FINAL REPORT 

© 2009. Scientific Certification Systems, Inc.

Life Cycle Impact Assessment (LCIA) 

of Renewable Electrical Generation Technologies 

Compared to the WECC Baseline

 Conducted in accordance with ISO 14044 LCIA Framework 

and the Draft SCS-002/ANSI Life Cycle Metrics Standard, 

“Type III Life-Cycle Impact Profile Declarations

for Materials, Products, Services and Systems”

Prepared for the Western Area Power Administration

and

Tri-State Generation and Transmission Association, Inc.

March 2009

2200 Powell Street, Suite 725

Emeryville, CA 94608

510-452-8000

PROJECT AUTHORS/CONTRIBUTORS

Stanley Rhodes, Ph.D. — Project Manager, Senior LCSEA Practitioner

Fjalar Kommonen — Senior LCSEA Practitioner and Modeler

Chet Chaffee, Ph.D. — Senior LCA Practitioner

Linda Brown — Senior Editor and Project Support

Neil Thomas — GIS Specialist

S. Clayton Palmer – Environmental Economist

Bill Karsell -- Biologist
Renewable Electrical Generation Technologies 

Compared to WECC Baseline —

Final LCIA Report 

T-1

Main Report

Life Cycle Impact Assessment of

Renewable Elcctrical Generation 

Technologies Compared to the 

WECC Baseline

TABLE OF CONTENTS 

Executive Summary .................................................................................................i

Terms and Definitions ................................................................................................. vi

Section 1. Study Overview 1.1. Study Background...........................................................1-1

. 1.2. Study Goals.....................................................................1-1

. 1.3. Scope of Work ................................................................1-1

. 1.4. Limitations......................................................................1-2

Section 2. Overview of LCSEA

Framework 2.1. Historical Perspective .....................................................2-1

2.2. LCSEA Methodology and Metrics ................................2-2

2.2.1. Classification Protocols........................................2-3

2.2.2. Characterization Protocols....................................2-3

2.3. Steps for Conducting Assessments..................................2-4 

2.3.1. Determination of Scope/Boundary Conditions.....2-4

2.3.2. Life Cycle Inventory Analysis..............................2-5

2.3.3. Life Cycle Impact Assessment .............................2-5

2.4. Impact Groups, Impact Categories & Category

Indicators .........................................................................2-6

Section 3. Study 

Conventions, Assumptions 

and Considerations 3.1. LCI Conventions and Assumptions................................3-1

3.1.1. Raw Materials.......................................................3-1

3.1.2. By-Products ..........................................................3-1

3.1.3. Fuel Inputs and Outputs........................................3-1

3.1.4. Emissions to Air ...................................................3-2

3.1.5. Emissions to Water...............................................3-2

3.1.6. Solid Wastes .........................................................3-2

3.1.7. Line Losses...........................................................3-2

3.2. Site-Dependent Factors Used to Calculate Regional 

Emissions.........................................................................3-2

3.2.1. Regional Acidification Loading Assumptions......3-2

3.2.2. Ground Level Ozone.............................................3-6

3.2.3. Particulate Loading ..............................................3-11

3.2.4. Chronic Hazardous Chemical Loadings ..............3-15
Renewable Electrical Generation Technologies 

Compared to WECC Baseline —

Final LCIA Report 

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Section 4. 4.1. Project Description and Background ..............................4-1

The WECC (US) 4.1.1. Project Description ...............................................4-1

LCIA Baseline 4.1.2. Project Background ..............................................4-1

4.2. WECC Regional Power Baseline....................................4-1

4.2.1. General Description ..............................................4-1

4.2.2. Sub-NERC Regional Baselines ............................4-2

4.2.3. Scope of WECC Baseline Assessment .................4-3

4.3. WECC Baseline Power Mix ...........................................4-4

4.4. Data Sources ...................................................................4-4

4.4.1. Primary Data Sources...........................................4-4

4.4.2. Additional Data Sources.......................................4-6

4.4.3. Upstream Unit Processes......................................4-6

4.5. Key Project Assumptions and Considerations.................4-6

4.5.1. Characterization of Receiving Environments 

for Emissions Category Indicators .............................4-7

4.5.2. Water Resource Depletion....................................4-7

4.5.3. Key Species Indicator...........................................4-8

4.5.5. Characterization of Wastes...................................4-8

4.5.5. Characterization of Coal Assay to Determine 

 Material Use..........................................................4-8

4.5.6. LCIA Data for Nuclear Power Systems................4-8

4.6. Summary LCI Results.....................................................4-9

4.7. Landscape Disruption Group — Habitats Disrupted .....4-10

4.8. LCSEA Results...............................................................4-11

4.9. Summary of Results and Discussion...............................4-12

4.9.1. WECC Baseline ....................................................4-12

Section 5. 5.1. Project Description and Background ..............................5-1

Stateline 300MW Wind 5.1.1. Project Description ...............................................5-1

Generation System 5.1.2. Project Background ..............................................5-1

5.1.3. Specific Issues Surrounding Functional

 Equivalency and System Boundaries...................5-2

5.2. Stateline Power Generation System Description ............5-3

5.2.1. System Boundaries, Scoping and Specific 

 Unit Processes.......................................................5-3

5.2.2. Functional Unit .....................................................5-4

5.3. Baseline Case ..................................................................5-4

5.4. Integrating Wind into Regional Power Pool System ......5-4

5.5. Data Sources ...................................................................5-5

5.5.1. Materials and Energy Used in Wind Farm

 Construction, Operations and Maintenance........5-5

5.5.2. Direct Physical Disruption Associated with

 the Wind Farm ....................................................5-6

5.5.3. Direct Physical Disruption Associated with

 Back-Up Power (Scenario 2)..............................5-7

5.6. Key Assumptions............................................................5-8

5.6.1. Windforce Analysis..............................................5-8

5.6.2. Back-Up Units in Scenario 2 ................................5-8

5.6.3. Amount of Back-Up Power Required for 

 Scenario 2 ...........................................................5-8

5.6.4. Assumptions Related to Wind Farm Material

 and Energy Inputs...............................................5-10

5.6.5. Habitat Disruption Assumptions...........................5-12
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Compared to WECC Baseline —

Final LCIA Report 

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5.6.6. Natural Gas Back-Up Power Assumptions...........5-13

5.7. Summary LCI Results.....................................................5-13

5.8. LCSEA Results...............................................................5-14

5.9. Discussion of Results.......................................................5-19

5.9.1. Proper Scoping......................................................5-19

5.9.2. Wind System with No Added Back-Up 

 Power (Scenario 1) .............................................5-20

5.9.3. 85% Wind Power / 15% Natural Gas Back-Up

 Power (Scenario 2) ..............................................5-21

5.10. Differences in Scenarios’ Performance .........................5-21 

Section 6. 6.1. Project Description and Background ..............................6-1

Glen Canyon Hydropower 6.1.1. Project Description ...............................................6-1

Generation System 6.1.2. Project Background ..............................................6-1

6.2. Power Generation System Description ...........................6-3

6.2.1. System Boundaries, Scoping and Specific 

 Unit Processes.......................................................6-3

6.2.2. Plant Location.......................................................6-5

6.2.3. Construction..........................................................6-6

6.2.4. Operations and Maintenance ................................6-6

6.2.5. Power Transmission..............................................6-8

6.2.6. Function and Functional Unit ...............................6-9

6.3. Baseline Case ..................................................................6-9

6.4. Data Sources and Data Quality .......................................6-10

6.4.1. Data Sources.........................................................6-10

6.4.2. Data Quality..........................................................6-10

6.5. Key Assumptions and Scoping Considerations..............6-10

6.5.1. Allocation of Impacts ...........................................6-10

6.5.2. LCI Model Assumptions.......................................6-12

6.5.3. Biophysical Impact Focus.....................................6-12

6.5.4. Drought Related Impacts......................................6-13

6.5.5. Water Resource Depletion....................................6-14

6.5.6. Uncertainty Surrounding Causes of Observed

 Adverse Impacts ...................................................6-16

6.5.7. Creation of Habitat ...............................................6-16

6.5.8. Auxiliary Power to Augment Post-ROD

 Power Generation..................................................6-17

6.6. Habitat Disruption and Effects on Species – Gross 

Impacts Allocation Case ..................................................6-17

6.6.1. Habitat Disruption to Areas Occupied by 

 Facilities................................................................6-17

6.6.2. Habitat Disruption Due to Glen Canyon

 Project Operations ................................................6-18

6.6.3. Glen Canyon – Effects on Key Species................6-30

6.7. Habitat Disruption and Effects on Species –

Hydropower Function Case .............................................6-33

6.7.1. Riparian/Wetland Habitat Disruption ...................6-33

6.7.2. Loss of Key Species: Humpback Chub ................6-33

6.8. Summary LCI Results......................................................6-34

6.9. LCSEA Results................................................................6-35

6.10. Discussion of Results.....................................................6-39

6.10.1. Energy Resource Depletion ................................6-40

6.10.2. Water Resource Depletion..................................6-40
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Compared to WECC Baseline —

Final LCIA Report 

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6.10.3. Terrestrial Habitat Disruption.............................6-40

6.10.4. Riverine Habitat Disruption................................6-40

6.10.5. Riparian/Wetland Habitat Disruption. ................6-41

6.10.6. Key Species Loss................................................6-41

6.10.7. Accumulated GHG Radiative Forcing and 

Oceanic Acidification Loadings ...........................6-42

6.10.8. Regional Air Emission Impact Categories .........6-42

6.10.9. Eco-toxic Chemical Loading and Radioactive

 Wastes...................................................................6-42

6.11. Next Steps .....................................................................6-43

6.11.1. Impact Allocation ...............................................6-43

6.11.2. Riparian and Aquatic (Lake) Habitat..................6-43

6.11.3. System Assessment.............................................6-43

Supplemental Report

Life Cycle Impact Assessment 

Methodology Applied To 

Thermal Generation Technologies 

Compared to the WECC 

Baseline: A Conceptual 

Demonstration

Description of Supplemental Report................... S-i

Section 7. 7.1. Project Description and Background ..............................7-1

Project #2: Colstrip Coal 7.1.1. Project Description ...............................................7-1

Power Generation System 7.1.2. Project Background ..............................................7-1

7.2. Colstrip Power Generation System Description ..............7-2

7.2.1. Colstrip Station Power Plant.................................7-2

7.2.2. Coal Assay, Mining and Transport.......................7-3

7.2.3. Transmission.........................................................7-4

7.3. Baseline Case: The WECC Regional Power Pool .........7-4

7.4. Data Sources ...................................................................7-4

7.4.1. Colstrip Station .....................................................7-4

7.4.2. Rosebud Mine.......................................................7-4

7.4.3. Additional Emissions Data for Coal Plant

 Operations from SCS LCSEA Database...............7-4

7.4.4. Ancillary Upstream Unit Processes......................7-5

7.4.5. Dispersion Modeling of Emissions.......................7-5

7.4.6. Physical Disturbance ............................................7-5

7.5. Key Assumptions and Considerations............................7-6

7.5.1. Issues Related to Impact Categories with 

Human Health Endpoints......................................7-6

7.5.2. Physical Disruption Issues....................................7-7

7.5.3. Transmission.........................................................7-7

7.6. LCI Results .....................................................................7-8

7.7. Habitat and Species Disruption.......................................7-9

7.8. LCSEA Results...............................................................7-9

7.9. Summary of Results and Discussion...............................7-11
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Compared to WECC Baseline —

Final LCIA Report 

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7.10. Preliminary Environmental Performance Index of 

 Colstrip ..........................................................................7-13

Section 8. 8.1. Project Description and Background ..............................8-1

Project #4: Natural Gas 8.1.1. Project Description ...............................................8-1

Power Generation System 8.1.2. Project Background ..............................................8-1

8.2. Power Generation System Description ............................8-1

8.2.1. Unit Processes.......................................................8-1

8.2.2. Plant Location.......................................................8-2

8.2.3. Differences between NGSC and NGCC 

Systems.................................................................8-3

8.3. Baseline Case ..................................................................8-3

8.4. Data Sources ...................................................................8-3

8.5. Key Assumptions............................................................8-3

8.5.1. Assumptions Related to Power Plant Modeling ....8-3

8.5.2. Habitat Disruption Assumptions............................8-3

8.6. Summary LCI Results.....................................................8-4

8.7. LCSEA Results...............................................................8-5

8.8. Discussion of Results......................................................8-8

8.9. Environmental Performance Index .................................8-10

Appendices 1. Practitioner Qualifications

2. General Bibliography

3. KCL ECO Model: Brief Description

4. Power Plants in the US WECC Power Pool, by State

5. WECC Biomass Electricity Generation Plants in 

 Year 2000 (EGRID02)

6. SCS-002, Annex A 1C (Excerpt from SCS-002)

7. LCIA Climate Metrics: Introduction and Annexes 

 1A-1C (Excerpt from SCS-002-1)
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems i

EXECUTIVE SUMMARY

For this report, SCS conducted a life-cycle impact assessments (LCIA) of two 

renewable electrical technologies: the Glen Canyon Hydropower Station in Arizona and 

the Stateline Wind Power Generation System on the border of Washington and Oregon. 

SCS then compared these results to impact levels calculated for the WECC NERC 

Region. As prescribed in the ISO 14044 Standard and Draft Standard (SCS-002), the 

study assessed and compared the LCIA results of these renewable electrical generating 

plants to those of the WECC across the full range of environmental and human health 

that have been shown to be environmentally relevant to electricity production within the 

Western region of the United States. 

The report contains the following information:

• a description of the Glen Canyon Hydropower System;

• a description of the Stateline Wind Power Generation System;

• a description of the WECC regional power pool; 

• a description of the data utilized for the assessment; 

• a discussion of key assumptions; 

• a summary of life cycle inventory results; 

• a summary of life cycle impact assessment results; and

• a discussion of results. 

Upon request of WAPA, this report underwent peer review by individuals from 

Argonne National Laboratory.

The LCIA results from this study are reported in the format specified in the SCS002 Committee Draft in order to facilitate use of the findings by policy makers and other 

stakeholders. Two different Life Cycle Impact Declarations are presented for the Glen 

Canyon Project based on different sets of assumptions that reflect different operating 

scenarios for the dam. One scenario assumes that the dam is used for multiple functions, 

from recreation through water storage, flood control and power generation. In this case, 

the environmental impacts are allocated across functions in compliance with allocation 

procedures set forth in ISO 14044. In the second case, all environmental impacts 

resulting from the Glen Canyon project are assigned to a single function, power 

generation. For the Stateline Wind Power Project a Life Cycle Impact Declaration of the 

Wind System with No Added Backup power is presented.

Supplemental Report on Thermal Technologies

Included under this document’s cover is a supplemental report. As part of the 

commission of this study by Western Area Power Administration, SCS gathered data on 

two thermal electrical generating units; the Colstrip Generating Powerplant in Montana 

and two generic types of natural gas-fired electrical generators. The detailed data that 

would be required to perform a Life Cycle Impact Assessment and prepare a Life Cycle 

Impact Declaration were not available for these two case studies. Instead, publicly 
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems ii

available data were used. Where no data existed, SCS substituted data from other sources 

in order to provide a complete – albeit conceptual data set. 

The goals of this supplemental report are (1) to demonstrate how an LCIA method 

might be used in the case of a thermal generator and (2) to identify problems that might 

arise in a complete LCIA analysis of power plants similar to those chosen for this 

demonstration project.

Significant insights have been gained in studying an LCIA method approach to 

examining the environmental footprint of these two thermal technologies. With these new 

insights, a complete and cogent LCIA analysis and Life Cycle Impact Declaration could 

be completed if a complete data set were used. 

Significant Findings

1. The WECC has the lowest greenhouse gas loading per 1,000 GWh of any NERC 

region in the US solely because of the large fraction of hydropower constituting the 

overall power mix (28 percent). 

2. If sited properly, the environmental performance of wind generation facilities is 

excellent when wind is a small fraction of the total energy available in a power pool. 

However, performance can degrade significantly with increasing levels of wind 

energy production. Because wind energy is not dispatchable, at higher levels of wind 

energy production its environmental performance approaches that of the power used 

to back it up.

3. Hydropower capacity offers the best backup source to preserve wind power’s 

environmental performance while allowing higher system penetration levels for wind. 

4. The environmental performance of coal-fired power plants vary quite widely, but can 

exceed that of even the WECC, depending upon: 1) the assay of coal inputs; 2) the 

method of mining; 3) the type and efficiency of energy generation; 4) the type of 

pollution control technologies employed; and 5) the location of the mine and power 

plant relative to areas of high population density and areas susceptible to exceedance 

of environmental thresholds.

5. On balance, natural gas-fired combined cycle power plants can perform better than 

the WECC average, though their performance is sensitive to location. Their energy 

resource-depletion ratings are worse than the WECC due to the relatively small 

reserves of natural gas.

6. The LCIA methodology can provide accurate, credible and relevant environmental 

performance results for all energy production systems studied. The ability to 

compare environmental performance among energy production alternatives and to a 

power-pool baseline can be especially useful for decision-makers.
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems iii

7. Unavailability of detailed proprietary data for power plant operations can be a 

significant obstacle to using the LCIA methodology to study those power plants.

Environmental Impact Profiles

Figure 1. Environmental Impact Profile of Glen Canyon Hydropower Generation System, 

Hydropower Function case, relative to the WECC baseline per 1,000 GWh.
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems iv

Figure 2. Environmental Impact Profile of Glen Canyon Hydropower Generation System, Water 

Conveyance Case, relative to the WECC baseline per 1,000 GWh.
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems v

Figure 3. Environmental Impact Profile of Stateline Wind System, Scenario 1.
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems vi

TERMS AND DEFINITIONS

I. Terms and Definitions Used in This Report

• Baseline —The reference case against which a material, product, service, or 

system is compared, where the indicator results represent the typical or 

predominant material, product, service or system for the sector, a prior version of 

the same product, service or system, or another identified product, service or 

system. All environmentally relevant impact categories for the sector must be 

included in the baseline comparison.

• Biobased Resource — commercial or industrial product (other than food or feed) 

that is composed, in whole or in significant part, of biological products or 

renewable domestic agricultural materials (including plant, animal, and marine 

materials) or forestry materials.1

• Category Indicator — The selected node for use in reporting the lifecycle impact 

assessment (LCIA) result. The indicator is often a quantifiable midpoint node 

within a given stressor-effect network that is selected to represent the impact 

category because it can be linked both to the initial stressor value and to the 

endpoint impact.

• Effect — A measurable, adverse change to human health or the environment. Also 

referred to as an “impact” (as in “impact category”)

• Emission Loading – The amount of emissions released into an environment that 

deposits into or resides in areas that exceed identified thresholds. This emission 

loading incorporates relative potency, fate and transport of the emission(s), as 

well as spatial and temporal characteristics of the identified endpoints.

• Environmental Characterization Factor (ECF) —A mathematical expression 

derived from the quantitative characterization of the relative degree to which a 

particular stressor affects the environment or human health within a specific 

impact category. 

• Environmental Data — Data used to characterize the condition of providing and 

receiving environments.

• Environmental Impact Profile (abbreviated as “Impact Profile”) — The 

cumulative summary of life-cycle impact assessment (LCIA) category indicator 

results representing the environmental performance of a material, product, service 

or systems, adjusted to a specific functional unit. 

• Environmental Mechanism — A distinct and measurable physical, chemical, 

radiological or biological process(es) that links stressor(s) to effects of human 

health or the environment. 

• Environmentally Preferable — A material, product, service or system that has 

lower environmental impacts than the current reference baseline across the lifecycle, without environmental trade-offs in any category indicators. 

 1 Farm Security and Rural Investment Act of 2002 (Public Law 107-17), (“2002 Farm Bill”), Section 9002.
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems vii

• Habitat Baseline — The condition of the habitat in a given area prior to the 

establishment of the production infrastructure associated with the material, 

product, service or system. 

• Impact — A measurable, adverse change to the human health or the environment. 

Also referred to as an effect (as in “stressor-effect network”).

• Impact Category — An issue of environmental or human health concern (e.g., 

climate change, acid rain) that represents a distinct or linked environmental 

mechanism(s). 

• Impact Endpoint — An identifiable impact on the natural environment, human 

health or natural resource reserves that can be linked back to a stressor(s) through 

a defined environmental mechanism. Also referred to simply as “endpoint.”

• Impact Group — Impact categories with common or similar midpoints/endpoints. 

• Impact Profile – See Environmental Impact Profile.

• Life Cycle Assessment (LCA) — Assessment that in includes determination of 

appropriate scope and boundary conditions, a complete life-cycle inventory, and a 

complete life-cycle impact assessment.

• Life Cycle Impact Profile Declaration (or simply, Life Cycle Impact Declaration) 

– A report summarizing the environmental impact profile derived from the use of 

the LCSEA as referenced in this Standard. There are three types of declarations: 

1) basic declaration of impacts; 2) reduced impact declaration; and 3) declarations 

of environmental preferability.

• LCIA Functional Unit (or simply, functional unit)— A common unit of output 

(e.g., 1000 GWh for electricity) to which category indicator results are 

normalized.

• Life Cycle Impact Assessment (LCIA) — The phase of life cycle assessment that 

converts life cycle inventory results (both inputs and outputs) into life cycle 

category indicator results by calculating the magnitude and environmental 

relevance of the resultant environmental/human health impacts. 

• Life Cycle Inventory (LCI) — The phase of life cycle assessment involving the 

identification, compilation and quantification of inputs and outputs associated 

with a given material, product, service or system throughout its life cycle.

• Midpoint Node —Any distinct, measurable intermediate chemical or biological or 

physical process along the stressor-effect network between the stressor point (e.g., 

emission, extraction) and the endpoint.

• Node — Any chemical or biological or physical process along a stressor-effect 

network model of an environmental mechanism. 

• Providing environment — The natural resource reserves from which resources are 

extracted.

• Receiving environment — The air, water, soil, and habitats into which emissions 

are deposited or in which they reside.

• Reserve base — The quantification of the natural repositories of a given natural 

resource that is economically or technically recoverable. 

• Resource depletion factor (RDF) — The characterization factor that reflects the 

rate of resource depletion against its reserve base.

• Stressor — Any input, output, and direct physical disruption activity associated 

with a material, product, service or system that can be linked to an effect. 
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems viii

• Stressor Characterization Factor (SCF) — A mathematical expression used to 

aggregate related stressors based on their relative potency with respect to a 

specific impact category. 

• Stressor-Effect Network — A model used to represent an environmental 

mechanism, in which a chain of events are shown to link the inputs, outputs, and 

direct physical disruption activities associated with a material, product, service or 

system to impact endpoints. Also referred to as “impact chains” or “impact-effects 

networks.”

• Threshold — An environmental condition that, when exceeded, is linked to 

adverse environmental or human health effects

• Unit operations – Distinct processes associated with industrial process associated 

a material, product, service or system across the scope of the assessment.

 

II. Abbreviations Used in This Report 

 

Ac acre

Asl Above sea level

BPA Bonneville Power Administration

Bq Becquerel (a measure of radioactivity, where 1 Bq equals 1 disintegration 

per second (compared to 1 curie = 3.7 x 1010 disintegrations per second).

CANDU Canada Deuterium Uranium (heavy water reactor technology)

CEA Canadian Electricity Association

CRSP Colorado River Storage Project

ECF Environmental Characterization Factor

EGRID Emissions & Generation Resource Integrated Database

EIA Energy Information Administration

EPI Environmental Performance Index

Eq. Equivalent

GCMRC Grand Canyon Monitoring and Research Center

GWh Gigawatt Hour (=1,000,000 kilowatt hours)

GWP Global Warming Potential

GLO Ground Level Ozone

Ha. Hectare

HEC Human Exposure Coefficient

HEF Human Exposure Factor

HF Hydrofluoric Acid

HRC Human Reference Concentration

HWR Heavy Water Reactor

IGCC Integrated Gasification Combined Cycle

ISO International Organization for Standardization; 

also, Independent System Operator

Kg Kilogram

LCA Life Cycle Assessment

LCI Life Cycle Inventory Analysis

LCIA Life Cycle Impact Assessment

LCSEA Life Cycle Stressor Effects Assessment
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems ix

LWR Light water reactor

LBWR Light boiler water reactor

MAF Million acre-feet

MWh Megawatt hour 

NAAQS National Ambient Air Quality Standards

NAAIB North American Association of Issuing Bodies

NERC North American Electric Reliability Council

NOAEL No Observed Adverse Effects Limit 

NOx Nitrogen Oxides

NRC Nuclear Regulatory Commission

NPRI National Pollutant Release Inventory (Canada)

ODP Ozone Depletion Potential

ODS Stratospheric Ozone Depleting Substances

PM Particulate Matter

RAINS Regional Air Pollution Information and Simulation model

RCRA Resource Conservation and Recovery Act

RDF Resource Depletion Factor

RfC Human Reference Concentration

RfD Human Reference Dose

RIVM Rijksinstituut Voor Volksgezondheid en Milieu (National Institute of 

Public Health and the Environment), Coordination Center for Effects2

ROW Right of Way

RNP Renewable Northwest Power 

RPP Regional Power Pool

RTO Regional Transmission Organization

SARA Superfund Amendments and Reauthorization Act

SCF Stressor Characterization Factor

SCS Scientific Certification Systems, Inc.

SOx Sulfur Oxides

Sv Sieverts

t Tonne (metric)

TBq Tera Becquerel (1 Bq x 1012)

TCDD Tetrachlorodibenzodioxin

TCLP Toxicity Characteristic Leachate Procedure

TRI Toxic Release Inventory (USA) 

WECC Western Electricity Coordinating Council

 2

 The CCE is the Data Center of the International Cooperative Programme on Modeling and Mapping of Critical Levels 

and Loads and Air Pollution Effects, Risks and Trends (ICP Modeling and Mapping, ICP M&M) and supports the work 

of the Convention on Long-range Transboundary Air Pollution (LRTAP) of the United Nations Economic Commission 

for Europe (UNECE).
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 1-1

Section 1.

STUDY OVERVIEW

1.1. Study Background

In 2002, the Western Area Power Administration (Western) contracted Scientific 

Certification Systems (SCS) to demonstrate the use of Life-Cycle Stressor Effects 

Assessment (LCSEA), a site-dependent life-cycle impact assessment (LCIA) approach, as 

a tool for establishing the environmental impact profiles of electric power generation 

systems in the western U.S. The study now consists of two reports. The first is an LCIA 

case study of two renewable electrical productions facilities: the Glen Canyon 

Hydropower System and the Stateline Wind Power Station. In a supplemental report, the 

concept of an LCIA approach, using publicly identifiable data and surrogate data, is 

applied to two thermal power plants: Colstrip Coal Power System and two natural gasfired technologies. The latter analyses were completed as a demonstration of what the 

opportunities and difficulties of applying this approach to thermal units. 

During the course of the project, Tri-State joined Western as an additional interested 

party and study sponsor.

1.2. Study Goals 

The goals of this renewable energy study were as follows:

• to demonstrate the use of the LCSEA methodology in establishing the 

environmental impact profile of selected electric power generation systems;

• to establish the impact profile of the WECC regional power pool to be used as a 

baseline against which the impact profiles of specific power generation systems 

can be measured and scaled (environmental efficiency analysis);

• to establish the Life-Cycle Impact Profile of the Glen Canyon Hydropower 

System as compared to the WECC regional power pool;

• to establish the Life-Cycle Impact Profile of the Stateline Wind Power System 

as compared to the WECC regional power pool;

• to demonstrate the degree to which the results of such a study can be used to 

support informed science-based energy policy discussions, to guide energy 

company decision-making and investments, and to support energy purchasing.

1.3. Scope of Work 

The study utilized life-cycle impact assessment to:
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• Establish the WECC (US) Impact Profile Baseline 

The WECC regional power pool consists of a wide diversity of power types, and 

extends over a vast section of the western US and Canada. In this study, the 

assessment was confined to power generation in the eleven US states included in 

the WECC.

• Determine the Impact Profile of a sample of renewable electrical energy 

generations systems: a Hydroelectric Generation System and a Wind Power 

Generation System

This project involved the establishment of the Life-Cycle Impact – LCIA study 

and a Life Cycle Declaration of the Glen Canyon Dam hydroelectric power 

generation system in the state of Arizona. Additionally, a Life-Cycle Impact study 

– LCIA was completed for the Stateline Wind Power generation system on the 

boarder of Washington and Oregon. No Life-cycle Declaration was made for this 

generation system.

The scope of assessment under LCSEA is cradle-to-grave, consistent with internationally 

recognized life-cycle assessment principles. For electric power generation systems, this 

scope typically includes: energy resource (and ancillary resource) extraction, raw 

material transport, fuel processing, fuel transport, power plant construction and 

operations, power transmission and distribution, waste disposal and treatment, and power 

plant decommissioning (Figure 1.1). 

Figure 1.1. Simplified schematic of the life cycle of an electric power generation system

1.4. Limitations

The following limitations in scope should be noted:

• The study did not address end-of-life issues (e.g., decommissioning of plants) 

associated with the electric power generation systems examined, even though 

this is within the normal scope of LCSEA, except as otherwise noted.
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• The study did not address one-time or non-recurring accidental releases from 

any of the electric power generation systems.

• The study addressed power quality or reliability concerns only to a limited 

degree, and did not address the security of the electric power generation systems 

examined.

• The study did not address possible worker safety concerns associated with 

electric power generation systems examined. 

• The study did not calculate environmental category indicators associated with 

noise, visual impact, or aesthetics.

In terms of the assessments conducted, the study was limited in two additional respects: 

1) certain inventory data and environmental characterization data were unavailable or 

unattainable by SCS within the agreed-upon budgets and timelines; and 2) while the 

study sought to demonstrate the methodology using certain baseline cases for 

comparison, other baseline cases might have been selected and thereby provided 

additional insights into the study findings.
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Section 2.

OVERVIEW OF LCSEA FRAMEWORK 

2.1. Historical Perspective 

The field of life-cycle assessment first began development in the 1960s in response to 

fuel and energy shortages. By the 1970s, analytical methods were proposed to conduct an 

analysis of fuel and raw material uses in the energy sector and in various industrial 

systems. These analyses were first referred to as Resource and Environmental Profile 

Analyses (REPA). In the late 1970s, the seminal text on conducting REPAs was 

published by Boustead and Hancock (1979) entitled Handbook of Industrial Energy 

Analysis. Between 1979 and 1990, additional environmental factors were added to 

REPAs, such as air emissions, water effluents, and solid wastes. REPA studies were 

considered to be useful inventories of the environmental inputs and outputs of industrial 

systems, and as such, were described as “Life Cycle Inventories” (LCI). Starting in the 

late 1980s and early 1990s, a number of software tools were developed to help interested 

companies conduct LCIs for their own industrial systems.

In 1990, the Society of Environmental Toxicology and Chemistry (SETAC) sponsored a 

conference in Vermont (USA), at which the term “Life Cycle Assessment” was used to 

describe studies in which factors associated with each life-cycle phase, including raw 

material use, energy use, emissions to air and water, and solid wastes were reviewed for 

an entire industrial system. In the Vermont conference, participants described Life Cycle 

Assessment (LCA) as having three parts: a) the Life Cycle Inventory (LCI), b) Life Cycle 

Interpretation, and c) Life Cycle Improvement. During this time, discussions among LCA 

practitioners focused on identifying better ways to use LCA for environmental decisionmaking purposes. The need for a methodology capable of linking system inputs and 

outputs to environmental effects thus became apparent, leading to the development of

life-cycle impact assessment (LCIA) from what was originally called life cycle 

interpretation, and ultimately, to the publication of an international standard (ISO-14044) 

in 2000.3

ISO-14044 was the product of six years of negotiation among delegates representing 

more than 100 countries. This standard established a common framework whereby the 

LCI results could be further classified and characterized in order to determine their 

relative impacts on the environment, then aggregated into a set of environmentally 

relevant impact category indicators. The main objective was to convert the LCI data into 

environmentally relevant category indicator results. The ISO 14044 standard is a 

 3

 ISO-14042 was drafted under the auspices of the ISO Technical Committee on Environmental Management (TC207). A number of collaborative publications contributed toward the development of the LCIA standard. Among the 

most prominent of these were the Nordic Guidelines on Life-Cycle Assessment (1995), including the LCA-Nordic 

Technical Reports 1-10, and the Society for Environmental Toxicology and Chemistry (SETAC) publications A 

Conceptual Framework for Life-Cycle Impact Assessment (1993) and Towards a Methodology for Life-Cycle Impact 

Assessment (1996).
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guidance standard that provides the basic methodological requirements to conduct 

scoping, the LCI and LCIA phases. At the center of the LCIA guidance is the 

establishment of the LCIA framework, which requires that impact categories be 

established in accordance with their identified environmental mechanisms. Such 

environmental mechanisms are the biophysical impact pathways (stressors, potentials, 

midpoints, and endpoints) related to the inputs and outputs inventoried during the LCI 

phase, as well as any biophysical impacts that have identified midpoints/endpoints. 

In 1995, the LCSEA methodology was among the first LCIA approaches to formally 

integrate LCI results with environmental impact assessment (EIA), environmental impact 

statements (EIS) and other standard environmental impact data sets. The outcome of this 

development was to transition LCIA modeling from a site-generic approach to a more 

site-dependent methodology.

Site-dependent LCIA methods for calculating category indicators, especially those 

associated with regional and local emissions, have continued to be refined, particularly by 

governments in Europe. The Danish Guideline for LCA, the Nordic Guideline for LCA 

and others have contributed by integrating dispersion modeling data into an LCIA 

framework. The United Nations Environment Programme (UNEP) has established a 

working group to codify LCA practice based on the existing advanced models, including 

the Danish and Nordic guidelines, and the SCS LCSEA methodology. The European 

Union (EU) is planning to adopt the UNEP model once it has been codified.

2.2. LCSEA Methodology and Metrics 

In LCSEA, the physical, chemical or biological environmental mechanisms that link an 

industrial input, output or activity (i.e., the “stressor”) to an observable impact (i.e., the 

“effect”) are modeled as “stressor-effect networks” (Figure 2.1). The environmental 

mechanisms used in this model include effects on ecosystems, effects on human health, 

and the net depletion or accretion of natural resources. LCSEA calculations involve the 

collection, analysis and integration of two types of data: 1) inventory data (i.e., the energy 

system’s land use, resource and energy inputs, environmental releases and wastes that act 

as potential stressors), and 2) characterization data that put these inventory data into the 

perspective with respect to various environmental impacts.4

Consistent with standard LCIA practice, the LCSEA methodology contains formal 

protocols for classification of inventory results and characterization of these results with 

regard to their respective impacts.

 4

 Like all LCIA models, LCSEA is a data integration methodology focused on collecting and analyzing a variety of 

existing data resources rather than on conducting traditional EIA research. 
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Figure 2.1. Example of a Stressor-Effect Network

2.2.1. Classification Protocols

To start, impact categories are identified that represent distinct stressor-effects 

networks with defined nodes (Figure 2.1). For each impact category, a category 

indicator is selected that is representative of a distinct node along the stressor-effect 

network. “Core” impact categories are then distinguished from categories that are not 

relevant to a specific region, as described in SCS-002 (Appendix 6). Aggregation of 

stressor-effect networks with unrelated nodes is not permitted. 

Inventory data are then assigned to one or more relevant category indicators. Any 

inventory data that cannot be assigned to a category indicator must be identified in the 

inventory, but may be excluded from the final indicator results if sufficient 

justification is provided. 

2.2.2. Characterization Protocols

All category indicators must be characterized using spatial and temporal parameters. 

