United States

Environmental

Protection

Agency



# Benefits Analysis for the Final

Section 316(b) Existing Facilities

Rule

EPA 821

- R

- 14

- 005

May 2014Benefits Analysis for the Final 316(b) Existing Facilities Rule Table of Contents

May 2014 i 

# Table of Contents

1 Introduction

................................ ................................ ................................ ................................ ... 1

- 1

1.1 Summary of the Final Rule and Other Options Considered

................................ ............................ 1

- 2

1.2 Study Design

................................ ................................ ................................ ................................ ... 1

- 3

1.2.1 Coastal Regions

................................ ................................ ................................ ..................... 1

- 4

1.2.2 Great Lakes Region

................................ ................................ ................................ ............... 1

- 5

1.2.3 Inland Region

................................ ................................ ................................ ........................ 1

- 5

1.3 Orga nization of the Document

................................ ................................ ................................ ........ 1

- 5

2 Baseline Impacts

................................ ................................ ................................ ............................ 2

- 1

2.1 Introduction

................................ ................................ ................................ ................................ ..... 2

- 1

2.2 Major Anthropogenic Stressors in Aquatic Ecosystems

................................ ................................ . 2

- 1

2.2.1 Habitat Loss

................................ ................................ ................................ .......................... 2

- 2

2.2.2 Water Quality

................................ ................................ ................................ ........................ 2

- 3

2.2.3 Ov erharvesting

................................ ................................ ................................ ...................... 2

- 7

2.2.4 Invasive Species

................................ ................................ ................................ .................... 2

- 8

2.3 CWIS Impacts on Aquatic Ecosystems

................................ ................................ ........................... 2

- 8

2.3.1 Losses of Fish from IM&E

................................ ................................ ................................ ... 2

- 9

2.3.2 IM&E Effects on T&E species

................................ ................................ ........................... 2

- 12

2.3.3 Thermal Effects

................................ ................................ ................................ ................... 2

- 12

2.3.4 Chemical Effects

................................ ................................ ................................ ................. 2

- 13

2.3.5 Effects of Flow Alteration

................................ ................................ ................................ ... 2

- 15

2.4 Community

- level or Indirect Effects of CWIS

................................ ................................ .............. 2

- 15

2.4.1 Altered Community Structure and Patchy Distribution of Species

................................ ..... 2

- 16

2.4.2 Altered Food Webs

................................ ................................ ................................ ............. 2

- 16

2.4.3 Reduced Taxa and Genetic Diversity

................................ ................................ .................. 2

- 17

2.4.4 Nutrient Cycling Effects

................................ ................................ ................................ ..... 2

- 17

2.4.5 Reduced Ecological Resistance

................................ ................................ ........................... 2

- 17

2.5 Cumulative Impacts of Multiple Facilities

................................ ................................ .................... 2

- 17

2.5.1 Clustering of Facilities and CWIS on Major Rivers

................................ ........................... 2

- 18

2.5.2 Implications of Clustered Facilities for Cumulative Impacts

................................ .............. 2

- 19

2.6 Case Studies of Facility IM&E Impacts

................................ ................................ ........................ 2

- 19

2.6.1 Bay Shore Power Station

................................ ................................ ................................ .... 2

- 20

2.6.2 Indian Point Nuclear Power Plant

................................ ................................ ....................... 2

- 21

2.6.3 Indian River Power Plant

................................ ................................ ................................ .... 2

- 22

2.7 Conclusions

................................ ................................ ................................ ................................ ... 2

- 23Benefits Analysis for the Final 316(b) Existing Facilities Rule Table of Contents

May 2014 ii 

### 3 Assessment of Impingement and Entrainment Mortality

................................ .......................... 3

- 1

3.1 Introduction

................................ ................................ ................................ ................................ ..... 3

- 1

3.2 Methods

................................ ................................ ................................ ................................ ........... 3

- 1

3.2.1 Objectives of IM&E Analysis

................................ ................................ ............................... 3

- 1

3.2.2 IM&E Loss Metrics

................................ ................................ ................................ .............. 3

- 1

3.2.3 Valuation Approach

................................ ................................ ................................ .............. 3

- 2

3.2.4 Rationale for EPA’s Approach to Valuation of IM&E

................................ ......................... 3

- 3

3.2.5 Extrapolation of IM&E to Develop Regional Estimates

................................ ....................... 3

- 5

3.3 IM&E by Region

................................ ................................ ................................ ............................. 3

- 6

3.3.1 California Region

................................ ................................ ................................ .................. 3

- 6

3.3.2 North Atlantic Region

................................ ................................ ................................ ........... 3

- 7

3.3.3 Mid

- Atlantic Region

................................ ................................ ................................ ............. 3

- 8

3.3.4 South Atlantic Region

................................ ................................ ................................ ........... 3

- 9

3.3.5 Gulf of Mexico Region

................................ ................................ ................................ ....... 3

- 10

3.3.6 Great Lakes Region

................................ ................................ ................................ ............. 3

- 12

3.3.7 Inland Region

................................ ................................ ................................ ...................... 3

- 13

3.3.8 National Estimates

................................ ................................ ................................ .............. 3

- 14

3. 4 Limitations and Uncertainties

................................ ................................ ................................ ........ 3

- 15

3.4.1 Data Limitation and Uncertainty

................................ ................................ ......................... 3

- 15

3.4.2 Structural Uncertainty

................................ ................................ ................................ ......... 3

- 16

3.4.3 Parameter Uncertainty

................................ ................................ ................................ ......... 3

- 17

3.4.4 Engineering Uncertainty

................................ ................................ ................................ ..... 3

- 18

4 Economic Benefit Categories

................................ ................................ ................................ ........ 4

- 1

4.1 Economic Benefit Categories of the Rule

................................ ................................ ....................... 4

- 1

4.2 Market and Nonmarket Direct and Indirect Use Benefits from Reduced IM&E

............................ 4

- 4

4.2.1 Commercial Fisheries

................................ ................................ ................................ ........... 4

- 5

4.2.2 Recreational Fisheries

................................ ................................ ................................ ........... 4

- 5

4.2.3 Subsistence Fishers

................................ ................................ ................................ ............... 4

- 6

4.2.4 Benefits from Improved Protection to T&E Species

................................ ............................ 4

- 6

4.3 Nonuse Benefits from Reduced IM&E

................................ ................................ ........................... 4

- 7

5 Impacts and Benefits on Threatened and Endangered Species

................................ ................. 5

- 1

5.1 Introduction

................................ ................................ ................................ ................................ ..... 5

- 1

5.2 T&E Species Affected by CWIS

................................ ................................ ................................ ..... 5

- 2

5.2.1 T&E Species Identification and Data Collection

................................ ................................ .. 5

- 2

5.2.2 Number of T&E Species Affected per Facility

................................ ................................ ..... 5

- 3

5.2.3 Number of Facilities Affecting Individual T&E Species

................................ ...................... 5

- 6

5.2.4 Summar y of Overlap between Cooling Water Intake Structures and T&E Species

............. 5

- 8Benefits Analysis for the Final 316(b) Existing Facilities Rule Table of Contents

May 2014 iii 

### 5.2.5 Summary of Overlap between Cooling Water Intake Structures and Critical Habitat

.......... 5

- 8

5.2.6 Effect of the Final Rule on Facilities Overlapping T&E Species Habitat

............................. 5

- 9

5.2.7 Species with Documented IM&E

................................ ................................ .......................... 5

- 9

5.3 Societal Values for Preservation of T&E Species Affected by IM&E

................................ .......... 5

- 12

5.4 Assessment of Benefi ts to T&E Species

................................ ................................ ....................... 5

- 13

5.4.1 Economic Valuation Methods

................................ ................................ ............................. 5

- 13

5.4.2 Case Studies

................................ ................................ ................................ ........................ 5

- 13

5.4.3 Limitation and Uncertainties

................................ ................................ ............................... 5

- 20

6 Commercial Fishing Benefits

................................ ................................ ................................ ........ 6

- 1

6.1 Methodology

................................ ................................ ................................ ................................ .... 6

- 1

6.1.1 Estimating Consumer and Producer Surplus

................................ ................................ ......... 6

- 1

6.2 Benefits Estimates for Regional Commercial Fishing

................................ ................................ ... 6

- 10

6.2.1 California Region

................................ ................................ ................................ ................ 6

- 12

6.2.2 North Atlantic Region

................................ ................................ ................................ ......... 6

- 13

6.2.3 Mid

- Atlantic Region

................................ ................................ ................................ ........... 6

- 14

6.2.4 South Atlantic Region

................................ ................................ ................................ ......... 6

- 15

6.2.5 Gulf of Mexico Region

................................ ................................ ................................ ....... 6

- 16

6.2.6 Great Lakes Region

................................ ................................ ................................ ............. 6

- 16

6. 2.7 National Estimates

................................ ................................ ................................ .............. 6

- 17

6.3 Limitations and Uncertainties

................................ ................................ ................................ ........ 6

- 18

7 Recreational Fishing Benefits

................................ ................................ ................................ ....... 7

- 1

7.1 Introduction

................................ ................................ ................................ ................................ ..... 7

- 1

7.2 Methodology

................................ ................................ ................................ ................................ .... 7

- 1

7.2.1 Estimating Marginal Value per Fish

................................ ................................ ..................... 7

- 2

7.2.2 Calculating Recreational Fishing Benefits

................................ ................................ ............ 7

- 7

7.2.3 Sensitivity Analysis Based on the Krinsky and Robb (1986) Approach

.............................. 7

- 7

7.3 Benefits Estimates for Recreational Fishing by Region

................................ ................................ .. 7

- 8

7.3.1 California Region

................................ ................................ ................................ .................. 7

- 8

7.3.2 North Atlantic Region

................................ ................................ ................................ ........... 7

- 9

7.3.3 Mid

- Atlantic Region

................................ ................................ ................................ ........... 7

- 10

7.3.4 South Atlantic Region

................................ ................................ ................................ ......... 7

- 11

7.3.5 Gulf of Mexico Region

................................ ................................ ................................ ....... 7

- 12

7.3.6 Great Lakes Region

................................ ................................ ................................ ............. 7

- 13

7.3.7 Inland Region

................................ ................................ ................................ ...................... 7

- 14

7.3.8 National Estimates

................................ ................................ ................................ .............. 7

- 15

7.4 Limitations and Uncertainties

................................ ................................ ................................ ........ 7

- 16

8 Nonuse Benefit Transfer Approach

................................ ................................ ............................. 8

- 1Benefits Analysis for the Final 316(b) Existing Facilities Rule Table of Contents

May 2014 iv 

### 8.1 Introduction

................................ ................................ ................................ ................................ ..... 8

- 1

8.2 Public Policy Significance of Ecological Improvements from the Final Rule

................................ 8

- 2

8.2.1 Effects on Depleted Fish Populations

................................ ................................ ................... 8

- 2

8.2.2 Marine Protected Areas

................................ ................................ ................................ ......... 8

- 3

8.2.3 Restoration of Freshwater Ecosystems

................................ ................................ ................. 8

- 5

8.2.4 Summary of Evidence for Nonuse Values of Ecosystems Affected by CWIS

..................... 8

- 6

8.3 Benefit Transfer for Nonuse Values in the North Atlantic and Mid

- Atlantic Regions

................... 8

- 6

8.3.1 Description of the Benefit Transfer Study and BSPV Methods

................................ ............ 8

- 7

8.3.2 Benefit Transfer Methodology

................................ ................................ .............................. 8

- 9

8.4 Benefit Transfer Results for the Final Rule and Options Considered

................................ ........... 8

- 16

8.5 Habitat

- Based Methodology for Estimating Nonuse Values for Fish Production Lost to IM&E

. 8

- 17

8.6 Limitations and Uncertainties

................................ ................................ ................................ ........ 8

- 19

8.6.1 Scale of Fishery Improvements

................................ ................................ ........................... 8

- 19

8.6.2 Scale and Characteristics of the Affected Population

................................ ......................... 8

- 19

8.6.3 Fish Population Size, Type and Improvement from the Elimination of IM&E

.................. 8

- 20

9 Assessment of Social Cost of Carbon

................................ ................................ ........................... 9

- 1

9.1 Analysis Approach and Data Inputs

................................ ................................ ................................ 9

- 1

9.1.1 Electric Generators

................................ ................................ ................................ ................ 9

- 1

9.1.2 Manufacturers

................................ ................................ ................................ ....................... 9

- 6

9.2 Key Findings for Regulatory Options

................................ ................................ ............................. 9

- 7

9.2.1 Electric Generators

................................ ................................ ................................ ................ 9

- 7

9.2.2 Manufacturers

................................ ................................ ................................ ....................... 9

- 8

10 Summary of Monetized Benefits for Existing Units

................................ ................................ . 10

- 1

10.1 Introduction

................................ ................................ ................................ ................................ ... 10

- 1

10.2 Sum mary of Methods and Limitations

................................ ................................ .......................... 10

- 1

10.3 Summary of Baseline Losses and Monetized Benefits for the Final Rule and Options Considered

for Existing Units

................................ ................................ ................................ .......................... 10

- 1

11 Stated Preference Survey

................................ ................................ ................................ ............ 11

- 1

11.1 Introduction

................................ ................................ ................................ ................................ ... 11

- 1

11.2 Survey Design

................................ ................................ ................................ ............................... 11

- 2

11.2.1 Survey Format

................................ ................................ ................................ ..................... 11

- 2

11.2.2 Experimental Design

................................ ................................ ................................ ........... 11

- 4

11.2.3 Pre

- Tests

................................ ................................ ................................ .............................. 11

- 6

11.3 Sampling Frame

................................ ................................ ................................ ............................. 11

- 7

11.4 M ail Survey Responses

................................ ................................ ................................ ................. 11

- 9

11.5 Non

- Response Study

................................ ................................ ................................ ................... 11

- 12Benefits Analysis for the Final 316(b) Existing Facilities Rule Table of Contents

May 2014 v 

### 11.5.1 Non

- Response Sample

................................ ................................ ................................ ...... 11

- 13

11.5.2 Statistical Testing of Mail Survey and Non

- Response Data

................................ ............. 11

- 14

11.6 Random Utility Model

................................ ................................ ................................ ................. 11

- 17

11.6.1 Model Specification

................................ ................................ ................................ .......... 11

- 18

11.6.2 Model Estimation

................................ ................................ ................................ .............. 11

- 19

11 .6.3 Approach for Estimating Weights

................................ ................................ ..................... 11

- 20

11.6.4 Model Results

................................ ................................ ................................ ................... 11

- 21

11.6.5 Validity Tests

................................ ................................ ................................ .................... 11

- 24

11.7 Estimation of Implicit Prices and WTP

................................ ................................ ....................... 11

- 26

11.8 Method for Estimating Regional Benefits

................................ ................................ ................... 11

- 29

11.9 Results for the Final Rule and Regulatory Options Considered

................................ .................. 11

- 30

11.10 Uncertainties

................................ ................................ ................................ ................................ 11

- 32

12 Analysis of New Units at Existing Facilities

................................ ................................ .............. 12

- 1

12.1 Introduction

................................ ................................ ................................ ................................ ... 12

- 1

12.2 Analysis Approach and Benefits for IM&E Reductions at New Units

................................ ......... 12

- 1

12.2.1 Flow Reductions at New Units

................................ ................................ ........................... 12

- 1

12.2.2 IM&E Reductions and Associated Benefits per MGD

................................ ....................... 12

- 2

12.2.3 IM&E Reductions and Associated Benefits under the final Rule and Options Co nsidered for

New Units

................................ ................................ ................................ ........................... 12

- 3

12.2.4 Limitations and Uncertainties for the Analysis of IM&E Reductions and Associated Benefits

for N ew Units

................................ ................................ ................................ ...................... 12

- 6

12.3 Analysis of Social Cost of Carbon for New Units

................................ ................................ ......... 12

- 7

12.3.1 Analysis Approach and Data Inputs

................................ ................................ .................... 12

- 7

12.3.2 Key Findings for Regulatory Options

................................ ................................ ................. 12

- 8

12.4 Monetized Benefits for New Units

................................ ................................ ................................ 12

- 9

13 Summary of National IM&E Reductions and Benefits for Existing and New Units

............. 13

- 1

13.1 Introduction

................................ ................................ ................................ ................................ ... 13

- 1

13.2 Summary of Limitations and Uncertainties

................................ ................................ ................... 13

- 1

13.3 Summary of Baseline IM&E Losses and IM&E Reductions

................................ ........................ 13

- 2

13.4 Summary of National Monetized Benefits

................................ ................................ .................... 13

- 7

13.5 Results based on the SP Survey

................................ ................................ ................................ ... 13

- 11

13.6 Break

- Even Analysis

................................ ................................ ................................ ................... 13

- 11

14 References

................................ ................................ ................................ ................................ .... 14

- 1

Appendix A: Extrapolation Methods

................................ ................................ ................................ .... A

- 1

A.1 Introduction

................................ ................................ ................................ ................................ .... A

- 1Benefits Analysis for the Final 316(b) Existing Facilities Rule Table of Contents

May 2014 vi 

### A.2 Manufacturing Facilities

................................ ................................ ................................ ................. A

- 1

A.2.1 Traditional Manufacturers (MN Facilities)

................................ ................................ .......... A

- 2

A.2.2 Non

- Utility Manufacturers (MU Facilities)

................................ ................................ ......... A

- 5

A.3 Electric Power Generating Facilities

................................ ................................ .............................. A

- 6

A.3.1 Defining the Strata and Control Variables

................................ ................................ ........... A

- 7

A.3.2 Comparison of Results of the Detailed Questionnaire and Post

- Stratified Weighting

Schemes

................................ ................................ ................................ ............................... A

- 8

A.4 Adjustment for State Regulations of CWIS

................................ ................................ ................... A

- 9

Appendix B: Consideration of Potential Effects due to Thermal Discharges

................................ ... B

- 1

B.1 Introduction

................................ ................................ ................................ ................................ .... B

- 1

B.2 Genera l Effects of Thermal Discharges on Aquatic Biota and Ecosystems

................................ ... B

- 1

B.2.1 Primary Producers

................................ ................................ ................................ ................ B

- 2

B.2.2 Primary Heterotrophs

................................ ................................ ................................ ........... B

- 2

B.2.3 Zooplankton

................................ ................................ ................................ ......................... B

- 3

B.2.4 Benthic Community

................................ ................................ ................................ ............. B

- 3

B.2.5 Fish

................................ ................................ ................................ ................................ ....... B

- 3

B.2.6 Ecosystem Functions and Services

................................ ................................ ...................... B

- 3

B.3 Influence of Site

- Specific Factors and Environmental Setting on Thermal Effects

....................... B

- 4

B.3.1 Geographic Location

................................ ................................ ................................ ............ B

- 4

B.3.2 Marine vs. Freshwater Receiving Waters

................................ ................................ ............ B

- 5

B.3.3 Receiving Water Volume

................................ ................................ ................................ ..... B

- 5

B.3.4 Rate of Water Exchange

................................ ................................ ................................ ....... B

- 5

B.3.5 Local Land Use

................................ ................................ ................................ .................... B

- 5

B.3.6 Local Habitats

................................ ................................ ................................ ...................... B

- 6

B.4 Uncertainties and Limitations of Assessing Thermal Impacts

................................ ....................... B

- 6

B.5 Case Studies

................................ ................................ ................................ ................................ .... B

- 6

B.5.1 Brayton Point Station

................................ ................................ ................................ ........... B

- 7

B.5.2 Qu ad Cities Nuclear Station

................................ ................................ ............................... B

- 10

B.5.3 Point Beach Nuclear Station

................................ ................................ .............................. B

- 12

Appendix C: Details of Regional IM&E

................................ ................................ ............................... C

- 1

C.1 California Region

................................ ................................ ................................ ........................... C

- 1

C.2 North Atlantic Region

................................ ................................ ................................ .................... C

- 3

C.3 Mid

- Atlantic Region

................................ ................................ ................................ ....................... C

- 6

C.4 South Atlantic Region

................................ ................................ ................................ .................. C

- 10

C.5 Gulf of Mexico Region

................................ ................................ ................................ ................. C

- 12

C.6 Great Lakes Region

................................ ................................ ................................ ...................... C

- 14Benefits Analysis for the Final 316(b) Existing Facilities Rule Table of Contents

May 2014 vii 

### C.7 Inland Region

................................ ................................ ................................ ............................... C

- 17

C.8 National Estimates

................................ ................................ ................................ ........................ C

- 20

Appendix D: Discounting Benefits

................................ ................................ ................................ ......... D

- 1

D.1 Introduction

................................ ................................ ................................ ................................ .... D

- 1

D.2 Timing of Benefits

................................ ................................ ................................ .......................... D

- 1

D.3 Discounting and Annualization

................................ ................................ ................................ ...... D

- 3

Appendix E: List of T&E Species Overlapping CWIS

................................ ................................ ........ E

- 1

Appendix F: Detailed Methodologies for Estimating Benefits to Threatened and Endangered

Species

................................ ................................ ................................ ................................ ............ F

- 1

F.1 IM&E of Sea Turtles

................................ ................................ ................................ ....................... F

- 1

F.2 Application of Whitehead’s (1993) Benefit Transfer Approach for Estimating WTP for T&E Sea

Turtle Species

................................ ................................ ................................ ................................ .. F

- 3

Appendix G: Estimation of Price Changes for Consumer Surplus

................................ .................... G

- 1

G.1 Introduction

................................ ................................ ................................ ................................ .... G

- 1

G.2 Method ology and Results

................................ ................................ ................................ ............... G

- 1

Appendix H: Details of Regional Commercial Fishing Benefits

................................ ......................... H

- 1

Appendix I: Details of Regional Recreational Fishing Benefits

................................ ........................... I

- 1

I.1 California Region

................................ ................................ ................................ ............................. I

- 1

I.2 North Atlantic Region

................................ ................................ ................................ ...................... I

- 5

I.3 Mid

- Atlantic Region

................................ ................................ ................................ ......................... I

- 9

I.4 South Atlantic Region

................................ ................................ ................................ .................... I

- 13

I.5 Gulf of Mexico Region

................................ ................................ ................................ ................... I

- 15

I.6 Great Lakes Region

................................ ................................ ................................ ........................ I

- 19

I.7 Inland Region

................................ ................................ ................................ ................................ . I

- 23Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 1: Introduction

May 2014 1

- 1 

# 1 Introduction

EPA is issuing the final rule implementing s ection 316(b) of the Clean Water Act (CWA) to address the

enviro nmental impacts of cooling water intake structures (CWIS). The withdrawal of cooling water from

streams, rivers, estuaries and coastal marine waters by CWIS causes adverse environmental impacts

(AEI) to aquatic biota and communities in these waterbodies. T hese impacts are caused through several

means, including impingement mortality (where fish and other aquatic life are trapped on equipment at

the entrance to the CWIS and entrainment (where aquatic organisms, including eggs and larvae, are

pulled into the cooling system, passed through the heat exchanger, then discharged back into the source

body). Additional adverse effects are often associated with CWIS operation, including nonlethal effects of

impingement, thermal discharges, chemical effluents, flow mod ifications caused by these facilities, and

other impacts of variable and unknown magnitudes.

The final rule would establish national performance requirements for the location, design, construction,

and capacity of CWIS . It is designed to minimize the AEI caused by CWIS through reduction of volume,

frequency, and/or seasonality of water withdrawals. The final rule will significantly reduce impingement

mortality and entrainment (IM&E), as well as reduce the magnitude of other impacts (i.e., thermal,

chemical , and flow alteration) on aquatic ecosystems. Thus, changes in CWIS design or operation

resulting from the final rule are likely to result in enhanced ecosystem function and increased ecological

services provided by affected waterbodies.

The two broad cate gories of regulated facilities include: (1) electric generators and (2) manufacturers.

These facilities include existing electric generators and manufacturers with a design intake flow (DIF) of

at least 2 million gallons per day ( mgd ) that use at least 25 percent of the water (measured on an average

annual basis for each calendar year) exclusively for cooling purposes

.

EPA is required to conduct a benefit

- cost analysis under Executive Order s 12866 and 13563 for

economically significant rules . This report pr esents the methods EPA used for the environmental

assessment and benefits analysis of the regulatory options. EPA had three main objectives: (1) to develop

a national estimate of the baseline magnitude of IM&E at regulated facilities; (2) to estimate chang es in

I M&E of fish and invertebrates as a result of the rule ; and (3) to estimate the national economic benefits

of reduced IM&E

.

This report describes the regulatory options that EPA considered, and identifies the types of economic

benefits that are lik ely to be generated by improved ecosystem functioning under different regulator y

options

. The report also presents the basic concepts involved in analyzing these economic benefits

— including benefit categories and benefit taxonomies associated with market a nd nonmarket goods and

changes in ecological services likely to result from reduced IM&E

. Specific c hapters of the report detail

the methods used to estimate values for reductions in IM&E

. The organization of this analysis is

described in Section 1.3.

The analysis conducted in support of the final rule and discussed in this report is based on data generated

or obtained in accordance with EPA’s Quality Policy and Information Quality Guidelines. EPA’s quality

assurance (QA) and quality control (QC) activi ties for this rulemaking include the development, approval

and implementation of Quality Assurance Project Plans for the use of environmental data generated or

collected from all sampling and analyses, existing databases and literature searches, and for th e

development of any models which used environmental data. Unless otherwise stated within this

document, the data used and associated data analyses were evaluated as described in these qualityBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 1: Introduction

May 2014 1

- 2 

### assurance documents to ensure they are of known and documented quality, meet EPA's requirements for

objectivity, integrity and utility, and are appropriate for the intended use.



## 1.1 Summary of the Final Rule and Other Options Considered

EPA considered regulatory options for existing units and new units at existing facili ties. The options

apply only to existing facilities with a DIF for cooling water of 2 mgd or greater. EPA considered three

options for the existing units based on two technologies:

 Proposal Option 4: IM for Facilities > 50 mgd. Establish i mpingement m ortal ity c ontrols at a ll

e xisting f acilities that withdraw over 50 mgd; d etermine e ntrainment c ontrols for f acilities g reater

than 2 mgd DIF o n a s ite

- specific b asis

.

 Final Rule

– Existing Units: IM Everywhere. Establish i mpingement m ortality c ontrols at a ll

e x isting f acilities that withdraw over 2 mgd; d etermine e ntrainment c ontrols for f acilities g reater

than 2 mgd DIF o n a s ite

- specific b asis

.

 Proposal Option 2: IM Everywhere and E for Facilities > 125 mgd. Establish i mpingement

m ortality c ontrols at a ll e xisting f acilities that withdraw over 2 mgd DIF ; r equire f low r eduction

c ommensurate with closed

- cycle recirculating systems for entrainment control b y f acilities

g reater t han 125 mgd DIF

.

Proposal Options 4 and Proposal Option 2 above correspond to Option s 4 and 2 from EPA’s analysis for

the proposed rule ( USEPA 2011 ) with some modifications. The final rule is Option 1 from the proposed

rule with the same modifications. The final rule will estab lish entrainment controls for facility greater

than 2 mgd DIF on a site

- specific basis, as would Proposal Option 4. F indings presented in this document

assume that facilities with impoundments will qualify as having closed

- cycle recirculating systems in th e

baseline. As a result, EPA estimated zero IM&E reductions for these facilities under the final rule and

other options considered; however, these facilities remain subject to today’s rule and are assigned

administrative costs. To the extent that some of t hese facilities do not qualify as having closed

- cycle

recirculating systems in the baseline, the monetized benefits reported in this document may be

underestimates. 1



### EPA considered four regulatory options for new units at existing facilities. Stand

- alone new units are

newly built units adjacent to existing units and repowered units are existing units that have been wholly or

partially demolished and rebuilt or upgraded on the same site.

 Option A: Entrainment performance requirements for all standalone new units and all types of

repowered units.

 Option B: Entrainment performance requirements for all stand

- alone new units, and replaced or

repowered units in which turbine or condenser are newly built or replaced.

 Option C: Entrainment performance requirements for all stand

- alone new units, and repowered

new units where the turbine and condenser are newly built or replaced, but excluding high

efficiency systems.

 Final Rule

– Option D: Entrainment performance requirements for all stand

- alone new units

only.

1 EPA notes that the vast majority of these facilities occur in the Inland benefits region. Any underestimation in monetized

benefits due to the treatment of facilities with impoundments is likely to be minor because comm ercial fishing benefits and

non use be nefits are not estimated for the Inland region.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 1: Introduction

May 2014 1

- 3 

### Refer to Section VI of the preamble for a more complete description of the final rule and other options

considered for existing and new units.

This report presents EPA’s analysis of environmental and economic benefits for the final rule and the

other options co nsidered described above. EPA also presents monetized values for baseline IM&E losses

at existing facilities. The associated benefits estimates equivalent to benefits if all baseline IM&E losses

were to be eliminated. EPA emphasizes that this not a regulat ory option and that it presents baseline

values for illustration purposes only.

EPA discounted and annualized benefits for the final rule and other options considered following three

steps. First, EPA developed a time profile of benefits to show when benef its occur. Second, the Agency

calculated the total discounted present value of the benefits as of the year 2013. Finally, EPA annualized

the benefits of the final rule and other options considered, over a 51

- year time span. Refer to Appendix D

for addition al detail regarding discounting and annualization.



## 1.2 Study Design

EPA’s analysis of the regulatory options examined CWIS impacts and regulatory benefits in seven study

regions

. EPA defined the study regions on the basis of ecological similarities within regi ons (e.g.,

freshwater versus marine, similar communities of aquatic species), and on characteristics of commercial

and recreational fishing activities. The seven study regions are: California 2



### , North Atlantic, Mid Atlantic,

South Atlantic, Gulf of Mexico, Great Lakes, and Inland. The Great Lakes region includes all facilities

located on the Great Lakes, the Inland region includes all other freshwater facilities, and the remaining

five regions include coastal and estuarine facilities. Sections 1.2.1, 1.2.2, and 1.2.3 provide additional

detail regarding the definition of each region. National estimates are the sum of regional estimates. Table

1

- 1 presents the number of regulated facilities that participated in the Section 316(b) Industry Surveys and

their tota l actual intake flow by study region. EPA excluded facilities that it classifies as baseline closures

from all totals and figures presented throughout this document, including Table 1

- 1 . Baselines closures

are also excluded from all totals and figures pres ented throughout this document. EPA classifies an

electric generating facility as a baseline closure if it has retired all steam operations since the 316(b)

survey was conducted or if EPA expects that it will retire its steam capacity by 2021, according t he 2011

EIA

- 860 Database published by the Energy Information Administration (EIA) and U.S. Department of

Energy (DOE). For manufacturers, baseline closures are facilities showing materially inadequate financial

performance in the baseline. Refer to Appendi x H of the Economic Analysis (EA) for additional detail

regarding baseline closures.

The facility universe includes facilities that are subject to state regulations for CWIS in California and

New York. The California state regulation requires closed

- cycle recirculating systems for coastal electric

generating facilities while the New York state regulation requires closed

- cycle recirculating systems for

all in

- state facilities with DIF greater than or equal to 20 mgd. Fourteen surveyed facilities fall within the

scope of the California state regulation and 32 surveyed facilities fall within the scope of the New York

state regulation. 3 

### EPA determined that the state regulations are at least as stringent as the final rule and

other options considered. Facilities within the scope of the state regulations would be subject to the

requirements of the final rule, but they may not be required to install additional technologies to reduce

IM&E under the final rule. Within the benefits analysis for the 316(b) rule, EPA ass igns these facilities

baseline levels of IM&E that are commensurate with compliance with the state regulations. These

2 Includes four regulated facilities in Hawaii.

3 These counts exclude 6 California facilities and 5 New York facilities which EPA classifies as baseline closures.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 1: Introduction

May 2014 1

- 4 

### facilities do not influence the occurrence and magnitude of benefits under the final rule, similar to other

facilities which already meet the requirements of the final rule.

EPA has determined that 280 surveyed facilities currently satisfy the IM performance standard

established by the final rule or use one of several compliant technologies to achieve this goal, including

all facilities that are subject to the California and New York state regulations described above. Although

these 280 facilities are subject to the requirements of the final rule, they may not be required to install

technologies in order to comply with the final rule. Thus, t hese facilities have not been factored into the

benefits analysis for the final rule.

Table 1

- 1 : Number of Facilities and Total Mean Operational Flow, by Region a,b

Region Number of Surveyed

Facilities Flow

(billions of gallons per day)

Non

- Recirculating

Facilities c Recirculating

Facilities Total Flow

California d 21 10.65 0.00 10.65

Great Lakes 50 16.24 0.24 16.47

Inland e 566 107.56 18.06 125.62

Mid

- Atlantic 46 24.69 0.07 24.76

Gulf of Mexico 22 10.14 0.05 10.18

North Atlantic 21 5.93 0.00 5.93

South Atlantic 12 5.91 0.05 5.96

All Regions 738 181.12 18.46 199.58

a This table presents counts of unweighted facility counts and flow for surveyed facilities (excluding baseline closures). The regional

study design for the benefits analysis weights based on flow rather than facility counts. EPA did not developed weighted facility

counts by benefits region. The “All Regions” total of 738 surveyed facilities includes 532 electric generating facilities and 206

manufacturing facilities, excluding baseline closures. The total (weighted) estimated universe of facilities, excludi ng baseline

closures, is 1,065 facilities.

b The facility counts and flow presented in this table include facilities which are subject to state regulations for CWIS in Ca lifornia

and New York. Within the benefits analysis for the 316(b) rule, EPA assigns these facilities baseline levels of IM&E that are

commensurate with compliance with the state regulations.

c Recirculating facilities are facilities with closed

- cycle recirculating systems or impoundments that qualify as closed

- cycle

recirculating systems. Non

- recirculating facilities includes facilities with CWIS classified as once

- through.

d The California region includes four facilities in Hawaii. There are no coastal facilities in Oregon and one costal facility i n

Washington is classified as a baseline closure.

e A facility in Texas has intakes located in both the Inland and Gulf of Mexico regions. It is included within the Inland regio n within

in the table to prevent the double counting of facilities.

Source: U.S. EPA analysis for this report.



### 1.2.1 C oastal Regions

The five coastal regions (California, North Atlantic, Mid

- Atlantic, South Atlantic, and Gulf of Mexico)

correspond to regions defined by the National Oceanic and Atmospheric Administration ’s (NOAA)

National Marine Fisheries Service (NMFS). These r egions include facilities that withdraw cooling water

from estuar ies, tidal river s and ocean facilities within the NMFS regions.

Coastal regions are defined as follows. Th e California region includes all coastal, estuarine or tidal

facilities in the state of California, plus four facilities in Hawaii. The North Atlantic region encompasses

coastal, estuarine, or tidal facilities in Maine, New Hampshire, Massachusetts, Rhode Island, and

Connecticut. The Mid

- Atlantic region includes all coastal, estuarine or tidal facilities in New York, New

Jersey, Pennsylvania, Delaware, Maryland, the District of Columbia, and Virginia

. The South Atlantic

region includes all coastal , estuarine or tidal f acilities in North Carolina, South Carolina, Georgia, and theBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 1: Introduction

May 2014 1

- 5 

### east coast of Florida. Finally, the Gulf of Mexico region includes coastal , estuarine or tidal facilities in

Texas, Louisiana, Mississippi, Alabama, and the west coast of Florida. Coastal regions include a total of

123 facilities

.

1.2.2 Great Lakes Region

The Great Lakes region is defined in accord ance with the CWA to include facilities withdrawing cooling

water from Lake Superior, Lake Michigan, Lake Huron (including Lake St. Clair), Lake Erie and Lake

Ontario, and the connecting channels (Saint Mary’s River, Saint Clair River, Detroit River, Niagara

River, and Saint Lawrence River to the Canadian border) ( Great Lake s 1990 )

. The Great Lakes region is

comprised of 50 facilities

.

1.2.3 Inland Region

The Inland region includes all regulated facilities that withdraw water from all inland waterbodies such as

freshwater streams and rivers, lakes, reservoirs (excluding those i ncluded within the Great Lakes Region)

regardless of geographical location

. There are 566 such facilities in 39 states (including states with both

coastal and inland facilities).



## 1.3 Organization of the Document

Chapter 2 provides information on the baseline conditions of the water bodies affected by regulated

facilities. To obtain regional IM&E estimates, EPA extrapolated loss rates from facilities for which IM&E

data are available (hereafter

, model facilities), to all regulated facilities within the same reg ion. EPA’s

extrapolation methods for, and results from, regional IM&E models are described in Chapter 3

.

EPA provides an overview of all benefits (Chapter 4 ) and investigates several benefit categories in detail,

including: benefits from improved protectio n of threatened and endangered (T&E) species (Chapter 5 ),

commercial fishing benefits (Chapter 6 ), recreational fishing benefits (Chapter 7 ), and nonuse benefit

transfer (Chapter 8 )

. Chapter 9 presents benefits estimates based on the social cost of carbon. Chapter 10

summarizes benefits for existing units estimated using the methodologies described in Chapters 5 through

9. EPA also used the preliminary results of a its 316(b) stated preference study to illustrate potential

willingness to pay (WTP) for aquat ic ecosystem improvements (Chapter 11 ) . Chapter 12 presents benefit

estimates for new units at existing facilities based on benefits methodologies described in Chapter 5

through 9. Chapter 13 summarizes total national benefits for existing and new units at regulated facilities

.

Additional details regarding EPA’s benefits analysis are pre sented in Appendix A through Appendix I.

Appendix A presents the extrapolation methods used by EPA to analyze the benefits from reducing

IM&E at regulated facilities; Appendix B describes potential ecological effects due to thermal discharges;

Appendix C p resents detailed output from IM&E models; Appendix D discusses economic discounting

and the expected timing of benefits; Appendix E presents a list of T&E species likely impacted by IM&E ;

Appendix F provides details on the methodologies used to estimate th e effects of IM&E on T&E species,

and the benefits from the section 316(b) rule ; Appendix G presents EPA’s analysis of the potential for

IM&E reductions to impact the market price of commercially fished species; Appendix H presents details

of the benefits of IM&E on commercial fishing by region; and Appendix I presents detailed regional

results of the effects of IM&E on recreational fishing benefits

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chap ter 2: Baseline Impacts

May 2014 2

- 1 

# 2 Baseline Impacts

2.1 Introduction

This chapter provides a brief summary of adverse environmental impacts from the IM&E of fish and

invertebrates in CWIS used by electric power and manufacturing facilities subject to the final rule under

s ection 316(b) of the CWA.

CWIS impacts do not occur in isolation from other ongoing physical, chemical, and biological stressors

on aquatic habitats and biota in the receiving waterbody. Additional anthropogenic stressors may include,

but are not limited to: degraded water and sediment quality, low dissolv ed oxygen (DO), eutrophication,

fishing pressure , channel or shoreline (habitat) modification, hydrologic regime changes, and invasive

species. For example, many aquatic organisms subject to the effects of cooling water withdrawals reside

in impaired (i.e. , CWA 303(d) listed) waterbodies. Accordingly, they are potentially more vulnerable to

cumulative impacts from other anthropogenic stressors ( USEPA 2006 a ) . The effect of these

anthropogenic stressors on local biota may contribute to or compound the local impact of IM&E

, depending on the influence of location

- specific factors. In addition to multiple stressors acting on biota

near a single CWIS, multiple fac ilities and CWIS located in close proximity along the same waterbody

may have additive or cumulative effects on aquatic communities ( USEPA 2006 a )

.

Although it is difficult to measure, an aquatic po pulation's compensatory ability

— the capacity for a

species to increase survival, growth, or reproduction rates in response to decreased population

— is likely

compromised by I M &E and the cumulative impact of other stressors in the environment over extended

periods of time ( USEPA 2006 a ) . These cumulative impacts may lead to subtle, less

- easily observed

changes in aquatic communities and ecosystem function. These secondary impacts are difficult to isola te

from background variability, partly because of the limited scope and inherent limitations of the data

available to characterize IM&E

.

Since the aquatic habitat quality and health of the biotic community are shaped by the cumulative effect

of many factor s, it is important to characterize the environmental context of baseline impacts. This will

permit comparisons between the relative influences of CWIS

- related stressors and other factors, and result

in a more accurate estimate of the environmental impact o f the final rule.

This chapter provides a qualitative description of baseline IM&E impacts and anthropogenic stressors

found in aquatic environments affected by CWIS

.



## 2.2 Major Anthropogenic Stressors in Aquatic Ecosystems

All ecosystems and biota are subject to natural variability in environmental conditions (e.g., seasonal

perturbations), as well as periodic large

- scale disturbances in environmental settings (e.g., drought, flood,

fire, disease). Indigenous aquatic species and communities are adapted to this natural variability, such that

large

- scale events elicit a predictable loss, response and recovery cycle. Conversely, anthropogenic

stressors tend to be more chronic in nature and often do not lead to recognizable recovery phases. Instead

these stressors often lead to long

- term environmental degradation associated with lowered biodiversity,

reduced primary and secondary production, and a lowered capacity or resiliency of the ecosystem to

recover to its original state in response to natural perturbations ( Rapport and Whitford 1999 )

.

Anthropogenic stressors are present to some degree in all major waterbodies of the United States, and a re

the result of many different impacts ( Table 2

- 1 ). Four of the more important stressors include: (i) habitatBenefits Analysis for the Final 316(b) Existing Facilities Rule Chap ter 2: Baseline Impacts

May 2014 2

- 2 

### loss; (ii) degraded water quality and sediment contamination; (iii) extractive uses of aquatic resources;

and (iv) invasion by non

- indigenous spe cies ( Rapport and Whitford 1999 ) . CWIS

- related impacts are

listed here as a separate, fifth category of anthropogenic stress, one with many apparent similarities to

overharvesting. Other large

- scale stressors, such as change in watershed land use and engineering

diversions, may be present. Thus, the true impact of CWIS on an aquatic community may be partly

masked, or difficult to det ect, due to the influence of other stressors on the receiving water.

The remainder of this section summarizes effects of these four anthropogenic stressors on the waterbodies

affected by regulated facilities . CWIS impacts on the aquatic ecosystems are summ arized in Section 2.3

.

Table 2

- 1 : Anthropogenic Stressors Impacting Aquatic Ecosystems Potentially Affected, Both

Directly and Indirectly, by the Final Rule and Options Considered

Anthropogenic Stressor Impacted by the Rule

Scale of Stressor Proposal

Option 4 Final Rule Proposal

Option 2

CWIS Yes: Direct Yes: Direct Yes: Direct Local/Regional/National

Habitat loss

Development No No No Local

Eutrophication Yes: Indirect Yes: Indirect Yes: Indirect Local/Regional

Climate change No No No Regional/National/Global

Engineering diversions

Re

- routing No No No Local/Regional

Flow adjustments/removals/

modifications No No Yes: Direct Local/Regional

Water impoundments/damming No No No Local/Regional

Water quality

Eutrophication Yes: Indirect Yes: Indirect Yes: Indirect Local/Regional

Loss of riparian buffer zones No No No Local/Regional

Sedimentation No No Yes: Direct Local/Regional

Chemical pollution (organics,

heavy metals, etc.) No No Yes: Direct Local/Regional

Non

- native / invasive species Yes: Indirect Yes: Indirect Yes: Indirect Local/Regional

Extractive uses (e.g. fishing) Yes: Indirect Yes: Indirect Yes: Indirect Local/Regional

Source: U.S. EPA analysis for this report



### 2.2.1 Habitat Loss

Structural aquatic habitat is generally recognized as the most significant determinant of the nature and

composition of aquatic communities. Human occupation and restructuring of shorelines; construction and

maintenance of harbors; installation of dams, ca nals, and other navigational infrastructure; draining of

wetlands for agriculture and residential uses; and degradation of critical fish habitats have all taken a

heavy toll on the numbers and composition of local fish and shellfisheries. Most regulated fa cilities have

been built on shoreline locations where power

- generation buildings, roadways, CWIS , canals,

impoundments, and other water storage or conveyance structures have often been constructed at the cost

of natural habitat, including terrestrial, aqua tic, and wetlands.

The loss of coastal and estuarine wetlands that serve as important fishery spawning and nursery areas is

particularly severe, with an estimated historical loss of 100 million acres of wetlands since the late 1700s

( Bromberg and Bertness 2005 ; USEPA 2010 c) . Critical fishery habitat loss is not restricted to nearshore

environments. Decades of fishing activities have degraded offshore bottom habitats ( Auster and Langton

1999 ; Turner et al. 1999 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chap ter 2: Baseline Impacts

May 2014 2

- 3 

### The main impact of aquatic habitat loss is a reduction in the number of fish in the environment, a

reduction in fish spawning and nursery areas, shifts in species dominance based on available habitat, and

local extirpatio n of historical fish species. Habitat loss in adjacent shoreline areas exacerbates the effect of

CWIS losses, since many fish species affected by IM&E (e.g., bay anchovy, winter flounder) rely on

coastal wetlands as nursery areas.

In riverine environments , the effects of channelization and navigation can also lead to habitat loss. For

example, Tondreau et al. ( 1982 ) conducted a 10

- year study of the aquatic ecosystem of the Missouri River

near the Neal Generating facility in Sioux City, IA. The investig ators found that the combined effects of

channelization, heavy barge traffic, and high river flow rates had resulted in a significant loss of fish

habitat. As a result, reported IM&E is relatively minor, because local fish populations were already

greatly diminished.

2.2.2 Water Quality

Water quality is a major stressor of aquatic biota and habitats. Degraded surface water and sediment

contaminants reflect current and historical industrial, agricultural and residential land use as well as

discharges from wastew ater treatment facilities . Poor water quality can limit the numbers, composition,

and distribution of fish and invertebrates; reduce spawning effort and growth rates; select for pollution

tolerant species; cause periodic fish kills; or result in adverse ef fects to piscivorous wildlife.

CWA s ection 303(d) listings inventory, on a state

- by

- state basis, the locations of impaired waters not

meeting designated uses and the known or suspected source(s) of impairment. Figure 2

- 1 identifies

regulated facilities, t hose within two miles of a 303(d)

- listed waterbody, and those impaired for

temperature , using a database of 303(d) waterbodies assembled in October, 2010 . The map clearly shows

that facilities along the coasts, Great Lakes, and major waterways such as the Mississippi, Missouri, and

Ohio rivers are located in the vicinity of impaired waterbodies.

EPA’s analysis of regulated facilities demonstrated that the majority of facilities ( 7 4 percent) are within

two miles of a 303(d)

- listed waterbody. Table 2

- 2 summar izes the number of regulated facilities on

waterbodies impaired by any cause, by region. These include impairment due to chemical, physical, and

biological factors, categorized into biological stressors, nutrients, organic enrichment/loading,

bioaccumulati on, toxics, unknown causes, and general water quality impairment.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 4



### Figure 2

- 1 : Map of Facilities Located on 303(d) Waters and Those 303(d) Waters Listed for

Temperature in 2010Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 5 

### The most common causes of impairment for water bodies serving as 316(b) source waters are

polychlorinated biphenyls (PCBs), pathogens, mercury, as well as organic enrichment/oxygen

depletion and nutrients. The entire universe of all 303(d) water quality impairment causes is much

too diverse to cover fu lly in this section. However, below is a discuss ion of some of the more

common and important physico

- chemical impairments in aquatic environment where regulated

facilities draw cooling water from

, and discharge to

, 303(d) listed waters.

 An oversupply of nu trients can result in excessive algal production, reduced light clarity,

more frequent outbreaks of harmful algal blooms (HABs), high internal loads of

biochemical oxygen demand (BOD), and spatial and temporally variable DO levels. In

addition, eutrophicat ion can reduce or eliminate habitat

- formers such as coral reefs and

submerged aquatic vegetation (SAV), and create other adverse ecological effects.

Thermal discharges from regulated facilities can increase receiving water temperature,

which may favor form ation of blue

- green algal blooms.

 Low levels of dissolved oxygen (hypoxia) may be present in many estuaries and coastal

waters ( IWG 2010 ) , in the hypolimnia of eutrophic lakes, and in areas of high organic

loading (e.g., below wastewa ter treatment plant outfalls). DO concentrations may be

further decreased in or downstream of thermal plumes arising from cooling water return

discharges from regulated facilities. Low DO can limit the distribution of fish and

macroinvertebrates, reduce gr owth rates, and alter nutrient and carbon recycling.

 Persistent, bioaccumulative and toxic substances (PBTs) such as mercury or PCBs may

be present in waterbodies near regulated facilities, due to atmospheric deposition of local

air emissions or from histo rical uses of PCBs in electrical transformer units, in addition to

other urban or industrial sources. These PBTs can impair water uses by regulatory

restrictions or advisories regarding acceptable ingestion of fish consumption (see below),

as well as affec ting higher trophic level predators in the food chain.

 Toxic pollutants, such as metals, polycyclic aromatic hydrocarbons (PAHs), pesticides,

biofouling chemicals, or chlorine may be present in the discharge of regulated facilities.

This could lead to loc al extirpation of sensitive species, or to greatly altered biological

communities due to chronic impacts on viability, growth, reproduction, and resistance to

other stressors.

In addition to the 303(d) listings, many of the waterbodies in which the CWIS ar e located are

subject to fish advisories. Fish advisories are issued by States to protect their citizens from the

risk of eating contaminated fish or wildlife ( USEPA 2009 a)

. Fish advisories are recommendations

a nd do not carry regulatory authority, but they indicate the presence of bioaccumulative

chemicals which may pose risk for humans and piscivorous wildlife, and which may also

interfere with the reproduction and survival of taxa in lower trophic levels. 4

4 Although fish advisories do not themse lves carry regulatory authority, waterbodies may be included on 303(d)

lists because of persistent fish advisories resulting from the bioaccumulation of specified and unspecified toxics.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 6 

### Table 2

- 2 : Number of Regulated Facilities on 303(d)

- listed Waterbodies, by Impairment

and Region a

Impairment California Great

Lakes Inland Mid

Atlantic Gulf of

Mexico North

Atlantic South

Atlantic Total

Regulated Facilities 21 50 566 46 22 21 12 738

Biological Stressors

Noxious Aquatic Plants 1 1

Nuisance Exotic Species 3 3 6

Pathogens 6 9 85 5 1 9 4 119

Nutrients

Algal Growth 1 1

Nutrients 9 37 3 1 2 6 58

Organic Enrichment / Loading

Organic Enrichment

, Oxygen

Depletion 2 6 43 1 5 3 6 66

Sediment 2 3 15 2 22

Persistent, Bioaccumulative, Toxic (PBTs)

Dioxins 2 13 12 2 29

Fish Consumption Advisory

, Pollutant Unspecified 3 7 1 11

Mercury 3 24 85 3 2 2 119

P CB s 9 45 122 10 2 1 189

Pesticides 10 11 15 36

Physical Alterations

Flow Alteration 4 4

Habitat Alteration 1 7 8

Temperature 6 3 9

Turbidity 21 1 2 24

Toxics

Ammonia 1 1 2

Chlorine 1 1

Metals (Other Than Mercury) 5 4 37 6 1 53

Total Toxicity 7 4 2 1 14

Toxic Inorganics 1 1 2

Toxic Organics 3 8 2 13

Unknown / Other Causes

Cause Unknown 8 8

Cause Unknown

- Fish Kills 1 1

Cause Unknown

- Impaired

Biota 2 2 12 2 18

Other Cause 3 1 4

Water Quality Use Impairments (General)

Oil And Grease 4 3 7

pH 3 7 10

Salinity

, T DS, Sulfates

, Chlorides 1 1 6 8

Taste, Color And Odor 3 1 4

All Impairment Categories

One or More Impairments 18 46 398 38 12 20 11 543

a Waterbodies may be listed for multiple impairments and facilities may be counted in more than one row.

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 7 

### EPA’s 2008 National Listing of Fish Advisories (NLFA) database indicates that 97 percent of the

advisories are due (in order of importance) to: mercury, PCBs, chlordane, dioxins, and DDT

( USEPA 2009 a) . Fish advi sories have been issued for 39 percent of the total river miles

(approximately 1.4 million river miles) and 100 percent of the Great Lakes and connecting

waterways ( USEPA 2009 a) . Fish advisories have been steadi ly increasing over the NLFA period

of record (1993

- 2008), but these increases are interpreted to reflect the increase in the number of

waterbodies being monitored by States and advances in analytical methods rather than increasing

levels of these problemat ic chemicals.

The water quality impacts arising from the combination of operations and/or discharges of

regulated facilities and other anthropogenic sources (as indicted by the presence of widespread

fish advisories) could result in highly degraded or alt ered aquatic communities that may be

further reduced by IM&E.

2.2.3 Overharvesting

Overharvesting is a general term which describe s the exploitation of an aquatic population (e.g.,

fish, shellfish, and kelp) in an unsustainable fashion to the point of reducing or even eliminating

much of the population. Stocks of commercial and recreationally important species are reduced as

a result of fishing, but such fish catches may be sustainable if sufficient recruitment of juveniles

into the fishery can replace populatio n losses from fishing and other stressors. 5 

### Unfortunately for

many aquatic species, overharvesting has a long history and in many instances has preceded

impacts by other competing anthropogenic stressors by several centuries ( Jackson et al. 2001 )

.

Many species (and fishery stocks) subject to IM&E are also subject to overharvesting. Fo r

example, the 2011 NMFS stock status report indicated that 14 percent of federally monitored fish

stocks were being fished at rates above the maximum sustainable yield (“overfishing”), while 21

percent of species are considered over

- exploited (“overfished ”) ( NMFS 2012 c ) ; many of these

fish stocks are also subject to IM&E

. Table 2

- 3 lists 10 groups of species subject to IM&E that

are overfished or subject to overfishing. Additional detail regarding the status of stocks is

provided in Chapter 6 on commercial fishing benefits. Notably , this assessment does not include

many important fishery species not subject to federal regulation t hat may be subject to high

IM&E, nor does this assessment consider threatened and endangered (T&E) species.

Severe overfishing can drive species to ecological insignificance, where the overfished

populations no longer interact meaningfully in the food web with other species in the community,

or even to extinction ( Jackson et al. 2001 )

. The collapse of the Great Lakes whitefish fisheries has

been shown to be principally due to overfishing, although habitat alteration and introduction of a

non

- indigenous (exotic) invader (sea lamprey) were also contributory ( Rapport and Whitford

1999 )

.

5 Recruitment is the number of young fish that enter into a populati on.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 8 

### Table 2

- 3 : Depleted Commercial Fish Stocks Subject to IM&E

Stock or Stock Complex Status of Stock a Stock Region

Surfperches Overfished but not subject to overfishing b California

Atlantic Cod Overfished or subject to overfishing North Atlantic

Windowpane Overfished but not subject to overfishing North Atlantic

Winter Flounder Overfished but not subject to overfishing North Atlantic

Flounders Overfished or subject to overfishing North Atlantic

Atlantic Menhaden Subject to overfishing but not overfished North Atlantic/South Atlantic

American Shad Overfished North Atlantic/Mid

- Atlantic

Weakfish Overfished but not subject to overfishing North Atlantic/Mid

Atlantic/South Atlantic

Alewife Overfished Mid

- Atlantic

Tautog Overfished and subject to overfishing Mid

- Atlantic

a Species group may consist of many individual component species with conflicting stock statuses. The most common stock

status among the component species was designated the Status of Stock for the species group.

b "Perch" species were used as a proxy for S urfperch.

Source: NMFS 2012c and U.S. EPA analysis for this report



### 2.2.4 Invasive Species

Non

- indigenous, invasive species (NIS) are a significant and increasingly prevalent stressor in

both freshwater and marine environments ( Cohen and Carlton 1998 ; Ruiz et al. 1999 )

. Approximately 300 NIS are established in marine and estuarine habitats of the continental U nited

S tates , and that rate of invasion is rapidly increasing ( Ruiz et al. 2000 ) . Aquatic NIS are

taxonomically diverse and include plants, fish, crabs, snails, clams, mussels, bryozoans, and

nudibranchs

. Analysis of freshwater NIS indicated that between 10 to 15 percent are nuisance

species with undesirable eff ects ( Ruiz et al. 1999 ) . The adverse implications of marine and

coastal NIS are generally not as well

- characterized as those in freshwater settings.

Intera ctions between NIS and other anthropogenic stressors are likely to affect the colonization

and distribution of native species subject to CWIS impacts. Thermal discharges from regulated

facilities may extend the seasonal duration of non

- resident organisms, allowing transient summer

species to become permanently established in geographic areas beyond their historical range. For

example, in Mount Hope Bay, increased water temperature due to the Brayton Point Station

facility led to an increase in abundance of the predacious ctenophore Mneimiopsis leidyi as well

as increased overwintering in the Bay for this formerly seasonal resident ( USEPA 2002b )

.



## 2.3 CWIS Impacts on Aquatic Ecosystems

EPA has determined that multiple types of adverse environmental impacts may be associated with

CWIS operatio ns at regulated facilities , depending on site

- specific conditions at an individual

facility. Many of these facilities employ once

- through cooling water systems that impinge fish

and other aquatic organisms on intake screens if the intake velocity exceeds t hese organisms’

locomotive ability to move away. Impinged organisms may be killed, injured or weakened,

depending on the nature and capacity of the plant’s filter screen configuration, cleaning and

backwashing operations, and fish return system used to ret urn organisms to the source water. In

addition, early life stage fish or planktonic organisms can be entrained by the CWIS and

subjected to death or injury due to high velocity and pressure, increased temperature, andBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 9 

### chemical anti

- biofouling agents in the system. This IM&E can act in concert with the other

stressors identified above.

The magnitude and regional importance of IM&E is generally a function of the operational intake

volumes and the characteristics of the aquatic community in the region (see Cha pter 3 for details)

. IM&E can contribute to: impacts to T&E species (Chapter 4 ); reductions in ecologically critical

aquatic organisms, including important elements of an ecosystem’s food chain; diminishment of

organism populations’ compensatory reserves; population declines , including reductions of

indigenous species population levels, commercial fisheries (Chapter 6 ), and recreational fisheries

(Chapter 7 ); and stresses to overall communities and ecosystems, as evidenced by reductions in

diversity or othe r changes in ecosystem structure or function. In addition, fish and other species

affected directly and indirectly by CWIS can provide other valuable ecosystem goods and

services, including nutrient cycling and ecosystem stability.

The impacts of IM&E occu r at many levels of ecological organization and across a wide range of

environmental scales. Table 2

- 4 presents a summary of direct and indirect impacts of CWIS and

IM&E . The effects are identified as direct, indirect, or a combination. This table also ind icates the

relative scale (local, regional, national) of the particular effect. In most cases, EPA was unable to

estimate the magnitude of these effects due to a lack of data . T his section discuss es a subset of

these effects.

2.3.1 Losses of Fish from IM&E

The most visible direct impact of IM&E is the loss of large numbers of aquatic organisms,

distributed non

- uniformly among fish, benthic invertebrates, phytoplankton, zooplankton, and

other susceptible aquatic taxa (e.g., sea turtles). This has immediate and di rect effects on the

population size and age distribution of affected species, and may cascade through food webs.

Populations of aquatic organisms decline when recruitment rates are lower than mortality rates.

Natural sources of mortality for fish species include predation, food availability, injury, climatic

factors and disease. Anthropogenic sources of fish mortality, both proximate and ultimate,

include fishing, habitat modification, pollution, and IM&E at CWIS

. R educing IM&E will

contribute to the healt h and sustainability of fish populations by lowering the total mortality rate

for these populations.

In some cases, IM&E has been shown to be a significant source of anthropogenic mortality to

depleted stocks of commercially targeted species

. For example, IM&E [ expressed as age

- one

equivalents (A1E)] equal approximately 10 percent of the average annual recruitment to the

Southern New England/Massachusetts stock of winter flounder ( Pseudopleuronectes americanus )

( IM&E values from Chapter 3 ; recruitment data from Terceiro ( 2008 ) )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 10 

### Table 2

- 4 : CWIS Effects on Ecosystem Functions/Cumulative Impacts Potentially

Affected, Both Directly and Indirectly, by the 316(b) Rule

Category Direct/Indirect Local/Regional/

National

A. Impingement and Entrainment (direct and indirect effects)

Effects on Individuals

Loss of individuals (direct effects) Direct Local/Regional/National

Phytoplankton Direct Local/Regional/National

Zooplankton (excluding fish larvae/eggs) Direct Local/Regional/National

Invertebrates Direct Local/Regional/National

Fish Direct Local/Regional/National

Non

- fish vertebrates Direct Local/Regional/National

Species and Population

- Level Effects

Alteration of phenology of system (function of % water

reduction in stream) Direct Local/Regional/National

Altered distribution of populations Direct Local

Altered niche space Direct Local/Regional

Altered stable age distributions of populations Direct Regional

Loss of keystone species Direct Local

Loss of T&E species Direct Regional

Novel selection pressure (e.g., negatively buoyant or

stationary eggs) Direct & Indirect Local

Reduced/altered genetic diversity Direct & Indirect Regional/National

Reduced lifetime ecological function of individuals Direct Local/Regional

Community and Trophic Relationships

Altered competitive interactions Direct & Indirect Local

Disrupted trophic relationships Direct & Indirect Local

Disrupted control of disease

- harboring insects (e.g., mosquito

larvae, etc.) Indirect & Direct Local/Regional

Increased quantity of detritivores Indirect Local

Loss of ecosystem engineers (due to trophic interactions) Indirect & Direct Local

Reduced potential for energy flows (e.g. trophic transfers) Indirect Local/Regional

Species diversity and richness Direct & Indirect Local/Regional/National

Trophic cascades Indirect & Direct Local/Regional

Ecosystem Function

Altered ecosystem succession Indirect & Direct Local/Regional

Decreased ability of ecosystem to control nuisance species

(algae, macrophytes) Indirect Local

Disrupted cross

- ecosystem nutrient exchange (e.g.,

up/downstream, aquatic/terrestrial) Indirect Regional

Disrupted nutrient cycling Indirect & Direct Local/Regional

Reduced compensatory ability to deal with environmental

stress (resilience) Direct & Indirect Regional

Reduced ecosystem resistance Indirect Local/Regional

Reduced ecosystem stability (alternate states) Indirect Local/Regional

Sediment regulation Indirect Local/Regional

Substrate regulation Indirect Local

B. Thermal Effects (direct and indirect)

Novel selection pressure (e.g., thermal optima, location of

breeding, etc.) Direct & Indirect Regional/National

Altered phenology Direct Local/Regional

Links between temperature and metabolism

Dissolved oxygen (physical) Direct Local

Dissolved oxygen (bacterial, respiratory rates) Indirect LocalBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 11 

### Table 2

- 4 : CWIS Effects on Ecosystem Functions/Cumulative Impacts Potentially

Affected, Both Directly and Indirectly, by the 316(b) Rule

Category Direct/Indirect Local/Regional/

National

Ecological energetic demands Indirect Local/Regional

Ecological nutrient demands Indirect Local/Regional

Altered algal productivity Direct & Indirect Local/Regional

Shifted nutrient cycling Indirect & Direct Local/Regional

C. Chemical Effects (anti

- foulants, etc.)

Altered survival/growth/production Indirect & Direct Local

Altered food web dynamics Indirect Local

D. Altered Flow Regimes (local and system

- wide)

Altered flow velocity Direct & Indirect Local/Regional

Altered turbulence regime Direct & Indirect Local/Regional

E. Cumulative Impacts (as a concentrated number of facilities)

May push systems over the edge of nonlinearities in the

system Direct/Indirect Local/Regional

Intensified CWIS effects (as above, Section B.) Direct/Indirect Local/Regional

Intensified thermal effects (as above, Section B.) Direct/Indirect Local/Regional

Source: U.S. EPA analysis for this report



### In addition to its impact on stocks of marine commercial fish species, IM&E increases the

pressure on native freshwater species, such as lake whitefish ( Coregonus clupeaformi ) and yellow

perch ( Perca flavescens ), whose populations have seen dramatic declin es in recent years ( USDOI

2008 ; Wisconsin DNR 2003 ) . Although recovery of these species is greatly affected by fisheries

policy ( e.g., NEFSC 2008 )

, IM&E represent an additional sou rce of mortality to fish populations

being harvested at unsustainable levels.

Overall, IM&E is likely to contribute to reduction in the population sizes of species targeted by

commercial and recreational fishers, particularly for stocks that are undergoin g rebuilding.

Although these reductions may be small in magnitude compared to fishing pressure ( Lorda et al.

2000 ) , and often difficult to measure due to the low statistical power of fisheries surveys, a

reduction in mortality rates on overfished populations is likely to increase the rate of stock

recovery. Although researchers know less about the population biology of forage fish not targeted

by fishers, similar benefits are likely to accrue for these s pecies. Overall , reducing IM&E may

lead to more

- rapid stock recovery, a long

- term increase in commercial fish catches, increased

population stability following periods of poor recruitment and, as a consequence of increased

resource utilization, an increase d ability to minimize the invasion of exotic species ( Shea and

Chesson 2002 ; Stachowicz and Byrnes 2006 )

.

For many fish species, IM&E may not lead to measurable reductions in adult populatio ns. These

losses, however, are likely to reduce the compensatory ability of populations to respond to

environmental variability, including temperature extremes, heavy predation, disease, or years

with low recruitment. Additionally, because predation rates are often directly related to the

concentration of available prey, IM&E may lead to indirect population effects, whereby

reductions in a prey fish may indirectly result in reductions to predator species or increases to

species in apparent competition ( Holt 1977 )

.

Moreover, IM&E represents a novel selective pressure for fish populations. Consequently,

populations may be selected for resistance to IM&E (through behavioral or physiological

changes) at the expense of other, more “natural” evolutionary pressures. Although this may helpBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 12 

### sustain populations in the short term, it may reduce genetic diversity and population stability in

the long

- term.

2.3.2 IM&E Effects on T&E species

T&E species are species vulnerable to future extinction or at risk of extinction in the near future,

respectively. Due to low population sizes, IM&E from CWIS may represent a substantial portion

of the annual reproduction of T&E species. Consequently, IM&E may either lengthen population

recovery time, or hasten the demise of these species. For these reason s , the population

- level and

social values of T&E losses are likely to be more important than the absolute number of losses

that occur.

Adverse effects on T&E species due to water withdrawals by CWIS may occur in several ways:

 Populations of T&E species may suffer increased mortality as a consequence of IM&E.

 T&E species may suffer indirect harm if the CWIS substantially alters the food web in

which these sp ecies interact

.

 T&E species may suffer indirect harm if the CWIS substantially alters habitat that is

critical to the ir long

- term survival.

Chapter 5 provides detail on CWIS impacts on T&E species.

2.3.3 Thermal Effects

Once

- through cooling water systems releas e heated effluent as a byproduct. Concerns about the

impacts of heated effluents are addressed by provisions of CWA section 316(a) rule. Most of the

facilities subject to 316(b) IM&E concerns have also been required to address the impact of

thermal polluti on in the discharge

- receiving waters ( Abt Associates 2010b )

.

Thermal pollution has long been recognized as having effects upon the structure and function of

ecosystem s ( Abt Associates 2009 )

. Numerous studies have shown that thermal discharges may

substantially alter the structure of the aquatic community by modifying photosynthetic ( Bulthuis

1987 ; Chuang et al. 2009 ; Martinez

- Arroyo et al. 2000 ; Poornima et al. 2005 ) , metabolic

, and

growth rates ( Leffler 1972 ) , and reducing levels of DO . Thermal pollution ma y also alter the

location and timing of fish behavior including spawning ( Bartholow et al. 2004 ) , aggregation

, and

migratio n ( USEPA 2002b ) , and may resu lt in thermal shock

- induced mortality for some species

( Ash et al. 1974 ; Deacutis 1978 ; Smythe and Sawyko 2000 )

. Thus , thermal p ollution is likely to

alter the ecological services provided by ecosystems surrounding facilities returning heated

cooling w ater into nearby waterbodies.

Adverse temperature effects may also be more pronounced in aquatic ecosystems that are already

subjec t to other environmental stressors such as high biochemical oxygen demand (BOD) levels,

sediment contamination, or pathogens. Thermal discharges may have indirect effects on fish and

other vertebrate populations through increasing pathogen growth and infec tion rates . Langford

( 1990 ) reviewed several studies on disease incidence and temperature, and while he found no

simple, causal relationship between the two, he did note that it was clear that warmer water

enhances the growth rates and survival of pathogens, and that infection rates tended to be lower in

cooler waters.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 13 

### The magnitude of thermal effects on ecosystem services is related to facility

- specific factors

, including the volume of the waterbody from which cooling water is withdrawn and returned,

other heat loads, the rate of water exchange, the presence of nearby refugia, and the assemblage

of nearby fish species. In addition to reducing total IM&E , cooling tower s reduce thermal

polluti on . Consequently, the installation o f closed

- system cooling towers c ould have

geographically variable effects on ecosystems, ranging from comprehensive changes in

community structure and habitat type ( Schiel et al. 2004 ) , to localized changes in the relative

proportion of species adapted to warm and cold water ( Millstone Environmental Laboratory

2009 )

. Further information on thermal discharges is provided in Appendix B.

2.3.4 Chemical Effects

One of the environmental impacts assoc iated with operation of electric generators is the release of

chemicals in the discharge of once

- through cooling water. These chemicals include metals from

internal corrosion of pipes, valves and pumps (e.g., chromium, copper, iron, nickel, and zinc),

additives (anti

- fouling, anti

- corrosion, and anti

- scaling agents) and their byproducts, and

materials from boiler blowdown and cleaning cycles

.

EPA used the Discharge Monitoring Re port Pollutant Loading Tool (DMR

- PLT) 6 

### to obtain

estimated annual pollutant loadings for regulated facilities. EPA extracted data for all regulated

facilities (excluding those designated as baseline closures) by querying on a facility’s NPDES

permit identi fication number . Of the 739 regulated facilities (excluding baseline closures)

, 569

have annual loading estimates in DMR

- PLT; of these, nearly 75 percent are electric power

generators. Table 2

- 5 lists the top 20 pollutants discharged by regulated facilities in 20 11 , sorted

by mass. These chemicals represent pollutants generated by the operation and maintenance of the

facility and other location

- specific activities

. The most common pollutants include: total

dissol ved solids, calcium carbonate

, sulfate

, chloride and fecal coliform.

In addition to these pollutants, facilities also discharge anti

- fouling agents. Biofouling is a serious

operational concern for facilities . Microbial biofouling on surfaces in cooling wat er systems can

accelerate metal corrosion, increase resistance to heat transfer energy, and increase fluid frictional

resistance ( Cloete et al. 1998 ) . Sessile macrofouling

- organisms such as algae, insects, hydroids,

polychaetes, barnacles, mussels and tunicates can colonize i ntake pipes, bulkheads, and filter

screens, and may clog pipes and reduce intake flows or filter

- screen effectiveness. Further, some

of these infestations produce larvae, which can colonize downstream equipment including

pipelines, valves, and heat exchang ers. Severe macrofouling

- associated problems can include

intake flow reduction, increased pressure drop across heat exchangers, and equipment breakdown.

6 The Discharge Monitoring Report (DMR) Pollutant Loading Tool calculates pollutant loadings from EPA’s

Permit Compliance System (PCS) and Integrated Compliance Information System for the National Pollutant

Discharge Elimination System (ICIS

- NPDES) a s well as wastewater pollutant discharge data from EPA’s Toxics

Release Inventory (TRI). Data is currently available for the years 2007 through 2011.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 14



### Table 2

- 5 : Top 20 Pollutants Discharged by Regulated Facilities, by

Total Annual Loadings (2011)

Para meter Number of

facilities Total Load ing

( million lbs /yr)

1 Solids, total dissolved 42 18,508.3

2 Hardness, total (as CaCO3) 31 1,548.5

3 Solids, total suspended 487 651.0

4 Coliform, fecal general 82 535.3

5 Residue, total filterable (dried at 105 C) 8 524.3

6 Sulfate, total (as SO4) 52 485.1

7 Chloride (as Cl) 53 440.3

8 Nickel, total recoverable 41 395.4

9 Selenium, total recoverable 51 262.6

10 Lead, total recoverable 47 251.2

11 Chromium, total recoverable 27 224.7

12 Chromium, trivalent total recoverable 4 217.7

13 Sulfate 11 178.6

14 Cadmium, total recoverable 32 165.6

15 Solids, total dissolved

- 180 deg. C 7 127.7

16 Calcium Chloride 1 106.9

17 Chemical Oxygen Demand (COD) 35 105.9

18 Solids, total dissolved (TDS) 3 102.1

19 Chromium, hexavalent dissolved (as Cr) 14 97.4

20 Antimony, total (as Sb) 12 81.9

Source: Discharge Monitoring Report Pollutant Loading Tool (DMR

- PLT)



### These anti

- fouling and cleaning chemicals potentially pose a risk to organisms downstream of the

CWIS discharge. Adverse effects to aquatic organisms may include acute and residual effects of

biocides used as anti

- fouling agents in condenser tubes, or from chemicals resulting from

corrosion or use in cleaning of either stream or cooling cycles ( Kelso and Milburn 1979 ) . A

typical bio fouling procedure is continuous low

- level chlorination at chronic toxicity levels with

an occasional high (“shock”) dose. The use of oxidants (chlorine, bromide) can give rise to

residuals and/or disinfection byproducts (DBPs) such as trihalomethanes, halo acetic acid,

bromoform, and others ( Taylor 2006 ) . Concentrations of released chemicals are variable among

facilities, and are a function of treatment dose, CWIS design, rates of degradation, and the

volume and flushing rate of the receiving water.

With the exception of chlorination impacts ( Taylor 2006 ) , the potential effects of chemicals in

facilities’ cooling water discharges on local aquatic ecosystems are not well

- characterized. In

most cases, chemical effects are considered, along with thermal and mechanical effects, as a

component of the cumulative stress of entrainment on organisms

. Little information is available

on the chronic or low

- level effects of these disc harge chemicals on local ecosystems or in concert

with other anthropogenic stressors

.

Review of the effects of chemical treatment and discharge into the environment suggests that

direct ecotoxicity in discharge plumes is relatively rare beyond the point o f discharge or mixing

zone near the pipe outlet ( Poornima et al. 2005 ; Taylor 2006 )

. However, concentrations of these

chemicals may be additive to low

- level chronic adverse effect with other anthropogenic stressors

identified above.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 15 

### 2.3.5 E ffects of Flow Alteration

The operation of CWIS and discharge returns significantly alter patterns of flow within receiving

waters both in the immediate area of the CWIS intake and discharge pipe, and in mainstream

waterbodies, particularly in inland river ine settings. In ecosystems with strongly delineated

boundaries (i.e., rivers, lakes, enclosed bays, etc.), CWIS may withdraw and subsequently return

a substantial proportion of water available to the ecosystem. For example, of the 435 facilities

that are located on freshwater streams or rivers, 30 percent (132) of these facilities have average

actual intake flow that is greater than 5 percent of the mean annual flow of the source waters. 7



### Even in situations where the volume of water downstream of regulated facilities change s

relatively little, the fl ow characteristics of the waterbody , including turbulence and water

velocity, may be significantly altered. This is particularly true in locations with multiple CWIS

located c lose to each other.

Altered flow ve locities and turbulence may lead to several changes in the physical environment,

inclu ding sediment deposition ( Hoyal et al. 1995 ) , se diment transport ( Bennett and Best 1995 )

, and turbidity ( Sumer et al. 1996 ) , each of which play a role in the physical structuring of

ecosystems. Biologically, flow velocity is a dominant controlling factor in aquatic ecosystem s.

Flow has be en shown to alter feeding rates , se ttlement and recruitment rates ( Abelson and Denny

1997 ) , bioturbation activity ( Biles et al. 2003 )

, growth rates ( Eckman and Duggins 1993 ) , and

population dynamics ( Sanford et al. 1994 )

.

In addition to flow rates, turbulence plays an important role in the ecology of small organisms,

including fish eggs and larvae, phytoplankton, and zooplankton. In many cases, the turbulence of

a waterbody directly affect s the behavior of aquatic organisms, including fish, with respect to

swimming speed ( Lupandin 2005 ) , location preference with a waterbody ( Liao 2007 ) , predator

prey interactions ( Caparroy et al. 1998 ; MacKenzie and Kiorboe 2000 )

, recruitment rates

( MacKenzie 2000 ; Mullineaux and Garland 1993 ) , and the metabolic costs of locomotion ( Enders

et al. 2003 ) . The sum of these effects may result in changes to the food web or the location of

used habitat, and thereby substantially alter the aquatic environment

.

Climate change is predicted to have variable effects on future river discharge in different regions

of the United States, with some rivers expected to have large increases in flood flows while other

basins will experience water stress. For example, Palmer et al. ( 2008 ) predict that mean annual

river discharge is expected to increase by about 20 percent in the Potomac and Hudson River

basins but to decrease by about 20 percent in Oregon's Klamat h River and California's

Sacramento River. Thus, the adverse effects of flow alteration may increase or decrease over

longer periods for larger rivers, depending on their geographic location.



## 2.4 Community

- level or Indirect Effects of CWIS

In addition to the direct effects of CWIS

, IM&E may alter a wide range of aquatic ecosystem

functions and services at the community

- level ( Table 2

- 4 )

. Most of these impacts on aquatic

community function and service are poorly characterized, given the limited scope of IM&E

st udies and an incomplete knowledge of baseline or pre

- operational conditions within affected

waters.

7 Facility counts exclude baseline closures.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 16 

### For example, fish are essential for energy transfer in aquatic food webs ( Summers 1989 ) , and for

the regulation of food web structure

. Fish play important roles in nutrient cycling ( Wilson et al.

2009 ) and sediment processes, and are known to play key roles in the maintenance of aquatic

biodiversity ( Holmlund and Hammer 1999 ; Peterson and Lubchenco 1997 ; Postel and Carpenter

1997 ; Wilson and Carpenter 1999 )

.

While IM&E o f commercially or recreationally important fish species can be quantified and

monetized (Chapters 6 and 7 ), the accompanying loss of other aquatic organisms may be poorly

characterized (e.g., lumped into broad taxa such as “forage fish” or “other”) or simply not

reported. In addition, IM&E on species of lower concern may create unrealized ripples of

ecological effect within the aquatic community. Species may r espond to altered ecological

circumstances such as reduced predation, altered food concentrations, or slower nutrient

recycling, etc

. Therefore, the removal of selected fish species or considerable biomass by IM&E

may substantially affect these processes

.

Several examples of ecological services indirectly affected by IM&E are described below,

although others listed in Table 2

- 4 may be of equal importance for individual ecosystems.

2.4.1 Altered Community Structure and Patchy Distribution of Species

The role of s ome aquatic species may be more critical in shaping the structure and composition of

the community than that of others. These keystone species are species that have an effect on

community structure disproportionate to their population ( Paine 1966 ; Paine 1969 )

. Consequently, the loss or reduction of keystone species may lead to substantial changes in aquatic

food we bs, and decrease overall ecosystem stability. Thus, the potential for ecosystem impacts

resulting from, for example, the loss of an important predator fish due to IM&E may not be

strictly proportional to the number or biomass of lost fish or foregone fish production.

The operation of CWIS by generating facilities can lead to localized areas of depressed fish and

shellfish abundance. Facilities (and the intake volume they represent) are distributed in a non

uniform manner along coastlines and rivers, and ma y be clustered (Section 2.5 ), such that IM&E

and the populations they affect are geographically heterogeneous. This can result in a highly

localized and patchy distribution of aquatic organisms in regional areas. A secondary effect is

increased probability of colonization and establishment by NIS due to niche space availability

caused by a local reduction in the density of native organisms ( Byrnes et al. 2007 ; Ovaskainen

and Cornell 2006 )

.

2.4.2 Altered Food Webs

Sources of mortality, including IM&E , may disrupt established predator

- prey relationships and

the niche space available to species through direct pathways (i.e., mortality of the organism) or

indirectly (i.e., alterations to the food web). The lo ss of young

- of

- year (YOY) predators (e.g.,

striped bass) or important forage fish (e.g., menhaden and bay anchovy) is likely to affect trophic

relationships and alter food webs. These changes may alter the realized species niche and life

history traits due to alterations in inter

- and intra

- specific interactions (e.g., predator

- prey,

competition, mate selection, etc.) ( Fortier and Harris 1989 ; Hixon and Jones 2005 ; Jirotkul 1999 )

. These alterations in trophic interactions and food webs, combined with other CWIS

- related

impacts such a s thermal pollution (Section 2.2.3 ) or flow alteration (Section 2.3.5 ), may lead to

rapid changes in life history strategies as a consequence of facultative ( Ball and Baker 1996 ) or

evolutionary changes ( Hairston et al. 2005 ; Reznick and Endler 1982 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 17 

### 2.4.3 Reduced Taxa and Genetic Diversity

IM&E may lead to reductions in local community biodiversity (due to destruction of selected

species) or in a loss of genetic diversity in individual fish populations. IM&E represents a novel

selective pressure on early life stages that may reduce the genetic diversity of resident fish and

prevent the recovery of depleted stocks ( Stockwell et al. 2003 ; Swain et al. 2007 ; Walsh et al.

2006 )

. Because many populations stocks are differentiated by oceanic region and/or timing of

migratory movements, IM&E could alter the seasonal timing and movement (i.e., phenology) of

overall fish p opulations, which could have ramifications for predator species.

2.4.4 Nutrient Cycling Effects

IM&E impacts may alter the pace of nutrient cycling, and energy transfer through food webs.

Fish species have been shown to have substantial effects on nitrogen, pho sphorous, and carbon

cycling due to storage effects (i.e., large quantities of nutrients are found within fish biomass) and

translocation effects (i.e., fish migrate, moving large quantities of nutrients to new ecosystems)

( Kitchell et al. 1979 ; Vanni et al. 1997 )

. These alterations in nutrient cycling could lead to

redirection of nutrient flows to other components of the ecosystem including water column

phytoplankton, benthic macroalgae and attached epiphytes, with subs equent changes to the

condition of critical ecosystem habitats, such as submerged aquatic vegetation. Juvenile Atlantic

menhaden ( Brevoortia tyrannus ) are capable of significantly grazing down plankton

concentrations in Chesapeake Bay, leading to more

- rapi d regeneration of nutrients and enhanced

primary production. Removal of juvenile menhaden by IM&E would lead to reduced grazing and

turnover of nutrients and increased algal density in the water column ( Gottlieb 1998 ) . The amount

of nitrogen and p hosphorus regenerated in facility discharge water due to nutrient recycling of

IM&E biota might also lead to areas of localized nutrient enrichment near outfalls ( Abt

Associates 2010a )

. Additionally, the preferential removal of upper water column species by

IM&E could increase energy flow to benthic organisms, and thereby increase the relative

importance of detritivores in bottom communities.

2.4.5 Reduced Ecological Resistance

The effect of lo ng

- term or chronic IM&E may lead to a decrease in ecosystem resistance and

resilience (i.e., ability to resist and recover from disturbance including invasive species) ( Folke et

al. 2004 ; Gunderson 2000 ) . That is, IM&E is likely to reduce the ability of ecosystems to

withstand and recover from adverse environmental impacts, whether those impacts are due to

anthropogenic effects or natural variability.



## 2.5 Cumulative Impacts of Multiple Facilities

Cumulative effects of CWIS are likely to occur if multiple facilities are located in clo se proximity

such that they impinge or entrain aquatic organisms within the same source waterbody, watershed

system, or along a migratory pathway of a specific species (e.g., striped bass in the Hudson River)

( USEPA 2004 a) . The cumulative impacts of CWIS may be exacerbated by the presence of other

anthropogenic stressors discussed above (Section 2.2 ).

EPA analyses suggest that approximately 20 percent of all regulated facilities are located on

waterbodies with multiple CWIS ( USEPA 2004 a) . Inspection of geographic locations of

regulated facilities (approximated by CWIS latitude and longitude) indicates that facilities inBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 18 

### inland settings ar e clustered around rivers to a greater extent than marine and estuarine facilities

(see Figure 2

- 1 ).

2.5.1 Clustering of Facilities and CWIS on Major Rivers

To illustrate the potential for cumulative impacts, EPA reviewed data from five major U.S. rivers

with c lustered concentrations of facilities

. Table 2

- 6 summarizes average annual river flow and

facility DIF and actual intake flow (AIF). Based on the non

- uniform distribution of facilities,

locations were noted where the potential for cumulative impacts is hig h ( Abt Associates 2010b )

.

Table 2

- 6: U.S. Rivers with Largest Withdrawals by Regulated Facilities

River Avg. Annual a

Flow (mgd) Facilities Cumulative

DIF (mgd) DIF as % Avg.

Annual Flow Cumulative

AIF (mgd) AIF as %

Avg. Annual

Flow

Mississippi 383,266 57 22,436 5.9 13,170 3.4

Ohio 181,615 47 19,315 10.6 13,384 7.4

Missouri 49,249 23 10,718 21.8 6,598 13.4

Illinois 8,079 11 6,259 77.5 1,605 19.9

Delaware 7,562 11 3,585 47.4 1,485 19.6

Sources: USGS 1990 and U.S. EPA analysis for this report



### For example, the Mississippi River provides source water for cooling water for 57 facilities along

its length, 8 

### with 27 facilities located in Louisiana upstream of the Mississippi River delta. Using

facility intake coordinates as location markers, the relative distance s between facilities were

estimated ( Abt Associates 2010b ) . In upper Louisiana, facilities are typically separated by tens of

miles; inter

- facility distance decreases downstream of Baton Rouge, LA. Several locations along

the Mississippi River have clusters of facilities :

 Between Ascension and St. James Parishes, a 13

- mile span of the river hosts six

manufacturing facilities, three of which have intakes located within the same mile. These

facilities have a combined DIF of nearly 270 mgd.

 Fifteen miles downstream, near Gar yville, LA, there is a cluster of three facilities within

six miles of the river stretch.

 Seven miles further downstream near Laplace, LA, six facilities are located on a six

- mile

stretch of the river. Four of these facilities, with a combined DIF exceedin g 5 billion

gallons per day ( bgd ) (three generators and one manufacturer), are located within a 1.7

mile section of river.

 Further downstream in Chalmette, LA (just east of New Orleans), three manufacturers,

capable of withdrawing up to 457 mgd, are cluste red within four river miles.

Therefore, the potential for cumulative impacts is high, and investigating ecosystem effects by

extrapolating results on a per facility basis is likely to underestimate the true effects.

8 This total excludes one facility that EPA projects as bas eline closure.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 19 

### 2.5.2 Implications of Clustered Facilities fo r Cumulative Impacts

The cumulative impact of clustered facilities may be significant, due to the concentrated IM&E,

combined intake flows, and the potential for other impacts such as thermal discharges. It should

also be noted that power generation demand and cooling intake water volume are typically at

their annual maximum during mid

- late summer, which is also a period of seasonal low flows and

highest in

- stream temperatures. The effect of cumulative impacts may be greater in inland or

Great Lakes waters due to the following factors:

 The majority of national AIF is associated with freshwater CWIS.

 Freshwater facilities use a greater relative volume of available fish habitat than marine or

estuarine counterparts.

 Seasonal variation in power demand and river flow may increase entrainment potential

during low

- flow periods of the year ( NETL 2009 ) . Although low flows are traditionally

in late summer to early fall, drought conditions and manipulations of water levels may

lead to low flow during other periods. This may be locally significant if periods of low

flow overlap with seasonal concentrations of eggs, developing YOY, and migrating

juveniles.

 Freshwater facilities are more likely to be clustered along a waterbody, and pose a greater

risk of cumulative impacts. This is exacerbated by the presence of numerous

impoundments associated with navigational lock and dam structures located on larger

rivers (e.g., Mississippi, Missouri, Ohio , etc). These impoundments result in slow or

slack water conditions with a lower effective volume than free

- flowing reaches or periods

of higher flow.



## 2.6 Case Studies of Facility IM&E Impacts

While the information provided in this chapter provides a broad ov erview of potential impacts

associated with CWIS , it is highly informative to evaluate these impacts in the context of actual

facilities to see how and to what extent these impacts and IM&E are realized, how site

- specific

factors come into play, the effect s of cumulative impacts, and what has been learned with regard

to community

- level effects. Case studies provide useful, detailed information for evaluating

IM&E and major stressors in the context of a specific waterbody or region.

As part of the Phase II r egulations, review and analyses of IM&E data and environmental

information w ere presented in comprehensive case studies in EPA’s 2002 Case Study Analysis

for the Proposed Section 316(b) Phase II Existing Facilities Rule ( USEPA 2002a )

. The document

provided detailed analyses of CWIS impacts in major regional waterbodies throughout the U nited

S tates. These cases studies included:

 Delaware Estuary Watershed: a regional assessment of the impacts of 7 generating and 6

manufacturing facilities in the transition zone of the Delawar e River Estuary. The

estuary’s transition zone was chosen due to its biological, recreational, and economic

importance, and because of the high concentration of CWIS.

 Ohio River Watershed: a detailed assessment of the impacts of 9 (of 29) facilities in a

5 00

- mile stretch of the Ohio River between the McAlpine and New Cumberland pools,

this case study is representative of a large industrial river.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 20 

###  Tampa Bay Watershed: highlighted as a representative of the Southeast Atlantic and Gulf

coasts, this case study included four of eight facilities in watersheds draining into Tampa

Bay.

 San Francisco Bay/Delta Estuary: included as representative of an urban estuary, and a

waterbody containing several T&E species, this case study highlighted the effects of two

large g enerating facilities.

 Brayton Point Facility: a case study of a single facility and its impacts on a confined

waterbody.

 Seabrook and Pilgrim Facilities: with a pair of facilities located in the same ecological

region, but with very different CWIS placemen ts, this case study highlights the potential

effects of CWIS location of IM&E impacts.

 J.R. Whiting Facility: an assessment of the before and after effects of the installation of a

deterrent net on IM&E for a representative facility on the Great Lakes.

 Mon roe Facility: located nearby the J.R. Whiting facility (above), the Monroe facility

case study provides an estimate of the effects of IM&E on Great Lakes facilities.

These regional case studies provide a set of information describing the variety of CWIS im pacts

under marine, coastal, and riverine environmental settings . The following sections present three

additional case studies to provide examples of facility

- specific CWIS impacts in settings

including freshwater coastal (Bay Shore, Oregon, OH), estuarine (Indian Point, Buchanan, NY),

and estuarine

- coastal (Indian River, Sussex County, DE) environments. These brief case studies

also illustrate the quantitative levels of IM&E , the indirect effects of IM&E on local aquatic

ecosystems, and the cumulative effe cts of combined effects ( IM&E and thermal).

2.6.1 Bay Shore Power Station

The Bay Shore power station is a 631 megawatt ( MW ) facility located on the south shore of Lake

Erie near the confluence of the Maumee River and Maumee Bay, OH

. C ooling water for the four

coal

- fired steam

- electric units is withdrawn from Maumee River/Maumee Bay via an open intake

channel of approximately 3,700 ft in length, and enters the facility via a shoreline surface CWIS.

Approximately 749 mill ion gallons per day ( mgd ) are withdra wn, including once

- through cooling

water and sluice water used for transporting bottom ash from the boilers to ash settling ponds

( OEPA 2010 ) . Major environ mental concerns for the facility include IM&E and thermal impacts.

Bay Shore Power Station IM&E: Medium

- sized Plant with Large

- Scale Impacts :

A comprehensive demonstration study, conducted in 2005

- 2006, estimated annual impingement

at greater than 46 mill ion fish per year, the majority of which were forage fish species

— emerald

shiner and gizzard shad. Annual estimates for entrainment were equally impressive

— 209 million

fish eggs, 2,247 million fish larvae, and 14 million juvenile fish ( OEPA 2010 ) . As noted on the

NDPES fact sheet, “It is likely that Bay Shore Station impinges and entrains more fish than all

other power stations in Ohio combined.” Notably, the facility does not currently employ

technologies to reduce IM&E ( OEPA 2010 )

.

In addition to IM&E effects, concerns have also been raised regarding the size and impact of the

thermal discharge plume

— a focus of concern for local residents and commercial fishermen.

Depending on wind patterns and hydrological factors, the thermal plume extends to the southBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 21 

### shore of Maumee Bay (over 1 mile from the facility). The Ohio Environmental Protection

Agency (OEPA) assessed the results from a 2002 thermal mixing zone study, and concluded that

the thermal discharge exceeded Ohio water quality standards for temperature within the thermal

plume (>85 o 

### F in Maumee Bay), but that the impacts on aquatic life and designated uses in

Maumee River/Bay did not justify reduction of the thermal mixing zone. However, it did find that

the thermal activity could restrict recreational activities in certain areas of the facility and

required th e facility owners to conduct a two

- year study of the benthic community within the

mixing zone ( OEPA 2010 )

.

2.6.2 Indian Point Nuclear Power Plant

The Indian Poin t nuclear power plant is a 2,045 MW facility located in Buchanan, Westchester

County, New York, on the east shoreline of the Hudson River. Cooling water (up to 2,500 mgd )

for the two nuclear

- fired steam

- electric units (Units 2 and 3) is withdrawn from the estuarine

portion of the Hudson River through three intake structures on the shoreline ( NYSDEC 2003a )

. The heated non

- contact cooling water is discharged through sub

- surface diffuser ports in a

discharge canal located downstream of the intake structures.

C oncerns regarding impact to fish, particularly anadromous striped bass populations, as well as a

high level of involvement and litigation from local stakeholder groups , have made the Indian

Point power generat ion plant (along with other Hudson River facilities ) particularly well

characterized in terms of IM&E impacts. Accordingly, the Hudson River aquatic community has

been sampled and studied over many decades, with detailed investigation starting in the 1970s

.

Results suggest that IM&E impacts to the local and transient anadramous fish species are

substantial. For example, studies of fish entrainment in 1980 predicted fish class reductions

ranging from 6 to 79 percent, depending on fish species ( Boreman and Goodyear 1988 )

. Subsequent sampling work predicted year

- class reductions due to IM&E of 20 percent for striped

bass, 25 percent fo r bay anchovy, and 43 percent for Atlantic tomcod

. The Final Environmental

Impact Statement (FEIS) prepared by the New York State Department of Environmental

Conservation (NYSDEC) concluded these levels of mortality “could seriously deplete any

resilience or compensatory capacity of the species needed to survive unfavorable environmental

conditions” ( USEPA 2006 a)

.

Indian Point Final Environmental Impact Statement (FEIS ) details cumulative effects:

Th e FEIS estimated, from samples collected between 1981 and 1987 for three facilities (Indian

Point, Roseton, Bowline Point), that average annual entrainment included 16.9 million American

shad, 303.4 million striped bass, 409.6 million bay anchovy, 468 mill ion white perch, and 826.2

million river herring ( NYSDEC 2003b ) . The loss of such large numbers of forage fish species and

the potential impact on higher level piscivores is of high concern. The FEIS also viewed the

overall effect of the CWIS impacts on the aquatic community as analogous to habitat d egradation

rather than overfishing. This judgment was based on evidence that the entire aquatic community

was affected rather than only specimens of higher trophic level species.

The FEIS considered the role of other major environmental factors currently or historically

present in the Hudson River. These factors have the capacity to affect fish populations either

positively (enhancements) or negatively (stressors). Relevant factors include, but are not limited

to: improvements to water quality due to upgra des to sewage treatment facilities , invasions by

exotic species (e.g., zebra mussel), chemical contamination by toxins (e.g., PCBs and heavyBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 22 

### metals), global climate shifts such as increases in annual mean temperatures and higher

frequencies of extreme weat her events (e.g., the El Nino

- Southern Oscillation), and stricter

management of individual species stocks such as striped bass ( USEPA 2006 a)

.

In April 2010, the NYSDEC denied a request by Indian Poi nt for a CWA s ection 401Water

Quality Certificate. The CWA requires that, prior to any federal agency issuing a license or

permit for a particular project (in this case, the approval of the State Discharges Permit

Elimination System [SPDES] permit), it mus t certify that the project meets State water quality

standards. The NYSDEC denial letter cited, among other concerns, continuing concerns over

IM&E including potential impacts to two species protected under the Endangered Species Act

(ESA)

— the Shortnose Sturgeon (endangered) and the Atlantic Sturgeon (endangered).

2.6.3 Indian River Power Plant

The Indian River Generating Station (IRGS) is a 784 MW facility located in Sussex County,

Delaware, on the south shore of the Indian River. Cooling water for three of the IRGS’s four

coal

- fired steam

- electric units is withdrawn upstream from the freshwater portion of Indian River

via an intake canal at a maximum rate of 411 mgd , or 21 times the average flow rate of Indian

River. Heated return water is discharged via a canal into the upper reaches of Island Creek, a

small tributary of Indian River, entering at Ward Cove. Island Creek and Ward Cove are part of a

large estuarine stretch (approximately 150 acres) of Indian River that provides important fish and

crab habitat. Its lower salinity and location in the estuary make it attractive to important species

s uch as bay anchovy, spot, menhaden larvae, and young blue crabs.

Indian River Power Plant has impact on important local species:

The 2003 316(b) Comprehensive Demonstration Study for the Indian River Power Plant reported

IM&E for a number of important spe cies ( Entrix 2003, as described in Bason 2008 ) . This IM&E

has been recalculated by a local stakeholder group as A1E for bay anchovy (1.6 million), blue

crab (300,000), croaker (270,000), and menhaden (60,000) ( Bason 2008 )

.

Due to t he size of the heated discharge relative to the receiving water, thermal effects of the

facility were also investigated. Based upon monitoring data collected from 1998 to 1999, the

316(a) report assessed the effects of elevated water temperatures on ecosys tem communities with

a focus on eight important fish species: bay anchovy, menhaden, winter and summer flounder,

croaker, spot, striped bass, and weakfish. This report determined that juvenile and adult target

species, although able to avoid areas of high water temperature, were not permanently restricted

from most stretches of the Indian River, nor did they suffer loss of habitat services associated

with these segments. The study concluded an overall condition of no adverse effect, or no

appreciable harm, on the fish and shellfish populations in the Indian River and Delaware Bay

( Entrix 2001 )

.

Despite the overall conclusion of no adverse effect, the report documented localized thermal

impacts of consequence. For example, during warmer months, the thermal discharge reached

potential adverse levels in Island Creek, often ext ending downstream to Ware Cove ( Entrix

2001 ) . The mortality associat ed with sub

- adult stages of fish and crabs and the avoidance of the

area by sub

- adult and adult fish were substantial issues. In addition to direct thermal impacts to

biota, temperature

- related reductions in DO were observable (mean reduction = 0.6 mg/l) i n the

discharge canal. These reductions contributed to the amplitude of the day

- night (diel) cycle of DOBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 2: Baseline Impacts

May 2014 2

- 23 

### concentrations, already widely fluctuating due to cumulative effects of eutrophication in the river

( Bason 2008 )

.



## 2.7 Conclusions

Considerable information is available on the direct effects of CWIS and IM&E (Chapter 3) on

commercially (Chapter 6) and recreationally important (Chapter 7 ) species derived from the

accumulated data from facility

- specific basis 316(b) studies and investig ations. This information

allowed EPA to monetize the potential commercial and recreational fishing benefits for the final

rule and other options EPA considered. However, as demonstrated in this section, much less

information and high uncertainty exist rega rding the magnitude and importance of indirect and/or

cumulative impacts of CWIS, particularly effects on lower trophic organisms or ecosystem

functions. This condition is due to the limitations of 316(b) sampling programs, as well as the

failure of permit ting process to consider the additive or cumulative effects of other major

anthropogenic stressors. While EPA can identify and hypothesize regarding the direction and

relative importance of impacts of CWIS on the totality of the aquatic ecosystem (i.e., no t just

focused on selected higher trophic level predator species and common prey), EPA is currently

unable to connect these effects with quantifiable environmental benefits. Thus, it is highly likely

that the total environmental and monetary impacts of CWI S are significantly underestimated, and

that characterization of the fuller spectrum of benefits arising from reducing or eliminating IM&E

will await future, targeted research efforts.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 1 

# 3 Assessment of Impingement and Entrainment Mortality

3.1 Introduction

This chapter discusses the methods EPA used to convert results from IM&E sampling studies into metric s

suitable as inputs for EPA’s s ection 316(b) benefits analysis. 9 

### Section 3.2 provides a brief overview of

IM&E metrics, and outlines how they were used in the benefits analysis. Section 3.3 presents IM&E , by

region, under baseline conditions, and the reductions in these losses under alternative regulatory options.

Section 3.4 discusses limitations and uncer tainties in the IM&E analysis.

EPA’s IM&E assessment methods are discussed in detail in Chapter A

- 1 of the Regional Benefits

Analysis for the Final Section 316(b) Phase III Existing Facilities Rule (Regional Benefits Analysis)

( USEPA 2006 b ) . Changes in methodology since EPA’s Phase III analysis include: (1) the addition of new

IM&E data for several California facilities, (2) engineering reductions for power generators were

estimated for sample facilities that received the detailed q uestionnaire rather than for all regulated

generators, and (3) estimated changes in the proportionate reduction in IM&E under the final rule and

Proposal Options 2 and 4 . Other modifications are identified in relevant portions of Section 3.2

.



## 3.2 Methods

3.2.1 Objec tives of IM&E Analysis

EPA’s evaluation of IM&E data had four main objectives:

 To develop regional and national estimates of the magnitude of IM&E;

 To standardize IM&E using common biological metrics that allow comparison across species,

years, facilities, and geographical regions;

 To provide IM&E metrics suitable for use in national economic benefits analysis; and,

 To estimate changes in metrics as a result of estimated reductions in IM&E under the final rule

and Proposal Options 2 and 4.

EPA’s use of thes e methods for national rulemaking does not imply that these methods are the best or

most suitable for studies of single facilities. In many cases, site

- specific details on local fish populations

and waterbody conditions may make other assessment approaches , such as population or ecosystem

modeling, possible.

3.2.2 IM&E Loss Metrics

Three loss metrics were derived from facility IM&E monitoring data available to EPA: (1) age

- one

equivalents (A1E) , (2) forgone fishery yield, and (3) production forgone. These metric s are described

9 For the purposes of its national analysis, EPA assumed 100 percent entrainment mortality. This assumption is discussed at

length in Chapter A7 of the Regional Analysis Document for the Final Section 316(b) Existing Facilities Rule ( USEPA

2004 a) . Briefly, EPA assessed 37 entrainment survival studies and found them variable, unpredictable, unreliable, and not

defensible. As such, these studies support an assumption of 0 percent survival for entrained organisms in benefits

assessments.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 2 

### briefly below. Equations used to calculate metrics and other details are provided in Chapter A

- 1 of EPA’s

Regional Benefits Analysis ( USEPA 2006 b )

.

3.2.2.1 Age

- One Equivalents



### The Equivalent Adult Model (EAM) is a method for converting organisms of different ages (life stages)

into an equivalent number of individuals in any single age ( Goodyear 1978 ; Horst 1975 ) . For its 316(b)

analyses, EPA standardized all IM&E into e quivalent numbers of 1

- year

- old fish, a value referred to as

A1Es. This conversion allows losses to be compared among species, years, facilities, and regions.

To conduct EAM calculations requires a life history schedule, for each species, incorporating age

- specific

mortality rates. Using these species

- specific survival tables, a conversion rate between all life history

stages and age 1 is calculated. For life history stages younger than 1 year of age, the conversion rate is

calculated as the product of all stage

- specific survival rates between the stage at which I M&E occurs and

age 1. Consequently, the loss of an individual younger than age 1 results in a conversion rate less than 1.

For individuals older than 1 year, the conversion rate is calculated as the quotient of all stage

- specific

survival rates between the stage at which IM&E occurs and age 1. Consequently, the loss of an individual

older than age 1 results in a conversion rate greater than 1.

Additional details on the EAM calculation are provided in Chapter A

- 1 of EPA’s Regional Benefits

Analysis ( USEPA 2006 b ) . For the results presented in this chapter, the treatment of early life stages in

this calculation considers all larval life stages reported in the original IM&E studies

.

3.2.2.2 Forgone Fishery Yield of Commercial and Recreational Species 

# Recreational

Fishery yield is a measure of the biomass harvested from a cohort of fish. 10 

### EPA expressed IM&E of

harvested species in terms of forgone (lost) fishery yield. To convert losses to forgone fishery yield, EPA

used the Thompson

- Bell equilibrium yield model ( Ricker 1975 ) wit h the assum ptions that 1) IM&E

reduce the future yield of harvested adults, and 2) reductions in IM&E will lead to an increase in

harvested biomass.

The Thompson

- Bell model is based on the principles used to estimate the expected yield in any harvested

fi sh population ( Hilborn and Walters 1992 ; Quinn and Deriso 1999 ) . The general procedure involves

multiplying age

- specific harvest rates by age

- specific weights to calcula te an age

- specific expected yield.

The lifetime expected yield for a cohort of fish is the sum of all age

- specific expected yields. Details of

these calculations are provided in Chapter A

- 1 of EPA’s Regional Benefits Analysis ( USEPA 20 06 b )

.

3.2.2.3 Production Forgone for All Species 

# Recreational

Production forgone is an estimate of the biomass that would have been produced had individuals not been

impinged or entrained ( Rago 1984 ) . It is calculated for all forage species from species

- and age

- specific

growth rates and survival probabilities. This forgone biomass represents a decrease in prey availability for

predator species, and is calculated becaus e IM&E for forage species are not included in the forgone

fishery yield calculations. Additional details regarding the calculation of production forgone are provided

in Chapter A

- 1 of EPA’s Regional Benefits Analysis ( USEPA 2006 b )

.

3.2.3 Valuation Approach

EPA’s benefits analysis focused on increased commercial and recreational fishery harvests estimated

from projected reductions in IM&E . For consistency with reported harvest data, commercial harvest is

10 A cohort of fish refers to fish produced in the same year, also referred to as a year

- class of fish.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 3 

### reported in pounds and recreational harvest is reported in numbers of fish. To project changes in fishery

harvests, EPA integrated two components of fishery yield that change as a consequence of IM&E : direct

contributions of commercially and recreationally harvested species (hereafter fishe ry species), and

indirect contributions of forage species consumed by fishery species ( Figure 3

- 1 ). The direct contribution

of fishery species to yield (left side of Figure 3

- 1 ) is calculated by converting A1E mortality to forgone

yield as described in Sec tion 3.2.2 . The contribution of forage species to fishery yield is measured as a

biotic transfer of mass through the food web to fishery species that are subsequently harvested (right side

of Figure 3

- 1 ). EPA used a simple trophic transfer model for this p urpose (discussed in Chapter A

- 1 of

EPA’s Regional Benefits Analysis ( USEPA 2006 b ) , assuming a trophic transfer efficiency of 0.10 ( Pauly

and Christensen 1995 )

. 11 

### Trophic transfer efficiency represents the fraction of forage species biomass

incorporated into predator (fishery) species biomass. EPA estimated total changes to commercial and

recreational harvest yield as the sum of the contributions of fishery and for age species. For benefits

analysis, total yield was separated into commercial and recreational fractions based on the proportion of

harvest occurring within each type of fishery, and benefits were calculated for harvestable adult fish.

Details of the comme rcial and recreational fishing benefits analysis are provided in Chapters 6 and 7 of

this report, respectively.

3.2.4 Rationale for EPA’s Approach to Valuation of IM&E

EPA’s approach to estimating changes in fish harvest assumed that IM&E result in a reduction in the

number of harvestable adults, and that IM&E reductions result in increases to future fish harvests. This

approach estimates incremental fishery yield forgone because of IM&E and does not require knowledge

of population size or total yield of a fishe ry.

EPA’s forgone fishery yield analysis requires species

- and stage

- specific schedules of natural mortality

(M), fishing mortality (F), and weight

- at

- age. The yield model assumes that these key parameters (F, M,

and weight

- at

- age) are independent of IM&E for all species. EPA recognizes that this assumption does

not fully reflect the dynamic nature of fish populations. However, by conducting benefits analysis using

estimates of forgone yield, EPA was able to use a simple and direct measure of the potential economic

value associated with each I M &E

- related death. Used of t his approach was warranted given: (1) the scope

and objectives of its analysis of harvested species, (2) data availability, and (3) difficulties in

distinguishing the causes of population ch anges. Each of these factors is discussed below.

3.2.4.1 Scope and Objectives of EPA’s Analysis of Harvest Species



### EPA’s overall objective was to develop regional

- and national

- scale estimates of the magnitude of IM&E

at hundreds of facilities subject to the final rule . As a consequence of the large geographic scope and

multiple ecosystems involved, EPA modeled fishery yield using a relatively simplified approach to

estimate the vulnerability of dozens of species to IM&E on a national scale. Although sufficient dat a may

exist to model the effects of IM&E on population and community

- level impacts, sufficient data do not

exist at the national scale to make such studies feasible.

11 EPA notes that its model of trophic transfer is a very simple and idealized representation of trophic dynamics; it is not

intended to capture the details of trophic transfer in actual aquatic ecosystems. In reality, food webs and trophic dynamics

are much more complex than EPA’s simple model implies, and include details that are specific to each particular aquatic

ecosystem. This complexity was beyond the scope of EPA’s analysis and the available data.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 4



### Figure 3

- 1 : General Approach Used to Evaluate IM&E as Forgone Fishery Yield

3.2.4.2 Data Availability and Uncertainties Related to Modeling Fish Harvest



### Forgone fishery yield and production forgone models used by EPA required age

- specific life history data

for all species analyzed. EPA acknowledges t hat many fish population models are available, and that

these models may produce more accurate population

- level impacts of IM&E . EPA did not pursue the

development of species

- specific population models for several reasons:

 Constructing population models re quires a large set of parameters and numerous assumptions

about the nature of stock dynamics for each species, including current stock size, stock

recruitment relationships, changes to growth and mortality rates as a function of stock size, and

the separat ion of certain species into geographically based stock units. Because of these

limitations, fewer than 40 percent of U.S.

- managed commercially harvested fish s tocks have been

fully assessed ( NMFS 2009 ; NMFS 2010 a) . As such, the information necessary to build more

complex population models is available only for a subset of harvested species, which represent a

minor fraction of IM&E

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 5 

###  Numerous d ifficulties exist in the definition of the size and spatial extent of fish stocks. As a

result, it is often unclear how IM&E at particular coolin g water intake structures (CWIS ) can be

related to specific stocks at a regional scale. For example, juvenile A tlantic menhaden

( Brevoortia tryannus ) found in Delaware Bay recruit from both local and long distances ( Light

and Able 2003 ) . As a result, estimating the effects of local IM&E on recruitment rates would not

be suf ficient to understand the stock

- recruitment relationship for Delaware Bay menhaden.

Consequently, issues of data availability and difficulties estimating the effects of localized IM&E on

regional

- scale fish stocks led EPA to determine that the constructio n of population models for all species

subject to IM&E was not feasible. The level of uncertainty that would accompany the construction of

such models (if constructing them were even possible) would be difficult to support with available data at

both the n ational and population level for many species.

3.2.4.3 Difficulties Distinguishing Causes of Population Cha nges



### It is fundamentally difficult to demonstrate a causal relationship between a single stressor and changes in

fish population sizes. Fish populations are affected by multiple nonlinear stressors and are constantly in

flux. As such, determining whether changes to fish populations are the consequence of an identifiable

stressor due to natural fluctuation around an equilibrium stock size is difficult. Fish rec ruitment , the

number of young fish surviving early life stages (e.g., egg, larvae, juvenile) to join an adult population, is

a multidimensional process, and identifying and distinguishing the causes of variance in fish recruitment

remains a fundamental pro blem in fisheries science, stock management, and impact assessment ( Boreman

2000 ; Hilborn and Walters 1992 ; Quinn and Deriso 1999 ) . Consequently, resolving issues of population

fluctuation was beyond the scope and objectives of EPA’s s ection 316(b) benefits analysis.

3.2.5 Extrapolation of IM&E to Develop Regional Estimates

EPA examined IM&E and the economic benefits of reducing these losses at a regional scale. EPA then

aggregated e stimated benefits across all regions to produce a national benefits estimate. Regions were

based on regions used by fisheries management agencies such as the National Marine Fisheries Service

(NMFS). The geographical scope of all regions is described in Chapter 1 (Section 1.2).

