 describes the utility’ s decision alternatives and strategies. Chapter 3 describes the building of
the decision tree used for the calculations. Chapter 6 summarizes how well the alternatives meet the
objectives and chapter 7 describes value models that are used to assess the preferences of the stakeholders
for the utility's decision alternatives and strategies. Chapter 8 contains the results of the decision analysis
and chapter 9 provides a conclusion.
2. The transmission line decision
2.1 The utility's decision problem
This decision analysis addresses a decision problem faced by a utility company in a rural area of
approximately 80 square miles which currently consists primarily of undeveloped desert land, low density
housing and a few higher density developments. The population in this area, shown in Figure 1, is
expected to grow significantly in the next five to ten years. Presently, a 33 kV line provides electricity to
all the customers in this area. To meet projected future demand, this line needs to be upgraded to 115 kV.
This new line must connect to the substations shown in Figure 1 at the north-eastern and the south
western comer of the service area. Because the new line has a fairly low voltage and serves a sub-region
of the utility's service area it is also referred to as a sub-transmission line.
3
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Lakeland Rd
(3.9mi) (Z5nu)
(1.2mi)
Vilain Rd
Hyppic Terrace
I Existing Lines
i Pond
School
Residential Area
B Future Residential Area
□ Commercial Area (Business
Offices. Shops...)
Substation
Undevelopped Areas
Figure I. Layout or the existing transmission lines that can be upgraded to 115 kV
4
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N
Lakeland Rd
Vilain Rd
Proposed (i) ~ ~ ~: | School 3 Future Residential Area Substation Pond
R O U t“ n ! " " ■ Residential Area 0 C^ ercialArea(Busine“ S Undcvelopped Areas
' Offices, Shops...)
Figure 2. Layout of the proposed new 115 kV line routes
5
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Assuming the utility company must build the line at some point (either today or in 5 years) it is
faced with two decisions: first, which route should be used for the new line, and second, which EMF
mitigation alternative should be used in order to limit the field exposure. Three possible routes are shown
in Figure 2. EMF mitigation alternatives include splitting the lines in order to reduce currents, and
switching the side of the road at which the line is built to the side with less population. Table 1 shows the
different alternatives considered for this decision analysis.
Table 1
Proposed Alternatives
Route Alternatives Length of Line
1. Lakeland Rd - Jackson Rd : 15.2 miles
2. Lakeland Rd - Goat Creek Rd - Donavan Rd : 17.2 miles
3. US Highway - Donavan Rd : 15.2 miles
EMF Mitigation Alternatives
The following line configurations were considered for each route:
1. Base case line : Regular 3 phase, 115kV
2. Split phase the lines
3. Split phase the line only at populated areas
4. Change the side of the road on which the power lines are to be built at high
density areas
W AIT 5 Years
With this alternative, the utility company waits 5 years and then decides on one of the
routes and one of the EMF mitigation alternatives.
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2.2 Potential Stakeholders and Objectives
Stakeholders in this decision are any individuals or organizations that are potentially affected by
the decision consequences or that have a professional or other interest in the decision. The local residents
and the various residential and commercial development companies are examples of the potentially
affected parties. The interested parties are not directly impacted by the decision but have an interest in the
issue. Environmental groups such as the "Advocates for the Desert" do have an interest in the decision.
Their concern is with the potential negative impacts a new line will have on the environment.
It is important to select a broad range of stakeholders in order to provide the decision maker with
a comprehensive set of objectives (Keeney, 1992). The principal objectives of this decision problem that
come to mind are to minimize the potential health and safety impacts that might be associated with the
new transmission lines, both during and after the construction; to minimize the impact on the
environment; to minimize the social impact on the residents in the area; to minimize the direct costs of
building the line; and to maximize the quality of electrical service.
However, different stakeholders are likely to put a different emphasis on these objectives. For
example, the residential and commercial developers are likely to stress the quality and reliability of the
electrical service; environmentalists will stress objectives related to the environment; local residents will
be concerned with health and social effects.
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3. Stakeholders, objectives, and attributes
3.1 Stakeholders
The goal is to select stakeholders that can jointly provide a comprehensive list of the objectives
for this decision. Table 2 lists the stakeholder groups that were considered in the decision analysis.
Table 2
List of the stakeholders considered in the decision analysis
Environmentalists: California Council for Environmental and Economic
Balance
Advocates for the California Desert
Sierra Club
Residents: Residents within 400 ft of the proposed line sitings
Residents affected by aesthetics
Future residents
Travelers
Utility Company: Utility of the Desert
Developers: Residential company
Land owners
Chamber of Commerce
Groups concerned
With EMF:
School district
Omaha Parents for the Prevention of Cancer
Professional G roups: American Physical Society
Bioelectromagnetic Society
Regulators: California Public Utility Commission
US National Park System
State California Park System
City and County Offices
For each group, at least one organization was contacted and objectives were elicited from one or more of
their representatives.
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The utility company and the developers both want the line to be built and thus are in favor of
such project. The developers include the residential company which wants to be sure that the future lines
can support their electrical needs, the land owners, and the Chamber of Commerce who wants to promote
growth in the area. The Utility Company o f the Desert is in charge of the project and is the final decision
maker.
The government agencies and regulators typically want growth in the area and yet need to
address the public concerns. The City and County offices, for example, want to make sure that all the
legal permits are obtained, all the regulations are met, and all the concerns of the public are answered.
The US National Park System is more concerned with the regulatory aspects of building new lines on
undeveloped areas and the potential environmental impact associated with them.
The environmentalists, the residents, and the groups concerned with EMF are all stakeholder
groups which are concerned with the potential negative consequences associated with the proposed new
lines. Future residents as well as temporary residents like travelers or business owners need also to be
considered in the analysis.
3.2 Objectives for Each Stakeholder Group
When possible, a representative from the stakeholder groups was interviewed and his or her
objectives were elicited individually. Table 3 lists the objectives for each stakeholder group. They were
asked to list what they thought were the most important objectives to reach in that decision.
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Table 3
Combined objectives elicited in interviews from each stakeholder group
1. Utility Company;
Minimize health and safety impacts. (E)°
Minimize environmental impacts. (E)
Minimize social impacts. (E)
Maximize equity of the decision process. (P)
Meet regulations. (M)
Maximize responsibilities with regard to the public. (M)
Maximize benefits to the community. (E)
Minimize direct costs. (E)
Minimize indirect costs. (E)
Minimize delays. (M)
Minimize impacts on system reliability. (E)
Minimize potential EMF exposure. (M)
Minimize disruptions of customer service. (E)
Minimize impact on corporate image.(E)
2. Environmentalists:
Minimize environmental impacts. (E)
Minimize environmental disruption during construction.(E)
Minimize impact on biota and non-biota. (E)
Minimize health and safety impacts. (E)
Minimize length of line. (M)
Minimize impact on aesthetics. (E)
Minimize future growth. (M)
Maximize conservation. (M)
Maximize consistency with land-use plans. (E)
3. Residents:
Minimize health and safety impacts from construction phase. (E)
Minimize health and safety impacts from EMF. (E)
Minimize indirect costs (Increase in rates). (E)
Minimize direct costs (Property depreciation). (E)
Minimize hassle associated with construction and new lines
(noise; dirt and dust; traffic delays).(E)
Maximize fairness in route selection. (P)
Minimize the fear due to electromagnetic fields. (E)
Minimize impact on the environment (E)
Minimize aesthetic impacts. (E)
Maximize benefits. (E)
Minimize interference with radio and television reception. (E)
4. Developers:
Minimize delays of planned development (M)
Minimize impact on planned development layouts. (M)
Maximize health and safety of workers and of future residents. (E)
Minimize hassle due to construction. (E)
Minimize environmental impact. (E)
Minimize loss of marketability. (E)
Maximize future service. (E)
Maximize future growth. (M)
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Table 3 (continued).
5. Special Groups:
Minimize environmental impact. (E)
Minimize health and safety impacts. (E)
Maximize information distribution about EMF. (P)
Minimize unnecessary fear. (E)
6. Regulators:
Maximize compliance with local and governmental regulations. (M)
Minimize environmental impact (E)
Maximize public acceptance (taxpayers). (M)
Maximize safety and health. (M)
Maximize aesthetics. (M)
Minimize financial loss (i.e.: loss in property taxes... ) (E)
0 (E)= Ends objective (P)= Process objective (M)= Means Objective
The decision analyst then ordered the objectives as listed in Table 3 and categorized them in three types:
ends, means, and process objectives (see Keeney, 1992):
- Ends objectives are important in and by themselves. They are the essential reasons for the
interest in the situation. When someone asks why an end objective is important, the answer is self-
evident. For example, protecting the environment or the health and safety of the public are objectives that
need no further justification.
- Means objectives are important because they help to achieve the ends objectives. For example,
to m inim ize potential EMF exposure is a means objective because it contributes to the ends objective of
m inim izing the human health and safety impacts, as well as the environment (biota).
- Process objectives relate to how a decision is to be made, for example, fairness in the decision
process, or involvement of the public. The process objectives are important because they point out ways to
improve the decision-making processes.
As Table 3 indicates, all of the stakeholders are concerned with the ends objectives of minimizing
health and safety impacts, and minimizing environmental impacts. The utility company is concerned with
m axim izing the equity of the decision process, meeting its responsibilities with regard to the public, and
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maximizing the benefits to the community. Several economic objectives were defined, but. the utility
company clearly shows concern for the public's perspective on the proposed transmission line upgrade.
The environmentalist group is clearly concerned with the conservation of the biota and non-biota and
most of its objectives are directly related with the protection of the environment. The residents show
various concerns. Health and safety and economic objectives dominate overall but there is also concern
for the quality of service that the future line will provide.