Stressor characterization factors (SCFs) and environmental characterization factors 

(ECFs) or their equivalent must be established before an indicator calculation can be 

conducted. SCFs characterize the relative potency of various stressors contributing to 

the same environmental effect. The relative scale used for the SCF is based upon 

known chemical, biological or physical parameters that are both reproducible and 
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peer reviewed. ECFs characterize the fate and transport of the stressors, including 

threshold analysis and integration of the relative severity, duration, and reversibility 

of the measured effect. Threshold analysis involves determining whether a given 

effect has crossed a defined threshold. To establish an effects threshold, a scientific 

consensus must exist regarding the threshold level. The relative scale used for the 

ECF is 0-1. Further discussions of SCFs and ECFs by indicator are found in Section 

3 and in Appendix 6.

Meeting the Requirements of Comparative Assertion

LCSEA metrics meet the requirements of the ISO 14044 LCIA framework and the SCS002 Committee Draft for making “comparative assertions”. In this case, Glen Canyon 

Hydropower Station impact levels (i.e., environmental performance) are compared to the 

averaged impact levels of the combined power mix that makes up power production of 

the WECC NERC region. The environmental relevance of the selected impact group, 

impact categories and related category indicators must be demonstrated in order to be 

included as a measure of environmental performance. 

In this study, the two renewable electrical power systems were compared to the WECC 

baseline. Consistent with the comparative assertion requirements of ISO 14044 and the 

SCS-002 Committee Draft, all environmentally relevant impact categories were identified 

and corresponding category indicator results calculated for both Glen Canyon and 

Stateline as well for power systems making up the WECC. Whereas standard LCA 

models do not address the key habitat and species issues that have long been the center of 

environmental attention of multiple stakeholders concerned about hydropower and wind 

power projects, LCSEA metrics have been specifically designed to address the 

complexity and degree of ecological disturbance (impacts on riverine, wetlands, 

terrestrial, lake and riparian habitats, and loss of key species) associated with power 

generation systems. LCA studies that have not addressed these key issues have been 

considered misleading or of little use in making comparisons between fossil generation 

systems and hydropower and wind generation systems. By addressing the key habitat 

and species issues in a standard way for all power generation systems, LCSEA metrics 

provide a more robust comparison between power systems to allow the inherent strengths 

of each generation technology to be reviewed with greater credibility.

2.3. Steps for Conducting Assessments

The steps for conducting assessments of electric power generation systems consistent 

with the SCS-002 Committee Draft are summarized below.

2.3.1. Determination of Scope and Boundary Conditions

All projects begin by setting boundary conditions and establishing the scope of a 

project. 
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• All relevant unit processes are identified for the electric power generation 

system, and for the baseline against which the system is to be compared.

• Study boundaries are delineated, incorporating relevant spatial (i.e., 

geographic) and temporal conditions.

• The functional unit is determined for the electric power generation system and 

for the baseline against which the system is to be compared. Typically, this 

functional unit is 1,000 gigawatt-hours. Additionally, any line losses due to 

transmission distance are factored into the LCIA calculations. 

• Scoping must account for spinning or other reserves that are necessary due to 

intermittency of a particular generation source (e.g., wind, solar) or FERCmandated minimum flow requirements (i.e., hydro), or any other changes to 

specific power generation systems that could alter the power mix in the 

regional power pool.

2.3.2. Life Cycle Inventory Analysis

After setting the boundary conditions and scope of the study, a life cycle inventory is 

conducted. 

• Data related to system inputs and outputs for each unit process are collected. 

(Only those data that are relevant to the calculation of category indicator 

results related to active impact categories are required.)

• Inputs and outputs are calculated by unit process. For this study, SCS used the

KCL-ECO LCI model (see Appendix 3).

• Appropriate spatial and temporal characterization is conducted to ensure that 

unit process data are not improperly aggregated. 

2.3.3. Life Cycle Impact Assessment

Once the LCI is completed, the LCIA or impact assessment phase of a project is 

begun. 

• Defining Stressor-Effects Networks — Stressor-effects networks are 

identified and properly described before use in calculating category indicator 

results related to the electric power generation system and the regional 

baseline under study. Measurable nodes (usually a midpoint node along the 

stressor-effect network) are identified based on the strength of their linkages 

to the stressor and the impact endpoint. The node with the strongest link to 

both the stressor and the impact endpoint is identified as the category indicator 

for the stressor-effect network. The name of the category indicator reflects the 

midpoint node or impact endpoint selected.

• Classification — Inventory data are assigned to impact categories in 

accordance with LCIA modeling requirements. 
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• Characterization — Environmental data are collected for use in 

characterizing the classified inventory data.5 These data are integrated into the 

calculation of characterization factors on a site-specific or site-dependent 

basis where regional and local effects are an issue, taking into account the 

following considerations:

- the current state (i.e., degree of stress) of the receiving or providing 

environment at the midpoint node or impact endpoint;

- the spatial attributes, such as geographic area and scale of the respective 

receiving/providing environments.

- the temporal aspects, such as duration, residence time, persistence, timing, 

and the reversibility of the environmental mechanism.

• Inventory data are characterized.

• Data are also collected to account for any impacts to habitats or key species 

resulting from direct physical disruption of terrestrial, aquatic, or riparian 

habitats.

• Aggregation — Once the classified inventory data are characterized by unit 

process, these data are aggregated to calculate the category indicator results.6

• Environmental Impact Profile — Together, these indicator results form the 

Environmental Impact Profile. Sensitivity analyses are conducted as needed to 

confirm results. 

• Life Cycle Impact Declaration — The impact profile of a given power 

generation system is compared to the impact profile of a baseline case on an 

indicator-by-indicator basis to generate the Life Cycle Impact Declaration. 

2.4. Impact Groups, Impact Categories and Category Indicators 

As noted above, according to ISO 14044 and the SCS-002 Committee Draft, all impact 

categories must first be reviewed for their environmental relevance to the sector 

represented by the material, product, service or system. Table 2.1 provides the list of all 

impact categories that must be reviewed. To exclude any of these impact categories, a 

justification must be provided that illustrates why the category is not relevant to the 

study. Similarly, additional impact categories may be considered if justification can be 

provided that they are required based on characterization of active midpoints. SCS-002 

Annex A, included here as Appendix 6, provides the required algorithms, specific 

assumptions, data requirements, characterization models and background information 

related to each group, impact category and category indicators. 

Within the scope of this study, those impact categories and category indicators in the 

final column of Table 2.1 were found to be environmentally relevant. The process for 

 5 Environmental data may come from a variety of sources, including governmental, academic, industry and stakeholder 

publications, as well as privately held databases. Examples of data sources related to energy resource depletion include 

environmental impact assessments (EIA), the US Geological Survey, National Energy Board (NEB) of Canada, World 

Energy Institute, and British Petroleum. Examples of data sources related to the direct physical disruption indicators 

include Federal Energy Relicensing Commission (FERC) reports and LANDSAT data. Examples of data sources 

related to emission loadings include US Environmental Protection Agency Toxic Release Inventory (TRI) data, 

monitoring records, and sampling records.

6

 Data aggregation under an impact indicator takes place only if such aggregation does not reduce the overall accuracy 

of the indicator result. 
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determining environmental relevance followed protocols is described in Appendix 6. 

Justification for the exclusion of impact categories is provided in Appendix 7. 

Table 2.1. LCSEA Impact Groups, Categories and Category Indicators

LCSEA Impact Groups and Category Indicators Required Node for 

Category Indicator 

Core Impact Categories for 

this study, based on 

environmental relevance

Abiotic/Biotic Resource Depletion Group

Non-renewable Energy Resource Depletion Midpoint Node 2 Core

Water Resources Depletion Midpoint Node 2 Core

Biobased Resource Depletion Midpoint Node 2

Strategic Metals Resource Depletion Midpoint Node 2

Landscape Disruption Group

Terrestrial Habitat Disruption Midpoint Node 2 Core

Aquatic (Lake) Habitat Disruption Midpoint Node 2

Aquatic (River) Habitat Disruption Midpoint Node 2 Core

Riparian/Wetland Habitat Disruption Midpoint Node 2 Core

Loss of Key Species Midpoint Node 3 Core

Climate Change Emissions Group

Accumulated GHG Radiative Force Loading7 Midpoint Node 4 Core

Radiative Force Loading

- - Well-Mixed Greenhouse Gases

- - Tropospheric Ozone8

- - Soot (Carbon Black)9

Midpoint Node 3

Aerosol Force Cooling10 Midpoint Node 3

Environmental Effects Emissions Group11

Acidification Loading (Oceanic) Midpoint Node 3 Core

Acidification Loading (Regional) Midpoint Node 3 Core

Stratospheric Ozone Depleting Chemical Loading Midpoint Node 2

Ecotoxic Chemical Loading Midpoint Node 2 Core

Eutrophication Loading (Regional) Midpoint Node 2

Human Health Effects Emissions Group

Ground Level Ozone Exposures Midpoint Node 3 Core

Particulate (PM 2.5 equivalent) Exposures Midpoint Node 3 Core

Pulmonary Toxic Chemical Exposures Midpoint Node 3 Core

Systemic Toxic Chemical Loading Midpoint Node 2 Core

Neurotoxic Chemical Loading Midpoint Node 2 Core

Indoor Inhalation Hazard Loading Midpoint Node 2

Noise Exposures12 Midpoint Node 2

Untreated Hazardous Wastes Group

Specific Untreated Hazardous Waste Risks Potential Node 1 Core13

Eq. is equivalent, t is metric tons, kg is kilograms, ha is hectare

 7

 Normalized to GMT2040 EOT 8 By justified regional midpoints

9 By justified regional midpoints

10 By regional cooling zone, where appropriate 11 Materials and products are not required to calculate cumulative loadings; rather, environmental loadings are 

calculated based on the functional unit. 

12 Accounts for noise in exceedance of a 60 Decibel threshold.

13 In this study, untreated radioactive waste risks, measured as Equivalent GBq Pu-239
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Section 3.

STUDY CONVENTIONS, ASSUMPTIONS AND CONSIDERATIONS

This Section addresses key conventions, as well as assumptions made in calculating LCI 

and LCIA results for regional and local emissions addressed in this study. Additional 

assumptions and considerations related to the LCSEA framework are described in 

Appendix 6, while further assumptions specific to the assessment of the WECC and Glen 

Canyon Hydropower Station and Stateline Wind Power Station are described in Sections 

4 and 5 and 6.

3.1. LCI Conventions and Assumptions 

The following conventions and assumptions were applied during the LCI phase of data 

collection and processing. 

3.1.1. Raw Materials

Raw materials and fuels extracted from the earth were burdened with their inherent 

feedstock value and, in addition, were burdened with the resources, energy, direct 

physical disruption, emissions, and wastes associated with extraction, refining and 

transportation. 

3.1.2. By-Products

By-products, such as fly ash and gypsum associated with power production from coal, 

were recorded as output amounts, but subsequent processing or use of such 

byproducts were outside the study boundaries. 

3.1.3. Fuel Inputs and Outputs

Fuel inputs included the total amount of fuel inputs from all sources in the defined 

electric power generation system, including fuels used for transportation and 

processing, as well as in power generation and delivery. The calculations for 

electricity used in different processes, such as oil refining, were performed according 

to the relevant KCL ECO Model unit operations for grid electricity, based upon 

statistical values for grid electricity. The KCL ECO Model was also the source of 

data for production of fuels for truck and ship transport, based on unit operations for 

oil refining.

Transportation data were recorded in terms of the type of vehicle and the distance 

involved, including whether a trip was one-way or round-trip. These data were then 

converted into units of vehicle-kilometers, and according to the corresponding unit 

operations in the KCL ECO Model converted into quantities of resources and fuel 

consumed and emissions and wastes generated.
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3.1.4. Emissions to Air 

Air emissions speciated by chemical and recorded in mass flow (mass per volume per 

unit of time) represent discharges into the atmosphere after passing through emission 

control devices. Air emissions were calculated for all system processes, including 

operations associated with the generation of electricity, process emissions, and 

emissions resulting from the production and combustion of fuels for process or 

transportation energy. All such emissions were left unaggregated and unallocated.

3.1.5. Emissions to Water

In this study, there were no reported emissions to water. It was not within the scope 

of this demonstration study for SCS to perform due diligence on the data provided.

3.1.6. Solid Wastes

Solid wastes, recorded in units of mass, represent all emissions to ground from unit 

operations within the systems studied. While solid waste inventory values are 

provided for the completeness of the study, solid waste is, in fact, an input to a final 

unit operation, solid waste management (i.e., landfill, incineration, etc.). 

Within the LCSEA methodology, the accounting of resource wastes occurs under the 

net resource use calculations. Air emissions generated by incineration are accounted 

for under their respective category indicators (e.g., particulate loading).

3.1.7. Line Losses 

For this study, it was assumed that there is a 2% loss of delivered power due to line 

losses in transmission, based on the statistical average for the transmission distances 

involved.14

3.2. Site-Dependent Factors Used to Calculate Regional Emissions

The following discussion describes the key assumptions, data and considerations used to 

calculate the category indicators associated with regional and local emission loadings in 

this study. Specific assumptions related to Glen Canyon, Stateline and the WECC 

baseline is described greater detail in their specific sections.

3.2.1. Regional Acidification Loading Assumptions

In this study, SCS assumed that the emissions dispersed within concentric plumes 

around the plants over long averaging periods. This assumption is supported by a 

number of modeling exercises using the RAINS model under varied meteorological 

and stack conditions (Figure 3.1). 

 14 The 2% line loss value is corroborated in a number of sources, including Vattenfall Generation’s Certified 

Environmental Product Declaration of Electricity from Forsmarks Kraftgrupp AB (FKA), S-P-00021; 2001. 
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Figure 3.1. Acidification Dispersion Modeling in Europe 

Source: Institute of Energy Research (IER), Stuttgart University. 

CORINAIR is the database for emissions in Europe.

The calculation shown in this figure was performed to determine 

acidification deposition, but is also representative of NOx dispersion. 

Scale: Size of total affected region equals about 2000 km from edge to edge.

The geographical distribution of critical acidification load exceedance is based upon 

the UNEP/RIVM (1999) global acidification report, where exceedance maps for 1992 

are given together with estimates for 2015. An overview map from the UNEP report 

is shown below (Figure 3.2). The UNEP report also provides an exceedance map 

forecast for 2015, essentially showing the same exceedances.
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Figure 3.2. Exceedance areas for acidification in North America in 1992

The map grid is 1o by 1o. All areas with a deposition/critical ratio over 1 (yellow to red) 

are exceedance areas. The ovals indicate areas of 800-km radius. 

Source: UNEP (1997).

To obtain the acidification ECF for North American locations, the following method 

has been used. Acidifying substances were assumed to be dispersed according to the 

EcoSense function, shown in the figure as concentric segments around the point of 

emissions. These segments were placed on the map showing the exceedance grid 

according to UNEP/RIVM (1999), and then the exceedance percentage of every 

segment area was estimated. (See example for Washington State, Figure 3.3).

Acid dep. (S+N) / critical load (meq)

0 – 1.0

1.0 – 1.5

1.5 – 2.0

> 2.0

Agriculture

Ice, water, not data
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Figure 3.3. Example of Acidification Exceedance Mapping from a Point Source in Washington State

Source: RIVM/UNEP - Global assessment of acidification and eutrophication of natural ecosystems (1999)

The ECF value calculation results are presented in Table 3.1 for the geographical 

regions relevant for the study.

Table 3.1. Composite Acidification ECF values calculated by State

Emission region Acidification ECF 

Washington 0.07

 Montana 0.07

 Oregon 0.06

 Idaho 0.06

 Wyoming 0.02

California 0

Nevada 0

Utah 0

Colorado 0

Arizona 0

New Mexico 0

The above results would be possible to verify using long-range Lagrangian 

dispersion/deposition modeling for the actual geographical locations in question, and 

by superimposing the deposition results on the exceedance map.15 This kind of ECF 

 15 The Lagrangian derivative is the change over time of an air parcel’s velocity or concentration as measured from the 

perspective of the parcel itself. It is the sum of the instantaneous change at a fixed location and the convective change 

(or change due to the movement of the parcel through a field of velocity or background concentrations). Integration of 

Concentric Land in Weighted

element* exceedance exceedance

0 - 10% 15% 2%

10 - 20% 10% 1%

20 - 50% 5% 2%

50 - 80% 10% 3%

80-100% 0% 0%

Total 7%

* denotes percent of total cumulative 

acidifying deposition that deposits within the

segment area

Washington

Estimating ECF
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assessment, however, was not possible within the resources allocated to this project. 

Earlier work performed in Europe has shown that results from the simplified 

approach used here is in good agreement with results from more elaborate 

dispersion/deposition modeling methods. 

3.2.2. Ground Level Ozone

3.2.2.1. Human Health and Vegetative Impacts

In the LCSEA methodology, two indicator values can be calculated for ground 

level ozone: a human health indicator and a vegetation category indicator. Each 

indicator has its own threshold of critical exceedance. The World Health 

Organization (WHO) established the threshold for the onset of human health 

effects to be an exposure to 60 parts per billion (ppb) of ground level ozone over a 

period of 8 hours, while the threshold for the onset of damage to sensitive crops is 

40 ppb based on a cumulative exposure of 3000 ppb-hours. The 60-ppb/8-hour 

limit has been used as the basis for establishing regulations to protect human 

health. However, in the case of vegetative damage, the data are more complex, 

and the linkage between the 40 ppb exposure level and the duration of exposure to 

specific vegetative damage is less clear. As a result, no regulatory limits have 

been set based on this threshold. For this study, only the human health indicator 

was calculated. 

The indicator results are calculated using the following equation, and reported in 

cumulative exposure units of measure (persons * ppm O3 * hours).

Ground Level Ozone Exposures = ∑i [ ∑n (NOx emissions x SCFregion x ECEC)]

Where:

• The loading represents the cumulative exposure over threshold (AOT 60), delineated by isopleth, of 

NOx-equivalent emissions.

 • i represents the total number of unit processes.

 • n represents the total number of ozone precursors emitted by a unit process.

 • SCF is the specific conversion rate of NOx and other precursors to NOx equivalence based on 

background concentrations of VOCs and NOx in a given region

 • ECEC is the product of the cumulative exposure as determined by AOT 60 mapping by isopleth, and 

the corresponding population density within the dispersion domain.

3.2.2.2. Considerations in Establishing SCFs and ECFs 

Establishment of the SCFs and ECFs used to calculate the ground level ozone 

indicator involves the correlation of threshold concentrations to point source 

emissions and the resultant cumulative human exposure. 

 this function gives the trajectory of the parcel, which is the change of the parcel’s position or concentration over time. 

This trajectory is used to determine the horizontal and vertical extent of the contaminant plume over a given area, 

which is used to calculate cumulative concentrations. 
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3.2.2.2.1. Establishing SCFs

The SCF for ground level ozone is based on the establishment of conversion 

rates for kg of O3 formed per kg of NOx or VOCs emitted. 

• The following atmospheric reactions are used to estimate the range of 

conversion rates: 

o Intermediate alkyl-hydroxyl free radicals (ROO·) are formed from 

VOCs, CO or hydroxyl radical (OH·) and NOx. 

o The peroxy radicals and ozone (O3) oxidize nitrous oxide free 

radicals (NO·) to form nitrogen dioxide (NO2). 

o NO2 is split by ultraviolet radiation (UV), leading to the formation 

of NO· and the release of oxygen free radicals (O·). 

o Oxygen free radicals then react with oxygen (O2) to form O3.

• Conversion rates are also dependent upon meteorological conditions and 

the background concentrations of both VOCs and NOx.

• Secondary SCFs may be required to establish the specific conversion rate 

for a given region of the various compounds that comprise the aggregated 

VOC release. Either the maximum incremental reactivity (MIR) or photooxidative chemical potential (POCP) reactivity ranking may be used to 

determine this secondary SCF.16

The ratios of conversion from NOx to ozone can vary significantly — for 

instance, from 0.2 to 1.3 kg O3 per kg of NOx released — depending upon the 

regional background concentrations of VOCs and how limited the NOx 

concentrations are within that region (Table 3.2).17 

Table 3.2. SCF values for four different areas within Europe

Area SCFs (kg O3 / kg NOx)

N Lappland, Finland 1.232

E Svealand, Sweden 0.957

SE England 0.228

C Germany 0.276

Additionally, a difference between initial concentrations of nitric oxide free 

radicals (NO•) has been observed between urban and rural environments. A 

British government study of rural and urban areas found that the 97th

percentile seasonal average for ozone was 52 ppb in rural areas and 43 ppb in 

 16 MIRs are established by the California Air Resources Board; POCPs are published in the Nordic Guidelines.

17 LCSEA Practitioner’s Manual, Scientific Certification Systems, the Swedish Environmental Research Institute (IVL) 

and Soil and Water, 1997.
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urban centers.18 The lower values for urban areas were attributed to the 

removal reaction of NO• with O3, resulting in lower levels of ozone formation 

in urban centers due to higher mobile source emissions. The British study 

results suggest that the same level of NOx emissions in urban centers forms 

20% less O3 than in rural areas. The SCFs for rural areas in the vicinity of 

large urban areas are likely to be in the range of 1.2, while in urban areas, the 

value is likely to be approximately 0.8. For isolated rural areas, much lower 

SCF values are expected. 

In the current study, an SCF of 1.0 was assumed, which is the equivalent of 

one kilogram of O3 forming for each kilogram of NOx emitted. For VOCs, the 

corresponding factor, based on European correlations in the Danish Guideline, 

was assumed as 0.55 kg O3/kg VOC. 

3.2.2.2.2. Establishing the ECF based upon the AOT-60 Exposure 

Framework

In order to establish the ECF for ground level ozone, an exceedance threshold 

must be identified. No absolute scientific consensus has been reached for 

determining the threshold for chronic human health effects from exposure to 

ground level ozone. The World Health Organization’s (WHO) Air Quality 

Guidelines use a threshold of 60 ppb averaged over an 8-hour period (i.e., 

where the concentration level is calculated from running eight-hour averages 

of the one-hour mean concentrations).19 In this study, SCS used the WHO 

threshold, based on its compatibility with the European Union’s AOT-60 

(“accumulated concentration over threshold”) Framework. Several 

publications and websites present the scientific underpinnings of the AOT-60 

approach and integrate these data sets into the regulatory framework to 

address trans-boundary pollution.20 

The AOT-60 Framework allows for the establishment of an ECF based upon: 

1) the relative population densities of different regions that exceed the 60-

ppb/8-hr. threshold; or alternatively 2) the relationship of these population 

densities to the overall percentage of total NOx emissions contributing to the 

cumulative annual exposure. The AOT-60 threshold is expressed as the 

number of people exposed, multiplied by hours of annual cumulative ozone 

exposure above 60 ppb. The Human Exposure Factor (HEF) is expressed per 

gram of NOx or equivalent VOC emitted as “person * ppm O3 * hours / g 

NOx”, and represents a unit of cumulative exposure for a given region. The 

HEFs for 41 regions or countries in Europe have been determined with the 

 18 Derwent, D., “Ozone Trends in the British Isles and their European Policy Context, Climate Research Division,” 

Meteorological Office, Bracknell, UK [EPG1/3/164], 2002.

19 World Health Organization (WHO) Air Quality Guidelines for Europe, 2nd Edition, 2000. 20 Readers interested in this framework are directed to the general website of the Coordination Center for Effects in 

Holland, CCE, RIVM. http://arch.rivm.nl/cce.
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RAINS model (Hauschild et al. 2000) based upon population densities and 

areas of exceedance of 60 ppb, as shown for 17 countries in Table 3.3.21 

Table 3.3. Data required for establishing a site-dependent ECF for ground level ozone

Country Area, 

km2

Area, 

km x km *

Persons

per km2

HEF:

pers⋅ppm⋅hours/

g NOx

22

Austria 83 845 290 96 7.0E-05

Belgium 30 518 175 330 3.8E-04

Denmark 43 094 208 121 3.4E-05

Finland 338 145 582 15 8.5E-07

France 543 965 738 106 2.2E-04

Germany 356 974 597 228 1.7E-04

Greece 131 957 363 79 1.9E-05

Ireland 70 284 265 51 1.2E-05

Italy 301 303 549 190 2.0E-04

Luxembourg 2 586 51 156 1.1E-04

Netherlands 41 526 204 370 2.3E-04

Norway 323 877 569 13 2.1E-06

Poland 323 250 569 119 1.1E-04

Portugal 92 389 304 106 1.3E-04

Spain 504 790 710 78 4.6E-05

Sweden 449 964 671 20 1.2E-05

Switzerland 41 293 203 169 9.8E-05

United Kingdom 244 100 494 238 9.9E-05

* Approximate square root of the column to the left

The data in Table 3.3 can be used to calculate the Human Exposure 

Coefficient (HEC), representing the rate at which cumulative exposure varies 

by population density. The slope value is determined by linear regression 

analysis (Figure 3.4). The product of the HEC and the average population 

density of any region within a known dispersion domain is the site-dependent 

ECF. If the highest exposure value given for the regions in Table 3.3 (3.8E-4) 

were set at an ECF of 1, then the HEC would be calculated to be 0.0022. The 

ECF value would then be calculated as:

ECFGround Level Ozone = 0.0022 * PD

 21 Hauschild M. and Potting J. (2002), Danish Guideline: Spatial differentiation in life cycle impact assessment - the 

EDIP2000 methodology. Institute for Product Development, Technical University of Denmark. Guidelines from the 

Danish Environmental Protection Agency, 2000.

22 Source: Danish Guideline.
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where PD is the average population density within a 300-kilometer distance 

from the emission source point (i.e., the assumed dispersion domain). 

Figure 3.4. Determining the Human Exposure Coefficient for Ground Level Ozone

pers⋅ppm⋅hours/g NOx

Given the equation for calculating ECFs, and assuming the concentric plume 

pattern, then all that remains is to estimate the population density for the 

regions within the current study. Population density data for the US is shown 

in Figure 3.5.

Figure 3.5. Population density of the United States in year 2000

Convert to people per square km by multiplying with 0.3861
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© 2009. Scientific Certification Systems, Inc. Page 3-11

The estimated population densities for the dispersion domains (i.e., the 

receiving environments) relevant to the projects (both power generation 

systems and baselines) are shown in Table 3.4, together with the 

corresponding ECFs.

Table 3.4. Composite Ground Level Ozone ECF Values for WECC States,

Calculated According to the ECF Approximation Method

Emission location Population density*

Persons / (km)2

Ground level 

ozone ECF

Washington 28.2 0.062

Montana 2.1 0.005

Oregon 11.4 0.025

Idaho 4.7 0.010

Wyoming 1.8 0.004

California 73.7 0.162

Nevada 4.2 0.009

Utah 8.1 0.018

Colorado 12.3 0.027

Arizona 12.5 0.027

New Mexico 4.8 0.011 *

 within 300 km distance from the point of emission

While specific domains within each state varied from region to region, Table 

3.4 shows the composite ECF values by state for those states serviced by the 

WECC. For the WECC baseline impact profile, the ECF values for specific 

generation systems were calculated in accordance with standard LCSEA 

protocols for several key generation systems. Sensitivity analysis 

demonstrated that the composite statewide ECFs provide approximately the 

same overall indicator loadings for ground level ozone as the more sitedependent ECFs. As such, the composite values are the only ECFs provided 

in this study report. The low value ECF factors in Wyoming and Montana are 

due to low population density per the equation in page 3-9, 

3.2.3. Particulate Loading

3.2.3.1. Establishing the SCF

The assumptions in this study for calculating the SCFs for particulates are 

consistent with the approach described in Danish Guideline, Appendix 8.1 

(Hauschild & Wenzel 1998), in which relative potency characterization factors 

are established using ambient air quality standards based on the human reference 

concentrations (HRC, or RfC) for particulate matter.23

 23 The abbreviation, HRC, is used in Europe, while the abbreviation, RfC, is used in the U.S.
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The Danish Guideline provides example values for relevant ambient particulate 

concentrations. For example, the recommended 24-hour limit value for the 

United Kingdom is 50 μg/m3.

24 The regulatory thresholds set for annual national 

ambient air quality by the US Environmental Protection Agency are 50 μg/m3 for 

PM-10, and 15 μg/m3 for PM-2.5. Using 50 μg/m3 as the HRC value for PM-10, 

the relative potency would be calculated by the Danish Guideline as 1/HRC = 

2E+4 m3/g, while for PM-2.5, the relative potency would be 1/HRC = 6.7E+4 

m3/g. The SCF values for the indirect formation of aerosols and for SO2 have 

been derived as averages from the European health damage factors published in 

Krewitt et al. (2001), relative to PM-10 damage factors.

Table 3.5. SCF values as PM-10 equivalents

3.2.3.2. Establishing the ECFs

The ECFs reflect the cumulative annual human exposure associated with a given 

amount of release. The region-dependent ECF is established in much the same 

way as the ground level ozone ECF in that it is dependent upon the atmospheric 

residence time of the various PM fractions, the release height, meteorologically 

dependent dispersion and deposition patterns, and the population density in the 

dispersion domain. 

3.2.3.2.1. No Threshold Exposure Modeling

The complexity of the various PM fractions, plus the uncertainty surrounding 

the composition of the various fractions, complicates the establishment of 

background thresholds. For example, depending on the assay of a given coal 

source, there can be a wide distribution of constituents in a PM fraction. 

Consequently, the resulting variation in health effects from various fractions 

 24 Danish Guideline: Spatial differentiation in life cycle impact assessment - the EDIP2000 methodology. Hauschild M. 

and Potting J., Institute for Product Development, Technical University of Denmark. Guidelines from the Danish 

Environmental Protection Agency, 2002, Appendix 8.

PM Fractions Potency factors

(1/HRC)

PM-10 eq. SCF

m3/g (t PM-10eq/t)

Particles – as PM-10 μm 

fraction 2.0E+04 1.00

Particles – as PM< 2.5 μm 

fraction 6.7 E+04 3.33

Particles - indirect sulfates 

per emitted SO2 3.0E+04 1.5

Particles - indirect nitrates

per emitted NOx 2.0E+04 1.0

Sulfur dioxide (SO2) 6.8E+02 0.034
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of PM emissions and a multitude of other emission sources creates levels of 

uncertainty that preclude the establishment of a threshold concentration. Since 

the indicator is derived strictly on a basis of cumulative exposure, the 

indicator has been calculated instead on an absolute basis without use of a 

threshold concentration. 

3.2.3.2.2. Establishing the Human Exposure Factors

The dispersion model used must cover distances up to one thousand 

kilometers in order to account for potential mobility and residence time 

contributing to the cumulative exposure for some of the PM fractions (Figure 

3.6). 

Figure 3.6. Cumulative exposure as percent of total according to dispersion models

Sources: TSP and NO2 examples from European Commission (1998)25

Modeling by Krewitt et. al. (2001) calculated the cumulative exposure for the PM 

fractions covering a region of 5500 x 5100 km that was divided into 150 x 150 km 

grid cells. Krewitt et. al. 2001 determined the HEFs from one metric ton per 

annual emissions of SO2, sulfate aerosols, nitrate aerosols and PM-10 as 

calculated with the EcoSense model for 14 European countries at 1990 and 

projected 2010 conditions. In Table 3.6 below, the results have been converted to 

an emission rate of 1 gram/second (g/s) of the substance, where the HEF is 

represented in units of person * (μg / m3) * (g/s)-1 of emitted substance. 

 25 European Commission Directorate-General XII 1999: ExternE; Externalities of Energy. Volume 7: Methodology 

1998 Update, p.63.
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Table 3.6. Examples of human exposure factors in Europe 1990 

Source: Krewitt et al. 200126

* The population density values have been estimated roughly from statistical data for surrounding 

 areas/countries within 300 km radius (the km2 include also sea and other uninhabited areas).

As in the case of establishing the ECFs for ground level ozone, the establishment 

of a site-dependent ECF for PM fractions requires that HEFs be plotted against 

the relevant population densities within the dispersion area domain. The data in 

Table 3.6 can be used to calculate the HEC (i.e., the slope determined by linear 

regression) that represents the rate that cumulative exposure varies by population 

density (Figure 3.7). 

0

2 000

4 000

6 000

8 000

10 000

12 000

14 000

16 000

18 000

0 20 40 60 80 100 120

population density, persons per km2

SO2 Sulfate Nitrate PM-10 Linear (PM-10)

Figure 3.7. Determining the Human Exposure Coefficient for PM Loading

person * (μg / m3) * (g/s)-1

If the highest exposure value in Table 3.6 is defined as ECF=1, the “best-fit” HEC 

(i.e., the linear regression slope with the least uncertainty) for all fractions is 

calculated to be 0.007. This HEC multiplied by the population density yields the 

site-dependent ECF for each project using the following equation: 

 26 Krewitt, W., Trukenmüller, A., Bachmann, T. and Heck, T. Country-specific Damage Factors for Air Pollutants – A 

Step Towards Site Dependent Life Cycle Impact Assessment. Int. J. LCA 6(4) pp199 – 210 (2001).

Point of emission Population

density *

Exposure factor,

person * (μg / m3)

1 g/s,

31.5 t/year

Persons/(km)2 SO2 

emission

Sulfate 

aerosol from 

SO2

Nitrate 

aerosol 

from NOx

PM-10 

emission

The Netherlands 106 16 777 11 638 8 782 12 236

Austria 108 12 268 12 239 14 312 11 384

Italy 64 8 925 8 935 11 013 9 650

Finland 10 1 829 2 027 2 377 1 230
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ECFPM = 0.007 * PD//(persons per km2)

where PD is the average population density within a 300-kilometer distance from 

the emission source point (i.e., the assumed dispersion domain). The ECFs for the 

current study are shown in Table 3.7. 

Table 3.7. Composite PM Loading ECF values for WECC states

Emission location Population density 

(Persons/km2)

PM Loading 

ECF 

Washington 28.2 0.020

Montana 2.1 0.001

Oregon 11.4 0.008

Idaho 4.7 0.003

Wyoming 1.8 0.001

California 73.7 0.052

Nevada 4.2 0.003

Utah 8.1 0.006

Colorado 12.3 0.009

Arizona 12.5 0.009

New Mexico 4.8 0.003

3.2.4. Chronic Hazardous Chemical Loadings 

Stack emissions data from previous SCS studies have been used to confirm the 

validity of calculated emissions factor. 

3.2.4.1. Classification Issues

3.2.4.1.1. Determining the Chemicals in this Group of Indicators 

Although coal systems and typical light water nuclear reactor systems within 

the WECC generate a wide range of radiological and non-radiological 

releases, these releases were grouped based on common endpoints and routes 

of exposure into the same sets of category indicators.

3.2.4.1.2. Classification by Specific Health Effects Endpoints 

Within LCIA practice, a sharp division exists over the appropriate approach 

for classifying hazardous chemical loadings. On the one hand, the Danish 

Guideline recommends that all chemicals within this group be aggregated into 

one indicator. The Guideline reflects a largely European assumption that as 

long as the chemicals are classified generically by governments as toxic 

and/or hazardous, no further sub-classification is required. Both the 

International Life Sciences Institute (ILSI) and SETAC (North America) have 

rejected the European assumption as an oversimplification of the variety of 

endpoints possible for hazardous chemical exposure, and have proposed a 

classification step that leverages existing toxicological methods and data. This 

growing consensus position proposes that these chemicals be classified 
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according to their specific non-cancer and carcinogenic endpoints. SCS 

adopted the SETAC position for this study.

While SETAC has proposed this classification outline, no published studies 

(prior to this study) to date have used this classification approach. Several 

methodological issues have arisen while applying this classification approach. 

For example, it was necessary to conduct the assessment by using the 

classification and characterization steps in an iterative manner. Typically, 

these steps are applied sequentially: first, establishing and defining the impact 

category, then characterizing the impacts. However, due to the complexity of 

the environmental mechanisms associated with this grouping, it was necessary 

not only to identify specific health endpoints, but also, to include the routes of 

exposure as part of the sub-classification of indicators. TCDD and related 

compounds provide a good case example of why the 

classification/characterization process must be iterative. While the routes of 

exposure for these compounds routinely include inhalation as well as indirect 

uptake from soils through the food chain, additional routes of exposure exist 

(e.g., bioaccumulative potential from the recirculation of these compounds in 

the environment). Furthermore, unlike many of the compounds associated 

with these endpoints, these chemicals tend to bio-magnify in the body. As a 

result, even though the entire class of compounds has similar endpoints, their 

mechanisms differ sufficiently to necessitate the use of separate indicators to 

be consistent with the SETAC framework.