To obtain regional IM&E estimates, EPA extrapolated losses observed at 9 8 facilities with IM&E data

(hereafter model facilities) to al l regulated facilities within the same region. Extrapolation of IM&E rates

was necessary because only a subset of all regulated facilities have conducted IM&E studies. To allow

extrapolation, EPA assumed that all facilities, regardless of size, have simila r IM&E rates after

normalization by flow. IM&E data were extrapolated on the basis of operational flow, in millions of

gallons per day ( mgd ), where mgd is the average operational flow over the period 1996

- 1998 as reported

by facilities in response to EPA’s Section 316(b) Detailed Questionnaire and Short Technical

Questionnaire (USEPA 2000) . Operational flow at all facilities was scaled using a multiplicative factor

that reflected the effectiveness of in

- place technologies used to reduce IM&E . During the extrapolation

procedure, EPA also applied weighting f actors to regulated facilities based on questionnaire results.

Weighting factors for the current analysis were based on results of the Detailed Questionnaire. Additional

details of EPA’s extrapolation methods are provided in Appendix A.

The assumption that IM&E is proportional to flow is consistent with other published IM&E studies and

models. Power facilities on the Great Lakes exhibit an increasing relationship (on a log

- log scale)

between facility size (measured as electrical output) and IM&E rates ( Kelso and Milburn 1979 ) , and

Goodyear ( 1978 ) predicted entrainment on the basis of the ratio of cooling water flow to sour ce water

flow. Additionally, the Spawning and Nursery Area of Consequence (SNAC) model, used as a screeningBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 6 

### tool for assessing potential IM&E impacts at Chesapeake Bay facilities, assumes that entrainment is

proportional to cooling water withdrawal rates ( Polgar et al. 1979 )

.

EPA recognizes that actual IM&E per mgd may vary substantially, resulting from a variety of time

- and

facility

- specific features, such as sampling date, location and type of intake structure, as well as from

ecological features that affect the abundance and species composition of fish in the vicinity of each

facility. Consequently, EPA’s extrapolation procedure relies heavily on the assumption that IM&E rates

recorded at model facilities are representative of IM&E rates at other facilities in the region. Although

this assumption may not be met in some cases, limiting the extrapolation procedure within regions

reduces the likelihood that model facilities are unrepresentative.

This method of extrapolation makes the best use of a limited amount of empirical data, and is the only

feasible approach for developing a national estimate of IM&E , and the associated benefits of IM&E

reduction. While acknowledging t hat extrapolation introduces uncertainty into IM&E estimates, EPA has

not identified information suggesting a systematic bias in regional loss estimates based upon

extrapolation.



## 3.3 IM&E by Region

3.3.1 California Region

Table 3

- 1 and Table 3

- 2 present e stimated baseline IM&E and reductions in IM&E under the final rule

and other options considered. Estimated total baseline IM&E in the California region is 51.55 million

A1Es per year, of which 24.56 million ( 47.6 percent) are forage fish. Approximately 5.6 percent of total

baseline A1E mortality is assigned a direct use value from recreational or commercial fishing ( Table 3

- 1 ).

Table 1 of Appendix C presents species

- specific data on impingement and entrainment under the baseline

conditions and estimated red uctions under all options. Among commercially and recreationally

- harvested

species, the greatest losses occur in crabs, rockfishes, and sea basses (Appendix Table C

- 1).

The majority of IM&E in the California region occur due to entrainment (Appendix C Tab le 1). Because

the final rule and Proposal Option 4 do not reduce entrainment , they each reduce baseline A1E mortality

by only 1.4 percent (0.73/51.55) and 1. 3 percent (0.68/51.55), respectively ( Table 3

- 1 ). Conversely, by

requiring the installation of clo sed

- cycle recirculating systems , which effectively reduce entrainment

mortality, Proposal Option 2 reduces A1E mortality by 61.1 percent (31.52/51.55) , providing more than

40 times the reduction in A1E mortality ( Table 3

- 1 ).

Table 3

- 1 : Summary of Baseline IM&E at All Regulated facilities (Manufacturing

and Generating) in California, and Reductions Under the Final Rule and Other

Options Considered

IM&E Loss Metric (per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

All Species (million A1E) 0.68 0.73 31.52 51.55

Forage Species (million A1E) 0.17 0.18 15.00 24.56

Commercial & Recreational Species (million A1E) 0.50 0.54 16.52 26.98

Commercial & Recreational Harvest (million fish) 0.05 0.06 1.76 2.88

A1E Losses with Direct Use Value (%) 8.0% 8.0% 5.6% 5.6%

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 7 

### Production forgone due to baseline IM&E is estimated to be 1 9

. 65 million pounds of fish, leading to a

decrease in fishery yield of 4

. 59 million pounds per year ( Table 3

- 2 ). The final rule is estimated to result

in increased fishery yields of 0.02 million pounds per year. Increases in fishery yields under other options

considered range from 0.02 million pounds per year under Proposal Option 4 to 2.80 million pounds per

year under Proposal Option 2. Estimated increases in fishery yields under Proposal Option 2 are more

than 100 times greater than under the final rule and Proposal Option 4 ( Table 3

- 2 ).

Table 3

- 2 : Baseline Losses in Fishery Yield, Catch, and Production

Forgone as a Consequence of IM&E at All Regulated facilities

(Manufacturing and Generating) in California, an d Reductions Under

the Final Rule and Other Options Considered

IM&E Loss Metric (million per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

Forgone Fishery Yield (lbs) 0.02 0.02 2.80 4.59

Forgone Commercial Catch (lbs) <0.01 <0.01 1.18 1.93

Forgone Recreational Catch (fish) 0.04 0.04 0.88 1.43

Production Forgone (lbs) 0.09 0.10 12.00 19.65

Source: U.S. EPA analysis for this report



### Raw numbers of IM&E in California can be found in Appendix Table C

- 2.

3.3.2 North Atlantic Region

Table 3

- 3 and Table 3

- 4 present e stimated baseline IM&E and reductions in IM&E under the final rule

and other options considered . Estimated total baseline IM&E in the North Atlantic region is 57.86 million

A1Es per year, 78.4 percent (45.34 million) of which are forage fish. Approximately 2.1 percent of total

baseline A1E mortality is assigned a direct use value from recreational or commercial fishing ( Table 3

- 3 ).

Table 3 of Appendix C presents species

- specific data on impingement and entrainment under the baseline

conditions and estimated reductions under all options. Briefly, the vast majority (99.0 percent) of all A1E

mortality in the North Atlantic occur as a consequence of entrainment mortality (Appendix Table C

- 3).

Notably, the co mbined IM&E of winter flounder, cunner, and sculpins account for 96.9 percent of all

IM&E of commercially and recreationally

- harvested species.

Because the final rule and Proposal Option 4 do not reduce entrainment , they reduce baseline IM&E A1E

mortality by 1.6 percent (0.93/57.86) and 0.7 percent (0.40/57.86), respectively ( Table 3

- 3 ). Conversely,

by requiring the installation of closed

- cycle recirculating systems, which effectively reduce entrainment

mortality, Proposal Option 2 reduces A1E mortality by 76.7 percent (44.40/57.86) ( Table 3

- 3 ).Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 8



### Table 3

- 3 : Baseline IM&E and IM&E Reductions at All Regulated Facilities

(Manufacturing and Generating) in the North Atlantic, and Reductions Under the

Final Rule and O ther Options Considered

IM&E Loss Metric (per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

All Species (million A1E) 0.40 0.93 44.40 57.86

Forage Species (million A1E) 0.35 0.77 34.80 45.34

Commercial & Recreational Species (million A1E) 0.05 0.16 9.60 12.52

Commercial & Recreational Harvest (million fish) <0.01 0.02 0.91 1.19

A1E Losses with Direct Use Value (%) 1.5% 1.8% 2.1% 2.1%

Source: U.S. EPA analysis for this report



### Production forgone due to baseline IM&E is estimated to be 26.03 million pounds of fish, leading to a

decrease in fishery yield of 0. 98 million pounds per year ( Table 3

- 4 ). The final rule will result in

increased fishery fields of 0.01 million pounds per y ear. Increases in fishery yields under other options

considered range from less than 0.01 million pounds under Proposal Option 4 to 0.75 million pounds

under Proposal Option 2. Estimated increases in fishery yields under Proposal Option 2 are more than 75

times greater than under the final rule and Proposal Option 4 ( Table 3

- 4 ).

Table 3

- 4 : Baseline Losses in Fishery Yield, Catch, and Production

Forgone as a Consequence of IM&E at All Regulated Facilities

(Man ufacturing and Generating) in the North Atlantic, and Reductions

Under the Final Rule and Other Options Considered

IM&E Loss Metric (million per year) Reductions in Losses

Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

Forgone Fishery Yield (lbs) <0.01 0.01 0.75 0.98

Forgone Commercial Catch (lbs) <0.01 <0.01 0.33 0.43

Forgone Recreational Catch (fish) <0.01 <0.01 0.56 0.73

Production Forgone (lbs) 0.03 0.26 19.93 26.03

Source: U.S. EPA analysis for this report



### Raw numbers of IM& E in the North Atlantic can be found in Appendix Table C

- 4.

3.3.3 Mid

- Atlantic Region

Table 3

- 5 and Table 3

- 6 present e stimated baseline IM&E and reductions in IM&E under the final rule

and other options considered . Estimated total baseline IM&E in the Mid

- Atlan tic region is 630.97 million

A1Es per year, including 475.89 million A1Es of forage fish (75.4 percent). Approximately 3. 3 percent of

total baseline A1E mortality are assigned a direct use value from recreational or commercial fishing

( Table 3

- 5 ). Table 5 of Appendix C presents species

- specific data on impingement and entrainment under

the baseline conditions and estimated reductions under all options. Briefly, the vast majority ( 93.8

percent) of all A1E mortality in the Mid

- Atlantic occur as a consequence of entrainment mortality. Nearly

half ( 44.7 percent) of the IM&E estimated for commercially

- and recreationally

- harvested species occurs

in Blue Crab, and substantial IM&E (i.e., greater than 13 million A1E) is estimated for Atlantic Croaker,

Atlantic Menhaden, Spot, and White Perch.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 9 

### Because of the high proportion of IM&E attributed to entrainment mortality, EPA estimate s that the final

rule and Proposal Option 4 reduce A1E mortality by 5.2 perce nt (32.99/630.97) and 4

. 8 percent

(30.50/630.97), respectively ( Table 3

- 5 ). Conversely, by requiring the installation of closed

- cycle

recirculating systems, Proposal Option 2 would reduce A1E mortality by approximately 87.4 percent

(551.90/630.97)

.

Table 3

- 5 : Baseline IM&E and IM&E Reductions at All Regulated Facilities

(Manufacturing and Generating) in the Mid

- Atlantic, and Reductions Under the

Final Rule and Other Options Considered

IM&E Loss Metric (per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

All Species (million A1E) 30.50 32.99 551.90 630.97

Forage Species (million A1E) 11.63 12.75 415.46 475.89

Commercial & Recreational Species (million A1E) 18.87 20.25 136.44 155.08

Commercial & Recreational Harvest (million fish) 4.68 5.01 18.20 20.51

A1E Losses with Direct Use Value (%) 15.3% 15.2% 3.3% 3.3%

Source: U.S. EPA analysis for this report



### EPA projects that baseline IM&E reduces fishery production by 5 2

. 74 million pounds, and decreases

fishery yield by 1 5

. 07 million pounds per year ( Table 3

- 6 ). The final rule will result in increased fishery

yields of 3.89 million pounds per year. Increases in fishery yields under other op tions considered range

from 3.63 million pounds per year under Proposal Option 4 to 13.38 million pounds per year under

Proposal Option 2. Estimated increases in fishery yields under Proposal Option 2 are more than three

times greater than under the final rule and Proposal Option 4 ( Table 3

- 6 ).

Table 3

- 6 : Baseline Losses in Fishery Yield, Catch, and Production

Forgone as a Consequence of IM&E at All Regulated Facilities

(Manufacturing and Generating) in the Mid

- Atlantic, and Reductions

Under the Final Rule and Other Options Considered

IM&E Loss Metric (million per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

Forgone Fishery Yield (lbs) 3.63 3.89 13.38 15.07

Forgone Commercial Catch (lbs) 2.87 3.07 7.17 8.00

Forgone Recreational Catch (fish) 0.43 0.46 5.10 5.82

Production Forgone (lbs) 7.83 8.40 46.50 52.74

Source: U.S. EPA analysis for this report



### Raw numbers of IM&E in the Mid

- Atlantic region can be found in Appendix Table C

- 6.

3.3.4 South Atlantic Region

Table 3

- 7 and Table 3

- 8 present e stimated baseline IM&E and reductions in IM&E under the final rule

and other options considered . Estimated total baseline IM&E in the South Atlantic region is estimated to

be 26.36 million A1Es per year, including 24.61 million forage fish A1Es. Approximately 1. 1 percent of

total baseline A1E mortality is assigned a direct use value from recreational or commercial fishing ( Table

3

- 7 ). Table 7 of Appendix C presents species

- s pecific data on impingement and entrainment under theBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 10 

### baseline conditions and estimated reductions under all options. Unlike other regions, the majority ( 65.0

percent) of all A1E mortality in the South Atlantic occur as a consequence of impingement mortali ty.

Among commercially

- and recreationally

- harvested species, IM&E is greatest in Drums and Croakers and

Blue Crab.

Due to the high proportion of IM&E lost to impingement, the final rule and Proposal Option 4 are

projected to reduce A1E mortality by 49.1 p ercent (12.93/26.36) and 4 4

. 0 percent (11.61/26.36),

respectively . However, because the installation of closed

- cycle recirculating systems reduces water usage,

Proposal Option 2 is projected to reduce A1E mortality by 9 7 .1 percent (25.60/26.36) ( Table 3

- 7 )

.

Table 3

- 7 : Baseline IM&E and IM&E Reductions at All Regulated Facilities

(Manufacturing and Generating) in the South Atlantic, and Reductions Under the

Final Rule and Other Options Considered

IM&E Loss Metric (per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

All Species (million A1E) 11.61 12.93 25.60 26.36

Forage Species (million A1E) 10.98 12.21 23.91 24.61

Commercial & Recreational Species (million A1E) 0.63 0.72 1.69 1.75

Commercial & Recreational Harvest (million fish) 0.09 0.10 0.27 0.28

A1E Losses with Direct Use Value (%) 0.7% 0.8% 1.0% 1.1%

Source: U.S. EPA analysis for this report



### Production forgone due to baseline IM&E is estimated to be 0.71 million pounds per year, leading to a

decrease in fishery yield of approximately 0.12 million pounds per year. The final rule will increase

fishery yields of 0.05 million pounds per year. Increases in fishery yields under other opt ions considered

range from 0.04 million pounds per year under Proposal Option 4 to 0.12 million pounds per year under

Proposal Option 2. Estimated increases in fishery yields under Proposal Option 2 are more than two times

greater than under the final rule and Proposal Option 4 ( Table 3

- 8 ).

Table 3

- 8 : Baseline Losses in Fishery Yield, Catch, and Production

Forgone as a Consequence of IM&E at All Regulated Facilities

(Manufacturing and Generating) in the South Atlantic, and Reductions

Under the Final Rule and Other Options Considered

IM&E Loss Metric (million per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

Forgone Fishery Yield (lbs) 0.04 0.05 0.12 0.12

Forgone Commercial Catch (lbs) 0.04 0.04 0.08 0.08

Forgone Recreational Catch (fish) 0.01 0.02 0.10 0.11

Production Forgone (lbs) 0.12 0.15 0.67 0.71

Source: U.S. EPA analysis for this report



### Raw numbers of IM&E in the South Atlantic region can be found in Appendix Table C

- 8.

3.3.5 Gulf of Mexico Region

Table 3

- 9 and Table 3

- 10 present the e stimated baseline IM&E and reductions in IM&E under the final

rule and other options considered . Estimated total baseline IM&E in the Gulf of Mexico is estimated to beBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 11 

### 147.01 million A1Es per year, including 50.15 million forage fish A1Es. Approximately 8. 8 percent of

total baseline A1E mortality are assigned a direct use value from recreational or commercial fishing

( Table 3

- 9 ). Table 9 of Appendix C presents species

- s pecific data on impingement and entrainment under

the baseline conditions and estimated reductions under all options. The majority ( 63.6 percent) of all A1E

mortality in the Gulf of Mexico occur as a consequence of entrainment mortality. Among commercially

and recreationally

- harvested species, IM&E is greatest in Blue Crab, and Pink Shrimp, which together

account for 67.8 percent of A1E mortality with direct use value. Other commercially

- or recreationally

harvested fish species with substantial IM&E (i.e. , greater than 5 million A1E) include Black Drum,

Menhaden, and Silver Perch (Appendix Table C

- 9).

Due to the low proportion of IM&E lost to impingement, the final rule and Proposal Option 4 are

proje cted to reduce A1E mortality by 27.4 percent (40.29/147. 01) and 2 6

. 4 percent (38.82/147.01)

, respectively. In contrast, Proposal Option 2 is estimated to reduce A1E mortality by 7 0.3 percent

(103.42/147.01) ( Table 3

- 9 ), nearly triple the estimated reductions of the final rule or Proposal Option 4.

Table 3

- 9 : Baseline IM&E and IM&E Reductions at All Regulated Facilities

(Manufacturing and Generating) in the Gulf of Mexico, and Reductions Under the

Final Rule and Other Options Considered

IM& E Loss Metric (per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

All Species (million A1E) 38.82 40.29 103.42 147.01

Forage Species (million A1E) 4.88 5.06 31.69 50.15

Commercial & Recreational Species (million A1E) 33.94 35.22 71.73 96.86

Commercial & Recreational Harvest (million fish) 5.15 5.35 9.83 12.92

A1E Losses with Direct Use Value (%) 13.3% 13.3% 9.5% 8.8%

Source: U.S. EPA analysis for this report



### Production forgone due to baseline IM&E is estimated to be 79.65 million pounds per year, 43.3 percent

of which is forgone fishery yield. The final rule will result in increased fishery yields of 3.51 million

pounds per year. Increases in fishery yields under other options considered range from 3. 38 million

pounds per year under Proposal Option 4 to 21.78 million pounds per year under Proposal Option 2.

Estimated increases in fishery yields under Proposal Option 2 are more than six times greater than under

the final rule and Proposal Option 4 ( Tabl e 3

- 10 ).

Table 3

- 10 : Baseline Losses in Fishery Yield, Catch, and Production

Forgone as a Consequence of IM&E at All Regulated Facilities

(Manufacturing and Generating) in the Gulf of Mexico, and Reductions

Under the Final Rule and Other Options Considered

IM&E Loss Metric (million per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

Forgone Fishery Yield (lbs) 3.38 3.51 21.78 34.45

Forgone Commercial Catch (lbs) 1.64 1.70 4.27 6.03

Forgone Recreational Catch (fish) 0.75 0.78 2.14 3.08

Production Forgone (lbs) 6.54 6.78 49.81 79.65

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 12 

### Raw numbers of IM&E in the Gulf of Mexico can be found in Appendix Table C

- 10.

3.3.6 Great Lakes Region

Table 3

- 11 and Table 3

- 12 present e stimated baseline IM&E and reductions in IM&E under the final rule

and other options considered . Estimated total baseline IM&E in the Great Lakes is 261.26 million A1Es

per year, including 240.01 millio n A1E of forage fish. Approximately 1. 7 percent of total baseline A1E

mortality is assigned a direct use value from recreational or commercial fishing ( Table 3

- 11 ). Table 11 of

Appendix C presents species

- specific data on impingement and entrainment under the baseline conditions

and estimated reductions under all options. Briefly, among commercially and recreationally

- harvested

species, the greatest losses occur in Smelts.

The vast majority ( 90.6 percent) of IM&E in the Great Lakes occur due to impin gement (Appendix Table

C

- 11). Accordingly, the final rule and Proposal Option 4 are projected to reduce baseline A1E mortality

by 81.5 percent (202.58/248.47) and 70.4 percent (184.04/261.26) , respectively ( Table 3

- 11 ). By

requiring the installation of clo sed

- cycle recirculating systems , which reduce the volume of water

required for cooling purposes, Proposal Option 2 reduces A1E mortality by 95.1 percent (248.47/261.26)

( Table 3

- 11 ).

Table 3

- 11 : Baseline IM& E and IM&E Reductions at All Regulated Facilities

(Manufacturing and Generating) in the Great Lakes, and Reductions Under the

Final Rule and Other Options Considered

IM& E Loss Metric (per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

All Species (million A1E) 184.04 202.58 248.47 261.26

Forage Species (million A1E) 175.88 193.58 230.50 240.01

Commercial & Recreational Species (million A1E) 8.16 9.00 17.97 21.25

Commercial & Recreational Harvest (million fish) 2.58 2.84 3.98 4.35

A1E Losses with Direct Use Value (%) 1.4% 1.4% 1.6% 1.7%

Source: U.S. EPA analysis for this report



### Production forgone due to baseline IM&E is estimated to be 63.28 million pounds of fish, leading to a

decrease in fishery yield of 4.14 million pounds per year ( Table 3

- 12 ). The final rule will result in

increased fishery yields of 2.69 million pounds per year. Increases in fishery yields under other options

considered range from 2.4 4 million pounds per year under Proposal Option 4 to 3.78 million pounds per

year under Proposal Option 2. Estimated increases in fishery yields under Proposal Option 2 are over 40

percent greater than under the final rule or Proposal Option 4 ( Table 3

- 12 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 13



### Table 3

- 12 : Baseline Losses in Fishery Yield, Catch, and Production

Forgone as a Consequence of IM&E at All Regulated Facilities

(Manufacturing and Generating) in the Great Lakes, and Reductions

Under the Final Rule and Other Options Considered

IM&E Loss Metric (million per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

Forgone Fishery Yield (lbs) 2.44 2.69 3.78 4.14

Forgone Commercial Catch (lbs) 1.12 1.24 1.70 1.84

Forgone Recreational Catch (fish) 1.33 1.47 2.04 2.23

Production Forgone (lbs) 30.67 33.79 55.61 63.28

Source: U.S. EPA analysis for this report



### Raw numbers of IM&E in the Great Lakes region can be found in Appendix Table C

- 12.

3.3.7 Inland Region

Table 3

- 13 and Table 3

- 14 present e stimated baseline IM&E and reductions in IM&E under the final rule

and other options considered . Estimated total baseline IM&E in the Inland region is 755.97 million A1Es

per year, including 599.13 million A1E of forage fish. Approximately 1. 6 percent of total baseline A1E

mortality is assigned a direct use value from recreational or commercial fishing ( Table 3

- 13 ). Table 13 of

Appendix C presents species

- specific data on impingement and entrainment under the baseline conditions

and estimated reductions under all options. Briefly, the majority ( 63.0 percent) of all A1E mortality in the

Inland region occur as a consequence of impingement mortality (Appendix Table C

- 13). Notably, the

IM&E of sunfish ac count for 78.4 percent of the IM&E of recreationally

- harvested species.

The final rule and Proposal Option 4 are projected to r educe baselin e A1E mortality by 47.8 percent

(361.55/755.97) and 46.0 percent (348.12/755.97) , respectively ( Table 3

- 13 ). The ins tallation of closed

cycle recirculating systems under Proposal Option 2 reduces A1E mortality by 83.6 percent

(632.19/755.97) , providing a benefit more than 70 percent larger than the benefits of the final rule or

Proposal Option 4 ( Table 3

- 13 ).

Table 3

- 13 : Baseline IM&E and IM&E Reductions at All Regulated Facilities

(Manufacturing and Generating) in the Inland Region, and Reductions Under the

Final Rule and Other Options Considered

IM&E Loss Metric (per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

All Species (million A1E) 348.12 361.55 632.19 755.97

Forage Species (million A1E) 324.34 336.25 507.31 599.13

Commercial & Recreational Species (million A1E) 23.79 25.31 124.88 156.84

Commercial & Recreational Harvest (million fish) 3.57 3.73 9.70 11.90

A1E Losses with Direct Use Value (%) 1.0% 1.0% 1.5% 1.6%

Source: U.S. EPA analysis for this report



### The decrease in production due to baseline IM&E is estimated to be 384.55 million pounds of fish,

leading to a decrease in fishery yield of 10

. 41 million pounds per year ( Table 3

- 14 ). The final rule will

result in increased fishery yields of 3. 25 million p ounds per year. Increases in fishery yield under other

options considered range from 3.11 million pounds per year under Proposal Option 4 to 8.48 millionBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 14 

### pounds per year under Proposal Option 2. Estimated increases in fishery yields under Proposal Option 2

are over two times greater than under the final rule and Proposal Option 4 ( Table 3

- 14 ).

Table 3

- 14 : Baseline Losses in Fishery Yield, Catch, and Production

Forgone as a Consequence of IM&E at All Regulated Facilities

(Manufacturing and Generating) in the Inland Region, and Reductions

Under the Final Rule and Other Options Considered

IM&E Loss Metric (million per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

Forgone Fishery Yield (lbs) 3.11 3.25 8.48 10.41

Forgone Commercial Catch (lbs) <0.01 <0.01 <0.01 <0.01

Forgone Recreational Catch (fish) 3.57 3.73 9.70 11.90

Production Forgone (lbs) 84.97 89.40 309.65 384.55

Source: U.S. EPA analysis for this report



### Raw numbers of IM&E in the Inland region can be found in Appendix Table C

- 14.

3.3.8 National Estimates

Table 3

- 15 and Table 3

- 16 present e stimated baseline IM&E and reductions in IM&E under the final rule

and other options considered . Estimated total baseline IM&E nationally is 1,930.97 million A1Es per

year, including 1,459.70 million A1E of forage fish. Approximately 2. 8 percent of total baseline A1E

mortality is assigned a direct use value from recreational or commercial fishing ( Table 3

- 15 ). Table 15 of

App endix C presents species

- specific data on impingement and entrainment under the baseline conditions

and estimated reductions under all options. Briefly, the majority ( 57.3 percent) of all A1E mortality

nationally occur as a consequence of entrainment morta lity (Appendix Table C

- 15).

The final rule and Proposal Option 4 are projected to reduce baseline A1E mortality by 33.8 percent

(652.00/1,930.97) and 31.8 percent (614.16/1,930.97) , respectively ( Table 3

- 15 ). The installation of

closed

- cycle recirculating systems under Proposal Option 2 reduces A1E mortality by 84.8 percent

(1,637.49/1,930.97) , providing a benefit more than twice as large as the benefits of the final rule or

Proposal Option 4 ( Table 3

- 15 ).

Table 3

- 15 : Baseline IM&E and IM&E Reductions at All Regulated Facilities

(Manufacturing and Generating) Nationally, and Reductions Under the Final Rule

and Other Options Considered

IM&E Loss Metric (per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

All Species (million A1E) 614.16 652.00 1637.49 1930.97

Forage Species (million A1E) 528.22 560.80 1258.67 1459.70

Commercial & Recreational Species (million A1E) 85.94 91.20 378.82 471.28

Commercial & Recreational Harvest (million fish) 16.13 17.11 44.66 54.02

A1E Losses with Direct Use Value (%) 2.6% 2.6% 2.7% 2.8%

Source: U.S. EPA analysis for this report



### The decrease in production due to baseline IM&E is estimated to be 626.60 million pounds of fish,

leading to a decrease in fishery yield of 69.76 million pounds per year ( Table 3

- 16 ). The final rule isBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 15 

### estimated to result in an increased fishery yield 13.42 million pounds per year

. Increases in fishery yields

under other options considered range from 12.63 million pounds per year under Proposal Option 4 to

51.11 million pounds per year under Proposal Option 2. Estimated increases in fishery yields under

Proposal Option 2 are nearly four times greater than under than final rule or Proposal Option 4 ( Table

3

- 16 ).

Table 3

- 16 : Baseline Losses in Fishery Yield, Catch, and Production

Forgone as a Consequence of IM&E at All Regulated Facilities

(Manufacturing and Generating) Nationally, and Reductions Under the

Final Rule and Other Options Considered

IM&E Loss Metric (million per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

Forgone Fishery Yield (lbs) 12.63 13.42 51.11 69.76

Forgone Commercial Catch (lbs) 5.68 6.07 14.72 18.32

Forgone Recreational Catch (fish) 6.13 6.50 20.53 25.31

Production Forgone (lbs) 130.25 138.89 494.17 626.60

Source: U.S. EPA analysis for this report



### Raw numbers of national IM& E can be found in Appendix Table C

- 16.



## 3.4 Limitations and Uncertainties

F our major kinds of uncertainty may lead to imprecision and bias in EPA’s IM&E analysis: data,

structural, statistical, and engineering uncertainty. Data limitations and uncertainty re fers to uncertainty

and inconsistency in sampling methodologies used in facility

- specific IM&E studies. Structural

uncertainty reflects the simplification built into any model of a complex natural system. Parameter

uncertainty refers to uncertainty in the numeric estimates of model parameters. Finally, engineering

uncertainty refers to the fact that facilities do not operate in the exact same manner on an annual basis.

3.4.1 Data Limitation and Uncertainty

EPA based its q uantification of regional and national IM &E on cumulative data generated by collection at

individual facilities. In turn, these data are heterogeneous products of location

- specific investigations set

in differing geographic and ecological provinces. Interpretation of the significance and trends o f IM&E at

regional and national scales (and of the accompanying ecological benefits upon mitigation) must consider

the strengths and weaknesses of this data.

The IM&E data from model facilities constitute a heterogeneous composite of results from many faci lity

specific studies. Sampling effort and data quality control vary tremendously among IM&E studies and

baseline source water characterization programs. There is little uniformity among studies as to the

intensity, frequency and duration of data collectio n as well as the scope of target biota collected,

identified, and enumerated. Sampling regimes may be properly adjusted to ensure that changes in local

biotic activity associated with diurnal, tidal, and lunar cycles are incorporated; or may reflect regula rly

spaced sampling points with little concern paid to capturing environmental variability.

In addition to the differences in environmental scope, sampling methods are not uniform among studies

with regard to the types and meshes of sampling nets, deploym ent location of sampling nets (e.g., outside

or within the intake structure), length and weight measurements, observations of field conditions,Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 16 

### characterization of reference areas, etc. In addition to different sampling methods and timing, some

sampling pr ograms are designed primarily to estimate IM&E for a select suite of recreational or

commercially important aquatic organisms. Studies differ in their taxonomic sorting classes and

specificity of identification of impinged and entrained organisms (e.g., eg gs, ichthyoplankton,

zooplankton, etc.). Thus, many IM&E studies are poorly suited to provide insight into the direct and

indirect impacts to forage fish species, non

- vertebrate organisms (zooplankton, tunicates, algae, worms,

etc.), or community/ecosystem impacts. For older facilities, sampling data commonly lack pre

- operational

(i.e., baseline) samples or community surveys to compare to the results of more

- current IM&E data.

Finally, few IM&E studies are designed to allow evaluation of community impacts o r ecosystem effects

(Section 2.4).

Within regions, studies of IM&E from model facilities are typically composed of data from a relatively

limited number of facilities. Most facility

- specific IM&E studies are limited to one or two years, and are

rarely rep licated within a time period that allows direct comparison of trends without historical

complications due to fishery stock trends, climatic changes, or shifts in collection methods or water

quality. Thus, studies within a regional database may not accurate ly represent average climatic and

oceanographic conditions (e.g., El Nino years). Additionally, studies within the database may include

historical (>20 years ago ) and recent data, thus incorporating considerable uncertainty due to the annual

variability of highly dynamic fish stocks. Thus, extrapolation from regional collections of facility

- specific

studies may not provide a true regional estimate because the available data may or may not be fully

representative of regional trends and/or of associated ecolo gical benefits derived from mitigating IM&E

impacts.

3.4.2 Structural Uncertainty

The models EPA used to evaluate IM&E simplify complex processes. The degree of simplification is

substantial, but necessary, because of limited data availability and the need to g enerate estimates on a

national scale. Simplification occurs with respect to many processes within the model, to ensure

computational tractability and national applicability ( Table 3

- 17 ).

While EPA recognizes these uncertainties, addressing each of these uncertainties in a defensible way

would require data that does not currently exist (see Section 3.2.4.2 ), would be time

- consuming and

resource

- intensive to develop, and c ould lead to greater parameter uncertainty (Section 3.4.3 ).Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 17 

### Table 3

- 17 : Structural Uncertainties

Aspect of Model General Description Specific Treatment in Model

Biological

submodels Life history traits are fixed Life history parameters in the models (i.e., growth, survival) are constant

through time and are thus independent of biological conditions (e.g., fish

densities, seasonality, weather, recruitment variability, food availability,

fisheries pressure, etc.).

No trophic effects Indirect food web effects such as trophic cascades, growth and population

limitations due to a lack of food, etc., are not considered. Trophic transfer

is treated simplistically.

Outside impacts not addressed IM&E loss rates are affected by a variety of outside influences not included

in the model (e.g., fisheries pressure, pollution, future development,

invasive species, climate change, etc.).

Valuation

structure National nonuse benefits Fish species grouped into two categories: harvested or not harvested (i.e.,

forage for harvested species). Harvested fish are assigned use values within

the national analysis. EPA used benefit transfer to estimate nonuse values

for the North Atlantic and Mid

- Atlantic regions (Chapter 8). Nonuse values

for other regions are not included in the comparison of benefits and costs

for the final rule. EPA also conducted a stated preference survey to assess

total values (Chapter 10). EPA, however, did not include survey estimates

in its benefits totals for the rule but the estimates illustrate the potential

magnitude of total va lues.

Fishing pressure constant The valuation procedure assumes that fisheries harvests will increase

proportionately to decreases in IM&E, independent of Federal and State

policies on commercial and recreational fishing (i.e., fisheries quotas,

closures , bag limits, etc.).



### 3.4.3 Parameter Uncertainty

Parameter uncertainty refers to variability in the value of parameters used in biological and economic

modeling. EPA must estimate a ll parameters from sampling studies that cannot identify the true values of

interest due to statistical and logistical limitations. These limitations are broadly driven by three

processes, including parameter fluctuation through time, geographic location, and sampling.

The true value of many biological parameters fluctuates on an annual basis, due to changes in weather,

food availability, indirect food

- web effects, and compensatory population dynamics. Consequently,

parameter values used within biological submodels, despite being based upon the best available data

obtained from the scientific literature, cannot be without error due to annual variability in fish growth and

(natural and fisheries) mortality rates. Similarly, because IM&E rates are driven by a combination of

intake flow and the presence of vulnerable fish, actual IM&E cannot remain constant through time.

True values of biological parameters and facility IM&E vary geographically. Biological parameters may

vary substantially within regions due t o changes in substrate, water temperature and salinity, etc., while

facility IM&E data may be strongly connected to local substrates, distance from shore, depth, etc. It

follows, then, that using biological data and extrapolating facility

- specific IM&E rat es to the regional

scale will result in parameter variability based solely on geographic considerations.

Finally, all model parameters contain uncertainty because they are small samples taken from a much

larger dataset. Biological parameters such as morta lity rates must be estimated using incomplete sampling

data. Facility

- reported IM&E studies necessarily subsample cooling water, and often do not take replicate

samples across tidal periods, seasons, time of day, and between years. Moreover, these studies often

present IM&E with limited taxonomic detail (i.e., the identification of eggs, larvae, and juveniles is not

species

- specific), and do not have standard methodologies. As is the case with retrospective data, these

studies also reflect the biological an d physical state of the waterbody when studies were conducted. In

some cases, the state of the waterbody itself has changed substantially since sampling was conducted.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 18 

### EPA recognizes many sources of parameter uncertainty in its models ( Table 3

- 18 ), all of which lead to

uncertainty in point estimates of IM&E . The nature of these uncertainties, however, does not inherently

bias the point estimate. EPA reported all biological and physical parameters in good faith, and as such,

parameter estimates are unlikely to be biased in aggregate, but distributed both above and below true

parameter values. Thus, parameter uncertainty has resulted in imprecision rather than inaccuracy in model

output. 12



### 3.4.4 Engineering Uncertainty

EPA’s evaluation of IM&E was also affected by u ncertainty about the engineering and operating

characteristics of the study facilities. It is unlikely that facility operating characteristics (e.g., seasonal,

diurnal, or intermittent changes in intake water flow rates) are constant throughout any particu lar year. As

such, the timing of sampling, and the annual repeatability of IM&E , may be biased by facility operating

conditions. EPA assumed that the facilities’ loss estimates were provided in good faith and did not

include any biases or omissions that si gnificantly modified loss estimates.

12 Accuracy refers to the degree of closeness of model results to the actual value. P r ecision refers to the reproducibilit y of model

output, or the degree to which repeated measurements (or samples, for example from different model facilities) under similar

conditions will result in the same model output.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 3: Assessment of IM&E

May 2014 3

- 19 

### Table 3

- 18 : Parameters Included in EPA’s IM&E Analysis Subject to Uncertainty

Model Aspect Parameter Description

IM&E monitoring

/loss rate estimates Sampling regimes Sampling regimes are subject to numerous facility

- specific details. No

established guidelines or performance standards for how to design and conduct

sampling regimes. Not all sampling studies measured both impingement and

entrainment mortality.

Extrapolation

assumptions Extrapolation of monitoring data to annual IM&E rates assumes sampling

occurred under average conditions, and that diurnal/seasonal/annual cycles in

fish presence and vulnerability and various technical factors (e.g., net

collecti on efficiency; hydrological factors affecting IM&E rates) do not play a

substantial role in the accuracy of extrapolation. No established guidelines or

consistency in sampling regimes.

Species selection Criteria for the selection of species evaluated in IM&E studies are neither

well

- defined nor uniform across facilities. At many facilities, IM&E data was

collected for only a subset of species, usually only fish and shellfish.

Sensitivity of fish to

IM&E Entrainment mortality was assumed by EPA to be 100 percent. Back

calculations were done in cases where facilities reported entrainment rates that

assumed <100 percent mortality. These calculations were limited by data

reporting (i.e., species

- specific survival rates were not always provided).

Impingement survival was included if presented in facility documents.

Biological/life

history Natural mortality rates Natural mortality rates (M) difficult to estimate, and vary with time and

geography. Model results are highly sensitive to M.

Growth rates Simple e xponential growth rates or simple size

- at

- age parameters used, and

assumed constant across all locations and years.

Geographic

considerations Migration patterns; IM&E occurring during spawning runs or larval out

migration; location of harvestable adults; intermingling with other stocks.

Forage valuation Harvested species assumed to be food limited; trophic transfer efficiency to

harvested species estimated by EPA based on general models; no consideration

of trophic transfer to species not impinged and e ntrained.

Fish stock

characteristics Fishery yield For most harvested species, only one species

- specific value for fishing

mortality rate (F) was used for all stages subject to harvest. Used stage

- specific

constants for fraction vulnerable to fishery.

Harvest behavior No assumed dynamics among harvesters to alter fishing rates or preferences in

response to changes in stock size. Recreational access assumed constant (no

changes in angler preferences or effort).

Stock interactions IM&E assumed to be par t of reported fishery yield rates on a statewide basis.

No consideration of possible substock harvest rates or interactions, no

unreported catch.

Ecological

system Fish community Long

- term trends in fish community composition or abundance were not

considered (general food webs assumed to be static), nor were indirect trophic

interactions. Used constant value for trophic transfer efficiency, and specific

trophic interactions were not considered. Trophic transfer to organisms not

impinged and entraine d is not considered.

Spawning dynamics Sampled years assumed to be typical with respect to choice of spawning areas

and timing of migrations that could affect vulnerability to IM&E

(e.g., presence of larvae in vicinity of intake structure).

Hydrology Sampled years assumed to be typical with respect to flow regimes and tidal

cycles that could affect vulnerability to IM&E (e.g., presence of larvae in

vicinity of CWIS).

Meteorology Sampled years assumed to be typical with respect to vulnerability to IM& E

(e.g., presence of larvae in vicinity of intake structure).Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 4: Econ omic Benefit Categories

May 2014 4

- 1 

# 4 Economic Benefit Categories

Changes in CWIS design or operations resulting from the final s ection 316(b) rule for regulated facilities

are expected to reduc e IM&E of fish, shellfish, and other aquatic organisms , thereby increas ing the

numbers of aquatic or ganisms and local and regional fishery populations

.

The aquatic organisms affected by CWIS provide a wide range of ecosystem services. Ecosystem services

are the physical, chemical, and biological functions performed by natural resources and the human

benefits derived from those functions, including both ec ological and human use services ( Daily 1997 ;

Daily et al. 1997 ) . Scientific and public interest in protecting ecosystem services is increasing with the

recognition that these services are vuln erable to a wide range of human activities and are difficult, if not

impossible, to replace with human technologies ( Meffe 1992 )

.

In addition to their importance in providing food and other goods of direct use to hum ans, the organisms

lost to IM&E are critical to the continued functioning of the ecosystems of which they are a part. Fish are

essential for energy transfer in aquatic food webs, regulation of food web structure, nutrient cycling,

maintenance of sediment p rocesses, redistribution of bottom substrates, the regulation of carbon fluxes

from water to the atmosphere, and the maintenance of aquatic biodiversity ( Holmlund and Hammer 1999 ;

Peterson and Lubchenco 1997 ; Postel and Carpenter 1997 ; Wilson and Carpenter 1999 ) . Many of these

ecosystem services can be maintained only by the continued presence of all life st ages of fish and other

aquatic species in their natural habitats. Section 2.3 provide s detail on potential CWIS impacts on aquatic

ecosystems , but because of inadequate data, EPA could not evaluate or monetize many of these impacts.

In addition to economic benefits categories associated with the reductions in IM&E, EPA also assessed

benefits associated with changes in carbon dioxide (CO 2 

### ) emissions. EPA monetized these benefits based

on the social cost of carbon. Social cost of carbon is an “estimate of the monetized damages associated

with an incremental increase in carbon emissions in a given year” and it “is intended to include (but is not

limited to) changes in net agricultural productivity, human health, property damages from increased flood

risk, and t he value of ecosystem services due to climate change” ( Interagency Working Group 2010, p.1 )

. The following sub

- sections focus on b enefits categories associated with IM&E reductions. See Chapter 9

for additional discussion of benefits from changes in emissions based on the social cost of carbon.



## 4.1 Economic Benefit Categories of the Rule

The economic benefits of reducing I M &E at regulated facilities stem from both market and nonmarket

goods and services that the affected resources provide. These benefits can be divided into the following

categories ( Table 4

- 1 , below).

 Market benefits: Market benefits are positive welfare impacts t hat can be quantified using

money

- denominated measures of consumer and producer surplus. The most obvious example of

market benefits from reduced IM&E is benefits to commercial fisheries. Changes in IM&E will

directly affect the price, quantity, and/or qua lity of fish harvests . T he monetary value of the

changes can be measured directly through market measures of consumer and producer behavior.

Market benefits may be further categorized in terms of direct and indirect benefits. By definition,

all market bene fits are use benefits, as they involve either direct or indirect uses of goods or

services.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 4: Econ omic Benefit Categories

May 2014 4

- 2 

###  Market direct use benefits: These benefits are related to goods directly used

, and bought

and sold in markets; for example, fish caught for sale to consumers.

 Mark et indirect use benefits: These benefits occur through indirect or secondary effects on

marketed goods and contribute indirectly to an increase in welfare for users of the resource.

For example, an increase in the number of forage fish may increase the pop ulation of

commercially valuable species, which are marketed to consumers. Thus, reducing IM&E of

forage species can result in indirect welfare gains for commercial fishers and consumers who

purchase fish.

 Nonmarket benefits: Nonmarket benefits consist of goods and services that are not traded in the

marketplace, but are nonetheless positively affected by reduced IM&E . Higher catch rates for

recreational fishing are a nonmarket benefit. A nglers place a high value on catching f ish during

their fishing trips, so higher catch rates from reduced IM&E will translate directly to greater

utility from participation in recreational fishing. Because the monetary value of these

improvements cannot be established by observing market transa ctions, nonmarket valuation

techniques must be employed to estimate such benefits. Nonmarket benefits may be further

categorized in terms of direct and indirect use benefits, and nonuse benefits.

 Nonmarket direct use benefits: These benefits consist of go ods and services that have direct

uses, but are not traded in the marketplace. Higher catch rates for recreational fishing provide

a typical nonmarket direct use benefit.

 Nonmarket indirect use benefits: These benefits contribute indirectly to an increase the

welfare of those who engage in nonmarketed uses of a resource. For example, positive

impacts on local fisheries may generate an improvement in the population levels and diversity

of fish

- eating bird species. In turn, bird watchers might obtain greater enjoyment from their

outings, as they are more likely to see a wider mix or greater numbers of birds. The increased

welfare of the bird watchers is thus an indirect consequence of the initial impact on fish.

 Nonuse benefits: These benefits occur when indi viduals value improved environmental

quality without any past, present, or anticipated future use of the resource in question.

Individuals may gain utility simply from knowing that a particular good exists (existence

value), or from knowing that a good is available for others to use now and in the future

(bequest value). Nonuse , or passive, benefits of reduced IM&E may include increased

biodiversity, improved conditions for the recovery of T&E species that have no direct or

indirect uses and welfare gains t o nonusers when reduced IM&E to forage species improve

overall ecosystem function.

Table 4

- 1 presents the benefit categories EPA considered for regulated facilities. The table also presents

the various data needs, data sources, and estimation approaches associated with each category. A

complete list of the ecosystem services potentially affect ed by reduction in I M &E is presented in Chapter

2 (Table 2

- 4).

In addition the approaches presented in Table 4

- 1 , EPA developed and implemented an original stated

preference (SP) study to estimate the total monetary valu e (use plus nonuse value) of aquatic resource

improvements from the 316(b) rule

. 13 

### EPA has not accounted for values estimated from the s urvey in the

quantitative comparison of costs and benefits. EPA plans to obtain Science Advisory Board ( SAB ) review

13 SP surveys , in general, ask questions that elicit individuals’ value s for carefully specified changes in an environmental

amenity ( Freeman III 2003 )Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 4: Econ omic Benefit Categories

May 2014 4

- 3 

### of the SP survey , and considers the inclusion of benefits based on the survey to be premature prior to the

completion of the SAB review. Cha pter 11 presents preliminary survey results to illustrate the potential

magnitude of benefits.

Table 4

- 1 : Summary of Benefit Categories

, Data Needs, Potential Data Sources, Approaches,

and Analyses Completed

Benefit Category Basic Data Needs Potential Da ta Sources/

Approaches/Analyses Completed

Market Goods, Direct Use

 Increased commercial landings  Estimated change in landings of

specific species

 Estimated change in total economic

impact  Based on facility

- specific I M &E data

and ecological modeling.

 Changes in commercial fishery

landings estimated using a market

based approach.

 Indirect economic impacts not

estimated due to data constraints.

Market Goods, Indirect Use

Increase in:

 Equipment sales, rental, and repair

 Bait and tackle sales

 Consumer market choices

 Choices in restaurant meals

 Property values near the water

 Ecotourism (charter trips, festivals,

other organized activities with fees

, such as riverwalks)  Estimated change in landings of

specific species

 Relationship between increased

fish/s hellfish landings and secondary

markets

 Local activities and participation

fees

 Estimated numbers of participating

individuals  Indirect market impacts not estimated

due to data constraints such as lack of

information on the relationship

between increased f

ish/shellfish yield

and secondary impacts.

Nonmarket Goods, Direct Use

 Improved value of a recreational

fishing trip due to increased catch of

targeted/preferred species and

incidental catch

 Improved value of subsistence

fishing

 Value of additional recreational

participation and additional fishing

trips  Value of an improvement in catch

rate

 Esti mated number of affected

anglers or estimate of potential

anglers

 Value of a fishing day  Changes in the value of a recreational

fishing trip estimated based on benefit

transfer (including recreational use

values of selected T&E species).

 Changes in the value of subsistence

fishing not estimated.

 Number of affected anglers and

increase in trips not estimated due to

data constraints.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 4: Econ omic Benefit Categories

May 2014 4

- 4 

### Table 4

- 1 : Summary of Benefit Categories

, Data Needs, Potential Data Sources, Approaches,

and Analyses Completed

Benefit Category Basic Data Needs Potential Data Sources/

Approaches/Analyses Completed

Nonmarket Goods, Indirect Use

 Increase in value of boating, scuba

diving, and near

- water recreational

experience from observing fish

while boating, scuba

- diving, hiking,

or picnicking, and watching aquatic

birds fish or catch aquatic

invertebrates

 Increase in boating, scuba

- diving,

an d near

- water recreation

participation  Estimated number of affected near

water recreationists, divers, and

boaters

 Value of boating, scuba

- diving, and

near

- water recreation experience

 Value of a recreation day  Increased trip value n ot estimated due

to data constraints such as number of

affected recreational users.

 Changes in recreational participation

were not estimated. They are

expected to be negligible at the

regional level because fishery yield

impacts are generally small.

Nonuse Goods

Increase in nonuse values such as:

 Existence (stewardship)

 Altruism (interpersonal concerns)

 Bequest (interpersonal and

intergenerational equity) motives

 Appreciation of the importance of

ecological services apart from human

uses or motives (Table 2

- 4)  I M &E estimates

 Primary valuation research using

stated preference approach

 Applicable studies upon which to

conduct benefit transfer

 Location of CWIS and T&E species

ranges  Estimate nonuse values for an

increase in relative fish abundance

within two benefits regions using

benefit transfer. Not estimated for

other regions due to a lack of

applicable studies.

 Used geographic information system

(GIS) data to identify T&E species

potentially impacted by CWIS based

on the overlap of CWIS locations and

T&E species ranges.

 E PA used the results of the 316(b)

stated preference survey to illustrate

total values for the 316(b) rule,

including nonuse values . However,

did not include estimates based on the

316(b) SP survey in its comparison of

costs and benefits of the rule.



## 4.2 Market and Nonmarket Direct and Indirect Use Benefits from Reduced IM&E

Direct use benefits from reduced IM&E are the simplest to envision. The welfare of commercial,

recreational, and subsistence fishers is improved when fish stocks increase

, and catch ra tes rise or effort

decreases. Higher catch rates increase the revenue and growth of commercial fisheries, the enjoyment of

recreational fishing trips, and the availability of food for subsistence fishers

— all of which are quantifiable

benefits arising direc tly from changes in I M &E. Methodologies for estimating use values for recreational

and commercial species are well developed, and some of the species affected by I M &E have been studied

extensively. As a result, estimation of associated use values is often straightforward.

Indirect use benefits refer to welfare improvements for those individuals whose activities are enhanced as

an indirect consequence of fishery or habitat improvements. For example, an improvement in the

population of a forage fish species m ay be of no direct consequence to recreational or commercial fishers.

However, the increased presence of forage fish will have an indirect effect on commercial and

recreational fishing values if it increases food supplies for commercial and recreational pr edatory species.

Thus, improvements in forage species populations can result in a greater number (and/or greater

individual size) of those fish that are targeted directly by recreational or commercial fishers. In such an

instance, the incremental increase in recreational and commercial fishing benefits would be an indirect

consequence of the effect on forage fish populations.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 4: Econ omic Benefit Categories

May 2014 4

- 5 

### The following sections discuss the benefits estimates presented in each chapter of this report, and

techniques for estimating benefit s of reduced I M &E for each category of benefits. 14



### 4.2.1 Commercial Fisheries

Commercial fishing benefits include both direct and indirect market use values. The social benefits

derived from increased landings by commercial fishers can be valued by examining the markets through

which the landed fish are sold. The first step of the analysis involves a fishery

- based assessment of

I M &E

- related changes in commercial landings (pounds of commercial species as sold dockside by

commercial harvesters). The changes in landi ngs are then valued according to market data from relevant

fish markets (dollars per pound) to derive an estimate of the change in gross revenue to commercial

fishers. The final steps entail converting the I M &E

- related changes in gross revenues into estima tes of

social benefits. These social benefits consist of the sum of the producers’ and consumers’ surpluses that

are derived as the changes in commercial landings work their way through the multi

- market commercial

fishery sector.

Indirect use values in mar kets occur through increases in commercial species caused by increased

numbers of forage fish. An improvement in the population of a forage fish species may be of no direct

consequence to commercial fishers. However, the increased presence of forage fish w ill have an indirect

effect on commercial fishing values if it increases food supplies for commercial predatory species. Thus,

improvements in forage species populations can result in a greater number (and/or greater individual size)

of those fish that are targeted directly by commercial fishers. In such an instance, the incremental increase

in commercial fishing benefits would be an indirect consequence of the final rule’s effect on forage fish

populations. See Chapter 3 for a discussion on the indirect in fluence of forage fish on abundance of

commercial and recreational species.

Chapter 6 provides more detail on EPA’s analysis of commercial fishing benefits from reducing I M &E at

the regulated facilities’ cooling water intakes.

4.2.2 Recreational Fisheries

Recre ational fishing benefits include both direct and indirect nonmarket use values. R ecreational use

benefits cannot be tracked in the market because much of the recreational activity associated with these

fisheries occurs as nonmarket events. However, a varie ty of nonmarket valuation methods exist for

estimating use value, including both “revealed” and “stated” preference methods ( Freeman III 2003 )

. These methods use other observable behavior to infer users’ value for environmental goods and services.

Examples of revealed preference methods include travel cost, hedo nic pricing, and random utility models.

Compared to nonuse values, nonmarket use values are often considered relatively easy to estimate, due to

their relationship to observable behavior, the variety of revealed preference methods available, and public

fam iliarity with the recreational services that surface waterbodies provide.

To evaluate the recreational benefits of the regulatory options for regulated facilities, EPA developed a

benefit transfer approach based on a meta

- analysis of recreational fishing v aluation studies. The analysis

was designed to measure the various factors that determine WTP for catching an additional fish per trip.

14 Many of the fish species affected by IM&E at CWIS sites are harvested both recreationally and commercially. To avoid

double

- counting the economic impacts of IM&E of these species, EPA determined, based on historic NMFS landings data,

the proportions of total species landings attributable to recreational and commercial fishing, and applied these proportions to

the total number of affected fish.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 4: Econ omic Benefit Categories

May 2014 4

- 6 

### The estimated meta

- model allows EPA to calculat e the marginal value per fish for different species, based

on resource an d policy context characteristics.

Indirect use values for forage species occur through increases in recreational species caused by increased

numbers of forage fish. An improvement in the population of a forage fish species may be of no direct

consequence to recreational anglers. However, the increased presence of forage fish will have an indirect

effect on recreational fishing values if it increases food supplies for recreational predatory species. Thus,

improvements in forage species p opulations can result in a greater number (and/or greater individual size)

of those fish that are targeted directly by recreational anglers. In such an instance, the incremental

increase in recreational fishing benefits would be an indirect consequence of the effect on forage fish

populations. See Chapter 3 for a discussion on the indirect influence of forage fish on abundance of

commercial and recreational species.

Chapter 7 provides detail on the application of the meta

- regression model EPA used to estima t e

recreational fishing benefits of the final rule and regulatory options it considered

.

4.2.3 Subsistence Fishers

Subsistence fisheries benefits include both direct and indirect nonmarket use values. Subsistence use of

fishery resources can be important in are as where socioeconomic conditions (e.g., the number of low

income households) or the mix of ethnic backgrounds make such fishing economically or culturally

significant to a component of the community. In cases of Native American use of affected fisheries, the

value of an improvement can sometimes be inferred from settlements in legal cases

, e.g., compensation

agreements between affected tribes and various government or other institutions in cases of resource

acquisitions or resource use restrictions. For th e general population, the value of improved subsistence

fisheries may be estimated from the costs saved in acquiring alternative food sources. This method may

underestimate the value of a subsistence fishery meal to the extent that the store

- bought foods m ay be less

preferred by some individuals than consuming a fresh

- caught fish. Subsistence fishery benefits are not

included in EPA’s benefits regional analyses. Impacts on subsistence fishers may constitute an important

environmental justice consideration, which could result in EPA underestimat ing the total benefits of the

final rule and regulatory options it considered . EPA’s Environmental Justice analysis is presented in

Chapter 12 of the e conomic a nalysis of the final 316(b) rule (USEPA 2014a)

.

4.2.4 Benefits f rom Improved Protection to T&E Species

T&E and other special status species can be adversely affected in several ways by CWIS. T&E species

can suffer direct harm from I M &E; they can suffer indirect impacts if I M &E at CWIS adversely affects

another species upon which the T&E species relies within the aquatic ecosystem (e.g., as a food source);

or they can suffer impacts if the CWIS disrupts their habitat (e.g., via thermal discharges). The loss of

individuals of listed species from IM&E at CWIS is particular ly important because, by definition, these

species are already rare and at risk of irreversible decline because of other stressors.

Benefits from improved protection of T&E species can include both direct and indirect nonmarket use

values, as well as nonu se values. EPA identified nine special status fish species, six in California and

three in the Inland region, for which I M &E data were available. Due to their special status as well as the

fact that most of these species have either very limited or no dire ct uses, the major portions of the value

for T&E species are nonuse values. However, some of these species have potentially significant

recreational and commercial use values

, for example , sturgeon and paddlefish. EPA applied benefit

transfer to estimate r ecreational use values for a subset of T&E species for which limited catch andBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 4: Econ omic Benefit Categories

May 2014 4

- 7 

### release fisheries exist. EPA did not estimate potential commercial use values of these species due to the

lack of market data.

Chapter 5 provides more detail on EPA’s analysis of T&E species benefits from reducing I M &E at CWIS

of regulated facilities

.



## 4.3 Nonuse Benefits from Reduced IM&E

Comprehensive estimates of total resource value include both use and nonuse values, such that the

resulting total value estimates may be compared to total social cost. Recent economic literature provides

substantial support for the hypothesis that nonuse values, such as option and existence values, are greater

than zero. In fact, small per capita nonuse values held by a substantial fraction of the p opulation can be

very large in the aggregate. “Nonuse values, like use values, have their basis in the theory of individual

preferences and the measurement of welfare changes. According to theory, use values and nonuse values

are additive” ( Freeman III 1993 )

. 15 

### Consequently, both EPA’s own Guidelines for Preparing Economic

Analysis and the Office of Management and Budget’s (OMB) Circular A

- 4 governing r egulatory a nalysis,

support the need to assess nonuse values ( USEPA 2010 a; USOMB 2003 ) . Excluding nonuse values from

consideration is likely to understate substantially total social values.

Reducing I M &E of fish and shellfish may result in both use and nonuse benefits. Of the organisms that

EPA anticipate s will be protected by the s ection 316(b), only about 3 percent of A1E will eventually be

harvested by commercial and recreational fishers

, and therefore can be valued with direct use valuation

techniques. The remainder , which were not assign ed direct use value in this analysis, constitute the

majority

— 97 percent

— of the total estimated reductions in IM&E. Table 4

- 2 s ummarize s baseline I M &E

and reduction s in I M &E by four loss categories: all species, forage species, total commercial and

recreat ional species, and harvested commercial and recreational species. Although unlanded forage fish

contribute to the yield of harvested fish and therefore have an indirect use value that is captured by the

direct use value of the commercial species, this indi rect use value represents only a portion of the total

value of unlanded fish. Society also values both landed and unlanded fish for reasons unrelated to use

— for example, individual welfare may be affected simply by knowing these fish exist. Additionally, n onuse

values are likely to be substantial because fish and other species found within aquatic habitats impacted

directly and indirectly by CWIS provide other valuable ecosystem goods and services. These include

nutrient cycling and ecosystem stability. The refore, a comprehensive estimate of the welfare gain from

reducing I M &E must include an estimate of nonuse benefits.

In contrast to direct and indirect use values, nonuse values are oftenmore difficult to estimate. SP

methods, or benefit transfer based on SP studies, are the generally accepted techniques for estimating

these values ( USEPA 2010 a; USOMB 2003 ) . SP methods rely on carefully designed surveys, which

either ask individuals about their WTP for particular ecological improvements, such as increased

protection of aquatic specie s or habitats with particular attributes, or to choose among competing

hypothetical “packages” of ecological improvements and household cost in which the choice implies

WTP . In either case, values are estimated by statistical analysis of survey responses.

15 This additive property holds under traditional conditions related to resource levels and prices for substitute goods in the

household production model ( Freeman III 1993 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 4: Econ omic Benefit Categories

May 2014 4

- 8 

### Table 4

- 2 : Summary of Baseline National IM&E and Reductions in IM&E, for the

Final Rule and Other Options Considered

I M&E Loss Metric (per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

All Species (million A1E) 614.16 652.00 1637.49 1930.97

Forage Species (million A1E) 528.22 560.80 1258.67 1459.70

Commercial & Recreational Species (million A1E) 85.94 91.20 378.82 471.28

Commercial & Recreational Harvest (million fish) 16.13 17.11 44.66 54.02

A1E Losses with Direct Use Value (%) 2.6% 2.6% 2.7% 2.8%

Source: U.S. EPA analysis for this report



### Nonuse values may be more difficult to assess than use values for several reasons. First, nonuse values

are not associated with easily observable behavior. Second, nonuse values may be held by both users and

nonusers of a resource. Because nonusers may be less familiar with particular services provided by a

resource, the y may value the resource differently compared to users of the same resource. Thi rd, the

development of a defensible SP survey is often a time

- and resource

- intensive process. Fourth, even

carefully designed surveys may be subject to certain biases associated with the hypothetical nature of

survey responses ( Mitchell and Carson 1989 ) . Finally, efforts to disaggregate total WTP into its use and

nonuse components have proved troublesome ( Carson et al. 1999 )

.

Although EPA is not always able to estimate changes in nonuse values as part of regulatory development,

an extensive body of environmental economics literature demonstrates that the public holds significant

value for service flows from natural resources well beyond those associated with direct uses ( Boyd et al.

2001 ; Fischman 2001 ; Heal et al. 2001 ; Herman et al. 2001 ; Ruhl and Gregg 2001 ; Salzman et al. 2001 ;

Wainger et al. 2001 ) . Studies have documented public values for the services provided by a variety of

natural resources potentially affected by environmen tal impacts, including fish and wildlife ( Loomis et al.

2000 ; Stevens et al. 1991 ) ; wetlands ( Woodward and Wui 2001 ) ; wilderness ( Walsh et al. 1984 ) ; critical

habitat for T&E species ( Hagen et al. 1992 ; Loomis and Ekstrand 1997 ; Whitehead and Blomquist 1991 ) ;

shoreline quality ( Grigalunas et al. 1988 ) ; and beaches, shorebirds, and marine mammals ( Rowe et al.

1992 ) , among others. However, given EPA’s re gulatory schedule, developing and implementing SP

surveys to elicit total value (i.e., nonuse and use) of environmental quality changes resulting from

environmental regulations is often not feasible. In this case, EPA designed and implemented an original

S P survey to estimate total monetary value (including use and nonuse value) of potential aquatic resource

improvements that might occur as a result of the final 316(b) rule

. As described in Section 4.1 , EPA does

not include the benefits it estimated based on the survey in the comparison of costs and benefits for the

final rule. Chapter 11 provides additional details on the survey, implementation, and presents preliminary

benefits estimates to illustrate the potential of magnitude of total benefits. EPA also developed a benefit

transfer based on an other existing SP survey to estimate nonuse benefits resulting from the final 316(b)

rule for the North and Mid

- Atlantic regions. The benefit transfer is described in Chapter 8

.

Existing SP studies suggest that nonu se benefits of aquatic habitat improvements may be significant. For

example, results from a study of public values of migratory fish restoration projects in Rhode Island

showed that nonuse motives such as existence and bequest were rated as “important” or “very important”

by 62 and 76 percent of survey respondents, respectively. Use motives such as commercial and

recreational fishing, on the other hand, were rated as “important” or “very important” by only 38 and 43

percent of the survey respondents, respec tively ( Johnston et al. 2012, unpublished data )

. Additional detail

regarding the Rhode Island study is provided in Chapter 8

, Section 8.3.1

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 4: Econ omic Benefit Categories

May 2014 4

- 9 

### Many ecosystems affected by CWIS provide goods and services that contribute to societal well

- being (see

Chapter 2 ), but may be generally unrecognized because of the indirect nature of the effect . As such, even

va luations based on SP approaches are unlikely to capture the full economic value of the affected

ecosystem services ( Cos tanza and Folke 1997 ) . Despite these limitations, benefit transfer based on SP

studies is the generally accepted techniquefor estimating total (use and nonuse) values. EPA was able to

identify a single existing study that could be used to estimates tota l values (nonuse and use values) for

reductions in I M &E in some regions. Chapter 8 provides more detail on EPA’s quantitative analysis of

nonuse benefits from reducing I M &E at the CWIS of regulated facilities

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 1 

# 5 Impacts and Benefits on Threatened and Endangered Species

5.1 Introduction

T&E species are species vulnerable to future extinction or at risk of extinction in the near future,

respectively. These designations may be made because of low or rapidly declining population levels, loss

of essential habitat, or life history stages that are particularly vulnerable to environmental alteration,

disturbance, or other human impacts.

The withdrawal of cooling water from streams, rivers, estuaries and coastal marine waters leads to IM&E

of a large number of aquatic organisms. For species vulnerable to future extinction, IM&E from CWIS

may represent a substantial portion of annual reproduction. Consequently, IM&E may either lengthen

recovery time, or hasten the demise of these species. For these rea sons, the population

- level and social

values of T&E losses are likely to be disproportionately higher than the absolute number of losses that

occur.

Adverse effects of CWIS on T&E species may occur in several ways:

 Populations of T&E species may suffer dir ect harm as a consequence of IM&E. This direct

loss of individuals may be particularly important because T&E species have severely

depressed population levels that are approaching local, national, or global extinction.

 T&E species may suffer indirect harm if the CWIS substantially alters the food web in which

these species interact. This might occur as a result of altered populations of predator or prey

species, the removal of foundation species, or (for species with parasitic life history stages)

the loss of a host species.

 CWIS may alter habitat that is critical to the long

- term survival of T&E species. This might

occur as a consequence of changes in the thermal characteristics of local waterbodies, altered

flow regimes, turbidity, or changes in substrat e characteristics as a consequence of any of

these changes (Chapter 2 ).

By definition, T&E species are characterized by low population levels. As such, it is unlikely that these

species will be recorded in IM&E monitoring studies due to the logistical limitations of sampling and

identification effort, time of day, season, and year. For T&E species to be recorded in monitoring studies,

1) an individual of a T&E species must be captured during the (often short) sa mpling window, and 2) the

organism must be identifiable. Thus, despite the fact that the population impacts of IM&E on T&E

species may be high, the effects are difficult to ascertain and quantify within a framework designed for

common, more

- abundant specie s. Thus, EPA identifies spatial overlap between CWIS and T&E species

habitat ranges to estimate the potential for adverse IM&E impacts.

As noted, T&E species affected by CWIS may have both use and nonuse values. However, despite the

existence of T&E specie s with potentially high use values (e.g., Pacific salmonids), the majority of T&E

species affected by IM&E are relatively unknown, and those that are unidentifiable may not have any

direct use values (e.g., delta smelt). Given that protecting of T&E specie s implies value, and that the

majority of T&E species may not have direct use value, the majority of the economic value for T&E

species must come from nonuse values. Species

- specific estimates of nonuse values held for the

protection of T&E species can be derived only by primary research using stated preference techniques.

However, EPA did not have the resources necessary to develop such estimates for T&E species for thisBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 2 

### rulemaking. As an alternative, EPA used a benefit transfer approach that relies on inf ormation from

existing studies ( USEPA 2010 a)

.

EPA was able to use a benefit transfer approach to estimate changes in recreational use values for a subset

of T&E species that are highly valued by recreational anglers (i.e., paddlefish 16 

### and sturgeon).

Commercial and nonuse values are not monetized for any of the affected species. Therefore, benefit

estimates presented in this chapter are incomplete and highly conservative (i.e., low).

In this chapter, EPA explores the extent to which CWIS may affect species prote cted by the Endangered

Species Act on national and regional scales (Section 5.2 ), documents the v alue society place s on the

protection of T&E species (Section 5.3 ), and applies economic valuation studies of T&E species to case

studies of sea turtles and fi nfish in the Inland region (Section 5.4 ).



## 5.2 T&E Species Affected by CWIS

To assess the potential impacts of CWIS on T&E species, EPA constructed a database that identifies

spatial overlap between CWIS and vulnerable life history stages of all aquatic T&E s pecies for which data

are available. The database allowed EPA to estimate the potential for adverse IM&E impacts on T&E

species.

5.2.1 T&E Species Identification and Data Collection

First, all species currently listed under the Endangered Species Act (as of Aug ust 6, 2012) with aquatic

life history stages were identified using the US Fish and Wildlife Service Environmental Conservation

Onli ne System ( USFWS 2012a ) . This primary list of all T&E species was filtered to include only species

with life hist ory stages vulnerable to CWIS mortality according to life history data. Examples of

vulnerable stages include planktonic egg stages occurring near

- or in

- shore (e.g., marine species spawning

offshore were excluded unless other vulnerable stages are found n ear

- or in

- shore), free

- swimming larval

stages residing near

- or in

- shore, and adult life history stages that occur near

- or in

- shore. L ife history

data used to exclude species from further consideration was obtained from a wide variety of sources

( AFSC 2010 ; ASMFC 2012 ; Froese and Pauly 2009 ; NatureServe 2012 ; NEFSC 2010 ; PIFSC 2010a ;

PIFSC 2010b ; SEFSC 2010 ; SWFSC 2010 ; USFWS 2012a ) . After filtering by life history data, the list of

T&E species potentially affected by IM&E contained 2 8 7 species.

Whenever possible, EPA obtained the geographical distribution of T&E species susceptible to IM&E in

geographic information system ( GIS ) format as polygon (shape) files, line files (for inhabitants of small

creeks and rivers) and as a subset of geodatabase files. Data s ources include the US Fish and Wildlife

Service ( USFWS 2010a )

, including shapefiles for critical habitat designated under the Endangered

Species Act, NOAA’s Office of Response and Restoration ( NOAA 2010 )

, NatureServe ( NatureServe

2012 ) , and NOAA NMFS ( NMFS 2010a ; NMFS 2010 b ; NMFS 2010c ) . For several freshwater species,

geographic ranges were available only as 6

- digit hydrologic unit codes (HUC) ( NatureServe 2012 ;

USFWS 2010a ) . For these species, GIS data layers were generated using a GIS HUC database obtained

from the USGS ( Steeves and Nebert 1994 ) . For several speci es, no GIS data could be acquired. For these

species, species distribution descriptions were compared with mapped CWIS , and inspected for

geographic overlap. In all such cases (e.g., the “inarticulated brachiopod,” Lingula reevii , endemic to

16 Note: the American Paddlefish is listed on T&E species lists for many states, but is not currently protected nationally under

the US Endangered Species Act. A review of the species’ status in 1992 revealed that although the species did not then meet

the requirements to be listed as threatened at the federal level, the US Fish and Wildlife Service expressed its concern for the

future of the species.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 3 

### Kaneohe Bay, HI) no regulated facilities were located within 10 kilometers, and further inspection was

not warranted.

5.2.2 Number of T&E Species Affected per Facility

To investigate the potential for individual facilities to affect a wide variety of T&E species, EPA

calcula ted the number of T&E species affected on a per

- facility basis. This calculation allowed EPA to

assess the magnitude of differences between regions of CWIS effects on T&E species.

Nationally, 99 of the 287 aquatic T&E species (34 percent) had vulnerable l ife history stages that either

overlapped with CWIS, or records of IM&E ( Table 5

- 1 ). These species overlapped with 523 of 738

regulated facilities (71 percent) ( Figure 5

- 1 ). Among facilities, the variability in the number of T&E

species potentially affecte d ranges between 0 and 32 species ( Table 5

- 1 ), with more than 90 percent of

facilities affecting fewer than 7 T&E species, and more than 99 percent of facilities affecting fewer than

12 species ( Figure 5

- 2 ).

Excluding facilities whose CWIS that do not ove rlap with at least one T&E species, the average number

of species per facility is 4.13 (minimum 1, maximum 32) ( Table 5

- 1 ). Sea turtles, snails and freshwater

mussels had the highest overlap rate on a per

- facility basis, averaging 4.7, 4.1 and 3.7 species per facility,

respectively. Anadromous and freshwater fish had lower overlap rates with CWIS, averaging slightly

higher than one species per interacting facility ( Table 5

- 1 ).

Driven by the high number of IM&E freshwater mussels overlapping with facility CW IS, the majority of

all species by facility interactions occur in the inland region. However, the shape of cumulative

distribution plots is similar among regions after accounting for sample size, suggesting that the overall

probability of a facility affect ing one or more T&E species is not a function of geographic region ( Figure

5

- 3 ).Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 4 

### Figure 5

- 1 : Map of overlap of CWA section 316(b) existing facilities and T&E species habitat ranges (all circles, 523

facilities) or overlapping with critical habitat (orange c ircles, 27 facilities). Because critical habitat is a subset of total T&E

species habitat, a total of 523 facilities overlap the habitat of one or more T&E species.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 5 

### Figure 5

- 2 : Empirical c umulative distribution function plot of the number of T&E species

potentially affe cted on a per

- facility basis by regulated facilities nationwide

. Sample size is 738.

Table 5

- 1 : Number of T&E Species with Geogr aphical Distributions

Overlapping Regulated Facilities, on a Per

- facility Basis

Subset of Affected Species a # Species T&E Species per Facility c

All Facilities Interacting Facilities b

Avg Max Avg Max

All T&E Species 99 2.9 32 4.1 32

T&E Freshwater Mussels 53 1.9 22 3.7 22

T&E Anadromous Fish 12 0.3 5 1.2 5

T&E Freshwater Fish 21 0.1 4 1.4 4

T&E Snails 7 0.3 7 4.1 7

T&E Sea Turtles 6 3.8 5 4.7 5

a T& E species include species listed as threatened or endangered by the US Fish and Wildlife Service (fresh

water) or NOAA National Marine Fisheries Service (marine)

b Interacting Facilities = all facilities with CWIS inside the range of at least one T&E speci es

c Avg = Average, Max = Maximum

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 6 

### Figure 5

- 3 : C umulative distribution plot of the number of T&E species potentially affect ed on a

per

- facility basis by regulat ed facilities nationwide

. Sample sizes (i.e., number of regulated

facilities) are noted in parentheses. The horizontal axis is equivalent in all plots, with the

exception of the Inland region (noted with an asterisk *).



### 5.2.3 Number of Facilities Affecting Indi vidual T&E Species

To investigate the cumulative potential for CWIS to affect individual T&E species, EPA calculated the

number of facilities affecting each T&E species. There are 2,158 examples of overlaps between species

and facilities across 99 T&E species nationally, resulting in an average of 21.8 facilities per species

( Table 5

- 2 ). Consequently, many T&E species are likely to be affected by a large number of facilities.

Thus, even if individual facilities have low IM&E of T&E species, the cumulati ve effect of regulated

facilities on these populations may be substantial. The variation among species was large and ranged

between 1 and 103 facilities per species ( Table 5

- 2 ). Overall, 10 percent of species are affected by 1

facility, 53 percent of speci es are affected by up to 6 facilities 73 percent of species are affected by up to

25 facilities, and 92 percent are affected by up to 74 facilities ( Figure 5

- 4 ).Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 7 

### Table 5

- 2 : Number of Facilities with CWIS Within the Geographical Distribution of

T&E Species, on a Per

- species Basis

Subset of Affected Species a Species Overlaps Facilities per T&E Species

Average Maximum

All T&E Species 99 2158 21.8 103

T&E Freshwater Mussels 53 1176 21.8 103

T&E Anadromous Fish 12 235 19.6 101

T&E Freshwater Fish 21 65 3.1 7

T&E Snails 7 199 28.4 49

Sea Turtles 6 483 80.5 102

a T& E species included species listed as threatened or endangered by the US Fish and Wildlife Service (fresh water) or

NOAA National Marine Fisheries Service (marine)

. Source: U.S. EPA analysis for this report



### When subsets of related species were assessed, sea turtles had the highest average number of overlapping

facilities (80.5) ( Table 5

- 2 ), a value skewed by these species’ extensive ranges (i.e., entire Atlantic, Gulf

of Mexico, and/or Pacific coast), and the potential for IM&E impacts at all life stages. Following sea

turtles, snails and freshwater mussels had the highest average number of overlapping facilities (28.4 and

21.8 facilities per species, respectively). Excepting turtles, freshwater mussels accounted for 8 of the top

10 species sorted by the c ount of CWIS overlap ( Figure 5

- 5 ). Following freshwater mussels, anadromous

fish species were most likely to be affected, with an average of 19

. 6 facilities per species ( Table 5

- 2 ).

This average, however, is highl y skewed by two species of fish (the palli d sturgeon, Scaphirhynchus

albus and the shortnose sturgeon, Acipenser brevirostrum ) which accounted for 70 percent of all overlap

between facilities and anadromous fish species ( Figure 5

- 5 ). Finally, freshwater fish species averaged 3.1

facilities with po tential IM&E per species ( Table 5

- 2

, Figure 5

- 5 ).

Figure 5

- 4 : Empirical c umulative distribution function plot of the number of facilities that overlap

geographically with vulnerable life history stages of T&E species. Species represented on the plot

are those that overlap with a minimum of one regulated facility. Sample size is 99.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 8 

### Figure 5

- 5 : Cumulative distribution plots of the number of facilities likel y to affect individual

threatened or endangered species, grouped by species life history trait. Sample sizes (species per

life history trait) are in parentheses, and represent those species potentially affected by a

minimum of one regulated facility. The h orizontal axis is equivalent in all plots, with the exception

of Freshwater Fish (noted with an asterisk *).



### 5.2.4 Summary of Overlap between Cooling Water Intake Structures and T&E Species

Nationally, 34 percent of T&E species with vulnerable life history sta ges overlap with a m inimum of one

CWIS ( Table 5

- 1 ), and 71 percent of CWIS overlap with at least one T&E species. This suggests a high

probability that T&E populations are affected by IM&E. The potential for these impacts is widespread:

T& E species overlap CWIS in all geographical regions of the country ( Figure 5

- 3 ), in all waterbody

types, and across multiple life histories ( Figure 5

- 5 ). Finally, EPA’s analysis includes only federally listed

T&E species. Thus, the number of T&E species (in cluding those species defined as threatened or

endangered under state law) affected by IM&E is likely understated.

5.2.5 Summary of Overlap between Cooling Water Intake Structures and Critical Habitat

At some point following the listing of a species under the ES A, the US Fish and Wildlife Service or

NOAA will designate critical habitat. Critical habitat is defined as areas occupied by the species at the

time of listing which either 1) contain physical or biological features essential to conservation which

require special management considerations or protection, or 2) is essential for conservation.

To investigate the impact of regulated facilities on critical habitat, EPA assessed the number of facilities

with CWIS located within critical habitat. Overall, 27 faci lities overlapped with critical habitats

designated for 21 species protected by the ESA ( Figure 5

- 1 ). Of these 27 facilities, 14 overlapped with

critical habit for only one species; no facility overlapped with more than 8 species.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 9 

### 5.2.6 Effect of the Final Rule on Facilities Overlapping T&E Species Habitat

To estimate the potential effect of the final rule on T&E species, EPA estimated the number of regulated

facilities overlapping the habitat of one or more T&E species. Based upon data from the 316(b) industry

s urvey ( USEPA 2000 ) , EPA estimates there are 143 facilities likely to be in compliance with the final rule

(final determination of compliance will be based on site

- specific determination of BTA for entr ainment),

and that a minimum of 192 facilities will be required to implement measures to reduce IM&E. There was

insufficient data for EPA to estimate compliance status for the remaining 188 facilities ( Figure 5

- 6 ).

5.2.7 Species with Documented IM&E

Although dif

ficult to observe and quantify, EPA identified 14 T&E species with documented IM&E from

facility IM&E studies ( Table 5

- 3 ). Notably, several of these IM&E studies were conducted prior to the

listing of some of the T&E species identified (i.e., delta smelt, longfin smelt). Therefore, current annual

IM&E may be lower for these species, particularly if species’ populations have decreased or if facilities

have been required to install additional technologies during the permitting process. Alternatively, IM&E

may be similar in magnitude at facilities whose operating permits have been administratively continued

while these new species were listed.

In addition to identifying T&E species reported in IM&E studies, EPA also identified taxa in these studies

not identified by species but whose genus matched T&E species overlapping with the reporting facility

location ( Table 5

- 3 ). Although these instances are not confirmed IM&E of T&E species, they provide

evidence that additional T&E species are likely to be d irectly affected by IM&E

.

Including only individuals identified by species, EPA ident ified more than 95 ,000 baseline losses of T&E

species ( Table 5

- 3 ). However, for several reasons, T &E species suffering IM&E are likely to be

underreported. First, T&E species are found at low population densities, and the volume of water sampled

by facilit y

- level impingement and entrainment studies is low. Thus, it is likely that many T&E species

suffered IM&E outside of sampling periods and were never recorded. Second, because a high proportion

of all IM&E occurs during early life history stages (i.e., egg , larvae) when species identification is more

challenging, T&E species may not be recognized during sampling. For example, endangered species of

darter, including the Cherokee and duskytail darters, may be reported as “darter,” or “unidentified darter”.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 10 

### Figure 5

- 6 : Map of 316(b) existing facilities with CWIS overlapping the habitat of one or more T& E species, and these

facilities’ compliance with the final rule. Overall, EPA estimates that 143 facilities are likely to be in compliance with th e

final rule (green circles), 192 facilities are not yet in compliance with the final rule (red circles), and there is insufficient

data for EPA to estimate compliance status for the remaining 188 facilities (orange circles).Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 11 

### Table 5

- 3 : Documented IM&E of T&E Species a

Resolution Common Name Latin Name Baseline IM&E

Qualitative b Not Extrapolated Extrapolated Estimated

IM&E c

Species Atlantic Salmon Salmo salar 

-

Chinook Salmon Oncorhynchus tshawytscha  5,470

Coho Salmon Oncorhynchus kisutch 

-

Delta Smelt Hypomesus transpacificus  62,526

Green Sea Turtle Chelonia mydas 

-

Hawksbill Sea Turtle Eretmochelys imbricata 

-

Kemp's Ridley Sea Turtle Lepidochelys kempii 

-

Leatherback Sea Turtle Dermochelys coriacea 

-

Loggerhead Sea Turtle Caretta caretta  5

- 50

Longfin Smelt Spirinchus thaleichthys  24,919

Olive Ridley Sea Turtle Lepidochelys olivacea 

-

Pallid Sturgeon Scaphirhynchus albus  50

Steelhead Trout Oncorhynchus mykiss  5

Topeka Shiner Notropis topeka  15

Genus Alabama Sturgeon Scaphirhynchus suttkusi  8,174

Atlantic Sturgeon Acipenser oxyrinchus oxyrinchus  785,667

Blackside Dace Phoxinus cumberlandensis  10

Chum Salmon Oncorhynchus keta  22

Green Sturgeon Acipenser medirostris  785,667

Gulf Sturgeon Acipenser oxyrinchus desotoi  785,667

Shortnose Sturgeon Acipenser brevirostrum  785,667

a Species listed as threatened or endangered under state laws, such as the American Paddlefish ( Polyodon spathula ), are not included in this list.

b "Qualitative" indicates the species is reported by name from a minimum of one facility, but no loss estimates are provided.

c Baseline IM&E reported for genera reflect IM&E for all species within the gen us. Losses are likely dominated by more

- common congeners.

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 12 

## 5.3 Societal Values for Preservation of T&E Species Affected by IM&E

This section examines governmental spending, policy decisions, and private donations associated

with the preservation and restoration of T&E species. This section provide s evidence of societal

preferences for T&E preservation and spending related to ensuring sustainability of T&E species.

The U.S. Fish and Wildlife Service (FWS) reports annual expenditures for the conservation of

T&E species. Using the report for fiscal y ear 2011 ( USFWS 2012b ) EPA calculated total

government (federal and state) expenditures for the 9 9 federally listed T&E species with

vulnerable life history stages that overlap CWIS ( Table 5

- 4 ). Excludi ng expenditures on T&E

species (and distinct population segments) not subject to IM&E

, federal and state expenditures on

T&E species potentially affected by CWIS exceeded $593. 2 million during FY 2011 , and

accounted for 6 8 percent of all governmental spend ing on f ish, m arine r eptiles, c rustaceans,

c orals, c lams , aquatic snails and m arine m ammals listed under the ESA ( USFWS 2012b )

.

In addition to direct governmental spending associated with the protection of T&E species that

overlap with CWIS , the presence of these species often guides policy discussions, and may

require the installation of abatement technologies that reduce T&E species mortality and allow

these species to migrate. For example, the life history of the American paddlefish ( Polyodon

spathula ) (listed on many state T&E species lists, but not protected under the ESA) is

occasionally discussed during Federal Energy Regulatory Commission relicensing of dams,

because of the animal’s highly migratory life history. In the Wisconsin River, fo r example,

Alliant Energy has been required to install a multi

- million dollar fishway at the Prairie du Sac

dam, primarily to allow the passage of paddlefish and lake sturgeon ( WPLC v. FERC 2004 )

. Considerations for T&E species have also been responsible for changes in water diversions on the

San Joaquin

- Sacramento R iver delta, limiting water for downstream users. Under current

regulations, the volume of water removed from the San

- Joaquin

- Sacramento River at the Banks

Pumping Plant is limited from December to June, to protect d elta s melt ( NRDC v. Kempthorne

2007 ) . This restriction limits the volume of water available for consumption as drinking water

and for use in large

- scale irrigation projects. Water restrictions attributable due to the potential for

negative effects on delta smelt populations, ha ve been estimated to result in the loss of 21,100

Table 5

- 4 : Federal and State Expenditures for

T&E Species Overlapping with CWIS

Species Group Expenditure

(2011$,

millions)

Anadromous Fish $483.4

Freshwater Fish $57.6

Freshwater Mussels $13.0

Snails $0.1

Sea Turtles $39.1

All Species Overlapping CWIS $593.2

All Fish, Marine Reptile, Crustaceans, Coral,

Marine Mammal, Aquatic Snail and Clam

Species $869.1

Source: USFWS ( 2012b )Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 13 

### farm

- related jobs and $703 million in agricultural revenue in 200 9 alone ( Boxall 2010 ; Howitt et

al. 2009 )

. 17



### Although government spending and policy decisions made to protect or enhance stocks of T&E

species are not direct indications of economic benefits, they indicate that society does place a

significant value on protecting and restoring species at risk of ext inction

.



## 5.4 Assessment of Benefits to T&E Species

5.4.1 Economic Valuation Methods

Estimating the benefits of preserving T&E species by reducing IM&E is difficult for several

reasons. First, the contribution to ecosystem stability, ecosystem function, and life hist ory remain

relatively unknown for many T&E species. Second, because much of the wildlife economic

literature focuses on commercial and recreational benefits that are not relevant for many protected

species (i.e., use values), a paucity of economic data foc uses on the benefits of preserving T&E

species. Consequently, nonuse values comprise the principal source of benefit estimates for most

T&E species.

To obtain an accurate estimate of the nonuse values of T&E species affected by IM&E, first,

quantitative IM &E impacts, and the benefits of policy options, must be estimated for T&E

species. Second, an economic value must be obtained for the value of reducing IM&E as a

consequence of increased population sizes, extinction avoidance, and, for certain species (e.g

., Salmonids), the potential for re

- establishment of a commercial fishery.

Benefit transfer involves extrapolating existing estimates of nonmarket values to geographic

locations or species that differ from the original analytical situation. Thus, the appr oach transfers

estimates of values for preserving T&E species in one region to another region, or to a similar

species. Ideally, the resource (i.e. species ), policy variable ( e

. g ., change in species status,

recovery interval, population size , etc.), and th e benefitting population (i.e., defined human

population) are identical. Such a match rarely occurs. Despite discrepancies in these variables,

however, a benefit transfer approach can provide useful insights into the social benefits gained by

reducing IM&E of T&E species. 18



### 5.4.2 Case Studies

EPA attempted to estimate the benefits of the final rule for all T&E species with documented and

quantified IM&E at CWIS. In most cases, EPA was unable to locate or calculate key components

of the analysis necessary to apply a benefit transfer approach. However, EPA was able to obtain

sufficient data to estimate the economic benefits to two categories of T&E species: a subset of

T&E fish species in the Inland region, and loggerhead sea turtles. The case studies of potential

e conomic benefits from a decrease in T&E mortality are discussed below.

17 Water diversion in the San Joaquin

- Sacramento River is currently undergoing active litigation. See San Luis &

Delta

- Mendota Water Authority, et al. v. Salazar, et al., USDC Case No. 1:09

- CV

- 407 OWW GSA, and

consolidated cases.

18 Types of benefit transfer studies are discussed at length in U.S. EPA ( 2010 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 14 

### 5.4.2.1 Inland Region

Baseline IM&E of Special Status Species and Reductions in IM&E Under the Final Rule and

Options Considered



### EPA estimated IM&E for three T& E species in the Inland region : pallid sturgeon, American

paddlefish, and Topeka shiner. However, sufficient data were available to estimate the benefits of

the final rule for only the pallid sturgeon ( Scaphirhynchus albus ) and the American paddlefish

( Pol yodon spathula)

. As such , benefits estimates address only 73 to 8 3 percent of estimated T&E

A1E losses in the Inland region ( Table 5

- 5 ).

The pallid sturgeon is listed as an endangered species under the ESA ; the American paddlefish is

not listed federally

. In the early 1990s, the U.S. FWS conducted a review of the paddlefish for

threatened status, but ultimately did not list the species ( Allardyce 1991 ) . However, the review

noted that immediate efforts were needed to restore stocks and degraded habitats ( Allardyce

1991 )

. A lthough not currently protected federally, paddlefish are protected by 11 states.

The American paddlefish is a large species ( 85 inches length and more than 220 lbs) with roe

suitable for caviar. The species once supported a large commercial fishery in the Mississippi

Valley, and current ly supports a limited recreational fishery in some states. Likewise, the pallid

sturgeon is one of t he largest (30 to 60 inches) fish found in the Missouri

- Mississippi River

drainage, with specimens weighing up to 85 pounds. Because their large size make s them a

desirable commercial and trophy sport fish, and because they have roe suitable for caviar, both

pallid sturgeon and American paddlefish have potentially significant direct use values. All

extractive uses of the pallid sturgeon, however, are prohibi ted under the ESA.

To estimate total baseline IM&E , EPA used the EAM to model A1Es for each of the three T&E

species (Chapter 3 ). 19 

### The choice of facilities used to extrapolate IM&E from model facilities was

based on species’ historic ranges and current di stributions. In addition to baseline estimates of

IM&E for pallid sturgeon , paddlefish, and Topeka shiner

, EPA calculated reductions in IM&E

under the final rule and Proposal Options 2 and 4 ( Table 5

- 5 ).

Table 5

- 5 : Annual Baseline IM&E and Reductions in Baseline IM&E of

T&E Species at Regulated facilities in the Inland Region, by Regulatory

Option (A1E)

T&E Species Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline

Paddlefish 7,930 8,245 15,660 18,841

Pallid Sturgeon 65 68 78 90

Topeka Shiner 2,911 3,010 3,472 3,985

Total 10,906 11,323 19,210 22,916

a The IM& E data used to develop regional estimates are from sampling at the Wabash and Cayuga

facilites in 1976, the only year of sampling data for these facilities.

Source: U.S. EPA analysis for this report

19 IM&E of Paddlefish and pallid sturgeon as observed at nine and two model facilities, respectively.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 15 

### Benefit Transfer Approach: Estimated WTP for Protection of Inland T&E Species



## Nonuse Values

EPA ident ified two studies that estimated both non use and use values for sturgeon . One study

found that citizens of Maine are willing to pay $ 38.87 ( 2011 $) as a one

- time tax to create a self

sustaining population of shortnose sturgeon ( Kotchen and Reiling 2000 ) , a species listed as

endangered under the ESA ( NMFS 2004 )

. A separate study found that lake sturgeon is a popular

wildlife

- v iewing species in Wisconsin

, and that viewers place a substantial value on protection of

lake sturgeon population s. The average viewer’s WTP to maintain the current sturgeon

population of Wisconsin’s Lake Winnebago system was $ 127.37 ( 2011 $). With an esti mated

3,176l sturgeon viewers in 2002, total WTP for sturgeon

- viewing opportunities in the Winnebago

system was $ 0.41 million ( 2011 $). Together, the results of these studies indicate that nonuse

values for preservation of sturgeon are likely to be signific ant. However, EPA was unable to

monetize total nonuse benefits from reduced IM&E because reliable population estimates needed

to transfer the values were unavailable.



## Use Values

 Pallid sturgeon and paddlefish have potentially high commercial use values as

sources of roe. This value has increased dramatically owing to the collapse of

Caspian Sea sturgeon populations ( Speer et al. 2000 ) . Paddlefish roe have been

reported to sell for more than $300 per pound, and as much as three pounds of roe

may be harvested from a large female ( McKean 2007 )

. Despite these reports, EPA

was unable to reliably quantify total commercial values for these species due to a

lack of market data.

 Recreational use values fo r sturgeon and paddlefish caught in inland waters or

paddlefish were not available. Based on a review of literature describing these

species, EPA determined that sturgeon species (including white, green, and pallid

sturgeons) and paddlefish share many char acteristics, including roe suitable for caviar

and their value as game fish. Consequently, WTP values for sturgeon obtained in

California were used to value recreational use of these species in the Inland region. A

limited recreational fishery (mostly catc h and release) exists for paddlefish in several

states; although harvesting pallid sturgeon is illegal, the species is sometimes caught

by recreational anglers.

To estimate recreational use values for paddlefish and pallid sturgeon, EPA applied estimates

from a random utility model (RUM) analysis conducted to evaluate recreational fishing benefits

of the 2004 Section 316(b) Phase II Final Rule. Model results indicate that California anglers

were willing to pay $ 73.27 ( 2011 $) to catch a sturgeon ( USEPA 2004 a)

, a value transferred to

anglers for pallid sturgeon and paddlefish in the Inland region ( Table 5

- 6 ). 20



### The recreational use value from eliminating baseline IM&E of pallid sturgeon and pa ddlefish is

approximately $ 1.2 million using a 3 percent discount rate and $1.1 million using a 7 percent

discount rate. Annualized benefits for the final rule will be $415,000 using a 3 percent discount

rate and $320,000 using a 7 percent discount rate. A nnualized benefits for other options

considered range from $399,000 to $664,000 using a 3 percent discount rate and $307,000 to

20 The Phase II analysis did not estimating WTP for catching a sturgeon in other states. Given similarity in species

characteristics, EPA used WTP for sturgeon caught in California to value sturgeon and paddlefish species in the

Inland region.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 16 

### $460,000 using a 7 percent discount rate. EPA notes that these are underestimates of the total

values of reducing IM&E to T&E sp ecies in the Inland region because both nonuse and

commercial values, which are likely to be substantial, are not incorporated.

Table 5

- 6 : Estimated Annual WTP for Eliminating or Reducing IM&E of Special Status

Fish Species at Regulated facilities in the Inland Region, for the Final Rule and Other

Options Considered (2011$) a

T&E Species Annualized Benefits (2011$, 1,000s)

Proposal Option 4 Final Rule Proposal Option 2 Baseline

Paddlefish $581.0 $604.1 $1,147.4 $1,380.5

Pallid Sturgeon $4.8 $5.0 $5.7 $6.6

Total Undiscounted $585.8 $609.1 $1,153.1 $1,387.0

3% Discount Rate

Annualized Value $399.1 $415.0 $663.9 $1,210.7

7% Discount Rate

Annualized Value $307.2 $319.5 $460.1 $1,116.7

a The IM& E data used to develop regional estimates are from sampling at the Wabash and Cayuga facilities in 1976, the only year

of sampling data for these facilities.

Source: U.S. EPA analysis for this report



### 5.4.2. 2 Potential Nonuse Values for T& E Species in the Inland Region



### To illustrate the potential magnitude of nonuse values for T&E species affected by IM&E in the

Inland region, EPA applied a WTP meta

- analytical model ( Richardson and Loomis 2009 ) to

hypothetical scenarios . Because EPA currently does not have region

- wide IM&E for all T&E

species, nor population models to estimate the effect of IM&E on population size, EPA presents

estimates only to assess the range of benefits potentially resulting from the final rule and o ther

options considered. The modeled scenarios estimate the WTP for 0. 25 percent and 0.5 percent

increases for all T&E fish populations in the Inland region.

The model EPA used to estimate nonuse values using benefit transfer is a double log specification

(Model 4 from Richardson and Loomis ( 2009 ) ), where:

ln WTP (2006$) =

- 153.231 + 0.870 ln CHANGESIZE + 1.256 VISITOR + 1.020 FISH + 0.772

MARINE + 0.826 BIRD

– 0.603 ln RESPONSERATE+ 2.767 CONJOINT + 1.024

CHARISMATIC

– 0.903 MAIL + 0.078 STUDYYE AR

Model variables are described in Table 5

- 7

. Excepting all policy

- relevant variables, EPA used the

mean values for all model parameters, and converted estimates to 20 11 $ using the consumer price

index ( USBLS 2011 )

.

For a 0.25 percent change in T&E fish population size, projected WTP per household per year is

$ 1.07. With 59.9 million households 21 

### , total WTP for T&E fish in the Inland region is $ 63.1

million. For a 0.5 percent change in T&E fish populations, WTP per household is $ 1.94 per year,

resulting in WTP values of $ 114.3 million in the Inland region (all values 2011 $).

21 Household number in the Inland region is calculated for states where at least o ne T&E species affected by IM&E

is found.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 17 

### Table 5

- 7 : Variables in the R ichardson and Loomis (2008) Meta

- Analysis Model and

Values Used in EPA’s Application

Variable Name Description Value Used in EPA’s Application

ln WTP Natural log of willingness to pay Estimated by model

ln CHANGESIZE Natural log of the percentage change in

the population of the species of interest Log of percentage change in fish

population: ln(.25) and ln(.5)

VISITOR = 1 if survey respondents are visitors

rather than full

- time residents 0.0

FISH = 1 for fish species 1.0

MARINE = 1 for marine mammals 0.0

BIRD = 1 for bird species 0.0

ln RESPONSERATE Natural log of the survey response rate 4.0

CONJOINT = 1 for conjoint method surveys 0.0

CHARISMATIC = 1 for charismatic species 0.0

MAIL Indicates mail surveys 0.9

STUDY YEAR Year of study 2007

Sources: Richardson and Loomis (2008), U.S. EPA analysis for this report



### 5.4.2. 3 Sea Turtles



### Six species of sea turtles live in U.S. waters: g reen ( Chelonia mydas )

, h awksbill ( Eretmochelys

imbricata ) , Kemp's Ridley ( Lepidochelys kempii )

, l eatherback ( Dermochelys coriacea )

, l oggerhead ( Caretta caretta ) , and Olive Ridley ( Lepidochelys olivacea ) sea turtles. All have

extensive ranges, migrate long distances during their lifetime, and are listed as either threatened

or endangered (T&E) under the ESA. Becau se of these large ranges, substantial overlap exists

between sea turtle habitat and CWIS for regulated power generating and manufacturing facilities.

Additionally, because individuals of all ages and sizes are susceptible to impingement and

entrainment ( Norem 2005 ) , more than 730 potential interactions between species and CWIS may

result in the injury or death of these T&E species ( Table 5

- 1

, details in Appendix F, Section 1)

.

Evidence for Public Values for Sea Turtles



### In addition to research sponsored by the National Science Foundation and various private

philanthropic organizations, federal and state governmental spending on sea turtle protection

under the ESA totaled $33.8 million in FY2008 ( Table 5

- 4 ). Moreover, dozens of academic,

nonprofit, and ecotourism organizations recruit thousand s of volunteers every year to participate

in sea turtle conservation and research projects (Appendix Table F

- 2). Volunteers are often

required to undergo substantial training at their own expense and commit to spend long hours

working, often during the nig ht. For example, the nonprofit organization Earthwatch matches

volunteers with academic researchers working at field stations around the world. By paying to

spend time working with scientists on research projects, volunteers support sea turtle research and

conservation both financially and logistically, and gain first

- hand experience of conservation

issues. Trips may last from days to several weeks, and often require a commitment of 10 or more

hours per day. For example, on one 10

- day volunteer trip with a cost of $2,450 (plus airfare),

volunteers spend time tagging, measuring, and weighing leatherback seat turtles in Trinidad,

patrolling beaches from sundown to the early hours of the morning ( Earthwatch Institute 2010 )

.

Baseline IM&E of Special Status Species and Potential IM&E Reductions Under the Final

Rule and Options Considered



### Several passive

- use (e.g., wildlife viewing and photography) and nonuse values are associated

with U.S. sea turtle populations. Many households express passive use value by participating inBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 18 

### ecotourism activities, such as visiting sea turtle nesting areas, or by participating in sea turtle

conservation activities ( Frazer 2005 ) . Additionally, a high proportion of governmental

expenditures on T&E species are for turtle species ( Table 5

- 4 ), suggesting that the public values

t he preservation of sea turtle populations.

Electric generating facilities are known to impinge and entrain all six species of sea turtles found

in U.S. waters ( Norem 2005 ) , with more than 730 occurrences of overlap between species ranges

and CWIS ( Table 5

- 1 ). I ncidences of mortality have been reported at facilities in California,

Texas, Florida, South Carolina, North Carolina, and New Jersey ( National Research Council

1990 ; Plotkin 1995 ) . These facilities span a wide range of intake flows ( less than 30 mgd to more

than 1,400 mgd AIF ), suggesting that sea turtle mortality is n ot limited to large intakes. Although

quantitative reports are available from a few power stations, high

- quality data is available from

only one source, the St. Lucie Nuclear Power Plant, at Hutchinson Island, FL, where annual

capture rates range from 350 to 1,000 turtles (Appendix Table F

- 1). Despite estimates of

mortality rates due to entrainment of less than 3 percent, approximately 85 percent of entrained

organisms show evidence of injury as a result of entrainment ( Norem 2005 )

. As such, true

mortality rates from CWIS may be higher than reported, particularly for individuals captured

repeatedly (37 percent of green and 13 percent of loggerhead sea turtles entrained between May

and December 2000 were recaptured individuals) ( Norem 2005 )

.

Although the magnitude of IM&E is small relative to fishing

- related mortality, the cumula tive

impact of IM&E is unclear. The only study presenting a quantitative estimate of annual IM&E

estimated mortality rates to be between 5 and 50 individuals per year ( Plotkin 1995 )

. Consequently, sufficient data does not exist to estimate baseline sea turtle mortality due to

entrainment and impingement at regional or national scales. However, the lower population sizes,

long life

- span, and high reproductive potential of adult turtles ( Crouse et al. 1987 ) , mean the final

existing f acilities rule is likely to have only a small effect on the long

- term viability of turtle

populations.

Potential Benefits of Protecting Sea Turtle Species



## Per

- household WTP

EPA identified a study that used a stated preference valuation approach to estimate the total

economic value (i.e., use and nonuse values) of a management program designed to reduce the

risk of extinction for loggerhead sea turtles ( Whitehead 199 3 )

. The mail survey asked North

Carolina households whether they were willing to pay for a management program that reduces the

probability that loggerhead sea turtles will be extinct in 25 years. EPA used Whitehead ( 1993 ) to

assess th e range of benefits potentially resulting from the final rule and Proposal Options 2 and 4

(detailed method ology in Appendix F, Section 2 )

. EPA included the resulting benefits estimates

here as an illustrative example and did not include them its national benefit totals for the final rule

and options considered.

EPA reviewed the a vailable data sources and biological models to assess the potential impact of

baseline IM&E and reductions in IM&E on the probability of sea turtle extinction in 25 years.

Although analyses of sea turtle extinction risk have been conducted ( e.g., Conant et al. 200 9 )

, EPA was unable to identify an existing model or analysis that could be readily used in

conjunction with available mortality data to estimate the marginal impacts of CWIS on sea turtle

extinction risk. Estimates from the literature suggest that IM&E is of relatively low importance

compared to other human

- induced mortality such as shrimp trawling and other fisheries ( PlotkinBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 19 

### 1995 ) . However, Crouse et al. ( 1987 ) found that mortality at juvenile and subadult life stages can

h ave a substantial effect on population growth, which suggest s that small changes in surviv al at

these age classes could have a measurable impact on extinction risk. For this illustrative example,

EPA assumed a marginal change in extinction probability of loggerhead sea turtles due to the

final rule is of 0.01 (i.e., a 1 percent decrease in the probability of extinction in 25 years)

. EPA

bases this assessment upon reports that IM&E may result in the loss of more than 100 turtles per

year (Appendix Table E

- 1 ), and because turtle population growth rates are known to be sensitive

to changes in juvenile and subadult mortality (Crouse et al. 1987).

EPA used a va lue of 0. 01 within Whitehead’s ( 1993 ) modeling framework to estimate household

value s for changes in extinction risk for loggerhead sea turtles as a consequence of the final rule

(details of this calculation are in Appendix Section F

- 2 ). Although EPA did not base this

assessment on formal quantitative analysis of extinction risk, it illus trate s the magnitude of

potential benefits associated with reductions in sea turtle IM&E . Using the published mean values

for all other model parameters, EPA calculated an annual household value of $ 0.37 ( 2011 $).

Estimates were converted to 2011 dollars usi ng the consumer price index ( USBLS 2011 )

.



## Total WTP for all Households

Whitehead’s ( 1993 ) study for loggerhead sea turtle management activitie s was based on a state

wide survey of North Carolina residents. However, the large geographic range of sea turtles

suggests that households of many coastal states through their U.S. range would value activities

that decrease their extinction risk. There is also the potential for differential values within and

across states. Households farther away from the resource may value sea turtle survival less than

households near the ocean because they are less likely to participate in passive uses of the

resource. A lthough EPA recognizes that the application of the benefit transfer may overestimate

household values for states with population centers far from sea turtle habitat, e vidence from the

literature suggests that households may value changes in environmental r esource that are

occurring at great distances. For example, Pate and Loomis ( 1997 ) found that respondents were

willing to ascribe stated preference values to environmental amenity changes in other states. As

such, by focusing on residents of coastal state s only, estimated benefits may undervalue national

willingness to pay for the preservation of loggerhead sea turtles.

As noted above, EPA includes its calculations for the benefits of protecting sea turtles here as an

illustrative example. For this example , EPA focused solely on impacts to loggerhead sea turtles

(one of six T&E sea turtle species in the United States). By focusing only on loggerhead sea

turtles, EPA notes that estimated benefits are likely to be lower than those held by individuals for

all T&E turtle species. EPA chose this species of turtles because they are late

- maturing, have an

existing population model ( Crouse et al. 1987 ) , an existing valuation study ( Whitehead 1993 )

, and are the most commonly affected species of turtle (App endix F). The U.S. range of loggerhead

sea turtles includes the Gulf of Mexico, South Atlantic, Mid

- Atlantic, and North Atlantic 316(b)

regions ( USFWS 2010b ) . Assuming affected populations include all households within states

with regul ated facilities that potentially have an impact on loggerhead sea turtles, 54.83 million

households would be willing to pay for improved protection of this species ( Table 5

- 8 ). EPA

applied the mean household WTP of $ 0.37 ( 2011 $) to all four regions because the Whitehead

( 1993 ) function does not include income or other demographic variables that allow estimation of

state

- specific WTP. The total annual WTP for a 1 percent increase in the survival probability of

l oggerhead sea turtles annualized at a 3 percent discount rate is $19.3 million. Annualized

benefits for each region are presented in Table 5

- 8 , assuming that benefits begin to accrue in 2014Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 20 

### and continue throughout the compliance period. Because EPA does n ot currently have accurate

national estimates of IM&E for turtle species, nor are population models available that estimate

the effect of the existing facilities rule on population size and extinction risk, EPA is presenting

these estimates only to assess the potential range of benefits, and is not including them in national

benefits totals for the final rule and options considered. A ctual benefits may be higher or lower

than these estimates, with Proposal Option 2 likely to provide substantially greater be nefits than

the final rule and Proposal Option 4.

Table 5

- 8 : Benefits of a 1 Percent Increase in the Probability that Loggerhead Sea

Turtles Will Not Be Extinct in 25 Years

Region States Included Number of

Households

(millions) Annualized Benefits

(2011$, millions)

3% Discount Rate 7% Discount Rate

North Atlantic CT, MA, ME,

NH, RI 5.41 $1.90 $1.86

Mid

- Atlantic DE, MD, NJ,

NY, PA, VA 21.11 $7.41 $7.25

South Atlantic FL, GA, NC, SC 12.06 $4.24 $4.14

Gulf of Mexico a FL, LA, MS, TX 16.26 $5.71 $5.59

Total

- 54.83 $19.26 $18.84

a Florida households are included in both the South Atlantic and Gulf of Mexico regions. To prevent double

- counting,

Florida households were apportioned between these regions based on relative AIF.

Note: Because of uncertainty in estimates of increased survival probability, and because benefits were not calculated for

options, these values are not included in national totals.

Source: U.S. EPA analysis for this report



### 5.4.3 Limitati on and Uncertainties

Table 5

- 9 summarizes the caveats, omissions, biases

, and uncertainties known to affect the

estimate d benefits for sea turtles ( Section 5.4.2.3 ), and T&E finfish in the Inland region (Section

5.4.2.1 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 5: Impacts and Benefits on T&E Species

May 2014 5

- 21 

### Table 5

- 9 : Caveats, Omissions, Biases, and Uncertainties in the T&E Species Benefits

Estimates

Issue Impact on Benefits

Estimate Comments

Change in T&E populations

due to IM&E is uncertain Estimates

understated Projected changes in number of fish affected may be

underestimated because neither cumulative impacts of

IM&E over time nor interactions with other stressors are

considered.

IM&E effects are not

estimated for all T&E species

and all regions Estimates

understated EPA was unable to estimate IM&E of T&E species for

all regions due to lack of data. The large amount of

overlap between T&E ranges and CWIS suggests that

many affected species are likely to be missing from

IM&E reports.

Benefit estimates include

only a subset of species

identified as affected Estimates

understated EPA was unable to apply benefit transfer of values for

all affected species. Benefits estimates address 80 to 84

percent of documented T&E A1E losses in the Inland

region.

Benefit estimates used in

benefit cost analysis include

only recreational use values Estimates

understated EPA applied recreational use values to estimate benefits

for the species included in the analysis. Values held for

T&E species are primarily nonuse values, which were

not mone tized. In addition, some of the affected species

have commercial use values, which were not estimated.

Benefit transfer introduces

uncertainties Uncertain EPA applied a recreational use value for sturgeon in

California to value sturgeon and paddlefish in the Inland

region. This value may over

- or understate recreational

values of sturgeon and paddlefish in the Inland region.

Ecological consequences of

reduced numbers of T&E

species Estimates

understated WTP values are unlikely to include damage to food

w ebs and ecosystem stability as a consequence of the

removal or restoration of T&E species.

Effects of thermal impacts

from CWIS on T&E

populations is uncertain Uncertain EPA has few data on the effect of thermal discharge on

T&E species.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 1 

# 6 Commercial Fishing Benefits

Commercial fisheries can be adversely affect ed by IM&E in addition to many other stressors.

C ommercially landed fish are exchanged in markets with observable prices and quantities;

however, estimating the change in economic surplus from increases in the number of

commercially landed fish requires consideration of various conceptual and empirical issues. This

chapter provides an overview of these issues, and presents how EPA estimated the change in

commercial fisheries

- related economic surplus associated with the elimination of, and reduction

in, baseline IM&E under the fi nal rule and regulatory options it considered.

This chapter includes a review of the concept of economic surplus, and describes economic

theory and empirical evidence regarding the relationship between readily observable dockside

prices and quantities and the economic welfare measures of producer and consumer surplus that

are suitable for benefit

- cost estimation.

Section 6.1 describes the methodology used t o estimat e the commercial fisheries

- related benefits

, including conceptual and empirical discussions of producer and consumer surplus

. Section 6.2

presents the commercial fisheries

- related benefits by region

, and Section 6.3 presents the

limitations and uncertainties associated with EPA ’ s analysis.



## 6.1 Methodology

The methodology EPA employed to estimate the commercial fishing benefits associated with the

regulatory options for the final rule closely follows the analysis EPA conducted for the S ection

316(b) Phase III Final Rule ( USEPA 2006 b)

. Changes from that a nalysis include updated

estimates of baseline IM&E and IM&E reductions

, and updated dockside prices. EPA estimated

dockside prices based on the five

- year average price between 2007 and 20 11, from commercial

fishing landings data obtained from the National Oceanic and Atmospheric Administration ’s

National Marine Fisheries Service ( NMFS ) ( NMFS 2012a )

.

