United States
Environmental Protection
Agency

Office of Water
Washington, DC 20460

EPA-821 -R-2 3-014
December 13, 2023


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v>EPA

United States
Environmental Protection
Agency

Regulatory Impact Analysis for Revisions to
the Effluent Limitations Guidelines and
Standards for the Meat and Poultry Products
Point Source Category

EPA-821 -R-23 -014

December 13, 2023

U.S. Environmental Protection Agency
Office of Water (4303T)

Engineering and Analysis Division
1200 Pennsylvania Avenue, NW
Washington, DC 20460


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RIAfor Proposed Meat and Poultry Products ELGs

Acknowledgements and Disclaimer

This report was prepared by the U.S. Environmental Protection Agency. Neither the United States
Government nor any of its employees, contractors, subcontractors, or their employees make any warranty,
expressed or implied, or assume any legal liability or responsibility for any third party's use of or the
results of such use of any information, apparatus, product, or process discussed in this report, or represent
that its use by such party would not infringe on privately owned rights.


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RIAfor Proposed Meat and Poultry Products ELGs

Contents

Table of Contents

Table of Contents	i

List of Tables	v

List of Figures	vii

Abbreviations	viii

Executive Summary	ES-1

1	Introduction	1-1

1.1	Background	1-1

1.2	Overview of the Costs and Economic Impacts Analysis	1-2

1.2.1	Main Regulatory Options Presented in the Proposed Rule	1-2

1.2.2	Baseline	1-4

1.2.3	Cost and Economic Analysis Requirements under the Clean Water Act	1-4

1.2.4	Analyses of the Regulatory Options and Report Organization	1-4

2	Overview of the MPP Industry	2-1

2.1	Industry Sectors	2-1

2.2	Questionnaire and Subcategorization	2-4

2.3	Trends in Production, Prices, and International Trade	2-5

2.3.1	Production and Wholesale Prices	2-5

2.3.2	International Trade	2-6

2.4	Trends in Industry Concentration	2-7

2.5	Economies of Scale	2-10

2.6	Product Mixes	2-10

2.7	Summary	2-11

3	Compliance Costs	3-1

3.1	Analysis Approach and Inputs	3-1

3.2	Key Findings for Regulatory Options	3-4

3.3	Key Uncertainties and Limitations	3-6

4	Cost and Economic Impact Screening Analyses	4-1

4.1	Analysis Overview	4-1

4.2	Total After-Tax Private Costs	4-1

4.3	Cost-to-Revenue Analysis: Facility-Level Screening Analysis	4-1

4.3.1 Analysis Approach and Data Inputs	4-2

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RIA for Proposed Meat and Poultry Products ELGs	Contents

4.3.2	Key Findings for Regulatory Options	4-3

4.3.3	Uncertainties and Limitations	4-4

4.4 Cost-to-Revenue Screening Analysis: Parent Entity-Level Analysis	4-5

4.4.1	Analysis Approach and Data Inputs	4-5

4.4.2	Key Findings for Regulatory Options	4-6

4.4.3	Uncertainties and Limitations	4-7

5	Facility Closure Analysis	5-1

5.1	Analysis Overview	5-1

5.2	Analysis Inputs	5-1

5.2.1	Depreciation	5-1

5.2.2	Combined Tax Rate	5-2

5.2.3	Weighted Average Cost of Capital (WACC)	5-2

5.3	Baseline Discounted Cash Flow	5-3

5.4	After-Tax Compliance Costs	5-3

5.4.1	Tax Shield	5-3

5.4.2	After-Tax Compliance Costs	5-4

5.5	Post-Compliance Discounted Cash Flow	5-4

5.6	Extrapolation to Full Universe	5-5

5.7	Results	5-6

5.8	Uncertainties and Limitations	5-6

6	Market Impact Analysis	6-1

6.1	Analysis Overview	6-1

6.2	Analysis Methodology	6-1

6.2.1	Domestic and Trade Demand and Supply Functions	6-1

6.2.2	Pre-Regulatory Equilibrium	6-2

6.2.3	Post-Regulatory Equilibrium	6-3

6.3	Data	6-4

6.3.1	Trade Data and Baseline Quantity and Price Data	6-4

6.3.2	Elasticity Estimates	6-5

6.4	Pre- and Post-Regulatory Equilibria	6-9

6.4.1	Pre-Regulatory Equilibrium	6-9

6.4.2	Compliance Costs	6-9

6.4.3	Post-Regulatory Equilibrium	6-10

6.4.4	Market-Level Impacts	6-11

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Contents

6.5	Barrier-to-Entry Analysis	6-13

6.6	Uncertainties and Limitations	6-16

7	Assessment of Impacts on Employment	7-1

7.1	Background and Context	7-1

7.2	Post-Compliance Closures	7-1

7.3	New Treatment Technology	7-3

7.4	New Market Equilibrium	7-3

7.5	Estimated Impacts of the Proposed Rule	7-5

7.6	Uncertainties and Limitations	7-6

8	Cost Pass-Through Analysis	8-1

8.1	Background and Context	8-1

8.2	Total Compliance Costs	8-2

8.3	Facility-Level Cost-to-Revenue Analysis	8-3

8.4	Parent Entity-Level Cost-to-Revenue Analysis	8-4

8.5	Facility Closures	8-5

9	Assessment of Potential Impact of the Regulatory Options on Small Entities - Initial
Regulatory Flexibility Act (IRFA) Analysis	9-1

9.1	Why this Action is being Considered	9-2

9.2	Objectives and Legal Basis for the Proposed Rule	9-2

9.3	Description and Number of Small Entities to Which the Proposed Rule Will Apply	9-2

9.3.1	Determining Parent Entity of MPP Facilities	9-2

9.3.2	Determining Whether Parent Entities of MPP Facilities are Small	9-2

9.4	Projected Compliance Requirements, Classes of Small Entities Subject to the Compliance
Requirements, and Professional Skills Needed to Comply	9-4

9.4.1	Projected Compliance Requirements	9-4

9.4.2	Classes of Small Entities Subject to the Compliance Requirements	9-5

9.4.3	Professional Skills Needed to Comply	9-5

9.5	Other Federal Rule that may Duplicate, Overlap, or Conflict with the Proposed Rule	9-5

9.6	Potential Economic Impact on Small Entities	9-5

9.7	Minimization of Economic Impacts on Small Entities Consistent with Statutory Objectives, and
Consideration of Alternatives	9-10

9.8	Uncertainties and Limitations	9-12

10	Unfunded Mandates Reform Act (UMRA) Analysis	10-1

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Contents

10.1	UMRA Analysis of Impact on Government Entities and the Private Sector	10-1

10.2	UMRA Analysis Summary	10-2

11	Other Administrative Requirements	11-1

11.1	Executive Order 12866: Regulatory Planning and Review and Executive Order 14094:

Modernizing Regulatory Review	11-1

11.2	Executive Order 12898: Federal Actions to Address Environmental Justice in Minority Populations
and Low-Income Populations, Executive Order 14008: Tackling the Climate Crisis at Home and
Abroad, and Executive Order 14096: Revitalizing our Nation's Commitment to Environmental
Justice for All	11-2

11.3	Executive Order 13045: Protection of Children from Environmental Health Risks and Safety Risks
	11-3

11.4	Executive Order 13132: Federalism	11-3

11.5	Executive Order 13175: Consultation and Coordination with Indian Tribal Governments	11-4

11.6	Paperwork Reduction Act of 1995 	 11-5

11.7	National Technology Transfer and Advancement Act	11-6

12	Cited References	12-1

Appendix A. Proposed Rule Costs at 7 Percent Discount Rate	A-l

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Contents

List of Tables

Table ES-1-1: Regulatory Options Analyzed for the Proposed Rule	ES-2

Table ES-1-2: Estimated Total Annualized After-Tax Compliance Costs (in millions, 2022$)	ES-3

Table 1-1: Regulatory Options Analyzed for the Proposed Rule	1-3

Table 2-1: Number of Firms in the MPP Industry Sector, by Year and Segment	2-2

Table 2-2: Number of Establishments in the MPP Industry Sector, by Year and Segment	2-3

Table 2-3: Number of Employees in the MPP Industry Sector, by Year and Segment	2-3

Table 2-4: Number of Facilities in MPP Industry by Process and Discharge Type	2-5

Table 2-5: U.S. Domestic Production and Wholesale Prices from 2010 to 2022	2-5

Table 2-6: U.S. Imports and Exports by Meat Product from 2010 to 2022 (Million Pounds)	2-7

Table 2-7: 2012 and 2017 MPP Industry Economic Census	2-8

Table 2-8: Average Number of Establishments per Firm in the MPP Industry Sector, by Year and

Segment	2-9

Table 2-9: Annual Production Levels by Meat Category from 2010 to 2022	2-10

Table 3-1: Estimated Total Social Costs by Regulatory Option and Discharge Type, 3 percent discount
rate (in millions, 2022$, at 2025)	3-4

Table 3-2: Time Profile of Costs to Society (in millions, 2022$)	3-5

Table 4-1: Estimated Total Annualized After-Tax Compliance Costs (in millions, 2022$)	4-1

Table 4-2: Facility-Level After-Tax Compliance Cost-to-Revenue Analysis Results by Discharge Type
and Regulatory Option	4-3

Table 4-3: Entity-Level Cost-to-Revenue Analysis Results	4-6

Table 5-1: Depreciation Schedule over Analysis Period	5-1

Table 5-2: Estimated Percent Closures by Production Size, Discharge Type, Processing Type, and CTR.5-
5

Table 5-3: Facility Closure Extrapolation Results	5-6

Table 6-1: Data Sources by Data Requirement	6-4

Table 6-2: Baseline Prices and Quantities by Meat Product	6-5

Table 6-3: Sources of Own-Price Elasticity of Demand	6-6

Table 6-4: Estimates of Cross-Price Elasticities of Demand	6-6

Table 6-5: Sources of Long-Run Own-Price Elasticity of Supply	6-7

Table 6-6: Average Long-Run Elasticity of Supply Estimates by Meat Product	6-7

Table 6-7: Estimated Armington Trade Elasticities with Respect to U.S. Price	6-8

Table 6-8: Estimated Pre-Regulatory Quantities and Prices	6-9

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RIAfor Proposed Meat and Poultry Products ELGs

Contents

Table 6-9: Estimated Post-Regulatory Quantities and Prices	6-10

Table 6-10: Post-Compliance Meat Market Prices Compared to Baseline Prices	6-12

Table 6-11: Post-Compliance Meat Market Quantities Compared to Baseline Prices	6-12

Table 6-12: Capital Cost and Baseline Expenditure Ratios by Processing Type and Regulatory Option... 6-
15

Table 7-1: Average Facility Labor Productivity and Production by Process Type and Production Size ..7-2

Table 7-2: Employment Changes Due to Facility Closures by Regulatory Option and Process Type (#

FTE)	7-2

Table 7-3: Estimated FTE Requirements for Operation of Treatment Technology, by Process Type and
Regulatory Option	7-3

Table 7-4: Percentages of Facilities Belonging to Each Meat Process	7-4

Table 7-5: Labor Productivity by Process Type	7-4

Table 7-6: Change in FTE by Process Type and Regulatory Option	7-5

Table 7-7: Short-run and Long-run Employment Impacts Associated with the Proposed Rule	7-6

Table 8-1: Weighted Average Percentage of Compliance Costs Incurred by Facilities (1-CPT) by Meat
Product	8-2

Table 8-2: Estimated Total Annualized Pre-Tax Compliance Costs with CPT, 3 percent discount rate (in
millions, 2022$, at 2025)	8-2

Table 8-3: Estimated Total Annualized After-Tax Compliance Costs with CPT (in millions, 2022$)	8-2

Table 8-4: Facility-Level After-Tax Compliance Cost-to-Revenue Analysis Results by Discharge Type
and Regulatory Option	8-3

Table 8-5: Entity-level cost-to-revenue analysis results	8-4

Table 8-6: Facility Closure Extrapolation with CPT Results	8-5

Table 9-1: NAICS Codes and SBA Size Standards for Owners of MPP Facilities	9-3

Table 9-2: Minimum and Maximum Revenue and Employment Thresholds Applied to Firms with

Missing NAICS Codes	9-4

Table 9-3: Number of Entities by NAICS Code and Size	9-4

Table 9-4: Entity-Level CTR Analysis Results by Entity Type	9-7

Table 9-5: Estimated Cost-to-Revenue Impact on Small Parent Entities, by Facility Type	9-9

Table 10-1: Compliance Costs by Sector (in millions, 2022$)	10-2

Table 12-1: Estimated Total Social Costs by Regulatory Option and Discharge Type (in millions, 2022$,
at 2025)	A-l

Table 12-2: Time Profile of Costs to Society (in millions, 2022$)	A-l

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List of Figures

Figure 6-1: Establishment Entry and Exit Rates for MPP and all U.S. Industries, from 2000-2020	6-14

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Abbreviations

Abbreviations

BAT

Best available technology economically achievable

BCA

Benefit and Cost Analysis

BCT

Best conventional pollutant control technology

BEA

U.S. Bureau of Economic Analysis

BLS

U.S. Bureau of Labor Statistics

BPT

Best practicable control technology currently available

CFR

Code of Federal Regulations

CPT

Cost pass-through

CTR

Cost-to-revenue

CWA

Clean Water Act

D&B

Dun and Bradstreet

DCF

Discounted cash flow

EA

Environmental Assessment

ELGs

Effluent limitations guidelines and standards

EO

Executive Order

EPA

U.S. Environmental Protection Agency

FCF

Free cash flow

FIML

Full information maximum likelihood

FRED

Federal Reserve Economic Data

FSIS

Food Safety and Inspection Service

FTE

Full time equivalent

GDP

Gross domestic product

GIPSA

Grain Inspection, Packers and Stockyards Administration

HHI

Herflndahl-Hirschman Index

ICIS-NPDES

Integrated Compliance Information System National Pollutant Discharge Elimination