3.2.4.2. Characterization Issues

In both coal and nuclear power generation systems, the only chemicals in this 

group of indicators with potentially active human health or environmental 

endpoints are those associated with direct inhalation routes of exposure, and 

indirect exposure through uptake of heavy metals through soils and water into the 

food chain. Characterization of indicators associated with direct inhalation 

exposure was conducted in a manner consistent with the approaches described 

above for ground level ozone and particulates. The characterization of indicators 

that involve indirect exposure requires site-specific dispersion modeling and 

analysis. For this study, SCS drew upon information reported in an analysis 

conducted by Cantox Environmental under a separate series of studies regarding 

chemicals involved in secondary routes of exposure.27

3.2.4.2.1. Establishing SCFs

For non-radiological compounds, the SCFs (i.e., human toxicity factors) were 

obtained from the human reference concentrations listed for hazardous 

chemicals in the Danish Guideline, Appendix 8.1. For radiological 

compounds, the HRC is derived from national emission standards and dose 

coefficients for various radionuclides and their daughter decay nuclides, as 

 27 Cantox Environmental. Report to EPCOR, Appendix A. June 6, 2001.
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described, for example, in USEPA (1993)28. According to US national 

emission standards, the emission standard threshold value for radionuclides is 

defined as follows: "Emissions to the ambient air shall not exceed those 

amounts that would cause any member of the public to receive in any year an 

effective dose equivalent of 10 mREM/year." In scientific notation, the 

corresponding dose value is 0.1 mSv/a (milliSievert per annum). This is also 

an accepted international standard worldwide.

The dose coefficient for each radionuclide depends on the type and intensity 

of the radiation emitted; the half-life time of the decay is also relevant. 

Radionuclides are characterized by the US EPA (1993) using effective dose 

coefficients for humans submerged in air in (Sv/s)/(Bq/m3) for each nuclide, 

as shown in Table 3.8. The SCF value is calculated from the dose coefficients 

as Rn-222 equivalents, by dividing the values in column 2 with the value for 

Rn-222. From the dose coefficient values and the dose standard of 0.1 

mSv/a, HRC values also have been calculated.

Table 3.8. Potency Factors (SCFs) and Human Reference Concentrations (HRC)

 for Selected Radionuclides

Nuclide + daughters

Dose coefficient for 

submersion in air, 

(Sv/s)/(Bq/m3)

Equivalent dose 

coefficient SCF, Bq 

Rn-222 eq / Bq 

(nuclide) 

HRC, Bq/m3

H-3 3.31E-19 3.74E-06 9.58E+06

C-14 2.24E-19 2.53E-06 1.42E+07

Kr-85 7.60E-15 8.60E-02 417.2

Kr-88 1.02E-13 1.15E+00 31.1

Xe-133 1.56E-15 1.76E-02 2032.7

Xe-135 1.19E-14 1.35E-01 266.5

Rn-220 1.13E-13 1.28E+00 28.1

Rn-222 8.84E-14 1.00E+00 35.929

Pb-210 8.97E-17 1.01E-03 3.54E+04

Po-210 4.16E-19 4.71E-06 7.62E+06

 28 USEPA (1993): External Exposure to Radionuclides in Air, Water, and Soil. Federal Guidance Report EPA-402-R93-081. 29 Rn-222 is a major contributor to the natural background dose for humans. A check of the above calculation can 

easily be found in the literature. In the UNSCEAR 2000 annual report, the annual effective dose at a typical natural 

background radon concentration of 10 Bq/m3 from outdoor exposure during 1760 h/a is given as 0.095 mSv/a. 

Calculating backwards, the HRC for a 0.1 mSv/a dose at 8760 hours of exposure requires 2.1 Bq/m3. This value is 

obviously much more cautious than earlier tabulations, such as those in USEPA 1993. On the other hand, German 

radiation protection authorities allow 80 Bq/m3 radon in urban areas (Frischknecht et. al. 1996), which is 8 - 40 times 

above the values calculated from the UNSCEAR report. The value in this table (35.9 Bq/m3) then is within the range of 

these three values from the literature.
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3.2.4.2.2. Establishing ECFs 

The ECFs reflect the cumulative annual human exposure associated with a 

given amount of chemical release from a given point source. As in the case of 

ground level ozone and PM, the region-dependent ECF is dependent upon the 

atmospheric residence time of the emitted chemicals, the release height, 

meteorologically dependent dispersion and deposition patterns, and the 

population density in the dispersion domains. Figure 3.8 shows examples of 

the cumulative exposure as a function of distance from the source of emission.

Figure 3.8. Cumulative exposure as percent of total according to dispersion models30

Source: Potting et. al. (2000).

The study results from Potting et. al. (2000) can be used to establish 

cumulative HEFs. In the study, two different models were used for the 

exposure calculations: the EUTREND31 Gaussian plume type model for short 

distances (up to about 10 km), and the WMI trajectory model for regional 

distances (up to over 2500 km distance).32 For these models, two substances 

were investigated: benzene, which has an atmospheric residence time of seven 

 30 References: European Commission (1998), ExternE: Externalities of Energy, Volume 7, Methodology 1998 Update, 

Chapter 4: Models for Air Pollution Analysis. Potting, J., Trukenmüller, A., van Jaarsveld, H. and Hauschild, M. 

(2000); Site dependent assessment of human exposure from air emissions in life cycle assessment. In: Potting, J. 

(2000): Spatial differentiation in life cycle impact assessment, Doctoral thesis, Utrecht University, March 2000. 

31 Van Jaarsveld J.A., W.A.J. van Pul and F.A.A.M. de Leeuw: Modelling transport and deposition of persistent 

organic pollutants in the European region. Atmospheric Environment, Vol. 1997, Issue 31, pp 1011 – 1024. 32 Krewitt W., P.Mayerhofer, R.Friedrich, A. Trukenmüller, T. Heck, A.Gressmann, F. Raptis, F. Kaspar, J. Sachau, K. 

Rennings, J. Diekmann, B. Praetorius. ExternE – Externalities of energy. National implementation in Germany (EUR 

18271). Directorate-General XII for Science, Research and Development of the European Commission, 1997.

0

10

20

30

40

50

60

70

80

90

100

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Distance from point of emission, km

Hydrochloric acid Benzene 
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days, and hydrochloric acid, with a corresponding residence time of seven 

hours. These two substances were used as surrogates for emissions of 

substances with similar chemical and physical properties, including 

atmospheric residence times. A whole class of low boiling point organic 

compounds emitted from coal operations would have exposure factors similar 

to benzene. Likewise, some compounds that are susceptible to wet deposition 

would have exposure factors similar to hydrochloric acid. In the case of 

radioactive substances, the radioactive decay half-life also must be considered 

when establishing the ECF.

To calculate the HEF, the Potting study used the EMEP grid in Europe for a 

region of 5500 x 5100 km divided into 150 x 150 km grid cells.33 When an 

emission of one gram per second (1 g/s) of the substance was located in any of 

the grid cells, the HEF, expressed as “person * (μg / m3)”, was obtained as a 

result. 

The HEF was calculated for various release heights and 

meteorological/climatic conditions (e.g., maritime, central, South Europe and 

northern locations). In the case of hydrochloric acid, the average HEF was 

2460 person * (μg / m3) per g/s. In the case of a longer-lived substance, 

benzene, the average HEF was 50,000 person * (μg / m3). Depending on the 

point of emission the HEF values varied as shown below in Table 3.9. 

Table 3.9. Data required for establishing a site-dependent 

ECF for chronic hazardous chemical loadings – direct inhalation only

Source: Potting et al., 2000

Point of emission Exposure factor, person * (μg/m3) Population 

Density*

1 g/s Benzene type 

substance

Hydrochloric acid 

type substance Persons/(km)2

The Netherlands 71 700 11 280 106

Austria 67 460 4 320 108

Italy 54 280 5 050 64

Finland 11 020 570 10

* This value was not given in Potting (2000). The values have been estimated roughly from statistical 

data for surrounding areas/countries within 300 km radius (the km2 includes sea and other 

uninhabited areas). 

The data in Table 3.9 can be used to calculate the HEC (the slope calculated 

through linear regression), which represents the rate that cumulative exposure 

varies by population density for hydrochloric acid-type chemicals and 

benzene type chemicals (Fig. 3.8). The product of the HEC and the average 

population density of any region within a known dispersion domain is the sitedependent ECF. Using the above data, and assuming an ECF = 1 for the 

highest values in the two columns, the regression analysis yielded the 

 33 EMEP, 1998.Transboundary acidifying air pollution in Europe. MSC-W status report 1998 – Parts 1 and 2. 

EMEP/MSC-W Report 1/98, Norwegian Meteorological Institute, Oslo, Norway.
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© 2009. Scientific Certification Systems, Inc. Page 3-20

following HECs for long-range chemicals and short-range chemicals within a 

given indicator group. 

Figure 3.9. Determining the Human Exposure Coefficient for 

Chronic Hazardous Chemical Loadings, person * (μg / m3) * (g/s)-1

The ECF values, therefore, were:

ECFs short-range compounds = 0.0011 * PD/(persons per km2)

ECFs long-range compounds = 0.0094 * PD/(persons per km2)

Table 3.10 shows the ECF values for the regions relevant to the projects and 

baseline cases included in this study report.

Table 3.10. ECF Values for WECC states

Chronic Hazardous Chemical Loadings

Emission location Population 

density 

(Persons/km2)

ECF

short-range

ECF

long-range

Washington 28.2 0.031 0.265

Montana 2.1 0.002 0.020

Oregon 11.4 0.013 0.107

Idaho 4.7 0.005 0.044

Wyoming 1.8 0.002 0.017

California 73.7 0.081 0.693

Nevada 4.2 0.005 0.039

Utah 8.1 0.009 0.076

Colorado 12.3 0.014 0.116

Arizona 12.5 0.014 0.118

New Mexico 4.8 0.005 0.045
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The classification of radionuclides into short-range or long-range substances 

can be checked against the radioactive decay half-lives shown in Table 3.11. 

The nuclides Kr-85, Kr-88, Xe-135 and Rn-220 have decay half-lives below 

10 hours, and therefore must be classified as short-range substances. 

However, given the non-ionic nature of these noble gases, the atmospheric 

velocity of transport may warrant a longer-range classification, pending 

further research. The nuclides H-3 and C-14, on the contrary, have a short 

atmospheric lifetime, despite the radioactive decay that is measured in years.

Table 3.11. Radioactive Decay Half-Life for Selected Nuclides

Nuclide + daughters Dominant nuclide half life

C-14 5730 years

Pb-210 22.3 years

H-3 12.4 years

Po-210 138 days

Xe-133 5.2 days

Rn-222 3.8 days

Rn-220 10.6 hours

Xe-135 9.1 hours

Kr-85 4.5 hours

Kr-88 2.84 hours
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Section 4.

The WECC (US) REGIONAL POWER BASELINE 

4.1. Project Description and Background

4.1.1. Project Description

Under this project, SCS calculated the impact profile of the Western Electricity 

Coordinating Council (WECC) electric power generation system, which served as the 

baseline for comparison in this study. A baseline impact profile represents the 

averaged level of impact by indicator of all power generation systems that make up 

the total mix of power in a regional power pool. In this study, the assessment was 

confined to power generation in the eleven US states included in the WECC. 

4.1.2. Project Background 

The WECC baseline impact profile provides a common point of reference against 

which individual power generation systems contributing to the power pool can be 

compared, and against which improvement efficiencies can be measured. The 

calculation of the regional power pool impact profile involves a survey and analysis 

of the full spectrum of power generation sources comprising the power pool, 

summarized below. The full list of power plants that make up the WECC and their 

related datasets is provided in Appendix 4. 

4.2. WECC Regional Power Baseline

4.2.1. General Description 

As described by the North American Electric Reliability Council (NERC), the 

Western Electricity Coordinating Council, or WECC, “comprises the entire Western 

Interconnection. With a footprint of 1.8 million square miles and members operating 

in 14 states in the Western US, two Canadian provinces, and Baja Norte, Mexico, the 

WECC is the largest geographically of the ten NERC regions. WECC members 

represent the entire spectrum of bulk electricity users and are divided into five 

member classes: large transmission owners, small transmission owners, electric line 

of business entities that do no operate transmission, end users, and state and 

provincial regulators.”34 The WECC is part of a national NERC regional system with 

specific control centers in each region as shown in Figure 4.1.

 34 http://www.nerc.com/regional/wecc.html
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Figure 4.1. Control Areas within WECC and other NERC Regional Power Pools 

4.2.2. Sub-NERC Regional Baselines

The data used to established the overall WECC baseline can also be aggregated 

within either the subregions of the various NERC regions or at the ISO levels as 

described below. However, the complexity of transactions related to 

import/export of power exchanges in sub-NERCs make them less than ideal as 

LCIA baselines. 

• Subregions — Within the NERC regions, specific subregions have been 

identified, as shown in Table 4.1. These subregions are defined by EPA, 

and as such, are lined up with existing EPA environmental data.
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Table 4.1. NERC Subregions

Source: EGRID 2002

eGRID subregion name States involved

ASCC Alaska Grid

ASCC Miscellaneous AK

ECAR Michigan MI

ECAR Ohio Valley IN,KY,MD,MI,OH,PA,TN,VA,WV

ERCOT All TX

FRCC All FL

HICC Miscellaneous HI

HICC Oahu HI

MAAC All DC,DE,MD,NJ,PA,VA

MAIN North MI,WI

MAIN South IA,IL,IN,MN,MO

MAPP All IA,IL,MI,MN,MT,ND,NE,SD,WI,WY

NPCC New England CT,IL,MA,ME,NH,RI,VT

NPCC NYC/Westchester NY

NPCC Long Island NY

NPCC Upstate NY NY,PA

SPP North KS,MO

SPP South AR,LA,MO,NM,OK,TX

SERC Mississippi Valley AR,IA,LA,MO,MS,OK,TX

SERC South AL,FL,GA,MS

SERC Tennessee Valley AL,GA,KY,MS,NC,TN

SERC Virginia/Carolina GA,NC,SC,VA

WECC California CA,NV,UT

WECC Great Basin CA,ID,MT,NV,OR,UT,WA,WY

WECC Pacific Northwest CA,ID,MT,OR,WA,WY

WECC Rockies AZ,CO,MT,NE,NM,SD,UT,WY,

WECC Southwest AZ,CA,NM,NV,TX

• ISO Regions — The regions controlled by the Independent System 

Operators (ISOs) provide an even greater degree of regional 

differentiation. The selection of ISO-controlled regions has several 

potential advantages: 1) the ISOs control much of the data needed for the 

assessments; 2) the ISOs are making the direct dispatch decisions that 

must be taken into consideration for the assessments; and 3) the ISOs are 

involved in reviewing and integrating new source generation. Depending 

on size and breadth, one ISO or a group of ISOs could be considered an 

appropriate baseline. The California ISO, for instance, is large enough to 

serve as a discrete baseline.

4.2.3. Scope of WECC Baseline Assessment 

For this study, the WECC power pool was defined as the total electricity generation 

from the utility and non-utility power plants operating within the US part of the 
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WECC region. The functional unit for the study was derived from data associated 

with net annual generated electricity, normalized to 1,000 GWh.

The total energy produced in the WECC in 2000 was 667,640 GWh. Table 4.2 

provides an overview of the WECC total generation by plant primary fuel, as reported 

in EGRID 2002. The category, “other”, which represents 4.6% of total generation, 

includes wind, geothermal, biomass, solar, waste fuel, and other minor plant 

contributions. 

Table 4.2. WECC Electricity Generation in the Year 2000 by Main Primary Fuel

Source: EGRID2002. 

Fuel Total WECC

GWh %

Coal 217,013 32.5%

Hydro 188,382 28.2%

Gas 105,672 23.3%

Nuclear 74,164 11.1%

Oil 1,917 0.3%

Other 30,490 4.6%

Total generation 667,640 100.0%

The full electric power generation system includes not only the power plants, but also 

the “upstream” unit processes involved in the extraction, processing and delivery of 

fuels, such as coal mining, primary oil and gas extraction, processing and distribution, 

lime production and transport. As noted in Section 1, impacts associated with end-oflife dismantling of plants were not assessed for the full WECC. Such impacts are 

typically insignificant relative to the impacts associated with the operation lifetime. 

4.3. WECC Baseline Power Mix

The generation mix included in the WECC regional baseline was derived from the 

EGRID database. This generation mix is described in Appendix 4. 

4.4. Data Sources 

4.4.1. Primary Data Sources 

The establishment of the US WECC baseline involved a review of readily available 

data pertaining to generation plant types, size/capacity, GWh production, locations, 

ages, technology specs, type and amount of material flows. Data on fuels, emissions, 

efficiencies and co-generation for both the utility and non-utility power plants were 

derived primarily from two sources: SCS’s LCSEA database and the EGRID 

database. Both sources are considered to have excellent data quality. 
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The SCS LCSEA database integrates data from a variety of published industry, 

government, and independent reports and life-cycle assessment studies, and in 

addition, incorporates data collected and analyzed under previous SCS LCSEA 

studies of power generation in North America and Europe conducted over the past 

decade. 

The EGRID database contains data on emissions and resources associated with 

electric power plants operating in the United States, integrating data sources on power 

plants and power companies from three different federal agencies – the 

Environmental Protection Agency (EPA), the Energy Information Administration 

(EIA), and the Federal Energy Regulatory Commission (FERC). Its data relate to 

more than 4,700 power plants and nearly 2,000 generating companies.35

Power plant data obtained from the EGRID 2002 database for eleven western states -

— Washington, Oregon, California, Arizona, Utah, Wyoming, Colorado, New 

Mexico, Montana, Idaho, and Nevada — were confirmed by SCS on a plant-by-plant 

basis (Figure 4.2).

For example, hydropower generation listed in EGRID 2002 was checked by 

comparing its list of power plants to the list of dams in the National Inventory of 

Dams (NID) database, which identifies over 71,000 dams in the United States, and 

the USGS Basins database. This 

crosscheck was conducted because the EGRID database did not 

include all of the data needed to 

develop a framework to calculate 

the full life-cycle impacts, since it 

did not have data on size of the 

impoundments associated with 

each hydropower plant. EGRID 

lists the power plants, but not the 

dams themselves. Moreover, in 

some cases, a single power plant 

is associated with more than one 

dam; likewise, multiple power 

plants may be associated with a 

single dam. By overlapping the 

NID and USGS databases, SCS 

was able to check on the number 

of installations in the WECC and 

subsequently link surface area 

calculations for major impoundments with specific power gener-

 35 EGRID description source: www.epa.gov/cleanenergy/egrid/whatis.htm#what

Figure 4.2.

Confirming Major Plant Locations in the US WECC

(Source: EGRID 2000)
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ation capacity. 

The EGRID database was also useful in providing data on a number of other aspects 

of each plant including (but not limited to) annual fuel use, annual capacity, 

efficiency, annual net production of electricity, ownership, and location. EGRID also 

contains annual emission amounts by plant for criteria pollutants: SOx, NOx (annual 

and ozone season emissions), CO2 and mercury.

4.4.2. Additional Data Sources 

In addition to EGRID and the SCS LCSEA database, SCS consulted other published 

data sources on coal mining and coal quality.36 For instance, the mass (kg.) of release 

data for chemicals and metals such as arsenic, cadmium, lead, manganese, nickel 

compounds and polycyclic aromatics, were taken from a study published by NREL.37

Radioactive Rn-222 emissions from coal mining and combustion were found in the 

benchmark Swiss study (Frischknecht et. al. 1996).38 The US EPA Toxic Release 

Inventory (TRI) data, though available, were not used as the basis of the calculations. 

Whereas TRI data are generated for regulatory purposes based on generic EPA 

emissions factors, LCSEA requires site-specific emissions data in order to accurately 

assess category indicators.

Additional data for solar, wind, geothermal, and biomass generation were identified 

through state databases.

4.4.3. Upstream Unit Processes

Generally speaking, upstream unit processes were found not to have significant sitedependent issues; therefore, SCS drew upon data from its energy sector database, 

including data from North American and European operators. Sensitivity analyses 

were conducted to confirm that the use of these data was justified, and will be 

described further in the final study report for peer review.

4.5. Key Project Assumptions and Considerations

Classification and characterization assumptions and considerations pertinent to the 

WECC power have been discussed in Sections 2 and 3 of this report, and are described 

more extensively in Appendix 6. 

 36 Hydrogen chloride and hydrogen fluoride emissions were mainly assigned to coal combustion, consistent with earlier 

SCS studies.

37 Spath, P., Mann, M., Kerr, D. Life-Cycle Assessment of Coal-Fired Power Production. NREL, June, 1999. 38 Frischknecht, R. et al., Life cycle inventory of energy systems. Basic methods and data for environmental comparison 

of energy systems and for the inclusion of energy systems in an environmental assessment of Switzerland (in German). 

Swiss Energy Economy Administration (Bundesamt fuer Energiewirtschaft BEW). The Foundation for Projects and 

Research of the Electricity Industry (Projekt- und Studienfonds der Elektrizitätswirtschaft PSEL). 3rd Edition, July 

1996.
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During the period over which this study has been conducted, SCS has gradually been able 

to increase the accuracy of the data sets used to establish category indicators for the 

baseline impact profile. For example, concurrent to this study, LCSEA algorithms 

continued to be refined; these refinements now allow captured in the SCS-002 Committee 

Draft, including refinements for several category indicators involving human health 

endpoints to be calculated with respect to cumulative annual exposures based upon 

accurate population density mapping. These advances have made it possible to calculate 

the WECC air emission loadings with greater accuracy.

Specific considerations and assumptions specific to the establishment of the WECC 

baseline impact profile are described below:

4.5.1. Characterization of Receiving Environments for Emissions Category 

Indicators

The establishment of indicator results for category indicators with regional and local 

impact endpoints required considerable data collection, characterization modeling and 

key assumptions. For example, the characterization of the various receiving 

environments for the acidification, ground level ozone, PM, and chronic hazardous 

chemical loading indicators each required modeling that took into account specific 

meteorological conditions and airsheds. 

LCI and LCIA modeling were completed for significant power systems within the 

WECC before averaging the entire mix of power systems into the WECC baseline 

impact profile. Because of the very large area encompassed by the WECC, the 

receiving environments were prioritized by technology, nameplate capacity and 

location. By ordering the process in this manner, the larger generation systems were 

first characterized and the indicator results calculated for the acidification, ground 

level ozone, particulate, and chronic hazardous chemical loadings. For the remaining 

smaller units, composite ECFs by state were used.

4.5.2. Water Resource Depletion 

SCS researched the issues surrounding depletion of surface water and ground water in 

the WECC region, looking for evidence of increases rates of evaporation (e.g., in the 

case of lakes formed from impoundments), and increased rates of aquifer depletion. 

Although such changes may have historically been a significant factor, SCS did not 

find sufficient evidence of significant changes in rates of water depletion to warrant 

the cost of calculating this indicator for the WECC. Even in areas of large water 

impoundments, such as Lake Powell, conflicting data concerning rates of evaporation 

made such calculations difficult. An exception was noted in the case of geothermal 

power, which constitutes only a very small fraction of the total WECC power pool 

capacity. Here, significant net depletion was observed, related to current efforts to 

reinject water from aquifers to generate additional steam. However, given the small 

contribution of geothermal power to the total WECC power pool, this net depletion 

did not materially influence the average for the power pool.
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4.5.3. Key Species Indicator

Impacts calculated under the key species disruption indicator relate to given 

population of that species at a specific location, and, therefore, are not expressed as a 

WECC indicator “average” result. 

4.5.4. Characterization of Wastes 

Mining and plant operation wastes are potentially hazardous due to their high metal 

content (particularly slags, sludges, slurries and ashes). Dewatering practices from 

mining can involve re-injection of groundwater and, therefore, can result in 

contamination. In order to characterize the waste streams from coal power systems, 

both groundwater and surface water monitoring data are needed to confirm that 

wastes are fully contained for the duration of their potential to leach into the receiving 

environment. For the WECC power pool baseline impact profile calculations, SCS 

assumed that the waste stream management practices of the coal power generation 

systems do not result in measurable impacts on groundwater quality.

4.5.5. Characterization of Coal Assay to Determine Material Use

For coal systems, the modeling incorporated assumptions based upon published 

statistics on the type of coal mining (surface or underground) and the sulfur content of 

coal. From the combination of sulfur content, heat value and SOx emission levels, 

SCS estimated the degree of flue gas desulfurization based on the age and type of 

coal generation in the WECC, which in turn yielded input data for lime consumption 

and associated upstream processes.

4.5.6. LCIA Data for Nuclear Power Systems

After completing several LCIA studies on various light water reactors systems, SCS 

has found that most light water reactor nuclear systems have very similar impact 

profiles. The similarities are due to the similar designs of all reactors, similar burn-up 

rates, central enrichments facilities (only one in the US), identical waste storage 

requirements, very tight regulations on emissions, and that fact that almost all were 

built during the same phase of technology development. As a result, SCS modeled 

the nuclear systems within the WECC without obtaining or using site-dependent data 

from the actual facilities. Since hydropower does not create any impacts related to 

nuclear power, this shortcoming in the scope of work was not considered significant 

to the overall comparative assertion of Glen Canyon to the WECC. 
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4.6. Summary LCI Results

The LCI results are summarized in Table 4.3. 

Table 4.3. Life-Cycle Inventory Results for the WECC Regional Power Pool 

Data are normalized to a production of 1,000 GWh.

WECC Regional Power Pool Average

Inventory Unit

Outputs

Emissions, air

Arsenic kg 16

Benzene kg 6

Cadmium kg 1

CFC-114 kg 34

CH4 kg 906,170

CO2, fossil kg 478,383,000

PM-10, TSP kg 197,030

VOC, HC kg 29,910

HCl kg 26,959

HF kg 683

Mercury kg 7

Manganese kg 14

NOx kg 956,413

Lead kg 10

Rad. act. Rn-222 GBq 2,910

Rad. act. noble gases GBq 250

SO2 kg 731,940

Emissions, water --

Wastes NA

Energy

electric power MWh 1,000,000

Inputs

Resources

Coal kg 200,080,000

Crude oil kg 3,631,900

Natural gas kg 48,502,000

Uranium in ore kg U 3,048

Limestone kg 3,183,900

-- denotes negligible or zero result

NA denotes data not available or not provided. 
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4.7. Landscape Disruption Group - Habitats Disrupted

LCSEA includes an assessment of direct habitat disturbance from all power systems 

operating within the WECC, including effects on species abundance and productivity 

from power generation facilities as well as from land use functions associated with 

administration buildings, roads, mines, and right-of-ways (e.g., for transmission lines). 

Because of the size and complexity of the WECC, the current scope of work did not 

permit a detailed assessment of various degree and types of habitats disrupted from 

overall power operations. However, given the focus of this study on the Glen Canyon 

Hydropower Station and on the Stateline Wind Power Station, key assumptions could be 

made and still meet the objectives of LCIA assessment. The following assumptions were 

made: 

• The scale of terrestrial habitat disruption per 1000 GWh was established for the 

WECC baseline. This impact category has significant contributions from 

transmission line ROWs, coal mining, hydropower operations, natural gas 

extraction and distribution, and coal transport. ROWs constituted the largest 

single source of impacts in this category. 

• Wetlands/riparian, riverine and lake habitats disruption from Glen Canyon were 

assumed to be at “worst case” disruption levels relative to the levels of the WECC 

baseline. For the Stateline Wind Power system, two scenarios were created: a 

“stand alone” scenario and one that includes a natural gas-fired “backup” 

generator to compensate for the intermittency of the wind power system. The 

terrestrial, riparian, riverine habitat disruption levels for the Stateline project 

differ according to the scenario used. The level of disruption per 1000 GWh for 

other major generation systems in the WECC was estimated to be an order of 

magnitude lower than impact levels observed from the Glen Canyon Dam and 

Stateline operations, as can be seen from the following table. 

Table 4.4.

Scale of Disruption of Riparian/Wetlands, Riverine and Lake Habitats within WECC Power Mix 

Fuel Type Percentage of 

WECC Power Mix Scale of Habitat Disruption

Coal 32.5% R/W neg., R neg., L neg

Gas 23.3% R/W neg., R neg., L neg.

Nuclear 11.1% R/W neg., R neg., L neg. 

Oil 0.3% Unimportant to Baseline impact levels

Other – including 

Wind 4.6%

Unimportant to Baseline impact levels

 Hydro 28.2%

R/W = 25 to 14,000 h, 

R = 0 to >600 m, 

L = > 30 h 

Total generation 100.0%

Riparian/Wetland = R/W, Riverine = R, Lake = L, h= Hectare, m = miles
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As can be seen from the Table 4.4, 66.9% of the total power derives from nuclear, 

coal and natural gas that has negligible levels of impacts of riparian/wetlands, riverine 

and lake habitats. Hence, hydropower constitutes 99% of the source of these 

impacts for the WECC baseline values. Due to the sheer size of the Glen Canyon 

dam and impoundment, its habitat disruption impact levels represent the higher range 

for all hydropower systems. 

4.8. LCSEA Results 

Category indicator results are calculated for the entire system, based on the classification 

and characterization steps described in Sections 2 and 3 and incorporating the special 

study assumptions and considerations described above. These category indicator results 

together form the baseline impact profile for the WECC regional power pool system, as 

summarized in Table 4.5. Tables 4.6 and 4.7 show examples of the LCSEA calculations 

by indicator category. (Additional detailed data for the other indicator categories will be 

provided in the final study report for peer review.)

Table 4.5. WECC Impact Profile — Category Indicator Results per 1,000 GWh Production 

Key Indicator Unit WECC Baseline

Non-renewable Energy Resource Depletion Eq. GJ of oil 5,207,000

Water Resources Depletion Acre-feet NC

Terrestrial Habitat Disruption Eq. ha. disturbed 1,88239

Aquatic (Lake) Habitat Disruption Eq. ha. disturbed Not broken out

Aquatic (River) Habitat Disruption Eq. river miles Not broken out

Riparian/Wetland Habitat Disruption Eq. ha. disturbed Not broken out

Loss of Key Species % loss key species NA40

Accumulated GHG Radiative Force Loading Eq. t CO2 500,000

Acidification Loading (Oceanic) t CO2 165,000

Acidification Loading (Regional) Eq. t SO2 6.5

Eco-Toxic Chemical Loading Eq. kg As NC

Ground Level Ozone Loading* t O3 8.9

Particulate Loading* Eq. t PM10 12.2

Pulmonary Toxic Chemical Loading* Eq. kg Benzene 5.2

Systemic Toxic Chemical Loading Eq. kg TCDD NC

Neurotoxic Chemical Loading Eq. kg Hg 5.7

Radioactive Waste Loading Eq. GBq Pu-239 NC

-- denotes negligible or zero result; NC denotes not calculated; NA denotes not applicable.

Results above 10,000 are rounded to the nearest 1,000.

* These category indicators were calculated as loadings at the time that the WECC portion of this study was 

conducted. Since that time, the algorithms for these three indicators have been converted to exposure 

calculations. Because Glen Canyon did not result in any emissions associated with these three impact 

categories, the upgrading of these indicator results to measurements of exposure was deemed unnecessary. 

 39 As noted in Section 2, four habitat disruption indicators have been identified. At the time the current study was 

initiated, however, habitat disruption calculations were collapsed under a single indicator. The WECC indicator result 

was calculated with data collected at that time, and hence is presented as a single indicator result. 40 Not applicable. The baseline for key species is based on pre-system species populations in the same region. 
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Table 4.6. LCSEA Non-Renewable Energy Resource Depletion Results for

the WECC Baseline Case per 1,000 GWh

Energy Resource Energy Stressor

Equivalent

Energy 

 Resource 

Depletion 

Factor

Equivalent

Resource

Depletion Resource Characterization Resource (RDF25): Depletion

Inventory Consumed Factor (SCF) Consumed Rate of dep /

Resource (t) (GJ/t) (GJ) Rate of oil dep (GJ oil eq.)

Uranium in 

ore 3.048 900,000.0 2,743,524 0.51 1,399,197

Crude oil 3,631 45.6 165,596 1.00 165,596

Natural gas 48,501 53.4 2,589,937 0.94 2,434,541

Coal 200,080 21.6 4,313,725 0.28 1,207,843

WECC baseline

9,812,782 5,207,177

Table 4.7. LCSEA Accumulated GHG Radiative Force Loading Results for 

the WECC Baseline Case per 1,000 GWh

Accumulated 

GHG Radiative Life-Cycle Global Gross Environment Net

Force Loading Inventory Warming Emission Characterization Emission

Inventory Result Potential Loading Factor (ECF) Loading 

Emission (t/a) (t CO2 eq./t) (t CO2 eq.) (t CO2 eq.)

Fossil CO2 478,383 1.0 478,383 1.000 478,383

CH4 906 23.0 20,842 1.000 20,842

CFC-11 0.034 9,300.0 741 1.000 741

WECC baseline

499,966 499,966

4.9. Summary of Results and Discussion 

4.9.1. WECC Baseline 

The impact levels observed for the WECC baseline were largely consistent with 

expectations, given the power mix of the region. Among the results that stand out are 

the following: 

Western Coal Systems — Many of the regional emission concentrations—

ground level ozone, particulates, acidification and the HAPS related emissions — 

resulted in exposures that were quite low on an annual cumulative basis. This 

level of performance for coal systems reflects the location of these units in 

isolated regions far from population centers and the fact that the best coal seams 

were located in these remote regions. 

The WECC’s Hydropower is making a major contribution to containing the 

overall Greenhouse Gas Loading of the US — While most NERC regions rely 

largely on coal and nuclear power generation as the core of their baseload power, 

the WECC has the unique advantage of having significant hydropower capacity. 
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Its 188,383 GWh in hydropower generation represents one of the highest hydro 

production regions in the world. 

From the perspective of the accumulated GHG radiative force loading, this factor 

has a significant effect on the WECC baseline impact profile. Hydropower 

generation in the region represents an annual displacement of 134 million metric 

tons of greenhouse gases (from 307 million metric tons to 447 million metric 

tons) that would otherwise be emitted if the hydropower system was 

decommissioned and replaced with the average mix of remaining WECC power. 

This displacement value represents a difference of 43%. Over the lifetime of the 

current hydropower facilities (40 years), the difference amounts to a displacement 

of 5.9 gigatons. It should be noted that this displaced tonnage is on a scale that is 

relevant to international estimates of the expected increase in retained 

atmospheric greenhouse gases over the same time period (about 170 gigatons).41

If drought conditions in the western US persist, the WECC could become a much 

greater source of greenhouse gas emissions on this scale. 

The following section provides an analysis of results by impact category. 

4.9.1.1. Analysis of Results by Indicator for the WECC Regional Power Pool

Table 4.8 provides a short discussion of the WECC indicator results. 

Table 4.8. Discussion of Net Indicator Results for the WECC per 1000 GWh

Indicator WECC Discussion 

Energy Resource 

Depletion 

5,207,000 GJ This indicator is a direct reflection of the power mix 

that comprises the WECC. For instance, natural gas, 

constituting a relative high percentage of the mix 

(26%), has a high RDF. Note in Table 4.6 that the ratio 

between net and gross energy depletion for the WECC is 

0.53.

Terrestrial Habitat 

Disruption42

1,882 Ha This indicator result is derived from a combination of 

impacts associated with transmission line ROW, coal 

mining, and hydropower.

Aquatic (Lake) 

Habitat Disruption 

NC This indicator could not be calculated within the scope 

of this study.

Aquatic (River) 

Habitat Disruption

NC This indicator could not be calculated within the scope 

of this study.

Riparian/Wetland 

Habitat Disruption

NC This indicator could not be calculated within the scope 

of this study.