EPA measured commercial fishing benefits as changes in producer surplus. Estimated benefits for

each region are presented in Section 6.2. EPA also conside red potential consumer surplus values

associated with IM&E, but did not estimate changes in consumer surplus for the final rule and

options considered because it found that dockside prices would not change enough to produce

measurable shifts in consumer su rplus. Appendix H presents the details of EPA’s assessment of

consumer surplus.

6.1.1 Estimating Consumer and Producer Surplus

The total loss to the economy from IM&E impacts on commercially harvested fish species is

determined by the sum of changes in both pro ducer and consumer surplus ( Hoagland and Jin

2006 )

. EPA modeled IM&E using the methods presented in Chapter 3 . EPA assumed a linear

relationship between stock and harvest. That is, if 10 percent of the current commercially targeted

stock were harvested, EPA assumed that 10 percent of any increase in that species due to lower

IM&E would be harvested. Thus, EPA assumed that the percentage increase in harvest is the

same as the percentage increase in t he fish population. The percentage of fish harvested is based

on historical fishing mortality rates. EPA used historical NMFS landings data on commercial and

recreational catch to determine the proportions of total species landings attributable toBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 2 

### recreati onal and commercial fishing. EPA applied these proportions to the estimated total change

in harvest to distribute benefits between commercial and recreational fisheries.

Producer surplus provides an estimate of the economic benefits to commercial fishers

. W elfare

changes can also be expected to accrue to final consumers of fish and to commercial consumers

, including processors, wholesalers, retailers, and middlemen

, if the projected increase in catch due

to the rule is accompanied by a decrease in price. Th ese impacts can be expected to flow through

the tiered commercial fishery market (as described in Holt and Bishop ( 2002 ) ).

Holt and Bishop (2002) used a fishery market model to estimate changes in welfare as a result of

changes in the level of the commercial fish ing harvest. The market model takes as inputs the

expected change in harvest and baselin e gross revenues, and provides as outputs the expected

change in producer and consumer surplus. In general, the analysis of market impacts involves the

following steps (Bishop and Holt ( 2003 ) ):

1. Assessing the net welfare change s for fish consumers due to changes in fish harvest and

the corresponding change in fish price.

2. Assessing net welfare changes for fish harvesters due to the change in total revenue,

which could be positive or negative.

3. Calculating the change in net social benefits when the fish harvest changes.

Figure 6

- 1 illustrates a simplified fishery market model as shown in Bishop and Holt ( 2003 )

. For

simplicity, the authors assume that the fishery is managed on quota basis with the baseli ne quota

shown as F

1 

### and baseline dockside or ex

- vessel price as P 1 

### . They use an inverse demand function,

P(F) , because fish are perishable, with the quantity harvested driving price in the short run.

Figure 6

- 1 : Fishery Market Model , reproduced from B ishop and Holt ( 2003 )

6.1.1.1 Step 1: Assessing Benefits to Consumers



### The downward sloping line labeled P(F), depicted in Figure 6

- 1 , represents a general equilibrium

demand function that accounts for markets downstream of commercial fishers. As describedBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 3 

### above, t he vertical curve F 1 

### is the quantity of fish supplied to the market by commercial fishers

under the baseline conditions. Equ ilibrium is attained at the point where P(F) equals F 1



### . The

intersection of these two lines gives the price P 1 

### at which quantity F 1 

### is sold. In this case the total

amount paid by consumers for fish is equal to P 1 

### × F 1



### , which is equal to the area of the box es U +

V + W in the graph. The consumer surplus

, or benefit to consumers

, is equal to the area of the

triangle T.

The measurement of the benefits from reducing IM&E relies on the assumption that a decrease in

mortality of fish

, larvae

, and eggs under a sce nario of reduced IM&E would increase fish

populations and the quantity of fish supplied to consumers (i.e., an increase from F 1 

### to F 2 

### ). If the

quantity of fish available to the market increases from F 1 

### to F 2



### , this in turn would result in a lower

market price for fish (i.e., P 2 

### ). T he total amount paid by consumers changes to P 2 

### × F 2



### , which is

equal to the area of the boxes V + W + Y + Z

. T his area may be smaller or larger than area U + V

+ W

, but unequivocally increases the consumer surplus so that it is equal to the area of the

triangle T + U + X. The difference in consumer surplus between the reduced IM&E scenario and

the current baseline scenario (i.e., U + X) is the measure of benefits to consumers from redu cing

IM&E

.

Estimating the change in the price of fish from changes in commercial fish harvest requires the

following input data: (1) a n estimate of the baseline prices and quantities of the commercial

fishing harvest, (2) the estimated change in the comme rcial fishing harvest under the reduced

IM&E scenario, and (3) an understanding of the price elasticity of demand for fish. The price

elasticity of demand for fish measures the percentage change in demand in response to a

percentage point change in fish pr ice. Thus, the inverse elasticity, or price flexibility, measures

the percent change in price for a given percent change in quantity.

To properly estimate price changes, it is necessary to consider the contribution of the species to

the overall market. Be cause individual demand functions incorporating substitutes are not

available for most species, EPA estimated price changes in the following way.

The Agency estimated the total baseline harvest for relevant species (commercial species of

similar types to those affected by IM&E) using NMFS landings data from 2007 to 2011in three

categories: finfish, shrimp, and crabs. 22 

### EPA aggregated the species to account for substitution.

The totals for finfish were summed for the East Coast and Gulf, and for the West Coast, while

totals for shrimp and crabs were summed across all coastal regions. 23 

### EPA summed estimated

harvest increas es from the elimination of baseline IM&E according to the same species and

regional categories (column 3 in Table 6

- 1 ).

EPA estimated price elasticity of demand based on a review of the economics literature ( Asche et

al. 2005 ; Capps Jr. and Labregts 1991 ; Cheng and Capps Jr. 1988 ; Davis et al. 2007 ; Lin et al.

1988 ; Tsoa et al. 1982 ) (column 6 in Table 6

- 1 ) . The percentage change in price was calculated

by dividing percentage change in harvest by elasticity. As shown in Table 6

- 1

, the expected price

changes resulting from eliminating baseline levels of IM&E are very small, ranging fro m 0.21

percent to 2.5 percent. EPA expects that price changes would be substantially less for the final

rule due to much lower reductions in IM&E. Appendix H of this document presents the detailed

calculations and results.

22 For example, offshore species such as tuna and swordfish, baitfish species, and shellfish were not included.

23 Harvests for Alaska and Hawaii were not included in the totals.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 4 

### Table 6

- 1 : Estimated Average Percentage Change in Ex

- Vessel Price by Region and

Species Group from the Elimination of Baseline IM&E

Region Species

Group Increase in Harvest

from Elimination of

Baseline IM&E a

(lbs) Total Average

Annual Harvest a Percentage

Change in

Harvest Elasticity Percentage

Change in

Price b

California Finfish 1,920,625 489,705,990 0.39%

- 1.89

- 0.21%

East Coast

and Gulf Finfish 12,548,060 265,617,830 4.72%

- 1.89

- 2.50%

All Regions Crabs 1,373,553 258,973,619 0.53%

- 1.31

- 0.40%

All Regions Shrimp 369,750 279,365,691 0.13%

- 0.63

- 0.21%

a Sum of total landings for all relevant species.

b Percentage changes in price reflect the average across all species within the species group and region.

Sources: U.S. EPA analysis for this report, NMFS (2012a)



### EPA did not include estimates of changes in consumer surplus for commercial species. Prices

must change in order for consumer surplus to change. Most species of fish have numerous close

substitutes . The literature suggests that when there are plentiful substitute fish products, numerous

fishers, and a strong ex

- vessel market, individ ual fishers are generally price takers

. Although

there are exceptions, fisheries economics studies often make these assumptions in ana lyzing

regional effects from harvest changes (e.g., Her r mann 1996 ; Thunberg et al. 1995 ) and

international markets ( e.g., Clarke et al. 1992 ) . Consumer surplus measures that NMFS has

estimated for past environmental impact statements tend to be quite low. NMFS fisheries analyses

incorporate price changes for large changes in regional or national harvest, such as stock

rebuilding. However, for small changes in landings, such as those EPA expects under the final

rule, it is standard to assume that prices are fixed. 24



### 6.1.1.2 Step 2: Assessing Producer Surplus



### In an unregulated fishery, the long

- run change in producer surplus due to an increase in fish

stocks will be zero percent of the c hange in gross revenues because in open access fisheries,

excess profits are always driven to zero at the margin . Most fisheries are, however, regulated with

quotas or restrictive permits to prevent overfishing . Thus, lasting economic benefits accrue to

co mmercial fishers from reductions in IM&E and the subsequent increase in harvest . Fishery

regulations seek to create sustainable harvests that maximize resource rents. 25 

### In a regulated

fishery, IM&E impacts reduce the number of fish available to harvest. Thi s reduction may lead to

more

- stringent regulations and decreases in harvest. In this case, the change in producer surplus

can be related to the change in harvest and the resulting gross revenue.

In Figure 6

- 1 , the line C represents the cost to the producer of supplying a pound of fish. The

model assumes that average cost is equal to marginal cost, that is, C is constant for all pounds

produced. 26 

### When the supply of fish is equal to F 1



### , the commercial fishers sell F 1 

### pounds of fish

at a price of P 1 

### and earn revenues equal to U + V + W. The area between P 1 

### and C is the producer

24 P ersonal communications with NM FS economists Cindy Thomson ( 2008 ) , Eric Thunberg ( 2008 ) , Steve Freese

( 2008 ) , and Sabrina Lo vell ( 2013 )

.

25 In addition, even in open a ccess fisheries, intramarginal rents are earned by at least some boats ( Thunberg 2008 )

.

26 If marginal cost s increase as harvest increases, some of the producer surplus per unit will be lost due to the

increased costs.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 5 

### surplus that accrues to producers for each pound of fish. Total producer surplus realized by

producers is equal to ( P 1



### - C) × F 1



### . In the example, this producer surplus is equal to the area of U

+ V. The area W is the amount that producers pay for capital and labor and to suppliers if the

harvest equals F 1 

### (e.g., fishing gear and the costs of operating in the market).

When supply increases to F 2



### , the pro ducers sell F 2 

### pounds of fish at a price of P 2



### . The total cost to

produce F

2 

### increases from W to W + Z. The total producer surplus changes from U + V to V + Y.

This change may be either positive or negative, depending on the relative elasticity of demand

, which changes the r elative sizes of areas U and Y.

In theory, producer surplus is equal to normal profits (total revenue minus fixed and variable

costs), minus the opportunity cost of capital. The fixed costs and inputs are incurred

independently of the e xpected marginal changes in the level of fish landings ( Squires et al. 1998 ;

Thunberg and Squires 2005 )

. Total v ariable costs including labor, fuel, ice, and other supplies,

however, vary directly with the level of landings. Furthermore, because EPA estimated the

opportunity cost o f capital to be only about 0.4 to 2.6 percent of producer surplus, EPA assumed

that normal profits are a sufficient proxy for producer surplus ( USEPA 2004 a) . As a result, EPA’s

assessment of producer surplus is a relatively straightforward calculation in which the change in

producer surplus is calculated as a species

- and region

- specific fraction of the change in gross

revenue due to increased landings.

The change in producer surplus, captu red by “normal profits,” is assumed to be equivalent to a

fixed proportion of the change in gross revenues . EPA estimated gross revenue change from the

change in the commercial harvest due to reducing IM&E, and the change in prices associated

with the incr eased commercial harvest. As discussed above, EPA estimated price changes to be

negligible, and therefore did not include price changes in the model. EPA estimated species

- and

region

- specific Net Benefits Ratios, which represent the fractional share of gross revenue

associated with net benefits. EPA’s approach for estimating Net Benefits Ratios using available

data on variable costs from sources such as the NMFS is described in more detail in

S ection A4

- 10 of US EPA ( 2006 ) . EPA then applied the Net Benefits R atio to the estimated

change in gross revenue under the 316(b) final rule and regulatory options EPA considered to

estimate the increase in producer surplus.

Table 6

- 2 to Table 6

- 7 present the Net Benefit Ratios, which range from 0.15 to 0.85, by regions

and species

. 27

, 28 

### See Chapter 1 , Section 1.2 for descriptions of the seven study regions. EPA

excluded the Inland region from the analysis because of a negligible commercial fishing harvest

in this region. EPA notes that this approach yields an estimate of benefits to commercial

fisherman, not benefits to society as a whole because changes in consumer surplus are not

captured, and because people may also have nonmarket values for commercial fish (e.g.,

recreational and existence values). As described in Sec tion 6.1.1.1 , EPA did not estimate changes

in consumer surplus because the expected changes in consumer surplus due to the final rule will

27 Positi ve Net Benefits Ratios reflect the assumption that commercial fishers will accrue rents (profits) in regulated

fisheries. When calculating the Net Benefits Ratios, EPA assumed that the predicted changes in harvest are such

that fixed costs and variable co sts per ton will not change. If costs remain constant, a marginal change in harvest is

more likely to result in increases in profit and positive producer surplus.

28 In the case of species aggregates (e.g., forage species), EPA assumed that the net benefit ratio is equal to the

simple average of all empirically estimated net benefit ratios in the region. Species aggregates are listed as “Other”

in Table 6

- 2 to Table 6

- 7.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 6 

### be minor. EPA’s analysis of nonmarket benefits for fisheries improvements is presented in

Chapter 8.

Table 6

- 2: Cal ifornia Region, Management Method, Gear Type, Status of Stock, and Net

Benefits Ratio, by Species

Species Main Management

Method Main Gear

Type Status of Stock a Net Benefits

Ratio

Anchovies Annual landings Roundhaul Not subject to

overfishing 0.64

Cabezon Total allowable catch Hook

- and

- line Not overfished or subject

to overfishing 0.52

Crabs Seasonal closures Pots and traps Undefined 0.74

Drum and Croaker Permits Nets Unknown 0.42

Dungeness Crab Size, no females, closed

during molting season Traps Unknown 0.74

Flounders Quotas Bottom trawl Not overfished or subject

to overfishing 0.64

California Halibut Total allowable catch Longline Unknown 0.58

Other N/A N/A N/A 0.53

Rockfish Quotas Trawls Not overfished or subject

to overfishing b 0.62

California

Scorpionfish Quotas Otter trawl Not overfished 0.47

Sculpin Nonrestrictive permits Trawls Unknown 0.64

Sea Bass Season, size, gear

restrictions Gillnets Unknown 0.66

Shad, American None Nets Unknown 0

Shrimp Seasonal closures Trawl Unknown 0.15

Smelt Seasonal closures Nets Unknown 0.66

Surfperch Quotas Handlines Overfished but not

subject to overfishing b,c,d 0.37

N/A = not applicable

a Status of stock designations based on data from the NMFS, Summary of Stock Status, 2 nd Quarter 2012 ( NMFS 2012b )

.

b Species group consists of many individual component species with conflicting stock status. The most common stock status

among the component species was designated the Status of Stock for the species group.

c "Perch" species were used as a proxy for surfperch.

d “Overfished but not subject to overfishing” means that the fish stock is at a low level but is expected to rebuild given

current rates of commercial fishing

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 7 

### Table 6

- 3 : North Atlantic Region, Management Method, Gear Type, Status of Stock, and

Net Ben efits Ratio , by Species

Species Main Management

Method Main Gear Type Status of Stock a Net Benefits

Ratio

Bluefish Quotas Gillnets Not overfished or subject

to overfishing 0.63

Butterfish Quotas NA Not subject to overfishing 0.64

Atlantic Cod Time/area closures Otter trawl Overfished or subject to

overfishing 0.66

Crab Size, sex, season Traps Unknown 0.57

American Plaice Size Otter trawl Not overfished or subject

to overfishing 0.63

Windowpane Time/area closures Bottom trawl Overfished but not subject

to overfishing b,c 0.63

Winter Flounder Quotas Otter trawls Overfished but not subject

to overfishing b 0.64

Flounder Total allowable landing Bottom trawl Overfished or subject to

overfishing b 0.63

Red Hake Quotas Otter trawls Not overfished or subject

to overfishing 0.62

Silver Hake Quotas Otter trawls Not overfished or subject

to overfishing 0.63

Atlantic Herring Total allowable catch Purse seine Not overfished or subject

to overfishing 0.76

Atlantic

Mackerel Annual quota Unknown Not overfished or subject

to overfishing 0.77

Atlantic

Menhaden Not reg. In this area Unknown Subject to overfishing but

not overfished 0.68

Other N/A N/A N/A 0.57

White Perch Size limits Unknown Unknown 0.82

Pollock Time/area closures Bottom trawl Not overfished or subject

to overfishing 0.71

Sculpin Open access Unknown Unknown 0

Scup Quotas Otter trawls Not overfished or subject

to overfishing 0.69

Searobin Open access (by catch) Unknown Unknown 0

Shad, American Mortality targets Unknown Overfished 0.6

Skate Catch limits Otter trawl Not overfished or subject

to overfishing b 0.68

Tautog Possession limits Otter trawl Unknown 0.46

Weakfish Size limits Trawls Overfished but not subject

to overfishing 0.76

N/A = not applicable

a Status of stock designations based on data from the National Marine Fisheries Service, Summary of Stock Status, 2 nd Quarter 2012

( NMFS 2012b ) . Supplemental stock status designations based on data from the Atlantic States Marine Fisheries Commission

( ASMFC 2012 )

.

b Species g roup consists of many individual component species with conflicting stock status. The most common stock status among

the component species was designated the Status of Stock for the species group.

c “Overfished but not subject to overfishing” means that th e fish stock is at a low level but is expected to rebuild given current rates

of commercial fishing.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 8 

### Table 6

- 4 : Mid

- Atlantic Region, Management Method, Gear Type, Status of Stock, and

Net Benefits Ratio , by Species

Species Main Management

Method Main Gear Type Status of Stock a Net Benefits

Ratio

Alewife Bans, species of concern Fish weirs Overfished 0.85

American Shad Chesapeake fishery

closed Unknown Overfished 0.84

Atlantic Croaker Gear restrictions Gillnets Not overfished or subject to

overfishing 0.74

Atlantic

Menhaden Open access Purse seine, otter

trawl, gill net Not overfished or subject to

overfishing 0.67

Black Drum Quotas Unknown Unknown 0.7

Blue Crab Limits on female crabs,

size Pots Unknown 0.57

Bluefish Quotas Gillnets Not overfished or subject to

overfishing 0.63

Butterfish Quotas Unknown Not subject to overfishing 0.64

Crab Season, size Unknown Unknown 0.57

Drum and

Croaker Gear restrictions, quotas Nets Not subject to overfishing 0.74

Flounder Quotas Bottom trawl Not overfished or subject to

overfishing 0.65

Other N/A N/A N/A 0.73

Red Hake Quotas Otter trawls Not overfished or subject to

overfishing b 0.62

Scup Quotas Otter trawls Not overfished or subject to

overfishing 0.69

Searobin Open access Unknown Unknown 0

Silver Hake Quotas Otter trawls Not overfished or subject to

overfishing b 0.63

Spot License Haul seines Unknown 0.84

Striped Bass Quotas Gill nets Not overfished or subject to

overfishing 0.67

Striped Mullet Gear restrictions Cast nets Unknown 0.7

Tautog Possession limits Otter trawl Overfished and subject to

overfishing 0.46

Weakfish Size limits Trawls Overfished but not subject

to overfishing c 0.76

White Perch Size limits Unknown Unknown 0.82

N/A = not applicable

a Status of stock designations based on data from the NMFS, Summary of Stock Status, 2 nd Quarter 2012 ( NMFS 2012b )

. Supplemental stock status designations based on data from the Atlantic States Marine Fisheries Commission ( ASMFC 2012 )

.

b Estimates from the North Atlantic region are presen ted because red and silver hake stocks were not reported in the Mid

- Atlantic

region.

c “Overfished but not subject to overfishing” means that the fish stock is at a low level but is expected to rebuild given curr ent rates

of commercial fishing.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 9 

### Table 6

- 5 : South Atlantic Region, Management Method, Gear Type, Status of Stock, and

Net Benefits Ratio , by Species

Species Main Management

Method Main Gear Type Status of Stock a Net Benefits

Ratio

Blue Crab Size limits Pots Unknown 0.57

Crab Size, sex, season limits Traps Unknown 0.57

Drum and

Croaker Open access (by catch) Otter trawl bottom,

gill nets Not subject to overfishing 0.54

Atlantic

Menhaden Five year annual cap on

reduction fishery in

Chesapeake Unknown Subject to overfishing but

not overfished 0.76

Other N/A N/A N/A 0.59

Spot License Haul seines Unknown 0.7

Stone Crab Size limits Traps Unknown 0.58

Weakfish Size limits Trawls Overfished but not subject

to overfishing b 0.64

a Status of stock designations based on data from the NMFS, Summary of Stock Status, 2 nd Quarter 2012 ( NMFS 2012b )

. Supplemental stock status designations based on data from the Atlantic States Marine Fisherie s Commission ( ASMFC 2012 )

.

b “Overfished but not subject to overfishing” means that the fish stock is at a low level but is expected to rebuild given curr ent rates

of commercial fishing.



### Table 6

- 6: Gulf of Mexico Region, Management Method, Gear Type, Status of Stock, and

Net Benefits Ratio, by Species

Species Main Management

Method Main Gear Type Status of Stock a Net Benefits

Ratio

Blue Crab Limited entry, pot limits Pots Unknown 0.72

Black Drum Limited access permits Hand lines, gill nets Unknown 0.69

Leatherjacket N/A Rod/reel, hand and

long lines, pots and

traps Unknown 0

Mackerels Quotas Hook

- and

- line Not overfished or subject to

overfishing 0.75

Menhaden Seasonal/area closures Purse seines Unknown 0.76

Other N/A N/A N/A 0.46

Sea Basses Quotas Traps Unknown 0.72

Sheepshead Size Cast net Unknown 0.84

Shrimp Same as pink shrimp Unknown Not overfished or subject to

overfishing b 0.43

Spot License Haul seines Unknown 0.54

Stone Crab Size Traps Not subject to overfishing 0.71

Striped Mullet Gear restrictions Strike nets Unknown 0.79

Striped Mullet Gear restrictions Strike nets Unknown 0.79

a Status of stock designations based on data from the NMFS, Summary of Stock Status, 2 nd Quarter 2012 ( NMFS 2012b )

.

b Species group consists of many individual component species with conflicting stock status. The most common stock status amon g

the component species was designated the Status of Stock for the species group.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 10 

### Table 6

- 7 : Great Lakes Region, Management Method, Gear Type, Status of Stock, and

Net Benefits Ratio , by Species

Species Main Management

Method Main Gear Type Status of Stock Net Benefits Ratio

Bullhead State specific Gill and trap nets Unknown 0.29

Freshwater Drum State specific Gill and trap nets Unknown 0.29

Other State specific Gill and trap nets Unknown 0.29

Smelt State specific Gill and trap nets Unknown 0.29

White Bass State specific Gill and trap nets Unknown 0.29

Whitefish State specific Gill and trap nets Unknown 0.29

Yellow Perch State specific Gill and trap nets Unknown 0.29



### 6.1.1.3 Step 3: Estimating Net Social Benefits When the Fishing Harvest Increases



### EPA estimated t he change in net social benefits when the commercial fishing harvest increases

from F

1 

### to F 2 

### by adding the results from Steps 1 and 2. Because area U is a transfer from

comme rcial fishers to consumers, it does not affect social benefits. Therefore, the change in net

social benefits is area X + Y (s ee Figure 6

- 1 ). However, if demand elasticity is such that c hanges

in price are negligible, as EPA expects (Section 6.1.1.1 ), area X will be negligible relative to Y,

and total social benefits will be measured by area Y.



## 6.2 Benefits Estimates for Regional Commercial Fishing

The first step of the analysis o f commercial fishing benefits involves a fishery

- based assessment

of IM&E

- related changes in harvested species landings. Many of the fish species affected by

IM&E at CWIS sites are harvested both recreationally and commercially. As described in Section

6.1 .1

, EPA assumed a linear relationship between stock and harvest and used historical NMFS

landings data on commercial and recreational catch to determine the proportions of total species

harvest attributable to recreational and commercial fishing. EPA appli ed these proportions to the

estimated total change in harvest to distribute benefits between commercial and recreational

fisheries. EPA then used the estimated change in commercial fishery harvest as a basis for

estimating changes in producer surplus in th e commercial fishing industry.

EPA assessed whether potential harvest increases under the final rule and options considered are

reasonable when compared to historic harvest data. For this assessment, EPA compared estimated

increases in commercial yield fr om the elimination of baseline IM&E for each species to average

regional commercial harvest from 2007 to 2011. Table 6

- 8 summarizes baseline IM&E and

harvest data for fourteen species for which the potential increase in commercial yield from the

eliminatio n of baseline IM&E exceeds 10 percent of regional harvest.

Notably, none of the species identified include major fisheries: many are infrequently targeted,

and several have historical commercial harvests which vary widely on an annual basis. In many

cases , the species identified are not subject to a federal fisheries management plan, and the

overall status of stock is unknown. These uncertainties may increase the error associated with the

regional

- scale effects occurring as a consequence of the extrapolati on of IM&E. Moreover, it is

possible that the regional extrapolation of species

- specific results may be biased because

available IM&E studies are old (and therefore reflect IM&E under substantially different

populations), or because particularly high IM&E counts at one or more facilities measured during

an anomalous year may result in erroneous estimates of IM&E.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 11 

### The sixteen species for which the potential increase in commercial yield from the elimination of

baseline IM&E exceeds 10 percent of regional har vest include cabezon, California halibut,

rockfish, and sculpin in the California region; sculpin in the North Atlantic region; spot, and

weakfish in the Mid

- Atlantic region; black drum, drum and croaker, leatherjacket, spot, and

striped mullet in the Gulf of Mexico region; and freshwater drum, smelt, and white bass in the

Great Lakes region. No increases exceeding 10 percent were found in the South Atlantic region.

Among these fourteen species, the potential harvest increases range from 12 percent for striped

mullet in the Gulf of Mexico to 1,512 percent for sculpin in the North Atlantic.

EPA used harvest and fisheries data to develop reasonable caps on increases in commercial

harvest from the elimination of baseline IM&E and IM&E reducti ons under the final rule and

options considered. Economists and biologists with NMFS recommended using either m aximum

sustainable yield (MSY) or historical harvest to assign reasonable caps on projected total harvest

under the post

- compliance scenario. 29 

### NM FS biologists provided MSY for three species groups:

California cabezon, California sculpin, and West Coast rockfishes

. 30 

### While there is no stock

assessment for halibut, NMFS biologists suggested averaging the most recent four peaks in

harvest. For other s pecies lacking MSY data, EPA capped post

- compliance harvest at the 90 th



### percentile of annual harvest from 1982 to 2011. This follows recommendations from NMFS

scientists to use harvest data for 25 years or more. 31



### North Atlantic sculpin. Mid

- Atlantic spot, and Great Lakes freshwater drum and white bass were

the only four species estimated to reach these caps within EPA’s analysis. Caps for these four

species are shown in bold type in Table 6

- 8 . Notably, historical commercial catch of both North

Atlantic scu lpin and Mid

- Atlantic spot are widely variable. For example, between 1995 and 2011,

there were several years with no commercial catch of sculpin reported. For spot, commercial

harvests changed by more than 2 million pounds per year (alternating between inc reases and

decreases) for each year between 2006 and 2011. For Northeast Atlantic sculpin and Mid

- Atlantic

spot, these data suggest that commercial catch may not be limited by fish population, and that a

large and sustained increase in commercial landings beyond the cap due to the reduction of

IM&E is unreasonable.

The following sections present estimated benefits from commercial harvest changes in six of the

seven study regions and the total for the six regions. The Inland region is excluded from the

analy sis due to a negligible commercial fishing harvest in this region.

29 Cindy Thomson, NMFS, personal communication ( 2008 )

.

30 NMFS biologists suggested that sculpin in California be evaluated in combination with scorpionfish, as these

species are grouped when determining the MSY.

31 M any fish populations peaked more than 25 years ago, when virgin , non

- exploited populations existed and

maximum harvests were achievable.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 12 

### Table 6

- 8 : Potential Harvest Increase from Eliminating IM&E as a Percentage of Total

Harvest and P otential Harvest Capping Rules Used in EPA ’ s Analysis

Region and

Species Baseline

Harvest

2007

- 2011

(1,000 lbs.) Baseline

IM&E

(1,000 lbs.) Potential

%

Increase

in

Harvest Maximum

Harvest

1982

- 2011

(1,000 lbs.) 90th

Percentile

of Max.

Harvest

(1,000 lbs.) MSY or

Other

Capping

Rule

(1,000 lbs.) Cap Used

(1,000

lbs.)

California

Cabezon 53.7 76.1 142% 374.2 261.2 207.2 a No Cap e

California Halibut 495.5 176.9 36% 1,337.1 1.238.4 982.1 b No Cap

California Drum

and Croaker 53.8 6.9 13% 1,491.5 1,288.6 No Cap

California

Rockfish 2,741.3 1,634.5 60% 58,286.7 42.942.2 77,161.8 c No Cap

California Sculpin 3.8 3.7 97% 19.5 7.6 482.8 d No Cap

North Atlantic

Sculpins 1.6 24.2 1,512% 4.8 4.8 4.8

Mid

- Atlantic Spot 3,478.4 1,303.1 37% 4,784.6 4,543.0 4,543.0

Mid

- Atlantic

Weakfish 267.4 503.7 188% 7,023.5 6,714.1 No Cap

Gulf of Mexico

Black Drum 4,621.9 1,945.0 42% 10,644.4 7,314.6 No Cap

Gulf of Mexico

Drum and

Croaker 111.8 47.8 43% 2,934.7 663.8 No Cap

Gulf of Mexico

Leatherjacket 61.0 107.1 176% 519.7 447.4 No Cap

Gulf of Mexico

Spot 16.9 46.3 274% 473.4 356.4 No Cap

Gulf of Mexico

Striped Mullet 10,800.3 1,343.6 12% 30,433.6 27,789.7 No Cap

Great Lakes

Freshwater Drum 585.9 248.8 42% 905.1 795.0 209.1 795.0

Great Lakes

Smelt 380.5 92.9 24% 4,105.0 3,672.0 No Cap

Great Lakes

White Bass 523.6 916.5 175% 1,332.0 771.7 248.1 771.7

a MSY (maximum sustainable yield).

b Average of most recent four peaks in harvest

.

c MSY for rockfishes for the West Coast

.

d MSY for all scorpionfish and sculpins

.

e “No Cap” indicates that no cap was used during benefit estimation because increases did not result in exceedance of the 90 th

percentile of maximum harvest, MSY, or other capping rule.

Sources: U.S. EPA analysis for this report ; NMFS data on baseline harvest, historical landings, and MSY

.



### 6.2.1 California Region

Baseline levels of I M &E account for 1 .9 million pounds of commercial fishing losses annually in

the California region, as shown in Table 6

- 9

. Rockfish account for the major portion of overall

losses in this region. EPA estimated t he annual undiscounted commercial fishing benefits of

eliminating baseline I M &E to be approximately $2.0 million , as shown in Table 6

- 9

. Applying aBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 13 

### 3 percent discount rate, EPA estimates the annualized benefits of eliminating baseline I M &E to

be $1.7 million

. Applying a 7 percent rate, these annualized benefi ts are approximately $ 1.5

million

.

As shown in Table 6

- 9

, EPA estimates that annual commercial harvest will increase by

approximately 7 ,000 pounds under the final rule. Annualized benefits to commercial fishers under

the file rule will be about $3,000 usin g a 3 percent discount rate and $2,000 using a 7 percent

discount rate. For other options considered, the annual increase is commercial harvest would

range from about 7,000 pounds under Proposal Option 4 to 1.2 million pounds under Proposal

Option 2. The a ssociated annual benefits under other options considered would range from about

$3,000 to $651,000 using a 3 percent discount rate and $2,000 to $422,000 using a 7 percent

discount rate (Table 6

- 9 ). Appendix H presents species

- specific results for the esti mated annual

increase in harvest and monetary benefits to commercial fishers.

Table 6

- 9 : Commercial Fishing Benefits from Eliminating or Reducing Baseline

IM&E Mortality Losses at Regulated Facilities in the California Region, for the

Final Rule and Option s Considered (2011$)

Regulatory Option Annual Increase in

Commercial

Harvest

(1,000 lbs) Annualized Benefits from Increase in Commercial

Harvest

(2011$, 1,000s)

Undiscounted 3% Discount

Rate 7% Discount

Rate

Proposal Option 4 7 $5 $3 $2

Final Rule 7 $5 $3 $2

Proposal Option 2 1,177 $1,236 $651 $422

Baseline 1,929 $2,025 $1,698 $1,519

Source: U.S. EPA analysis for this report



### 6.2.2 North Atlantic Region

Baseline levels of I M &E account for 414 ,000 pounds of annual commercial fishing losses in the

North Atlantic region, as shown in Table 6

- 1 0

, with flounder playing a particularly important

role. EPA estimated the annual undiscounted benefits to commercial fishers from eliminating

baseline I M &E to be approximately $ 476 ,000 , as shown in Table 6

- 1 0

. EPA estimates the total

annualized benefits from eliminating baseline I M &E, applying a 3 percent discount rate, to be

$ 399 ,000 . Applying a 7 percent rate , these annualized benefits are approximately $ 357 ,000

.

As shown in Table 6

- 1 0 , annual commercial harvest will increase by approximately 7,000 pounds

under the final rule. Annualized benefits to commercial fishers under the final rule will be about

$4,000 using 3 percent discount rates and $3,000 using 7 perce nt discount rates. For other options

considered, the annual increase in commercial harvest ranges from about 3,000 pounds under

Proposal Option 4 to 318,000 pounds under Proposal Option 2. The associated annual benefits

under other options considered range from about $1,000 to $202,000 using a 3 percent discount

rate and $1,000 to $136,000 using a 7 percent discount rate (Table 6

- 1 0 ). Appendix H presents

species

- specific results for the estim ated annual increase in harvest and monetary benefits to

commercia l fishers.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 14 

### Table 6

- 10 : Commercial Fishing Benefits from Eliminating or Reducing

Baseline IM&E Mortality Losses at Regulated Facilities in the North Atlantic

Region, for the Final Rule and Options Considered (2011$)

Regulatory Option Annual Increase in

Commercial

Harvest

(1,000 lbs) Annualized Benefits from Increase in Commercial

Harvest

(2011$, 1,000s)

Undiscounted 3% Discount

Rate 7% Discount

Rate

Proposal Option 4 3 $2 $1 $1

Final Rule 7 $6 $4 $3

Proposal Option 2 318 $365 $202 $136

Baseline 414 $476 $399 $357

Source: U.S. EPA analysis for this report



### 6.2.3 Mid

- Atlantic Region

Baseline levels of I M &E account for approximately 7.8 million pounds of commercial fishing

losses annually in the Mid

- Atlantic region, as shown in Table 6

- 1 1 . Atlantic menhaden, blue crab,

drum and croaker, spot, weakfish , and “other” species 32 

### are the primary drivers of I M &E in the

Mid

- Atlantic region. EPA estimated t he annual undiscounted benefits to commercial fishers from

eliminating baseline I M &E to be $2.6 million , as shown in Table 6

- 1 1

. Applying a 3 percent

discount rate, annualized benefits from eliminating baseline I M &E are estimated to be $ 2.2

million . Applying a 7 percent rate, these annualized benefits are approximately $ 1.9 million

.

As shown in Table 6

- 1 1

, EPA estimates that annual commercial harvest will increase by

approximately 3.1 million pounds under the final rule. Annualized benefits to commercial fishers

under the final rule will be about $260,000 using a 3 percent discount rate and $190,000 using a 7

percent discount rate. For other options considered, the annual increase in commercial harvest

ranges from 2.9 million pounds under Proposal Option 4 to 7.1 million pounds under Proposal

Option 2. The associated annual benefits under other options consid ered range from about

$242,000 to $1.2 million using a 3 percent discount rate and $177,000 to $770,000 using a 7

percent discount rate (Table 6

- 1 1 ). Appendix H presents species

- specific results for the estimated

annual increase in harvest and monetary be nefits to commercial fishers.

32 The “other” species category includes losses which could not be assigned to a specific species group.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 15 

### Table 6

- 11 : Commercial Fishing Benefits from Eliminating or Reducing

Baseline IM&E Mortality Losses at Regulated Facilities in the Mid

- Atlantic

Region, for the Final Rule and Options Considered (2011$)

Regulatory Option Annual Increase in

Commercial

Harvest

(1,000 lbs) Annualized Benefits from Increase in Commercial

Harvest

(2011$, 1,000s)

Undiscounted 3% Discount

Rate 7% Discount

Rate

Proposal Option 4 2,873 $383 $242 $177

Final Rule 3,072 $411 $260 $190

Proposal Option 2 7,090 $2,373 $1,206 $770

Baseline 7,758 $2,586 $2,169 $1,939

Source: U.S. EPA analysis for this report



### 6.2.4 South Atlantic Region

Baseline levels of I M &E account for 78 ,000 pounds of commercial fishing losses in the South

Atlantic region, as shown in Table 6

- 1 2 . The estimated undiscounted annual commercial fishing

benefits of eliminating baseline I M &E are driven primarily by Atlantic menhaden, spot, and drum

and croaker and t otal $ 20 ,000 , as shown in Table 6

- 1 2

. Applying a 3 percent discount rate, the

annualized benefits of eliminating baseline I M &E are estimated to be $ 17 ,000 . Applying a 7

percent rate, these annualized benefits are $ 15 ,000

.

As shown in Table 6

- 1 2

, EPA estimates that annual commercial harvest will increase by

approximately 41,000 pounds under the final rule. Annualized benefits to commercial fishers

under the final rule will be about $6,000 using 3 percent discount rates and $5,000 using 7

percent di scount rates. For other options considered, the annual increase in commercial harvest

ranges from 37,000 pounds under Proposal Option 4 to 76,000 pounds under Proposal Option 2.

The associated annual benefits under other options considered range from $6,00 0 to $10,000

using a 3 percent discount rate and $4,000 to $7,000 using a 7 percent discount rate (Table 6

- 1 2 ).

Appendix H presents species

- specific results for the estimated annual increase in harvest and

monetary benefits to commercial fishers.

Table 6

- 12 : Commercial Fishing Benefits from Eliminating or Reducing

Baseline IM&E Mortality Losses at Regulated Facilities in the South Atlantic

Region, for the Final Rule and Options Considered (2011$)

Regulatory Option Annual Increase in

Commercial

Harvest

(1,000 lbs) Annualized Benefits from Increase in Commercial

Harvest

(2011$, 1,000s)

Undiscounted 3% Discount

Rate 7% Discount

Rate

Proposal Option 4 37 $9 $6 $4

Final Rule 41 $10 $6 $5

Proposal Option 2 76 $19 $10 $7

Baseline 78 $20 $17 $15

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 16 

### 6.2.5 Gulf of Mexico Region

Baseline levels of I M &E account for more than 6 .0 million pounds of commercial fishing losses

in the Gulf of Mexico region annually, as shown in Table 6

- 1 3 . These losses are driven by black

drum, s triped mullet, and Atlantic menhaden. The estimated undiscounted annual commercial

fishing benefits from eliminating baseline I M &E are approximately $ 3 .9 million , as shown in

Table 6

- 1 3

. Applying a 3 percent discount rate, estimated commercial fishing bene fits from

eliminating baseline I M &E are estimated to be $ 3.4 million . Applying a 7 percent rate, these

annualized losses are approximately $ 3.2 million

.

As shown in Table 6

- 1 3

, EPA estimates that annual commercial harvest will increase by

approximately 1 .7 million pounds under the final rule. Annualized benefits to commercial fishers

under the file rule will be about $515,000 using a 3 percent discount rate and $379,000 using a 7

percent discount rate. For other options considered, the annual increase in co mmercial harvest

ranges from 1.6 million pounds under Proposal Option 4 to 4.3 million pounds under Proposal

Option 2. The associated annual benefits under other options considered range from $497,000 to

$1.7 million using a 3 percent discount rate and $36 5,000 to $1.3 million using a 7 percent

discount rate (Table 6

- 1 3 ). Appendix H presents species

- specific results for the estimated annual

increase in harvest and monetary benefits to commercial fishers.

Table 6

- 13 : Commercial Fishing Benefits from Elimina ting or Reducing

Baseline IM&E Mortality Losses at Regulated Facilities in the Gulf of Mexico

Region, for the Final Rule and Options Considered (2011$)

Regulatory Option Annual Increase in

Commercial

Harvest

(1,000 lbs) Annualized Benefits from Increase in Commercial

Harvest

(2011$, 1,000s)

Undiscounted 3% Discount

Rate 7% Discount

Rate

Proposal Option 4 1,642 $779 $497 $365

Final Rule 1,704 $808 $515 $379

Proposal Option 2 4,265 $2,651 $1,702 $1,256

Baseline 6,033 $3,926 $3,427 $3,161

Source: U.S. EPA analysis for this report



### 6.2.6 Great Lakes Region

Baseline levels of I M &E account for more than 1.1 million pounds of commercial fishing losses

in the Great Lakes region annually, as shown in Table 6

- 1 4 . These losses are driven by the white

bass, freshwater drum, and “other” species. EPA estimated the annual undiscounted commercial

fishing benefits from eliminating baseline I M &E in this region to be approximately $279,000 , as

shown in Table 6

- 1 4

. Total annualized commercial benefits from eliminatin g baseline I M &E,

applying a 3 percent discount rate, are estimated to be $ 244,000 . Applying a 7 percent rate, these

annualized losses are $ 225,000

.

As shown in Table 6

- 1 4 , EPA estimates that annual commercial harvest will increase by 838,000

pounds under the final rule. Annualized benefits to commercial fishers under the final rule will be

about $145,000 using a 3 percent discount rate and $110,000 using a 7 percent discount rate. For

other options considered, the annual increase in commercial harvest rang es from 784,000 pounds

under Proposal Option 4 to 1.1 million pounds under Proposal Option 2. The associated annualBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 17 

### benefits under other options considered range from $135,000 to $162,000 using a 3 percent

discount rate and $102,000 to $116,000 using a 7 p ercent discount rate (Table 6

- 1 4 ). Appendix H

presents species

- specific results for the estimated annual increase in harvest and monetary

benefits to commercial fishers.

Table 6

- 14 : Commercial Fishing Benefits from Eliminating or Reducing

Baseline IM&E Mo rtality Losses at Regulated Facilities in the Great Lakes

Region, for the Final Rule and Options Considered (2011$)

Regulatory Option Annual Increase in

Commercial

Harvest

(1,000 lbs) Annualized Benefits from Increase in Commercial

Harvest

(2011$, 1,000s)

Undiscounted 3% Discount

Rate 7% Discount

Rate

Proposal Option 4 784 $202 $135 $102

Final Rule 838 $217 $145 $110

Proposal Option 2 1,092 $266 $162 $116

Baseline 1,137 $279 $244 $225

Source: U.S. EPA analysis for this report



### 6.2.7 National Estimates

Nationally, b aseline levels of I M &E account for more than 17.3 million pounds of commercial

fishing losses annually, as shown in Table 6

- 1 5

. EPA estimated the annual undiscounted

commercial fishing benefits from eliminating baseline I M &E to be approximatel y $ 9.3 million

, as

shown in Table 6

- 1 5

. Total annualized commercial benefits from eliminating baseline I M &E,

applying a 3 percent discount rate, are estimated to be $ 8.0 million. A pplying a 7 percent rate,

these annualized losses are $ 7.2 million.

As shown in Table 6

- 1 5 , EPA estimates that annual commercial harvest will increase by 5.7

million pounds under the final rule. Annualized benefits to commercial fishers under the final rule

will be about $0.9 million using a 3 percent discount rate and $0. 7 million using a 7 percent

discount rate. For other options considered, the annual increase in commercial harvest ranges

from 5.3 million pounds under Proposal Option 4 to 14.0 million pounds under Proposal Option

2. The associated annual benefits under o ther options considered range from $ 0.9 to $ 3.9 million

using a 3 percent discount rate and $ 0.7 to $ 2.7 million using a 7 percent discount rate ( Table 6

-

1 5 ). Appendix H presents species

- specific results for the estimated annual increase in harvest and

mon etary benefits to commercial fishers for each region.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 6: Commercial Fishing Benefits

May 2014 6

- 18 

### Table 6

- 15 : National Commercial Fishing Benefits from Eliminating or Reducing

Baseline IM&E Mortality Losses at Regulated Facilities, for the Final Rule and

Options Considered (2011$)

Regulatory Option Annual Increase in

Commercial

Harvest

(1,000 lbs) Annualized Benefits from Increase in Commercial

Harvest

(2011$, 1,000s)

Undiscounted 3% Discount

Rate 7% Discount

Rate

Proposal Option 4 5,345 $1,379 $883 $652

Final Rule 5,669 $1,457 $934 $689

Proposal Option 2 14,019 $6,910 $3,935 $2,707

Baseline 17,349 $9,312 $7,953 $7,215

Source: U.S. EPA analysis for this report



## 6.3 Limitations and Uncertainties

Table 6

- 1 6 summarizes the caveats, omissions, biases

, and uncertainties known to affect the

estimates that EPA developed for the benefits analysis.

Table 6

- 16 : Caveats, Omissions, Biases, and Uncertainties in the Commercial Benefits

Estimates

Issue Impact on Benefits

Estimate Comments

Change in commercial landings due

to IM&E is uncertain Uncertain Projected changes in harvest may be under estimated

because cumulative impacts of IM&E over time

, interactions with other stressors , and population

changes, are not considered.

Some estimates of commercial

harvest losses due to IM&E under

current conditions are not

region/species

- specific Uncertain EPA estimated the impact of IM&E in the case

study analyses based on the most current data

available data provided by the facilities. However,

in some cases these data are 20 years old or older.

Thus, they may not reflect current fish stock and

waterbody conditions.

Effect of change in stocks on

landings is not considered Uncertain EPA assumed a linear stock to harvest relationship,

so that a 10 percent change in stock would have a

10 percent change in landings; this may be low or

high, depending on the condition of the stocks.

Region

- specific fisheries regulations also will affect

the validity of the linear assumption.

Effect of uncer tainty in estimates of

commercial landings and prices is

unknown Uncertain EPA assume d that N MFS landings data are accurate

and complete. In some cases prices and/or

quantities may be reported incorrectly.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 1 

# 7 Recreational Fishing Benefits

7.1 Introduction

This chapter presents the estimated benefits to recreational anglers from improved recreational

fishing opportunitie s due to reductions in IM&E under the final rule and regulatory options EPA

considered for section 316(b). EPA used a benefit transfer approach based on a meta

- analysis of

economic studies of recreational fishing benefits from improved catch rates. Benefit transfer

involves adapting research conducted for another purpose to address the policy questions at hand

( Bergstrom and De Civita 1999 )

. Benefit

- cost analysis of environmental regulations rarely affords

sufficient time to conduct original stated or revealed preference studies specific to policy effects.

Benefit transfer is a widely used approach which provides information to inform policy d ecisions

in benefit

- cost analysis of environmental regulations. EPA notes that Smith et al. ( 2002, p.134 )

state that “...nearly all benefit cost analyses rely on ben efit transfers...”

Boyle and Bergstrom ( 1992 ) define b enefit transfer as “the transfer of existing estimates of

nonmarket values to a new study which is different from the study for which the values were

originally estimated.” There are four types of benefit transfer studies: point estimate, benefit

function, meta

- analysis, and Bayesian techniques ( USEPA 2010 a) . These types may be

categorized into three fundamental classes: (1) transfer of an unadjusted fixed value estimate

generated from a single study site; (2 ) the use of expert judgment to aggregate or otherwise alter

benefits to be transferred from a site or set of sites; and (3) estimation of a value estimator model

derived from study site data, often from multiple sites ( Bergstrom and De Civita 1999 ) . Recent

studies have shown little support for the accuracy or validity of the first method, leading to

increased attention to, and use of, adjust ed values estimated by one of the remaining two

approaches ( Bergstrom and De Civita 1999 ) . The third class of benefit transfer approaches

i ncludes meta

- analysis techniques, which economists have explored increasingly as a potential

basis of policy analysis conducted by various government agencies charged with the stewardship

of natural resources. 33



### Section 7.2 provides a brief overview of th e benefit transfer methodology EPA used for

estimating the recreational fishing benefits. Chapter A5 of EPA’s Regional Benefits Analysis of

the Final Section 316(b) Phase III Existing Facilities Rule ( USEPA 2006 b ) provides a detaile d

description of the benefit transfer methodology that EPA employed in this analysis. Section 7.2

also highlights updates to the Phase III methodology. Section 7.3 presents the recreational fishing

benefits by region, and Section 7.4 summarizes the limitat ions and uncertainties inherent in

EPA’s analysis of recreational fishing benefits.



## 7.2 Methodology

EPA’s analysis of recreational fishing benefits from reducing IM&E at CWIS at regulated

facilities includes the following general steps:

33 Meta

- analysis is “the statistical analysis of a large collection of results from individual studies for the purposes of

integrating the findings” ( Glass 1976 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 2 

### 1. Estimate the forgone c atch of recreational fish (in number of fish) due to baseline

IM&E and increases in recreational harvest under regulatory options. EPA modeled

these losses using the methods presented in Chapter 3

. EPA’s estimates of recreational

fish losses are expressed as the number of harvestable adults because this is the measure

to which recreational values are attributed. 34 

### M any of the fish species affected by IM&E

at CWIS sites are harvested both recreationally and commercially. EPA used the

proportion of total speci es landings attributable to recreational fishing to estimate

baseline losses in recreational harvest due to baseline (current) levels of IM&E and

reductions in recreational harvest losses under the final rule and other options considered.

2. Estimate the marginal value per fish. EPA used the estimated meta

- regression

described in Chapter A5 of Regional Benefits Analysis of the Final Section 316(b) Phase

III Rule ( USEPA 2006 b) to estimate marginal values per fish for the species affected by

IM&E at all regulated existing facilities . To calculate the marginal value per fish for the

affected species, EPA chose input values for the independent variables based on the

affected species characteristics, study regions, and demogr aphic characteristics of the

affected angling populations. The study design variables were selected based on current

economic literature. This step is described in more detail in Section 7.2.1.

3. Estimate the value of forgone recreational catch lost to baseline IM&E benefits

under regulatory options

. EPA multiplied the marginal value per fish by the number of

recreational fish currently lost to baseline IM&E that would otherwise be caught by

recreational anglers and increases in recreational fishing harv est under policy options,

respectively.

7.2.1 Estimating Marginal Value per Fish

EPA used a benefit transfer function based on meta

- analysis of recreational fishing studies from

the Section 316(b) Phase III Final Rule to estimate marginal values per fish for the species

affected by IM&E at regulated facilities

. The general approach follows standard methods

illustrated by Johnston et al. ( 2006 ) and Shrestha et al. ( 2007 ) , among many others (e.g.,

Rosenberger and Phipps 2007). This function allows EPA to forecast willingness to pay ( WTP )

based on assigned values for model variables, chosen to best represent a resource change in the

316(b) policy context. EPA’s m eta

- analysis results imply a simple benefit function of the

following general form:

ln (WTP) = intercept + ∑(coefficient i 

### )(Independent Variable Values i 

### ) (7

- 1)

Here, ln (WTP) is the dependent variable in the meta

- analysis

— the natural log of WTP for

catching an additional fish

. The independent variables included in the meta

- analysis characterize

the species being valued, study location, baseline catch rate, elicitation and survey methods,

demog raphics of survey respondents, and other specific characteristics of each study.

To calculate the marginal value per fish for the species affected by regulated facilities, EPA chose

input values for the independent variables based on the characteristics of the affected species,

study regions, and demographic characteristics of the affected angling populations. The study

design variables were selected based on current economic literature. Table 7

- 1 provides the

34 Adul t fish of harvestable age means that they are the age at which they can legally be harvested.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 3 

### independent variable names

, the estimated varia ble coefficients ( coefficient i 

### ), and the assigned

input values for each of the independent variables in the model.

EPA followed Johnston et al. ( 2006 ) in assigning values for methodological attributes (i.e.,

variables characterizing the study methodology used in the original source studies), which are s et

at mean values from the meta data except in cases where theoretical con siderations dictate

particular assignments. This approach follows general guidance from Bergstrom and Taylor

( 2006 ) that meta

- analysis benefit transfer should incorporate theoretical expectations and

structures, at least in a weak form. In this instance , two of the methodology variables, RUM_nest

and high_resp

_ rate

, are inclu ded with an assigned value of one. RUM_year represents the year in

which the study was conducted, converted to an index by subtracting 1976. It was given the value

of 9.37, corresponding to average study year of 1985, because there was no clear justificati on for

selecting a specific year based on the meta

- data. In their detailed analysis of methodological

variable specifications for this meta

- analysis model, Stapler and Johnston ( 2009 ) found that “the

additional error associated with an empirical, mean value treatment of methodological covariates

is relatively modest, on averag e.”

EPA decided not to include the error term when using the regression equation to predict marginal

values per fish. Bockstael and Strand ( 1987 ) argue that if the econometric error in an equation is

due primarily to omitted variables, the error term should be included, but if the error is due

primarily to random preferences or measurement error, it should be excluded. Because the error

term is positive, the empirical effect of including this term is to increase the predicted marginal

values. The authors warned against t he practice of assuming that all error is associated with

omitted variables. If the error is due to random preferences or measurement errors, the estimated

WTP values are likely to be upward biased if the error term is included. EPA decided not to

include the error term in the estimation of WTP per fish because the source of error in the

underlying meta

- data is unknown. EPA notes that when the error term is excluded, the values

predicted by the regression equation are more consistent with those from the un derlying studies.

Table 7

- 2 presents region

- and species

- specific values for the input variables that vary across

regions. Table 7

- 3 presents the estimated marginal value per fish for all species affected by IM&E

in each region.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 4 

### Table 7

- 1: Independent Variable Assignments for Regres sion Equation

Variable Coefficient Assigned Value Explanation

Intercept

- 1.4568 1 The equation intercept was set to one by

default.

SP_conjoint

- 1.1672 0 Binary variables denoting the type of stated

preference, travel cost, or random utility used

for the study. Current academic literature

suggests that nested RUM models produce

the most accurate valuation results, so

RUM_nest was set to one, and the other

s tudy methodology variables were set to

zero. SP_dichot

- 0.9958 0

TC_individual 1.1091 0

TC_zonal 2.0480 0

RUM_nest 1.3324 1

RUM_nonnest 1.7892 0

SP _year 0.08754 0 Variables denoting the year that the study

was conducted by study type (stated

preference, travel cost, or random utility

model). S P _year and TC

_year were set to

zero because EPA selected RUM, above.

RUM_year was set equal to the average

value across the studies in the analysis, 9.37

. TC _year

- 0.03965 0

RUM_year

- 0.00291 9.37

SP _mail 0.5440 0 Sp_mail and sp_phone correspond to mail

and phone survey methods for stated

preference studies, Since RUM_nest was the

model specified above rather than stated

preference (i.e, SP_conjoint

, SP_dichot )

,

SP _mail and SP _phone were set to zero. SP _phone 1.0859 0

high_resp_rate

- 0.6539 1 Binary variable indicating that the survey

response rate exceeded 50 percent. EPA set

high_response_rate to one because high

response rates may provide more accurate

estimates

.

inc_thou 0.003872 Varies Household income of survey respondents in

thousands of dollars. Inc_thou was set to the

median household income for each study

region evaluated, based on U.S. Census data.

age42_down 0.9206 0.0972 Binary variables indicating whether the

average age of respondents was less than 43

or 43 and greater. Age42_down and

age43_up were set to their sample means. age43_up 1.2221 0.2711

trips19_down 0.8392 0.1100 Binary variables indicating whether the mean

number of fishing trips taken each year by

sample respondents was less than 20 or 20

and greater. Trips19_down and trips20_up

were set to their sample means. trips20_up

- 1.0112 0.3350

nonlocal 3.2355 0 Binary variable indicating that respondents

in the sample were not local residents.

Because the default (zero) value for the

nonlocal dummy variable represents a

combination of local and nonlocal anglers,

nonlocal was set to zero.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 5 

### Table 7

- 1: Independent Variable Assignments for Regression Equation

Variable Coefficient Assigned Value Explanation

big_game_pac 2.2530 Varies

Binary variables indicating the targeted

species. Species

- targeted variables were

assigned input values based on

characteristics of the species affected by

IM&E and the study region. In general, the

match between the affected species and the

variables in t he meta

- analysis equation was

good. big_game_natl 1.5323 Varies

big_game_satl 2.3821 Varies

small_game_pac 1.6227 Varies

small_game_atl 1.4099 Varies

flatfish_pac 1.8909 Varies

flatfish_atl 1.3797 Varies

other_sw 0.7339 Varies

musky 3.8671 Varies

pike_walleye 1.0412 Varies

bass_fw 1.7780 Varies

trout_GL 1.8723 Varies

trout_nonGL 0.8632 Varies

salmon_pacific 2.3570 Varies

salmon_atl_morey 5.2689 Varies

salmon_GL 2.2135 Varies

steelhead_pac 2.1904 Varies

steelhead_GL 2.3393 Varies

cr_nonyear

- 0.08135 Varies Variables describing catch rates. C r_nonyear

indicates the catch rate for studies presenting

catch rate per hour, per day, or per trip. It

was assigned species and region

- specific

values for the coastal and Great Lakes

regions based on catch rates data provided by

the National Marine Fisheries Service

(NMFS 2002

, 2003 ) and the Michigan

Department of Natural Resources ( MDNR

2002 ) . For the Inland region, EPA assigned

values to the cr_nonyear variable based on

the average values for ea ch species from the

studies. Spec_cr is a binary variable

indicating that the study presents information

on the baseline catch rate. EPA set spec_cr

to one. Catch_year is a binary variable

indicating that the study presented catch rates

on a per year basis and cr_year is the annual

catch rate from the study. Cr_year and

catch_year were set to zero because catch

per trip and catch per day are more common

measures of angling quality. cr_year

- 0.05208 0

catch_year 1.2693 0

spec_cr 0.6862 1

shore

- 0.1129 Varies

cr_year

- 0.05208 0

catch_year 1.2693 0

spec_cr 0.6862 1

shore

- 0.1129 Varies Binary variable indicating that all

respondents in the sample fished from shore.

Shore was assigned values based on NMFS

( 2002

, 2003 ) and U.S. Fish and Wildli fe

Service ( USDOI and USDOC 2002 ) survey

data indicating the average percentage of

anglers who fish from shore in each region.

Source: U.S. EPA (2006)Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 6 

### Table 7

- 2 : Region

- and Species

- s pecific Variable Assignments for the Regression

Equation a

Variable Region

California North

Atlantic Mid

Atlantic South

Atlantic Gulf of

Mexico Great

Lakes Inland

inc_thou 54.385 55.000 51.846 40.730 36.641 44.519 58.240

Shore 24.0 24.0 23.1 30.0 25.0 48.0 57.0

Species b Species Type

Dummy

Variable c Baseline Catch Rate, Expressed in Fish per Day ( cr_nonyear ) d

Small game e small_game_atl

,

small_game_pac 2.7 1.6 1.6 2.2 2.2 2.1

Flatfish f flatfish_atl

,

flatfish_pac 1.3 1.0 1.0 1.5

Other

saltwater other_sw 1.7 1.7 1.7 1.7 1.7

Salmon Salmon_GL 0.2 0.2

Walleye/pike pike_walleye 0.8 0.8

Bass bass_fw 0.2 0.2

Panfish g 4.7 4.7 4.7

Trout 3.2 3.2

Unidentified 1.7 1.7 1.7 1.7 1.9 1.9 3.8

a See Table 7

- 1 for information regarding the specification of variables that EPA held fixed across regions.

b The table is restricted to species groups which correspond to species impacted by IM&E at regulated facilities.

c This column indicates which species type dumm y variable was set to one to represent each species.

d Blank cells indicate that IM&E losses are not estimated for the species in that benefits region.

e For “small game” fish in the North Atlantic, Mid

- Atlantic, South Atlantic, Gulf of Mexico, and Inland regions, small_game_atl was

set to one. For “small game” fish in the California region, small_game_pac was set to one.

f For “flatfish” in the North Atla ntic, Mid

- Atlantic, South Atlantic, Gulf of Mexico, Great Lakes, and Inland regions, flatfish_atl was

set to one. For flatfish in the California region, flatfish_pac was set to one.

g To indicate that the target species was “panfish,” all species type dumm y variables were set to zero.

Source: U.S. EPA ( 2006 )Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 7 

### Table 7

- 3: Marginal Recreational Value per Fish, by Region and Species (2011$) a

Species California North

Atlantic Mid

Atlantic South

Atlantic Gulf of

Mexico Great

Lakes Inland

Small game $ 7.60 $ 6.22 $ 6.17 $ 5.99 $ 5.89 $ 5.61

Flatfish $ 10.21 $ 6.24 $ 5.88 $ 5.87

Other saltwater $ 3.09 $ 3.12 $ 3.05 $ 2.98 $ 2.91

Salmon $ 13.88 $ 13.88

Walleye/pike $ 4.30 $ 4.29

Bass $ 8.95 $ 9.43

Panfish $ 1.11 $ 1.39 $ 1.11

Trout $ 9.87 $ 2.96

Unidentified $ 3.25 $ 3.15 $ 3.39 $ 2.99 $ 3.83 $ 6.51 $ 2.33

a Blank cells indicate that recreational value per fish was not estimated because zero IM&E losses are estimated for the

species in that benefits region.

Source: U.S. EPA ( 2006 ) , converted to 2011 $ using the Consumer Price Index (USBLS 2011 )



### 7.2.2 Calculating Recreational Fishing Benefits

EPA estimated the recreational welfare gain from eliminating current IM& E and the recreational

welfare gain from the final rule and other options considered by combining estimates of the

marginal value per fish with the estimated recreational fishing losses under the baseline level of

IM&E, and the reduction in recreational fi shing losses attributable to the final rule and other

options considered. To calculate the recreational welfare gain from eliminating baseline IM&E,

EPA multiplied the marginal value per fish by the number of fish that are lost due to baseline

IM&E that wo uld otherwise be caught by recreational anglers. To calculate the recreational

welfare gain from the final rule and other options considered, EPA multiplied the marginal value

per fish by the estimated additional number of fish caught by recreational angle rs that would have

been impinged or entrained in the absence of the regulation. As explained in Chapter 3, these

calculations express recreational fish losses as the number of harvestable adults.

7.2.3 Sensitivity Analysis Based on the Krinsky and Robb (1986) Ap proach

The meta

- analysis model briefly described above can be used to predict mean WTP for catching

an additional fish. However, estimates derived from regression models are subject to some degree

of error and uncertainty. To better characterize the uncert ainty or error bounds around predicted

WTP, EPA adopted the statistical procedure described by Krinsky and Robb in their 1986 Review

of Economics and Statistics paper, “Approximating the Statistical Property of Elasticities.” The

procedure involves sampling from the variance

- covariance matrix and means of the estimated

coefficients. WTP values are then calculated for each drawing from the variance covariance

matr ix, and constructing an empirical distribution of WTP values. By varying the number of

drawings, it is possible to generate an empirical distribution with a desired degree of accuracy

( Krinsky and Robb 1986 ) . The lower or upper bound of WTP values can then be identified ba sed

on the 5 th 

### and 95 th 

### percentile of WTP values from the empirical distribution. These bounds may

help decision

- makers understand the uncertainty associated with the benefit results.

The results of EPA’s calculations are shown in Table 7

- 4 . The table pres ents 95 th 

### percentile upper

confidence bounds and 5 th 

### percentile lower confidence bounds for the marginal value per fish for

each species in each region. These bounds can be used to estimate upper and lower confidenceBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 8 

### bounds for the WTP for improvements in recreational catch rates from eliminating baseline

IM&E or reducing IM&E under the final rule and other options considered. Refer to EPA ( 2006 )

for more detail on the specific calculations. The 5 th 

### percentile values shown in Table 7

- 4 show

that, with the except ion of panfish, even the lowest estimates of recreational value are well above

$1.00 per fish. Certainly, all are above zero.

Table 7

- 4: Confidence Bounds on Marginal Recreational Value per Fish, Based

on the Krinsky and Robb Approach ( 2011$) a

Species California North

Atlantic Mid

Atlantic South

Atlantic Gulf of

Mexico Great

Lakes Inland

5 th Percentile Lower Confidence Bounds b

Small game $4.40 $2.23 $2.37 $2.84 $3.00 $1.68

Flatfish $5.35 $3.98 $3.92 $4.05

Other saltwater $1.87 $1.87 $1.94 $2.24 $2.23

Salmon $8.53 $8.53

Walleye/pike $2.28 $2.07

Bass $4.63 $4.48

Panfish $0.55 $0.73 $0.55

Trout $6.39 $1.59

Unidentified $1.95 $1.88 $2.00 $2.25 $2.47 $3.49 $1.13

95 th Percentile Upper Confidence Bounds

Small game $13.01 $17.53 $16.23 $12.59 $1.55 $18.90

Flatfish $19.49 $9.86 $8.92 $8.66

Other saltwater $5.11 $5.20 $4.82 $3.95 $3.78

Salmon $22.61 $22.61

Walleye/pike $8.16 $8.92

Bass $17.38 $19.96

Panfish $2.20 $2.61 $2.20

Trout $15.34 $5.53

Unidentified $5.42 $5.26 $6.00 $3.99 $6.18 $12.25 $4.81

a Blank cells indicate that recreational value per fish was not estimated because IM&E losses are not estimated for the

species in that benefits region.

b Upper and lower confidence bounds based on results of the Krinsky and Robb ( 1986 ) approach.

Source: U.S. EPA ( 2006 ) , converted to 20011$ using the Consumer Price Index ( USBLS 2011 )

.



## 7.3 Benefits Estimates for Recreational Fishing by Region

7.3.1 California Region

Table 7

- 5 presents the estimated increase in recreational fishing harvest and associated welfare

gains from the elimination of baseline IM&E in the California region. EPA estimates an annual

harvest increase of 1.4 million fish from the elimination of baseline IM&E, the majority

attributable to reduced entrainment of rockfish and sea bass. The associated mean annual welfare

gain is $ 4.0 million and $ 3.6 million

, evaluated at 3 percent and 7 percent discount rates,

respectively. The majority of the monetized recreational benefits from eliminating baseline IM&E

is attributable to entrainment of “other saltwater” fish. 35

35 The “other saltwater” species group includes banded drum, black drum, chubby, cod family, cow cod, croaker,

grouper, grunion, grunt, high

- hat, kingfish, lingco d, other drum, perch, porgy, rockfish, sablefish, sand drum,

sculpin, sea bass, smelt, snapper, spot, spotted drum, star drum, white sea bass, wreckfish, other bottom species,

other coastal pelagics, and “no target” saltwater species.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 9 

### Table 7

- 5 also presents the annual recreational harvest increases and welfare gains to California

anglers under the final rule and other options considered. EPA estimates that the final rule will

increase annual harvest by 0.04 million fish. The mean annualized welfare gain under final rule

will be less than $0.1 million usi ng both 3 percent and 7 percent discount rates. Annual harvest

increases under other options considered range from 0.04 million fish under Proposal Option 4 to

0.88 million fish under Proposal Option 2. Mean annualized benefits under other options

consider ed range from less than $0.1 to $1.5 million using a 3 percent discount rate and less than

$0.1 to $1.0 million using a 7 percent discount rate. Appendix I presents additional species

specific results for final file rule, other options considered, and the elimination of baseline IM&E.

Table 7

- 5 : Recreational Fishing Benefits from Eliminating or Reducing Baseline IM&E

at Regulated Facilities in the California Region, for the Final Rule and Options

Cons idered (2011$)

Regulatory Option Annual Increase in

Recreational

Harvest

(harvestable adult

fish) Annualized Benefits from Increase in Recreational

Harvest

(2011$, 1,000s) a

3 % Discount Rate 7 % Discount Rate

5 th Mean 95 th 5 th Mean 95 th

Proposal Option 4 35,420 $42 $69 $114 $30 $50 $83

Final Rule 38,159 $45 $74 $123 $33 $54 $89

Proposal Option 2 877,174 $919 $1,543 $2,595 $592 $994 $1,673

Baseline 1,431,170 $2,408 $4,044 $6,803 $2,153 $3,616 $6,084

a 5th and 95th are the 5th and 95th percentiles based on the results of the Krinsky and Robb (1986) approach.

Source: U.S. EPA analysis for this report



### 7.3.2 North Atlantic Region

Table 7

- 6 presents the estimated increase in recreational fishing harvest and ass ociated welfare

gains from the elimination of baseline IM&E in the North Atlantic region. EPA estimates an

annual harvest increase of 0.73 million fish from the elimination of baseline IM&E, the majority

attributable to reduced entrainment of winter flound er, cunner, and sculpin

. The associated mean

annual welfare gain is $ 2.7 million and $ 2.4 million

, evaluated at 3 percent and 7 percent

discount rates, respectively. The majority of the monetized recreational benefits from eliminating

baseline IM&E is attr ibutable to entrainment of “flatfish” and “other saltwater” fish

. 36



### Table 7

- 6 also presents the annual recreational harvest increases and welfare gains to North

Atlantic anglers under the final rule and other options considered. EPA estimates that the final

rule will increase annual harvest by less than 0.01 million. The mean annua lized welfare gain

under final rule will be less than $0.1 million using both 3 percent and 7 percent discount rates.

Annual harvest increases under other options considered range from less than 0.01 million fish

under Proposal Option 4 to 0.56 million fis h under Proposal Option 2. Mean annualized benefits

under other options considered range from less than $0.1 to $1.4 million using a 3 percent

discount rate and from less than $0.1 to $0.9 million using a 7 percent discount rate. Appendix I

36 The “other saltwat er” species group includes banded drum, black drum, chubby, cod family, cow cod, croaker,

grouper, grunion, grunt, high

- hat, kingfish, lingcod, other drum, perch, porgy, rockfish, sablefish, sand drum,

sculpin, sea bass, smelt, snapper, spot, spotted drum, star drum, white sea bass, wreckfish, other bottom species,

other coastal pelagics, and “no target” saltwater species.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 10 

### presents additi onal species

- specific results for final file rule, other options considered, and the

elimination of baseline IM&E.

Table 7

- 6 : Recreational Fishing Benefits from Eliminating or Reducing Baseline IM&E

at Regulated Facilities in the North Atlantic Region, fo r the Final Rule and Options

Considered (2011$)

Regulatory Option Annual Increase in

Recreational

Harvest

(harvestable adult

fish) Annualized Benefits from Increase in Recreational

Harvest

(2011$, 1,000s) a

3 % Discount Rate 7 % Discount Rate

5 th Mean 95 th 5 th Mean 95 th

Proposal Option 4 1,367 $3 $4 $7 $2 $3 $5

Final Rule 7,975 $14 $23 $36 $10 $16 $27

Proposal Option 2 562,305 $852 $1,371 $2,219 $573 $921 $1,491

Baseline 733,985 $1,682 $2,705 $4,380 $1,504 $2,419 $3,917

a 5th and 95th are the 5th and 95th percentiles based on the results of the Krinsky and Robb (1986) approach.

Source: U.S. EPA analysis for this report



### 7.3.3 Mid

- Atlantic Region

Table 7

- 7 presents the estimated increase in recreational fishing harvest and associated welfare

gains from the elimination of baseline IM&E in the Mid

- Atlantic region. EPA estimates an

annual harvest increase of 5.82 million fish from the elimination of baseline IM&E, the m ajority

attributable to reduced IM&E of spot and Atlantic croaker

. The associated mean annual welfare

gain is $ 16.2 million and $ 14.5 million

, evaluated at 3 percent and 7 percent discount rates,

respectively. The majority of the monetized recreational benefits from eliminating baseline IM&E

is attributable to the entrainment of “ other saltwater ” fish

.

Table 7

- 7 also presents the annual recreati onal harvest increases and welfare gains to Mid

Atlantic anglers under the final rule and other options considered. EPA estimates that the final

rule will increase annual harvest by 0.46 million fish. The mean annualized welfare gain under

final rule will be $1.1 million using a 3 percent rate and $0.8 million using a 7 percent discount

rate. Annual harvest increases under other options considered range from 0.43 million fish under

Proposal Option 4 to 5.10 million fish under Proposal Option 2. Mean annuali zed benefits under

other options considered range from $1.0 to $8.6 million using a 3 percent discount rate and from

$0.7 to $5.5 million using a 7 percent discount rate. Appendix I presents additional species

specific results for final file rule, other op tions considered, and the elimination of baseline IM&E.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 11 

### Table 7

- 7 : Recreational Fishing Benefits from Eliminating or Reducing Baseline IM&E

at Regulated Facilities in the Mid

- Atlantic Region, for the Final Rule and Options

Considered (2011$)

Regulatory Option Annual Increase in

Recreational

Harvest

(harvestable adult

fish) Annualized Benefits from Increase in Recreational

Harvest

(2011$, 1,000s) a

3 % Discount Rate 7 % Discount Rate

5 th Mean 95 th 5 th Mean 95 th

Proposal Option 4 427,924 $531 $988 $1,961 $376 $700 $1,389

Final Rule 460,839 $572 $1,063 $2,108 $405 $753 $1,493

Proposal Option 2 5,103,595 $5,132 $8,634 $15,072 $3,273 $5,506 $9,612

Baseline 5,823,189 $9,665 $16,249 $28,341 $8,643 $14,531 $25,343

a 5th and 95th are the 5th and 95th percentiles based on the results of the Krinsky and Robb (1986) approach.

Source: U.S. EPA analysis for this report



### 7.3.4 South Atlantic Region

Table 7

- 8 presents the estimated increase in recreational fishing harvest and associated welfare

gains from the elimination of baseline IM&E in the South Atlantic region. EPA estimates an

annual harvest increase of 0.11 million fish from the elimination of baseline IM&E, the majority

attributable to reduced IM&E of “other saltwater” fish , especially spot and croakers

. The

associated mean annual welfare gain is $ 0.3 million evaluated at both 3 percent and 7 percent

discount rates. The majority of the monetized recreational ben efits from eliminating baseline

IM&E is attributable to entrainment of “other saltwater” fish

.

Table 7

- 8 also presents the annual recreational harvest increases and welfare gains to South

Atlantic anglers under the final rule and other options considered. EPA estimates that the final

rule will increase annual harvest by 0.02 million fish. The mean annualized welfare gain under

final rule will be less than $0.1 million using both 3 percent and 7 percent discount rates. Annual

harvest increases under other op tions considered range from 0.01 million fish under Proposal

Option 4 to 0.10 million fish under Proposal Option 2. Mean annualized benefits under other

options considered range from less than $0.1 to $0.2 million using a 3 percent discount rate and

from l ess than $0.1 to $0.1 million using a 7 percent discount rate. Appendix I presents additional

species

- specific results for final file rule, other options considered, and the elimination of baseline

IM&E.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 12 

### Table 7

- 8 : Recreational Fishing Benefits from Elimi nating or Reducing Baseline IM&E

at Regulated Facilities in the South Atlantic Region, for the Final Rule and Options

Considered (2011$)

Regulatory Option Annual Increase in

Recreational

Harvest

(harvestable adult

fish) Annualized Benefits from Increase in Recreational

Harvest

(2011$, 1,000s) a

3 % Discount Rate 7 % Discount Rate

5 th Mean 95 th 5 th Mean 95 th

Proposal Option 4 12,983 $18 $24 $33 $13 $17 $23

Final Rule 18,725 $26 $35 $47 $18 $24 $33

Proposal Option 2 104,943 $129 $173 $234 $86 $115 $156

Baseline 111,075 $211 $284 $385 $189 $254 $344

a 5th and 95th are the 5th and 95th percentiles based on the results of the Krinsky and Robb (1986) approach.

Source: U.S. EPA analysis for this report



### 7.3.5 Gulf of Mexico Region

Table 7

- 9 presents the estimated increase in recreational fishing harvest and associated welfare

gains from the elimination of baseline IM& E in the Gulf of Mexico region. EPA estimates an

annual harvest increase of 3.08 million fish from the elimination of baseline IM&E, the majority

attributable the impingement of spotted seatrout and the entrainment of black drum and pinfish

. The associated mean annual welfare gain is $ 9.6 million and $ 8.8 million

, evaluated at 3 percent

and 7 percent discount rates, respectively. The majority of the monetized recreational benefits

from eliminating baseline IM&E is attributable to both the impingement of “sm all game” fish and

the entrainment of “other saltwater” species

.

Table 7

- 9 also presents the annual recreational harvest increases and welfare gains to Gulf of

Mexico anglers under the final rule and other options considered. EPA estimates that the final

r ule will increase annual harvest by 0.78 million fish. The mean annualized welfare gain under

final rule will be $2.3 million using a 3 percent discount rate and $1.6 million using a 7 percent

discount rate. Annual harvest increases under other options con sidered range from 0.75 million

fish under Proposal Option 4 to 2.14 million fish under Proposal Option 2. Mean annualized

benefits under other options considered range from $2.2 to $5.1 million using a 3 percent

discount rate and from $1.6 to $3.8 million using a 7 percent discount rate. Appendix I presents

additional species

- specific results for final file rule, other options considered, and the elimination

of baseline IM&E.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 13 

### Table 7

- 9 : Recreational Fishing Benefits from Eliminating or Reducing Baseline I M&E

at Regulated Facilities in the Gulf of Mexico Region, for the Final Rule and Options

Considered (2011$)

Regulatory Option Annual Increase in

Recreational

Harvest

(harvestable adult

fish) Annualized Benefits from Increase in Recreational

Harvest

(2011$, 1,000s) a

3 % Discount Rate 7 % Discount Rate

5 th Mean 95 th 5 th Mean 95 th

Proposal Option 4 749,144 $1,260 $2,183 $3,904 $914 $1,583 $2,831

Final Rule 777,488 $1,308 $2,265 $4,051 $948 $1,643 $2,938

Proposal Option 2 2,137,861 $3,357 $5,116 $8,122 $2,476 $3,774 $5,991

Baseline 3,077,617 $6,457 $9,575 $14,756 $5,955 $8,831 $13,610

a 5th and 95th are the 5th and 95th percentiles based on the results of the Krinsky and Robb (1986) approach.

Source: U.S. EPA analysis for this report



### 7.3.6 Great Lakes Region

Table 7

- 10 presents the estimated increase in recreational fishing harvest and associated welfare

gains from the elimination of baseline IM& E in the Great Lakes region. EPA estimates an annual

harvest increase of 2.23 million fish from the elimination of baseline IM&E, the majority

attributable to IM&E of white bass and “unidentified” species

. The associated mean annual

welfare gain is $ 13.8 m illion and $ 12.8 million

, evaluated at 3 percent and 7 percent discount

rates, respectively. The majority of the monetized recreational benefits from eliminating baseline

IM&E is attributable to the impingement of bass and “unidentified” fish

.

Table 7

- 10 also presents the annual recreational harvest increases and welfare gains to Great

Lakes anglers under the final rule and other options considered. EPA estimates that the final rule

will increase annual harvest by 1.47 million fish. The mean annualized wel fare gain under final

rule will be $7.2 million using a 3 percent discount rate and $5.3 million using a 7 percent

discount rate. Annual harvest increases under other options considered range from 1.33 million

fish under Proposal Option 4 to 2.04 million f ish under Proposal Option 2. Mean annualized

benefits under other options considered range from $6.5 to $8.9 million using a 3 percent

discount rate and from $4.8 to $6.4 million using a 7 percent discount rate. Appendix I presents

additional species

- speci fic results for final file rule, other options considered, and the elimination

of baseline IM&E.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 14 

### Table 7

- 10 : Recreational Fishing Benefits from Eliminating or Reducing Baseline

IM&E at Regulated Facilities in the Great Lakes Region, for the Final Rule and

Options Considered (2011$)

Regulatory Option Annual Increase in

Recreational

Harvest

(harvestable adult

fish) Annualized Benefits from Increase in Recreational

Harvest

(2011$, 1,000s) a

3 % Discount Rate 7 % Discount Rate

5 th Mean 95 th 5 th Mean 95 th

Proposal Option 4 1,331,956 $3,446 $6,509 $12,385 $2,562 $4,839 $9,208

Final Rule 1,466,650 $3,793 $7,166 $13,636 $2,820 $5,328 $10,138

Proposal Option 2 2,044,018 $4,717 $8,922 $16,993 $3,359 $6,354 $12,102

Baseline 2,232,409 $7,306 $13,825 $26,338 $6,738 $12,751 $24,292

a 5th and 95th are the 5th and 95th percentiles based on the results of the Krinsky and Robb (1986) approach.

Source: U.S. EPA analysis for this report



### 7.3.7 Inland Region

Table 7

- 11 presents the estimated increase in recreational fishing harvest and associated welfare

gains from the elimination of baseline IM&E in the Inland region. EPA estimates an annual

harvest increase of 11.90 million fish from the elimination of baseline IM&E, the majority

attributable to IM&E of “bass,” “panfish,” and “unidentified” species groups . The associated

mean annual welfare gain is $32.1 million and $29.6 million, evaluated at 3 percent and 7 percent

discount rates, respectively. The majority of the mo netized recreational benefits from eliminating

baseline IM&E is attributable to IM&E of “bass,” “panfish,” and “unidentified” fish.

Table 7

- 11 also presents the annual recreational harvest increases and welfare gains to Inland

anglers under the final rule and other options considered. EPA estimates the final rule will

increase annual harvest by 3.73 million fish. The mean annualized welfare gain under the final

rule will be $7.6 million using a 3 percent discount rate and $5.7 million using a 7 percent

disc ount rate. Annual harvest increases under other options considered range from 3.57 million

fish under Proposal Option 4 to 9.70 million fish under Proposal Option 2. Mean annualized

benefits under other options considered range from $7.3 to $17.2 million u sing a 3 percent

discount rate and $5.4 to $11.9 million using a 7 percent discount rate. Appendix I presents

additional species

- specific results for final file rule, other options considered, and the elimination

of baseline IM&E.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 15 

### Table 7

- 11 : Recreational Fishing Benefits from Eliminating or Reducing Baseline IM&E

at Regulated Facilities in the Inland Region, for the Final Rule and Options Considered

(2011$)

Regulatory Option Annual Increase in

Recreational Harvest

(harvestable adult

fish) Annualized Benefits from Increase in Recreational Harvest

(2011$, 1,000s) a

3 % Discount Rate 7 % Discount Rate

5 th Mean 95 th 5 th Mean 95 th

Proposal Option 4 3,570,053 $3,503 $7,284 $15,231 $2,616 $5,440 $11,375

Final Rule 3,731,608 $3,661 $7,613 $15,918 $2,735 $5,686 $11,889

Proposal Option 2 9,704,334 $8,290 $17,204 $35,865 $5,726 $11,883 $24,773

Baseline 11,900,351 $15,471 $32,105 $66,919 $14,270 $29,611 $61,722

a 5th and 95th are the 5th and 95th percentiles based on the results of the Krinsky and Robb (1986) approach.

Source: U.S. EPA analysis for this report



### 7.3.8 National Estimates

Table 7

- 12 presents the estimated national increase in recreational fishing harvest and associated

welfare gains to anglers from eliminating baseline IM&E. EPA estimates an annual harvest

increase of 25.31 million fish from eliminating baseline IM&E

. The associated mean annual

welfare gain is $ 78.8 million and $ 72.0 million, evaluated at 3 percent and 7 percent discount

rates, respectively.

Table 7

- 12 also presents the national recreational harvest increases and welfare gains to anglers

under the final rule and other options considered. EPA estimate s the final rule will increase

annual harvest by 6.50 million fish. The mean annualized welfare gain under final rule will be

$ 18.2 million using a 3 percent discount rate and $ 13.5 million using a 7 percent discount rate.

Annual harvest increases under ot her options considered range from 6.13 million fish under

Proposal Option 4 to 20.53 million fish under Proposal Option 2. Mean annualized benefits under

other options considered range from $ 17.1 to $ 43.0 million using a 3 percent discount rate and

$ 12.6 t o $ 29.5 million using a 7 percent discount rate. Appendix I presents additional species

specific results for the final rule, other options considered, and the elimination of baseline IM&E.

Table 7

- 12 : National Recreational Fishing Benefits from Eliminatin g or Reducing

Baseline IM&E at Regulated Facilities, for the Final Rule and Options Considered (2011$)

Regulatory Option Annual Increase in

Recreational Harvest

(harvestable adult

fish) Annualized Benefits from Increase in Recreational Harvest

(2011$, 1,000s) a

3 % Discount Rate 7 % Discount Rate

5 th Mean 95 th 5 th Mean 95 th

Proposal Option 4 6,128,847 $8,803 $17,061 $33,635 $6,513 $12,632 $24,914

Final Rule 6,501,444 $9,419 $18,239 $35,919 $6,969 $13,504 $26,607

Proposal Option 2 20,534,230 $23,396 $42,963 $81,100 $16,085 $29,547 $55,798

Baseline 25,309,796 $43,200 $78,787 $147,922 $39,452 $72,013 $135,312

a 5th and 95th are the 5th and 95th percentiles based on the results of the Krinsky and Robb (1986) approach.

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 7: Recreational Fishing Benefits

May 2014 7

- 16 

## 7.4 Limitations and Uncertainties

A number of limitations and uncertainties are common in application of benefit transfer

approaches to valuing benefits of environmental policies and programs. To better characterize the

uncertainty or error bounds around predicted WTP, EPA adopted the statistical procedure

described by Krinsky and Robb in their 1986 Review of Economics and Statistics paper

“Approximating the Statistical Property of Elasticities, ” to generate lower and upper bound WTP

values identified as the 5th and 95th percentile of values from the empirical distribution.

Additional detail regarding the Krinsky and Robb approach is provided in Section 7.2.3 . These

bounds may help decision

- maker s understand the uncertainty associated with the benefit results

for eliminating baseline IM&E and the 316(b) final rule and regulatory options considered.

Specific limitations and uncertainties associated with the estimated regression model and the

underl ying studies are discussed in Section A5

- 3.3e of EPA ( 2006 ) . A dditional limitations and

uncertainties associated with the calculation of per

- fish values from the model, and with the use

of those values to estimate the welfare gain resulting from the final secti on 316(b) regulation and

regulatory options considered, are addressed below in Table 7

- 13

.

Table 7

- 13 : Other Caveats, Omissions, Biases, and Uncertainties in the Recreational

Benefits Estimates

Issue Impact on

Benefits

Estimate Comments

Exclusion of error term

from regression

equation to predict

marginal values Estimates

understated B ecause the source of error in the underlying meta

- data is unknown EPA

decided not to include the error term in estimating marginal values per

fish . EPA notes that if the source of error is due primarily to the omitted

variables the estimated WTP may be biased downward. See Section 7.2.1

for more a detailed discussion regarding EPA’s treatment of the error

term.

Validity and reliability

of benefit transfer Uncertain The va lidity and reliability of benefit transfer

— including that based on

meta

- analysis

— depend on a variety of factors. While benefit transfer can

provide valid measures of use benefits, tests of its performance have had

mixed results ( e.g. Desvousges et al. 1998 ; Smith et al. 2002 ; Vandenberg

et al. 2001 ) . Nonetheless, benefit transfers are increasingly applied as a

core component of benefit

- cost analyses conducted by EPA and other

government agencies ( Bergstrom and De Civita 1999 ; Griffiths undated )

. Smith et al. ( 2002, p.134 ) stat e that “nearly all benefit cost analyses rely

on benefit transfers, whether they acknowledge it or not.” An important

factor in any benefit transfer is the ability of the study site or estimated

valuation equation to approximate the resource and context fo r which

benefit estimates are desired. As is common, the meta

- analysis model

presented here provides a close but not perfect match to the context in

which values are desired.

IM&E estimates Uncertain R ecreational losses due to IM&E may be higher or lower than expected

for a number of reasons . Projected changes in recreational catch may be

underestimated because cumulative impacts of IM&E over time are not

considered. In particular, IM&E estimates include only individuals

directly lost to IM&E , not their pr ogeny. Additionally, the interaction of

IM&E with other stressors may have either a positive or negative effect

on recreational catch. Finally, in estimating recreational fishing losses,

EPA used the most current IM&E data available provided by facilities,

which in some cases may not reflect current conditions.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 1 

# 8 Nonuse Benefit Transfer Approach

8.1 Introduction

Comprehensive estimates of total social value include both use and nonuse values, and may be compared

to total social cost. “Non

- use values, like use values, have their basis in the theory of individual

preferences and the measurement of welfare changes. According to theory, use values and non

- use values

are additive” ( Freeman III 1993 ) . Consequently, excluding nonuse values from consideration is likely to

substantially understate total social values. Recent economic literature provides strong support for the

hypothes is that nonuse values are greater than zero for many types of environmental improvements.

Moreover, when a substantial fraction of the population holds even small per capita nonuse values, these

nonuse values can be very large in the aggregate. As stated b y Freeman ( 1993 ) , “there is a real possibility

that ignoring non

- use values could result in serious misallocation of resources.” Both EPA’s own

Guidelines for Preparing Economic Analysis and OMB’s Circular A

- 4, governing regulatory analysis,

support the need to assess nonuse values ( USEP A 2010a ; USOMB 2003 )

.

The vast majority (97 percent) of current (i.e., baseline) IM&E at CWIS consist of forage species and

unlanded individuals of recreational and commercial species (Chapter 3). Although these forage and

unlanded fish do not have direct use values, they may be valued by nonusers of fisheries resources (whose

value for such fish is by definition a nonuse valu e) and by users separate from their use value. The nonuse

values are likely to be substantial because fish and other species found within aquatic habitats impacted

directly and indirectly by CWIS provide other valuable ecosystem goods and services, includi ng nutrient

cycling and ecosystem stability. Therefore, a comprehensive estimate of the welfare gain from reducing

IM&E must include an estimate of nonuse benefits. The following sections present EPA’s qualitative

assessment of nonuse benefits and partial monetized nonuse benefits based on benefit transfer from an

existing stated preference study. EPA evaluated the public’s nonuse values for aquatic habitats

qualitatively by considering evidence from existing aquatic restoration and protection programs (Sec tion

8.2 ). EPA also provides a quantitative estimate of the numbers of A1E whose benefits are likely to be

mainly associated with nonuse (Table 3

- 15; reproduced as Table 8

- 1 ). Finally, EPA used benefit transfer

to generate a partially monetized estimate of nonuse benefits associated with reductions in IM&E of fish,

shellfish, and other aquatic organisms under the final rule and other options considered in the North

Atlantic and Mid

- Atlantic Regions . The methodology is described in Section 8.3 and Section 8. 4 presents

the results.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 2 

### Table 8

- 1 : Baseline IM&E and IM&E Reductions at All Regulated Facilities

(Manufacturing and Generating) Nationally, and Reductions under the Final Rule

and Other Options Considered

I M&E Loss Metric (per year) Reductions in Losses Baseline

Losses Proposal

Option 4 Final

Rule Proposal

Option 2

All Species (million A1E) 614.16 652.00 1637.49 1930.97

Forage Species (million A1E) 528.22 560.80 1258.67 1459.70

Commercial & Recreational Species (million A1E) 85.94 91.20 378.82 471.28

Commercial & Recreational Harvest (million fish) 16.13 17.11 44.66 54.02

A1E Losses with Direct Use Value (%) 2.6% 2.6% 2.7% 2.8%

Source: U.S. EPA analysis for this report



## 8.2 Public Policy Significance of Ecological Improvements from the Final Rule

EPA expects that c hanges to CWIS design and operation resulting from the final existing facilities rule

will reduce IM&E of fish, shellfish, and other aquatic organisms and lead to increases in lo cal and

regional fishery populations and ecosystem stability. In addition to those direct effects, many indirect

ecosystem goods and services are affected by IM&E , thermal effects, and flow alteration. Due to the

wide

- ranging nature of these indirect effec ts, the existing facilities rule is likely to enhance the value of

ecosystem goods and services provided by aquatic habitats, and will help reduce the overall impact of

anthropogenic effects on aquatic systems affected by CWIS. Chapter 2 provides a detailed list of

ecosystem services potentially affected by the rule.

EPA assessed the potential magnitude of nonuse benefits using information regarding government

spending on the protection, restoration, and regulation of various aquatic hab itats . These habitats include

Marine Protected Areas (Section 8.2.2 ) and a subset of freshwater ecosystems undergoing large

- scale

restoration efforts (Section 8.2.3 ). Although not estimates of benefits of improving aquatic ecosystems,

these expenditures ar e still an indication of significant social values for the protection of aquatic

resources.

8.2.1 Effects on Depleted Fish Populations

Reducing IM&E will contribute to the health and sustainability of the affected fish populations by

lowering the overall level o f mortality for these populations. Fish populations suffer from numerous

sources of mortality, both natural and anthropogenic. Natural sources include weather, predation by other

fish, and the availability of food. Human activities besides IM&E include fis hing, pollution, and habitat

alteration. Fish populations decline when they are unable to compensate sufficiently for their overall level

of mortality. Although it is difficult to measure, the compensatory ability of an aquatic population

— the

capacity for a species to increase survival, growth, or reproduction rates in response to decreased

population

—

is likely compromised by IM&E and the cumulative impact of other stressors in the

environment over extended periods of time ( USEPA 2006 a)

.

Lowering the overall mortality level increases the probability that a population will be able to

compensate for mortality at a level sufficient to maintain long

- term health. In some cases, impingement

and entrainmen t may be significant source of mortality to already

- depleted stocks of commercially

targeted species (see Chapter 2). Depleted saltwater fish stocks affected by IM&E include winter

flounder, Atlantic Cod, and rockfish, for example ( NMFS 2012 ) . As discussed in Chapter 2, IM&E alsoBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 3 

### increases the pressure on freshwater s pecies native to the Great Lakes, s uch as lake whitefish and yellow

perch, the populations of which have declined dramatically in recent years ( USDOI 2008 ; Wisconsin

DNR 2003 )

.

The federal govern ment and the states have recognized t he public importance of maintaining sustainable

fisheries, achieving recovery of depleted fish stocks, and ensuring that functioning ecosystems are passed

to future generations . Federal and state government actions have i nclude d buying fishing licenses and

fishing vessels from individual fishers when stocks appear depressed , imposing restrictions on

commercial and recreational harvests, conducting large

- scale ecosystem restoration projects ( USDOI

2008 ) , and President George W. Bush’s ex ecutive order creatin g a national system of marine protected

areas ( Executive Order No. 13158 2001 )

. T ogether, these governmental actions suggest that the public

holds substantial nonuse values for aquatic habitats.

8.2.2 Marine Protected Areas

A Marine Protected Area (MPA) is “any area of the marine environment that has been reserved by

federal, state, tribal, territorial, or local laws or regulations to provide lasting protection for part or all of

the natural and cultural resources therein” ( Executive Order No. 13158 2001 )

. In some s tates, the majority

of coastal waters are found within MPAs (e.g., Massachusetts, Hawaii ). The ecological i mportance of

MPAs varies widely because of the broad focus on the preservation and maintenance of cultural and

natural resources, and/or sustainable production ( NMPAC 2006 )

. Consequently, evaluating the impact of

CWIS o n the entire universe of MPAs may overstate the nonuse values for the ecological benefits

associated with reductions in IM&E: because some MPAs are focused on the preservation of cultural

resources (including historic shipwrecks, aircraft and other struc tures, submerged prehistoric remains, and

sites with traditional cultural properties), they are likely to be less ecologically important than others.

For this reason , EPA focused on facilities in MPAs within the National Estuary Program (NEP). The NEP

was established in the 1987 amendments to the CWA because the “Nation’s estuaries are of great

importance to fish and wildlife resources and recreation and economic opportunity [and because

maintaining] the health and ecological integrity of these estuarie s i s in the national interest” ( Water

Quality Act 1987 ) . In a ddition to the 28 estuaries designated under the NEP ( USEPA 2010b ) , EPA

included facilities found in Chesapeake Bay ( which is protected by the Chesapeake Bay Program [ CBP ] ).

Substantial federal and state resources have been directed to the NEP and CBP to enhance conservation of

and knowledge about estuari es. Including funds received from federal, state, local and private sources,

from 2005 to 2013 , the NEP spent $ 3.5 billion to protect and restore aquatic habitat, support land

acquisitions , conduct outreach and research, upgrade wastewater and stormwater infrastructure, and

implement other priority actions to benefit the health of the 28 estuaries designated under the NEP.

Approximately 11.1 percent, or $ 389 million, was designated for restoration programs (USEPA 201 4).

Between fiscal ye ars 199 5 and 2004, direct funding by federal and State governments to restore the

Chesapeake Bay averaged $366 million annually (GAO 2005), with an additional $131 million in direct

spending fiscal year 2005 (CBP 2007). . Moreover, recent governmental action is li kely to increase

restoration efforts in the future ( Executive Order No. 13508 2009 ) , Thes e expenditures reflect high public

values for r estoring (or protecting) the biological integrity of these ecosystems.

A total of 44 regulated facilities are located on 32 waterbodies within M PAs designed to preserve natural

resources and/or to ensure susta inable production ( NOAA 2012 ) ( Figure 8

- 1 ; Table 8

- 2 ). Although these

facilities are located in fresh, brackish, and marine waters, the vast majority located within MPAs are in

coastal waters and are most highly concentrated in the Northeastern U.S. (i.e. both coastal and inlandBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 4 

### facilities) ( Figure 8

- 1 ; Table 8

- 2 ). Under the final rule, EPA estimates that 60 percent of regulated

facilities (15 out of 25 facilities for which data are available) found within MPAs obtain reductions in

impingement mortality. This estimate is based upon facilities for which suffici ent data exist for EPA to

estimate technology currently in

- place. Additionally, although entrainment may be reduced at some

facilities as a consequence of the final rule, EPA was not able to estimate reductions in entrainment likely

to occur due to site

- sp ecific determination of entrainment BTA for facilities with CWIS inside of MPAs

.

Figure 8

- 1: Regulated Facilities with CWIS Located in Marine Protected AreasBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 5 

### Table 8

- 2 : 316(b) Facilities in Marine Protected Areas and Improvements in IM&E Tech for

the Final Rule and Other Options Considered

Region Number of Facilities with Improved

Technologies by Option a,b

Baseline Proposal

Option 4 Final Rule Proposal

Option 2

IM E IM E IM E Number of

Facilities Affected

Waterbodies Facilities With

Tech Data b

California 1 0 1 0 1 1 2 2 1

North Atlantic 2 0 2 0 2 2 7 6 6

Mid

- Atlantic 8 0 8 0 8 6 24 15 12

South Atlantic 0 0 0 0 0 0 2 1 1

Gulf of Mexico 2 0 2 0 3 3 3 3 3

Great Lakes 0 0 0 0 0 0 0 0 0

Inland 2 0 2 0 2 2 6 5 2

Total 15 0 15 0 16 14 44 32 25

a IM is impingement mortality and E is entrainment.

b EPA does not have adequate data for all facilities to e stimate current compliance with, or the number of facilities installing improved

technologies because of, the final rule.

Source: U.S. EPA analysis for this report



### 8.2.3 Restoration of Freshwater Ecosystems

Reducing the effect of CWIS at regulated facilities is likely to benefit aquatic ecosystems nationwide.

Due to a high density of facilities, and the potential for cumulative impacts associated with facilities in

close proximity to each other (see Chapter 2 for additional details), the greatest improvements may occur

in areas of the Great Lakes Basin and Mississippi River. There are large

- scale ecosystem restoration

efforts for these freshwater bodies that indicate public support for restoring the ecological health of these

ecosystems ( Northeast Midwest Institute 2010 ; USDOI 2008 ; USFWS 2011 ; Upper Mississippi River

Basin Association 2004 )

.

Nationally, ecosystem restoration efforts focus on many issues, including coastal habitat restoration,

pr otection of fish species, and conservation of migratory birds. For example, the federal government

provided in excess of $1.7 billion for sport fish restoration between fiscal years 2005 and 2009 ( USFWS

2010 c)

, and has initiated a 5

- year multi

- agency initiative to restore the ecosystems of the Great Lakes, for

which $ 1.05 billion of federal funds were appropriated in fiscal years 2010 through 2012 (G reat Lakes

Restoration Initiative 2012)

. Additionally, t he restoration of major inland ri ver ecosystems has been

recognized as a worthwhile goal, with more than $100 million spent on restoring ecosystems along the

Mississippi River ( Brescia 2002 ; USEPA 2004 b)

.

Overall, the federal government spent more than $ 600 million on major restoration projects in aquatic

ecosystems in FY2012 ( Behrens 2012 ; USACE 2013 )

. These projects include, but are not limited to, the

construction of fish ladders, restoration of wetland nursery habitat, and the reduction of pollution. These

e xpenditures indicate a high value placed on the maintenance and restoration of ecosystem function and

the integrity of freshwater ecosystems.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 6 

### 8.2.4 Summary of Evidence for Nonuse Values of Ecosystems Affected by CWIS

Overall, the public appears to hold substant ial nonuse values for ecosystems and species impacted by

CWIS. For example, governments at various levels have committed to the designation of MPAs covering

large areas. Governments also have committed substantial resources to the restoration of degraded a quatic

ecosystems.

EPA notes that funding amounts for the protection and restoration of aquatic ecosystems is not an

appropriate measure of benefits (i.e., willingness to pay (WTP)). As described by Brown ( 1993 )

“e conomic efficiency involves a balance between demand and supply, whereas restoration cost has

not hing to do with demand or value ” (p.88). Moreover, these costs do not necessarily reflect a cost

effective allocation of resources ( Kopp and Smith 1993 ) . High costs of restoration or protection may

overstate benefits, and likewise, while low costs may under

- state benefits.

Although not estimates of benefits of improving aquatic ecosystems, these expendi tures are still an

indication of significant social values for the protection and resource of aquatic resources affected under

the final rule and options considered. Chapter 2 provides additional qualitative discussion of adverse

environmental impacts from regulated facilities for which society is like to hold significant nonuse values.



## 8.3 Benefit Transfer for Nonuse Values in the North Atlantic and Mid

- Atlantic

Regions

Stated preference (SP) methods and benefit transfers based on SP studies are the generally accepted

techniques for estimating total social values (including use and nonuse) values. SP methods rely on

surveys that ask people to state their WTP for particular ecological improvements, such as increased

protection of aquatic species or habitats wit h particular attributes. EPA searched the literature for SP

studies that estimated WTP for ecological improvements similar to those impacted by CWIS of regulated

facilities. EPA identified a SP survey of Rhode Island resid ents that is a relatively good mat ch to the

316(b) policy context and used this study to develop a benefit transfer approach to estimate nonuse

benefits associated with reduction in IM&E under the final rule and other options considered. EPA was

only able to use this approach for the Nort h Atlantic and Mid

- Atlantic regions.

The study developed a Bioindicator

- Based Stated Preference Valuation (BSPV) method specifically for

applications to ecological systems, 37 

### and used it to address Rhode Island residents’ preferences for the

restoration of migratory fish passage over dams in a watershed within Rhode Island ( Johnston et al.

2012 ) . The study results have been published in multiple scientific journals and books including Johnston

et al. ( 2012 ) , Johnston et al. ( 2011a ) , Johnston et al. ( 2011b ) , and Zhao et al. (2013 ) . EPA app lied a model

presented by Zhao et al. (2013 )

.

Similar to the 316(b) regulatory context, the study addressed policy changes affecting individuals of

forage species but for which ultimate population effects are unknown. The authors estimated total values

by asking respondents to consider changes in ecological indicators reflecting quantity of habitat,

abundance of wildlife, ecological condition, and abundance of migratory fish species. The study’s choice

experim ent allows direct estimation of households’ WTP for policies that increase the number of fish in

watersheds. The benefits transfer involves a translation from reintroducing fish to aquatic habitats to

reducing IM&E. Within the benefit transfer application, EPA is able to focus on nonuse values by holding

constant all effects related to identifiable human uses.

37 The stated preference survey was funded by the EPA’s Science to Achieve Results (STAR) competitive grant program.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 7 

### Section 8.3.1 d escribes the transfer study and BSPV methods in greater detail. This is followed by a

description of EPA’s benefit transfer methods (S ection 8.3.2 ) and estimated benefits for the 316(b) final

rule and other options considered in Section 8.4 . EPA also developed an original SP survey to assess

public values for reductions in IM&E and ecosystem improvements under the final rule. The 316(b) SP

survey is discussed separately in Chapter 11. However, EPA notes that it would be inappropriate to add

the benefits from the benefits transfer approach to benefits based on the SP survey, as this would result in

double

- counting of benefits.

8.3.1 Description of the Benefit Transfer Study and BSPV Methods

As described by Johnston et al. ( 2012 ) , the Rhode Island study developed the BSPV method to promote

ecological clarity, and closer integration of ecological and economic information within SP studies. The

study focus on improved ecological valuation is an EPA priority as described in findings of EPA’s

Science Advisory Board’s Committee on Valuing the Protection of Ecological System and Services

( USEPA 2009 b) . In contrast to traditional SP valuation, BSPV employs a more structured and formal use

of ecological indicators to characterize and communicate welfare

- relevant changes. The method begins

wit h a formal basis in ecological science, and extends to relationships between attributes in respondents’

preference functions and those used to characterize policy outcomes.

Specific BSPV guidelines ensure that survey scenarios and resulting welfare estima tes are characterized

by (1) a formal basis in established and measurable ecological indicators, (2) a clear structure linking

these indicators to attributes influencing individuals’ well

- being, (3) consistent and meaningful

interpretation of ecological in formation, and (4) a consequent ability to link welfare measures to

measurable and unambiguous policy outcomes. The welfare measures provided by the BSPV method can

be linked unambiguously to models and indicators of ecosystem function, are based on measur able

ecological outcomes, and are more easily incorporated into benefit

- cost analysis than traditional SP

valuation studies. The BSPV method also provides a means to estimate values for ecological outcomes

that individuals might value, even though they may not fully understand all relevant ecological science.

The study developed the BSPV methods for a case study addressing public preferences for the restoration

of migratory fish passage in the Pawtuxet Watershed. The BSPV survey ( Rhode Island River: Migrato ry

Fishes and Dams ) was designed to estimate WTP of Rhode Island residents for options that would

provide fish passage over dams, and access to between 225 and 900 acres of historical habitat within the

Pawtuxet Watershed for which there is currently no fi sh passage ( Johnston e t al. 2011a ; Johnston et al.

2011b ; Johnston et al. 2012 ; Zhao et al. 2013 ) . The watershed currently provides no spawning habitat for

migratory fish; access to all 4,347 acres of potential habitat is blocked by 22 dams and other obstructions

( Erkan 2002 )

.

The survey was developed and tested over 21⁄2 years through a collaborative process involving

interactions of economists and ecologists; meetings with resource managers, natural scientists, and

stakeholder groups. This included 12 focus groups with 105 total participants. In addition to survey

development and testing in focus groups, individual interviews were conducted with both ecological

experts and non

- experts. Tests included cognitive interviews ( Kaplowitz et al. 2004 ) , verbal protocols

( Schkade and Payne 1994 ) , and other pretests in order to gain additional insight into respondents’

understanding and interpretation of the survey. Careful attention to development and testing helped ensure

that the survey language and for mat would be easily understood by respondents, that respondents would

have similar interpretations of survey terminology and scenarios, and that the survey scenarios captured

restoration outcomes viewed as relevant and realistic by both respondents and nat ural scientists. In allBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 8 

### cases, the authors paid particular attention to the use and interpretation of ecological indicators and related

information in the survey.

The choice scenarios and restoration options presented within the survey were informed in par t by data

and restoration priorities in the Strategic Plan for the Restoration of Anadromous Fishes to Rhode Island

Coastal Streams ( Erkan 2002 ) . The study authors drew additional information from the ecological

literature on fish passage restoration, intervie ws with ecologists and policy experts, and other sources

described below. Consistent with the strategic plan, the choice experiment within the survey addressed

restoration methods that neither require dam removal nor would cause appreciable changes in rive r flows;

considered options included fish ladders, bypass channels, and fish lifts. The choice experiment addresses

forage species such as alewife and blueback herring that are neither subject to current recreational or

commercial harvest in Rhode Island n or are charismatic species. Hence, the species affected are a close

analog to the forage fish affected in the 316(b) policy context. Moreover, the study’s policy context

involves changes to technologies used within in

- water structures (i.e., the use of fi sh ladders or fish lifts at

dams), providing another parallel to the 316(b) context, which also involves the use of new technologies

within in

- water structures to mitigate harm to aquatic organisms.

The choice experiment asked respondents to consider alter native options for the restoration of migratory

fish passage in the Pawtuxet Watershed. Respondents were provided with two multi

- attribute restoration

options, “Restoration Project A” and “Restoration Project B,” as well as a status quo option that would

r esult in no policy change and zero household cost. An example of a choice question is presented in

Figure 8

- 2 . Prior to administration of the choice experiment questions, the survey provided information

that: (1) described the current status of Rhode Islan d river ecology and migratory fish compared to

historical baselines, (2) characterized affected ecological systems and linkages, (3) described the methods

and details of fish passage restoration, and (4) provided the definitions, derivations, and interpret ations of

ecological indicators used in the survey scenarios, including the reason for their inclusion. All survey

language and graphics were pretested carefully to ensure respondent comprehension.

Within each choice experiment question, the restoration op tions are characterized by seven attributes,

including five ecological indicators, one attribute characterizing public access, and one attribute

characterizing unavoidable household cost. The study fielded multiple versions of the survey, including

variati ons in the definition or set of included ecological indicators. The versions differ in the metric used

to characterize the impacts of restoration on migratory fish.

The first uses a Population Viability Analysis ( PVA ) score that indicates “the probability (in percentage

terms) that migratory species will still migrate the river in 50 years, as calculated by scientists” (Zhao et

al. 2013, p.10). The second, uses a migratory fish score, migrants , that indicates “the expected number of

adults fish that will s wim upstream each year”, “[p]resented as a percentage of the reference values for the

watershed” (Zhao e l. 2013, p.10). Respondents were either sent the PVA or migrants version. The other

four ecological indicators presented include (1) the quantity of ri ver habitat accessible to migratory fishes

( acres ), (2) the abundance of fish suitable for recreational harvest ( catch ), (4) the abundance of fish

dependent wildlife ( wildlife ), and (4) overall ecological condition measured by an index of biotic integrity

score ( IBI ). EPA used a model variant published by Zhao et al. (2013) which was estimated based on

combined responses to both survey versions ( PVA and migrants ). The model specification allows EPA to

isolate WTP for migrants , which provides a good match to the policy variable (i.e., the number of fish

saved).

EPA estimated the number of fish saved under the final rule and other options considered using the

methods described in Chapter 3. Although the PVA score is likely to be affected by the number of fishBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 9 

### saved, estimating expected changes in population viability in the 316(b) context is not feasible due to the

lack of data allowing EPA to relate changes in individual species losses to populations, which is

particularly the case for forage species.

8.3.2 Benefit Transfer Methodology

The following subsections describe EPA’s benefit transfer methods using the BSPV study. Section 8.3.2.1

describes the estimation of WTP for a percentage increase in fish numbers and Section 8.3.2.2 describes

the application of BSPV WTP values to IM&E reductions under the final rule and other options

considered.

8.3.2.1 Estimating WTP for a Percentage Increase in Fish Numbers



### Figure 8

- 2 is a sample choice experiment question from the migrants version of the study as presented in

Zhao et al. (2013). 38 

### The five ecological attributes ( migrants

, acres

, catch

, wildlife , and IBI ) are expressed

as a percentage relative to upper and lower reference conditions (i.e., best and worst possible in the

Pawtuxet) as defined in the survey information. Relative scores represent percent progress towards the

upper reference condition (100 percent), starting from the lower reference condition (0 percent). This

implies bou nds on the potential attribute levels that might occur in the choice questions, following

guidance in the literature to provide visible choice sets ( Bateman et al. 2004 )

. Because the survey used

lower and upper bounds on a percentage point scale, it can be used for benefits transfer if IM&E

reductions can be translated to the same scale. Hence, EPA based its benefit transfer on estimated WTP

per percentage increase in fish numbers ( migrants , “migratory fish” in Figure 8

- 2 ) relative to reference

conditions.