System

IRFA

Initial regulatory flexibility analysis

IRS

Internal Revenue Service

JW

Jaro-Winkler

LMIC

Livestock Marketing Information Center

MACRS

Modified Accelerated Cost Recovery System

MPP

Meat and poultry products

NAICS

North American Industry Classification System

NARA

North American Renderers Association

NO A A

National Oceanic and Atmospheric Administration

NPDES

National Pollutant Discharge Elimination System

NPRM

Notice of proposed rulemaking

NSPS

New Source Performance Standards

NTTAA

National Technology Transfer and Advancement Act

OIRA

Office of Information and Regulatory Affairs

O&M

Operation and maintenance

OMB

Office of Management and Budget

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Abbreviations

POTW

Publicly owned treatment works

PRA

Paperwork Reduction Act

PSES

Pretreatment Standards for Existing Sources

PSNS

Pretreatment Standards for New Sources

QA

Quality assurance

QC

Quality control

RIA

Regulatory Impact Analysis

RFA

Regulatory Flexibility Act

ROW

Rest of world

SBA

Small Business Administration

SBAR

Small business advocacy review

SBC

Survey of Current Businesses

SBREFA

Small Business Regulatory Enforcement Fairness Act

SEC

U.S. Securities and Exchange Commission

SISNOSE

Significant impact on a substantial number of small entities

TDD

Technical Development Document

UMRA

Unfunded Mandates Reform Act

UNFAO

United Nations Food and Agriculture Organization

USDA

United States Department of Agriculture

WACC

Weighted average cost of capital

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Executive Summary

Executive Summary

EPA is proposing a regulation that revises the technology-based effluent limitations guidelines and
standards (ELGs) for the meat and poultry products (MPP) point source category, 40 CFR part 432. The
proposed rule revises or establishes effluent limitations for the MPP industry based on Best Practicable
Control Technology Currently Available (BPT), Best Conventional Pollutant Control Technology (BCT),
Best Available Technology Economically Achievable (BAT), and Pretreatment Standards for Existing
Sources (PSES). Depending on the regulatory option, the proposed rule sets new limits for nitrogen,
phosphorus, conventional pollutants, and/or chlorides.

This action is a significant regulatory action that was submitted to the Office of Management and Budget
(OMB) for interagency review. This Regulatory Impact Analysis (RIA) presents an assessment of the
compliance costs and impacts associated with this proposal and presents analyses to meet various
statutory and Executive Order requirements. The accompanying Benefit and Cost Analysis for Revisions
to the Effluent Limitations Guidelines and Standards for the Meat and Poultry Products Point Source
Category (BCA) document presents social costs and benefits of the action, consistent with Executive
Orders 12866,13563, and 14094.

Regulatory Options

For this proposed rule, EPA evaluated three regulatory options, with and without chlorides, as
summarized in Table ES-1-1 and further described in the notice of proposed rulemaking (NPRM) for the
action. EPA proposes to establish BAT effluent limitations based on the technologies described in
Option 1.

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Executive Summary

Table ES-1-1: Regulatory Options Analyzed for the Proposed Rule

Discharge
type

Process type

Technology Basis for BAT/BCT/PSES Regulatory Options3

Option 1

Option 2

Option 3

Chlorides

Production13

Technology

Production13

Technology

Production13

Technology

Production13

Technology

Direct

Meat first

>50 M

Direct 2

>50 M

Direct 2

>	10 M

>	20 M

Direct 1
Direct 2

>5 M

Chlorides 2

Meat further

>50 M

Direct 2

>50 M

Direct 2

>	10 M

>	20 M

Direct 1
Direct 2

>5 M

Chlorides 2

Poultry first

> 100 M

Direct 2

> 100 M

Direct 2

>	10 M

>	20 M

Direct 1
Direct 2

>5 M

Chlorides 2

Poultry further

>7 M

Direct 2

>7 M

Direct 2

>	10 M

>	20 M

Direct 1
Direct 2

>5 M

Chlorides 2

Render

> 10 M

Direct 2

> 10 M

Direct 2

>	10 M

>	20 M

Direct 1
Direct 2

>5 M

Chlorides 2

Indirect

Meat first

>50 M

Indirect 1

>50 M
>200 M

Indirect 1
Indirect 2

>5 M
> 30 M

Indirect 1
Indirect 2

>5 M

Chlorides 2

Meat further

>50 M

Indirect 1

>50 M

Indirect 1

>5 M
> 30 M

Indirect 1
Indirect 2

>5 M

Chlorides 2

Poultry first

> 100 M

Indirect 1

> 100 M
>200 M

Indirect 1
Indirect 2

>5 M
> 30 M

Indirect 1
Indirect 2

>5 M

Chlorides 2

Poultry further

>7 M

Indirect 1

>7 M

Indirect 1

>5 M
> 30 M

Indirect 1
Indirect 2

>5 M

Chlorides 2

Render

> 10 M

Indirect 1

> 10 M
>350 M

Indirect 1
Indirect 2

>5 M
> 30 M

Indirect 1
Indirect 2

>5 M

Chlorides 2

a.	See TDD for a description of these technologies ((U.S. Environmental Protection Agency, 2023c).

b.	Production reported in millions (M) of pounds per year.

Source: U.S. EPA Analysis, 2023

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Executive Summary

Annualized Private Compliance Costs

EPA estimates that the regulatory options result in incremental costs to owners and operators of MPP
facilities when compared to the baseline (Table ES-1-2). On an after-tax basis, the proposed rule (Option
1) has estimated incremental annualized compliance costs of $210 million.

Table ES-1-2: Estimated Total Annualized After-Tax Compliance Costs (in millions, 2022$)

Regulatory Option

Direct

Indirect

Total

Option 1

$196.4

$13.9

$210.3

Option 2

$196.4

$394.0

$590.4

Option 3

$202.6

$793.0

$995.6

Option lwith chlorides

$253.6

$100.5

$354.1

Option 2 with chlorides

$253.6

$480.6

$734.2

Option 3 with chlorides

$259.8

$879.6

$1,139.4

Source: U.S. EPA Analysis, 2023.

Impacts on the MPP Market and Potential Cost Pass-Through

EPA examined the effects of the proposed revisions to the MPP ELGs on the national markets for beef,
pork, chicken, and turkey. Based on a linear supply and demand model, EPA estimated the change in
market price, U.S. demand and supply, and foreign demand and sales. EPA estimated that the proposed
rule may result in a small increase in price and small decrease in supply and demand. EPA then assessed
the potential cost pass-through and reduction of facility and firm impacts resulting from this price
increase. The market impact analysis and cost pass-through analysis are described in Chapter 6 and
Chapter 8, respectively.

Potential Impacts on Employment

EPA estimated the potential impacts of this proposed rulemaking on employment, measured in terms of
changes in full-time equivalent (FTE) labor inputs. EPA estimated short-run employment impacts from
post-compliance closures and long-run employment impacts associated with the operation of new
treatment technology and new market equilibrium. In the short run, the Agency estimates negative
employment impacts associated with each regulatory option. In the long run, EPA estimates positive
employment impacts associated with each regulatory option. This analysis is detailed in Chapter 7.

Potential Impacts on Small Entities

In accordance with the Regulatory Flexibility Act (RFA) requirements, EPA assessed whether the
regulatory options would have "a significant impact on a substantial number of small entities"
(SISNOSE). The analysis is detailed in Chapter 9.

Under the proposed rule (Option 1), EPA estimates that one small entity owning MPP facilities would
incur costs exceeding one percent of revenue. On the basis of percentage, this entity represents less than
one percent of small entities. The analysis shows no small entities incurring costs greater than three
percent of revenue. Overall, this screening-level analysis suggests that the analyzed regulatory options are
unlikely to have a significant economic impact on a substantial number of small entities.

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Executive Summary

Unfunded Mandate Reform Act

Under Title II of the Unfunded Mandates Reform Act (UMRA) of 1995 section 202, EPA generally must
prepare a written statement, including a cost-benefit analysis, for proposed and final rules with "Federal
mandates" that might result in expenditures by State, local, and Tribal governments, in the aggregate, or
by the private sector, of $100 million (adjusted annually for inflation) or more in any one year (i.e., about
$184 million in 2022 dollars). EPA estimates that the private sector would incur expenditures of greater
than $184 million, in the aggregate, in any one year. EPA estimates the total annualized pre-tax
compliance costs for private entities to range from $232 million under Option 1 to $1,234 million under
Option 3 with chlorides.

Other Administrative Requirements

EPA conducted analyses to address other administrative requirements. Key findings, which are discussed
further in Chapter 11, include:

•	Executive Order 12866: Regulatory Planning and Review and Executive Order 14094:
Modernizing Regulatory Review: Pursuant to the terms of Executive Orders 12866 and 14094,
this action is a significant regulatory action. As such, the action is subject to review by the OMB.
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 estimated benefits and costs associated
with this action; this analysis is detailed in the BCA (U.S. Environmental Protection Agency,
2023a).

•	Executive Order 12898: Federal Actions to Address Environmental Justice in Minority
Populations and Low-Income Populations, Executive Order 14008: Tackling the Climate
Crisis at Home and Abroad, and Executive Order 14096: Revitalizing our Nation's
Commitment to Environmental Justice for All: EPA examined whether the benefits from this
proposed rule may be differentially distributed among population subgroups in the affected areas.
This analysis is detailed in the accompanying Environmental Assessment for Revisions to the
Effluent Limitations Guidelines and Standards for the Meat and Poultry Products Point Source
Category (EA) (U.S. Environmental Protection Agency, 2023b). The analysis showed that
communities in close proximity to MPP facilities have greater proportions of low-income
individuals and individuals identifying as Asian, Black, and/or Hispanic than the national average
and could be at risk of pollutant exposure. EPA also assessed communities served by public water
systems downstream of MPP direct dischargers and tribal lands in proximity to MPP facilities.
This analysis is detailed in the EA (U.S. EPA, 2023b).

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RIAfor Proposed Meat and Poultry Products ELGs

1: Introduction

1 Introduction

1.1 Background

EPA is proposing a regulation that revises the technology-based effluent limitations guidelines and
standards (ELGs) for the meat and poultry products (MPP) point source category, 40 CFR part 432. The

effluent guidelines applicable to direct discharging MPP facilities were last revised in 2004, and do not
reflect best available treatment technologies for nutrients, as required by CWA section 304(b). For
indirect dischargers, there are currently no nationally applicable pretreatment standards, although CWA
307(b) requires such standards where, as here, there is passthrough and interference with POTW
operations.

In addition, Executive Order 12866, directs agencies to identify the market failure they attend to address
when issuing a rulemaking. A market failure is the inefficient distribution of goods and services in the
free market, which may occur for a variety of reasons, such as externalities, market power, or asymmetric
information. An externality occurs when the societal costs or benefits of a good or service are not
captured in the market price of that good or service. This proposed rule would address the negative
externality of water pollution generated by direct discharges of MPP plants. The current market prices of
MPP production, do not reflect full societal costs, of meat production. As there is no market for direct
discharges, prices do not capture the costs to the communities who may be impacted by this pollution, and
may encourage MPP companies to produce more products and more water pollution than if pollution's
costs to society were reflected in those prices.

MPP plants with indirect discharges impose costs on water systems for those pollutants removed by the
POTWs. Where POTWs pass the treatment costs to indirect discharges through fees, the cost of pollution
control can be included in the price of meat. However, because not all POTWs fully pass on these
treatment costs to MPP plants, more pollution may occur than if pollution costs were fully borne by MPP
plants. Furthermore, POTWs typically do not remove all pollutants received from indirect dischargers.
Those pollutants in the MPP effluent not removed by the POTWs constitute a negative externality to the
public that the agency seeks to address with the proposed rule.

The proposed rule revises or establishes effluent limitations for the MPP industry based on Best
Practicable Control Technology Currently Available (BPT), Best Conventional Pollutant Control
Technology (BCT), Best Available Technology Economically Achievable (BAT), and Pretreatment
Standards for Existing Sources (PSES). Depending on the regulatory option, the proposed rule sets new
limits for nitrogen, phosphorus, conventional pollutants, and/or chlorides.

This document describes the Agency's analysis of the costs and economic impacts of the three regulatory
options that were evaluated by EPA. This document also provides information pertinent to meeting
several legislative and administrative requirements.

This document complements and builds on information presented separately in other reports, including:

• Technical Development Document for Proposed Effluent Limitations Guidelines and Standards
for the Meat and Poultry Products Point Source Category (TDD) (U.S. Environmental Protection
Agency, 2023c). The TDD summarizes the technical and engineering analyses supporting the

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RIAfor Proposed Meat and Poultry Products ELGs

1: Introduction

proposed rule, including cost methodologies, pollutant removal estimates, non-water quality
environmental impacts, and calculation of the proposed effluent limitations.

•	Benefit and Cost Analysis for Revisions to the Effluent Limitations Guidelines and Standards for
the Meat and Poultry Products Point Source Category (BCA) (U.S. Environmental Protection
Agency, 2023a). The BCA summarizes the societal benefits and costs estimated to result from
implementation of the proposed regulatory options.