Overall, five general classes of ends objectives emerge from this listing: the safety, environment,
social, economic and quality of service related objectives. Figure 3 shows the five major ends objectives
and relates them systematically to the process and means objectives. In order to provide a consistent set of
objectives that capture all the stakeholders' concerns, it is then useful to construct a combined hierarchy of
ends objectives (a tree that specifies, at increasing levels of detail, what the higher level objectives mean).
To achieve this, one begins with the major ends objectives listed in Table 3. Subsequently, each top level
objective is specified by a set of objectives that define it. The sub-objectives of the individual stakeholders
are used for this purpose. If some of the sub-objectives are defined at even lower levels of detail, the
process is repeated. Figure 4 shows the result of this process.
3.3 Definition of the attributes
The ends objectives in Figure 4 need to be operationalized in order to assess how well the
alternative routes and EMF mitigation attributes achieve them. To accomplish this task, each of the
eleven lowest level objective in Figure 4 is defined by an attribute that indicates the potential
consequences of each strategy. These are defined in Table 4.
It is important for the decision analysis that the attributes in Table 4 are well defined,
understandable, and operational. The attributes are well defined if they capture the intended meaning of
12
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the ends objectives and are unambiguous. The attributes are understandable, if they are relevant and clear
to lay people. The attributes are operational if it is possible to describe the consequences of the
alternatives with respect to them. In addition, they must provide a sound basis for judgments about the
desirability of the various degrees to which the objectives might be achieved (Keeney, 1992).
MEANS OBJECTIVES
H I
| Minimize length oflinc HI
Minimize EMF exposure
Maximize compliance
► j Mimn ia : Aesthetic Impacts
Minimize fear o f EMF
Minimize hassles
]
Maximize customer satisfaction
Minimize delays
PROCESS OBJECTIVES
Maximize consistancy
with land use plans
Maximize public
invoivment
Maximize information
distribution
Maximize fairness in mule
selection
Maximize equity of decision
process_________
ENDS OftJECnVES
MINIMIZE HEALTH AND SAFETY IMPACTS
MINIMIZE ENVIROMENTAL IMPACTS
MINIMIZE SOCIAL IMPACTS
MINIMIZE COSTS
MAXIMIZE QUALITY OF SERVICE
Figure 3. Means-ends objective network
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Minimize Health and
Safety Impacts
Maximize Quality
o f Service
Minimize Enviromental
Impacts_______
Minimize Social
Impacts
Minimize Direct Costs
Minimize Fears due to
Electromagnetic Fields
Minimize Health and Safety
Impacts from Construction
Minimize Enviromental
Disruption
Minimize Noise, Dirt and Dust
Minimiz Trafic Delays
Maximize Health and Safety of
Workers during Construction
Maximize Support of Long Term
Growth in the Region
Minimize Disruption of
Customer Service
Minimize Impact on Aesthetics
Minimize Health Impacts
from EMF exposure
ENDS
OBJECTIVES FOR
SUBTRANSMISSION LINES
Figure 4. Combined hierarchy of the ends objective
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Table 4
Objectives and attributes
OBJECTIVES ATTRIBUTES
Health & Safetv
Minimize health impacts from EMF
exposure
Number of cancers
Minimize health and safety impacts
to workers during construction
Number of serious injuries*=
(Number of worker hours) x
(Risk/Hours)
Environment
Equivalent miles = (Miles in
Res/Com/School) + (1.5 ) x (Miles
Minimize environmental disruption
in sparsely pop. areas) + (2) x
(Miles in undeveloped areas) + (10)
x (Miles in biological sensitive
areas)
Social
Minimize fear of the residents
Number of residents experiencing
fear
Minimize disruptions to the Number of total person-days of
residents dusruption
Equivalent miles = Miles of regular
overbuilt + 2 x miles new regular
Minimize visual degradation 115kV + 1.5 x Split existing lines +
2.5 x New split lines + Number of
street crossings
Economic
Minimize property value
depreciation
$ of depreciation
Total Costs Total real year $
Oualitv of Service
Disruption of customer service
Number of hours without service for
all residents for 1 year
Maximize support of future Equivalent miles of line providing
development support for future developments
* injury that would prevent the worker from continuing
his/her work for at least 4 days
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Minimise health impacts from EMF exposure - Minimize number of cancers
To measure health effects from EMF exposure, the increase in number of cancers over a period of
ten years is estimated. A ten year horizon is used because, on average, residents stay in this area for about
ten years. The cancers of concern are leukemia and brain cancer. The unit for this attribute is number of
cancers.
M inimize health and safety impacts to workers during construction - Minimize number of injuries
The measure of health and safety impacts on workers is the number of injuries that will occur
during the construction. For the purpose of this analysis, an injury is defined as any event that will
prevent the worker from attending to his/her duties for a period of four days or more. The unit for this
attribute is number of injuries.
M inimize environmental disruption - Minimize Equivalent miles disrupted by project
Environmental disruption will primarily occur during the construction phase and the longer the
line is, the more severe the disruption will be. In comparison with the sparsely populated or undeveloped
areas, the environmental disruption will be less severe in currently developed areas where lines already
exist and thus less damage will be done to the environment during construction.
A constructed measure "equivalent miles” was developed that captured these ideas:
Equivalent miles o f environmental disruption = / x miles o f line in developed areas
+ 1.5 x miles o f line in sparsely populated areas + 2 x miles o f line in undeveloped areas
+ 10 x miles o f line in biologically sensitive areas.
In effect, this constructed measure says that a mile of line in a sparsely populated area is 1.5 times "worse"
in terms of environmental disruption than a mile in a developed area, that a mile of line in an unpopulated
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area is twice as bad as a mile in a developed area, and that a mile along a biologically sensitive area like
the pond located along Jackson road is 10 times as bad.
Minimize fear o f the residents - Minimize number o f residents experiencing fear
This attribute is the number of residents experiencing fear of EMF during the first year of
construction.
M inimize disruption - M inimize number of total person-davs of disruption
This attribute is defined as the total number of person-days of disruption that the population
along a route will experience during the construction.
Minimize aesthetic impact - equivalent miles
Aesthetic impacts will be determined by four factors: The length of the line, the configuration of
the line (regular or split), whether the line is new or built over an existing line and the number of street
crossings. With the other factors equal, the longer the line, the more overall aesthetic impacts it will
have. The configuration of the line will affect its appearance: Split phase lines have six conductors and
thus have worse appearance than regular lines. When the line is built over an existing 33 kV line, the
overall aesthetic impact is less than when a line is built where none existed before. Finally, a street
crossing has additional aesthetic impacts.
To capture these thoughts, the following equivalent mile measure was constructed:
Equivalent miles o f aesthetic impacts = miles o f regular overbuilt lines
+ 2 x miles o f new regular lines + 1.5 x miles o f split overbuilt lines
+ 2.5 x split new lines + number o f street crossings.
This measure implies that new lines have "twice the aesthetic impacts" of overbuilt lines, that split lines
have 1.5 times the aesthetic impacts of a regular line, when they are overbuilt, and 2.5 times the aesthetic
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impact when they are new. The aesthetic impact of a street crossing is judged to be equivalent to a mile
of regular overbuilt line.
M inimize property value depreciation -1996 dollar depreciation value
This attribute is measured in 1996 real undiscounted dollars of total depreciation of property
values near the new lines.
Minimize total cost - 1996 dollar cost
Cost of building the new lines is measured in 1996 real undiscounted dollars.
Minimise disruption of customer service - number of resident-hours without service
To measure disruption of customer service the total of resident hours of disrupted service was
estimated. These numbers were calculated for a period of one year and the unit is hours.
Maximize support of future development- equivalent miles
The more miles of new line that pass through areas with development potential, the better the
new line will be able to support future development in the area. The measure for this objective was chosen
to be the number of miles of new line that passes through undeveloped areas.
4. Decision alternatives and strategies
4.1 Alternatives routes
Three different routing alternatives were considered for this decision analysis. Figure 2 shows
the proposed routes selected for this decision problem.
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Lakeland Rd - Jackson Rd:
This route is 15.2 miles long. There are existing lines through the entire route except on Jackson
Rd where they are no present lines passing by the depicted future residential area. This route passes
through two large undeveloped areas, one future residential area with a forecast population of 150, and a
commercial area with a population of 100. It also passes along a pond considered as a biologically
sensitive area. The total population within 400 ft of this route is 397.
Lakeland Rd • Goat Creek Rd - Donavan Rd:
This is the longest route with 17.2 miles. It passes through two undeveloped areas, one
residential area of population 75, and one commercial area of population 100. The total population of the
route is 342. There are existing lines throughout the entire route except for half a mile on Donavan road
between Goat Creek and Jackson road.
US Highway - Donavan
This proposed route is 15.2 miles. It passes through a large unpopulated area, a school with an
assumed population of 250, and a commercial area with a population of 100. This route has the largest
population with 497 residents considered in the analysis. There exists lines throughout the entire route
except for about one mile next to the school.
4.2 EMF mitigation alternatives
Several different EMF mitigation alternatives exist. For the purpose of this decision analysis,
four different options were selected, chosen for their differences in cost and EMF reduction potentials.
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Regular 115 kV:
This is the base case and represents the basic upgrade of line from 33 to 115 kV. The 115 kV
line is installed on wooden poles and has a triangular configuration. The minimum clearance above the
ground is 30 feet. When the new line passes areas with an existing 33 kV line, new poles are constructed
and both lines would use the same poles, with the 115 kV line being built over the 33 kV line.
Split phase:
Instead of a single circuit line with three conductors, two parallel circuits with six conductors
would be built and phased to achieve maximum field cancellation. This form of construction is
significantly more expensive than conventional single-circuit construction. When the whole line is split
phase, the total field reduction is greatest.