EPA notes that the choice experiment question in the survey instrument also presented the increased

num ber of fish and the total possible increase in the number of fish (the upper reference condition)

directly below the percent improvement in migratory fish,. The number of fish affected by the existing

facilities rule is many times larger than the number of fish corresponding to the maximum reference

condition within the survey materials, because the Rhode Island survey covers a single watershed, rather

than a large region. Because of this difference in scale, directly apply ing values per fish from the study to

the 316(b) fish reduction estimates would likely overstate benefits of the final rule. Basing the benefit

transfer on percentage improvement ameliorates this difference in scale, at least partially, because

improvements are bounded by the 100 percent u pper reference condition in all cases. The remainder of

this section describes EPA’s approach for using the implicit price, or WTP per percentage improvement,

in migratory fish based on the Rhode Island study. Additional discussion of scale of fisheries

im provements and the affected population is provided in Section 8.6

.

38 In the PVA versio n, the “migratory fish” (i.e., migrant s) attribute is replaced with the PVA attribute.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 10 

### Figure 8

- 2: Example Choice Experiment Question from the Zhao et al. ( 201 3 ) S tudy including the

Migratory Fish ScoreBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 11 

### Zhao et al. (2013) estimated a random utility model using simulated likelihood mixed logit accounting fo r

correlations in choices from the same respondent. 39 

### Zhao et al. (2013) specified coefficients on all non

cost attributes, except catch, as random with a normal distribution within the mixed logit model. The

study specified the coefficient on annual househ old cost ( cost ) with sign

- reversed as random with a

bounded triangular distribution. This cost specification ensures positive marginal utility of income. The

likelihood simulations use Halton draws, or “intelligent draws”, from the parameter distributions during

model estimation. Halton draws are “generated number theoretically rather than randomly and so

successive points at any stage ‘know’ how to fill in the gaps left by earlier points” ( Bhat 2001, p. 684 )

. This can improve model estimation compared to using purely random draws.

Table 8

- 3 presents the Zhao et al. (2013) unrestricted mixed logit model. The mod el was estimated based

on both the PVA and migrants choice experiments i ncluding multiplicative interactions between each

non

- cost attribute and d_mig , a dummy variable identifying observations from the migrants choice

experiment. 40 

### The model is significant at p<0.0001 with a pseudo

- R 2 

### of 0.31. The coefficients of all

environme ntal attributes, expect catch , are significant at p<0.01. The interactions allow for coefficient

estimates to vary systematically between the PVA and migrants choice experiments. Using this

specification, the marginal utility of non

- cost attribute k is giv en by (

̂ ̂ ) for the migrants

choice experiment.

39 Mixed logit is an approach for modeling discrete choices subject to preference heterogeneity, based on the assumption that

individual’s preferences are randomly distr ibuted and that heterogeneity in population preferences can be captured by

estimating the mean and variance of the random parameter distributions ( Holmes & Adamowicz 2003 ) . As described by

Hensher and Greene ( 2003, p. 170 ) , “the mixed logit model offers an extended framework within which to capture a greater

amount of behavioral choice making. Broadly speaking, the mixed logit model aligns itself much more with reality than

most discrete choice models with every individual having their own inter

- related syst ematic and random components for

each alternative in their perceptual choice set(s).”

40 Zhao et al. (2013) present an additional pooled model without interactions. That model is not presented here because it does

allow for the isolation of WTP for changes in migrants and thus not well suited for benefits transfer to the 316(b) context.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 12 

### Table 8

- 3 : Results of the Unrestricted Model from Zhao et al. (2013)

Variable Coefficient Standard Error

Random P arameters

a cres 0.0463*** 0.0117

f ish ( PVA and migrants pooled) 0.0169*** 0.0043

IBI 0.0497*** 0.0168

a ccess 1.1577*** 0.2056

w ildlife 0.0267*** 0.0083

n either

- 4.2235*** 0.4522

c ost (bounded triangular, sign reversed) 0.0533*** 0.0058

Non

- random Parameters

c atch 0.0011 0.0082

a cres × d_mig 0.0010 0.0161

fish × d_mig 0.0093 0.0087

IBI × d_mig

- 0.0345 0.0229

a ccess × d_mig 0.2170 0.2643

w ildlife × d_mig

- 0.0038 0.0113

n either × d_mig

- 0.1865 0.8233

c atch × d_mig

- 0.0052 0.0114

Random Parameter Distributions

std. dev. acres 0.0679*** 0.0216

std. dev. fish 0.0154 0.0115

std. dev. IBI 0.0816*** 0.0294

std. dev. access 1.5873*** 0.2544

std. dev. wildlife 0.0174 0.0257

std. dev. neither 4.8330*** 0.7627

spread cost (bounded triangular) 0.0533*** 0.0058

Model Statistics

- 2 Log likelihood χ 1,127.26***

-

Pseudo

- R 2 0.31

-

Observations (N

) 1,634

-

Notes:

***, **, * indicates significance at 1%, 5%, 10% levels, respectively.

Parameter Descriptions:

acres

– The number of acres of river habitat accessible to migratory fish.

fish

– Variable that pools observations on PVA and migrants across the two choice experiments.

PVA

– Population viability analysis (PVA) score. This was described to respondents as “the probability (in percentage terms)

that migratory species will still migrate the river in 50 years, as calculated by scientists.”

migrants

- The percentage point increase in the number of migratory fish able to reach watershed habitat.

catch

– The number of catchable

- size fish in restored areas.

wildlife

– Number of fish

- eating wildlife species that are common in restored areas.

IBI

– Index of biotic integrity (IBI) score reflecting the similarity of the restored area to the most undisturbed watershed in

Rhode Island.

access

– Indicates whether the restored area is accessible to the public for walking and fishing.

cost

– The household annual cost required to implement the restoration program.

neither

– Alternative specific constant (ASC) assoc iated with the status quo, or a choice of neither plan.

d

- mig

– Binary (dummy) variable identifying observations from the choice experiment including migrants to represent effects

on migratory fish.

Sources: U.S. EPA Analysis for this report, Zha o et al. ( 2013)



### Implicit prices for each attribute are calculated based on the ratio of marginal utility and cost as (

̂ ̂ )

̂

⁄ . Because the betas are random for some attributes, simulations are used to

estimate WTP per percentage improv ement for each of the environmental attributes. Zhao et al. (2013)

estimated WTP using the welfare simulation approach of Johnston and Duke ( 2007 ) following HensherBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 13 

### and Greene ( 2003 ) . “The procedure begins with a parameter simulation following the parametric

bootstrap of Krinsky and Robb ( 1986 ) , with R =10 00 random draws taken from the mean parameter vector

and associated covariance matrix. For each draw, the resulting parameters are used to characterize

asymptotically normal empirical densities for fixed and random coefficients. For each of these R draws, a

coefficient simulation is then conducted for each random coefficient, with S =1000 draws taken from

simulated empirical densities (either normal or bounded triangular, depending on the distribution for each

coefficient). Welfare measures are calculated fo r each draw, resulting in a combined empirical

distribution of R × S observations from which summary statistics are derived” (Zhao et al. 2013, p.17

- 18).

The resulting empirical distributions accommodate both the sampling variance of parameter estimates and

the estimated distribution of random parameters.

The welfare simulation approach provides a mean WTP estimate of $0.69 per percentage point increase in

migratory fish in 2008$ ( (

̂ ̂ )

̂ ⁄ )

, and $0.72 when adjusted to 2011 $. 41 

### Results

for total household WTP for a series of percentage improvements in fish numbers are shown below in

Table 8

- 4 . A zero percent improvement would mean no additional fish and 100 percent represents the

maximum possible number of fish that may be s upported by the ecosystem. 42 

### These percentage

improvements do not represent population increases; rather, they reflect new fish within a specific habitat

area that may be counted. In context of the 316(b) benefit transfer, the new fish are A1E saved under

r egulatory options.

EPA transferred the estimate of $0.72 per percentage improvement to estimate nonuse benefits of 316(b)

regulatory options as described in the next section. The model makes it possible to distinguish benefits

associated with resource use s from those associated primarily with nonuse motives. Because EPA used

the implicit price for migratory fish changes for the benefit transfer application, WTP is estimated for

increases in non

- harvested fish alone. The transfer holds constant all effects related to identifiable human

uses (e.g., effects on catchable fish, public access, observable wildlife, etc.). The remaining welfare

effects

— derived purely from effects on fish with little or no direct human use

— may therefore be most

accurately characteri zed as a nonuse benefit realized by households for the protection of all fish (

including forage fish).

Table 8

- 4 : WTP per Percentage Increase in the Number of Fish (2011$)

Percentage Point Increase

in Number of Fish WTP per % Increase in the

Number of Fish Total WTP per Household

1 $0.72 $0.72

12 $ 0.72 $1.44

20 $0.72 $14.41

33 $0.72 $23.78

100 $0.72 $72.06

Source: U.S. EPA analysis for this report

41 Within the Pawtuxet Watershed study area (the original study location), each percentage point increase in is equivalent to

12,250 individual fish migrating upstream.

42 E PA converted the implicit price from 2008$ to 2011$ using the consumer price index.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 14 

### 8.3.2.2 Estimating Total WTP for Eliminating or Reducing IM&E



### The BSPV study was developed as a case study for a watershed

- level policy in Rhode Island. While it

provides parameterized benefit functions that require the fewest assumptions to implement for

extrapolation to the 316(b) case, estimates are more likely to be representative of nonuse values held by

individuals residing in the Northeast United States. EPA expects that it would provide less accurate

estimates of nonuse values for residents of other U.S. regions outside the Northeast. EPA was un able to

identify existing valuation studies conducted in other regions that would provide benefit functions of

comparable quality and applicability to the 316(b) regulatory context. Although other studies in the

literature value changes in aquatic resource s, they do not provide a good match to the 316(b) policy

scenario in terms of the expected resource change. The large number of assumptions required for

developing benefit transfer based on these studies would result in greater uncertainties compared to

ap plication of the BSPV study. Therefore, EPA restricted the benefit transfer to the North Atlantic and

Mid

- Atlantic EPA 316(b) study regions.

The structure of the transfer study dictates that WTP should be evaluated based on the single species that

would ex perience the greatest relative increase in abundance from restoration and that WTP estimates

from multiple species impacted by IM&E should not be treated as strictly additive. This is related to the

issue of independent valuation and summation. Species lik ely act as substitutes in people’s utility. That is,

if one species population has increased, WTP to increase a second species may be lower if the species are

viewed as substitutes. If one values a set of species independently through separate application of the

valuation function, then the individual species estimates do not account for substitution among the species

in people’s preferences and their summation could lead to misleading results. Johnston et al. (2002a)

discusses this issue in the context of environmental management and states that “If interactions among

multiple elements of environmental management programs exist, the use of survey methods such as

contingent valuation to value single dimensions of these programs in isolation (i.e., relative t o the same

‘initial state of the world’) may provide misleading results” (p. 4

- 1).

To match the original valuation scenario to the 316(b) policy scenario, EPA selected the single species in

the Northeast United States that is most impacted among those spe cies with sufficient stock information

to conduct the analysis. The selected species is most likely to be a commercially or recreationally

harvested species because of the availability of stock information. However, as discussed in the previous

section, EP A is able to focus on nonuse values by using migrants attribute for the benefit transfer. The

total baseline IM&E in the North

- Atlantic and Mid

- Atlantic regions were evaluated together to represent

the Northeast United States. for consistency with the avai lable stock assessments, which include waters

from Maine to North Carolina. EPA selected winter flounder 43 

### as the species for the benefit transfer after

considering multiple criteria:

 Stock Assessment Data

– EPA defines biomass at maximum sustainable yield (B MSY 

### ) as the

baseline when estimating the percentage increase in fish abundance under the 316(b) regulatory

options. An estimate of B MSY 

### must be available from a recent stock assessment. B MSY 

### was

available for winter flounder from a recent stock assessmen t.

 Current Stock Size

– Current biomass of the stock must be less than B MSY ; 

### otherwise, a percent

improvement is not calculable. For example, striped bass and croaker stocks exceed B MSY 

### and

were removed based on this criterion. The current biomass of winte r flounder is less than B MSY



### .

43 Winter flounder are harvested commercially; however fish of commercial species may be forage during early life

- stages and

have nonuse values.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 15 

###  Magnitude of IM&E

– EPA selected the species with the highest relative magnitude of baseline

IM&E on a percentage basis when compared to total age

- one fish in the stock and B MSY 

### . Baseline

IM&E for winter flounder (6.2 million) is high when compared total age

- one fish in the winter

flounder stock and B MSY



### . 44 

### Various other species, such as butterfish and bluefish, suffer much

lower baseline IM&E.

Winter flounder is the only species for which EPA conducts the benefits transfer, du e to stock data

availability and the aforementioned issues related independent valuation, summation, and substitution.

EPA notes that baseline IM&E of winter flounder represents less than one percent of total baseline

IM&E. It is difficult to ascertain the upper bound of nonuse benefits if the transfer were able to account

for multiple species.

EPA expects that decreasing IM&E will lead to increased fish abundance in affected waterbodies. EPA

assumed that the total number of fish introduced to local habita ts throughout the Northeast under the final

rule and regulatory options considered would be equivalent to the sum of A1E reductions for the North

Atlantic and Mid

- Atlantic regions. Application of the BSPV model results requires that the increases be

expr essed as a percentage increase over current conditions relative to a maximum number of fish that

could be supported by the ecosystem. For the benefit transfer, EPA measured IM&E on a normalized

yardstick based on fishery managed to the maximum sustainable yield. This measure should not be

interpreted as a population impact.

To calculate improvements under the final rule and regulatory options considered, EPA compared the

reduction in A1E lost to IM&E to an estimate of the number of age

- 1 fish in the winte r flounder

population at B MSY



### . Available fish stock assessments of winter flounder did not estimate the number of

eggs or larvae in the population; instead, the youngest fish modeled were of age 1. Additionally, EPA

used the number of age

- 1 fish in the pop ulation as the basis for comparison in recognition of the fact that

winter flounder adults migrate seasonally from estuaries to offshore shelf areas. Accordingly, adults are

less likely to suffer IM&E than young fish. The most recent stock assessment for t he Southern New

England winter flounder conducted by the Northeast Fisheries Science Center ( NEFSC 2011 ) indicates

that spawning stock biomass (SSB MSY 45 

### ) at maximum sustainable yield is 43, 661 metric tons. EPA

calculated the approximate number of age

- 1 fish per metric ton of spawning stock biomass to be 2,624

using age

- class data for 2005 ( NEFSC 2008 )

. 46 

### EPA multiplied the current SSB MSY 

### of 43,661 metric tons

by 2,624 to generate an estimate a maximum of 114. 6 million age

- one fish at maximum sustainable

yield. 47

44 EPA used the estimated n umber of age

- one fish in the Southern New England winter flounder stock from Terceiro ( 2008 )

. The most recent stock assessment, released in 2011 ( NEFSC 2011 ) , did not provide an estimate of the number of age

- one

fish.

45 SSB MSY i s the standard measure of biomass used by fisheries biologists to set fishing quotas. It includes only fish capable of

reproduction: for winter flounder, this includes fish age 3 or greater. Accordingly, winter flounder SSB MSY will always be

lower than B MS Y because it excludes fish younger than age 3.

46 This is based on 8.8 million age

- one fish for 3,368 metric tons of spawning stock biomass.

47 EPA analysis used data for the Southeast New England winter flounder stock. The Gulf of Maine (GOM) winter flounder

stock is also within the North Atlantic region, however, estimates of B MSY for the GOM stock are highly variable and a

consensus estimate is not provided by NMFC. The effect on es timated benefits is relatively minor because the range of B MSY

indic ates that the stock would be relatively small (around 10 percent) compared to the Southern New England stock at

maximum sustainable yield.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 16 

### EPA’s calculation of nonuse values from eliminating or reducing IM&E for each regulatory option

involved the following steps:

1. Calculate the percent increase of winter flounder relative to total age

- 1 winter flounder at

maximum sustainable yield in the Northeast U.S. (the North Atlantic and Mid

- Atlantic regions

combined) by comparing A1E reductions under each regulatory option relative to a baseline of

114.6 million fish.

2. Multiply the percentage point c hange by the household WTP of $0.72 per percentage point

improvement ( Table 8

- 4 ) to calculate the WTP per household per year for the relative increase in

winter flounder resulting from the regulatory option.

3. Calculate annual regional WTP for each regulator y option by multiplying WTP per household per

year by the total number of households within the North Atlantic and Mid

- Atlantic regions,

respectively.

The results from implementing these steps for the final rule and the other options considered are describ ed

in Section 8.4 . Discussion of geographic scale and other uncertainties are provided in Section 8.6

.



## 8.4 Benefit Transfer Results for the Final Rule and Options Considered

Table 8

- 5 summarizes EPA’s estimates of WTP for increased fish numbers resulting from the 316(b) final

rule and options considered in the North Atlantic and Mid

- Atlantic regions. EPA estimated that

elimination of all baseline IM&E would increase the number of winter flounder in the Northeast United

States by more than 6.2 million fish. This is equivalent to a 5.4 percentage point increase relative to a

maximum of 114.6 million fish (i.e., 6.2 million divided by 114.6 million). Multiplying the 5.4 percent

increase by a value of $0.72 per percentage point increase (as presented in Table 8

- 4 ) yields a household

WTP of $3.92 per year. Applying the household WTP values to the number of households in each region

results in annualized WTP values of $ 20.2 million and $ 78.9 million for the North Atlantic and Mid

Atlantic regions, respectively, using a discount rate of 3 percent. Annualized WTP values are $ 19.8

million for the North Atlantic and $ 77.2 million for the Mid

- Atlantic using a discount rate of 7 percent.

These numbers represent the nonuse value of eliminating all baseline losses of IM&E based on the benefit

transfer using the BSPV study. These are thus the maximum possible nonuse values based on this benefits

transfer covering these two regions.

EPA estimated that the final rule will increase winter flounder numbers by 0.07 percent in the North

Atlantic and Mid

- Atlantic waters. Applying per household WTP to this percent increase in the number of

winter flounder ($ 0.05 ) and to the number of households in each region yields the tot al WTP for

improvements in winter flounder abundance. The estimated annualized WTP for the final rule in the

North Atlantic region will be about $0. 2 million using both 3 percent and 7 percent discount rates. For the

Mid

- Atlantic, annualized WTP will be $0

. 8 million using a 3 percent discount rate and $0. 7 million using

a 7 percent discount rate. Table 8

- 5 also presents household WTP and annualized WTP for Proposal

Option 4 and Proposal Option 2.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 17



### Table 8

- 5 : Nonuse Value of Eliminating or Reducing Baseline IM&E for the Final

Rule and Options Considered for Regulated Facilities in the North Atlantic and

Mid

- Atlantic Regions

Step Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline

Reduction in Northeast IM &E (millions of A1E) 0.03 0.08 4.78 6.23

Percentage increase in age

- 1 fish in Northeast waters

relative to age

- 1 stock at MSY 0.02% 0.07% 4.18% 5.44%

Household WTP per Household (2011$) $0.02 $0.05 $3.01 $3.92

North Atlantic a

Annual WTP (millions of 2011$) $0.09 $0.28 $16.35 $21.29

Annualized WTP (3% discount rate; millions of

2011$) $0.06 $0.21 $10.43 $20.21

Annualized WTP (7% discount rate; millions of

2011$) $0.05 $0.17 $7.61 $19.77

Mid

- Atlantic b

Annual WTP (millions of 2011$) $0.34 $1.09 $63.80 $83.10

Annualized WTP (3% discount rate; millions of

2011$) $0.25 $0.81 $40.70 $78.89

Annualized WTP (7% discount rate; millions of

2011$) $0.20 $0.65 $29.69 $77.17

Total Northeast (North Atlantic plus Mid

- Atlantic)

Annual WTP (millions of 2011$) $0.42 $1.37 $80.14 $104.39

Annualized WTP (3% discount rate; millions of

2011$) $0.31 $1.01 $51.13 $99.10

Annualized WTP (7% discount rate; millions of

2011$) $0.25 $0.82 $37.30 $96.95

a Based on 5.41 million households.

b Based on 21.11 million households.

Source: U.S. EPA analysis for this report



## 8.5 Habitat

- Based Methodology for Estimating Nonuse Values for Fish

Production Lost to IM&E

EPA also developed a habitat

- based method for estimating nonuse values for fish lost to IM&E for the

proposed rule ( USEPA 2011 b)

. 48 

### The purpose of the method was to estimate the value of fish losses d ue

to IM&E by approximating the area of habitat required to produce and support the number of organisms

lost to IM&E. Provision of fish habitat and nursery for aquatic species is one of the ecosystem services

provided by wetlands and submerged aquatic vege tation (SAV). Thus, WTP for fish production services

associated with wetlands and SAV can provide an indirect basis for estimating the nonuse values of

increased number of fish. These values may be transferred from available wetlands and SAV valuation

stud ies. 49 

### These studies found that survey respondents were aware of the fish production services

provided by eelgrass (submerged aquatic vegetation, SAV) and wetlands; individuals expressed support

48 EPAfocused on nonuse value of fish production services because use values were estimated using other valuation met hods

described in Chapter 5 through 7.The nonuse values are estimated as the total WTP for fish production services by nonusers

of these resources.

49 Refer to Chapter 9 of the Environmental and Economic Benefits Analysis (EEBA) for the proposed rule for t he list of

valuation studies used in EPA’s analysis (USEPA 2011b).Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 18 

### for programs that include increasing SAV and wetland areas wit h the expressed goal of restoring depleted

fish and shellfish populations (Johnston et al. 2002b; Mazzotta 1996 ; Opaluch et al. 1995 ; 1998 ) . EPA’s

habitat

- based approach involved estimating the area of habitat required to replace fish and shellfish lost to

IM&E and calculating public WTP for the estimated habitat area. When combined, these data yield an

estimate of household values for an increase in fish and shellfish abundance which in turn provides an

indirect estimate of the benefits of reducing or eliminating IM&E.

The habitat

- based benefit transfer approach for the proposed rule involved four general steps:

1. Estimate the area of habitat necessary to produce and support the number of organisms lost to

IM&E.

2. Develop per acre WTP values for fish production services that support fish species affected by

IM&E (i.e., SAV a nd wetlands).

3. Estimate the total nonuse value of baseline IM&E by multiplying WTP values for fish and

shellfish services by the estimated area of habitat required to offset baseline IM&E.

4. Estimate the nonuse benefits of reduced IM&E by multiplying WTP valu es for fish and shellfish

services by the area of habitat required to offset IM&E reduced by regulatory options.

The WTP values used for fish and shellfish habitat services were based on an in

- depth search of the

economic literature to identify valuation s tudies that estimate WTP for aquatic habitat services using

methods which are inclusive of nonuse values (e.g., contingent values, conjoint analysis). EPA used

additional information to isolate the proportion of WTP associated with fish habitat services fr om other

services such as bird habitat and mosquito control. The habitat

- based benefit transfer method estimates

only those values related to IM&E of organisms, not any indirect ecosystem effects of IM&E, or chemical

effects of CWIS (Chapter 2).

For the p roposed rule, EPA estimated national WTP to compensate for baseline IM&E losses under the

habitat

- based approach to be about $3.6 billion and $3.7 billion using 3 percent and 7 percent discount

rates, respectively. For Proposal Option 1, EPA estimated tota l national WTP of $513.3 million using a 3

percent discount rate and $477.2 million using a 7 percent discount rate. National WTP for Proposal

Options 4 and 2 ranged from $509.9 million to $2.1 billion using a 3 percent discount rate and $474.0

million to $1.5 billion using a 7 percent discount rate. Refer to Chapter 9 of the EEBA for the proposed

rule (USEPA 2011b) for additional detail on the habitat

- based benefit transfer method, results for the

proposed regulatory options, and limitations and uncertaint ies associated with the approach.

EPA did not consider the habitat

- based approach appropriate for primary analysis of nonuse benefits and

thus did not include habitat

- based estimates in the total benefits of eliminating or reducing IM&E under

the proposed regulatory options. Likewise, EPA does not re

- estimate the habitat

- based approach for the

final rule or include benefits based on the habitat

- based approach within the comparison of benefits and

costs for the final rule. Since the proposed rule, EPA has r evised its estimates of baseline IM&E, IM&E

reductions under regulatory options, and revised the compliance schedule. However, if EPA were to re

estimate the habitat

- based analysis for the final rule, EPA expects that the results for the final rule would

g enerally be similar to results described above for Proposal Option 1. 50 

### The habitat

- based approach helps

to illustrate the potential magnitude of nonuse values from the final rule, and provides additional support

50 As described in the Chapter 1, the final rule is Option 1 from EPA’s analysis for the proposed rule ( U.S. EPA 2011 ) with

s ome modifications. Proposal Options 4 and Proposal Option 2 correspond to Options 4 and 2 from EPA’s analysis for the

proposed rule ( U.S. EPA 2011 ) with some modifications.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 19 

### for the benefit transfer results presented i n Section 8.4 , and the results of EPA’s SP survey described in

Chapter 10.



## 8.6 Limitations and Uncertainties

By designing a survey instrument directly for the context at hand, EPA could use the stated preference

survey results without the need to transfer ben efits. However, EPA did not complete its stated preference

study in time to have it fully peer reviewed for this analysis. Thus, EPA is relying on this benefits

transfer to estimate, in part, nonuse values.

A number of issues are common to all benefit t ransfers. The technique involves adapting research found

in the available literature and conducted for one purpose, to another purpose

, to address the policy

questions at hand. Some of the limitations and uncertainties associated with i mplementing a benef it

transfer using Johnston et al. ( 2012 ) are ad dressed below. Broader limitations and uncertainties associated

with benefit transfer in general are discussed by Johnston and Rosenberger ( 2010 )

.

8.6.1 Scale of Fishery Improvements

Given the scope of the survey upon which benefit transfer results are based ( Johnston et al. 2012 ; Zhao et

al. 201 3 )

, the most reliable results apply within the range of the attributes presented to the respondents in

the choice experiment . As shown in Figure 8

- 2 , the percentage point increases in the number of fish for

all analyzed 316(b) regulatory options are les s than 33 percent, which is within the range of the fish

migrants attribute changes presented in the survey instrument. ).

8.6.2 Scale and Characteristics of the Affected Population

The results of the Rhode Island study ( Johnston et al. 2012 ; Zhao et al. 2013 ) reflect WTP for

improvements in nearby watersheds. WTP may decline as policy areas become more distant. The most

reliable application of these results would be to calculate WTP for IM&E reductions in a single local

watershed. However, the final rule will reduce IM&E and improve fish populations in multiple

wa tersheds within some states. Although it is not unreasonable that households would hold values for

multiple watersheds, this is a departure from the transfer study context. As noted, EPA assumed that

households have consistent values for improvements in mu ltiple watersheds within their state or region.

Moreover, for transfers based on absolute fish numbers, EPA assumed that the per household WTP for

changes in the numbers of fish for all watersheds located within the state, including watersheds that are

sh ared by multiple States, would be at least equal to the WTP value for improvements in a single

watershed. Hence, EPA estimated per household WTP based on the average watershed improvement

within the state. The transfer study context was a single watershed in Rhode Island ( Johnston et al. 2012 ;

Zhao et al. 2013 )

. Using the benefit transfer approaches outlined here, the benefit function is applied to all

s tates in the North Atlantic and Mid

- Atlantic regions without adjustment, based on mean household

income or local watershed characteristics. Some heterogeneity in WTP would be expected across s tates

and regions due to diversity in species and public values. EPA did not extend the benefit transfer b eyond

the North Atlantic and Mid

- Atlantic regions because of the potential for substantial differences in

preferences , demographics, and species characteristics in other regions compared to the original context

of the transfer study. This likely results in the underestimation of nonuse benefits.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 8: Nonuse Benefit Transfer Approach

May 2014 8

- 20 

### 8.6.3 Fish Population Size, Type and Improvement from the Elimination of IM&E

To c onduct the benefit transfer, EPA assumed that the gain in fish abundance would be equal to IM&E

reductions under the final rule and options considered. These gains are not intended to represent changes

in fish population, but are merely normalized as perce ntages of age

- one fish at maximum sustainable

yield.

While both the transfer study and policy contexts involve forage fish, the specific species compositions

involved differ between transfer study ( Johnston et al. 2012 ; Zhao et al. 2013 ) and the 316(b) context. For

example, most of the fish affected within the transfer study are migratory fish such as river her ring, while

such species may account for a smaller propor tion of those affected by CWIS subject to the final rule. If

WTP is sensitive to the specific type of forage fish involved, this could be a potential source of

generalization error.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 9: Assessment of Social Cost o f Carbon

May 2014 9

- 1 

# 9 Assessment of Soc ial Cost of Carbon

Benefits of regulatory actions include p otential effects from estimated changes in greenhouse gas (GHG)

emissions associated with energy requirements of compliance technology and installation downtime

under the final rule and other optio ns considered. Decreases in GHG emissions, measured as CO 2 

### equivalents, may reduce the burden of global climate change to society in future years, and thus may

create a positive benefit to society, while increases in GHG emissions can impose a negative ben efit, or

cost, to society. EPA refers to the costs from increased emissions as the social cost of carbon (SCC) . EPA

estimated the benefit, or cost, to society from changes in GHG emissions expected to result from the final

rule and other options considered

. EPA based this estimate on the SCC concept, which reflects the cost

(or benefit) to society associated with an incremental change in CO 2 

### - equivalent emissions in a given year.

This chapter presents EPA’s analysis for existing units at Electric Generators and Manufacturers ( Section

9.1 ) . See Chapter 12 for EPA’s analysis for new units

.

EPA estimated the change in CO 2 

### emissions resulting from the energy penalty associated with closed

cycle recirculating system technology, auxiliary energy requirements for op erating compliance

technology, and technology installation downtime f or E lectric G enerators. Energy penalty effects result

from reduced energy conversion efficiency of the power generating system

. EPA estimated the change in

CO 2 

### emissions resulting only fr om the energy penalty and increase in the auxiliary energy requirement f or

M anufacturers. EPA assumed no change in CO 2 

### emissions f or compliance technology installation

downtime at Manufacturers because the short

- term replacement of energy by electric power generating

facilities that would otherwise be produced at M anufacturers could either increase or decrease emissions.

Refer to Appendix I of the Economic Analysis (EA) for the final rule (USEPA 2014a) for additional

detail on compliance technology effects that impose costs via impact on revenue or energy requirements.



## 9.1 Analysis Approach and Data Inputs

9.1.1 Electric Generators

As discussed in Chapter 3 and Appendix I of the EA , EPA expects Electric Generators to temporarily

suspend electricity generation activiti es to install compliance technology, and to incur annual generation

losses due to energy penalty and auxiliary energy requirements. In the case of downtime, other electric

power fac ilities will have to compensate for these generation losses by generating m ore electricity to meet

electricity demand. This may require an increased or decreased energy input, which may lead to increased

or decreased CO 2 

### emissions, depending on the energy input and generation profile of the generating units

used to compensate for the generation losses. In the case of the energy penalty and auxiliary energy

requirements, either the affected Electric Generators or other electric power facilities or both will have to

compensate for these generation losses by generating more electrici ty to meet electricity demand. As

with downtime, this may require an increased or decreased energy input, which may lead to increased or

decreased CO 2 

### emissions..

EPA estimated the potential increase in CO 2 

### emissions , based on results from the electricit y market

analysis using the Integrated Planning Model (IPM ® 

### ). For the existing unit provision of the final rule,

EPA used results for the Electricity Market Analysis

- Final Rule option from the IPM analysis (for

details on that analysis, see Chapter 6 of the EA for the final rule) to estimate changes in CO 2 

### emissions.

As discussed in Chapter 6 of the EA for the final rule , the IPM analysis accounted only partially for theBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 9: Assessment of Social Cost o f Carbon

May 2014 9

- 2 

### new unit provision of the final rule. Consequently, to avoid underestimating the effect on CO 2 

### emissions,

EPA assumed that the IPM

- based CO 2 

### emissions effects of the final rule reflect the existing unit provision

only, and assessed the impact on CO 2 

### emissions from the new unit provision of the final rule in a separate

analysis discussed in Chapter 12. To the extent that changes in CO 2 

### emissions estimated in IPM also

reflect the impact of the new unit provision of the final rule, the estimated reductions in CO 2 

### effe cts and

associated SCC benefit, which are assigned to the existing unit provision of the final rule

, may be unders

estimated.

As described in Chapter 6 of the EA for the final rule, EPA did not conduct a separate electricity market

analysis to assess the r egulatory impacts of Proposal Option 2 as analyzed in support of the final rule.

Instead, the Agency used results from the IPM analysis of Proposal Option 2 (referred to as Market Model

Analysis Option 2 in the context of IPM analysis) conducted in support of the proposed rule . As described

in the Chapter 6 of the Economic and Benefits Analysis (EBA) for the proposed rule, that IPM analysis

used an older IPM platform

– IPM V3.02_EISA. 51 

### For details on that analysis, see the EBA for the

proposed rule.

EPA ca lculated the difference in CO 2 

### emissions reported in the baseline (i.e., pre

- policy ) case and policy

case of the IPM analysis. Because EPA did not analyze Proposal Option 4 in IPM in support of either the

proposed rule or the final rule , EPA could not esti mate CO 2 

### emissions specifically for that option.

However, Proposal Option 4 is similar to the existing unit provision of the final rule in that both set

performance standards based on IM technology . Moreover, compliance costs for Proposal Option 4 are

slightly lower than those of the existing unit provision of the final rule (see Chapter 3 of the EA for the

final rule ). Therefore, the change in CO 2 

### emissions for Proposal Option 4 is likely to be no larger than the

emission changes calculated for the Electricity Market Analysis

– Final Rule

.

To estimate the change in CO 2 

### emissions for the 46

- year analysis period of 2014 through 2059, EPA first

calculated the change in CO 2 

### emissions from baseline to policy option, as estimated in the IPM electricity

m arket analyses. As described in Chapter 6 of the EA for the final rule , the IPM V4.10_MATS platform

embeds three run years

– 2015, 2020, and 2030. These run years represent multiple years and specific

technology

- installation years as shown in Table 9

- 1

.

Table 9

- 1 : IPM V4.10_MATS Run

- Year Specification

– Final Rule a,b

Run Year Represented Years Regulatory Effects Captured

– Final Rule

2015 2014

- 2016 Operations and financial c hanges i n anticipation of future compliance a

2020 2017

- 2024 IM technology installation

2030 2025

- 2034 Steady

- state post

- compliance period; captures potential permanent

changes.

a As discussed in Appendix P of the EA for the final rule, IPM reflects an assumption of perfect foresight.

b V4.10_MATS is the IPM version that EPA used to analyze the Final Mercury and Air Toxics Standards (MATS).

51 Although Proposa l Option 2 analyzed in support of the final rule set impingement mortality and entrainment performance

standards similar to those analyzed under Market Model Analysis Option 2, the expected compliance responses differ in

terms of technologies that some fac ilities will install and the associated costs. In addition, administrative requirements

considered for Proposal Option 2 differ from those analyzed in IPM for the proposed rule. Also, the current universe of

regulated facilities is slightly smaller than th e universe of regulated facilities analyzed for the proposed rule. Finally,

compared to Market Model Analysis Option 2, Proposal Option 2 provides facilities with more flexibility and a longer

window to comply with the regulatory requirements. EPA judges t hat despite these differences, the electricity market

analysis results from the proposed rule are sufficient to assess the change in CO 2 emissions under Proposal Option 2

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 9: Assessment of Social Cost o f Carbon

May 2014 9

- 3 

### As described in Chapter 6 of the economic and benefits analysis for the proposed rule (USEPA 2011a)

, EPA specified four run years for the IPM analysis in accordance with the compliance

- technology

installation schedule considered at that time: 2015, 2020, 2025 , and 2028

. These run years represent

multiple years and specific technology

- installation years as follows:

Table 9

- 2 : IPM V3.02_EISA Run

- Year Specification

– Proposal Option 2 a

Run Year Represented Years Regulatory Effects Captured

– Proposed Rule

2015 2013

- 2017 IM technology installation

2020 2018

- 2022 Entrainment control technology installation

– non

- nuclear facilities

2025 2023

- 2027 Entrainment control technology installation

– nuclear facilities

2028 2028 Steady

- state post

- compliance period; captures potential permanent

changes.

a V3.02_EISA is the IPM version that EPA used to model electric generation for the proposed Transport Rule.



### EPA assumed that any observed changes in CO 2 

### emissions between the baseline case and the policy case

are attributable to the analyzed 316(b) regulatory requirements. For the final rule, EPA assumed that the

difference in CO 2 

### emissions reported for 2015 is the same as the difference in the other thre e years

represented by 2015, i.e., 2014 through 2016. EPA applied the same methodology to the remaining two

run years, thereby generating the change in CO 2 

### emissions for the 21

- year period of 2014 through 2034. 52



### EPA used the same methodology for Proposal Option 2, generating a time profile of changes in CO 2



### emissions for the 16

- year period of 201 3 through 2028

.

In reviewing the estimated change s in CO 2 

### emissions from the IPM runs, EPA observed that for some

regulatory options and some analysis years, CO 2 

### e missions decline even though EPA would expect the

options to have effects of replacing and/or providing additional electrici ty generation, as described above.

On closer inspection, in these cases, the generation mix between the baseline and the regulatory option

case changes in such a way that a CO 2 

### emissions decrease is plausible

– e.g., increased generation from

nuclear facilities (which are non

- CO 2 

### emitting) and reduced generation from coal or other fossil fuel

facilities.

The run

- year configuration emb edded in the IPM V4.10_MATS platform used for the analysis of the final

rule was set independent of the 316 ( b ) compliance and technology installation schedule . Unlike the case

with the IPM analysis done in support of the proposed rule, EPA did not change t his configuration to

better reflect the final rule requirements. EPA expects all regulated facilities to install compliance

technologies during the 5

- year period of 2018 through 2022, which is within the range of years

represented by the 2020 IPM run year. To align year

- specific changes in CO 2 

### emissions estimated for the

Electricity Market Analysis

- Final Rule as part of the IPM analysis with technology

- installation schedule

of the final rule and consequently, Proposal Option 4, EPA made the following assu mptions:

 As discussed in Chapter 6 of the EA for the final rule, the three years (2014 through 2016)

represented by the 2015 IPM run year, have the same characteristics as the 2015 year. These three

years immediately precede the technology

- installation per iod assumed in the IPM analysis. EPA

assumed that the year

- specific changes in CO 2 

### emissions estimated for Electricity Market

52 Even though no compliance technology is installed during the 3

- year period repr esented by the 2015 IPM run year, any

changes in the market behavior resulting in changes in CO 2 emissions are due to anticipated compliance with the 316(b)

requirements. As discussed in Appendix P of the Final Rule EA report, IPM reflects an assum ption of perfect foresight

, which means that market players have complete knowledge of the nature and timing of the constraints, including those

crea ted by regulatory requirements that will be imposed in future years during the analysis period, and make decisions based

on this knowledge.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 9: Assessment of Social Cost o f Carbon

May 2014 9

- 4 

### Analysis

- Final Rule for 2014 through 2016 are the same as those that will occur during 2015

through 2017, i.e., the 3

- year period immediately preceding the technology

- installation period

anticipated under the final rule.

 Similar to the 2015 IPM run year , the eight years (2017 through 2024) that are represented by the

2020 IPM run year have the same characteristics as the 2020 run year. As a result, in the IPM

analysis, downtime was applied as a single value for each of the eight years. EPA assumed that

the resulting total difference in CO 2 

### emissions for this eight

- year period (CO 2 

### emissions reported

for the 2020 IPM run year t imes eight

– the number of years that the 2020 run year represents) is

the same as the total difference in CO 2 

### emissions that would have resulted if all facilities were to

install IM technologies during the five

- year period, 2018 through 2022, when complia nce

technology will be installed under the final rule. EPA converted the eight

- year total of CO 2 

### emissions change to a yearly value for each of the five years, 2018 and 2022, by simply dividing

the total emissions change over the eight years by five.

 Fina lly, using the same approach as that used for the 2015 IPM run year, EPA assumed that the

year

- specific changes in CO 2 

### emissions estimated for the 2030 IPM run year and consequently,

for each of the 10 years it represents

– 2025 through 2034

– are the same as those that would

occur during the 10

- year period of 2023 through 2032. In other words, the Agency “moved” the

emissions changes in the 10

- year IPM

- analysis period of 2025 through 2034 to the 10

- year period

of 2023

- 2032, the years following expected com pletion of technology installation under the final

rule. The change in CO 2 

### emissions reported for the final rule in 2030 is negative (i.e., CO 2



### emissions in that year decline from the baseline to the policy case ). To avoid understating the

potential effect of regulatory requirements on CO 2 

### emissions

, EPA applied this decrease only to

the 10 years represented by 20 30 and assumed zero change in CO 2 

### emissions during the

remaining years in the social

- cost analysis period, i.e., 2033 through 2059.

The technology

- installation schedules EPA assumed for the IPM analysis in support of the proposed rule

differ from those assumed for Proposal Option 2 analyzed in support of the final rule. As shown in Table

9

- 2 , for the proposed rule, EPA assumed that facilities would install IM technologies during a 5

- year

window of 2013 through 2017. Further, EPA assumed that non

- nuclear and nuclear facilities would install

entrainment control technologies during 2018 through 2022, and 2023 through 2027, respectively. As

discussed ear lier in this chapter, for the existing unit provision of the final rule, these technology

installation periods are 2018 to 2022, 2021 to 2025, and 2026 to 2030, respectively. To align year

- specific

changes in CO 2 

### emissions estimated for Market Model Analys is Option 2 with technology

- installation

schedules EPA assumed for Proposal Option 2 analyzed in support of the final rule, EPA made the

following assumptions:

 Proposal Option 2 and Market Model Analysis Option 2 require both IM and entrainment control

tec hnologies. To capture differences in energy requirements to install and operate these two sets

of technologies, EPA aligned year

- specific changes in CO 2 

### emissions estimated for Mark et

Model Analysis Options 2 with technology

- specific installation schedules currently assumed for

Proposal Option 2. To capture changes in emissions associated with IM technology, EPA

assumed that the year

- specific changes in CO 2 

### emissions estimated for Market Model Analysis

Option 2 during 2013 through 2017 are the same as those that EPA would have estimated for

2018 through 2022. For entrainment

- control technology installation at non

- nuclear facilities, the

Agency assumed that the changes in emissions it estimated for 2018 through 2022 are the same as

those it would have estimat ed for 2021 through 2025. For installation of entrainment controlBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 9: Assessment of Social Cost o f Carbon

May 2014 9

- 5 

### technology at non

- nuclear facilities, the Agency assumed that the changes in emissions estimated

for 2023 through 2027 are the same as those that EPA would have estimated for 2026 through

20 30. Unlike the case of Electricity Market Analysis

- Final Rule, under Market Model Analysis

Option 2, the change in CO 2 

### emissions reported for the steady

- state year (2028) is positive (i.e.,

CO 2 

### emissions in that year increase from the baseline to the post

- policy case ). To avoid

understating the potential effect of regulatory requirements on CO 2 

### emissions

, EPA applied this

increase in emissions over the remaining years in the social

- cost analysis period, i.e., 2031

through 2059

.

To estimate the benefits of changes in CO 2 

### emi ssions due to the existing unit provision of the final rule

and Proposal Option 2, EPA used SCC values from Technical Support Document: Technical Update of

the Social Cost of Carbon for Regulatory Impact Anal ysis

- Under Executive Order 12866 developed by

the United States Government Interagency Working Group on Social Cost of Carbon, 2013 (Interagency

Working Group 2013). The Working Group estimated annual unit SCC values ($ per metric ton) for 2010

through 205 0 ( Table 9

- 3 ). Three of these four sets are based on the average unit SCC values across

models, and socio

- economic and emissions scenarios, for each of three SCC discount rates: 5.0, 3.0, and

2.5 percent. The Work Group developed a fourth set of unit SCC v alues as the 95 th 

### percentile value of the

3 percent discount rate

- based SCC values; these values represent the potential for higher

- than

- expected

impacts from temperature change f a rther out in the tails of the SCC distribution. 53



### Table 9

- 3 : Unit Social Cost of Carbon, 2010

- 2050 ($ per metric ton of CO 2 

### ;

2011$) a

Year Discount Rates

2.5% 3 .0 % 5.0%

Average SCC

Value Average SCC

Value High SCC Value Average SCC

Value

2010 $55.4 2 $ 34.15 $ 94.98 $11.74

2015 $ 0.83 $ 39.48 $116.32 $ 11.74

2020 $ 68.30 $45.89 $ 136.59 $12.81

2025 $ 73.63 $ 50.16 $ 152.60 $14.94

2030 $ 80.04 $55.49 $169.68 $17.07

2035 $ 85.37 $ 59.76 $ 186.75 $20.28

2040 $ 91.77 $ 65.10 $ 203.82 $22.41

2045 $98.18 $70.43 $219.83 $25.61

2050 $ 103.51 $75.77 $ 234.77 $ 27.75

a SCC values were calculated for 2010 through 2050 and vary by year; this table reports SCC values only for

every fifth year.

Sources: Interagency Working Group, 2013; updated to 2011$ for this analysis using the GDP

deflator.



### These unit SCC values represent the present value of the future stream of costs to society from a change

in GHG emissions in a given year, recognizing that the impact of changes in CO 2 

### in the atmosphere

occurs not only in the year in which the emissions ar e generated, but extends over a substantial period

into the future. 54 

### In the 2013 Technical Support Document (TSD) (Interagency Working Group 2013),

53 For more information on the assumptions and methodology used to develop these SCC values see the 2013

TSD(Interagency Working Group 2013) available online at:

http://www.whitehouse.gov/sites/default/files/omb/inforeg/social_cost_of_carbon_for_ria_2013_update.pdf

.

54 The unit SCC values reported in the 2013 TSD and used in the current analysis are global SCC values. The Interagency

Working Group determined that the use of global measures of benefits for greenhouse gas reductions is preferable toBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 9: Assessment of Social Cost o f Carbon

May 2014 9

- 6 

### these values are in 2007 dollars; EPA restated these values in 2011 dollars using the GDP deflator series.

T he SCC values published by the Working Group increase in real economic terms from year to year,

reflecting the increasing marginal cost to society of additional GHG emissions and increasing cumulative

burden of climate change over time. Because the Working Group published unit SCC values only through

2050, EPA extended the unit SCC values from 2050 to 2059, assuming that the annual real rate of change

in the future SCC values remained the same as in the period 2049 to 2050.

EPA calculated the benefits of t he year

- to

- year changes in CO 2 

### emissions as a product of the year

- by

- year

unit SCC values and the estimated year

- by

- year changes in CO 2 

### emissions. The Agency then discounted

the resulting year

- by

- year benefit values, summed the discounted values, and annua lized them using

discounts rate of 3 percent and 7 percent. 55



### 9.1.2 Manufacturers

To estimate the change in CO 2 

### emissions due to compliance for Manufacturers, EPA estimated the

replacement energy required during downtime and as a result of the energy penalty and auxiliary energy

requirements. For downtime, electricity otherwise produced by Manufacturers will instea d be produced

by the electric power industry. Therefore, electricity generation and associated CO 2 

### emissions of

Manufacturers decrease during downtime while generation and emissions from the electric power

industry increase. Depending upon the carbon inten sity of generation by the electric power industry

relative to that of generation by Manufacturers, CO 2 

### emissions may increase or decrease during

downtime. Given this uncertainty, EPA assumed no net change in CO 2 

### emissions during downtime. If the

carbon int ensity of generation for the electric power industry is greater than that for Manufacturers’, this

assumption will underestimate the increase in CO 2 

### emissions, and vice versa.

For a given quantity of energy input 56 

### , energy penalty and auxiliary energy requ irements reduce the

amount of electricity that is available to the facility to meet baseline consumption needs and/or for sale. 57



### EPA assumed that Manufacturers will not be able to increase energy input to offset this loss, with the net

effect that a facili ty will need to purchase more electricity from other electric power generators or will

deliver less electricity for external consumption. EPA assumed that these electricity losses, whether due to

energy penalty or to auxiliary energy requirements, will be replaced by the electric power industry. This

means that the facility’s own CO 2 

### emissions will be unchanged but that CO 2 

### emissions may increase as

other electric power generators make up this loss. EPA calculated the increase in CO 2 

### emissions from the

gene ration of replacement electricity by the power industry based on the average CO 2 

### emissions intensity

for United States.

EPA first calculated the replacement electricity required to offset the electricity loss from energy penalty

and auxiliary energy requi rements, assuming Manufacturers would incur the these effects from 2010

domestic measures. Refer to the 2013 TSD (Interagency Working Group 2013), and the earlier 2010 TSD (Interagency

Working Group 2010) for additional discussion of global v ersus domestic measures.

55 This discounting approach diverge s from the discount rate concepts used to develop the SCC values. However, the 3 percent

and 7 percent discount rates are appropriate given that the alternative year

- by

- year SCC values reflect a range of factors

including not only discount rates, but also different impact/socio

- economic evolution scenarios, modeling

approach/framework, and damage functions.

56 The energy that is consumed to generate electricity.

57 See Appendix I of the EA for detailed discussion of how energy penalty and auxiliary energy requirements affect electric

power generation and the supply of electricity otherwise available for consumption at facilities installing compliance

technology.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 9: Assessment of Social Cost o f Carbon

May 2014 9

- 7 

### through 2059 (see Appendix I of the EA for the final rule). EPA then calculated the CO 2 

### emissions

intensity based on projected total electricity generation ( USDOE 2013b) and associated CO 2 

### emissions

( US DOE 2013a) by year. EIA projects these values only to 2040, so EPA assumed no change in carbon

intensity beyond 2040. EPA multiplied the carbon intensity in each year by the replacement electricity

required in that year to calculate the C O 2 

### emissions due to the energy penalty of Manufacturers. EPA

multiplied the estimated CO 2 

### emission values, by year, by the same unit SCC values as those used for

Electric Generators ( Table 9

- 3 ).



## 9.2 Key Findings for Regulatory Options

9.2.1 Electric Generators

Table 9

- 3 presents the total reduction in CO 2 

### emissions and associated values of SCC in 2013 for Electric

Generators, by option and discount rate. The SCC values reported for Proposal Option 4 are the same as

those repo rted for existing unit provision of t he final rule because EPA assumed that CO 2 

### emissions for

Proposal Option 4 would be the same as those calculated in the IPM analysis for Market Model Analysis

1, which aligns most closely with the existing unit provision of the final rule. To the extent th at Proposal

Option 4 is less stringent than Market Model Analysis 1 or the existing unit provision of the final rule, the

SCC values reported for Proposal Option 4 are overstated.

As reported in Table 9

- 4 , EPA e stimates that the existing unit provision of the final rule (and Proposal

Option 4) will result in a total reduction of 9.6 million tons of CO 2 

### equivalents ( tCO2eq ). As discussed

above, EPA assesses that this reduction is likely the result of changes in generation mix that lead to more

electricity g enerated by facilities with lower carbon emissions or none at all, such as nuclear facilities, a nd

less electricity generated by coal or other fossil fuel facilities. Using the average SCC values calculated at

a 3 percent discount rate, EPA estimates that this reduction in carbon emissions will result in average

annual benefits of $ 12.4 million at the 3 percent discount rate and $ 13.4 million at the 7 percent discount

rate. EPA estimates that under Proposal Option 4, total carbon emissions would increase by 1,471.9

million of tCO2eq. Using the average SCC values calculated at a 3 percent discount rate, EPA estimates

the average annual (negative) benefit associated with this increase in carbon emissions to be

- $ 1,613.6

milli on at the 3 percent discount rate and

- $ 1,197.9 million at the 7 percent discount rate.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 9: Assessment of Social Cost o f Carbon

May 2014 9

- 8 

### Table 9

- 4 : Total Reduction in Carbon Emissions and Associated Benefits Under the Final Rule

and Other Options Considered

– Electric Generators (SCC Values in 2013; 2011$, millions)

Option Total Reduction in

Emissions

(tCO2eq , millions ) Discount Rate for Calculating SCC Unit Values

2.5% 3.0% 5.0%

Average SCC

Value Average SCC

Value High SCC

Value Average SCC

Value

3% Discount Rate for Annualizing Benefits

Proposal Option 4 a 9.6 $18.1 $12.4 $37.7 $3.8

Final Rule

– Existing Units b 9.6 $18.1 $12.4 $37.7 $3.8

Proposal Option 2

- 1,471.9

- $ 2,281.0

- $ 1,613.6

- $ 4,988.0

- $ 536.2

7% Discount Rate for Annualizing Benefits

Proposal Option 4 a 9.6 $19. 6 $13. 4 $ 40.7 $4.1

Final Rule

– Existing Units b 9.6 $19. 6 $13. 4 $ 40.7 $4.1

Proposal Option 2

- 1,471.9

- $ 1,714.4

- $ 1,197.9

- $ 3,693.7

- $ 388.9

a To the extent that EPA used IPM results for Electricity Market Analysis

– Final Rule as a proxy for Proposal Option 4, benefits for Proposal

Option 4 are likely to be over

- stated.

b To the extent that the change in CO 2 emissions estimated for the existing unit provision of the final rule partially accounts for the change in

CO 2 emissions due to the new unit provision of the final rule, benefits reported for the existing unit provision of the final rule may be

overstated.

Source: U.S. EPA analysis for this report



### 9.2.2 Manufacturers

Table 9

- 5 presents the total reduction in CO 2 

### emissions and associated benefit values for Manufacturers

by option. Under the final rule and Proposal Option 4, EPA assessed no reduction in CO 2 

### emissions.

Under Proposal Option 2, EPA calculated an increase of 25.4 million in tCO2eq . Using the average SCC

values calculated at a 3 percent discount rate, EPA estimates the benefits associated with the estimated

increase CO 2 

### - equivalent emissions to b e

- $27.8 million at the 3 percent discount rate and $20.3 million at

the 7 percent discount rate.

Table 9

- 5 : Total Reduction in Carbon Emissions and Associated Benefits Under the Final Rule

and Other Options Considered

– Manufacturers (SCC Values in 2013; $201 1, millions)

Option Total Emissions

(tCO2eq , millions ) Discount Rate for Calculating SCC Unit Values

2.5% 3.0% 5.0%

Average SCC

Value Average SCC

Value High SCC

Value Average SCC

Value

3% Discount Rate for Annualizing Benefits

Proposal Option 4 a 0.0 $0.0 $0.0 $0.0 $0.0

Final Rule

– Existing Units 0.0 $0.0 $0.0 $0.0 $0.0

Proposal Option 2

- 25.4

- $ 39.2

- $ 27.8

- $ 85.8

- $ 9.6

7% Discount Rate for Annualizing Benefits

Proposal Option 4 a 0.0 $0.0 $0.0 $0.0 $0.0

Final Rule

– Existing Units 0.0 $0.0 $0.0 $0.0 $0.0

Proposal Option 2

- 25.4

- $ 29.1

- $ 20.3

- $ 62.7

- $ 6.7

a To the extent that EPA used IPM results for Market Model Analysis 1 as a proxy for Proposal Option 4, benefits for Proposal O ption 4 are

likely to be over

- stated.

Source: U.S. EPA analysis for this report



### Table 9

- 6

, Table 9

- 7 , and Table 9

- 8 present the change in CO 2 

### emissions and associated undiscounted

benefits for existing units for Electric Generators and Manufacturers by year for Proposal Option 4, the

final rule, and Proposal Option 2, respectively.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 9: Assessment of Social Cost o f Carbon

May 2014 9

- 9 

### Table 9

- 6 : Social Cost of Carbon by Year for Electric Generators and Manufacturers

– Proposal Option 4 ($201 1, millions )

Year Emissions

(tCO2eq , millions ) Discount Rate for Calculating SCC Unit Values

2.5% 3.0% 5.0%

Average SCC

Value Average SCC

Value High SCC Value Average SCC

Value

2013 0.0 $0.0 $0.0 $0.0 $0.0

2014 0.0 $0.0 $0.0 $0.0 $0.0

2015 0.2 $13.3 $8.6 $25.5 $2.6

2016 0.2 $13.8 $8.9 $26.2 $2.8

2017 0.2 $14.0 $9.1 $27.1 $2.8

2018 0.0

- $2.8

- $1.9

- $5.6

- $0.6

2019 0.0

- $2.9

- $1.9

- $5.7

- $0.6

2020 0.0

- $3.0

- $2.0

- $5.9

- $0.6

2021 0.0

- $3.0

- $2.0

- $6.1

- $0.6

2022 0.0

- $3.1

- $2.0

- $6.2

- $0.6

2023 0.9 $65.5 $44.0 $134.0 $12.7

2024 0.9 $66.5 $45.0 $137.0 $13.7

2025 0.9 $67.5 $46.0 $139.9 $13.7

2026 0.9 $68.5 $47.0 $142.8 $14.7

2027 0.9 $69.5 $47.9 $145.8 $14.7

2028 0.9 $70.4 $48.9 $148.7 $14.7

2029 0.9 $71.4 $49.9 $151.6 $15.7

2030 0.9 $73.4 $50.9 $155.5 $15.7

2031 0.9 $74.3 $50.9 $158.5 $16.6

2032 0.9 $75.3 $51.8 $161.4 $16.6

2033 0.0 $0.0 $0.0 $0.0 $0.0

2034 0.0 $0.0 $0.0 $0.0 $0.0

2035 0.0 $0.0 $0.0 $0.0 $0.0

2036 0.0 $0.0 $0.0 $0.0 $0.0

2037 0.0 $0.0 $0.0 $0.0 $0.0

2038 0.0 $0.0 $0.0 $0.0 $0.0

2039 0.0 $0.0 $0.0 $0.0 $0.0

2040 0.0 $0.0 $0.0 $0.0 $0.0

2041 0.0 $0.0 $0.0 $0.0 $0.0

2042 0.0 $0.0 $0.0 $0.0 $0.0

2043 0.0 $0.0 $0.0 $0.0 $0.0

2044 0.0 $0.0 $0.0 $0.0 $0.0

2045 0.0 $0.0 $0.0 $0.0 $0.0

2046 0.0 $0.0 $0.0 $0.0 $0.0

2047 0.0 $0.0 $0.0 $0.0 $0.0

2048 0.0 $0.0 $0.0 $0.0 $0.0

2049 0.0 $0.0 $0.0 $0.0 $0.0

2050 0.0 $0.0 $0.0 $0.0 $0.0

2051 0.0 $0.0 $0.0 $0.0 $0.0

2052 0.0 $0.0 $0.0 $0.0 $0.0

2053 0.0 $0.0 $0.0 $0.0 $0.0

2054 0.0 $0.0 $0.0 $0.0 $0.0

2055 0.0 $0.0 $0.0 $0.0 $0.0

2056 0.0 $0.0 $0.0 $0.0 $0.0

2057 0.0 $0.0 $0.0 $0.0 $0.0

2058 0.0 $0.0 $0.0 $0.0 $0.0

2059 0.0 $0.0 $0.0 $0.0 $0.0

2060 0.0 $0.0 $0.0 $0.0 $0.0

2061 0.0 $0.0 $0.0 $0.0 $0.0

2062 0.0 $0.0 $0.0 $0.0 $0.0

2063 0.0 $0.0 $0.0 $0.0 $0.0

2064 0.0 $0.0 $0.0 $0.0 $0.0

Present Value 3%

- $483.1 $330.3 $1,007.6 $101.7

Annualized, 3%

- $18.1 $12.4 $37.7 $3.8

Present Value 7%

- $290.4 $198.0 $603.0 $60.8

Annualized 7%

- $19.6 $13.4 $40.7 $4.1

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 9: Assessment of Social Cost o f Carbon

May 2014 9

- 10 

### Table 9

- 7 : Social Cost of Carbon by Year for Electric Generators and Manufacturers

– Final

Rule

- Existing Units ($201 1, millions )

Year Emissions

(tCO2eq

, millions ) Discount Rate for Calculating SCC Unit Values

2.5% 3.0% 5.0%

Average SCC

Value Average SCC

Value High SCC Value Average SCC

Value

2013 0.0 $0.0 $0.0 $0.0 $0.0

2014 0.0 $0.0 $0.0 $0.0 $0.0

2015 0.2 $13.3 $8.6 $25.5 $2.6

2016 0.2 $13.8 $8.9 $26.2 $2.8

2017 0.2 $14.0 $9.1 $27.1 $2.8

2018 0.0

- $2.8

- $1.9

- $5.6

- $0.6

2019 0.0

- $2.9

- $1.9

- $5.7

- $0.6

2020 0.0

- $3.0

- $2.0

- $5.9

- $0.6

2021 0.0

- $3.0

- $2.0

- $6.1

- $0.6

2022 0.0

- $3.1

- $2.0

- $6.2

- $0.6

2023 0.9 $65.5 $44.0 $134.0 $12.7

2024 0.9 $66.5 $45.0 $137.0 $13.7

2025 0.9 $67.5 $46.0 $139.9 $13.7

2026 0.9 $68.5 $47.0 $142.8 $14.7

2027 0.9 $69.5 $47.9 $145.8 $14.7

2028 0.9 $70.4 $48.9 $148.7 $14.7

2029 0.9 $71.4 $49.9 $151.6 $15.7

2030 0.9 $73.4 $50.9 $155.5 $15.7

2031 0.9 $74.3 $50.9 $158.5 $16.6

2032 0.9 $75.3 $51.8 $161.4 $16.6

2033 0.0 $0.0 $0.0 $0.0 $0.0

2034 0.0 $0.0 $0.0 $0.0 $0.0

2035 0.0 $0.0 $0.0 $0.0 $0.0

2036 0.0 $0.0 $0.0 $0.0 $0.0

2037 0.0 $0.0 $0.0 $0.0 $0.0

2038 0.0 $0.0 $0.0 $0.0 $0.0

2039 0.0 $0.0 $0.0 $0.0 $0.0

2040 0.0 $0.0 $0.0 $0.0 $0.0

2041 0.0 $0.0 $0.0 $0.0 $0.0

2042 0.0 $0.0 $0.0 $0.0 $0.0

2043 0.0 $0.0 $0.0 $0.0 $0.0

2044 0.0 $0.0 $0.0 $0.0 $0.0

2045 0.0 $0.0 $0.0 $0.0 $0.0

2046 0.0 $0.0 $0.0 $0.0 $0.0

2047 0.0 $0.0 $0.0 $0.0 $0.0

2048 0.0 $0.0 $0.0 $0.0 $0.0

2049 0.0 $0.0 $0.0 $0.0 $0.0

2050 0.0 $0.0 $0.0 $0.0 $0.0

2051 0.0 $0.0 $0.0 $0.0 $0.0

2052 0.0 $0.0 $0.0 $0.0 $0.0

2053 0.0 $0.0 $0.0 $0.0 $0.0

2054 0.0 $0.0 $0.0 $0.0 $0.0

2055 0.0 $0.0 $0.0 $0.0 $0.0

2056 0.0 $0.0 $0.0 $0.0 $0.0

2057 0.0 $0.0 $0.0 $0.0 $0.0

2058 0.0 $0.0 $0.0 $0.0 $0.0

2059 0.0 $0.0 $0.0 $0.0 $0.0

2060 0.0 $0.0 $0.0 $0.0 $0.0

2061 0.0 $0.0 $0.0 $0.0 $0.0

2062 0.0 $0.0 $0.0 $0.0 $0.0

2063 0.0 $0.0 $0.0 $0.0 $0.0

2064 0.0 $0.0 $0.0 $0.0 $0.0

Present Value 3%

- $483.1 $330.3 $1,007.6 $101.7

Annualized, 3%

- $18.1 $12.4 $37.7 $3.8

Present Value 7%

- $290.4 $198.0 $603.0 $60.8

Annualized 7%

- $19.6 $13.4 $40.7 $4.1

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 9: Assessment of Social Cost o f Carbon

May 2014 9

- 11 

### Table 9

- 8 : Social Cost of Carbon by Year for Electric Generators and Manufacturers

– Proposal

Option 2 ($201 1, millions )

Year Emissions

(tCO2eq , millions ) Discount Rate for Calculating SCC Unit Values

2.5% 3.0% 5.0%

Average SCC

Value Average SCC

Value High SCC Value Average SCC

Value

2013 0.0 $0.0 $0.0 $0.0 $0.0

2014 0.0 $0.0 $0.0 $0.0 $0.0

2015 0.0 $0.0 $0.0 $0.0 $0.0

2016 0.0 $0.0 $0.0 $0.0 $0.0

2017 0.0 $0.0 $0.0 $0.0 $0.0

2018 3.2 $210.3 $137.9 $413.7 $41.4

2019 3.2 $213.7 $144.8 $427.5 $41.4

2020 3.2 $220.6 $148.2 $441.3 $41.4

2021

- 27.7

- $1,924.4

- $1,273.1

- $3,878.4

- $355.3

2022

- 27.8

- $1,956.4

- $1,304.3

- $3,972.1

- $385.4

2023

- 31.2

- $2,230.3

- $1,497.9

- $4,560.4

- $432.7

2024

- 31.3

- $2,273.4

- $1,537.9

- $4,680.5

- $468.1

2025

- 31.3

- $2,307.6

- $1,571.9

- $4,782.4

- $468.2

2026

- 51.5

- $3,845.3

- $2,636.8

- $8,020.2

- $824.0

2027

- 51.5

- $3,900.1

- $2,691.6

- $8,184.7

- $824.0

2028

- 51.5

- $3,954.9

- $2,746.5

- $8,349.3

- $823.9

2029

- 51.5

- $4,009.8

- $2,801.4

- $8,514.0

- $878.9

2030

- 51.5

- $4,119.7

- $2,856.3

- $8,733.7

- $878.9

2031

- 38.0

- $3,078.4

- $2,106.3

- $6,561.8

- $688.6

2032

- 38.0

- $3,118.9

- $2,146.7

- $6,683.3

- $688.6

2033

- 38.0

- $3,159.3

- $2,187.2

- $6,804.6

- $729.1

2034

- 38.0

- $3,199.8

- $2,227.7

- $6,966.6

- $729.1

2035

- 38.0

- $3,240.2

- $2,268.2

- $7,088.0

- $769.6

2036

- 38.0

- $3,280.6

- $2,308.6

- $7,209.3

- $769.5

2037

- 37.9

- $3,361.3

- $2,348.9

- $7,330.0

- $809.9

2038

- 37.9

- $3,401.5

- $2,389.1

- $7,491.4

- $809.9

2039

- 37.9

- $3,441.5

- $2,429.3

- $7,611.7

- $850.2

2040

- 37.9

- $3,481.4

- $2,469.4

- $7,732.0

- $850.1

2041

- 37.9

- $3,521.9

- $2,509.9

- $7,853.5

- $890.6

2042

- 37.9

- $3,562.4

- $2,550.3

- $7,974.9

- $890.6

2043

- 37.9

- $3,602.9

- $2,590.8

- $8,096.3

- $931.1

2044

- 37.9

- $3,643.4

- $2,631.3

- $8,217.8

- $931.1

2045

- 37.9

- $3,724.3

- $2,671.8

- $8,339.2

- $971.6

2046

- 37.9

- $3,764.8

- $2,712.3

- $8,460.7

- $971.6

2047

- 37.9

- $3,805.3

- $2,752.8

- $8,541.6

- $1,012.0

2048

- 37.9

- $3,845.8

- $2,793.2

- $8,663.1

- $1,012.0

2049

- 37.9

- $3,886.2

- $2,833.7

- $8,784.5

- $1,052.5

2050

- 37.9

- $3,926.7

- $2,874.2

- $8,906.0

- $1,052.5

2051

- 37.9

- $3,967.6

- $2,915.3

- $9,029.1

- $1,053.3

2052

- 37.9

- $4,009.0

- $2,956.9

- $9,154.0

- $1,054.0

2053

- 37.9

- $4,050.7

- $2,999.2

- $9,280.6

- $1,054.8

2054

- 37.9

- $4,092.9

- $3,042.0

- $9,408.9

- $1,055.7

2055

- 37.9

- $4,135.6

- $3,085.5

- $9,539.0

- $1,056.5

2056

- 37.9

- $4,178.7

- $3,129.6

- $9,670.9

- $1,057.4

2057

- 37.9

- $4,222.2

- $3,174.3

- $9,804.7

- $1,058.3

2058

- 37.9

- $4,266.2

- $3,219.7

- $9,940.2

- $1,059.3

2059

- 37.9

- $4,310.6

- $3,265.7

- $10,077.7

- $1,060.3

2060 0.0 $0.0 $0.0 $0.0 $0.0

2061 0.0 $0.0 $0.0 $0.0 $0.0

2062 0.0 $0.0 $0.0 $0.0 $0.0

2063 0.0 $0.0 $0.0 $0.0 $0.0

2064 0.0 $0.0 $0.0 $0.0 $0.0

Present Value 3%

- - $62,019.1

- $43,872.4

- $135,622.3

- $14,589.0

Annualized, 3%

- - $2,320.2

- $1,641.3

- $5,073.8

- $545.8

Present Value 7%

- - $25,804.9

- $18,030.6

- $55,597.3

- $5,855.4

Annualized 7%

- - $1,743.5

- $1,218.2

- $3,756.4

- $395.6

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facili ties Rule Chapter 10: Summary for Existing Units

May 2014 10

- 1 

# 10 Summary of Monetized Benefits for Existing Units

10.1 Introduction

This chapter presents a summary of the monetized benefits for existing units under the final rule and

options considered. Chapters 5 through 9 describe the methods and data EPA used to monetize benefits.

Refer to Chapter 1 for a description of the requirem ents of the final rule and other options considered. The

national benefits estimates presented in this chapter do not include benefits estimated using EPA’s SP

survey. Refer to Chapter 11 for detail on the SP survey and results.



## 10.2 Summary of Methods and Lim itations

EPA based it s estimates of national monetized benefits for IM&E reductions under the final rule and

option s considered on its regional estimates of monetized benefits by summing over the seven study

regions. EPA estimated mean national use values, as well as values that include the 5 th 

### percentile lower

bound and 95 th 

### percentile upper bound of the recreational benefits estimates. 58 

### EPA’s estimates of

changes in GHG emissions and associated benefits are at the national level. Monetizing the benefits

r esulting from IM&E reductions and GHG emissions reductions under the final rule and options

considered is challenging. The preceding chapters discuss specific limitations and uncertainties associated

with estimating reductions in IM&E and monetized benefit s. The national benefits estimates presented in

Section 10.3 are subject to the same uncertainties inherent in the valuation approaches EPA used for

assessing regional benefits described in Chapter 5 through 9. The combined effect on estimated use values

( threatened and endangered species, commercial fishing, and recreational fishing ) is of unknown

magnitude and direction (i.e., the estimates may over

- or understate the anticipated national level of use

benefits). Nevertheless, EPA has no data to indicate t hat the results for estimated use benefits are atypical

or unreasonable. EPA was unable to estimate monetized nonuse benefits for IM&E in all regions using

the benefit transfer approach described in Chapter 8. Therefore, the monetized benefits estimates

presented in this section do not reflect total benefits associated with reducing IM&E at existing units at

regulated facilities, and overall national benefits may accordingly be higher.



## 10.3 Summary of Baseline Losses and Monetized Benefits f or the Final Rule and

Options Considered for Existing Units

Table 10

- 1 shows that the total annual national value of IM&E losses due to CWIS at existing units of

regulated facilities. Neither the final rule n or other options considered would eliminate all baseline IM&E

losses. EPA presents the baseline v alues for illustration purposes . EPA did not estimate baseline impacts

related to GHG emissions or associated values.

 Discounted at 3 percent, the total value of baseline IM&E losses is $ 187.1 million per ye ar

including $78.8 million in recreational fishing losses, $8.0 million in commercial fishing losses,

$ 1.2 million in T&E species losses

, and $99.1 million in forgone nonuse benefits . The total value

58 The lower estim ates of value presented in this chapter are measured by the sum of the 5 th percentile lower bound estimates

of recreational values plus the mean value estimates for all other categories of value. The higher estimates of value present ed

in this chapter are measured by the sum of the 95 th percentile upper bound estimates of recreational values plus the mean

value estimates for all other categories of value.Benefits Analysis for the Final 316(b) Existing Facili ties Rule Chapter 10: Summary for Existing Units

May 2014 10

- 2 

### of these fishery losses ranges from $ 151.5 million and $ 256.2 million based on the 5 th 

### percentile

lower bound and 95 th 

### percentile upper bound for recreational values, respectively.

 Discounted at 7 percent , the total value of baseline IM&E losses is $ 177.3 million per year

including $ 72.0 million in recreational fishing losses, $ 7.2 million in commercial fishing losses,

$ 1.1 million in T&E species losses

, and $96.9 million in forgone nonuse benefits. The total value

of these fishery losses ranges from $ 144.7 million and $ 240.6 million based on the 5 th 

### percentile

lower bound and 95 th 

### percentile upper bound for recreational values, respectively.

More detailed discussions of the valuation of impacts under the baseline conditions in each region are

provided in Chapters 5 through 8.

Table 10

- 2, Table 10

- 3, and Table 10

- 4 present EPA ’ s estimates of benefits of reducing IM&E under the

final rule and each of the regulatory options EPA considered for existing units (20 11 $, discounted at 3

percent and 7 percent). Table 10

- 5 provides a summary of benefits includin g the avoided SCC. Monetized

benefits of reductions in IM&E and reduction in GHG emissions based on 3 percent average SCC values

, evaluated at a 3 percent discount rate, are as follows:

 Proposal Option 4 results in benefits of $ 31.0 million per year, with estimates based on the 5 th



### percentile lower bound and 95 th 

### percentile upper bound for recreational values, totaling $ 22.8

million and $ 47.6 million

.

 The final rule results in benefits of $ 33.0 million per year, with estimates based on the 5 th



### percentile lower bound and 95 th 

### percentile upper bound for recreational values, totaling $ 24.1

million and $ 50.6 million

.

 Proposal Option 2 results in benefits of

- $ 1,542.6 million per year, with estimates based on the

5 th 

### percentile lower bound and 95 th 

### percentile upper bound for recreational values, totaling

- $ 1,562.2 million and

- $ 1,504.5 million

.

Evaluated at a 7 percent discount rate, the monetized benefits of the regulatory analysis options are

somewhat smaller for Proposal Option 4 and the final rule , and greater for Proposal Option 2 :

 Proposal Option 4 results in benefits of $ 27.2 million per year, with estimates based on the 5 th



### percentile lower bound and 95 th 

### percentile upper bound for recreational values, totaling $ 21.1

million and $ 39.5 million

.

 The final rule results in benefits of $ 28.7 million per year, with estimates based on the 5 th



### percentile lower bound and 95 th 

### percentile upper bound for recreational values, totaling $ 22.2

million and $ 41.8 million

.

 Proposal Option 2 results in benefits of

- $ 1,148.2 million per year, with estimates based on the

5 th 

### percentile lower bound and 95 th 

### percentile upper bound for recreational values, totaling

- $ 1,161.7 million and

- $ 1,122.0 million

.

More detailed discussions of benefits under each option are provided in Chapters 5 through 9

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 10: Summary for Existing Units

May 2014 10

- 3 

### Table 10

- 1 : Summary of Annualized Benefits from the Elimination of Baseline IM&E at Existing Units of Regulated Facilities

(2011$, millions) a

Region Recreational Fishing Benefits Commercial

Fishing

Benefits c T&E

Species

Benefits d,e Nonuse

Benefits Total Benefits b

Low Mean High Low Mean High

3% Discount Rate

California $2.4 $4.0 $6.8 $1.7

- - $4.1 $5.7 $8.5

North Atlantic $1.7 $2.7 $4.4 $0.4

- $20.2 $22.3 $23.3 $25.0

Mid

- Atlantic $9.7 $16.2 $28.3 $2.2

- $78.9 $90.7 $97.3 $109.4

South Atlantic $0.2 $0.3 $0.4 $0.0

- - $0.2 $0.3 $0.4

Gulf of Mexico $6.5 $9.6 $14.8 $3.4

- - $9.9 $13.0 $18.2

Great Lakes $7.3 $13.8 $26.3 $0.2

- - $7.5 $14.1 $26.6

Inland $15.5 $32.1 $66.9

- $1.2

- $16.7 $33.3 $68.1

Total $43.2 $78.8 $147.9 $8.0 $1.2 $99.1 $151.5 $187.1 $256.2

7% Discount Rate

California $2.2 $3.6 $6.1 $1.5

- - $3.7 $5.1 $7.6

North Atlantic $1.5 $2.4 $3.9 $0.4

- $19.8 $21.6 $22.6 $24.0

Mid

- Atlantic $8.6 $14.5 $25.3 $1.9

- $77.2 $87.8 $93.6 $104.5

South Atlantic $0.2 $0.3 $0.3 $0.0

- - $0.2 $0.3 $0.4

Gulf of Mexico $6.0 $8.8 $13.6 $3.2

- - $9.1 $12.0 $16.8

Great Lakes $6.7 $12.8 $24.3 $0.2

- - $7.0 $13.0 $24.5

Inland $14.3 $29.6 $61.7

- $1.1

- $15.4 $30.7 $62.8

Total $39.5 $72.0 $135.3 $7.2 $1.1 $96.9 $144.7 $177.3 $240.6

"

- " = not estimated

a All benefits presented in this table are annualized, i.e., represent the sum of the discounted stream of benefits annualized over 51 years (2014 to 2064). See Appendix D for detail.

b A range of recreational fishing benefits is provided, based on the Krin sky and Robb technique, to estimate the 5th and 95th percentile limits on the marginal value per fish predicted by the

meta

- analysis. Commercial fishing benefits are computed based on a region

- and species

- specific range of gross revenue, as explained in Ch apter 6 of this report. EPA estimated

recreational use benefits for some T&E species, as explained in Chapter 5. To calculate the total monetizable value columns ( low, mean, high), the values for commercial fishing benefits

and T&E species benefits are add ed to the respective low, mean, and high values for recreational fishing benefits.

c No significant commercial fishing takes place in the Inland region. Thus, this region is excluded from the commercial fishing analysis.

d Recreational use benefits from in creased abundance of T&E species with potentially high recreational use values (e.g., paddlefish and sturgeon). See Chapter 5 of this report

for more detail on EPA’s analysis of T&E benefits.

e Zeros represent values less than 1,000.

Source: U.S. EPA anal

ysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 10: Summary for Existing Units

May 2014 10

- 4 

### Table 10

- 2 : Summary of Annualized Benefits Associated with IM&E Reductions under Proposal Option 4 (2011$, millions) a

Region Recreational Fishing Benefits Commercial

Fishing

Benefits c T&E

Species

Benefits d,e Nonuse

Benefits Total Benefits b

Low Mean High Low Mean High

3% Discount Rate

California $0.0 $0.1 $0.1 $0.0

- - $0.0 $0.1 $0.1

North Atlantic $0.0 $0.0 $0.0 $0.0

- $0.1 $0.1 $0.1 $0.1

Mid

- Atlantic $0.5 $1.0 $2.0 $0.2

- $0.2 $1.0 $1.5 $2.5

South Atlantic $0.0 $0.0 $0.0 $0.0

- - $0.0 $0.0 $0.0

Gulf of Mexico $1.3 $2.2 $3.9 $0.5

- - $1.8 $2.7 $4.4

Great Lakes $3.4 $6.5 $12.4 $0.1

- - $3.6 $6.6 $12.5

Inland $3.5 $7.3 $15.2

- $0.4

- $3.9 $7.7 $15.6

Total $8.8 $17.1 $33.6 $0.9 $0.4 $0.3 $10.4 $18.7 $35.2

7% Discount Rate

California $0.0 $0.1 $0.1 $0.0

- - $0.0 $0.1 $0.1

North Atlantic $0.0 $0.0 $0.0 $0.0

- $0.1 $0.1 $0.1 $0.1

Mid

- Atlantic $0.4 $0.7 $1.4 $0.2

- $0.2 $0.8 $1.1 $1.8

South Atlantic $0.0 $0.0 $0.0 $0.0

- - $0.0 $0.0 $0.0

Gulf of Mexico $0.9 $1.6 $2.8 $0.4

- - $1.3 $1.9 $3.2

Great Lakes $2.6 $4.8 $9.2 $0.1

- - $2.7 $4.9 $9.3

Inland $2.6 $5.4 $11.4

- $0.3

- $2.9 $5.7 $11.7

Total $6.5 $12.6 $24.9 $0.7 $0.3 $0.3 $7.7 $13.8 $26.1

"

- " = not estimated

a All benefits presented in this table are annualized, i.e., represent the sum of the discounted stream of benefits annualized over 51 years (2014 to 2064). See Appendix D for detail.

b A range of recreational fishing benefits is provid ed, based on the Krinsky and Robb technique, to estimate the 5th and 95th percentile limits on the marginal value per fish pr edicted by the

meta

- analysis. Commercial fishing benefits are computed based on a region

- and species

- specific range of gross revenu e, as explained in Chapter 6 of this report. EPA estimated

recreational use benefits for some T&E species, as explained in Chapter 5. To calculate the total monetizable value columns ( low, mean, high), the values for commercial fishing benefits

and T&E spe cies benefits are added to the respective low, mean, and high values for recreational fishing benefits.

c No significant commercial fishing takes place in the Inland region. Thus, this region is excluded from the commercial fishing analysis.

d Recreational use benefits from increased abundance of T&E species with potentially high recreational use values (e.g., paddlefish and stur geon). See Chapter 5 of this report

for more detail on EPA’s analysis of T&E benefits.

e Zeros represent values less than 1,000.

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 10: Summary for Existing Units

May 2014 10

- 5 

### Table 10

- 3 : Summary of Annualized Benefits Associated with IM&E Reductions under the Final Rule for Existing Units (2011$,

millions) a

Region Recreational Fishing Benefits Commercial

Fishing

Benefits c T&E

Species

Benefits d,e Nonuse

Benefits Total Benefits b

Low Mean High Low Mean High

3% Discount Rate

California $0.0 $0.1 $0.1 $0.0

- - $0.0 $0.1 $0.1

North Atlantic $0.0 $0.0 $0.0 $0.0

- $0.2 $0.2 $0.2 $0.2

Mid

- Atlantic $0.6 $1.1 $2.1 $0.3

- $0.8 $1.6 $2.1 $3.2

South Atlantic $0.0 $0.0 $0.0 $0.0

- - $0.0 $0.0 $0.1

Gulf of Mexico $1.3 $2.3 $4.1 $0.5

- - $1.8 $2.8 $4.6

Great Lakes $3.8 $7.2 $13.6 $0.1

- - $3.9 $7.3 $13.8

Inland $3.7 $7.6 $15.9

- $0.4

- $4.1 $8.0 $16.3

Total $9.4 $18.2 $35.9 $0.9 $0.4 $1.0 $11.8 $20.6 $38.3

7% Discount Rate

California $0.0 $0.1 $0.1 $0.0

- - $0.0 $0.1 $0.1

North Atlantic $0.0 $0.0 $0.0 $0.0

- $0.2 $0.2 $0.2 $0.2

Mid

- Atlantic $0.4 $0.8 $1.5 $0.2

- $0.7 $1.2 $1.6 $2.3

South Atlantic $0.0 $0.0 $0.0 $0.0

- - $0.0 $0.0 $0.0

Gulf of Mexico $0.9 $1.6 $2.9 $0.4

- - $1.3 $2.0 $3.3

Great Lakes $2.8 $5.3 $10.1 $0.1

- - $2.9 $5.4 $10.2

Inland $2.7 $5.7 $11.9

- $0.3

- $3.1 $6.0 $12.2

Total $7.0 $13.5 $26.6 $0.7 $0.3 $0.8 $8.8 $15.3 $28.4

"

- " = not estimated

a All benefits presented in this table are annualized, i.e., represent the sum of the discounted stream of benefits annualized over 51 years (2014 to 2064). See Appendix D for detail.

b A range of recreational fishing benefits is provided, based on the Krinsky and Robb technique, to estimate the 5th and 95th p ercentile limits on the marginal value per fish predicted by the

meta

- analysis. Commercial fishing benefits are computed based on a region

- and species

- specific range of gross revenue, as explained in Chapter 6 of this report. EPA estimated

recreational use benefits for some T&E species, as explained in Chapter 5. To calculate the total monetizable value columns ( low, mean, high), the values for commercial fishing benefits

and T&E species benefits are added to the respective low, mean, and high values for recreational fishing benefits.

c No significant commercial fishing takes place in the Inland region. Thus, this region is excluded f rom the commercial fishing analysis.

d Recreational use benefits from increased abundance of T&E species with potentially high recreational use values (e.g., paddle fish and sturgeon). See Chapter 5 of this report

for more detail on EPA’s analysis of T&E b enefits.

e Zeros represent values less than 1,000.

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 10: Summary for Existing Units

May 2014 10

- 6 

### Table 10

- 4 : Summary of Annualized Benefits Associated with IM&E Reductions under Proposal Option 2 (2011$, millions) a

Region Recreational Fishing Benefits Commercial

Fishing

Benefits c T&E

Species

Benefits d,e Nonuse

Benefits Total Benefits b

Low Mean High Low Mean High

3% Discount Rate

California $0.9 $1.5 $2.6 $0.7

- - $1.6 $2.2 $3.2

North Atlantic $0.9 $1.4 $2.2 $0.2

- $10.4 $11.5 $12.0 $12.9

Mid

- Atlantic $5.1 $8.6 $15.1 $1.2

- $40.7 $47.0 $50.5 $57.0

South Atlantic $0.1 $0.2 $0.2 $0.0

- - $0.1 $0.2 $0.2

Gulf of Mexico $3.4 $5.1 $8.1 $1.7

- - $5.1 $6.8 $9.8

Great Lakes $4.7 $8.9 $17.0 $0.2

- - $4.9 $9.1 $17.2

Inland $8.3 $17.2 $35.9

- $0.7

- $9.0 $17.9 $36.5

Total $23.4 $43.0 $81.1 $3.9 $0.7 $51.1 $79.1 $98.7 $136.8

7% Discount Rate

California $0.6 $1.0 $1.7 $0.4

- - $1.0 $1.4 $2.1

North Atlantic $0.6 $0.9 $1.5 $0.1

- $7.6 $8.3 $8.7 $9.2

Mid

- Atlantic $3.3 $5.5 $9.6 $0.8

- $29.7 $33.7 $36.0 $40.1

South Atlantic $0.1 $0.1 $0.2 $0.0

- - $0.1 $0.1 $0.2

Gulf of Mexico $2.5 $3.8 $6.0 $1.3

- - $3.7 $5.0 $7.2

Great Lakes $3.4 $6.4 $12.1 $0.1

- - $3.5 $6.5 $12.2

Inland $5.7 $11.9 $24.8

- $0.5

- $6.2 $12.3 $25.2

Total $16.1 $29.5 $55.8 $2.7 $0.5 $37.3 $56.6 $70.0 $96.3

"

- " = not estimated

a All benefits presented in this table are annualized, i.e., represent the sum of the discounted stream of benefits annualized over 51 years (2014 to 2064). See Appendix D for detail.

b A range of recreational fishing benefits is provided, based on the Krinsky and Robb technique, to estimate the 5th and 95th p ercentile limits on the marginal value per fish predicted by the

meta

- analysis. Commercial fishing benefits are computed based on a region

- and species

- specific range of gross revenue, as explained in Chapter 6 of this report. EPA estimated

recreational use benefits for some T&E species, as explained in Chapter 5. To calculate the total monetizable value columns ( low, mean, high), the values for commercial fishing benefits

and T&E species benefits are added to the respective low, mean, and high values for recreational fishing benefits.

c No significant commercial fishing takes place in the Inland region. Thus, this region is excluded f rom the commercial fishing analysis.

d Recreational use benefits from increased abundance of T&E species with potentially high recreational use values (e.g., paddle fish and sturgeon). See Chapter 5 of this report

for more detail on EPA’s analysis of T&E b enefits.

e Zeros represent values less than 1,000.

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 10: Summary for Existing Units

May 2014 10

- 7 

### Table 10

- 5 : Summary of Annualized Benefits by Regulatory Option for Existing Units (2011$, millions) a

Regulatory

Option Recreational Fishing Benefits Commercial

Fishing

Benefits c T&E Species

Benefits d,e Nonuse

Benefits SCC e Total Benefits

Low Mean High Low Mean High

3% Discount Rate

Proposal Option 4 $8.8 $17.1 $33.6 $0.9 $0.4 $0.3 $12.4 $22.8 $31.0 $47.6

Final Rule $9.4 $18.2 $35.9 $0.9 $0.4 $1.0 $12.4 $24.1 $33.0 $50.6

Proposal Option 2 $23.4 $43.0 $81.1 $3.9 $0.7 $51.1

- $1,641.3

- $1,562.2

- $1,542.6

- $1,504.5

7% Discount Rate

Proposal Option 4 $6.5 $12.6 $24.9 $0.7 $0.3 $0.3 $13.4 $21.1 $27.2 $39.5

Final Rule $7.0 $13.5 $26.6 $0.7 $0.3 $0.8 $13.4 $22.2 $28.7 $41.8

Proposal Option 2 $16.1 $29.5 $55.8 $2.7 $0.5 $37.3

- $1,218.2

- $1,161.7

- $1,148.2

- $1,122.0

a All benefits presented in this table are annualized, i.e., represent the sum of the discounted stream of benefits annualized over 51 years (2014 to 2064). See Appendix D for detail.

b A range of recreational fishing benefits is provided, based on the Krinsky and Robb technique, to estimate the 5th and 95th p ercentile limits on the marginal value per fish predicted by the meta

analysis. Commercial fishing benefits are computed based on a region

- and species

- specific range of gross revenue, as explained in Chapter 6 of this report. EPA estimated recreational use

benefits for some T&E species, as explained in Chapter 5. To calculate the total monetizable value columns (low, mean, high), th e values for commercial fishing benefits and T&E species benefits

are added to the respective low, mean, and high values for recreational fishing benefits.

c No significant commercial fishing takes place in the Inland region. Thus, this region is excluded from the commercial fishing analysis.

d Recreational use benefits from increased abundance of T&E species with potentially high recreational use values (e.g., paddle fish and sturgeon).

See Chapter 5 of this report for more detail on EPA’s analysis of T&E benefits.

e SCC results presented here are based on 3 percent average SCC values.

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 1 

# 11 Stated Preference Survey

11.1 Introduction

EPA developed a stated preference survey to estimate total values (use plus nonuse) for

improvements to fishery resources and ecosystems affected by IM&E f rom regulated facilities. 59



### Understanding total public WTP for resulting changes in fishery resources, including the more

difficult to estimate nonuse valu es, is necessary to determine the full range of benefits associated

with reductions in IM&E, and simplifies the determination of whether the benefits of government

action to reduce IM&E at existing facilities are commensurate with the costs of such actions

. Because potential nonuse values may be substantial, failure to recognize such values may lead to

improper inferences regarding benefits and costs, and an inefficient allocation of society’s

resources. As discussed in Chapter 8 , EPA was able to generate only a partial estimate of nonuse

benefits using benefit transfer with existing SP data. Moreover, estimates from high quality

primary valuation studies are generally considered superior to those from benefit transfer

( Johnston & Rosenberger 2010 ) because primary studies are designed for the specific context of

the policy case, whereas transferring results from other studies may require assumptions to

facilitate transfer that may not be co mpletely accurate

. EPA developed and implemented the SP

survey to fill this gap by providing data which could be used to estimate total benefits for all U.S.

regions.

EPA plans to obtain SAB review of the SP survey EPA conducted. The SAB review would be i n

addition to the external peer review EPA already conducted on the survey. SAB review will

provide high caliber, independent professional judgment concerning the quality of the survey

done to date, including possible improvements EPA could make to the ana lysis . EPA also plans

to seek SAB input on whether

, how and in what circumstances this or similar survey s could be

used as support for national rulemaking s or 316(b) NPDES permitting

. EPA expects that while

this process will add time (it may take a year or more), given the importance of this issue for the

evaluation of ecological benefits generally, it is worth taking the time to seek this additional

input. Given the planned SAB review, using the SP survey results prior to completion of the

review would be premature. EPA is committed to working with the states to support their site

specific permitting decisions with the benefit of the SAB review once it is completed.

EPA has not accounted for values estimated from the survey in the comparison of monetized

co sts and benefits. This chapter describes the design of the SP survey and presents current, but

not necessarily final, model estimation results. EPA also describes a method for monetizing

benefits for the final rule and presents a preliminary estimate of be nefits for the final rule and

options considered to illustrate the potential magnitude of regulatory benefits and demonstrate

progress towards this effort. Discussion of peer reviewer comments related to their confidence in

the study results and lim itatio ns for policy analysis is presented in Section 11.10

.

59 As discussed in Chapter 8, nonuse values are values people may hold for an environmental improvement that are

not associated with use (e.g., recreation) of the resource.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 2 

## 11.2 Survey Design

SP surveys , in general, ask questions that elicit individuals’ stated values for carefully specified

changes in an environmental amenity. This value is typically estimated in terms of WTP, defined

as the maximum amount of money (or some other commodity) that an individual or household

would be willing to give up in exchange for a specified environmental change, rather than go

without that change. EPA designed the SP survey as a choice e xperiment. Choice experiments,

also called choice models, are a n SP technique in which individuals’ values are estimated based

on their choices over a set of hypothetical but realistic multi

- attribute policy options designed to

mimic the consumer decision

- making that occurs in actual markets , and span the range of

possible policy options

. 60 

### Choice experiments have been applied in many past studies to assess

WTP for ecological resource improvements , which is also the context of the main improvement

in the 316 (b) policy case ( e.g., Bennett and Blamey 2001 ; Hanley et al. 2006 ; Hoehn et al. 2004 ;

Johnston et al. 2002 a; Johnston et al. 2011b ; Johnston et al. 2012 ; Milon and Scrogin 2006 ;

Morrison et al. 2002 ; Morrison and Bennett 2004 ; Opaluch et al. 1999 )

.

Advantages of these choice

- based methods include similarity to familiar referenda or market

choice contexts, in which individuals choose among alternative bundles of attributes or

commodities (for example, attributes of consumer electronics) at different c osts ( Freeman 2003 )

. Among other advantages, such methods are intended to reduce strategic and other survey biases

that can be associated with alternative ways of using survey questions to elicit values, versus

assessing WTP through market transactions or referenda. For exam ple, some types of SP surveys

ask respondents to express their WTP using open

- ended questions, payment cards, or bidding

games. Increasingly, however, these types of SP surveys have been replaced in the literature by

choice

- based methods. 61



### C hoice experime nts also allow survey respondents to express WTP for a wide range of different

potential outcomes, differentiated by their attributes . This enables EPA to isolate the marginal

effects of different potential policy outcomes on stated choices and hence

, on e stimated WTP

. EPA can thereby estimate benefits for a wider range of potential policy outcomes than would be

possible with alternative SP methods. This is a primary factor distinguishing choice experiments

from older forms of SP analysis, in which stated W TP is typically contingent upon a single

specification of ecological and other policy effects.

11.2.1 Survey Format

EPA followed established choice experiment methodology in the developing the format of the

316(b) SP survey ( Adamowicz et al. 1998 ; Bateman et al. 2002 ; Bennett and Blamey 2001 ;

Louviere et al. 2000 ) . Respondents are presented with two alternative hypothetical policy options

60 In addition to choice experiments, stated preference techniques include as contingent valuation (CV). CV surveys

typically ask respondents, “What are you willing to pay?” for a parti cular environmental improvement, or in a

dichotomous choice form as “are you willing to pay $X?” for a particular environmental improvement. In general,

CV surveys focus on a comparison between the status quo and a particular environmental improvement (ak in to a

one

- time offer). This is different from the consumer decision

- making that occurs in actual markets and involves

comparing status quo to multiple environmental outcomes. Therefore, EPA relied on the choice experiment

technique that mimics common mar ket situations in its study design.

61 Choice

- based methods are also increasingly employed in the marketing research literature to analyze consumer

preferences. In particular, choice based experiments are a popular in modeling brand choice ( Erdem and Keane

1996 ) and demand for new products ( Brownstone and Train 1996 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 3 

### described by multiple attributes. They are asked to choose (or vote for) the policy they prefer,

much as one would choose a preferred option in a public referendum. Respondents may also

c hoose to reject both policies and retain the status quo. The underpinning theoretical model is

adapted from a standard random utility specification in which household h chooses among three

choice options (

j=A,B,N ), including two multi

- attribute policy options ( A, B ) and a fixed “No

Policy” (the status quo ) ( N ) that includes no policy changes and zero cost to the household. Each

choice option reflects a hypothetical but feasible outcome under various 316(b) regulatory

alternatives.

The effects of the policy options are described in terms of a household cost and four

environmenta l endpoints, or attributes: (a) commercial fish populations , (b) fish populations (all

fish) , (c) fish saved per year , and (d) condition of aquatic ecosystems . The definition of each

attribute is presented in Table 11

- 1

. Ecological attribute s are expressed relative to upper and

lower reference conditions; i.e., best and worst possible conditions of the attribute, as defined in

survey informational materials. R espondents were asked to evaluate changes in fish saved per

year as a percentage of current estimat ed mortality, but those changes were also illustrated in

terms of numbers of A1E fish. 62 

### Relative scores represent percent progress towards the upper

reference condition (100 percent ), starting from the l ower reference condition (0 percent), both

keyed to r eadily understood conditions. Presentation of all ecological attributes was informed by

input from focus groups and cognitive interviews (Johnston et al. 1995 ; Kaplowitz et al. 2004 )

used to pretest the survey instrument.

Values for “fish saved” in the referendum questions are based on EPA’s estimate of A1E losses

due to CWIS at baseline. Refer to Chapter 3 for additional description of the A1E metric.

I ntroductory materials in the survey describe the age classes impacted due to c ooling water

intakes and the “fish saved” metric as “ young adult fish (the equivalent of one year old ) .” P re

testing during focus groups and cognitive interviews suggested that participants understood the

“fish saved” attribute and the concept of “young fi sh” as reflecting initial IM&E of eggs and other

juvenile life stages expressed as in terms of the A1E metric . Page three of the survey booklet

includes introductory materials that specify the proportion of “fish saved” that are and are not

comme rcial or r ecreational species.

Values are reflected in the survey by individuals’ willingness to “vote” for policies that would

result in an increase in their cost of living, in exchange for specified changes in the four

environmental attributes. Other questions in the survey elicit information including whether the

respondent is a user of the affected aquatic resources, household income, and other respondent

demographics. 63

62 A1E, in addition to providing a way to standardize organisms lost to IM&E so that it could be compared among

species, years, facilities, and regions, is a convenient way to express losses of all life stages, including fish eggs

and larvae, as numbe rs of individual age

- one equivalent fish.

63 The four environmental attributes were designed based on the Johnston et al. ( 2011a ; 2011b ; 2012 ) Bioindicator

Based Stated Preference Valuation (BSPV) method which was developed to promote ecological clarity and closer

integration of ecological and economic information within SP studies. This methodology was developed in part to

address t h e EPA Science Advisory Board’s call, in its May 2009 report, Valuing the Protection of Ecological

Systems and Services: A Report of the EPA Science Advisory Board ( USEPA 2009 b)

, for improved quantitative

linkages between ecological services and economic valuation of those services.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 4 

### Table 11

- 1: Definitions of Policy Attributes and Baseline (No Policy) Values

Attribute Definition

Commercial Fish

Populations A score between 0 and 100 percent showing the overall health of commercial and

recreational fishing populations. High scores mean more fish and greater fishing potential.

A score of 100 means that these fish populations are at a size that maximizes long

- term

harvest: 0 means no harvest.

Fish Populations

(All Fish) A score between 0 and 100 percent showing the estimated size of all fish populations

compared to natural levels without human influence. A score of 100 means that

populations are the largest natural size possible; 0 means no fis h.

Fish Saved (per

Year) A score between 0 and 100 percent showing the reduction in young fish lost compared to

current levels. A score of 100 would mean that no fish are lost in cooling water intakes (all

fish would be saved because of the new policy).

Condition of

Aquatic

Ecosystems A score between 0 and 100 percent showing the ecological condition of affected areas,

compared to the most natural waters in the region. The score is determined by many

factors including water quality and temperature, the he alth of aquatic species, and habitat

conditions.

Cost per Year How much the policy will cost your household, in unavoidable ongoing price increases for

products and services you buy, including electricity and common household products.

Source: U.S. EPA analysis for this report



### 11.2.2 Experimental Design

The experimental design is the plan for varying attribute levels across questions within a survey

and across survey versions, so that aggregated responses will provide enough data for efficient

estimation of model parameters and WTP. Respondents were presented with three separate policy

questions in the survey, each with a specific combination of policy options. The ex perimental

design specifies how these attribute levels were “mixed and matched” within choice questions,

thereby developing an empirical data framework with appropriate statistical properties to allow

for analysis of respondent’s choices ( Louviere et al. 2000 )

. It generat es multiple unique

combinations of policy options for different respondents to compare.

Table 11

- 2 presents the set of attribute levels that are used across the option pairs. Following

guidance from the literature, EPA designed the attribute levels to illu strate realistic policy

scenarios that “span the range over which we expect respondents to have preferences, and/or are

practically achievable” (Bateman et al. 2002, p. 259; USEPA 2012a; USEPA 2012b).

In interpreting the results, it is useful to keep in mind that three of the attributes spanned a

relatively narrow range of percentage values reflecting realistic ecological expectations (e.g.,

commercial fish populations differing by no more than six perc entage points from the baseline),

while the “fish saved per year” attribute, which was ultimately used to estimate household WTP

for the policy options, spanned a much larger range ( i.e ., up to 95 percentage points). T his reflects

the expected range of po tential reductions based on the performance of the technologies consider

for the regulatory options. Given this realistic distinction in attribute spread, EPA expects that the

WTP per percentage point will be lower for fish saved than for other attributes because

respondents “see” most of the possible ranges of fish saved. Allowing the range of variables to

vary according to realistic ecological and technological expectations is recommended practice in

SP design ( Bateman et al. 2002 )

.

EPA applied a fract ional factorial experimental design representing a subset of all possible

combinations of environmental attributes and household cost. This allows efficient estimation of

particular effects of interest with a relatively small number of choice questions ( Louviere et al.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 5 

### 2000 )

, thereby reducing the cognitive burden faced by respondents ( i.e., by reducing the number

of questions that each respondent must answer; Holmes and Adamowicz 2003 ) . EPA generated

the design usi ng a D

- efficiency criterion for main effects estimation ( Kuhfeld and Tobias 2005 ;

Kuhfeld 2010 ) . This design enables model coefficients, and hence, estimated WTP , to be

estimated with greater precision

, i.e., lower standard errors or variability, for any given number of

observations. It also minimizes correlation between attributes across survey questions (i.e.,

attributes do not “move together” across different survey questions), so that the unique effect of

each attribute on respondents’ choices, and ultimately, values, can be isolated. 64



### The experimental design for the 316(b) survey is characterized by 72 unique Option A vs. Option

B pairs, each corresponding to a choice question defined by an orthogonal (independent) array of

attribute leve ls for the two policy options. It is standard practice to include more than one choice

question in each survey, thus increasing the information obtained from each respondent ( Layton

2000 ; Poe et al. 19 97 ) . EPA randomly assigned the 72 option pairs to 24 distinct versions for each

of the four regional surveys and the national survey, with three option pairs (i.e., choice

questions) per survey booklet. See the ICR supporting statement ( USEPA 2011 C) for additional

detail on the experimental design.

64 EPA removed dominated pairs where one option is superior to th e other in all attributes. Allowing such pairs

would effectively limit respondents to selecting between the dominant choice option and the No Policy option.

Focus groups showed that respondents react negatively and often protest when offered dominated pai rs. Given that

such choices provide negligible statistical information compared to choices involving non

- dominated pairs, they

are typically avoided in choice experiment statistical designs.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 6 

### Table 11

- 2 : Attribute Levels Assigned Across Policy Options and Survey Versions

Attribute Baseline ( No

Policy ) a Max

Change

Assigned Attribute Levels Assigned to Option A vs. Option B Pairs

1 2 3 4 5 6

Commercial Fish Populations (Score showing the overall health of commercial and recreational fish populations)

Northeast 42% 6% 43% 45% 48%

- - -

Southeast 39% 6% 40% 42% 45%

- - -

Pacific 56% 6% 57% 59% 62%

- - -

Inland 39% 6% 40% 42% 45%

- - -

National 51% 6% 52% 54% 57%

- - -

Fish Populations (all fish) (Score showing the estimated size of all fish populations compared to natural levels

without human influence)

Northeast 26% 4% 27% 28% 30%

- - -

Southeast 24% 4% 25% 26% 28%

- - -

Pacific 32% 4% 33% 34% 36%

- - -

Inland 33% 4% 34% 35% 37%

- - -

National 30% 4% 31% 32% 34%

- - -

Fish Saved per Year (Score showing the reduction in young fish lost compared to current levels)

Northeast 0% 95% 5% 50% 95%

- - -

Southeast 0% 90% 25% 55% 90%

- - -

Pacific 0% 95% 2% 50% 95%

- - -

Inland 0% 95% 55% 75% 95%

- - -

National 0% 95% 25% 55% 95%

- - -

Aquatic Ecosystem Condition (Score showing the ecological condition of affected areas, compared to the most

natural waters in the region)

Northeast 50% 4% 51% 52% 54%

- - -

Southeast 68% 4% 69% 70% 72%

- - -

Pacific 51% 4% 52% 53% 55%

- - -

Inland 42% 4% 43% 44% 46%

- - -

National 53% 4% 54% 55% 57%

- - -

Household Costs (The increase in annual household cost, in unavoidable price increases)

Northeast $0 $72 $12 $24 $36 $48 $60 $72

Southeast $0 $72 $12 $24 $36 $48 $60 $72

Pacific $0 $72 $12 $24 $36 $48 $60 $72

Inland $0 $72 $12 $24 $36 $48 $60 $72

National $0 $72 $12 $24 $36 $48 $60 $72

a Each question includes a “no policy” option, characterized by the baseline levels for each attribute and a household cost of $0.

Source: U.S. EPA analysis for this report



### 11.2.3 Pre

- Tests

Following recommended method s for SP survey design, EPA used focus groups and cognitive

interviews to test wording and attribute selection and ensure that respondents understand and are

not cognitively burdened by the question format (cf. Arrow et al. 1993 ; Bateman et al. 200 2 ;

Bennett and Blamey 2001 ; Kaplowitz et al. 2004 ; Powe 2007 ) . The survey instrument was pre

tested extensively in six focus groups, with eight to ten partic ipants each , and a set of eight one

on

- one cognitive interviews ( USEPA 2010d ) . Each cognitive interview included only one

participant. This allowed in

- depth exploration of the cognitive processes respondents used to

answer survey questions, without the potential for interpersonal dynamics to sway respondents’Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 7 

### comments ( Kaplowitz et al. 2004 ) . These focus group s and cognitive interviews were in addition

to ten focus groups and two series of cognitive interviews that were conducted previously by EPA

in 2004 and 2005 to test an earlier version of the survey developed in anticipation of the Phase III

benefits analy sis. Focus groups and cognitive interviews also included questions following the

verbal protocol format suggested by Schkade and Payne ( 1994 ) , in which respondents were asked

to talk through the process used to answer choice questions. Within focus group and cognitive

interviews, the moderator first asked the participants to complet e a draft survey questionnaire.

The moderator then led a general conversation which led the group/individual through a series of

debriefing questions. During debriefing, the moderator asked focus group and cognitive interview

participants about their react ions to the survey format and content, their interpretations of survey

materials (including questions and the information provided), whether the survey questions were

clear, whether the background information presented in the survey or introductory materia ls was

sufficient, whether respondents felt like the questions were leading, what went through

participants’ minds when they read survey information and questions, and response motivations.

Debriefing questions also explored whether responses were influenc ed by hypothetical, strategic,

symbolic and other biases noted in the stated preference literature.

The participants’ comments and feedback provided important information on such concerns as

whether (1) questions and survey information were readily underst ood, (2) respondents were

interpreting questions similarly to how EPA interprets them, (3) responses or survey

interpretations showed any evidence of heuristics or survey biases, including hypothetical bias,

(4) respondents were addressing choice questions in a manner commensurate with utility

maximization and neoclassical WTP estimation, and (5) respondents were following instructions

provided in the survey instrument and responding to questions accordingly. Focus group

participants’ responses to the surve y choice questions could not be included in model estimation

because the draft surveys completed during pre

- testing represent evolving versions and differed

somewhat from the final survey. EPA modified the survey several times based on the results of

these pre

- tests to help minimize potential biases and ensure shared and accurate interpretation of

survey language by the respondents. The amount of pre

- testing conducted for SP surveys varies

within the literature and tends to be related to the complexity of t he survey instrument. However,

the amount of time and number of focus groups the Agency used is significantly greater than

many academic studies and matches the practice in developing SP surveys for natural resource

damage assessments.



## 11.3 Sampling Frame

The s ampling frame is the population from which the potential respondents are selected, in this

case, at random. EPA designed the 316(b) SP study as a household mail survey, because the

household is the fundamental economic decision

- making unit for WTP studies. The mail survey

approach avoids potential sampling biases in telephone surveys associated with the incomplete

coverage of landline and cellphone databases. The mail address sample of households in the

continental U.S. was from drawn from a database which covers 97 percent of residences in the

United States including city

‐ style addresses and PO boxes, and covers single

‐ unit, multi

‐ unit, and

other types of housing structures

.

EPA stratified households based on the geographic boundaries of four regions: Northeast,

Southeast, Inland, and Pacific. The SP regions are based on state boundaries and include both

coastal and freshwater facilities in the Northeast, Southeast, and Pacific regions. These regionsBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 8 

### differ from t he 316(b) benefits regions used elsewhere in this Benefits Analysis which separate

coastal and freshwater resources. During survey pretesting, EPA found that respondents more

easily understood regional boundaries based on states than boundaries that distin guished between

coastal and freshwater facilities.

Table 11

- 3 presents the States included in each SP region, the total number of households in each

region, the target number of completed surveys, and the number of surveyed households for each

survey regio n. EPA developed target sample sizes for each region to p rovide statistically robust

results while minimizing the cost and burden of the survey to individual respondents

. 65 

### The target

sample sizes refer to completed mail surveys. A larger number of househol ds must be mailed

surveys because only a portion of households that receive a survey complete and return it.

EPA selected a total target sample of 2,000 completed surveys across all four regional surveys to

provide estimates of population percentages with a margin of error ranging from 3.6 to 5.8

percentage points at the 95 percent confidence level. 66 

### Th ese 2,000 surveys were allocated across

the four regions based on the number of households in each region relative to the total number of

household in the c ontinental United States. In addition, a minimum number of completed surveys

were required for each region to enable model estimation. Monte Carlo experiments indicate that

approximately 6 to 12 completed responses are required for each profile (unique set of choice

options) in order to achieve large sample statistical properties for choice experiments ( Louviere et

al. 2000, p. 104, citing Bunch and Batsell 1989 ) . As described previously, the experimental

design includes 72 option profiles. Following this guidance, the experiment design require s 12

completed surveys for each of the 72 profiles, for a total of 864 profile responses per region

(72 ×12 =864). A minimum of 288 completed surveys were hence required for each region

because each survey version includes three profiles (864÷3=288).

The allocation of the 2,000 completed surveys across the four regions resulted in target sample

sizes of 417 for the Northeast region, 562 for the Southeast region, 289 for the Pacific region, and

732 for the Inland region. EPA also conducted a national mail survey with a target sample size of

288 completed surveys. EPA mailed the survey to 7,840 households in total, anticipating a

response rate of 30 percent. EPA assumed that it would take respondents an average of 30

minutes to complete and mail back the questionnaire.

65 EPA included three choice questions within each survey, to inc rease information obtained from each respondent.

It is standard practice within choice experiment and dichotomous choice contingent valuation surveys to include

more than one choice question in each survey ( Layton 2000 ; Poe et al. 1997 ) . Including more than three choice

questions may have negatively affected the response rate by increasing burden on respondents and includ ing fewer

would have increased survey costs by requiring additional households to be sampled.