•	Environmental Assessment for Revisions to the Effluent Limitations Guidelines and Standards for
the Meat and Poultry Products Point Source Category (EA) (U.S. Environmental Protection
Agency, 2023b). The EA summarizes the environmental and human health improvements that are
estimated to result from implementation of the proposed regulatory options. The EA also
describes the environmental justice analysis conducted.

The proposed revisions to the ELGs for the MPP point source category are 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.

1.2 Overview of the Costs and Economic Impacts Analysis

This section describes the key components of the analysis framework.

1.2.1 Main Reguia tory Options Presented in the Proposed Rule
For this proposed rule, EPA evaluated three regulatory options: Options 1-3, as shown in Table 1-1, plus
each of these same options with chlorides, as shown in Table 1-1.

•

Option 1





•

Option 2





•

Option 3





•

Option 1

with

chlorides

•

Option 2

with

chlorides

•

Option 3

with

chlorides

EPA proposes to establish BAT/PSES effluent limitations based on the technologies described in Option
1.

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Table 1-1: Regulatory Options Analyzed for the Proposed Rule

Discharge
type

Process type

Technology Basis for BAT/BCT/PSES Regulatory Options3

Option 1

Option 2

Option 3

Chlorides

Production13

Technology

Production13

Technology

Production13

Technology

Production13

Technology

Direct

Meat first

>50 M

Direct 2

> 50 M

Direct 2

> 10 M
>20 M

Direct 1
Direct 2

>5 M

Chlorides 2

Meat further

>50 M

Direct 2

> 50 M

Direct 2

> 10 M
>20 M

Direct 1
Direct 2

>5 M

Chlorides 2

Poultry first

> 100 M

Direct 2

> 100 M

Direct 2

> 10 M
>20 M

Direct 1
Direct 2

>5 M

Chlorides 2

Poultry further

>7 M

Direct 2

>7 M

Direct 2

> 10 M
>20 M

Direct 1
Direct 2

>5 M

Chlorides 2

Render

> 10 M

Direct 2

> 10 M

Direct 2

> 10 M
>20 M

Direct 1
Direct 2

>5 M

Chlorides 2

Indirect

Meat first

>50 M

Indirect 1

> 50 M
>200 M

Indirect 1
Indirect 2

>5 M
>30 M

Indirect 1
Indirect 2

>5 M

Chlorides 2

Meat further

>50 M

Indirect 1

> 50 M

Indirect 1

>5 M
>30 M

Indirect 1
Indirect 2

>5 M

Chlorides 2

Poultry first

> 100 M

Indirect 1

> 100 M
>200 M

Indirect 1
Indirect 2

>5 M
>30 M

Indirect 1
Indirect 2

>5 M

Chlorides 2

Poultry further

>7 M

Indirect 1

>7 M

Indirect 1

>5 M
>30 M

Indirect 1
Indirect 2

>5 M

Chlorides 2

Render

> 10 M

Indirect 1

> 10 M
>350 M

Indirect 1
Indirect 2

>5 M
>30 M

Indirect 1
Indirect 2

>5 M

Chlorides 2

a.	See TDD for a description of these technologies (U.S. Environmental Protection Agency, 2023c).

b.	Production reported in millions (M) of pounds per year.

Source: U.S. EPA Analysis, 2023

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1.2.2	Baseline

The baseline for the analyses supporting this proposed rule reflects the 2004 rule requirements. The
Agency estimated and presents in this report the incremental compliance costs that facilities could incur
under each of the three regulatory options presented in Table 1-1, with and without chlorides, relative to
this baseline.

As described in the preamble for this proposed rule, EPA relied on the following main sources of
information to define the baseline universe of facilities potentially subject to this proposed rule:

•	U.S. Department of Agriculture (USDA) Food Safety and Inspection Service (FSIS) data on
federally inspected meat and poultry facilities.

•	North American Renderers Association (NARA) information on the rendering industry.

•	EPA's Integrated Compliance Information System National Pollutant Discharge Elimination
System (ICIS-NPDES) database.

•	EPA's MPP survey of facilities engaged in meat and poultry slaughtering and processing, and
rendering, activities. EPA developed two survey questionnaires to collect site-specific technical
and economic information: a Census Questionnaire and a Detailed Questionnaire. The Census
Questionnaire was administered as a census of the industry to confirm the list of facilities that fall
within the MPP industry. A statistically representative subset of MPP facilities were asked to
answer a more extensive set of questions in the Detailed Questionnaire, including additional
questions on processing operations, wastewater generation, and financial information.

1.2.3	Cost and Economic Analysis Requirements under the Clean Water Act

EPA's effluent limitations guidelines and standards for the meat and poultry processing industry are
promulgated under the authority of the Clean Water Act (CWA) Sections 301, 304, 306, 307, 308, 402,
and 501 (33 U.S.C. 1311, 1314, 1316, 1317, 1318, 1342, and 1361). In establishing national effluent
guidelines and pretreatment standards for pollutants, EPA considers the availability and economic
achievability of control and treatment technologies, as well as specified statutory factors including
"costs." 33 U.S.C. 1311(b)(2)(A), 1314(b)(2)(B).

EPA analyzed economic achievability. The cost and economic impact analysis for this rulemaking also
focuses on understanding the magnitude and distribution of compliance costs across the industry, and the
broader market impacts. This report also documents analyses required under other legislative (e.g.,
Regulatory Flexibility Act, Unfunded Mandates Reform Act) and administrative requirements (e.g.,
Executive Order 12866: Regulatory Planning and Review, as supplemented by Executive Order 14094:
Modernizing Regulatory Review).

1.2.4	Analyses of the Regulatory Options and Report Organization

This document discusses the following analyses EPA performed in support of the regulatory options as
compared to the baseline:

•	Overview of the MPP industry (Chapter 2), which presents an overview of the MPP industry,
including recent trends in the number of facilities and firms; data on MPP facilities and their

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discharge and processing type; and a description of trends in production, prices, industry
concentration, and international trade.

•	Compliance cost assessment (Chapter 3), which describes the cost components and calculates
industry-wide social costs by regulatory option.

•	Cost and economic impact screening analyses (Chapter 4), which presents industry-wide after-
tax compliance costs by regulatory option and evaluates the impacts of compliance on MPP
facilities and their owning entities on an after-tax cost-to-revenue basis.

•	Facility closure analysis (Chapter 5), which evaluates the potential for the proposed regulatory
options to result in the closure of MPP facilities, based on a discounted cash flow (DCF) analysis.

•	Market impact analysis (Chapter 6), which evaluates the effects of the proposed regulatory
options on the national markets for beef, pork, chicken, and turkey.

•	Employment impact analysis (Chapter 7), which evaluates the short- and long-term employment
effects of the proposed regulatory options.

•	Cost Pass-Through Analysis (Chapter 8), which assesses costs and impacts assuming a non-zero
cost-pass scenario.

•	Initial Regulatory Flexibility Act (RFA) analysis (Chapter 9) which assesses the impact of the
rule on small entities on the basis of a revenue test, i.e., cost-to-revenue comparison.

•	Analyses to address other legislative and administrative requirements (Chapters 10 and 11),

such as UMRA and Executive Orders 12866 and 14094.

Chapter 12 provides detailed information on sources cited in the text, and Appendix A: Proposed Rule
Costs at 7 Percent Discount Rate presents industry-wide compliance costs by regulatory option using an
alternative discount rate.

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2 Overview of the MPP Industry

This section provides a general description of the MPP industry. Section 2.1 provides a snapshot of the
meat and poultry products industry based on Statistics of U.S. Business datasets from the last 10 years;
Section 2.2 describes EPA's MPP survey and the respondents; Section 2.3 provides recent trends in
production, wholesale prices, and international trade in the MPP industry; Section 2.4 describes recent
trends in concentration in the MPP industry; Section 2.5 discusses the presence of economies of scale
within the MPP industry; and Section 2.6 provides an overview of the product mixes in the MPP industry.

2.1 Industry Sectors

The MPP point source category includes facilities "engaged in the slaughtering, dressing and packing of
meat and poultry products for human consumption and/or animal food and feeds. Meat and poultry
products for human consumption include meat and poultry from cattle, hogs, sheep, chickens, turkeys,
ducks and other fowl as well as sausages, luncheon meats and cured, smoked or canned or other prepared
meat and poultry products from purchased carcasses and other materials. Meat and poultry products for
animal food and feeds include animal oils, meat meal and facilities that render grease and tallow from
animal fat, bones and meat scraps" (See 40 CFR 432.1). These facilities can be categorized as one of five
process types:

•	"Meat first" refers to facilities that slaughter animals, excluding poultry.

•	"Meat further" refers to facilities that further process animal products, excluding poultry.1

•	"Poultry first" refers to facilities that slaughter poultry.

•	"Poultry further" refers to facilities that further process poultry.

•	"Render" refers to facilities that render meat and poultry materials.

MPP facilities generally fall under four North American Industry Classification System (NAICS) codes:

•	Animal (except Poultry) Slaughtering (NAICS 311611),

•	Meat Processed from Carcasses (NAICS 311612),

•	Rendering and Meat Byproduct Processing (NAICS 311613), and

•	Poultry Processing (NAICS 3 1 1615).

NAICS 311611 consists of establishments primarily engaged in slaughtering animals (except poultry and
small game). Establishments that slaughter and prepare meats are included in this industry. NAICS
311612 comprises establishments primarily engaged in processing or preserving meat and meat
byproducts (except poultry and small game) from purchased meats. This industry includes establishments
primarily engaged in assembly cutting and packing of meats (i.e., boxed meats) from purchased meats.

A facility that both slaughters animals and further processes animal products, excluding poultry, is categorized as "meat
first."

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NAICS 311613 comprises establishments primarily engaged in rendering animal fat, bones, and meat
scraps. NAICS 311615 comprises establishments primarily engaged in (1) slaughtering poultry and small
game and/or (2) preparing processed poultry and small game meat and meat byproducts.

Table 2-1 presents the number of firms in each NAICS sector from 2010 to 2020. Between 2010 and
2020, the number of firms engaged in Animal Slaughtering, Rendering and Meat Byproduct Processing,
and Poultry Processing decreased, while the number of firms engaged in Meat Processed from Carcasses
had a slight increase. The number of firms engaged in Animal Slaughtering and Rendering and Meat
Byproduct Processing experienced the largest decreases, at 15.7 and 29.5 percent respectively. During
this same period, the number of firms engaged in Meat Processing from Carcasses and Poultry Processing
remained relatively unchanged.

Table 2-1: Number of Firms in the MPP Industry Sector, by Year and Segment

Year

Animal (except Poultry)
Slaughtering (NAICS
311611)

Meat Processed from
Carcasses (NAICS
311612)

Rendering and Meat
Byproduct
Processing (NAICS
311613)

Poultry
Processing (NAICS
311615)

Number

% Change

Number

%

Change

Number

% Change

Number

%

Change

2010

1,431



1,195



122



320



2011

1,402

-2.0%

1,208

1.1%

119

-2.5%

372

16.3%

2012

1,427

1.8%

1,202

-0.5%

114

-4.2%

307

-17.5%

2013

1,367

-4.2%

1,206

0.3%

110

-3.5%

313

2.0%

2014

1,414

3.4%

1,241

2.9%

116

5.5%

323

3.2%

2015

1,385

-2.1%

1,212

-2.3%

113

-2.6%

320

-0.9%

2016

1,344

-3.0%

1,245

2.7%

110

-2.7%

317

-0.9%

2017

1,343

-0.1%

1,196

-3.9%

99

-10.0%

310

-2.2%

2018

1,274

-5.1%

1,222

2.2%

93

-6.1%

302

-2.6%

2019

1,233

-3.2%

1,273

4.2%

89

-4.3%

307

1.7%

2020

1,207

-2.1%

1,242

-2.4%

86

-3.4%

300

-2.3%

2010-2020 Comparison

Total
Percent
Change

-15.7%

3.9%

-29.5%

-6.3%

Average
Annual
Growth
Rate

-1.7%

0.4%

-3.4%

-0.6%

Sources: U.S. Census Bureau, 2023

Table 2-2 presents the number of establishments2 in each meat product category from 2010 to 2020.
Between 2010 and 2020, the number of establishments engaged in Animal Slaughtering, Rendering and
Meat Byproduct Processing, and Poultry Processing decreased, while the number of establishments

An establishment is a single physical location at which business is conducted or services or industrial operations are
performed.

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engaged in Meat Processed from Carcasses increased. These trends are consistent with trends in the
number of firms. During this period, in the Rendering and Meat Byproduct Processing Industry sector, the
number of firms decreased at a much higher rate (29.5 percent) than the number of establishments
(7 percent), a sign of consolidation.

