Economic Analysis for the Final Section 316(b) Existing Facilities Rule; May 2014


&EPA
United States
Environmental Protection
Agency
Economic Analysis for the
Final Section 316(b) Existing
Facilities Rule
EPA-821-R-14-001
May 2014

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U.S. Environmental Protection Agency
Office of Water (4303T)
1200 Pennsylvania Avenue, NW
Washington, DC 20460

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Economic Analysis for Final 316(b) Existing Facilities Rule
Table of Contents
Table of Contents
Table of Contents	i
1	Introduction and Executive Summary	1-1
1.1	Background	1-1
1.2	Overview of the Economic Analysis of the Final Rule	1-2
1.2.1	Facilities Subject to the Final Rule	1-2
1.2.2	Final Rule and Other Options Considered	1-5
1.2.3	Analyses Performed in Support of the Final Rule	1-7
1.3	Summary of Analysis Results	1-9
2	Introduction to Industry Profiles	2-1
2A	Profile of the Electric Power Industry	2A-1
2A. 1	Introduction	2A-1
2A.2 Industry Overview	2A-1
2A.2.1 Industry Sectors	2A-1
2A.2.2 Prime Movers	2A-2
2A.2.3 Ownership	2A-4
2A.3 Domestic Production	2A-6
2A.3.1 Generating Capacity	2A-6
2A.3.2 Electricity Generation	2A-7
2A.3.3 Geographic Distribution	2A-9
2A.4 Facilities Subject to the Final Rule	2A-12
2A.4.1 Ownership Type	2A-12
2A.4.2 Ownership Type and Parent Entity Size	2A-13
2A.4.3 Facility Size	2A-13
2A.4.4 Geographic Distribution	2A-15
2A.4.5 Waterbody and Cooling System Type	2A-15
2A.5 Industry Trends	2A-16
2A.5.1 Current Status of Industry Deregulation	2A-16
2A.5.2 Air Emissions Regulations	2A-19
2A.5.3 Renewable Portfolio Standards	2A-21
2A.5.4 Greenhouse Gas Emissions Regulations	2A-22
2A.5.5 Summary of Effects of Regulatory and Non-Regulatory Trends on Cooling Water Intake
Systems	2A-22
2A.6 Industry Outlook	2A-23
2A.6.1 Energy Market Model Forecasts	2A-23
2A.7 Glossary	2A-24
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2B Summary Profile of the Primary Manufacturing Industries	2B-1
2B. 1 Introduction	2B-1
2B.2 General Industry Descriptions; Role in the U.S. Economy	2B-2
2B. 2.1 Value of Shipments	2B -3
2B.2.2 Employment	2B-4
2B.2.3 Numbers of Facilities and Firms	2B-5
2B.3 Cost Pass-Through Assessment	2B-7
2B.3.1 Fraction of Each Industry's Production Subject to the Final Rule	2B-8
2B.3.2 Industry Concentration	2B-9
2B.3.3 Import Competition in Domestic Markets	2B-10
2B.3.4 Export Dependence - Competition in Foreign Markets	2B-12
2B.3.5 Long-Term Industry Growth	2B-13
2B.4 Financial Performance and Outlook Assessment	2B-14
2B.4.1 Capacity Utilization	2B-15
2B.4.2 Current Financial Data and Industry Outlook	2B-16
3	Compliance Costs	3-1
3.1	Compliance Costs for Existing Units	3-1
3.1.1	Analysis Approach and Data Inputs	3-2
3.1.2	Key Findings	3-10
3.1.3	Uncertainties and Limitations	3-16
3.2	Compliance Costs for New Units	3-17
3.2.1	Analysis Approach and Data Inputs	3-17
3.2.2	Key Findings	3-18
3.3	Total Compliance Costs of the Final Rule	3-18
3.4	Administrative Costs to States and Federal Government	3-19
3.4.1	Analysis Approach and Data Inputs	3-19
3.4.2	Key Findings	3-20
3.4.3	Uncertaintie s and Limitations	3-21
4	Economic Impact Analyses - Electric Generators	4-1
4.1	Analysis Overview	4-1
4.2	Cost and Economic Impact Analysis - Existing Units	4-2
4.2.1	Cost-to-Revenue Analysis: Facility-Level Screening Analysis	4-3
4.2.2	Cost-to-Revenue Screening Analysis: Entity-Level Analysis	4-8
4.2.3	Analysis of Impact of Compliance Costs on Electricity Prices	4-13
4.2.4	Analysis of Impact of Compliance Costs on Household Electricity Costs	4-18
4.2.5	Analysis of Short-Term Reduction in Capacity Availability Due to Installation Downtime	4-21
4.3	Cost and Economic Impact Analysis - New Units	4-29
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4.3.1	Analysis Approach and Data Inputs	4-30
4.3.2	Key Findings	4-32
4.3.3	Uncertainties and Limitations	4-33
5	Economic Impact Analyses - Manufacturers	5-1
5.1	Introduction	5-1
5.2	Overview of the Manufacturers Impact Analysis	5-1
5.2.1	Facility Universe	5-1
5.2.2	Methodology	5-2
5.2.3	Data Sources	5-2
5.3	Facility-Level Impacts: Cost-to-Revenue Screening Analysis	5-3
5.4	Facility-Level Impacts: Severe Impact Analysis	5-5
5.4.1	Analysis Approach and Data Inputs	5-5
5.4.2	Key Findings	5-8
5.5	Facility-Level Impacts: Moderate Impact Analysis	5-9
5.5.1	Analysis Approach and Data Inputs	5-9
5.5.2	Key Findings	5-11
5.6	Entity-Level Impacts	5-13
5.6.1	Analysis Approach and Data Inputs	5-13
5.6.2	Key Findings	5-14
5.7	Uncertainties and Limitations	5-16
6	Impacts of the Final Rule in the Context of National and Regional Electricity Markets	6-1
6.1	Model Analysis Inputs and Outputs	6-3
6.1.1	Analysis Y ears	6-3
6.1.2	Key IPM Inputs for the Electricity Market Analysis of the Final Rule	6-4
6.1.3	Key Outputs of the Electricity Market Analysis Used to Assess the Effects of the Final Rule	6-6
6.2	Regulatory Options Analyzed	6-8
6.3	Findings from the Electricity Market Analysis	6-10
6.3.1	Analysis Results forthe Year 2030 - To Reflect Steady-State, Post-Compliance Operations	6-10
6.3.2	Analysis Results for 2020 - To Capture the Effect of Technology-Installation Downtime	6-22
6.4	Uncertainties and Limitations	6-25
7	Total Social Costs	7-1
7.1	Analysis Approach and Data Inputs	7-1
7.2	Key Findings for Regulatory Options	7-4
7.2.1	Costs of Regulatory Compliance	7-4
7.2.2	Costs of Government Administration of Regulatory Requirements	7-5
7.2.3	Total Social Cost	7-7
8	Social Costs and Benefits	8-1
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8.1	Summary of Benefits Estimation for the Final Rule	8-1
8.2	Comparison of Benefits and Social Costs by Option	8-2
9	Employment Effects	9-1
9.1	Assessing Employment Effects of Regulations	9-2
9.1.1	General Considerations	9-2
9.1.2	Employment in the Electric Power Industry	9-5
9.1.3	Employment in the Primary Manufacturing Industries	9-6
9.2	Current State of Knowledge Based on the Peer-Reviewed Literature	9-12
9.2.1	Regulated Industry Sectors	9-13
9.2.2	Environmental Protection Sector	9-13
9.3	Macroeconomic Net Employment Impacts	9-14
9.4	Overall Analysis Conclusion	9-14
10	Impacts on Small Entities - Regulatory Flexibility Act (RFA) Analysis	10-1
10.1	Analysis of Electric Generators	10-3
10.1.1 Analysis Approach and Data Inputs	10-3
10.1.2Findings for Regulatory Options	10-6
10.2	Analysis of Manufacturers	10-8
10.2.1 Analysis Approach and Data Inputs	10-8
10.2.2Findings for Regulatory Options	10-12
10.3	Uncertainties and Limitations	10-13
11	Unfunded Mandates Reform Act (UMRA) Analysis	11-1
11.1	UMRA: Analysis of Impact on Government Entities	11-3
11.1.1	Compliance Costs	11-3
11.1.2	Administrative Costs	11-4
11.2	UMRA: Analysis of Impact on Small Governments	11-5
11.3	UMRA: Analysis of Impact on the Private Sector	11-6
11.4	UMRA: Analysis Summary	11-7
12	Other Administrative Requirements	12-1
12.1	Executive Order 12866: Regulatory Planning and Review and Executive Order 13563: Improving
Regulation and Regulatory Review	12-1
12.2	Executive Order 12898: Federal Actions to Address Environmental Justice in Minority Populations and
Low-Income Populations	12-2
12.2.1	Presence of Low-Income Populations in the Benefit Population	12-4
12.2.2	Assessment of Presence of Minority Populations in the Benefit Population	12-8
12.2.3	Overall Finding	12-8
12.3	Executive Order 13045: Protection of Children from Environmental Health Risks and Safety Risks .... 12-11
12.4	Executive Order 13132: Federalism	12-11
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12.5	Executive Order 13158: Marine Protected Areas	12-12
12.6	Executive Order 13175: Consultation and Coordination with Indian Tribal Governments	12-14
12.7	Executive Order 13211: Actions Concerning Regulations That Significantly Affect Energy Supply,
Distribution, or Use - Statement of Energy Effects	12-14
12.7.1 Impact on Electricity Generation	12-15
12.7.2Impact on Electric Generating Capacity	12-15
12.7.3	Impact on Cost of Energy Production	12-16
12.7.4	Dependence on Foreign Supply of Energy	12-16
12.7.5	Impact on Coal Production	12-17
12.7.6	Overall E.O. 13211 Finding	12-17
12.8	Paperwork Reduction Act of 1995 	12-17
12.9	National Technology Transfer and Advancement Act	12-18
References	R-l
Appendix A Profile of the Aluminum Industry	A-l
A. 1 Introduction	A-l
A.2 Summary Insights from this Profile	A-2
A.2.1 Likely Ability to Pass Compliance Costs Through to Customers	A-2
A.2.2 Financial Health and General Business Outlook	A-3
A.3 Domestic Production	A-3
A.3.1 Output	A-4
A.3.2 Prices	A-7
A.3.3 Number of Facilities and Firms	A-8
A.3.4 Employment and Productivity	A-l 1
A.3.5 Capital Expenditures	A-13
A.3.6 Capacity Utilization	A-14
A.4 Structure and Competitiveness	A-16
A.4.1 Firm Size	A-16
A.4.2 Concentration Ratios	A-17
A.4.3 Foreign Trade	A-18
A.5 Financial Condition and Performance	A-22
A.6	Facilities Operating Cooling Water Intake Structures	A-24
A.6.1 Waterbody and Cooling Water Intake System Type	A-25
A.6.2 Facility Size	A-25
A.6.3 Firm Size	A-25
Appendix B Profile of the Chemicals and Allied Products Industry	B-l
B.	1 Introduction	B-l
B.2 Summary Insights from this Profile	B-4
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B.2.1 Likely Ability to Pass Compliance Costs Through to Customers	B-4
B.2.2 Financial Health and General Business Outlook	B-4
B.3 Domestic Production	B-5
B.3.1 Output	B-5
B.3.2 Prices	B-9
B.3.3 Number of Facilities and Firms	B-9
B.3.4 Employment and Productivity	B-l 1
B.3.5 Capital Expenditures	B-13
B.3.6 Capacity Utilization	B-14
B.4 Structure and Competitiveness	B-15
B.4.1 Firm Size	B-15
B.4.2 Concentration Ratios	B-16
B.4.3 Foreign Trade	B-19
B.5 Financial Condition and Performance	B-24
B.6	Facilities Operating Cooling Water Intake Structures	B-28
B.6.1 Waterbody and Cooling System Type	B-29
B.6.2 Facility Size	B-29
B.6.3	Firm Size	B-29
Appendix C Profile of Food and Kindred Products Industry	C-l
C.	1 Introduction	C-l
C.2 Summary Insights from this Profile	C-2
C.2.1	Likely Ability to Pass Compliance Costs Through to Customers	C-2
C.2.2 Financial Health and General Business Outlook	C-2
C.3 Domestic Production	C-3
C.3.1 Output	C-4
C.3.2 Prices	C-6
C.3.3 Number of Facilities and Firms	C-7
C.3.4 Employment and Productivity	C-9
C.3.5 Capital Expenditures	C-l 1
C.3.6 Capacity Utilization	C-12
C.4 Structure and Competitiveness	C-13
C.4.1 Firm and Facility Size	C-14
C.4.2 Concentration Ratios	C-15
C.4.3 Foreign Trade	C-16
C.5 Financial Condition and Performance	C-l8
C.6 Facilities Operating Cooling Water Intake Structures	C-20
C.6.1 Waterbody and Cooling System Type	C-20
C.6.2 Facility Size	C-20
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C.6.3	Firm Size	C-21
Appendix D Profile of the Paper and Allied Products Industry	D-l
D. 1 Introduction	D-l
D.2 Summary Insights from this Profile	D-2
D.2.1	Likely Ability to Pass Compliance Costs Through to Customers	D-3
D.2.2 Financial Health and General Business Outlook	D-3
D.3 Domestic Production	D-3
D.3.1 Output	D-4
D.3.2 Prices	D-7
D.3.3 Number of Facilities and Firms	D-8
D.3.4 Employment and Productivity	D-l 1
D.3.5 Capital Expenditures	D-13
D.3.6 Capacity Utilization	D-14
D.4 Structure and Competitiveness	D-16
D.4.1 Firm Size	D-17
D.4.2 Concentration Ratios	D-17
D.4.3 Foreign Trade	D-l8
D.5 Financial Condition and Performance	D-22
D.6	Facilities Operating Cooling Water Intake Structures	D-24
D.6.1 Waterbody and Cooling System Type	D-25
D.6.2 Facility Size	D-25
D.6.3	Firm Size	D-26
Appendix E Profile of the Petroleum Refining Industry	E-l
E.	1 Introduction	E-l
E.2 Summary Insights from this Profile	E-2
E.2.1	Likely Ability to Pass Compliance Costs Through to Customers	E-2
E.2.2 Financial Health and General Business Outlook	E-2
E.3 Domestic Production	E-3
E.3.1 Output	E-3
E.3.2 Prices	E-6
E.3.3 Number of Facilities and Firms	E-7
E.3.4 Employment and Productivity	E-8
E.3.5 Capital Expenditures	E-10
E.3.6 Capacity Utilization	E-l 1
E.4 Structure and Competitiveness	E-12
E.4.1 Firm Size	E-13
E.4.2 Concentration Ratios	E-13
E.4.3 Foreign Trade	E-14
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E.5 Financial Condition and Performance	E-17
E.6	Facilities Operating Cooling Water Intake Structures	E-19
E.6.1 Waterbody and Cooling Water Intake System Type	E-19
E.6.2 Facility Size	E-20
E.6.3	Firm Size	E-20
Appendix F Profile of the Steel Industry	F-l
F.	1 Introduction	F-l
F.2 Summary Insights from this Profile	F-3
F.2.1	Likely Ability to Pass Compliance Costs Through to Customers	F-3
F.2.2 Financial Health and General Business Outlook	F-3
F.3 Domestic Production	F-4
F.3.1 Output	F-5
F.3.2 Prices	F-8
F.3.3 Number of Facilities and Firms	F-9
F.3.4 Employment and Productivity	F-l 1
F.3.5 Capital Expenditures	F-13
F.3.6 Capacity Utilization	F-14
F.4 Structure and Competitiveness	F-15
F.4.1 Firm Size	F-15
F.4.2 Concentration Ratios	F-16
F.4.3 Foreign Trade	F-17
F.5 Financial Condition and Performance	F-19
F.6	Facilities Operating Cooling Water Intake Structures	F-21
F.6.1 Waterbody and Cooling Water Intake System Type	F-22
F.6.2 Facility Size	F-22
F.6.3	Firm Size	F-23
Appendix G Profile of Facilities in Other Industries	G-l
G.	1 Facilities Operating Cooling Water Intake Structures	G-2
G.	1.1 Waterbody and Cooling System Types	G-3
G.1.2 Facility Size	G-3
G.	1.3 Entity Size	G-3
Appendix H Use of Sample Weights in the Final Rule Analyses	H-l
H.	1 Facility-Level Weights	H-2
H.	1.1 Electric Generators	H-2
H. 1.2 Manufacturers	H-7
H.2 Entity-Level Weights	H-10
H.2.1 Electric Generators	H-10
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H.2.2	Manufacturers	H-13
H.3	Summary	H-16
Appendix I Compliance Technology Effects that Impose Costs Via Impact on Revenue or Energy
Requirements	1-1
I.1	Energy Penalty	1-2
I.1.1	Electric Generators	1-2
1.1.2 Manufacturers	1-5
1.2	Auxiliary Energy Requirement	1-6
1.2.1	Electric Generators	1-7
1.2.2	Manufacturers	1-7
1.3	Technology Installation Downtime	1-8
1.3.1	Electric Generators	1-9
1.3.2	Manufacturers	1-11
Appendix J Mapping Manufacturers' Standard Industrial Classification Codes to North American
Industry Classification System Codes	J-l
Appendix K Cost Pass-Through Analysis	K-l
K. 1 The Choice of Facility-Specific versus Industry-Specific CPT Coefficients	K-l
K.2 Market Structure Analysis	K-3
K.2.1 Industry Concentration	K-3
K.2.2 Import Competition	K-6
K.2.3 Export Competition	K-7
K.2.4 Long-Term Industry Growth	K-8
K.3 Conclusions	K-9
Appendix L Adjusting Baseline Facility Cash Flow	L-l
L. 1 Background: Review of Overall Business Conditions	L-l
L.2 Framing and Executing the Analysis	L-5
L.2.1 Methodology for Development of ATCF Adjustment Factors	L-6
L.3 Analysis Results	L-7
Appendix M Estimating Capital Outlays for Discounted Cash Flow Analyses - Manufacturers	M-l
M.l Analytic Concepts Underlying Analysis of Capital Outlays	M-2
M.2 Specifying Variables for the Analysis	M-5
M.3 Selecting the Regression Analysis Dataset	M-7
M.4 Specification of Models to be Tested	M-9
M. 5 Model V alidation	M-12
M.6 Updating Inputs to Estimate Capital Outlays for the Final Rule	M-l9
Appendix N Analysis of Other Regulations - Manufacturers	N-l
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N. 1 Regulations Potentially Affecting Manufacturers	N-l
N.2 Methodology	N-2
N.2.1 Determination of Applicability to 316(b) Manufacturing Facilities	N-2
N.2.2 Estimating Facility-Level Costs	N-3
N.3 Results	N-5
N.3.1 Baseline Analysis	N-5
N.3.2 Post-Compliance Analysis	N-5
Appendix O Economic Impact Methodology - Manufacturers	O-l
0.1 Facility-Level Impacts: Severe Impact Analysis	0-1
0.1.1 Calculation of Baseline Free Cash Flow and Performance of Baseline Closure Test	0-1
0.1.2 Calculation of Post-Compliance Free Cash Flow and Performance of Post-Compliance Closure
Test	0-5
0.2 Facility-Level Impacts: Moderate Impact Analysis	0-8
0.2.1 Calculation of Moderate Impact Metrics	0-8
0.2.2 Developing Threshold Values for Pre-Tax Return on Assets (PTRA)	O-IO
0.2.3 Developing Threshold Values for Interest Coverage Ratio (ICR)	0-11
Appendix P Overview of the Integrated Planning Model	P-l
P. 1 Overview of the Integrated Planning Model	P-l
P.2 Key Specifications of the IPM V4.10_MATS Platform	P-2
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 1: Introduction and Executive Summary
1 Introduction and Executive Summary
1.1 Background
This document (the Economic Analysis or EA) provides analytical support to EPA's Final Existing Facilities Rule
(hereafter referred to as the final rule). This rule implements Clean Water Act (CWA) 316(b) requirements
governing cooling water intake structures at existing facilities that (1) are designed to withdraw more than two
million gallons per day (mgd) of water from rivers, streams, lakes, reservoirs, estuaries, oceans, or other waters of
the United States, and (2) use at least 25 percent of this water for cooling purposes. The national requirements,
which will be implemented through National Pollutant Discharge Elimination System (NPDES) permits, are
based on the best technology available (BTA) to minimize the adverse environmental impact associated with the
use of cooling water intake structures.
This is EPA's third effort to establish CWA 316(b) requirements for existing facilities, which includes facilities in
the electric power industry (Electric Generators) and any other industries where facilities meet the rule's
applicability criteria. Because these non-power industry facilities are mostly in manufacturing industries, EPA
refers to them as Manufacturers, but this term includes facilities in other non-power generating industries as well.
EPA's two preceding efforts are:
1.	The suspended 2004 Final Section 316(b) Phase II Existing Facilities Rule (suspended 2004 Phase II
Final Rule or Phase II Final Rule), which applied to existing electric power facilities with a design intake
flow (DIF) of 50 mgd or greater, and
2.	The 2006 Final Section 316(b) Phase III Existing Facilities Rule (2006 Phase III Final Rule or Phase III
Final Rule), which applied to existing electric power facilities with a DIF of less than 50 mgd and
existing manufacturing facilities above two mgd.
Both of these rules were challenged in court and subsequently remanded to EPA for further rulemaking.
Specifically, in 2004, EPA published the Phase II Final Rule applicable to existing power facilities (69 FR 41576
(July 9, 2004)). However, in response to a remand order from the Second Circuit Court of Appeals in 2007, EPA
suspended the Phase II regulation. In a later rulemaking in 2006, EPA published the Phase III Final Rule, which
establishes categorical regulations for certain new offshore oil and gas extraction facilities, and establishes that
316(b) requirements for electric power facilities with a DIF of less than 50 mgd and existing manufacturing
facilities should be established by the NPDES Permit Director on a site-specific basis using best professional
judgment. In 2010, the Fifth Circuit Court of Appeals accepted EPA's request to remand the existing facility
portion of the Phase III rule to the Agency for further rulemaking.
In response to these court rulings, EPA initiated development of new CWA 316(b) requirements for existing
electric power facilities and manufacturing facilities. As a result of this effort, EPA published the Proposed
Section 316(b) Existing Facilities Rule in April 2011 (proposed rule) and two Notices of Data Availability (Notice
of Data Availability Related to Impingement Mortality Control Requirements and Notice of Data Availability
Related to the EPA Stated Preference Survey, referred to as the NODAs). Following receipt of public comments
and reassessment of the regulatory options, EPA is now publishing the final rule. This final rule culminates EPA's
actions to re-promulgate regulatory provisions to replace the suspended 316(b) requirements.
Throughout this document, EPA refers to the suspended 2004 Phase II Final Rule, the 2006 Phase III Final Rule,
and the proposed rule as previous 316(b) regulations.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 1: Introduction and Executive Summary
This document describes EPA's analysis of the cost and economic impacts conducted in support of the final rule.
It also provides information pertaining to legislative and administrative requirements. This document
complements and builds on information presented separately in other reports, including:
>	Technical Development Document for the Final Section 316(b) Existing Facilities Rule (TDD) (U.S.
EPA, 2014d). The TDD provides background on the final rule; discusses applicability and summarizes
the final rule; and documents EPA's engineering analyses to support the development of technology and
administrative costs to facilities to implement the rule and costs to States and federal government to
administer the rule.
>	Benefits Analysis for the Final Section 316(b) Existing Facilities Rule (BA) (U.S. EPA, 2014a). The BA
summarizes the societal benefits expected to result from implementation of the final rule.
1.2 Overview of the Economic Analysis of the Final Rule
1.2.1 Facilities Subject to the Final Rule
As stated above, the final rule applies to facilities in the electric power and other industries (1) with intakes
designed to withdraw more than two million gallons of water per day from waters of the United States and (2) that
use at least 25 percent of this water for cooling purposes (regulated facilities, or Electric Generators and
Manufacturers). EPA identified the universe of Electric Generators and Manufacturers based on responses to the
2000 Detailed Industry Questionnaire (DO), the 2000 Industry> Short Technical Questionnaire (STO), and the
1999 Industry Screener Questionnaire (ISO) (throughout this document, these are referred to as the 316(b)
survey) developed for the previous 316(b) regulations.1 From these surveys, EPA determined that the vast
majority of Manufacturers conduct their primary business2 in the following six industries: Aluminum, Chemicals
and Allied Products, Food and Kindred Products, Paper and Allied Products, Petroleum Refining, and Steel
Industries (Primary Manufacturing Industries). EPA also identified in the survey responses some cooling water-
dependent facilities whose principal operations lie in businesses other than the electric power industry or the
Primary Manufacturing Industries. EPA refers to these additional industries as "Other Industries," but refers to
facilities in these industries under the broad terminology of Manufacturers.3
The final rule includes provisions applicable to existing units and new units at these facilities. EPA uses the term
final, rule-existing units to refer to the existing unit provision of the final rule and the analyses pertaining to the
existing unit provision; the term final, rule-new units refers to the provision of the final rule for new units and the
analyses pertaining to the new unit provision.
Final Rule-Existing Units
EPA estimates that 544 Electric Generators, 509 Manufacturers in six Primary Manufacturing Industries, and 12
Manufacturers in Other Industries will be subject to the existing unit provision of the final rule.
Electric Generators
EPA's analyses indicate that the Electric Generators represent substantial shares of the electric power industry:
approximately 46 percent of total electric power generating capacity, approximately 9 percent of all electric power
1	For more information on the 316(b) survey, refer to the Information Collection Request (U.S. EPA, 2000).
2	Manufacturers may engage in more than one industry; in particular, Manufacturers often generate electricity, both for onsite use and
for sale to the electric power grid.
3	These industries are: Crop Production, Mining (Except Oil and Gas), Textile Mills, Wood Product Manufacturing, Primary Metal
Manufacturing, Transportation Equipment Manufacturing, and Miscellaneous Manufacturing.
1-2
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 1: Introduction and Executive Summary
facilities, and approximately 5 percent of all parent entities in the overall electric power industry Table 1-1). For
detailed information on the electric power industry, see Chapter 2A: Profile of the Electric Power Industry.
Table 1-1: Electric Generators Share of Electric Power Industry: Facilities, Parent
Entities, and Total Capacity in 2011

Regulated Electric Generators

Electric Power Industry3
Numberb
% of Total
Parent Entities
2,905
159
5.5%
Facilities
6,058
544
9.0%
Capacity (MW)
1,153,044
529,463
45.9%
a. Data for electric power industry are from the 2011 EIA-860 database (U.S. DOE, 2011b) and 2011 EIA-861 database (U.S.
DOE, 2011c).

b. Facility counts are sample-weighted estimates, generated using original survey weights. For details, see Appendix H.
Source: U.S. EPA analysis for this report; U.S. DOE, 2011b; U.S. DOE, 2011c
As reported in Table 1-2, approximately half of the Electric Generators draw water from a freshwater river (283
facilities or 52 percent), followed by lakes or reservoirs (115 facilities or 21 percent) and estuaries or tidal rivers
(88 facilities or 16 percent). Table 1-2 also reports that almost two thirds of the regulated facilities (343 facilities
or 63 percent) employ a once-through cooling system. Approximately 27 percent for facilities (149 facilities)
currently have a closed-cycle recirculating system (CCRS) for their cooling water system. EPA expects that
facilities with a properly operated CCRS would not generally need to install additional technology to comply with
the BTA standard of the final rule-existing units and did not include costs for additional compliance technology
for facilities with a qualified CCRS.
Table 1-2: Number of Electric Generators by Waterbody and Cooling Water
System Type3'

Waterbody Type
CCRSC
Once-Through
Combination
Other
Total
Estuarv/Tidal River
5
72
9
1
88
Freshwater Stream/River
103
147
29
3
283
Great Lake
4
32
2
0
38
Lake/Reservoir
36
71
7
1
115
Ocean
0
20
0
0
20
Total
149
343
47
5
544
a. Individual values may not sum to totals due to independent rounding.

b. Facility counts are sample-weighted estimates, generated using original survey weights. For details, see Appendix H.
c. As explained at page 1-6, the final rule includes
a provision in which facilities with cooling water system
impoundments may qualify as baseline CCRS and may not need to install additional technology for compliance. EPA
identified 40 Electric Generators with cooling water system impoundments and that may qualify as baseline CCRS under
the final rule. These facilities are included in the count of facilities with CCRS.

Source: U.S. EPA, 2000

Manufacturers
Table 1-3 presents industry-wide facility counts and counts of regulated facilities, by industry, for the Primary
Manufacturing Industries and Other Industries. The Petroleum Refining Industry accounts for the largest share of
Manufacturers (11 percent of the estimated regulated total), while facilities in the Aluminum, Paper and Allied
Products, and Steel Industries make up the second largest category (4 percent).
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 1: Introduction and Executive Summary
Table 1-3: Industry-Wide and Regulated Manufacturing Facilities, by Industry3 0
Industry
Industry Total
Regulated
Facilities
Regulated % of
Industry Total
Primary Manufacturing Industries
Aluminum
583
22
4%
Chemicals and Allied Products
13,138
175
1%
Food and Kindred Products
4,119
34
1%
Paper and Allied Products
4,706
194
4%
Petroleum Refining
303
35
11%
Steel
1,233
48
4%
Total - Primary Manufacturing Industries
24,082
509
2%
Other Industries
NA
12
NA
a. Individual values may not sum to totals due to independent rounding.
b. These are sample-weighted estimates of the number of Manufacturers, calculated using technical weights. This number
excludes 67 facilities estimated to be at substantial risk of financial failure regardless of any additional financial burden that
might result from the final rule. For details see Appendix H.
Source: U.S. DOC, 2009 SUSB; U.S. EPA, 2000

As reported in Table 1-4, EPA estimates that the vast majority (76 percent) of Manufacturers withdraw cooling
water from freshwater streams or rivers, followed by lakes and reservoirs (8 percent). Almost half of the
Manufacturers employ once-through cooling systems (47 percent), followed by "combination" systems (22
percent) and CCRS (20percent)4
Table 1-4: Number of Manufacturers by Waterbody and Cooling-System Typea'D'c tl'e
Waterbody Type
CCRS
Once-Through
Combination
Other
Unknown
Total
Estuarv/Tidal River
1
21
16
0
0
38
Freshwater Stream/River
95
185
79
34
4
397
Great Lake
0
21
10
7
0
38
Lake/Reservoir
7
13
12
11
0
42
Ocean
0
5
0
0
0
5
Total
103
245
117
52
4
521
a. Individual values may not sum to totals due to independent rounding.

b. These are sample-weighted facility counts, calculated using technical weights. This number excludes 67 baseline-closure facilities that EPA estimated to
be at substantial risk of financial failure regardless of any additional financial burden that might result from the final rule or other considered options. For
details see Appendix H.
c. Includes facilities in the Primary Manufacturing Industries and Other Industries.

d. Four facilities have an unknown cooling water system type

e. As explained at page 1-6, the final rule includes a provision in which facilities with cooling water system impoundments may qualify as baseline CCRS
and may not need to install additional technology for compliance. EPA identified 24 Manufacturers with cooling water system impoundments and that may
qualify as baseline CCRS under the final rule. These facilities are included in the count of facilities with CCRS.

Source: U.S. EPA, 2000

Final Rule-New Units
The new unit provision of the final rule applies to newly constructed, stand-alone electric power generating units
at existing facilities. Unlike the analysis for the existing unit provision, EPA cannot predict the facilities at which
new construction will take place, or the number and size of new units. Instead, EPA estimated the potential
coverage of the new unit provision of the final rule based on the quantity of electric power generating capacity
that will come online and be subject to the new unit provision in future years. In addition, EPA considered a range
of options for the new unit provision of the final rule, each of which would cover a different quantity of new unit
capacity.
4 Not all Manufacturers that have installed a cooling tower are classified as using CCRS. Facilities with multiple cooling water systems
may be "combination" systems that employ both closed-cycle and once-through cooling. Manufacturers may also list "helper" cooling
towers in their survey responses, which are generally used to mitigate discharge temperatures and do not necessarily reduce intake
flows.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 1: Introduction and Executive Summary
Table 1-5 reports capacity subject to the final rule and other new unit options EPA considered. Section 1.2.2
describes the coverage specifications for the new unit provision of the final rule and other new unit options
considered.
Table 1-5: Estimated Annual Average Generating Capacity
Subject to New Unit Provision

Option
Affected Capacity (MW)
Option A
2,055
Option B
840
Option C
116
Final Rule - New Units
23
Source: U.S. EPA analysis for this report
1.2.2 Final Rule and Other Options Considered
In developing the final rule, EPA considered three options for existing units, and four options for new units.
Final Rule-Existing Units
EPA considered and analyzed three options for existing units. All of the options apply to existing facilities with
DIF greater than two mgd, and include impingement mortality (IM) technology-based, performance standards.
The options vary by the DIF level at which the uniform IM technology standards apply and by whether facilities
would be required to meet entrainment control technology-based standards, again based on DIF level. In addition,
the existing unit options include provisions for site-specific determination of whether entrainment technology-
based standards would be required at facilities. Each option draws from one of the options that EPA analyzed for
the proposed rule.
> Final Rule (similar to Proposal Option 1 but with IM flexibilities outlined in NODA 1 and recalculated
limits): IMat Existing Facilities With DIF Greater than two mgd; Entrainment Controls for Facilities
Greater than two mgd DIF Determined on a Site-Specific Basis: Under the existing unit provision of the
final rule, existing facilities subject to this rule must comply with one of seven alternatives identified in
the national BTA standard for IM. EPA identified modified traveling screens with a fish return system as
the technology basis for this performance standard. In addition, permitting authorities may establish
entrainment controls as BTA on a site-specific basis for facilities with at least two mgd DIF. EPA expects
all regulated facilities to install IM controls in accordance with the existing units requirements by 2022.
> Proposal Option 4: IM Controls at Existing Facilities with DIF of 50 mgd or Greater; Best Professional
Judgment-based Permits for Existing Facilities with Design Intake Flow Less than 50 mgd but Greater
than two mgd DIF. Proposal Option 4 is the same as the final rule in all respects except that Proposal
Option 4 requires only existing facilities with DIF of 50 mgd or greater to achieve the uniform national
IM design/performance standard. These facilities are also subject to site-specific entrainment
determinations. Existing facilities between 2 and 50 mgd would remain subject to 316(b) permitting based
on best professional judgment (BPJ) for both IM and entrainment control design/performance standard. In
analyzing this option, EPA assumed that all Electric Generators and Manufacturers required to install IM
controls would do so by 2022.
> Proposal Option 2; IM for Facilities With DIF Above two mgd and Entrainment Controls for Existing
Facilities with DIF of 125 mgd or Greater. Under this option, existing facilities with a cooling water
intake with a DIF exceeding 125 mgd would be required to meet performance standards based on IM and
entrainment control technology. Standards for entrainment control technology would be set equivalent to
intake flow levels for closed-cycle cooling. All other existing facilities would be required to meet IM
technology-based performance standards only. In addition, entrainment controls would be established by
the permitting authority on a site-specific basis for all facilities with DIF less than 125 mgd. In analyzing
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 1: Introduction and Executive Summary
this option, EPA assumed that Manufacturers and non-nuclear Electric Generators would install
entrainment controls by 2025, nuclear Electric Generators would install entrainment controls by 2030,
and all Electric Generators and Manufacturers required to install IM controls would do so by 2022.
As described in Section I. G. of the Preamble for the final existing facilities rule, and as defined at §125.92,
Special definitions, (c) (2) of the final rule, CCRS includes a system with impoundments of waters of the United
States where the impoundment was lawfully created for the purpose of serving as part of the cooling water system
(hereafter referred to as the Impoundments Provision). Under this provision, facilities with qualifying
impoundments of waters of the United States are subject to the final rule, but may meet the rule's BTA standard
for impingement mortality through operation of a CCRS in the baseline.5 EPA identified 64 regulated facilities
that operate a cooling water system with an impoundment in their baseline; EPA expects that most of these
facilities will qualify as baseline CCRS, and would meet the final rule's performance standard without additional
compliance technology. Therefore, unless otherwise stated, in the analyses of the existing unit provision of the
final rule and other options considered,6 EPA did not assign costs for additional compliance technology to those
facilities and assigned administrative costs commensurate with baseline CCRS.7
Final Rule-New Units
In developing the new unit provision of the final rule, EPA considered four options, each of which includes
specifications requiring that new stand-alone and/or repowered units at an existing facility with DIF exceeding
two mgd meet technology performance standards commensurate to those required of a new facility under the
316(b) Phase I rule.8 These standards require entrainment control technology performance equivalent to the intake
flow levels that would be achieved by a CCRS. EPA considered two categories of new units at an existing facility
as candidates for coverage under the new unit provision: (1) a newly built, stand-alone generating unit,9 that is
constructed at an existing facility and does not meet the definition of a new facility and (2) an existing unit that is
rebuilt, replaced or repowered (generally referred to simply as repowered) where a new condenser and turbine are
built and undergoes significant modifications. In all four of the new unit options EPA considered, all of the new
units falling in the first category would be subject the new unit provision of the final rule. The options considered
by EPA vary by the definition of new units of the second category that would be subject to the entrainment
controls-based performance standard (i.e., CCRS). For any of the options considered, new units in the second
category that would not be subject to the entrainment control-based performance standard would instead be
regulated under the BTA standard applicable to existing units.
In developing the final rule, EPA considered and analyzed the following four options; these options differ based
on the type of modifications at repowering units:
The final rule also specifies that Permit Directors will determine whether an impoundment minimizes the withdrawal of water for
cooling purposes and would therefore meet the CCRS definition. As a result, in some cases, facilities with cooling water system
impoundments may not qualify as baseline CCRS and would need to install additional technology to meet the final rule's BTA
standard for impingement mortality.
6	For Proposal Option 2, EPA also assumed that these facilities will meet entrainment technology requirements, as applicable.
7	EPA also assessed the cost, economic impact, and benefits of the final rule and other options EPA considered, assuming that none of
the facilities with cooling water system impoundments would qualify as baseline CCRS (see Memorandum to the Record (DCN 12-
2501)). Whether these facilities qualify as baseline CCRS and, further, whether they incur additional technology cost, was not a factor
in EPA's determination of BTA for the final rule.
8	For details on the Phase I Final New Facilities Rule, see http://water.epa.gOv/lawsregs/lawsguidance/cwa/316b/phasel/index, cfm.
9	The term stand-alone in this context refers to the definitions established in the Phase I Rule. Per Phase I 316(b), at 125.83: "A stand-
alone facility is a new, separate facility that is constructed on property where an existing facility is located and whose processes are
substantially independent of the existing facility at the same site (see 40 CFR 122.29(b)(l)(iii))."
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 1: Introduction and Executive Summary
>	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 only those replaced
or repowered units in which the existing unit's turbine and condenser are newly built or replaced.
>	Option C: Entrainment performance requirements for all stand-alone or new units, and for repowered
new units where the turbine and condenser are newly built or replaced, but excluding high efficiency
systems. This option is the same as Option B, except that repowered or replaced units that meet the
criteria for high efficiency systems are excluded. High efficiency generating systems, which are defined
as those that achieve a thermal conversion heat rate of 7,000 Btu per kWh after being repowered, already
use a considerably smaller amount of cooling water per megawatt (MW) of power generated. For
example, a combined cycle generating system may use nearly half as much cooling water for the same
generating output capacity as a coal-fired unit. This option recognizes the inherent benefit of highly
efficient systems and is intended to provide an incentive for greater implementation of high efficiency
systems. The exclusion may also apply to cogeneration systems as well, if they meet the criterion.
>	Final Rule (Option D): Entrainment performance requirements for all stand-alone new units. Under this
option, none of the second category of new units - replaced or repowered units where the turbine and
condenser are newly built or replaced - would be subject to the performance standard based on
entrainment requirements. This is equivalent to the compliance requirements for new units as analyzed in
support of the proposed rule.
For details on specific technologies considered for the final rule and other options EPA considered, see the TDD;
see the Federal Register notice and rule language for further discussion of regulatory requirements.
1.2.3 Analyses Performed in Support of the Final Rule
The cost and economic impact 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) activities 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 the 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 quality 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.
Generally, in performing analyses of the final rule and other options considered, EPA followed closely the
analysis approaches and impact evaluation concepts used in the analysis for the previous 316(b) analyses,
including the proposed rule, and to the extent possible, relied on the same data sources.1" This document discusses
these analyses, the methodologies used to conduct them, and the analysis results as follows:
>	Chapter 2: Industry> Profiles provides a detailed description of the Electric Power Industry and a summary
of more detailed discussions of the six Primary Manufacturing Industries and Other Industries presented
in Appendices A through G of this document.
>	Chapter 3: Compliance Costs describes components of technology and administrative costs to facilities to
implement, and administrative costs to States and federal government to administer, the final rule and
other options EPA considered. This chapter also calculates the industry-wide compliance costs to the
10 For more details on these analyses see the suspended 2004 Phase II Final Rule EA report, the 2006 Phase III Final Rule EA report, and
the 2010 Proposed Rule EA report.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 1: Introduction and Executive Summary
Electric Power Industry, the six Primary Manufacturing Industries, and Other Industries. This chapter
presents cost estimates for existing units and new units.
>	Chapter 4: Economic Impact Analyses - Electric Generators analyzes the impact of the existing unit
provision of the final rule and other options considered on Electric Generators and their parent entities,
based on a cost-to-revenue analysis. This chapter also looks at the impacts of the existing unit provision
of the final rule and other options considered in terms of increased electricity prices for households and
for other consumers of electricity. Finally, this chapter analyzes the impact of the new unit provision of
the final rule on decisions to construct stand-alone and repower fossil fuel and combined cycle generating
units (the barrier-to-development analysis).
>	Chapter 5: Economic Impact Analyses - Manufacturers analyzes the impact of the final rule and other
options on the Manufacturers segment of regulated facilities in terms of severe impacts (i.e., facility
closures) and moderate impacts (i.e., adverse changes in a facility's financial position that are of lower
severity than closure). This chapter also analyzes impacts on their parent entities, based on a cost-to-
revenue comparison. EPA conducted this analysis only for existing units.
>	Chapter 6: Electricity Market Analysis analyzes the impacts of the final rule using the Integrated Planning
Model (IPM11) and provides insight into the effects that the final rule requirements will have on regulated
facilities and on the Electric Power Industry as a whole, at the national and regional levels.
r Chapter 7: Total Social Costs looks at the impact of the final rule and other options considered in terms
of total costs to society. EPA conducted this analysis for existing units and new units.
>	Chapter 8: Social Costs and Benefits compares the estimated total social costs of the final rule and other
options considered, to the estimated benefits. The detailed benefits analysis is presented in a separate
Benefits Analysis (BA) report. EPA conducted this analysis for existing units and new units.
>	Chapter 9: Employment Effects provides a qualitative assessment of the employment effects that will
accompany the final rule and analyzes national-level changes in employment in the environmental
protection sector. EPA conducted this analysis for existing units and new units.
>	Chapter 10: Regulatory Flexibility Act (RFA) Analysis addresses the requirements of the RFA and
analyzes the impact of the final rule and other options considered on small entities on the basis of a cost-
to-revenue comparison. EPA conducted this analysis only for existing units.
>	Chapter 11: Unfunded Mandates Reform Act (UMRA) Analysis addresses the requirements of UMRA by
analyzing the impact on government entities, both in terms of compliance costs to government-owned
Electric Generators and in terms of administrative costs to governments implementing the rule. This
analysis also compares the impacts to small governments with those of large governments and small
private entities. EPA conducted this analysis only for existing units.
>	Chapter 12: Other Administrative Requirements addresses the requirements of Executive Orders that EPA
is required to satisfy for this rule, notably Executive Order 13211, which requires EPA to determine
whether this action will have a significant effect on energy supply, distribution, or use. EPA conducted
this analysis only for existing units.
This document includes 15 appendices:
>	Appendices A-G: provide detailed descriptions of the six Primary Manufacturing Industries and the Other
Industries subject to the final rule.
11 IPM is a comprehensive electricity market optimization model that analyzes the impacts of environmental regulations and other
economic factors within the context of regional and national electricity markets. EPA has used IPM to analyze the impacts of various
regulatory actions affecting the electric power sector over the last decade, particularly Clean Air Act regulations.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 1: Introduction and Executive Summary
¦	Appendix A: Profile of Aluminum Industry
¦	Appendix B: Profile of the Chemicals and Allied Products Industry
¦	Appendix C: Profile of Food and Kindred Products Industry
¦	Appendix D: Profile of the Paper and Allied Products Industry
¦	Appendix E: Profile of the Petroleum Refining Industry
¦	Appendix F: Profile of the Steel Industry
¦	Appendix G: Other Industries
>	Appendix H: Sample Weights describes the development and use of sample weights for the cost and
economic impact analysis of the final rule and other options considered.
>	Appendix I: Energy Effects describes how EPA accounted for three technology-related cost and operating
effects: energy penalty, auxiliary energy requirement, and technology installation downtime.
>	Appendix J: SIC to NAICS Data Conversion discusses the mapping of the facility-level 4-digit SIC codes
for which the 316(b) survey-based facility information for Manufacturers was originally reported, onto 6-
digit NAICS codes for use in the current cost and economic impact analysis.
>	Appendix K: Cost Pass-Through Analysis analyzes the cost pass-through (CPT) potential for the six
Primary Manufacturing Industries.
>	Appendix L: Adjusting Baseline Facility Cash Flow describes EPA's development of adjustment factors
to bring certain 316(b) survey-based financial data for the six Primary Manufacturing Industries to the
present.
r Appendix M: Estimating Capital Outlays describes the analysis used to estimate ongoing capital outlays
for use in the facility-level cash flow analyses for Manufacturers.
>	Appendix N: Analysis of Other Regulations presents analysis of other environmental regulations that were
recently or will soon be promulgated, potentially imposing additional costs on Manufacturers beyond
those reflected in their baseline financial statements.
>	Appendix (): Economic Impact Methodology - Manufacturers provides supporting details on the cost and
economic impact analysis conducted for Manufacturers and discussed in Chapter 5 of this document.
>	Appendix P: Overview of the Integrated Planning Model provides an overview of IPM V4.10_MATS
platform, which is the basis of the electricity market analysis discussed in Chapter 6.
The following section summarizes the cost and economic impact analysis results.
1.3 Summary of Analysis Results
In reaching its decisions concerning the final rule, EPA analyzed the rule's overall cost, potential economic
impacts, and expected benefits. In some instances, EPA undertook different analyses for the existing and new unit
provisions of the final rule. The main findings from these analyses are summarized below. As described above at
page 1-6, the final rule includes a provision under which certain facilities with cooling water system
impoundments may be defined as baseline CCRS, and which may not need to install additional technology to
comply with the final rule's BTA standard for impingement mortality. EPA identified 64 regulated facilities with
an impoundment as part of the cooling water system; however, EPA does not know whether these facilities will
qualify as baseline CCRS and, further, will not need to install additional compliance technology. The results
summarized below assume that all of these facilities will qualify as baseline CCRS and will meet the final rule's
BTA standard for impingement mortality without additional technology:
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 1: Introduction and Executive Summary
>	EPA estimates that the final rule will result in total annual costs to society of approximately $275 million
at a 3 percent discount rate and $297 million at a 7 percent discount rate,12 accounting for both the new
unit and the existing unit provisions.
>	EPA estimates that the final rule - existing and new unit provisions - will result in national monetized
benefits to society of approximately $33 million annually at the 3-percent discount rate, and $29 million
annually at the 7-percent discount rate. Some potentially significant benefit categories have not been fully
monetized, and thus the national monetized benefits are likely to understate substantially the rule's
expected benefits to society.13
>	EPA analyzed whether the new unit provision of the final rule could constitute a barrier to building new
capacity that would be within the coverage of the final rule's new unit provision. Based on comparison of
the cost of a CCRS in relation to the cost of such new units, EPA concluded that the new unit provision
would minimally affect decisions to build new generating capacity, and thus would not constitute a barrier
to development of such opportunities.
>	Under the existing unit provision of the final rule, EPA estimates that the majority of Electric Generators
(86 percent) will incur compliance costs of less than 1 percent of revenue.
>	EPA estimates that none of the approximately 500 regulated Manufacturers facilities in the Primary
Manufacturing Industries will incur severe impacts (i.e., potentially close) as a result of the rule's existing
unit provision. EPA estimates that 12 facilities in the Primary Manufacturing Industries will experience
financial stress short of closure.
>	EPA estimates that between 123 and 159 parent entities own the regulated Electric Generators; the
majority of these parent entities (between 91 and 94 percent) will incur compliance costs of less than 1
percent of revenue under the existing unit provision of the final rule.
>	Between 120 and 337 entities own regulated facilities in the Primary Manufacturing Industries; a
substantial majority (between 108 and 319 entities, or between 90 and 95 percent) will incur costs of less
than 1 percent of revenue under the rule's existing unit provision. Ten entities own regulated facilities in
the Other Industries; the majority of these entities (seven entities or 70 percent) will incur costs of less
than 1 percent of revenue.
>	On average, across the United States, EPA estimates that the existing unit provision of the final rule will
increase electricity production costs by 0.009 cents per kWh, causing a 0.1 percent increase in average
electricity prices. This impact varies regionally by electric power market area, ranging from nearly zero
cents per kWh to 0.040 cents per kWh. The corresponding annual increase in electricity costs is
approximately $1.03 per household.
>	EPA estimates that the existing unit provision of the final rule will not materially affect national or
regional electricity markets on a long-term basis. In addition, the temporary capacity loss from
compliance-technology installation will not cause material reliability effects.
>	For the Regulatory Flexibility Act (RFA) analysis, EPA estimates that between 31 and 52 small entities
own 69 Electric Generators. Under the existing unit provision of the final rule, between zero and three of
these small entities will incur compliance costs exceeding 1 percent of revenue, representing between 0
and 10 percent of all small entities that own Electric Generators. EPA estimates that no small entities
owning Electric Generators will incur compliance costs exceeding 3 percent of revenue. For the
12	EPA used these discount rates to reflect how society values cost and benefit streams that extend into the future and vary over time. See
Chapter 3: Compliance Costs and Chapter 7: Total Social Costs.
13	See BA Chapter 4: Economic Benefit Categories of the Benefits Analysis for additional discussion of benefits categories monetized by
EPA.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 1: Introduction and Executive Summary
Manufacturers segment, EPA estimates that between 17 and 52 small entities own regulated facilities in
the Primary Manufacturing Industries. Under the existing unit provision of the final rule, EPA estimates
that three to four small entities that own Primary Manufacturing Industries facilities will incur costs
exceeding 1 percent of revenue (8 to 18 percent of small entities owning regulated facilities in the
Primary Manufacturing Industries), and zero to one small entities will incur costs exceeding 3 percent of
revenue (0 to 6 percent of small entities). In addition, EPA estimates that two entities in the Other
Industries will incur costs exceeding 1 percent of revenue, with no entity incurring costs exceeding 3
percent of revenue.
>	For the analyses required under Title II of the Unfunded Mandates Reform Act (UMRA) of 1995, Pub. L.
104-4, EPA estimates that for Electric Generators, the maximum cost to governments (excluding the
federal government) in any one year, for compliance with, and administration of, the existing unit
provision of the final rule, will be approximately $71 million and that the maximum cost to the private
sector in any given year (compliance cost only) will be approximately $0.8 billion. For Manufacturers,
these numbers are $1 million and $0.4 billion, respectively. Thus, EPA determined that the final rule
contains a federal mandate that may result in expenditures of $100 million or more for State, local, and
Tribal governments, in the aggregate, or the private sector in any one year. From the UMRA analysis,
EPA concluded that the rule's existing unit provisions will not significantly or uniquely affect small
governments, including Tribal governments, compared to large governments or small private entities for
in either the Electric Generators or Manufacturers segment.
>	EPA estimates that by 2030 the final rule may cause net retirement of approximately 1,000 MW of
generating capacity (i.e., permanent capacity losses). Based on the estimated early retirement of electric
generating capacity, EPA finds that the final rule is a significant energy action and may have a significant
adverse effect on the supply, distribution, or use of energy at a national or regional level in accordance
with Executive Order 13211: Actions Concerning Regulations That Significantly Affect Energy Supply,
Distribution, or Use. However, EPA views the potential loss of capacity as a comparatively minor impact
because of the projected low capacity utilization and associated low electricity supply contribution from
those electric generating units that are projected to retire.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2: Introduction to Industry Profiles
2 Introduction to Industry Profiles
EPA identified two broad industry categories as the most reliant on cooling water in their operations and thus
containing substantial numbers of facilities that will be subject to the final rule and other options EPA considered:
1.	Electric Generators
2.	Manufacturers - specifically six industries, the Primary Manufacturing Industries, as referred to in this
document:
¦	Paper and Allied Products (NAICS 322)
¦	Chemicals and Allied Products (NAICS 325)
¦	Petroleum Refining (NAICS 324)
¦	Steel (NAICS 3311 and 3312)
¦	Aluminum (NAICS 3313)
¦	Food and Kindred Products (NAICS 311 and 3121).
In addition, from the 316(b) survey, EPA identified that facilities in industries other than the Primary
Manufacturing Industries, including non-manufacturing industries, also use cooling water and will therefore be
subject to the final rule. However, based on EPA's reviews of industries" reliance on cooling water, the cooling
water intake flow of facilities in these remaining industries is small relative to that of the power industry and the
six Primary Manufacturing Industries. In this document, regulated facilities in industries other than the electric
power generating industry and the Primary Manufacturing Industries, are referred to as the Other Industries
facilities.
EPA prepared detailed economic profiles of the Electric Power Industry and the six Primary Manufacturing
Industries. These profiles review information on the industries" historical economic/financial performance,
structure, and economic outlook, and provide insight on how the requirements of the final rule will affect them. In
particular, the profiles assess the number of facilities that EPA expects will be subject to the final rule, economic
activity and employment in the regulated segments, and factors influencing the ability of these industries to meet
the final rule's compliance requirements without undue adverse economic impact. EPA also prepared a less-
detailed profile of the Other Industries facilities, focusing on characteristics of the small number of these facilities
that EPA identified as part of the 316(b) survey.
This chapter includes the detailed profile of the Electric Power Industry (Chapter 2A) and a summary profile for
the six industries comprising the Primary Manufacturing Industries (Chapter 2B).
The detailed profiles for the six Primary Manufacturing Industries are contained in the following appendices:
>	Appendix A: Paper and Allied Products (NAICS 322),
>	Appendix B: Chemicals and Allied Products (NAICS 325),
>	Appendix C: Petroleum Refining (NAICS 324),
>	Appendix D: Steel (NAICS 3311 and 3312),
>	Appendix E: Aluminum (NAICS 3313),
>	Appendix F: Food and Kindred Products (NAICS 311 and 3121),
Appendix G reviews information on facilities identified in the Other Industries group.
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Chapter 2A: Electric Power Industry Profile
2A Profile of the Electric Power Industry
2A.1 Introduction
This profile compiles and analyzes economic and operational data for the electric power generating industry. It
provides information on the structure and overall performance of the industry and describes important trends that
may influence the nature and magnitude of the final rule's economic impacts.
The Electric Power Industry is one of the most extensively studied industries. The Energy Information
Administration (EIA), among others, publishes a multitude of reports, documents, and studies on an annual basis.
This profile does not repeat those efforts. Rather, this profile compiles, summarizes, and presents those industry
data that are important in the context of the final rule.
The remainder of this profile is as follows:
>	Section 2A. 2 provides a brief overview of the industry, including descriptions of major industry segments,
types of generating facilities, and the entities that own generating facilities.
>	Section 2A.3 provides data on industry production, capacity, and geographic distribution.
>	Section 2A.4 focuses on the electric power facilities estimated to be subject to the final rule (or regulated
facilities);14 this section provides information on their physical, geographic, and ownership
characteristics.
>	Section 2A. 5 provides a brief discussion of factors affecting the future of the Electric Power Industry,
including the status of electric utility regulatory restructuring and ongoing changes in air quality
regulations.
>	Section 2A. 6 summarizes forecasts of market conditions through the year 2035 from the Annual Energy
Outlook 2012.
>	Section 2A. 7 provides a glossary of key terms used in this chapter.
2A.2 Industry Overview
This section provides a brief overview of the industry, including descriptions of major industry sectors, types of
generating facilities, and the entities that own generating facilities.
2A.2.1 Industry Sectors
The electricity business includes three major functional service components or sectors: generation, transmission,
and distribution, which are defined as follows (Joskow, 1997; U.S. DOE, 2007):
> The generation sector includes the facilities that produce, or "generate," electricity. A mechanically
driven rotary generator usually produces electric power. Generator drivers, also called prime movers,
include steam turbines; gas- or diesel-powered internal combustion machines; and turbines powered by
streams of moving fluid such as water from a hydroelectric dam. Most boilers are heated by direct
combustion of fossil or biomass-derived fuels, or waste heat from the exhaust of a gas turbine or diesel
14 This term regulatedfacilities is different from rate-regulated facilities and entities as discussed later in this chapter. Rate-regulated
facilities and entities are those that operate in a rate-regulation framework, in which a government regulatory authority sets prices at
which the rate-regulated facilities and entities sell generated electricity or other electricity-related services.
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Chapter 2A: Electric Power Industry Profile
engine, but heat from nuclear, solar, and geothermal sources is also used. Electric power may also be
produced without a generator by using electrochemical, thermoelectric, or photovoltaic (solar)
technologies.
>	The transmission sector is the network of large, high-voltage power lines that deliver electricity from
power generating facilities to local areas. Electricity transmission involves the "transportation" of
electricity from facilities to distribution centers using a complex system. Transmission requires
interconnecting and integrating a number of generating facilities into a stable, synchronized, alternating
current (AC) network; scheduling and dispatching all connected facilities to balance the demand and
supply of electricity in real time; and, managing the system for equipment failures, network constraints,
and interaction with other transmission networks.
>	The distribution sector is the local delivery system - the relatively low-voltage power lines that bring
power to homes and businesses. Electricity distribution relies on a system of wires and transformers along
streets and underground to provide electricity to residential, commercial, and industrial consumers. The
distribution system involves both the provision of the hardware (e.g., lines, poles, transformers) and a set
of retailing functions, such as metering, billing, and various demand management services.
Of the three industry sectors, only electricity generation produces the environmental impacts that are the focus of
this regulation. The remainder of this profile focuses on the generation sector of the industry.
2A.2.2 Prime Movers
Electric power facilities use a variety of prime movers to generate electricity. Several factors determine the choice
of prime mover in developing an electric power generating facility: the type of load that the facility will serve, the
availability of fuels, and energy requirements. Most prime movers use fossil fuels (coal, oil, and natural gas) as an
energy source and employ some type of turbine to produce electricity. According to the Department of Energy,
the most common prime movers are as follows (U.S. DOE, 2007):15
>	Steam Turbine: Most of the electricity in the United States is produced with steam turbines. In a fossil-
fueled steam turbine, the fuel is burned in a boiler to produce steam. The resulting steam then turns the
turbine blades that turn the shaft of the generator to produce electricity. In a nuclear-powered steam
turbine, the boiler is replaced by a reactor containing a core of nuclear fuel (primarily enriched uranium).
Heat produced in the reactor by fission of the uranium is used to make steam. The steam is then passed
through the turbine generator to produce electricity, as in the fossil-fueled steam turbine. Steam-turbine
generating units are used primarily to serve the base load of electric utilities. Fossil-fueled steam-turbine
generating units range in size (nameplate capacity) from one megawatt to more than 1,000 megawatts.
The size of nuclear-powered steam-turbine generating units in operation today ranges from 75 megawatts
to more than 1,400 megawatts.
>	Gas Turbine: In a gas turbine (combustion-turbine) unit, hot gases produced from the combustion of
natural gas and distillate oil in a high-pressure combustion chamber are passed directly through the
turbine, which spins the generator to produce electricity. Gas turbines are commonly used to serve the
peak loads of the electric utility. Gas-turbine units can be installed at a variety of site locations, because
their size is generally less than 100 megawatts. Gas-turbine units also have a quick startup time, compared
with steam-turbine units. As a result, gas-turbine units are suitable for peak load, emergency, and reserve-
power requirements. The gas turbine, as is typical with peaking units, has a lower efficiency than the
steam turbine used for base load power.
Text is verbatim from the cited source. Formatting added by EPA.
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> Combined Cycle: The efficiency of the gas turbine is increased when coupled with a steam turbine in a
combined cycle operation. In this operation, hot gases (which have already been used to spin one turbine
generator) are moved to a waste-heat recovery steam boiler where the water is heated to produce steam
that, in turn, produces electricity by running a second steam-turbine generator. In this way, two generators
produce electricity from one initial fuel input. All or part of the heat required to produce steam may come
from the exhaust of the gas turbine. Thus, the supplementary steam-turbine generator may be operated
with the waste heat. Combined cycle generating units generally serve intermediate loads because they can
be started more quickly than steam turbines.
> Internal Combustion: These prime movers have one or more cylinders in which the combustion of fuel
takes place. The engine, which is connected to the shaft of the generator, provides the mechanical energy
to drive the generator to produce electricity. Internal-combustion (or diesel) generators can be easily
transported, can be installed upon short notice, and can begin producing electricity nearly at the moment
they start. Thus, like gas turbines, they are usually operated during periods of high demand for electricity.
They are generally about five megawatts in size.
> Hydroelectric Generating Units: Hydroelectric power is the result of a process in which flowing water is
used to spin a turbine connected to a generator. The two basic types of hydroelectric systems are those
based on falling water and natural river current. In the first system, water accumulates in reservoirs
created by the use of dams. This water then falls through conduits (penstocks) and applies pressure
against the turbine blades to drive the generator to produce electricity. In the second system, called a run-
of-the-river system, the force of the river current (rather than falling water) applies pressure to the turbine
blades to produce electricity. Since run-of-the-river systems do not usually have reservoirs and cannot
store substantial quantities of water, power production from this type of system depends on seasonal
changes and stream flow. These conventional hydroelectric generating units range in size from less than 1
megawatt to 700 megawatts. Because of their ability to start quickly and make rapid changes in power
output, hydroelectric generating units are suitable for serving peak loads and providing immediately
available back-up reserve power (spinning reserve), as well as serving base load requirements. Another
kind of hydroelectric power generation is the pumped storage hydroelectric system. Pumped storage
hydroelectric facilities use the same principle for generation of power as the conventional hydroelectric
operations based on falling water and river current. However, in a pumped storage operation, low-cost
off-peak energy is used to pump water to an upper reservoir where it is stored as potential energy. The
water is then released to flow back down through the turbine generator to produce electricity during
periods of high demand for electricity.
In addition to those listed above, a number of other less common prime movers are used to generate electricity
(U.S. DOE, 2007):
> Other Prime Movers: Other methods of electric power generation, which presently contribute only small
amounts to total power production, have potential for expansion. These include geothermal, solar, wind,
and biomass (wood, municipal solid waste, agricultural waste, etc.). Geothermal power comes from heat
energy buried beneath the surface of the earth. Although most of this heat is at depths beyond current
drilling methods, in some areas of the country, magma - the molten matter under the earth's crust from
which igneous rock is formed by cooling - flows close enough to the surface of the earth to produce
steam. That steam can then be harnessed for use in conventional steam-turbine facilities. Solar power is
derived from the energy (both light and heat) of the sun. Photovoltaic conversion generates electric power
directly from the light of the sun; whereas, solar-thermal electric power generators use the heat from the
sun to produce steam to drive turbines. Wind power is derived from the conversion of the energy
contained in wind into electricity. A wind turbine is similar to a typical wind mill. However, because of
the intermittent nature of sunlight and wind, high capacity utilization factors cannot be achieved for these
facilities. Several electric utilities have incorporated wood and waste (for example, municipal waste, corn
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
cobs, and oats) as energy sources for producing electricity at their power facilities. These sources replace
fossil fuels in the boiler. The combustion of wood and waste creates steam that is typically used in
conventional steam-electric facilities.
The final rule is only relevant for power generators that use substantial amounts of cooling water, and not all
prime movers require substantial amounts of cooling water. Only prime movers with a steam-electric generating
cycle use large enough amounts of cooling water to be subject to the final rule. This profile, therefore,
differentiates between steam-based generating capacity and other prime movers, and treats the following prime
movers as steam-electric:
>	Steam turbine, including generating units that are fueled by coal, gas, oil, waste, nuclear, geothermal, and
solar steam (not including combined cycle)
>	Combined cycle, which includes a steam turbine and exhaust gas combustion turbine.
2A.2.3 Ownership
The U.S. Electric Power Industry consists of two broad categories of firms that own and operate electric power
facilities - utilities and nonutilities (U.S. DOE, 2012a; U.S. DOE, 2007):
>	Electric utility: An electric utility (utility) is an entity providing electric power within a designated
franchised service area. Utilities generally operate in a rate-regulation framework, in which a government
regulatory authority sets prices at which the rate-regulated entity sells generated electricity or other
electricity-related services. Electric utilities have traditionally operated in a vertically integrated
framework, which included power generation, transmission, and distribution. However, "generating
utilities," which are the focus of this profile within the utility segment, may provide only power
generation services and not provide transmission or local distribution services. Other electric utility
segments include "transmission utilities," which are the rate-regulated owners/operators of transmission
systems, and "distribution utilities," which are the rate-regulated owners/operators of distribution systems
serving retail customers.
>	Nonutilitv: A nonutility is an entity that owns and/or operates electric power generating units but is not
subject to rate regulation. Nonutilities generate power for their own use and/or for sale to utilities, and
other entities that operate in a non-regulated pricing environment. A nonutility does not have a designated
franchise service area, and does not transmit or distribute electricity.
Electric utilities can be subdivided further into three major ownership categories: investor-owned utilities,
publicly owned utilities, and rural electric cooperatives. EPA identified ownership type for each electric power
facility using data collected through the 2010 Questionnaire for the Steam Electric Power Generating Effluent
Guidelines (the SE industry survey), and from the EIA 860 and 861 databases (U.S. EPA, 2010e; U.S. DOE,
2006; U.S. DOE, 2009c; U.S. DOE 2009d; U.S. DOE, 2011b; U.S. DOE, 2011c). Summary discussions of these
categories follow (U.S. DOE, 2012a; U.S. DOE, 2007):
>	Investor-owned utilities: Investor-owned utilities (IOUs) are for-profit, privately owned businesses. The
electricity prices of IOUs are regulated by State and/or federal governments, which in turn approve rates
that allow a fair rate of return on investment. These rate-regulated utilities either distribute profits to
stockholders as dividends or reinvest the profits. Most IOUs engage in generation, transmission, and
distribution. Historically, IOUs have been most successful in serving large, consolidated markets where
economies of scale afford the lowest rates. IOUs operate as service monopolies in specified geographic
areas. As a condition for granting of the service monopoly, IOUs are required to serve all customers,
giving them access to service under similar conditions and charging comparable prices to similar
classifications of consumers. In 2011, IOUs operated 1,310 facilities, which accounted for approximately
50 percent of all U.S. electric power generating capacity (see Figure 2A-1).
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Chapter 2A: Electric Power Industry Profile
> Publicly owned utilities: These are nonprofit, government agencies that provide service to their
communities and nearby consumers at cost. They return any excess funds to consumers in the form of
community contributions, or reinvest the excess funds in plant and equipment. Publicly owned electric
utilities can be federal power agencies, State authorities, municipalities, and other political subdivisions
(e.g., public power districts and irrigation projects). Smaller municipal utilities, which make up the
majority of municipal utilities, are non-generators engaging solely in the purchase of wholesale electricity
for resale and distribution. Larger municipal utilities, as well as State and federal utilities, usually
generate, transmit, and distribute electricity. In general, publicly owned utilities do not pay certain taxes
and have access to tax-free financing, giving them a lower cost of capital than IOUs. In 2011, the federal
government operated 201 facilities (accounting for 7 percent of total U.S. electric power generating
capacity), States owned 90 facilities (2 percent of U.S. capacity), municipalities owned 868 facilities (5
percent of U.S. capacity), and other political subdivisions owned 157 facilities (two percent of U.S.
capacity).
> Rural electric cooperatives: Cooperative electric utilities ("coops") are member-owned entities created to
provide electricity to those members. These utilities provide electricity to rural sparsely populated areas,
which IOUs historically viewed as uneconomical operations. Electric cooperatives operate at cost and, as
nonprofit entities, are exempt from income tax. Cooperatives are incorporated under State laws and are
usually directed by an elected board of directors. The Rural Utilities Service (formerly the Rural
Electrification Administration), the National Rural Utilities Cooperative Finance Corporation, the Federal
Financing Bank, and the Bank for Cooperatives are important sources of debt financing for cooperatives.
In 2011, rural electric cooperatives operated 251 generating facilities and accounted for approximately 4
percent of all U.S. electric power generation capacity.
The type of entity that owns and operates electric power facilities is a key factor affecting the recovery, through
higher electricity rates, of increases in production costs that may result from compliance with the final rule or
other options EPA considered. As such, entity type is an important consideration for assessing the impact of the
final rule and other options considered, on regulated facilities and electricity consumers. However, ownership
type is not the only determining factor for conclusions regarding compliance cost recovery at regulated facilities.
An additional key factor is the regulatory environment in the State where a 316(b) facility is located. Other factors
include the business operation model of the facility owner(s), the ownership and operating structure of the facility
itself, and the role of market mechanisms used to sell electricity.
Figure 2A-1 reports the number of electric power facilities and their capacity in 2011, by type of ownership. To
determine the ownership type for each facility, EPA relied on the information reported in the SE industry survey,
the 2006 EIA-860, 2009 and 2011 EIA-860, and 2009 and 2011 EIA-861 databases, and additional research (U.S.
EPA, 2010e; U.S. DOE, 2006; U.S. DOE, 2009c; U.S. DOE, 2009d; U.S. DOE, 2011b; U.S. DOE, 2011c).16 The
horizontal axis also presents the percentage of the U.S. total generating capacity and facilities that each type
represents. This figure reflects data for all electric power generating facilities with at least one non-retired unit in
2011 that submitted Form EIA-860 for 2011. The figure shows that in 2011, nonutilities accounted for the largest
percentage of facilities (51 percent) but represented only 30 percent of total generating capacity. Investor-owned
utilities operated the second largest percentage of facilities at 22 percent, and accounted for 50 percent of total
U.S. capacity.
16 Prior to 2007, EIA-860 database reported ownership information at the utility/operator level.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
Figure 2A-1: Distribution of Facilities and Nameplate Capacity by Ownership Type, 2011
340.3 GW
Nonutility
1,118
578.0 GW
Investor-owned
1,310
55.7 GW
Municipality
861!
51.9 GW
251
Cooperative
76.7 GW
201
Federal
28.3 GW
I 157
Political Subdivision
17.8 GW
90
State
Capacity (MW) ¦ Number of Plants
4.3 GW
63
Unknown/Other
0%
20%
40%
60%
80%
100%
Source: U.S. DOE, 2011b; U.S. DOE, 2011c; U.S. DOE, 2006; U.S. EPA, 2010e
2A.3 Domestic Production
This section reviews generating capacity and electricity generation. Section 2A.3.1 provides data on capacity, and
Section 2A.3.2 provides data on generation. Section 2A.3.3 reviews the geographic distribution of generation
facilities and capacity.
2A.3.1 Generating Capacity
The rating of a generating unit, expressed in megawatts (MW), is a measure of its ability to produce electricity.
Capacity and capability are the two most common measures. Nameplate capacity, which is generally greater than
a generating unit's net summer or winter capacity, is the maximum rated (i.e., full-load) output of a generating
unit under specified conditions, as designated by the manufacturer. Net summer capacity is the maximum output
that a generating unit can supply to system load at the time of summer peak demand17; it reflects a reduction in
capacity due to electricity use for station service or auxiliaries. Net winter capacity is the maximum output that a
generating unit can supply to system load at the time of winter peak demand18; it also reflects a reduction in
capacity due to electricity use for station service or auxiliaries. In general, aggregate net summer capacity exceeds
net winter capacity (U.S. DOE, 2007).
In 2010, utilities owned and operated the majority of net summer capacity (58 percent) in the United States, with
nonutilities owning the remaining 42 percent. Nonutility ownership of net summer capacity increased
substantially in the last few years, with nonutility ownership of net summer capacity increasing by 111 percent
between 2000 and 2010, compared with a decrease in utility ownership of net summer capacity of 0.4 percent
over the same period. This trend in the ownership profile reflects the divestiture of capacity by rate-regulated
utilities to nonutility power producers to meet State-based deregulation requirements. Overall, total net summer
17 In the United States, summer peak is the period of June 1 through September 30.
18 In the United States, winter peak is the period of December 1 through February 28(29).
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
capacity increased during this period, from approximately 811,719 MW in 2000 to 1,039,062 MW in 2010 (see
Figure 2A-2).
Figure 2A-2: Net Summer Capacity, 2000 to 2010
700,000
600,000
in
!
S 500,000
u>
o
2
400,000
o
re
Q.
O 300,000
O
E
E
= 200,000
¦*—i
o
Z
100,000
~ Utility BNonutility
1111
rS? <§>N -a*' ^ ^ ^ ^ ^
Source: U.S. DOE, 2011a
2A.3.2 Electricity Generation
The production of electricity is referred to as generation and is measured in units of produced energy, such as
kilowatt-hours (kWh) or megawatt-hours (MWh). Generation can be measured as gross generation or net
generation. Gross generation is the total amount of electricity produced by an electric power facility. Net
generation is the amount of gross generation less electricity consumed by the electricity generating facility for
operation of the power generating station, including, for example, lights at the facility, operation of fuel supply
systems, and electricity required for pumping at pumped-storage facilities. In other words, net generation is the
amount of electricity available to the transmission system beyond that needed to operate facility equipment (U.S.
DOE, 2012a).
As reported in Table 2A-1, total net electricity generation in the United States for 2010 was 4,125 TWh.19 In 2010,
coal accounted for the largest share of total electricity generation (45 percent), despite a 6 percent decline over the
11-year period of 2000 through 2010. Natural gas (24 percent) and nuclear power (20 percent) provide the next
largest shares of generation. Other energy sources accounted for smaller shares of total generation, with
hydropower representing 6 percent; renewable energy, 4 percent; and petroleum, 0.3 percent (see Figure 2A-3).
In 2010, utility-owned facilities accounted for 60 percent of total electricity generation, with nonutility-owned
facilities accounting for 40 percent. The distribution of generation between utilities and nonutilities varied by
19 One terawatt-hour is 109 kilowatt-hours or 10° megawatt-hours.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
energy source, with utilities accounting for larger shares of coal-, hydropower-, petroleum-, and nuclear power-
fueled electricity generation than nonutilities.
As presented in Table 2A-1, over the 11-year period of 2000 through 2010, total net generation increased by
approximately 8 percent. Increases in nuclear -, natural gas-, renewables-fueled electricity generation and
electricity generation from "other" fuels comprised most of this increase. During the same period, coal-,
hydropower-, petroleum-, and other gases-fueled electricity generation declined, with petroleum recording the
largest percent decline of 67 percent.
Between 2000 and 2010, electricity generated by utilities declined by 18 percent while electricity generated by
nonutilities more than doubled. EIA and other analysts expect this trend to continue in the coming years, as
nonutility power producers build more facilities or purchase existing facilities from traditional integrated utilities.
Comparing 2000 and 2010 across all fuel-source categories, utilities generated a larger share of their electricity
using natural gas (a 35 percent increase) and renewables (a 700 percent increase), even as their overall generation
declined. For nonutilities, the largest percentage increase in electricity generation (689 percent) occurred for
nuclear power, followed by "other" fuels and natural gas. In terms of absolute quantity of generated electricity,
natural gas, followed by coal, accounted for the largest increase for nonutilities.
Table 2A-1: Net Generation by Energy Source and Ownership Type, 2000 to 2010 (TWh)

Utilities

Nonutilities

Total

Energy Source
2000
2010
% Change
2000
2010
% Change
2000
2010
% Change
Coal
1,697
1,378
-18.8%
270
469
74.0%
1,966
1,847
-6.1%
Hydropower
248
232
-6.7%
22
23
5.6%
270
255
-5.7%
Nuclear
705
425
-39.8%
48
382
688.5%
754
807
7.0%
Petroleum
72
26
-63.9%
39
11
-71.8%
111
37
-66.7%
Natural Gas
291
393
35.1%
310
595
91.8%
601
988
64.3%
Other Gases
0
0
NA
14
11
-19.3%
14
11
-18.9%
Renewables3
2
18
700.0%
79
149
89.7%
81
167
106.6%
Other
0
0
NA
5
12
158.5%
5
13
168.2%
Total
3,015
2,472
-18.0%
787
1,653
110.2%
3,802
4,125
8.5%
a. "Renewables" include wind, solar thermal and photovoltaic, wood and wood derived fuels, geothermal, and other biomass.

b. "Other" includes non-biogenic municipal solid waste, batteries, chemicals, hydrogen, pitch, purchased steam, sulfur, tire-derived fuels, and
miscellaneous technologies.








Source: U.S. DOE, 2011a








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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
Figure 2A-3: Percent of Electricity Generation by Primary Fuel Source and Facility Ownership Type, 2010
50%
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
¦ Utility

1
~ Nonutility

—

-o*
O'

Source: U.S. DOE, 2011a

o
&

2A.3.3 Geographic Distribution
Electricity is a commodity that cannot be stored or transported easily over long distances. As a result, the
geographic distribution of power facilities is of primary importance to ensure a reliable supply of electricity to all
customers. The U.S. bulk power system is composed of three major networks, or power grids:
> The Eastern Interconnected System covers the largest part of the United States, from the eastern end of
the Rocky Mountains and the northern borders to the Gulf of Mexico States (including parts of northern
Texas) on to the Atlantic seaboard. This system contains six of the North American Electric Reliability
Corporation (NERC) regions, defined below (Florida Reliability Coordinating Council, FRCC; Midwest
Reliability Organization, MRO; Northeast Power Coordinating Council, NPCC (U.S. component);
Reliability First Corporation, RFC; Southeastern Electric Reliability Council, SERC; and Southwest
Power Pool, SPP).
> The Western Interconnected System covers nearly all of areas west of the Rocky Mountains, including the
Southwest. The only NERC region within this system is the Western Energy Coordinating Council,
WECC (U.S. component).
> The Texas Interconnected System, the smallest of the three, covers the majority of Texas. The only NERC
region within this system is Texas Regional Entity (TRE).
The Texas system does not link to the Eastern and Western systems, and the Eastern and Western systems have
only limited interconnection to each other. The Eastern and Western systems link to adjacent parts of the
Canadian grid system, while the Western and Texas systems link with Mexico.
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These major networks contain extra high voltage connections, which allow for power transmission from one part
of the network to another. Wholesale transactions can take place within these networks to reduce power costs,
increase supply options, and ensure system reliability.
Reliability refers to the ability of power systems to meet the demands of consumers at any given time. Efforts to
enhance reliability reduce the probability of power outages. NERC is responsible for the overall reliability,
planning, and coordination of the power grids. Electric utilities formed this voluntary organization in 1968,
following a large blackout in the Northeast in 1965. NERC is organized into eight regional organizations that
cover the 48 contiguous States, and two affiliated councils that cover Hawaii, part of Alaska, and portions of
Canada and Mexico.20 These regional organizations are responsible for the overall coordination of bulk power
policies that affect their regions' reliability and quality of service. As discussed above, interconnection between
the bulk power networks is limited in comparison to the degree of interconnection within the major bulk power
systems. Further, the degree of interconnection between NERC regions even within the same bulk power network
is also limited. Consequently, each NERC region deals with electricity reliability issues in its own region, based
on available capacity and transmission constraints. The regional organizations also aid in the exchange of
information among member utilities in each region and among regions. Service areas of the member utilities
determine the boundaries of the NERC regions. Though limited by the larger bulk power grids described above,
NERC regions do not necessarily follow State boundaries. Figure 2A-4 provides a map of the 2012 NERC
regions, which include:
>	ASCC - Alaska Systems Coordinating Council
>	FRCC - Florida Reliability Coordinating Council
>	HICC - Hawaii Coordinating Council
>	MRO - Midwest Reliability Organization
>	NPCC - Northeast Power Coordinating Council (U.S.)
>	RFC - Reliability First Corporation
>	SERC - Southeastern Electric Reliability Council
>	SPP - Southwest Power Pool
r	TRE - Texas Regional Entity
>	WECC - Western Energy Coordinating Council (U.S.).
20 Energy concerns in the States of Alaska, Hawaii, the Dominion of Puerto Rico, and the Territories of American Samoa, Guam, and the
Virgin Islands are not under reliability oversight by NERC.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
Figure 2A-4: 2012 North American Electric Reliability Corporation (NERC) Regions3
NPCC
MRO
SPP
SERC
TRE
FRCC
\
a. The ASGC and HIGC regions are not shown.
Source: US: DOE, 2012b
Table 2A-2 reports the distribution of all existing electric power facilities and total capacity by NERC region, as
of 2011. As shown in Table 2A-2, WECC has the largest number of facilities (1,677, or approximately 28 percent
of all facilities in the United States). However, these facilities account for only approximately 19 percent of total
national capacity. Conversely, SERC has the largest fraction of total national capacity (approximately 26 percent),
but only 16 percent of facilities.
The final rule may affect the various NERC regions differently, in terms of impact on profitability, electricity
prices, and other impact measures. These different effects result from differences in the economic characteristics
of regulated facilities across the regions and in the baseline economic characteristics of the NERC regions
themselves, together with the market segmentation due to limited interconnectedness among NERC regions.
Table 2A-2: Distribution of Existing Facilities and Total Capacity by NERC Region, 2011
NERC Region
Facilities
Capacity
Number
% of Total
Total MW
% of Total
ASCC
124
2 0%
2.234
0.2%
FRCC
134
2.2%
65,700
5.7%
11 ICC
38
0.6%
2.810
0.2%
MRO
785
13.0%
63.712
5.5%
NPCC
754
12.4%
81.223
7.0%
RFC
1.017
16.8%
254.071
22.0%
SI-RC
944
15.6%
297,564
25.8%
SPP
320
5.3%
71.307
6.2%
TRE
265
4.4%
99,132
8.6%
WECC
1,677
27.7%
215,290
18.7%
Total
6,058
100.0%
1,153,044
100.0%
Source; U.S. DOE, 2011b.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
2A.4 Facilities Subject to the Final Rule
Section 316(b) of the Clean Water Act applies to point source facilities that use or propose to use a cooling water
intake structure that withdraws cooling water directly from a surface waterbody of the United States. Among
power facilities, only those facilities employing a steam-based generating technology - i.e., steam turbine and
combined cycle turbine generating units - require sufficient amounts of cooling water to be subject to the final
rule and therefore, are of interest to this analysis.
The following sections describe electric power facilities EPA expects will be subject to the final rule (regulated
facilities). This final rule applies to existing steam electric power generating facilities that meet the applicability
criteria in the final rule:
>	Is a point source that uses or proposes to use a cooling water intake structure;
>	Has at least one cooling water intake structure that uses at least 25 percent of the water it withdraws for
cooling purposes;
>	Has a National Pollutant Discharge Elimination System (NPDES) permit or is required to obtain one; and
>	Has a design intake flow (DIF) of two million gallons per day (mgd) or greater.
The final rule also covers stand-alone new units at such facilities (the new unit provision of the final rule). New
units at existing facilities are addressed in Chapter 3: Compliance Costs.
EPA identified 544 regulated facilities, based on (1) data collected from the 2000 Industry Short Technical
Questionnaire (STO) and the 2000 Detailed Industry Questionnaire {DO) (316(b) survey) and (2) the rule
applicability requirements above (for details see Chapter 3).
The following sections describe the physical and geographic characteristics, as well as ownership of the facilities
subject to the final rule:
>	Ownership type: Section 2A. 4.1 describes the distribution of all facilities and their parent-entities in the
industry, as well as facilities subject to the final rule and their parent-entities across ownership categories.
>	Parent-entity size: Section 2A.4.2 assesses the distribution of parent-entities across ownership categories
by parent-entity size for the entire industry, and for parent entities that own facilities subject to the final
rule.
>	Facility size: Section 2A.4.3 assesses regulated facilities based on generating capacity.
>	Geographic distribution: Section 2A. 4.4 describes the geographic distribution of regulated facilities
across NERC regions.
>	Waterbody and cooling system type: Section 2A.4.5 documents the type of waterbody from which
regulated facilities withdraw cooling water and the type of cooling system they operate.
2A.4.1 Ownership Type
As described above, utilities fall into six major ownership categories: investor-owned utilities, nonutilities,
federally-owned utilities, State-owned utilities, municipalities, and rural electric cooperatives. This classification
is important because EPA must assess the impact of the final rule on State, local, and tribal governments in
accordance with the Unfunded Mandates Reform Act (UMRA) of 1995 (see Chapter 11: UMRA Analysis) 21
21 As discussed earlier in this chapter, while ownership type may affect the ability of facilities and their parent entities to recover
increased electricity generation costs due to the final rule, ownership type is not a sole or a deciding factor of cost recovery potential.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
Table 2A-3 reports the number of parent-entities, facilities, and capacity by ownership type for the regulated
facilities subset (for a discussion of the determination of parent-entities for regulated facilities, see Chapter 4:
Cost Impact Analyses - Electric Generators). Overall, EPA estimates that regulated facilities account for
approximately 5 percent of all parent entities, 9 percent of all electric power facilities, and 46 percent of total
electric power sector capacity.22'23 Investor-owned utilities own the majority of regulated facilities (68 percent),
while nonutilities own the second largest share (12 percent). Regulated facilities that are owned by investor-
owned utilities account for the largest share (76 percent) of total capacity subject to the final rule.
Table 2A-3: Regulated Facilities, their Parent Entities, and Total Capacity by
Ownership Type, 2011

Parent Entities a'b
Facilities a'b'c
Total Capacity (MW)a c
Ownership Type
Number
% of Total
Number0
% of Total
Number0
% of Total
Cooperative
22
13.8%
33
6.1%
19,902
3.8%
Federal
1
0.6%
12
2.2%
24,087
4.5%
Investor-owned
63
39.6%
369
67.8%
404.416
76.4%
Municipality
37
23.3%
49
8.9%
19.922
3.8%
Nonutilitv
27
17.0%
64
1 1.8%
44.761
8.5%
Other Political
6
3.8%
1 1
2.0%
9.649
1.8%
Subdivision

State
3
1.9%
6
1.1%
6,726
1.3%
Total
159
100.0%
544
100.0%
529,463
100.0%
a. Individual values may not sum to reported totals due to independent rounding.

b. EPA based ownership information for regulated facilities and their parent entities on information gathered through the
2010 Steam Electric industry survey. 2009 and 2011 EIA-860 and EIA 861 databases, and additional research of
publically available information.

c. Facility counts and capacity values are sample-weighted estimates calculated using original survey weights (for details
see Appendix H: Sample Weights).
Source: U.S. EPA analysis for this report; U.S. DOE, 2006; U.S. DOE, 2009c; U.S. DOE, 2009d; U.S.
DOE, 2011b; U.S. DOE, 2011c; U.S. EPA, 2010e

2A.4.2 Ownership Type and Parent Entity Size
EPA estimates that approximately 25 percent of the entities that own regulated facilities are small entities (Table
2A-4), according to Small Business Administration (SBA) business size criteria.
The size distribution of parent entities that own regulated facilities varies by ownership type. The smallest share
of small entities is in the other political subdivision category (2 percent), while small municipalities make up the
largest share of small entities (36 percent).
EPA estimates that of 544 regulated facilities, 71(13 percent) are owned by small entities (Table 2A-4, following
page). The largest share of regulated facilities owned by small entities are owned by cooperatives (39 percent),
while the remaining 61 percent of regulated facilities owned by small entities are owned by municipalities,
investor-owned, nonutilities, and other political subdivisions. By definition, States and the federal government are
large entities. For a detailed discussion of identification and size determination of parent entities of regulated
facilities, see Chapter 4 and Chapter 11.
2A.4.3 Facility Size
EPA also assessed the size of regulated facilities in terms of their generating capacity, which is relevant because
capacity is a direct measure of a facility's importance in meeting electricity demand and reliability needs. The
22 EPA estimates that 6,058 electric power facilities operate in the United States; 2,905 entities own these facilities and account for
1,153,044 MW of total generating capacity.
23 The number of parent entities for the overall Electric Power Industry is the number of utilities/operators reported as owning/operating
existing electric power facilities in the 2011 EIA-860 database (U.S. DOE, 201 lb).
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
majority of regulated facilities (59 percent) have a capacity of less than 1,000 MW, while only a few regulated
facilities (5 percent) have a capacity greater than 2,500 MW (Figure 2A-5).
Table 2A-4: Regulated Facilities and their Parent Entities by Ownership Type and Parent Size,
2011a









Number of Entitiesb
Number of Facilitiesc'd
Ownership Type
Small
Large
Total
% Small
Small
Large
Total
% Small
Cooperative
18
3
21
85.7%
28
5
33
84.8%
Federal
0
1
1
0.0%
0
12
12
0.0%
Investor-owned
7
53
60
1 1 7%
8
361
369
2.1%
Municipality
19
19
38
500%
20
29
49
40.4%
Nonutilitv
8
22
30
26.7%
15
50
64
22.8%
Other Political Subdivision
1
5
6
16.7%
1
10
1 1
9.0%
State
0
3
3
0.0%
0
6
6
0.0%
Total
53
106
159
33.3%
71
473
544
13.0%
a.	Numbers may not sum to totals due to independent rounding.
b.	For details on the determination of parent entities and their size see Chapter
and Chapter 10.



c.	Facility counts are sample-weighted estimates, and are based on the original survey weights (for details see Appendix H).
d.	EPA based the size classification for facilities on the size of their parent entities. In cases where multiple owners own a facility, EPA assumed
the facility to be small if at least one of the owners is a small entity.





Source: U.S. EPA analysis for this report; U.S. DOE, 2006; U.S. DOE, 2011b; U.S. DOE, 2011c; U.S. DOE, 201 Id: U.S. EPA,
2010e








Figure 2A-5: Number of Regulated Facilities by Size (in MW), 2011a
225
200
175
<*)
0)
= 150
0
re
LL
1	125
to
3
U)
& 100
a>
n
E
3
75
50
25

¦

I

1
129

no


\j
m
GO

II




38
1Q

1



N"1
>-
>-


n- v v
Facility Size (MW)
a.	Numbers may not sum to totals due to independent rounding.
b.	The numbers of facilities and capacity are sample-weighted estimates, based on the original survey weights (see Appendix H).
Source: U.S. EPA analysis for this report; U.S. DOE, 2011b
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
2A.4.4 Geographic Distribution
EPA assessed the potential reliability impact of the final rule and other options considered resulting from
installation downtime, by reviewing the distribution of regulated facilities and their capacity across NERC
regions. Installation downtime occurs when facilities temporarily shut down their electric power generation for
installation of certain compliance technologies. NERC regions are built around confined market areas that are
meaningful for assessing the adequacy of generating capacity to meet regional electricity demand. While
electricity may be imported from beyond the borders of a NERC region, the generating capacity within the region
will generally be the primary source of electric supply for meeting the region's electricity demand and for
ensuring adequate supply reliability within the region. Even though reductions in capacity caused by installation
downtime are usually no more than a few weeks longer than ordinary maintenance outages, electric supply
reliability in a region could be weakened to an undesirable level if a substantial number of facilities in a region
incurred downtime at the same time. As a result, reviewing the number of facilities that may incur downtime and
their electric power generating capacity can provide insight into the potential impact of the final rule, or other
options considered, on regional electric supply reliability.
As reported in Table 2A -5. NERC regions show considerable differences in the number of regulated facilities and
their capacity and the percentages of facilities and capacity represented by regulated facilities. Regulated facilities
have the greatest share of capacity in the RFC region (58 percent of total RFC capacity), followed by SERC (55
percent of total TRE capacity); consequently, the potential downtime effect in these NERC regions is likely to be
the greatest. Regulated facilities have the smallest share of capacity in ASCC (1 percent of total ASCC capacity),
followed by WECC (20 percent of total WECC capacity); therefore, the downtime effect in these NERC regions
is likely to be of less consequence. Not all of the regulated facilities will experience downtime; therefore, this
assessment may overstate the percentage of facilities and regional capacity affected by downtime.24
Table 2A-5: Regulated Facilities and their Capacity by NERC Region, 2011
NERC Region
Facilities
Capacity (MW)
Total Number
of Facilities
Regulated Facilitiesa'b
Total Capacity
Regulated Capacitya'b
Number
% of Total
in Region
MW
% of Total in
Region
ASCC
124
1
0.8%
2.234
31
1.4%
FRCC
134
24
184%
65.700
34.523
52.5%
IIICC
38
3
7.9%
2.810
F189
42.3%
MRO
785
60
7.7%
63.712
28.220
44 3%
Nl'CC
754
59
7.8%
8F223
40.596
50.0%
RFC
1.017
140
13.8%
254.071
146.689
57.7 %
si;rc
944
136
14.4%
297.564
162.838
54.7 %
spp
320
40
12.5%
71.307
29.490
41.4%
i
265
41
15.5%
99.132
42.612
43.0%
wire
1.677
39
2.3%
215.290
43.276
20.1%
Total
6,058
544
9.0%
1,153,044
529,463
45.9%
a.	Individual values may not sum to reported totals due to independent rounding.
b.	Facility counts and capacity are weighted estimates calculated using original survey weights (for details see Appendix H).
Source: U.S. EPA analysis for this report; U.S. DOE, 2011b
2A.4.5 Waterbody and Cooling System Type
As reported in Table 2A-6, approximately half of the Electric Generators draw water from a freshwater river (283
facilities or 52 percent), followed by lakes or reservoirs (115 facilities or 21 percent) and estuaries or tidal rivers
(88 facilities or 16 percent). As reported in the table, most of the regulated facilities (343 facilities or 63 percent)
employ a once-through cooling system.
24 In particular, nuclear generating facilities are not expected to incur any additional downtime for installing technology for compliance
with the final rule.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
Table 2A-6: Number of Regulated Facilities by Waterbody and Cooling System Type3'"
Waterbody Type
Recirculating0
Once-Through
Combination
Other
Total
Number
%of
Total
Number
%of
Total
Number
%of
Total
Number
%of
Total
Number
%of
Total
Kstuarv/Tidal River
5
3.4%
72
21.1%
9
19.3%
1
20.0%
88
16 1%
l'reshwater Stream/River
103
69.4%
147
43.0%
29
61.6%
3
66.0%
283
52.0%
Great I.akc
4
2.7 %
32
9.3%
2
4.2%
0
0.0%
38
7.0%
I ,ake/Reservoir
36
24.5%
71
20.7%
7
14.9%
1
20.0%
115
21.2%
Ocean
0
0.0%
20
5.9%
0
0.0%
0
0.0%
20
3.7%
Total
149
100.0%
343
100.0%
47
100.0%
5
100.0%
544
100.0%
Percent of Total
27.4%
63.0%
8.7%
1.1%
100.0%
a.	Individual values may not sum to reported totals due to independent rounding.
b.	Facility counts are weighted estimates calculated using original survey weights (for details see Appendix H).
c.	Includes facilities with cooling water system impoundments, which may qualify as baseline CCRS (see Chapter 1).
Source: U.S. EPA analysis fortius report; U.S. DOE, 2011b; U.S. EPA, 2000
2A.5 Industry Trends
Industry deregulation and several environmental regulations and programs have had significant impacts on the
Electric Power Industry in recent years. Section 2A.5.1 discusses the status of industry deregulation, Section
2A.5.2 discusses air emissions regulations, Section 2A.5.3 discusses renewable portfolio standards, and Section
2A.5.4 discusses carbon emissions regulations. All of these trends have, and/or will, affect the Electric Power
Industry.
2A.5.1 Current Status of Industry Deregulation
The Electric Power Industry has evolved over the past two decades from a highly regulated industry with
traditionally structured electric utilities to a less regulated, more competitive industry. Several key pieces of
federal legislation have supported this transition. Traditionally, the industry has operated under a regulation
framework based on the premise that the supply of electricity is a natural monopoly, where a single supplier could
provide electric services at a lower total cost than could be provided by several competing suppliers. During the
past several decades, however, the relationship between electricity consumers and suppliers has undergone
substantial change, as governments and regulatory agencies recognized that electricity generation does not
necessarily meet the definition of a natural monopoly. As a result, the federal government and States have taken
steps to promote competition in generation. The objective is to achieve higher electricity production efficiency
among electric power generators, while recognizing that the delivery of electricity via transmission and
distribution systems remains within the definition of a natural monopoly. A key step in this effort is the required
unbundling of the traditional, vertically integrated electric power business. The electricity generation business and
therefore, the electric power generating assets, have been separated from the electricity transmission and
distribution business. Electric restructuring has two essential aspects: wholesale access and retail access.
Wholesale access refers to the ability of electric power generating entities - utilities and independent power
producers - to access transmission systems to compete for wholesale markets, i.e., distribution utilities and
independent marketers buying and selling electricity. Retail access refers to the ability of marketers and retailing
businesses of utilities to obtain access to distribution systems to sell electricity to end-use consumers, thereby
introducing consumer choice of electricity supplier (or retail choice).
The initial actions promoting competition in wholesale electric power markets began with the Public Utility
Regulatory Policies Act of 1978 (PURPA), which established business terms by which certain nonutility
electricity-generators - "qualifying facilities" or QFs - could sell electricity to utilities. Later, the Energy Policy
Act of 1992 (EPACT) made it easier for nonutilities to enter the wholesale electric power market by creating a
new category of nonutility power producers - exempt wholesale generators or EWGs - which were exempt from
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
the Public Utility Holding Company Act of 1935 (PUHCA) regulation (EEMCTF, 2007).25 In 1996, the Federal
Energy Regulatory Commission (FERC) issued Order 888. This order further promoted wholesale electric
competition by ensuring non-discriminatory access by power producers to transmission services, which traditional
rate-regulated utilities continued to own. Order 888 also provided a basis for retail choice of electricity supplier,
and established guidelines for the formation of Independent System Operators (ISOs). ISOs are independent,
federally regulated entities (for rate regulation purposes) established to coordinate regional electric power
generation and transmission in a non-discriminatory manner.
Nearly a decade later, the Energy Policy Act of 2005 (EPAct 2005) repealed the original PUHCA of 1935, while
enacting provisions to encourage investment in energy infrastructure and transferring oversight for certain
consumer protection authorities from the Securities and Exchange Commission (SEC) to FERC and the States.
Specifically, EPAct 2005 enacted a new PUHCA (PUHCA of 2005), which gives FERC, as opposed to SEC,
jurisdiction over holding companies. EPAct 2005 also modified PURPA of 1978, removing some pricing
provisions that had resulted in consumers paying above-market prices for some electricity. In addition, EPAct
2005 created the Electric Reliability Organization (ERO), now certified as the NERC, to enforce mandatory
electric reliability rules on all users, owners, and operators of the electric power generation and transmission
systems (FERC, 2006).
Key Changes in the Regulatory and Operating Structure of the Electric Power Industry
Industry deregulation continues to change the structure of the Electric Power Industry. Some of the key changes
include:
>	Provision of services: Under the traditional regulatory system, vertically integrated utilities generally
provided the full slate of services for generation, transmission, and distribution of electric power. Since
the mid-1990s, federal and State policies have led to increased competition in the generation sector of the
industry. Increased competition has resulted in separation of power generation, transmission, and retail
distribution services. Utilities that provide transmission and distribution services continue to be rate-
regulated and must divest their generation assets. In the deregulated framework, entities that generate
electricity are no longer subject to rate regulation and do not operate in protected franchise markets.
>	Relationship between electricity providers and consumers: Under traditional regulation, utilities provided
electric service to all customers within a defined geographic franchise area at prices (electric rates)
approved by the regulatory commission. Consumers within a given utility franchise area were able to
purchase electricity only from the utility franchised to serve that area. Similarly, electricity suppliers were
not free to pursue customers outside their designated service territories. Although most consumers
continue to receive power that is either generated by, or purchased and resold by, their local distribution
company (LDC), retail competition has allowed some consumers - in particular, larger industrial and
commercial consumers - to purchase electricity from producers other than the local distribution utility. In
some instances, they can obtain lower prices than would be available through the traditional supply
structure.
>	Electricity prices: Under the traditional system, State and federal authorities regulated many aspects of
utilities' business operations, including, in particular, their prices. Regulatory authorities set electricity
prices for each utility, based on the cost of producing and delivering power to customers and including a
reasonable rate of return on invested capital (i.e., under the cost-of-service framework). In the deregulated
25 PUHCA of 1935 was passed by the United States Congress to facilitate regulation of electric utilities, by either limiting their
operations to a single state, and thus subjecting them to effective state regulation, or forcing divestitures so that each company became
a single integrated system serving a limited geographic area. In addition, PUHCA of 1935 required holding companies to obtain
permission from the Securities and Exchange Commission (SEC) prior to engaging in a non-utility business and further required that
such businesses be kept separate from the rate-regulated businesses.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
environment, competitive market forces set prices for generated electricity. Electricity sellers and buyers,
who may be local distribution utilities or direct retail purchasers, negotiate through power pools or one-
on-one to set the price of electricity. As in any competitive market, prices reflect the interaction of supply
and demand. During most time periods, the price of electricity in a given competitive wholesale
electricity market (e.g., an integrated dispatch region) is set by the generating unit with the highest energy
production cost that is dispatched to meet spot market electricity demand - i.e., the unit with the highest
production cost determines the "marginal cost" of production and therefore the short-run energy price
(Beamon, 1998).
New Industry Participants
PURPA and EPAct set business terms by which nonutility generators - QFs and EWGs, respectively - could
enter the wholesale power market. Under PURPA, utilities are required to buy power from QFs (usually
cogeneration or renewable energy-based generators) in their service area, at a price equal to the avoided
production cost of the buying utility. EPAct did not require utilities to purchase power from EWGs. Instead,
EPAct gave FERC the authority to order utilities to provide access to their transmission systems on a case-by-case
basis. However, access to the systems proved to be slow and burdensome. In response, FERC issued Order 888,
which required all utilities that own and/or operate transmission facilities to file open-access transmission tariffs
(OATTs) providing open, non-discriminatory access to their transmission systems. Furthermore, in 1999, FERC
issued Order 2000, calling for the development of Regional Transmission Organizations (RTOs), which
independently control and operate the transmission systems (EEMCTF, 2007).26
State Activities
The status of electricity restructuring varies across States. As of 2010, 22 of 50 States had initiated efforts to
design restructured electricity markets and pass enabling legislation. However, eight of these 22 States - Arizona,
Arkansas, California, Montana, Nevada, New Mexico, Oregon, and Virginia - experienced difficulties during the
transition to a competitive electricity market, such as lack of competition for residential customers or substantial,
unanticipated rate increases; consequently, seven of these eight States suspended the restructuring process.
According to the most recent information available, as of September 2010, only 15 States27 and the District of
Columbia were operating with some degree of competitive wholesale and retail electricity markets. In those 16
jurisdictions, at least part of the energy component of retail electricity prices is determined in a deregulated
market. The remaining 28 States had not introduced electricity restructuring legislation as of 2010. The 35 States
with regulated electricity markets host 3,985 facilities (66 percent of all U.S. electric power facilities) and 732
GW of generating capacity (64 percent of total U.S. generating capacity) (U.S. DOE, 2010c; U.S. DOE, 201 lb).
Figure 2A-6 provides a national map of the status of electricity restructuring.
The status of restructuring of the Electric Power Industry is an important factor in assessing the impact of the final
rule on regulated facilities and electricity consumers. In particular, the degree of rate regulation and conversely,
the extent of competition in electric power generation, substantially affect the ability of regulated facilities to pass
cost increases to consumers via electricity rate increases. Utilities, which continue to generate and sell electricity
in the traditional regulated industry structure, are more likely to recover additional power generation costs that
result from compliance with the final rule, than nonutilities, which may be able to recover cost increases via
increased prices, but only to the extent that increased prices are supported by the competitive market. Most
facilities subject to the final rule (323 of 544 or 59 percent) are located in States with rate-regulated electricity
generation markets; these facilities account for 61 percent of total generating capacity (322 GW of 529 GW) and
26 RTO is similar to ISO, with the main difference being the ability of RTO to control and monitor the electric power transmission
system over a wider area across State borders.
27 These 15 States are: Connecticut, Delaware, Illinois, Maine, Maryland, Massachusetts, Michigan, New Hampshire, New Jersey, New
York, Ohio, Pennsylvania, Rhode Island, Texas, and Oregon.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2A: Electric Power Industry Profile
total generation (1,570 TWh of 2,561 TWh) at facilities subject to the final rule. These facilities may be able to
recover increased production costs due to regulatory compliance through higher regulation-based electricity rates,
subject to approval by utility regulatory authorities. However, even for these generators, other factors can be
important in determining the extent of cost recovery. These other factors include the business operation model of
the owner or operator, the ownership structure of the facility itself, and the role of market mechanisms m
dispatching production from generators.2" The other 221 facilities subject to the final rule (41 percent) are located
in States where electricity generation is deregulated and cost recovery is less certain; these facilities account for
approximately 39 percent of total generating capacity and total generation at facilities subject to the final rule
(U.S. DOE, 201 lb).: '
Figure 2A-6: Electricity Regulation Restructuring by State, as of September 2010
Electricity Restructuring by State
J L f O Active

Source: U.S. DOE, 2010c

2A.5.2 Air Emissions Regulations
A number of recent air emission regulations affect electric power generators and may change the economics of
power production, the profile of the electricity market, and electricity rates. Under these regulations, power
28 As discussed earlier in this chapter, while regulatory status in a given State affects the ability of electric power facilities and their
parent entities to recover electricity generation costs, it is not the only factor and should not be used as the sole basis for cost-pass-
through determination.
29 Facility counts and capacity and generation values are sample-weighted estimates generated using Original Survey Weights. For
details, see Appendix H.
30 Capacity values are from the 2011 EIA-860 database. EPA calculated generation values as a five-year average (2007-2011) using
generation values from the EIA-906/920/923 database. In using the year-by-year generation values to develop an average over the data
years, EPA set aside from the average calculation, generation values that are anomalously low. Such low generating output would
likely result from a generating unit being out of service for maintenance.
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generators must meet emission limits by physically reducing air emissions via control technology, adjusting
operations to reduce emissions (e.g., using lower sulfur coal or simply producing less electricity), or by
purchasing emissions allowances that permit release of pollutant emissions. These regulations and programs have
reduced significantly the emissions of sulfur dioxide (S02) and nitrogen oxides (NOx) from power generation. In
some instances, these programs have caused, or will cause, changes in electric power sector operations, including:
>	Increased use of lower pollution fuels
>	Repowering of existing production capacity - e.g., converting traditional steam turbine capacity to
combined cycle operation, which includes a steam and non-steam electricity generation capability and is
more energy efficient
>	Accelerated development of new capacity
>	Earlier retirement of older and typically higher air pollution-intensive capacity for which substantial
investments to reduce emissions are not economical to undertake.
The final rule will overlap with these ongoing air-emission regulatory programs in requiring further changes to
facility operations and further affecting the economics of power production.
Phase I of the Acid Rain Program began implementation in 1995; this program has achieved significant
environmental and health benefits by reducing S02 and NOx emissions and associated ambient pollutant
concentrations. The program affects more than 2,000 electric power generating facilities powered by coal, oil, or
natural gas. The program was the first air pollution program in the United States to rely on a market mechanism -
allowance trading - for allocating emission reductions. Instead of a command and control regulatory approach,
the allowance trading program is market-based, allocating an initial endowment of S02 emission credits to each
utility and allowing the credits to be bought, sold, or banked (as long as emissions levels are met) for future use.
The Acid Rain Program allows flexibility in selecting the most cost-effective approach to reduce emissions.
While allowing flexibility in the approach to reducing emissions, the program did not implement an allowance
trading system for NOx emissions. During Phase II of the program, which began in 2000, the program set a cap
on the number of allowances, ensuring achievement of the intended reductions in total pollutant emissions (U.S.
EPA, 2009b).
In a second market-based regulatory action, EPA promulgated the Clean Air Interstate Rule (CAIR) in 2005 to
further reduce S02 and NOx emissions in 27 eastern States and the District of Columbia through an allowance-
trading program. On July 11, 2008, the U.S. Court of Appeals for the D.C. Circuit vacated CAIR. However, on
December 23, 2008, the U.S. Court of Appeals issued a new ruling that repealed the vacatur and instead,
remanded CAIR to EPA but allowed key provisions to remain in place while EPA re-worked the regulation. The
court noted: "allowing CAIR to remain in effect until it is replaced by a rule consistent with our opinion would at
least temporarily preserve the environmental values."31 The Court tasked EPA with modifying CAIR to address
the issues in its July 11, 2008 decision (U.S. EPA, 2010a).
Promulgated in 2005, CAIR established Phase I caps for NOx and S02 for 2009 and 2010, respectively, and Phase
II caps for NOx and S02 for 2015. For S02 allowances, CAIR relied on the same allowances and trading program
the Acid Rain Program uses. However, because the Acid Rain Program did not include a NOx trading program,
EPA provided new NOx emission allowances under CAIR. CAIR allows each of the 28 eastern States and the
District of Columbia to decide how to achieve the specified emission reductions within their jurisdictions. EPA
expects that most jurisdictions will achieve the required levels by mandating reduced emissions from the power
generation sector (U.S. EPA, 2009a).
State of North Carolina v. EPA, Case No. 05-1244, (D.C.Cir. 2003)
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On July 6, 2011, EPA promulgated the Cross-State Air Pollution Rule (CSAPR) to replace CAIR. The rule
required 28 States in the eastern half of the United States to improve air quality by reducing power facility
emissions of S02, NOx, and/or ozone-season NOx, which cross State lines and significantly contribute to ground-
level ozone and/or fine particulate pollution problems in States other than those that are the sources of the
emissions. Subsequently, the Agency issued a supplemental rule for CSAPR which limited NOx emissions during
the ozone-season. The pollutant emissions that these rules limited - S02, NOx and ozone-season NOx - react in
the atmosphere to form PM2.5 and ground-level ozone and are transported long distances. This made it difficult
for a number of States to meet the national clean air standards that Congress directed EPA to establish to protect
public health (U.S. EPA, 201 la). However, again, a court action has delayed implementation of the regulation:
the U.S. Court of Appeals for the D.C. Circuit stayed CSAPR on December 30, 2011. Subsequently, on August
21, 2012, the court issued an opinion vacating the rule and ordering EPA to revert to the Clean Air Interstate Rule
(CAIR) as an interim regulatory program/2 EPA reviewed the expected impact of the vacatur and concluded that
it had no material effect on its analyses and findings in support of the final rule.
Also building off CAIR, the Clean Air Visibility Rule (CAVR), finalized on June 15, 2005, requires emission
controls to reduce S02 and NOx emissions using Best Available Retrofit Technology (BART) for industrial and
power generation facilities.
The Clean Air Act (CAA) amendments of 1990 directed EPA to control mercury and other hazardous air
pollutants from major sources of air emissions. For power facilities using fossil fuels, the amendments required
EPA to conduct a study of hazardous air pollutant emissions (CAA Section 112(n)(l)(A)). The CAA amendments
also required EPA to make a finding as to whether additional regulation was appropriate and necessary, based on
this study and other information. In 2000, the Administrator found that regulation of hazardous air pollutants,
including mercury from coal- and oil-fired power facilities, was appropriate and necessary (65 FR 79825). On
February 16, 2012, EPA promulgated the final Mercury and Air Toxics Standards (MATS) for power facilities
(77 FR 9304). The rule establishes uniform national standards to reduce toxic air pollutants from new and existing
coal- and oil-fired power facilities. Pollutants covered in the standards include metals such as mercury, arsenic,
chromium, and nickel; acid gases such as hydrochloric acid and hydrofluoric acid; dioxins and fiirans; and
particulate matter. Affected power facilities may use any number of practices, technologies, and strategies to meet
the new emission limits, including using wet and dry scrubbers, dry sorbent injection systems, activated carbon
injection systems, and fabric filters.
2A.5.3 Renewable Portfolio Standards
In many States, Renewable Portfolio Standards (RPS) require electric utilities to generate a certain percentage of
power from renewable sources. States have adopted RPS increasingly since the late 1990s: as of September 2011,
31 States and Washington, DC have mandatory RPS policies, four of which have Alternative Energy Portfolio
Standards. In addition, eight States have adopted non-mandatory renewable portfolio targets, leaving only 11
States with no standards or goals (PCGCC, 2011). Typically, RPS aim to achieve 1 to 5 percent renewable power
generation in the first year and then require increasing percentages every year thereafter, with most States aiming
for around 15 to 25 percent renewable power generation by 2020 to 2025 (PCGCC, 2009). The definition of
renewable sources differs among States. Some States allow only new renewables (renewable sources built after a
certain year) while others allow all renewables, new and existing. Some RPS also involve credit-trading programs
in which investors and power generators decide whether to use and/or develop renewable energy-based generating
capacity, or to purchase renewable energy credits to meet RPS requirements. These programs are similar to the
programs used in the air emissions regulations mentioned in Section 2A.5.2. Eventually, RPS should result in
increased competition, efficiency, and innovation among the renewable energy sectors and should distribute
renewable energy at the lowest possible cost (AWEA, 1997). A more recent development in electric portfolio
32 EME Homer City Generation, L.P. v. EPA, 2012 WL 3570721 (D.C.Cir. 2012)
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standards is the clean energy standard (CES), which requires that clean energy sources provide a fraction of
electric sales.33 Four of the six States that recently adopted electric portfolio standards chose to enact CES as
opposed to RPS (PCGCC, 2011).
2A.5.4 Greenhouse Gas Emissions Regulations
Greenhouse gas (GHG) emissions reduction programs - in particular for carbon dioxide (C02), which is the
primary energy consumption-based GHG - are beginning to surface among States and on the national agenda. In
the absence of federal action, five States34 have adopted C02 performance standards while another 11 States35
have enacted utility sector cap and trade programs (PCGCC, 2012). For both the Northeast Regional Greenhouse
Gas Initiative (RGGI) and the Western Climate Initiative (WCI)/7 groups of States in a given region joined in
multi-state programs to achieve C02 emission reductions. The RGGI program held its first auction of C02 credits
on September 25, 2008. According to RGGI, the member States have capped and will reduce C02 emissions from
the power sector by 10 percent by 2018 (RGGI, 2012). The WCI looks to reduce GHG emissions to levels 15
percent below 2005 emissions by 2020 (WCI, 2012).
In April 2007, the Supreme Court concluded that EPA has the authority to regulate C02 and other greenhouse
gases under the Clean Air Act.38 Though this finding has yet to result in a comprehensive set of rules concerning
GHG reductions at the federal level, EPA has begun targeting certain sectors for regulation. On December 23,
2010, EPA entered into a settlement agreement to issue rules that would address greenhouse gas emissions from
fossil fuel-fired power facilities. Following this agreement, EPA published the Proposed Greenhouse Gas New
Source Performance Standard for Electric Generating Units on April 13, 2012 (U.S. EPA, 2012a). This regulation
requires new fossil fuel-fired electric power generators with greater than 25 megawatt electric power generating
capacity, to meet an output-based limit of 1,000 pounds of C02 per megawatt-hour. EPA is evaluating the public
comments on the proposed rule and has not determined a schedule at this time for taking final action on the
proposed rule.
2A.5.5 Summary of Effects of Regulatory and Non-Regulatory Trends on Cooling Water Intake
Systems
These regulatory and non-regulatory trends have mixed effects on Electric Power Industry operations in terms of
their impact on cooling water intake systems and cooling water requirements. The air pollution regulations
described above will shift power generation from older, more highly polluting generating units, including coal-
fired units, to less polluting capacity, including nuclear capacity and natural gas capacity, in particular, to natural
gas-based combined cycle capacity. Shifts to nuclear capacity may increase cooling water requirements because
nuclear capacity generally has higher cooling water requirements per unit of electricity generated than other
steam-based generation. However, shifts to natural gas capacity will generally reduce cooling water requirements
for two reasons. First, natural gas-fired steam electric generation has lower cooling water requirements than other
steam-based generation, per unit of electricity generated. Second, natural gas/combined cycle generation, which is
33 Depending on the way in which clean energy is defined, these sources may include some non-renewable electric power generation
technologies.
34 California, Illinois, Montana, Oregon, and Washington.
35 Connecticut, Delaware, Florida, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, and
Vermont.
30 The RGGI consists of Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Rhode
Island, and Vermont.
37 The WCI consists of Arizona, California, Montana, New Mexico, Oregon, Utah, and Washington.
38 Massachusetts vs. Environmental Protection Agency, 549 U.S. 497
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increasingly the generation base of new capacity and capacity that replaces older, rebuilt coal-fired capacity, has
even lower cooling water requirements because the combustion turbine component of the combined cycle
operation requires no cooling water.
GHG emission reduction policies will have similar mixed effects. On the one hand, these policies will encourage
improved energy conversion efficiency in electric power generation, requiring fewer energy inputs for power
generation and associated cooling water requirements. However, the primary effect of GHG emission reduction
policies will be to shift generation to less GHG emissions intensive capacity. Shifts to nuclear capacity, with no
GHG emissions, will increase cooling water requirements. Shifts to natural gas/combined cycle capacity - with
lower GHG emissions than other fossil fuel/steam-based capacity and, for natural gas/combined cycle, better
energy conversion efficiency and even lower GHG emissions - will again reduce cooling water requirements and
related impacts.
Finally, renewable energy policies will likely have a neutral-to-beneficial effect on cooling water requirements
and related impacts. Increased use of wind- and solar-based generation will reduce cooling water requirements,
except in the case of solar/thermal capacity (as opposed to solar photovoltaic-based generation), which involves a
steam generation cycle, much like conventional fossil fuel/steam-based generation. Increased use of biomass/
steam-based generation will likely be neutral in terms of cooling water requirements compared with the mix of
non-renewable generation. Compared, however, to air pollution and GHG emission reduction policies, renewable
energy policies will not favor generation from nuclear capacity; this trend will be beneficial in terms of cooling
water requirements and related impacts.
2A.6 Industry Outlook
This section presents a summary of forecasts from the Annual Energy Outlook 2013 (AEO2013) (U.S. DOE,
2013).
2A.6.1 Energy Market Model Forecasts
This section discusses forecasts of electric energy supply, demand, and prices based on data and modeling by the
EIA and as presented in AEO2013, which contains projections of future market conditions through the year 2040,
based on a range of assumptions regarding overall economic growth, global fuel prices, and legislation and
regulations affecting energy markets. EIA's National Energy Modeling System (NEMS) is the basis for these
projections, which reflect all federal, State, and local laws and regulations in effect as of September 2012.
Electricity Demand
EIA projects electricity demand to grow by approximately 0.9 percent annually between 2011 and 2040, for the
Reference case, resulting in an overall growth of 28 percent. EIA projects this growth based on an estimated 27
percent total increase (at an average annual increase of 0.8 percent) in commercial sector demand for electricity,
stemming mainly from growth in commercial floor space in the service industries, despite tightening standards for
building shells and energy efficiency. In addition, EIA projects total residential demand to increase by 24
percent by 2040, compared to 2011 (at an average annual increase of 0.7 percent), driven mainly by a
growing number of U.S. households and continued population shifts to warmer climates with greater cooling
requirements. However, energy efficiency improvements offset this increased demand to a degree, resulting
in a 6-percent decline in an average electricity demand per household by 2040, compared to 2011. The
industrial sector has seen declining growth rates for electricity demand since 2000 due to increased competition
from foreign manufacturers and a shift by domestic manufacturers toward producing less energy-intensive goods.
EIA expects total electricity demand in the industrial sector to grow by 17 percent (as an average annual rate of
0.5 percent) as the world economy recovers. While electricity demand in the transportation sector is expected to
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remain relatively small, the EIA predicts it to triple by 2040, driven by increases in future sales of electric plug-in
light duty vehicles.
Capacity Retirements
According to AEO2013, fossil fuel-fired capacity will make up the largest share of total retired capacity. Overall,
EIA forecasts that 86.9 GW of total fossil-steam capacity will retire between 2011 and 2040, including 37.9 GW
of oil and natural gas fired steam capacity. EIA predicts that coal will have the largest share of capacity
retirements, with an expected 48.8 GW of retired capacity by 2040, (47.2 percent of total retirements). EIA also
projects that an additional 7.1 GW of nuclear capacity, 8.2 GW of combustion turbine/diesel, and 1.2 GW of
renewable capacity will retire during this period.
Capacity Additions
According to AEO2013, the nation will need 340 GW of new generating capacity between 2011 and 2040 to meet
growing electricity demand and to offset the retirement of 103 GW of existing capacity. EIA projects that these
capacity requirements will be met by natural gas, renewable energy, coal, and nuclear power sources - in the
order of expected contribution. Of the new capacity projected to come online between 2011 and 2035, EIA
projects that approximately 63 percent will be natural gas-fired, 31 percent will be fueled by renewables, 3
percent will be by coal-fired, and 3 percent will be nuclear energy. The increase in renewable capacity results in
part from RPS, as described in Section 2A.5.3.
Electricity Generation
According to AEO2013, electricity generation from natural gas-fired facilities will increase to meet growing
electricity demand and to offset losses in capacity from facility retirements. EIA projects that coal-fired
generation will remain the largest source of electricity throughout the forecast period, although its share of total
U.S. generation will decline. At the same time, though, EIA projects that natural gas-fired power facilities will
account for much of the new capacity built between 2011 and 2040. Coal-fired generation will decrease between
2011 and 2040, reducing its share of total generation from 42 percent to an estimated 35 percent. The anticipated
decrease in the share of coal generation results primarily from rising construction costs. Also, concern regarding
future greenhouse gas emissions limitations and current federal and State regulations contribute to coal's
declining share of total generation. EIA projects that the share of total generation associated with natural gas-fired
technologies will increase from 24 percent to 30 percent. EIA projects that the share of total generation from
renewable power sources will increase from 13 percent in 2011 to 16 percent of total generation in 2040. Nuclear
power generation, however, is expected to decrease from 19 percent to 17 percent as a share of total generation.
Electricity Prices
According to AEO2013, electricity prices will rise by 9.1 percent between 2011 and 2040. AEO2013 projects that
by 2025, electricity prices will fall by 4 percent, but by 2035 will rise to above 2011 prices. An increase in
electricity prices between 2011 and 2040 will vary by sector, with the largest increase expected to occur in the
industrial sector (14.7 percent), followed by the residential sector (8.5 percent), the transportation sector (7.1
percent), and the commercial sector (5.9 percent). Overall, average end-use electricity prices are expected to be
10.8 cents per kilowatt hour in 2040 ($2011).
2A.7 Glossary
Base Load: A baseload generating unit normally satisfies all or part of the minimum or base load of the system
and, therefore, produces electricity at an essentially constant rate and runs continuously. Baseload units are
generally the newest, largest, and most efficient of the three types of units.
(http ://www. eia. doe .gov/cneaf/ electricity/page/prim2/chapter2 .html)
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Combined Cycle Turbine: An electric power generating technology in which electricity is produced from
otherwise lost waste heat exiting from one or more gas (combustion) turbines. The exiting heat is routed to a
conventional boiler or to heat recovery steam generator for utilization by a steam turbine in the production of
electricity. This process increases the efficiency of the electric power generating unit.
Distribution: The portion of an electric system that is dedicated to delivering electric energy to an end user.
Electricity Available to Consumers: Power available for sale to customers. Approximately 8 to 9 percent of net
generation is lost during the transmission and distribution process.
Gas Turbine: A gas turbine typically consisting of an axial-flow air compressor and one or more combustion
chambers, where liquid or gaseous fuel is burned and the hot gases are passed to the turbine. The hot gases
expand to drive the generator and are then used to run the compressor.
Generation: The process of producing electric energy by transforming other forms of energy. Generation is also
the amount of electric energy produced, expressed in energy quantity units such as kilowatt-hours (kWh) and
megawatt-hours (MWh).
Gross Generation: The total amount of electric energy produced by the generating units at a generating station or
stations, measured at the generator terminals.
Hydroelectric Generating Unit. A unit in which the turbine generator is driven by falling water.
Intermediate load: Intermediate-load generating units meet system requirements that are greater than baseload but
less than peakload. Intermediate-load units are used during the transition between baseload and peak load
requirements, (http://www.eia.doe.gov/cneaf/electricity/page/prim2/chapter2.html)
Internal Combustion Engine: An internal combustion engine has one or more cylinders in which the process of
combustion takes place, converting energy released from the rapid burning of a fuel-air mixture into mechanical
energy. Diesel or gas-fired engines are the principal fuel types used in these generators.
Kilowatt-hours (kWh): A measure of electric energy generated or consumed. The amount of energy generated
from one Kilowatt of fully utilized capacity during one hour. A Megawatt-hour (MWh) is also an energy measure
and equals 1,000 Kilowatt-hours.
Load: Refers to either demand for electricity or total electricity generated.
Megawatt (MW): Unit of power equal to one million watts. A watt is a measure of power, or the potential to
produce or consume electricity (or other energy).
Nameplate Capacity. The amount of electric power delivered or required for which a generator, turbine,
transformer, transmission circuit, station, or system is rated by the manufacturer.
Net Generation: Gross generation minus electricity used by the electricity generating facility (or company).
Nonutility. A corporation, person, agency, authority, or other legal entity or instrumentality that owns electric
generating capacity and does not produce or sell electricity under a rate-regulation framework. Nonutility power
producers include qualifying cogenerators, qualifying small power producers, and other nonutility generators
(including independent power producers) without a designated franchised service area that do not file forms listed
in the Code of Federal Regulations, Title 18, Part 141. (http://www.eia.doe.gov/emeu/iea/glossary.html)
Other Prime Movers: Methods of power generation other than steam turbines, combined cycles, gas combustion
turbines, internal combustion engines, and hydroelectric generating units. Other prime movers include:
geothermal, solar, wind, and biomass.
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Peakload: A peakload generating unit, normally the least energy efficient of the three unit types, is used to meet
requirements during the periods of greatest, or peak, load on the system.
(http ://www. eia. doe .gov/cneaf/ electricity/page/prim2/chapter2 .html)
Prime Movers: The engine, turbine, water wheel or similar machine that drives an electric power generator. Also,
for reporting purposes, a device that directly converts energy to electricity, e.g. photovoltaic, solar, and fuel
cell(s).
Reliability. Electric system reliability has two components: adequacy and security. Adequacy is the ability of the
electric system to supply customers at all times, taking into account scheduled and unscheduled outages of system
facilities. Security is the ability of the electric system to withstand sudden disturbances, such as electric short
circuits or unanticipated loss of system facilities. (http:/www.eia.doe.gov/cneaf/electricity/epavl/glossary.html)
Spinning Reserve: Reserve generating capacity running at a zero load and synchronized to the electric system. It is
the unloaded section of synchronized generation that is able to respond immediately to serve load.
Steam Turbine: A generating unit in which the prime mover is a steam turbine. The turbines convert thermal
energy (steam or hot water) produced by generators or boilers to mechanical energy or shaft torque. This
mechanical energy is used to power electric generators, including combined cycle electric power generating units
that convert the mechanical energy to electricity.
System: Physically connected generation, transmission, and distribution facilities operated as an integrated unit
under one central management or operating supervision.
Transmission: The movement or transfer of electric energy over an interconnected group of lines and associated
equipment between points of supply and points at which it is transformed for delivery to consumers, or is
delivered to other electric systems. Transmission is considered to end when the energy is transformed for
distribution to the consumer.
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Chapter 2B: Indus try Profiles - Manufacturers
2B Summary Profile of the Primary Manufacturing Industries
2B.1 Introduction
EPA identified six manufacturing industries that use substantial amounts of cooling water in their operations and
are likely to contain the largest numbers of non-power industry facilities and cooling water intake capacity subject
to the final rule:
1.	Aluminum
2.	Chemicals and Allied Products
3.	Food and Kindred Products
4.	Paper and Allied Products
5.	Petroleum Refining
6.	Steel.
Of the estimated 589 non-power industry regulated facilities (referred to herein as Manufacturers), 576 are in
these six Primary Manufacturing Industries, and 13 fall in a wide range of other industries, including non-
manufacturing industries {Other Industries).
EPA profiled the Primary Manufacturing Industries39 and the entities that own them along several dimensions to
support its assessment of the economic impact of the final rule on the regulated facilities in these sectors
>	Size of the industry based on value of output, value added, and number of establishments and firms
>	Employment and labor productivity
>	Capital outlays
>	Capacity utilization
>	Industry structure and competitiveness
>	Competition in international markets
>	Financial condition and performance.
The profiles describe how the industries have changed over time in each of these dimensions and summarize key
business outlook information for the industries. The profiles also provide insight into the likely impact of the final
rule on the regulated facilities, the entities that own them, and the industries, overall4" In particular, the profiles
help EPA assess the ability of facilities and parent entities to meet the final rule's compliance requirements
without incurring substantial adverse economic/financial impact. Key considerations in this assessment include
(1) the ability of the regulated facilities to shift compliance costs to customers through price increases (cost pass-
through), and (2) the financial health of the industry and its general business outlook.
These detailed profiles are Appendices A-F. This chapter summarizes the detailed profiles, including review of:
>	The role of each industry in the U.S. economy and key economic trends. For each industry, this chapter
reports historical profiles of: (1) output in terms of value of shipments, (2) employment, and (3) number
of facilities and firms.
39	EPA also developed costs for facilities in Other Industries that are subject to the rule. However, EPA chose not to profile these
additional industries because the 316(b) survey and other data indicate that there are very few regulated facilities and little cooling
water intake capacity in any of these industries.
40	To the extent possible, the information provided for the Primary Manufacturing Industries in this chapter reflects data for the specific
NAICS codes with facilities that EPA estimates will be subject to the final rule. These values may differ from those reported
elsewhere in the document, where data for earlier analysis years are in the SIC framework. In these instances, EPA used less specific
NAICS codes to maintain data consistency with the SIC-based data.
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>	Factors underlying the assessment of cost pass-through potential. To assess the potential for regulated
facilities to recover compliance costs through price increases, EPA performed a market structure analysis
for each industry that accounts for four factors: (1) fraction of industry output that is expected to be
subject to the final rule, (2) industry concentration, (3) extent of competition in international markets, and
(4) long-term historical industry growth.
>	Financial health and general business outlook. EPA reviewed the following metrics for each industry: (1)
capacity utilization, (2) net profit margin, and (3) return on capital.
From these assessments, EPA concluded that:
>	Zero cost pass-through is an appropriate assumption in analyzing economic impact for all of the Primary
Manufacturing Industries.
>	Each of the Primary Manufacturing Industries would be able to withstand the compliance costs of the
Final 316(b) Existing Facilities Rule without material, adverse financial impact.
The following sections of this chapter are as follows:
>	Overview of the Primary Manufacturing Industries and their role in the U.S. economy
¦	Section 2B.2.1: Value of Shipments
¦	Section 2B.2.2: Employment
¦	Section 2B.2.3: Numbers of Facilities and Firms
>	Factors of primary importance for assessing cost pass-through potential
¦	Section 2B.3.1: Fraction of Each Industry's Production
¦	Section 2B.3.2: Industry Concentration
¦	Section 2B.3.3: Import Competition in Domestic Markets
¦	Section 2B.3.4: Export Dependence - Competition in Foreign Markets
¦	Section 2B.3.5: Long-Term Industry Growth
>	Factors of primary importance for assessing financial performance and general economic condition
¦	Section 2B.4.1: Capacity Utilization
¦	Section 2B.4.2: Current Financial Data and Industry Outlook.
2B.2 General Industry Descriptions; Role in the U.S. Economy
The Primary Manufacturing Industries vary in terms of their size and role in the U.S. economy, but as a whole,
their economic contribution is substantial. To illustrate, in 2010, these industries represented approximately 21
percent of employment in the total U.S. manufacturing industry, and about 2 percent of total U.S. non-farm
employment (BLS, 2014). The Food and Kindred Products Industry is the largest of the Primary Manufacturing
Industries in terms of both facility and firm counts. This industry also accounts for the highest shares of
employment and output, in value of shipments, of the Primary Manufacturing Industries. The Chemicals and
Allied Products Industry, the second largest in terms of facility and firm counts, accounts for a relatively high
share of employment and value of shipments. On the other hand, the Petroleum Refining Industry boasts a
relatively high value of shipments but is one of the smaller industries in terms of facility and firm counts and also
has a smaller share of employment. The Aluminum, Paper, and Steel Industries also account for significantly less
U.S. output, with value of shipments for the past decades remaining around $100 billion or less. In terms of
employment, among the Primary Manufacturing Industries, the Aluminum Industry supports the least
employment, while the Steel and Paper and Allied Products Industries provide significantly higher levels of
employment.
In the past decade, all of the Primary Manufacturing Industries experienced declining employment. Only the Food
and Kindred Products Industry saw increasing employment since 1990. From 1990 to 2009, the Paper and Allied
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Products, Petroleum Refining and Steel Industries also declined in size in terms of facility and firm counts. In
contrast, the Food and Kindred Products Industry has seen a major expansion in the number of facilities and
firms. Since 1990, output increased in each of the Primary Manufacturing Industries except for the Aluminum,
and Paper and Allied Products Industries. Output increased the most in the Petroleum Refining Industry, more
than doubling between 1990 and 2010. The following sections review these industries" participation in the U.S.
economy in terms of value of shipments, employment, and number of facilities and firms.
2B.2.1 Value of Shipments
Over the past two decades, the Food and Kindred Products Industry remained the largest of the Primary
Manufacturing Industries in terms of value of shipments, on an inflation-adjusted basis.41 The Chemicals and
Allied Products Industry was the second largest for most of the period, until 2005 when the Petroleum Refining
Industry surpassed Chemicals and Allied Products to become the second largest industry. On the other hand, the
Aluminum Industry remained the smallest of the industries throughout this period. Figure 2B-1, below, displays
value of shipments for the Primary Manufacturing Industries from 1990 to 2010.
Output for two of the Primary Manufacturing Industries - Aluminum and Paper and Allied Products - declined,
on an inflation-adjusted basis, from 1990 to 2010, while output for the remaining industries increased. The
declining output for the Aluminum and Paper and Allied Products Industries reflects several factors, including a
longer-term trend of declining importance in the U.S. economy and increasing import penetration.
All of the Primary Manufacturing Industries experienced declining output during the recent recession, but since
then, have begun to recover. The declines during the recession were greater on a percentage basis for the
economically cyclical industries (Aluminum, Chemicals and Allied Products, Paper and Allied Products,
Petroleum Refining, and Steel), and least for Food and Kindred Products, which is a consumer-staples industry
and therefore, less cyclical.
>	The Aluminum Industry experienced an overall decline in value of shipments over the past two decades of
about 27 percent. While the industry saw major decreases in 2008 and 2009 due to the economic
downturn, in 2010 value of shipments rebounded with a 28 percent increase.
>	The Chemicals and Allied Products Industry s value of shipments more than doubled (63 percent)
between 1990 and 2010, despite declines in the early part of each decade. In 2009, during the economic
downturn, the industry experienced a nearly 20 percent decline in value of shipments, but began to
recover with a 15 percent increase in 2010.
>	The Food and Kindred Products Industry experienced substantial growth over the two decades, with
value of shipments increasing overall by about 44 percent. Intermittent declines interrupted this growth,
with the greatest decline (about 4 percent) occurring in 2009.
>	The Paper and Allied Products Industry, like the Aluminum Industry, saw an overall decline in value of
shipments of around 21 percent between 1990 and 2010. The industry experienced a major drop in value
of shipments during the recent recession, but began to rebound in 2010 with a 5 percent increase.
>	The Petroleum Refining Industry recorded the highest increase in value of shipments between 1990 and
2010, about 140 percent. The industry saw a large setback in 2009, but began recovering in 2010 with a
steep rise in value of shipments.
>	The Steel Industry> recorded an increase in value of shipments over the period of analysis of
approximately 21 percent. Value of shipments for the industry declined at the beginning of the 2000s, but
41 All dollar values reported in this chapter are in constant dollars of the year 2011.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Indus try Profiles - Manufacturers
then saw significant increases beginning in 2004. Value of shipments declined steeply in 2009, but rose
steeply in 2010.
Figure 2B-1: Value of Shipments for the Primary Manufacturing Industries from 1990 to 2010
$800,000
$700,000
h $600,000
S $400,000
$300,000
S $200,000
$100,000
*	*
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
> Aluminum B Chemicals A Food & Kindred Products X Paper )l( Petroleum * Steel
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1992, 1997, 2002, and 2007EC.
2B.2.2 Employment
Figure 2B-2 provides employment information for the profiled manufacturing industries from 1990 to 2010. In
2010, the Food and Kindred Products Industry had the highest employment while the Aluminum and Petroleum
Refining Industries had the lowest. Employment levels have varied for the manufacturing industries over the past
two decades, but overall, the industries have seen a decline in employment. These declines reflect increasing labor
productivity, but also declining total output, in particular, for the Aluminum and Paper and Allied Products
Industries.
>	The Aluminum Industry experienced a 50 percent decline in employment between 1990 and 2010, with
2010 employment levels at 28,700 employees.
>	The Chemicals and Allied Products Industry experienced an approximately 24 percent decline in
employment between 1990 and 2010. In 2010, the industry employed 370,100 workers.
>	The Food and Kindred Products Industry is the only profiled industry to experience an increase in
employment between 1990 and 2010, about 6 percent. However, this rise was largely due to a large
recorded increase in employment in 1997, and employment has since declined. The large increase in
employment between 1996 and 1997 coincides with the conversion from SIC codes to NAICS codes,
which includes redefinition of some industry sectors and possible assignment of establishments and
employment into difference industry-level sectors. This likely explains the magnitude of change in that
year. Absent that single year of substantial increase, employment would likely be flat over the total
period.
2B-4
May 2014

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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Indus try Profiles - Manufacturers
> The Paper and Allied Products Industry saw a 51 percent decline in employment between 1990 and 2010,
ending the period with 110,100 employees in 2010.
> The Petroleum Refining Industry experienced a relatively smaller decline of 12 percent between 1990 and
2010. However, the past decade saw a slight rise in employment of nearly 2 percent, from 62,100
employees in 2000 to 63,300 employees in 2010.
> Steel Industry> employment declined by approximately 47 percent between 1990 and 2010, with 2010
employment levels at 136,300 employees.
Figure 2B-2: Number of Employees in the Primary Manufacturing Industries from 1990 to 2010
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41
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o
-Aluminum
-Petroleum
¦Chemicals
Steel
¦Paper
Food & Kindred Products
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1992, 1997, 2002, and 2007EC.
2B.2.3 Numbers of Facilities and Firms
The Food and Kindred Products Industry has by far the largest number of facilities and firms, followed by the
Chemicals and Allied Products Industry and the Steel Industry. The Aluminum and Petroleum Refining Industries
are the smallest in terms of facilities and firms, with the Paper and Allied Products Industry being only slightly
larger. Figure 2B-3 shows the number of facilities in each industry from 1990 to 2010, while Figure 2B-4 shows
the number of firms. The industries have experienced varying changes in numbers of facilities and firms, with the
counts in some industries increasing, while decreasing in others. In some instances, these changes reflect overall
economic conditions - periods of economic growth and recession; in others, the industries are experiencing
longer-term decline. Changes in industry concentration also contribute to changes in the number of firms and, to a
less degree, facilities in these industries. See the profile appendices for discussion of these factors.
> The Aluminum Industry saw a 12 percent rise in facilities over the 20 years, and a slight decline, of less
than 1 percent, in firms. In the past decade, both counts rose except for declines in 2002, 2005, and during
the most recent economic downturn. In 2009, facility counts rebounded with a slight rise, reaching 330
facilities, while firm counts continued to decline to 230.
> The Chemicals and Allied Products Industry expanded between 1990 and 2009 with increases in both the
number of facilities and firms (36 percent and 23 percent, respectively). In 2009, both facility and firm
counts declined, ending the period of analysis at 4,800 facilities and 3,400 firms.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Indus try Profiles - Manufacturers
>	The Food and Kindred Products Industry increased in size relative to facility and firm counts, by more
than 50 percent. In 2009, both facility and firm counts declined by about 3 percent to 28,900 and 24,100,
respectively.
>	The Paper and Allied Products Industry experienced overall declines in both the number of facilities (32
percent), and number of firms (23 percent) over the analysis period. In 2005, both facility and firm counts
began declining. In 2009, the number of facilities continued to decline, ending the period with 490
facilities, while the number of firms rose to 290.
>	The Petroleum Refining Industry also saw a decrease in the number of facilities and firms in the industry
between 1990 and 2009 (11 percent and 7 percent, respectively). The industry saw major fluctuations in
both facility and firm counts throughout the period, with annual declines and increases as high as 33
percent. However, the industry ended the period with a significant decline in 2008 and a lesser decline in
2009, ending the period with 300 facilities and 200 firms.
>	The Steel Industry experienced an 8 percent decline in the number of firms in the industry and a very
slight decline, less than 1 percent, in the number of facilities. In the last decade, facility and firm counts
declined significantly from 2002 to 2004 and then again at the end of the period of analysis, with 1,230
facilities and 970 firms in 2009.
Figure 2B-3: Number of Facilities in the Primary Manufacturing Industries from 1990 to 2009
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Steel
Food & Kindred Products
Source: U.S. DOC, 1990-1997SBA; U.S. DOC, 1998-2009 SUSB.
2B-6
May 2014

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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Indus try Profiles - Manufacturers
Figure 2B-4: Number of Firms in the Primary Manufacturing Industries from 1990 to 2009
30,000
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Q> Aluminum Chemicals )( Paper )l( Petroleum % Steel —±—Food & Kindred Products
Source: U.S. DOC, 1990-1997SBA; U.S. DOC, 1998-2009 SUSB.
2B.3 Cost Pass-Through Assessment
The extent to which regulated facilities can recover compliance costs from consumers through price and revenue
increases is an important factor in assessing the economic/financial impact of the final rule's compliance
requirements on regulated facilities and firms owning those facilities. EPA reviewed five factors, which together
indicate the likely ability of cost pass-through for facilities in each of the Primary Manufacturing Industries.
These include:
> Fraction of total production value in an industry that is expected to be subject to the final rule. In general,
the greater this fraction, the more likely that facilities incurring compliance costs will be able to pass on
regulation-induced increases in production costs - along with those other facilities in the industry that are
also incurring those costs. EPA used a threshold of 50 percent to assess whether this factor would
contribute to regulated facilities in a given industry being able to pass forward compliance costs as price
increases.
> Degree of industry concentration. Indicates the potential for market power, and ability of facilities and
firms to increase prices in response to increases in production costs
> Import penetration. Indicates the extent to which the U.S. industry - and specifically, the regulated
facilities - faces competition in U.S. markets from foreign producers, which will not be subject to the
rule's requirements. Higher competition from imports reduces cost pass-through potential for regulated
facilities.
> Export dependence. Indicates the extent to which the U.S. industries compete with foreign producers in
non-U.S. markets - with, again, the recognition that foreign producers will not incur costs under the final
rule. In general, the greater the share of facilities' revenue from foreign sales, the lower the cost pass-
through potential of regulated facilities.
> Long-term historical industry growth. A factor in each industry's overall business outlook. Growing
industries presumably face growing demand for their products, with greater potential for increasing prices
4,100
3.600
3,100
2,600
2.100
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Indus try Profiles - Manufacturers
in response to increased production costs. Declining industries presumably face growing competition
within a declining market, with less potential for increasing prices in response to increased production
costs.
Table 2B-1 summarizes EPA's findings relative to these industry-level factors. In the table, a indicates that a
factor represents potential support for an industry's ability to pass costs to consumers while a indicates a
factor that would make cost pass-through less likely. As shown in the table, none of the Primary Manufacturing
Industries consistently displays strong potential for cost pass-through across the factors analyzed. For instance,
the Aluminum Industry has a relatively large percentage of production in regulated facilities, though below 50
percent, and benefits from some industry concentration and minimal export dependence. However, this industry is
exposed to high competition in domestic markets from international suppliers and has experienced negative long-
term industry growth relative to the U.S. economy as a whole. The Petroleum Refining Industry appears to have
the greatest likelihood of passing on costs but is still subject to domestic competition due to a relatively small
fraction of the industry being subject to regulation and to a low amount of industry concentration. EPA assumed
that none of the Primary Manufacturing Industries will be able to pass on compliance costs to consumers. This
assumption has the potential to overstate impacts to Manufacturers to the extent that facilities in some industries
may in fact be able to pass some compliance costs to consumers.
Table 2B-1: Factors Relevant to Cost Pass-Through Assessment
Industry
Fraction of
Production
Subject to Rule3
Industry
Concentration6
Import Penetration0
Export Dependence"1
Long-Term
Industry Growth6
Aluminum
-
Mixed
-
+
-
Chemicals and
Allied Products
-
Mixed
-
-
+
Food and
Kindred Products
-
-
+
+
-
Paper and Allied
Products
-
-
+
+
-
Petroleum Refining
-
-
+
+
+
Steel
-
-
+
+
-
a. This column indicates whether the fraction of the industry's production that is subject to this final rule is above or below an assumed threshold value of 50
percent, with industries above the threshold marked with "+" and those below with In the following discussion, EPA refers to this factor as the Regulated
Fraction.
b. This column indicates whether the industry is considered concentrated based on the HHI for each industry, with concentrated industries indicated with "+"
and unconcentrated or moderately concentrated industries marked with Industries that have both concentrated and unconcentrated or moderately
concentrated sectors are marked as "mixed."
c. This column indicates whether the import penetration ratio is above or below the threshold value of 28 percent, with industries below the threshold marked
with "+" and those above with
d. This column indicates whether the export dependence ratio is above or below the threshold value of 22 percent, with industries below the threshold
marked with "+" and those above with
e. This column indicates whether the long-term growth rate is above or below the threshold value of 2.46 percent, with industries below the threshold
marked with "+" and those above with
Source: U.S. EPA analysis for this report

2B.3.1 Fraction of Each Industry's Production Subject to the Final Rule
In general, the greater the fraction of production value in an industry that will incur costs from regulatory
requirements, the more likely that facilities incurring compliance costs will be able to pass on those increases in
production costs (Regulated Fraction). EPA assesses that facilities in industries with a Regulated Fraction
exceeding 50 percent are likely to be able to pass on compliance costs, because a greater fraction of production in
the industry is subject to rule requirements, and is expected to incur compliance costs than is not. This section
2B-8
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Indus try Profiles - Manufacturers
describes the fraction of each Primary Manufacturing Industry EPA estimated will be subject to the final rule.42
Overall, EPA estimates that a small fraction of total production value in the Primary Manufacturing Industries
will be subject to the final rule: approximately 2 percent of facilities and 20 percent of the total value of shipments
{Table 2B-2). The number of regulated facilities as a fraction of industry totals is small across all industries, with
regulated Manufacturers in the Petroleum Refining having the largest fraction of facility counts at 11 percent. The
fraction does not exceed 5 percent for any of the remaining industries.
Regulated Fractions of production based on value of shipments are generally higher, with the Steel Industry
accounting for the largest share (48 percent), followed by the Aluminum Industry (46 percent), Paper and Allied
Products Industry (39 percent), and Petroleum Refining Industry (38 percent). The fraction for the remaining
industries does not exceed 14 percent. While Regulated Fractions for two of the industries - Aluminum Industry
and Steel Industry -are nearly 50 percent, the percentage of value of shipments subject to this final rule does not
exceed 50 percent for any of the Primary Manufacturing Industries. The Regulated Fractions for the Primary
Manufacturing Industries all suggest limited potential for cost pass-through.
Table 2B-2: Regulated Fraction of Facilities, Value of Shipments, by Industry

Number of Facilities
Value of Shipments (mill; $2011)a'b

Regulated0

Regulated0
Industry
NAICS Code
Industry Total
Number
% of Ttl
Industry Total
Value
% of Ttl
Aluminum
3313
583
22
4%
$32,966
$15,131
46%
Chemicals
325
13,138
175
1%
$716,178
$102,914
14%
Food
311/3121
4.1 19
34
1%
$755,071
$16 881
2%
Paper
322
4.706
194
4%
$I7v577
$66 845
39%
Petroleum
3241 1
303
35
1 1%
$601,212
$229,480
38%
Steel
3311/2
1.233
48
4%
$1 18.089
$57,195
48%
Total
NA
24,082
509
2%
$2,397,094
$488,446
20%
a. For this analysis, facility revenue was used as a measure of output for sample facilities. This includes revenues for all regulated facilities in the
Primary Manufacturing Industries, excluding baseline closures.

b. To compare revenues at regulated facilities with the industry value of shipments, EPA brought revenues at regulated facilities to 2010 using industry-
specific Producer Price Index (PPI) series published by the Bureau of Labor Statistics (BLS), and stated in 2011 dollars using the GDP deflator series
published by the Bureau of Economic Analysis (BEA).
c. EPA estimated number of regulated facilities and regulated facility revenues using technical weights. Regulated facility counts and associated revenue
exclude baseline closures and exclude 13 facilities with NAICS codes that do not fall into any of these six Primary Manufacturing Industries (see
Appendix H).
Source: U.S. DOC, 2010 ASM; U.S. DOC, 2009 SUSB; U.S. EPA, 2000

2B.3.2 Industry Concentration
The degree of industry concentration indicates the potential for market power, and the consequent ability of
facilities and firms to increase prices in response to increases in production costs. Table 2B-3 reports the
Herfindahl-Hirschman Index (HHI), by segment, for each of the Primary Manufacturing Industries, as reported by
the U.S. Department of Commerce (DOC). The HHI is a generally accepted measure of market concentration
used by the U.S. Department of Justice (DOJ) to evaluate mergers: the higher the HHI value, the greater the
degree of concentration and potential for market power, and the greater the potential for cost pass-through if the
regulated facilities are owned by the more dominant firms in an industry. Based on the U.S. Department of Justice
(DOJ) guidelines for evaluating mergers, an HHI under 1,000 indicates an unconcentrated market, an HHI
between 1,000 and 1,800 indicates moderate concentration, and an HHI in excess of 1,800 indicates concentrated
markets. The summary findings for industry concentration are as follows:
42 The values reported in this section are for the entire industries, as opposed to only the individual NAICS codes of facilities potentially
subject to this final rule, to assess the ability of regulated facilities to pass on costs to consumers. Because facilities subject to this
regulation likely complete with facilities outside of their specific 6-digit NAICS codes, EPA reports values for higher-level NAICS
codes.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Indus try Profiles - Manufacturers
> The Aluminum Industry includes two concentrated segments and one unconcentrated segment. DOC did
not report HHI for the fourth segment.
> The Chemicals and Allied Products Industry also displays a mix of industry concentrations with three
concentrated, four moderately concentrated, and four unconcentrated segments. DOC did not report HHI
for two of the industry segments.
> The Food and Kindred Products Industry consists of two unconcentrated segments.
> The Paper and Allied Products Industry contains one moderately concentrated segment and two
unconcentrated segments.
> The Petroleum Refining Industry is unconcentrated.
> The Steel Industry> consists of five segments, four of which are unconcentrated. U.S. DOC did not report
HHI for the fifth segment.
EPA concluded that facilities in only the Aluminum, and Chemicals and Allied Products Industries might possess
relatively weak cost pass-through potential, based on the moderate concentration finding. All of the remaining
industries show little potential for cost pass-through based on industry concentration.
Table 2B-3: Concentration Ratios by Industry and Sub-Industry Sector

Total Number of
Herfindahl-

Total Number of
Herfindahl-
NAICS Code
Firms
Hirschman Index3
NAICS Code
Firms
Hirschman Index3
Aluminum
Food & Kindred Products
33I3II
12
NA
311
21,355
102
331312
34
2,250
3121
3,160
483

108
931
Paper and Allied Products
331315
89
1,995
322110
30
1.024
Chemicals and Allied Products
32212
151
673
325110
38
2,535
322130
77
713
325120
96
1.415
Petroleum Refining
325131
72
1.265
324110
98
807
325181
36
2,392
Steel
325188
396
224
331111
235
786
325199
540
361
331112
20
NA
325211
803
400
331222
237
297
325221
15
NA
331221
120
402
325222
88
2,071
331210
134
436
325311
137
/, 136

325312
50
NA

325411
3H5
1.424

325412
763
457

a. Sectors in bold are concentrated based on DOJ criteria. Sectors in italics are moderately concentrated based on DOJ criteria.

Source: U.S. DOC. 2007 EC

2B.3.3 Import Competition in Domestic Markets
Import penetration, shown in Figure 2B-5, measures the extent to which domestic firms encounter foreign
competition in domestic markets. In general, the greater the competition from imports - whose production is not
subject to the final rule - the lower will be the cost pass-through potential for regulated facilities. In effect, the
presence of import competition adjusts the information on fraction of domestic output that is subject to the final
rule (Section 2B.3.1): substantial competition from imports further reduces the cost pass-through potential.
EPA calculated import penetration as total imports divided by total value of domestic consumption in that
industry where domestic consumption equals domestic production plus imports minus exports. The estimated
import penetration ratio for all U.S. manufacturing industries (NAICS 31-33) for 2010 is 28 percent. EPA
determined that industries with import ratios close to or above 28 percent would more likely face stiff competition
2B-10
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Industry Profiles - Manufacturers
from foreign firms and thus would be less able to pass compliance costs through to customers. Over the past two
decades, all of the Primary Manufacturing Industries have seen a rise in import penetration.
> The Aluminum Industry's import penetration ratio doubled in the last two decades, increasing from just
below 16 percent in 1990 to about 32 percent in 2010. The first major rise in import penetration occurred
in 1994, primarily due to exports from Russian producers (USGS, 1994a). Import penetration declined at
the end of the analysis period, in 2007 and 2010. However, in 2010, import penetration still exceeded the
average ratio for manufacturers, indicating that the industry faces a relatively high level of competition
from foreign producers.
> The Chemicals and Allied Products Industry experienced a continuous rise in import penetration between
1990 and 2010, except for a slight decline in 2010 of less than 1 percent. Over the past two decades,
import penetration increased by more than 20 percentage points, with the majority of that rise occurring
during the 1990s. In 2010, import penetration in the industry was approximately 31 percent, above the 28
percent average for manufacturers, implying that the industry faces relatively higher competition from
foreign producers.
> The Food and Kindred Products Industry was least affected by imports between 1990 and 2010. Overall,
import penetration grew by about 3 percentage points between 1990 and 2010. In 2010, the import
penetration ratio was 8 percent, significantly less than the average for manufacturers, indicating that the
industry is not likely to face strong competition from foreign producers.
> The Paper and Allied Products Industry's import penetration ratio remained relatively constant between
1990 and 2010, fluctuating between 15 percent and 20 percent. In 1990, the import ratio was
approximately 16 percent and by 2010, increased to 17 percent. In 2010, import penetration in the
industry was below the 28 percent average for manufacturers, suggesting that the industry does not face
high competition from foreign producers relative to other manufacturing industries.
> The Petroleum Refining Industry's import penetration ratio generally increased over the analysis period,
increasing by 7 percentage points, and ending the period in 2010 at 17 percent. While the industry has
faced increasing competition from foreign producers, the import penetration ratio remains significantly
lower than the manufacturing industries' average of 28 percent.
r The Steel Industry experienced a high level of fluctuation in import penetration between 1990 and 2010,
increasing from approximately 15 percent in 1990 to 23 percent in 2010. In 2010, import penetration was
below the average for manufacturers.
EPA concluded that four of the Primary Manufacturing Industries - Food and Kindred Products, Paper and Allied
Products, Petroleum Refining, and Steel Industries - would see improved cost pass-through potential based on the
Import Penetration factor. The Aluminum, and Chemicals and Allied Products Industries are both exposed to
substantial import competition, with reduced cost pass-through potential. This observation offsets to a degree the
more favorable cost pass-through finding for these industries based on the Regulated Fraction factor43 (Section
2B.3.1).
43 Both industries have Regulated Fractions of nearly 50 percent.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Indus try Profiles - Manufacturers
Figure 2B-5: Import Penetration for the Primary Manufacturing Industries from 1990 to 2010
35.00%
30.00%
0.00%
25.00%
20.00%
t 15.00%
o
10.00%
5.00%
^ # # / # / / # / ^ ^ ^ ^
¦Aluminum
¦Chemicals
¦Food & Kindred Products
¦Paper
Petroleum
¦Steel
Source: U.S. ITC, 1990-2010
2B.3.4 Export Dependence - Competition in Foreign Markets
While imports rose over the past two decades, each of the industries became increasingly dependent on exports.
Export dependence, calculated as exports divided by value of shipments, measures the share of a segment's sales
that EPA presumes to be subject to foreign competition in export markets. Firms in industries that rely, to a
greater extent, on export sales would have less latitude in increasing prices to recover compliance-related
increases in production costs because foreign firms would not be subject to those increased costs. The estimated
export dependence ratio for all U.S. manufacturing industries for 2010 is 22 percent. EPA assesses that industries
with export ratios close to or above 22 percent, are at a relatively greater disadvantage in their potential ability for
cost pass-through. Figure 2B-6 reports export dependence for the Primary Manufacturing Industries from 1990 to
2010.
> The Aluminum Industry experienced an overall increase in export dependence of around 2 percentage
points between 1990 and 2010. In 2010, export dependence was 18 percent, below the average export
dependence for manufacturers.
> The Chemicals and Allied Products Industry had the highest export dependence of the Primary
Manufacturing Industries for the majority of the past two decades. The industry also saw an increase in its
dependence on exports, of about 11 percentage points. In 2010, export dependence in the industry was
above the average export dependence for manufacturers of 22 percent.
> The Food and Kindred Products Industry experienced little change in export dependence, which
increased by 3 percentage points between 1990 and 2010. In 2010, export penetration increased more
substantially, ending the period at 17 percent, but still 5 percentage points below the average export
penetration for manufacturers.
2B-12
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Indus try Profiles - Manufacturers
> The Paper and Allied Products Industry's export dependence rose by approximately 7 percentage points
between 1990 and 2010. However, in 2010, the Paper and Allied Products industry's export dependence
of 17 percent was below the average for manufacturers.
> The Petroleum Refining Industry's export dependence remained relatively low for the majority of the past
two decades, remaining constant at 4 percent until 2005. Overall, export dependence nearly tripled
between 1990 and 2010. In 2010, export dependence for the Petroleum Refining industry was 10 percent,
well below the average export dependence for manufacturers.
> The Steel Industry> 's export dependence more than doubled during the period of analysis, rising from 5
percent in 1990 to 13 percent in 2010. In 2010, export dependence remained well below the average
export dependence for manufacturers.
From this assessment, EPA concluded that five of the Primary Manufacturing Industries - Aluminum, Food and
Kindred Products, Paper and Allied Products, Petroleum Refining, and Steel Industries - would see improved cost
pass-through potential based on the Export Dependence factor.
Figure 2B-6: Export Dependence for the Primary Manufacturing Industries from 1990 to 2010
30.00%
25.00%
5.00%
0.00%
v. 20.00%
15.00%
10.00%
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Indus try Profiles - Manufacturers
growth to that of the entire U.S. economy. As shown, only the Chemicals and Allied Products and Petroleum
Refining Industries experienced long-term growth greater than the economy as a whole. The other four industries
experienced lower long-term growth than the general U.S. economy, with the Aluminum and Paper and Allied
Products Industries experiencing negative growth.
EPA concluded that two of the Primary Manufacturing Industries - Chemicals and Allied Products and Petroleum
Refining - would see improved cost pass-through potential based on the Long-Term Growth factor.
Table 2B-4: Long-Term Industry Growth
Industry
Average Annual Growth Rate,
1990 to 2010
Aluminum
-1.59%
Chemicals and Allied Products
2.48%
Food and Kindred Products
1.84%
Paper and Allied Products
-1.18%
Petroleum Refining
4.48%
Steel
0.99%
U.S. Economy3
2.46%
a. Long-term growth for the LIS. economy is based on GDP growth.
Source: US.DOC, 1990 and 2010 ASM; U.S. BR4, 2012a
2B.4 Financial Performance and Outlook Assessment
The extent to which regulated facilities can absorb compliance costs is an important factor in assessing the
economic/financial impact of the final. EPA reviewed four factors that, together, indicate the likely ability of
facilities in each of the Primary Manufacturing Industries to absorb costs. These include:
> Capacity utilization measures the extent to which an industry's asset base - plant and equipment - is
employed in producing output, and is generally higher for industries that are experiencing strong financial
performance. All else equal, capacity utilization correlates directly with financial return on capital, which
is a key measure of the financial performance and health of an industry.
> Net profit margin in an industry must be sufficiently positive if the industry is to remain economically
viable and attract capital. Industries with sufficiently positive net profit margins, indicating strong
financial conditions, are more likely to be able to costs.
> Return on total capital in an industry must be sufficient if the industry is to remain economically viable
and attract capital. Again, industries with sufficient returns on total capital are more likely to be able to
withstand costs.
> Near-term industry outlook45 \ndicates the near-term trend (one to two years) in financial performance.
Industries whose financial performance is expected to improve, near-term, are in a better financial
position to be able to absorb costs.
Table 2B-5 displays the results of EPA's assessment of financial performance, with indicating strong
performance and indicating weak performance. Only the Petroleum Refining Industry has consistently
positive indicators for financial performance. However, all of the Primary Manufacturing Industries experienced
increasingly stronger financial performance in 2012 after weakness during the 2008 to 2009 recession. In
addition, all the industries have either positive or neutral near-term outlooks. EPA assesses that facilities in each
of the Primary Manufacturing Industries exhibited sufficiently strong financial performance and near-term
outlook to absorb the compliance costs associated with this rule.
45 Based on assessments by Standard and Poor (S&P), a major business analysis and financial assessment firm.
2B-14
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Indus try Profiles - Manufacturers
Table 2B-5: Factors Relevant to Financial Performance and Outlook Assessment
Industry
Capacity Utilization3
Net Profit Marginb
Return on Capital0
Short-Term Outlook"1
Aluminum
-
+
+
+
Chemicals and Allied
Products
-
+
+
+
Food and Kindred Products
+/-
+
+
+/-
Paper and Allied Products
+
+
+
+/-
Petroleum Refining
+
+
+
+
Steel
+/-
+
+
+/-
a. This column indicates whether capacity utilization in each industry, in 2010, is substantially above or below the threshold value of 78.8
percent, with industries above the threshold demarcated with "+" and those below with Industries with capacity utilization that is
approximately equal to the threshold value are indicated as neutral (+/-)
b. This column indicates whether the net profit margin for each industry, in 2012, shows recovery from the recent recession (+) or shows
continued weak financial condition (-).
c. This column indicates whether the return on capital for each industry, in 2010, shows recovery from the recent recession (+) or shows
continued weak financial condition (-).
d. This column indicates whether the near-term S&P outlook is positive (+), negative (-), or neutral (+/-).
Source: U.S. EPA analysis for this report
2B.4.1 Capacity Utilization
Capacity utilization measures actual output as a percentage of total potential output given available capacity.
Capacity utilization indicates excess or insufficient capacity in an industry, and indicates the likelihood of new
investment. Industries and facilities that achieve higher capacity utilization will generally achieve higher financial
returns and will have better prospects for strong financial performance, and, as such, will be better able to
withstand the costs of compliance. This is especially true for industries with substantial fixed costs, such as the
Aluminum Industry, where capacity utilization is linked closely to financial performance. The current long-term
capacity utilization for manufacturing, as a whole, is 78.8 percent (Federal Reserve Board of Governors, 2012c).
In 2010, capacity utilization in all but the Paper and Allied Products and Petroleum Refining Industry was below
this figure, due largely to declines during the recent economic downturn. Figure 2B-7 displays capacity utilization
for the six Primary Manufacturing Industries from 1990 to 2010.46
> The Aluminum Industry saw declining capacity utilization between 1990 and 1999, of 11 percentage
points. In 2010, capacity utilization was 72 percent, 7 percentage points below the long-term
manufacturing industry value of about 79 percent.
> The Chemicals and Allied Products Industry experienced an overall decline of 8 percentage points,
ending the period with a capacity utilization of 75 percent in 2010. In 2010, capacity utilization in this
industry was about 4 percentage points below that of the long-term capacity utilization for manufacturers
as a whole.
> The Food and Kindred Products Industry experienced the smallest fluctuation in this 21 -year period, with
capacity utilization ranging between 77 percent and 85 percent. In 2010, capacity utilization was 78
percent for an overall decline of 8 percent for the period of analysis. Capacity utilization in the industry in
2010 was just 1 percentage point below that of the overall manufacturing industry.
> The Paper and Allied Products Industry tended to have the highest capacity utilization of the six Primary
Manufacturing Industries, fluctuating between 81 percent and 98 percent. In 2010, the industry's capacity
40 For the Aluminum, Food and Kindred Products, Paper and Allied Products, and Steel Industries, the reported values are the annual
value of shipments- weighted average of capacity utilization for the NAICS sectors reported in the individual profiles (see Appendices
A through F).
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Indus try Profiles - Manufacturers
utilization was 81 percent, about 3 percentage points above the long-term manufacturing industry
utilization.
> The Petroleum Refining Industry s capacity utilization saw little change, relative to the other Primary
Manufacturing Industries, between 1990 and 2010. Capacity utilization for the industry was 87 percent in
2010, 8 percentage points above the long-term manufacturing industry capacity utilization.
> The Steel Industry experienced considerable volatility in capacity utilization between 1990 and 2010, with
an overall decline of 7 percentage points. In 2010, the industry saw a large increase in capacity utilization,
reaching 77 percent, just 2 percentage points below that of the entire manufacturing industry.
EPA concluded that two of the Primary Manufacturing Industries - Paper and Allied Products and Petroleum
Refining - stood in relatively stronger financial condition based on the Capacity Utilization factor, with a high
likelihood of being able to absorb compliance costs. Another two of the industries - Steel and Food and Kindred
Products - had capacity utilization levels close to that of the entire manufacturing industry, indicating a likely
ability to absorb costs. Only capacity utilization for the Aluminum and Chemicals and Allied products indicated a
potentially weaker financial condition relative to the overall manufacturing industry.
Figure 2B-7: Capacity Utilization for the Primary Manufacturing Industries from 1990 to 2010
100
95
90
85
80
= 75
g
u
(5
S" 70
(6
u
65
60
55
50
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
—~—Aluminum -¦-Chemicals -^Food & Kindred Products —^Paper -4^Petroleum ¦^KSteel
Source: Federal Reserve Board of Governors, 2012a; U.S. DOC, 1990-2010 SPC; U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-
2006, and 2008-2010 ASM; U.S. DOC, 1992, 1997, 2002, and 2007 EC
2B.4.2 Current Financial Data and Industry Outlook
The financial performance and condition of the Primary Manufacturing Industries are important determinants of
their ability to absorb the costs of regulatory compliance without material, adverse economic/financial impact.
They are particularly important factors in the ability of the regulated facilities and their owners to finance the
capital outlays needed for regulatory compliance. To provide insight into the industries" financial performance
2B-16
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Industry Profiles - Manufacturers
and condition, EPA reviewed two key measures of financial performance over the 21-year period, 1988 to 2010:
net profit margin and return on total capital. EPA calculated these measures using data from the Quarterly
Financial Report for Manufacturing, Mining, and Trade Corporations (QFR) published by the U.S. Census
Bureau. Financial performance in the most recent financial reporting period (2010) obviously is not a perfect
indicator of conditions at the time of regulatory compliance. However, examining the trend and deviation from
the trend through the most recent reporting period gives insight into where the industries may be in terms of
financial performance and condition, at the time of compliance. In addition, the volatility of performance against
the trend, in itself, provides a measure of the potential risk faced by the industries in a future period in which
compliance requirements are faced. All else equal, the more volatile the historical performance, the more likely
the industries may be in a period of relatively weak financial conditions at the time of compliance.
Net profit margin is calculated as after-tax income before nonrecurring gains and losses as a percentage of sales or
revenues, and measures profitability, as reflected in the conventional accounting concept of net income. Over
time, the firms in an industry and the industry collectively, must generate a sufficiently positive profit margin if
the industry is to remain economically viable and attract capital. Year-to-year fluctuations in profit margin stem
from several factors, including: variations in aggregate economic conditions (including international and U.S.
conditions), variations in industry-specific market conditions (e.g., short-term capacity expansion resulting in
overcapacity), or changes in the pricing and availability of inputs to the industry's production processes (e.g., the
cost of energy to the aluminum production process). The extent to which these fluctuations affect an industry's
profitability, in turn, depends heavily on the fixed vs. variable cost structure of the industry's operations.
Return on total capital is calculated as annual pre-tax income divided by total financial capital, calculated as the
sum of (1) long-term debt, (2) all other noncurrent liabilities, and (3) total stockholders' equity.47 This concept
measures the total productivity of the capital deployed by a firm or industry, regardless of the financial source of
the capital (i.e., equity, debt, or liability element). As such, the return on total capital provides insight into the
profitability of a business' assets independent of financial structure and is thus a "purer" indicator of asset
profitability than return on equity. In the same way as described for net profit margin, the firms in an industry and
the industry collectively, must generate a sufficient return on capital over time, if the industry is to remain
economically viable and attract capital for replacement and growth of its productive asset base. The factors
causing short-term variation in net profit margin will also be the primary sources of short-term variation in return
on total capital.
Figure 2B-8 displays net profit margin while Figure 2B-9 displays return on total capital for the Primary
Manufacturing Industries from 1990 to 2012 48 The financial performance of the six industries over the past two
decades differs greatly, with some industries showing great volatility while others have remained relatively stable.
EPA determined whether these measures indicate ability to absorb compliance requirements by comparing the
values for each of the Primary Manufacturing Industries in 2012 to the long-term trends for each industry. EPA
also determined the financial outlook for each industry based on the near-term industry outlook.
> The Aluminum Industry shows cyclical financial performance, with declines in the early 1990s, early
2000s, and in the late 2000s, during the recent recession. After a major drop in financial performance in
2008, both net profit margin and return on total capital rose quickly as the industry recovered. In 2012,
both indicators declined, but to values closer to the industry's long-term average. The industry is expected
to continue to improve, with industry experts projecting a positive outlook for the industry in 2013 (S&P,
2013a).
47 A comparable value could be derived from the asset side of industries' balance sheet, in which case the analysis would focus on all
assets but current assets. The data for the calculation, as described here, is readily available in QFR.
48 For additional detail on the financial performance of the Primary Manufacturing Industries over the full period analyzed by EPA, refer
to Appendices A through F.
May 2014
2B-17
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Economic Analysis for Final 316(b) Existing Facilities Rule Chapter 2B: Industry Profiles - Manufacturers
> The Chemicals and Allied Products Industry experienced fluctuations in financial performance over the
period of analysis, but was not affected greatly by the recent economic recession. In 2012, net profit
margin was slightly above the industry's average net profit margin for 1990 to 2012, while return on total
capital was slightly below the industry's long-term average. According to industry experts, the outlook for
the industry in 2013 is positive (S&P, 2013c).
> The Food and Kindred Products Industry's net profit margin and return on total capital remained
relatively stable between 1990 and 2012, with slight declines in financial performance during the recent
recession. In 2012, net profit margin was slightly above the long-term average for the industry, while
return on total capital was below the industry's long-term average. The outlook for this industry in 2013
varies by sub-industry sector, with a positive outlook for the distillers and vintners sector and neutral
outlooks for the soft drinks and packaged foods and meats sectors (S&P, 2013e; S&P, 2013g; S&P,
2013b).
> The Paper and Allied Products Industry experienced substantial a decline in financial performance during
the recent economic downturn. However, the industry has since begun recovery, with 2012 net profit
margin and return on total capital near the industry's long-term averages. The overall outlook for financial
performance in 2013 is neutral. While experts believe pricing levels will remain high, the long-term trend
in demand remains negative (S&P, 2013f). This projection is consistent with the observation earlier in
this chapter that the Paper and Allied Products Industry is among U.S. industries with a longer-term
declining importance in the overall economy.
> The Petroleum Refining Industry saw considerable volatility in financial condition over the period of
analysis, with significant declines during the recent recession. Financial condition has since improved,
with 2012 net profit margin and return on total capital both slightly above long-term averages. Experts
report a positive near-term outlook for the industry, as North American refiners are expected to benefit
from global demand for U.S. refined products (S&P, 2013d). This projection is consistent with the
observation of increased export dependence for this industry.
> The Steel Industry is a highly cyclical industry, and showed varying financial performance over the period
of analysis, with the greatest declines in performance occurring during the recent recession. Beginning in
2010, the industry has achieved significant improvement in performance with 2012 net profit margin and
return on total capital slightly above long-term averages. Looking forward, analysts report a neutral
outlook forthe Steel Industry in 2013, as remaining excess steel capacity offsets expected increases in
volume of steel shipments (S&P, 2013h).
EPA concluded that all the Primary Manufacturing Industries would be in sufficiently strong financial condition
to absorb the costs of regulatory compliance without material, adverse economic/financial impact. Although the
industries experienced substantial decreases in financial performance during the recent recession, they have all
begun recovery from the downturn, with all nearing or, in some cases, already reaching their long-term average of
performance forthe assessed financial metrics.
2B-18
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Industry Profiles - Manufacturers
Figure 2B-8: Net Profit Margin for the Primary Manufacturing Industries from 1990 to 2012a
20.00%
15.0
10.00%
£> 5.00%
0.00%
-5.00%
-10.00%
-15.00%
1990
0 2011 2012
-Aluminum
-Chemicals
•Food & Kindred Products
-Paper
-Petroleum
-Steel
a. Data for 2012 reflects the most recent data available, which is for Q1 through Q3.
Source: U.S. DOC, 1990-2010 OFR
May 2014
2B-19
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 2B: Industry Profiles - Manufacturers
Figure 2B-9: Return on Total Capital for the Primary Manufacturing Industries from 1990 to 2012s
30.00%
25.00%
20.00%
15.00%
"ro
*5.
^ 10.00%
re
£
c
C 5.00%
3
at
cc
0.00%
-5.00%
-10.00%
-15.00%
~ Aluminum —¦—Chemicals —±—Food & Kindred Products N c Paper )lf Petroleum • Steel
a. Data for 2012 reflects the most recent data available, which is for Q1 through Q3.
Source: U.S. DOC, 1990-2010 OFR
1990 1991V992 1963 1994 1995 1996 1997 1998 1999 2000 2001 29B2 2003 2004 2005 2006 200712968 2009 2010 2011 2012
2B-20
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
3 Compliance Costs
EPA analyzed the costs and economic impacts of the existing and new unit provisions of the final rule and other
options EPA considered as described in Chapter 1: Introduction. Key inputs for these analyses include the
estimated costs to facilities subject to the final rule (regulated facilities or Electric Generators and Manufacturers)
to comply with and to the State and federal governments to administer the final rule and other options considered.
This chapter describes the methodology and data that EPA used to calculate industry-level, annualized
compliance costs, and how EPA uses these costs to analyze the rule's economic impacts.
The Technical Development Document (TDD) provides a detailed description of compliance technologies as well
as discusses development of technology and administrative costs to existing facilities to comply with, and costs to
permitting authorities to administer, the final rule and other options considered (U.S. EPA, 2014d).
The following sections of this chapter describe:
> The development of costs to facilities for complying with the existing unit provision of the final rule and
other options considered, including the compliance-related outlays for certain administrative activities
incurred by regulated facilities (Section 3.1)
> The development of costs for complying with the new unit provision of the final rule and other new unit
options EPA considered for installing entrainment control technology (Section 3.2)
> Compliance costs for both the existing unit and new unit provisions of the final rule (Section 3.3)
> The development of costs to States and the federal government for administering the existing unit
provision of the final rule and other options considered (Section 3.4)
In developing compliance costs for the analysis, generally EPA followed closely the analysis approaches and
impact evaluation concepts used in the analysis for the previous CWA §316(b) regulatory analyses, including the
proposed rule. To the extent possible, EPA also relied on the same data sources.49
The cost analysis presented in this chapter assumes that all facilities with cooling water system impoundments
will qualify as baseline CCRS and will meet the impingement mortality performance standard under the final rule
and other options considered without installing additional compliance technology.5" Therefore, EPA did not
assign additional technologies to these facilities and assigned administrative costs commensurate with baseline
CCRS under the final rule and other options considered. To the extent that some of these facilities do not qualify
as baseline CCRS, and would therefore need to install additional compliance technology and meet additional
administrative requirements, the total costs reported in this chapter may be underestimates. See Memorandum to
the Record (DCN 12-2501) forthe range of total compliance costs based on whether these facilities would need to
install additional compliance technology and meet additional administrative requirements.
3.1 Compliance Costs for Existing Units
EPA estimated costs to facilities for complying with the existing unit provision of the final rule and other options
EPA considered. In the remainder of this section, the term final rule refers to the existing unit provision of the
49 For more information on these analyses, see Chapter Bl: Summary' of Compliance Costs in the suspended 2004 Economic and
Benefits Analysis for the Final Section 316(b) Phase II Existing Facilities Rule (U.S. EPA, 2004a) and Chapter CI: Summary' of Cost
Categories and Key Analysis Elements for Existing Facilities in the 2006 Economic and Benefits Analysis for the Final Section 316(b)
Phase III Existing Facilities Ride (U.S. EPA, 2006).
50 For Proposal Option 2, EPA also assumed that these facilities will meet entrainment technology requirements, as applicable.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
final rule. Development of compliance costs involves four principal steps, the last two of which are the focus of
the discussion below:
1. Determining the set of facilities potentially installing compliance technologies. See the TDD report and
Appendix H: Sample Weights of this document for details.
2. Developing costs to regulated facilities, which are broken into four main cost components:
> Installing and operating compliance technology
> Installation downtime
> Energy penalty
> Administrative activities
See the TDD for details.
3. Developing a technology-installation schedule based on the years during which facilities will meet
regulatory requirements. This schedule supports analysis of the timing of compliance costs, benefits, and
the potential impact on electricity supply resulting from shutdown of generating units during compliance
technology installation.
4. Estimating total industry costs for all regulated facilities under the final rule and other options considered.
EPA used an analysis period that begins in 2013, the expected promulgation year of the final rule at the time EPA
completed the analyses, with all options analyzed as of that date.51 All costs are in 2011 dollars, based on the data
available at the time EPA developed the analysis framework.
3.1.1 Analysis Approach and Data Inputs
Facilities Potentially Incurring Compliance Costs
The final rule will apply to existing facilities with a design intake flow (DIF) for cooling water exceeding
two million gallons per day (mgd) (for more details on application of this rule, see Chapter 1: Introduction). The
other options considered would also apply to the same overall set of facilities; however, the uniform national
standards and associated technology requirements for Proposal Option 4 would apply only to facilities with DIF
of at least 50 mgd.
As detailed in the TDD, EPA developed costs for technology to reduce impingement mortality (IM) and
entrainment (E). The cost estimates reflect the incremental costs attributed only to the final rule and other options
considered, accounting for the cooling water intake systems that are already present in the baseline. The specific
technologies, which vary in their application by option, reduce IM&E through one of two methods:
> Exclusion of organisms through implementation of design and construction technologies to reduce IM
> Flow reduction through conversion of cooling systems from once-through to recirculating operation to
reduce the DIF and IM&E.
As discussed in detail in Appendix H, the final rule analysis focuses on 544 Electric Generators and 521
Manufacturers.52 Using the information collected through the 316(b) survey, EPA determined that certain
regulated facilities would already meet the performance requirements of a given option and did not assign
51 At the time EPA conducted the cost and economic impact analyses, the Agency expected to promulgate the final rule in 2013.
Consequently, all cost and economic analyses assume 2013 to be the rule promulgation year. Because the rule is being promulgated in
the first half of 2014, EPA concluded that it would be reasonable to continue using 2013 as the assumed promulgation year for the
regulatory analysis because differences in the estimated costs and benefits of the rule due to this slight imprecision are minimal.
52 EPA estimated the number of Electric Generators using facility-count based weights and the number of Manufacturers using technical
1weights; these facility counts exclude baseline closures. For details, see Appendix H.
3-2
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
additional technology requirements or associated costs. Specifically, these facilities either (1) have a closed-cycle
recirculating system (CCRS) in place,53 (2) already meet IM reduction requirements in the baseline, or (3) are
subject to State requirements that are at least as stringent as those of the final rule or one of the other options
considered (Table 3-1). However, these facilities are still subject to the rule, and would therefore incur costs for
certain non-technology related activities (e.g., permitting, and compliance monitoring and reporting).
Consequently, EPA estimated compliance technology costs for 305 Electric Generators and 297 Manufacturers
under the final rule, 290 Electric Generators and 101 Manufacturers under Proposal Option 4, and 341 Electric
Generators and 307 Manufacturers under Proposal Option 2. Table 3-1 and Table 3-2 present weighted counts of
Electric Generators and Manufacturers, respectively.
Table 3-1: Number of Electric Generators with and without Additional Technology Requirements for the
Final Rule and Other Options Considered1
Facility Categories
Re
gulatorv Option
Proposal
Option 4
Final Rule-
Existing
Units
Proposal
Option 2
Total number of Electric Generators
544
544
544
Facilities meeting performance requirements in their baseline
- Facilities with baseline closed-cycle recirculating systems'5
- New York facilities with DIF>20mgdc
- California facilities that use coastal and estuanne waters for cooling0
- Facilities with intake velocity equal to or less than 0.5 feet per second
254
149
28
16
35
239
149
28
16
35
203
149
28
16
8
- Other facilities meeting performance requirements in the baseline
26
11
2
Number of Electric Generators with additional technology requirements
290
305
341
a. These are weighted facility counts estimated using facility count-based weights; these values are rounded to the nearest integer and may not sum to the
reported totals due to rounding (see Appendix H).
b. These counts include 40 facilities with cooling water system impoundments. The cooling water intake systems for these facilities may qualify as baseline
CCRS, in which case these facilities may meet the performance requirements under the final rule and other options considered without needing to install
additional compliance technology.
c. These facilities are subject to State regulations that are at least as stringent as the final rule and the other options considered.
Source: U.S. EPA analysis for this report
53 The final rule definition of a closed-cycle recirculating system includes cooling water impoundments that meet specified criteria (see
§125.92, Special definitions, (c) (2) of the final rule). Subject to site-specific review by Permit Directors, these facilities may meet the
rule's BTA standard for impingement mortality through operation of a CCRS in the baseline, and thus might not need to install
additional technology to meet the rule's BTA standard for impingement mortality. At present, EPA does not know whether individual
facilities that are known to have impoundments will qualify as baseline CCRS. The cost information presented in this chapter assumes
that all facilities known to have impoundments as part of their cooling water intake system will meet the baseline CCRS criterion and
would not incur additional technology cost (but would incur certain administrative costs). To the extent that some of these facilities do
not qualify as baseline CCRS, the costs reported in this chapter may be underestimates. Thus, these costs are the lower value in a
range based on whether facilities with an impoundment will or will not qualify as baseline CCRS. See Memorandum to the Record
(DCN 12-2501) for the range of costs that could occur based on whether these facilities would need to install additional compliance
technology.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
Table 3-2: Number of Manufacturers with and without Additional Technology Requirements for the Final
Rule and Other Options Considered1

Regulatory Option

Final Rule-

Facility Categories
Proposal
Option 4
Existing
Units
Proposal
Option 2
Total number of Manufacturers
521
521
521
Facilities meeting performance requirements in their baseline
- Facilities with baseline closed-cycle recirculating systems6
419
103
224
103
214
103
- New York facilities with DIF>20mgdc
20
20
20
- Facilities with intake velocity equal to or less than 0.5 feet per second
79
79
79
- Other facilities meeting performance requirements in the baseline
218
23
13
Number of Manufacturers with additional technology requirements
101
297
307
a. These are weighted facility counts estimated using technical weights; these values are rounded to the nearest integer and may not sum to the reported totals
due to rounding (see Appendix H).
b. These counts include 24 facilities with cooling water system impoundments. The cooling water intake systems for these facilities may qualify as baseline
CCRS, which case these facilities may meet the performance requirements under the final rule and other options considered without needing to install
additional compliance technology.
c. These facilities are subject to State regulations that are at least as stringent as the final rule and the other options considered.