66 Margin of error was calculated assuming that the population percentage selecting a specific answer (e.g., “yes”) in

a binary question is 50 percent (i.e., wors t case scenario). This is the worst case scenario because it indicates that

there is disagreement among people regarding the correct response (i.e., 50 percent select “yes” and 50 percent

select “no”) and the standard error of the proportion is large (Orme 2010). The range of the margin of error (3.6 to

5.8 percent) is based on the sample sizes for each region. For example, the sample percentage selecting a specific

response to a binary question based on a sample of 732 households has a margin of error of p lus or minus 3.6

percent at a 95 percent confidence level whereas the sample percentage selecting a specific response based on a

sample of 288 households will have a margin of error of plus or minus 5.8 percent.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 9 

### Table 11

- 3 : Target Sample Sizes and Number of Mailed Surveys by Survey Region

Survey Region State Included Number of

Households a Target Sample

Size b

, c Number of

Surveyed

Households d

Northeast CT, DC, DE, MA, MD, ME,

NH, NJ, NY, PA, RI, VT 23,281,296 417 1,440

Southeast AL, FL, GA, LA, MS, NC,

SC, TX, VA 31,378,122 562 1,920

Pacific CA, OR, WA 40,852,983 289 1,040

Inland AR, AZ, CO, ID, IA, IL, IN,

KS, KY, MI, MN, MO, MT,

ND, NE, NM, NV,

OH, OK,SD, TN, UT, WI,

WV, WY 16,158,206 732 2,480

Total for Regional

Surveys U.S. (excluding AK and HI) 111,670,607 2,000 6,880

National Survey U.S. (excluding AK and HI) 111,670,607 288 960

a The number of households in each region was obtained based on the estimated population size and average household size from

the 2006

- 2008 American Community Survey (U.S. Census Bureau 2009).

b Target sample sizes presented here refer to completed mail surveys.

c The sample is allocated to each region in proportion to the total number of households in that region, with at least 288 comp leted

surveys required for each region to estimate the main effects and interactions under an experimental design model.

d The number of intended completed questionnaires for each survey region was rounded up so that the same number of households

received each of the 2 4 survey vers ions.

Source: U.S. EPA analysis for this report



### EPA used multiple preview and reminder mailings to promote a high response rate and minimize

the potential for non

- resp onse bias. This approach follows Dillman et al. ( 2009 ) , which is am ong

the most commonly cited sources for survey logistics management. Households were selected

from the U.S. Postal Service Digital Sequence File (DSF) of residences which, i n total

, covers 97

percent of residences in the U nited States. EPA also conduct ed a follow

- up study of households

that did not return a completed mail survey to determine whether survey non

- respondents are

fundamentally different than survey respondents. The follow

- up survey included demographic

and attitudinal questions.



## 11.4 Mail Survey Re sponses

P ublished guidance for SP survey design recommends conducting a pilot study to inform

potential changes to other survey versions ( Arrow et al. 1993 ; Bateman et al. 2002 ) . Following

this guidance, EPA undertook the Northeast region of the survey in advance of the other regions

and national survey , as described in the ICR for the 316(b) SP survey ( USEPA 2011 c)

. After

review of the Northeast survey responses, EPA received approval from the Office of Management

and Budget (OMB) to implement the remaining survey regions (Inland, Southeast, and Pacific)

and the national survey. EPA fielded the r emaining survey versions in October 2011. EPA

received a total of 2,313 completed mail surveys. Table 11

- 4 summarizes the number of

completed surveys received and the response rate (responses as a percentage of mailed surveys

minus undeliverable surveys). The average response rate was 32 percent. This response rate is

comparable to various other recent mail surveys in the SP literature ( e.g., Boyle and Özdemir

2009 ; Hanley et al. 2006 ; Johnston and Duke 2009 ; Johnston and Bergstrom 2011 )Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 10 

### Table 11

- 4 : Completed Survey Received and Response Rates by Survey Version

Survey Region Households

Surveyed Completed Surveys

Received Response Rate a

Northeast 1,440 421 31%

Southeast 1,920 506 29 %

Pacific 1,040 311 32%

Inland 2,480 787 35 %

National Survey 960 28 8 3 4 %

Total 7,840 2,313 32%

a The number of undeliverable surveys was subtracted from surveys mailed when calculating the response rate for each

survey region . Undeliverable surveys are those surveys that were returned to sender

. Source: U.S. EPA analysis for this report



### Analysis of the survey data across all four regions and the national survey indicates that

respondents appear to have been evaluating tradeoffs between costs and benefits of policy options

presented to them, and that WTP is responsive to scope (i.e., the q uantity of environmental

improvements across different attributes). Respondents appear to have understood and

distinguished between different types of outcomes from 316(b) regulation. About 90 percent of

respondents answered the choice experiment questions (questions 4, 5, and 6). Question 8 asked

respondents to rate the statement that the survey material was easy to understand. Only 14 percent

disagreed with that statement (see Figure 11

- 1 ). Seventy

- one percent of respondents strongly

agreed or agreed when asked in a 5

- level Likert scale question whether they were confident in

their responses to the survey questions. The vast majority indicated that they would answer the

same way if parallel questions were asked in a binding referendum, with less than three percent of

respondents indicating otherwise (see Figure 11

- 2 ).

About 75 percent of mail survey respondents were under age 65 and the majority of those

completing the survey (63 percent) were male. About 87 percent of respondents selected “white”

for racia l category. For additional information on the demographic characteristics of respondents

see EPA’s survey analysis memo to the 316(b) rulemaking record (USEPA 2012).Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 11



### Figure 11

- 1: Summary of Responses to Regarding Respondent

Understanding across All Su rveysBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 12



### Figure 11

- 2: Summary of Responses Regarding Respondent Confidence

across All Surveys



## 11.5 Non

- Response Study

EPA conducted a follow

- up study of households that did not return a completed mail survey to

identify whether survey non

- respondents are funda mentally different than survey respondents in

certain attributes

. The follow

- up study included a set of key attitudinal questions and socio

demographic variables that are most likely to be associated with WTP for reducing fish mortality

from CWISs and impr ovements in fish populations and conditions in the affected aquatic

ecosystems. Section 11.5.1 describes the non

- response sample and Section 11.5.2 describesBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 13 

### statistical tests that EPA conducted comparing the main mail survey sample and the non

- response

sample.

11.5.1 Non

- Response Sample

EPA implemented the follow

- up study using two subsamples: the first subsample received a

paper questionnaire via U.S. Postal Servic e Priority Mail®, and the second subsample was

surveyed by telephone. Both non

- response subsamples were asked the same set of attitudinal and

demographic questions. It took participants approximately five minutes to complete the follow

- up

study.

EPA’s targ et sample across all regions for the non

- response study was 600 completed non

response surveys

. This is the sample size required for a two

- sided test showing a difference of 12

percentage points to be rejected with statistical power of 80 percent. In total , EPA planned to

achieve 400 complete d surveys in the Priority Mail subsample and 200 complete d questionnaires

in the telephone subsample. EPA allocated the initial target non

- response complete d surveys to

each survey region in proportion to the mail surve y sample size of each region . The priority mail

subsample was conducted in advance of the telephone subsample. EPA conducted additional

telephone calls to ensure that it reached targets for the total number of complete non

- response

surveys in each region, if the priority mail response fell short of the target. The number of

completed non

- response surveys is summarized in Table 11

- 5 by subsample. Overall response

rates for the non

- response study ranged from about 21.5 percent in the Southeast to 29.5 percent

for the national survey.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 14 

### 11.5.2 Statistical Testing of Mail Survey and Non

- Response Data

EPA compared the respondent and non

- respondent samples statistically according to eight

characteristics to evaluate potential for non

- response bias:

1. Age : age of the household member completing the survey

2. Gender : gender of the household member completing the survey

3. Education : highest level of education completed by the household member complet ing

the survey

4. Employment : whether the survey participant is currently employed (yes/no)

5. Hispanic or Latino origin : whether the participant is of Hispanic or Latino ethnicity

(yes/no)

6. Race : racial category of the participant

7. Income : annual household income

8. Importance of protecting aquatic ecosystems: attitudinal question asking the participant

to rate how important he or she considers the protection of aquatic ecosystems. Table 11

- 5: Completed Non

- Response Surveys Received and Response Rates by

Survey Region and Survey Mode

Survey Subsample/Survey Region Sample Size Completed Surveys Response Rate

Priority Mail Subsample

Northeast 146 48 32.9%

Southeast 297 71 23.9%

Inland 389 127 32.6%

Pacific 159 58 36.5%

National Survey 146 58 39.7%

Telephone Subsample

Northeast 331 63 19.0%

Southeast 410 81 19.8%

Inland 356 71 19.9%

Pacific 160 20 12.5%

National Survey 125 22 17.6%

Total Non

- Response Sample

Northeast a 426 111 26.1%

Southeast 707 152 21.5%

Inland 745 198 26.6%

Pacific 319 78 24.5%

National Survey 271 80 29.5%

a For the Northeast region, EPA included 51 households which did not return the Priority Mail questionnaire within the

telephone subsample in order to achieve the target number of completes. As a result, the total sample size for the

Northeast is less than the sum of the Priority Mail and telephone subsamples.

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 15 

### T able 11

- 6 summarizes the characteristics of the respondents to the main surveys and non

response surveys.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 16 

### Table 11

- 6: Characteristics of the Main and Non

- Response Samples by Survey Region a

Statistic Northeast Southeast Inland Pacific National Survey

Main Non

- Response Main Non

Response Main Non

Response Main Non

Response Main Non

Response

Age

Average age 54.6 53.7 54.3 56.6 53.7 56.1 52.8 49.7 54.2 53.2

Percent under 65 74.6% 73.9% 74.1% 68.9% 76.3% 67.4% 76.1% 89.6% 72.7% 70.0%

Gender

Percent male respondents 63.9% 44.5% 62.3% 46.7% 64.6% 51.3% 62.7% 55.1% 60.4% 45.6%

Employment

Percent currently employed 63.6% 62.7% 59.2% 57.9% 64.4% 54.4% 65.0% 68.4% 60.2% 57.0%

Percent employed under age

65 76.9% 79.3% 75.0% 79.4% 76.9% 73.8% 80.3% 74.6% 72.5% 72.7%

Educational Attainment b

Bachelor’s Degree or

Higher 45.9% 46.4% 44.1% 34.0% 43.1% 30.1% 50.8% 44.2% 46.9% 39.3%

Race and Ethnicity c

Percent white respondents 86.6% 85.7% 82.3% 78.8% 91.0% 93.0% 84.7% 75.7% 83.4% 80.8%

Percent Hispanic or Latino

Origin 5.1% 5.6% 9.9% 9.9% 3.4% 5.2% 13.3% 13.3% 7.0% 11.4%

Total Household Income d

Average $88,880 $81,480 $75,588 $74,179 $73,567 $59,598 $96,144 $79,306 $79,496 $63,681

Standard Deviation $69,309 $68,486 $62,618 $66,760 $57,261 $54,966 $71,282 $67,757 $60,972 $57,415

Percent >$60,000 55.7% 49.0% 48.1% 44.8% 48.1% 31.0% 57.2% 50.0% 51.9% 37.5%

Imp ortance of Aquatic Ecosystems e

Average Ranking 4.0 4.0 3.9 4.0 3.8 3.9 4.0 4.1 3.9 3.9

a Respondents who did not answer a given demographic question were excluded when calculating percentages.

b The surveys included six categories for educational attainment: (1) less than high school, (2) high school or equivalent, (3) high school + technical school, (4) one or more years of college, (5)

bachelor’s degree, and (6) graduate degree.

c The surveys i nclude six categories for education attainment: (1) American Indian or Alaskan Native, (2) Black or African American, (3) Nat ive Hawaiian or Other Pacific Islander, (4) Asian, (5)

White, and (6) Other. Respondents could select more than one racial category . The “Percent white respondents” presented above includes respondents that selected other racial categories in addition

to white.

d The survey asked respondents to select one of eight categories for annual household income. The average and standard devia tion reported here were calculated using the midpoint of each range.

The amount of $250,000 was used for the highest income category included in the survey (“$250,000 or more”).

e Respondents were asked to rate the “importance of protecting aquatic ecosyst ems” on a scale of 1 to 5, 1 being “not important” and 5 being “very important”.

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 17 

### For categorical or ordinal variables (i.e., all variables except age), EPA tested for statistical

differences between respondents and non

- respondents using both the Mann

- Whitney U Test and

χ 2 

### Test of Proportions. EPA used the Student’s t

- test for age, the only cardinal variable in the

group. EPA considered a variable to be statistically different across the two populations if the null

hypothesis of equality could be rejected at p <0.10. Table 11

- 7 presents the variables which were

found to be statistically d ifferent for each survey region and the national survey.

Table 11

- 7: Variables Found to be Statistically Different Across Respondent and

Non

- Respondent Samples

Survey Region Variables

Northeast Gender, education

Southeast Gender, education

Pacific Importance of aquatic ecosystems, race

Inland Age, gender, education, employment a , and income

National Survey Gender, income

a Employment was not statistically different for respondents under the age of 65.

Source: U.S. EPA analysis for this report



### In general, attitudes towards the protection of aquatic ecosystems tended to be similar across

samples for most survey regions, with a large majority of respondent rating it as important. No

statistical difference was found in rating the protection of aquati c ecosystems among respondents

and non

- respondents, the only exception being the Pacific region. The average ranking was

slightly higher for non

- respondents than respondents in the Pacific region. The vast majority of

participants in the non

- response study also indicated that government should be at least somewhat

involved in environmental protection. 67



### EPA developed for the weights for those demographic variables which were found to be

statistically different in each region to account for over

- and under

- r epresented groups in the mail

survey dataset used for model estimation. Section 11.6.3 describes weight development.



## 11.6 Random Utility Model

EPA’s analysis of the 316(b) survey data is grounded in the random utility model presented by

Hanemann ( 1984 ) and McConnell ( 1990 ) . The use of the r andom utility model is standard in the

SP literature for attribute

- based SP data, such as that provided by choice experiments ( Bateman et

al. 2002 ; Bennett and Blamey 2001 ) . Under the model, “utility is the sum of systematic [or

observed] and random [or unobserved] components” ( Holmes and Adamowicz 2003, p. 189 ) . The

individual choices are systematic (i.e., deterministic) from the perspective of the individual, while

the random component refle cts preferences which are unobservable to the researcher, among

other things ( Holmes and Adamowicz 2003 ) . The mod el is applied extensively within SP research,

and allows for the calculation of well

- defined welfare measures (i.e., WTP ) from choice

experiment models ( Bennett and Blamey 2001 ; Louviere et al. 2000 ) . This section describes

67 Multiple questions in the main mail surve y asked respondents about their views toward government and

environmental protection (e.g., questions 1

- 5 and 1

- 6 on page 3 of the mail survey). However, the wording of

these questions differed from the question included in the non

- response survey, such th at they are not directly

comparable.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 18 

### EPA’s model specification (Section 11.6.1 ), model estimation (Section 11.6.2 ), approach for

estimating weights (Section 11.6.3 ), and model results (Section 11.6.4 ).

11.6.1 M odel Specification

Table 11

- 8 lists and defines the variables included in the random utility models. For each choice

option, the respondent may choose Option A, Option B, or No Policy, where No Policy is

characterized by zero change in all attributes.

Tab le 11

- 8: Summary of Variables Included in the Random Utility Models for the

Regional and National Surveys

Variable Variable Definition

CONSTANT Alternative specific constant (ASC) associated with No Policy, or choice of neither

plan.

COM_FISH Score showing the overall health of commercial and recreational fish populations.

FISH_POP Score showing the estimated size of all fish populations compared to natural levels

without human influence.

FISH_SAV Score showing the percentage point reduction in young fish lost compared to current

levels.

AQUATIC Score showing the ecological condition of affected areas, compared to the most natural

waters in the region.

COST The increase in annual household cost, in unavoidable price increases for products and

s ervices, including electricity and common household products.

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 19 

### The linear econometric specification of the model of the observable component of utility appears

as:

v(



) =  0 

### +  1 

### ( Δ

fish_sav ) +  2 

### ( Δ com_fish ) +  3 

### ( Δ fish_pop ) (11

- 1)

+  4 

### ( Δ aquatic ) +  5 

### ( cost )

This specification allows EPA to estimate the relative linear “main effects” of the four

environmental attributes on utility. The estimated constant (  0 

### ) represents utility associated with

the relevant ASC (alternative specific constant). This is a fixed coefficient estimated within

choice experiments that is designed to capture “systematic but unobserved information about why

respondents chose a particular option (that is, unrelated to choice set attrib utes)” ( Bennett and

Blamey 2001 ) . ASCs become statisti cally significant in choice experiment models when elements

other than the independent variables, or choice attributes, in the model influence respondents’

choices ( Kerr and Sharp 2006 )

. Here, EPA included an ASC for No Policy; this variable takes a

value of 1 for the No Policy option and a value of 0 for either of the two available policy options.

Hence,  0 

### in this model represents the fixed utility associated with No Policy (mainta ining the

status quo), holding all other attribute changes at zero.

E conomic theory provides guidance regarding some, but not all, aspects of model specification

for mixed logit models within SP choice experiments

. For example, the parameter on program

co st is expected to have a negative sign, reflecting a positi ve marginal utility of income

. Com parison of model output suggested that the greatest robustness of results is achieved when

cost is modeled as fixed rather than random. This specification also avo ids well

- known

challenges for welfare estimation associated with the specification of a random coefficient on

program cost ( Hensher and Greene 2003 ; Scarpa et al. 2008 ; Train and Weeks 2005 )

. Coefficients

on all variables except that on program cost ( cost ) are specified as random with a normal

distribution

.

11.6.2 Model Estimation

EPA estimated t he random utility model s for all four regions and the national survey using

maximum likelihood mixed logit with Halton draws. As described in Chapter 8, Halton draws, or

“intelligent draws”, are “generated number theoretically rather than randomly and so successive

points at any stage ‘know’ how to fill in the gaps left by earlier points” ( Bhat 2001, p. 684 )

. The

mixed logit model is an approach for modeling preference heterogeneity based on the assumpti on

that individuals’ preferences are randomly distributed and that heterogeneity in population

preferences can be captured by estimating the mean and variance of the random parameter

distributions ( Holmes and Adamowicz 2003 )

. As described by Henscher and Greene ( 2003 ) , “the

mixed logit model offers an ex tended framework within which to capture a greater amount of

behavioral choice making. Broadly speaking, the mixed logit model aligns itself much more

closely with reality than most discrete choice models. This is because every individual has their

own int er

- related systematic and random components for each alternative in their perceptual

choice set(s)” (p. 170). It is a highly flexible model that “obviates the three limitations of

standard logit by allowing for random taste variation, unrestricted substit ution patterns, and

correlation in unobserved factors over time” ( Train 2009, p. 134 )

.

The mixed logit model allows for the possibility of preference heterogeneity but cannot attach

specific parameter values to particular individuals. That is, the model relaxes the assumption ofBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 20 

### respondents being identical, which is required for multinomial logit estimation, and replaces it

with a less restrictive assumption that respondents’ preferences follow distribution. The theory

and methods of mixed logit modeling are well

- established ( Train 2009 ) , and it has now become

standard practice in many areas of research ( Hensher and Greene 2003 ) . These models allow for

coefficients on attributes to be distrib uted across sampled individuals according to a set of

estimated coefficient s and r esearcher

- imposed restrictions

. The models are evaluated numerically

using random draws because choic e probabilities take the form of an integral over a mixing

distribution that does not have a closed form ( Train 2009 ) . The l ikelihood simulation for the

models estimated by EPA used 300 Halton (random) draws. 68 

### Coefficients on all variables except

that on program cost ( cost ) are specified as random with a normal distribution. As discussed in

the previous section, the greatest model robustness was achieved when cost was specified as

fixed.

11.6.3 Approach for Estimating Weights

EPA developed weights for each region to account for the over

- and under

- representation of

demographic groups in the mail survey data for each reg ion. As described in Section 11.5.2

, EPA

statistically compared a set of key demographic characteristics across respondent and non

respondent samples. For those characteristics which were statistically different, EPA developed

weights such that the weight given to particular subgroup of individuals within the analyzed

sample (sample proportion) matches the weight for the same subgroup in the overall (population

proportion). 69 

### EPA used data from Census 2010 and the American Community Survey (ACS) as

the target for the desired population.

EPA applied one of two approaches to calculate the weights assigned to each respondent in the

mail survey dataset: (1) subgroup weighting and (2) raking. The combination of demographic

characteristics dictated which approach was applied for a given region:

 Subgroup weighting

– Applied if the population proportions for each subgroup could be

calculated directly based on data from ACS and Census 2010. For example, the 2010

ACS reports educational attainment by gender, the two characteristics which were

statistically different in the Northeast and Southeast survey regions. Because separate

proportions for males and females for educational attainmen t were available according to

gender, EPA could calculate population proportions directly from the data for these

regions. EPA also used subgroup weighting for race in the Pacific region.

 Raking

– Used when the number and combination of variables are such that EPA could

not calculate the grid of sample and population proportions directly using Census or ACS

data. Raking uses an iterative process to match the subpopulations weights to the

population statistics, using targets for the individual demographic ch aracteristics of

interest. Additional detail on raking is provided by ( Izrael et al. 2004 ) This appr oach was

68 EPA also ran the models with 200, 400, and 500 Halton draw to assess model robustness. They indicate that the

models are relatively robust (stable) across different numbers of draws, for the “fish saved” attribute in particular.

69 EPA could not develop weights for the importance of aquatic ecosystems in the Pacific region because a statistical

target (e.g., Census for ACS data) was unavailable (adjusting would have increased WTP). EPA did not weight

based on employm ent in the Inland region because employment was not statistically different for respondents

under the age of 65 and EPA weighted for age.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 21 

### used to weight for age, gender, education, and income in the Inland region and for gender

and income for the national survey.

11.6.4 Model Results

Mixed logit model statistics suggest good statistical fit across the regional survey versions. Table

11

- 9 p resents results for both linear and weighted linear models for each survey region. The

following discussion, however, focuses on the weighted model since this model allows to correct

for differences in demographic characteristics of respondents and genera l population. For the

weighted linear models, t he χ 2 

### values ranged from 483. 07 to 1,119.22 (all with d.f. = 21,

p<0.0001) and pseudo

- R 2 

### ranged from 0.23 to 0.31 for the regional surveys. The national

weighed linear model has a χ 2 

### value of 394.0 ( d.f.

= 21, p<0.0001) and pseudo

- R 2 

### of 0.23.

The variable for fish saved ( fish_sav ) is significant in all four regional weighted linear models

, commercial fish populations ( com_fish ) is significant in two of the four regional models , and

aquatic ecological condi tion ( aquatic ) is statistically significant in two of the four regional

models. The significance of these attributes suggests positive implicit prices; that is, positive

WTP for changes in individual attributes. Analogous outcomes are common in choice

exp eriments across the literature addressing aquatic ecological improvements, with the substantial

majority of choice attributes found to have statistically significant impacts ( Carlsson et al. 2003 ;

Do and Bennett 2009 ; Johnston et al. 2011a ; Johnston et al. 2011b )

. The ASC was signific ant in

three of the five models.

As noted above, all variables except cost represent percent progress toward the upper ecological

reference condition (100 percent ). Hence, these coefficients may be directly interpreted as the

relative marginal utility derived from a one percentage point change in each ecological attribute

. In the estimated Southeast weighted linear model, for example, marginal utility is greatest (per

percentage point) for increases in commercial fish populations ( com_fish ), with lower (but still

statistically significant) impacts associated with changes in the number of fish saved ( fish_sav ).

The percentage differences in environmental attributes across the options presented were much

larger for the number of fish saved ( fish_sav ) than for the other variables. Therefore, the

coefficients on fish_sav tend to be lower than on other environmental attributes. Following

recommended practice in SP valuation, these variations correspond with realistic ecological and

policy expectations for reg ulatory outcomes ( Bateman et al. 2002 )

. The lack of significance of

com_fish

, all_fish and aquatic in some models may be related to the relatively small changes in

these attributes included in the survey, relative to effects on fish saved, which were mu ch larger.

There are only two coefficients of unexpected sign and neither is significant.

Direct comparisons of statistical fit measures across different choice experiments in the literature

can be misleading and should be viewed with extreme caution. Ma ny measures of model fit are

not directly comparable across different datasets or models. Nonetheless, the overall statistical fit

of the model appears broadly similar to choice experiments found in the published literature

addressing environmental improve ments both worldwide and in the United States. Johnston et al.

(2011a,b), in a similar survey of ecological improvements, report a pseudo

- R 2 

### of 0.30. By

comparison, using a commonly reported measure of model fit (pseudo

- or McFadden R 2 

### ),

Campbell et al. ( 2009 ) report a pseudo

- R 2 

### of 0.20; Carlsson et al. ( 2003 ) report pseudo

- R 2 

### values

between 0.12 and 0.27; Do and Bennett ( 2009 ) repo rt pseudo

- R 2 

### between 0.07 and 0.18; and

Colombo and Hanley ( 2008 ) report values between 0.16 and 0.36. Other measures of fit are alsoBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 22 

### similar, although again, cauti on must be exercised when drawing conclusions from any such

comparisons across models.

EPA also tested alternative models and conducted various validity tests using the survey data and

model results

. This included investigation of non

- linear functional forms, including stepwise

models and inverse hyperbolic sine (IHS) models, as it is possible that there is diminishing

marginal WTP for fish saved. However, EPA found that model results did not improve under

non

- linear specifications. For the stepwise models

, EPA coded fish saved as a set of binary

(dummy) variables instead of a continuous variabl e for each survey region and results are

intuitive. Resulting WTP across steps seems to suggest a generally linear relationship. EPA

designed the IHS model for each survey region to capture potential nonlinearities in WTP for fish

saved. R eview of IHS resu lts indicate that the fit and intuitiveness var ies somewhat across

models, but in general, models do no t improve upon linear speci fication. Results for these

alternative models are included in the 316(b) rulemaking docket. Based on these results, EPA

used the weighted linear specification as its primary models in this report for preliminary

assessment of WTP. The Agency also notes that with only three attribute levels (per region), it

would be difficult to capture non

- linearities in the fish saved attribute

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 23 

### Table 11

- 9 : Linear and Weighted Linear Model Results

Variable Coefficient a,b

(Standard Error)

Northeast Southeast Inland Pacific National

Linear Weighted

Linear Linear Weighted

Linear Linear Weighted

Linear Linear Weighted

Linear Linear Weighted

Linear

Random parameters in utility functions

CONSTANT - 0.56919

- 0.52259

- 0.19920

- 1.63728***

- 3.56478***

- 3.53149*** 0.18220 0.18797

- 2.09328***

- 1.49361***

(0.42972) (0.37095) (0.30806) (0.33244) (0.58123) (0.56418) (0.45022) (0.49719) (0.45875) (0.48000)

COM_FISH 0.13145* 0.21316*** 0.12662*** 0.08871* 0.06082** 0.02335 0.15056** 0.11072 0.08925 0.07350

(0.06765) (0.05180) (0.04660) (0.04991) (0.02946) (0.02773) (0.07282) (0.08606) (0.06077) (0.06015)

FISH_POP 0.13602 0.06502 0.14670**

- 0.02800 0.02175 0.01007 0.21176* 0.16039 0.02838 0.19524*

(0.10508) (0.09369) (0.06364) (0.07830) (0.04405) (0.04182) (0.11078) (0.12739) (0.10735) (0.11069)

FISH_SAV 0.02852*** 0.02900*** 0.02183*** 0.02596*** 0.01483*** 0.01597*** 0.04389*** 0.03645*** 0.02241*** 0.02116***

(0.00537) (0.00464) (0.00462) (0.00507) (0.00439) (0.00393) (0.00698) (0.00683) (0.00585) (0.00665)

AQUATIC 0.17102 0.20135* 0.24591*** 0.06163 0.04630 0.04864 0.34171*** 0.31963**

- 0.12105

- 0.10694

(0.10955) (0.10306) (0.07741) (0.08284) (0.05036) (0.04478) (0.11007) (0.13338) (0.11085) (0.17007)

Non

- random parameters in utility functions

COST - 0.02677***

- 0.02106***

- 0.03868***

- 0.04209***

- 0.03356***

- 0.03280***

- 0.02756***

- 0.02177

- 0.03739***

- 0.03294***

(0.00513) (0.00453) (0.00417) (0.00502) (0.00298) (0.00284) (0.00518) (0.00534) (0.00520) (0.00578)

Derived standard deviations for parameter distributions

sdCONSTANT 0.37257 0.19465 0.00256 0.29835 5.91389*** 5.18984*** 0.09866 0.01702 0.18221 0.08915

(1.01103) (1.01704) (4.10600) (1.20020) (0.97758) (0.89828) (1.0278) (6.00963) (2.51713) (1.29659)

sdCOM_FISH 0.43573*** 0.13635 0.26774*** 0.17567 0.12217* 0.12565** 0.30101 0.32221* 0.27147 0.30494*

(0.12740) (0.16831) (0.09727) (0.12699) (0.06487) (0.06115) (0.30183) (0.18467) (0.41960) (0.17425)

sdFISH_POP 0.51160** 0.58902*** 0.04792 0.34982 0.07409 0.12423 0.22539 0.23578 0.54531 0.64049**

(0.21996) (0.18116) (0.39545) (0.21724) (0.07769) (0.08723) (0.41340) (0.25612) (1.33621) (0.30347)

sdFISH_SAV 0.05755** 0.04375*** 0.05697*** 0.06335** 0.04838*** 0.04359*** 0.05362 0.05332*** 0.05514*** 0.08467***

(0.02241) (0.01269) (0.01339) (0.02852) (0.00615) (0.00554) (0.04330) (0.01546) (0.01773) (0.02698)

sdAQUATIC 0.61933*** 0.64976 0.45656*** 0.77220 0.44593*** 0.33881*** 0.35905 0.29608 0.81244 1.19443*

(0.22791) (0.44299) (0.12343) (0.60628) (0.08826) (0.08224) (0.57884) (0.26966) (0.53981) (0.72258)

Model significance

Model χ

2 582.48 538.59 741.92 700.17 1,191.94 1,119.22 578.74 483.07 413.53 394.00

(d.f. = 21,

p<0.0001) (d.f. = 21,

p<0.0001) (d.f. = 21,

p<0.0001) (d.f. = 21,

p<0.0001) (d.f. = 21,

p<0.0001) (d.f. = 21,

p<0.0001) (d.f. = 21,

p<0.0001) (d.f. = 21,

p<0.0001) (d.f. = 21,

p<0.0001) (d.f. = 21,

p<0.0001)

Pseudo

- R 2 0.24 0.23 0.24 0.24 0.25 0.24 0.32 0.31 0.24 0.23

a For random parameters in utility functions, coefficients represent the estimated means of random parameter distributions.

b ***, **, * indicates s ignificance at 1%, 5%, 10% level s, respectively

. Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 24 

### 11.6.5 Validity Tests

Generally accepted economic thinking maintains that obtaining greater quantities of a desired

economic good will lead to higher levels of consumer utility ( Heberlein et al. 2005 ) . A scope test

looks at whether respondents’ WTP is greater for (or not less than) a good that is somehow larger,

either in a quantitative or qualitative sense. There are two types of scope tests. An internal scope

(or within

- sample) test involves comparing multiple WTP estimates from SP responses collected

from the same responden ts” while an external scope test “employs split

- sample designs to

compare WTP estimates across samples from the sample population” (Lew and Wallmo 2011). A

major criticism of stated preference studies had been that this relationship

– consumers preferring

greater quantities of a good over lesser quantities of that same good

– is sometimes violated when

valuating environmental amenities. Evidence provided by these early findings prompted the 1993

NOAA Panel on Contingent Valuation to regard surveys that exhib it insensitivity to scope as

“unreliable” ( Arrow et al. 1993 ) . Compared to tests of scope in contingent valuation, the role of

external scope tests within choice modeling has receiv ed much less attention in the literature ( cf.,

Heberlein et al. 2005 )

.

Unlike open

- ended contingent valuation questions, choice experiments provide a direct

mechanism for respondents to react to the scope and scale of resource changes, by enabling

respondents to compare polic y options with different levels for each attribute. As noted by

Bennett and Blamey ( 2001, p. 231 ) , “internal scope tests are automatically available from the

results of a [choice modeling] exercise.” That is, choice experiments already include “internal”

scope tests because resp ondents compare levels across Options A and B. Respondents express

WTP for incremental improvements in environmental attributes through their selection of No

Policy, Option A, or Option B within the choice questions and model results indicate that WTP is

h igher for an option with a greater level of goods. Within a choice modeling context, external

scope tests may also be confounded by differences in the implied choice frame ( Bennett and

Blamey 2001 ) . These caveats aside, an external scope test can provide some additional insight

into response patterns, and some researchers view these tests as a “stronger” form of validation

than internal scope tests. EPA therefore implemented a form of external scope tests to evaluate

this form of validity using the mail survey data for each survey region. As the experimenta l

design was not originally conceived to allow formal tests of external scope, the following test is

illustrated as an alternative approach that is possible given the current experimental design and

available data. 70



### EPA used a split sample to look at respo ndents’ selections for Options A and B separately and

obtain a more “external” perspective based on the concept that, if all else is orthogonal

(effectively equal), a choice option with more fish saved should be chosen more often than a

choice option with fewer fish saved. Splitting out Options A and B provides a more convincing

test, because it shows that the same patterns apply to both Options A and B. EPA limited the test

to the fish saved attribute because fish saved is the only attribute that EPA is us ing at this time to

estimate WTP for regulatory options. To distinguish this test from the “internal” scope tests

automatically performed by choice experiments, it is implemented using a split sample of choice

options viewed in isolation. To implement the test, EPA first created a dataset only of

70 External scope tests were recommended for contingent valuation studies (Arrow et al. 1993) . Because s cope tests

are automatically a vailable from the results of a choice modeling exercise (Bennett and Blamey ( 2001, p. 231 )

, accounting for external scope tests in the experimental design was not necessary.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 25 

### observations on Option A for all survey responses, along with a dummy (0

- 1) variable indicating

whether that option was chosen. 71 

### EPA then further split this sample into three sub

- samples based

on the three levels o f fish saved assigned to each region within the experimental design. Using the

Pacific region as an example, the three sub

- samples are: (1) observations on Option A when

percent fish saved = 95 percent, (2) observations on Option A when percent fish saved = 50

percent, and (3) observations on Option A when percent fish saved =2 percent. Because of the

near orthogonal nature of the experimental design, all other attribute levels should be

approximately equal across each of these three sub

- samples. Given this split sample, EPA

expected to observe the greatest proportion of respondents choosing Option A in sub

- sample (1),

followed by sub

- sample (2) and then (3). This order would establish external sensitivity to scope.

EPA then repeated the same test for Option B.

The results of the scope sensitivity test are presented in Table 11

- 10 . The results tables illustrate

means and standard deviations for respondent choices for each observation of Option A and

Option B. The external scope tests for split samples of both Options A and B demonstrate scope

sensitivity for all survey regions, as indicated by economic theory. The values of other choice

attributes ( com_fish

, fish_pop

, aquatic , and cost ) are approximately equal over the split samples,

as one would expect given the experimental design. The proportion of respondents choosing

Option A declines as the percentage of fish declines for all survey regions. Using the Inland

region as an example, the proportion of respondents choosing Option A declines from 0.42 to

0.39 t o 0.37 as the percentage of fish saved declines from 95 percent to 75 percent to 55 percent.

Option B exhibits a similar decline in respondent choice with fish saved all survey regions. EPA

used the χ

2 

### test of proportions to examine whether the proportions were statistically different

across levels of fish saved for a given option. The null hypothesis of equality in proportions is

rejected at p <0.10 for all regions and options. This shows that respondent choices were

statistically different across levels of fish saved.

EPA also conducted further testing with the responses split by survey question as well as option

to respond to the external peer review. Using this approach, each question/option sample includes

only one choice from each respondent. The null h ypothesis of equality in proportion is rejected at

p<0,10 or better for 22 of the 30 cases (5 survey versions x 3 questions x 2 options = 30). EPA

did not generate the survey experimental design with such tests in mind, so the combination of

other choice a ttributes ( com_fish

, fish_pop

, aquatic , and cost ) vary somewhat across cases when

split by question and option, which would affect the results of this scope test in a systematic

fashion. Overall, results indicate sensi tivity to scope for fish saved.

71 Thus, each respondent is represented up to three times, once for each choice question in their survey booklet.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 26 

### Table 11

- 10: Results of the Split

- Sample External Validity Test for Each Survey Region

Region/ Percent Fish Saved Option A Option B

Mean Std. Dev. Mean Std. Dev.

Northeast

95% 0.4617 0.4992 0.4861 0.5004

50% 0.4274 0.4954 0.4415 0.4973

5% 0.2473 0.4320 0.2345 0.4243

χ 2 Test of Proportions a 42.43

(d.f.=2; p<0.001) 58.81

(d.f.=2; p<0.001)

Southeast

90% 0.4796 0.5001 0.4000 0.4904

55% 0.3593 0.4803 0.2939 0.4560

25% 0.2922 0.4553 0.2602 0.4392

χ 2 Test of Proportions a 35.58

(d.f.=2; p<0.001) 23.29

(d.f.=2; p<0.001)

Inland

95% 0.4225 0.4943 0.3679 0.4825

75% 0.3897 0.4880 0.3234 0.4681

55% 0.3652 0.4818 0.2712 0.4449

χ 2 Test of Proportions a 5.00

(d.f.=2; p<0.082) 15.77

(d.f.=2; p<0.001)

Pacific

95% 0.4929 0.5008 0.5993 0.4909

50% 0.3722 0.4843 0.4118 0.4931

2% 0.1932 0.3955 0.2333 0.4237

χ 2 Test of Proportions a 53.89

(d.f.=2; p<0.001) 76.63

(d.f.=2; p<0.001)

National

95% 0.4753 0.5003 0.4604 0.4994

55% 0.3571 0.4801 0.3013 0.4598

25% 0.3269 0.4700 0.2737 0.4466

χ 2 Test of Proportions a 13.60

(d.f.=2; p<0.001) 24.06

(d.f.=2; p<0.001)

a The null hypothesis is that the proportion of respondents choosing an option is equal for all percentage fish saved.

Source: U.S. EPA analysis for this report



## 11.7 Estimation of Implicit Prices and WTP

EPA used the results of the random utility models presented in Table 11

- 9 to estimate the implicit

price or marginal annual WTP for a one percentage point change in each of the four

environmental attributes within each survey region. This represents WTP per household, per year,

for a one percentage point change in the correspon ding choice model attribute. For example, one

could calculate the marginal WTP for each additional percentage increase in fish saved , holding

all else constant. If utility is modeled as a linear function of attributes, implicit prices may be

calculated as IP

a 

### = ⁄ , where β

a 

### is the estimated coefficient on a n environmental attribute

(e.g., change in fish saved ), and β

n 

### is the coefficient on program cost . Assuming a linearBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 27 

### preference function as estimated above, compensating surplus (or household WTP) f or any given

policy option may be calculated as: 72



### WTP = (11

- 2)

where the delta ( ) represents a cha nge in the attribute in question. That is, total WTP for a policy

change is calculated as the sum of the product of implicit prices and corresponding attribute

changes. Once a preference function is estimated, the decision to include or exclude the ASC

( co nstant ) in subsequent welfare estimation must be made on a case

- by

- case basis; economic

theory alone is insufficient to determine this choice. 73 

### In this case, EPA excludes the ASC when

calculating compensating surplus, because by definition it reflects anti cipated utility change

unrelated to the included model attributes. Section 11.8 includes additional discussion of EPA’s

treatment of the ASC when analyzing regulatory benefits.

EPA notes that ecological systems are typically characterized by correlation a mong many

processes and outcomes. In the context of IM&E , for example, a reduction in A1E losses

( fish_sav ) may be correlated with changes in fish populations ( fish_pop ), aquatic ecosystem

condition ( aquatic ), and commercial fish populations ( com_fish ). It would have been difficult to

determine which attribute(s) caused respondents to choose one scenario over another had the SP

survey scenarios incorporated the same correlations . For example, if it were the case that large

reductions in IM&E always accom pany large positive effects on fish populations and large

positive effects on ecosystem condition and these correlations were embedded within survey

scenarios, it would have been difficult to estimate the specific influence of each attribute on

respondents ’ choices.

The experimental design used in the SP survey breaks this correlation and allows different survey

attributes to vary independently. This enables different respondents to view many different

possible policy outcomes, each with different combinat ions of fish_sav

, fish_pop

, aquatic and

com_fish . While some of the resulting scenarios might be unlikely in actual aquatic systems, they

are not ecologically impossible. For example, the experimental design allows respondents to

consider scenarios in wh ich large reductions in fish losses accompany very small changes in fish

populations and aquatic condition (positive changes in fish_sav in some questions are also paired

with no change in the population or aquatic condition metrics). Because attributes v ary

independently across the 72 different choice questions presented to respondents in each survey

region and national survey, it is possible to estimate the unique effects of each attribute on

individuals’ choices and therefore, values. By breaking the co rrelation between these attributes

present in ecosystems, the choice experiment design allows estimation of the independent effect

of each attribute on choices and WTP. The environmental attributes have almost zero correlation

in the resulting experimental design. This allows WTP for each ecological effect to be estimated,

independent from all other effects. Based on recommendations from external peer reviewers, EPA

is currently conducting additional analysis to assess the robustness of fish saved under alt ernative

treatments of the other environmental attributes.

72 EPA excluded the ASC when estimating the benefits of regulatory options because there is no clear theoretical

reason for inclusion. The magnitude and sign of the coefficient on ASC varies across regions.

73 The treatment of the ASC is discussed by Adamowicz et al. ( 1998 ) and Morrison et al. ( 2002 ) , among others.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 28 

### Because the mixed logit model includes random coefficients, EPA estimate s implicit prices using

the welfare simulation approach of Johnston and Duke ( 2007 ; 2009 ) following the framework

outlined by Hensher and Greene ( 2003 )

. The procedure begins with a parameter simulation

f ollowing the parametric bootstrap of Krinsky and Robb ( 1986 ) , with R =1

, 000 draws taken from

the mean parameter vector and associated covariance matrix. For each draw, the resulting

parameters are used to characterize asymptotically normal empirical densities for fixed and

random coefficients. For each of these R draws, a coefficient simulation is then conducted for

each random coefficient, with S =1000 draws taken from simulated empirical densities. Here, all

coefficient simulations draw from a normal distribu tion except for that on cost , which is fixed.

EPA calculated WTP measures for each draw, resulting in a combined empirical distribution of

R×S observations from which summary statistics were derived. All implicit prices are modeled as

the WTP for a one per centage point change in the ecological attribute , all else being constant

.

The resulting mean implicit prices and 90 percent confidence intervals for the ASC (constant) and

environmental attributes in each region are presented in Table 11

- 11

. The point es timates for

implicit prices tend to be larger for commercial fish populations, fish populations (all fish), and

aquatic ecosystem condition than for fish saved , although the statistical significance of these point

estimates varies

. This is not surprising g iven the relatively narrow range over which these

attributes vary. Hence, some point estimates that appear large may not be statistically significant,

and vice versa. In the Pacific for example, households value a one percentage point increase in

commercia l fish populations or aquatic ecosystem condition about three or eight times,

respectively, the value of a one percentage point increase in fish saved. The mean implicit prices

for a 1 percent improvement in fish saved under the regional weighted linear models range from

$0.50 in the Inland region to $1.77 in the Pacific region. The mean implicit price based on the

national survey is $0.66

. Peer reviewers indicated that EPA should focus on the regional over th e

national survey results because of concerns regarding the smaller size and representativeness of

the national sample. EPA included implicit prices based on the national survey for illustrative

purposes.

EPA did not use t he national survey results in its analysis of regulatory options. EPA found that

the implicit price for fish saved was relatively robust (stable) across mixed logit models with 200,

400, and 500 Halton draws. These additional model results are included in the 316(b) rulemaking

docket. Alth ough the discussion in this section refers to WTP for a percentage point increase in

fish saved, it is important to note that this variable represents a one percentage point reduction

relative to the level of baseline mortality (e.g., the Northeast survey booklet indicated a baseline

loss of 1.1 billion fish). This relationship between the percentage point reduction and cardinal fish

losses was specified clearly in survey questions, and the same relationship was maintained

throughout each survey . WTP per p ercentage point reduction reflects a specific quantity of fish

saved, rather than a general relative reduction of one percent from an unspecified level of IM&E

. The regional and national surveys have different baseline fish losses. EPA expected survey

resp onses to vary across the regions, because residents might have different values and baseline

losses differ.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 29 

### Table 11

- 11 : Estimated Implicit Prices for a Once Percentage Point Change in Each

Attribute, WTP per Household, per Year (2011$) a

Survey Version and Environmental

Attribute 5 th Mean 95 th

Northeast

Commercial Fish Populations ( COM_FISH ) $6.45 $10.30 $14.86

Fish Populations (all fish) ( FISH_POP )

- $4.53 $3.09 $10.89

Fish Saved ( FISH_SAV

) $0.95 $1.44 $2.07

Aquatic Ecosystem condition ( AQUATIC ) $1.44 $9.76 $19.01

Southeast

Commercial Fish Populations ( COM_FISH ) $0.16 $2.10 $4.11

Fish Populations (all fish) ( FISH_POP )

- $3.81

- $0.69 $2.48

Fish Saved ( FISH_SAV

) $0.42 $0.62 $0.83

Aquatic Ecosystem condition ( AQUATIC )

- $2.01 $1.43 $4.75

Inland

Commercial Fish Populations ( COM_FISH )

- $0.67 $0.69 $2.08

Fish Populations (all fish) ( FISH_POP )

- $1.83 $0.28 $2.48

Fish Saved ( FISH_SAV

) $0.28 $0.50 $0.70

Aquatic Ecosystem condition ( AQUATIC )

- $0.78 $1.47 $3.68

Pacific

Commercial Fish Populations ( COM_FISH )

- $1.37 $5.37 $13.60

Fish Populations (all fish) ( FISH_POP )

- $2.32 $7.71 $18.53

Fish Saved ( FISH_SAV

) $1.07 $1.77 $2.62

Aquatic Ecosystem condition ( AQUATIC ) $5.01 $15.32 $27.48

National

Commercial Fish Populations ( COM_FISH )

- $0.81 $2.22 $5.50

Fish Populations (all fish) ( FISH_POP ) $0.41 $5.82 $11.28

Fish Saved ( FISH_SAV

) $0.28 $0.66 $1.07

Aquatic Ecosystem condition ( AQUATIC )

- $12.30

- $3.52 $5.20

a The implicit prices are per percentage point increase from the specified baseline (reference) levels for each survey.

Source: U.S. EPA analysis for this report



### While 95 percent confidence intervals are rather large for com_fish

, fish_pop , and aquatic

, and

sometimes include zero in the range, the confidence intervals are rather narrow for fish saved and

do not include zero within the 95 percent confidence interval. This highlights a very specific

result of the stated preference survey, which is that the WTP to protect fish and shellfish from

impingement and entrainment, even when there are no effects on the other attributes, is greater

than zero. This is the case despite the vociferous objections of some commenters opposed to the

stated preference survey . To be clear, these benefit estimates represent an average WTP for

protecting fish and shellfish from impingement and entrainment and incorporate the responses of

all respondents, including those who expressed zero WTP . 74



## 11.8 Method for Estimating Regional B enefits

EPA used the implicit prices, or WTP per percentage point change , for fish saved ( fish_sav ) to

estimate annual monetized benefits for each survey region under the final rule and regulatory

options considered. EPA did not estimate changes or potenti al benefits associated with changes in

the other three environmental attributes. EPA’s focus on the fish saved attribute for benefits

estimation is consistent with recommendations from external peer reviewers. Peer reviewers

74 About 17 percent of survey respondents selected No Poli cy (i.e., zero WTP) for all three choice questions.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 30 

### indicated that using fish saved exclusively for benefits estimation helps to alleviate concerns

regarding overlaps in the definitions of environmental attributes and potential interactions

between environmental attributes which are not accounted for in the main effects experimental

desi gn. It also allays concerns with the degree of ecological uncertainty involved in the modeling

and prediction of effects on fish populations and aquatic ecosystems.

For each survey region, EPA calculated annual household WTP under regulatory options by

mu ltiplying the estimating percentage change in fish saved by the regional implicit price for fish

saved from Table 11

- 11 . As noted above, EPA did not include the implicit price on the ASC

within the benefits calculation. Once a preference function is estima ted, the decision to include or

exclude the ASC in subsequent welfare estimation must be made on a case

- by

- case basis;

economic theory alone is insufficient to determine this choice ( Adamowicz et al. 1998 ; Morri son

et al. 2002 )

. By excluding the ASC here (and other ecological attributes), EPA is presenting a

clean estimate of WTP for fish saved alone, without other actual or possibly speculated benefits

associated with reductions in IM& E. This approach is consistent with peer review comment that

the exclusion of the ASC “...is not a problem for the annual household WTP estimated provided

in the report for the regulatory options since these are calculated using only the marginal WTP for

a o ne unit change in fish saved” ( Applied Planning Corporation 2012, p. 34 )

.

Total annual WTP for fish saved under each regulatory option is calculated by multiplying annual

household WTP by the number of household in the region from Census 2010. EPA then

discounted and annualized regional WTP using discount rates of 3 and 7 percent. Refer to

Appendix D for additional regarding discounting and the compliance schedule. As stated

previously, the boundaries of the SP survey regions differ slightly from the proposed rule regions.

Because regional IM&E is a function of operational intake flow, EPA accounted for differences

in regional boundaries by adjusting the proposed rule compliance schedule based on state

- level

AIF data by waterbody type (i.e., coastal/estuarine or fr eshwater).



## 11.9 Results for the Final Rule and Regulatory Options Considered

As noted previously, EPA considers it premature to include the SP survey results in the

quantitative comparison of costs and benefits prior to completion of the SAB review. This section

presents preliminary benefits for the final rule and options considered to illustrate the potential

magnitude of regulatory benefits and demonstrate progress towards this effort.

Table 11

- 12 presents IM&E, percen t fish saved, and WTP per household by regulatory option.

Percent fish saved and mean household WTP for the final rule vary across regions, from less than

one percent and less than $1 in the Pacific region to 56 percent and $28 in the Inland region.

Percen t fish saved and WTP per household are lower than the final rule under Proposal Option 4

and greater under Proposal Option 2.

Table 11

- 13 presents annualized benefits by regulatory option using both 3 percent and 7 percent

discount rates. Total benefits un der the final rule for all survey regions are $1.4 billion using a 3

percent discount rate and $1.1 billion using a 7 percent discount rate. Around half of the total

benefits under the final rule are from the Inland Survey region. Total benefits under Prop osal

Option 4 are slightly less than the final rule using both 3 percent and 7 percent discount rates.

Total benefits for Proposal Option 2 are $3.4 billion and $2.3 billion using 3 percent and 7

percent discount rates, respectively, and are greater than b enefits under both Proposal Option 4

and the final rule.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 31 

### Table 11

- 12 : Reduction in A1E Losses, Percent Fish Saved and WTP per Household

(2011$) by Survey Region for the Final Rule and Options Considered

Survey Version and

Regulatory Option IM&E WTP per Household

Reduction in

A1E Losses

(in millions) Fish Saved

(%) a 5 th Mean 95 th

Northeast

Proposal Option 4 45.45 5.61% $5.31 $8.06 $11.62

Final Rule 48.86 6.03% $5.71 $8.66 $12.49

Proposal Option 2 512.53 63.23% $59.91 $90.89 $130.99

Eliminating Baseline IM&E b 594.73 73.37% $69.51 $105.47 $152.00

Southeast

Proposal Option 4 218.96 29.92% $12.49 $18.69 $24.96

Final Rule 228.54 31.23% $13.04 $19.51 $26.06

Proposal Option 2 544.48 74.41% $31.06 $46.47 $62.08

Eliminating Baseline IM&E b 663.79 90.72% $37.87 $56.66 $75.68

Inland

Proposal Option 4 348.47 51.98% $14.53 $25.74 $36.46

Final Rule 373.25 55.68% $15.56 $27.57 $39.05

Proposal Option 2 547.85 81.72% $22.85 $40.46 $57.31

Eliminating Baseline IM&E b 619.58 92.42% $25.84 $45.76 $64.82

Pacific c

Proposal Option 4 1.28 0.37% $0.40 $0.66 $0.97

Final Rule 1.36 0.39% $0.42 $0.69 $1.03

Proposal Option 2 32.63 9.40% $10.03 $16.65 $24.59

Eliminating Baseline IM&E b 52.87 15.23% $16.25 $26.97 $39.84

a When calculating percent fish saved, EPA used a baseline which reflected current technology at regulated facilities

including those facilities in CA and NY that are subject to state regulations. This differs from the rest of the benefits

analysis, where E PA assigns these facilities baseline IM&E reductions commensurate with technologies required by the

state regulations. This approach is consistent with the survey materials which were based on total IM&E. Fish saved under

the elimination of baseline IM&E c an be less than 100 percent because EPA does attribute IM&E reductions at facilities

subject to state regulations to the existing facilities rule.

b This hypothetical scenario reflects the benefits that would be achieved if all IM&E were eliminated.

c The calculation of Fish Saved (%) for the Pacific survey region includes reductions in A1E losses at Hawaii facilities.

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 32 

### Table 11

- 13 : Annualized Monetized Benefits (millions of 2011$)

Survey Version and

Regulatory Option 3 % Discount Rate 7 % Discount Rate

5 th Mean 95 th 5 th Mean 95 th

Northeast

Proposal Option 4 $90.6 $137.4 $198.1 $69.8 $105.9 $152.7

Final Rule $97.4 $147.8 $212.9 $75.0 $113.9 $164.1

Proposal Option 2 $824.0 $1,250.1 $1,801.7 $535.6 $812.7 $1,171.2

Eliminating Baseline

IM&E a $1,545.1 $2,344.2 $3,378.6 $1,537.4 $2,332.5 $3,361.7

Southeast

Proposal Option 4 $297.1 $444.5 $593.7 $229.6 $343.6 $458.9

Final Rule $310.2 $464.0 $619.8 $239.7 $358.7 $479.1

Proposal Option 2 $634.4 $949.1 $1,267.8 $422.9 $632.8 $845.2

Eliminating Baseline

IM&E a $1,167.4 $1,746.6 $2,333.0 $1,161.6 $1,737.8 $2,321.3

Inland

Proposal Option 4 $436.7 $773.4 $1,095.6 $339.5 $601.2 $851.7

Final Rule $468.0 $828.8 $1,174.0 $363.8 $644.2 $912.6

Proposal Option 2 $603.1 $1,068.2 $1,513.1 $414.3 $733.7 $1,039.3

Eliminating Baseline

IM&E a $1,006.9 $1,783.3 $2,526.1 $1,001.9 $1,774.3 $2,513.5

Pacific b

Proposal Option 4 $4.7 $7.8 $11.5 $3.7 $6.1 $9.0

Final Rule $5.0 $8.2 $12.1 $3.9 $6.5 $9.5

Proposal Option 2 $98.3 $163.2 $241.0 $69.5 $115.4 $170.4

Eliminating Baseline

IM&E a $251.8 $418.0 $617.3 $250.6 $415.9 $614.2

Total for Regional Surveys

Proposal Option 4 $829.1 $1,363.1 $1,898.8 $642.6 $1,056.8 $1,472.2

Final Rule $880.5 $1,448.8 $2,019.0 $682.5 $1,123.2 $1,565.3

Proposal Option 2 $2,159.9 $3,430.7 $4,823.7 $1,442.4 $2,294.5 $3,226.1

Eliminating Baseline

IM&E a $3,971.3 $6,292.0 $8,854.9 $3,951.4 $6,260.5 $8,810.6

a This hypothetical scenario reflects the benefits that would be achieved if all IM&E were to be eliminated.

b The calculation of benefits for the Pacific survey region excludes households in Hawaii because Hawaii households were not

included in the mail survey sample.

Source: U.S. EPA analysis for this report



## 11.10 Uncertainties

SP methods have “... been tested and validated through years of research and are widely accepted

by ... government agencies and the U.S. courts as reliable techniques for estimating non

- market

values” ( Bergstrom and Ready 2009, p. 26 ) . OMB’s Circular A

- 4 notes that SP results “have also

been widely used in regulatory analyses by Federal agencies” ( USOMB 2003, p. 22 )

. EPA’s own

peer

- reviewed Guidelines for Preparing Economic Analysis (USEPA 2010a) indicate that the use

of SP study data, when the study is conducted properly in accord with best current practices, is

the only potential method for monetizing non

- use values

. However, EPA recognizes that

controversy remains over the use of stated preference results in benefit

- cost analysis for

rulemaking, at least in this particular instan ce

. Consistent with established best practices for SPBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 11: Stated Preference Survey

May 2014 11

- 33 

### surveys, EPA has sought to minimize possible biases by careful and thorough construction and

testing of the survey instrument.

While in EPA ’s view, the study incorporates current best professional practice in the conduct of

SP studies, EPA acknowledges that the results of any empirical study d epe nd on the methodology

applied. The Agency recognizes that potential biases may still remain and may influe nce the

results of the study. The magnitude and direction of any effects on benefits estimates is unknown.

Refer to the “Peer Review Report

– 316(b ) Stated Preference Survey Report Document (Final

Submission)” ( Applied Planning Corporation 2012 ) in the 316(b) rulemaking docket for

additional detail on the external peer review pr ocess and peer reviewer comments. EPA notes that

its analysis of the survey data and models is ongoing. EPA plans to obtain SAB review of the SP

survey EPA conducted. SAB review will provide additional high caliber, independent

professional judgment concer ning the quality of the survey done to date, including possible

improvements EPA could make. EPA is also seeking SAB input on whether

, how , and in what

circumstances this or similar survey s could be used, as support for national rulemaking s or 316(b)

NPDES

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 12: Analysis of New Units

May 2014 12

- 1 

# 12 Analysis of New Units at Existing Facilities

12.1 Introduction

In addition to the analysis presented in the preceding chapters for existing units at regulated

facilities, EPA analyzed benefits for new units at existing facilities. The new unit provision of th e

final rule applies to newly constructed electric power generating units at existing facilities and

repowering of existing generating units where the turbine and condenser are replaced. Unlike the

case for the existing unit provision , EPA cannot predict the facilities at which such new or

repowered units will be constructed, or the number and size of new or repowered units that will

be constructed. Instead, EPA estimated the pot ential coverage of the new unit provision of the

final rule based on the quant ity of electric power generating capacity that will be instal led and

subject to the new unit provision in future years. In addition, EPA considered a range of option s

for the final rule’s new unit provision, each of which would cover a different quantity o f new

units capacity.

 Option A: Entrainment performance requirements for all stand

- alone new units and all

types of repowered units.

 Option B: Entrainment performance requirements for all stand

- alone new units, and

replaced or repowered units in which turb ine or condenser are newly built or replaced.

 Option C : Entrainment performance requirements for all stand

- alone new units, and

repowered new units where the turbine and condenser are newly built or replaced, but

excluding high efficiency systems.

 Final Ru le

– New Units (Option D): Entrainment performance requirements for all

stand

- alone new units only.

This chapter presents EPA’s benefits analysis under the final rule and options considered for new

units. Section 12.2 presents EPA’s analysis of IM&E reduct ions and associated benefits. Section

12.3 presents EPA’s analysis of GHG emissions reductions and associated benefits. Section 12.3

summarizes monetized benefits for new units including benefits associated with IM&E reductions

and GHG emissions reductions . Refer to Chapter 8 of the Technical Development Document

(TDD) for additional information on the engineering analysis for new units.



## 12.2 Analysis Approach and Benefits for IM&E Reductions at New Units

EPA’s methodology for estimating IM&E reductions at existing units involves extrapolating

facility

- specific data to other existing facilities within the same region. EPA could not apply the

existing units methodology directly to new units because facility

- specific information is

unavailable for new units. I nstead, EPA estimated per mgd IM&E reductions and the monetary

value of benefits for new units based on the analysis of existing units.

12.2.1 Flow Reductions at New Units

The engineering analysis provided the annual reduction in intake flow at CWIS nationally un der

the final rule and options considered for new units. The annual flow reductions are cumulative

over the analysis period. For example, an annual flow reduction of 10 mgd would mean aBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 12: Analysis of New Units

May 2014 12

- 2 

### reduction of 10 mgd in year 1, 20 mgd (10 mgd × 2) by year 2, 30 mgd ( 10 mgd × 3) by year 3,

and so on. The flow reductions are projected to begin in 2014 and end in 2059, the final year of

the compliance period. The peak, or maximum, flow reduction is the flow reduction achieved in

2059. EPA included a declining profile at the end of the compliance period for recreational and

commercial fishing, nonuse, and T&E species benefits consistent with the analyses for existing

units.

Table 12

- 1 presents the estimated annual and peak flow reductions at new units under the final

rule and options considered for new units. The final rule will r e sult in an annual flow reduction of

68 mgd, with a total peak flow reduction of 3,128 mgd nationally in 2059. Refer to Appendix D

for additional discussion of the compliance schedule.

Table 12

- 1 : Flow Reductions for New Units Under the Final Rule for New Units and

Options Considered (mgd)

Option Annual Flow Reduction Peak Flow Reduction

Option A 1,282 58,972

Option B 462 21,252

Option C 68 3,128

Final Rule

– New Units 7 322

Source: U.S. EPA analysis for this report



### 12.2.2 IM&E Reductions and Associated Benefits per MGD

EPA calculated the reduction in IM&E per mgd of flow reduction nationally by dividing

estimated baseline IM& E losses at existing facilities by baseline weighted AIF (in mgd). EPA

also calculated benefits per mgd by dividing the monetized value of baseline IM&E losses by

baseline weighted AIF (in mgd). EPA calculated separate per mgd values by loss mode

(impingement mortality versus entrainment) in order to account for differences in baseline IM

technology across new and existing units. EPA assumed that, in the absence of the rule for new

units, baseline best professional judgment requirements imposed by permitting authorities for

once

- through cooling would be equivalent to modified Ristroph screens or intake velocity of 0.5

feet per second

.

Table 12

- 2 presents the annual IM&E reductions per mgd and Table 12

- 3 presents annual benefits

per mgd, both by los s mode. The benefits values underlying Table 11

- 3 are based on benefits

estimation methods described in the Chapter 5 through 8. EPA notes that these are partial benefits

estimates for the final rule and options considered because EPA was unable to estimat e nonuse

benefits for five of seven regions using the benefits transfer approach described in Chapter 8.

Table 12

- 4 presents annual benefits per mgd by loss mode based on EPA’s SP survey. 75 

### As

discussed in Chapter 11, EPA does not include benefits estimates based on the SP survey in its

quantitative comparison of benefits and costs for the final rule. The survey values are presented

here for illustrative purposes. EPA also notes the SP survey was designed to assess existing,

rather than new units. All values and maps presented in the survey reflected only existing units.

75 Per mgd values for the SP survey were calculated using the sum of regional survey versions.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 12: Analysis of New Units

May 2014 12

- 3 

### EPA calculated I M&E reductions and benefits for each year of the analysis period by multiplying

the IM flow reduction and E flow reduction in that year by the respective “per mgd ” values. EPA

summed across loss modes to generate total IM&E reductions and benefits for each year. EPA

discounted and annualized b enefits using 3 percent and 7 percent discount rates

.

Table 12

- 2 : Annual IM&E Reductions per MGD of Flow Reduction for New Units

by Loss Mode a

IM&E

Loss Mode A1E per mgd Commercial and

Recreational Harvest

(fish per mgd) Forage Species Commercial and

Recreational Species All Species

IM 4,340 712 5,052 133

E 4,069 1,922 5,991 175

Notes:

IM = impingement mortality; E = entrainment; A1E = age

- one equivalent; mgd = millions of gallons per day

a EPA calculated the reduction in IM&E per mgd of flow reduction nationally by dividing estimated baseline IM&E

losses at existing facilities by baseline weighted AIF (in mgd).

Source: U.S. EPA analysis for this report



### Table 12

- 3 : Annual Benefits per MGD of Flow Reduction for New Units by Loss Mode

(2011$) a

IM&E Loss

Mode Recreational

Commercial T& E Nonuse

Low Mean High

IM $112 $216 $426 $11 $5 $4

E $173 $304 $551 $41 $3 $562

Notes:

IM = impingement mortality; E = entrainment

a EPA calculated benefits per mgd by dividing the monetized value of baseline IM& E losses at existing facilities by baseline

weighted AIF (in mgd).

b Benefits presented in this table do not include benefits associated with changes in greenhouse gas emissions.

Source: U.S. EPA analysis for this report



### Table 12

- 4 : Annual Benefits per MGD of Flow Reduction for New Units

by Loss Mode based on the SP Survey (2011$) a



### IM&E Loss

Mode 5th Percentile Mean 95th Percentile

IM $9,117 $15,042 $20,950

E $15,142 $23,464 $33,214

Notes:

IM = impingement mortality; E = entrainment

a EPA calculated benefits per mgd based on the SP survey by dividing the estimated value of baseline

IM&E losses at existing facilities by baseline weighted AIF (in mgd).

Source: U.S. EPA analysis for this report



### 12.2.3 IM &E Reductions and Associated Benefits under the final Rule and Options

Considered for New Units

Table 12

- 5 summarizes national IM&E reductions under the final rule for new units and options

considered. IM&E reductions will increase throughout the complianc e period. The values

presented in Table 12

- 5 reflect the peak reduction achieved in 2059, the final year of theBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 12: Analysis of New Units

May 2014 12

- 4 

### compliance period. The final rule for new units will result in a peak reduction of about 2.3 million

A1E.

Table 12

- 5 : National IM&E Reductions under the Final Rule and Options Considered for

New Units a

Regulatory

Option A1E (in millions) Commercial and

Recreational Harvest

(millions of fish) Forage Species Commercial and

Recreational Species All Species

Option A 303.94 123.86 427.81 12.28

Option B 109.53 44.64 154.17 4.43

Option C 16.12 6.57 22.69 0.65

Final Rule

-

New Units 1.66 0.68 2.34 0.07

Notes:

A1E = age

- one equivalent

a The IM& E reductions presented in this table reflect the peak reduction achieved in 2059, the final year of the compliance period.

Source: U.S. EPA analysis for this report



### Table 12

- 6 presents national annualized benefits under the final rule and options considered for

new units based on the benefits estimation methods described in Chapters 5 through 8. Mean

annualized benefits under the final rule for new units will be $0.1 million using a 3 p ercent

discount rate and less than $0.1 million using a 7 percent discount rate. Annualized benefits under

other options considered for new units range from $1.1 to $21.4 million using a 3 percent

discount rate and $0.8 to $14.5 million using a 7 percent d iscount rate.

Table 12

- 7 presents national benefits for new units based on the results of the SP survey. Using

the SP survey, mean annualized benefits under the final rule for new units would be$3.3 million

using a 3 percent discount rate and $2.3 million using a 7 percent discount rate. Mean annualized

benefits under other options considered for new units range from $31.6 to $596.7 million using a

3 percent discount rate and from $22.4 to $423.1 million using a 7 percent discount rate. As noted

above, EPA has presented benefits estimates based the SP survey for illustrative purposes and

does not include values based on the SP survey in its quantitative comparison of costs and

benefits for the rule.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 12: Analysis of New Units

May 2014 12

- 5



### Table 12

- 6 : National Annualized Benefits for IM&E Reductions under the Final Rule and Options Considered for

New Units (2011$, 1,000s)

Regulatory Option Recreational

Commercial T&E Nonuse Total Benefits

Low Mean High Low Mean High

3% Discount Rate

Option A $4,138.2 $7,370.2 $13,553.0 $893.6 $90.7 $13,077.4 $18,199.9 $21,431.9 $27,614.7

Option B $1,491.3 $2,656.0 $4,884.1 $322.0 $32.7 $4,712.8 $6,558.8 $7,723.5 $9,951.6

Option C $219.5 $390.9 $718.9 $47.4 $4.8 $693.7 $965.4 $1,136.8 $1,464.7

Final Rule

- New Units $22.6 $40.2 $74.0 $4.9 $0.5 $71.4 $99.4 $117.0 $150.8

7% Discount Rate

Option A $2,722.0 $4,848.0 $8,914.9 $587.8 $59.7 $8,958.6 $12,328.0 $14,454.0 $18,520.9

Option B $980.9 $1,747.1 $3,212.7 $211.8 $21.5 $3,228.4 $4,442.7 $5,208.9 $6,674.5

Option C $144.4 $257.1 $472.9 $31.2 $3.2 $475.2 $653.9 $766.7 $982.4

Final Rule

- New Units $14.9 $26.5 $48.7 $3.2 $0.3 $48.9 $67.3 $78.9 $101.1

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Chapter 12: Analysis of New Units

May 2014 12

- 6



### Table 12

- 7 : National Annualized Benefits for IM&E Reductions

under the Final Rule and Options Considered for New Units

based on the SP Survey (2011$, millions)

Regulatory Option 5th Percentile Mean 95th Percentile

3 % Discount Rate

Option A $381.8 $596.7 $842.7

Option B $137.6 $215.0 $303.7

Option C $20.3 $31.6 $44.7

Final Rule

- New Units $2.1 $3.3 $4.6

7 % Discount Rate

Option A $270.7 $423.1 $597.5

Option B $97.6 $152.5 $215.3

Option C $14.4 $22.4 $31.7

Final Rule

- New Units $1.5 $2.3 $3.3

Source: U.S. EPA analysis for this report



### 12.2.4 Limitations and Uncertainties for the Analysis of IM&E Reductions and

Associated Benefits for New Units

EPA’s methodology for analyzing benefits from reducing IM& E at new units relies on the

estimated IM&E reductions and monetary benefits from the analysis of existing units. Thus, it is

subject to limitations and uncertainties inherent in the EPA’s methodology for existing units.

Refer to Section 3.4 for a discussi on of limitations and uncertainties in EPA’s analysis of IM&E

for existing units and Chapters 5 through 8 for monetary benefits, and Chapter 11 for the SP

survey. Additional limitations and uncertainties specific to EPA’s analysis of new units also

apply. These are addressed below in Table 12

- 8

.Benefits Analysis for the Final 316(b) Existing Facilities Chapter 12: Analysis of New Units

May 2014 12

- 7 

### Table 12

- 8 : Limitations and Uncertainties in EPA’s Analysis of IM&E Reductions and

Associated Benefits at New Units

Issue Impact on

Benefits

Estimate Comments

National rather than

regional flow reductions Uncertain EPA’s analysis for existing units examined IM&E and the economic

benefits of reducing these losses at a regional scale. To obtain regional

I M&E estimates, EPA extrapolated losses observed at model fac ilities

to existing units at regulated facilities within the same region. Regional

flow reductions were unavailable for new units; therefore, EPA

extrapolated per mgd benefits to new units based on national benefits

and national weighted flow from the anal ysis for existing units. This

assumption could lead to the over

- or under

- estimation of benefits for

new units depending on their ultimate regional distribution.

Timing of flow

reductions Uncertain The annual flow reduction for new units is constant with the total flow

reduction increasing linearly over the compliance period. As a result,

peak IM&E is not achieved until the 2059, the final year of the

compliance period. This assumption would tend to under

- estimate

annualized benefits if the new units come into operation sooner than

projected and over

- estimate benefits if they come into operation later

than projected.

Engineering uncertainty Uncertain EPA’s evaluation of I M&E was also affected by uncertainty about the

engineering and operating characteristics of the new units. Units

defined as “new” under the rule would be required to meet equivalent

performance to closed

- cycle recirculating systems. EPA expects that

most new units will install wet cooling towers. EPA may over

- or

under

- estimate benefits for new units if the flow at new units and

percentage flow reduction due to the rule deviate from EPA’s

assumptions. Refer to Chapter 8 of the TDD for additional information

on the eng ineering analysis for new units and potential uncertainties.



## 12.3 Analysis of Social Cost of Carbon for New Units

Because EPA does not expect Electric Generators to shut down to install cooling towers at new

units, for new units, EPA estimated the change in CO 2 

### resulting from the energy penalty only.

Energy penalty effects result from reduced energy conversion efficiency of the power generating

system. Refer to Appendix I of the economic analysis for the final rule (USEPA 2014) for

additional detail on compliance technology effects that impose costs via impact on revenue or

energy requirements.

12.3.1 Analysis Approach and Data Inputs

EPA estimated the monetary value of higher CO 2 

### emissions resulting from auxiliary energy

requirements asso ciated with operating cooling towers as follows:

 EPA first calculated the amount of additional electricity (in MWh) required to operate

cooling towers at new units, assuming Electric Generators would incur this additional

energy requirement beginning in th e first year any new generating unit would begin to

operate a cooling tower, i.e., 2017, through 2059. 76

76 As discussed in Chapter 3 of the Economic Analysis, EPA estimates that facilities will require four years to install

cooling towers . EPA assumed that 2014 will be the first year when any Electric Generator will begin installation

of its cooling tower according to the new unit provision of the final rule.Benefits Analysis for the Final 316(b) Existing Facilities Chapter 12: Analysis of New Units

May 2014 12

- 8 

###  EPA next estimated the amount of fuel required to generate this additional electricity (in

BTUs). The Agency assumed that existing facilities will be a ble to generate additional

electricity onsite, i.e., at new units at those facilities. EPA estimated additional fuel

requirement for coal and combined cycle natural gas units by multiplying the additional

energy requirement by heat rates for coal and combi ned cycle natural gas electric

generating units, respectively. 77



###  The Agency then multiplied the resulting fuel usage values by coal or natural gas carbon

dioxide emissions coefficients published by EIA ( US DOE 2013c), depending on the new

unit type, to estim ate an increase in CO 2 

### emissions due to the energy penalty. 78



###  Finally, EPA multiplied the estimated CO 2 

### emission values, by year, by the same unit

SCC values as those used for Electric Generators (Table 9

- 3).

12.3.2 Key Findings for Regulatory Options

Table 12

- 9 presents the total reduction in CO 2 

### emissions and associated SCC values in 2013 for

new units at Electric Generators, by option and discount rate. EPA estimates that the new unit

provision of the final rule will result in a total increase of 0.3 million of tCO2eq . Using the 3

percent average SCC values, EPA estimates the a verage annual benefit associated with this

increase in carbon emissions to be

- $ 0.3 million at the 3 percent discount rate and

- $ 0.2 million at

the 7 percent discount rate. EPA estimates that under the other new units options considered

– Options A, B, and C

– total carbon emissions would increase by 22.0, 8.9, and 2.0 million of

tCO2eq , respectively

. Using the 3 percent average SCC values, EPA estimates the a verage

annual ben efit associated with th ese increase s in carbon emissions to be

- $ 22.5 million,

- $9.1

million, and

- $2.1 million at the 3 percent discount rate and

- $ 13.8 million

, - $5.6 million, and

- $1.3 million at the 7 percent discount rate , respectively

.

Table 12

- 9 : Reduction in Carbon Emissions and Associated Average Annual Benefits

- New Units (SCC Values in 2013; $201 1, millions)

Option Total Emissions

(Millions; tCO2eq) Discount Rate for Calculating SCC Unit Values

2.5% 3 % 5 %

Average SCC

Value Average SCC

Value High SCC Value Average SCC

Value

3 % Discount Rate for Annualizing Benefits

Option A

- 22.0

- $31. 3

- $22. 5

- $ 69.7

- $ 7.7

Option B

- 8.9

- $12. 6

- $9.1

- $28. 1

- $3. 1

Option C

- 2.0

- $2.9

- $2.1

- $6.4

- $0. 7

Final Rule

– New

Units - 0.3

- $0.4

- $0.3

- $0.9

- $0.1

7% Discount Rate for Annualizing Benefits

Option A

- 22.0

- $19. 5

- $ 13.8

- $42. 8

- $4. 6

Option B

- 8.9

- $ 7.9

- $5.6

- $17. 2

- $ 1.9

Option C

- 2.0

- $1.8

- $1.3

- $3.9

- $0.4

Final Rule

– New

Units - 0.3

- $0.3

- $0.2

- $0.6

- $0.1

Source: U.S. EPA analysis for this report

77 EPA used heat rates based on higher heating values (H HV) of fuel.

78 For details see Carbon Dioxide Emissions Coefficients by Fuel published on February 14, 2013 available online at

http://www.eia.gov/environment/emissions/co2_vol_mass.cfm

.Benefits Analysis for the Final 316(b) Existing Facilities Chapter 12: Analysis of New Units

May 2014 12

- 9 

## 12.4 Monetized Benefits for New Units

Table 12

- 10 summarizes the annual monetized benefits associated with IM&E reductions and

changes in GHG emissions for new units. Using 3 percent average SCC values, mean annualized

benefits for the final rule for new units are

- $0.2 million using a 3 percent discount rate and

- $0.1

million using a 7 percent discount rate. Benefits for other options considered for new units range

from

- $0.9 to

- $1.1 million using a 3 percen t discount rate and

- $0.5 to $0.6 million using a 7

percent discount rate.Benefits Analysis for the Final 316(b) Existing Facilities Chapter 12: Analysis of New Units

May 2014 12

- 10



### Table 12

- 10: National Annualized Benefits under the Final Rule and Options Considered for New Units (2011$,

millions)

Regulatory Option Recreational

Commercial T&E Nonuse Total Benefits

Low Mean High Low Mean High

3% Discount Rate

Option A $4,138.2 $7,370.2 $13,553.0 $893.6 $90.7 $13,077.4 $18,199.9 $21,431.9 $27,614.7

Option B $1,491.3 $2,656.0 $4,884.1 $322.0 $32.7 $4,712.8 $6,558.8 $7,723.5 $9,951.6

Option C $219.5 $390.9 $718.9 $47.4 $4.8 $693.7 $965.4 $1,136.8 $1,464.7

Final Rule

- New Units $22.6 $40.2 $74.0 $4.9 $0.5 $71.4 $99.4 $117.0 $150.8

7% Discount Rate

Option A $2,722.0 $4,848.0 $8,914.9 $587.8 $59.7 $8,958.6 $12,328.0 $14,454.0 $18,520.9

Option B $980.9 $1,747.1 $3,212.7 $211.8 $21.5 $3,228.4 $4,442.7 $5,208.9 $6,674.5

Option C $144.4 $257.1 $472.9 $31.2 $3.2 $475.2 $653.9 $766.7 $982.4

Final Rule

- New Units $14.9 $26.5 $48.7 $3.2 $0.3 $48.9 $67.3 $78.9 $101.1

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Chapter 13: National Summary

May 2014 13

- 1 

# 13 Summary of National IM&E Reductions and Benefits for Existing

and New Units

13.1 Introduction

This chapter summarizes the results of the seven regional analyses

, and presents EPA’s estimates of the

national benefits of the final rule and opti ons considered for new and existing units at regulated facilities.

As described in Chapter 1, EPA considered three options for the existing units based on two technologies:

 Proposal Option 4: IM for Facilities > 50 mgd. Establish i mpingement m ortality c ontrols at

a ll e xisting f

acilities that withdraw over 50 mgd; d etermine e ntrainment c ontrols for f acilities

g reater than 2 mgd DIF o n a s ite

- specific b asis

.

 Final Rule

– Existing Units: IM Everywhere. Establish i mpingement m ortality c ontrols at a ll

e xisting f acilities that withdraw over 2 mgd; d etermine e ntrainment c ontrols for f acilities

g reater than 2 mgd DIF o n a s ite

- specific b asis

.

 Proposal Option 2: IM Everywhere and E for Facilities > 125 mgd. Establish i mpingement

m ortality c ontrols at a ll e xi sting f acilities that withdraw over 2 mgd DIF ; r equire f low r eduction

c ommensurate with closed

- cycle recirculating system for entrainment control b y f acilities

g reater t han 125 mgd DIF

.

The final rule will establish entrainment controls for facility greate r than 2 mgd DIF on a site

- specific

basis, as would Proposal Option 4. EPA did not analyze entrainment benefits under the final rule or

Proposal Option 4 because entrainment requirements are site specific.

EPA considered four regulatory options for new uni ts at existing facilities:

 Option A: Entrainment performance requirements for all stand

- alone new units and all types of

repowered units.

 Option B: Entrainment performance requirements for all stand

- alone new units, and replaced

or repowered units in which the turbine or condenser are newly built or replaced.

 Option C : Entrainment performance requirements for all stand

- alone new units, and repowered

new units where the turbine and condenser are newly built or replaced, but excluding high

efficiency systems.

 Final Rule

– New Units (Option D): Entrainment performance requirements for all stand

alone new units only.

Refer to Section VI of the preamble for additional description of the final rule and other options

considered for existing and new units.

Section 1 3.2 describes EPA’s methodology for aggregating benefits at the national level ; Section 13.3

summarizes baseline IM&E and estimated reductions in IM&E under the final rule and options

considered ; Section 13.4 presents national benefits; and Section 13.5 su mmarizes results of the SP survey,

and Section 13.6 discusses nonuse benefits and presents a break

- even analysis.



## 13.2 Summary of Limitations and Uncertainties

EPA notes that quantifying and monetizing the benefits that result from reductions in IM&E and GHG

em issions under the final rule and options considered for the existing facilities rule is challenging. TheBenefits Analysis for the Final 316(b) Existing Facilities Chapter 13: National Summary

May 2014 13

- 2 

### preceding sections discuss specific limitations and uncertainties associated with estimating reductions in

IM&E and monetized benefits. EPA estimated n ational

- level benefits associated with IM&E reductions

by summing benefit estimates over the seven study regions. Thus, national benefit estimates are subject to

the same uncertainties inherent in the valuation approaches EPA used for assessing each of the four

benefit categories associated with IM&E reductions ( threatened and endangered species, commercial

fishing, recreational fishing, and nonuse values). The combined effect of these uncertainties is of

unknown magnitude and direction (i.e., the estimates may over

- or understate the anticipated national

level of use benefits). Nevertheless, EPA has no data to indicate that the results for any of the benefit

categories are atypical or unreasonable. EPA’s analysis of changes in GHG emissions and associated

benefits was conducted at the national level, regional benefits were not estimated . EPA calculated

national benefits based on the SP survey estimates by summing results for the four SP survey regions. As

noted above, estimates based on EPA’s SP survey are included to illustrate the potential magnitude of

total values of ecological improvements resulting from the final rule.



## 13.3 Summary of Baseline IM&E Losses and IM&E Reductions

Based on the results of the regional analyses, EPA calculated total IM&E under ba seline (i.e., pre

regulatory) conditions and the total amount by which losses would be reduced under the final rule and

options considered

. The number of fish lost at regulated facilities is presented in terms of A1E losses ( i.e.,

the number of individual fish of different ages impinged and entrained by facility intakes, expressed as

A1E )

.

Table 13

- 1 presents baseline impingement, entrainment, and total IM&E for existing units. The table

shows that total national annual losses for all regulated facilities are 1.9 billion fish in terms of A1E. EPA

notes that the count of total lost organisms is larger than values expressed in A1E . This table shows that

about 39 percent

, or 0.8 billion fish of all A1E losses, occur in the Inland regio n, followed by the Mid

Atlantic region with 0.6 billion fish lost. Chapter 3 provides a m ore detailed discussion of IM&E in each

region

.

Table 13

- 1 : Baseline National A1E Losses at All Regulated Facilities (m illions of

A1E)

Region IM E IM&E

California 1.1 50.4 51.5

North Atlantic 0.6 57.2 57.9

Mid

- Atlantic 39.1 591.9 631.0

South Atlantic 17.1 9.2 26.4

Gulf of Mexico 53.5 93.5 147.0

Great Lakes 236.7 24.6 261.3

Inland 476.0 279.9 756.0

Total 824.2 1,106.7 1,931.0

Notes:

A1E = age

- one equivalent; IM = impingement mortality; E = entrainment; IM&E = impingement mortality and entrainment

Source: U.S. EPA analysis for this report



### EPA also calculated the total national IM&E avoided based on the expected reductions in IM&E at each

facility due to technology installation required by the final rule and under each option considered

. Table

13

- 2 through Table 13

- 4 present expected annual reductions at existing units , expressed as A1E, by

region . The fi nal rule will reduce annual A1E losses by 0.7 billion fish existing units. In comparison,Benefits Analysis for the Final 316(b) Existing Facilities Chapter 13: National Summary

May 2014 13

- 3 

### Proposal Option 4 would reduce A1E l osses by 0.6 billion fish and Proposal Option 2 would reduce

annual A1E losses by 1.6 billion fish. Table 13

- 5 presents reductions in A1E losses for the final rule and

options considered for new units. The final rule, including both new and existing units, will reduce A1E

losses by 0.7 billion fish ( Table 13

- 6 ).

Table 13

- 2 : Reductions in National A1E Losses for All Regulated Facilities (millions

of A1E) under Proposal Option 4

Region IM E IM&E

California 0.7 <0.01 0.7

North Atlantic 0.4 <0.01 0.4

Mid

- Atlantic 29.6 0.93 30.5

South Atlantic 11.6 <0.01 11.6

Gulf of Mexico 38.7 0.08 38.8

Great Lakes 184.0 0.02 184.0

Inland 347.7 0.39 348.1

Total 612.8 1.41 614.2

Notes:

A1E = age

- one equivalent; IM = impingement mortality; E = entrainment; IM&E = impingement mortality and entrainment

Source: U.S. EPA analysis for this report



### Table 13

- 3 : Reductions in National A1E Losses for All Regulated Facilities (millions

of A1E) under the Final Rule

Region IM E IM&E

California 0.7 <0.01 0.7

North Atlantic 0.4 0.51 0.9

Mid

- Atlantic 31.6 1.40 33.0

South Atlantic 12.4 0.48 12.9

Gulf of Mexico 40.2 0.08 40.3

Great Lakes 202.5 0.06 202.6

Inland 359.6 2.00 361.6

Total 647.5 4.53 652.0

Notes:

A1E = age

- one equivalent; IM = impingement mortality; E = entrainment; IM&E = impingement mortality and entrainment

Source: U.S. EPA analysis for this report



### Table 13

- 4 : Reductions in National A1E Losses for All Regulated Facilities (millions

of A1E) under Proposal Option 2

Region IM E IM&E

California 0.8 30.8 31.5

North Atlantic 0.6 43.8 44.4

Mid

- Atlantic 36.1 515.8 551.9

South Atlantic 17.0 8.6 25.6

Gulf of Mexico 48.2 55.2 103.4

Great Lakes 230.8 17.7 248.5

Inland 414.7 217.4 632.2

Total 748.2 889.3 1,637.5

Notes:

A1E = age

- one equivalent; IM = impingement mortality; E = entrainment; IM&E = impingement mortality and entrainment

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Chapter 13: National Summary

May 2014 13

- 4 

### Table 13

- 5 : Reductions in National A1E Reductions under the Final Rule and Options

Considered for New Units (millions of A1E)

Regulatory Option IM E IM&E

Option A 74.5 353.3 427.8

Option B 26.8 127.3 154.2

Option C 4.0 18.7 22.7

Final Rule

- New Units 0.4 1.9 2.3

Notes:

A1E = age

- one equivalent; IM = impingement mortality; E = entrainment; IM&E = impingement mortality and entrainment

Source: U.S. EPA analysis for this report



### Table 13

- 6 : Reductions in National A1E Reductions under the Final Rule

– Existin g

and New Units (millions of A1E)

Regulatory Option IM E IM&E

Final Rule

- Existing Units 647.5 4.5 652.0

Final Rule

- New Units 0.4 1.9 2.3

Final Rule

- Existing and

New Untis 647.9 6.5 654.3

Notes:

A1E = age

- one equivalent; IM = impingement mortality; E = entrainment; IM&E = impingement mortality and entrainment

Source: U.S. EPA analysis for this report



### Table 13

- 7 present s EPA ’ s estimates of the current level of total annual IM&E and the reduction in total

annual IM&E for the baseline, final rule and oth er options considered for existing units using the three

metrics presented in Section 3.2.2

. The final rule will provide greater IM&E reductions at existing units

than Proposal Option 4, but lesser IM&E reductions than Proposal Option 2. Table 13

- 8 present s IM&E

reductions under the final rule and other options considered for new units according to the same metrics

as Table 13

- 7. The final rule, including both new and existing units, will reduce annual foregone fishery

yield by 13.5 million pounds and annual biomass prodution foregone by 139.8 million pounds ( Table

13

- 9 ).

Table 13

- 7 : Baseline National IM&E and IM&E Reductions for Regulated Facilities for

the Final Rule and Options Considered

Regulatory Option Millions of A1E Foregone Fishery

Yield

(million lbs) a Biomass Production Forgone

(million lbs)

Proposal Option 4 614.2 12.6 130.3

Final Rule

- Existing

Units 652.0 13.4 138.9

Proposal Option 2 1,637.5 51.1 494.2

Baseline 1,931.0 69.8 626.6

Notes:

A1E = age

- one equivalents

a The reductions in foregone fishery yield presented here are equal to increases in commercial and recreational harvest. Refer to

Chapter 3 for additional detail regarding the calculation of foregone fishery yield and bioma ss production forgone.

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Chapter 13: National Summary

May 2014 13

- 5 

### Table 13

- 8 : Reductions in IM&E under the Final Rule and Options Considered for New

Units

Regulatory Option Millions of A1E Foregone Fishery

Yield

(million lbs) a Biomass Production Forgone

(million lbs)

Option A 427.8 18.4 160.0

Option B 154.2 6.6 57.7

Option C 22.7 1.0 8.5

Final Rule

- New Units 2.3 0.1 0.9

Notes:

A1E = age

- one equivalents

a The reductions in foregone fishery yield presented here are equal to increases in commercial and recreational harvest. Refer to

Chapter 3 for additional detail regarding the calculation of foregone fishery yield and biomass production forgone.

Source: U.S. EPA analysis for this repo rt



### Table 13

- 9 : Reductions in IM&E under the Final Rule

– Existing and New Units

Regulatory Option Millions of A1E Foregone Fishery

Yield

(million lbs) a Biomass Production Forgone

(million lbs)

Final Rule

- Existing

Units 652.0 13.4 138.9

Final Rule

- New Units 2.3 0.1 0.9

Final Rule

- Existing and

New Units 654.3 13.5 139.8

Notes:

A1E = age

- one equivalents

a The reductions in foregone fishery yield presented here are equal to increases in commercial and recreational harvest. Refer to

Chapter 3 for additional detail regarding the calculation of foregone fishery yield and biomass production forgone.

Source: U.S. EPA analysis for this report



### As shown for all regions in Table 13

- 10

, Table 13

- 11

, Table 13

- 12 , and by region in Chapter 3 , the

harvested commercial and recreational fish species that have direct use values comprise between 1 and 9

percent of baseline IM&E in each region, resulting in a national average of only 3 percent of IM&E for

which EPA monet ized value based on direct use. The remaining 97 percent of IM&E include s

unharvested recreational and commercial fish and forage fish which are not associated with direct use

. EPA’s nonuse benefit transfer was limited to two of the seven benefits regions, and EPA did not include

nonuse values for unharvested fish in its primary benefits analysis for the remaining five regions. Thus,

EPA has likely understated the total benefits significantly due to the regional limitations of its nonuse

analysis and the re latively large fraction of IM&E reductions which are not commercially or

recreationally harvested.Benefits Analysis for the Final 316(b) Existing Facilities Chapter 13: National Summary

May 2014 13

- 6 

### Table 13

- 10 : Distribution of National IM&E Reduction for Existing Units for All

Regulated Facilities for th e Final Rule and Other Regulatory Options Considered

Regulatory Option All

Species

(millions

of A1E) Forage

Species

(millions of

A1E) Commercial

and

Recreational

Species

(millions of

A1E) Commercial

and

Recreational

Harvest

(millions of fish

harvested) Percent of Fish

with Monetized

Use Value a

Proposal Option 4 614.2 528.2 85.9 16.1 2.6%

Final Rule

- Existing

Units 652.0 560.8 91.2 17.1 2.6%

Proposal Option 2 1,637.5 1,258.7 378.8 44.7 2.7%

Baseline 1,931.0 1,459.7 471.3 54.0 2.8%

Notes:

A1E = age

- one equivalent

a "Percent of fish with monetized use value" is equal to "commercial and recreational harvest (millions of fish harvested)" div ided

by "all species (millions of A1E)."

Source: U.S. EPA Analysis for this report



### Table 13

- 11 : Distribution of National IM&E Reductions under the Final Rule and Options

Considered for New Units

Regulatory Option All

Species

(millions

of A1E) Forage

Species

(millions of

A1E) Commercial

and

Recreational

Species

(millions of

A1E) Commercial

and

Recreational

Harvest

(millions of fish

harvested) Percent of Fish

with Monetized

Use Value a

Option A 427.8 303.9 123.9 12.3 2.9%

Option B 154.2 109.5 44.6 4.4 2.9%

Option C 22.7 16.1 6.6 0.7 2.9%

Final Rule

- New Units 2.3 1.7 0.7 0.1 2.9%

Notes:

A1E = age

- one equivalent

a "Percent of fish with monetized use value" is equal to "commercial and recreational harvest (millions of fish harvested)" div ided

by "all species (millions of A1E)."

Source: U.S. EPA Analysis for this report



### Table 13

- 12 : Distribution of National IM&E Reductions under the Final Rule

– Existing

and New Units

Regulatory Option All

Species

(millions

of A1E) Forage

Species

(millions of

A1E) Commercial

and

Recreational

Species

(millions of

A1E) Commercial

and

Recreational

Harvest

(millions of fish

harvested) Percent of Fish

with Monetized

Use Value a

Final Rule

- Existing

Units 652.0 560.8 91.2 17.1 2.6%

Final Rule

- New Units 2.3 1.7 0.7 0.1 2.9%

Final Rule

- Existing and

New Units 654.3 562.5 91.9 17.2 2.9%

Notes:

A1E = age

- one equivalent

a "Percent of fish with monetized use value" is equal to "commercial and recreational harvest (millions of fish harvested)" div ided

by "all species (millions of A1E)."

Source: U.S. EPA Analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Chapter 13: National Summary

May 2014 13

- 7 

## 13.4 Summary of National Monetized Benefits

EPA based it s estimates of total national baseline losses and total national benefits associated with IM&E

reductions under the final rule and option s considered on its estimates of regional monetize d baseline

losses and final rule and regulatory option benefits. To address the difference s in the timing of benefits

and costs, EPA developed a time profile of total benefits from all regulated facilities that reflects when

benefits from compliance

- relate d changes at each facility w ill be realized. EPA then discounted and

annualized benefits using 3 percent and 7 percent discount rates. 79 

### Appendix D of this report provides

detail on EPA’s development of the timeline of benefits.

EPA estimated mean national use values, as well as values that include the 5 th 

### percentile lower bound and

95 th 

### percentile upper bound of the recreational benefit estimates

. 80 

### Table 13

- 13 and Table 13

- 14 present

these results for each region and for the nation as a whole. The national benefit estimates do not include

benefits based on EPA’s SP survey presented in Chapter 11.

Table 13

- 13 summarizes EPA ’ s estimates of the regional and national annualized benefits of reducing

IM&E and GHG emissions under the final rule and each o f the regulatory options EPA considered for

existing units (discounted at 3 percent and 7 percent ). Table 13

- 14 presents the sum of benefits for the

final rule for existing units and new units. Refer to Chapter 10 for additional detail regarding benefits f or

existing units and Chapter 12 for additional detail regarding benefits for new units. The national value of

these reductions in IM&E and GHG emissions , evaluated at a 3 percent discount rate, is as follows:

 Proposal Option 4 results in national benefits of $ 31.0 million per year, with estimates based on

the 5 th 

### percentile lower bound and 95 th 

### percentile upper bound for recreational values, totaling

$ 22.8 million and $ 47.6 million ( Table 13

- 13 ).

 The final rule for existing units results in national benefits of $ 33.0 million per year, with

estimates based on the 5 th 

### percentile lower bound and 95 th 

### percentile upper bound for

recreational values, totaling $ 24.1 million and $ 50.6 million ( Table 13

- 13 ) . Including

requirements for new units, the final rule results in national benefits of $32.8 million per year,

with estimates based on the 5 th 

### percentile lower bound and 95 th 

### percentile upper bound for

recreational values, totaling $23.9 million and $50.5 million ( Table 13

- 14 ).

 Proposal Option 2 results in n ational benefits of

- $ 1,542.6 million per year, with estimates

based on the 5 th 

### percentile lower bound and 95 th 

### percentile upper bound for recreational values,

totaling

- $ 1,562.2 million and

- $ 1,504.5 million ( Table 13

- 13 ).

Evaluated at a 7 percent discount rate, the national use benefits of the regulatory analysis options are

somewhat smaller for the final rule and Proposal Option 4, and greater for Proposal Option 2 :

 Proposal Option 4 results in national benefits of $ 27.2 million per year, with estimates based on

the 5 th 

### percentile lower bound and 95 th 

### percentile upper bound for recreational values, totaling

$ 21.1 million and $ 39.5 million ( Table 13

- 13 ).

79 The 3 percent rate represents a reasonable estimate of the socia l rate of time preference. The 7 percent rate represents an

alternative discount rate, recommended by the Office of Management and Budget (OMB) that reflects an estimated

opportunity cost of capital.

80 The lower estimates of value presented in this chapte r are measured by the sum of the 5 th percentile lower bound estimates

of recreational values plus the mean value estimates for all other categories of value. The higher estimates of value present ed

in this chapter are measured by the sum of the 95 th percen tile upper bound estimates of recreational values plus the mean

value estimates for all other categories of value.Benefits Analysis for the Final 316(b) Existing Facilities Chapter 13: National Summary

May 2014 13

- 8 

###  The final rule for existing units results in national benefits of $ 28.7 million per year, with

estimate s based on the 5 th 

### percentile lower bound and 95 th 

### percentile upper bound for

recreational values, totaling $ 22.2 million and $ 41.8 million ( Table 13

- 13 ). Including

requirements for new units, the final rule results in national benefits of $28.6 million pe r year,

with estimates based on the 5 th 

### percentile lower bound and 95 th 

### percentile upper bound for

recreational values, totaling $22.1 million and $41.7 million ( Table 13

- 14 ).

 Proposal Option 2 results in national use benefits of

- $ 1,148.2 million per year

, with estimates

based on the 5 th 

### percentile lower bound and 95 th 

### percentile upper bound for recreational values,

totaling

- $ 1,161.7 million and

- $ 1,122.0 million ( Table 13

- 13 ).

More detailed discussions of benefits under each option are provided in Chapters 5 through 9

. National

benefits for new units are discussed in Chapter 12.Benefits Analysis for the Final 316(b) Existing Facilities Chapter 13: National Summary

May 2014 13

- 9 

### Table 13

- 13 : Summary of National Annualized Benefits for Existing Units for All Regulated Facilities ( (2011$, millions) a

Regulatory

Option Recreational Fishing Benefits Commercial

Fishing

Benefits c T&E Species

Benefits d,e Nonuse

Benefits SCC e Total Benefits

Low Mean High Low Mean High

3% Discount Rate

Proposal Option 4 $8.8 $17.1 $33.6 $0.9 $0.4 $0.3 $12.4 $22.8 $31.0 $47.6

Final Rule $9.4 $18.2 $35.9 $0.9 $0.4 $1.0 $12.4 $24.1 $33.0 $50.6

Proposal Option 2 $23.4 $43.0 $81.1 $3.9 $0.7 $51.1

- $1,641.3

- $1,562.2

- $1,542.6

- $1,504.5

7% Discount Rate

Proposal Option 4 $6.5 $12.6 $24.9 $0.7 $0.3 $0.3 $13.4 $21.1 $27.2 $39.5

Final Rule $7.0 $13.5 $26.6 $0.7 $0.3 $0.8 $13.4 $22.2 $28.7 $41.8

Proposal Option 2 $16.1 $29.5 $55.8 $2.7 $0.5 $37.3

- $1,218.2

- $1,161.7

- $1,148.2

- $1,122.0

a All benefits presented in this table are annualized, i.e., represent the sum of the discounted stream of benefits annualized over 51 years (2014 to 2064). See Appendix D for detail.

b A range of recreational fishing benefits is provided, based on the Krin sky and Robb technique, to estimate the 5th and 95th percentile limits on the marginal value per fish predicted by the meta

analysis. Commercial fishing benefits are computed based on a region

- and species

- specific range of gross revenue, as explained in C hapter 6 of this report. EPA estimated recreational use

benefits for some T&E species, as explained in Chapter 5. To calculate the total monetizable value columns (low, mean, high), the values for commercial fishing benefits and T&E species benefits

are ad ded to the respective low, mean, and high values for recreational fishing benefits.

c No significant commercial fishing takes place in the Inland region. Thus, this region is excluded from the commercial fishing analysis.

d Recreational use benefits from i ncreased abundance of T&E species with potentially high recreational use values (e.g., paddlefish and sturgeon).

See Chapter 5 of this report for more detail on EPA’s analysis of T&E benefits.

e SCC results presented here are based on 3 percent average SC C values.

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Chapter 13: National Summary

May 2014 13

- 10 

### Table 13

- 14: Summary of National Annualized Benefits for the Final Rule for Existing Units and New Units (2011$, millions) a

Regulatory

Option Recreational Fishing Benefits Commercial

Fishing Benefits c T&E Species

Benefits d,e Nonuse

Benefits SCC Total Benefits

Low Mean High Low Mean High

3% Discount Rate

Final Rule

- Existing Units $9.4 $18.2 $35.9 $0.9 $0.4 $1.0 $12.4 $24.1 $33.0 $50.6

Final Rule

- New

Units $0.0 $0.0 $0.1 $0.0 $0.0 $0.1

- $0.3

- $0.2

- $0.2

- $0.1

Final Rule

- Existing Units +

New Units $9.4 $18.3 $36.0 $0.9 $0.4 $1.1 $12.1 $23.9 $32.8 $50.5

7% Discount Rate

Final Rule

- Existing Units $7.0 $13.5 $26.6 $0.7 $0.3 $0.8 $13.4 $22.2 $28.7 $41.8

Final Rule

- New

Units $0.0 $0.0 $0.0 $0.0 $0.0 $0.0

- $0.2

- $0.1

- $0.1

- $0.1

Final Rule

- Existing Units +

New Units $7.0 $13.5 $26.7 $0.7 $0.3 $0.9 $13.2 $22.1 $28.6 $41.7

a All benefits presented in this table are annualized, i.e., represent the sum of the discounted stream of benefits annualized over 51 years (2014 to 2064). See Appendix D for detail.

b A range of recreational fishing benefits is provided, based on the Krin sky and Robb technique, to estimate the 5th and 95th percentile limits on the marginal value per fish predicted by the meta

analysis. Commercial fishing benefits are computed based on a region

- and species

- specific range of gross revenue, as explained in C hapter 6 of this report. EPA estimated recreational use

benefits for some T&E species, as explained in Chapter 5. To calculate the total monetizable value columns (low, mean, high), the values for commercial fishing benefits and T&E species benefits

are ad ded to the respective low, mean, and high values for recreational fishing benefits.

c No significant commercial fishing takes place in the Inland region. Thus, this region is excluded from the commercial fishing analysis.

d Recreational use benefits from increased abundance of T&E species with potentially high recreational use values (e.g., paddle fish and sturgeon).

See Chapter 5 of this report for more detail on EPA’s analysis of T&E benefits.

e SCC results presented here are based on 3 percent average SCC values.

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Chapter 13: National Summary

May 2014 13

- 11 

## 13.5 Results based on the SP Survey

Table 13

- 15 and Table 13

- 16 summarize national benefit estimates for the final rule and options

considered for existing and new units based on EPA’s SP survey. The national totals are based on

the sum of estimates for each survey region. As described in Chapter 12, EPA does not incl ude

benefit estimates based on the survey in its comparison of benefits and costs for the final rule and

options considered. However, the magnitude of benefits estimated based on the survey results

illustrate that total values of ecological improvements ma y be substantially greater than the partial

monetized benefits used for the benefit cost comparison ( Table 13

- 13 and Table 13

- 14 ).

Table 13

- 15: Summary of National Benefits for the Final Rule and Options Considered for

Existing Units based on the SP Survey (2011$, millions)

Regulatory Option 3 % Discount Rate 7 % Discount Rate

5 th Mean 95 th 5 th Mean 95 th

Proposal Option 4 $829.1 $1,363.1 $1,898.8 $642.6 $1,056.8 $1,472.2

Final Rule

- Existing Units $880.5 $1,448.8 $2,019.0 $682.5 $1,123.2 $1,565.3

Proposal Option 2 $2,159.9 $3,430.7 $4,823.7 $1,442.4 $2,294.5 $3,226.1

Source : U.S. EPA analysis for this report



### Table 13

- 16: Summary of National Benefits for the Final Rule for Existing and New Units

based on the SP Survey (2011$, millions)

Regulatory Option 3 % Discount Rate 7 % Discount Rate

5 th Mean 95 th 5 th Mean 95 th

Final Rule

- Existing Units $880.5 $1,448.8 $2,019.0 $682.5 $1,123.2 $1,565.3

Final Rule

- New Units $2.1 $3.3 $4.6 $1.5 $2.3 $3.3

Final Rule

- Existing and

New Units $882.6 $1,452.1 $2,023.6 $683.9 $1,125.5 $1,568.6

Source : U.S. EPA analysis for this report



## 13.6 Break

- Even Analysis

Comprehensive estimates of total resource value include both use and nonuse values and may be

compared to total social cost. Recent economic literature provides strong support for the

hypothesis that mean nonuse values are greater than zero. This is supported by the results of

EPA’s stated preference survey as described in Section 13.5. The per

- capita nonuse values need

not be large to result i n substantial benefits for the final rule. When small per

- capita nonuse

values are held by a substantial fraction of the population, the aggregate val ue can be very large.

However, in this specific context, EPA included nonuse values for only two of the se ven benefits

regions within its primary estimates of national benefits for the final rule and other options

considered. EPA did include benefit estimates based on the SP survey in its comparison of

benefits and costs for the final rule and options consider ed.

As shown in Table 13

- 12 above, nearly all

— 97 percent

— IM&E at cooling water intake

structures under current conditions (the baseline scenario) consist of either forage species or

un landed recreational and commercial species that are not harvested and th us not reflected in

EPA’s estimated direct use values

. Although individuals do not use these resources directly, they

may value changes in the status or quality of these resources

. EPA did not include nonuse valuesBenefits Analysis for the Final 316(b) Existing Facilities Chapter 13: National Summary

May 2014 13

- 12 

### for forage and unlanded species occurring in five of the seven benefits regions. Due to the

uncertainties of providing estimates of the magnitude of nonuse values associated with the

regulatory options for all regions, this section provides an alternative approach. EPA used an

alternative “break

- even ” analysis approach f or evaluating the potential relationship between costs

and benefits associated with IM&E reductions. This approach identif ies what the unmonetized

nonuse values would have to be in order for the benefits of the proposed options to equal costs.

To calculate a break

- even value, EPA subtracted its estimate s of monetized commercial and

recreational use benefits for the final rule and regulatory options considered from the estimated

annual compliance costs incurred by facilities subject to the final rule. The resulting “net cost”

enable d EPA to work backwards to estimate what the nonuse values would need to be (in terms

of WTP per household per year) in order for total annualized benefits to equal annualized costs

. Table 13

- 17 provide s this assessment for the final rule and options considered . The table show s

benefit values using a 3 percent or 7 percent discount rate, respectively.

As shown in Table 13

- 17 , for total annualized benefits to equal total annualized costs, nonuse

values per household would h ave to be at least $ 2.27 for the final rule using a 3 percent discount

rate and $2.59 using a 7 percent discount rate.

Table 13

- 17: Implicit Nonuse Value

— Break

- Even Analysis (2011$)

Regulatory

Option a Use

Benefits of

IM&E

Reductions

(2011$,

millions) a Annual

Social Cost

(2011$,

millions) b Annual Nonuse

Benefits Necessary

to Break Even

(2011$) c Number of

Households in

States with

Regulated

Facilities

(millions) d Annual

Break

- Even

Nonuse

WTP per

Household

(2011$) e

3% Discount Rate

Proposal Option 4 $19.6 $251.8 $232.2 114.9 $2.02

Final Rule

- Existing and New

Units $14.5 $274.9 $260.4 114.9 $2.27

Proposal Option 2 $0.0 $3,643.2 $3,643.2 114.9 $31.72

7% Discount Rate

Proposal Option 4 $14.5 $272.1 $257.6 114.9 $2.24

Final Rule

- Existing and New

Units $0.0 $297.3 $297.3 114.9 $2.59

Proposal Option 2 $0.0 $3,583.0 $3,583.0 114.9 $31.19

a Benefits are discounted using a 3% or 7% discount rate, respectively. Use benefits include estimated commercial fishing benef its,

recreational fishing benefits, and use benefits for T&E species.

b The total social cost of the final rule includes facility compliance costs and administrative costs.

c Annualized compliance costs minus annualized use benefits.

d Includes households in states with at least one surveyed facility. Household counts are based on Census 2010 (U.S. Census Bur eau

2010).

e Dollars per household per year that, when added to use benefits, would yield a total annualized benefit (use plus nonuse) equal to

the annualized costs.

Source: U.S. EPA analysis for this report; U.S. Census Bureau, 2010



### While this approach of backing out the “break

- even” nonuse value per household does not answer

the question of what nonuse values might actually be for the final rule and regulatory options

considered , these results do frame what the unknown values would have to be in order for

benefits to equal or exceed costs. The break

- even approach poses the question: “Is the true per

household WTP for the nonuse amenities (existence and bequest) associated with an option likelyBenefits Analysis for the Final 316(b) Existing Facilities Chapter 13: National Summary

May 2014 13

- 13 

### to be greater or less than the ‘ break

- even ’ benefit levels displayed in Table 13

- 17 ? ” The results o f

EPA’s SP survey (Chapter 11) illustrate the potential magnitude of nonuse and total values for

316(b) regulatory options and suggest that household values may exceed the break

- even point for

the final rule. Mean household WTP for the final rule based on the survey ranges from $0.69 in

the Pacific region to $27.57 in the Inland region.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 1 

# 14 References

Abelson, A., Denny, M. (1997). Settlement of Marine Organisms in Flow. Annual Review of

Ecology & Systematics , 28, 317.

Abt Associates, Inc. (2009). Summary of Ecological Effects of Thermal Discharge. Cambridge,

MA. Memorandum to EPA dated October 28, 2009.

Abt Associates, Inc. (2010a). Estimates of the amount of TN and TP regenerated by I&E losses

(Under Work Assignment 2

- 09, Task 4). Cambridge, MA. Memorandum t o EPA data

January 21, 2010.

Abt Associates, Inc. (2010b). Source Water Body Comparisons (Under Work Assignment 2

- 09,

Task 4). Cambridge, MA. Memorandum to EPA dated February 23, 2010.

Adamowicz, W., Boxall, P., Williams, M. and Louviere, J. (1998). Stated Preference Approaches

for Measuring Passive Use Values: Choice Experiments and Contingent Valuation.

American Journal of Agricultural Economics , 80(1): 64

- 75.

Alaska Fisheries Science Center (AFSC) of the NOAA National Marine Fisheries Service.

(2010). A laska Fisheries Science Center Publications Database. Available at:

http://access.afsc.noaa.gov/pubs/search.cfm

Allardyce, D. A. (1991). Endangered and threatened wildlife and plants: notice of findings on

petition to list the paddlefish. Pierre, South Da kota: U.S. Fish and Wildlife Service.

Applied Planning Corporation. (2012). Peer Review Report: 316(b) Stated Preference Survey

Report Document (Final Submission). EPA Contract: EP

- H

- 000334.

Arrow, K., Solow, R., Leamer, E., Portney, P., Rander, R. and Sc human, H. (1993). Report of the

NOAA Panel on Contingent Valuation. Federal Register, 58: 4602

- 4614.

Asche, F., Bjorndal, T. and Gordon, D. V. (2005). Demand Structure for Fish. Bergen, Norway:

Institute for Research in Economics and Business Administrati on. Bergen, Norway, SNF

Project No. 5256: SIP Resource Management.

Ash, G. R., Chymko, N. R. and Gallup, D. N. (1974). Fish kill due to 'cold shock' in Lake

Wabamun, Alberta. Journal of the Fisheries Research Board of Canada, 11: 1822

- 1824.

Atlantic State s Marine Fisheries Commission (ASMFC). (2012). Managed Species. Available at:

http://www.asmfc.org/managedspecies.htm

Auster, P. J., and Langton, R. W. (1999). The effects of fishing on fishery habitat. American

Fishery Society Symposium , 22.

Ball, S. L., and Baker, R. L. (1996). Predator

-- Induced Life History Changes: Antipredator

Behavior Costs or Facultative Life History Shifts? Ecology , 77(4): 1116

- 1124.