Table 2-2: Number of Establishments in the MPP Industry Sector, by Year and Segment

Year

Animal (except Poultry)
Slaughtering (NAICS
311611)

Meat Processed from
Carcasses (NAICS
311612)

Rendering and Meat
Byproduct
Processing (NAICS
311613)

Poultry
Processing (NAICS
311615)

Number

% Change

Number

%

Change

Number

% Change

Number

%

Change

2010

1,519



1,323



228



532



2011

1,494

-1.6%

1,345

1.7%

220

-3.5%

583

9.6%

2012

1,513

1.3%

1,349

0.3%

214

-2.7%

517

-11.3%

2013

1,458

-3.6%

1,348

-0.1%

210

-1.9%

524

1.4%

2014

1,506

3.3%

1,384

2.7%

213

1.4%

532

1.5%

2015

1,474

-2.1%

1,360

-1.7%

222

4.2%

537

0.9%

2016

1,427

-3.2%

1,407

3.5%

220

-0.9%

532

-0.9%

2017

1,431

0.3%

1,358

-3.5%

203

-7.7%

532

0.0%

2018

1,357

-5.2%

1,391

2.4%

208

2.5%

524

-1.5%

2019

1,324

-2.4%

1,441

3.6%

212

-1.9%

524

0.0%

2020

1,290

-2.6%

1,423

-1.2%

212

0.0%

517

-1.3%

2010-2020 Comparison

Total
Percent
Change

-15.1%

7.6%

-7.0%

-2.8%

Average
Annual
Growth
Rate

-1.6%

0.7%

-0.7%

-0.3%

Sources: U.S. Census Bureau, 2023

Table 2-3 presents the number of employees in each meat product category from 2010 to 2020. Between
2010 and 2020, the number of employees engaged in Meat Processed from Carcasses, Rendering and
Meat Byproduct Processing, and Poultry Processing increase by 17.3, 8.4, and 11.6 percent, while the
number of employees engaged in Animal Slaughtering had increased by only 4 percent.

Table 2-3: Number of Employees in the MPP Industry Sector, by Year and Segment

Year

Animal (except Poultry)
Slaughtering (NAICS
311611)

Meat Processed from
Carcasses (NAICS
311612)

Rendering and Meat
Byproduct
Processing (NAICS
311613)

Poultry
Processing (NAICS
311615)

Number

% Change

Number

%

Change

Number

% Change

Number

%

Change

2010

156,191



103,358



9,506



224,261



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Table 2-3: Number of Employees in the MPP Industry Sector, by Year and Segment

Year

Animal (except Poultry)
Slaughtering (NAICS
311611)

Meat Processed from
Carcasses (NAICS
311612)

Rendering and Meat
Byproduct
Processing (NAICS
311613)

Poultry
Processing (NAICS
311615)

Number

% Change

Number

%

Change

Number

% Change

Number

%

Change

2011

156,041

-0.1%

101,442

-1.9%

8,699

-8.5%

222,666

-0.7%

2012

154,061

-1.3%

103,526

2.1%

8,370

-3.8%

220,521

-1.0%

2013

155,982

1.2%

97,759

-5.6%

8,496

1.5%

216,295

-1.9%

2014

145,515

-6.7%

98,091

0.3%

8,020

-5.6%

216,598

0.1%

2015

152,594

4.9%

98,150

0.1%

8,868

10.6%

226,273

4.5%

2016

147,390

-3.4%

109,084

11.1%

8,916

0.5%

231,457

2.3%

2017

154,895

5.1%

110,978

1.7%

8,874

-0.5%

240,416

3.9%

2018

159,349

2.9%

113,443

2.2%

8,818

-0.6%

246,713

2.6%

2019

166,495

4.5%

113,508

0.1%

9,262

5.0%

243,310

-1.4%

2020

162,393

-2.5%

121,195

6.8%

10,300

11.2%

250,183

2.8%

2010-2020 Comparison

Total
Percent
Change

4.0%

17.3%

8.4%

11.6%

Average
Annual
Growth
Rate

0.4%

1.6%

0.8%

1.1%

Sources: U.S. Census Bureau, 2023

2.2 Questionnaire and Subcategorization

As described in Section 1.2.2, EPA relied on several data sources, including EPA's MPP survey, to
determine the universe of facilities in the MPP industry. Table 2-4 presents the number of facilities in
each by process and discharge type, based on EPA's analysis of these data sources. There are an
estimated 5,055 facilities in total in the MPP industry: 3,879 (77 percent) are MPP dischargers that
discharge their wastewater directly to waters of the United States (direct dischargers) or send their
wastewater to a publicly owned treatment works (POTW) (indirect dischargers), and 1,176 (23 percent)
are zero dischargers, which do not discharge any wastewater to the environment.

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Table 2-4: Number of Facilities in MPP Industry by Process and Discharge Type

Process

Number of Facilities

Direct Dischargers

Indirect Dischargers

Zero Dischargers

Total

Meat First

47

509

270

826

Meat Further

29

2,741

690

3,460

Poultry First

70

168

52

290

Poultry Further

6

169

119

294

Render

19

121

45

185

Total

171

3,708

1,176

5,055

Source: U.S. EPA analysis, 2023.

2.3 Trends in Production, Prices, and International Trade

In this section, EPA summarizes the recent trends in production, prices, imports, and exports in each U.S.
MPP industry.

2.3.1 Production and Wholesale Prices

Table 2-5 presents U.S. domestic production and wholesale prices in the beef, pork, chicken, and turkey
markets from 2010 to 2022. Between 2010 and 2022, production in beef, pork, and chicken steadily
increased. Production in turkey remained relatively stable during this period. The wholesale price for beef
spiked in 2014 and then again in 2021 but otherwise remained relatively stable. Wholesale prices for pork
and chicken remained relatively stable between 2010 to 2020 and began to steadily increase after that
period. The wholesale price for turkey remained relatively stable from 2010 to 2022.

Table 2-5: U.S. Domestic Production and Wholesale Prices from 2010 to 2022

Year

Production (Million Pounds)

Average Wholesale Prices

$2022 per Million Pounds)

Beef

Pork

Chicken

Turkey

Beef3

Porkb

Chickenc

Turkeyd

2010

26,304

22,437

36,910

5,644

$2,084,871

$1,172,215

NA

$1,170,854

2011

26,195

22,758

37,202

5,791

$2,389,579

$1,300,410

NA

$1,290,089

2012

25,913

23,253

37,039

5,967

$2,520,289

$1,104,564

NA

$1,177,918

2013

25,720

23,187

37,830

5,806

$2,457,841

$1,220,612

$1,246,533

$1,138,067

2014

24,252

22,843

38,565

5,756

$3,027,217

$1,495,682

$1,287,319

$1,261,527

2015

23,690

24,499

40,048

5,627

$2,948,197

$1,017,626

$1,100,050

$1,187,941

2016

25,221

24,941

40,696

5,981

$2,451,825

$1,008,078

$1,014,677

$1,080,553

2017

26,187

25,584

41,662

5,981

$2,498,066

$1,088,442

$1,104,901

$982,839

2018

26,872

26,315

42,601

5,878

$2,395,040

$945,428

$1,127,633

$869,146

2019

27,155

27,638

43,905

5,818

$2,505,031

$969,401

$1,003,366

$950,014

2020

27,174

28,303

44,583

5,743

$2,579,422

$897,110

$818,519

$1,039,960

2021

27,948

27,675

44,899

5,558

$2,854,281

$1,170,023

$1,082,680

$1,271,256

2022

28,290

26,994

46,206

5,222

$2,632,438

$1,113,816

$1,405,267

$1,496,779

Total
Percentage
Change6

7.55%

20.31%

25.19%

-7.48%

26.26%

-4.98%

12.73%

27.84%

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Table 2-5: U.S. Domestic Production and Wholesale Prices from 2010 to 2022

Year

Production (Million Pounds)

Average Wholesale Prices

$2022 per Million Pounds)

Beef

Pork

Chicken

Turkey

Beef3

Porkb

Chickenc

Turkeyd

a.	Average of monthly prices of: choice 1-3, 600-900 lbs; select 1-3, 600-900 lbs; and boneless, 90 percent, fresh (excluding
imported boneless, 90 percent, fresh).

b.	Average of monthly prices of: Pork cutout composite; loins, 14-19 lbs, Bl 1/4", trimmed; bellies, 10-12 lbs, skin on,
trimmed; hams, 20-23 lbs, Bl, trimmed; trimmings, 72 percent, fresh.

c.	Average of monthly prices of: national composite. Data on wholesale prices were not available for 2010 to 2012.

d.	Average of monthly prices of: Hens, 8-16 lbs; toms, 16-24 lbs; breast, 4-8 lbs; drumsticks; wings, full cut.

e.	The total percentage change for the wholesale price of chicken is calculated as the 10-year percentage change between
2013 to 2022 due to data limitations.

Source: Knight et at., 2023; Haley, 2020; Haley et at., 2016; Haley et at., 2015a; Economic Research Service, 2023a

2.3.2 International Trade

Table 2-6 presents U.S. imports and exports for beef, pork, chicken, and turkey from 2010 to 2022.
Imports and exports for beef increased relatively steadily between 2010 and 2022 with a temporary peak
in imports and dip in exports in 2015. Pork exports steadily increased between 2010 to 2020 with a slight
peak in 2020 and a steady decline between 2020 and 2022. Pork imports remained relatively stable
between 2010 to 2022. During this period, imports and exports of chicken remained relatively stable with
a slight dip in exports in 2015. Turkey imports during this period remained relatively stable and turkey
exports peaked in 2012 until a dip in 2015. Turkey exports then steadily increased until 2019 until they
began to steadily decline into 2022.

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Table 2-6: U.S. Imports and Exports by Meat Product from 2010 to 2022 (Million Pounds)

Year

Imports

Exports

Beef3

Pork

Chicken

Turkey

Beef3

Pork

Chicken

Turkey

2010

2,298

859

107

25

2,300

4,223

6,762

581

2011

2,057

803

107

21

2,785

5,196

6,978

703

2012

2,220

802

111

22

2,452

5,379

7,274

797

2013

2,250

880

122

20

2,588

4,986

7,345

741

2014

2,947

1,011

117

27

2,574

5,092

7,297

775

2015

3,368

1,116

131

45

2,267

5,010

6,321

529

2016

3,012

1,091

131

50

2,557

5,239

6,645

569

2017

2,993

1,116

126

25

2,859

5,632

6,786

622

2018

2,998

1,042

139

19

3,160

5,877

7,069

611

2019

3,058

945

131

12

3,026

6,321

7,103

639

2020

3,339

904

145

21

2,951

7,279

7,368

571

2021

3,346

1,180

155

22

3,431

7,026

7,355

548

2022

3,391

1,344

176

85

3,536

6,338

7,278

407

Total
Percentage
Change

47.6%

56.4%

65.4%

238.7%

53.8%

50.1%

7.6%

-29.9%

a. The import and export values for beef also include veal.
Source: Economic Research Service, 2023b

2.4 Trends in Industry Concentration

In this section, EPA summarizes the available information on consolidation and concentration within the
national MPP industry.

As presented in Table 2-7, according to Economic Census data, the number of firms in each of the MPP
industries listed above increased between 2012 and 2017, with the exception of NAICS 311611 which
experienced a moderate decline in the number of firms. Additionally, the percentage of sales or revenue
attributable to the largest firms in NAICS 311611,311612, and 311615 were relatively unchanged
between 2012 and 2017. In NAICS 311613, there was a 10.3 percent increase in sales or revenue
attributable to the four largest firms, pointing to increased concentration in the rendering and meat
byproduct processing industry.

Another indication of concentration in these industries is the Herfindahl-Hirschman index (HHI), which is
a measure of the size of firms in an industry in relation to the size of the industry. HHI values under 1,500
point to a competitive market, values between 1,500 and 2,000 point to a moderately concentrated market,
and values above 2,500 point to a highly concentrated market. The HHI value for NAICS 311611
increased from 1,085 to 1,175, indicating this industry remained competitive between 2012 and 2017. The
HHI value for NAICS 311612 increased from 332 to 355, while the HHI value for NAICS 311615
decreased from 600 to 565, suggesting that these industries also remained competitive. The HHI value for
NAICS 311613 increased substantially, from 673 in 2012 to 1,109 in 2017, indicating that while this
industry became significantly more concentrated overtime, it still remained competitive.

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Table 2-7: 2012 and 2017 MPP Industry Economic Census







Sales, value of shipments, or revenue of







Number of

largest firms as percent of total sales,

Herfindahl-



Firms

value of shipments, or revenue (%)

Hirschman index

Industry

2012

2017

2012

2017

2012

2017

Animal (except Poultry)

1,420

1,297

100.0

100.0





Slaughtering (311611)













4 largest firms

4

4

60.7

63.4

-

-

8 largest firms

8

8

75.8

76.8

-

-

20 largest firms

20

20

86.4

87.1

-

-

50 largest firms

50

50

92.8

93.3

1,085

1,175

Meat Processed from

1,204

1,241

100.0

100.0





Carcasses (311612)













4 largest firms

4

4

32.8

33.0

-

-

8 largest firms

8

8

42.3

41.6

-

-

20 largest firms

20

20

55.4

56.0

-

-

50 largest firms

50

50

71.2

71.5

332

355

Rendering and Meat

115

100

100.0

100.0





Byproduct Processing









-

-

(311613)













4 largest firms

4

4

44.5

54.8

-

-

8 largest firms

8

8

62.7

71.2

-

-

20 largest firms

20

20

83.4

89.1

-

-

50 largest firms

50

50

96.3

98.6

673

1,109

Poultry Processing

319

308

100.0

100.0





(311615)













4 largest firms

4

4

39.8

39.4

-

-

8 largest firms

8

8

54.1

54.3

-

-

20 largest firms

20

20

77.4

76.6

-

-

50 largest firms

50

50

92.4

92.7

600

565

Source: U.S. Census Bureau, 2017b

According to a 2000 USDA study (MacDonald et al., 2000), based on U.S. Census data, the four-firm
concentration ratio3 for the cattle slaughter industry rose from 25 percent in 1977 to 71 percent in 1992.
During this same period, the four-firm concentration ratio for the hog industry increased from 31 to
43 percent, 22 to 41 percent for the chicken industry, and 41 to 45 percent for the turkey industry. The
authors of this report find similar results for the same period using Grain Inspection, Packers and
Stockyards Administration (GIPSA) data. Moreover, in 2021, Deese et al. (2021a) report that the top four
processors of beef, poultry, and pork account for 82, 54, and 66 percent of these markets, respectively.