Source: U.S. EPA analysis for this report

Costs of Installing and Operating Compliance Technology
As detailed in the TDD, the major components of costs to install and operate compliance technology costs are:
> Capital costs: These costs include the cost of designing and installing the assigned compliance
technology. EPA estimates that facilities will require four years to install cooling towers and thus spread
each facility's capital costs for cooling tower installation over four years. The Agency estimates that
installation of non-cooling tower technologies will take less than one year and expects that facilities will
incur all the associated capital costs in one year.
> Pilot study. These costs are associated with wedgewire screens and include testing temporary smaller
scale screens suspended from a floating structure in the waterbody near where screens would be located.
EPA expects that only Manufacturers will have to perform this study and that facilities will incur these
costs in the year of technology installation.54
> Annual operation and maintenance (O&M) costs: These costs include outlays for operation, maintenance,
and upgrading activities that occur annually, and include fixed and variable components. In addition,
O&M costs also account for the auxiliary energy required to operate an assigned compliance technology.
Depending on whether a facility is required to install IM technology or a cooling tower, facility type (i.e.,
Electric Generator or Manufacturer), and the facility's baseline operating circumstances, EPA analyzed
this increase in energy requirement as either a reduction in generated electricity that is available for sale
or use, or as an increase in the variable production cost of sold or used electricity.
In addition to these cost components, which EPA estimated for each facility, EPA also accounted for two
technology-related effects that result in additional costs to facilities as follows:
> Energy penalty. This effect results from reduced energy-conversion efficiency of the electricity
generating system, which occurs with operation of retrofitted, closed-cycle recirculating system
compliance technologies. This reduction in energy-conversion efficiency is not present in IM
technologies. As is the case with the auxiliary energy requirement, depending on facility type (i.e.,
Electric Generator or Manufacturer) and baseline facility operating circumstances, EPA analyzed energy
54 This study is conducted to meet both the impingement mortality and entrainment requirements under § 125.94(c) and § 125.94(d),
respectively, given that wedgewire screens can reduce only impingement mortality or both impingement mortality and entrainment,
depending on selected mesh size. In all cases, the pilot study helps resolve design and feasibility issues regarding debris loading. For
details, see the TDD.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
penalty as either a reduction in generated electricity that is available for sale or use or as an increase in
production cost of sold or used electricity.
> Installation downtime: Installation of certain compliance technologies will require a one-time, temporary
downtime period for the facility.
Appendix I: Energy Effects provides details of the methods EPA used to estimate costs associated with an
increase in auxiliary energy requirement, energy penalty, and downtime and their effects on facility
operations.
The TDD describes the methodology EPA used to estimate costs for the final rule and other options EPA
considered.
Administrative Activities and Associated Costs
Under the final rule, regulated facilities will undertake a range of administrative activities to determine applicable
compliance requirements, obtain needed permits, and perform periodic monitoring and reporting subsequent to
initial compliance efforts. In analyzing the costs of the final rule and other options considered, EPA estimated
costs for the following three categories of administrative activities:
> Start-up activities: EPA assumed that start-up activities will begin during the first year after promulgation
of the final rule, 2014, and recur every five years.
> Initial permitting activities: These activities include review of permit applications and other information
compiled by regulated facilities during the initial permitting process. The Agency assumed that facilities
with post-promulgation permits expiring after December 31, 2016, will begin these activities three years
before expiration of their first post-promulgation permit and all other regulated facilities will begin these
activities three years prior to expiration of their second post-promulgation permit.
> Annual activities: These activities include collection and review of monitoring data, and other information
produced by regulated facilities on an annual basis. The Agency assumed that facilities will begin these
activities during the technology-installation year.
> Non-annually recurring activities: These activities include a subset of initial permitting activities that
repeat periodically in the future. While under the final rule these application activities are required every
permit cycle, Permit Directors will likely not require facilities to repeat them as soon as the second permit
cycle after the initial compliance with regulatory requirements. Consequently, EPA assumed that
recurrence of these activities will begin 10 years after the initial permitting activities begin, i.e., during the
third post-compliance permit cycle, and recur every five years after that. EPA estimates that only 10
percent of regulated facilities would undertake these non-annually recurring activities.55
For details on these activities as well as time and labor requirements associated with these activities, see the
Information Collection Request for Cooling Water Intake Structures at Existing Facilities (Final Rule) (Final
Rule ICR) (U.S. EPA, 2014b). EPA estimated costs for these activities by first developing 2011 hourly labor rates
by labor category as follows:
> EPA obtained raw wage rates for all facility and contractor employees, and for State and federal
government employees, from the Bureau of Labor Statistics Occupational Employment Statistics for May
2011 (http://www.bls.gov/oes/'). EPA restated these hourly wages forward from the second quarter of
2011 to the annual average for 2011 using the Bureau of Labor Statistics' Employment Cost Index
(http ://www.bls .gov/ncs/ect/home .htm).
55 Because EPA cannot determine which regulated facilities will undertake these activities, the Agency assigned 10 percent of the costs
for each recurring activity to each regulated facility.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
> To account for additional labor-related costs associated with benefits, indirect costs (e.g., overhead), and
fee, EPA developed the following add-ons:
¦ A fringe benefits multiplier applicable to unloaded wages, ranging from 1.42 to 1.65 by occupation
category, based on the BLS Employer Costs for Employee Compensation as of the second quarter of
2012 (http://www.bls.gov/news.release/archives/ecec 12072011.htm).
¦ An indirect cost multiplier of 15 percent for facilities and States and 50 percent for contract services;
applicable to wages plus benefits.
¦ Contractor fee multiplier of 8 percent for contract services; applicable to the sum of wages, benefits,
and indirect costs.
> These calculations yield fully loaded labor costs, by labor category, in 2011 dollars.
Table 3-3: Average Hourly Labor Rates for Facility Employees
and Contract Workers by Labor Category ($2011)
Labor Categories
Hourly Rate3
Facility Employees
Facility Manasiement
$95.90
Fconomist

Junior Technical

CAI) Operator
$37 10
Clerical
$21.70
Contractor-Provided Employees
Manaaer
$ 126.90
Biolosiist
$63 50
Statistician
$XI 70
Biological Technician
$43.60
a. Fully loaded hourly rates include base labor costs with add-ons for employee benefits,
overhead, and fee (for contracted employees).

Source: U.S. EPA analysis for this report

In addition to labor costs, administrative costs also include non-labor components, which EPA estimated as a per-
hour add-on to labor cost. EPA also restated these costs in 2011 dollars using Gross Domestic Product (GDP)
deflator index published by the U.S. Bureau of Economic Analysis (BEA).
EPA multiplied these unit costs - labor rates and non-labor costs - by the number of hours, by labor category, and
activities that would be required for each administrative activity, and summed these costs across the
administrative activities.
Development of Technology-Installation Years
The years in which individual regulated facilities will install compliance technologies are an important input to
the time profile of costs that regulated facilities and society will incur due to the final rule. This profile is
necessary for two reasons:
> To estimate the net present value of compliance costs to the regulated industry> and society. The longer
facilities wait to install compliance technologies, the lower is the present value of future cost outlays.
> To analyze the effects of technology-installation downtime on electricity markets. If a large quantity of
generating capacity is out of service for compliance-technology installation at the same time in a given
North American Electric Reliability Council (NERC) region, this could lead to reduced reserve margins
and jeopardize the reliability of power operations in that NERC region. Electricity production costs could
also increase in the short term in an affected region if a substantial fraction of lower production cost
capacity were out of service in that region at the same time.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
EPA expects that each regulated facility will study compliance technologies and operational measures, and
subsequently install, incorporate, and optimize the technology most appropriate for each site following rule
promulgation. In evaluating compliance technologies, EPA considered the magnitude and complexity of process
changes and new equipment installations that would be required at facilities to comply with the final rule. The
standards and limitations represent Best Technology Available (BTA) to minimize the adverse environmental
impact associated with the use of cooling water intake structures.
In contrast to the proposed rule, the final rule gives Permit Directors the authority to establish specific compliance
requirements and compliance schedules and does not include a requirement for compliance with the IM
performance standards within the specific universal timeframe of eight years of promulgation. EPA expects,
however, that the existing unit provision of the final rule will generally result in compliance within a similar time
frame. EPA did not specify universal compliance dates for IM standards because the specific method of
compliance with these standards is tied to the determination of entrainment control requirements. Specifically,
under the existing unit provision of the final rule, facilities must meet IM requirements as soon as practicable after
issuance of a final permit establishing the entrainment control requirements determined by the Permit Director.
The final rule aligns compliance deadlines for IM and entrainment control requirements. If technologies required
for compliance with IM and entrainment control standards overlap, which could result in facilities needing more
time to comply with IM standards, the Permit Director will schedule compliance with the IM requirements to
match the schedule for the entrainment control requirements.
The combination of (1) permit reissuance, (2) the Permit Director's determination of BTA for entrainment
control, and (3) the subsequent schedule of requirements for IM, will result in some facilities, particularly those
already in a permit proceeding, or with controls similar to what the new permit requires, being in compliance
within a very short time frame. Some facilities that are not now in a permitting proceeding may need as much as
three years to conduct studies, including but not limited to the benefits valuation, the Entrainment
Characterization Study, and other entrainment studies, and to collect data (for details on specific studies and data
to be collected, see Final Rule ICR). Finally, depending on the types of control selected, facilities may need
additional time to design, construct, and implement their technologies. In some cases, the Permit Director's
determination for entrainment control may result in a facility meeting both the IM and entrainment control BTA
requirements in fewer than eight years. All facilities will be required to follow their schedule as determined by the
Permit Director.
The final rule schedule anticipates that facilities will have three years before the first post-promulgation expiration
of their National Pollutant Discharge Elimination System (NPDES) permit, to conduct studies and to collect data.
Facilities with NPDES permits expiring after December 31, 2016 must submit this information to States and the
federal government for review no later than 180 days before permit expiration. EPA expects the review of the
submitted materials to take approximately a year, at which time the permitting authorities determine the
requirements and conditions to include in the new permit. Facilities with permits expiring after promulgation of
the final rule but before December 31, 2016 (i.e., before these facilities can be reasonably expected to complete
the required studies and collect the necessary data) may request that permitting authorities temporarily waive the
316(b) requirements. In such cases, the permitting authorities must determine the schedule for submission of the
waived permit application requirements. Regardless of when NPDES permits come up for renewal after
promulgation of the final rule, the schedule of requirements established by the permitting authorities will ensure
compliance with those requirements as soon as practicable. In developing technology-installation schedules for
Electric Generators, EPA expects permitting authorities to take measures to ensure adequate energy reliability and
necessary grid reserve capacity during any expected facility outage associated with installation of compliance
technology.56
56 These measures may include establishing a staggered schedule for multiple facilities serving the same localities. The permitting
authorities may consult with independent system operators and state public utility regulatory agencies when establishing a schedule
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
As stated above, EPA assumed 2013 to be the rule promulgation year and developed the technology-installation
schedule used in the regulatory analysis relative to that year. For Electric Generators and Manufacturers for which
the first expiration of their NPDES permits following rule promulgation occurs after December 31, 2016, EPA
assumed that the permitting authorities will review submitted materials during the first year and facilities will
install IM technologies during the second year of their first post-promulgation permit cycle. For all other
facilities, EPA assumed that the permitting authorities will review submitted materials during the first year and
facilities will install IM technologies during the second year of their second post-promulgation permit cycle.
These assumptions result in a five-year technology-installation period of 2018 through 2022.
Because design and installation of some entrainment control technologies (i.e., cooling towers) may require more
time than those required for IM technology, EPA assumed a longer period to install entrainment control
technology. Specifically, under Proposal Option 2, the only option for which EPA analyzed installation of
entrainment control technologies, non-nuclear Electric Generators and Manufacturers required to meet the
entrainment control standards would have until 2025 to do so, while nuclear Electric Generators would have to
meet these standards no later than 2030. EPA assumed that regulated facilities would install cooling towers during
the five-year windows of 2021 through 2025 and 2026 through 2030, respectively. As discussed in Appendix I,
the Agency assumed that nuclear Electric Generators would coordinate with Permit Directors so that cooling
towers could be installed during regular refueling outages. For this analysis, EPA assumed that nuclear facilities
would install cooling towers during the third or fourth 5-year window after promulgation of the final rule and all
other facilities would do so in the year of their second or third post-promulgation NPDES permit renewal.
Because EPA was unable to identify those facilities for which Permit Directors would establish entrainment
control technology as BTA on a site-specific basis, the Agency did not analyze technology costs associated with
these site-specific requirements. Consequently, the cost and economic analyses conducted in support of the final
rule assume that under the existing unit provision of the final rule and Proposal Option 4, Electric Generators and
Manufacturers install IM technology only. These analyses also assume that under Proposal Option 2, Electric
Generators with DIF exceeding 125 mgd install only cooling towers and all other Electric Generators install only
IM technologies. Under Proposal Option 2, a small number of Manufacturers are assigned IM technologies in
addition to entrainment control technologies due to the use of non-contact cooling water, and contact cooling
water and process water at those facilities.
Although EPA did not estimate technology costs for facilities for which Permit Directors establish entrainment
technology as BTA on a site-specific basis, EPA did include the costs for data collection and studies that facilities
will need to perform in order to provide information to Permit Directors to make these site-specific
determinations. EPA included these costs in the administrative costs estimated for the final rule and other options
considered.
To summarize, EPA made the following assumptions regarding the timing of technology installation:
> Facilities will install IM technology during the five-year window of 2018 through 2022.
> For the regulatory option that requires installation of entrainment control technology (Proposal Option 2),
non-nuclear Electric Generators and Manufacturers will complete installation of entrainment technology
during the five-year window of 2021 through 2025 (following a five-year permit cycle), in the year of
their second or third post-promulgation NPDES permit renewal. Each of these years represents the last of
the four years required to install a cooling tower.
> For Proposal Option 2, nuclear Electric Generators required to install entrainment control technologies
will complete installation during the five-year window of 2026 through 2030, in the year of their third or
for Electric Generators. The permitting authorities may determine that extenuating circumstances warrant establishing a different
compliance date for manufacturing facilities.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
fourth post-promulgation ISI. Again, each of these years represents the last of the four years required to
install a cooling tower.
> For Proposal Option 2, EPA assumed that a small number of Manufacturers assigned both IM and
entrainment control technologies would install both technologies at the same time, during the five-year
window of 2021 through 2025. Again, each of these years represents the last of the four years required for
installation of entrainment control technology.
EPA assumed that regulated facilities meeting the compliance requirements of the final rule and other options
considered in the baseline would install no additional technology nor incur additional technology-related costs.
However, these facilities would still have to undertake certain permit-related activities and incur costs associated
with these activities. To account for these activities, the Agency developed facility-specific cost-incurrence
schedules relative to these facilities' post-promulgation NPDES expiration years using the same approach as that
used for facilities installing compliance technologies.
EPA notes that the assumed technology-installation years may not be the actual years when installation occurs.
However, these assumptions reflect the approximate years, and thus provide a practical basis for the cost and
economic impact analysis. For the final rule and Proposal Option 4, these assumptions result in an overall
technology-installation window of nine years, 2014 through 2022. For Proposal Option 2, these assumptions
result in a 17-year technology-installation window of 2014 through 2030 (including years during which facilities
would undertake some administrative activities prior to installation (see Administrative Activities and Associated
Costs, page 3-5).57
Development of Total Compliance Costs
EPA developed total compliance costs for Electric Generators and Manufacturers by aggregating various
components of compliance costs discussed in the preceding sections as follows:
> First, EPA calculated total compliance costs for the 519 regulated facilities (313 Electric Generators and
206 Manufacturers), for which EPA explicitly developed and analyzed compliance costs.58
> The Agency calculated compliance costs on a "year-explicit" basis relative to the year when it assumed
facilities would incur compliance costs. To do this, EPA restated compliance costs from the preceding
step to specific cost-incurrence years, in 2011 dollars, using:
¦ Construction Cost Index (CCI) from McGraw Hill Construction
¦ Employment Cost Index (ECI) published by the Bureau of Labor Statistics (BLS)
¦ Electricity price projections from the Annual Energy Outlook 2012 (AEO2012) (U.S. DOE,
2012c)
¦ BEA's GDP deflator index.59
57 EPA conducted the cost and economic impact analyses on a calendar-year basis; for the economic impact analyses, EPA treated
calendar year 2014 as the first post-promulgation analysis year.
58 Facility counts exclude baseline closures.
59 Specifically, EPA restated all compliance technology costs to an estimated technology-installation year using the Construction Cost
Index (CCI) from McGraw Hill Construction, and all administrative costs to an estimated cost incurrence year using the Employment
Cost Index (ECI) from the Bureau of Labor Statistics. The Agency used the average of the year-to-year changes in the CCI and ECI,
respectively, over the most recent 10-year reporting period. Because CCI and ECI are nominal cost-adjustment indices, the resulting
costs are as of the compliance year or cost incurrence year, and in the dollars of that year. To restate compliance costs in 2011 dollars,
the Agency deflated the nominal dollar values to 2011 using the average of the year-to-year changes in the Gross Domestic Product
(GDP) deflator index published by the U.S. Bureau of Economic Analysis (BEA) over the most recent 10-year reporting period. As a
result, all dollar values reported in this analysis are in constant 2011 dollars. Energy penalty and downtime costs were adjusted based
on Annual Energy Outlook 2012 (AEO2012) electricity price projections. Because the AEO2012 electricity price projections are in
constant dollars, these adjustments yielded values in 2011 dollars.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
EPA developed and applied the CCI, ECI, and GDP adjustment factors through 2020, and applied the
AEO adjustment factors through 2035, the year through which EIA reports these projections. Because
long-term price projections for the individual categories of costs adjusted using these factors are uncertain
after these years, EPA assumed only zero real growth (i.e., no change beyond general inflation) after 2020
and 2035, respectively.6"
> EPA discounted all costs to the assumed year of rule promulgation, 2013, at a rate of 7 percent.61
> EPA annualized one-time costs and other costs that recur on other than an annual basis, over a specific
useful life, implementation, and/or event recurrence period, using the 7 percent discount rate:
¦ Capital costs of non-cooling tower technologies: 20, 25, or 30 years
¦ Capital costs of cooling towers: 30 years
¦ Pilot study costs: 30 years62
¦ Downtime, and initial permitting costs: 30 years
¦ Non-annually recurring permit-related costs: five and six years.
> EPA added annualized capital, pilot-study, downtime, and initial and non-annually recurring permitting
costs to annual O&M, energy penalty, and administrative costs to derive total annualized compliance
costs, where costs are expressed on an equivalent annual cost basis.
> EPA applied sample weights to these costs to estimate costs for 544 Electric Generators and 521
Manufacturers. For details on development and application of sample weights, see Appendix H.
EPA considered costs on both a pre-tax and after-tax basis. Pre-tax costs provide insight on the total expenditures
as initially incurred by the facilities. After-tax costs are a more meaningful measure of compliance impact on
privately owned, for-profit facilities, and incorporate approximate capital depreciation and other relevant tax
treatments in the analysis. EPA calculated the after-tax value of compliance costs by applying combined federal
and State tax rates to the pre-tax costs for privately owned, for-profit facilities.63 EPA used State corporate rates
from the Federation of Tax Administrators (http://www.taxadmin.org/) combined with federal corporate tax rate
schedules from the Department of the Treasury, Internal Revenue Service. EPA uses either pre- or after-tax
compliance costs in different analyses, depending on the purpose of each analysis.
3.1.2 Key Findings
Electric Generators
As reported in Table 3-4, EPA estimates, on a pre-tax basis, that 544 Electric Generators will incur $224.9 million
in costs under the existing unit provision of the final rule and $224.1 million and $3,763.5 million under Proposal
Options 4 and 2, respectively. On an after-tax basis, these costs are $147.6 million for the final rule, $147.0
million for Proposal Option 4, and $2,545.7 million for Proposal Option 2.
00 Hie Agency concluded that because 2020 is in the middle of a 5-year technology-installation window for IM technology installation
(2018-2022) and only one year before the cooling tower-installation window, this year should closely reflect the operating conditions
of these regulated facilities at the time of technology installation.
01 The rate of 7 percent is an estimate of the opportunity cost of capital to society.
02 Thirty years is the longest useful life assumed for any IM reduction and entrainment control technologies considered for this rule.
03 Government-owned entities and cooperatives are not subject to income taxes. For details on the approach EPA used to distinguish
among the government-owned, privately owned, and cooperative ownership categories for Electric Generators, see Chapter 4:
Economic Impact Analysis - Electric Generators. All Manufacturers are privately owned.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
Table 3-4 also presents costs by North American Electric Reliability Corporation (NERC) regions. Each NERC
region is responsible for managing electricity reliability issues in its region, based on available capacity and
transmission constraints. Service areas of the member facilities determine the boundaries of the NERC regions.
Because of differences in operating characteristics of Electric Generators across NERC regions, as well as
differences in the baseline economic and electric power system regulatory circumstances of the NERC regions
themselves, the final rule and other options considered may affect costs, profitability, electricity prices, and other
impact measures differently across NERC regions. Under the final rule, EPA estimates that after-tax compliance
costs will be the highest in the SERC region and the lowest in the WECC region. These findings are also true
under the two other options considered in development of this rule.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
Table 3-4: Annualized Compliance Costs to Electric Generators by NERC Region, for the Final Rule and
Other Options Considered - Existing Units (Millions; $2011; at 2013)a'

One-Time Costs

Recurring Costs

Monitoring,
Record

Permit-
Related

Initial
Initial and

Keeping,

Non-

NERC
Region0
Capital
Technology
Pilot Study
Installation
Downtime
Permit
Application
Follow-Up
Start-Up
O&M
and
Reporting
Energy
Penalty
Annually
Recurring
Total
Proposal Option 4
Pre-Tax Compliance Costs
ASCC
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
FRCC
$10.2
$0.0
$5.0
$0 9
$0.0
$3.6
$0.1
$0 0
$0.1
$20.0
IIICC
?
$0 0
)
$0 1
$0.0

)
$0 0
$0 0
$2.5
MRO
1
$0.0
$0 1
$2 5
$0.0
$3 2
$0.3
$0 0
$0.4
$12.6
NPCC
S
$0.0
$0.0

$0.0
$3 8
$0.3
$0 0
$0 2
$13.6
RFC
$29 9
$0.0
$0.0
$5 3
$0 1
$21.0
$0.8
$0 0
$0 8
$57.9
SFRC
)
$0.0
$18.1
$6 2
$0 1
$16.6
$0 8
$0 0

DC
DC
oc
&
SPP
1
$0.0
$7.3
$0.8
$0.0

$0.2
$0 0
$0 1
$12.2
i ri ;
>
$0.0
$0.3
$2 1
$0.0
$4 6
2
$0 0
$0 3
$16.1
wfcc
$0.1
$0.0
$0.0
$0.1
$0.0
$0.0
$0.2
$0.0
$0.0
$0.5
Total
$111.7
$0.0
$30.9
$19.6
$0.3
$55.6
$3.0
$0.0
$3.1
$224.1
After-Tax Compliance Costs
ASCC
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
FRCC
$6.3
$0.0
$3.1
$0.6
$0.0
$2.2
$0.1
$0.0
$0.1
$12.4
IIICC
*
$0.0
$0.0
$0 1
$0.0
$0.6
$0.0
$0 0
$0 0
$1 5
MRO
)
$0.0
$0.1

$0.0
$2.6
$0.2
$0 0
$0 3
$10.0
NPCC

$0.0
$0.0
$0 9
$0.0
$2.3
2
$0 0
$0 1
$8.1
RFC
2
$0.0
$0.0
$3 4
$0.0
$12.8
$0.5
$0 0
$0 5
$35.4
SFRC
$31 1
$0 0
$11.1
$4 3
$0 1
$12.5
>
$0 0
$0 7
$60.3
SPP
$1 3
$0.0

$0 5
$0.0

$0 1
$0 0
$0.1
$7.6
i ri ;
)
$0.0
2

$0.0
$3 2
2
$0 0
$0.2
$11.4
WFCC
$0.1
$0.0
$0.0
$0.1
$0.0
$0.0
$0.1
$0.0
$0.0
$0.4
Total
$73.3
$0.0
$19.0
$13.1
$0.2
$37.3
$2.0
$0.0
$2.1
$147.0
Final Rule-Existing Units
Pre-Tax Compliance Costs
ASCC
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
FRCC
2
$0 0
)
$0 9
$0 0
$3 6
1
$0 0
$0 1
$20.0
IIICC
$1.3
$0.0
$0.0
$0 1
$0.0
$1.1
$0.0
$0 0
$0 0
$2.5
MRO
4
$0.0
$0.1
$2 5
$0.0
$3 2
$0.3
$0 0
$0.4
$13.0
NPCC
$7.7
$0.0
$0.0

$0.0
$3 9
$0.3
$0 0
$0 2
$13.7
RFC
$30 0
$0.0
$0.0
$5 3
$0 1
$21.1
$0.8
$0 0
$0 8
$58.1
SFRC
)
$0.0
$18.1
$6 2
$0 1
$16.6

$0 0
$1.0
$88.8
SPP
1
$0.0
$7.3
$0.8
$0.0
$1.7
$0.2
$0 0
$0 1
$12.2
i ri ;
>
$0.0
$0.3
$2 1
$0.0
$4 6
2
$0 0
$0 3
$16.1
WFCC
$0.1
$0.0
$0.0
$0.1
$0.0
$0.0
$0.2
$0.0
$0.0
$0.5
Total
$112.2
$0.0
$31.9
$19.6
$0.3
$55.8
$3.0
$0.0
$3.1
$224.9
After-Tax Compliance Costs
ASCC
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
FRCC
*
$0.0
1
$0 6
$0.0
$2 2
1
$0 0
$0 1
$12.4
IIICC
<
$0.0
$0.0
$0 1
$0.0
$0 6
$0.0
$0 0
$0 0
$1.5
MRO
$5 2
$0.0
$0.1

$0.0
$2 6
$0.2
$0 0
$0 3
$10.2
NPCC
>
$0.0
$0.0
$0 9
$0.0
$2 3
2
$0 0
$0 1
$8 3
RFC
?
$0 0
$0.0
$3 4
$0 0
$12.9
>
$0 0
$0 5
$35.6
SFRC
$31 1
$0.0
$11.1
$4 3
$0 1
$12.5
$0.6
$0 0
$0 7
$60.3
SPP
$1 3
$0.0
$4.5
$0 5
$0.0
$1.1
1
$0 0
$0.1
$7.6
i ri ;
)
$0.0
2

$0.0
$3 2
2
$0 0
$0 2
$1 1.4
WFCC
$0.1
$0.0
$0.0
$0.1
$0.0
$0.0
$0.1
$0.0
$0.0
$0.4
Total
$73.7
$0.0
$19.0
$13.1
$0.2
$37.5
$2.0
$0.0
$2.1
$147.6
Proposal Option 2
Pre-Tax Compliance Costs
ASCC
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
FRCC
$138.0
$0.0
$15.0
$0.0
$0.0
$41.6
$1.2
$46.6
$0.0
$242.5
3-12
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
Table 3-4: Annualized Compliance Costs to Electric Generators by NERC Region, for the Final Rule and
Other Options Considered - Existing Units (Millions; $2011; at 2013)a'

One-Time Costs

Recurring Costs

Monitoring,
Record

Permit-
Related

Initial
Initial and

Keeping,

Non-

NERC
Region0
Capital
Technology
Pilot Study
Installation
Downtime
Permit
Application
Follow-Up
Start-Up
O&M
and
Reporting
Energy
Penalty
Annually
Recurring
Total
HICC
$15.2
$0.0
$1.4
$0.0
$0.0
$3.7
$0.2
$1.2
$0.0
$21.8
MRO
$128.7
$0.0
$7.5
$0.5
$0.0
$39.6
$2.2
$51.5
$0.1
$230.1
NPCC
$114.3
$0.0
$10.2
$0.3
$0.0
$41.2
$1.2
$44.0
$0.0
$211.3
RFC
$685.5
$0.0
$42.1
$0.6
$0.1
$202.0
$5.3
$154.9
$0.1
$1,090.5
SERC
$780.3
$0.0
$100.0
$0.3
$0.1
$266.9
$6.7
$286.1
$0.0
$1,440.4
SPP
$69.9
$0.0
$5.0
$0.1
$0.0
$14.7
$1.0
$10.0
$0.0
$100.7
TRE
$231.2
$0.0
$11.4
$0.1
$0.0
$98.7
$2.2
$82.3
$0.0
$425.8
WECC
$0.1
$0.0
$0.0
$0.1
$0.0
$0.0
$0.2
$0.0
$0.0
$0.4
Total
$2,163.2
$0.0
$192.6
$1.9
$0.3
$708.4
$20.2
$676.6
$0.3
$3,763.5
After-Tax Compliance Costs
ASCC
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
FRCC
$86.9
$0.0
$9.3
$0.0
$0.0
$26.0
$0.8
$28.9
$0.0
$1 j2 I)
HICC
$9.3
$0.0
$0.9
$0.0
$0.0
$2.3
$0.1
$0.8
$0.0
$1 I
MRO
$91.8
$0.0
$4.7
$0.4
$0.0
$27.8
$1.5
$33.9
$0.1
$160.1
NPCC
$68.3
$0.0
$6.1
$0.2
$0.0
$24.7
$0.7
$26.3
$0.0
$126.3
RFC
$419.4
$0.0
$25.9
$0.4
$0.0
$123.9
$3.3
$95.3
$0.1
$668.4
SERC
$572.0
$0.0
$78.1
$0.2
$0.1
$194.8
$4.7
$212.6
$0.0
$1,062.6
SPP
$44.2
$0.0
$3.1
$0.1
$0.0
$9.3
$0.6
$6.3
$0.0
$63.7
TRE
$163.0
$0.0
$8.3
$0.1
$0.0
$68.4
$1.6
$57.6
$0.0
$298.9
WECC
$0.1
$0.0
$0.0
$0.1
$0.0
$0.0
$0.1
$0.0
$0.0
$0.3
Total
$1,454.9
$0.0
$136.5
$1.4
$0.2
$477.2
$13.5
$461.7
$0.2
$2,545.7
a. ASCC - Alaska Systems
Coordinating Council; FRCC - Florida Reliability Coordinating Council; F1ICC - Flawaii Coordinating Council; MRO -
Midwest Reliability Organization; NPCC - Northeast Power Coordinating Council; RFC - ReliabilityFirst Corporation; SERC - Southeastern Electric
Reliability Council; SPP - Southwest Power Pool; TRE - Texas Reliability Entity, and WECC - Western Energy Coordinating Council.
b. As described earlier in this chapter, the costs presented in this table assume that all facilities with cooling water impoundments qualify as baseline
CCRS, and incur no additional technology costs for regulatory compliance (but do incur administrative costs). Thus, these costs are the lower value in a
range based on whether facilities with an impoundment will or will not qualify as baseline CCRS and would not need to install additional technology. See
Memorandum to the Record (DCN 12-2501) for the range of costs that could occur based on whether these facilities would need to install additional
compliance technology.
c. No explicitly analyzed facilities are located in the ASCC NERC region; an
mplicitly analyzed facility in ASCC facility was grouped with facilities in
the WECC region (for discussion on explicitly and analyzed facilities see Appendix H).

Source: U.S. EPA analysis for this report

Manufacturers
As reported in Table 3-5, EPA estimates, on a pre-tax basis, that Manufacturers will incur $78.8 million in costs
under the existing unit provision of the final rule and $55.2 million, and $243.7 million under Proposal Options 4
and 2, respectively. On an after-tax basis, these costs are $47.5 million (the existing unit provision of the final
rule), $33.4 million (Proposal Option 4), and $146.7 million (Proposal Option 2).
May 2014
3-13
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
Table 3-5: Annualized Compliance Costs to Manufacturers by Industry Sector, for the Final Rule and
Other Options Considered - Existing Units (Millions; $2011; at 2013]
a

One-Time Costs

Recurrin
g Costs

Permit-

Initial
Initial and

Monitoring,
Record

Related
Non-

Sector
Capital
Technology
Pilot
Study"
Installation
Downtime
Permit
Application
Follow-Up
Start-Up
O&M
Keeping, &
Reporting
Energy
Penalty
Annually
Recurring
Total
Proposal Option 4
Pre-Tax National Costs
Aluminum
$0.1
$0.0
$0.0
$0.4
$0.0
$0.0
$0.3
$0.0
$0.1
$0.9
Chemicals
$8 5
$0.0
$0.3
$3.3
$0.1
$2 3
$2.3
$0.0
$0 5
$17.4
Food

$0.0
$0.0
$0.5
$0.0
$0 7
$0.4
$0.0
$0 1
$2.7
Paper
3,6 2
$0.0
$0.0
$4.0
$0.1
$1 0
$2.8
$0.0
$0 6
$14.7
Petroleum

$0.0
$0.0
$0.6
$0.0
$0 9
$0.3
$0.0
$0 1
$6.1
Steel
3,8 7
$0.0
$0.0
$1.5
$0.0

$0 6
$0.0
$0 2
$12.1
Other
$0.6
$0.0
$0.0
$0.3
$0.0
$0.3
$0.2
$0.0
$0.0
$1.4
Total
$29.2
$0.0
$0.3
$10.5
$0.3
$6.4
$6.9
$0.0
$1.7
$55.2
After-Tax National Costs
Aluminum
$0.0
$0.0
$0.0
$0.3
$0.0
$0.0
$0.2
$0.0
$0.0
$0.6
Chemicals
$5 3
$0.0
$0.2
$2.0
$0.1
$1 5

$0.0
$0.3
$10.7
Food
$0.6
$0.0
$0.0
$0.3
$0.0
$0 4
$0.2
$0.0
$0.0
$1.5
Paper
$3 7
$0.0
$0.0
$2.4
$0.1
$0 6
$1.7
$0.0
$0.4
$8.9
Petroleum
$2 4
$0.0
$0.0
$0.4
$0.0
$0 6
$0.2
$0.0
$0.1
$3.6
Steel
$5.2
$0.0
$0.0
$0.9
$0.0
$0.6
$0.4
$0.0
$0.1
$7.3
Other
$0.4
$0.0
$0.0
$0.2
$0.0
$0.2
$0.1
$0.0
$0.0
$0.8
Total
$17.7
$0.0
$0.2
$6.4
$0.2
$3.9
$4.2
$0.0
$1.0
$33.4
Final Rule-Existing Units
Pre-Tax National Costs
Aluminum
$0.2
$0.0
$0.0
$0.4
$0.0
$0.1
$0.3
$0.0
$0.1
$1.1
Chemicals
$15.1
$0.0
$0.3
$3.3
$0.1
$3.1
$2.3
$0.0
$0.5
$24.8
Food

$0 0
$0 0
$0 5
$0 0
$0 9
$0.4
$0.0
$0 1
$3.2
Paper
$1X2
$0 0
$0 1

$0 1
$3 0
$2.8
$0.0
$0 6
| 3C |
! oc 1
irsi
\^\
Petroleum

$0 0
$0.0
$0 6
$0 0
$1 0
$0.3
$0.0
$0 1
$6.7
Steel
$9 1
$0 0
$0.0

$0 0

$0 6
$0.0
$0 2
$12.7
()ther
$0.8
$0.0
$0.0
$0.3
$0.0
$0.3
$0.2
$0.0
$0.0
$1.6
Total
$49.4
$0.0
$0.4
$10.5
$0.3
$9.6
$6.9
$0.0
$1.7
$78.8
After-Tax National Costs
Aluminum
$0.1
$0.0
$0.0
$0.3
$0.0
$0.0
$0.2
$0.0
$0.0
$0.7
Chemicals
$9 2
$0 0
$0 2
$2 0
$0.1
$1 9

$0.0
$0.3
$15.2
Food
$0.8
$0 0
$0.0
$0.3
$0.0
$0 5
$0.2
$0.0
$0.0
$1.8
Paper

$0 0
$0 1
$2 4
$0.1
$1 8
$1.7
$0.0
$0 4
$17.4
Petroleum
$2 7
$0 0
$0 0
$0 4
$0.0
$0 6
$0.2
$0.0
$0 1
$4 0
Steel
$5.4
$0.0
$0.0
$0.9
$0.0
$0.7
$0.4
$0.0
$0.1
$7.6
Other
$0.5
$0.0
$0.0
$0.2
$0.0
$0.2
$0.1
$0.0
$0.0
$1.0
Total
$29.7
$0.0
$0.3
$6.4
$0.2
$5.8
$4.2
$0.0
$1.0
$47.5
Proposal Option 2
Pre-Tax National Costs
Aluminum
$0.2
$0.0
$0.0
$0.4
$0.0
$0.1
$0.3
$0.0
$0.1
$1.1
Chemicals
$60.5
$0.0
$2.0
$2.9
$0.1
$22.2
$3.5
$3.8
$0 5
$95.6
Food

$0 0
$0.3
$0.3
$0 0
$4 3
$0.8
$0.0
$0 1
$18.9
Paper
$21 2
$0 0
$0 4
$3 9
$0 1
$4 3
$3 1
$0.4
$0 6
$33.9
Petroleum

$0 0
$0 4
$0.3
$0 0
$5 1
$0.7
$0.1
$0.0
$22.6
Steel
$48 7
$0 0

$0 8
$0 0
$14.4
$1.8
$0.0
$0 1
$67.0
()ther
$2.4
$0.0
$0.1
$0.2
$0.0
$1.2
$0.3
$0.3
$0.0
$4.5
Total
$161.9
$0.0
$4.6
$8.8
$0.3
$51.6
$10.4
$4.6
$1.4
$243.7
After-Tax National Costs
Aluminum
$0.1
$0.0
$0.0
$0.3
$0.0
$0.0
$0.2
$0.0
$0.0
$0.7
Chemicals
$37 1
$0 0
$1 3
$1.8
$0 1
$13 5
$2.2
$2.4
$0 3
$58.5
Food
$7 6
$0 0
$0 2
$0 2
$0 0
$2 5
$0.5
$0.0
$0.0
$1 F0
Paper

$0 0
$0.2
$2 3
$0 1
$2 6
$1.9
$0 3
$0 4
$20.5
Petroleum
$9.4
$0 0
$0.3
$0.2
$0 0
$3 1
$0.4
$0.1
$0.0
$ 13.5
3-14
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
Table 3-5: Annualized Compliance Costs to Manufacturers by Industry Sector, for the Final Rule and
Other Options Considered - Existing Units (Millions; $2011; at 2013]
a

One-Time Costs

Recurrin
g Costs

Permit-

Initial
Initial and

Monitoring,
Record

Related
Non-

Sector
Capital
Technology
Pilot
Study"
Installation
Downtime
Permit
Application
Follow-Up
Start-Up
O&M
Keeping, &
Reporting
Energy
Penalty
Annually
Recurring
Total
Steel
$28.9
$0.0
$0.8
$0.5
$0.0
$8.6
$1.1
$0.0
$0.1
$39.9
Other
$1.4
$0.0
$0.1
$0.1
$0.0
$0.7
$0.2
$0.2
$0.0
$2.7
Total
$97.4
$0.0
$2.8
$5.3
$0.2
$31.0
$6.3
$2.9
$0.8
$146.7
a. As described earlier in this chapter, the costs presented in this table assume that all facilities with cooling water impoundments qualify as baseline CCRS,
and incur no additional technology costs for regulatory compliance (but do incur administrative costs). Thus, these costs are the lower value in a range based
on whether facilities with an impoundment will or will not qualify as baseline CCRS and would not need to install additional technology. See Memorandum
to the Record (DCN 12-2501) for the range of costs that could occur based on whether these facilities would need to install additional compliance
technology.
b. Annualized pilot study costs under the final rule and Proposal Option 4
are less than $12,000 on a
pre-tax basis and less than $10,000 on an after-tax basis.
Source: U.S. EPA analysis for this report

Electric Generators and Manufacturers
Table 3-6 presents total compliance costs for Electric Generators and Manufacturers.
May 2014
3-15
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
Table 3-6: Annualized Compliance Costs to Electric Generators and Manufacturers, for the Final Rule and
Other Options Considered - Existing Units (Millions; $2011; at 2013)a'

One-Time Costs

Recurring Costs

Initial
Initial and

Monitoring,
Record

Permit-
Related Non-

Facility Group
Capital
Technology
Pilot
Study0
Installation
Downtime
Permit
Application
Follow-Up
Start-Up
O&M
Keeping, and
Reporting
Energy
Penalty

Annually
Recurring
Total
Proposal Option 4
Pre-Tax Compliance Costs
Generators
$111.7
$0.0
$30.9
$19.6
$0.3
$55.6
$3.0
$0.0
$3.1
$224.1
Manufacturers
$29.2
$0.0
$0.3
$10.5
$0.3
$6.4
$6.9
$0.0
$1.7
$55.2
Total
$140.9
$0.0
$31.2
$30.1
$0.6
$61.9
$9.9
$0.0
$4.8
$279.4

After-Tax Compliance
Costs

Generators
$73.3
$0.0
$19.0
$13.1
$0.2
$37.3
$2.0
$0.0
$2.1
$147.0
Manufacturers
$17.7
$0.0
$0.2
$6.4
$0.2
$3.9
$4.2
$0.0
$1.0
$33.4
Total
$90.9
$0.0
$19.1
$19.5
$0.4
$41.2
$6.2
$0.0
$3.1
$180.4
Final Rule-Existing Units
Pre-Tax Compliance Costs
Generators
$112.2
$0.0
$30.9
$19.6
$0.3
$55.8
$3.0
$0.0
$3.1
$224.9
Manufacturers
$49.4
$0.0
$0.4
$10.5
$0.3
$9.6
$6.9
$0.0
$1.7
$78.8
Total
$161.5
$0.0
$31.4
$30.1
$0.6
$65.4
$9.9
$0.0
$4.8
$303.6

After-Tax Compliance
Costs

Generators
$73.7
$0.0
$19.0
$13.1
$0.2
$37.5
$2.0
$0.0
$2.1
$147.6
Manufacturers
$29.7
$0.0
$0.3
$6.4
$0.2
$5.8
$4.2
$0.0
$1.0
$47.5
Total
$103.5
$0.0
$19.2
$19.5
$0.4
$43.3
$6.2
$0.0
$3.1
$195.1
Proposal Option 2
Pre-Tax Compliance Costs
Generators
$2,163.2
$0.0
$192.6
$1.9
$0.3
$708.4
$20.2
$676.6
$0.3
$3,763.5
Manufacturers
$161.9
$0.0
$4.6
$8.8
$0.3
$51.6
$10.4
$4.6
$1.4
$243.7
Total
$2,325.1
$0.0
$197.2
$10.7
$0.6
$760.1
$30.6
$681.2
$1.7
$4,007.2

After-Tax Compliance
Costs

Generators
$1,454.9
$0.0
$136.5
$1.4
$0.2
$477.2
$13.5
$461.7
$0.2
$2,545.7
Manufacturers
$97.4
$0.0
$2.8
$5.3
$0.2
$31.0
$6.3
$2.9
$0.8
$146.7
Total
$1,552.3
$0.0
$139.2
$6.8
$0.4
$508.2
$19.8
$464.6
$1.1
$2,692.3
a. As described earlier in this chapter, the costs presented in this table assume that all facilities with cooling water impoundments qualify as baseline CCRS,
and incur no additional technology costs for regulatory compliance (but do incur administrative costs). Thus, these costs are the lower value in a
range based
on whether facilities with an impoundment will or will not qualify as baseline CCRS and would not need to install additional technology. See Memorandum
to the Record (DCN 12-2501) for the range of costs that could occur based on whether these facilities would need to install additional compliance
technology.

b. Values may not add up due to rounding.

c. Annualized pilot study costs under the final rule and Proposal Option 4 are less than $12,000 on
pre-tax basis and less than $10,000 on an after-tax basis.
Source: U.S. EPA analysis for this report

3.1.3 Uncertainties and Limitations
This analysis is subject to the following uncertainties and limitations:
> Given the passage of time since completion of the 316(b) survey, the survey data may no longer
accurately reflect the business conditions or cooling water usage of the sampled facilities, and the
facilities in the broader population that these sample facilities represent. To the extent that survey data
underlying the costs are outdated, EPA may have over- or under-estimated compliance technology costs
presented here.
> The set of facilities in the earlier survey may differ from the set of facilities that will be complying with
the final rule, because either a facility has been retired or generating and manufacturing units have been
added since that time.
> Given the substantial number and diverse characteristics of Electric Generators that must be accounted for
on a sample-weighted basis (the implicitly analyzed facilities), it is impossible for EPA to develop sample
weights that accurately account for all economic and operating differences of these facilities (see
3-16
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
Appendix H). Consequently, compliance costs EPA developed for the electric power industry may be
over- or under-estimated due to statistical error in the facility sample weights.
> Additional uncertainties are associated with the downtime cost estimates discussed in Appendix I. EPA
relied on IPM-projected estimates of electricity generation and variable production costs and historical
EIA electricity generation and prices, which may not be representative of actual electricity market
conditions when regulated facilities suspend their operations to install compliance technology. Further, to
the extent that technology installation occurs during the shoulder months of spring and fall, when
electricity demand is typically below the annual average, the downtime costs, which EPA estimated using
average annual generation, cost and revenue, are likely to be over-stated.
> For uncertainties associated with administrative activities as well as their timing and labor requirements,
see the TDD. To the extent that the average hourly labor rates used in this analysis differ from the actual
rates that States and federal government will pay to their employees, EPA may have may have over- or
under-estimated administrative costs.
> To the extent that EPA used the same set of facilities for the analysis of this regulation as the set of
facilities it used for the previous 316(b) analyses, the same set of uncertainties regarding the facility
sample and cost estimates apply.
> As described earlier in this chapter, the final rule definition of a CCRS includes cooling water
impoundments that meet specified criteria (see §125.92, Special, definitions, (c) (2) of the final rule).
Subject to site-specific review by Permit Directors, these facilities may meet the rule's BTA standard for
impingement mortality through operation of a CCRS in the baseline, and may not need to install
additional technology to meet the rule's BTA standard for impingement mortality. At present, EPA does
not know whether individual facilities that are known to have impoundments will qualify as baseline
CCRS. The cost information presented in this chapter assumes that all facilities known to have
impoundments as part of their cooling water intake system will not incur additional technology costs to
meet the rule's BTA performance standard (but would incur certain administrative costs). To the extent
that some of these facilities do need to install additional compliance technology, the costs reported in this
chapter may be underestimates. Thus, these costs are the lower value in a range based on whether
facilities with an impoundment will or will not qualify as baseline CCRS, and would not need to install
additional compliance technology. See Memorandum to the Record (DCN 12-2501) for the range of costs
that could occur based on whether these facilities would need to install additional compliance technology.
3.2 Compliance Costs for New Units
Electric power generating units at Electric Generators that meet the definition of a new unit will be required to
achieve intake flow commensurate with the performance of a closed-cycle recirculating system under the final
rule. This section summarizes the data and methodology used to estimate total compliance costs associated with
the new unit provision of the final rule and other new unit options for Electric Generators (for a more detailed
description of the methodology, see the TDD). The Agency expects compliance costs associated with new units at
Manufacturers will be negligible in total. Therefore, this discussion focuses on Electric Generators only. In this
section, the term final rule refers to the provision of the final rule that applies to new units.
3.2.1 Analysis Approach and Data Inputs
New units at existing facilities whose construction begins after the effective date of the final rule must comply
with the new unit provision of the final rule. EPA assumed that it would take approximately four years to
construct a new unit and install a cooling tower; therefore, the Agency assumed that 2017 will be the first year
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
when any new unit subject to the final rule will come online and begin cooling tower operation after the rule
promulgation.
EPA expects Electric Generators with new generating units to incur capital costs, additional fixed and variable
O&M costs, and additional costs from auxiliary energy requirements from installation and operation of
entrainment control technology. In addition, EPA expects these facilities to incur costs associated with initial
start-up, initial permitting, annual monitoring, and reporting and recordkeeping activities to implement the final
rule. Facilities will not have to undertake follow-up start-up activities associated with the new units. EPA used the
same methodology to calculate total industry compliance costs associated with new units at existing facilities, as
that used for existing units at existing facilities (see Section 3.2).
EPA was unable to determine which Electric Generators will construct new units or the precise timing of new unit
construction. Therefore, the Agency estimated compliance costs for new units only at the national level and not at
the NERC-region level. Further, the Agency assumed that the same number of new unit construction events, in
terms of electric power generating capacity, would occur in every year during the 30-year analysis period.
3.2.2 Key Findings
Table 3-7 presents total annualized pre-tax and after-tax compliance costs estimated for Electric Generators under
the new unit provision of the final rule and other new unit options considered. As reported in Table 3-7, EPA
estimates, on a pre-tax basis, that the new unit provision of the final rule will result in $1.7 million in compliance
costs to facilities. On apre-tax basis, Options A, B, and C would result in $100.1 million, $40.3 million, and $9.5
million in compliance costs to facilities, respectively. On an after-tax basis, the new unit provision of the final rule
will result in $ 1.1 million in compliance costs to facilities. Under other new unit options considered - Options A,
B, and C - this cost would be $61.0 million, $24.6 million, and $5.8 million, respectively.
Table 3-7: Annualized Compliance Costs to Electric Generators for the Final Rule and Other New Unit
Options Considered (Millions; $2011; at 2013)

One-Time Costs

Recurring Costs

Permit-

Initial

Monitoring,
Record

Related
Non-

Option
Capital
Technology
Pilot
Study
Installation
Downtime
Permit
Application
Initial
Start-Upa
O&M
Keeping, and
Reporting
Energy
Penalty
Annually
Recurring
Total
Pre-Tax Compliance Costs
Option A
$71.3
$0.0
$0.0
$0.2
$0.0
$27.6
$0.8
$0.0
$0.0
$100.1
Option B
$28.7
$0.0
$0.0
$0.1
$0.0
$11.1
$0.4
$0.0
$0.0
$40.3
Option C
$6.5
$0.0
$0.0
$0.1
$0.0
$2.5
$0.4
$0.0
$0.0
$9.5
Final Rule -
$0.9
$0.0
$0.0
$0.1
$0.0
$0.4
$0.4
$0.0
$0.0
$1.7
New Units

After-Tax Compliance Costs
Option A
$43.5
$0.0
$0.0
$0.1
$0.0
$16.8
$0.5
$0.0
$0.0
$61.0
Option I '>

$0.0
$0.0
$0 1
$0 0
$6.8
$0.2
$0.0
$0 0
$24 6
Option C

$0.0
$0.0
$0 1
$0 0
$1.5
$0.2
$0.0
$0 0
$5 8
Final Rule -
$0.6
$0.0
$0.0
$0.1
$0.0
$0.2
$0.2
$0.0
$0.0
$1.1
New Units

a. Initial start-up costs are less than $50,000.

Source: U.S. EPA analysis for this report

3.3 Total Compliance Costs of the Final Rule
As reported in Table 3-8, EPA estimates that under the final rule, Electric Generators and Manufacturers will
incur $305.4 million in costs on a pre-tax basis and $196.2 million on an after-tax basis, accounting for both the
new unit and the existing unit provisions. The new unit provision accounts for less than one percent of total costs.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
Table 3-8: Total Annualized Compliance Costs of the Final Rule for Electric Generators and Manufacturers
(Millions; $2011; at 2013)a b

One-Time Costs

Recurring Costs

Initial
and

Monitoring,
Record

Permit-
Related

Option
Capital
Technology
Pilot
Study
Installation
Downtime
Initial
Permit
Application
Follow-
Up
Start-Up
O&M
Keeping,
and
Reporting
Energy
Penalty
Non-
Annually
Recurring
Total
Pre-Tax Compliance Costs
Existing Units
$161.5
$0.0
$31.4
$30.1
$0.6
$65.4
$9.9
$0.0
$4.8
$303.6
New Units
$0.9
$0.0
$0.0
$0.1
$0.0
$0.4
$0.4
$0.0
$0.0
$1.7
Total
$162.5
$0.0
$31.4
$30.2
$0.6
$65.7
$10.2
$0.0
$4.8
$305.4
After-Tax Compliance Costs
Existing Units
$103.5
$0.0
$19.2
$19.5
$0.4
$43.3
$6.2
$0.0
$3.1
$195.1
New Units
$0.6
$0.0
$0.0
$0.1
$0.0
$0.2
$0.2
$0.0
$0.0
$1.1
Total
$104.0
$0.0
$19.2
$19.5
$0.4
$43.5
$6.4
$0.0
$3.1
$196.2
a. As described earlier in this chapter, the costs presented in this table assume that all facilities with cooling water impoundments qualify as baseline CCRS,
and incur no additional technology costs for regulatory compliance (but do incur administrative costs). Thus, these costs are the lower value in a range based
on whether facilities with an impoundment will or will not qualify as baseline CCRS and would not need to install additional technology. See Memorandum
to the Record (DCN 12-2501) for the range of costs that could occur based on whether these facilities would need to install additional compliance

technology.
b. Numbers may not add up due to rounding.
Source: U.S. EPA analysis for this report

3.4 Administrative Costs to States and Federal Government
EPA also estimated costs to States and the federal government for administering the final rule and other options
EPA considered in development of this rule. These costs closely link to the administrative costs to regulated
facilities and mainly reflect labor costs to review information produced by regulated facilities and to write the
necessary permits. EPA determined that these costs would vary across regulatory options, based primarily on
differences in administrative requirements for facilities installing IM technology compared to those installing
entrainment control technologies, i.e., cooling towers. This section presents administrative costs for the final rule
and other options considered for existing and new units at Electric Generators and Manufacturers.
3.4.1 Analysis Approach and Data Inputs
Existing Units
EPA analyzed administrative costs for 46 States and one territory with designated NPDES permitting authority
under section 402(c) of the Clean Water Act (CWA). EPA is responsible for permitting and incurs the
administrative costs associated with facilities located in four States and eight territories without designated
NPDES permitting authority. EPA estimated costs for the following three categories of administrative activities
for the existing unit provision of the final rule and other options considered:
> Initial permitting activities: These activities include initial start-up activities and review of permit
applications and other information submitted by regulated facilities during the permitting process. Unlike
regulated facilities, States and federal government will not have to undertake follow-up start-up activities.
> Annual activities: These activities include review of annual monitoring data and other information
submitted by regulated facilities on an annual basis.
> Non-anmially recurring activities: These activities include a subset of initial permitting activities that
repeat periodically in the future. As discussed for regulated facilities, while these activities are required
every permit cycle, Permit Directors will likely not require facilities to repeat them as soon as the second
permit cycle after the initial compliance with regulatory requirements. Consequently, EPA assumed that
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
all activities in this subset begin 10 years after the initial permitting activities begin, i.e., during the third
post-compliance permit cycle, and recur every five years after that.
EPA's estimates of administrative costs to permitting authorities for the final rule include both the costs of
administering the rule's IM technology provisions and the costs for site-specific evaluation and determination of
entrainment technology as BTA.
Each NPDES permitting authority incurs costs only one time for start-up activities and for any activities that
apply to the total set of facilities located in that permitting authority's jurisdiction. Activities that apply to
individual facilities occur as many times as the number of regulated facilities in the jurisdiction.
These costs do not account for the costs that permitting authorities otherwise incur for administering permits on
the basis of Best Professional Judgment (BPJ) determinations, as currently occurs in the absence of a national
316(b) regulation. To the extent that permitting authorities incur such costs, the incremental costs to permitting
authorities for administering the the final rule and other options considered are overstated - as the BPJ costs
would be subtracted from the estimated administrative costs to calculate the incremental costs for permit
development and administration. It is possible that the administrative costs now being incurred by permitting
authorities exceed the costs reported here for permit administration. In this case, the rule's incremental costs for
permit administration would be negative (see Memorandum to the Record (DCN 12-2504) for a discussion of
permitting authorities' activities in development of BPJ permits).
For details on these activities as well as time and labor requirements associated with these activities, see the TDD.
To estimate administrative costs associated with these activities, EPA first developed hourly labor rates by labor
category using the same data sources and method described above on page 3-5. Table 3-9 presents the resulting
labor rates EPA used to estimate administrative costs for States and the federal government.
Table 3-9: Average Hourly Labor Rates for State and Federal Government
Employees by Labor Category ($2011)a

Average Hourly Labor Rate for
Labor Categories
State Governments
Federal Government
Senior Technical
$60.10
$87.50
Junior Technical
$45 30
.80
Clerical
$28.70
$33.50
a. Fully loaded hourly rates include base labor costs with add-ons for employee benefits and overhead.
Source: U.S. EPA analysis for this report

EPA calculated total administrative costs by multiplying these average hourly rates by the number of hours, by
labor category, and activity events that would be required for each administrative activity, and summing these
costs across the administrative activities.
New Units
The Agency expects that government costs for administering the new unit requirements for Manufacturers will be
negligible. Therefore, EPA analyzed these costs only for Electric Generators. The Agency assumed that NPDES
authorities would incur initial permitting and annual monitoring, reporting, and recordkeeping costs to administer
the new unit provision. For details on these activities, see the TDD. EPA followed the same steps to calculate total
administrative costs for new units as it followed for existing facilities. EPA assumed that all new unit activity will
occur in States with NPDES permitting authority.
3.4.2 Key Findings
As shown in Table 3-10, EPA estimates that States and the federal government will incur $1.1 million to
administer the final rule for existing units. EPA estimates this cost would be $ 1.1 million and $0.7 million to
administer Proposal Options 4 and 2, respectively.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
Table 3-10: Annualized Administrative Costs to States and Federal Government for Electric
Generators and Manufacturers - Existing Units (Millions; $2011; at 2013)

Option
Initial
Permit Application3
Monitoring,
Recordkeeping
and Reporting
Non-Annually
Recurring Total
Total
Proposal Option 4
$0.5
$0.5
$04
$l.l
Final Rule-Kxistiii" Units
$0.5
$0.5
$0 I

Proposal Option 2
$0.2
$0.4
$0.0
$0.7
a. These costs include initial start-up costs that are less than $20,000, which are the same regardless of regulatory option.
Source: U.S. EPA analysis for this report

As shown in Table 3-11, in addition to the existing unit requirements, States will incur less than $50,000 to
administer the new unit provision of the final rule. States would incur $0.1 million to administer the new unit
requirements under Option A and less than $50,000 to administer the new units requirements under Options B and
C.
As shown in Table 3-12, EPA estimates that the total cost to States and federal government to administer existing
and new unit provisions of the final rule will be $1.2 million. The new unit provision accounts for approximately
4 percent of total government administrative costs.
Table 3-11: Annualized Administrative Costs to States and Federal Government for Electric
Generators and Manufacturers - New Units (Millions; $2011; at 2013)
Option
Initial
Permit Applicationa'b
Monitoring,
Recordkeeping
and Reportingb
Non-Annually
Recurring Total
Total"
Option A
$0.0
$0.1
$0.0
$0.1
Option B
$0.0
$0.0
$0.0
$0.0
Option C
$0.0
$0.0
$0.0
$0.0
Final Rule - New
Units
$0.0
$0.0
$0.0
$0.0
a. Under Option A, initial permit application costs are less than $40,000.
b. Under the new unit provision of the final rule and Options B and C, initial permit application costs are less than $15,000; monitoring,
recordkeeping, and reporting costs under these options are less than $40,000, and total costs are less than $50,000.
Source: U.S. EPA analysis for this report
Table 3-12: Total Annualized Administrative Costs to States and Federal Government of the
Final Rule for Electric Generators and Manufacturers (Millions; $2011; at 2013)
Option
Initial
Permit Application
Monitoring,
Recordkeeping
and Reporting
Non-Annually
Recurring Total
Total
Existing Units
$0.5
$0.6
$0.1
$1.1
New Units3
$0.0
$0.0
$0.0
$0.0
Total
$0.5
$0.6
$0.1
$1.2
a. Under the new unit provision of the final rule, initial permit application costs are less than $15,000; monitoring, recordkeeping, and
reporting costs under these options are less than $40,000 and total costs are less than $50,000.
Source: U.S. EPA analysis for this report

3.4.3 Uncertainties and Limitations
For uncertainties associated with administrative activities as well as their timing and labor requirements, see the
TDD. Other uncertainties and limitations include:
> To the extent that the average hourly labor rates that EPA used in this analysis differ from the rates that
State and federal governments pay to their employees, EPA may have over- or under-estimated total
administrative costs.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 3: Compliance Costs
> As described above, the estimated costs to States and the federal government do not account for the costs
that permitting authorities otherwise incur for administering permits on the basis of Best Professional
Judgment (BPJ) determinations, as currently occurs in the absence of a national 316(b) regulation. To the
extent that permitting authorities incur such costs, the incremental costs to permitting authorities for
administering the final rule and other options considered are overstated - as the BPJ costs would be
subtracted from the estimated administrative costs to calculate the incremental costs for permit
development and administration. It is possible that the administrative costs now being incurred by
permitting authorities exceed the costs reported here for permit administration. In this case, the rule's
incremental costs for permit administration would be negative (see Memorandum to the Record (DCN 12-
2504) for a discussion of permitting authorities' activities in development of BPJ permits).
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
4 Economic Impact Analyses - Electric Generators
4.1 Analysis Overview
This chapter and Chapter 6: Electricity Market Analysis analyze the economic impact on Electric Generators of
both the existing and new unit provisions of the final rule and other options EPA considered.64
EPA performed the existing unit analysis in two parts, the key elements of which are parallel in concept to the
impact analyses undertaken for Manufacturers, and described in Chapter 5: Economic Impact Analyses -
Manufacturers. In particular, the impact analyses for both Electric Generators and Manufacturers begin with a
cost-to-revenue screening analysis to assess the potential significance of compliance costs to regulated facilities.
For Manufacturers, this screening analysis is followed by a more rigorous analysis of economic/financial impact
using cash flow models to assess the impact of compliance costs on the financial performance of regulated
facilities. The key concepts of this after-tax cash flow/business value analysis are similar to the cash flow and
present value concepts involved in the electricity market analysis conducted for Electricity Generators using the
Integrated Planning Model (IPM).
The two parts of the analysis conducted for Electric Generators are as follows:
1. A cost and economic impact analysis reflecting baseline operating characteristics of regulated facilities. This
is a static analysis and assumes no changes in those baseline operating characteristics - e.g., level of
electricity generation and revenue - as a result of the requirements of the final rule and other options
considered. This analysis includes five analyses:
> A cost-to-revenue screening analysis to assess the impact of compliance outlays on individual regulated
facilities (Section 4.2.1).
> A cost-to-revenue screening analysis to assess the impact of compliance outlays on domestic parent
entities that own regulated facilities (Section 4.2.2).65
> A screening-level analysis of the potential impact of compliance costs on electricity prices, across
consumer groups (Section 4.2.3).
> An analysis of the potential impact of compliance costs on electricity prices to residential households
(Section 4.2.4).
> An analysis of the reduction in the availability of generating capacity due to downtime during installation
of compliance technology, and the impact of that capacity reduction on the North American bulk power
system (Section 4.2.5).
For each of these analyses except for the analysis of technology installation downtime impacts (Section 4.2.5),
EPA assessed the impacts of the final rule and other options considered for two cases: (1) assuming that all
facilities with a cooling water system impoundment qualify as CCRS in the baseline and will meet the
performance standard for impingement mortality under the final rule and other options considered without
additional technology,66 and (2) assuming that no facilities with a cooling water system impoundment qualify as
04 See Chapter 1: Introduction for option descriptions.
05 The cost-to-revenue analyses provide an indication of the relative magnitude of the compliance costs, controlling for the size or
market share of the facility or entity. These analyses are not designed to predict closures and/or other types of economic impact on
regulated facilities or entities that own these facilities.
00 For Proposal Option 2, EPA also assumed that these facilities will meet entrainment technology requirements, as applicable.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
CCRS in the baseline and thus may need to install additional technology under the final rule and other options
considered. In all these impact analyses, the impacts differ slightly under the alternative assumptions; EPA reports
analysis results separately for each alternative assumption. For the analysis of technology installation downtime
impacts (Section 4.2.5), the analysis results presented in this chapter assume that all facilities with cooling water
system impoundments will qualify as baseline CCRS and will not need to install additional compliance
technology and incur additional downtime.67
2. A broader electricity market analysis, based on the IPM, is discussed in Chapter 6. Unlike the preceding
analysis, this electricity market analysis accounts for the effect of compliance costs using detailed information
on the baseline and projected profiles of the operating finances of individual facilities and generating units.
Very importantly, this analysis reflects the interdependence of generating units in supplying power to the
electric transmission grid. This analysis accounts for expected changes in the operating characteristics and
generation profile of regulated facilities and other electric power facilities over time from both:
> Estimated changes in electricity markets, operating characteristics, and generation profile of facilities
independent of the final rule and other options considered and
> Estimated changes in electricity markets, operating characteristics, and generation profile of facilities as a
result of the final rule or other options considered.
For these analyses, EPA closely followed the methodologies used to conduct analyses in support of the previous
316(b) regulatory analyses, including the proposed rule, and, to the extent possible, relied on the same data
sources.
For new units, EPA analyzed the impact of the new unit provision of the final rule on decisions of existing
facilities to construct stand-alone new units at existing facilities that would be subject to the new unit provision.
Under this provision, electric power generating units that meet the definition of a new unit will be required to
achieve intake flow commensurate with a closed-cycle recirculating system (CCRS). This question of potential
impact of this provision on the construction of new stand-alone units is important because these units will
generally operate with higher energy efficiency and lower environmental impact than older electric generating
capacity, which the new units would tend to displace as a source of electric power generation. As such, EPA
sought to ensure that the new unit provision would not impede construction of stand-alone new units. As is the
case with existing units, EPA conducted this analysis, termed the barrier-to-development analysis, in two parts:
r EPA compared the compliance costs for new units to the overall cost of building and operating
generating units, on a per MW basis. The purpose of this analysis is to determine whether the required
addition of CCRS as part of a new unit would substantially increase the cost for the new stand-alone unit,
and adversely affect the decision to construct it. This analysis is discussed in Section 4.3 of this chapter.
> EPA also assessed these costs as part of its electricity market analyses using IPM, as discussed in Chapter
6. This analysis tests the impact of the new unit requirements on electricity markets accounting for the
expected number and timing of new unit installations, and provides additional insight on whether the
costs of complying with the new unit provision of the final rule would affect future capacity additions.
This analysis is discussed in Chapter 6.
4.2 Cost and Economic Impact Analysis - Existing Units
This section summarizes the data and methodology EPA used to conduct cost and economic impact analyses of
the existing unit provision of the final rule and other existing unit options considered.
67 EPA also conducted this analysis assuming that no facilities with a cooling water system impoundment qualify as baseline CCRS and
thus may need to install additional technology to meet the performance standards under the final rule and other options considered.
However the Agency found only minimal differences in analysis results.
4-2
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
4.2.1 Cost-to-Revenue Analysis: Facility-Level Screening Analysis
The cost-to-revenue measure compares the cost of installing and operating compliance technologies with the
facility's operating revenue, and provides a screening-level analysis of the impact of the final rule and other
options considered. As discussed in Chapter 2: Industry! Profiles, the majority of regulated facilities (59 percent)
operate in States with rate-regulated electricity markets. EPA estimates that facilities located in these States may
be able to recover compliance cost-based increases in their production costs through increased electricity prices.
This depends on the business operation model of the facility owner(s), the ownership and operating structure of
the facility itself, and the role of market mechanisms used to sell electricity. In contrast, in States in which electric
power generation has been deregulated, cost recovery is less certain. While facilities operating within deregulated
electricity markets may be able to recover some of their additional production costs through increased revenue,
EPA cannot determine the extent of cost recovery ability for each facility.68
In conducting the facility cost-to-revenue analysis, the Agency assumed that regulated facilities will not be able to
pass any of the increase in their production costs to consumers (zero cost pass-through). EPA makes this
assumption for analytic convenience; it provides a worst-case scenario of impacts on regulated facilities. Even
though the majority of regulated facilities may be able to pass nearly all increases in production costs to
consumers through increased electricity prices, determining exactly which facilities will be able to, and the extent
of cost pass-through that these facilities may achieve, is difficult. Consequently, assuming zero cost pass-through
is appropriate for a screening-level, upper bound estimate of the potential cost impact on regulated facilities and
their parent entities. To the extent that some regulated facilities are able to recover some of the increased costs
through increased prices, this analysis will overstate facility-level impacts. While helpful to understand potential
cost impacts, this analysis generally does not indicate whether profitability is jeopardized, cash flow is affected, or
risk of financial distress is increased.
Analysis Approach and Data Inputs
As described in Chapter 3: Compliance Costs, EPA conducted economic impact analyses assuming 5-year
technology-installation windows of 2018 through 2022 for IM technology installation, 2021 through 2025 for
installation of cooling towers by non-nuclear Electric Generators, and 2026 through 2030 for installation of
cooling towers by nuclear Electric Generators.
EPA used a single year, 2011, as the basis for comparing facility-level compliance costs to facility-level revenue.
Specifically, EPA compared annualized after-tax compliance costs (see Chapter 3) with estimated 2011 facility
69,70
revenue.
As discussed in Chapter 2, while regulatory status in a given State affects the ability of electric power facilities and their parent
entities to recover electricity generation costs, it is not the only factor and should not be used solely as the basis for cost-pass-through
determination.
09 For private, tax-paying entities, after-tax costs are a more relevant measure of potential cost burden than pre-tax costs. For non-tax-
paying entities (e.g., State government and municipality owners of regulated facilities), the estimated costs used in this calculation
include no adjustment for taxes.
70 Although regulated facilities are expected to install compliance technologies in years after 2011, EPA sought to ensure that the cost
and revenue estimates used in the cost-to-revenue analysis would be consistent in terms of cost-year. Although, elsewhere in this
analysis, EPA estimated compliance costs for future years based on potential real change in costs over time, EPA was less confident in
projecting future revenue for facilities (and parent entities, later in the analysis) given the potential for facility-level changes (e.g.,
adding or retiring generating capacity) that could materially change the facility's (or parent entity's) revenue. Therefore, to avoid
introducing additional uncertainty into the analysis, EPA used 2011 as the basis for the revenue and compliance cost estimates for
facilities, regardless of when they are expected to incur compliance costs. Because this analysis relies on a ratio of cost to revenue as
opposed to absolute values, the ratio for a given facility will be the same in years beyond the selected analysis year as long as the cost
and revenue values are as of the same year and the basis for projecting those values is the same, going forward from the selected
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
EPA developed facility-level revenues for all regulated facilities using data from the Energy Information
Administration (EIA) of the U.S. Department of Energy (DOE) on electricity generation by prime mover, and
utility/operator-level electricity prices and disposition. Specifically, EPA multiplied the 5-year average of
electricity generation values over the period 2007 to 2011 from the EIA-906/920/923 database by 5-year average
electricity prices over the period 2007 to 2011 from the EIA-861 database.71
To provide cost and revenue comparisons on consistent analysis- and dollar-year bases, EPA converted all costs
and revenues to the cost-to-revenue analysis year of 2011, and expressed them in 2011 dollars as follows:
> The EIA electricity price data are reported in nominal dollars of each year. EPA's first step in calculating
facility revenue was to restate these values in 2011 dollars using the Gross Domestic Product (GDP)
deflator index published by the U.S. Bureau of Economic Analysis (BEA). The Agency then averaged
these individual yearly values.72
> EPA originally estimated all compliance-technology costs, except for installation downtime and energy
penalty, as of February 2009. EPA used the Construction Cost Index (CCI) from McGraw Hill
Construction to adjust all compliance technology costs to 2011. Because the CCI is a nominal cost
adjustment index, the resulting technology costs are for the assumed year of compliance, 2011, and in
2011 dollars.
> As detailed in Appendix I: Energy Effects, EPA estimated costs associated with the energy penalty and
downtime using IPM-based variable cost estimates and EIA-based revenue values. The IPM-based
variable production cost values are 3-year averages of values projected for 2015, 2020, and 2030. EPA
did not adjust these values to account for possible real changes in variable production costs between these
years and 2011, because the Agency had no reliable basis for making these adjustments. If cost changes
follow the historically observed trend - costs increase at a greater rate than general inflation - then these
variable production costs will be overstated in the cost-to-revenue analysis. The EIA-based facility
revenue values used in these calculations are the same as those used to calculate cost-to-revenue ratios
and discussed above.
> Because administrative costs were originally estimated for 2011 and in 2011 dollars, EPA made no
additional adjustments in these values.
In the cost-to-revenue comparisons, EPA used cost-to-revenue thresholds of 1 and 3 percent as markers of
potentially significant impacts. EPA assumed that facilities incurring costs below 1 percent of revenue will not
face significant economic impacts, and facilities with costs of at least 1 percent but less than 3 percent of revenue
have a chance of facing significant economic impacts. Facilities incurring costs of at least 3 percent of revenue
have a higher probability of significant economic impacts. As part of this screening analysis, EPA also considered
whether costs would be negligible at the level of the facility. EPA did so by comparing total facility costs to total
facility revenue relative to the 0.1 percent threshold, with costs below 0.1 percent of revenue considered so slight
in relation to the overall scale of business activity, measured by facility revenue, as to be negligible in terms of
analysis year. That is, beyond the selected analysis year, cost and revenue values are assumed to change at the same rate and thus, the
ratio of these values will be constant over time.
71 EPA used 5-year averages instead of single-year values to avoid possibly anomalous years in terms of electricity generation and
prices. In using the year-by-year revenue values to develop an average over the data years, EPA eliminated generation values that are
anomalously low from the average calculation. Such low generating output likely results from temporary disruption in operation, such
as a generating unit being out of service for maintenance.
72 Because the AEO2012 electricity price projections are in constant dollars, these adjustments yield 2020 revenue values in 2011
dollars.
4-4
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
potential adverse impact.73 That is, the regulation is more likely to spur facilities with a compliance cost-to-
revenue value of less than 0.1 percent to seek and successfully implement cost-cutting measures or revenue
enhancements compared to those facilities with a cost-to-revenue value above 0.1 percent, for which such a
strategy has lower probability of success. Also, local governments may be more likely to provide tax benefits to
avoid closure in cases where regulatory costs are negligible.
EPA carried the findings from this analysis forward to Chapter 6: Electricity Market Analysis and evaluated the
findings from the market model analysis in the context of the findings from the 0.1 percent threshold analysis.
EPA compared facility-level costs and revenue on a non-weighted basis and determined the number of instances
in which facilities incurred costs in the cost-to-revenue impact ranges. EPA applied facility-level sample weights
(see Appendix H: Sample Weights for a discussion of how EPA developed and applied the weights) to the
individual facility counts within each impact category to estimate the number of facilities at the population level
in these ranges.
Key Findings
Table 4-1 reports facility-level cost-to-revenue results by North American Reliability Corporation (NERC) region
for the final rule and other options considered.74 Under the assumption that all facilities with cooling water system
impoundments qualify as baseline CCRS, EPA estimates that overall, under the final rule, the vast majority of
regulated facilities (86 percent) will incur compliance costs less than 1 percent of revenue; this is true for all
NERC regions. Under Proposal Option 4, the vast majority of regulated facilities would also incur costs less than
1 percent of revenue, at 87 percent; again, this finding is true for all NERC regions. EPA estimates that Proposal
Option 2 would have a greater impact on regulated facilities, with 58 percent of facilities incurring costs
exceeding 1 percent of revenue, and 43 percent incurring costs exceeding 3 percent of revenue.75 Under this
option, findings vary across NERC regions. Under the assumption that no facilities with cooling water system
impoundments qualify as baseline CCRS, the analysis results are similar, with the vast majority of facilities
incurring compliance costs of less than 1 percent of revenue under the final rule and Proposal Option 2 (86
percent and 87 percent, respectively). Under Proposal Option 2, most regulated facilities (62 percent) would incur
costs exceeding 1 percent of revenue, with 46 percent incurring costs exceeding 3 percent of revenue.76
As reported in Table 4-2, regardless of the assumption on whether facilities with cooling water system
impoundments qualify as baseline CCRS, under the final rule and Proposal Option 4, compliance costs are
negligible for approximately half of regulated facilities, compared to the overall scale of business activity at the
facility measured by facility revenue (i.e., less than 0.1 percent of revenue). Proposal Option 2 would impose
higher costs on regulated facilities, with 65 percent and 70 percent incurring costs exceeding 0.1 percent of
revenue, under the alternative assumptions that all facilities with cooling water system impoundments qualify as
baseline CCRS and no facilities with cooling water system impoundments qualify as baseline CCRS, respectively.
The finding that the final rule would impose no more than negligible costs on a substantial fraction (49 - 52
percent) of facilities is significant, as it underscores the low expected burden of the final rule on the operating
73 As described in the introduction to this chapter, EPA performed a similar analysis for Manufacturers (see Chapter 5: Economic Impact
Analyses - Manufacturers).
74 NERC is responsible for the overall reliability, planning, and coordination of the national and regional power grids. It is organized into
regional units that are responsible for the overall coordination of bulk power policies that affect their regions' reliability and quality of
service (see Chapter 2).
15 In these calculations, facilities with cost-to-revenue ratios of at least 3 percent were included in the number of facilities with cost-to-
revenue such ratios of at least 1 percent.
16 In these calculations, facilities with a cost-to-revenue ratio of at least 3 percent were included in the count of facilities with a cost-to-
revenue ratio of at least 1 percent.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
economics of regulated electric power facilities. As described above, EPA reached a presumptive finding for these
facilities that compliance costs would be so low as to be negligible in terms of potential adverse impact.
Table 4-1: Facility-Level Cost-to-Revenue Analysis Results by NERC Region, Final Rule-Existing Units
and Other Options Considered3'15'0
NERC
Region
Assuming All Facilities with Cooling Water System
Impoundments Qualify as Baseline CCRS
Assuming No Facilities with Cooling Water System
Impoundments Qualify as Baseline CCRS
Total Number
of Facilities'1
No Revenue6
Number of Facilities with a
Ratio of
Total Number
of Facilities'1
No Revenue6
Number of Facilities with a
Ratio of
<1%
>1 and
<3%
>3%
<1%
>1 and
<3%
>3%
Proposal O
ption 4
ASCC
0
0
0
0
0
0
0
0
0
0
FRCC
24
0
22
2
0
24
0
22
2
0
IIICC
3
0
3
0
0
3
0
3
0
0
MRO
60
0
49
9

63
0
52
8

NPCC
58
0
51
5

58
0
51
5

RFC
135
0
119
2

136
0
120
2

SKRC
145
2
130
6

141
2
125
4
9
SPP
36
0
30
5

37
0
28
8

i ri :
45
0

46
0
36
5

wkcc
37
0
35
2
0
36
0
34
2
0
Total
544
2
475
35
31
544
2
471
36
34
Final Rule - Existing Units
ASCC
0
0
0
0
0
0
0
0
0
0
FRCC
24
0
22
2
0
24
0
22
2
0
IIICC
3
0
3
0
0
3
0
3
0
0
MRO
60
0
46
11

63
0
49
11

NPCC
58
0
49
7
2
58
0
49
7
2
Rl-'C
135
0
119
2

136
0
120
2

SKRC
145
2
130
6

141
2
125
4
9
SPP
36
0
30
5

37
0
28
8

IRK
45
0

46
0
36
5

WKCC
37
0
35
2
0
36
0
34
2
0
Total
544
2
470
40
31
544
2
467
41
34
Proposal O
ption 2
ASCC
0
0
0
0
0
0
0
0
0
0
FRCC
24
0
10
6
8
24
0
9
8
8
IIICC
.•>
0
0
0
3

0
0
0
3
MRO
60
0
19
17
25
63
0
20
16
!6
NPCC
58
0
34
9
14
58
0
34
9
14
RFC
135
0
52
18
>6
136
0
50
19
>7
SKRC
145
2
41
27
75
141
2
37
25
U>
SPP
36
0
24
0

37
0
17
0
!()
IRK
45
0
12
0
i3
46
0
3
7
36
WKCC
37
0
35
2
0
36
0
34
2
0
Total
544
2
228
79
235
544
2
205
86
251
a. ASCC - Alaska Systems Coordinating Council; FRCC - Florida Reliability Coordinating Council; F1ICC - Flawaii Coordinating Council; MRO -
Midwest Reliability Organization; NPCC - Northeast Power Coordinating Council; RFC - ReliabilityFirst Corporation; SERC - Southeastern Electric
Reliability Council; SPP - Southwest Power Pool; TRE - Texas Reliability Entity, and WECC - Western Energy Coordinating Council.
b. No explicitly analyzed facilities are located in the ASCC region. For more information on explicitly and implicitly analyzed facilities, see Appendix H.
c. Facility counts may not sum to reported totals due to independent rounding.
d. Facility counts exclude baseline closures.
e. EIA reports no revenue for 1 facility (2 on a weighted basis); consequently, the facility-level cost-to-revenue analysis is conducted for 542 facilities.
Source: U.S. EPA analysis for this report
4-6
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
Table 4-2: Facilities with Costs Below 0.1 Percent of Revenue by NERC Region, Final Rule-Existing Units
and Other Options Considered3' 'c

Assuming All Facilities with Cooling Water System
Impoundments Qualify as Baseline CCRS
Assuming No Facilities with Cooling Water System
Impoundments Qualify as Baseline CCRS

Number of Facilities with a

Number of Facilities with a
NERC
Total Number

Ratio of
Total Number
No
Ratio of
Region
of Facilities'1
No Revenue6
<0.1%
>0.1%
of Facilities'1
Revenue6
<0.1%
>0.1%
Proposal Option 4
ASCC
0
0
0
0
0
0
0
0
FRCC
24
0
16
i
24
0
17
8
IIICC
3
0
0
3
3
0
0
3
MRO
60

63
0
16
47
NPCC
58
0
37

58
0
37
21
RFC
135
0
58
<
136
0
53
83
SKRC
145

82
i
141
2
76
63
SPP
36
0
17
)
37
0
13
24
i ri:
45
0
24
i
46
0
19
27
wkcc
37
0
35
2
36
0
34
2
Total
544
2
285
257
544
2
265
276
Final Rule - Existing Units
ASCC
0
0
0
0
0
0
0
0
FRCC
24
0
16
i
24
0
17
8
IIICC
3
0
0
3
3
0
0
3
MRO
60
0
17

63
0
16
47
NPCC
58
0
37

58
0
37
21
RFC
135
0
58
<
136
0
53
83
SKRC
145
2
82
i
141
2
76
63
SPP
36
0
17
)
37
0
13
24
TRK
45
0
24
i
46
0
19
27
WKCC
37
0
35
2
36
0
34
2
Total
544
2
285
257
544
2
265
276
Proposal Option 2
ASCC
0
0
0
0
0
0
0
0
l'RCC
24
0
8
S
24
0
7
17
IIICC
3
0
0

3
0
0
3
MRO
60
0
8
>
63
0
8
55
NPCC
58
0
29
)
58
0
29
29
RFC
135
0
40
>
136
0
35
101
SKRC
145
2
39
1
141
2
35
104
SPP
36
0
19

37
0
9
28
TRK
45
0
12
33
46
0
3
43
WKCC
37
0
35
2
36
0
34
2
Total
544
2
190
352
544
2
160
382
a. ASCC - Alaska Systems Coordinating Council; FRCC - Florida Reliability Coordinating Council; F1ICC - Flawaii Coordinating Council; MRO -
Midwest Reliability Organization; NPCC - Northeast Power Coordinating Council; RFC - ReliabilityFirst Corporation; SERC - Southeastern Electric
Reliability Council; SPP - Southwest Power Pool; TRE - Texas Reliability Entity, and WECC - Western Energy Coordinating Council.

b. No explicitly analyzed facilities are located in the ASCC region. For more information on explicitly and implicitly analyzed facilities, see
Appendix H.
c. Facility counts may not sum to reported totals due to independent rounding.
d. Facility counts exclude baseline closures.

e. EIA reports no revenue for 1 facility (2 on a weighted basis); consequently, the facility-level cost-to-revenue analysis is conducted for 542 facilities.
Source: U.S. EPA analysis for this report

Uncertainties and Limitations
The analysis of facility-level impacts is subject to several uncertainties and limitations, including:
> Given the large number of implicitly analyzed facilities, it is impossible to develop sample weights that
accurately account for all economic and operating differences among these facilities. Specifically, the
facility count-based weights EPA used, account only for the number of facilities within each NERC
region (see Appendix H). The actual compliance costs assigned to each of the explicitly analyzed facilities
May 2014
4-7
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
may differ from the costs that would be assigned to the implicitly analyzed facilities they represent.
Consequently, the facility counts in each impact magnitude group may be over- or under-estimated.
> To the extent that the IPM-projected variable production costs used to estimate the cost of energy penalty
and technology-installation downtime differ from actual 2011 variable production costs, the impact of the
final rule and other options considered may be over- or under-stated.
> To the extent that cost and revenue values do not change at the same rate beyond 2011, individual facility
cost-to-revenue ratios calculated using 2011 cost and revenue values and the total impact of the final rule
and other options considered may be over- or under-stated.
> As noted above, for analytic convenience, EPA assumed that regulated facilities will not be able to pass
on any increase in their production costs due to compliance with the rule to consumers through higher
electricity prices. Because some facilities are expected to recover some of their compliance costs through
price and revenue increases, this analysis likely overstates the potential impact of the final rule and other
options considered on regulated facilities. Such revenue increases would lead to a lower cost-to-revenue
ratio. In particular, the approximately 60 percent of regulated facilities that operate in a rate-regulated
environment may recover all or a substantial fraction of their compliance cost through revenue increases.
In addition, depending on the effect of regulation-induced production cost increases on market prices,
generating facilities operating in deregulated markets may recover some of their compliance costs.
4.2.2 Cost-to-Revenue Screening Analysis: Entity-Level Analysis
EPA also analyzed the economic impact of the existing unit provision of the final rule and other options
considered at the level of parent entity, referred to as the "entity level" in the remainder of this section. The cost-
to-revenue screening analysis at the entity level provides insight on the impact of compliance requirements on
those entities that own more than one regulated facility; the analysis attempts to answer the question of whether
owning multiple facilities that need to comply with today's rule leads to a significant financial hardship. EPA
conducted this analysis at the highest level of domestic ownership, referred to as the "domestic parent entity." The
Agency performed this analysis for only the entity with the largest share of ownership (the "majority owner") in a
regulated facility.77'78 As with the facility-level cost-to-revenue analysis (Section 4.2.1), the entity-level analysis
presented in this chapter assumes no pass-through of compliance costs to electricity consumers.
Analysis Approach and Data Inputs
To analyze the entity-level economic/financial impact of compliance requirements, EPA aggregated facility-level
compliance costs, calculated on an annualized after-tax basis (see Section 4.2.1), to the entity level and compared
these costs to entity revenue. Similar to the facility-level analysis, EPA used cost-to-revenue ratios of 1 and 3
percent to assess whether these entity-level costs could constitute a significant impact. The Agency assumed that
entities incurring costs below 1 percent of revenue will not face significant economic impacts, while entities with
costs of at least 1 percent but less than 3 percent of revenue have a chance of facing significant economic impacts,
with entities incurring costs of at least 3 percent of revenue have a higher probability of significant economic
impacts.
This analysis involved the following steps:
> Identifying the parent entity.
> Determining the parent-entity revenue.
77 Throughout these analyses, EPA refers to the owner with the largest ownership share as the "majority owner" even when the
ownership share is less than 51 percent.
78 When two entities have equal ownership shares in a facility (e.g., 50 percent each), EPA analyzed both entities and assigned 100
percent of facility-level compliance costs to each entity.
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May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
> Estimating compliance costs at the level of the parent entity.
Identifying the Parent Entity
EPA identified the highest-level domestic parent entity for the explicitly and implicitly analyzed Electric
Generators (see Appendix H). As discussed below, EPA needs this information to support an estimate of entity-
level impact that reflects the numbers of parent entities for both the explicitly and implicitly analyzed Electric
Generators.
EPA relied on the information from the 2010 Questionnaire for the Steam Electric Power Generating Effluent
Guidelines (SE industry survey), 2009 EIA-861 and EIA-860 databases, and corporate/financial websites to
determine ownership for Electric Generators that participated in the SE industry survey. For all other facilities, the
Agency used the 2011 EIA-861 and 2011 EIA-860 databases and corporate/financial websites.79 EPA used the
same data sources to determine each entity's ownership share in each regulated facility it owned. As stated above,
EPA conducted the entity-level cost-to-revenue analysis only for entities with the largest share of ownership in
regulated facilities.
Estimating Parent-Entity Revenue
For each parent entity identified in the preceding step, EPA estimated revenue as follows:
> EPA used entity-level revenue from the SE industry survey, where reported. For entities with revenue
reported for more than one survey year (i.e., 2007, 2008, and/or 2009), EPA used the average. For entities
with revenue reported for only one survey year, EPA used the value reported for that year.
> For entities with no revenue reported in the SE industry survey, EPA used revenue from
corporate/financial websites, if available. To be consistent with the SE industry survey data, EPA tried to
obtain revenue for at least one of the three survey years (i.e., 2007, 2008, and/or 2009) and used the
80
average.
> For publicly owned entities with no revenue reported in either the SE industry survey or on the
corporate/financial websites, the Agency used the 2007-2011 average revenue from the EIA-861
database.
EPA restated entity revenue values in 2011 dollars using the GDP Deflator and assumed that these revenues were
the same in the 2011 analysis year.81
Estimating Compliance Costs at the Parent-Entity Level
Because EPA developed compliance costs only for explicitly analyzed facilities, the Agency was able to assign
facility-level costs directly to only the entities that own explicitly analyzed facilities, and for only the explicitly
analyzed facilities that they own. However, such a limited analysis would have omitted consideration of the costs
79 For facilities included in the analysis conducted in support of the revisions of the existing Effluent Limitations Guidelines and
Standards for the Steam Electric Power Generating Point Source Category (SE ELG), EPA used ownership information from that
analysis. At the time SE ELG ownership analysis was conducted, 2009 EIA data were the most current data available.
80 For two entities EPA used revenue reported for 2010.
81 Although EPA expects regulated facilities to install required technologies during a window of time that is farther into the future, EPA
was not confident in projecting revenue of entities that own these facilities beyond 2011. As is the case with the facility-level cost-to-
revenue analysis (Section 4.2.1), to be consistent with the revenue estimates, EPA used 2011 as the basis for the revenue and
compliance cost estimates, regardless of when facilities owned by these entities are expected to incur compliance costs. Because this
analysis relies on a ratio of cost to revenue as opposed to absolute values, the ratio for a given entity will be the same in years beyond
the selected analysis year as long as cost and revenue values are as of the same year and the basis for projecting those values is the
same, going forward from the selected analysis year. That is, beyond the selected analysis year, cost and revenue values are assumed
to change at the same rate and thus, the ratio of these values will be constant over time.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
incurred by implicitly analyzed facilities at the parent-entity level. To address this limitation, EPA developed
weighting approaches to estimate and assign costs at the entity level that would account for the costs incurred by
both explicitly and implicitly analyzed facilities.
Because the facility-level weights do not apply at the parent-entity level, and further, because EPA cannot develop
joint facility-/entity-level weights, EPA conducted this analysis using two weighting approaches. These
approaches provide a range of estimates for the number of entities incurring compliance costs and the costs
incurred by any entity that owns a regulated facility:
> Using facility-level weights: EPA applied facility-level weights to annualized, after-tax compliance costs it
estimated for the explicitly analyzed facilities and aggregated those costs to the level of the parent entity
that owns them. In effect, this analysis assumes that a parent entity that owns one or more explicitly
analyzed facilities owns and incurs the compliance costs for those facilities and the implicitly analyzed
facilities represented by the sample weights applied to the costs for the explicitly analyzed facilities. EPA
then compared the resulting entity-level costs to entity revenue. To the extent that parent entities of
explicitly analyzed facilities do not own implicitly analyzed facilities and consequently, would not incur
their costs, this approach will overstate impacts on individual parent entities. Because this approach does
not account for entities that own only implicitly analyzed facilities, it underestimates the number ofparent
entities that own regulated facilities.
> Using entity-level weights: EPA aggregated annualized, after-tax compliance costs developed for the
explicitly analyzed facilities to the level of the parent entity without applying facility-level weights and
compared the resulting entity-level costs to entity revenue. To account for parent entities that own only
implicitly analyzed facilities - and thus are not directly captured in the analysis that uses facility-level
weights - EPA applied entity-level weights to entity counts in each cost-to-revenue impact category to
extrapolate the findings to the total population of parent entities, including those that own only implicitly
analyzed facilities. For details on development of entity-level weights, see Appendix H. To the extent that
parent entities of explicitly analyzed facilities also own implicitly analyzed facilities and consequently,
would incur their costs, this approach will understate impacts on individual parent entities. However,
unlike the approach using facility-level weights, this approach provides a more accurate estimate of the
number of entities that own regulated facilities.
Key Findings
Table 4-3 reports analysis results for the final rule and other options considered under the assumption that all
facilities with cooling water system impoundments qualify as baseline CCRS. Usingfacility-level weights, EPA
estimates that 123 parent entities own 544 regulated facilities. EPA estimates that the majority of parent entities
(91 percent) will incur compliance costs of less than 1 percent of revenue under the existing unit provision of the
final rule. For the other options considered, EPA estimated that 91 percent and 70 percent of parent entities would
incur compliance costs of less than 1 percent of revenue under Proposal Option 4 and Proposal Option 2,
respectively. As discussed above, this approach is likely to overstate the costs to individual parent entities but may
underestimate the number of parent entities in a given impact range.
Using entity weights, EPA estimates that 159 parent entities own 544 regulated facilities (Table 4-3). Similar to
the analysis conducted using facility-level weights, EPA estimates that the majority of parent entities (94 percent)
will incur compliance costs of less than 1 percent of revenue under the final rule. For the other options considered,
EPA estimates that 94 percent and 78 percent of parent entities would incur compliance costs of less than 1
percent of revenue under Proposal Options 4 and 2, respectively. As described above, this approach is likely to
understate the costs to individual parent entities but provides a more comprehensive estimate of the number of
parent entities incurring costs.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
Table 4-4 reports analysis results for the final rule and other options considered under the assumption that no
facilities with cooling water system impoundments qualify as baseline CCRS. Using facility-level, weights, EPA
estimates that 123 parent entities own 544 regulated facilities. Using entity weights, EPA estimates that 159 parent
entities own 544 regulated facilities. Again, EPA estimates that the majority of parent entities will incur
compliance costs of less than 1 percent of revenue under the final rule and other options considered regardless of
the weighting case.
Overall, this analysis shows that the entity4evel compliance costs are low in comparison to entity4evel revenues;
consequently, the final rule will not additionally "penalize" parent entities that own more than one regulated
facility as a result of their ownership of multiple facilities.
Table 4-3: Entity-Level Cost-to-Revenue Analysis Results, Using Facility-Level Weights, Final Rule-
Existing Units and Other Options Considered - Assuming All Facilities with Cooling Water System
Impoundments Qualify as Baseline CCRSa
Entity Type
Using Facility-Level Weights
Using Entity-Level Weights
Total
Number
of Entities
Number of Entities with a Cost-to-
Revenue Ratio of
Total
Number
of Entities
Number of Entities with a Cost-to-Revenue
Ratio of
<1%
>1 % and
<3%
>3%
Unknown6
<1%
>1% and
<3%
>3%
Unknown6
Proposal Option 4
Cooperative
13
13
0
0
0
21
21
0
0
0
Federal
1
1
0
0
0
1
1
0
0
0
Investor-owned
57
56
0
0
1
60
59
0
0
1
Municipality
19
16
3
0
0
38
38
0
0
0
Nonutilitv
26
20
0
0
6
30
23
0
0
7
Other Political
Subdivision
4
3
0
0
1
6
5
0
0
2
State
3
3
0
0
0
3
3
0
0
0
Total
123
112
3
0
8
159
150
0
0
9
Final Rule - Existing Units
Cooperative
13
13
0
0
0
21
21
0
0
0
Federal
1
1
0
0
0
1
1
0
0
0
Investor-owned
57
56
0
0
1
60
59
0
0
1
Municipality
19
16

0
0
38
38
0
0
0
Nonutilitv
26
20
0
0
6
30
23
0
0
7
Other Political
Subdivision
4
3
0
0
1
6
5
0
0
2
State
3
3
0
0
0
3
3
0
0
0
Total
123
112
3
0
8
159
150
0
0
9
Proposal Option 2
Cooperative
13
9
2
2
0
21
16
5
0
0
Federal
1
0
0
1
0
1
0
0
1
0
Investor-owned
57
44
9
3
1
60
54
5
0
1
Municipality
19
12
5
2
0
38
30
6
2
0
Nonutilitv
26
17
1
2
6
30
20
2
1
7
Other Political
Subdivision
4
1
0
2
1
6
2
0
3
2
State
3
3
0
0
0
3
3
0
0
0
Total
123
86
17
12
8
159
124
18
7
9
a. Entity counts may not sum to reported totals due to independent rounding.
b. EPA was unable to determine revenues for 8 parent entities (9 weighted).
Source: U.S. EPA analysis for this report
May 2014
4-11
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
Table 4-4: Entity-Level Cost-to-Revenue Analysis Results, Using Facility-Level Weights, Final Rule-
Existing Units and Other Options Considered
- Assuming No Facilities with Cooling Water System
Impoundments Qualify as Baseline CCRSa

Using Facility-Level Weights
Using Entity-Level Weights

Number of Entities with a Cost-to-

Total

Revenue Ratio of

Total

Revenue Ratio of

Number

>1% and

Number

>1% and

Entity Type
of Entities
<1%
<3%
>3%
Unknown6
of Entities
<1%
<3%
>3%
Unknown6
Proposal Option 4
Cooperative
13
12
1
0
0
21
19
2
0
0
Federal
1
1
0
0
0
1
1
0
0
0
Investor-owned
55
55
0
0
0
60
60
0
0
0
Municipality
15
12
3
0
0
38
38
0
0
0
Nonutilitv
25
19
0
0
6
30
23
0
0
7
Other Political
4
3
0
0
1
6
5
0
0
2
Subdivision

State
3
3
0
0
0
3
3
0
0
0
Total
116
105
4
0
7
159
149
2
0
9
Final Rule - Existing Units
Cooperative
13
12
1
0
0
21
19
2
0
0
Federal
1
1
0
0
0
1
1
0
0
0
Investor-owned
55
55
0
0
0
60
60
0
0
0
Municipality
15
12
3
0
0
38
38
0
0
0
Nonutilitv
25
19
0
0
6
30
23
0
0
7
Other Political
4
3
0
0
1
6
5
0
0
2
Subdivision

State
3
3
0
0
0
3
3
0
0
0
Total
116
105
4
0
7
159
149
2
0
9
Proposal Option 2
Cooperative
13
8
2
3
0
21
15
5
2
0
Federal
1
0
0
1
0
1
0
0
1
0
Investor-owned
55
39
10
6
0
60
51
9
0
0
Municipality
15
8
5
2
0
38
28
8
3
0
Nonutilitv
25
16
1
2
6
30
19
2
1
7
Other Political
4
1
0
2
1
6
2
0
3
2
Subdivision

State
3
3
0
0
0
3
3
0
0
0
Total
116
75
18
16
7
159
117
24
9
9
a. Entity counts may not sum to reported totals due to independent rounding.

b. EPA was unable to determine revenues for 7 parent entities (9 weighted).

Source: U.S. EPA analysis for this report

Uncertainties and Limitations
The analysis of entity-level impacts is subject to several uncertainties and limitations, including:
> As described above, EPA applied the facility-level and entity-level weights in developing the estimates of
entity-level impacts and the numbers of entities incurring costs in given cost-to-revenue impact ranges.
The use of these sample weights creates the potential to over- or under-state the impact of regulatory
requirements.
¦ Use of the facility-level weights alone likely overstates the cost-to-revenue impact on identified
parent entities while potentially understating the number of parent entities in a given cost-to-revenue
impact category.
¦ Use of entity-level weights alone may underestimate the number of facilities owned by a parent entity
and the associated compliance costs incurred by the parent entity.
> The facility count-based sample weights EPA used account only for the number of facilities within each
NERC region (see Appendix H). The actual compliance costs assigned to each of the explicitly analyzed
4-12
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
facilities may differ from the costs that would be assigned to the implicitly analyzed facilities that they
represent. Consequently, the cost estimates generated through application of facility-level weights may be
over- or under-stated at the level of a given parent entity. This may also be the case with the entity counts
in each of the impact magnitude groups, even if the facility-weights account properly for facility
ownership.
> The entity-level revenues obtained from the SE industry survey, corporate, and financial websites are for
2007, 2008, and/or 2009 and those estimated based on EIA data for 2007 through 2011. To the extent that
actual 2011 entity revenues are different, on a constant dollar basis, from estimated values, the impact of
the final rule and other options considered on parent entities of regulated facilities may be over- or under-
estimated.
> To the extent that cost and revenue values change at different rates after 2011, individual entity cost-to-
revenue ratios calculated using 2011 cost and revenue values, and the total impact of the final rule and
other options considered may be over- or under-stated.
> As is the case with the facility-level analysis discussed in Section 4.2.2, the zero cost pass-through
assumption is relatively simple and used for analytic convenience. Because some entities are expected to
recover some of their compliance costs through price and revenue increases, this analysis likely overstates
the potential entity-level impact of the final rule and other options considered.
4.2.3 Analysis of Impact of Compliance Costs on Electricity Prices
As part of its analysis of the cost and economic impact of the final rule and other options considered, EPA
assessed the potential increase in electricity prices to electricity consumer groups, including residential,
commercial, industrial, and transportation, and to households (discussed in Section 4.2.4). The facility-level and
entity-level cost-to-revenue screening analyses, discussed in Sections 4.2.1 and 4.2.2, reflect an assumption that
regulated facilities and their parent entities will absorb 100 percent of the compliance burden (zero cost pass-
through). In contrast, this electricity price impact analysis and the household electricity cost analysis, assume 100
percent pass-through of compliance costs in electricity prices (full cost pass-through). If this full cost pass-
through condition were to occur, the screening analyses discussed in Sections 4.2.1 and 4.2.2 would not be
relevant because the two conditions (no cost pass-through and full cost pass-through) could not occur for the
same regulated facility.
As discussed earlier in Section 4.2.1, facilities located in States where electricity prices remain regulated under the
traditional cost-of-service rate regulation framework may be able to recover compliance cost-based increases in
their production costs through increased electricity prices, depending on the business operation model of the
facility owner(s), the ownership and operating structure of the facility itself, and the role of market mechanisms
used to sell electricity. Cost recovery is less certain for facilities located in States where electric power generation
has been deregulated. Moreover, even though individual facilities subject to the final rule may not be able to
recover all of their compliance costs through increased revenues, the market-level effect may still be that
consumers will see higher overall electricity prices because of changes in the cost structure of electricity supply
and resulting changes in market-clearing prices in deregulated electricity markets.
For the electricity price impact and the household electricity cost analyses, the Agency assumed that 100 percent
of compliance costs would be passed through to consumers. This assumption is appropriate for two reasons: (1)
the majority of facilities subject to the final rule are likely to be able to recover increases in their production costs
through increased electricity prices because these facilities operate in the cost-of-service framework and (2) for
facilities operating in States where electric power generation has been deregulated, EPA cannot estimate this
consumer price effect at the State level. Thus, this full cost pass-through assumption represents a "worst-case"
impact scenario from the perspective of the electricity consumers. It will avoid understating the potential cost
May 2014
4-13
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
impact to consumers from the final rule and other options considered. To the extent that all compliance-related
costs are not passed through to consumers, this analysis will overstate consumer impacts.
Analysis Approach and Data Inputs
EPA assumed that compliance costs would be fully passed through as increased electricity prices and allocated
among customer classes in proportion to the baseline quantity of electricity consumption by consumer group.
EPA performed this analysis at the NERC-region level, as follows:
> EPA summed weighted pre-tax facility-level annualized compliance costs by NERC region.82
> EPA estimated the approximate average price impact per unit of electricity consumption by dividing total
compliance costs by the projected total MWh of sales in 2020 by NERC region, from Al-X)20l2. EPA
followed this approach for all NERC regions except the ASCC and HICC regions, for which AEO2012
does not provide projections. For these two NERC regions, the Agency used the historical quantity of
electricity sales - total and by consumer group - from the 2011 EIA-861 database.
> EPA compared the estimated average price effect to the projected electricity price by customer class and
NERC region for 2020 from AEO2012 for all NERC regions except, again, for ASCC and HICC. To
estimate average electricity price by consumer group for ASCC and HICC, EPA divided electricity
revenue by electricity sales (MWh) reported in the 2011 EIA-861 database for each consumer class.
Key Findings
As reported in Table 4-5, assuming that all facilities with cooling water system impoundments qualify as baseline
CCRS, under the existing unit provision of the final rule annualized compliance costs (in cents per kWh sales)
range from nearly zero cents in the WECC region to 0.040 cents in the HICC region. EPA reached the same
finding for Proposal Option 4. Under Proposal Option 2, costs range from nearly zero cents in the WECC region
to 0.351 cents in the HICC region. On average, across the United States, the existing unit provision of the final
rule and Proposal Option 4 result in a cost of 0.009 cents per kWh, while Proposal Option 2 results in a higher
cost of 0.155 cents per kWh.
Assuming that no facilities with cooling water system impoundments qualify as baseline CCRS, under the
existing unit provision of the final rule and Proposal Option 4, annualized compliance costs also range from
nearly $0.00 in the WECC region to 0.040 cents in the HICC region. Under Proposal Option 2, costs also range
from nearly zero cents in the WECC region to 0.351 cents in the HICC region. Across the United States, on
average, the existing unit provision of the final rule and Proposal Option 4 result in a cost of 0.011 cents per kWh,
while Proposal Option 2 results in a cost of 0.171 cents per kWh.
82 These compliance costs are in 2011 dollars as of a given technology-installation year (2018 through 2030, depending on a regulatory
option) and discounted to 2020 at 7 percent.
4-14
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
Table 4-5: Compliance Cost per kWh of Sales by NERC Region in 2020, Final Rule-Existing Units and
Other Options Considered3'15'0
NERC
Region
Total Electricity Sales
(at 2020; kWh)
Assuming All Facilities with Cooling Water
System Impoundments Qualify as Baseline CCRS
Assuming No Facilities with Cooling Water
System Impoundments Qualify as Baseline CCRS
Annualized Pre-Tax
Compliance Costs (at
2020; $2011)
Costs per Unit of Sales
(2011^/kWh Sales)
Annualized Pre-Tax
Compliance Costs (at
2020; $2011)
Costs per Unit of Sales
(2011^/kWh Sales)
Proposal Option 4
ASCC
6,318,369,000
$0
0.000
$0
0.000
FRCC
227,725,769,000
$32,085,596
0.014
$32,625,282
0.014
HICC
9,961,653,000
$4,010,571
0.040
$4,010,571
0.040
MRO
212,722,061,000
$20,283,069
0.010
$26,888,489
0.013
NPCC
269,363,615,000
$21,760,125
0.008
.760.125
0.008
RFC
875,942,368,000
$93,043,545
0.01 1
.032.827
0.013
SERC
1,056,641,854,000
$142,575,030
0.013
$147,171,619
0.014
SPP
206,449,802,000
$19,596,770
0.009
$36,909,900
0.018
TRE
332,132,690,000
$25,777,009
0.008
$44,382,046
0.013
WECC
705,550,339,000
$788,032
0.000
$774,608
0.000
U.S.
3,906,950,928,000
$359,919,748
0.009
$425,555,466
0.011
Final Rule - Existing Units
ASCC
6,318,369,000
$0
0.000
$0
0.000
FRCC
227,725,769,000
$32,085,596
0.014
$32,625,282
0.014
HICC
9,961,653,000
$4,010,571
0.040
$4,010,571
0.040
MRO
212,722,061,000
$20,852,642
0 010
$27,459,636
0 013
NPCC
269,363,615,000
$22,079,437
0.008
1.079.437
0.008
RFC
875,942,368,000
$93,308,548
0.01 1
.775
0.013
SERC
1,056,641,854,000
$142,575,030
0.013
.532
0.014
SPP
206,449,802,000
$19,596,770
0.009
$36,909,900
0.018
TRE
332,132,690,000
$25,777,009
0.008
$44,382,046
0.013
WECC
705,550,339,000
$788,032
0.000
$774,608
0.000
U.S.
3,906,950,928,000
$361,073,637
0.009
$427,009,786
0.011
Proposal Option 2
ASCC
6,318,369,000
$0
0.000
$0
0.000
FRCC
227,725,769,000
$389,416,274
0.171
$404,032,918
0.177
HICC
9,961,653,000
$34,953,404
0.351
$34,953,404
0.351
MRO
212,722,061,000
$369,493,353
0.174
!.511.290
0.194
NPCC
269,363,615,000
$339,326,908
0.126
$339,326,908
0.126
RFC
875,942,368,000
$1,751,066,574
0.200
$1.82 1.672.930
0.208
SERC
1,056,641,854,000
$2,313,029,308
0.219
$2.i70.905.008
0.224
SPP
206,449,802,000
$161,631,013
0.078
$416,336,889
0.202
TRE
332,132,690,000
$683,768,032
0.206
$891,860,951
0.269
WECC
705,550,339,000
$660,327
0.000
$646,903
0.000
U.S.
3,906,950,928,000
$6,043,345,192
0.155
$6,694,247,200
0.171
a. ASCC - Alaska Systems Coordinating Council; FRCC - Florida Reliability Coordinating Council; HICC - Hawaii Coordinating Council; MRO -
Midwest Reliability Organization; NPCC - Northeast Power Coordinating Council; RFC - ReliabilityFirst Corporation; SERC - Southeastern Electric
Reliability Council; SPP - Southwest Power Pool; TRE - Texas Reliability Entity, and WECC - Western Energy Coordinating Council.
b. The electricity price impact analysis assumes full pass-through of all compliance costs to electricity consumers.
c. No explicitly analyzed facilities are located in the ASCC region. For more information on explicitly and implicitly analyzed facilities see Appendix H.
Source: U.S. EPA analysis for this report
As discussed above, EPA compared the per kWh compliance cost to baseline electricity prices for each consumer
group and for the average electricity price of all consumer groups, to determine the potential significance of these
compliance costs on electricity prices. As reported in Table 4-6, assuming that all facilities with cooling water
system impoundments qualify as baseline CCRS, EPA estimates that across the United States, the existing unit
provision of the final rule will result in a less than 0.1 percent price increase. The Agency estimates that Proposal
Option 4 would result in approximately the same price increase, while Proposal Option 2 would result in a higher
increase of 1.6 percent. Looking across the four consumer groups, overall, industrial consumers are estimated to
experience the highest price increases: 0.1 percent under the existing unit provision of the final rule and Proposal
Option 4 and 2.3 percent under Proposal Option 2. Residential consumers are estimated to experience the lowest
May 2014
4-15
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
price increases: less than 0.1 percent under the final rule and Proposal Option 4 and 1.3 percent under Proposal
Option 2.
Assuming that no facilities with cooling water system impoundments qualify as baseline CCRS, EPA estimates
that across the United States, the existing unit provision of the final rule and Proposal Option 4 result in a 0.1
percent increase, with Proposal Option 2 leading to a 1.8-percent increase. Again, overall, industrial consumers
are estimated to experience the highest price increases: 0.2 percent under the existing unit provision of the final
rule and Proposal Option 4 and 2.6 percent under Proposal Option 2. Residential consumers are estimated to
experience the lowest price increases: less than 0.1 percent under the final rule and Proposal Option 4 and 1.5
percent under Proposal Option 2.
Table 4-6: Projected 2020 Price (Cents per kWh of Sales) and Potential Price Increase Due to Compliance
Costs by NERC Region (2011 cents), Final Rule-Existing Units and Other Options Considered - Assuming
All Facilities with Cooling Water System Impoundments Qualify as Baseline CCRSa'b'c
NERC
Region
Compliance
Cost (^/kWh)
Residential
Commercial
Industrial
Transportation
All Consumer
Group Average
Baseline
Price
%
Change
Baseline
Price
%
Change
Baseline
Price
%
Change
Baseline
Price
%
Change
Baseline
Price
%
Change
Proposal O
ption 4
A SCC
().()()()
17.60
0.00%
15.09
0.00%
15.71
0.00%
NA
NA
16.07
0.00%
l'RCC
0.0I4
11.81
0.12%
9.85
0.14%
9.14
0.15%
9.12
0.15%
10.80
0.13%
IIICC
0.040
34.68
0.12%
32.37
0.12%
28.40
0 14%
NA
A
31.59
0.13%
MRO
0.0I0
10.41
0.09%
8.26
0.12%
6.12
0.16%
8.83
0 11%
8.14
0.12%
NPCC
0.008
17.56
0.05%
14.01
0.06%
8.73
0.09%
13.42
0.06%
14.45
0.06%
Rl'C
0.0I I
12.84
0.08%
10.66
0.10%
7.27
0.15%
9.96
0.1 1%
10.40
0.10%
SKRC
0.01 3
10.57
0.13%
9.1 9
0.15%
6.13
0.22%
8.60
0.16%
8.85
0.15%
SPP
0.009
9.60
0.10%
8.21
0.12%
5.97
0.16%
9.30
0.10%
8.10
0.12%
i ri ;
0.008
11.36
0.07%
7.60
0 10%
5.88
0.13%
9 62
0.08%
8.60
0.09%
wkcc
0.000
11.92
0.00%
10.56
0.00%
6.67
0.00%
9.43
0.00%
10.14
0.00%
U.S.
0.009
11.80
0.08%
10.00
0.09%
6.60
0.14%
10.36
0.09%
9.79
0.09%
Final Rule - Existing Units
ASCC
0.000
17.60
0.00%
15.09
0.00%
15.71
0.00%
NA
NA
16.07
0.00%
FRCC
0.014
11.81
0.12%
9.85
0 14%
9.14
0.15%
9.12
0.15%
10.80
0.13%
IIICC
0.040
34.68
0.12%
32.37
0.12%
28.40
0 14%
NA
A
31.59
0.13%
MRO
0.010
10.41
0.09%
8.26
0.12%
6.12
0.16%
8.83
0 11%
8.14
0.12%
NPCC
0.008
17.56
0.05%
14.01
0.06%
8.73
0.09%
13.42
0.06%
14.45
0.06%
Rl'C
0.011
12.84
0.08%
10.66
0.10%
7.27
0.15%
9.96
0.11%
10.40
0.10%
SKRC
0.013
10.57
0.13%
9.1 9
0.15%
6.13
0.22%
8.60
0.16%
8.85
0.15%
SPP
0.009
9.60
0.10%
8.21
0.12%
5.97
0.16%
9.30
0 10%
8.10
0.12%
i ri ;
0.008
11.36
0.07%
7.60
0.10%
5.88
0.13%
9 62
0.08%
8.60
0.09%
wire
0.000
11.92
0.00%
10.56
0.00%
6.67
0.00%
9.43
0.00%
10.14
0.00%
U.S.
0.009
11.80
0.08%
10.00
0.09%
6.60
0.14%
10.36
0.09%
9.79
0.09%
Proposal O
ption 2
ASCC
0.000
17.60
0.00%
15.09
0.00%
15.71
0.00%
NA
NA
16.07
0.00%
l'RCC
0.171
1 1.81
1 45%
9.85
1.74%
9.14
1 87%
9.12
1 87%
10.80
1.58%
IIICC
0.351
34.68
1 01%
32.37
1.08%
28.40
1 24%
NA
A
31.59
1.11%
MRO
0.174
10.41
1 67%
8.26
2.10%
6.12
2.84%
8.83
1 97%
8.14
2.13%
NPCC
0.126
17.56
0.72%
14.01
0.90%
8.73
1 4S%
13.42
0.94%
14.45
0.87%
Rl'C
0.200
12.84
1.56%
10.66
1.88%
7.27
2.75%
9.96
2.01%
10.40
1.92%
SKRC
0.219
10.57
2.07%
9.19
2.38%
6.13
3.57%
8.60
2.55%
8.85
2 47%
SPP
0.078
9.60
0.82%
8.21
0.95%
5.97
%
9.30
0.84%
8.10
0.97%
IRK
0.206
1 1.36
1 81%
7.60
2 71%
5.88
3.50%
9 62
2 14%
8.60
2.39%
WKCC
0.000
1 1.92
0.00%
10.56
0.00%
6.67
0.00%
9.43
0.00%
10.14
0.00%
U.S.
0.155
11.80
1.31%
10.00
1.55%
6.60
2.34%
10.36
1.49%
9.79
1.58%
a. ASCC - Alaska Systems Coordinating Council; FRCC - Florida Reliability Coordinating Council; F1ICC - Flawaii Coordinating Council; MRO -
Midwest Reliability Organization; NPCC - Northeast Power Coordinating Council; RFC - ReliabilityFirst Corporation; SERC - Southeastern Electric
Reliability Council; SPP - Southwest Power Pool; TRE - Texas Reliability Entity, and WECC - Western Energy Coordinating Council.
b. The electricity price impact analysis assumes full pass-through of all compliance costs to electricity consumers.
c. No explicitly analyzed facilities are located in the ASCC region. For more information on explicitly and implicitly analyzed facilities see Appendix H.
Source: U.S. EPA analysis for this report
4-16
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
Table 4-7: Projected 2020 Price (Cents per kWh of Sales) and Potential Price Increase Due to Compliance
Costs by NERC Region (2011 cents), Final Rule-Existing Units and Other Options Considered - Assuming
No Facilities with Cooling Water System Impoundments Qualify as Baseline CCRSa'b'c
NERC
Region
Compliance
Cost (^/kWh)
Residential
Commercial
Industrial
Transportation
All Consumer
Group Average
Baseline
Price
%
Change
Baseline
Price
%
Change
Baseline
Price
%
Change
Baseline
Price
%
Change
Baseline
Price
%
Change
Proposal O
ption 4
ASCC
().()()()
17.60
0.00%
15.09
0.00%
15.71
0.00%
NA
NA
16.07
0.00%
l'RCC
0.0I4
1 1.81
0.12%
9.85
0.15%
9.14
0.16%
9.12
0.16%
10.80
0.13%
IIICC
0.040
34.68
0.12%
32.37
0.12%
28.40
0 14%
NA
A
31.59
0.13%
MRO
0.01 3
10.41
0.12%
8.26
0.15%
6.12
0.21%
8.83
0 14%
8.14
0.16%
NPCC
0.008
17.56
0.05%
14.01
0.06%
8.73
0.09%
13.42
0.06%
14.45
0.06%
Rl'C
0.01 3
12.84
0.10%
10.66
0.12%
7.27
0.17%
9.96
0.13%
10.40
0.12%
SKRC
0.0I4
10.57
0.13%
9.19
0.15%
6.13
0.23%
8.60
0.16%
8.85
0.16%
SPP
0.0I8
9.60
0 19%
8.21
0.22%
5.97
0.30%
9.30
0 19%
8.10
0.22%
TRE
0.01 3
1 1.36
0.12%
7.60
0.18%
5.88
0.23%
9 62
0 14%
8.60
0.16%
WECC
0.000
11.92
0.00%
10.56
0.00%
6.67
0.00%
9.43
0.00%
10.14
0.00%
U.S.
0.011
11.80
0.09%
10.00
0.11%
6.60
0.16%
10.36
0.11%
9.79
0.11%
Final Rule - Existing Units
ASCC
0.000
17.60
0.00%
15.09
0.00%
15.71
0.00%
NA
NA
16.07
0.00%
l'RCC
0.014
1 1.81
0.12%
9.85
0.15%
9.14
0.16%
9.12
0.16%
10.80
0.13%
IIICC
0.040
34.68
0.12%
32.37
0.12%
28.40
0 14%
NA
A
31.59
0.13%
MRO
0.013
10.41
0.12%
8.26
0.16%
6.12
0.21%
8.83
0.15%
8.14
0.16%
NPCC
0.008
17.56
0.05%
14.01
0.06%
8.73
0.09%
13.42
0.06%
14.45
0.06%
Rl'C
0.013
12.84
0 10%
10.66
0.12%
7.27
0.17%
9.96
0.13%
10.40
0.12%
SKRC
0.014
10.57
0.13%
9.19
0.15%
6.13
0.23%
8.60
0.16%
8.85
0.16%
SPP
0.018
9.60
0.19%
8.21
0.22%
5.97
0.30%
9.30
0.19%
8.10
0.22%
TRE
0.013
1 1.36
0.12%
7.60
0.18%
5.88
0.23%
9.62
0.14%
8.60
0.16%
WECC
0.000
1 1.92
0.00%
10.56
0.00%
6.67
0.00%
9.43
0.00%
10.14
0.00%
U.S.
0.011
11.80
0.09%
10.00
0.11%
6.60
0.17%
10.36
0.11%
9.79
0.11%
Proposal O
ption 2
ASCC
0.000
17.60
0.00%
15.09
0.00%
15.71
0.00%
NA
NA
16.07
0.00%
FRCC
0.177
11.81
1.50%
9.85
1.80%
9.14
1.94%
9.12
1 94%
10.80
1.64%
IIICC
0.351
34.68
1 01%
32.37
1.08%
28.40
1 24%
NA
A
31.59
%
MRO
0.194
10.41
1.86%
8.26
2.35%
6.12
^ 17%
8.83
2.20%
8.14
2.38%
NPCC
0.126
17.56
0.72%
14.01
0.90%
8.73
%
13.42
0.94%
14.45
0.87%
Rl'C
0.208
12.84
1.62%
10.66
1.95%
7.27
2.86%
9.96
2.09%
10.40
2.00%
SKRC
0.224
10.57
2 12%
9.19
2 44%
6.13
3.66%
8.60
2.61%
8.85
2.54%
SPP
0.202
9.60
2 10%
8.21
2.46%
5.97
3.38%
9.30
2 17%
8.10
2.49%
IRK
0.269
1 1.36
2.36%
7.60
3.53%
5.88
4 S7%
9 62
2.79%
8.60
3.12%
WKCC
0.000
1 1.92
0.00%
10.56
0.00%
6.67
0.00%
9.43
0.00%
10.14
0.00%
U.S.
0.171
11.80
1.45%
10.00
1.71%
6.60
2.59%
10.36
1.65%
9.79
1.75%
a. ASCC - Alaska Systems Coordinating Council; FRCC - Florida Reliability Coordinating Council; F1ICC - Flawaii Coordinating Council; MRO -
Midwest Reliability Organization; NPCC - Northeast Power Coordinating Council; RFC - ReliabilityFirst Corporation; SERC - Southeastern Electric
Reliability Council; SPP - Southwest Power Pool; TRE - Texas Reliability Entity, and WECC - Western Energy Coordinating Council.
b. The electricity price impact analysis assumes full pass-through of all compliance costs to electricity consumers.
c. No explicitly analyzed facilities are located in the ASCC region. For more information on explicitly and implicitly analyzed facilities see Appendix H.
Source: U.S. EPA analysis for this report
Uncertainties and Limitations
This analysis is subject to several uncertainties and limitations, including:
> The assumptions regarding the full pass-through of compliance costs to electricity prices are relatively
simple and are used for analytic convenience. As stated previously, to the extent that some regulated
facilities would not fully pass compliance costs to consumers through higher electricity prices, this
analysis overstates the potential impact of the existing unit provision of the final rule and other options
considered on electricity consumers.
May 2014
4-17
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
> The assumption that compliance costs would be allocated across consumer classes on a uniform cents per
kilowatt-hour basis may not reflect the allocation that would occur in a regulated cost-of-service
ratemaking framework that guarantees full cost recovery assumed in this analysis. As a result, this
analysis may over- or understate the impact in specific consumer groups.
4.2.4 Analysis of Impact of Compliance Costs on Household Electricity Costs
As described above, EPA analyzed the potential impact of electricity prices increases on households, again
assuming a simple 100 percent pass-through of compliance costs in electricity prices. As stated above, this
assumption may overstate the eventual consumer cost impact.
Analysis Approach and Data Inputs
EPA assumed that compliance costs would be fully passed through as increased electricity prices and allocated
among customer classes in proportion to the baseline quantity of electricity consumption by consumer group (see
Section 4.2.3). EPA analyzed the potential impact on annual electricity costs at the level of the average household,
using the estimated household electricity consumption quantity by NERC region. This is appropriate given the
structure and functioning of sub-national electricity markets around which NERC regions are defined, and
regional variations in household electricity consumption profiles.83 The steps in this calculation are as follows:
> EPA used the all consumer-group average cost per MWh of electricity sales estimated by NERC region in
Section 4.2.3.
> To calculate average annual electricity sales per household, EPA divided the total quantity of residential
sales (in MWh) for 2011 in each NERC region by the number of households in that region. The Agency
obtained both the quantity of residential sales and the number of households for all NERC regions from
the 2011 EIA-861 database. EPA assumed that the average quantity of electricity sales per household by
NERC region would remain the same in 2020 as in 2011.
> To assess the potential annual cost impact per household, EPA multiplied the estimated average price
impact by the average quantity of electricity sales per household in 2011 by NERC region.
Key Findings
Table 4-8 reports the results of this analysis by NERC region under the assumption that all facilities with cooling
water system impoundments qualify as baseline CCRS. As shown in Table 4-8, under the existing unit provision
of the final rule, the average annual cost per residential household varies by NERC region, ranging from $0.01 in
WECC to $2.82 in HICC. EPA reached the same finding for Proposal Option 4. Under Proposal Option 2, the
average annual cost per residential household also varies across NERC regions, ranging from $0.01 in WECC to
$31.72 in SERC. EPA estimated that on average, for a typical U.S. household, the final rule will result in a cost of
$1.03 per household. EPA estimates that this cost would be $1.03 per household under Proposal Option 4 and
$17.23 per household under Proposal Option 2.
Table 4-9 reports the results of this analysis by NERC region under the assumption that no facilities with cooling
water system impoundments qualify as baseline CCRS. Under the existing unit provision of the final rule and
Proposal Option 4, the average annual cost per residential household ranges from $0.01 in WECC to $2.82 in
HICC. Under Proposal Option 2, the average annual cost per residential household ranges from $0.01 in WECC
to $39.90 in TRE. EPA estimated that on average, for atypical U.S. household, the final rule will result in a cost
83 NERC is responsible for the overall reliability, planning, and coordination of the power grids; it is organized into regional councils
that are responsible for the overall coordination of bulk power policies that affect their regions' reliability and quality of service (see
Chapter 2).
4-18
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
of $1.21 per household, with Proposal Option 4 and Proposal Option 2 resulting in $1.22 per household and
$19.08 per household, respectively.
Table 4-8: Average Annual Cost per Household in 2020 by NERC Region, Final Rule-Existing Units and
Other Options Considered - Assuming All Facilities with Cooling Water System Impoundments Qualify as
Baseline CCRSa bc
NERC
Region
Total Annual
Compliance Cost
(at 2020; Million;
$2011)
Total Electricity
Sales (at 2020;
MWh)
Compliance
Cost per Unit
of Sales
($2011/MWh)
Residential
Electricity Sales (at
2020; MWh)
Number of
Households
(at 2020)
Residential
Sales per
Residential
Consumer
(MWh)
Compliance
Cost per
Household
($2011)
Proposal Oi
ption 4
ASCC
$0
6,318,369
$0.00
2,133,836
273,608
7.80
$0.00
FRCC
$32,085,596
227,725,769
$0.14
109,212,622
8,068,660
13.54
$1.91
IIICC
$4,010,571
9,961,653
$0.40
2,928,743
417,531
7.01
$2 82
MRO
$20,283,069
212,722,061
$0.10
58,858,262
5,649,545
10.42
$0.99
NPCC
$21,760,125
269,363,615
$0.08
101,954,820
13,493,947
7.56
$0.61
RFC
$93,043,545
875,942,368
$0.11
341,731,920
33,100,790
10.32
$1.10
skrc
$142,575,030
1.056.641.854
$0 13
375.962.516
25,942,358
14.49
$1.96
SPP
$19,596,770
206.449.802
$0 09
75.232.915
5,499,815
13.68
$1.30
i ri;
$25,777,009
332.132.690
$0.08
73.044.353
4,915,790
14.86
$1.15
wkcc
$788,032
705.550.339
$0.00
240.006.906
26,646,858
9.01
$0.01
U.S.
$359,919,748
3,906,950,928
$0.09
1,381,066,893
124,008,902
11.14
$1.03
Final Rule - Existing Units
ASCC
$0
6,318,369
$0.00
2,133,836
273,608
7.80
$0.00
FRCC
$32,085,596
227,725,769
$0.14
109,212,622
8.068.660
13.54
$1.91
IIICC
$4,010,571
9,961,653
$0.40
2,928,743
417.531
7.01
$2.82
MRO
$20,852,642
212,722,061
$0.10
58,858,262
5.649.545
10.42
$1.02
NPCC
$22,079,437
269,363,615
$0.08
101,954,820
13.493.947
7.56
$0.62
Rl'C
$93,308,548
875.942.368
$0 1 1
341.731.920
33.100.790
10.32
$1.10
SKRC
$142,575,030
1.056.641.854
$0 13
375.962.516
25,942,358
14.49
$1.96
SPP
$19,596,770
206.449.802
$0 09
75.232.915
5,499,815
13.68
$1.30
i ri;
$25,777,009
332.132.690
$0.08
73.044.353
4,915,790
14.86
$1.15
wire
$788,032
705.550.339
$0.00
240.006.906
26,646,858
9.01
$0.01
U.S.
$361,073,637
3,906,950,928
$0.09
1,381,066,893
124,008,902
11.14
$1.03
Proposal 0|
ption 2
ASCC
$0
6.318.369
$0.00
2.133.836
273.608
7.80
$0.00
FRCC
$389,416,274
227.725.769
$1.71
109.212.622
8.068.660
13.54
$23.15
IIICC
$34,953,404
9.961.653
$3 51
2.928.743
417.531
7.01
$24.61
MRO
$369,493,353
212.722.061

58.858.262
5.649.545
10.42
$18.10
NPCC
$339,326,908
269.363.615

101.954.820
13.493.947
7.56
$9.52
RFC
$1,751,066,574
875.942.368
$2 00
341.731.920
33,100,790
10.32
$20.64
SKRC
$2,313,029,308
1.056.641.854
$2 19
375.962.516
25,942,358
14.49
$31.72
SPP
$161,631,013
206.449.802
$0 78
75.232.915
5,499,815
13.68
$10.71
TRK
$683,768,032
332.132.690
$2 06
73.044.353
4,915,790
14.86
$30.59
WECC
$660,327
705,550,339
$0.00
240,006,906
26,646,858
9.01
$0.01
U.S.
$6,043,345,192
3,906,950,928
$1.55
1,381,066,893
124,008,902
11.14
$17.23
a. ASCC - Alaska Systems Coordinating Council; FRCC - Florida Reliability Coordinating Council; F1ICC - Flawaii Coordinating Council; MRO -
Midwest Reliability Organization; NPCC - Northeast Power Coordinating Council; RFC - ReliabilityFirst Corporation; SERC - Southeastern Electric
Reliability Council; SPP - Southwest Power Pool; TRE - Texas Reliability Entity, and WECC - Western Energy Coordinating Council.
b. The rate impact analysis assumes full pass-through of all compliance costs to electricity consumers.
c. No explicitly analyzed facilities are located in the ASCC region. For more information on explicitly and implicitly analyzed facilities see Appendix H.
Source: U.S. EPA analysis for this report
May 2014
4-19
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
Table 4-9: Average Annual Cost per Household in 2020 by NERC Region, Final Rule-Existing Units and
Other Options Considered - Assuming No Facilities with Cooling Water System Impoundments Qualify as
Baseline CCRSa bc
NERC
Region
Total Annual
Compliance Cost
(at 2020; Million;
$2011)
Total Electricity
Sales (at 2020;
MWh)
Compliance
Cost per Unit
of Sales
($2011/MWh)
Residential
Electricity Sales (at
2020; MWh)
Number of
Households
(at 2020)
Residential
Sales per
Residential
Consumer
(MWh)
Compliance
Cost per
Household
($2011)
Proposal Oi
ption 4
ASCC
$0
6,318,369
$0.00
2,133,836
273,608
7.80
$0.00
l'RCC
$32,625,282
227,725,769
$0 14
109,212,622
8,068,660
13.54
$1.94
IIICC
$4,010,571
9,961,653
$0 40
2,928,743
417,531
7.01
$2.82
MRO
$26,888,489
212,722,061
$0 13
58,858,262
5,649,545
10.42
$1.32
NPCC
$21,760,125
269,363,615
$0 08
101,954,820
13,493,947
7.56
$0.61
Rl'C
$111,032,827
875,942,368
$0 13
341.731.920
33.100.790
10.32
$1 ^1
skrc
$147,171,619
1,056,641,854
$0 14
375.962.516
25.942.358
14.49
$2.02
SPP
$36,909,900
206,449,802
$0 18
75.232.915
5.499.815
13.68
$2.45
i ri ;
$44,382,046
332,132,690
$0 13
73.044.353
4.915.790
14.86
$1.99
wkcc
$774,608
705,550,339
$0.00
240.006.906
26.646.858
9.01
$0.01
U.S.
$425,555,466
3,906,950,928
$0.11
1,381,066,893
124,008,902
11.14
$1.21
Final Rule - Existing Units
ASCC
$0
6,318,369
$0.00
2,133,836
273,608
7.80
$0.00
l'RCC
$32,625,282
227,725,769
$0 14
109,212,622
8,068,660
13.54
$1.94
IIICC
$4,010,571
9,961,653
$0 40
2,928,743
417,531
7.01
$2.82
MRO
$27,459,636
212,722,061
$0 13
58,858,262
5,649,545
10.42
$1.34
NPCC
$22,079,437
269,363,615
$0 08
101,954,820
13,493,947
7.56
$0.62
Rl'C
$111,286,775
875,942,368
$0 13
341,731,920
33,100,790
10.32
$1 ^1
SKRC
$147,481,532
1,056,641,854
$0 14
375,962,516
25,942,358
14.49
$2.02
SPP
$36,909,900
206,449,802
$0 18
75,232,915
5,499,815
13.68
$2.45
i ri ;
$44,382,046
332,132,690
$0 13
73,044,353
4,915,790
14.86
$1.99
wire
$774,608
705,550,339
$0.00
240,006,906
26,646,858
9.01
$0.01
U.S.
$427,009,786
3,906,950,928
$0.11
1,381,066,893
124,008,902
11.14
$1.22
Proposal 0|
ption 2
ASCC
$0
6,318,369
$0.00
2,133,836
273.608
7.80
$0.00
l'RCC
$404,032,918
227,725,769

109,212,622
8.068.660
13.54
$24.01
IIICC
$34,953,404
9,961,653
$3 51
2,928,743
417.531
7.01
$24.61
MRO
$412,511,290
212,722,061
$1 94
58,858,262
5.649.545
10.42
$20.20
NPCC
$339,326,908
269,363,615

101,954,820
13.493.947
7.56
$9.52
Rl'C
$1,823,672,930
875,942,368
$2 08
341,731,920
33,100,790
10.32
$21.49
SKRC
$2,370,905,008
1,056,641,854
$2 24
375,962,516
25,942,358
14.49
$32.52
SPP
$416,336,889
206,449,802
$2 02
75,232,915
5,499,815
13.68
$27.59
IRK
$891,860,951
332,132,690
$2 69
73,044,353
4,915,790
14.86
$39.90
WECC
$646,903
705,550,339
$0.00
240,006,906
26,646,858
9.01
$0.01
U.S.
$6,694,247,200
3,906,950,928
$1.71
1,381,066,893
124,008,902
11.14
$19.08
a. ASCC - Alaska Systems Coordinating Council; FRCC - Florida Reliability Coordinating Council; F1ICC - Flawaii Coordinating Council; MRO -
Midwest Reliability Organization; NPCC - Northeast Power Coordinating Council; RFC - ReliabilityFirst Corporation; SERC - Southeastern Electric
Reliability Council; SPP - Southwest Power Pool; TRE - Texas Reliability Entity, and WECC - Western Energy Coordinating Council.
b. The rate impact analysis assumes full pass-through of all compliance costs to electricity consumers.
c. No explicitly analyzed facilities are located in the ASCC region. For more information on explicitly and implicitly analyzed facilities see Appendix H.
Source: U.S. EPA analysis for this report
Uncertainties and Limitations
The analysis of household electricity cost impact is subject to several uncertainties and limitations, including:
> Within a rate regulation framework that guarantees full cost recovery, assumed in this analysis, fixed and
variable costs would be allocated among customer classes based on the contribution of each class to
consumption during specific electricity production periods. As a result, the allocation of costs to the
residential class could be higher or lower than those estimated in this analysis based on the assumption
that costs would be passed on to consumers in the form of a flat-rate price increase per unit of power, to
4-20
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
be distributed in proportion to the current electricity consumption profile. In addition, this analysis
ignores heterogeneous impacts at the household level, which may be more important for utilities that use
block-rate pricing or other price-discrimination rate structures, in which unit consumption prices vary by
consumption level. The analysis also does not account for rate structures - e.g., lifeline rates - which
could moderate the impact of otherwise increased rates on lower income households.
> As noted above, the assumptions regarding pass-through of compliance costs to electricity prices are
relatively simple. To the extent that some facilities subject to the final rule are not able to fully pass
compliance costs to consumers through higher electricity prices, this analysis overstates the potential
impact of the final rule and other options considered on households.
4.2.5 Analysis of Short-Term Reduction in Capacity Availability Due to Installation Downtime
EPA analyzed the reduction in availability of generating capacity due to technology-installation downtime, as
well as the impact of that capacity reduction on the North American bulk power system under the existing unit
provision of the final rule and other options considered.84 The downtime requirements at the facility level and in
total vary by analyzed option as follows:
> For the existing unit provision of the final rule, 187 Electric Generators are estimated to incur net
downtime, ranging from 0.3 to nine weeks
> For the Proposal Option 4, 183 Electric Generators are estimated to incur net downtime, ranging from 0.3
to nine weeks
> For the Proposal Option 2, 286 Electric Generators are estimated to incur net downtime of between 0.3
and nine weeks for IM technology installation and either four weeks (non-nuclear facilities) or 24 weeks
(nuclear facilities) for installation of cooling towers.85'86
Analysis Approach and Data Inputs
EPA estimated the quantity of generating capacity that would be temporarily out of service by NERC region over
the years in which facilities would be expected to install technology for complying with the final rule and other
options considered. This analysis aims to provide insight into whether the quantity of capacity that might be out of
service at a given time would be substantial in relation to total available generating capacity by NERC region,
and, as a result, potentially pose a short-term issue in electricity supply reliability.
EPA distributed the occurrence of installation downtime by facility, and by NERC region, over the periods in
which facilities are expected to install compliance technology under the final rule and other options considered.
Specifically, EPA distributed downtime occurrence in such way that the total capacity out of service, by NERC
region, would be as uniform as possible over the periods in which facilities would be expected to install
compliance technology and incur downtime.
In implementing this procedure, EPA recognized that the amount of capacity at a facility that would need to be
removed from service at a given time for completion of technology installation could not be "subdivided" - i.e.,
all of the generating capacity associated with a given intake structure would need to be taken out of service at the
84 EPA assumed that installation of cooling towers at new units under the new unit provision of the final rule will require no additional
construction period or downtime.
85 These are counts of surveyed non-retired DQ and STQ facilities (see Appendix H).
80 Assuming that no facilities with a cooling water system impoundment qualify as baseline CCRS, 216, 212, and 316 Electric
Generators would incur net downtime under the final rule, Proposal Option 4, and Proposal Option 2, respectively. This downtime
would also range from 0.3 to nine weeks for IM technology installation and be either four weeks (non-nuclear facilities) or 24 weeks
(nuclear facilities) for cooling-tower installation. The Agency found that these additional weeks of downtime resulted in only minimal
differences in short-term reliability effects.
May 2014
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Chapter 4: Economic Impact Analyses - Electric Generators
same time to complete compliance technology installation for that intake structure. However, the implementation
of this procedure involved a key simplifying assumption that will tend to overstate the capacity availability impact
during the several year period of technology installation. Compliance technologies and downtime duration for the
installation of these technologies are assigned to individual intake structures. As a result, only generating capacity
associated with a specific intake structure would be expected to be out of service as a result of technology
installation at a given time. For this analysis, EPA was unable to identify the specific steam-generating units and
quantity of generating capacity associated with the individual intake structures. Thus, this analysis assumes that
all steam-generating capacity at a given facility will be out of service at the same time. Therefore, to the extent
that some regulated facilities may operate several intake structures with different generating units assigned to the
different intake structures, this analysis may overstate the impact of downtime on short-term capacity availability.
As discussed in Chapter 3, EPA assumed that facilities assigned non-cooling tower technologies will install
compliance technology during a 5 -year time period of 2018 through 2022. The Agency assumed that non-nuclear
and nuclear facilities assigned cooling towers will install compliance technology during 5-year windows of 2021
through 2025, and 2026 through 2030, respectively. Further, EPA assumed that downtime will occur in the year
when a facility would complete technology installation. The Agency also assumed that facilities will incur
downtime during the spring or fall seasons so as not to coincide with either the winter or summer higher demand
periods. Consequently, facilities incurring installation downtime would have 10 time periods in which the
downtime might occur (i.e., two time periods - spring and fall - for each of the possible compliance years).
EPA distributed the occurrence of downtime capacity as evenly as possible over these potential technology- and
facility type-specific downtime periods, recognizing the limitation described above that all of a facility's reported
steam-generating capacity would need to be taken out of service at once !'1 The resulting assignments of facility
capacity to individual downtime periods were then summed over the facilities, by NERC region, to yield a
potential reduction in capacity availability by downtime period. EPA intentionally did not assign these capacity
estimates to particular years and/or seasons; the Agency assumed that each NERC region would work with
facility owners to coordinate the occurrence of downtime within a given technology installation/compliance
window in such way as to minimize the potential for adverse reductions in supply reliability due to the occurrence
of installation downtime.
This distribution of downtime occurrence illustrates how the incremental installation downtime and capacity
availability effects might occur during the available technology installation/compliance window - based on this
specific approach for distributing the occurrence of downtime. Table 4-10 and Table 4-11 present a summary of
the resulting downtime capacity values by downtime period, for each NERC region, for the final rule and other
options considered. For Proposal Option 2, downtime capacity for facilities assigned IM technologies and non-
nuclear facilities installing cooling towers is presented separately from that for nuclear facilities assigned cooling
towers, because the windows for installing compliance technology would be different. Specifically, the former set
of facilities would incur downtime during an 8-year window of 2018 through 2025 (16 downtime periods), while
the latter set of facilities would incur downtime during a 5-year window of 2026 through 2030 (10 downtime
periods).
To evaluate the reliability impact of technology-installation downtime, EPA assessed whether the amount of
generating capacity that would be unavailable could prevent a given NERC region from meeting Reliability
Standards developed and enforced by NERC - i.e., whether a given NERC region will be able to meet its
electricity demand and its reserve margin requirement.88 For eight of 10 NERC regions - TRE, FRCC, MRO,
87 This methodology of capacity assignment to individual downtime periods does not account for the National Pollutant Discharge
Elimination System (NPDES) permit renewal. Consequently, for some facilities expected to incur technology installation downtime, it
resulted in an implied compliance schedule slightly different from that assumed for the other cost and economic impact analyses
discussed in this report.
88 For more information, see http://www.nerc.com/files/StandardsBackground.pdf and http://www.nerc.com/page.php?cid=2%7C97.
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Chapter 4: Economic Impact Analyses - Electric Generators
NPCC, RFC, SERC, SPP, and WECC - EPA used information on projected generating capacity, electricity
demand, and reserve margins from NERC's 2010 Long-Term Reliability Assessment (LTRA) report.89 Because
electric supply reliability in Alaska and Hawaii is not under NERC's oversight, the 2010 LTRA report does not
include information on these States. Therefore, to assess reliability impact for the two NERC regions represented
by these two states - ASCC and HICC, respectively - EPA performed an additional analysis using different data..
The 2010 LTRA report defines reserve margin as the amount of unused available capacity at peak load in an
electric power system, as a percentage of total electricity demand (NERC, 2010). To make this reliability
assessment, EPA compared, by NERC region, the Reference Reserve Margin set by NERC with projected actual
reserve margin adjusted for capacity loss as the result of 316(b) technology installation, referred to herein as
Compliance Adjusted Potential Reserve Margin90
EPA calculated Compliance Adjusted Potential Reserve Margin as follows:
CAPRM = - 3I6bNDC - N'%id) <4_1)
Where:
CAPRM = Compliance Adjusted Potential Reserve Margin, or baseline NERC region reserve margin
{Reference Reserve Margin) adjusted for the reduction in available capacity due to installation
downtime
.1 PC = Adjusted Potential Capacity (MW), an available capacity value published by NERC and defined
as the sum of net capacity resources, existing uncertain resources less all derates,91 total
proposed resources reduced by a confidence factor and net non-firm transactions. This capacity
value includes future capacity additions and adjusts for the possibility that some of this future
capacity may not be available when estimated to be constructed.
316bNDC = 316(b) Net Downtime Capacity (MW), or estimated capacity reductions due to 316(b)
installation downtime, by NERC region and year; calculated as described above.
NID = Net Internal Demand (MW), a NERC-published region-level electricity demand value, defined
as total internal demand reduced by dispatchable controllable (capacity) demand response.
The result of this calculation is capacity that would be available at peak demand after adjusting available capacity
for capacity reductions due to installation downtime as a percentage of projected electricity demand.
In performing this calculation, EPA used NERC-reported data for Adjusted Potential Capacity and Net Internal
Demand for the winter season. The 2010 LTRA report contains analysis of winter and summer bulk power system
reliability, but does not report information for the shoulder season demand periods - fall and spring - which are
the periods when EPA expects that installation downtime would generally occur. EPA used information for the
winter season because, for the United States, winter is generally a lower demand season than summer. Therefore,
winter would provide a better basis for analyzing the impact of downtime-based capacity reductions that would
actually be expected to occur during the lower demand shoulder season operating periods. To the extent that
While the 2011 LTRA report was available at the time of this analysis, EPA used the 2010 LTRA report because the NERC regions
covered in that report align better with NERC regions in the 2011 EIA database.
EPA obtained all baseline reserve margin and other information from NERC's 2010 Long-Term Reliability Assessment (LTRA)
report (NERC, 2010), available online at: http://www.nerc.com/pa/RAPA/ra/Reliabilitv%20Assessments%20DL/2010 LTRA v2-
.pdf.
Derated capacity accounts for the amount of capacity that is expected to be unavailable at seasonal peak due to expected operating
limitations, or loss in production capability over time due to aging of the generating unit. For example, a generating unit may not be
able to operate at regular full output during periods of peak summer demand due to thermal discharge limits. The forecast of capacity
availability at peak demand periods would account for these reductions.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
technology installation occurs during the shoulder months of spring and fall, when electricity demand is on
average below that during winter, the reliability impact estimated using winter demand is likely to be over-stated.
In addition, EPA used NERC-reported data for the 2019/2020 winter season, which is the last year covered by the
2010 LTRA report. EPA determined that values reported for 2019/2020, which lies approximately in the middle
of the 5 -year window of IM technology installation (2018 through 2022) and just before the beginning of the
cooling tower-installation period (2022-2030), provide a reasonable basis for analyzing the reliability impact of
downtime.
To determine whether the reduction in available capacity due to installation downtime could pose a bulk power
reliability concern, EPA compared Compliance Adjusted Potential Reserve Margin with Reference Reserve
Margin, as reported by NERC. Reference Reserve Margin (percent MW) represents either the target reserve
margin provided by the region/subregion or the target reserve margin assigned by NERC based on capacity mix
(i.e., thermal vs. hydro).
As stated above, EPA performed these calculations for eight NERC regions for which the 2010 LTRA report
provides information - TRE, FRCC, MRO, NPCC, RFC, SERC, SPP, and WECC - and conducted a different
analysis, discussed below, for the remaining two NERC regions - ASCC and HICC. Table 4-10 reports results of
the analysis conducted for the eight NERC regions from the 2010 LTRA report:
> NERC Reference Reserve Margin (percentage) level
> Net Internal Demand (MW) for the 2019/2020 winter season
r Adjusted Potential Capacity (MW) for the 2019/2020 winter season
> EPA's estimate of Downtime Capacity (MW) for each of the analyzed downtime periods
> Compliance Adjusted Potential Reserve Margin (percentage), as calculated above, by downtime period,
based on the 2019/2020 winter Net Internal Demand and Adjusted Potential Capacity.
In any downtime period, the higher the percentage of total capacity that potentially would be out of service due to
regulatory compliance, the greater the potential for electricity supply reliability effects.
It is important to note that this analysis of downtime effects does not account for the duration of downtime. As
noted above, the analysis assumes that all of the downtime across facilities in a region occurs at the same time
within a given seasonal analysis period. This assumption may lead to an overstatement of the potential impact of
downtime on electricity supply reliability to the extent that individual facilities would require downtime that is
shorter than the seasonal analysis period and individual facilities' downtime could be scheduled to avoid overlap
during a given seasonal analysis period. As discussed in Chapter 3, the final rule does not specify a rigid timeline
for compliance with regulatory requirements. Instead, the final rule gives Permit Directors the authority to
establish specific compliance requirements and compliance schedules for individual facilities. Under the final
rule, Permit Directors are given the flexibility to consider issues concerning maintenance of adequate energy
reliability and necessary grid reserve capacity during any facility outage. In doing so, Permit Directors may
consult independent system operators and state public utility regulatory agencies. Ultimately, all facilities will be
required to follow their schedule as determined by the Permit Director.
As discussed above, the 2010 LTRA report does not include information on Alaska and Hawaii. Therefore, to
assess reliability impact for these regions, EPA performed an additional analysis to examine downtime capacity as
a percentage of total regional capacity (Table 4-11).
For IM technology, which is the minimum technology standard required nationally under the final rule and other
options considered, the required duration of net downtime is between 0.3 and nine weeks. Under the final rule,
only three analyzed facilities are estimated to incur nine weeks of downtime, while net downtime averages 0.3
weeks for the majority of facilities. Under other options considered - Proposal Option 4 and Proposal Option 2 -
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Chapter 4: Economic Impact Analyses - Electric Generators
only two and one facilities installing IM technologies would incur nine weeks of downtime, respectively; similar
to the final rule, for majority of facilities installing IM technologies under these options net downtime would
average 0.3 weeks. For cooling towers required under Proposal Option 2, most non-nuclear facilities, which are
the vast majority of Electric Generators, are assigned 4 weeks of downtime, while some non-nuclear facilities are
assigned no net downtime. Only nine nuclear facilities are assigned 24 weeks of downtime, while the other
nuclear facilities are assigned no net downtime. Thus, incremental downtime is quite low for nearly all facilities
under the final rule and Proposal Option 4 and for facilities assigned IM technologies under Proposal Option 2.
Key Findings
For eight out of 10 NERC regions (i.e., all NERC regions except for ASCC and HICC), capacity loss due to
compliance-technology installation is not expected to prevent any of these regions from meeting either the
expected electricity demand or required reserve capacity margin under either the final rule or other options
considered in development of the final rule. Table 4-10 reports, for each NERC region, the Reference Margin, the
baseline Demand and Capacity values derived from the LTRA report, and the estimated Downtime Capacity and
Compliance Adjusted Potential Capacity Margin. The analysis results are reported for each of the 10 periods in
which downtime might occur under the final rule and Proposal Option 4 (5-year IM technology-installation
window of 2018 through 2022) and Proposal Option 2 (5-year cooling tower-installation window of 2026 through
2030). For Proposal Option 2, analysis results are reported for 16 periods (8-year technology-installation window
of 2018-2025 for IM technology (2018-2022) and cooling towers at non-nuclear facilities (2021-2025). As
presented in Table 4-10, Compliance Adjusted Potential Capacity Margin remains greater than the target
Reference Margin for the final rule and other options considered across all eight NERC regions and potential
downtime periods. Specifically, under the final rule and other options considered, the Compliance Adjusted
Potential Capacity Margin is more than twice the target Reference Margin in all NERC regions except FRCC. In
the FRCC region, Compliance Adjusted Potential Capacity Margin is less than two times the NERC region's
target Reference Margin but remains substantially greater than the Reference Margin in all of the cases analyzed:
the lowest Compliance Adjusted Potential Capacity Margin observed in any of the installation periods is 28
percent, compared to the target Reference Margin of 15 percent.
To assess reliability impact for ASCC and HICC, EPA performed an additional analysis where the Agency looked
at downtime capacity as a percentage of total regional capacity in each of these two regions (Table 4-11). Only
one Electric Generator is located in ASCC (a non-nuclear facility with relatively low capacity of 28 MW). This
facility is expected to install IM technology under all three analyzed options, requiring 0.3 weeks of net
downtime. Given the small facility size and relatively short net downtime duration, EPA does not expect large
reliability effects in the ASCC region as a result of the rule.
The HICC region includes three Electric Generators, all of which are non-nuclear. These facilities are relatively
large with 610 MW, 372 MW, and 104 MW of steam capacity. EPA estimates that under the final rule, only one
facility (610 MW) will incur additional downtime (0.3 weeks); this facility represents approximately 22 percent of
the region's total electric generating capacity. These findings are also true for Proposal Option 4. EPA estimates
that under Proposal Option 2, all three facilities would incur net downtime of four weeks for cooling tower
installation; these facilities represent 22 percent, 13 percent, and 4 percent of the total regional capacity. Given the
relatively large size of these facilities, it is quite likely they operate multiple intake structures, in which case they
would not need to be completely out of service to complete technology installation.
In conclusion, based on the findings for each of the eight NERC regions in which EPA performed an explicit
analysis of impact of technology installation on Reference Margin, EPA concludes that the short-term loss of
capacity as the result of compliance with the final rule and other options considered will not cause material
reliability effects. In addition, for the ASCC and HICC regions, where EPA was not able to analyze impact on
Reference Margin, EPA also concludes that the final rule or other options considered will not have a material
adverse impact on electric supply reliability.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
Table 4-10: Summary of Downtime Impact Analysis by NERC Region and Downtime Period, Final Rule-Existing Units and Other Options
Considered
NERC
Region3
Ref
Marginb
Demand0
Cap"
Measuree'f'g
Downtime Periods'1
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16
Proposal Option 4
EM Technology
FRCC
15.0%
49.082
66.175
Downtime Capacity (MW)
3.333
1.722
1.159
1.042
962
1.004
0
0
0
0

Compl Adj Potential Cap Margin
28%
31%
32%
33%
33%
33%
35%
35%
35%
35%
MRO
15.0%
38.423
59.120
Downtime Capacity (MW)
1.390
1.391
1.399
1.396
1.401
1.398
1.402
1.352
1.391
228
Compl Adj Potential Cap Margin
50%
50%
50%
50%
50%
50%
50%
50%
50%
53%
NPCC
15.0%
48.959
83.830
Downtime Capacity (MW)
1.037
821
768
690
589
592
476
447
0
0
Compl Adj Potential Cap Margin
69%
70%
70%
70%
70%
70%
70%
70%
71%
71%
RFC
15.0%
157.200
243.589
Downtime Capacity (MW)
4.805
4.807
4.823
4.784
4.824
4.829
4.781
4.782
4.823
641
Compl Adj Potential Cap Margin
52%
52%
52%
52%
52%
52%
52%
52%
52%
55%
SERC
15.0%
201.577
291.657
Downtime Capacity (MW)
6.884
6.882
6.878
6.862
6.883
6.849
6.818
6.875
6.874
836
Compl Adj Potential Cap Margin
41%
41%
41%
41%
41%
41%
41%
41%
41%
44%
SPP
13.6%
37.294
69.820
Downtime Capacity (MW)
1.716
1.640
916
882
749
649
390
0
0
0
Compl Adj Potential Cap Margin
83%
83%
85%
85%
85%
85%
86%
87%
87%
87%
TRE
12.5%
49.307
98.049
Downtime Capacity (MW)
2.380
1.315
1.187
1.175
1.189
1.192
1.115
970
726
0
Compl Adj Potential Cap Margin
94%
96%
96%
96%
96%
96%
97%
97%
97%
99%
WECC
14.1%
117.072
185.346
Downtime Capacity (MW)
1.129
817
202
0
0
0
0
0
0
0
Compl Adj Potential Cap Margin
57%
58%
58%
58%
58%
58%
58%
58%
58%
58%
Final Rule
EM Technology
FRCC
15.0%
49.082
66.175
Downtime Capacity (MW)
3.333
1.722
1.159
1.042
962
1.004
0
0
0
0

Compl Adj Potential Cap Margin
28%
31%
32%
33%
33%
33%
35%
35%
35%
35%
MRO
15.0%
38.423
59.120
Downtime Capacity (MW)
1.390
1.403
1.399
1.396
1.401
1.406
1.405
1.375
1.385
228
Compl Adj Potential Cap Margin
50%
50%
50%
50%
50%
50%
50%
50%
50%
53%
NPCC
15.0%
48.959
83.830
Downtime Capacity (MW)
1.037
821
768
690
589
626
629
637
0
0
Compl Adj Potential Cap Margin
69%
70%
70%
70%
70%
70%
70%
70%
71%
71%
RFC
15.0%
157.200
243.589
Downtime Capacity (MW)
4.829
4.830
4.823
4.833
4.824
4.833
4.835
4.820
4.823
510
Compl Adj Potential Cap Margin
52%
52%
52%
52%
52%
52%
52%
52%
52%
55%
SERC
15.0%
201.577
291.657
Downtime Capacity (MW)
6.884
6.882
6.878
6.862
6.883
6.849
6.818
6.875
6.874
836
Compl Adj Potential Cap Margin
41%
41%
41%
41%
41%
41%
41%
41%
41%
44%
SPP
13.6%
37.294
69.820
Downtime Capacity (MW)
1.716
1.640
916
882
749
649
390
0
0
0
Compl Adj Potential Cap Margin
83%
83%
85%
85%
85%
85%
86%
87%
87%
87%
TRE
12.5%
49.307
98.049
Downtime Capacity (MW)
2.380
1.315
1.187
1.175
1.189
1.192
1.115
970
726
0
Compl Adj Potential Cap Margin
94%
96%
96%
96%
96%
96%
97%
97%
97%
99%
WECC
14.1%
117.072
185.346
Downtime Capacity (MW)
1.129
817
202
0
0
0
0
0
0
0
Compl Adj Potential Cap Margin
57%
58%
58%
58%
58%
58%
58%
58%
58%
58%
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
Table 4-10: Summary of Downtime Impact Analysis by NERC Region and Downtime Period, Final Rule-Existing Units and Other Options
Considered
NERC
Region3
Ref
Marginb
Demand0
Cap"
Measuree'f'g
Downtime Periods'1
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16
Proposal Option 2
EM Technology and Coolin
j Towers - Non-Nuclear Facilities
FRCC
15.0%
49.082
66.175
Downtime Capacity (MW)
0
0
0
0
0
0
3.333
2.534
1.823
1.880
1.909
1.913
1.159
1.112
1.042
962
Compl Adj Potential Cap Margin
35%
35%
35%
35%
35%
35%
28%
30%
31%
31%
31%
31%
32%
33%
33%
33%
MRO
15.0%
38.423
59.120
Downtime Capacity (MW)
117
115
99
67
63
40
1.804
1.777
1.786
1.771
1.783
1.790
1.783
1.747
1.695
406
Compl Adj Potential Cap Margin
54%
54%
54%
54%
54%
54%
49%
49%
49%
49%
49%
49%
49%
49%
49%
53%
NPCC
15.0%
48.959
83.830
Downtime Capacity (MW)
376
311
103
25
0
0
2.895
1.778
1.428
1.187
1.258
1.254
1.227
740
0
0
Compl Adj Potential Cap Margin
70%
71%
71%
71%
71%
71%
65%
68%
68%
69%
69%
69%
69%
70%
71%
71%
RFC
15.0%
157.200
243.589
Downtime Capacity (MW)
1.217
146
158
0
0
0
7.055
7.071
7.021
7.048
7.074
7.056
7.082
7.090
7.017
946
Compl Adj Potential Cap Margin
54%
55%
55%
55%
55%
55%
50%
50%
50%
50%
50%
50%
50%
50%
50%
54%
SERC
15.0%
201.577
291.657
Downtime Capacity (MW)
654
75
13
0
0
0
9.506
9.519
9.525
9.506
9.501
9.530
9.496
9.492
9.500
1.094
Compl Adj Potential Cap Margin
44%
45%
45%
45%
45%
45%
40%
40%
40%
40%
40%
40%
40%
40%
40%
44%
SPP
13.6%
37.294
69.820
Downtime Capacity (MW)
185
0
0
0
0
0
1.716
1.640
985
882
999
937
936
993
0
0
Compl Adj Potential Cap Margin
87%
87%
87%
87%
87%
87%
83%
83%
85%
85%
85%
85%
85%
85%
87%
87%
TRE
12.5%
49.307
98.049
Downtime Capacity (MW)
0
0
0
0
0
0
2.380
2.357
2.420
2.458
2.397
2.362
2.404
2.470
2.328
900
Compl Adj Potential Cap Margin
99%
99%
99%
99%
99%
99%
94%
94%
94%
94%
94%
94%
94%
94%
94%
97%
WECC
14.1%
117.072
185.346
Downtime Capacity (MW)
0
0
0
0
0
0
1.129
817
202
0
0
0
0
0
0
0
Compl Adj Potential Cap Margin
58%
58%
58%
58%
58%
58%
57%
58%
58%
58%
58%
58%
58%
58%
58%
58%
Cooling Towers -Nuclear Facilities
FRCC
15.0%
49.082
66.175
Downtime Capacity (MW)
0
0
0
0
0
0
0
0
0
0

Compl Adj Potential Cap Margin
35%
35%
35%
35%
35%
35%
35%
35%
35%
35%
MRO
15.0%
38.423
59.120
Downtime Capacity (MW)
631
0
0
0
0
0
0
0
0
0
Compl Adj Potential Cap Margin
52%
54%
54%
54%
54%
54%
54%
54%
54%
54%
NPCC
15.0%
48.959
83.830
Downtime Capacity (MW)
563
0
0
0
0
0
0
0
0
0
Compl Adj Potential Cap Margin
70%
71%
71%
71%
71%
71%
71%
71%
71%
71%
RFC
15.0%
157.200
243.589
Downtime Capacity (MW)
2.019
2.019
0
0
0
0
0
0
0
0
Compl Adj Potential Cap Margin
54%
54%
55%
55%
55%
55%
55%
55%
55%
55%
SERC
15.0%
201.577
291.657
Downtime Capacity (MW)
3.494
2.003
1.845
1.200
0
0
0
0
0
0
Compl Adj Potential Cap Margin
43%
44%
44%
44%
45%
45%
45%
45%
45%
45%
SPP
13.6%
37.294
69.820
Downtime Capacity (MW)
0
0
0
0
0
0
0
0
0
0
Compl Adj Potential Cap Margin
87%
87%
87%
87%
87%
87%
87%
87%
87%
87%
TRE
12.5%
49.307
98.049
Downtime Capacity (MW)
0
0
0
0
0
0
0
0
0
0
Compl Adj Potential Cap Margin
99%
99%
99%
99%
99%
99%
99%
99%
99%
99%
WECC
14.1%
117.072
185.346
Downtime Capacity (MW)
0
0
0
0
0
0
0
0
0
0
Compl Adj Potential Cap Margin
58%
58%
58%
58%
58%
58%
58%
58%
58%
58%
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
Table 4-10: Summary of Downtime Impact Analysis by NERC Region and Downtime Period, Final Rule-Existing Units and Other Options
Considered
NERC
Region3
Ref
Margin'1
Demand'
Cap"
Measure'
a
Downtime Periods
1
8
10 11 12 13
14 15
16
a. ASCC - Alaska Systems Coordinating Council; FRCC - Florida Reliability Coordinating Council; HICC - Hawaii Coordinating Council; MRO - Midwest Reliability Organization; NPCC - Northeast
Power Coordinating Council; RFC - ReliabilityFirst Corporation; SERC - Southeastern Electric Reliability Council; SPP - Southwest Power Pool; TRE - Texas Reliability Entity, and WECC - Western
Energy Coordinating Council.
b. Reference reserve margin: either the target reserve margin provided by the region/subregion or NERC assigned based on capacity mix (i.e., 15 percent and 10 percent reserve margin for predominantly
thermal and hydro systems, respectively).
c. The projected 2019/2020 winter net internal demand. Net internal demand is a total internal demand reduced by dispatchable controllable (capacity) demand response used to reduce peak load.
d. The projected 2019/2020 winter adjusted potential capacity. Adjusted potential capacity is the sum of existing-certain, existing-other, future-planned, adjusted future-other, adjusted conceptual
resources, net firm, expected, and provisional transactions. For more information, see the 2010 LTRA report.
e. Compliance Adjusted Potential Capacity Margin is calculated as (Adjusted Potential Capacity - Downtime Capacity - Net Internal Demand) / Net Internal Demand.
f. 316(b) Facility-Level Downtime Capacity values are from the 2011 E1A-860 database. Facility-level capacity used to analyze the downtime impact includes steam capacity only.
g. In most instances when downtime capacity in a given time period exceeds 2 percent of the total capacity in the region, thi s downtime capacity belongs to an individual facility and, therefore, could not
be subdivided to ensure a more uniform downtime capacity distribution across time periods. To the extent that not all steam generating capacity at these individual facilities would need to be out of
service at the same time to complete technology installation, the assessment of capacity-availability impact is likely overstated in these instances.
h. Facilities are estimated to experience downtime due to installation of 1M technologies during a 5-year period of 2018 through 2022. Non-nuclear and nuclear facilities are estimated to experience
downtime during 5-year windows of 2021 through 2025 and 2026 through 2030, respectively. Consequently, under Proposal Option 2, during 2021 and 2022 some facilities will be installing cooling
towers, while some will be installing 1M technologies.
Source: U.S. EPA analysis for this report; NERC 2010
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
Table 4-11: Downtime Capacity for the ASCC and HICC NERC Regions, by Region and
Compliance Year, Final Rule-Existing Units and Other Options Considered3

NERC
Total Regional
Measure0'"1

Region
Capacity (MW)b
1
2
3
Proposal Option 4
IM Technology

Downtime Capacity (MW)
28
0
0

% of Region Total
1%
0%
0%

Downtime Capacity (MW)
610
0
0

% of Region Total
22%
0%
0%
Final Rule
IM Technology

Downtime Capacity (MW)
28
0
0

% of Region Total
1%
0%
0%

Downtime Capacity (MW)
610
0
0

% of Region Total
22%
0%
0%
Proposal Option 2
IM Technology and Cooling
Towers - Non-Nuclear Facilities

Downtime Capacity (MW)
28
0
0

% of Region Total
1%
0%
0%

Downtime Capacity (MW)
610
372
104

% of Region Total
22%
13%
4%
Cooling Towers - Nuclear Facilities

Downtime Capacity (MW)
0
0
0

% of Region Total
0%
0%
0%

Downtime Capacity (MW)
0
0
0

% of Region Total
0%
0%
0%
a. When downtime capacity in a given time period exceeds 2 percent of the total capacity in the region, this downtime capacity
belongs to an
individual facility and, therefore, could not be subdivided to ensure a more uniform downtime capacity distribution
across time periods. To the extent that not all steam generating capacity at these individual facilities would need to be out of service at
the same time to complete technology installation, the assessment of capacity availability impact is likely overstated in these
instances.

b. Regional capacity values for HICC and ASCC are from the 2011 EIA-860 database. Regional capacity is a total of steam and non-
steam capacity.

c. Facility-level downtime capacity values are from the 2011 EIA-860 database. Facility-level capacity used for the downtime
assessment includes steam capacity only.

d. There is only one Electric Generator in the ASCC NERC region and three Electric Generators in the HICC NERC region; none of
these facilities are nuclear.