Part split:
This alternative consists in splitting the line only at the areas where a school, a residential, or a
commercial area is present. This alternative was considered in order to find an alternative that could
balance costs versus field reduction.
Alternate sides:
Since the field strength is inversely proportional to the square of the distance, EMF field strength
can be reduced by increasing the right-of-way distance. This can be achieved simply by constructing the
line on the opposite side of the street of an existing residential, commercial, or school area. Switching
will only be considered at the high population areas like schools, commercial areas, and both the existing
and planned residential area.
2 0
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Wait 5 years:
The utility company may choose to wait five years until further research is done and possible new
shielding techniques are available and the research may become more conclusive. The advantage of this
alternative is that it may prove to be worthwhile if the growth in the area is lower than expected. The
disadvantage is that on the opposite hand, there might be a higher than expected growth and the research
might still be inconclusive in five years.
S . Decision t r e e
The decision tree (Figure 5) shows the structure of the decision problem. The initial decision
involves four alternatives. The utility company can decide to build the line on route 1 , route 2 , route 3, or
to decide to wait five years before construction. For the purpose of the analysis, it was assumed that home
owners, shop owners and their children will live in the area for 10 years. This allows to calculate
potential impacts of future EMF research on the decision and examine the impact of that decision on the
subsequent five years . This five year split also allows to account for population growth which will be
determined after the first five years.
Following the initial decision to chose a route, the decision maker must decide what EMF
mitigation measure to use. Each alternative is followed by uncertainties about EMF research results
(positive, conflicting negative), uncertainties about health effects (yes, no), and uncertainties about future
population growth (high, low). "Research positive" means that the ongoing and future biological and
epidemiological studies are consistently positive and that there is evidence establishing a causal
relationship between EMF exposure and health effects. "Research conflicting" means that the issue
remains as it is today - unresolved with inconclusive findings. "Research negative" means that ongoing
and future studies will show no significant link between EMF exposure and health effects. If the "Wait 5
years" alternative is chosen, the research results will be known at the time that decisions need to be made.
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PEfZPoa
No H a th Effects
Hfri Future growth,
HattRacaehCctdlktiag
PRoCerf
^fcohhRathNcgawe
.Low Fubrc growth.
^Locd Split Phwe
Jwittfa Side of the Rood
US Highway- Dcoewp
No H a h b Effects
Split
Loaded Split Phac
\switth Side of the Rood.
Ljfcdand- Go* Qedt* Docann.
Kakh R o v ch Podtive
\U3 Hqjbwoy- PoMvm
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Figure 5. Decision tree for the power line siting problem.
Decision branches originate in squares, chance events originate in circles, and triangles denote end nodes.
When the tree ends with a *+’ sign, it is continued with the subtree just above it.
2 2
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The second uncertainty is about the existence of health effects, conditional on the research
outcomes. This means that the research will indicate whether or not there is a causal link between EMF
exposure and biological changes, but these changes might also produce a specific adverse health outcome.
In this decision analysis, leukemia and brain cancer are considered as the primary health outcomes of
interest Thus, even if the research turns out to be positive in five years, it would not be certain that EMF
exposure promotes leukemia.
The third uncertainty is about the potential population growth in the area. The primary reason
for upgrading the existing 33 kV system to 115 kV lines is to be able to provide electrical service for
future residents. For the purpose of the analysis, we have considered two scenarios which are given
initially the same likelihood: P (High future growth) and P (Low future growth). High future growth
assumes that the population will increase by 20% in five years and then stay at that level for the
remaining five years. Low future growth assumes no increase in population in the next ten years.
When taking the decision to wait 5 years, the utility company will first learn the research
outcome after five years, followed by the growth outcome. The decision maker must then decide which
route to build. We assume that even if the growth is lower than expected after five years, the utility
company will still decide to build thinking that there will be sufficient growth in the future to justify the
upgraded lines. Another decision immediately follows where the EMF mitigation alternative must be
chosen. The issue of whether there are health effects is resolved and the associated consequences accrue.
If the decision is taken to build today and to choose one of the three routes, the utility company learns
about the growth, the health research, and the health effects only after five years, after both decisions
(Route and EMF mitigation) have been taken.
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6 Performance of the alternatives
6.1 Health and safety:
6.1.1 Cancers:
In order to estimate the potential adverse effects associated with EMF exposure, the number of
cancers associated with EMF exposure was calculated for each alternative. Exposure models by Adams
(1995) were used to estimate the cumulative individual exposure associated with EMF exposure form 115
kV lines. These models were combined with a dose-response function to estimate increases in cancer, if
there are health effects.
Adams calculated field exposure for the residents at different points on the map shown in Figure
2 on page 5 which shows the three proposed routes. The Lakeland - Jackson passes by a future
development of assumed future population of 150. The Lakeland • Goat Creek - Donavan route passes by
a residential area of population 75 and is two miles longer. The US Highway - Donavan route passes by a
school with 250 students, faculty, and staff. All three routes pass by a commercial area of population 100.
To calculate exposure, Adams divided the map into cells. Each cell is 0.5 mile long along the route and
400 ft. wide. Cells are located on each side of the route and each is further subdivided into 20 sub-cells
0.5 miles long and 20 feet wide. For the purpose of the exposure calculations, it was assumed that no
buildings were present within 100 feet of the lines. Thus the first 5 sub-cells were not included in the
calculations. Regardless of the position on the map, the population is assumed to be distributed evenly in
the given cell. The exposure is then calculated for each individual at the center of that sub-cell. For
example, there are 75 people in the residential area depicted on the map. These people are distributed in
the 100 to 300 feet range thus in 10 sub-cells. The average exposure is then calculated for each of these
people at the center of the cell.
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There are five types of areas used for the EMF exposure calculations:
Low density areas: These are all the areas on the map which are not specified as either a school,
residential, future residential, or commercial area. For the purpose of the calculations though,
undeveloped areas indicated in Figure 1 and 2 will be considered as low density cells. The total assumed
population for each of these low density area is 2.5 residents per cell. They are located from 100 to 400
feet from the line. This means that there are 15 grids each with 2.5 / 15 = 0.17 persons / grid.
School: The total population for the school is 250 including staff, students, and teachers. The
school is located 100 to 240 feet from the line. To remain consistent in our equality of exposure, it was
assumed that the time spent by one child during a school day under EMF exposure was equal to on adult
being exposed to the same field for a period of 24 hours. Using this rationale, we could thus calculate the
average individual exposure for the students.
Residential: The total population is 75. The residential area is located 100 to 300 feet from the
road on one side of the line and 160 - 360 feet on the opposite side of the line. This is because of the road
assumed to be 60 feet wide as well as the right-of-way imposed by 115 kV lines.
Future Development: The total assumed future population is 150. This is located at the same
distance from the line the residential area is.
Commercial: The total population is 100 and the area is located at the same distance from the
line the residential area is.
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Given the population density for each cell and the location of each cell the EMF cumulative
exposure is calculated as described by Adams, Zhang, Morgan, and Nair (1996). A calculation of variable
magnetic fields adjacent to transmission lines was presented by Olsen (1994). Figure 6 shows the
mapping of randomly chosen x values onto the daily maximum current, % of daily maximum current, and
the current unbalance. The last diagram shows a sample 5 minute period of the field strength at 50 feet.
The loading and current unbalance are generated as functions of time using a Monte Carlo approach.
Before the magnetic profiles are calculated at a certain point in time, the following steps are taken:
- The daily maximum current, which reflects the annual variations in loading, is randomly
selected from a range of values as indicated in Figure 6.
- The percentage of daily maximum current, reflecting daily variations in loading is chosen from
one of the three possible values.
- The current unbalance, both magnitude and phase angle, reflecting variable load unbalance, is
randomly selected from an allowed range.
These steps are repeated for different distances up to and including 400 feet from the lines.
Once this set of data was obtained, the population in each grid was submitted to the above
simulation for their respective distance from the lines. The total cumulative exposure was then calculated
for each of the twelve alternatives. For the purpose of this analysis the only exposure function considered
was the time weighted average assuming a linear dose response function. The cumulative exposure for
the whole population along a route was determined.
In order to approximate the number of leukemia cases per year of exposure, u'e needed to
translate the cumulative population exposure to an incremental risk associated with EMF exposure. A
dose-response function was created for that purpose (Figure 7). To calculate the incremental risk, we first
calculate the average individual exposure by dividing the population exposure (in mG) by the total number
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Amps
of people along the line. This yields the average individual exposure which then is plotted on the x-axis.
Judging from the epidemiological studies, if there truly are health effects from
Daily Maximum Current
500
400
200
100
0
0 0.2 0.4 0.6 0.8 1
x, random value
Current Unbalance
2
1 . 5
1
0.5
0
0 0.2 0.4 0.6 0.8 1
x, random value
% of Daily Max. Curr.
0.8
.= 0.6
0s
0.4
0.2
0 0.2 0.4 0.6 0.8 1
x, random value
Field Strength at 50'
1 2 3 4 5
Time (minutes)
Figure 6. Ranees of values for variability used for the exposure calculations
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EMF exposure, they would likely double or triple the base rate of the leukemia and brain cancer. A dose
response function was defined that has no increase in cancer risk for an EMF exposure of 0 mG and a
five-fold increase for 10 mG.
Thus, the dose-response function is defined as
Odds ratio = (0.4 « mG) + I.
Using this odds ratio (OR), the individual incremental cancer risk IR can be calculated as
IR = OR * B R - BR,
where BR is the base rate of the cancer under consideration. IR has to be multiplied by the affected
population to obtain incremental population risks.