Barnett, P. R. O. (1972). Effects of Warm Water Effluents from Power Stations on Marine Life.

Proc eedings of the Royal Society B: Biological Sciences , 180(1061): 497

- 509.

Bartholow, J. M., Campbell, S. G. and Flug, M. (2004). Predicting the thermal effects of dam

removal on the Klamath River. Environmental Management , 34(6): 856

- 874.

Bason, C. (2008). Comments on the National Pollutant Discharge Elimination System Draft

Permit for the Indian River Generating Station: Delaware Center for the Inland Bays.

April 4, 2008.

Bateman, I. J., Cole, M., Cooper, P., Georgiou, S., Hadley, D. and Poe, G. L. (2004). On visible

choice sets and scope sensitivity. Journal of Environmental Economics and Management

, 47(1): 71

- 93.

Bateman, I. J., R.T. Carson, Day, B., Hanemann, M., Hanley, N., Hett, T., Jones

- Lee, M.,

Loomes, G., Mourato, S., Ozdemiroglu, E., Pierce , D.W., Sugden, R., and Swanson, J.

(2002). Economic Valuation with Stated Preference Surveys: A Manual . Northampton,

MA: Edward Elgar.

Behrens, C. E. (2012). Energy and Water Development: FY 2013 Appropriations. Congressional

Research Service Document 7

- 5 700, R42498, 67 pp.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 2 

### Beitinger, T. L., Bennett, W. A. and McCauley, R. W. (2000). Temperature Tolerances of North

American Freshwater Fishes Exposed to Dynamic Changes in Temperature.

Environmental Biology of Fishes , 58(3): 237

- 275.

Bell, F. W. (1986). Comp etition from Fish Farming in Influencing Rent Dissipation: The

Crawfish Fishery. American Journal of Agricultural Economics , 68(1): 95

- 101.

Bennett, J., and Blamey, R. (Eds.). (2001). The Choice Modelling Approach to Environmental

Valuation . Northampton, MA: Edward Elgar.

Bennett, S. J., and Best, J. L. (1995). Mean flow and turbulence structure over fixed, two

dimensional dunes: implications for sediment transport and bedorm stability.

Sedimentology , 42(3): 491

- 513.

Bergstrom, J. C., and De Civita, P. (1 999). Status of Benefits Transfer in the United States and

Canada: A Review. Canadian Journal of Agricultural Economics , 47(1): 79

- 87.

Bergstrom, J. C., and Ready, R. C. (2009). What Have We Learned from Over 20 Years of

Farmland Amenity Valuation Research in North America? Review of Agricultural

Economics , 31(1): 21

- 49.

Bergstrom, J. C., and Taylor, L. O. (2006). Using meta

- analysis for benefits transfer: Theory and

practice. Ecological Economics , 60(2): 351

- 360.

Bhat, C. R. (2001). Quasi

- random maximum s imulated likelihood estimation of the mixed

multinomial logit model. Transportation Research Part B , 35: 677

- 693.

Biles, C. L., Solan, M., Isaksson, I., Paterson, D. M., Emes, C. and Raffaelli, D. G. (2003). Flow

modifies the effect of biodiversity on eco system functioning: an in situ study of estuarine

sediments. Journal of Experimental Marine Biology and Ecology , 285

- 286: 165

- 177.

Bishop, R. C., and Holt, M. (2003). Estimating Post

- harvest Benefits from Increases in

Commercial Fish Catches with Implicati ons for Remediation of Impingement and

Entrainment Losses at Power Plants Agricultural & Applied Economics Staff Paper

Series: University of Wisconsin

- Madison, Department of Agricultural & Applied

Economics.

Bockstael, N. E., and Strand Jr., I. E. (1987). The Effect of Common Sources of Regression Error

on Benefit Estimates. Land Economics , 63(1): 11

- 20.

Boreman, J. (2000). Surplus production, compensation, and impact assessments of power plants.

Environmental Science & Policy , 3(Supplement 1): 445

- 449.

B oreman, J., and Goodyear, P. (1988). Estimates of Entrainment Mortality for Striped Bass and

Other Fish Species Inhabiting the Hudson River Estuary. American Fisheries Society

Monograph , 4: 152

- 160.

Boxall, B. (2010). Despite dire predictions, California farm jobs aren't disappearing. Los Angeles

Times , February 22, 2010.

Boyd, J., King, D. and Wainger, L. A. (2001). Compensation for Lost Ecosystem Services: The

Need for Benefit

- Based Transfer Ratios and Restoration Criteria. Stanford Environmental

Law Jou rnal , 20(2): 393

- 412.

Boyle, K. J., and Bergstrom, J. C. (1992). Benefit transfer studies: Myths, pragmatism, and

idealism. Water Resources Research , 28(3): 657

- 663. Boyle, K. J., and Özdemir, S. (2009). Convergent Validity of Attribute

- Based, Choice Questions

in Stated

- Preference Studies. Environmental and Resource Economics , 42(2): 247

– 264.

Brescia, C. J. (2002). Testimony of Christopher J. Brescia, President of Mid west Area River

Coalition 2000, on Proposals for a Water Resources Development Act of 2002, before the

Committee on Environment and Public Works, United States Senate. June 18, 2002.

Bresette, M., Gorham, J. and Peery, B. (1998). Site Fidelity and Size Fre quencies of Juvenile

Green Turtles (Chelonia mydas) Utilizing Near Shore Reefs in St. Lucie County, Florida.

Marine Turtle Newsletter , 82: 5

- 7.

Brock, T. D. (1985). Life at High Temperatures. Science , 230: 132

- 138.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 3 

### Bromberg, K. D., Bertness, M. D. (2005) . Reconstructing New England salt marsh losses using

historical maps. Estuaries, 28(6): 823

- 832.

Brown, G. M. (1993). “Economics of Natural Resource Damage Assessment: A Critique”, In R.

J. KoppV. K. Smith (Eds.), Valuing Natural Assets: The Economics of Natural Resource

Damage Assessment (pp. 73

- 105). Washington, D.C.: Resources for the Future.

Brownstone, D., and Train, K. (1996). Forecasting New Product Penetration with Flexible

Substitution Patterns. Journal of Econometrics , 89(1

- 2): 109

- 129.

Bulthuis, D. A. (1987). Effects of temperature on photosynthesis and growth of seagrasses.

Aquatic Botany , 27(1): 27

- 40.

Bunch, D. S., and Batsell, R. R. (1989). A Monte Carlo Comparison of Estimators for the

Multinomial Logit Model. Journal of Marketing R esearch , 26: 56

- 68.

Byrnes, J. E., Reynolds, P. L. and Stachowicz, J. J. (2007). Invasions and Extinctions Reshape

Coastal Marine Food Webs. PLoS ONE , 2(3): e295.

Campbell, D., Hutchinson, W. G. and Scarpa, R. (2009). Using Choice Experiments to Explore

the Spatial Distribution of Willingness to Pay for Rural Landscape Improvements.

Environment and Planning , 41(1): 97

- 111.

Caparroy, P., Pérez, M. T. and Carlotti, F. (1998). Feeding behaviour of Centropages typicus in

calm and turbulent conditions. Marine Ecology

- Progress Series, 168: 109

- 118.

Capps Jr., O., and Labregts, J. A. (1991). Assessing Effects of Prices and Advertising on

Purchases of Finfish and Shellfish in a Local Market in Texas. Southern Journal of

Agricultural Economics , July: 181

- 194.

Carlsson, F., Frykblom, P. and Liljenstolpe, C. (2003). Valuing Wetland Attributes: An

Application of Choice Experiments. Ecological Economics , 47(1): 95

- 103.

Carson, R. T., Flores, N. E. and Mitchell, R. C. (1999). “The Theory and Measurement of

Passive

- Use Value.” In I. J. Bateman and K. G. Willis (Eds.), Valuing Environmental

Preferences: Theory and Practice of the Contingent Valuation Method in the US, EU, and

Developing Countries (pp. 97

- 130). New York: Oxford University Press.

Cheng, H.

- T., and Capps Jr., O. (1988). Demand Analysis of Fresh and Frozen Finfish and

Shellfish in the United States. American Journal of Agricultural Economics , 70(3): 533.

Chesapeake Bay Program (CBP). (2007). Chesapeake Bay Watershed Assistance Network

Access to Federal Fu nds: A Collaborative Effort of the Chesapeake Bay Federal

Agencies Committee and the Chesapeake Bay Watershed Assistance Network,

Annapolis, Maryland: Chesapeake Bay Program, 101 pp.

Choi, D. H., Park, J. S., Hwang, C. Y., Huh, S. H. and Cho, B. C. (2002). Effects of thermal

effluents from a power station on bacteria and heterotrophic nanoflagellates in coastal

waters. Marine Ecology Progress Series , 229: 1

- 10.

Chuang, Y.

- L., Yang, H.

- H. and Lin, H.

- J. (2009). Effects of a thermal discharge from a nuclear

p ower plant on phytoplankton and periphyton in subtropical coastal waters. Journal of

Sea Research , 61(4): 197

- 205.

Clarke, R. P., Yoshimoto, S. S. and Pooley, S. G. (1992). A bioeconomic analysis of the

northwestern Hawaiian islands lobster fishery. Marine Resource Economics , 7:115

- 140.

Clean Water Act, 33 U.S.C. 1326(b) C.F.R. (1972).

Cleary, D. (1969). Demand and Prices for Shrimp: U.S. Department of Commerce, Bureau of

Commercial Fisheries, Division of Economic Research.

Cloete, T. E., Jacobs, L. and Br özel, V. S. (1998). The chemical control of biofouling in industrial

water systems. Biodegradation , 9(1): 23

- 37.

Cohen, A. N., and Carlton, J. T. (1998). Accelerating invasion rate in a highly invaded estuary.

Science , 279(5350): 555.

Coles, S. L. (1984) . Colonization of Hawaiian reef corals on new and denuded substrata in the

vicinity of a Hawaiian power station. Coral Reefs , 3(3): 123

- 130.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 4 

### Colombo, S., and Hanley, N. (2008). How Can We Reduce the Errors from Benefits Transfer? An

Investigation Using the Choice Experiment Method. Land Economics , 84(1): 128

- 147.

Conant, T. A., Dutton, P. H., Eguchi, T., Epperly, S. P., Fahy, D. D., Godfrey, M. H.,

MacPherson , S.L., Possardt, E.E., Schroeder, B.A., Seminoff, J.A., Snover, M.L., Upite,

C.M, and Witherington , B. E. (2009). Loggerhead Sea Turtle ( Caretta Caretta ) 2009

Status Review Under the U.S. Endangered Species Act. Report of the Loggerhead

Biological Review Team to the National Marine Fisheries Service. 222 pp.

Cooke, S. J., Bunt, C. M. and Schreer, J. F. (2004). Understanding fish behavior, distribution, and

survival in thermal effluents using fixed telemetry arrays: a case study of smallmouth

bass in a discharge canal during winter. Environmental Management , 33(1): 140

- 150.

Costanza, R., Folke, C. (1997 ). “Valuing Ecosystem Services with Efficiency, Fairness, and

Sustainability as Goals.” In G. Daily (Ed.), Nature's services: Societal dependence on

natural ecosystems . Washington, D.C.: Island Press.

Crouse, D. T., Crowder, L. B. and Caswell, H. (1987). A Stage

- Based Population Model for

Loggerhead Sea Turtles and Implications for Conservation. Ecology , 68(5): 1412

- 1423.

Daily, G. C. (Ed.). (1997). Nature’s Services: Societal Dependence on Natural Ecosystems

. Washington, D.C.: Island Press.

Daily, G. C., Alexander, S., Ehrlich, P. R., Goulder, L., Lubchenco, J., Matson, P. A., Mooney,

H.A., Postel, S., Schneider, S.H., Tilman, D., and Woodwell, G. M. (1997). Ecosystem

Services: Benefits Supplied to Human Societies by Natural Ecosystems . Washington,

DC: Eco logical Society of America.

Davis, C., Yen, S. and Hwan

- Lin, B. H. (2007). Consumer Demand for Meat Cuts and Seafood,

Selected Paper. Paper presented at the Annual Meeting of the American Agricultural

Economics Association, July 29

- August 1, Portland, OR.

Deacutis, C. F. (1978). Effect of Thermal Shock on Predator Avoidance by Larvae of Two Fish

Species. Transactions of the American Fisheries Society , 107(4): 632

- 635.

Desvousges, W. H., Johnson, F. R. and Banzhaf, H. S. (1998). Environmental Policy Analysis

with Limited Information: Principles and Applications of the Transfer Method

. Northampton, MA: Edward Elgar Publishers.

Dillman, D. A., Smyth, J. D. and Christian, L. M. (2009). Internet, Mail and Mixed Mode

Surveys: The Tailored Design Method (3 ed.). New York, NY: John Wiley and Sons.

Do, T. N., and Bennett, J. (2009). Estimating wetland biodiversity values: a choice modelling

application in Vietnam's Mekong River Delta. Environment and Development

Economics , 14: 163

- 186.

Doll, J. P. (1972). An Economic Analysis of Shrimp Ex

- Vessel Prices, 1950

- 1968. American

Journal of Agricultural Economics , 54(3): 431

- 440.

Dominion. (2011). Brayton Point Power Station. Available at:

http://www.dom.com/about/stations/fossil/brayton

- point

- power

- station.jsp

EA E ngineering, Science, and Technology. (2008). Point Beach Nuclear Plant Evaluation of the

Thermal Effects Due to a Planned Extended Power Uprate. Prepared for FPL Energy

Point Beach, LLC, August 2008.

Earthwatch Institute. (2010). Trinidad's Leatherback Sea Turtles. Available at:

http://www.earthwatch.org/exped/sammy.html. Accessed May 25, 2010.

Eckman, J. E., and Duggins, D. O. (1993). Effects of Flow Speed on Growth of Benthic

Suspension Feeders. Biology Bulletin , 185(1): 28

- 41.

Eggers, J. M. (1989). Inci dental capture of sea turtles at Salem Generating Station, Delaware Bay,

New Jersey. Paper presented at the Proceedings of the Ninth Annual Workshop on Sea

Turtle Conservation and Biology. NOAA Tech. Memo. NMFS

- SEFC

- 232, Jekyll Island,

Georgia.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 5 

### Eggers, J. M., Haberland, M. W. and Griffin, J. C. (2001). Growth of Juvenile Loggerhead Sea

Turtles Near PSE&G's Salem Generating Station, Delaware Bay, New Jersey. Marine

Turtle Newsletter , 59: 5

- 7.

Enders, E. C., Boisclair, D. and Roy, A. G. (2003). The effect of turbulence on the cost of

swimming for juvenile Atlantic salmon (Salmo salar). Canadian Journal of Fisheries &

Aquatic Sciences , 60(9): 1149

- 1160.

Entrix, Inc. (2001). An ecological risk

- based 316(a) demonstration for the Indian River power

plant: report prepared for Conectiv Energy.

Entrix, Inc. (2003). An ecological risk

- based 316(b) demonstration for the Indian River power

plant: report prepared for NRG Energy, Inc. Wilmington, DE.

Erdem, T., and Keane, M. P. (1996). Decision

- Making under Uncertainty: Capturing Dynamic

Brand Choice Processes in Turbulent Consumer Goods Markets. Marketing Science

, 15(1): 1

- 20.

Erkan, D. E. (2002). Strategic Plan f or the Restoration of Anadromous Fishes to Rhode Island

Coastal Streams. Wakefield, RI: Rhode Island Department of Environmental

Management, Division of Fish and Wildlife.

Ernest, R. G., Martin, R. E., Peery, B. D., Storm, D. G., Wilcox, J. R. and Walls, N . W. (1988).

Sea turtle entrapment at a coastal power plant. Paper presented at the Proceedings of the

Southeastern Workshop on Aquatic Ecological Effects of Power Generation, December

1986, Mote Technical Report No. 124, Sarasota, FL.

Executive Order No. 13158. (2001). Marine Protected Areas, 3 C.F.R (2001, comp) C.F.R.

Executive Order No. 13508. (2009). Chesapeake Bay Protection and Restoration, 74 Federal

Register 23099 (May 14, 2009) C.F.R.

Fischman, R. L. (2001). The EPA’s NEPA Duties and Ecosystem Ser vices. Stanford

Environmental Law Journal , 20(2): 497

- 536.

Folke, C., Carpenter, S., Walker, B., Scheffer, M., Elmqvist, T., Gunderson, L. and Holling, C. S.

(2004). Regime Shifts, Resilience, and Biodiversity in Ecosystem Management. Annual

Review of Eco logy, Evolution, & Systematics , 35(1): 557

- 581.

Fortier, L., and Harris, R. P. (1989). Optimal foraging and density

- dependent competition in

marine fish larvae. Marine Ecology

- Progress Series , 51: 19

- 33.

Frazer, N. B. (2005). Conflicting Views of Sea Tu rtles: How many do we need, how much are

they worth? Paper presented at the Centre for Maritime Research Conference, People and

the Sea II.

Freeman III, A. M. (1993). “Non

- use values in natural resource damage assessment. “In R. J.

KoppV. K. Smith (Eds.), Valuing Natural Assets . Washington, D.C.: Resources for the

Future.

Freeman III, A. M. (2003). The Measurement of Environmental and Resource Values: Theory

and Methods . Washington, D.C.: Resources for the Future.

Freese, S., Northwest Region, National Mar ine Fisheries Service, Sustainable Fisheries Division.

(2008). August 14, 2008.

Froese, R., and Pauly, D. (2009). Fishbase (version 07/2009). Fisheries Centre, University of

British Columbia. Available at: www.fishbase.org

Gibson, M. R. (2002). Winter flounder abundance near Brayton Point Station, Mt. Hope Bay

revisited: separating local from regional impacts using long

- term abundance data: Rhode

Island Division of Fish and Wildlife Research.

Glass, G. V. (1976). Primary, Secondary, and Meta

- Analysis of Research. Educational

Researcher , 5(10): 3

- 8.

Goodyear, C. (1978). Entrainment Impact Estimates Using the Equivalent Adult Approach,

FWS/OBS

- 78/65. Washington, D.C.: U.S. Department of the Interior, Fish and Wildlife

Service.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 6 

### Gottlieb, S. J. (1998). Nutr ient removal by age

- 0 Atlantic menhaden (Brevoortia tyrranus) in

Chesapeake Bay and implications for seasonal management of the fishery. Ecological

Modelling , 112(2

- 3): 111

- 130.

Government Accountability Office (GAO). (2005). Chesapeake Bay Program: Impro ved

strategies are needed to better assess, report, and manage restoration progress.

Washington, D.C, 94 pp.

Great Lakes

. (1990). 33 U.S.C 1268(a)(3)(b) C.F.R.

Great Lakes Restoration Initiative

. (2012). Great Lakes Restoration: Fiscal Year 2012 Report to

the Congress and the President. Prepared by the United States Environmental Protection

Agency in Partnership with the Great Lakes Interagency Task Force. October 2012.

Griffiths, C. (undated). The Use of Benefit

- Cost Analysis in Environmental Policy Makin g

Working Paper. Washington, DC: National Center for Environmental Economics, U.S.

Environmental Protection Agency.

Grigalunas, T. A., Opaluch, J. J., Reed, M. M. R. and French, D. (1988). Measuring Damages to

Marine Natural Resources from Pollution Incide nts under CERCLA: Application of an

Integrated Ocean Systems/Economic Model. Marine Resource Economics , 5(1): 1

- 21.

Gunderson, L. H. (2000). Ecological Resilience

- In Theory and Application. Annual Review of

Ecology & Systematics , 31: 425.

Hagen, D. A., Vincent, J. W. and Welle, P. G. (1992). Benefits of Preserving Old

- Growth Forests

and the Spotted Owl. Contemporary Economic Policy , 10(2): 13

- 26.

Hairston, N. G., Ellner, S. P., Geber, M. A., Yoshida, T. and Fox, J. A. (2005). Rapid evolution

and the con vergence of ecological and evolutionary time. Ecology Letters , 8(10): 1114

-

1127.

Hanemann, W. M. (1984). Welfare evaluations in contingent valuation experiments with discrete

responses. American Journal of Agricultural Economics , 66(3): 332

- 341.

Hanley, N ., Colombo, S., Tinch, D., Black, A. and Aftab, A. (2006). Estimating the benefits of

water quality improvements under the Water Framework Directive: are benefits

transferable? European Review of Agricultural Economics , 33: 391

- 413.

Hayes, D. B., Dodd, H. R. and Lessard, J. L. (2006). Effects of small dams on cold water stream

fish communities. American Fisheries Society Symposium , 587

- 601.

HDR Engineering, Inc. (2009). Quad Cities Nuclear Station Adjusted Thermal Standard CWA

316(a) Demonstration. Final Draft. Prepared for Exelon Nuclear. November, 2009.

Heal, G., Daily, G. C., Ehrlich, P. R., Salzman, J., Boggs, C., Hellmann, J., Hughes, J., Kremen,

C., and Ricketts, T. (2001). Protecting Natural Capital through Ecosystem Service

Districts. Stanford Envi ronmental Law Journal , 20(2): 333

- 364.

Heberlein, T. A., Wilson, M. A., Bishop, R. C. and Schaeffer, N. C. (2005). Rethinking the Scope

Test as a Criterion for Validity in Continent Valuation. Journal of Environmental

Economics and Management , 50(1): 1

- 22

. Hensher, D., and Greene, W. (2003). The Mixed Logit model: The state of practice.

Transportation , 30(2): 133

- 176.

Herman, J. S., Culver, D. C. and Salzman, J. (2001). Groundwater Ecosystems and the Service of

Water. Stanford Environmental Law Journal , 2 0(2): 479

- 496.

Her r mann, M. (1996). Estimating the induced price increase for Canadian Pacific halibut with the

introduction of the individual vessel quota program. Canadian Journal of Agricultural

Economics , 44: 151

– 164.

Hilborn, R., and Walters, C. J. (1992). Quantitative Fisheries Stock Assessment: Choice,

Dynamics and Uncertainty . New York: Chapman and Hall.

Hillman, R. E., Davis, N. W. and Wennemer, J. (1977). Abundance, diversity, and stability in

shore

- zone fish communities in an area of Long Islan d Sound affected by the thermal

discharge of a nuclear power station. Estuarine and Coastal Marine Science , 5(3): 355

-

381.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 7 

### Hixon, M. A., and Jones, G. P. (2005). Competition, predation, and density

- dependent mortality

in demersal marine fishes. Ecology , 86 (11): 2847

- 2859.

Hoagland, P., and Jin, D. (2006). Science and Economics in the Management of an Invasive

Species. BioScience , 56(11): 931

- 935.

Hoehn, J. P., Lupi, F. and Kaplowitz, M. D. (2004). Internet

- Based Stated Choice Experiments in

Ecosystem Mitig ation: Methods to Control Decision Heuristics and Biases. Paper

presented at the Valuation of Ecological Benefits: Improving the Science Behind Policy

Decisions.

Holly Jr., F. M., Li, S. and Weber, L. J. (2004). River temperature predictions downstream of

Quad Cities Nuclear Generating Station. Preliminary Draft. Submitted to Exelon

Generation. April, 2004. Iowa City, IA: Iowa Institute of Hydroscience & Engineering

(IIHR), University of Iowa.

Holmes, T. P., and Adamowicz, W. L. (2003). “Attribute

- based methods.” In Champ P.A., K. J.

Boyle and T. C. Brown (Eds.), A Primer on Nonmarket Valuation (pp. 171

- 220).

Dordrecht: Kluwer Academic Publishers

Holmlund, C. M., and Hammer, M. (1999). Ecosyste m services generated by fish populations.

Ecological Economics , 29(2): 253

- 268.

Holt, M. T., and Bishop, R. C. (2002). A semiflexible normalized quadratic inverse demand

system: an application to the price formation of fish. Empirical Economics , 27(1): 23

- 47.

Holt, R. D. (1977). Predation, apparent competition, and the structure of prey communities.

Theoretical Population Biology, 12(2): 197

- 229.

Horst, T. J. (1975). “The Assessment of Impact Due to Entrainment of Ichthyoplankton.” In S. B.

Saila (Ed.), Fis heries and Energy Production: A Symposium . Lexington: D.C. Heath.

Howitt, R. E., MacEwan, D. and Medellín

- Azuara, J. (2009). Economic Impacts of Reductions in

Delta Exports on Central Valley Agriculture. ARE Update , 12(3): 1

- 4.

Hoyal, D. C. J. D., Atkinso n, J. F., Depinto, J. V. and Taylor, S. W. (1995). The effect of

turbulence on sediment deposition. Journal of Hydraulic Research , 33(3): 349

- 360.

Hu, W., Veeman, M. M. and Adamowicz, W. L. (2005). Labelling Genetically Modified Food:

Heterogeneous Consum er Preferences and the Value of Information. Canadian Journal

of Agricultural Economics , 53(1): 83

- 102.

Interagency Working Group (IWG). (2010). Scientific Assessment of Hypoxia in U.S. Coastal

Waters. National Centers for Coastal Ocean Science. May 2010.

Interagency Working Group on Social Cost of Carbon , United States Government (Interagency

Working Group). (2013). Technical Support Document: Technical Update of the Social

Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866. May

20 13.

Interagency Working Group on Social Cost of Carbon , United States Government (Interagency

Working Group). (2010). Technical Support Document: Social Cost of Carbon for

Regulatory Impact Analysis Under Executive Order 12866. May 2013.

Izrael, D., Hoagl in, D. C. and Battaglia, M. P. (2004). To Rake or Not To Rake Is Not the

Question Anymore with the Enhanced Raking Macro. Paper presented at the SUGI

Conference, Montreal, Canada. Available at:

http://www2.sas.com/proceedings/sugi29/207

- 29.pdf

Jackson, J. B., Kirby, M.X., Berger, W.H., Bjorndal, K.A., Botsford, L.W., Bourque, B.J.,

Bradbury , R.H., Cooke, R., Erlandson, J., Estes, J.A., Hughes, T.P., Kidwell, S., Lange,

C.B., Lenihan, H.S., Pandolfi, J.M., Peterson, C.H., Steneck, R.S., Tegner, M.J., and

War ner, R. R. (2001). Historical overfishing and the recent collapse of coastal

ecosystems. Science , 293(5530): 629

- 637.

Jiang, Z.

- B., Zeng, J.

- N., Chen, Q.

- Z., Huang, Y.

- J., Liao, Y.

- B., Xu, X.

- Q. and Zheng, P. (2009).

Potential impact of rising seawater te mperature on copepods due to coastal power plantsBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 8 

### in subtropical areas. Journal of Experimental Marine Biology and Ecology , 368(2): 196

-

201.

Jirotkul, M. (1999). Population density influences male

- male competition in guppies. Animal

Behaviour , 58(6): 1169

- 1175.

Johnston, R. J., and Bergstrom, J. C. (2011). Valuing Farmland Protection: Does Policy Guidance

Depend On the Econometric Fine Print? Applied Economic Perspectives and Policy

, 33(4): 639

- 660.

Johnston, R. J., and Duke, J. M. (2007). W illingness to Pay for Agricultural Land Preservation

and Policy Process Attributes: Does the Method Matter? American Journal of

Agricultural Economics , 89(4): 1098

- 1115.

Johnston, R. J., and Duke, J. M. (2009). Willingness to Pay for Land Preservation acro ss States

and Jurisdictional Scale: Implications for Benefit Transfer. Land Economics , 85(2): 217

-

237.

Johnston, R. J., Ranson, M. H., Besedin, E. Y. and Helm, E. C. (2006). What Determines

Willingness to Pay per Fish? A Meta

- Analysis of Recreational Fish ing Values. Marine

Resource Economics , 21(1): 1

- 32.

Johnston, R. J., and Rosenberger, R. S. (2010). Methods, Trends and Controversies in

Contemporary Benefit Transfer. Journal of Economic Surveys , 24(3): 479

- 510.

Johnston, R. J., Schultz, E. T., Segerson, K. and Besedin, E. Y. (2011a). “Bioindicator

- Based

Stated Preference Valuation for Aquatic Habitat and Ecosystem Service Restoration”. In

J. Bennett (Ed.) International Handbook on Non

- Marketed Environmental Valuation (pp.

159

- 186). Cheltenham, UK: Edward Elgar.

Johnston, R. J., Schultz, E. T., Segerson, K., Besedin, E. Y. and Ramachandran, M. (2012).

Enhancing the Content Validity of Stated Preference Valuation: The Structure and

Function of Ecological Indicators. Land Economics , 88(1): 102

- 120.

Johnston , R. J., Segerson, K., Schultz, E. T., Besedin, E. Y. and Ramachandran, M. (2011b).

Indices of Biotic Integrity in Stated Preference Valuation of Aquatic Ecosystem Services.

Ecological Economics , 70(11): 1946

- 1956.

Johnston, R. J., Swallow, S. K., Allen, C. W. and Smith, L. A. (2002a). Designing

Multidimensional Environmental Programs: Assessing Tradeoffs and Substitution in

Watershed Management Plans. Water Resources Research , 38(7): 1

- 13.

Johnston, R. J., Weaver, T. F., Smith, L. A. and Swallow, S. K. (1 995). Contingent valuation

focus groups: insights from ethnographic interview techniques. Agricultural and

Resource Economics Review , 24(1): 56

- 69.

Johnston, R.J. G. Magnusson, M.J. Mazzota, and J.J. Opaluch. ( 2002b ) . Combining Economic

and Ecological Ind icator to Prioritize Salt Marsh Restoration Actions. American Journal

of Agricultural Economics , 84: 1362

- 1370.

Kaplowitz, M. D., Lupi, F. and Hoehn, J. P. (2004). “Multiple Methods for Developing and

Evaluating a Stated

- Choice Questionnaire to Value Wetl ands.” In S. Presser, J. M.

Rothget, M. P. Couper, J. T. Lesser, E. Martin, J. Martin and E. Singer (Eds.), Methods

for Testing and Evaluating Survey Questionnaires . New York: John Wiley and Sons.

Keller, A. A., Oviatt, C. A., Walker, H. A. and Hawk, J. D. (1999). Predicted Impacts of Elevated

Temperature on the Magnitude of the Winter

- Spring Phytoplankton Bloom in Temperate

Coastal Waters: A Mescosm Study. Limnology and Oceanography , 44(2): 344

- 35 6.

Kelso, J. R. M., and Milburn, G. S. (1979). Entrainment and Impingement of Fish by Power

Plants in the Great Lakes which use the Once

- Through Cooling Process. Journal of Great

Lakes Research , 5(2): 182

- 194.

Kerr, G. N., and Sharp, B. M. H. (2006). “Tra nsferring mitigation values for small streams.” In J.

Rolfe and J. Bennett (Eds.), Choice Modelling and the Transfer of Environmental Values

. Edward Elgar.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 9 

### Kitchell, J. F. (2007). The ecology of Lake Michigan: past, present, and future. Prepared for

Wiscon sin Electric Power Company, Oak Creek Facility.

Kitchell, J. F., O'Neill, R. V., Webb, D., Gallepp, G. W., Bartell, S. M., Koonce, J. F. and

Ausmus, B. S. (1979). Consumer Regulation of Nutrient Cycling. Bioscience , 29(1): 28

-

34.

Kopp, R. J., Smith, V. K. (1993). Valuing Natural Assets: The Economics of Natural Resource

Damage Assessment. Washington D.C.: Resources for the Future.

Kotchen, M. J., and Reiling, S. D. (2000). Environmental attitudes, motivations, and contingent

valuation of nonuse values: a c ase study involving endangered species. Ecological

Economics, 32(1), 93

- 107.

Krinsky, I., and Robb, A. L. (1986). On Approximating the Statistical Properties of Elasticities.

Review of Economics & Statistics , 68(4): 715.

Krishnamoorthy, R., Mohmed, H. E. S. and Shahulhameed, P. (2008). Temperature effect on

behavior, oxygen consumption, ammonia excretion and tolerance limit of the fish

fingerlings Alepes djidaba

. Journal of Environmental Science and Engineering , 50: 169

-

174.

Kuhfeld, W. F. (2010). Marketi ng Research Methods in SAS: Experimental Design, Choice,

Conjoint, and Graphical Techniques. Cary, NC: SAS Institute.

Kuhfeld, W. F., and Tobias, R. D. (2005). Large factorial designs for product engineering and

marketing research applications. Technometri cs , 47: 132

- 141.

Langford, T. E. L. (1990). Ecological effects of thermal discharges . Barking, Essex: Elsevier

Applied Science Publishers Ltd.

Layton, D. F. (2000). Random coefficient models for stated preference surveys. Journal of

Environmental Economic s and Management , 40(1): 21

- 36.

Leffler, C. W. (1972). Some effects of temperature on the growth and metabolic rate of juvenile

blue crabs, Callinectes sapidus, in the laboratory. Marine Biology, 14(2): 104

- 110.

Lew, D.K, and K. Wallmo. ( 2011 ) . External T ests of Scope and Embedding in Stated Preference

Choice Experiments: An Application to Endangered Species Valuation. Environmental

and Resource Economics , 48: 1

- 23.

Liao, J. C. (2007). A review of fish swimming mechanics and behaviour in altered flows.

Phi losophical Transactions of the Royal Society B: Biological Sciences , 362: 1973

- 1993.

Light, P. R., and Able, K. W. (2003). Juvenile atlantic menhaden ( Brevoortia tyrannus ) in

Delaware Bay, USA are the result of local and long

- distance recruitment. Estuari ne,

Coastal and Shelf Science , 57(5

- 6): 1007

- 1014.

Limnetics, Inc. (1974). An environmental study of the ecological effects of the thermal discharges

from Point Beach, Oak Creek, and Lakeside Power Plants on Lake Michigan. Study

conducted for Wisconsin Ele ctric Power Company by Limnetics, Inc. Milwaukee, WI.

Lin, B.

- h., Richards, H. S. and Terry, J. M. (1988). An Analysis of the Exvessel Demand for

Pacific Halibut. Marine Resource Economics , 4: 305

- 314.

Loomis, J., and Ekstrand, E. (1997). Economic Benefit s of Critical Habitat for the Mexican

Spotted Owl: A Scope Test Using a Multiple

- Bounded Contingent Valuation Survey.

Journal of Agricultural and Resource Economics , 22(2): 356

- 366.

Loomis, J., Kent, P., Strange, L., Fausch, K. and Covich, A. (2000). Meas uring the total

economic value of restoring ecosystem services in an impaired river basin: results from a

contingent valuation survey. Ecological Economics , 33(1): 103

- 117.

Lorda, E., Danila, D. J. and Miller, J. D. (2000). Application of a population dyn amics model to

the probabilistic assessment of cooling water intake effects of Millstone Nuclear Power

Station (Waterford, CT) on a nearby winter flounder spawning stock. Environmental

Science & Policy , 3(Supplement 1): 471

- 482.

Louviere, J. J., Hensher, D . A. and Swait, J. D. (2000). Stated Preference Methods: Analysis and

Application . Cambridge, UK: Cambridge University Press.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 10 

### Lovell, S., Economist, National Marine Fisheries Service, Office of Science and Technology

(2013). March 12, 2013.

Lupandin, A. I. (2005). Effect of Flow Turbulence on Swimming Speed of Fish. Biology Bulletin

, 32(5): 461

- 466.

MacKenzie, B. R. (2000). Turbulence, larval fish ecology and fisheries recruitment: a review of

field studies. Oceanologica Acta , 23(4): 357

- 375.

MacKenzie, B. R., and Kiorboe, T. (2000). Larval Fish Feeding and Turbulence: A Case for the

Downside. Limnology and Oceanography , 45(1): 1

- 10.

Mallin, M. A., Stone, K. L. and Pamperl, M. A. (1994). Phytoplankton community assessments of

seven southeast U.S. cooling reservoirs. Water Research , 28(3): 665

- 673.

Marrasse, C., Lim, E. and Caron, D. (1992). Seasonal and daily changes in bacterivory in a

coastal plankton community. Marine Ecology

- Progress Series , 82(3): 281

- 289.

Martinez

- Arroyo, A., Abundes, S., González, M. E. and Rosas, I. (2000). On the Influence of

Hot

- Water Discharges on Phytoplankton Communities from a Coastal Zone of the Gulf

o f Mexico. Water, Air & Soil Pollution , 119(1

- 4): 209

- 230.

Martinez

- Arroyo, A., Abundes, S., González, M. E. and Rosas, I. (2000). On the Influence of

Hot

- Water Discharges on Phytoplankton Communities from a Coastal Zone of the Gulf

of Mexico. Water, Air & Soil Pollution , 119(1

- 4): 209

- 230.

Mazany, L., Roy, N. and Schrank, W. E. (1996). Multi

- product allocation under imperfect raw

material supply conditions: the case of fish products. Applied Economics , 28(3): 387

- 396.

Mazzotta, M. J. (1996). Measuring Pu blic Values and Priorities for Natural Resources: An

Application to the Peconic Estuary System. PhD Dissertation, University of Rhode

Island.

McConnell, K. E. (1990). Models for Referendum Data: The Structure of Discrete Choice Models

for Contingent Valuat ion. Journal of Environmental Economics and Management , 18(1):

19

- 34.

McKean, A. (2007). $50 an Ounce: Can Montana’s paddlefish survive the growing international

demand for their eggs? Montana Outdoors , May

– June 2007. Available at:

http://fwp.mt.gov/mtout doors/HTML/articles/2007/Paddlefish.htm

McMahon, R. F. (1975). Effects of Artificially Elevated Water Temperatures on the Growth,

Reproduction and Life Cycle of a Natural Population of Physa Virgata Gould. Ecology

, 56(5): 1167

- 1175.

Meffe, G. K. (1992). T echno

- Arrogance and Halfway Technologies: Salmon Hatcheries on the

Pacific Coast of North America. Conservation Biology , 6(3): 350

- 354.

Michigan Department of Natural Resources (MDNR). (2002). Data from the 2001 Recreational

Angler Survey. Charlevoix Fish eries Research Station. Charlevoix, MI: Received from

David Clapp, Charlevoix Great Lakes Research Station.

Millstone Environmental Laboratory. (2009). Annual Report 2008: Monitoring the Marine

Environment of Long Island Sound at Millstone Power Station, W aterford, Connecticut.

Millstone, CT: Millstone Environmental Laboratory.

Milon, J. W., and Scrogin, D. (2006). Latent preferences and valuation of wetland ecosystem

restoration. Ecological Economics , 56: 162

- 175.

Mitchell, R. C., and Carson, R. T. (1989)

. Using Surveys to Value Public Goods: The Contingent

Valuation Method. Washington, D.C.: Resources for the Future.

Morrison, M., and Bennett, J. (2004). Valuing New South Wales rivers for use in benefit transfer.

Australian Journal of Agricultural and Res ource Economics , 48(4): 591

- 611.

Morrison, M., Bennett, J., Blamey, R. and Louviere, J. (2002). Choice Modeling and Tests of

Benefit Transfer. American Journal of Agricultural Economics , 84(1): 161

- 170.

Moss Landing Marine Laboratories. (2006). Ecologica l Effects of the Moss Landing Power Plant

Thermal Discharge: A report submitted to the Monterey Bay National Marine Sanctuary

Integrated Monitoring Network (SIMoN) and Monterey Bay Sanctuary Foundation.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 11 

### Mullineaux, L. S., and Garland, E. D. (1993). Larval Recruitment in Response to Manipulated

Field Flows. Marine Biology , 116(4): 667

- 683.

National Energy Testing Laboratory (NETL). (2009). Impact of Drought on United States Steam

Electric Power Plant Cooling Water Intakes and Related Water Management Issues . April

2009.

National Marine Fisheries Service (NMFS) of the National Oceanic and Atmospheric

Administration (NOAA). (2009). 2008 Report to Congress: The Status of U.S. Fisheries.

Silver Spring, MD. 23 pp.

National Marine Fisheries Service (NMFS) of the N ational Oceanic and Atmospheric

Administration (NOAA). (2004). Shortnose Sturgeon ( Acipenser brevirostrum ).

Available at: http://www.nmfs.noaa.gov/prot_res/species/fish/Shortnose_sturgeon.html.

Accessed October 14, 2004.

National Marine Fisheries Service ( NMFS) of the National Oceanic and Atmospheric

Administration (NOAA). (2010a). Fish Stock Sustainability Index: 2009 Quarter 4

Update Through December 31, 2009 (NOAA, U.S. Department of Commerce, Trans.).

Silver Spring, MD. 3 pp.

National Marine Fisheries S ervice (NMFS) of the National Oceanic and Atmospheric

Administration (NOAA). (2010b). NOAA Fisheries Geographic Information Systems,

Fisheries Data: Critical Habitat. Available at:

http://www.nmfs.noaa.gov/gis/data/critical.htm

National Marine Fisheries Se rvice (NMFS) of the National Oceanic and Atmospheric

Administration (NOAA). (2010c). NOAA National Marine Fisheries Service Southwest

Regional Office, GIS Data. Available at:

http://swr.nmfs.noaa.gov/salmon/layers/finalgis.htm

National Marine Fisheries Ser vice (NMFS) of the National Oceanic and Atmospheric

Administration (NOAA ). (2012a). Annual Commercial Landing Statistics. Available at:

http://www.st.nmfs.noaa.gov/commercial

- fisheries/commercial

- landings/annual

landings/index

National Marine Fisheries Ser vice (NMFS) of the National Oceanic and Atmospheric

Administration (NOAA). (2012b). Status of Stocks: 2nd Quarter: Office of Sustainable

Fisheries, National Oceanic and Atmospheric Administration (NOAA).

National Marine Fisheries Service (NMFS) of the Nati onal Oceanic and Atmospheric

Administration (NOAA). (2002). Marine Recreational Fisheries Statistics Survey

(MRFSS), Snapshot Query. Available at:

http://www.st.nmfs.noaa.gov/st1/recreational /queries/catch/snapshot.html

National Marine Fisheries Service (NMFS) of the National Oceanic and Atmospheric

Administration (NOAA). (2003). Marine Recreational Fisheries Statistics Intercept

Survey. Available at: http://www.st.nmfs.gov/recreational/the_mrfss.html

National Marine Fisheries Service (NMFS) of the Natio nal Oceanic and Atmospheric

Administration (NOAA). (2012c). Status of Stocks: Report on the Status of U.S.

Fisheries for 2011: Office of Sustainable Fisheries, National Oceanic and Atmospheric

Administration (NOAA).

National Marine Fisheries Service (NMFS) of the National Oceanic and Atmospheric

Administration (NOAA). (2001). Endangered Species Act

– Section 7 Consultation

Biological Opinion, the NMFS Highly Migratory Species Division Office of Sustainable

Fisheries’ proposal to authorize fisheries under th e Fishery Management Plan for Atlantic

Tunas, Swordfish, and Sharks (HMS FMP).

National Marine Fisheries Service (NMFS), U.S. Fish and Wildlife Service (USFWS). (1998a).

Recovery Plan for U.S. Pacific Populations of the East Pacific Green Turtle (Chelonia

mydas). Silver Spring, MD: National Marine Fisheries Service.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 12 

### National Marine Fisheries Service (NMFS), U.S. Fish and Wildlife Service (USFWS). (1998b).

Recovery Plan for U.S. Pacific Populations of the Olive Ridley Turtle (Lepidochelys

olivacea). Silver S pring, MD: National Marine Fisheries Service.

National Marine Fisheries Service (NMFS), U.S. Fish and Wildlife Service (USFWS). (2009).

Recovery Plan for the Northwest Atlantic Population of the Loggerhead Sea Turtle

(Caretta caretta), Second Revision. Sil ver Spring, MD: National Marine Fisheries

Service.

National Marine Protected Areas Center (NMPAC). (2006). A classification system for Marine

Protected Areas in the United States. Silver Spring, MD.

National Oceanic and Atmospheric Administration (NOAA). ( 2010). Environmental Sensitivity

Index (ESI) Maps: Office of Response and Restoration.

National Oceanic and Atmospheric Administration (NOAA). (2012). National Marine Protected

Areas Center: The Marine Protected Areas Inventory. Available at:

http://mpa.go v/dataanalysis/mpainventory/

National Research Council. (1990). Decline of the Sea Turtles: Causes and Prevention

. Washington, D.C.: National Academies Press.

Natural Resources Defense Council (NRDC) v. Kempthorne. (2007). 506 F. Supp. 2d 322 (E.D.

Cal. 2 007).

NatureServe. (2012). NatureServe Explorer: An Online Encyclopedia of Life. Available at:

http://www.natureserve.org/explorer/

New York State Department of Environmental Conservation (NYSDEC). (2003a). Fact Sheet:

New York State Pollutant Discharge El imination System (SPDES) Draft Permit Renewal

with Modification, Indian Point Electric Generating Station. Buchanan, NY.

New York State Department of Environmental Conservation (NYSDEC). (2003b). Final

Environmental Impact Statement: Concerning the Applica tions to Renew NYSPDES

Permits for the Roseton 1 & 2 and Indian Point 2 & 3 Steam Electric Generating Stations,

Orange, Rockland and Westchester Counties.

Norem, A. D. (2005). Injury assessment of Sea Turtles utilizing the neritic zone of the

Southeastern United States. Master of Science Thesis, University of Florida.

Northeast Fisheries Science Center (NEFSC) of the NOAA National Marine Fisheries Service.

(2008). Assessment of 19 Northeast Groundfish Stocks through 2007: Report of the 3rd

Groundfish Ass essment Review Meeting (GARM III), Northeast Fisheries Science

Center, Woods Hole, Massachusetts, August 4

- 8, 2008, U.S. Department of Commerce,

NOAA Fisheries, 884 pp.

Northeast Fisheries Science Center (NEFSC) of the NOAA National Marine Fisheries Servic e.

(2010). Northeast Fisheries Science Center Publications. Available at:

http://www.nefsc.noaa.gov/publications/

Northeast Fisheries Science Center (NEFSC) of the NOAA National Marine Fisheries Service.

(2011). 52nd Northeast Regional Stock Assessment Wor kshop (52nd SAW): Assessment

Summary Report.

Northeast Midwest Institute. (2010). Upper Mississippi River Basin. Available at:

http://www.nemw.org/index.php/policy

- areas/water

- and

- watersheds/upper

- mississippi

river

- basin. Accessed March 7, 2010

Nuclear Reg ulatory Commission (NRC). (2010). Notice: Nextera Energy Point Beach, LLC;

Point Beach Nuclear Plant, Units 1 and 2, Draft Environmental Assessment and Draft

Finding of No Significant Impact Related to the Proposed License Amendment To

Increase the Maximum Reactor Power.

Ohio Environmental Protection Agency (OEPA). (2010). Fact Sheet: National Pollution

Discharge Elimination System (DPDES) Permitting Program. Oregon, OH: Bayshore

Station. March 2010.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 13 

### Opaluch, J. J., Grigalunas, T. A., Mazzotta, M. J., Johns ton, R. J. and Diamantedes, J. (1999).

Recreational and Resource Economic Values for the Peconic Estuary Peconic Estuary

Program. Peace Dale, RI. 124 pp.

Opaluch, J. J., Grigalunas, T., Diamantides, J. and Mazzotta, M. J. (1995). Environmental

Economics in Estuary Management: The Peconic Estuary Program. Maritimes, 38(3): 21

-

23.

Opaluch, J. J., Grigalunas, T., Mazzotta, M. J., Diamantides, J. and Johnston, R. J. (1998).

Resource and Recreational Economic Values for the Peconic Estuary. Report prepared

for Peconic Estuary Program, Suffolk County Department of Health Services, Riverhead,

NY, by Economic Analysis, Inc., Peace Dale, RI.

Orme, B. (2010). Getting Started with Conjoint Analysis: Strategies for Product Design and

Pricing Research. Second Edition, M adison, WI, Research Publishers LLC.

Ovaskainen, O., Cornell, S. J. (2006). Space and Stochasticity in population dynamics.

Proceedings of the National Academy of Sciences of the United States of America , 103:

12781

- 12786.

Pacific Islands Fisheries Scienc e Center (PIFSC) of the NOAA National Marine Fisheries

Service. (2010a). Fishery Biology and Stock Assessment Division. Available at:

http://www.pifsc.noaa.gov/fbsad/index.php

Pacific Islands Fisheries Science Center (PIFSC) of the NOAA National Marine Fisheries

Service. (2010b). Pacific Islands Fisheries Science Center Staff Publications Database.

Available at: http://www.pifsc.noaa.gov/library/publication_search.php

Paine, R. T. (1966). Food web complexity and species diversity. American Naturalist , 10 0: 65

-

75.

Paine, R. T. (1969). A Note on Trophic Complexity and Community Stability. The American

Naturalist , 103(929): 91

- 93.

Palmer, M. A., Reidy Liermann, C. A., Nilsson, C., Flörke, M., Alcamo, J., Lake, P. S. and Bond,

N. (2008). Climate change and the world's river basins: anticipating management options.

Frontiers in Ecology and the Environment , 6(2): 81

- 89.

Pate, J., and Loomis, J. (1997). The effect of distance on willingness to pay values: a case study

of wetlands and salmon in California. Ecolo gical Economics , 20(3): 199

- 207.

Pauly, D., and Christensen, V. (1995). Primary Production Required to Sustain Global Fisheries.

Nature , 374(6519): 255

- 257.

Peterson, C. H., and Lubchenco, J. (1997). “Marine Ecosystem Services.” In G. C. Daily (Ed.),

Natu re’s Services, Societal Dependence on Natural Ecosystems (pp. 177

- 194).

Washington, D.C.: Island Press.

Plotkin, P. T., (Ed). (1995). National Marine Fisheries Service and U. S. Fish and Wildlife

Service Status Reviews for Sea Turtles Listed under the Enda ngered Species Act of 1973.

Silver Spring, MD: National Marine Fisheries Service.

Poe, G. L., Welsh, M. P. and Champ, P. A. (1997). Measuring the Difference in Mean

Willingness to Pay when Dichotomous Choice Contingent Valuation Responses are not

Independe nt. Land Economics , 73(2): 255

- 267.

Pohl, O. (2002). New jellyfish problem means jellyfish are not the only problem, New York

Times , May 21, 2002.

Polgar, T. T., Summers, J. K. and Haire, M. S. (1979). Evaluation of the effects of the

Morgantown SES cooli ng system on spawning and nursery areas of representative

important species. Final report. 149 pp.

Poornima, E. H., Rajadurai, M., Rao, T. S., Anupkumar, B., Rajamohan, R., Narasimhan, S. V.,

Rao, V. N. R., and Venugopalan, V. P. (2005). Impact of thermal discharge from a

tropical coastal power plant on phytoplankton. Journal of Thermal Biology , 30(4): 307

-

316.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 14 

### Postel, S., and Carpenter, S. (1997). “Freshwater Ecosystem Services.” In G. C. Daily (Ed.),

Nature’s Services, Societal Dependence on Natural Ecosy stems (pp. 195

- 214).

Washington, DC: Island Press.

Powe, N. A. (2007). Redesigning Environmental Valuation: Mixing Methods Within Stated

Preference Techniques . Cheltenham, UK: Edward Elgar.

Quinn, T. J., and Deriso, R. B. (1999). Quantitative Fish Dynamics . New York: Oxford

University Press.

Rago, P. J. (1984). Production forgone: An alternative method for assessing the consequences of

fish entrainment and impingement losses at power plants and other water intakes.

Ecological Modelling , 24(1

- 2): 79

- 111.

Rap port, D. J., and Whitford, W. G. (1999). How Ecosystems Respond to Stress. BioScience

, 49(3): 193

- 203.

Reznick, D., and Endler, J. A. (1982). The Impact of Predation on Life History Evolution in

Trinidadian Guppies ( Poecilia reticulata ). Evolution , 36(1): 160

- 177.

Richardson, L., and Loomis, J. (2009). The total economic value of threatened, endangered and

rare species: An updated meta

- analysis. Ecological Economics , 68(5): 1535

- 1548.

Ricker, W. E. (1975). Computation and interpretation of biological stat istics of fish populations.

Fisheries Research Board of Canada , Bulletin 191.

Rosenberger, R., and Phipps, T. (2007). “Correspondence and Convergence in Benefit Transfer

Accuracy: Meta

- Analytic Review of the Literature.” In S. NavrudR. Ready (Eds.),

Enviro nmental Value Transfer: Issues and Methods (Vol. 9, pp. 23

- 43): Springer

Netherlands.

Rowe, R. D., Shaw, W. D. and Schulze, W. (1992). “Nestucca Oil Spill.” In K. Ward and J.

Duffield (Eds.), Natural Resource Damages (pp. 527

- 554). New York: Wiley and Sons

. Ruhl, J. B., and Gregg, R. J. (2001). Integrating Ecosystem Services into Environmental Law: A

Case Study of Wetlands Mitigation Banking. Stanford Environmental Law Journal

, 20(2): 365

- 392.

Ruiz, G. M., Fofonoff, P. W., Carlton, J. T., Wonham, M. J. and Hines, A. H. (2000). Invasion of

Coastal Marine Communities in North America: Apparent Patterns, Processes, and

Biases. Annual Review of Ecology & Systematics , 31: 481

- 531.

Ruiz, G. M., Fofonoff, P., Anson, H. H. and Grosholz, E. D. (1999). Non

- Indigenou s Species as

Stressors in Estuarine and Marine Communities: Assessing Invasion Impacts and

Interactions. Limnology and Oceanography , 44(3): 950

- 972.

Salzman, J., Thompson Jr., B. H. and Daily, G. C. (2001). Protecting Ecosystem Services:

Science, Economic s, and Law. Stanford Environmental Law Journal , 20(2): 309

- 332.

Sanford, E. B., Bertness, D. and M. D. Gaines, S. D. (1994). Flow, food supply and acorn

barnacle population dynamics. Marine Ecology

- Progress Series , 104: 49

- 62.

Scarpa, R., Thiene, M. and Train, K. (2008). Utility in Willingness to Pay Space: A Tool to

Address Confounding Random Scale Effects in Destination Choice to the Alps. American

Journal of Agricultural Economics , 90(4): 994

– 1010.

Schiel, D. R., Steinbeck, J. R. and Foster, M. S. (2004). Ten Years of Induced Ocean Warming

Causes Comprehensive Changes in Marine Benthic Communities. Ecology , 85(7): 1833

-

1839.

Schkade, D. A., and Payne, J. W. (1994). How People Respond to Contingent Valuation

Questions: A Verba l Protocol Analysis of Willingness to Pay for an Environmental

Regulation. Journal of Environmental Economics and Management , 26(1): 88

- 109.

Shea, K., and Chesson, P. (2002). Community ecology theory as a framework for biological

invasions. Trends in Ecolo gy & Evolution , 17(4): 170

- 176.

Shrestha, R., Rosenberger, R. and Loomis, J. (2007). “Benefit Transfer Using Meta

- Analysis in

Recreation Economic Valuation, in Benefit Transfer Accuracy: Meta

- Analytic Review ofBenefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 15 

### the Literature.” In S. Navrud and R. Ready (E ds.), Environmental Value Transfer: Issues

and Methods (pp. 161

- 177). Dordrecht, The Netherlands: Kluwer Academic Publishers.

Smith, V. K., Van Houtven, G. and Pattanayak, S. K. (2002). Benefit Transfer via Preference

Calibration: 'Prudential Algebra' for Policy. Land Economics , 78(1): 132.

Smythe, A. G., and Sawyko, P. M. (2000). Field and laboratory evaluations of the effects of 'cold

shock' on fish resident in and around a thermal discharge: an overview. Environmental

Science & Policy , 3(Supplement 1): 225

- 232.

Southeast Fisheries Science Center (SEFC) of the NOAA National Marine Fisheries Service.

(2010). SouthEast Data, Assessment and Review (SEDAR). Available at:

http://www.sefsc.noaa.gov/sedar/

Southwest Fisheries Science Center (SWFSC) of the NOAA N ational Marine Fisheries Service.

(2010). Southwest Fisheries Science Center Fisheries Ecology Publications Database.

Available at:

http://swfsc.noaa.gov//publications/fedbin/qrypublications.asp?ParentMenuId=54

Speer, L., Lauck, L., Pikitch, E., Boa, S., D ropkin, L. and Spruill, V. (2000). Roe to Ruin: The

Decline of Sturgeon in the Caspian Sea and the Road to Recovery. Nartural Resources

Defense Council, Wildlife Conservation Society, and SeaWeb. December 2000.

Squires, D., Freese, S., Herkelrath, J. and Herrick, J., S.F. (1998). Cost

- Benefit Analysis of

Pacific Whiting Allocation: National Marine Fisheries Service, Southwest Fisheries

Science Center.

Squires, L. E., Rushforth, S. R. and Brotherson, J. D. (1979). Algal response to a thermal effluent:

study of a power station on the Provo River, Utah, USA. Hydrobiologia, 63(1): 17

- 32.

Stachowicz, J. J., and Byrnes, J. E. (2006). Species Diversity, invasion success, and ecosystem

functioning: disentangling the influence of resource competition, facilitation, and

extrinsic factors. Marine Ecology

- Progress Series , 311: 251

- 262.

Stapler, R. W., and Johnston, R. J. (2009). Meta

- Analysis, Benefit Transfer, and Methodological

Covariates: Implications for Transfer Error. Environmental Resource Economics , 42:

227

– 246.

Steeves, P., and Nebert, D. (1994). 1:250,000

- scale Hydrologic Units of the United States. U.S.

Geological Survey, Reston, VA.

Stevens, T. H., Echeverria, J., Glass, R. J., Hager, T. and More, T. A. (1991). Measuring the

Existence Value of Wildlife: W hat Do CVM Estimates Really Show? Land Economics

, 67(4): 390

- 400.

Stockwell, C. A., Hendry, A. P. and Kinnison, M. T. (2003). Contemporary evolution meets

conservation biology. Trends in Ecology & Evolution , 18(2): 94

- 101.

Sullivan, K., Martin, D. J., Car dwell, R. D., Toll, J. E. and Duke, S. (2000). An analysis of the

effects of temperature on salmonids of the Pacific Northwest with implications for

selecting temperature criteria. Portland, OR: Sustainable Ecosystems Institute.

Sumer, B. M., Kozakiewicz, A., Fredsoe, J. and Deigaard, R. (1996). Velocity and Concentration

Profiles in Sheet

- Flow Layer of Movable Bed. Journal of Hydraulic Engineering

, 122(10): 549

- 558.

Summers, J. K. (1989). Simulating the indirect effects of power plant entrainment losses o n an

estuarine ecosystem. Ecological Modelling , 49(1

- 2): 31

- 47.

Sun, J. F. (1995). Understanding the US Demand for Shrimp Imports and Welfare Distributions.

Paper presented at the International Cooperation for Fisheries and Aquaculture

Development: Proceed ings of the 7th Biennial Conference of the International Institute of

Fisheries Economics and Trade.

Swain, D. P., Sinclair, A. F. and Mark Hanson, J. (2007). Evolutionary response to size

- selective

mortality in an exploited fish population. Proceedings of the Royal Society B: Biological

Sciences , 274(1613): 1015

- 1022.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 16 

### Taylor, C. J. L. (2006). The effects of biological fouling control at coastal and estuarine power

stations. Marine Pollution Bulletin , 53(1

- 4): 30

- 48.

Teixeira, T. P., Neves, L. M. and Araúj o, F. G. (2009). Effects of a nuclear power plant thermal

discharge on habitat complexity and fish community structure in Ilha Grande Bay, Brazil.

Marine Environmental Research , 68(4): 188

- 195.

Terceiro, M. (2008). Southern New England/Mid

- Atlantic winter flounder. In Northeast Fisheries

Science Center (Ed.), Assessment of 19 Northeast Groundfish Stock through 2007:

Report of the 3rd Groundfish Assessment Review Meeting (GARM III) (pp. 2.457

- 452.528). Woods Hole, MA: Northeast Fisheries Science Center, U.S. Department of

Commerce.

Thomson, C., Economist, National Marine Fisheries Service, Southwest Fisheries Science Center

(2008). August 12 and 18, 2008.

Thunberg, E., Natural Resource Management Economist, U.S. National Marine Fisheries Service,

Social Scien ce Branch. (2008). August 8 and 22, 2008.

Thunberg, E. M., Bresnyan, E. W. and Adams, C. M. (1995). Economic analysis of technical

interdependencies and the value of effort in a multi

- species fishery. Marine Resource

Economics , 10: 59

- 76.

Thunberg, E., Squires, E., Economists, U.S. National Fisheries Service, Social Science Branch.

(2005). February 18, 2005.

Tondreau, R., Hey, J. and Shane, E. (1982). Missouri River Aquatic Ecology Studies: Ten Year

Summary (1972

- 1982). Sioux City, IA: Prepared for Iowa Public Service Company.

Train, K. E. (2009). Discrete Choice Methods with Simulation . Cambridge, UK: Cambridge

University Press.

Train, K. E., and Weeks., M. (2005). “Discrete Choice Models in Preference Space and Willing

to

- Pay Space.” In R. Scarpa and A. Alberini (Eds.), Applications of Simulation Methods

in Environmental and Resource Economics (pp. 1

– 16). Dordrecht, Netherlands: Springer.

Tsoa, E., Schrank, W. E. and Roy, N. (1982). U.S. Demand for Selected Groundfish Products,

1967

- 80. American Journal of Agricultural Economics , 64(3): 483

- 489.

Turner, S. J., Thrush, S. F., Hewitt, J. E., Cummings, V. J. and Funnell, G. (1999). Fishing

impacts and the degradation or loss of habitat structure. Fisheries Management &

Ecology , 6(5): 401

- 420.

Turtle Expert Working Group (TEWG). (2000). Assessment Update for the Kemp’s Ridley and

Loggerhead Sea Turtle Populations in the Western North Atlantic. U.S. Department of

Commerce, 115 pp.

U.S. Bureau of Labor Statistics (USBLS). (2011). Consumer Price Index History Ta ble: All Items

Indexes and Annual Percent Changes From 2013 to Present. Available at:

ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.txt

U.S. Census Bureau. ( 2010 ) . 2010 Census: Summary File 1. Accessed on 8/8/2012.

U.S. Census Bureau. ( 2009 ) . American C ommunity Survey Data 2006

- 2008.

U.S. Department of Energy ( USDOE ). (2013a). AEO 2013 National Energy Modeling System.

Electricity Supply, Disposition, Prices, and Emissions, Reference Case. United States

Energy Information Administration (EIA). Available at:

http://www.eia.gov/oiaf/aeo/tablebrowser/#release=AEO2013ER&subject=0

-

AEO2013ER&table=13

- AEO2013ER®ion=0

- 0&cases=early2013

- d102312a.

Accessed February 5, 2013

U.S. Department of Energy ( US DOE). (2013b). AEO 2013 National Energy Modeling System.

Ene rgy

- Related Carbon Dioxide Emissions by Sector and Source, United States,

Reference Case. United States Energy Information Administration (EIA). Available at:

http://www.eia.gov/oiaf/aeo/tablebrowser/#release=AEO2013ER&subject=0

-

AEO2013ER&table=13

- AEO2013E R®ion=0

- 0&cases=early2013

- d102312a.

Accessed February 5, 2013.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 17 

### U.S. Department of Energy ( US DOE). (2013c). Carbon Dioxide Emissions Coefficients by Fuel.

Available at: http://www.eia.gov/environment/emissions/co2_vol_mass.cfm. Accessed

February 14, 2013

. U.S. Department of the Interior (USDOI). (2008). Fisheries: Aquatic and Endangered Resources

Available at:

http://www.glsc.usgs.gov/main.php?content=research_risk&title=Species%20at%20Risk

0&menu=research. Accessed June 23, 2004.

U.S. Department of the I nterior Fish and Wildlife Service (USFWS), U.S. Department of

Commerce (USDOC) Economics and Statistics Administration and U.S. Census Bureau.

(2002). 2001 National Survey of Fishing, Hunting, and Wildlife

- Associated Recreation.

U.S. Environmental Protecti on Agency (USEPA). (1977). Interagency 316(a) Technical

Guidance Manual and Guide for Thermal Effects Sections of Nuclear Facilities’

Environmental Impact Statements. In Office of Water, Enforcement Permits Division,

Industrial Permits Branch (Ed.). Washin gton, D.C.

U.S. Environmental Protection Agency (USEPA). (2000). Section 316(b) Industry Survey.

Detailed Industry Questionnaire: Phase II Cooling Water Intake Structures and Industry

Short Technical Questionnaire: Phase II Cooling Water Intake Structures, January 2000

(OMB Control Number 2040

- 0213). Industry Screener Questionnaire: Phase I Cooling

Water Intake Structures, January, 1999 (OMB Control Number 2040

- 0203) (Vol. January

1999).

U.S. Environmental Protection Agency (USEPA). (2002a). Case Study Anal ysis for the Proposed

Section 316(b) Phase II Existing Facilities Rule. In Office of Water (Ed.).

U.S. Environmental Protection Agency (USEPA). (2002b). Clean Water Act NPDES Permitting

Determination for Thermal Discharge and Cooling Water Intake from Bray ton Point

Station in Somerset, MA. In United States Environmental Protection Agency Region 1:

New England (Ed.).

U.S. Environmental Protection Agency (USEPA). (2004a ) . Regional Analysis Document for the

Final Section 316(b) Phase II Existing Facilities Rul e. In Office of Science and

Technology Engineering and Analysis Division (Ed.).

U.S. Environmental Protection Agency (USEPA). (2004b). Technical Development Document

for the Proposed Section 316(b) Rule for Phase III Facilities. In Office of Water (Ed.).

U .S. Environmental Protection Agency (USEPA). (2006a). National Pollutant Discharge

Elimination System

- Final Regulations to Establish Requirements for Cooling Water

Intake Structures and Phase III Facilities, 40 CFR Parts 9, 122, 123, 124, and 125 C.F.R.

U.S. Environmental Protection Agency (USEPA). (2006b). Regional Benefits Analysis of the

Final Section 316(b) Phase III Existing Facilities Rule. In Office of Water (Ed.).

U.S. Environmental Protection Agency (USEPA). (2009a). National Fish Advisory Listin gs

2008: Technical Fact Sheet.

U.S. Environmental Protection Agency (USEPA). (2009b). Valuing the Protection of Ecological

Systems and Services: A Report of the EPA Science Advisory Board. In Office of the

Administrator, Science Advisory Board (Ed.).

U.S. Environmental Protection Agency (USEPA). (2010a). Guidelines for Preparing Economic

Analyses.

U.S. Environmental Protection Agency (USEPA). (2010b). National Estuary Program Booklet.

U.S. Environmental Protection Agency (USEPA). (2010c). Office of Wetlands website. Available

at: http://www.epa.gov/wetlands/awm

U.S. Environmental Protection Agency (USEPA). (2010d). Supporting Statement: Request to

Conduct Focus Groups, 316(b) Benefits Survey.

U.S. Environmental Protection Agency (USEPA). (2011a). Economic an d Benefits Analysis for

Proposed Section 316(b) Existing Facilities Regulation. EPA 821

- R

- 11

- 003, March 28,

2011.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 14

- 18 

### U.S. Environmental Protection Agency (USEPA). (2011b). Environmental and Economic

Benefits Analysis for Proposed Section 316(b) Existing Facil ities Rule. EPA 821

- R

- 11

- 002, March 28, 2011.

U.S. Environmental Protection Agency (USEPA). (2011c). Supporting Statement for Information

Collection Request for Willingness to Pay Survey §316(b) Existing Facilities Cooling

Water Intake Structures: Instrume nt, Pre

- test, and Implementation.

U.S. Environmental Protection Agency (USEPA). (2012a). 316(b) Stated Preference (SP) Survey

– Documentation for Survey Design Values Spreadsheet. Memorandum to the 316(b)

Existing Facilities Rule Record. June 2, 2012.

U.S . Environmental Protection Agency (USEPA). (2012b). 316(b) Stated Preference (SP) Survey

– Overview of Preliminary Modeling Exercises for Attribute Values. Memorandum to the

316(b) Existing Facilities Rule Record. June 2, 2012.

U.S. Environmental Protectio n Agency (USEPA). (2012c). 316(b) Stated Preference (SP) Survey

– Survey Methods and Model Results. Memorandum to the 316(b) Existing Facilities

Rule Record. June 5, 2012.

U.S. Environmental Protection Agency (USEPA). (2014). NEP Financing Strategies. Nati onal

Estuary Program, from http://water.epa.gov/type/oceb/nep/fund.cfm

U.S. Fish and Wildlife Service (USFWS). (2009). Federal and State Endangered and Threatened

Species Expenditures: Fiscal Year 2008. US Fish and Wildlife Service Endangered

Species Progr am. 252 pp.

U.S. Fish and Wildlife Service ( USFWS). (2010a). Critical Habitat Portal, from

http://crithab.fws.gov/

U.S. Fish and Wildlife Service (USFWS). (2010b). North Florida Ecological Services Office:

Loggerhead Sea Turtle ( Caretta caretta ). Available at:

http://www.fws.gov/northflorida/seaturtles/turtle%20factsheets/loggerhead

- sea

- turtle.htm

U.S. Fish and Wildlife Service (USFWS). (2010c). Sport Fish Restoration Program Final

Apportionments (1952

- 2010). Arlington, VA : United States Fish and Wildlife S ervice,

Wildlife and Sport Fish Restoration Program. 12 pp.

U.S. Fish and Wildlife Service (USFWS). (2011). Native Species Conservation. Great Lakes

- Big Rivers. Availablet at: http://www.fws.gov/midwest/Fisheries/topic

nativespecies.htm. Accessed March 7 , 2011.

U.S. Fish and Wildlife Service (USFWS). (2012a). Environmental Conservation Online System,

from http://ecos.fws.gov/tess_public/

U.S. Fish and Wildlife Service (USFWS). (2012b). Federal and State Endangered and Threatened

Species Expenditures: Fisc al Year 2011. US Fish and Wildlife Service Endangered

Species Program. 281 pp.

U.S. Geological Survey (USGS). (1990). Water Fact Sheet: Largest Rivers in the United States.

Reston, VA: U.S. Geological Survey, U.S. Department of the Interior.

U.S. Office of Management and Budget (USOMB). (2003). Circular A

- 4, September 17.

United States Army Corps of Engineers (USACE). (2013). Building on a Foundation of Strength:

Fiscal Year 2012 United States Army Annual Financial Report. U.S. Army Corps of

Engineers

– Civ il Works. 98 pp.

Upper Mississippi River Basin Association. (2004). River and Basin Facts. Available at:

http://www.umrba.org/facts.htm. Accessed June 23, 2004.

Vandenberg, T. P., Poe, G. L. and Powell, J. R. (2001). “Accessing the Accuracy of Benefits

Tra nsfer: Evidence from a Multi

- Site Contingent Valuation Study of Groundwater

Quality.” In J. C. Bergstrom, K. J. Boyle and G. L. Poe (Eds.), The Economic Value of

Water Quality (pp. 101

- 120). Cheltenham, UK: Edward Elgar.

Vanni, M. J., Layne, C. D. and Arno tt, S. E. (1997). "Top

- down" trophic interactions in lakes:

effects of fish on nutrient dynamics. Ecology , 78(1): 1

- 20.Benefits Analysis for the Final 316(b) Existing Facilities Rule Chapter 14: References

May 2014 1 4

- 19 

### Wainger, L. A., King, D., Salzman, J. and Boyd, J. (2001). Wetland Value Indicators for Scoring

Mitigation Trades. Stanford Environment al Law Journal , 20(2): 413

- 478.

Walsh, M. R., Munch, S. B., Chiba, S. and Conover, D. O. (2006). Maladaptive changes in

multiple traits caused by fishing: impediments to population recovery. Ecology Letters , 9:

142

- 148.

Walsh, R. G., Loomis, J. B. and Gil lman, R. A. (1984). Valuing Option, Existence, and Bequest

Demands for Wilderness. Land Economics , 60(1): 14

- 29.

Water Quality Act. (1987). (P.L. 100

- 4), §317(a)(1)(A) and (B) adding §320 to the CWA, 33,

US.C. §1330. 33 U.S.C. 1326(b), 33 USC 1268, Sec. 1 18(a)(3)(b).

Whitehead, J. C. (1993). Total Economic Values for Coastal and Marine Wildlife: Specification,

Validity, and Valuation Issues. Marine Resource Economics , 8(2): 119

- 132.

Whitehead, J. C., and Blomquist, G. C. (1991). Measuring Contingent Values for Wetlands:

Effects of Information About Related Environmental Goods. Water Resources Research

, 27(10): 2523

- 2531.

Wilson, M. A., and Carpenter, S. R. (1999). Economic Valuation o f Freshwater Ecosystem

Services in the United States: 1971

– 1997. Ecological Applications , 9(3): 772

- 783.

Wilson, R. W., Millero, F. J., Taylor, J. R., Walsh, P. J., Christensen, V., Jennings, S. and

Grosell, M. (2009). Contribution of Fish to the Marine In organic Carbon Cycle. Science

, 323(5912): 359

- 362.

Wisconsin Department of Natural Resources (Wisconsin DNR). (2003). Adrift on the sea of life.

Wisconsin Natural Resources, June, 17

- 21.

Wisconsin Power & Light Company (WPLC) v. Federal Energy Regulatory Commission

(FERC). (2004). 363 F.3d 453 (DC Circ. 2004).

Woodward, R. T., and Wui, Y.

- S. (2001). The economic value of wetland services: a meta

analysis. Ecological Economics , 37(2): 257

- 270.

Zhao, M., Johnston, R. J. and Schultz, E. T. (2013). What to Value and How? Ecological

Indicator Choices in Stated Preference Valuation. Env ironmental Resource Economics.

Published online February 8, 2013.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix A: Extrapolation Methods

May 2014 A

- 1 

# Appendix A: Extrapolation Methods

A.1 Introduction

This appendix provides detail on estimating facility

- level weights used in estimating benefits at a

regional level. EPA buil t its weighting approach on the sample weight s developed for

manufacturing facilities and electric power generating facilities in the analysis of 316(b) Phase II

and Phase III regulations ( USEPA 2004 a; USEPA 2006 b)

. EPA expanded on the existing

approach by developing new facility

- level weights that account for differences between electric

power facilities that received the Detailed Questionnaire (DQ) and those that received the Short

Technical Questionnaire (STQ), and to account for facility location, a key parameter in the

benefits analysis. EPA used this new set of “benefits weights” to estimate baseline IM&E losses

and reductions in IM&E losses under the final rule and other options considered and to adjust for

the timing of these reductions and associated benefits.



## A.2 Manufacturing Facilities

The current analysis of manufacturing facilities incorporates a set of weights that EPA developed

for the 2006 Final Phase III Rule , which EPA refers to as technical weights

. The technical

w eights are based on engineering information obtained from the 316(b) Manufacturers

Questionnaire . The technical weights account for the number of affected facilities and the cost of

installing new technology , but do not account for facility location or int ake flow at a regional

level. EPA developed additional adjustments to the technical weights because IM&E losses are a

function of facility location and intake flow. The purpose of the additional adjustments is to

ensure thatweighted regional mean operation al, or actual, intake flow (AIF)for survey facilities is

consistent with EPA’s best estimates for all regulated manufacturing facilities in each of eight

regions: North Atlantic, Mid

- Atlantic, South Atlantic, Gulf of Mexico, California, Pacific

Northwest, 81 

### Great Lakes, and Inland regions. 82



### EPA developed the weight adjustments separately for traditional manufacturers (MN facilities)

and non

- utility manufacturers (MU facilities). 83 

### Data was not available for total regional intake

flow for MN and MU facilities . Thus, rather than calibrating the weights based on flow, EPA

calibrated them based on facility counts such that the weighted number of surveyed facilities in

each region equals the total number of facilities in that region. This approach assumes that the

flow characteristics of the non

- surveyed facilities, which are represented by weights, are the same

as surveyed facilities (DQ facilities).

81 The Pacific Northwest region ultimately is excluded from the benefits analysis because it includes a single DQ

facilit y which is projected to close as baseline.

82 See Chapter 1 for additional information regarding regional definitions

.

83 MN facilities include aluminum, steel, chemical, pulp and paper, and petroleum refining manufacturing industries.

Note that Food and Kindred Products is not included in this list of industries for two reasons: a) this industry was

not included in the original stratification of manufacturers, and b) all facilities later identified to be in the Food and

Kindred Product industries were part of the MU universe

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix A: Extrapolation Methods

May 2014 A

- 2 

### The following two sections describe development of weight adjustment factors for MN and MU

facilities, respectivel y.

A.2.1 Traditional Manufacturers (MN Facilities)

EPA stratified the universe of MN facilities by region and industry category

. 84 

### EPA first

determined the distribution of regulated facilities by study region, and then calculated adjusted

benefits weights based on this distribution.

A.2.1.1 Determining the Distribution of Regulated Facilities by Study Region



### The industry survey requested that responding facilities provide Standard Industrial Classification

(SIC) codes. 85 

### EPA used PCS (Permit Compliance System) and ICIS

- NPDES (Integrated

Compliance Information System

- NPDES) to obtain latitude

- longitude coordinates (lat

- long ) for

all facilities in relevant SIC codes

. F acilities within relevant SIC code s were assigned to a study

region using lat

- long . A map of RF1 reaches was also used to indicate whether the facility location

is coastal/estuarine or inland

. 86 

### Table A

- 1 presents the distribution of the facility universe

according to region and industry based on the PCS/ICIS data.

The sample frame for the survey screener of manufacturing facilities did not include all facilities

in the relevant SIC codes. Information on which facilitie s were included is not available.

Therefore, EPA used two simplifying assumptions to develop weight adjustment factors: (1) the

total number regulated facilities in any single industry equals the sum of technical weights, 87 

### and

(2) the geographic distributi on of NPDES permitted facilities in the relevant SIC codes is

representative of the geographic distribution of regulated facilities.

For each industry, EPA assumed that the geographic distribution of facilities included in the EPA

PCS/ICIS database is equ ivalent to the geographic distribution of the DQ sample frame. To

implement this assumption, EPA redistributed the weights of DQ facilities in each study region to

match the geographic distribution of facilities in the PCS/ICIS database. The second and thi rd

columns in Table A

- 1 present the estimated distribution of regulated MN facilities based on

PCS/ICIS data. 88



### A.2.1.2 Calculating Adjusted Weights for the Benefits Analysis



### EPA first compared the regional distribution of DQ facilities to the distribution of facilities

present in the PCS/ICIS universe. Table A

- 1 presents the distribution of DQ facilities based on

technical weights, the weight adjustment factors for MN facilities, and the expected number of

84 EPA did not adjust w eights for petroleum refineries because survey screeners were sent to the entire universe and

DQs were sent to all regulated facilities. EPA assigned a weight of 1 to facilities determined to be in other

industries after receipt o f the DQ . No adjustment was made to these weights.

85 The SIC code describes the primary activity of the facility. EPA did not convert SIC codes to North American

Industry Classification codes (NAICS) when developing benefits weights because the industry survey used SIC

codes and relevant databases were searchable by SIC code.

86 EPA’s reach file (RF1) is a database of interconnected steam segments of “reaches” that comprise the surface

water drainage system for the United States.

87 As noted in Section A. 2, the technical weights account for the number of affected facilities.

88 EPA used the following databases to obtain information on the number of facilities in each SIC code: FRS

(Federal Registry System), PCS (Permit Compliance System), ICIS

- NPDES (Inte grated Compliance Information

System

- NPDES) and TRI (Toxics Release Inventory). None of these databases contains intake flow.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix A: Extrapolation Methods

May 2014 A

- 3 

### DQ facilities for all regions. EPA re

- estimated the number of DQ facilities in each region using

the PCS/ICIS distribution of facilities in that region. This adjustment factor was defined as the

quotient of the number of DQ facilities with in a region and industry divided by the original

number of weighte d DQ facilities assigned to the same stratum. If the PCS/ICIS facilities

universe indicated that a region had a small number of facilities within a single industry and did

not have DQ facilities (e.g., the North Atlantic region for the Aluminum sector), EPA assumed

that no regulated facilities exist within the stratum.

Because regions without DQ facilities comprised a small fraction of the PCS/ICIS facility

universe, this assumption is likely to introduce negligible error. If the adjusted weight for a

sample DQ facility was less than one, EPA used a weight of one to fully count the flow. In the

economic analysis, EPA estimated that 20 MN facilities will close under baseline conditions.

Accordingly, EPA excluded these facilities from the weights readjustment a nd benefits analysis.

The final two columns of Table A

- 1 present estimated total flow for each sector and region when

both original DQ and adjusted weights have been applied. In the paper and steel sectors, adjusted

weighted AIF is slightly smaller due to the lack of DQ facilities for those combinations of sector

and region. Conversely, adjusted

- weighted AIF in the chemical sector increases slightly due to

good coverage of DQ facilities, which shifted weights to facilities with above

- average flow.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix A: Extrapolation Methods

May 2014 A

- 4 

### Table A

- 1: MN DQ Distribution and Calculation of Weight Adjustment Factors

Benefits

Region Distribution of

Facilities in

PCS/ISIS DQ

weighted

Facility

Count a Adjustment

Factor b Adjusted

Weight

Facility

Count DQ

weighted

AIF Adjusted

Weighted

AIF 

### Number %

Aluminum

North Atlantic 7 6 % 0 c 0 0 0

Mid

- Atlantic 11 9% 0 0 0 0

South Atlantic 1 1% 0 0 0 0

Great Lakes 2 2% 3 0.09 0 0 0

Gulf of Mexico 1 1% 0 0 0 0

Pacific

Northwest 0 0% 0 0 0 0

California 0 0% 0 0 0 0

Inland 95 81% 13 1.01 13 87 88.3

Total 117 100% 16 13 87 88.3

Chemical

North Atlantic 16 1% 0 0 0 0

Mid

- Atlantic 75 6% 4 2.14 9 28.7 61.3

South Atlantic 9 1% 4 0.26 1 56.4 14.5

Great Lakes 32 3% 17 0.23 2 80.5 18.7

Gulf of Mexico 100 8% 4 2.85 12 283.9 809.8

Pacific

Northwest 4 0% 0 0 0 0

California 5 0% 4 0.14 1 1.5 0.4

Inland 951 80% 112 1.04 117 1,782.8 1,860.0

Total 1,192 100% 146 142 2,233.8 2,764.8

Paper

North Atlantic 2 1% 0 0 0 0

Mid

- Atlantic 7 2% 0 0 0 0

South Atlantic 8 2% 0 0 0 0

Great Lakes 19 5% 3 1.68 5 6.7 11.2

Gulf of Mexico 2 1% 0 0 0 0

Pacific

Northwest 3 1% 0 0 0 0

California d 0 0% 3 1 3 32.2 32.2

Inland 354 90% 91 0.95 84 1,193.3 1,134.30

Total 395 100% 96 91 1,232.2 1,177.7

Steel

North Atlantic 3 1% 0 0 0 0

Mid

- Atlantic 5 2% 0 0 0 0

South Atlantic 1 0% 0 0 0 0

Great Lakes 25 10% 6 0.54 3 2,054.3 1,112.1

Gulf of Mexico 3 1% 0 0 0 0

Pacific

Northwest 1 0% 0 0 0 0

California 2 1% 0 0 0 0

Inland 214 84% 28 1.03 29 519.6 535

Total 254 100% 34 32 2,573.9 1,647.1

Petroleum

North Atlantic 0 0% 0 0 0 0

Mid

- Atlantic 2 11% 2 1 2 203.4 203.4

South Atlantic 0 0% 0 0 0 0

Great Lakes 0 0% 0 e 0 0 0

Gulf of Mexico 1 5% 1 1 1 42.6 42.6Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix A: Extrapolation Methods

May 2014 A

- 5 

### Table A

- 1: MN DQ Distribution and Calculation of Weight Adjustment Factors

Benefits

Region Distribution of

Facilities in

PCS/ISIS DQ

weighted

Facility

Count a Adjustment

Factor b Adjusted

Weight

Facility

Count DQ

weighted

AIF Adjusted

Weighted

AIF 

### Number %

Pacific

Northwest 0 0% 0 0 0 0

California 1 5% 1 1 1 31.8 31.8

Inland 16 79% 16 1 16 391.2 391.2

Total 20 100% 20 20 668.9 668.9

Other

Inland 2 100% 2 1 2 4.6 4.6

Total 2 100% 2 2 4.6 4.6

Total for All Industries

North Atlantic 28 1% 0 0 0 0

Mid

- Atlantic 100 5% 6 11 232 264.7

South Atlantic 19 1% 4 1 56.4 14.5

Great Lakes 78 4% 29 10 2,141.4 1,142.0

Gulf of Mexico 107 5% 5 13 326.5 852.4

Pacific

Northwest 8 0% 0 0 0 0

California 8 0% 8 5 65.5 64.4

Inland 1,632 82% 261 260 3,978.5 4,013.4

Total 1,980 100% 314 300 6,800.4 6,351.4

a EPA did not adjust weights for petroleum refineries or facilities in “other industries” because they are not in the five SIC codes

for which EPA developed weights . EPA assumed that these facilities do not represent any other facilities.

b Blank cells indicate that an adjustment factor was not estimated.

c Though these regions account for more than 5 percent of a luminum manufacturers, the average flow for a luminum manufacturers

is less than 10 mgd . Potential benefits associate d with these facilities would be relatively minor.

d Although the PCS/ICIS data did not identify any p aper facilities in the California region, there is 1 facility in this region that

received a DQ with a weight of 3. This weight was not adjusted.

e There was 1 refinery in the Great Lakes region that received a DQ . However

, this facility was assessed as a baseline closure in the

economic analysis

, and thus receives an adjustment factor of 0 , and excluded from the benefits analysis.

Sources: U.S. EPA PCS and ICIS

- NPDES databases, U.S. EPA analysis for this report



### A.2.2 Non

- Utility Manufacturers (MU Facilities)

EPA accounted for the geographic distribution of MU facilities using a methodology similar to

that used for MN facilities. EPA adjusted the we ights so that the distribution of the weighted

number of DQ facilities matched the actual geographic distribution of the facility universe. Under

this approach, EPA first determined the distribution of regulated facility by study region, and then

calculate d adjusted weights for use in the benefits analysis.

A.2.2.1 Determining the Distribution of Regulated Facilities by Study Region



### The entire universe of MU facilities was known based on the survey screener, and the EPA used

the Online Tracking Information System (OTIS) facility

- finder tool was used to obtain facility

location data. 89 

### EPA distributed the universe of facilities among study regions based on the

regional distribution of MU facilities with location data from OTIS Facility

- finder.

89 While the survey screener asked for facilities’ flow, EPA was unable to develop adjustment factors using total

flow as a contr ol variable.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix A: Extrapolation Methods

May 2014 A

- 6 

### A.2.2.2 Calculat ing Adjusted Weights for the Benefits Analysis



### For each study region, EPA compared the estimated number of MU facilities with the DQ

weighted number of facilities in the region. An adjustment factor was calculated as the quotient of

the estimated number of facilities in each region divided by the DQ

- weighted number of facilities

in each region. If the adjusted weight for a facility was less than one, EPA assigned a weight of

one to account fully for the flow of the sampled facility. Accordingly, EPA exclude d 9 baseline

closures from the benefits analysis and weights readjustment

. 90 

### Adjustment factors and adjusted

flow by benefits region are presented in Table A

- 2.

Table A

- 2: MU Adjustment Factors and Adjusted Flow by Benefits Region

Benefits Region Facility

Distribution

from OTIS DQ

weighted

Facilities Adjustment

Factor a Total Original

Weighted Flow

(mgd) Total Adjusted

Weighted Flow

(mgd)

MU Facilities

North Atlantic 6 5 1.2 220.9 275.3

Mid

- Atlantic 4 7 0.5 474.5 384.9

South Atlantic 2 0 No DQs 0.0

Great Lakes 14 12 1.2 1,186.4 1,500.0

Gulf of Mexico 8 6 1.3 577.0 744.0

Pacific Northwest 0 1 0.0 0 0.0

California 2 1 2.0 3.6 7.3

Inland 16 4 17 5 0.9 6,841.7 6,615.2

Total 200 207 9,303.7 9,526.7

Non

- Utility ( NU ) Facilities Determined to be Manufacturers b

Inland N/A 12 1.0 386.7 386.7

Total

Grand Total N/A 219

- 9,690.4 9,913.3

Notes:

DQ = detailed questionnaire; mgd = millions of gallons per day; MU = Non

- utility manufacturers

a Blank cells indicate that an adjustment factor was not estimated.

b Two facilities that were surveyed as non

- utilities were later determined to be non

- utility manufacturers

, and are analyzed as such

in the economic and benefits analyses . Their weights were not adjusted because they we re not part of the original MU facility

universe and are both in the inland region. Given that the majority of MU facilities are located in the Inland region, the us e of

original weights is unlikely to bias regional benefit results.

Source: U.S. EPA analys is for this report



## A.3 Electric Power Generating Facilities

The benefits analysis for electric power generating facilities uses a combination of weights from

the 316(b) Phase II and Phase III analyses and new sample weights . Weights from Phase II and

Phase III accounted for non

- sampled facilities and non

- respondents to industry surveys and are

referred to as the original survey weights

. 91



### When estimating national

- level benefits, use of only survey weights based on facility

- s pecific

(e.g., size and engineering) characteristics can lead to conditional bias. In particular, th e original

survey weights do not not consider factors influencing the occurrence and size of benefits, such as

90 This total includes one facility that would be subject to the New York state regulation of CWIS.

91 In general, the original survey weights are numerically very low, as EPA had eithe r DQ or STQ information for

621 of the 634 regulated elect ric generating facilities. For more information on EPA’s Section 316(b) Industry

Surveys, refer to the Information Collection Request ( USEPA 2000 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix A: Extrapolation Methods

May 2014 A

- 7 

### the location of facilities subject to the fin al rule and regulatory options, AIF , similarities among

aquatic species affected by these facilities, and characteristics of commercial and recreational

fishing activities in the area. EPA used a post

- stratification weight adjustment to calculate

benefits weights that account for data dimensions not included in the original sample design.

These benefits weights re

- scale DQ

- based weights using additional information from the STQ so

that total regional flows represented by both weighting systems are equivalen t.

The remainder of this appendix describes the post

- stratification weight adjustment for electric

power generating facilities. Section A.3.1 describes how the strata were defined. Section A.3.2

presents and discusses the estimates resulting from the post

- stratified weighting schemes and

compares th ese to the original DQ weights.

A.3.1 Defining the Strata and Control Variables

EPA included six study regions when developing benefits weights for electric power generating

facilities: North Atlantic, Mid

- Atlan tic, South Atlantic, Gulf of Mexico, Great Lakes, Inland, and

California regions. Strata characteristics used to adjust weights are presented in Table A

- 3

.

IM&E is largely a function of mean AIF and characteristics of local fishery resources. Therefore,

re gional, non

- recirculated AIF is the most important factor in defining strata for the benefits

estimation. It is more important to group estimated total benefits by non

- recirculated intake flow

in a study region than by number of facilities. When calculatin g weights, EPA included a strata

based on a 125 mgd DIF so that benefit estimates accurately reflect changes in technology under

the final rule and other options considered under the regulation.

Table A

- 3: Matrix of Strata and Control Variables for Adjus ting DQ Weights for

Electric Generating Facilities

Strata AIF ( mgd )

Recirculating Facilities a Non

- Recirculating Facilities b

DIF < 125 mgd DIF > 125 mgd DIF < 125 mgd DIF > 125 mgd

North Atlantic 0 0 238 6,259

Mid

- Atlantic 68 0 257 24,203

South Atlantic 46 0 0 5,943

Gulf of Mexico 0 46 0 9,347

Great Lakes 57 181 255 14,774

Inland 1,397 16,060 1,753 98.653

California c 0 0 62 11,249

Total 1,569 16,286 2,564 170,428

Notes:

DQ = detailed questionnaire; AIF = actual intake flow; DIF = design intake flow; mgd = millions of gallons per day

a Recirculating facilities are facilities with closed

- cycle recirculating systems or impoundments that qualify as closed

cycle recirculating systems.

b Non

- recirculating facilities includes facilities with CWIS classified as once

- through.

c The California region includes three facilities in Hawaii.

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix A: Extrapolation Methods

May 2014 A

- 8 

### A.3.2 Comparison of Results of the Detailed Questionnaire and Post

- Stratified

Weighting Schemes

EPA assigned post

- stratification weights so that tabulations of total mean AIF for each region and

DIF threshold correspond to the best estimates of AIF. The best estimates, or control totals, for

each region are calculat ed using AIF data from the DQ and STQ, and facility

- level sample

weights that account for non

- sampled facilities and non

- respondents. The DQ total is the total

AIF of facilities to which weights adjustments are applied. Table A

- 4 summarizes DQ and control

totals by region, DIF threshold, and baseline recirculating technology. By design, the post

stratification estimate of me an AIF equals the control total estimate (i.e., benefits weights are the

quotient of the control total divided by the DQ total).

AIF is the most important factor in determining benefits. Therefore,, accounting for flow while

minimizing the variance of the weights is the best approach. This is accomplished by assigning an

equal weight to all facilities within a given stratum. One alternati ve would be to adjust the

original DQ weight, but that would increase the variance of new weights. The additional variance

is not likely to reflect the characteristics on which t h e estimates depend , and therefore these

weights would be inferior.

Table A

- 4: Comparison of Results of the DQ and Post

- Stratified Weighting Schemes a

Region AIF for Recirculating Facilities b AIF for Non

- Recirculating Facilities c

DIF < 125 mgd DIF > 125 mgd DIF < 125 mgd DIF > 125 mgd

DQ

Total

(mgd) Control

Total

(mgd) d DQ

Total

(mgd) Control

Total

(mgd) d DQ

Total

(mgd) Control

Total

(mgd) d DQ

Total

(mgd) Control

Total

(mgd) d

North Atlantic 0 0 0 0 209 238 3,163 6,259

Mid

- Atlantic 58 68 0 0 231 257 7,649 24,203

South Atlantic 0 46 0 0 0 0 2,391 5,943

Gulf of Mexico 0 0 46 46 0 0 5,963 9,347

Great Lakes 0 57 0 181 66 255 4,002 14,774

Inland 615 1,397 3,223 16,060 1,036 1,753 46,235 98.653

California e 0 0 0 0 62 62 1,205 11,249

Total 6 73 1,569 3,269 16,286 1,604 2,564 70,609 170,428

Notes:

DQ = detailed questionnaire; AIF= actual intake flow; DIF = design intake flow; mgd = millions of gallons per day

a A limited number of total STQ facilities did not have a DQ facility to represent them within the technology class (recirculating

versus non

- recirculating), region

, and DIF strata. Their flow was added to the respective totals for the other technology class when

calculating benefits weights, and is assigned the same benefits weights as the other technology class within the same region and

DIF stata

.

b Recirculating facili ties are facilities with closed

- cycle recirculating systems or impoundments that qualify as closed

- cycle

recirculating systems.

c Non

- recirculating facilities include facilities with CWIS classified as once

- through.

d The control totals are t he best estima tes for each region are calculated using operational flow data from DQ and STQ, and facility

level sample weights that account for non

- sampled facilities and non

- respondents.

e The California region includes three facilities in Hawaii.

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix A: Extrapolation Methods

May 2014 A

- 9 

## A. 4 Adjustment for State Regulations of CWIS

EPA also included an adjustment to account for the California and New York state regulations of

CWIS. The California state regulation requires closed

- cycle recirculating systems for coastal

electric generating facilities and the New York state regulation requires closed

- cycle recirculating

systems for all in

- state facilities with DIF greater than or equal to 20 mgd. Fourteen surveyed

facilities fall within the scope of the California state regulation and 32 surveyed facilities fall

within the scope of the New York state regulation. EPA’s benefits analysis assigns these facilities

baseline IM&E commensurate with compliance with the state regulations.

EPA included a weight adjustment to account for the state regulations because the assumed

technology (i.e., closed

- cycle recirculating system) at facilities which are within the scope of the

state regulations does not accurately represent technology at facilities which are not within the

sco pe of the state regulations. Failing to account for state regulations would result in the

underestimation of baseline IM&E losses and IM&E reductions under the final rule and options

considered.

EPA calculated the best estimate of flow for facilities subj ect to state regulations (i.e., control

flow) based on the difference between total DQ

- weighted flow in each region with these facilities

included and excluded from the weighting analysis. Table A

- 5 presents the regional DQ

- weighted

AIF and control AIF tot als for facilities subject to state regulations

. EPA adjusted the DQ

weighted total for each region upward to match the respective control total. In the California

region, EPA only adjusted weights for coastal generators within the state of California; it did not

adjust weights for California manufacturing facilities and Hawaii facilities which are not subject

to the state regulation. The Mid

- Atlantic, Great Lakes, and Inland regions all include facilities

which are subject to the New York state regulation. For these regions, EPA grouped generators

and manufacturers when estimating adjustment factors to ensure that each region had at least one

DQ facility to represent facilities within the region subject to the New York state regulation.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix A: Extrapolation Methods

May 2014 A

- 10 

### Table A

- 5: Matrix of Strata and Control Variables for Facilities Subject to State

Regulations for CWIS

Region Weighted AIF

Including Facilities

Subject to State

Regulations (mgd)

(a) Weighted AIF

Excluding Facilities

Subject to State

Regulations (mgd)

(b) DQ Total

(mgd) Control Total

(mgd)

(a

- b)

North Atlantic 6,772 6,772 0 0

Mid

- Atlantic 25,199 16,862 1,043 8,337

South Atlantic a 5,943 5,943 0 0

Gulf of Mexico 10,989 10,989 0 0

Great Lakes 17,639 13,840 281 3,799

Inland 131,291 127,730 3,351 3,561

California

–

Coastal Generators 10,175 0 895 10,175

California

–

Manufacturers and

Hawaii Facilities 1,221 1,221 0 0

Total 209,230 183,357 5,569 25,872

Notes:

AIF = actual intake flow; DQ = detailed questionnaire; mgd = millions of gallons per day

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 1 

# Appendix B: Consideration of Potential Effects due to Thermal

Discharges

B.1 Introduction

Impacts of thermal discharges, along with other stressors, are a relevant consideration when

assessing the potential impacts of electric power facility cooling water intakes and associated

discharges. Seve ral studies have demonstrated the adverse effects that increased temperatures or

altered seasonal thermal regimes have on local biota and fauna. In some cases, studies have

indicated little or no apparent harm is caused by the thermal discharges. This emph asizes the need

for NPDES permit writers to consider site

- specific factors when assessing the potential ecological

effects due to thermal discharges.

This appendix provides information on the general effects of thermal discharges on aquatic biota

and ecos ystems, considers the influence of site

- specific factors and environmental settings on

determining the level (if any) of ecological impacts, and discusses limitation and uncertainty

associated with thermal studies. This appendix also presents three case st udies from power

facilities in different environmental settings (Brayton Point Station, Quad Cities Nuclear Station,

and Point Beach Nuclear Plant) which underwent detailed thermal studies under CWA section

316(a) provisions, and which show the importance of site

- specific factors in determining the

potential for appreciable harm. The section 316(a) demonstrations described in the three case

studies represent unusually complete and thorough investigations of thermal impacts to receiving

aquatic ecosystems. Thermal investigations at other power facilities are highly site specific, but

typically have a much reduced scope and effort compared to those portrayed by the case studies.

It should be noted that even at power facilities where demonstrations of no appre ciable harm have

been made to regulatory authorities under section 316(a), supporting thermal studies nonetheless

often show periods during which thermal limits are exceeded. Impacts of thermal discharges

should therefore be revisited on a case

- by

- case bas is as conditions change, for example (i) if

facilities increase their power capacity (i.e., “uprate”) and increase thermal loads to the receiving

waterbody; (ii) if the thermal assimilative capacity of the receiving waterbody is otherwise

compromised; or ( iii) in the face of new evidence that cooling water discharges are causing

appreciable harm to the balanced, indigenous population/community of shellfish, fish, and

wildlife or fail to ensure the protection or propagation of the population. Such assessment s need

to consider the extent, duration, timing, and frequency of adverse thermal impacts, the target

threshold temperature for each species, the potential for adverse temperature effects on larger

ecological processes, and other relevant site

- specific fac tors.



## B.2 General Effects of Thermal Discharges on Aquatic Biota and

Ecosystems

Thermal discharges affect aquatic organisms by elevating water temperatures or altering seasonal

patterns of temperature change. Temperature is a vitally important variable for aquatic

ecosystems, affecting virtually all biota and biologically mediated processes, chemical reactions,

as well as structuring the physical environment of the water column. There is a well

- established

scientific literature cataloguing the impacts of el evated or variable temperature on a wideBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 2 

### spectrum of aquatic life, including numerous species

- specific determinations of thermal tolerance

limits for growth, survival, reproduction, and behavior (e.g., Beitinger et al. 2000 ; Leffler 1972 ;

McMahon 1975 )

.

Much of the relevant primary research on power plant thermal discharges dates from the 1970's

1980's; typically based on laboratory studies, field investigations, or environmental impact

assessments associated with the siting, permitting, and/or operation of power facilities with

sign ificant thermal plumes (e.g., Barnett 1972 ; Coles 1984 ; Hillman et al. 1977 ; Langford 1990

(for review) ; Squires et al. 1979 ) . These studies found that the thermal discharges may affect

aquatic species growth, survival, and reproduction, alter c ommunity diversity and density, and

may have led to shifts in ecological habitat. The character and magnitude of the observed impacts

varies among the studies, however.

Interest in this topic and relevant studies have also re

- emerged in the last decade a s part of a

greater effort associated with the assessment and characterization of potential eff ects of global

climate change ( e.g., Schiel et al. 2004 ) . The material below provides a representative, exemplary

mix of studies on thermal effects for organisms and communities in a range of trophic levels or

ecosystems with some emphasis on more recent research. The majority of the cited studies were

identified from internet searches and cross

- referencing appropriate p ermitting databases. 92



### B.2.1 Primary Producers

Thermal discharges affect aquatic primary production through direct effects on photosynthetic

activity and selection of temperature

- tolerant species in phytoplankton, periphyton, macroalgae

and submerged aquatic vegetation (SAV), and indirectly through tem perature

- related changes in

nutrient availability and grazer activities. Several studies reported that thermal discharges

substantially altered the local abundance and structure of the aquatic community, particularly

benthos and periphyton (e.g., Chuang et al. 2009 ; Martinez

- Arroyo et al. 2000 ; Schiel et al. 2004 ;

Squires et al. 1979 ) . Studies by Mallin et al. ( 1994 ) suggest that indirect effects of discharge

altered the phytoplankton community taxonomic structure near the outfall and in general, support

different communities of algae than those present in the background waters. Several authors

su ggest that residual chlorine (anti

- fouling agent) may also influence these patterns ( Choi et al.

2002 ; Moss Landing Marine Laboratories 2006 ; Poornima et al. 2005 )

.

B.2.2 Primary Heterotrophs

The bacterial and microbial components of aquatic ecosystems generally have a positive response

to increasing water temperature

– growth rates and bacterially mediated processes are enhanced

until temperature tolerance limits are approached. Most studies found that the growth rates of

bacteria and water temperatures are positively correlated. In contrast, Choi et al. ( 2002 ) found

lower rates of bacteria production near outfalls but attributes this effect to residual chlorine in th e

discharge water rather than temperature alone.

92 Abt Associates used several general search engines for preliminary searches for scientific and grey literature

including Scirus: http://www.scirus.com/; Google Scholar: http://scholar.google.com/ ; and Dogpile:

http://www.dogpile.com/ , as well as publicly available information from NPDES permits and related s ection

316a/316b studies.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 3 

### B.2.3 Zooplankton

Zooplankton and other pelagic macroinvertebrates typically increase their grazing activities and

growth rate in response to increased temperature. Marasse et al. ( 1992 ) observed a higher rate of

bacteria consumption (i.e., bacterivory) by samples of plankton that were incubated at higher

temperatures. Jiang et al. ( 2009 ) suggests that copepod species with larger body sizes are more

sensitive to thermal increases, and that this water temperature increase induces mortalities of

cope pods. As noted for other organisms, estuarine copepods have more tolerance to thermal stress

than those from more stenothermal, deepwater environments.

B.2.4 Benthic Community

Benthic species and communities are often particularly vulnerable to thermal di scharge due to

association with the substrate and limited ability to migrate from impacted areas. Growth rates

and spawning times are usually accelerated by increased temperature ( Barnett 1972 ) . McMahon

( 1975 ) and Leffler ( 1972 ) found that snails and blue crabs, respectively, exhibit more rapid

growth at higher temperatures, but both studies also obs erve greater species mortality. The study

by Coles ( 1984 ) found a positive effect with the thermal effluent as both the number of organisms

and the colonization b y coral reef propagules near the outfall were significantly greater than

background areas. A recent study of benthic communities and associated biota near a nuclear

power plant discharge show that the thermal pollution alters composition and decreases rich ness

in benthic cover ( Teixeira et al. 2009 )

.

B.2.5 Fish

Fish are extremely wel l

- studied with regard to temperature tolerance and thermal limits in both

the laboratory and field. The thermal habitat requirements of coldwater, coolwater, and

warmwater fish species are well

- characterized (e.g., Beitinger et al. 2000 ; Sullivan et al. 2000 )

, and these may be the basis for regulatory sub

- classification of water bodies. Thermal discharges

can influence the spatial distribution of fish due to direct responses to altered temperature (i.e.,

attraction, avoidance), effect on dissolved oxygen concentrations, and impacts to prey and habitat

availability ( Cooke et al. 2004 ; Sullivan et al. 2000 ) . Rapid fluctuations and decreases in water

temperature, usually associated with steep thermal gradients in temperate winter waters, can lead

to “cold shock” with reduced survival ( Ash et al. 1974 ; Deacutis 1978 )

.

Smyth e and Sawyko ( 2000 ) evaluat ed th e effect of “cold s hock” on fish and found no effect on

larger predator species, though a forage species (gizzard shad) had lower survival rates. Some

studies of thermal discharges have not observed significant effects in local fish communities.

Hi llman et al. ( 1977 ) and Krishnamoorthy et al. ( 2008 ) found that impact s on shore

- zone fish and

fingerlings from power station discharge s were minima l. A study o f salmonids by Sullivan et al.

( 2000 ) maintains that direct mortality from temperature is unlikely since acute lethal temperatures

are rarely, if ever, observed in the field

. Specifically, this study suggests that there is little or no

risk of mortality i f the annual maximum temperature is less than 26°C, but suggests a site

- specific

analysis when annual maximum temperatures exceed 24°C.

B.2.6 Ecosystem Functions and Services

In addition to the species

- specific impacts, investigators have looked at the effects of thermal

discharges on the structuring of species assemblages and communities, as well as secondaryBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 4 

### ecosystem function and services. Thermal discharges may have both d etrimental and beneficial

effects. For example, the bleaching and destruction of coral reefs by elevated thermal discharges

is well documented, but Coles ( 1984 ) i n the Moss Landing study found that the thermal effluent

may have some beneficial effects, such as enhancing new coral regrowth or providing preferred

water temperatures for avian birds and mammals.

Work in seven Southeastern U.S. cooling reservoirs indic ated that direct thermal effects on

phytoplankton communities were generally minimal, but that the smaller reservoirs were more

prone to algal blooms due to nutrient trapping and elevated temperatures ( Mallin et al. 1994 )

. Indirect effects of excessive thermal loads in these reservoirs caused ecosystem

- wide alterations

arising from both top

- down (higher trophic co nsumers) and bottom

- up (primary producers)

effects. Martinez

- Arroyo et al. ( 2000 ) found that phytoplankton subjected to elevated water

temperature exhibited lowered photosynthetic capaci ty and light harvesting efficiency, and

required more light to reach a net oxygen production. Thus, primary production and oxygen

levels, both critical ecosystem functions, may be decreased as a result of elevated temperatures.

Teixeira et al. ( 2009 ) evaluated the effect of thermal discharge on fish communities and habitat

structure in rocky substrates near a nuclear power plant in southeastern Brazil. Their studies

indicate the heated effluents affected habitat structure as well as fish community structure and its

eco

- spatial distribution. Lowered fish species richness was observed i n the impacted area,

attributed to a reduction in benthic cover of a habitat

- forming species ( Sargassum sp.).



## B.3 Influence of Site

- Specific Factors and Environmental Setting on

Thermal Effects

As noted above, the environmental setting (i.e., the nature of the receiving waters) can have a

pronounced influence on the potential for and the magnitude of adverse thermal impacts on biota.

While physical features near the discharge and temporal climatic patterns usually dictate the

observed level of thermal devia tions for any given discharge, several environmental factors may

be important in determining the magnitude of potential impacts, including: geographic location,

marine vs. freshwater environments, volume of receiving water, rate of water exchange, other

he at loads, and local habitats.

B.3.1 Geographic Location

Geographic location determines the duration and intensity of annual solar heating and usually

dictates the resulting maximum ambient temperatures for the receiving waters. The more

southerly the faci lity, the higher the seasonal temperature maxima is likely to be, increasing the

possibility of reaching upper thermal temperature limits for sensitive organisms. Despite

acclimation, relatively few North American aquatic organisms will tolerate chronic wa ter

temperatures in excess of 35

- 40 o 

### C ( Brock 1985 )

.

Northerly receiving waters will have lower maximum ambient temperatures in summer, but will

also exhibit greater seasonal variation; with a more extreme temperature gradient between

di scharge and surface water during winter. Conversely, sub

- tropical water temperatures have less

seasonal variation, and a more consistent thermal gradient is maintained between discharge and

ambient conditions. Adverse effects to aquatic organisms are gener ally most pronounced at the

acute and chronic high lethal temperatures and/or due to rapid fluctuations (e.g., "cold shock").Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 5 

### B.3.2 Marine vs. Freshwater Receiving Waters

Adverse thermal impacts have been documented in both freshwater and marine ecosystems , but

the likelihood of impacts may be considered slightly greater in freshwaters simply due to the

presumption that marine waters constitute a greater thermal reservoir due to larger volume and

tidal flushing. However, as noted above, site

- specific featur es will dictate the effective volume

and the flushing rate, which are likely to be the key to vulnerability of receiving water ecosystem

to thermal impacts. Clearly, the magnitude of thermal impacts also depends on the composition of

the local biota and wh ether such organisms are temperature

- sensitive. The sensitivity of

coldwater freshwater fish (e.g., trout, salmonids, darters) to increased water temperature and

associated lowering of available dissolved oxygen has been well characterized ( Beitinger et al.

2000 ; Sullivan et al. 2000 ) . There is less temperature

- sensitivity in marine estuarine fish, which

are often more tolerant than offshore fish, since estuarine fish are subject to regular

environmental fluctuations.

B.3.3 Receiving Water Volume

The volume of the receiving water is a critical factor since it determines the total amount of heat

that can be absorbed by a water body while still remaining at an acceptable temperature. The

effective volume subject to the thermal discharge may be significantly less than that of the entire

water body if it is constrained physically (e.g., narrow discharge channel, small coastal

embayment) or can vary in the short term (e.g., low tide, hydropower releases), seasonally (e.g.,

thermall y stratified lakes, salinity stratified estuary), or longer (e.g., multi

- year droughts). Due to

the buoyant properties of warm water, the effective mixed volume can be reduced even further if

the thermal plume is not effectively or rapidly mixed into the r eceiving waters.

B.3.4 Rate of Water Exchange

The rate of water exchange is another factor which can compensate for a small effective volume.

A short hydraulic residence time (HRT) (i.e., rapid flushing) of the receiving water at the point of

the thermal discharge can rapidly dissipate a high heat load. Large fast rivers, open ocean outfalls,

and coastal embayments with sweeping longshore currents, etc. can generally better tolerate

thermal discharges and have limited or highly localized impacts to biota. Poorly flushed systems,

those with seasonal flow minima, or episodic hydrologic inputs, are more likely to experience

widespread or persistent thermal impacts. In some cases, the flow or volume of the thermal

discharge may be very much greater than the re ceiving water.