Additionally, according to a USDA study from 2018 (MacDonald et al., 2018), the median sales per
company for broilers, fed cattle, hogs and pigs, and turkeys increased by 123, 119, 3,233, and 33 percent
between 1987 to 2012, respectively. These increases in sales midpoints indicate a shift of production of
these commodities towards larger farms with more revenue. The median inventory per company for beef
cows over this period increased marginally from 86 to 110 cows (24 percent). These trends in
consolidation slowed between 2007 and 2012. Deese et al. (2021b) report that the four largest meat-

The four-firm concentration ratio measures the combined share of the market for the four largest firms in that market.

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processing companies operating in the United States increased gross profits by 120 percent and net
income by 500 percent since 2019.

Table 2-8 presents the average number of establishments per firm in each meat product category from
2010 to 2020. Between 2010 and 2020, the average number of establishments per firm engaged in Animal
Slaughtering, Meat Processed from Carcasses, and Poultry Processing remained relatively unchanged,
with an average annual growth rate of 0.1%, 0.3%, and 0.4%, respectively. However, the average number
of establishments per firm engaged in Rendering and Meat Byproduct Processing saw a substantial
increase of 31.9% from 2010 to 2020, and an average annual growth rate of 2.8%.

An increase in the average number of establishments per firm is a sign of consolidation, resulting in larger
firms operating a greater number of unified establishments. On the other hand, a lower average indicates a
less consolidated market, with greater dispersion or fragmentation of firm owned establishments . The
high average annual growth rate of the average number of establishments per firm engaged in Rendering
and Meat Byproduct Processing is a sign of consolidation, either by way of acquisitions or mergers with
other businesses. Furthermore, a more consolidated industry sector has the potential to allow firms to
more easily benefit from economies of scale.

Table 2-8: Average Number of Establishments per Firm in the MPP Industry Sector, by Year and
Segment

Year

Animal (except Poultry)
Slaughtering (NAICS
311611)

Meat Processed from
Carcasses (NAICS
311612)

Rendering and Meat
Byproduct
Processing (NAICS
311613)

Poultry
Processing (NAICS
311615)

Number

% Change

Number

%

Change

Number

% Change

Number

%

Change

2010

1.06



1.11



1.87



1.66



2011

1.07

0.4%

1.11

0.6%

1.85

-1.1%

1.57

-5.7%

2012

1.06

-0.5%

1.12

0.8%

1.88

1.5%

1.68

7.5%

2013

1.07

0.6%

1.12

-0.4%

1.91

1.7%

1.67

-0.6%

2014

1.07

-0.1%

1.12

-0.2%

1.84

-3.8%

1.65

-1.6%

2015

1.06

-0.1%

1.12

0.6%

1.96

7.0%

1.68

1.9%

2016

1.06

-0.2%

1.13

0.7%

2.00

1.8%

1.68

0.0%

2017

1.07

0.4%

1.14

0.5%

2.05

2.5%

1.72

2.3%

2018

1.07

0.0%

1.14

0.3%

2.24

9.1%

1.74

1.1%

2019

1.07

0.8%

1.13

-0.6%

2.38

6.5%

1.71

-1.6%

2020

1.07

-0.5%

1.15

1.2%

2.47

3.5%

1.72

1.0%

2010-2020 Comparison

Total
Percent
Change

0.7%

3.5%

31.9%

3.7%

Average
Annual
Growth
Rate

0.1%

0.3%

2.8%

0.4%

Sources: U.S. Census Bureau, 2023

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2.5	Economies of Scale

Recent trends in MPP industry consolidation and concentration may be partially attributable to economies
of scale within the industry (MacDonald et al., 2000). Ollinger et al. (2005) find evidence of large
economies of scale within the poultry industry in the United States. The authors find that the production
costs for the largest poultry processing plants was 8 percent lower than plants half the size and 20 percent
lower than plants one eighth the size between 1967 to 1992. MacDonald and Ollinger (2000) find
evidence of moderate economies of scale in the U.S. hog industry. The authors find that the largest hog
processing plants could sell products at a cost 2 to 3 percent lower than plants half the size and 10 percent
lower than plants one tenth the size between 1963 and 1992.

2.6	Product Mixes

In this section we summarize the recent trends in product mixes in the MPP industry. Table 2-9 presents
product mix (commodity production as a percentage of the total industry production) from 2010 to 2022.
Overall, in 2022, beef, lamb and mutton, and pork made up about 26, 0.12, and 25 percent of the total
meat produced in the United States, respectively. Additionally, chicken and turkey made up about 43 and
5 percent of total meat production in 2022, respectively. Between 2010 and 2022, the industry shares of
beef, lamb and mutton, and turkey decreased. During this same period, the industry shares of pork and
chicken increased.

Table 2-9: Annual Production Levels by Meat Category from 2010 to 2022

Year

Annual Industry Shares of Production (Million Pounds)

Beef

Lamb and Mutton

Pork

Chicken

Turkey

2010

28.76%

0.18%

24.53%

40.36%

6.17%

2011

28.44%

0.16%

24.71%

40.40%

6.29%

2012

28.07%

0.17%

25.19%

40.12%

6.46%

2013

27.75%

0.17%

25.01%

40.81%

6.26%

2014

26.48%

0.17%

24.95%

42.11%

6.29%

2015

25.20%

0.16%

26.06%

42.60%

5.99%

2016

26.00%

0.15%

25.72%

41.96%

6.17%

2017

26.30%

0.15%

25.70%

41.85%

6.01%

2018

26.39%

0.15%

25.84%

41.84%

5.77%

2019

25.94%

0.14%

26.41%

41.95%

5.56%

2020

25.65%

0.13%

26.72%

42.08%

5.42%

2021

26.31%

0.13%

26.05%

42.27%

5.23%

2022

26.48%

0.12%

25.27%

43.25%

4.89%

A 2010 - 2022

-2.28%

-0.06%

0.73%

2.89%

-1.28%

Annual Average

26.75%

0.15%

25.55%

41.66%

5.88%

Source: Knight et al., 2023; Haley, 2020; Haley et al., 2016; Haley et al., 2015b

According to MacDonald et al. (2018), the number of farms specializing in livestock production has
increased in tandem with observed trends in consolidation. The percent of livestock produced by farms
with no crop production increased by 22 percent between 1996 and 2015. Since the 1970s, cattle slaughter
plants have transitioned away from just selling carcasses to further processors and towards slaughtering

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and processing carcasses to make boxed (cut-up) and ground beef products. MacDonald et al. (2000) find
that, based on industry averages, boxed beef accounted for 9.3 percent of total shipments in 1963 and
grew to 56.2 percent in 1992. This trend was largely driven by large firms who saw their share of boxed
beef shipments rise from 8.1 percent to 71.6 percent.

During the same period, MacDonald et al. (2000) found that hog slaughter plants have also moved away
from vertically integrated operations where they were slaughtering carcasses, cutting them up and then
producing final products such as bacon, sausages, or ham, and towards specializing in just producing cut-
up carcasses and selling them to brand-name retailers for further processing. Based on industry averages,
cut-up carcasses accounted for 27.5 percent of total shipments at hog slaughter plants in 1963 and grew to
52.4 percent in 1992. Moreover, the share of bacon, ham, and other cured pork products produced at non-
slaughter plants as a share of total shipments in the market grew from 42.8 percent in 1982 to 63.1 percent
in 1992. The share of sausage and similar products produced at non-slaughter plants a share of total
shipments in the market grew from 55.9 percent in 1982 to 77 percent in 1992. MacDonald et al. (2000)
further explain that slaughter plants can produce boxed beef and cut-up pork at a lower cost per pound
and avoid the higher transportation costs of shipping whole and half carcasses. Because of this, meat
processors, wholesalers, and retailers commonly purchase boxed beef and cut-up pork from slaughter
plants.

2.7 Summary

Over the past two decades, the U.S. MPP industry has undergone significant consolidation, resulting in
fewer, but larger dominant plants. This consolidation has led to increased concentration, raising concerns
about competition and market power. The shift toward larger plants has been driven by technological
scale economies and changes in labor relations, providing cost advantages and economies of scale,
enabling them to outcompete smaller facilities (MacDonald et al. (2018). Moreover, data pertaining to the
industry's Herfindahl-Hirschman index (see Table 2-7), average number of establishments per firm
(Table 2-8), and establishment entry and exit rates (see Figure 6-1) suggest a trend towards consolidation.

Despite the current state of the industry, there is no consensus on whether the trend towards further
consolidation and specialization will continue, or if the observed changes have reached a plateau. With
global meat consumption anticipated to increase by 14% by 2030, compared to the base period average of
2018-2020 (OECD/FAO, 2021), there is a possibility of further consolidation and specialization in the
U.S. to meet global demand. However, new governmental actions, such as the Meat and Poultry Supply
Chain Action Plan, that aim to combat market dominance, could lead to a decline in consolidation in the
industry (USDA, 2022). Additionally, advancements in the meat-replacement and alternative products
industry, which have become significantly cheaper and have a lower climate impact than traditional meat
production, have the potential to disrupt the current market composition of the U.S. MPP industry
(Brennan et al., 2021; Newton et al., 2021). As a result, the future of the U.S. MPP industry remains
uncertain, as multiple factors have the potential to reshape the industry from its current state.

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3 Compliance Costs

In developing the proposed rule, EPA assessed the costs and economic impacts for three regulatory
options summarized in Table 1-1, with and without chlorides. The options are labeled Option 1 through
Option 3, in order of the stringency of the effluent limits relative to the baseline, and Option 1 with
chlorides through Option 3 with chlorides. The key input for the compliance cost analysis is the estimated
costs to MPP facilities (and their owners) for implementing control technologies upon which the proposed
BAT and BPT limitations and pretreatment standards are based.4 This chapter summarizes EPA estimates
of the incremental compliance costs attributable to the regulatory options.5 EPA determined that state and
federal governments do not own regulated entities and thus would not incur material incremental costs,
but control authorities would incur some additional reporting and recordkeeping costs.

The TDD describes the control technologies and their respective wastewater treatment performance in
greater detail (U.S. Environmental Protection Agency, 2023c). The TDD also describes how EPA
estimated facility-specific capital and operation and maintenance (O&M) costs. The cost analysis uses the
2004 rule as the baseline and incorporates treatment technology that facilities have in place at the time of
this proposed action.

3.1 Analysis Approach and Inputs

EPA estimated costs to MPP facilities for meeting the limitations of the regulatory options. There are
three principal steps to compliance cost development, the last of which is the focus of the discussion
below:

1.	Determining the set of facilities potentially implementing compliance technologies for each
regulatory option. See TDD for details.

2.	Developing facility-level costs for each technology option. See TDD for details.

3.	Estimating total industry costs for all facilities in the MPP universe for each of the regulatory
options.

EPA reports costs in 2022 dollars and discounts future costs to 2025, the anticipated rule promulgation
year.

3.1.1.1 Facility-Specific Costs Approach

As detailed in the TDD, EPA developed costs for MPP facilities to implement treatment technologies to
control the pollutants addressed by the regulatory options.

EPA assessed the operations and treatment system components currently in place at a given facility, and
identified equipment and process changes that the facility would likely make to meet each of the

Dischargers are not required to use the technologies specified as the basis for the rule. They are free to identify other
perhaps less expensive technologies as long as they meet the BAT limitations and pretreatment standards in the rule.
The analysis of the regulatory options presented in this RIA apply only to existing sources. Impact analyses for BAT
and BPT limits are not reported separately. New sources would also be subject to New Source Performance Standards
(NSPS) equivalent to BAT and Pretreatment Standards for New Sources (PSNS) equivalent to PSES.

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regulatory options presented in Table 1-1. Facilities that do not discharge wastewater (1,176 facilities that
are zero dischargers) or that employ technologies which would already meet the given limitations or
standards do not incur incremental costs under the regulatory options. Facilities that fall below the
applicable production threshold under each regulatory option also do not incur incremental costs.

3.1.1.2	Facility-Level Costs

EPA estimated compliance costs for all existing MPP facilities that generate wastestreams covered by the
regulatory options, estimated to be a total of 3,879 facilities with direct or indirect discharges. Of these
facilities, only a subset would incur non-zero costs under any of the regulatory options analyzed based on
existing control technologies and production thresholds defined in the regulatory options: 845 facilities
under options 1 and 2, 1,620 facilities under option 3, 946 facilities under options 1 and 2 with chlorides,
and 1,621 facilities under option 3 with chlorides. The TDD provides additional details on this analysis.

The major components of technology costs are:

•	Capital costs, which include the cost of compliance technology equipment, installation,
construction, and other upfront, non-annually recurring outlays associated with compliance with
the regulatory options. As explained in the TDD, compliance technologies are assumed to have a
useful life of either 20 years or 40 years. EPA assumes that facilities incur full capital costs in the
first installation year and 70 percent of capital costs 20 years later, the year in which 70 percent of
capital equipment must be replaced at the end of its useful life of 20 years.

•	Annual O&M costs, which include the labor costs for operating and inspecting the compliance
technology equipment, as well as the cost of materials and electricity to run the treatment units.
Facilities incur these costs each year.