Key Species NA There is no regional baseline for this indicator.

Accumulated GHG 

Radiative Force 

Loading

500,000 Eq. t 

CO2

This result was expected, given the mix of power 

sources. 

 41 International Panel on Climate Change

42 Aquatic and riparian/wetland habitat disruption were not broken out in the baseline case.
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Acidification Loading

(Oceanic)

164,891 t 

CO2

A midpoint has been identified demonstrating an 

oceanic acidification exceedance of critical load by 

isopleth. Exceedance maps are available. The discovery 

of this exceedance requires the establishment of this 

impact category and corresponding category indicator. 

The only inventory value required to meet the 

calculation is the total carbon dioxide emission, and 

therefore, no SCF is required. The ECF is represented 

by the fraction of total CO2 that deposits in the ocean 

from the annual gross release of CO2.

Acidification Loading

(Terrestrial / Inland 

Waterways) 

6.5 Eq. t 

SO2

The acidification loading for average power generated 

in the WECC, normalized to 1,000 GWh, is relatively 

low, due to:1) the significant contribution of nuclear 

power and hydropower to the WECC baseline; and 2) 

the low percentage of gross emissions of acidifying 

gases that deposit in areas of exceedance. 

Ecotoxic Chemical 

Loading (Soil/Water)

NC This indicator was identified in the LCSEA framework 

only after the data collection portion of work had been 

conducted, and as such, could not be calculated within 

the current study.

Ground Level Ozone 

Loading 

8.9 t O3 This study’s findings indicate that the ground level 

ozone loading for average power in the WECC, 

normalized to 1,000 GWh, is relatively low compared 

to other NERC regions, due to: 1) the significant 

contribution of nuclear power and hydropower to the 

WECC baseline; and 2) the low average background 

concentrations in the overall WECC. 

Particulate Loading 12.2 Eq. t 

PM10

This study’s findings indicate that the particulate 

loading for average power in the WECC, normalized to 

1,000 GWh, is relatively low compared to other NERC 

regions, due to: 1) the significant contribution of 

nuclear power and hydropower to the WECC baseline; 

and 2) the relatively low population densities and 

potential for exposure across the overall WECC region.

Pulmonary Chemical 

Loading

5 Eq. kg 

benzene

This study’s findings indicate that the pulmonary 

chemical loading for average power generated in the 

WECC, normalized to 1,000 GWh, is relatively low 

compared to other NERC regions, due to: 1) the 

significant contribution of nuclear power and 

hydropower to the WECC baseline; and 2) the 

relatively low population densities and potential for 

exposure across the overall WECC region.

Systemic Chemical 

loading (heavy metals) 

NC This indicator could not be calculated within the scope 

of this study.

Neurotoxic Chemical 

Loading

6 Eq. kg Hg. This study’s findings indicate that the neurotoxic 

chemical loading for average power generated in the 

WECC, normalized to 1,000 GWh, is relatively low 

compared to other NERC regions, due to: 1) the 

significant contribution of nuclear power and 

hydropower to the WECC baseline; and 2) the 

relatively low population densities and potential for 

exposure across the overall WECC region.

-- denotes a zero or negligible result; NC denotes that an indicator result was not calculated.
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Section 5.

STATELINE 300 MW WIND SYSTEM

5.1. Project Description and Background

5.1.1. Project Description

In this project, SCS assessed the environmental performance of the 300 MW Stateline wind 

power generation system, then compared the results to the WECC regional power pool 

baseline.

5.1.2. Project Background 

In the case of wind power, the scope of a life-cycle assessment includes not only the impacts 

from construction, operations/maintenance and end-of-life, but also any indirect impacts that 

may be associated with back-up power sources used to offset the intermittency of wind as a 

fuel source. In this study, SCS modeled the Stateline wind power generation system in two 

different ways – the first scenario assumed that no back-up power was required, while the 

second scenario assumed that back-up power was needed.

• Scenario 1: Stateline Wind Power Generation System, Requiring No Additional 

Back-up Power

Under this scenario, SCS established the impact profile for the Stateline system itself, 

based strictly on the amount of delivered power it produces, normalized to 1,000 GWh. 

The impacts associated with the life-cycle are those resulting from the construction, 

routine operations and maintenance of the wind farm; any habitat disruption and impacts 

on species associated with the installation of the turbines towers and supporting 

infrastructure, and final dismantling of the wind turbines at the end of their useful life. 

• Scenario 2: Stateline Wind Power Generation System Plus Back-Up Power

Under this scenario, SCS established the impact profile, normalized to 1,000 GWh, 

reflecting: 1) the direct impacts associated with the construction, operation, and 

dismantling of the Stateline wind power generation system; and 2) indirect impacts 

associated with back-up sources required to counter the intermittency in the electricity 

produced by the wind turbines. In this case, the system boundaries have been defined to 

take into account the full range of industrial processes involved in delivering electricity 

that meets minimum quality and reliability standards. (See the discussion of “Functional 

Equivalency” in Section 5.1.3 below.)

The WECC power pool system, which serves as the baseline in this project, consists of base 

load units (coal, nuclear, hydroelectric and natural gas), reserve units that handle 

seasonal/daily load demand (produced primarily by coal, dispatches planned over and 

predictable loads), and peak loading units (mostly natural gas). Wind power does not fit 
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neatly into any of these categories, given the potential problems of low capacity factor, and 

unpredictable intermittency. Scenario 2 offered an opportunity to examine more closely how 

the wind farm integrates into the regional power pool system. Certain assumptions were 

made in this regard, as described below. 

5.1.3. Specific Issues Surrounding Functional Equivalency and System Boundaries

Scenario 2 has been included to meet the basic LCA requirement that comparisons between 

systems incorporate an analysis of “functional equivalence.”43 In order to compare the wind 

farm to the baseline, the WECC power pool, functional equivalency between the two had to 

be established. A short discussion of this issue follows.

Generally speaking, functional equivalency means that a product performs the identical (or 

substantially the same) function as another product to which it is compared. In the case of 

electricity, the quality of power delivered to the end customer must fall within a defined 

range of charge parameters to be useful.

Traditional electricity generation technologies that are designed to be dispatched to meet 

demand loads within a power system deliver electricity that maintains the quality of the 

charge within these acceptable ranges. In the case of certain passive renewable technologies, 

however, intermittency in generation affects the quality of the power delivered to users. 

Examples of such technologies are wind farms, run-of-river hydropower plants and 

photovoltaic power generation. Of these, wind farms have the greatest degree of generation 

unpredictability. 

To fulfill the life cycle prerequisite to establish functional equivalency before making 

comparisons, the 300-MW Stateline wind power generation system therefore was analyzed in 

terms of the generation of equivalent power quality, including any back-up power sources 

required to achieve this objective. For the Wind System Plus Back-up Power scenario 

modeled in this project, SCS assumed that for every 850 MW of electricity produced by the 

wind-farm, 150 MW is required from natural gas units. This assumption and its implications 

are discussed more fully in the sections that follow. (Reports published by Oakridge 

National Laboratory indicate that eastern Washington wind power has been integrated 

through the Bonneville Power Administration (BPA), which is largely hydropower.44 

However, SCS lacked the data needed to model the implications from using hydropower as 

back-up power.) 

 43 The term, back-up powering, is related to the more familiar term, co-firing. When coal-fired units introduce a 

percentage of biomass into the overall fuel mix, such mixes are referred to as co-fired coal/biomass systems. The 

relative percentage of co-firing is readily determined by analyzing the input amounts. In much the same way, wind 

power and back-up power sources act together to produce an overall total production of electricity. Such 

combinations work together in much the same way as co-fired coal/biomass systems, except that the energy 

production takes place physically at different locations.

44 Oak Ridge National Laboratory. 
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5.2. Stateline Power Generation System Description

5.2.1. Wind Farm 

The Stateline Wind Energy Center (“Stateline”) is a state-of-the-art 300-MW windfarm 

owned by FPL Energy, Inc., a subsidiary of Florida Power & Light Co. The Stateline facility 

is the largest commercial wind project in the Northwest U.S.45 

Stateline’s 660-kW Vestas wind turbines straddle the Vansycle Ridge on the WashingtonOregon border, near the towns of Touchet, WA and Pendleton, OR. Operations began in 

July 2001, and completion of the windfarm is projected to involve expansions on both sides 

of the border. The turbines are powered by winds averaging 16-18 mph traveling up the 

Columbia Gorge (Table 5.1). This wind is considered sufficient to generate 30-35% of the 

windfarm’s 300-MW capacity year-round. Power is marketed by Pacific Power Marketing 

(PPM) Energy to Bonneville Power 

Administration (BPA) and Seattle City Light.

Stateline is surrounded by agricultural land. In 

addition, the land between the turbines 

continues to be used for agricultural purposes, 

primarily dryland wheat and cattle grazing 

(Figure 5.1).46 The proximity of the site to preexisting transmission lines has been beneficial 

in reducing the need for new cables and 

minimizing transmission line losses. The FPL 

Energy substation is connected to transmission 

owned by PacifiCorp.

According to the Renewable Northwest Project (RNP) website: 

“The Stateline wind project was planned carefully and underwent extensive review to 

minimize its environmental impact. Early biological studies indicated that the site 

receives little use by birds or other vulnerable species. The project uses tubular towers 

and buried cables in order to avoid adding new perching places for birds. Slower-moving 

blades and an upwind design further minimize any potential for avian fatality.

Electronic control systems point each turbine into the wind and adjust the pitch of the 

blades to make the best use of wind at any speed. The turbines can generate power at 

wind speeds of 7 to 56 mph. At higher speeds the turbines automatically shut down — a 

feature that allows them to withstand hurricane-force winds.”

 45 http://www.rnp.org/Projects/stateline.html, website of the Renewable Northwest Project (RNP), a coalition of 

public-interest organizations and energy companies. 46 http://www.ppmenergy.com/cs_stateline.html

Figure 5.1. Stateline Wind Energy Center
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Table 5.1. Stateline Wind Turbine Facts

Source: www.rnp.org/Projects/stateline.htm

Blade Length: 76 feet

Turbine Height: 166 feet

Peak Output per Turbine: 660,000 watts (660 kW)

Manufacturer: Vestas American Wind Technology

Operable Wind Speed: 7 to 58 mph

Vansycle Ridge Avg. Wind Speed: 16 to 18 mph

Number of Turbines (Nov. 2002): 454

Total Project Output: Peak 300 MW 

5.2.2. Functional Unit

The functional unit of the modeled system is an annual generation of 1,000 GWh, the same 

scale of production used to normalize results from other electric power systems included in 

the current study.

5.3. Baseline Case

The averaged impact profile for power generated in the WECC power pool, per 1,000 GWh, 

serves as the baseline impact profile for comparison. A detailed description is provided in 

Section 6 of this report.

5.4. Integrating Wind into the Regional Power Pool System

As discussed above, the key issue surrounding the integration of wind power into a regional 

power pool system is the need for back-up power to correct for wind’s inherent intermittency as 

a power source. The US National Renewable Energy Laboratory (NREL) has suggested that the 

problem of intermittency can be overcome by widely dispersing the wind farms so that the 

cumulative effects of intermittency can be significantly offset by the very localized windforce 

variability. More accurate windforce forecasts would reduce the need to dispatch more peaker 

units to maintain stability. A recent study conducted by the Oak Ridge National Laboratory in 

Tennessee, however, suggests that the intermittency effects within the Bonneville Power 

Administration (BPA) regional system have resulted in a measurable increase in variability to 

delivered bulk power. The author of that study also projected that intermittency will be the 

factor that establishes the upper limits to penetration of wind into a regional power pool 

system.47 While not directly analyzed, it could be assumed that Stateline wind power generation 

system is dispatched through BPA and is contributing to the current increase in variability.

 47 Hirst, Eric, “Integrating Wind Energy with BPA Power System: Preliminary Study,” September 2002. 
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A report commissioned by the California Energy Commission48 describes experiences in Europe 

and Japan that indicate that wind power penetration up to 10 to 20 percent does not pose stability 

problems, provided that sufficient grid connection capacity is provided. 

5.5. Data Sources 

5.5.1. Materials and Energy Used in Wind Farm Construction, Operations, and 

Maintenance

For the inventory modeling SCS used proxy data from the ECLIPSE project initiated by the 

European Union, which has published extensive life-cycle inventory information on 

renewable energy processes.49

The specific ECLIPSE wind power station data used as the proxy for this project is a Vestas 

600 kW station with the following characteristics (Table 5.2). Assumptions related to these 

data are provided in Section 5.6.4 below.

Table 5.2. Vestas V 44 Main Technical Data

Parameter Specification

Power 600 kW

Number of blades 3

Rotor diameter 44m

Swept area 1521 m2

Tower tubular

Height of the tower (standard hub height) estimated 37m (35m)

Variable speed no

Power control pitch

System lifetime 20 years

Full load hours 2500 h/y

Transformer losses 1%

Electrical output over the lifetime 2,97E+7 kWh

The main source of the LCI data in the ECLIPSE report is a literature study: Life-Cycle Value 

Assessment of a Wind Turbine, Pembina Institute, Alberta, Canada, McCulloch M., Raynolds 

M., Laurie M., 2000. The quality of the LCI data is good, since it includes full accounts of 

construction, operation and dismantling. (See the ECLIPSE fact box in Section 5.5.1 below.) 

 48 Julie Blunden, KEMA-XENERGY, June 2004 “Intermittent Wind Generation: Summary Report of Impacts on

Grid System Operations”. Consultant Report, prepared for the California Energy Commission. 

http://www.energy.ca.gov/pier/final_project_reports/CEC-500-2004-091.html 49 Environmental and Ecological Life cycle Inventories for present and future Power Systems in Europe; Synthesis 

Report 2004, http://www.eclipse-eu.org/
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5.5.2. Direct Physical Disruption Associated with the Wind Farm 

As described in Section 5.2.1, Stateline is located in an area that spans the Oregon and 

Washington border and is located predominantly on land that is in use as agricultural land for 

farming and grazing of cattle.

To calculate the habitat disruption associated with the Stateline system, Western put SCS in 

touch with the operators, who in turn provided SCS with the bulk of the data needed to 

calculate the level of habitat disturbance. Data was mostly compiled from reports produced 

for licensing the facility. In addition, SCS conducted an on-site assessment to determine the 

status of the agricultural lands in use and the potential for disturbance to unique or special 

habitats or species, and to review the land used specifically for the wind turbines or the 

associated facilities.

The specific structures and equipment that have an actual footprint and had to be examined 

for potential disturbance to habitat and species were:

• Turbine Towers

• Transmission Cables

• Building Facilities

• Roads

Each turbine is anchored to the ground by bolting a steel tower that holds the turbine to a 

cement pad. Each pad is 16 ft. in diameter and 2.5 ft. deep, using 54 cubic yards of concrete. 

In addition, an area is cleared around each tower pad to facilitate maintenance of the tower 

and associated hardware and cable. The area around each tower is approximately 0.5 acres 

(0.2 hectares). This amounts to a total of around 227 acres (92 hectares) of disturbed land. 

Each tower is connected to the system via an underground cable. The area of the

underground cable adjacent to the towers does not add significant land use, as the area is 

already maintained for tower maintenance.

The wind facility is close to existing transmission lines and therefore does not add 

significantly to habitat disturbance through the lines connecting the wind facility to the 

existing transmission system. A 115-kV line is located about 6 miles from the project 

substation, and another 230 kV line is about 3 miles from the project substation. As far as 

could be determined from the available reports, no significant amount of habitat is disturbed 

to maintain Right of Ways (ROWs) for the lines connecting the wind facility to the nearby 

transmission lines.

Buildings are set on previously used agricultural land. Even assuming total habitat loss 

where buildings are now placed, the amount of land is minimal. Roads provide a similar 

scenario. Most roads used to maintain facilities for the project are pre-existing structures that 

are still in use by the landowner for farm/ranch maintenance. According to the reports 

provided, around 100 acres (40.5 hectares) of additional disturbed habitat can be attributed to 

the overall facilities and roads.
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Neither published reports nor direct on-site examination provided any evidence that aquatic 

habitats of any note were affected by the project. The same is true for icon species. 

Although there are some birds in the area, bird use of the area is minimal and bird loss due to 

the project is almost non-existent. In one year, there were only three reports of birds downed 

in the area of the wind facility. Regardless of whether these bird interactions were directly 

caused by the wind facility, the exceedingly low number of incidents provides no evidence 

that key or icon species are being affected by the project. 

The minimal effect on habitats and species is the result of good pre-planning by the wind 

facility operators. In planning for the project, the operators identified already disturbed lands 

that are still currently under use for agriculture. This minimizes the amount of disturbance 

necessary to put up, operate, and maintain the wind facility as the lands are already set up to 

allow vehicle traffic and native ecosystems are already highly disturbed due to the farming 

and grazing activities on the land. In addition, the lack of native forests on the land precludes 

any disturbance due to the wind tower construction, operation, or maintenance. To avoid 

disturbance to key or icon species, the operators conducted thorough studies of the area to 

determine if any areas with good wind force for energy generation also were lands used by 

select species such as key mammals, reptiles, or amphibians, or by mobile or migratory 

species such as birds or butterflies.50 The studies identified birds as the major concern, 

documenting areas of high bird use and low bird use to ensure that towers could be placed in 

low-use areas. In addition, the operators chose wind tower designs that did not require any 

additional infrastructure such as guide wires, which have been shown to be detrimental to 

flying species.

Lastly, SCS identified one other major concern for this life cycle study of a wind farm. SCS 

examined the potential for the wind farm to significantly disrupt farming activities, such that 

additional lands would have to be used to provide the same agricultural services. If, in fact, 

this were true, this could cause a significant impact. The potential impacts to the agricultural 

lands at Stateline are successfully mitigated by the tower design and placement. The towers 

are higher than towers used in many previous wind facilities, allowing the blades to be longer 

yet stay further from the ground. This creates much less disturbance for farming or ranching. 

Crops are grown within feet of the towers, and the towers are spaced such that the farming 

equipment can easily move between towers. Cattle are also grazed on some of the lands, and 

with the higher towers and improved blade design, there is no chance of directly 

impacting/hitting cattle, and the noise reduction is sufficient that cattle do not seem to be 

bothered as they can be seen grazing directly adjacent to the towers.

5.5.3. Direct Physical Disruption Associated with Back-Up Power (Scenario 2)

SCS used the habitat disruption data developed for Section 8 of this study to address the 

back-up power modeled into Scenario 2. 

 50 Citations to be inserted.
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5.6. Key Assumptions

This section summarizes assumptions specific to this project only. Other assumptions and 

considerations related to the application of the LCSEA model are described in Sections 3 and 4.

5.6.1. Windforce Analysis 

The overall quality of the windforce was not analyzed within the scope of this study. 

One aspect of the analysis of quality of the windforce is an assessment of ramp rates. The 

assumption for the wind power generation ramp rate is that there will be at least one hour 

from full capacity to zero and vice versa (nearly the same as the data in the Xcel study 

referenced below). During this hour, operators will have time to respond to these fluctuations 

in energy production by bringing on or by backing off other generating assets as required. 

5.6.2. Back-Up Units in Scenario 2

SCS has assumed that natural gas units are brought on-line to serve as back-up power 

sources. SCS has further assumed that these are the most efficient natural gas units in the 

system, i.e. combined cycle or single cycle plants. The same gas turbines that run in the 

present system, supported by the redispatching of some hydropower capacity, suffice to 

guarantee that partial losses (or gains) in load can also be covered during the day. During offpeak periods, it is assumed that base load coal units would be powered down to 

accommodate any added production from the wind farm. 

5.6.3. Amount of Back-Up Power Required for Scenario 2

In attempting to project the actual amount of make-up power that will be needed, several 

variables must be considered. Because the analysis required to factor in all of these variables 

was far too complex for the scope of this study, research conducted by Xcel Energy on the 

effects of wind power on their power pool system was used as the surrogate for this study. 

The Xcel Energy Case

The Xcel Energy research was one of six cases included in a report published by the Utility 

Wind Interest Group (UWIG 2003), in which the impact of wind farms on power system 

operating costs were analyzed.51. In the Xcel case, the Xcel Energy-North52 system has a 

combined capacity of 8,000 MW. By calendar year 2000, Xcel Energy had a nameplate wind 

generation capacity of about 280 MW in its northern control area, similar in size to the 

Stateline project. This area includes 75% of the power consumption of Minnesota, plus 

smaller parts of Michigan, Wisconsin, and North and South Dakota. Xcel’s generating 

resources are predominantly thermal, with the total thermal generating capacities exceeding 

 51 UWIG 2003. Wind Power Impacts on Electric-Power-System Operating Costs; Summary and Perspective on 

Work Done to Date, November 2003. http://www.uwig.org/operatingimpacts.html 52 Characterizing the Impacts of Significant Wind Generation Facilities on Bulk Power System Operations 

Planning. Xcel Energy – North Case Study, Final Report, May 2003. http://www.uwig.org/operatingimpacts.html
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7,000 MW. Peaking units fueled by natural gas and oil comprise 20% of this capacity. The 

remaining 80% of Xcel’s thermal capacity is obtained from more economical units fueled by 

coal, nuclear energy, and wood. The wind power penetration is 3.5%. The most important 

load following — and wind fluctuation compensation — assets are the three Sherco coal 

units with 654, 660 and 807 MW capacity. These units have ramp rates of 12, 12, and 15 

MW/minute, as compared to a maximum ramp rate for the 280-MW wind farm of 2–4 

MW/minute. Import and export exchanges also take part in the load following. The main 

import source is Manitoba hydropower. 

The main conclusions of the Xcel Energy study were as follows:

• Cost of wind generation forecast inaccuracy for day-ahead scheduling: 

US$0.39/MWh to $1.44/MWh

• Cost of additional load following reserves: no cost

• Cost of intra-hour load following “energy component”: US $ 0.41/MWh

• Cost of additional regulation reserves: no cost, however the regulating burden did 

increase by approximately 4%.

These costs can be compared with an average power generation cost of about US $40/MWh. 

The Xcel report did not comment on which technologies were used when the wind power 

cost additions were calculated. The cost increases reported (2-5%), however, would indicate 

very low additional load following costs or losses due to inaccurate scheduling information.

Assuming that all of the wind power ancillary cost (US $ 0.85 – 1.83 /MWh) is incurred by 

replacing coal power with gas power, and that the incremental fuel cost for replacement is 

US $20/MWh (in 2002 the fuel cost of coal electricity was about US $10, and about US 

$30/MWh for gas), the coal power replacement by gas power generation then would be 4.3 –

9.2% (0.85/20 = 4.3%; 1.83/20 = 9.2 %) of the total wind generation. Based on this analysis, 

it can be assumed that a 4–9 % additional back-up by natural gas power generation would be 

needed to meet the functional equivalent power generation. Extrapolating these results to the 

WECC showed that approximately 15% additional back-up of natural gas to total power 

produced from the wind farm would be consistent with the Xcel Energy case as long as the 

energy production penetration does not exceed 5% of the total GWh of the WECC. Thus, 

under Scenario 2, the power is assumed to be generated as 900 GWh wind power and 159 

GWh natural gas power per year, which when normalized to the functional unit of 1,000 

GWh, corresponds to 850 GWh wind, 150 MWh natural gas (i.e. 85%/15%).

As the percentage of wind power to total regional system power approaches the 5% level, the 

Xcel Energy study suggests that the percentage of required back-up power will also increase. 

Some projections derived from the Xcel study suggest that as much as 30% natural gas to 

total delivered bulk power from wind power would be required. However, it will be 

impossible to predict the exact amount of additional dispatch until there is greater experience.
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5.6.4. Assumptions Related to Wind Farm Material and Energy Inputs

The data used in calculating ECLIPSE LCI results for the Vestas 600 kW turbine are 

summarized in the breakout box below (“ECLIPSE Wind Turbine Report”). SCS amended 

those results in the following ways.

• The estimated lifetime of all parts of the wind power station was extended from 20 

years to 50 years, while the lifetime for moving parts (nacelle and rotor blades) was 

left at 20 years.53 The lifetime extension was based on arguments made, for example, 

in the Swiss ETH study (Frischknecht, 1996).54 The lifetime assumption did not 

affect the per-kWh operating environmental burdens, but did affect the lifetime 

allocation of both construction and end-of-life burdens.55

• The operating full-load hours were changed from 2,500 to 3,000 hours per annum, 

according to the capacity utilization given (30 to 35%) for Stateline. The assumed 

capacity factor was 34.2 %.

• The functional unit was changed from 1 kWh to the 1,000 GWh value used for all of 

the electric power systems included in this study (which is on the same order of 

magnitude as the expected annual output of the full-size 300-MW Stateline wind farm 

operating at maximum capacity, 900 GWh. 

• No attempt was made to scale the data up from 600 to 660 kW units. 

• Because the original data used by ECLIPSE are somewhat out-of-date, referring to 

1995 to 1998 state of technology, the results must be viewed as “worst case.” With 

newer technology, the overall burdens may reduce as much as 20 to 30%. Inclusion of 

an appropriate recycling rate for steel and copper used in construction would also 

lower some inventory results.

• In calculating the LCIA results, SCS assumed that the wind turbines were 

manufactured in heavily industrialized manufacturing regions, based on its research 

of such activities. This assumption is reflected particularly in the air emission loading 

calculations, in that emissions were considered more likely to exceed thresholds. 

 53 From a sensitivity analysis standpoint, if the lifetime of the wind power system was assumed to be 30 years 

instead of 50, the LCI and LCSEA indicator values would increase by a factor of about 1.5.

54 Frischknecht, R. et al. 1996: Life cycle inventory of energy systems. Basic methods and data for environmental 

comparison of energy systems and for the inclusion of energy systems in an environmental assessment of 

Switzerland. Swiss Energy Economy Administration (Bundesamt fuer Energiewirtschaft BEW). The Foundation for 

Projects and Research of the Electricity Industry (Projekt- und Studienfonds der Elektrizitätswirtschaft PSEL). 3rd 

Edition, July 1996.

55 As the ECLIPSE results were only available for the whole system, a common lifetime was assumed for all parts. 

However, since the moving parts (and the associated manufacturing emissions and energy consumption) represent 

only a small fraction of the total used materials (about 18%), the error in the results from the use of a prolonged 

lifetime estimate for the moving parts was small. Additionally, since the ECLIPSE model assumes that 15% of the 

nacelle and rotor blade materials is replaced by new materials during their lifetime, the prolonged life estimate could 

be accurate given efficient maintenance, 
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ECLIPSE Wind Turbine Report (adapted from p. 51 of report)

4.1.2 Data source and quality

The data for the material balance is taken from [6]: Life-Cycle Value Assessment of a Wind Turbine, Pembina 

Institute, Alberta, Canada, McCulloch M., Raynolds M., Laurie M., 2000. It is not clear if the data include or not the 

losses of material during the fabrication step. Strong hypothesis had also to be taken for the operation of the plant 

and the end-of-life. Data sources:

Materials consumed for the elements of the wind turbine (nacelle, tower, rotor blades):

• The global mass of the elements of the wind turbine (mass of nacelle, rotor blades, tower) are taken from 

[McCulloch et. al. 2000].56

• The upstream processes of current materials like steel, aluminum, or copper were taken from the Eclipse database, 

and are representative of Europe.

Process of the main elements of the wind turbines:

• The process energy and water for the different elements of the wind turbine (nacelle, tower, blades) is taken from 

Vestas Environmental statement, such as process emissions and waste. 

• The upstream processes of current materials like steel, aluminum, or copper was taken from the Eclipse database. 

• The upstream process of glass fiber is taken from Vattenfall (composition based on US manufacturer data, energy 

based on an estimation from Vattenfall)

Electricity mix: 

• The electricity mix is taken from the Eclipse database.

Upstream process of natural gas: 

• The upstream process of natural gas is taken from the Eclipse database.

On-site energy:

• The energy necessary for the erection of the wind turbine (combustion of diesel) is assumed to be represented by a 

building machine (EDF data derived from CIT OEkologik). The quantity on the necessary energy is derived from 

[9]: Beitrag zum kumulierten Energieaufwand ausgewählter Windenergiekonverter“, Pick & Wagner, and supposed 

to be dependant on the height of the tower and on the weight to lift.

Transport processes: 

• Transport, by lorry or cargo ship is taken from the Eclipse database.

Operating data: 

• Operation includes the replacement of some of the elements (i.e. material & energy for fabrication process & 

transport, source for proportion of material replacement: KEMA & EDF expertise), the necessary lubricant.

Transports (source: Techwise [10]): 

• The transport for routine visits on the farm (by car, based on a determined distance and number of visits / year).

Recycling processes: 

• Only transport is taken into account.

Waste treatment: 

• An incineration module and a landfill module are included, based on ETHZ96: “Abfaelle in SAVE” & “Abfaelle 

in Inertstoffdeponie”.

 56 Life-Cycle Value Assessment of a Wind Turbine, Pembina Institute, Alberta, Canada, McCulloch M., Raynolds 

M., Laurie M., 2000.
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5.6.5. Habitat Disruption Assumptions 

No assumptions were needed to evaluate land disturbance for the Stateline windfarm. All of 

the information used was made available either through documents or the SCS on-site visit. 

Direct measures were made of tower size and associated disturbances from building, 

operating, and maintaining the project. Since Stateline was constructed on highly modified 

agricultural lands, and since these lands remain in comparable agricultural use, a minimum 

ECF of 0.1 was assigned to the calculation of habitat disruption (Table 5.3). This ECF 

reflects SCS’s estimate that continuous farming and ranching on the land has resulted in a 

90% reduction in biodiversity from the land’s original state. The disturbance attributable to 

Stateline is therefore accounted for as 10% of the total disturbance of approximately 326 

acres (132.4 ha) — i.e., 32.6 acres (13.2 ha) — of equivalent original habitat for the 300-MW 

facility. When normalized to 1,000 GWh, this result becomes 14.7 hectares (36.3 acres). 

Table 5.3. Estimated Habitat Disruption for the 300 MW Wind Power Plant 900 GWh/a System. 

Terrestrial Land

Use (ha)

Pre-project Status Post-project Status ECF Hectares 

Disrupted

 a. Turbines

 1. General Habitat 92 Highly modified ag lands Highly modified ag lands 0.1 9.2

 2. Rare/Threatened Habitat 0

 3. Critical Habitat 0

 4. Wetlands Habitat 0

 5. Riparian Habitat 0

 b. Buildings and Roads

 1. General Habitat 40.5 Highly modified ag lands Highly modified ag lands 0.1 4

 2. Rare/Threatened Habitat 0

 3. Critical Habitat 0

 4. Wetlands Habitat 0

 5. Riparian Habitat 0

 c. Transmission Lines

 1. General Habitat NA

 2. Rare/Threatened Habitat 0

 3. Critical Habitat 0

 4. Wetlands Habitat 0

 5. Riparian Habitat 0

Aquatic

 a. Turbines

 1. Lacustrine 0

 2. Riverine 0

 b. Buildings and Roads

 1. Lacustrine 0

 2. Riverine 0

 c. Transmission Lines

 1. Lacustrine 0

 2. Riverine 0

Total Terrestrial 13.2

Total Riparian 0.0

Total Aquatic 0.0
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Table 5.4 provides the estimated hectares of habitat disturbance per 1,000 GWh, including 

estimate assumed for this study. Note that the habitat disruption associated with the Stateline 

power generation system (Scenario 1), is far lower than the disruption estimates for 

comparable wind power systems built on previously undisturbed lands. 

Table 5.4. Average Estimated Acres of Habitat Disturbed for

Various Electric Power Technologies (per 1000 GWh)57

Energy Type Avg. Estimated Hectares Disturbed per 1,000 GWh 

Coal (1998) 1882.6

Nuclear (1998) 37.25 

Natural Gas (1998) 81

Oil (1998) 81 58

Hydro (1998) 445

Wind (2001) 287.559

5.6.6. Natural Gas Back-Up Power Assumptions

The back-up power production system used for Scenario 2 is based on the natural gas single 

cycle (NGSC) system described in Section 8 of this report. 

5.7. Summary LCI Results

The LCI results for the 300 MW Stateline wind power generation system are shown in Table 5.5. 

LCI results are summarized for: 1) the 300 MW wind system with no additional back-up power 

(Scenario 1); 2) the back-up powered electric power system based on an assumption of 85 % 

wind power and 15 % natural gas power (Scenario 2); and 3) the WECC regional power pool. 

The energy resources, energy inputs, and emissions shown in the table for the wind-farm reflect 

the construction, transport, installation and maintenance of turbines and other capital equipment, 

as well as eventual dismantling after 50 years.

 57 Report for Exelon: Life-Cycle Stressor Effects Assessment of the PJM Regional Power Pool and Selected Exelon 

Assets Within the PJM, Scientific Certification Systems, December 2001. 58 Habitat disruption acreage attributed to natural gas was used as a surrogate value, tested by sensitivity analysis. 

59 This disruption value for wind power represents an upper range value, based on SCS research to date, reflecting 

the siting of wind farms in areas leading to disturbance of native habitats.
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Table 5.5. Main Life-Cycle Inventory Results for the 300 MW Wind Power Plant 900 GWh/a System 

(Scenario 1), the Back-Up Powered 1,059 GWh/a System (Scenario 2), and the WECC Power Pool (Baseline), 

based on KCL-ECO LCI Modeling. Data are normalized to a production of 1,000 GWh. 

Scenario 1 Scenario 2 WECC Power 

Pool

Baseline

Inventory Unit

Outputs

Emissions, air

Arsenic kg -- -- 16

Benzene kg -- -- 6

Cadmium kg -- -- 1

CFC-114 kg 34

CH4 kg 2,400 3,432,890 906,170

CO2, fossil kg 2,713,000 100,584,850 478,383,000

PM10, TSP, dust kg 2,980 9,140 197,030

HC, VOC kg 613 520 29,910

HCl kg -- -- 26,959

HF kg -- -- 683

Mercury kg -- -- 7

Manganese kg -- -- 14

NOx kg 5,630 198,037 956,413

Lead kg -- -- 10

Rad. act. Rn-222 GBq -- -- 2,910

Rad. act. noble gases GBq -- -- 250

SO2 kg 8,580 8,460 731,940

Emissions, water -- -- --

Energy

electric power MWh 1,000,000 1,000,000 1,000,000

Inputs

Resources

Coal kg 633,100 461,200 200,080,000

Lignite kg 121,900 88,100

Crude oil kg 207,067 150,900 3,631,900

Natural gas kg 172,083 26,325,000 48,502,000

Uranium in ore kg U -- -- 3,048

Limestone/dolomite kg -- -- 3,183,900

Hazardous waste

(--) denotes result of negligible or zero 

5.8. LCSEA Results 

From the LCI data, the LCSEA indicator results have been calculated, using the appropriate 

stressor and environmental characterization factors, as discussed in Sections 3 and 4. In Table 

5.6, LCSEA indicators are summarized for: 1) the 300 MW wind power generation system with 

no additional backup power (Scenario 1); 2) the back-up powered electric power system based 

on an assumption of 85 % wind power and 15 % natural gas power (Scenario 2); and 3) the 

WECC regional power pool. Tables 5.7 to 5.12 present in more detail the calculation of key 

indicators. 
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Table 5.6. Life-Cycle Impact Indicator Results for Scenario 1 (the 300-MW, 900 GWh/a Wind System), 

Scenario 2 (the Wind + Back-Up Power System, 1059 GWh/a), and the WECC Regional Power Pool, 

Normalized to 1,000 GWh.60

Impact Profile:

Stateline 

System 

(Scenario 1) —

Impact Profile:

Stateline System 

(Scenario 2)

85% wind /15% 

natural gas

WECC Power 

Pool Baseline 

Impact Profile

Key Indicator Unit

Energy Resources Depleted Eq. GJ of oil 21,000 1,786,000 5,207,000

Water Resources Depleted Acre-feet -- -- NC

Terrestrial Habitat Disruption Eq. Ha disturbed 14.7 14.7 1,880

Riparian Habitat Disruption Eq. Ha disturbed -- NC Not broken 

out

Aquatic Habitat Disruption Eq. Ha disturbed -- NC Not broken 

out

Key Species % loss of key species -- NC NA

Greenhouse Gas Loading Eq. t CO2 2,770 112,000 500,000

Acidification Loading Eq. t SO2 1.6 5.9 6.5

Ground Level Ozone Loading t O3 0.6 3.0 8.9

Particulates Eq. t PM10 5.4 4.3 12.2

Neurotoxic Chem. Loading Eq. t Hg. -- -- 0.0057

Pulmonary (non-carc) Chem. Loading Eq. t HF -- -- 0.5423

Pulmonary (Carc.) Chem. Loading Eq. t benzene -- -- 0.0041

Systemic Chem. Loading Eq. t TCDD -- -- NC

Radioactive Waste Loading Eq. TBq Pu-239 -- -- NC

Coal Ash Waste Loading -- -- NC

(--) denotes negligible or zero result. NA is not available, NC is not calculated. 