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y = (.4x) + 1
5
3
1
0
10 5 0
Cumulative Exposure in mG
To calculate the incremental population risk for n people exposed to a population exposure of z
mG, using the above dose-response function:
1. Calculate z/n - average individual exposure
2. Determine Odds Ratio[z/n ] - Base Risk = average incremental risk for an individual
3. Determine Incremental Population Risk = O R [z/n j x B R x n
Figure 7. Dose-response function for an individual if there is a health effect
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Table 5 shows the incremental population risk findings.
Table5
Incremental population risk due to EM F exposure from transmission lines over a 1 year period
R id e l
Cunuiative
espoaunKmG)
mG/person**
Population Risk***
( if there is a heal t h r ife t)
Regular 115 kV
Split phase
Part split
Change sides
397
397
397
397
120.25
75.41
85.04
75.07
0.3029
0.1899
0.2142
0.1891
0 .0 0 4 8 1 0
0 .0 0 3 0 1 6
0 .0 0 3 4 0 2
0 .0 0 3 0 0 3
Route 2
Regular 11 5 kV
Split phase
Part split
Change sides
342
342
342
342
96.84
61.12
72.11
65.28
0.2832
0.1787
0.2108
0.1909
0 .0 0 3 8 7 4
0 .0 0 2 4 4 5
0 .0 0 2 8 8 4
0 .0 0 2 6 1 1
Rmde3
Regular 115 kV
Split phase
Part split
Change sides
497
497
497
497
180.41
110.02
119.65
103.00
0.3630
0.2214
0.2407
0.2072
0 .0 0 7 2 1 6
0 0 0 4 4 0 1
0 .0 0 4 7 8 6
0 .0 0 4 1 2 0
* Total number o f parsons within 400 f t o f each side o f the proposed lines.
* * Cumulative Exposure / Total number a f persons
*** Annual Popul rt i on risk =[](n£j/person)x (Base rate) x (Total number o f persons)]
- [(Base rate) x (Total number of persons)]
where /(mOperson) =f 0.4 x mG/person) + / see figure 7
First, the total number of residents for each route is determined. Tfes is achieved by counting the
miles of line along the. km density cells, and by adding the population of tfie different special areas
(School, residential, etc.). Note that route 3 has the highest count since it passes along a school with a
popolationof250.
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The cumulative exposure column displays the exposure calculations by Adams (1995). The
individual cumulative exposure is then calculated simply by dividing the exposure by the total number of
people. The population risk is then calculated using the following equation:
Incremental Population risk = (Odds Ratio x Base Rate x Total number of persons)
- (Base rate x Total number o f persons).
The Odds Ratio is obtained by using the dose-response function as described previously.
The annual base rate of leukemia is 0.0001 per person per year (American Cancer Society, 1992).
As the results indicate, Route 2 with a global split phase configuration has the lowest number of
expected cancers per year. There is a significant difference between the regular 115 kV configuration and
the other three EMF mitigation measures. Even if the line is split only at high population density areas,
there is a significant decrease in comparison with the regular 115 kV ( around 40% for all three routes).
Note also that route 3 has the highest number of estimated cancers per year, almost twice the amount of
route 2 for all of the EMF mitigation alternatives.
Cancer risk was calculated for all endpoints of the decision tree. For the "no health effects"
endpoints, the cancer risk estimate was set to 0. For the other branches, the risk estimates depended on
the route chosen, the EMF mitigation measure chosen, and on whether or not there was population
growth. When there is growth, the population is multiplied with a growth factor (20%) for the second five
years of the decision tree. If the decision is to wait, there will be no incremental risk during the first five
years. If a line is built after at that point, the incremental risk is calculated, depending on the route,
mitigation alternative, and whether or not there is growth. In this case, the incremental risk is
accumulated for five years only.
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As an example, consider the case in Figure 5, in which route 1 is chosen, the regular 115 kV
configuration is adopted, there is high future growth after five years, the health research ends up being
positive, and there are health effects.
The total number of cancers is then calculated as follows:
Total number o f cancers for the IOyears =(5 years x Number ofcancers per year) + (5 yearsx
Number o f cancers per year if there is growth).
If on the other hand, the utility company decides to wait five years before upgrading the lines and after
five years, health research is positive, there is high future growth, route 1 is chosen with a regular 115 kV
configuration and there are health effects, then the total number of cancers is calculated as follows:
Total number o f cancers for the 10 years = (5 years) x Number of cancers per year if there is
growth.
6.1.2 Number of serious injuries
Whenever construction of power line occurs, a construction risk is associated with it. This risk
comes from possible electrocution, falls, and other serious injuries. For the purpose of the decision
analysis, serious injuries is defined as any injury that will prevent a worker from continuing his/her work
for four days or more. These numbers were obtained in the following manner.
First the average construction time for each route was assessed. A utility expert was interviewed
and asked how long it takes on average to build 15 miles of 115 kV line. The same question was then
repeated for the split line scenario. For the alternate side, the average number of side changes based on
the layout was assessed. It was also said that it would take less time than split phase. The same reasoning
was used for each route. The average number of workers to be working on a project like this was assumed
to be ten. The total number of working hours was thus calculated for each route.
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In order to estimate the actual risk for each route, statistical incident rates per hour of work data was used
(US Department of Labor, 1992). The base rate for the 115 kV was approximated as follows.
The total cases of injury reported for electrical work was estimated using data from the Bureau of
Census to an average of 13.4 cases for 100 workers per year. This gave us a rate of0.000067 incident /
hour / worker. Using Figure 2, the utility expert was asked to estimate the time required to build the line
for each of the EMF alternatives proposed. The same process was used for the two other routes and Table
6 lists the estimated time length for each of the twelve alternatives.
In the event the initial decision is to wait five years, we assume for the purpose of this analysis
that even if the technology might advance in five years, the risks associated with power line constructions
will remain, and new technology might reduce known risks but also bring new risks. We thus assume that
the values estimated in Table 6 remain the same in five years.
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Table 6.
Total number of serious injuries during the total construction time
Route 1 Time to complete Total person hours Risk/Hour* Total number of
entire route of work serious injuries**
(months)
Regular 115 kV 3 10000 0.000067 0.670
Split phase 4 13333 0.000071 0.947
Part split 3.5 11667 0.000068 0.793
Change sides 3.8 12667 0.000069 0.874
Route 2
Regular 115 kV 3.6 12000 0.000067 0.804
Split phase 4.5 15000 0.000071 1.065
Part split 4.1 13667 0.000068 0.929
Change sides 4.3 14333 0.000069 0.989
Route 3
Regular 115 kV 3.1 10333 0.000067 0.692
Split phase 4 13333 0.000071 0.947
Part split 3.5 11667 0.000068 0.793
Change sides 3.8 12667 0.000069 0.874
* Base rate fo r ■workers estimated from data o f Bureau o f the Census,
'Occupational and Injury and Illness Incident Rates, by Industry
1991-1992'
* * injury that would prevent the worker from continuing his/her work
fo r a period o f a t least 4 days
6.2 Environment:
To calculate the potential effect of 115 kV power lines would have on the environment, the miles
of line along the developed areas, the miles of line along sparsely populated areas, the miles along
undeveloped areas, and the miles along biologically sensitive areas were estimated using Figure 2 on page
5. The equivalent miles were calculated using the equation defined in Table 7.
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Table 7.
Equivalent miles of environmental disruption due to construction and transmission lines
Miles of line
along
developed
areas
Miles of line
along
sparsely
developed
Miles of line
along
undeveloped
areas
Miles of line
along
biological
sensitive
Total
miles
Total
equivale
miles
areas areas
Route 1 1 11,2 2,5 0,5 15,2 27,8
Route 2 2 12,7 2 , 5 0 17,2 26,05
Route 3 2 11,7 1,5
0 15,2 22,55
Equivalent weighted miles o f enviromental disruption = Miles o f line along developed areas +
(1.5 x Miles along sparsely developed areas) + (2 x Miles along undeveloped areas) +
(10 x Miles along biologically sensitive areas)
For example, the total equivalent miles for Route 1 are calculated by adding the mile of route that
will pass along developed areas to the 11.2 miles along the sparsely developed areas to the 2.5 miles of
undeveloped area to the 0.5 miles passing along the biologically sensitive area. These four different
measures are multiplied by their respective weights to yield a total equivalent weighted mile value of 27.8.
the highest among the alternatives.
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6.3 Social
6.3.1 Resident's fear
The number of residents experiencing fear was estimated using past data from similar cases and
expert elicitation. First, data from open houses that were conducted by a utility company on a similar case
were used to establish the base case value of each route. These survey forms indicated the address of the
concerned party, as well as his/her concerns with the new lines. For this attribute, only those individuals
concerned by EMF exposure were counted.
The following estimates only pertain to a regular 113 kV line design. It is assumed that the
number of people experiencing fear will not vary regardless of the EMF mitigation used. The rationale
behind this assumption is that people will express fear as long as a bigger line will be installed, regardless
of the configuration. The residents have little or no knowledge about the differences in miligaus amounts
between the different configurations. Their fear will thus not be reduced if split phase is used instead of a
regular 115 kV configuration. The number of resident experiencing fear is assumed to be dependent on
the future growth and the results of the EMF research. It is assumed that in a growth scenario, the same
percentage of people will express fear as in the no-growth scenario. If the decision is made to build the
line now, there will be no impact by the research outcome on the number of people experiencing fears.
However, if the decision to build the line is delayed for five years, then the research outcome will have a
significant impact on the number of people experiencing fears. In order to obtain values for the EMF
mitigation alternatives, a psychologist was asked to estimate the potential increase/decrease in residents'
fear depending on the health research. The psychologist simply estimated the percent change in fear for
the three research outcome alternatives (positive, conflicting, negative).