Source: U.S. DOE, 2011b; U.S. EPA analysis for this report

Uncertainties and Limitations
The analysis of reliability effects is subject to several uncertainties and limitations, including:
> To the extent that generating capacity and electricity demand projected for winter of 2019/2020 are
different from the actual capacity and demand during installation downtime periods, reliability effects
may be over- or underestimated.
> To the extent that winter electricity demand on average exceeds demand occurring during the shoulder
seasons of spring and fall, reliability effects may be over-estimated.
4.3 Cost and Economic Impact Analysis - New Units
As discussed in Chapter 3, electric power generating units that meet the definition of a new unit will be required
to achieve intake flow commensurate with CCRS under the final rule. In addition to estimating the total cost of
the new unit provision (see Chapter 3), EPA also considered whether the new unit provision would impede the
construction of new stand-alone units at existing facilities. As described in the introduction to this chapter, this
question is important because new stand-alone units will generally operate with higher energy efficiency and
lower environmental impact - in terms of water usage, air pollutant emissions, and water pollutant discharges -
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
than older electric generating capacity, which the new units would tend to displace as a source of electric power
generation. This section summarizes the data and methodology EPA used to conduct the barrier-to-development
analysis.
To assess the effects of the new unit provision of the final rule and other new unit options considered on decisions
to build generating units to obtain additional capacity, EPA compared the cost of CCRS to the cost of building
and operating generating units without the new unit requirements, on a pre-tax, per MW basis.
4.3.1 Analysis Approach and Data Inputs
To assess the relative magnitude of compliance costs for new units, EPA compared annualized pre-tax compliance
costs, per MW of capacity, to the total cost of building and operating an electric power generating facility, also on
a per MW and pre-tax basis. Because EPA was unable to determine which Electric Generators will construct new
generating units, the Agency conducted this analyses at the national level only and not at the NERC-region level.
Only prime movers with a steam electric generating cycle use large enough amounts of cooling water to be
affected by the new unit provision of the final rule. EPA identified two types of prime movers - steam turbine and
combined cycle steam turbine - that constitute the steam electric prime movers of interest. Steam turbine prime
movers generally rely on coal, oil, and biomass for fuel, while combined cycle prime movers generally rely on
natural gas. For simplicity, EPA looked only at coal steam and natural gas combined cycle capacity to assess
whether the new unit provision of the final rule would impede development of new capacity. Here, coal steam
capacity is broadly viewed as including all single cycle fossil and biomass generating systems. EPA excluded
nuclear capacity from the analysis because the Agency concluded that any new nuclear units would likely meet
the final rule's requirements in the baseline and their incremental compliance costs would be zero. For more
information, see the TDD.
EPA's estimates for compliance costs for new units are based on the difference in costs between the cost of
building generating units without installation of cooling towers and those that would likely be incurred if cooling
towers were installed in the process. As described in Chapter 3, EPA expects Electric Generators with new units
to incur the following technology costs:
> Capital costs
> Additional fixed and variable O&M costs, and
> Additional costs from auxiliary energy requirements from installation and operation of entrainment
technology.
These new units would not, however, incur costs associated with the energy penalty (i.e., the loss of thermal
conversion efficiency that occurs with the addition of CCRS to existing units).
In addition, EPA expects these facilities to incur costs associated with the following administrative activities to
implement the final rule:
> Initial start-up,
> Initial permitting,
> Annual monitoring, and reporting and recordkeeping activities.
EPA developed total compliance costs using the same methodology as that described in Chapter 3 with the
following exceptions:
> Instead of promulgation year (2013), EPA discounted all compliance costs to 2017, i.e., the first year of
cooling tower operation after rule promulgation, assuming it takes four years to install a cooling tower.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 4: Economic Impact Analyses - Electric Generators
> EPA considered only new capacity estimated to come online during any one given year as opposed to
throughout the 30-year analysis period.
> Instead of looking at total compliance costs for all types of new units in the aggregate, EPA looked
separately at costs for two stand-alone new unit types: fossil fuel (coal) generating units and stand-alone
combined cycle generating units
To assess the potential impact on constructing stand-alone fossil fuel and combined cycle generating units to
obtain additional generating capacity, EPA used total overnight capital and O&M costs, at the national-level, for
building and operating a single-unit advanced pulverized coal facility of 650 MW and a conventional natural gas
combined cycle (NGCC) facility of 540 MW provided in the Updated Capital Cost Estimates for Electricity
Generation Plants report (Updated Capital Costs report) published by DOE's EIA in November 2010 (U.S. DOE,
2010d).92
To be consistent with the methodology EPA used to estimate total compliance costs for existing units, EPA first
brought building and operating costs, originally reported in EIA's Updated Capital Costs report in 2010 dollars, to
2017 using CCI and restated in 2011 dollars using the GDP deflator. The Agency then annualized these costs over
30 years using a discount rate of 7 percent.93 Finally, EPA compared the estimated compliance costs per MW of
capacity to the cost of constructing and operating electric power facilities also calculated on a per MW of capacity
basis.94 EPA conducted this analysis in two ways:
> First, comparing only capital and other upfront costs on unannualized basis. This comparison captures the
effect of additional capital outlay and associated financing that the unit developer would encounter in
deciding whether to move forward with new unit construction including the cost of CCRS.
> Second, by comparing total annualized costs. This comparison provides insight on the relative
competitiveness of a new unit including CCRS to a unit without CCRS.
The distinction among types of new capacity is important not only in specifying the capital and other costs for
constructing and operating the various generating capacity options, but also for specifying the CCRS costs to be
analyzed in conjunction with these options. In particular, combined cycle capacity includes both a steam and non-
steam generating cycle, and only the steam capacity component of generating capacity uses cooling water. As a
result, because the CCRS for a combined cycle unit is sized based on the steam component of generating capacity,
the CCRS requirement for combined cycle capacity will be lower - on a per MW of total capacity basis - than for
an all steam-based capacity installation. Other factors, including the cooling water required for different boiler
and fuel types, also influence the CCRS requirement for a given generating type: coal-based steam capacity
requires greater cooling water capacity than other steam-based fuel systems. These factors also lead to differences
in CCRS capital and operating costs depending on the specific generation system and fuel type selected within the
new generating capacity options. In this analysis, based on the combination of these factors, EPA assumes that the
cost of adding CCRS to an NGCC unit is approximately half the cost of adding CCRS to a coal-fired unit, on a
per-MW of total installed capacity basis.
92 As defined by the EIA, "Overnight cost" is an estimate of the cost at which a facility could be constructed assuming that the entire
process from planning through completion could be accomplished in a single day. This concept avoids issues and assumptions
concerning the change in costs, and their accumulation over time, during the period of facility construction. For more information see
http://www.eia.gov/oiaf/beck plantcosts/pdf/updatedplantcosts.pdf.
93 Thirty years is the assumed technology life of a cooling tower; hence, EPA used 30 years for annualization purposes to align the cost
of construction with compliance costs. This period is shorter than the actual performance life of generating units constructed and
operated over the past several decades.
94 To state costs on a per MWh basis, EPA assumed an 80-percent capacity utilization rate, which is the same capacity factor as that EPA
used in developing compliance costs for new units. The use of the 80-percent capacity utilization rate assumes that new stand-alone
capacity will operate as base-load capacity.
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Chapter 4: Economic Impact Analyses - Electric Generators
4.3.2 Key Findings
EPA presents the findings from this analysis below, reporting the findings, first, for the comparison based only on
capital and other up-front costs (Table 4-12), and, then for the comparison based on total annualized costs (Table
4-13).
Table 4-12 presents results for the comparison of the capital and other up-front costs for installing CCRS costs to
the cost of building and operating new units, per MW of capacity. On a per MW of capacity basis, these costs
represent approximately 2.2 percent of the cost of building anew, stand-alone coal-fired facility and 3.7 percent
of the cost of building a new, stand-alone NGCC facility. The larger percentage of additional costs from CCRS
installation for new NGCC units compared to new coal units largely reflects the lower initial cost for developing
new NGCC capacity, which is in the denominator of the percentage cost calculation. The lower initial cost for
NGCC capacity offsets the effect of the lower CCRS cost for NGCC capacity compared to coal-fired capacity
(see Table 4-12).
Table 4-12: CCRS Capital and Other Upfront Costs for New Units as Percent of Costs for Building
Generating Units (Not Annualized; at 2017; $2011 )a
New Capacity Specification
EIA New Facility
Category
Cost of Building
New Capacity
(S2011/MW)
Capital and Other
Upfront Costs for
CCRS Installation
(S2011/MW)
CCRS Costs as
Percent of Costs to
Build
New stand-alone fossil fuel steam capacity
Single Unit Advanced
Pulverized Coal
$3,540,443
$78,367
2.2%
New stand-alone combined cycle capacity
Conventional NGCC
$1,093,323
$40,373
3.7%
a. Compliance costs include capital, start-up, and initial permitting costs. Costs to build a stand-alone generating unit include capital costs
only.
Sources: U.S. DOE, 2010d; U.S. EPA analysis for this report
Table 4-13 presents results for the comparison of CCRS costs to new unit costs on the basis of total annualized
costs, again per MW of capacity. On a per MW of capacity basis, CCRS compliance costs represent 3.4 percent of
the cost of building and operating a new, stand-alone coal-fired facility and 4.7 percent of the cost of building and
operating a new, stand-alone NGCC facility.
Table 4-13: Total Compliance Costs for CCRS Installation and Operation for New Units, as Percent of
Costs for Building and Operating Generating Unit (Annualized; at 2017; $2011)
New Capacity Specification
EIA New Facility
Category
Cost of Building and
Operating New
Capacity
(S2011/MW)
Total Compliance
Costs - CCRS
Installation and
Operation
(S2011/MW)
Compliance Costs as
Percent of Costs to
Build and Operate
New stand-alone fossil fuel steam
capacity
Single Unit Advanced
Pulverized Coal
$340,154
$11,425
3.4%
New stand-alone combined cycle
capacity
Conventional NGCC
$125,302
$5,938
4.7%
Sources: U.S. DOE, 2010d; U.S. EPA analysis for this report
As reported in Table 4-12 and Table 4-13, the costs of adding CCRS technology as part of building a new, stand-
alone unit are quite low in relation to the costs of new capacity, based on comparison both with capital and other
upfront costs, and with total annualized costs.
Given the low cost of CCRS in relation to the cost of new capacity, EPA concludes that the CCRS requirement
will not pose a barrier to development of new units.
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Chapter 4: Economic Impact Analyses - Electric Generators
4.3.3 Uncertainties and Limitations
The barrier-to-development analysis is subject to uncertainties and limitations. In particular, the cost of cooling
tower installation and operation varies based on the size of the generating unit and configuration as defined by
fuel type and electric generating configuration, as described above. To the extent that the size and configuration of
a potential new unit is different from the assumptions that underlie new capacity costs, the relative magnitude of
the compliance costs for new capacity may be under- or over-estimated. In addition, because EPA cannot predict
the specific facilities at which new units would be built or the specific costs that would be incurred in building the
capacity without or with CCRS, EPA is unable to account for facility-specific factors that could cause the cost
relationships to differ from those estimated in this analysis. Regardless, given the low percentages of additional
cost that would be incurred for adding CCRS to a new unit, EPA concludes that the requirement to add CCRS at
certain new units would not impede development of that capacity.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 5: Economic Impact Analyses - Manufacturers
5 Economic Impact Analyses - Manufacturers
5.1 Introduction
This chapter assesses the expected economic impact on Manufacturers of the existing unit provision of the final
rule and other options EPA considered. As explained in Chapter 1, the cost of the new unit provision for
Manufacturers is negligible. Correspondingly, EPA concludes that the new unit provision will not constitute a
barrier to development - that is, development of new, stand-alone units - as discussed in Chapter 4 for Electric
Generators. Therefore, the cost and economic impact assessment discussion in this chapter focuses on existing
units only and the terms final rule and other options considered refer to existing units. This chapter includes a
facility-level analysis, which assesses the impact of compliance requirements and costs on Manufacturers, and an
entity-level analysis, which assesses the regulatory impact on the entities that own Manufacturers (parent entities
or entities). For each of these analyses, EPA assessed the impacts of the final rule and other options EPA
considered for two cases: (1) assuming that all facilities with a cooling water system impoundment qualify as
CCRS in the baseline and will meet the performance standard for impingement mortality under the final rule and
other options considered without additional technology,95 and (2) assuming that no facilities with a cooling water
system impoundment qualify as CCRS in the baseline and thus may need to install additional technology under
the final rule and other options considered. In all but one of the impact analyses, the results are the same under
each of the assumptions; however, for the cost-to-revenue analysis, the impacts differ under the alternative
assumptions. For this analysis, EPA reports a range of impacts based on the assumptions described above. The
assumption that all Manufacturers with a cooling water system impoundment will qualify as baseline CCRS and
not need to install additional compliance technology has a slightly smaller impact in some cases than the
alternative assumption.
The remaining sections of this chapter are as follows:
> Overview of the Manufacturers impact analysis (Section 5.2), including:
¦ Summary of the impact concepts used in this analysis
¦ EPA's estimates of the number of Manufacturers
¦ Data sources for this analysis
> Facility-level impact analysis: cost-to-revenue screening analysis (Section 5.3)
> Facility-level impact analysis: severe impacts (Section 5.4)
> Facility-level impact analysis: moderate impacts (Section 5.5)
> Entity-level impact analysis (Section 5.6)
> Uncertainties and limitations (Section 5.7).
5.2 Overview of the Manufacturers Impact Analysis
5.2.1 Facility Universe
EPA estimated the cost and economic impact of the existing unit provision of the final rule and other options EPA
considered on regulated manufacturing facilities, and the entities that own these facilities. In the same way as
undertaken for the previous 316(b) analyses, this analysis focused on 575 facilities in the six Primary
Manufacturing Industries and 13 facilities in the Other Industries. As the first step in this analysis, EPA
determined which of these facilities show materially inadequate financial performance in the baseline - that is, in
95 For Proposal Option 2, EPA also assumed that these facilities will meet entrainment technology requirements, as applicable.
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Chapter 5: Economic Impact Analyses - Manufacturers
the absence of the regulation. These baseline closure facilities are at substantial risk of financial failure regardless
of the final 316(b) regulation. EPA excluded them from the analysis of cost and regulatory impacts.
EPA undertook the impact analysis for the Primary Manufacturing Industries and estimated industry-level cost
and impact results by applying sample weights to results estimated for surveyed facilities. The impact analysis for
Other Industries is restricted to a sample of 12 facilities for which EPA received surveys, but which are not part of
the statistically valid sample (for details, see Appendix H). As a result, EPA's analysis for the Other Industries
group is limited to these known facilities; EPA did not apply sample weights to extend the findings to a broader
population.96 Although EPA performed the impact analysis for the Other Industries group using only these
facilities, in EPA's view, its analysis for the Other Industries group provides a sufficient basis for regulation
development. EPA's review of the engineering characteristics of cooling water intake and use in the Other
Industries group indicates that cooling water intake and use in these industries do not differ materially from that
of Electric Generators or Manufacturers in the Primary Manufacturing Industries.
5.2.2 Methodology
In the same way as described for Electric Generators in Chapter 4, EPA undertook the facility-level economic
impact analysis of the final rule for Manufacturers in two parts: (1) a cost-to-revenue screening analysis (Section
5.3) to assess the potential significance of compliance costs to regulated facilities, and (2) a more rigorous
facility-level impact analysis (Section 5.3), which uses economic/financial impact using cash flow models to
assess the impact of compliance costs on the financial performance of regulated facilities. The facility-level
impact analysis focuses first on the potential for facility closures due to the regulation (severe impacts). The
analysis then considers the potential for financial stress short of closure based on adverse changes in a facility's
financial position that are not threatening to its short-term viability (moderate impacts), but may present
challenges in obtaining financing (Section 5.5). The entity-level impact analysis assesses whether entities that
own multiple facilities are likely to incur a significant impact due to the entity's total compliance cost burden
(,Section 5.6). Impacts may be significant at the entity level whether or not they are significant at the facility level,
if an entity owns a number of facilities that incur costs and the total of these costs is substantial at the entity level.
In addition, an entity-level analysis supports assessment of impacts on small businesses, as required by the
Regulatory Flexibility Act (RFA) (Chapter 10). Other chapters consider the impacts on small entities.97
5.2.3 Data Sources
This analysis relies on data provided in the financial section of the 2000 Detailed Industry Questionnaire {DO)
(316(b) survey). The 316(b) survey financial data include facility and parent-entity income statements and balance
sheets for the three years 1996, 1997, and 1998.
In addition to the survey data, EPA used the following secondary data sources to characterize economic and
financial conditions in the analyzed industries:
> Department of Commerce economic census and survey data, including the Economic Census (EC);
Census of Manufactures, Annual Surveys of Manufactures (ASM), Quarterly Financial Report (QFR),
Statistics of U.S. Businesses (SUSB) and Survey of Plant Capacity (SPC);
> Interactive Tariff and Trade Dataweb, published by the U.S. International Trade Commission;
> Federal Reserve Board of Governors industry data, including Moody's Yield on Seasoned Corporate Baa
and Acta Bonds for all industries and Industrial Production and Capacity Utilization;
90 Stated another way, EPA used weights of one for these facilities.
97 This chapter also cites Appendices K, L, M, N and O, which address particular elements of the cost and economic impact analysis EPA
conducted for Manufacturers.
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Chapter 5: Economic Impact Analyses - Manufacturers
> Producer Price Index, published by the U.S. Bureau of Labor Statistics;
> Implicit Price Deflator for Gross Domestic Product, published by the U.S. Bureau of Economic Analysis;
and
> Annual Statement Studies, published by Risk Management Association (RMA).
The following sections describe the calculations and results of the severe and moderate facility-level impact
assessments and the entity-level impact assessment.
5.3 Facility-Level Impacts: Cost-to-Revenue Screening Analysis
EPA conducted a cost-to-revenue-based screening analysis to determine the potential impact of regulatory costs
on Manufacturers. In the cost-to-revenue comparisons, EPA used cost-to-revenue thresholds of 1 and 3 percent as
markers of potentially significant impacts. EPA determined that facilities incurring costs below 1 percent of
revenue will not face significant economic impacts, while facilities with costs of at least 1 percent but less than 3
percent of revenue have a chance of facing significant economic impacts. Facilities incurring costs of at least 3
percent of revenue have a higher probability of significant economic impacts. EPA compared after-tax annualized
compliance costs and revenue on a non-weighted basis and determined the number of instances in which facilities
incurred costs in these cost-to-revenue impact ranges. EPA applied facility-level sample weights (see Appendix H:
Sample Weights for a discussion of how EPA developed and applied the weights) to the individual facility counts
within each impact category to estimate the number of facilities at the population-level in these ranges.
Of the 509 facilities, 504 facilities incur costs less than 1 percent of revenue and five facilities incur costs between
1 and 3 percent of revenue under the final rule (see Table 5-1). For Proposal Option 4, all 509 facilities incur costs
less than 1 percent of revenue. Under the more expensive Proposal Option 2, 497 to 498 facilities incur costs less
than 1 percent, 10 to 11 facilities incur costs between 1 and 3 percent, and one facility incurs costs of greater than
3 percent of revenue.98
As part of this screening analysis, EPA also considered whether costs would be negligible at the level of the
facility. Specifically, EPA examined whether compliance costs would be below 0.1 percent of facility revenue,
indicating that costs are negligible, or above 0.1 percent of revenue. In the former case, EPA reached a
presumptive finding that costs are so slight in relation to the overall scale of business activity, measured by
facility revenue, as to be negligible in terms of potential adverse impact. All facilities that would go from positive
to negative discounted cash flow value due to the final rule are in poor financial health, but the 0.1 percent
threshold separates the facilities that have a much higher possibility of salvaging their situation from those with a
lower probability. That is, the regulation is more likely to spur facilities with a compliance cost-to-revenue value
of less than 0.1 percent to seek and successfully implement cost-cutting measures or revenue enhancements
compared to those facilities with a cost-to-revenue value above 0.1 percent, for which such a strategy has lower
probability of success. Also, local governments may be more likely to provide tax benefits to avoid closure in
cases where regulatory costs are negligible. As shown in Table 5-2, for the final rule, a substantial majority of
facilities - 415 to 417 out of 509 facilities - incur compliance costs that are less than 0.1 percent of revenue.
Under Proposal Option 4, which imposes technology requirements on fewer facilities, 458 to 460 facilities incur
compliance costs less than 0.1 percent of revenue. Proposal Option 2 would impose higher costs on regulated
facilities, with only 375 to 377 facilities incurring costs below 0.1 percent of revenue. The Chemicals, Paper, and
The ranges in numbers of facilities falling above or below the various cost-to-revenue thresholds result from application of the
alternative assumptions on treatment of facilities with cooling water system impoundments: for example, the lower value for number
of facilities with cost below 1 percent of revenue reflects the assumption that no facilities with cooling water system impoundments
qualify as baseline CCRS, while the higher value reflects the assumption that all facilities with cooling water system impoundments
qualify as baseline CCRS.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 5: Economic Impact Analyses - Manufacturers
Steel industries are the only Primary Manufacturing industries with a relatively larger number (more than one) of
facilities with non-negligible costs for the final rule.
Table 5-1: Facility-Level Cost to Revenue Analysis Results, Final Rule- Existing Units and Other Options
Considered3
Industry
Number of Regulated
Facilities'"
Number0 of Facilities with a Ratio of
<1%
>1 and <3%
>3%
Proposal Option 4
Aluminum
24
24
0
0
Chemicals
167
167
0
0
Food
34
34
0
0
Paper
197
197
0
0
Petroleum
31
31
0
0
Steel
47
47
0
0
Total in the Primary Manufacturing Industries
500
500
0
0
Additional known facilities in Other Industries
9
9
0
0
Total
509
509
0
0
Final Rule-Existing Units
Aluminum
24
24
0
0
Chemicals
167
162
4
0
Food
34
34
0
0
Paper
197
197
0
0
Petroleum
31
31
0
0
Steel
47
47
0
0
Total in the Primary Manufacturing Industries
500
496
4
0
Additional known facilities in Other Industries
9
8
1
0
Total
509
504
5
0
Proposal Option 2
Aluminum
24
23 - 24
0- 1
0
Chemicals
167
162
4
0
Food
34
31
3
0
Paper
197
197
0
0
Petroleum
31
31
0
0
Steel
47
46
1
0
Total in the Primary Manufacturing Industries
500
490-491
9-10
0
Additional known facilities in Other Industries
9
7
1
1
Total
509
497-498
10-11
1
a. Values may not sum to total due to rounding.
b. Number of regulated facilities excludes baseline closures. For a discussion of how EPA estimated baseline closures, see Section 5.4.1.
c. Ranges reflect the alternative assumptions on treatment of facilities with cooling water system impoundments. See text.
Source: U.S. EPA analysis for this report
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 5: Economic Impact Analyses - Manufacturers
Table 5-2: Facilities with Costs Below 0.1 Percent of Revenue, Final Rule-Existing Units and
Other Options Considereda
Industry
Number of
Regulated Facilities'"
Number0 of Facilities with a Ratio of
<0.1% >0.1%
Proposal Option 4
Aluminum
24
23-24
0-1
Chemicals
167
136
31
Food
34
34
0
Paper
197
187
10
Petroleum
31
30
1
Steel
47
43
5
Total in the Primary Manufacturing Industries
500
453 - 454
46-48
Additional known facilities in Other Industries
9
5-6
3-4
Total
509
458 - 460
49-52
Final Rule-Existing Units
Aluminum
24
23-24
0-1
Chemicals
167
127
39
Food
34
34
0
Paper
197
154
43
Petroleum
31
30
1
Steel
47
41
6
Total in the Primary Manufacturing Industries
500
410-411
89-90
Additional known facilities in Other Industries
9
5-6
3-4
Total
509
415-417
92-94
Proposal Option 2
Aluminum
24
23 - 24
0- 1
Chemicals
167
118
49
Food
34
27
7
Paper
197
150
46
Petroleum
31
27
4
Steel
47
25
22
Total in the Primary Manufacturing Industries
500
371-372
129 -130
Additional known facilities in Other Industries
9
4-5
4-5
Total
509
375-377
133 -135
a. Values may not sum to total due to rounding.
b. Number of regulated facilities excludes baseline closures. For a discussion of how EPA estimated baseline closures, see Section 5.4.1.
c. Ranges reflect the alternative assumptions on treatment of facilities with cooling water system impoundments. See text.
Source: U.S. EPA analysis for this report
5.4 Facility-Level Impacts: Severe Impact Analysis
5.4.1 Analysis Approach and Data Inputs
EPA based the assessment of severe impacts for Manufacturers on the change in a facility's estimated business
value, which EPA estimated from a discounted present value analysis of baseline cash flow and the change in
cash flow resulting from regulatory compliance." If the estimated discounted cash flow value of the facility is
positive before considering the effects of regulatory compliance, but becomes negative when accounting for
compliance costs, then EPA considered the facility a candidate for closure due to costs imposed by the regulation.
EPA also included findings from the cost-to-revenue analysis, presented in Section 5.3, in the closure analysis.
Specifically, EPA determined whether compliance costs would fall below the threshold of 0.1 percent of revenue,
and thus be judged as inconsequential, as part of the post-compliance severe impact analysis. For a facility to be
assessed as a post-compliance closure based on the discounted cash flow value test, annualized compliance costs
also needed to exceed 0.1 percent of revenue.
99 This cash flow analysis is similar in concept to the IPM analysis conducted for Electric Generators.
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For the discounted cash flow value test, EPA compared the estimated ongoing business value of the facility with a
threshold value of zero for the closure decision. As long as the discounted cash flow value of the facility is greater
than zero, the business is earning its cost of invested capital and continuation of the business is financially
beneficial. However, in the contrary case, if the discounted cash flow value of the facility is less than zero in the
baseline or becomes less than zero as a result of compliance outlays, then the business would not earn its cost of
invested capital and the owners would be better off financially by terminating the business. EPA designated
facilities with a negative baseline value as baseline closures and did not test these facilities for additional adverse
impacts from regulatory compliance.
In an alternative formulation of this concept, business owners would compare the discounted cash flow value of
the facility with the value that the facility's assets would bring in liquidation. In this case, the estimated ongoing
business value would be compared with a value that may be different from zero: liquidation value could be
positive or negative. When liquidation value is positive, business owners might benefit financially by terminating
a business and seeking its liquidation value even when the ongoing business value is positive but less than the
estimated liquidation value. With negative liquidation value - which generally would result from business
termination liabilities (e.g., site clean-up) - the opposite result could occur: business owners may find it
financially advantageous to remain in business even though the business earns less than its cost of invested
capital, if the liquidation value of the business is "more negative," and thus less in value, than the ongoing
business based on the discounted cash flow analysis. EPA considered this alternative impact test formulation for
the previous 316(b) analyses conducted for Manufacturers. However, the liquidation value estimates are
substantially speculative and subject to considerable error because such an assessment requires detailed facility-
specific financial and operational history, and projections of future asset values and liabilities that are
considerably uncertain. For these reasons, EPA decided against using liquidation value for comparison with
ongoing business value in the closure test.
The cash flow concept used in calculating ongoing business value for the closure analysis is free cash flow
available to all capital. This is the cash available to the providers of capital - both equity owners and creditors -
on an after-tax basis from business operations, and takes into account the cash required for ongoing replacement
of the facility's capital equipment. EPA discounted free cash flow at an estimated after-tax total cost of capital to
yield the estimated business value of the facility. The following sections summarize the baseline and post-
compliance cash flow concepts. Appendix (): Economic Impact Methodology - Manufacturers provides additional
details for these calculations.
Calculation of Baseline Free Cash Flow and Performance of Baseline Closure Test
EPA performed the following steps:
> Calculate the average of income statement data from surveys over response years and restate these values
in 2011 dollars using the BEA's GDP Deflator Index series.
> Adjust after-tax income to exclude the effects of financial structure.
> Calculate after-tax cash flow from operations, before interest, by adjusting income for non-cash charges
such as depreciation and amortization.
> Remove the implied cash flow benefit of any negative taxes, as reported in the facility's income statement
after adjustment for removal of interest. This assumption is consistent with a later step in the post-
compliance analysis in which EPA limited the cash flow benefit of tax deductions on compliance outlays
not to exceed the taxes reported in the baseline income statement (and adjusted for interest).
> Adjust after-tax cash flow to reflect estimated real change in business performance, as reflected in
baseline cash flow, from the time of survey data collection to the present (see Appendix L: Adjusting
Baseline Facility Cash Flow). This adjustment addresses two concerns: (1) that facility survey data are
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 5: Economic Impact Analyses - Manufacturers
from a period that deviated cyclically from the longer-term trend of business performance for the 316(b)
manufacturing industries, and (2) that some of the industries might be experiencing a longer-term trend of
deteriorating economic performance. In both cases, using the survey-based data for the current analysis -
without accounting for these possible effects - could lead to misleading estimates of the affected
industries' ability to withstand the compliance cost burdens of the final rule and other options considered.
> Calculate free cash flow by adjusting after-tax cash flow from operations for estimated ongoing capital
equipment outlays (see Appendix M).100
> Calculate baseline facility value as the present value of free cash flow over a 30-year analysis horizon,
using an estimated real (i.e., excluding the effects of inflation), after-tax cost of capital of 7 percent. The
use of 30 years as the time horizon reflects the facility-level analysis period for the final rule and other
options considered.
As explained above, EPA considered a facility to be a baseline closure if its estimated business value was
negative before incurring regulatory compliance costs. EPA neither tested baseline closures for adverse impact in
the post-compliance impact analysis nor included their compliance costs in the tally of total costs of 316(b)
regulatory compliance.
Calculation of Post-Compliance Free Cash Flow and Performance of the Post-Compliance
Closure Test
For the post-compliance closure analysis, EPA recalculated annual free cash flow, accounting for changes in
revenue, annual expenses, and taxes that would result from compliance-related outlays. EPA combined the post-
compliance free cash flow value and the estimated compliance capital outlay in the present value framework to
calculate business value on a post-compliance basis. As described above, for the post-compliance severe impact
test, EPA also considered whether compliance costs would exceed 0.1 percent of revenue. As part of this analysis,
EPA considered whether Manufacturers would be able to pass on compliance costs to customers through
increased prices. From the analyses presented in Appendix K: Cost Pass-Through Analysis, EPA concluded that
an assumption of zero cost pass-through is appropriate for analyzing the impact of the final rule and other options
considered on facilities in the six Primary Manufacturing Industries (same assumption used in the previous 316(b)
Manufacturers analyses). This means that facilities cannot increase revenue in conjunction with incurrence of
compliance costs and instead must absorb all compliance-related costs and operating effects (e.g., income loss
from facility shutdown during equipment installation) within their baseline cash flow and financial condition. To
the extent that facilities would be able to pass some of the compliance costs to customers through price increases
and associated revenue increases, the analysis may overstate the potential impact on regulated facilities.
Calculation of post-compliance, free cash flow involved the following steps:
> Adjust baseline, annual, free cash flow to reflect compliance outlay effects. Relevant compliance cost and
other operating effects include (1) annual change in revenue (assumed to be zero in this analysis, because
of EPA's finding that regulated facilities would not be able to increase prices and revenue to recover
100 In the primary analysis, included in this chapter, EPA adjusted the cash flow analysis to account for industry-level changes in financial
performance, including the impact new regulations, between when financial data was collected and 2011 (for more information, see
Appendix L: Adjusting Baseline Facility Cash Flow). Therefore, this analysis did not reflect the cost impact of environmental
regulations that came into effect beginning in 2012. Recognizing this potential impact, EPA also undertook an alternative case
analysis to account for the additional impact of these more recent federal environmental regulations. In this analysis, EPA adjusted
baseline cash flow and post-compliance cash flow to reflect costs that facilities might incur from compliance with recently
promulgated federal environmental regulations whose costs would not be fully reflected in the after-tax cash flow adjustment analysis.
This analysis, which is documented in Appendix N: Analysis of Other Regulations, found no material effect on either the baseline or
post-compliance facility impact analysis, as reported in this chapter. The alternative case analysis, which incorporated estimated
compliance costs from the recent federal environmental regulations, found no change in baseline or post-compliance closures.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 5: Economic Impact Analyses - Manufacturers
compliance costs), (2) annually recurring operating and maintenance costs, (3) the annual equivalent of
initial permitting and non-annually recurring permitting costs, (4) annually recurring permitting costs,
(5)the annual equivalent of the net income loss from installation downtime, and (6) related changes in
taxes.101
> Limit tax adjustment not to exceed taxes as reported in the facility's baseline financial statement.
> Calculate post-compliance facility value based on a comparison of the present value of post-compliance
free cash flow with the compliance capital outlay. As in the baseline analysis, EPA accounted for the
compliance capital outlay as an undiscounted cash outlay in the first analysis period and used a 7 percent
discount rate for this present value calculation.
For the cost-to-revenue part of the post-compliance severe impact analysis, EPA divided facility-level revenue by
the facility's after-tax annualized, total compliance cost. If this value exceeded 0.1 percent, EPA considered
compliance costs to be more than negligible in terms of possible adverse financial impact of the facility.
EPA considered a facility to be a post-compliance closure if:
1. Its estimated business value was positive in the baseline, but became negative after adjusting for
compliance-related cost, revenue, and tax effects, and
2. Its cost-to-revenue value was more than a negligible percentage of revenue.
EPA measured the significance of closures in terms of losses in output, which is equal to total revenue reported
for regulatory closure facilities. EPA estimated national results by multiplying facility results by facility sample
weights.
5.4.2 Key Findings
Table 5-3 reports estimated severe impacts for Manufacturers facilities for the final rule and other options
considered. As described in Appendix H, EPA estimated that 70 facilities would close in the baseline. EPA
removed these facilities from the severe impact analysis, leaving 509 Manufacturers that EPA estimated to incur
compliance costs. EPA estimated that none of these remaining facilities will incur severe impacts as a result of the
final rule. EPA reached the same finding - no severe impacts - for Proposal Option 4. For Proposal Option 2,
EPA found that one facility would be at risk of closure.
101 For the facility cash flow analysis, EPA treated the income loss from installation downtime on an annual equivalent basis even though
this financial event occurs only once, and at the beginning of the assumed analysis period, for two reasons. First, the installation
downtime is assumed to have a useful "financial life" of 30 years to reflect the total potential business life of the facility with the
installed compliance technology (note that reinstallation of the basic capital equipment other than cooling towers, which is assumed to
recur on a 20-, 25-, or 30-year interval depending on the specific technology, does not require a new round of downtime). Because
compliance capital equipment is assumed to have a specific useful life and the discounted cash flow analysis is structured around this
period, if EPA were to include the income loss from installation downtime (which EPA assumes to have a 30-year useful life) as a
one-time up-front cost, its impact would be overstated in the discounted cash flow calculation. Second, calculation of the downtime
cost on an annual basis allows the tax effect from the one-time income loss to be summed with other annual tax effects for applying
the limit to tax offsets, as explained in the next step of the analysis.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 5: Economic Impact Analyses - Manufacturers
Table 5-3: Number of Facilities with Severe Impacts by Sector, Final Rule-Existing
Units and Other Options Considered
Sector
Total Operating
in Baseline
Facilities with Severe Impacts
Number
Percentage
Revenue
(million;
$2011)
Proposal Option 4
Aluminum
24
0
0%
$0
Chemicals and Allied Products
167
0
0%
So
Food and Kindred Products
34
0
0%
So
Paper and Allied Products
197
0
0%
So
Petroleum Refining
31
0
0%
so
Steel
47
0
0%
so
Total Facilities in Primary Manufacturing
Industries3
500
0
0%
$0
Additional known facilities in Other Industries
9
0
0%
so
Final Rule-Existing Units
Aluminum
24
0
0%
so
Chemicals and Allied Products
167
0
0%
so
Food and Kindred Products
34
0
0%
so
Paper and Allied Products
197
0
0%
So
Petroleum Reliniim
31
0
0%
So
Steel
47
0
0%
so
Total Facilities in Primary Manufacturing
Industries3
500
0
0%
$0
Additional known facilities in Other Industries
9
0
0%
so
Proposal Option 2
Aluminum
24
0
0%
so
Chemicals and Allied Products
167
0
0%
so
Food and Kindred Products
34
0
0%
so
Paper and Allied Products
197
0
0%
So
Petroleum Reliniim
31
0
0%
So
Steel
47
1
3%
S2.262
Total Facilities in Primary Manufacturing
Industries3'b
500
1
0%
$2,262
Additional known facilities in Other Industries
9
0
0%
so
a. Values may not sum to reported totals due to independent rounding.
b. For Proposal Option 2, the percentage of severe impacts is 0.3 percent.
Source: U.S. EPA analysis for this report
5.5 Facility-Level Impacts: Moderate Impact Analysis
5.5.1 Analysis Approach and Data Inputs
EPA also conducted an analysis of financial stress short of closure to assess the occurrence of moderate impacts
on Manufacturers. EPA does not consider facilities incurring moderate impacts as being at risk of closure due to
the final rule and other options considered. The regulation, however, might reduce their financial performance to
the point where they experience greater difficulty and higher costs in obtaining financing for future investments.
The following discussion outlines the calculations undertaken for this assessment; Appendix O provides a detailed
discussion of this analysis.
The analysis of moderate impacts examined two financial measures:
Pre-Tax Return on Assets (PTRA): ratio of pre-tax operating income - earnings before interest and taxes
(EBIT) - to assets. This ratio measures the operating performance and profitability of a business" assets
independent of financial structure and tax circumstances. PTRA is a comprehensive measure of a facility's
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 5: Economic Impact Analyses - Manufacturers
economic and financial performance. If a facility cannot sustain a competitive PTRA on a post-compliance
basis, it will likely face difficulty financing its investments, including the outlay for compliance equipment.
Interest Cov erase Ratio (ICR): ratio of pre-tax operating cash flow - earnings before interest, taxes, and
depreciation (EBITDA) - to interest expense. This ratio measures the facility's ability to service its debt
based on current, ongoing financial performance, and to borrow for capital investments. Investors and
creditors will be concerned about a facility whose operating cash flow does not comfortably exceed its
contractual obligations. As ICR increases, the facility's general ability to meet interest payments and carry
credit also increases. ICR also provides a measure of the amount of cash flow available for equity after
interest payments.
Creditors and equity investors review the above two measures as criteria to determine whether and under what
terms they will finance a business. PTRA and ICR also provide insight into a facility's ability to generate funds
for compliance investments from internally generated equity, i.e., from after-tax cash flow.
Calculation of Moderate Impact Metrics
EPA calculated facility-level PTRA and ICR measures using data collected from the 316(b) industry survey,
adjusted for inflation to 2011. EPA calculated these measures on a baseline and post-compliance basis. In
calculating the baseline values of the PTRA and ICR measures, EPA applied the same cash flow adjustments as
described above for the facility closure analysis, to the numerators of the PTRA and ICR measures. In the same
way as described for the closure analysis, EPA intends these adjustments to capture the change in the financial
performance of facilities in the Primary Manufacturing Industries between the time of the 316(b) survey and the
present (see Appendix L).
Developing Threshold Values for PTRA and ICR
For evaluating manufacturing facilities according to the moderate impact measures, EPA compared baseline and
post-compliance PTRA and ICR to 316(b) industry-specific thresholds that were developed from RMA data.
RMA compiles and reports financial statement information by industry as provided by member commercial
lending institutions. The threshold values represent the lowest 25th percentile values of PTRA and ICR for
statements received by RMA for the 13 years from 1998 to 2010 within relevant industries (RMA, 2011). EPA
developed 316(b) industry-level values by weighting and summing the RMA industry values according to the
definition of 316(b) industries. Thresholds by sector ranged from 0.5 percent to 2.7 percent for PTRA and from
1.2 to 2.7 for ICR. Because the financial statements received by RMA are for businesses applying for credit from
member institutions, the data do not represent a random sample. In particular, the RMA data likely exclude
representation from the financially weakest businesses, which are unlikely to seek financing from RMA member
lending institutions. As a result, EPA views the threshold values as somewhat likely to overestimate the
occurrence of moderate impacts on regulated facilities. Both measures are important to financial success and
ability to attract capital.
EPA consolidated the 6-digit North American Industry Classification System (NAICS) code data into industry-
level weighted averages, weighted by 2010 value of shipments from ASM (U.S. DOC, 2010). For each industry
and impact measure, a separate threshold was calculated. Appendix O describes the use of the RMA data for
calculating the threshold values for pre-tax return on assets and interest coverage ratio.
Summary of Threshold Values
Table 5-3 reports the resulting threshold values for PTRA and ICR by industry. The PTRA values range from 0.3
percent for the Aluminum Industry to 2.7 percent for Petroleum Refining. The ICR values range from 1.2 for the
Aluminum Industry to 2.7 for Petroleum Refining.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 5: Economic Impact Analyses - Manufacturers
Table 5-3: Summary of Moderate Impact Thresholds by Manufacturers
Industry, based on 2!>h percentile value of entities reporting data to RMA
Industry
PTRA
ICR
Aluminum
0.3
1 .2
Chemicals and Allied Products

2 1
Food and Kindred Products
F5
2.4
Paper and Allied Products
0.9
1.8
Petroleum Reliniim
21
21
Steel
0.4
1.4
()ther
0.5
1.6
Source: U.S. EPA analysis for this report
Calculation of Moderate Impacts
In estimating the occurrence of moderate impacts, EPA first set aside from the analysis facilities assessed as
baseline or post-compliance closures, which varies across the final rule and other options considered. EPA then
examined whether the remaining facilities (1) meet the moderate impact thresholds in the baseline, and (2) are
thus candidates for testing the occurrence of moderate impacts on a post-compliance basis. Specifically, EPA
identified the remaining facilities falling below one or both of the moderate impact thresholds as having failed the
moderate impacts test in the baseline, and removed them from the post-compliance moderate impact analysis.
EPA identified facilities failing one or both thresholds in the post-compliance analysis as having failed the
moderate impact test.
5.5.2 Key Findings
EPA began the moderate impact analysis by testing whether facilities that passed the post-compliance closure
(severe impact) analysis would fail the moderate impact test in the baseline. Because the number of post-
compliance closures varies by regulatory option (see Table 5-4), the number of facilities brought forward to the
moderate impact analysis also varies by option: 509 facilities passed the post-compliance closure analysis for the
final rule and Proposal Option 4 (no post-compliance closures), while 508 facilities passed the post-compliance
closure analysis for Proposal Option 2 (one post-compliance closure).1"2 EPA conducted the baseline moderate
impact analysis for those facilities that were brought forward for a given option. EPA found that the one facility
that failed the post-compliance closure analysis for Proposal Option 2, while passing the closure analysis for the
final rule and Proposal Option 4, failed the moderate impact test in the baseline. As a result, even though the
number of facilities brought forward to the baseline moderate impact analysis varied by regulatory option, the
number of facilities remaining in the post-compliance analysis did not vary by regulatory option. Of the 509
facilities, EPA found that 49 facilities failed the moderate impact test in the baseline for the final rule and
Proposal Option 4, while 47 facilities failed the moderate impact test in the baseline for Proposal Option 2. EPA
removed these facilities from the post-compliance moderate impact analysis, leaving 454 facilities in Primary
Manufacturing Industries and seven facilities in the Other Industries, regardless of regulatory option (see Table
5-4).
102 For Proposal Option 2, EPA estimates five of the 509 facilities analyzed, as post-compliance closures (see Table 5-1% however,
because of rounding there are actually slightly fewer than five post-compliance closures and therefore, 505 facilities pass the post-
compliance severe impact test.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 5: Economic Impact Analyses - Manufacturers
Table 5-4: Number of Facilities in Moderate Impact Analysis, by Sector
Analysis Step and Industry
Proposal Option 4
Final Rule
Proposal Option 2
Facilities Passing Post-Compliance Closure (Severe Impact) Analysis
Aluminum
24
24
24
Chemicals and Allied Products
167
167
167
Food and Kindred Products
34
34
34
Paper and Allied Products
197
197
197
Petroleum Reliniim
31
31
31
SteeP
47
47
46
Total Facilities in Primary Manufacturing Industries3
500
500
499
Additional known facilities in Other Industries
9
9
9
Total Facilities Passing Post-Compliance Closure Analysis3
509
509
508
Baseline Moderate Impact Failures
Aluminum
5
5
5
Chemicals and Allied Products
19
19
19
Food and Kindred Products
3
3
3
Paper and Allied Products
9
9
9
Petroleum Reliniim
1
1
1
Steel1'
9
9
8
Total Facilities in Primary Manufacturing Industries3
47
47
45
Additional known facilities in Other Industries
2
2
2
Total Facilities Failing Baseline Moderate Impact Analysis3
49
49
47
Facilities Carried Forward to Post-Compliance Moderate Impact Analysis
Aluminum
20
20
20
Chemicals and Allied Products
147
147
147
Food and Kindred Products
31
31
31
Paper and Allied Products
187
187
187
Petroleum Refilling
30
30
30
Steel
38
38
38
Total Facilities in Primary Manufacturing Industries3
454
454
454
Additional known facilities in Other Industries
7
7
7
Total Facilities in Post-Compliance Moderate Impact Analysis3
461
461
461
a. Values may not sum to reported totals due to independent rounding.
b. Industries with differences in findings by regulatory option in post-compliance closure analysis and baseline moderate impact analysis are highlighted
with gray shading.
Source: U.S. EPA analysis for this report
Table 5-5 reports the estimated moderate impacts for the final rule and other options considered. Of the 461
Manufacturers assessed as remaining in the analysis after excluding post-compliance closures and baseline
moderate impact failures, EPA estimated that 12 facilities, or 3 percent of facilities analyzed, will incur moderate
impacts under the final rule. EPA estimated that two facilities would incur moderate impacts under Proposal
Option 4, and that 12 facilities would incur moderate impacts under Proposal Option 2.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 5: Economic Impact Analyses - Manufacturers
Table 5-5: Facilities with Moderate Impacts by Sector, Final Rule-Existing Units and Other Options
Considered

Number of
Number of Facilities with Moderate Impacts

Facilities
Proposal Option 4
Final Rule-Existing Units
Proposal Option 2
Industry
Analyzed
Number
Percentage
Number
Percentage
Number
Percentage
Primary Manufacturing Industries
Aluminum
20
0
0%
0
0%
0
0%
Chemicals and Allied Products
I47
0
0%
4
3%
4
3%
Food and Kindred Products
31
0
0%
0
0%
0
0%
Paper and Allied Products
187
0
0%
6
3%
6
3%
Petroleum Refining
30
I
3%
1
3%
1
3%
Steel
38
1
3%
1
3%
1
3%
Total Facilities in Primary
454
2
1%
12
3%
12
3%
Manufacturing Industries3

Known facilities in Other
7
0
0%
0
0%
0
0%
Industries

a. Values may not sum to reported totals due to independent rounding.
Source: U.S. EPA analysis for this report
5.6 Entity-Level Impacts
The analysis of impact on entities that own Manufacturers goes beyond the facility impact analysis to determine
whether entities that own regulated facilities may incur impacts at the level of the entity in a way that is not
revealed by the facility impact analysis. For example, depending on the magnitude of total compliance costs, an
entity may incur an adverse impact at the entity level at the same time that one or more individual facilities incur
facility-level impacts, severe or moderate, or even if none of the facilities owned by the entity incur adverse
impacts. Entities incurring adverse impacts at the level of the entity may be at greater risk of weaker business
performance in their respective industries due to the overall burden of compliance requirements. Alternatively, an
entity may not incur an adverse impact at the entity level (based on the analysis described below) even as one or
more of the individual facilities that the entity owns incur facility-level impacts. In this case, the opposite outcome
would apply: the entity would be less likely to experience an overall weakening of business performance even
though one or more of its facilities would be adversely affected by the regulation. Thus, the entity-level analysis
provides another level of assessment beyond that provided by the facility-level impact analysis.
5.6.1 Analysis Approach and Data Inputs
For the assessment of entity-level impacts, EPA performed a screening analysis, by comparing annualized after-
tax compliance costs to entity revenue and identifying the numbers of entities incurring costs in three cost-to-
revenue ranges: less than 1 percent; at least 1 percent but less than 3 percent; and 3 percent or greater. EPA
determines that entities incurring costs less than 1 percent of revenue are not likely to incur an adverse impact at
the entity level. EPA determines that entities incurring costs at least 1 percent but less than 3 percent of revenue
have a higher chance of facing an adverse impact, while entities incurring costs that are 3 percent of revenue or
greater have an even higher probability of an adverse impact.llb EPA compared total annualized after-tax
compliance costs to entity-level revenue by:
1. Identifying the parent entity,
2. Determining the parent entity revenue,
3. Estimating compliance costs at the level of the parent entity.
103 EPA did not apply the 0.1 percent threshold test for identifying whether costs would be negligible to the facility, as described above,
in this analysis. While relevant as a pre-screen in the closure and moderate impact tests, it is not relevant in this analysis since the
entity-level analysis is a cost-to-revenue analysis itself - that is, it would only screen out facilities whose cost-to-revenue values are
already very low and for which there would be no more than negligible contribution, by definition, to the entity-level cost-to-revenue
burden.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 5: Economic Impact Analyses - Manufacturers
Identifying the Parent Entity
EPA used information reported in the 316(b) survey, supplemented by research on corporate websites, to identify
parent entities.
Estimating Parent Entity Revenue
EPA obtained entity-level revenue from several sources including Dunn & Bradstreet data (D&B, 2009),
corporate websites and recent annual reports, and the 316(b) survey. Where entity-level revenue was not available
from any of these sources, EPA summed the revenue of owned facilities to the level of the entity. The Agency
restated these revenue values in 2011 dollars using BEA's GDP Deflator Index.
Estimating compliance costs at the level of the parent entity
EPA's sample-based facility analysis supports specific estimates of (1) the number of regulated facilities and (2)
the total compliance costs that these facilities would incur. However, the sample-based analysis does not support
specific estimates of the number of entities that own these facilities, or of regulated facilities that a single entity
may own, or the total of compliance costs across those facilities.
Thus, EPA estimated the number of parent entities, compliance costs at the level of the parent entity, and
associated entity-level impacts as a range based on two weighting cases. These cases provide approximate upper
and lower bound estimates of: (1) the number of entities incurring compliance costs and (2) the costs incurred by
any entity that owns a regulated facility. These cases are as follows:
> Case 1: This case assumes that all facilities represented by sample weights are owned by the same entity
that owns the sample facility; it represents a lower bound estimate of number of entities and an upper
bound estimate of total compliance costs that an entity may incur. For this case, EPA grouped together all
facilities with a common parent entity and sample-weighted the facility compliance costs using technical-
weights (see Appendix H). The Agency then calculated these costs as a percentage of entity revenue.
> Case 2: This case assumes that the facilities represented by sample weights are owned by different entities
than those that own the known sample facilities; it represents an upper bound estimate of the number of
entities that own regulated facilities, and a lower bound estimate of the total compliance costs that an
entity may incur. For this case, EPA aggregated compliance costs developed for sample facilities to the
level of their parent entity without application of facility technical weights and calculated the resulting
entity-level costs as a percentage of entity revenue. EPA then used an entity-level weighting scheme,
which is derived from facility-level sample weights, to account for parent entities that may own only
facilities that are represented by sample facilities - and thus are not directly captured under Case 1 (for
details on this entity-level weighting scheme, see Appendix H).
As discussed in Chapter 4 for Electric Generators, EPA used 2011 as the basis for the revenue and compliance
cost estimates for facilities, regardless of when they are expected to incur compliance costs to ensure that the cost
and revenue estimates used in the cost-to-revenue analysis would be consistent in terms of cost-year.
5.6.2 Key Findings
Table 5-6 summarizes the results from the entity-level impact analysis under Case 1 and Case 2. The table reports
the number of entities that EPA estimated to incur costs in three ranges: less than 1 percent of revenue, at least 1
percent but less than 3 percent of revenue, and 3 percent of revenue or greater.
Under Case 1, for the final rule, of the 120 entities that own regulated facilities, 108 incur costs less than 1 percent
of revenue, six incur costs between 1 and 3 percent of revenue, and one incurs costs greater than 3 percent of
revenue. For Proposal Option 4, 113 entities incur costs less than 1 percent of revenue, two incur costs between 1
5-14
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 5: Economic Impact Analyses - Manufacturers
and 3 percent of revenue, and no entity incurs costs greater than 3 percent revenue. The impact findings for
Proposal Option 2 are the same as those reported for the final rule.
Under Case 2, for the final rule, of the 337 entities that own regulated facilities, 319 incur costs less than 1 percent
revenue, six incur costs between 1 and 3 percent revenue, and no entity incurs costs greater than 3 percent
revenue. Under Proposal Option 4, 324 entities incur costs less than 1 percent revenue, one incurs costs between 1
and 3 percent revenue, and no entity incurs costs greater than 3 percent of revenue. The impact findings for
Proposal Option 2 are the same as those reported for the final rule. For both Case 1 and Case 2, the entity-level
impacts for the final rule are closer to Proposal Option 2 than to Proposal Option 4 because the final rule imposes
technology costs on a greater number of facilities than Proposal Option 4.
For the final rule and other options considered, the results of the entity-level analysis do not greatly differ from
the facility-level results, indicating that entities that own multiple regulated facilities do not face additional risks.
Table 5-6: Entity-Level Cost-to-Revenue Analysis Results, Final Rule- Existing Units and Other Options
Considered

Case 1:
Lower bound estimate of number of
Case 2: Upper bound estimate of number of

entities that own regulated facilities
entities that own regulated facilities

Total
Number of Entities with a Ratio of
Total
Number of Entities with a Ratio of

Number

>1% and

Number

>1% and

Industry
of Entities
<1%
<3%
>3%
Unknown3
of Entities
<1%
<3%
>3%
Unknown3
Proposal Option 4
Aluminum
4
4
0
0
0
1 1
1 1
0
0
0
Chemicals and Allied Products
30
29
0
0
1
121
117
0
0
4
Food and Kindred Products
6
6
0
0
0
20
20
0
0
0
Paper and Allied Products
37
36
0
0
1
104
101
0
0
3
Petroleum Relininsi
16
15
0
0
1
25
24
0
0
1
Steel
13
11
1
0
1
32
29
0
0
3
Xiuitipie"
4
4
0
0
0
14
14
0
0
0
Other Industries
10
8
1
0
1
10
8
1
0
1
Total0
120
113
2
0
5
337
324
1
0
12
Final Rule-Existing Units
Aluminum
4
4
0
0
0
11
1 1
0
0
0
Chemicals and Allied Products
30
27
1
1
1
121
113
4
0
4
Food and Kindred Products
6
6
0
0
0
20
20
0
0
0
Paper and Allied Products
37
34
2
0
1
104
101
0
0
3
Petroleum Relininsi
16
15
0
0
1
25
24
0
0
1
S
13
11
1
0
1
32
29
0
0
3
Xiuitipie"
4
4
0
0
0
14
14
0
0
0
Other Industries
10
7
2
0
1
10
7
2
0
1
Total0
120
108
6
1
5
337
319
6
0
12
Proposal Option 2
Aluminum
4
4
0
0
0
11
11
0
0
0
Chemicals and Allied Products
30
27
1
1
1
121
113
4
0
4
Food and Kindred Products
6
6
0
0
0
20
20
0
0
0
Paper and Allied Products
37
34
2
0
1
104
101
0
0
3
Petroleum Relininsi
16
15
0
0
1
25
24
0
0
i
Steel
13
1 1
1
0
1
32
29
0
0
3
Multiple'''
4
4
0
0
0
14
14
0
0
0
Other Industries
10
7
2
0
1
10
7
2
0
1
Total0
120
108
6
1
5
337
319
6
0
12
a. EPA was unable to determine revenues for 5 parent entities under Case 1 and for 12 parent entities under Case 2.

b. Entities designated as "multiple" own more than one facility, and those facilities belong to different manufacturing sectors. Facilities designated as
'multiple" belong either to one of the Primary Manufacturing Industries or to the Other Industries; however, they are owned by entities that own facilities in
multiple manufacturing industries.

c. Values may not sum to reported totals due to independent rounding.

Source: U.S. EPA analysis for this report

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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 5: Economic Impact Analyses - Manufacturers
5.7 Uncertainties and Limitations
The analyses of facility-level and entity-level impacts for the Manufacturers segment are subject to a range of
uncertainties and limitations, including:
> The facility-level data for these analyses are from the 316(b) survey conducted by EPA in 1999 and
reflect reporting years of 1996, 1997, 1998. Recognizing the length of time since collection of these data,
EPA adjusted facility financial data to account for changes in overall economic conditions and industry
performance from the time of the original survey to 2011 (see Appendix L). This adjustment improves the
validity of using these data for the current analyses, but introduces uncertainty, and cannot account for all
facility-level financial and overall economic/ financial changes since the time of the 316(b) survey.
> The analyses of facility-level and entity-level costs and impacts rely on data collected through the 316(b)
survey, as outlined above. The use of data from surveyed facilities to support the cost and economic
impact analysis is an appropriate and valid approach for assessing the impact of the final rule and other
options considered: the sampled facilities serve as models for assessing cost and impact across the
expected universe of regulated facilities. Inevitably, however, use of sampled facilities as the basis for the
analysis introduces uncertainty in the estimates of the number of regulated facilities and the estimates of
total costs and impacts across the regulated facility universe.
> The assessment of entity-level impacts relies on approximate upper and lower bound concepts of the
number of affected parent entities and the numbers of regulated facilities that these entities may own. In
EPA's view, the range of results from these analyses provides appropriate insight into the overall extent
of entity-level effects.
> The use of RMA data as the basis for the moderate impact thresholds provides an approximate basis for
the assessment of moderate financial impacts. As described, the RMA data are not based on a statistically
valid sample. In addition, these data may introduce bias in the quartile values, given the characteristics of
businesses that the RMA data represent. Finally, the 25th percentile value is not a perfect indicator of the
occurrence of adverse financial condition, and therefore, occurrence of adverse impact from the final rule
and other options considered. The value is indicative of weak financial condition and performance
relative to other businesses present in the RMA data, but is not an absolute indicator of financial
weakness.
> For some impact categories, this chapter presents results as a range, based on alternative assumptions of
whether all or none of the facilities with cooling water system impoundments will qualify as baseline
CCRS, and thus avoid costs - and impacts - for installation of additional technology to meet the rule's
BTA standard for impingement mortality. The range of results thus reflects uncertainty over the effect of
the final rule's impoundments provision.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
6 Impacts of the Final Rule in the Context of National and Regional
Electricity Markets
In analyzing the impacts of various regulatory actions affecting the electric power sector over the last decade,
EPA has used the Integrated Planning Model (IPM®), a comprehensive electricity market optimization model that
can evaluate such impacts within the context of regional and national electricity markets.1"4'105 To assess facility-
and market-level effects of the final rule, EPA used an updated platform of this same analytic system: Integrated
Planning Model Version 4.10 MATS (IPM V4.10_MATS) (U.S. EPA, 2010b; U.S. EPA, 2013), the specifications
of which are summarized in Appendix P: Overview of the Integrated Planning Model.1"6 EPA did not conduct
electricity market analysis of either Proposal Option 4 or Proposal Option 2 using the IPM V4.10 MATS
platform. To the extent that Proposal Option 4 would result in lower compliance costs to facilities compared to
those estimated for the final rule (see Chapter 3: Compliance Costs), it is likely to result in smaller impacts on
national and regional electricity markets compared to impacts estimated for the final rule. To the extent that under
Proposal Option 2 facilities would incur higher compliance costs, undergo longer technology-installation
downtime, and require additional energy to run compliance technologies compared to the final rule, Proposal
Option 2 would have greater impacts on national and regional electricity markets compared to impacts of the final
rule. For the results of the electricity market analysis conducted for Proposal Option 2, referred to as Market
Model Analysis Option 2 in the context of that analysis, see Economic and Benefits Analysis for Proposed Section
316(b) Existing Facilities Rule (Proposal EBA) (EPA 821-R-l 1-001). EPA did not conduct an electricity market
analysis of Proposal Option 4 in support of the proposed rule.1"7
Also, the electricity market analysis for the final rule assumes that none of the facilities with a cooling water
system impoundment will qualify as baseline CCRS, and therefore may require installation of additional
compliance technology to meet the final rule's BTA performance standards. In this regard, the findings presented
in this chapter differ from those presented in Chapter 3: Compliance Costs, which assume that all of the facilities
with a cooling water system impoundment qualify as baseline CCRS. Similarly, the findings in this chapter
correspond to the upper range of impact values for Electric Generators, as presented in Chapter 4: Economic
Impact Analysis - Electric Generators, which assume that none of the facilities with an impoundment qualify as
baseline CCRS. As a result, the analysis presented in this chapter may overstate the impact of the final rule in
terms of total cost incurred, reduced utilization of Electric Generators, capacity closures, and downtime impact.
104 Specifically, EPA used IPM for the Section 316(b) Phase II regulations, the Proposed Section 316(b) Existing Facilities Rale, the
Proposed Effluent Guidelines for the Steam Electric Power Generating Category, and numerous Clean Air Act regulatory actions.
105 EPA reviewed a number of electricity market models for potential use in analyzing the impact of the 316(b) Phase II regulation in its
analyses for the suspended 2004 Phase II Rule. At that time, EPA concluded that IPM represented the best choice for 316(b) rule
analyses considering a number of factors: ability to receive and account for as inputs, the cost and operating effect specifications of the
316(b) regulation; ability to assess the impact of 316(b) regulatory requirements on capacity dispatch and utilization, capacity
planning and management (i.e., capacity expansion, modifications, and retirements), and electricity production costs and prices; level
of documentation and acceptance of the models for use in analyzing electricity market impacts of environmental regulations; ability to
incorporate other environmental regulatory actions in the baseline analysis; ability to incorporate EPA preferences in terms of
adjustments to the baseline electricity demand forecasts built into the model; and cost of model usage. On the basis of this prior model
review and selection process, EPA decided to rely again on IPM for the analyses of the existing facilities rule.
100 For more information on IPM, see http://www.epa.gov/airmarkets/progsregs/epa-ipm/toxics.html.
107 While the Market Model Analysis Option 2 analyzed as part of the Electricity Market Analysis is not identical to Proposal Option 2,
analyzed as part of other cost and economic analyses conducted in support of the Proposed Section 316(b) Existing Facilities Rule
(proposed rule), the two options align closely. Hie main difference is in the number of facilities analyzed; specifically, the IPM
platform used in the analysis of proposed rule included 533 of the 559 explicitly and implicitly analyzed regulated facilities, For
details see Proposal EBA report.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
The electricity market analysis is a more comprehensive analysis compared to the screening-level analyses
discussed in Chapter 4: Economic Impact Analyses - Electric Generators. In contrast to the screening-level
analyses, which are static analyses and do not account for interdependence of electric generating units in
supplying power to the electric transmission grid, IPM accounts for potential changes in the generation profile of
electric generating units and consequent changes in market-level generation costs, as the electric power market
responds to higher generation costs for electric power facilities subject to the final rule. IPM is also dynamic in
that it is capable of using forecasts of future conditions to make decisions for the present. Additionally, in contrast
to the screening-level analyses in which EPA assumed no pass-through of compliance costs, IPM depicts
production activity in competitive wholesale electricity markets where some recovery of compliance costs
through increased electricity prices is possible but not guaranteed. Finally, IPM incorporates electricity demand
growth assumptions from the Department of Energy's (DOE) Annual Energy Outlook 2010 (AEO2010), whereas
the screening-level analyses discussed in other chapters of this document assume that facilities would generate
approximately the same quantity of electricity after promulgation of the final rule as they did on average during
2007-2011.
Increases in electricity production costs and potential reductions in electricity output at regulated facilities can
have a range of market impacts that extend beyond the effect on regulated facilities. In addition, the impact of
compliance requirements on regulated facilities may be seen differently when the analysis considers the impact on
those facilities in the context of the broader electricity market instead of looking at the impact on a stand-alone,
single-facility basis. Therefore, use of a comprehensive, electricity market modeling system that accounts for
interdependence of electric generating units, is important in analyzing regulatory impacts on the electric power
industry as a whole.
EPA's use of IPM for this analysis is consistent with the intended use of the model to evaluate the effects of
changes on electricity production costs, on electricity generation costs, subject to specified demand and emissions
constraints. As discussed in greater detail in Appendix P, IPM generates least-cost resource dispatch decisions
based on user-specified constraints such as environmental, demand, and other operational constraints. The model
can be used to analyze a wide range of electric power market questions at the facility, regional, and national
levels. In the past, applications of IPM have included capacity planning, environmental policy analysis and
compliance planning, wholesale price forecasting, and asset valuation.
IPM uses a long-term dynamic linear programming framework that simulates the dispatch of generating capacity
to achieve a demand-supply equilibrium on a seasonal basis and by region. The model seeks the optimal solution
to an "objective function," which is the summation of all the costs incurred by the electric power sector, i.e.,
capital costs, fixed and variable operation and maintenance (O&M) costs, and fuel costs, over the entire evaluated
time horizon. The objective function is minimized subject to a series of supply and demand constraints. Supply-
side constraints include capacity constraints, availability of generation resources, generating unit minimum
operating constraints, transmission constraints, and environmental constraints. Demand-side constraints include
reserve margin constraints and minimum system-wide load requirements.
As done for the previous section 316(b) regulatory analyses, in analyzing the final rule, EPA first specified
additional fixed and variable costs that EPA expects regulated facilities will incur to comply with the final rule.
EPA then ran IPM to determine the dispatch of electric generating units that will meet projected demand at the
lowest costs, subject to the same constraints as those present in the analysis baseline.
This chapter is organized as follows:
> Section 6.1 summarizes the key inputs to IPM for performing the electricity market analysis of the final
rule and the key outputs reviewed as indicators of the regulatory effect.
> Section 6.2 describes how the option analyzed in the context of the electricity market analysis differs from
the final rule discussed elsewhere in this document.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
> Section 6.3 provides the findings from the electricity market analysis.
> Section 6.4 identifies key uncertainties and limitations in the electricity market analysis.
6.1 Model Analysis Inputs and Outputs
To assess the impact of the final rule, EPA compared the policy case projections to the IPM baseline (i.e., pre-
policy) case projections of the modeled electricity market behavior.
6.1.1 Analysis Years
As discussed in Appendix P, the IPM V4.10_MATS platform models the electric power market over the 43-year
period from 2012 to 2054. Within this total analysis period, EPA looked at shorter IPM analysis periods (run-year
windows)1"8 to assess the market-level effect of the final rule. To assess the impact of the final rule during the
period when regulated facilities temporarily suspend their operation to install compliance technologies - the
short-term effects analysis or the downtime effects analysis - EPA used results reported for the 2020 IPM run
year. As discussed in Chapter 3: Compliance Costs, for the cost and economic impact analyses, EPA assumed
that Electric Generators will install IM technologies during the 5-year window of 2018 through 2022. Because
this technology-installation window falls within the time period captured by the 2020 run year (i.e., 2017-2024),
EPA determined that 2020 is an appropriate year to capture the effects of technology-installation downtime. The
incurrence of downtime may lead to higher electricity generation costs overall, as generating units at regulated
facilities are taken out of service to complete technology installation and other, presumably higher production cost
generating units are dispatched to meet electricity demand. Because of the potential resulting increase in
electricity generations costs, it is important to examine market-level effects during the period in which downtime
would occur.
To assess the longer term effect of the final rule on electricity markets during the period after compliance
technology is installed at all regulated facilities - the steady-state post-compliance period - EPA analyzed results
reported for the IPM 2030 run year.1"9 EPA expects this steady-state period to begin in the last year of the
technology-installation window, i.e., 2022, and continue into the future. The 2022 analysis year is captured in the
IPM 2020 run year, as opposed to the 2030 run year. However, because all analysis years represented by the 2030
run year (i.e., 2025-2034) fall outside the technology-installation window of 2018 through 2022, EPA determined
that 2030 is an appropriate year to capture longer term, steady-state effects of the final rule. Effects that may
occur during this steady-state period include potential permanent losses in generating capacity from early
retirement (closure) of generating units and the consequent need to dispatch other, potentially higher production
cost, generating units to offset these capacity losses, and long-term increases in overall electricity generation costs
due to higher operating expenses at regulated facilities.11"
108 Due to the highly data- and calculation-intensive computational procedures required for the IPM dynamic optimization algorithm,
IPM is run only for a limited number of years. Run years are selected based on analytical requirements and the necessity to maintain a
balanced choice of run years throughout the modeled time horizon. Each rim year represents other adjacent years in addition to the run
year itself.
109 The 2020 rim year accounts for costs recognized within the period of 2017-2024. Some administrative costs start after 2024. By the
2030 run year, all facilities have recognized all one-time cost outlays, and as well have begun incurring annually and non-annually
recurring costs that begin after the technology installation period.
110 In seeking to minimize the cost of meeting electricity demand, IPM will tend to shift production away from regulated facilities that
incur higher compliance costs, either to regulated facilities that incur relatively lower compliance costs or to non-regulated facilities,
which incur no compliance costs. Any of these changes - whether a simple increase in production costs for previously dispatched
units or changes hi the profile of generating unit dispatch - mean hicreased total costs for electricity generation, compared to the pre-
regulation baseline.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
EPA expects the increase in electricity production costs observed during the steady-state post-compliance period
to be less than that during the period of technology-installation downtime. Specifically, during the downtime
period, capacity losses include both the temporary losses during technology installation and permanent losses
from early capacity retirement. In contrast, during the steady-state post-compliance period, capacity losses would
result only from early retirements.
The two run years - 2020 and 2030 - provide different views of the industry over time, accounting for changes in
electricity demand and generation mix, and for the effects of compliance with other regulatory requirements
imbedded in the IPM V4.10_MATS platform.
6.1.2 Key IPM Inputs for the Electricity Market Analysis of the Final Rule
Existing Units at Existing Facilities
For existing units at existing facilities, the inputs for the electricity market analyses include compliance costs,
technology-installation year, and cost-incurrence year. IPM models 520 of the 532 currently non-retired facilities
that responded to the 316(b) survey (for details see Appendix H: Sample Weights and Appendix P).
These input cost categories are as follows:
> Capital cost inputs, which include the cost of compliance technology equipment, construction, and other
upfront, non-annually recurring outlays associated with compliance with the final rule. Capital costs were
specified in terms of the expected useful service life of the capital outlay. Compliance technologies
considered under the final rule are assumed to have a useful life of either 20, 25, or 30 years.
In the electricity market analysis, these outlays were converted into a constant annual charge using IPM's
conventional frameworks for recognition of capital outlays over the useful life of the technology.
> Annual Fixed O&M cost inputs were expressed in dollars per kilowatt (kW) of capacity per year.
> Annual Variable O&M cost inputs were expressed in dollars per kilowatt hour (kWh) of generation. As
described in Chapter 3, for the final rule these costs also include additional auxiliary energy required to
operate some IM technologies.
> Permitting cost inputs consist of start-up administrative costs, initial permitting costs, annual monitoring,
reporting, and recordkeeping costs, and non-annually recurring administrative costs. For the purpose of
the electricity market analysis, permitting cost inputs were expressed as follows:
¦ Start-up administrative activities occur every five years; for the IPM analysis, costs associated with
these activities were annualized over five years and expressed in dollars per kW of capacity.
¦ Initial permitting activities occur only once and are necessary for the on-going operation of the
facility; for the IPM analysis, costs associated with these activities were annualized over the life of
the IPM analysis (43 years) and expressed in dollars per kW of capacity.
¦ Annual monitoring, reporting, and recordkeeping activities occur every year starting in the year of
technology installation; for the IPM analysis, costs associated with these activities were expressed in
dollars per kW of capacity.
¦ Non-annually recurring administrative activities associated with permit renewal application begin 10
years after the initial permitting activities begin and recur every five years after that;111 for the IPM
111 These activities include a subset of initial permitting activities that repeat periodically in the future. While under the final rule these
application activities are required every permit cycle, Permit Directors will likely not require facilities to undertake them as soon as
the second permit cycle after the initial compliance with regulatory requirements. Consequently, EPA assumed that all of these
activities will begin 10 years after the initial permitting activities begin, i.e., during the third post-compliance permit cycle, and recur
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
analysis, costs associated with these activities were annualized over five years and expressed in
dollars per kW of capacity.
> Installation downtime capacity reductions enter the analysis as a designated time period during which
affected generating units are taken out of service for installation of compliance technology. Technology-
installation downtime values are expressed in the number of weeks, and are estimated and applied in the
analysis, as the additional downtime beyond normally scheduled downtime for affected generating units
(see Chapter 3). That is, facility operators are assumed to schedule downtime for 316(b) compliance in
conjunction with ordinary scheduled downtime; the effect of 316(b) compliance downtime on electricity
markets thus results only from the extension of downtime beyond the ordinary scheduled downtime. EPA
assumes that installation downtime will occur in the year in which a facility complies with the final rule.
In the IPM analysis, the technology-installation downtime for each affected generating unit is spread
uniformly over the eight years (2017 through 2024) represented by the 2020 run year, i.e., the run year
that EPA used to assess downtime impact.112
In addition to specifying these cost elements, the IPM assigns a cost-incurrence year to each facility. As discussed
in Chapter 3, EPA assumed that regulated facilities will install required compliance technologies during the 5-
year period of 2018 through 2022.113 The technology-installation year is also the downtime year and also the first
year when facilities start incurring O&M costs and costs associated with annual monitoring, and reporting and
recordkeeping activities. Facilities incur costs associated with initial permitting activities in specific years prior to
the technology-installation year; non-annually recurring administrative costs then recur according to the schedule
outlined above following technology installation. Finally, regulated facilities begin to incur costs associated with
start-up administrative activities in the first year after rule promulgation.
Because the electricity market analysis is performed at the level of the individual boiler and/or generating unit,
EPA had to allocate facility-level costs to boilers/generating units. EPA followed an approach similar to that used
in the previous section 316(b) regulatory analyses. Specifically, EPA allocated facility-level costs across all
affected steam generating units (boilers and generators) using allocation factors developed based either on steam
generating capacity from IPM or on boiler-level water flow data from 2005 EIA-767.114 For facilities with
available design intake flow data, this distribution was based on each affected generating unit's proportion of total
design intake flow; for facilities without available design intake flow, this distribution was based on each
generating unit's proportion of total steam electric capacity. Generator-level compliance costs were aggregated to
the boiler level (for use in IPM) based on the boiler-generator crosswalk contained in the IPM baseline datasets.
IPM modelers used the inputs above to calculate the net present value of annualized costs using IPM's
conventional framework for recognizing costs incurred overtime.115
every five years after that. EPA estimates that only 10 percent of regulated facilities would undertake these non-annually recurring
activities.
112 This required treatment is an artifact of the way in which IPM performs analysis using single model run-years to represent the effect
over a specified range of years. One-eighth of the downtime value is assigned to each year in the 8-year period of 2017-2024.
113 EPA obtained information on NPDES permit renewals from either the steam electric industry survey, the Water Permit Compliance
System (PCS), or the Integrated Compliance Information Systems - National Pollutant Discharge Elimination System (ICIS-NPDES).
114 The latest year for which EIA flow data are available is 2005.
115 IPM seeks to minimize the total, discounted net present value - as facilities and firms would likely do - of the costs of meeting
demand, accounting for power operation constraints, and environmental regulations over the entire planning horizon. These costs
include the cost of any new generating capacity, pollution control construction, fixed and variable operating and maintenance costs,
and fuel costs. As described in the IPM documentation, "capital costs in IPM's objective function are represented as the net present
value oflevelized stream of annual capital outlays, not as a one-time total investment cost. The payment period used in calculating the
levelized annual outlays never extends beyond the model's planning horizon: it is either the book life of the investment or the years
remaining in the planning horizon, whichever is shorter. This treatment of capital costs ensures both realism and consistency in
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Chapter 6: Electricity Market Analysis
New Units at Existing Facilities
Under the final rule, generating units that meet the definition of a new unit, i.e., newly built, stand-alone units at
existing facilities, whose construction begins after the effective date of the rule, will be required to install closed-
cycle recirculating system (CCRS) technology (i.e., cooling towers). For the cost and economic impact analysis,
EPA assumed that it would take approximately four years to construct a new unit and install a cooling tower;
therefore, the Agency assumed that 2017 will be the first year when any new unit subject to the final rule will
come online and begin cooling tower operation after promulgation. Compliance costs for these new units include
capital costs, annual fixed and variable O&M costs, auxiliary energy requirement, start-up administrative costs,
initial permitting costs, and costs associated with annual monitoring, reporting, and recordkeeping activities (for
details see Chapter 3). For the IPM analysis, EPA expressed fixed and variable O&M, initial permitting, and
annual monitoring, reporting, and recordkeeping costs in the same way as that described earlier for existing units
at existing facilities - i.e., in dollars per kW or kWh - and expressed capital cost in dollars per kW. Because EPA
anticipates start-up administrative activities for new units to occur only once during the first year after rule
promulgation, for IPM analysis EPA annualized this cost over the life of IPM analysis, i.e., 43 years. EPA
annualized capital costs over 30 years, i.e., the assumed performance life of a cooling tower. Unlike the case with
existing units, for new units, EPA analyzed the auxiliary energy requirement as a reduced net saleable generating
output from the affected unit due to energy required to operate cooling towers. The IPM analysis accounts for this
requirement as a reduction in generating capacity.
6.1.3 Key Outputs of the Electricity Market Analysis Used to Assess the Effects of the Final
Rule
The IPM V4.10_MATS platform provides outputs for the NERC regions that lie within the continental United
States. As described in Appendix P, the IPM V4.10_MATS platform does not analyze electric power operations in
Alaska and Hawaii because these states" electric power operations are not interconnected to the continental U.S.
power grid.
IPM generates a series of outputs at different levels of aggregation (model plant,116 region, and nation). EPA used
a subset of the available IPM outputs to assess the cost and economic impact of the final rule on electricity
markets. For each model run (baseline case and policy case) and for the run years indicated above, the following
model outputs were generated:
> Capacity - Capacity is a measure of the ability to generate electricity. This output measure reflects the
summer net dependable capacity of all generating units at the facility. The model differentiates between
existing capacity, which is associated with existing generating units and new capacity additions, which
are not associated with any specific existing or new generating units.117
> Early Retirements - IPM models two types of facility closures: closures of nuclear facilities as a result of
license expiration and economic closures as a result of negative net present value of future operation. This
analysis considers only economic closures as the result of the final rule.
> Energy> Price - The average annual wholesale electricity price received for the sale of electricity.
accounting for the full cost of each of the investment options in the model. The cost components appearing in IPM's objective function
represent the composite cost over all years in the planning horizon rather than just the cost in the individual model run years. This
permits the model to capture more accurately the escalation of the cost components over time." (Chapter 2 in U.S. EPA, 2010b)
110 EPA uses the term facility throughout the EA to refer to individual regulated facilities, including power plants. However, there are
instances where this chapter refers to IPM model and documentation terminology, such as model plant. In these instances, this chapter
uses the IPM terminology - i.e.., plant instead offacility.
117 While IPM does model building new capacity if new capacity is the cheapest way to meet electricity demand, it does not specify
whether this new capacity is associated with new units at existing facilities or new facilities.
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> Capacity Price - The premium over energy prices received by facilities operating in peak hours during
which system load approaches available capacity; capacity price is part of the total wholesale electricity
price. The capacity price is the premium required to stimulate new market entrants to construct additional
capacity, cover costs, and earn a return on their investment. This price manifests as short term price spikes
during peak hours and, in long-run equilibrium, need be only so large as is required to justify investment
in new capacity.
> Generation - The amount of electricity produced by each generating units that is available for dispatch to
the transmission grid ("net generation"). IPM provides summer, winter, and total annual generation.
> Fuel Costs - The cost of fuel consumed in the generation of electricity. IPM provides summer, winter,
and total annual fuel costs.
> Variable Operation and Maintenance (VOM) Costs - Non-fuel O&M costs that vary with the level of
generation, e.g., cost of consumables, including water, lubricants, and electricity. IPM provides summer,
winter, and total annual VOM costs. In the policy case, variable O&M costs also include the variable
share of the costs of compliance with the final rule.
> Fixed Operation and Maintenance (FOM) Costs - O&M costs that do not vary with the level of
generation, e.g., labor costs and capital expenditures for maintenance. In the policy case, fixed O&M
costs also include the fixed share of the final rule compliance costs, annualized capital costs, start-up
administrative costs, initial permitting costs, and non-annually recurring administrative costs.
> Capital Costs - The cost of construction, equipment, and capital. Capital costs include costs associated
with investment in new equipment, e.g., the replacement of a boiler or condenser, installation of
technologies to meet various regulatory requirements.
> Air Emissions - IPM models carbon dioxide (C02), nitrogen oxide (NOx), sulfur dioxide (S02), and
mercury (Hg) emissions resulting from electricity generation.
Comparison of these outputs for the baseline and policy cases provides insight into the effect of the final rule on
regulated facilities and broader electricity markets.118
In interpreting the results from the electricity market analysis, EPA considered the findings from Chapter 4:
Economic Impact Analyses - Electric Generators concerning whether compliance costs would be negligible at the
level of the facility - that is, whether annualized compliance cost would be below 0.1 percent of facility revenue.
This would indicate that costs are negligible.119 Costs at 0.1 percent of revenue or higher would indicate that costs
are not negligible. As described in Chapter 4 and Chapter 5: Economic Impact Analyses - Manufacturers, for
facilities with estimated compliance costs that are less than 0.1 percent of revenue, EPA reached a presumptive
finding that costs are so slight in relation to the overall scale of business activity, measured by facility revenue, as
to be negligible in terms of potential adverse impact. In the case of the Manufacturers impact analysis, EPA set
those facilities aside in performing the severe impact analysis (i.e., closure) and moderate financial impact
analyses. However, for the corresponding impact analyses undertaken for Electric Generators - namely the
118 IPM output also includes total fuel usage, which is not part of the analysis discussed in this chapter. However, data on fuel
consumption are analyzed as part of the analysis that EPA conducted to meet the requirements of the Executive Order 13211: Actions
Concerning Regulations That Significantly Affect Energy Supply, Distribution, or Use. This analysis is discussed in Chapter 12: Other
Administrative Requirements.
119 As described in Chapter 4, facilities that would go from positive to negative discounted cash flow value due to the final rule are in
poor financial health, but the 0.1 percent threshold separates the facilities that have a much higher possibility of salvaging their
situation from those with a lower probability. That is, the regulation is more likely to spur facilities with a compliance cost-to-revenue
value of less than 0.1 percent to seek and successfully implement cost-cutting measures or revenue enhancements compared to those
facilities with a cost-to-revenue value above 0.1 percent, for which such a strategy has lower probability of success. Also, local
governments may be more likely to provide tax benefits to avoid closure in cases where regulatory costs are negligible.
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Chapter 6: Electricity Market Analysis
electricity market analysis presented in this chapter, which also tests for the occurrence of closures - it would not
be appropriate to remove the facilities with negligible compliance costs from the electricity market analysis.
Unlike the Manufacturers impact analyses, which are performed for individual facilities without considering a
total market effect, the electricity market analysis is performed in the context of the total market and requires that
all facilities and their estimated compliance costs and associated operating effects (e.g., installation downtime and
energy penalty, as applicable) be accounted for in the analysis - regardless of the level of the cost. Accordingly,
EPA kept all facilities in the analysis regardless of whether the 0.1 percent negligibility threshold is exceeded, and
evaluated the findings from the electricity market analysis in the context of the findings from Chapter 4.
An additional consideration involves the fact that EPA could account for the 0.1 percent negligibility threshold in
evaluating the electricity market analysis results only for the Detailed Questionnaire (DQ) facilities for which
EPA developed cost estimates for impact analyses conducted for Electric Generators as reported in Chapter 4.
Specifically, of the 520 regulated facilities that are included in the electricity market analysis (see page 6-4), 221
are analyzed on a non-sample-weighted basis in the cost and economic impact analyses discussed in Chapter 4;
the remaining 299 facilities in the electricity market analysis (which are Short Technical Questionnaire (STQ)
facilities) are accounted for in the analyses conduced for Electric Generators and discussed in Chapter 4 through
use of sample weights.120 This means that the evaluation of electricity market analysis results in the context of the
0.1-percent negligibility threshold applies to 221 of the 520 facilities in the electricity market analysis. EPA
provides this evaluation of electricity market analysis results as part of the discussion of Impact on Individual
Regulated Facilities, in Section 6.3.1.
6.2 Regulatory Options Analyzed
As stated above, for the electricity market analysis for the final rule, EPA analyzed only the provisions of the final
rule and did not undertake electricity market analysis for the other regulatory options that are discussed elsewhere
in this document. EPA had performed electricity market analysis for other regulatory options in its analysis for the
proposed rule. Given that the other regulatory options EPA considered at proposal differ little from the options
EPA analyzed in developing the final rule, EPA decided that it would not gain new insights from re-analyzing
these options for the final rule - in particular, insights that would alter its determinations regarding the final rule.
Given the significant expense for completing the electricity market analysis for additional options and the
expectation that the Agency would not gain new insights that would cause it to alter the regulation, EPA therefore
decided not to run IPM for other regulatory options. EPA did decide to undertake electricity market analysis for
the final rule (or as described below, regulatory requirements that align very closely with the final rule) to confirm
its determinations regarding the expected effects of the final rule in the context of electricity markets. As expected
and as documented in the later sections of this chapter, EPA did not find substantial adverse impacts from the
final rule. This overall finding matches the findings from the electricity market analysis conducted for Option 1 in
support of the proposed rule (referred to as Market Model Analysis Option 1 in the context of that analysis) that
very closely aligns with the final rule.
The final rule requirements as specified for the electricity market analysis, and the way in which IPM is able to
simulate these requirements, align closely with the actual specifications of the existing and new unit provisions of
the final rule, and with how EPA expects the final rule to affect the regulated units and the electricity market,
overall. However, there are slight differences, which are described below. As discussed below, the final rule
requirements analyzed in the context of electricity market analysis differ slightly from the actual final rule
requirements analyzed and discussed elsewhere in this document. To distinguish between the two sets of final rule
requirements, EPA refers to the final rule requirements analyzed as part of the electricity market analysis as The
Electricity Market Analysis - Final Rule.
120 See Appendix H: Use of Sample Weights in the Final Rule Analyses, for details of the DQ facilities and how EPA analyzed these
facilities and the Short Technical Questionnaire facilities in the Electric Generators impact analysis.
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Chapter 6: Electricity Market Analysis
Existing Units at Existing Facilities
For existing units at existing facilities, aside from the difference in the analyzed universe of regulated facilities
discussed above and in Appendix P.121 the analyzed Electricity Market Analysis - Final Rule embeds higher
administrative and technology requirements and associated costs compared to those specified for the final rule and
discussed elsewhere in this document (19 percent and 15 percent higher, respectively, over all regulated facilities).
As a result, the total regulatory cost for existing units as reflected in the Electricity Market Analysis - Final Rule
is 15 percent higher than the estimated cost of the existing unit provision of the final rule.122 EPA made these
changes to the administrative and technology requirements of the final rule after the IPM run had been initiated;
to the extent that the Electricity Market Analysis - Final Rule embeds higher compliance costs, the impact of the
final rule, as reflected in the findings of this analysis, may be overstated. In addition, as described earlier in this
chapter, the electricity market analysis assumes that none of the facilities with cooling water system
impoundments will qualify as baseline CCRS. This assumption also leads to likely overstatement of impacts, at
all levels of the market model analysis.
New Units at Existing Facilities
As described in Chapter 1: Introduction, under the new unit provision of the final rule, construction of new,
stand-alone fossil fuel and combined cycle units are considered new units under the final rule and are required to
achieve entrainment control technology performance equivalent to the intake flow levels that would be achieved
by a CCRS.123
Not all new coal steam and combined cycle capacity coming online during the IPM analysis period will be subject
to the new unit provision of the final rule; to the extent that some of this capacity is associated with new units at
new facilities, it will be subject to the 316(b) Phase I rule for cooling water intake structures at new facilities. In
addition, some new capacity that is not subject to the Phase I rule will also not meet the definition of new capacity
to which the final rule's new unit provision applies - namely, new, stand-alone generating capacity. In the IPM
analysis, it is not possible to determine either the share or the location of the new generating capacity projected by
IPM that will be subject to the final rule's new unit provision. In view of this limitation, EPA accounted for the
fact that not all new IPM capacity would be subject to the final rule by assigning a fraction of compliance costs to
all new combined cycle and coal steam capacity coming online during the IPM analysis period. EPA used the
estimated fraction of new capacity installations that would be subject to the requirements of the final rule for this
adjustment.124
As described above for the existing unit provision of the final rule, the Electricity Market Analysis - Final Rule
also embeds higher administrative and technology requirements and associated costs for the new units at existing
facilities compared to those anticipated under the new unit provision of the final rule. EPA has determined that
this cost difference is too small to materially affect the findings of the electricity market analysis. Further, to the
extent that the compliance costs used in this analysis are higher compared to those of the new unit provision of the
final rule, the impact of the final rule, as reflected in the findings of this analysis, may be overstated.
121 Specifically, the IPM V4.10_MATS platform includes 520 of the 544 electric power facilities subject to the final rule. Facilities
excluded from the IPM analysis include three facilities in Hawaii and one facility in Alaska (i.e., areas that are outside the geographic
scope of the model), four on-site facilities that are not connected to the integrated electric transmission grid, four facilities excluded
from the IPM baseline as the result of custom adjustments made by ICF International, and 12 facilities that did not respond to the
316(b) survey (see Appendix H: Sample Weights).
122 EPA made this calculation using annualized costs as calculated with the methodology outlined in Chapter 3.
123 See Chapters 1 and 4 for additional detail on the new unit provision of the final rule.
124 For details on how EPA estimated total new capacity and capacity subject to Phase I requirements and the final rule requirements as
well as the details on development of compliance costs for new units, see Memorandum to the Record, Repowering and 316(b), dated
March 9, 2011, DCN 10-6634.
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Chapter 6: Electricity Market Analysis
6.3 Findings from the Electricity Market Analysis
The impacts of the Electricity Market Analysis - Final Rule are analyzed as the difference between key economic
and operational impact metrics that compare the policy case to the baseline case. This section presents two sets of
analysis:
> Analysis of long-term regulatory impacts (steady-state impact analysis): As discussed earlier, EPA
analyzed the long-term impact of the final rule by comparing baseline and policy run results reported for
2030. These results provide insight on the effect of the final rule during the steady-state period of post-
compliance operations. The Agency conducted the long-term impact analysis for the entire electricity
market and for the group of regulated facilities (Section 6.3.1).
> Analysis of short-term regulatory impacts (downtime impact analysis): EPA also presents a subset of
results for the 2020 model run year, which captures regulatory impacts during the transition to compliance
with the rule. The Agency conducted this analysis for the entire electricity market (Section 6.3.2).
6.3.1 Analysis Results for the Year 2030 - To Reflect Steady-State, Post-Compliance
Operations
In these results, which reflect conditions in the period of 2025 through 2034, all facilities are expected to be in
compliance with the final rule. EPA considered impact metrics of interest at three levels of aggregation:
> Impact on national and regional electricity markets,
> Impact on regulated facilities as a group, and
> Impact on individual regulated facilities.
Impact on National and Regional Electricity Markets
The market-level analysis assesses national and regional changes as a result of the requirements of the Electricity
Market Analysis - Final Rule. The following five measures are analyzed:
> Changes in available capacity: This measure analyzes changes in the capacity available to generate
electricity. A long-term reduction in available capacity may result from partial or full closures of electric
power facilities. For this impact measure, EPA distinguished between existing capacity and new capacity
additions and also analyzed capacity closures. Only capacity that is projected to remain operational in the
baseline case but is closed in the policy case is considered a closure attributable to the final rule. The
electricity market analysis may project partial facility closures with some, but not all, generating units at a
given facility retiring or full facility closures with all generating units at a given facility retiring. This
analysis may also project avoided closures when generating units estimated to retire in the baseline case
continue to operate in the policy case. Avoided closures may occur among facilities that incur no
compliance costs under the final rule or for which compliance costs are low relative to other regulated
facilities.
> Changes in the price of electricity: This measure considers changes in regional wholesale electricity
prices - the sum of energy and capacity prices - as a result of the final rule. In the long term, electricity
prices may change as a result of increased generation costs at regulated facilities or due to generating unit
closures. For this analysis, EPA combined both components of the estimated electricity price - i.e.,
energy price and capacity price - into a single energy-unit equivalent price (i.e., $/MWh of energy).125
125 Note that while electricity prices are often reported in cents per kWh of energy (0/kWh), electricity prices presented and discussed in
this chapter are reported in dollars per MWh of energy ($/MWh) to be consistent with other values reported from IPM on a per MW or
per MWh basis.
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> Changes in generation: This measure considers the amount of electricity generated. At a regional level,
long-term changes in generation may result from generating unit retirements or a change in the amount of
electricity traded between regions. At the national level, the demand for electricity does not change
between the baseline case and the policy case (generation within the regions is allowed to vary) because
meeting demand is an exogenous constraint imposed by the model. For this reason, the main effects EPA
expects to observe are changes in price. However, demand for electricity does vary across the modeling
horizon according to the model's underlying electricity demand growth assumptions.
> Changes in costs: This measure considers changes in the overall cost of generating electricity, including
fuel costs, variable and fixed O&M costs, and capital costs. Fuel costs and variable O&M costs are
production costs that vary with the level of generation. Fuel costs generally account for the single largest
share of production costs. Fixed O&M costs and capital costs do not vary with generation. They are fixed
in the short term and therefore do not affect the dispatch decision of a unit (given sufficient demand, a
unit will dispatch as long as the price of electricity is at least equal to its per MWh production costs).
However, in the long run, these costs need to be recovered for a unit to remain economically viable.
> Changes in variable production costs per MWh: This measure considers the change in average variable
production cost per MWh of generated electricity. Variable production costs include fuel costs and other
variable O&M costs but exclude fixed O&M costs and capital costs. Production cost per MWh is a
primary determinant of how often a generating unit is dispatched. This measure presents information
similar to total fuel and variable O&M costs, but normalized for changes in generation.
> Changes in C02, NOx, S02, and Hg emissions: This measure considers the change in emissions from
electricity generation, for example, due to changes in the fuel mix. Compliance with the final rule may
lead to higher generation costs and make electricity generated by some units at regulated facilities more
expensive compared to that generated at other generating units. These changes may in turn result in
changes in air pollutant emissions, depending on the emissions profile of dispatched units.
Table 6-1 summarizes IPM results for the Electricity Market Analysis - Final Rule at the level of the national
market and also by North American Electric Reliability Corporation (NERC) region. All of the impact metrics
described above are reported at both the national and NERC level except wholesale electricity prices, which are
calculated in IPM only at the regional level.
As reported in Table 6-1, this analysis indicates that the option considered in this analysis - Electricity Market
Analysis - Final Rule - will have small effects on the electricity market, on both the national and regional sub-
market basis, in 2030. This analysis also shows that Electricity Market Analysis - Final Rule is not likely to
impede construction of new combined cycle and coal steam generating units.
Overall at the national level, the net change in total capacity, including reductions in capacity due to early
retirements and capacity additions at new facilities/units, is essentially zero. Consequently, the Electricity Market
Analysis - Final Rule is not expected to have a material ongoing effect on capacity availability and supply
reliability at the national level. At the NERC region level, four of the eight analyzed NERC regions record nearly
no change in capacity, three regions record non-consequential capacity losses, with the largest loss, 0.7 percent,
occurring in the TRE region; one region - SPP - records a modest capacity increase of 1.5 percent.
At the national level, the analysis shows a total net increase in retired capacity of approximately 1 GW, or less
than 0.1 percent of the total baseline capacity in 2030 (capacity retirements are discussed in greater detail in the
next section Impact on Regulated Facilities as a Group). This 1 GW of net capacity loss reflects a combination of
closures and avoided closures of generating units (as described above). Overall, the IPM analysis indicates that
the final rule will lead to early retirement of approximately 4 GW of generating capacity and approximately 3 GW
of avoided closure of capacity otherwise projected to retire by 2030, resulting in net closure of approximately 1
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GW of generating capacity, or less than 0.1 percent of the total baseline capacity in 2030. With only one
exception, these retirements involve older, less efficient generating units with very low capacity utilization rates.
Five of the eight analyzed NERC regions record modest increases in retired capacity, with the largest increase, 0.8
percent of baseline retired capacity, projected to occur in the TRE region. One NERC region - SPP - is estimated
to experience avoided capacity closures, where 1.5 percent of capacity otherwise projected to retire in the
baseline, becomes a more economically viable source of electricity in the policy case due to changes in the
relative economics of electricity production across the full market, and thus avoids closure. Consequently, the
final rule is not expected to have a material ongoing effect on capacity availability and supply reliability at either
the national or the NERC region level.
The 1 GW of retired capacity is replaced by new, more efficient, and less polluting capacity. Because the new
capacity is more efficient and less costly to run than the retired capacity, it will run at a higher capacity utilization
rate than the retired capacity; therefore, less new capacity is required to meet electricity demand than the retired
capacity that it replaces. As shown in Table 6-2, under the Electricity Market Analysis - Final Rule, new capacity
additions would increase by 1 GW at the national level; this increase represents 0.5 percent of new baseline
capacity and 0.1 percent of total baseline capacity (see Table 6-2). As reported in Table 6-2, this increase in new
capacity is mostly comprised of combined cycle capacity followed by other non-steam capacity, with coal steam
capacity additions remaining zero in both the baseline case and the policy case. Consequently, this analysis shows
that the final rule is not likely to impede construction of new combined cycle and coal steam generating units.
As reported in Table 6-1, at the national level, in a way similar to that described for net changes in capacity, the
net change in generation is essentially zero, as electricity demand is assumed not to change as a result of the
regulation. No NERC region records a consequential change in total generation.
Overall, the Electricity Market Analysis - Final Rule would have only a slight impact on electricity prices. For
three out of eight NERC regions, electricity prices are projected to decline slightly - by no more than $0.05 per
MWh (0.1 percent) in the TRE region. Electricity prices increase in the remaining five NERC regions, with the
largest increase, $0.29 per MWh (0.4 percent), occurring in the NPCC region. These very small estimated changes
in electricity prices are essentially within the analytic "noise" of the electricity market modeling system.
At the national level, total costs increase by less than 0.3 percent of the baseline value - again, a very modest
amount. None of the cost components changes in a material way. Across regions, no NERC region records an
increase in total generation costs exceeding 0.5 percent.
The change in variable production costs ($/MWh) - a specific measure of the effect of the Electricity Market
Analysis - Final Rule on short-run generation costs - is nearly zero, with no NERC region recording a
consequential change.
At the national level, the change in emissions is very small relative to baseline emissions, with S02 and Hg
emissions decreasing by 0.1 percent, C02 emissions decreasing by approximately 1 million metric ton (essentially
zero percent change from the baseline), and NOx emissions essentially unchanged. The impact on emissions
varies by NERC region, decreasing slightly or remaining essentially unchanged in most instances.
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Table 6-1: Impact of the Electricity Market Analysis - Final Rule on National and Regional Markets, for the
Year 2030ab
Economic Measures

Final Rule
(all dollar values in $2011)
Baseline Value
Value
Difference
% Change
National Totals
Total Capacity (GW)
1,106
1,105
0
0.0%
Existing

-0.1%
New Additions

0.1%
Early Retirements

1
0.1%
Flectricitv Prices i $/M\Vh I
NA
NA
NA
NA
Generation (TWh)
4.701
4.701
0
0.0%
Costs (SMillionsi
$222,765
$223,333
,8
0.3%
Fuel Cost
SI 19.976
$1 19.961

0.0%
Variable O&M
SI 6.253
$16,290
$38
0.2%
Fixed O&M
$60,034
$60,496
>2
0.8%
Capital Cost
$26,501
$26,586
$84
0.3%
Variable Production Cost (S/MWh)
$28.98
$28.98
$0 00
0.0%
COi Fmissions ( Million Metric I ons)
2.451
2.450
-1
0.0%
I Ig Fmissions ( I ons)
9
9
0
-0.1%
NO\ Fmissions ( Million I ons)
2
2
0
0.0%
SO, Fmissions (Million I ons)
2
2
0
-0.1%
Florida Reliability Coordinating Council (FRCC)
Total Capacity (GW)
68
68
0
0.0%
Existing

0
-0.3%
New Additions

0
0.3%
Early Retirements

()
0.3%
Electricity Prices ($/MWh)
$73.98
$73.97
-$0 01

0.0%
Generation (TWh)
271
271
0

0.0%
Costs (SMillionsi
$15,667
$15,719

0 3%
Fuel Cost
$10,433
$10,426

-0.1%
Variable O&M
$893
$894
$2

0.2%
Fixed O&M
$2,541
$2,568
$27

1.1%
Capital Cost
$1,800
$1,830
$30

1.7%
Variable Production Cost (S/MWh)
$41.85
$41.82
-$0 03

-0.1%
CO-. Fmissions (Million Metric I ons)
129
129
0

0.0%
1 Ig Fmissions (Tons)
0
0
0

0.0%
NOx Fmissions (Million I ons)
0
0
0
-0.4%
S02 Emissions (Million Tons)
0
0
0
-0.4%
Midwest Reliability Organization (MRO)
Total Capacity (GW)
76
76
0
0.0%
Fxistiim
1
0

0.0%
New Additions

0.0%
Farlv Retirements

0.0%
Flectricitv Prices i $/MWh I
$63.04
$63 26
$0 21

0 3%
Generation ( TWh)
317
317
0

0.0%
Costs (SMillionsi
$13,896
$13,958
$62

0.4%
Fuel Cost
$6,104
$6,107
$2

0.0%
Variable O&M
$1,226
$1,231
$5

0.4%
Fixed O&M
$4,295
$4,345
$50

1.2%
Capital Cost
$2,270
$2,275
*>-

0.2%
Variable Production Cost (S/MWh)
$23 16
$23 17
$001

0.1%
COi Fmissions (Million Metric I ons)
208
208
0

0.0%
1 Ig Fmissions ( Tons)
1
1
0

0.0%
NOx Fmissions (Million I ons)
0
0
0

0.0%
SO: Fmissions (Million I ons)
0
0
0
-0.1%
May 2014
6-13
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
Table 6-1: Impact of the Electricity Market Analysis - Final Rule on National and Regional Markets, for the
Year 2030ab
Economic Measures
(all dollar values in $2011)
Baseline Value
Final Rule
Value
Difference
% Change
Northeast Power Coordinating Council (NPCC)
Total Capacity (GW)
73
73
0
-0.4%
Fxistiim

o
-0.5%
New Additions

o
0.1%
Farlv Retirements

o
0.5%
Flectricitv Prices i $/M\Vh I
$73.05
$73 34
$0.29
0.4%
Generation (TWh)
264
264
0
0.0%
Costs (SMillionsi
$1 3.5%
$13,624
$2X
0.2%
Fuel Cost
$7,446
$7,445
-$l
0.0%
Variable O&M
$925
$927
$1
0.1%
1-ixed O&M
$4,239
i
$20
0.5%
Capital Cost
$9X5
$993
$X
(>.X%
Variable Production Cost ($/MWh)
$31 75
$31 74
$0.00
0.0%
C02 Emissions (Million Metric Tons)
79
79
0
0.0%
Hg Emissions (Tons)
0
0
0
0.0%
NOx Emissions (Million Tons)
0
0
0
-0.1%
S02 Emissions (Million Tons)
0
0
0
-0.1%
ReliabilityFirst Corporation (RFC)
Total Capacity (GW)
237 | 237
0
0.0%
Existing
1
0
-0.1%
New Additions
1
0
0.1%
Early Retirements

0
0.1%
Electricity Prices ($/MWh)
$66.02
$66 17
$0.15
0.2%
Generation (TWh)
1,112
I.I 1 1
0
0.0%
Costs (SMillionsi
$55.X31
$55.9XX
$157
0.3%
Fuel Cost
$27 017
$27,010
-$x
0.0%
Variable O&M
$3.5 IX
$3,531

0.4%
1-ixed O&M

$17,576
$130
0.7%
Capital Cost
$7.X49
$7.X7I
$22
0.3%
Variable Production Cost (S/MWh)
$27 47
$27.4X
$0.01
0.0%
C02 Emissions (Million Metric Tons)
641
640
0
-0.1%
Hg Emissions (Tons)
3
3
0
-0.1%
NOx Emissions (Million Tons)
1
1
0
-0.1%
S02 Emissions (Million Tons)
1
1
0
-0.1%
Southeast Electric Reliability Council (SERC)
Total Capacity (GW)
274 | 274
0
-0.1%
Existing
1
0
-0.1%
New Additions
1
o
0.0%
Early Retirements

o
0.1%
Electricity Prices ($/MWh)
$64.9X
$65.06
$o.ox
0.1%
Generation ( TWh)
1.239
1.239
0
0.0%
Costs (SMillionsi
$57 253
$57,435
$1X2
0.3%
Fuel Cost
$32,009
$32,020
$11
0.0%
Variable O&M
$3,979
$3,994
$14
0.4%
1-ixed O&M
765
$16,917
$152
0.9%
Capital Cost
$4,500
$4,505
$5
0.1%
Variable Production Cost (S/MWh)
$29 05
$29 06
$0.02
0.1%
C02 Emissions (Million Metric Tons)
695
695
0
0.0%
1 Ig Fmissions ( Tons)
2
2
0
-0.1%
NOx Fmissions (Million I ons)
0
0
0
0.0%
SO: Fmissions (Million I ons)
1
1
0
0.0%
6-14
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
Table 6-1: Impact of the Electricity Market Analysis - Final Rule on National and Regional Markets, for the
Year 2030ab
Economic Measures

Final Rule
(all dollar values in $2011)
Baseline Value
Value
Difference
% Change
Southwest Power Pool (SPP)
Total Capacity (GW)
59
60
1
1.5%
Fxistiim

1
1.5%
New Additions

o
0.0%
Farlv Retirements

-1
-1.5%
Flectricitv Prices i $/MWh I
$60.93
$60.92
-$0.01
0.0%
Generation (TWh)
237
237
0
-0.1%
Costs (SMillionsi
$10,527
$10,558
$31
0.3%
Fuel Cost
$6,197
$6,191
-$5
-0.1%
Variable O&M
$980
$979
-$l
-0.1%
1-ixed O&M
$2,460
$2,501
$41
1.7%
Capital Cost
$890
$886
-$4
-0.4%
Variable Production Cost ($/MWh)
$30 27
$30.28
$0.02
0.1%
CO, Fmissions ( Million Metric Tons)
169
169
0
-0.3%
1Ig Fmissions ( Tons)
1
0
0
-0.3%
N()\ Fmissions ( Million I ons)
0
0
0
0.5%
SO, Fmissions (Million I ons)
0
0
0
-0.4%
Texas Reliability Entity (TRE)
Total Capacity (GW)
98
97
-1
-0.7%
Existing

-1
-0.8%
New Additions

0
0.1%
Early Retirements

0.8%
Electricity Prices ($/MWh)
$67.61
$67.56
-$0.05

-0.1%
Generation (TWh)
393
393
0

0.0%
Costs (SMillionsi
$18,398
$18,445
$48

0 3%
Fuel Cost
$1 1.987
$1 1.980
-$7

-0.1%
Variable O&M
$1,433
$1,435

0.2%
1-ixed O&M
$3,858
$3,894
$37

1.0%
Capital Cost
$1,121

$15

1 3%
Variable Production Cost (S/MWh)
$34.13
$34 12
-$0.01

0.0%
COi Fmissions (Million Metric I ons)
213
213
0

0.0%
1 Ig Fmissions ( Tons)
1
1
0

0.0%
NOx Fmissions (Million I ons)
0
0
0
-0.1%
S02 Emissions (Million Tons)
0
0
0
0.0%
Western Electricity Coordinating Council (WECC)
Total Capacity (GW)
220
220
0
0.0%
Existing

0
0.0%
New Additions

0
0.0%
Early Retirements
|
0
0.0%
Electricity Prices ($/MWh)
$64.93
$64.96
$0.03
0.0%
Generation ( TWh)
869
869
0
0.0%
Costs (SMillionsi
$37,596
$37,606
$9
0.0%
Fuel Cost
$18,782
$18,782
$0
0.0%
Variable O&M
$3,299
$3,299
$0
0.0%
l ixed O&M
$8,430
$8,435
$5
0.1%
Capital Cost
$7,086
$7,089
$4
0.1%
Variable Production Cost (S/MWh)
$25.40
$25 40
$0.00
0.0%
COi Fmissions (Million Metric I ons)
317
317
0
0.0%
1 Ig Fmissions ( Tons)
2
2
0
0.0%
NOx Fmissions (Million I ons)
0
0
0
0.0%
SO, Fmissions (Million I ons)
0
0
0
-0.1%
May 2014
6-15
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
Table 6-1: Impact of the Electricity Market Analysis - Final Rule on National and Regional Markets, for the
Year 2030ab
Economic Measures
(all dollar values in $2011)
Baseline Value
Final Rule
Value
Difference
% Change
a. Facilities with cooling water system impoundments are assumed not to qualify as baseline CCRS, which likely overstates the final rule's cost and impact.
b. Numbers may not sum to reported totals due to rounding.
Source: U.S. EPA analysis for this report
Table 6-2: Impact of the Electricity Market Analysis - Final Rule on New Capacity (GW), at
the Year 2030a

Electricity Market Analysis - Final Rule
Capacity Type
Baseline Total
Capacity
Post-Compliance
Total Capacity
Difference
% Change
Coal Steam
0
0
0
NA
Combined Cycle
75
76
1
0.8%
Combustion Turbine
6
6
0
0.0%
I Ivdro
0
0
0
NA
Nuclear
0
0
0
NA
()/(i Steam
0
0
0
NA
Other Non-Steanif'
25
25
0
0.1%
Other Steam'
9
9
0
0.0%
Total
114
115
1
0.5%
a. Facilities with cooling water system impoundments are assumed not to qualify as baseline CCRS, which likely overstates the final
rule's impact.

b. Other non-steam capacity includes wind, solar, pumped storage, and fuel cell.

c. Other steam capacity includes biomass, geothermal, municipal solid waste, fossil waste, landfill gas, tires, and non-fossil waste.
Source: U.S. EPA analysis for this report

Impact on Regulated Facilities as a Group
EPA used the same IPM V4.10_MATS results for 2030 that were used to analyze the impact on national and
regional electricity markets described above for the analysis of impact on regulated facilities as a group. However,
this analysis considers the effect of the Electricity Market Analysis - Final Rule only on the regulated facilities
modeled in IPM (i.e., 520 facilities). The analysis results for the group of regulated facilities (Table 6-3) overall
show a slightly greater impact than that observed over all generating units in the IPM universe (i.e., market-level
analysis discussed in the preceding section (Impact on National and Regional Electricity Markets)). This
difference is due to the fact that in the electricity market as a whole, impacts on regulated facilities are offset by
changes in capacity and energy production at the other electric power facilities.
The metrics of interest are largely the same as those presented above for the analysis of the effect on the
electricity market as a whole. However, in this analysis, the impact measures reflect only the economic activities
of the 520 regulated facilities analyzed in IPM. In addition, a few measures differ:
1. Because prices are determined at the market level within IPM, IPM does not distinguish between prices
for regulated facilities and other facilities. Thus, prices are not reported.
2. Changes in emissions at a subset of electric power facilities, as opposed to the electricity market as a
whole, provide incomplete insight for the overall estimated effect of the regulation on emissions and are
therefore not presented.
3. Because capacity additions modeled in IPM cannot be attributed to specific generating units, they cannot
be analyzed for a subset of electricity power facilities, and consequently are not reported.
4. The number of regulated facilities projected to close is presented.
The following four measures are reported in the analysis of regulated facilities as a group; in all instances, these
measures are tabulated only for 520 regulated facilities:
6-16
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
r Changes in available capacity. These changes are defined in the same way as in the preceding section
(Impact on National and Regional Electricity Markets), with the exception of the units used (MW vs. GW
of capacity).
> Changes in generation: Long-term changes in generation may result from a reduction in available
capacity (see discussion above) or less frequent dispatch of a generating unit due to higher production
costs resulting from compliance response. At the same time, the final rule may lead to an increase in
generation for some regulated facilities if their compliance costs are low relative to other regulated
facilities.
> Changes in costs: These changes are defined in the same way as in the preceding section (Impact on
National and Regional Electricity Markets).
> Changes in variable production costs perMWh: These changes are defined in the same way as in the
preceding section (Impact on National and Regional Electricity Markets).
Table 6-3 reports results of the electricity market analysis for regulated facilities as a group.
As described above, EPA interpreted the findings from the electricity market analysis in the context of the 0.1
percent negligibility threshold analysis presented in Chapter 4. At the outset, EPA notes that under the final rule,
221 facilities accounted for in the electricity market analysis that were also accounted for on a non-sample-
weighted basis in Chapter 4, appear to be evenly divided between facilities with negligible and non-negligible
compliance costs as percent of revenue in terms of potential adverse impact. Specifically, for 109 of these 221
facilities, annualized compliance costs are less than 0.1 percent of revenue, while for the remaining 112 facilities
these costs exceed 0.1 percent of revenue.
The impacts of the Electricity Market Analysis - Final Rule on regulated facilities differ from the total market
impacts as these facilities become less competitive compared to facilities that do not incur compliance costs under
the Electricity Market Analysis - Final Rule. As a result, capacity and generation impacts are greater for this set of
facilities than those estimated for the entire electricity market, relative to the baseline. However, the net change in
total capacity and generation for the group of regulated facilities remains very small. For instance, while there is
essentially no change in either total available capacity or electricity generation for the overall electricity market at
the national level, for the group of regulated facilities, total available capacity and electricity generation fall by
only 0.4 percent and 0.1 percent, respectively. For regulated facilities as a group, the total capacity loss from early
retirements is approximately 2 GW at the national level, or 0.4 percent of total baseline capacity at regulated
facilities. Five NERC regions incur a loss in total capacity, with the largest percentage loss of 2.8 percent and the
largest absolute loss of 0.9 GW occurring in the NPCC region.
The 2 GW of capacity loss at regulated facilities reflects a combination of closures and avoided closures of
generating units in the universe of regulated facilities. Some unit closures result in full facility closures (i.e., all
generating units at a facility close), while others result in only partial facility closures (i.e., some but not all
generating units at a facility close). As discussed above, for avoided closures, a generating unit projected to close
in the baseline case remains open in the policy case, in some instances resulting in an avoided full facility closure.
Overall, 22 generating units close (4 GW) and 12 generating units avoid closure (2 GW) in the policy case,
resulting in net closure of 10 generating units (approximately 2 GW) in the Electricity Market Analysis - Final
Rule analysis. The 22 generating unit closures reflect retirement of nine units at six full-closure facilities (2 GW)
and retirement of 13 units at six partial-closure facilities (2 GW). Of the 22 generating units closing in the policy
case, most do not contribute significantly to electricity supply in the baseline case, with 14 and seven units having
a capacity utilization rate of zero and less than 11 percent, respectively. Only one closing unit has substantial
capacity utilization, with a rate of approximately 66 percent. Given the low capacity utilization of these units,
EPA anticipates that their closure would not have a material employment impact.
May 2014
6-17
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
Of the six full-facility closures, EPA analyzed only two of these facilities on a non-sample-weighted basis in
Chapter 4. In the Chapter 4 impact analysis, EPA estimated a cost-to-revenue value exceeding the 0.1 percent
negligibility threshold for both of these closures: 3.6 percent for one facility and 2.1 percent for the second. Of the
six partial-facility closures, EPA analyzed only one of these facilities on a non-sample-weighted basis in Chapter
4: EPA estimated a cost-to-revenue value of 0.6 percent at the level of the facility. In summary, all of the full- and
partial-facility closures that EPA analyzed on a non-sample-weighted basis in Chapter 4 incur costs that EPA
estimates to exceed the 0.1 percent negligibility threshold. In contrast, none of the facilities with costs below the
0.1 percent negligibility threshold were projected in the electricity market analysis to be either a full- or partial-
facility closure.
Other analyzed effects of the Electricity Market Analysis - Final Rule for the group of regulated facilities are of
less consequence. At the national level, total generation at regulated facilities declines by less than 2 TWh or
approximately 0.1 percent of baseline generation in these facilities. At the regional level, the MRO and SERC
regions record slight increases in generation essentially amounting to zero percent of baseline generation at
regulated facilities in these regions, with the remaining five NERC regions recording a reduction in electricity
generation of no more than 0.4 percent in FRCC.
Over all regulated facilities, total costs increase by less than 0.3 percent of the baseline value - again, a modest
amount. None of the cost components changes in a material way. All NERC regions except FRCC record slight
increases within the regulated facility group, ranging from less than 0.01 percent in NPCC to 0.7 percent in MRO.
There is essentially no change in variable production costs ($/MWh) at the national level, while at the NERC
region, the change does not exceed 0.2 percent for any of the regions. These findings of very small effects confirm
EPA's conclusion, stated above, that the estimated capacity closures among regulated facilities are of little
economic consequence at both the national and regional levels.
6-18
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
Table 6-3: Impact of the Electricity Market Analysis - Final Rule on Regulated Facilities, as a Group, at the
Year 2030ab
Economic Measures
(all dollar values in $2011)
Baseline Value
Electricity Market Analysis - Final Rule
Value f Difference [ % Change
National Totals
Total Capacity (MW)
460.917
458.884
-2.032
-0.4%
Karlv Retirements - Number of Facilities
17
23
6
35.3%
Full and Partial Retirements - Capacity (MW)
25.562
27.597
2.035
8.0%
Generation (GWh 1
2.575.886
2.574.166
-1.721
-0.1%
Costs (SMillionsi
SI 12.840
$1 13.204
$364
0.3%
Fuel Cost
S58.I75
$58,095
-$80
-0.1%
Variable O&M
S7.628
$7,665
$37
0.5%
Fixed ()&M
$43,356
$43,781
$425
1.0%
Capital Cost
$3,681
$3,663
-$ 18
-0.5%
Variable Production Cost ($/MWh)
$25.55
$25.55
$0.00
0.0%
Florida Reliability Coordinating Council (FRCC)
Total Capacity (MW)
30,794
30,591
-203
-0.7%
Karlv Retirements - Number of Facilities
0
1
1
NA
Full and Partial Retirements - Capacity (MW)
0
203
203
NA
Generation (GWh)
123.828
123.301
-527
-0.4%
Costs (SMillionsi
$6,248
$6,243
-$5
-0.1%
Fuel Cost

-$31
-0.7%
Variable O&M
$403
$405
$2
0.4%
Fixed O&M
$1,640
$1,664
$24
1.5%
Capital Cost
$46
$46
$0
0.0%
Variable Production Cost ($/MWh)
$36.84
$36.76
-$0.08
-0.2%
Midwest Reliability Organization (MRO)
Total Capacity (MW)
31,747
31,747
0
0.0%
Karlv Retirements - Number of Facilities
0
0
0
NA
Full and Partial Retirements - Capacity (MW)
359
359
0
0.0%
Generation (GWh)
193.212
193.242
30
0.0%
Costs (SMillionsi
$7,771
$7,822
$52
0.7%
Fuel Cost
$3,599
$3,598
-$l
0.0%
Variable O&M
$725
$729
$4
0.6%
Fixed O&M
$3,098
$3,147
$49
1.6%
Capital Cost
$348
$348
-$l
-0.2%
Variable Production Cost (S/MWh)
$22.38
$22.39
$0.01
0.1%
Northeast Power Coordinating Council (NPCC)
Total Capacity (MW)
30,977
30,122
-855
-2.8%
Karlv Retirements - Number of Facilities
2
3
1
50.0%
Full and Partial Retirements - Capacity (MW)
4.431
5.286
855
19.3%
Generation (GWh)
120.069
120.044
-25
0.0%
Costs (SMillionsi
$6,537
$6,537
$1
0.0%
Fuel Cost
$2,921
$2,919
-$2
-0.1%
Variable O&M
$283
$284
$1
0.5%
Fixed O&M
$3,284
$3,285
$1
0.0%
Capital Cost
$49
$49
$0
0.0%
Variable Production Cost (S/MWh)
$26.68
$26.68
$0.00
0.0%
ReliabilityFirst Corporation (RFC)
Total Capacity (MW)
126,905
126,683
-222
-0.2%
Karlv Retirements - Number of Facilities
0
0
0
NA
Full and Partial Retirements - Capacity (MW)
2.172
2.395
223
10.2%
Generation (GWh)
789.683
789.063
-619
-0.1%
Costs (SMillionsi
$34,505
$34,606
$102
0.3%
Fuel Cost
$17,051
$17,022
-$29
-0.2%
Variable O&M
$2,123
$2,136
$12
0.6%
Fixed O&M
$14,092
$14,216
$124
0.9%
May 2014
6-19
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
Table 6-3: Impact of the Electricity Market Analysis - Final Rule on Regulated Facilities, as a Group, at the
Year 2030ab
Economic Measures
(all dollar values in $2011)
Baseline Value
Electricity Market Analysis - Final Rule
Value
Difference
% Change
Capital Cost
$1,239
$1,233
-$6
-0.5%
Variable Production Cost ($/MWh)
$24.28
$24.28
$0.00
0.0%
Southeast Electric Reliability Council (SERC)
Total Capacity (MW)
142,840
142,366
-475
-0.3%
Early Retirements - Number of Facilities
10
13
3
30.0%
Full and Partial Retirements - Capacity (MW)
11,802
12.278
476
4.0%
Generation (GWh)
897,655
897.657
3
0.0%
Costs (SMillions)
$38,203
$38,363
$161
0.4%
Fuel Cost
$20,008
$20,012
$3
0.0%
Variable O&M
$2,464
$2,479
$14
0.6%
Fixed O&M
$14,219
$14,367
$148
1.0%
Capital Cost
$1,510
$1,505
-$5
-0.3%
Variable Production Cost ($/MWh)
$25.04
$25.05
$0.02
0.1%
Southwest Power Pool (SPP)
Total Capacity (MW)
24.487
25.018
530
2.2%
Karlv Retirements - Number of Facilities
3
4
1
33 3%
Full and Partial Retirements - Capacity (MW)
2.177
1.648
-530
-24.3%
Generation (GWh)
123.126
122.714
-411
-0.3%
Costs (SMillions)
$5,093
$5.1 15
$22
0.4%
Fuel Cost
$2,628
$2,619
-$9
-0.3%
Variable O&M
$520
$520
-$l
-0.1%
Fixed O&M
$1,610
$1,647
$37
2.3%
Capital Cost
$335
$329
-$6
-1.9%
Variable Production Cost ($/MWh)
$25.57
$25.58
$0.01
0.0%
Texas Reliability Entity (TRE)
Total Capacity (MW)
38,378
37,570
-808
-2.1%
Early Retirements - Number of Facilities
0
0
0
NA
Full and Partial Retirements - Capacity (MW)
1.035
1.843
808
78.1%
Generation (GWh 1
I7F087
170.924
-163
-0.1%
Costs (SMillions)
$7,507
$7,534
$27
0.4%
Fuel Cost
$4,293
$4,282
-$l 1
-0.3%
Variable O&M
$676
$679
$3
0.5%
Fixed O&M
$2,506
$2,542
$35
1.4%
Capital Cost
$32
$32
$0
0.0%
Variable Production Cost ($/MWh)
$29.04
$29.02
-$0.02
-0.1%
Western Electricity Coordinating Council (WECC)
Total Capacity (MW)
34.788
34.788
0
0.0%
Karlv Retirements - Number of Facilities
2
2
0
0.0%
Full and Partial Retirements - Capacity (MW)
3.585
3.585
0
0.0%
Generation (GWh)
157,228
157,219
-8
0.0%
Costs (SMillions)
$6,977
$6,982
$5
0.1%
Fuel Cost
$3,516
$3,515
-$l
0.0%
Variable O&M
$434
$434
$0
0.1%
Fixed O&M
$2,907
$2,912
$5
0.2%
Capital Cost
$121
$121
$0
0.0%
Variable Production Cost (S/MWli)
$2542
$25.12
$0.00
0.0%
a. Facilities with cooling water system impoundments are assumed not to qualify as baseline CCRS, which likely overstates the final rule's cost and impact.
b. Numbers may not sum to reported totals due to rounding.
Source: U.S. EPA analysis for this report
6-20
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
Impact on Individual Regulated Facilities
Results for the group of regulated facilities as a whole may mask shifts in economic performance among
individual regulated facilities. To assess potential facility-level effects, EPA analyzed the distribution of facility-
specific changes between the baseline and policy cases for the following three metrics:
> Capacity Utilization, defined as generation divided by capacity times 8,760 hours
> Electricity Generation, as defined above
> Variable Production Costs perMWh, defined as variable O&M cost plus fuel cost divided by net
generation .
Table 6-4 presents the estimated number of regulated facilities with specific degrees of change in operations and
financial performance as a result of the Electricity Market Analysis - Final Rule. Metrics of interest include the
number of facilities with reductions in capacity utilization or generation (on left side of the table), and the number
of facilities with increases in variable production costs (on right side of the table).
This table excludes regulated facilities with estimated significant status changes in 2030 that render these metrics
of change not meaningful - i.e., a facility is either a full, partial, or avoided closure in either the baseline case or
the policy case. As a result, the measures presented in Table 6-3, such as change in electricity generation, are not
meaningful for these facilities. For example, for a facility that is projected to close in the baseline but avoids
closure under the policy case, the percent change in electricity generation relative to baseline cannot be calculated.
On this basis, 92 facilities are excluded from the analysis of effects on individual regulated facilities.
In addition, the change in variable production cost per MWh of generation could not be developed for 22 facilities
with zero generation in either the baseline case or the policy case. For these facilities, variable production cost per
MWh cannot be calculated for either the baseline case or the policy case because electricity generation is reported
as zero (the divisor in the variable production cost calculation, MWh, is zero); therefore, the change in variable
production cost per MWh cannot be meaningfully determined. These instances would typically occur because the
facilities have high production costs and are therefore rarely dispatched to meet electricity demand. Such facilities
may be kept available, though, as back-up generation capability for instances of very high demand and/or to
maintain electricity supply during unplanned outages. For change in variable production cost per MWh, these
facilities are recorded in the "N/A" column.
Under the Electricity Market Model - Final Rule, the analysis of changes in individual regulated facilities
indicates that most facilities experience only slight effects - i.e., no change or less than a 1 percent reduction or 1
percent increase. Only six facilities are estimated to incur a reduction in capacity utilization and 13 facilities a
reduction in generation of at least 1 percent, with only five facilities estimated to incur an increase in variable
production costs per MWh of at least 1 percent.
May 2014
6-21
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
Table 6-4: Impact of the Electricity Market Analysis - Final Rule on Individual Regulated Facilities at the
Year 2030 (Number of Regulated Facilities With Indicated Effect)3

Reduction

Increase

Economic Measures
>3%
>1 % and
<3%
<1%
No Change
<1%
>1 % and
<3%
>3%
N/Ac,d
Change in Capacity Utilizationb
1
5
45
340
35
2
0
92
Change in Generation
9
4
37
345
29
2
2
92
Change in Variable Production
Costs/MWh
2
1
70
86
242
4
1
114
a. Facilities with cooling water system impoundments are assumed not to qualify as baseline CCRS, which likely overstates the final rule's impact.
b. Hie change in capacity utilization is the difference between the capacity utilization percentages in the baseline and policy cases. For all other
measures, the change is expressed as the percentage change between the baseline and post-compliance values.
c. Facilities with status changes in either the baseline case or the policy case were excluded from these calculations. Specifically, there are 17 full
baseline facility closures, 59 partial baseline facility closures, four avoided partial facility closures, six partial policy facility closures, and six partial
policy facility closures.
d. The change in variable production cost per MWh could not be developed for 22 facilities with zero generation in either or both of the baseline and
policy cases.
Source: U.S. EPA analysis for this report
6.3.2 Analysis Results for 2020 - To Capture the Effect of Technology-Installation Downtime
This section presents market-level results for the Electricity Market Analysis - Final Rule for the 2020 IPM run
year, which represents 2017 through 2024. As discussed above, this IPM run year captures the period when
regulated facilities are expected to install compliance technologies under the final rule. Of particular importance
as a potential impact, the additional downtime from installation of compliance technologies will manifest as
increased electricity production costs resulting from the dispatch of higher-production-cost generating units
during the period when units are taken offline to install compliance technologies. Because these effects are of
most concern in terms of potential impact on national and regional electricity markets, this section presents results
only for the overall electricity market and does not present results for the subset of regulated facilities.
Table 6-5 presents the following national and NERC region market-level impacts for 2020:
> Electricity price changes, including changes in energy prices and capacity prices
> Generation changes
> Cost changes, including changes in fuel costs, variable O&M costs, fixed O&M costs, and capital costs
> Changes in variable production costs per MWh
> Changes in C02, Hg, NOx, and S02 emissions.
Table 6-5 presents the results for the baseline and policy cases, the absolute difference between the two cases, and
the percentage difference. The following discussion of the impact findings for the Electricity Market Analysis -
Final Rule focuses on these differences.
As discussed earlier, regulated facilities are expected to install compliance technologies during the 5-year period
of 2018 through 2022, which falls in the range of years represented by the 2020 IPM run year (for details see
Appendix P). Consequently, results for the year 2020 are indicative of annual effects during each of these years.
As shown in Table 6-5, the estimated effects of technology installation downtime under the Electricity Market
Analysis - Final Rule are small. At the national level, total production costs increase by 0.4 percent, with fixed
O&M increasing the most by 0.8 percent. Total production costs increase in all NERC regions, with MRO and
SPP recording the largest increase of 0.6 percent. Fixed O&M, variable O&M, and fuel costs increase slightly in
all NERC regions, with capital costs increasing in all but two NERC regions. In these two regions, RFC and TRE,
capital costs decline, but by no more than 0.1 percent.
6-22
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
At the national level, variable production costs ($/MWh) increase by approximately 0.2 percent. While the effect
on energy production costs varies across NERC regions, this effect is small overall, not exceeding 0.4 percent in
FRCC.
Another potential market-level impact of the Electricity Market Analysis - Final Rule is the possible increase in
electricity prices. While electricity prices increased in all NERC regions, the magnitude of that increase is
generally small, ranging from $0.15 per MWh (0.3 percent) in MRO and WECC to $0.56 per MWh (0.9 percent)
in FRCC.
Finally, the impact on air pollution emissions is also small. At the national level, Hg and S02 emissions decline by
0.1 percent, NOx emissions increase by only 0.1 percent, and C02 emissions essentially remain the same. While
the impact on emissions varies by NERC region, increasing in some and declining in others, overall changes are
small relative to the baseline.
These small effects reflect the limited duration of downtime for installing compliance technology under the final
rule, and the fact that technology installation is expected to occur over five years.
Table 6-5: Short-Term Effect of Technology Installation Downtime on National Electricity Market Under the
Electricity Market Analysis - Final Rule - 2020a b
Economic Measures
(all dollar values in $2011)
Baseline Value
Electricity Market Analysis - Final Rule
Value
Difference
% Change
National Totals
Flectncitv Prices ($/MWh I
NA
NA
NA
NA
Generation (TWhi

4.304

4.304
0
0.0%
Costs (SMillionsi

>88

$175 640
$652
0.4%
Fuel Cost

$91,786

$91 941
$155
0.2%
Variable O&M

>52

$15,103
$51
0.3%
Fixed ()&M

$53,982

$54 428
$445
0.8%
Capital Cost

68
$1
0.0%
Variable Production Cost ($/MWh)

$24.82

$24 87
$0.05
0.2%
CO; Fmissions (Million Metric Tonnes)

2.293

2.293
0
0.0%
1 lg Fmissions (Tons)

9
0
-0.1%
NOx Emissions (Million Tons)
2
2
0
0.1%
SO; Emissions (Million Tons)
2
2
0
-0.2%
Florida Reliability Coordinating Council (FRCC)
Flectncitv Prices ($/MWh)
$59.12
$59.68
$0.56
0.9%
Generation (TWhi
237
237
0
0.0%
Costs (SMillionsi
$10,991
$1 1.042
$51
0.5%
Fuel Cost
$7,849
$7,871
$22
0.3%
Variable O&M
$832
$837
$6
0.7%
Fixed O&M
$2,141
$2,164
$23
1.1%
Capital Cost
$169
$169
$0
0.0%
Variable Production Cost ($/MWh)
$36 68
$36 82
$0.13
0.4%
CO; Emissions (Million Metric Tonnes)
119
119
0
0.3%
Hg Emissions (Tons)
0
0
0
0.5%
NOx Emissions (Million Tons)
0
0
0
0.4%
SO; Emissions (Million Tons)
0
0
0
0.3%
Midwest Reliability Organization (MRO)
Electricity Prices ($/MWh)
$51.72
$51.87
$0.15
0.3%
Generation (TWhi
286
286
0
0.0%
Costs (SMillionsi
$10,797
$10,860
$64
0.6%
Fuel Cost
$4,754
$4,761
$6
0.1%
Variable O&M
$1,089
$1,093
$4
0.4%
Fixed O&M
$3,961
$4,010
$48
1.2%
Capital Cost
$993
$997
$5
0.5%
Variable Production Cost (S/MWli)
$20.41
$20.44
$0.03
0.2%
CO; Emissions (Million Metric Tonnes)
198
198
0
-0.1%
May 2014
6-23
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
Table 6-5: Short-Term Effect of Technology Installation Downtime on National Electricity Market Under the
Electricity Market Analysis - Final Rule - 2020a b
Economic Measures
(all dollar values in $2011)
Baseline Value
Electricity Market Analysis - Final Rule
Value
Difference
% Change
Hg Emissions (Tons)
1
1
0
-0.1%
NOx Emissions (Million Tons)
0
0
0
-0.1%
S02 Emissions (Million Tons)
0
0
0
-0.2%
Northeast Power Coordinating Council (NPCC)
Electricity Prices ($/MWh)
$53.65
$53.83
$0.18
0.3%
Generation (TWh)
259
259
0
0.0%
Costs (^Millions)
SI 1.570
$1 1.601
$31
0.3%
Fuel Cost
$5.631
$5,641
$10
0.2%
Variable O&M
$873
$874
$1
0.1%
Fixed O&M

$4,391
$19
0.4%
Capital Cost
$6 95
$695
$0
0.0%
Variable Production Cost ($/MWh)
$25.1 1
$25.16
$0.05
0.2%
CO; Fmissions (Million Metric Tonnes)
70
70
0
-0.1%
I Ig Fmissions ( I ons)
0
0
0
0.1%
NOx Emissions (Million Tons)
0
0
0
0.0%
SO; Emissions (Million Tons)
0
0
0
1.4%
ReliabilityFirst Corporation (RFC)
Klectricitv Prices ($/MWh)
$49.38
$49.57
$0.19
0.4%
Generation (TWh)
1.025
1.026
0
0.0%
Costs (^Millions)
$45,477
$45.641
$164
0.4%
Fuel Cost
$21,968
$21,995
$28
0.1%
Variable O&M
$3.221
$3,238
$17
0.5%
Fixed O&M
$15,794
$15,919
$125
0.8%
Capital Cost
$4,495
$4,488
-$6
-0.1%
Variable Production Cost (S/MWh)
$24 57
$24.60
$0.03
0.1%
COi Fmissions ( Million Metric Tonnes)
605
605
0
0.0%
I Ig Fmissions ( I ons)
2
2
0
-0.1%
NOx Emissions (Million Tons)
1
1
0
0.2%
SO; Emissions (Million Tons)
1
1
0
0.1%
Southeast Electric Reliability Council (SERC)
Klectricitv Prices ($/MWh)
$49.33
$49.60
$0.27
0.6%
Generation (TWh)
1.142
1.141
0
0.0%
Costs (SMillions)
$46,287
$46,472
$185
0.4%
Fuel Cost
$25,160
$25,177
$17
0.1%
Variable O&M
$3,688
$3,705
$16
0.4%
Fixed O&M
$15,018
$15,167
$149
1.0%
Capital Cost
$2,421
$2,423
$2
0.1%
Variable Production Cost (S/MWh)
$25.27
$25.30
$0.04
0.1%
CO-. Fmissions (Million Metric Tonnes)
649
649
0
0.0%
Hg Emissions (Tons)
2
2
0
-0.3%
NOx Emissions (Million Tons)
0
0
0
0.0%
SO; Emissions (Million Tons)
1
1
0
-0.4%
Southwest Power Pool (SPP)
Klectricitv Prices (S/MWh)
$44.92
$45.10
$0.18
0.4%
Generation (TWh)
221
221
0
0.0%
Costs (SMillions)
$8,604
$8,660
$56
0.6%
Fuel Cost
$4,844
$4,859
$15
0.3%
Variable O&M
$939
$940
$1
0.1%
Fixed O&M
$2,170
$2,210
$40
1.8%
Capital Cost
$651
$651
$0
0.0%
Variable Production Cost (S/MWh)
$26.1 1
$26.19
$0.08
0.3%
COi Fmissions (Million Metric Tonnes)
161
161
0
-0.1%
Fig Emissions (Tons)
0
0
0
-0.4%
6-24
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
Table 6-5: Short-Term Effect of Technology Installation Downtime on National Electricity Market Under the
Electricity Market Analysis - Final Rule - 2020a b
Economic Measures
(all dollar values in $2011)
Baseline Value
Electricity Market Analysis - Final Rule
Value
Difference
% Change
NOx Emissions (Million Tons)
0
0
0
0.3%
S02 Emissions (Million Tons)
0
0
0
-1.0%
Texas Reliability Entity (TRE)
Electricity Prices ($/MWh)
$49.18
$49.39
$0.21
0.4%
Generation (TWh)
346
346
0
0.0%
Costs (SMillionsi
$13,343
$13,407
$64
0.5%
Fuel Cost
$8.51.3
$8,538
$25
0.3%
Variable O&M
$1,351
$1,356
$5
0.4%
Fixed O&M
$3.31')
$3,353
$34
1.0%
Capital Cost
$161
$160
$0
-0.1%
Variable Production Cost ($/MWh)
$28.47
$28.55
$0.08
0.3%
C02 Emissions (Million Metric Tonnes)
194
194
0
0.0%
Hg Emissions (Tons)
1
1
0
0.1%
NOx Emissions (Million Tons)
0
0
0
0.1%
S02 Emissions (Million Tons)
0
0
0
-2.1%
Western Electricity Coordinating Council (WECC)
Flectncitv Prices ($/MWh I
$49.86
$50.01
$0.15
0.3%
Generation (TWhi
787
787
0
0.0%
Costs (SMillionsi
$27,918
$27,958
$39
0.1%
Fuel Cost
$ 13.066
$ 13.099
$33
0.3%
Variable O&M
$3,060
$3,060
$1
0.0%
Fixed O&M
$7,208
$7.2 F3
$5
0.1%
Capital Cost
\
$4,585
$1
0.0%
Variable Production Cost (S/MWh)
$20.49
$20.53
$0.04
0.2%
C02 Emissions (Million Metric Tonnes)
297
297
0
0.0%
Hg Emissions (Tons)
2
2
0
0.3%
NOx Emissions (Million Tons)
0
0
0
0.0%
S02 Emissions (Million Tons)
0
0
0
0.7%
a. Facilities with cooling water system impoundments are assumed not to qualify as baseline CCRS, which likely overstates the final rule's cost and impact.
b. Numbers may not sum to reported totals due to rounding.
Source: U.S. EPA analysis for this report
6.4 Uncertainties and Limitations
EPA's electricity market analysis of the Electricity Market Analysis - Final Rule involves several sources of
uncertainty:
> Demand for electricity: IPM assumes that electricity demand at the national level will not change between
the baseline case and the policy case (although generation within the regions is allowed to vary); this
constraint is exogenous to the model. The IPM V4.10_MATS embeds a baseline energy demand forecast
that is derived from DOE's AEO2010. IPM does not capture changes in demand that may result from
electricity price increases associated with the Electricity Market Analysis - Final Rule (i.e., demand is
inelastic with respect to price). While this constraint may overestimate total electricity demand in the
policy case because of higher generating costs due to compliance with the Electricity Market Analysis -
Final Rule and consequently, higher electricity prices, EPA does not expect this to significantly affect the
electricity market analysis results analyzed in support of the Electricity Market Analysis - Final Rule. As
described in Section 6.3.1 and Section 6.3.2, the price increases associated with the Electricity Market
Analysis - Final Rule are generally small. EPA therefore concludes that the assumption of inelastic
demand-responses to changes in prices is reasonable.
May 2014
6-25
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 6: Electricity Market Analysis
> Fuel prices: Prices of fuels (e.g., natural gas and coal) are determined endogenously within IPM. IPM
modeling of fuel prices uses both short- and long-term price signals to balance supply and demand in
competitive markets for the various fuels across the modeled time horizon. The model relies on the
AEO2010 electricity demand forecast for the United States and employs various assumptions regarding
fuel supplies, and the performance and cost of electric generation technologies as well as pollution
controls. Differences in actual fuel prices relative to those modeled by IPM, such as lower natural gas
prices that may result from increased domestic production, would be expected to affect the cost of
electricity generation and therefore the amount of electricity generated, irrespective of the Electricity
Market Analysis - Final Rule.
> International imports: IPM assumes that imports from Canada and Mexico will not change between the
baseline case and the policy case. Holding international imports constant would potentially overstate
production costs and electricity prices, because imports are not subject to the Electricity Market
Analysis - Final Rule and may therefore become more competitive relative to domestic capacity,
displacing some of the more expensive domestic generating units. Correspondingly, holding imports fixed
may understate effects on marginal domestic units, which would be displaced by increased imports. EPA
does not expect that this assumption materially affects results, however, because only one of the eight
NERC regions is projected to import electricity (WECC) in 2030, and the level of imports compared to
domestic generation is very small (0.1 percent).
> Compliance costs: In the aggregate, EPA estimates that total compliance costs are less than 1 percent
higher for the Electricity Market Analysis - Final Rule as compared to the existing provision of the final
rule discussed in other chapters of this document, due the difference in administrative costs. Further, the
Electricity Market Analysis - Final Rule accounts only partially for the new unit provision of the final
rule and includes slightly different administrative costs. To the extent that the overall cost of the
Electricity Market Analysis - Final Rule is higher or lower than that of the final rule, including the
existing and new unit provisions, the electricity market analysis results may be over- or under-estimated,
respectively.
> Downtime associated with installation of compliance technologies: EPA estimates that the installation of
several compliance technologies will require regulated facilities installing such technologies to be offline
longer than standard maintenance outages during the technology installation year. Because the eight years
(2017 through 2024) that are represented by the 2020 run year are assumed to have the same
characteristics as the run year itself, downtime was applied as an average over all eight years. A potential
drawback of this approach is that the snapshot of the downtime effect reflected in the 2020 run year
analysis results is the average effect and does not reflect potentially more adverse effects of capacity
being down in any one NERC region during any one year. Further, given that technology-installation
downtime is expected to occur over five years (2018 - 2022), the 8-year average approach may further
underestimate the downtime effect of the Electricity Market Analysis - Final Rule.
> As described earlier in this report, the final rule definition of a CCRS includes cooling water
impoundments that meet specified criteria (see §125.92(c)(2) of the final rule). Subject to site-specific
review by Permit Directors, these facilities may meet the rule's BTA standard for impingement mortality
through operation of a CCRS in the baseline, and may not need to install additional technology to meet
the rule's BTA performance standards. At present, EPA does not know whether individual facilities that
are known to have impoundments will qualify as baseline CCRS and not need to install additional
compliance technology. The compliance response and cost information on which the market model
analysis is based assumes that no facilities known to have impoundments as part of their cooling water
system, will meet the baseline CCRS criterion. To the extent that some of these facilities do not need to
install additional compliance technology to meet the final rule's performance standards, the costs and
impacts reported in this chapter are likely to be overestimates.
6-26
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 7: Total Social Costs
7 Total Social Costs
This chapter develops EPA's estimates of the costs to society resulting from the final rule and other options
considered in development of this rule. As analyzed in this chapter, the social costs of regulatory actions are the
opportunity cost to society of employing scarce resources to prevent the environmental damage otherwise
occurring except for the design and operation of compliance technology. These compliance-related social costs
include (1) costs to Electric Generators and Manufacturers to comply with the final rule, and (2) costs to State and
federal governments to administer regulatory compliance. EPA conducted this analysis for existing units at
Electric Generators and Manufacturers and new units at Electric Generators.
7.1 Analysis Approach and Data Inputs
Chapter 3: Compliance Costs provides details on compliance-related costs to Electric Generators and
Manufacturers, and costs to the National Pollutant Discharge Elimination System (NPDES) permitting authorities
and the federal government for administering the rule. As is the case with compliance-related costs to regulated
facilities, social costs also include capital costs, fixed and variable operation and maintenance (O&M) costs,
auxiliary energy requirement, energy penalty, costs associated with technology installation downtime, and
administrative costs to implement the final rule and other options considered. Further, social costs include the
same costs to States and the federal government to administer the final rule and additional options considered as
those discussed in Chapter 3. These costs form the basis for the analysis of social costs with the following
exceptions:
> The compliance costs used to estimate total social costs differ in their consideration of taxes from those
reported in Chapter 3, which were calculated for the purpose of estimating the private costs and impacts
of the final rule and other options considered. In the analysis of costs to society, compliance costs are
considered without accounting for any tax effects. The costs to society are the full value of the resources
used, whether they are paid for by the regulated facilities or by all taxpayers in the form of lost tax
126
revenues.
> The social cost accounting for installation downtime differs from that used in estimating compliance-
related costs to regulated facilities, which were then used in the economic impact analyses discussed
elsewhere in this document. In the facility impact analysis, EPA accounts for downtime as the loss in net
income from temporary suspension of operations, in particular for electricity generation, both at Electric
Generators and Manufacturers. However, the cost to society from this suspension of operations differs
from the cost incurred by the regulated facilities. When generating units are out of service for installation
of compliance technology, other generating units provide the electricity that would otherwise have been
generated by the out-of-service units. The cost to society is the increase in electricity production costs
from other generators needing to supply the electricity otherwise produced by the (formerly lower cost)
out-of-service units. For details on how EPA estimated the social cost of technology installation
downtime, see Appendix I: Energy Effects.
> For Manufacturers, a similar concept, described above for technology installation downtime, applies to
the auxiliary energy requirement and energy penalty that results from operation of cooling towers
required under Proposal Option 2. For facilities that generate electricity, EPA accounts for the auxiliary
120 For the cost and economic impact analyses, compliance costs are measured as they affect the financial performance of the regulated
facilities and their parent entities. Therefore, these impact analyses consider the tax deductibility of compliance expenditures, as
appropriate depending on the tax status of the regulated facility and entity.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 7: Total Social Costs
energy requirement and energy penalty as lost electricity sales revenue or as the cost to purchase
replacement electricity. However, again, the cost to society is different: if other generating units provide
the electricity that cannot be delivered for consumption due to the energy penalty, then the cost to society
is the marginal production cost incurred by the other generating units in producing that electricity. As
discussed in Appendix I, no energy penalty is associated with operation of IM technologies.
For Electric Generators, EPA accounted for the auxiliary energy requirement and energy penalty resulting
from operation of cooling towers, and for the auxiliary energy requirement resulting from operation of IM
technologies, using the same methodology as that used in the economic impact analyses discussed
elsewhere in this document. For details on how EPA estimated the social cost of the auxiliary energy
requirement and energy penalty, see Appendix I.
As described in Chapter 3, for existing units at existing facilities, EPA assumed that facilities, in the aggregate,
would install compliance technology as follows. Under the final rule and Proposal Option 4, facilities are assumed
to achieve compliance via installation of IM technology during the 5-year window of 2018 through 2022. In the
lead-up to compliance, these facilities would incur various planning and other administrative-type costs; these
costs are expected to begin in 2014, the first year following promulgation. Because Proposal Option 2 involves
installation of entrainment-control technologies (closed-cycle recirculating systems) in addition to IM technology,
EPA anticipated that compliance with this option would occur over a longer timeframe. The Agency assumed that
non-nuclear Electric Generators and Manufacturers would install cooling towers during a 5-year window of 2021
through 2025, while nuclear Electric Generators would do so during a 5-year window of 2026 through 2030.127
Facilities that are already in compliance with regulatory requirements will not incur technology-installation costs
but may incur administrative costs, again beginning in 2014.
These assumptions result in an overall compliance window of nine years, 2014 through 2022 for the final rule and
Proposal Option 4, and a 17-year compliance window of 2014 through 2030 for Proposal Option 2, with the year
2030 being the last year of technology installation for any facility under any of the regulatory options considered
for this rule. EPA assumed that facilities would continue to incur capital costs to install replacement IM
technology, O&M costs, auxiliary energy requirement, energy penalty, and costs associated with annually and
non-annually recurring administrative activities through at least one cycle of compliance technology life over the
aggregate of regulated facilities.128 However, under Proposal Option 2, EPA assumed that facilities would not re-
install - i.e., completely rebuild - entrainment control technologies (required components such as piping and the
concrete basin can be reused). EPA developed a year-explicit schedule of compliance outlays over the 46-year
period of 2014 through 2059 according to cost-incurrence assumptions discussed in Chapter 3;129 however, unlike
the case with compliance-related costs to regulated facilities discussed in Chapter 3, this schedule explicitly
accounts for technology reinstallation and cost recurrence. In those instances when the estimated useful life of a
127 EPA assumed that it would take four years to install a cooling tower. Each of these technology-installation years represents the last
year of installation, i.e., the year when a cooling tower would begin to operate.
128 The social cost-analysis approach differs from the private cost analysis described in Chapter 3 and used in the subsequent impact
analyses discussed in Chapter 5: Economic Impact Analyses-Manufacturers, Chapter 4: Economic Impact Analyses-Electric
Generators, and Chapter 10: Regulatory Flexibility Act (RFA) Analysis. Those analyses do not explicitly account for continued
recurrence of these costs. However, they account for recurrence of these costs through use of annualized costs. The methodology for
social cost differs from the private cost analysis because of EPA's need to account for the aggregate of costs on a year-by-year basis
for all regulated facilities, based on explicit consideration of when costs would occur. That is, for the social cost analysis, costs are not
annualized for individual facilities; however, costs are annualized in the social cost analysis but for the total of facilities, with
allowance for costs over the full social cost analysis period.
129 The end of the analysis period, 2059, was determined based on the life of the longest-lived compliance technology (30 years), and the
last year of technology installation for any facility under any of the regulation options considered for this rule (2030). For this
analysis, EPA assumed that this last year of technology installation for all regulated facilities, in the aggregate, overlaps with the first
year of steady-state compliance with the final rule and other options considered.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 7: Total Social Costs
given compliance cost outlay extended beyond the remaining number of compliance years in the overall social
cost analysis period, EPA prorated the initial cost value based on the remaining number of compliance years in
the analysis.
In the same way as described in previous chapters, the social cost analysis assumes that all facilities with cooling
water system impoundments will qualify as baseline CCRS, and will not need to install additional technology
under the final rule and other options considered. To the extent that some of these facilities do not qualify as
baseline CCRS and would need to install additional compliance technology, the social costs reported in this
chapter may be underestimates. See Memorandum to the Record (DCN 12-2501) for the range of social costs
under the alternative assumptions.
For estimating the social cost of the new unit provision of the final rule at Electric Generators, EPA assumed that
the same number of new units, in terms of generating capacity, would come online each year during the 46-year
social cost analysis period, beginning in 2017.130 EPA accounted for compliance costs for these units on an as-
incurred basis, as it did for existing units at existing facilities.
EPA also included administrative costs to NPDES permitting authorities and the federal government discussed in
Chapter 3. The Agency accounted for these costs in the same way as that described above for regulated facilities.
Government administrative costs in the social cost analysis reflect the opportunity cost of expending taxpayer
dollars to administer this regulation in lieu of other public projects.
After creating a cost-incurrence schedule for each cost component for each facility, EPA summed these facility-
level costs for each year. The Agency then adjusted these costs for estimated real (i.e., inflation-adjusted) change
between their stated year and the year(s) of their incurrence as follows:
> All technology costs were first adjusted to their incurrence year(s) using the Construction Cost Index
(CCI) from McGraw Hill Construction, and then restated to a constant dollar basis using the Gross
Domestic Product (GDP) deflator index published by the U.S. Bureau of Economic Analysis (BEA);
> All administrative costs were adjusted to their incurrence year(s) using the Employment Cost Index (ECI)
Bureau of Labor Statistics (BLS), and then restated to a constant dollar basis using the GDP deflator.
> The foregone revenue associated with the auxiliary energy requirement, energy penalty, and downtime
were adjusted to their incurrence year(s) based on Annual Energy Outlook 2012 (AEO2012) electricity
price projections published by the Energy Information Administration (EIA) of the U.S. Department of
Energy (DOE). Unlike the technology and administrative cost adjustments, the AEO electricity price
projections are inflation-adjusted and thus require no further adjustment.
> As discussed in Appendix I, EPA developed variable generation costs used to estimate the cost of
auxiliary energy requirement, energy penalty, and downtime using IPM projections.131 Therefore, EPA
did not make any further adjustments to these costs.
EPA developed the CCI and ECI adjustment factors only through the year 2020 and AEO adjustment factors were
available through 2035; after these years, EPA assumed that the real change in prices is zero - that is, costs are
130 New units at existing facilities whose construction begins after the effective date of the final rule must comply with the new unit
provision of the final rule. EPA assumed that it will take approximately four years to construct a new unit and install a cooling tower;
therefore, the Agency assumed that 2017 will be the first year when any new unit subject to the final rule will come online.
131 These projections are based on the IPM V4.10_MATS platform, which EPA used to assess the impact of the final rule on national and
regional electricity markets using the Integrated Planning Model (IPM). For details on IPM and the electricity market analysis, see
Chapter 6: Electricity Market Analysis.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 7: Total Social Costs
expected to change in line with general inflation.lj2 This assumption is reasonable, given the uncertainty of long-
term future price projections.
After developing the year-explicit schedule of total social costs and adjusting them for predicted real change to
the year of their incurrence, EPA calculated the present value of these cost outlays as of the promulgation year by
discounting the cost in each year back to 2013, using both 3-percent and 7-percent discount rates. These discount
rate values reflect guidance from the Office of Management and Budget (OMB) regulatory analysis guidance
document, Circular A-4 (OMB, 2003). EPA calculated the constant annual equivalent value (annualized value),
again using the two values of the discount rate, 3 percent and 7 percent, over a 51-year social cost analysis period.
The 51-year period reflects the 46 years of potential cost incurrence, as described above, plus an additional five
years during which benefits stemming from reduced impingement and entrainment of aquatic organisms are
expected to accrue to society even though, for the social cost and benefit analysis, compliance technology is
assumed to have ceased functioning. That is, EPA estimates that benefits will continue for five years after the end
of the useful life of a compliance technology, and will decline to zero over this period.133
To estimate social costs of the final rule and other options considered, EPA assumed that the market prices for
labor, equipment, material, and other compliance resources needed to comply with the rule represent the
opportunity costs to society for use of those resources in regulatory compliance. The Agency also assumed that
the final rule and other options considered will not affect the aggregate quantity of electricity or other affected
goods and services sold to consumers. Thus, the social cost of regulatory requirements includes no loss in
consumer and producer surplus from reduced sales of electricity or other goods and services produced by
regulated facilities, given the small impact of the regulation on electricity production cost for the total industry
(see Chapter 6: Electricity Market Analysis). EPA's estimates include direct compliance costs for facilities
estimated to close because of regulatory requirements (i.e., policy closures). This approach may overstate the
social costs of compliance, to the extent that the net economic loss to society in facility closures is less than the
estimated cost to society of compliance.134
7.2 Key Findings for Regulatory Options
The following sections present EPA's estimates of social costs for the final rule and other options considered.
7.2.1 Costs of Regulatory Compliance
Table 7-1 presents annualized direct compliance costs for the existing unit provision of the final rule and other
options considered, for Electric Generators and Manufacturers. At the 3-percent discount rate, EPA estimates
annualized costs of compliance of $271.4 million for the existing unit provision of the final rule, $250.7 million
for Proposal Option 4, and $3,642.5 million for Proposal Option 2. At the 7-percent discount rate, these costs are
$294.3 million, $271.1 million, and $3,582.3 million, respectively. These costs include the direct costs of
132 EPA used the average of the year-to-year changes in the CCI and ECI over the most recent ten-year reporting period to bring these
values to specific cost incurrence years. EPA was not confident in projecting real changes in cost values beyond 2020; consequently,
in making this adjustment, the Agency assumed zero real growth starting in 2021.
133 See BA for a summary of benefits methodology and the phase-down of benefits following termination of compliance activities within
the social cost analysis period.
134 Including costs for regulatory closures yields an estimate of social costs assuming that all facilities, except those assessed as baseline
closures, would incur the costs of regulatory compliance and continue to operate post-regulation. Calculating costs as if all facilities
continue operating will overstate social costs if the social cost of compliance is greater than the net economic loss to society from
facility closure. Whether this result will hold depends, in part, on the difference between social and private discount rates, and the
marginal cost to society to replace the lost production of goods and services in closing facilities.
7-4
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 7: Total Social Costs
compliance, the cost of installation downtime as described above, and the administrative costs incurred by
regulated facilities.lj5
Table 7-1: Summary of Annualized Direct Compliance Costs - Existing Units (Millions; $2011; at 2013)a
Discount Rate
Proposal Option 4
Final Rule-Existing Units
Proposal Option 2
3%
$250.7
$271.4
$3,642.5
7%
$271.1
$294.3
$3,582.3
a. The costs presented in this table assume that all facilities with cooling water impoundments qualify as baseline CCRS, and incur no additional technology
costs for regulatory compliance (but do incur administrative costs). See Memorandum to the Record (DCN 12-2501) for the range of costs that could occur
based on whether these facilities would need to install additional compliance technology.
Source: U.S. EPA analysis for this report

Table 7-2 presents annualized direct compliance costs for new units at Electric Generators under the new unit
provision of the final rule and other new unit options considered. As reported in Table 7-2, using the 3-percent
discount rate, EPA estimates that the new unit provision of the final rule will result in $2.5 million in compliance
costs to facilities. Under other new unit options considered - Options A, B, and C - this cost would be $130.7
million, $52.7 million, and $12.5 million, respectively.1^6 Using the 7-percent discount rate, EPA estimates that
the new unit provision of the final rule will result in $1.9 million in compliance costs to facilities. Under the other
new unit options considered - Options A, B, and C - this cost would be $108.0 million, $43.5 million, and $10.3
million, respectively.
Table 7-2: Summary of Annualized Direct Compliance
Costs - New Units (Millions; $2011; at 2013)

Discount

Final Rule -
Rate
Option A
Option B
Option C
New Units
3%
$130.7
$52.7
$12.5
$2.5
7%
$108.0
$43.5
$10.3
$1.9
Source: U.S. EPA analysis for this report
As reported in Table 7-3, EPA estimates that under the final rule, Electric Generators and Manufacturers will
incur $273.8 million at the 3-percent discount rate and $296.2 million at the 7-percent discount rate, accounting
for both the existing unit provision (Table 7-1) and the new unit provision (Table 7-2).
Table 7-3: Total Annualized Direct Compliance Costs of the Final
Rule (Millions; $2011; at 2013)a
Discount Rate
Existing Units
New Units
Total
3%
$271.40
$2.50
$273.80
7%
$294.30
$1.90
$296.20
a. The costs presented in this table assume that all facilities with cooling water impoundments qualify
as baseline CCRS, and incur no additional technology costs for regulatory compliance (but do incur
administrative costs). See Memorandum to the Record (DCN 12-2501) for the range of costs that
could occur based on whether these facilities would need to install additional compliance technology.
Source: U.S. EPA analysis for this report
7.2.2 Costs of Government Administration of Regulatory Requirements
Table 7-4 summarizes government administrative costs under the final rule and other options considered, for
existing units at Electric Generators and Manufacturers. EPA estimates that the existing unit provision of the final
rule will result in $1.0 million (at both the 3-percent and 7-percent discount rates) in government administrative
costs. These findings are also true for Proposal Option 4. For Proposal Option 2, EPA estimates approximately
$0.7 million (3-percent and 7-percent discount rates). Under all options, State and Territory governments bear
135 For definition of existing unit options see Chapter 1.
130 For definition of new unit options see Chapter 1.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 7: Total Social Costs
almost all administrative costs of no more than $1.0 million, with the federal government bearing no more than
$0.04 million.
Table 7-4: Summary of Annualized Government Administrative Costs - Existing Units (Millions; $2011; at
2013)
Discount
Rate
Government
Level
Proposal Option 4
Final Rule - Existing Units
Proposal Option 2
3%
State/Territory
$1.0
$1.0
$0.7
Federal3
$0.0
$0.0
$0.0
Total"
$1.0
$1.0
$0.7
7%
State/Territory
$1.0
$1.0
$0.7
Federal3
$0.0
$0.0
$0.0
Total"
$1.0
$1.0
$0.7
a. The value is less than $40,000.
b. Values may not sum to totals due to independent rounding.
Source: U.S. EPA analysis for this report
Table 7-5 presents annualized administrative costs to States and federal government for new units at Electric
Generators under the new unit provision of the final rule and other new unit options EPA considered. EPA
assumed that all new units activity will occur in States with NPDES permitting authority. As reported in Table
7-5, using the 3-percent discount rate, EPA estimates that the new unit provision of the final rule will result in
$0.1 million in administrative costs to States. Under other new unit options considered - Options A, B, and C -
this cost would be $0.2 million, $0.1 million, and $0.1 million, respectively. Using the 7-percent discount rate, the
new unit provision of the final rule and other new unit options considered result in approximately the same
administrative costs as those estimated using the 3-percent discount rate.
Table 7-5: Summary of Annualized Government Administrative
Costs - New Units (Millions; $2011; at 2013)

Discount
Government

Final Rule -
Rate
Level
Option A
Option B
Option C
New Units

State/Territory
$0.2
$0.1
$0.1
$0.1
3%
Federal3
$0.0
$0.0
$0.0
$0.0

Total"
$0.2
$0.1
$0.1
$0.1

State/Territory
$0.1
$0.1
$0.1
$0.1
7%
Federal3
$0.0
$0.0
$0.0
$0.0

Total"
$0.1
$0.1
$0.1
$0.1
a. EPA assumed that all new units activity will occur in States with NPDES permitting
authority.

b. Values may not sum to totals due to independent rounding.