B.3.5 Local Land Use

Local land uses may also be influential in that they can provide additional thermal load s to the

water body independent of the thermal discharge. Developed urban watersheds with large

percentages of impervious cover may produce large storm water flow s with temperatures that are

well above ambient temperatures in the receiving waters. Agricultural lands and irrigation return

water may also increase local thermal loading. Channelization and removal of riparian buffer

ve getation can increase water temperature through lack of shading, reflective artificial substrates,

and removal of deep pool habitats.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 6 

### B.3.6 Local Habitats

Benthic biota and/or habitats (e.g., oyster reefs, eelgrass, and mussel beds) found in nearshore

en vironments are often subject to greater impact since these largely sessile communities are

affixed to the substrate. On the other hand, mobile aquatic organisms can track temperature

change and fine

- tune their temporal and spatial distribution ( Cooke et al. 2004 ) . Biota can

sometimes avoid adverse thermal impacts by seeking out localized areas of cooler or better

aerated waters (e.g., deep pool, tributary stream, bottom waters) for short

- term or seasonal

residence. These areas provide habitat that may allow the temperature

- sensitive organisms to

persist and emigrate back into the affected water body once the thermal stress is reduced. Thermal

effects could be more severe in homogenous environments (e.g., open water column , unstratified

reservoir) where the biota does not have access to these refugia. Thermal displacements from

spawning habitat due to dam construction and operation (e.g., bottom water releases) has also

been a concern in western rivers and elsewhere ( Bartholow et al. 2004 ; Hayes et al. 2006 )

.



## B.4 Uncertainties and Limitations of Assessing Thermal Impacts

One of the major difficulties in accurately characterizing the influence of thermal discharges on

aquatic communities is the uncertainty due to the potential influence of other a biotic water quality

factors. Thermal discharges from power plant cooling systems often contain elevated levels of

additional constituents including, but not restricted to: residual chlorine, total suspended solids,

total dissolved solids, cleaning agents and surfactants, metals, and nutrients. The presence of

these constituents may complicate the interpretation of the environmental factor(s) that are

responsible for observed changes in biotic communities.

For example, several of our studies on thermal ef fects on primary producers noted that residual

chlorine in the discharge may be responsible for some of the observed effects ( Chuang et al.

2009 ; Poornima et al. 2005 ) . Interaction of thermal effects and heavy metals was responsible for

some phytoplankton taxonomic changes in one reservoir investigated by Mallin et al. ( 1994 )

. Looking at the behavior of smallmouth bass, Cooke et al ( 2004 ) found that a majority of a local

radio

- tagged population overwintered in the warmest portions of a thermal discharge to Lake

Erie. However, this area also was high in habitat complexity, had adequate flow velocity refuges,

and abundant forage, so selection for this habitat may not be a simple thermal preference.

Adverse temperature effects may also be more pronounced in aquatic ecosystems which are

already subject to other environmental stressors such as high biochemical oxygen demand (BOD)

levels, sediment con tamination, or pathogens. Thermal discharges may have indirect effects on

fish and other vertebrate populations through increasing pathogen growth and infection rates.

Langford ( 1990 ) reviewed several studies on disease incidence and te mperature, and while he

found no simple, causal relationship between the two, he did note that it was clear that warmer

water enhances the growth rates and survival of pathogens, and that infection rates tended to be

lower in cooler waters.



## B.5 Case Studie s

Three case studies were selected for large power generating stations from which thermal

discharges may have a potential impact to the local aquatic community/ecosystem. These three

case studies provide examples of investigations of thermal impacts in dif ferent environmentalBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 7 

### settings (marine coastal embayment, coastal Great Lake, and freshwater river), and at differing

spatial scales (community, habitat, ecosystem).

B.5.1 Brayton Point Station

Brayton Point Station (BPS) is a 1538 megawatt (MW) coal and oil

- fired electrical generating

station located in Somerset, MA. This facility takes cooling water from and discharges heated

effluent to Mount Hope Bay (MHB), a large coastal embayment within Massachusetts and Rhode

Island. Generation Unit 1 began operati ng in 1963, Unit 2 in 1964, Unit 3 in 1969, and Unit 4 in

1974 ( Dominion 2011 )

.

One of th e most thorough examinations of the individual and cumulative effects of a power plant

thermal discharge was conducted as part of the regulatory review of the CWA section 316(a)

variance request application submitted in May 2001 as part of the NPDES discha rge permit

(Permit No. MA 003654) renewal for BPS. The permitee’s 316(a) variance request application

sought to keep the existing permit temperature criteria (maximum temperature of 95 o 

### F; delta

(departure from ambient) temperature of 22 o 

### F), and to reduce the total heat load from the existing

permit limits. However, these thermal criteria were still less stringent than what would be

required by either technology

- based or water quality

- based discharge limits.

CWA 316(a) authorizes alternative thermal disch arge limits when it is demonstrable that the

proposed thermal limits “will assure the protection and propagation of a balanced indigenous

population (BIP) of shellfish, fish, and wildlife in and on that body of water.” To evaluate

whether the thermal limit s proposed in the May 2001 316(a) variance request application would

meet this protective criterion, EPA, in accordance with the 316(a) Technical Guidance Manual

( USEPA 1977 ) , conducted a review of the historical and current conditions of MHB biota on a

community

- by

- commun ity evaluation, and considered potential thermal impacts to

phytoplankton, zooplankton, habitat formers, shellfish, finfish, and other vertebrate (i.e., sea

turtles and mammalian) wildlife. The findings of the community impact analyses are contained in

the “ Clean Water Act NPDES Permitting Determinations for Thermal Discharge and Cooling

Water Intake from Brayton Point Station in Somerset, MA ” ( USEPA 2002 a) dated July 22, 2002

(hereafter “ Determinations ”) and summarized below.

For each of the community types, the Determinations provi des a preliminary consideration of

whether the community’s nature, estuarine setting, and water column distribution within MHB

relative to the location and magnitude of the BPS thermal discharge would result in a finding of

“low potential impact areas” and lessened environmental concerns for the granting of the 316(a)

variance. For those communities in MHB for which a “low potential impact” conclusion was not

possible, the severity of the thermal effect was gauged by comparison to a list of a priori decisio n

criteria for each community.

EPA judged that MBH was not a low potential impact area for phytoplankton. As seagrasses and

salt marshes have historically declined in importance in MHB, the phytoplankton community is

the dominant primary producer ( USEPA 2002 a) . The recent (2001) occu rrence of a nuisance

blue

- green algal bloom (dominated by the cyanophyte Anacystis aeruginosa ) in MHB near BPS

may be due to the high nutrients and warm water temperatures which favor formation of such

bloom. It was considered likely that thermal plume fro m BPS was a contributing factor.

Perhaps of greater importance is the finding that the MHB phytoplankton community does not

undergo the typical winter

- spring phytoplankton bloom cycle ( Keller et al. 1999 ) . Extensive workBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 8 

### was conducted on plankton communities in experimental mesocosms where temperature was

shifted to mimic the expected thermal conditions in MHB surface wate rs. Extrapolating these

changes seen in the mesocosms, such changes in phytoplankton population dynamics could very

likely lead to significant impacts within the trophic dynamics of the MHB food web. Redirecting

carbon away from benthic consumers and into pelagic food webs could represent a reduction in

prey species for benthic

- feeding finfish such as winter flounder, windowpane flounder,

hogchoker, and tautog.

EPA judged that MHB was not a low potential impact area for zooplankton since it is an estuary

t hat serves as a spawning site for numerous fish and invertebrate species ( USEPA 2002 a) . The

most noticeable thermal effect in this community is the recent increase in abundance of the

ctenophore Mneimiopsis leid y i , and increased overwintering in MHB for this formerly seasonal

resident. Dramatic increases in comb jellies (i.e., ctenophores) are usually indicative of stressed

ecosystems with symptoms of increased water temperatures, increased nutrient levels, and

depleted fish stocks ( Pohl 2002 ) . Since M. leidyi is a voracious consumer of pelagic fish eggs as

well as zooplankton by which it competes with young

- of

- year winter flounder, it was concluded

that BPS was significantly contributing to thermal increases in MHB

, and facilitating expansion

of the range and time of year distribution of the comb jellies.

Eelgrass is a coldwater plant that ranges from North Carolina to Canada and grows well in soft

bottom, low energy environments. Despite the current lack of eelgrass, the EPA judged that MBH

was not a low potential impact area for habitat formers since the historic presence of extensive

eelgrass meadows shows that it is capable of supporting this habitat type ( USEPA 2002 a)

. Experimental work has shown that optimal temperature ranges for photosynthesis decrease with

increasing turbidity ( Bulthuis 1987 ) so that in turbid waters, eelgrass growth decreases with

increased temperature, because photosynthetic rates decrease and respiration rates increase. Based

on the current lack of eelgrass, it was concluded that the combination of poor water quality and

increased water temperature result in an “exclusion zone” for eelgrass growth in M HB ( USEPA

2002 a) . Since BPS he lps to elevate the water temperature over significant portions of the bay, it is

considered a contributory cause to this exclusion.

EPA judged that MBH was not a low potential impact area for shellfish and macroinvertebrates

due to the presence of commerci ally important species, the “substantial” densities of these

species, the spawning and nursery areas in MHB, and the important role in ecosystem function

that this community provides ( USEPA 2002 a) . Benthic sampling indicated that there have been

no significant changes in the benthic co mmunity between the 1970’s and mid

- 1990’s or over the

span of time when BPS has been active and the annual heat flux was increased. The sampling also

indicates a strong representation in the benthic community of the amphipod Ampelisca which is a

preferred prey item for juvenile winter flounder. Overall, EPA found no substantial evidence of

harm to shellfish and macroinvertebrates from the current thermal discharge, and any alternative

which reduces the thermal discharge would be acceptable.

EPA judged that MHB was not a low potential impact area for finfish due to the presence of

numerous recreational and commercially important species, the important spawning and nursery

areas, and the potential for blockage of fish migration ( USEPA 2002 a) . The analysis for finfish

was specifically targe ted at determining the appropriate thermal discharge limits for BPS in order

to protect finfish populations, and included a retrospective examination of total finfish abundance

trends in relation to plant operations. The analysis determined an acceptable a nnual flux of heat

into MHB that is protective of finfish populations, based on the temperature thresholds for acuteBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 9 

### and chronic mortality as well as for several sub

- lethal effects for some representative important

species (RIS).

The finfish stocks in MHB have declined precipitously since 1984

- 1985, a period which marked

the shift of Unit 4 at BPS from closed

- cycle recirculating to once

- through cooling operations.

Further, work by Gibson ( 2002 ) suggests that winter f lounder have been declining since at least

the initiation of sampling in 1972. Although BPS had been operational for 9 years at that point,

no fishery data are available to estimate what the finfish community was like prior to 1972.

Comparison of the recor d of annual heat flux to MHB over that last 28 year period to records of

finfish abundance led EPA to conclude that an annual heat flux of 28 trillion British thermal units

(tBTU) to MHB, as proposed in the 316(a) variance request application, would be una ble to stop

or reverse a decline in fish populations, and thus would not be protective of the finfish

community.

The temperature tolerance limits of 16 RIS were reviewed to establish temperature thresholds for

the more sensitive of these species (winter fl ounder, striped bass). These thresholds were used to

establish critical temperatures for three target depth strata (surface, middle, and bottom waters) at

two key seasonal periods (winter, summer). Winter corresponds to the period (March 1

- 31) of

active w inter flounder spawning, and when large numbers of larval planktonic winter flounder are

present in MHB. The summer index period (July 15

– August 15) corresponds to the warmest

time of the year.

Predictive hydrothermal models (CORMIX for near

- field effe cts; WQMAP for far

- field effects)

of MHB provided a means of evaluating the potential thermal impacts caused by the current (i.e.,

existing permit), the proposed (i.e., the requested 316(a) variance), and two alternative reduced

heat flux options for BPS o perations, as well as a “no

- plant” condition. During warm summer

conditions, the proposed operational heat flux would impact 62 percent of the bottom water strata

as compared to 4 percent under a no

- plant scenario, while other alternative operating options

would have reduced impact proportional to their proposed total heat fluxes. Using this method, it

is possible to show impacts to all target depth strata during summer conditions and impacts to the

bottom strata during winter.

The study also considered o ther heat effects on finfish caused by the thermal discharge. The first

involved the attractive nuisance nature of the thermal plume ( USEPA 2002 a) . The plume acts as

an attractant for large numbers of striped bass and bluefish in the fall and winter, and disrupts the

seasonal migration of these species. The crowding of large numbers of these species into a

restricted area increases the potential for weakening or disease since the warm temperatures

increase the metabolism of these fish at the same time there is reduced feeding due to a l ack of

prey.

Similarly, the trapping of Atlantic menhaden in the thermal plume affects the migration of this

species, and likely increases impingement mortality and entrainment (IM&E) due to longer

periods spent in proximity to intake structures, which ha s been evidenced by several recent large

winter impingement loss events. Another effect noted was the establishment in MHB of

smallmouth flounder ( Etropus microstomus ) which is at the northern limit of its geographic

distribution range. It is important to note that an increased abundance or distribution shift to a

warm water species is not indicative of protection of a BIP.

EPA judged that MBH is a low potential impact area for other vertebrate life since it is not a

significant habitat for marine mammals or sea turtles ( USEPA 2002 a) . Overall, there is noBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 10 

### potential for harm from the current thermal discharge, and any alternative which reduces the

thermal discharge would be acceptable.

A summary of current ecosystem thermal effects and predicted impacts associated with the

proposed thermal flux was prepared ( USEPA 2002 a) . The current thermal effects for which there

appears to be no disagreement include:

 Appearance of nuisance algal bloo ms;

 Absence of normal winter

- spring phytoplankton bloom;

 Overwintering of the ctenophore Mneimiopsis leidyi ;

 Overwintering of striped bass and bluefish in discharge canal;

 Increased abundance of smallmouth flounder in MHB;

 Thermal avoidance of most of MHB by adult winter flounder; and

 Multiple fish kills as a result of large impingement events in the winter.

Evaluating the proposed 316(a) variance request, EPA predicted that, under the proposed thermal

discharge under the 316(a) variance request, the fo llowing would occur:

 Large areas of MHB would be avoided by juvenile winter flounder and striped bass

during warm summer months;

 Extensive areas of MHB would experience water temperatures resulting in chronic

toxicity to juvenile winter flounder;

 Reduced w inter flounder egg hatching success for the entire MHB for the warmest winter

months;

 Increased predation on winter flounder eggs and larvae by sand shrimp; and

 Potential exclusion of eelgrass.

EPA also considered potential impacts from other stressors th at could be responsible for mortality

of finfish in MHB; including overfishing, predators, water quality, brown tides, and I M &E

( USEPA 2002 a) . Each of these stressors was examined for its potential role in causing or

contributing to the finfish collapse

. Analyses of these othe r potent ial stressors indicated that while

possibly contributory, the adverse effects of each were generally exacerbated by the thermal

conditions caused by the BPS plume

.

Based on the hydrothermal and ecological analyses conducted and documented in the

Determina tions document, EPA concluded that a BIP has not been maintained in MHB, and that

the current BPS thermal discharge is a significant contributor to this problem ( USEPA 2002 a)

. Further, the proposed thermal reductions in annual heat flux contained in the 316(a) variance

request applicat ion would not allow for the recovery of the winter flounder or the wider balanced

indigenous ecosystem. Accordingly, EPA denied the permitee’s variance request, and reissued the

NPDES permit in 2003 with the provision for installing closed

- cycle recirculat ing systems in all

four of the power units.

B.5.2 Quad Cities Nuclear Station

Quad Cities Nuclear Station (QCNS) is a dual

- unit nuclear fueled steam electric generating

facility (SIC 4911) located on a 765

- acre site along the Mississippi River in Cordova, Illinois

. QCNS Units I ( 866 net megawatts (MW) ) and 2 ( 871 net MW ) began commercial production of

electricity in 1973. QCNS withdraws water from the Mississippi River for non

- contact condenser

cooling and various service water uses. After passing through the condensers, the cooling water

from Units 1 and 2 mixes and then exits to the River via a discharge canal. QCNS is located onBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 11 

### Pool 14 of the Mississippi River, at approximate River Mile 506.5 above the confluence of the

Ohio River.

The thermal discharge is authorized under the Station’s NPDES Permit, issued by the Illinois

EPA ( ILEPA ) . Thermal limits in the NPDES Permit are based on Illinois environmental

regulations, and studies and Demonstrations related to the thermal plume are performed under

CWA s ection 316(a). During the latest NDPES permit renewal cycle, QCNS requested issuance

of a 316(a) variance for a propos ed alternative thermal standard, specifically relaxation of a

maximu m thermal excursion temperature limits by 2 o 

### F during late summer months (July

September), which would increase the predicted frequency of expected thermal excursions from 1

percent to 3 percent. This variance request was based on a demonstration that futu re operations

of QCNS would assure the protection and propagation of a balanced indigenous community

(BIC) of fish, wildlife, and shellfish , particularly within Pool 14

.

To evaluate the potential thermal impacts of QCNS’ discharge on Pool 14, a number of

c omprehensive studies were conducted (including thermal plume modeling and field surveys,

review of current (“prospective analysis”) and historic (“retrospective demonstration”) biota

monitoring, and water quality assessment. The thermal plume modeling is c ontained in “ 

## River

temperature predictions downstream of Quad Cities Nuclear Generating Station ” ( Holly Jr.

et al. 2004 )

. The elements and findings of the biological and water quality assessments are

contained in the “ Quad Cities Nuclear Station Adjusted Thermal Standard CWA 316(a)

Demonstration

, Final Draft ” ( HDR 2009 ) dated November 2009 (hereafter “ De monstration ”) and

summarized below.

The thermal plume model study was able to successfully reproduce temperature field data

(collected September 2003) without any adjustment of non

- physical parameters ( Holly Jr. et al.

2004 ) . The model was used to show compliance of the thermal plume with the proposed

alternative standard. The model validation revealed the importance of including site

- specific

river

- entraining structures such as wing dams and chute closure dams in the model, as these have

an important influence on the thermal flow patterns in the vicinity of the QCNS and local

Steamboat Island ( Holly Jr. et al. 2004 )

.

Current and past monitoring efforts have collected data on a variety of aquatic communities,

including phytoplankton, zooplankton, benthic macroinve rtebrates (including freshwater

mussels), ichthyoplankton, and finfish, which are summarized in the Demonstration ( HDR 2009 )

. For the prospective assessment, QCNS conducted comprehensive literature surveys, analyzed

field data

, and followed EPA approved protocols for assessi ng potential thermal impacts on RIS

of fis h. RIS species selected for the QCNS Demonstration include d largemouth bass, channel

catfish, spotfin shiner, and walleye. River and plant operating conditions were selected to provide

a conservative assessment of potential power p lant

- related biological effects (i.e., the biothermal

assessment focused on the months of June, July, August, and September ) . The results indicate

that the proposed alternative thermal standard would have a negligible impact on largemouth

bass, channel catfish, and a slightly positive one for spotfin shiner (i.e., increased growth) ( HDR

2009 ) . Walleye chronic mortality could be increased by 8.5 percent immediately downstream of

the mixing zone, but placed in the areal relationship of the discharg e to Pool 14, this would

translate to a < 1 percent effect on the walleye population in the p ool ( HDR 2009 )

.

The retrospective a ssessment indicated some changes in the upper trophic levels (i.e., finfish) in

Pool 14 since the Station began operating, but concluded that those changes are not attributable to

the thermal input from QCNS ( HDR 2009 )

. In addition, the overall stability and health of upperBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 12 

### trophic levels over the length of the monitoring period suggests that lower trophic levels (i.e.,

zooplankton, phytoplankton) have remained stable an d abundant, providing an adequate food

supply to allow and sustain growth of the finfish and mussel populations. The retrospective

assessment also found that neither nuisance species (e.g., zebra mussel) nor heat tolerant species

of fish have come to predominate in Pool 14 due to QCNS operations ( HDR 2009 )

.

In addition, the Demonstration examined the potential for harmful interactions between the

QCNS thermal discharge and other pollutants

, including dissolved organic carbon, total

phosphorus, total nitrogen, biocides (i. e., anti

- fouling chemicals) , heavy metals, and other thermal

discharges located upstream . This analysis indicated that there was no evidence to suggest that

the small amount of additional heat that would be permitted to be discharged to Pool 14 under the

p roposed alternative standard would have an adverse synergistic effect with other pollutants

( HDR 2009 )

.

QCNS, b ased on their interpretation of EPA guidance documents and 316(a) D emonstrations for

other facilities, maintained that the overall standard of compliance (i.e., prot ection of the BIC )

would be demonstrated by meeting a series of functional criteria. Because this is a request for a

change in the thermal standard, the Demonstration needed to show that these conditions will be

satisfied in the future if the proposed stan dard wa s adopted :

 No substantial increase in abundance or distribution of any nuisance spec ies or heat

t olerant community ;

 No substantial decreases in formerly abundant indigenous species or community structure

to resemble a simpler successional stage than is natural for the locality and season, other

than nuisance species ;

 No unaesthetic appearance, odor, or taste of the water ;

 No elimination of an established or potential economic or recreational use of the waters ;

 No reduction in the successful completi on of life cycles of indigenous species, including

those of migratory species ;

 No substantial reduction of community heterogeneity or trophic structure ;

 No adverse impact on threatened or endangered species ;

 No destruction of unique or rare habitat, withou t a detailed and convincing justification of

why the destruction should not constitute a basis of denial ; and

 No detrimental interaction with other pollutants, discharges, or water

- use activities.

Based on the results of the thermal plume modeling study, t he prospective analysis, the

retrospective assessment, and the successful meeting of the criteria listed above, QCNS

concluded that past or future operations have not caused appreciable harm to the BIC

.

B.5.3 Point Beach Nuclear Station

Point Beach Nuclear Plant (PBNP) is located on the western shore of Lake Michigan in Two

Rivers, Manitowoc County, WI . The facility consists of two nuclear powered steam electric

generating units with a total net capacity of 1,540 megawatts thermal ( MWt ) each. Generation

Uni t 1 began commercial operation in December 1970 and Unit 2 in October 1972 (EA 2008).

The units operate with a once

- through cooling water system ( EA 2008 )

. C ooling water is

withdrawn from a deep intake (22 ft. contour) in Lake Michigan, and c urrent pumping capacity is

estimated to be 680,000 g allons per minute. Each unit discharges the non

- contact cooling water to

Lake Michigan via its own outfall located at a mean temperature increase of 11.5°C (20.7°F)

above the intake water temperature at t he maximum flow rate ( EA 2008 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 13 

### PBNP planned to implement an extended power uprate (EPU) at both units in the 2010/2011 time

frame that wa s expected to increase the existing plant output by approximately 17 percent. The

proposed EPU does not re sult in an increase in water being withdrawn from Lake Michigan, nor

will it result in an increase in the amount of water discharged to Lake Michigan ( NRC 2010 )

. However, EPU did require modification of the facility’s Wisconsin Discharge Elimination

System (WPDES) permit for the dischar ge of a pollutant from a point s ource into waters of the

state ( which includes the addition of heat from a point source ) . According to a modeling study

performed by PBNP in 2008, the temperature of the discharge water wa s expected to increase by

a maximum of 3.6 °F (2.0 °C)

, and the thermal plume expand as a result of the proposed EPU

( NRC 2010 )

.

In support of the permit modification request, PBNP prepared an assessment of the potential

impacts of the thermal discharge from the planned EPU (i.e., the “Planned Change”) . This

assessment is summarized in “ Point Beach Nuclear Plant Evaluation of the Thermal Effects Due

to a Planned Extended Power Uprate ” ( EA 2008 )

. S ince there currently are no temperature

limits in the PBNP WPDES permit or thermal water quality standards for Lake Michigan, this

assessment represented a “good faith effort” by PBNP to demonstrate that the impacts of the EPU

would not have a significant effect on the fish or shellfish communities in Lake Michigan ( EA

2008 )

.

Evaluation of the potential effects on the Lake Michigan aquatic community in the vicinity of the

PBNP post

- EPU discharge was based on a review of historical and current monitoring data

collected in the vicinity of the facility and other power facilities that utilize L ake Michigan water

for once

- through cooling ( EA 2008 ) . Those study results were compared to expected responses of

16 Wisconsin Department of Natural Resource (WDNR) selected Representative Important

Species (RIS) to the projected higher discharg e temperatures and larger thermal plume that will

result from the planned EPU. The evaluation placed emphasis on the RIS

, and whether or not the

BIC in the vicinity of the PBNP discharge would continue to be protected.

The assessment relied heavily on the findings of the Type I CWA section 316(a) Demonstration

conducted by the facility in the 1970s as well as the 1976 finding by WDNR that no appreciable

harm had occurred to the local BIC due to facility operations ( EA 2008 ) . The s tudies involved

investigations of primary and secondary trophic l evels from phytoplankton through fish in both

reference and thermally affected areas ( EA Engineering 2008 ; Limnetics 1974, as cited in EA

2008 )

.

R ecent entrainment and impingement mo nitoring studies at PBNP indicate that the same species

that were common in the vicinity of t he facility during the Type I Demonstration r emain common

near the facility despite lake

- wide changes in the Lake Michigan fish community ( Kitchell 2007,

as cited in EA 2008 ) . Recent fisheries data collect ed from both PBNP and the Kewaunee Nuclear

Power Plant (KNPP), which is located only five miles north of PBNP, show that the same species

seasonally occur in nearshore areas in the vicinity of the shoreline discharge structures. These

findings indicate tha t the BIC is protected under similar operating conditions as ha ve occurred

historically at PBNP.

Evaluation of the modeled discharge temperatures and plume configurations under the planned

EPU indicates that the predicted area, volume, and behavior of the plume will not be substantially

different than under current PBNP operating conditions and similar to those evaluated during the

Type 1 Demonstration ( EA 2008 )

. Based on the thermal model results using a 0.2 ft./sec along

shore current, the plan ned EPU would expand the surface area of the 6.0oC contour from 27 to 39Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix B: Thermal Discharges

May 2014 B

- 14 

### acres; the 4.0oC contour would increase from 79 to 105 acres; and the 2.0oC contour would

increase from 315 to 390 acres ( EA 2008 ) . These projected increases in plume size are relatively

small compared to the surface area available for mixing

. U nder critical summer conditions the

buoyant plume provides an area of safety as well as a zone of passage when discharge

temperatures approach or exceed upper avoidance temperatures of the RIS fish.

The RIS evaluation showed that the predicted impact of the warmer and larger thermal plume as a

result of the EPU at PBNP will be negligible ( EA 2008 ) . Thermal criteria for some of the 12 RIS

fish species would be exceeded in th e plume, but mainly at the point of discharge or in small

areas for relatively brief periods of time. Fish readily move into and out of thermal discharge

plumes, depending on their thermal requirements and the thermal regime of the plume at any

given time. Cool and coldwater fish species would be somewhat restricted with regard to use of

the plume area, especially during summer , but these species generally spend the summer well

offshore. In addition, t he warmwater RIS could slightly benefit from the warmer temperatures.

Combining these observations with the size of the PBNP plume relative to available lake habitat,

it was concluded that the larger and warmer thermal plume resulting from the planned EPU

would have a minimal and insignificant impact on the fis h community in Lake Michigan ( EA

2008 )

. Similar conclusions were reached for the four invertebrate RIS (shellfish and opossum

shrimp).

Overall, the assessment concluded that the increased heat load to the discharge would not

endanger the protect ion and propagation of a BIC of shellfish, fish, and wildlife in and on Lake

Michigan. Th is conclusion was based on several lines of evidence including:

 The PBNP Type I Demonstration established that the original thermal plume did not

cause “prior apprecia ble harm;”

 The PBNP thermal plumes resulting from the planned EPU will not be substantially

larger than the original/existing plumes;

 There have been no changes in the aquatic community attributable to operation of the

facility that would preclude relianc e on the results of the Type I Demonstration for

PBNP;

 The changes to the Lake Michigan fish community that have occurred during the past 50

years have occurred on a lake

- wide basis;

 The impacts on RIS will be negligible; and

 The conclusion with respect to the effect of the planned EPU is consistent with

assessments undertaken at other power facilities on Lake Michigan.

While the cooling water thermal plume of PBNP was expected to be larger as a result of the

proposed EPU, it was not expected to disrupt the local BIC or have a significant impact on RIS of

Lake Michigan ( EA 2008 )

. Recently, as part of the facilities’ operating license renewal, the

Nuclear Regulatory Commission developed a draft Environmental Assessment (EA) for the

power uprate. The draft EA was issued in December 2010 with a finding of no significant impact

( NRC 2010 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 1 

# Appendix C: Details of Reg ional IM&E

C.1 California Region

Table C

- 1: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the California Region (million A1Es

per year), and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

All forage species 0.17 0.18 0.20 0.29 <0.01 <0.01 14.81 24.28 0.17 0.18 15.00 24.56

All harvested species 0.50 0.54 0.58 0.85 <0.01 <0.01 15.94 26.14 0.50 0.54 16.52 26.98

American shad <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Cabezon <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.05 0.08 <0.01 <0.01 0.05 0.08

California halibut <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.20 0.33 <0.01 <0.01 0.20 0.33

California scorpionfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Crabs (other) 0.02 0.02 0.02 0.03 <0.01 <0.01 6.65 10.91 0.02 0.02 6.68 10.94

Sea Basses <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 2.42 3.96 <0.01 <0.01 <0.01 3.96

Shrimp (other) <0.01 <0.01 <0.01 0.01 <0.01 <0.01 0.53 0.88 <0.01 <0.01 0.54 0.89

Drums and croakers 0.04 0.04 0.04 0.07 <0.01 <0.01 0.19 0.32 0.04 0.04 0.24 0.38

Dungeness crab <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 <0.01 <0.01 <0.01 0.01

Flounders < 0.01 <0.01 0.01 0.02 <0.01 <0.01 0.08 0.13 <0.01 <0.01 0.09 0.15

Fish (other) <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 <0.01 <0.01 <0.01 0.02

Northern anchovy 0.29 0.32 0.33 0.49 <0.01 <0.01 0.03 0.04 0.29 0.32 0.36 0.54

Rockfishes 0.01 0.01 0.02 0.02 <0.01 <0.01 5.40 8.85 0.01 0.01 5.42 8.88

Salmon <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Sculpins 0.01 0.01 0.01 0.02 <0.01 <0.01 0.36 0.60 0.01 0.01 0.38 0.62

Smelts <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01

Striped bass <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 0.02 <0.01 <0.01 0.01 0.02

Sunfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Surfperches 0.10 0.11 0.11 0.16 <0.01 <0.01 <0.01 <0.01 0.10 0.11 0.11 0.16

Total (all species) 0.68 0.73 0.77 1.13 <0.01 <0.01 30.75 50.42 0.68 0.73 31.52 51.55

Notes:

P4 = Proposal Option 4; F = Final Rule

– Existin g Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 2 

### Table C

- 2: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the California Region (million individuals per

year), and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

American shad <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Blennies <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 390.33 639.92 <0.01 <0.01 390.33 639.92

Bluegill <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Brown bullhead <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Cabezon <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01 2.84 4.65 <0.01 <0.01 2.84 4.65

California halibut <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 3.29 5.40 <0.01 <0.01 3.29 5.40

California scorpionfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Chinook salmon <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Crabs (other) 0.02 0.02 0.03 0.04 <0.01 <0.01 3,088.48 5,063.36 0.02 0.02 3,088.51 5,063.39

Delta smelt <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 <0.01 <0.01 <0.01 0.01

Drums and croakers 0.18 0.19 0.20 0.30 < 0.01 <0.01 390.48 640.16 0.18 0.19 390.68 640.46

Dungeness crab <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.04 0.06 <0.01 <0.01 0.04 0.06

Fish (other) 0.04 0.04 0.04 0.06 <0.01 <0.01 554.48 909.03 0.04 0.04 554.52 909.10

Flounders <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 136.20 223.29 <0.01 <0.01 136.20 223.30

Gobies <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 673.78 1,104.62 <0.01 <0.01 673.78 1,104.62

Herrings 0.02 0.03 0.03 0.04 <0.01 <0.01 11.19 18.35 0.02 0.03 11.22 18.39

Longfin smelt <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Northern anchovy 0.37 0.39 0.42 0.61 <0.01 <0.01 352.68 578.20 0.37 0.39 353.10 578.81

Pacific herring <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 15.43 25.30 < 0.01 <0.01 15.43 25.30

Rockfishes 0.01 0.01 0.01 0.02 <0.01 <0.01 27.29 44.74 0.01 0.01 27.30 44.76

Sacramento splittail <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01

Salmon <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Sculpins <0.01 <0.01 <0.01 0.01 <0.01 <0.01 20.45 33.53 <0.01 <0.01 20.46 33.54

Sea Basses <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 5.65 9.26 <0.01 <0.01 5.65 9.26

Shrimp (other) 0.01 0.02 0.02 0.02 <0.01 <0.01 183.13 300.24 0.01 0.02 183.15 300.26

Silversides 0.05 0.05 0.05 0.08 <0.01 <0.01 51.98 85.22 0.05 0.05 52.04 85.30

Smallmouth bass <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Smelts <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 1.55 2.54 <0.01 <0.01 1.55 2.54

Striped bass <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 4.82 7.91 <0.01 <0.01 4.82 7.91

Sunfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Surfperches 0.06 0.06 0.06 0.09 <0.01 <0.01 <0.01 <0.01 0.06 0.06 0.06 0.09

Total (all species) 0.77 0.83 0.88 1.30 <0.01 <0.01 5,914.12 9,695.80 0.77 0.83 5,915.00 9,697.09

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 3 

## C.2 North Atlantic Region

Table C

- 3: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the North Atlantic (million A1Es per year), and

Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

All forage species 0.35 0.37 0.50 0.53 <0.01 0.40 34.30 44.80 0.35 0.77 34.80 45.34

All harvested species 0.05 0.05 0.07 0.08 <0.01 0.11 9.52 12.44 0.05 0.16 9.60 12.52

American plaice <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

American shad <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Atlantic cod <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 <0.01 <0.01 0.01 0.01

Atlantic herring <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.09 0.12 <0.01 <0.01 0.09 0.12

Atlantic mackerel < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.02 0.02 <0.01 <0.01 0.02 0.02

Atlantic menhaden <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.03 0.04 <0.01 <0.01 0.03 0.04

Bluefish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Butterfish <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Crabs (other) 0.02 0.02 0.03 0.03 <0.01 <0.01 <0.01 <0.01 0.02 0.02 0.03 0.03

Cunner <0.01 <0.01 <0.01 <0.01 <0.01 0.04 3.14 4.10 <0.01 0.04 3.14 4.11

Fish (other) <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Pollock <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Red hake <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Sculpins <0.01 <0.01 <0.01 <0.01 <0.01 0.02 1.43 1.87 <0.01 0.02 1.44 1.87

Scup <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Searobin <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 <0.01 <0.01 <0.01 0.01

Silver hake <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Skates <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Striped bass <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Tautog <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.08 0.11 <0.01 <0.01 0.08 0.11

Weakfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

White perch <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Windowpane <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.02 0.02 <0.01 <0.01 0.02 0.02

Winter flounder 0.02 0.02 0.02 0.02 <0.01 0.05 4.69 6.13 0.02 0.07 4.71 6.15

Total (all species) 0.40 0.42 0.57 0.61 <0.01 0.51 43.83 57.24 0.40 0.93 44.40 57.86

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 4 

### Table C

- 4: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the North Atlantic (million individuals per

year), and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Alewife 0.02 0.02 0.02 0.03 <0.01 0.02 2.13 2.78 0.02 0.04 2.15 2.80

American plaice <0.01 <0.01 <0.01 <0.01 <0.01 0.86 73.53 96.04 <0.01 0.86 73.53 96.04

American sand lance 0.05 0.05 0.07 0.08 <0.01 6.31 542.26 708.25 0.05 6.36 542.33 708.33

American shad <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01

Atlantic cod <0.01 <0.01 <0.01 <0.01 <0.01 0.50 43.33 56.59 <0.01 0.50 43.33 56.59

Atlantic herring <0.01 <0.01 0.01 0.01 <0.01 0.37 32.23 42.09 <0.01 0.38 32.24 42.11

Atlantic mackerel <0.01 <0.01 <0.01 <0.01 <0.01 30.35 2,608.87 3,407.48 <0.01 30.35 2,608.87 3,407.48

Atlantic menhaden <0.01 <0.01 <0.01 <0.01 <0.01 18.06 1,552.60 2,027.86 <0.01 18.07 1,552.60 2,027.87

Atlantic silverside 0.04 0.05 0.06 0.07 <0.01 0.41 35.65 4.56 0.04 0.46 35.71 46.63

Atlantic tomcod <0.01 <0.01 <0.01 <0.01 <0.01 0.03 2.32 3.03 <0.01 0.03 2.32 3.03

Bay anchovy <0.01 0.01 0.01 0.01 <0.01 239.73 20,604.68 26,912.03 <0.01 239.74 20,604.69 26,912.04

Blueback herring <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Bluefish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.02 0.03 <0.01 <0.01 0.02 0.03

Butterfish <0.01 <0.01 <0.01 <0.01 <0.01 0.05 4.48 5.86 <0.01 0.05 4.49 5.86

Crabs (other) 0.01 0.01 0.02 0.02 <0.01 <0.01 <0.01 <0.01 0.01 0.01 0.02 0.02

Cunner <0.01 <0.01 <0.01 <0.01 <0.01 125.28 10,767.77 14,063.92 <0.01 125.28 10,767.78 14,063.92

Fish (other) 0.02 0.02 0.03 0.03 < 0.01 2.24 192.48 251.40 0.02 2.26 192.51 251.43

Fourbeard rockling <0.01 <0.01 <0.01 <0.01 <0.01 1.99 171.36 223.81 <0.01 1.99 171.36 223.81

Grubby <0.01 <0.01 0.01 0.01 <0.01 1.85 159.12 207.83 <0.01 1.86 159.13 207.84

Hogchoker 0.01 0.01 0.02 0.02 <0.01 2.36 202.71 264.77 0.01 2.37 202.73 264.79

Lumpfish <0.01 <0.01 <0.01 <0.01 <0.01 0.19 16.57 21.64 <0.01 0.19 16.57 21.64

Northern pipefish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.42 0.55 <0.01 < 0.01 0.43 0.56

Pollock <0.01 <0.01 <0.01 <0.01 <0.01 0.01 1.28 1.67 <0.01 0.02 1.28 1.67

Radiated shanny <0.01 <0.01 <0.01 <0.01 <0.01 0.47 40.74 53.21 <0.01 0.47 40.74 53.21

Rainbow smelt 0.02 0.02 0.02 0.02 <0.01 0.08 6.51 8.51 0.02 0.09 6.54 8.53

Red hake <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Rock gunnel <0.01 <0.01 <0.01 <0.01 <0.01 1.70 146.13 190.86 <0.01 1.70 146.13 190.86

Sculpins <0.01 <0.01 <0.01 < 0.01 <0.01 0.94 80.72 105.42 <0.01 0.94 80.72 105.43

Scup <0.01 <0.01 <0.01 <0.01 <0.01 0.07 6.14 8.02 <0.01 0.07 6.14 8.03

Seaboard goby < 0.01 <0.01 <0.01 <0.01 <0.01 10.22 878.37 1,147.25 <0.01 10.22 878.37 1,147.25

Searobin <0.01 <0.01 <0.01 <0.01 <0.01 0.05 4.24 5.53 <0.01 0.05 4.24 5.53

Silver hake 0.01 0.01 0.02 0.02 <0.01 2.44 209.93 274.19 0.01 2.45 209.94 274.20

Skates <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Striped bass <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Striped killifish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.02 0.03 <0.01 <0.01 0.02 0.03

Tautog <0.01 <0.01 <0.01 <0.01 <0.01 125.83 10,815.39 14,126.11 <0.01 125.84 10,815.39 14,126.11

Threespine stickleback <0.01 <0.01 0.01 0.01 <0.01 <0.01 0.03 0.04 <0.01 <0.01 0.04 0.06

Weakfish <0.01 <0.01 <0.01 <0.01 <0.01 1.47 126.32 164.99 <0.01 1.47 126.32 164.99Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 5 

### Table C

- 4: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the North Atlantic (million individuals per

year), and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

White perch <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 0.10 0.14 <0.01 <0.01 0.11 0.14

Windowpane <0.01 <0.01 <0.01 <0.01 <0.01 8.88 762.82 996.32 <0.01 8.88 762.82 996.33

Winter flounder 0.03 0.03 0.04 0.04 <0.01 28.72 2,468.75 3,224.46 0.03 28.75 2,468.79 3,224.51

Total (all species) 0.28 0.30 0.40 0.44 <0.01 611.52 52,560.02 68,649.28 0.28 611.82 52,560.42 68,649.72

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 6 

## C.3 Mid

- Atlantic Region

Table C

- 5: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the Mid

- Atlantic (million A1Es per year), and

Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

All forage species 10.91 11.65 13.32 14.42 0.72 1.09 402.14 461.47 11.63 12.75 415.46 475.89

All harvested species 18.66 19.94 22.79 24.67 0.20 0.31 113.65 130.42 18.87 20.25 136.44 155.08

Alewife 0.02 0.03 0.03 0.03 <0.01 <0.01 <0.01 <0.01 0.02 0.03 0.03 0.04

American shad <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Atlantic croaker 0.18 0.19 0.22 0.24 0.02 0.03 11.85 13.60 0.20 0.23 12.08 13.84

Atlantic herring <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Atlantic menhaden 12.67 13.53 15.47 16.74 <0.01 <0.01 1.73 1.99 12.67 13.54 17.20 18.73

Black crappie <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Black drum <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Blue crab 0.84 0.90 1.03 1.11 0.11 0.16 59.39 68.16 0.95 1.06 60.42 69.27

Bluefish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Bluegill <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Brown bullhead <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 0.01

Bullheads <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Butterfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Channel catfish 0.01 0.01 0.01 0.01 <0.01 <0.01 <0.01 <0.01 0.01 0.01 0.01 0.01

Crabs (other) 0.02 0.02 0.02 0.03 <0.01 <0.01 <0.01 <0.01 0.02 0.02 0.02 0.03

Crappie <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Cunner <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01

Freshwater drum <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Menhadens <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Muskellunge <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Fish (other) 0.76 0.81 0.92 1.00 0.01 0.02 5.93 6.81 0.77 0.24 0.34 7.81

Red drum <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Red hake <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Scup <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Searobin <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Silver hake <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Silver perch <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Smallmouth bass <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Spot 1.72 1.84 2.10 2.27 0.03 0.05 19.30 22.15 1.75 1.89 21.40 24.42Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 7 

### Table C

- 5: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the Mid

- Atlantic (million A1Es per year), and

Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Spotted seatrout <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Striped bass <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.76 0.88 <0.01 <0.01 0.77 0.88

Striped mullet <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01

Summer flounder 0.01 0.01 0.02 0.02 <0.01 <0.01 <0.01 <0.01 0.01 0.01 0.02 0.02

Sunfish 0.01 0.01 0.01 0.01 <0.01 <0.01 <0.01 <0.01 0.01 0.01 0.01 0.01

Tautog <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Weakfish 0.84 0.89 1.02 1.11 <0.01 <0.01 1.49 1.70 0.84 0.90 2.51 2.81

White perch 1.55 1.66 1.89 2.05 0.02 0.04 13.11 15.04 1.57 1.69 15.00 17.09

Whitefish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Windowpane <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Winter flounder <0.01 0.01 0.01 0.01 <0.01 <0.01 0.06 0.07 <0.01 0.01 0.07 0.08

Total (all species) 29.57 31.60 36.11 39.08 0.93 1.40 515.78 591.89 30.50 32.99 551.90 630.97

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 8 

### Table C

- 6: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the Mid

- Atlantic (million individuals per year),

and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Alewife 0.10 0.10 0.12 0.13 <0.01 <0.01 1.68 1.92 0.10 0.11 1.80 2.05

American shad 0.02 0.02 0.02 0.02 0.03 0.05 18.41 21.13 0.05 0.07 18.43 21.15

Atlantic croaker 0.66 0.71 0.81 0.88 0.34 0.51 189.17 217.08 1.01 1.22 189.98 217.96

Atlantic herring <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Atlantic menhaden 20.54 21.95 25.08 27.15 0.06 0.09 33.65 38.62 20.60 22.04 58.74 65.77

Atlantic silverside 0.41 0.44 0.50 0.54 0.05 0.08 30.24 34.70 0.46 0.52 30.74 35.24

Atlantic tomcod 0.04 0.04 0.05 0.05 <0.01 <0.01 <0.01 <0.01 0.04 0.04 0.05 0.05

Bay anchovy 4.02 4.29 4.91 5.31 48.59 73.22 26,996.15 30,979.52 52.60 77.51 27,001.05 30,984.82

Black crappie <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Black drum <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Blue crab 0.84 0.89 1.02 1.10 1.68 2.53 932.50 1,070.10 2.51 3.42 933.53 1,071.20

Blueback herring 0.37 0.39 0.45 0.49 0.01 0.02 6.66 7.65 0.38 0.41 7.11 8.13

Bluefish <0.01 <0.01 0.01 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 0.01

Bluegill <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Bluntnose minnow <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Brown bullhead < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.03 0.03 <0.01 <0.01 0.03 0.04

Bullheads <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Butterfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Carp <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Chain pipefish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01

Channel catfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Crabs (other) 0.01 0.01 0.01 0.01 <0.01 <0.01 <0.01 <0.01 0.01 0.01 0.01 0.01

Crappie <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Cunner <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01

Darters <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Fish (other) 1.56 1.66 1.90 2.06 1.88 2.83 1,044.61 1,198.74 3.44 4.50 1,046.51 1,200.80

Freshwater drum <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Gizzard shad 0.10 0.11 0.12 0.13 <0.01 <0.01 <0.01 <0.01 0.10 0.11 0.12 0.13

Gobies <0.01 <0.01 <0.01 <0.01 0.07 0.11 39.50 45.33 0.07 0.11 39.50 45.33

Grubby <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Herrings <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Hogchoker 0.15 0.16 0.19 0.20 12.83 19.34 7,129.97 8,182.02 12.99 19.50 7,130.16 8,182.22

Menhadens <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.03 0.03 <0.01 <0.01 0.03 0.03

Muskellunge <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Northern pipefish <0.01 0.01 0.01 0.01 <0.01 <0.01 2.92 3.35 0.01 0.02 2.93 3.37

Rainbow smelt <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01

Red drum <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Red hake 0.02 0.02 0.03 0.03 <0.01 <0.01 <0.01 <0.01 0.02 0.02 0.03 0.03Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 9 

### Table C

- 6: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the Mid

- Atlantic (million individuals per year),

and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Scup <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Seaboard goby <0.01 <0.01 <0.01 <0.01 6.76 10.20 3,758.88 4,313.52 6.77 10.20 3,758.89 4,313.52

Searobin <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Shiners <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.27 0.31 <0.01 <0.01 0.27 0.31

Silver hake <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Silver perch <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Silversides <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.78 0.90 <0.01 <0.01 0.78 0.90

Smallmouth bass <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Spot 2.67 2.86 3.26 3.53 0.11 0.17 63.87 73.29 2.79 3.03 67.13 76.82

Spotted seatrout <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Striped bass 0.01 0.01 0.01 0.01 0.52 0.79 291.01 333.95 0.53 0.80 291.03 333.97

Striped killifish 0.09 0.10 0.11 0.12 <0.01 <0.01 <0.01 <0.01 0.09 0.10 0.11 0.12

Striped mullet <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Suckers <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Summer flounder 0.02 0.02 0.03 0.03 <0.01 <0.01 <0.01 <0.01 0.02 0.02 0.03 0.03

Sunfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Tautog <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Threespine stickleback <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Weakfish 0.96 1.03 1.18 1.27 0.24 0.36 133.56 153.27 1.20 1.39 134.74 154.55

White perch 0.82 0.87 1.00 1.08 1.15 1.74 641.08 735.68 1.97 2.61 642.08 736.76

Whitefish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Windowpane <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Winter flounder 0.02 0.02 0.02 0.02 0.05 0.07 25.26 28.99 0.06 0.09 25.28 29.01

Total (all species) 33.49 35.78 40.90 44.26 74.40 112.13 41,340.26 47,440.14 107.89 147.91 41,381.16 47,484.40

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 10 

## C.4 South Atlantic Region

Table C

- 7: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the South Atlantic (million A1Es per year), and

Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

All forage species 10.98 11.77 16.05 16.21 <0.01 0.44 7.86 8.41 10.98 12.21 23.91 24.61

All harvested species 0.63 0.68 0.92 0.93 <0.01 0.04 0.76 0.82 0.63 0.72 1.69 1.75

Atlantic menhaden 0.13 0.14 0.19 0.19 <0.01 <0.01 0.02 0.03 0.13 0.14 0.21 0.22

Blue crab 0.23 0.25 0.34 0.34 <0.01 <0.01 <0.01 <0.01 0.23 0.25 0.34 0.34

Crabs (other) <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.02 0.02 <0.01 <0.01 0.02 0.02

Drums and croakers 0.01 0.01 0.02 0.02 <0.01 0.04 0.63 0.68 0.01 0.05 0.65 0.70

Flounders <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Fish (other) <0.01 <0.01 0.01 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01

Pinfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Silver perch 0.14 0.15 0.21 0.21 < 0.01 <0.01 <0.01 <0.01 0.14 0.15 0.21 0.21

Spot 0.10 0.11 0.15 0.15 <0.01 <0.01 0.08 0.08 0.10 0.11 0.23 0.23

Spotted seatrout <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Stone crab <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01

Weakfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Total (all species) 11.61 12.44 16.97 17.14 <0.01 0.48 8.62 9.22 11.61 12.93 25.60 26.36

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 11 

### Table C

- 8: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the South Atlantic (million individuals per

year), and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Atlantic menhaden 0.21 0.23 0.31 0.31 <0.01 3.48 62.28 66.59 0.21 3.71 62.59 66.90

Atlantic silverside 0.03 0.03 0.05 0.05 <0.01 <0.01 <0.01 <0.01 0.03 0.03 0.05 0.05

Bay anchovy 6.59 7.06 9.63 9.73 <0.01 53.13 949.88 1,015.58 6.59 60.19 959.52 1,025.31

Blue crab 0.23 0.25 0.34 0.34 <0.01 <0.01 <0.01 <0.01 0.23 0.25 0.34 0.34

Crabs (other) <0.01 <0.01 <0.01 <0.01 <0.01 14.77 264.07 282.33 <0.01 14.77 264.07 282.33

Drums and croakers 0.06 0.06 0.08 0.08 <0.01 52.55 939.64 1,004.62 0.06 52.61 939.72 1,004.70

Fish (other) 0.43 0.46 0.63 0.64 <0.01 6.04 107.92 115.39 0.43 6.50 108.55 116.02

Flounders <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Gobies <0.01 <0.01 <0.01 <0.01 <0.01 79.08 1,413.86 1,511.63 <0.01 79.08 1,413.86 1,511.63

Herrings <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Pinfish <0.01 <0.01 <0.01 <0.01 <0.01 1.58 28.20 30.15 <0.01 1.58 28.20 30.15

Scaled sardine <0.01 < 0.01 0.01 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 0.01

Shrimp (other) 2.30 2.46 3.36 3.39 <0.01 23.01 411.34 439.78 2.30 25.47 414.69 443.17

Silver perch 0.12 0.12 0.17 0.17 <0.01 <0.01 <0.01 <0.01 0.12 0.12 0.17 0.17

Spot 0.18 0.20 0.27 0.27 <0.01 47.60 851.08 909.94 0.18 47.80 851.35 910.21

Spotted seatrout <0.01 <0.01 <0.01 <0.01 <0.01 0.78 13.96 14.92 <0.01 0.78 13.96 14.92

Stone crab <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Weakfish 0.01 0.01 0.02 0.02 <0.01 2.23 39.93 42.69 0.01 2.25 39.94 42.70

Total (all species) 10.17 10.90 14.87 15.02 <0.01 284.24 5,082.16 5,433.62 10.17 295.15 5,097.03 5,448.64

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 12 

## C.5 Gulf of Mexico Region

Table C

- 9: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the Gulf of Mexico (million A1Es per year), and

Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

All forage species 4.84 5.03 6.03 6.70 0.04 0.04 25.66 43.45 4.88 5.06 31.69 50.15

All harvested species 33.90 35.18 42.20 46.85 0.04 0.04 29.53 50.01 33.94 35.22 71.73 96.86

Atlantic croaker 1.42 1.48 1.77 1.96 <0.01 <0.01 <0.01 <0.01 1.42 1.48 1.77 1.97

Black drum 0.01 0.01 0.01 0.02 <0.01 <0.01 3.61 6.12 0.02 0.02 3.62 6.13

Blue crab 4.86 5.05 6.06 6.72 0.02 0.02 11.59 19.63 4.88 5.06 17.65 26.35

Leatherjacket 0.59 0.62 0.74 0.82 <0.01 <0.01 0.02 0.03 0.59 0.62 0.76 0.85

Mackerels <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Menhadens 4.26 4.42 5.30 5.89 <0.01 <0.01 0.03 0.05 4.26 4.42 5.33 5.94

Fish (other) 1.28 1.32 1.59 1.76 <0.01 <0.01 0.10 0.16 1.28 0.97 1.18 1.93

Pinfish 0.02 0.03 0.03 0.03 <0.01 <0.01 0.65 1.11 0.03 0.03 0.68 1.14

Pink shrimp 18.44 19.14 22.95 25.48 0.01 0.01 8.17 13.83 18.45 19.15 31.12 39.31

Red drum 0.07 0.07 0.09 0.10 <0.01 <0.01 <0.01 0.01 0.07 0.07 0.10 0.11

Sea basses <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Searobin 0.80 0.83 1.00 1.11 <0.01 <0.01 0.22 0.38 0.80 0.84 1.22 1.49

Sheepshead <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 0.02 0.04 <0.01 <0.01 0.02 0.04

Silver perch 0.24 0.25 0.30 0.33 <0.01 <0.01 3.12 5.28 0.25 0.26 3.42 5.61

Spot 0.33 0.34 0.41 0.45 <0.01 <0.01 0.05 0.09 0.33 0.34 0.46 0.54

Spotted seatrout 1.08 1.12 1.35 1.50 <0.01 <0.01 0.09 0.15 1.08 1.12 1.44 1.65

Stone crab 0.16 0.17 0.20 0.22 <0.01 <0.01 0.25 0.43 0.16 0.17 0.45 0.65

Striped mullet 0.32 0.33 0.40 0.44 <0.01 <0.01 1.59 2.70 0.32 0.33 1.99 3.14

Total (all species) 38.74 40.21 48.23 53.55 0.08 0.08 55.19 93.46 38.82 40.29 103.42 147.01

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 13 

### Table C

- 10: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the Gulf of Mexico (million individuals per

year), and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Atlantic croaker 6.64 6.90 8.27 9.18 0.07 0.07 49.45 83.75 6.71 6.96 57.73 92.93

Bay anchovy 1.86 1.93 2.32 2.57 126.59 126.59 91,714.39 155,318.87 128.45 128.52 91,716.71 155,321.44

Black drum 0.01 0.01 0.01 0.01 40.50 40.50 29,342.08 49,690.98 40.51 40.51 29,342.09 49,691.00

Blue crab 4.84 5.03 6.03 6.69 0.12 0.12 85.58 144.93 4.96 5.14 91.61 151.63

Chain pipefish 0.03 0.03 0.04 0.04 <0.01 <0.01 0.65 1.10 0.03 0.03 0.68 1.14

Fish (other) 3.19 3.32 3.98 4.42 4.11 4.11 2,980.35 5,047.23 7.31 7.43 2,984.32 5,051.65

Gobies 0.06 0.06 0.07 0.08 1.43 1.43 1,038.00 1,757.86 1.49 1.49 1,038.07 1,757.94

Gulf killifish 0.02 0.02 0.02 0.02 <0.01 <0.01 <0.01 <0.01 0.02 0.02 0.02 0.02

Hogchoker 0.06 0.06 0.08 0.09 0.08 0.08 60.53 102.51 0.15 0.15 60.61 102.60

Leatherjacket 0.41 0.42 0.51 0.56 0.33 0.33 241.86 409.59 0.74 0.76 242.37 410.16

Mackerels <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Menhadens 6.91 7.17 8.60 9.54 0.11 0.11 81.98 138.83 7.02 7.28 90.58 148.37

Pinfish 0.05 0.05 0.06 0.07 0.05 0.05 32.83 55.60 0.10 0.10 32.90 55.68

Pink shrimp 18.80 19.51 23.41 25.98 0.05 0.05 38.48 65.16 18.85 19.57 61.88 91.15

Red drum 0.07 0.07 0.08 0.09 <0.01 <0.01 0.33 0.57 0.07 0.07 0.42 0.66

Scaled sardine 0.14 0.14 0.17 0.19 1.25 1.25 902.35 1,528.14 1.38 1.39 902.52 1,528.33

Sea basses <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Searobin 0.51 0.52 0.63 0.70 0.03 0.03 20.96 35.50 0.53 0.55 21.59 36.20

Sheepshead <0.01 <0.01 < 0.01 <0.01 0.16 0.16 116.63 197.51 0.16 0.16 116.63 197.51

Silver perch 0.20 0.20 0.24 0.27 37.41 37.41 27,105.51 45,903.34 37.61 37.62 27,105.75 45,903.61

Spot 0.60 0.62 0.74 0.82 0.01 0.01 10.59 17.93 0.61 0.63 11.33 18.75

Spotted seatrout 0.52 0.54 0.64 0.71 2.24 2.24 1,625.98 2,753.61 2.76 2.78 1,626.63 2,754.33

Stone crab 0.12 0.12 0.15 0.16 12.07 12.07 8,745.52 14,810.59 12.19 12.19 8,745.67 14,810.76

Striped mullet 0.19 0.20 0.24 0.27 <0.01 <0.01 4.62 7.82 0.20 0.21 4.86 8.09

Tidewater

silverside 0.13 0.13 0.16 0.18 0.01 0.01 10.47 17.73 0.14 0.15 10.63 17.90

Total (all species) 45.35 47.07 56.46 62.68 226.65 226.65 164,209.14 278,089.16 272.00 273.72 164,265.60 278,151.84

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 14 

## C.6 Great Lakes Region

Table C

- 11: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the Great Lakes (million A1Es per

year), and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

All forage species 175.87 193.55 220.56 226.20 0.01 0.03 9.94 13.81 175.88 193.58 230.50 240.01

All harvested species 8.15 8.97 10.22 10.49 <0.01 0.03 7.75 10.76 8.16 9.00 17.97 21.25

Black bullhead <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Black crappie <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Bluegill <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Brown bullhead 0.02 0.02 0.02 0.02 <0.01 <0.01 <0.01 <0.01 0.02 0.02 0.02 0.02

Bullheads <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Channel catfish 0.16 0.17 0.19 0.20 <0.01 <0.01 <0.01 <0.01 0.16 0.17 0.20 0.20

Crappie <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.02 0.02 <0.01 <0.01 0.02 0.02

Freshwater drum 0.31 0.34 0.38 0.39 <0.01 <0.01 0.46 0.64 0.31 0.34 0.84 1.03

Muskellunge <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Fish (other) 0.03 0.04 0.04 0.04 <0.01 <0.01 <0.01 <0.01 0.03 <0.01 <0.01 0.04

Rainbow smelt 0.35 0.38 0.44 0.45 <0.01 0.02 5.33 7.40 0.35 0.40 5.76 7.85

Salmon <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Sauger <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Sculpins <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 0.02 <0.01 <0.01 0.01 0.02

Smallmouth bass 0.05 0.05 0.06 0.06 <0.01 <0.01 <0.01 <0.01 0.05 0.05 0.06 0.06

Smelts 2.60 2.87 3.27 3.35 <0.01 <0.01 0.01 0.01 2.60 2.87 3.28 3.36

Sunfish 0.06 0.06 0.07 0.07 <0.01 <0.01 0.86 1.19 0.06 0.07 0.93 1.26

Walleye 0.06 0.07 0.08 0.08 <0.01 <0.01 0.24 0.33 0.06 0.07 0.31 0.41

White bass 3.83 4.21 4.80 4.92 <0.01 <0.01 0.76 1.06 3.83 4.21 5.56 5.98

Whitefish 0.13 0.15 0.17 0.17 <0.01 <0.01 <0.01 <0.01 0.13 0.15 0.17 0.17

Yellow perch 0.54 0.60 0.68 0.70 <0.01 <0.01 0.07 0.09 0.54 0.60 0.75 0.79

Total (all species) 184.02 202.52 230.78 236.69 0.02 0.06 17.68 24.57 184.04 202.58 248.47 261.26

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 15 

### Table C

- 12: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the Great Lakes (million individuals per

year), and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Alewife 9.70 10.68 12.17 12.48 10.31 32.56 10,003.26 3,898.65 20.02 43.24 10,015.44 13,911.13

Black bullhead <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01

Black crappie <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Blueback herring <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Bluegill 0.04 0.05 0.06 0.06 <0.01 <0.01 0.05 0.07 0.05 0.05 0.11 0.13

Bluntnose minnow 0.03 0.03 0.04 0.04 <0.01 0.01 3.42 4.75 0.03 0.04 3.45 4.79

Brown bullhead 0.01 0.02 0.02 0.02 <0.01 <0.01 <0.01 <0.01 0.01 0.02 0.02 0.02

Bullheads <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Burbot <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.29 0.40 <0.01 <0.01 0.29 0.40

Carp 0.03 0.03 0.04 0.04 0.89 2.82 866.66 1,204.14 0.92 2.85 866.69 1,204.18

Channel catfish 0.10 0.11 0.12 0.12 <0.01 <0.01 0.61 0.85 0.10 0.11 0.74 0.98

Chinook salmon <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Crappie <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 0.38 0.53 <0.01 <0.01 0.39 0.54

Darters <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.75 1.05 <0.01 <0.01 0.76 1.05

Emerald shiner 26.33 28.98 33.02 33.87 0.04 0.12 36.38 50.55 26.37 29.10 69.40 84.41

Fish (other) 0.18 0.19 0.22 0.23 11.23 35.46 10,895.22 15,137.95 11.41 35.65 10,895.44 15,138.17

Freshwater drum 0.59 0.65 0.74 0.76 1.54 4.86 1,494.29 2,076.18 2.13 5.51 1,495.03 2,076.94

Gizzard shad 28.91 31.81 36.25 37.18 1.04 3.29 1,009.94 1,403.23 29.95 35.10 1,046.20 1,440.41

Golden redhorse <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Herrings <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 2.93 4.07 <0.01 <0.01 2.93 4.07

Logperch 0.27 0.30 0.34 0.35 0.03 0.10 31.55 43.83 0.30 0.40 31.88 44.18

Muskellunge <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.32 0.44 <0.01 <0.01 0.32 0.44

Rainbow smelt 0.24 0.27 0.31 0.31 0.72 2.28 701.29 974.38 0.97 2.55 701.60 974.70

Salmon <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 1.62 2.25 <0.01 <0.01 1.62 2.25

Sauger <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01

Sculpins <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.92 1.28 <0.01 <0.01 0.92 1.28

Shiners 0.70 0.77 0.88 0.90 0.04 0.13 39.21 54.47 0.74 0.90 40.08 55.37

Silversides 0.04 0.04 0.05 0.05 <0.01 <0.01 <0.01 <0.01 0.04 0.04 0.05 0.05

Smallmouth bass 0.01 0.02 0.02 0.02 <0.01 < 0.01 <0.01 <0.01 0.01 0.02 0.02 0.02

Smelts 1.18 1.30 1.48 1.52 0.04 0.13 39.56 54.97 1.22 1.43 41.04 56.49

Spotted sucker < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Striped killifish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Suckers <0.01 <0.01 <0.01 <0.01 0.03 0.10 31.48 43.74 0.04 0.11 31.49 43.75

Sunfish <0.01 0.01 0.01 0.01 <0.01 <0.01 2.54 3.53 0.01 .02 2.55 3.54

Threespine

stickleback 0.02 0.02 0.03 0.03 <0.01 <0.01 0.18 0.25 0.02 0.02 0.21 0.28

Walleye 0.09 0.10 0.11 0.11 <0.01 0.03 9.25 12.86 0.10 0.13 9.36 12.97

White bass 2.14 2.35 2.68 2.75 0.06 0.19 57.17 79.44 2.20 2.54 59.86 82.19Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 16 

### Table C

- 12: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the Great Lakes (million individuals per

year), and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

White perch 9.14 10.06 11.46 11.76 0.25 0.80 245.11 340.56 9.39 10.86 256.57 352.31

Whitefish 0.03 0.03 0.04 0.04 <0.01 <0.01 0.08 0.11 0.03 0.03 0.12 0.15

Yellow perch 0.74 0.82 0.93 0.96 0.02 0.05 14.81 20.58 0.76 0.87 15.75 21.54

Total (all species) 80.58 88.68 101.05 103.64 26.28 82.96 25,489.28 35,415.10 106.85 171.64 25,590.33 35,518.74

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 17 

## C.7 Inland Region

Table C

- 13: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the Inland Region (million A1Es

per year), and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

All forage species 324.12 335.14 386.58 443.70 0.21 1.11 120.73 155.43 324.34 336.25 507.31 599.13

All harvested species 23.61 24.42 28.16 32.33 0.17 0.89 96.71 124.51 23.79 25.31 124.88 156.84

American shad 0.04 0.04 0.04 0.05 <0.01 <0.01 <0.01 <0.01 0.04 0.04 0.04 0.05

Black bullhead 0.13 0.13 0.15 0.17 <0.01 <0.01 <0.01 <0.01 0.13 0.13 0.15 0.18

Black crappie 0.05 0.05 0.05 0.06 <0.01 <0.01 0.37 0.48 0.05 0.05 0.42 0.54

Bluegill 1.46 1.51 1.74 2.00 <0.01 <0.01 0.13 0.17 1.46 1.51 1.87 2.17

Brown bullhead 0.02 0.02 0.02 0.03 <0.01 <0.01 0.03 0.04 0.02 0.02 0.05 0.07

Bullheads 0.02 0.02 0.02 0.02 <0.01 <0.01 <0.01 <0.01 0.02 0.02 0.03 0.03

Channel catfish 1.13 1.16 1.34 1.54 < 0.01 <0.01 0.74 0.95 1.13 1.17 2.08 2.50

Crappie 0.08 0.08 0.09 0.11 <0.01 <0.01 1.03 1.32 0.08 0.09 1.12 1.43

Freshwater drum 0.82 0.85 0.98 1.13 <0.01 0.04 4.64 5.97 0.83 0.89 5.62 7.10

Menhadens <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01

Muskellunge <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Fish (other) <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.05 0.06 <0.01 <0.01 0.05 0.07

Rainbow smelt 0.10 0.10 0.11 0.13 <0.01 <0.01 0.15 0.20 0.10 0.10 0.27 0.33

Salmon <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Sauger 0.07 0.07 0.08 0.09 <0.01 0.01 1.29 1.65 0.07 0.08 1.36 1.74

Smallmouth bass 0.16 0.17 0.19 0.22 <0.01 0.03 2.72 3.50 0.17 0.19 2.92 3.73

Smelts <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Striped bass 0.11 0.11 0.13 0.15 <0.01 <0.01 <0.01 <0.01 0.11 0.11 0.13 0.15

Sturgeons <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.02 0.02 <0.01 <0.01 0.02 0.02

Sunfish 13.76 14.23 16.41 18.84 0.14 0.75 80.88 104.13 13.91 14.98 97.30 122.97

Walleye 0.04 0.04 0.05 0.05 <0.01 <0.01 0.50 0.65 0.04 0.04 0.55 0.70

White bass 1.62 1.68 1.94 2.22 <0.01 0.02 1.96 2.52 1.63 1.70 3.89 4.74

White perch 1.78 1.84 2.12 2.44 <0.01 <0.01 0.41 0.52 1.78 1.85 2.53 2.96

Whitefish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Yellow perch 2.24 2.31 2.67 3.06 <0.01 0.02 1.79 2.31 2.24 2.33 4.46 5.37

Total (all species) 347.74 359.55 414.75 476.03 0.39 2.00 217.45 279.94 348.12 361.55 632.19 755.97

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 18 

### Table C

- 14: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the Inland Region (million individuals per

year), and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Alewife 14.78 15.29 17.63 20.24 <0.01 <0.01 0.47 0.61 14.78 15.29 18.10 20.85

American shad 6.58 6.80 7.84 9.00 <0.01 <0.01 <0.01 <0.01 6.58 6.80 7.84 9.00

Bay anchovy 0.01 0.01 0.01 0.01 <0.01 <0.01 <0.01 <0.01 0.01 0.01 0.01 0.01

Bigmouth buffalo 0.01 0.01 0.02 0.02 <0.01 0.02 1.98 2.55 0.02 0.03 1.99 2.56

Black bullhead 0.12 0.12 0.14 0.16 <0.01 <0.01 0.02 0.02 0.12 0.12 0.16 0.18

Black crappie 0.12 0.12 0.14 0.16 0.02 0.08 9.12 11.74 0.14 0.21 9.26 11.90

Blue crab <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Blueback herring 64.16 66.34 76.52 87.83 1.14 5.92 643.06 827.87 65.30 72.26 719.58 915.70

Bluegill 12.29 12.71 14.66 16.82 0.03 0.16 17.65 22.72 12.32 12.87 32.31 39.55

Bluntnose minnow 0.05 0.05 0.06 0.07 3.21 16.65 1,807.24 2,326.63 3.26 16.70 1,807.31 2,326.70

Brown bullhead 0.02 0.02 0.02 0.02 <0.01 <0.01 0.13 0.17 0.02 0.02 0.15 0.19

Bullheads 0.02 0.02 0.02 0.02 <0.01 0.01 1.35 1.74 0.02 0.03 1.37 1.76

Burbot <0.01 <0.01 <0.01 <0.01 0.01 0.05 5.89 7.59 0.01 0.06 5.90 7.59

Carp 0.13 0.13 0.15 0.18 2.74 14.25 1,546.60 1,991.08 2.87 14.38 1,546.75 1,991.25

Channel catfish 0.70 0.73 0.84 0.96 0.14 0.71 77.07 99.22 0.84 1.44 77.91 100.19

Crappie 0.21 0.21 0.24 0.28 0.04 0.23 24.87 32.02 0.25 0.44 25.12 32.30

Darters 0.34 0.36 0.41 0.47 0.11 0.55 59.43 76.51 0.45 0.90 59.84 76.98

Emerald shiner 1.38 1.42 1.64 1.89 0.47 2.45 266.39 342.94 1.85 3.88 268.03 344.83

Fish (other) 28.75 29.73 34.29 39.36 44.39 230.44 25,013.58 32,202.21 73.14 260.17 25,047.88 32,241.57

Freshwater drum 1.58 1.63 1.89 2.16 1.96 10.19 1,106.12 1,424.00 3.54 11.83 1,108.00 1,426.17

Gizzard shad 107.49 111.14 128.20 147.15 12.43 64.55 7,007.01 9,020.74 119.93 175.70 7,135.21 9,167.89

Gobies <0.01 <0.01 <0.01 <0.01 0.05 0.27 29.82 38.39 0.05 0.27 29.82 38.39

Golden redhorse 0.02 0.02 0.03 0.03 <0.01 <0.01 1.05 1.35 0.02 0.03 1.08 1.38

Hogchoker <0.01 <0.01 0.01 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 0.01

Logperch 0.34 0.36 0.41 0.47 0.02 0.11 11.87 15.28 0.37 0.47 12.28 15.75

Menhadens <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Muskellunge <0.01 <0.01 <0.01 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 0.01

Rainbow smelt 0.07 0.07 0.08 0.09 0.04 0.20 21.76 28.02 0.11 0.27 21.84 28.11

River carpsucker 0.01 0.01 0.01 0.02 <0.01 0.02 1.89 2.44 0.01 0.03 1.91 2.45

Salmon <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Sauger 0.08 0.08 0.09 0.11 0.20 1.06 115.46 148.65 0.28 1.14 115.56 148.75

Shiners 1.18 1.22 1.40 1.61 0.19 1.00 108.94 140.25 1.37 2.22 110.35 141.86

Silversides 0.01 0.01 0.02 0.02 0.03 0.16 17.09 22.00 0.04 0.17 17.11 22.02

Skipjack herring 0.53 0.54 0.63 0.72 <0.01 <0.01 0.20 0.25 0.53 0.55 0.83 0.97

Smallmouth bass 0.05 0.05 0.06 0.07 0.04 0.18 20.03 25.79 0.08 0.24 20.09 25.85

Smelts <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Spotted sucker <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Striped bass 0.57 0.59 0.68 0.78 <0.01 <0.01 <0.01 <0.01 0.57 0.59 0.68 0.78Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 19 

### Table C

- 14: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) in the Inland Region (million individuals per

year), and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Striped killifish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Sturgeons <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.54 0.69 <0.01 <0.01 0.54 0.69

Suckers 0.06 0.06 0.07 0.08 2.83 14.70 1,595.57 2,054.12 2.89 14.76 1,595.63 2,054.19

Sunfish 2.21 2.28 2.63 3.02 0.42 2.19 238.12 306.55 2.63 4.47 240.75 309.57

Threespine

stickleback <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Walleye 0.05 0.05 0.06 0.07 0.11 0.57 62.39 80.32 0.16 0.63 62.45 80.39

White bass 0.91 0.94 1.08 1.24 0.70 3.61 392.34 505.10 1.60 4.55 393.42 506.34

White perch 1.34 1.38 1.60 1.83 0.43 2.24 242.75 312.51 1.77 3.62 244.34 314.34

Whitefish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.28 0.36 <0.01 <0.01 0.28 0.36

Yellow perch 3.07 3.17 3.66 4.20 0.72 3.72 404.19 520.35 3.78 6.89 407.85 524.55

Total (all species) 249.27 257.74 297.30 341.23 72.49 376.37 40,852.60 52,593.18 321.76 634.10 41,149.89 52,934.41

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 20 

## C.8 National Estimates

Table C

- 15: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) Nationally (million A1Es per year),

and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

All forage species 527.24 557.69 643.23 708.05 0.98 3.11 615.44 751.65 528.22 560.80 1258.67 1459.70

All harvested species 85.51 89.79 104.95 116.18 0.42 1.42 273.87 355.09 85.94 91.20 378.82 471.28

Alewife 0.02 0.03 0.03 0.03 <0.01 <0.01 <0.01 <0.01 0.02 0.03 0.03 0.04

American plaice <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

American shad 0.04 0.04 0.04 0.05 <0.01 <0.01 <0.01 <0.01 0.04 0.04 0.05 0.05

Atlantic cod < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 <0.01 <0.01 0.01 0.01

Atlantic croaker 1.60 1.67 1.99 2.21 0.02 0.03 11.86 13.61 1.63 1.70 13.85 15.81

Atlantic herring <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.09 0.12 <0.01 <0.01 0.10 0.12

Atlantic mackerel < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.02 0.02 <0.01 <0.01 0.02 0.02

Atlantic menhaden 12.80 13.67 15.66 16.93 <0.01 <0.01 1.79 2.05 12.80 13.68 17.44 18.99

Black bullhead 0.13 0.13 0.15 0.17 <0.01 <0.01 <0.01 <0.01 0.13 0.13 0.16 0.18

Black crappie 0.05 0.05 0.05 0.06 <0.01 <0.01 0.37 0.48 0.05 0.05 0.42 0.54

Black drum 0.01 0.01 0.01 0.02 <0.01 <0.01 3.61 6.12 0.02 0.02 3.63 6.13

Blue crab 5.94 6.20 7.42 8.18 0.12 0.18 70.99 87.79 6.06 6.37 78.41 95.97

Bluefish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Bluegill 1.46 1.51 1.75 2.00 <0.01 <0.01 0.13 0.17 1.46 1.51 1.88 2.17

Brown bullhead 0.04 0.04 0.04 0.05 <0.01 <0.01 0.04 0.05 0.04 0.04 0.08 0.10

Bullheads 0.02 0.02 0.03 0.03 <0.01 <0.01 <0.01 <0.01 0.02 0.02 0.03 0.04

Butterfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Cabezon <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.05 0.08 <0.01 <0.01 0.05 0.08

California halibut <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.20 0.33 <0.01 <0.01 0.20 0.33

California

scorpionfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Channel catfish 1.29 1.35 1.55 1.75 <0.01 <0.01 0.74 0.96 1.29 1.35 2.29 2.71

Crabs (other) 0.06 0.06 0.08 0.09 <0.01 <0.01 6.67 10.93 0.06 0.07 6.75 11.02

Sea Basses <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 2.42 3.96 <0.01 <0.01 <0.01 3.96

Shrimp (other) <0.01 <0.01 <0.01 0.01 <0.01 <0.01 0.53 0.88 <0.01 <0.01 0.54 0.89

Crappie 0.08 0.08 0.09 0.11 <0.01 <0.01 1.04 1.35 0.08 0.09 1.14 1.45

Cunner <0.01 <0.01 < 0.01 <0.01 <0.01 0.04 3.14 4.10 <0.01 0.04 3.14 4.11

Drums and croakers 0.05 0.06 0.06 0.08 <0.01 0.04 0.83 1.00 0.05 0.09 0.89 1.08

Dungeness crab <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 <0.01 <0.01 <0.01 0.01

Flounders 0.01 0.01 0.01 0.02 <0.01 <0.01 0.08 0.13 0.01 0.01 0.09 0.15

Freshwater drum 1.13 1.19 1.37 1.52 <0.01 0.04 5.10 6.61 1.14 1.23 6.47 8.13Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 21 

### Table C

- 15: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) Nationally (million A1Es per year),

and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Leatherjacket 0.59 0.62 0.74 0.82 <0.01 <0.01 0.02 0.03 0.59 0.62 0.76 0.85

Mackerels <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Menhadens 4.26 4.42 5.30 5.89 <0.01 <0.01 0.03 0.05 4.26 4.42 5.34 5.94

Muskellunge <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Fish (other) 2.08 2.19 2.58 2.83 0.01 0.02 6.08 7.04 2.09 1.21 1.53 9.87

Northern anchovy 0.29 0.32 0.33 0.49 <0.01 <0.01 0.03 0.04 0.29 0.32 0.36 0.54

Pinfish 0.02 0.03 0.03 0.03 <0.01 <0.01 0.66 1.11 0.03 0.03 0.69 1.15

Pink shrimp 18.44 19.14 22.95 25.48 0.01 0.01 8.17 13.83 18.45 19.15 31.12 39.31

Pollock <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Rainbow smelt 0.44 0.48 0.55 0.58 <0.01 0.02 5.48 7.60 0.45 0.50 6.03 8.18

Red drum 0.08 0.08 0.09 0.10 <0.01 <0.01 <0.01 0.01 0.08 0.08 0.10 0.12

Red hake <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Rockfishes 0.01 0.01 0.02 0.02 <0.01 <0.01 5.40 8.85 0.01 0.01 5.42 8.88

Salmon <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Sauger 0.07 0.07 0.08 0.09 <0.01 0.01 1.29 1.65 0.07 0.08 1.36 1.75

Sculpins 0.02 0.02 0.02 0.03 <0.01 0.02 1.81 2.48 0.02 0.03 1.83 2.51

Scup <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Sea basses <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01

Searobin 0.81 0.84 1.00 1.11 <0.01 <0.01 0.23 0.39 0.81 0.84 1.23 1.50

Sheepshead <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.02 0.04 <0.01 <0.01 0.02 0.04

Silver hake <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Silver perch 0.39 0.41 0.51 0.55 <0.01 <0.01 3.12 5.28 0.39 0.41 3.63 5.83

Skates <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Smallmouth bass 0.21 0.22 0.26 0.29 <0.01 0.03 2.72 3.50 0.22 0.25 2.98 3.79

Smelts 2.61 2.87 3.27 3.36 <0.01 < 0.01 0.01 0.02 2.61 2.87 3.28 3.37

Spot 2.15 2.28 2.65 2.87 0.03 0.06 19.43 22.32 2.18 2.34 22.09 25.20

Spotted seatrout 1.09 1.13 1.35 1.50 <0.01 <0.01 0.09 0.16 1.09 1.13 1.44 1.66

Stone crab 0.16 0.17 0.20 0.22 <0.01 <0.01 0.25 0.43 0.16 0.17 0.45 0.65

Striped bass 0.11 0.12 0.14 0.16 <0.01 <0.01 0.77 0.89 0.12 0.12 0.91 1.05

Striped mullet 0.32 0.33 0.40 0.44 <0.01 <0.01 1.59 2.70 0.32 0.33 1.99 3.14

Sturgeons <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.02 0.02 <0.01 <0.01 0.02 0.02

Summer flounder 0.01 0.01 0.02 0.02 <0.01 <0.01 <0.01 <0.01 0.01 0.01 0.02 0.02

Sunfish 13.83 14.31 16.50 18.93 0.14 0.75 81.74 105.32 13.98 15.05 98.24 124.24

Surfperches 0.10 0.11 0.11 0.16 <0.01 <0.01 <0.01 <0.01 0.10 0.11 0.11 0.16

Tautog <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 0.08 0.11 <0.01 <0.01 0.08 0.11Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 22 

### Table C

- 15: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) Nationally (million A1Es per year),

and Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Walleye 0.10 0.11 0.13 0.13 <0.01 <0.01 0.74 0.97 0.10 0.11 0.86 1.11

Weakfish 0.84 0.90 1.02 1.11 <0.01 <0.01 1.49 1.71 0.84 0.90 2.51 2.81

White bass 5.45 5.89 6.74 7.15 <0.01 0.02 2.72 3.58 5.46 5.91 9.46 10.72

White perch 3.33 3.50 4.02 4.49 0.02 0.04 13.52 15.57 3.36 3.54 17.53 20.06

Whitefish 0.14 0.15 0.17 0.17 <0.01 <0.01 <0.01 <0.01 0.14 0.15 0.17 0.17

Windowpane <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.02 0.02 <0.01 <0.01 0.02 0.02

Winter flounder 0.03 0.03 0.03 0.04 <0.01 0.05 4.75 6.19 0.03 0.08 4.78 6.23

Yellow perch 2.78 2.91 3.35 3.76 <0.01 0.02 1.86 2.40 2.78 2.93 5.20 6.16

Total (all species) 612.75 647.47 748.19 824.23 1.41 4.53 889.31 1106.74 614.16 652.00 1637.49 1930.97

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 23 

### Table C

- 16: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) Nationally (million individuals per year), and

Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Alewife 24.60 26.09 29.95 32.87 10.32 32.59 10,007.54 13,903.96 34.92 58.68 10,037.49 13,936.83

American plaice <0.01 <0.01 <0.01 <0.01 <0.01 0.86 73.53 96.04 <0.01 0.86 73.53 96.04

American sand lance 0.05 0.05 0.07 0.08 < 0.01 6.31 542.26 708.25 0.05 6.36 542.33 708.33

American shad 6.59 6.82 7.86 9.03 0.03 0.05 18.42 21.14 6.63 6.87 26.28 30.16

Atlantic cod <0.01 <0.01 <0.01 <0.01 <0.01 0.50 43.33 56.59 <0.01 0.50 43.33 56.59

Atlantic croaker 7.31 7.61 9.08 10.06 0.41 0.58 238.62 300.83 7.72 8.19 247.71 310.89

Atlantic herring 0.01 0.01 0.02 0.02 <0.01 0.37 32.23 42.09 0.01 0.39 32.24 42.11

Atlantic mackerel <0.01 <0.01 <0.01 <0.01 <0.01 30.35 2,608.87 3,407.48 <0.01 30.35 2,608.87 3,407.48

Atlantic menhaden 20.76 22.18 25.40 27.47 0.06 21.64 1,648.53 2,133.07 20.82 43.82 1,673.93 2,160.54

Atlantic silverside 0.48 0.52 0.61 0.65 0.05 0.50 65.89 81.26 0.54 1.01 66.50 81.92

Atlantic tomcod 0.04 0.04 0.05 0.06 < 0.01 0.03 2.32 3.03 0.04 0.07 2.37 3.08

Bay anchovy 12.49 13.31 16.89 17.64 175.17 492.67 140,265.10 214,225.98 187.66 505.98 140,281.99 214,243.63

Bigmouth buffalo 0.01 0.01 0.02 0.02 < 0.01 0.02 1.98 2.55 0.02 0.03 1.99 2.56

Black bullhead 0.12 0.12 0.14 0.16 <0.01 <0.01 0.02 0.02 0.12 0.12 0.16 0.18

Black crappie 0.12 0.13 0.14 0.17 0.02 0.08 9.12 11.74 0.14 0.21 9.26 11.90

Black drum 0.01 0.01 0.01 0.02 40.50 40.50 29,342.08 49,690.98 40.51 40.51 29,342.09 49,691.00

Blennies <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 390.33 639.92 <0.01 <0.01 390.33 639.92

Blue crab 5.91 6.17 7.39 8.14 1.80 2.65 1,018.09 1,215.03 7.71 8.82 1,025.48 1,223.17

Blueback herring 64.53 66.74 76.98 88.32 1.15 5.94 649.73 835.52 65.68 72.68 726.70 923.84

Bluefish <0.01 <0.01 0.01 0.01 <0.01 <0.01 0.02 0.03 <0.01 <0.01 0.03 0.04

Bluegill 12.33 12.76 14.71 16.88 0.03 0.16 17.70 22.79 12.37 12.92 32.41 39.67

Bluntnose minnow 0.08 0.09 0.10 0.11 3.21 16.66 1,810.66 2,331.37 3.29 16.75 1,810.76 2,331.48

Brown bullhead 0.03 0.04 0.04 0.05 <0.01 <0.01 0.16 0.20 0.03 0.04 0.20 0.25

Bullheads 0.02 0.02 0.02 0.03 <0.01 0.01 1.35 1.74 0.02 0.03 1.38 1.77

Burbot <0.01 <0.01 <0.01 <0.01 0.01 0.06 6.18 7.99 0.01 0.06 6.19 7.99

Butterfish <0.01 <0.01 <0.01 <0.01 <0.01 0.05 4.48 5.86 <0.01 0.06 4.49 5.86

Cabezon <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 2.84 4.65 <0.01 <0.01 2.84 4.65

California halibut <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 3.29 5.40 <0.01 <0.01 3.29 5.40

California scorpionfish <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Carp 0.16 0.17 0.19 0.21 3.64 17.07 2,413.26 3,195.22 3.80 17.24 2,413.45 3,195.43

Chain pipefish 0.03 0.03 0.04 0.04 <0.01 <0.01 0.65 1.10 0.03 0.03 0.68 1.14

Channel catfish 0.81 0.84 0.97 1.09 0.14 0.71 77.69 100.08 0.94 1.55 78.65 101.17

Chinook salmon <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01

Crabs (other) 0.04 0.05 0.05 0.07 <0.01 14.77 3,352.55 5,345.69 0.04 14.82 3,352.61 5,345.76

Crappie 0.21 0.22 0.25 0.29 0.04 0.23 25.25 32.55 0.25 0.45 25.50 32.84

Cunner <0.01 <0.01 <0.01 <0.01 <0.01 125.28 10,767.77 14,063.92 <0.01 125.28 10,767.78 14,063.92

Darters 0.35 0.36 0.42 0.48 0.11 0.55 60.18 77.56 0.45 0.91 60.60 78.03Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 24 

### Table C

- 16: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) Nationally (million individuals per year), and

Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Delta smelt <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.01 <0.01 <0.01 <0.01 0.01

Drums and croakers 0.23 0.25 0.28 0.38 <0.01 52.55 1,330.12 1,644.78 0.23 52.80 1,330.40 1,645.16

Dungeness crab <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 0.04 0.06 <0.01 <0.01 0.04 0.06

Emerald shiner 27.71 30.40 34.66 35.75 0.51 2.57 302.77 393.49 28.22 32.97 337.43 429.24

Fish (other) 34.17 35.42 41.09 46.79 61.61 281.13 40,788.65 54,861.96 95.78 316.55 40,829.74 54,908.74

Flounders <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 136.20 223.29 <0.01 <0.01 136.20 223.30

Fourbeard rockling <0.01 <0.01 <0.01 <0.01 <0.01 1.99 171.36 223.81 <0.01 1.99 171.36 223.81

Freshwater drum 2.17 2.28 2.62 2.92 3.50 15.05 2,600.41 3,500.19 5.67 17.33 2,603.03 3,503.11

Gizzard shad 136.50 143.06 164.58 184.46 13.48 67.84 8,016.95 10,423.97 149.97 210.90 8,181.53 10,608.43

Gobies 0.06 0.06 0.07 0.08 1.56 80.89 3,194.95 4,457.82 1.62 80.95 3,195.03 4,457.91

Golden redhorse 0.03 0.03 0.04 0.04 <0.01 <0.01 1.05 1.35 0.03 0.04 1.09 1.39

Grubby <0.01 <0.01 0.01 0.01 <0.01 1.85 159.13 207.84 <0.01 1.86 159.14 207.85

Gulf killifish 0.02 0.02 0.02 0.02 <0.01 <0.01 <0.01 <0.01 0.02 0.02 0.02 0.02

Herrings 0.03 0.03 0.03 0.04 <0.01 <0.01 14.12 22.41 0.03 0.04 14.15 22.46

Hogchoker 0.24 0.25 0.30 0.32 12.92 21.78 7,393.21 8,549.29 13.15 22.03 7,393.51 8,549.62

Leatherjacket 0.41 0.42 0.51 0.56 0.33 0.33 241.86 409.59 0.74 0.76 242.37 410.16

Logperch 0.61 0.65 0.75 0.82 0.05 0.21 43.41 59.11 0.67 0.87 44.16 59.93

Longfin smelt <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Lumpfish <0.01 <0.01 <0.01 <0.01 <0.01 0.19 16.57 21.64 <0.01 0.19 16.57 21.64

Mackerels <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01

Menhadens 6.91 7.17 8.60 9.55 0.11 0.11 82.01 138.87 7.02 7.28 90.61 148.41

Muskellunge <0.01 <0.01 0.01 0.01 <0.01 <0.01 0.32 0.45 <0.01 < 0.01 0.33 0.46

Northern anchovy 0.37 0.39 0.42 0.61 <0.01 <0.01 352.68 578.20 0.37 0.39 353.10 578.81

Northern pipefish 0.01 0.01 0.01 0.02 <0.01 0.01 3.35 3.91 0.02 0.03 3.36 3.92

Pacific herring <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 15.43 25.30 <0.01 <0.01 15.43 25.30

Pinfish 0.05 0.05 0.06 0.07 0.05 1.62 61.04 85.76 0.10 1.68 61.10 85.83

Pink shrimp 18.80 19.51 23.41 25.98 0.05 0.05 38.48 65.16 18.85 19.57 61.88 91.15

Pollock <0.01 <0.01 <0.01 <0.01 <0.01 0.01 1.28 1.67 <0.01 0.02 1.28 1.67

Radiated shanny <0.01 <0.01 <0.01 <0.01 <0.01 0.47 40.74 53.21 <0.01 0 .47 40.74 53.21

Rainbow smelt 0.33 0.35 0.41 0.43 0.76 2.56 729.57 1,010.91 1.09 2.91 729.98 1,011.34

Red drum 0.07 0.08 0.09 0.10 <0.01 <0.01 0.33 0.57 0.07 0.08 0.43 0.67

Red hake 0.02 0.02 0.03 0.03 <0.01 < 0.01 <0.01 <0.01 0.02 0.02 0.03 0.03

River carpsucker 0.01 0.01 0.01 0.02 <0.01 0.02 1.89 2.44 0.01 0.03 1.91 2.45

Rock gunnel <0.01 <0.01 <0.01 <0.01 <0.01 1.70 146.13 190.86 <0.01 1.70 146.13 190.86

Rockfishes 0.01 0.01 0.01 0.02 <0.01 <0.01 27.29 44.74 0.01 0.01 27.30 44.76

Sacramento splittail <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Salmon <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 1.62 2.25 <0.01 <0.01 1.62 2.25

Sauger 0.08 0.08 0.09 0.11 0.20 1.06 115.46 148.65 0.28 1.14 115.56 148.75Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 25 

### Table C

- 16: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) Nationally (million individuals per year), and

Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Scaled sardine 0.15 0.15 0.18 0.20 1.25 1.25 902.35 1,528.14 1.39 1.40 902.54 1,528.34

Sculpins <0.01 0.01 0.01 0.02 <0.01 0.94 102.09 140.23 0.01 0.95 102.10 140.25

Scup <0.01 <0.01 <0.01 <0.01 <0.01 0.07 6.14 8.02 <0.01 0.07 6.14 8.03

Sea Basses <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 5.65 9.26 <0.01 <0.01 5.65 9.26

Seaboard goby <0.01 <0.01 <0.01 <0.01 6.76 20.41 4,637.25 5,460.76 6.77 20.42 4,637.26 5,460.77

Searobin 0.51 0.53 0.63 0.70 0.03 0.08 25.20 41.04 0.54 0.60 25.83 41.74

Sheepshead <0.01 <0.01 <0.01 <0.01 0.16 0.16 116.63 197.51 0.16 0.16 116.63 197.51

Shiners 1.88 1.99 2.28 2.51 0.23 1.13 148.42 195.04 2.11 3.12 150.70 197.55

Shrimp (other) 2.31 2.48 3.37 3.41 <0.01 23.01 594.47 740.02 2.31 25.48 597.84 743.43

Silver hake 0.02 0.02 0.02 0.02 <0.01 2.44 209.93 274.19 0.02 2.46 209.95 274.21

Silver perch 0.31 0.33 0.42 0.44 37.41 37.41 27,105.51 45,903.34 37.73 37.74 27,105.92 45,903.78

Silversides 0.10 0.11 0.12 0.15 0.03 0.16 69.85 108.12 0.13 0.27 69.97 108.27

Skates <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Skipjack herring 0.53 0.54 0.63 0.72 <0.01 <0.01 0.20 0.25 0.53 0.55 0.83 0.97

Smallmouth bass 0.06 0.07 0.08 0.09 0.04 0.18 20.03 25.79 0.10 0.25 20.11 25.87

Smelts 1.18 1.30 1.48 1.52 0.04 0.13 41.11 57.51 1.22 1.43 42.59 59.03

Spot 3.45 3.67 4.28 4.63 0.13 47.79 925.53 1,001.16 3.58 51.46 929.81 1,005.79

Spotted seatrout 0.52 0.54 0.64 0.72 2.24 3.02 1,639.94 2,768.53 2.76 3.56 1,640.58 2,769.25

Spotted sucker <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01 <0.01

Stone crab 0.12 0.12 0.15 0.16 12.07 12.07 8,745.52 14,810.59 12.19 12.19 8,745.67 14,810.76

Striped bass 0.58 0.60 0.69 0.79 0.52 0.79 295.84 341.86 1.10 1.39 296.52 342.65

Striped killifish 0.09 0.10 0.12 0.13 <0.01 <0.01 0.02 0.03 0.09 0.10 0.14 0.16

Striped mullet 0.19 0.20 0.24 0.27 <0.01 <0.01 4.62 7.82 0.20 0.21 4.86 8.09

Sturgeons <0.01 <0.01 <0.01 < 0.01 <0.01 <0.01 0.54 0.69 <0.01 <0.01 0.54 0.69

Suckers 0.06 0.07 0.08 0.09 2.86 14.80 1,627.05 2,097.86 2.93 14.87 1,627.12 2,097.94

Summer flounder 0.02 0.02 0.03 0.03 <0.01 <0.01 <0.01 <0.01 0.02 0 .02 0.03 0.03

Sunfish 2.22 2.29 2.64 3.03 0.43 2.20 240.66 310.09 2.64 4.49 243.31 313.12

Surfperches 0.06 0.06 0.06 0.09 <0.01 <0.01 <0.01 <0.01 0.06 0.06 0.06 0.09

Tautog <0.01 <0.01 <0.01 <0.01 <0.01 125.83 10,815.39 14,126.11 <0.01 125.84 10,815.39 14,126.11

Threespine stickleback 0.03 0.04 0.04 0.05 <0.01 <0.01 0.21 0.29 0.03 0.04 0.26 0.34

Tidewater silverside 0.13 0.13 0.16 0.18 0.01 0.01 10.47 17.73 0.14 0.15 10.63 17.90

Walleye 0.14 0.15 0.17 0.18 0.12 0.60 71.64 93.18 0.26 0.75 71.81 93.36

Weakfish 0.98 1.04 1.20 1.29 0.24 4.06 299.81 360.95 1.22 5.11 301.01 362.24

White bass 3.05 3.29 3.77 4.00 0.76 3.80 449.52 584.53 3.80 7.09 453.28 588.53

White perch 11.30 12.32 14.06 14.67 1.84 4.77 1,129.04 1,388.88 13.14 17.09 1,143.10 1,403.55Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix C: Details of Regional IM&E

May 2014 C

- 26 

### Table C

- 16: Baseline IM&E at All Regulated Facilities (Manufacturing and Generating) Nationally (million individuals per year), and

Reductions in IM&E for Option Scenarios Estimated for All Sources of Mortality

Species Impingement Entrainment IM&E

P4 F P2 B P4 F P2 B P4 F P2 B

Whitefish 0.03 0.03 0.04 0.04 <0.01 <0.01 0.36 0.47 0.03 0.04 0.39 0.51

Windowpane <0.01 <0.01 <0.01 0.01 <0.01 8.88 762.82 996.32 <0.01 8.88 762.83 996.33

Winter flounder 0.05 0.05 0.06 0.07 0.05 28.79 2,494.01 3,253.45 0.09 28.84 2,494.07 3,253.52

Yellow perch 3.81 3.99 4.59 5.15 0.73 3.77 419.01 540.94 4.54 7.76 423.60 546.09

Total (all species) 419.91 441.30 511.87 568.56 399.82 1,693.86 335,447.57 497,316.28 819.74 2,135.17 335,959.44 497,884.85

Notes:

P4 = Proposal Option 4 ; F = Final Rule

– Existing Uni ts; P2 = Proposal Option 2; and B = Baseline

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix D: Discounting Benefits

July 8, 2014 D

- 1 

# Appendix D: Discounting Benefits

D.1 Introduction

Discounting refers to the economic conversion of future benefits and costs to present values, accounting

for the fact that individuals tend to value future outcomes less than comparable near

- term outcomes.

Annualization refers to the conversion of a series of annual costs or benefits of differing amounts to an

equivalent annual series of constant costs or benefits. Discounting and annualization are important

techniques which allow the comparison of benefits and /or costs that occur in different time periods.

EPA’s discounting and annualization methodology for the benefits analysis of the final rule and options

considered, included three steps. First, EPA developed a time profile of benefits to show when benefits

occur. Second, the Agency calculated the total discounted present value of the benefits as of th e year

2013. Finally, EPA annualized the benefits of the final rule and other options considered, over a 51

- year

time span. The following sections explain these steps in detail.



## D.2 Timing of Benefits

T o calculate the annualized value of the potential welfare gain s, EPA first calculated the undiscounted

welfare gain from the expected annual regional reductions in IM&E under the final rule and other option s

considered assuming all facilities have installed required technology. Then, EPA created a time profile of

benefits that takes into account the regulatory and biological time lags between the potential promulgation

of the final rule and each regulatory option considered, and the realization of benefits.

EPA assigned each facility a technology installation year which varies across facilities and regulatory

options based on facility characteristics and type of technology being installed. Facilities installing

impingement only technology have technology installation years ranging from 2018 to 2022, non

- nuclear

ele ctric generating facilities and manufacturing facilities installing towers have technology installation

years ranging from 2020 to 2024, and nuclear generating facilities installing towers have technology

installation years ranging from 2026 to 2030. EPA estimates that a small number of manufacturers could

be required to install both IM&E technology and towers. EPA assumed that these facilities would install

both technologies at the same time, during the 5

- year window of 2021 through 2025. Compliance i s

assumed to continue until the year 2059 for all facilities. See Chapter 3 of the EA report for more detail

.

A biological time lag occurs between installation of technologies to reduce IM&E and realization of

commercial and recreational angling benefits because these fish may require several years to grow and

mature before commercial and recreational anglers can harvest them

. For example, a larval fish spared

from entrainment (in effect, at age zero) may be caught by a recreational angler at age three . A three

- year

time lag then arises between the installation of technologies to reduce IM&E and the realization of the

estimated recreational benefit. Likewise, if a one

- year

- old fish is spared from impingement and is then

harvested by a commercial fishe rman at age two, there is a one

- year lag between the installation of

technologies to reduce IM&E and the subsequent commercial fishery benefit. In general, there will be

relatively short time lags between implementation of technologies to reduce IM&E and the su bsequent

timing of changes in catch for fish that tend to be harvested at young ages. In contrast, for long

- lived fish

that tend to be caught at relatively older ages , there would be longer time lags and, hence, the effects of

discounting would be larger, resulting in lower present values.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix D: Discounting Benefits

July 8, 2014 D

- 2 

### To model the biological time lags, EPA collected species

- specific information on ages of fish at harvest to

estimate the average time required for a fish spared from IM&E, to reach a harvestable age. The estimated

time la gs vary, depending on the life history of each fish species affected. EPA used this information,

along with information about the estimated age and species composition of IM&E in each study region, to

develop a benefits schedule for facilities in each regi on. 93 

### EPA used these lags in analyses for both

existing and new units.

EPA assumes that once facilities have installed technology, commercial and recreational fishing benefits

from facilities in most regions (the California, North Atlantic, Mid

- Atlantic, an d South Atlantic regions)

increase over a seven

- year period to a long

- term, steady

- state average. This average is equal to the

approximated per

- facility benefit value discussed above, according to a numerical profile of <0.0, 0.1,

0.2, 0.8, 0.9, 0.95, 1.0> . This profile is the fraction of the steady

- state benefit value (i.e., the percentage of

commercial and recreational fish spared from IM&E that reach a harvestable age) that is realized in each

of the first seven years following a facility installing tech nology.

For regions with a relatively high contribution of impingement to total IM&E ( the Inland, Great Lakes,

and Gulf of Mexico regions), EPA used an adjusted profile of <0.1, 0.2, 0.8, 0.9, 0.95, 1.0> for

commercial and recreational fishing benefits

. This adjusted profile reflects the fact that impinged fish are

usually larger and older than entrained fish

, and thus benefits will be realized sooner in these three

regions. These profile values are approximations based on a review of the age

- specific fis hing mortality

rates that EPA used in the IM&E analysis and best professional judgment. 94



### In all regions, this fraction remains 1.0 until the final year of compliance, 2059. The commercial and

recreational fishing benefits profile declines at the end of the compliance period in the same fashion that it

increases after technology installation. This reflects the fact that the fish saved by technology would

survive and could still be harvested beyond the end of the compliance period. Specifically, at the end of

the compliance period, benefit values decline following a profile of <0.9, 0.8, 0.2, 0.1, 0.05, 0.0> , with

the last benefits occurring in 2064

. Therefore, the benefits analysis encompasses a 51

- year period from

rule promulgation and first incidence of com pliance

- related costs in 2014, until the final benefits are

realized in 2064. The number of years when benefits do not equal zero varies among the regulated

facilities, depending on the year that it installs technology.

EPA assumes no initial biological lag for nonuse benefits (including benefit transfer and preliminary

benefits based on the 316(b) SP survey) at the start of the compliance period because nonuse benefits are

not based on the harvest of fish spared from IM& E. EPA assumes that benefits begin accruing

immediately when a facility installs technology, and continue being generated in full until the year 2059.

The nonuse benefit transfer includes a linear decline in benefits starting at the end of the compliance

p eriod following a profile of <1.0, 0.82, 0.62, 0.37, 0.20, 0.06, 0.0> with the last benefits occurring in

2064. This profile reflects NMFS estimates of age

- specific and fisheries

- related mortality. For the

analysis for the 316(b) SP survey, EPA assumes tha t benefits end in 2059, the final year of the

compliance period, and does not include a declining profile beyond this year. This is consistent with the

definition of the fish saved attribute which was used to generate preliminary benefits estimates based o n

93 The benefits profile aggregated across all facilities in a region or nationwide was calcu lated using facility

- level sample

weights. These facility

- level sample weights were designed so that the weighted actual regional intake flow for the sample

facilities is the same as the estimated actual regional intake flow for the entire universe of faci lities. These sample weights

are described in more detail in Appendix A.

94 EPA applied biological lags consistent with the Inland, Great Lakes, and Gulf Mexico regions when estimating commercial,

recreational, and T&E species benefits for new units becaus e these regions account for the majority of national benefits for

these categories.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix D: Discounting Benefits

July 8, 2014 D

- 3 

### the 316(b) SP survey. EPA does not include any lags in its analysis of benefits associated with changes in

GHG emissions.



## D.3 Discounting and Annualization

Using the time profile of benefits discussed above, EPA discounted the total benefits generated in ea ch

year of the analysis to 20 13 using the following formula:

(D

- 1)

where:

Benefits

t 

### = benefits in year t

r = discount rate (3 percent and 7 percent)

t = year in w hich benefits are incurred

After calculating the pres ent v alue (PV) of these benefit streams, EPA calculated a constant annual

equivalent value (annualized value) using the annualization formula presented below, again using two

discount rates, 3 percent and 7 percent

. 95 

### Although the analysis perio d extends further

, EPA annualized

benefits over the assumed period of compliance for regulated facilities

. EPA followed t his same

annualization concept and period of annualization in the cost analysis, although the time horizon for

calculating the present value is shorter than for benefits. Using the same annualization period for both

benefits and social costs allows EPA to compar e constant annual equivalent values of benefits and costs

that have been calculated on a mathematically consistent basis. The annualization formul a is as follows:

(D

- 2)

where:

r = discount rate (3 percent and 7 percent )

n = annualization period, 51 years for the benefits analysis

Table D

- 1 presents a summary of the time profile of benefits discounted at the 3 percent and 7 percent

rates for the final rule a nd the regulatory options considered, on the national scale . The table also presents

the total and annualized value s that are equivalent to this stream of benefits.

95 The three percent rate represents an estimate of the social rate of time preference.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix D: Discounting Benefits

July 8, 2014 D

- 4 

### Table D

- 1 : Time Profile of Discounted National Mean Benefits at Regulated Facilities by Reg ulatory Option using 3% and 7%

Discount Rates (2011$, millions) a

Year Proposal Option 4 Final Rule

– Existing Units Proposal Option 2 Final Rule

– New Units Final Rule

- Existing Units

and New Units

3% 7% 3% 7% 3% 7% 3% 7% 3% 7%

2013 $0.000 $0.000 $0.000 $0.000 $0.000 $0.000 $0.000 $0.000 $0.000 $0.000

2014 $0.000 $0.000 $0.000 $0.000 $0.000 $0.000 $0.004 $0.004 $0.004 $0.004

2015 $8.147 $7.550 $8.147 $7.550 $0.000 $0.000 $0.008 $0.008 $8.156 $7.557

2016 $8.124 $7.246 $8.124 $7.246 $0.000 $0.000 $0.014 $0.012 $8.138 $7.259

2017 $8.095 $6.951 $8.095 $6.951 $0.000 $0.000 $0.008 $0.007 $8.103 $6.957

2018

- $1.517

- $1.254

- $1.334

- $1.103 $118.959 $98.325 $0.002 $0.002

- $1.332

- $1.101

2019

- $1.488

- $1.184

- $1.302

- $1.036 $121.271 $96.489

- $0.005

- $0.004

- $1.307

- $1.040

2020

- $0.670

- $0.513

- $0.158

- $0.121 $121.582 $93.120

- $0.011

- $0.009

- $0.170

- $0.130

2021 $0.542 $0.399 $1.236 $0.911

- $999.546

- $736.937

- $0.017

- $0.012 $1.219 $0.899

2022 $5.572 $3.955 $6.772 $4.806

- $974.242

- $691.429

- $0.023

- $0.016 $6.749 $4.790

2023 $43.850 $29.958 $45.283 $30.936

- $1,079.211

- $737.294

- $0.029

- $0.020 $45.253 $30.916

2024 $49.786 $32.741 $51.603 $33.936

- $1,052.143

- $691.931

- $0.036

- $0.024 $51.567 $33.913

2025 $51.111 $32.356 $53.031 $33.571

- $1,031.582

- $653.048

- $0.043

- $0.027 $52.988 $33.544

2026 $51.040 $31.103 $52.955 $32.270

- $1,709.258

- $1,041.604

- $0.049

- $0.030 $52.905 $32.240

2027 $50.690 $29.735 $52.582 $30.845

- $1,689.775

- $991.236

- $0.056

- $0.033 $52.526 $30.812

2028 $49.896 $28.175 $51.737 $29.215

- $1,671.154

- $943.666

- $0.063

- $0.035 $51.675 $29.180

2029 $49.052 $26.663 $50.840 $27.635

- $1,651.425

- $897.664

- $0.069

- $0.038 $50.771 $27.597

2030 $48.215 $25.229 $49.951 $26.137

- $1,634.747

- $855.380

- $0.076

- $0.040 $49.875 $26.097

2031 $46.811 $23.578 $48.496 $24.427

- $1,143.475

- $575.955

- $0.079

- $0.040 $48.417 $24.387

2032 $46.005 $22.306 $47.642 $23.099

- $1,131.655

- $548.693

- $0.086

- $0.042 $47.556 $23.058

2033 $15.959 $7.448 $17.547 $8.190

- $1,120.741

- $523.087

- $0.092

- $0.043 $17.455 $8.147

2034 $15.494 $6.961 $17.036 $7.654

- $1,109.610

- $498.532

- $0.098

- $0.044 $16.938 $7.610

2035 $15.043 $6.506 $16.540 $7.153

- $1,098.347

- $475.024

- $0.104

- $0.045 $16.436 $7.108

2036 $14.604 $6.080 $16.058 $6.685

- $1,086.843

- $452.477

- $0.110

- $0.046 $15.948 $6.640

2037 $14.179 $5.682 $15.591 $6.248

- $1,074.992

- $430.812

- $0.116

- $0.046 $15.475 $6.202

2038 $13.766 $5.311 $15.136 $5.839

- $1,062.923

- $410.051

- $0.122

- $0.047 $15.015 $5.792

2039 $13.365 $4.963 $14.696 $5.457

- $1,050.571

- $390.135

- $0.127

- $0.047 $14.568 $5.410

2040 $12.976 $4.639 $14.268 $5.100

- $1,038.033

- $371.068

- $0.133

- $0.047 $14.135 $5.053

2041 $12.598 $4.335 $13.852 $4.767

- $1,025.492

- $352.881

- $0.138

- $0.047 $13.714 $4.719

2042 $12.231 $4.051 $13.449 $4.455

- $1,012.802

- $335.486

- $0.143

- $0.047 $13.305 $4.407

2043 $11.875 $3.786 $13.057 $4.163

- $999.981

- $318.856

- $0.148

- $0.047 $12.909 $4.116

2044 $11.529 $3.539 $12.677 $3.891

- $987.047

- $302.967

- $0.153

- $0.047 $12.524 $3.844

2045 $11.193 $3.307 $12.307 $3.636

- $974.019

- $287.791

- $0.158

- $0.047 $12.150 $3.590

2046 $10.867 $3.091 $11.949 $3.399

- $960.912

- $273.305

- $0.162

- $0.046 $11.787 $3.352

2047 $10.551 $2.889 $11.601 $3.176

- $947.742

- $259.482

- $0.167

- $0.046 $11.434 $3.131Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix D: Discounting Benefits

July 8, 2014 D

- 5 

### Table D

- 1: Time Profile of Discounted National Mean Benefits at Regulated Facilities by Regulatory Option using 3% and 7%

Discount Rates (2011$, millions) a

Year Proposal Option 4 Final Rule

– Existing Units Proposal Option 2 Final Rule

– New Units Final Rule

- Existing Units

and New Units

3% 7% 3% 7% 3% 7% 3% 7% 3% 7%

2048 $10.243 $2.700 $11.263 $2.968

- $934.525

- $246.298

- $0.171

- $0.045 $11.092 $2.923

2049 $9.945 $2.523 $10.935 $2.774

- $921.273

- $233.729

- $0.175

- $0.044 $10.760 $2.730

2050 $9.655 $2.358 $10.616 $2.593

- $908.001

- $221.750

- $0.179

- $0.044 $10.438 $2.549

2051 $9.374 $2.204 $10.307 $2.423

- $894.911

- $210.383

- $0.182

- $0.043 $10.125 $2.380

2052 $9.101 $2.060 $10.007 $2.265

- $881.999

- $199.596

- $0.186

- $0.042 $9.821 $2.222

2053 $8.836 $1.925 $9.715 $2.116

- $869.263

- $189.360

- $0.190

- $0.041 $9.526 $2.075

2054 $8.579 $1.799 $9.433 $1.978

- $856.700

- $179.647

- $0.193

- $0.040 $9.240 $1.937

2055 $8.329 $1.681 $9.158 $1.849

- $844.308

- $170.430

- $0.196

- $0.040 $8.961 $1.809

2056 $8.086 $1.571 $8.891 $1.728

- $832.085

- $161.684

- $0.200

- $0.039 $8.692 $1.689

2057 $7.851 $1.468 $8.632 $1.615

- $820.030

- $153.385

- $0.203

- $0.038 $8.429 $1.577

2058 $7.622 $1.372 $8.381 $1.509

- $808.141

- $145.510

- $0.206

- $0.037 $8.175 $1.472

2059 $7.400 $1.283 $8.137 $1.410

- $796.414

- $138.038

- $0.209

- $0.036 $7.928 $1.374

2060 $6.459 $1.078 $7.086 $1.182 $35.306 $5.891 $0.065 $0.011 $7.151 $1.193

2061 $5.567 $0.894 $6.093 $0.979 $29.154 $4.682 $0.054 $0.009 $6.146 $0.987

2062 $1.384 $0.214 $1.586 $0.245 $13.337 $2.062 $0.027 $0.004 $1.613 $0.249

2063 $0.680 $0.101 $0.795 $0.118 $7.937 $1.181 $0.016 $0.002 $0.811 $0.121

2064 $0.330 $0.047 $0.387 $0.055 $3.942 $0.565 $0.008 $0.001 $0.395 $0.057

Total Present Value b

- $828.931 $402.860 $880.882 $424.898

- $41,234.429

- $16,994.287

- $4.694

- $1.492 $876.188 $423.406

Annualized Value c

- $31.012 $27.219 $32.955 $28.708

- $1,542.641

- $1,148.205

- $0.176

- $0.101 $32.779 $28.607

a Values presented here are based on 3 percent average SCC values.

b The total present value is equal to the sum of the values of the benefits realized in all years of the analysis, discounted t o 201 3

.

c The annualized value represents the total present value of the benefits of the rule , distributed over a 5 1

- year period.