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The assumption is made that in case the research proves to be positive in 5 years, the number of
concerned residents will double. If the research stays conflicting as it is today, the number concerned
residents will remain the same as it is today. It is further assumed that there will not be any concerned
residents if the research turns out to be negative.
Looking at Table 8, let us consider the base case for route 1 : Regular 115 kV with 45 people
experiencing fear.
Table 8.
Total number of residents experiencing fear of EMF
Number of persons
Route 1 experiencing fear
of EMF
Regular 115 kV 45
Split phase 30
Part split 39
Change sides 25
Route 2
Regular 115 kV 42
Split phase 25
Part split 31
Change sides 23
Route 3
Regular 115 kV 59
Split phase 38
Part split 46
Change sides 30
Referring to the decision tree in Figure 7, the number of residents experiencing fear at the chance node
"Health Research Positive" is 90. At the node below, the value is 45. And if health research turns out to
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be negative, then it is assumed that no people are experiencing fear. Since the measure is not time-
dependent, the same calculations are used for the "Wait 5 years" node. We thus assume that after five
years, the number of people experiencing fear will remain constant, regardless of the growth outcome.
6.3.2 Construction disruption days:
This attribute was estimated using two variables: Time to build half mile of line, and the total
number of residents. The total disruption days per alternative were calculated using the following
formula:
Total Disruption Days = Time to build 1/2 mile o f line x Total number o f residents.
It was estimated that the possible negative consequences associated with the construction of the
line (noise, dirt, traffic...) would affect each resident within a 1/4 mile radius of their home. The worst
case scenario would thus be equal to 1/2 mile worth of line construction for each resident. The time
estimates made by the utility expert for the calculation of the annual population risk in Table 5 were
used. The total number of disruption days is then calculated using the above equation. Table 9 shows the
results of the calculations for each alternative.
In order to account for future growth, the total number of disruption days is calculated at the time
of construction. For the case ofRoute 1', we leam about the growth at the end of the first five years.
Therefore, the total number of disruption days experienced by the residents is simply the product of the
total number of residents today and the average construction time for 1/2 mile of line.
For the 'Wait 5 years' alternative, the utility company will learn about the population growth at
the time of the decision. Thus if there is high future growth, the alternative will be penalized since the
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total number of disruption days must be multiplied by the growth factor of 1 .2 yielding a higher
disruption.
Table 9.
Number of estimated disruption davs to residents due to the construction of the line
Time to build Time to build 1/2 Total number of Total disruption
entire route mile of line residents days
Route 1 (months) (days)
Regular 115 kV 3 1.97 397 783.55
Split phase 4 2.63 397 1044.74
Part split 3.5 2.30 397 914.14
Change sides 3.8 2.50 397 992.50
Route 2
Regular 115 kV 3.6 2.09 342 715.81
Split phase 4.5 2.62 342 894.77
Part split 4.1 2.38 342 815.23
Change sides 4.3 2.50 342 855.00
Route 3
Regular 115 kV 3.1 2.04 497 1013.62
Split phase 4 2.63 497 1307.89
Part split 3.5 2.30 497 1144.41
Change sides 3.8 2.50 497 1242.50
6.3.3 Visual degradation
This attribute is defined by a utility function comprised of 5 attributes, each a natural scale. In
order to evaluate potential aesthetic impact of each alternative, differences between each line type must be
made. For instance, a regular three phase 115 kV does not have the same aesthetic impact a 115 kV split
phase line has. The latter one has six lines connected to the pole thus making it a lot more noticeable
than the regular line. Also, if a route requires a new line, that is that there were no previous line, then we
39
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can assume that a new line will certainly have a greater negative impact on aesthetics than simply
upgrading an existing 33 kV line. All different scenarios were considered: the overbuilding of existing
lines, the building of new lines, split lines, and new split lines. Street crossings will also have a negative
impact on aesthetics. The alternative that proposes to change the line to the other side of the street at
populated areas proposes a lot of street crossings. A power line crossing a road is certainly more
noticeable than a regular line along its side.
Using the equation previously defined in section 3 (and in italic at the bottom of Table 10), the
component miles were determined for each of the twelve alternatives and the equivalent mile equation
above was used to calculate the estimates in Table 10.
Table 10.
Equivalent miles of visual degradation
Route I
O v erb u ilt existing
lines
New lines
Split phase
existing lines
New split Line crossing
phase lines stre et
Total equivalent
miles of visual
degradation*
Regular IIS IcV
Split phase
Part split
Change sides
14.2
13
14.2
1
1
1
14.2
1.2
7
I 7
7
9
23.2
30.8
23.8
25.2
Route 2
Regular 115 IcV
Split phase
Part split
Change sides
16.7
15
16.7
0.5
0.5
0.5
16.7
1.7
9
0.5 9
9
11
26.7
35.3
27.55
28.7
Route 3
Regular 115 kV
Split phase
Part split
Change sides
13.7
12.5
13.7
1.5
0.9
1.5
13.2
1.3
14
2 14
0.5 14
16
30.7
38.8
31.5
32.7
* E quivalent M iles o f V isual D egradation ■ M iles o f overbuilt lines + 12 s m ile s o f new line)
* - (l.S x m ites o f split phase existing lines)
* (2.5 x miles o f new solitohase lines) + 1 mile for each street crossina
4 0
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6.4 Economic
6.4.1 Change in property value:
The changes in property value estimated in this report only take into account the potential
adverse effects the EMF exposure from the proposed lines will have on the property’s value. It was
assumed that the average property value of a house located in a sparsely populated rural area was
$100,000. Using literature reviews and expert elicitation, the potential impact of 115 kV lines on property
value were estimated for each health research scenarios. It was assumed that the impact on property value
would be the same regardless of the EMF mitigation alternative chosen.
If health research is positive, then we assume a 10% depreciation on the property value. If the
research is conflicting, as it is today, the property value is assumed to remain unchanged. If the research
is negative, it is assumed that the house will appreciate by 5%. The rationale is that the upgraded lines
will provide better service and efficiency to the houses they serve as well as reduce the fear of EMF
expressed by the residents.
The total number of houses per route was estimated using the data from a survey conducted in a
setting similar to the one created for this analysis. The population residing in school and commercial area
was subtracted from the total population. The future residents were not counted. The average number of
residents per house was assumed to be three. In the event of future growth, the growth factor
(GrowthFactor = 1.2) was only applied to the number of house residents and not the total number of
people as for the other measures. The total amount of property value change was calculated by
multiplying the estimated number of houses for each route times their average price ($1 0 0 K) times the
estimated depreciation. If the utility company decides to wait 5 years, the total dollar amounts obtained
above must be multiplied by the growth factor if there is growth.
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6.4.2 Costs
This measure was estimated by first approximating the cost per mile of construction. This value
was elicited for the base case from utility experts and was estimated to be $355,000 per mile. The base
case were then calculated for each route using their respective mileage multiplied by the price per mile.
Using utility company data and engineering judgments, the cost estimates in Table 11 were obtained.
Note that for the “Change Sides” alternative, the line was moved from one side of the street to the other
only when passing by a school, a residential (existing or future) or a commercial area. Route 1 with a
regular 115 kV is the cheapest alternative. Real (uninflated and undiscounted) costs in five years were
assumed to be the same as costs today.
Table 11.
Total cost
Route 1 Total Cost
(in SI,000)
Regular 115 kV
Split phase
Part split
Change sides
SS 385
58 078
S7 162
59 155
Route 2
Regular 115 kV
Split phase
Part split
Change sides
S6 094
S9 141
S8 105
S6 344
S10 360
Route 3
Regular 115 kV
Split phase
Part split
Change sides
S5 585
58 326
S7 428
59 495
42
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6.5 Quality of service
6.5.1 Disruption of service:
It was assumed that the entire population of the area depicted in Figure 1 (estimated at 2,000)
would be affected by potential service disruptions. The expected length of electrical outage for each
resident per year was assumed to be 4 hours. It was also assumed that the installation of 115 kV lines
would reduce the electrical outages by 50%, independent of route and EMF mitigation measure. For the
purpose of this analysis, the person outage hours depend on whether there is growth and on whether or not
a new line is built now or in 5 years.
If the 'Wait 5 years' alternative is chosen, then the residents will experience more outages because
of the lower reliability and efficiency of the system compared to the proposed 115 kV configuration. They
thus will be penalized for the first five years as opposed to route I, 2, and 3 which will benefit from the
50% reduction in outages for 10 years.
6.5.2 Support of future development
Using the data in Table 7, only the miles of line along undeveloped areas were considered since
they offer the greatest potential for future development. The first two routes both have 2.5 miles of
undeveloped area along the lines and route3 only passes through 1 mile of undev eloped area as Table 7
indicates. The calculation is made at the first year of construction. If the utility company decides to wait 5
years, it is assumed that the amount of undeveloped area for each route will be the same as it is today.
43
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6 .6 Probability parameters
The estimates of the probabilities of research outcomes, growth, and the conditional probabilities
of health effects given the different research outcomes are as follows:
P (Health Research Positive) = 0.2
P (Health Research Conflicting) = 0.7
P (Health Research Negative) = 0.1
P (Health Effects / Health Research Positive) = 0.4
P (No Health Effects / Health Research Positive) = 0 .6
P (Health Effects / Health Research Conflicting) = 0.1
P (No Health Effects / Health Research Conflicting) = 0.9
P (Health Effects / Health Research Negative) = 0.01
P (No Health Effects / Health Research Negative) = 0.99
These estimates were obtained informally through discussions with several EMF experts. These
experts felt that in five years, the issue would most likely still be inconclusive and conflicting. The
highest probability was thus given to P(Health Research Conflicting). Assuming then that the research
will be no longer conflicting in five years, some of the experts felt that it would be more likely that the
research outcomes turn out positive rather than negative. Using this reasoning, a probability ratio of 2:1
was assigned to these two events. Using the arbitrary base of P (Health Research Conflicting) = 0.7, the
three probabilities were assigned as shown above.