3.1.1.3	Total Compliance Costs

EPA used the following methodology and assumptions to aggregate compliance cost components,
described in the preceding sections, and develop total facility compliance costs for the three regulatory
options, with and without chlorides:

•	EPA estimated compliance costs (including zero costs, where applicable) for each of the 3,879
MPP facilities that generate wastewater discharges (see TDD for details). All other facilities
covered by the MPP point source category do not generate wastestreams covered by the
regulatory options and therefore incur zero costs.

•	EPA discounted all future cost values to 2025. For the social costs presented in this section, EPA
used a discount rate of 3 percent. To assess impacts on firms, as discussed in the remainder of this

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RIA document, EPA used the industry's estimated private cost of capital.6 EPA also discounted
costs at 7 percent.7

•	EPA annualized 70 percent of one-time capital costs over 20 years, and 30 percent of one-time
capital costs over 40 years, to reflect the useful life of different components of the treatment
technologies.

•	EPA added annualized capital and annual O&M costs to derive total annualized compliance costs.

For the assessment of compliance costs to MPP facilities as an estimate of total social cost, EPA
considered costs on a pre-tax basis. Pre-tax costs provide insight on the total expenditures as initially
incurred by the facilities.

3.1.1.4 Estima ted Social Cost of Compliance

EPA calculated the expected costs to society incurred because of compliance with each regulatory option.
These costs incorporate a compliance schedule that varies by discharge type and assumes the time profiles
of technology implementation and administrative costs. EPA incorporated a compliance schedule
assuming:

•	Direct dischargers will come into compliance over five years, with 20 percent incurring capital
costs to install treatment technology in each of the first five years of the analysis period. Direct
dischargers will also start to incur annual O&M costs on this schedule. As described above, 70
percent of capital must be re-installed after 20 years. As a result, 20 percent of direct dischargers
will incur 70 percent of capital costs in each of years 21-25.

•	All indirect dischargers will come into compliance, and install treatment technology, in the third
year of the analysis period and replace 70 percent of capital costs in year 24, after the 20-year
useful life. Indirect dischargers will start to incur annual O&M costs in year 3.

Social costs also include the administrative costs of compliance, including:

•	A one-time burden for facilities to read and comprehend the rule, estimated to be 8 hours per
facility.

•	A one-time burden for Control Authorities and the Agency to review the ELGs and establish
monitoring requirements, and an annual burden to review pollutant data submitted by MPP

EPA estimated the industry's private cost of capital as the weighted average cost of capital (WACC) based on the
median values reported in the MPP detailed questionnaire for debt-to-equity ratio, interest rate of debt, and equity rate
of return, as well as the federal corporate income tax rate and national average state corporate income tax rate. See
Section 5.2.3 for more information on the WACC calculation.

The rate of 7 percent is an estimate of the private opportunity cost of capital. For the social cost analysis presented in
Chapter 7 of the BCA, EPA uses a3 percent discount rate. This discount rate reflects society's valuation of differences
in the timing of consumption; the 7 percent discount rate is an estimate of the private opportunity cost of capital to
society. In Circular A-4, the Office of Management and Budget (OMB) recommends that 3 percent be used when a
regulation affects private consumption, and 7 percent in evaluating a regulation that will mainly displace or alter the
use of capital in the private sector (U.S. OMB, 2003; updated 2009). The same discount rates are used for both benefits
and costs in the BCA. Costs at a 7 percent discount rate are presented in Appendix A.

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dischargers. These burdens are incurred in accordance with dischargers' compliance schedule, as
described above.

After creating a compliance schedule for technology implementation, EPA summed the costs each
discharger is expected to incur in each year and aggregated these costs to estimate the total social costs for
each year of the analysis. Specifically, EPA assumed that capital costs for technology equipment,
installation, and other upfront, non-annually recurring expenditures associated with compliance with the
regulatory options are incurred in the compliance year for each facility. Annual fixed and variable O&M
(e.g., operating labor, maintenance labor and materials, electricity required to operate treatment
technologies) are incurred each year beginning the year the technology is installed.

EPA then calculated the present value of these costs as of the anticipated rule promulgation year by
discounting the cost in each year back to 2025 using a 3 percent discount rate, assuming that costs accrue
at the end of each year in the analysis period. EPA also calculated the annualized value, using a 3 percent
discount rate over a 40-year period.

3.2 Key Findings for Regulatory Options

Table 3-1 presents annualized incremental costs for each regulatory option, discounted at 3 percent,
relative to the baseline. These costs represent the basis of the social cost analysis described above. EPA is
considering pretreatment standards with conditional limits for nutrient removal which would provide
flexibility for POTWs to waive nutrient limits for MPP industrial users. This could potentially result in
lower cost to MPP facilities, however EPA cannot predict who would use this flexibility, and therefore
cannot estimate those cost savings. EPA is requesting comment on conditional limits for MPP indirect
dischargers. Specifically, EPA is requesting data that may help analyze these impacts in the future as well
as the incremental impacts on cost savings and benefits.

Table 3-1: Estimated Total Social Costs by Regulatory Option and Discharge Type, 3 percent
discount rate (in millions, 2022$, at 2025)

Regulatory Option

Direct

Indirect

Total

Option 1

$216.5

$15.3

$231.9

Option 2

$216.5

$426.3

$642.8

Option 3

$223.7

$853.6

$1,077.3

Option 1 with chlorides

$279.6

$109.9

$389.6

Option 2 with chlorides

$279.6

$520.9

$800.5

Option 3 with chlorides

$286.8

$948.2

$1,235.0

Source: U.S. EPA Analysis, 2023.

Table 3-2 provides a more detailed breakdown of the social cost calculations. The table presents, for each
regulatory option, the assumed time profiles of technology implementation costs incurred relative to the
baseline. The annualized costs, discounted 3 percent, can be found at the bottom of the table. Costs are
highest in 2049 and 2028, when indirect facilities are assumed to incur capital costs. Control Authorities
and the Agency also incur 60 percent of annual costs for direct dischargers and 100 percent of annual
costs for indirect dischargers in 2049.

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Table 3-2: Time Profile of Costs to Society (in millions, 2022$)

Year

Option 1

Option 2

Option 3

Option 1 with
chlorides

Option 2 with
chlorides

Option 3 with
chlorides

2025

$0.0

$0.0

$0.0

$0.0

$0.0

$0.0

2026

$191.9

$191.9

$198.1

$251.1

$251.1

$257.3

2027

$229.7

$229.7

$237.2

$300.2

$300.2

$307.7

2028

$353.1

$2,403.8

$4,942.3

$880.4

$2,931.1

$5,469.5

2029

$321.7

$682.8

$1,043.3

$499.6

$860.7

$1,221.2

2030

$361.3

$722.4

$1,084.2

$550.4

$911.5

$1,273.4

2031

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2032

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2033

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2034

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2035

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2036

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2037

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2038

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2039

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2040

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2041

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2042

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2043

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2044

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2045

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2046

$316.1

$677.2

$1,037.6

$490.9

$852.0

$1,212.3

2047

$316.1

$677.2

$1,037.6

$490.9

$852.0

$1,212.3

2048

$316.1

$677.2

$1,037.6

$490.9

$852.0

$1,212.3

2049

$365.6

$1,909.4

$3,795.0

$792.8

$2,336.6

$4,222.2

2050

$316.1

$677.2

$1,037.6

$490.9

$852.0

$1,212.3

2051

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2052

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2053

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2054

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2055

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2056

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2057

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2058

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2059

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2060

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2061

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2062

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2063

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2064

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2065

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

PV, 3%

$5,359.4

$14,858.2

$24,900.8

$9,004.5

$18,503.3

$28,545.9

Annualized













costs, 3%

$231.9

$642.8

$1,077.3

$389.6

$800.5

$1,235.0

Source: U.S. EPA Analysis, 2023.

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3: Compliance Costs

3.3 Key Uncertainties and Limitations

Despite EPA's use of best available data, including information provided to EPA in the MPP survey, this
analysis has uncertainties:

•	The MPP survey did not have a 100 percent response rate. In the absence of accurate data for a
given facility, EPA made assumptions about facility production which affect the applicability of
each regulatory option based on the production thresholds presented in Table 1-1, as well as the
estimated quantity of wastewater produced and thus treatment costs for meeting the limits under
applicable regulatory options. To the extent that actual production at facilities differs from EPA's
estimated production, the number of affected facilities and total costs of the proposed regulatory
options may be over- or understated.

•	EPA assumed that 70 percent of capital costs are for technology components that have a useful
life of 20 years, and 30 percent of capital costs are for technology components that have a useful
life of 40 years. This is an assumption based on averaging over compliance technologies,
technology components, and facilities, and may not reflect the exact equipment installed at each
facility.

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4: Screening-Level Economic Impacts

4 Cost and Economic Impact Screening Analyses

4.1	Analysis Overview

EPA assessed the costs and economic impacts of the regulatory options using a screening-level
assessment reflecting current operating characteristics of MPP facilities and with assignment of estimated
compliance costs to those facilities. This screening-level assessment, which is documented in this chapter,
includes two specific analyses:

•	A cost-to-revenue (CTR) screening analysis to assess the impact of compliance outlays on
individual MPP facilities (Section 4.3)

•	A CTR screening analysis to assess the impact of compliance outlays on domestic parent-entities
owning MPP facilities (Section 4.4)

4.2	Total After-Tax Private Costs

After-tax costs are a more appropriate measure of compliance impact on privately owned for-profit
facilities than pre-tax costs. Thus, EPA uses after-tax compliance costs for the impact screening analyses
presented in this chapter, as well as all impact analyses following this chapter. EPA calculated the after-
tax compliance costs by applying combined federal and state tax rates to the pre-tax cost values. For this
adjustment, EPA used state corporate tax rates for 2023 (Tax Foundation, 2023) combined with a 21
percent federal corporate tax rate from the Department of the Treasury, Internal Revenue Service (U.S.
Department of the Treasury Internal Revenue Service, 2023). For this analysis, EPA used a discount rate
of 7.6 percent, equal to the industry's estimated private cost of capital.6

Table 4-1 presents total annualized after-tax compliance costs by regulatory option and discharge type.8

Table 4-1: Estimated Total Annualized After-Tax Compliance Costs (in millions, 2022$)

Regulatory Option

Direct

Indirect

Total

Option 1

$196.4

$13.9

$210.3

Option 2

$196.4

$394.0

$590.4

Option 3

$202.6

$793.0

$995.6

Option 1 with chlorides

$253.6

$100.5

$354.1

Option 2 with chlorides

$253.6

$480.6

$734.2

Option 3 with chlorides

$259.8

$879.6

$1,139.4

Source: U.S. EPA Analysis, 2023.

4.3 Cost-to-Revenue Analysis: Facility-Level Screening Analysis

The CTR measure compares the cost of implementing and operating compliance technologies with the
facility's operating revenue to provide a screening-level assessment of the impact of the regulatory
options. In assessing the cost impact of the regulatory options on MPP facilities in this screening-level
analysis, the Agency assumed that the facilities would not be able to pass compliance costs either
downstream to meat and poultry product consumers in the form of increased prices for end-products or

Total costs include a one-time burden of 8 hours per facility for MPP dischargers to read and understand the rule. EPA
did not include these costs in its assessment of impacts (Sections 4.3-4.4, Chapters 5-9) as this burden is de minimis and
is not expected to affect the results.

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4: Screening-Level Economic Impacts

upstream to farmers in the form of reduced prices for inputs. This is a worst-case scenario of regulatory
impacts to MPP facilities.

4.3.1 Analysis Approach and Data Inputs

EPA divided annualized after-tax compliance costs by revenue at the facility level.9 As described below,
EPA used a combination of MPP survey data, facility-level revenue estimates, and Dun & Bradstreet
(D&B) Hoover's revenue estimates. EPA assesses facilities incurring costs below one percent of revenue
as unlikely to face material economic impacts, facilities with costs of at least one percent but less than
three percent of revenue as having a higher chance of facing material economic impacts, and facilities
incurring costs of at least three percent of revenue as having a still higher probability of material
economic impacts.

4.3.1.1	MPP Survey Revenue

For facilities that responded to the MPP detailed questionnaire and provided financial data that EPA
deemed reliable, EPA used reported 2021 facility revenue, adjusted to 2022 dollars using the GDP
deflator (U.S. Bureau of Economic Analysis, 2023), for the facility CTR analysis. EPA reviewed financial
responses to the MPP detailed questionnaire to assess the validity of the information provided by
comparing responses across years, across facilities owned by the same parent company, to firm-level
values, or to reported production. Where possible, EPA cleaned and manually adjusted data that had
apparent issues, such as values reported in the wrong units. In some cases, EPA was able to identify
values that were misreported (e.g., several facilities owned by the same parent company reported the same
facility-level revenue) but was unable to make appropriate corrections; EPA did not use these data. In
these cases, EPA relied on Hoover's or estimated revenue.

4.3.1.2	Dun & Bradstreet Hoovers Revenue Data

EPA also collected revenue data from D&B Hoovers dataset for facilities under the 4-digit NAICs code:
3116 (animal slaughtering and processing). EPA conducted a matching process programmatically in R to
match records in the D&B Hoovers data ("Hoovers facilities") to MPP facilities using an approximate
string matching method based on the Jaro-Winkler (JW) string metric (NIST, 2022). To complete this
matching process, EPA relied on information about MPP facilities, as well as information reported in
Hoovers records, on the address, city, state, county, and zip code of facilities. If this process returned no
results, EPA also matched based on facility name, limiting matches to those in the same city and state.