Results above 10,000 are rounded to the nearest 1,000.

 60 It should be noted that the indicators have been slightly modified to conform to the ASTM Draft Standard 

E06.71.10 since this set of calculations was completed. Specifically, a new oceanic acidification indicator has been 

added, the pulmonary loading indicators have been collapsed back to one indicator, and the coal ash waste loading is 

now addressed under the Ecotoxic Chemical Loading (Soil/Water) indicator, as shown in Sections 2 and 6. 

However, these changes will not have a material effect on the impact profile of Stateline to the baseline. 

Modifications will be made to this Section before the report is released for peer review.
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Table 5.7. Project #5: LCSEA Energy Resource Depletion Results for

Stateline Electric Power System (Scenarios 1 and 2), Per 1,000 GWh Production

Energy Resource Energy Stressor

Equivalent

Energy

Resource Depletion FactorEquivalent

Resource

Depletion Resource Characterization Resource (RDF25): Depletion

Inventory Consumed Factor (SCF) Consumed Rate of dep /

Resource (t) (GJ/t) (GJ) Rate of oil dep (GJ oil eq.)

Uranium in ore 0.00002 900,000 16 0.510 8

Crude oil 207 45.6 9,442 1.000 9,442

Natural gas 172 53.4 9,189 0.940 8,638

Coal 633 15.5 9,813 0.280 2,748

Lignite 121 9.5 1,148 0.280 322

Electric Power 

System:

100% Wind —

Scenario 1

29,608 21,157

Uranium in ore 0.000015 900,000.0 13 0.510 7

Crude oil 176 45.6 8,026 1.000 8,026

Natural gas 35,361 53.4 1,888,287 0.940 1,774,989

Coal 538 15.5 8,341 0.280 2,335

Lignite 103 9.5 976 0.280 273

Electric Power 

System:

85% Wind / 15% 

Natural Gas —

Scenario 2

1,905,643 1,785,631

Table 5.8. Project #5: LCSEA Greenhouse Gas Loading Results for 

Stateline Electric Power System (Scenarios 1 and 2), Per 1,000 GWh Production

Greenhouse Life-Cycle Global Gross Environment Net

Gases Loading Inventory Warming Emission Characterization Emission

Inventory Result Potential Loading Factor (ECF) Loading 

Emission (t/a) (t CO2 eq./t) (t CO2 eq.) (t CO2 eq.)

Fossil CO2 2,713 1.0 2,713 1.000 2,713

CH4 2 23.0 55 1.000 55

Electric Power 

System:

100% Wind—

Scenario 1 2,768 2,768

Fossil CO2 100,585 1.0 100,585 1.00 100,585

CH4 517 23.0 11,890 1.00 11,890

Electric Power 

System:

85% Wind / 15% 

Natural Gas —

Scenario 2 112,475 112,475

Table 5.9. Project #5: LCSEA Acidification Loading Results for 

Stateline Electric Power System (Scenarios 1 and 2), Per 1,000 GWh Production

Acidification Life-Cycle Stressor Gross Environment Net

Loading Inventory Characterization Emission Characterization Emission

Inventory Result Factor Loading Factor (ECF) Loading 

Emission (t) (t SO2 eq./t) (t SO2 eq.) (t SO2 eq.)

SO2 8.6 1.000 8.6 0.150 1.3

NOx 5.6 0.700 3.9 0.075 0.3

Electric Power 

System:

100% Wind —

Scenario 1 12.5 1.6

SO2 16 1.000 16 See Table 5.11 1.63

NOx 198 0.700 139 See Table 5.11 4.31

Electric Power 

System:

85% Wind / 15% 

Natural Gas —

Scenario 2 155 5.94
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Table 5.10. Project #5: LCSEA Ground Level Ozone Loading Results for 

Stateline Electric Power System (Scenarios 1 and 2), Per 1,000 GWh Production

Ground Level Life-Cycle Stressor Gross Environment Net

Ozone Loading Inventory Characterization Emission Characterization Emission

Inventory Result Factor (SCF) Loading Factor (ECF) Loading 

Emission (t) (t O3/t) (t O3) (t O3)

NOx 2.4 1.000 2.4 0.220 0.5

CH4 1.0 0.010 0.0 0.220 0.0

VOC, HC 0.3 0.410 0.1 0.220 0.0

Electric Power 

System:

100% Wind —

Scenario 1

2.5 0.6

NOx 99 1.000 99 See Table 5.11 2.94

CH4 258 0.010 3 See Table 5.11 0.07

VOC, HC 0 0.420 0 See Table 5.11 0.02

Electric Power 

System:

85% Wind / 15% 

Natural Gas —

Scenario 2 102 3.03

Table 5.11. Project #5: LCSEA Particulate Loading Results for 

Stateline Electric Power System (Scenarios 1 and 2), Per 1,000 GWh Production

Particulate Life-Cycle Stressor Gross Environment Net

Matter Loading Inventory Characterization Emission Characterization Emission

Inventory Result Factor (SCF) Loading Factor (ECF) Loading 

Emission (t) (t PM10 eq/t) (t PM10 eq) (t PM10 eq)

TSP 3.0 1.00 3.0 0.250 0.7

SO2 8.6 1.50 12.9 0.250 3.2

NOx 5.6 1.00 5.6 0.250 1.4

Electric Power 

System:

100% Wind —

Scenario 1 21.5 5.4

TSP 11.7 1.00 11.7 See Table 5.11 0.7

SO2 16.3 1.50 24.4 See Table 5.11 2.8

NOx 96.6 1.00 96.6 See Table 5.11 0.8

Electric Power 

System:

85% Wind / 15% 

Natural Gas –

Scenario 2 132.7 4.3

For the combined wind power - gas system (Scenario 2), the LCSEA spreadsheet calculation 

from LCI data must be presented as a breakdown in two different operations, as below in Table 

5.12, because the manufacturing of wind power equipment takes place in an industrial region 

where high population density and acidification exceedances give rise to high ECF values. Such 

calculations are not needed for the indicators, energy resource depletion and greenhouse gas 

loading, since the environmental characterization is global. For the acidification, ground level 

ozone loading and particulates loading indicators, the ECF values are completely different for the 

industrial region where equipment is manufactured, and for the region near the windfarm, where 

the natural gas electricity production is assumed to take place. In the gas power plant case, the 

loading from manufacturing is negligible in comparison to operation emissions from power plant 

flue gas.
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Table 5.12. Break-out of Air Emission Loading ECFs Associated with

Regional Air Emission Indicators for Scenario 2, per 1000 GWh

Inventory 

Emission

Life-Cycle

Inventory 

Result (t)

Stressor 

Characterization 

Factor (SCF)

Gross 

Emission 

Loading 

(t SO2 eq.)

Environment 

Characterization 

Factor (ECF)

Net 

Emission 

Loading

(t SO2 eq.)

Acidification Loading

SO2 7 1.000 7 0.150 1.09

NOx 5 0.700 3 0.075 0.25

150 MW wind farm 

production system

850 GWh 1.34

SO2 9 1.000 9 0.060 0.54

NOx 193 0.700 135 0.030 4.06

Gas power

production system

150 GWh 4.60

Ground Level Ozone Loading

(t O3) (t O3)

NOx 2 1.000 2 0.22 0.53

CH4 1 0.010 0 0.22 0.00

VOC, HC 0 0.420 0 0.22 0.02

150 MW wind farm 

production system

850 GWh

3 0.55

NOx 97 1.000 97 0.025 2.42

CH4 257 0.010 3 0.025 0.06

VOC, HC 0 0.420 0 0.025 0.00

Gas power

production system

150 GWh

99 2.48

Particulate Loading

(t PM10 eq) (t PM10 eq)

150 MW wind farm TSP 2.5 1.00 2.5 0.250 0.6

production system SO2 7.3 1.50 10.9 0.250 2.7

850 GWh NOx 0.0 1.00 0.0 0.250 0.0

13.5 3.4

Gas power TSP 9.1 1.00 9.1 0.008 0.1

production system SO2 9.0 1.50 13.5 0.008 0.1

150 GWh NOx 96.6 1.00 96.6 0.008 0.8

119.2 1.0

5.9. Discussion of Results

5.9.1. Proper Scoping

The results of this study reinforce the importance of proper scoping in establishing the 

environmental impact profile of wind power systems. In order to determine the full impact, 

an analysis should be conducted to assess the possible need for back-up power, including 

assessment of transmission grid stability and transmission capacities.
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5.9.2. Wind System with No Added Back-up Power (Scenario 1)

Consistent with expectations for western wind power systems, the Stateline wind power 

generation system has one of the smallest impact profiles of any power system measured to 

date by SCS (Figure 5.2).61 This outcome reflects the fact that the energy resource depletion 

and emission loadings were derived only from the manufacturing and maintenance of the 

turbine equipment and associated infrastructure, and not from the energy generation itself. 

Figure 5.2. Environmental Impact Profile of Stateline Wind System, Scenario 1.

The fact that the land used for the project was already in a highly disturbed state – i.e., 

significantly altered from its original and pristine condition – was reflected in the application 

of an ECF of 0.1 to account for the previous disturbance. Had the wind farm been placed on 

pristine, unaltered land, the habitat disruption would have been considerably higher (326 

acres or 132.4 hectares).

 61 SCS has conducted life-cycle research on a variety of electric power systems — including coal, natural gas, 

nuclear, hydropower, bunker oil, and wind technologies – as well as several regional power pools. 
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5.9.3. 85% Wind Power / 15% Natural Gas Back-up Power (Scenario 2)

As expected, the addition of natural gas in a back-up powered system increases results in the 

following impact indicators: energy resource depletion, greenhouse gas loading, acidification 

loading, ground level ozone loading, and PM loading. 

• Energy Resource Depletion — While natural gas-generated power constituted 

only 15% of the system, the energy resource depletion rose from Scenario 1 by 

84-fold (Table 5.7). This increase demonstrates how dramatically the impact 

profile for wind power can be changed when augmented even to a small degree by 

traditional power technologies.

• Greenhouse Gas Loading — Large differences were also noted between 

Scenario 1 and Scenario 2 in terms of the greenhouse gas loading. In this case, 

the increase was 41-fold (Table 5.8).

• Regional Air Emission Loadings (Acidification, Ground Level Ozone, PM) —

In the case of the regional air emission loadings, the net emission loadings were 

substantially lower than the gross emission loadings, reflecting the low population 

densities of the region outside of Portland (ground level ozone, particulates). 

• Habitat Disruption — There was no significant increase in habitat disruption 

from Scenario 1 to Scenario 2, reflecting the inherently small physical footprint of 

natural gas units. 

5.10. Differences in Scenarios’ Performance

The environmental performance of Scenarios 1 and 2 are compared to the WECC power pool in 

Table 10.13. As can be seen in the table, adding wind power under Scenario 1 to the power pool 

is essentially an impact free option for increasing the energy supply, as long as wind penetration 

into the power pool remains relatively low. Under Scenario 2, the anticipated environmental 

benefits would be reduced in three areas — energy resource depletion, greenhouse gas loading 

and acidification loading. 

As the percentage of wind penetration increases in the WECC, Scenario 2 will become more 

likely, due to the limitations in availability of BPA hydropower for back-up dispatch.
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Table 5.13. Scenario 1 (wind power only) compared to the WECC regional power pool

Indicator Unit

Stateline Impact 

Profile

Wind power 

only

Stateline Impact 

Profile

(85 % wind and 

15% gas)

WECC Regional 

Power Pool

Energy Resources Depleted Eq. GJ of oil 21,000 1,786,000 5,207,000

Water Resources Depleted Acre-feet -- -- NC

Terrestrial Habitat Disruption*

Eq. ha 

disturbed 14.7 14.7 1,882

Aquatic Habitat Disruption

Eq. ha 

disturbed -- NC Not broken out

Riparian/Wetland Habitat 

Disruption

Eq. Ha 

disturbed --

NC

Not broken out

Key Species % loss -- NC NA

Greenhouse Gases Eq. t CO2 2,770 112,000 500,000

Stratospheric Ozone Depletion Eq. t CFC-11 -- -- 0.027

Acidification Loading Eq. t SO2 1.6 5.9 6.5

Ground Level Ozone Loading t O3 0.6 3 8.9

Particulates Loading Eq. t PM10 5.4 4.3 12.2

Neurotoxic Chem. Loading Eq. t Hg. -- -- 0.0057

Pulmonary (non-carc) Chem. 

Loading Eq. t HF -- -- 0.5423

Pulmonary (Carc.) Chem. 

Loading Eq. t benzene -- -- 0.0041

Systemic Chem. Loading Eq. t TCDD -- -- NC

Radioactive Wastes

Eq. TBq Pu239 -- -- NC

Coal Ash Waste Eq. t Hg. -- -- NC

(--) denotes negligible or zero result. NA is not available, NC is not calculated.

Results above 10,000 are rounded to the nearest 1,000.
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Section 6.

GLEN CANYON HYDROPOWER GENERATION SYSTEM

6.1. Project Description and Background 

6.1.1. Project Description

In this project, SCS established an impact profile for the Glen Canyon Dam hydroelectric 

power generation system, and compared this impact profile to that of the WECC regional 

power pool baseline. Additionally, SCS examined the degree to which changes made in 

hydropower dispatch in order to meet modified low fluctuating flow requirements of the 

1996 Record of Decision (ROD) may have resulted in impact trade-offs, due to the flow 

modifications and the use of alternative load-following power sources. 

6.1.2. Project Background

Glen Canyon is one of 58 dams constructed by the US 

Bureau of Reclamation, delivering electricity to customers 

throughout the west. Glen Canyon is among the largest 

hydroelectric facilities in the region, alongside Hoover 

Dam on the lower Colorado (Arizona), Grand Coulee Dam 

on the Columbia River (Washington), Shasta Dam on the 

Sacramento River (California) and Yellowtail Dam on the 

Bighorn River (Montana).62 This multi-purpose unit was 

built not only to generate electricity, but also to store 

water for municipal and industrial water uses, land 

reclamation, flood control, and public outdoor recreation. 

The Glen Canyon facility – the dam, power plant and Lake 

Powell reservoir – is the centerpiece of the Colorado River 

Storage Project (CRSP), which includes three additional 

storage units and 11 participating projects.63

Glen Canyon has been the subject of intensive environmental interest and scrutiny since its 

inception in the late 1950s. The site was originally selected as a compromise to prevent 

construction of an alternative dam that would have resulted in the flooding of the Dinosaur 

National Monument area. Since that time, federal, state and tribal agencies, recreational 

 62 US Bureau of Reclamation, Dept. of the Interior, Power Resources Office, Reclamation: Managing Water in the 

West — Hydroelectric Power. July 2005. 63 43 U.S.C. §§ 620-620o, April 11, 1956, as amended 1962, 1964, 1968 and 1980. The Colorado River Storage 

Project Act “provides for the comprehensive development of the water resources of the Upper Colorado River Basin 

to: regulate the flow of the Colorado River; store water for beneficial consumptive use to make it possible for states 

of the Upper Basin to use the apportionments made to and among them in the Colorado River Compact and the 

Upper Colorado River Basin Compact, respectively; provide for the reclamation of arid and semiarid land, the 

control of floods, and the generation of hydroelectric power.”

Figure 6.1. Glen Canyon Dam

Photo: National Park Service

Source: Glen Canyon Assn.
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fishermen and boaters, Native American groups and environmental organizations have 

expressed concerns about the project’s impacts on habitats, wildlife and cultural resources. 

These concerns have centered primarily around two consequences of dam construction and 

water regulation: changes in seasonal and daily river flow fluctuations, and marked changes 

in water temperatures downstream.64

In 1980, a cost-benefit study being conducted to investigate the potential to add new 

generators to produce more power was halted in the face of unanswered questions about 

impacts on key habitats and species, both upstream as a result of inundation, and downstream 

as a result of changes in water flows.65 In 1982, the Bureau of Reclamation initiated the Glen 

Canyon Environmental Studies (GCES) program, a program now encompassed under the 

mandate of the Grand Canyon Monitoring and Research Center (GCMRC).66 Evidence 

gathered by GCES, together with plans to rewind the generators, led to the decision to 

undertake the preparation of a formal Environmental Impact Statement in November 1989, a 

process that took six years to complete. During this period, in 1991, an interim regimen of 

modified flows was instituted, while plans were laid for further study.67 According to the 

Bureau of Reclamation, the publication of the Final Environmental Impact Statement (FEIS) 

in 1995 received “broad and intense interest” from a wide cross-section of public and private 

stakeholders. The FEIS called attention to a range of impacts, both positive and negative, 

while raising a number of questions regarding the causes and extent of these impacts.68 (See 

further discussion, Section 6.6.)

Based on the findings of the FEIS, a Record of Decision (ROD) was signed by the Secretary 

of the Interior in October 1996, requiring the dam to be operated within more stringent 

environmental parameters, including: minimum and maximum flows, limitations in 

fluctuations, new triggering mechanisms for conducting beach/habitat-building flows, and 

the establishment of the Glen Canyon Dam Adaptive Management Program (AMP) to 

continue monitoring environmental evidence and adapting operational requirements 

accordingly. As described in the Secretary of the Interior’s Report to Congress in 2001, “the 

National Academy of Sciences described the AMP as “a science policy experiment of local, 

regional, national, and international importance.”69

Among the most significant changes resulting from the ROD has been the change in dispatch 

of Glen Canyon generated power. Whereas Glen Canyon was historically used for load 

following power generation, compliance with the new modified flow regime has altered its 

power production profile. As a result, other power plants in the region have had to be tapped 

to fill the gap during peak periods. 

 64 Bureau of Reclamation, U.S. Dept. of the Interior, Operation of Glen Canyon Dam: Colorado River Storage 

Project, Arizona. Final Environmental Impact Statement (FEIS), March 1995. 65 Ibid.

66 National Park Service, U.S. Department of the Interior, 2005. Website: http://www.nps.gov/glca/damindx.htm 67 Dates confirmed in verbal correspondence to SCS by representatives of Western. 68 Bureau of Reclamation, U.S. Dept. of the Interior, Glen Canyon Adaptive Management Program. Website: 

http://www.usbr.gov/uc/rm/amp/background.html#background 69 Secretary of the Interior, Report to Congress: Operations of Glen Canyon Dam Pursuant to the Grand Canyon 

Protection Act of 1992, Water Years 1999 – 2001, May 2002.
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6.2. Power Generation System Description

6.2.1. System Boundaries, Scoping and Specific Unit Processes 

The Glen Canyon hydropower generation system includes the power plant and dam complex, 

upstream processes related to major construction materials (concrete, steel, copper), and 

power transmission. Along with Aspinall and Flaming Gorge hydropower stations, Glen 

Canyon generated sufficient power before the ROD to satisfy existing contractual loadfollowing requirements for every day except Sunday (Figure 6.2). After the ROD, the 

resulting shortfall of dispatchable power (about 25%) led to the use of alternative loadfollowing power sources. Given the type of load demand required for this time of day, makeup power comes from a combined cycle natural gas (NGCC) source.

Life-cycle scoping requires assessments on complete systems. The Glen Canyon hydropower 

station is part of the larger Colorado River hydropower system comprising a network of 

hydropower plants sited up- and downstream, including the Hoover Dam. Glen Canyon 

should be considered part of this larger system because it has distinct environmental links in 

terms of cause and effects to the operations of other hydropower stations along the river. For 

instance, flow management decisions at Glen Canyon Dam have significant implications for 

Hoover Dam, Lake Mead, and river flow all the way to the Sea of Cortez in Baja. Although it 

was beyond the scope of this study to consider the complete hydropower system operating 

along the full length of the river, SCS would recommend that the study be extended to 

encompass such facilities in order to develop a more comprehensive understanding of the 

degree to which the Glen Canyon hydropower station is responsible for indirect impacts 

along the Colorado River.
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Figure 6.2. CRSP Generation Before and After Glen Canyon ROD and Flaming Gorge BO

Before Glen Canyon 

ROD

After Glen Canyon ROD
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5.2.2. Plant Location

The Glen Canyon facility is located on the upper Colorado River close to the Utah border, 

two miles northwest of Page, Arizona, and 15 miles upriver from Lee’s Ferry (Figure 6.3). 

The massive Lake Powell reservoir created behind the dam is primarily within Utah state 

borders, within an area now designated as the Glen Canyon National Recreation Area.

Lake Powell extends up to 186 miles upstream. The total drainage area of the Upper 

Colorado River basin is approximately 108,355 sq. miles.70 Major upstream tributaries 

include the Upper Colorado, Green, Gunnison, and San Juan Rivers. 

Below the dam, the river flows for fifteen miles through lower Glen Canyon in the Glen 

Canyon National Recreation Area, then flows 278 miles through Grand Canyon National 

Park. The river borders the Navajo Indian Reservation to the east (Glen and Marble 

Canyons), while the Hopi Indian Reservation is farther to the east. In Grand Canyon National 

Park, the river flows past the Havasupai Indian and Hualapai Indian Reservations. 

Downstream tributaries include the Little Colorado and Paria Rivers.

 70 Bureau of Reclamation, U.S. Dept. of the Interior. Website. http://www.usbr.gov/dataweb/dams/az10307.htm

GLEN CANYON DAM

Figure 6.3. Glen Canyon Dam Location
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The canyon walls of the Glen Canyon dam site and reservoir are largely formed from 

medium to fine-grained Navajo sandstone, ubiquitous in the area. Red to buff in color, the 

sandstone is moderately porous and highly absorptive.71

6.2.3. Construction

The construction of Glen Canyon Dam was authorized under the Colorado River Storage 

Project Act of 1956 (Public Law 84-485):

“ . . . for the purposes, among others, of regulating the flow of the Colorado River, 

storing water for beneficial consumptive use, making it possible for the States of the 

Upper Basin to utilize, consistently with the provisions of the Colorado River 

Compact, the apportionments made to and among them in the Colorado River 

Compact and the Upper Colorado River Basin Compact, respectively, providing for 

the reclamation of arid and semiarid land, for the control of floods, and for the 

generation of hydroelectric power, as an incident of the foregoing purposes . . . . In 

1968 Congress enacted the Colorado River Basin Project Act (43 U.S.C. 1501 et. 

seq.).” 72

Construction was begun in 1957, and completed in 1963, with power generation 

commencing in September 1964.73 Construction of the 710-foot concrete thick arch dam 

required the use of 4,901,000 cu. yd. of 

concrete, with an additional 469,000 cu. yd. of 

concrete used in the construction of the power 

plant, penstocks, and related infrastructure 

(Table 6.1). 

Due to the remote location of the facility, it was also necessary to construct the Glen Canyon 

bridge to transport construction materials and equipment (Figure 6.4). The 1,271-ft. long 

steel-arch structure spans the river 865 feet 

downstream from the dam.74

6.2.4. Operations and Maintenance

The Glen Canyon facility has been in continuous 

operation since 1964. Its eight generators were each 

originally rated at 118,750 kW, for a combined total 

capacity of 960 MW (Figure 6.5). In 1992, the 

Bureau of Reclamation completed an environmental 

 71 Glen Canyon Association, Website: http://www.glencanyonassociation.org 72 Secretary of the Interior, Report to Congress: Operations of Glen Canyon Dam Pursuant to the Grand Canyon 

Protection Act of 1992, Water Years 1999 – 2001, May 2002. 73 Bureau of Reclamation, U.S. Dept. of the Interior. Website. http://www.usbr.gov/dataweb/dams/az10307.htm 74 Bureau of Reclamation, U.S. Dept. of the Interior, 2005. Website: http://www.usbr.gov/dataweb/html/crsp.html

Figure 6.4. Glen Canyon Bridge 

Table 6.1. Glen Canyon Dam 

Dimensions

Crest Elevation .............................. 3715.0 ft

Structural Height ................................ 710 ft

Hydraulic Height ................................ 583 ft

Crest Length .................................... 1,560 ft

Crest Width .......................................... 25 ft

Base Width ......................................... 300 ft

Volume of Concrete .......... 4,901,000 cu yd
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assessment of the impacts of uprating and rewinding, resulting in a finding of no significant 

impacts (FONSI). Based on this finding, generators were uprated, starting in the mid-90’s 

(except Unit 7, scheduled for service in 2006-7). As of 2005, seven generators are now rated 

at 165,000 kW each, while the remaining unit is rated at 157,000 kW each, for a combined 

capacity of 1,312,000 kW.75 Unit circuit breakers have been replaced (2000), and the 

penstocks have been recoated with MC tar.76 

The reservoir has a total capacity of 

approximately 27 million acre-feet (maf), with 

an active capacity of about 24.3 maf. Water can 

be released from the dam in three ways: 1) 

through the power plant, with a capacity of 

33,200 cfs; 2) through the river outlet works, 

capable of spilling 15,000 cfs; and 3) through the 

spillways, with a combined capacity of 208,000 

cfs. Since the introduction of modified releases 

in 1991, releases have generally been held at or 

below 20,000 cfs, except in rare “floodflow” 

conditions (Table 6.2).77

Table 6.2. Glen Canyon Floodflow Release History

Year(s) Amount Released Reason

1965 NA Excess water released to balance reservoir

1980 NA Excess water released to test spillways

1983 Up to 100,000 cfs Heavy spring run-off; temporary 8-foot retaining 

wall built to hold back floodwater.

1984, 1985, 1986 40-50,000 cfs / 1 mo./yr Heavy run-off years.

1990, 1991 NA Research flows for EIS.

1996 45,000 cfs / 7 days Controlled flood, evaluating habitat restoration 

potential.

 75 Correspondence from R. Gattis, Bureau of Reclamation, US Dept. of the Interior, to G. Burton, Western.

76 Bureau of Reclamation, U.S. Dept. of the Interior, Operation of Glen Canyon Dam: Colorado River Storage 

Project, Arizona. Final Environmental Impact Statement (FEIS), March 1995. 77 US Geological Survey, Western Coastal and Marine Geology, Glen Canyon, Website:

http://walrus.wr.usgs.gov/grandcan/dam.html

Figure 6.5. Glen Canyon Generators 
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6.2.5. Power Transmission

Power generated at the Glen Canyon 

power plant is sold to customers in 

Arizona, Colorado, Utah, Wyoming, New 

Mexico, and Nevada, supplying the 

annual electrical needs of about 400,000 

households.78 The transmission system is 

operated by Western Area Power 

Administration (Western), and is linked 

to its larger system of more than 16,800 

circuit miles (27,000 kilometers) of 

transmission lines, 258 substations, and 

other electric power facilities in a 

geographic area covering 1.3 million 

square miles (3.38 million square 

kilometers) in 15 central and western 

states.79 The system transports CRSP 

power to key load points, and is 

integrated with preference-user and 

private-company transmission lines to 

form the CRSP Interconnected 

Transmission System (Figure 6.6).80 The 

CRSP Customer Service Center (CSC) 

office in Salt Lake City is a member of the Western Regional Transmission Assn. (WRTA) 

and Southwest Regional Transmission Assn. (SWRTA), and operates within the Western 

Electric Coordinating Council (WECC).81

From the Glen Canyon switchyard, 2 major transmission lines run due south to the Flagstaff 

(FLG) switching station, while 1 line runs east to the Navajo (NAV) facility (Figure 6.7).82 

Additionally, two separately owned T-lines tie into the Glen Canyon switchyard complex 

from the west. 

 78 Secretary of the Interior, Report to Congress: Operations of Glen Canyon Dam Pursuant to the Grand Canyon 

Protection Act of 1992, Water Years 1999 – 2001, May 2002. 79 Western Area Power Administration, General Requirements for Interconnection, Dept. of Energy, Sept. 1999. 80 US Bureau of Reclamation, Dept. of the Interior, 2005, Attachment K, Authorities And Obligations. 

http://www.usbr.gov/dataweb/html/crsp.html

81 Western Area Power Administration, Website: http;//www.wapa.gov/ 82 GIS maps supplied by Western Area Power Administration.

Figure 6.6. CRSP Management Center, with

Western’s Marketing / Transmission Territory
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6.2.6. Function and Functional Unit 

Glen Canyon hydropower station has historically served a load-following function within the 

WECC, i.e., supplying power as needed to meet changing daily demand. However, under the 

restrictive flow regimes of the ROD, Glen Canyon can no longer fulfill this function without 

make-up power from back-up sources. Additional power sources capable of flexible 

deployment have been needed to fill the gap, at levels between 20 and 30% of the power 

generated by the hydropower station.

The functional unit for the Glen Canyon is 1,000 GWh of load-following power generation.

6.3. Baseline Case

The averaged impact profile for power generated in the WECC power pool, per 1,000 GWh, 

serves as the baseline impact profile for comparison. As described in Section 4 of this report, the 

WECC power pool system consists primarily of base load units (coal, nuclear, hydroelectric and 

natural gas), reserve units that handle seasonal/daily load demand (produced mainly by coal 

plants and combined cycle natural gas plants), and peak loading units (mostly natural gas).

Figure 6.7. Power transmission from Glen Canyon

Above: Northernmost section of transmission system.

Left: Sheet #01 break-out, showing transmission tower 

(red dots) spaced approximately 500 meters apart. Each 

GIS sheet provides detailed vegetative cover mapping. 
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6.4. Data Sources and Data Quality

6.4.1. Data Sources

Data utilized for this study were derived from a combination of first-hand and second-hand 

sources, including published governmental and agency reports (e.g., Report to Congress, 

Glen Canyon and Electric Power Marketing Environmental Impacts Statements); maps; 

photographs; satellite-generated images; correspondence; interviews and first-hand 

observation. In addition, data were used from the Grand Canyon Model, the STARS model, 

and from various databases (temperature, sediment, flow, etc.) housed at the Grand Canyon 

Monitoring and Research Center in Arizona.

6.4.2. Data Quality 

As already discussed, the Glen Canyon hydropower generation system has been the subject 

of intensive scrutiny since its initial inception and construction. Much of the data evaluated 

for this report were extracted from previous reports and publications that have been used to 

meet a wide variety of regulatory requirements, and have in many cases undergone extensive 

peer review as well as review from stakeholders and the general public. As such, the 

accuracy and quality of the data SCS used in this report is considered to be quite high. 

The documents provided both a quantitative and qualitative analysis of the flora and fauna 

both on a regional and a local scale. In addition, the data on dam construction, dam 

operations, and ongoing mitigation activities was informative and comprehensive.

In areas where SCS utilized data from existing models and databases, the data quality 

parameters are well known, based on direct measurements and tested extrapolation and 

modeling methodologies. Extensive internal and external reviews have been conducted on 

data monitoring, analysis and modeling aspects.83

6.5. Key Assumptions and Scoping Considerations

This section summarizes assumptions specific to this project only. Other assumptions and 

considerations related to the application of the LCSEA methodology are described in Sections 2 

and 3, and Appendix 6.

6.5.1. Allocation of Impacts

The Congressional Act that authorized the construction of Glen Canyon Dam, the power 

plant and Lake Powell, identified electric power production as “incident” to the operation of 

the dam for purposes related to the development of water in the Colorado River Basin

 83 For instance, the GCMRC Protocol Evaluation Program established a peer-reviewed data evaluation process. 

http://www.gcmrc.gov/products/pep/pep.htm
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states.84 A task then, for this study, was to determine the proper allocation of impacts to the 

production of electrical power when much (or all) of the infrastructure of the dam and 

associated reservoir were built for other purposes. 

SCS attempted to uncover an engineering, scientific or political basis for allocating the 

environmental impacts of the 472-foot-tall dam and the 199-mile lake to the power function 

alone but was unable to do so. That is, there appears to be no objective method to parse the 

environmental impacts of the dam and lake into impacts allocated exclusively to the electric 

power function, apart from the environmental impacts of the water storage and delivery 

system of these facilities. 

Therefore, this study allocated impacts in two different and extreme ways:

• The Gross Impacts Allocation Case, a “worst-case” allocation, assigned all 

documented environmental impacts from the dam and lake structures to the Glen 

Canyon hydropower generation system. This case assumes that hydropower 

generation is a primary and inseparable purpose of the project and is responsible for 

producing the environmental impacts from the entire Glen Canyon Dam and Lake 

Powell facility, its operation and effects.

• At the other extreme, the Hydropower Function Case, a “best case” allocation, 

assigns to the hydropower electrical generation only those effects that are caused 

because of the existence and operation of a power plant within Glen Canyon Dam. 

Hourly and daily changes in water releases from the dam caused by changes in 

generation to follow electricity demand, resulting in hourly and daily stage changes in 

the Colorado River, are assigned to hydropower. Monthly water releases assigned by 

Reclamation, lowered river temperature caused by the retention of water in a large 

impoundment, sediment retention in Lake Powell, disruption of the riverine habitat 

above the dam, evaporative water loss due to the existence of the lake and other lakerelated environmental impacts were not assigned to hydropower because they are 

artifacts of the existence of the dam and reservoir.

As stated above, the latter case is justified by the Colorado River Storage Project Act of 

1956. It is clearly the case, however, that the dam and its large reservoir and the power plant 

exist together as an integrated facility to meet Congress’ overall purpose of water 

development in the Western U.S. as envisioned in the CRSPA. The two cases – one with 

environmental impacts associated with the existence of the dam and reservoir and one 

without – constitute “book ends” for the measurement of environmental impacts associated 

with power production. They represent the endpoints of the range of possible allocations to 

power that could be made. 

 84 Colorado River Storage Project Act of 1956 (Public Law 84-485)
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6.5.2. LCI Model Assumptions

The main assumptions regarding the applied LCA inventory model are as follows:

• Initial construction impacts have been 

allocated to the functional unit of 1,000 

GWh, assuming a lifetime of 100 years 

and a 3,320,195 MWh annual power 

generation as reported for FY 2004. 

• Data for annual fuel use for plant 

operation and maintenance were not 

available, and therefore were 

approximated as 0.02 kg diesel 

oil/MWh, or 66,400 kg per year.

• Temporal characterization of CO2

emissions from manufacturing of 

construction materials was calculated 

for 2005, assuming that construction 

time was 1963 and that the first full 

year of power generation was 1965.

6.5.3. Biophysical Impact Focus

The Final Environmental Impact Statement 

prepared for Glen Canyon in 1995 addressed a 

variety of issues, including biophysical 

indicators of environmental impacts, as well as 

economic and social factors such as 

recreational value, cultural resources and costs 

of operation (see sidebar below). 

As described earlier in this study, the scope of LCIA is focused more narrowly on an 

assessment of biophysical impacts only, using quantitative indicators. Issues related to 

recreational uses, effects on cultural resources and cost considerations were outside the scope 

of this project. Data from the Glen Canyon FEIS were utilized along with other data 

resources to conduct this study, as described under Section 6.4 above.

For the same reasons, issues related to aesthetic concerns are not addressed in this study. 

Aesthetics are clearly a matter of concern to stakeholders. In the case of Glen Canyon, an 

active campaign exists to drain the reservoir and restore the canyon to its original state, 

motivated in large part by the drive to restore the canyon to its original state of natural 

beauty. However, aesthetics are highly subjective. Others might argue that the beauty of the 

lake in the middle of an otherwise arid to semi-arid terrain is of at least equal aesthetic value. 