Source: U.S. EPA analysis for this report

As reported in Table 7-6, EPA estimates that States and the federal government will incur approximately $1.1
million at both the 3-percent and 7-percent discount rates, to administer both the existing unit provision (Table
7-4) and the new unit provision (Table 7-5) of the final rule to Electric Generators and Manufacturers. As
described in Chapter 3, EPA notes that these costs do not account for the costs that permitting authorities
otherwise incur for administering permits on the basis of Best Professional Judgment (BPJ) determinations, as
currently occurs in the absence of a national 316(b) regulation. To the extent that permitting authorities incur such
costs, the incremental costs of the regulation are overstated - as the BPJ costs would be subtracted from the
estimated administrative costs to calculate society's incremental costs for permit development and administration.
It is possible that the administrative costs now being incurred by permitting authorities exceed the costs reported
here for permit administration. In this case, the rule's incremental costs for permit administration would be
negative (see Memorandum to the Record (DCN 12-2504) for a discussion of permitting authorities' activities in
development of BPJ permits).
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 7: Total Social Costs
Table 7-6: Total Annualized Government Administrative
Costs for the Final Rule (Millions; $2011; at 2013)
Discount
Government

Rate
Level
Existing Units
New Units3
Total"

State/Territory
$1.0
$0.1
$1.1
3%
Federal
$0.0
$0.0
$0.0

Total"
$1.0
$0.1
$1.1

State/Territory
$1.0
$0.1
$1.0
7%
Federal
$0.0
$0.0
$0.0

Total"
$1.0
$0.1
$1.1
a. EPA assumed that all new units activity will occur in States with NPDES
permitting authority.

b. Values may not sum to totals due to independent rounding.

Source: U.S. EPA analysis for this report

7.2.3 Total Social Cost
Table 7-7 reports the total annualized social costs, including direct compliance costs to regulated facilities and
administrative costs to State and federal governments, discounted at both 3-percent and 7-percent rates, for
existing units at Electric Generators and Manufacturers. At the 3-percent discount rate, total social costs are
$272.4 million for the existing unit provision of the final rule, $251.8 million for Proposal Option 4, and $3,643.2
million for Proposal Option 2. At the 7-percent discount rate, these costs are $295.3 million for the existing unit
provision of the final rule, $272.1 million for Proposal Option 4, and $3,583.0 million for Proposal Option 2.
Compliance costs account for the larger share of total social costs across all three analyzed options, with
government administrative costs accounting for less than 1 percent.
Table 7-7: Summary of Total Social Costs - Existing Units (Millions; $2011; at 2013)a
Discount
Rate
Cost Category
Proposal Option 4
Final Rule-Existing Units
Proposal Option 2
3%
Compliance Cost
$250.7
$271.4
$3,642.5
Gov. Admin.
$1.0
$1.0
$0.7
Total"
$251.8
$272.4
$3,643.2
7%
Compliance Cost
$271.1
$294.3
$3,582.3
Gov. Admin.
$1.0
$1.0
$0.7
Total"
$272.1
$295.3
$3,583.0
a. The costs presented in this table assume that all facilities with cooling water impoundments qualify as baseline CCRS, and may incur no additional
technology costs for regulatory compliance (but do incur administrative costs). See Memorandum to the Record (DCN 12-2501) for the range of costs that
could occur based on whether these facilities would need to install additional compliance technology..
b. Values may not sum to totals due to independent rounding.
Source: U.S. EPA analysis for this report
Table 7-8 presents total annualized social costs for new units at Electric Generators under the new unit provision
of the final rule and other new unit options EPA considered1^7. As reported in Table 7-8, using the 3-percent
discount rate, EPA estimates that the new unit provision of the final rule will result in $2.5 million in total social
costs. Under other new unit options considered - Options A, B, and C - this cost would be $130.9 million, $52.8
million, and $12.6 million, respectively. Using the 7-percent discount rate, EPA estimates that the new unit
provision of the final rule will result in $2.0 million in compliance costs to facilities. Under the other new unit
options considered - Options A, B, and C - this cost would be $108.2 million, $43.6 million, and $10.4 million,
respectively.
137 As discussed in Chapter 3, the Agency expects compliance costs associated with new units at Manufacturers will be negligible in total.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 7: Total Social Costs
Table 7-8: Summary of Total Social Costs - New Units (Millions;
$2011; at 2013)
Discount
Rate
Cost Category
Option A
Option B
Option C
Final Rule - New
Units
3%
Compliance Cost
$130.7
$52.7
$12.5
$2.5
Gov. Admin.3
$0.2
$0.1
$0.1
$0.1
Total"
$130.9
$52.8
$12.6
$2.5
7%
Compliance Cost
$108.0
$43.5
$10.3
$1.9
Gov. Admin.3
$0.1
$0.1
$0.1
$0.1
Total"
$108.2
$43.6
$10.4
$2.0
a. EPA assumed that all new unit activity will occur in States with NPDES permitting authority.
b. Values may not sum to totals due to independent rounding.
Source: U.S. EPA analysis for this report
Table 7-9 reports total annualized social costs for the final rule, including the existing unit provision (Table 7-7)
and the new unit provision (Table 7-8). As reported in Table 7-9, EPA estimates that the final rule will result in
$274.9 million at the 3-percent discount rate and $297.3 million at the 7-percent discount rate in total social costs.
The new unit provision accounts for less than 1 percent of total costs.
Table 7-9: Total Social Costs of the Final Rule
Millions; $2011; at2013)a
Discount Rate
Cost Category
Existing Units
New Units"
Total"
3%
Compliance Cost
$271.4
$2.5
$273.8
Gov. Admin.
$1.0
$0.1
$1.1
Total0
$272.4
$2.5
$274.9
7%
Compliance Cost
$294.3
$1.9
$296.2
Gov. Admin.
$1.0
$0.1
$1.1
Total0
$295.3
$2.0
$297.3
a. The costs presented in this table assume that all facilities with cooling water impoundments qualify as baseline
CCRS, and incur no additional technology costs for regulatory compliance (but do incur administrative costs). See
Memorandum to the Record (DCN 12-2501) for the range of costs that could occur based on whether these facilities
would need to install additional compliance technology.
b. EPA assumed that all new unit activity will occur in States with NPDES permitting authority.
c. Values may not sum to totals due to independent rounding.
Source: U.S. EPA analysis for this report
Table 7-10, Table 7-11 and Table 7-12 provide the time profiles of costs for the broad cost categories: direct
compliance costs, administrative costs, and total social costs for the existing unit provision of the final rule,
Proposal Option 4, and Proposal Option 2, respectively. The largest compliance outlays occur over the years 2018
through 2022 (the existing unit provision of the final rule and Proposal Option 4) and 2018 through 2030
(Proposal Option 2), when regulated facilities make capital outlays for compliance technology and incur
technology-installation downtime.138 As stated above, EPA does not expect regulated facilities to re-install
cooling towers. Replacement of IM capital equipment and consequent additional capital outlays are required for
all facilities under the final rule and Proposal Option 4, and for some facilities (i.e., facilities installation IM
technologies) under Proposal Option 2, reflected in the higher costs in year 2038 through 2047.
Table 7-13 presents time profiles of total social costs including compliance costs to facilities and administrative
costs to States and the federal government, for new units at Electric Generators under the final rule and other new
unit options considered. Table 7-14 presents the time profile of total social costs of the final rule, including the
existing unit provision (Table 7-11) and the new unit provision (Table 7-13).
138 As discussed in Chapter 3, EPA assumed that it would take facilities four years to install cooling towers, considered under Proposal
Option 2, with the fourth year being the year of technology-installation downtime. Therefore, while 2021 is the first year any facilities
required to install a cooling tower experiences technology-installation downtime, 2018 is the first year any such facility begins to
occur capital costs for installation of a cooling tower.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 7: Total Social Costs
Table 7-10: Time Profile of Total Social Costs for Proposal Option 4
(Millions; $2011)
Year
Compliance Costs
Administrative Costs
Total
2013
$0.0
$0.0
$0.0
2014
$47 8
$0 3
$48 1
2015
$90.2
$0 0
$90.2
2016
$98.0
$0 0
$98 0
20I7
$88.5
$2 0
$90.5
2018
1.6

$593.7

$874.7
$2 0
$876.7
2020
$870.7
$2 0
$872.7
2021
W>
$3 0
1.6
2022
$1,144.1
$0 8
5.0
2023
*.0
$0 8
8.8
2024
\6
$0 8
r>.4
2025
7.3
$0 8
8.2
2026
<1
$0 8
8.9
2027
7.0
$1.1
8.1
2028

9.6
2029
>4

2030
).5

:>.5
2031
4.1

9.1
2032
7.0
$1.1
8.1
2033

9.6
2034
>4

2035
).5

:>.5
2036
4.1

9.1
2037
7.0
$1.1
8.1
2038
$389.0

$390.1
2039
$408 9

9.9
2040
$308.8

$309.8
2041
$3504

$351 5
2042
$554.2
$1.1
5.2
2043
1.9

3.0
2044
$341.1

$342.2
2045
$392.2

$393.2
2046
\8

f>.8
2047
$321.4
$1.1
$322.4
2048
J.I

:>.l
2049
>4

2050
$130.3

2051
$130 1

2052
$127.4
$1.1
8.5
2053

9.6
2054
>4

2055
).5

:>.5
2056
>0

2058
4.3
$0 9
9.2
2059
$137.0
$0 9
$137.9
2060

$0 0

2061
$0 0
$0 0
$0 0
2062
$0 0
$0 0
$0 0
2063
$0 0
$0 0
$0 0
2064
$0.0
$0.0
$0.0
Present Value, 3%
$6,702.1
$27.2
$6,729.3
Annualized, 3%
$250.7
$1.0
$251.8
Present Value, 7%
$4,012.6
$15.1
$4,027.8
Annualized, 7%
$271.1
$1.0
$272.1
Source: U.S. EPA analysis for this report
May 2014
7-9
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 7: Total Social Costs
Table 7-11: Time Profile of Total Social Costs for Final Rule-Existing Units
(Millions; $2011)
Year
Compliance Costs
Administrative Costs
Total
2013
$0.0
$0.0
$0.0
2014
$47 8

$48 1
2015
$90.2
$0 0
$90.2
2016
$98 0

$98 0
20I7
$88 5
$2 0
$90.5
2018
$655 8
$2 1
$657.8
2019
$927 3
[)
$929 3
2020
$1,087 0
$2.0
.U)
2021
$623 8
$3.0
V8
2022
$1,229 5
$0 8
).4
2023
5
8
4.3
2024
$131.1
8
1.9
2025
8
$0.8

2026
6
8

2027
5

$1336
2028
$134.1
1)
5.1
2029
9
1)
<.9
2030
0
1)
V0
2031
6

4.6
2032
5

$1336
2033
$134.1
1)
5.1
2034
9
1)
<.9
2035
0
1)
VO
2036
6

4.6
2037
5

$1336
2038
$411.7
1)
2.8
2039
$423 8
1)
4.8
2040
$323 6
1)
$324.6
2041
$363 2

$364.3
2042
$571 2

2.3
2043
0
1)
5.0
2044
$366 6
1)
$367.6
2045
7
1)

2046
$201 3

$202.3
2047
$359 7

$360.7
2048
0
1)
$138.0
2049
4
1)

2050
0
1)
¦?.()
2051
2

$137 3
2052
7

4.8
2053
$134.1
1)
5.1
2054
9
1)
<.9
2055
0
1)
VO
2056
5
1)
2.6
2057
9
$1 0
¦)})
2058
5
9
V4
2059
$143.0
$0.9
$143.9
2060

$0 0

2061
$0.0
$0.0
$0 0
2062
$0 0
$0 0
$0 0
2063
$0 0
$0 0
$0 0
2064
$0.0
$0.0
$0.0
Present Value, 3%
$7,253.5
$27.2
$7,280.7
Annualized, 3%
$271.4
$1.0
$272.4
Present Value, 7%
$4,355.4
$15.1
$4,370.5
Annualized, 7%
$294.3
$1.0
$295.3
Source: U.S. EPA analysis for this report
7-10
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 7: Total Social Costs
Table 7-12: Time Profile of Total Social Costs for Proposal Option 2
(Millions; $2011)

Year
Compliance Costs
Administrative Costs
Total
2013
$0.0
$0.0
$0.0
2014
$24.4
$0.4
$24.8
2015
$36.3
$0.2
$36.5
2016
$35.5
$0.2
$35.7
2017
$34.9
$1.1
$36.0
2018
$3,196.3
$1.0
$3,197.3
2019
$4,824.0
$1.3
$4,825.2
2020
$7,430.8
$1.2
$7,432.1
2021
$9,838.4
$1.4
$9,839.8
2022
$8,925.6
$0.8
$8,926.4
2023
$9,013.6
$0.7
$9,014.3
2024
$7,338.4
$0.6
$7,339.1
2025
$6,516.4
$0.6
$6,517.0
2026
$5,083.0
$0.6
$5,083.6
2027
$4,854.1
$0.7
$4,854.8
2028
$4,508.9
$0.7
$4,509.6
2029
$4,258.7
$0.7
$4,259.4
2030
$4,158.2
$0.7
$4,158.9
2031
$3,244.0
$0.7
$3,244.7
2032
$3,249.4
$0.7
$3,250.2
2033
$3,252.2
$0.7
$3,252.9
2034
$3,278.9
$0.7
$3,279.6
2035
$3,300.9
$0.7
$3,301.6
2036
$3,300.8
$0.7
$3,301.5
2037
$3,300.5
$0.7
$3,301.2
2038
$3,329.9
$0.7
$3,330.6
2039
$3,322.9
$0.7
$3,323.6
2040
$3,320.8
$0.7
$3,321.5
2041
$3,364.4
$0.7
$3,365.1
2042
$3,340.9
$0.7
$3,341.6
2043
$3,356.2
$0.7
$3,356.9
2044
$3,364.4
$0.7
$3,365.1
2045
$3,464.6
$0.7
$3,465.3
2046
$3,388.5
$0.7
$3,389.2
2047
$3,364.7
$0.7
$3,365.4
2048
$3,312.1
$0.7
$3,312.8
2049
$3,335.5
$0.7
$3,336.2
2050
$3,305.1
$0.7
$3,305.8
2051
$3,301.7
$0.7
$3,302.4
2052
$3,301.3
$0.7
$3,302.0
2053
$3,300.4
$0.7
$3,301.1
2054
$3,304.1
$0.7
$3,304.8
2055
$3,300.9
$0.7
$3,301.6
2056
$3,300.0
$0.7
$3,300.7
2057
$3,299.1
$0.7
$3,299.8
2058
$3,301.3
$0.7
$3,302.0
2059
$3,301.7
$0.6
$3,302.3
2060
$0.0
$0.0
$0.0
2061
$0.0
$0.0
$0.0
2062
$0.0
$0.0
$0.0
2063
$0.0
$0.0
$0.0
2064
$0.0
$0.0
$0.0
Present Value, 3%
$97,364.2
$18.2
$97,382.4
Annualized, 3%
$3,642.5
$0.7
$3,643.2
Present Value, 7%
$53,021.4
$10.0
$53,031.4
Annualized, 7%
$3,582.3
$0.7
$3,583.0
Source: U.S. EPA analysis for this report
May 2014
7-11
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 7: Total Social Costs
Table 7-13: Time Profile of Total Social Costs - New Units (Millions; $2011)

Final Rule - New
Year
Option A
Option B
Option C
Units
2013
$0.0
$0.0
$0.0
$0.0
2014
$20.4
$8.2
$2.0
$0.4
2015
$41.1
$16.5
$3.8
$677
2016
$62.3
$25.1
$5.8
$679
2017
$87.7
$35.4
$8.1
'$'0
2018
$92.5
$37.3
$8.6
$1.4
2019
$97.4
$39.2
$9.1
$175
2020
$10273
$41.2
$9.6
$1/7
2021
$T06.0
$42/7
$To7o
$178
2022
$109.7
$44.2
sio7i
$179
2023

$45.8
$T6''.'8
$276
2024
jTT'y 4
$47.3'
$Ti7'i
$271
2025
$121.1
$48.8
$11.5
$272
2026
$124.8
$50.3
$11.9
$2.3
2027
$I'28.'6
$51.8
$12.3
$24
2028
$132.3
$5373
$12.7
$275
2029
$136.1
$54.9
$13.1
$276
2030
$139.9
$56.4
$13.4
$277
2031
$143.9
$58.0
$13.8
$278
2032
$147.7
$59.6
$14.2
$279
2033
$151.6
$61.1
$14.6
$376
2034
$155.9
$62.9
$15.1
$371
2035
$1604
$64.7
$15.5
$372
2036
$164.2
$66.2
$15.9
$373
2037
$168.1
$67.8
$16.3
'$34
2038
$TvT.9
$69.3'
$16.7
$375
2039
$T75."8
$70.9
$17.1
$376
2040
$TV9.6
$724
$17.5'
'$377
2041
$183.4
$74.0
$17.9
$378
2042
$187.3'
$75.5
$18.3'
$379
2043
$191.1
$77.1
$18.6
$46
2044
$194.9
$78.6
$T'9.'6
$471
2045
$198.8
$80.1
$19.4
$472
2046
$202.6
$81.7
$19.8
$473
2047
$2064
$83.2
$26.2
$44
2048
$21073
$848
$26.6
$475
2049
$214.1
$86.'3
$2i7'6
$476
2050
$2179
$87.9
$21.4
$477
2051
$22178
$894
$21.8
$478
2052
$22576
$91.0
$22.2
$479
2053
$229.4
$92.5'
$22.6
$576
2054
$233.3'
$94.1
$22.9
$571
2055
$237'. 1
$95.6
$2373
$572
2056
$24L0
$97.2
$23.7
$573
2057
$244.8
$98.7
$24.1
$54
2058
$248.'6
$16673
$24.5'
$575
2059
$252.5'
sT617s
$24.9
$576
2060
S(7(i
S(T(i
S(T(i
$676
2061
$0.0
$0.0
$0.0
$0.0
2062
S(7(i
S(T(i
S(T(i
$676
2063
Soli
$676'
$676'
$676
2064
$0.0
sTiTi
sTiTi
$676
Present Value, 3%
$3,498.6
$1,410.5
$337.6
$68.1
Annualized, 3%
$130.9
$52.8
$12.6
$2.5
Present Value, 7%
$1,600.9
$645.4
$153.3
$29.6
Annualized, 7%
$108.2
$43.6
$10.4
$2.0
Source: U.S. EPA analysis for this report
7-12
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 7: Total Social Costs
Table 7-14: Time Profile of Total Social Costs (Millions; $2011)
Year
Existing Units
New Units
Total
2013
$0.0
$0.0
$0.0
2014
$48.1
$0.4
$48.5
2015
$90.2
$0.7
$90.8
2016
$98.0
$0.9
$98.9
2017
$90.5
$1.3
$91.8
2018
$657.8
$1.4
$659.3
2019
$929.3
$1.5
$930.8
2020
$1,089.0
$1.7
$1,090.6
2021
$626.8
$1.8
$628.6
2022
$1,230.4
$1.9
$1,232.2
2023
$124.3
$2.0
$126.3
2024
$131.9
$2.1
$134.0
2025
$133.7
$2.2
$135.8
2026
$134.4
$2.3
$136.7
2027
$133.6
$2.4
$135.9
2028
$135.1
$2.5
$137.5
2029
$138.9
$2.6
$141.5
2030
$136.0
$2.7
$138.6
2031
$134.6
$2.8
$137.4
2032
$133.6
$2.9
$136.4
2033
$135.1
$3.0
$138.1
2034
$138.9
$3.1
$142.0
2035
$136.0
$3.2
$139.1
2036
$134.6
$3.3
$137.9
2037
$133.6
$3.4
$136.9
2038
$412.8
$3.5
$416.2
2039
$424.8
$3.6
$428.4
2040
$324.6
$3.7
$328.3
2041
$364.3
$3.8
$368.1
2042
$572.3
$3.9
$576.2
2043
$195.0
$4.0
$199.0
2044
$367.6
$4.1
$371.7
2045
$517.7
$4.2
$521.9
2046
$202.3
$4.3
$206.6
2047
$360.7
$4.4
$365.1
2048
$138.0
$4.5
$142.5
2049
$141.5
$4.6
$146.0
2050
$138.0
$4.7
$142.7
2051
$137.3
$4.8
$142.1
2052
$134.8
$4.9
$139.7
2053
$135.1
$5.0
$140.1
2054
$138.9
$5.1
$144.0
2055
$136.0
$5.2
$141.2
2056
$132.6
$5.3
$137.9
2057
$129.9
$5.4
$135.3
2058
$156.4
$5.5
$161.9
2059
$143.9
$5.6
$149.5
2060
$0.0
$0.0
$0.0
2061
$0.0
$0.0
$0.0
2062
$0.0
$0.0
$0.0
2063
$0.0
$0.0
$0.0
2064
$0.0
$0.0
$0.0
Present Value, 3%
$7,280.7
$68.1
$7,348.8
Annualized, 3%
$272.4
$2.5
$274.9
Present Value, 7%
$4,370.5
$29.6
$4,400.1
Annualized, 7%
$295.3
$2.0
$297.3
Source: U.S. EPA analysis for this report
May 2014
7-13
-------
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
8 Social Costs and Benefits
This chapter compares national monetized benefits and social costs for the final rule and other options EPA
considered. The social costs in this analysis include (1) costs to Electric Generators and Manufacturers to comply
with the final rule, and (2) costs to State and federal governments to administer regulatory compliance. Some
potentially significant benefit categories have not been fully monetized, and thus the national monetized benefits
are likely to understate substantially the rule's expected benefits to society.lj9 EPA conducted this analysis for the
existing and new unit provisions. For details on the analysis of social costs, see Chapter 7: Total Social Costs in
this document. For details on the analysis of benefits, see the Benefits Assessment (BA) report (U.S. EPA, 2014a).
This chapter also satisfies the requirements of Executive Order 12866: Regulatory Planning and Review and
Executive Order 13563: Improving Regulation and Regulatory Review.
8.1 Summary of Benefits Estimation for the Final Rule
Benefits from the final rule occur due to the reduction in impingement mortality and entrainment (IM&E) at
cooling-water intake structures (CWISs) affected by the rule. IM&E kills or injures large numbers of aquatic
organisms at all life stages. By reducing the levels of IM&E, the final rule and other options considered would
increase the number of fish, shellfish, and other aquatic organisms in the affected waterbodies. This in turn would
directly and indirectly improve use benefits such as those associated with recreational and commercial fisheries,
and other types of benefits, including nonuse values of the affected resources. The BA Chapter 4: Economic
Benefit Categories Associated with IM&E Reduction provides an overview of the types and sources of benefits
anticipated and how these benefits are estimated (i.e., monetized, quantified but not monetized, or assessed
qualitatively) (U.S. EPA, 2014a). Chapter 5 through Chapter 9 and Chapter 12 of the BA report provide detailed
descriptions of the methodologies used to analyze the benefits of the final rule and other options considered.
The economic benefits of the final rule and other options considered can be broadly defined according to
categories of goods and services provided by the species that are affected by IM&E from CWISs. The first
category includes benefits that pertain to the use (direct or indirect) of the affected fishery resources. The "direct
use" benefits of the options include both "market" commodities (e.g., commercial fisheries) and ""nonmarket"
goods (e.g., recreational angling). Indirect use benefits also can be linked to either market or nonmarket goods and
services. An example of an indirect use benefit would be the manner in which reduced IM&E-related losses of
forage species leads through the aquatic ecosystem food web to enhance the biomass of species targeted for
commercial (market) and recreational (nonmarket) uses.
The second category includes benefits that are independent of any current or anticipated use of the resource; these
are known as "nonuse" or "passive use" values. Nonuse benefits reflect human values associated with existence
and bequest motives, or willingness to pay (WTP) for the knowledge that an ecosystem is functioning without the
effects of human activity, or to pass such ecosystem function on to future generations.
EPA estimated the economic benefits from the regulatory options using a range of valuation methods, depending
on the benefit category, data availability, and other relevant factors. Commercial fishery benefits are valued using
market data. Recreational angling benefits are valued using a benefit-transfer approach. Nonuse values were
partially estimated for two of the seven benefits regions using a separate benefit transfer approach. Agency
benefits estimates are based on projected numbers of age-one equivalent fish saved and changes in harvest under
139 See BA Chapter 4: Economic Benefit Categories Associated with IM&E Reduction of the Benefits Analysis for additional discussion
of benefits categories monetized by EPA.
May 2014
8-1
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
final regulatory options. EPA also estimated benefits associated with changes in C02-equivalent emissions based
on the social cost of carbon.
EPA derived national benefit estimates for the final rule and other options considered from a series of regional
studies across the country representing a range of waterbody types and aquatic resources. EPA obtained national
benefit estimates by summing regional benefits. EPA calculated the monetary value of benefits of the national
regulatory options for existing facilities using two discount rate values: 3 percent and 7 percent. All dollar values
presented are in 2011 dollars (annual average). Because avoided fish deaths occur mainly in fish that are younger
than harvestable age (eggs, larvae, and juveniles), the estimated use benefits from avoided IM&E include a
biological lag to account for the time required for fish to grow and mature to harvestable size. Appendix D of the
BA provides detail on the time profile of expected benefits.
8.2 Comparison of Benefits and Social Costs by Option
Chapter 7 in this document and Chapter 13: National Benefits in the BA present estimates of social costs and
benefits, respectively, for the final rule and other options considered. In the same way as described in previous
chapters, the social cost and benefits analysis assumes that all facilities with cooling water system impoundments
will qualify as baseline CCRS, and may not need to install additional technology under the final rule and other
options considered. To the extent that some of these facilities do not qualify as baseline CCRS and would need to
install additional compliance technology, the social costs and benefits reported in this chapter may be
underestimates. See Memorandum to the Record (DCN 12-2501) for the range of social costs and benefits under
the alternative assumptions.
As documented in the BA, the monetized benefit values EPA developed for the regulatory options presented in
this chapter include estimated use values for commercial and recreational fishing (including recreational use value
of threatened and endangered species) for all benefits regions, estimated partial nonuse values for two of the seven
benefit regions, and national benefits associated with changes in C02 equivalent emissions. EPA is unable, at this
time, to estimate a monetized value of nonuse benefits from reduced IM&E in all of the seven benefits regions
because of limitations in the valuation literature. As described in Chapter 3 of the BA, the harvested commercial
and recreational fish species that have direct use values comprise between 1 and 10 percent of baseline IM&E in
each region, with a national average of 3 percent. The remaining 97 percent of IM&E includes unharvested
recreational and commercial fish and forage fish which do not have direct use values. EPA's nonuse analysis was
limited to two of the seven benefit regions and EPA did not estimate values for unharvested fish in the remaining
five benefits regions. The total estimated benefits are likely to be significantly understated due to the regional
limitations of EPA's nonuse analysis and the relatively large fraction of IM&E reductions that are not
commercially or recreationally harvested. EPA also did not assess use values other than commercial and
recreational fishing, such as improved recreation opportunities for non-fishing activities (e.g., diving or wildlife
viewing), in this analysis. EPA notes, however, that recreational users other than fishers (e.g., divers) are likely to
have positive use values for all fish and shellfish species, including commercially and recreationally targeted
species as well as for forage species. Although the analysis omits some categories of use benefits (i.e., benefits for
recreational users other than fishers), EPA captured the likely largest use-value categories (i.e., commercial and
recreational fishing).
As stated above, EPA was unable to use benefit transfer to generate national estimates of nonuse benefits for the
final rule and other options considered. EPA's nonuse analysis generated estimates of nonuse values for resource
changes expected to result in the North Atlantic and Mid-Atlantic benefit regions from the final options, but EPA
was unable to estimate reliable nonuse valuations for changes expected to result in other study regions. EPA
developed and fielded an original stated preference survey to estimate total WTP for improvements to fishery
resources affected by IM&E from regulated facilities (75 FR 42,438, July 21, 2010). The survey attempted to
assess how much survey respondents would be willing to pay for improvements to fishery resources affected by
8-2
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
IM&E from regulated facilities. EPA presents preliminary benefits estimates based on the stated preference
survey in Chapter 77 of the BA. However, given that reviews of the stated preference survey and its results
remain ongoing, and in consideration of the diversity of public comments on potential use of the stated preference
survey, EPA decided not to rely on the survey results in estimating the rule's total benefits or to use them in
decision-making for this rule.
Table 8-1 presents EPA's estimates of monetized benefits and total social costs for the existing unit provision of
the final rule and other options considered, at 3 percent and 7 percent discount rates, and annualized over 51
years. As stated above, the benefits values used in this analysis include benefits associated with changes in
greenhouse gas emissions for both existing and new units at existing facilities (for details see Chapter 9 of the BA
report). At the 3 percent discount rate, EPA estimates that social costs exceed mean monetized benefits by $239.4
million for the final rule, and $220.8 million and $5.2 billion for Proposal Options 4 and 2, respectively. At the 7
percent discount rate, social costs exceed mean monetized benefits by $266.6 million for the final rule, by $244.9
million for Proposal Option 4, and by $4.7 billion for Proposal Option 2. Note that these net benefit estimates are
understated because nonuse benefits are understated.
Table 8-1: Total Annualized Benefits and Social Costs - Existing Units (Millions;
$2011; at 2013)a

Discount Rate
Option
3%
7%
Proposal Option 4
Total Monetized Benefits'5
$31.0
$27.2
Total Social Costs,c
$251.8
$272.1
Final Rule-Existing Units
Total Monetized Benefits'5
$33.0
$28.7
Total Social Costs,c
$272.4
$295.3
Proposal Option 2
Total Monetized Benefits'5
-$1,542.6
-$1,148.2
Total Social Costs,c
$3,643.2
$3,583.0
a. As described in previous chapters, the social costs and benefits presented in this table assume that all facilities with
cooling water impoundments qualify as baseline CCRS, and incur no additional technology costs for regulatory
compliance (but do incur administrative costs). See Memorandum to the Record (DCN 12-2501) for the range of costs
and benefits that could occur based on whether these facilities would need to install additional compliance technology.
b. Total Monetized Benefits are the estimated "mean" values. Additional "low" and "high" value estimates are
presented in Chapter IS of the BA report. These values also include benefits associated with changes in greenhouse
gas emissions.
c. Total Social Costs include compliance costs to facilities and government administrative costs.
Source: U.S. EPA analysis for this report
Table 8-2 presents EPA's estimates of monetized benefits and social costs for the new unit provision of the final
rule and other new unit options considered in development of the final rule.
May 2014
8-3
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
Table 8-2: Total Benefits and Social Costs - New Units (Millions; $2011; at 2013)

Discount Rate
Option
3%
7%
Option A
Total Monetized Benefits3
-$1.1
$0.6
Total Social Costs5
$130.9
$108.2
Option B
Total Monetized Benefits3
-$1.3
-$0.4
Total Social Costs5
$52.8
$43.6
Option C
Total Monetized Benefits3
-$0.9
-$0.5
Total Social Costs'5
$12.6
$10.4
Final Rule - New Units
Total Monetized Benefits3
-$0.2
-$0.1
Total Social Costs5
$2.5
$2.0
a. Total Monetized Benefits are the estimated "mean" values. Additional "low" and "high" value estimates are presented in
Chapter IS of the BA report. These values also include benefits associated with changes in greenhouse gas emissions.
b. Total Social Costs include compliance costs to facilities and government administrative costs.
Source: U.S. EPA analysis for this report

Table 8-3 presents total monetized benefits and total social costs of the final rule, including the existing and new
unit provisions, for Electric Generators and Manufacturers. As shown in Table 8-3, EPA estimates that under the
final rule, social costs exceed mean monetized benefits by $242.1 million at the 3-percent discount rate and by
$268.7 million at the 7-percent discount rate. Note that these net benefit estimates are understated because nonuse
benefits are understated.
Table 8-3: Total Benefits and Social Costs of the Final Rule (Millions; $2011; at
2013)a

Discount Rate
Option
3%
7%
Existing Units
Total Monetized Benefits'5
$33.0
$28.7
Total Social Costsc
$272.4
$295.3
New Units
Total Monetized Benefits'5
-$0.2
-$0.1
Total Social Costsc
$2.5
$2.0
Total
Total Monetized Benefits'5
$32.8
$28.6
Total Social Costsc
$274.9
$297.3
a. As described in previous chapters, the social costs and benefits presented in this table assume that all facilities with
cooling water impoundments qualify as baseline CCRS, and incur no additional technology costs for regulatory
compliance (but do incur administrative costs). See Memorandum to the Record (DCN 12-2501) for the range of costs
and benefits that could occur based on determination of whether an impoundment qualifies as baseline CCRS.
b. Total Monetized Benefits are the estimated "mean" values. Additional "low" and "high" value estimates are
presented in BA Chapter IS. These values also include benefits associated with changes in greenhouse gas emissions.
c. Total Social Costs include compliance costs to facilities and government administrative costs.
Source: U.S. EPA analysis for this report
The following tables provide additional detail on net benefits. Table 8-4 presents time profiles of benefits and
social costs for the existing unit provision of the final rule and other options considered. EPA estimated benefits
assuming the same technology-installation schedule and analysis periods as those assumed for social costs (see
Chapter 7 in this document). Table 8-5 presents the time profiles of monetized benefits and total social costs for
both the existing and new unit provisions of the final rule.
8-4
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
Table 8-4: Time Profile of Benefits and Social Costs by Option (Millions; $2011)

Proposal Option 4
Final Rule - Existing Units
Proposal Option 2

Total Monetized

Year
Benefits
Total Social Costs
Benefits
Total Social Costs
Benefits
Total Social Costs
2013
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
2014
$0.0
$48.1
$0.0
$48.1
$0.0
$24.8
2015
$8.6
$90.2
$8.6
$90.2
$0.0
$36.5
2016
$8.9
$98.0
$8.9
$98.0
$0.0
$35.7
2017
$9.1
$90.5
$9.1
$90.5
$0.0
$36.0
2018
-$1.8
$593.7
-$1.5
$657.8
$137.9
$3,197.3
2019
-$1.8
$876.7
-$1.6
$929.3
$144.8
$4,825.2
2020
-$0.8
$872.7
-$0.2
$1,089.0
$149.5
$7,432.1
2021
$0.7
$611.6
$1.6
$626.8
-$1,266.2
$9,839.8
2022
$7.3
$1,145.0
$8.8
$1,230.4
-$1,271.2
$8,926.4
2023
$58.9
$118.8
$60.9
$124.3
-$1,450.4
$9,014.3
2024
$68.9
$126.4
$71.4
$131.9
-$1,456.4
$7,339.1
2025
$72.9
$128.2
$75.6
$133.7
-$1,470.8
$6,517.0
2026
$75.0
$128.9
$77.8
$134.4
-$2,510.1
$5,083.6
2027
$76.7
$128.1
$79.5
$133.6
-$2,555.9
$4,854.8
2028
$77.7
$129.6
$80.6
$135.1
-$2,603.6
$4,509.6
2029
$78.7
$133.4
$81.6
$138.9
-$2,650.1
$4,259.4
2030
$79.7
$130.5
$82.6
$136.0
-$2,702.0
$4,158.9
2031
$79.7
$129.1
$82.6
$134.6
-$1,946.7
$3,244.7
2032
$80.7
$128.1
$83.5
$133.6
-$1,984.4
$3,250.2
2033
$28.8
$129.6
$31.7
$135.1
-$2,024.2
$3,252.9
2034
$28.8
$133.4
$31.7
$138.9
-$2,064.2
$3,279.6
2035
$28.8
$130.5
$31.7
$136.0
-$2,104.5
$3,301.6
2036
$28.8
$129.1
$31.7
$134.6
-$2,145.0
$3,301.5
2037
$28.8
$128.1
$31.7
$133.6
-$2,185.2
$3,301.2
2038
$28.8
$390.1
$31.7
$412.8
-$2,225.5
$3,330.6
2039
$28.8
$409.9
$31.7
$424.8
-$2,265.7
$3,323.6
2040
$28.8
$309.8
$31.7
$324.6
-$2,305.8
$3,321.5
2041
$28.8
$351.5
$31.7
$364.3
-$2,346.3
$3,365.1
2042
$28.8
$555.2
$31.7
$572.3
-$2,386.7
$3,341.6
2043
$28.8
$163.0
$31.7
$195.0
-$2,427.2
$3,356.9
2044
$28.8
$342.2
$31.7
$367.6
-$2,467.7
$3,365.1
2045
$28.8
$393.2
$31.7
$517.7
-$2,508.2
$3,465.3
2046
$28.8
$196.8
$31.7
$202.3
-$2,548.7
$3,389.2
2047
| OO
I oo!
!
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
Table 8-5: Time Profile of Benefits and Social Costs of the Final Rule (Millions; $2011)

Existing
Units
New Units
Total
Year
Total Monetized
Total Social
Total Monetized
Total Social
Total Monetized
Total Social

Benefits
Costs
Benefits
Costs
Benefits
Costs
2013
$0.0
$0.0
$0.0
$0.0
$0.0
$0.0
2014
$0.0
$48.1
$0.0
$0.4
$0.0
$48.5
2015
$8.6
$90.2
$0.0
$0.7
$8.7
$90.8
2016
$8.9
$98.0
$0.0
$0.9
$8.9
$98.9
2017
$9.1
$90.5
$0.0
$1.3
$9.1
$91.8
2018
-$1.5
$657.8
$0.0
$1.4
-$1.5
$659.3
2019
-$1.6
$929.3
$0.0
$1.5
-$1.6
$930.8
2020
-$0.2
$1,089.0
$0.0
$1.7
-$0.2
$1,090.6
2021
$1.6
$626.8
$0.0
$1.8
$1.5
$628.6
2022
$8.8
$1,230.4
$0.0
$1.9
$8.8
$1,232.2
2023
$60.9
$124.3
$0.0
$2.0
$60.8
$126.3
2024
$71.4
$131.9
$0.0
$2.1
$71.4
$134.0
2025
$75.6
$133.7
-$0.1
$2.2
$75.5
$135.8
2026
$77.8
$134.4
-$0.1
$2.3
$77.7
$136.7
2027
$79.5
$133.6
-$0.1
$2.4
$79.5
$135.9
2028
$80.6
$135.1
-$0.1
$2.5
$80.5
$137.5
2029
$81.6
$138.9

-$0.1
$2.6
$81.5
$141.5
2030
$82.6
$136.0

-$0.1
$2.7
$82.4
$138.6
2031
$82.6
$134.6

-$0.1
$2.8
$82.4
$137.4
2032
$83.5
$133.6

-$0.2
$2.9
$83.4
$136.4
2033
$31.7
$135.1

-$0.2
$3.0
$31.5
$138.1
2034
$31.7
$138.9

-$0.2
$3.1
$31.5
$142.0
2035
$31.7
$136.0

-$0.2
$3.2
$31.5
$139.1
2036
$31.7
$134.6

-$0.2
$3.3
$31.5
$137.9
2037
$31.7
$133.6

-$0.2
$3.4
$31.5
$136.9
2038
$31.7
$412.8

-$0.3
$3.5
$31.4
$416.2
2039
$31.7
$424.8

-$0.3
$3.6
$31.4
$428.4
2040
$31.7
$324.6

-$0.3
$3.7
$31.4
$328.3
2041
$31.7
$364.3

-$0.3
$3.8
$31.4
$368.1
2042
$31.7
$572.3

-$0.3
$3.9
$31.4
$576.2
2043
$31.7
$195.0

-$0.4
$4.0
$31.3
$199.0
2044
$31.7
$367.6

-$0.4
$4.1
$31.3
$371.7
2045
$31.7
$517.7

-$0.4
$4.2
$31.3
$521.9
2046
$31.7
$202.3

-$0.4
$4.3
$31.3
$206.6
2047
$31.7
$360.7

-$0.5
$4.4
$31.2
$365.1
2048
$31.7
$138.0

-$0.5
$4.5
$31.2
$142.5
2049
$31.7
$141.5

-$0.5
$4.6
$31.2
$146.0
2050
$31.7
$138.0

-$0.5
$4.7
$31.2
$142.7
2051
$31.7
$137.3

-$0.6
$4.8
$31.1
$142.1
2052
$31.7
$134.8

-$0.6
$4.9
$31.1
$139.7
2053
$31.7
$135.1

-$0.6
$5.0
$31.1
$140.1
2054
$31.7
$138.9

-$0.6
$5.1
$31.0
$144.0
2055
$31.7
$136.0

-$0.7
$5.2
$31.0
$141.2
2056
$31.7
$132.6

-$0.7
$5.3
$31.0
$137.9
2057
$31.7
$129.9

-$0.7
$5.4
$30.9
$135.3
2058
$31.7
$156.4

-$0.8
$5.5
$30.9
$161.9
2059
$31.7
$143.9

-$0.8
$5.6
$30.9
$149.5
2060
$28.4
$0.0

$0.3
$0.0
$28.7
$0.0
2061
$25.2
$0.0

$0.2
$0.0
$25.4
$0.0
2062
$6.7
$0.0
$0.1
$0.0
$6.9
$0.0
2063
$3.5
$0.0
$0.1
$0.0
$3.6
$0.0
2064
$1.7
$0.0
$0.0
$0.0
$1.8
$0.0
PV 3%
$880.9
$7,280.7
-$4.7
$68.1
$876.2
$7,348.8
Annualized at 3%
$33.0
$272.4
-$0.2
$2.5
$32.8
$274.9
PV 7%
$424.9
$4,370.5
-$1.5
$29.6
$423.4
$4,400.1
Annualized at 7%
$28.7
$295.3
-$0.1
$2.0
$28.6
$297.3
Source: U.S. EPA analysis for this report
8-6
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
9 Employment Effects
In addition to addressing the costs and benefits of the proposed rule, EPA has analyzed the impacts of the final
rule on employment. This chapter presents the results of this assessment. Executive Order 13563, which
supplements Executive Order 12866, states, "Our regulatory system must protect public health, welfare, safety,
and our environment while promoting economic growth, innovation, competitiveness, and job creation'1
(emphasis added). While estimates of employment impacts typically are not included in a standard benefit-cost
analysis,14" such an analysis is of particular concern in the current economic climate, but at the same time, could
not become the basis upon which to justify the regulation.
This employment discussion addresses requirements of Executive Order 12866: Regulatory Planning and Review
and Executive Order 13563: Improving Regulation and Regulatory Review, discussed in Chapter 12: Other
Administrative Requirements. This chapter presents an overview of the various ways compliance with an
environmental regulation can affect employment. A short qualitative discussion of labor requirements associated
with the installation, operation, and maintenance of control requirements, as well as reporting and recordkeeping
requirements under the final rule is included in Sections 9.2.2 and 9.4. However, due to data and methodology
limitations, EPA did not quantify the final rule's direct and indirect effects on employment, or the effects induced
by changes in workers" incomes. EPA continues to explore the relevant theoretical and empirical literature and to
seek public comments in order to ensure that the way EPA characterizes the employment effects of its regulations
is valid and informative.
This chapter is organized as follows:
> Section 9.1 describes the economic theory for analyzing regulation-induced employment impacts:
¦ Section 9.1.1 provides a conceptual framework for considering the potential influence of
environmental regulation on employment in the U.S. economy and discusses the limited empirical
literature that is available.
¦ Section 9.1.2 discusses potential employment impacts in the Electric Power Industry
¦ Section 9.1.3 discusses potential employment impacts in the selected Primary Manufacturing
Industries, including Aluminum, Chemicals and Allied Products, Food and Kindred Products, Paper
and Allied Products, Petroleum Refining, and Steel Manufacturing.
> Section 9.2 presents an overview of the peer-reviewed literature relevant to evaluating the effect of
environmental regulation on employment in regulated industry sectors and the environmental protection
sector.
> Section 9.3 discusses macroeconomic net employment effects. The EPA is currently in the process of
seeking input from an independent expert panel on economy-wide impacts, including employment
effects.141
> Section 9.4 addresses the particular influence of this final rule on employment.
> Section 9.5 offers several conclusions based on the discussion in the preceding sections.
140 One exception is the extent to which labor costs are part of compliance costs in a benefit-cost analysis.
141 EPA is establishing a new Science Advisory Board (SAB) panel of economic experts with experience in economy-wide modeling to
make recommendations to the agency on the technical merits and challenges, and the potential value added of using economy-wide
models to evaluate costs, benefits, and economic impacts in a regulatory setting. The SAB panel will also identify potential paths
forward for improvements that could address such challenges.
May 2014
9-1
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
9.1 Assessing Employment Effects of Regulations
The effects of environmental regulation on employment are difficult to disentangle from other economic changes
and business decisions that affect employment over time, regions, and industries. Labor markets respond to
regulation in complex ways. That response depends on the elasticities of demand and supply for labor and the
degree of labor market imperfections (e.g. wage stickiness, long-term unemployment, etc.). The unit of
measurement (e.g. number of jobs, types of jobs, hours worked, or earnings) may affect the observability of that
response. Net employment impacts are composed of a mix of potential declines and gains in different areas of the
economy (i.e., the directly regulated sector, upstream and downstream sectors, and the environmental controls
sector) and over time. In light of these difficulties, economic theory provides a constructive framework for
approaching these assessments and for better understanding the inherent complexities in such assessments. This
section briefly describes theory relevant to the impact of regulation on labor demand at the regulated firm, in the
regulated industry, and in the environmental protection sector; and highlights the importance of considering
potential effects of regulation on labor supply, a topic addressed further in a subsequent section.
9.1.1 General Considerations
Neoclassical microeconomic theory describes how profit-maximizing firms adjust their use of productive inputs
in response to changes in their economic conditions.142 In this framework, labor is one of many inputs to
production, along with capital, energy, and materials. In competitive output markets, profit maximizing firms take
prices as given, and choose quantities of inputs and outputs to maximize profit. Factor demand at the firm, then, is
determined by input and output prices.143'144
Berman and Bui (2001) and Morgenstern, Pizer, and Shih (2002) specifically tailored one version of the standard
neoclassical model to analyze how environmental regulations affect labor demand decisions.145 Environmental
regulation is modeled as effectively requiring certain factors of production, such as pollution abatement or
environmental control capital investment, that would not be freely chosen by profit maximizing/cost-minimizing
firms. In Berman and Bui's (2001) theoretical model, the change in a firm's labor demand arising from a change
in regulation is decomposed into two main components: output and substitution effects.146 In the output effect,
regulation affects the profit-maximizing quantity of output by affecting the marginal cost of production. The
output effect describes how, if labor-intensity of production is held constant, a decrease in output generally leads
to a decrease in labor demand. However, the opposite impact is also possible. As noted by Berman and Bui, in the
past, researchers often assumed that regulation increases marginal cost, and thereby reduces output; however, a
regulation could induce a firm to upgrade to less polluting and more efficient equipment or processes that could
lower marginal production costs. In this case, output could theoretically increase. Specifically, regulatory
requirements for environmental protection can cause firms to invest in research and development in order to
innovate production processes and technologies that reduce pollution. The R&D can lead to new innovations that
not only reduce pollution but improve production efficiencies as well, thereby reducing marginal production
costs. Without the environmental regulation, the investment in R&D might not have occurred. On the other hand,
if a regulation causes the marginal cost of production to fall, the expectation is that firms would adopt the less
142 See Layard and Walters (1978), a standard microeconomic theory textbook, for a discussion.
143 See Hamermesh (1993), Chapter 2, for a derivation of the linn's labor demand function from cost-minimization.
144 In this framework, labor demand is a function of quantity of output and prices (of both outputs and inputs).
145 Berman and Bui (2001) and Morgenstern, Pizer, and Shih (2002) use a cost-minimization framework, which is a special case of profit-
maximization with fixed output quantities.
140 Hie authors also discuss a third component, the impact of regulation on factor prices, but conclude that this effect is unlikely to be
important for large competitive factor markets, such as labor and capital. Morgenstern, Pizer and Shih (2002) use a very similar
model, but they break the employment effect into three parts: 1) the demand effect; 2) the cost effect; and 3) the factor-shift effect.
9-2
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
polluting and more efficient equipment or processes on their own without the need for the regulation. One
possible reason that might not occur is that the decrease in a firm's capital cost without the regulation is
insufficient to justify the capital cost of the new equipment or process.
The substitution effect describes how regulation affects the labor intensity of production while holding output
constant. Although increased environmental regulation generally results in higher utilization of production factors
such as environmental control equipment and energy to operate that equipment, the resulting impact on labor
demand is ambiguous. For example, in their attempt to offset increased production costs due to compliance with
the final rule, manufacturing facilities that are subject to the final rule (Manufacturers) may change their
production processes to reduce dependence on cooling water, thereby leading to a change in input mix. The
change in input mix may result in lower domestic demand for some inputs and higher demand for other inputs,
potentially leading to decreased and increased labor demand, respectively, in sectors producing those inputs.
These effects due to input substitution are difficult to estimate, particularly without specific information from the
affected industries.
In summary, because the output and substitution effects may be both positive, both negative or some combination,
standard neoclassical theory alone does not point to a definitive net effect of regulation on labor demand at
regulated firms. Operating within the bounds of standard neoclassical theory, however, rough estimation of net
employment effects is possible with empirical study, specific to the regulated firms, when data and methods of
sufficient detail and quality are available. The available literature illustrates some of the difficulties for empirical
estimation: studies sometimes rely on confidential plant-level employment data from the U.S. Census Bureau,
possibly combined with environmental control expenditure data that are too dated to be reliably informative. In
addition, the most commonly used empirical methods in the literature do not permit the estimation of net effects.
These studies are discussed later in this chapter.
The above discussion describes a conceptual framework for analyzing potential employment effects at a particular
firm, within a regulated industry. It is important to emphasize that employment impacts at a particular firm will
not necessarily represent impacts for the overall industry; therefore, the theoretical approach requires some
adjustment when applied at the industry level.
As stated, the responsiveness of industry labor demand depends on how the output and substitution effects
interact.147 At the industry level, labor demand will be more responsive when: (1) the price elasticity of demand
for the product is high, (2) other factors of production can be easily substituted for labor, (3) the supply of other
factors is highly elastic, or (4) labor costs are a large share of the total costs of production.148 So, for example, if
all firms in the industry are faced with the same compliance costs of regulation and product demand is inelastic,
then industry output may not change much at all, and output of individual firms may only be slightly changed.149
In this case the output effect may be small, while the substitution effect will still depend on the degree of
substitutability or complementarity between factors of production. Continuing the example, if new environmental
control equipment requires labor to install and operate, labor is more of a complement than a substitute. In this
case the substitution effect may be positive, and if the output effect is small or zero, the total effect may then be
positive. As with the potential effects for an individual firm, theory alone is unable to determine the sign or
magnitude of industry-level regulatory effects on labor. Determining these signs and magnitudes requires
additional sector-specific empirical study. To conduct such targeted research would require estimates of product
demand elasticity; production factor substitutability; supply elasticity of production factors; and the share of total
costs contributed by wages, by industry, and perhaps even by facility. Many of these data items are not publicly
147 Marshall's laws of derived demand - see Ehrenberg & Smith, Chapter 4.
148 See Ehrenberg & Smith, p. 108.
149 This discussion draws from Berman and Bui (2001), p. 293.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
available for environmental rules, would require significant time and resources in order to access confidential U.S.
Census data for research, and also would not be necessary for other components of a typical economic analysis.
In addition to changes to labor demand in the regulated industry, net employment impacts encompass changes
within the environmental protection sector and, potentially in other related sectors as well. Environmental
regulations often create increased demand for environmental control equipment and services needed for
compliance. This increased demand may increase revenue and employment in the environmental protection
industry. At the same time, the regulated industry is purchasing the equipment and these costs may impact labor
demand at regulated firms. Therefore, it is important to consider the net effect of compliance actions on
employment across multiple sectors or industries.
If the U.S. economy is at full employment, even a large-scale environmental regulation is unlikely to have a
noticeable impact on aggregate net employment.150 Instead, labor would be reallocated primarily from one
productive use to another (e.g., from producing electricity or steel to producing environmental control
equipment). Theory supports the argument that, in the case of full employment, the net national employment
effects from environmental regulation are likely to be small and transitory (e.g., as workers move from one job to
another).151 On the other hand, if the economy is operating at less than full employment, economic theory does not
clearly indicate the direction or magnitude of the net impact of environmental regulation on employment; it could
cause either a short-run net increase or short-run net decrease (Schmalansee and Stavins, 2011). An important
fundamental research question is how to accommodate unemployment as a structural feature in economic models.
This feature may be important in evaluating the impact of large-scale regulation on employment (Smith, 2012).
Affected sectors may experience transitory effects as workers change jobs. Some workers may need to retrain or
relocate in anticipation of the new requirements or require time to search for new jobs, while shortages in some
sectors or regions could bid up wages to attract workers. It is important to recognize that these adjustment costs
can entail local labor disruptions, and although the net change in the national workforce is expected to be small,
localized reductions in employment can still have negative impacts on individuals and communities just as
localized increases can have positive impacts.
While the current discussion focuses on labor demand effects, environmental regulation may also affect labor
supply. In particular, pollution and other environmental risks may impact labor productivity152 or employees'
ability to work. While there is an accompanying, and parallel, theoretical approach to examining impacts on labor
supply, similar to labor demand, it is even more difficult and complex to study labor supply empirically.
To summarize the discussion in this section, economic theory provides a framework for analyzing the impacts of
environmental regulation on employment. The net employment effect incorporates expected employment changes
(both positive and negative) in the regulated sector, the environmental protection sector, and other relevant
sectors. Using economic theory, labor demand impacts for regulated firms, and also for the regulated industry, can
be decomposed into output and substitution effects. Economic theory suggests that labor supply effects are also
possible. Finally, even if a regulation's impact on employment is positive, that does not necessarily mean the
regulation is good for society overall.
150 Full employment is a conceptual target for the economy where every individual who wants to work and is available to do so at
prevailing wages, is actively employed.
151 Arrow et. al. 1996; see discussion on bottom of p. 8. In practice, distributional impacts on individual workers can be important, as
discussed later in this section.
152 See for example Graff Zivin and Neidell (2012).
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
9.1.2 Employment in the Electric Power Industry
According to the U.S. Bureau of Labor Statistics (BLS), in 2011, the electric power generation, transmission and
distribution sector (NAICS 2211) employed 398,000 workers (BLS, 2012c). In the overall Electric Power
Industry, installation, maintenance, and repair occupations accounted for the largest share of workers
(30 percent).153 These occupation categories include jobs involved in inspection, testing, repairing and
maintaining electrical equipment and/or installation and repair of cables used in electrical power and distribution
systems. Other major occupation categories include office and administrative support (17 percent), production
occupations (15 percent), architecture and engineering (11 percent), business and financial operations (7 percent)
and management (6 percent). The other occupation categories each account for less than 5 percent of employment
in the industry (BLS, 2012d).
As shown in Table 9-1, employment in the Electric Power Industry as a whole has declined steadily since 1990, at
an average annual rate of approximately 2 percent, resulting in an overall decrease of 28 percent. At the same
time, electricity generation increased by 36 percent.
Table 9-1: Total Employment and Labor Intensity in the Electric Power Industry
Year
Number of Employees3
Electricity Generationb
Labor Intensity
Number
% Change
TWh
% Change
Employees
per TWh
% Change
1990
550,200
NA
3,038
NA
181
NA
1991
544.300
-1.1%
3.074
1.2%
177
-2.2%
1992
536.700
-1.4%
3.084
0.3%
174
-1.7%
1993
523.100
-2.5%
3.197
3.7 %
164
-6.0%
1994
504.400
-3.6%
3.248
1.6%
155
-5.1%
1995
486.000
-3.6%
3.353
3.3%
145
-6.7%
1996
464,200
-4.5%
3.444
2.7%
135
-7.0%
1997
449,200
-3.2%
3.492
1.4%
129
-4.6%
1998
443,800
-1.2%
3.620
3.7 %
123
-4.7 %

438.400
-1.2%
3.695
2.1%
119
-3.2%
2000
434.400
-0.9%
3.802
2.9%
1 14
-3.7 %

433.800
-0.1%
3.737
-1.7%
1 16
1.6%
2002
433.800
0.0%
3.858
3.3%
1 12
-3.2%

417.900
-3.7%
3.883
0.6%
108
-4.3%
2004
408,600
-2.2%
3.971
2.2%
103
-4.4%
2005
401,300
-1.8%
4.055
2.1%
99
-3.8%
2006
396,100
-1.3%
4.065
0.2%
97
-1.5%

397.600
0.4%
4.157
2.3%
96
-1.8%
2008
403.700
1.5%
4.1 19
-0.9%
98
2.5%

404.100
0.1%
3.950
-4.1%
102
4.4%
2010
398.000
-1.5%
4.125
4.4%
96
-5.7 %
Total Percent Change
(1990-2010)
-27.7%
35.8%
-46.7%
Total Percent Change
(2000-2010)
-8.4%
8.5%
-15.6%
Average Annual Rate of
Change (1990-2010)
-1.6%
1.5%
-3.1%
a. Total number of employees reported for NAICS 2211: Electric Power Generation, Transmission and Distribution. Includes full- and part-time, temporary
and intermittent employees. Employee counts are not seasonally adjusted.
b. Net electricity generation reported in the 2010 Electric Power Annual report published by the Energy Information Administration.
Sources: U.S. DOE, 2001; U.S. DOE, 2011a, BLS, 2012c
153 BLS does not provide specific occupational employment estimates for the electric power generation industry.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
9.1.3 Employment in the Primary Manufacturing Industries
Employment trends varied over the last two decades in the individual industries comprising the Primary
Manufacturing Industries. Most industries experienced declines in employment, as did the Primary Manufacturing
Industries group overall.
Aluminum
In 2011, the Aluminum Industry (NAICS 331311, 331312, 331314, 331315) employed approximately 30,000
workers (U.S. DOC, 2011 ASM). As shown in Table 9-2, employment in this industry as a whole declined
steadily since the early 1990s, at an average annual rate of 3 percent, resulting in an overall decrease in
employment of 50 percent. During this time, value added also decreased (39 percent), although not as rapidly as
employment. The more rapid reduction in employment compared to that in value added results in an overall
decline in labor intensity (19 percent). As discussed in more detail in the Aluminum Industry profile (Appendix
A), during the last two decades, Aluminum industry production fluctuated in response to changes in domestic and
foreign demand. During the recent recession, production contracted substantially, with value added decreasing by
54 percent during 2007 through 2009. Employment fell by a smaller amount, 20 percent. However, as the
economic recovery began in 2010, value added in the Aluminum Industry increased by 40 percent, but
employment increased by less than 1 percent. For a detailed discussion of the Aluminum Industry, see Appendix
A.
9-6
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
Table 9-2: Total Employment and Labor Intensity in the Aluminum Industry

iN umber of
Employees"
Value Added1'
Labor Intensity

Employees per
Million $ of

Value Added;

Year
Number
% Change
Millions; $2011
% Change
$2011
% Change
1990
57,525
n/a
$9,453
n/a
6.1
n/a
1991
57,627
0.2%
$8,232
-12.9%
7.0
15.0%
1992
57,734
0.2%
$9,238
12.2%
6.2
-10.7%
1993
56,330
-2.4%

$7,724
-16.4%
7.3
16.7%
1994
53,821
-4.5%

$8,787
13.8%
6.1
-16.0%
1995
54,100
0.5%

$10,209
16.2%
5.3
-13.5%
1996
54,257
0.3%

$9,103
-10.8%
6.0
12.5%
1997
50,121
-7.6%

$9,518
4.6%
5.3
-11.7%
1998
49,655
-0.9%

$10,581
11.2%
4.7
-10.9%
1999
48,743
-1.8%

$11,004
4.0%
4.4
-5.6%
2000
46,929
-3.7%

$8,128
-26.1%
5.8
30.3%
2001
43,358
-7.6%

$7,545
-7.2%
5.7
-0.5%
2002
40,085
-7.5%

$7,948
5.3%
5.0
-12.2%
2003
37,301
-6.9%

$7,015
-11.7%
5.3
5.4%
2004
34,549
-7.4%

$7,848
11.9%
4.4
-17.2%
2005
34,835
0.8%

$8,190
4.4%
4.3
-3.4%
2006
34.316
-1.5%

$9,859
20.4%
3.5
-18.2%
2007
35,750
4.2%

$9,003
-8.7%
4.0
14.1%
2008
34,621
-3.2%

$8,086
-10.2%
4.3
7.8%
2009
28,532
-17.6%
$4,138
-48.8%
6.9
61.0%
2010
28,704
0.6%
$5,787
39.9%
5.0
-28.1%
Total Percent Change

-50.1%

-38.8%

-18.5%
(1990-2010)

Total Percent Change

-38.8%

-28.8%

-14.1%
(2000-2010)

Average Annual Rate of Change

-3.4%

-2.4%

-1.0%
(1990-2010)

a. Total number of employees reported for primary (NAICS 331311 & 331312) and secondary (NAICS 331314 & 331315) stages of aluminum production.
Includes full- and part-time, temporary and intermittent employees. Employee counts are not seasonally adjusted.

b. Value Added reported in the Economic Census (EC) and Annual Survey of Manufacturers (ASM) published by the U.S. Census Bureau.
Sources: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1992, 1997, 2002, and 2007EC.
Chemicals and Allied Products
In 2011, the Chemicals and Allied Products Industry (NAICS 325110, 325120, 325131, 325181, 325188, 325199,
325211, 325221, 325222, 325311, 325312, 325411, 325412) employed approximately 392,000 workers (U.S.
DOC, 2011 ASM). As shown in Table 9-3, employment in this industry declined since 1990 at an average annual
rate of approximately 1 percent, resulting in an overall decline of 24 percent. This decrease in employment can be
attributed to cost-reduction measures such as restructuring and downsizing, which have been induced by
competitive pressures (see Appendix B). At the same time, value added increased by 53 percent, leading to a large
overall decline in labor intensity (51 percent). Though the industry is hiring additional science personnel as the
complexity of work rises, the demand for highly skilled workers is not expected to reverse the loss in chemicals
industry employment (C&EN, 2010). For a detailed discussion of the Chemicals and Allied Products Industry, see
Appendix B.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
Table 9-3: Total Employment and Labor Intensity in the Chemicals and Allied Products Industry

i\ umber of Employees'1
Value Added1'
Labor Intensity

Employees per
Million $ of

Value Added;

Year
Number
% Change
Millions; $2011
% Change
$2011
% Change
1990
488,860
n/a
$149,676
n/a
3.3
n/a
1991
478,491
-2.1%
$144,281
-3.6%
3.3
1.5%
1992
470,126
-1.7%
$147,898
2.5%
3.2
-4.2%
1993
462,125
-1.7%
$146,186
-1.2%
3.2
-0.6%
1994
454,225
-1.7%
$155,738
6.5%
2.9
-7.7%
1995
462,111
1.7%
$164,397
5.6%
2.8
-3.6%
1996
452,142
-2.2%
$156,068
-5.1%
2.9
3.1%
1997
437,598
-3.2%
$175,378
12.4%
2.5
-13.9%
1998
444,442
1.6%
$182,834
4.3%
2.4
-2.6%
1999
452,547
1.8%
$176,701
-3.4%
2.6
5.4%
2000
455,163
0.6%
$173,456
-1.8%
2.6
2.5%
2001
448,030
-1.6%
$169,085
-2.5%
2.6
1.0%
2002
459,451
2.5%
$188,198
11.3%
2.4
-7.9%
2003
439.382
-4.4%
$203,568
8.2%
2.2
-11.6%
2004
417,519
-5.0%
$223,228
9.7%
1.9
-13.3%
2005
412,389
-1.2%
$239,864
7.5%
1.7
-8.1%
2006
398,181
-3.4%
$244,969
2.1%
1.6
-5.5%
2007
414,638
4.1%
$242,080
-1.2%
1.7
5.4%
2008
406,068
-2.1%
$231,946
-4.2%
1.8
2.2%
2009
378.691
-6.7%
$210,502
-9.2%
1.8
2.8%
2010
370,102
-2.3%
$229,291
8.9%
1.6
-10.3%
Total Percent Change

-24.3%

53.2%

-50.6%
(1990-2010)

Total Percent Change

-18.7%

32.2%

-38.5%
(2000-2010)

Average Annual Rate of Change

-1.4%

2.2%

-3.5%
(1990-2010)

a. Total number of employees reported for Basic Chemicals (NAICS 325110, 325120, 325131, 325181, 325188, 325199), Resins and Synthetics (NAICS
325211, 325221, 325222), Pesticides and Fertilizers (NAICS 325311, 325312), and Pharmaceuticals (NAICS 325411, 325412). Includes full- and part-time,
temporary and intermittent employees. Employee counts are not seasonally adjusted.
b. Value Added reported in the Economic Census (EC) and Annual Survey of Manufacturers (ASM) published by the U.S. Census Bureau.
Sources: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1992, 1997, 2002, and 2007EC.
Food and Kindred Products
The Food and Kindred Products Industry (NAICS 311,3121) employed approximately 1,485,000 workers in 2011
(U.S. DOC, 2011 ASM). As shown in Table 9-4, between 1990 and 2010, employment in the Food and Kindred
Products Industry increased at an average annual rate of 0.3 percent, resulting in an overall increase of 6 percent.
Overall, employment in this industry increased nearly every year during the 1990s but declined during 2000s. A
very modest increase in employment during the last two decades coupled with a significant industry growth (51
percent increase in value added) show that the Food and Kindred Products Industry has become significantly less
labor intensive (30 percent decline in labor intensity. For a detailed discussion of the Food and Kindred Products
Industry, see Appendix C.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
Table 9-4: Total Employment and Labor Intensity in the Food and Kindred Products Industry

i\ umber of Employees'1
Value Added1'
Labor Intensity

Employees per
Million $ of

Value Added;

Year
Number
% Change
Millions; $2011
% Change
$2011
% Change
1990
1,351,500
n/a
$210,689
n/a
6.4
n/a
1991
1,341,200
-0.8%
$208,726
-0.9%
6.4
0.2%
1992
1,382,500
3.1%
$222,453
6.6%
6.2
-3.3%
1993
1,395,800
1.0%
$228,810
2.9%
6.1
-1.8%
1994
1,391,400
-0.3%
$232,043
1.4%
6.0
-1.7%
1995
1,400,300
0.6%
$239,887
3.4%
5.8
-2.7%
1996
1,386,800
-1.0%
$232,425
-3.1%
6.0
2.2%
1997
1,565,470
12.9%
$257,439
10.8%
6.1
1.9%
1998
1,565,407
0.0%
$267,945
4.1%
5.8
-3.9%
1999
1,573,693
0.5%
$268,570
0.2%
5.9
0.3%
2000
1,599,585
1.6%
$272,466
1.5%
5.9
0.2%
2001
1,595,160
-0.3%
$278,815
2.3%
5.7
-2.5%
2002
1,582,065
-0.8%
$286,526
2.8%
5.5
-3.5%
2003
1,538,062
-2.8%
$300,329
4.8%
5.1
-7.2%
2004
1,514,620
-1.5%
$308,113
2.6%
4.9
-4.0%
2005
1,508,006
-0.4%
$314,092
1.9%
4.8
-2.3%
2006
1,487,276
-1.4%
$301,188
-4.1%
4.9
2.9%
2007
1,541,750
3.7%
$303,741
0.8%
5.1
2.8%
2008
1,516,819
-1.6%
$301,812
-0.6%
5.0
-1.0%
2009
1,471,227
-3.0%
$311,893
3.3%
4.7
-6.1%
2010
1,433,907
-2.5%
$317,317
1.7%
4.5
-4.2%
Total Percent Change

6.1%

50.6%

-29.6%
(1990-2010)

Total Percent Change

-10.4%

16.5%

-23.0%
(2000-2010)

Average Annual Rate of

0.3%

2.1%

-1.7%
Change (1990-2010)

a. Total number of employees reported for Food Manufacturing (311) and Beverage Manufacturing (3121). Includes full- and part-time, temporary and
intermittent employees. Employee counts are not seasonally adjusted.
b. Value Added reported in the Economic Census (EC) and Annual Survey of Manufacturers (ASM) published by the U.S. Census Bureau.
Sources: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1992, 1997, 2002, and 2007EC.
Paper and Allied Products
The Paper and Allied Products Industry (NAICS 3221) employed approximately 108,000 workers in 2011 (U.S.
DOC, 2011 ASM). As shown in Table 9-5, employment in this industry has declined steadily, by 51 percent
overall, since 1990. At the same time, value added fluctuated cyclically with the economy, but declined overall by
18 percent; most of this decline took place during the last decade. As discussed in more detail in the Paper and
Allied Products Industry profile, during the last decade, the industry faced increased foreign competition,
overcapacity, and difficulty adapting to changing business conditions. Specifically, demand for paper products
has weakened as electronic substitution, such as online bill paying, email, internet publications, and electronic
readers, has gained popularity.
As shown in Table 9-5, the industry's labor intensity declined overall by 39 percent since 1990. For a detailed
discussion of the Paper and Allied Products Industry, see Appendix D.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
Table 9-5: Total Employment and Labor Intensity in the Paper and Allied Products Industry

i\ umber of Employees'1
Value Added1'
Labor Intensity

Employees per
Million $ of

Value Added;

Year
Number
% Change
Millions; $2011
% Change
$2011
% Change
1990
222,267
n/a
$50,899
n/a
4.4
n/a
1991
220,785
-0.7%
$45,433
-10.7%
4.9
11.3%
1992
222,077
0.6%
$44,591
-1.9%
5.0
2.5%
1993
217,353
-2.1%
$41,100
-7.8%
5.3
6.2%
1994
213,815
-1.6%
$43,511
5.9%
4.9
-7.1%
1995
211,179
-1.2%
$61,157
40.6%
3.5
-29.7%
1996
207,835
-1.6%
$48,708
-20.4%
4.3
23.6%
1997
201,540
-3.0%
$47,191
-3.1%
4.3
0.1%
1998
195,053
-3.2%
$48,116
2.0%
4.1
-5.1%
1999
187,519
-3.9%
$48,804
1.4%
3.8
-5.2%
2000
179,280
-4.4%
$52,075
6.7%
3.4
-10.4%
2001
170,661
-4.8%
$46,579
-10.6%
3.7
6.4%
2002
158,857
-6.9%
$47,401
1.8%
3.4
-8.5%
2003
148,092
-6.8%
$43,274
-8.7%
3.4
2.1%
2004
136,646
-7.7%
$43,712
1.0%
3.1
-8.7%
2005
135,590
-0.8%
$43,778
0.2%
3.1
-0.9%
2006
127,931
-5.6%
$45,605
4.2%
2.8
-9.4%
2007
125,483
-1.9%
$43,596
-4.4%
2.9
2.6%
2008
118,512
-5.6%
$42,558
-2.4%
2.8
-3.3%
2009
113,473
-4.3%
$40,911
-3.9%
2.8
-0.4%
2010
110,055
-3.0%
$41,574
1.6%
2.6
-4.6%
Total Percent Change

-50.5%

-18.3%

-39.4%
(1990-2010)

Total Percent Change

-38.6%

-20.2%

-23.1%
(2000-2010)

Average Annual Rate of

-3.5%

-1.0%

-2.5%
Change (1990-2010)

a. Total number of employees reported for Paper Mills (NAICS 322110), Pulp Mills (NAICS 32212), and Paperboard Mills (NAICS 322130). Includes foll-
and part-time, temporary and intermittent employees. Employee counts are not seasonally adjusted.
b. Value Added reported in the Economic Census (EC) and Annual Survey of Manufacturers (ASM) published by the U.S. Census Bureau.
Sources: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1992, 1997, 2002, and 2007EC.
Petroleum Refining
The Petroleum Refining Industry (NAICS 324110) employed approximately 62,000 workers in 2011 (U.S. DOC,
2011 ASM). As shown in Table 9-6, overall, during the last two decades, employment in the industry declined by
12 percent, despite a modest increase of 2 percent during 2000s. Further, as discussed in the Petroleum Refining
Industry profile (Appendix E), during the last two decades, employment in the Petroleum Refining Industry
fluctuated due to volatility of crude oil prices and refinery product prices. However, despite these fluctuations, the
Petroleum Refining Industry grew substantially since 1990, with value added increasing by 133 percent. For a
detailed discussion of the Petroleum Refining Industry, see Appendix E.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
Table 9-6: Total Employment and Labor Intensity in the Petroleum Refining Industry

i\ umber of Employees'1
Value Added1'
Labor Intensity

Employees per
Million $ of

Value Added;

Year
Number
% Change
Millions; $2011
% Change
$2011
% Change
1990
71,900
n/a
$35,801
n/a
2.0
n/a
1991
73,900
2.8%
$29,991
-16.2%
2.5
22.7%
1992
74,800
1.2%
$28,267
-5.7%
2.6
7.4%
1993
73,100
-2.3%
$27,091
-4.2%
2.7
2.0%
1994
72,000
-1.5%
$33,758
24.6%
2.1
-21.0%
1995
70,400
-2.2%
$33,308
-1.3%
2.1
-0.9%
1996
67,200
-4.5%
$35,450
6.4%
1.9
-10.3%
1997
65,448
-2.6%
$41,362
16.7%
1.6
-16.5%
1998
64,920
-0.8%
$31,820
-23.1%
2.0
28.9%
1999
63,619
-2.0%
$41,140
29.3%
1.5
-24.2%
2000
62,118
-2.4%
$46,806
13.8%
1.3
-14.2%
2001
63,258
1.8%
$50,383
7.6%
1.3
-5.4%
2002
62,540
-1.1%
$34,372
-31.8%
1.8
44.9%
2003
60,010
-4.0%
$47,010
36.8%
1.3
-29.8%
2004
60,004
0.0%
$65,627
39.6%
0.9
-28.4%
2005
62,531
4.2%
$118,700
80.9%
0.5
-42.4%
2006
60,855
-2.7%
$122,097
2.9%
0.5
-5.4%
2007
64,839
6.5%
$118,881
-2.6%
0.5
9.4%
2008
66,851
3.1%
$80,536
-32.3%
0.8
52.2%
2009
65,462
-2.1%
$67,918
-15.7%
1.0
16.1%
2010
63,263
-3.4%
$83,267
22.6%
0.8
-21.2%
Total Percent Change

-12.0%

132.6%

-62.2%
(1990-2010)

Total Percent Change

1.8%

77.9%

-42.8%
(2000-2010)

Average Annual Rate of

-0.6%

4.3%

-4.7%
Change (1990-2010)

a. Total number of employees reported for Petroleum Refineries (NAICS 324110). Includes full and part time, temporary and intermittent employees.
Employee counts are not seasonally adjusted.
b. Value Added reported in the Economic Census (EC) and Annual Survey of Manufacturers (ASM) published by the U.S. Census Bureau.
Sources: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1992, 1997, 2002, and 2007EC.
Steel
The Steel Industry (NAICS 3311, 3312) employed approximately 142,000 workers in 2011 (U.S. DOC, 2011
ASM). As shown in Table 9-7, employment in the Steel Industry declined steadily since 1990, declining overall
by 47 percent. At the same time, value added grew, however modestly, by 5 percent. As a result, the Steel
Industry has become significantly less labor intensive - a reduction of 50 percent since 1990. As discussed in the
Steel Industry profile (Appendix F), the industry's declining labor intensity results from industry consolidation
and increased production from mini-mills, which require less labor than the integrated steel manufacturing
process. During the recent recession, Steel Industry production contracted significantly, with value added
declining by 65 percent in 2009. However, employment contracted by a smaller amount, 13 percent. As the
economy began to recover in 2010, Steel Industry production increased by 109 percent while employment
remained flat, declining by less than 1 percent. For a detailed discussion of the Steel Industry, see Appendix F.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
Table 9-7: Total Employment and Labor Intensity in the Steel Industry

N umber of Employees'1
Value Added1'
Labor Intensity

Employees per
Million $ of

Value Added;

Year
Number
% Change
Millions; $2011
% Change
$2011
% Change
1990
258,369
n/a
$37,663
n/a
6.9
n/a
1991
245,462
-5.0%
$30,985
-17.7%
7.9
15.5%
1992
238,829
-2.7%
$33,147
7.0%
7.2
-9.0%
1993
229,248
-4.0%
$35,713
7.7%
6.4
-10.9%
1994
226,001
-1.4%
$39,170
9.7%
5.8
-10.1%
1995
224,716
-0.6%
$40,812
4.2%
5.5
-4.6%
1996
220,625
-1.8%
$40,254
-1.4%
5.5
-0.5%
1997
214,075
-3.0%
$43,124
7.1%
5.0
-9.4%
1998
212,875
-0.6%
$41,046
-4.8%
5.2
4.5%
1999
203,664
-4.3%
$36,912
-10.1%
5.5
6.4%
2000
206,332
1.3%
$34,892
-5.5%
5.9
7.2%
2001
188,488
-8.6%
$27,375
-21.5%
6.9
16.4%
2002
173,705
-7.8%
$29,825
9.0%
5.8
-15.4%
2003
160.914
-7.4%
$27,444
-8.0%
5.9
0.7%
2004
154,589
-3.9%
$45,925
67.3%
3.4
-42.6%
2005
145,866
-5.6%
$45,476
-1.0%
3.2
-4.7%
2006
142,721
-2.2%
$45,701
0.5%
3.1
-2.6%
2007
157,027
10.0%
$47,504
3.9%
3.3
5.8%
2008
156,856
-0.1%
$53,783
13.2%
2.9
-11.8%
2009
136,897
-12.7%
$18,950
-64.8%
7.2
147.7%
2010
136,259
-0.5%
$39,522
108.6%
3.4
-52.3%
Total Percent Change

-47.3%

4.9%

-49.7%
(1990-2010)

Total Percent Change

-34.0%

13.3%

-41.7%
(2000-2010)

Average Annual Rate of Change

-3.1%

0.2%

-3.4%
(1990-2010)

a. Total number of employees reported for Iron and Steel Mills and Ferroalloy Manufacturing (NAICS 3311) and Steel Product Manufacturing from
Purchased Steel (NAICS 3312). Includes full- and part-time, temporary and intermittent employees. Employee counts are not seasonally adjusted,
b. Value Added reported in the Economic Census (EC) and Annual Survey of Manufacturers (ASM) published by the U.S. Census Bureau.
Sources: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1992, 1997, 2002, and 2007EC.
9.2 Current State of Knowledge Based on the Peer-Reviewed Literature
The labor economics literature contains an extensive body of peer-reviewed empirical work analyzing various
aspects of labor demand, relying on the theoretical framework discussed in Section 9.1.1.154 This work focuses
primarily on the effects of employment policies, e.g. labor taxes, minimum wage, etc.155 In contrast, the peer-
reviewed empirical literature specifically estimating employment effects of environmental regulations is very
limited. This section presents an overview of the latter. As discussed in Section 9.1.1, determining the direction of
employment effects in regulated industries is challenging because of the complexity of the output and substitution
effects. Complying with a new or more stringent regulation may require additional inputs, including labor, and
may alter the relative proportions of labor and capital used by regulated firms (and by firms in other relevant
industries) in their production processes. Impacts on the environmental protection sector as well as to labor supply
have also been explored by the peer-reviewed literature.
154 Again, see Hamermesh (1993) for a detailed treatment.
155 See Ehrenberg & Smith (2000), Chapter 4: "Employment Effects: Empirical Estimates" for a concise overview.
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Chapter 9: Employment Effects
9.2.1 Regulated Industry Sectors
Determining the direction of net employment effects of regulation on industry is challenging. Two papers that
present a formal theoretical model of the underlying profit-maximizing/cost-minimizing problem of the firm are
Berman and Bui (2001) and Morgenstern, Pizer, and Shih (2002).
Berman and Bui (2001) developed an innovative approach to estimate the effect on employment of environmental
regulations in California. Their model empirically examines how an increase in local air quality regulation affects
manufacturing employment in the South Coast Air Quality Management District (SCAQMD), which incorporates
Los Angeles and its suburbs. During the time frame of their study, 1979 to 1992, the SCAQMD enacted some of
the country's most stringent air quality regulations. Using SCAQMD's local air quality regulations, Berman and
Bui identify the effect of environmental regulations on net employment in the regulated industries.156 In
particular, they compare changes in employment in affected plants to those in other plants in the same 4-digit SIC
industries but in regions not subject to the local regulations.157 The authors find that "while regulations do
impose large costs, they have a limited effect on employment" (Berman and Bui, 2001, p. 269). Their conclusion
is that local air quality regulation "probably increased labor demand slightly" but that "the employment effects of
both compliance and increased stringency are fairly precisely estimated zeros, even when exit and dissuaded entry
effects are included" (Berman and Bui, 2001).158 In their view, the limited effects likely arose because 1) the
regulations disproportionately affected capital-intensive plants with relatively little employment, 2) the plants
sold to local markets where competitors were subject to the same regulations (so that sales were relatively
unaffected), and 3) abatement inputs served as complements to employment.
Morgenstern, Pizer, and Shih (2002) developed a similar structural approach to Berman and Bui's, but their
empirical application uses pollution abatement expenditures from 1979 to 1991 at the plant-level, including air,
water, and solid waste, to estimate net employment effects in four highly regulated sectors (pulp and paper,
plastics, steel, and petroleum refining). Thus, in contrast to Berman and Bui (2001), this study identifies
employment effects by examining differences in abatement expenditures rather than geographical differences in
stringency. They conclude that increased abatement expenditures generally have not caused a significant change
in net employment in those sectors.
Other research suggests that more highly regulated counties may generate fewer jobs than less regulated ones
(Greenstone, 2002; Walker, 2011). However, because these latter studies compare employment in more regulated
to less regulated counties they can only estimate relative impacts on employment and therefore they cannot
estimate changes in net employment. List et al. (2003) find some evidence that this type of geographic relocation
may be occurring. Overall, the peer-reviewed literature does not provide evidence that an environmental
regulation has a large impact on net employment (either negative or positive) in the long run across the whole
economy.
9.2.2 Environmental Protection Sector
The long-term effects of a regulation on employment in the environmental protection sector, which provides
goods and services to help the regulated sector to comply with regulatory requirements, are difficult to assess.
Nevertheless, EPA expects labor demand in the industry supplying environmental control equipment to increase
in the years following promulgation of a regulation during which regulated facilities install compliance
150 Note that similarly to Morgenstern, Pizer, and Shih (2002), this study does not estimate the number of jobs created in the
environmental protection sector.
157 Berman and Bui (2001) include more than 40 4-digit SIC industries in their sample.
158 Including the employment effect of existing facilities and facilities dissuaded from opening will increase the estimated impact of
regulation on employment. This employment effect is not included in Morgenstern, Pizer, and Shih (2002).
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 9: Employment Effects
technology.159 A report by the U.S. International Trade Commission (2013) shows that domestic environmental
services revenues have grown by 41 percent between 2000 and 2010. According to U.S. Department of
Commerce (2010) data, by 2008, 119,000 environmental technology (ET) firms generated approximately $300
billion in revenues domestically, producing $43.8 billion in exports, and supporting nearly 1.7 million jobs in the
United States. Air environmental control technology accounted for 18 percent of the domestic ET market and 16
percent of exports. Small and medium-size companies represent 99 percent of private ET firms, producing 20
percent of total revenue (U.S. DOC, 2010).
EPA expects the final rule to affect employment in the environmental protection sector as the result of labor
requirements associated with the installation, operation, and maintenance of compliance technology. The short-
term effects will occur during the approximate technology-installation years of 2018 through 2022 as regulated
facilities begin to comply with the final rule, with longer-term effects associated with on-going operation and
maintenance of installed equipment to follow possibly on a more steady-state basis. For the final rule, EPA
expects the industries producing and installing compliance technology - the environmental protection sector, as
referred to in this chapter - will include construction, truck transportation, machinery manufacturing, plastics
manufacturing, wood preservation, electrical equipment manufacturing, and cement and concrete product
manufacturing sectors, among many others. The Agency expects that labor needs to conduct reporting and
recordkeeping activities under the final rule will largely be met by the regulated sectors themselves. See the
Technical Development Document {TDD) for details on the types of compliance equipment and services required
under the final rule (U.S. EPA, 2014d).
9.3 Macroeconomic Net Employment Impacts
The preceding sections outlined the challenges associated with estimating net employment effects within the
regulated sector, in the environmental protection sector, and labor supply impacts. These challenges make it very
difficult to estimate accurate net employment effects for the whole economy that would appropriately capture the
way in which costs, compliance spending, and environmental benefits propagate through the macro-economy.
Quantitative estimates are further complicated by the fact that macroeconomic models often have very little detail
at the sector level and usually assume that the economy is at full employment. EPA is in the process of
establishing a new Science Advisory Board panel of economic experts with experience in economy-wide
modeling. EPA seeks recommendations from the panel on the technical merits and challenges, and the potential
value added, of using economy-wide models to evaluate costs, benefits, and economic impacts, including
employment, in a regulatory setting. EPA will request that the SAB panel identify potential paths forward for
improvements that could help address such challenges.
9.4 Overall Analysis Conclusion
In conclusion, deriving estimates of how environmental regulations will impact net employment is a difficult task,
requiring consideration of labor demand in both the regulated and environmental protection sectors. Economic
theory predicts that the total effect of an environmental regulation on labor demand in regulated sectors is not
necessarily positive or negative. Peer-reviewed econometric studies that use a structural approach, applicable to
overall net effects in the regulated sectors, converge on the finding that such effects, whether positive or negative,
have been small and have not affected employment in the national economy in a significant way. Effects on labor
demand in the environmental protection sector seem likely to be positive. Finally, new evidence suggests that
environmental regulation may improve labor supply and productivity.160 Overall, employment effects are likely to
vary in their magnitude over time and across sectors.
159 See Bezdek, Wendling, and Diperna (2008), for example, and U.S. Department of Commerce (2010).
160 See, for example U.S. EPA (2011 d) and Graff Zivin and Neidell (2013).
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Chapter 9: Employment Effects
Environmental regulations typically are phased in to allow firms time to invest in the necessary technology and
process changes to meet the new standards. Noticeable effects of a regulation on employment in the regulated
sector typically will not occur until after a regulation takes effect. When a regulation is promulgated, industry's
first response is to order environmental control equipment. As the compliance date of the regulation approaches,
the installation of needed environmental control equipment can produce a short-term increase in labor demand for
specialized workers within the environmental protection sector, as well as the directly regulated industry sector
(Schmalansee and Stavins, 2011). These short-term employment effects essentially occur once as regulated
facilities move to comply with the regulation to a substantial degree and turn to suppliers in the industries that
produce and install compliance equipment, i.e., the environmental protection sector. In the short run, spanning the
initial technology installation window of 2018 through 2022, the final rule is likely to affect the regulated sectors,
construction sector, transportation sector, and other sectors comprising the environmental protection sector, based
on the type of compliance equipment and services identified in the TDD (U.S. EPA, 2014d).
In aggregate, the sectors supplying environmental protection equipment and services may experience a temporary
increase in jobs created as more environmental control systems are designed, manufactured, and installed due to
the final rule. In addition, because of regional variation in the presence of regulated facilities and supporting
industries, and in consumption patterns, short- and long-run employment effects likely will vary across the United
States. It is possible that positive net employment effects in the near term will be due to the potential hiring of idle
labor resources by the regulated sectors to plan for and meet new environmental control requirements rather than
to workers diverted from other productive employment. However, it is also possible that in the long run, as the
economy returns to full employment, any changes in employment in the regulated sectors due to the final rule will
be offset mostly by employment changes in other sectors. This realization adds further to the uncertainty in
estimating employment effects for a substantial number of years into the future.
Even if regulated facilities are able to reduce the impact of regulatory requirements by changing their production
processes in the post-rule environment, production costs may still be higher compared to those before the rule. As
a result, regulated facilities may seek to increase their product prices in response to the higher production costs.
For example, attempts by Electric Generators to recover increases in electricity generation costs, however small,
are likely to result in higher electricity rates. The impact of this increase will vary by region, customer group (e.g.,
industrial, commercial, transportation, and residential), and by industry, depending on the electricity-use
intensity.161 Further, the extent to which Electric Generators are able to pass their costs to consumers through
higher electricity rates, will vary by region. Specifically, Electric Generators operating in regions where electricity
prices remain regulated under the traditional cost-of-service rate regulation framework may be able to recover
compliance cost-based increases by increasing consumer rates.162 However, cost recovery is less certain for
Electric Generators operating in States where electric power generation has been deregulated, and will depend on
the competitive circumstances of specifically affected facilities. Overall, the long-run changes in employment will
likely depend on how the Electric Power Industry, Primary Manufacturing Industries, and Other Industries adjust
in response to the new regulatory requirements, the upstream and downstream effects of those adjustments on the
rest of the economy, as well as the overall state of the economy and labor markets. The long-run employment
effects in the directly affected sectors will depend on a number of economic factors, including changes in labor
requirements to operate the infrastructure in general and compliance technology in particular at regulated
facilities, the potential to change production processes to become less dependent on cooling water, availability of
alternative technologies to meet compliance requirements, and changes in demand for the outputs of the directly
161 See Chapter 6: Electricity Market Analysis for assessment of the impacts of increased production costs on wholesale electricity prices
and Chapter 4: Economic Impact Analysis - Electric Generators for analyses of the impacts on retail rates by customer group.
162 However, even for Electric Generators operating under traditional rate regulation, the recovery of cost increases through increased
rates is not certain, and will depend on additional factors such as the facility ownership structure and operating model, approval of
public utility commissions, and the importance and role of market mechanisms in dispatching production of electricity across
generating units. See Chapter 2A for additional discussion.
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Economic Analysis for Final 316(b) Existing Facilities Rule Chapter 9: Employment Effects
affected sectors. Because of these and many other interrelated factors, including significant data and methodology
limitations, fully assessing the employment impacts of the final rule is a difficult task.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 10: Regulatory Flexibility Act (RFA) Analysis
10 Impacts on Small Entities - Regulatory Flexibility Act (RFA) Analysis
The Regulatory Flexibility Act (RFA) of 1980, as amended by the Small Business Regulatory Enforcement
Fairness Act (SBREFA) of 1996, requires federal agencies to consider the impact of their regulatory proposals on
small entities,163 to analyze alternatives that minimize those impacts, and to make their analyses available for
review and comment by the public. The Act is concerned with three types of small entities: small businesses,
small nonprofits, and small government jurisdictions.
The RFA describes the analyses and procedures federal agencies must complete for a proposed rule unless the
agency certifies that the rule, if promulgated, would not have a significant economic impact on a substantial
number of small entities. A statement of factual basis - e.g., addressing the number of small entities affected by
the regulatory action, the expected cost impact on these entities, and evaluation of the economic impacts - must
support this certification.
In accordance with RFA requirements, EPA assessed the impact of the final rule and found that the regulation
would not have a "significant economic impact on a substantial number of small entities" (SISNOSE) and
certified to that finding (no-SISNOSE) at the time of the regulatory proposal. To support the analysis and
promulgation of the final rule, EPA again assessed whether the final rule and other options EPA considered in
development of this rule, would again qualify for certification for a no-SISNOSE finding. This assessment
involved the following steps:
> Identifying the domestic parent entities of facilities subject to the final rule (regulated entities and
regulated facilities or Electric Generators and Manufacturers).
> Determining which of those domestic parent entities are small entities, based on Small Business
Administration (SBA) entity size criteria.
> Assessing the potential impact of the regulatory options on those small entities by comparing the
estimated entity-level, annualized compliance cost to entity-level revenue. Small entities with compliance
costs estimated to be at least 1 percent or 3 percent of entity-level revenue would potentially incur
significant impacts.
> Assessing whether those small entities incurring potentially significant impacts represent a substantial
number of small entities based on (1) the estimated absolute numbers of small entities incurring
potentially significant impacts according to the two cost impact criteria, and (2) the percentage of small-
entities in the relevant entity categories that EPA estimated would incur these impacts.
For the final rule, EPA conducted this analysis for the existing unit provision only; therefore, the term final rule
refers to the existing unit provision only. EPA undertook the assessment of small entity impacts separately for
Manufacturers and Electric Generators, using somewhat different population-level estimation methods. The
separate analyses reflect the different levels of information available for Manufacturers and Electric Generators
from the 316(b) survey. In particular, the 316(b) survey provides facility-level information for essentially the
entire universe of Electric Generators. In contrast, the sample of Manufacturers for which the 316(b) survey
provides information is much smaller than the regulated universe of manufacturing facilities. As a result, a more
precise analysis of potential entity-level impacts is possible for Electric Generators than for Manufacturers, and
the different analytic methods reflect this difference.
103 Section 603(c) of the RFA provides examples of such alternatives as: (1) the establishment of differing compliance or reporting
requirements or timetables that take into account the resources available to small entities; (2) the clarification, consolidation, or
simplification of compliance and reporting requirements under the rule for such small entities; (3) the use of performance rather than
design standards; and (4) an exemption from coverage of the rule, or any part thereof, for such small entities.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 10: Regulatory Flexibility Act (RFA) Analysis
This chapter first describes the analytic approach and findings for Electric Generators (Section 10.1) and
Manufacturers (Section 10.2), and then reviews uncertainties and limitations of these analyses (Section 10.3). The
RFA analysis results presented in this chapter assume that all facilities with cooling water system impoundments
will qualify as baseline CCRS, and will not need to install additional technology under the final rule and other
options considered. To the extent that some of these facilities do not qualify as baseline CCRS and would need to
install additional compliance technology, the impacts reported in this chapter may be underestimates. See
Memorandum to the Record (DCN 12-2501) for the range of impacts under the alternative assumptions.
Overall, the RFA analysis for Electric Generators found that few small entities would potentially incur a
significant impact under the final rule and other options considered. For the final rule, EPA estimates that zero to
three small entities will incur costs exceeding 1 percent of revenue, while no small entities will incur costs
exceeding 3 percent of revenue. At the 1 percent of revenue threshold, the associated percentages of small entities
subject to the final rule are 0 to 10 percent. These findings are the same for Proposal Option 4. EPA estimates a
higher level of small entity impacts for the more expensive Proposal Option 2: six to seven small entities would
incur costs exceeding 1 percent of revenue, and one to three small entities would incur costs exceeding 3 percent
of revenue. The associated percentages of regulated small entities are correspondingly higher at 12 to 23 percent
for the 1 percent of revenue threshold, and 2 to 10 percent for the 3 percent of revenue threshold (see Table 10-1).
Table 10-1: Summary of Findings of the Small Entity Impact Analysis for the Final
Rule and Other Options Considered, by Regulated Industry Segment and Overall
Regulatory Option
and Regulated
Industry Segment
Cost Impact Category
Cost >1 % of Revenue
Cost >3% of Revenue
Number of Small
Entities
% of Small
Entitiesb
Number of Small
Entities0
% of Small
Entitiesb
Electric Generators
Proposal Option 4
0 to 3
0% to 10%
0
0%
Final Rule
0 to 3
0% to 10%
0
0%
Proposal Option 2
6 to 7
12% to 23%
1 to 3
2% to 10%
Manufacturers3
Proposal Option 4
0
0%
0
0%
Final Rule
3 to 4
8% to 18%
Oto 1
0% to 6%
Proposal Option 2
3 to 4
8% to 18%
Oto 1
0% to 6%
Electric Generators and Manufacturersa'd
Proposal Option 4
0 to 3
0% to 6%
0
0%
Final Rule
3 to 7
4% to 13%
0 to 1
0% to 2%
Proposal Option 2
9 to 1 1
10% to 21%
1 to 4
1% to 8%
a. Entity counts used in these calculations exclude Manufacturers in Other Industries.
b. Percentage of small entities incurring a cost-to-revenue impact involves range estimates in both the numerator (number of
affected entities) and denominator (number of regulated entities).
c. Entities with cost-to-revenue ratios of at least 3 percent are included in the number of entities with cost-to-revenue such
ratios of at least 1 percent.
d. For the firm-level cost-to-revenue analysis, EPA analyzed two cases for Electric Generators and two cases for
Manufacturers. When combining the results for Electric Generators and Manufactures, this results in four potential
combinations. EPA reported the range of number of small entities and percentage of small entities across these four cases.
Due to differences in firm counts across these four cases, the values reported as the range for number of small entities may
not directly correspond to the values used to calculate the range reported for the percentage of small entities.
Source: U.S. EPA analysis for this report
The findings for Manufacturers are comparable, with very few small entities estimated to incur a significant
impact under the final rule and other options considered. For the final rule, EPA estimates that three to four small
parent entities will incur costs exceeding 1 percent of revenue, and zero to one small parent entity will incur costs
exceeding 3 percent of revenue. The associated percentages of small entities subject to the final rule are 8 percent
to 18 percent at the 1 percent threshold, and zero percent to 6 percent at the 3 percent threshold. These findings
are the same for Proposal Option 2. Proposal Option 4, which imposes technology requirements on a smaller
10-2
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subset of facilities, would have a smaller impact on small entities. Under this option, no parent entity would incur
costs exceeding either 1 percent or 3 percent of revenue (see Table 10-1).
Overall, EPA estimates for the final rule that three to seven small entities will incur costs exceeding 1 percent of
revenue, while zero to one small entity will incur costs exceeding 3 percent of revenue. The percentages of small
entities are 4 to 13 percent at the 1 percent threshold, and 0 to 2 percent at the 3 percent threshold. For Proposal
Option 4, EPA estimates that zero to three small entities would incur costs exceeding 1 percent of revenue (0 to 6
percent of small entities), and no small entity would incur costs exceeding 1 percent of revenue. For Proposal
Option 2, nine to 11 small entities would incur costs exceeding the 1 percent threshold (10 to 21 percent of small
entities), and one to four small entities would incur costs exceeding the 3 percent threshold (1 to 8 percent of
small entities) (see Table 10-1).
In summary, under the final rule, EPA estimates that a small number of small parent entities will incur a
potentially significant cost impact in the individual regulated industry segments, and overall, for both segments.
The maximum number of small entities estimated to incur costs exceeding 1 percent is seven, overall, with three
of these small entities in the Electric Generators segment and four in the Manufacturers segment. The maximum
number of small entities with costs estimated to exceed 3 percent is one, overall, with one small entity in the
Manufacturers segment. In each case, the maximum value reflects the high end of an uncertainty range that is
based on different sample weighting approaches. Values in the interior of these ranges may represent more
reasonable estimates of the number of small entities incurring significant impacts.
The estimated numbers of entities with significant impacts also represent small percentages of the estimated
number of small entities, overall, and in the individual segments. The maximum percentage values at the 1 percent
of revenue threshold are 13 percent, overall, 10 percent for Electric Generators, and 18 percent for Manufacturers.
At the 3 percent threshold, the maximum percentage values are 2 percent, overall, 0 percent for Electric
Generators, and 6 percent for Manufacturers. Again, these values reflect the high end of an uncertainty range.
In all instances, the absolute numbers of small entities estimated to incur significant impacts - at the 1 or 3
percent of revenue threshold, and by industry segment and overall - are well below EPA's guidance value (100
small entities with a significant impact) for identifying whether a regulation would cause a significant impact on a
substantial number of small entities.
10.1 Analysis of Electric Generators
10.1.1 Analysis Approach and Data Inputs
EPA used the following methodology and assumptions in performing the RFA analysis for Electric Generators.
Identifying Entities that Own Regulated Facilities
Consistent with the entity-level cost-to-revenue analysis (Chapter 4: Economic Impact Analyses- Electric
Generators), EPA conducted the RFA analysis at the highest level of domestic ownership, referred to as the
"domestic parent entity." The analysis included only entities with the largest share of ownership (majority owner)
in 532 explicitly and implicitly analyzed Electric Generators (see Appendix H). As described below, EPA
identified the parent entity for both the explicitly and implicitly analyzed facilities. Considering both categories of
facilities supports an assessment of entity-level impact that reflects the number of parent entities for not only the
explicitly analyzed Electric Generators and associated parent entities, but also for the implicitly analyzed Electric
Generators and associated parent entities.
As described for the entity-level cost-to-revenue analysis, EPA identified the majority owner for each explicitly
analyzed facility using the 2010 Questionnaire for the Steam Electric Power Generating Effluent Guidelines (SE
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industry survey), 2009 and 2011 databases published by the Department of Energy's (DOE) Energy Information
Administration (EIA), and corporate and financial websites.
Determining Whether Entities that Own Regulated Facilities Are Small
EPA determined the size of each parent entity identified in the previous step using the most recent SBA size
threshold guidelines available at the time of the analysis.164 The criteria for entity size determination vary by the
organization/operation category of the parent entity, as follows:
> Privately owned entities
¦ Include investor-owned utilities and non-utility entities with a primary business other than electric
power generation.165
¦ The relevant size criterion varies by North American Industry Classification System (NAICS) sector,
and is revenue, assets, or number of employees (Table 10-2).
> Rural Electric Cooperatives
¦ The relevant size criterion is based on the number of employees and varies by NAICS sector (Table
10-2).
> Publicly owned entities
¦ Include federal, State, municipal, and other political subdivision entities.
¦ Facilities owned by federal and State governments were considered to be large; facilities owned by
municipalities and other political units with population less than 50,000 were considered to be small.
164 To conduct this analysis, EPA used SBA size threshold guidelines published in 2013. The 2013 set of small business size guidelines is
available online at http://www.sba.gov/sites/default/files/files/size table 01072013d').pdf ("U.S. SBA. 20131 In addition, for entities
whose business operations concentrate in electric power generation, transmission, and distribution, including cooperatives, EPA used
employment-based SBA thresholds outlined in 78 FR 77343.
165 Certain regulated facilities are owned by entities whose primary business is not electric power generation.
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Table 10-2: NAICS Codes and SBA Size Standards for Entities that Own Electric Generators, With a
Primary Business Other Than Electric Power Generation

NAICS Code
NAICS Description
SBA Size Standard
212111
Bituminous Coal and Lignite Surface
500 employees
~22iTf2~
Mining
Fossil Fuel Electric Power Generation
750 employees
22 III'?"
Other Electric Power Generation
250 employees
221121a
Electric Bulk Power Transmission and
Control
500 employees
2211223
Electric Power Distribution
1,000 employees
221210
Natural Gas Distribution
500 employees
331110
Iron and Steel Mills and Ferroalloy
Manufacturing
1,000 employees
331315
Aluminum Sheet, Plate, and Foil
Manufacturing
750 employees
333611
Turbine and Turbine Generator Set Units
Manufacturing
1,000 employees
488320
Marine Cargo Handling
$35.5 million in revenue
491110
Postal Service
$7 million in revenue
522110
Commercial Banking
$175 million in assets
523910
Miscellaneous Intermediation
$7 million in revenue
524126
Direct Property and Casualty Insurance
Carriers
1,500 employees
525910
Open-End Investment Funds
$7 million in revenue
525990
Other Financial Vehicles
$7 million in revenue
541990
All Other Professional, Scientific, and
Technical Services
$14 million in revenue
551112
Offices of Other Holding Companies
$7 million in revenue
562212
Solid Waste Landfill
$35.5 million in revenue
562219
Other Nonhazardous Waste Treatment and
Disposal
$35.5 million in revenue
562920
Materials Recovery Facilities
$ 19 million in revenue
611310
Colleges, Universities, and Professional
Schools
$25.5 million in revenue
a. Note that some entities within NAICS 2211 are e
igaged in a range of operations with different 6-digit NAICS codes, and potentially different NAICS-
specific employment thresholds. To the extent that these entities could be classified using a different 6-digit NAICS code than the code provided in the SE
industry survey or found through research, their size classification could differ.

b. Is based on the 2007 NAICS framework and includes biomass, geothermal, wind, solar, and tidal generation.
Source: U.S. SBA, 2013; 78 FR 77343

To determine whether a majority owner is a small entity according to these criteria, EPA compared the value of
the relevant size criterion for the majority owner to the relevant SBA entity-size threshold value. EPA used the
following data sources and methodology to estimate the value of the relevant size criterion for each parent entity:
> Revenue: EPA used entity-level revenue values from the SE industry survey, if the SE survey reported
those values. For entities with values reported for more than one survey year (i.e., 2007, 2008, and/or
2009), EPA used the average of reported values. For entities with values reported for only one survey
year, EPA used the reported value. For entities that did not report revenue values in the SE survey, EPA
used revenue values from corporate/financial websites, if those values were available. To be consistent
with data from the SE industry survey, EPA searched for revenue for at least one of the three survey years
(i.e., 2007, 2008, and/or 2009) and if multiple values were found, used the average of the reported values
for determining entity size. For some entities however, EPA was unable to find revenue values for any of
these three years and used revenue values for 2010. If corporate/financial websites did not report revenue
values, the Agency used the 2007-2011 average of revenue values from the EIA-861 database. EPA
restated entity revenue values in 2011 dollars using the Gross Domestic Product (GDP) deflator index
published by the U.S. Bureau of Economic Analysis (BEA).
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> Employment: EPA used entity-level employment values from the SE industry survey, if the SE survey
reported those values. For entities with values reported for more than one survey year (i.e., 2007, 2008,
and/or 2009), EPA used the average of reported values. For entities with values reported for only one
survey year, EPA used the reported value. For entities with no employment values reported in the SE
industry survey, EPA used employment values from corporate/financial websites. As is the case with
revenue values, to be consisted with data from the SE industry survey, the Agency tried to obtain
employment values for at least one of the three survey years. For entities for which EPA was not able to
find employment values for either 2007, 2008, or 2009, the Agency used employment values for 2010.
> Population: EPA obtained population data for municipalities and other non-state political subdivisions
from the U.S. Census Bureau (estimated population for 2010).
EPA identified as small those parent entities for which the relevant measure is less than the SBA size criterion and
included them in the RFA analysis.
Significant Impact Test for Small Entities
To assess the extent of economic/financial impact on small entities for Electric Generators, EPA relied on the
"sales test" and used cost-to-revenue thresholds of 1 and 3 percent as markers of potentially significant impacts.
The Agency assumed that entities incurring costs below 1 percent of revenue will not face significant economic
impacts, while entities with costs of at least 1 percent but less than 3 percent of revenue have a chance of facing
significant economic impacts. Entities incurring costs of at least 3 percent of revenue have a higher probability of
significant economic impacts.
EPA developed compliance cost and revenue values for small entities using the same methodology as that
outlined for the general entity-level cost-to-revenue analysis discussed in Chapter 4. In addition, in the same way
as described for the general cost-to-revenue analysis in Chapter 4, EPA conducted this RFA analysis using two
weighting approaches:
> Using facility-level weights: For this case, EPA applied facility-level weights to the estimated compliance
costs for Electric Generators identified as being owned by a given parent entity.
> Using entity-level, weights: For this case, EPA applied entity-level weights to the calculated number of
parent entities estimated to incur costs in each cost-to-revenue range.
Consistent with the analysis discussed in Chapter 4, EPA assumed that regulated facilities, and consequently,
their parent entities, will not be able to pass any of the increase in their production costs to consumers (zero cost
pass-through). To the extent that this assumption is not the case, the potential for impacts found here will be
overstated.
10.1.2 Findings for Regulatory Options
As described above, EPA developed estimates of the number of small Electric Generators entities incurring costs
in the specified cost-to-revenue impact ranges using two weighting concepts:
> Using facility-level, weights, EPA estimates that 31 small entities own 69 regulated facilities (Table 10-3).
This assessment may overstate the number of facilities and compliance costs at the level of any given
small parent entity, but will also likely underestimate the number of affected small parent entities.
> Using entity-level weights, EPA estimates that 52 small entities own 69 regulated facilities (Table 10-3).
This calculation may understate the number of facilities and compliance costs at the level of any given
small parent entity, but accounts more comprehensively for the number of small entities that own
regulated facilities.
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Table 10-4 presents findings from the analyses outlined above in terms of numbers of small entities incurring
costs exceeding the significant impact thresholds of 1 percent and 3 percent. EPA estimates that under the final
rule, between zero and three entities will incur compliance costs exceeding 1 percent of revenue, representing
between zero and 10 percent of all small entities that own regulated facilities. Using facility-level weights, all
these entities are municipalities (43 percent of all small municipalities), while using entity-level weights, no
entities incur costs exceeding 1 percent of revenue. EPA estimates that no entities will incur compliance costs
exceeding 3 percent of revenue under either of the two weighting concepts. EPA reached the same findings for
Proposal Option 4.
EPA estimates that Proposal Option 2 would have a larger impact on small entities that own regulated facilities.
The Agency estimates that under this option, between six and seven entities would incur compliance costs
exceeding 1 percent of revenue, representing 12 percent and 23 percent of all small entities that own regulated
facilities, respectively. Further, EPA estimates that compliance costs would exceed 3 percent of revenue for one to
three small entities (2 percent and 10 percent of all small entities that own regulated facilities, depending on the
weighting concept).
Given (1) the small absolute number of small entities estimated to incur a potentially significant cost impact and
(2) the low percentage of small entities that own Electric Generators, EPA concludes that the final rule will not
have "a significant impact on a substantial number of small entities" within the Electric Generators industry
segment.
Table 10-3: Number of Regulated Facilities and Entities that Own these Facilities by Ownership
Type and Size (assuming two alternative weighting cases)ab

Number of Parent Entities
Ownership
Small Entity Size
Number of Regulated
Facilities0
Using Facility-Level
Weights
Using Entity-Level
Weights®
Type
Standard
Total
Small"
% Small
Total
Small"
% Small
Total
Small"
% Small
Cooperativef
number of employees
29
24
83.1%
13
11
84.6%
21
18
85.7%
Federal
assumed large
14
0
0.0%
1
0
0.0%
1
0
0.0%
Investor-ownedf
number of
employees/revenue/assets
376
8
2.2%
57
6
10.5%
60
7
11.7%
Municipality
50,000 population served
38
16
43.1%
19
7
36.8%
38
19
50.0%
Nonutilityf
number of
employees/revenue/assets
72
21
28.7%
26
7
26.9%
30
8
26.7%
Other Political
Subdivision
50,000 population served
9
0
0.0%
4
0
0.0%
6
0
0.0%
State
assumed large
7
0
0.0%
3
0
0.0%
3
0
0.0%
Total
544
69
12.7%
123
31
25.2%
159
52
32.7%
a. For details on weighting cases and facility and entity counts, see Appendix H.
b. Ten analyzed surveyed DQ and STQ facilities are owned by a joint venture of two entities with equal ownership shares.
c. Facility counts are weighted estimates generated using facility-count based weights. For details, see Appendix H.
d. EPA was unable to determine the size of seven parent entities and assumed that these entities are small.
s. There are 53 small parent entities on an unweighted basis, one of which is another political subdivision entity. This entity owns only
implicitly analyzed facilities; consequently, there is no explicitly analyzed entity in the other political subdivision ownership category to
represent this implicitly analyzed small parent entity. As the result, weighted entity counts do not include one small other political subdivision
f. SBA thresholds vary by 6-digit NAICS code of
Source: U.S. EPA analysis for this report
parent entity.

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Chapter 10: Regulatory Flexibility Act (RFA) Analysis
Table 10-4: Estimated Cost-to-Revenue Impact on Small Entities that Own Electric Generators, by
Ownership Typea'b'c
Parent Entity Type
Using Facility-Level Weights
Using Entitv-Level Weights
Cost >1 % of Revenue
Cost >3% of Revenue
Cost >1 % of Revenue
Cost >3% of Revenue
Number of
Small
Entities
% of Small
Entities
Number of
Small
Entities
% of Small
Entities
Number of
Small
Entities
%of Small
Entities
Number of
Small
Entities
%of Small
Entities
Proposal Option 4
Rural Electric Cooperative
0
0.0%
0
0.0%
0
0.0%
0
0.0%
Investor-Owned Utility
0

0
0.0%
0
0.0%
Municipality
3
42.9%
0

0
0.0%
0
0.0%
Nonutility
0
0.0%
0

0
0.0%
0
0.0%
Other Political Subdivision
0
NA
0
NA
0
NA
0
NA
Total
3
9.7%
0
0.0%
0
0.0%
0
0.0%
Final Rule
Rural Electric Cooperative
0
0.0%
0
0.0%
0
0.0%
0
0.0%
Investor-Owned Utility
0
0.0%
0
0.0%
0
0.0%
0
0.0%
Municipality
3
42.9%
0

0
0.0%
0
0.0%
Nonutility
0
0.0%
0

0
0.0%
0
0.0%
Other Political Subdivision
0
NA
0
NA
0
NA
0
NA
Total
3
9.7%
0
0.0%
0
0.0%
0
0.0%
Proposal Option 2
Rural Electric Cooperative
3
27.3%
2
18.2%
5
27.3%
0
0.0%
Investor-Owned Utility
0
0.0%
0

0
0.0%
0
0.0%
Municipality
3
42.9%
0
0.0%
0
0.0%
0
0.0%
Nonutility
1
14 i%
1
14 i%
1
14 i%
1
14 i%
Other Political Subdivision
0
NA
0
NA
0
NA
0
NA
Total
7
22.6%
3
9.7%
6
11.6%
1
2.2%
a. The impact values presented in this table assume that all facilities with cooling water impoundments qualify as baseline CCRS, and incur no additional
technology costs for regulatory compliance.
b. Entities with cost-to-revenue ratios of at least 3 percent are included in the number of entities with cost-to-revenue such ratios of at least 1 percent.
c. EPA was not able to obtain revenue and therefore was not able to calculate cost-to-revenue ratio for four small entities (five on a weighted basis).
Source: U.S. EPA analysis for this report
10.2 Analysis of Manufacturers
10.2.1 Analysis Approach and Data Inputs
EPA determined whether entities that own Manufacturers are small according to the SBA entity size criteria, in
two steps:
> Identify the domestic parent entity of the sample Manufacturers, and
> Determine the size of entities that own the sample Manufacturers (for details on sample Manufacturers,
see Appendix H).
Identification of Domestic Parent Entities
Consistent with the entity-level, cost-to-revenue analysis (Chapter 5: Economic Impact Analyses -
Manufacturers), EPA conducted the RFA analysis at the highest level of domestic ownership, referred to as the
"domestic parent entity." EPA included only entities with the largest share of ownership (majority owner)166 as
reported in the 316(b) survey. As was done for the entity-level cost-to-revenue analysis, EPA used information
reported in the 316(b) survey, if available, to identify and characterize the parent entity in terms of information
(business sector, revenue and employment) that is relevant for the small entity size determination. In instances
where the survey did not provide a response, EPA searched corporate websites and annual reports, and Dun &
100 Throughout the analyses, EPA refers to the owner with the largest ownership share as the "majority owner" even when the ownership
share is less than 51 percent.
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Bradstreet data (D&B, 2009) to obtain information on parent entity NAICS sector, revenues, and employment. If
parent revenue and/or employment were not available from any of these sources, EPA summed the revenue and/or
employment information for all facilities owned by the entity as a lower-bound estimate of these metrics. This
backup approach has the potential to understate the size of the parent entity and thus overstate the impact on small
entities.
Size Determination of Domestic Parent Entities
EPA identified the size of each entity that owns a sampled Manufacturer using the most recent SBA size threshold
guidelines. These thresholds define the minimum entity-level employment, generation, or revenue size, by
industry (by 6-digit NAICS code), below which an entity qualifies as small according to SBA guidelines. To
determine entity size, EPA used data from the sources listed above.
EPA started with the unique entity-level, 6-digit NAICS codes for entities that own regulated facilities under the
regulatory analysis options.167 Table 10-5 presents the unique entity-level 6-digit NAICS codes and
corresponding SBA size standards used to determine the size of entities that own Manufacturers.
167 Where EPA could not determine the entity-level NAICS code, EPA used the facility-level NAICS code for assigning the entity to a
NAICS sector. If neither the entity- nor the facility-level NAICS code could be determined, EPA assumed that the parent entity was
small. This assumption may overstate the count of small entities and thus, the impact of the final rule and other options considered in
development of this rule on small entities.
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Chapter 10: Regulatory Flexibility Act (RFA) Analysis
Table 10-5: Unique 6-Digit Entity-Level NAICS Codes and SBA Size Standards for Manufacturers
NAICS
NAICS Description
SBA Size Threshold
I I 1930
Sugarcane Farming
$750,000 in Revenue
miTo
l imber Tract Operations
$7,000,000 in Revenue
TiTTTl
Crude Petroleum and Natural lias Lxtraction
500 Lmployees
TiIJio
Iron Ore Mining
500 Lmployees
Tl23'7l
Potash. Soda, and Borate Mineral Mining
500 Lmployees
____
l!lectric Power Distribution
7.0()().()()0 MWh of Llectnc Generation
31 1221
Wet Com Milling
750 Lmployees
TTTTTT
Cane Sugar Manufacturing
750 Lmployees

Beet Sugar Manufacturing
750 Lmployees
371942
Spice and Lxtract Manufacturing
500 Lmployees
JTJITo
Broadwoven Fabric Mills
1.000 Llll)
32TTT3
Sawmills
500 Lmployees
322121
Paper (except Newsprint) Mills
750 Lmployees
322122
Newsprint Mills
750 Lmployees
322T30
Paperboard Mills
750 Lmployees
322271
Corrugated and Solid Fiber Box Manufacturing
500 Lmployees
322220
Paper Bag and Coated and Treated Paper Manufacturing
500 Lmployees
322291
Sanitary Paper Product Manufacturing
500 Lmployees
32jf|o
Petroleum Refineries
1.500 Lmployees
3247*91
Petroleum Lubricating Oil and Urease Manufacturing
500 Lmployees
325120
Industrial lias Manufacturing
1.000 Llll)
325180
Other Basic Inoraanic Chemical Manufacturiim
1.000 Lmployees
325IW
All Other Basic Oraanic Chemical Manufacturiim
1.000 Lmployees
325211
Plastics Material and Resin Manufacturiim
750 Lmployees
325311
Nitrogenous Fertilizer Manufacturiim
1.000 Lnif
325320
Pesticide and Other Agricultural Chemical Manufacturing
500 Lmployees
325412
Pharmaceutical Preparation Manufacturing
750 Lmployees
325510
Paint and Coating Manufacturing
500 Lmployees
325992
Photographic Film, Paper, Plate and Chemical Manufacturing
500 Lmployees
32599S
All Other Miscellaneous Chemical Product and Preparation Manufacturing
500 Lmployees
33'TTTo
Iron and Steel Mills and Ferroalloy Manufacturing
1.000 Lnif
331210
Iron and Steel Pipe and Tube Manufacturing from Purchased Steel
1.000 Lmployees
331221
Rolled Steel Shape Manufacturing
1.000 Lmployees
331222
Steel Wire Drawing
1.000 Lmployees
?
Alumina Refining and Primary Aluminum Production
1.000 Llll)
331315
Aluminum Sheet, Plate and Foil Manufacturing
750 Lmployees
337Jfo
Nonferrous Metal (except Aluminum) Smelting and Refining
1.000 Lmployees
332312
Fabricated Structural Metal Manufacturing
500 Lmployees
33^910
Mattress Manufacturing
500 Employees
339999
All Other Miscellaneous Manufacturing
500 Employees

Lumber. Ph wood. Millwork. and Wood Panel Merchant Wholesalers
100 Employees
423930
Recyclable Material Merchant Wholesalers
100 Lmployees
l2l?IO
____
Grain and Field Bean Merchant Wholesalers
100 Lmployees

Other Chemical and Allied Products Merchant Wholesalers
100 Lmployees
'124710
_____
Petroleum Bulk Stations and Terminals
100 Lmployees

Other Gasoline Stations
$i 4.000.000 in Revenue
522220
Sales Financing
$7,000,000 in Revenue
523910
Miscellaneous Intermediation
$7,000,000 in Revenue
523930
Investment Advice
$7,000,000 in Revenue
524126
Direct Property and Casualty Insurance Carriers
1.500 Lmployees
525991]
Other Financial Vehicles
$7,000,000 in Revenue
synio
Lessors of Residential Buildings and Dwellings
$25,000,000 in Revenue
55717*2
Offices of Other I Iolding Companies
$7,000,000 in Revenue
561110
Office Administrative Services
$7,000,000 in Revenue
Source: U.S. SBA, 2013
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Chapter 10: Regulatory Flexibility Act (RFA) Analysis
Similarly to the general entity-level cost-to-revenue analysis discussed in Chapter 5, EPA estimated the number
of small entities that own Manufacturers as a range, based on alternative assumptions about the possible
ownership of regulated facilities by small entities:
> Case 1: Lower bound estimate of number of entities that own regulated facilities; upper bound estimate of
total compliance costs that an entity may incur.
> Case 2: Upper bound estimate of number of entities that own regulated facilities; lower bound estimate of
total compliance costs that an entity may incur.
The remainder of this section presents data organized by the entity's industry sector. EPA determined an entity's
sector based on the sample facilities owned by the entity, and their industry sector(s). If all of the sampled
facilities owned by the entity are in the same industry sector, then EPA assigned that industry sector to the entity.
However, if the sample facilities owned by the entity are in more than one industry sector, then EPA assigned the
entity to the "Multiple Industries" entity sector. In this analysis, EPA found that two known facilities in the Other
Industries group were owned by entities that also own facilities in the Primary Manufacturing Industries. EPA
included these entities in the Multiple Industries sector.
Table 10-6 reports the total number of entities that own regulated facilities and the number and percentage of
those entities EPA determined to be small, based on these alternative analytic cases.
Table 10-6: Number of Entities by Sector and Size (under alternative ownership cases)3'0'"

Case 1: Lower bound estimate of number of
Case 2: Upper bound estimate of number of

entities that own regulated facilities
entities that own regulated facilities

Total Number
Number of
Percentage of
Entities that
Total Number
Number of
Percentage of
Entities that
Industry Sector
of Entities
Small Entities
are Small
of Entities
Small Entities
are Small
Aluminum
4
2
50.0%
11
4
40.6%
Chemicals and Allied Products
30
5
16.7%
121
21
17.7%
Food and Kindred Products
6
0
0.0%
20
0
0.0%
Paper and Allied Products
37
7
18.9%
104
23
21.8%
Petroleum Refining
16
2
12.5%
25
2
8.4%
Steel
13
1
7.7%
32
2
5.2%
Multiple Industries
4
0
0.0%
14
0
0.0%
Entities that own facilities in Primary
110
17
15.5%
327
52
16.0%
Manufacturing Industries

a. For details on weighting cases and facility and entity counts, see Appendix H.
b. Excludes entities that own only sample facilities assessed as baseline closures. For details, see Chapter 5.

c. Individual numbers may not sum to reported totals due to independent rounding.
d. EPA did not compile comparable information for Other Industries facilities and the entities that own them because it did not have a statistically valid
sample of facilities from which to develop such estimates.

Source: U.S. EPA analysis for this report

Similarly to the RFA analysis conducted for Electric Generators (Section 10.1), to assess the economic/financial
impact on small entities, EPA compared the annualized, after-tax compliance costs for each identified entity to the
entity's annual revenue. The Agency identified entities for which annualized compliance costs are at least 1
percent and 3 percent of revenue and evaluated the absolute number and the percentage of entities in each impact
category, and by Manufacturing Industry. Consistent with the entity-level cost-to-revenue analysis discussed in
Chapter 5, the Agency assumed that entities incurring costs below 1 percent of revenue are unlikely to face
significant economic impacts. Alternatively, entities with costs of at least 1 percent of revenue have a higher
chance of facing significant economic impacts, and entities incurring costs of at least 3 percent of revenue have a
still higher likelihood of significant economic impacts.
Chapter 5 provides additional details of how EPA developed these entity-level compliance cost and revenue
values.
May 2014
10-11
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 10: Regulatory Flexibility Act (RFA) Analysis
10.2.2 Findings for Regulatory Options
Table 10-7 presents findings from the analyses outlined above in terms of numbers of small entities incurring
costs exceeding the significant impact thresholds of 1 percent and 3 percent.
Under the final rule, EPA estimates that three to four small entities that own regulated facilities in the Primary
Manufacturing Industries incur costs exceeding 1 percent of revenue threshold (8 to 18 percent of small entities
that own regulated facilities); zero to one small entities incur costs exceeding 3 percent of revenue (zero to 6
percent of small entities). The ranges reflect the alternative weighting approaches, Case 1 (lower bound estimate
of number of entities that own regulated facilities), and Case 2 (upper bound estimate of number of entities that
own regulated facilities). For the small entities that own facilities in Other Industries, one incurs costs exceeding 1
percent of revenue, with no entity incurring costs exceeding 3 percent of revenue.
Under Proposal Option 4, EPA estimates that no small entity would incur costs exceeding 1 percent of revenue or
3 percent of revenue. For Proposal Option 2, EPA reached the same findings as for the final rule.
Table 10-7: Estimated Cost-To-Revenue Impact on Small Entities that Own Manufacturers, by Industry3'"'0

Case 1: Lower bound estimate of number of
Case 2: Upper bound estimate of number of

entities that own regulated facilities
entities that own regulated facilities

Cost >1% of Revenue
Cost > 3% of Revenue
Cost >1% of Revenue
Cost > 3 % of Revenue

Number of

Small
%of Small
Small
%of Small
Small
% of Small
Small
%of Small
Industry
Entities
Entities
Entities
Entities
Entities
Entities
Entities
Entities
Proposal Option 4
Aluminum
0
0%
0
0%
0
0%
0
0%
Chemicals and Allied Products
0
X,
0
%,
0
%,
0
%,
Food and Kindred Products
0
A
0
A
0
A
0
A
Paper and Allied Products
0
%,
0
%,
0
%,
0
%,
Petroleum Reliniim
0
%,
0
%,
0
%,
0
%,
Steel
0
%,
0
%,
0
%,
0
%,
Multiple Industries
0
NA
0
NA
0
NA
0
NA
Entities that own regulated
0
0%
0
0%
0
0%
0
0%
facilities in Primary
Manufacturing Industries d

Additional entities that own
1
-
0
-
1
-
0
-
known regulated facilities in
Other Industries6

Final Rule
Aluminum
0
0%
0
0%
0
0%
0
0%
Chemicals and Allied Products
1
%
1
%
4
%,
0
%,
Food and Kindred Products
0
A
0
A
0
A
0
A
Paper and Allied Products
2
%
0
%,
0
%,
0
%,
Petroleum Reliniim
0
%,
0
%,
0
%,
0
%,
Steel
0
%,
0
%,
0
%,
0
%,
Multiple Industries
0
NA
0
NA
0
NA
0
NA
Entities that own regulated
3
18%
1
6%
4
8%
0
0%
facilities in Primary
Manufacturing Industries d

Additional entities that own
2
-
0
-
2
-
0
-
known regulated facilities in
Other Industries6

10-12
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 10: Regulatory Flexibility Act (RFA) Analysis
Table 10-7: Estimated Cost-To-Revenue Impact on Small Entities that Own Manufacturers, by Industry3'"'0

Case 1: Lower bound estimate of number of
Case 2: Upper bound estimate of number of

entities that own regulated facilities
entities that own regulated facilities

Cost >1 % of Revenue
Cost > 3% of Revenue
Cost >1 % of Revenue
Cost >3% of Revenue

Number of

Small
%of Small
Small
%of Small
Small
%of Small
Small
%of Small
Industry
Entities
Entities
Entities
Entities
Entities
Entities
Entities
Entities
Proposal Option 2
Aluminum
0
0%
0
0%
0
0%
0
0%
Chemicals and Allied Products
1
%
1
%
4
>/„
0
>/„
Food and Kindred Products
0
A
0
A
0
A
0
A
Paper and Allied Products
2
/,
0
y„
0
y„
0
y„
Petroleum Reliniim
0
y„
0
y„
0
y„
0
y„
Steel
0
y„
0
y„
0
y„
0
y„
Multiple Industries
0
NA
0
NA
0
NA
0
NA
Entities that own regulated
3
18%
1
6%
4
8%
0
0%
facilities in Primary
Manufacturing Industries d

Additional entities that own
2
-
0
-
2
-
0
-
known regulated facilities in
Other Industries6

a. For details on weighting cases and facility and entity counts, see Appendix H.
b. Excludes entities that own only sample facilities assessed as baseline closures.

c. The impact values presented in this table assume that all facilities with cooling water impoundments qualify as baseline CCRS, and incur no additional
technology costs for regulatory compliance.
d. Individual numbers may not sum to reported totals due to independent rounding.
e. EPA reports impact results for small entities that own facilities in Other Industries only as the findings from the analysis of those specific facilities for
which EPA received 316(b) survey responses. Because EPA lacks a statistically valid sample of facilities in Other Industries, the Agency did not develop
population-level estimates of (1) total small entities that own facilities in Other Industries, (2) the number of these small entities incurring potentially
significant impacts, or (3) the percentage of total regulated small entities that these entities would represent. EPA has no statistically valid basis for
developing such estimates.

Sources: U.S. EPA analysis for this report

10.3 Uncertainties and Limitations
The RFA analysis for regulated facilities - Electric Generators and Manufacturers - is subject to several
uncertainties and limitations, including:
> None of the sample-weighting approaches used for this analysis accounts precisely for the number of
parent-entities and compliance costs assigned to those entities simultaneously for either Electric
Generators or Manufacturers. However, the values presented in this chapter are reasonable estimates of
the numbers of small entities that could incur a significant impact according to the impact concepts.
> To the extent that information reported in the 316(b) survey for Manufacturers and used in this analysis
does not reflect 2011 conditions, the number of small parent entities of Manufacturers may be over- or
under-stated, and the impact of the final rule and other options considered on parent entities of
Manufacturers may be over- or under-estimated.
> The RFA analysis for Electricity Generators relies on facility count-based sample weights to extrapolate
costs from the explicitly analyzed facilities to the implicitly analyzed facilities (see Appendix H). The use
of sample weighting to extend the estimated compliance costs to the implicitly analyzed facilities
inherently introduces uncertainty into the analysis. Consequently, the cost estimates generated through
applying facility-level weights may over- or under-state the costs that a given parent-entity would incur.
This could also be the case with the entity counts in each of the impact magnitude groups (e.g., number of
entities with costs exceeding 3 percent of revenue), even if the facility-weights account properly for
facility ownership.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 10: Regulatory Flexibility Act (RFA) Analysis
> For Electric Generators, the entity-level revenue values from the various data sources (SE industry
survey, corporate and financial websites, and EIA databases) are for years ranging from 2007 through
2011. To the extent that the actual 2011 entity revenue values differ, on a constant dollar basis, from the
estimated values, this analysis may over- or under-estimate the impact of the final rule and other options
on parent entities of Electric Generators.
> Likewise, for Electric Generators, the entity-level revenue, assets, employment, and electricity sales
values for determining entity size are also derived from data for years ranging from 2007 through 2011.
To the extent that these historical data-based values would differ from actual 2011 values, the analysis
may over- or under-state the number of parent entities that are classified as small.
> As is the case with the general entity-level cost-to-revenue analysis conducted for Electric Generators
(Chapter 4), the zero cost pass-through assumption used for the RFA analysis is relatively simple and
used for analytic convenience rather than being an accurate description of the market sector in which
these facilities operate. To the extent that some small entities are able to pass at least some compliance
costs to consumers through higher electricity prices, this analysis overstates the potential entity-level
impact of the final rule and other options considered.
> As described earlier in this chapter, the RFA analysis results presented in this chapter assume that all
facilities known to have impoundments as part of their cooling water intake system will qualify as
baseline CCRS, and will not incur additional technology cost under the final rule and other options EPA
considered. To the extent that some of these facilities would incur costs for installation of compliance
technology, the impact findings reported in this chapter may be underestimates. See Memorandum to the
Record (DCN 12-2501) for the range of impacts that could occur based whether these facilities would
need to install additional compliance technology.
10-14
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 11: UMRA Analysis
11 Unfunded Mandates Reform Act (UMRA) Analysis
Title II of the Unfunded Mandates Reform Act {UMRA) of 1995, Pub. L., 104-4 requires that federal agencies
assess the effects of their regulatory actions on State, local, and Tribal governments, and the private sector. Under
UMRA section 202, the promulgating authority - in this case, EPA - generally must prepare a written statement
and a cost-benefit analysis for proposed and final rules with "Federal mandates" that may result in expenditures
by State, local, and Tribal governments, in the aggregate, or by the private sector, of $100 million or more
(adjusted annually for inflation) in any one year. Before promulgating a regulation for which a written statement
is needed, UMRA section 205 generally requires EPA to identify and consider a reasonable number of regulatory
alternatives and to adopt the least costly, most cost-effective, or least burdensome alternative that achieves the
objectives of the rule. The provisions of section 205 do not apply when they are inconsistent with applicable law.
Moreover, section 205 allows EPA to adopt an alternative other than the least costly, most cost-effective, or least
burdensome alternative if the Administrator publishes with the rule an explanation of why EPA did not adopt that
alternative. Before EPA establishes any regulatory requirements that might significantly or uniquely affect small
governments, including Tribal governments, the Agency must have developed a small government agency plan
under UMRA section 203. The plan must provide for: (1) notifying potentially affected small governments, (2)
enabling officials of affected small governments to have meaningful and timely input in the development of EPA
regulatory proposals with significant intergovernmental mandates, and (3) informing, educating, and advising
small governments on compliance with regulatory requirements.
Concerning the question of whether the final rule could result in expenditures by State, local, and Tribal
governments, or by the private sector, exceeding $139 million168 in any one year, EPA found the following:
> EPA estimates that the maximum cost to governments (excluding the federal government) in any one
year, for compliance169 with, and administration of, the final rule, is $72.3 million.17"
> EPA estimates that the maximum cost to the private sector in any one year for compliance with the final
rule is $1.1 billion.
Thus, EPA determined that the final rule contains a federal mandate that may result in expenditures of $139
million or more for the private sector in any one year. Accordingly, under UMRA section 202, EPA has prepared
a written statement, presented in the preamble to the final rule, which includes (1) a cost-benefit analysis; (2) a
summary of State, local, and Tribal input; (3) a discussion related to the least burdensome option requirement; and
(4) an analysis of small government burden. This chapter contains additional information to support that
statement, including information on compliance and administrative costs, and on impacts to small governments.
Chapter 8 contains information on the cost-benefit analysis, which UMRA provisions also require, and which is
summarized in the preamble.
EPA conducted the UMRA analysis presented in this chapter for the existing unit provision of the final rule.171
This analysis generally relies on the analytic conventions described elsewhere in this document. Key
considerations for the UMRA analysis include:
108 $ 13 9 million is the value in $2011 of the $ 100 million threshold value, adjusted for inflation based on the GDP Deflator, as stated in
UMRA at the time of its enactment in 1995.
109 Governments own some Electric Generators and thus incur compliance costs.
170 Maximum costs are undiscounted costs incurred by the entire universe of the relevant set of affected entities - governments (excluding
the federal government) or private sector - in a given year of occurrence.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 11: UMRA Analysis
> Costs (both technology-related and administrative) to Manufacturers and Electric Generators to comply
with the final rule and other options considered reflect pre-tax cost values (consistent with the social cost
analysis).
> Annualized costs are developed from the social cost framework described in Chapter 7: Total Social
Costs. For this analysis, EPA used annualized 2013 cost values stated in 2011 dollars. All costs reflect
weighted values unless otherwise noted.
> For all cost items in the social cost analysis except Electric Generators downtime, costs reflect (1) the
assignment of compliance costs to regulated facilities, and (2) the assignment of administrative costs to
governments based on the location of regulated facilities. For the UMRA analysis, EPA allocated these
costs to governments, by type172 and size, and to the private sector, by size, based on the characteristics of
the facilities or the governments to which these costs were originally assigned in the cost and economic
impact analyses. However, EPA did not develop social cost estimates for Electric Generators downtime at
the level of the regulated facility and instead, based the values on the aggregate increase in variable costs
of electricity generation for the entire industry while units are down.173 Accordingly, for the social cost
analysis, these costs are not assigned to individual facilities. As a result, for the UMRA analysis, it is not
possible to use the original assignment of Electric Generators downtime costs to allocate (1) government
costs among the relevant government groups - State, local and Tribal, as a group, vs. federal; and small
vs. large government - or (2) private costs between relevant small and large private entities.174
EPA sought a method that would assign the cost of Electric Generators downtime to the various groups
that would incur the additional costs and associated electricity price increases that would result from
downtime. These groups include electricity consumers- households, business customers, institutional
customers, and governments - which may experience price increases. While it would be possible to
allocate the social cost of Electric Generators downtime across electricity customer classes - for example,
based on the total consumption of electricity by customer classes, as reported in data from the Department
of Energy, Energy Information Administration - data are not available to assign these costs to small and
large entities within these customer classes. As an alternative, EPA allocated the social cost of downtime
to the affected groups in proportion to total electricity generation at the facility level for facilities subject
to the final rule. This allocation is similar to the assignment of other compliance costs in the UMRA
analysis, which flow to relevant groups based on the origin of costs at the level of regulated facilities.
EPA views the allocation to be within a range of reasonable judgment, in particular given that Electric
Generators downtime cost constitutes a small part of the final rule's total social cost (approximately 11
percent).
> In the same way as described in previous chapters, the UMRA analysis assumes that all facilities with
cooling water system impoundments will qualify as baseline CCRS, and will not need to install additional
technology under the final rule and other options considered. To the extent that some of these facilities do
not qualify as baseline CCRS, the costs and impacts reported in this chapter may be underestimates. See
171 UMRA requires analysis of costs by types and size of government entity, and by government vs. private sector. Because EPA cannot
predict the kinds of private or government entities that may incur costs for either complying with, or administering, the new unit
provision, EPA was not able to perform the UMRA analysis for costs from the new unit provision.
172 State, local and Tribal, as a group, and Federal.
173 As opposed to the cost (loss in income) incurred by regulated Electric Generators due to downtime. See Chapter 7: Total Social Costs,
for more information on the development of social costs, in general, and social cost of installation downtime for Electric Generators,
in particular.
174 Although UMRA does not require analysis of costs by size of private entity, this analysis uses information on the costs incurred by
small private entities in examining whether the final rule would uniquely affect small governments.
11-2
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 11: UMRA Analysis
Memorandum to the Record (DCN 12-2500) for the range of costs and impacts under the alternative
assumptions.
The remainder of this chapter reports the impact of the final rule and other options considered on government
entities (Section 11.1), small government entities (Section 11.2), and the private sector (Section 11.3). The final
section of the chapter summarizes overall findings relative to UMRA requirements (Section 11.4).
11.1 UMRA: Analysis of Impact on Government Entities
EPA assessed the burden of the final rule and other options considered on State, local, and tribal government
entities that own Electric Generators and Manufacturers. The use of the phrase "government entities" in this
section does not include the federal government, which owns 14 of the 544 Electric Generators (weighted). In
evaluating the magnitude of regulatory impact on government entities, EPA considered two burden concepts:
1. Compliance costs incurred by government entities that own regulated facilities. Because no
Manufacturers are government-owned, EPA limited this assessment to Electric Generators.
2. Administrative costs incurred to implement the final rule and other options considered. This assessment
applies to both Electric Generators and Manufacturers.
EPA performed these assessments only for the existing unit provision of the final rule and other existing unit
options considered because as stated above, EPA cannot predict the kinds of private or government entities that
may incur costs for either complying with, or administering, the new unit provision. Administrative costs to
government entities are based on the permit administration costs for facilities that require State review (see
Section 11.1.2).
See Chapter 10: Regulatory Flexibility Act (RFA) Analysis for information on how EPA identified the owner
entities, and determined their type and size.
11.1.1 Compliance Costs
Table 11-1 reports the number of State and local government entities that own Electric Generators, and the
number of Electric Generators they own. Overall, EPA estimates that 47 State and local government entities own
65 Electric Generators. Municipalities own the majority (74 percent) of the government-owned Electric
Generators, followed by other political subdivisions (17 percent) and State governments (9 percent).175
Table 11-1: Government-Owned Electric Generators and Their Parent Entities
Entity Type
Parent Entities3
Electric Generators6
Municipality
38
48
Other Political Subdivision
6
11
State
3
6
Tribal
0
0
Total
47
65
a. Counts of entities that own explicitly and implicitly analyzed Electric Generators; these counts do not rely on sample weights.
b. Counts of explicitly and implicitly analyzed Electric Generators; these counts do not rely on sample weights.
Source: U.S. EPA analysis for this report

EPA estimates that in the aggregate, State and local government entities will incur total annualized cost of $11.3
million under the final rule, with an average and maximum of $0.2 million and $1.3 million per facility,
respectively. The highest annualized compliance cost incurred by a State-owned facility is $0.2 million (see
Table 11-2).
175 Entity counts include parent entities of explicitly and implicitly analyzed Electric Generators, and are not sample-weighted. Facility
counts include explicitly and implicitly analyzed Electric Generators, and are not sample-weighted.
May 2014
11-3
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 11: UMRA Analysis
Table 11-2: Compliance Costs to Government Entities that Own Electric Generators (Millions;
$2011)

Maximum
Ownership Type
Number of
Regulated Facilities
(weighted)3
Total Weighted,
Annualized Pre-tax
Compliance Cost
Average Annualized
Compliance Cost per
Facilityb
Annualized
Compliance Cost per
Facility0
Proposal Option 4
Municipality
38
$4.4
$0.1
$0.5
Other Political Subdivision
9
$5.9
$0.6
$1.3
State
7
$0.6
$0.1
$0.2
All Facilities
54
$10.9
$0.2
$1.3
Final Rule
Municipality
38
$4.8
$0.1
$0.5
Other Political Subdivision
9
$5.9
$0.6
$1.3
State
7
$0.6
$0.1
$0.2
All Facilities
54
$11.3
$0.2
$1.3
Proposal Option 2
Municipality
38
$28.9
$0.8
$4.3
Other Political Subdivision
9
$78.1
$8.4
$16.0
State
7
$4.6
$0.7
$1.4
All Facilities
54
$111.5
$2.1
$16.0
a. Because Table 11-2 reports sample-weighted cost estimates, facility counts in this table also reflect sample weighting and differ from the
values reported in Table 11-1 and Table 11-4, which are un-weighted values. See Appendix H: Sample Weights for discussion of the use of
sample weights for estimating costs.

b. EPA calculated average cost per facility using the total number of regulated facilities owned by entities in a given ownership category.
c. Reflects maximum of un-weighted costs to explicitly analyzed facilities only.
Source: U.S. EPA analysis for this report

11.1.2 Administrative Costs
EPA estimates that 46 States and one territory with NPDES permitting authority will incur costs to administer the
final rule and options considered.176 As shown in Table 11-3, EPA estimates that State and local government
entities will incur annualized costs of $0.9 million to administer the final rule for Electric Generators and
Manufacturers. Under the final rule, annual monitoring, reporting, and recordkeeping activities account for the
largest portion of administrative costs.
170 Federal government permitting authorities will also incur costs to administer the final rule. As stated earlier in this chapter, consistent
with UMRA analysis requirements, EPA did not account for costs to federal entities in this analysis.
11-4
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 11: UMRA Analysis
Table 11-3: Annualized Government Administrative Costs to States (Millions;
$2011)

Annualized Cost,
Annualized Cost,
Total Annualized
Activity
Electric Generators
Manufacturers
Cost
Proposal Option 4
Start-Up Activities

$0.0a
Initial Permitting Activities
$0.2
$0.2
$0.4
Annual Monitoring, Reporting, and
Recordkeeping Activities
$0.2
$0.2
$0.5
Non-Annually Recurring Permitting Activities
$0.(7
$0.(7
$0.1
Total0
$0.5
$0.4
$0.9
Final Rule
Start-Up Activities
$0.0"
Initial Permitting Activities
$0.2
$0.2
$0 4
Annual Monitoring, Reporting, and
$0.2
$0.2
$0.5
Recordkeeping Activities

Non-Annually Recurring Permitting Activities
$0.(7
$0.(7
$0.1
Total0
$0.5
$0.4
$0.9
Proposal Option 2
Start-Up Activities

$o.oa
Initial Permitting Activities

$0.1
$0.2
Annual Monitoring, Reporting, and
Recordkeeping Activities
$0.2
$0.2
$0.4
Non-Annually Recurring Permitting Activities
$0.(7
SO. (7
SoV(7
Total0
$0.2
$0.4
$0.6
a. Costs associated with start-up activities are estimated for both Electric Generators and Manufacturers; these costs are less than $20,000.
b. Costs are less than $50,000.

c. Excludes costs to federal government entities.

Source: U.S. EPA analysis for this report

11.2 UMRA: Analysis of Impact on Small Governments
As part of the UMRA analysis, EPA also assessed whether the final rule and other options considered would
significantly and uniquely affect small governments. Specifically, EPA examined whether the final rule, or the
options considered, would affect small governments in a way that is disproportionately burdensome in
comparison to the effect on large governments. EPA compared the estimates for small governments of total costs,
cost per facility, and average cost per MW, with those values for large governments. EPA also compared the per
facility costs incurred for small government-owned facilities with those incurred by non-government-owned
facilities. The Agency assessed costs per facility on the basis of both average and maximum annualized cost per
facility.
Of 65 government-owned Electric Generators, EPA identified 20 facilities that are owned by 20 small
governments. These 20 facilities constitute approximately 31 percent of the total number of government-owned
facilities.177
Table 11-4: Government-Owned Electric Generators, by Size of Government3
Entity Type
Large
Small
Total
Municipality
29
19
48
Other Political Subdivision
10
1
11
State
6
0
6
Tribal
0
0
0
Total
45
20
65
a. Counts of explicitly and implicitly analyzed Electric Generators; these are not sample-weighted counts. See
Appendix H for discussion on explicitly and implicitly analyzed facilities and facility sample weights.
Source: U.S. EPA analysis for this report

177 Counts exclude federal government entities and regulated facilities they own.
May 2014
11-5
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 11: UMRA Analysis
As reported in Table 11-5, EPA estimates that compliance costs are lower for small government entities in
comparison to large government entities or to small and large private entities in the aggregate and on a per facility
basis, regardless of the analyzed option. This finding suggests that the final rule will not, and other options
considered would not, uniquely or disproportionately affect small government entities.
For the final rule, EPA estimates that small government entities will incur total annualized costs of $2.6 million,
which is less than the total cost of $8.6 million incurred by large government entities or the $8.5 million incurred
by small private entities. On a per-facility basis, EPA estimates that facilities owned by small government entities
will incur an average cost of less than $0.2 million with a maximum of $0.5 million. For facilities owned by large
government entities, EPA estimates an average cost exceeding $0.2 million per facility, with a maximum of $ 1.3
million.178 For small private entity-owned facilities, EPA estimates an average cost of less than $0.2 million per
facility, but still slightly more than that estimated for small government-owned entities, with a maximum of $ 1.4
million. Thus, the costs for small government-owned facilities are less than those owned by large government-
owned facilities and small and large private entity-owned facilities. EPA interprets these findings to indicate that
the final rule will not uniquely or disproportionately affect small governments.
Table 11-5: Compliance Costs to Entities that Own Regulated Electric Generators by Ownership
Type and Size (Millions; $2011)

Number of
Total Annualized
Average Annualized
Maximum Facility

Entity
Facilities
Pre-Tax
Pre-tax Compliance
Annualized Pre-tax
Ownership Type
Size
(weighted)ab
Compliance Costsb
Cost per Facility0
Compliance Costd
Proposal Option 4
Government
Small
16
$2.4
$0.1
$0.5
(excluding federal)
Large
37
$8.5
$0.2
$1.3
Private6
Small
53
$8.5
$0.2
$1.4

Large
423
$183.8
$0.4
$5.0
All Facilities'
544
$219.2
$0.4
$5.0
Final Rule
Government
Small
16
$2.6
$0.2
$0.5
(excluding federal)
Large
37
$8.6
$0.2
$1.3
Private6
Small
53
$8.5
$0.2
$1.4

Large
423
$184.3
$0.4
$5.0
All Facilities'
544
$220.0
$0.4
$5.0
Proposal Option 2
Government
Small
16
$2.6
$0.2
$0.5
(excluding federal)
Large
37
$108.9
$2.9
$16.0
Private6
Small
53
$84.5
$1.6
$11.9

Large
423
$2,783.5
$6.6
$64.2
All Facilities'
544
$3,339.3
$6.1
$64.2
a. Because Table 11-5 reports cost estimates, which are sample-weighted values, facility counts in this table also reflect sample weighting, and
differ from the values reported in Table 11-1 and Table 11—
t, which are un-weighted counts. For details on sample weights see Appendix H.
b. Ten analyzed surveyed DQ and STQ facilities are owned by a joint venture of two entities with equal ownership shares. For reporting total
compliance costs to parent entities, EPA assigned 50 percent of facility costs to each entity that owns this facility.
c. EPA calculated average cost per facility using the total number of regulated facilities owned by entities in a given ownership category.
d. Reflects maximum of unweighted costs to explicitly analyzed facilities only.

e. Facility counts and cost estimates reported for the private sector include facilities owned by rural electric cooperatives.
f. Facility counts and cost estimates reported for All Facilities include facilities owned by the federal government and these facilities" costs.
Source: U.S. EPA analysis for this report

11.3 UMRA: Analysis of Impact on the Private Sector
The final part of the UMRA analysis concerns compliance costs to private entities. For private entities that own
regulated facilities, EPA estimates $1.2 billion as the highest undiscounted pre-tax compliance cost in any single
year will be under the final rule. This value exceeds the inflation-adjusted UMRA impact threshold of $139
178 Excluding federal government entities and regulated facilities they own.
11-6
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 11: UMRA Analysis
million (2011$). In addition, EPA estimates total annualized pre-tax compliance costs to private entities of
approximately $270.1 million under the final rule.
11.4 UMRA: Analysis Summary
Although EPA estimates that the final rule will not result in expenditures of at least $139 million (2011$) for
governments (excluding the federal government), EPA does estimate that the private sector will incur costs
exceeding this value in a single year. Table 11-6 summarizes compliance costs for publicly- and privately-owned
entities, and costs to governments (i.e., NPDES permitting authorities) to administer the final rule.
EPA estimates that governments (excluding federal government) will incur $12.2 million in total annualized
costs: $11.3 million in annualized compliance costs for Electric Generators and $1.0 million in annualized
administrative costs. The maximum one-year cost for governments (excluding federal government) is $72.3
million, in 2019. For the private sector, EPA estimates total annualized costs of $270.1 million, with a maximum
one-year value of $1,145.2 million in 2022.
Table 11-6: Summary of UMRA Costs for Final Rule (Millions; $2011)"
Sector Incurring Costs
Annualized Cost
Maximum
One-Year
Cost
Compliance Costs
Government
Administrative Costs
Total
Government (excluding
federal)
$11.3
$1.0
$12.2
$72.3
Private
$270.1
N/A
$270.1
$1,145.2
a. Cost estimates reported for the private sector include facilities owned by rural electric cooperatives.
Source: U.S. EPA analysis for this report
May 2014
11-7
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
12 Other Administrative Requirements
This chapter presents analyses conducted in support of the final rule to address the requirements of Executive
Orders and Acts applicable to this regulation. These analyses complement EPA's analyses done in accordance
with the Regulatory Flexibility Act (RFA) and Unfunded Mandates Reform Act (UMRA), which were presented
in previous chapters.
12.1 Executive Order 12866: Regulatory Planning and Review and Executive Order
13563: Improving Regulation and Regulatory Review
Under Executive Order 12866 (58 FR 51735, October 4, 1993), EPA must determine whether the regulatory
action is "significant" and therefore subject to review by the Office of Management and Budget (OMB) and to
other requirements of the Executive Order. The order defines a "significant regulatory action" as one that is likely
to result in a regulation that may:
> Have an annual effect on the economy of $100 million or more, or adversely affect in a material way the
economy, a sector of the economy, productivity, competition, jobs, the environment, public health or
safety, or State, local, or Tribal governments or communities; or
> Create a serious inconsistency or otherwise interfere with an action taken or planned by another agency;
or
> Materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and
obligations of recipients thereof; or
> Raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles
set forth in the Executive Order.
Executive Order 13563 (76 FR 3821, January 21, 2011) was issued on January 18, 2011. This Executive Order
supplements Executive Order 12866 by outlining the President's regulatory strategy to support continued
economic growth and job creation, while protecting the safety, health, and rights of all Americans. Executive
Order 13563 requires considering costs, reducing burdens on businesses and consumers, expanding opportunities
for public involvement, designing flexible approaches, ensuring that sound science forms the basis of decisions,
and retrospectively reviewing existing regulations.
Pursuant to the terms of Executive Order 12866, EPA determined that the final rule is an "economically
significant regulatory action" because it is likely to have an annual effect on the economy of $100 million or
more. As such, it is subject to review by the Office of Management and Budget (OMB) under Executive Orders
12866 and 13563. Any changes made in response to OMB suggestions or recommendations will be documented
in the docket for this action.
EPA prepared an analysis of the potential benefits and costs associated with this action; this analysis is described
in Chapter 8: Social Costs and Benefits.
As detailed in earlier chapters of this report, EPA also assessed the impact of the final rule on the wholesale price
of electricity (Chapter 6: Electricity Market Analysis), retail electricity prices by consumer group (Chapter 4:
Economic Impact Analyses: Electric Generators), and on employment or labor markets (Chapter 9: Employment
Effects).
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
12.2 Executive Order 12898: Federal Actions to Address Environmental Justice in
Minority Populations and Low-Income Populations
Executive Order 12898 (59 FR 7629, February 11, 1994) requires that, to the greatest extent practicable and
permitted by law, each federal agency must make the achievement of environmental justice part of its mission.
E.O. 12898 provides that each federal agency must conduct its programs, policies, and activities that substantially
affect human health or the environment, in a manner that ensures such programs, policies, and activities do not
have the effect of (1) excluding persons (including populations) from participation in, or (2) denying persons
(including populations) the benefits of, or (3) subjecting persons (including populations) to discrimination under
such programs, policies, and activities because of their race, color, or national origin.
The final rule and other options considered require that the location, design, construction, and capacity of cooling
water intake structures (CWIS) at regulated facilities reflect the best technology available for minimizing adverse
environmental impact. For several reasons, EPA does not expect that the final rule will have an exclusionary
effect, deny persons the benefits of the participation in a program, or subject persons to discrimination because of
their race, color, or national origin. In fact, because EPA expects that this rule will help to preserve the health of
aquatic ecosystems located in reasonable proximity to regulated facilities, it expects that all populations, including
minority and low-income populations, will benefit from improved environmental conditions as a result of this
rule.
To meet the objectives of Executive Order 12898, EPA examined whether the final rule could distribute benefits
among population sub-groups in a way that is significantly less favorable to low-income and minority
populations. For this analysis, EPA reviewed the profile of populations that would be expected to benefit (the
"benefit populations") from reduced IM&E of aquatic organisms as a result of the final rule and other options
considered. As shown in Table 12-1, the analysis considered the benefit populations associated with 503 regulated
facilities - 346 Electric Generators and 157 Manufacturers - that could potentially implement technology
improvements as a result of the final rule and other options considered.179 The majority of these facilities are
located inland, and in the eastern half of the United States. For this analysis, EPA defined the benefit population
as (1) all individuals who live within a 50-mile radius of the facilities and (2) any additional anglers who live
outside of the 50-mile facility buffer but within a 50-mile radius of the river segments, or river reaches, nearest to
the facilities. Individuals who live within a 50-mile radius of a facility may receive both use (e.g., recreational
fishing or wildlife viewing) and non-use benefits from the improved aquatic ecosystem health of the area (e.g.,
satisfaction from knowing that the overall ecosystem health has improved). Anglers who live within the 50-mile
buffer zone of a reach are likely to fish the affected waterbodies and thus benefit from improved catch rates as a
result of the final rule.180
179 This includes all Electric Generators in the regulatory analysis - both those covered by the detailed questionnaire and those covered by
the less detailed short technical questionnaire - and all Manufacturers facilities covered by the survey of Manufacturers, except for
certain excluded groups of facilities, which are listed in Table 12-1. None of the excluded facilities are expected to install compliance
technology because of the final rule, and thus are excluded from the Environmental Justice analysis. The remaining facilities, which
are included in the Environmental Justice analysis, are those that could be assigned a compliance technology - IM technology or a
closed-cycle recirculating system - under any analyzed option to satisfy the best technology available (BTA) requirement for IM
and/or entrainment standards.
180 According to the US Fish and Wildlife Service, over 65% of anglers travel less than 50 miles one-way on a typical fishing trip (U.S.
DOI, 2006).
12-2
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
Table 12-1: Number of Regulated Facilities Included in the Environmental Justice Analysis for
the Final Rule1

Facility Categories
Electric Generators
Manufacturers
Total number of regulated facilities
656
234
Total number of facilities excluded from analysis:
310
77
- Baseline Closures
124
28
- Facilities with baseline closed-cycle recirculating
systemsb
146
43
- New York facilities with DIF>20mgdc
26
6
- California electric power facilities that use coastal and
14
N/A
estuarine waters for cooling0
Number of regulated facilities included in the
Environmental Justice Analysis
346
157
a. The analysis is based on those facilities in the regulatory analysis whose location is explicitly known. This includes all Electric Generators
facilities and the sample of Manufacturers facilities. Because EPA does not know the location of sample-represented Manufacturers facilities,
these facilities cannot be included in the environment justice analysis, and the facility counts for Manufacturers presented in this table are not
sample-weighted.
b. These counts include 40 Electric Generators and eight Manufacturers with cooling water system impoundments. The cooling water intake
systems for these facilities may qualify as baseline CCRS; these facilities may meet the final rule's performance requirements without needing
to install additional compliance technology.
c. These facilities are subject to State regulations that are at least as stringent as the final rule and the other options considered.
Source: U.S. EPA analysis for this report

For the assessment of the distribution of benefits among population sub-groups, EPA compared on a State-by-
State basis, key demographic characteristics of the sub-State populations that are expected to benefit from the
final rule with those demographic characteristics at the level of the State. If the demographic profile of the sub-
State benefit population was found to be statistically similar to the demographic profile of the State and not
exclusionary of minority and low-income populations specifically, then the final rule would be assessed as not
yielding an unfavorable distribution of benefits, from the perspective of the public policy principles of Executive
Order 12898.
EPA completed the analysis of the socio-economic characteristics of the populations affected by regulated
facilities using the Fish Consumption Pathway (FCP) Module, which reports population estimates by socio-
economic characteristics (U.S. EPA, 2004b).181 The two demographic variables of interest for this environmental
justice analysis are those within the FCP Module that best capture the low-income and minority aspects of the
populations affected, which are:
> Annual household income: less than $25,000 (low-income);182 and
> Race and Ethnicity: white Hispanic, black or African American, Asian or Native Hawaiian or Other
Pacific Islander, and American Indian and Alaska Native.
As described above, EPA assumed that the primary groups that are likely to benefit the most from the final rule
are (1) all individuals who live within a 50-mile radius of the facilities and (2) any additional anglers who live
outside of the 50-mile facility buffer but within a 50-mile radius of the reaches nearest to regulated facilities.183 To
181 The FCP Module is part ofthe Risk-Screening Environmental Indicators (RSEI) Model (U.S. EPA, 2004b).
182 Household data in the FCP Module are available for the following household income categories: less than $10,000; $10,000 to
$19,999; $20,000 to $24,999; $25,000 to $29,999; $30,000 to $34,999; $35,000 to $39,999; $40,000 to $49,999; $50,000 to $74,999;
$75,000 to $99,999; and more than $100,000. For this analysis as well as previous 316(b) rule analyses, EPA combined multiple
categories into a low-income group based on the U.S. Department of Elealth and Eluman Services' poverty guidelines for a family of
four living in the contiguous United States or D.C. The current (2013) poverty guideline is $23,550, which falls near the upper end of
the $20,000 to $24,999 income range (U.S. E1HS, 2013). For the current analysis, EPA used $25,000 as the upper threshold for the
low-income group.
183 Users of the resources receive both use and nonuse benefits from the final rule, while nonusers of the resource receive only nonuse
benefits. Nonusers could potentially include all individuals in a given State or other defined benefit region, which could be larger than
May 2014
12-3
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
assess whether a lower-income or minority group would experience a disproportionately low share of the final
rule's benefits in relation to the general population, the income and race of the affected populations were
calculated in the FCP Module and analyzed statistically, using the following procedures:
> The coordinate locations of each of the regulated sample facilities - Existing Generators and
Manufacturers - were imported into the FCP Module.
> The FCP module estimated the number of individuals residing within 50 miles of each facility.
> The FCP module calculated the number of additional anglers that fish in the affected reaches but that do
not live within a 50-mile radius of the facility on the affected reach. EPA made this calculation by first
estimating the number of anglers within a 50-mile radius of the affected reach and second, subtracting the
number of anglers within 50 miles of the facility that overlap with the 50-mile radius surrounding the
affected reach.
> Areas affected by regulated facilities were spatially defined. They were then superimposed on the FCP
Module's grid, and cell-level population data from Census 2010 were used to define a demographic
profile for the affected populations.
> EPA worked with these data on a State-by-State basis.
> To assess the presence of environmental justice concerns for the final rule and other options considered,
EPA compared the composition of the affected populations' income and race with the demographic
composition of the State population as follows:
¦ Calculating the percentage of individuals in the vicinity of regulated facilities that are low-income
and comparing it to the average percentage of low-income population within each affected State.
¦ Calculating the percentage of individuals in the vicinity of regulated facilities that are a minority and
comparing it to the average percentage of minority population within each affected State.
¦ Testing the statistical significance of any adverse differences in these observed State-by-State
relationships. That is, the differences are only of concern ("adverse") in the context of the
Environmental Justice analysis when a calculated percentage for the benefit population is lower than
the percentage for the general population. In effect, the analysis uses the observed relationships in
individual States as a set of observations for testing the statistical significance of differences across all
States.
If the demographic profiles of the benefit populations and general State populations are not statistically different
and not exclusionary of low-income and minority populations specifically, then the final rule would be assessed
as not yielding an unfavorable distribution of benefits, from the perspective of the public policy principles of
Executive Order 12898.
12.2.1 Presence of Low-Income Populations in the Benefit Population
Facilities in 47 States are expected to install technologies in response to the final rule.184 Table 12-2 reports the
percentage of low-income individuals for the benefit population and the overall State population, by State.
Instances in which the percentage is lower for the benefit population than for the overall State population indicate
a lower rate of participation in the final rule's expected benefits in the low-income population group than in the
general population.
a State. EPA's benefits transfer and stated preference methodologies assign benefits to residents of all States within the affected
region. However, EPA notes that the magnitude of nonuse values may be related to the proximity to the affected resource.
184 Idaho, Nevada, and South Dakota have no facilities that are expected to install compliance technology.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
As reported in Table 12-2 the percentage of low-income individuals in the benefit populations is lower than the
percentage for States' general populations in 34 of the 47 States, but with an average overall difference of only -
0.75 percent and mean difference of -0.35 percent. This indicates that the overall rates of participation in the final
rule's expected benefits in the low-income population groups are similar to the general population. The greatest
negative difference, -4.78 percent, occurs in New York, followed by Montana, at -3.42 percent, and North Dakota,
at 3.14 percent. All other negative differences (31 of the 34 instances of negative difference) are less than 3
percent (as an absolute value). In no State would the low-income population be excluded or denied participation
in the benefits of the final rule - that is, in all States, the ratio is greater than zero for the benefit population.
Although the percentage of low-income individuals in the benefit populations is lower than the percentage for the
general populations in some States, the difference across States may not be statistically significant. The following
paragraphs review the statistical analysis of these observed relationships.
May 2014
12-5
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
Table 12-2: Low-Income Population Participation in Final Rule Benefits by State3

Percentage of Low-Income Individuals
< S25,000/'vear)
States
Affected by Facilities
State Total
Difference (Affected minus State)
Alabama
16.98%
17.22%
-0.24%
Alaska*1
(187%
973%
3^%
Arizona
T8X)0%
T5in%
2.80%
Arkansas
19:05%
TSj'Fu
0.86%
California
TIs9%
T'3.78%
:579o%
Colorado
lO'&%
12.30%
185%
Connecticut
13 70%
'9755%
4.75%
Delaware
1118%
TL21%
5.98%
Florida
TX88%
fjg2%
0.06%
Georgia
T^TFu

-n75%
Hawaiib
8"99%
970%
-0.71%
Illinois
12"83%
12.86%
-0.03%
Indiana
1349%
13:80%
-i7JF7
Iowa
TIi9%
iTIFu
0.41%
Kansas
'l2S2%
12.62%
77]7r7
Kentucky
FJi%
1779%
7:39%
Louisiana
1X97%
T%29%
-0.32%
Maine
TnJi%
1273%
3 (3.r;
Maryland
876%
03%
-i7n7%
Massachusetts
To"65%
T'0.85%
7779%
Michigan
14.67%
14.89%
-0.22%
Minnesota
10:44%
To.80%
-0.36%
Mississippi
19:69%
JOFu
-17(79%
Missouri
1299%
ii7D%
-1.13%
Montana
TT7il%
[4'56%
777i2%
Nebraska
1L69%
TI'20%
-nJF7
New Hampshire
'l0:'60%
7.92%
2.68%
New Jersey
TIfiru
9.25%
152%
New Mexico
T7J9%
1836%
-7757%
New York
9:61%
14.38%
-478%
North Carolina
FT:-:;
Y5J0%
7758%
North Dakota
9:42%
T 2756%
77TF7
Ohio
14:62%
14.41%
FJF7
Oklahoma
1570%
1647%
-0.71%
Oregon
1272%
il7D%
-77F%
Pennsylvania
rrsFu
1273%
-F9F7
Rhode Island
TTTiFu
1153%
-1.46%
South Carolina
16:08%
1(755%
-F:j7%
Tennessee
16:98%
T(7(7i"7
0.37%
Texas
14:80%
7(7:77%
-1797%
Utah
10.20%
10.90%
-0.70%
Vermont
14:06%
777i5%
'2.60%
Virginia
10:09%
'fo.48%
-n39%
Washington
13:68%
1230%
1.38%
West Virginia
1570%
77:72%
-L9F7
Wisconsin
'fL06%
n7w%
-n9l%
Wyoming
837%
To:'oo%
-1.63%
Total
13.24%
13.99%
-0.75%
Mean
13.21%
13.56%
-0.35%
P-valuec
-
-
0.29
a. The "Affected Population" includes all individuals within 50 miles of a regulated facility and any anglers within 50 miles of the reach nearest to
these facilities.

b. Additional angler populations were not counted for Alaska and Hawaii facilities due to lack of RF1 network coverage in those States.
c. A p-value of 0.05 or less would support the hypothesis that the percentage of low-income individuals in areas affected by facilities is statistically
less than the overall low-income percentage in States with facilities, based on a 95-percent confidence interval.
Source: U.S. EPA analysis for this report

12-6
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
To test the statistical significance of these observed State-by-State relationships, EPA compared the percentage of
low-income individuals affected by regulated facilities to the overall percentage of low-income individuals on a
State-by-State basis using a one-tail /-test. This analysis tests whether the mean of the percentages for the affected
populations is lower, in a statistically significant way, than that of the percentages for the States' general
populations. The analysis is based on the following equation:
Where:
t = t-statistic
Xa = Mean percentage of low-income individuals within the affected populations'
sample
Xs = Mean percentage of low-income individuals within the State populations'
sample
sa = Variance of percentages of low-income individuals within the affected
populations' sample
s s = Variance of percentages of low-income individuals within the State populations'
sample
na = Sample size of affected populations
n = Sample size of State populations.
This /-test shows that the percentage of low-income individuals in areas affected by regulated facilities is not
lower, in a statistical significant way, than the overall percentage of low-income individuals based on a p-value,
or observed significance level, of 0.29.185 This finding indicates that lower-income populations are not
significantly underrepresented in the regulation's estimated "benefit population" as compared to the States'
general populations. The final rule thus does not systematically discriminate against, or exclude or deny
participation of, the lower-income population group in a way that would be contrary to the intent of E.O. 12898.
In particular, EPA observes that the lower-income population group is materially present in the benefit population
for all States and the amount by which the lower-income population group is less present relative to the overall
population is very small. Indeed, in these States, the finding that low-income populations are observed to be less
present in the potential benefit population, would mean that this population group has systematically incurred less
damage from the ongoing operation of cooling water intake structures at regulated facilities than the general
population of these States. Finally, because all regulated facilities are subject to the final rule, there can be no
systematic discrimination or exclusion of low-income populations from participation in the final rule's benefits,
based, for example, on selection of only specific facilities to which the final rule would apply.
185 A p-value of 0.05 or less would support the hypothesis that the percentage of low-income to individuals in areas affected by regulated
facilities is significantly different from the overall low-income percentages in states with regulated facilities based on a 95-percent
confidence interval.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
12.2.2 Assessment of Presence of Minority Populations in the Benefit Population
Table 12-3 reports the percentage of individuals in each minority category within areas affected by the regulated
facilities by State. The State with the highest percentage of minorities within areas that are affected by the final
rule is Hawaii, with 75.90 percent, while North Dakota has the lowest at 7.00 percent.
As reported in Table 12-3, minority populations are, on average, more present in the estimated benefit population
than in the States" general populations. On average, the percentage of minority individuals in the benefit
population exceeds the percentage in the general State population by 1.34 percent. Thus, on average, minority
populations would be expected to participate by a somewhat greater extent than States" general populations in the
final rule's benefits. Of the 47 States with regulated facilities, the difference is negative in 20 States (less presence
of minority populations) and is positive in 27 States (greater presence of minority populations). The negative
difference exceeds 10 percent (as an absolute value) in three States - Alaska, New Mexico, and New York.
EPA compared the percentage of minority population in areas affected by regulated facilities with the general
percentage of minority population on a State-by-State basis using, again, a one-tail Mest. EPA performed this
analysis individually for each of the four minority categories and for all four categories as a group. Based on this
/-test, the percentage of minority population in areas affected by regulated facilities is not significantly lower than
the overall percentage of minority population in States with regulated facilities, based on a calculated p-value of
0.33 which is well above the critical value of 0.05.186 P-values for white Hispanic, black or African American,
Asian or Native Hawaiian or Other Pacific Islander, and American Indian and Alaska Native are all well above
the critical value of 0.05 as well. This indicates that the percentages in each minority category are not significantly
lower in areas affected by regulated facilities compared to the State.
12.2.3 Overall Finding
Based on this comparison of socio-economic characteristics of individuals affected by regulated facilities to the
affected States" overall populations, neither the low-income population nor minority populations are significantly
less present in the estimated benefit population than in the States" general populations. As described in the
preceding discussion, EPA"s findings on these questions are slightly stronger for the participation of minority
populations in the rule's benefits than for low-income populations in the rule's benefits. On average, the
percentage of minority individuals within the affected areas is greater than the State (Table 12-3) while the
percentage of low-income individuals within affected areas is less than the State (Table 12-2). However, in both
instances, any findings of lower participation by the low-income population or minority populations are not
statistically significant.
Thus, from this analysis, neither population group participates to a lower extent, in a statistically significant way,
in the benefits of the final rule than the general population in States with regulated facilities. With a p-value of
0.26, Native Americans have the lowest test statistic (greatest statistical significance) among the low-income and
minority groups tested by EPA. However, summary statistics show that on average, the percentage of Native
Americans in affected areas exceeds the percentage of Native Americans in States' general populations,
suggesting that they will share more than proportionally in the benefits of the final rule. EPA judges that the final
rule does not systematically discriminate against, or exclude or deny participation of, the lower-income
population group or minority populations in a way that would be contrary to the intent ofE.O. 12898. EPA thus
concludes, overall, that the final rule is consistent with the policy intent ofE.O. 12898.
180 A p-value of 0.05 or less would support the hypothesis that the percentage of minority individuals in areas affected by regulated
facilities is significantly different from the overall percentage of minority individuals in States with regulated facilities based on a 95-
percent confidence interval.
12-8
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
Table 12-3: Minority Population Participation in the Final Rule Benefits by State3

Ratio of Racial Categories to White, Non-Hispanic Individuals'"

Affected by Facilities
State Total
Difference (=Affected minus State)

White

Native

All
White

Native

All
White

Native

All
States0
Hispanic
Black
American
Asian
Minorities
Hispanic
Black
American
Asian
Minorities
Hispanic
Black
American
Asian
Categories
Alabama
3.86%
22.81%
0.71%
1.33%
28.72%
3.34" 0
26.67" 0
0.71"0
1.29%
32.01%
0.52%
-3.86%
0.00%
0.04".,
-3.29%
Alaska
L90%
636%
Io32%
lo'Fo
fj'9'2%
422%
'378%
13163
31(i'%
7i"33!
3331
3331
3331
'333'%
377F1
Arizona
7243%
149%
2476%
676%
XX7
XX7
'452%
333
'329%
56393
'33131
3331
13131
"137""!
3331
Arkansas
7137
3337%
0.98%
L27%
28^69%
333!
F'JFu
632%
i'3(i'%
2420%
3313
3331
363"""!
"'339%
749""!
California
"34.68%

7.82%
144%
102%
XX7
XX7
388%
1743
1333
58331
3313
33F1
X33!
'428%
_____
737%
Colorado

J.97%

'2.32%
33(5%
Jg'26%
1X95%
33F!
1313
315%
2333
3731.
1331.
ot1%

313"!
Connecticut
7tx:%

loT%
9 26%
4722%
ifiif;
11363
649%
442%
2330%
3131
383%
633%
317%
17331
Delaware
673%
''20.52%
_____
337!
457%
3232%
3317
2336%
638%
'343%
X3F!
6331.
3331
3T31
ilTFl,
F'lFl
Florida
"20.79%

337!
1(4%
FT*?7:;
2Fo6%
3393
649%
3.68%
3333
X3?7
ol'TFl
6313.
"3167%
673"!
Georgia
7.96%
TlTFu
0.55" o
1(3%
7X77
3313
X7F1
633%
'352%
4333
6331.
3313
6331.
133"!
6731,
I Iawaii
'3.22%
164%
_____
639%
X3F1
X317
376%
3.09%
049%
X73'l
7076%
3313
'63(31
3331
3233
313"!
Illinois
"l'2.'70%
___

q36%
FIF!
3161%
1479%
j 5 08;,3
639%
'486%
3333
3331
631%
lolol?".!
3171%
132%
Indiana

7T3F!
o35%
'469%
JX73
7317
'358%
333
1313
1333
(IJFl
5.(3"..
6'4'F!
3131
i7!j3!
Iowa
549%
4.66%
337!
i'79%
XX7
462%
313%
333
1313
1333
oIF'l
1331.
ol'Fl,
71313
33F!
Kan sas
676%
To!56%
133!
138%
XX7
973%
6.33%
131%
313%
3331
3331
'423%
6331
'"3377,
F131
Kentucky
'2.67%
9.84%
7X7
i'49%
XX7
272%
313%
639%
i'3(i%
1333
X6F!
13F!
6313,
'637%
IFF!
Louisiana
4/77%
InxFu
078%
1331
XX7
1(3%
X371
675%
333
38331
1313
3313
63F!
'6317',
71331
Maine
739%
'3.33%
3177
J 86%
1X07%
113%
13r%
638%
333
333
'428%
'3631,
3"131
217%
8331
Maryland
8^91%
"26^63%
7X7
7J9%
7X73
373!
3313
63(3,',
5313
43331
333
3331
63(31
313"!
37F1
Massachusetts
7317
7.87%
'632%
337'!
IlJFu
T.74%
737%
048%
33%
21363
ol'Fl
3731
633"!
3)72%
Iq 57',(1
Michigan
7317
7X37
633H
236%
*X373
189%
fX(3%
672%
333%
21313
6313.
'6333.
3731
"'3"."63%
oil'""!
Minnesota
313!
570%
6.96%
'436'%
XX7
448%
5313
132%
'429%
3363
333%
636%
3331
'616%
6116%
Mississippi
373!
3613%
037%
L37%
40 2!%
J.2F0
37313
638%
63F!
F331
6331
3331
3313
313"!
3731
Missouri
4.0()°..
12.75" o
0.57%
2.07%
19.44° 0
347" 0
1 1.98" 0
0.53"0
1.84%
17,51"..
0.89%
0.77"..
0.04".,
0.23".,
1.94"0
Montana
IIV'u
633!
'5.29%
6"66%
9.86%
333%
33i3
(333
075%
1333
1377
'643%
3331
'"3163!
333!
Nebraska
733%
3131
L27%
L91%
15188%
337!
'487%
132%
333
3313
X7F1
3163
3137
'"3168""!
3137
New Hampshire
777!
'7.29%
043%
642%
Jf'24%
I'F%
138%
638%
339%
11331
3'(i(i%
13)1%
31131
7731,
17931
New Jersey
ITxFu
3X37
6.84%
8"93%
4462%
XX7
333u
639%
333
39331
X3F!
3131.
613%
3T3"!
316%
New Mexico
TFwTl
0.62%
28'Jl%
636%
4442%
X337
335%
1333
1313
33131
-33633.
3331
IFl'Fl
"333"!
37H31
New York
9.89%

3377
3371
287'Fu
XX7
17883
63'8%
396%
311131
X7FI
3313
3331
"333"!
33731
North Carolina
6.84%
37X71
37F!
2J9%
TFrFu
313!
2338%
333
337!
31331
312%
3331
3331
"3167""!
3731
North Dakota
395%
o3I%
3177
63F!
363!
337
137%
3(4%
713!
3331
4x70%
X37!
37F1
'"333"!
3331
Ohio
272%
7X77
7317
L86%
jX/F!
3(3%
1272%
637%
i'79%
13113
6363.
'6119%
6313,
oloF!
63(1%
Oklahoma
'5.98%
907%
X177
L98%
2748%
'378%
333
9313
333!
23431.
3363
1313
o'lFl
'"3163""!
6317,
Oregon
TTiTiTl
2.63%
i'331.'
531%
2078%
13(33
37)4%
333
3313
3331
3131
'639%
3231
713"!
1317,
Pennsylvania
5A7%
74/79%
3317
737!
XX3
773!
1333
6323
333!
3331
6331
'3231.
633"!
1777
77'5""!
Rhode Island
7.44%
9.09%
o34%
3137
X377
337!
348%
631%
'333
21313
13o%
1313
707%
3187%
1367,
South Carolina
'5.29%
3X37
i'36%
L9l'%
JJ'28%
437%
2839%
6.55%
1313
3i33'l
633%
3331
6331
1713"!
631%
T ennessee
425%
"1646%
044%
131%
22.66%
466%
1333
642%
366'%
23131
636%
3331
6313
3337
3331
May 2014
12-9
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
Table 12-3: Minority Population Participation in the Final Rule Benefits by State3
States0
Ratio of Racial Categories to White, Non-Hispanic Individuals'"
Affected by Facilities
State Total
Difference (=Affected minus State)
White
Hispanic
Black
Native
American
Asian
All
Minorities
White
Hispanic
Black
Native
American
Asian
All
Minorities
White
Hispanic
Black
Native
American
Asian
All
Categories
Texas
27.23%
15.68%
1.09%
4.96%
48.95%
36.25" o
12.40%
1.02"o
4.18%
53.85" o
-9.02%
3.27%
0.07%
0.78"o
-4.90%
Utah
12.74%
1.39%
1.03%
3.76%
18.91%
1 1.98" o
1.25%
1.51%
3.12%
17.86%
0.76%
0.14%
-0.48%
0.63"o
1.05%
Vermont
8.92%
5.74%
0.49%
2.13%
17.29%
1.27" o
1.06%
0.38" o
1.35" o
4.07" o
7.65%
4.68%
0.11%
0.78"o
13.22%
Virginia
7.52" o
25.54" o
0.60%
6.12%
39.77%
6.86" o
20.30",,
0.54"o
5.91%
33.61%
0.66" o
5.24" o
0.06"o
0.20" o
6.17%
Washington
14.03%
2.85"o
1.71%
5.53%
24.12%
10.08%
4.00",,
1.92%
8.38" o
24.38%
3.95" o
-1.15%
-0.21%
-2.85" o
-0.27" o
West Virginia
I.I 1%
6.57"o
0.20%
1.13%
9.00%
1.06%
3.57" o
0.22" o
0.73"o
5.58" o
0.04" o
3.00"..
-0.02" o
0.40" o
3.42" o
Wisconsin
6.92"o
6.44" o
0.97" o
2.99%
17.32%
5.36" o
6.62" o
1.09%
2.42" o
15.49%
1.56%
-0.18%
-0.12%
0.57"o
1.83%
Wyoming
8.49%
0.93"o
1.18%
0.78"o
1 1.38" o
8.14"o
0.94" o
2.63"o
0.94"o
12.65%
0.35" o
-0.01%
-1.44%
-0.17" o
-1.27" o
Total
1 1.74" o
15.72" o
0.80" o
5.53"o
33.80%
14.84%
13.36%
1.25%
5.34" o
34.79%
-3.10" <>
2.37" o
-0.45" o
0.19%
-0.99%
Moan
8.83" o
12.1 1%
2.49%
5.02"o
28.45" o
9.27" o
1 1.35" o
1.88%
4.62"o
27.12" o
-0.43" o
0.76" o
0.61%
0.40" o
1.34%
P-valuesd
-
-
-
-
-
-
-
-
-
-
0.40
0.35
0.26
0.42
0.33
a. The "Affected Population" includes all individuals within 50 miles of a regulated facility and any anglers within 50 miles of the reach nearest these facilities.
b. The U.S. Census Bureau (U.S. DOC, 2011) defines ethnic and racial categories as follows: ""Hispanic or Latino" refers to a person of Cuban, Mexican, Puerto Rican, South or Central American, or other
Spanish culture or origin regardless of race." '"White" refers to a person having origins in any of the original peoples of Europe, the Middle East, or North Africa. It includes people who indicated their race(s) as
"White" or reported entries such as Irish, German, Italian, Lebanese, Arab, Moroccan, or Caucasian. 'Black or African American" refers to a person having origins in any of the Black racial groups of Africa. It
includes people who indicated their race (s) as 'Black, African Am., or Negro," or wrote in entries such as African American, Kenyan, Nigerian, or Haitian. 'American Indian and Alaska Native" refers to a
person having origins in any of the original peoples of North and South America (including Central America), and who maintains tribal affiliation or community attachment. This category includes people who
indicated their race (s) as 'American Indian or Alaska Native" or reported their enrolled or principal tribe, such as Navajo, Blackfeet, Inupiat, Yup'ik, or Central American Indian groups or South American
Indian groups. "Asian" refers to a person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent, including, for example, Cambodia, China, Indian, Japan, Korea,
Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. It includes people who indicated their race(s) as 'Asian Indian," "Chinese," "Filipino," "Korean," "Japanese," "Vietnamese," and 'Other Asian" or
provided other detailed Asian responses. 'Native Hawaiian and Other Pacific Islander" refers to a person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands. It includes
people who indicated their race(s) as 'Native Hawaiian," 'Guamanian or Chamorro," "Samoan," or 'Other Pacific Islander" or provided other detailed Pacific Islander rezones. 'Some Other Race" includes all
other responses not included in the White, Black or African American, American Indian or Alaska Naive, Asian and Native Hawaiian or Other Pacific Islander race categories described above. Respondents
reporting entries such as multiracial, mixed, interracial, or Hispanic or Latino group (for example, Mexican, Puerto Rican, Cuban, or Spanish) in response to the race question are included in this category." For
this environmental justice analysis, EPA allocated 'some other race" among the ethnic and racial categories described above.
c. Additional angler populations were not counted for Alaska and Hawaii facilities due to lack of RF1 network coverage in those States.
d. A p-value of 0.05 or less would support the hypothesis that the percentage of each minority category in areas affected by facilities is statistically lower than the overall percentage of each category in States,
with facilities based on a 95% confidence interval.
Source: U.S. EPA analysis for this report
12-10
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
12.3 Executive Order 13045: Protection of Children from Environmental Health Risks
and Safety Risks
Executive Order 13045 (62 FR 19885, April 23, 1997) applies to any rule that (1) is determined to be
"economically significant" as defined under Executive Order 12866 and (2) concerns an environmental health or
safety risk that EPA has reason to believe might have a disproportionate effect on children. If the regulatory
action meets both criteria, the Agency must evaluate the environmental health and safety effects of the planned
rule on children and explain why the planned regulation is preferable to other potentially effective and reasonably
feasible alternatives considered by the Agency. This final rule is an economically significant rule as defined under
Executive Order 12866. However, it does not concern an environmental health or safety risk that would have a
disproportionate effect on children. This regulation establishes requirements for cooling water intake structures to
protect aquatic organisms. Therefore, EPA determined that the final rule is not subject to Executive Order 13045.
12.4 Executive Order 13132: Federalism
Executive Order 13132 (64 FR 43255, August 10, 1999) requires EPA to develop an accountable process to
ensure "meaningful and timely input by State and local officials in the development of regulatory policies that
have federalism implications." "Policies that have federalism implications" are defined in the Executive Order to
include regulations that have "substantial direct effects on the States, on the relationship between the national
government and the States, or on the distribution of power and responsibilities among the various levels of
government."
Under section 6 of Executive Order 13132, EPA may not issue a regulation that has federalism implications, that
imposes substantial direct compliance costs, and that is not required by statute unless the federal government
provides the funds necessary to pay the direct compliance costs incurred by State and local governments or unless
EPA consults with State and local officials early in the process of developing the regulation. EPA also may not
issue a regulation that has federalism implications and that preempts State law, unless the Agency consults with
State and local officials early in the process of developing the regulation.
The final rule does not have federalism implications. It will not have substantial direct effects on the States, on the
relationship between the national government and the States, or on the distribution of power and responsibilities
among the various levels of government, as specified in Executive Order 13132. EPA estimates an average annual
burden of $0.9 million, for States to collectively administer the existing unit provision of the final rule.187 Further,
the final rule will also impose a compliance cost burden on State and local governments on any government
entities that own regulated facilities. EPA identified 48 regulated facilities that are owned by State or local
government entities; the Agency estimated that under the existing unit provision of the final rule these facilities
will incur an average annual compliance cost of approximately $0.2 million per facility.188
The national regulatory requirements will be implemented through permits issued under the NPDES program.
Forty-six States and territories are currently authorized pursuant to section 402(b) of the CWA, to implement the
NPDES program. In States not authorized to implement the NPDES program, EPA issues NPDES permits. Under
the CWA, States are not required to become authorized to administer the NPDES program. Rather, such
authorization is available to States if they operate their programs in a manner consistent with section 402(b) and
applicable regulations. Generally, these provisions require that State NPDES programs include requirements that
187 This estimate does not include costs to administer the new unit provision of the final rule; however, EPA expects these costs to be
small.
188 Cost values were calculated over the 51-year analysis period used for analysis of social costs, discounted and annualized using the 7-
percent discount rate (see Chapters 7 and 11).
May 2014
12-11
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
are as stringent as federal program requirements. States retain the ability to implement requirements that are
broader in scope or more stringent than federal requirements (see Section 510 of the CWA).
EPA does not expect the final rule to have substantial direct effects on either authorized or nonauthorized States
or on local governments because it will not change how EPA and the States and local governments interact or
their respective authority or responsibilities for implementing the NPDES program. This rule establishes national
requirements for existing electric power and manufacturing facilities with cooling water intake structures.
NPDES-authorized States that currently do not comply with the regulations based on this rule might need to
amend their regulations or statutes to ensure that their NPDES programs are consistent with federal section 316(b)
requirements. (See 40 CFR 123.62(e).) For purposes of this rule, the relationship and distribution of power and
responsibilities between the federal government and the State and local governments are established under the
CWA (e.g., sections 402(b) and 510); nothing in this rule alters that. Thus, the requirements of section 6 of the
Executive Order do not apply to this rule.
12.5 Executive Order 13158: 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 States, the majority of coastal waters are found
within MPAs (e.g., Massachusetts, Hawaii).The ecological importance of MPAs varies widely because of their
broad focus on the preservation and maintenance of cultural and natural resources, and/or sustainable production
(NMPAC, 2006). Consequently, evaluating the impact of CWISs on 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 structures,
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 MPAs within the National Estuary Program (NEP). The NEP was established in
the 1987 amendments to the Clean Water Act (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 estuaries is in the national interest" (Water Quality Act of 1987, 1987). In addition to
the 28 estuaries designated under the NEP (U.S. EPA, 2010d), EPA included facilities found in Chesapeake Bay
(itself 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 estuaries. 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 (U.S. EPA, 2014c). Between fiscal years 1995 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 likely to increase restoration efforts in the future (Executive Order No. 13508, 2009). All told, these
expenditures reflect high public values for restoring (or protecting) the biological integrity of these ecosystems.
A total of 44 regulated facilities are located on 32 waterbodies within MPAs designed to preserve natural
resources and/or to ensure sustainable production (NOAA, 2012; Table 12-4). Although these facilities are found
in fresh, brackish, and marine waters, the vast majority of facilities located within MPAs are in coastal waters and
are most highly concentrated in the Northeastern U.S. (i.e., both coastal and inland facilities) (Figure 12-1; Table
12-4). 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 (IM). This estimate is based
12-12
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
upon facilities for which sufficient 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-specific determination of entrainment BTA for
facilities with CWIS inside of MPAs.