44
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In order to specify the conditional probabilities, the P (Health Effects | Health Research
Conflicting) was first estimated by the experts since it should be close to the unconditional probability that
there are health effects with the current state of knowledge. The experts were asked to regard leukemia as
the specific health effect, and they estimated the conditional probability to be fairly low and it was
assigned to be 0.10. If in five years, the epidemiological and biological research is positive, this
conditional probability should increase. However, following an informal discussion regarding the specific
health outcome of leukemia, it was concluded that there would be less than a 50 - 50 chance of a true link
between EMF and leukemia. Thus a probability of 0.4 was assigned to the conditional probability
P(Health Effects | Health Research Positive). The conditional probability P (Health Effects | Health
Research Conflicting) was estimated to be less than half of the conditional probability of P (Health Effects
| Health Research Positive) and was assigned a probability of 0.1. Finally, a low conditional probability of
0.01 was attributed to P(Health Effects | Health Research Negative) to indicate that even in this case, there
still exists a chance for a true link between leukemia and EMF.
7. Value Model
A value model is needed to evaluate the consequences at the end of the decision tree in terms of a
single number. This involves two steps: definition of single measure value functions that indicate how the
relative value changes as a function of the levels of a measure; and development of weights for the
measures that indicate the relative importance of units in one measure vs. units in another measure.
For this analysis, all single attribute value functions were assumed to be linear. To obtain weights, two
decision analysts were asked to tradeoff units in each measure against 1996 dollars. In other words, they
were asked to state the price they were willing to pay in order to eliminate one unit of each measure. For
example, as it can be seen in Table 12, the decision analysts stated a value of 2 million dollars to eliminate
one cancer. Values were obtained for every measure except cost and depreciation which are already in
45
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real dollars. Both analysts provided very similar unit value tradeoffs and, where differences existed, they
were resolved in a discussion.
Illustrative unit value tradeoffs for other stakeholders are also shown in Table 12 as well. While
these value tradeoffs were not elicited from representatives of the groups, they will be used in the
subsequent analysis to illustrate the sensitivity or robustness of the results with respect to changing value
perspectives. The base case analysis was done with the judgments of the decision analysts.
Weights and single attribute value functions were combined using the following simple additive
value function:
UPQ = PriceCancer x NoCancers + Pricelnjury x Noinjury + PriceEnv x MilesEnv + PriceFear
x NoResidentsFear + PriceDisruption x NoDisrDavs + PriceVisual xMilesVisual +
Depreciation + Costs + PriceService x NoDisruptionHours + PriceFutDev x MilesFutDev.
The aggregate U(X) represents the total equivalent cost of a consequence to be attached to the
endpoints (triangles) of the decision tree shown in Figure 5.
46
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Table 12.
Price-out table for all measures bv all stakeholders and decision analysts
Objective Value local residents EnviromoitairsTs Utility cnmnanv Decision analysts
(M o a n )* S S S S
Minimize health impacts from EMF
(Number of cantos)
Minimize health and safety impacts
(Numtacfsa-iouj injuria)
1 Cancer
1 Injury
10 Million
100000
5 Million
100 000
1 Million
200 000
2 Million
100000
Minimize cnviromontal impact 1 mQe of undeveloped land 10000 100000 10000 100000
(Equivalent miles of line)
Minimize fear
1 resident not ctperiatdng
fear for 5 jean
1000 100 100 1000
(Number of rcsidmts expressing fear)
Minimize disruption to residents
1 resident exposed for one
day
50 30 10 20
(Number of disruption dajs)
Minimize visual degradation 1 mile of overbuilt line 10000 1000 10 000 sooo
(Equivalatt miles of line)
Minimize disruption of customer
service
(Number of houn of saviee disruption)
Minimize support af future
development
(Equivalait miles af line)
1 resident hour of last
pamr
(Vice per mile of line that
can support future
development
30
-10 000
10
10000
10
-100000
to
-200000
* Refer to Tables 5 - 1 1
8 . Analysis
With the information described in terms of the ten attributes, the consequences of any endpoint of
the decision tree in Figure 7 can be characterized. With the utility function previously defined, these ten
numbers can be converted into an equivalent cost estimate. All of the different decision strategies can
thus be evaluated by substituting expected equivalent costs at each of the chance nodes. The smallest
equivalent expected cost is then substituted at each of the corresponding decision nodes. Using this
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substitution procedure starting at the end nodes, the equivalent expected costs are computed back to the
root node "Best Decision' (von Winterfeldt & Trauger, 1996).
Table 13 shows the expected consequences for all alternatives and attribute consequences. The
health impacts attribute shows that the health consequences are low and vary only slightly among the
different mitigation alternatives. The environmental consequences indicate that Route 3 is the best for the
environment since it doesn't pass by the pond and goes along fewer undeveloped areas. However, since it
passes along more developed areas, the disruption to the residents and the visual degradation
consequences are higher than for the other routes. The disruption of customer service is the same for all
the routes but higher for the wait S years. If there is a growth in the population and the line is not built,
the disruption of service will be higher. If there is no growth in the population, the disruption of service
will be the same as it is for the route 1. 2, and 3 alternatives. Table 13 also indicates that the impacts on
property value depreciation are low in comparison with the costs to build the line which, in turn, vary
widely among the EMF alternatives.
By multiplying the consequences in Table 13 by their respective unit value tradeoffs ( Table 12),
we obtain Table 14 which lists the expected equivalent costs for all alternatives. This allows the decision
maker to quickly identify which objectives have the highest expected cost and thus have the highest
impact on the decision. Total costs clearly is the largest item, followed by the environmental impacts and
customer service. Equivalent costs for cancers, in contrast, are only in the tens of thousands of dollars (all
routes, “Base case”). Fear and health and safety impacts have both fairly low equivalent costs when
compared with total costs.
48
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Table 13.
Alternatives bv objectives matrix (consequences!
CALCU1.AT ED
TOR to YEARS
Route 1
Base case
Split phase
Part split
Change sides
Route 2
Base case
Split phase
Part split
Change sides
Route 3
M lnlm lie M inimize Minimize
health Impacts health and cntirom enlal
IVom EMK safe!}' Impacts Impact
M inimize Tear
n° Cancers for
10 years
7.63E -03
4 78E -03
5 39F. -03
4.76E -03
6 ME -03
3 88E -03
4.57E -03
■ I ME -03
n° Injuries Equivalent miles n° People
0.67
0.95
0.79
0 87
0 8 0
I 07
0.93
0 9 9
2780
27.80
27.80
2780
26.05
26.05
26.05
26.05
45 00
3000
39.00
25.00
4200
2500
31 00
23 00
Base case 1 M E -03 0 69 22 55 59 00
Split phase 6.98E -03 0 95 22 55 3800
Part split 7.59E -03 0.80 22,55 46 00
Change sides 6.53E -03 0 8 7 22 55 30 00
Wait 5 Years 4.00E -03 0.67 27.80 5692
M inimize
llsrupUon to
residents
M inimize visual
degradation
M inimize
disruption or
custom er service
M aximize support
of IWure
development
M inimize Costs
Minimize
Depreciation
Days Equivalent miles
Outage hours for
10 years
Miles supporting
development
Dollars Dollars
782.10 23.20 42 000 00 2 50 S5 385 000 00 $80 789.50
1 044.10 30 80 42 000.00 2.50 $8 078 000.00 $80 789.50
913 10 23.80 42 000.00 2.50 $5 623 000.00 $80 789.50
992.50 25.20 42 000.00 2.50 $5 635 000.00 $80 789.50
71480 26 70 42 000.00 2.50 $6 094 000.00 $92 169.00
896 05 35 30 42 000.00 2.50 $9 M l 000 00 $92 169.00
8)3.95 27.55 42 000.00 2.50 $6 331 000.00 $92 169.00
855.00 28.70 42 000.00 2.50 $6 344 000.00 $92 169.00
1 013 90 30 70 42 000.00 1.00 $5 585 000.00 $82 00500
1 307.10 38.70 42 000.00 1.00 $8 326 000 00 $82 00500
1 143.10 31 60 42 000.00 1.00 $5 802 000 00 $82 0051)0
1 242.50 32.70 42 000.00 1.00 $5 875 000 00 $82 00500
81050 23 20 62 000.00 2.50 $5 385 000.00 $80 790.1)0
49
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Table 14.