From a quantitative standpoint, one could assess the degree to which a physical change to a 

landscape – by means of construction of a dam and reservoir, installation of transmission 

towers, etc. — has altered the viewshed. But it is not clear that such a measure would 

Issues addressed in the Glen Canyon FEIS

Source: Final Environmental Impact Statement 

March 1995.

• How do dam operations affect the amount and 

quality of water available from Lake Powell at 

specific times?

• How do dam operations affect sediment 

resources throughout the study area?

• How do dam operations affect fish – their life 

cycles, habitat, and ability to spawn?

• How do dam operations affect vegetation in 

the river corridor?

• How do dam operations affect area wildlife 

and their habitat?

• How do dam operations affect the populations 

of endangered and other special status species 

throughout Glen and Grand Canyons?

• How do dam operations affect other electrical 

production in the area, including those 

methods that have impacts on air quality?

• How do dam operations affect the continued 

existence of cultural resources in the study 

area?

• How do dam operations affect recreation in the 

study area?

• How do dam operations affect the ability of 

Glen Canyon Powerplant to supply 

hydropower at the lowest possible cost?

• How do changes in Glen Canyon Dam 

operations affect non-use value?
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provide an adequate or accurate reflection of the complex aesthetic issues to be addressed. 

As such, there is no attempt in this study to provide indicators of aesthetic impact.

6.5.4. Drought Related Impacts

Since 1999, the Colorado River basin has been experiencing a severe drought. According to 

a July 2005 update posted on the Bureau of Reclamation website:

 “In the summer of 1999, Lake Powell was essentially full with reservoir storage at 

97 percent of capacity. Inflow volumes for 5 consecutive water years were 

significantly below average. Total unregulated inflow in water years 2000, 2001, 

2002, 2003, and 2004 was 62, 59, 25, 51, and 51 percent of average, respectively. 

Inflow in water year 2002 was the lowest ever observed since the completion of 

Glen Canyon Dam in 1963. ... Lake Powell reached a low elevation on April 8, 

2005, at 3,555 feet (145 feet from full pool).” 

One notable consequence of the drawdown in lake level has been the marked increase in 

water temperatures of dam discharges. Historically, water temperatures in the Colorado 

River downstream of 

Glen Canyon varied 

considerably, from 

lows near freezing to 

highs of about 85°F, 

reflecting run-off 

flows, sediment content, and other 

seasonal factors. After the construction 

of the dam, water 

discharge temperatures stabilized at 

an average of 45-

50°F, with only 

slight seasonal variations over the course 

of the year, and 

downstream temperatures warming only 

slightly. This change in temperature profile has been cited as a major factor in creating 

suitable habitat for non-native trout species, and potentially, for impacting the populations of 

warm water native fish species such as the endangered humpback chub. As a result of the 

current drought, however, average temperatures have risen markedly by as much as 6-7°F 

(Figure 6.8).

Figure 8.8. Annual Temperature Patterns below Glen Canyon Dam
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While hydrological conditions have improved somewhat in recent months, the long-term 

outlook is as yet undetermined.85 Data reviewed by SCS in the preparation of this report did 

not factor in these recent temperature developments. As such, SCS made no attempt to 

address any variables that might be associated with unusual persistent drought conditions, 

other than specifically stated. On the contrary, SCS made an effort to select data sets that 

were representative, to the extent possible, of the average condition of the project. 

6.5.5. Water Resource Depletion

In addition to direct outflows, net water resource depletion from a reservoir can occur when 

water: 1) evaporates and transpires into the atmosphere; and/or 2) seeps into sediments and 

rocks on the lake floor and banks as lake levels rise. 

As required under the Colorado River Basin Project Act of 1968, Public Law 90-537, the 

Water Resources Group of the Bureau of Reclamation has been preparing reports of 

consumptive water uses and losses for successive 5-year periods since October 1970. These 

reports include annual evaporative loss estimates for Lake Powell. Evaporative losses are 

directly linked to lake water elevation, since the higher the elevation, the greater the lake 

water surface area. The Bureau’s methodology for calculating evaporation utilizes “a 

multiple regression equation relating gross annual evaporation to elevation and latitude” with 

adjustments as needed to reflect climatic subareas.

Potter and Drake [1989] 

modeled evaporation at 

various lake elevations, 

based on Bureau data. At 

two-thirds full, the lake’s 

surface is approximately 

125,000 acres. At this level, 

based on the Bureau of 

Reclamation data, Lake 

Powell loses a net 500,000 

acre-feet/year (af/y) to evaporation. (This net calculation 

is based on evaporation 

levels from the lake minus 

pre-dam evaporative losses 

from the river.) When full, 

this net loss increases to about 725,000 af/y (Figure 6.9).86 

 85 Tom Ryan, Bureau of Reclamation, July 11, 2005 Update. http://www.usbr.gov/uc/water/crsp/cs/gcd.html. 86 Lake Powell: Virgin Flow to Dynamo, Lauren D. Potter and Charles L. Drake, University of New Mexico Press, 

Albuquerque, 1989. In terms of pre-dam evaporation, Potter and Drake state: “From an analysis of the topography 

and the vegetation and with an effective annual precipitation of 5.71 inches in the area, the pre-lake evaporation 

losses were calculated to be about 227,000 acre-feet per year (af/yr). However, this includes about 60,000 af/yr of 

evaporation of precipitation that once fell on the hillsides and now falls directly into the lake, considered to be but an 

augmentation to the reservoir. If this is subtracted, the net pre-lake evaporative loss for comparative purposes would 

be about 167,000 af/yr.” (page 210.)

Figure 6.9. Net evaporation losses at different lake 

surface levels, Lake Powell.
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In terms of remaining observed water losses, the Potter and Drake discounted transpiration as 

a significant factor, since the increase in terrestrial vegetation around the lake was noted to be 

relatively minor as the lake surface rose between 1964 and 1980. Instead, they concluded that 

the highly permeable sediments and rocks along the floor and wall likely have absorbed the 

remaining water. This bank storage was noted, but not included in water depletion 

calculations.87

In calculating net water evaporation for this study, SCS assumed the lake to be two-thirds 

full, on average, over its 40-year lifetime, which equates to approximately 21 million acre 

feet (maf) of water active capacity88. This assumption was made to take into account the 

high storage years of the mid-1980s and the more recent low storage years of the drought 

period (Table 6.3). (Note that evaporation levels in the drought years of 2004 and 2005 

exceed historic evaporation levels of the pre-dam river by only about 20%. In March 2007, 

reservoir storage was reported to be 11.52 million acre-feet, 47% of capacity.89)

Table 6.3. Evaporation at Lake Powell

Source: U.S. Bureau of Reclamation

Evaporation (1,000 af/y)

1996 582.0

1997 592.7

1998 605.3

1999 605.6

2000 576.9

5-year Average 

(1996—2000)

592.5

2001 533.0

2002 436.5

2003 352.8

2004 278.3

2005 289.0

5-year Average 

(2001—2005)

377.9

No water depletion was calculated to take into account the creation of habitat in new high 

water zones (NHWZ) (see 6.5.6 below) along the river banks, for instance, with respect to 

the aggressive invasive tamarisk shrubs that are known to deplete water through their deep 

tap roots and exceptionally high rates of evapotranspiration.90

 87 According to Potter and Drake, “Some of the [water] returns to the lake during low-water seasons. The remainder 

becomes a part of the ground-water system . . . Since it will not be subject to evaporation and is at depths too great 

for root systems to penetrate, this water could become a significant water resource.” Pg. 210. 88 Data provided by Gary Burton from the Colorado River Storage Project Book.

89 Tom Ryan, USBR Water Resources Group. “Lake Powell - Glen Canyon Dam - Current Status”

http://www.usbr.gov/uc/water/crsp/cs/gcd.html, March 2007. 90 National Park Service, Nature and Science website: 

http://www.nature.nps.gov/biology/ipm/manual/exweeds1.cfm

Decline in lake level 

due to drought

Nearly full
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No additional water resource depletion was calculated for the combined cycle natural gas 

assumed to be used as the auxiliary power source during the post-ROD period. 

6.5.6. Uncertainty Surrounding Causes of Observed Adverse Impacts 

Extensive environmental monitoring in the Glen Canyon and along the Colorado River has 

called attention to a number of environmental impacts observed in the upstream and 

downstream regions impacted by the facility. At the same time, the causal relationship 

between specific stressors and effects remains uncertain. 

For instance, in assessing effects on native and non-native fish species, one must consider not 

only the dam-related impacts — such as changes in water temperatures, changes in daily and 

seasonal flow fluctuations, and the physical barrier of the dam itself – but also factors such as 

the stocking of non-native species for recreational purposes (e.g., trout), pest and disease 

vectors (e.g., Asian tape worm), etc.

In this study, it was not possible to tease out the cause and effect relationship for every 

parameter. In the case of species-specific effects, too little data existed for most species 

during pre-dam conditions to fully understand what changes (increases or decreases) may 

have occurred. Even for those species where population or habitat estimates were available 

for a large segment of time, the cause of changes was not always clear. 

As a result, SCS assumed a one-to-one relationship between physical disturbance and 

observed changes to the associated ecosystem parameters. No attempt was made to allocate 

effects amongst numerous causes. If the extent of a species or habitat changed (increased or 

decreased over time) and at least part of the cause was related to dam construction or 

operations, SCS assumed that the full change is associated with the dam. This assumption 

led to conservative calculations that may well overstate the impacts associated with dam 

operations; however, without an ability to pin down the causes of impacts, this approach 

provided a more precautionary set of results. 

6.5.7. Creation of Habitat

As noted in the 1995 Glen Canyon FEIS, and in the Interior Secretary’s 2001 Report to 

Congress, the construction and operation the Glen Canyon facility has resulted in positive as 

well as negative impacts on certain habitats and species. 

In this study, both the creation and depletion of habitats were considered. For habitats that 

are endemic to the area, increases or decreases were tabulated and a net value was calculated 

for habitat disturbance when appropriate. For example, a net value for available river habitat 

could be calculated, since the river habitat is endemic to the area and might either be 

increased or decreased over time. For habitats that are not endemic to the area, such as Lake 

Powell, SCS identified and quantified those habitats and listed them in the habitat discussion 

below. Newly created habitats were not, however, used in net value calculations or in 

calculations of environmental ratings. There is no question that newly created habitat, such 

as Lake Powell, can provide a variety of social and ecological benefits. However, before the 
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benefits can be duly incorporated into the LCSEA calculations, further work is needed to 

quantify the extent to which these newly created habitats support the endemic species and 

habitats. Studies that document the similarities and differences between newly created 

habitat and pre-existing habitat and species would allow SCS to incorporate these habitats 

into the net value calculations. 

6.5.8. Auxiliary Power to Augment Post-ROD Power Generation 

The institution of the modified low-fluctuating flow regime has transformed Glen Canyon 

from a system that provided load following power to a system providing more baseload 

support for the WECC power grid. Prior to the 1996 Record of Decision (ROD), daily 

fluctuations were allowed between 3,000 – 30,000 cfs. Starting with interim flow 

modifications instituted in 1991, and formalized by the 1996 ROD, daily fluctuations 

dropped to a daily maximum fluctuation of 8,000 cfs. Accordingly, the Glen Canyon power 

plant is no longer running at its maximum capacity. At this scale of power generation, the 

total loss in operating capacity is about 500 MW.91 

The environmental benefits of this modified flow regime are being closely tracked by the 

GCMRC, Western, and other research institutions and stakeholders. Less well understood 

are the potential unintended environmental trade-offs associated with the use of make-up 

power to fulfill the following load function. 

6.6. Habitat Disruption and Effects on Species – Gross Impacts Allocation 

Case

As described in Sections 2 and 3, LCSEA evaluation of impacts includes an accounting of the 

direct habitat disturbance as well as decreases or increases in species abundance and productivity 

from land use functions such as buildings, roads, mines, dams and transmission lines, as well as 

from project operations. As described in Section 6.5.1, the Gross Impacts Allocation Case 

assigns all impacts of the Glen Canyon facility to hydropower.

6.6.1. Habitat Disruption to Areas Occupied by Facilities

The areas affected directly by the construction of Glen Canyon dam include portions of the 

Colorado River and Glen Canyon. These areas encompass both terrestrial and aquatic 

habitats containing a wide variety of species. 

The facilities at Glen Canyon include buildings, bypass, the dam, parking lots, the power 

plant, and the substation. Roads in the area were not included as most serve multiple 

purposes and were not attributed to facilities alone.

The terrestrial cover types and the aquatic (riverine) areas disturbed by dam facilities are 

shown in Table 6.4 below. The total habitat disruption due to facilities is 44 acres, while the 

total riverine habitat disrupted is 13.8 acres.

 91 Correspondence with G. Burton, Western Area Power Administration.
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Table 6.4. Areas of Disturbance Associated with Glen Canyon Dam Facilities

Facility Description Perimeter Area

Building Shadscale-Mixed Grass-Mixed Scrub 570 ft. 0.397 ac

Bypass Mormon Tea-Mixed Scrub 502 ft. 0.348 ac.

Shadscale-Mixed Grass-Mixed Scrub 362 ft. 0.188 ac.

Water 3580 ft. 9.05 ac.

Dam Mormon Tea-Mixed Scrub 3580 ft. 9.05 ac.

Water 3580 ft. 7.05 ac.

Parking lot Shadscale-Mixed Grass-Mixed Scrub 2864 ft. 4.60 ac.

Water 2864 ft. 4.60 ac.

Power station Mormon Tea-Mixed Scrub 1537 ft. 2.02 ac.

Shadscale-Mixed Grass-Mixed Scrub 1537 ft. 2.02 ac.

Sub station Shadscale-Mixed Grass-Mixed Scrub 3528 ft. 12.5 ac.

Shadscale-Mixed Grass-Mixed Scrub 1827 ft. 4.25 ac.

6.6.2. Habitat Disruption Due to Glen Canyon Project Operations

Dam operations accounted for the largest subset of physical disturbance associated with the 

project. The operation of the dam created Lake Powell, which is responsible for inundating a 

significant run of the Colorado River and associated tributaries upstream of Glen Canyon 

dam, as well as Glen Canyon itself. In addition, more than 200 miles of the Colorado River 

downstream of Glen Canyon have been affected by dam operations. Changes in flow 

dynamics over time have led to a number of habitat alterations. In addition to the dam itself, 

the installation and maintenance of transmission lines can have a potential impact on 

associated habitats; as such, SCS worked to identify the types of habitats associated with 

transmission lines as well as the level of disturbance caused by maintenance of the lines.

Sections 6.6.2.1 and 6.6.2.2 describe the affected areas and the methods SCS used to estimate 

the associated physical disturbance. 

6.6.2.1. Aquatic and Riparian/Wetland Habitats

Pre-dam River Habitat Upstream of Glen Canyon Dam

A number of studies describe the physical area of Glen Canyon.92 Many studies include 

discussions of the length of river that was inundated by the flooding of Glen Canyon and 

its tributaries. However, SCS was unable to find any estimates of the amount of river 

habitat disturbed upstream of the dam.

 92 Citations to be inserted, final report.
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To determine the amount of river habitat affected by the creation of Lake Powell behind 

Glen Canyon Dam, SCS obtained the assistance of GIS specialists from Western Area 

Power Administration (WAPA).93 First, USGS maps were located that showed contours 

of the original course of the Colorado River and tributaries.94 To calculate the pre-Glen 

Canyon Dam Colorado River and related tributary channels, the accuracy of the 

boundaries shown was checked. Three methods were used to ensure the accuracy of the 

boundary identifications:

• A comparison was made of contour line features between the 1921 Southern 

California Edison Co. and 1977 USGS 1:24K Topographic Maps. This 

comparison resulted in a reasonably exact match of historic channel delineation. 

A digital overlay comparison was not done because the 1921 maps were not georeferenced and created at a smaller (uncommon) scale.

• The historic river channel was identified both by symbol and title on the 1977 

USGS 1:24K Topographic Maps.

• The channel boundary symbol was confirmed from the USGS Bathymetric 

Features symbol set.

The boundaries were then digitized from the historic river and tributary channels 

identified on the USGS 1:24000 Topographic maps. Table 6.5 shows the USGS maps 

used.

The maps were not sufficient to provide a direct measure of riparian habitat along the 

Colorado River and tributaries upstream of the dam. To estimate riparian habitat that 

existed above the dam site prior to construction, SCS conferred with GCMRC staff 

(Barbara Ralston). GCMRC provided estimates of riparian habitat coverage in presentday areas similar to those believed to be in existence prior to the dam. Using these 

estimates, SCS expanded the estimate by multiplying it by the length of river now 

inundated by Lake Powell.

 93 WAPA Contract GIS Specialists Eric Weisbender and Bob Almovdar

94 Citation to be inserted, final report.
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Table 6.5. USGS Maps Upstream of Glen Canyon Dam

24K QUAD ID 24K QUAD NAME STATE

o36111g2 Cedar Tree Bench Arizona

o36111h1 West Canyon Creek Arizona

o36111h2 Face Canyon Arizona

o36111h3 Wild Horse Mesa Arizona

o36111h4 Page Arizona

o37110a8 Rainbow Bridge Arizona

o37110b4 Monitor Butte Utah

o37110b5 No Mans Mesa North Utah

o37110b6 Deep Canyon North Utah

o37110b7 Wilson Creek Utah

o37110b8 Nasja Mesa Utah

o37110c4 Mikes Mesa Utah

o37110c5 Nokai Dome Utah

o37110c6 Alcove Canyon Utah

o37110c7 The Rincon Utah

o37110c8 Davis Gulch Utah

o37110d5 Halls Crossing NE Utah

o37110d6 Halls Crossing Utah

o37110d7 The Rincon NE Utah

o37110d8 Stevens Canyon South Utah

o37110e5 Knowles Canyon Utah

o37110e6 Bullfrog Utah

o37110e7 Hall Mesa Utah

o37110f4 Good Hope Bay Utah

o37110f5 Ticaboo Mesa Utah

o37110g3 Copper Point Utah

o37110g4 Hite South Utah

o37110g5 Mount Holmes Utah

o37110h3 Sewing Machine Utah

o37110h4 Hite North Utah

o37111a1 Cathedral Canyon Utah

o37111a2 Gregory Butte Utah

o37111a3 Gunsight Butte Utah

o37111a4 Warm Creek Bay Utah

o37111a5 Lone Rock Utah

o37111b1 Navajo Point Utah

o37111b2 Mazuki Point Utah

o37111b3 Sit Down Bench Utah
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Table 6.6 shows the measures of river habitat inundated by the construction of Glen 

Canyon dam and the creation of Lake Powell.

Table 6.6. Pre-dam River Habitat Upstream of Glen Canyon Dam

RIVER NAME PERIMETER AREA SQ_METERS ACRES SQ_MILES

Colorado River 337 miles 42,663,838.761 10,542.420 16.47260

San Juan River 120 miles 10,357,831.922 2,559.466 3.99918

Escalante River 53.3 miles 1,851,064.124 457.406 0.71470

Dirty Devil River 29.2 miles 632,835.472 156.376 0.24434

TOTAL 539.5 miles 55505570.3 13715.7 21.4

Post-dam Lake Habitat Upstream of Glen Canyon Dam

In addition to estimating the loss of river habitat, a measure of habitat created by the 

project was required – in this case, the addition of one of the largest lakes in North 

America, Lake Powell. Numerous publications provided information pertaining to the 

size of Lake Powell.95 SCS chose to verify those figures by digitizing current USGS 

topographic maps and calculating the surface area of Lake Powell. Table 6.7 shows the 

area calculated for Lake Powell by this process. The size calculated matches well with 

published figures (156,000 – 165,000 acres). For this study, SCS used 158,127 acres 

(63,993 hectares), a compromise between SCS’s digitized calculations and those cited in 

the literature. 

Table 6.7 Post-dam Lake Habitat Upstream of Glen Canyon Dam, based on Digitized Data

Size of Lake Habitat

Perimeter 1432.8 miles

Area in Square Meters 639,920,128

Acres 158,127 

Square Miles 247

Pre-Dam and Post-Dam River Habitat Downstream of Glen Canyon Dam

The disturbance associated with the Colorado River downstream of Glen Canyon dam is 

the subject of ongoing intensive studies. Not surprisingly, the literature on the ecological 

impacts of Glen Canyon Dam is substantial and complex. Numerous reports, 

publications and Internet websites describe the types and amounts of impacts to river 

habitat, riparian habitat, and even to some associated terrestrial habitats. These resources 

provide descriptions of the native species in place before the dam, and their associated 

habitats, as well as descriptions of the changes that have occurred to the species 

complexes and their habitats after the operation of the dam for several decades. 

 95 Citations to be inserted, final report.
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The literature leaves no doubt that there have been significant changes to in-river species 

as well as species that depend on riparian and terrestrial habitats adjacent to the Colorado 

River. The Environmental Impact Statements that have been published provide good 

summaries of the relevant information. 

As described in earlier sections, the LCSEA methodology requires that both aquatic and 

terrestrial habitat changes be calculated. In the case of the downstream portion of the 

river, it is clear that river habitat is still available; however, there is no single compilation 

of the amount of river habitat that may have been lost or added as a result of the 

operations of the dam. SCS also found no specific quantitative estimates of the loss of 

in-river habitat or riparian habitat downstream of Glen Canyon dam.

To determine the most efficient way to compile a quantitative measure of in-river habitat 

changes over the 200+ miles of affected river downstream, SCS met with staff members 

of Argonne National Laboratory. In discussions about the available data and literature on 

Glen Canyon dam, it was decided that the most practical way forward was to use existing 

sets of data that had already been gathered and compiled into databases as part of 

previous projects — i.e., STARS, the Grand Canyon Ecosystem Model (GCM), the 

Colorado River Flow Stage & Sediment Model (CRFSS). SCS contracted Ecometric 

Research Inc., the company that helped develop the Grand Canyon Ecosystem Model, to 

assist in identifying ways to estimate in-river habitat and riparian habitat from pre- and 

post-dam conditions. 

For in-river habitat, a decision was made to use the wetted width of the river by rivermile by month for a given set of years representing pre-dam and post-dam conditions. 

Wetted width for this project is defined as the area that is inundated 100% of the time 

assuming specific flows. To estimate changes in wetted width over time, several 

parameters first had to be defined: 

 Appropriate periods of time for calculating pre-dam and post-dam estimates

 Length of the river effected by Glen Canyon Dam

Time series were identified for both pre-dam (1956) and post-dam (1992) conditions by 

using discharge rates over various periods of time in the following way:

1. The historical record of monthly volumes released from Glen Canyon Dam or 

past the Lee’s Ferry gauge was ranked to determine the median annual volume 

between 1948 and 2004 (8.72 maf). 

2. The proportion of volume in each month for each year was computed and average 

proportions for each month for the pre-dam (1948-1960) and post-dam (1975-

2004) periods calculated. Years between 1960 and 1975 were omitted from the 

analysis because of the potential effect of dam construction and reservoir filling 

on monthly volume patterns.
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3. Each year during the pre-dam and post-dam periods was ranked according to its 

similarity in relative seasonal volume patterns to the average condition for the 

appropriate period. Ranking was conducted by minimizing the sum of squared 

differences between the average monthly proportions and the year-specific 

proportions.

1956 was used to represent the pre-dam condition because its annual volume (8.51 maf) 

was very close to the median value (8.72 maf), and the seasonal pattern in volume 

distribution was the fourth closest out of the thirteen years used to represent pre-dam 

conditions. 1992 was used to represent the post-dam conditions because of its similar 

annual volume (8.03 maf) to the median and because it ranked first in terms of the 

seasonal volume distribution out of the 30 years used to represent the post-dam period.

Temperature data by river mile were compared pre-and post-dam to determine the length 

of river necessary to input into the estimates. Temperature, reflecting differences in 

hydrology, was the most consistent measure available over long periods of time that 

could be modeled to determine if differences based on hydrology could be seen. Monthly 

averages for each reach for these two years were computed. No data were available for 

1956, so data for the pre-dam period were used to represent a monthly pattern for the 

entire river. Water temperature data in 1992 were only available for the Glen Canyon and 

Furnace Flats reaches. Temperatures for other reaches were predicted by the Grand 

Canyon Ecosystem Model (GCM). 

Table 6.8 shows observed and predicted temperature data. The data show that observed 

temperatures are different from both predictions along the entire length of the river from 

Glen Canyon almost to Lake Mead. 

Table 6.8. Temperature Comparisons by River Reach from Glen Canyon to Lake Mead.

The pre-dam temperature data shows strong seasonal variation with very low water 

temperatures during winter months (3-6° C), rapid increases in temperature during the

spring, and maximum water temperatures during the summer of 23-27° C. In the post-
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dam period, water temperature variation has been greatly reduced. Observations in 1992 

showed a temperature range of 7.7-10.0° C flowing through Glen Canyon Dam with 

maximum temperatures occurring in November and December (a temporal inversion in 

monthly thermograph). Temperatures are warmer downstream and show maximum 

values during summer months due to longitudinal warming. Post-dam maximum 

temperatures are well below maxima reached during the pre-dam period, and lower than 

required by native fish.

Table 6.9 shows the comparisons of discharge rates over time used to determine the best 

fit of discharges to pre-dam and post-dam periods of time. There was a fairly large 

discrepancy between predicted and observed water temperatures in 1992 at the Furnace 

Flats reach. GCM model parameters were tuned to match observed water temperatures 

observed since 2000. Reduced volumes from Glen Canyon Dam since 2000 have led to 

water temperatures at Furnace Flats during the summer of 13-15° C. Observed data from 

1992 may be reflective of the overall temperature pattern in the post-dam period, but not 

of temperatures in the last five years (see Section 6.5.3). The predicted data for 1992 may

provide a more representative picture of seasonal and longitudinal trends in water 

temperature for the 2000+ post-dam period.

Wetted width estimates were then calculated for the length of the river and time series 

determined in the steps outlined above. Minimum wetted width is a performance 

measure intended to capture the amount of aquatic riverine habitat under prescribed times 

(pre- and post-dam). Daily minimum flows for each month in 1956 and 1992 were 

determined from 15-minute discharge records at the Lee’s Ferry gauge. Daily minimum 

discharge was used as input to the STARS-derived wetted width-discharge relationship 

for over 700 cross-sections between Glen Canyon Dam and Diamond Creek on the 

Colorado River in Grand Canyon to compute minimum daily wetted widths. These 

minimum widths were then averaged by reach and month (Table 6.10).

Trends in wetted width follow known effects of Glen Canyon Dam and other dams. 

Operation of Glen Canyon Dam has reduced discharge during the spring and increased 

baseflows during fall, winter, and summer. As a result, wetted widths in the pre-dam 

period tended to be higher than in the post-dam from April through June, and visa-versa 

during other months. The minimum productive area represented by minimum wetted 

width is considerably higher in the post-dam period in September, October, and 

December, and moderately lower in May and June. The change in wetted width between 

pre- and post-dam periods varied by reach, with narrower reaches showing less change in 

width for a given change in discharge. 
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Table 6.9 Comparison of Discharge Rates Over Time
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Table 6.10. Wetted Width Pre- and Post-Dam

Pre-Dam and Post-Dam Riparian/Wetland Habitat Associated with Glen Canyon Dam

The impoundment of water in Lake Powell resulting from the construction of Glen 

Canyon dam eliminated upstream riparian/wetlands habitats along the Colorado River 

and its tributaries, the San Juan, Escalante and Dirty Devil rivers. 

In terms of downstream disruption of riparian habitat, the situation is more complex. 

Prior to dam construction, the high flow rate was around 125,000 cfs, leaving a very 

small band of riparian habitat well above the canyon floor. This band is referred to as the 

old high water zone (OHWZ). Upon building of the dam, the flow was regulated such 

that the high flow rates dropped to around 33,000 cfs. As a result, the new high water 

zones (NHWZ) along the canyon walls directly downstream of the dam in Glen Canyon, 

and further downstream in the Grand Canyon National Park, are significantly lower than 

the OHWZ. While vegetative communities in the OHWZs are generally in decline, most 

likely due to dewatering and lack of nutrient replenishment, some of the OHWZ plants 

are long-lived, and this zone therefore still forms a distinct band of vegetation in the 

Grand Canyon. 

Average daily minimum wetted width (in feet) by month and reach in 1956 (pre-dam) and 1992 (post-dam)
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During the pre-ROD period, the riparian zone expanded due to less scour, more sediment 

stabilization, and longer exposure of the wetted surface area. All of these factors allowed 

vegetative cover to expand. In the post-ROD period, flow rates have been further reduced 

to a high flow of around 15,000 cfs, with an average flow between 10,000 – 11,000 cfs in 

recent years, augmented by four experimental flood flows in 1996, 1997, 2000 and 2004. 

This flow regime allowed for further expansion of the riparian areas.

SCS is unaware of any prior research conducted on the total riparian area change along 

the entire stretch of the Colorado River affected by the Glen Canyon Dam (both upstream 

and downstream). A recent study by GCMRC (Ralston, B., 2006) involving mapping of 

riparian vegetation downstream of the Glen Canyon Dam made it possible for GCMRC 

to provide SCS with estimates of riparian vegetation at a few specific points along the 

river. These estimates were then combined with distance along the river, and used to 

produce estimates for this study of total riparian zone vegetation along the Colorado 

River downstream of Glen Canyon Dam. 

The estimate of riparian vegetation existing prior to dam construction is about 33,191 

hectares (82,000 acres). Since construction of the dam, a NHWZ of about 104,000 

hectares (257,000 acres) of riparian vegetation was estimated for the pre-ROD period. 

The NHWZ is estimated to have expanded to about 280 thousand hectares (close to 700 

thousand acres) since flows were further modified to comply with the ROD. 

6.6.2.2. Terrestrial Habitats 

Terrestrial habitat disruption can be accounted for by the loss of terrestrial habitat 

upstream of the Glen Canyon Dam due to the filling of Lake Powell. Little to no 

significant terrestrial habitat has been removed or disrupted downstream of Glen Canyon 

Dam, with the exception of riparian habitat which is handled as a separate topic and 

indicator in this study (see 6.6.2.1). 

Current calculations confirmed by GIS experts at Western show that a total of 144,411 

acres (58,442 hectares) of terrestrial habitat was flooded. This figure was derived by 

taking the coverage of Lake Powell (158,127 acres) and subtracting the area covered by 

the river channels flooded above Glen Canyon dam. In addition, the footprints of the 

facilities (buildings, bypass, dam, parking lot, power station, and substation) were 

checked, estimated (58 acres), and added to the total.

SCS also reviewed the degree to which terrestrial habitats may have been affected by 

construction and maintenance of transmission lines linking the Glen Canyon Dam to the 

interconnected grid. To estimate actual physical disruption associated with transmission 

lines, it was first necessary to identify those lines that were built to specifically connect 

Glen Canyon dam operations to the existing electricity grid. The lines identified are 

shown in Table 6.11. 

In addition, it was necessary to identify the land cover types in the Right of Ways 

(ROWs) associated with each line. ROWs are those designated areas in and around the 
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transmission lines that are required to be kept clear of any objects that could cause 

damage to, or the loss of operation of, transmission lines. Table 6.11 shows each land 

cover type as well as the amount of each type of land cover associated with each 

transmission line.

The last issue to be examined was whether any of the land cover areas associated with 

ROWs are regularly or periodically cleared of vegetation to ensure that there are no 

objects that could cause loss of operation of the transmission lines. For these areas, SCS 

considered the clearing of vegetative cover as a cause of physical disruption, as it does 

cause loss of biological diversity in the areas of the lines, as well as disrupt the potential 

continuity of ecosystems where the lines occur. 

The total vegetative land cover within transmission line ROWs is 9,232 acres, which 

excludes areas covered by water or industrial buildings. According to the unit in Western 

that manages the ROWs, none of the ROWs for Western are required to have vegetation 

cleared at regular intervals. However, those land cover areas that contain Ponderosa Pine 

are the most likely to require at least periodic maintenance (some sort of clearing or 

pruning). SCS considered the areas with Ponderosa Pine the only areas worth considering 

as containing physically disrupted ecology. This reduced the 9,232 acres to only 535 

acres of disrupted vegetative cover.
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Table 6.11. Land Cover in Transmission Right of Ways Associated with Glen Canyon Dam
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6.6.2.3. Overall Habitat Disruption 

Table 6.12 summarizes the calculations of habitat disruptions described in previous 

sections. 

 

Table 6.12. Overall Habitat Disruption

Area Disrupted

Terrestrial Habitat Acres Hectares

 Inundated by Lake Powell 144,411 58,441

 ROWs 535 217

 Facilities 58 23

TOTAL 145,004 58,681

Riparian/Wetland Habitat

 Upstream /Downstream River 82,000 33,184

 ROWs 16 6

TOTAL 82,016 33,191

Lake Habitat*

 Above Glen Canyon Dam 0

 Below Glen Canyon Dam 0

Eq. River Miles

Riverine Habitat

 Above Glen Canyon Dam 307

 Below Glen Canyon Dam 225

TOTAL 532

* As there was no lake prior to construction of the dam, there was zero disruption 

to lake habitat attributable to the dam project. 

6.6.3. Glen Canyon –Effects on Key Species

This section discusses several species that have been affected by the construction and 

operation of the Glen Canyon dam. Considerable data have been compiled by GCRMC and 

others regarding the status of species endemic to the Colorado River and its surrounding 

environs, as well as introduced, both above and below Glen Canyon dam. Table 6.13 

provides a summary of these species. 
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Table 6.13. Species Overview

Native Fish

Species

Introduced

Fish Species

Endangered

Species

Locally Extinct

Species

Bluehead sucker Black crappie American peregrine falcon Bonytail chub

Bonytail chub Bluegill Bald eagle Colorado squawfish

Colorado squawfish

Humpback chub

Channel catfish Belted kingfisher Razorback sucker 

Roundtail chub

Razorback sucker Largemouth bass California brown pelican Southwestern river otter

Roundtail chub Smallmouth bass California clapper rail Yuma clapper rail

Speckled dace Striped bass Desert pupfish

Walleye Hualapai Mexican vole

Fathead minnow Humpback chub

Green sunfish Kanab ambersnail

Red shiner Light-footed clapper rail

Western mosquitofish Moapa dace

Flathead catfish Mojave tui chub

Blue tilapia Osprey

Yellow bullhead

Common carp Sonoran pronghorn

Rainbow trout Southwestern willow flycatcher

Threadfin shad Vaquita

Golden shiner Virgin river chub

Brown trout Woundfin

Goldfish

Plains killifish

Black bullhead

Sailfin molly

Brook trout

Rio Grande cichlid

Arctic grayling

Cutthroat trout

Northern pike

Redside shiner

Redear sunfish

Mozambique tilapia

Redbelly tilapia

Rock bass

Guppy

Yellow bass

White crappie

Shortfin molly

Rio Grande sucker

White bass

Bigmouth buffalo

Smallmouth buffalo

Brown bullhead

Convict cichlid

Grass carp

Black buffalo

Warmouth

Spotted bass

Yellow perch
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For the purposes of this LCIA study, within the allocated budget, an indicator species was 

selected to represent the impacts of the dam construction and ROD. This is consistent 

with the requirements of the Draft National Standard (SCS-002) (Appendix 6), which 

requires that the loss of key species be estimated by examining the data for all key 

species and selecting the species that has the greatest added mortality from project 

operations. Considerations in the selection of the indicator species were:

• Native to the region. A species native to the region was selected in order to 

provide a reflection of changes attributable to the Glen Canyon dam since its 

construction. 

• Fish species. A fish species was selected in order to capture changes occurring 

over the largest potential area of altered habitat, which in this case was river 

habitat. 

• Endangered. A listed endangered species was selected consistent with the 

requirements of the SCS-002 standard.

In the case of Glen Canyon dam, several species have been 

affected by the construction and operation of the dam. 