Facilities with CWIS
O Coastal
A Inland
Regions
V'jp'A California Region
\'///.\ Great Lakes Region
/\ Gulf of Mexico Region
| Inland Region
Mid-Atlantic Region
J North Atlantic Region
3] South Atlantic Region
Figure 12-1: Regulated Facilities with CWISs Located in Marine Protected Areas
Source: NOAA, 2012; U,S. EPA analysis for this report
May 2014
12-13
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
Table 12-4: 316(b) Facilities in Marine Protected Areas, and Improvements in IM&E Technologies for the
Final Rule and Other Options Considered

Number of Facilities with Improved Technologies by Optiona'b
Baseline

Proposal Option 4
Final Rule
Proposal Option 2
Affected
Regulated
Facilities With
Benefits Region
IM
E
IM
E
IM
E
Waterbodies
Facilities
Tech Datab
Calrfornra
1
0
1
0
1
1
2
2
1
North Atlantrc
2
0
2
0
2
2
7
6
6
Mrd-Atlantrc
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 estimate current compliance with the final rule.
Source: U.S. EPA analysis for this report
12.6 Executive Order 13175: Consultation and Coordination with Indian Tribal
Governments
Executive Order 13175 (65 FR 67249, November 6, 2000) requires EPA to develop an accountable process to
ensure "meaningful and timely input by tribal officials in the development of regulatory policies that have tribal
implications." "Policies that have tribal implications" is defined in the Executive Order to include regulations that
have "substantial direct effects on one or more Indian Tribes, on the relationship between the federal government
and the Indian Tribes, or on the distribution of power and responsibilities between the federal government and
Indian Tribes."
The final rule does not have tribal implications. It will not have substantial direct effects on tribal governments,
on the relationship between the federal government and Indian Tribes, or on the distribution of power and
responsibilities between the federal government and Indian Tribes, as specified in Executive Order 13175. The
national cooling water intake structure requirements would be implemented through permits issued under the
NPDES program. No tribal governments are currently authorized pursuant to section 402(b) of the CWA to
implement the NPDES program. In addition, EPA's analyses show that no facility subject to the final rule is
owned by tribal governments and thus this regulation does not affect Tribes in any way in the foreseeable future.
Consequently, Executive Order 13175 does not apply to this regulation.
12.7 Executive Order 13211: Actions Concerning Regulations That Significantly Affect
Energy Supply, Distribution, or Use - Statement of Energy Effects
L.O. 13211 (66 I R 2S355, Ma\ 22, 2UU1) requires LPA lo prepare and submit a Slulemenl oi'Lnerg) UVecLs Lo
the Administrator of the Office of Information and Regulatory Affairs, Office of Management and Budget, for
actions identified as Significant Energy Actions. Subsequent to issuance of E.O. 13211, OMB prepared an
implementation memorandum for E.O. 13211 outlining specific criteria for assessing whether a regulation
constitutes a "significant energy action" and for which a Statement of Energy Effects would thus be required.189
These criteria include:
> Reductions in crude oil supply in excess of 10,000 barrels per day;
> Reductions in fuel production in excess of 4,000 barrels per day;
> Reductions in coal production in excess of 5 million tons per year;
189 Executive Order 13211 was issued May 18, 2001. The Office of Management and Budget later released an Implementation Guidance
memorandum on July 13,2002.
12-14
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
> Reductions in natural gas production in excess of 25 million Mcf per year;19"
> Reductions in electricity production in excess of 1 billion kilowatt-hours (kWh) per year, or in excess of
500 megawatts (MW) of installed capacity;
> Increases in the cost of energy production in excess of 1 percent;
> Increases in the cost of energy distribution in excess of 1 percent;
> Significant increases in dependence on foreign supplies of energy; or
> Having other similar adverse outcomes, particularly unintended ones.
Of the potential significant adverse effects on the supply, distribution, or use of energy (listed above), only five
potentially apply to the final rule. Through increases in the cost of generating electricity and shifts in the types of
generators employed, the final rule might affect (1) the production of electricity, (2) the amount of installed
capacity, (3) the cost of energy production, (4) the dependence on foreign supplies of energy, and (5) the
production of coal.
The Agency assessed the energy effects of the final rule for these five impact effects. For this assessment, EPA
relied on Integrated Planning Model (IPM) analyses undertaken by EPA for the final rule and as documented
previously in Chapter 6.191 From this analysis, EPA finds that the compliance requirements of the final rule may
affect the electric power sector in a way - specifically as pertains to impact on electric generating capacity - that
would constitute a significant adverse effect under E.O. 13211, and thus includes this Statement of Energy Effects
in the economic analysis. EPA presents its findings for each of these of these five effects in the following
sections.
12.7.1 Impact on Electricity Generation
Based on the electricity market analysis results, EPA found that final rule will not reduce electricity production by
more than 1 billion kWh hours per year. EPA estimated that under the final rule, the electric power sector, in the
aggregate, would generate 18,861,736 kWh less electricity in 2030 (the steady-state post-compliance year). This
is significantly less than the 1 billion kWh reduction required for the regulation to be considered a "significant
energy action." EPA recognizes that generation from regulated facilities may be reduced more substantially;
however, this reduction would be offset by increased production from other electric power facilities, resulting in
no significant effect on overall production. From this assessment, EPA judges that the final rule will not constitute
a significant energy action and will not cause a significant adverse effect based on the criterion of reduced
electricity generation.
12.7.2 Impact on Electric Generating Capacity
As documented in Chapter 6, EPA's electricity market analysis estimated that by 2030 the final rule will result in
net retirement of 998 MW of generating capacity, which exceeds the threshold of 500 MW of installed capacity
identified in the OMB guidance as an indicator of significant adverse effect. Specifically, the final rule will lead to
early retirement of 23 generating units accounting for 4,090 MW of capacity. These retirements are offset by
3,092 MW of avoided retirement of capacity otherwise projected to retire by 2030, resulting in net retirement of
998 MW of generating capacity. With only one exception, these retirements involve older, less efficient
generating units with very low capacity utilization rates. Specifically, for 15 of the 23 projected unit retirements,
projected capacity utilization in 2030, absent the final ride, is zero; while for seven units, capacity utilization is
190 Mcf is a measure of volume of natural gas. One Mcf equals one thousand (1,000) cubic feet of natural gas.
191 As described in Chapter 6, for this analysis EPA assumed that none of the facilities with cooling water system impoundments would
qualify as baseline CCRS and thus assigned compliance technology, where applicable, to these facilities.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
projected to be less than 15 percent. The 998 MW of net retired capacity is replaced by 589 MW of new capacity;
because older and less efficient capacity is replaced by new, more energy-efficient, and less polluting capacity,
these retirements simply mean that 409 MW less capacity is needed to fulfill the same demand.192
Because the final rule could lead to a net loss of more than 500 MW of installed generating capacity, EPA finds
that the final rule would constitute a significant energy action and may cause a significant adverse effect based on
the criterion of reduced electric generating capacity. Despite this finding, EPA notes, however, that the impact of
lost electric generating capacity is comparatively minor because of the projected low capacity utilization and
associated low electricity supply contribution from those electric generating units that are projected to retire.
12.7.3 Impact on Cost of Energy Production
Based on the IPM analysis results, EPA estimated that the final rule will not significantly affect the cost of
electricity production in either the short run or the long run. EPA estimates that in the short run (2020), energy
production costs (variable costs per MWh) will increase only slightly, by 0.2 percent and that in the long run
(2030), the change is essentially zero. EPA estimated that in the short run, electricity prices will increase in all
NERC regions; however, the magnitude of that increase is generally small, ranging from 0.3 percent to 0.9
percent, with seven out of eight NERC regions recording an increase of no more than 0.6 percent. In the long run,
the final rule will have only a slight impact on electricity prices, with three out of eight NERC regions recording a
slight decline not exceeding 0.1 percent and the remaining five NERC regions recording slight prices increases
not exceeding 0.4 percent.
From this assessment, EPA concludes that the final rule will not constitute a "significant energy action" and
would not cause a "significant adverse effect" based on the criterion of increased cost of energy production.
12.7.4 Dependence on Foreign Supply of Energy
EPA's electricity market analysis did not explicitly consider the effects of the final rule on foreign imports of
energy. However, the final rule will only affect U.S. electric power generators, which are generally not subject to
significant foreign competition. Only Canada and Mexico are connected to the U.S. electricity grid, and
transmission losses are substantial when electricity is transmitted over long distances. In addition, the effects on
installed capacity and electricity prices are estimated to be small.
As presented in Table 12-5, under the final rule, based on the IPM analysis results, coal-based electricity
generation, and therefore, coal consumption by electric power facilities are expected to decline very slightly - less
than 0.1 percent. Generation using biomass and hydro power is also expected to decline slightly by less than 0.1
percent, with oil-based electricity generation declining by less than 2 percent. Generation using other fuels -
natural gas, nuclear power, and wind power - and consequently, consumption of those fuels, are expected to
increase, however modestly. These changes are inconsequential and are essentially within the analytic "noise" of
the electricity market analysis system.
Given such small increases in usage of natural gas and, nuclear power, and wind power, it is reasonable to assume
that the increase in demand for these fuels will be met through domestic supply, thereby not increasing U.S.
192 EPA does not consider the loss of capacity to technology-installation downtime to fall within the scope of E.O. 13211 because this
loss is temporary. However, even if it did, it would be of low consequence. Based on the IPM analysis results reported for 2020, i.e.,
the year that represents technology-installation period, during that period, the final rule will result in approximately 902 MW total
capacity losses, including the net increase in retired capacity and the increase in new capacity. As described in Chapter 6, the
downtime capacity loss at any individual facility due to the final rule is for a substantially shorter duration than a full year.
Specifically, 208 Electric Generators modeled in IPM are estimated to incur net downtime, ranging from 0.3 to nine weeks, with 192
facilities incurring only 0.3 weeks of downtime and only three facilities incurring nine weeks of downtime. Further, these capacity
losses can be spread over facilities in such way that the impact at any time is less than the sum of downtime capacity reductions across
the affected facilities.
12-16
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
dependence on foreign supply of any of these fuels. Therefore, EPA concludes that the final rule will not increase
dependence on foreign supply of energy.
Table 12-5: Total Market-Level Capacity, Generation, and Fuel Use by Fuel Type3

Generating Capacity (MW)
Electricity Generation (GWh)
Fuel Consumption (TBtu)
Fuel Type
Baseline
Final
Rule
Diff
%
Change
Baseline
Final Rule
Diff
%
Change
Baseline
Final
Rule
Diff
% Change
Biomass
7.313
7.311
-2
0.0%
52.073
52.067
-6
0.0%
574
574
0
0.0%
Coal
301.207
301.137
-70
0.0%
2.043.801
2.042.848
-953
0.0%
20.999
20.987
-12
-0.1%
Fossil Wasteb
872
872
0
0.0%
2.062
2.062
0
0.0%
18
18
0
0.0%
Geothermal
3.466
3.466
0
0.0%
23.961
23.961
0
0.0%
585
585
0
0.0%
Hydro
98.816
98.816
0
0.0%
286.396
286.366
-30
0.0%
0
0
0
NA
Landfill Gas
4.505
4.505
0
0.0%
32.636
32.636
0
0.0%
445
445
0
0.0%
MSW
2.133
2.133
0
0.0%
14.392
14.392
0
0.0%
228
228
0
0.0%
Natural Gas
476.869
476.210
-659
-0.1%
1.191.096
1.191.980
884
0.1%
8.730
8.733
3
0.0%
Non-Fossil
1.026
1.026
0
0.0%
5.852
5.852
0
0.0%
55
55
0
0.0%
Nuclear
103.155
103.155
0
0.0%
819.308
819.375
67
0.0%
8.592
8.593
1
0.0%
Oil
37.841
38.144
303
0.8%
179
175
-3
-1.9%
2
*)
0
-2.1%
I'd Coke
2.677
2.677
0
0.0%
18.980
18.980
0
0.0%
187
187
0
0.0%
Solar
1.332
1.332
0
0.0%
2.733
2.733
0
0.0%
0
0
0
NA
\\ aste Coal
2.120
2.120
0
0.0%
15.612
15.612
0
0.0%
165
165
0
0.0%
Wind
62.779
62.800
22
0.0%
192.838
192.898
59
0.0%
0
0
0
NA
Total
1,106,110
1,105,704
-406
0.0%
4,701,917
4,701,936
19
0.0%
40,580
40,572
-8
0.0%
a. Numbers may not add to reported totals due to rounding.
b. Includes 250 MW of imported capacity and 894 GWli of imported electricity from Canada and Mexico.
Source: U.S. EPA analysis for this report
12.7.5 Impact on Coal Production
EPA's electricity market analysis did not explicitly consider the effects of the final rule on U.S. coal production.
However, given the very small reduction in coal-based electricity generation and therefore, reduction in coal
consumption of less than 0.1 percent (see Table 12-5), it is reasonable to assume that the reduction in demand for
coal will not have a consequential impact on coal production. Therefore, EPA concludes that the final rule will
not significantly affect domestic coal production.
12.7.6 Overall E.O. 13211 Finding
From these analyses, EPA finds that the final rule is a significant energy action and may have a significant
adverse effect on the supply, distribution, or use of energy at a national or regional level in accordance with the
criteria published by OMB for implementing E.O. 13211. As described above, EPA reached this finding based on
the projected net loss of 998 MW of electric generating capacity, which exceeds the OMB criterion of reduction
in excess of 500 MW in installed capacity for establishing a significant adverse effect. As stated above, EPA
views the projected loss of capacity as comparatively minor because of the projected low capacity utilization and
associated low electricity supply contribution from those electric generating units that are projected to retire. As a
result, EPA prepared this Statement of Energy Effects. For more information on the effects of the final rule on
electricity markets, see Chapter 6.
12.8 Paperwork Reduction Act of 1995
The Paperwork Reduction Act of 1995 (PRA) (superseding the PRA of 1980) is implemented by the Office of
Management and Budget (OMB) and requires that agencies submit a supporting statement to OMB for any
information collection that solicits the same data from more than nine parties. The PRA seeks to ensure that
federal agencies balance their need to collect information with the paperwork burden imposed on the public by the
collection.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Chapter 12: Other Administrative Requirements
The definition of "information collection" includes activities required by regulations, such as permit development,
monitoring, record keeping, and reporting. The term "burden" refers to the "time, effort, or financial resources"
the public expends to provide information to or for a federal agency, or to otherwise fulfill statutory or regulatory
requirements. PRA paperwork burden is measured in terms of annual time and financial resources the public
devotes to meet one-time and recurring information requests (44 U.S.C. 3502(2); 5 C.F.R. 1320.3(b)).
Information collection activities may include:
> reviewing instructions;
> using technology to collect, process, and disclose information;
> adjusting existing practices to comply with requirements;
> searching data sources;
> completing and reviewing the response;
> and transmitting or disclosing information.
Agencies must provide information to OMB on the parties affected, the annual reporting burden, and the
annualized cost of responding to the information collection, and whether the request significantly impacts a
substantial number of small entities. An agency may not conduct or sponsor, and a person is not required to
respond to, an information collection unless it displays a currently valid OMB control number. The Office of
Management and Budget (OMB) has approved the information collection requirements contained in this rule
under the provisions of the Paperwork Reduction Act, 44 U.S.C. 3501 et seq. and has assigned OMB control
number 2060-05. The final rule requires applicable facilities to perform several data-gathering activities as part of
the permit application process. The information collection requirements include a one-time burden associated
with the initial permit application and those activities associated with monitoring and reporting after the permit is
issued. EPA estimates a total average annual burden of 634,596 hours for the final rule's information collection
requirements. EPA estimates an annual average reporting and record-keeping burden to facilities responding to
the final rule of 588 hours per respondent (i.e., annual average of 627,666 hours of burden divided among an
anticipated annual average of 1,068 facilities).193 EPA estimates a reporting and record-keeping burden to Permit
Directors, for the review, oversight, and administration of the rule, of 147 hours per respondent (i.e., an annual
average of 6,930 hours of burden divided among anticipated 46 States and one territory with NPDES permitting
authority on average per year).
12.9 National Technology Transfer and Advancement Act
Section 12(d) of the National Technology Transfer and Advancement Act (NTTAA) of 1995, Pub L. No. 104-113,
Sec. 12(d) directs EPA to use voluntary consensus standards in its regulatory activities unless doing so would be
inconsistent with applicable law or otherwise impractical. Voluntary consensus standards are technical standards
(e.g., materials specifications, test methods, sampling procedures, and business practices) that are developed or
adopted by voluntary consensus standard bodies. The NTTAA directs EPA to provide Congress, through OMB,
explanations when the Agency decides not to use available and applicable voluntary consensus standards. This
final rule does not involve such technical standards. Therefore, EPA is not considering the use of any voluntary
consensus standards.
193 The 1,068 figure differs from the total regulated universe of 1,065 facilities and reflects different numbers of Electric Generators and
Manufacturers undertaking activities related to information collection request (ICR) in each of the three years covered by this ICR.
12-18
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
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Appendix A: Aluminum Industry Profile
Appendix A Profile of the Aluminum Industry
A.1 Introduction
EPA's Detailed Industry Questionnaire, hereafter referred to as the DQ, identified two 3-digit SIC codes in the
Nonferrous Metals manufacturing industry (SIC codes 333/335) with at least one existing facility that operates a
cooling water intake structure (CWIS), holds a NPDES permit, withdraws at least two million gallons per day
(mgd) from a water of the United States, and uses at least 25 percent of its intake flow for cooling purposes
(facilities with these characteristics are hereafter referred to as "facilities potentially subject to the Final Existing
Facilities regulation" or "regulated facilities"). For the purpose of this analysis, EPA identified a six-digit NAICS
code for each of these potential facilities using information from the DQ and public sources (see Appendix J:
Mapping Manu facturers Standard Industrial Classification (SIC) Codes to North American Industry
Classification System (NAICS) Codes). As the result of this mapping, EPA identified four 6-digit NAICS codes in
the Nonferrous Metals manufacturing industry (NAICS 331311-5).
For these four NAICS codes, Table A-l, below, provides a description of the industry segment, a list of primary
products manufactured, and the number of facilities estimated to be potentially subject to the 316(b) Existing
Facilities regulation based on the minimum withdrawal threshold of two mgd.
Table A-1: Existing Facilities in the Aluminum Industry (NAICS 33131)
NAICS
Code
NAICS Description
Important Products Manufactured
Number of
Regulated
Facilities3
Primary Stages of Production (Primary Aluminum)
331311
Alumina refining
Refining alumina (i.e. aluminum oxide) generally from bauxite.
6
331312
Primary aluminum
production
Aluminum from alumina and/or aluminum from alumina and rolling, drawing,
extruding, or casting the aluminum they make into primary forms (i.e. bar,
billet, ingot, plate, rod, sheet, strip).
7
Secondary Stages of Production (Secondary Aluminum)
331314
Secondary smelting and
alloying of aluminum
Recovered aluminum and aluminum alloys from scrap and/or dross (i.e.
secondary smelting) and billet or ingot (except by rolling); manufactured alloys,
powder, paste, or flake from purchased aluminum.
3
331315
Aluminum sheet, plate,
and foil manufacturing
Flat-rolling or continuous casting sheet, plate, foil, and welded tube from
purchased aluminum; recovered aluminum from scrap.
9
Total NAICS 331311 -5b
26
a. Number of weighted detailed questionnaire survey respondents.
b. Individual numbers may not add up due to independent rounding.
Source: Executive Office of the President, 1987; U.S. EPA 2000; U.S. EPA analysis for this report
As shown in Table A-l, EPA estimates that, out of an estimated total of 88194 facilities with a NPDES permit and
operating cooling water intake structures in the Aluminum Industry (NAICS 331311-5), 25 facilities (or 28
percent) are estimated to be subject to the final rule. EPA also estimated the percentage of total production that
occurs at facilities estimated to be subject to the final rule and other options EPA considered. The total value of
shipments forthe profiled Aluminum Industry (NAICS 3313) from the 2010 Annual Survey of Manufactures is
$33.0 billion ($2011). Value of shipments, a measure of the dollar value of production, was selected forthe basis
of this estimate. Because value of shipments data were not collected using the DQ, these data were not available
forthe sample of manufacturing facilities potentially subject to the regulatory analysis. Total revenue, as reported
on the DQ, was used as a close approximation for value of shipments for these facilities. EPA estimates the total
194 This estimate of the number of facilities holding a NPDES permit and operating a cooling water intake structure is based on the
responses from facilities that received the 1999 screener questionnaire.
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Appendix A: Aluminum Industry Profile
revenue of facilities in the Aluminum Industry subject to the final rule is $15.1 billion ($2011).195 Therefore, EPA
estimates that 46 percent of total domestic aluminum production occurs at facilities estimated to be subject to the
final regulation.
Table A-2 provides the crosswalk between NAICS codes and SIC codes for the profiled Aluminum NAICS codes.
The table shows that of the profiled 6-digit NAICS codes in the Aluminum Industry, alumina refining (NAICS
331311), primary aluminum production (NAICS 331312), and aluminum sheet, plate, and foil manufacturing
(NAICS 331315) have a one-to-one relationship to SIC codes. Secondary smelting and alloying of aluminum
(NAICS 331314) represents two SIC codes: secondary nonferrous metals (3341) and primary metal products
(3399).
Table A-2: Relationships between NAICS and SIC Codes for the Aluminum Industry
NAICS
Code
NAICS Description
SIC
Code
SIC Description
Number of
Establishments
(2009)a
Value of
Shipments
(2010;
Millions;
$2011)
Employment
(2010)
331311
Alumina refining
2819
Industrial inorganic chemicals
15
$1,037
1,497
331312
Primary aluminum
production
3334
Primary aluminum
65
$4,739
6,648
331314
Secondary smelting and
alloying of aluminum
3341
Secondary nonferrous metals
133
$5,197
4,460
3399
Primary metal products, n.e.c.
331315
Aluminum sheet, plate, and
foil manufacturing
3353
Aluminum sheet, plate, and
foil
113
$14,627
16,099
a. Hie number of establishments relies on data from the 2009 Statistics of U.S. Businesses. Value of Shipments and Employment reflect 2010 data.
Source: U.S. DOC, 2010 ASM; U.S. DOC, 2009 SUSB
A.2 Summary Insights from this Profile
The key purpose of this profile is to provide insight into the ability of Aluminum Industry firms to absorb
compliance costs under the final rule without material adverse economic/financial effects. The industry's ability
to absorb compliance costs is primarily influenced by two factors: (1) the extent to which the industry can shift
compliance costs to its customers through price increases, and (2) the financial health of the industry and its
general business outlook.
A.2.1 Likely Ability to Pass Compliance Costs Through to Customers
As reported in the following sections of this profile, the Aluminum Industry on average has a moderate-to-high
degree of market concentration, with the profiled Primary Aluminum production segment being slightly more
concentrated than the profiled Secondary Aluminum Production segment. This potentially supports the notion that
firms in the Primary Aluminum production segment may be able to pass some portion of their compliance-related
costs through to consumers while firms in the Secondary Aluminum production segment may not. However, the
domestic Primary Aluminum production segment faces significant competition from imports into the U.S. market,
which has increased overtime and is likely to continue doing so going forward. Substantial competitive pressure
from abroad weakens the potential of firms in the Primary Aluminum production segment to pass through to
customers a significant portion of their compliance-related costs. The Secondary Aluminum production segment
does not appear to be reliant on sales into foreign markets, nor does it seem to face significant competition from
imports. As discussed above, given the relatively large proportion of total value of shipments in the profiled
Aluminum Industry (nearly 50 percent), in addition to the moderate-to-high degree of concentration in the
profiled Aluminum Industry, and strong competitive pressures from abroad existing only in the Primary
195 To compare revenue values of regulated facilities with the industry value of shipments, EPA brought revenue values for regulated
facilities forward to 2010 using industry-specific Producer Price Index (PPI) values published by the Bureau of Labor Statistics (BLS)
and stated in 2011 dollars using GDP deflator published by the Bureau of Economic Analysis (BEA).
A-2
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Appendix A: Aluminum Industry Profile
Aluminum segment, EPA judges that regulated facilities in the profiled Aluminum Industry subject to the 316(b)
Existing Facilities Regulation may have the potential to recover compliance costs through price increases to
customers. However, in an effort to avoid overstating the ability of regulated facilities to pass on compliance costs
to consumers, EPA assumes zero cost pass through. In other words, EPA judges that facilities would have to
absorb all compliance costs within their operating finances (see following sections and Appendix K: Cost Pass-
Through Analysis, for further information).
A.2.2 Financial Health and General Business Outlook
Over the last two decades, the Aluminum Industry, like other U.S. manufacturing industries, has experienced a
range of economic/financial conditions, including substantial challenges. In the early 1990s, the domestic
Aluminum Industry was adversely affected by reduced U.S. demand and the dissolution of the Soviet Union,
which resulted in substantially increased Russian aluminum exports. Although domestic market conditions
improved by middle of that decade, weakness in Asian markets, along with growing Russian exports, dampened
performance during the latter half of the 1990s. Demand for Aluminum Industry products declined again during
2000 through 2002, reflecting recessionary weakness in both the U.S. and world economies, and again resulted in
oversupply of aluminum and declining financial performance of facilities in the Aluminum Industry. As the U.S.
economy began to show signs of recovery in 2003, so did the overall Aluminum Industry with higher demand
levels and improved financial performance over the course of 2004 and 2006. Despite increasing costs of energy
and other aluminum production inputs, which led to lower aluminum production levels and higher aluminum
prices during that time, demand for aluminum grew; increasing prices of steel and copper compared to aluminum
led to aluminum substitution in the manufacturing of certain goods like cable, beverage cans, and automobile
parts (USGS, 2006c). Higher demand for aluminum also led to smelter restarts and substantial increases in
primary aluminum production throughout 2007 and the first half of 2008. The recent recession, however, resulted
in lower demand for aluminum, leading to significantly lower aluminum prices and consequent production cuts by
aluminum smelters. By June 2009, 54 percent of domestic production smelting capacity was idle (USGS, 2008a).
Moreover, relatively high electricity rates in the United States compared to those in other nations diminishes the
likelihood that domestic smelters will reopen in the near term (USGS, 2008a). In 2011, production of primary and
secondary aluminum rose, after declines in 2008 and 2009, although production has not yet returned to pre-
recession levels. While the United States is still somewhat reliant on imports, in 2011 the rise in exports outpaced
the increase in imports. Furthermore, domestic smelters increased operations to approximately 64 percent of rated
or engineered capacity, after having fallen to 49 percent in 2009 (USGS, 2010c; USGS, 2012c). As the Aluminum
Industry continues to recover, the industry should be able to absorb additional regulatory compliance costs
without a material financial impact.
A.3 Domestic Production
The Primary stages of aluminum production involve mining bauxite ore and refining it into alumina, one of the
feedstocks for aluminum metal. Direct electric current is used to split the alumina into molten aluminum metal
and carbon dioxide. The molten aluminum metal is then collected and cast into ingots. Technological
improvements over the years have improved the efficiency of aluminum smelting, with a particular emphasis on
reducing energy requirements. Currently, no commercially viable alternative exists to the electrometallurgical
process (Aluminum Association, 2001).
Secondary stages of aluminum production involve recovering aluminum and aluminum alloys from scrap and/or
dross, making billet and ingot, and manufacturing of alloys, powder, paste, of flake from purchased aluminum. In
2009, aluminum recovered from purchased scrap was about three million tons, of which about 60 percent came
from new (manufacturing) scrap and 40 percent from old scrap (discarded aluminum products). Aluminum
recovered from old scrap was equivalent to about 35 percent of apparent consumption (USGS, 2010c).
Reclamation of used aluminum beverage cans continues to be a major source of supply for the U.S. aluminum
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
industry, generating large savings in production energy costs (USGS, 2009c). In contrast to the steel industry,
aluminum minimills have had limited impact on the profitability of traditional integrated aluminum producers.
Aluminum minimills are not able to produce can sheet of the same quality as that produced by integrated
facilities. As a result, they are able to compete only in production of commodity sheet products for the building
and distributor markets, which are considered mature markets.
In addition, the Secondary stages of aluminum production include manufacturing of semi-fabricated aluminum
products. Examples of semi-fabricated aluminum products include (Aluminum Association, undated):
> sheet (cans, construction materials, and automotive parts);
> plate (aircraft and spacecraft fuel tanks);
> foil (household aluminum foil, building insulation, and automotive parts);
> rod, bar, and wire (electrical transmission lines); and
> extrusions (storm windows, bridge structures, and automotive parts).
U.S. aluminum companies are generally vertically integrated. Major aluminum companies own large bauxite
reserves, mine bauxite ore and refine it into alumina, produce aluminum ingot, and operate the rolling mills and
finishing facilities used to produce semi-fabricated aluminum products. As noted above, the Primary stages of
aluminum production involves the electrometallurgical process, which is extremely energy intensive. Electricity
accounts for approximately 30 percent of total production costs for primary aluminum smelting. The industry is
therefore a major industrial user of electricity, spending more than two billion dollars annually. Throughout the
years aluminum facilities have been pursuing opportunities to reduce their use of electricity as a means of
lowering costs. Consequently, in the last 50 years, the average amount of electricity needed to make a pound of
aluminum has declined from 12 kilowatt hours to approximately 7 kilowatt hours (Aluminum Association,
undated).
A.3.1 Output
At the end of the last decade, the transportation sector was the largest North American market for aluminum,
accounting for 6 billion pounds, or 28 percent of total consumption. Other major markets included: containers and
packaging (22 percent); building and construction (28 percent); electrical (7 percent); machinery and equipment
(7 percent); and consumer durables (6 percent) (Aluminum Association, 2009).
Demand for aluminum reflects the overall state of domestic and world economies, as well as long-term trends in
aluminum products use in major end-use sectors. Because aluminum production involves large fixed investments
and capacity adapts slowly to fluctuations in demand, the industry has experienced alternating periods of excess
capacity and tight supplies. The early 1980s was a period of oversupply, high inventories, and excess capacity. By
1986, excess capacity was closed, inventories were low, and demand increased substantially. The early 1990s
were affected by reduced U.S. demand and the dissolution of the Soviet Union, resulting in large increases in
Russian exports of aluminum. By the mid-1990s, global production declined, demand rebounded, and aluminum
prices rose. Subsequent increased production reflected an overall increase in the demand for aluminum with
stronger domestic economic growth, driven by increased consumption by the transportation, container, and
construction segments. The economic crises in Asian markets in the later 1990s, along with growing Russian
exports, again resulted in a period of oversupply, although U.S. demand for aluminum remained strong.
Demand declined again in 2000 through 2002 due to slower growth in both the domestic and world economies,
resulting in oversupply. In addition, production in China increased during this period, and although increased
Chinese consumption helped reduce the surplus slightly, the country switched from being a net importer to a net
exporter. The U.S. aluminum surplus was mitigated somewhat as demand in the automotive and housing markets
remained relatively high through mid-2003. In addition, the California energy crisis in 2000 and 2001 reduced
production from primary smelters located in the Pacific Northwest (Aluminum Association, 1999; USGS, 1999a;
USGS, 1998d; USGS, 1994a; Value Line, 2001).
A-4
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
Table A-3 shows trends in output of aluminum by Primary and Secondary stages of aluminum production.
Secondary aluminum production grew from 24 percent to just under 40 percent of total domestic production over
the period from 1991 to 2010. Primary production of aluminum recorded a net decrease over the 20-year period,
with a particularly sharp decline in 2001. As noted above, this decrease reflects reduced domestic and world
demand for aluminum, and curtailed production at a number of Pacific Northwest mills caused by the California
energy crisis (S&P 2001b; USGS, 2001c). From 2003 to 2006, the industry experienced a period of decline in
total production, despite some increases in the secondary stage of production. Total production remained fairly
constant in recent years except for a significant increase in 2007 (approximately 17 percent) and a substantial
decline in 2009 (approximately 27 percent). In 2010, total production continued to decline, but to a much lesser
extent than in 2009.
Table A-3: U.S. Aluminum Production
Year
Aluminum Ingot
Primary Stages of Production
Secondary Stages of Production
Total Production
Thousand MT
% Change
Thousand MT
% Change
Thousand MT
% Change
I 991
4.121
NA
1.320
NA
5.441
NA
I 992
4.042
-1.9%
1.610
22.0%
5.652
3.9%
1993
3.695
-8.6%
1.630
1.2%
5.325
-5.8%
1994
3.299
-10.7%
1.500
-8.0%
4.799
-9.9%
1995
3.375
2.3%
1.510
0.7%
4.885
1.8%
1996
3.577
6.0%
1.580
4.6%
5.157
5.6%
1997
3.603
0.7%
1.530
-3.2%
5.133
-0.5%
1998
3.713
3.1%
1.500
-2.0%
5.213
1.6%
I 999
3.779
1.8%
1.570
4.7%
5.349
2.6%
2000
3.688
-2.4%
1.370
-12.7%
5.058
-5.4%
200I
2.637
-28.5%
1.210
-1 1.7%
3.847
-23.9%
2002
2.707
2.7%
1.170
-3.3%
3.877
0.8%
2003
2.703
-0.1%
1.070
-8.5%
3.773
-2.7%
2004
2.516
-6.9%
1.160
8.4%
3.676
-2.6%
2005
2.481
-1.4%
1.080
-6.9%
3.561
-3.1%
2006
2.284
-7.9%
1.260
16.7%
3.544
-0.5%
2007
2.554
1 1.8%
1.600
27.0%
4.154
17.2%
2008
2.658
4.1%
1.340
-16.3%
3.998
-3.8%
2009
1.727
-35.0%
1.190
-1 1.2%
2.917
-27.0%
20I0"
1.720
-0.4%
1.120
-5.9%
2.840
-2.6%
Total percent change
1991-2010
-58.3%
-15.2%
-47.8%
Total percent change
2000-2010
-53.4%
-18.2%
-43.9%
Average annual
growth rate196
-4.5%
-0.9%
-3.4%
a. Values for 2010 represent estimates from the USGS 2011 Mineral Commodity Summaries.
Source: USGS, 1995-2011c
Value of shipments and value added are two common measures of manufacturing output.197 Change in these
values overtime provides insight into the overall economic health and outlook for an industry. Value of
shipments is the sum of receipts earned from the sale of outputs; it indicates the overall size of a market or the
size of a firm in relation to its market or competitors. Value added, defined as the difference between the value of
shipments and the value of inputs used to make the products sold, measures the value of production activity in a
particular industry.
190 In this appendix, average annual growth rate refers to a year-to-year, constant percentage growth mean, which is calculated as the
compound annual growth rate between the first and last values. This is the same concept as the geometric mean, if all of the individual
year-to-year values are the same as those used in calculating the constant percentage growth mean.
197 Terms highlighted in bold and italic font are further explained in the glossary.
May 2014
A-5
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
Figure A-l reports constant dollar value of shipments and value added for the Primary and Secondary stages of
aluminum production between 1987 and 2010.
Figure A-1: Value of Shipments and Value Added for Profiled Aluminum Industry Segments (millions, $2011)a
Value Added
Value of Shipments
S8,000
S7,000
------------- tJ U N N tJ tJ tJ tJ tJ tJ tJ
^^^©^©^©^©^©^©^©^©^©^©^©OOOOOOOOOOO
QC iC 5C ^© ^© ^© ^© ^© ^© ^© ^© ^© ^© O O O O O O O O O O —
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American Industry
Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic
Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007
EC
~ Primary Stages of
Production (SIC to
NAICS)
* Primary Stages
Production (NAIC S
331311 and 331312)
¦ Secondary Stages of
Production (SIC to
NAICS)
¦ Secondary Steage of
Production (NAICS
331314 and 331315)
S6,000
g S5,000
3 S4,000
£
¦a S3,ooo
a
¦o
¦s
S2,000
Q
3
13 si,ooo
>

0
a
1
S30,000
S28,000
S26,000
S24,000
S22,000
S20,000
S18,000
S16,000
S14,000
S12,000
S10,000
S8,000
S6,000
S4,000
S2,000
SO
Primary' Stages of
Production (SIC and
NAICS)
Primary' Stages of
Production (NAICS
331311 and 331312)
Secondary' Stages of
Production (SIC to
NAICS)
Secondary Stages of
Production (NAICS
331314 and 331315)
The pattern in the value of Primary Aluminum shipments is generally the same as that in the quantity of
shipments (Table A-3). Production trends during 1987 through 2003 reflect trends in demand for aluminum; both
production and value of shipments fell with increases in the percentage of domestic demand provided by imports.
A-6
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
A similar trend can be observed for the Secondary Aluminum production during this period, which substitutes in
some but not all markets for Primary Aluminum. About half-way through the last decade however, value of
shipments for both Primary and Secondary Aluminum began to rise and continued to do so steadily (with a
significantly steeper increase in the Secondary Aluminum segment) through 2006-2008, when the current
economic recession began. By 2009, both Primary and Secondary Aluminum segments saw significant decreases
in value of shipments. In 2010, as the economy began to recover, both profiled segments began to recover as
evidenced by more than 20 percent increases in value of shipments that year.
Value added by aluminum production excludes the value of purchased materials and services (including
electricity). Figure A-l shows more fluctuation in value added during the last decade than in value of shipments
for both Primary and Secondary Aluminum production segments, which could be attributed to fluctuating input
prices without the industry being able to implement significant price adjustments due to relatively stiff
competition from foreign markets. However, beginning in 2003, both value of shipments and value added for
Primary and Secondary Aluminum production segments experienced growth, which could be attributed to an
overall increase in market demand for aluminum, both domestically and world-wide. During that time, the
Primary Aluminum segment experienced greater fluctuations in value added compared to the Secondary
Aluminum segment. These fluctuations can be attributed to rising cost of inputs, particularly energy and alumina
(USGS, 2009c). However, as the result of recessionary pressures during 2007 through 2009, value of shipments
and value added began fell significantly in both profiled Aluminum segments, with Secondary Aluminum
segment experiencing larger declines. As economy began to recover in 2010, both segments saw slight
improvements in their performance.
Between late 1980s through 1993, value of shipments in the Secondary Aluminum production segment declined
and then recovered by mid-decade, before declining again in the late 1990s. As described above, the profiled
Secondary Aluminum production segment is comprised of secondary smelting and alloying of aluminum and
production of semi-finished aluminum products such as aluminum sheet, plate, and foil. Demand for secondary
smelting and alloying of aluminum is primarily driven by demand from semi-finished aluminum products
manufacturing firms. Demand for secondary and semi-finished aluminum products reflects demand from
transportation, container, construction, and auto industries. Despite the rising cost of aluminum production during
most of the last decade, which resulted in higher aluminum prices, world demand for aluminum continued to
increase; prices for copper and steel experienced more significant increases compared to those of aluminum,
leading to greater aluminum substitution in production of various goods such as cable, beverage cans, and
automobile parts (USGS, 2006a). Consequently, increasing demand for aluminum products during the last decade
through the recession of 2008 resulted in increased value of shipments. As discussed in the next section, however,
prices for the Primary and Secondary Aluminum segment products dropped in 2009, as the result of the recession,
only to rebound during 2010 and 2011. Looking forward, experts expect a recovery in aluminum prices, after a
major decline in 2012. The outlook for the Aluminum Industry is positive due to the combination of expected
volume gains and higher prices (S&P, 2013a).
Overall, while the Primary Aluminum production segment shows lower values for the constant dollar value of
shipments and value added at the end of the analysis period than at the beginning of the period, the Secondary
Aluminum production segment shows a lower value for constant dollar value of shipments but a higher value for
value added. The declining value of shipments and value added in the Primary Aluminum production segment
reflect the increasing role of imports in meeting total U.S. demand and the increased competition this segment
faces from foreign markets. Over time, the U.S. producers of Primary Aluminum products have been forced to
withstand the cost of rising input costs due to increasing pressure from foreign markets.
A.3.2 Prices
The producer price index (PPI) measures price changes, by segment, from the perspective of the seller, and
indicates the overall trend of product pricing, and thus supply-demand conditions, within a segment.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
The price trends shown for Primary Aluminum in Figure A-2 reflect the fluctuations in world supply and demand
discussed in the previous section. During the early 1980s, the Aluminum Industry experienced oversupply, high
inventories, excess capacity, and weak demand, resulting in falling prices for aluminum. By 1986, much of the
excess capacity had permanently closed, inventories had been worked down, and worldwide demand for
aluminum increased strongly. This resulted in price increases through 1988, as shown in Figure A-2.
In the early 1990s, the dissolution of the Soviet Union had a major impact on aluminum markets. Large quantities
of Russian aluminum that formerly had been consumed internally, primarily in military applications, were sold in
world markets to generate hard currency. At the same time, world demand for aluminum was decreasing. The
result was increasing inventories and depressed aluminum prices. In response to declining aluminum prices, the
United States and five other primary aluminum producing nations signed an agreement in January 1994 to curtail
global output, At the time of the agreement, there was an estimated global overcapacity of 1.5 to 2.0 million
metric tons per year (S&P, 2000).
By the mid-1990s, production cutbacks, increased demand, and declining inventories led to a sharp rebound of
prices. Prices declined again during the late 1990s, however, when the economic crises in Asian markets reduced
the demand for aluminum (USGS, 200 le). During 2000, prices rebounded sharply, only to fall again in 2002 due
to the economic recession. Prices seen by both profiled segments increased significantly between 2003 and 2007.
An increase in global demand, especially in emerging markets like China with cheap shipping and labor rates
contributed to price increases during 2006 and 2007. But in 2009, prices dropped in response to the financial
crisis and recession that began in 2007/2008. As shown in Figure A-2, prices for Aluminum Plate, Sheet and Foil
Manufacturing products have recovered since 2009. PPI index data for Primary Aluminum Production are only
available up until 2009; however, according to the USGS (2010a), the annual average price of Primary Aluminum
metal increased in 2010.
Figure A-2: Producer Price Indexes for Profiled Aluminum Industry Segments3
a. Data source does not provide Producer Price Indices for NAICS 331311 and NAICS 331314. PPI index data for Primary Aluminum Production are
only available through 2009.
Source: BLS, 201 If
—»—Primary Aluminum
Production (NAICS
331312)
-Aluminum Plate.
Sheet, and Foil
Manufacturing
(NAICS 331315)
A.3.3 Number of Facilities and Firms
U.S. Geological Survey data indicate that between 1995 and 2010 the number of Primary Aluminum facilities and
the number of domestic firms that own them declined, as shown in Table A-4. The number of domestic firms and
A-8
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
facilities they own declined sharply in 2002 and dropped again in 2004. The bulk of the idled capacity in the
beginning of last decade resulted from curtailed production at a number of Pacific Northwest mills caused by the
California energy crisis. Most of the smelters outside of this region continued to operate at or near their
engineered capacities (S&P 2001b; USGS, 2001c; USGS, 2002a). However, by 2007, the amount of idled
capacity decreased because new power contracts were obtained by producers, which led to a slight increase in
production. Domestic smelters operated at 69 percent of their capacity (USGS, 2008a). Because of the 2008
recession and the resulting decrease in demand for aluminum during the first half of 2009 smelter closures took
place in Alcoa, TN; Massena, NY; and Ravenswood, WV, and by the beginning of the fourth quarter of 2009,
domestic smelters were operating at only 49 percent of rated or engineered capacity (USGS, 2010c).
Table A-4: Primary Stages of Aluminum Production - Number of
Companies and Plants

Year
Number of Companies
Number of Plants
1995
13
22
1996
13
22
1997
13
22
1998
13
23
1999
12
23
2000
12
23
2001
12
23
2002
7
16
2003
7
15
2004
6
14
2005
6
15
2006
6
15
2007
5
13
2008
6
14
2009
6
13
2010
5
9
Source: USGS, 1995-2011c
Table A-5 shows that the number of Primary Aluminum production facilities generally decreased every year
between 1990 and 1999 and have generally risen every year after that until 2005, when it began to fluctuate.
During the last decade, the number of Primary Aluminum facilities overall increased by nearly 82 percent. The
number of facilities in the Secondary Aluminum production segment showed a more consistent trend, increasing
nearly every year. Yet, between 2000 and 2009, the number of the Secondary Aluminum facilities decreased by
nearly 11 percent due to declines in 2002, 2007 and 2009.
May 2014
A-9
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
Table A-5: Number of Facilities for Profiled Aluminum Industry Segments

Primary Stages of Aluminum Productionb
Secondary Stages of Aluminum Production0

Number of

Year3
Establishments
Percent Change
Establishments
Percent Change
1990
61
NA
229
NA
1991
64
5.3%
241
5.3%
1992
60
-7.5%
238
-1.0%
1993
52
-13.5%
224
-6.2%
1994
49
-5.8%
227
1.5%
1995
47
-2.5%
227
0.1%
1996
58
22.6%
207
-8.9%
1997
41
-29.2%
214
3.2%
1998
37
-9.9%
226
5.8%
1999
39
5.4%
247
9.3%
2000
44
12.8%
276
11.7%
2001
49
11.4%
289
4.7%
2002
57
16.3%
236
-18.3%
2003
63
10.5%
243
3.0%
2004
78
23.8%
250
2.9%
2005
73
-6.4%
251
0.4%
2006
69
-5.5%
264
5.2%
2007
81
17.4%
253
-4.2%
2008
79
-2.5%
254
0.4%
2009
80
1.3%
246
-3.1%
Total Percent
30.7%

7.6%

Change 1990-2009

Total Percent
81.8%

-10.9%

Change 2000-2009

Average Annual
1.4%

0.4%

Growth Rate

a. Before 1998, these data were compiled in the Standard Industrial Classification (SIC) system; since 1998, these data have been compiled
in the North American Industry Classification System (NAICS). For this analysis,
EPA converted the NAICS classification data to the SIC
code classifications using the 1997 Economic Census Bridge Between NAICS and SIC.

b. NAICS 331311-2

c. NAICS 331314-5

Source: U.S. DOC, 1990-1997SBA; U.S. DOC, 1998-2009 SUSB

From 1990 up until the mid to late 1990s, the number of firms in both the Primary Aluminum and Secondary
Aluminum segments declined steadily (Table A-6). Both segments than experienced a period of expansion, as the
number of firms grew into the middle of the next decade. Between 2000 and 2009, the number of Primary
Aluminum production firms more than doubled leading to an overall growth of approximately 63 percent over the
two decades. On the other hand, declines in the number of Secondary Aluminum production firms at the end of
the last decade offset gains made in the first half of the decade, leading to an overall decline of approximately 15
percent over the two-decade analysis period.
A-10
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
Table A-6: Number of Firms for Profiled Aluminum Industry Segments
Year3
Primary Stages of Aluminum Production6
Secondary Stages of Aluminum Production0
Number of Firms
Percent Change
Number of Firms
Percent Change
I 990
42
NA
192
NA
I 991
46
7.7%
206
7.2%
I 992
41
-10.4%
204
-1.0%
I 993
38
-7.6%
190
-6.9%
1994
38
-0.9%
185
-2.4%
199 5
35
-7.5%
182
-2.0%
I 996
44
-27.8%
161
-1 14%
1997
27
-38.6%
172
7.1%
I 998
27
-0.9%
182
5.7 %
I 999
29
7.4%
199
9.3%
2000
32
10.3%
225
13.1%
200I
38
18.8%
239
6.2%
2002
50
31.6%
190
-20.5%
2003
51
2.0%
197
3.7 %
2004
63
23.5%
201
2.0%
2005
62
-1.6%
194
-3.5%
2006
57
-8.1%
209
7.7%
2007
69
21.1%
172
-17.7%
2008
68
-1.4%
164
-4.7 %
2009
69
1.5%
164
0.0%
Total Percent Change
1990-2009
62.4%
-14.6%
Total Percent Change
2000-2009
115.6%
-27.1%
Average Annual Growth
Rate
2.6%
-0.8%
a. Before 1998, these data were compiled in the SIC system; since 1998, these data have been compiled in the North American Industry
Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the
1997 Economic Census Bridge Between NAICS and SIC.
b. NAICS 331311-2
c. NAICS 331314-5
Source: U.S. DOC, 1990-1997SBA; U.S. DOC, 1998-2009 SUSB
A.3.4 Employment and Productivity
Figure A-3 provides information on employment for the profiled Primary and Secondary Aluminum production
segments. Employment trends in the Primary Aluminum segment reflect producers" efforts to compete with less
labor-intensive minimills through improvements in labor productivity (McGraw-Hill, 2000). Overall, between
1987 and 2010, both the Primary and Secondary Aluminum segments saw substantial declines in employment of
approximately 61 percent and more than 38 percent, respectively. Most of this decline can be attributed to the
current decade, during which employment in the Primary and Secondary Aluminum segments fell by about 54
percent and nearly 30 percent, respectively.
May 2014
A-11
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
Figure A-3: Employment for Profiled Aluminum Industry Segments3
40,000
35,000
30,000
^ 25,000
E 20,000
15,000
E 10,000
5,000
—A— Primary Stages of
Production (SIC to
NAICS)
—A— Primarv Stages of
Production (NAICS
331311 and 331312)
—-~— Secondary Stages of
Production (SIC to
NAICS)
—« Secondary Stages of
Production (NAICS
331314 and 331315)
------------- N U U N IJ IJ U U
ceccac'O '>s eooeeoeoeoB-
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the SIC classification data to the NAICS code classifications using the 1997
Economic Census Bridge Between SIC and NAICS.
Source: U.S. DOQ 1988-1991, 1993-1996, 1998-2001, 2002-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and
2007 EC
Table A-7: presents year-over-year changes in value added per labor hour, a measure of labor productivity, for the
Primary and Secondary Aluminum production segments between 1987 and 2010. The trend in labor productivity
in both segments shows volatility over the entire analysis period, reflecting variations in capacity utilization
(Section A.3.6). Between 1987 and 2010, labor productivity in the Primary Aluminum segment decreased by 19
percent, with an average annual decline of approximately 1 percent. During the same time, labor productivity in
the Secondary Aluminum segment improved by about 62 percent, despite significant declines between 2006 and
2009. During the last decade, however, both profiled segments experienced an improvement in labor productivity
with the Primary Aluminum segment showing a 10 percent increase and the Secondary Aluminum segment
showing an approximately 16 percent increase.
A-12
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
Table A-7: Productivity Trends for Profiled Aluminum Industry Segments ($2011)
Year3
Primary Stages of Aluminum Production
Secondary Stages of Aluminum Production
Value Added
(millions)
Production
Hours
(millions)
Value Added/Hour
Value Added
(millions)
Production
Hours
(millions)
Value Added/Hour
($/hour)
Percent
Change
($/hour)
Percent
Change
1987
$4,550
32
142
NA
$4,046
51
79
NA
1988
$7,366
37
201
41.6%
$4,408
53
84
5.5%
1989
$5,837
35
167
-16.9%
$4,230
54
79
-5.6%
I 990
$4 555
37
123
-26.5%
$4,898
52
94
18.5%
I 991
$1.612
38
96
-21.9%
$4,600
51
91
-3.1%
I 992
$ i.4 id
38
90
-6.2%
$5,808
52
1 1 1
22.7 %
I 993
$2,705
35
78
-12.8%
$5,019
51
99
-10.7 %
I 994
$3,444
32
107
36.9%
$5,343
49
108
9.2%
199 5
$4 761
34
141
31.3%
$5,448
52
106
-2.7%
I 996
$i.440
34
103
-27.0%
$5,664
53
108
2.1%
1997
$i.700
31
119
15.8%
$5,818
52
1 12
3.6%
I 998
$3,518
32
1 1 1
-6.4%
$7,063
51
140
25.1%
I 999
$3,099
30
102
-8.5%
$7,905
49
162
16.1%
2000
$3,008
29
104
2.2%
$5,120
46
1 10
-32.0%
200I
$3,228
24
135
29.3%
$4,317
43
100
-9.3%
2002
$2,926
24
122
-9.3%
$5.02 i
41
123
23.3%
2003
$2,177
21
105
-14.0%
$4.818
41
117
-4.9%

$3,015
19
156
48.5%
$4,834
41
118
0.3%

$2,565
17
150
-3.8%
$5,625
43
130
10.5%
2006
$3,414
16
208
38.7%
$6,445
41
159
22.1%
2007
$3,067
18
167
-19.9%
$5,936
42
140
-1 1.9%
2008
$2,877
18
156
-6.6%
$5,209
41
129
-8.1%
2009
$1,115
15
75
-51.6%
$3,023
30
101
-21.4%
2010
$1,592
14
115
52.4%
$4,195
33
128
26.8%
Total Percent Change
1987-2010
-65.0%
-56.8%
-19.0%
3.7%
-35.8%
61.5%
Total Percent Change
2000-2010
-47.1%
-52.0%
10.2%
-18.1%
-29.4%
16.1%
Average Annual
Growth Rate
-4.5%
-3.6%
-0.9%
0.2%
-1.9%
2.1%
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American Industry
Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997Economic
Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007
EC
A.3.5 Capital Expenditures
Aluminum production is a highly capital-intensive process. Capital expenditures are needed to modernize,
replace, and when market conditions warrant, expand capacity. Environmental requirements may also require
substantial capital expenditures.
Table A-8 presents capital expenditures in the Primary and Secondary Aluminum production segments during
1987 through 2010. As shown by the table, capital expenditures in the Primary Aluminum segment fluctuated in
the early 1990s, but steadily increased beginning in 1995 and through the remainder of the decade, eventually
increasing more than 200 percent. In the last ten years however, this segment has shown large fluctuations in
capital expenditures from one year to the next, rising and falling as much as 52 percent in a single year. These
changes resulted from the production surges and cutbacks, and capacity fluctuations, in response to supply and
demand conditions prevalent in the market for aluminum.
Capital expenditures in the Secondary Aluminum production segment also fluctuated considerably between 1987
and 2007, peaking in 1990, ten years earlier than in the Primary Aluminum segment. Between 1991 and 1993
producers of Secondary Aluminum reduced capital expenditures by approximately 53 percent. Capital
expenditures in this segment fluctuated during the remainder of the decade until 2001, after which expenditures
May 2014
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Appendix A: Aluminum Industry Profile
decreased more than 60 percent in two years. However, between 2005 and 2007, outlays increased by 70 percent
in response to increase in world demand. However, as a result of the recession beginning in 2007/2008, lack of
credit to aluminum companies was expected to cause delays in expansion projects in many parts of the world
(USGS, 2008a). Indeed, in 2009, capital expenditures in both profiled segments appeared to be impacted by the
recession with declines of about 38 percent and 57 percent in the Primary Aluminum segment and the Secondary
Aluminum segment, respectively. In 2010, as the world economy began to recover, however slowly, capital
expenditures increased by about 6 percent and 53 percent in the Primary Aluminum segment and the Secondary
Aluminum segment, respectively.
Table A-8: Capital Expenditures for Profiled Aluminum Industry Segments (millions, $2011)
Year3
Primary Stages of Aluminum Production
Secondary Stages of Aluminum Production
Capital Expenditures
Percent Change
Capital Expenditures
Percent Change
1987
$451
NA
$830
NA
1988
$347
-23.2%
$955
15.0%
1989
S
124%
$997
4.4%
1990
:>
-5.7 %
$1,157
16.1%
1991
s
5.8%
$922
-20.4%
1992
¦)
0.4%
$741
-19.6%
1993
1
-21.2%
:>
-41.2%
1994
$238
-22.4%
:>
7.8%
1995
$258
8.6%
2
28.0%
1996
S
27.0%
5
2.3%
1997
¦)
70.3%
:>
-9.0%
1998
:>
15.6%
s
-9.2%
1 999
S
-9.1%
1
10.3%
2000
:>
42.9%
s
4.8%
2001
s
-44.3%
2
34.8%
2002
$227
-51.5%
:>
-43.7 %
2003
$127
-44.1%
s
-31.0%
2004
5
38.0%
s
-0.2%
2005
¦)
-26.1%

39.6%
2006
:>
28.6%
7
13.5%
2007
$216
30.0%
:>
49.0%
2008
$222
2.4%
'i
-23.4%
2009
7
-38.0%
$241
-56.6%
2010
$145
5.5%
$370
53.2%
Total Percent Change
1987 - 2010
-67.9%
-55.4%
Total Percent Change
2000 - 2010
-82.8%
-37.1%
Average Annual Growth
Rate
-4.8%
-3.5%
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American Industry
Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic
Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007
EC
A.3.6 Capacity Utilization
Capacity utilization measures actual output as a percentage of total potential output given the available capacity.
Capacity utilization reflects excess or insufficient capacity in an industry and is an indication of whether new
investment is likely. Capacity utilization is also closely linked to financial performance for industries with
substantial fixed costs, such as the Aluminum Industry. Like integrated steel mills, the aluminum manufacturing
process requires a large capital base to transform raw material into finished product. Because of the resulting high
fixed costs of production, earnings can be very sensitive to production levels, with high output levels relative to
capacity needed for facilities to remain profitable.
A-14
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
Figure A-4 shows capacity utilization from 1989 through 2011 for the two profiled Aluminum Industry segments.
As shown, capacity utilization fluctuated substantially throughout the 23-year analysis period for both segments.
Between 1989 and 1998, capacity utilization in the Secondary Aluminum production segment increased on
average, largely due to high demand for rolled aluminum products, which account for more than 50 percent of all
shipments from the Aluminum Industry. Increased consumption by the transportation segment, the largest end-use
segment for the Secondary Aluminum production segment, is responsible for bringing idle capacity into
production (McGraw-Hill, 1999). At the same time, capacity utilization in the profiled Primary Aluminum
production segment remained approximately the same after some fluctuations during that decade. However,
between 1998 and 2001, the general weakening of demand for aluminum products during the Asian economic
crisis and later, general economic weakness in domestic and world economies, resulted in a marked fall-off in
capacity utilization in both profiled segments. Again, reflecting the economic recovery that began in 2002,
capacity utilization in both profiled segments began to rise and by 2008 had risen substantially. While capacity
utilization in both profiled segments fluctuated during the current decade, the Primary Aluminum production
segment generally experienced larger fluctuations. More recently, as a result of the economic recession that began
in 2007/2008, both profiled segments experienced a decline in capacity utilization. While during 2010 and 2011,
production in both profiled Aluminum Segments began to increase in response to general economic recovery
leading to higher capacity utilization, the recovery in the Secondary Aluminum segment was slightly delayed and
seems to have been slower compared to that in the Primary Aluminum segment. Recovery in the Primary
Aluminum segment began in 2010, and from 2009 to 2011 capacity utilization in this segment increased by about
36 percent. The Secondary Aluminum segment began to recover in 2011 and during that year its capacity
utilization increased by approximately 5 percent.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
Figure A-4: Capacity Utilization Rates (Fourth Quarter) for Profiled Aluminum Industry Segments3b,c,d
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997
Economic Census Bridge Between NAICS and SIC.
b. Before 2007, U.S. Census sampled every industry in a specific NAICS6. Beginning in 2007, U.S. Census only sampled certain industries within any
NAICS6, and therefore, the data collected before 2007 cannot be directly compared to the data collected in 2007 and beyond.
c. Capacity Utilization for the Primary Aluminum production segment (NAICS 331311/2) for 2007-2009 are for NAICS 331312; 2007-2009 data for
NAICS 331311 were not available from the Census Bureau at the time of the analysis.
d. Capacity utilization values for 2011 represent third quarter data.
Source: ' U.S. DOC, 1989-2011 SPC
— Primarv Stages of Aluminum
Production (SIC to NAICS)
¦ Primary Stages of Aluminum
Production (NAICS 331311/2)
—A— Secondary Stages of
Aluminum Production (SIC to
NAICS)
—*— Secondary Stages of
Aluminum Production (NAICS
331314/5)
A.4 Structure and Competitiveness
On average, the U.S. Aluminum Industry has moderate-to-high industry concentration, with the Primary
Aluminum production segment being slightly more concentrated than the Secondary Aluminum production
segment. A number of large mergers among aluminum producers have increased the degree of concentration in
the industry in recent years. For example, Alcoa (the largest aluminum producer) acquired Alumax (the third
largest producer) in 1998 and Reynolds (the second largest producer) in May 2000. Alcan acquired Algroup in
2000 and Pechiney in 2004. As the result of these acquisitions, three companies accounted for 41 percent of
primary global aluminum output. In 2007, Rusal and Sual and Rio Tinto acquired Alcan, thereby increasing
concentration in the Aluminum Industry. At that time, industry analysts speculated that with a greater degree of
concentration, capacity would be more closely managed during varying market conditions, which would likely
reduce volatility of industry prices and profits (USGS, 2008a).
A.4.1 Firm Size
The Small Business Administration (SBA) defines a small firm for Primary Aluminum production (NAICS
331311 and 331312) as a firm with 1,000 or fewer employees and for Secondary Aluminum Production (NAICS
331314 and 331315) as a firm with 750 or fewer employees. The Statistics of U.S. Businesses (SUSB) provides
employment data for firms with 500 or fewer employees and does not specify data for companies with 500-750
A-16
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
employees for the Primary Production industry and 500-1000 for the Secondary Production industry. Based on
2009 data for firms with up to 500 employees,
> 56 of the 69 firms in the Primary Aluminum production segment had less than 500 employees. Therefore,
at least 81 percent of this segment's firms are classified as small. These small firms owned 56 facilities, or
70 percent of all facilities in the segment.
> 173 of the 199 firms in the Secondary Aluminum production segment had less than 500 employees.
Therefore, at least 87 percent of this segment's firms are classified as small. These small firms owned 183
facilities, or 74 percent of all facilities in the segment.
Table A-9 below shows the distribution of firms and facilities in the Primary Aluminum production segment
(NAICS 331311 and 331312) and the Secondary Aluminum production segment (NAICS 331314 and 331315) by
employment size of the parent firm.
Table A-9: Number of Firms and Facilities by Employment Size Category for the Profiled
Aluminum Industry Segments, 2009

Employment
Primary Stages of Aluminum Production
Secondary Stages of Aluminum Production
Size Category
Number of Firms
Number of Facilities
Number of Firms
Number of Facilities
0-19
44
44
107
107
20-99
9
9
46
49
100-499
3
3
20
27
500+
13
24
26
63
Total
69
80
199
246
Source: U.S.DOC, 2009 SUSB
A.4.2 Concentration Ratios
Concentration is the degree to which industry output is concentrated in a few large firms. Concentration is closely
related to entry barriers with more concentrated industries generally having higher barriers.
The four-firm concentration ratio (CR4) and the Herfindahl-Hirschman Index (HHI) are common measures of
industry concentration. The CR4 indicates the market share of the four largest firms. For example, a CR4 of 72
percent means that the four largest firms in the industry account for 72 percent of the industry's total value of
shipments. The higher the concentration ratio, the less competition there is in the industry, other things being
equal.198 An industry with a CR4 of more than 50 percent is generally considered concentrated. The HHI indicates
concentration based on the largest 50 firms in the industry. It is equal to the sum of the squares of the market
shares for the largest 50 firms in the industry. For example, if an industry consists of only three firms with market
shares of 60, 30, and 10 percent, respectively, the HHI of this industry would be equal to 4,600 (602 + 302 + 102).
The higher the index, the fewer the number of firms supplying the industry and the more concentrated the
industry. Based on the U.S. Department of Justice's guidelines for evaluating mergers, markets in which the HHI
is under 1,000 are considered unconcentrated, markets in which the HHI is between 1,000 and 1,800 are
considered to be moderately concentrated, and those in which the HHI is in excess of 1,800 are considered to be
concentrated.
Table A-10 shows that, overall, the concentration ratios for the profiled Primary Aluminum production segment
(NAICS 331311 and 331312) have increased for the top four and eight firms, in spite of slight declines in 2007,
since 1997. In 2007, the four largest firms in this segment accounted for 90 in the NAICS 331311 sub-segment
and 77 percent in the NAICS 331312 sub-segment of total U.S. primary capacity. Consolidation in the industry
198 Note that the measured four-firm concentration ratio and the HHI are very sensitive to how the industry is defined. An industry with a
high concentration in domestic production may nonetheless be subject to significant competitive pressures if it competes with foreign
producers or if it competes with products produced by other industries (e.g., plastics vs. aluminum in beverage containers).
Concentration ratios based on share of domestic production are therefore only one indicator of the extent of competition in an
industry.
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Appendix A: Aluminum Industry Profile
since the early 1990s has increased market concentration. With the merger of Alcoa, Inc. and Reynolds in May
2000, the single merged company accounted for 50 percent of domestic primary aluminum capacity, and the four
largest U.S. producers controlled 72 percent of domestic capacity (Alcoa Inc. for 50 percent, Century Aluminum
Co. for almost 10 percent, and Noranda Aluminum Inc. and Ormet Primary Aluminum Corp. for 6 percent each)
reported at the end of 2002 (USGS, 2002a). The HHI reported for NAICS 331312 sub-segment is 2,250,
indicating that this sector is concentrated. While no 2007 HHI is reported for NAICS 331311 sub-segment, given
that twenty largest firms in this sub-segment account for the entirety of this sub-segment's total value of
shipments (CR20=100) together with a high four-firm ratio, it is reasonable to conclude that this sub-segment is
also highly concentrated.
As reported in Table A-10, in 2007 the profiled Secondary Aluminum production NAICS 331313 and NAICS
331314 sub-segments had HHI of 931 and 1,995, respectively. On average, this segment as a whole can be
considered moderately concentrated. Thus, based on these ratios and indices, firms in the profiled Primary
Aluminum production segment on average enjoy higher market power than those in the profiled Secondary
Aluminum production segment. Consequently, based on market concentration data, while the firms in the Primary
Aluminum production segment may be able to pass some of their compliance costs onto their consumers, the
firms in the Secondary Aluminum production segment are less likely to be able to do so. However, an accurate
assessment of the cost pass-through potential of firms in the Aluminum Industry must be considered in
conjunction with other measures of market power.
Table A-10: Selected Ratios for the Profiled Aluminum Industry Segments, 1987,1992,1997, 2002 and
2007
SIC (S) or

Total
Concentration Ratios
NAICS (N)

Number of

Herfindahl-
Code
Yearb'c
Firms
4 Firm (CR4)
8 Firm (CR8)
20 Firm (CR20)
50 Firm (CR50)
Hirschman Index
S2819a
1987
427
38%
49%
68%
84%
468
1992
446
39%
50%
68%
85%
677

1997
5
NA
100%
NA
NA
NA
NT 331311
2002
8
97%
100%
NA
NA
NA

2007
12
90%
99%
100%
NA
NA
S 3334
1987
34
74%
95%
99%
100%
1,934
1992
30
59%
82%
99%
100%
1,456

1997
13
59%
82%
100%
NA
1,231
N 331312
2002
26
85%
98%
100%
100%
NA

2007
34
77%
95%
100%
100%
2,250
S 3341
1987
365
24%
36%
52%
74%
251
1992
346
28%
41%
60%
79%
300

1997
87
41%
54%
76%
94%
630
N 331314
2002
124
45%
58%
79%
96%
694

2007
108
55%
66%
83%
96%
931
S 3353
1987
39
74%
91%
99%
100%
1,719
1992
45
68%
86%
99%
100%
1,633

1997
41
65%
85%
98%
100%
1.447
N 331315
2002
79
71%
87%
97%
100%
1.856

2007
89
71%
87%
98%
100%
1,995
a. SIC code represents largest percentage of facilities and value of shipments within this NAICS based on the 1997 Bridge Between SIC and NAICS
b. Before 1997, data were compiled in the SIC system; since 1997, these data have been compiled in the NAICS system. For this analysis, EPA converted
the NAICS classification data to the SIC code classifications using the 1997 Economic Census Bridge Between NAICS and SIC.
c. The 2002 Census of Manufactures is the most recent concentration ratio data available.
Source: U.S. DOC, 1987, 1992, 1997, 2002, and 2007EC
A.4.3 Foreign Trade
This profile uses two measures of foreign competition: export dependence and import penetration.
Import penetration measures the extent to which domestic firms are exposed to foreign competition in domestic
markets. Import penetration is calculated as total imports divided by total value of domestic consumption in that
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May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
industry: where domestic consumption equals domestic production plus imports minus exports. Theory suggests
that higher import penetration levels will reduce market power and pricing discretion because foreign competition
limits domestic firms' ability to exercise such power. Firms belonging to segments in which imports account for a
relatively large share of domestic sales would therefore be at a relative disadvantage in their ability to pass-
through costs because foreign producers would not incur costs as a result of the Final Existing Facilities
Regulation. The estimated import penetration ratio for the entire U.S. manufacturing sector (NAICS 31-33) for
2010 is 28 percent. For characterizing the ability of industries to absorb compliance cost burdens, EPA judges that
industries with import ratios close to or above 28 percent would more likely face stiff competition from foreign
firms and thus be less likely to succeed in passing compliance costs through to customers.
Export dependence, calculated as exports divided by value of shipments, measures the share of a segment's sales
that is presumed subject to strong foreign competition in export markets. The Final Existing Facilities Regulation
would not increase the production costs of foreign producers with whom domestic firms must compete in export
markets. As a result, firms in industries that rely to a greater extent on export sales would have less latitude in
increasing prices to recover cost increases resulting from regulation-induced increases in production costs. The
estimated export dependence ratio for the entire U.S. manufacturing sector for 2010 is 22 percent. For
characterizing the ability of industries to absorb compliance cost burdens, EPA judges that industries with export
ratios close to or above 22 percent are at a relatively greater disadvantage in potentially recovering compliance
costs through price increases since export sales are presumed subject to substantial competition from foreign
producers.
Table A-11 reports export dependence and import penetration for both the Primary and Secondary Aluminum
production segments, from 1990 through 2010. Imports of Primary Aluminum rose dramatically in 1994,
primarily due to the large exports from Russian producers. Representatives of major aluminum producing
countries met in late 1993 and 1994 to address the excess global supply of primary aluminum. Those discussions
resulted in the Russian Federation's agreement to reduce production by 500,000 MTs per year, and plans for other
producers to cut their production and to assist Russian producers to improve their environmental performance and
stimulate the development of internal demand for the Russian production (USGS, 1994a). Nonetheless, imports
continued to represent a substantial and increasing share of total U.S. consumption until 2007. From 2007 to
2009, both exports and imports declined by approximately 39 percent and 42 percent, respectively in response to
economic recession and consequent decline in demand (44 percent) for Primary Aluminum. As the world
economy in general and U.S. economy in particular began to recover in 2010, higher demand for Primary
Aluminum resulted in its greater exports and imports. In 2011, domestic primary production rose but remained
below 2008 levels. Imports of aluminum increased slightly over 2010 levels while exports of scrap continued to
rise (USGS, 2012c).
Between 1990 and 2010, imports in the Primary Aluminum production segment on average grew by more than 4
percent each year while exports declined by more than 3 percent and value of shipments declined by nearly 4
percent each year, thereby indicating a continuous growth in dependence of the U.S. economy on Primary
Aluminum imports and a steady decline of U.S. competitiveness on the world aluminum market. In 2010, the
import penetration ratio for the Primary Aluminum production segment was 63 percent, which is more than
double the U.S. manufacturing industry average of 28 percent. The export dependence ratio for the Primary
Aluminum production segment in 2010 was 28 percent compared to the national manufacturing average of 22
percent. This shows that the regulated facilities in the profiled Primary Aluminum production segment are subject
to significant international competitive pressures, largely manifesting though the increasing penetration of foreign
product into domestic markets as well as declining competitiveness of domestically produced aluminum on world
aluminum markets. Consequently, these facilities are not very likely to be able to pass a material share of
compliance costs through to consumers.
Facilities in the profiled Secondary Aluminum production segment face lower competition from foreign producers
in domestic and foreign markets than facilities in the profiled Primary Aluminum production segment. In the
May 2014
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Appendix A: Aluminum Industry Profile
Secondary Aluminum production segment, between 1990 and 2010 exports and imports experienced an annual
average growth, however small, of approximately 1 percent, while value of shipments declined slightly by less
than 1 percent. In 2010, the import penetration ratio for the Secondary Aluminum production segment was 14
percent, which is one-half of the U.S. manufacturing industry average of 28 percent. The export ratio for the
Secondary Aluminum production segment in 2010 was 15 percent, or seven percentage points below the average
for the U.S. manufacturing industry. Consequently, regulated facilities in the profiled Secondary Aluminum
production segment would probably be in a better position to recover regulation-induced increases in production
costs through price increases compared to regulated facilities in the profiled Primary Aluminum production
segment.
Overall, the competitive pressures from foreign firms/markets may offset the finding stated above, that the
profiled Aluminum Industry would appear to possess market power from being a moderately to highly
concentrated industry. While the Primary Aluminum segment appears to be highly concentrated, it is subject to
significant international competitive pressures. On the other hand, while competitive pressures in the Secondary
Aluminum segment appear to be less significant, this segment exhibits lower level of market concentration. As a
result, from a total market perspective, the industry is not likely to possess any substantial market power
advantage in being able to pass compliance costs through to customers as price increases.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
Table A-11: Import Share and Export Dependence for the Profiled Aluminum Industry Segments ($2011)
Year3
Value of Imports
(millions)
Value of Exports
(millions)
Value of
Shipments
(millions)
Implied
Domestic
Consumptionb
Import
Penetration0
Export
Dependence"1
Primary Stage of Aluminum Production
I 990
$3,063
$3,063
$12,829
$12,829
24%
24%
I 991
3,2.680
$2,680

$11,228
24%
24%
I 992
$2,724
$2,724
$10,398
$10,398
26%
26%
I 993
$3,628
$3,628
$9,198
$9 198
39%
39%
1994
3,5.567
$5,567
$9,396
$9,396
59%
59%
1995
3,5.884
$5,884
$10,588
>88
56%
56%
1996
3,4.891
$4,891
$9,290
$9 290
53%
53%
1997
3,6.131
>
$9,971
,16
42%
15%
I 998
3,6.289
7
$9,967
>29
42%
13%
I 999
3,6.326
;
$9,124
65
45%
14%
2000
3,6.688
)
$9,139
187
46%
15%
200I
3,6.000
$1,069
$7,783

47%
14%
2002
3,5.959
$925
$7,709
'42
47%
12%
2003
3,5.986
$848
$6,428
>65
52%
13%

3,7.645
i
$7,195
,62
56%
16%
2005
3,8.899
)
$6,925
154
62%
21%
2006
3,10.846
$1,941
$8,182
$17,087
63%
24%
2007
3,9.980
)
$8,384
>95
60%
21%
2008
3,9.352
$1,679
$8,544
!I7
58%
20%
2009
$5,830
$1,072
$4,662
$9,420
62%
23%
2010
$7,017
$1,601
$5,775
$11,191
63%
28%
Total Percent Change
1990 - 2010
129.1%
-47.7%
-55.0%
-12.8%

Total Percent Change
2000 - 2010
4.9%
19.5%
-36.8%
-22.8%

Average Annual
Growth Rate
4.2%
-3.2%
-3.9%
-0.7%

Secondary Stages of Aluminum Production
1990
$2,506
$2,506
$22,446
$22,446
1 1%
1 1%
1991
i

$20,307
$20,307
9%
9%
1 992
$1,847
$1,847
$20,545
$20,545
9%
9%
1 993
)
)
$18,365
165
10%
10%
1994
$1,947
$1,947
$20,291
$20,291
10%
10%
1995
$2,727
$2,727
$24,906
$24,906
1 1%
1 1%
1 996
$2,283
$2,283
$22,330
$22,330
10%
10%
1997
)
$3,314
$23,178
$21,653
8%
14%
1 998
!
$3,125
$22,015
$20,808
9%
14%
1 999
!
$2,955
$21,397
$20,400
10%
14%
2000
$2,154
$2,997
$21,160
$20,317
1 1%
14%
2001
$1,877
$2,596
$18,546
!27
1 1%
14%
2002
$2,016
$2,272
$18,402
47
1 1%
12%
2003
$2,095
$2,283
$18,279
$18,092
12%
12%

$2,550
$2,775
$20,396
$20 171
13%
14%
2005
$3,468
$3,165
$23,385
$23,688
15%
14%
2006
$3,998
$3,722
$27,018
$27 295
15%
14%
2007
$3,710
$3,765
$26,858
$26 803
14%
14%
2008
$3,316
$3,979
$24,437
$2 1.774
14%
16%
2009
$1,852
$2,750
.382
183
13%
18%
2010
$2,648
$3,065
$19,823
$19,407
14%
15%
Total Percent Change
1990 - 2010
5.7%
22.3%
-11.7%
-13.5%

Total Percent Change
2000 - 2010
23.0%
2.3%
-6.3%
-4.5%

Average Annual
Growth Rate
0.3%
1.0%
-0.6%
-0.7%

May 2014
A-21
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
Table A-11: Import Share and Export Dependence for the Profiled Aluminum Industry Segments ($2011)
a. Before 1998, the Department of Commerce compiled data in the SIC system; since 1998, these data have been compiled in the North American Industry
Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic
Census Bridge Between NAICS and SIC.
b. Calculated by EPA as shipments + imports - exports.
c. Calculated by EPA as imports divided by implied domestic consumption.
d. Calculated by EPA as exports divided by shipments.
Source: U.S. ITC, 1990-2010
Table A-12 shows trends in exports and imports for the profiled Primary and Secondary Aluminum production
segments separately. U.S. aluminum companies have a large overseas presence, which makes it difficult to
analyze import data. Reported import data may reflect shipments from an overseas facility owned by a U.S. firm.
The import data therefore do not provide a completely accurate picture of the extent to which foreign companies
have penetrated the domestic market for aluminum. This table shows that imports have grown substantially in
both profiled segments between 1993 and 2010. Exports of Primary Aluminum declined significantly, with some
fluctuation over the period. Exports of Secondary Aluminum, on the other hand, increased by more than 30
percent, also with some fluctuations during this analysis period. Overall, both profiled segments experienced a
decline in exports and imports during 2007 through 2009 in response to economic recessionary pressures;
however, this trend seems to have reversed in 2010 in response to economic recovery.
Table A-12: Trade Statistics for Aluminum and Semi-fabricated Aluminum Products (Quantities in
thousand metric tons; Values in millions, $2011)

Primary Aluminum Production
Secondary Aluminum Production

Import3
Exportb
Import3
Exportb
Year
Quantity
Value
Quantity
Value
Quantity
Value
Quantity
Value
1993
1,840
$3,113
400
$783
400
$1,212
594
$2,144
1994
2,480
$4,935
339
$760
507
$1,534
719
$2,619
1995
1,930
$5,126
369
$958
622
$2,282
812
$3,638
1996
1,910
$4,144
417
$930
498
$1,749
760
$3,247
1997
2,060
$4,688
352
$812
562
$2,035
882
$3,678
1998
2,400
$4,848
265
$595
649
$2,272
893
$3,607
1999
2,650
$4,908
318
$672
735
$2,320
907
$3,347
2000
2,490
$5,149
273
$598
791
$2,668
845
$3,041
2001
2,560
$4,910
192
$400
683
$2,202
751
$2,649
2002
2,790
$4,967
206
$414
796
$2,363
706
$2,312
2003
2,870
$5,142
214
$423
653
$1,818
690
$2,288
2004
3,250
$6,887
298
$662
724
$2,284
795
$2,788
2005
3,660
$8,094
329
$755
927
$3,072
886
$3,299
2006
3,440
$9,927
346
$995
914
$3,547
923
$3,931
2007
2,950
$8,847
349
$1,017
801
$3,276
887
$3,980
2008
2,790
$8,154
308
$929
693
$2,892
929
$4,197
2009
2,900
$5,133
262
$532
499
$1,604
739
$2,929
2010
2,650
$6,240
284
$724
666
$2,318
786
$3,299
Total Percent Change
1993-2010
44.02%
100.46%
-29.00%
-7.56%
66.50%
91.30%
32.32%
53.84%
Total Percent Change
2000-2010
6.43%
21.19%
4.03%
21.10%
-15.80%
-13.10%
-6.98%
8.49%
Average Annual
Growth Rate
2.17%
4.18%
-1.99%
-0.46%
3.04%
3.89%
1.66%
2.57%
a. Table 10: U.S. Imports for Consumption of Aluminum, by Class
b. Table 9: U.S. Exports of Aluminum, by Class
Source: USGS, 1993-2010a
A.5 Financial Condition and Performance
The financial performance and condition of the Aluminum Industry are important determinants of its ability to
absorb the costs of regulatory compliance without material, adverse economic/financial impact. To provide
A-22
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
insight into the industry's financial performance and condition, EPA reviewed two key measures of financial
performance over the period 1988 to 2012: net profit margin and return on total capital. EPA calculated these
measures using data from the Quarterly Financial Report for Manufacturing, Mining, and Trade Corporations
(QFR) published by the U.S. Census Bureau. Financial performance in the most recent financial reporting period
(2012) is obviously not a perfect indicator of conditions at the time of regulatory compliance. However,
examining the trend and deviation from the trend through the most recent reporting period gives insight into
where the industry may be in terms of financial performance and condition, at the time of compliance. In addition,
the volatility of performance against the trend, in itself, provides a measure of the potential risk faced by the
industry in a future period in which compliance requirements are faced: all else equal, the more volatile the
historical performance, the more likely the industry may be in a period of relatively weak financial conditions at
the time of compliance.
Net profit margin is calculated as after-tax income before nonrecurring gains and losses as a percentage of sales
or revenues, and measures profitability, as reflected in the conventional accounting concept of net income. Over
time, the firms in an industry, and the industry collectively, must generate a sufficient positive profit margin if the
industry is to remain economically viable and attract capital. Year-to-year fluctuations in profit margin stem from
a several factors, including: variations in aggregate economic conditions (including international and U.S.
conditions), variations in industry-specific market conditions (e.g., short-term capacity expansion resulting in
overcapacity), or changes in the pricing and availability of inputs to the industry's production processes (e.g., the
cost of energy to the aluminum production process). The extent to which these fluctuations affect an industry's
profitability, in turn, depends heavily on the fixed vs. variable cost structure of the industry's operations. In a
capital intensive industry such as the Aluminum Industry, the relatively high fixed capital costs as well as other
fixed overhead outlays, can cause even small fluctuations in output or prices to have a large positive or negative
affect on profit margin.
Return on total capital is calculated as annual pre-tax income divided by the sum of current portion of long-term
debt due in one year or less, long-term debt due in more than one year, all other noncurrent liabilities and total
stockholders' equity (total capital). This concept measures the total productivity of the capital deployed by a firm
or industry, regardless of the financial source of the capital (i.e., equity, debt, or liability element). As such, the
return on total capital provides insight into the profitability of a business' assets independent of financial structure
and is thus a "purer" indicator of asset profitability than return on equity. In the same way as described for net
profit margin, the firms in an industry, and the industry collectively, must generate over time a sufficient return on
capital if the industry is to remain economically viable and attract capital. The factors causing short-term variation
in net profit margin will also be the primary sources of short-term variation in return on total capital.
Figure A-5 shows net profit margin and return on total capital for the Aluminum Industry between 1998 and 2012.
The graph shows considerable volatility in both metrics. Financial performance declined significantly between
1988 and 1992, reflecting general economic weaknesses and oversupply in the market (McGraw-Hill, 2000). By
the mid-1990s, performance improved as demand recovered and aluminum prices increased. Between 2000 and
2002 financial performance declined again, reflecting economic downturn in both the United States and world
economies. Financial health of the Aluminum Industry began to improve after that and continued to do so until it
significantly deteriorated in 2008 as a result of recession that affected every industry in the nation. During the
fourth quarter of 2008 and early 2009, a number of smelters closed and the price of aluminum continued to
decline (USGS, 2008a). However, as the economy began to recover during the latter part of 2009 and 2010, both
net profit margin and return on total capital increased and, in 2010, exceeded pre-recessionary levels. In 2011, one
smelter that has closed in 2009 was reopened while five potlines, which closed in late 2008 and early 2009, were
restarted (USGS, 2012c). After a steep increase in 2010, profit margin and return on total capital declined in 2011
and 2012, moving towards each indicators long-term average.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
Figure A-5: Net Profit Margin and Return on Total Capital for the Non-Ferrous Metals Industry
20%
15%
10%
5%
0%
-5%
-10%
-15%
* Net Profit Margin * R eturn on Total Capital
Source: U.S. DOC, 1988-2012 OFR
A.6 Facilities Operating Cooling Water Intake Structures
Section 316(b) of the Clean Water Act applies to point source facilities that use or propose to use a cooling water
intake structure that withdraws cooling water directly from a surface waterbody of the United States. In 1982, the
Primary Metals industries as a whole (including Steel and Non-ferrous producers) withdrew 1,312 billion gallons
of cooling water, accounting for approximately 1.7 percent of total industrial cooling water intake in the United
States.199 The industry ranked 3rd in industrial cooling water use, behind the electric power generation industry,
and the chemical industry (U.S. DOC, 1982).
This section provides information for facilities in the profiled aluminum segments estimated to be subject to
regulation under the final rule and other options EPA considered. Existing facilities that meet the following
conditions are potentially subject to regulation:
> Have a National Pollutant Discharge Elimination System (NPDES) permit or are required to obtain one;
> Use or propose to use one or more cooling water intake structures to withdraw water from waters of the
United States;
> Use at least twenty-five (25) percent of the water withdrawn exclusively for contact or non-contact
cooling purposes; and
> Meet the specific applicability coverage criteria for the final rule and other options EPA considered in
terms of design intake flow (i.e., two mgd).
EPA initially identified the set of facilities that were estimated to be potentially subject to the 316(b) Existing
Facilities Regulation based on a minimum applicability threshold of two mgd; this section focuses on these
facilities for the Aluminum segment.2""
199 Data on cooling water use are from the 1982 Census of Manufactures. 1982 was the last year in which the Census of Manufactures
reported cooling water use.
200 EPA applied sample weights to the sampled facilities to account for non-sampled facilities and facilities that did not respond to the
survey. For more information on EPA's 2000 DQ, please refer to the Information Collection Request (U.S. EPA, 2000).
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A-24
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix A: Aluminum Industry Profile
A.6.1 Waterbody and Cooling Water Intake System Type
Table A-13 shows the distribution of facilities by type of waterbody and cooling water intake system.
Table A-13: Number of Facilities Estimated Subject to the 2 mgd All Option by Waterbody Type and
Cooling Water Intake System for the Profiled Aluminum Industry
Waterbody Type
Cool ins; Water Intake System
Recirculating11
Once-Through
Total
Number
% of Total
Number
% of Total
Fstuarv/Tidal River
0
0%
4
21%
4
Freshwater Stream/River
3
73%
14
64%
17
I ,ake or Reservoir
1
27%
0
0%
1
Great Lake
0
0%
3
15%
3
Total
4
17%
21
83%
26
a. Includes facilities that have cooling towers as well as those that use impoundments.
Source: U.S. EPA, 2000; U.S. EPA analysis for this report
A.6.2 Facility Size
The regulated facilities in the Aluminum Industry subject to the final rule and other options EPA considered are
relatively large. Figure A-6 shows the number of regulated facilities by employment size category.
Figure A-6: Number of Regulated Facilities Estimated Subject to the 316(b) Existing Facilities Regulation by
Employment Size for the Profiled Aluminum Industry
14 -

10 -

8 -

6 -

4 -

2
y
o -I

44-

Less than
100
100-249
250-499
500-999
1000 or
greater
Source: U.S. EPA, 2000; U.S. EPA analysis for this report
A.6.3 Firm Size
EPA used the Small Business Administration (SBA) small entity size standards to determine the number of
section 316(b) profiled Aluminum Industry facilities owned by small firms. Firms in the Primary Production of
Aluminum segment are defined as small if they have 1000 or fewer employees; firms in the Secondary Production
segment are defined as small if they have 750 or fewer employees. EPA estimates there are seven small entity-
owned facilities, and 18 large entity-owned facilities in the Aluminum Industry subject to the regulation.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Appendix B Profile of the Chemicals and Allied Products Industry
B.1 Introduction
EPA's Detailed Industry Questionnaire, hereafter referred to as the DQ, identified 13 four-digit SIC codes in the
Chemical and Allied Products Industry (SIC 28) with at least one existing facility that operates a CWIS, holds a
NPDES permit, withdraws at least two million gallons per day (mgd) from a water of the United States, and uses
at least 25 percent of its intake flow for cooling purposes (facilities with these characteristics are hereafter referred
to as "facilities potentially subject to the 316(b) Existing Facilities Regulation" or "regulated facilities"). For this
analysis, EPA identified a six-digit NAICS code for each of these potential facilities using the information from
DQ and public sources (see Appendix J: Mapping Manu facturers Standard Industrial Classification (SIC) Codes
to North American Industry Classification System (NAICS) Codes). As the result of this mapping, EPA identified
15 6-digit NAICS codes in the Chemicals and Allied Products Industry (NAICS 325).
For each of the 15 NAICS codes, Table B-l, following page, provides a description of the industry segment, a list
of primary products manufactured, the total number of the DQ respondents (weighted to represent a national total
of facilities that hold a NPDES permit and operate cooling water intake structures (CWIS)), and the number of
facilities estimated to be potentially subject to Final 316(b) Existing Facilities Regulation based on the minimum
withdrawal threshold of two mgd (see Chapter 1: Introduction for more details on the final rule applicability
criteria).
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Table B-1: Facilities in the Chemicals and Allied Products Industry (NAICS 325)
NAICS
NAICS
Description
Important Products Manufactured
Number of
Regulated
Facilities3
Basic Chemicals (NAICS 3251XX)
325110
Petrochemical mfg
Acyclic hydrocarbons such as ethylene, propylene, and butylene and cyclic
aromatic hydrocarbons such as benzene and toluene made from refined
petroleum or liquid hydrocarbons.
13
325120
Industrial gas mfg
Industrial organic and inorganic gases in compressed, liquid, and solid forms.
4
325131
Inorganic dye &
pigment mfg
Inorganic dyes and pigments such as antimony, copper, lead, and titanium
based pigments.
9
325181
Alkalies &
chlorine mfg
Alkalies such as chlorine, sodium, and hydroxide using an electrolysis process.
19
325188
All other basic
inorganic chemical
mfg
Basic inorganic chemicals except industrial gases, inorganic dyes and pigments,
alkalies and chlorine, and carbon black.
32
325199
All other basic
organic chemical
mfg
Basic organic chemical products, (except aromatic petrochemicals, industrial
gases, synthetic organic dyes and pigments, gum and wood chemicals, cyclic
crudes and intermediates, and ethyl alcohol).
38
Total Basic Chemicals
115
Resins and Synthetics (NAICS 3252XX)
325211
Plastics material &
resin mfg
Resins, plastics materials, and nonvulcanizable thermoplastic elastomers and
mixing and blending resins on a custom basis; noncustomized synthetic resins.
25
325221
Cellulosic organic
fiber mfg
Cellulosic (i.e. rayon and acetate) libers and filaments in the form of
monofilament, filament yam, staple, or tow.
1
325222
Noncellulosic
organic fiber mfg
Noncellulosic (i.e. nylon, polyolefm, and polyester) fibers and filaments in the
form of monofilament, filament yarn, staple, or tow.
9
Total Resins and Synthetics
34
Pesticides and Fertilizers (SIC 3253XX)
325311
Nitrogenous
fertilizer mfg
Nitrogenous fertilizer materials and mixing ingredients into fertilizer; fertilizer
from animal or sewage waste.
9
325312
Phosphatic
fertilizer mfg
Phosphatic fertilizer material and phosphatic material mixed into fertilizer.
1
Total Pesticides and Fertilizers
10
Pharmaceuticals (3254XX)
325411
Medicinal &
botanical mfg
Uncompounded medicinal chemicals and their derivatives (i.e. generally for use
by pharmaceutical preparation manufacturers); grading, grinding, and milling
uncompounded botanicals.
2
325412
Pharmaceutical
preparation mfg
In-vivo diagnostic substances and pharmaceutical preparations (except
biological) intended for internal and external consumption in dose forms, such
as ampoules, tablets, capsules, vials, ointments, powders, solutions, and
suspensions.
6
Total Pharmaceuticals
8
Other Chemical Segments0
325611
Soap & other
detergent mfg
Soaps and other detergents, such as laundry detergents, dishwashing detergents,
toothpaste gels, tooth powders, and natural glycerin.
4
325998
All other
miscellaneous
chemical product
& preparation mfg
Chemical products excluding basic chemicals, resins, and synthetic rubber;
cellulosic and noncellulosic fiber and filaments; pesticides, fertilizers, and other
agricultural chemicals; pharmaceuticals and medicines; paints, coating and
adhesives; soap, cleaning compounds, and toilet preparations; printing inks;
explosives; custom compounding of purchased resins; and photographic films,
paper, plates, and chemicals.
9
Total Other
13
Total Chemicals and Allied Products (NAICS 325)
Total NAICS Code 325

179
a. Number of weighted detailed questionnaire survey respondents.
b. Individual numbers may not add up due to independent rounding.
c. Not included in analysis.
Source: Executive Office of the President, 1987; U.S. EPA 2000; U.S. EPA analysis for this report
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
As shown in Table B-l, EPA estimates that, out of an estimated total of 6,945201 facilities with a NPDES permit
and operating cooling water intake structures in the Chemicals and Allied Products Industry (NAICS 325), 179
facilities (or 3 percent) would be subject to the final rule. The total value of shipments for the Chemicals and
Allied Products Industry (NAICS 325) from the 2010 Annual Survey of Manufactures, published by the U.S.
Census Bureau, is $716.2 billion ($2011). Value of shipments, a measure of the dollar value of production, was
selected for the basis of this estimate. Because the DQ did not collect value of shipments data, these data were not
available for regulated facilities. Total revenue, as reported on the DQ, was used as a close approximation for
value of shipments for these facilities. EPA estimated the total revenue of facilities expected to be subject to
regulation to be $103.0 billion ($2011).2"2 Therefore, EPA estimates that 14 percent of total production in the
chemical industry occurs at facilities estimated to be subject to regulation under the final rule.
The DQ responses indicate that four chemical segments account for a significant majority of the Chemicals and
Allied Products Industry facilities subject to the 316(b) Final Existing Facilities Regulation: (1) Basic Chemicals
(including NAICS codes 325110, 325120, 325131, 328181, 325188, 325199); (2) Resins and Synthetics
(including NAICS codes 325211, 325221, and 325222); (3) Pesticides and Fertilizers (including NAICS codes
325311 and 325312); and (4) Pharmaceuticals (including NAICS codes 325411, and 325412). This profile
therefore provides detailed information for these four industry segments.
Table B-2 on the following page provides the cross-walk between NAICS codes and SIC codes for the profiled
chemical NAICS codes. The table shows that some NAICS code industry segments have 1 to 1 relationships to
SIC codes, while the other NAICS codes in the four profiled chemical segments correspond to two SIC codes.
Table B-2: Relationship between NAICS and SIC Codes for the Chemicals and Allied Products Industry
(2010)
NAICS
Code
NAICS Description
SIC Code
SIC Description
Number of
Establishments
(2009)a
Value of
Shipments
(2010; Millions;
$2011)
Employment
(2010)
Basic Chemicals
325110
Petrochemical manul-g
2865
Cyclic crudes & intermediates
50
$79,828
8,632
2869
Industrial organic chemicals, n.e.c.
325120
Industrial gas manul-g
2869
Industrial organic chemicals, n.e.c.
493
$7,356
9,445
2813
Industrial gases
325131
Inorganic dye and pigment
manuf-g
2816
Inorganic pigments
87
$5,174
5,549
2819
Industrial inorganic chemicals,
n.e.c.
328181
Alkalies & chlorine manuf-g
2812
Alkalies & chlorine
44
$6,112
5,661
325188
All other inorganic chemical
manul-g
2819
Industrial inorganic chemicals,
n.e.c.
637
$24,302
29,838
2869
Industrial organic chemicals, n.e.c.
325199
All other organic chemical
manuf-g
2869
Industrial organic chemicals, n.e.c.
729
$82,703
64,301
2899
Chemical preparations, n.e.c.
201 This estimate of the number of facilities potentially subject to regulation is based on the universe of facilities that received the 1999
screener questionnaire.
202 To compare revenue values of regulated facilities with the industry value of shipments, EPA brought revenue values for regulated
facilities forward to 2010 using industry-specific Producer Price Index (PPI) values published by the Bureau of Labor Statistics (BLS)
and stated in 2011 dollars using GDP deflator published by the Bureau of Economic Analysis (BEA).
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Table B-2: Relationship between NAICS and SIC Codes for the Chemicals and Allied Products Industry
(2010)
NAICS
Code
NAICS Description
SIC Code
SIC Description
Number of
Establishments
(2009)a
Value of
Shipments
(2010; Millions;
$2011)
Employment
(2010)
Resins and Synthetics
325211
Plastics material & resin
manuf-g
2821
Plastics materials & resins
1,036
$81,590
58,275
325221
Cellulosic organic fiber
manuf-g
2823
Cellulosic manmade fibers
18
$814
1,157
325222
Noncellulosic organic fiber
manuf-g
2824
Organic fibers, noncellulosic
105
$6,122
12,560
Pharmaceuticals
325311
Nitrogenous fertilizer manuf-
g
2873
Nitrogenous fertilizers
152
$7,324
4,529
325312
Phosphatic fertilizer manuf-g
2874
Phosphatic fertilizers
73
$8,776
5,839
Pesticides and Fertilizers
325411
Medicinal & botanical
manuf-g
2833
Medicinals & botanicals
384
$11,458
25,672
325412
Pharmaceutical preparation
manuf-g
2834
Pharmaceutical preparations
974
$140,594
138,644
2835
Diagnostic substances
a. Hie number of establishments is based on data from the 2009 Statistics of U.S. Businesses. Value of Shipments and Employment reflect 2010 data.
Source: U.S. DOC, 2010 ASM; U.S. DOC, 2009 SUSB
B.2 Summary Insights from this Profile
A key purpose of this profile is to provide insight into the ability of chemicals firms to absorb compliance costs
under the final rule without material adverse economic/financial effects. The industry's ability to absorb
compliance costs is primarily influenced by two factors: (1) the extent to which the industry may be expected to
shift compliance costs to its customers through price increases, and (2) the financial health of the industry and its
general business outlook.
B.2.1 Likely Ability to Pass Compliance Costs Through to Customers
As reported in the following sections of this profile, the chemicals industry has a variable level of concentration,
with some industry segments exhibiting relatively low concentration while others show somewhat higher
concentration. Regardless of the domestic industry concentration level and its implications for market power, the
Chemicals and Allied Products Industry faces increasing competitive pressure from abroad, which substantially
limits any apparent ability of firms to pass a significant portion of their compliance-related costs through to
customers. In addition, the relatively low share of total industry output that is estimated subject to regulation
under the final rule and other options EPA considered also diminishes a firms" ability to shift compliance costs to
customers. For these reasons, in its analysis of regulatory impacts for the chemicals industry, EPA judges that
regulated facilities would be unable to pass compliance costs through to customers; i.e., regulated facilities must
absorb all compliance costs (see following sections. Appendix K: Cost Pass-Through Analysis, and Chapter 5:
Economic Impact Analysis for Manufacturers, for further information).
B.2.2 Financial Health and General Business Outlook
Over the last two decades, the Chemicals and Allied Products Industry, like other U.S. manufacturing industries,
has experienced a range of economic/financial conditions and a number of substantial challenges. In the early
1990s, the domestic Chemicals and Allied Products Industry was affected by reduced U.S. demand as the
economy entered a recessionary period. Although domestic market conditions improved by mid-decade, weakness
in Asian markets, along with other domestic economic factors, dealt a serious blow to the chemicals industry in
1998. A significant drop in demand for Chemicals and Allied Products during the economic recession of the early
B-4
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
2000s resulted in record low capacity utilization and a significant drop in capital expenditures. All profiled
Chemicals and Allied Products Industry segments except Pharmaceuticals saw significant declines in exports,
imports, value of shipments as well as value added. As the U.S. economy began to recover, the domestic
Chemicals and Allied Products Industry saw continuous improvements in demand levels and consequent
improvement of financial performance during 2003 to 2005. By 2007, value of shipments significantly grew,
prices were at record highs, and labor productivity increased, with the Pharmaceuticals industry segment
performing especially well. Beginning in 2008, the Chemicals and Allied Products Industry faced a substantial
drop in demand due to the economic recession. This economic downturn forced firms in the Chemicals and Allied
Products Industry to realign their research and development capabilities, marking a shift in companies" long-term
strategies and prompting them to identify growth opportunities in areas such as energy, food and water (Jagger,
2009). In 2011, the Diversified Chemicals sub-industry index fell by more than 8 percent, while the S&P 15000
index dropped only 0.3 percent; however, it has increased by 14 percent year to date through June 29 compared to
an 8 percent rise in the S&P 1500 (S&P, 2012). Experts expect continued strong performance, projecting a
positive outlook for the industry in 2013 (S&P, 2013c). With the recent positive trend in the industry, the
Chemicals and Allied Products Industry should be able to absorb additional regulatory compliance costs without a
material financial impact.
B.3 Domestic Production
The U.S. Chemical and Allied Products industry includes a large number of companies that, in total, produce
more than 70,000 different chemical products. These products range from commodity materials used in other
industries to finished consumer products such as soaps and detergents. The industry accounts for over $630 billion
of total manufacturing value added (Bassi and Yudken, 2009).
The Chemical and Allied Products industry as a whole is highly energy-intensive. This is especially the case for
basic chemicals as well as certain specialty chemical segments (i.e., industrial gases). The industry relies upon
energy inputs not only for fuel and power for its operations, but also as raw materials in the manufacturing of
many of its products. For example, oil and natural gas are raw materials (termed "feedstocks") for the
manufacture of organic chemicals. However, various technology developments throughout the years have allowed
the industry to become less energy intensive; the U.S. chemical industry has reduced its fuel and power energy
consumed per unit of output by 53 percent since 1974 (ACC, 2009). In addition, the recent drop in domestic
natural gas prices relative to global crude oil prices has placed domestic petrochemical firms at a comparative
advantage, in terms of improved feedstock cost, over other regions of the world (S&P, 2012).
B.3.1 Output
Figure B-l shows constant dollar value of shipments and value added for the four profiled Chemicals and Allied
Products Industry segments between 1988 and 2010.2lb Value of shipments and value added are two common
measures of manufacturing output. Change in these values overtime provides insight into the overall economic
health and outlook for an industry. Value of shipments is the sum of receipts earned from the sale of outputs; it
indicates the overall size of a market or the size of a firm in relation to its market or competitors. Value added,
defined as the difference between the value of shipments and the value of inputs used to make the products sold,
measures the value of production activity in a particular industry.
Figure B-l shows that between 1988 and 1993, the Basic Chemicals segment experienced a slight decrease in
both value of shipments and value added, followed by volatility through 1998. Mid-1990s were marked by
increased competition in the global market for petrochemicals, which comprise a large portion of basic chemical
products. The increased competition stems from the considerable capacity expansions for these products seen in
203 Terms highlighted in bold and italic font are further explained in the glossary.
May 2014
B-5
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Industry Profile
developing nations during that time (McGraw-Hill, 2000). Both value of shipments and value added declined in
2001 as the Basic Chemicals segment faced decreased demand due to economic slowdown. During 2002, as the
economy began to show the first signs of recovery, value of shipments and value added began to grow steadily
and rapidly and continued to do so through 2007-2008, when global economy again began to decline. During
2009, the Basic Chemicals segment experienced a significant drop in value of shipments and value added of
approximately 28 percent and 21 percent, respectively. However, the segment seems to have recovered during the
following year, when its value of shipments and value added grew by nearly 28 percent and 33 percent,
respectively.
Overall, during 1988 through 2007-2008, the profiled Resins and Synthetics, and Pesticides and Fertilizers
segments remained more stable than the Basic Chemicals segment. In the early 1990s, domestic producers
benefited from the relatively weak dollar, which made U.S. products more competitive in the global market.
During the latter part of the 1990s, the strength of the U.S. economy bolstered domestic end-use markets,
offsetting the effect of reduced U.S. export sales, which resulted from increased global competition and a
strengthened dollar (McGraw-Hill, 2000). The global economic slowdown that began in 2000 led to decreased
production, in particular, of chemical goods that are used in the production processes of other industries, notably
steel, apparel, textiles, forest products, and technology. During 2002 through 2007-2008, the value of shipments
and value added of both the Resins and Synthetics and Pesticides and Fertilizers segments remained relatively
stable. During 2008 and 2009, as the result of global recessionary pressures, both segments experienced
significant declines in value of shipment and value added; however, while the Resins and Synthetics sector seems
to have recovered during 2010, the Pesticides and Fertilizers segment experienced further declines.
Of the four profiled industry segments, the Pharmaceuticals segment saw the least volatility coupled with
significant overall growth. During 1988 through 2006, value of shipments and value added in the Pharmaceuticals
segment experienced nearly steady increases; however, since 2006, this segment has seen steady declines in both
value of shipments and value added.
While all four profiled segments grew over the last two decades, the Pharmaceuticals segment grew the most,
despite modest contractions during the latter part of the last decade. Between 1988 and 2010, value of shipments
and value added in this segment on average grew by 4 percent each year and more than doubled as a result. The
Basic Chemicals came second, with value of shipments and value added increasing by more than 73 percent and
40 percent, respectively. During the same time, value of shipments and value added in the Resins and Synthetics
segment grew only by 18 percent and 1 percent, respectively. The Pesticides and Fertilizers segment experienced
significantly stronger growth during the last decade with value of shipments growing by more than 76 percent and
value added more than doubling (compared to the two-decade growth of 32 percent and 43 percent, respectively).
The composition of the Chemicals and Allied Products Industry has changed over time, with increasing emphasis
being placed on high-technology fields such as pharmaceuticals, biotechnology, and advanced materials. The
recent recession caused declines in industry-wide output. However, this downturn is motivating companies to
seek new ways to grow and realign research and development capabilities to seek new growth opportunities in
renewable energy and food production (Jagger, 2009). Indeed, as discussed earlier, the Basic Chemicals and the
Resins and Synthetics segments already seem to have recovered growing significantly during 2010. While the
Pesticides and Fertilizers segment still saw a decline in its value of shipments and value added during 2010, this
decline was significantly smaller compared to that during 2009, signaling potential recovery. The Pharmaceuticals
segment began to see modest contractions during prosperous pre-recessionary years and recent recessionary
pressures did not seem to have accelerated this trend. This performance trend should better position regulated
facilities in the Chemicals and Allied Products Industry to absorb compliance costs of the final rule.
B-6
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Industry Profile
Figure B-1: Value of Shipments and Value Added for Profiled Chemicals and Allied Products Industry Segments
(millions, $2011 f
Value of Shipments
o
6ft
VI
3
I
S220,000
S200,000
S180,000
S160,000
S140,000
S120,000
S100,000
S80,000
S60,000
S40,000
S20,000
SO
-k— Basic Chemicals
(SIC toNAICS)
— Basic Chemicals
(NAICS 3251XX)
— Resins and
Synthetics (SIC to
NAICS)
Resins and
Synthetics (NAICS
3252XX)
-~— Pesticides and
Fertilizers (SIC to
NAICS)
—» Pesticides and
Fertilizers (NAICS
3253XX)
-M— Pharmaceuticals
(SIC to NAICS)

— Pharmaceuticals
(NAICS 3254XX)
ve *e ve 'e ve 'e e 'e VS ve e ve
so oo ve ve vo ve e — e e -c —
IJ i j t ,> I ^ tj rv rj iv i j tv
— u w -b. 'Jl ev -4 ce « o
Value Added
S130,000
S120,000
S110,000
S100,000
~ S90,000
® S80,000
- S70,000
§ S60,000
^S50,000 £
o
* S40,000
^ S30,000
o
J5 S20,000
S10,000
-*— Basic Chemicals
(NAICS 3251XX)
-A— Basic Chemicals
(SIC to NAICS)
-¦— Resins and
Synthetics (NAICS
3252XX)
-¦— Resins and
Synthetics (SIC to
NAICS)
~ Pesticides and
Fertilizers (NAICS
3253JD0
-~— Pesticides and
Fertilizers (SIC to
NAICS)
— — — — — ^ — — — — — —
ve ve ve e vo vo e vo e e ve e o o e o o
oooovo>evevseieveveveveoooooo
oe >£ a n hJU£b'.nsv~oc£ >ee — k» u ^ rji
M tJ tJ
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997. these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the
1997 Economic Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010jISM; U.S. DOC, 1987, 1992, 1997, 2002, and
2007EC.
Table B-3 provides the Federal Reserve System's index of industrial production for the 4 profiled industry
segments, showing trends in production since 1990. This index reflects total output in physical terms, whereas
value of shipments and value added reflect the value of output in economic terms. Table B-3 shows varying trends
in the four segments since 1990, but sharp declines in production in all segments except Pharmaceuticals during
2000 through 2001. These declines were caused by the marked slowdown in the U.S. economy, which affected
May 2014
B-7
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
demand in major chemical-using segments such as steel, apparel, textiles, forest products, and the technology
sectors (Chemical Marketing Reporter, 2001).
Between 1990 and 2011, the Pharmaceuticals segment saw the largest increase in production exceeding 66
percent, while the Basic Chemicals and Resins and Synthetics experienced increases of less than 5 percent.
During the same time, the Pesticides and Fertilizers segment experienced an overall production decline of more
than 10 percent. During the last decade, production growth in the Pharmaceuticals segment was significantly
smaller, at 10 percent. The Basic Chemicals segment also saw a modest increase in production of approximately 6
percent. However, production in the Resins and Synthetics and Pesticides and Fertilizers segments declined by
approximately 15 percent and 4 percent, respectively.
Table B-3: Industrial Production Index for Chemicals and Allied Products Industry Segments
(Annual Averages)
Year
Basic Chemicals3
Resins and Syntheticsb
Pesticides and Fertilizers0
Pharmaceuticals'*
Index
2007=100
Percent
Change
Index
2007=100
Percent
Change
Index
2007=100
Percent
Change
Index
2007=100
Percent
Change
I 990
81.2
NA
80.5
NA
104.1
NA
50.5
NA
I 991
77.6
-4.5%
78.6
-2.3%
100.6
-3.4%
54.0
7.0%
I 992
78.5
1.2%
83.2
5.8%
104.9
4.2%
53.3
-1.2%
I 993
75.5
-3.8%
84.0
1.0%
105.8
0.8%
53.5
0.4%
1994
76.2
0.9%
90.7
8.0%
105.6
-0.2%
55.7
4.0%
1995
76.1
-0.1%
91.3
0.6%
105.2
-0.4%
57.9
4.1%
I 996
76.0
-0.1%
89.4
-2.1%
107.3
2.0%
61.4
6.0%
1997
81.8
7.6%
95.0
6.3%
1 1 1.3
3.8%
64.7
5.4%
I 998
79.0
-3.4%
99.0
4.3%
1 13.7
2.1%
70.4
8.7%
I 999
82.7
4.7 %
100.0
1.0%
102.4
-9.9%
73.2
4.0%
2000
79.9
-3.4%
97.0
-3.0%
96.9
-5.4%
76.2
4.1%
200I
72.2
-9.7 %
87.7
-9.6%
89.2
-7.9 %
82.0
7.7%
2002
76.8
6.4%
89.3
1.8%
92.1
3.2%
87.8
7.1%
2001
79.2
3.1%
87.4
-2.1%
96.3
4.5%
90.9
3.5%
2004
86.3
9.0%
90.5
3.5%
100.4
4.3%
91.3
0.4%
2005
86.7
0.4%
96.9
7.1%
104.2
3.8%
94.9
3.9%
2006
89.0
2.7 %
94.9
-2.0%
108.6
4.3%
98.8
4.1%
2007
100.0
12.3%
100.0
5.4%
100.0
-7.9%
100.0
1.2%
2008
88.3
-1 1.7%
85.0
-15.0%
86.5
-13.5%
97.7
-2.3%
2009
73.1
-17.2%
73.8
-13.2%
90.9
5.1%
91.8
-6.0%
2010
86.3
18.1%
85.7
16.0%
94.8
4.3%
85.1
-7.3%
2011
84.5
-2.1%
82.3
-3.9%
93.1
-1.8%
83.8
-1.5%
Total Percent
Change 1990-
2011
4.0%
2.3%
-10.6%
66.1%
Total Percent
Change 2000-
2011
5.7%
-15.2%
-3.9%
10.0%
Average
Annual Growth
Rate204
0.2%
0.1%
-0.5%
2.4%
a. NAICS 3251.
b. NAICS 3252.
c. NAICS 3253
d. NAICS 3254
Source: Federal Reserve Board of Governors, 2012b
204 In this appendix, average annual growth rate refers to a year-to-year, constant percentage growth mean, which is calculated as the
compound annual growth rate between the first and last values. This is the same concept as the geometric mean, if all of the individual
year-to-year values are the same as those used in calculating the constant percentage growth mean.
B-8
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
B.3.2 Prices
The Producer Price Index (PPI) measures price changes, by segment, from the perspective of the seller, and
indicates the overall trend of product pricing, and thus supply-demand conditions, within a segment.
Chemicals product prices fluctuate in large part as a result of varying energy prices. For instance, basic
petrochemicals, which comprise the majority of organic chemical products and are a part of the Basic Chemicals
segment, depend heavily on energy commodities as inputs to the production process - energy input costs may
account for up to 85 percent of total product costs. The prices of natural gas and oil therefore influence the
production costs and the selling price for these products. High basic petrochemical prices affect prices for
chemical intermediate and final end products. The cyclical nature of market supply and demand conditions also
significantly influence prices for commodity chemical products. Finally, all analyzed chemicals industry segments
are characterized by large existing capital investments and production capacity, which can lead to fluctuations in
prices in response to imbalances in supply and demand.
Figure B-2 shows PPI for the profiled Chemicals and Allied Products Industry segments for 1987 through 2010.
All profiled segments except Pharmaceuticals saw some volatility during that time in response to changing
economic conditions, energy prices, and changes in operating processes. For instance, the price jump for the
Resins and Synthetics and Basic Chemicals segments in 2000 is the result of an increase in the price of natural
gas - feedstock for 70 percent of U.S. ethylene production (Chemical Marketing Reporter, 2001). Price increases
for Resins and Synthetics also reflected a shift by U.S. producers away from production of commodity resins to
specialty and higher value-added products (McGraw-Hill, 2000). Overall, during 1987 through 2008, selling
prices increased for all four profiled chemicals industry segments, especially during the last decade. As the result
of recent recession, prices for all profiled segments except Pharmaceuticals declined significantly during 2009,
but recovered by 2011.
Figure B-2: Producer Price Indexes for Profiled Chemicals and Allied Products Industry Segments
400

-Basic Chemicals
(NAICS 3251)
- Resins and
Synthetics (NAICS
3252)
-Pesticides and
Fertilizers (NAICS
3253)
- Pharmaceuticals
(NAICS 3254)
H-h-h-h-h-h-h-h-N-N-N-N-N-KlKlKlKlKlKlKlKlKlKlKlKl
sS «s «s «s «s «s «s «s «s «s «s «s «s e e e e e e e e e e e e
cececeffvsvsvsvs'sS 'sS 'sS 'sSssssseeoooh-h-
Source: BLS, 201 lg
B.3.3 Number of Facilities and Firms
According to Statistics of U.S. Businesses, the number of facilities in the Basic Chemicals segment remained
relatively stable between 1990 and 1997, followed by five consecutive years of decreases in the number of
facilities. In 2003, however, the number of facilities increased again and remained relatively flat for the next few
years. Overall, between 1990 and 2009, the number of facilities in the Basic Chemicals segment declined by more
May 2014
B-9
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
than 6 percent. During the same time period, the Resins and Synthetics and Pharmaceuticals segments saw overall
increases of approximately 93 and 46 percent, respectively, while the number of facilities in the Pesticides and
Fertilizers segment remained relatively constant, declining by less than 1 percent. Above-average increases in the
number of facilities in the Resins and Synthetics segment reported during 1995 and 1996 reflected growth in
demand for plastics in a number of end-uses (McGraw-Hill, 2000). During 2009, all profiled segments except the
Pesticides and Fertilizers segment saw a reduction in the number of facilities; the number of facilities in the
Pesticides and Fertilizers segment remained the same. It is possible that some facilities became unprofitable and
closed down as the result of increasing costs and lower demand as the result of recent recessionary pressures.
Table B-4: Number of Facilities for Profiled Chemicals and Allied Products Industry Segments
Year3
Basic Chemicalsb
Resins and Synthetics0
Pesticides and Fertilizers'*
Pharmaceuticals6
Number of
Facilities
Percent
Change
Number of
Facilities
Percent
Change
Number of
Facilities
Percent
Change
Number of
Facilities
Percent
Change
1990
2.181
NA
601
NA
227
NA
933
NA
1991
2.275
4.3%
621
3.3%
228
0.4%
962
3.1%
1992
2.261
-0.6%
555
-10.6%
251
10.1%
1,013
5.4%
1993
2.283
1.0%
600
8.1%
250
-0.4%
1,044
3.0%
1994
2.261
-0.9%
595
-0.8%
233
-6.8%
981
-6.0%
1995
2.234
-1.2%
659
10.8%
239
2.6%
1.005
2.4%
1996
2.152
-3.7%
741
12.4%
252
5.4%
1.142
13.7%
1997
2.247
4.4%
705
-4.9%
215
-14.7%
1.190
4.2%
1998
2.157
-4.0%
677
-4.0%
221
2.8%
1.241
4.3%
1999
2.135
-1.0%
700
3.4%
222
0 s%
1.249
0.6%
2000
2.113
-1.0%
714
2.0%
222
0.0%
1.251
0.2%
2001
2.065
-2.3%
744
4.2%
223
0.5%
1.257
0.5%
2002
1.976
-4.3%
806
8.3%
207
-7.2%
1.244
-1.0%
2003
2.042
3.3%
907
12.5%
189
-8.7%
1.268
1.9%
2004
2.065
1.1%
905
-0.2%
193
2.1%
1.280
0.9%
2005
2.021
2 1%
924
2.1%
193
0.0%
1.281
0.1%
2006
2.022
0.0%
906
-1.9%
188
-2.6%
1.317
2.8%
2007
2.076
2.7%
926
2.2%
198
5.3%
1.368
3.9%
2008
2,142
3.2%
1.195
29.0%
225
13.6%
1,399
2.3%
2009
2,040
-4.8%
1.159
-3.0%
225
0.0%
1,358
-2.9%
Total Percent
Change 1990-2009
-6.5%
92.8%
-0.9%
45.6%
Total Percent
Change 2000-2009
-3.5%
62.3%
1.4%
8.6%
Average Annual
Growth Rate
-0.4%
3.5%
0.0%
2.0%
a. Before 1997, data were compiled in the SIC system; since 1997, these data have been compiled in the North American Industry Classification System
(NAICS). For this analysis, EPA converted the SIC classification data to the NAICS code classifications using the 1997 Economic Census Bridge Between
SIC and NAICS.
b. NAICS 3251.
c. NAICS 3252.
d. NAICS 3253
e. NAICS 3254
Source: U.S. DOC, 1990-1997SBA; U.S. DOC, 1998-2009 SUSB
Table B-5 shows the number of firms in the four profiled chemical segments between 1990 and 2009. The trend in
the number of firms during this analysis period is similar to that in the number of facilities. During the last two
decades, the Resins and Synthetics segment saw the largest increase in the number of firms (nearly 152 percent)
followed by the Pharmaceuticals segment (nearly 45 percent), and the Pesticides and Fertilizers segment
(approximately 9 percent). During the same time, the number of firms in the Basic Chemicals segment remained
practically unchanged, declining only by less than 1 percent; however, during the last decade the number of firms
in this segment increased by more than 8 percent.
The number of firms in the Basic Chemicals segment peaked in 1994, and then declined almost steadily during
1995 through 2005; in 2006 the number of firms began to increase and continued to do so through 2008. The
B-10
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Resins and Synthetics and Pesticides and Fertilizers segment saw a number of sharp increases and declines
throughout the entire analysis period, never really stabilizing. The number of firms in the Pharmaceuticals
segment dropped significantly in 1995 but in 2006 the number of firms in this segment began to increase and
continued to do so through 2008. During 2009, all four profiled segments saw a reduction in the number of firms
probably as the result of industry contraction caused by global recession. Further, the recent increasing cost of
feedstock (largely crude oil) and other factors increasing production costs has led to consolidation and mergers of
national and multinational chemical companies (MBendi, 2010).
Table B-5: Number of Firms for Profiled Chemicals and Allied Products Industry Segments
Year3
Basic Chemicalsb
Resins and Synthetics0
Pesticides and Fertilizers'*
Pharmaceuticals6
Number of
Firms
Percent
Change
Number of
Firms
Percent
Change
Number of
Firms
Percent
Change
Number of
Firms
Percent
Change
I 990
1.189
NA
353
NA
163
NA
799
NA
I 991
1.227
3.2%
380
7.6%
161
-1.2%
835
4.4%
I 992
1.267
3.3%
319
-16.1%
180
1 1.8%
872
4.5%
I 993
1.294
2.1%
350
9.7%
177
-1.7%
908
4.1%
1994
2.245
73.5%
595
70.0%
233
31.6%
981
8.1%
1995
1.251
-44.3%
409
-31.3%
166
-28.8%
859
-12.5%
I 996
1.161
-7.2%
477
16.6%
181
9.0%
991
15.3%
1997
1.222
5.2%
434
-9.0%
174
-3.9%
1.033
4.3%
I 998
1.136
-7.0%
395
-9.0%
173
-0.6%
1.073
3.8%
I 999
1.096
-3.5%
411
4.1%
175
1.2%
1.076
0.3%
2000
1.090
-0.5%
429
4.4%
174
-0.6%
1.073
-0.3%
200I
1.085
-0.5%
456
6.3%
178
2.3%
1.074
0.1%
2002
1.020
-6.0%
518
13.6%
165
-7.3%
1.053
-2.0%
2003
1.091
7.0%
635
22.6%
146
-1 1.5%
1.065
1.1%
2004
1.086
-0.5%
622
-2.0%
150
2.7%
1.074
0.8%
2005
1.085
-0.1%
653
5.0%
154
2.7%
1.074
0.0%
2006
1.105
1.8%
647
-0.9%
152
-1.3%
1.107
3 1%
2007
1.158
4.8%
662
2.3%
162
6.6%
1.140
3.0%
2008
1.249
7.9%
905
36.7%
178
9.9%
1.179
3.4%
2009
1.178
-5.7%
889
-1.8%
177
-0.6%
1.158
-1.8%
Total Percent
Change 1990-2009
-0.9%
151.8%
8.6%
44.9%
Total Percent
Change 2000-2009
8.1%
107.2%
1.7%
7.9%
Average Annual
Growth Rate
0.0%
5.0%
0.4%
2.0%
a. Before 1997, data were compiled in the SIC system; since 1997, these data have been compiled in the NAICS. For this analysis, EPA converted the SIC
classification data to the NAICS code classifications using the 1997 Economic Census Bridge Between SIC and NAICS.
b. NAICS 3251.
c. NAICS 3252.
d. NAICS 3253
e. NAICS 3254
Source: U.S. DOC, 1990-1997SBA;U.S. DOC, 1998-2009 SUSB
B.3.4 Employment and Productivity
Figure B-3 provides information on employment from the Annual Survey of Manufactures and Economic Census.
During the last two decades, with the exception of minor short-lived fluctuations, employment in the Basic
Chemicals and Resins and Synthetics segments generally declined. This decrease reflects the industry's
restructuring and downsizing efforts, which are intended to reduce costs in response to competitive challenges.
During the same time period, employment in the Pharmaceuticals segment fluctuated significantly, but began to
fall in 2002 and continued to do so almost steadily through 2010. The Pesticides and Fertilizers segment
experienced the least amount of fluctuation in employment but had fairly significant employment losses relative
to the small size of this segment. Between 1988 and 2010, only the Pharmaceuticals segment showed an overall
increase in industry employment of nearly 12 percent. The Pesticides and Fertilizers segment had the largest
overall reduction in employment of approximately 41 percent, with the Basic Chemicals and Resins and
May 2014
B-11
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Synthetics segments coming very close with 34 percent and 37 percent, respectively. During the last decade,
however, all four profiled segment saw significant declines in employment, possibly due to the industry's
restructuring and downsizing efforts.
Figure B-3: Employment for Profiled Chemicals and Allied Products Industry Segments3
u
w
£
Erf
220,000
200,000
180,000
160,000
140,000
120,000
100,000
80,000
60,000
40,000
20,000
— —— — ———————— t J t J t J tJ M M
'sc 's© O 's© O O O 's© 's© 'sc 'n£ o o o o o o o o o o o
« v*\„
—¦— Resins and Synthetics (NAICS
3252XX)
—¦— Resins and Synthetics (SIC to
NAICS)
• Pesticides and Fertilizers
(NAICS 3253XX)
—~-— Pesticides and Fertilizers (SIC
to NAICS)
—A— Basic Chemicals (SIC to
NAICS)
—*— Basic Chemicals (NAICS
3251XX)
—x— Pharmaceuticals (NAICS
3254XX)
—X— Pharmaceuticals (SIC to
NAICS)
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the SIC classification data to the NAICS code classifications using the 1997
Economic Census Bridge Between SIC and NAICS.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007
EC
Table B-6 presents the change in value added per labor hour, a measure of labor productivity, for each of the
profiled industry segments during 1988 through 2010. Productivity trends in each segment show considerable
volatility through the 1990s into the 2000s. For the Basic Chemicals segment, productivity gains during this early
period segment reflect firms" attempts to reduce costs by restructuring production and materials handling
processes in response to maturing domestic markets and increased global competition (S&P, 2001a). During 1988
through 2010, all four segments saw significant increases in productivity. Much of this growth occurred between
2000 and 2010, when productivity increased by 110 percent in the Basic Chemicals segment, 60 percent in the
Resins and Synthetics segment, 184 percent in the Pesticides and Fertilizers segment, and 33 percent in the
Pharmaceuticals segment. The complexity of the industry is increasing, requiring highly developed skills and
workers with better training and education. In addition, scientifically trained personnel - such as chemists,
chemical engineers, agronomists, toxicologists, and biologists - are in high demand. Increases in spending and
productivity for the chemical industry are not expected to reverse the loss in chemicals industry employment
(C&EN, 2010).
B-12
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Table B-6: Productivity Trends for Profiled Chemicals and Allied Products Industry Segments ($2011)
Year3
Basic Chemicals
Resins and Synthetics
Pesticides and Fertilizers
Pharmaceuticals
Prod.
Hours
(mill.)
Value Added/Hour
Prod.
Hours
(mill.)
Value Added/Hour
Prod.
Hours
(mill.)
Value Added/Hour
Prod.
Hours
(mill.)
Value Added/Hour
$/hr.
% Change
$/hr.
% Change
$/hr
%
Change
$/hr
% Change
1988
229
252
NA
166
195
NA
25
186
NA
133
365
NA
1989
228
274
8.6%
172
187
-4.6%
26
147
-21.1%
137
380
4.3%
1990
234
260
-5.0%
170
173
-7.1%
27
135
-7.8%
136
407
7.0%
1991
239
229
-1 1.8%
167
162
-6.6%
27
151
1 1.6%
134
437
7.4%
1992
240
229
0.0%
166
169
4.3%
26
143
-5.2%
146
419
-4.2%
1993
229
230
0.3%
164
168
-0.8%
25
135
-5.6%
147
427
1.9%
1994
212
254
10.4%
168
189
12.9%
26
200
47.9%
153
424
-0.7%
1995
214
279
9.9%
167
206
9.0%
26
228
14.1%
177
363
-14.4%
1996
220
237
-14.9%
156
199
-3.6%
25
241
5.6%
175
381
5.0%
1997
213
304
27.8%
156
211
6.2%
22
234
-2.8%
154
471
23.4%
1998
211
299
-1.4%
153
223
5.7%
22
244
4.3%
154
520
10.4%
1999
201
278
-7.2%
146
219
-2.0%
21
157
-35.7%
166
517
-0.6%
2000
204
252
-9.4%
146
205
-6.1%
19
146
-7.1%
178
502
-2.8%
2001
194
223
-1 1.6%
130
188
-8.6%
18
145
-0.9%
187
528
5.1%
2002
189
256
14.9%
130
195
3.7%
17
167
15.6%
189
593
12.3%
2003
188
277
8.3%
127
202
3.6%
17
180
8.0%
189
650
9.7%
2004
181
368
32.9%
119
266
31.9%
16
234
29.7%
183
664
2.1%
2005
175
451
22.7%
118
293
10.1%
15
256
9.3%
186
658
-1.0%
2006
170
497
10.1%
107
300
2.4%
14
205
-19.7%
186
675
2.6%
2007
169
465
-6.4%
127
260
-13.2%
15
387
88.5%
183
679
0.6%
2008
166
467
0.4%
117
216
-17.0%
16
582
50.3%
167
718
5.8%
2009
154
393
-15.7%
97
264
22.3%
16
445
-23.5%
162
722
0.5%
2010
153
528
34.3%
100
327
23.9%
16
414
-6.9%
163
668
-7.4%
1988-2010
-33.2%
109.7%
-39.6%
67.3%
-36.1%
122.9%
22.6%
83.2%
2000-2010
-24.9%
109.9%
-31.2%
59.3%
-15.7%
184.0%
-8.5%
33.0%
Average
Annual
Growth
Rate
-1.8%
3.4%
-2.3%
2.4%
-2.0%
3.7%
0.9%
2.8%
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the NAICS. For this analysis,
EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic Census Bridge Between NAICS and SIC.
Source: U.S. DOC. 1988-1991. 1993-1996. 1998-2001. 2003-2006. and 2008-2010 ASM; U.S. DOC. 1987. 1992. 1997. 2002. and 2007 EC
B.3.5 Capital Expenditures
The Chemicals and Allied Products Industry is relatively capital-intensive. According to the 2007Economic
Census, facilities in NAICS 325 had aggregate capital spending of approximately $16.7 billion in 2007. Capital-
intensive industries are characterized by large, technologically complex manufacturing facilities, which reflect the
economies of scale required to manufacture products efficiently. New capital expenditures are needed to
extensively modernize, expand, and replace existing capacity to meet growing demand. Table B-7 shows that all
four profiled Chemicals and Allied Products Industry segments experienced substantial increases in capital
expenditures through the 1990s. Much of the growth in capital expenditures was driven by investment in capacity
expansions to meet the increase in global demand for chemical products. Domestically, the continued substitution
of synthetic materials for other basic materials and rising living standards caused consistent growth in the demand
for chemical commodities (S&P, 2001a). Expenditures declined somewhat during the early 2000s due to a
weakening economy. Capital expenditures in the Basic Chemicals and Resins and Synthetics segments increased
during the middle of the last decade only to decline between 2008 and 2010. Capital expenditures in the
Pharmaceuticals segment overall declined throughout the latter half of the decade. Only the Pesticides and
Fertilizers segment saw an increase in capital expenditures over the entire period of analysis. Toward the end of
the last decade, the industry began to look towards new capital expenditure strategies for growth in the near
future, hoping to capitalize on long-term societal "megatrends," including increased use of renewable energy and
the need for improved food and water supplies (Jagger, 2009).
May 2014
B-13
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Table B-7: Capital Expenditures for Profiled Chemicals and Allied Products Industry Segments (in
millions, $2011)
Year3
Basic Chemicals
Resins and Synthetics
Pesticides and Fertilizers
Pharmaceuticals
Capital
Expenditures
Percent
Change
Capital
Expenditures
Percent
Change
Capital
Expenditures
Percent
Change
Capital
Expenditures
Percent
Change
1988
$6,036
NA
$3,976
NA
$307
NA
$3,191
NA
1989
$7,778
28.9%
$4 500
13.2%
$415
35.1%
$3,531
10.6%
1990
$8,593
10.5%
$5,213
15.8%
$372
-10.5%
$3,173
-10.1%
1991
$8,672
0.9%
$4 798
-7.9%
$632
70.1%
$3,482
9.8%
1992
$8 405
-3.1%
$3.73|
-22.2%
$764
20.9%
$4,554
30.8%
1993
$6 497
-22.7 %
;
18.5%
$486
-36.4%
$4,435
-2.6%
1994
$5,850
-9.9%
$4 591
3.8%
$473
-2.6%
$4,503
1.5%
1995
$7 789
33.1%
$4,3 32
-5.6%

8.5%
$4,983
10.7 %
1996
$9,535
22.4%
$3,794
-12.4%
$687
3.3.7%
$4 759
-4.5%
1997
$9 1 79
-3.7 %
$4 775
25.9%
$1,072
55.9%
$4 845
1.8%
1998
$9 054
-1.4%
$5,358
12.2%
$981
-8.5%
$4,400
-9.2%
1999
$8 024
-1 1.4%
$5,586
4.3%
$762
-22.3%
$4 702
6.9%
2000
$6 990
-12.9%
$3,542
-36.6%

-41.0%
$5 700
21.2%
2001
$6,203
-1 1.3%
$2 879
-18.7%
$423
-6.1%
$6 279
10.2%
2002
$5 207
-16.1%
$3,022
5.0%

-1.0%
$6,253
-0.4%
2003
$4,463
-14.3%
$2,088
-30.9%
$329
-21.3%
$6,186
-1.1%
2004
$4,833
8.3%
$2 259
8.2%
$321
-2.4%
$6,903
1 1.6%
2005
$5,176
7.1%
$2,835
25.5%
$346
7.6%
$5,349
-22.5%
2006
$6,048
16.8%
$2 824
-0.4%
$422
22.0%
$4 569
-14.6%
2007
$7,584
25.4%
$3,326
17.8%
$487
15.5%
$5,369
17.5%
2008
$6,300
-16.9%
$2,771
-16.7%
$847
73.7%
$3,752
-30.1%
2009
$6,138
-2.6%
$2 260
-18.4%
$1,038
22.6%
$2 965
-21.0%
2010
$5,339
-13.0%
$1,835
-18.8%
$673
-35.2%
$2,804
-5.4%
Total Percent
Change 1988 -
2010
-11.5%
-53.8%
118.9%
-12.1%
Total Percent
Change 2000 -
2010
-23.6%
-48.2%
49.6%
-50.8%
Average Annual
Growth Rate
-0.6%
-3.5%
3.6%
-0.6%
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the NAICS. For this analysis,
EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007EC
B.3.6 Capacity Utilization
Capacity utilization measures actual output as a percentage of total potential output given the available capacity.
Capacity utilization reflects excess or insufficient capacity in an industry and is an indication of whether new
investment is likely. To take advantage of economies of scale, chemical commodities are typically produced in
large facilities. Capacity additions in this industry are often made on a relatively large scale and can substantially
affect the industry's capacity utilization rates.
Figure B-4 presents capacity utilization from 1990 to 2011 for the entire Chemicals and Allied Products Industry
(NAICS 325). Capacity utilization for the industry fluctuated throughout the 1990s, dropping from 1990 through
1993, increasing gradually through 1997, and then dropping rapidly to alow of 72 percent in 2001. The next eight
years showed recovery, with increases in capacity utilization each year except during the recessions of 2001 and
2008. Following a period of consistent increases in capacity utilization, the Chemicals and Allied Products
Industry conserved cash by cutting capital spending by 20.1 percent at the beginning of the 2008 recession,
according to the American Chemistry Council (C&EN, 2010). Overall, between 1990 and 2011, capacity
utilization in the Chemicals and Allied Products Industry fell by 7 percent. As the U.S. economy recovers,
companies in the Chemicals and Allied Products Industry could still find themselves with significant excess
B-14
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
capacity, despite recent cuts in capacity investments, and may not return to making major investments until 2011
(C&EN, 2010).
Figure B-4: Capacity Utilization Rates for Profiled Chemicals and Allied Products Industry'
,a-b,c
- Chemical Manufacturing
(NAICS 325)
cccccccccc — — — — — — — — — — — —
cccccccccccc — — — — c — cc — —
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the
North American Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC
code classifications using the 1997 Economic Census Bridge Between NAICS and SIC.
b. Before 2007, U.S. Census sampled every industry in a specific NAICS6. Beginning in 2007, U.S. Census only sampled certain
industries within any NAICS6, and therefore, the data collected before 2007 cannot be directly compared to the data collected in
2007 and beyond.
c. Data are for NAICS 325: Chemical Manufacturing.
Source: Federal Resen'e Board of Governors, 2012a
B.4 Structure and Competitiveness
The Chemicals and Allied Products Industry continues to restructure and reduce costs in response to competitive
challenges, including global oversupply for commodities. In the early 1990s, the chemical industry's cost-cutting
came largely from restructuring and downsizing. The industry has taken steps to improve productivity, and
consolidated to cut costs. Companies seeking growth within these relatively mature industry segments have made
acquisitions to achieve production or marketing efficiencies. The Resins and Synthetics segment, for example,
experienced sizable consolidations in the late 1990s into 2000 (S&P, 2001a). In the most recent decade, there has
been a significant increase in trade activity for all profiled Chemicals and Allied Products Industry segments, with
particularly notable growth in imports of pesticides, fertilizers, and pharmaceutical products. Consolidation and
restructuring efforts have also been very strong since 2000, as global chemical merger and acquisition activity
climbed from $33 billion to $55 billion in 2005 to 2007 alone (Chang, 2008).
B.4.1 Firm Size
The Small Business Administration (SBA) defines small firms in the chemical industries according to the firm's
number of employees. Firms in the Basic Chemicals segment (325110, 325120, 325131, 328181, 325188, and
325199) and Resins and Synthetics (NAICS codes 325211, 325221, and 325222) are defined as small if they have
1,000 or fewer employees (except for NAICS 325211, for which the threshold is 750 or fewer employees). Firms
in the NAICS industry 325311 and 325312 of the Pesticides and Fertilizers segment are considered small if they
May 2014
B-15
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
have 1,000 or fewer and 500 or fewer employees, respectively. Firms in Pharmaceuticals (NAICS codes 325411
and 325412) are defined as small if they have 750 or fewer employees. The size categories reported in the
Statistics of U.S. Businesses (SUSB) do not correspond with the SBA size classifications, therefore preventing
precise use of the SBA size threshold in conjunction with SUSB data.
The SUSB data presented in Table B-8 show that in 2009, 953 of 1,178 firms in the Basic Chemicals segment had
less than 500 employees. Therefore, at least 81 percent of firms in this segment were classified as small. These
small firms owned 1068 facilities, or 52 percent of all facilities in the segment. In the Resins and Synthetics
Industry segment, 762 of 889 firms, or 86 percent, had less than 500 employees in 2009. These small firms owned
837 of 1,159 facilities (72 percent) in this segment. In the Pesticides and Fertilizers segment, 84 percent of firms
(149 of 177) had fewer than 500 employees, owning 67 percent of all facilities in that segment. And for the
Pharmaceuticals segment, 1,021 of the 1,170 firms (87 percent) had less than 500 employees, and these firms
accounted for 76 percent of the total number of facilities.
Table B-8 below shows the distribution of firms and facilities in the four profiled segments by the employment
size of the parent firm.
Table B-8: Number of Firms and Facilities by Firm Size Category for the Chemicals and Allied Products
Industry Segments, 2009

Basic Chemicals
Resins and Synthetics
Pesticides and Fertilizers
Pharmaceuticals

Number of
Number of
Number of
Number of
Number of
Number of
Number of
Number of
Year
Firms
Facilities
Firms
Facilities
Firms
Facilities
Firms
Facilities
0-I9
536
538
374
375
103
103
649
649
20-99
262
283
272
290
37
38
230
237
100-499
155
247
1 16
172
9
10
142
170
500+
225
972
127
322
28
74
149
336
Total
1,178
2,040
889
1,159
177
225
1,170
1,392
Source: U.S. DOC, 2009 SUSB
B.4.2 Concentration Ratios
Concentration is the degree to which industry output is concentrated in a few large firms. Concentration is
closely related to entry barriers with more concentrated industries generally having higher barriers.
The four-firm concentration ratio (CR4) and the Herfindahl-Hirschman Index (HHI) are common measures of
industry concentration. The CR4 indicates the market share of the four largest firms. For example, a CR4 of 72
percent means that the four largest firms in the industry account for 72 percent of the industry's total value of
shipments. The higher the concentration ratio, the less competition there is in the industry, other things being
equal.2"5 An industry with a CR4 of more than 50 percent is generally considered concentrated. The HHI indicates
concentration based on the largest 50 firms in the industry. It is equal to the sum of the squares of the market
shares for the largest 50 firms in the industry. For example, if an industry consists of only three firms with market
shares of 60, 30, and 10 percent, respectively, the HHI of this industry would be equal to 4,600 (602 + 302 + 102).
The higher the index, the fewer the number of firms supplying the industry and the more concentrated the
industry. Based on the U.S. Department of Justice's guidelines for evaluating mergers, markets in which the HHI
is under 1,000 are considered unconcentrated, markets in which the HHI is between 1,000 and 1,800 are
considered to be moderately concentrated, and those in which the HHI is in excess of 1,800 are considered to be
concentrated.
205 Hie measured concentration ratio and the HHF are very sensitive to how the industry is defined. An industry with a high concentration
in domestic production may nonetheless be subject to significant competitive pressures if it competes with foreign producers or if it
competes with products produced by other industries (e.g., plastics vs. aluminum in beverage containers). Concentration ratios based
on share of domestic production are therefore only one indicator of the extent of competition in an industry.
B-16
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Industry Profile
Of the profiled Chemicals and Allied Products segments, as shown in Table B-9, the following industry sub-
sectors were highly concentrated in 2007: Petrochemical Manufacturing (NAICS 325110), Noncellulosic Organic
Fiber Manufacturing (NAICS 325222), and Alkalies and Chlorine manufacturing (NAICS 325181). HHI and CH4
values indicated that Industrial Gas Manufacturing (NAICS 325120), Inorganic Dye and Pigment Manufacturing
(NAICS 325131), Medicinal and Botanical manufacturing (NAICS 325411), and Nitrogenous Fertilizer
Manufacturing (NAICS 325311) were all moderately concentrated. In contrast, Plastics Material and Resin
Manufacturing (NAICS 325211), Pharmaceutical Preparation Manufacturing (NAICS 325412), Other Basic
Inorganic Chemical Manufacturing (NAICS 325188), and Other Basic Organic Chemical Manufacturing (NAICS
325199) would be considered competitive. The diversity of products in some of the profiled industry segments,
however, makes generalizations about concentration less reliable than in industry segments with a more limited
product slate. That is, within a single NAICS code, the numbers of producers may vary substantially by individual
product - firms may possess relatively high market power in products with a smaller number of competing
producers even though the total NAICS code would appear to have a relatively low concentration. On the basis of
concentration information, some industry segments would therefore appear to be moderately concentrated;
accordingly, firms in these segments might possess a moderate degree of market power and thus the ability to pass
compliance costs through to customers as price increases. However, as discussed above and more specifically in
the following section, competition from foreign producers in both domestic and export markets, increasingly
restrains the discretionary pricing power of U.S. firms in the profiled industry segments.
May 2014
B-17
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Table B-9: Selected Ratios for SIC and NAICS Codes Within Profiled Chemicals and Allied Products
Industry Segments in 1987,1992, 1997, 2002, and 2007

Concentration Ratios
SIC (S) or

20 Firm
50 Firm
Herfindahl-
NAICS (N) Code
Year3
4 Firm (CR4)
8 Firm (CR8)
(CR20)
(CR50)
Hirschman Index
Basic Chemicals
S 2869
1987
31%
48%
68%
86%
376
1992
29%
43%
67%
86%
336

1997
60%
83%
98%
100%
1.187
N325110
2002
85%
94%
100%
100%
2.662

2007
80%
94%
100%
100%
2,535
S 2813
1987
77%
88%
95%
98%
1,538

1992
78%
91%
96%
99%
1,629

1997
64%
85%
96%
99%
1,223
N325120
2002
64%
82%
91%
99%
1,218

2007
68%
88%
98%
100%
1,415
S 2816
1987
64%
76%
94%
99%
1,550

1992
69%
79%
93%
99%
1,910
N 325131
1997
67%
79%
95%
100%
1,848
2002
69%
82%
96%
100%
1,704

2007
61%
77%
96%
100%
1,265
S 2812
1987
72%
93%
99%
100%
2,328
1992
75%
90%
99%
100%
1,994

1997
78%
92%
100%
100%
2,870
N325181
2002
73%
90%
100%
100%
1,786

2007
84%
96%
100%
100%
2,392
S 2819
1987
38%
49%
68%
84%
468
1992
39%
50%
68%
85%
677

1997
31%
42%
63%
82%
394
N325188
2002
21%
33%
56%
80%
217

2007
20%
33%
56%
79%
224
S 2869
1987
31%
48%
68%
86%
376
1992
29%
43%
67%
86%
336

1997
25%
38%
57%
80%
256
N325199
2002
22%
36%
57%
80%
238

2007
32%
43%
61%
80%
361
Resins and Synthetics
S 2821
1987
20%
33%
61%
89%
248
1992
24%
39%
63%
90%
284

1997
26%
39%
64%
89%
304
N325211
2002
32%
46%
68%
88%
443

2007
32%
47%
68%
85%
400
S 2823
1987
NA
100%
NA
NA
NA
1992
98%
NA
NA
NA
NA

1997
100%
NA
NA
NA
NA
N325221
2002
93%
NA
NA
NA
NA

2007
89%
99%
100%
NA
NA
S 2824
1987
76%
92%
98%
100%
2,403
1992
74%
90%
98%
100%
2,158

1997
69%
87%
98%
100%
1,708
N 325222
2002
57%
82%
96%
100%
1,262

2007
70%
81%
93%
99%
2,071
Pesticides and Fertilizers
S 2873
1987
33%
55%
82%
97%
486
1992
48%
67%
91%
99%
792

1997
54%
76%
94%
99%
903
N 325311
2002
54%
79%
95%
98%
977

2007
61%
83%
92%
97%
1,136
S 2874
1987
48%
74%
98%
99%
880
1992
62%
83%
98%
99%
1,528
B-18
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Table B-9: Selected Ratios for SIC and NAICS Codes Within Profiled Chemicals and Allied Products
Industry Segments in 1987,1992, 1997, 2002, and 2007

Concentration Ratios
SIC (S) or

20 Firm
50 Firm
Herfindahl-
NAICS (N) Code
Year3
4 Firm (CR4)
8 Firm (CR8)
(CR20)
(CR50)
Hirschman Index

1997
71%
88%
99%
100%
1,675
N325312
2002
78%
93%
100%
100%
1,853

2007
83%
93%
98%
100%
NA
Pharmaceuticals
S 2833
1987
72%
80%
89%
95%
2,588
1992
76%
84%
91%
97%
2,999

1997
62%
73%
85%
93%
2.059
N 325411
2002
64%
73%
83%
92%
2.704

2007
54%
61%
75%
87%
1,424
S 2834
1987
22%
36%
65%
88%
273
1992
26%
42%
72%
90%
341

1997
36%
50%
71%
89%
462
N 325412
2002
36%
53%
76%
89%
530

2007
35%
54%
76%
90%
457
a. Before 1997, data were compiled in the SIC system; since 1997, these data have been compiled in the NAICS system. For this analysis, EPA converted
the NAICS classification data to the SIC code classifications using the 1997 Economic Census Bridge Between NAICS and SIC.