Where possible, the Agency also identified the parent company of MPP facilities by identifying instances
where a parent company name was present in the MPP facility name.10 EPA conducted this process using
a list of parent companies based on the top 100 meat and poultry processors in the United States by net
sales in 2021 from the National Provisioner (The National Provisioner, n.d.) and the 100 Hoovers parent
companies with the most company locations listed in the Hoover's dataset. Moreover, EPA conducted

For private, tax-paying entities, after-tax costs are a more relevant measure of potential private cost burden than pre-tax
costs.

In most instances, EPA shortened the parent company name to the first one or two words in the name to facilitate more
accurate matching.

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4: Screening-Level Economic Impacts

this same process using brand names11 from the top 15 firms with the most facilities in the MPP facility
list.

After completing the full matching process, EPA conducted a manual review of all matches and kept only
those matches determined to be correct.

4.3.1.3 Revenue Estimation Approach

If a facility did not report revenue in the MPP detailed questionnaire, and EPA was unable to identify a
reliable Hoovers revenue estimate, EPA estimated facility-level revenue based on production and
estimated unit sales ($/lb). EPA first calculated average unit sales by process type by dividing reported
MPP sales by production for facilities that responded to the MPP detailed questionnaire, limited to those
facilities that EPA deemed to have valid survey revenue and production.

EPA then multiplied these unit sale prices by the reported or estimated production,12 based on the
facility's process type. If a facility reported more than one process type, EPA multiplied the value of
production for those process types by their respective average unit sale prices. EPA calculated the
estimated revenue by facility as the sum of the total sales by process type at that facility.

4.3.2 Key Findings for Reguia tory Options

Table 4-2 presents the facility CTR analysis results for each of the regulatory options. Under all
regulatory options analyzed, most facilities would not experience compliance costs exceeding one or three
percent of revenue. However, additional facilities would experience costs greater than one percent of
revenue (and less than three percent of revenue) with regulatory Options 3 and 2 compared to Option 1
(with and without chloride costs).

Table 4-2: Facility-Level After-Tax Compliance Cost-to-Revenue Analysis Results by Discharge
Type and Regulatory Option





Total
Number

Number of Facilities with a
Ratio of

Percent of All Dischargers with a
Ratio of

Discharge
Type

Total
Number of
Dischargers

of
Facilities
with
Costs

0%a

<1%

>1
and
<3%

>3%

0%a

<1%

>1
and
<3%

>3%

Option 1

Direct

171

126

45

120

5

1

26%

70%

3%

0.6%

Indirect

3,708

719

2,989

718

0

1

81%

19%

0%

0.03%

Total

3,879

845

3,034

838

5

2

78%

22%

0.1%

0.1%

Option 2

Direct

171

126

45

120

5

1

26%

70%

3%

0.6%

Indirect

3,708

719

2,989

708

7

4

81%

19%

0.2%

0.1%

Total

3,879

845

3,034

828

12

5

78%

21%

0.3%

0.1%

EPA identified brand names by researching company websites and the USDA Meat, Poultry, and Egg Product
Inspection Directory (https://www.fsis.usda.gov/inspection/establishments/meat-poultry-and-egg-product-inspection-
directory).

See the TDD for more information on EPA's methodology for estimating production in cases where reported
production was unavailable or deemed inaccurate (U.S. Environmental Protection Agency, 2023c).

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4: Screening-Level Economic Impacts

Table 4-2: Facility-Level After-Tax Compliance Cost-to-Revenue Analysis Results by Discharge
Type and Regulatory Option





Total
Number

Number of Facilities with a
Ratio of

Percent of All Dischargers with a
Ratio of

Discharge
Type

Total
Number of
Dischargers

of
Facilities
with
Costs

0%a

<1%

>1
and
<3%

>3%

0%a

<1%

>1
and
<3%

>3%

Option 3

Direct

171

135

36

128

4

3

21%

75%

2%

2%

Indirect

3,708

1,485

2,223

1,448

27

10

60%

39%

0.7%

0.3%

Total

3,879

1,620

2,259

1,576

31

13

58%

41%

0.8%

0.3%

Option 1 with chlorides

Direct

171

129

42

120

6

3

25%

70%

4%

2%

Indirect

3,708

817

2,891

811

0

6

78%

22%

0%

0.2%

Total

3,879

946

2,933

931

6

9

76%

24%

0.2%

0.2%

Option 2 with chlorides

Direct

171

129

42

120

6

3

25%

70%

4%

2%

Indirect

3,708

817

2,891

801

9

7

78%

22%

0.2%

0.2%

Total

3,879

946

2,933

921

15

10

76%

24%

0.4%

0.3%

Option 3 with chlorides

Direct

171

136

35

126

6

4

20%

74%

4%

2%

Indirect

3,708

1,485

2,223

1,445

30

10

60%

39%

0.8%

0.3%

Total

3,879

1,621

2,258

1,571

36

14

58%

41%

0.9%

0.4%

a. These facilities already meet discharge requirements for the wastestreams controlled by a given regulatory option and
therefore are not estimated to incur compliance costs.

Source: U.S. EPA analysis, 2023.

4.3.3 Uncertainties and Limitations

Despite EPA's use of the best available information and data, this analysis of facility-level impacts has
uncertainties and limitations, including:

•	EPA lacked revenue data for many facilities. Of the 3,879 MPP dischargers, 173 facilities
reported revenue that EPA determined to be valid. EPA used estimated Hoover's revenue for an
additional 626 facilities. EPA estimated revenue for the remaining 3,080 facilities. In addition,
EPA relied on revenue from different data years - reported and estimated revenue reflect 2021
production and prices; D&B Hoovers revenue are from 2020. To the extent that temporary shocks
to prices and production in 2020 resulting from the COVID-19 pandemic (Whitehead et al., 2022)
affected 2020 revenue, as compared to 2021, comparing compliance costs based on 2021
production to 2020 revenue may over- or underestimate the impact of the regulatory options.

•	As noted above, the zero-cost pass-through assumption represents a worst-case scenario from the
perspective of the facility owner. To the extent that companies can pass some compliance costs
on to consumers or farmers, this analysis overstates the potential impact of the regulatory options
on MPP facilities.

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4: Screening-Level Economic Impacts

•	EPA utilized a 40-year analysis period, with MPP facilities incurring full capital costs in year one
and 70 percent of capital costs in year 21. EPA reviewed technology components to calculate 70
percent, which is an average of the portion of capital that would need to be replaced after 20
years. In practice, facilities may have to replace more or less than this average, which may lead
them to incur compliance costs that differ from EPA's estimates.

•	MPP facilities may be able to offset the costs of compliance by offsetting other operating costs or
generating additional revenue through the use or sale of treatment byproducts. This could include
(1) the capture and use or sale of methane produced from the breakdown of organic matter in an
anerobic lagoon or biological treatment system; (2) the sale of industrial sludge to farms for
beneficial reuse as fertilizer or soil amendments; or (3) the additional rendering of oil and grease
(O&G) removed by the dissolved air flotation (DAF) technology. The third would generate
additional revenue for facilities with on-site rendering capacity while also reducing solids
disposal costs. EPA is considering quantifying and monetizing these three categories of cost
offsets for the final rule and requests comment on each.

4.4 Cost-to-Revenue Screening Analysis: Parent Entity-Level Analysis

EPA also assessed the economic impact of the regulatory options at the parent entity level. The CTR
screening analysis at the entity level adds particular insight on the impact of compliance requirements on
those entities that own multiple facilities. EPA conducted this screening analysis at the highest level of
domestic ownership, referred to as the "domestic parent entity." The entity-level analysis maintains the
worst-case analytical assumption of no pass-through of compliance costs, either downstream to meat and
poultry product consumers in the form of increased prices for end-products or upstream to farmers in the
form of reduced prices for inputs, used for the facility-level cost-to-revenue analysis in Section 4.3.

4.4.1 Analysis Approach and Data Inputs

To assess the entity-level economic/financial impact of compliance requirements, EPA summed facility-
level annualized after-tax compliance costs calculated in Section 4.2 to the level of the MPP facility
owning entity and compared these costs to parent entity revenue.

Similar to the facility-level analysis, EPA used cost-to-revenue ratios of one and three percent as markers
of potential impact for this analysis. Also similar to the assumptions made for the facility-level analysis,
for this entity-level analysis the Agency assumed that entities incurring costs below one percent of
revenue are unlikely to face significant economic impacts, while entities with costs of at least one percent
but less than three percent of revenue have a higher chance of facing significant economic impacts, and
entities incurring costs of at least three percent of revenue have a still higher probability of significant
economic impacts.

This entity-level cost-to-revenue analysis involved the following steps to obtain inputs needed to calculate
the CTR: (1) determining the parent entity; (2) determining the parent entity revenue; (3) estimating
compliance costs at the level of the parent entity. The sections below describe these steps.

Determining the Parent Entity

EPA identified parent entities and facilities owned by each parent entity using a combination of the
census and detailed questionnaires, supplemental information provided by firms, D&B Hoovers data (as

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4: Screening-Level Economic Impacts

described in Section 4.3.1.2), and manual review. EPA primarily identified parent entities based on
responses to Question 2 in the census and detailed questionnaires, which asked respondents to indicate if
a facility has a parent company and provide parent company information where relevant. To account for
differences in reported parent entity names (e.g., "corp." versus "corporation"), EPA standardized parent
names by removing punctuation and words like "company," "incorporated," "corporation," "inc," and
"11c." EPA supplemented responses to this question with data from D&B Hoover's to ensure reported
parent entity names are accurate and consistent across multiple facilities. EPA also conducted a manual
review of MPP facilities, searching corporate websites, annual reports, U.S. Securities and Exchange
Commission (SEC) filings, and conducting other general internet searches to improve identification of
facilities' parent entities.

Determining Parent Entity Revenue

For each parent entity identified in the preceding step, EPA determined revenue values based on
information reported in the detailed questionnaire, the D&B Hoovers database, and from corporate or
financial websites, if those values were available. If parent entity revenue was unavailable from these
sources, EPA estimated revenue as the sum of facility revenue across all facilities owned by that parent
entity. EPA adjusted entity revenue values to 2022 dollars using the GDP deflator (U.S. Bureau of
Economic Analysis, 2023).

Estimating Compliance Costs at the Level of the Parent Entity

EPA identified each MPP facility's parent entity, and in cases where no parent entity was identified, EPA
assumed the facility is a single-facility entity. EPA summed facility-level compliance costs for each
facility owned by a parent entity under each regulatory option to calculate parent entity level compliance
costs.

4.4.2 Key Findings for Reguia tory Options

Table 4-3 presents the results from the entity-level impact for each regulatory option. The table shows the
number of entities that incur costs in four ranges: no cost, non-zero costs less than one percent of an
entity's revenue, at least one percent but less than three percent of revenue, and at least three percent of
revenue.

Overall, this screening-level analysis shows that under regulatory options 1 and 2, with and without
chlorides, most entities are likely to incur zero costs and almost all are likely to incur costs less than one
percent of revenue. Under Option 3 and Option 3 with chlorides, fewer entities are likely to incur zero
costs and more entities are likely to incur costs greater than three percent of revenue.

Table 4-3: Entity-Level Cost-to-Revenue Analysis Results

Regulatory
Option

Total
Number of
Entities

Number of Entities with a Ratio of

Percent of Entities with a Ratio ofb

0%a

>0 and
<1%

>1 and
<3%

>3%

0%a

>0 and
<1%

>1 and
<3%

>3%

Option 1

3,114

2,717

394

3

0

87%

13%

0.1%

0.0%

Option 2

3,114

2,717

393

3

1

87%

13%

0.1%

0.0%

Option 3

3,114

2,118

978

14

4

68%

31%

0%

0%

Option 1 with
chlorides

3,114

2,659

451

3

1

85%

14%

0.1%

0.0%

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Table 4-3: Entity-Level Cost-to-Revenue Analysis Results



Total

Number of Entities with a Ratio of

Percent of Entities with a Ratio ofb

Regulatory

Number of



>0 and

>1 and





>0 and

>1 and



Option

Entities

0%a

<1%

<3%

>3%

0%a

<1%

<3%

>3%

Option 2 with



















chlorides

3,114

2,659

451

3

1

85%

14%

0.1%

0.0%

Option 3 with



















chlorides

3,114

2,118

978

14

4

68%

31%

0%

0%

a. These entities own only facilities that already meet discharge requirements for the wastestreams addressed by a given

regulatory option and are therefore not estimated to incur any compliance technology costs.







b. Percentages may not add up to 100 percent due to rounding.











Source: U.S. EPA Analysis, 2023.

4.4.3 Uncertainties and Limitations

Despite EPA's use of the best available information and data, this analysis of entity-level impacts has
uncertainties and limitations, including:

•	EPA assumed that many facilities are single-facility entities when unable to find ownership
information. As a result, EPA may be overestimating the number of entities in the MPP industry
and potentially underestimating impacts to entities that own multiple facilities.

•	EPA obtained revenue information from the census and detailed questionnaire responses, D&B
Hoover's data, and estimates derived from production data. EPA reconciled variation in revenue
information from each data source, but actual revenue may still differ.

•	Revenue data reported in the questionnaires and estimated based on production are for 2021 and
D&B Hoovers revenue data are for the year 2020. To the extent that actual 2024 entity revenue
values are different, on a constant dollar basis, from those EPA utilized, the CTR measure for
parent entities of facilities may be over- or underestimated.

•	As is the case with the facility-level analysis discussed in Section 4.3, the zero-cost passthrough
assumption represents a worst-case scenario from the perspective of the facility owner. To the
extent that companies can pass some compliance costs downstream to consumers or upstream to
farmers, this analysis may overstate the potential impact of the baseline and regulatory options on
entities owning MPP facilities.