However, little quantitative data is available on these species. 

The species for which the most data have been collected, and 

the best estimates of population change over time exist, is the 

humpback chub. 

The humpback chub (Gila cypha) is a member of the minnow family. According to the 

U.S. Fish and Wildlife Service, the humpback chub is believed to have evolved 3-5 

million years ago, and lives primarily in canyons with swift currents and white water.

“Historically, it inhabited canyons of the Colorado River and four of its tributaries: the 

Green, Yampa, White and Little Colorado rivers, with the largest known populations in 

the Little Colorado.”96

The humpback chub was formally listed as an endangered species by the U.S. Fish and 

Wildlife Service in the 1960s, and given full protection under the Endangered Species 

Act of 1973. Since its initial listing, U.S. recovery strategies have included boosting and 

protecting river flows in the spring, monitoring fish population numbers and managing 

stocking of non-native predatory fish. GCMRC oversees monitoring and research of the 

Grand Canyon population of humpback chub under the auspices of the Glen Canyon 

Dam Adaptive Management Program (GCDAMP). Recovery efforts are also being 

monitored by the Upper Colorado River Endangered Fish Recovery Program, a 

public/private partnership.

Estimates of the humpback chub population since the construction of the dam until 1989 

are highly uncertain, given the lack of monitoring data. The population of humpback 

chub at the time that formal monitoring efforts commenced in 1989 was estimated to be 

around 10,000 using constant mortality, and 13,500 with variable mortality. Since that 

time, monitoring data indicate that the population of humpback chub steadily declined to 

 96 U.S. Fish and Wildlife website: http://www.fws.gov/coloradoriverrecovery/Crhbc.htm
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4-5,000 in 2000, then stabilized, showing a slight increase by 2005 (Figure 6.10). 

According to GCMRC: 

“The death of 15% to 20% of adult fish each year and a low rate of juvenile fish 

surviving into adulthood contributed to the decline. Adult mortality rates and the 

failure of juvenile fish to reach adulthood have both been attributed to changes in 

Little Colorado River and Colorado River hydrology, the weakening of young fish 

by the nonnative Asian tapeworm (Bothriocephalus acheilognathi), and competition 

with and predation by nonnative fish species.” 97

With respect to the recent stabilization in humpback chub population, GCMRC reported:

“The exact causes of the stabilization of the adult population and increased 

numbers of young humpback chub cannot be specified at this time. However, 

humpback chub in Grand Canyon are thought to have benefited from several 

changes, including the experimental removal of nonnative fish, experimental 

water releases, and drought-induced warming.”

It is not clear whether an end of the drought would reverse the current stabilized trend, 

given river conditions and continued adaptive management measures.

6.7. Habitat Disruption and Effects on Species – Hydropower Function Case

As described in Section 6.5.1, the Hydropower Function Case assigns the impacts of only the 

construction and operation of the power plant to hydropower. It is the difference between the 

project as it currently operates and the project as if it were not operated for power generation.

6.7.1. Riparian/Wetland Habitat Disruption

This indicator represents habitat losses on the low side of the riparian zone. Power 

operations cause somewhat higher water surface elevations than would be caused by releases 

for water delivery alone. The 1995 Glen Canyon Dam Operation EIS estimated that current 

power operations would reduce riparian/wetland habitat by 16.5 percent, or 66 hectares.

However this would be a short-term loss. Any habitat lost along the low side of the riparian 

zone because of the somewhat elevated water surface would be replaced along the high side 

by vegetation supported by the somewhat raised water table.

6.7.2. Loss of Key Species: Humpback Chub

The loss of key species, i.e. humpback chub, because of power operations could not be 

calculated due to scientific uncertainty. With available data it is impossible to distinguish the 

effect of power operations from other environmental factors. The humpback chub population 

 97 U.S. Department of Interior, USGS Fact Sheet 2006-3109 Final. “Grand Canyon Humpback Chub Population 

Stabilizing.” July 2006. Available at www.gcmrc.gov/files/pdf/fs_2006_3109.pdf.
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has been affected by parasites, competition with and predation by other species, and lower, 

warmer flows. In addition some perceived population changes may be attributable to 

methodological artifacts.

Figure 6.10. Age Structured Mark Recapture Models of Grand Canyon HBC Population

Source: USGS98

6.8. Summary LCI Results

The life-cycle inventory results for the Glen Canyon dam and hydropower generation system are 

shown in Table 6.14. 

 98Ibid.
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Table 6.14. Main Life-Cycle Inventory Results for the Glen Canyon Hydropower Generation System 

compared to the WECC Power Pool Baseline. (Normalized to a production of 1,000 GWh.)

Glen Canyon Hydropower 

Generation System WECC Power Pool Baseline

Inventory Unit

Outputs

Emissions, air

Arsenic kg 16

Benzene kg 6

Cadmium kg 1

CFC-114 kg 34

CH4 kg 2 906,170

CO2 (annual emissions) kg 69,200 478,383,000

CO2, (construction emissions) kg 3,270

PM10, TSP, dust kg 5 197,030

HC, VOC kg 320 29,910

HCl kg 26,959

HF kg 683

Mercury kg 7

Manganese kg 14

NOx kg 1,005 956,413

Lead kg 10

Rad. act. Rn-222 GBq 2,910

Rad. act. noble gases GBq 250

SO2 kg 45 731,940

Emissions, water --

Energy

electric power MWh 1,000,000

Hazardous waste

Resources

Coal kg 3,726 200,080,000

Lignite kg

Crude oil kg 21,460 3,631,900

Natural gas kg 31 48,502,000

Uranium in ore kg U 0.003 3,048

6.9. LCSEA Results 

From the LCI data, the LCSEA indicator results have been calculated, using the appropriate 

stressor and environmental characterization factors, as discussed in Sections 2 and 3. In Table 

6.15, LCSEA indicators are summarized for the Glen Canyon Hydropower Generation System 

and the WECC regional power pool. 
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 6-36

Table 6.15. Life-Cycle Impact Indicator Results for the Glen Canyon Hydropower Generation System, 

and the WECC Power Pool Baseline. Data are normalized to a production of 1,000 GWh.

Key Indicator Unit

Baseline:

WECC Power 

Pool

Gross Impacts 

Allocation 

Case

Hydropower 

Function 

Case

Non-Renewable Energy Resource Depletion Eq. GJ of oil 5,207,000 1,011 1,011

Water Resource Depletion Acre-feet NC 151,000 --

Terrestrial Habitat Disruption Eq. Ha disturbed 1,882 18,000 --

Aquatic (Lake) Habitat Disruption Eq. Ha disturbed -- -- --

Aquatic (Lake) Habitat Created Eq. Ha disturbed NC 20,000 --

Aquatic (River) Habitat Disruption Eq. river miles 35* 160 --

Riparian/Wetland Habitat Disruption Eq. Ha disturbed 3,175* 9,997 66

New Riparian/Wetland Habitat Created Eq. Ha disturbed NA 285,300 --

Loss of Key Species: Humpback Chub % loss of key species NA 50% loss NC

Accumulated GHG Radiative Force Loading Eq. t CO2 500,000 71 71

Acidification Loading (Oceanic) Eq. t CO2 165,000 23 23

Acidification Loading (Regional) Eq. t SO2 6.5 -- --

Ground Level Ozone Loading t O3 8.9 -- --

Particulate Matter Loading Eq. t PM10 12.2 -- --

Pulmonary Toxic Chemical Loading Eq. kg benzene 5.2 -- --

Systemic Toxic Chemical Loading Eq. kg TCDD NC -- --

Neurotoxic Chemical Loading Eq. kg of mercury 5.7 -- --

Ecotoxic Chemical Loading Eq. kg of arsenic NC -- --

Radioactive Hazardous Wastes Eq. GBq Pu 239 NC -- --

(--) denotes a result of negligible or zero; (*) represents a calculated value for a highly environmentally efficient hydro facility in 

the WECC, and therefore is an extreme worst case for WECC mix; NA is not available, NC is not calculated. 

Habitat creation indicators shown in green. Results above 10,000 have been rounded to the nearest 1,000.

For the Gross Impacts Allocation Case, as reflected in the green rows, new lake habitat and new 

riparian habitats have been created as a result of the dam construction, and are accordingly 

included in the impact profile. However, these indicator results were not integrated with the 

aquatic (lake) habitat depletion or riparian/wetland habitat depletion indicators. Integration into 

a net habitat change (depletion / creation) is only possible when the habitats created and the 

habitats depleted are of comparable composition. 

• The aquatic (lake) habitat depletion indicator refers only to the depletion of existing lake 

habitat. As there was no lake habitat prior to construction of the dam, this indicator result 

is zero.

• The riparian/wetland habitat depletion indicator refers to loss of riparian/wetland habitat 

that existed at the time of dam construction. Significant losses in existing 

riparian/wetland habitats also occurred as a result of altered river flows after construction 

of the dam and particularly after institution of the ROD. The new habitat that has 

emerged at the NWHZ has undergone significant alteration in composition, in part as a 

result of the intrusion of non-native species. 

Tables 6.16 to 6.18 present in more detail the calculations used to determine the non-renewable 

energy resource depletion, accumulated GHG radiative force loading and oceanic acidification 

loading indicator results. 
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 6-37

Table 6.16. Non-Renewable Energy Resource Depletion Results for the Glen Canyon Hydropower 

Generation System. Data are normalized to a production of 1,000 GWh.

Non-renewable 

Energy 

Resource Energy Stressor

Equivalent

Energy 

 Resource 

Depletion Factor

Equivalent

Resource

Depletion Resource Characterization Resource (RDF25): Depletion

Inventory Consumed Factor (SCF) Consumed Rate of dep. /

Resource (t) (GJ/t) (GJ) Rate of oil depl. (GJ oil eq.)

Crude oil 21 45.6 979 1.0 979

Natural gas 0.03 53.4 2 0.94 2

Coal 4 28.0 104 0.28 30

Uranium in ore 3.4E-06 900,000 3 0.54 2

Electric Power 

System:

Glen Canyon

1,088 1,011

Table 6.17. Accumulated GHG Radiative Force Loading Results for the Glen Canyon Hydropower 

Generation System. Data are normalized to a production of 1,000 GWh.

Accumulated 

GHG Radiative Life-Cycle Global Gross Environment Net

Force Loading Inventory Warming Emission Characterization Emission

Inventory Result Potential Loading Factor (ECF) Loading 

Emission (t/a) (t CO2 eq./t) (t CO2 eq.) (t CO2 eq.)

Fossil CO2

(construction) 3.3 1.0 3 0.46 2

Fossil CO2

(operation) 69 1.0 69 1.00 69

Electric Power 

System:

Glen Canyon 

72 71

Table 6.18. Acidification Loading (Oceanic) Results for the Glen Canyon Hydropower Generation System.

Data are normalized to a production of 1,000 GWh.

Acidification Life-Cycle Global Gross Environment Net

Loading (Oceanic) Inventory Warming Emission Characterization Emission

Inventory Result Potential Loading Factor (ECF) Loading 

Emission (t/a) (t CO2 /t) (t CO2 ) (t CO2 )

Fossil CO2

(construction) 3.3 1.0 3.3 0.33 1.1

Fossil CO2

(operation) 69 1.0 69 0.33 22.8

Electric Power 

System:

Glen Canyon 

72 23.9

Figure 6.11 provides a graphic representation of the impact profile of the Gross Impacts 

Allocation Case. This graphic representation is limited in that it does not include a representation 

of created lake or riparian habitats, as discussed further in Section 6.9.
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 6-38

Figure 6.11. Environmental Impact Profile of Glen Canyon Hydropower Generation System, 

Gross Impacts Allocation Case, relative to the WECC baseline, per 1,000 GWh

Environmental Performance Declaration

Environmental Performance Declaration

Gross Impact Allocation Case
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 6-39

6.10. Discussion of Results 

All results for the Glen Canyon hydropower generation system are shown in comparison to the 

WECC regional power pool (Table 6.19). 

Table 6.19. Percent Deviation of the Glen Canyon Dam Category Indicator Results

Compared to WECC Baseline, per 1,000 GWh

Gross Impacts 

Allocation Case

Hydropower Function 

Case

Indicator Units

WECC 

Regional 

Power Pool

Baseline

Impact 

Profile

% change 

in impact 

levels 

relative to 

baseline

Impact 

Profile

% change 

in impact 

levels 

relative to 

baseline

Energy Resource Depletion Eq. GJ oil 5,207,000 1,011 +99% -- +99%

Water Resources Depleted Acre-feet NC 150,000 -99% -- +99%

Terrestrial Habitat Disruption Eq. ha depleted 1,882 18,000 -99% -- +99%

Aquatic (Lake) Habitat Disruption Eq. ha depleted -- -- +99% -- +99%

Aquatic (Lake) Habitat Creation Eq. ha created NC (20,000) * Not 

included -- * Not included

Aquatic (River) Habitat Disruption Eq. river miles 35* 160 -99% -- +99%

Riparian/Wetland Habitat Disruption Eq. ha depleted 143* 9,997 -99% 66 +99%

Riparian/Wetland Habitat Creation Eq. ha created NC (95,000) * Not 

included -- * Not included

Loss of Key Species: Humpback Chub % loss NA 50% loss 0% NC +99%

Accumulated GHG Radiative Force 

Loading Eq. t CO2 500,000 71 +99% -- +99%

Acidification (Oceanic) Eq. t CO2 165,000 23 +99% -- +99%

Acidification (Regional) Eq. t SO2 6.5 -- +99% -- +99%

Ecotoxic Chemical Loading (Soil/Water) Eq. kg of arsenic NC -- +99% -- +99%

Ground Level Ozone Loading t O3 8.9 -- +99% -- +99%

Particulate Loading Eq. t PM-10 12.2 -- +99% -- +99%

Pulmonary Toxic Chemical Loading Eq. kg benzene 5.2 -- +99% -- +99%

Systemic Toxic Chemical Loading Eq. kg TCDD NC -- +99% -- +99%

Neurotoxic Chemical Loading Eq. kg of 

mercury

5.7 -- +99% -- +99%

Radioactive Hazardous Wastes Eq. GBq. Pu 

239 NC -- +99% -- +99%

 (--) denotes a result of negligible or zero; (*) represents a calculated value for a highly environmentally efficient hydro facility 

in the WECC, and therefore is an extreme worst case for WECC mix; NA is not available, NC is not calculated. 

Results above 10,000 have been rounded to the nearest 1,000.

* Habitat creation indicator results were not included in the calculation of the Environmental Performance Index. Further 

discussion regarding the altered composition of new riparian habitat and the new lake habitat is recommended to determine 

whether such indicators should be included.

Indexing the percent to which each impacts was reduced or higher than the WECC provides a 

detailed mapping of the impact profile on the Glen Canyon Hydropower Station. The 

Environmental Performance Index (EPI) reflects the relative change in impact levels that 

occurred as a result of: 1) dam construction, and 2) the ROD. As shown in the table, the 
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 6-40

individual indicator ratios that are used to calculate the Glen Canyon indexing tends to fall into 

extremes, reflecting the physical scale of the Glen Canyon system and the inherent non-polluting 

nature of hydropower generation. A short discussion follows. 

6.10.1. Non-Renewable Energy Resource Depletion 

Because the Glen Canyon Hydropower System utilizes a renewable resource, only a 

negligible amount of non-renewable energy resources associated with operations and power 

transmission are depleted per 1000 GWh generation. The rating for this indicator is +99% 

relative to the WECC baseline. As discussed in Section 4, the impact profile of the WECC 

baseline itself is significantly influenced by the degree to which it is constituted by 

hydropower (28%) as compared to most other North American baselines.

6.10.2. Water Resource Depletion

In the Gross Impacts Allocation Case, the loss of water resources due to enhanced 

evaporation makes Lake Powell second only to Lake Mead (Hoover Dam) in terms of water 

depletion rates for power systems within the WECC. In the Hydropower Function Case, 

there is no water depletion impact.

6.10.3. Terrestrial Habitat Disruption 

In the Hydropower Function Case, there is minimal terrestrial habitat impact. Some impact 

is associated with transmission line ROW creation and operation. 

In the Gross Impacts Allocation Case, terrestrial habitat disruption can be accounted for by 

the loss of terrestrial habitat upstream of the Glen Canyon Dam due to the filling of Lake 

Powell. Little to no significant terrestrial habitat has been removed or disrupted downstream 

of Glen Canyon Dam, with the exception of riparian habitat which is handled as a separate 

topic and indicator in this study. 

Given the sheer size of Lake Powell, terrestrial habitat disruption per 1,000 GWh is clearly 

among the largest in the WECC thus far. Although SCS has not had the data required to 

calculate the average terrestrial habitat disruption for all hydro projects in the WECC, the 

following factors support the assigned -99% index value: 1) the fact that hydropower only 

makes 28% of the power generated in the WECC, and 2) the fact that most of the remaining 

power comes from sources involving far less terrestrial habitat disruption.

6.10.4. Riverine Habitat Disruption

In the Gross Impacts Allocation Case, the loss of 307 miles of river (186 miles of the 

Colorado river, 72 miles of the San Juan River, 32 miles of the Escalante River, and 17 miles 

of the Dirty Devil River) above Glen Canyon Dam (as measured by GIS specialists at 

WAPA), plus the disruption of 225 miles of river downstream of Glen Canyon Dam as a 

result of modified flow regulation, represents a total of 532 miles of Colorado River and 

tributaries disrupted by the building and operation of Glen Canyon Dam. Only a couple of 
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 6-41

other western hydropower installations (e.g., Hoover Dam, Grand Coulee, Shasta Dam and 

Yellowtail Dam) impact river miles on a similar scale, while the majority of power 

generation in the WECC baseline (72%) impacts little to no river miles. 

6.10.5. Riparian/Wetland Habitat Disruption 

In the Gross Impacts Allocation Case, the decline of the old high water zone (OHWZ) 

riparian habitat below the dam, combined with the inundation of riparian habitat above the 

dam, is estimated at 33,191 hectares. Even though there has been a simultaneous increase in 

the riparian habitat in the new high water zone (NHWZ), this new habitat was not included in 

calculations of the EPI. Sufficient work has not yet been conducted to know the full extent 

of change over time in terms of the diversity and abundance of the species making up the 

riparian zone. It is known that many of the indigenous species from pre-dam times also 

occur in the present day riparian zones. However, it is also well documented that some nonnative species, including one highly invasive species, the tamarisk, began to occupy the 

riparian zone after the building of the dam and has since increased significantly in both 

absolute and percent cover over time. 

In order to calculate a net increase between the old and new riparian zones, it would be 

necessary to determine that the composition of the biological community between time 

intervals (comparing pre-dam baseline conditions to post-dam conditions) is of equal 

biological integrity and ecology to allow a net increase to be estimated. If the increase is due 

to a significant shift in the biological community that comprises the riparian zone (i.e., a 

significant shift away from the non-disrupted state before the dam), then a net increase would 

not apply as the pre-dam biology/ecology would not be expanding. Instead the expansion 

would be due to a highly modified biological community, and potentially to species that 

would cause other shifts in the ecology of the area. 

GCMRC is currently conducting studies to help determine the type or extent of change over 

time. At this time, SCS’s estimate, based on worst-case assumptions, is that there has been a 

70-90% shift in species coverage away from the original composition since the building of 

the dam in at least some of the NHWZ riparian areas. Thus, given the length of the affected 

river corridor downstream of the dam, as well as the inundated riparian zones above the dam, 

SCS has assumed in indicator ratio of -99. Should ongoing studies show that the riparian 

biota is closer to the original state than qualitatively estimated in this report, the EPI could be 

improved.

The Hydropower Function Case shows a loss of 66 hectares of riparian/wetland habitat due 

to a slightly elevated high water zone. However, this loss could be offset in the long term by 

new habitat supported along the upland edge of the riparian strip by a slightly elevated water 

table.

6.10.6. Key Species Losses 

As described in Section 6.2.3, humpback chub was selected as the indicator species for this 

impact category. The highest abundance estimated since data has been collected (1989) was 
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 6-42

nearly 10,000 fish. According to the most recent scientific studies reported by GCMRC, the 

humpback chub has now stabilized at around 5,000 fish. It is not yet known whether the 

chub will continue to increase in abundance, or resume its decline, given river conditions and 

continued adaptive management measures. 

Accordingly, in the Gross Impacts Allocation Case, population losses are estimated at 50 

percent. In the Hydropower Function Case, there is no evidence that population declines 

have been caused by power operations.

6.10.7. Accumulated GHG Radiative Forcing and Oceanic Acidification Loadings 

The WECC has the lowest greenhouse gas loading per 1,000 GWh of any NERC region in 

the US solely because of the large percentage of hydropower constituting the overall power 

mix (28%). The large storage hydropower units, such as Glen Canyon, are the major pillars 

of the hydropower complex supplying the WECC. Without Glen Canyon, an additional 2.4 

million metric tons per 1,000 GWh would be emitted by the WECC, assuming that make-up 

power was derived from the same mix of WECC power sources in the same proportions. 99

In both the Gross Impacts Allocation and Hydropower Function Cases, the only significant 

source of greenhouse gas loading came from the residual greenhouse gases still in the 

atmosphere from the concrete used in the construction of the dam. This result highlights just 

how much concrete was required. However, this loading is very minor in comparison to the 

greenhouse gas loading associated with the WECC baseline.

6.10.8. Regional Air Emission and Human Health Emission Impact Categories 

Acidification (terrestrial/inland water) Loading, Ground Level Ozone Loading, Particulate 

Loading, Systemic Toxic Chemical Loading, Pulmonary Toxic Chemical Loading, Neurotoxic 

Chemical Loading

As a comprehensive assessment approach, LCIA requires that all issues of human health and 

environment linked to the power production system be included in its scope. Many studies 

tend to emphasize areas of significant impacts while ignoring those areas of negligible 

impacts. This study confirms that Glen Canyon does not contribute to human-health or 

regional environmental impacts. All regional impact indicators had negligible loadings. 

6.10.9. Eco-toxic Chemical Loading and Radioactive Wastes 

There were no impacts related to Glen Canyon operations. 

 99 If hydropower were to be decommissioned throughout the WECC, the overall greenhouse gas loading for the 

WECC would jump by 43%, from 497,000 to 715,000 eq. tons CO2 /1000 GWh, assuming that this power was 

made up consistent with the current WECC power mix. 
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 6-43

6.11. Next Steps

6.11.1. Impact Allocation According to Economic Benefits

Hydropower projects are unique among power generation systems in their service of multiple 

functions. In the Gross Impacts Allocation Case, all impacts associated with the Glen 

Canyon project were allocated to hydropower generation. This worst-case allocation ignores 

the other key functions served by the dam, including land reclamation, flood control, water 

storage and recreation. Even under this worst-case allocation, this study confirms the fact 

that (and quantifies the extent to which) Glen Canyon contributes positively to the WECC 

baseline per 1000 GWh production in terms of energy resource depletion, greenhouse gas 

loadings, oceanic acidification, regional air impact loadings, and hazardous waste.

It is a matter for others to consider as to whether the remaining impacts should be reallocated 

among the various functions served by the Glen Canyon project. However, as a next step, 

SCS would suggest that the impacts of Glen Canyon be recalculated given a range of 

allocation approaches. For example, where no other scientifically-based allocation methods 

are available, LCIA allows the environmental impacts to be allocated proportionally to a 

project’s economic benefits.

6.11.2. Determining Credits for Created Riparian and Aquatic (Lake) Habitat

As discussed in this Section, it was not possible with the available data and project budget to 

adequately evaluate the quality of lake and riparian habitats created. As such, although these 

habitats were identified and quantified, they were not included in EPI calculations. Once a 

quality factor is assigned to these habitats (i.e., an environmental characterization factor), it 

will be possible to incorporate them into the calculation. This could significantly improve 

the Glen Canyon EPI, as any amount of created habitat will add to the overall rating. 

6.11.3. System Assessment

As noted earlier, the degree to which the operations of the Glen Canyon Hydropower Station 

fit within the larger Colorado River system of hydropower plants was not addressed in the 

current study. For instance, the contribution of hydropower to the CRSP from Aspinall and 

Flaming Gorge dams was not taken into consideration, despite their role in supporting the 

load following function. Nor did this study take into consideration the degree to which Glen 

Canyon water storage decisions are influenced by the needs of Hoover Dam.

SCS would recommend that an extended analysis of the Colorado River hydropower system, 

be considered.
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report

Supplemental Report

Life Cycle Impact Assessment Methodology 

Applied To Thermal Generation Technologies 

Compared to the WECC Baseline:

A Conceptual Demonstration

Prepared for the Western Area Power Administration,

the United States Bureau of Reclamation,

Tri-State Generation and Transmission Association, Inc.

March 2009

Scientific Certification Systems, Inc.

2200 Powell Street, Suite 725

Emeryville, CA 94608

510-452-8000

PROJECT AUTHORS/CONTRIBUTORS

Stanley Rhodes, Ph.D. — Project Manager, Senior LCSEA Practitioner

Fjalar Kommonen — Senior LCSEA Practitioner and Modeler

Chet Chaffee, Ph.D. — Senior LCA Practitioner

Linda Brown — Senior Editor and Project Support

Neil Thomas — GIS Specialist

S. Clayton Palmer – Environmental Economist

Bill Karsell -- Biologist
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. S-1

Life Cycle Impact Assessment Methodology 

Applied to Thermal Generation Technologies 

Compared to the WECC Baseline:

A Conceptual Demonstration

Description of Supplemental Report

The LCIA method, applied to renewable electrical generation technologies, as shown in 

this report, is a useful tool for understanding the environmental impact of different electrical 

renewable generating technologies. The case studies used here are a large hydroelectric power

plant on a major river in the Western United States and a wind generator in the same U.S. region. 

In order to understand the context in which these technologies exist, their environmental impacts 

were compared to the existing WECC baseline.

The LCIA method holds promise for thermal generating technologies as well. As part of 

its commission from Western, SCS gathered data from two thermal electric power plants: 

Colstrip, a coal-fired power plant in western Montana; and a generic natural gas-fired power 

plant in the western United States.

Because only public data were available, detailed LCIA assessments could not be made. 

The goals of this task are: (1) to demonstrate how an LCIA method might be used in the case of a 

thermal generator; and (2) to identify problems that might arise in a complete LCIA analysis of 

power plants similar to those chosen for this demonstration project. 

SCS has labeled this as a supplemental report. It differs significantly from the LCIA 

assessment done for Glen Canyon Dam and the Stateline Wind project in that it lacks data from 

specific categories of the life cycles of these electrical generators. For example, we had no data 

on the coal supply contract for the Colstrip facility. Therefore in order to carry out a more 

detailed analysis we used some generic information about the environmental effects of coal 

mining generally. This data gathering helped us to understand more specifically what data would 

be needed – in addition to those that are publicly available – to complete an LCIA assessment of 

a coal-fired power plant. 

What follows is a detailed description of an LCIA method applied to two thermal power 

plants using data that are readily available. Again, as with the renewable technologies assessed in 

our earlier report, the environmental impacts of these two generators are compared to the 

detailed WECC baseline in order to make the results comparable to the earlier report on the two 

renewable technologies.

Significant insights have been gained in studying an LCIA method approach to 

examining the environmental footprint of these two thermal technologies. With these new 

insights, a complete and cogent LCIA analysis and Life Cycle Impact Declaration could be 

completed if a complete data set were used. 
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 7-1

Section 7.

COLSTRIP COAL POWER GENERATION SYSTEM

7.1. Project Description and Background

7.1.1. Project Description

Under this project, SCS evaluated the utility of the LCIA methodology to determine the 

ecological footprint of the Colstrip electric power generation system. The resulting impact 

profile was then compared to WECC baseline impact profile. 

7.1.2. Project Background 

The importance of coal as an electricity fuel source is undisputed. Its abundance, domestic 

accessibility, relatively low cost, and dispatch reliability make it the cornerstone of any 

future energy scenario for the US economy. At the same time, concerns about the 

environmental and human health impacts of coal combustion persist. 

Past LCIA studies of coal power have demonstrated that the actual levels of impacts can vary 

quite widely, depending upon such factors as: 1) the assay of coal inputs; 2) the method of 

mining; 3) the type of energy generation at the power plant; 4) the type of pollution control 

technologies employed; and 5) the location of the mine and power plant relative to areas of 

high population density or areas susceptible to exceedance of environmental thresholds.100 

Given the skepticism with which many policymakers and stakeholders regard coal power, an 

important objective of this project was to demonstrate the comprehensive reach of the 

LCSEA technique in establishing an accurate impact profile of coal power generation 

systems in light of these variables. 

Although strictly speaking, the Colstrip power plant is situated on the MAPP side of the 

borderline between the WECC and MAPP regional power pools in the state of Montana, the 

decision was made to compare the Colstrip power generation to the WECC baseline impact 

profile for consistency with the other projects included in this supplemental report.

 100 Scientific Certification Systems, Inc. Life-Cycle Stressor Effects Assessment of the PJM Regional Power Pool 

and Selected Exelon Assets Within the PJM. December 2001. Scientific Certification Systems, Inc. An 

Environmental Assessment of Selected Canadian Electric Power Generation Systems Using a Site-Dependent LifeCycle Impact Assessment Approach. February 2005.
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 7-2

7.2 Colstrip Power Generation System Description

7.2.1. Colstrip Station Power Plant

The Colstrip power plant is located in the town of Colstrip in southeastern Montana, east of 

the state’s most populous city, Billings (Figure 7.1).101 The four coal-fired generating units 

that comprise the plant have a combined generation capacity of 2,094 MW. At this size, 

Colstrip is the second largest coal-fired project west of the Mississippi. The two older units 

— Units 1 and 2 — each with a capacity of about 307 MW, began providing power 

commercially in 1975 and 1976. The more recently built units — Units 3 (1984) and 4 

(1986) — each have more than twice the capacity of the older units, about 750 MW per unit. 

The plant is co-owned by PPL 

Montana LLC, a subsidiary of PPL 

Generation LLC, Portland General 

Electric Company, Puget Sound 

Energy, Inc., PacifiCorp, AVISTA 

Corporation and NorthWestern 

Energy LLC. PPL is the largest of the 

owners, with a 50% stake in Units 1 

and 2, and a 30% stake in Unit 3, for a 

combined generating capacity of 529 

MW. 

The plant’s utilization of low-sulfur coal and state-of-the-art scrubbers enables it to keep 

sulfur dioxide emissions below the levels mandated under Phases One and Two of the Clean 

Air Act. The efficiency of the flue gas desulfurization (FGD) equipment installed at Units 1 

and 2 is 76%. At the newer Units 3 and 4, the FGD efficiency is 94.5%. Flue gas particle 

removal efficiency is 99% at Units 1 and 2, 98.8 % Unit 3 and 4. The plant also meets US 

EPA standards for nitrogen oxide emissions.

A schematic of the model used for LCA calculations of the Colstrip plant is shown in Figure 

7.2. The entire system modeled for the assessment includes the power plant itself, and the 

following main upstream processes: coal mining and transport, limestone production and 

transport, primary oil refining and fuel distribution, natural gas production, processing and 

distribution. These unit processes, shown in the following simplified schematic, were derived 

from the KCL-ECO LCI model.

 101 http://www.pplweb.com/ppl+generation/coal+plants/colstrip.htm

Figure 7.1. Colstrip Power Plant
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© 2009. Scientific Certification Systems, Inc. Page 7-3

7.2.2. Coal Assay, Mining and Transport

The Rosebud Mine is operated by Western Energy Company, a surface coal mining 

subsidiary of Westmoreland Mining LLC (part of Westmoreland Coal Company).102 

According to the company website, “Colstrip is one of the region’s most cost-efficient and 

cleanest power plants.” 

The 25,000-acre Rosebud surface mine complex is located near the town of Colstrip and the 

Northern Cheyenne Indian Reservation. It produces approximately ten million tons per year 

from three active pits.103 In 2004, the mine produced 12.7 million tons. Coal reserves and 

deposits are estimated at 502 million tons. 

Until 1958, the coal mined from this location was used to power Northern Pacific Railroad 

locomotives. After locomotives were switched to diesel fuel, coal mining at the site was 

suspended. After a ten-year hiatus, coal mining was resumed in 1968, this time to supply 

coal for electric power generation. Almost all of the coal mined at Rosebud is sold to the 

Colstrip Station, built adjacent to the mine, under long-term contracts. The power plant was 

specifically designed to burn Rosebud coal, which has a heat content of 8,529 BTU/lb and a 

sulfur content of 0.74%.

Rosebud coal is delivered to the Colstrip Station primarily via conveyor belts, and also partly 

by truck and rail.

 102 www.westmoreland.com/coal.asp?topic=westmoreland_mining#rosebud 103 All tons referenced in this section are short tons.

Figure 7.2. Major Unit Processes of 

the Colstrip Electric Power 

Generation System
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 7-4

The company lists total disturbed acreage as 15,255 acres, plus an additional 6,969 reclaimed 

acres. According to the company, “Reclamation activities consist of filling the voids created 

during coal removal, replacing sub-soils and top-soils and then re-establishing the vegetative 

cover. At the conclusion of reclamation activities, the area disturbed by mining will look 

similar to what it did before mining begun.”104 An example of reclamation activities is 

described on the Montana State University Ecosystem Restoration website for the Eagle 

Rock site located at the Rosebud mine.105

7.2.3. Transmission

A 500-kV transmission system transfers Colstrip power to markets within and to the west of 

state of Montana.

106 The length of transmission lines from Colstrip to the nearest tie-in had 

not yet been determined at the time of this writing.

7.3. Baseline Case: The WECC Regional Power Pool

The averaged impact profile for power generated in the WECC power pool, per 1,000 GWh, 

serves as the baseline impact profile for comparison. A detailed description is provided in 

Section 6 of this report. 

7.4. Data Sources 

7.4.1. Colstrip Station

The data for LCI modeling of the Colstrip Station unit processes were derived from Colstrip 

documentation for plant year 2000 contained in the EGRID 2002 database, as well as from 

data submitted in EIA forms. The information covered boilers, flue gas desulfuring and 

generators.

7.4.2. Rosebud Mine

Data related to coal mining at the Rosebud mine was obtained from the Westmoreland Coal 

Company website and the RDI CoalDat coal transaction database (2001).107 

7.4.3. Additional Emissions Data for Coal Plant Operations from SCS LCSEA Database

Data from recent LCSEA studies served as a valuable benchmark for the current study. For 

instance, during a study recently completed for the Canadian Electricity Association, SCS 

 104 www.westmoreland.com/coal.asp?topic=coal_overview#chart 105 ecorestoration.montana.edu/mineland/histories/coal/eagle_rock/default.htm. 106 http://www.northwesternenergy.com. Northwestern Energy is a co-owner of the transmission lines from 

Colstrip, and leases 30% of the power generated by Unit 4 of the Colstrip Station. The Northwestern Energy's 

electric transmission system services more than two-thirds of Montana, with voltage levels ranging from 50,000 to 

500,000 volts. Its transmission system has interconnections to five major transmission systems located in the 

WECC area, as well as one interconnection to a system that connected with the MAPP region. 107 http://www.westmoreland.com/coal.asp?topic=westmoreland_mining#rosebud; RDI, CoalDat Database, 2001.
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was given an opportunity to review detailed privately held documents related to an Albertabased coal power generation system. Review of these documents enabled SCS to confirm 

many assumptions that otherwise would have had greater uncertainty. One example were the 

detailed data provided regarding the routes of exposure for heavy metal releases, which 

confirmed that dispersion into the receiving environment was limited and that potential 

uptake into either the food chain or water systems was not significant. Given the similar 

population density of Alberta to the Montana area, similar fate and exposure routes were 

extrapolated to the Colstrip case. Such information was vital for modeling three of the four 

chronic hazardous chemical loading impact categories.