Source: U.S. DOC, 1987, 1992, 1997, 2002, and 2007EC

B.4.3 Foreign Trade
The Chemicals and Allied Products Industry is one of the largest exporters in the United States. In fact, U.S.
manufacturers produce 19 percent of the world's chemicals, more than any other country (ACC, 2009).
This profile uses two measures of foreign competition: export dependence and import penetration.
Import penetration measures the extent to which domestic firms are exposed to foreign competition in domestic
markets. Import penetration is calculated as total imports divided by total value of domestic consumption in that
industry: where domestic consumption equals domestic production plus imports minus exports. Theory suggests
that higher import penetration levels will reduce market power and pricing discretion because foreign competition
limits domestic firms" ability to exercise such power. Firms belonging to segments in which imports account for a
relatively large share of domestic sales would therefore be at a relative disadvantage in their ability to pass-
through costs because foreign producers would not incur costs as a result of the final rule. The estimated import
penetration ratio for the entire U.S. manufacturing sector (NAICS 31-33) for 2010 is 28 percent. For
characterizing the ability of industries to absorb compliance cost burdens, EPA judges that industries with import
ratios close to or above 28 percent would more likely face stiff competition from foreign firms and thus be less
likely to succeed in passing compliance costs through to customers.
Export dependence, calculated as exports divided by value of shipments, measures the share of a segment's sales
that is presumed subject to strong foreign competition in export markets. The final rule would not increase the
production costs of foreign producers with whom domestic firms must compete in export markets. As a result,
firms in industries that rely to a greater extent on export sales would have less latitude in increasing prices to
recover cost increases resulting from regulation-induced increases in production costs. The estimated export
dependence ratio for the entire U.S. manufacturing sector for 2010 is 22 percent. For characterizing the ability of
industries to absorb compliance cost burdens, EPA judges that industries with export ratios close to or above 22
percent are at a relatively greater disadvantage in potentially recovering compliance costs through price increases
since export sales are presumed subject to substantial competition from foreign producers.
Table B-10 presents trade statistics for each of the profiled Chemicals and Allied Products Industry segments.
Both export dependence and import penetration experienced increases in each of these segments between 1990
and 2010.
May 2014
B-19
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Industry Profile
Globalization of markets has become a key factor in the Basic Chemicals segment, with both import penetration
and export dependence growing substantially over the 21 -year analysis period - imports more than quadrupled and
exports nearly doubled. The greater growth in imports underscores the increasing competition from foreign
producers in domestic and world markets.
Increased globalization has also affected the Resins and Synthetics segment. Imports and exports of resins and
synthetics have increased significantly over the 21 -year analysis period, reflecting the continued growth in the
global market. As with the Basic Chemical segment, this segment has shown substantial overall increases in
values of imports and exports with total growth of 218 percent and 141 percent, respectively during the last two
decades. Import penetration grew more quickly than export dependence in this segment due to declining export
opportunities and increased foreign competition in domestic markets. Nevertheless, the United States remained a
net exporter of resins and synthetics, despite these trends. The market for pesticides and fertilizers has also
become increasingly competitive. Significant capacity expansions for pesticides and fertilizers worldwide
increased competition in domestic markets from imports and began to limit export opportunities for U.S.
producers. Through 1999, the segment still exported more than it imported. However, this balance recently
changed as imports exceeded exports from 2000 through 2010. From 1990 through 2010, imports in the profiled
Pesticides and Fertilizers segment grew by 446 percent, while exports declined 2 percent. The Pharmaceuticals
segment had by far the largest surge in trade activity over the observed period, with imports growing over
fourteen-fold, and exports increasing by 578 percent.
In 2010, import penetration ratios in the Basic Chemicals and Resins and Synthetics segments were 24 and 18
percent respectively, compared to 28 percent reported for the U.S. manufacturing industry as a whole. Therefore,
neither of these two profiled segments faces strong competition from foreign firms in U.S. markets. At the same
time, the import penetration ratio was 46 percent for the Pesticides and Fertilizers segment and 41 percent for the
Pharmaceuticals segment, suggesting that businesses in these segments do face strong competition from foreign
firms in the U.S. markets. Further, between 1990 and 2010 import penetration ratios for all profiled segments rose
significantly, which could indicate that foreign firms have begun aggressive pursuit of these U.S. markets.
In 2010, the export dependence ratio was 24 percent for the Basic Chemicals segment, 35 percent for the Resins
and Synthetics segment, 26 percent for the Pesticides and Fertilizers segment, and 23 percent for the
Pharmaceuticals segment compared to 22 percent reported for the U.S. manufacturing industry as a whole.
Therefore, all 4 segments likely face significant competitive pressure in retaining their positions in the foreign
markets. Further, for all profiled chemical industry segments except Pesticides and Fertilizers, export dependence
has been, for the most part, steadily increasing during the last two decades. All profiled segments except
Pharmaceuticals were affected by the economic recession and experienced declines in export dependence, either
in 2009 or 2010. Given these levels of exposure to competition from foreign firms in domestic and export
markets, the profiled chemicals industry segments likely have limited discretionary power to recover compliance
costs expected to be incurred as the result of the Final Existing Facilities Regulation through price increases.
Recent trends in international chemicals markets imply that U.S. producers in the profiled Chemicals and Allied
Products Industry will continue to face strong competition from foreign producers. However, trade is also
expected to play an important role in industry growth as increased importance is given to bilateral and multilateral
trade agreements. Free Trade Area of the Americas (FTAA) and other free trade agreements with Chile and
Vietnam offer U.S. chemical companies the opportunity to expand exports to these regions/countries. Trade
barriers such as higher tariff rates are falling in many countries as a result of commitment to the Chemical Tariff
Harmonization Agreement. These developments are favorable for increasing exports from the United States. At
the same time, industry exposure to fluctuations in regional and global economic conditions is on the rise due to
the increasing share of imports in domestic consumption (AllBusiness, 2009).
B-20
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Table B-10: Trade Statistics for Profiled Chemicals and Allied Products Industry Segments ($2011)

Value of
Value of
Value of
Implied

Imports
Exports
Shipments
Domestic
Import
Export
Year3
(millions)
(millions)
(millions)
Consumptionb
Penetration0
Dependence"1
Basic Chemicals
I 990
$15,441
$20,508
$124,294
$119,228
13%
16%
I 991
74
$20,967
$117,809
$112,416
14%
18%
I 992
3,16 040
$20,749
$117,788
$113,079
14%
18%
I 993

$20,173
$112,509
$108 056
15%
18%
1994
$18.1 38
$22,632
$115,449
J55
16%
20%
1995
$21,385
$27,370
$123,043
>57
18%
22%
1996
3,22 642
$25,688
$121,005
J58
19%
21%
1997
3,24 848
$29,499
$134,988
$130,337
19%
22%
I 998
$24,6 38
$26,801
$125,634
$123,471
20%
21%
I 999
3,26.2 51
$27,082
$122,779
$121,949
22%
22%
2000
3,11.447
$30,289
$129,120
$130,279
24%
23%
200I
$30,440
$28,994
$114,750
$1 16.197
26%
25%
2002
$29,583
$27,963
$117,399
>20
25%
24%
2003
$32,591
$31,448
$130,321
463
25%
24%
2004
$37,528
$36,242
$155,373
'>60
24%
23%
2005
79
$37,929
$175,705
$181 955
24%
22%
2006
•45
$42,922
$196,275
$198 937
23%
22%
2007
$48 587
$46,853
$213,699
$215.433
23%
22%
2008
$58 210
$50,991
$224,141
$2 >1.360
25%
23%
2009
$39,297
$39,790
$161,039
$160,545
24%
25%
2010
$49,033
$49,355
$205,476
$205,154
24%
24%
Total Percent Change 1990-2010
217.5%
140.7%
65.3%
72.1%
Total Percent Change 2000-2010
55.9%
63.0%
59.1%
57.5%
Average Annual Growth Rate
6%
4%
3%
3%
Resins and Synthetics
1990
$4,163
$12,377
$69,353
$61,139
7%
18%
1991
'>4
$13,751
$63,852
$54 165
8%
22%
1992
>6
$12,550
$65,362
$57,418
8%
19%
1993
$5,5 30
$12,436
$64,923
$58 018
10%
19%
1994
$6 799
$14,210
$71,854
$64 443
1 1%
20%
1995
$7 902
$17,247
$79,858
$70,513
1 1%
22%
1996
$7,898
$17,312
$73,987
$64,573
12%
23%
1997
$8,280
$17,420
$78,045
$68 904
12%
22%
1998
$8,397
$16,206
$76,615
$68 805
12%
21%
1 999
$8 704
$15,942
$75,600
$68,362
13%
21%
2000
$9 898
$18,330
$79,985
$71,553
14%
23%
2001
$9.31 5
$16,854
$69,747
$62,209
15%
24%
2002
$9,3 50
$17,071
$68,288
$60,568
15%
25%
2003
$10,343
$17,989
$70,662
$63,016
16%
25%
2004
53
$21,153
$79,387
$69 887
17%
27%
2005
20
$23,564
$94,417
$85,373
17%
25%
2006
48
$26,164
$95,972
$84 856
18%
27%
2007
)9
$29,386
$99,283
$84 196
17%
30%
2008
18
$31,122
$94,876
$78,272
19%
33%
2009
$9,839
$24,619
$68,307
$53,528
18%
36%
2010
$12,794
$31,415
$88,526
$69,905
18%
35%
Total Percent Change 1990-2010
207.3%
153.8%
27.6%
14.3%
Total Percent Change 2000-2010
29.3%
71.4%
10.7%
-2.3%
Average Annual Growth Rate
6%
5%
1%
1%
Pesticides and Fertilizers
1990
$1,839
$4,084
$12,157
$9,912
19%
34%
1991
'>2
$4 581
$12,456
538
17%
37%
1 992
75
$3,586
$11,110
199
18%
32%
1 993
53
$2,680
$10,302
576
20%
26%
1994
$2,150
$3,891
$12,539
799
20%
31%
1995
$2,250
$4,508
$13,589
$1 1.331
20%
33%
1 996
$2,208
$4,240
$13,714
$1 1.681
19%
31%
May 2014
B-21
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Table B-10: Trade Statistics for Profiled Chemicals and Allied Products Industry Segments ($2011)
Year3
Value of
Imports
(millions)
Value of
Exports
(millions)
Value of
Shipments
(millions)
Implied
Domestic
Consumption6
Import
Penetration0
Export
Dependence"1
I997
$3.1 14
$4,201
$12.6.39
$1 1.552
27%
3.3%
1998
$3.1 18
$4,43 3
$12,379
>64
28%
.36%
1999
$2 961
$3,978
$9 944
J28
3.3%
40%
2000
3,3.4 57
$3,051
$9 126
$9,533
.36%
3.3%
200I
$3,992
$2,739
$8.51 1
764
41%
32%
2002
$3,2 36
$2,684
$8 829
$9,380
34%
.30%
2003
$4,743
$2,932
$9 917
$1 1.728
40%
.30%
2004
3-5 595
$3,183

586
41%
28%
2005
3,7.520
$3,430
$1 1.402
493
49%
.30%
2006
$6.80.3
$3,354
$10,118
566
50%
3.3%
2007
$8,782
$3,695
$14,660
747
44%
25%
2008
')()
$7,739
$20,143
$26 464
53%
.38%
2009
$6,302
$4,004
$16,293
$18,591
34%
25%
2010
$10,040
$4,171
$16,100
$21,969
46%
26%
Total Percent Change 1990-2010
446.0%
2.1%
32.4%
121.6%
Total Percent Change 2000-2010
190.4%
36.7%
76.4%
130.5%
Average Annual Growth Rate
9%
0%
1%
4%
Pharmaceuticals
1990
$5,467
$5,154
$77,532
$77,845
7%
7%
1991
$6,6 32
$5,596
$82,271
$83,307
8%
7%
1992
$7 742
$6,572
$85,466
$86,636
9%
8%
1993
$7 681
$6,693
$87,026
$88 015
9%
8%
1994
$8,5 30
$6,797
$89,759
$91 492
9%
8%
1995
$10614
$6,834
$92,570
$96,350
1 1%
7%
1996
)9
$7,466
$97,745
$103,878
13%
8%
1997
>3
$11,306
$105,316
$1 1 1.773
16%
1 1%
1998
$22 6 58
$13,191
$117,210
378
18%
1 1%
1 999
$29,398
$15,081
$123,989
305
21%
12%
2000
$35,420
$17,204
$128,852
$147,067
24%
13%
2001
$40.3.38
$19,734
$139,526
$160,130
25%
14%
2002
$47,727
$19,637
$154,403
$182,493
26%
13%
2003
$56 618
$22,804
$161,340
$195 155
29%
14%
2004
$59 0 50
$26,594
$160,883
$193,339
31%
17%
2005
$60,395
$26,941
$162,456
$195 910
31%
17%
2006
$67 796
$28,532
$168,059
$207,323
3.3%
17%
2007
$72 120
$29,885
$164,545
$206,780
35%
18%
2008
$78,360
$32,020
$163,216
$209,556
37%
20%
2009
$79,310
$33,976
$158,057
$203,390
39%
21%
2010
$80,879
$34,928
$152,052
$198,002
41%
23%
Total Percent Change 1990-2010
1379.4%
577.7%
96.1%
154.4%
Total Percent Change 2000-2010
228.3%
203.0%
118.0%
134.6%
Average Annual Growth Rate
14%
10%
3%
5%
a. Before 1997, data were compiled in the SIC system; since 1997, these data have been compiled in the NAICS system. For this analysis, EPA
converted the NAICS classification data to the SIC code classifications using the 1997 Economic Census Bridge Between NAICS and SIC.
b. Calculated by EPA as shipments + imports - exports.
c. Calculated by EPA as imports divided by implied domestic consumption.
d. Calculated by EPA as exports divided by shipments.
Source: U.S. ITC, 1989-2010
B-22
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Industry Profile
Figure B-5: Value of Imports arid Exports for Profiled Chemicals and Allied Products Industry Segments3
Basic Chemicals
a

•a

«
o
V.
r-l
+»
•—

'¦*-

S60,000
S55,000
S50.000
S45,000
S40,000
S35,000
S30,000
S25.000
S20.000
S15,000
S10,000
T 1 1 1 1 1 1 1 1 1-
^ ^ 'o © ©
© — N>
9 W ^ W o o
o © © © © ©
© — M '+i .u 'J\
¦* Exports (NAICS 3252XX)
*—Imports (NAICS 3252XX)
May 2014
B-23
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Figure B-5: Value of Imports and Exports for Profiled Chemicals and Allied Products Industry Segments3
Pesticides and Fertilizers
Pharmaceuticals
— S15,000
£ S13,000
o
s S11,000
S ~ S9,000
C3 o
» N
fc ^ S7,000
S5,000
S3,000
SI,000
—~— Exports (SIC to NAICS)
—A— Imports (SIC to NAICS)
-t Exports (NAICS 3253XX)
-k Imports (NAICS 3253XX)
hi

o
o
o
o
o
o
o
_

00
o
o
S90,000
a
§ $80,000
—~—Exports (SIC to NAICS) —»—Exports (NAICS 3254XX)
—a— Imports (SIC to NAICS) —*—Imports (NAICS 3254XX)
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American Industry
Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic
Census Bridge Between NAICS and SIC.
Source: U.S. ITC, 1989-2011

&
fl

«
o

O
o
o
O
o

oe
o
o
$70,000
$60,000
$50,000
$40,000
$30,000
$20,000
_
_
_
_
_
_
_
_
_
_

•o
•o

•o

¦u

©s
<1
00
'sS
©

4*.

B.5 Financial Condition and Performance
The financial performance and condition of the chemical industry are important determinants of its ability to
absorb the costs of regulatory compliance without material, adverse economic/financial impact. To provide
B-24
May 2014
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Industry Profile
insight into the industry's financial performance and condition, EPA reviewed two key measures of financial
performance over the period 1988 to 2012: net profit margin and return on total capital. EPA calculated these
measures using data from the Quarterly Financial Report for Manufacturing, Mining, and Trade Corporations
(QFR) published by the U.S. Census Bureau. Financial performance in the most recent financial reporting period
(2012) is obviously not a perfect indicator of conditions at the time of regulatory compliance. However,
examining the trend, and deviation from the trend, through the most recent reporting period gives insight into
where the industry may be, in terms of financial performance and condition, at the time of compliance. In
addition, the volatility of performance against the trend, in itself, provides a measure of the potential risk faced by
the industry in a future period in which compliance requirements are faced: all else equal, the more volatile the
historical performance, the more likely the industry may be in a period of relatively weak financial conditions at
the time of compliance.
Net profit margin is calculated as after-tax income before nonrecurring gains and losses as a percentage of sales
or revenues, and measures profitability, as reflected in the conventional accounting concept of net income. Over
time, the firms in an industry, and the industry collectively, must generate a sufficient positive profit margin if the
industry is to remain economically viable and attract capital. Year-to-year fluctuations in profit margin stem from
several factors, including: variations in aggregate economic conditions (including international and U.S.
conditions), variations in industry-specific market conditions (e.g., short-term capacity expansion resulting in
overcapacity), or changes in the pricing and availability of inputs to the industry's production processes (e.g., the
cost of energy to the chemical process). The extent to which these fluctuations affect an industry's profitability, in
turn, depends heavily on the fixed vs. variable cost structure of the industry's operations. In a capital intensive
industry such as the chemical and allied products industry, the relatively high fixed capital costs as well as other
fixed overhead outlays, can cause even small fluctuations in output or prices to have a large positive or negative
affect on profit margin.
Return on total capital is calculated as annual pre-tax income divided by the sum of current portion of long-term
debt due in 1 year or less, long-term debt due in more than 1 year, all other noncurrent liabilities and total
stockholders' equity (total capital). This concept measures the total productivity of the capital deployed by a firm
or industry, regardless of the financial source of the capital (i.e., equity, debt, or liability element). As such, the
return on total capital provides insight into the profitability of a business' assets independent of financial structure
and is thus a "purer" indicator of asset profitability than return on equity. In the same way as described for net
profit margin, the firms in an industry, and the industry collectively, must generate over time a sufficient return on
capital if the industry is to remain economically viable and attract capital. The factors causing short-term variation
in net profit margin will also be the primary sources of short-term variation in return on total capital.
Figure B-6 presents net profit margin and return on total capital for public-reporting firms in two chemical
industry segments - (1) Basic Chemicals, Resins, and Synthetics Manufacturing, which covers profiled segments
Basic Chemicals and Resins and Synthetics and (2) Pharmaceuticals and Medicines Manufacturing - from 1988
through 2012. Figure B-6 also presents net profit margin and return on total capital for public-reporting firms in
Other Chemicals segment - from 1992 through 2012.206 The first segment corresponds approximately to the
profiled Basic Chemicals and Resins and Synthetics industry segments; the second segment corresponds
approximately to the profiled Pharmaceuticals industry segment; and the third segment corresponds to the profiled
Pesticides and Fertilizers industry segment. The financial performance information reported in Figure B-6
confirms the trends and performance discussed above in this section.
206 For the Other Chemicals QFR segment, which includes the profiled Pesticides and Fertilizers segment, QFR data are available only
since 1992. In addition to NAICS 3253: Pesticide, Fertilizer, and Other Agricultural Chemical Manufacturing, which corresponds to
the profiled Pesticides and Fertilizers segment, the QFR Other Chemicals segment includes NAICS 3255: Paint, Coating, and
Adhesive Manufacturing; NAICS 3256: Soap, Cleaning Compound, and Toilet Preparation Manufacturing, and NAICS 3259: Other
Chemical Product and Preparation Manufacturing.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Industry Profile
As shown in Figure B-6, the Basic Chemicals and Resins and Synthetics segments have seen moderate volatility
of financial performance over the analysis period. Return on total capital moved off a post-recession low near -3
percent in 1992 to achieve levels of 7 to 10 percent during 1995-1997. Recovery of demand accompanied by
industry restructuring and downsizing accounted for the upturn in performance. During the latter part of the 1990s
decade, though, increased competition from foreign producers and demand weakness in Asian markets eroded this
performance. As a result, return on capital fell gradually through 2000. In 2001, a series of factors - high energy
and raw material prices at the start of the year, overcapacity, the terrorist attacks, and slowing U.S. and global
economies at the end of the year - led to a further sharp decline in return on capital performance of approximately
percent to less than one percent. Starting in 2002, however, return on total capital showed steady improvement,
increasing to nearly 10 percent by 2005 and then leveling out prior to the economic recession of 2008. Net profit
margin shows a similar, though less volatile, trend, with declines in 2000 through 2001, followed by steady
improvement between 2002 and 2005. In 2005, net profit margin reached a peak value of 6.6 percent, before
dipping in 2008 along with the general trend of the economy. In 2009 and 2010, both net profit margin and return
on total capital rose as the economy recovered. Return on total capital continued to rise steeply in 2011, followed
by a decline in 2012, while net profit margin increased at a slower rate in 2011 and again in 2012.
The same factors largely influenced performance in the Pharmaceuticals and Medicines Manufacturing segment
over the 21 -year period. Performance in this segment was stronger than that in the other industry segments and
followed a less volatile pattern. Net profit margins rose from a low near 12 percent in 1993 to a peak of 15.9
percent in 1998. Since then, performance trended down to reach a low of approximately 14 percent in 2000. This
segment achieved steady, though moderate improvement during 2002 to 2004, and then rose rapidly to reach a
period high level of 21.7 percent in 2008. Return on total capital again shows a similar, though more volatile,
trend compared to net profit margin. In 2009, both net profit margin and return on total capital continued to rise,
only to be followed by relatively sharp declines in 2010. In 2011, net profit margin and return on total capital
increased. In 2012, return on total capital declined while net profit margin continued to rise, though slightly.
The Other Chemicals segment, which includes the profiled Pesticides and Fertilizers segment, was susceptible to
the same economic influences mentioned in the previous two paragraphs. The financial performance of this
segment was more volatile than the Pharmaceutical segment but more stable than the Basic Chemicals segment.
Both the net profit margin and return on total capital for this segment followed a similar pattern: performance was
extremely transient for the first decade, peaking in 1996 and then falling sharply until 2001. In the 2000s decade,
the financial health of this industry was much more stable and has been rising since 2001, with the exception of
2005. However, current levels of performance still have not reached the same peak level they rose to in 1996.
Both net profit margin and return on total capital declined in 2009, but performance improved slightly in 2010.
Net profit margin began to decline in 2011, while return on total capital did not decline until 2012.
Overall, the majority of profiled segments of the chemical industry were not greatly affected by the recent
economic downturn. The Basic Chemicals and Resins and Synthetics segments were most affected, with steep
declines into 2008, but have since recovered.
B-26
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Figure B-6: Net Profit Margin and Return on Total Capital for the Chemicals and Allied Products Industry Segments
Basic Chemicals, Resins, and Synthetics Manufacturing
20%
18%
15%
13%
10%
8%
5%
3%
0%
-3%
-5%
—~— Net Profit Margin —*— Return on T otal Capital
Pharmaceuticals and Medicines Manufacturing
35%
30%
25%
20%
15%
10%
5%
0%
—~— Net Profit Margin —*— Re turn on T otal Cap ital
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Figure B-6: Net Profit Margin and Return on Total Capital for the Chemicals and Allied Products Industry Segments
Other Chemicals Manufacturing (Incl. Pesticides and Fertilizers)
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%
—«— Net Profit Margin —±— Return on T otal Capital
Source: U.S. DOC, 1988-2012 OFR
B.6 Facilities Operating Cooling Water Intake Structures
Section 316(b) of the Clean Water Act applies to point source facilities that use or propose to use a cooling water
intake structure that withdraws cooling water directly from a surface waterbody of the United States. In 1982, the
Chemicals and Allied Products Industry withdrew 2,797 billion gallons of cooling water, accounting for
approximately 3.6 percent of total industrial cooling water intake in the United States.2"7 The industry ranked 2nd
in industrial cooling water use behind the electric power generation industry (U.S. DOC, 1982).
This section provides information for facilities in the profiled chemical and allied products segments estimated to
be subject to regulation under the final rule and other options EPA considered. Existing facilities that meet the
following conditions are potentially subject to regulation:
> Have a National Pollutant Discharge Elimination System (NPDES) permit or are required to obtain one;
> Use or propose to use one or more cooling water intake structures to withdraw water from waters of the
United States;
> Use at least twenty-five (25) percent of the water withdrawn exclusively for contact or non-contact
cooling purposes; and
> Meet the specific applicability coverage criteria for the final rule and other options EPA considered in
terms of design intake flow (i.e., two mgd).
The regulatory analysis options also cover substantial additions or modifications to operations undertaken at such
facilities. EPA initially identified the set of facilities that were estimated to be potentially subject to the 316(b)
207 Data on cooling water use are from the 1982 Census of Manufactures. 1982 was the last year in which the Census of Manufactures
reported cooling water use.
B-28
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Indus try Profile
Existing Facilities Regulation based on a minimum applicability threshold of two mgd; this section focuses on
these facilities for the Chemicals and Allied Products segment.2"8
B.6.1 Waterbody and Cooling System Type
Table B-ll shows the distribution of facilities by type of waterbody and cooling water intake system.
Table B-11: Number of Facilities Estimated Subject to the 316(b) Existing Facilities Regulation by
Waterbody Type and Cooling Water Intake System for the Chemicals and Allied Products Industry
Waterbody Type
Recirculating
Combination
Once-Through
Other
Total
No.
% of Total
No.
% of Total
No.
% of Total
No.
%of
Total
Fstuarv/ Tidal River
0
0%
13
36%
3
3%
0
0%
16
()cean
0
0%
0
0%
9
10%
0
0%
9
I ,ake/Reservoir
4
12%
6
17%
4
5%
0
0%
15
Freshwater River/ Stream'1
30
88%
17
47%
62
68%
10
70%
119
Great Fake
0
0%
0
0%
13
14%
4
30%
17
Total"
35
20%
36
21%
91
52%
14
8%
175
a. Four freshwater facilities" cooling water intake system types are unknown.
b. Individual numbers may not add to total due to independent rounding.
Source: U.S. EPA, 2000; U.S. EPA analysis for this report
B.6.2 Facility Size
The facilities in the Chemicals and Allied Products Industry that that EPA expects to be subject to regulation
under the final rule and other options EPA considered are relatively large, with the vast majority of facilities
employing more than 100 employees. Figure B-7 shows the number of facilities in the profiled chemical segments
by employment size category.
Figure B-7: Number of Facilities Estimated Subject to the 316(b) Existing Facilities Regulation by Employment
Size for the Profiled Chemicals and Allied Products Industry
5:

13
¦TT
1

4.
1
3
1
5
N
29
n
Less than 100-249 250-499 500-999 1000 and
100 greater
Source: U.S. EPA, 2000; U.S. EPA analysis for this report
B.6.3 Firm Size
EPA used the Small Business Administration (SBA) small entity size standards to determine the number of
facilities in the three profiled chemical segments that are owned by small firms. Firms in the Basic Chemicals
208 EPA applied sample weights to the sampled facilities to account for non-sampled facilities and facilities that did not respond to the
survey. For more information on EPA's 2000 Section 316(b) Industry Survey, please refer to the Information Collection Request (U.S.
EPA, 2000).
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix B: Chemicals Industry Profile
segment (NAICS codes 325110, 325120, 325131, 325181, 325188, and 325199), firms in the Resins and
Synthetics sector (NAICS codes 325221, and 325222), and firms in the Pesticides and Fertilizer segment (NAICS
code 32311) are defined as small if they have 1,000 or fewer employees except firms in NAICS 32521 as well as
firms in the Pharmaceutical segment (NAICS codes 325411 and 325412), which are defined as small if they have
750 or fewer employees; remaining firms in the Pesticides and Fertilizer segment (NAICS 325312) are defined as
small if they have 500 or fewer employees. EPA estimates that 26 small entity-owned facilities and 154 large
entity-owned facilities in the Chemical segment will be subject to the 316(b) Existing Facilities regulation.209
209 EPA did not have sufficient survey data to determine the size of entities owning four facilities. EPA assumed these facilities to be
small entity-owned facilities in order to not understate the effect of this rule on small entities.
B-30
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Indus try Profile
Appendix C Profile of Food and Kindred Products Industry
C.1 Introduction
EPA's Detailed Industry Questionnaire, hereafter referred to as the DQ, identified five 4-digit SIC codes in the
Food and Kindred Products manufacturing industry (SIC 20) with at least one existing facility that operates a
CWIS, holds a NPDES permit, withdraws at least two million gallons per day (mgd) from a water of the United
States, and uses at least 25 percent of its intake flow for cooling purposes (facilities with these characteristics are
hereafter referred to as "facilities potentially subject to the 316(b) Existing Facilities regulation" or "regulated
facilities"). For the purpose of this analysis, EPA identified a six-digit NAICS code for each of these potential
facilities using the information from DQ and public sources (see Appendix J: Mapping Manufacturers Standard
Industrial Classification (SIC) Codes to North American Industry Classification System (NAICS) Codes). As the
result of this mapping, EPA identified five 6-digit NAICS codes in the Food and Kindred Products manufacturing
industry (NAICS 322).
For each of these five analyzed 6-digit NAICS codes, Table C-1 following page, provides a description of the
industry segment, a list of primary products manufactured, the total number of detailed questionnaire respondents
(weighted to represent a national total of facilities that hold a NPDES permit and operate cooling water intake
structures (CWIS)), and the number of facilities estimated to be potentially subject to the section final rule based
on the minimum withdrawal threshold of two mgd (see Chapter 1: Introduction for more details on the final rule
applicability criteria). Although the respondent DQs fall in only five of the 48 four-digit SIC codes that map onto
52 NAICS codes within the Food and Kindred Products Industry, EPA knows of no basis to exclude any of the
remaining four-digit SIC codes (or six-digit NAICS codes) from consideration in this profile. Accordingly, this
profile focuses on the entirety of SIC 20 that map onto NAICS 311/3121, Food and Kindred Products.
Table C-1: Existing Facilities in the Food and Kindred Products Industry (NAICS 311/3121)
NAICS
NAICS
Description
Important Products Manufactured
Number of
Regulated Facilities
311221
Wet com
milling
Com oil cake and meal; com starch; com syrup; dextrose, fructose; glucose; high
fructose syrup; starches
14
311312
Cane sugar
refining
Cane sugar; molasses; granulated sugar; raw sugar; cane syrup (all made from
sugarcane); molasses, blackstrap; granulated sugar; refined sugar; syrup (all
made from purchased raw cane or sugar syrup)
14
311313
Beet sugar mfg
Beet sugar; molasses; granulated sugar; liquid sugar; powdered sugar; syrup (all
made from sugar beets)
7
312140
Distilleries
Distilled and blended liquors, except brandy; gin; rum; vodka; whiskey;
cocktails; cordials; eggnog; grain alcohol for medicinal and beverage purposes
3

Total NAICS 311/3121a
37
a. Individual numbers may not add up to total due to independent rounding.
Source: Executive Office of the President, 1987; U.S. EPA, 2000; U.S. EPA analysis for this report
The Food and Kindred Products Industry includes facilities that process or manufacture food and beverages for
human consumption, feed for animals, and other related products. Statistics for the industry were previously
recorded under the Standard Industry Classification (SIC) code of 20, for Food and Kindred Products. SIC 20
included nine industry groups at the three-digit SIC level, and 48 industries at the four-digit SIC level. Under the
SIC system, beverage manufacturing was included in SIC 20, the Food and Kindred Products sector. In 1997, the
U.S. Census Bureau began reporting economic activity in the North American Industry Classification System
(NAICS), which replaced the SIC system (U.S. DOC, 1997). Under NAICS, the previous SIC 20 sector is
recorded in one 3-digit NAICS sector (NAICS 311) and one 4-digit NAICS sector (NAICS 3121), Beverage
Manufacturing. Because the analysis period for this profile extends across the SIC-to-NAICS transition, most of
the data series presented in the profile include data both the SIC and NAICS frameworks: in general, for years
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Indus try Profile
prior to 1997, data are in the SIC framework; for 1997 and after, data are in the NAICS framework. Table C-2
summarizes the relationship between SIC and NAICS codes used for this profile and provides summary
information on the relevant NAICS sectors from the 2010 Annual Survey of Manufacturers and 2009 Statistics of
U.S. Businesses, both published by the U.S. Census Bureau.
Table C-2: Relationship between NAICS and SIC Codes for the Food and Kindred Products Industry
NAICS
Code
NAICS
Description
SIC Code
SIC Description
Number of
Establishments
(2009)"
Value of Shipments
(2010; Millions; $2011)
Employment
(2010)
311
(Excl.
31181 la)
Food
Manufacturing
20— (excl.
2082, 2084-
6, and 2097)
Food and Kindred Products
24,731
$656,721
1,315,188

2082
Malt Beverages

Beverage
Manufacturing
2084
Wines, Brandy, and Brandy
Spirits

3121
2085
Distilled and Blended Liquors
4,119
$94,840
118,719

2086
Bottled and Canned Soft Drinks
and Carbonated Waters

2097
Manufactured Ice

a. NAICS 311811: Retail Bakeries is not a part of manufacturing sectors in the SIC framework. Because Annual Survey of Manufacturers, used to analyze
Food and Kindred Products manufacturing sector, provides data only for manufacturing sectors, EPA excluded NAICS 311811 from the totals to the Food
and Kindred Products sector.
b. The most recent data on number of establishments is available for 2009 from Statistics of U.S. Businesses. Value of Shipments and Employment reflect
2010 data.
Sources: U.S. DOC, 2010 ASM; U.S. DOC, 2009 SUSB
C.2 Summary Insights from this Profile
The key purpose of this profile is to provide insight into the ability of firms in the Food and Kindred Products
Industry to absorb compliance costs from the final rule and other options EPA considered without material
adverse economic/financial effects. The industry's ability to absorb compliance costs is primarily influenced by
two factors: (1) the extent to which the industry may be expected to shift compliance costs to its customers
through price increases and (2) the financial health of the industry and its general business outlook.
C.2.1 Likely Ability to Pass Compliance Costs Through to Customers
As reported in the following sections of this profile, the Food Manufacturing and Beverage Manufacturing
segments face somewhat limited foreign competitive pressures, and, based on this factor, would have some
latitude to pass through to customers any increase in production costs resulting from regulatory compliance.
However, within the U.S. market, the Food Manufacturing and Beverage Manufacturing segments have relatively
low concentrations. Although niche product and/or regional segments are likely to face lighter overall
competition, the lack of industry concentration, as described later in this profile, suggests that firms in this
industry may have little ability to recover compliance costs through increased prices - particularly if the increased
costs do not occur in a relatively uniform way throughout the industry. Given the likelihood that only a relatively
small subset of facilities and firms in this industry will face additional costs as a result of the final rule and other
options EPA considered, EPA judges that a conservative assumption of no-cost-pass-through is appropriate for
analysis of the impact on this industry. Consequently, for the cost and economic impact analysis, EPA assumed
that regulated facilities would absorb all compliance costs within their operating finances (see following sections
and Appendix K: Cost Pass-Through Analysis, for further information).
C.2.2 Financial Health and General Business Outlook
Unlike the more cyclical sectors in the other profiled Primary Manufacturing Industries, the profiled Food and
Kindred Products Industry, being a consumer staples industry, was not as strongly affected by the economic
downturns that occurred in the early 2000s and in 2008-2009. During the last two decades, this industry has
C-2
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Industry Profile
maintained relatively healthy financial performance and steady growth despite economic fluctuations, increasing
government regulations, and changing consumer preferences and behavior. To remain competitive, firms in the
Food and Kindred Products Industry have been able to promptly respond to changing economic, business, and
regulatory environment by offering a greater variety of products while consistently and cost-effectively producing
high quality products (Rockwell Automation, 2008). Extremely high prices for many food commodities brought a
cash windfall in much of 2006-2008 for the industry. However, more recently, the global financial crisis has
created new challenges as consumers move to cheaper food options and increasingly cook at home (Plunkett
Research, 2010). The industry has exhibited substantially less fluctuation in capacity utilization and financial
performance than more cyclical industries, such as the other five Primary Manufacturing Industries. Although
foreign competition increased, the industry also experiences significantly less international competition than firms
in the other Primary Manufacturing Industries, as indicated by the industry's lower reliance on export sales and
the lower extent of import penetration in domestic markets.
On the whole, the Food and Kindred Products Industry has seen an increase in the level of capital expenditures
during the last two decades, despite fluctuations, and has correspondingly recorded a rise in labor productivity in
spite of multiple annual declines over the period. However, in the last decade capital expenditures actually
declined and the recent financial crisis led to significant declines in employment at the end of the period. These
factors suggest that the industry's capital equipment base had been maintained and regularly improved during the
1990s but that the business may face inordinate needs for capital expenditure due, for example, to offset the past
decade in which capital outlays seem to have substantially retrenched. Within the broader Food and Kindred
Products Industry, the Food Manufacturing segment has generally achieved more stable growth and financial
performance than the Beverage segment.
In 2012, the Packaged Foods and Meats index rose 6.9 percent compared to a 13.7 percent rise in the S&P 1500.
For 2013, the outlook for this sub-industry of the Food and Kindred Products is neutral. In the long-term, experts
believe that growth opportunities will lie in appealing to consumers' interest in healthier eating (S&P, 2013e).
The Soft Drinks sub-industry, another segment of the Food & Kindred Products sector, saw a 4.6 percent increase
in 2012. The outlook for the Soft Drinks sub-industry is neutral, with experts expecting growth in line with the
overall market (S&P, 2013g). The Distiller & Vintners sub-industry index increased 29.9 percent in 2012 and has
a positive outlook for 2013 (S&P, 2013b).
Given the proven ability of the profiled Food and Kindred Products Industry to withstand economic fluctuations,
regulatory changes, and constantly changing consumer behavior and business environment together with recent
industry trends may suggest that going forward, the profiled Food and Kindred Products Industry is very likely to
continue its moderate steady growth accompanied by relatively healthy financial performance. Further, EPA
judges that the profiled Food and Kindred Products Industry is currently in better economic/financial condition
overall than the other profiled Primary Manufacturing Industries and that this industry should be able to absorb
the cost of final rule compliance requirements without material adverse financial impact.
C.3 Domestic Production
At the beginning of this decade, the profiled Food and Kindred Products Industry was one the largest
manufacturing industries in the United States, with the Food Manufacturing and Beverage segments accounting
for approximately one-sixth of U.S. industrial activity in 2000 (McGraw-Hill, 2000). In 2009, U.S. total food
sales exceeded $1.5 trillion (Plunkett Research, 2010), and the Food Manufacturing segment alone accounted for
over 10 percent of all manufacturing shipments (U.S. DOC, 2008). The industry is considered mature, however,
and firms are constantly seeking new avenues for increased sales in domestic and foreign markets. With total food
industry shipments growing more slowly than GDP, U.S. producers have actively sought growth opportunities in
overseas markets. Although exports still make up a small share of domestic shipments, changes in global food
consumption could lead to increased demand and trade for processed food products going forward. As developing
May 2014
C-3
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Indus try Profile
countries experience growth in income, the demand for higher quality food products, such as meat products,
present an opportunity for U.S. firms to increase exports. In developed countries, consumer demand for food is
driven mainly by convenience and specialty food products (U.S. DOC, 2008).
C.3.1 Output
Figure C-l, following page, shows trends in constant dollar value of shipments and value added for the Food
Manufacturing and Beverage Manufacturing segments.21" Change in these values over time provides insight into
the overall economic health and outlook for an industry. Value of shipments is the sum of receipts earned from
the sale of outputs; it indicates the overall size of a market or the size of a firm in relation to its market or
competitors. Value added, defined as the difference between the value of shipments and the value of inputs used
to make the products sold, measures the value of production activity in a particular industry.
Over-time trends in value of shipments and value added show that both the Food Manufacturing and Beverage
Manufacturing segments have achieved generally stable performance over the 1987-2010 analysis period: these
industries have not been substantially affected by fluctuations in the performance trend of the U.S. economy. The
lack of major swings in shipments and value added results largely from the consumer staple-character of the
industry. At the end of the 1987-2010 analysis period, both profiled segments ended with a higher total value of
shipments and value added: constant dollar value of shipments in the profiled Food Manufacturing and Beverage
Manufacturing segments increased by about 96 percent and 28 percent, respectively, while value added increased
by 109 percent and 42 percent, respectively. The general trends indicate that firms in these industry segments
have been able to increase shipments and value added, which is a sign that these firms have been successful in
finding ways to expand their market and continue to grow.
210
C-4
Terms highlighted in bold and italic font are further explained in the glossary.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Indus try Profile
Figure C-1: Value of Shipments and Value Added for the Profiled Food Manufacturing and Beverage Manufacturing
Segments (millions, $2011)a
Value of Shipments
S675,000
S650,000
S625,000
S600,000
S575,000
S550,000
S525,000
^ S500,000
S S475,000
S450,000
S425,000
S400,000
S375,000
S350,000
S325,000
S300,000
"C
o
o
£—
— — — — — — — — — — —— — IJ (J (J Nl IJ IJ u u u u
OOOOsSsSsSsSsSsSsCsSsCOOOOOOOOOOO
oeoeceoo««o««oo«oooooooooo —
S95,000
^ S92,500
S90,000
S87,500
S85,000
S82,500
S80,000
S77,500
S75,000
S72,500
S70,000
S67,500
S65,000
S62,500
S60,000
03
<
c
era
era
-FoodMfg.(
NAICS 311)
- FoodMfg.
(SlCto ~
NAICS)
- Beverage
Mfg.
(NAICS
3121)
- Beverage
Mfg. (SIC to
NAICS)
Value Added
.61
S260,000
S240,000
S220,000
S200,000
i
S180,000
-O S160,000
O
£ S140,000
S120,000
S100,000
S80,000
S60,000

a /

V
r

__
4 / V
_ ¦

»v

¦ ¦

S55,000
CD
o
era
n>
-FoodMfg.(
NAICS 311)
—* Food Mfg. (SIC
to NAICS)
S40,000
£
S37,500 j?
S30,000
— Beverage Mfg.
(NAICS 3121)
— Beverage Mfg.
(SIC to NAICS)
scocscoooooo^oo^ooooooooos^
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American Industry
Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997Economic
Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007
EC
Table C-3 provides the Federal Reserve System's index of industrial production for the profiled Food
Manufacturing and Beverage Manufacturing segments, showing trends in production between 1990 and 2011.
This index more closely reflects total output in physical terms, whereas value of shipments and value added
reflect the economic value of production. The production index is expressed as a percentage of output in the base
year, 2007. With the exception of modest decreases in production during 1996, 2008, 2009 and 2010, the Food
Manufacturing segment has seen year-to-year production increases throughout the analysis period, with an overall
increase in production of 29 percent (8 percent during the last decade). Being less of a consumer staple industry
segment, the Beverage Manufacturing segment saw slightly more fluctuations during the analysis period and
experienced an overall increase of 37 percent for the entire period (26 percent during the last decade). Food
May 2014
C-5
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Indus try Profile
manufacturers continue to invest in greater automation in manufacturing processes with budgeted spending for
facility equipment, upgrades, computers, and automation remaining at steady levels. With the recent national
concerns over food safety and increasing food safety regulations, food manufacturers will likely also begin
investing in additional technological processes to meet increasing food safety requirements (U.S. DOC, 2008).
Table C-3: U.S. Food and Beverage Manufacturing Industry Industrial Production Index
Year
Food Manufacturing3
Beverage Manufacturingb
Index 2007=100
Percent Change
Index 2007=100
Percent Change
I 990
78.1
NA
74.6
NA
I 991
79.5
1.8%
75.6
1.3%
I 992
81.0
1.9%
75.9
0.5%
I 993
83.1
2.7 %
75.8
-0.2%
1994
83.6
0.6%
79.0
4.2%
1995
85.8
2.6%
79.5
0.7 %
I 996
84.0
-24%
83.0
4.3%
1997
86.3
2.8%
84.3
1.6%
I 998
904
4.4%
85.6
1.5%
I 999
91.2
14%
81.3
-5.0%
2000
92.7
1.7%
81.1
-0.2%

92.8
0.0%
80.9
-0.2%
2002
95.0
2.4%
81.2
0.3%
2003
95.6
0.7 %
86.3
6.3%

95.6
0.0%
89.7
4.0%
2005
98.6
34%
94.8
5.7%
2006
99.5
0.9%
94.4
-0.5%
2007
100.0
0.5%
100.0
5.9%
2008
98.7
-1.3%
95.2
-4.8%
2009
98.2
-0.6%
98.6
3.6%
20I0
98.0
-04%
98.4
-0.2%
2011
100.3
2.3%
102.1
3.8%
Total Percent Change
1990-2011
28.5%
37.0%
Total Percent Change
2000-2011
8.2%
26.0%
Average Annual
Growth Rate211
1.2%
1.5%
a. NAICS 311
b. NAICS 3121
Source: Federal Reserve Board of Governors, 2012b
C.3.2 Prices
The producer price index (PPI) measures price changes, by segment, from the perspective of the seller, and
indicates the overall trend of product pricing, and thus supply-demand conditions, within a segment.
As shown in Figure C-2, price levels in the profiled Food Manufacturing and Beverage Manufacturing segments
have risen steadily between 1987 and 2011, with an average annual growth rate of more than 2 percent. Total
spending on food makes up about 13 percent of a household's total average annual expenditures. Of the average
$6,111 in food spending, $3,417 is used for food to be consumed in the home and $2,694 is used for food
consumed away from home. Prepared meals, ready-to-serve products, ethnically diverse food products, and
organic food are showing increased demand as the U.S. population becomes older, more frugal, more diverse, and
increasingly concerned about nutrition (U.S. DOC, 2008). The Beverage Manufacturing segment has also seen a
steady increase in consumer spending over the last two decades despite being more susceptible to economic
fluctuations. Further, industry experts expect the Beverage Manufacturing industry segment to continue the
211 In this appendix, average annual growth rate refers to a year-to-year, constant percentage growth mean, which is calculated as the
compound annual growth rate between the first and last values. This is the same concept as the geometric mean, if all of the individual
year-to-year values are the same as those used in calculating the constant percentage growth mean.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Indus try Profile
modest but stable upward trend as manufacturers address consumer concerns about appropriate beverage size and
environmentally friendly packaging (CID, 2010). The Food Manufacturing segment saw a slight decline in 2009
due to the most recent recession but then experienced steep rises in prices in 2010 and even more so in 2011.
Figure C-2: Producer Price Indexes for Food Manufacturing and Beverage Manufacturing Segments
190
180
170
160
150
140
130
120
110
100
- Food Manufacturins
-Beverage Manufacturing

Source: BLS, 2011b
C.3.3 Number of Facilities and Firms
Table C-4 and Table C-5 present the number of facilities and firms for the Food Manufacturing and Beverage
Manufacturing segments between 1990 and 2009. As reported in the Statistics of U.S. Businesses, between 1990
and 2009, the number of facilities in the Food Manufacturing segment increased by 48 percent. The number of
firms in this segment grew by about 54 percent during this time period. During the same analysis period, the
number of facilities and number of firms in the Beverage Manufacturing segment increased even more
dramatically, by 87 percent and 99 percent, respectively. During the last decade, however, the Food
Manufacturing saw a number of mergers and acquisitions (U.S. DOC, 2008). Consequently, while the number of
facilities and firms in the Beverage Manufacturing grew by 50 percent and 57 percent, respectively, during the
last decade, the Food Manufacturing segment saw smaller increases in both of 24 percent and 25 percent,
respectively.
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Appendix C: Food and Kindred Products Industry Profile
Table C-4: Number of Facilities Owned by Firms in the Food and Beverage Manufacturing Segments3
Year
Food Manufacturing
Beverage Manufacturing
Number of Facilities
Percent Change
Number of Facilities
Percent Change
1990
16,740
NA
2,200
NA
1991
16,790
0.3%
2,211
0.5%
1992
17,824
6.2%
2,287
3.4%
1993
18,114
1.6%
2,281
-0.3%
1994
17,795
-1.8%
2,293
0.5%
1995
17,726
-0.4%
2,333
1.7%
1996
18,587
4.9%
2,576
10.4%
1997
18,558
-0.2%
2,660
3.3%
1998
20,088
8.2%
2,601
-2.2%
1999
19,954
-0.7%
2,671
2.7%
2000
19,902
-0.3%
2,748
2.9%
2001
20,340
2.2%
3,033
10.4%
2002
19,136
-5.9%
3,099
2.2%
2003
19,873
3.9%
3,082
-0.5%
2004
19,667
-1.0%
3,222
4.5%
2005
19,339
-1.7%
3,376
4.8%
2006
19,126
-1.1%
3,556
5.3%
2007
25,796
34.9%
3,960
11.4%
2008
25,760
-0.1%
4,050
2.3%
2009
24,731
-4.0%
4,119
1.7%
Total Percent Change 1990-
2009
47.7%
87.2%
Total Percent Change 2000-
2009
24.3%
49.9%
Average Annual Growth
Rate
2.1%
3.4%
a. Before 1998, data were compiled
in the SIC system; since 1998, these data have been compiled in the North American Industry Classification System
(NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic Census Bridge Between
NAICS and SIC.

Source: U.S. DOC, 1990-1997SBA; U.S. DOC, 1998-2009 SUSB

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Appendix C: Food and Kindred Products Indus try Profile
Table C-5: Number of Firms in the Food and Beverage Manufacturing Segments3
Year
Food Manufacturing
Beverage Manufacturing
Number of Firms
Percent Change
Number of Firms
Percent Change
I 990
13.346
NA
1.789
NA
I 991
13.418
0.5%
1.818
1.6%
I 992
14.409
7.4%
1.875
3.1%
1993
14.698
2.0%
1.867
-0.4%
1994
14.378
-2.2%
1.893
1.4%
1995
14.330
-0.3%
1.954
3.2%
1996
15.189
6.0%
2.192
12.2%
1997
15.189
0.0%
2.235
2.0%
I 998
16.656
9.7%
2.137
-4.4%
I 999
16.559
-0.6%
2.196
2.8%
2000
16.533
-0.2%
2.267
3.2%

16.960
2.6%
2.558
12.8%
2002
15.796
-6.9%
2.616
2.3%
2003
16.561
4.8%
2.576
-1.5%

15.51 1
-6.3%
2.692
4.5%
2005
15.274
-1.5%
2.839
5.5%
2006
15.093
-1.2%
2.998
5.6%
2007
21.591
43.1%
3.388
13.0%
2008
21.501
-0.4%
3.477
2.6%
2009
20.595
-4.2%
3.554
2.2%
Total Percent Change
1990-2009
54.3%
98.7%
Total Percent Change
2000-2009
24.6%
56.8%
Average Annual
Growth Rate
2.3%
3.7%
a. Before 1998, data were compiled in the SIC system; since 1998, these data have been compiled in the North American Industry Classification System
(NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic Census Bridge Between
NAICS and SIC.
Source: U.S. DOC, 1990-1997SBA; U.S. DOC, 1998-2009 SUSB
C.3.4 Employment and Productivity
The U.S. Food and Kindred Products Industry is among the most modern in the world. A steady trend of industry
growth and accompanying capital outlays have both increased production capacity and led to installation of
increasingly modern and more efficient, higher technology, production equipment. Indeed, spending for
production, packaging and process control equipment is the most robust automation capital area (see Section
C.3.5, below). The more advanced technology production equipment requires a more skilled labor force;
therefore, the key to future productivity gains are said to lie in better skills training of line operators and
supervisors. At the same time, more advanced technology equipment has resulted in more automated production
process and has reduced the number of employees needed per dollar of production (Higgins, 2005).
Figure C-3 presents employment for the two profiled segments between 1987 and 2010. As shown in Figure C-3,
between 1987 and 2010, employment exhibited different behavior in the two profiled segments. Other than sharp
increases in 1988 and 1997, employment in the Food Manufacturing segment was relatively stable, decreasing by
no more than 3 percent and increasing by no more than 4 percent. Over the entire analysis period, employment in
the Food Manufacturing segment increased by 42 percent. During the last decade, however, employment in this
segment fell by 10 percent. This drop in employment is likely the result of heavy investments in technology and
increased automation and production improvements, which persisted in the Food Manufacturing segment in the
last decade and have allowed companies to increase output while relying on fewer employees (U.S. DOC, 2008).
In the latter years of the past decade, employment in the Food Manufacturing segment has followed a steady
downward trend.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Indus try Profile
The Beverage Manufacturing segment has experienced more volatility over the last two decades. Between 1987
and 1994, employment in the Beverage Manufacturing segment fell nearly every year, before reversing this trend
and experiencing gains through 2001. These employment gains, however, were followed by consecutive
significant declines of nearly 10 and 9 percent in 2002 and 2003, respectively. After relatively stable few years,
2007 saw a significant employment increase of over 8 percent. However, this increase in employment in the
Beverage Manufacturing segment was followed by a major decline between 2007 and 2010.
Figure C-3: Employment for Food Manufacturing and Beverage Manufacturing Segments3
,o/o
1,600,000
1,500,000
1,400,000
1,300,000
1,200,000
1,100,000
1,000,000
900,000
800,000
- 158,000
153,000
148,000 03
o
+ 143,000 o
138,000 ora
- 133,000
'JQ
128.000
123.000
118.000
«s o o sc ,s s5 o o sc o «s o o e e e o ® e e e o ® e
ocoeoc'sso'ss'o'o'sso'ss'o'ssoeooooooooh-
-j x ss o — (J w 'Ji e- x ss ® — t J M 'Ji s- x o ®
¦ Food Mfg.( NAICS 311)
¦Beverage Mfg. (NAICS 3121)
— Food Mfg. (SIC to NAICS)
h— Beverage Mfg. (SIC to NAICS)
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997
Economic Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007
EC
Table C-6 presents the change in value added per labor hour, a measure of labor productivity, for the two profiled
industry segments between 1987 and 2010. As shown in this table, labor productivity in the Food and Beverage
Manufacturing segments has generally grown steadily and at an average annual rate of approximately 1 and 2
percent, respectively. However, labor productivity in the Beverage Manufacturing segment has shown a greater
degree of fluctuation, with both annual increases and decreases in productivity exceeding 10 percent during the
last decade. Overall, the Beverage manufacturing segment saw a greater increase in productivity during the last
two decades, 59 percent, compared to a 30 percent productivity gain in the Food Manufacturing segment, with
substantial gains occurring during the last decade. Technology improvement in the industry has played an
important role in increasing production during the last decade, as automation has allowed output levels to increase
without significant increases in employment (U.S. DOC, 2008).
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Appendix C: Food and Kindred Products Indus try Profile
Table C-6: Productivity Trends for Food and Beverage Manufacturing Segments ($2011)a
Year
Food Manufacturing
Beverage Manufacturing
Value Added
($ millions)
Production
Hours
(millions)
Value Added/Hour
Value Added
($ millions)
Production
Hours
(millions)
Value Added/Hour
$/hr
Percent
Change
$/hr
Percent
Change
1987
$128,652
1.325
97
NA
$33,824
148
228
NA
1988
$ 173.363
1.71 1
101
4.3%
$34,713
145
239
4.5%
1989
$169,530
1.708
99
-24%
$34,018
142
240
0.7 %
I 990
$177,426
1.788
99
0.0%
$33,264
140
237
-1.3%
I 991
$174,218
1.776
98
-11%
$34,508
139
248
4.4%
I 992
$186,838
1.877
100
1.5%
$35,614
140
254
2.6%
I 993
$193,652
1.901
102
2.3%
$35,158
144
244
-3.9%
I 994
$195,166
1.933
101
-0.9%
$36,878
138
267
94%
1995
$202,677
1.938
105
3.6%
$37,210
139
268
0.4%
I 996
$192,814
1.91 1
101
-3.6%
$39.61 1
139
285
6.5%
1997
$217.598
2.200
99
-2.0%
$39.841
149
268
-64%
I 998
$226,922
2.232
102
2.8%
$41,023
148
278
3.7 %
I 999
$228,963
2.270
101
-0.8%
$39,607
140
283
1.9%
2000
$234,125
2.284
102
1.6%
$38.341
153
251
-1 1.4%

$239,376
2.259
106
3.4%
$39,439
150
263
5.1%
2002
$246,676
2.236
1 10
4.1%
$39,850
139
286
8.8%
2003
$255,103
2.239
1 14
3.3%
$45,225
138
327
14.1%
2004
$261.1 18
2.203
119
4.0%
$46,995
132
355
8.7%

$264,854
2.195
121
1.8%
$49,239
135
364
2.4%
2006
$254,072
2.156
118
-2.3%
$47.1 15
138
342
-5.9%
2007
$254,763
2.236
1 14
-3.4%
$48,978
148
331
-3.2%
2008
$255,088
2.228
115
0.5%
$46,724
146
319
-3.6%
2009
$265,291
2.163
123
7.1%
$46,601
143
326
2.2%
2010
$269,230
2,125
127
3.3%
$48,087
132
364
11.5%
Total Percent Change
1987-2010
109.3%
60.5%
30.4%
42.2%
-10.7%
59.3%
Total Percent Change
2000 - 2010
15.0%
-7.0%
23.6%
25.4%
-13.6%
45.2%
Average Annual
Growth Rate
3.3%
2.1%
1.2%
1.5%
-0.5%
2.0%
a. Before 1997, data were compiled in the SIC system; since 1997, these data have been compiled in the North American Industry Classification System
(NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic Census Bridge Between
NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007EC
C.3.5 Capital Expenditures
The profiled Food and Kindred Products Manufacturing industry is capital intensive, and has invested
substantially in capital to implement automation, introduce process controls, and reduce inventories in order to
ultimately improve yield and reduce labor costs. Capital-intensive industries are characterized by a large value of
capital equipment per dollar value of production. In order to modernize, expand, and replace existing capacity,
new capital expenditures are needed. In 2010, total capital expenditures for the Food Manufacturing and
Beverage Manufacturing segments amounted to about $17 billion. Approximately 85 percent of that spending (see
Table C-7) occurred in the Food Manufacturing segment.
Between 1987 and 2010, capital expenditures in the Food Manufacturing segment increased by nearly 80 percent
at an average annual rate of approximately 3 percent, peaking at about $17 billion in 1999. The Beverage
Manufacturing segment has also seen substantial growth in capital expenditures during this time period. Between
1987 and 2010, expenditures in this segment increased by 23 percent, at an average annual rate of 1 percent and
peaking at nearly $4 billion in 2002. During the last decade, however, capital expenditures in the Food and
Beverage Manufacturing industry segments declined by approximately 7 and 23 percent, respectively.
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Appendix C: Food and Kindred Products Indus try Profile
Table C-7: Capital Expenditures for Food and Beverage Manufacturing Segments (millions, $2011 )a
Year
Food Manufacturing
Beverage Manufacturing
Capital Expenditures
Percent Change
Capital Expenditures
Percent Change
1987
$7,896
NA
$2,099
NA
1988
$10,035
274%
$2,174
3.5%
1989
$10,751
74%
$2,099
-3.4%
I 990
$1 1.432
6.3%
$1,847
-12.0%
I 991

-1.0%
$2,082
12.8%
I 992
998
6.0%
$2,143
2.9%
I 993
285
-5.9%
$1,890
-1 1.8%
I 994
637
3 1%
$2,210
16.9%
1995

15.3%
$2,540
15.0%
I 996
$12,692
-5.4%
$2,476
-2.5%
1997
$14,364
13.2%
$3,191
28.9%
I 998
$15,143
5.4%
$2,943
-7.8%
I 999
518
94%
$2,982
1.3%
2000

-7.3%
$3,357
12.6%

289
-6.7%

-6.5%
2002
466
-5.8%
$3,750
19.5%
2003
049
-3.1%
$2,855
-23.9%
2004
$12,998
-0.4%
$2,831
-0.9%
2005
$13,596
4.6%

19.8%
2006
$13,831
1.7%
$3,363
-0.9%

$13,977
1.1%

-5.8%
2008
$16,243
16.2%
$3,594
13.4%
2009
$14,031
-13.6%
$3,014
-16.1%
20I0
$14,240
1.5%
$2,590
-14.1%
Total Percent Change
1987-2010
80.3%
23.4%
Total Percent Change
2000 - 2010
-7.0%
-22.9%
Average Annual
Growth Rate
2.6%
0.9%
a. Before 1997, data were compiled in the SIC system; since 1997, these data have been compiled in the North American Industry Classification System
[NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic Census Bridge Between
NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007EC
C.3.6 Capacity Utilization
Capacity utilization measures output as a percentage of total potential output from available capacity. Capacity
utilization reflects excess or insufficient capacity in an industry and is an indication of whether new investment is
likely. The degree of fluctuation in capacity utilization is also an indicator of the relative stability of demand and
business conditions in an industry.
As shown in Figure C-4, between 1990 and 2011, capacity utilization in the Food Manufacturing and Beverage
and Tobacco Manufacturing212 industry segments generally trended downward. The Food Manufacturing
segment, however, did not experience the volatility that the Beverage and Tobacco Manufacturing segment
experienced over the same period. Food Manufacturing capacity utilization rates have generally remained within
the 78 and 86 percent range, while the Beverage and Tobacco Manufacturing segment experienced a high of 85
percent in 1996, followed by a significant decline to below 69 percent by 2009. Further, the Beverage and
Tobacco Manufacturing segment was significantly affected by economic downturns in the early 1990s and early
and late 2000s, when its capacity utilization significantly dropped to 72, 66, and 69 percent, respectively. Between
1990 and 2011, capacity utilization declined in both segments, although the Beverage and Tobacco
212 The Census Bureau provides capacity utilization data are available only for the 3-digit NAICS sector NAICS 312: Beverage and
Tobacco Manufacturing sector. The Census Bureau does not provide capacity utilization data for the 4-digit NAICS sector NAICS
3121: Beverage Manufacturing.
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Appendix C: Food and Kindred Products Indus try Profile
Manufacturing segment experienced a more substantial drop: while capacity utilization in the Food
Manufacturing segment declined by a about 3 percent, capacity utilization in the Beverage and Tobacco
Manufacturing declined by nearly 17 percent.
Again, significantly less fluctuation in capital utilization in the profiled Food Manufacturing segment during the
analysis period, suggests that this segment is characterized by a lower degree of susceptibility to economic
changes compared to the profiled Beverage Manufacturing segment. This pattern is likely to continue going
forward. That overall capacity utilization remained at a moderate level throughout the analysis period for both
profiled segments - roughly between 66 and 86 percent - implies that the profiled Food and Beverage
Manufacturing segments do not face requirements for large outlays for capital expansion in the near term.
Figure C-4: Capacity Utilization for Food Manufacturing and Beverage and Tobacco Manufacturing Segments3
90
85
80
75
70
65
—*— Food Manufacturing (NAICS 311) —~— B everage & Tobaco Manufacturing (NAICS 312)
a. The Federal Reserve provides capacity utilization data for the combined NAICS 312 (Beverage and Tobacco Manufacturing) sectors. The Federal
Reserve does not provide capacity utilization data for just the Beverage Manufacturing sector.
Source: Federal Reserve Board of Governors, 2012
C.4 Structure and Competitiveness
Food Manufacturing and Beverage Manufacturing companies range in size from multi-billion dollar corporations
to small producers with revenues a fraction of the size of the large producers. Many of the companies in these
segments are diversified producers of multiple food or beverage products. Because food is a necessary purchase,
demand is less affected by the ups and downs of the economy than for other industries.
The Food Manufacturing segment has consolidated over the last two decades as companies moved to diversify
their product offerings and gain market share. This segment has also looked abroad to tap into the emerging
markets of foreign countries. According to the Food Institute, 99 mergers and acquisitions occurred among food
processing companies in 2006, up from 94 in 2005, but down from 168 in 2000 (U.S. DOC, 2008). These
acquisitions and mergers permit companies to acquire more efficient manufacturing facilities, close inefficient
facilities, expand product lines, and increase market share in a mature market (U.S. DOC, undated). Some recent
mega-mergers in the Food Manufacturing segment include the Kraft Foods" acquisition of Nabisco, General
Mills" acquisition of Pillsbury, and Tyson's bringing beef and pork firm IBP into its lineup. In 2008 and 2009,

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May 2014
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Appendix C: Food and Kindred Products Indus try Profile
mergers and acquisitions were concentrated in the restaurant industries with limited M&A activity among food
processing companies (The Food Institute Report, 2009).
The Beverage Manufacturing segment recorded acquisitions and mergers during the last decade, although not
nearly as many as the Food Manufacturing segment. Product differentiation is a key strategy for larger firms to
increase brand awareness and market share (Yahoo, 2005). As sales in the United States slowed, firms in the non-
alcoholic beverage industry saw their largest gains from non-U.S. markets. In fact, in 2008 alone, PepsiCo had
three international deals (Value Line, 2004).
In the alcoholic beverage sub-segment, Anheuser-Busch lost the rank of world's largest brewer due to the merger
of Inbrew and Brazil's Ambev. The merger between Adolph Coors and Molson further consolidated the industry.
Brewers began to look for acquisitions in China, which is seen as an untapped market. Constellation Brands
purchased the Robert Mondavi Corporation, a leader in wine making, and began to work in a joint venture with
the French vintner Domaines Barons de Rothschild. Diageo and France's Pernod Ricard bought Seagrams
Company, after outbidding the tandem of Bacardi and Brown-Forman. In recent years, Sazerac Company has
purchased Constellation Brands' value spirits business, and Sabmiller and Molson Coors Brewing Company have
merged (Yahoo, 2005).
C.4.1 Firm and Facility Size
For almost all NAICS codes in the Food Manufacturing and Beverage Manufacturing segments, the Small
Business Administration defines a small firm as having fewer than 500 employees. The exceptions are NAICS
codes 311221, 311312, 311313, 311821, and 312140, which are considered small if the firm has fewer than 750
employees, and NAICS codes 311223, 311225, 311230, and 311422, which are deemed small if the firm employs
fewerthan 1,000 employees. The size categories reported in Statistics of U.S. Businesses (SUSB) do not
correspond with the SBA size classifications, therefore preventing precise use of the SBA size threshold in
conjunction with SUSB data. Table C-8 reports the size distribution of firms and facilities in the Food
Manufacturing and Beverage Manufacturing segments for 2009. As shown in the table, small establishments
dominate both segments:
> 20,049 of 20,595 (97 percent) firms in the Food Manufacturing segment had fewer than 500 employees.
These small firms owned 21,099 facilities, or 85 percent of all facilities in the segment.
> 3,485 of 3,554 (98 percent) firms in the Beverage Manufacturing segment had fewer than 500 employees.
These small firms owned 3,553 facilities, or 86 percent of all Beverage Manufacturing facilities.
Because some six-digit NAICS codes within the Food Manufacturing and Beverage Manufacturing segments
have small business size thresholds of greater than 500 employees, the reported numbers and percentages of
businesses with fewer than 500 employees represent lower bounds of the number and percentage of small
businesses in these industry segments.
In general, the percentage of small firms in the food and beverage industry is comparable to the percentage of
small firms in all manufacturing industries combined. In 2009, approximately 97 percent of the firms in NAICS
311 and 3121 had fewer than 500 employees, compared to almost 99 percent for all manufacturing. However,
compared to the Primary Manufacturing Industries, the Food Manufacturing and Beverage Manufacturing
industries have a significantly higher percentage of firms within the industry identified as small. As noted below,
however, the larger companies within each segment dominate in terms of producing the majority of shipments for
each segment, with the 50 largest firms in Food Manufacturing accounting for 51 percent of shipments, while the
50 largest companies in Beverage Manufacturing producing an even greater share of shipments, at 83 percent of
the total (see Table C-9, following page).
C-14
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Indus try Profile
Table C-8: Number of Firms and Facilities by Size Category for Food and Beverage Manufacturing
Segments, 2009

Employment Size
Food Manufacturing3
Beverage Manufacturing6
Category
No. of Firms
No. of Facilities
No. of Firms
No. of Facilities
D-I9
15.022
15.078
2.870
2.874
20-99
3.757
4.072
495
518
100-499
1.270
1.949
120
161
500+
546
3.632
69
566
Total
20,595
24,731
3,554
4,119
a. NAICS 311

b. NAICS 3121

Source: U.S.DOC, 2009 SUSB

C.4.2 Concentration Ratios
Concentration is the degree to which industry output is concentrated in a few large firms. Concentration is closely
related to entry barriers, with more concentrated industries generally having higher barriers.
The four-firm concentration ratio (CR4) and the Herfindahl-Hirschman Index (HHI) are common measures of
industry concentration. The CR4 indicates the market share of the four largest firms. For example, a CR4 of 72
percent means that the four largest firms in the industry account for 72 percent of the industry's total value of
shipments. The higher the concentration ratio, the less competition there is in the industry, other things being
equal.213 An industry with a CR4 of more than 50 percent is generally considered concentrated. The HHI indicates
concentration based on the largest 50 firms in the industry. It is equal to the sum of the squares of the market
shares for the largest 50 firms in the industry. For example, if an industry consists of only three firms with market
shares of 60, 30, and 10 percent, respectively, the HHI of this industry would be equal to 4,600 (602 + 302 + 102).
The higher the index, the fewer the number of firms supplying the industry and the more concentrated the
industry. Based on the U.S. Department of Justice's guidelines for evaluating mergers, markets in which the HHI
is under 1,000 are considered unconcentrated, markets in which the HHI is between 1,000 and 1,800 are
considered to be moderately concentrated, and those in which the HHI is in excess of 1,800 are considered to be
concentrated.
As shown in Table C-9, based on the most recent data, the Food Manufacturing segment has an HHI of 102, and
the Beverage Manufacturing segment has an HHI of 483. At these HHI levels, the two industry segments,
especially the Food Manufacturing segment, appear unconcentrated. With relatively low concentration in the
affected industries, firms are unlikely to possess the market power to recover regulatory compliance costs through
price increases, particularly if those costs do not apply relatively uniformly and broadly throughout the industry.
The concentration ratios also show that each profiled segment operates in unconcentrated markets. The Beverage
Manufacturing segment has the higher concentration of the two segments, with a CR4 of 39 percent. This is
slightly lower than the 50 percent threshold, which would indicate some market concentration. The CR4 for the
Food Manufacturing segment is considerably lower at only 15 percent. In this segment, the top 50 companies
control roughly half of the market, indicating a relatively unconcentrated market segment. In the Beverage
Manufacturing segment, the top 50 companies control 83 percent of the market. As noted above, however,
mergers and acquisitions are occurring in both segments, which will likely lead to increased concentration in the
future. Also, certain sub-segments within each segment can be highly concentrated. For example, within the soft
drink market, Coca-Cola claims around 50 percent of the global market, followed by Pepsi with roughly 21
percent and Cadbury-Schweppes with 7 percent (Yahoo, 2005).
213 Note that the measured concentration ratio and the HHF are very sensitive to how the industry is defined. An industry with a high
concentration in domestic production may nonetheless be subject to significant competitive pressures if it competes with foreign
producers or if it competes with products produced by other industries (e.g., plastics vs. aluminum in beverage containers).
Concentration ratios based on share of domestic production are therefore only one indicator of the extent of competition in an
industry.
May 2014
C-15
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Indus try Profile
Table C-9: Selected Ratios for Food Manufacturing and Beverage Manufacturing Segments

Concentration Ratios

Herfindahl-

Total Number

Hirschman
NAICS Code
Year
of Firms
4 Firm (CR4)
8 Firm (CR8)
20 Firm (CR20)
50 Firm (CR50)
Index
311
1997
21958
14%
22%
35%
51%
91
2002
23334
17%
25%
40%
53%
119
2007
21355
15%
23%
38%
51%
102
3121
1997
2169
41%
52%
66%
79 %
532
2002
2445
40%
53%
69%
82%
512
2007
3160
39%
52%
71%
83%
483
Source: U.S. DOC, 1987, 1992, 1997, 2002, and 2007EC
C.4.3 Foreign Trade
This profile uses two measures of foreign competition: export dependence and import penetration.
Import penetration measures the extent to which domestic firms are exposed to foreign competition in domestic
markets. Import penetration is calculated as total imports divided by total value of domestic consumption in that
industry: where domestic consumption equals domestic production plus imports minus exports. Theory suggests
that higher import penetration levels will reduce market power and pricing discretion because foreign competition
limits domestic firms" ability to exercise such power. Firms belonging to segments in which imports account for a
relatively large share of domestic sales would therefore be at a relative disadvantage in their ability to pass-
through costs because foreign producers would not incur costs as a result of the final rule. The estimated import
penetration ratio for the entire U.S. manufacturing sector (NAICS 31-33) for 2010 is 28 percent. For
characterizing the ability of industries to absorb compliance cost burdens, EPA judges that industries with import
ratios close to or above 28 percent would more likely face stiff competition from foreign firms and thus be less
likely to succeed in passing compliance costs through to customers.
Export dependence, calculated as exports divided by value of shipments, measures the share of a segment's sales
that is presumed subject to strong foreign competition in export markets. The final rule would not increase the
production costs of foreign producers with whom domestic firms must compete in export markets. As a result,
firms in industries that rely to a greater extent on export sales would have less latitude in increasing prices to
recover cost increases resulting from regulation-induced increases in production costs. The estimated export
dependence ratio for the entire U.S. manufacturing sector for 2010 is 22 percent. For characterizing the ability of
industries to absorb compliance cost burdens, EPA judges that industries with export ratios close to or above 22
percent are at a relatively greater disadvantage in potentially recovering compliance costs through price increases
since export sales are presumed subject to substantial competition from foreign producers.
Table C-10 presents trade statistics for the profiled Food and Kindred Products Industry.214 Imports and exports
play a small role in this industry, with 2010 import penetration and export dependence ratios of 7.9 and 7.6
percent, respectively. Both measures of foreign competition are well below the 2010 U.S. manufacturing
averages. Given just these measures, it would be reasonable to assume that these segments do not face significant
foreign competitive pressures, and would have more latitude in passing through to customers any increase in
production costs resulting from regulatory compliance. However, as noted above, the HHI of the Food
Manufacturing and Beverage Manufacturing segments is 102 and 483, respectively suggesting firms in these
segments have low market power, limiting their ability to pass through any increase in production costs.
Due to data limitations, it is not possible to accurately separate the Food and Beverage Manufacturing segments.
C-16 May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Industry Profile
Table C-10: Trade Statistics for Profiled Food and Kindred Products Industry3
Year
Value of Imports
(millions, $2011)
Value of Exports
(millions, $2011)
Value of Shipments
(millions, $2011)
Implied Domestic
Consumptionb
Import
Penetration0
Export
Dependenced
1990
$26,532
$25,141
$522,290
$523,681
5.1%
4.8%
1991
$24,867
$26,366
$507,082
$505,582
4.9%
5.2%
1992
$25,829
$29,094
$527,922
$524,656
4.9%
5.5%
1993
$24,968
$29,691
$534,254
$529,531
4.7%
5.6%
1994
$26,372
$32,737
$539,596
$533,231
4.9%
6.1%
1995
$27,246
$36,135
$552,471
$543,582
5.0%
6.5%
1996
$30,402
$36,856
$559,217
$552,763
5.5%
6.6%
1997
$31,761
$36,743
$643,879
$638,897
5.0%
5.7%
1998
$32,919
$34,776
$645,784
$643,927
5.1%
5.4%
1999
$35,100
$32,794
$633,691
$635,997
5.5%
5.2%
2000
$36,336
$33,881
$633,455
$635,909
5.7%
5.3%
2001
$36,933
$35,092
$642,347
$644,189
5.7%
5.5%
2002
$39,486
$32,934
$638,055
$644,607
6.1%
5.2%
2003
$43,504
$34,437
$669,496
$678,562
6.4%
5.1%
2004
$48,090
$32,767
$684,390
$699,713
6.9%
4.8%
2005
$50,509
$35,086
$694,567
$709,990
7.1%
5.1%
2006
$53,275
$38,134
$676,672
$691,812
7.7%
5.6%
2007
$56,435
$44,623
$719,524
$731,337
7.7%
6.2%
2008
$60,648
$54,768
$766,377
$772,257
7.9%
7.1%
2009
$54,268
$49,458
$738,583
$743,393
7.3%
6.7%
2010
$59,811
$57,003
$751,561
$754,368
7.9%
7.6%
Total Percent
Change 1990-2010
125.4%
126.7%
43.9%
44.1%
Total Percent
Change 2000 - 2010
64.6%
68.2%
18.6%
18.6%
Average Annual
Growth Rate
4%
4%
2%
2%
a. Before 1997, data were compiled in the SIC system; since 1997, these data have been compiled in the North American Industry Classification System
(NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic Census Bridge Between
NA1CS and SIC.

b. Calculated by EPA as
shipments + imports -
exports.

c. Calculated by EPA as
d. Calculated by EPA as
imports divided by implied domestic consumption,
exports divided by shipments.

Source: U.S. ITC, 1989-2010

As shown in Figure C-5, between 1990 and 2010, imports of Food and Kindred Products steadily increased at an
average annual rate of 4 percent leading to an overall increase of 125 percent (65 percent during the last decade).
Exports of Food and Kindred Products also increased during this time period at an average annual rate of 4
percent leading to an overall increase of 127 percent (68 percent during the last decade). While imports
experienced a relatively steady increase, exports fluctuated significantly during the analysis period: Exports
increased between 1990 and 1996, declined for the next three years, remained relatively steady through 2004, and
then increased through 2008. Both exports and imports declined in 2009 but then returned to an upward trend in
2010. During most of the 1990s, the Food and Kindred Products Industry recorded a trade surplus, even though
the value of imports was steadily growing. However, in 1999, this trend reversed itself and during the last decade,
the Food and Kindred Products Industry was characterized by trade deficit. Starting in 2005, however, exports
have been growing at a higher rate than imports, thereby shrinking the deficit.
May 2014
C-17
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Indus try Profile
Figure C-5: Value of Imports and Exports for Profiled Food and Kindred Products Industry (millions, $2011)a
S60,000

_
_
_
_
_
_
_

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w
tJ

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o
s©
¦©

W
4*.

•-4
oc
so
o

'ji

-J
00
•o
e>
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997
Economic Census Bridge Between NAICS and SIC.
Source: U.S. ITC, 1989-2010
3 S56,000
®
N
& S52,000
£
S S48,000
§ S44,000
a
s
£ S40.000
&
« S36,000
ca
g, S32,000
X
U
(_ S28,000
o
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Indus try Profile
outlays, can cause even small fluctuations in output or prices to have a large positive or negative affect on profit
margin.
Return on total capital is calculated as annual pre-tax income divided by the sum of current portion of long-term
debt due in 1 year or less, long-term debt due in more than one year, all other noncurrent liabilities and total
stockholders" equity (total capital). This concept measures the total productivity of the capital deployed by a firm
or industry, regardless of the financial source of the capital (i.e., equity, debt, or liability element). As such, the
return on total capital provides insight into the profitability of a business" assets independent of financial structure
and is thus a "purer" indicator of asset profitability than return on equity. In the same way as described for net
profit margin, the firms in an industry, and the industry collectively, must generate over time a sufficient return on
capital if the industry is to remain economically viable and attract capital. The factors causing short-term variation
in net profit margin will also be the primary sources of short-term variation in return on total capital.
Figure C-6 shows a trend in net profit margins and return on total capital for Food and Kindred Products Industry
firms between 1988 and 2012. Despite some fluctuations in response to recessions in 1993, 2001, and 2008, when
both profit margins and return on total capital fell slightly but recovered shortly after, this industry reported
positive profit margins and return on total capital over the entire analysis period. After the most recent recession
in 2008, both net profit margin and return on total capital rose in 2009 and 2010. In 2011 both indicators declined
while in 2012 net profit margin saw a slight increase as return on total capital continued to decline. In 2012, return
on total capital remained below its long-term average, while net profit margin was slightly above its long-term
average.
That demand for food and beverages remained high during otherwise weak economic conditions, indicates that
the profiled industry segments should be able to continue robust financial performance over the foreseeable
future, thus suggesting strong ability to absorb the costs associated with the final rule. In the long term, the Food
and Beverage Manufacturing industry will continue to focus on and adjust to consumer lifestyles and tastes,
including both opportunities in developing international markets and the particular needs of an aging U.S.
population. Future growth opportunities might include introduction and distribution of products that appeal to
consumers" interest in healthier eating and environmental sustainability (S&P, 2010c).
Figure C-6: Net Profit Margin and Return on Total Capital for Food and Kindred Products Industry
20%
18%
16%
14%
12%
10%
2%
0%
~T~
~T~
~T~
~T~
~T~
~T~
~T~
~T~
~T~
~T~
~T~
~T~
"T"
"T"
"T"
"T"
"T"
"T"
____________
^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^
» K C C 's£ 'sC 'sc 'sc 'sc 'sc 'sc 'sc © © © © © o o
XC5 — - W 'J\ 0\
N N N N N f
-j ac « © h N
-Net Profit Margin
-Return on Total
Capital
Source: U.S. DOC, 1988-2012 QFR
May2014
C-19
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Indus try Profile
C.6 Facilities Operating Cooling Water Intake Structures
Point source facilities that use or propose to use a cooling water intake structure that withdraws cooling water
directly from a surface waterbody of the United States are potentially subject to section 316(b) of the Clean Water
Act. In 1982, the Food and Kindred Products Industry withdrew 272 billion gallons of cooling water, accounting
for approximately 5 percent of total manufacturing cooling water intake in the United States. The industry ranked
sixth in industrial cooling water use, behind the electric power generation industry, chemical, primary metals,
petroleum and coal products, and paper and allied products industries (U.S. DOC, 1982).
This section provides information for the facilities in the Food and Kindred Products Industry that EPA estimates
to be subject to regulation under the final rule and other options EPA considered. Existing facilities that meet the
following conditions are potentially subject to regulation:
> Have a National Pollutant Discharge Elimination System (NPDES) permit or are required to obtain one;
> Use or propose to use one or more cooling water intake structures to withdraw water from waters of the
United States;
> Use at least twenty-five (25) percent of the water withdrawn exclusively for contact or non-contact
cooling purposes; and
> Meet the specific applicability coverage criteria for the final rule and other options EPA considered in
terms of design intake flow (i.e., two mgd).
EPA initially identified the set of facilities that were estimated to be potentially subject to the final rule based on a
minimum applicability threshold of two mgd; this section focuses on these facilities for the Food and Kindred
Products segment.215
C.6.1 Waterbody and Cooling System Type
Table C-ll reports the distribution of the Food and Kindred Products Industry facilities by type of waterbody and
cooling water intake system.
Table C-11: Number of Food and Kindred Products Facilities Estimated Subject to the 316(b) Existing

Facilities Regulation by Waterbody Type and Cooling Water Intake System

Waterbody Type
Recirculating1"
Combination
Once-Through
Other
Total
No.
% of Total
No.
% of Total
No.
% of Total
No.
% of Total
Estuary/Tidal River
0
0%
0
0%
7
50%
0
0%
7
Freshwater River/ Stream
14
100%
3
50%
7
50%
3
100%
27
Great Lake
0
0%
3
50%
0
0%
0
0%
3
Total3
14
36%
7
18%
14
36%
3
9%
37
a. Individual numbers may not add up to total due to independent rounding.
b. Includes facilities that have cooling towers as well as those that use impoundments.

Source: U.S. EPA, 2000; U.S. EPA analysis for this report

C.6.2 Facility Size
Figure C- 7 shows the employment size category for the Food and Kindred Products Industry facilities EPA
expects to be subject to the final rule and other options EPA considered.
215 EPA applied sample weights to the sampled facilities to account for non-sampled facilities and facilities that did not respond to the
survey. For more information on EPA's 2000 Section 316(b) Industry Survey, please refer to the Information Collection Request (U.S.
EPA, 2000).
C-20
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix C: Food and Kindred Products Indus try Profile
Figure C-7: Number of Facilities Estimated Subject to the Final 316(b) Existing Facilities Regulation by Employment
Size for the Combined Food and Kindred Products Industry
25

10 -

5 -

0 -

20
10

or
/—^
Less than
100
100-249 250-499 500-999
1000 or
greater
Source: U.S. EPA, 2000; U.S. EPA analysis for this report
C.6.3 Firm Size
EPA used the Small Business Administration (SBA) small entity size standards to determine the number of
facilities in the Food and Kindred Products facility dataset that are owned by small firms. EPA estimates that no
small entity-owned facilities and 37 large entity-owned facilities in this industry segment will be subject to the
final regulation.
May 2014
C-21
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
Appendix D Profile of the Paper and Allied Products Industry
D.1 Introduction
EPA's Detailed Industry Questionnaire, hereafter referred to as the DQ, identified five 4-digit SIC codes in the
Paper and Allied Products Industry (SIC 26) with at least one existing facility that operates a CWIS, holds a
NPDES permit, withdraws at least two million gallons per day (mgd) from a water of the United States, and uses
at least 25 percent of its intake flow for cooling purposes (facilities with these characteristics are hereafter referred
to as "facilities potentially subject to the 316(b) Existing Facilities regulation" or "regulated facilities"). For the
purpose of this analysis, EPA identified a six-digit NAICS code for each of these potential facilities using the
information from DQ and public sources (see Appendix J: Mapping Manu facturers Standard Industrial
Classification (SIC) Codes to North American Industry Classification System (NAICS) Codes). As the result of
this mapping, EPA identified six 6-digit NAICS codes in the Paper and Allied Products Industry (NAICS 322).
For each of these six analyzed 6-digit NAICS codes, Table D-l, following page, provides a description of the
industry segment, a list of primary products manufactured, the total number of detailed questionnaire respondents
(weighted to represent a national total of facilities that hold a NPDES permit and operate cooling water intake
structures (CWIS)), and the number of facilities estimated to be potentially subject to the final rule based on the
minimum withdrawal threshold of two mgd (see Chapter 1: Introduction for more details on the final rule
applicability criteria).
Table D-1: Existing Facilities in the Paper and Allied Products Industry (NAICS 322)
NAICS
NAICS
Description
Important Products Manufactured
Number of Regulated
Facilities3
322110
Pulp Mills
Pulp from bagasse, linters, rags, straw, wastepaper, and wood manufactured by
chemical, mechanical, or semichemical processes without making paper for
paperboard.
33
32212
Paper Mills
Paper from wood pulp and other liber pulp, converted paper products; integrated
operations of producing pulp and manufacturing paper if primarily shipping paper
or paper products.
136
322130
Paperboard
Mills
Paperboard, including paperboard coated on the paperboard machine, from wood
pulp and other liber pulp; and converted paperboard products; integrated
operations of producing pulp and manufacturing paperboard if primarily shipping
paperboard or paperboard products.
48
Total
217
Other Paper and Allied Products Segments
322222
Coated and
Laminated Paper
Manufacturing
Cutting and coating paper, cutting a laminating paper and other flexible materials
(except plastics film), laminating aluminum and other metal foils for non-
packaging uses from purchased foil.
3
322224
Uncoated Paper
and Multiwall
Bag
Manufacturing
Uncoated, multiwall, paper bags manufactured from purchased paper.
3
322299
All Other
Converted Paper
Products
Manufacturing
Containers, bags, coated and treated paper, stationary products, and sanitary paper
products from paper and paperboard products; converted pulp products (i.e. egg
cartons, food trays, and other food containers) from molded pulp.
3
Total Other
8
Total Paper and Allied Products (NAICS 322)
Total NAICS Code 322 I 225
a. Number of weighted detailed questionnaire survey respondents.
b. Individual numbers may not add up due to independent rounding.
Source: Executive Office of the President, 1987; U.S. EPA, 2000; U.S. EPA analysis for this report
May 2014
D-1
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
As shown in Table D-l, EPA estimates that out of an estimated total of 563 facilities216 with a NPDES permit and
operating cooling water intake structures in the Paper and Allied Products Industry (NAICS 322), that 225 (40
percent) are expected to be subject to the 316(b) Final Existing Facilities Regulation. EPA also estimated the
percentage of total industry production that occurs at facilities estimated to be subject to regulation under the final
rule and other options EPA considered. Total value of shipments for the Paper and Allied Products Industry
(NAICS 322) from the 2010 Annual Survey of Manufactures (ASM), published by the U.S. Census Bureau, is
$173.6 billion ($2011). Value of shipments, a measure of the dollar value of production, was selected for the basis
of this estimate. Because the DQ did not collect value of shipments data, these data were not available for the
potential existing facilities. Total revenue, as reported on the DQ, was used as a close approximation for value of
shipments for these facilities. EPA estimated the total revenue of facilities in the paper industry expected to be
subject to the 316(b) Existing Facilities regulation is $66.8 billion ($2011).217 Therefore, EPA estimates that the
percentage of total production in the paper industry that occurs at facilities estimated to be subject to regulation is
39 percent.
The responses to the DQ indicate that three segments account for most of the existing Manufacturers in the Paper
and Allied Products Industry: (1) Pulp Mills (NAICS 322110), (2) Paper Mills (NAICS 32212), and (3)
Paperboard Mills (NAICS 322130). The remainder of this profile therefore focuses on these three industry
segments.
Table D-2 provides the cross-walk between NAICS codes and SIC codes for the profiled paper NAICS codes.
The table shows that both Pulp Mills and Paperboard Mills have a 1 to 1 relationship to their SIC codes. A large
portion of SIC code 2621 (84 percent based on value of shipments) corresponds to Newsprint Mills. NAICS
322121, classified as Paper (except newsprint) Mills, corresponds to three SIC codes (2621, 2676, and 3842).
Table D-2: Relationship between NAICS and SIC Codes for the Paper and Allied Products Industry
NAICS
Code
NAICS
Description
SIC
Code
SIC Description
Number of
Establishments
(As of 2009)a
Value of
Shipments (As
of 2010;
Millions;
$2011)
Employment
(As of 2010)
322110
Pulp mills
2611
Pulp mills
40
$4,328
6,296
322121
Paper (except
newsprint) mills
2621
2676
3842
Paper Mills
Sanitary Paper Products
Surgical Appliances and Supplies
246
$45,358
64,405
322122
Newsprint mills
2621
Paper Mills
25
$3,371
4,171
322130
Paperboard mills
2631
Paperboard mills
181
$27,958
35,183
a. The most recent data on number of establishments is available for 2009 from Statistics of U.S. Businesses. Value of Shipments and Employment reflect
2010 data.
Sources: U.S. DOC, 2010 ASM; U.S. DOC, 2009 SUSB
D.2 Summary Insights from this Profile
A key purpose of this profile is to provide insight into the ability of pulp and paper firms to absorb compliance
costs under the final rule without material adverse economic/financial effects. The industry's ability to absorb
compliance costs is primarily influenced by the following two factors: (1) the extent to which the industry may be
expected to shift compliance costs to its customers through price increases and (2) the financial health of the
industry and its general business outlook.
216 This estimate of the number of facilities potentially subject to regulation is based on the universe of facilities that received the 1999
screener questionnaire.
217 To compare revenue values of regulated facilities with the industry value of shipments, EPA brought revenue values for regulated
facilities forward to 2010 using industry-specific Producer Price Index (PPI) values published by the Bureau of Labor Statistics (BLS)
and stated in 2011 dollars using GDP deflator published by the Bureau of Economic Analysis (BEA).
D-2
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
D.2.1 Likely Ability to Pass Compliance Costs Through to Customers
As reported in the following sections of this profile, the Paper and Allied Products Industry is relatively
unconcentrated, which would suggest that firms in this industry may face difficulty in passing through to
customers a significant portion of their compliance-related costs. The domestic Pulp Mills industry segment also
faces significant competitive pressures from abroad, further curtailing the potential of firms in this industry to
pass through to customers a significant portion of their compliance-related costs. The domestic Paper Mills and
Paperboard Mills industry segments do not face as significant foreign competitive pressures, and, based on this
factor, would have more latitude in passing through to customers any increase in production costs resulting from
regulatory compliance. However, foreign pressure is likely to increase as capacity in foreign countries,
particularly China, continues to grow and exert pressure on the domestic market. As discussed above, given the
proportion of total value of shipments in the industry estimated to be subject to regulation under the final rule and
other options EPA considered, EPA judges that regulated facilities in the Paper and Allied Products Industry
subject to the 316(b) Existing Facilities Regulation are not likely to be able to recover compliance costs through
prices increases to customers. For these reasons, in its analysis of regulatory impacts for the Paper and Allied
Products Industry, EPA assumed that regulated facilities would be unable to pass compliance costs through to
customers: i.e., they must absorb all compliance costs within their operating finances (see following sections and
Appendix K: Cost Pass-Through Analysis for more information).
D.2.2 Financial Health and General Business Outlook
Over the past two decades, the Paper and Allied Products Industry, like other U.S. manufacturing industries, has
experienced a range of economic/financial conditions, including substantial challenges. Going into 2000, the
industry's financial performance started to improve from the erratic conditions of 1990s, but the subsequent
recession and global economic downturn, coupled with continuing overproduction, led to declining financial
results that persisted through 2003. Financial performance in 2004 through 2007 showed significant improvement
and steady growth. However, during the recent economic recession, the Paper and Allied Products Industry's
revenues and overall market value once again decreased significantly, but less so than the overall S&P 500 trend
(McNutt, 2009).
Throughout the past decade, the Paper and Allied Products Industry continued to face increased foreign
competition, global and domestic overcapacity, and difficulty adapting to changing business conditions (McNutt,
Cenatempo & Kinstrey, 2004). The industry outlook for 2013 is neutral, with continuing high pricing levels, due
to improvements in economic activity and increasing employment levels, being offset by negative long-term
demand trends (S&P, 2013f). With a number of indicators showing recovery since the recent financial downturn,
businesses potentially regulated by the final rule are likely to absorb additional regulatory compliance costs
without incurring a significant financial impact.
D.3 Domestic Production
The Paper and Allied Products Industry is one of the top ten U.S. manufacturing industries; the larger forest
products industry, which includes the paper and allied products subsector, accounts for approximately 5 percent of
the nation's GDP (AF&PA, 2009). Growth in the paper industry is generally tied closely to overall gross domestic
product (GDP) growth. Although, the domestic market consumes over 90 percent of total U.S. Paper and Allied
Products Industry output, beginning in 2000, exports took on an increasingly important role, and growth in a
number of foreign paper and paperboard markets became a key factor in the health and expansion of the U.S.
industry (McGraw-Hill, 2000). The Paper and Allied Products Industry is considered mature, with growth slower
than that of the GDP, and over the years U.S. producers have continued to seek growth opportunities in overseas
markets. Although exports still represent a small share of domestic shipments for the Paper and Paperboard mills
May 2014
D-3
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
segment, they exert an important marginal influence on capacity utilization. Prices and industry profits, which are
sensitive to capacity utilization, have therefore become increasingly sensitive to trends in global markets.
The U.S. Paper and Allied Products Industry has a worldwide reputation as a high quality, high volume, and low-
cost producer. The industry benefits from many key operating advantages, including a large domestic market; the
world's highest per capita consumption; a modern manufacturing infrastructure; adequate raw material, water, and
energy resources; a highly skilled labor force; and an efficient transportation and distribution network (Stanley,
2000). Over the last two decades, U.S. producers have faced growing competition from new facilities constructed
overseas, however (McGraw-Hill, 2000). The 2009 AF&PA Annual Survey of Paper, Paperboard, and Pulp
Capacity reports that the average annual rate of contraction from 2001 to 2007 hovered around 1 percent, largely
as a result of foreign competition and more recently, the domestic economic recession (AF&PA, 2009). Industry
capacity for multiple paper grades continued to decline in more recent years as producers sought a balance in
supply and demand for categories of production suffering from overcapacity (S&P, 2013f).
The Paper and Allied Products Industry is a major energy user, second only to the chemicals and metals
industries. However, 56 percent of total energy used in 1998-1999 was self-generated electricity (McGraw-Hill,
2000). The use of renewable resources (biomass, black liquor, hydroelectric, etc.) for energy production has
increased steadily over the past several decades, rising from 40 percent of total industry energy consumption in
1972 to 56 percent in 2000. Renewable resource-based energy was estimated to account for about 60 percent of
consumption in 2004 (PaperAge, 2004a).
With the slowing of the U.S. economy in 2000, and the onset of recession in 2001, the resulting drop in demand
and prices put pressure on companies in the industry to eliminate excess capacity. Through aggressive
consolidation and streamlining of their operations, facilities sought to lower expenses through elimination of older
and less cost efficient operations. In 2002, paper companies eliminated three million tons of capacity, with similar
reductions expected in 2003 (Value Line, 2003). While this consolidation led to a balance in supply and demand
and subsequent relative financial soundness, the Paper and Paperboard industry segment suffered from the 2008-
2009 recession with nearly all grades and segments recording declines in global consumption. One exception,
tissue paper, grew 1.0 - 1.5 percent in 2009 (Uutela, 2010).
The connection between business activity and office paper demand is eroding as electronic substitution, such as
online bill paying, email, internet publications, and electronic readers, become viable substitutes for several uses
of paper (S&P, 2010a). For instance, in 1999, newsprint demand was at its peak but with the advent and growing
popularity of the internet, domestic newsprint demand has fallen 57 percent in ten years (Timonen, 2010).
However, paper as a means for transmitting and storing information is far from being obsolete. Global paper
consumption increased dramatically in the decade prior to the economic recession, and will continue to rise
especially in developing countries (Environmental Paper Network, 2007).
D.3.1 Output
The Paper and Allied Products Industry has experienced continued globalization and cyclical patterns in
production and earnings over the last two decades. Capital investments in the 1980s resulted in significant
overcapacity. U.S. producers experienced record sales in 1995. In 1996, lower domestic and foreign demand,
coupled with declining prices, caused the industry's total shipments to decline by 2.2 percent. Three consecutive
years of increasing demand and slowly increasing prices led to better industry performance at the end of the
1990s. During these years, domestic producers controlled operating rates to allow drawdown of high inventories
and to achieve higher capacity utilization. U.S. producers also placed a greater emphasis on foreign markets both
through export sales and investments in overseas facilities (McGraw-Hill, 2000). The paper industry segment
recorded improved sales and stronger earnings in 1999 and early 2000, but began to experience declines in sales
in the second half of 2000, reflecting reduced paper and packaging demand due to the slowdown in the U.S.
economy and a growth in imports (S&P, 2001c). Most products were characterized by weak demand, reduced
D-4
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
production and price reductions in 2001, due to continuing reductions in domestic demand (Paperloop Inc., 2001).
Annual sales in the United States in 2001 dropped 1.5 percent, while earnings at the top 31 U.S. corporations fell
by nearly 75 percent, partly due to a decrease in prices of up to 15 percent (Paun et al., 2004).
Capacity for the U.S. Paper and Paperboard segment declined annually from 2001 to 2003, in contrast to annual
increases in capacity for the previous two decades. Capacity declined 1.9 percent in 2001, 1.3 percent in 2002,
and 0.4 percent in 2003, and remained largely unchanged from 2004 to 2006 due to increased foreign
competition, mature domestic markets, and competition from other media (PaperAge, 2004b). Overcapacity has
been a problem within the industry. As the world economy began to slow in the early 2000s, demand in the
United States and abroad waned, forcing producers to limit production to prevent oversupply and keep pricing
levels from dropping further (S&P, 2004b). In addition to production downtime, many older, less efficient, single
mill operations were permanently closed. In 2001, pulp production decreased 7.3 percent to 53 million tons, while
paper and paperboard production decreased 5.5 percent to 81 million tons (Paun et al., 2004). During the rest of
the decade, however, the overall production for the U.S. Paper and Allied Products Industry remained relatively
flat until the recession of 2008-2009, when production of all grades began to decline.218 Only tissue production
remained strong during the recessionary period (McNutt, 2009). During 2009 alone, total printing-writing paper
shipments experienced a 17 percent decline, shipments for Kraft paper fell by 16 percent and containerboard by
9.5 percent (AF&PA, 2009). Although these industry segments showed decline in total output, the last quarter of
2009 saw relative production increases from the previous months, and signaled the beginning of recovery from
the economic downturn.
Figure D-l shows the trend in value of shipments and value added for the three profiled segments.219 Value of
shipments and value added, two common measures of manufacturing output, provide insight into an industry's
overall economic health and outlook. Value of shipments is the sum of receipts from the sale of outputs; it
indicates the overall size of a market or the size of a firm in relation to its market or competitors. Value added
measures the value of production activity in a particular industry and is calculated as the difference between the
value of shipments and the value of inputs from other industries used to make the products sold.
Between 1987 and 2010, the Paper and Allied Products Industry performed erratically, with swings in value of
shipments and value added generally following the performance trend of the aggregate U.S. economy. Of the
three profiled industry segments, the Paperboard Mills segment recorded an overall increase in the total value of
shipments and value added during the 24-year analysis period, while both the Paper Mills and the Pulp Mills
segments recorded real declines over the same period, with Pulp Mills faring the worst. Moreover, the recent
downturn in the housing market has been particularly disruptive for this industry. Stagnant new home sales have
left saw mills unable to sell lumber products, forcing many to shut down operations. As a result, these closings
have caused the price of inputs such as wood chips and kraft pulp to increase. The combination of rising input
prices and a sharp decline in demand has led manufacturers to sell their products at a loss thereby reducing the
total value of shipments for this industry in recent years (Great American Group, 2009). During 2010, value of
shipments has continued to decline in the Pulp Mills segment, though to a lesser extent. In the Paper Mills
segment value of shipments increased by less than 1 percent while in the Paperboard Mills segment it increased
by 17 percent. While projections for long-term demand trends remain negative, prices are expected to remain
relatively high in 2013 (S&P, 2013f).
218 Grades are product categories such as containerboard, packaging, printing & writing papers, newsprint, and tissue.
219 Terms highlighted in bold and italic font are further explained in the glossary.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
Figure D-1: Value of Shipments and Value Added for Profiled Paper and Allied Products Segments (Millions, $2011)a
Value of Shipments
S80,000
o
N
s
o
E
VI
"8
3
3
S70.000
S60,000
S50,000
S40,000
S30,000
S20,000
S10,000
Paper Mills (NAICS
32212)
Paper Mills (SIC to
NAICS)
Paperboard Mills (NAICS
322130)
—«— Paperboard Mills (SIC to
NAICS)
—A— Pulp Mills (NAICS
322110)
—A— Pulp Mills (SIC to NAICS)
OCOCOC'nS'>C<>C<>C'>CinSinSinSinSinSOOOOOOOOOO^
s) OC C w h ( J W 'Jl ^ s) se c C (J W ^ oc c c
Value Added
&
<
s
3
S40,000
S35,000
S30,000
S25,000
S20,000
S15,000
S10,000
S5,000
SO

.A'
"A- A.
A A a A
-A A-
Paper Mills (NAICS 32212)
— Paper Mills (SIC to NAICS)
-~— Paperboard Mills (NAICS
322130)
Paperboard Mills (SIC to
NAICS)
-A— Pulp Mills (NAICS 322110)
—A— Pulp Mills (SIC to NAICS)
i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—i—r
M ~ > M M M M M N N N N N N N N N N N
oooooooooooooooooooooooo
icicscooooooccccoooooooooo —
v)5C'CO^tJW4i^^-goeCO«-WW4i^Cs^OCCO
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American Industry
Classification System (NAICS). For this analysis, EPA converted the SIC classification data to the NAICS code classifications using the 1997 Economic
Census Bridge Between SIC and NAICS.
Source: U.S. DOC, 1988-1991,1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987,1992, 1997, 2002, and 2007
EC
Table D-3 provides the Federal Reserve System's index of industrial production for the profiled Paper and Allied
Products Industry segments, which shows trends in production between 1990 and 2011. This index more closely
reflects total output in physical terms, whereas value of shipments and value added reflect the economic value of
production. The production index is expressed as a percentage of output in the base year, 2007. Overall, between
1990 and 2011, production for all three segments declined, with the Paper Mills segment experiencing the largest
decline of 27 percent. During 2008 and 2009, production fell in all three profiled segments as the result of
economic recession, with the Pulp Mills segment experiencing the largest reduction of approximately 16 percent.
Industrial production in the Pulp Mills segment continued to decline significantly in 2010 but has rebounded in
D-6
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
2011 with a nearly 7 percent increase. In the Paper Mills and Paperboard segments, industrial production
recovered slightly in 2010 only to decline in 2011.
Table D-3: U.S. Paper and Allied Products Industry Industrial Production Index (Annual Averages)
Year
Pulp Mills3
Paper Millsb
Paperboard Mills0
Index
2007=100
Percent
Change
Index
2007=100
Percent
Change
Index
2007=100
Percent
Change
I 990
85.3
NA
1 16.7
NA
95.1
NA
I 991
86.6
1.6%
1 12.8
-3.3%
94.2
-1.0%
I 992
911
5.2%
111.5
-1.2%
98.4
4.4%
I 993
76.5
-16.0%
1 10.8
-0.6%
100.5
2.1%
1994
81.0
5.9%
1 17.0
5.6%
106.3
5.8%
1995
87.1
7.5%
121.0
3.4%
1 10.2
3.7%
I 996
79.9
-8.3%
1 13.9
-5.9%
105.0
-4.7 %
1997
79.5
-0.4%
1 12.7
-1.0%
107.6
2.5%
I 998
81.7
2.7 %
1 13.3
0.5%
108.7
1.0%
I 999
82.3
0.8%
1 18.4
4.5%
1 10.2
1.4%
2000
81.2
-1.4%
1 16.0
-2.0%
105.6
-4.1%

82.9
2.1%
107.6
-7.3%
101.5
-3.9%
2002
101.3
22.3%
106.9
-0.7%
102.1
0.6%
2003
102.7
1.3%
103.3
-3.3%
98.6
-3.5%
2004
98.5
-4.0%
106 9
3.4%
98.1
-0.5%
2005
95.0
-3.6%
107.6
0.7%
93.7
-4.5%
2006
93.2
-1.9%
105 8
-1.7%
96 3
2.7 %
2007
99.9
7.2%
100.0
-5.5%
100.0
3.9%
2008
97.8
-2.2%
99 1
-0.9%

-8.3%
2009
83.2
-14.9%
87.1
-12.1%
87.1
-5.0%
20I0
72.2
-13.3%
87.6
0.6%
95.0
9.0%
2011
77.0
6.7%
85.2
-2.8%
94.2
-0.9%
Total Percent Change
1990-2011
-9.7%
-27.0%
-1.0%
Total Percent Change
2000-2011
-5.1%
-26.6%
-10.8%
Average Annual
Growth Rate220 1990 -
2011
-0.5%
-1.5%
0.0%
a. NAICS 32211.
b. NAICS 32212.
c. NAICS 32213.
Source: Federal Reserve Board of Governors, 2012b
D.3.2 Prices
The producer price index (PPI) measures price changes, by segment, from the perspective of the seller, and
indicates the overall trend of product pricing, and thus supply-demand conditions, within a segment.
Price levels in the U.S. Paper and Allied Products Industry closely reflect domestic and foreign demand, and
industry capacity and operating rates, which determine supply (S&P, 2001c). Prices tend to be volatile due to
mismatches between short-term supply and demand. The industry is very capital intensive, and development of
new capacity requires several years. Prices therefore tend to increase when demand and capacity utilization rise,
and drop sharply when demand softens or when new capacity comes on line. In the past, producers have been
reluctant to cut production when demand declines because fixed capital costs are a substantial portion of total
manufacturing costs; this reluctance has occasionally caused persistent oversupply. During the economic
220 In this appendix, average annual growth rate refers to a year-to-year, constant percentage growth mean, which is calculated as the
compound annual growth rate between the first and last values. This is the same concept as the geometric mean, if all of the individual
year-to-year values are the same as those used in calculating the constant percentage growth mean.
May 2014
D-7
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
slowdown of 2001, however, producers appeared more willing to cut output to prevent sharp reductions in prices
(Ince, 1999; S&P, 2001c).
As shown in Figure D-2, the Paper and Allied Products Industry suffered from low prices throughout the early
1990s. The depressed prices resulted from the paper boom of the late 1980s. Prices recovered in the mid-1990s
before declining again in the latter part of that decade. Entering the 2000s decade, prices in the Paper and Allied
Products Industry reversed course and rose, before experiencing declines in 2001 and 2002, as prices for most
paper grades dropped between 5 and 15 percent (Value Line, 2003). Faced with substantial declines in demand
during those years, producers cut production, endured downtime, and closed less efficient facilities to prevent
major price declines for paper products (S&P, 2001c). Prices started to level off near the end of 2002, and
proceeded to rise during 2003 through 2007.
In 2008, Paper and Allied Products Industry prices reached near historical peak levels. Overall, following the
recession, prices remained comparable to the strong 2008 averages. Prices for many grades of paper trended
higher for most of 2008 due in part to capacity closures. Market pulp prices have fallen sharply and quickly in
2009 (McNutt, 2009). Paperboard prices also fell drastically in 2009. However, Paper and Allied Products
Industry manufacturers have exhibited more resilient prices compared to other industries during the current
economic downturn (Cody, 2009). As the world economy began to recover in 2010, so did the prices for all three
profiled segments; in fact, in 2010, prices increased to levels that surpassed the 2008 averages.
Figure D-2: Producer Price Indexes for Profiled Paper and Allied Products Segments
- Paperboard Mills (NAICS
322130)
- Paper Mills (NAICS
32212)
- Pulp Mills (NAICS
322110)
S S S S S S S S S S S S © © © ©
ce do « 's© 'so 'so 'so 'n© 's© 'so o © © © ©
OC M W 4i 'Jl ^ 56 'sC © — M U*
U tJ W
*>¦ 'Jl C\ -s] jC c © -
Source: BLS, 2011c
D.3.3 Number of Facilities and Firms
Table D-4 and Table D-5 present the number of facilities and firms for the three profiled Paper and Allied
Products Industry segments between 1990 and 2009. During the last two decades, the number of facilities and
firms in all three segments behaved erratically, with drastic increases and declines from one year to the next.
Overall, the number of facilities declined in all three profiled segments, with Paper Mills experiencing the largest
decline of more than 39 percent at an average annual decline rate of approximately 3 percent. During the last
decade however, the Paperboard Mills experienced the largest decline in the number of facilities of nearly 24
percent.
D-8
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
One reason for this decline in the number of facilities in the Pulp Mills sector was the increase in the number of
mills that produce de-inked recycled market pulp and thus displace demand for virgin pulp mill product. These
are secondary fiber processing plants that use recovered paper and paperboard as their sole source of raw material.
Producers of de-inked market pulp have experienced strong demand over the past several years in both U.S. and
foreign markets. In fact, U.S. de-inked recycled market pulp capacity more than doubled between 1994 and 1998
(McGraw-Hill, 2000). The secondary fiber share of total papermaking fiber production increased steadily during
the decade, reaching 37 percent in 1999 (McGraw-Hill, 2000). Overcapacity in the 1990s limited the construction
of new facilities. In 1998 and 1999, alone, 0.6 and 2.5 million tons of paper and paperboard capacity were
removed from the capacity base. Over the same period, more than one million tons of pulp capacity was removed
(Pponline, 1999). In 2001 and 2002, 8.2 million tons of capacity closed, mostly in containerboard, market pulp,
and print and writing papers (PaperAge, 2004c).
In terms of firms, however, the three profiled sectors behaved differently during the last two decades. Between
1990 and 2009, the number of parent firms in the Paper Mills and Paperboard Mills segments decreased by
approximately 27 percent and 19 percent, respectively. However, during the last decade, while the number of
firms in the Paperboard Mills segment decreased by 21 percent, the Paper Mills segment experienced an increase
of approximately 2 percent. Between 1990 and 2009, the number of firms in the Pulp Mills segment on average
remained the same, even though during the last decade it declined by approximately 14 percent.
There has been extensive restructuring and consolidation in the Paper Mills segment during the second half of
2000s decade, especially for containerboard producers - resulting in a higher concentration of top producers.
Boxboard and newsprint manufacturers have also experienced a significant number of closures. Newsprint is
perceived to be the weakest subsector of the Paper and Allied Products Industry, and may face additional
consolidation in the future (McNutt, 2009). Whereas it seems that other Paper and Allied Products Industry
product categories have merely suffered from volatility in the U.S. and global economy, newsprint and graphic
papers have demonstrated long-term decline in demand and susceptibility to closures due to increasing
competition from electronic products (AF&PA, 2009).
During 2007-2008, the number of firms and facilities in all three profiled Paper and Allied Products Industry
segments decreased due to industry contraction caused by global recession. As the global economy began to
recover in 2009, all three profiled segments saw an increase in the number of firms, while the number of facilities
either continued to decline or remained unchanged. It is possible that in their attempts to gain or to maintain their
financial stability, the incumbent firms closed some of their older and higher cost facilities and sold off other
facilities to newly emerging entities.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
Table D-4: Number of Facilities Owned by Firms in the Profiled Paper and Allied Products Segments

Pulp Mills"
Paper
Mills0
Paperboard Mills'1

Number of
Percent
Number of
Percent
Number of
Percent
Year3
Facilities
Change
Facilities
Change
Facilities
Change
1990
46
NA
327
NA
226
NA
1991
53
15.2%
349
6.7%
228
0.9%
1992
44
-17.0%
324
-7.2%
222
-2.6%
1993
46
4.5%
306
-5.6%
217
-2.3%
1994
52
13.0%
316
3.3%
218
0.5%
1995
53
1.9%
317
0.3%
219
0.5%
1996
62
17.0%
344
8.5%
228
4.1%
1997
41
-33.9%
259
-24.7%
214
-6.1%
1998
44
7.3%
235
-9.4%
232
8.4%
1999
45
2.3%
242
3.2%
233
0.4%
2000
48
6.7%
240
-1.0%
238
2.1%
2001
51
6.3%
238
-0.8%
247
3.8%
2002
44
-13.7%
271
14.0%
231
-6.5%
2003
38
-13.6%
287
5.9%
221
-4.3%
2004
43
13.2%
385
2.4%
221
0.0%
2005
43
0.0%
368
-4.4%
210
-5.0%
2006
44
2.3%
348
-5.4%
205
-2.4%
2007
26
-18.2%
328
-5.7%
187
-8.8%
2008
40
11.1%
275
-16.2%
189
1.1%
2009
40
0.0%
271
-1.5%
181
-4.2%
Total Percent Change
1990-2009
-13.0%
-39.3%
-19.9%
Total Percent Change
2000-2009
-16.7%
-12.9%
-23.9%
Average Annual
Growth Rate
-0.7%
-2.6%
-1.2%
a. Before 1997, data were compiled in the SIC system; since 1997, these data have been compiled in the North American Industry Classification System
(NAICS). For this analysis,
2PA converted the SIC classification data to the NAICS code classifications using the 1997 Economic Census Bridge Between
SIC and NAICS.

b. NAICS 322110.

c. NAICS 32212.

d. NAICS 322130.

Source: U.S. DOC, 1990-1997SBA; U.S. DOC, 1998-2009 SUSB

D-10
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
Table D-5: Number of Firms in the Profiled Paper and Allied Products Segments
Year3
Pulp Mills"
Paper Mills0
Paperboard Mills'1
Number of
Firms
Percent
Change
Number of
Firms
Percent
Change
Number of
Firms
Percent
Change
I 990
31
NA
238
NA
102
NA
I 991
37
19.4%
274
14.7%
102
0.0%
I 992
29
-21.6%
256
-6.3%
95
-6 9%
I 993
32
10.3%
248
-3.1%
99
4.2%
1994
37
15.6%
261
5.1%
96
-3.0%
199 5
32
-13.5%
259
-0.7%
93
-3.1%
I 996
43
34.4%
277
6.7%
101
8.6%
1997
27
-37.2%
232
-16.1%
85
-15.8%
I 998
32
18.5%
158
-31.9%
95
1 1 8%
I 999
33
3.1%
169
7.0%
95
0.0%
2000
36
9.1%
171
1.2%
105
10 5%

40
11.1%
179
4.7 %
1 16
10.5%
2002
27
-32.5%
224
25.1%
107
-7.8%
2003
27
0.0%
210
-6.3%
90
-15.9%

31
14 8%
226
7.6%
92
2.2%
2005
30
-3.2%
211
-6.6%
88
-4.3%
2006
31
3.3%
197
-6.6%
87
-1.1%
2007
26
-16.1%
198
0.5%
80
-8.0%
2008
29
1 1.5%
169
-14.6%
81
1.3%
2009
31
6.9%
174
3.0%
83
2.5%
Total Percent Change
1990-2009
0.0%
-27.0%
-18.6%
Total Percent Change
2000-2009
-13.9%
1.8%
-21.0%
Average Annual
Growth Rate
0.0%
-1.6%
-1.1%
a. Before 1997, data were compiled in the SIC system; since 1997, these data have been compiled in the North American Industry Classification System
(NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic Census Bridge Between
NA1CS and SIC.
b. NAICS 322110.
c. NAICS 32212.
d. NAICS 322130.
Source: U.S. DOC, 1990-1997SBA; U.S. DOC, 1998-2009 SUSB
D.3.4 Employment and Productivity
The U.S. Paper and Allied Products Industry is among the most modern in the world. It has a highly skilled labor
force and is characterized by large capital expenditures, which have been principally aimed at productivity
improvements.
Beginning in 1987 through the mid-1990s, employment in the three profiled Paper and Allied Products Industry
segments remained relatively constant. Since 1996, employment at Pulp Mills has dropped considerably,
decreasing by 58 percent by 2010. Paper Mills also saw a substantial reduction in the workforce of more than 50
percent in the same period. Employment in Paperboard Mills fell the least over this period, but still declined by
nearly 36 percent. Part of this employment loss is attributable to firms closing older and higher cost facilities with
lower employee productivity (McNutt, Cenatempo & Kinstrey, 2004). Pulp, Paper, and Paperboard Mills as a
whole have faced serious losses in employment beginning in the late 1990s and continuing into the 2000s.
Employment in the Paperboard Mills segment began to increase in 2009 and continued through 2010. Despite the
signs of global economic recovery, for the Pulp Mills and Paper Mills segments, employment losses continued
through 2010. Figure D-3 presents employment for the three profiled Paper and Allied Products Industry
segments between 1987 and 2010.
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Appendix D: Paper Industry Profile
Figure D-3: Employment for Profiled Paper and Allied Products Segments3
>
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Appendix D: Paper Industry Profile
Table D-6: Productivity Trends for Profiled Paper and Allied Products Segments ($2011)
Year3
Pulp Mills
Paper Mills
Paperboard Mills
Value
Added
($ mil)
Prod.
Hrs.
(mil)
Value
Added/Hour
Value
Added
($ mil)
Prod.
Hrs.
(mil)
Value
Added/Hour
Value
Added ($
mil)
Prod.
Hrs.
(mil)
Value
Added/Hour
$/hr
Percent
Change
$/hr
Percent
Change
$/hr
Percent
Change
1987
$3,990
24
167
NA
$30,657
248
124
NA
$12,092
89
137
NA
1988
$5,269
24
220
32.1%
$34,368
251
137
11.0%
$14,842
91
163
19.6%
1989
$6,417
25
253
14.6%
$34,713
249
139
1.5%
$14,335
89
161
-1.7%
1990
$5,359
28
193
-23.4%
$32,797
248
132
-5.0%
$12,743
91
141
-12.4%
1991
$3,706
28
134
-30.6%
$30,732
250
123
-7.0%
$10,995
87
127
-9.7%
1992
$3,781
26
144
7.1%
$28,682
254
113
-8.3%
$12,128
88
137
7.9%
1993
$2,478
23
107
-25.4%
$27,726
252
1 10
-2.4%
$10,897
90
121
-1 1.8%
1994
$2,968
22
136
27.0%
$28,233
244
1 16
5.0%
$12,310
94
131
8.5%
1995
$5,441
23
241
76.8%
$38,137
238
160
38.7 %
$17,579
98
180
37.1%
1996
$3,000
24
126
-47.9%
$32,547
235
139
-13.6%
$13,161
95
139
-23.0%
1997
$2,019
13
156
24.5%
$33,061
236
140
0.9%
$12.1 1 1
93
130
-6.2%
1998
$1,860
12
149
-4.4%
$32,865
225
146
4.4%
$13,391
90
148
14.1%
1 999
$1,883
12
161
7.7%
$33,307
218
153
4.7%
$13,614
86
158
6.6%
2000
$2,334
12
196
22.0%
$34,519
202
170
1 1.5%
$15,222
86
176
1 1.5%
2001
$1,766
12
148
-24.9%
$31,032
190
164
-4.0%
$13,781
83
165
-6.3%
2002
$2,064
13
164
1 1.2%
$32,075
173
185
13.1%
$13,262
75
176
6.3%
2003
$1,999
13
151
-8.2%
$28,975
164
177
-4.3%
$12,300
74
165
-6.0%
2004
$2,173
13
167
1 1.0%
$29,396
155
190
7.1%
$12,143
67
180
9.2%
2005
$1,903
12
155
-7.3%
$30,552
161
190
0.2%
$1 1.323
63
178
-1.0%
2006
$1,939
12
158
1.9%
$30,725
146
211
10.7%
$12,941
62
210
17.8%
2007
$2,425
13
188
19.0%
$27,949
138
203
-3.7%
$13,222
64
207
-1.2%
2008
$2,399
13
180
-4.0%
$27,964
132
212
4.4%
$12,194
60
202
-2.7%
2009
$1,924
1 1
171
-5.4%
$26,603
122
219
3.2%
$12,384
58
213
5.8%
2010
$2,079
1 1
198
15.8%
$25,745
115
224
2.3%
$13,750
59
233
9.0%
Total % Change
1987-2010
-47.9%
-56.0%
18.5%
-16.0%
-53.6%
81.0%
13.7%
-33.3%
70.4%
Total Percent
Change 2000-
2010
-11.0%
-11.6%
0.7%
-25.4%
-43.1%
31.1%
-9.7%
-31.5%
32.0%
Average Annual
Growth Rate
-2.8%
-3.5%
0.7%
-0.8%
-3.3%
2.6%
0.6%
-1.7%
2.3%
a. Before 1997, data were compiled in the SIC system; since 1997, these data have been compiled in the North American Industry Classification System
(NAICS). For this analysis, EPA converted the SIC classification data to the NAICS code classifications using the 1997 Economic Census Bridge Between
SIC andNAlCS.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007
EC
D.3.5 Capital Expenditures
The Paper and Allied Products Industry is highly cyclical and capital intensive. Capital-intensive industries are
characterized by a large value of capital equipment per dollar value of production. New capital expenditures are
needed to modernize, expand, and replace existing capacity. The total level of capital expenditures for the profiled
Paper and Allied Products Industry was $3.5 billion in 2010. The Paper Mills and Paperboard Mills segments
accounted for approximately 89 percent of that spending (see Table D-7). Most of the spending is for production
improvements (through existing machine upgrades, retrofits, or new installed equipment), environmental
concerns, and increased recycling (McGraw Hill, 2000). The total capital expenditure during recent years has
been considerably less, in real terms, than what was spent in the early 1990s, as producers became wary of adding
too much capacity that might lead to oversupply and depressed prices.
Overall, during 1987 through 2010, the Paper Mills segment experienced the largest reduction in capital
expenditures (64 percent), followed by the Paperboard Mills segment (6 percent) and the Pulp Mills segment (2
percent). The Department of Commerce estimates that environmental spending accounted for about 14 percent of
all capital outlays made by the U.S. Paper and Allied Products Industry since the 1980s, and the Cluster Rule
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
promulgated in 1998 is expected to have encouraged increased environmental expenditures (S&P, 2001c). North
American producers have improved production asset quality in the latter half of the 2000s through incremental
investment and closure of uncompetitive lines. Between 1999 and 2007, the median age of paper machine lines
decreased by 23 percent. During the same time, the average maximum speed of paper machine lines increased by
33 percent, the average width by 35 percent, and the average capacity by 20 percent (McNutt, 2009). However, it
was suggested that some industries, such as containerboard producers, had been successful enough at matching
supply with demand that investment in new capital became an attractive option in 2010 (Waghorne, 2010).
Indeed, during 2010, capital expenditures increased by more than 41 percent for Paperboard Mills, after a loss of
38 percent in the previous year as a result of the economic downturn. Pulp Mills and Paper Mills also saw
increases in capital expenditures, following significant declines in 2009, of 38 percent and 45 percent,
respectively.
Table D-7: Capital Expenditures for Profiled Paper and Allied Products Segments (millions, $2011)
Year3
Pulp Mills
Paper Mills
Paperboard Mills
Capital
Expenditures
Percent
Change
Capital
Expenditures
Percent
Change
Capital
Expenditures
Percent
Change
1987
$404
NA
$5,239
NA
$1,351
NA
1988
$523
29.3%
$6,008
14.7%
$2,566
89.9%
1989

1 17.2%
1)74
51.0%
C>94
5.0%
1990
$1,653
45.6%
149
-21.2%
C>69
73.4%
1991
501
-9.2%
892
-17.6%
$3,261
-30.2%
1992

-23.9%
$4,653
-21.0%
$3,020
-7.4%
1993
$617
-46.0%
Ml
-0.3%
$2,379
-21.2%
1994

-27.5%
917
5.9%
$2,476
4.1%
1995
$642
43.5%
$4,345
-1 1 6%
906
17.3%
1996
$952
48.2%
779
10.0%
$3,217
10.7%
1997
$462
-51.5%
1)48
5.6%
162
-32.8%
1998

19.3%
274
4.5%
846
-14 6%
1 999
$244
-55.8%
$3,985
-24.4%
C>6I
-10.0%
2000
$303
24.2%
$4,220
5.9%

-8.8%
2001
$241
-20.3%
$3,936
-6.7%
$1,286
-15.1%
2002
$230
-4.6%
$3,433
-12.8%
$1,006
-21.8%
2003
$219
-4.7%
$3,303
-3.8%
$921
-8.4%

$220
0.2%
$2,380
-27.9%
$1,086
17.9%
2005
$136
-38.0%
$2,572
8.1%

5.2%
2006
$399
193.0%
$2,456
-4.5%
$1,091
-4.5%
2007
$294
-26.2%
$2,417
-1.6%
$1,205
10.5%
2008
$358
21.5%
$2,013
-16.7%
$1,449
20.2%
2009
$288
-19.4%
$1,320
-34.4%
$899
-38.0%
2010
$397
37.8%
$1,911
44.7%
$1,273
41.6%
Total Percent Change
1987-2010
-1.7%
-63.5%
-5.8%
Total Percent Change
2000-2010
31.4%
-54.7%
-16.0%
Average Annual
Growth Rate 1987 -
2010
-0.1%
-4.3%
-0.3%
a. Before 1997, data were compiled in the SIC system; since 1997, these data have been compiled in the North American Industry Classification System
(NAICS). For this analysis, EPA converted the SIC classification data to the NAICS code classifications using the 1997 Economic Census Bridge Between
SIC and NAICS.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007
EC
D.3.6 Capacity Utilization
Capacity utilization measures actual output as a percentage of total potential output given the available capacity.
Capacity utilization provides insight into the extent of excess or insufficient capacity in an industry, and into the
likelihood of investment in new capacity.
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Appendix D: Paper Industry Profile
As shown in Figure D-4, capacity utilization fluctuated sharply in all three profiled segments over the analysis
period. Capacity utilization increased between 1989 and 1994, and then fell sharply in 1995. This sharp drop
resulted from an effort to reduce inventories, which began rising in 1995 in response to low demand and
oversupply (McGraw-Hill, 2000). As inventories were sold off and global economic activity strengthened,
capacity utilization began to rise again in 1996, peaked in 1997, and again declined in 1998 due to reduced
demand from the Asian market (S&P, 2001c). With the global economic slowdown starting in 2000, paper
producers were forced to implement production cutbacks and downtime to prevent oversupply from further
depressing prices. As a result, utilization rates fell farther in 2000 and 2001 to values below those observed in the
prior decade. At the same time, overall capacity contracted as companies permanently closed less efficient
facilities. By 2004, capacity utilization in the Paperboard Mills and Pulp Mills industry segments had returned to
its 1990 level, while capacity utilization in the Pulp Mills industry segment increased between 2001 and 2002 and
remained relatively constant over 2003 to 2004.
In the second half of the 2000s decade, capacity utilization rose substantially for Paperboard and Pulp Mills
previous to the economy collapse in 2008. During this same period, capacity utilization for Paper Mills fluctuated,
but remained fairly low. Producers of many grades curtailed production and capacity in those categories suffering
from overcapacity in an effort to improve the balance between supply and demand (S&P, 2010a). U.S. paper and
paperboard capacity edged down 0.8 percent in 2008 to 96.3 million tons, and declined 7.3 percent cumulatively
since its 2000 peak level (AF&PA, 2009).
During 2008 through 2010, capacity utilization declined almost steadily. Boxboard and containerboard producers
experienced increasing excess capacity, but still below 2001 to 2003 levels. The market pulp and printing and
writing papers sectors also experienced relatively high levels of excess capacity/low capacity utilization, but this
was expected to be remedied by recovery from the economic recession. For the struggling newsprint industry,
supply and demand were kept in balance through capacity rationalization, but further cutbacks were expected
(McNutt, 2009). Overall, total capacity for Paper and Paperboard Mills was slated to expand by 0.3 percent in
both 2010 and 2011, with uncoated mechanical paper, tissue paper, linerboard, corrugating medium, and market
pulp being forecast as the most successful product grades (AF&PA, 2009). However, despite the signs of
economic recovery during 2010, the profiled Paper and Allied Products Industry still suffered from excess
capacity; the Pulp Mills and Paper Mills segments each saw a decline in capacity utilization (approximately 5
percent and 7 percent, respectively), while capacity utilization in the Paperboard Mills segment remained
constant. The fact that capacity utilization either declined or remained unchanged coupled with increases in
production and capital expenditures across all three profiled segments, signals that in 2010, capacity expansion as
the result of economic recovery outpaced demand for Paper and Allied Products.
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Appendix D: Paper Industry Profile
Figure D-4: Capacity Utilization Rate (Fourth Quarter) for Paper and Allied Products Segments a,b
—~— Paperboard Mills (SIC to NAICS) —~— Paperboard Mills (NAICS 322130)
—i- - Pulp Mills (SIC to NAICS) —*— Pulp Mills (NAICS 322110)
--¦—Paper Mills (SIC to NAICS) ¦ Paper Mills (NAICS 32212)
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the SIC classification data to the NAICS code classifications using the 1997
Economic Census Bridge Between SIC and NAICS.
b. Before 2007, U.S. Census sampled every industry in a specific NAICS6. Beginning in 2007, U.S. Census only sampled certain industries within any
NAICS6, and therefore, the data collected before 2007 cannot be directly compared to the data collected in 2007 and beyond.
Source: U.S. DOC, 1989-2006 SPC;U.S. DOC, 2007-2010 SPC data M'as obtained from the Census Bureau, however the data do not
meet the criteria outlined in the Census Bureau's Statistical Quality Standard: Releasing Information Products. Data is included here
for completeness as it is the only data available for Capacity Utilization for these years
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D.4 Structure and Competitiveness
The Paper and Allied Products Industry companies range in size from large corporations with billions of dollars of
sales, to small producers with revenue a fraction of the size of the large producers. Because all Paper and Allied
Products companies use the same base materials in their production, most manufacture more than one product. To
escape the extreme price volatility of commodity markets, many smaller manufacturers have differentiated their
products by offering value-added grades. The smaller markets for value-added products make this avenue less
available to the larger firms (S&P, 2001c).
The Paper and Allied Products Industry consolidated through mergers and acquisitions and has closed older mills
during the last two decades as a way to improve profits in a mature industry. About six percent of North American
containerboard capacity was shut down (most were on a permanent basis) in late 1998 and early 1999. Companies
were reluctant to invest in any major new capacity, which might result in excess capacity (S&P, 2001c). In 1999,
new capacity additions in the Paper and Allied Products Industry were at their lowest level of the past ten years
(Pponline.com, 2000); this caution in adding to capacity has continued through the 2000 to 2010 decade. Another
problem for the industry has been the increasing capacity being brought online in foreign countries (S&P, 2004a).
U.S. mills responded to the increased foreign competition by cutting capacity and retiring obsolete equipment
and, with help from private equity investors, had succeeded in constraining supply and improving average product
quality, hoping to improve long-term returns. Moreover, the devaluation of the dollar towards the end of the last
decade made domestic paper products more affordable than foreign goods (Great American Group, 2009).
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Appendix D: Paper Industry Profile
Major mergers in the most recent decade include International Paper's acquisition of Champion International in
2000 and Union Camp in 1999, Georgia-Pacific's takeover of Fort James Corp. (itself a 1997 combination of
James River and Fort Howard), Weyerhaeuser's acquisition of Willamette Industries Inc., the merger of Mead and
Westvaco, and Temple-Inland's takeover of Gaylord Container (S&P, 2001c, 2004b).
D.4.1 Firm Size
For this industry, the Small Business Administration defines a small firm as having fewer than 750 employees.
The size categories reported in the Statistics of U.S. Businesses (SUSB) do not correspond with the SBA size
criteria, therefore preventing precise use of the SBA size threshold in conjunction with SUSB data. The SUSB
data presented in Table D-8 show the following size distribution in 2009:
> 21 of 31 (68 percent) firms in the Pulp Mills segment had less than 500 employees. Therefore, at least 68
percent of firms were classified as small. These small firms owned 22 facilities, or 55 percent of all
facilities in the segment.
> 128 of 174 (74 percent) firms in the Paper Mills segment had less than 500 employees. These small firms
owned 131, or 48 percent of all Paper Mills.
> 49 of 83 (59 percent) firms in the Paperboard Mills segment had less than 500 employees. Therefore, at
least 59 percent of paperboard mills were classified as small. These firms owned 53, or 29 percent of all
Paperboard Mills.
An unknown number of the firms with more than 500 employees have less than 750 employees, and would
therefore also be classified as small firms. Table D-8 below shows the distribution of firms and facilities for each
profiled segment by employment size of the parent firm.
Table D-8: Number of Firms and Facilities by Size Category for Profiled Paper and Allied Products
Segments in 2009

Employment Size
Category
Pulp
Mills
Paper Mills
Paperboard Mills
No. of Firms
No. of
Facilities
No. of Firms
No. of
Facilities
No. of Firms
No. of
Facilities
0-19
1 1
1 1
65
65
20
20
20-99
7
7
28
28
12
13
100-499
3
4
35
38
17
20
500+
10
18
46
140
34
128
Total
31
40
174
271
83
181
Source: U.S. DOC, 2009 SUSB
D.4.2 Concentration Ratios
Concentration is the degree to which industry output is concentrated in a few large firms. Concentration is
closely related to entry barriers, with more concentrated industries generally having higher barriers.
The four-firm concentration ratio (CR4) and the Herfindahl-Hirschman Index (HHI) are common measures of
industry concentration. The CR4 indicates the market share of the four largest firms. For example, a CR4 of 72
percent means that the four largest firms in the industry account for 72 percent of the industry's total value of
shipments. The higher the concentration ratio, the less competition there is in the industry, other things being
equal.3 An industry with a CR4 of more than 50 percent is generally considered concentrated. The HHI indicates
3 Note that the measured concentration ratio and the HHI are very sensitive to how the industry is defined. An industry with a high
concentration in domestic production may nonetheless be subject to significant competitive pressures if it competes with foreign
producers or if it competes with products produced by other industries (e.g., plastics vs. aluminum in beverage containers).
Concentration ratios based on share of domestic production are therefore only one indicator of the extent of competition in an
industry.
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Appendix D: Paper Industry Profile
concentration based on the largest 50 firms in the industry. It is equal to the sum of the squares of the market
shares for the largest 50 firms in the industry. For example, if an industry consists of only three firms with market
shares of 60, 30, and 10 percent, respectively, the HHI of this industry would be equal to 4,600 (602 + 302 + 102).
The higher the index, the fewer the number of firms supplying the industry and the more concentrated the
industry. Based on the U.S. Department of Justice's guidelines for evaluating mergers, markets in which the HHI
is under 1000 are considered unconcentrated, markets in which the HHI is between 1,000 and 1,800 are
considered to be moderately concentrated, and those in which the HHI is in excess of 1,800 are considered to be
concentrated.
Table D-9 shows that in 2007, the latest year for which concentration data is available, Pulp Mills had the highest
concentration with HHI of 1,024, followed by the Paperboard Mills segment with HHI of 713, and the Paper Mills
segment with HHI of 673. The Pulp Mills segment also had the highest CR4 ratio of 54 percent. At these HHI
levels, the Paper Mills and Paperboard Mills segments are unconcentrated while the Pulp Mills segment is at the
lower end of the moderately concentrated range. With the majority of the firms in this industry having relatively
small market shares, this suggests limited potential for passing through to customers any increase in production
costs resulting from regulatory compliance.
The concentration ratios for the three profiled segments remained relatively stable between 1987 and 2007, with
an overall increase through 2002 and a slight decline in 2007. During late 1990s, the top five U.S. firms
controlled 38 percent of production capacity, with higher concentrations in individual product lines due to
targeted consolidation and specialization (Ince, 1999). As described previously, the period of consolidation in the
Paper and Allied Products Industry on average continued throughout the second half of the decade.
Containerboard producers in particular went through a period of extensive restructuring resulting in a higher
concentration of top producers (McNutt, 2009). However, an overall decline in concentration indicators in 2007
together with an increase in the number of firms during 2008/2009 in all three segments, potentially suggests that
going forward, the profiled Paper and Allied Products Industry may become even less concentrated.
Table D-9: Selected Ratios for Profiled Paper and Allied Products Segments, 1987,1992,1997, 2002,
and 2007

SIC (S) or

Total
Concentration Ratios
NAICS (N)
Code
Year
Number
of Firms
4 Firm (CR4)
8 Firm (CR8)
20 Firm
(CR20)
50 Firm
(CR50)
Herfindahl-
Hirschman Index
S 2611
1987
26
44%
69%
99%
100%
743
1992
29
48%
75%
98%
100%
858

1997
24
59%
86%
100%
100%
1.106
N322110
2002
21
61%
88%
100%
100%
1.175

2007
30
54%
82%
100%
100%
1,024
S 2621
1987
122
33%
50%
78%
94%
432
1992
127
29%
49%
77%
94%
392

1997
139
34%
55%
80%
94%
467
N32212
2002
187
50%
66%
81%
97%
721

2007
151
46%
62%
83%
96%
673
S 2631
1987
91
32%
51%
77%
97%
431
1992
89
31%
52%
80%
97%
438

1997
81
34%
53%
82%
98%
485
N322130
2002
80
49%
68%
88%
99%
749

2007
77
46%
68%
89%
99%
713
Source: U.S. DOC, 1987, 1992, 1997, 2002, and 2007EC
D.4.3 Foreign Trade
This profile uses two measures of foreign competition: export dependence and import penetration.
Import penetration measures the extent to which domestic firms are exposed to foreign competition in domestic
markets. Import penetration is calculated as total imports divided by total value of domestic consumption in that
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Appendix D: Paper Industry Profile
industry: where domestic consumption equals domestic production plus imports minus exports. Theory suggests
that higher import penetration levels will reduce market power and pricing discretion because foreign competition
limits domestic firms' ability to exercise such power. Firms belonging to segments in which imports account for a
relatively large share of domestic sales would therefore be at a relative disadvantage in their ability to pass-
through costs because foreign producers would not incur costs as a result of the Existing Facilities regulation. The
estimated import penetration ratio for the entire U.S. manufacturing sector (NAICS 31-33) for 2010 is 28 percent.
For characterizing the ability of industries to absorb compliance cost burdens, EPA judges that industries with
import ratios close to or above 28 percent would more likely face stiff competition from foreign firms and thus be
less likely to succeed in passing compliance costs through to customers.
Export dependence, calculated as exports divided by value of shipments, measures the share of a segment's sales
that is presumed subject to strong foreign competition in export markets. The final rule would not increase the
production costs of foreign producers with whom domestic firms must compete in export markets. As a result,
firms in industries that rely to a greater extent on export sales would have less latitude in increasing prices to
recover cost increases resulting from regulation-induced increases in production costs. The estimated export
dependence ratio for the entire U.S. manufacturing sector for 2010 is 22 percent. For characterizing the ability of
industries to absorb compliance cost burdens, EPA judges that industries with export ratios close to or above 22
percent are at a relatively greater disadvantage in potentially recovering compliance costs through price increases
since export sales are presumed subject to substantial competition from foreign producers.
Table D-10 presents trade statistics for the Pulp Mills and Paper and Paperboard Mills segments. Imports and
exports play a much larger role in the Pulp Mills segment than for the other two segments. Import penetration and
export dependence levels for the Pulp Mills segment were an estimated 143 and 128 percent, respectively, in
2010, while for the Paper and Paperboard Mills segments, import penetration and export dependence ratios were
13 and 11 percent, respectively. While there have been some fluctuations in import penetration and export
dependence during the last two decades, overall, the Pulp Mills segment remained significantly more reliant on
foreign trade compared to the other two segments. For Pulp Mills, the large share of domestic production that is
exported and domestic consumption served by imports implies the industry faces significant foreign competition,
limiting the industry's ability to pass through to customers any increase in production costs resulting from
regulatory compliance. For Paper and Paperboard Mills, both measures of foreign competition are well below the
U.S. manufacturing averages estimated for 2010. Given just these measures, it would be reasonable to assume that
these two segments do not face significant foreign competitive pressures, and would have more latitude in passing
through to customers any increase in production costs resulting from regulatory compliance. However, foreign
pressure is likely to increase as capacity in foreign countries, particularly China, continues to grow and exert
pressure on the domestic market (McNutt, Cenatempo & Kinstrey, 2004). In addition, as noted above, the HHI of
the Paper Mills and Paperboard Mills segments is 673 and 713, respectively, suggesting firms in these segments
have small market shares, which would curtail their ability to pass through any increase in production costs.
May 2014
D-19
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
Table D-10: Trade Statistics for Profiled Paper and Allied Products Segments (Millions, $2011

Year3
Value of Imports
Value of Exports
Value of Shipments
Implied
Domestic
Consumptionb
Import
Penetration0
Export
Dependence"1
Pulp Mills
I 989
$5.1 10
$5,935
$10,453
$9,628
53%
57%
fwo
>89
*B*7*
$9.787
$9.3 19
*5(1%
5*3%
fwi
452
4**2*4*
$8.074*
$7.103
4*9%
5*5%
I992
S3.300
7*8**9*
$8.089
$6.600
5(1%
5**9%
IW
S95
5**94*
$6.20(1
$5.501
5*3%
5*8%
FwT
$3,433
1***8**9*
$6.845*
$6.088
5*6%
6*7%
I995
414
5**2*6
$9.618*
$8.506
6*4%
6*8%
fy%
3,3.736
5**7*8*
8*
$6.666
5*6%
*6*1%
1**997
Sl<>*23
3**5**7*
2*
$3.637
foo%
i*o(l%
r;m
$044
ri*74
6
$3.816
*8*8%
8*9%
niw
$3^494
r>*72
4*
$3.887
*9(1%
9(1%
2000
$4,383
$4*3**44
9
$4.568
*96%
9*6%
2(1(7]
419
5**5**9*
7
$3.907
*8*8%
8*8%
2002
IB
4**2**8*
2*
$3.930
77%
7*9%
2003
$3,236
$3,316
5*
$4.604
7(1%
7*1%
2004
548
$3,538
7
$4.807
74%
7*4%
2005
$3,583
$3,832
4*
$4~335
*83%
8*4%
2006
:*>*7**(1*
1*4*7
5*
$4~268
*85%
8*7%
2007
1*89
4**4**9*
$5.365*
S5*I)(*iI
*8*2%
8*3%
2008
282
:)53
$5,501
$4,731
91%
92%
2009
Sl<>*22
>0***1
4*
$2.795
94%
9*6%
2010
sTJiJil
$5**3*%
$4*32*8
Sl8*l*2
1**4*3%
*1***28%
Total Percent
Change 1989 - 2010
-21.3%
-6.7%
-58.6%
-70.8%
Total Percent
Change 2000 - 2010
-8.3%
21.8%
-8.5%
-38.4%
Average Annual
Growth Rate 1989 -
2010
-1.1%
-0.3%
-4.1%
-5.7%
Paper and Paperboard Mills
1989
$12,800
$5,164
$96,828
$104,464
12%
5%
1990
$12,399
756
$92,854
$99,497
12%
6%
1991
1*6(1
17***2*
$86.067
sm*(>*i3
*1***2%
*8%
1992
>13
7*7*9*
$85.002*
$881866
1**2%
*8%
1993
jTi 2 n
5*8*1
$82,172
$8?k8() 1
1**3%
*8%
1994
sriTwi

$88.14(1
S92l)22
*1***2%
*8%
1995
sBTB
5**64*
sToiwF
$713325
1***3%
9%
1996
sTI^T
$9,337

$;js7r7
*1**4%
i*o%
1997
$T2"67i
5**7*3*
$91.455*
$95353
1**3%
9%
1998
**>*5**(*>*
1*5*4
$91.191
S'«OM3
1**4%
9%
1 999
>07*
r;*7*8*
$91.966
S98J05
*1**4%
*8%
2000
1*8**(*>*
34(1
$94,715
s*i*o*i*3(li
B**%*
9%
2001
1*3*8
2**5**8*
$85.898*
$927678
B**%*
*8%
2002
1*2**5*
1*5**2*
$82.321
S89J94
B**%*
7%
2003
1*2**(*>*
1*2**3*
$77.583*
$8X68**5
B**%*
*8%
2004
3*2**5*
2**1****1
$79.092*
S8t50(>*
*1**7%
*8%
2005
79(1
79(1*
$80.921
*$**8*8*772***1*
1**7%
*8%
2006
7*6**1
lol
$81.994*
S8'7*(>95
*1**6%
9%
2007
1*8**7*
7*5**7*
$80.594*
S851924
B**%*
i*o%
2008
1*1***9*
1*3**1
$81.523*
S8(7o71
B**%*
i*o%
2009
r>*86
1*72
$72.625*
$71239
i**3%
i*o%
2010
*$**1**7*8*7*
$83**5*5
f7MM7
$78:*n*9
1***3%
1**7%
Total Percent
Change 1989 - 2010
-23.5%
61.8%
-20.8%
-25.2%
Total Percent
Change 2000 - 2010
-34.7%
0.2%
-19.0%
-22.9%
D-20
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
Table D-10: Trade Statistics for Profiled Paper and Allied Products Segments (Millions, $2011

Year3
Value of Imports
Value of Exports
Value of Shipments
Implied
Domestic
Consumptionb
Import
Penetration0
Export
Dependence"1
Average Annual
Growth Rate 1989 -
2010
-1.3%
2.3%
-1.1%
-1.4%
a. Before 1997, data were compiled in the SIC system; since 1997, these data have been compiled in the North American Industry Classification System
(NAICS). For this analysis, EPA converted the SIC classification data to the NAICS code classifications using the 1997 Economic Census Bridge Between
SIC and NAICS.
b. Calculated by EPA as shipments + imports - exports.
c. Calculated by EPA as imports divided by implied domestic consumption.
d. Calculated by EPA as exports divided by shipments.
Source: U.S. ITC, 1989-2010
Overall, during the last two decades, the value of imports in the Pulp Mills segment declined at an average annual
rate of more than 1 percent resulting in an overall decline of approximately 21 percent. While the value of exports
in this segment declined, it did so at an average annual rate of less than 1 percent resulting in a lower overall
decline of about 7 percent. During the same time, the value of imports in the Paper and Paperboard Mills declined
by approximately 24 percent while the value of exports increased by nearly 62 percent.
As shown in Figure D-5, the value of imports and exports peaked in the mid-1990s, before dropping and
rebounding in 2000. As expected, values of both dropped again in 2001 and 2002, as the global economy fell into
recession. In the Pulp Mills segment, the value of imports and exports grew steadily from 2003 to 2008, while the
Paper and Paperboard industry segments turned increasingly towards exporting product and showed a slight
overall decrease in imports.
During 2009, the value of imports and exports within the Pulp Mills segment declined significantly by 39 percent
and 15 percent, respectively; however, both rebounded rapidly in 2010 increasing by 54 percent and 29 percent,
respectively, as the world economy began to recover. The Paperboard and Paper Mills segments also saw declines
in trade during 2009, although less significant than those observed in the Pulp Mills segment (at 25 percent and 16
percent, respectively); during 2010, while exports increased significantly by 18 percent, imports remained
relatively constant. As the world economy continues to recover, the biggest growth in paper consumption is likely
to take place in Asia (excluding Japan). This growth, driven largely by India and China's rapidly increasing
populations and developing markets, is expected to rise dramatically in the next decade (Environmental Paper
Network, 2007). In particular, China's overall paper demand is projected to grow from approximately 60 million
tons in 2005 to 143 million in 2021 (RISI, 2007).
May 2014
D-21
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
Figure D-5: Value of Imports and Exports for Profiled Paper and Allied Products Segments
(millions, $2011)a
Pulp Mills
S7,000

s a s5,ooo
s *5
¦•S — S4,000
O i—I
S2,000
SI,000
Ed se S3,000
—~— Exports (SIC to
NAICS)
—~— Exports (NAICS
322110)
-A--- Imports (SIC to
NAICS)
—*— Imports (NAICS
322110)
VO '^O 'vO lO *~"
qo v© vo ifl ve vq to ve to vo I*™-.
^ 4^ os 3C O ©
Paper and Paperboard Mills
S20,000
518,000
H S16,000
C £ S14,000
85 §
£ •• S12,000
o S
a-® S10,000
u &
w S8,000
a
S6,000
S4,000
S2,000
— Exports (SIC to
NAICS)
-~— Exports (NAICS
32212 and NAICS
322130)
-A— Imports (SIC to
NAICS)
-A— Imports (NAICS
32212 and NAICS
322130)
"O "O "O "O "O "O "O "O "O "O "O _
ce 'c 'c ^ 's£ o o o « © © ©
¦sO©h-MW*.^On^OCO©h-»s>
^ ^ 00 « O
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the SIC classification data to the NAICS code classifications using the
1997 Economic Census Bridge Between SIC and NAICS.
Source: U.S. ITC, 1989-2010
D.5 Financial Condition and Performance
Financial performance in the Paper and Allied Products Industry is closely linked to macroeconomic cycles, both
in the domestic market and those of key foreign trade partners, and the resulting levels of demand. Many pulp
producers, for example, were not very profitable during most of the 1990s as chronic oversupply, cyclical
demand, rapidly fluctuating operating rates, sharp inventory swings, and uneven world demand plagued the global
D-22
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
pulp market for more than a decade (Stanley, 2000). The ability of Paper and Allied Products Industry
manufacturers to withstand recession and react to changing global economic conditions will be critical in the
coming years.
Net Profit Margin is calculated as after-tax income before nonrecurring gains and losses as a percentage of sales
or revenue, and measures profitability, as reflected in the conventional accounting concept of net income. Over
time, the firms in an industry, and the industry collectively, must generate a sufficient positive profit margin if the
industry is to remain economically viable and attract capital. Year-to-year fluctuations in profit margin stem from
several factors, including: variations in aggregate economic conditions (including international and U.S.
conditions), variations in industry-specific market conditions (e.g., short-term capacity expansion resulting in
overcapacity), or changes in the pricing and availability of inputs to the industry's production processes (e.g., the
cost of energy to the pulp and paper process). The extent to which these fluctuations affect an industry's
profitability, in turn, depends heavily on the fixed vs. variable cost structure of the industry's operations. In a
capital intensive industry such as the Paper and Allied Products Industry, the relatively high fixed capital costs as
well as other fixed overhead outlays, can cause even small fluctuations in output or prices to have a large positive
or negative affect on profit margin.
Return on Total Capital is calculated as annual pre-tax income divided by the sum of the current portion of long-
term debt due in 1 year or less, long-term debt due in more than 1 year, all other noncurrent liabilities and total
stockholders' equity (total capital). This concept measures the total productivity of the capital deployed by a firm
or industry, regardless of the financial source of the capital (i.e., equity, debt, or liability element). As such, the
return on total capital provides insight into the profitability of a business' assets independent of financial structure
and is thus a "purer" indicator of asset profitability than return on equity. In the same way as described for net
profit margin, the firms in an industry, and the industry collectively, must generate over time a sufficient return on
capital if the industry is to remain economically viable and attract capital. The factors causing short-term variation
in net profit margin will also be the primary sources of short-term variation in return on total capital.
Figure D-6 shows trends in net profit margins and return on total capital for the Paper and Allied Products
Industry between 1989 and 2012. The figure shows considerable volatility in both metrics. Profitability and return
on capital declined steadily between 1988 and 1993, reflecting oversupply in world markets and decreasing
shipments from U.S. producers (McGraw-Hill, 2000). By the mid-1990s, financial performance peaked as
demand rebounded, but weakened again in 1997 and 2001, reflecting slower growth in both the U.S. and the
world economy. Coupled with overproduction in the U.S. and global markets, these factors led to deteriorating
financial performance during these years. However, both net profit margins and return on capital improved
gradually from 2004 to early 2007. During 2008, however, the industry's financial performance declined
significantly owing to the current recession. During the entire decade, total shareholder returns for the Paper and
Allied Products Industry, indexed to year 2001, performed at a higher level than the S&P 500 index. However, at
the start of the recession in 2008, total shareholder returns began falling quickly back to S&P 500 levels. Ten of
the largest public US-based forest and paper companies posted earnings of US $1.2 billion in the third quarter of
2008. All but two companies posted positive or improved earnings, reflecting an estimated US $1.1 billion of tax
credits for the use of black liquor as a biofuel to generate energy (PricewaterhouseCoopers, 2009).By 2009, as the
world economy began to show some signs of recovery, both net profit margin and return on total capital had risen
to pre-recession levels and continued to rise into 2010. In 2011 and 2012, net profit margin and return on total
capital declined, moving towards the long-term averages for each of the respective indicators.
May 2014
D-23
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
Figure D-6: Net Profit Margin and Return on Capital for Paper and Allied Products Industry
16%
14%
12%
10%
8%
6%
4%
2%
0%
-2%
4%

—t— Net Profit Margin —*— Return on T otal Cap ital
Source: U.S. DOC, 1988-2012 OFR
D.6 Facilities Operating Cooling Water Intake Structures
Point source facilities that use or propose to use a cooling water intake structure that withdraws cooling water
directly from a surface waterbody of the United States are potentially subject to section 316(b) of the Clean Water
Act. In 1982, the Paper and Allied Products Industry withdrew 534 billion gallons of cooling water, accounting
for approximately 0.7 percent of total industrial cooling water intake in the United States. The industry ranked 5th
in industrial cooling water use, behind the electric power generation industry, and the chemical, primary metals,
and petroleum industries (U.S. DOC, 1982).
This section provides information for facilities in the profiled paper and allied products segments potentially
subject to the final rule and other options EPA considered. Existing facilities that meet the following conditions
are potentially subject to regulation:
> Have a National Pollutant Discharge Elimination System (NPDES) permit or are required to obtain one;
> Use or propose to use one or more cooling water intake structures to withdraw water from waters of the
United States;
> Use at least twenty-five (25) percent of the water withdrawn exclusively for contact or non-contact
cooling purposes; and
> Meet the specific applicability coverage criteria for the final rule and other options EPA considered in
terms of design intake flow (i.e., two mgd).
The regulatory analysis options also cover substantial additions or modifications to operations undertaken at such
facilities. EPA identified the set of facilities that were estimated to be potentially subject to the Final 316(b)
D-24
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
Existing Facilities regulation based on a minimum applicability threshold of two mgd; this section focuses on
these facilities in the profiled Paper and Allied Products Industry.5
D.6.1 Waterbody and Cooling System Type
Table D-ll reports the distribution of facilities in the profiled Paper and Allied Products Industry that are
potentially subject to the final rule and other options EPA considered by type of waterbody and cooling water
intake system. The tables show that most of the facilities have either a once-through system or employ a
combination of a once-through and closed system.
Table D-11: Number of Facilities Estimated Subject to the 316(b) Existing Facilities Regulation by

Waterbody Type and Cooling Water Intake System for the Profiled Paper and Allied Products Segments

Recirculating
Combination
Once-Through
Other

Waterbody Type
No.
% of Total
No.
% of Total
No.
% of Total
No.
% of Total
Total
Estuary/Tidal River
0
0%
0
0%
6
5%
0
0%
6
Ocean
0
0%
0
0%
0
0%
0
0%
0
Lake/Reservoir
0
0%
6
14%
6
5%
1 1
34%
23
Freshwater River/ Stream
29
100%
35
86%
105
85%
19
58%
188
Great Lake
0
0%
0
0%
6
5%
3
8%
9
Total3
29
13%
41
18%
122
54%
33
14%
225
a. Individual numbers may not add up to total due to independent rounding.