Total equivalent dollar amounts of all the objectives for all the alternatives
CALCULATED
FOR 10 YEARS
ftflidndtc health Mbdndte health
Impacts than and safety
EMF Intact*
Midmkc
emlromtntul
intact
M idndufcar
M iinfee disruption
to residents
IVflnbifeesfcud
-S _ — . s . . t
oegnMMnon
Mbdmfcc
disruption of
customer service
Mudndu support
of future
drvetopnirut
Midndce Costs
IVMndte
Depreciation
R d U c I
Base case
Split phase
h it split
Change sides
SI 5 25267
S9 56251
S10 786.14
S9 52222
S67 000.00
$94 700.00
S79 300.00
$87400.00
$2780000.00
$2780000.00
$2780000.00
$2780000.00
$45000.00
$30000.00
$39000.00
$25000.00
$15 641.80
$2088220
$1826200
$19850.00
$116000.00
$154000.00
$119000.00
$126000.00
$420000.00
$420000.00
$420000.00
$420000.00
-$500 000.00
-$500 000.00
-$500000.00
-$500 000.00
$5385000.00
S8 078 000.00
$5623000.00
$5635000.00
$80 789.50
$80789.50
$80789.50
$80 789.50
RoUe2
Base case
Split phase
h it split
Change sides
$12285.01
S7 751.88
$9144.35
$8 281.10
$80400.00
$106500.00
$92900.00
$98900.00
$2605000.00
$2605000.00
$2605000.00
$2605000.00
$42000.00
$25000.00
$31000.00
$23000.00
$14295.60
$17920.80
$16279.20
$17100.00
$133 500.00
$176500.00
$137 750.00
$143 500.00
$420000.00
$420000.00
$420000.00
$420000.00
-$500000.00
-$500 000.00
-$500000.00
-$500000.00
$6094000.00
$9141000.00
$6331 000.00
$6344000.00
$92169.00
$92169.00
$92169.00
$92169.00
Roule3
Base case
Split phase
h it split
Change sidos
S22 883.33
S13 956.94
S15 173.60
$13 061.78
$69200.00
$94700.00
$79300.00
$87400.00
$2255000.00
$2255000.00
$2255000.00
$2255000.00
$59000.00
$38000.00
$46000.00
$30000.00
$20277.60
$2614220
$2286200
$24850.00
$153 500.00
$193 500.00
$158000.00
$163 500.00
$420000.00
$420000.00
$120000.00
$420000.00
•$200000.00
-$200000.00
•$200000.00
-$200000.00
$5 585000.00
$8326000.00
$5802000.00
$5 875000.00
$82005.00
$82005.00
$82005.00
$82005.00
Wait 5 Yeas S7 990.00 $67000.00 $2780000.00 $56920.00 $17210.00 $116000.00 $620000.00 -$500 000.00 $5 385000.00 $80 790.00
50
This matrix also allows the decision analyst to estimate what variable (value tradeoffs,
probabilities, or consequences) will have a sufficient impact on the total expected cost and lead to a switch
in the decision. Table 14 indicates that cancers, fear, and safety impacts equivalent costs are not
important enough to have a major effect on the final decision. Using the same reasoning, the analyst can
also conclude that the environmental, customer service, and future development measures might be high
enough to switch the final decision when sensitivity analyses is run.
Table 15.
Ranking of the alternatives
Calculated for 10 years Total
Route 1
Base case S8,424,680
Split phase SI 1,167,930
Part split $8,670,140
Change sides S8,683,560
Route 2
Base case S8,993,650
Split phase
S12,091,840
Part split $9,235,240
Change sides $9,251,950
Route 3
Base case $8,466,870
Split phase $11,249,300
Part split $8,680,340
Change sides $8,750,820
Wait 5 Years $8,630,910
Table 15 shows the total expected equivalent cost for all alternatives. The alternative with the
least equivalent expected cost is to build 'Route 1' with a regular 115 kV configuration ($8.42 Million),
followed closely by ‘Route 3 ’ ($8.47 Million). The ‘Wait 5 years’ alternative only ranks third at $206K
from the preferred alternative. For each of the three routes, the base case (no special EMF mitigation)
51
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always has the lowest equivalent expected cost and to split phase the entire route is always the least
preferred alternative as Figure 8 clearly indicates. This is partly due to the difference in construction costs
and the fact that even if there is a significant reduction in EMF with the line split phased, the impact
of the health attribute is minimal on the total estimated cost The graph in Figure 9 clearly indicates that
Route 2 is the least preferred route, regardless of the EMF mitigation measure.
SI4000000
$12000000
S10000000
S8 000 000
S6 000 000
S4 000 000
$2000 000
S O
Route 1 Route 2 Route 3
Figure 8 . Expected equivalent costs vs. routes for each EMF alternative
S14000000
$12 000 000
$10000000
$8000000
S6 000 000
S4000 0 0 0
S2 000 000
SO
Figure 9. Expected equivalent costs vs. EMF alternative for each route
Base Split Part Change
case phase split sides
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Sensitivity of model parameters:
As the results show, the base case model leads to two close contenders (route 1 and route 2, base
case). It is thus worth considering different ‘what if scenarios that might change our results. All
variables were thus parametrized to allow the effects of changes in any of the specific estimates to be
easily investigated. Sensitivity analysis allows interested parties to evaluate the different strategies using
their own input parameters ( Keeney & von Winterfeldt, 1994). It indicates which changes of the input
parameters might change the implications of the base cases analysis.
The analysis that follows is divided in three parts. First, parameters that could change the
decision from building now to wait five years were identified. Second, we assume that the utility company
has to build now and run sensitivity analysis on route selection, not considering the ‘Wait 5 years’
alternative. Finally, we assume that route 1 is a winner and run sensitivity analysis on the mitigation
measures only.
Sensitivity of ‘Waiting 5 years’ versus building now
Using Table 13 on page 47, we first identify which attributes have a higher expected value for
‘Wait 5 years’ than for ‘Route 1’. Once these attributes are identified, we run sensitivity analysis on each
parameter to see how much of a change is required for the 'Wait 5 years' alternative to have a sufficiently
higher equivalent value than Route 1 to make it the most desired alternative, that is the one with the
lowest equivalent total cost. The cancer attribute can produce this switch.
Some home owners, especially those with small children, may feel the elimination of the
potential risk of health effects (cancer) associated with electromagnetic fields is of considerable value to
them, that is more than the $2 Million estimated by the decision analysts. A sensitivity analysis of the
effect of the equivalent cost of a cancer was thus run and is shown in Figure 10. It shows that for values
53
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of $58 Million per cancer or more, the alternative 'Wait 5 years' is preferred. When looking at the total
equivalent costs in Table 14, we see that the attribute ‘cancer’ carries a small weight in the total expected
cost for each alternative. This explains why such a high value for the estimate of a cancer is required to
switch the decision. However, it also tells us that the decision might be sensitive to the estimates used to
approximate the number of cancers for each route. We thus go back to our incremental risk (IR) formula
on page 28 and run sensitivity analysis on its parameters.
Sensitivity Analysis on
the equivalent cost of a cancer
$9 600K -
$9 500K -
to $9 400K-
o
o $9 300K -
ji $9 200K -
8 $9100K -
* $9 000K-
■ £ $8 900K -
7 3 $8 800K -
• | $8 700K -
[g* $8 600K -
$8 500K -
$8 400K-
@ Lakeland-Jackson
♦ Lakeland- Goat Creek- Donavan
▲ US Highway- Donavan
^ Wait 5 Years
Threshold Values:
KNoCancers = 58M
■ EV = $ 8 853K
Equivalent cost of a cancer
Figure 10. Sensitivity analysis on the equivalent cost of a cancer
A sensitivity analysis of varying the base rate (BR) is shown in Figure 11. It shows
that for BR values of0.005 or higher, the alternative to wait 5 years is preferred to any of the other
alternatives. However, it is the only parameter that will switch the decision. Event if the probability of
health research is 1, and no other variables are changed, the decision does not switch and building route 1
is recommended. A two-way sensitivity analysis was done on the equivalent cost of a cancer and on BR.
The results of the analysis are shown in Figure 12. As it can be seen, the decision becomes very sensitive
when both variables are considered. This figure indicates that for example, a value of $2.6 million for a
54
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cancer combined with a base rate of 0.0023 would be sufficient to switch the decision to waiting S years.
We can therefore conclude that the base case tree is sensitive to the attribute 'cancer*.
Sensitivity Analysis on
® Lakeland-Jackson
♦ Lakeland-Goat Creek-Donavan
A US Highway- Donavan
1 Wait 5 Years
Threshold Values:
BaseRate = 0.00290
EV = $8 852K
0.00050 0.00230 0.00410
BaseRate
Figure 11. Sensitivity analysis on the base rate (BR1 used to calculate the incremental cancer risk
BaseRate
C O
O
o
T 3
< U
u
< u
Q .
X
V
■a
>
'3
O’
tu
S9 600K
S9 500K-
S9 400K-
S9 300K-
S9 200K-
S9 100K-
S9 000K-
S8 900K-
S8 800K-
S8 700K-;
S8 600K
S8 500K
S8 400K
< o
0£
< u
t n
c a
C Q
Sensitivity Analysis on
Equivalent cost of a cancer and BaseRate
0.005'
0.0041
5 0.00321
0.0023
0.00141
0.0005'
iH Lakeland- Jackson
I I Lakeland- Goat Creek- Donavan
H US Highway- Donavan
lH Wait 5 Years
1.0M 1.8M 2.6M 3.4M 4.2M 5.0M
Equivalent cost of a cancer in $ millions
Figure 12. Two-way sensitivity analysis on the base rate (BR) and on the equivalent cost of a cancer
55
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Sensitivity analysis on route selection
For this analysis, we assume that the utility company has to build now and we thus do not
consider the alternative to wait S years when we run the analysis. Looking at Table 15 on page 49. we
see that under this scenario. Route 3 becomes the challenger, only $22K behind Route 1. Using the same
reasoning as for the previous sensitivity analysis, we use Table 14 on page 38 to identify the attributes that
score higher for Route 1 than for Route 3. Only one attribute, ‘environmental impact’, has a higher
estimated value for Route 1 than for Route 3. We thus run sensitivity analysis on that attribute (Figure
13). The resulting graph shows that if a stakeholder values one mile of environmental disruption at
S108K, the optimal decision switches from building on route 1 to building on route 3. The estimated
value given by the environmentalists and the decision analysts was S1 0 0K, only S8 K . less than the amount
required to switch the decision. We can therefore conclude that the decision is very sensitive to the value
of the environmental attribute.
Sensitivity Analysis on
the equivalent cost of one mile of enviromental disruption
c n
O
y
-o
v
y
< D
Q .