In addition, the SCS database contains: 1) numerous coal plant descriptions and estimates of 

actual emissions obtained from Title V Applications; 2) stack monitoring data compiled by 

Environment Canada confirming the mass of release for chemicals such as barium, 

chromium, copper, nickel, lead, manganese, polycyclic aromatic, and arsenic compounds, 

and acids such as hydrochloric, sulfuric and hydrogen fluoride; 3) Air Information 

Management System (AIMS) data on actual emissions of SOx, NOx, CO, VOCs, PM-10 and 

fugitive dust; 4) data from the Fossil Information Report Management System (FIRMS); and 

5) data from various NPDES, water consumption, and hazardous waste reports.

7.4.4. Ancillary Upstream Unit Processes

SCS evaluated the potential contribution of impacts from upstream unit processes — lime 

production and transport; primary oil refining and fuel distribution; and natural gas 

production, processing and distribution — and determined that site-dependent issues would 

not influence the overall Colstrip system calculations when normalized to the functional unit, 

1,000 GWh. As such, SCS modeled these unit processes based upon its extensive coal 

database, including data from European and North American operators, and in addition, 

utilized surrogate data obtained from the KCL-ECO LCI model. Sensitivity analysis was 

used to justify the use of these data. This analysis consisted of tripling the LCI values to 

determine whether this change would affect the final indicator results. Where any such 

changes were negligible, the data were accepted.

7.4.5. Dispersion Modeling of Emissions 

Dispersion modeling data directly related to the various emissions from the Colstrip Station 

were not found during the course of this research and therefore were not available for use in 

this study. SCS relied on concentric dispersion modeling approach described in Sections 3 

and 4, based on European published data.108

7.4.6. Physical Disturbance 

No data were made available to SCS pertaining to the types or degree of habitat disrupted or 

key species disturbance in connection with power generation activities. Nor could total acres 

of habitat disrupted be normalized to the total coal output from the mine due to lack of 

production data relative to the acres disturbed. While initial estimates could be ventured, 

 108 Bachmann, T. and Krewitt, W., 2001.
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such estimates would carry significant uncertainty, and would require verification. 

Specifically, the following data would be required:

• Based on prior research, including a study of 29 coal plants in the PJM regional 

power pool, and Swiss LCA data, SCS would estimate the physical footprint of the 

power plant to be between 100-120 acres (40-49 hectares).109 Information on the 

types of habitat and species disturbed by the siting of this plant would be required to 

determine indicator values.

• As noted earlier, total disturbed acreage at the Rosebud mine is reported to be 15,255 

acres. Applying the method described in Section 4, SCS would anticipate that the 

actual habitat disruption from the mine would be less than this amount. The factors 

that would be taken into consideration would be: 1) the amount of land undergoing 

reclamation; 2) the amount of land being actively mined; 3) previous uses of the land, 

prior to current mining activities to support electricity generation; and 4) the types of 

habitat and species disturbed. 

• Assuming 500 kV steel tower-supported transmission lines, the standard US regulated 

right-of-way is 160 feet. The following data is needed before SCS can determine the 

habitat disruption associated with these transmission lines: 1) distance from Colstrip 

Station to nearest tie-in line; 2) current and previous land use with the ROW zone; 3) 

number (and type) of towers; 4) habitat types for the land occupied by the 

transmission lines; and 5) maintenance schedules to clear back vegetation. For 

example, data collected for the Glen Canyon Project (Section 8) show that despite 

long transmission lines, these lines have resulted in little habitat disruption, since the 

naturally low growing vegetation has not been altered, and no vegetation maintenance 

is required.

7.5. Key Assumptions and Considerations

Classification and characterization assumptions and considerations pertinent to the Colstrip 

project and the other projects included in the current study have been discussed in Sections 3 and 

4 of this report. The following discussion focuses on issues that relate exclusively to the Colstrip 

electric power generation system and that require further elaboration. 

7.5.1. Issues Related to Impact Categories with Human Health Endpoints

7.5.1.1. Potential Hazardous Chemicals of Concern 

Toxic Release Inventory (TRI) data were available for the Colstrip plant from the US 

EPA database. However, for this modeling exercise, these data were not applicable. 

Whereas TRI data are generated for regulatory purposes based on generic EPA emissions 

factors, the LCSEA Model requires site-specific emission data in order to accurately 

assess impact indicators.

 109 Scientific Certification Systems, Inc. Life-Cycle Stressor Effects Assessment of the PJM Regional Power Pool 

and Selected Exelon Assets Within the PJM. December 2001. Also, Frischknecht, R. et Al. 1996.
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SCS relied on NREL data and data related to comparable combustion technology as the 

basis of the indicator calculation.110 One exception was the mercury emission factor, 

which was taken as reported for Colstrip in EGRID2002 (0.024 mg/kWh). 

For comparison, two sets of data for some relevant chemicals are shown in Table 7.1.

Table 7.1. Stack emission factors for coal combustion according to Colstrip TRI data as listed in 

EPA database, and data published in NREL Coal LCA 1999.

Chemical compound emitted

Colstrip:

TRI data 

mg/kWh

NREL Coal LCA:

TRI data 

(mg/kWh)

Arsenic Compounds 0.0110 0.0495

Cadmium Compounds -- 0.0041

Lead Compounds 0.0197 0.0300

Manganese Compounds 0.1689 0.0430

Mercury Compounds 0.0241 0.0366

7.5.1.2. Characterization of Wastes

Mining and plant operational wastes are potentially hazardous due to their high metal 

content (particularly slags, sludges, slurries and ashes). Dewatering practices from 

mining can involve re-injection of groundwater and, therefore, can result in 

contamination. In order to characterize the waste streams from a coal power generation 

system, both groundwater and surface water monitoring data are needed to ensure wastes 

are fully contained for the duration of their potential to leach into the receiving 

environment. Based on results from earlier studies performed by SCS, it was assumed 

for the current project that the projected waste stream management practices of the 

Colstrip system are resulting in no measurable impact on groundwater quality.

7.5.2. Physical Disturbance 

As described in Section 7.4.6, additional data collection and analysis are required before 

these indicators can be calculated.

7.5.3. Transmission 

As discussed in Section 4, a 2% loss of delivered power due to line losses in transmission 

was assumed, based on the statistical average for the transmission distances involved.

 110 NREL 1999. Spath P.L., Mann M. K., Kerr D. R.: “Life Cycle Assessment of Coal-fired Power Production.” 

NREL/TP-570-25119.
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7.6. LCI Results

The functional unit for the study is 1,000 GWh. All data pertaining to net annual generated 

electricity are normalized to 1,000 GWh to faciliate the analysis and to provide a common basis 

for comparison to the WECC baseline impact profile. LCI results are summarized in Table 7.2. 

Table 7.2. Life-Cycle Inventory Results for the Colstrip Power Generation System and 

the WECC Power Pool Baseline, per 1,000 GWh

Colstrip Power Gen. System WECC Power Pool Baseline

Inventory Unit

Outputs

Emissions, air

Arsenic kg 47 16

Benzene kg 12 6

Cadmium kg 4 1

CFC-114 kg -- 34

CH4 kg 156,770 906,170

CO2, fossil kg 1,041,720,000 478,383,000

TSP coarse kg 618,820 197,030

PM-10 (power plant) kg 188,020 NA

VOC, HC kg 3,580 29,910

HCl kg 23,850 26,959

HF kg 930 683

Mercury kg 23 7

Manganese kg 41 14

NOx kg 2,119,600 956,413

Lead kg 28 10

Rad. act. Rn-222 GBq 34 2,910

Rad. act. noble gases GBq 2 250

SO2 kg 814,220 731,940

Emissions, water -- --

Wastes NA NA

Energy

electric power MWh 1,000,000 1,000,000

Inputs

Resources

Coal kg 666,749,000 200,080,000

Crude oil kg 4,987,500 3,631,900

Natural gas kg 459,080 48,502,000

Uranium in ore111 kg U 29 3,048

Limestone/dolomite kg 15,906,000 3,183,900

-- denotes negligible or zero result; NA denotes data not available or not provided

 111 The uranium ore value in the Colstrip column reflects the fact that the grid electricity used by lime production 

and coal mining contains nuclear electricity.
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7.7. Habitat and Species Disruption 

As described in Section 7.4.6, habitat disruption and species mortality data collection and 

analysis are required before these indicators can be calculated.

7.8. LCSEA Results 

The impact indicator results are calculated for the entire system, based on the classification and 

characterization steps described in Sections 3 and 4, and incorporating the special study 

assumptions and considerations described above. These impact indicator results together 

comprise the impact profile of the Colstrip electric power generation system, as summarized in 

Table 7.3. Below, the spreadsheets in Tables 7.4 to 7.8 show examples of LCSEA indicator 

calculations by impact category. 

Table 7.3. Colstrip Impact Profile — Impact Indicator Results per 1,000 GWh Production 

Compared to the WECC Regional Baseline

Key Indicator Unit

Colstrip

Impact Profile

WECC 

Baseline

Energy Resources Depleted Eq. GJ of oil 4,042,000 5,207,000

Water Resources Depleted Acre-feet -- NC

Terrestrial Habitat Disruption Eq. ha. disturbed NC 1,882112

Aquatic (Lake) Habitat Disruption Eq. ha. disturbed NC Not broken out

Aquatic (River) Habitat Disruption Eq. river miles NC Not broken out

Riparian/Wetland Habitat Disruption Eq. ha. disturbed NC Not broken out

Loss of Key Species % loss key species NC NA113

Greenhouse Gases Eq. t CO2 1,045,000 500,000

Acidification Loading (Oceanic) t CO2 NC 165,000

Acidification Loading (Terrestrial / Inland Waterways) Eq. t SO2 111 6.5

Ground Level Ozone Loading t O3 4.9 8.9

Particulate Matter Loading Eq. t PM10 4.1 12.2

Neurotoxic Chemical Loading (ingestion) Eq. kg Hg 1.3 6

Pulmonary Chemical Loading (inhalation) Eq. kg Benzene 4 5.2

Systemic Chemical Loading Eq. kg TCDD NC NC

Eco-Toxic Chemical Loading Eq. kg As NC NC

Radioactive Waste Loading Eq. GBq Pu-239 -- NC

 (--) denotes negligible or zero result. NA is not available, NC is not calculated. 

Results above 10,000 are rounded to the nearest 1,000.

 112 As noted in Section 2, the ASTM draft standard E06.71.10 has identified four habitat disruption indicators. At the time the 

current study was initiated, however, habitat disruption calculations were collapsed under a single indicator. The WECC 

indicator result was calculated at that time.

113 Not applicable. The baseline for key species is based on pre-system species populations in the same region. See Section 3.
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Table 7.4. Project #2: LCSEA Energy Resource Depletion Results for 

the Colstrip Power Generation System, per 1,000 GWh

Energy Resource Energy Stressor

Equivalent

Energy 

 Resource 

Depletion 

Factor

Equivalent

Resource

Depletion Resource Characterization Resource (RDF25): Depletion

Inventory Consumed Factor (SCF) Consumed Rate of dep /

Resource (t) (GJ/t) (GJ) Rate of oil dep (GJ oil eq.)

Uranium

 in ore 0.029 900,000 25,983 0.510 13,251

Crude oil 4,988 45.6 227,431 1.000 227,431

Natural gas 459 53.4 24,515 0.940 23,044

Coal 666,749 20.2 13,494,666 0.280 3,778,507

Power Gen. 

System:

Colstrip 

13,772,595 4,042,233

Table 7.5. Project #2: LCSEA Greenhouse Gas Loading Results for 

the Colstrip Power Generation System, per 1,000 GWh

Greenhouse Life-Cycle Global Gross Environment Net

Gases Loading Inventory Warming Emission Characterization Emission

Inventory Result Potential Loading Factor (ECF) Loading 

Emission (t/a) (t CO2 eq./t) (t CO2 eq.) (t CO2 eq.)

Fossil CO2 1,041,720 1.0 1,041,720 1.000 1,041,720

CH4 157 23.0 3,606 1.000 3,606

CFC-11 0.004 21,800.0 84 1.000 84

Power Gen. 

System:

Colstrip 

1,045,410 1,045,410

Table 7.6. Project #2: LCSEA Acidification Loading Results for 

the Colstrip Power Generation System, per 1,000 GWh

Acidification Life-Cycle Stressor Gross Environment Net

Loading Inventory Characterization Emission Characterization Emission

Inventory Result Factor Loading Factor (ECF) Loading 

Emission (t) (t SO2 eq./t) (t SO2 eq.) (t SO2 eq.)

SO2 814 1.000 814 0.070 57

NOx 2,120 0.700 1,484 0.035 52

HCl 24 0.880 21 0.070 1

HF 1 1.680 2 0.070 0

Power Gen. 

System:

Colstrip 

2,321 111
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Table 7.7. Project #2: LCSEA Ground Level Ozone Loading Results for 

the Colstrip Power Generation System, per 1,000 GWh

Ground Level Life-Cycle Stressor Gross Environment Net

Ozone Loading Inventory Characterization Emission Characterization Emission

Inventory Result Factor (SCF) Loading Factor (ECF) Loading 

Emission (t) (t O3/t) (t O3) (t O3)

NOx 1,060 1.000 1,060 0.005 5

CH4 78 0.010 1 0.005 0

VOC, HC 2 0.550 1 0.005 0

Power Gen. 

System:

Colstrip 

1,062 5

Table 7.8. Project #2: LCSEA Particulate Matter Loading Results for 

the Colstrip Power Generation System, per 1,000 GWh

Particulate Life-Cycle Stressor Gross Environment Net

Matter Loading Inventory Characterization Emission Characterization Emission

Inventory Result Factor (SCF) Loading Factor (ECF) Loading 

Emission (t) (t PM10 eq./t) (t PM10 eq.) Factor (t PM10 eq.)

PM-10 807 1.00 807 0.001 1

SO2 814 1.50 1,221 0.001 1

NOx 2,120 1.00 2,120 0.001 2

Power Gen. 

System:

Colstrip 

4,148 4

7.9. Summary of Results and Discussion 

The Colstrip impact profile reflects a combination of factors, including the combustion of coal 

with low contaminant levels, the location of the plant and mine relative to areas of population 

density and areas of susceptibility to exceedance of environmental thresholds, the use of 

advanced combustion technology and high-end pollution control technologies, and the sparse 

population density of Montana. The results are summarized by indicator in Table 7.9. 
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Table 7.9. Comparing Net Indicator Results between the Colstrip Power Generation System

and the WECC per 1000 GWh

Indicator Net Indicator Results

Colstrip 

Power 

System

WECC

Baseline

Environmental Significance 

Between Net Indicator Results

Energy Resource 

Depletion 

4,042,000 GJ 5,207,000 GJ The 22% advantage associated with Colstrip as 

compared to the WECC corresponds to the fact that 

the WECC includes a high percentage (26%) of 

natural gas, which has a high RDF. The ratio between 

net and gross energy depletion for the WECC is 0.53, but 

for Colstrip is only 0.29. 

Terrestrial Habitat 

Disruption114

NC 1,880 Ha This indicator could not be calculated by based on 

information obtained to date.

Greenhouse Gas 

Loadings 

1,045,000 

Eq. t CO2

500,000 

Eq. t CO2

This result was expected, since hydropower, a 

significant contributor to the WECC baseline, does 

not emit greenhouse gases, and since the greenhouse 

gas emissions from nuclear power are limited to those 

associated with fuel enrichment. 

Acidification Loading 111 

Eq. t SO2

6.5 

Eq. t SO2

This result was expected, again given the significant 

contribution of nuclear power and hydropower to the 

WECC baseline. It should be noted that only about 

5% of the gross emissions of acidifying gases emitted 

by Colstrip result in deposition in areas of 

exceedance. 

Ground Level Ozone 

Loadings 

4.9

 t O3

8.9 

t O3

The Colstrip system had a lower ground level ozone 

loading than the WECC baseline, based on the plant’s 

location, and more specifically, the sparse population 

density of the Montana region and the low average 

background concentrations for the Montana region 

when compared to the overall WECC 

Particulate Loadings 4.1 

Eq. t PM10

12.2 

Eq. t PM10

The Colstrip system’s advantage relative to the 

WECC baseline reflects differences in population 

densities and the potential for exposure. It demonstrates a benefit of locating coal plants in rural areas. 

Neurotoxic Chemical 

Loading

1.3 

Eq. kg Hg.

6

Eq. kg Hg.

 Same comment as Particulates, above.

Systemic Chemical 

loading (heavy metals) 

NC NC This indicator could not be calculated within the 

scope of this study.

-- denotes a zero or negligible result; NC denotes that an indicator result was not calculated.

 114 Aquatic and riparian/wetland habitat disruption were not broken out in the baseline case.
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7.10. Preliminary Environmental Performance Analysis of Colstrip

The environmental performance of the Colstrip power generation system relative to the 

regional WECC power pool impact profile is presented in Table 7.10.

Table 7.10. Preliminary Environmental Performance Analysis of the Colstrip Power Generation System 

Relative to the WECC Power Pool

Indicator Unit Colstrip Impact Profile WECC Regional Power 

Pool

Energy Resources Depleted Eq. GJ of oil 4,042,000 5,207,000

Water Resources Depleted Acre-feet -- NC

Terrestrial Habitat Disruption* Eq. ha disturbed NC 1,880

Aquatic Habitat Disruption Eq. ha disturbed NC Not broken out

Riparian/Wetland Habitat Disruption Eq. ha disturbed NC Not broken out

Key Species % loss NC NA

Greenhouse Gases Eq. t CO2 1,045,000 500,000

Acidification Loading Eq. t SO2 111 6.5

Ground Level Ozone Loading t O3 4.9 8.9

Particulate Matter Loading Eq. t PM10 4.1 12.2

Neurotoxic Chem. Loading (ingestion) Eq. t Hg. 1.3 5.7

Pulmonary Chemical Ldg. (inhalation) Eq. t benzene 4 5.2

Systemic Chemical Loading Eq. kg TCDD NC NC

Eco-Toxic Chemical Loading Eq. kg As NC NC

Radioactive Wastes Eq. GBq Pu-239 -- NC

(--) denotes negligible or zero result. NA is not available, NC is not calculated. 

Results above 10,000 are rounded to the nearest 1,000.

The results presented in table 8.10 shed light on the significance of the technologies currently 

in use, and establishing a benchmark for evaluating potential upgrades and power generation 

options. Most power generation systems are no more or less efficient in their overall 

environmental performance than average power generation in their regional pools.

The Colstrip system is, on balance, more environmentally efficient than average power 

generated by the WECC power pool. As shown in Table 7.13, the calculated results for many 

impact indicators were lower than might be expected, reflecting the rural location of the 

facility and the efficiency of the combustion technology employed. If the Colstrip system 

does not cause significant disruptions to aquatic or riparian/wetland habitats, its performance 

for these indicators will be high as well.
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Section 8.

NATURAL GAS POWER GENERATION SYSTEM 

8.1. Project Description and Background

8.1.1. Project Description

Under this project, SCS evaluated the utility of the LCIA methodology to determine the 

ecological footprint of two natural gas-fired power generation systems. The resulting impact 

profile was then compared to the WECC baseline impact profile.

8.1.2. Project Background 

Two separate examples of “base load” natural gas power production were selected to 

demonstrate the environmental impacts at different levels of efficiency.

• Scenario 1: Natural gas is often the fuel for conventional singe cycle steam turbine 

(NGSC) applications. NGSC processes tend to be used for quickly varying loads and for 

partial loads corresponding to a capacity factor around 10% to 40%, as natural gas prices 

have reached rather high levels. For very short peak load periods single cycle gas turbines 

(GT) are deployed, but such GT plants are not included in this assessment. 

• Scenario 2: The higher fuel efficiency attainable with combined cycle natural gas 

(NGCC) plants has led to an increasing number of such installations, often by adding 

waste heat recovery boilers and a steam cycle to existing GT power plants. NGCC plants 

are better suited as base load plants than NGSC plants because they have better fuel 

economy. NGCC plants are also fast load followers

8.2. Power Generation System Description

8.2.1. Unit Processes

The NGSC and NGCC natural gas power generation systems include the power plants, 

upstream processes such as natural gas production, processing and distribution, and power 

transmission. A schematic of the natural gas systems modeled in this Project is shown in 

Figure 8.1. A flow diagram of a combined cycle plant is shown in Figure 8.2.
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Figure 8.1. Major Unit Processes of the Natural Gas Power Generation System 

Figure 8.2. Flow diagram of NGCC plant.

8.2.2. Plant Location

The natural gas plants modeled were assumed to be located near the Pacific coast, in the 

vicinity of Portland, Oregon. The location was chosen to be near that of the Stateline 

windfarm, the subject of Project #5.
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8.2.3. Differences between NGSC and NGCC Systems

The most relevant characteristic of NGSC plant efficiency is the heat rate, expressed as 

gigajoules (GJ) of fuel input per MWh produced. In the EGRID02 database, the utility 

natural gas power plant heat rates for NGSC plants vary from around 12,000 to 14,000 

Btu/kWh (12.6 – 14.8 GJ/MWh). In the NGSC scenario modeled in this Project, a value of 

13.1 GJ/MWh (12,417 Btu/kWh) was used. Other important characteristics are listed in the 

LCI Table 8.1.

The main difference between the NGSC and NGCC systems is the heat rate, which according 

to EGRID02 and SCS database information is 8,000 - 9,000 Btu/kWh (8.4 - 9.5 GJ/MWh). 

In the NGCC system modeled in this Project, a heat rate value of 9.23 GJ/MWh (8,749 

Btu/kWh) was used.

8.3. Baseline Case

The averaged impact profile for power generated in the WECC power pool, per 1,000 GWh, 

serves as the baseline impact profile for comparison. As described in Section 6 of this report, the 

WECC power pool system consists primarily of base load units (coal, nuclear, hydroelectric and 

natural gas), reserve units that handle seasonal/daily load demand (produced mainly by coal 

plants and combined cycle natural gas plants), and peak loading units (mostly natural gas).

8.4. Data Sources 

The modeling conducted in this Project is based on data gathered and analyzed by SCS in 

previous LCSEA studies and other published LCA studies, as well as government and industry 

reports related to natural gas power production. 

8.5. Key Assumptions

This section summarizes assumptions specific to this project only. Other assumptions and 

considerations related to the application of the LCSEA model are described in Sections 3 and 4.

8.5.1. Assumptions Related to Power Plant Modeling 

Environmental impacts from construction material manufacturing and processing were 

regarded as having low relevance in this model. No other such assumptions were necessary 

in this assessment other than those described in the general LCSEA framework as presented 

in Sections 3 and 4.

8.5.2. Habitat Disruption Assumptions 

For this project, SCS assumed that habitat disruption results calculated for the natural gas 

systems in a prior study (200 acres, or 81 hectares, per 1000 GWh) would serve as a suitable 
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surrogate value for the NGSC system modeled in this project.115 This habitat was assumed to 

be general terrestrial habitat, containing no critical habitats. The area of disturbed habitat 

was assumed to be somewhat smaller (148 acres, or 60 hectares) for the NGCC system, given 

that the size of the gas turbine, waste heat boiler, and steam turbine is estimated to be 

relatively constant per consumed fuel unit (see Table 8.3 below).

8.6. Summary LCI Results

The life-cycle inventory results for the two natural gas example systems are shown in Table 8.1. 

Table 8.1. Main Life-Cycle Inventory Results for the NGSC and NGCC Systems compared to the WECC 

Power Pool Baseline, based on KCL-ECO LCI Modeling. (Normalized to a production of 1,000 GWh.)

NGSC Power System NGCC Power System WECC Power Pool Baseline

Inventory Unit

Outputs

Emissions, air

Arsenic kg -- -- 16

Benzene kg -- -- 6

Cadmium kg -- -- 1

CFC-114 kg -- -- 34

CH4 kg 3,432,890 2,602,430 906,170

CO2, fossil kg 655,192,000 509,251,000 478,383,000

PM10, TSP, dust kg 60,916 46,228 197,030

HC, VOC kg -- -- 29,910

HCl kg -- -- 26,959

HF kg -- -- 683

Mercury kg -- -- 7

Manganese kg -- -- 14

NOx kg 1,288,326 977,420 956,413

Lead kg -- -- 10

Rad. act. Rn-222 GBq -- -- 2,910

Rad. act. noble gases GBq -- -- 250

SO2 kg 59,783 45,360 731,940

Emissions, water -- -- --

Energy

electric power MWh 1,000,000 1,000,000 1,000,000

Inputs

Resources

Coal kg -- -- 200,080,000

Lignite kg -- --

Crude oil kg -- -- 3,631,900

Natural gas kg 234,766,000 178,158,000 48,502,000

Uranium in ore kg U -- -- 3,048

Hazardous waste

(--) denotes result of negligible or zero 

 115 Private study conducted by SCS for a European government entity, 1997. 
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8.7. LCSEA Results 

From the LCI data, the LCSEA indicator results have been calculated, using the appropriate 

stressor and environmental characterization factors, as discussed in Sections 3 and 4. In Table 

8.2, LCSEA indicators are summarized for: 1) the natural gas single cycle (NGSC) power plant, 

2) the natural gas single cycle (NGCC) power plant, and 3) the WECC regional power pool.

Tables 8.3 to 8.7 present in more detail the key impact indicator calculations. 

Table 8.2. Life-Cycle Impact Indicator Results for the NGSC and NGCC systems, and the WECC Power 

Pool Baseline, based on KCL-ECO LCI Modeling. Data are normalized to a production of 1,000 GWh.116

NGSC Impact 

Profile

NGCC Impact 

Profile

Baseline:

WECC Power 

Pool

Key Indicator Unit

Energy Resources Depleted Eq. GJ of oil 11,784,000 8,943,000 5,207,000

Water Resources Depleted Acre-feet -- -- NC

Terrestrial Habitat Disruption Eq. Ha disturbed 81 60 1,880

Aquatic Habitat Disruption Eq. Ha disturbed NC NC See above

Riparian/Wetland Habitat Disruption Eq. Ha disturbed NC NC Not broken out

Key Species % loss of key species NC NC NA

Greenhouse Gas Loading Eq. t CO2 734,000 569,000 500,000

Acidification Loading Eq. t SO2 30.6 23.3 6.5

Ground Level Ozone Loading t O3 16.5 12.5 8.9

Particulates Eq. t PM10 6.4 4.8 12.2

Neurotoxic Chem. Loading Eq. t Hg. -- -- 0.0057

Pulmonary (non-carc) Chem. Loading Eq. t HF -- -- 0.5423

Pulmonary (Carc.) Chem. Loading Eq. t benzene -- -- 0.0041

Systemic Chem. Loading Eq. t TCDD -- -- NC

Radioactive Waste loading Eq. TBq Pu-239 -- -- NC

Coal Ash Waste Loading -- -- NC

(--) denotes a result of negligible or zero; NC indicates that the result was not calculated

Results above 10,000 are rounded to the nearest 1,000.

 116 It should be noted that the indicators have been slightly modified to conform to the ISO 14044 and Draft ANSI 

SCS-002 Standards since this set of calculations was completed. Specifically, a new oceanic acidification indicator 

has been added, the pulmonary loading indicators have been collapsed back to one indicator, and the coal ash waste 

loading is now addressed under the Ecotoxic Chemical Loading (Soil/Water) indicator, as shown in Sections 2 and 

6. However, these changes will not have a material effect on the impact profile of the modeled natural gas systems 

relative to the baseline. Modifications will be made to this Section before the report is released for peer review.
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 8-6

Table 8.3. Project #4: LCSEA Energy Resource Depletion Results for

NGSC and NGCC Natural Gas Power Generation Systems, Per 1,000 GWh Production

Energy Resource Energy Stressor

Equivalent

Energy

Resource Depletion FactorEquivalent

Resource

Depletion Resource Characterization Resource (RDF25): Depletion

Inventory Consumed Factor (SCF) Consumed Rate of dep /

Resource (t) (GJ/t) (GJ) Rate of oil dep (GJ oil eq.)

Uranium in ore 0.000000 900,000.0 0 0.510 0

Crude oil 0 45.6 0 1.000 0

Natural gas 234,766 53.4 12,536,504 0.940 11,784,314

Coal 0 15.5 0 0.280 0

Lignite 0 9.5 0 0.280 0

Electric Power 

System:

Natural Gas 

Single Cycle

12,536,504 11,784,314

Uranium in ore 0.000000 900,000.0 0 0.510 0

Crude oil 0 45.6 0 1.000 0

Natural gas 178,158 53.4 9,513,637 0.940 8,942,819

Coal 0 15.5 0 0.280 0

Lignite 0 9.5 0 0.280 0

Electric Power 

System:

Natural Gas 

Combined Cycle

9,513,637 8,942,819

Table 8.4. Project #4: LCSEA Greenhouse Gas Loading Results for 

NGSC and NGCC Natural Gas Power Generation Systems, Per 1,000 GWh Production

Greenhouse Life-Cycle Global Gross Environment Net

Gases Loading Inventory Warming Emission Characterization Emission

Inventory Result Potential Loading Factor (ECF) Loading 

Emission (t/a) (t CO2 eq./t) (t CO2 eq.) (t CO2 eq.)

Fossil CO2 655,192 1.0 655,192 1.00 655,192

CH4 3,433 23.0 78,956 1.00 78,956

Electric Power 

System:

Natural Gas 

Single Cycle

734,148 734,148

Fossil CO2 509,251 1.0 509,251 1.00 509,251

CH4 2,602 23.0 59,856 1.00 59,856

Electric Power 

System:

Natural Gas 

Combined Cycle

569,107 569,107
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 8-7

Table 8.5. Project #4: LCSEA Acidification Loading Results for 

NGSC and NGCC Natural Gas Power Generation Systems, Per 1,000 GWh Production

Acidification Life-Cycle Stressor Gross Environment Net

Loading Inventory Characterization Emission Characterization Emission

Inventory Result Factor Loading Factor (ECF) Loading 

Emission (t) (t SO2 eq./t) (t SO2 eq.) (t SO2 eq.)

SO2 60 1.000 60 0.060 3.59

NOx 1,288 0.700 902 0.030 27.05

Electric Power 

System:

Natural Gas 

Single Cycle 962 30.64

SO2 45 1.000 45 0.060 2.72

NOx 977 0.700 684 0.030 20.53

Electric Power 

System:

Natural Gas 

Combined Cycle 730 23.25

Table 8.6. Project #4: LCSEA Ground Level Ozone Loading Results for 

NGSC and NGCC Natural Gas Power Generation Systems, Per 1,000 GWh Production

Ground Level Life-Cycle Stressor Gross Environment Net

Ozone Loading Inventory Characterization Emission Characterization Emission

Inventory Result Factor (SCF) Loading Factor (ECF) Loading 

Emission (t) (t O3/t) (t O3) (t O3)

NOx 644 1.000 644 0.025 16.10

CH4 1,716 0.010 17 0.025 0.43

VOC, HC 0 0.420 0 0.025 0.00

Electric Power 

System:

Natural Gas 

Single Cycle 661 16.53

NOx 489 1.000 489 0.025 11.04

CH4 1,301 0.010 13 0.025 0.33

VOC, HC 0 0.420 0 0.025 0.00

Electric Power 

System:

Natural Gas 

Combined Cycle 502 12.54
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 8-8

Table 8.7. Project #4: LCSEA Particulate Loading Results for

NGSC and NGCC Natural Gas Power Generation Systems, Per 1,000 GWh Production

Particulate Life-Cycle Stressor Gross Environment Net

Matter Loading Inventory Characterization Emission Characterization Emission

Inventory Result Factor (SCF) Loading Factor (ECF) Loading 

Emission (t) (t PM10 eq/t) (t PM10 eq) (t PM10 eq)

TSP 60.9 1.00 60.9 0.008 0.5

SO2 59.8 1.50 89.7 0.008 0.7

NOx 644.2 1.00 644.2 0.008 5.2

Electric Power 

System:

Natural Gas 

Single Cycle

794.8 6.4

TSP 46.2 1.00 46.2 0.008 0.4

SO2 45.4 1.50 68.0 0.008 0.5

NOx 488.7 1.00 488.7 0.008 3.9

Electric Power 

System:

Natural Gas 

Combined Cycle 603.0 4.8

8.8. Discussion of Results 

In comparison to the WECC baseline, both natural gas power production systems are burdened 

by high energy resource depletion, which is explained by the high RDF for natural gas. The 

acidification and ground level ozone indicators results for the natural gas systems were relatively 

high as compared to the WECC baseline, due to: 1) the level of NOx emissions associated with 

these systems; and 2) the location selected for modeling these units. Not only is population 

density higher in the Portland area than the WECC average, but acidification ECFs are higher as 

well, because of soil acidification exceedances in the Pacific Northwest area, as shown in Figure 

4.2, Section 4.

On the other hand, habitat disruption associated with natural gas systems was quite low 

compared to the WECC baseline impact profile, and chronic hazardous chemical loadings were 

negligible, whereas these indicators are active within the WECC given its mix of power 

generation sources. (See Environmental Impact Profile for NGCC system, Figure 8.3.)

When comparing the two natural gas technology scenarios, the driving factor was the lower 

resource depletion (24%) associated with the NGCC system. This fuel efficiency led to 

measurable reductions in most other indicators, since emissions from natural gas combustion, 

production and transmission per produced electrical energy unit all were reduced in the same 

proportion. 
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 8-9

Figure 8.3. Environmental Impact Profile of NGCC System Compared to WECC Baseline
Renewable Electrical Generation Technologies Compared to WECC Baseline — Final LCIA Report 

© 2009. Scientific Certification Systems, Inc. Page 8-10

8.9. Environmental Performance Comparison between NGSC and NGCC

The environmental performance of the NGSC and NGCC natural gas systems in comparison to 

the WECC regional power pool are shown in Table 8.8.

As can be seen from the table, the NGCC’s 24% reduction in fuel consumption as compared to 

the NGSC improves its overall efficiency somewhat. The NGCC showed the following gains in 

performance over the NGSC scenario: 

• greenhouse gas loading — 20% gain in efficiency;

• ground level ozone — 17% gain in efficiency; 

• energy resource depletion – 14% gain in efficiency ;

• particulates loading —13% gain in efficiency ; and 

• in acidification loading — 7% gain in efficiency.

Table 8.8. Environmental Performance Index 

of the Natural Gas Single Cycle Power Plant compared to the WECC baseline.117

Indicator Unit

NGSC Impact 

Profile

NGCC Impact 

Profile

WECC 

Regional Power 

Pool

Energy Resources Depleted Eq. GJ of oil 11,784,314 8,942,819 5,207,177

Water Resources Depleted Acre-feet -- -- NC

Terrestrial Habitat Disruption Eq. ha disturbed 80 80 1,880

Aquatic Habitat Disruption Eq. ha disturbed NC -- Not broken out

Riparian/Wetland Habitat Disruption Eq. ha disturbed NC -- Not broken out

Key Species % loss NC NC NA

Greenhouse Gases Eq. t CO2 734,148 569,107 499,970

Stratospheric Ozone Depletion Eq. t CFC-11 -- -- 0.027

Acidification Loading Eq. t SO2 30.64 23.25 6.5

Ground Level Ozone Loading t O3 16.53 12.54 8.9

Particulates Loading Eq. t PM10 6.4 4.8 12.2

Neurotoxic Chem. Loading Eq. t Hg. -- -- 0.0057

Pulmonary (non-carc) Chem. Loading Eq. t HF -- -- 0.5423

Pulmonary (Carc.) Chem. Loading Eq. t benzene -- -- 0.0041

Systemic Chem. Loading Eq. t TCDD -- -- NC

Radioactive Wastes Eq. TBq Pu-239 -- -- NC

Coal Ash Waste Eq. t Hg. -- -- NC

NA is not available, NC is not calculated.

Results above 10,000 are rounded to the nearest 1,000.

 117 As noted under Section 9.7, the indicators have been slightly modified to conform to the ASTM Draft Standard 

E06.71.10 since this set of calculations was completed, as described in Sections 2 and 6. However, these 

modifications will not have a material effect on the EPI of the modeled natural gas systems relative to the baseline. 

Modifications will be made to this Section before the report is released for peer review.