Source: U.S. EPA, 2000; U.S. EPA analysis for this report

D.6.2 Facility Size
All of the pulp and paper facilities EPA expects to be subject to the final rule and other options EPA considered
are relatively large, with only eight facilities employing fewer than 100 people. Figure D-7 shows the number of
facilities in the profiled Paper and Allied Products Industry potentially subject to the regulation by employment
size category.
Figure D-7: Number of Facilities Estimated to be Subject to the 316(b) Existing Facilities Regulation by Employment
Size for Profiled Paper and Allied Products Industry
90
80
70
60
50
40
30
20
10
0
Source: U.S. EPA, 2000; U.S. EPA analysis for this report
Less than 100-249 250-199 500-999 1000 and
100 greater
EPA applied sample weights to the sampled facilities to account for non-sampled facilities and facilities that did not respond to the
survey. For more information on EPA's 2000 Section 316(b) Industry Survey, please refer to the Information Collection Request (U.S.
EPA, 2000).
May 2014
D-25
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix D: Paper Industry Profile
D.6.3 Firm Size
EPA used the Small Business Administration (SBA) small entity size standards to determine the number of
facilities in the three profiled paper segments that are owned by small firms. Firms in this industry are considered
small if they employ fewer than 750 people. EPA estimates that 31 small entity-owned facilities and 194 large
entity-owned facilities in the Paper and Allied Products Industry are potentially subject to the Final 316(b)
Existing Facilities regulation.
D-26
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
Appendix E Profile of the Petroleum Refining Industry
E.1 Introduction
EPA's Detailed Industry Questionnaire, hereafter referred to as the DQ, identified the Petroleum Refining
Industry (SIC 2911 or NAICS 324110) with at least one existing facility that operates a CWIS, holds a NPDES
permit, withdraws at least two million gallons per day (mgd) from a water of the United States, and uses at least
25 percent of its intake flow for cooling purposes (facilities with these characteristics are hereafter referred to as
"facilities potentially subject to the 316(b) Existing Facilities regulation" or "regulated facilities").
Table E-l, below, provides a description of the industry segment, a list of primary products manufactured, the
total number of the DQ respondents (weighted to represent a national total of facilities that hold a NPDES permit
and operate cooling water intake structures), and the number of facilities estimated to be potentially subject to the
final rule based on the minimum withdrawal threshold of two mgd (see Chapter 1: Introduction for more details
on the final rule applicability criteria).
Table E-1: Existing Facilities in the Petroleum Refining Industry (NAICS 324110)
NAICS
NAICS
Description
Important Products Manufactured
Number of Regulated
Facilities3
324110
Petroleum
Refineries
Gasoline, including finished base stocks and blending agents; jet fuel; kerosene;
light fuel oils; heavy fuel oils, including grades no. 5, 6, heavy diesel-type, heavy
gas-enrichment oils; lubricating oils and greases; unfinished oils and lubricating oil
base stock; asphalt; liquefied refinery gases, including other aliphatics (feed stock
and other uses); and other finished petroleum products, including waxes.
39
a. Number of weighted detailed questionnaire survey respondents.
Source: Executive Office of the President, 1987; U.S. EPA, 2000; U.S. EPA analysis for this report
As shown in Table E-l, EPA estimates that, out of an estimated total of 163221 facilities with a NPDES permit and
operating cooling water intake structures in the Petroleum Refining Industry (NAICS 324110), 39 (or 24 percent)
would be subject to regulation under the 316(b) Final Existing Facilities Regulation. EPA also estimated the
percentage of total production that occurs at facilities estimated to be subject to regulation under each analysis
option. Total value of shipments for the Petroleum Refining Industry (NAICS 32411) from the 2010 Annual
Survey of Manufactures is $601.2 billion ($2011). Value of shipments, a measure of the dollar value of
production, was selected for the basis of this estimate. Because the DQ did not collect value of shipments data,
these data were not available for existing facilities. Total revenue, as reported on the DQ, was used as a close
approximation for value of shipments for these facilities. EPA estimated the total revenue of facilities expected to
be subject to regulation under the 316(b) Existing Facilities Regulation to be $229.5 billion ($2011).222 Therefore,
EPA estimates that the percentage of total production in the Petroleum Refining Industry that occurs at facilities
estimated to be subject to the regulation is 38 percent.
Table E-2 provides the crosswalk between NAICS codes and SIC codes for the profiled petroleum NAICS codes.
For the Petroleum Refineries segment, the translation of SIC-reported data to the NAICS framework is
straightforward as these frameworks have a simple one-to-one match for Petroleum Refining: NAICS code
324110 and SIC code 2911.
221 This estimate of the number of facilities holding a NPDES permit and operating a cooling water intake structure is based on the
responses from facilities that received the 1999 screener questionnaire.
222 To compare revenue values of regulated facilities with the industry value of shipments, EPA brought revenue values for regulated
facilities forward to 2010 using industry-specific Producer Price Index (PPI) values published by the Bureau of Labor Statistics (BLS)
and stated in 2011 dollars using GDP deflator published by the Bureau of Economic Analysis (BEA).
May 2014
E-1
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
Table E-2: Relationship between NAICS and SIC Codes for the Petroleum Refining Industry (2010)
NAICS
Code
NAICS
Description
SIC
Code
SIC Description
Number of
Establishments
(2009)a
Value of Shipments
(2010; Millions;
$2011)
Employment
(2010)
324110
Petroleum
Refineries
2911
Petroleum Refilling
303
$601,212
63,263
a. Hie data on number of establishments is based on data from the 2009 Statistics of U.S. Businesses. Value of Shipments and Employment reflect 2010
data.
Sources: U.S. DOC, 21)III ASM: U.S. DOC, 2009 SUSB
E.2 Summary Insights from this Profile
A key purpose of this profile is to provide insight into the ability of Petroleum Refining firms to absorb
compliance costs under the final rule without material, adverse economic/financial effects. The industry's ability
to absorb compliance costs is primarily influenced by the following two factors: (1) the extent to which the
industry may be expected to shift compliance costs to its customers through price increases and (2) the financial
health of the industry and its general business outlook.
E.2.1 Likely Ability to Pass Compliance Costs Through to Customers
As reported in the following sections of this profile, the Petroleum Refining Industry is relatively unconcentrated,
which suggests that firms in this industry would have less power to pass a significant portion of their compliance-
related costs through to customers. As discussed above, given the relatively small proportion of total value of
shipments in the industry estimated to be subject to regulation under each option (less than 50 percent), EPA
judges that regulated refineries subject to the 316(b) Existing Facilities Regulation are not likely to be able to
recover compliance costs through price increases to customers. Even though the Petroleum Refining Industry is
not characterized by high competitive pressure from foreign markets, the low market concentration leads EPA to
judge that the market power held by individual firms is likely to be quite small. For these reasons, in its analysis
of regulatory impacts for the Petroleum Refining segment, EPA assumed that regulated facilities would be unable
to pass compliance costs through to customers: i.e., they must absorb all compliance costs within their operating
finances (see following sections and Appendix K: Cost Pass-Through Analysis, for further information).
E.2.2 Financial Health and General Business Outlook
Over the past two decades, Petroleum Refining, like other U.S. manufacturing industries, has experienced a range
of economic/financial conditions, including substantial challenges. In the early 1990s, the domestic Petroleum
Refining Industry was affected by reduced U.S. demand as the economy entered a recessionary period. Although
domestic market conditions improved by mid-decade, oversupply of crude oil, weakness in Asian markets, along
with other domestic factors, materially weakened refiners" financial performance in 1998. As petroleum
producing countries reduced crude oil supply and refiners cut production, prices rebounded in the late 1990s and
into 2000, before another U.S. recession, the attacks of 9/11, and global economic downturn again had a negative
effect on petroleum refiners. As the U.S. economy began recovery from its economic weakness caused by the
2001 recession, the domestic Petroleum Refining Industry also recovered, with continuous improvements in
demand levels and financial performance during 2003 to 2007. Between July and December of 2008, however, at
the outset of the recent economic recession, the price of crude oil dropped more than $100 a barrel. Economists
predict that this slide in oil demand will rebound as the economy recovers in the coming years (Protec Fuel
Management, 2008). In fact, the 2009 Annual Energy Outlook, published by the U.S. Energy Information
Administration (EIA) of the U.S. Department of Energy (DOE), projects that petroleum production will increase
from 13.08 quadrillion Btu in 2008 to 15.51 in 2020, 15.68 in 2030, and 15.87 in 2035, showing gradual
expansion in domestic petroleum production (U.S. DOE, 2009a). In addition, according to the 2010 Annual
Energy Outlook, total liquid fuels consumption, including petroleum products, will grow by roughly 1 percent
annually until 2035, owing a majority of this increase to the transportation sector's growing demand (U.S. DOE,
E-2
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
2010a). Although the Petroleum Refining Industry has weathered difficult periods over the last two decades,
experts report a positive outlook for the industry in 2013 (S&P, 2013d). The recent strengthening of the industry's
financial condition and general business outlook, as the world and U.S. economy recover from the recent
recession, point to the ability of the regulated facilities in the Petroleum Refining Industry to absorb additional
regulatory compliance costs without imposing significant financial impacts.
E.3 Domestic Production
The Petroleum Refining Industry accounted for about 11 percent of the value of shipments of the entire U.S.
manufacturing sector and employed approximately 0.5 percent of the manufacturing sector's workers in the late
2000s (U.S. DOC, 2009a). According to the Annual Survey of Manufactures, in 2010, Petroleum Refineries
achieved shipments of approximately $601 billion dollars ($2011) and employed 63,263 people. At the end of the
last decade, petroleum products constituted approximately 37 percent of the total energy used in the United States,
including virtually all of the energy consumed in transportation (U.S. DOE, 2009b).
According to EIA, 150 Petroleum Refineries operated in the United States in 2008 (U.S. DOE, 2009b).223 Some
data reported in this profile are taken from EIA publications. Readers should note that the Census data reported
for NAICS 324110 cover a somewhat broader range of facilities than do the U.S. DOE/EIA data, and the two data
sources are therefore not entirely comparable.224
The petroleum industry includes exploration and production of crude oil, refining, transportation, and marketing.
Petroleum refining is a capital-intensive process that converts crude oil into a variety of refined products.
Refineries range in complexity, depending on the types of products produced. Nearly half of all U.S. refinery
output is motor gasoline.
The number of U.S. refineries has declined by almost half since the early 1980s. The remaining refineries have
improved their efficiency and flexibility to process heavier crude oils by adding "downstream" capacity.225 While
the number of refineries has declined, the average refinery capacity and utilization has increased, resulting in an
increase in domestic refinery production overall.
E.3.1 Output
Table E-3 shows trends in production of petroleum refinery products from 1990 through 2010. In general, output
of refined products grew over this period, reflecting growth in transportation demand and other end-uses. Output
fell in 1991 due to the domestic economic recession, and the early years of the 2000s experienced little or
negative growth because of the downturn of the U.S. economy and events of 9/11 (API, 2003). At the beginning
of 2002, petroleum products were in excess supply in the world market, and the focus was on the elimination of
excess supplies and stabilization of prices (U.S. DOE, 2004). In 2003, the industry rebounded, with refinery
processing increasing 2 percent, producing record or near record levels of gasoline and distillate (API, 2004).
Petroleum production continued to increase until the global recession hit in 2008. U.S. demand for oil and gas
refined products fell by more than three million b/d from the peak in February 2008 to the trough in June 2009
during the global economic slowdown; as a result, refining margins narrowed and refiners responded by reducing
throughput rates, idling and closing less efficient facilities, and cutting capital expenditures (S&P, 2010b). In
223 In addition, one operating and one idle refinery were located in Puerto Rico and one operating refinery in the Virgin Islands.
224 For comparison, preliminary 1997 Census data included 244 establishments for NAICS 3241/SIC 2911, whereas U.S. DOE/EIA
reported 164 operable refineries as of January 1997.
225 The first step in refining is atmospheric distillation, which uses heat to separate various hydrocarbon components in crude oil. Beyond
this basic step are more complex operations (generally referred to as "downstream" from the initial distillation) that increase the
refinery's capacity to process a wide range of crude oils and increase the yield of lighter (low-boiling point) products such as gasoline.
These downstream operations include vacuum distillation, cracking units, reforming units, and other processes (U.S. DOE, 1999a).
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Appendix E: Petroleum Refining Industry Profile
2009, overall U.S. production fell by 1.5 percent, but by 2010 production had already rebounded with an increase
in total output of 3.1 percent he greatest increase in total output throughout the entire period. As the U.S. and
global economies continue to improve, Petroleum Refining firms are also likely to see improvements in their
markets and earnings. This should place companies in a better position to incur any costs associated with
regulatory compliance.
Table E-3: U.S. Petroleum Refinery Production (million barrels per day)
Year
Motor
Gasoline
Distillate Fuel
Oil
Jet Fuel
Residual Fuel
Oil
Other
Products3
Total Output
Percent Change in
Total Output
I 990
6.96
2.93
1.49
0.95
0.78
15.272
NA
I 991
6.98
2.96
1.44
0.93
0.76
15.256
-0.1%
I992
7.06
2.97
1.40
0 89
0.80
15.398
0.9%
1993
7.30
3.13
1.42
0.84
0.78
15.787
2 5%
1994
7.18
3.21
1.45
0.83
0.79
15.791
0.0%
1995
7.46
3.16
1.42
0 79
0.78
15.994

1996
7.57
3.32
1.52
0.73
0.76
16.324
2.1%
1997
7.74
3 39
1.55
0.71
0.84
16.759
2.7 %
1998
7.89
3.42
1.53
0.76
0.89
17.03
1.6%
I 999
7.93
3.40
1.57
0.70
0.84
16.989
-0.2%
2000
7.95
3 58
1.61
0.70
0.79
17.243
1.5%
200I
8.02
3.70
1.53
0 72
0.73
17.285
0.2%
2002
8.18
3 59
1.51
0.60
0.77
17.273
-0.1%
2003
8.19
3.71
1.49
0 66
0.78
17.487
1.2%
2004
8.27
3.81
1.55
0.66
0.84
17.814
1.9%
2005
8.32
3.95
1.55
0.63
0.75
17.8
-0.1%
2006
8.36
4.04
1.48
0 64
0.76
17.975
1.0%
2007
8.36
4.13
1.45
0.67
0.75
17.994
0.1%
2008
8.55
4.29
1.49
0 62
0.66
18.146
0.8%
2009
8.79
4.05
1.40
0.60
0.61
17.882
-1.5%
20I0
9.05
4.23
1.42
0.58
0.65
18.428
3.1%
Total Percent Change
1990-2010
30.0%
44.5%
-4.7%
-38.7%
-16.8%
20.7%

Total Percent Change
2000-2010
13.8%
18.0%
-11.7%
-16.4%
-18.4%
6.9%

Average Annual
Growth Rate220
1.3%
1.9%
-0.2%
-2.4%
-0.9%
0.9%

a. Kerosene, lubricants, petrochemical feedstocks, waxes, and miscellaneous products.
Source: U.S. DOE, 2010b
Value of shipments and value added are two common measures of manufacturing output.227 They provide insight
into the overall economic health and outlook for an industry. Value of shipments is the sum of the receipts a
manufacturer earns from the sale of its outputs; it indicates the overall size of a market or the size of a firm in
relation to its market or competitors. Value added measures the value of production activity in a particular
industry. It is the difference between the value of shipments and the value of inputs (from other industries) used to
make the products that are sold.
Figure E-l shows value of shipments and value added for petroleum products from 1987 to 2010. Value of
shipments rose through 1990; however, during and following the recession of 1991, value of shipments fell
through 1994. This was followed by some volatility over the next few years until experiencing a sharp drop in
1998, when a range of factors led to a dramatic decrease in petroleum prices. Increased production quotas by
OPEC, increased production from Iraq through the ""oil-for-food" program, weak demand in Asia due to their
220 In this appendix, average annual growth rate refers to a year-to-year, constant percentage growth mean, which is calculated as the
compound annual growth rate between the first and last values. This is the same concept as the geometric mean, if all of the individual
year-to-year values are the same as those used in calculating the constant percentage growth mean.
227 Terms highlighted in bold and italic font are further explained in the glossary.
E-4
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Appendix E: Petroleum Refining Industry Profile
financial crisis, and a warm winter in the U.S. all increased the supply of petroleum products (U.S. DOE, 1999c).
Estimates of worldwide petroleum supply exceeding demand during 1998 range from 1.47 million barrels per day
to 2.4 million barrels per day (World Oil, 1999).
As crude oil producers and refiners cut back on production, the industry was restored with significant
improvements in 1999 and 2000, before the global economic slowdown and weakening demand decreased the
value of shipments in 2001. From 2003 through 2008, however, value of shipments increased significantly,
peaking at nearly $765 billion in 2008. In 2009, value so shipments saw a drastic decline, followed by an increase
the value of shipments in 2010. Value added generally followed the path of value of shipments over the last two
decades, with the main difference being that value added peaked in 2006 and then began its decline in 2007.
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Appendix E: Petroleum Refining Industry Profile

Figure E-1: Value of Shipments and Value Added for the Petroleum Refining Industry (millions, $2011)a
Value Added
Value of Shipments
^ S770,000
— S720,000
o
^ S670,000
— S620,000
2 S570,000
^ S520,000
£ S470,000
| S420,000
3 S370,000
S320,000
'S S270,000
S220,000
S170,000
>
S120,000
S125,000
S115,000
S15,000
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American Industry
Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic
Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007
EC
—*— Petroleum
Refineries
(NAICS 324110)
—A— Petroleum
Refinineries (SIC
to NAICS)
3 S105.000
o
£ S95.000
= S85,000
S S75,000
« S65,000
S55.000
g S45,000
^ S35,000
S25,000
—*— Petroleum
Refineries (NAICS
324110)
—A— Petroleum
Refineries (SIC to
NAICS)
E.3.2 Prices
The producer price index (PPI) measures price changes from the perspective of the seller, and indicates the overall
trend of product pricing, and thus provides insight into supply-demand conditions, within a given industry.
Figure E-2 shows substantial fluctuations in petroleum product prices between 1987 and 2011. Through the early
1990s, refiners faced declining prices due to the effects of the 1991 recession and weak demand before
rebounding somewhat in the mid-1990s. Prices fell in 1998 as a massive oversupply of petroleum products
E-6
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
coupled with decreased demand led to significant drops in petroleum prices. As the subsequent production
cutbacks took hold and the glut of supply dwindled, prices recovered in 1999 and 2000, as shown in Figure E-2.
The higher prices reflect low refinery product inventories and higher crude oil input prices (Value Line, 2010).
Excess supply, the global recession, impacts from 9/11, and the relatively warm winter of 2001-2002 led to
decreases in prices in subsequent years (U.S. DOE, 2004). During 2003 to 2008, however, prices rose
dramatically. By 2008, the price of petroleum products was over double the price seen in 2000, the previous peak
year during the 1987 to 2002 time period.
During the second half of 2008, Petroleum Refining Industry prices began to decline as the result of economic
recession and continued to do so through the middle of 2009. Oil prices fell during 2008 due to a broad-based
financial de-leveraging occurring across all markets and investment asset classes. The drop in oil prices nearly
exactly corresponded to price movements in the collapsing stock market (Protec Fuel Management, 2008). Prices
rebounded in 2010 and 2011 as the world economy began to recover. In 2035, the average real price of crude oil
is expected to be $133 per barrel ($2008) (U.S. DOE, 2009a).
Figure E-2: Producer Price Index for the Petroleum Refining Industry
Source: BLS, 201 Id
E.3.3 Number of Facilities and Firms
The number of operable refineries fell substantially during the 1980s, with fluctuations in the number of refinery
firms and facilities through the 1990s and 2000s. The earlier decrease resulted in part from the elimination of the
Crude Oil Entitlements Program in the early 1980s. The Entitlements Program encouraged smaller refineries to
add capacity throughout the 1970s. After the program was eliminated, surplus capacity and falling profit margins
led to the closure of less efficient capacity (U.S. DOE, 1999a). The decrease in the number of refineries
continued, as the industry consolidated to improve margins. After peaking in the early 1980s, refining capacity
decreased throughout the rest of the decade. Refining capacity has remained relatively stable since the decrease in
the 1980s, with a slight upward trend occurring in the latter part of the 1990s into the 2000s.
Table E-4 presents the numbers of refinery facilities and firms from 1990 to 2009 based on Statistics of U.S.
Businesses for NAICS 324110. As shown in the table, despite some significant losses in 1997 and 2003, both the
number of refinery facilities and the number of firms reporting Petroleum Refining as their primary business grew
between 1990 and 2007. In 2008, both the number of firms and number of refinery facilities decreased
significantly, followed by lesser declines in 2009. In spite of the declines at the end of the period, the number of
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
petroleum refinery firms grew 24 percent from 2000 to 2009, while the number of facilities correspondingly grew
by 2 percent.
Table E-4: Number of Firms and Facilities for the Petroleum Refining Industry
Year3
Firms
Facilities
Number
Percent Change
Number
Percent Change
I 990
215
NA
340
NA
I 991
215
0.0%
346
1.8%
I 992
185
,
303
-12.4%
I 993
148
-20.0%
251
-17.2%
1994
161
8.8%
265
5.6%
199 5
150
-6.8%
251
-5.3%
I 996
173
15.3%
275
9.6%
1997
128
-26.0%
248
-9.8%
I 998
155
21.1%
304
22.6%
I 999
145
-6.5%
292
-3.9%
2000
162
1 1.7%
298
2.1%
200I
165
1.9%
302
1.3%
2002
202
22.4%
349
15.6%
2003
142
-29.7 %
274
-21.5%
2004
155
9.2%
364
32.8%
2005
177
14.2%
301
-17.3%
2006
228
28.8%
352
16.9%
2007
258
13.2%
374
6.3%
2008
201
-22.1%
311
-16.8%
2009
200
-0.5%
303
-2.6%
Total Percent Change 1990-
2009
-7.0%
-10.9%
Total Percent Change 2000-
2009
23.5%
1.7%
Average Annual Growth Rate
-0.4%
-0.6%
a. Before 1998, these data were compiled in the Standard Industrial Classification (SIC) system; since 1998, these data have been compiled in the North
American Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the
1997 Economic Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1990-1997SBA; U.S. DOC, 1998-2009 SUSB
E.3.4 Employment and Productivity
Between 1987 and 2010, employment in the Petroleum Refining segment declined by 15 percent, from 74,600 to
63,263 employees, as shown in Figure E-3. After increasing in the early 1990s, employment at Petroleum
Refineries declined almost continuously through 2003, reflecting overall industry consolidation, before showing
slight recovery up until 2008. In the latter part of the decade, employment in the Petroleum Refining segment yet
again followed a downward trend. The declining level of employment is not so much an indicator of financial
success for the industry, but rather an indicator of the increasing mechanization of petroleum refineries. The
industry has become highly automated, with the average annual revenue per worker currently at over $3 million
(First Research, 2009).
E-8
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
Figure E-3: Employment for the Petroleum Refining Industry3
o
o
&
E
a
"S
s-
o
-a
E
80,000
77,500
75,000
72,500
70,000
67,500
65,000
62,500
60,000
57,500
55,000
52,500
50,000
—A— Petroleum Refineries
(SIC 2911)
¦ Petroleum Refineries
(NAICS 324110)
'i e e e o e e e o e e =
ooocoo*c«vc««««««*coooooooo®oi-'
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997 these data have been compiled in the North American Industry
Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic
Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and
2007 EC
Table E-5 shows substantial year-to-year changes in labor productivity, measured by value added per production
hour. These fluctuations largely reflect volatility in value added, which in turn indicates variation in the
relationship between input prices (primarily crude oil) and refinery product prices. Changes in production hours
from year to year were less volatile, with a net reduction over the period 1987 to 2010. Value added was not
negatively affected, as it more than tripled over the same period.
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Appendix E: Petroleum Refining Industry Profile
Table E-5: Productivity Trends for the Petroleum Refining Industry ($2011)a
Year
Value Added
(millions)
Production Hours
(millions)
Value Added/Hour
($/hr)
% Change in Value
Added/ Hour
1987
$24,867
103
$241
NA
1988
.978
103
$340
41.2%
1989
.159
105
$336
-1.1%
I 990
.801
106
$338
0.7 %
I 991
.991
107
$282
-16.8%
I 992
.267
109
$259
-8.2%
I 993
.091
107
$254
-1.6%
I 994
3,33.758
1 10
$307
20.6%
1995
$33,308
107
$312
1.7%
I 996
$35,450
103
$346
10.7%
1997
.362
100
$414
19.9%
I 998
.820
98
$325
-21.5%

94
$437
34.3%
2000
.806
92
$507
16.0%
200I
$50,383
94
$539
6.3%
2002
$34,372
84
$408
-24.3%
2003
.010
83
$568
39.3%
2004
.627
83
$794
39.8%
2005
$1 18.700
89
$1,336
68.2%
2006
.097
88
392
4.2%
2007
$1 18.881
92
$1,293
-7.1%
2008
.536
95
$851
-34.2%
2009
.918
94

-15.5%
20I0
$83,267
89
$931
29.5%
Total Percent Change 1987-
2010
234.9%
-13.4%
286.8%

Total Percent Change 2000-
2010
77.9%
-3.1%
83.7%

Average Annual Growth
Rate 1987-2010
5.4%
-0.6%
6.1%

41.6%
1992
>
74%
1993
7
-4.6%
1994
1
-9.6%
1995
)
4.0%
1996
1
-13 1%
1997
>
-19.7%
1998
!
-2.9%
1 999
$5,147
-6.8%
2000
>
16.3%
2001
i
42.3%
2002
)
6.4%
2003
!
-9.2%
2004

-6.0%
2005
)
54.3%
2006
)
2.5%
2007
!
49.8%
2008
7
0.6%
2009
$17,413
-5.6%
2010
$1 1.948
-31.4%
Percent Change 1987- 2010
235.7%

Percent Change 2000- 2010
99.6%

Average Annual Growth Rate
1987-2010
5.4%

a. Before 1997, these data were compiled in the Standard Industrial Classification (SIC) system; since 1997, these data have been compiled in the North
American Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the
1997 Economic Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007
EC
E.3.6 Capacity Utilization
Refinery capacity is frequently measured in terms of crude oil distillation capacity. EIA defines refinery capacity
utilization as input divided by calendar day capacity, which is the maximum amount of crude oil input that can be
processed during a 24-hour period with certain limitations. Some downstream refinery capacities are measured in
terms of "stream days," which is the amount a unit can process when running full capacity under optimal crude
and product mix conditions for 24 hours (U.S. DOE, 1999a). Downstream capacities are reported only for specific
units or products, and are not summed across products, since not all products could be produced at the reported
levels simultaneously.
Figure E-4 below shows the fluctuation in capacity utilization rates over the period 1990-2010, based on U.S.
Census Bureau data. Overall, capacity utilization fluctuated over a relatively low range over the last two decades.
Between 1990 and 1994, capacity utilization steadily increased, followed by a sharp drop in 1995. It remained
relatively stable until 2004 when excess supply, recession, and other factors led to decreases in rates during the
early part of this decade hitting particularly hard in 2005. The industry recovered very quickly, however, as
capacity utilization increased during the following two years before dropping in 2008 and 2009 as a result of the
economic downturn. Capacity utilization then rebounded in 2010 to end the two-decade period with no overall
change. Overall, refinery utilization remained relative high during the last two decades. Capacity utilization for
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
production of specific products may vary, however, as the industry adjusts to changes in the desired product mix
and characteristics.
Figure E-4: Capacity Utilization Rates (Fourth Quarter) for the Petroleum Refining Industry3,13
Petroleum Refining
(SIC to NAICS)
Petroleum Refineries
(NAICS 324110)
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997
Economic Census Bridge Between NAICS and SIC.
b. Prior to 2007, U.S. Census sampled every industry in a specific NAICS6. Beginning in 2007, U.S. Census only sampled certain industries within any
NAICS6, and therefore, the data collected before 2007 cannot be directly compared to the data collected in 2007 and beyond.
Source: U.S. DOC, 1989-2010 SPC
E.4 Structure and Competitiveness
The U.S. Petroleum Refining Industry is made up of integrated international oil companies, integrated domestic
oil companies, and independent domestic refining/marketing companies. In general, the petroleum industry is
highly integrated, with many firms involved in more than one stage of petroleum industry operations. Large
companies, referred to as the "majors," are fully integrated across crude oil exploration and production, refining,
and marketing. Smaller, nonintegrated companies, referred to as the "independents," generally specialize in one
segment of the industry.
Like the oil business in general, refining was dominated in the 1990s by integrated internationals, specifically a
few large companies such as Exxon Corporation, Mobil Corporation, and Chevron Corporation. These three
ranked in the top ten of Fortune 500 sales during this time period. Substantial diversification by major petroleum
companies into other energy and non-energy segments was financed by high oil prices in the 1970s and 1980s.
With lower profitability in the 1990s, the major producers began to exit unconventional energy operations (e.g.,
oil shale) as well as coal and non-energy operations in the 1990s. Some have recently ceased chemical production.
During the 1990s and into the early 2000s, several mergers, acquisitions, and joint ventures occurred in the
Petroleum Refining segment in an effort to cut cost and increase profitability. This consolidation took place
among the largest firms (as illustrated by the acquisition of Amoco Corporation by British Petroleum in 1999, the
merger of Chevron and Texaco in 2001, the merger of Conoco and Phillips in 2002, and the mega-merger of
Exxon and Mobil Corporation in 1998) as well as among independent refiners and marketers (e.g., the
independent refiner/marketer Ultramar Diamond Shamrock (UDS) acquired Total Petroleum North America in
1997) (U.S. DOE, 1999b, 2004). Merger activity slowed during the earlier part of the decade, possibly because
companies were trying to address financial issues after the 2001 recession and/or wanted to make sure that
economy was indeed recovering (U.S. DOE, 2004).
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
At the end of the last decade, the oil industry became less vertically integrated. The share of U.S. refining capacity
owned by independent refiners with no production operations was eight percent in 1990 while by 2007, this share
exceeded 21 percent. Important mergers and acquisitions in the later part of the decade included: ChevronTexaco
and Unocal in 2005; Valero and Premcor in 2005; ConocoPhillips and Burlington Resources in 2006; Anadarko,
Kerr-McGee, and Western Gas Resources in 2006; and Occidental and Vintage Petroleum in 2006 (API, 2008).
E.4.1 Firm Size
For NAICS 324110, the Small Business Administration defines a small firm as having 1,500 or fewer employees.
The size categories reported in the Statistics of U.S. Businesses (SUSB) do not correspond with the SBA size
classifications, therefore preventing precise use of the SBA size threshold in conjunction with SUSB data. Table
E-7 below shows the distribution of firms and establishments in NAICS 324110 by the employment size of the
parent firm. The SUSB data show that 137 of the 303 NAICS 324110 establishments reported for 2009 (45
percent) are owned by larger firms (those with 500 employees or more), some of which may still be defined as
small under the SBA definition, and 166 (55 percent) are owned by small firms (those with fewer than 500
employees).
Table E-7: Number of Firms and Establishments for the
Petroleum Refining Industry by Firm Employment Size
Category, 2009a

Employment Size
Category
Number of Firms
Number of Establishments
0-I9
126
126
20-99
18
20
100-499
19
20
500+
37
137
Total
200
303
a. Based on NAICS 324110

Source: U.S.DOC, 2009 SUSB

E.4.2 Concentration Ratios
Concentration is the degree to which industry output is concentrated in a few large firms. Concentration is closely
related to entry barriers, with more concentrated industries generally having higher barriers.
The four-firm concentration ratio (CR4) and the Herfindahl-Hirschman Index (HHI) are common measures of
industry concentration. The CR4 indicates the market share of the four largest firms. For example, a CR4 of 72
percent means that the four largest firms in the industry account for 72 percent of the industry's total value of
shipments. The higher the concentration ratio, the less competition there is in the industry, other things being
equal.228 An industry with a CR4 of more than 50 percent is generally considered concentrated. The HHI indicates
concentration based on the largest 50 firms in the industry. It is equal to the sum of the squares of the market
shares for the largest 50 firms in the industry. For example, if an industry consists of only three firms with market
shares of 60, 30, and 10 percent, respectively, the HHI of this industry would be equal to 4,600 (602 + 302 + 102).
The higher the index, the fewer the number of firms supplying the industry and the more concentrated the
industry. Based on the U.S. Department of Justice's guidelines for evaluating mergers, markets in which the HHI
is under 1,000 are considered unconcentrated, markets in which the HHI is between 1,000 and 1,800 are
228 Note that the measured concentration ratio and the HHF are very sensitive to how the industry is defined. An industry with a high
concentration in domestic production may nonetheless be subject to significant competitive pressures if it competes with foreign
producers or if it competes with products produced by other industries (e.g., plastics vs. aluminum in beverage containers).
Concentration ratios based on share of domestic production are therefore only one indicator of the extent of competition in an
industry.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
considered to be moderately concentrated, and those in which the HHI is in excess of 1,800 are considered to be
concentrated.
As shown in Table E-8, the CR4 and the HHI for NAICS 324110 are both below the benchmarks of 50 percent
and 1,000, respectively. For the Petroleum Refining segment, the HHI is 807, suggesting that as of 2007, the
sector was still fairly unconcentrated, although the trend has been toward becoming a more concentrated industry.
With the majority of the firms in this industry having small market shares, this suggests limited potential for
passing through to customers any increase in production costs resulting from regulatory compliance.
Table E-8: Selected Ratios for the Petroleum Refining Industry
SIC (S) or

Total
Concentration Ratios
NAICS (N)
Year
Number of
4 Firm
8 Firm
20 Firm
50 Firm
Herfindahl-
Code

Firms
(CR4)
(CR8)
(CR20)
(CR50)
Hirschman Index
S 2911
1987
200
32%
52%
78%
95%
435
1992
132
30%
49%
78%
97%
414

1997
122
29%
49%
82%
98%
422
N324110
2002
88
41%
64%
89%
99%
640

2007
98
48%
73%
92%
100%
807
Source: U.S. DOC, 1987, 1992, 1997, 2002, and 2007EC
E.4.3 Foreign Trade
This profile uses two measures of foreign competition: export dependence and import penetration.
Import penetration measures the extent to which domestic firms are exposed to foreign competition in domestic
markets. Import penetration is calculated as total imports divided by total value of domestic consumption in that
industry: where domestic consumption equals domestic production plus imports minus exports. Theory suggests
that higher import penetration levels will reduce market power and pricing discretion because foreign competition
limits domestic firms" ability to exercise such power. Firms belonging to segments in which imports account for a
relatively large share of domestic sales would therefore be at a relative disadvantage in their ability to pass-
through costs because foreign producers would not incur costs as a result of the Final Existing Facilities
Regulation. The estimated import penetration ratio for the entire U.S. manufacturing sector (NAICS 31-33) for
2010 is 28 percent. For characterizing the ability of industries to absorb compliance cost burdens, EPA judges that
industries with import ratios close to or above 28 percent would more likely face stiff competition from foreign
firms and thus be less likely to succeed in passing compliance costs through to customers.
Export dependence, calculated as exports divided by value of shipments, measures the share of a segment's sales
that is presumed subject to strong foreign competition in export markets. The Final Existing Facilities Regulation
would not increase the production costs of foreign producers with whom domestic firms must compete in export
markets. As a result, firms in industries that rely to a greater extent on export sales would have less latitude in
increasing prices to recover cost increases resulting from regulation-induced increases in production costs. The
estimated export dependence ratio for the entire U.S. manufacturing sector for 2010 is 22 percent. For
characterizing the ability of industries to absorb compliance cost burdens, EPA judges that industries with export
ratios close to or above 22 percent are at a relatively greater disadvantage in potentially recovering compliance
costs through price increases since export sales are presumed subject to substantial competition from foreign
producers.
Table E-9 presents trade statistics for the profiled Petroleum Refining segment from 1990 to 2010. The table
shows that while export dependence has been relatively stable up until the mid-2000s, import penetration
decreased during the national economic weakness of the early 1990s, before leveling off through the mid-1990s.
Import penetration increased steadily through 2000 and then dropped slightly in 2001 and 2002. Since then, the
industry resumed a gradual increase in import penetration through 2006, followed by slight fluctuations between
2006 and 2010. On the other hand, export penetration increased from 5 percent in 2007 to 10 percent in 2010.
This cycle closely follows the periods of growth, stability, and decline of the U.S. economy during the volatile
E-14
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
two decades. Mexico received the largest amount of U.S. exported petroleum and coal products in 2008, followed
by Netherlands and Canada (U.S. DOC, 2009b). Imports of refined petroleum products increased 40.9 percent
from 1989 to 2008, with 46.3 percent of total imports coming from OPEC countries (U.S. DOE, 2009b).
The import penetration ratio for facilities in the Petroleum Refining segment in 2010 was only 17 percent, well
below the U.S. manufacturing segment average of 28 percent. The export dependence ratio for petroleum refiners
in 2010 was only 10 percent compared to the U.S. manufacturing average of 22 percent. Thus, based on the lack
of competitive pressures from foreign markets/firms, the Petroleum Refining Industry appears to be in a position
to pass-through to consumers a significant portion of compliance-related costs associated with the Final Existing
Facilities Regulation. However, given the low HHI for this industry, EPA expects that existing market
competition among domestic firms most likely nullifies any favorable influence the lack of foreign competitors
would have on increasing the market power of firms in this industry.
Table E-9: Foreign Trade Statistics for the Petroleum Refining Industry ($2011)
Year
Value of
Imports
(millions)
Value of
Exports
(millions)
Value of
Shipments
(millions)
Implied
Domestic
Consumption3
Import
Penetrationb
Export
Dependence0
1990
$24,055
$9,394
$250,072
$264,733
9%
4%
1991
$17,884
$9,630
$220,269
$228,523
8%
4%
1992
$16,162
$8,523
$201,623
$209,262
8%
4%
1993
$15,263
$8,168
$188,176
$195,271
8%
4%
1994
$14,338
$7,031
$182,484
$189,790
8%
4%
1995
$13,232
$7,408
$189,159
$194,983
7%
4%
1996
$26,870
$8,588
$215,472
$233,754
11%
4%
1997
$29,142
$9,219
$212,535
$232,458
13%
4%
1998
$24,431
$6,870
$156,502
$174,062
14%
4%
1999
$30,443
$7,523
$188,351
$211,271
14%
4%
2000
$53,714
$11,151
$275,421
$317,984
17%
4%
2001
$46,638
$10,088
$249,777
$286,328
16%
4%
2002
$41,239
$9,510
$239,468
$271,198
15%
4%
2003
$49,900
$11,034
$269,383
$308,250
16%
4%
2004
$67,686
$14,450
$357,614
$410,850
16%
4%
2005
$96,926
$19,845
$505,479
$582,561
17%
4%
2006
$106,298
$28,144
$562,389
$640,543
17%
5%
2007
$113,137
$32,531
$618,962
$699,568
16%
5%
2008
$141,309
$60,304
$764,795
$845,800
17%
8%
2009
$80,789
$42,623
$479,793
$517,959
16%
9%
2010
$107,148
$61,618
$601,212
$646,742
17%
10%
Total Percent Change
1990-2010
345.4%
555.9%
140.4%
144.3%

Total Percent Change
1990-2010
99.5%
452.6%
118.3%
103.4%

Average Annual
Growth Rate
8%
10%
4%
5%

a. Calculated by EPA as shipments + imports - exports.
b. Calculated by EPA as imports divided by implied domestic consumption.
c. Calculated by EPA as exports divided by shipments.
Note: Before 1997, these data were compiled in the Standard Industrial Classification (SIC) system; since 1997, these data have been compiled in the North
American Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the
1997 Economic Census Bridge Between NAICS and SIC.
Source: U.S. ITC, 1989-2010
The United States consumes more petroleum than it produces, requiring net imports of both crude oil and refined
products to meet domestic demand. In 2008, the United States imported 9.76 million barrels per day (MBD) of
crude oil and 3.12 MBD of refined products. These refined product imports represented roughly 16 percent of the
19.42 MBD of refined products supplied to U.S. consumers. The U.S. exported 1.80 MBD of refined products in
2008 (U.S. DOE, 2009b).
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
Imports of refined petroleum products have fluctuated since 1985. Imports rose to 2.3 MB in the early 1980s, due
to rapid growth in oil consumption, especially consumption of light products, which exceeded the growth in U.S.
refining capacity. Imports then declined as a result of the 1990-91 recession and increased upgrading of refinery
capacity resulting primarily from the 1990 Clean Air Act Amendments and other environmental requirements
(U.S. DOE, 1997). Since the 1995 low point, imports steadily increased through 2000 with the exception of 1998,
before dropping again, due to general economic weakness, in 2001 and 2002 (see Figure E-5). Up until 2008,
both imports and exports showed rapid growth, with value of imports surpassing 100 billion dollars, and the value
of exports reaching nearly 60 billion dollars. In 2009, both imports and exports declined significantly. In 2010,
exports rebounded to a level higher than that of 2008 while the rise in imports was relatively smaller.
Figure E-5: Value of Imports and Exports for the Petroleum Refining Industry (millions, $2011)a
—~— Exports (SIC 2911) —~— Exports (NAICS 3 24110)
—A— Imports (SIC 2911) —*— Imports (NAICS 324110)
a Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American Industry
Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic
Census Bridge Between NAICS and SIC.
Source: U.S. ITC, 1989-2010
R ®
k N
S140,000
S120,000
S100,000
S80,000
S60,000
S40,000
S20,000
SO
ve
o

tJ
fci

fci

4->

Petroleum exports include heavy products such as residual fuel oil and petroleum coke, which are produced as co-
products with motor gasoline and other light products. Production of these heavier products often exceeds U.S.
demand, and foreign demand absorbs the excess. Distillate fuel oil is the leading petroleum export product,
accounting for 29 percent of petroleum exports in 2008, followed by petroleum coke (almost 22 percent of
exports) and residual fuel oil (almost 20 percent) (U.S. DOE, 2009b). Exports generally reflect foreign demand,
but other factors influence exports as well. For example, exports of motor gasoline increased due to high prices in
Europe at the time of the 1990 Persian Gulf War (U.S. DOE, 1997). U.S. refiners and marketers have gained
experience in marketing to diverse world markets, and U.S. products are now sold widely abroad. As reported by
the International Trade Administration and shown in Figure E-5, the real value of petroleum exports fluctuated
between $6 and $10 billion during the years 1990 and 2002, and then increased over six-fold by the end of the
decade.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
E.5 Financial Condition and Performance
The financial performance and condition of the Petroleum Refining segment are important determinants of its
ability to absorb the costs of regulatory compliance without material adverse economic/financial impact. To
provide insight into the industry's financial performance and condition, EPA reviewed two key measures of
financial performance over the period 1992 to 2012: net profit margin and return on total capital. EPA calculated
these measures using data from the Quarterly Financial Report (QFR). Financial performance in the most recent
financial reporting period (2012) is obviously not a perfect indicator of conditions at the time of regulatory
compliance. However, examining the trend, and deviation from the trend, through the most recent reporting
period gives insight into where the industry may be, in terms of financial performance and condition, at the time
of compliance. In addition, the volatility of performance against the trend, in itself, provides a measure of the
potential risk faced by the industry in a future period in which compliance requirements are faced: all else equal,
the more volatile the historical performance, the more likely the industry may be in a period of relatively weak
financial conditions at the time of compliance.
Net profit margin is calculated as after-tax income before nonrecurring gains and losses as a percentage of sales
or revenue, and measures profitability, as reflected in the conventional accounting concept of net income. Over
time, the firms in an industry, and the industry collectively, must generate a sufficient positive profit margin if the
industry is to remain economically viable and attract capital. Year-to-year fluctuations in profit margin stem from
several factors, including: variations in aggregate economic conditions (including international and U.S.
conditions), variations in industry-specific market conditions (e.g., short-term capacity expansion resulting in
overcapacity), or changes in the pricing and availability of inputs to the industry's production processes (e.g., the
cost of energy to the petroleum refining process). The extent to which these fluctuations affect an industry's
profitability, in turn, depends heavily on the fixed vs. variable cost structure of the industry's operations. In a
capital intensive industry such as Petroleum Refining, the relatively high fixed capital costs as well as other fixed
overhead outlays, can cause even small fluctuations in output or prices to have a large positive or negative affect
on profit margin.
Return on total capital is calculated as annual pre-tax income divided by the sum of: current portion of long-term
debt due in 1 year or less, long-term debt due in more than 1 year, all other noncurrent liabilities and total
stockholders' equity (total capital). This concept measures the total productivity of the capital deployed by a firm
or industry, regardless of the financial source of the capital (i.e., equity, debt, or other liability element). As such,
the return on total capital provides insight into the profitability of a business' assets independent of financial
structure and is thus a "purer" indicator of asset profitability than return on equity. In the same way as described
for net profit margin, the firms in an industry, and the industry collectively, must generate, over time, a sufficient
return on capital if the industry is to remain economically viable and attract capital. The factors causing short-term
variation in net profit margin will also be important sources of short-term variation in return on total capital.
Figure E-6 below shows trends in net profit margins and return on total capital for the Petroleum Refining
segment between 1988 and 2012. Through the first half of the 1990s, unusually low product margins, low
profitability, and substantial restructuring characterized the petroleum industry. These low profit margins resulted
from three supply-side factors - (1) increases in operating costs as a result of governmental regulations; (2)
expensive upgrading of processing units to accommodate lower-quality crude oils;229 and (3) upgrading of
operations to adapt to changes in demand for refinery products230 - coupled with lower product prices, resulting
229 Crude oils processed by U.S. refineries have become heavier and more contaminated with materials such as sulfur. This trend reflects
reduced U.S. dependence on the more expensive high gravity ("light") and low sulfur ("sweet") crude oils produced in the Middle
East, and greater reliance on crude oil from Latin America (especially Mexico and Venezuela), which is relatively heavy and contains
higher sulfur ("sour") (U.S. DOE, 1999a).
230 Demand for lighter products such as gasoline and diesel fuel has increased, and demand for heavier products has decreased.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
from competitive pressures (API, 1999). In the late 1990s, the petroleum industry pursued cost-cutting measures
throughout their operations (Rodekohr, 1999).2,1 These cost-cutting measures, along with increases in the prices
of petroleum refining products, resulted in significantly improved financial performance in the Petroleum
Refining Industry. Refinery profits remained high in 2000 and the first half of 2001, due to low product
inventories and high operating rates. The latter half of 2001 and 2002 saw the effects of the global recession, the
attacks of 9/11, and a mild winter. These factors, coupled with world supply in excess of demand, led to decreases
in refiner margins, as crude oil prices increased and petroleum product prices decreased. In 2003, as the U.S.
economy began recovery from its economic hardship, the domestic Petroleum Refining segment returned to
relatively strong financial performance.
During the last decade, Petroleum Refining Industry's performance continued to improve from 2004 through
2006, reaching the highest return on total capital and net profit margin observed over the time period. The
industry showed a decrease in both net profit margin and return on total capital in 2007 and 2008, trending along
with the beginning of the U.S. and global economy decline. At the end of the last decade, the oil and gas refining
and marketing sub-was facing a challenging environment due to imbalance between supply and demand. This
imbalance stemmed from a fall in U.S. demand for refined products by more than 3 million b/d from February
2008 to June 2009, at the same time that a minimum of 2 million b/d per year of new refining capacity worldwide
was expected between 2009 and 2014 (S&P, 2010b; U.S. DOE, 2009a). In 2009, net profit margin and return on
capital continued to decrease while in 2010 net profit margin decreased less severely and return on total capital
increased. In 2011, both indicators saw significant rises, followed by declines in 2012.
Figure E-6: Net Profit Margin and Return on Total Capital for the Petroleum Refining Industry
—~— N et Pro fit M argin A Return on T otal C apital
Source: U.S. DOC, 1988-2012 OFR
24%
22%
20%
18%
16%
14%
12%
10%
8%
6%
4%
2%
0%

_
_
_
_
_
_
_
_
_
_

o
o

•s©

4-t

©^

00
's©
©
—

4-t

©^
^4
00
S©
©

231 Reductions in costs resulted from:
> divesting marginal refineries and gasoline outlets;
> divesting less profitable activities (e.g., gasoline credit cards);
> reducing corporate overhead costs, including eliminating redundancies through restructuring;
> outsourcing some administrative activities; and use of new technologies requiring less labor.
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May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
E.6 Facilities Operating Cooling Water Intake Structures
Section 316(b) of the Clean Water Act applies to point source facilities that use, or propose to use, a cooling water
intake structure that withdraws cooling water directly from a surface waterbody of the United States. In 1982, the
Petroleum and Coal Products industry (SIC 29) withdrew 590 billion gallons of cooling water, accounting for
approximately 0.8 percent of total industrial cooling water intake in the United States.2j2 The industry ranked 4th
in industrial cooling water use, behind the electric power generation industry and the chemical and primary metals
industries (U.S. DOC, 1982).
This section provides information for facilities in the petroleum segment estimated to be subject to regulation for
the final rule and other options EPA considered. Existing facilities that meet the following conditions are
potentially subject to regulation:
> Have a National Pollutant Discharge Elimination System (NPDES) permit or are required to obtain one;
> Use or propose to use one or more cooling water intake structures to withdraw water from waters of the
United States;
> Use at least twenty-five (25) percent of the water withdrawn exclusively for contact or non-contact
cooling purposes; and
> Meet the specific applicability coverage criteria for the final rule and other options EPA considered in
terms of design intake flow (i.e., two mgd).
EPA initially identified the set of facilities that were estimated to be potentially subject to the 316(b) Existing
Facilities Regulation based on a minimum applicability threshold of two mgd; this section focuses on these
facilities for the Petroleum Refining Industry.233
E.6.1 Waterbody and Cooling Water Intake System Type
Table E-10 shows the distribution of facilities by type of waterbody and cooling water intake system. According
to the American Petroleum Institute and EPA, water use at Petroleum Refineries has been declining because
facilities are increasing their reuse of water (U.S. EPA, 1996a).
Table E-10: Number of Facilities Estimated Subject to the 316(b) Existing Facilities Regulation by
Waterbody Type and Cooling Water Intake System for the Petroleum Refining Industry
Waterbody Type
Cooling Water Intake System
Total
Recirculating
Combination
Once-Through
Number
% of Total
Number
% of Total
Number
% of Total
Estuary/ Tidal River
0
0%
3
30%
2
40%
5
Ocean
0
0%
0
0%
1
20%
1
Lake/Reservoir
1
5%
0
0%
0
0%
1
Freshwater River/ Stream
22
95%
5
50%
2
40%
29
Great Lake
0
0%
2
20%
0
0%
2
Total3
23
58%
11
28%
5
14%
39
a. Individual numbers may not add up to total due to independent rounding.
Source: U.S. EPA, 2000; U.S. EPA analysis for this report
232 Data on cooling water use are from the 1982 Census of Manufactures. 1982 was the last year in which the Census of Manufactures
reported cooling water use.
233 EPA applied sample weights to the sampled facilities to account for non-sampled facilities and facilities that did not respond to the
survey. For more information on EPA's 2000 Section 316(b) Industry Survey, please refer to the Information Collection Request (U.S.
EPA, 2000).
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix E: Petroleum Refining Industry Profile
E.6.2 Facility Size
All petroleum refinery facilities that EPA expects to be subject to the final rule and other options EPA considered
are relatively large. Figure E-7 shows the number of potentially regulated facilities by employment size category.
Figure E-7: Number of Facilities Estimated Subject to the 316(b) Existing Facilities Regulation by Employment Size
for the Petroleum Refining Industry
_UL
18
16
14
12
io H
8
6
4
2
0
>t
Less than
100
X 7

100-249
250-499
500-999
1000 and
greater
Source: U.S. EPA, 2000; U.S. EPA analysis for this report
E.6.3 Firm Size
EPA used the Small Business Administration (SBA) small entity thresholds to determine the number of facilities
in the Petroleum Refining segment that are owned by small firms. Firms in this industry are considered small if
they employ fewer than 1,500 people. EPA estimates that four small entity-owned facilities and 35 large entity-
owned facilities in the Petroleum Refining segment will be subject to the final regulation.
E-20
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
Appendix F Profile of the Steel Industry
F.1 Introduction
EPA's Detailed Industry Questionnaire, hereafter referred to as the DQ, identified five 4-digit SIC codes in the
Steel Works, Blast Furnaces, and Rolling and Finishing Mills Industries (SIC 331) with at least one existing
facility that operates a CWIS, holds a NPDES permit, withdraws at least two million gallons per day (mgd) from a
water of the United States, and uses at least 25 percent of its intake flow for cooling purposes (facilities with these
characteristics are hereafter referred to as "facilities potentially subject to the 316(b) Existing Facilities
regulation" or "regulated facilities"). For the purpose of this analysis, EPA identified a six-digit NAICS code for
each of these potential facilities using the information from DQ and public sources (see Appendix J: Mapping
Manufacturers Standard Industrial Classification (SIC) Codes to North American Industry Classification System
(NAICS) Codes). As the result of this mapping, EPA identified five 6-digit NAICS codes in the Steel and Allied
Products manufacturing industry (NAICS 3311/2).
For each of the five NAICS codes, Table F-l, below, provides a description of the industry segment, a list of
primary products manufactured, the total number of detailed questionnaire respondents (weighted to represent a
national total of facilities that hold a NPDES permit and operate cooling water intake structures), and the number
of facilities estimated to be potentially subject to the 316(b) Existing Facilities Regulation based on the minimum
withdrawal threshold of two mgd.
Table F-1: Existing Facilities in the Steel Industry (NAICS 3311/2)
NAICS
NAICS
Description
Important Products Manufactured
Number of
Regulated
Facilities3
Steel Mills (NAICS 3311)
331111
Iron and Steel
Mills
Hot metal, pig iron, and silvery pig iron from iron ore and iron and steel scrap;
converting pig iron, scrap iron, and scrap steel into steel; hot-rolling iron and steel into
basic shapes, such as plates, sheets, strips, rods, bars, and tubing; merchant blast
furnaces and byproduct or beehive coke ovens
42
331112
Electrometallurgic
al ferroalloy
products
manufacturing
Iron-rich alloys and more pure forms of elements added during the steel
manufacturing process. Ferroalloys add critical elements for low and high metal alloys.
2
Steel Products (NAICS 3312)
331210
Iron and steel pipe
and tubes
manufacturing
from purchased
steel
Production of welded or seamless steel pipe and tubes and heavy riveted steel pipe
from purchased materials
9
331221
Rolled steel shape
manufacturing
Cold-rolling steel sheets and strip from purchased hot-rolled sheets; cold-drawing steel
bars and steel shapes from hot-rolled steel bars; producing other cold finished steel
13
331222
Steel wire drawing
Drawing wire from purchased iron or steel rods, bars, or wire; further manufacture of
products made from wire; steel nails and spikes from purchased materials
3
Total Steel Products b
24
Total Steel (NAICS 3311/2)
Total NAICS Code 3311/2b | 68
a. Number of weighted detailed questionnaire survey respondents.
b. Individual numbers may not add up due to independent rounding.
Source: Executive Office of the President, 1987; U.S. EPA, 2000; U.S. EPA analysis for this report
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
As shown in Table F-l, EPA estimates that, out of an estimated total of 476 facilities234 with a NPDES permit and
operating cooling water intake structures in the Steel Industry (NAICS 3311/2), 68 (14 percent) are expected to be
subject to the Final 316(b) Existing Facilities regulation. EPA also estimated the percentage of total production
that occurs at facilities estimated to be subject to the final rule and other options EPA considered. Total value of
shipments for the Steel Industry (NAICS 3311/2) from the 2010 Annual Survey of Manufactures is $118.1 billion
($2011). Value of shipments, a measure of the dollar value of production, was selected for the basis of this
estimate. Because the DQ did not collect value of shipments data, these data were not available for existing
facilities. Total revenue, as reported on the DQ, was used as a close approximation for value of shipments for
these facilities. EPA estimated the total revenue of facilities expected to be subject to the 316(b) Existing
Facilities Regulation is $57.2 billion ($2011).235 Therefore, EPA estimates that 48 percent of total production in
the Steel Industry occurs at facilities estimated to be subject to regulation.
The responses to the Detailed Questionnaire indicate that two main steel segments account for all of the potential
regulated facilities: (1) Steel Mills (NAICS codes 331111 and 331112) and (2) Steel Products (NAICS codes
331210, 331221, and 331222).
Table F-2 provides the crosswalk between the new NAICS codes and the SIC codes for the profiled steel NAICS
codes. The table shows that electrometallurgical ferroalloy product manufacturing (NAICS 331112), rolled steel
shape manufacturing (NAICS 331221), steel wire drawing (NAICS 331222), and Iron and steel pipes and tubes
manufacturing from purchased steel (NAICS 331210) have a one-to-one relationship to SIC codes. The remaining
NAICS code - iron and steel mills (NAICS 331111) - corresponds to two SIC codes.
234 This estimate of the number of facilities holding a NPDES permit and operating a cooling water intake structure is based on the
responses from facilities that received the 1999 screener questionnaire.
235 To compare revenue values of regulated facilities with the industry value of shipments, EPA brought revenue values for regulated
facilities forward to 2010 using industry-specific Producer Price Index (PPI) values published by the Bureau of Labor Statistics (BLS)
and stated in 2011 dollars using GDP deflator published by the Bureau of Economic Analysis (BEA).
F-2
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
Table F-2: Relationships between NAICS and SIC Codes for the Steel Industries (2010)
NAICS Code
NAICS
Description
SIC Code
SIC Description
Number of
Establishments
(2009)a
Value of
Shipments
(2010;
Millions;
$2011)
Employment
(2010)
331111
Iron and steel mills
3312
Blast furnaces and steel
mills
566
$94,823
95,129
3399
Blast furnaces and steel
mills
331112
Electrometallurgical
ferroalloy product
manufacturing
3313
Electrometallurgical
products
22
$1,224
1,784
331221
Rolled steel shape
manufacturing
3316
Cold finishing of steel
shapes
168
$7,056
9,174
331222
Steel wire drawing
3315
Steel wire and related
products
276
$5,616
13,382
331210
Iron and steel pipes
and tubes
manufacturing from
purchased steel
3317
Steel pipe and tubes
201
$9,369
16,790
a. The most recent data on number of establishments is available for 2009 from Statistics of U.S. Businesses. Value of Shipments and Employment reflect
2010 data.
Sources: U.S. DOC, 2010 ASM; U.S. DOC, 2009 SUSB
F.2 Summary Insights from this Profile
The key purpose of this profile is to provide insight into the ability of Steel Industry firms to absorb compliance
costs under the final rule without material adverse economic/financial effects. The industry's ability to absorb
compliance costs is primarily influenced by two factors: (1) the extent to which the industry may be expected to
shift compliance costs to its customers through price increases and (2) the financial health of the industry and its
general business outlook.
F.2.1 Likely Ability to Pass Compliance Costs Through to Customers
As reported in the following sections of this profile, the Steel Mill segment is moderately concentrated while the
Steel Products segment is unconcentrated, which suggests that firms in the profiled Steel Industry would have
difficulty in passing a significant portion of their compliance-related costs through to customers. The domestic
Steel Industry does not appear to face significant competition from foreign trade. Despite, the relatively high
proportion of total value of shipments in the industry estimated subject to regulation under the final rule and other
options EPA considered (nearly 50 percent), based on the overall lack of market power in the industry EPA
judges that regulated facilities subject to the 316(b) Existing Facilities Regulation are not likely to be able to
recover compliance costs through price increases to customers and would have to absorb all compliance costs
within their operating finances (see following sections and Appendix K: Cost Pass-Through Analysis, for further
information).
F.2.2 Financial Health and General Business Outlook
Over the past two decades, the U.S. Steel Industry, like other U.S. manufacturing industries, experienced a range
of economic/financial conditions, including substantial challenges. The U.S. Steel Industry went through a
difficult restructuring process in the 1980s and early 1990s, including the closing of a number of inefficient mills,
substantial investment in new technologies, and reductions in the labor force. Although U.S. demand for steel was
strong in the late 1990s, low-priced imports increased substantially in 1998 because of the Asian financial crisis,
with the associated decline in Asian demand for steel and currency devaluations, thereby causing a number of
bankruptcies of U.S. Steel firms and steelworker layoffs. In addition to being affected by the increased inflow of
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
low-priced imported steel, the U.S. Steel Industry was also negatively affected by economic recession in 2000 and
2001. Tariffs provided temporary relief through 2002, but were removed by the end of 2003. By 2003, the U.S.
Steel Industry's financial performance improved significantly, particularly for the Steel Mills industry segment,
and value of shipments and value added increased substantially. During this time, demand grew considerably, the
industry became more concentrated with high levels of productivity, and trade activity increased. The 2008
recession slowed growth of the U.S. Steel Industry, with a substantial decrease in production in 2008. Moving out
of the recession, experts expect an increase in the volume of steel shipped in 2013. Experts also project a seven
percent increase in consumption, following a nine percent rise in 2012. However, remaining excess steel capacity
offsets this expected increases in volume of steel shipments leaving experts to project a neutral outlook for 2013
(S&P, 2013h). Overall, the current condition of the Steel Industry suggests that, financial performance may be
improving since the recent recession, indicating an average ability to absorb additional regulatory compliance
costs.
F.3 Domestic Production
Steel is one of the most important products of the U.S. industrial metals industry. For most of the twentieth
century, the U.S. Steel Industry consisted of a few large companies utilizing an integrated steelmaking process to
produce raw steel. The integrated process requires a large capital investment to process coal, iron ore, limestone,
and other raw materials into molten iron, which is then transformed into finished steel products. In recent decades,
the integrated Steel Industry has undergone a dramatic downsizing as a result of increased steel imports,
decreased consumption by the auto industry, and the advent of "minimills" (S&P, 2001b). While the traditional
integrated facilities using basic oxygen furnaces (BOF) still account for a substantial share of U.S. steel mill
product production, the share of electric arc furnace (EAF) facilities using scrap steel as an input has grown
steadily.236 By 2007, about 47 companies, operating about 98 steelmaking facilities, used the EAF steelmaking
process; these non-integrated, minimill facilities produced 57 million metric tons of steel, an increase of about 1.7
percent compared with that of 2006, and accounted for 41.8 percent of total U.S. steelmaking (USGS, 2007f). The
range of products produced by EAFs has also expanded over time. Initially, EAFs produced primarily lower-
quality structural materials. Starting in the 1990s, EAFs began producing higher quality sheet products as well. A
majority of recent capacity additions have been at EAF facilities.
Basic steel mill products include carbon steel, steel alloys, and stainless steel. Steel forming and finishing
operations may take place at facilities co-located with steelmaking or at separate facilities. These operations use
steel (in the form of blooms, billets, and slabs) in combination with heating, rolling or drawing, pickling, cleaning,
galvanizing, and electroplating processes in various combinations to produce finished bars, wire, sheets, and coils
(semifinished steel products). Establishments that produce hot rolled products, along with basic BOF and EAF
steelmaking facilities, are included in NAICS 331111 while establishments that primarily engaged in
manufacturing of electrometallurgical ferroalloys are included in NAICS 331112. NAICS codes 331222, 331221,
and 331212 perform additional processing of steel bars, wires, sheets, and coils (including cold-rolling of sheets)
to produce steel products for a variety of end-uses (U.S. EPA, 2000).
The Steel Industry represents about 3 percent of total U.S. energy demand, and the total cost of energy accounts
for approximately 15-20 percent of the total manufacturing cost (NEED, 2010). Steelmakers use coal, oil,
electricity, and natural gas to fire furnaces and run process equipment. Minimill producers require large quantities
of electricity to operate the electric arc furnaces used to melt and refine scrap metal, while integrated steelmakers
depend on coal-fired facilities' coal and electricity for up to 60 percent of their total energy requirements (NEED,
236 Production from open hearth furnaces, which dominated production until the early 1950s, ended in 1991. BOF facilities have
traditionally been referred to as integrated producers, because they combined iron-making from coke, production of pig iron in a blast
furnace, and production of steel in the BOF. In recent years, some facilities have closed their coke ovens. These BOF facilities are no
longer fully integrated.
F-4
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
2010). Because of its high energy intensity, the Steel Industry has invested over $60 billion in new technologies
since 1975 in an effort to improve energy efficiency and productivity. As a result of this effort as well as
increased use of recycled steel and older facility closures, the industry has been able to reduce its energy
consumption by 45 percent per ton of steel since 1973 (NEED, 2010).
F.3.1 Output
Steel mill products are sold to service centers (which buy finished steel, often process it further, and sell to a
variety of fabricators, manufacturers, and construction industry clients), to vehicle producers, and to the
construction industry. The rapid growth in sales of heavy sport utility vehicles contributed to increased U.S. steel
consumption in the 1990s. However, recent efforts to increase the fuel efficiency of vehicles have eroded steel's
position in the automotive market as a whole, as aluminum and plastic have replaced steel in many automotive
applications. Other end-uses for steel include a wide range of agricultural, industrial, appliance, transportation,
and container applications. Use of steel in beverage cans has been largely replaced by aluminum.
Table F-3 shows trends in production from the two major groups of steel producers: BOF and EAF facilities.
Table F-3: U.S. Steel Production by Type of Producer
Year
Steel Production
Percent from BOFc
Percent from EAFd
Million MT
% Change
I 990'1
89.7
NA
59.1%
37.3%
iwT
79.7
-11.1%
60.0%
38.4%
1 992
84.3
5.8%
62.0%
38.0%
1993
88.8
5.3%
60.6%
39.4%
1994
91.2
2.7%
60.7%
39.3%
199 5
95.2
4.4%
59.6%
40.4%
1996
95.5
0.3%
57.4%
42.6%
1997
98.5
3.1%
56.2%
43.8%
1998
98.6
0.1%
54.9%
45.1%
1 999
97.4
-1.2%
53.7 %
46.3%
2000
102
4.7%
53.0%
47.0%
2001
90.1
-1 1.7%
52.6%
47.4%
2002
91.6
1.7%
49.6%
50.4%
2003
93.7
2.3%
49.0%
51.0%
2004
99.7
6.4%
47.8%
52.2%
2005
94.9
-4.8%
45.0%
55.0%
2006
98.2
3.5%
42.9%
57.1%
2007
98.1
-0.1%
41.8%
58.2%
2008
91.9
-6.3%
42.6%
57.4%
2009
59.4
-35.4%
38.2%
61.8%
2010-'
90.0
51.5%
39.0%
61.0%
Percent Change 1990-2010
0.33%

Percent Change 2000-2010
-11.76%

Average Annual Growth
Rate237
0.02%

a. 3.5 percent of 1990 production was from open hearth furnaces.
b. 1.6 percent of 1991 production was from open hearth furnaces.
c. Basic oxygen furnaces
d. Electric arc furnaces
3. Data provided for 2010 are estimated values.
Source: USGS, 1995b, 1999b, 2002b, 2006b, 2010b, and 2011b
237 In this appendix, average annual growth rate refers to a year-to-year, constant percentage growth mean, which is calculated as the
compound annual growth rate between the first and last values. This is the same concept as the geometric mean, if all of the individual
year-to-year values are the same as those used in calculating the constant percentage growth mean.
May 2014
F-5
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
This table shows the cyclical nature of the U.S. Steel Industry, with variations in growth from year to year
reflecting general domestic and world economic conditions, persistent excess production capacity worldwide, the
competitive strength of imports, and trends in steel's share of the automotive and other end-use markets for steel.
The U.S. Steel Industry went through a difficult restructuring process in the 1980s and early 1990s, including the
closing of a number of inefficient mills, substantial investment in new technologies, and reductions in the labor
force. Following this difficult transition, the United States became a world leader in low-cost production, led by
the minimill producers. Although U.S. demand for steel was strong in the late 1990s, low-priced imports
increased substantially in 1998, which led to a number of U.S. steel bankruptcies and steelworker layoffs. The
increased imports resulted from the Asian financial crisis, with the associated decline in Asian demand for steel
and currency devaluations. The U.S. government initiated the Steel Action Program in response to the crisis,
focusing on strong enforcement of trade laws through the World Trade Organization and bilateral efforts to
address market-distorting practices abroad.238 The industry began to show signs of recovery in the second half of
1999, but by 2000, capacity utilization saw major declines (U.S. DOC, 2011 (SPC)).
Beginning in 2000, the weakening of the U.S. economy significantly reduced steel demand and total U.S. steel
production fell by nearly 12 percent in 2001. In March 2002, the U.S. Steel Industry received temporary relief
under Section 201 of the 1974 Trade Act with three years of tariffs ranging up to 30 percent on certain steel
imports. Relief from imports was nullified to some extent when the U.S. Department of Commerce exempted 727
imported steel products from the tariff in June 2002. By year-end, 2002 was the fourth highest steel import year in
U.S. history (USGS, 2002f). Removal of all tariffs occurred on December 4, 2003 (S&P, 2004c). The Steel
Industry recovered, but slowly, from the import penetration in the late 1990s followed by the economic recession
in 2001. In 2003, the integrated Steel Industry had poor operating results, as high raw material costs outweighed
increased sales and higher volumes. As a result, most domestic steel producers instituted a raw material surcharge
to offset sharply rising costs for raw materials such as scrap, iron ore and coke.
Between 2000 and 2005, world steel demand increased by 6 percent, and China surpassed Japan, Russia, and the
United States to become the number one steel producer (British Geological Survey, 2005). During this period the
two different methods for producing steel - integrated (ore-based) and electric arc furnace (scrap-based) - began
converging in response to the changing cost balance of raw materials, scrap and energy (AISI, 2001a). Despite the
increase in demand in the first half of the decade, steel production declined substantially between 2000 and 2010,
as shown in Table F-3. This was largely due to significant declines that occurred in 2001, 2008 and 2009,
coinciding with the recent economic downturns.
Value of shipments and value added are two common measures of manufacturing output.239 Change in these
values overtime provides insight into the overall economic health and outlook for an industry. Value of
shipments is the sum of receipts earned from the sale of outputs; it indicates the overall size of a market or the
size of a firm in relation to its market or competitors. Value added, defined as the difference between the value of
shipments and the value of inputs used to make the products sold, measures the value of production activity in a
particular industry.
Figure F-l presents trends in constant-dollar value of shipments and value added for the profiled Steel Mills and
Steel Products segments. Value of shipments and value added from Steel Mills declined in the early 1990s, and
recovered through 1997, prior to the 1998 import crisis and the later U.S. economic recession. The segment's
value of shipments began to decline after 1997 and continued to do so through 2001. However, from 2002
through 2008, the Steel Mills segment experienced continuous growth, with value of shipments peaking at over
238 World steel trade is characterized by noncompetitive practices in a number of countries, which have resulted in substantial friction
over trade issues since the late 1960s. Since 1980, almost 40 percent of the unfair trade practice cases investigated in the U.S. have
been related to steel products (U.S. DOC, 2000).
239 Terms highlighted in bold and italic font are further explained in the glossary.
F-6
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
$132 billion at the end of that period. Steel Mills value added also continued to decline until 2001 and then
increased drastically in 2004. Between 2004 and 2006, value added for the Steel Mills segment remained
relatively constant. This stagnation was followed by more substantial growth up until 2008. In 2009, both value
added and value of shipments for the Steel Mills segment fell drastically (by over 50 percent). These large
declines were followed by significant increases in 2010. Value of shipments and value added for Steel Products
were less volatile, increasing gradually during 1990 through 1995 and 1996, respectively, when both value of
shipments and value added began to decline, bottoming in 2003. From 2004 to 2008, both value of shipments and
value added for the profiled Steel Products segment experienced overall moderate growth. Like the Steel Mills
segment, value added and value of shipments in the Steep Products segment declined in 2009 and then rebounded
in 2010.
May 2014
F-7
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
Figure F-1:Value of Shipments and Value Added for Profiled Steel Industry Segments (millions, $2011)a
Value of Shipments

c
o
*5
0
3
1
S130.000
S120.000
S110.000
S100.000
S90,000
S80,000
S70,000
S60,000
S50,000
S40,000
S30,000
S20,000
S10,000
—A— Steel Mills (SIC to NAICS)
-*— Steel Mills (NAICS 3311)
— Steel Products (SIC to NAICS)
-~— Steel Products (NAICS 3312)
OOsSsSsSsSsSsSsSsSsSsSsSSSSSSSSSSSS
x » x < m < « « 40I«e
Value Added
y.
<
w
s
1
S50,000
S45,000
S40,000
S35,000
S30,000
S25,000
S20,000
S15,000
S10,000 ,4-++
S5,000
—A— Steel Mills (SIC to NAICS)
-*— Steel Mills (NAICS 3311)
— Steel Products (SIC to NAICS)
-~— Steel Products (NAICS 3312)
«>elelelele*c*c*c*c*c*c*cooooooooooo
XXX««««««««««SSSSSSSOOOH
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997
Economic Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and
2007 EC
F.3.2 Prices
The producer price index (PPI) measures price changes, by segment, from the perspective of the seller, and
indicates the overall trend of product pricing, and thus supply-demand conditions, within a segment.
F-8
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
As shown in Figure F-2, below, prices increased from 1987 to 1989 and then dropped slightly in the early 1990s,
due to depressed domestic economy and the resulting decline in demand for steel. During the 1990s, prices in
both profiled segments remained on average unchanged, with prices in the Steel Mills segments rising temporarily
in the middle of the decade. As the U.S. and world economies began to recover in 2002, so did steel prices, which
began to rise and continued to do so through 2008. Prices declined in 2009 and then rose for the remainder of the
period of analysis. Despite some fluctuation, prices at the end of the last decade were significantly higher than at
the beginning of the analysis period. Overall, during the last two decades, prices in the profiled Steel Mills
segment showed a slightly higher degree of volatility compared to those in the profiled Steel Products segment.
Figure F-2: Producer Price Index for Profiled Steel Industry Segments
270
- Steel Mills (NAICS
3311)
¦Steel Products (NAICS
3312)
CdCdCdCdCdCdCdCdCdCdCdoo©©©©
CCGCGC'nSO'OOO'sS'OOO'nSOOOO
Source: BLS, 201 le
F.3.3 Number of Facilities and Firms
The number of operating Steel Mills fluctuated significantly between 1990 and 2009, as the U.S. industry
underwent a substantial restructuring. Table F-4 shows substantial decreases in the number of facilities in the
profiled Steel Mills segment in 1992 and 1993 due to a significant decrease in global demand and resulting
overcapacity. This decrease was followed by a significant recovery in 1995 and 1996, and another significant drop
in 1997. The number of facilities continued to rise through 2001, with the largest increase around 1999. This
increase may have resulted in part from the advent of minimills, as discussed above. The import crisis during
1997-1998 ultimately led to bankruptcy for a number of U.S. producers, including LTV and Bethlehem Steel
(S&P, 2001b). Additionally, seven major bankruptcies occurred over 2002 and early 2003, including Bayou Steel
Corp, Kentucky Electric Steel Inc, Slater Steel Inc, and Weirton Steel Corp (USGS, 2004b). Between 2000 and
2009, the number of facilities in the Steel Mills and Steel Products segments dropped by 41 percent and 40
percent, respectively. Largely due to declines at the end of the period, the Steel Mills segment saw an overall
increase of just under 2 percent in the number of facilities between 1990 and 2009 with an average annual growth
rate of less than 1 percent. Also mainly due to a decline in 2009, the Steel Products segment saw a decline in
firms of 2 percent at an average annual rate of less than 1 percent over the period.
May 2014
F-9
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
Table F-4: Number of Facilities in the Profiled Steel Industry Segments3

Steel Mills
Steel Products
Year
Number of
Facilities
Percent Change
Number of
Facilities
Percent Change
1990
579
NA
659
NA
1991
609
5.3%
782
18.7%
1992
499
-18.1%
807
3.1%
1993
436
-12.7%
808
0.1%
1994
431
-1.1%
779
-3.5%
1995
477
10.7%
766
-1.6%
1996
555
16.4%
748
-2.4%
1997
377
-32.1%
705
-5.8%
1998
410
8.7%
769
9.1%
1999
702
71.2%
824
7.2%
2000
1,003
42.9%
933
13.2%
2001
1,374
37.0%
939
0.6%
2002
1,259
-8.4%
870
-7.3%
2003
876
-30.4%
828
-4.8%
2004
799
-8.8%
734
-11.4%
2005
839
5.0%
716
-2.5%
2006
827
-1.4%
698
-2.5%
2007
901
8.9%
699
0.1%
2008
698
-22.5%
724
3.6%
2009
588
-15.8%
645
-10.9%
Total Percent Change
1990-2009
1.6%
-2.1%
Total Percent Change
2000-2009
-41.4%
-30.9%
Average Annual Growth
Rate
0.1%
-0.1%
a. Before 1998, data were compiled in the SIC system;
since 1998, these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code
classifications using the 1997 Economic Census Bridge Between NAICS and SIC.

Source: U.S. DOC, 1990-1997SBA; U.S. DOC, 1998-2009 SUSB

Table F-5 shows the number of firms in the two profiled steel segments between 1990 and 2009. The trend in the
number of firms over the period between 1990 and 2009 is similar to the trend in the number of facilities in the
profiled Steel Mills industry segment. The number of firms in this segment decreased to a period-low of 288 in
1997, before increasing significantly during 1998 through 2001, to 1,269 firms. This rise in the number of Steel
Mill firms was followed by declines during 2002 through 2004, and then a slight recovery in 2005. Between 2000
and 2009, the number of firms in the Steel Mills segment fell by nearly 50 percent. Overall, between 1990 and
2009, the number of Steel Mill firms declined by 6 percent at an average annual rate of less than 1 percent. The
number of firms in the Steel Products segment also decreased between 1992 and 1997, before rising steadily
through 2001, and then declining between 2002 and 2009. Like the Steel Mills segment, the number of firms in
the Steel Products segment experienced a decline not only in the last decade - 29 percent - but an overall decline
of 11 percent between 1990 and 2009.
F-10
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
Table F-5: Number of Firms in the Profiled Steel Industry Segments3
Year
Steel Mills
Steel Products
Number of Firms
Percent Change
Number of Firms
Percent Change
I 990
482
NA
578
NA
I 991
505
4.7%
615
6.4%
I 992
401
-20.6%
642
4.3%
I 993
345
-14.0%
622
-3.1%
1994
342
-0.9%
599
-3.7 %
1995
388
13.6%
588
-1.8%
I 996
462
19.1%
567
-3.5%
1997
288
-37.7 %
528
-6.9%
I 998
320
1 1.0%
577
9.3%
I 999
603
88.4%
628
8.8%
2000
900
49.3%
725
15.4%
200I
1.269
41.0%
729
0.6%
2002
1.149
-9.5%
681
-6.6%
2003
758
-34.0%
684
0.4%
2004
684
-9.8%
598
-12.6%
2005
718
5.0%
580
-3.0%
2006
708
-1.4%
568
-2.1%
2007
776
9.6%
564
-0.7%
2008
566
-27.1%
599
6.2%
2009
454
-19.8%
517
-13.7%
Total Percent Change
1990-2009
-5.8%
-10.6%
Total Percent Change
2000-2009
-49.6%
-28.7%
Average Annual
Growth Rate
-0.3%
-0.6%
a Before 1998, data were compiled in the SIC system; since 1998, these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code
classifications using the 1997 Economic Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1990-1997SBA; U.S. DOC, 1998-2009 SUSB
F.3.4 Employment and Productivity
Figure F-3, following page, provides information on employment from the Annual Survey of Manufactures and
the Economic Census for the profiled Steel Mills and Steel Products segments. As shown in the figure, between
1987 and 2010, employment levels in the Steel Mills segment decreased by a total of nearly 50 percent at an
average annual rate of 3 percent. Employment is a significant cost component for steelmakers. Labor cost
reductions enabled Steel Mills to improve profitability and competitiveness in the face of limited opportunities for
price increase in the highly competitive market of Steel Products. A steady decline in employment in the 1990s
reflects a smaller number of Steel Mill facilities and firms, in conjunction with aggressive efforts to improve
worker productivity in order to cut labor costs and improve profits (McGraw-Hill, 1998). Employment declined
further as a result of the 1997-1998 import crisis, with almost 26,000 U.S. steelworkers reportedly losing their
jobs (AISI, 2001b). During the 2000s decade, employment in the Steel Mills segment declined until 2006 when
the industry had a sudden rise in number of employees in 2007 and 2008, followed by declines. Employment in
the Steel Products segment also declined, except for an increase between 2006 and 2008, at an average annual rate
of nearly 2 percent resulting in a total decline of approximately 33 percent over the period 1987-2010
(approximately 37 percent between 2000 and 2010).
May 2014
F-11
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
Figure F-3: Employment for Profiled Steel Industry Segments3
220,000
200,000
180,000
160,000
140,000
120,000
100,000
80,000
60,000
40,000
—A— Steel Mills (SIC to
NAICS)
—*— Steel Mills (NAICS 3311)
—¦— Steel Products (SIC to
NAICS)
¦ Steel Products (NAICS
3312)
20,000
««««««««« '^'nC'nC'nCOOOO
K> K> K> K> K> K> K>
tn 9s oe vs o
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997
Economic Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007
EC
Table F-6 presents the change in value added per labor hour, a measure of labor productivity, for the Steel Mills
and Steel Products segments between 1987 and 2010. Labor productivity at Steel Mills increased significantly
over this period, despite a decline of nearly 60 percent in 2009. Between 1987 and 2010, value added per labor
hour increased approximately 120 percent, with most growth - 86 percent - taking place since 2000. Much of this
increase in labor productivity can be attributed to the restructuring of the U.S. Steel Industry and the increased
role of minimills in production. Minimills are capable of producing rolled steel from scrap with substantially
lower labor needs than integrated mills (McGraw-Hill, 1998). Labor productivity in the Steel Products segment
has also experienced an overall growth between 1987 and 2010, although less so compared to that in the Steel
Mills segment; labor productivity grew by about 24 percent between 1987 and 2010, with most of this growth -
approximately 35 percent - taking place between 2000 and 2010.
F-12
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
Table F-6: Productivity Trends for the Profiled Steel Industry Segments ($2011)a
Year
Steel Mills
Steel Products
Value Added
(millions)
Production
Hours
(millions)
Value Added/Hour
Value Added
(millions)
Production
Hours
(millions)
Value Added/Hour
$/hr
Percent
Change
$/hr
Percent
Change
1987
$28,210
313
$90
NA
$9,333
105
$89
NA
1988
$33,942

$102
12.9%
$9,575
91
$106
18.7%
1989
$32,359
357
$91
-1 1.0%
$9,336
109
$86
-19.0%
I 990
$29,416
323
$91
0.4%
$8,247
89
$92
7.6%
I 991
$22,682
287
$79
-13.1%
$8,303
104
$80
-13.0%
I 992
$25,207
285
$88
1 1.8%
$7,940
84
$95
17.9 %
I 993
$26,573
276
$96
8.9%
$9,140
106
$86
s s
I 994
$30,085
275
$109
13.7%
$9,084
88
$ 101
20.0%
1995
$31,461
271
$1 16
6.1%
$9,350
1 10
$85
-1 8.0%
I 996
$30,772
268

-1.2%
$9,482
130
$71
-14.2%
1997
$34,066
259
$M2
14.9%
$9,058
106
$86
1 8.0%
I 998
$32,340
252
$128
-2.8%
$8,706
108
$81
-5.9%
I 999
$28,535
243
$1 18
-8.2%
$8,377
103
$82
1.2%
2000
$26,357
248
$106
-9.5%
$8,534
104
$82
0.3%

$20,574
289
$71
-33 1%
$6,800
92
$74
-10.2%
2002
$22,827
200
$1 14
60.5%
$6,998
86
$81
10.6%
2003
$21.349
185
$1 16
1.2%
$6,095
80
$76
-6.9%

$37,867
191
$198
71.5%
$8,058
73

46.0%

$37,332
183
$204
2.7%
$8,143
73

1.1%
2006
$37,739
178
$212
3.9%
$7,962
71

0.0%
2007
$39,586
189
$209
-1.2%
$7 918
78
$101
-9 i%
2008
$45,165
188
$240
14.5%
$8,618
76

12.4%
2009
$15,123
150
$101
-58.0%
$3,827
55
$69
-39.2%
2010
$32,631
164
$199
97.4%
$6,892
62
$110
59.3%
Total Percent Change
1987-2010
15.7%
-47.5%
120.2%
-26.2%
-40.4%
23.9%
Total Percent Change
2000-2010
23.8%
-33.6%
86.6%
-19.2%
-40.1%
34.8%
Average Annual
Growth Rate
0.6%
-2.8%
3.5%
-1.3%
-2.2%
0.9%
a Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American Industry
Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997Economic
Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007EC
F.3.5 Capital Expenditures
New capital expenditures are needed to modernize, expand, and replace existing capacity to meet growing
demand. Capital expenditures in the profiled Steel Mills and the Steel Products segments between 1987 and 2010
are presented in Table F-7, following page. As shown in the table, capital expenditures in both the Steel Mills and
the Steel Products segments fluctuated significantly during this analysis period. Steel Mills" capital outlays
increased in the late 1980s and early 1990s, rising by a total of 109 percent between 1987 and 1991. This
substantial increase coincides with the advent of thin slab casting, a technology that allowed minimills to compete
in the market for flat rolled sheet steel. The significant decreases in capital expenditures by Steel Mills that
followed this expansion reflect the bottoming out of the demand for Steel Products in the early 1990s. The
recovery in capital expenditures in the mid-1990s reflected increased demand and higher utilization rates
(McGraw-Hill, 1998). The import crisis of the late 1990s and later weakening of the U.S. economy put pressure
on the domestic Steel Industry, and expenditures for new capacity began to decline in 1997 in both segments
(McGraw-Hill, 2000). However, capital expenditures in the Steel Mills segment recovered during the 2000s,
increasing by approximately 25 percent, while the Steel Products segments saw a decline of approximately 21
percent. Overall, between 1987 and 2010, capital expenditures increased by about 54 percent in the Steel Mills
segment and dropped by approximately 50 percent in the Steel Products segment.
May 2014
F-13
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
Table F-7: Capital Expenditures for the Profiled Steel Industry Segments (millions, $2011)a
Year
Steel Mills
Steel Products
Capital Expenditures
Percent Change
Capital Expenditures
Percent Change
1987
$2,182
NA
$940
NA
1988
3,3.281
50.4%
$71 1
-24.3%
1989

26.0%
$797
12.1%
I 990
$4,055
-1.9%
$797
0.0%
I 991
$4,553
12.3%
$572
-28 3%
I 992
$3,325
-27.0%
$588
2.8%
I 993
$2,612
-21.4%
$644
9.6%
I 994
$3,737
43.1%
$741
15.0%
1995
$3,843
2.8%
$721
-2.7%
I 996
$3,880
1.0%

7.2%
1997
$3,581
-7.7%
$715
-7.6%
I 998
$3,486
-2.7%
$685
-4.1%
I 999
$2,957
-15.2%
$574
-16.2%
2000
$2,688
-9.1%
$599
4.2%
200I
$1,937
-27.9%

-23.6%
2002
$1,679
-13.3%
$497
8.6%
2003
$1,154
-31.3%
$506
1.9%
2004

51.3%
$525
3.7%
2005
$2,043
17.1%
$409
-22.2%
2006
$2,012
-1.5%

5.7%
2007
$3,438
70.9%

19.9%
2008
$4,704
36.8%

0.0%
2009
$3,096
-34.2%

-8.6%
20I0
$3,366
8.7%
$475
0.3%
Total Percent Change
1987-2010
54.3%
-49.5%
Total Percent Change
2000-2010
25.2%
-20.7%
Average Annual Growth
Rate
1.9%
-2.9%
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American Industry
Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997Economic
Census Bridge Between NAICS and SIC.
Source: U.S. DOC, 1988-1991, 1993-1996, 1998-2001, 2003-2006, and 2008-2010 ASM; U.S. DOC, 1987, 1992, 1997, 2002, and 2007
EC
F.3.6 Capacity Utilization
Capacity utilization measures actual output as a percentage of total potential output given the available capacity.
Capacity utilization provides insight into the extent of excess or insufficient capacity in an industry, and into the
likelihood of investment in new capacity. Figure F-4 presents capacity utilization index for 1990 through 2011 for
the profiled Steel Mill and Steel Products segments. Capacity utilization followed a similar trend for both industry
segments. Capacity utilization in the Steel Products segment declined by 22 percent over the last two decades and
by 8 percent during the last decade. The Steel Mills segment saw a decline of less than 1 percent over the entire
period, and increased by 15 percent between 2000 and 2011. The most dramatic drops in capacity utilization took
place around the 2001 and the 2008 economic recessions; in fact, the 2009 drop in capacity utilization marked the
most drastic drop in capacity utilization in the last two decades. For the Steel Mills segment, capacity utilization
dropped by 31 percent in 2009 while for the Steel Products segment it fell by 34 percent. In 2010, capacity
utilization for both Steel Mills and Steel Products increased drastically and continued to rise in 2011.
F-14
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
Figure F-4: Capacity Utilization Rates (Fourth Quarter) for Profiled Steel Industry Segments3,13,0
a. Before 1997, the Department of Commerce compiled data in the SIC system; since 1997, these data have been compiled in the North American
Industry Classification System (NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997
Economic Census Bridge Between NAICS and SIC.
b. Prior to 2007, U.S. Census sampled every industry in a specific NAICS6. Beginning in 2007, U.S. Census only sampled certain industries within any
NAICS6, and therefore, the data collected before 2007 cannot be directly compared to the data collected in 2007 and beyond.
c. Capacity utilization rates for 2010 are for the fourth quarter, or annual average where fourth quarter is not available, and utilization rates for 2011 are
for the third quarter.
Source: U.S. DOC, 1989-2010 SPC
1
1
1
1

'n©

o
o
o
o
o
'nC
'O
o

W
4*.

©N
-4
oe
o
©

4-.

©
—k— Steel Mills (NAICS 3311)
—Steel Products (NAICS 3312)
F.4 Structure and Competitiveness
The Steel Mill segment is comprised of two different kinds of facilities, integrated mills and minimills. The
integrated steelmaking process requires expensive plant and equipment purchases that will support production
capacities ranging from two million to four million tons per year. Until the early 1960s, integrated steelmaking
was the dominant method of U.S. steel manufacturing. Since then, the integrated steel business underwent
dramatic downsizing due to competition from minimills and imports. These trends reduced the number of
integrated steelmakers (S&P, 2001b). Minimills vary in size, from capacities of 150,000 tons at small facilities to
larger facilities with annual capacities of between 400,000 tons and two million tons. Integrated companies have
significant capital costs of approximately $2,000 per ton of capacity compared with minimills" $500 per ton.
Because minimills do not require as much investment in capital equipment as integrated steelmakers, minimills
have been able to lower prices during periods of weak demand, driving integrated companies out of many of the
commodity steel markets (S&P, 2001b). The advent of minimills, with their lower initial capital investments, has
made it easier for new producers to enter the market.
F.4.1 Firm Size
For both the Steel Mills and Steel Products segments, the Small Business Administration defines a small firm as
having 1,000 or fewer employees (750 or fewer employees for NAICS 331112). The size categories reported in
the Statistics of U.S. Businesses (SUSB) do not correspond with the SBA size classifications, therefore preventing
May 2014
F-15
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
precise use of the SBA size threshold in conjunction with SUSB data. Table F-8 below shows the distribution of
firms, facilities, and receipts by the employment size of the parent firm.
The SUSB data presented in Table F-8 show that in 2009, 388 of 454 firms in the Steel Mills segment had less
than 500 employees. Therefore, at least 85 percent of firms in this segment were classified as small. These small
firms owned 400 facilities, or 68 percent of all facilities in the segment. Of the 645 firms with facilities that
manufacture Steel Products, 480, or 74 percent, employ fewer than 500 employees, and are therefore considered
small businesses. Small firms own 74 percent of facilities in the industry.
Table F-8: Number of Firms and Facilities by Employment Size Category in the
Profiled Steel Industry Segments, 2009

Employment Size
Steel Mills
Steel Products
Category
Number of Firms
Number of Facilities
Number of Firms
Number of Facilities
0-19
255
255
223
223
20-99
71
73
142
142
100-499
62
72
I 15
I 15
500+
66
188
165
165
Total
454
588
645
645
Source: U.S.DOC, 2009 SUSB
F.4.2 Concentration Ratios
Concentration is the degree to which industry output is concentrated in a few large firms. Concentration is
closely related to entry barriers with more concentrated industries generally having higher barriers.
The four-firm concentration ratio (CR4) and the Herfindahl-Hirschman Index (HHI) are common measures of
industry concentration. The CR4 indicates the market share of the four largest firms. For example, a CR4 of 72
percent means that the four largest firms in the industry account for 72 percent of the industry's total value of
shipments. The higher the concentration ratio, the less competition there is in the industry, other things being
equal.24" An industry with a CR4 of more than 50 percent is generally considered concentrated. The HHI indicates
concentration based on the largest 50 firms in the industry. It is equal to the sum of the squares of the market
shares for the largest 50 firms in the industry. For example, if an industry consists of only three firms with market
shares of 60, 30, and 10 percent, respectively, the HHI of this industry would be equal to 4,600 (602 + 302 + 102).
The higher the index, the fewer the number of firms supplying the industry and the more concentrated the
industry. Based on the U.S. Department of Justice's guidelines for evaluating mergers, markets in which the HHI
is under 1000 are considered unconcentrated, markets in which the HHI is between 1,000 and 1,800 are
considered to be moderately concentrated, and those in which the HHI is in excess of 1,800 are considered to be
concentrated.
Table F-9 presents concentration ratios for the profiled segments. The Steel Mills segment is comprised of
NAICS 331111 and 331112. The HHI for NAICS 331111 was 786 in 2007. The HHI for NAICS 331112 is not
reported in 2007, but was 2,196 in 2002. In 2007, Steel Products, comprised of NAICS 331222, 331221, and
331210, had HHIs of 297, 402, and 436, respectively. Consequently, the Steel Products segment is considered
competitive, based on standard measures of concentration. Because the Steel Mills segment is mostly comprised
of firms in the NAICS 331111 industry sector, this segment is also mostly competitive. For the Steel Products
segment, the CR4 and the HHI for all relevant NAICS codes are below the benchmarks of 50 percent and 1,000,
respectively. The relatively low concentration values suggest low overall ability of the industry to pass through
240 Note that the measured concentration ratio and the HHF are very sensitive to how the industry is defined. An industry with a high
concentration in domestic production may nonetheless be subject to significant competitive pressures if it competes with foreign
producers or if it competes with products produced by other industries (e.g., plastics vs. aluminum in beverage containers).
Concentration ratios based on share of production are therefore only one indicator of the extent of competition in an industry.
F-16
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
compliance costs as price increases to customers. However, in the Steel Mills segment, only NAICS code 331111
is below the HHI benchmark and neither segment is below the CR4 benchmark of 50 percent.
Table F-9: Selected Ratios for the Profiled Steel Industry Segments
SIC (S) or
NAICS (N) Code
Year
Total Number
of Firms
Concentration Ratios
4 Firm (CR4)
8 Firm (CR8)
20 Firm
(CR20)
50 Firm
(CR50)
Herflndahl-
Hirschman Index
Steel Mills
S 3312a
1987
271
44%
63%
81%
94%
607
1992
135
37%
58%
81%
96%
551
N331111
1997
191
33%
53%
75%
94%
445
2002
285
44%
59%
78%
93%
657
2007
235
52%
67%
84%
95%
786
S 3313
1987
25
55%
78%
99%
100%
1,208
1992
31
56%
77%
98%
100%
1,103
N331112
1997
19
61%
82%
100%
100%
1,123
2002
19
75%
92%
100%
100%
2,196
2007
20
56%
83%
100%
NA
NA
Steel Products
S 3315
1987
274
21%
34%
54%
78%
212
1992
271
19%
32%
54%
80%
201
N331222
1997
199
21%
36%
56%
80%
223
2002
270
30%
42%
61%
85%
326
2007
237
25%
42%
62%
85%
297
S 3316
1987
156
45%
62%
82%
95%
654
1992
158
43%
60%
81%
96%
604
N331221
1997
153
44%
60%
81%
96%
631
2002
121
34%
51%
73%
93%
491
2007
120
31%
49%
71%
92%
402
S 3317
1987
155
23%
34%
58%
85%
242
1992
166
19%
31%
53%
80%
194
N331210
1997
166
20%
30%
52%
82%
200
2002
133
26%
39%
61%
86%
279
2007
134
34%
49%
70%
91%
436
a. SIC code represents largest percentage of facilities and value of shipments within this NAICS based on the 1997 Bridge Between SIC and NAICS
Source: U.S. DOC, 1987, 1992, 1997, 2002, and 2007EC
F.4.3 Foreign Trade
This profile uses two measures of foreign competition: export dependence and import penetration.
Import penetration measures the extent to which domestic firms are exposed to foreign competition in domestic
markets. Import penetration is calculated as total imports divided by total value of domestic consumption in that
industry: where domestic consumption equals domestic production plus imports minus exports. Theory suggests
that higher import penetration levels will reduce market power and pricing discretion because foreign competition
limits domestic firms" ability to exercise such power. Firms belonging to segments in which imports account for a
relatively large share of domestic sales would therefore be at a relative disadvantage in their ability to pass-
through costs because foreign producers would not incur costs as a result of the final rule. The estimated import
penetration ratio for the entire U.S. manufacturing sector (NAICS 31-33) for 2010 is 28 percent. For
characterizing the ability of industries to absorb compliance cost burdens, EPA judges that industries with import
ratios close to or above 28 percent would more likely face stiff competition from foreign firms and thus be less
likely to succeed in passing compliance costs through to customers.
Export dependence, calculated as exports divided by value of shipments, measures the share of a segment's sales
that is presumed subject to strong foreign competition in export markets. The Final Existing Facilities regulation
would not increase the production costs of foreign producers with whom domestic firms must compete in export
markets. As a result, firms in industries that rely to a greater extent on export sales would have less latitude in
increasing prices to recover cost increases resulting from regulation-induced increases in production costs. The
May 2014
F-17
-------
Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
estimated export dependence ratio for the entire U.S. manufacturing sector for 2010 is 22 percent. For
characterizing the ability of industries to absorb compliance cost burdens, EPA judges that industries with export
ratios close to or above 22 percent are at a relatively greater disadvantage in potentially recovering compliance
costs through price increases since export sales are presumed subject to substantial competition from foreign
producers.
The global market for steel continues to be extremely competitive. From 1945 until 1960, the U.S. Steel Industry
enjoyed a period of prosperity and was a net exporter until 1959. However, by the early 1960s, foreign steel
industries had thoroughly recovered from World War II and had begun construction of new facilities that were
more advanced and efficient than the U.S. integrated steel mills. Foreign producers also enjoyed lower labor
costs, allowing them to take substantial market share from U.S. producers. This increased competition from
foreign producers, combined with decreased consumption in some key end use markets, served as a catalyst for
the restructuring and downsizing of the U.S. Steel Industry. The industry emerged from this restructuring
considerably smaller, more technologically advanced and internationally competitive (S&P, 2001b). Global steel
trade fell during the economic recession of 2008, trade imbalances narrowed, and governments responded with an
increase in trade policy measures to support the Steel Industry such as tariff increases, non-tariff barriers in
emerging Asia, export-facilitating measures, and trade remedy measures (OECD, 2009).
Table F-10 presents trade statistics for the profiled Steel Industry segments from 1990 to 2010. As shown in the
table, export dependence experienced slight fluctuations throughout the period, as did import penetration. Both
export dependence and import penetration rose by 8 percentage points between 1990 and 2010. Historically, the
U.S. Steel Industry has exported a relatively small share of shipments compared to the steel industries of other
developed nations (McGraw-Hill, 2000). U.S. steel exports rose in 1995 to the highest level since 1941, and
dropped slightly until 2003. From 2003 to 2010, the value of exports rose steadily, except for slight declines in
2009. Import penetration rose to 19 percent in 1994, 1996, and 2000 and reached another peak of 27 percent in
2008, after hovering around 15 percent in the early 1990s. This increase in imports reflected excess steel capacity
worldwide and the competitiveness of foreign steel producers, as described previously. Canada received the
largest amount of U.S. exported steel in 2007, followed by Mexico. Brazil, China, the EU, Germany, Japan, the
Republic of Korea, Mexico, Russia, and Ukraine were major sources of steel mill product imports (USGS, 2008f).
The Steel Industry's import penetration ratio in 2010 was 23 percent (compared to the 28 percent penetration for
the entire U.S. manufacturing industry), implying that domestic steel producers likely do not face highly
significant competition from foreign firms in setting prices on the domestic market. The Steel Industry's export
dependence ratio in 2010 was 13 percent (compared to the 22 percent export dependence for the entire U.S.
manufacturing industry), suggesting that this industry's overall cost pass-through potential is not significantly
affected by its foreign market sales.
The combination of moderate import penetration and relatively low export dependence suggest that international
trade considerations are not a strong factor in determining the cost pass-through potential of firms facing
compliance requirements under the final rule. However, potential changes in tariffs and other international trade
policies that were implemented during the recent recession, as well as the global recession, itself, may have
altered the overall balance of international competitiveness factors affecting the U.S. Steel Industry.
F-18
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
Table F-10: Import Penetration and Export Dependence: Profiled Steel Mills and Steel Products Segments
($2011)a

Value of
Implied

Value of Imports
Value of Exports
Shipments
Domestic
Import
Export
Year
(millions)
(millions)
(millions)
Consumptionb
Penetration0
Dependence"1
1990
SI 6.500
$4,799
$96,993
$108,695
15%
5%
1991
$14,894
$6,005
$84,916
$93,804
16%
7%
1992
$14,744
$4,886
$86,095
$95,953
15%
6%
1993
$15,645
$4,474
$89,999
$101,170
15%
5%
1994
$21,789
$4,682
$98,723
$115,830
19%
5%
1995
$21,218
$6,978
$103,695
$117,935
18%
7%
1996
$22,022
$6,114
$101,269
$117,177
19%
6%
1997
$23,214
$7,195
$103,007
$119,026
20%
7%
1998
$27,585
$6,714
$100,494
$121,365
23%
7%
1999
$21,606
$6,104
$91,488
$106,990
20%
7%
2000
$24,693
$6,849
$90,038
$107,882
23%
8%
2001
$18,595
$6,387
$77,207
$89,415
21%
8%
2002
$19,302
$5,947
$77,682
$91,036
21%
8%
2003
$17,048
$7,011
$76,006
$86,042
20%
9%
2004
$34,606
$8,661
$110,833
$136,778
25%
8%
2005
$35,363
$11,179
$116,067
$140,251
25%
10%
2006
$43,707
$12,016
$124,001
$155,692
28%
10%
2007
$40,353
$13,963
$132,914
$159,304
25%
11%
2008
$52,430
$18,098
$159,164
$193,496
27%
11%
2009
$21,706
$11,468
$82,157
$92,395
23%
14%
2010
$31,161
$15,079
$118,089
$134,171
23%
13%
Total Percent Change
1990 - 2010
88.9%
214.2%
21.7%
23.4%
Total Percent Change
1990 - 2010
26.2%
120.2%
31.2%
24.4%
Average Annual Growth
Rate
3.2%
5.9%
1.0%
1.1%
a. Before 1997, data were compiled in the SIC system; since 1998, these data have been compiled in the North American Industry Classification System
(NAICS). For this analysis, EPA converted the NAICS classification data to the SIC code classifications using the 1997 Economic Census Bridge Between
NA1CS and SIC.

b Calculated by EPA as shipments + imports - exports.

c. Calculated by EPA as imports divided by implied domestic consumption.

d. Calculated by EPA as exports divided by shipments.

Source: U.S. ITC, 1989-2010

F.5 Financial Condition and Performance
The financial performance and condition of the U.S. Steel Industry are important determinants of its ability to
absorb the costs of regulatory compliance without material, adverse economic/financial impact. To provide
insight into the industry's financial performance and condition, EPA reviewed two key measures of financial
performance over the period 1988 to 2012: net profit margin and return on total capital. EPA calculated these
using data from the Quarterly Financial Report (QFR) (see Appendix L: Adjusting Baseline Facility Cash Flow).
Financial performance in the most recent financial reporting period (2012) is obviously not a perfect indicator of
conditions at the time of regulatory compliance. However, examining the trend, and deviation from the trend,
through the most recent reporting period gives insight into where the industry may be, in terms of financial
performance and condition, at the time of compliance. In addition, the volatility of performance against the trend,
in itself, provides a measure of the potential risk faced by the industry in a future period in which compliance
requirements are faced: all else equal, the more volatile the historical performance, the more likely the industry
may be in a period of relatively weak financial conditions at the time of compliance.
Net profit margin is calculated as after-tax income before nonrecurring gains and losses as a percentage of sales
or revenue, and measures profitability, as reflected in the conventional accounting concept of net income. Over
time, the firms in an industry, and the industry collectively, must generate a sufficient positive profit margin if the
May 2014
F-19
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
industry is to remain economically viable and attract capital. Year-to-year fluctuations in profit margin stem from
several factors, including: variations in aggregate economic conditions (including international and U.S.
conditions), variations in industry-specific market conditions (e.g., short-term capacity expansion resulting in
overcapacity), or changes in the pricing and availability of inputs to the industry's production processes (e.g., the
cost of energy to the steel production process). The extent to which these fluctuations affect an industry's
profitability, in turn, depends heavily on the fixed vs. variable cost structure of the industry's operations. In a
capital intensive industry such as the Steel Industry, the relatively high fixed capital costs as well as other fixed
overhead outlays, can cause even small fluctuations in output or prices to have a large positive or negative affect
on profit margin.
Return on total capital is calculated as annual pre-tax income divided by the sum of current portion of long-term
debt due in 1 year or less, long-term debt due in more than one year, all other noncurrent liabilities and total
stockholders' equity (total capital). This concept measures the total productivity of the capital deployed by a firm
or industry, regardless of the financial source of the capital (i.e., equity, debt, or liability element). As such, the
return on total capital provides insight into the profitability of a business' assets independent of financial structure
and is thus a "purer" indicator of asset profitability than return on equity. In the same way as described for net
profit margin, the firms in an industry, and the industry collectively, must generate over time a sufficient return on
capital if the industry is to remain economically viable and attract capital. The factors causing short-term variation
in net profit margin will also be the primary sources of short-term variation in return on total capital.
Figure F-5, following page, presents trends in net profit margins and return on total capital for the Steel Industry
between 1988 and 2012. The graph shows considerable volatility in the trend over this analysis period. After
registering improvement in financial performance in the first half of the 1990s, Steel Industry financial
performance declined markedly between 1995 and 2002/2003, due first to increasing imports resulting from Asian
financial crisis with the associated decline in Asian demand for steel and currency devaluations, and later, general
economic weakness. Financial performance improved in 2002 slightly when the U.S. Steel Industry received
temporary relief with tariffs ranging up to 30 percent on certain steel imports. However, in 2003 the integrated
Steel Industry again saw poor operating results, as high raw material costs outweighed increased sales and higher
volumes. In 2004, the Steel Industry's financial performance improved strongly, with returns on total capital and
net profit margins peaking in 2006. In 2007, at the beginning of the recent economic recession, financial
performance of the Steel Industry began to deteriorate. That deterioration accelerated into 2009, followed by an
increase in both net profit margin and return on total capital in 2010. In 2011, net profit margin and return on total
capital increased steeply and continued to increase in 2012, bringing values for both indicators towards long-term
averages.
F-20
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
Figure F-5: Net Profit Margin and Return on Total Capital for the Iron and Steel Industry
23%
18%
13%
1
1
1
1
1
1
1

tw
tw

00
o
©

4-.

00
<0
©

-Net Profit Margin —*—Return on Total Capital
Source: U.S. DOC, 1988-2012 OFR
F.6 Facilities Operating Cooling Water Intake Structures
Section 316(b) of the Clean Water Act applies to point source facilities that use or propose to use a cooling water
intake structure that withdraws cooling water directly from a surface waterbody of the United States. In 1982, the
Primary Metals industries as a whole (including Nonferrous and Steel producers) withdrew 1,312 billion gallons
of cooling water, accounting for approximately 1.7 percent of total industrial cooling water intake in the United
States.241 The industry ranked third in industrial cooling water use, behind the electric power generation industry,
and the chemical industry (U.S. DOC, 1982).
This section provides information for facilities in the profiled steel segments estimated to be subject to regulation
under the final rule and other options EPA considered. Existing facilities that meet the following conditions are
potentially subject to regulation:
> Have a National Pollutant Discharge Elimination System (NPDES) permit or are required to obtain one;
> Use or propose to use one or more cooling water intake structures to withdraw water from waters of the
United States;
> Use at least twenty-five (25) percent of the water withdrawn exclusively for contact or non-contact
cooling purposes; and
> Meet the specific applicability coverage criteria for the final rule and other options EPA considered in
terms of design intake flow (i.e., two mgd).
241 Data on cooling water use are from the 1982 Census of Manufactures. 1982 was the last year in which the Census of Manufactures
reported cooling water use.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
EPA initially identified the set of facilities that were estimated to be potentially subject to the 316(b) Existing
Facilities Regulation based on a minimum applicability threshold of two mgd; this section focuses on these
facilities for the Steel Industry.242
F.6.1 Waterbody and Cooling Water Intake System Type
Minimills use electric-arc-furnaces (EAF) to make steel from ferrous scrap. The electric-arc-furnace is extensively
cooled by water, which is in turn recycled through cooling towers (U.S. EPA, 1995). This is important to note
since most new steel facilities are minimills.
Table F-ll shows the distribution of regulated facilities in the profiled Steel Industry by type of waterbody and
cooling water intake system. As reported in the table, most regulated facilities employ a combination of a once-
through and recirculating system. In addition, most regulated facilities in the Steel Industry draw water from a
freshwater stream or river.
Table F-11: Number of Facilities Estimated Subject to the 316(b) Existing Facilities Regulation by

l/Vaterbody Type and Cooling Water Intake System for the Profiled Steel Industry Segments

Cooling Water Intake Systems
Waterbody Type
Recirculating
Combination
Once-Through
Other
Total

Number
% of Total
Number
% of Total
Number
% of Total
Number
% of Total
Lake/Reservoir
0
0%
0
0%
1
5%
0
0%
1
Freshwater River/ Stream
13
100%
18
67%
20
89%
7
100%
57
Great Lake
0
0%
9
33%
1
5%
0
0%
10
Total3
13
18%
26
39%
21
32%
7
11%
68
a. Individual numbers may not add up to total due to independent rounding.

Source: U.S. EPA, 2000; U.S. EPA analysis for this report

F.6.2 Facility Size
Figure F-6 shows the number of regulated facilities by employment size category. The regulated facilities in the
Steel Mills and Steel Products segments are on average relatively large.
Figure F-6: Number of Facilities Estimated Subject to the 316(b) Existing Facilities Regulation by Employment Size for
Profiled Steel Industry Segments
35
30
25
20
15
10
5
0
Source: U.S. EPA, 2000; U.S. EPA analysis for this report
k
/
11

l f~(\
1 ¦ D o

/
Less than 100-249 250-499 500-999 1000 and
100 greater
242 EPA applied sample weights to the sampled facilities to account for non-sampled facilities and facilities that did not respond to the
survey. For more information on EPA's 2000 Section 316(b) Industry Survey, please refer to the Information Collection Request (U.S.
EPA, 2000).
F-22
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix F: Steel Industry Profile
F.6.3 Firm Size
EPA used the Small Business Administration (SBA) small entity size standards to determine the number of
section 316(b) profiled Steel Industry facilities owned by small firms. Firms in the Steel Mills and Steel Products
segments are defined as small if they have 1000 or fewer employees (except for facilities with NAICS code
331112 which are defined as small if they have 750 or fewer employees). EPA estimates that eight small entity-
owned facilities and 60 large entity-owned facilities in the Steel Industry will be subject to the final regulation. In
addition, the ownership size of three facilities was unable to be classified due to insufficient survey data.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix G: Other Industries Profile
Appendix G Profile of Facilities in Other Industries
The preceding profile appendices focus on the six Primary Manufacturing Industries - Paper and Allied Products,
Chemicals and Allied Products, Petroleum Refining, Steel, Aluminum, and Food and Kindred Products -
identified, after electric power generators, as using the largest amount of cooling water in their operations and
whose facilities are most likely, after electric power generators, to be subject to the final rule. However, facilities
in other industries use cooling water and will therefore be subject to the final rule if they meet the regulation's
specifications. This section of the profile provides information on a sample of facilities in these Other Industries.
EPA targeted its Detailed Industry Questionnaire at the electric power industry and manufacturing industries that
use large amounts of cooling water. However, the Agency received 13 questionnaire responses from facilities
with business operations in industries other than these major cooling water-intensive industries. EPA originally
judged these facilities to be non-utility Electric Generators; however, inspection of their responses indicated that
the facilities were better understood as cooling water-dependent facilities whose principal operations lie in
businesses other than Electric Generators or the Primary Manufacturing Industries. Unlike the sample facility
observations for the six Primary Manufacturing Industries, the sample of observations from Other Industries is not
based on a scientifically framed sample and the information from this sample of observations may not be reliably
extrapolated beyond these facilities. As a result, EPA's profile of information for the Other Industries facilities is
restricted to these 13 sample facilities and is not presented as national estimates.
All of the 13 Other Industries facilities withdraw at least two million gallons of water a day and meet other
regulated facility criteria, and thus would be subject to regulation under the final rule and other options EPA
considered for existing facilities. These facilities fall in a wide range of businesses, as defined by three-digit
NAICS industry group. Table G-l presents the number of responses received from facilities in the Other
Industries by industry group. The information summarized in the following sections focuses on these Other
Industries facilities, which EPA estimates will be subject to the final rule.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix G: Other Industries Profile
Table G-1: Facilities in Other Industries by 2-digit SIC code Estimated Subject to Regulation Under the
Final Rule and Other Options Considered
No. of
Facilities
NAICS
Code
SIC Description
Important Operations
1
111
Crop production
Establishments, such as farms, orchards, groves, greenhouses, and nurseries,
primarily engaged in growing crops, plants, vines, or trees and their seeds.
Including biological and physiological characteristics and economic
requirements, the length of growing season, degree of crop rotation, extent of
input specialization, labor requirements, and capital demands production
activities.
4
212
Mining (except oil and
gas)
Mining, mine site development, and beneficiating (i.e., preparing) metallic
minerals and nonmetallic minerals, including coal. Also includes ore extraction,
quarrying, and beneficiating (e.g., crushing, screening, washing, sizing,
concentrating, and flotation), customarily done at the mine site.
1
313
Textile mills
Transforming a basic fiber (natural or synthetic) into a product, such as yarn or
fabric, that is further manufactured into usable items, such as apparel, sheets
towels, and textile bags for individual or industrial consumption.
2
321
Wood product mfg.
Wood products, such as lumber, plywood, veneers, wood containers, wood
flooring, wood trusses, manufactured homes (i.e., mobile home), and
prefabricated wood buildings. Includes sawing, planing, shaping, laminating, and
assembling of wood products starting from logs that are cut into bolts, or lumber
that then may be further cut, or shaped by lathes or other shaping tools.
1
331
Primary metal mfg
Making (i.e., the primary production) nonferrous metals by smelting ore and/or
the primary refining of nonferrous metals by electrolytic methods or other
processes (except copper and aluminum).
2
332
Fabricated metal product
mfg
Produce intermediate or end products from metal. Does not include computers,
machinery, electronics, metal furniture, treat metals and other products fabricated
elsewhere.
1
336
Transportation
equipment mfg.
Equipment for transporting people and goods for each mode of transport - road,
rail, air and water. Land use motor vehicle equipment not designed for highway
operation (e.g., agricultural equipment, construction equipment, and materials
handling equipment).
1
339
Miscellaneous mfg.
A wide range of products that cannot readily be classified in specific NAICS
subsectors in manufacturing. Processes used by these establishments vary
significantly, both among and within industries.
Source: Executive Office of the President, 1987; U.S. EPA, 2000; U.S. EPA analysis for this report
G.1 Facilities Operating Cooling Water Intake Structures
Section 316(b) of the Clean Water Act applies to point source facilities that use or propose to use a cooling water
intake structure and that withdraw cooling water directly from a surface waterbody of the United States. This
section provides information for facilities in the Other Industries subject to the final rule and other options
Existing facilities that meet the following conditions are potentially subject to regulation:
> Have a National Pollutant Discharge Elimination System (NPDES) permit or are required to obtain one;
> Use or propose to use one or more cooling water intake structures to withdraw water from waters of the
United States;
> Use at least twenty-five (25) percent of the water withdrawn exclusively for contact or non-contact
cooling purposes; and
> Meet the specific applicability coverage criteria for the final rule and other options EPA considered in
terms of design intake flow (i.e., two mgd).
The final rule and other options EPA considered also cover substantial additions or modifications to operations
undertaken at such facilities.
G-2
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix G: Other Industries Profile
G.1.1 Waterbody and Cooling System Types
Table G-2 summarizes information on the Other Industries facilities by type of waterbody and cooling water
intake system.
Table G-2: Other Industries Facilities Estimated Subject to the 316(b) Existing Facilities Regulation by
l/Vaterbody and Cooling Water Intake System Type

Waterbody Type
Recirculating
Once-Through
Other
Total
Number
% of Total
Number
% of Total
Number
% of Total
Estuary/ Tidal River
I
33%
I
1 1%
0
0%
2
Freshwater Stream/River
2
67%
4
45%
1
100%
7
Great Lake
0
0%
2
22%
0
0%
2
Lake/Reservoir
0
0%
I
1 1%
0
0%
1
Ocean
0
0%
1
11%
0
0%
1
Total3
3
23%
9
69%
1
8%
13
a. Individual numbers may not sum to total due to independent rounding.

Source: U.S. EPA, 2000; U.S. EPA analysis for this report

G.1.2 Facility Size
Figure G-l shows the employment size category for the Other Industries facilities that EPA expects to be subject
to the final rule and other options EPA considered.
Figure G-1: Other Industries Facilities Estimated Subject to the Existing Facilities Regulation by Employment Size
Less than 100-249 250-499 500-999 Greater than
100 1000
Source: U.S. EPA, 2000; U.S. EPA analysis for this report
G.1.3 Entity Size
EPA used the Small Business Administration (SBA) small entity-size standards to determine whether small or
large entities own the Other Industries facilities. The SBA entity-size criteria define firms as small based on either
revenue or number of employees, depending on their NAICS code. EPA estimates that five small entity-owned
facilities and eight large entity-owned facilities in the Other Industries facility group will be subject to the 316(b)
Existing Facilities regulation.243
243 EPA did not have sufficient survey data to determine the size of the entity owning one facility. EPA assumed this facility to be a small
entity-owned facility in order to not understate the effect of this rule on small entities.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
Appendix H Use of Sample Weights in the Final Rule Analyses
EPA used facility-level sample weights to estimate costs and impacts on facilities subject to the final rule
(regulated facilities, or, Electric Generators and Manufacturers). For the 316(b) Phase II and Phase III regulations,
EPA developed and used facility-level survey sample weights (original survey weights) for Electric Generators
and Manufacturers based on responses to the 2000 Detailed Industry Questionnaire (DO), the 2000 Industry Short
Technical Questionnaire (STO), and the 1999 Industry Screener Questionnaire (ISO) (316(b) survey), and used
these weights in the earlier analyses.244 For Manufacturers, EPA continued to use these original survey weights
for the analyses of the proposed and final rules. However, for Electric Generators, because of changes to cost and
economic impact methodology, the Agency had to develop a different set of weights (new facility-level, weights).
Specifically, while for some Electric Generators the EPA was able to use the original survey weights, for others,
the Agency developed new weights to account for different approaches used to analyze facilities that received the
DQ and the STQ {new DO weights). Thus, the new facility-level weights used for Electric Generators are a
combination of the original survey weights and the new DO weights. The different facility-level weighting
approaches that are used to analyze Electric Generators and Manufacturers also provided the basis for
development and use of entity-level weights.
For Electric Generators, EPA knows with relative certainty the identity and location of all facilities that will be
within the scope of the final rule based on the survey information described above. However, the level of
available information varies depending on whether Electric Generators responded to the STQ or the DQ. While
EPA had sufficient information to estimate likely compliance response and technology costs for Electric
Generators that responded to the DQ, the Agency lacked needed information for Electric Generators that
responded to the STQ. For this reason, EPA estimated compliance technology costs for Electric Generators that
responded to the DQ and used sample weights to extrapolate the costs and other information to the population of
all Electric Generators estimated to be within the scope of the final rule. For Manufacturers, the use of sample
weights is required because the cost and economic impact analyses are based on a sample of facilities that were
surveyed from the total population of facilities that could be within the scope of the regulation. EPA does not
know the identity or location of the total population of facilities that would be within the scope of the final rule,
but used the sample weights to estimate industry-level costs and impacts based on the sample of facilities that are
used in the regulatory> analysis,245
This appendix describes the development and use of sample weights in the cost and economic impact analyses
EPA conducted for the final rule. Section H.l discusses EPA's development and use of facility-level weights and
Section H.2 discusses EPA's development of entity-level weights for Electric Generators and Manufacturers.
Section H. 3 summarizes the various weighting concepts used in the current analyses and in the relevant chapters
of this report. For Electric Generators, EPA developed two sets of facility and entity sample weights to conduct
the cost and economic impact analyses for the final rule. The two sets of weights reflect the alternative
assumptions regarding facilities known to have cooling water system impoundments and whether these facilities
will qualify as baseline CCRS, and thus avoid installation of addition of additional technology to comply with the
final rule: (1) assuming that all facilities with a cooling water system impoundment qualify as CCRS in the
baseline and will meet impingement mortality performance standards under the final rule and other options
considered without installing additional compliance technology,246 and (2) assuming that no facilities with a
244 For more information on the 316(b) survey, refer to the Information Collection Request (U.S. EPA, 2000).
245 For details on development of compliance costs for Electric Generators and Manufacturers, see Technical Development Document
(TDD).
240 For Proposal Option 2, EPA also assumed that these facilities will meet entrainment technology requirements, as applicable.
May 2014
H-1
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
cooling water system impoundment qualify as CCRS in the baseline and may need to install additional technology
to meet the impingement mortality performance standard under the final rule and other options considered.247
H.1 Facility-Level Weights
H.1.1 Electric Generators
For the facility-level analysis EPA conducted for Electric Generators, EPA used a combination of weights from
the earlier 316(b) Phase II and Phase III analyses and sample weights that the Agency developed specifically to
support the final rule analyses.
Original survey weights
As described in the regulatory-analysis documents for the earlier 316(b) regulations, EPA collected technical and
economic information from 656 electric power facilities expected to be subject to those regulations through STQ
(372 facilities) and DQ (284 facilities) (surveyed facilities). Based on these survey responses, EPA developed
facility sample weights to account for 15 additional facilities that did not respond to the DQ or the STQ (survey
non-respondents). In general, these original survey weights are numerically close to one, as EPA had either DQ or
STQ information for 656 facilities out of the 671 facilities presumed to be subject to the earlier 316(b)
regulations.
For the final rule analyses, EPA excluded 73 facilities (76 on a weighted basis) that have retired all steam
operations since the 316(b) survey was conducted and 51 facilities (51 on a weighted basis) that EPA expects will
retire their steam capacity by 2021, according to the 2011 EIA-860 database published by the Energy Information
Administration (EIA) of the U.S. Department of Energy (DOE) (baseline closures). For the 532 facilities
estimated to have steam operations (544 on a weighted basis), EPA continued to use the original survey weights
in all analyses that do not rely on compliance cost information for facilities, such as the industry profile (see
Chapter 2: Industry Profiles). EPA also used these original sample weights for DQ and STQ facilities, as listed in
Table H-l. While these facilities are within the scope of the final rule, they are not expected to incur additional
technology costs to meet requirements of the final rule; therefore, EPA did not have to extrapolate compliance
costs for these facilities and was able to use the original survey weights for these DQ and STQ facilities.248'249 As
described below, however, the Agency had to develop new sample weights for facilities expected to incur
compliance technology costs.
247 For Proposal Option 2, EPA also assumed that these facilities will not meet entrainment technology requirements, as applicable.
248 Hie States of California and New York already require these facilities to comply with standards at least as stringent as the final rule;
thus, EPA does not expect these facilities to install any compliance technology under any of the regulatory options considered in this
economic analysis. For the cost and economic impact analyses, these facilities are treated as if they already have closed-cycle
recirculating systems in their baseline.
249 Although EPA does not expect these facilities to incur compliance technology costs, they are within the scope of the final rule and will
be subject to various administrative requirements for permitting, monitoring, and compliance reporting. To assess what administrative
activities regulated facilities would have to undertake and to develop costs associated with these activities, EPA did not need facility-
level technical information as detailed as that required to develop facility-specific compliance technology costs. Therefore, the Agency
was able to determine facility-specific administrative requirements and to develop costs associated with these requirements for both
DQ and STQ facilities and did not need to develop new sample weights to extrapolate costs and other information from DQ facilities
to the STQ facilities.
H-2
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
Table H-1: Regulated DQ and STQ Electric Generators Not Expected to Incur Compliance Technology
Costs Under Either the Final Rule or Other Options Considered
Facility Category
Assuming All Facilities with
Impoundments Qualify as
Baseline CCRS
Assuming No Facilities with
Impoundments Qualify as
Baseline CCRS
Unweighted
Weighted3
Unweighted
Weighted3
Facilities that are known to have a closed-cycle recirculating
system in their baseline
106
109
106
109
Facilities with a cooling water system impoundment that may
as baseline CCRS and may meet the final rule's BTA
performance standards without additional technologyb
40
40
0
0
California facilities that use coastal and estuarine waters for
their cooling water system
14
16
14
16
New York facilities with design intake flow (DIF) of at least
20 million gallons per day (mgd)
26
28
26
28
Total
186
193
146
153
a. Facility counts were generated using the original survey weights.
b. If these facilities do not qualify as baseline CCRS, they may need to install additional technology to meet the performance requirements under the
final rule and other options considered, and would fall in a different facility category for the cost and economic impact analyses. Consequently, for
these facilities, EPA had to use different sample weight sets for conducting cost and economic impact analyses under two assumptions: (1) all facilities
with a cooling water system impoundment qualify as baseline CCRS and (2) no facilities with a cooling water system impoundment qualify as baseline
CCRS.
Source: U.S. EPA analysis for this report
New facility-level weights
As discussed above, the original survey weights were designed to account for 15 survey non-respondents because
in the previous 316(b) rule analyses, EPA developed costs for both DQ and STQ facilities that responded to the
316(b) survey. To assess cost and economic impacts for the final rule, EPA developed compliance technology
costs only for DQ facilities; upon review of the 316(b) survey responses, the Agency concluded that information
reported for STQ facilities was insufficient to estimate compliance technology costs. As a result, to extrapolate
compliance technology costs from the DQ facilities to the STQ facilities that may need to undertake a specific
compliance technology response considered for this rule, EPA had to develop a new set of sample weights - new
DQ weights. Specifically, EPA used the new DQ weights to extrapolate compliance technology costs and other
information (e.g., facility counts, generating capacity, DIF) from DQ facilities to all DQ and STQ facilities
incurring technology costs, including 316(b) survey non-respondents represented by these DQ and STQ
facilities:250'251
> Assuming facilities with cooling water system impoundments qualify as baseline CCRS. EPA extrapolated
information from 154 DQ facilities to 197 DQ and STQ facilities. As discussed above, when developing
the new DQ weights, EPA set aside 193 DQ and STQ facilities not installing any compliance technology
under either the final rule or the other options considered (Table H-l). For these 193 DQ and STQ
facilities the Agency used the original survey weights.
> Assuming facilities with cooling water system impoundments do not qualify as baseline CCRS. EPA
extrapolated information from 167 DQ facilities to 224 DQ and STQ facilities. Again, EPA set aside 153
DQ and STQ facilities without compliance technology requirements under either the final rule or the
other options considered (Table H-l)', for these facilities the Agency used the original survey weights.
Throughout this document, EPA refers to Electric Generators for which compliance costs - technology and
administrative - were specifically estimated as the "explicitly analyzed" facilities. The facilities for which
compliance costs were not specifically estimated are referred to as the "implicitly analyzed" facilities. Table H-2
provides a summary of explicitly and implicitly analyzed Electric Generators by facility group. For the cost and
250 For details on development of compliance technology costs, see the TDD.
251 Facility counts may not sum to reported totals because of sample weighting, which may involve non-integer values.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
economic impact analyses conducted in support of the final rule, EPA accounted for the implicitly analyzed
facilities by applying the appropriate facility-level weights to the findings - e.g., total compliance costs,
generating capacity, DIF, counts of impact finding - for the explicitly analyzed facilities.
Table H-2: Explicitly and Implicitly Analyzed Electric Generators

Assuming All
Facilities with
Impoundments
Qualify as Baseline
CCRS
Assuming No
Facilities with
Impoundments
Qualify as Baseline
CCRS
Explicitly Analyzed Facilities
All DQ facilities
227
227
STQ facilities with a closed-cycle recirculating system in the
baseline
60
60
STQ facilities with a cooling water system impoundment that
may qualify as CCRS in the baseline3
27
0
Coastal and estuarine California STQ facilities
11
11
New York STQ facilities with DIF of at least 20 mgd
15
15
Implicitly Analyzed Facilities
All other non-retired STQ facilities3
192
219
Facilities that did not respond to the 316(b) survey
12
12
Total
544
544
a. If these facilities do not qualify as baseline CCRS, they may need to install additional technology to meet the
performance standards required under the final rule and other options considered. Consequently, for this group of
facilities, EPA developed compliance costs and accounted explicitly for DQ facilities, but accounted only implicitly for
the STQ facilities using the new DQ weights. Therefore, in the cost and economic impacts analyses assuming these
facilities do not qualify as baseline CCRS, these 27 STQ facilities are included in the group of "All other non-retired STQ
facilities". In the alternate case, assuming these facilities do qualify as baseline CCRS, none of these facilities - whether
DQ and STQ facilities - will have to install compliance technology; as a result, EPA did not develop compliance
technology costs for these facilities and was able to account for both DQ and STQ facilities on an explicit basis using
original survey weights.
Source: U.S. EPA analysis for this report
Development of new DQ weights
In developing the new DQ weights for the current rule analyses, EPA considered several approaches in attempting
to account simultaneously for:
Four Classification Variables
Three Control Variables
> Generating capacity
> Number of facilities
> Design intake capacity
And
> North American Electric Reliability Corporation
(NERC) region
> Capacity/fuel type (coal steam, combined cycle,
etc.)
> Ownership (investor-owned, nonutility, etc.)
> Baseline cooling water intake structure
specifications and related compliance
requirements (Technology Group)
EPA was unable to develop a single set of weights that accurately accounted for all control variables according to
each classification variable, and therefore chose to develop three sets of weights, one based on each of the three
control variables. Even with this approach, EPA was unable to develop weights that accurately accounted for
facilities in all four classification variables. EPA chose to focus on weights that represented the NERC-region
classification and compliance requirements, i.e., the more important classifications for understanding the
252 253
economic implications of this action, as accurately as possible. '
For more details of the approaches considered by EPA see memorandum dated June 18, 2008 (DCN 12-2505).
H-4 May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
To ensure proper representation of STQ facilities by DQ facilities in terms of compliance response considered
under the final rule and other options considered (Compliance Requirements Groups), EPA grouped Electric
Generators into three Technology Groups (Table H-3). Because of the large number of factors determining
compliance response, EPA was unable to account for option-specific compliance response for all analyzed
options, while maintaining adequate representation of STQ facilities in each NERC region. Specifically, the
Agency did not account for compliance response under Proposal Option 4 and Proposal Option 2. Proposal
Option 4 requires only facilities with DIF of 50 mgd or greater to comply with impingement mortality standards,
while Proposal Option 2 requires all facilities to comply with impingement mortality standards but only facilities
whose DIF exceeds 125 mgd to meet entrainment control standards. To the extent that the final rule requires all
regulated facilities to meet the same set of standards - i.e., only impingement mortality- the outlined weights-
development framework accounts for option-specific compliance response.
For each control variable (i.e., number of facilities, total steam generating capacity, or total intake flow), EPA
developed a weight set that accounts only for that control variable in each NERC region and Technology
Group.254 As an example, using facility count-based weights accurately represents the number of facilities in each
NERC region and Technology Group, but may misrepresent the region's total capacity or intake flow. In contrast,
using capacity-based weights will accurately represent the total capacity in a given NERC region and compliance
group, but will not yield as accurate estimates of the number of facilities and total intake flow. Further, although
the underlying set of DQ facilities and the set of STQ facilities on which these weights were developed are the
same for each weight set, the weights for any DQ facility generally differ by weight set. Thus, as discussed in the
following section, cost estimates and other facility characteristics were weighted based on the concept
corresponding to the parameters underlying the cost or characteristic. Table H-4 presents unweighted and
weighted counts of regulated facilities by NERC region.
Table H-3: Technology Groups Used to Develop New DQ Weights
Technolo
gy Group
Compliance Requirements
Has Baseline Closed-
Cycle Recirculating
System or Located in
California or New York
Water Intake Velocity
Impingement Mortality
Entrainment
Mortality Controls
Yesa'b
NA
No Technology
No Technology
No
<=0.5 feet per second0
No Technology
CT Assigned
No
>0.5 feet per second
IM Assigned"1
CT Assigned
a. Because these facilities are assumed to be in compliance with the requirements of the final rule and other options
considered, EPA did not have to extrapolate compliance costs for these facilities. These facilities are explicitly analyzed
DQ and STQ facilities.
b. Under the assumption that all facilities with cooling water system impoundments qualify as baseline CCRS, EPA
included these facilities in the baseline CCRS category.
c. These facilities already meet the impingement mortality standards and are therefore not assigned impingement
mortality technology. Low water intake velocity, i.e., water intake velocity of equal to or less than 0.5 feet per second,
is not sufficient to meet entrainment control standards; therefore, if DIF at these facilities exceeds 125 MGD, they
would need to install cooling towers under Proposal Option 2.
d. Some facilities in this group already meet impingement mortality requirements and are therefore not assigned
impingement mortality technology.
Source: U.S. EPA analysis for this report
253 Accounting for NERC regions is particularly important for the electricity rate and household impact analyses (see Chapter 4:
Economic Impact Analysis - Electric Generators).
254 Because 14 regulated STQ facilities did not have an adequate DQ representation in their respective Compliance Requirements Groups
and NERC regions, EPA re-assigned these STQ facilities to the NERC regions with relatively more substantial DQ representation in
their Compliance Requirements Groups.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
Table H-4: Unweighted and Weighted Counts of Electric Generators by NERC Region3

Counts of Sampled Electric
Generators
Weighted Facility Counts Estimated Using0

Facility-Count
Based Weights

All Facilities with
No Facilities with
NERC
Region1'
DQ
STQ
All
Original
Survey
Weights
Impoundments
Qualify as Baseline
CCRS
Impoundments
Qualify as Baseline
CCRS
ASCC
0
1
1
1
0
0
FRCC
13
11
24
24
24
24
HICC
2
1
3
3
3
3
MRO
26
34
60
60
60
63
NPCC
25
29
54
59
58
58
RFC
59
79
138
140
135
136
SERC
59
75
134
136
145
141
SPP
14
26
40
40
36
37
TRE
17
24
41
41
45
46
WECC
12
25
37
39
37
36
U.S.
227
305
532
544
544
544
a. Counts exclude Electric Generators that have either retired all steam operations are expected to do so by 2021 according to the 2011 EIA-
860 database.

b. ASCC - Alaska Systems Coordinating Council; FRCC - Florida Reliability Coordinating Council; F1ICC - Flawaii Coordinating Council;
MRO - Midwest Reliability Organization; NPCC - Northeast Power Coordinating Council; RFC - ReliabilityFirst Corporation; SERC -
Southeastern Electric Reliability Council; SPP - Southwest Power Pool; TRE - Texas Reliability Entity, and WECC - Western Energy
Coordinating Council.
c. Slight misalignments of facility counts estimated using the original survey weights and facility-count based weights are present because re-
assigned 14 regulated STQ facilities did not have an adequate DQ representation in their respective Compliance Requirements Groups and
NERC regions to the NERC regions with relatively
more substantial DQ representation in their Compliance Requirements Groups.
Source: U.S. EPA analysis for this report

Use of new facility-level weights
EPA used different weight sets - facility-count based, capacity-based, or DIF-based - to estimate technology and
other compliance-related costs or other regulated facility characteristics according to the primary driver of a given
cost element or of a given facility characteristic. For example, facility's DIF is the primary driver of technology
capital cost. Accordingly, EPA used the DIF-based weights for extrapolating technology capital costs from the
DQ facility set to all DQ and STQ facilities that may need to undertake a specific compliance technology
response. For estimating facility counts and cost elements that are facility count-dependent (e.g., administrative
costs), EPA used the facility count-based weights.
For facilities for which EPA used the original survey weights (i.e., DQ and STQ facilities that are known to have
a closed-cycle recirculating system in place, including facilities with a cooling water system impoundment that
may qualify as CCRS in the baseline, California facilities that use coastal and estuarine waters for their cooling
water systems, and New York facilities with DIF of at least 20 mgd), the sample weights are the same regardless
of the weight set; they are the original survey weights.
Table H-5 provides information on what weight set was used for each compliance cost component.
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May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
Table H-5: Weights Applied to Each Cost Component
Weight Set
Cost Component
Capacity-based
Downtime impact costs
Energy penalty (auxiliary requirements and turbine backpressure)
DIF-based
Capital costs
O&M costs
Facility count-based
Initial permitting costs

Annually recurrnm administrative costs

Non-Anniiallv recurrnm administrative costs

State and l'ederal initial permitting costs

State and l'ederal annually recurnim costs

State and federal non-annually recurring administrative costs
Source: U.S. EPA analysis for this report
H.1.2 Manufacturers
EPA continued to use the original survey weights for the cost and economic impact analyses presented in this
document.255 EPA applied these weights to the Manufacturers that responded to the 316(b) survey to account for
non-sampled facilities and survey non-respondents. The methodology EPA used to develop these weights differs
by industry.
Facilities in the Primary Manufacturing Industries, except Food and Kindred Products
As discussed in the earlier 316(b) rule analyses, the initial set of Primary Manufacturing Industries - i.e., the set
that EPA expected to analyze at the time the 316(b) survey was conducted - did not include Food and Kindred
Product industry.256 The original survey weights used to analyze Manufacturers in this initial set of Primary
Manufacturing Industries consist of two parallel sets of weights. One set is used for all analyses except for the
facility-level economic impact analysis; EPA developed these weights based on the engineering information
obtained from the DQ and ISQ and refers to these sample weights as the "technical weights." EPA used the
second set of weights - "economic weights" - only for facility-level economic impact analysis; EPA developed
these weights based on the economic/financial information received in the DQ and ISQ.
EPA used the technical weights to estimate facility counts, total costs, and impacts on entities that own regulated
facilities. In developing these weights, EPA determined that survey responses for 11 facilities in the initial set of
Primary Manufacturing Industries lacked certain financial data needed for the facility-level impact analysis.
Therefore, EPA developed a second set of weights, the economic weights, based on the smaller set of facilities for
which the Agency obtained sufficient economic/financial data to support analysis of facility-level impacts. For
facilities in those parts of the sample frame from which the 11 facilities were removed, the economic weights are
slightly larger numerically than the corresponding technical weights 251 EPA used the economic weights,
developed for the slightly smaller facility set (11 fewer sample facilities than in the technical weight set), for the
facility-level impact analysis.
255 These are the same weights as those used in the cost and economic impact analyses conducted in support of the 2006 Final Section
316(b) Phase III Existing Facilities Rule (U.S. EPA, 2006).
250 As discussed in the earlier 316(b) analyses, these are the industries on which EPA based the DQ sample frame. These industries are:
Aluminum, Chemicals and Allied Products, Food and Kindred Products, Paper and Allied Products, Petroleum Refining, and Steel.
257 Recalculation of sample weights in the affected sample frame cells does not fully offset the loss in the total sample-weighted estimate
for regulated facilities because the affected sample frame cells include some facilities that EPA estimated would not be within the
scope of a 316(b) regulation - e.g., because reported cooling water intake did not meet the minimum coverage requirement. As a
result, some of the sample mass for the 11 excluded facilities is reassigned to sample facilities not within the scope of the 316(b)
regulation.
May 2014
H-7
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
Facilities in the Food and Kindred Products industry
As discussed in the earlier 316(b) Phase III rule analyses, EPA received 12 DQ responses from facilities with
business operations in the Food and Kindred Products industry, in contrast to the initial set of Primary
Manufacturing Industries. For the analysis conducted in support of the 2006 Final Section 316(b) Phase III
Existing Facilities Rule, EPA included the Food and Kindred Products industry in the set of Primary
Manufacturing Industries and used the cooling water usage-based multiplier of 3.11 to estimate the industry-level
costs and impacts of Phase III regulatory compliance for the Food and Kindred Products industry. Therefore,
these 12 sampled facilities represent 37 facilities in the Food and Kindred Products Industry. For these facilities,
economic weights are the same as technical weights.
For the current analysis, EPA kept the Food and Kindred Products industry in the set of Primary Manufacturing
Industries. However, because EPA did not have sufficient survey data for one of these 12 sampled facilities, EPA
adjusted both economic weights and technical weights to reflect the fact that only 11 of the 12 facilities provided
sufficient information for completing cost and economic impact analyses.
Facilities in Other Industries
In addition to 12 DQ responses from facilities in the Food and Kindred Products industry, EPA received 13 DQ
responses from facilities with business operations in industries other than the set of Primary Manufacturing
Industries. EPA originally considered these facilities to be non-utility electric power generators; however,
inspection of their survey responses indicated that these facilities should be classified as cooling water-dependent
facilities whose principal operations lie in businesses other than the electric power industry or the Primary
Manufacturing Industries. In the earlier Phase III rule analysis documents, EPA referred to these additional
258 259
industries as "Other Industries" and their facilities as "Other Industries facilities." ' However, for the purpose
of cost and economic impact analysis and discussion of analysis results, EPA refers to any non-generators under
the broad terminology of Manufacturers.
Because EPA did not receive the DQ responses for the Other Industries facilities through the structured sample
framework, EPA did not apply sample weights to these facilities, and treated them as "additional known facility"
observations with a sample weight of one.260
Similar to the 11 facilities in the Primary Manufacturing Industries with insufficient data for facility-level impact
analysis, three of the 13 Other Industries facilities also did not provide sufficient data for facility-level impact
analysis. Therefore, EPA excluded these three facilities from the facility-level economic impact analysis.
However, unlike the treatment of the excluded facilities in the Primary Manufacturing Industries, EPA did not
reassign the weights of these three facilities to the remaining Other Industries facilities. The reason for this
difference is because facilities in the Other Industries are not from a single sector and are considered standalone
facilities. Therefore, EPA assessed that it would be inappropriate to reassign the weight from these three facilities
to the remaining 10 facilities. For the remaining 10 facilities, the economic weights are therefore the same as the
technical weights.
258 These industries are: Crop Production, Mining (Except Oil and Gas), Textile Mills, Wood Product Manufacturing, Primary Metal
Manufacturing, Transportation Equipment Manufacturing, and Miscellaneous Manufacturing.
259 The 13 facilities in the Other Industries represent only the known, surveyed facilities. EPA did not estimate the total number of
facilities in the Other Industries because EPA does not think that this number can be reliably extrapolated from the sample of known
facilities in this group. However, because the statistically valid survey group of industries (i.e., Electric Generators and Manufacturers
in the six Primary Manufacturing Industries) reflects 99 percent of total estimated cooling water withdrawals, EPA expects that only a
few additional facilities in the Other Industries group potentially may be subject to the final rule.
260 EPA also applied this convention in the earlier 316(b) analyses, including those conducted for the proposed rule.
H-8
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
Summary of Unweighted and Weighted Facility Counts of Manufacturers
Table H-6 presents unweighted counts of Manufacturers that responded to the 316(b) survey and counts of
Manufacturers weighted according to the two weighting schemes. Using the technical weights, EPA estimated
that 588 facilities (575 facilities in the Primary Manufacturing Industries plus 13 facilities in the Other Industries)
will be subject to the final rule. Using the economic weights, EPA estimated that 579 facilities (569 facilities in
the Primary Manufacturing Industries plus 10 facilities in the Other Industries) will be subject to the final rule.
As described in the following section, EPA subsequently adjusted these counts to exclude baseline closures from
the cost and economic impact analysis for Manufacturers subject to the final rule.
Table H-6: Manufacturers that Responded to the 316(b) Survey and Sample-Weighted Estimates of Facility
Counts

Technical Weights
Economic Weights
Sector
Unweighted
Weighted3
Unweighted
Weighted3
Primary Manufacturing Industries
Aluminum
221
9
575
26
210
9
569
27
Chemicals and Allied Products
49
179
44
171
Food and Kindred Products
11
37
11
37
Paper and Allied Products
94
225
90
230
Petroleum Refining
29
39
28
36
Steel
29
68
28
68
Other Industries
13
13
10
10
Total, All Industries3
234
588
220
579
a. Both sets of counts are valid statistical estimates of the same, but unknown, number of Manufacturers.

b. Values may not sum to reported totals due to independent rounding.
Source: U.S. EPA analysis for this report

Development of the Set of Manufacturers for the Cost and Economic Impact Analysis -
Excluding Manufacturers Assessed as Baseline Closures
Similar to the earlier 316(b) analyses, EPA removed Manufacturers showing materially inadequate financial
performance in the baseline (baseline closures) from the cost and economic impact analyses conducted for the
final rule. To determine whether Manufacturers in Table H-6 are at material risk of business failure independent
of regulatory requirements, EPA relied on financial information collected through the 316(b) survey.261
As discussed above, 14 Manufacturers (33 sample weighted using technical weights) did not provide sufficient
information for the facility-level financial analysis. Because EPA did not have the information necessary to assess
whether these facilities would be baseline closures, the Agency assumed that these 14 facilities (33 on a weighted
basis) would not be baseline closures for the analyses that use technical weights 262 This assumption has the
potential to understate baseline closures and therefore overestimate the number of regulated facilities in each of
the analyses that use technical weights. As a result, this assumption may lead to overstating costs and entity-level
impacts.
Table H-7 reports the results of the baseline closure analysis. Using the technical weights, EPA assessed 67
facilities as baseline closures. Using the economic weights, EPA assessed 70 facilities as baseline closures. These
facilities are removed from the subsequent cost and economic impact analyses of the final rule and other options
considered.
Table H-8 presents weighted and unweighted counts of Manufacturers included in the cost and economic impact
analyses conducted for the final rule and discussed in this report - i.e., after excluding the baseline closures
261 For details of this analysis, see Chapter 5: Economic Impact Analysis - Manufacturers.
262 This assumption has the potential to understate baseline closures and therefore overestimate the number of regulated facilities in the
analyses that use technical weights. As a result, this assumption may lead to overstating entity-level impacts (Chapter 4 and Chapter
10).
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
reported in Table H-7. Using the technical weights, EPA estimates that 521 facilities (509 facilities in the Primary
Manufacturing Industries plus 12 facilities in the Other Industries) are subject to the final rule. Using the
economic weights, EPA estimates that 509 facilities (500 facilities in the Primary Manufacturing Industries plus
nine facilities in the Other Industries).
Table H-7: Manufacturers Assessed to be Baseline Closures
Sector
Technical Weights
Economic Weights
Unweighted
Weighted
Unweighted
Weighted
Primary Manufacturing Industries
27
66
27
69
Aluminum
I
3
1
3
Chemicals and Allied Products
I
4
1
4
Food and Kindred Products
I
3
1
3
Paper and Allied Products
13
31
13
33
Petroleum Reliniim
4
4
4
4
Steel
7
20
7
21
Other Industries
1
1
1
1
Total, All Industries"
28
67
28
70
a. Values may not sum to reported totals due to independent rounding.
Source: U.S. EPA analysis for this report
Table H-8: Manufacturers Included in Cost and Economic Impact Analyses - After
Exclusion of Baseline Closures
Sector
Technical Weights
Economic Weights
Unweighted
Weighted
Unweighted
Weighted
Primary Manufacturing Industries
194
509
183
500
Aluminum
8
22
8
24
Chemicals and Allied Products
48
175
43
167
Food and Kindred Products
10
34
10
34
Paper and Allied Products
81
194
77
197
Petroleum Reliniim
25
35
24
31
Steel
22
48
21
47
Other Industries
12
12
9
9
Total, All Industries"
206
521
192
509
a. Values may not sum to reported totals due to independent rounding.
Source: U.S. EPA analysis for this report
H.2 Entity-Level Weights
In addition to developing and using facility sample weights for the facility-level analysis, EPA also needed to
perform certain analyses at the level of the entity that owns regulated facilities. EPA performed these entity-level
analyses to meet Regulatory Flexibility Act (RFA) requirements (Chapter 10), which apply to small entities that
own regulated facilities, and for the entity-level cost-to-revenue analyses that were performed regardless of entity
size classification (Chapter 4 and Chapter J). Because facility-level sample weights do not apply at the level of
the entity and do not account for entity characteristics, such as the profile of entity ownership of regulated
facilities, EPA needed to develop sample weighting approaches for estimating entity-level costs, impacts, and
affected entity-level counts according to various classifications. These entity-level sample weighting approaches
are generally not as precise in their estimation concepts as the facility-level sample weights. As described below,
the entity-level weights generally provide ranges of results based on specific assumptions about the profile in
which entities own regulated facilities - e.g., how many regulated facilities does an individual entity own? and
what level of costs will the entity incur based on the number and profile of regulated facilities that the entity
owns?
H.2.1 Electric Generators
In addition to facility-level weights (Section H.l.l), EPA also developed sample weights at the parent-entity level
for estimating cost and economic impacts on parent entities that own Electric Generators. This allowed EPA to
H-10
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
extend entity-level analyses from entities that own explicitly analyzed facilities, to the estimated population of
parent entities that own explicitly and implicitly analyzed facilities. These entity-level weights are necessary
because parent entities that own only implicitly analyzed facilities (implicitly analyzed entities) would not be
accounted for by an analysis that focuses only on explicitly analyzed facilities and, as a result, only on their parent
entities (explicitly analyzed entities). As the result, such analysis may understate the absolute number of parent
entities affected by the final rule and other options considered. The use of entity-level weights allows EPA to
estimate more precisely the impacts on entities owning only implicitly analyzed facilities by taking into account
important entity characteristics (such as business size and type) in the development of the weights.
Development of entity-level weights
To develop entity-level weights, EPA first identified entities that currently own 532 analyzed surveyed DQ and
STQ facilities. For each identified parent entity, the Agency then determined ownership type - such as privately
owned, municipality, co-operative, etc. - and whether the owning parent entity would be classified as a small
entity based on Small Business Administration (SBA) entity size criteria. EPA developed entity-level weights in
accordance with this classification framework - by entity-ownership type and by entity size classification. Table
H-9 presents the number of analyzed sampled DQ and STQ facilities and their parent entities by entity ownership
type and size for entities that own at least one explicitly analyzed facility and for all entities.
Table H-9: Counts of Regulated Facilities and their Parent Entities by Entity Type and Size - Assuming All
Facilities with Impoundments Qualify as CCRS
Parent Entity Type
Small Entity Size
Standard
Number of Parent Entitiesa,b'°
Number of Facilities
Large
Small
Total
Large
Small
Total
Parent Entities Owning at Least One Explicitly Analyzed Facility
Rural Electric Cooperative
number of employees
2
11
13
3
14
15
Federal
assumed large
1
0
1
6
0
6
Investor-Owned Utilities
number of
employees/revenue/assets
51
6
57
236
6
242
Municipality
50,000 population served
12
7
19
17
7
24
Nonutility
number of
employees/revenue/assets
19
7
26
30
11
41
Other Political Subdivision
50,000 population served
4
0
4
5
0
5
State
assumed large
3
0
3
5
0
5
Total
92
31
123
302
38
340
All Known Parent Entities- i.e., Parent Entities Owning Only Implicitly Analyzed Facilities or at Least One Explicitly Analyzed
Facility"1
Rural Electric Cooperative
number of employees
3
18
21
5
28
33
Federal
assumed large
1
0
1
12
0
12
Investor-Owned Utilities
number of
emplovees/reven lie/assets
53
7
60
355
7
362
Municipality
50.000 population served
19
19
8
29
19
48
Nonutility
number of
emplovees/reven lie/assets
22
8
30
47
13
60
Other Political Subdivision
50.000 population served
5
1
6
10
1
1 1
State
assumed large
3
0
3
6
0
6
Total
106
53
159
464
68
532
a. EPA was unable to find entity revenue values needed to determine the size of five entities; consequently, EPA used the total revenue for all regulated
facilities owned by these entities to determine entity size.
b. EPA was unable to determine the size of two parent entities; EPA assumed that these entities are small.
c. Ten surveyed DQ and STQ facilities are owned by joint ventures of two entities.
d. These counts are unweighted estimates and reflect the known universe of facilities (i.e., facilities that responded to DQ and STQ) and their parent entities.
Source: U.S. EPA analysis for this report
May 2014
H-11
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
Table H-10: Counts of Regulated Facilities and their Parent Entities by Entity Type and Size - Assuming
No Facilities with Impoundments Qualify as CCRS
Parent Entity Type
Small Entity Size
Standard
Number of Parent Entitiesa,b'°
Number of Facilities
Large
Small
Total
Large
Small
Total
Parent Entities Owning at Least One Explicitly Analyzed Facility
Rural Electric Cooperative
number of employees
2
11
13
3
12
15
Federal
assumed large
1
0
1
6
0
6
Investor-Owned Utilities
number of
employees/revenue/assets
49
6
55
219
6
225
Municipality
50,000 population served
8
7
15
10
7
17
Nonutility
number of
emplovees/reven lie/assets
18
7
25
29
1 1
40
Other Political Subdivision
50.000 population served
4
0
4
5
0
5
State
assumed lame
3
0
3
5
0
5
Total
85
31
116
277
36
313
All Known Parent Entities- i.e., Parent Entities Owning Only Implicitly Analyzed Facilities or at Least One Explicitly Analyzed
Facility d
Rural Electric Cooperative
number of employees
3
18
21
5
28 j
Federal
assumed lame
1
0
1
12

Investor-Owned Utilities
number of
emplovees/reven lie/assets
53
7
60
355
7 | 362
Municipality
50.000 population served
19
19
8
29
8
Nonutility
number of
emplovees/reven lie/assets
22
8
30
47
13 | 60
Other Political Subdivision
50.000 population served
5
1
6
10

State
assumed lame
3
0
3
6
0 j 6
Total
106
53
159
464
68
532
a. EPA was unable to find entity revenue values needed to determine the size of five entities; consequently, EPA used the total revenue for all regulated
facilities owned by these entities to determine entity size.
b. EPA was unable to determine the size of two parent entities; EPA assumed that these entities are small.
c. Ten surveyed DQ and STQ facilities are owned by joint ventures of two entities.
d. These counts are unweighted estimates and reflect the known universe of facilities (i.e., facilities that responded to DQ and STQ) and their parent entities.
Source: U.S. EPA analysis for this report
EPA developed the entity-level weights for each combination category of entity size and entity type by dividing
the number of parent entities at the total population level (i.e., parent entities owning at least one explicitly
analyzed facility and parent entities owning only implicitly analyzed facilities) by the number of parent entities
owning at least one explicitly analyzed facility (Table H-ll). Applying these entity-level weights to the number of
explicitly analyzed entities yields an estimate of the number of parent entities that includes implicitly-analyzed
entities.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
Table H-11: Entity-Level Weights and Weighted Entity Counts

Entity Weights

All Facilities with
No Facilities with

Impoundments Qualify as
Baseline CCRS
Impoundments Qualify as
Baseline CCRS "
Weighted Entity Counts
Parent Entity Type
Small
Large
Total
Small
Large
Total
Small
Large
Total
Rural Electric Cooperative
1.64
1.50
1.62
1.64
1.50
1.62
3
18
21
Federal
().()()
.00
.00
0.00
DO
.00
1
0

Investors )\\ ned IJtilities
F 17
.04
.05
F17
.08
.09
53
7
60
Municipality
2.71
.58
.00
2.71
.38
.53
19
19

Nonutilitv
1.14
1 16

F14
.22
.20
22
8
30
Other Political Subdivision3
1.00
1.25
1.50
F00
.25
.50
5
0

State
0.00
1.00
1.00
0.00
1.00
1.00
3
0
3
Total
1.71
1.15
1.29
1.71
1.25
1.37
106
52
159
a. One small entity in the other political subdivision category owns only implicitly analyzed facilities (Table H-9); consequently, there is no explicitly
analyzed small entity to represent this implicitly analyzed small entity and weighted entity counts do not include one small entity in the other
political subdivision ownership category.
Source: U.S. EPA analysis for this report

Application of entity-level weights
EPA used entity-level weights to assess impacts on owning entities as part of the general cost and economic
impact analysis (Chapter 4) and in the RFA analysis (Chapter 10). Thus, the findings of impacts to entities
owning explicitly analyzed facilities (i.e., the number of parent entities in a given impact category) were
extrapolated to entities owning implicitly analyzed facilities with the same characteristics by multiplying by the
appropriate weight.
EPA conducted the entity-level impact analyses discussed in Chapter 4 and Chapter 10 using two weighting
approaches: (1) using only new facility-level weights and (2) using only entity-level weights. The Agency notes
that using only facility-level weights may overstate the impact on a given entity while underestimating the
number of entities in each impact category, while using only entity-level weights may understate the impact on an
individual entity while accounting more accurately for the total number of entities that own regulated facilities.
For this reason, EPA conducted entity-level analyses using both of these weighting concepts. Using neither
facility-level weights nor entity-level weights would likely underestimate both the number of facilities that may
be owned by a parent entity and associated compliance costs and the number of parent entities that own regulated
facilities. EPA chose not to combine the entity-level weights with the facility-level weights, because this has the
potential to overestimate both the number of facilities owned by a parent entity and associate costs and the
number of entities that own regulated facilities. The relevant chapters present more information on how EPA used
entity-level weights in the analysis.
H.2.2 Manufacturers
Similar to Electric Generators, in addition to facility-level weights {Section H. 1.2), EPA also developed sample
weights at the parent-entity level for estimating cost and economic impacts on parent entities that own
Manufacturers. This allowed EPA to extend entity-level analyses from entities that own surveyed facilities to the
estimated population of parent entities that own all regulated facilities. As discussed in Chapter 5, the entity-level
analysis goes beyond the facility-level analysis to assess whether entities that own regulated facilities may incur
impacts at the level of the entity in a way that is not revealed by the facility impact analysis. EPA's sample-based
facility analysis supports specific estimates of (1) the number of regulated facilities and (2) the total compliance
costs expected to be incurred by these facilities. However, the sample-based analysis does not support specific
estimates of the number of entities that own these facilities. In addition, the sample-based analysis does not
support specific estimates of the number of regulated facilities that may be owned by a single entity, or the total of
compliance costs across regulated facilities that may be owned by a single entity. The use of entity-level weights
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
allows EPA to more precisely estimate the impacts on entities owning not only the surveyed Manufacturers, but
the entire population of regulated facilities.
Development of Entity-Level Weights
As discussed in Chapter 5, for the entity-level analysis conducted for Manufacturers, EPA considered two
weighting cases based on facility-level technical weights developed from the 316(b) survey.263 These cases
provide approximate upper and lower bound estimates on: (1) the number of entities that own Manufacturers and
therefore, incur compliance costs and (2) the number of facilities owned and consequently, costs incurred by any
parent entity.264 These weighting cases are as follows:
Case 1: Lower bound estimate of number of entities that own regulated facilities; upper bound
estimate of number of regulated facilities that an entity may own and of total compliance costs
that an entity may incur.
For this case, EPA assumed that any entity that owns a regulated sample facility(ies), owns the known sample
facility(ies) and all of the sample weight associated with the sample facility(ies). This case minimizes the number
of affected entities, because the weight for each known affected entity is 1, while maximizing the number of
facilities any single entity may own. This also maximizes the potential cost burden to that entity, because EPA
assumed that entities own all facilities represented by the sample weights of the facility(ies) they are known to
own.
Case 2: Upper bound estimate of number of entities owning facilities that face requirements
under the regulation; lower bound estimate of total compliance costs that an entity may incur.
For this case, EPA inverted the prior assumption and assumed that (1) an entity owns only the regulated sample
facility(ies) that it is known to own from the sample analysis and (2) this pattern of ownership, observed for
sampled facilities and their parent entities, extends over the facility population represented by the sample
facilities. In this case, the entities are weighted based on the weight(s) of the facility(ies) they own. This case
minimizes the possibility of multi-facility ownership by a single entity and thus maximizes the count of affected
entities. It also minimizes the number of facilities any single entity may own and consequently, the potential cost
burden to that entity.
EPA assumed that none of the entities that own one sample facility own more than one facility. In this case, the
analysis is straightforward: the entity owns one regulated facility. EPA assumed that this configuration exists as
many times as the facility's sample weight and entity-level weight is the same as facility-level weight. However,
EPA found that 29 percent of the entities identified as owning a sample facility, own more than one sample
facility. Where the multiple facilities owned by the same entity have the same sample weight, the analysis is also
straightforward. EPA assumed that the entity owns the sample facilities that it is known to own and that this
configuration exists as many times as the uniform sample weight of the multiple facilities. Therefore, in this case,
entity-level weight is the same as the uniform facility-level weight.
In some instances, however, the sample facilities that are owned by the same entity have different sample weights.
These cases required a more complex analysis. EPA accounted for the ownership of multiple sample facilities by
a single entity, but restricted the count of the multiple facilities and their configuration of ownership for the entity-
level cost analysis based on the sample weights of the individual sample facilities. Specifically, EPA assumed that
263 As summarized in Table H-6, 14 facilities did not provide sufficient data for the facility impact analysis; however 11 of these facilities
provided sufficient data for estimating compliance cost, as needed for the entity-level analysis. Therefore, for the entity-level analysis,
EPA used technical weights and excluded three facilities with insufficient data and facilities they represent through technical weights.
264 The application of sample weights in the entity-level analyses for Manufacturers is the same as that used in the earlier 316(b) Phase III
rule analyses.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
the entity exists on a sample-weighted basis as many times as the highest of the sample weights among the sample
facilities known to be owned by the entity. However, sample facilities with a smaller sample weight, and their
compliance costs, can be included in the total instances of ownership by the entity for only as many times as their
sample weights. Otherwise, the total facility count implied in the entity analysis would exceed the sample-based
estimated total of facilities. For implementation, this concept means that all of the sample facilities known to be
owned by the same entity can be included in the ownership configuration for only as many sample weighted
instances as the smallest sample weight among the multiple facilities owned by the entity. Once the sample
weight of the smallest sample weight facility is "used up," a new multiple facility ownership is configured. This
configuration includes only facilities with weights greater than the weight of the smallest sample weight facility.
EPA assumed that this configuration exists for as many sample weighted instances as the difference between the
lowest sample weight and the next higher sample weight among the facilities owned by the entity. EPA repeated
this process- with successive removal of the new lowest sample weight facility - as many times as necessary until
only the highest sample weight facility remains in the ownership configuration. This process yields a set of
configurations, with estimated sample occurrence, in which varying numbers of facilities are assigned to the same
entity. These configurations are assumed to exist as many times as the assigned numbers of facilities; therefore,
the assigned facility counts be become entity-level weights.
Table H-12 presents unweighted and weighted entity counts by industry. EPA estimates that between 120 and 337
entities own regulated facilities. Of these entities, between 110 and 327 entities own regulated facilities in the
Primary Manufacturing Industries (including entities that own multiple facilities) and 10 entities own regulated
facilities in the Other Industries.
Table H-12: Parent Entities of Manufacturers Included in
Cost and Economic Impact Analyses

Sector
Unweighted
Weighted3
Primary Manufacturing Industries
110
327
Aluminum
4
11
Chemicals and Allied Products
30
121
Food and Kindred Products
6
20
Paper and Allied Products
37
104
Petroleum Refining
16
25
Steel
13
32
Multiple
4
14
Other Industries
10
10
Total, All Industries'1
120
337
a. Counts developed based on facility-level technical weights.
b. Values may not sum to reported totals due to independent rounding.
Source: U.S. EPA analysis for this report