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix E: List of T& E Species Overlapping CWIS

July 8, 2014 E

- 1 

# Appendix E: List of T&E Species Overlapping CWIS

Table E

- 1: List of 99 T &E Species Overlapping One or More Regulated CWIS

Latin Name Common Name

Acipenser brevirostrum Shortnose Sturgeon

Acipenser medirostris Green Sturgeon

Acipenser oxyrinchus desotoi Gulf Sturgeon

Acipenser oxyrinchus oxyrinchus Atlantic Sturgeon

Alasmidonta heterodon Dwarf Wedgemussel

Amblema neislerii Fat Threeridge

Amblyopsis rosae Ozark Cavefish

Arkansia wheeleri Ouachita Rock Pocketbook

Athearnia anthonyi Anthony's Riversnail

Campeloma decampi Slender Campeloma

Caretta caretta Loggerhead Sea Turtle

Chelonia mydas Green Sea Turtle

Cottus Paulus Pygmy Sculpin

Cyprinella caerulea Blue Shiner

Cyprogenia stegaria Fanshell

Dermochelys coriacea Leatherback Sea Turtle

Dromus dromas Dromedary Pearlymussel

Elliptio chipolaensis Chipola Slabshell

Elliptio spinosa Altamaha Spinymussel

Elliptio steinstansana Tar River Spinymussel

Elliptoideus sloatianus Purple Bankclimber

Epioblasma brevidens Cumberlandian Combshell

Epioblasma capsaeformis Oyster Mussel

Epioblasma florentina florentina Yellow (Pearlymussel) Blossom

Epioblasma florentina walkeri Tan Riffleshell

Epioblasma obliquata obliquata Catspaw (Purple Cat's Paw Pearlymussel)

Epioblasma obliquata perobliqua White (Pearlymussel) Catspaw

Epioblasma torulosa gubernaculum Green (Pearlymussel) Blossom

Epioblasma torulosa rangiana Northern Riffleshell

Epioblasma torulosa torulosa Tubercled (Pearlymussel) Blossom

Epioblasma turgidula Turgid (Pearlymussel) Blossom

Eretmochelys imbricata Hawksbill Sea Turtle

Etheostoma etowahae Etowah Darter

Etheostoma percnurum Duskytail Darter

Etheostoma scotti Cherokee Darter

Etheostoma wapiti Boulder Darter

Fusconaia cor Shiny Pigtoe

Fusconaia cuneolus Finerayed Pigtoe

Gasterosteus aculeatus williamsoni Unarmored Threespine Stickleback

Gila bicolor mohavensis Mohave Tui Chub

Hemistena lata Cracking Pearlymussel

Hypomesus transpacificus Delta Smelt

Lampsilis abrupta Pink (Pearlymussel) MucketBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix E: List of T& E Species Overlapping CWIS

July 8, 2014 E

- 2 

### Table E

- 1: List of 99 T&E Species Overlapping One or More Regulated CWIS

Latin Name Common Name

Lampsilis higginsii Higgins Eye (Pearlymussel)

Lampsilis powellii Arkansas Fatmucket

Lampsilis subangulata Shinyrayed Pocketbook

Lampsilis virescens Alabama Lampmussel

Lepidochelys kempii Kemp's Ridley Sea Turtle

Lepidochelys olivacea Olive Ridley Sea Turtle

Leptodea leptodon Scaleshell Mussel

Leptoxis ampla Round Rocksnail

Leptoxis foreman Interrupted (Georgia) Rocksnail

Leptoxis plicata Plicate Rocksnail

Leptoxis taeniata Painted Rocksnail

Margaritifera hembeli Louisiana Pearlshell

Medionidus penicillatus Gulf Moccasinshell

Medionidus simpsonianus Ochlockonee Moccasinshell

Notropis albizonatus Palezone Shiner

Noturus placidus Neosho Madtom

Noturus stanauli Pygmy Madtom

Obovaria retusa Ring Pink (Mussel)

Oncorhynchus clarki stomias Greenback Cutthroat

Oncorhynchus keta Chum Salmon

Oncorhynchus kisutch Coho Salmon

Oncorhynchus mykiss Steelhead Trout

Oncorhynchus tshawytscha Chinook Salmon

Oregonichthys crameri Oregon Chub

Pegias fabula Littlewing Pearlymussel

Percina rex Roanoke Logperch

Percina tanasi Snail Darter

Phoxinus cumberlandensis Blackside Dace

Plethobasus cicatricosus White (Pearlymussel) Wartyback

Plethobasus cooperianus Orangefoot (Pearlymussel) Pimpleback

Pleurobema clava Clubshell

Pleurobema collina James Spinymussel

Pleurobema curtum Black Clubshell

Pleurobema hanleyianum Georgia Pigtoe

Pleurobema marshalli Flat Pigtoe

Pleurobema plenum Rough Pigtoe

Pleurobema pyriforme Oval Pigtoe

Pleurobema taitianum Heavy Pigtoe

Pleurocera foremani Rough Hornsnail

Potamilus capax Fat Pocketbook

Potamilus inflatus Alabama (Inflated) Heelsplitter

Ptychocheilus lucius Colorado Pikeminnow (Squawfish)

Quadrula cylindrica strigillata Rough Rabbitsfoot

Quadrula fragosa Winged Mapleleaf

Quadrula intermedia Cumberland (Pearlymussel) Monkeyface

Quadrula sparsa Appalachian (Pearlymussel) Monkeyface

Quadrula stapes StirrupshellBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix E: List of T& E Species Overlapping CWIS

July 8, 2014 E

- 3 

### Table E

- 1: List of 99 T&E Species Overlapping One or More Regulated CWIS

Latin Name Common Name

Salmo salar Atlantic Salmon

Salvelinus confluentus Bull Trout

Scaphirhynchus albus Pallid Sturgeon

Scaphirhynchus suttkusi Alabama Sturgeon

Speoplatyrhinus poulsoni Alabama Cavefish

Toxolasma cylindrellus Pale (Pearlymussel) Lilliput

Villosa perpurpurea Purple Bean

Villosa trabalis Cumberland (Pearlymussel) Bean

Xyrauchen texanus Razorback Sucker

Source: U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix F: Methods for T&E Species Benefits

July 8, 2014 F

- 1 

# Appendix F: Detailed Methodologies for Estimating Benefits to

Threatened and Endangered Species

F.1 IM&E of Sea Turtles

Six species of sea turtles are found in waters of the United States: Green, Hawksbill, Kemp's Ridley,

Leatherback, Loggerhead, and Olive Ridley sea turtles. All have extensive ranges, migrate long distances

during their lifetime, and are listed as either T &E under the ESA. Because of these large ranges, there is

substantial overlap between sea turtle habitat and CWIS for regulated facilities. Moreover, because

individuals of all ages and sizes are susceptible to impingement and entrainment ( Norem 2005 ) , there are

more than 730 locations of pot ential interactions between species ranges and CWIS that may result in the

injury or death of these T&E species.

Power plants are known to entrain and impinge all species of sea turtles, with individual incidences of

mortality reported from California, Tex as, Florida, South Carolina, North Carolina

, and New Jersey

( Plotkin 1995 ) . Although the cumulative impact of this mortality is unclear, it may be relatively small

compared to fishing mortality. Although quantitative reports are available from a few power stations

( Table F

- 1 ), high

- quality data is available from only one source, the St. Lucie Nuclear Power Plant, at

Hutchinson Island, F lorida , where annual capture rates range from 350 to 1

, 000 turtles. Although

estimated mortalit y rates due to entrainment are < 3 percent , approximately 85 percent of entrained

organisms show evidence of injury as a result of entrainment ( Norem 2005 )

. As such, true mortality rates

from CWIS may be higher than reported, particularly for individuals who are recaptured repeatedly (37

percent of Green and 13 percent of Loggerhead sea turtles entrained between May and December 2000

were recaptured individuals) ( Norem 2005 )

.

In addition to research sponsored by the National Science Foundation, federal and state government al

spen ding on sea turtles under the ESA totaled $33. 8 million in FY2008 ( USFWS 2009 ) . Moreover, the

number of volunteer organizations dedicated to sea turtle recovery ( Table F

- 2 ) provides further evidence

of the high nonuse values placed upon the survival of these animals by the public.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix F: Methods for T&E Species Benefits

July 8, 2014 F

- 2 

### Table F

- 1: Reported Numbers of Sea Turtle Entrainment Incidences

Facility(s) Species Takes

Dates Takes / yr

Source

Non

- lethal Lethal Non

- lethal Lethal

Crystal R i ver, FL Kemp's Ridley, Loggerhead 40 5 1998 40 5 TEWG ( 2000 )

Brunswick, NC Loggerhead, Kemp's Ridley, Green 50 11 2000 50 11 NMFS ( 2001 )

Oyster Creek, NJ ; Salem, NJ;

and Hope, NJ Loggerhead 40 8 1999 40 8

NMFS ( 2001 ) Kemp's Ridley 7 3 1999 7 3

Green 8 2 1999 8 2

Salem, NJ Loggerhead, Kemp's Ridley, Green 23 2 1991 23 2 Eggers ( 2001 )

Salem, NJ Loggerhead 18 8 1980

- 1988 2.25 1 Eggers ( 1989 ) Salem, NJ Kemp's Ridley 6 6 1980

- 1988 0.75 0.75

St. Lucie, FL Loggerhead 6313 169 1976

- 2005 225.5 6 NMFS ( 2009 )

San Diego, Edison Olive Ridley QR QR QR QR QR ( NMFS and USFWS

1998b )

San Diego, Encina, Edison Green QR QR QR QR QR ( NMFS and USFWS

1998a )

St. Lucie, FL Leatherback 20 1976

- 1998 0.95 Bresette et al ( 1998 )

St. Lucie, FL Hawksbill 19 1976

- 1998 0.90 Bresette et al ( 1998 )

St. Lucie, FL Green 2297 1976

- 1998 109.38 Ernest et al ( 1988 )

St. Lucie, FL Kemp's Ridley 34 1976

- 1998 1.62 Bresette et al ( 1998 )

All US Waters Loggerhead

- 5

- 50 Annual

Estimate - 5

- 50 Plotkin ( 1995 )

Notes:

QR = qualitative resports only

“

- “ = value not availableBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix F: Methods for T&E Species Benefits

July 8, 2014 F

- 3 

### Table F

- 2: Subset of Nongovernmental Organizations Based in the United States Dedicated to

Sea Turtle Research and Conservation

Name Group Type Web Address

Amelia Island Sea Turtle Watch, Inc. Volunteer www.ameliaislandseaturtlewatch.com/

Archie Carr Center for Sea Turtle Research Academic accstr.ufl.edu/

Bald Head Island Conservancy Volunteer www.bhic.org/STPP.shtml

California Turtle & Tortoise Club Volunteer www.tortoise.org/

Caribbean Conservation Corporation Nonprofit www.helpingseaturtles.org/

Chelonian Research Foundation Academic www.chelonian.org/

Clearwater Marine Aquarium Nonprofit/Volunteer www.seewinter.com/what

- we

- do/nesting

Coastal Research and Education Society of

Long Island, Inc., New York State Sea

Turtle Program Nonprofit/Volunteer www.cresli.org/cresli/turtles/turtpage.html

Conservation International Sea Turtle

Flagship Program Nonprofit www.conservation.org/discover/centers_programs

/sea_turtles/Pages/seaturtles.aspx

Earthwatch Nonprofit/Ecotourism www.earthwatch.org

Gulf Coast Turtle and Tortoise Society Volunteer www.gctts.org/

Hawksbill Sea Turtle Recovery Project Government/Volunteer www.fpir.noaa.gov/PRD/prd_volunteer_opps.html

Malama na Honu Nonprofit/Volunteer malamanahonu.org/

Marine Turtle Specialist Group Academic www.iucn

- mtsg.org/

Maryland Marine Mammal and Sea Turtle

Stranding Network Government/Volunteer www.dnr.state.md.us/fish eries/oxford/research/fw

h/strandingprogram.html

National Aquarium in Baltimore, Marine

Animal Rescue Program Nonprofit/Volunteer www.aqua.org/oceanhealth_marp.html

National Save the Sea Turtle Foundation Nonprofit savetheseaturtle.org/

Network for Endangered Seaturtles Volunteer www.nestonline.org/

Ocean Conservancy Nonprofit www.oceanconservancy.org/

Riverhead Foundation for Marine Research

and Preservation Nonprofit/Volunteer www.riverheadfoundation.org/index.asp

Sanibel

- Captiva Conservation Foundation Nonprofit/Volunteer www.sccf.org/

Sea Turtle Restoration Project Nonprofit www.seaturtles.org

Share the Beach, Sea Turtle Volunteering

Program Volunteer www.alabamaseaturtles.com/

The Leatherback Trust Nonprofit leatherback.org/

The Turtle Foundation Nonprofit www.turtle

- foundation.org

Source: U.S. EPA analysis for this report



## F.2 Application of Whitehead’s (1993) Benefit Transfer Approach for Estimating

WTP for T&E Sea Turtle Species

EPA identified a study that used a stated preference valuation approach to estimate the total economic

value (i.e. use and nonuse values) of a management program designed to reduce the risk of extinction for

loggerhead sea turtles ( Whitehead 1993 )

. The mail survey asked North Carolina households whether they

were willing to pay a bid amount for a management program which reduces the probability that

loggerhead sea turtles would be extinct in 25 years. Within the model framework, the baseline ex tinction

risk and change from the management program are expressed in terms of a supply probability. Supply

probability reflects the probability that “the wildlife resource will continue to exist so it can be enjoyed by

recreational users and nonusers (p.1 21)” ( Whitehead 1993 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix F: Methods for T&E Species Benefits

July 8, 2014 F

- 4 

### The household value is expressed as the option price, or WTP to pay under conditions of future supply

and demand uncertainty. The option price is estimated by solving for the dollar amount which would

make the responden t indifferent to utility with and without the management program. The function used

to estimate the option price (Model B from Whitehead ( 1993 ) ) is:

OP (1991$) = 1.272 [p

2 

### (r 2 

### - q 2 

### )] / 0.029 Equation F

- 1

Variable definitions for the parameters in the function are described in Table F

- 3

.

EPA used Whitehead ( 1993 ) to assess the range of benefits potentially resulting from the final rule and

regulatory options considered. EPA reviewed avai lable data sources and biological models to assess the

potential impact of baseline losses and reductions on sea turtle supply probability (r 2 

### - q 2 

### ) . While analyses

of sea turtle extinction risk have been conducted (e.g., Conant et al. 2009), EPA was unable to identify an

existing model or analysis which could be readily used in conjunction with available mortality data to

estimate the marginal impacts of CWIS on sea turtle extinction risk.

Estimates from the literature suggest that IM&E is of relatively low importance compared to other

human

- induced mortality such as shrimp trawling and other fisheries ( Plotkin 1995 ) . However, Crouse et

al. ( 1987 ) found that mortality at juvenile and subadult life stages c an have a substantial effect on

population growth, suggesting that small changes in survival at these age classes could have a measurable

impact on extinction risk. As such, the marginal change in supply probability of loggerhead sea turtles

due to the fin al rule and proposed options is unlikely to be lower than 0.01 (i.e., a 1 percent decrease in

the probability of extinction over 25 years ).

EPA specified a marginal improvement of 0.01 within Whitehead’s ( 1993 ) modeling framework to bou nd

household values for changes in extinction risk for loggerhead sea turtles as a consequence of the final

rule . Although this assessment is not based on formal quantitative analysis of extinction risk, EPA intend s

it to illustrate the range of potential benefits associated with reductions in sea turtle losses. Using the

author’s mean values for demand probability (p 2 

### ) and supply probability without the management

program (q 2 

### ) ( Table F

- 3 ), EPA calculated an annual household value of $0.37 (2011$). Estimate s were

converted to 2011 dollars using the consumer price index ( USBLS 2011 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix F: Methods for T&E Species Benefits

July 8, 2014 F

- 5 

### Table F

- 3: Variable Descriptions and Values used for EPA’s Benefits Transfer Applic ation

Variable Description Value Used in EPA’s

Application

OP Option Price

- t he amount a household would be willing to pay

under conditions of supply and demand uncertainty

. Estimated by the model

p 2 Demand Probability

- for wildlife users, demand uncertainty

occurs when it is indeterminate whether recreational use of the

wildlife resource will be pursued because of uncertain travel

costs, income, and tastes. For nonusers, demand uncertainty

depends on uncertain tastes. 0.51

q 2 a Supply Probability without the Management Program

-

probability that the resource will continue to exist in 25 years

without implementation of the management program. 0.43

r 2 Supply Probability with the Management Program

- probability

that the resource will continue to exist in 25 years with

implementation of the management program. 0.44

(r 2 - q 2 ) b Marginal increase in supply probability resulting from the

management program

. 0.01

a The model results are linear for marginal improvements in supply probability.

b EPA notes that a marginal change in supply probability of 0.01 is substantially less than changes used by Whitehead (1993) fo r model

estimation. Whitehead (1993) estimated an annual household willingness to pay value of $10.98 (1991$) for a mean increase in supply

probability of 0.47 in 25 years.

Sources: Whitehead (1993), U.S. EPA analysis for this reportBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix G: Consumer Surplus

July 8, 2014 G

- 1 

# Appendix G : Estimation of Price Changes for Consumer Surplus

G.1 Introduction

EPA considered estimating consumer surplus values associated with reductions in IM&E, but found that

dockside pric es would change too little to produce measurable shifts in consumer surplus. This Appendix

presents the details of this analysis and the estimated price changes by region and species.



## G.2 Methodology and Results

To properly estimate price changes, it is ne cessary to consider the contribution of the species to the

overall market. Because individual demand functions incorporating substitutes are not available for most

species, EPA estimated price changes in the following way. . The Agency estimated the total baseline

harvest for relevant species (commercial species of similar types to those affected by IM&E) using

National Marine Fisheries Service (NMFS) landings data from 2007 to 2011 ( NMFS 2012 ) in three

categories: finfish, shrimp, and crabs. 96

, 

### The tota ls for finfish were summed for the East Coast and Gulf,

and for the West Coast, while totals for shrimp and crabs were summed across all coastal regions. 97 

### EPA

summed estimated harvest increases from the elimination of baseline IM&E according to the same

sp ecies and regional categories. Next, EPA calculated the percentage change in harvest if baseline IM&E

were to be eliminated, by dividing the total increase in harvest from elimination of baseline IM&E, by the

total harvest. EPA then estimated the percentag e change in price for each region and species by dividing

the percentage change in harvest by the elasticity for the species group (finfish, shrimp, or crabs).

This last step requires estimates of elasticities. The price elasticity of demand for fish meas ures the

percentage change in demand in response to a percentage change in fish price. Thus, the inverse elasticity,

or price flexibility, measures the percentage change in price for a given percentage change in quantity.

E PA’s review of the economics literature identified several potentially relevant studies, including Asche,

Bjorndal , and Gordon ( 2005 ) ; Capps and Lambrgets ( 1991 ) ; Cheng and Capps ( 19 88 ) ; Tsoa, Schrank , and

Roy ( 1982 ) ; Davis, Yen , and Hwan

- Lin ( 2007 ) ; and Lin, Richards

, and Terry ( 1988 )

.

Table G

- 1 presents the own

- price elasticities identified in the literature review for those commercial

s pecies where IM&E was estimated. Because elasticities can vary by species, the Agency grouped the

own

- price elasticities found in the literature review into three categories: (1) saltwater fish, (2) shrimp,

and (3) crabs. The median elasticities within eac h of these groups, presented in the fourth column of

Table G

- 1 , are the elasticities used in this analysis. Table G

- 1 shows that there is a substantial amount of

variation in the elasticity estimates, so by selecting the median elasticity rather than takin g an average, the

influence of the more extreme estimates is reduced. 98

g

96 For example, offshore species such as tuna and swordfish, baitfish species, and shellfish were not included.

97 Harvests for Alaska and Hawaii were not included in the totals.

98 Only two studies were available for crabs, so EPA used the mean elasticity for crabs. The Agency did not distinguish

between finfish elasticities for the Eas t and West Coast, because some sources provide elasticities based on models that

include both regions.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix G: Consumer Surplus

July 8, 2014 G

- 2 

### Table G

- 1 : Own

- Price Elasticity Estimates from Literature Review

Species

Group Species Study

Elasticity Median Species

Group Elasticity Study Notes

Saltwater Cod

- 0.54

- 1.89 Cheng and Capps ( 1988 )

Saltwater Cod

- 3.15

- 1.89 Bell ( 1986 ) as cited in Asche,

Bjorndal and Gordon ( 2005 )

Saltwater Cod(Blocks)

- 3.16

- 1.89 Mazany, Roy and Schrank ( 1996 ) as

cited in Asche, Bjorndal and Gordon

( 2005 )

Saltwater Cod(Fillets)

- 0.46

- 1.89 Tsoa, Schrank and Roy ( 1982 ) Long run estimate.

Saltwater Cod(Fillets)

- 1.89

- 1.89 Asche, Bjorndal and Gordon ( 2005 )

Saltwater Flounder

- 1.63

- 1.89 Mazany, Roy and Schrank ( 1996 ) as

cited in Asche, Bjorndal and Gordon

( 2005 )

Saltwater Flounder/Sole

- 0.45

- 1.89 Cheng and Capps ( 1988 )

Saltwater Flounder/Sole

- 1.04

- 1.89 Tsoa, Schrank and Roy ( 1982 ) Long run estimate.

Saltwater Halibut

- 5.56

- 1.89 Lin, Richards and Terry ( 1988 ) as

cited in Asche, Bjorndal and Gordon

( 2005 )

Saltwater Perch

- 0.70

- 1.89 Cheng and Capps ( 1988 )

Saltwater Perch

- 3.09

- 1.89 Capps and Lambrgets ( 1991 )

Saltwater Perch

- 0.60

- 1.89 Tsoa, Schrank and Roy ( 1982 ) Long run estimate.

Saltwater Perch

- 215.00

- 1.89 Bell ( 1986 ) as cited in Asche,

Bjorndal and Gordon ( 2005 )

Saltwater Rockfish

- 3.55

- 1.89 Capps and Lambrgets ( 1991 )

Saltwater Whitefish

- 5.24

- 1.89 Capps and Lambrgets ( 1991 )

Shrimp Shrimp

- 0.70

- 0.63 Cheng and Capps ( 1988 )

Shrimp Shrimp

- 1.08

- 0.63 Davis, Yen and Hwan

- Lin ( 2007 ) Low income estimate.

Shrimp Shrimp

- 0.30

- 0.63 Davis, Yen and Hwan

- Lin ( 2007 ) High income estimate.

Shrimp Shrimp

- 2.84

- 0.63 Capps and Lambrgets ( 1991 )

Shrimp Shrimp

- 0.63

- 0.63 Doll ( 1972 ) as cited in Cheng and

Capps ( 1988 )

Shrimp Shrimp 0.28

- 0.63 Cleary ( 1969 ) as cited in Cheng and

Capps ( 1988 )

Shrimp Shrimp

- 0.57

- 0.63 Sun ( 1995 ) as cited in Asche,

Bjorndal and Gordon ( 2005 )

Crabs Crabs

- 0.77

- 1.31 Cheng and Capps ( 1988 )

Crabs Crabs

- 1.84

- 1.31 Capps and Lambrgets ( 1991 )



### Table G

- 2 shows the results of the calculations of percentage changes in price. EPA applied these

percentage changes to the baseline prices to develop estimates of prices for the increased harvests that

would result from eliminating baseline IM&E. For example, the table shows that a 0.39 percent change in

total harvest in California is predicted to lead to a 0.21 percent change in finfish prices. These prices

changes translate into very small changes (generally one to two cents) in ex

- vessel prices per pound for

the species affected by IM&E. Tables G

- 3 to G

- 7 show the projected prices after eliminating baseline

IM&E.

EPA did not include estimates of changes in consumer surplus for commercial species. Prices must

change in order for consumer surplus to change. Most s pecies of fish have numerous close substitutes

. The literature suggests that when there are plentiful substitute fish products, lots of fishers, and a strong

ex

- vessel market, individ ual fishers are generally price takers

. Although there are exceptions, fi sheries

economics studies often make these assumptions in analyzing regional effects from harvest changes (e.g.,

Her r mann 1996 ; Thunberg et al. 1995 ) and international markets ( e.g., Clarke et al. 1992 )

. ConsumerBenefits Analysis for the Final 316(b) Existing Facilities Rule Appendix G: Consumer Surplus

July 8, 2014 G

- 3 

### surplus measures that have been estimated by NMFS for past environmental impact statements tend to be

quite low. NMFS fisheries analyses incorporate price changes for large changes in regional or national

h arvest, such as stock rebuilding. However, for small changes in landings, such as those expected under

the final rule, it is standard to assume that prices are fixed. 99



### Table G

- 2: Estimated Average Percentage Change in Ex

- Vessel Price by Region and

Specie s Group from the Elimination of Baseline IM&E

Region Species

Group Increase in Harvest

from Elimination of

Baseline IM&E a

(lbs) Total Average

Annual Harvest a Percentage

Change in

Harvest Elasticity Percentage

Change in

Price b

California Finfish 1,920,625 489,705,990 0.39%

- 1.89

- 0.21%

East Coast

and Gulf Finfish 12,548,060 265,617,830 4.72%

- 1.89

- 2.50%

All Regions Crabs 1,373,553 258,973,619 0.53%

- 1.31

- 0.40%

All Regions Shrimp 369,750 279,365,691 0.13%

- 0.63

- 0.21%

a Sum of total landings for all relevant species.

b Percentage changes in price reflect the average across all species within the species group and region.

Sources: U.S. EPA analysis for this report, NMFS (2012a)



### Table G

- 3: Estimated Price Changes for the California Region

Species Average Annual

Harvest 2007

- 2011 (thousand

lbs) Price Per

Pound

(2011$) Increase in Harvest

from Elimination of

Baseline IM&E

(thousand lbs) a Percentage

Change in

Price New Price

Per Pound

(2011$)

American Shad 57.9 $1.07 0.0

- 0.21% $1.07

Anchovies 13,637.3 $0.06 0.9

- 0.21% $0.06

Cabezon 53.7 $5.89 76.1

- 0.21% $5.88

California Halibut 495.5 $4.73 176.9

- 0.21% $4.72

California Scorpionfish 7.9 $3.83 0.0

- 0.21% $3.82

Commercial Crabs 1,386.3 $1.37 2.2

- 0.40% $1.36

Commercial Shrimp 4,272.1 $1.40 0.0

- 0.21% $1.39

Drums and Croakers 53.8 $0.56 6.9

- 0.21% $0.55

Dungeness Crabs 15,495.5 $2.31 6.1

- 0.40% $2.30

Flounders 381.3 $0.42 14.2

- 0.21% $0.42

Other 47,410.9 $1.16 6.6

- 0.21% $1.16

Rockfishes 2,741.3 $1.25 1,634.5

- 0.21% $1.25

Sculpins 3.8 $3.53 3.7

- 0.21% $3.52

Sea Basses 6.4 $2.76 0.0

- 0.21% $2.75

Smelts 323.0 $0.41 0.2

- 0.21% $0.41

Surfperches 17.5 $1.90 0.7

- 0.21% $1.90

Total 86,344.2

. 1,928.9

. .

a Values of 0.0 for increased harvest from elimination of baseline IM&E may include increases less than 0.1 thousand lbs.

Sources: U.S. EPA analysis for this report, NMFS (2012c)

99 Personal communications with NMFS economists Cindy Thomson ( 2008 ) , Eric Thunberg ( 2008 ) , Steve Freese ( 2008 ) , and

Sabrina Lovell ( 2013 )

.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix G: Consumer Surplus

July 8, 2014 G

- 4 

### Table G

- 4: Estimated Price Changes for the North Atlantic Region

Species Average Annual

Harvest 2007

- 2011 (thousand

lbs) Price Per

Pound

(2011$) Increase in Harvest

from Elimination of

Baseline IM&E

(thousand lbs) a Percentage

Change in

Price New Price

Per Pound

(2011$)

American Shad 30.3 $0.86 0.0

- 2.50% $0.84

Atlantic Cod 18,152.5 $1.64 2.3

- 2.50% $1.60

Atlantic Herring 168,023.6 $0.13 17.4

- 2.50% $0.13

Atlantic Menhaden 7,346.1 $0.12 4.8

- 2.50% $0.12

Bluefish 1,038.3 $0.57 0.0

- 2.50% $0.56

Butterfish 784.5 $0.68 0.2

- 2.50% $0.66

Commercial Crabs 16,083.4 $0.62 0.3

- 2.50% $0.61

Flounders 16,026.1 $1.95 373.1

- 2.50% $1.91

Mackerels 29,268.6 $0.17 2.2

- 0.40% $0.16

Other 332,156.1 $0.42 3.8

- 2.50% $0.41

Pollock 16,818.4 $0.64 0.0

- 2.50% $0.62

Red Hake 926.7 $0.39 0.0

- 2.50% $0.38

Sculpins 1.0 $0.11 3.2

- 2.50% $0.11

Scup 5,362.2 $0.75 0.1

- 2.50% $0.73

Searobin 53.3 $0.17 0.1

- 2.50% $0.16

Silver Hake 11,108.1 $0.59 0.6

- 2.50% $0.58

Skate Species 35,198.9 $0.22 0.5

- 2.50% $0.21

Tautog 142.6 $2.43 4.7

- 2.50% $2.37

Weakfish 11.1 $1.67 0.2

- 2.50% $1.63

White Perch 4.8 $1.20 0.0

- 2.50% $1.17

Total 658,536.4

. 413.6

. .

a Values of 0.0 for increased harvest from elimination of baseline IM&E may include increases less than 0.1 thousand lbs.

Sources: U.S. EPA analysis for this report, NMFS (2012c)Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix G: Consumer Surplus

July 8, 2014 G

- 5 

### Table G

- 5: Estimated Price Changes for the Mid

- Atlantic Region

Species Average Annual

Harvest 2007

- 2011 (thousand

lbs) Price Per

Pound

(2011$) Increase in Harvest

from Elimination of

Baseline IM&E

(thousand lbs) a Percentage

Change in

Price New Price

Per Pound

(2011$)

Alewife 343.8 $0.29 0.3

- 2.50% $0.28

American Shad 57.5 $0.83 0.9

- 2.50% $0.81

Atlantic Herring 6,658.6 $0.12 0.1

- 2.50% $0.11

Atlantic Menhaden 452,353.9 $0.07 3,700.8

- 2.50% $0.07

Black Drum 89.8 $2.20 0.2

- 2.50% $2.14

Blue Crab 85,836.4 $1.11 640.9

- 0.40% $1.10

Bluefish 2,996.3 $0.49 0.1

- 2.50% $0.48

Butterfish 494.1 $0.84 0.0

- 2.50% $0.82

Commercial Crabs 2,490.9 $0.54 0.3

- 0.40% $0.54

Drums and Croakers 10,159.5 $0.64 960.3

- 2.50% $0.63

Flounders 6,308.5 $2.08 6.1

- 2.50% $2.03

Other 602,868.9 $0.31 820.1

- 2.50% $0.30

Red Hake 360.0 $0.46 0.6

- 2.50% $0.44

Scup 4,121.8 $0.81 0.0

- 2.50% $0.79

Searobin 37.3 $0.21 0.0

- 2.50% $0.21

Silver Hake 4,877.3 $0.64 0.1

- 2.50% $0.63

Spot 3,478.4 $0.85 1,064.6

- 2.50% $0.82

Striped Bass 5,609.6 $2.12 55.9

- 2.50% $2.07

Striped Mullet 26.2 $0.45 0.2

- 2.50% $0.44

Tautog 135.3 $2.98 0.0

- 2.50% $2.90

Weakfish 267.4 $1.32 503.7

- 2.50% $1.29

White Perch 1,588.5 $0.79 2.6

- 2.50% $0.77

Total 1,191,159.9

. 7,757.9

. .

a Values of 0.0 for increased harvest from elimination of baseline IM&E may include increases less than 0.1 thousand lbs.

Sources: U.S. EPA analysis for this report, NMFS (2012c)



### Table G

- 6: Estimated Price Changes for the South Atlantic Region

Species Average Annual

Harvest 2007

- 2011 (thousand

lbs) Price Per

Pound

(2011$) Increase in Harvest

from Elimination of

Baseline IM&E

(thousand lbs) a Percentage

Change in

Price New Price

Per Pound

(2011$)

Atlantic Menhaden 1,828.1 $0.12 42.9

- 2.50% $0.11

Blue Crab 39,786.5 $0.95 3.2

- 0.40% $0.95

Commercial Crabs 583.7 $1.65 0.0

- 0.40% $1.65

Drums and Croakers 6,347.6 $0.51 12.5

- 2.50% $0.50

Other 94,277.5 $1.28 2.3

- 2.50% $1.25

Spot 854.3 $0.70 16.1

- 2.50% $0.68

Stone Crab 145.2 $4.01 0.4

- 0.40% $3.99

Weakfish 144.6 $1.02 0.6

- 2.50% $0.99

Total 143,967.5

. 78.1

. .

a Values of 0.0 for increased harvest from elimination of baseline IM&E may include increases less than 0.1 thousand lbs.

Sources: U.S. EPA analysis for this report, NMFS (2012c)Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix G: Consumer Surplus

July 8, 2014 G

- 6 

### Table G

- 7: Estimated Price Changes for the Gulf of Mexico Region

Species Average Annual

Harvest 2007

- 2011 (thousand

lbs) Price Per

Pound

(2011$) Increase in Harvest

from Elimination of

Baseline IM&E

(thousand lbs) a Percentage

Change in

Price New Price

Per Pound

(2011$)

Atlantic Menhaden 1,088,022.8 $0.07 1,173.2

- 2.50% $0.07

Black Drum 4,621.9 $0.83 1,945.0

- 2.50% $0.81

Blue Crab 53,055.9 $0.87 244.0

- 0.40% $0.87

Drums and Croakers 111.8 $5.19 47.8

- 2.50% $5.06

Leatherjacket 61.0 $1.51 107.1

- 2.50% $1.47

Mackerels 3,898.1 $1.16 0.4

- 2.50% $1.13

Other 1,384,185.9 $0.39 281.9

- 2.50% $0.38

Pink Shrimp 6,973.0 $2.00 369.7

- 0.21% $2.00

Sea Basses 179.4 $0.97 0.0

- 2.50% $0.95

Sheepshead 1,393.0 $0.44 0.0

- 2.50% $0.43

Spot 16.9 $0.51 46.3

- 2.50% $0.50

Stone Crab 5,587.9 $4.13 474.4

- 0.40% $4.11

Striped Mullet 10,800.3 $0.64 1,343.6

- 2.50% $0.62

Total 2,558,908.0

. 6,033.5

. .

a Values of 0.0 for increased harvest from elimination of baseline IM&E may include increases less than 0.1 thousand lbs.

Sources: U.S. EPA analysis for this report, NMFS (2012c)Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix H: Details of Commercial Fishing Benefits

July 8, 2014 H

- 1 

# Appendix H: Details of Regional Commercial Fishing Benefits

Table H

- 1: Commercial Fishing Benefits from Eliminating or Reducing Baseline IM&E at Regulated Facilities in the

California Region, by Species and Regulatory Option (2011$)

Species Name Average

Annual

Harvest

2007

- 2011

(1,000 lbs) Price

per

Pound Annual Increase in Commercial Harvest

(1,000 lbs) Annual Benefits from Increase in

Commercial Harvest

(2011$, 1,000s)

Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline

American Shad 57.9 $1.07 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Anchovies 13,637.3 $0.06 0.5 0.5 0.6 0.9 0.0 0.0 0.0 0.0

Cabezon 53.7 $5.89 0.1 0.1 46.4 76.1 0.2 0.3 143.6 235.4

California Halibut 495.5 $4.73 0.2 0.2 107.9 176.9 0.6 0.7 297.2 487.1

California Scorpionfish 7.9 $3.83 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1

Commercial Crabs 1,386.3 $1.37 0.0 0.0 1.3 2.2 0.0 0.0 1.4 2.2

Commercial Shrimp 4,272.1 $1.40 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Drums and Croakers 53.8 $0.56 0.7 0.8 4.3 6.9 0.2 0.2 1.0 1.6

Dungeness Crabs 15,495.5 $2.31 0.4 0.4 3.8 6.1 0.6 0.7 6.4 10.3

Flounders 381.3 $0.42 0.9 0.9 8.7 14.2 0.2 0.2 2.3 3.8

Other 47,410.9 $1.16 0.6 0.7 4.1 6.6 0.4 0.4 2.5 4.0

Rockfishes 2,741.3 $1.25 2.5 2.7 997.3 1,634.5 2.0 2.1 775.9 1,271.7

Sculpins 3.8 $3.53 0.1 0.1 2.2 3.7 0.2 0.2 5.1 8.3

Sea Basses 6.4 $2.76 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Smelts 323.0 $0.41 0.1 0.1 0.1 0.2 0.0 0.0 0.0 0.1

Surfperches 17.5 $1.90 0.4 0.5 0.5 0.7 0.3 0.3 0.4 0.5

Total (U ndiscounted) 86,344.2

. 6.5 7.0 1,177.4 1,928.9 4.8 5.2 1,235.8 2,025.1

Total (3% Discount Rate)

. . . . . . 3.0 3.3 650.8 1,698.4

Total (7% Discount Rate)

. . . . . . 2.2 2.4 422.5 1,518.8

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix H: Details of Commercial Fishing Benefits

July 8, 2014 H

- 2



### Table H

- 2: Commercial Fishing Benefits from Eliminating or Reducing Baseline IM&E at Regulated Facilities in the

North Atlantic Region, by Species and Regulatory Option (2011$)

Species Name Average

Annual

Harvest

2007

- 2011

(1,000 lbs) Price

per

Pound Annual Increase in Commercial Harvest

(1,000 lbs) Annual Benefits from Increase in

Commercial Harvest

(2011$, 1,000s)

Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline

American Shad 30.3 $0.86 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Atlantic Cod 18,152.5 $1.64 0.1 0.1 1.8 2.3 0.1 0.1 2.0 2.5

Atlantic Herring 168,023.6 $0.13 0.4 0.5 13.4 17.4 0.0 0.1 1.4 1.8

Atlantic Menhaden 7,346.1 $0.12 0.0 0.1 3.7 4.8 0.0 0.0 0.3 0.4

Bluefish 1,038.3 $0.57 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Butterfish 784.5 $0.68 0.1 0.1 0.2 0.2 0.0 0.0 0.1 0.1

Commercial Crabs 16,083.4 $0.62 0.2 0.2 0.3 0.3 0.1 0.1 0.1 0.1

Flounders 16,026.1 $1.95 1.2 4.6 286.0 373.1 1.5 5.7 355.5 463.8

Mackerels 29,268.6 $0.17 0.0 0.0 1.7 2.2 0.0 0.0 0.2 0.3

Other 332,156.1 $0.42 0.2 0.2 2.9 3.8 0.0 0.1 0.7 0.9

Pollock 16,818.4 $0.64 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Red Hake 926.7 $0.39 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Sculpins 1.0 $0.11 0.0 0.2 3.2 3.2 0.0 0.0 0.0 0.0

Scup 5,362.2 $0.75 0.0 0.0 0.1 0.1 0.0 0.0 0.1 0.1

Searobin 53.3 $0.17 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.0

Silver Hake 11,108.1 $0.59 0.1 0.1 0.5 0.6 0.0 0.1 0.2 0.2

Skate Species 35,198.9 $0.22 0.3 0.3 0.5 0.5 0.0 0.1 0.1 0.1

Tautog 142.6 $2.43 0.0 0.0 3.6 4.7 0.0 0.1 4.0 5.2

Weakfish 11.1 $1.67 0.0 0.0 0.2 0.2 0.0 0.0 0.2 0.3

White Perch 4.8 $1.20 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Total (U ndiscounted) 658,536.4

. 2.7 6.7 318.0 413.6 1.9 6.2 364.7 475.8

Total (3% Discount Rate)

. . . . . . 1.2 4.0 202.3 399.0

Total (7% Discount Rate)

. . . . . . 0.9 3.0 135.9 356.8

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix H: Details of Commercial Fishing Benefits

July 8, 2014 H

- 3



### Table H

- 3: Commercial Fishing Benefits from Eliminating or Reducing Baseline IM&E at Regulated Facilities in the Mid

Atlantic Region, by Species and Regulatory Option (2011$)

Species Name Average

Annual

Harvest

2007

- 2011

(1,000 lbs) Price

per

Pound Annual Increase in Commercial Harvest

(1,000 lbs) Annual Benefits from Increase in

Commercial Harvest

(2011$, 1,000s)

Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline

Alewife 343.8 $0.29 0.2 0.2 0.3 0.3 0.1 0.1 0.1 0.1

American Shad 57.5 $0.83 0.0 0.0 0.8 0.9 0.0 0.0 0.6 0.6

Atlantic Herring 6,658.6 $0.12 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0

Atlantic Menhaden 452,353.9 $0.07 2,503.2 2,674.8 3,398.8 3,700.8 126.4 135.0 171.6 186.8

Black Drum 89.8 $2.20 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.4

Blue Crab 85,836.4 $1.11 8.8 9.8 559.0 640.9 5.6 6.2 354.4 406.3

Bluefish 2,996.3 $0.49 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0

Butterfish 494.1 $0.84 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Commercial Crabs 2,490.9 $0.54 0.2 0.2 0.3 0.3 0.1 0.1 0.1 0.1

Drums and Croakers 10,159.5 $0.64 14.1 15.7 837.7 960.3 6.7 7.5 398.8 457.1

Flounders 6,308.5 $2.08 2.6 2.8 5.5 6.1 3.6 3.8 7.8 8.6

Other 602,868.9 $0.31 98.1 105.3 721.4 820.1 21.9 23.5 160.7 182.7

Red Hake 360.0 $0.46 0.5 0.5 0.6 0.6 0.1 0.1 0.2 0.2

Scup 4,121.8 $0.81 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Searobin 37.3 $0.21 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Silver Hake 4,877.3 $0.64 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0

Spot 3,478.4 $0.85 93.6 100.8 1,064.6 1,064.6 66.5 71.7 756.9 756.9

Striped Bass 5,609.6 $2.12 0.4 0.5 48.7 55.9 0.6 0.7 68.8 78.9

Striped Mullet 26.2 $0.45 0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1

Tautog 135.3 $2.98 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Weakfish 267.4 $1.32 150.4 160.9 449.3 503.7 150.9 161.4 450.8 505.3

White Perch 1,588.5 $0.79 0.2 0.3 2.2 2.6 0.2 0.2 1.5 1.7

Total (U ndiscounted) 1,191,159.9

. 2,872.9 3,072.5 7,090.1 7,757.9 382.9 410.7 2,372.6 2,586.0

Total (3% Discount Rate)

. . . . . . 242.1 259.7 1,206.2 2,168.8

Total (7% Discount Rate)

. . . . . . 177.1 190.1 769.7 1,939.4

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix H: Details of Commercial Fishing Benefits

July 8, 2014 H

- 4



### Table H

- 4: Commercial Fishing Benefits from Eliminating or Reducing Baseline IM&E at Regulated Facilities in the

South Atlantic Region, by Species and Regulatory Option (2011$)

Species Name Average

Annual

Harvest

2007

- 2011

(1,000 lbs) Price

per

Pound Annual Increase in Commercial Harvest

(1,000 lbs) Annual Benefits from Increase in

Commercial Harvest

(2011$, 1,000s)

Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline

Atlantic Menhaden 1,828.1 $0.12 25.7 27.5 42.2 42.9 2.2 2.4 3.7 3.8

Blue Crab 39,786.5 $0.95 2.2 2.3 3.2 3.2 1.2 1.3 1.7 1.7

Commercial Crabs 583.7 $1.65 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Drums and Croakers 6,347.6 $0.51 0.2 0.2 11.7 12.5 0.1 0.2 3.2 3.4

Other 94,277.5 $1.28 1.3 1.3 2.3 2.3 1.0 1.0 1.7 1.8

Spot 854.3 $0.70 7.0 7.5 15.6 16.1 3.4 3.8 7.6 7.9

Stone Crab 145.2 $4.01 0.3 0.3 0.4 0.4 0.6 0.7 0.9 1.0

Weakfish 144.6 $1.02 0.3 0.3 0.6 0.6 0.2 0.2 0.4 0.4

Total (U ndiscounted) 143,967.5

. 36.9 39.6 76.0 78.1 8.7 9.7 19.3 19.9

Total (3% Discount Rate)

. . . . . . 5.8 6.4 10.4 16.7

Total (7% Discount Rate)

. . . . . . 4.4 4.9 7.0 14.9

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix H: Details of Commercial Fishing Benefits

July 8, 2014 H

- 5



### Table H

- 5: Commercial Fishing Benefits from Eliminating or Reducing Baseline IM&E at Regulated Facilities in the Gulf

of Mexico Region, by Species and Regulatory Option (2011$)

Species Name Average

Annual

Harvest

2007

- 2011

(1,000 lbs) Price

per

Pound Annual Increase in Commercial Harvest

(1,000 lbs) Annual Benefits from Increase in

Commercial Harvest

(2011$, 1,000s)

Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline

Atlantic Menhaden 1,088,022.8 $0.07 841.3 873.2 1,053.6 1,173.2 44.7 46.3 55.9 62.3

Black Drum 4,621.9 $0.83 5.1 5.2 1,150.0 1,945.0 2.9 3.0 662.9 1,121.1

Blue Crab 53,055.9 $0.87 45.3 47.0 163.4 244.0 28.1 29.2 101.6 151.7

Drums and Croakers 111.8 $5.19 34.6 35.9 43.1 47.8 97.0 100.7 120.8 134.2

Leatherjacket 61.0 $1.51 74.3 77.2 95.1 107.1 0.0 0.0 0.0 0.0

Mackerels 3,898.1 $1.16 0.3 0.3 0.3 0.4 0.2 0.2 0.3 0.3

Other 1,384,185.9 $0.39 185.1 192.1 245.8 281.9 33.6 34.9 44.6 51.2

Pink Shrimp 6,973.0 $2.00 173.5 180.1 292.7 369.7 150.7 156.4 254.2 321.1

Sea Basses 179.4 $0.97 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Sheepshead 1,393.0 $0.44 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Spot 16.9 $0.51 27.8 28.9 39.3 46.3 7.7 7.9 10.8 12.7

Stone Crab 5,587.9 $4.13 117.2 121.6 330.2 474.4 344.9 358.0 972.0 1,396.2

Striped Mullet 10,800.3 $0.64 137.3 142.5 851.9 1,343.6 69.0 71.6 428.1 675.3

Total (U ndiscounted) 2,558,908.0

. 1,641.8 1,704.0 4,265.5 6,033.5 778.9 808.3 2,651.3 3,926.1

Total (3% Discount Rate)

. . . . . . 496.8 515.5 1,702.5 3,426.9

Total (7% Discount Rate)

. . . . . . 365.2 378.9 1,255.7 3,160.8

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix H: Details of Commercial Fishing Benefits

July 8, 2014 H

- 6



### Table H

- 6: Commercial Fishing Benefits from Eliminating or Reducing Baseline IM&E at Regulated Facilities in the

Great Lakes Region, by Species and Regulatory Option (2011$)

Species Name Average

Annual

Harvest

2007

- 2011

(1,000 lbs) Price

per

Pound Annual Increase in Commercial Harvest

(1,000 lbs) Annual Benefits from Increase in

Commercial Harvest

(2011$, 1,000s)

Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline Proposal

Option 4 Final

Rule Proposal

Option 2 Baseline

Bullhead 679.1 $0.40 17.9 19.7 22.8 23.5 2.1 2.3 2.6 2.7

Freshwater Drum 585.9 $0.18 73.8 81.4 203.3 209.1 3.9 4.3 10.8 11.2

Other 14,356.7 $1.03 320.0 352.2 451.4 481.3 95.8 105.5 135.2 144.1

Sculpins 14,356.7 $1.03 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.0

Smelts 380.5 $1.60 61.3 67.5 87.0 92.9 28.4 31.3 40.4 43.1

White Bass 523.6 $0.73 248.1 248.1 248.1 248.1 52.6 52.6 52.6 52.6

Whitefish 9,785.3 $0.99 59.4 65.4 74.5 76.4 17.1 18.8 21.4 22.0

Yellow Perch 1,543.6 $2.14 3.8 4.1 5.2 5.5 2.3 2.6 3.2 3.4

Total (U ndiscounted) 42,211.3

. 784.2 838.5 1,092.4 1,136.9 202.2 217.3 266.2 279.0

Total (3% Discount Rate)

. . . . . . 134.6 144.9 162.5 243.6

Total (7% Discount Rate)

. . . . . . 101.9 109.8 116.2 224.6

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 1 

# Appendix I: Details of Regional Recreational Fishing Benefits

I.1 California Region

Table I

- 1: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 4 in the California Region, by Sp ecies (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

California halibut 69.0 $5.35 $10.21 $19.49 0.0 0.8 1.5

Flounders 21.0 $5.35 $10.21 $19.49 0.0 0.2 0.5

Total (Flatfish) 90.0 $5.35 $10.21 $19.49 0.0 1.0 2.0

Striped bass 0.0 $4.40 $7.60 $13.01 0.0 0.0 0.0

Total (Small Game) 0.0 $4.40 $7.60 $13.01 0.0 0.0 0.0

Cabezon 10.0 $1.87 $3.09 $5.11 0.0 0.0 0.1

California scorpionfish 49.0 $1.87 $3.09 $5.11 0.1 0.2 0.3

Croakers 4,564.0 $1.87 $3.09 $5.11 8.5 14.1 23.4

Rockfish 618.0 $1.87 $3.09 $5.11 1.2 1.9 3.2

Sculpin 3,192.0 $1.87 $3.09 $5.11 5.9 9.8 16.3

Sea bass 276.0 $1.87 $3.09 $5.11 0.5 0.9 1.4

Smelts 16.0 $1.87 $3.09 $5.11 0.0 0.0 0.1

Sunfish 1.0 $1.87 $3.09 $5.11 0.0 0.0 0.0

Surfperch 25,654.0 $1.87 $3.09 $5.11 47.8 79.1 131.3

Total (Other Saltwater) 34,381.0 $1.87 $3.09 $5.11 64.0 106.0 176.0

Total (Unidentified) 949.0 $1.95 $3.25 $5.42 2.0 3.0 5.0

Total (Undiscounted) 35,420.0

. . . 67.0 110.0 183.0

Total (3% discount rate)

. . . . 42.0 69.0 114.0

Total (7% discount rate)

. . . . 30.0 50.0 83.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 2 

### Table I

- 2: Recreational Fishing Benefits from Reducing at Regulated Facilities under

the Final Rule in the California Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

California halibut 74.0 $5.35 $10.21 $19.49 0.8 0.8 1.5

Flounders 23.0 $5.35 $10.21 $19.49 0.2 0.2 0.5

Total (Flatfish) 97.0 $5.35 $10.21 $19.49 1.0 1.0 2.0

Striped bass 0.0 $4.40 $7.60 $13.01 0.0 0.0 0.0

Total (Small Game) 0.0 $4.40 $7.60 $13.01 0.0 0.0 0.0

Cabezon 11.0 $1.87 $3.09 $5.11 0.0 0.0 0.1

California scorpionfish 53.0 $1.87 $3.09 $5.11 0.1 0.2 0.3

Croakers 4,917.0 $1.87 $3.09 $5.11 9.2 15.3 25.1

Rockfish 665.0 $1.87 $3.09 $5.11 1.2 2.1 3.4

Sculpin 3,439.0 $1.87 $3.09 $5.11 6.4 10.7 17.5

Sea bass 297.0 $1.87 $3.09 $5.11 0.6 0.9 1.5

Smelts 18.0 $1.87 $3.09 $5.11 0.0 0.1 0.1

Sunfish 1.0 $1.87 $3.09 $5.11 0.0 0.0 0.0

Surfperch 27,638.0 $1.87 $3.09 $5.11 51.5 85.8 141.0

Total (Other Saltwater) 37,040.0 $1.87 $3.09 $5.11 69.0 115.0 189.0

Total (Unidentified) 1,022.0 $1.95 $3.25 $5.42 2.0 3.0 6.0

Total (Undiscounted) 38,159.0

. . . 72.0 119.0 197.0

Total (3% discount rate)

. . . . 45.0 74.0 123.0

Total (7% discount rate)

. . . . 33.0 54.0 89.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 3 

### Table I

- 3: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 2 in the California Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

California halibut 32,791.0 $5.35 $10.21 $19.49 175.9 334.8 638.9

Flounders 213.0 $5.35 $10.21 $19.49 1.1 2.2 4.1

Total (Flatfish) 33,004.0 $5.35 $10.21 $19.49 177.0 337.0 643.0

Striped bass 1,032.0 $4.40 $7.60 $13.01 5.0 8.0 13.0

Total (Small Game) 1,032.0 $4.40 $7.60 $13.01 5.0 8.0 13.0

Cabezon 6,110.0 $1.87 $3.09 $5.11 11.4 18.9 31.3

California scorpionfish 56.0 $1.87 $3.09 $5.11 0.1 0.2 0.3

Croakers 28,043.0 $1.87 $3.09 $5.11 52.5 86.8 143.4

Rockfish 243,212.0 $1.87 $3.09 $5.11 455.2 752.6 1,244.0

Sculpin 95,822.0 $1.87 $3.09 $5.11 179.3 296.5 490.1

Sea bass 437,354.0 $1.87 $3.09 $5.11 818.6 1,353.3 2,237.0

Smelts 20.0 $1.87 $3.09 $5.11 0.0 0.1 0.1

Sunfish 12.0 $1.87 $3.09 $5.11 0.0 0.0 0.1

Surfperch 29,282.0 $1.87 $3.09 $5.11 54.8 90.6 149.8

Total (Other Saltwater) 839,911.0 $1.87 $3.09 $5.11 1,572.0 2,599.0 4,296.0

Total (Unidentified) 3,227.0 $1.95 $3.25 $5.42 6.0 10.0 17.0

Total (Undiscounted) 877,174.0

. . . 1,759.0 2,954.0 4,970.0

Total (3% discount rate)

. . . . 919.0 1,543.0 2,595.0

Total (7% discount rate)

. . . . 592.0 994.0 1,673.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 4 

### Table I

- 4: Recreational Fishing Benefits from Eliminating Baseline IM&E at Regulated

Facilities in the California Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

California halibut 53,746.0 $5.35 $10.21 $19.49 287.2 548.5 1,047.3

Flounders 345.0 $5.35 $10.21 $19.49 1.8 3.5 6.7

Total (Flatfish) 54,091.0 $5.35 $10.21 $19.49 289.0 552.0 1,054.0

Striped bass 1,692.0 $4.40 $7.60 $13.01 7.0 13.0 22.0

Total (Small Game) 1,692.0 $4.40 $7.60 $13.01 7.0 13.0 22.0

Cabezon 10,015.0 $1.87 $3.09 $5.11 18.7 31.0 51.2

California scorpionfish 82.0 $1.87 $3.09 $5.11 0.2 0.3 0.4

Croakers 45,086.0 $1.87 $3.09 $5.11 84.4 139.5 230.6

Rockfish 398,609.0 $1.87 $3.09 $5.11 745.9 1,233.4 2,038.6

Sculpin 156,471.0 $1.87 $3.09 $5.11 292.8 484.2 800.2

Sea bass 716,959.0 $1.87 $3.09 $5.11 1,341.5 2,218.5 3,666.7

Smelts 30.0 $1.87 $3.09 $5.11 0.1 0.1 0.2

Sunfish 19.0 $1.87 $3.09 $5.11 0.0 0.1 0.1

Surfperch 43,011.0 $1.87 $3.09 $5.11 80.5 133.1 220.0

Total (Other Saltwater) 1,370,282.0 $1.87 $3.09 $5.11 2,564.0 4,240.0 7,008.0

Total (Unidentified) 5,106.0 $1.95 $3.25 $5.42 10.0 17.0 28.0

Total (Undiscounted) 1,431,170.0

. . . 2,871.0 4,822.0 8,112.0

Total (3% discount rate)

. . . . 2,408.0 4,044.0 6,803.0

Total (7% discount rate)

. . . . 2,153.0 3,616.0 6,084.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 5 

## I.2 North Atlantic Region

Table I

- 5: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 4 in the North Atlantic Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Winter flounder 765.0 $3.98 $6.24 $9.86 3.0 5.0 8.0

Total (flatfish) 765.0 $3.98 $6.24 $9.86 3.0 5.0 8.0

Atlantic mackerel 0.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Bluefish 1.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Striped bass 0.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Weakfish 0.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Total (small game) 1.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Atlantic Cod 37.0 $1.87 $3.12 $5.20 0.1 0.1 0.2

Cunner 18.0 $1.87 $3.12 $5.20 0.0 0.0 0.1

Pollock 1.0 $1.87 $3.12 $5.20 0.0 0.0 0.0

Sculpin 316.0 $1.87 $3.12 $5.20 0.7 0.7 1.4

Scup 8.0 $1.87 $3.12 $5.20 0.0 0.0 0.0

Searobin 41.0 $1.87 $3.12 $5.20 0.1 0.1 0.2

Tautog 15.0 $1.87 $3.12 $5.20 0.0 0.0 0.1

White Perch 0.0 $1.87 $3.12 $5.20 0.0 0.0 0.0

Total (other saltwater) 436.0 $1.87 $3.12 $5.20 1.0 1.0 2.0

Total (unidentified) 166.0 $1.88 $3.15 $5.26 0.0 1.0 1.0

Total (Undiscounted) 1,367.0

. . . 4.0 7.0 11.0

Total (3% discount rate)

. . . . 3.0 4.0 7.0

Total (7% discount rate)

. . . . 2.0 3.0 5.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 6 

### Table I

- 6: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under the Final Rule in the North Atlantic Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Winter flounder 3,471.0 $3.98 $6.24 $9.86 14.0 22.0 34.0

Total (flatfish) 3,471.0 $3.98 $6.24 $9.86 14.0 22.0 34.0

Atlantic mackerel 8.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Bluefish 1.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Striped bass 0.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Weakfish 0.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Total (small game) 9.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Atlantic Cod 50.0 $1.87 $3.12 $5.20 0.1 0.2 0.3

Cunner 941.0 $1.87 $3.12 $5.20 1.8 2.8 4.8

Pollock 1.0 $1.87 $3.12 $5.20 0.0 0.0 0.0

Sculpin 3,107.0 $1.87 $3.12 $5.20 5.8 9.4 15.9

Scup 9.0 $1.87 $3.12 $5.20 0.0 0.0 0.0

Searobin 51.0 $1.87 $3.12 $5.20 0.1 0.2 0.3

Tautog 139.0 $1.87 $3.12 $5.20 0.3 0.4 0.7

White Perch 0.0 $1.87 $3.12 $5.20 0.0 0.0 0.0

Total (other saltwater) 4,298.0 $1.87 $3.12 $5.20 8.0 13.0 22.0

Total (unidentified) 198.0 $1.88 $3.15 $5.26 0.0 1.0 1.0

Total (Undiscounted) 7,975.0

. . . 22.0 36.0 58.0

Total (3% discount rate)

. . . . 14.0 23.0 36.0

Total (7% discount rate)

. . . . 10.0 16.0 27.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 7 

### Table I

- 7: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 2 in the North Atlantic Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Winter flounder 229,386.0 $3.98 $6.24 $9.86 914.0 1,430.0 2,261.0

Total (flatfish) 229,386.0 $3.98 $6.24 $9.86 914.0 1,430.0 2,261.0

Atlantic mackerel 666.0 $2.23 $6.22 $17.53 1.9 3.8 11.5

Bluefish 1.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Striped bass 0.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Weakfish 25.0 $2.23 $6.22 $17.53 0.1 0.1 0.4

Total (small game) 692.0 $2.23 $6.22 $17.53 2.0 4.0 12.0

Atlantic Cod 955.0 $1.87 $3.12 $5.20 1.8 3.0 5.0

Cunner 79,272.0 $1.87 $3.12 $5.20 148.2 247.3 412.3

Pollock 3.0 $1.87 $3.12 $5.20 0.0 0.0 0.0

Sculpin 238,602.0 $1.87 $3.12 $5.20 445.9 744.4 1,241.0

Scup 96.0 $1.87 $3.12 $5.20 0.2 0.3 0.5

Searobin 618.0 $1.87 $3.12 $5.20 1.2 1.9 3.2

Tautog 10,583.0 $1.87 $3.12 $5.20 19.8 33.0 55.0

White Perch 0.0 $1.87 $3.12 $5.20 0.0 0.0 0.0

Total (other saltwater) 330,130.0 $1.87 $3.12 $5.20 617.0 1,030.0 1,717.0

Total (unidentified) 2,098.0 $1.88 $3.15 $5.26 4.0 7.0 11.0

Total (Undiscounted) 562,305.0

. . . 1,537.0 2,471.0 4,001.0

Total (3% discount rate)

. . . . 852.0 1,371.0 2,219.0

Total (7% discount rate)

. . . . 573.0 921.0 1,491.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 8 

### Table I

- 8: Recreational Fishing Benefits from Eliminating Baseline IM&E at Regulated

Facilities in the North Atlantic Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Winter flounder 299,352.0 $3.98 $6.24 $9.86 1,192.0 1,867.0 2,951.0

Total (flatfish) 299,352.0 $3.98 $6.24 $9.86 1,192.0 1,867.0 2,951.0

Atlantic mackerel 870.0 $2.23 $6.22 $17.53 1.9 5.8 15.4

Bluefish 1.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Striped bass 0.0 $2.23 $6.22 $17.53 0.0 0.0 0.0

Weakfish 32.0 $2.23 $6.22 $17.53 0.1 0.2 0.6

Total (small game) 903.0 $2.23 $6.22 $17.53 2.0 6.0 16.0

Atlantic Cod 1,235.0 $1.87 $3.12 $5.20 2.3 3.9 6.4

Cunner 103,533.0 $1.87 $3.12 $5.20 193.6 323.1 538.5

Pollock 4.0 $1.87 $3.12 $5.20 0.0 0.0 0.0

Sculpin 311,537.0 $1.87 $3.12 $5.20 582.5 972.1 1,620.4

Scup 123.0 $1.87 $3.12 $5.20 0.2 0.4 0.6

Searobin 794.0 $1.87 $3.12 $5.20 1.5 2.5 4.1

Tautog 13,817.0 $1.87 $3.12 $5.20 25.8 43.1 71.9

White Perch 0.0 $1.87 $3.12 $5.20 0.0 0.0 0.0

Total (other saltwater) 431,044.0 $1.87 $3.12 $5.20 806.0 1,345.0 2,242.0

Total (unidentified) 2,686.0 $1.88 $3.15 $5.26 5.0 8.0 14.0

Total (Undiscounted) 733,985.0

. . . 2,006.0 3,226.0 5,223.0

Total (3% discount rate)

. . . . 1,682.0 2,705.0 4,380.0

Total (7% discount rate)

. . . . 1,504.0 2,419.0 3,917.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 9 

## I. 3 Mid

- Atlantic Region

Table I

- 9: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 4 in the Mid

- Atlantic Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Summer Flounder 3,096.0 $3.92 $5.88 $8.92 12.4 17.8 27.6

Winter Flounder 386.0 $3.92 $5.88 $8.92 1.6 2.2 3.4

Total (Flatfish) 3,482.0 $3.92 $5.88 $8.92 14.0 20.0 31.0

Black Crappie 2.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Bluegill 9.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Brown bullhead 604.0 $0.55 $1.11 $2.20 0.2 0.7 1.2

Bullhead 6.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Channel catfish 1,686.0 $0.55 $1.11 $2.20 0.7 2.1 3.5

Crappie 1.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Menhaden 1.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Sunfish 129.0 $0.55 $1.11 $2.20 0.1 0.2 0.3

Total (Panfish) 2,438.0 $0.55 $1.11 $2.20 1.0 3.0 5.0

Bluefish 74.0 $2.37 $6.17 $16.23 0.2 0.5 1.2

Red drum 1,555.0 $2.37 $6.17 $16.23 3.7 9.6 25.2

Spotted seatrout 1,031.0 $2.37 $6.17 $16.23 2.4 6.4 16.7

Striped bass 773.0 $2.37 $6.17 $16.23 1.8 4.8 12.6

Weakfish 93,196.0 $2.37 $6.17 $16.23 220.9 575.8 1,513.3

Total (Small Game) 96,628.0 $2.37 $6.17 $16.23 229.0 597.0 1,569.0

Atlantic croaker 16,563.0 $1.94 $3.05 $4.82 32.1 50.6 79.8

Atlantic herring 33.0 $1.94 $3.05 $4.82 0.1 0.1 0.2

Black drum 149.0 $1.94 $3.05 $4.82 0.3 0.5 0.7

Cunner 0.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Scup 1.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Searobin 4.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Silver perch 1.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Smallmouth bass 34.0 $1.94 $3.05 $4.82 0.1 0.1 0.2

Spot 248,039.0 $1.94 $3.05 $4.82 481.1 757.9 1,194.5

Striped mullet 7.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Tautog 0.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

White perch 1,972.0 $1.94 $3.05 $4.82 3.8 6.0 9.5

Whitefish 248.0 $1.94 $3.05 $4.82 0.5 0.8 1.2

Total (Other Saltwater) 267,049.0 $1.94 $3.05 $4.82 518.0 816.0 1,286.0

Total (Unidentified) 58,327.0 $2.00 $3.39 $6.00 117.0 198.0 350.0

Total (Undiscounted) 427,924.0

. . . 878.0 1,633.0 3,241.0

Total (3% discount rate)

. . . . 531.0 988.0 1,961.0

Total (7% discount rate)

. . . . 376.0 700.0 1,389.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 10 

### Table I

- 10: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under the Final Rule in the Mid

- Atlantic Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Summer Flounder 3,308.0 $3.92 $5.88 $8.92 13.3 19.5 29.3

Winter Flounder 414.0 $3.92 $5.88 $8.92 1.7 2.4 3.7

Total (Flatfish) 3,723.0 $3.92 $5.88 $8.92 15.0 22.0 33.0

Black Crappie 2.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Bluegill 10.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Brown bullhead 647.0 $0.55 $1.11 $2.20 0.2 0.7 1.5

Bullhead 7.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Channel catfish 1,801.0 $0.55 $1.11 $2.20 0.7 2.1 4.1

Crappie 1.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Menhaden 1.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Sunfish 138.0 $0.55 $1.11 $2.20 0.1 0.2 0.3

Total (Panfish) 2,607.0 $0.55 $1.11 $2.20 1.0 3.0 6.0

Bluefish 79.0 $2.37 $6.17 $16.23 0.2 0.5 1.3

Red drum 1,661.0 $2.37 $6.17 $16.23 3.9 10.3 27.0

Spotted seatrout 1,101.0 $2.37 $6.17 $16.23 2.6 6.8 17.9

Striped bass 897.0 $2.37 $6.17 $16.23 2.1 5.5 14.6

Weakfish 99,705.0 $2.37 $6.17 $16.23 236.1 615.9 1,618.3

Total (Small Game) 103,444.0 $2.37 $6.17 $16.23 245.0 639.0 1,679.0

Atlantic croaker 18,458.0 $1.94 $3.05 $4.82 35.8 56.3 88.9

Atlantic herring 35.0 $1.94 $3.05 $4.82 0.1 0.1 0.2

Black drum 159.0 $1.94 $3.05 $4.82 0.3 0.5 0.8

Cunner 0.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Scup 1.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Searobin 4.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Silver perch 1.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Smallmouth bass 36.0 $1.94 $3.05 $4.82 0.1 0.1 0.2

Spot 267,172.0 $1.94 $3.05 $4.82 518.1 815.6 1,286.5

Striped mullet 8.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Tautog 0.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

White perch 2,119.0 $1.94 $3.05 $4.82 4.1 6.5 10.2

Whitefish 265.0 $1.94 $3.05 $4.82 0.5 0.8 1.3

Total (Other Saltwater) 288,258.0 $1.94 $3.05 $4.82 559.0 880.0 1,388.0

Total (Unidentified) 62,808.0 $2.00 $3.39 $6.00 126.0 213.0 377.0

Total (Undiscounted) 460,839.0

. . . 945.0 1,757.0 3,483.0

Total (3% discount rate)

. . . . 572.0 1,063.0 2,108.0

Total (7% discount rate)

. . . . 405.0 753.0 1,493.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 11 

### Table I

- 11: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 2 in the Mid

- Atlantic Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Summer Flounder 3,781.0 $3.92 $5.88 $8.92 14.9 22.3 33.8

Winter Flounder 2,823.0 $3.92 $5.88 $8.92 11.1 16.7 25.2

Total (Flatfish) 6,604.0 $3.92 $5.88 $8.92 26.0 39.0 59.0

Black Crappie 2.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Bluegill 11.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Brown bullhead 2,281.0 $0.55 $1.11 $2.20 1.4 2.7 5.0

Bullhead 8.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Channel catfish 2,059.0 $0.55 $1.11 $2.20 1.2 2.4 4.5

Crappie 1.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Menhaden 530.0 $0.55 $1.11 $2.20 0.3 0.6 1.2

Sunfish 157.0 $0.55 $1.11 $2.20 0.1 0.2 0.3

Total (Panfish) 5,049.0 $0.55 $1.11 $2.20 3.0 6.0 11.0

Bluefish 90.0 $2.37 $6.17 $16.23 0.2 0.6 1.5

Red drum 1,899.0 $2.37 $6.17 $16.23 4.5 11.7 30.8

Spotted seatrout 1,259.0 $2.37 $6.17 $16.23 3.0 7.8 20.4

Striped bass 91,823.0 $2.37 $6.17 $16.23 217.3 566.9 1,490.6

Weakfish 278,408.0 $2.37 $6.17 $16.23 659.0 1,719.0 4,519.6

Total (Small Game) 373,479.0 $2.37 $6.17 $16.23 884.0 2,306.0 6,063.0

Atlantic croaker 983,158.0 $1.94 $3.05 $4.82 1,906.3 3,003.0 4,733.8

Atlantic herring 40.0 $1.94 $3.05 $4.82 0.1 0.1 0.2

Black drum 182.0 $1.94 $3.05 $4.82 0.4 0.6 0.9

Cunner 0.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Scup 1.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Searobin 5.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Silver perch 1.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Smallmouth bass 41.0 $1.94 $3.05 $4.82 0.1 0.1 0.2

Spot 3,026,406.0 $1.94 $3.05 $4.82 5,868.1 9,243.9 14,571.9

Striped mullet 9.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Tautog 0.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

White perch 18,793.0 $1.94 $3.05 $4.82 36.4 57.4 90.5

Whitefish 303.0 $1.94 $3.05 $4.82 0.6 0.9 1.5

Total (Other Saltwater) 4,028,939.0 $1.94 $3.05 $4.82 7,812.0 12,306.0 19,399.0

Total (Unidentified) 689,524.0 $2.00 $3.39 $6.00 1,378.0 2,340.0 4,138.0

Total (Undiscounted) 5,103,595.0

. . . 10,102.0 16,996.0 29,670.0

Total (3% discount rate)

. . . . 5,132.0 8,634.0 15,072.0

Total (7% discount rate)

. . . . 3,273.0 5,506.0 9,612.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 12 

### Table I

- 12: Recreational Fishing Benefits from Eliminating Baseline IM&E at Regulated

Facilities in the Mid

- Atlantic Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Summer Flounder 4,092.0 $3.92 $5.88 $8.92 16.3 24.1 36.4

Winter Flounder 3,209.0 $3.92 $5.88 $8.92 12.7 18.9 28.6

Total (Flatfish) 7,301.0 $3.92 $5.88 $8.92 29.0 43.0 65.0

Black Crappie 3.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Bluegill 12.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Brown bullhead 2,569.0 $0.55 $1.11 $2.20 1.4 2.8 5.5

Bullhead 8.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Channel catfish 2,228.0 $0.55 $1.11 $2.20 1.2 2.4 4.8

Crappie 1.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Menhaden 609.0 $0.55 $1.11 $2.20 0.3 0.7 1.3

Sunfish 170.0 $0.55 $1.11 $2.20 0.1 0.2 0.4

Total (Panfish) 5,600.0 $0.55 $1.11 $2.20 3.0 6.0 12.0

Bluefish 97.0 $2.37 $6.17 $16.23 0.2 0.6 1.6

Red drum 2,055.0 $2.37 $6.17 $16.23 4.9 12.7 33.4

Spotted seatrout 1,362.0 $2.37 $6.17 $16.23 3.2 8.4 22.1

Striped bass 105,323.0 $2.37 $6.17 $16.23 249.2 650.3 1,709.8

Weakfish 312,082.0 $2.37 $6.17 $16.23 738.5 1,927.0 5,066.2

Total (Small Game) 420,920.0 $2.37 $6.17 $16.23 996.0 2,599.0 6,833.0

Atlantic croaker 1,127,044.0 $1.94 $3.05 $4.82 2,185.2 3,442.4 5,426.8

Atlantic herring 44.0 $1.94 $3.05 $4.82 0.1 0.1 0.2

Black drum 197.0 $1.94 $3.05 $4.82 0.4 0.6 0.9

Cunner 0.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Scup 1.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Searobin 6.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Silver perch 1.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Smallmouth bass 44.0 $1.94 $3.05 $4.82 0.1 0.1 0.2

Spot 3,453,578.0 $1.94 $3.05 $4.82 6,696.1 10,548.3 16,629.1

Striped mullet 9.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

Tautog 0.0 $1.94 $3.05 $4.82 0.0 0.0 0.0

White perch 21,411.0 $1.94 $3.05 $4.82 41.5 65.4 103.1

Whitefish 328.0 $1.94 $3.05 $4.82 0.6 1.0 1.6

Total (Other Saltwater) 4,602,664.0 $1.94 $3.05 $4.82 8,924.0 14,058.0 22,162.0

Total (Unidentified) 786,704.0 $2.00 $3.39 $6.00 1,573.0 2,669.0 4,721.0

Total (Undiscounted) 5,823,189.0

. . . 11,524.0 19,375.0 33,793.0

Total (3% discount rate)

. . . . 9,665.0 16,249.0 28,341.0

Total (7% discount rate)

. . . . 8,643.0 14,531.0 25,343.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 13 

## I. 4 South Atlantic Region

Table I

- 13: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 4 in the South Atlantic Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Flounders 402.0 $4.05 $5.87 $8.66 2.0 2.0 3.0

Total (Flatfish) 402.0 $4.05 $5.87 $8.66 2.0 2.0 3.0

Spotted seatrout 0.0 $2.84 $5.99 $12.59 0.0 0.0 0.0

Weakfish 183.0 $2.84 $5.99 $12.59 1.0 1.0 2.0

Total (Small Game) 183.0 $2.84 $5.99 $12.59 1.0 1.0 2.0

Croakers 1,440.0 $2.24 $2.98 $3.95 3.3 4.2 5.7

Pinfish 0.0 $2.24 $2.98 $3.95 0.0 0.0 0.0

Silver perch 39.0 $2.24 $2.98 $3.95 0.1 0.1 0.2

Spot 10,409.0 $2.24 $2.98 $3.95 23.6 30.6 41.2

Total (Other Saltwater) 11,888.0 $2.24 $2.98 $3.95 27.0 35.0 47.0

Total (Unidentified) 510.0 $2.25 $2.99 $3.99 1.0 2.0 2.0

Total (Undiscounted) 12,983.0

. . . 30.0 40.0 55.0

Total (3% discount rate)

. . . . 18.0 24.0 33.0

Total (7% discount rate)

. . . . 13.0 17.0 23.0

Source: U.S. EPA analysis for this report.



### Table I

- 14: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under the Final Rule (IM Everywhere) in the South Atlantic Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Flounders 430.0 $4.05 $5.87 $8.66 2.0 3.0 4.0

Total (Flatfish) 430.0 $4.05 $5.87 $8.66 2.0 3.0 4.0

Spotted seatrout 84.0 $2.84 $5.99 $12.59 0.3 0.6 1.2

Weakfish 201.0 $2.84 $5.99 $12.59 0.7 1.4 2.8

Total (Small Game) 284.0 $2.84 $5.99 $12.59 1.0 2.0 4.0

Croakers 5,705.0 $2.24 $2.98 $3.95 12.8 17.0 22.6

Pinfish 67.0 $2.24 $2.98 $3.95 0.1 0.2 0.3

Silver perch 42.0 $2.24 $2.98 $3.95 0.1 0.1 0.2

Spot 11,607.0 $2.24 $2.98 $3.95 26.0 34.6 46.0

Total (Other Saltwater) 17,421.0 $2.24 $2.98 $3.95 39.0 52.0 69.0

Total (Unidentified) 589.0 $2.25 $2.99 $3.99 1.0 2.0 2.0

Total (Undiscounted) 18,725.0

. . . 43.0 58.0 78.0

Total (3% discount rate)

. . . . 26.0 35.0 47.0

Total (7% discount rate)

. . . . 18.0 24.0 33.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 14 

### Table I

- 15: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 2 in the South Atlantic Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Flounders 587.0 $4.05 $5.87 $8.66 2.0 3.0 5.0

Total (Flatfish) 587.0 $4.05 $5.87 $8.66 2.0 3.0 5.0

Spotted seatrout 1,501.0 $2.84 $5.99 $12.59 4.1 8.9 18.7

Weakfish 347.0 $2.84 $5.99 $12.59 0.9 2.1 4.3

Total (Small Game) 1,848.0 $2.84 $5.99 $12.59 5.0 11.0 23.0

Croakers 76,510.0 $2.24 $2.98 $3.95 171.9 228.0 302.2

Pinfish 1,200.0 $2.24 $2.98 $3.95 2.7 3.6 4.7

Silver perch 58.0 $2.24 $2.98 $3.95 0.1 0.2 0.2

Spot 23,237.0 $2.24 $2.98 $3.95 52.2 69.2 91.8

Total (Other Saltwater) 101,006.0 $2.24 $2.98 $3.95 227.0 301.0 399.0

Total (Unidentified) 1,502.0 $2.25 $2.99 $3.99 3.0 4.0 6.0

Total (Undiscounted) 104,943.0

. . . 238.0 320.0 433.0

Total (3% discount rate)

. . . . 129.0 173.0 234.0

Total (7% discount rate)

. . . . 86.0 115.0 156.0

Source: U.S. EPA analysis for this report.



### Table I

- 16: Recreational Fishing Benefits from Eliminating Baseline IM&E at Regulated

Facilities in the South Atlantic Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Flounders 593.0 $4.05 $5.87 $8.66 2.0 3.0 5.0

Total (Flatfish) 593.0 $4.05 $5.87 $8.66 2.0 3.0 5.0

Spotted seatrout 1,604.0 $2.84 $5.99 $12.59 4.9 9.8 20.5

Weakfish 355.0 $2.84 $5.99 $12.59 1.1 2.2 4.5

Total (Small Game) 1,960.0 $2.84 $5.99 $12.59 6.0 12.0 25.0

Croakers 81,677.0 $2.24 $2.98 $3.95 183.3 243.6 323.0

Pinfish 1,283.0 $2.24 $2.98 $3.95 2.9 3.8 5.1

Silver perch 58.0 $2.24 $2.98 $3.95 0.1 0.2 0.2

Spot 23,943.0 $2.24 $2.98 $3.95 53.7 71.4 94.7

Total (Other Saltwater) 106,961.0 $2.24 $2.98 $3.95 240.0 319.0 423.0

Total (Unidentified) 1,562.0 $2.25 $2.99 $3.99 4.0 5.0 6.0

Total (Undiscounted) 111,075.0

. . . 251.0 338.0 459.0

Total (3% discount rate)

. . . . 211.0 284.0 385.0

Total (7% discount rate)

. . . . 189.0 254.0 344.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 15 

## I. 5 Gulf of Mexico Region

Table I

- 17: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 4 in the Gulf of Mexico Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Mackerels 994.0 $3.00 $5.89 $11.55 3.0 5.9 11.5

Red drum 19,500.0 $3.00 $5.89 $11.55 58.6 114.9 225.2

Spotted seatrout 394,780.0 $3.00 $5.89 $11.55 1,185.5 2,325.3 4,558.4

Total (Small Game) 415,274.0 $3.00 $5.89 $11.55 1,247.0 2,446.0 4,795.0

Atlantic croaker 153,811.0 $2.23 $2.91 $3.78 343.5 446.7 581.4

Black drum 4,185.0 $2.23 $2.91 $3.78 9.3 12.2 15.8

Pinfish 6,006.0 $2.23 $2.91 $3.78 13.4 17.4 22.7

Sea bass 103.0 $2.23 $2.91 $3.78 0.2 0.3 0.4

Searobin 73,120.0 $2.23 $2.91 $3.78 163.3 212.4 276.4

Sheepshead 1.0 $2.23 $2.91 $3.78 0.0 0.0 0.0

Silver perch 67.0 $2.23 $2.91 $3.78 0.1 0.2 0.3

Spot 21,098.0 $2.23 $2.91 $3.78 47.1 61.3 79.8

Striped mullet 5,350.0 $2.23 $2.91 $3.78 11.9 15.5 20.2

Total (Other Saltwater) 263,742.0 $2.23 $2.91 $3.78 589.0 766.0 997.0

Total (Unidentified) 70,129.0 $2.47 $3.83 $6.18 173.0 269.0 434.0

Total (Undiscounted) 749,144.0

. . . 2,009.0 3,481.0 6,225.0

Total (3% discount rate)

. . . . 1,260.0 2,183.0 3,904.0

Total (7% discount rate)

. . . . 914.0 1,583.0 2,831.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 16 

### Table I

- 18: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under the Final Rule in the Gulf of Mexico Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Mackerels 1,032.0 $3.00 $5.89 $11.55 3.1 6.1 11.9

Red drum 20,239.0 $3.00 $5.89 $11.55 60.8 119.2 233.7

Spotted seatrout 409,748.0 $3.00 $5.89 $11.55 1,230.1 2,413.7 4,731.4

Total (Small Game) 431,019.0 $3.00 $5.89 $11.55 1,294.0 2,539.0 4,977.0

Atlantic croaker 159,643.0 $2.23 $2.91 $3.78 356.4 463.7 603.1

Black drum 4,295.0 $2.23 $2.91 $3.78 9.6 12.5 16.2

Pinfish 6,226.0 $2.23 $2.91 $3.78 13.9 18.1 23.5

Sea bass 107.0 $2.23 $2.91 $3.78 0.2 0.3 0.4

Searobin 75,892.0 $2.23 $2.91 $3.78 169.4 220.5 286.7

Sheepshead 1.0 $2.23 $2.91 $3.78 0.0 0.0 0.0

Silver perch 70.0 $2.23 $2.91 $3.78 0.2 0.2 0.3

Spot 21,898.0 $2.23 $2.91 $3.78 48.9 63.6 82.7

Striped mullet 5,552.0 $2.23 $2.91 $3.78 12.4 16.1 21.0

Total (Other Saltwater) 273,683.0 $2.23 $2.91 $3.78 611.0 795.0 1,034.0

Total (Unidentified) 72,787.0 $2.47 $3.83 $6.18 180.0 279.0 450.0

Total (Undiscounted) 777,488.0

. . . 2,085.0 3,613.0 6,461.0

Total (3% discount rate)

. . . . 1,308.0 2,265.0 4,051.0

Total (7% discount rate)

. . . . 948.0 1,643.0 2,938.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 17 

### Table I

- 19: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 2 in the Gulf of Mexico Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Mackerels 1,237.0 $3.00 $5.89 $11.55 3.7 7.3 14.3

Red drum 26,734.0 $3.00 $5.89 $11.55 80.3 157.5 308.7

Spotted seatrout 524,007.0 $3.00 $5.89 $11.55 1,573.0 3,086.3 6,050.1

Total (Small Game) 551,978.0 $3.00 $5.89 $11.55 1,657.0 3,251.0 6,373.0

Atlantic croaker 191,598.0 $2.23 $2.91 $3.78 428.1 556.8 723.9

Black drum 941,083.0 $2.23 $2.91 $3.78 2,102.6 2,734.6 3,555.8

Pinfish 160,133.0 $2.23 $2.91 $3.78 357.8 465.3 605.0

Sea bass 128.0 $2.23 $2.91 $3.78 0.3 0.4 0.5

Searobin 111,200.0 $2.23 $2.91 $3.78 248.4 323.1 420.2

Sheepshead 28.0 $2.23 $2.91 $3.78 0.1 0.1 0.1

Silver perch 933.0 $2.23 $2.91 $3.78 2.1 2.7 3.5

Spot 29,782.0 $2.23 $2.91 $3.78 66.5 86.5 112.5

Striped mullet 33,192.0 $2.23 $2.91 $3.78 74.2 96.5 125.4

Total (Other Saltwater) 1,468,076.0 $2.23 $2.91 $3.78 3,280.0 4,266.0 5,547.0

Total (Unidentified) 117,807.0 $2.47 $3.83 $6.18 291.0 451.0 729.0

Total (Undiscounted) 2,137,861.0

. . . 5,228.0 7,968.0 12,649.0

Total (3% discount rate)

. . . . 3,357.0 5,116.0 8,122.0

Total (7% discount rate)

. . . . 2,476.0 3,774.0 5,991.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 18 

### Table I

- 20: Recreational Fishing Benefits from Eliminating Baseline IM&E at Regulated

Facilities in the Gulf of Mexico Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Mackerels 1,374.0 $3.00 $5.89 $11.55 4.1 8.1 15.9

Red drum 31,114.0 $3.00 $5.89 $11.55 93.4 183.2 359.3

Spotted seatrout 600,729.0 $3.00 $5.89 $11.55 1,803.5 3,537.7 6,936.8

Total (Small Game) 633,217.0 $3.00 $5.89 $11.55 1,901.0 3,729.0 7,312.0

Atlantic croaker 212,766.0 $2.23 $2.91 $3.78 475.3 618.2 804.0

Black drum 1,591,629.0 $2.23 $2.91 $3.78 3,555.8 4,624.9 6,014.2

Pinfish 266,978.0 $2.23 $2.91 $3.78 596.5 775.8 1,008.8

Sea bass 142.0 $2.23 $2.91 $3.78 0.3 0.4 0.5

Searobin 135,234.0 $2.23 $2.91 $3.78 302.1 393.0 511.0

Sheepshead 47.0 $2.23 $2.91 $3.78 0.1 0.1 0.2

Silver perch 1,532.0 $2.23 $2.91 $3.78 3.4 4.5 5.8

Spot 35,116.0 $2.23 $2.91 $3.78 78.5 102.0 132.7

Striped mullet 52,351.0 $2.23 $2.91 $3.78 117.0 152.1 197.8

Total (Other Saltwater) 2,295,795.0 $2.23 $2.91 $3.78 5,129.0 6,671.0 8,675.0

Total (Unidentified) 148,605.0 $2.47 $3.83 $6.18 367.0 569.0 919.0

Total (Undiscounted) 3,077,617.0

. . . 7,397.0 10,969.0 16,905.0

Total (3% discount rate)

. . . . 6,457.0 9,575.0 14,756.0

Total (7% discount rate)

. . . . 5,955.0 8,831.0 13,610.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 19 

## I. 6 Great Lakes Region

Table I

- 21: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 4 in the Great Lakes Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Smallmouth bass 2,314.0 $4.63 $8.95 $17.38 16.7 8,870.0 17,216.0

White bass 632,325.0 $4.63 $8.95 $17.38 4,567.3 8,870.0 17,216.0

Total (Bass) 634,639.0 $4.63 $8.95 $17.38 4,584.0 8,870.0 17,216.0

Whitefish 40,464.0 $6.39 $9.87 $15.34 332.0 514.0 799.0

Total (Other Trout) 40,464.0 $6.39 $9.87 $15.34 332.0 514.0 799.0

Black crappie 107.0 $0.73 $1.39 $2.61 0.3 0.5 1.0

Bluegill 1,010.0 $0.73 $1.39 $2.61 2.6 4.9 9.2

Channel catfish 12,995.0 $0.73 $1.39 $2.61 32.9 62.7 117.9

Crappie 321.0 $0.73 $1.39 $2.61 0.8 1.5 2.9

Rainbow smelt 4,722.0 $0.73 $1.39 $2.61 12.0 22.8 42.8

Sculpin 197.0 $0.73 $1.39 $2.61 0.5 1.0 1.8

Smelts 8,453.0 $0.73 $1.39 $2.61 21.4 40.8 76.7

Sunfish 676.0 $0.73 $1.39 $2.61 1.7 3.3 6.1

Yellow perch 29,926.0 $0.73 $1.39 $2.61 75.8 144.5 271.6

Total (Panfish) 58,408.0 $0.73 $1.39 $2.61 148.0 282.0 530.0

Salmon 609.0 $8.53 $13.88 $22.61 8.0 14.0 22.0

Total (Salmon) 609.0 $8.53 $13.88 $22.61 8.0 14.0 22.0

Northern Pike 3.0 $2.28 $4.30 $8.16 0.0 0.0 0.0

Walleye 18,082.0 $2.28 $4.30 $8.16 264.0 497.9 945.8

Total (Walleye/Pike) 18,085.0 $2.28 $4.30 $8.16 264.0 498.0 946.0

Total (Unidentified) 579,751.0 $3.49 $6.51 $12.25 3,032.0 5,661.0 10,661.0

Total (Undiscounted) 1,331,956.0

. . . 8,370.0 15,838.0 30,174.0

Total (3% discount rate)

. . . . 7,306.0 13,825.0 26,338.0

Total (7% discount rate)

. . . . 6,738.0 12,751.0 24,292.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 20 

### Table I

- 22: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under the Final Rule in the Great Lakes Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Smallmouth bass 2,546.0 $4.63 $8.95 $17.38 11.8 6,257.0 12,144.0

White bass 696,159.0 $4.63 $8.95 $17.38 3,222.2 6,257.0 12,144.0

Total (Bass) 698,705.0 $4.63 $8.95 $17.38 3,234.0 6,257.0 12,144.0

Whitefish 44,532.0 $6.39 $9.87 $15.34 284.0 440.0 683.0

Total (Other Trout) 44,532.0 $6.39 $9.87 $15.34 284.0 440.0 683.0

Black crappie 118.0 $0.73 $1.39 $2.61 0.1 0.2 0.3

Bluegill 1,112.0 $0.73 $1.39 $2.61 0.8 1.6 2.9

Channel catfish 14,302.0 $0.73 $1.39 $2.61 10.4 20.0 37.3

Crappie 362.0 $0.73 $1.39 $2.61 0.3 0.5 0.9

Rainbow smelt 5,347.0 $0.73 $1.39 $2.61 3.9 7.5 13.9

Sculpin 224.0 $0.73 $1.39 $2.61 0.2 0.3 0.6

Smelts 9,303.0 $0.73 $1.39 $2.61 6.8 13.0 24.2

Sunfish 766.0 $0.73 $1.39 $2.61 0.6 1.1 2.0

Yellow perch 32,942.0 $0.73 $1.39 $2.61 24.0 46.0 85.8

Total (Panfish) 64,475.0 $0.73 $1.39 $2.61 47.0 90.0 168.0

Salmon 671.0 $8.53 $13.88 $22.61 6.0 9.0 15.0

Total (Salmon) 671.0 $8.53 $13.88 $22.61 6.0 9.0 15.0

Northern Pike 3.0 $2.28 $4.30 $8.16 0.0 0.0 0.0

Walleye 20,041.0 $2.28 $4.30 $8.16 46.0 86.0 164.0

Total (Walleye/Pike) 20,044.0 $2.28 $4.30 $8.16 46.0 86.0 164.0

Total (Unidentified) 638,223.0 $3.49 $6.51 $12.25 2,224.0 4,153.0 7,821.0

Total (Undiscounted) 1,466,650.0

. . . 5,841.0 11,034.0 20,995.0

Total (3% discount rate)

. . . . 3,793.0 7,166.0 13,636.0

Total (7% discount rate)

. . . . 2,820.0 5,328.0 10,138.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 21 

### Table I

- 23: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 2 in the Great Lakes Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Smallmouth bass 2,902.0 $4.63 $8.95 $17.38 13.4 8,250.0 16,013.0

White bass 918,361.0 $4.63 $8.95 $17.38 4,250.6 8,250.0 16,013.0

Total (Bass) 921,263.0 $4.63 $8.95 $17.38 4,264.0 8,250.0 16,013.0

Whitefish 50,757.0 $6.39 $9.87 $15.34 324.0 501.0 779.0

Total (Other Trout) 50,757.0 $6.39 $9.87 $15.34 324.0 501.0 779.0

Black crappie 135.0 $0.73 $1.39 $2.61 0.1 0.2 0.4

Bluegill 1,334.0 $0.73 $1.39 $2.61 1.0 1.8 3.5

Channel catfish 16,552.0 $0.73 $1.39 $2.61 12.1 22.9 43.3

Crappie 4,373.0 $0.73 $1.39 $2.61 3.2 6.1 11.4

Rainbow smelt 76,779.0 $0.73 $1.39 $2.61 56.2 106.4 200.7

Sculpin 3,489.0 $0.73 $1.39 $2.61 2.6 4.8 9.1

Smelts 10,636.0 $0.73 $1.39 $2.61 7.8 14.7 27.8

Sunfish 10,788.0 $0.73 $1.39 $2.61 7.9 15.0 28.2

Yellow perch 41,148.0 $0.73 $1.39 $2.61 30.1 57.0 107.6

Total (Panfish) 165,234.0 $0.73 $1.39 $2.61 121.0 229.0 432.0

Salmon 910.0 $8.53 $13.88 $22.61 8.0 13.0 21.0

Total (Salmon) 910.0 $8.53 $13.88 $22.61 8.0 13.0 21.0

Northern Pike 5.0 $2.28 $4.30 $8.16 0.0 0.0 0.0

Walleye 89,320.0 $2.28 $4.30 $8.16 204.0 384.0 729.0

Total (Walleye/Pike) 89,325.0 $2.28 $4.30 $8.16 204.0 384.0 729.0

Total (Unidentified) 816,530.0 $3.49 $6.51 $12.25 2,846.0 5,313.0 10,006.0

Total (Undiscounted) 2,044,018.0

. . . 7,766.0 14,690.0 27,978.0

Total (3% discount rate)

. . . . 4,717.0 8,922.0 16,993.0

Total (7% discount rate)

. . . . 3,359.0 6,354.0 12,102.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 22 

### Table I

- 24: Recreational Fishing Benefits from Eliminating Baseline IM&E at Regulated

Facilities in the Great Lakes Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Smallmouth bass 2,976.0 $4.63 $8.95 $17.38 13.8 8,870.0 17,216.0

White bass 987,522.0 $4.63 $8.95 $17.38 4,570.2 8,870.0 17,216.0

Total (Bass) 990,498.0 $4.63 $8.95 $17.38 4,584.0 8,870.0 17,216.0

Whitefish 52,059.0 $6.39 $9.87 $15.34 332.0 514.0 799.0

Total (Other Trout) 52,059.0 $6.39 $9.87 $15.34 332.0 514.0 799.0

Black crappie 138.0 $0.73 $1.39 $2.61 0.1 0.2 0.4

Bluegill 1,393.0 $0.73 $1.39 $2.61 1.0 1.9 3.6

Channel catfish 17,068.0 $0.73 $1.39 $2.61 12.4 23.7 44.6

Crappie 5,932.0 $0.73 $1.39 $2.61 4.3 8.2 15.5

Rainbow smelt 104,556.0 $0.73 $1.39 $2.61 76.2 145.3 273.0

Sculpin 4,759.0 $0.73 $1.39 $2.61 3.5 6.6 12.4

Smelts 10,921.0 $0.73 $1.39 $2.61 8.0 15.2 28.5

Sunfish 14,686.0 $0.73 $1.39 $2.61 10.7 20.4 38.3

Yellow perch 43,518.0 $0.73 $1.39 $2.61 31.7 60.5 113.6

Total (Panfish) 202,970.0 $0.73 $1.39 $2.61 148.0 282.0 530.0

Salmon 986.0 $8.53 $13.88 $22.61 8.0 14.0 22.0

Total (Salmon) 986.0 $8.53 $13.88 $22.61 8.0 14.0 22.0

Northern Pike 5.0 $2.28 $4.30 $8.16 0.0 0.0 0.0

Walleye 115,883.0 $2.28 $4.30 $8.16 264.0 498.0 946.0

Total (Walleye/Pike) 115,889.0 $2.28 $4.30 $8.16 264.0 498.0 946.0

Total (Unidentified) 870,008.0 $3.49 $6.51 $12.25 3,032.0 5,661.0 10,661.0

Total (Undiscounted) 2,232,409.0

. . . 8,370.0 15,838.0 30,174.0

Total (3% discount rate)

. . . . 7,306.0 13,825.0 26,338.0

Total (7% discount rate)

. . . . 6,738.0 12,751.0 24,292.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 23 

## I. 7 Inland Region

Table I

- 25: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 4 in the Inland Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Smallmouth bass 8,142.0 $4.48 $9.43 $19.96 36.5 76.8 162.5

White bass 537,712.0 $4.48 $9.43 $19.96 2,410.5 5,070.2 10,731.5

Total (Bass) 545,853.0 $4.48 $9.43 $19.96 2,447.0 5,147.0 10,894.0

Whitefish 1,355.0 $1.59 $2.96 $5.53 2.0 4.0 7.0

Total (Other Trout) 1,355.0 $1.59 $2.96 $5.53 2.0 4.0 7.0

Black bullhead 20,797.0 $0.55 $1.11 $2.20 11.5 23.0 45.8

Black crappie 11,790.0 $0.55 $1.11 $2.20 6.5 13.0 25.9

Bluegill 276,051.0 $0.55 $1.11 $2.20 152.5 305.3 607.4

Brown bullhead 3,953.0 $0.55 $1.11 $2.20 2.2 4.4 8.7

Bullhead 2,682.0 $0.55 $1.11 $2.20 1.5 3.0 5.9

Channel catfish 188,768.0 $0.55 $1.11 $2.20 104.3 208.8 415.4

Crappie 20,410.0 $0.55 $1.11 $2.20 11.3 22.6 44.9

Menhaden 213.0 $0.55 $1.11 $2.20 0.1 0.2 0.5

Rainbow smelt 2,565.0 $0.55 $1.11 $2.20 1.4 2.8 5.6

Smelts 1.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Sunfish 161,748.0 $0.55 $1.11 $2.20 89.4 178.9 355.9

White Perch 3,360.0 $0.55 $1.11 $2.20 1.9 3.7 7.4

Yellow perch 247,054.0 $0.55 $1.11 $2.20 136.5 273.3 543.6

Total (Panfish) 939,390.0 $0.55 $1.11 $2.20 519.0 1,039.0 2,067.0

Salmon 4.0 $8.53 $13.88 $22.61 0.0 0.0 0.0

Total (Salmon) 4.0 $8.53 $13.88 $22.61 0.0 0.0 0.0

American shad 2,122.0 $1.68 $5.61 $18.90 3.6 11.8 40.2

Striped bass 13,681.0 $1.68 $5.61 $18.90 23.1 76.3 258.9

Sturgeon 154.0 $1.68 $5.61 $18.90 0.3 0.9 2.9

Total (Small Game) 15,957.0 $1.68 $5.61 $18.90 27.0 89.0 302.0

Northern pike 25.0 $2.07 $4.29 $8.92 0.1 0.1 0.2

Sauger 6,672.0 $2.07 $4.29 $8.92 13.9 28.5 59.6

Walleye 11,116.0 $2.07 $4.29 $8.92 23.1 47.4 99.2

Total (Walleye/Pike) 17,812.0 $2.07 $4.29 $8.92 37.0 76.0 159.0

Total (Unidentified) 2,049,682.0 $1.13 $2.33 $4.81 2,325.0 4,784.0 9,865.0

Total (Undiscounted) 3,570,053.0

. . . 5,357.0 11,140.0 23,295.0

Total (3% discount rate)

. . . . 3,503.0 7,284.0 15,231.0

Total (7% discount rate)

. . . . 2,616.0 5,440.0 11,375.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 24 

### Table I

- 26: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under the Final Rule in the Inland Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Smallmouth bass 9,392.0 $4.48 $9.43 $19.96 42.1 88.6 187.4

White bass 560,751.0 $4.48 $9.43 $19.96 2,513.9 5,287.5 11,191.6

Total (Bass) 570,143.0 $4.48 $9.43 $19.96 2,556.0 5,376.0 11,379.0

Whitefish 1,401.0 $1.59 $2.96 $5.53 2.0 4.0 8.0

Total (Other Trout) 1,401.0 $1.59 $2.96 $5.53 2.0 4.0 8.0

Black bullhead 21,509.0 $0.55 $1.11 $2.20 11.9 23.8 47.3

Black crappie 12,888.0 $0.55 $1.11 $2.20 7.1 14.2 28.4

Bluegill 285,614.0 $0.55 $1.11 $2.20 158.0 315.7 628.4

Brown bullhead 4,136.0 $0.55 $1.11 $2.20 2.3 4.6 9.1

Bullhead 2,781.0 $0.55 $1.11 $2.20 1.5 3.1 6.1

Channel catfish 196,096.0 $0.55 $1.11 $2.20 108.5 216.7 431.5

Crappie 23,044.0 $0.55 $1.11 $2.20 12.7 25.5 50.7

Menhaden 220.0 $0.55 $1.11 $2.20 0.1 0.2 0.5

Rainbow smelt 2,683.0 $0.55 $1.11 $2.20 1.5 3.0 5.9

Smelts 1.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Sunfish 174,183.0 $0.55 $1.11 $2.20 96.3 192.5 383.2

White Perch 3,477.0 $0.55 $1.11 $2.20 1.9 3.8 7.7

Yellow perch 256,905.0 $0.55 $1.11 $2.20 142.1 283.9 565.2

Total (Panfish) 983,538.0 $0.55 $1.11 $2.20 544.0 1,087.0 2,164.0

Salmon 4.0 $8.53 $13.88 $22.61 0.0 0.0 0.0

Total (Salmon) 4.0 $8.53 $13.88 $22.61 0.0 0.0 0.0

American shad 2,194.0 $1.68 $5.61 $18.90 3.7 12.4 41.5

Striped bass 14,146.0 $1.68 $5.61 $18.90 24.0 79.7 267.4

Sturgeon 167.0 $1.68 $5.61 $18.90 0.3 0.9 3.2

Total (Small Game) 16,507.0 $1.68 $5.61 $18.90 28.0 93.0 312.0

Northern pike 26.0 $2.07 $4.29 $8.92 0.1 0.1 0.2

Sauger 7,825.0 $2.07 $4.29 $8.92 16.1 33.8 69.8

Walleye 12,546.0 $2.07 $4.29 $8.92 25.8 54.1 112.0

Total (Walleye/Pike) 20,396.0 $2.07 $4.29 $8.92 42.0 88.0 182.0

Total (Unidentified) 2,139,619.0 $1.13 $2.33 $4.81 2,427.0 4,994.0 10,298.0

Total (Undiscounted) 3,731,608.0

. . . 5,599.0 11,642.0 24,343.0

Total (3% discount rate)

. . . . 3,661.0 7,613.0 15,918.0

Total (7% discount rate)

. . . . 2,735.0 5,686.0 11,889.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 25 

### Table I

- 27: Recreational Fishing Benefits from Reducing IM&E at Regulated Facilities

under Proposal Option 2 in the Inland Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Smallmouth bass 141,379.0 $4.48 $9.43 $19.96 633.7 633.7 633.7

White bass 1,286,644.0 $4.48 $9.43 $19.96 5,767.3 12,132.1 5,767.3

Total (Bass) 1,428,023.0 $4.48 $9.43 $19.96 6,401.0 6,401.0 6,401.0

Whitefish 1,688.0 $1.59 $2.96 $5.53 3.0 3.0 3.0

Total (Other Trout) 1,688.0 $1.59 $2.96 $5.53 3.0 3.0 3.0

Black bullhead 25,487.0 $0.55 $1.11 $2.20 14.1 14.1 14.1

Black crappie 108,409.0 $0.55 $1.11 $2.20 59.9 59.9 59.9

Bluegill 354,207.0 $0.55 $1.11 $2.20 195.8 195.8 195.8

Brown bullhead 11,390.0 $0.55 $1.11 $2.20 6.3 6.3 6.3

Bullhead 4,307.0 $0.55 $1.11 $2.20 2.4 2.4 2.4

Channel catfish 348,937.0 $0.55 $1.11 $2.20 192.9 192.9 192.9

Crappie 286,830.0 $0.55 $1.11 $2.20 158.6 158.6 158.6

Menhaden 254.0 $0.55 $1.11 $2.20 0.1 0.1 0.1

Rainbow smelt 7,121.0 $0.55 $1.11 $2.20 3.9 3.9 3.9

Smelts 1.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Sunfish 1,131,661.0 $0.55 $1.11 $2.20 625.6 625.6 625.6

White Perch 4,461.0 $0.55 $1.11 $2.20 2.5 2.5 2.5

Yellow perch 491,893.0 $0.55 $1.11 $2.20 271.9 271.9 271.9

Total (Panfish) 2,774,958.0 $0.55 $1.11 $2.20 1,534.0 1,534.0 1,534.0

Salmon 4.0 $8.53 $13.88 $22.61 0.0 0.0 0.0

Total (Salmon) 4.0 $8.53 $13.88 $22.61 0.0 0.0 0.0

American shad 2,531.0 $1.68 $5.61 $18.90 4.3 14.2 47.9

Striped bass 16,318.0 $1.68 $5.61 $18.90 27.5 91.5 308.7

Sturgeon 1,294.0 $1.68 $5.61 $18.90 2.2 7.3 24.5

Total (Small Game) 20,143.0 $1.68 $5.61 $18.90 34.0 113.0 381.0

Northern pike 29.0 $2.07 $4.29 $8.92 0.1 0.1 0.3

Sauger 133,280.0 $2.07 $4.29 $8.92 276.3 572.0 1,188.8

Walleye 155,606.0 $2.07 $4.29 $8.92 322.6 667.8 1,387.9

Total (Walleye/Pike) 288,916.0 $2.07 $4.29 $8.92 599.0 1,240.0 2,577.0

Total (Unidentified) 5,190,603.0 $1.13 $2.33 $4.81 5,889.0 12,116.0 24,981.0

Total (Undiscounted) 9,704,334.0

. . . 14,459.0 30,007.0 62,557.0

Total (3% discount rate)

. . . . 8,290.0 17,204.0 35,865.0

Total (7% discount rate)

. . . . 5,726.0 11,883.0 24,773.0

Source: U.S. EPA analysis for this report.Benefits Analysis for the Final 316(b) Existing Facilities Rule Appendix I: Details of Recreational Fishing Benefits

July 8, 2014 I

- 26 

### Table I

- 28: Recreational Fishing Benefits from Eliminating Baseline IM&E at Regulated

Facilities in the Inland Region, by Species (2011$)

Species Annual

Increase in

Recreational

Harvest

(harvestable

adult fish) Value per Fish Annual Benefits from Increase

in Recreational Harvest

(2011$, thousands)

5 th Mean 95 th 5 th Mean 95 th

Smallmouth bass 180,693.0 $4.48 $9.43 $19.96 810.0 1,703.8 3,606.4

White bass 1,567,058.0 $4.48 $9.43 $19.96 7,025.0 14,776.2 31,276.6

Total (Bass) 1,747,751.0 $4.48 $9.43 $19.96 7,835.0 16,480.0 34,883.0

Whitefish 1,947.0 $1.59 $2.96 $5.53 3.0 6.0 11.0

Total (Other Trout) 1,947.0 $1.59 $2.96 $5.53 3.0 6.0 11.0

Black bullhead 29,349.0 $0.55 $1.11 $2.20 16.2 32.4 64.6

Black crappie 137,629.0 $0.55 $1.11 $2.20 76.1 152.2 302.9

Bluegill 410,040.0 $0.55 $1.11 $2.20 226.7 453.3 902.4

Brown bullhead 14,007.0 $0.55 $1.11 $2.20 7.7 15.5 30.8

Bullhead 5,099.0 $0.55 $1.11 $2.20 2.8 5.6 11.2

Channel catfish 417,819.0 $0.55 $1.11 $2.20 231.0 461.9 919.5

Crappie 365,941.0 $0.55 $1.11 $2.20 202.3 404.6 805.4

Menhaden 291.0 $0.55 $1.11 $2.20 0.2 0.3 0.6

Rainbow smelt 8,741.0 $0.55 $1.11 $2.20 4.8 9.7 19.2

Smelts 1.0 $0.55 $1.11 $2.20 0.0 0.0 0.0

Sunfish 1,430,230.0 $0.55 $1.11 $2.20 790.8 1,581.1 3,147.6

White Perch 5,183.0 $0.55 $1.11 $2.20 2.9 5.7 11.4

Yellow perch 592,175.0 $0.55 $1.11 $2.20 327.4 654.7 1,303.3

Total (Panfish) 3,416,505.0 $0.55 $1.11 $2.20 1,889.0 3,777.0 7,519.0

Salmon 5.0 $8.53 $13.88 $22.61 0.0 0.0 0.0

Total (Salmon) 5.0 $8.53 $13.88 $22.61 0.0 0.0 0.0

American shad 2,905.0 $1.68 $5.61 $18.90 4.9 16.2 54.9

Striped bass 18,729.0 $1.68 $5.61 $18.90 31.4 104.6 354.1

Sturgeon 1,640.0 $1.68 $5.61 $18.90 2.7 9.2 31.0

Total (Small Game) 23,274.0 $1.68 $5.61 $18.90 39.0 130.0 440.0

Northern pike 34.0 $2.07 $4.29 $8.92 0.1 0.1 0.3

Sauger 170,509.0 $2.07 $4.29 $8.92 353.4 731.8 1,520.9

Walleye 198,517.0 $2.07 $4.29 $8.92 411.5 852.0 1,770.8

Total (Walleye/Pike) 369,060.0 $2.07 $4.29 $8.92 765.0 1,584.0 3,292.0

Total (Unidentified) 6,341,808.0 $1.13 $2.33 $4.81 7,195.0 14,803.0 30,522.0

Total (Undiscounted) 11,900,351.0

. . . 17,725.0 36,781.0 76,666.0

Total (3% discount rate)

. . . . 15,471.0 32,105.0 66,919.0

Total (7% discount rate)

. . . . 14,270.0 29,611.0 61,722.0

Source: U.S. EPA analysis for this report.