X
u
4 ^
c
JU
*3
>
'5
cr
U J
S10 400K-
S10 200K-
SIO 000K-
S9 800K-
S9 600K
S9 400K-
S9 200K-
S9 000K-
S8 800K
58 600K-
$8 400K
® Lakeland-Jackson
♦ Lakeland- Goat Creek- Donavan
▲ US Highway-Donavan
Threshold Values:
KMilesEnv = 108K
9 A
EV = $ 8 648K
150K IO O K 110K 120K 130K W O K
Equivalent cost of one mile of enviromental disruption
Figure 13. Sensitivity analysis on the equivalent cost of a mile of environmental disruption
56
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Sensitivity analysis on EMF mitigation measures
For this last analysis, we assume that the utility company has chosen to build now and has
selected Route 1 as the preferred route. We are now interested in finding parameters that will switch the
best EMF mitigation alternative from the base case scenario to the part split alternative which is only
S245K. more expensive (see Table 15). Again using Table 14, we identify which attributes have a greater
expected cost for the base case than for the split phase alternative. The attributes of cancer and fear both
have that profile and sensitivity analysis was thus run on parameters of both attributes. Figure 14 shows
that the EMF mitigation alternatives are not very sensitive to changes in the equivalent cost of a cancer.
The decision switches at $92Million.
Sensitivity Analysis on
the equivalent cost of a cancer for Route 1
CO
O
o
■o
a >
" 3
< u
a.
x
u
c
JO
e d
'5
a*
H i
Sll 900K-
Sll 600K-
Sll 300K-
S1I 000K-
S10 700K-
S10 400K-
S10 100K-
S9 800BC-
S9 500K-
S9 200K-
S8 900K-
70M 80M 90M 100M 110M 120M
Switch Side of the Road
Threshold Values:
_ KNoCancers = 92M
® ^ E V = $9 114K
Equivalent cost of a cancer
Figure 14. Sensitivity analysis on the equivalent cost of a cancer for Route 1
A similar sensitivity analysis on the base rate shows that the decision switches to ‘Alternative sides’ when
BR is greater or equal to 0.0046 (Figure 15).
57
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When we compare the results obtained for this analysis with the ones obtained in our first
analysis on the same parameters, we conclude that the EMF mitigation alternatives are less sensitive to
changes in the equivalent cost of a cancer than the routes and the ‘Wait 5 years’ alternatives are between
them. The BR required to switch the decision is also slightly higher for the EMF alternative analysis than
for the other analysis.
Sensitivity Analysis on
BaseRate
CO
O
o
■a
" 5
a >
a.
x
< u
- ♦ — *
c
JU
C O
>
'5
a r
U J
$12 500K-
$12 IOOK-
$11 700K-
$11 300K-
$10 900K-
$10 500K-
$10 100K-
$9 700K-
$9 300K-
$8 900K7
$8 500K-
0.0082 0.0010 0.0046
® Base Case Line
♦ Global Split Phase
▲ Local Split Phase
® Switch Side of the Road
Threshold Values:
BaseRate = 0.0046
EV = $9 114K
BaseRate
Figure 15. Sensitivity analysis on the base rate (BR1 used to calculate the incremental cancer risk
A sensitivity analysis of the equivalent cost of "fear" is shown in Figure 16. This shows that the
decision switches to the alternative side option at an equivalent cost of $ 14K. Stakeholders such as the
residents for example are likely to give such a high equivalent cost for this attribute.
58
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Sensitivity Analysis on
the estimated price paid not to experience fear
C O
O
O
•O
o
< u
a
x
-4 -»
c
>
■3
a*
W
$12 O O O K
$11 600KH
$11 200K-
-g $10 800K-
$10 400K— 1
$10 O O O K —
> $9 600K—
$9 200K— 1
$8 800K
• Base Case Line
♦ Global Split Phase
A Local Split Phase
H Switch Side of the Road
Threshold Values:
_ KNoResFear = 14K
EV = $9 007K
10K 12K 14K 16K 18K 20K
Estimated price paid not to experience fear
Figure 16. Sensitivity analysis on the price to be paid not to experience fear for 5 years
9. Conclusion and insights
The key conclusion from the above analysis can be summarized as follows. The overall ranking
shown in Table 15 results from judgments made by different experts and decision analysts and value
judgments provided by representatives from each of the stakeholder groups. It is however important to
stress that this decision analysis was based on many assumptions and limited data. In particular, the lack
of well understood dose-response mechanism and the resulting large uncertainties about health research
and health effects required a parametric approach to studying this routing problem. The primary purpose
of this report was to illustrate the use of decision analysis methods in transmission line siting problems
and to generate some qualitative insights.
59
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Among the insights learned from this illustration are the following:
1. It is not worth waiting five years to learn what the research will have shown by that time.
EMF exposure equivalent costs are too low and the penalty for the five year waiting period are not steep
enough. Even if the research is positive, there are associated health effects, and high future growth
occurs, the best decision is still to build route 1 now. Whether or not there is a high increase in
population will also not affect the decision.
2. The split phase alternative is the most expensive for all three routes. The sensitivity analyses
performed did not show any way to make this EMF mitigation alternative a winner.
3. It is worth for the utility company to wait 5 years if the attribute of health effects is given
greater weight either by increasing the equivalent cost of a cancer or by increasing the base rate value used
to estimate the total number of cancers for each alternative. As the sensitivity analysis has shown, the
switch can occur even more rapidly if we decide to change both the base rate value and the equivalent cost
of a cancer.
4. The base case configuration is preferred for all routes, except when the value of cancer or base
rate or both are very high. In this case, the "change side" alternative is preferred.
5. The environmental attribute makes the “Route 1 ” very sensitive to change. The biologically
sensitive area located on the Jackson portion of the route is the main cause for a possible change in the
ranking of the alternatives.
60
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6 . The fear attribute makes the EMF mitigation alternatives sensitive to change. As the
sensitivity analysis showed, the decision switches very rapidly from "Base case" to "Change side"
depending on the equivalent cost the residents are willing to pay to eliminate the fear of EMF.
Regarding the EMF problem in general, we can conclude that EMF has very little impact on the
overall decision. Fear of the residents actually carries a lot more wait than the potential health effects
associated with EMF. If health effects do become sufficiently important to mandate an EMF reduction
alternative, the analysis has shown that the utility company should then consider switching the line to the
opposite side of the street when it crosses populated areas.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
61
References
Adams, J. Letter report to the University of Southern California project "Integrated EMF Risk
Management", funded by the Electric Power Research Institute. Submitted October. 1995.
Adams, J., Zhang, J., Morgan, G. M. G., and Nair, L. (1996). A method for evaluating transmission
lines mitigation strategies that incorporate biological uncertainty. Risk Analysis, 15: 313-318.
American Cancer Society. (1992). Cancer Facts and Figures. Atlanta: American Cancer Society.
Anderson, L.E. (1993). Biological effects of extremely low-frequency electromagnetic fields: in vivo
studies. American Industrial Hygiene Association Journal, 54: 186-196.
Florig, H. (1992, July). Containing the Cost of the EMF Problem. Science. Vol. 257.
Gregory, R., & von Winterfeldt D. (1996). The effects of electromagnetic fields from transmission lines
on public fears and property values. Journal o f Environmental Management. 48: 1-14.
Keeney, R.L., & Raiffa, H. (1976). Decision With Multiple Objectives. New York: John Wiley and Sons
(reprinted New York : Cambridge University Press, 1993).
Keeney, R.L. (1992). Value-Focused Thinking: A Path to Creative Thinking. London. England:
Harvard University Press.
Keeney, R.L., & von Winterfeldt, D. (1994). Managing Nuclear Waste from Power Plants. Risk
Analysis, Vol. 14, No. 1.
Nair, I., Morgan, M., and Florig, H. (1989). Biological Effects o f Power Frequency Electric and
Magnetic. Washington D.C.: Office of Technology Assessment U.S. Congress.
National Institute of Environmental Health Sciences. (1995). Questions and answers about EMF. U.S.
Government Printing Office: Washington. D.C.
Olsen B. (1994). Development and Validation of Software for Predicting ELF Magnetic Fields Near
Power Lines. IEEE Transactions on Power Delivery, Vol. 10, pp. 1524-1534, July 1995.
Sagan, L. (1992). Epidemiological and Laboratory Studies of Power Frequency. JAMA, V ol. 268, No. 5.
62
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Savitz, D.A. (1992). Overview of epidemiologic research on electric and magnetic fields and cancer.
American Industrial Hygiene Journal. 54: 104-114.
Southern California Edison Company (1994). EMF Design Guidelines for New Electrical
Facilities transm ission Substation Distribution. Irwindale, CA.
U.S. Department of Labor (1992). Occupational Injuries and Illnesses in the United States by Industry,
1990. Washington, DC: U.S. Department of Labor.
von Winterfeldt, D., & Trauger (1996). Managing Electromagnetic Fields From Residential Electrode
Grounding Systems : A Predecision Analysis. Bioelectromagnetics, 17: 71-84.
von Winterfeldt, D., & Edwards (1986). Decision Analysis and Behavioral Research . Cambridge.
England: Cambridge University Press.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
63

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Asset Metadata

Creator Tardivat, Charles-Henri C. (author)

Core Title A decision analysis on powerline siting for a utility company

School Graduate School

Degree Master of Science

Degree Program Systems Management

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Energy,engineering, civil,health sciences, public health,OAI-PMH Harvest,sociology, public and social welfare,Urban and Regional Planning

Language English

Contributor Digitized by ProQuest (provenance)

Advisor Winterfeldt, Detlof (committee chair), John, Richard S. (committee member), Keeney, Ralph (committee member)

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c16-13653

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Rights Tardivat, Charles-Henri C.

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Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the au...

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