Application of entity-level weights
EPA used entity-level weights to assess impacts on owning entities as part of the general cost and economic
impact analysis (Chapter 5) and in the RFA analysis (Chapter 10). EPA conducted the entity-level impact
analyses discussed in Chapter 5 and Chapter 10 using two weighting approaches - Case 1 and Case 2 - discussed
above. The Agency notes that using the "Case 1" weighting approach may overstate the impact on a given entity
while underestimating the number of entities in each impact category, while using "Case 2" weighting approach
may understate the impact on an individual entity while potentially accounting more accurately for the total
number of entities that own regulated facilities. For this reason, EPA conducted entity-level analyses using both
of these weighting approaches and presented results for entity-level analyses as a range. The relevant chapters
present more information on how entity-level weights were used in the analysis.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix H: Sample Weights
H.3 Summary
Table H-13 summarizes EPA's use of weights in each of the analyses the Agency conducted for Electric
Generators and Manufacturers.
Table H-13: Use of Weights in the Cost and Economic Impact Analysis for the Final Rule
Chapter
Weights Used
Electric Generators3
Manufacturers'"
2: Industry Profile
> Original survey weights
> Original survey weights (T)
3: Compliance Cost Assessment
> New facility-level weights0
> Original survey weights (T)
4 and 5: Cost and Economic Impact
Assessment
> Facility-Level Analysis
> New facility-level weights
> Original survey weights for short-term reliability
assessment.
> Original survey weights (E)
> Entity-Level Analysis
> New facility-level weights, without using entity-level
weights
> Entity-level weights, without using new facility-level
weights
> Original survey weights (T)
6: Market Model Analysis
> No weights4
> Not included
7: Social Cost Assessment
> New facility-level weights
> Original survey weights (T)
8: Cost and Benefits
> New facility-level weights used in Social Cost
Assessment
> Original survey weights (T)
9: Employment Effects
> New facility-level weights used in Social Cost
Assessment
> Original survey weights (T)
10: Regulatory Flexibility Act (RFA) Analysis
> New facility-level weights
> Entity-level weights, without using new facility-level
weights
> Original survey weights (T)
11: Unfunded Mandates Reform Act (UMRA)
Analysis
> New facility-level weights for impacts to facilities
owned by governments and small governments
> No weights when only entity and facility counts are
presented without associated cost estimates
> Original survey weights (T)
12: Other Administrative Requirements
> New facility-level weights
> No weights for E.O. 13211: Energy Effects
> Original survey weights (T)
a. "DQ" refers to the Detailed Questionnaire.
b. Manufacturers survey sample weights consist of two sets, one used for economic impact analysis (denoted by an E), and another set used for all other
analyses (denoted by a T). For details on these two weight sets, see Section H. 1.2.
c. New facility-level weights are a combination of the original survey weights used for facilities with closed-cycle recirculating systems in the baseline,
coastal California facilities, and New York facilities with DIF of at least 20 mgd and the new-DQ weights used for all other facilities. For details on these
weights, see Section H.l.l.
d. "No weights" means that the analyses in a chapter do not use weights.
Source: U.S. EPA analysis for this report
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix I: Energy Effects
Appendix I Compliance Technology Effects that Impose Costs Via Impact
on Revenue or Energy Requirements
As discussed in Chapter 3: Compliance Costs, EPA accounted for three compliance technology-related
installation and operating effects that do not impose costs through a direct purchase of goods and services, but
through an impact on revenue and/or energy requirements. Although changes in energy requirements may impose
costs through purchases of energy inputs and/or electricity from external sources, the cost of energy inputs and
externally provided electricity may vary by the type of energy used by the facility and the facility's region (in
particular for purchase of electricity). For these reasons, EPA accounted for these compliance technology effects
through facility-level analysis of revenue and energy cost effects, instead of using uniform unit prices or costs for
all facilities. The three compliance technology effects are as follows:
> Energy> penalty. Energy penalty effects result from reduced energy conversion efficiency of the power
generating system, which occurs with operation of closed-cycle recirculating systems (CCRS or cooling
towers) required under Proposal Option 2. Depending on facility type (i.e., Electric Generator or
Manufacturer) and the facility's baseline operating circumstances, EPA assessed energy penalty as (1) a
reduction in the generated electricity that is available for sale or use (Electric Generators and
Manufacturers), (2) an increase in the production cost of electricity that is sold or used by the facility
(Electric Generators), or (3) the cost of purchasing electricity that is no longer able to be generated and
used by the facility in its operations (Manufacturers). EPA accounted for these effects in the separate cost
category, energy> penalty. Calculation of the energy penalty is discussed in Section 1.1.
> Auxiliary energy requirement. This effect results from the electricity required to operate an assigned
compliance technology. For Electric Generators and Manufacturers that generate electricity, EPA
assessed the auxiliary energy requirement associated with cooling towers in the same way as described
for the energy penalty, above: i.e., (1) reduction in the generated electricity that is available for sale or
use, (2) an increase in the variable production cost of sold or used electricity, or (3) the cost of purchasing
electricity.265 For Manufacturers that do not generate electricity, EPA assessed this effect based on the
cost of purchasing electricity to operate the compliance equipment. EPA included the cost of auxiliary
energy requirements in the operating and maintenance (O&M) cost category. Calculation of the auxiliary
energy requirement is discussed in Section 1.2.
> Installation downtime. Installation of certain compliance technologies will require a one-time, temporary
downtime period for the facility. Downtime may impose cost of facilities through lost electricity sales
(revenue less any avoided generation costs) and/or the cost of replacing electricity that is not able to be
generated and used by the facility during the downtime period. The latter case applies specifically to
Manufacturers that generate and use electricity in facility operations. EPA accounted for cost effects in
the separate cost category, installation downtime. Costs associated with downtime are discussed in
Section 1.3.
The Technical Development Document (TDD) details the methodology EPA used to develop facility-level cost
estimates for the final rule and other options EPA considered.
205 EPA used this method to estimate the cost of auxiliary energy requirements only for CCRS. Because the energy requirements for
impingement reduction technologies are much lower than for CCRS, EPA used a uniform costing approach for the auxiliary energy
requirement associated with IM technologies.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix I: Energy Effects
1.1 Energy Penalty
Operation of CCRS causes an increase in turbine back-pressure, which reduces the amount of electricity that is
produced by the generating unit for the same energy input. Operation of IM technologies does not have the same
effect. For regulatory options in which facilities could be assigned cooling towers, EPA assessed the energy
penalty as a permanent reduction in the electricity generation efficiency of affected generating units: for a given
level of energy input to the generating unit, the quantity of electricity that is available to be sold for revenue or
otherwise used by the power generator for onsite services (e.g., electricity for onsite offices) is reduced. EPA
assessed this reduction in unit generating efficiency as a percentage reduction in the generating capacity and
associated electric generating output for any given level of energy input.
EPA accounted for energy penalty effects for Electric Generators and Manufacturers using two different
methodologies.
1.1.1 Electric Generators
EPA assessed the impact of the energy penalty differently for Electric Generators depending on the type of
facility affected and the facility's baseline operating circumstances in terms of capacity utilization:
> For facilities that operate at high capacity utilization - namely, nuclear facilities and fossil fuel facilities
with capacity utilization exceeding 62 percent - EPA assumed that units, on average, will operate at full
output and that the energy penalty will manifest as a loss in generating capacity available for revenue
generation. As a result, the financial effect of the energy penalty is to reduce the revenue otherwise
received by the facility, but with no change in the cost of energy inputs to the facility.266
> For facilities that operate at lower capacity utilization - for this analysis, less than or equal to capacity
utilization of 62 percent - EPA assumed that units, on average, will not operate at full output, and that the
energy penalty effect can be offset by increasing the energy input to the unit, thereby avoiding a loss in
revenue. In this case, although the generating unit does not lose revenue, the cost of generating electricity
for sale from the unit will increase, and the financial effect is a reduction in the operating margin for
electricity sales from the affected unit.267
EPA estimated the unit generating efficiency loss at 1.5 percent of baseline steam generating capacity for non-
nuclear units and 2.5 percent of baseline steam generating capacity for nuclear units. As described above, the
Agency assumed that nuclear Electric Generators and non-nuclear Electric Generators with capacity utilization
exceeding 62 percent will not to be able to increase their electricity generation to make up this efficiency loss
onsite.268 EPA accounted for energy penalty at these regulated facilities as revenue loss as follows:
Energy Penalty ($) = Baseline Revenue ($) x Energy Penalty (%) (1-1)
EPA assumed that all other Electric Generators would have sufficient excess generating capacity to be able to
make up the potential loss in electricity generation onsite. For these facilities, EPA accounted for the energy
penalty as an increase in variable production costs, i.e., fuel and other variable O&M costs as follows:
Variable Production Costs ($) = Fuel Costs ($)+Variable O&M Costs ($) (1-2)
200 EPA did not have sufficient data to make this assessment at the level of a generating unit. To conduct this analysis at the facility level,
EPA used capacity utilization rates, revenue, and variable costs calculated for the group of steam generating units at a given facility.
267 Idem.
208 To make up the reduction in electricity generation at these regulated facilities and ensure adequate electricity supply in the United
States, other electric power facilities supplying to the grid would have to increase their electricity production.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix I: Energy Effects
and
Energy Penalty ($) = Variable Production Costs ($) * Energy Penalty (%) (1-3)
EPA estimated facility-specific annual average variable production costs and baseline revenue as follows:
> Variable production costs: To estimate average annual variable costs, EPA relied on data published by
the U.S. Department of Energy (DOE), Energy Information Administration (EIA) and projections from
the Integrated Planning Model (IPM). Using IPM data, the Agency first calculated average annual
variable cost values - fuel and variable O&M - on a per-unit of generated electricity basis (MWh) by
North American Electric Reliability Council (NERC) region and/or fuel type for each IPM data year -
2015, 2020, and 2030.269 EPA then calculated facility-level steam generation as a 5-year average of steam
net generation values reported in the EIA-906/920/923 database for 2007 through 2011.270 Finally, the
Agency estimated facility-specific average annual variable production costs as the product of (1) the 3-
year average of variable unit costs (calculated for 2015, 2020, and 2030), in accordance with the NERC
region of and/or fuel type used by a given facility, and (2) facility-level 2007-2011 average steam net
generation.
> Baseline revenue: To estimate average annual revenues, EPA used prime mover-level data on net
electricity generation from the EIA-906/920/923 database and utility-level electricity sales quantity and
revenue data from the EIA-861 database. EPA used the utility-level revenue and sales quantity data to
estimate electricity prices (revenue per MWh of sales) for each Electric Generator. As the measure of
price, EPA used the 5-year average of total (retail and wholesale,) prices (e.g., total revenue per MWh of
total sales) for 2007 through 2011. For the measure of facility-specific generating output, EPA used the
same 5-year average steam net generation values as used to estimate variable costs. To estimate the
amount of generated electricity sold, EPA first estimated the share of total power disposition sold through
both retail and wholesale operations for each facility using EIA-861 data as a 2007 to 2011 average. EPA
then used these shares to adjust facility-specific steam generation. Finally, the Agency estimated facility-
specific average annual baseline revenue as a product of (1) the adjusted steam generation and (2) prices.
EPA used the GDP Deflator series to restate the resulting variable cost and revenues in 2011 dollars.
Cost of Energy Penalty to Society
EPA used the same methodology to assess the cost of the energy penalty to society as that used to assess the cost
of energy penalty to regulated facilities and outlines above. Society incurs additional costs for the energy penalty
through either of two mechanisms:
1. Regulated facilities' consumption of additional energy to generate the same quantity of electricity for use
by consumers. As described above, EPA's private cost and social cost analysis assumes this case for
facilities that operate with lower capacity utilization - non-nuclear facilities with capacity utilization not
exceeding 62 percent. In this case, the social cost of the energy penalty is the cost of the additional energy
consumed to generate the unchanged quantity of useable electricity.
2. The general electric power grid's need to generate additional electricity that is not able to be made up by
regulated facilities because these facilities operate at high capacity utilization. EPA's cost analysis
269 EPA used IPM to assess the impact of the final rule and other options considered in development of this rule on the electric power
market as a whole. For details on this analysis see Chapter 6: Electricity Market Analysis. To estimate average annual variable
production costs, EPA used the IPM V4.10_MATS IPM platform.
270 In using the year-by-year revenue values to develop an average over the data years, EPA set aside from the average calculation,
generation values that are anomalously low. Such low generating output likely results from temporary disruptions in operation, such as
a generating unit being out of service for maintenance.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix I: Energy Effects
assumes this case occurs when facilities are unable to generate additional electricity because they operate
at high capacity utilization (assumed for all nuclear facilities and for non-nuclear facilities with capacity
utilization exceeding 62 percent). In this case, the social cost is the cost of generating the replacement
electricity, which, under economic dispatch,271 is presumed to be supplied by the lowest production cost
generating unit that is available to make up the electricity generation that is lost due to the energy penalty.
Again, according to economic dispatch, the cost of generating the replacement electricity should be at
least as high as the production cost of the regulated unit.272 Furthermore, given that these units are higher
capacity utilization units and thus likely have relatively lower production costs within the overall
generation mix, it is quite likely that the production cost for the replacement electricity will be higher,
perhaps substantially higher, than the cost of the regulated units incurring the energy penalty from CCRS
operation.273 As described above, EPA accounts for this cost - both for the private cost and social cost
analysis - based on the value of lost revenue.
Both of these treatments involve uncertainty of overstatement and understatement of social costs because of the
specific operating circumstances of individual generating units and facilities under economic dispatch - i.e., when
individual generating units will operate at full, or less than full, capacity - and the related considerations of
marginal production cost and pricing of electricity at specific times.
> For case one (low capacity utilization units), above, the assumption that low capacity utilization facilities
will be consistently able to offset the energy penalty via increased energy input may understate the social
cost of the energy penalty. Specifically, there will likely be hours in the year in which these units operate
at full output and thus would not be able to offset the energy penalty by increasing energy input to the
affected units. In this case, the general power grid (i.e., other generating units) would need to make up the
lost generation, and in the same way as described for high capacity utilization units, the cost of this
replacement electricity could be higher than the production cost of the low capacity utilization units.
> At the same time, for case two (high capacity utilization units), above, to the extent that the revenue loss
estimated for high capacity utilization units exceeds - at least some of the time - the cost of generating
replacement electricity by the overall power grid, the assumption that the social cost of the energy penalty
is equal to the lost revenue at these facilities, will overstate the social cost of the energy penalty (i.e., the
cost of the replacement electricity). Moreover, there may be off-peak periods during the year in which
high capacity utilization units will not operate at full output, and therefore would be able to offset the
energy penalty generation loss via increased energy input - with the additional energy cost (and social
cost) being less than the revenue received during those periods. This possibility again points to a
likelihood of overstatement of social cost for the case two assumption.
While EPA cannot determine the extent of error in either direction, the Agency judges, on balance, that the
methodology outlined in this section provides a reasonable approximation of the energy penalty's cost to society.
EPA notes that in performing such analyses at the level of the individual facility and generating unit,274 it would
be possible to account more accurately for the particular circumstances of the affected units over the course of the
year - i.e., when units would and would not be operating at maximum capacity, and the likely production cost of
replacement electricity (whether from the affected regulated units or the general electric power grid). Such
271 That is, at any point of time, electricity is supplied by the combination of available electric power generating units that, in the
aggregate, can meet electricity demand at the lowest total cost.
272 Otherwise, the lower production cost unit would have already been dispatched.
273 This is a considerable simplification of the economic dispatch concept, in that it does not account for a range of factors - for example,
"must run" requirements for certain generating units. However, overall, the least-cost-solution concept is the applicable governing
concept in the management of electric power generation throughout the country.
274 As would occur for the site-specific determinations of possible additional technology requirements under the final rule.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix I: Energy Effects
analysis would provide a more accurate assessment of both the cost to the individual facility, and the cost to
society.
1.1.2 Manufacturers
EPA used a different methodology to assess the impact of the energy> penalty for Manufacturers than that used for
Electric Generators because of data constraints and differences in the operating characteristics of these facilities.
For Manufacturers, EPA estimated that the unit generating efficiency loss is the same as for non-nuclear Electric
Generators, i.e., 1.5 percent of baseline steam generating capacity.275'276
Because Manufacturers are not, by definition, primarily in the business of generating electricity for sale, the
energy penalty can affect Manufacturers in ways that differ from Electric Generators. Depending on the specific
operating circumstances of a given Manufacturer, the energy penalty effect on Manufacturers includes:
> Reduced production of electricity for sale to external consumers - i.e., via the power grid - with loss of
revenue to the Manufacturer.
> Reduced production of electricity for consumption by the Manufacturer with a resulting requirement to
purchase electricity to offset the lost production.
Unlike the analysis done for Electric Generators, EPA did not analyze a case where Manufacturers increase
electricity generation, at an increased cost, in order to make up the energy lost due to the energy penalty. For
Manufacturers, EPA assumed that facilities are currently producing at their maximum rate and will not be able to
increase electricity generation.
To analyze the energy penalty effect for Manufacturers, EPA used the following information from the 316(b)
survey: (1) whether the facility generates electricity for its own consumption and/or external sale; (2) total
generation; (3) total sale of electricity (quantity and value) generated by the facility, if any; (4) total consumption
of electricity generated by the facility; and (5) cost of electricity generation in terms of fuel consumption and
other variable electric generation costs. When data were reported for more than one of the three survey years -
* * * * 277 278
1996, 1997, and 1998 - EPA used the average of these values as facility-level values for this analysis." "*
To calculate the cost of the energy penalty, EPA first multiplied the energy penalty percentage by total steam
generation (MWh) to obtain energy penalty as a quantity of electricity (MWh). EPA then applied the following
equation to each of the facilities to determine the value of the Total Penalty:
Energy Penalty ($) = En. Pen. /:s. x Elec. Rev. + En. Pen. /;s, x Elec. Price (1-4)
Where:
Energy Penalty ($) = The economic value of the energy penalty, reported in 2011 dollars
275 For five facilities assigned an energy efficiency loss, the survey did not provide total generation or capacity information and therefore
EPA could not calculate the loss in generation or the cost associated with that loss in generation. EPA expects this omission to be
relatively minor in significance.
270 For a detailed discussion of the development of these energy penalty values, see the TDD.
277 For 26 Manufacturers, information received from the survey indicated that a facility's total generation was higher than would be
feasible for the facility's reported generating capacity, even when operating at full output for all hours in a year. This indicates a
reporting error. EPA was not able to assess whether firms erred in their reporting by overstating total generation or by understating
capacity. For these facilities, EPA used the total generation value in assessing the energy penalty. EPA recognizes that this may lead to
an overstatement of the energy penalty value, to the extent that facilities erred in their reporting of total generation.
278 Some facilities did not report generating capacity at the facility level but instead, reported the values by generating unit. In these
instances, EPA used the sum of the reported unit-level capacity values.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix I: Energy Effects
En. Pen.ES
The portion of the energy penalty that exceeds a facility's electricity sales, for
facilities that do not sell electricity this value is equivalent to energy penalty.
Elec. Price
EIA-reported electricity prices for the industrial sector, by state, for the year
2011 measured in $/KWh.
Cost of Energy Penalty to Society
The primary cost of the Manufacturers energy penalty - to facilities and society - results from the replacement of
electricity otherwise generated by facilities. This replacement electricity serves two functions:
1. Replacement of electricity that Manufacturers would generate and consume themselves
2. Replacement of electricity that Manufacturers would generate and sell to the electric power grid.
The cost of generating the replacement electricity is the cost to society from the energy penalty. For the social cost
analysis (see Chapter 7: Total Social Costs), EPA approximated this value based on the unit price for purchasing
replacement electricity. EPA multiplied the unit price times the quantity of electricity generation lost due to the
energy penalty for each facility, to yield the social cost of the energy penalty, by facility. EPA summed these
values over the regulated facilities achieving compliance in a given year, to yield the total social cost of energy
penalty for all Manufacturers in the year. This approach assumes that the price for purchasing replacement energy
reflects the cost of generating electricity from the alternative supply sources. The price for purchasing electricity
reflects more closely the cost to society for generating replacement electricity than the price otherwise received by
facilities in selling electricity to the electric power grid.
This approach relies on the same methodologies as those described above for calculating the cost of the energy
penalty to facilities. However, the social cost of the energy penalty is calculated differently from what is shown in
Equation (1-4) for facilities. The second half of the equation, for calculating the component of electricity that
facilities would generate and consume themselves (the second of the two components of replacement electricity
listed above) remains the same. However, the calculation for the first half of the equation - the value of electricity
that Manufacturers would generate and sell to the electric power grid - differs in the social cost calculation in that
the price of purchasing replacement electricity is substituted for the facilities' forgone price of selling electricity.
1.2 Auxiliary Energy Requirement
Both L\1 technologies and cooling Lowers require eleelneiLx lo operate, liowexer, tins effect is more substantial for
cooling towers than for IM technologies. For both Electric Generators and Manufacturers, the effect of the
auxiliary energy requirement is the same as that described for the energy penalty in Section 1.1 .EPA estimated the
cost of the auxiliary energy requirement to facilities following similar procedures to those outlined in that section
with a few exceptions arising from whether facilities install IM technologies or cooling towers.
For both Electric Generators and Manufacturers, EPA included the cost of the auxiliary energy requirement in the
estimated cost of technology O&M.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix I: Energy Effects
1.2.1 Electric Generators
EPA estimated that for Electric Generators installing cooling towers under Proposal Option 2, auxiliary> energy>
requirements vary by facility, ranging from 0.1 to 3.2 percent of baseline steam generating capacity. As stated
earlier, the effect of the auxiliary energy requirement is more substantial for cooling towers than for IM
technologies. EPA assessed the impact of the auxiliary energy requirement differently depending on whether IM
technologies or cooling towers were assigned as follows:
> For cooling towers, EPA estimated auxiliary energy requirement using the same methodology as that
used to assess the effect of energy penalty. Specifically, EPA assumed that for generating units that
operate at high capacity utilization (namely, nuclear units and base load fossil fuel units with capacity
utilization exceeding 62 percent), the financial effect of the auxiliary energy requirement is to reduce the
revenue otherwise received by the generating unit, and for all other units the financial effect is an increase
in variable costs. For details on how EPA calculated the reduction in revenue and an increase in variable
costs due to the auxiliary energy requirement, see Section 1.1.1.
> For IM technologies, EPA assumed that the auxiliary energy requirement will manifest as a loss in
generating capacity available for revenue generation. As a result, the financial effect of this auxiliary
energy requirement is to reduce the revenue otherwise received by the generating unit, but with no change
in the cost of energy inputs to the generating unit. For details on the methodology EPA used to estimate
this revenue loss, see Phase II - Large Existing Electric Generating Plants, Technical Development
Document for the Final Section 316(b) Phase II Existing Facilities Rule (Final Phase II TDD) and the
TDD for the final rule.
Regardless of the approach used to calculate the value of the auxiliary energy requirement, EPA accounted for the
requirement in O&M.
As is the case with energy penalty discussed in Section 1.1.1, EPA used the same methodology to assess the cost
of the auxiliary energy requirement to society as that used to assess the cost of the auxiliary energy requirement to
regulated facilities. All of the uncertainty factors discussed in Section 1.1.1 for the social cost of the energy
penalty apply to the social cost for the auxiliary energy requirement, as well.
1.2.2 Manufacturers
For Manufacturers installing cooling towers under Proposal Option 2, the auxiliary requirement varies by facility,
ranging from 0 to 9.78 MW of capacity; this capacity requirement represents, on average, 3.2 percent of baseline
electric generating capacity, with a maximum of 48.5 percent of baseline generating capacity. 279As is the case
with Electric Generators, the effect of the auxiliary energy requirement is more substantial for cooling towers than
for IM technologies. Again, EPA assessed the impact of the auxiliary energy requirement differently depending
on whether IM technologies or cooling towers were assigned as follows:
> For cooling towers, EPA estimated the auxiliary energy requirement using a similar methodology to that
used to assess energy penalty. Specifically, the auxiliary energy requirement effect on Manufacturers
includes: (1) reduced production of electricity for sale to external consumers - i.e., via the power grid -
with loss of revenue to the Manufacturer; (2) reduced production of electricity for consumption by the
Manufacturer with a resulting requirement to purchase electricity to offset the lost production; and (3)
requirement to purchase electricity for meeting the auxiliary energy needs - even though the facility does
not generate any of its own electricity. Again, EPA did not analyze a case where Manufacturers are able
to increase energy generation to account for the energy lost due to the auxiliary requirement. EPA
calculated auxiliary energy requirement as follows:
279 Of the 588 Manufacturers, only seven have auxiliary energy requirements exceeding five MW.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix I: Energy Effects
Aux. Energy Requirement (MWh) = Aux. Power Requirement (MW) x 8,760 (1-5)
Where:
Aux. Energy Requirement = Annual energy requirement for operating the compliance system
(MWh)
Aux. Power Requirement = Capacity required for operation of the compliance system, measured in MW
(MW)
Energy Conversion = EPA assumed that facilities experience constant electricity demand for
compliance system operation for all hours of the year and therefore calculated
the auxiliary energy requirement by multiplying the capacity requirement by
8,760 hours (365 days times 24 hours per day).
EPA calculated revenue reduction and increased costs to purchase electricity due to the auxiliary energy
requirement, in a manner similar to that used for the energy penalty, using the following equation:
Aux Energy Requirement ($) = Aux keq..,,:s. ,,,, xElec. Rev. + Aux Req. ,/.:s. /;/, xElec. Price(I-6)
Where:
Aux. Energy Requirement
($)
Aux. Req.
Elec. Price
The economic value of the auxiliary requirement, reported in 2011 dollars
The portion of the auxiliary requirement that is less than or equal to the
facility's Electricity Sales (see below) less its Energy Penalty. For facilities that
do not sell electricity this value is zero.
Facility-level revenue from electricity sales per MWh of electricity sales; these
values are a simple 3-year average of values reported in the 316(b) survey for
1996, 1997, and 1998 and restated in 2011 dollars, divided by a simple 3-year
average of electricity sales reported in the 316(b) survey.
The portion of the auxiliary requirement that exceeds a facility's electricity
sales less energy penalty, for facilities that do not sell electricity this value
comprises the entirety of the auxiliary requirement.
EIA-reported electricity prices for the industrial sector, by state, for the year
2011 measured in $/KWh.
> For IM technologies, EPA assigned a value to the auxiliary energy requirement based on the price of
electricity for industrial consumers. This can be interpreted as the cost of replacing electricity that cannot
be generated by a facility or as an approximation of the revenue loss if the auxiliary energy requirement
reduces electricity sales. For details on the methodology EPA used to estimate this revenue loss, see the
Final Phase II TDD and the TDD for the final rule.
Regardless of the approach used to calculate the value of the auxiliary energy requirement, EPA accounted for the
requirement in O&M.
1.3 Technology Installation Downtime
Installation of certain compliance technologies will require facilities to shut down their business operations
temporarily (installation downtime). This downtime will lead to a loss in facility revenue and net income, which
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix I: Energy Effects
constitutes an additional regulation-induced cost to regulated facilities. In addition, specifically for Electric
Generators, depending on the extent and scheduling of installation downtime, the occurrence of these temporary
reductions in electricity supply could create local electricity market imbalances, with reductions in system
reliability reserve margins and/or short-term electricity price increases (see Chapter 4: Economic Impact Analysis
- Electric Generators and Chapter 6: Electricity Market Analysis). EPA first estimated the duration of downtime
(weeks) based on the type of compliance technology to be installed and the type of facility. EPA then assessed the
effect of this temporary suspension in generation activity on regulated facilities, their parent-entities, and society
as a whole.
1.3.1 Electric Generators
To assess the effect of temporary suspension in electricity generation necessary to install compliance technology
for Electric Generators, EPA first estimated the length of time for technology installation, and then assessed the
impact of this suspension on facility operations and financial standing, and as a cost to society as a whole.
Length of Time Required to Install Compliance Technology
For the cost and economic impact analyses, the Agency assumed that all Electric Generators installing IM
technologies and non-nuclear Electric Generators installing entrainment control technology (cooling towers)
would do so during customary annual maintenance, which typically requires facilities to shut down their electric
power generating units for a minimum duration of four weeks. Therefore, for these facilities, EPA calculated the
net downtime due to regulatory requirements as total downtime outage required for technology installation less
the four weeks of customary annual maintenance.
EPA assumed that cooling tower installation at nuclear facilities would take place either during extended capacity
up-ratings (ECUs) or during regular refueling outages. An ECU occurs no more than once during the life of a
nuclear facility. It lasts several months and is undertaken subject to approval by the Nuclear Regulatory
Commission (NRC). EPA assumed that nuclear facilities that have not applied to NRC for an ECU will do so in
the future and will install cooling towers during their ECUs; EPA expects that the length of the ECU will be
sufficient to install a cooling tower without requiring additional downtime, and did not assign technology
installation downtime to these nuclear facilities. EPA assumed that nuclear facilities that have already completed
or applied for an ECU from the NRC, would complete their ECU before cooling tower installation; thus, these
facilities would need to complete cooling tower installation during a regular refueling outage. In this case, EPA
calculated the net additional downtime required for cooling tower installation as (1) total estimated downtime
outage of 28 weeks less (2) an estimated four weeks for the regular refueling outage. Refueling outages occur on a
regular basis every 18 to 24 months and typically last four to six weeks; consequently, the Agency calculated the
additional downtime for cooling tower installation as total downtime less the four weeks of regular refueling
outage (i.e., the minimum outage duration). To the extent that a regular refueling outage would require longer
than four weeks (i.e., up to six weeks), EPA's estimate of net downtime duration and costs for the non-ECU
facilities is an overestimate.
EPA also considered whether other factors could influence the need for net downtime to complete installation of
compliance technology; in particular, the baseline operating level of a facility as determined by its capacity
utilization. Based on this consideration, EPA decided to assign no net downtime to facilities with very low
capacity utilization - specifically less than 15 percent. The Agency judged that given the low level of utilization
of these facilities, they very likely would be able to schedule downtime at a time when they do not need to
. i . • •. 280,281,282
generate electricity.
280 EPA calculated capacity utilization rates using nameplate capacity from the EIA databases and a five-year average net generation
reported in the EIA-906/920/923 for 2005 through 2011.
281 Only steam operations were included in the calculation of capacity utilization rate.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix I: Energy Effects
Table 1-1 presents the number of net downtime weeks by technology module assigned to Electric Generators.
Table 1-1
Module
: Estimated Average Net Downtime for Technology Modules3
Description
Estimated iSiel Downtime (Weeks)
CT
Cooling Tower
0 or 24 for nuclear, 4 for non-nuclear
1
3
4
7(73
1'0"3
15
Add Fish Flandlmg and Return System (includes screen replacement)
Add New Larger Intake Structure with Fish Handling and Return
Relocate Intake to Submerged Near-shore (20 M) with passive wedgewire
screen.
Module 3 plus Module 5: Add Fish Barrier Net
Module 1 plus Module 5
Variable Speed Cooling Water Pumps
0
2-4
9
2,3
Ti
0
a. For details on these technology modules and on how they were assigned to regulated facilities, see the TDD.
Source: U.S. EPA analysis for this report
Cost of Technology-Installation Downtime to Regulated Facilities
EPA calculated the financial loss to Electric Generators from installation downtime as lost revenue (from reduced
electricity sales by the facilities) less the variable production costs that would not be incurred during the net
installation downtime period. The Agency used average annual variable production costs and baseline revenue in
the same way as described for calculating the effect of energy penalty on facility operations (Section 1.1.1). EPA
first calculated all revenue and cost effects on a per-week basis (i.e., annual values divided by the number of
weeks a given facility is available for electricity generation in a given year, which assumes that all revenue and
cost values occur uniformly over this period of availability).283 Subtracting the variable cost reduction from
revenue, on a per-week basis, yields the net income loss per week from installation downtime. The Agency
multiplied these average weekly net revenue losses by the estimated number of net downtime weeks to yield the
one-time net income loss from installation downtime.
To the extent that Electric Generators are able to install compliance technology during the spring and fall, when
electricity demand is on average at its lowest, using average annual revenue and variable production costs may
overstate the cost of downtime to regulated facilities.
Cost of Technology Installation Downtime to Society
As discussed above, EPA assessed impacts to Electric Generators by calculating the cost of downtime as the lost
net income to facilities from suspension of operation to install compliance equipment. However, this approach
does not accurately capture the cost of downtime at electric power generating facilities to society (see Chapter 7).
When generating units are taken out of service to install compliance technology, other generating units
compensate for the lost electricity generation In this case, the opportunity cost to society from installation
downtime is the increase in energy production costs from using the alternative generating units to supply
electricity compared to the cost that would have been incurred if regulated units remained in service - and not the
loss in net income to the individual generating units that are temporarily out of service. As discussed earlier for
energy penalty, under the principles of economic dispatch (i.e., at any point of time, electricity is supplied by the
combination of available electric power generating units, which in the aggregate, can provide electricity at the
lowest total cost), the alternative generating units are presumed to provide the replacement electricity at a
282 In using the year-by-year revenue values to develop an average over the data years, EPA set aside from the average calculation,
generation values that are anomalously low. Such low generating output likely results from temporary disruption in operation, such as
a generating unit being out of service for maintenance.
283 For non-nuclear facilities, EPA assumed that generating units are available 48 weeks, i.e., total number of weeks in the entire year (52
weeks) less four weeks of assumed baseline customary maintenance downtime. For nuclear facilities, the Agency assumed 44 weeks,
i.e., total number of weeks in a year less eight weeks of assumed ISI-related downtime.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix I: Energy Effects
somewhat higher production cost than would otherwise be incurred.284 This increase in short-term energy
production cost is then the appropriate concept for social cost of downtime. The electricity market analysis,
described in Chapter 6, provides an estimate of the increase in energy production costs resulting from technology-
installation downtime.285 EPA used this estimated increase in energy production costs as the social cost of
technology-installation downtime. Specifically, EPA calculated the aggregate increase, from baseline to policy
case, in the annual variable O&M and annual fuel costs from the electric market analysis conducted using IPM
(see Chapter 6).286,287
1.3.2 Manufacturers
EPA focused its assessment of downtime impact for Manufacturers on the suspension of electricity generation,
which would accompany installation downtime for Manufacturers that generate electricity. Inability to generate
electricity could have several economic effects, including the need to purchase electricity to offset the lost
electricity supply during downtime, lost revenue from forgone electricity sales, and avoidance of certain costs that
would otherwise be incurred for electricity generation. EPA first estimated the length of time required for
technology installation and then assessed the impact of this suspension on facility operations and financial
standing, and the cost to society as a whole.
Length of Time Required to Install Compliance Technology
Similar to Electric Generators, EPA estimated the length of time required to install compliance technology in
weeks. Unlike for Electric Generators, EPA did not account for any time when Manufacturers might suspend
production for maintenance services. This assumption is appropriate because, unlike electric power generating
facilities, manufacturing facilities do not customarily shut down operations for maintenance. The required
downtime for IM technologies varies by module. Table 1-2 presents the number of net downtime weeks by
technology module assigned to Manufacturers.
284 This is a considerable simplification of the economic dispatch concept, in that it does not account for a range of factors - for example,
"must run" requirements for certain generating units. However, overall, the least-cost-solution concept is the applicable governing
concept in the management of electric power generation throughout the country.
285 EPA used results for the Electricity Market Analysis - Final Rule option from the IPM analysis conducted for the final rule as the basis
for this estimate (for details on that analysis, see Chapter 6). As described in Chapter 6, EPA did not conduct a separate IPM analysis
to assess regulatory impacts of Proposal Option 2 analyzed in support of the final rule on the national and regional electricity markets.
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 for the Proposed Section 316(b) Existing Facilities Rule. As described in Chapter 6 of the
Economic and Benefits Analysis for Proposed Section 316(b) Existing Facilities Ride (Proposed Rule EBA) report, that IPM analysis
used an older IPM platform - IPM V3.02_EISA. For details on that analysis, see Proposed Rule EBA report.
280 EPA assumed that facilities will incur technology installation downtime during the spring or fall seasons so as not to coincide with
either the winter or summer higher demand periods. The IPM modeling framework is built around winter and summer seasons, which
last seven and five months, respectively. For the purpose of this analysis, EPA used variable costs reported for the modeled winter
season. To the extent that these variable costs include changes in variable costs outside the actual spring and fall shoulder seasons, the
downtime impact of the final rule may be overestimated.
287 Updated from 2007 to 2011 dollars using the GDP deflator.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix I: Energy Effects
Table I-2: Estimated Average Net Downtime by Technology Module3
Module
Description
Estimated Net Downtime (Weeks)
CT
Cooling Tower
4
1
Add Fish Handling and Return System (includes screen replacement)
0
3
Add New Larger Intake Structure with Fish Handling and Return
0, 1
4
Relocate Intake to Submerged Near-shore (20 M) with passive wedgewire
screen.
3,7
10.2
Module 3 plus Module 5: Add Fish Barrier Net
0
10.3
Module 1 plus Module 5
0
15
Variable Speed Cooling Water Pumps
0
a. For details on these technology modules and on how they were assigned to regulated facilities, see the TDD.
Source: U.S. EPA analysis for this report
Cost of Technology Installation Downtime to Regulated Facilities
Installation downtime may affect business operations at a manufacturing facility in several ways:
> The facility may be unable to generate electricity or perform other business operations that depend on
cooling water.
> The facility may lose revenue from sale of electricity (if the facility sells electricity to the power grid), or
lose or defer revenue from the production and sale of other goods and services that are affected for
curtailed operations during downtime.
> The facility may shed the variable cost of generating electricity or of producing the goods and services
not produced during the downtime. However, the facility will continue to incur the fixed costs of
production associated with the affected operations.
> If, as part of its cooling water dependent operations, the facility generates electricity for its own use, and
some part of this self-generated electricity continues to be needed during downtime, the facility may need
to purchase replacement electricity.
Together, these effects may lead to a loss in pre-tax income, which EPA calculated and used as the cost to
Manufacturers for installation downtime in its analysis of facility impacts. EPA assumed that installation
downtime will affect facilities only through suspension of their electricity-generation activities, with no effect on
other facility processes. Specifically, EPA assumed that downtime requires Manufacturers to curtail electricity
generation and purchase power from the grid in order to continue operation. EPA calculated the cost of this
temporary suspension of power generation as the cost of purchasing replacement power plus the loss of any
revenues received from selling power, minus the variable costs of generating electricity. If a Manufacturer does
not sell power to the grid, then its cost of downtime is simply the cost of purchasing replacement power minus the
variable cost of generation.
EPA used information from the 316(b) survey to calculate the income loss in electric power-related operations.
The data sources and approach for the downtime loss calculation essentially are the same as described above for
the energy penalty effect. The analyses differ only in that the downtime analysis reflects full termination of
cooling water-dependent generation but only for the downtime period, while the energy penalty effect reflects a
partial reduction in cooling water-dependent generation but on an on-going basis following technology
installation. The data requirements include: (1) annual electric revenue reported as cooling water dependent, (2)
the fuel cost of electricity generation, which is assumed to be shed during the period of curtailed operations, (3)
the quantity of electricity consumed by the facility, (4) the quantity of electricity generated by the facility, and (5)
the unit price of replacement electricity. EPA calculated the pre-tax income loss from installation downtime as
follows:
1. Average annual electric revenue from cooling water-dependent generation is obtained from the facility
questionnaire and adjusted for inflation to 2011. This value is assumed to be the annual revenue loss in
electricity generation, from curtailment of cooling water-dependent operations.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix I: Energy Effects
2. Average annual fuel cost of electricity generation is obtained from the facility questionnaire and adjusted
for inflation to 2011. EPA assumes that this value is shed during the period of curtailed operations.
3. Calculate the quantity of replacement electricity to be purchased by the facility as the quantity of self-
generated electricity that is consumed by the facility. Calculate self-generated electricity consumed by the
facility as the lesser of (a) the facility's own electricity generation or (b) the electricity used within the
facility.
4. Calculate the cost of electricity purchased to replace self-generated electricity used by the facility by
multiplying the quantity of replacement electricity by the average electricity price, by state, for industrial
customers.
5. Calculate annual loss in pre-tax income for electric power-related operations as estimated revenue loss
from cooling water-dependent generation less estimated annual fuel cost of electricity generation plus
cost of electricity purchased to replace own-generated electricity.
6. Calculate pre-tax income loss in electric power-related operations, from installation downtime, by
multiplying the annual pre-tax income loss by the fraction of the year indicated as the net downtime
required for installing compliance equipment.
In some cases, EPA estimated a cost for replacement electricity that is less than a facility's fuel costs, resulting in
a negative cost (i.e., a gain in pre-tax income) from downtime. To avoid potentially understating the burden of
installation downtime, EPA set a floor of $0 for the cost of downtime.
Cost of Technology Installation Downtime to Society
EPA does not expect installation downtime to interrupt the production of goods at Manufacturers, but only to
interrupt their ability to produce their own power, requiring them to purchase replacement energy from the grid.
Thus, the primary cost of Manufacturers downtime - to facilities and society - results from the replacement of
electricity otherwise generated by facilities. To assess society's cost of downtime, EPA followed a similar method
to that described for the cost of the energy penalty to society (see page 1-6). The only difference is that for the
social cost of downtime, EPA calculated the cost of replacement electricity that Manufacturers would normally
generate and sell to the electric power grid as the price of purchasing replacement electricity (from item 4 in the
calculation steps above) less the cost to produce electricity (from item 2 in the calculation steps above). EPA did
not subtract facilities' cost of producing electricity for the energy penalty because it causes a net increase in
electricity requirements, while downtime only requires replacement of electricity that Manufacturers would
otherwise produce. Again, this approach assumes that the price for purchasing replacement energy reflects the
cost of generating electricity from the alternative supply sources.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix J: SIC to NAICS Data Conversion
Appendix J Mapping Manufacturers' Standard Industrial Classification
Codes to North American Industry Classification System Codes
At the time the 2000 Detailed Industry Questionnaire (DO) and the 1999 Industry Screener Questionnaire (ISO)
were designed and distributed, the United States used the Standard Industry Classification (SIC) framework for
assembling and reporting data by economic sector. Consequently, the 316(b) survey respondents were asked to
report their primary SIC codes. However, in 1997, the United States switched to the North American Industry
Classification System (NAICS) framework for industrial classification. To report and assess historical industry
trends in the earlier 316(b) rulemaking analyses, industry data for years after 1997 were mapped from the NAICS
framework back onto the SIC framework. Now that more than a decade of historical data is available in the
NAICS framework, EPA determined that it was appropriate to use the NAICS framework for the current analyses.
To use the 316(b) survey-based facility information, the Agency mapped facility-level 4-digit SIC codes onto 6-
digit NAICS codes to determine the industry to which to assign Manufacturers and for which to collect public
industry data.
Because there is not always a one-to-one relationship between an SIC and a NAICS code, EPA first used a
Manufacturer's NPDES permit identification number to obtain current information about the facility, including
facility's primary NAICS code. In the event that this information was not available or is unclear in the NPDES
database, EPA used the SIC code provided in the facility's survey response and SIC-to-NAICS crosswalk
provided by the U.S. Census Bureau to determine the appropriate NAICS code. When the crosswalk was not one-
to-one, EPA assigned the NAICS code with the largest share of value of shipments according to the 1997
Economic Census: Bridge Between NAICS and SIC (U.S. DOC, 1997).288
288 This bridge is available online at http://www.census.gov/epcd/ec97brdg/.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix K: Cost Pass-Through Analysis
Appendix K Cost Pass-Through Analysis
The impact on Manufacturers of the final rule and other options EPA considered will depend on the extent to
which regulated facilities are able to pass on compliance costs to customers through increased prices (cost pass-
through). This appendix presents the assessment of cost pass-through (CPT) potential for the six Primary
Manufacturing Industries.
EPA closely followed the methodology, and relied largely on the same data sources, used in the CPT analysis for
the previous 316(b) rule analyses (U.S. EPA, 2006; U.S. EPA, 201 lb). This appendix begins with a review of
approaches for assessing CPT potential associated with market-wide cost increase scenarios; it then discusses the
methodology and specific metrics used to assess CPT potential and provides the CPT assessment results for each
Primary Manufacturing Industry.
As was the case with the analysis conducted for the previous 316(b) rules, an assumption of zero CPT is
appropriate for analyzing the impact of the final rule and other options considered on facilities in the six Primary
Manufacturing Industries. For the economic/financial impact analysis, this assumption means that facilities must
absorb all compliance-related costs and operating effects (e.g., income loss from facility shutdown during
equipment installation) within their baseline cash flow and financial condition. To the extent that facilities would
be able to pass on some of the compliance costs to customers through price increases, the analysis using the zero
CPT assumption likely overstates the potential impact on regulated facilities.
K.1 The Choice of Facility-Specific versus Industry-Specific CPT Coefficients
When deciding which methodology to follow in conducting its cost-pass through analysis for the final rule, EPA
considered and rejected the two approaches of estimating facility-specific and industry-wide CPT rates as
infeasible and inappropriate before deciding to perform a market structure analysis which attempts to measure the
market power enjoyed by market players in each of the six industries. The factors EPA examined when
considering facility-specific CPT rates, and industry-wide CPT rates are presented in this section.
One method of examining the ability of a facility to pass-through compliance-related cost increases due to the
final rule and other options considered is to review the facility's historical performance in passing on previous
cost increases to consumers. For example, Ashenfelter et cil. (1998) estimate the CPT rate facing an individual
facility and distinguish that rate from the rate at which a facility passes through cost changes common to all
facilities in an industry, by regressing the price charged by a facility on both its costs and the costs of another
facility in the industry. The facility-specific CPT rate would relate a change in the prices charged by a specific
facility to a change in its production costs, assuming no changes in the production cost for rival producers of that
product. However, such an analysis is extremely complex. For example, in order to estimate facility-specific CPT
rates for every manufacturing facility included in the sample of 2000 Detailed Industry> Questionnaire (DO)
respondents, EPA would require, for each facility, detailed information on the products sold, the markets in which
these products are sold, as well as information identifying major competitors in each market. The DQ did not
obtain this information from surveyed facilities. And even if such information were available, the analysis would
remain highly challenging and subject to significant analytic error. As such, it is neither possible nor practical to
develop facility-specific CPT coefficients for Manufacturers.
Moreover, even if the Agency possessed the data necessary to estimate facility-specific CPT rates, these rates may
not be the appropriate measure of CPT potential for compliance-related cost increases stemming from the final
rule and other options considered. This regulation would force multiple facilities in each of Primary
Manufacturing Industry to incur compliance-related cost increases, which implies that for most facilities, the cost
increases would not apply only to them, but also to several of their competitors. Not surprisingly, previous studies
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix K: Cost Pass-Through Analysis
have found that the CPT rate for changes to an individual facility's cost differs from the rate at which a facility
would pass through cost changes that are common to all, or a substantial fraction of, facilities in an industry
(Ashenfelter et al., 1998). In general, the higher the share of facilities incurring the cost increase, or more
appropriately, the higher the share of total output produced by such facilities, the greater their ability will be to
pass on a greater portion of those costs to the consumer.
When an industry-wide cost shock occurs, an industry-wide CPT rate would be an appropriate and practical way
of assessing the potential of all facilities in that industry to pass through that cost increase to consumers (EPA,
2003). This rate provides an estimate of the change in each facility's output prices as a function of the increase in
its production costs, assuming that the same cost increase applies to all facilities in the industry. This rate is easier
to estimate than facility-specific CPT rates, assuming that perfect competition exists in the industry. Among other
things, perfect competition implies the existence of product homogeneity within the industry, homogeneity of
production technology among firms in the industry, and homogeneity of production costs among firms (i.e.,
pricing is at marginal cost). Under these conditions, the price response to a general industry-wide change in
production costs is likely to be industry-wide and similar across all firms. For example, in support of the
Economic, Environmental, and Benefits Analysis of the Final Metal Products & Machinery Rule (MP&M),
promulgated in 2003,289 EPA estimated industry-specific CPT rates because a large fraction of establishments in
these industries would be subject to the regulation. EPA regressed annual output price indices on annual input
cost indices for the MP&M industry (U.S. EPA, 2003). EPA confirmed the estimated CPT coefficients by a
market structure analysis that assessed, for each industry, the potential market power enjoyed by firms in the
industry and the consequent implications it had on their ability to pass through compliance-related costs.
Industry-wide CPT rates can be estimated for the analyzed manufacturing sectors based on the methodology used
for deriving industry-wide CPT rates for industries covered by the MP&M regulation, the 2006 Phase III final
rule, and the Proposed Existing Facilities Rule. As was the case with the previous 316(b) rules, because the final
rule and other options considered will affect only those facilities that operate a CWIS to withdraw cooling water
from surface waterbodies, only a subset of facilities in each industry sector would incur compliance-related cost
increases. As the cost increase associated with final rule, and other options considered, is not industry-wide, it is
questionable whether industry-wide CPT rates are appropriate for estimating the price response of regulated
facilities. If a substantial portion of production in each industry occurs at facilities not subject to the regulation,
then the use of industry-wide CPT rates may overstate the ability of facilities in these industries to pass-through
compliance-related costs to consumers.
To assess the reasonableness of using industry-wide CPT rates in the analysis of impacts to Manufacturers, EPA
estimated the share of total production in each of the six Primary Manufacturing Industries that occurs at
regulated facilities, using value of shipments, a measure of the dollar value of production. Because value of
shipments data were not collected using the DQ, these data were not available for the sample of Manufacturers;
therefore, the Agency used total revenue reported in the DQ, as a close approximation to value of shipments for
these facilities. EPA estimated the total revenue subject to the final rule by multiplying the revenue of surveyed
facilities (in $2011) by their respective facility sample weights and summing across all surveyed facilities (for
details on sample weights see Appendix H) 290 EPA obtained total value of shipments estimates from the 2010
Annual Survey of Manufactures (ASM) published by the U.S. Census Bureau.
As reported in Table K-l, the share of total value of shipments subject to the final rule varies by industry, ranging
from 2 percent in the Food and Kindred Products Industry to 48 percent in the Steel Industry. For four of the six
289 For details see Economic, Environmental, and Benefits Analysis of the Final Metal Products & Machinery Rule report available online
at http://water.epa.gov/scitech/wastetech/guide/mpm/upload/2003_l_3 l_guide_mpm_eeba_partl .pdf
290 For this calculation, EPA used technical weights and included facilities estimated to close in the baseline. For analysis of baseline
closures see Chapter 5: Economic Impact Analysis - Manufacturers.
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Appendix K: Cost Pass-Through Analysis
industries, significantly less than 50 percent of the total value of shipments would incur compliance costs. EPA
concludes for these industries, that the designated threshold for justifying the use of industry-wide CPT rates in
the economic/financial analysis has not been met. For the two industries - Steel and Aluminum - where the
percentage of total value of shipments subject to the final rule is less than, but close to, 50 percent, EPA concludes
that industry market structure should be taken into account in assessing CPT potential. Still, even for these
industries, it is questionable whether an industry-wide CPT estimate would be appropriate.
Given the inability to estimate facility-specific CPT rates and the finding that the use of industry-wide CPT rates
would not be appropriate for some, and perhaps all, of the Primary Manufacturing Industries, EPA conducted a
market-structure analysis to investigate the extent to which facilities in the Primary Manufacturing Industries have
sufficient market power to pass compliance-related costs on to consumers in the form of higher prices.
Table K-1:
Proportion of Value of Shipments Potentially Subject to Compliance-Related Costs
Associated with the Final Rule (Millions; $2011)

NAICS
Industry
Revenue for
Manufacturers Subject
to Final Rulea b
Total Value of
Shipments
Proportion of Total
Value of Shipments
Subject to Regulation
3313
Aluminum
$15,131
$32,966
45.9%
325
Chemicals and Allied Products
$102,914
$716,178
14.4%
31 I/3I2I
Food and Kindred Products
$16.8X1
$755,071
2.2%
322
Paper and Allied Products
$66,845
3.577
38.5%
3241 I
Petroleum Refiniim
$229,480
$601,212
38.2%
3311/2
Steel
$57,195
$118,089
48.4%
a. For this analysis, EPA used facility revenue as an appropriate surrogate in the absence of value of shipments for sample facilities. Revenue
estimates are the sum of weighted facility-level revenues and exclude revenue for baseline closures.

b. To compare regulated revenues with the industry value of shipments, EPA adjusted regulated revenues to 2010 using industry-specific Producer
Price Index (PPI) values published by the Bureau of Labor Statistics (BLS), and restated in 2011 dollars using GDP deflator published by the
Bureau of Economic Analysis (BEA).
Source: U.S. DOC, 2010 ASM; U.S. EPA, 2000

K.2 Market Structure Analysis
Information on the competitive structure and market characteristics of an industry provide insight into the likely
ranges of supply and demand elasticities and the sensitivity of output prices to input costs. For example, when
input costs increase, the profit-maximizing firm attempts to maintain its profits by increasing output prices, to the
extent permitted by market power. The amount of the cost increase the firm can pass on as higher prices depends
on the relative market power of the firm and its customers. The market structure analysis described in this section
attempts to measure the market power enjoyed by market players in each of the six industries. EPA combined this
analysis with information from industry review documents such as McGraw-Hill's U.S. Industry and Trade
Outlook to reach conclusions regarding the CPT ability of firms in each industry. The market structure analysis
consists of a review of economic data for the following four indicators of market power: industry concentration;
import competition; export competition; and long-term growth. Each of these indicators is discussed in detail
below. EPA notes that the impact of each of these four indicators of market power varies from industry to
industry. Furthermore, the results presented for each indicator must be interpreted with caution. Even though an
indicator for a particular industry may predict high CPT potential, the specific features of the industry may result
in the indicator having diminished significance in predicting market power.
K.2.1 Industry Concentration
The extent of concentration among a group of market participants is an important determinant of that group's
market power. An industry with many small firms typically has less market power than an industry with a few
large firms, because it is easier for a few large firms to collude, or act as though they have colluded, in production
and pricing decisions, than many small firms. All else being equal, highly concentrated industries would be more
likely to pass through a higher proportion of compliance costs that would result from the final rule.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix K: Cost Pass-Through Analysis
This analysis uses the Herfindahl-Hirschman Index (HHI) as a measure of market concentration. The HHI is
calculated by squaring the market share of each firm competing in the market and then summing the resulting
numbers.291 For example, for a market consisting of four firms with shares of thirty, thirty, twenty and twenty
percent, the HHI is 26 00 (302 + 302 + 202 + 202 = 26 00). The HHI takes into account the relative size and
distribution of the firms in a market and approaches zero when a market consists of a large number of firms of
relatively equal size. The HHI increases both as the number of firms in the market decreases and as the disparity
in size between those firms increases. Based on the U.S. Department of Justice (DOJ) guidelines for evaluating
mergers, an HHI under 1,000 indicates an unconcentrated market, an HHI between 1,000 and 1,800 indicates
moderate concentration, and an HHI in excess of 1,800 indicates concentrated markets.
The accuracy of any analysis of market power originating from industry concentration depends largely on
properly defining the relevant market. A well-defined market requires the inclusion of all competitors and the
exclusion of all non-competitors. Defining the relevant market too narrowly overstates market power, while
defining the market too broadly would underestimate it. The 4-digit SIC category and 6-digit NAICS, while not a
perfect delineation, are used most often by industrial organization economists in their studies because, among
publicly available data sources, these industries appear to correspond most closely to economic markets
(Waldman & Jensen, 1997). Therefore, Table K-2 below, reports industry concentration data for each of the 6-
digit NAICS codes that include at least one potentially regulated manufacturing facility for which DQ data are
available.
As shown in Table K-2, based on their HHI, 15 of the 6-digit NAICS markets292 would be unconcentrated, six
would be moderately concentrated, and only six would be concentrated according to the DOJ guidelines. Notably,
all sectors in the Steel Industry would be unconcentrated, which suggests that even though more than 50 percent
of value of shipments in the Steel Industry would potentially be subject to the final rule, the likelihood of
regulated facilities in this industry to pass compliance costs through to consumers is low.
Four of the six 6-digit NAICS sectors listed as being concentrated belong to the Chemicals and Allied Products
Industry; the other two sectors are in the Aluminum Industry. From a market power perspective, this seems to
suggest that at the 6-digit NAICS level, only these six NAICS sectors are sufficiently concentrated to argue that
their regulated facilities may possess sufficient market power to pass through a portion of their compliance costs -
assuming that competitor firms in the same industry do not incur similar cost increases.
291 EPA chose the Herfindahl-Hirschman Index for this analysis because it provides a more complete picture of industry concentration
compared to other measures such as the 4-firm and 8-firm concentration ratios. In contrast, the 4- and 8-firm concentration ratios do
not use the market share of all firms in the industry, and nor do they provide information about the distribution of firm size. For
example, if there were a significant change in the market shares among the firms included in the ratio, the value of the concentration
ratio would not change.
292 This includes 3-digit and 4-digit NAICS for Food and Beverage industries, respectively, because every 6-digit NAICS sector covered
by these two industries are expected to be affected by the final rule.
K-4
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Appendix K: Cost Pass-Through Analysis
Table K-2: Herfindahl-Hirschman Index for 6-Digit NAICS Sectors
NAICS
NAICS Description
Industry
HHI'"
Unconcentrated Markets (HHI < 1,000)
311
Food Manufacturing
Food Manufacturing
102
325998
All Other Miscellaneous Chemical
Product and Preparation Manufacturing
Chemicals
158
322299
All Other Converted Paper Product
Manufacturing
Paper
188
325188
All Other Basic Inorganic Chemical
Manufacturing
Chemicals
224
331222
Steel Wire Drawing
Steel
297
325199
All Other Basic Organic Chemical
Manufacturing
Chemicals
361
325211
Plastics Material and Resin
Manufacturing
Chemicals
400
331221
Rolled Steel Shape Manufacturing
Steel
402
331210
Iron and Steel Pipe and Tube
Manufacturing from Purchased Steel
Steel
436
325412
Pharmaceutical Preparation
Manufacturing
Chemicals
457
3121
Beverage Manufacturing
Food
483
322222
Coated and Laminated Paper
Manufacturnm
Paper
630
322130
Paperboard Mills
Paper
713
322121
Paper (except Newsprint) Mills
Paper
759
331 1 11
Iron and Steel Mills
Steel
786
3241 10
Petroleum Refineries
Petroleum
807
331314
Secondary Smelting and Alloying of
Aluminum
Aluminum
931

Moderately Concentrated
Markets (1,000 < HHI < 1,800)
322110
Pulp Mills
Paper
1,024
322224
Uncoated Paper and Multiwall Bag
Manufacturing
Paper
1,043
325311
Nitrogenous Fertilizer Manufacturing
Chemicals
1.136
325131
Inorganic Dye and Pigment
Manufacturing
Chemicals
1.265
325120
Industrial Gas Manufacturing
Chemicals
1,415
325411
Medicinal and Botanical Manufacturing
Chemicals
1,424
Concentrated Markets (1,800 < HHI)
331315
Aluminum Sheet, Plate, and Foil
Manufacturing
Aluminum
1,995
325611
Soap and Other Detergent
Manufacturing
Chemicals
2,025
325222
Noncellulosic Organic Fiber
Manufacturing
Chemicals
2,071
331312
Primary Aluminum Production
Aluminum
2.250
325181
Alkalies and Chlorine Manufacturing
Chemicals
2.392
325110
Petrochemical Manufacturing
Chemicals
2.535
Unknown
325312
Phosphatic Fertilizer Manufacturing
Chemicals
NA
331112
Electrometallurgical Ferroalloy Product
Manufacturing
Steel
NA
322122
Newsprint Mills
Paper
NA
325221
Cellulosic Organic Fiber Manufacturing
Chemicals
NA
331311
Alumina Refining
Aluminum
NA
a. The 2007 Economic Census is the most recent concentration data available.

b. 2007 Economic Census does not disclose HHI values for five of the analyzed 6-digit NAICS sectors: (1) NAICS 325312: Phosphatic Fertilizer
Manufacturing (a total of fifty companies), (2) NAICS 331112: Electrometallurgical Ferroalloy Product Manufacturing (a total of twenty companies), (3)
NAICS 322122: Newsprint Mills (a total of sixteen companies), (4) NAICS 325221: Cellulosic Organic Fiber Manufacturing (a total of fifteen companies),
and (5) NAICS 331311: Alumina Refining (a total of twelve companies)
Source: U.S. DOC, 2007EC

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Appendix K: Cost Pass-Through Analysis
To further examine the level of concentration in each of the analyzed six industries, EPA analyzed HHI at the
industry level as well. In general, while these estimates understate market power industry HHI should still provide
meaningful insight into the market power of firms in the industry because firms in each industry still produce
similar or related products (for example, paper products, chemicals, etc.).
Table K-3 shows that, at the industry level, the estimated HHI for five of the six Primary Manufacturing
Industries are quite small. Low HHI values imply that these industries have unconcentrated markets and within
these industries, individual firms do not enjoy much market power. Notably, the Chemicals and Allied Products
Industry has a low HHI, which suggests that the four 6-digit NAICS sectors with concentrated markets comprise a
small segment of the Chemicals and Allied Products Industry. Thus, it is reasonable to conclude that the majority
of regulated facilities in this industry have low market power. In addition, EPA notes that only 14 percent of
production in the Chemicals and Allied Products Industry would potentially be subject to compliance-related cost
increases, which suggests that the CPT potential of regulated facilities in this sector incurring such expenses
would be limited. As reported in Table K-3, the Aluminum Industry appears to be moderately concentrated. Thus,
based solely on an analysis of industry concentration, it would appear that regulated facilities in the Aluminum
Industry might enjoy moderate levels of market power, which may enable them to pass through costs at a more
than negligible rate. However, as cautioned at the beginning of the market structure analysis, an accurate
judgment of the market power held by firms in an industry must be reserved until all indicators have been
analyzed.
Table K-3: Herfindahl-Hirschman Index by Industry
NAICS
Industry
HHI'"
3313
Aluminum
1.045
325
Chemicals and Allied Products
1 14
31 I/3I2I
Food and Kindred Products
177
322
Paper and Allied Products
228
325
Chemicals and Allied Products
1 14
32411
Petroleum Refilling
807
3311/2
Steel
679
a. The 2007 Economic Census is the most recent concentration data available.
b. HHI values are as reported in the 2007 Economic Census for the 3- and 4-digit
NAICS codes and not value of shipments-weiglited HHI values for the profiled 6- and
5-digit NAICS codes.
Source: U.S. DOC, 2007 EC; U.S. EPA analysis for this report
K.2.2 Import Competition
Theory suggests that imports as a percent of domestic sales, or import penetration, are negatively associated with
market power because competition from foreign firms limits domestic firms" ability to exercise such power. Firms
that belong to sectors in which imports make up a relatively large proportion of domestic sales would therefore be
at a relative disadvantage in their ability to pass through costs compared to firms belonging to sectors with lower
levels of import penetration, the measure of import competition used in this analysis. Import penetration is
particularly relevant because foreign producers would not incur costs because of the final rule. In this market
structure analysis, EPA assumes that higher import penetration will generally imply that firms are exposed to
greater competition from foreign producers and would thus possess less market power to increase prices in
response to regulation-induced increases in production costs. EPA estimated import penetration ratios for each
industry as total imports in an industry divided by total value of domestic consumption in that industry; where
domestic consumption equals domestic production plus imports minus exports. Table K-4 reports import
penetration ratios based on 2010 ASM data for the six Primary Manufacturing Industries.
The estimated 2010 import penetration ratios vary by industry, ranging from 8 percent in the Food and Kindred
Products Industry to 30 percent in the Aluminum Industry. The estimated 2010 import penetration ratio for the
entire U.S. manufacturing sector (NAICS 31-33) is 28 percent. Considering that the United States is an open
K-6
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix K: Cost Pass-Through Analysis
economy, in sectors with import penetration ratios close to or above 28 percent, domestic firms most likely face
substantial competition from foreign firms. Such competition is likely to curtail the market power that domestic
firms would otherwise appear to possess, based strictly on a domestic market analysis. Further, given the fact that
foreign producers do not incur compliance cost increases from U.S. regulations, this finding would point to
reduced ability of domestic firms to pass through such costs. Thus, based on the import penetration ratios
presented in Table K-4, firms in all of the sectors except Aluminum appear to be in a position to pass through to
consumers a significant portion of compliance costs. However, given the relatively low HHIs for these sectors
(other than Aluminum), existing market competition among domestic firms most likely nullifies any favorable
influence that the lack of foreign competitors would have on increasing the market power of firms in these
industries. EPA also highlights the above average import penetration ratio for the Aluminum Industry, which
suggests low market power for firms in this industry. With respect to the Aluminum Industry, this fact may
offset - from a market power perspective - the finding of the industry being moderately concentrated. Thus, even
though there are relatively few domestic producers in the U.S. Aluminum Industry, the notable presence of
foreign producers in U.S. markets is likely to markedly reduce their market power.
Table K-4: Import Penetration by Industry, 2010
NAICS
Industry
Value of Imports
(Millions; $2011)a
Implied Domestic
Consumption
(Millions ;$2011)a b
Import
Penetration3'0
3313
Aluminum
$1 1.241
$32,966
29.7%
325
Chemicals and Allied Products
$180,147
$716,178
25.3%
311/3121
Food and Kindred Products
3,57.665
$755,071
7.6%
322
Paper and Allied Products
$21,490
77
12.6%
3241 1
Petroleum Refmiim
$63,134

9.8%
3311/2
Steel
$29,644
$1 18.089
22.5%
a. These revenues are the totals reported for the entire 3- and 4-digit NAICS codes and not just the sum of regulated 6-digit NAICS codes.
b. Implied Domestic Consumption = Value of Shipments + Value of Imports - Value of Exports.
c. Import Penetration = Value of Imports / Implied Domestic Consumption
Source: U.S. EPA analysis fortius report; U.S. DOC, 2010 *4SM; U.S. ITC, 2010

K.2.3 Export Competition
The final rule will not increase the production costs of foreign producers with which domestic firms must compete
in export markets. As a result, firms in industries that rely to a greater extent on export sales would have less
latitude to raise prices to recover compliance-related increases in production costs. They would therefore have a
lower CPT potential, all else being equal. This analysis uses export dependence, defined as the percentage of
shipments that an industry exports, to measure the degree to which a sector is exposed to competitive pressures
abroad in export sales. All else equal, firms in industries with relatively high export dependence will have lower
market power than those in industries with relatively low export dependence, due to their relatively larger reliance
on sales in export markets. Table K-5, below, reports export dependence ratios for the six industry sectors.
The estimated 2010 export dependence ratios for the Primary Manufacturing Industries vary by industry, ranging
from 3 percent in the Petroleum Refining Industry to 26 percent in the Chemicals and Allied Products Industry.
The estimated export dependence ratio for the entire U.S. manufacturing sector for the same year is 22 percent.
Thus, for all but one industry (Chemicals and Allied Products), the export dependence ratio is below the average
for the U.S. manufacturing sector. This finding implies that none of these industries would face strong
competitive pressures from foreign firms/markets in export market sales, and thus export dependence would not
diminish market power and CPT potential. However, this effect may not work as strongly in the opposite
direction, i.e., firms in an industry will have a comparatively high CPT potential simply because firms in that
industry are not active in export markets. From the standpoint of firms gaining market power, the finding of low
export dependence diminishes the importance of export competition as an indicator of market power. Thus, EPA
must rely on the other three indicators to gauge the amount of market power that firms in each industry are
expected to hold. For example, even though the Petroleum Refining and Food and Kindred Products Industries
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix K: Cost Pass-Through Analysis
have low export dependence, the low market concentration in these industries makes it likely that market power
held by individual firms is quite small.
Table K-5: Export Dependence by Industry, 2010
NAICS
Industry
Value of Export
(Millions; $2011)a
Value of Shipments
(Millions; $201 l)a
Export Dependenceb
3313
Aluminum
$6,182
$32,966
18.7%
325
Chemicals and Allied Products
SI 83.400
78
25.6%
311/3121
Food and Kindred Products
$58,385
$755,071
7.7%
322
Paper and Allied Products
$24,156
177
13.9%
3241
Petroleum Refining
$18,163

3.0%
3311/2
Steel
$16,058
$118,089
13.6%
a. These values are the totals reported for the entire 3- and 4-digit NAICS codes and not just the sum of regulated 6-digit NAICS codes.
b. Export Dependence = Value of Exports / Value of Shipments.
Source: U.S. EPA analysis fortius report; U.S. DOC, 2010 ASM; U.S. ITC, 2010
K.2.4 Long-Term Industry Growth
An industry's competitiveness and the ability of firms to engage in price competition are likely to differ between
declining and growing industries. Most studies have found that recent growth in revenue positively correlates with
profitability (Waldman & Jensen, 1997), which suggests a greater ability to recover costs fully. To examine trends
in long-term growth for each of the six industry sectors considered in this analysis, EPA estimated the average
annual growth rate in the constant dollar value of shipments between 1989 and 2010 as well as between 2000 and
2010 for each industry using data available from the U.S. Bureau of Census.293 EPA also calculated the average
annual growth rate for the economy as a whole, based on gross domestic product (GDP), as a threshold to
compare with growth in the industries. EPA expects regulated facilities in sectors with growth rates higher than
those experienced by the overall economy to be better positioned to pass through compliance costs rather than
being forced to absorb such cost increases in order to retain market share and revenue. As reported in Table K-6,
of the six Primary Manufacturing Industries, two industries - Paper and Allied Products and Aluminum -
experienced negative growth over both periods. The Petroleum Refining Industry experienced the largest growth,
displaying an annual growth rate of 5 percent between 1989 and 2010, and about 8 percent between 2000 and
2010. For the period 1989 to 2010, only the Petroleum Refining Industry grew at a rate greater than that of the
overall economy. For the more recent period, 2000 to 2010, all but two of the industries grew at a faster rate than
the overall economy. However, this comparison may be misleading, given the relatively weak performance of the
U.S. economy over this period. In particular, the absolute growth of these industries remains low when compared
with the total economy's growth over a longer period. From 1970 to 2010, the U.S. economy grew at an inflation-
adjusted annual rate of 2.8 percent, while from 1980 to 2010 the total economy grew at a rate of 2.7 percent (U.S.
EPA analysis for this report; U.S. BEA, 2012a). In comparison, only Steel's growth rate (2.7 percent) falls into
the range of long-term annual growth for the economy; however, the Steel Industry's growth rate does not exceed
the growth rate of the overall economy and therefore, would not indicate a relatively high rate of growth. In this
light, for all of these industries except for the Petroleum Refining Industry, EPA finds it is unlikely that firms
possess significant market power based on growing demand for their products. In effect, the long-term growth
performance of these five industries does not support a conclusion that regulated facilities in these industries
would be in a strong position to pass on a significant portion of their compliance costs. In contrast, the long-term
growth in the Petroleum Refining Industry indicates that firms in this industry may be better able to pass through
costs to consumers.
293 Hie period from 1989 to 2010 represents the two most recent decades that includes data consistent with the survey period for the 2000
Detailed Industry Questionnaire (1996-1998).
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Appendix K: Cost Pass-Through Analysis
Table K-6: Average Annual Growth Rate by Industry

Average Annual Growth Rate in Value of

Shipments
NAICS
Industry
1989 to 2010
2000 to 2010
3313
Aluminum
-4.9%
-1.9%
325
Chemicals and Allied Products
2.2%
2.2%
311/3121
Food and Kindred Products
1.2%
1.8%
322
Paper and Allied Products
-1.0%
-1.9%
32411
Petroleum Refining
4.6%
8.1%
3311/2
Steel
0.6%
2.7%
NA
U.S. Economy3
2.4%
1.5%
a. The average annual growth rate for the U.S. economy is based on GDP, not value of shipments.

Source: U.S. EPA analysis for this report; U.S. BEA, 2012a; U.S. DOC, 1989, 2000 and 2010 ASM
K.3 Conclusions
The analysis of individual indicators under the market-structure analysis revealed a few exceptions to the general
finding of low market power in all industries. However, considering the combined impact of all four indicators of
market power together with information on recent economic trends in these industries suggests that overall, firms
in each of the six industries hold relatively low market power and CPT potential. For example, the HHI for the
Aluminum Industry indicated that this sector is moderately concentrated, which would potentially allow regulated
facilities in this industry to pass through a significant portion of their compliance-related costs. In contrast,
however, the market structure analysis also found that the domestic Aluminum Industry witnessed a sustained
decline in production during the 1990s and faces stiff competition from foreign producers in its U.S. markets. As
discussed in the profile of this industry, in the early 1990s the domestic Aluminum Industry was affected by
reduced U.S. demand and the dissolution of the Soviet Union, which led to substantial increases in Russian
exports of aluminum. The recovery that followed was subsequently affected by the economic crises in Asian
markets in the second half of the 1990s, which along with growing Russian exports, again caused oversupply.
Demand for Aluminum Industry products declined again in 2000 through 2002, reflecting weakness in both the
U.S. and world economies, and again resulted in oversupply and declining financial performance. In 2003, the
U.S. economy began to recover, resulting in higher demand for aluminum and improving financial condition for
the Aluminum Industry through 2007. However, the recession that began in 2008 resulted in lower demand for
and production of aluminum, both in the United States and worldwide, and a consequent decline in the financial
performance of the Aluminum Industry.
Regulated facilities in the Aluminum Industry belong to either the Primary Aluminum Production segment
(NAICS 331311: Alumina Refining and NAICS 331312: Primary Aluminum Production) or the Secondary
Aluminum Production segment (NAICS 331314: Secondary Smelting and Alloying of Aluminum and NAICS
331315: Aluminum Sheet, Plate, and Foil Manufacturing) (for more information see Appendix A).The data
reported in the Aluminum Industry Profile indicate the Secondary Aluminum Production segment is less import
dependent and less concentrated than the Primary Aluminum Production segment. Further, while the Secondary
Aluminum Production segment has grown over the last two decades and especially in the last decade, the Primary
Aluminum Production segment has declined. Consequently, while domestic firms in the Secondary Aluminum
Production segment may be in a better position to pass some compliance-related costs to consumers than firms in
the Primary Aluminum Production segment, several factors combine to suggest that the Secondary Aluminum
Production segment has relatively low CPT potential (specifically, the general economic condition of the U.S.
Aluminum Industry as a whole throughout the last two decades). While the industry exhibits moderate-to-high
market concentration, there is also a rather high degree of import penetration and moderate export dependence.
294 In this appendix, average annual growth rate refers to a year-to-year, constant percentage growth mean, which is calculated as the
compound annual growth rate between the first and last values. This is the same concept as the geometric mean, if all of the individual
year-to-year values are the same as those used in calculating the constant percentage growth mean.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix K: Cost Pass-Through Analysis
This suggests overall, that domestic firms in this industry hold relatively low market power and are not likely to
have the ability to pass through significant portions of their compliance-related cost increases.
Regulated facilities in the Steel Industry belong either to the Steel Mills segment (NAICS 331111 and NAICS
331112) or to the Steel Products segment (NAICS 331210, NAICS 331221, and NAICS 331222). The Steel
Industry as a whole does not appear to be significantly subject to competition from foreign trade, implying some
potential for regulated facilities to pass on compliance costs to consumers. The Steel Products segment is
unconcentrated while the Steel Mills segment is moderately concentrated; however, the HHI Index for NAICS
331111, which contains the majority of regulated facilities, indicates that it is unconcentrated. The Steel Industry
as a whole is also unconcentrated. Based on the relatively low growth rates in the Steel Industry and low market
concentration, it is unlikely that domestic firms in this industry have the ability to pass through significant
portions of their compliance-related cost increases.
Summary
From the findings of the market structure analysis, EPA concluded that an assumption of zero CPT rate is
appropriate for all six Primary Manufacturing Industries for analyzing the final rule's economic impact. This
assumption is reasonable given the results of the market structure analysis and is superior to using industry-wide
CPT rates. In addition, EPA notes that by assuming a CPT rate of zero for all industries, the analysis of final rule
impacts is less likely to underestimate facility impacts - because the analysis assumes that facilities would absorb
one hundred percent of compliance costs. Thus, whereas an overstated CPT rate may erroneously underestimate
impacts for facilities incurring compliance-related cost increases, the use of a CPT rate of zero errs on the side of
caution, thus potentially overstating impacts to affected facilities.
Given that EPA estimates that much less than 50 percent of the total value of shipments in four of the six Primary
Manufacturing Industries will be subject to the final rule and the likelihood that these percentages represent upper
bound estimates, regulated facilities in these industries are not likely to be able to pass through to consumers a
material portion of their compliance costs. In the other two industries - Aluminum and Steel - EPA estimates that
46 percent and 48 percent of the total value of shipments, respectively, will be subject to the final rule. These
higher percentages of value of shipments that EPA estimates will be subject to the final rule imply more potential
for regulated facilities in these industries to pass through part of their compliance costs to consumers.
To validate these hypotheses, EPA undertook the market-structure analysis presented in the previous sections. In
general, the weight of evidence from the market-structure analysis suggests that firms in all six Primary
Manufacturing Industries are unlikely to possess significant levels of market power, thereby lending support to
EPA's hypothesis that most regulated facilities would not be in a position to pass through a significant portion of
compliance costs.
K-10
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
Appendix L Adjusting Baseline Facility Cash Flow
This appendix documents EPA's development and analysis of cash-flow adjustment factors used in the facility-
level baseline and post-compliance closure analyses. This analysis presents an updated version of the analysis
conducted for the previous 316(b) regulations, including the proposed rule. As was done for the proposed rule,
EPA used the Quarterly Financial Report (OFR) published by the U.S. Census Bureau as the primary data
source.295 The analysis for the final rule incorporates three additional years of data for 2009, 2010, and 2011,
beyond that used for the proposed rule.
EPA collected economic/financial data for manufacturing facilities subject to the final rule (regulated facilities or
Manufacturers) through the 2000 Detailed Industry Questionnaire (DO) and the 1999 Industry Screener
Questionnaire (ISO) (316(b) survey). The surveys collected these data for three years: 1996, 1997, and 1998. The
sample survey of Manufacturers and their financial data serve as models for testing the financial impact of the
final rule and options EPA considered. To provide valid insight into the ability of the six Primary Manufacturing
Industries296 to meet regulatory requirements without significant adverse financial impact, EPA sought to ensure
that the sample facility data reasonably reflect business conditions that might occur at the time of compliance.
EPA assessed two concerns it had that the facility survey data might yield erroneous conclusions:
1. Given that U.S. business conditions during the latter half of the 1990s, when the 316(b) survey was
conducted, were cyclically strong, EPA was concerned that business conditions might have been
abnormally favorable for some of the Primary Manufacturing Industries. If so, the business-performance
and valuation measures, which draw from survey data and support assessment of the burden of regulatory
compliance costs, might overstate industry's ability to bear these costs during more typical business
conditions. The resulting impact analysis might understate the potential impact of the regulatory analysis
options considered for the 316(b) regulations.
2. EPA was also aware from its profile analyses that some of the affected industries might be experiencing a
longer-term trend of deteriorating performance. Using sample facility data that do not reflect such
possible trends would again potentially overstate industry's ability to bear compliance costs and therefore,
understate the potential impact of the final rule and options EPA considered.
The Agency's assessment validated its concerns, so EPA developed a basis for adjusting survey financial data to
account for the short-term deviation from trend and non-neutral long-term trend.
L.1 Background: Review of Overall Business Conditions
As background for its analysis, EPA reviewed general economic data over the past several years to assess whether
business conditions during the 316(b) survey period (1996 - 1998) might be generally perceived as abnormally
favorable for the U.S. economy as a whole. This review confirmed EPA's concern.
Figure L-l - Figure L-3 present annual and average values for the analysis period of 1985 through 2011 for three
measures of general economic performance:
295 To develop adjustment factors for the previous Phase III proposed and final rules, the Agency used the Value Line Investment Survey
firm financial dataset published by the private independent financial research firm Value Line.
290 The six Primary Manufacturing industries are the Aluminum, Chemicals and Allied Products, Food and Kindred Products, Paper and
Allied Products, Petroleum Refining and Steel Industries.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
Figure L-l focuses on the growth trend of the broad economy, including all sectors. Growth stronger than the
average trend would indicate a strongly expanding economy and generally would indicate strong business
performance. This exhibit is based on data published by the Department of Commerce (DOC), Bureau of
Economic Analysis (U.S. BEA, 2012a).
Figure L-2 reports the rate of capital utilization for all manufacturing sectors. All else equal, when the rate of
capital utilization is higher than the average trend, demand for manufacturing output is strong and
manufacturing business performance would be generally strong. This exhibit is based on data published by
the U.S. Federal Reserve Bank (Federal Reserve Board of Governors, 2012d).
Figure L-3 reports the rate of growth in the Federal Reserve's Industrial Production Index, which is a measure
of the real output of the manufacturing industries. Growth stronger than the average trend would indicate a
strong expansion in the manufacturing industries and generally would indicate strong manufacturing business
performance. Like the preceding exhibit, this exhibit is based on data published by the U.S. Federal Reserve
Bank (Federal Reserve Board of Governors, 2012d).
In each case, 1996 to 1998 annual values are above the average trend line, indicating stronger overall economic
performance in the 316(b) survey data period than for the longer period presented in the charts. The data show a
consistent pattern over this three-year period:
> 1996: The values for 1996 are above the longer-term average trend but are the lower than the values for
1997, indicating that the manufacturing economy was in an upswing from 1996 to 1997.
> 1997: The values for 1997 are the highest of the three years.
> 1998: The values for 1998 are all lower than the values for 1997 and generally appear to be the beginning
of the downswing in economic performance that occurred in the latter part of the 1990s. In the case of
industrial production and capacity utilization in manufacturing industries, 1997 is the peak performance
year over the 1990s decade. This peak is followed by a decline in 1998 and subsequent years leading to
the recession in 2001. In the case of GDP growth, the fall-off in 1998 from 1997 is followed by one more
year of strong growth in 1999. During 2000 and 2001, GDP growth sharply falls. As the U.S. economy
began to recover during the first half of the last decade following the recession of 2001, so did production
in the Primary Manufacturing Sectors. The second half of the decade, however, once again experienced
an economic slowdown leading to the current recession. Even though the U.S. manufacturing sector
experienced some recovery after the recession of 2001, its performance never achieved the level of 1997.
L-2
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule Appendix L: Adjusting Baseline Facility Cash Flow
Figure L-1: Growth in Real Domestic Product, 1985-2011
6.0%
5.0%
4.0%
3.0%
2.0%
1.0%
—Year-to-Year Growth in GDP, Percent
—Averaae Annual Growth Rate
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May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule Appendix L: Adjusting Baseline Facility Cash Flow
Figure L-2: Capacity Utilization in Manufacturing Industries, 1985-2011
85.0%
Capacity Utilization
Average Capacity Utilization
83.0%
81.0%
79.0%
77.0%
75.0%
73.0%
71.0%
69.0%
67.0%
65.0%
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LA
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
Figure L-3: Growth in Industrial Production, 1985-2011
10.0%
Annual Growth Rate in Industrial Production
Average Annual Growth Rate
5.0%
0.0%
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ro -10.0%
-15.0%
L.2 Framing and Executing the Analysis
The objective of this analysis was to understand (1) the extent to which the business conditions and financial
performance of the Primary Manufacturing Industries reflected cyclically favorable conditions during the 316(b)
survey period and (2) whether these industries show a non-neutral longer term trend in economic/financial
performance - e.g., deterioration in performance over time independent of cyclical variation. If either or both of
these conditions were found, then the data used to test for these conditions would be used to adjust relevant
survey data items to a level consistent with normal business conditions and/or the longer term of performance.
EPA used the same data source and analytical approach as those used for the proposed rule. Specifically, EPA
used industry-level QFR data to infer the trend of performance in facility financial performance from industry-
level performance and adjusted facility-level financial data from the 316(b) survey based on analysis of the
industry-level performance. Although the industry-level information for adjusting facility data necessarily
represents a limitation in this analysis, the effort is warranted, given: (1) the potential for the facility impact
analysis to yield erroneous findings if it is based on data that reflect cyclically favorable conditions and (2) the
absence of facility data to support a more precise analysis.297 EPA was able to add three more years of QFR data -
2009, 2010, and 2011 - released since EPA conducted the analysis in support of the proposed rule.
297 For details on QFR data and other data sources EPA considered for this analysis, see Economic and Benefits Analysis for Proposed
Section 316(b) Existing Facilities Ride (EBA) available online at
http://water.epa.gov/lawsregs/lawsguidance/cwa/316b/upload/econandbenefits.pdf.
May 2014
L-5
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
L.2.1 Methodology for Development of ATCF Adjustment Factors
Similar to the proposed rule, EPA's overall approach was to analyze, for each industry group, the trend of
financial performance over a multi-year analysis period and to assess where the industry's financial performance
lay relative to that trend during the 316(b) survey data years of 1996 to 1998. For the final rule, EPA looked at the
24-year analysis period - 1988 through 2011. For each industry group, EPA used as analysis observations an
index of constant dollar-adjusted, after-tax cash flow for the relevant industry groups. EPA calculated a simple
regression of the index values against time, which provides a direct measure of the real (i.e., inflation-adjusted)
trend of financial performance over time for each industry group. EPA then compared the 1996 to 1998 average
of index values for each industry group with the trend values predicted from the estimated regression
coefficients - both for the 1996 to 1998 years and for 2011, which is the end of the analysis period. This allowed
EPA to determine the extent to which it should adjust 1996 to 1998 survey values to reflect (1) the deviation from
trend at 1996 to 1998 and (2) the trend from 1996 to 1998 to the end of the analysis period.
EPA followed these steps to calculate After-Tax Cash Flow (ATCF) adjustment factors using QFR:
> Choose variables, period of analysis, and industry sectors: EPA used quarterly Income (or Loss) After
Income Taxes (ATI) and Depreciation, Depletion, and Amortization of Property, Plant, and Equipment
(DDA) values, reported for either the Primary Manufacturing Industries or sectors within the industries,
as the basis for calculating ATCF for 24 years - 1988 through 2011 - for all of the sectors in the
following table, except for Pesticides and Fertilizers, and Resins and Synthetics. QFR data are available
for the Pesticides and Fertilizers sector only starting 1992. Consequently, EPA developed ATCF
adjustment factor for this sector using only 20 years of QFR data. QFR does not provide data specifically
for the Resins and Synthetics sector. Instead, these data are a part of the Basic Chemicals, Resins and
Synthetics sector. Therefore, EPA was unable to perform a separate QFR-based analysis for this sector
and used ATCF adjustment factor calculated for the Basic Chemicals sector for the Resins and Synthetics
sector (Table L-l).
Table L-1: Analysis Sectors and Corresponding Sectors Covered by QFR
Analysis Sector Name
QFR SIC
Sector
SIC Description
QFR NAICS
Sector
NAICS Description
Available for 1998 Q1 through 2001 03
Available for 2000 Q4 through 2008 Q4
Aluminum
333-336
Nonferrous Metals
3313,3314
Nonferrous Metals
Basic Chemicals; Resins and
Synthetics
281,282,286
Industrial Chemicals and
Synthetics
3251,3252
Basic Chemicals, Resins, and
Synthetics
Pharmaceuticals
283
Drugs
3254
Pharmaceuticals & Medicines
Resins and Synthetics1'
NA
NA
NA
NA
Pesticides and Fertilizers3
284, 285, 287,
289
Residual of Chemicals
3253, 3255,
3256, and 3259
Other Chemicals
Food and Kindred Products
22,21
Food & Kindred Products (Incl.
Tobacco 1
311,312
Food, Beverage, & Tobacco
Products
Paper and Allied Products
26
Paper & Allied Products
322
Paper
Petroleum Relininsi
29
Petroleum & Coal Products
324
Petroleum & Coal Products
Steel
331. 332. 329
Iron & Steel
3311,3312
Iron. Steel. & Ferroalloys
a. QFR does not provide data specifically for the Pesticides and Fertilizers sector. Instead, these data are a part of the Other Chemicals sector (SIC 284, 285,
287. and 289; NAICS 3253. 3255. 3256. and 3259)
b. QFR does not provide data specifically for the Resins and Synthetics sector. Instead, these data are a part of the Basic Chemicals, Resins and Synthetics
sector.
Source: U.S. DOC, 1998-2011 OFR; U.S. EPA analysis fortius report
> Adjust ATI and DDA values to constant dollars in 2011: EPA deflated all values to 2011 using the
GDP Deflator series published by the Bureau of Economic Analysis (U.S. BEA, 2012b).
L-6
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
> Calculate ATCF: EPA calculated quarterly ATCF values as quarterly ATI plus DDA for each industry,
and summed the resulting quarterly ATCF values to calculate annual ATCF values for 1988 through
2011.
> Generate ATCF index series:
¦ EPA first adjusted the ATCF series to eliminate negative values for each industry by adding to each
ATCF value in a given industry's 24-year series, the absolute value of the most negative ATCF value
for this industry, plus one. This adjustment has the effect of "vertically" shifting the ATCF values for
a given industry so that all values are positive while retaining the mathematical "shape" of the series
as needed for the trend analysis. This adjustment was necessary to prevent the undesirable inversion
of the ATCF index trend - calculated in the next step below - that would occur if a negative index
numerator is combined with a positive series in calculating the ATCF index series.
¦ EPA calculated ATCF index values for each year and industry by dividing each adjusted ATCF value
by the 24-year average of adjusted ATCF values.
> Calculate the time trend of ATCF index series: EPA regressed ATCF index values against year by
industry, to calculate the time trend of constant dollar ATCF over the period 1988 to 2011 (1992 to 2011
for the Pesticides and Fertilizers sector).
L.3 Analysis Results
Table L-2 summarizes the analysis results together with potential adjustments under varying interpretations of the
findings.
Table L-2: Statistical Significance of Regression Results and Potential Adjustments

Difference in Trend-
Difference in Trend-Predicted

Predicted ATCF Index and
ATCF Index at 2011 and

Statistically
Actual Index Values -
Actual Index Value at 1996-
Analysis Sector
P-Value
Significant?
both at 1996-19983
1998"
Aluminum
0.6148
no
-6.5%
NA
Basic Chemicals; Resins and Synthetics
078225
no
-iXT%
NA
Pharmaceuticals
oToooo
yes
20.0%
1444%
Resins and Synthetics0
NA
NA
NA
NA
Pesticides and Fertilizers
0.0005
yes
-25.7%
17.1%
Food and Kindred Products
0.0000
yes
TWo
38"o'%
Paper and Allied Products
0.0401
yes
Tu%
313%
Petroleum Refining
0.0011
yes
2L7%
93.0%
Steel
0.8483
no
-2^5%
NA
a. For sectors with statistically significant estimated trend factors, the "trend-predicted ATCF values" are the average of 1996-1998 predicted ATCF values
using the estimated non-zero time-trend factor. For sectors for which the estimated trend factor is not statistically significant, the "trend-predicted ATCF
values" are the simple 24-year average of ATCF index values -
i.e., the time-trend factor is assumed to be zero.

A negative value indicates that the actual value exceeds the trend-predicted ATCF value; a positive value indicates that the trend-predicted ATCF value
exceeds the actual value. In both instances, the reported percentage value is the adjustment that would be applied to bring the actual index value to the
1996-1998 trend-predicted value.

b. The "trend-predicted ATCF values" are at 2011 and are reported only for sectors for which the estimated time-trend factor is statistically significant. In
four instances, the estimated time-trend factor is positive and the trend-predicted ATCF index values at 2011 are higher than the actual index values at
1996-1998. In the case of the Paper and Allied Products sector, the estimated time-trend factor is negative and the trend-predicted ATCF index value at
2011 is lower than the actual index value at 1996-1998.

c. QFR does not provide data specifically for the Resins and Synthetics sector. Instead, these data are a part of the Basic Chemicals, Resins and Synthetics
Source: U.S. DOC, 1998-2011 QFR; U.S. EPA analysis for this report

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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
Several observations are relevant:
> The estimated trend value is not statistically significant for three of the eight analyzed sectors: Aluminum
(Figure L-4), Basic Chemicals, Resins and Synthetics (.Figure L-5), and Steel {Figure L-ll). For these
sectors:
¦ EPA decided not to use the estimated trend value in any adjustments, but to use simply the average
ATCF index values over the 24 years - i.e., a trend line with zero slope - as the basis of any
adjustment.
¦ The indicated direction of adjustment to bring their ATCF values to the 1996 to 1998 trend value is
negative - i.e., the ATCF adjustment would lower the estimated ATCF values for facilities in these
sectors.
¦ Consequently, EPA decided to adjust ATCF values for these sectors' facilities only to the 1996 to
1998 trend value. The downward adjustment of the ATCF values avoids overstating the ability of
facilities in these industries to comply with rule requirements.
> The estimated trend value is statistically significant for the other five sectors of the eight: Food and
Kindred Products (Figure L-6), Paper and Allied Products {Figure L-7), Pesticides and Fertilizers
{Figure L-8), Petroleum Refining {Figure L-9), and Pharmaceuticals {Figure L-10).
¦ Therefore, EPA could use the estimated trend line as the basis for adjustment either (1) to adjust the
survey-based ATCF values to trend at 1996-1998 or (2) to adjust ATCF values for the trend overtime
since the survey.
¦ For three of these sectors, Pharmaceuticals, Food and Kindred Products, and Petroleum Refining, the
calculated ATCF index values for 1996 through 1998 are roughly at or below the estimated trend
lines at 1996 to 1998 and the estimated trends show a steep increase in ATCF from 1996 through
1998 to 2011. On the other hand, the calculated ATCF index values for 1996 through 1998 for
Pesticides and Fertilizers are above the estimated trend line at 1996 to 1998, while the estimated trend
still shows a steep increase in ATCF from 1996 through 1998 to 2011. For Paper and Allied Products,
the calculated ATCF index value for is also above the estimated trend line but the estimated trend
shows a relatively steep decline in ATCF from 1996 through 1998 to 2011.
¦ The change in ATCF implied by the estimated trend lines occurs over too long a period and is too
large to reflect unchanging capital in an industry, in terms of number and/or size of facilities.
Although the trend values are statistically significant, for these reasons for four of the five sectors -
Food and Kindred Products, Pesticides and Fertilizers, Petroleum Refining, and Pharmaceuticals -
EPA decided not to adjust the survey-based ATCF values along the trend-i.e., from 1996 through
1998 to 2011. The estimated trend is positive and moving the survey-based ATCF along the trend
could have the effect of overstating the potential of facilities in these four sectors to comply with rule
requirements. As a result, the Agency decided to bring survey-based ATCF values for these sectors
only to the estimated trend at 1996 to 1998 and not adjust along the trend. On the other hand, for the
Pulp and Paper sector, EPA decided to adjust the survey- based ATCF values along the trend. Here,
the estimated trend is negative; not moving the survey-based ATCF along the trend could have the
effect of overstating the potential of facilities in this industry to comply with rule requirements.
Consequently, these adjustments from the original survey avoid overstating the potential of facilities
in these industries to meet rule requirements.
Table L-3 presents the cash flow adjustment factors developed based on the preceding findings and judgments.
The table also reports the adjustment factors used in the previous Phase III cost and economic impact analyses.
For Aluminum, Paper and Allied Products, Basic Chemicals, Resins and Synthetics, Pesticides and Fertilizers,
L-8
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Appendix L: Adjusting Baseline Facility Cash Flow
and Steel, the potential adjustment would reduce the survey-based ATCF values by the multiplicative factor. For
Food and Kindred Products, Petroleum Refining, and Pharmaceuticals the potential adjustment would increase
the survey-based ATCF values by the multiplicative factor. Because QFR does not provide information for the
Resins and Synthetics sector, EPA substituted the adjustment factor calculated for the Basic Chemicals, Resins
and Synthetics sector.
Table L-3: Potential ATCF Adjustment Factors
Analysis Sector
Adjustment Factors
Adjustments in Previous Analyses
To 1996-1998 Trend
or 2011 - Current
To 2003-P3Pa
To 2005-P3Fb
To 1996-1998
Trend - P4PC
Aluminum
NA
NA
0.9044
0.9346
Basic Chemicals; Resins and Synthetics
0.9228
1.1543
0.8501
0.8660
Pharmaceuticals

1.2526
1.2004
1.221S
Resins and Synthetics
1 1398
1.1948
0.8501
0.8660
Pesticides and Fertilizers
NA
NA
0.7420
0.7426
Food and Kindred Products
NA
NA
1.0355
1.0181
Food
NA
1 3835
NA
NA
Beverasies
NA
1.3076
NA
NA
Paper and Allied Products
1 0397
1.0386
0.8737
0.6700
Petroleum Refminsi
1.2480
1.4914
1.2304
1.2173
Steel
0.8056
0.9096
0.7539
0.7249
a. For more information on the development of these adjustments factors, see the 2004 Economic Analysis for the Proposed Section 316(b) Ride for Phase
III Facilities.
b. For more information on the development of these adjustments factors, see the 2006 Economic and Benefits Analysis for the Final Section 316(b) Phase
III Existing Facilities Rule.
c. For more information on the development of these adjustments factors, see the 2011 Environmental and Economic Benefits Analysis for Proposed Section
316(b) Existing Facilities Rule.
Source: U.S. DOC, 1998-2011 OFR; U.S. EPA analysis fortius report
The following eight charts depict the calculated ATCF Index Series and Trend-Predicted ATCF Index series for
the eight sectors representing the Primary Manufacturing Industries. The Trend-Predicted ATCF Index series is a
non-zero slope line and is labeled "Calculated Trend" for sectors for which the estimated time-trend factor is
statistically significant. For sectors for which the factor is not statistically significant, the Trend-Predicted Index
series is a zero slope line and is labeled "24-Yr Ave ATCF Index."
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
1.6
Figure L-4: ATCF Index Series and Calculated Trend - Aluminum
1.4
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
Figure L-5: ATCF Index Series and Calculated Trend - Basic Chemicals, Resins and Synthetics
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
Figure L-6: ATCF Index Series and Calculated Trend - Food and Kindred Products
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L-12
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
Figure L-7: ATCF Index Series and Calculated Trend - Paper and Allied Products
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May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
Figure L-8: ATCF Index Series and Calculated Trend - Pesticides and Fertilizers
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L-14
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
Figure L-9: ATCF Index Series and Calculated Trend - Petroleum Refining
2.2
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0.2
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May 2014
L-15
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
Figure L-10: ATCF Index Series and Calculated Trend - Pharmaceuticals
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L-16
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix L: Adjusting Baseline Facility Cash Flow
Figure L-11: ATCF Index Series and Calculated Trend-Steel
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May 2014
L-17
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
Appendix M Estimating Capital Outlays for Discounted Cash Flow
Analyses - Manufacturers
The analysis of economic impacts to Manufacturers involves calculation of the business value of sample facilities
on the basis of a discounted cash flow (DCF) analysis of operating cash flow as developed from the 316(b) survey
data.298 This appendix presents the details of the Capital Expenditure analysis, as performed and documented for
the previous 316(b) analyses, including proposed rule. EPA did not re-estimate the regression equation for the
analysis of the final rule, but did update some of the input data that is used to estimate Capital Expenditure based
on the regression analysis. These updates are described in Section M. 6. While the estimation of capital outlays
relies in part on data in the SIC framework and uses data from the Value Line dataset, which have been replaced
respectively by the NAICS framework and Quarterly Financial Reports (OFR) published by the U.S. Census
Bureau, EPA judges that the estimations of capital expenditures remain valid for the analysis of the current final
rule.299 As done for the proposed rule, this analysis was conducted for Manufacturers in the original set of
Primary Manufacturing Industries and does not include information for the Food and Kindred Products industry,
which was added as a primary industry for the 316(b) Phase III Final Rule analysis.3""
Business value is calculated on a pre- and post-compliance basis and the change in this value serves as an
important factor in estimating regulatory impacts in terms of potential facility closures. To be accurate in concept,
the business-value calculation should recognize cash outlays for capital acquisition as a component of cash flow.
However, the 316(b) survey did not request information from surveyed facilities on their cash outlays for capital
acquisition. Absent this data, EPA developed an estimate of cash outlays for capital acquisition. This appendix
describes the methodology EPA used to derive, for each sample facility, an estimate of cash outlays for capital
acquisition.
EPA Office of Water (OW) previously identified that the omission of cash outlays for capital acquisition from
DCF analyses may lead to overstatement of the business value of surveyed facilities and, as a consequence,
understatement of regulatory impacts in terms of estimated facility closures (U.S. EPA, 2003). In response to this
omission, the Office of Management and Budget suggested the adoption of depreciation expense as a surrogate
for cash outlays for capital replacement and additions. However, for several reasons EPA determined depreciation
to be a poor surrogate. First, depreciation is meant to capture the consumption/use of previously acquired assets,
not the cost of replacing, or adding to, the existing capital base. Therefore, depreciation is fundamentally the
wrong concept to use as a surrogate for capital outlays associated with capital replacement and additions. Second,
depreciation is estimated based on the historical asset cost, which may understate or overstate the real replacement
cost of assets. Third, both book and tax depreciation schedules generally understate the assets" useful life. Thus,
reported depreciation will overstate real depreciation value for recently acquired assets that are still in the
depreciable asset base, and conversely, understate the real depreciation value of assets that have expired from the
depreciable asset base but still remain in valuable use. Finally, depreciation does not capture the important
variations in capital outlays that result from differences in revenue growth and financial performance among
298 This analysis is limited to potentially affected facilities in SIC codes 26, 28, 29, and 33.
299 The prior analysis, and therefore this appendix, relied on classification of businesses in the SIC framework. Although other analyses
and presentations for the final rule have been updated to use the NAICS framework, this analysis continues to use the SIC framework
as the basis for business classification.
300 Although the Food and Kindred Products sector was ultimately included in the set of the Primary Manufacturing Industries, EPA
judged that it was not necessary to re-estimate the model with data for this additional industry because the model coefficients
originally estimated at 316(b) Phase III proposal did not vary by industry in a statistically significant way. EPA continues to rely on
this judgment as the basis for carrying forward the previously estimated regression relationship without inclusion of the Food and
Kindred Products sector as an explicitly analyzed sector.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
firms. Businesses with real growth in revenue will need to expand both their fixed and working capital assets to
support business growth, and all else being equal, growing businesses will have higher ongoing outlays for fixed
and working capital assets. Similarly, the ability of businesses to renew and expand their asset base depends on
the financial productivity of the deployed capital as indicated by measures such as return on assets (ROA) or
return on invested capital (ROIC). As a result, businesses with "strong" asset productivity will attract capital for
renewal and expansion of their asset base, while businesses with "weak" asset productivity will have difficulty
attracting the capital for renewal and expansion of the business' asset base. All else being equal, businesses with
strong asset productivity will have higher and businesses with weak asset productivity will have lower ongoing
outlays for capital.
As an approach to addressing the absence of data on cash outlays for capital acquisition to support the DCF
analysis, EPA estimated a regression model of capital outlays using reported capital expenditures and relevant
explanatory financial and business environment information for public-reporting firms in the original Primary
Manufacturing Industries. The Agency used the resulting model to estimate capital outlays for in-scope facilities,
which were then used in the DCF analyses to calculate business value of these facilities and estimate regulatory
impacts in terms of facility closures.301
This appendix discussed the methodology and data sources used to estimated capital outlays for Manufacturers,
and presents the findings from the regression analysis.302
M.1 Analytic Concepts Underlying Analysis of Capital Outlays
On the basis of general economic and financial concepts of investment behavior, EPA began its analysis by
outlining a framework relating the level of a firm's capital outlays to explanatory factors that:
> Can be observed for public-reporting firms - either as firm-specific information or general business
environment information - and thus be included in a regression analysis; and
> For firm-specific information, are also available for surveyed Manufacturers from the 316(b) survey.
EPA reviewed recent studies of the determinants of capital outlays to identify the explanatory concepts and
variables that might be used in and to specify the models for analysis. EPA's review of this literature generally
confirmed the overall approach to estimation of capital outlays and helped to identify additional specific variables
that other analysts found to contribute important information in the analysis of capital outlays (e.g., the decision to
test capacity utilization as an explanatory variable, see below, resulted from the literature review).
Table M-l summarizes the conceptual relationships between a firm's capital outlays and explanatory factors that
EPA sought to capture in this analysis. Specifically, this table outlines the concept of influence on capital outlays,
301 The approach and regression model described above are based largely on the approach and regression model developed in support of
the analysis of economic impacts for the Metal Products and Machinery Regulation (MP&M). This analysis provides a recent example
of the need to address the omission of capital acquisition cash outlay data from a DCF analysis. EPA notes that the Primary
Manufacturing Industries are similar to the industries analyzed in the MP&M analysis in that both sets are in the manufacturing sector.
In addition, the 316(b) survey and the MP&M survey instruments are similar in the information they ask; therefore, similar data are
available for the 316(b) manufacturers and MP&M survey facilities. As such, EPA relied heavily on prior experience from the MP&M
final regulation to estimate capital outlays for in-scope facilities.
302 Because the estimated regression model for Manufacturers is based on an earlier model developed for the MP&M final regulation,
much of the underlying research involved in the analytic development of the model had been previously completed and was not
required to be redone. Nonetheless, in order to present a lucid discussion of the analytic concepts underlying the model and the
rationale behind specifying variables for the analysis and specification of the regression model, a complete discussion of how the
regression model was developed is presented. During the course of the discussion, instances where prior experience gained during
estimating the regression model for the MP&M final regulation had a significant influence in the development of the current model are
clearly highlighted.
M-2
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Economic Analysis for Final 316(b) Existing Facilities Rule Appendix M: Estimating Capital Outlays
the general explanatory variable(s) that EPA identified to capture the concept in a regression analysis, and the
hypothesized mathematical relationship (sign of estimated coefficients) between the concept and capital outlays.
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
Table M-1: Summary of Factors Influencing Capital Outlays
Explanatory Factor/Concept To Be
Captured in Analysis
Translation of Concept to Explanatory Variable(s)
Expected
Relationship
Availability of attractive opportunities for
additional capital investment. A firm's
owners, or management acting on behalf of
owners, should expend cash for capital
outlays only to the extent that the expected
return on the capital outlays - whether for
replacement of, or additions to, existing
capital stock - are sufficient to compensate
providers of capital for the expected return
on alternative, competing investment
opportunities, taking into account the risk of
investment opportunities.
Historical Return On Assets of establishment as an indicator of investment
opportunities and management effectiveness, and, hence, of desirability to
expand capital stock and ability to attract capital investment. Use of a
historical variable implicitly assumes past performance is indicative of
future expectations.
Positive
Business growth and outlook as a
determinant of needfor capital expansion
and attractiveness of investment
opportunities. All else equal, a firm is more
likely to have attractive investment
opportunities and need to expand its capital
base if the business is growing and the
outlook for business performance is
favorable.
Revenue Growth, from the prior time period(s) to the present, provides a
historical measure of business growth and is a potential indicator of need for
capital expansion. Use of a historical variable implicitly assumes past
performance is indicative of future expectations.
Positive
Clearly, the theoretical preference is for a forward-looking indicator of
business growth and need for capital expansion. Options EPA identified
include Index of Leading Indicators and current Capacity Utilization, by
industry. Higher current Capacity Utilization may presage need for capital
expansion.
Positive
Importance of capital in business
production. All else equal, the more capital
intensive the production activities of a
business, the greater will be the need for
capital outlay to replenish, and add to, the
existing capital stock. More capital intensive
businesses will spend more in capital outlays
to sustain a given level of revenue over time.
The Capital Intensity of production as measured by the production capital
required to produce a dollar of revenue provides an indicator of the level of
capital outlay needed to sustain and grow production.
As an alternative to a firm-specific concept such as Capital Intensity of
production, differences in business characteristics might be captured by an
Industry Classification variable.
Positive
Life of capital equipment in the business.
All else equal, the shorter the useful life of
the capital equipment in a business, the
greater will be the need for capital outlay to
replenish, and add to, the existing capital
stock.
No information is available on the actual useful life of capital equipment by
business or industry classification. However, the Capital Turnover Rate, as
calculated by the ratio of book depreciation to net capital assets, provides an
indicator of the rate at which capital is depleted, according to book
accounting principles: the higher the turnover rate, the shorter the life of the
capital equipment. However, the measure is imperfect for reasons of both the
inaccuracies of book reporting as a measure of useful life, and as well the
confounding effects of growth in the asset base due to business expansion -
which will tend to lower the indicated turnover rate, all else equal, without a
real reduction in life of capital equipment.
As above, an alternative to a firm-specific concept, differences in business
characteristics might be captured by an Industry Classification variable.
Positive,
generally, but
with
recognition of
the potential
for counter-
trend effects
The cost of financial capital. The cost at
which capital - both debt and equity - is
made available to a firm will determine
which investment opportunities can be
expected to generate sufficient return to
warrant use of the financial capital for
equipment purchases. All else equal, the
higher the cost of financial capital, the fewer
the investment/capital outlay opportunities
that would be expected to be profitable and
the lower the level of outlays for
replacement of, or additions to, capital stock.
Preferably, measures of cost-of-capital would be developed separately for
debt and equity.
The Cost of Debt Capital, as measured by an appropriate benchmark interest
rate, provides an indication of the terms of debt availability and how those
terms are changing over time. Preferably, the debt cost/terms would reflect
the credit condition of the firm, which could be based on a credit safety
rating (e.g., S&P Debt Rating).
Negative
The cost of equity capital is more problematic than the cost of debt capital
since it is not directly observable for either public-reporting firms or, in
particular, private firms in the 316(b) manufacturers dataset. However, a
readily available surrogate such as Market-to-Book Ratio provides insight
into the terms at which capital markets are providing equity capital to
public-reporting firms', the higher the Market-to-Book Ratio, the more
favorable the terms of equity availability.
Negative
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
Table M-1: Summary of Factors Influencing Capital Outlays
Explanatory Factor/Concept To Be
Captured in Analysis
Translation of Concept to Explanatory Variable(s)
Expected
Relationship
The price of capital equipment. Hie price of
capital equipment - in particular, how capital
equipment prices are changing over time -
will influence the expected return from
capital outlays. All else equal, when capital
equipment prices are increasing, the
expected return from incremental capital
outlays will decline and vice versa.
However, although the generally expected
effect of higher capital equipment prices is to
remove certain investment opportunities
from consideration, the potential effect on
total capital outlay may be mixed. If
expected returns are such that the demand to
invest in capital projects is relatively
inelastic, the effect of higher prices for
capital equipment may be to raise, instead of
lower, the total capital outlay for a firm.
Index provides an indicator of the change in capital equipment prices.
Negative,
generally, but
with
recognition of
the potential
for counter-
trend effects
Source: U.S. EPA analysis for this report
M.2 Specifying Variables for the Analysis
Working from the general concepts of explanatory variables outlined above, EPA defined the specific explanatory
variables to be included in the analysis. A key requirement of the regression analysis is that the firm-specific
explanatory variables included in the regression analysis later be used as the basis for estimating capital
expenditures for Manufacturers. As a result, in defining the firm-specific variables, it was necessary to ensure that
the definition of variables selected for the regression analysis using data on public-reporting firms be consistent
with the data items available for Manufacturers. EPA's selection of firm-specific variables was further
constrained by the decision to use the Value Line Investment Survey (VL) as the source of firm-specific
information for the regression analysis (see Section M. 3).
Table M-2 reports the specific definitions of variables included in the analysis (both the dependent variable and
explanatory variables) as well as any additional data manipulations, the data sources, the estimation analysis
equivalent for Manufacturers (either the corresponding variable(s) in the 316(b) survey or other source outside the
survey), and any issues in variable definition.
Table M-2: Variables Used in the Capital-Expenditure Modeling Analysis
Variables for Re!
jression Analysis
Equivalent Used for
Manufacturers
Comment / Issue
Variable
Source
Calculation
Dependent Variable
Gross
Value Line
Obtained from VL as Capital
None: to be estimated
This value and all other dollar values in
expenditures

Spending per Share. CAPEX
based on estimated
the regression analysis were deflated to
on fixed

calculated by multiplying by
coefficients.
2002 using 2-digitSIC PPI values.
assets:

Average Shares Outstanding.

CAPEX,

includes

outlays to

replace, and

add to,

existing

capital stock

Explanatory Variables
Firm-Specific Variables
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
Table M-2: Variables Used in the Capital-Expenditure Modeling Analysis
Variables for Regression Analysis
Equivalent Used for
Manufacturers
Comment / Issue
Variable
Source
Calculation
Return On
Assets: ROA
Value Line
ROA = Operating Income /
Total Assets. Both Operating
Income, defined as Revenue
less Operating Expenses
(CoGS+SG&A), and Total
Assets were obtained directly
from VL.
From 316(b) survey:
Revenue less Total
Operating Expenses
(Material & Product
Costs + Production
Labor + Cost of Contract
Work + Fixed
Overhead + R&D +
Other Costs & Expenses)
Would have preferred an after-tax
concept in numerator and a deployed
production capital concept in
denominator. However, VL provides no
tax value per se and would require
calculation of tax using an estimated tax
rate, which could introduce error. Also
neither VL nor 316(b) survey data
provide sufficient information to get at
deployed production capital.
Revenue:
REV
Value Line
REV = Revenues. Revenues
directly available from VL.
From 316(b) survey:
Revenue
In the log-linear formulation this
variable captures percent change/growth
in revenues. However, the use of the
log-linear formulation, eliminates the
potential to set the growth term to zero
in estimating baseline capital outlays
for Manufacturers.
During the specification of the
regression model for the MP&M final
regulation, Total Assets was also tested
as a scale variable. Since it provided a
good, but not as strong, an explanation,
as REV it was not included in the final
specification. Based on this previous
finding, Total Assets was not
considered while specifying the
regression model.
Capital
Turnover
Rate: CAPT
Value Line
CAPT = Depreciation / Total
Assets. Depreciation and
Total Assets directly available
from VL.
From 316(b) survey:
Depreciation / Total
Assets
Would have preferred denominator of
net fixed assets instead of total assets.
However, VL provides detailed balance
sheet information for only the four most
recent years. Not possible to separate
current assets and intangibles from total
assets.
Capital
Intensity:
CAPI
Value Line
CAPI = Total Assets /
Revenue. Total Assets and
Revenue directly available
from VL
From 316(b) survey:
Total Assets / Revenue
As above, would have preferred net
fixed assets instead of total assets, but
needed data are not available from VL
for the full analysis period.
Market-to-
Book Ratio:
MV/B
Value Line
MV/B = average market price
of common equity (Price)
divided by book value of
common equity (Book Value
per Share). Price and Book
Value per Share directly
available from VL.
N/A (see
Comment/Issue)
During specification of the MP&M
regression model, MV/B was found to
highly correlated with other, more
important explanatory variables, which
makes sense, given that equity terms
would be derived from more
fundamental factors, such as ROA.
Thus, MV/B was omitted from the
MP&M regression model. As a result,
MV/B was not considered during the
specification of the 316(b)
manufacturers regression model which
eliminated the need to define an
approach to use this variable with
316(b) survey data.
General Business Environment Variables
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
Table M-2: Variables Used in the Capital-Expenditure Modeling Analysis
Variables for Regression Analysis
Equivalent Used for
Manufacturers
Comment / Issue
Variable
Source
Calculation
Interest on
10-year, A-
rated
industrial
debt:
DEBTCST
Moody's
Investor
Services
DEBTCST = annual average
of rates for each data year
Use average of
DEBTCST rates at time
of 316(b) survey.
10-year maturity, industry debt selected
as reasonable benchmark for industry
debt costs. 10 years became "standard"
maturity for industrial debt during
1990s.
Index of
Leading
Indicators:
ILI
Conference
Board
Monthly index series
available from Conference
Board. ILI = geometric mean
of current year values.
Use average of ILI
values at time of 316(b)
survey.
During specification of the MP&M
regression model, EPA found that ILI
and the CAPPRC (see below) are highly
correlated. Thus, ILI was omitted from
the MP&M regression model. As a
result, ILI was not considered during
the specification of the regression
model.
Capacity
Utilization by
Industry:
CAPUTIL
Federal
Reserve
Board
(Dallas
Federal
Reserve)
Monthly index series
available from Federal
Reserve. CAPUTIL = current
year average value.
Use average of
CAPUTIL values at time
of 316(b) survey.

Producer
Price Index
series for
capital
equipment:
CAPPRC
Bureau of
Labor
Statistics
(BLS)
Annual average values
available from BLS.
CAPPRC = current year
average value as reported by
BLS.
Use average of CAPPRC
values at time of 316(b)
survey.
BLS reports PPI series for capital
equipment based on "consumption
bundles" defined for manufacturing and
non-manufacturing industries. For this
analysis, EPA used the PPI series based
on the manufacturing industry bundle.
Source: U.S. EPA analysis for this report
M.3 Selecting the Regression Analysis Dataset
In addition to specifying the variables to be used in the regression analysis, EPA also needed to select the public-
firm dataset on which the analysis would be performed. As noted above, for this analysis EPA used VL data. The
decision to use VL as the source of firm-specific data for the analysis was driven by several considerations:
> Reasonable breadth of public-reporting firm coverage. The VL dataset includes over 8,500 publicly
traded firms and identifies principal business of these firms both by a broad industry classification (e.g.,
Paper/Forest) and by an SIC code assignment.
> Reasonable breadth of temporal coverage. VL provides data for 11 years - i.e., 1992-2002. Although
ideally EPA would have preferred a longer time series to include more years not in the "boom" business
investment period of the mid- to late-1990s.
> Reasonable coverage of concepts/data needed for analysis. The VL data includes a wide range of financial
data that are applicable to the analysis (VL provides 37 data items over the 11 reporting years; see
Attachment DB). However, because of the pre-packaged nature of the VL data, it was not possible to
customize any data items to support more precise definition of variables in the analysis. In particular,
EPA found that certain balance sheet items were not reported to the level of specificity preferred for the
analysis. Overall, though, EPA expects the consequence of using more aggregate, less-refined concepts
should be minor.
VL SIC-code definitions do not match the official SIC-code definitions generated by the U.S. Census Bureau;
however, in most instances a VL's SIC code can be reasonably matched to one or several Census-defined SIC
codes. To build the public-firm dataset corresponding to the original Primary Manufacturing Industries (SIC 26:
Paper and allied products, SIC 28: Chemicals and allied products, SIC 29: Petroleum and coal products, and SIC
33 Primary metal industries), EPA initially selected all firms included in the VL SIC-code families:
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
>
2600:
Paper/forest products,
>
2640:
Packaging and container,
>
2810:
Chemical (basic),
>
2813:
Chemical (diversified),
>
2820:
Chemical (specialty),
>
2830:
Biotechnology,
>
2834:
Drug,
>
2840:
Household products,
>
2844:
Toiletries/cosmetics,
>
2900:
Petroleum (integrated),
>
3311:
Steel (general), and
>
3312:
Steel (integrated)
This is the same dataset used for the previous 316(b) rules, including the proposed rule. In order to derive a
dataset of firms whose business activities closely match the activities of Manufacturers, EPA made or attempted
to make the following revisions to the initial dataset:
EPA found that the VL SIC code definition does not include categories that match SIC 331 and SIC 335
(combined together to form the aluminum sector in the original Phase III analysis). Since U.S. aluminum
companies are generally vertically integrated (S&P, 2001b), most aluminum companies own large bauxite
reserves and mine bauxite ore. As such, these firms are classified in VL under SIC 1000: Metals and mining. EPA
reviewed the business activities of firms listed in SIC 1000: Metals and mining, and included only those firms
described as aluminum companies in the regression analysis dataset.
EPA reviewed the business activities of firms listed in SIC 3400: Metal fabricating and found no firms whose
activities matched those described within the profiles of the original Primary Manufacturing Industries.303
EPA reviewed the business activities of firms listed in SIC 2840: Household products and SIC 2844:
Toiletries/cosmetics, and retained only those firms in the dataset whose activities matched those described within
the profiles of the original Primary Manufacturing Industries.
EPA deleted firms within SIC 2600: Paper/forest products whose business activities are solely limited to
timber/lumber production. These facilities are unlikely to use cooling water intake structures and therefore fall
outside the original Primary Manufacturing Industries.
EPA reviewed the business activities of firms listed in SIC 2830: Biotechnology and SIC 2834: Drug in order to
exclude firms that are exclusively research and development (R&D) firms and are unlikely to use cooling water
intake structures. However, based on the information provided by Value Line EPA was unable to segregate R&D
firms from the rest of the firms listed in these SIC codes.
EPA only retained firms in the VL dataset if they are situated in the U.S. or Canada, and for whom financial
information is available in U.S. dollars.
On inspection, EPA found that a substantial number of firms did not have data for the full 11 years of the analysis
period. The general reason for the omission of some years of data is that the firms did not become publicly listed
303 The profiles only focus on 4-digit SIC categories represented in the sample of facilities which received the 2000 Detailed Industry
Questionnaire.
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Appendix M: Estimating Capital Outlays
in their current operating structure - whether through an initial public offering, spin-off, divestiture of business
assets, or other significant corporate restructuring that renders earlier year data inconsistent with more recent
data - until after the beginning of the 11-year data period.304 As a result, the omission of observation years for a
firm always starts at the beginning of the data analysis period. This systematic front-end truncation of firm
observations in the dataset could be expected to bias the analysis in favor of the capital expenditure behavior
nearer the end of the 1990s decade. To avoid this problem, EPA removed all firm observations that have fewer
than 11 years of data. As a result, the dataset used in the analysis has a total of 2,244 yearly data observations and
represents 204 firms.
Table M-3 presents the number of firms by industry classifications.
Table M-3: Number of Firms by Industry Classifications
SIC Industry Classification
Number (if Firms
26: Paper and allied products
24
28: Chemicals and allied products
136
29: Petroleum and coal products
20
33: Primary metal industries
24
Source: U.S. EPA analysis for this report
M.4 Specification of Models to be Tested
On the basis of the variables listed above and their hypothesized relationship to capital outlays, EPA specified a
time-series, cross sectional model to be tested in the regression analysis. EPA's dataset consisted of 204 cross
sections observed over 11 years (1992 through 2002). The general structure of this model was as follows:
CAPEX,,, = /(ROA,,. REVifo CAPT,„ CAPI,,„ DEBTCST,, CAPPRC,. CAPUTIL,,) (M-l)
Where:
CAPEX,, = capital expenditures of firm in time period t;305
t = year (year = 1992, . . . , 2002);
i = firm /'(/' = 1, ... , 204);
j = industry classification j
ROA, , = return on total assets for firm /' in year I:
REV,, = revenue ($ millions) for firm i in year /:
CAPT, , = capital turnover rate for firm /' in year I:
CAPI, , = capital intensity for firm I in year I:
DEBTCST, = financial cost of capital in year I:
CAPPRC, = price of capital goods in year I:
CAPUTIL;, = the Federal Reserve Board's Index of Capacity utilization for a given industry j in year t.
304 When VL adds a firm to its dataset, it fills in the public-reported data history for the firm for the lesser of 11 years or the length of
time that the firm has been publicly listed and thus subject to SEC public reporting requirements.
305 All dollar values were deflated to 2002 using 2-digit PPI values.
May 2014 M-9
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EPA only tested log-linear model specifications for this analysis.306 The main advantage of the log-linear model is
that it incorporates directly the concept of percent change in the explanatory variables. Specifying the key
regression variables as logarithms permitted EPA to estimate directly as the coefficients of the model, the
elasticities of capital expenditures with respect to firm financial characteristics and general business environment
factors. The following paragraphs briefly discuss testing of the log-linear forms of the model. Parameter estimates
are presented for the final log-linear model only.
EPA specified a log-linear model, as follows:
ln(CAPEXu) = a + I[(3X ln(X,,,)| + I|7l. ln(Y,)| + s (M-2)
Where:
CAPEX,, = capital expenditures of firm year I:
(3X = elasticity of capital expenditures with respect to firm characteristic X;
X,-,. = a vector of financial characteristics of firm year I:
yy = elasticity of capital expenditures with respect to economic indicator Y;
Y, = a vector of economic indicators, year I: for CAPUTIL, Y is also differentiated by industry
classification
8 = an error term; and
ln(x) = natural log of x
Based on this model, the elasticity of capital expenditures with respect to an explanatory variable, for example,
return on assets is calculated as follows:
E(CAPEX)=dia{CfEX) = d{CAPEX)!CAPEX
v 7 d\n{ROA) d(ROA)/ROA
Since logarithmic transformation is not feasible for negative and zero values, such values in the VL public firm
dataset required linear transformation to be included in the analysis. The following variables in the sample
required transformation:
CAPEX: Eighteen firms in the sample reported zero capital expenditures at least in one time period. EPA set these
expenditures to $ 1.
REVENUE: Seven firms reported negative revenues in at least one time period. Because these are likely due to
accounting adjustments from prior period reporting, EPA set negative revenues for these firms to $ 1.
ROA: the values for return on assets in the public firm sample range from -2.9 to 0.7. Approximately 34 percent
of the firms in the dataset reported negative ROAs in at least one year. To address this issue while reducing
306 While specifying the MP&M regression model, EPA tested both linear and log-linear model specifications. The pattern of coefficient
significance was found to be better in the log-linear model. In addition, the log-linear model offered advantages in terms of retention
of early time period observations (by eliminating the need to use percent change variables) and variable specifications, and helped to
reduce outlier effects in the model. As a result, EPA selected a log-linear specification as the final regression model for the MP&M
final regulation. Based on these reasons and the similarity of industry sectors analyzed for the two regulations, EPA decided to test
only log-linear model specifications for the Phase III regression model.
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potential effects of data transformation on the modeling results, EPA used the following data transformation
approach:307
> EPA excluded 27 firms with any annual ROA values below the 95th percentile of the ROA distribution
(i.e., ROA#- 0.51).
> EPA used an additive data transformation to ensure that remaining negative ROA values were positive in
the logarithm transformation. The additive transformation was performed by adding 0.51 to all ROA
values.
As a result of the data transformation procedures outlined above, the VL public firm dataset on which the
regression model is based was reduced to 177 firms (204 - 27 firms) and 1,947 yearly data observations.
The analysis tested several specifications of a log-linear model, including models with the intercept and slope
dummies for different industrial sectors and models with the intercept suppressed.308 Slope dummies were used to
test the influence of industry classification on the elasticity of capital expenditures with respect to an explanatory
variable: e.g., using the product of an industry classification dummy variable and CAPPRC to test whether certain
industries responded differently to change in price of capital equipment over time. Following review of the
different models tested, EPA concluded that the estimated coefficients did not vary, significantly, by industry and
thus selected the simple log-linear model, with the intercept and no slope dummies as the basis for the 316(b)
manufacturers capital expenditures analysis. The results for this model are summarized below.
Cross-sectional, time-series datasets typically exhibit both autocorrelation and group-wise heteroscedasticity
characteristics. Autocorrelation is frequently present in economic time series data as the data display a "memory"
with the variation not being independent from one period to the next. Heteroscedasticity usually occurs in cross-
sectional data where the scale of the dependent variable and the explanatory power of the model vary across
observations. Not surprisingly, the dataset used in this analysis had both characteristics. Therefore, EPA estimated
the specified model using the generalized least squares procedure. This procedure involves the following two
steps:
First, EPA estimated the model using simple OLS, ignoring autocorrelation for the purpose of obtaining a
consistent estimator of the autocorrelation coefficient (p);
Second, EPA used the generalized least squares procedure, where the analysis is applied to transformed data. The
resulting autocorrelation adjustment is as follows:
= Zi?t - pZu_i (M-4)
where Zit is either dependent or independent variables.
EPA was unable to correct the estimated model for group-wise heteroscedasticity due to computational
difficulties. The statistical software used in the analysis (LIMDEP) failed to correct the covariance matrix due to
307 While specifying the MP&M regression model EPA conducted a sensitivity analysis to examine the degree to which the estimated
model was affected by this data transformation. Results of this analysis showed that the data transformation produces results that are
compatible with a model considering only positive ROA values and a model considering all ROA values. As a result, the Phase III
regression model utilized the same data transformation procedure.
308 While specifying the MP&M regression model, EPA also tested specifications that included the following structural modifications: (1)
testing contemporary vs. lagged specification of certain explanatory variables: e.g., using prior, instead of current period revenue,
REV, as an explanatory variable; (2) testing scale-normalized specification of the dependent variable: e.g., using CAPEX/REV as the
dependent variable instead of simple CAPEX; (3) testing flexible functional forms that included quadratic terms; and (4) testing
additional explanatory variables including the index of 10 leading economic indicators (ILI) and market-to-book ratio (MV/B).
Because EPA found that these structural modifications either did not improve the fit of the MP&M regression model or resulted in the
introduction of multicollinearity among variables, these structural modifications were not tested while specifying the Phase III
regression model.
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Appendix M: Estimating Capital Outlays
the very large number of groups (i.e., 177 firms) included in the dataset. Application of other techniques to correct
for group-wise heteroscedasticity was not feasible due to time constraints. The estimated coefficients remain
unbiased; however, they are not minimum variance estimators. Regression results reveal strong systematic
elements influencing capital expenditures: the analysis finds both statistically significant and intuitive patterns
that influence firm's investment behavior. We find a strong systematic element of capital expenditures variation
that allows forecasting of capital expenditures based on firm and business environment characteristics.
Table M-4 presents model results. The model has a fairly good fit, with adjusted R2 of 0.81. All coefficients have
the expected sign and all but one variable (cost of debt capital) are significantly different from zero at the 95th
percentile.
Table M-4: Time Series, Cross-Sectional Model Results
Variable
Coefficient
t-Statistics
Constant
21.880
2.618
Ln(ROA)
0.526
3.964
Ln(REV)
1.129
58.450
Ln(CAPT)
0.687
11.085
Ln(CAPI)
1.078
18.491
Ln(DEBTCST)
-0.789
-1.605
Ln(CAPPRC)
-5.957
-4.369
Ln(CAPUTIL)
1.716
2.842
Autocorrelation Coefficient
P
0.385
18.402
Source: U.S. EPA analysis for this report
The empirical results show that among the firm-specific variables, the output variable (REV) is a dominant
determinant of firms' investment spending. A positive coefficient on this variable means that larger firms invest
more, all else equal, which is clearly a simple expected result. In addition, as expected, firms with higher financial
performance and better investment opportunities (ROA) invest more, all else equal: for each one percent increase
in ROA, a firm is expected to increase its capital outlays by 0.53 percent. Other firm-specific characteristics were
also found important and will aid in differentiating the expected capital outlay for 316(b) manufacturers facilities
according to firm-specific characteristics. Firms that require more capital to produce a given level of business
activity (i.e., firms that have high capital intensity, CAPI) tend to invest more: a one percent increase in capital
intensity leads to a 1.08 percent increase in capital spending. Higher capital turnover/shorter capital life (CAPT)
also has a positive effect on investment decisions: a one percent increase in capital turnover rate translates to a
0.69 percent increase in capital outlays.
The model also shows that current business environment conditions play an important role in firms' decision to
invest. Negative signs on the capital price (CAPPRC) and debt cost (DEBTCST) variables match expectations,
indicating that falling (either relatively or absolutely) capital equipment prices and less costly credit are likely to
have a positive effect on firms' capital expenditures. The most influential factor is capital equipment prices for
manufacturing facilities. A one percent increase in the capital price index (CAPPRC) leads to a 5.96 percent
decrease in capital investment. Capacity utilization is also an influential factor: a one percent increase in the
Federal Reserve Index of Capacity Utilization for the relevant industrial sector (CAPUTIL) leads to a 1.7 percent
increase in capital investments. The fact that these systematic variables are significant in the regression analysis
means that EPA will be able to control for economy- and industry-wide conditions in estimating capital outlays
for Manufacturers.
M.5 Model Validation
To validate the results of the regression analysis, EPA used the estimated regression equation to calculate capital
expenditures and then compared the resulting estimate of capital expenditures with actual data. EPA used two
methods to validate its results:
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
> EPA used median values for explanatory variables from the VL data as inputs to estimate capital
expenditures and then compared the estimated value to the median reported capital expenditures, and
> EPA used 316(b) survey data to estimate capital expenditures and then compared the estimated values to
depreciation reported in the survey.
First, EPA estimated capital expenditures for a hypothetical firm based on the median values of the four
dependent variables from the VL data and the relevant values of the three economic indicators. The estimated
capital expenditures for this hypothetical firm are $43 million. EPA then compared this estimate to the median
value of capital expenditures from the Value Line data. The median capital expenditure value in the dataset is $36
million, which provides a close match to the estimated value. This is not surprising since the same dataset was
used to estimate the regression model and to calculate the median values used in this analysis.
EPA also used 316(b) survey data to confirm that the estimated capital expenditures seem reasonable. Because the
316(b) survey does not provide information on capital expenditures, EPA compared the capital expenditure
estimates to the depreciation values reported in the survey. Depreciation had been proposed as a possible
surrogate for cash outlays for capital replacements and additions. However, depreciation does not capture
important variations in capital outlays that result from differences in firms' financial performance.
For this analysis, EPA chose a representative facility from each of the original Primary Manufacturing Industries
for model validation. The selected facility for each sector corresponds as closely as possible to the hypothetical
median facility in the sector based on the distribution of facility revenues and facility return on assets. For each of
the facilities, EPA estimated capital expenditures using the estimated regression equation and facility financial
data. Table M-5 shows the estimated regression coefficients, financial averages for the original Primary
Manufacturing Industries, estimated facility capital expenditures, reported facility depreciation, and the
comparison of capital expenditures and depreciation.
As shown in Table M-5, the estimated model provides reasonable estimates of capital expenditures.
Table M-5: Estimation of Capital Outlays: Median Facilities Selected by Revenue and ROA Percentiles

Difference

between
Sectors
Pre-Tax
Return
on
Assets
(ROA)
Revenue
($2004,
millions)
Capital
Turnover
Rate
Capital
Intensity
Cost
of
Debt
Price of
Capital
Goods
Capacity
Utilization
Estimated
Capital
Expenditures
($2004,
millions)
Depreciation
($2004,
millions)
Depreciation
and Capital
Expenditures
($2004,
millions)
Coefficient

Intercept
0.53
1.13
0.69
1.08
-0.79
-5.96
1.72

(21.88)

Paper and
allied
0.16
252.00
0.09
0.89
7.71
137.6
0
86.24
$19.54
$16.73
($2.80)
products

Chemicals

137.6
0

and allied
0.27
244.59
0.06
1.14
7.71
79.36
$15.73
$14.69
($1.04)
products

Petroleum
and coal
0.22
1516.0
1
0.05
0.59
7.71
137.6
0
91.88
$47.03
$66.95
$19.93
products

Primary
metals
0.09
458.46
0.04
0.93
7.71
137.6
0
88.77
$16.07
$19.21
$3.14
industries

Food and
kindred
0.37
292.56
0.06
0.29
7.71
137.6
0
80.46
$4.82
$4.52
($0.30)
products

Source: U.S. EPA analysis for this report
May 2014
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Appendix M: Estimating Capital Outlays
One of the possible implications of the hypothesized relationships and estimated coefficient values from the prior
analysis is that a facility's predicted capital expenditures might be expected to increase relative to the facility's
actual depreciation as the facility's ROA increases. An extension of this hypothesis is that, at lower ROA values,
predicted capital expenditures would be less than the depreciation but that at higher ROA values, predicted capital
expenditures exceed depreciation. These hypotheses are consistent with the expectation that businesses with
higher financial performance will have relatively more attractive investment opportunities and are more likely to
attract the capital to undertake those investments. EPA examined whether these relationships occur in the
Manufacturers. Specifically, EPA calculated the predicted capital expenditure for each in-scope facility and
compared these values to the facilities' reported depreciation values. To remove the scale effect of revenue, EPA
normalized both the predicted capital expenditure and reported depreciation values by dividing by the three-year
average of revenue for each facility. EPA then estimated the simple linear relationship of the resulting revenue-
normalized capital expenditure and deprecation values against facility ROA. The five graphs on the following
pages present, for each of the five primary two-digit SIC code sectors, the normalized capital expenditure and
deprecation values, and the estimated trend lines for each sector's depreciation and capital expenditures with
respect to ROA.309 The graphs indicate the following:
The Paper and Allied Products (SIC 26) graph shows depreciation exceeding predicted capital expenditure at low
ROA values but this relationship reverses with predicted capital expenditure exceeding depreciation as ROA
increases. Thus, the calculations for these facilities match the hypothesized relationship.
The Chemicals and Allied Products (SIC 28) graph also shows depreciation exceeding predicted capital
expenditure at low ROA values, but again the relationship reverses with predicted capital expenditure exceeding
depreciation as ROA increases. This predicted relationship is observed more strongly for facilities in the
Chemicals and Allied Products industry than in the Paper and Allied Products industry.
The Petroleum and Coal Products (SIC 29) graph shows predicted capital expenditures exceeding depreciation
over the ROA range analyzed. However, the extent of difference does not materially change as ROA increases.
The Primary Metal Industries (SIC 33) graph also shows predicted capital expenditures exceeding depreciation
over the ROA range analyzed. However, unlike for the Petroleum and Coal Products facilities, the amount by
which predicted capital expenditures exceeds depreciation increases as ROA increases, thus matching the
hypothesized relationship.
The Food and Kindred Products (SIC 20) graph also shows that calculations for these facilities match the
hypothesized relationship, where predicted capital expenditures exceed depreciation over the ROA range
analyzed. The consistency of this result, as well as the CAPEX estimation in Table M-5 above, is notable to the
extent that it demonstrates the model's overall applicability across industries, as facility data from SIC 20 were
not used for model specification.
In summary, with the exception of facilities in the Petroleum and Coal Products industry, the estimated model
produces capital expenditure values that increase relative to reported depreciation with increasing ROA, which
matches the hypothesized relationship.
309 For presentation purposes, two outlier facilities were excluded from the graph for SIC 28: Chemicals and allied products, and one
outlier facility was excluded from the graph for SIC 26: Paper and allied products.
M-14
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
Figure M-1: Comparison of Estimated Capital Outlays to Reported Depreciation for 316(b) Manufacturers Survey
Facilities in the Paper and Allied Products Sector
Q
<3
0.02
ft
-0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 0.50
Return on Assets
~ DEPR
- linear (DEPR)
linear (C APEX)
Source: U.S. EPA analysis for this report
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
Figure M-2: Comparison of Estimated Capital Outlays to Reported Depreciation for 316(b) Manufacturers Survey
Facilities in the Chemicals and Allied Products Sector
-9-44-
V
OS
to
-o
3
0
a
a
0.12 -
0.10 -
0.04-
0.02-
-OrW-
-0.20
0.00
0.20
0.40
0.60 0.
Return onsets
1.00
1.20
1.40
~ EEPR
CAP EX
¦ Linear (EEPR)
Linear (CAPEX)
Source: U.S. EPA analysis for this report
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
Figure M-3: Comparison of Estimated Capital Outlays to Reported Depreciation for 316(b) Manufacturers Survey
Facilities in the Petroleum and Coal Products Sector
-9-44-
V
OS
to
-o
a
a
=
0
a
a
0.14
0.12 -
0.10 ¦
0.08 ¦
0.06 ¦
0.04-
0.02

, ~ ¦ . *
-0.10
0.00
0.10
0.20 0.30
Return on Assets
0.40
0.50
EEPR ¦ CAP EX Linear (EEPR)
Linear (CAPEX)
Source: U.S. EPA analysis for this report
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
Figure M-4: Comparison of Estimated Capital Outlays to Reported Depreciation for 316(b) Manufacturers Survey
Facilities in the Primary Metal Industries Sector
-Qt±Q-
V
OS
to
-o
53
3
0
a
a
«» 0.09
0.08
0.07
0.06
0.05
0.04
0.03
*0.02
0.01
-OrW-
-0.10
0.00
0.10
0.20 0.30
Return onsets
0.40
0.50
0.60
0.70
~ EEPR
CAP EX
¦ Linear (EEPR)
Linear (CAPEX)
Source: U.S. EPA analysis for this report
M-18
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
Figure M-5: Comparison of Estimated Capital Outlays to Reported Depreciation for 316(b) Manufacturers Survey
Facilities in the Food and Kindred Products Sector
0.12
B.
ft
0
0.10 -
0.06 -
0.04 -
0.02 -
-ftflO-
~~
-0.20
0.00
0.20
0.40
0.60 0.S
Return on Assets
l.OO
1.20
1.40
1.60
~ DEPR ¦ CAPEX Linear (DEPR)-
-Linear (CAPEX)
Source: U.S. EPA analysis for this report
M.6 Updating Inputs to Estimate Capital Outlays for the Final Rule
For the analysis of the final rule and other options considered, EPA used the 316(b) survey data reported for
1996-1998; the Agency restated these values in 2011 dollars using GDP Deflator series published by the U.S.
Bureau of Economic Analysis.
In the previous analyses, for the "General Business Environment" explanatory variables, EPA used a 3-year
average of data reported for 1996-1998. For the current analysis, EPA updated these "General Business
Environment" variables to the average of values over the period 1999-2010, the period between the end of the
survey data and the time period of the final rule analyses. For DEBTCST, EPA took an average of the yield on
10-year BAA-rated bonds from 1999-2010 from the Federal Reserve; for CAPPRC, EPA averaged the PPI for
capital goods from 1999-2010 from the Bureau of Labor Statistics; and for CAPUTIL, EPA averaged, by industry
segment, annual average capacity utilization from the U.S. Census. Using this relatively long-term average for
May 2014
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Appendix M: Estimating Capital Outlays
these three business environment variables is intended to account for changes in facilities' operating environment
over this period.
Attachment A Historical Variables Contained in the Value Line Investment Survey
Dataset
All variables are provided for 10 years (except where a firm has been publicly listed for less than 10 years):
> Price of Common Stock
> Revenues
> Operating Income
> Operating Margin
r Net Profit Margin
> Depreciation
> Working Capital
> Cash Flow per share
> Dividends Declared per share
> Capital Spending per share
> Revenues per share
> Average Annual Price-Earnings Ratio
> Relative Price-Earnings Ratio
> Average Annual Dividend
> Return Total Capital
> Return Shareholders Equity
> Retained To Common Equity
> All Dividends To Net Worth
> Employees
r Net Profit
> Income Tax Rate
> Earnings Before Extras
> Earnings per share
> Long Term Debt
> Total Loans
> Total Assets
> Preferred Dividends
> Common Dividends
> Book Value
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix M: Estimating Capital Outlays
> Book Value per share
> Shareholder Equity
> Preferred Equity
> Common Shares Outstanding
> Average Shares Outstanding
> Beta
> Alpha
> Standard Deviation
May 2014
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix N: Analysis of Other Regulations
Appendix N Analysis of Other Regulations - Manufacturers
N.1 Regulations Potentially Affecting Manufacturers
EPA also accounted for other recently published proposed or final environmental regulations that may impose
additional costs on Primary Manufacturing Industries beyond those reflected in facilities" baseline financial
statements. The after-tax cash flow (ATCF) adjustment analysis, which EPA undertook to bring cash flow
forward from the time of the survey (1996-1998) to the time of the regulatory analysis, accounts implicitly for
additional regulatory costs incurred through the end of 2011. However, it does not capture the impact of new
regulations that came into effect during, or soon after, this period and for which costs had not been incurred, or
fully incurred, by the end of 2011.
To account for potential costs that had not been fully incurred by the end of 2011, EPA researched additional
regulatory requirements that might apply to facilities in the Primary Manufacturing Industries, and for which costs
were not likely to have been captured in the ATCF adjustment analysis. This research included searching the
Federal Register and the EPA website for final or proposed regulations affecting the relevant NAICS groups and
industry sectors within the timeframe of concern. These searches identified seven regulations that apply to the
316(b) Manufacturing Industries and could result in additional costs to Manufacturers after 2011. EPA did not
include regulations that target either certain chemicals (such as Significant New Use Rules) or certain processes
(such as certain National Emissions Standards for Hazardous Air Pollutants) as the 316(b) survey did not provide
the information needed to determine whether these more narrow regulations would be applicable to the
Manufacturers facilities. In addition, EPA did not include regulations that affected only one facility.
Table N-l below summarizes these regulations (Other Regulations). The following discussion uses both the
regulation number presented in the first column and the abbreviated regulation name in parenthesis in the second
column.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix N: Analysis of Other Regulations
Table N-1: Regulations Potentially Affecting 316(b) Manufacturers
No. Regulation
Effective
Date
Summary
316(b) Industries Affected
Compliance
Date
1
National Emission Standards for
Hazardous Air Pollutants from
Petroleum Refineries (Petroleum
NESHAP)
10/09
Amends the national emission
standards for petroleum refineries
to add maximum achievable
control technology standards for
heat exchange systems
Petroleum Refining Industry
Not later than
10/12
2
National Emission Standards for
Hazardous Air Pollutants From the
Pulp and Paper Industry (Paper
NESHAP)
9/12
Amends national emissions
standards for hazardous air
pollutants for the pulp and paper
industry.
Paper and Allied Products
Industry
Not later than
9/12
3
National Emission Standards for
Hazardous Air Pollutants for Chemical
Manufacturing Area Sources
(Chemicals NESHAP)
10/12
Issues national emissions
standards for hazardous air
pollutants for nine area source
categories.
Chemicals and Allied
Products Industry
Not later than
10/12
4
National Emissions Standards for
Hazardous Air Pollutants: Primary
Aluminum Reduction Plants (Primary
Aluminum NESHAP)

Amends the national emissions
standards for hazardous air
pollutants for primary aluminum
reduction plants.
Aluminum Industry
Three years
after
publication of
final rule
5
Commercial and Industrial Solid Waste
Incineration Units (CISWI)
2/13;
8/13;
4/13
Issues a final decision on
emissions guidelines for
commercial and industrial solid
waste incineration units.
Chemicals and Allied
Products, Paper and Allied
Products, and Other
Industries
Not later than
2/15
6
National Emission Standards for
Hazardous Air Pollutants for Area
Sources: Industrial, Commercial, and
Institutional Boilers and Process
Heaters (Area ICI)
2/13
Establishes requirements for
industrial/commercial/institutional
boilers and process heaters located
at area sources to meet hazardous
air pollutants standards reflecting
the application of the maximum
achievable control
technology.
Food Production Industry
and Other Industries
Not later than
3/14 (2015 if
granted an
extension)
7
National Emission Standards for
Hazardous Air Pollutants for Major
Sources: Industrial, Commercial, and
Institutional Boilers and Process
Heaters (Major ICI)
4/13
Establishes requirements for
industrial/commercial/institutional
boilers and process heaters located
at major sources to meet
hazardous air pollutants standards
reflecting the application of the
maximum achievable control
technology.
Aluminum Industry,
Chemicals and Allied
Products, Paper and Allied
Products, Petroleum
Refining Industry, Steel
Industry, and Other
Industries
Not later than
1/16
Source: Rule preambles and supporting materials. See Reference section.
To account for the potential impact of the Other Regulations listed in Table N-l on regulated Manufacturers, EPA
determined which 316(b) industries EPA expects to be subject to these regulations, based on the NAICS codes
reported in Federal Register notices as potentially regulated categories. EPA relied on information reported in the
Federal Register notices and supporting documentation to develop per facility costs for the identified sectors. EPA
restated these costs on an after-tax basis in $2011 and subtracted them from the estimated baseline free cash flow
for each facility that EPA judged potentially affected by a regulation (see also Chapter 5: Cost and Economic
Impact Analysis - Manufacturers, Section 5.3). EPA then determined whether the potential costs associated with
these regulations would affect either the baseline or the post-compliance severe impact findings for each facility.
The remainder of this appendix discusses the methodology used for this analysis and the findings.
N.2 Methodology
N.2.1 Determination of Applicability to 316(b) Manufacturing Facilities
EPA first identified which of the regulated Manufacturers would potentially incur costs as a result of the Other
Regulations. EPA based this determination on the NAICS codes and/or industry description reported in either the
N-2
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Appendix N: Analysis of Other Regulations
Federal Register preamble or supporting documents of each regulation. EPA assumed that all regulated facilities
with a 3- or 6-digit NAICS code, depending on the regulation, expected to be regulated by one of the Other
Regulations would incur costs under that regulation. One exception to this rule is where the industries expected to
be regulated under the Area ICI, Major ICI, and CISWI overlapped; in this case, EPA assumed facilities would
comply with the most expensive of the applicable regulations.
EPA's assumption about the applicability of the regulation - i.e., that a regulated Manufacturer will incur costs
under the regulation, if it belongs to a NAICS code that is subject to that regulation - may overstate or understate
these regulations" additional cost burden on Manufacturers. Rules often only affect a specific part of an industry,
depending, for example, on specific emission or discharge characteristics, or existing pollution control
technology. This is true for a number of the Other Regulations, making it likely that not all regulated
Manufacturers in a given NAICS code covered by a rule, would actually incur costs under that rule. Little
information is available on those technical characteristics of regulated Manufacturers that would determine the
applicability of the regulations to these facilities. On the other hand, the list of potentially affected NAICS codes
provided in the Federal Register notices is not exhaustive and may not list all affected industries; to the extent that
this is true, EPA may have understated the costs to Manufacturers.
N.2.2 Estimating Facility-Level Costs
As described in the earlier 316(b) Existing Facilities regulatory analysis documents, EPA considered several
approaches for applying the costs of the Other Regulations to potentially affected 316(b) facilities. The cost
application approach selected for each regulation depends on the level of detail that was available in the
regulation's documentation. Regardless of specific approach, EPA calculated the average annualized per facility
cost, on an after-tax basis, for each regulation. Table N-2 summarizes the resulting per facility costs of the Other
Regulations.
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Appendix N: Analysis of Other Regulations
Table N-2: Per Facility Cost of Regulations that Affect 316(b) Industries3
No.
Regulation
Affected 316(b) NAICS
Codes
Cost Application Method
Average Per Facility
Cost (Pre-Tax;
$201 l)a
1
Petroleum NESHAP
324110
> Average annualized cost per
facility
> Includes cost savings to facilities
$21,486
2
Paper NEHSAP
322
> Average annualized cost per
facility
$18,421
3
Chemicals NESHAP
325
> Average annualized cost per
facility
$7,424
4
Primary Aluminum
NESHAP
331312
> Average annualized cost per
facility
$20,269
5
CISWI
321,322, 324, 325,331,332,
336, 339
> Average annualized cost per
facility
$37,089
6
Area ICI
11,311,321
> Average annualized cost per unit
(for coal, oil, and biomass)
> Assumed one affected unit per
facility
> For facilities with capacity
information, assumed that
affected units relied on the same
fuel as the generating units
> For facilities without capacity
information provided, multiplied
by the average facility cost
(calculated over facilities with
capacity information)
$16,030
7
Major ICI
321,322, 324, 325,331,332,
336, 339
> Average annualized cost per unit
(for coal, oil, natural gas, and
biomass)
> Assumed one affected unit per
facility
> For facilities with capacity
information, assumed that
affected units relied on the same
fuel as the generating units
> For facilities without capacity
information provided, multiplied
by the average facility cost
(calculated over facilities with
capacity information)
$916,098
a. EPA used the GDP Deflator series published by the U.S. Bureau of Economic Analysis of the U. S. Department of Commerce to state average cost per
facility in 2011 dollars.
Source: U.S. EPA analysis for this report
EPA summed the per facility costs in Table N-2 for each affected Manufacturer (based on NAICS code or
individual facility identification), converted to the resulting value to an after-tax basis, and subtracted this value
from baseline adjusted after-tax cash flow (see discussion of the impact analysis method in Chapter 5: Cost and
Economic Impact Analysis - Manufacturers). For all regulated Manufacturers that were operational in the
baseline, EPA determined whether the additional cost of complying with the Other Regulations would cause the
facility to (1) fail the baseline test and become a "baseline closure" or (2) fail the post-compliance impact test and
be considered a "severe impact."
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Appendix N: Analysis of Other Regulations
N.3 Results
N.3.1 Baseline Analysis
Of the 207 regulated sample Manufacturers that are operational in the baseline and have a design intake flow of at
least two mgd, EPA found that no additional facilities would become a baseline closure (i.e., before incurring
compliance costs under the final rule) due to application of the additional costs from the Other Regulations.31"
N.3.2 Post-Compliance Analysis
The post-compliance analysis sets aside facilities considered baseline closures. Because the adjusted baseline
analysis found that no additional Manufacturers would be assessed as baseline closures, EPA did not remove any
additional facilities from the post-compliance analysis. Of the 207 sample manufacturing facilities (i.e., those that
are not considered a baseline closure after applying the costs of the Other Regulations), EPA found that no
additional facilities would experience a severe impact as a result of incurring both the final rule compliance costs
and the costs of the Other Regulations.
310 This analysis excludes 14 sample facilities with insufficient survey-based economic data and 28 sample facilities determined to be
baseline closures without taking into account the impact of these other regulations.
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Appendix O: Economic Impact Methodology - Manufacturers
Appendix O Economic Impact Methodology - Manufacturers
EPA conducted an economic impact analysis of the final rule and other options EPA considered for
Manufacturers. Measures of economic impact include (1) a facility-level cost-to-revenue screening analysis, (2) a
facility-level impact analysis, and (3) an entity-level impacts analysis. This appendix details the methodology
used for the second analysis. For the final rule, the potential facility-level impacts on the Manufacturers segment
are defined in two ways:
> Severe impacts are facility closures and the associated losses in jobs at facilities that would close due to
the regulation.
> Moderate impacts are adverse changes in a facility's financial position that are not threatening to its
short-term viability.
In conducting these analyses, EPA closely followed the methodologies used to conduct analyses in support of the
previous 316(b) rule analyses and, to the extent practicable, relied on similar data sources. See Chapter 5: Cost
and Economic Impact Analysis - Manufacturers for data inputs and analysis approach details.
0.1 Facility-Level Impacts: Severe Impact Analysis
The assessment of severe impacts for Manufacturers is based on the change in the facility's estimated business
value, as determined from a discounted present value analysis of baseline cash flow and the change in cash flow
resulting from regulatory compliance. As described in Chapter 5, the assessment of post-compliance severe
impacts also includes a test of whether annualized compliance costs exceed a threshold of 0.1 percent of revenue.
The cash flow concept used in calculating ongoing business value for the closure analysis is free cash flow
available to all capital. Free cash flow is the cash available to the providers of capital - both equity owners and
creditors - on an after-tax basis from business operations, and takes into account the cash required for ongoing
replacement of the facility's capital equipment. Free cash flow is discounted at an estimated after-tax total cost of
capital to yield the estimated business value of the facility. Details of the calculation of free cash flow and the
discounting of free cash flow to yield the facility's estimated value are explained in the following sections.
0.1.1 Calculation of Baseline Free Cash Flow and Performance of Baseline Closure Test
Calculation of baseline free cash flow and performance of the baseline closure test involved the following steps:
Average survey income statement data over response years and convert to 2011 dollars: EPA first restated
facility income statement data reported for 1996, 1997, and 1998 in 1998 dollars, using the GDP Deflator. For
each of the data item, the Agency then calculated a simple average over the months and/or years for which data
were reported to develop an annual average income statement in 1998 constant dollars. For example, if a facility
reported income statement data for 1996, 1997, and 1998, then a simple average was calculated for the three
reported years. EPA then restated the annual average income statement data in 2011 dollars, again using the GDP
Deflator.
Calculate after-tax income excluding the effects of financial structure: The 316(b) survey responses include a
calculation of after-tax income in accord with conventional accounting principles. However, this calculation
reflects the financial structure of the business, which may include debt financing and thus interest charges against
income. Because the cash flow concept to be discounted in the business value analysis is cash flow available to all
capital, it is necessary to restate after-tax income to exclude the effects of debt financing, or on a be fore-interest
basis. This restatement involves: (1) increasing after-tax income by the amount of interest charges and (2)
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Appendix O: Economic Impact Methodology - Manufacturers
increasing taxes (and thereby reducing after-tax income) by the amount of tax reduction provided by interest
deductibility. This adjustment amounts to adding tax-adjusted interest expense to after-tax income and yields an
estimate of after-tax income independent of capital structure or financing effects. In calculating the tax
adjustment for interest, EPA used a combined federal/State corporate income tax rate. For this calculation, EPA
used a tax rate that integrates the federal corporate income tax rate (35 percent) and state-specific state corporate
income tax rates, based on facility location.
The combined federal/State corporate income tax rate was calculated as follows:
T = Is + Tp - (ts * xF) (0-1)
where:
x = estimated combined federal-State tax rate;
xS = State tax rate; and
xF = federal tax rate (35 percent).
After-tax income, before interest, was calculated as follows:
ATI-/]/= ATI + I - xl
or (0-2)
ATI-BI = ATI + (1 - x)I
where:
ATI-/]/ = after-tax income before interest;
ATI = after-tax income from baseline financial statement;
I = interest charge from baseline financial statement; and
x = estimated combined federal-State tax rate.
Calculate after-tax cash flow (ATCF) from operations, before interest, by adjusting income for non-cash charges:
The calculation of after-tax income may include a non-cash charge for depreciation (and potentially amortization).
To convert income to ATCF from operations, it is therefore necessary to add back any depreciation charge to the
calculation of after-tax income, before interest. Cash flow, before interest, was calculated as follows:
ATCF-/i/ = ATI-/]/ +D (0-3)
where:
ATCF-/i/ = after-tax cash flow before interest;
ATI-BI = after-tax income before interest; and
D = baseline depreciation.
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Appendix O: Economic Impact Methodology - Manufacturers
As a final step in the calculation of after-tax cash flow ATCF before interest, EPA eliminated the implied cash
flow benefit of any negative taxes, as reported in the facility's income statement and after adjustment for removal
of interest. That is, in these calculations, negative taxes increase after-tax income and cash flow, and thus appear
to improve the financial performance and value of the facility in terms of cash flow from operations. However,
whether and when the implied cash flow benefit of negative taxes can be realized depends on the overall
profitability and tax circumstances of the total enterprise, including any other facilities owned by the same parent
entity, and the extent of profitability in periods before or after the survey data periods. Not to overstate this effect,
EPA assumed that a facility would not receive the implied cash flow benefit from negative taxes - negative taxes,
after adjustment for interest, were set to zero in the baseline analysis. This assumption is consistent with a later
step in the post-compliance analysis in which EPA limited the cash flow benefit of tax deductions on compliance
outlays not to exceed the amount of taxes paid as reported in the baseline income statement (and adjusted for
interest). In theory, the application of this limit could cause some facilities that would otherwise pass the baseline
closure analysis, instead to fail the analysis if the reported amount of negative tax, after adjustment for interest,
would be sufficient to offset the negative cash flow from operations independent of taxes. In practice, though, this
limitation did not affect the findings of the baseline closure analysis. This limit was applied as a check and did not
cause a different outcome.
Adjust ATCF to reflect estimated real change in business performance from the time of survey data collection to
the present: EPA adjusted facility baseline cash flow to reflect the estimated real change (i.e., independent of
inflation) in business performance in the manufacturing industries from the time of the facility survey, 1996-1998,
to the 2011.
To calculate the adjustment factor, EPA collected ATCF data for public firms in the Primary Manufacturing
Industries over a 24-year period and developed adjustment factors by industry and/or key industry segment
(details of this analysis are contained in Appendix L: Adjusting Baseline Facility Cash Flow). Adjusted after-tax
cash flow is calculated as follows:
where:
ATCF-/i/ , [ j[ = after-tax cash flow before interest adjusted to reflect the real change in business
performance;
ATCF-BI = after-tax cash flow before interest; and
Adj = adjustment factor to reflect the real change in business performance.
Calculate free cash flow by adjusting ATCFfrom operations for ongoing capital equipment outlays: The measure
of ATCF from the previous step, cash flow from operations, reflects the cash receipts and outlays from ordinary
business operations, but includes no allowance for replacement of the facility's existing capital equipment. To
sustain ongoing operations, however, a business must expend cash for capital replacement. Accordingly, to
understand the true cash flow of a business, it is necessary to reduce cash flow from operations by an allowance
for capital replacement. For the calculation of free cash flow, EPA estimated baseline capital outlays from a
regression analysis of capital expenditures made by public firms in the Primary Manufacturing Industries over an
11-year period (details of this analysis and estimation framework are contained in Appendix M: Estimating
Capital Outlays Discounted Cash Flow Analyses). Free cash flow is calculated as follows:
ATCF-5/adj = ATCF-/i/ * Adj
(0-4)
FCF = ATCF-5/adj - CAPEX - OTHREGS
(0-5)
where:
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Appendix O: Economic Impact Methodology - Manufacturers
FCF = free cash flow
ATCF-5/adj = after-tax cash flow before interest adjusted to reflect the real change in business
performance; and
CAPEX = estimated baseline capital outlays; and
OTHREGS = annualized after-tax cost of compliance with federal environmental regulations that were
recently promulgated and whose costs are not likely to be reflected fully in the ATCF
adjustment analysis (Other Regulations). This variable and the associated analysis are not
part of the primary case analysis but were dealt with on an alternative, sensitivity case
basis.311
Or on a more detailed accounting statement basis:
FCF = REV - TC - T - xl - CAPEX - OTHREGS (0-6)
where:
FCF = free cash flow
REV = revenue
TC = total operating costs, excluding interest, depreciation, and taxes
T = baseline income tax
x = estimated combined federal-State tax rate;
I = interest charge from baseline financial statement;
xl = the increase in tax liability resulting from calculating income on a pre-interest basis;
CAPEX = estimated annual baseline capital outlays; and
OTHREGS = annualized cost of other compliance with federal environmental regulations that were
recently promulgated and whose costs are not likely to be reflected fully in the ATCF
adjustment analysis. This variable is only dealt with on an alternative, sensitivity case basis.
This calculation of free cash flow is based on a static representation of a facility's business. With the exception of
bringing estimated cash flow forward from the time of the survey, 1996-1998, to approximately the present, 2011,
the facility impact analysis assumes, in effect, that the facility's business will continue in the future - absent the
effects of regulation - exactly as reflected in the baseline financial statements provided in the 316(b) survey
responses.
Calculate baseline facility value as the present value offree cash flow over a 30-year analysis horizon: To
calculate baseline business value, EPA expressed free cash flow over a 30-year analysis period in present-value
311 EPA also undertook an alternative case analysis in which it further adjusted baseline cash flow to reflect costs that facilities might
incur from compliance with federal environmental regulations that were recently promulgated and whose costs are not likely to be
reflected fully in the ATCF adjustment analysis. This analysis, which is documented in Appendix N: Analysis of Other Regulations,
found no material effect on the facility impact analysis, as reported in this chapter. The alternative case analysis, which incorporated
estimated compliance costs from the recent federal environmental regulations, found one additional baseline closure and no change in
post-compliance closures.
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Appendix O: Economic Impact Methodology - Manufacturers
terms using an estimated real (i.e., excluding the effects of inflation), after-tax cost of capital of 7 percent. The
Agency calculated baseline business value of a facility as follows:
29 FCF
VALUE = Y - (0-7)
7^0 • CoO'
where:
VALUE = estimated baseline business value of the facility
FCF = free cash flow
CoC = after-tax cost-of-capital (7.0 percent); and
t = year index, t = 0-29 (30-year discounting horizon).
In the present value calculation, annual cash flows are assumed to accrue at the beginning of the year. As a result,
the first year of cash flows is already in present value terms - i.e., t = 0 for the first year of the analysis - and cash
flows in the 30th and final year of the analysis period are discounted over a 29-year period - i.e., t = 29 in the
final year of the analysis.
As explained above, EPA considered a facility to be a baseline closure if its estimated business value was
negative before incurring regulatory compliance costs. Baseline closures were neither tested for adverse impact in
the post-compliance impact analysis nor were their compliance costs included in the tally of total compliance
costs.
0.1.2 Calculation of Post-Compliance Free Cash Flow and Performance of Post-Compliance
Closure Test
For the post-compliance closure analysis, EPA recalculated annual free cash flow, accounting for changes in
revenue, annual expenses, and taxes that are estimated to result from compliance-related outlays. EPA combined
the post-compliance free cash flow value and the estimated compliance capital outlay in the present value
framework to calculate business value on a post-compliance basis.
For the post-compliance analysis, EPA considered whether Manufacturers would be able to pass forward
compliance costs to customers through increased prices. From the analyses presented in Appendix K: Cost Pass-
Through Analysis, EPA concluded that an assumption of zero cost pass-through is appropriate for analyzing the
impact of the regulatory analysis options on facilities in the six Primary Manufacturing Industries. Performance of
the impact analysis under this assumption means that facilities must absorb all compliance-related costs and
operating effects (e.g., income loss from facility shutdown during equipment installation) within their baseline
cash flow and financial condition. To the extent that facilities would be able to pass on some of the compliance
costs to customers through price increases, the analysis may overstate the potential impact on regulated facilities.
Calculation of post-compliance free cash flow and performance of the post-compliance closure test involved the
following steps:
Adjust baseline annual free cash flow to reflect compliance outlay effects: Compliance-related effects on annual
free cash flow include: annual change in revenue (assumed zero for this analysis); annually recurring operating
and maintenance costs; the annual equivalent of permitting and re-permitting costs, which recur on other than an
annual basis over the life of the analysis; the annual equivalent of the income loss from installation downtime; and
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Appendix O: Economic Impact Methodology - Manufacturers
related changes in taxes.312 For the other options considered, Proposal Option 4 and Proposal Option 2, involving
the installation of two technologies - IM technology and cooling tower - these compliance-related effects occur in
two stages. For this analysis, EPA assumed that the impact of these compliance-related effects would be
considered together in the year of the first technology installation and therefore conducted one analysis. The
change in taxes includes: (1) the tax effect of these annually recurring and annualized expenses and (2) the tax
effect from depreciation of initial compliance outlays. For calculating the tax effect of depreciation, EPA assumed
that compliance capital outlays would be depreciated for tax purposes on a straight-line schedule equal to the
assumed useful life of the technology. Post-compliance free cash flow was calculated as follows:
FCFpc = FCFbl + AR - ATC - x(- ATC - AD) (0-8)
where:
FCFpC = post-compliance free cash flow;
FCFBL = baseline free cash flow, as calculated above;
AR = change (increase) in revenue from pass through of compliance costs to customers313
ATC = change in total facility annual costs (excluding interest, depreciation and taxes), calculated
as the cost of operating and maintaining compliance equipment plus the annual equivalent of
certain non-annual costs, as described above, with costs associated with the first technology
considered as of the year of first technology installation and costs associated with the second
technology considered as of the year of second technology installation then discounted to the
year of first technology installation;
t = marginal tax rate for calculating compliance-related tax effects (combined federal-State tax
rate); and
AD = change in depreciation expense, calculated as compliance capital outlay (CC), for each
technology, divided by the useful life of the compliance technology.
Limit tax adjustment to not exceed taxes as reported in baseline financial statement: The tax effect of compliance
outlays is to reduce tax liability. As a result, in the free cash flow calculation, the tax adjustment generally
increases cash flow and business value and, all else equal, reduces the likelihood that a facility will fail the post-
compliance closure test. However, the extent to which a facility would realize this contribution to cash flow
depends on its tax circumstances. In particular, some businesses may not be paying sufficient taxes in the baseline
to take full benefit of the implied tax reduction at the facility level - unless the unused tax loss can be transferred
to other, profitable business units in the firm, these businesses would not be able to use fully the implied tax
reduction on a current basis. Also, the marginal tax rate for businesses with relatively low pre-tax income may be
less than the combined federal/State tax rate used in the analysis. While businesses may be able to carry forward
312 For the facility cash flow analysis, EPA treated the income loss from installation downtime on an annual equivalent basis even though
this financial event occurs only once, and at the beginning of the assumed analysis period. EPA treated the installation downtime on
an annualized basis for two reasons. First, the installation downtime is assumed to have a useful "financial life" of 30 years to reflect
the total potential business life of the facility with the installed compliance technology (note that reinstallation of the basic capital
equipment other than cooling towers, which is assumed to recur on a 20-, 25-, or 30-year interval depending on the specific
technology, does not require a new round of downtime). Since compliance capital equipment is assumed to have a specific useful life
and the discounted cash flow analysis is accordingly structured around this period, including the income loss from installation
downtime (which is assumed to have a 30-year useful life) as a one-time up-front cost would overstate its impact in the discounted
cash flow calculation. Second, calculation of the downtime cost on an annual basis allows the tax effect from the one-time income loss
to be summed with other annual tax effects for applying the limit to tax offsets, as explained in the next step of the analysis.
313 As described above, EPA concluded that Manufacturers are likely to have little or no potential to pass through compliance costs to
customers through price increases. Accordingly, this variable (AR) is assigned the value of zero in the Manufacturers impact analysis.
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Appendix O: Economic Impact Methodology - Manufacturers
tax losses to reduce taxes in later years, EPA recognizes that the implied cash flow benefit from tax reduction may
not be fully realized, particularly in circumstances involving single-facility parent entities. To reduce the risk of
overstating this tax-offset benefit in its analysis thereby potentially understating business impact, EPA limited the
amount of tax reduction from compliance outlays to be no greater than the amount of tax paid by facilities as
reported in the baseline financial statement. The analysis effectively assumes that facilities will not be able to
offset an implicit negative tax liability against positive tax liability elsewhere in operations of an owning entity or
to carry forward (or back) the negative income and its implicit negative tax liability to other positive
income/positive tax liability operating periods. Nevertheless, some businesses may be able to benefit from tax
reductions that exceed facility baseline taxes, especially if the facility is owned by a multiple-site entity.
Accordingly, EPA constrained the tax effect term in the free cash flow calculation, [-x( - ATC - AD)] as specified
above, to be no greater than baseline financial statement tax liability, T.
Calculate post-compliance facility value, including post-compliance free cash flow and the compliance capital
outlay: As in the baseline analysis, EPA calculated post-compliance facility value as the present value of free cash
flow and accounting for a two-stage compliance capital outlay.
For the other options considered - Proposal Option 4 and Proposal Option 2 - requiring the installation of two
technologies, a two-stage compliance outlay is created with the first outlay occurring in the year of the first
technology installation and a second outlay occurring in the year the second technology is installed. For the
purpose of this analysis, EPA assumes that a facility will take into consideration both capital outlays when
deciding whether to continue operating and therefore only one closure analysis is undertaken. Because the
estimated performance life for some IM compliance technology installations would cease before the end of the
30-year analysis period, this analysis accounts for reinstallation of IM compliance technologies after the end of
their initial performance period on a prorated basis. Facility post-compliance business value was calculated as
follows:
29 I'//
VAL UEPC = V - CC (0-9)
tt(i + cocy y '
where:
= estimated post-compliance business value of the facility
estimated post-compliance free cash flow
after-tax cost-of-capital (7.0 percent);
year index, t = 0-29 (30-year discounting horizon); and
compliance capital outlay, calculated for the first technology as an undiscounted cash outlay
in the year of first technology installation and for the second technology as the compliance
capital outlay discounted to the year of first technology installation. For technologies with a
useful life less than 30 years, the prorated cost of a second installation is also included in the
compliance capital outlay.
Calculate the cost to revenue of compliance: EPA calculated the cost-to-revenue value as annualized, after-tax
total compliance cost divided by facility-level revenue.
EPA considered a facility to be a post-compliance closure if:
1. Its estimated business value was positive in the baseline but became negative after adjusting for
compliance-related cost, revenue and tax effects, and
VALUER
FCFPC=
CoC =
t =
CC
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Appendix O: Economic Impact Methodology - Manufacturers
2. Annualized compliance cost exceeded the threshold of 0.1 percent.
In addition to tallying closure impacts in terms of the number of estimated facility closures, EPA also measured
the significance of closures in terms of losses in employment and output. Employment losses equal the number of
employees reported by closure facilities in survey responses; output losses equal total revenue reported for
regulatory closure facilities. EPA estimated national results by multiplying facility results by facility sample
weights.
0.2 Facility-Level Impacts: Moderate Impact Analysis
The analysis of moderate impacts examined two financial measures:
Pre-Tax Return on Assets (PTRA): ratio of pre-tax operating income - earnings before interest and taxes
(EBIT) - to assets. This ratio measures the operating performance and profitability of a business" assets
independent of financial structure and tax circumstances. PTRA is a comprehensive measure of a firm's
economic and financial performance. If a firm cannot sustain a competitive PTRA on a post-compliance
basis, it will likely face difficulty financing its investments, including the outlay for compliance equipment.
Interest Coverage Ratio (ICR): ratio of pre-tax operating cash flow - earnings before interest, taxes, and
depreciation (EBITDA) - to interest expense. This ratio measures the facility's ability to service its debt on
the basis of current, ongoing financial performance and to borrow for capital investments. Investors and
creditors will be concerned about a firm whose operating cash flow does not comfortably exceed its
contractual obligations. As ICR increases, the firm's general ability to meet interest payments and carry
credit also increases. ICR also provides a measure of the amount of cash flow available for equity after
interest payments.
Creditors and equity investors review the above two measures as criteria to determine whether and under what
terms they will finance a business. PTRA and ICR also provide insight into a firm's ability to generate funds for
compliance investments from internally generated equity, i.e., from ATCF. The following sections detail the
calculation and development of these threshold values.
0.2.1 Calculation of Moderate Impact Metrics
EPA calculated a facility's PTRA and ICR measures using data collected from the 316(b) survey, adjusted for
inflation to 2011. The two measures are defined as follows:
Pre- Tax Return on Assets
PTRA = (O-IO)
TA
where:
PTRA = pre-tax return on assets,
EBIT = pre-tax operating income, or earnings before interest and taxes, and
TA = total assets.
Or, stated in terms of income statement accounts,
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Appendix O: Economic Impact Methodology - Manufacturers
PTRA =
REV - (TC + D)
TA
(0-11)
where:
= pre-tax return on assets;
PTRA
REV = revenue;
TC
D
TA
total operating costs (excluding interest, taxes, and depreciation/amortization), with costs
associated with the first technology considered as of the year of first technology installation
and costs associated with the second technology considered as of the year of second
technology installation then discounted to the year of first technology installation;
depreciation, for each technology; and
total assets.
Interest Coverage Ratio
ICR =
EBITDA
I
(0-12)
where:
ICR = interest coverage ratio;
EBITDA = pre-tax operating cash flow, or earnings before interest, taxes, and depreciation (and
amortization) and
I = interest expense.
Or, stated in terms of income statement accounts,
REV-TC
ICR =
I
(0-13)
where:
ICR = interest coverage ratio;
REV = revenue;
TC = total operating costs (excluding interest, taxes, and depreciation/amortization), with costs
associated with the first technology considered as of the year of first technology installation
and costs associated with the second technology considered as of the year of second
technology installation then discounted to the year of first technology installation; and
I = interest expenses.
Including the effects of compliance costs, post-compliance PTRA and ICR are:
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Appendix O: Economic Impact Methodology - Manufacturers
\ri-:v -{/x: + mx: + D + M))]
PTRA> -= ~—— < % Profit Before Taxes Total Assets2sth - Ratio of profit before taxes divided by total assets and
multiplied by 100 for the lowest quartile of values in each 6-digit NAICS code.
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Appendix O: Economic Impact Methodology - Manufacturers
> Operating Profit - Gross profit minus operating expenses.
> Profit Before Taxes - Operating profit minus all other expenses (net).
RMA provides a measure of pre-tax return on assets that approximates the measure EPA defined for the moderate
impact analysis. As defined by RMA, this measure is the ratio of pre-tax income to assets, designated ROArma:
ROArma = Pre-Tax Income (EBT) / ASSETS25th
However, as defined by EPA for its analysis, the numerator of the PTRA measure requires the use of earnings
before interest and taxes (EBIT) instead of pre-tax income (EBT). Defined as EBIT, the PTRA numerator will
capture all return from assets, whether going to debt or equity. To derive a pre-tax, total return value, EPA
adjusted RMA's measure of PTRA using the median percentage values of EBIT and EBT available from RMA.
This adjustment yields the PTRA measure that EPA used in the moderate impact analysis, designated ROA316(b):
ROA316(b) = ROArma * EBIT / EBT
Negative values are included in the weighted-industry PTRA averages but a different method is used to adjust the
ROA values reported in RMA to the value used in the moderate impact analysis. Specifically, using only those
observations (i.e., 6-digit NAICS code and year combinations) with positive values for % Profit Before Taxes /
Total Assets, Operating Profit, and Profit Before Taxes, EPA calculated an adjustment factor by subtracting the
difference between ROA3i6(b) and ROArma as follows:
ROA3i6(b)-ROARMA = adjustment factor.
Those values were consolidated into industry-specific adjustment factors, weighted by 2010 value of shipments
from the Economic Censuses (U.S. DOC, 2010). Each negative PTRA observation from RMA was adjusted by its
industry specific adjustment factor to approximate the measure used in the moderate impact analysis:
ROArma + industry specific adjustment factor = ROA3i6(b)
The industry specific adjustment factors average 0.33 and range from 0.25 for the Other Industries to 0.48 for the
Aluminum industry.
0.2.3 Developing Threshold Values for Interest Coverage Ratio (ICR)
Interest coverage ratio (ICR) measures a business" ability to meet current interest payments and, on a pro-forma
basis, to meet the additional interest payments for new debt. A high ratio may indicate that a borrower would have
little difficulty in meeting the interest obligations of a loan. This ratio serves as an indicator of a firm's capacity to
take on additional debt, as might be required to finance installation of compliance technology.
The following data from Risk Management Association Annual. Statement Studies were used to calculate ICR:
> EBIT/Interest25m ~ Ratio of earnings (profit) before annual interest expense and taxes (EBIT) divided by
annual interest expense for the lowest quartile of values in each 6-digit NAICS code.
> % Depr., Dep., Amort./Sales med - Median ratio of annual depreciation, amortization and depletion
expenses divided by net sales and multiplied by 100.
> Operating Profit - Gross profit minus operating expenses.
RMA provides a measure of interest coverage that approximates the measure that EPA defined for the moderate
impact analysis. As defined by RMA, this measure is the ratio of earnings before interest and taxes to interest,
designated ICRrma:
ICRrma = EBIT / INTEREST25th
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Appendix O: Economic Impact Methodology - Manufacturers
However, as defined by EPA for its analysis, the numerator of the ICR measure requires the use of earnings
before interest, taxes, depreciation, and amortization (EBITDA) instead of earnings before interest and taxes
(EBIT). Defined this way, the ICR numerator will include all operating cash flow that could be used for interest
payments. To derive the desired ICR value (designated ICR3i6(b)), EPA adjusted the RMA value as outlined
below:
ICR3 i6(b) = EBITDA / INTEREST
Therefore, ICR316(b) = ICRrma * (EBIT + DA) / EBIT
or ICR3i6(b) = ICRrma * {1+ [(DA / SALES) / (EBIT / SALES)]}
For consistency of calculation, EPA used the median values available from RMA for the adjusting both the
numerator (DA / SALES) and denominator (EBIT / SALES) terms.314
EPA used the same method as described above to adjust the negative ICR values reported in RMA to the value
used in the moderate impact analysis. Including only those observations with positive values for EBIT/Interest, %
Depr., Dep., Amort./Sales, and Operating Profit, an adjustment factor was calculated by subtracting the difference
between ICR3i6(b) and ICRrma as follows:
ICR3i6(b)-ICRRMA = adjustment factor.
An industry specific adjustment factor was calculated for ICR values similar to the PTRA. Each negative ICR
observation from RMA was adjusted by its industry specific adjustment factor to approximate the measure used in
the moderate impact analysis:
ICRrma + industry specific adjustment factor = ICR3i6(b)
The industry specific adjustment factors average 0.61 and range from 0.39 for the Aluminum industry to 1.16 for
the Food and Kindred Products industry.
314 Numerator (% Depr., Dep., Amort./Sales) is available for quartile values; denominator (Operating Profit) only for median values.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix P: Overview of the Integrated Planning Model
Appendix P Overview of the Integrated Planning Model
As discussed in Chapter 6: Electricity Market Analysis, to assess the impacts of the final rule, EPA used the
Integrated Planning Model (IPM®), a comprehensive electricity market optimization model that can evaluate such
impacts within the context of regional and national electricity markets. Specifically, to assess facility- and market-
level effects of the final rule, EPA used the most current IPM platform available at the time of the analysis - the
Integrated Planning Model Version 4.10 MATS (IPM V4.10_MATS) (U.S. EPA, 2010b; U.S. EPA, 2013). This
Appendix provides an overview of the IPM V4.10_MATS platform specifications.
P.1 Overview of the Integrated Planning Model
IPM is an engineering-economic optimization model of wholesale electricity markets, which generates least-cost
resource dispatch decisions under the assumption of perfectly competitive markets and perfect foresight, based on
user-specified constraints such as environmental, demand, and other operational constraints. IPM's assumption of
perfect foresight implies that market players have complete knowledge of the nature and timing of the constraints,
including those created by regulatory requirements, that will be imposed in future years during the analysis
period, and make decisions based on this knowledge. The model can be used to analyze a wide range of electric
power market questions at the plant/15 regional, and national levels. In the past, applications of IPM have
included capacity planning, environmental policy analysis and compliance planning, wholesale price forecasting,
and asset valuation.
IPM uses a dynamic linear programming framework that simulates the dispatch of generating capacity over the
long-term (multiple decades) to achieve a demand-supply equilibrium on a seasonal basis and by region. The
model seeks the optimal solution to an "objective function," which is the summation of all the costs incurred by
the electric power sector, i.e., capital costs, fixed and variable operation and maintenance (O&M) costs, and fuel
costs, over the entire evaluated time horizon; the result is expressed as the net present value of all cost
components. The objective function is minimized subject to a series of user-defined supply and demand, or
system operating, constraints. Supply-side constraints include capacity constraints, availability of generation
resources, plant minimum operating constraints, transmission constraints, and environmental constraints.
Demand-side constraints include reserve margin constraints and minimum system-wide load requirements. The
optimal solution to the objective function is the least-cost mix of resources required to satisfy system-wide
electricity demand on a seasonal basis by region. In addition to existing capacity, the model also considers new
resource investment options, including capacity expansion at existing plants, as well as investment in new plants.
The model selects new investments while considering interactions with fuel markets, capacity markets, power
plant cost and performance characteristics, forecasts of electricity demand, system reliability considerations, and
other constraints. The resulting system dispatch is optimized given the resource mix, unit operating
characteristics, and fuel and other costs, to achieve the most efficient use of existing and new resources available
to meet demand. The model is dynamic in that the analysis covers a multiple decade period with information and
decisions in any specific period depending on the analysis information and optimization results for the entire
analysis period. The model is also forward-looking in that uses forecasts of future conditions to make decisions
for the present.
315 EPA uses the term facility throughout the EA to refer to individual regulated facilities, including power plants. However, there are
instances where this appendix refers to the IPM model and documentation terminology, such as model plant. In these instances, this
chapter uses the IPM terminology - i.e.., plant instead offacility.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix P: Overview of the Integrated Planning Model
P.2 Key Specifications of the IPM V4.10_MATS Platform
Electric Power Facility Universe
The IPM V4.10 MATS platform is based on an inventory of all U.S. utility- and non-utility-owned boilers and
generation plants that provide power to the integrated electric transmission grid, as recorded in the Department of
Energy's Energy Information Administration (EIA) databases EIA 860 (2006) and EIA 767 (2005).1"1'7 The IPM
V4.10_MATS universe consists of 14,920 generating units accounting for 4,910 existing electric power facilities.
The modeling system includes 520 of the 544 electric power facilities subject to the final rule. Facilities excluded
from the IPM analysis include three facilities in Hawaii and one facility in Alaska (i.e., areas that are outside the
geographic scope of the model), four on-site facilities that are not connected to the integrated electric transmission
grid, four facilities excluded from the IPM baseline as the result of custom adjustments made by ICF
International, and 12 facilities that did not respond to the 316(b) survey (see Appendix H: Sample Weights).318
Potential (New) Units
In addition to modeling existing electric power plants, IPM also models potential power plants to represent new
generation capacity that may be built during a model run. All the model plants representing new capacity are pre-
defined at IPM set-up and are differentiated by type of technology, regional location, and years available. IPM
"builds" new capacity to ensure that electricity demand is met at the lowest possible cost. To determine whether
building new capacity is more economically advantageous than letting existing plants produce enough electricity
to meet market demand, IPM takes into account cost differentials between various technologies, expected
technology cost improvements (by differentiating costs based on a plant's vintage, i.e., build-year), and regional
variations in capital costs that are expected to occur over time/19
Electricity Demand Baseline
The IPM V4.10_MATS platform embeds a baseline energy demand forecast from the Department of Energy's
Annual Energy Outlook 2010 (AEO2010), with adjustments by EPA to account for the effect of certain voluntary
energy efficiency programs. This electricity demand baseline is the same as that used by EPA in IPM-based
analyses for air program regulations.
Regional Analysis Framework
The IPM V4.10_MATS platform divides the U.S. electric power market into 32 regions in the contiguous 48
states (""lower-48"). It does not include generators located in Alaska or Hawaii. The 32 regions map to North
American Reliability Corporation (NERC) regions and sub-regions. IPM models electricity demand, generation,
transmission, and distribution within each region and across the transmission grid that connects regions. For the
analyses presented in this chapter, IPM regions were aggregated back into NERC regions. Figure P-l provides a
map of the NERC regions and Table P-3 lists the regions included in IPM V4.10_MATS platform and a
crosswalk between these NERC regions and the IPM regions.
310 IPM generating unit universe foes not include generating units in Hawaii or Alaska.
317 In some instances, plant information has been updated to reflect known material changes in a plant's generating capacity since 2005.
318 EPA's analysis of electricity market impacts of the final rule is based on the total of "lower-48"/grid-connected Electric Generators. In
the analyses described elsewhere in this report, the 12 survey non-respondents are accounted for in the facility sample weights (see
Appendix H). However, use of sample weights is not be appropriate in the IPM framework, and thus these survey non-respondent
facilities cannot be analyzed in the IPM-based electricity market analyses.
319 For more information see IPM documentation available at http://www.epa.gov/ainnarkets/progsregs/epa-ipm/index.html.
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix P: Overview of the Integrated Planning Model
Figure P-1: 2012 North American Electric Reliability Corporation (NERC) Regions
NPCC
MRO
— »¦«
RFCHrtSjft
SPP
SERC N
TRE
FRCC
a, Hie ASSC and HICC are not shown.
Source: U.S. DOE, 2012b
Table P-3: Crosswalk between NERC Regions and IPM Regions
NERC Region
Corresponding IPM Region(s)
ASCC
Alaska Systems Coordinating Council
Alaska plants are not included in IPM
IRK
Texas Regional Fntitv
FRCP
FRCC
Florida Reliability Coordinating Council
FRCC
IflCC
I lawaii
1 lawaii plants are not included in IPM
MRO
Midwest Reliability Organization
MRO. Wl 'VIS
NPCC
Northeast Power Coordination Council
DSNY, 1.1 LC, NFNG, NYC. IJPNY
RFC
ReliabilitvFirst Council
COMIX MAC]-. MACS. MACW. MIX'S. RFCO. RFCP
SKRC
Southeastern Electricity Reliabilit\ Council
FNTG, GWAY, SOU, TVA. I'VAK. VACA. VAPW
SPP
Southwest Power Pool
SPPN.SPPS
WFCC
Western Hlectricitv Coordinating Council
A/.NM. CA-N. CA-S. NWPF. PNW. RMI'A. SNV
Source:
U.S. EPA, 2010b; US.gPA, 2013

Regulations Accounted for in the IPM Analysis Baseline
An important reason for using IPM for the analysis of the final rule is that EPA uses the model to support analysis
of air regulations and the model thus incorporates in its analytic baseline, the expected compliance response for
air regulations affecting the power sector. For the purpose of analyzing the final rule, EPA used the most current
IPM baseline available at the time of analysis to make sure that this baseline reflects as much as possible, the
current regulatory state of the electric power industry and anticipated response to existing environmental
regulations. Thus, the IPM V4.10 MATS platform incorporates in its analytic baseline the expected compliance
response for the following air regulations affecting the power sector: the final Mercury and Air Toxics Standards
(MATS) rule; the final Cross-State Air Pollution Rule (CSAPR); established S02 emission rates arising from
State Implementation Plans; Title IV of the Clean Air Act Amendments; NGX SIP Call trading program; Clean Air
Act Reasonable Available Control Technology requirements and Title IV unit specific rate limits for NOx; the
Regional Greenhouse Gas Initiative; Renewable Portfolio Standards; New Source Review Settlements; and
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Economic Analysis for Final 316(b) Existing Facilities Rule
Appendix P: Overview of the Integrated Planning Model
several state-level regulations affecting emissions of S02, NOx, and Hg that were either in effect or expected to
come into force by 2017.320'321
Treatment of Individual Plants and Generating Units
As discussed earlier, IPM is supported by a database of existing boilers and electric generating units. To reduce
the size of the model and make the model manageable while capturing the essential characteristics of the
generating units, during analysis runs, individual boilers and electric generating units are aggregated into "model
plants." The "model plant" aggregation scheme is used to combine existing units with similar characteristics into
"model plants." It encompasses a variety of different classification categories including location, size, technology,
heat rate, fuel choices, unit configuration, S02 emission rates, and environmental regulations among others.322
In the analyses for EPA air regulations, IPM aggregates individual boilers and generators with similar cost and
operational characteristics into model plants. The Agency judges that this model plant aggregation is appropriate
for the analysis of the final rule.
Model Run years
The IPM V4.10_MATS platform models the electric power market over the 43-year period from 2012 to 2054.
Due to the highly data- and calculation-intensive computational procedures required for the IPM dynamic
optimization algorithm, IPM is run only for a limited number of years. Run years are selected based on analytical
requirements and the necessity to maintain a balanced choice of run years throughout the modeled time horizon.
Further, depending on the analytical needs, in the IPM analysis, these individual run years are assigned to
represent other adjacent years in addition to the run year itself. For the purpose of analyzing the final rule, EPA
did not make any changes to the run-year specification already defined in IPM as the time of analysis. Table P-4
lists run years used in the IPM analysis of the final rule and the years to which these run years map.
Table P-4: IPM V4.10_MATS Run-Year Specification3
Run year
Map Years
2015
2014-2016
2020
2017-2024
2030
2025-2034
a. The IPM V4.10 MATS also models ran years 2012 (2012-2013), 2040
(2035-2045), and 2050 (2046-2054). However, EPA did not use the data for
these run years to assess the impact of the final rale.
Selection of Compliance Responses
For the 316(b) Existing Facilities Rule analyses, EPA did not apply a feature available in the IPM framework in
which modeled plants select their compliance response to a regulation that is being analyzed. This capability is
used regularly in analyses of air regulations and allows facilities to be analyzed assuming a compliance response
selected from a menu of options, based on the most advantageous economic outcome to the facility. For the
analysis of the final rule, EPA determined the compliance response under the final rule outside of IPM by
evaluating baseline engineering factors for regulated facilities in relation to the requirements of a given regulatory
option. For each regulated facility, EPA determined the choice of technology, and its associated costs, and used
the data as inputs to the IPM run.
320 For more information on the IPM V4.10_MATS platform see http://www.epa.gov/airmarkets/progsregs/epa-ipm/index.html.
321 On August 21,2012, the D.C. Circuit vacated the Cross-State Air Pollution Rule (CSAPR). The Court remanded the rule back to the
Environmental Protection Agency (EPA) for further consideration. In the interim, the previously vacated Clean Air Interstate Rule
(CAIR) remains in effect, for now, by a standing Court order. EPA expects that this change had a minimal effect on the results of
analysis conducted in support of the final rule.
322 For more information on IPM V4.10_MATS platform see http://www.epa.gov/airmarkets/progsregs/epa-ipm/index.html.
P-4
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