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5: Facility Closure Analysis

5 Facility Closure Analysis

5.1	Analysis Overview

EPA assessed the potential for MPP facilities to close as a result of compliance with proposed revisions to
the MPP ELGs based on a discounted cash flow (DCF) under baseline and post-compliance conditions for
each of the regulatory options. This analysis tests the effects of the costs of compliance on the financial
performance and business value of the regulated facilities, based on changes in cash flow (and accounting
for ongoing capital outlays, depreciation, and taxes). The discounted present value of cash flow provides a
measure of business value. Reduction in business value, specifically when business value would become
negative because of incremental compliance costs, is an indicator of potential adverse financial impact of
the proposed rule's requirements. EPA performed this analysis in two steps:

•	A baseline analysis to assess business condition and value before changes in regulatory
requirements. The key purpose of this analysis is to identify entities that appear to have negative
business value independent of increased regulatory costs.

•	A post-compliance analysis to assess change in business value due to regulatory requirements.
This analysis assesses the reduction in business value from compliance costs, focusing on
whether some entities' business value is positive in the baseline but turns negative due to
compliance requirements.

EPA performed this analysis for facilities that reported financial data in the MPP detailed questionnaire.
EPA then extrapolated the results of this DCF analysis to the full universe of affected MPP facilities.

5.2	Analysis Inputs

5.2.1 Depreciation

EPA used the Modified Accelerated Cost Recovery System (MACRS) depreciation method. The Internal
Revenue Service (IRS) bases the depreciable life of an asset on the useful life. The IRS classifies property
with a 20-year useful life as 15-year property, and property with a 40-year useful life as 20-year property.
Using the half-year convention, we depreciate capital equipment based on the depreciation schedule
shown in Table 5-1, assuming 20-year capital is repurchased in year 21.

Table 5-1: Depreciation Schedule over Analysis Period



Depreciation rate



Depreciation rate



20-year

40-year



20-year

40-year

Year

capital

capital

Year

capital

capital

1

5.00%

3.75%

21

5.00%

2.23%

2

9.50%

7.22%

22

9.50%

0.00%

3

8.55%

6.67%

23

8.55%

0.00%

4

7.70%

6.18%

24

7.70%

0.00%

5

6.93%

5.71%

25

6.93%

0.00%

6

6.23%

5.28%

26

6.23%

0.00%

7

5.90%

4.89%

27

5.90%

0.00%

8

5.90%

4.52%

28

5.90%

0.00%

9

5.91%

4.46%

29

5.91%

0.00%

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Table 5-1: Depreciation Schedule over Analysis Period

Year

Depreciation rate

Year

Depreciation rate

20-year
capital

40-year
capital

20-year
capital

40-year
capital

10

5.90%

4.46%

30

5.90%

0.00%

11

5.91%

4.46%

31

5.91%

0.00%

12

5.90%

4.46%

32

5.90%

0.00%

13

5.91%

4.46%

33

5.91%

0.00%

14

5.90%

4.46%

34

5.90%

0.00%

15

5.91%

4.46%

35

5.91%

0.00%

16

2.95%

4.46%

36

2.95%

0.00%

17

0.00%

4.46%

37

0.00%

0.00%

18

0.00%

4.46%

38

0.00%

0.00%

19

0.00%

4.46%

39

0.00%

0.00%

20

0.00%

4.46%

40

0.00%

0.00%

Rates for 20-year capital based on half-year convention for 15-year property. Rates for 40-
year capital based on half-year convention for 20-year property.

Source: U.S. Department of the Treasury Internal Revenue Service, 2022

5.2.2	Combined Tax Ra te

To calculate the reduction in income taxes (i.e., tax shield) resulting from a reduction in taxable income
(due to increased capital, O&M, and interest expenses), EPA calculated the combined federal and state
income tax rate (tc) based on the facility's location and its parent company's corporate structure:

Tc Ty ~1~ Ts ( TJ'Ts )

where Ty is the federal tax rate and zs is the state tax rate.13 C corporations pay federal and state taxes at
the corporate level. S corporations and LLCs distribute earnings to partners, and these individuals pay the
taxes. For the purposes of this analysis, EPA assumed a tax rate of zero for S corporations and LLCs.
EPA assumed all other entities (limited partnerships, general partnerships, and sole proprietors) pay taxes
at the individual rate.

5.2.3	Weighted A verage Cost of Capital (WACC)

EPA used the weighted average cost of capital (WACC), or the average cost of capital the firm must pay
to all its investors, both debt and equity holders, as the discount rate in the facility closure analysis. The
WACC is calculated as:

WACC = Debt% * DebtCost% * (1 — tc) + Equity% * EquityCost%

where Debt% and Equity% is the approximate mix of debt and equity the ultimate parent company, or
the facility if it does not have an ultimate parent company, uses to finance capital improvements;
DebtCost% is the interest rate on loans to finance capital improvements; and EquityCost% is the
minimum rate of return on capital required to compensate equity owners for bearing risk. EPA obtained

If a state does not have a flat income tax rate, for corporations or individuals, EPA uses the tax rate for the highest
income bracket.

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these four values from the MPP detailed questionnaire. If a respondent indicated these values are
unknown, EPA used the median reported value across all detailed questionnaire responses.

5.3 Baseline Discounted Cash Flow

EPA calculated baseline present value of DCF as the present value over 40 years of free cash flow (FCF),
defined as:

EPA added depreciation back to net income to account for the fact that it is a non-cash flow. This
calculation is based on facility-level financial information provided in the detailed questionnaire for 2017,
2019, and 2021. After converting to 2022 dollars, EPA averaged across the three reported years and
assumed this average value remains constant over the period of analysis. EPA then took the present value
of the 40-year stream of FCF, with a discount rate equal to the WACC, to calculate the baseline present
value of DCF (DCFbl):

EPA identified facilities with DCFBL < 0 as baseline closures.

5.4 After-Tax Compliance Costs

5.4.1 Tax Shield

The depreciation rate represents the portion of capital equipment costs that can be written off each year to
offset annual income for tax purposes. Depreciation, along with O&M and interest expenses, represent the
reduction in taxable income in each year. To calculate the resulting reduction in income taxes (i.e., tax
shield) paid, EPA calculated:

• O&M tax shield as the product of annual O&M expenses and the facility's combined tax rate.
The tax shield in year /' is therefore:

• Interest tax shield as the product of interest paid on the portion of capital costs financed through
debt and the facility's combined tax rate. To estimate interest paid each year of the analysis
period, EPA multiplied the compliance capital outlay by the fraction financed through debt
(Debt%) and assumed equal payments in all years, equal to the annualized value of the debt
portion of the capital outlay (Capdebtannizd), using a discount rate equal to DebtCost%.u The
interest portion of the annual payment is based on the outstanding debt and DebtCost%. For
example, EPA calculated the interest and principal paid in year 1 as:

For simplification, EPA assumed a debt financing period equal to the useful life of the compliance technology
(20 years or 40 years). EPA assumed the debt portion of the facility's compliance capital outlay, Capdebt, would be
financed over a period not exceeding the expected life of the compliance equipment.

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FCF = Net income + depreciation = EBIT — interest — taxes + depreciation

40

TaxShield0M i = OMt * tc


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Interest = DebtCost% * Cap * Debt%

Principalt = CapdebtiCinnizd - Interestx

The interest paid in year 2 is then based on the outstanding debt (initial debt less principal paid in
year 1). Interest and principal payments in year 2 are therefore:

Interest2 = ((DebtCost% * Cap * Debt%) — Principalx) * DebtCost%
Principal = CapdebtiCinnizd - lnterest2

The tax shield in year /' is:

TaxShieldint i = Inter est t * tc

• Depreciation tax shield as the product of the depreciation rate (see Table 5-1), the total capital
outlay, and the facility's combined tax rate. The tax shield in year / is:

TaxShielddepri = DeprRatet * Cap * tc

The potential tax shield is the sum of the tax shields from O&M, interest, and depreciation expenses:

TaxShieldi = TaxShield0M t + TaxShieldint i + TaxShielddepri

5.4.2 A fter- Tax Compliance Costs

EPA calculated the after-tax compliance cost (CmplC) in year /' as:

CmplCi 0Mi ~l~ Capequity i -l~ Capdeb^iannizd TaxShieldi

where OMt is equal to the annual O&M costs, Capequity i is the equity portion of capital outlay,
Cap debt,annizd is the annualized value of the debt portion of capital outlay, and TaxShieldi is the
minimum of the calculated tax shield (as described in Section 5.4.1) and the average taxes paid in 2017,
2019, and 2021.15

5.5 Post-Compliance Discounted Cash Flow

EPA predicted a potential facility closure resulting from compliance with the revised MPP ELGs (post-
compliance closures) when the following two conditions were met:

(1) DCFbl > 0

(2) DCFbl — CmplCpy < 0

The first condition is that the facility had a non-negative baseline discounted cash flow without the
proposed rule and therefore was financially viable. The second condition is that the facility has a negative
discounted cash flow with the proposed rule and is therefore no longer financially viable as a result of the
proposed rule.

Facilities cannot reduce their tax liabilities more than the baseline amount of taxes paid.

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5.6 Extrapolation to Full Universe

EPA developed an approach to extrapolate the facility closure analysis, which was possible only for the
subset of facilities with sufficient financial data, to the full universe of MPP facilities. The extrapolation
approach relies on the relationship between facility CTR and assessed closures. EPA first developed a
dataset based on facilities with detailed financial information: for each relevant technology combination
(e.g., for a direct discharger, the relevant technology combinations are Direct 1, Direct 2, Direct 1 with
chlorides, and Direct 2 with chlorides), EPA calculated post-compliance DCF and facility CTR. Based on
these results and the production characteristics of each facility, EPA calculated the percentage of facility
closures by production size category, discharge type, processing type, and facility CTR (see Table 5-2; for
example, meat first direct dischargers with production less than 20 million pounds per year were assessed
as closures in 100 percent of instances when CTR was between 3 and 5 percent). Where data were
unavailable, EPA made assumptions about the percentage of facilities that may close based on the results
of the DCF analysis for similar production size, discharge type, processing type, and CTR categories (see
indicated values in Table 5-2).

Table 5-2: Estimated Percent Closures by Production Size, Discharge Type, Processing Type,
and CTR

Production size
(Ibs/yr)

Discharge
type

Processing
type

CTR <1%

CTR 1%-
3%

CTR 3%-
5%

CTR 5%-
10%

CTR
>10%

<20 M

Direct

Meat first

0%a

0%a

100%

100%a

100%a

<20 M

Direct

Meat further

0%

0%

0%

50%a

100%

<20 M

Direct

Poultry first

0%

0%

50%a

75%a

100%a

<20 M

Direct

Poultry further

0%a

0%

50%a

75%a

100%a

<20 M

Direct

Render

0%a

0%a

50%a

75%a

100%a

>= 20 M,
<50 M

Direct

Meat first

0%a

0%a

50%a

75%a

100%a

>= 20 M,
<50 M

Direct

Meat further

0%a

0%a

50%a

75%a

100%a

>= 20 M,
<50 M

Direct

Poultry first

0%a

0%a

50%a

75%a

100%a

>= 20 M,
<50 M

Direct

Poultry further

0%a

0%a

50%a

75%a

100%a

>= 20 M,
<50 M

Direct

Render

0%a

0%a

50%a

75%a

100%a

>50 M

Direct

Meat first

0%

0%a

50%a

75%a

100%a

>50 M

Direct

Meat further

0%a

0%a

50%a

75%a

100%a

>50 M

Direct

Poultry first

0%

0%

50%a

75%a

100%a

>50 M

Direct

Poultry further

0%a

0%a

50%a

75%a

100%a

>50 M

Direct

Render

0%

0%

50%a

75%a

100%a

<20 M

Indirect

Meat first

0%

0%

0%

0%

81%

<20 M

Indirect

Meat further

4%

0%

67%

60%

100%

<20 M

Indirect

Poultry first

17%

25%

0%

30%a

90%a

<20 M

Indirect

Poultry further

0%

14%

22%

30%a

90%a

<20 M

Indirect

Render

5%a

10%a

22%a

30%a

90%a

>= 20 M,
< 100 M

Indirect

Meat first

0%

0%

0%

0%

100%a

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Table 5-2: Estimated Percent Closures by Production Size, Discharge Type, Processing Type,
and CTR

Production size
(Ibs/yr)

Discharge
type

Processing
type

CTR <1%

CTR 1%-
3%

CTR 3%-
5%

CTR 5%-
10%

CTR
>10%

>= 20 M,
< 100 M

Indirect

Meat further

0%

0%a

0%a

50%a

100%

>= 20 M,
< 100 M

Indirect

Poultry first

0%

0%

0%

50%a

100%a

>= 20 M,
< 100 M

Indirect

Poultry further

0%

0%a

0%a

50%a

100%a

>= 20 M,
< 100 M

Indirect

Render

0%

0%

0%a

50%a

100%a

> 100 M

Indirect

Meat first

17%

51%a

51%a

76%a

100%a

> 100 M

Indirect

Meat further

0%

100%

100%a

100%a

100%a

> 100 M

Indirect

Poultry first

3%

20%

20%a

60%a

100%

> 100 M

Indirect

Poultry further

0%

51%a

51%a

76%a

100%a

> 100 M

Indirect

Render

0%

33%

33%a

67%a

100%a

a. EPA assumptions.

Source: U.S. EPA Analysis, 2023.

5.7 Results

EPA multiplied the number of facilities affected by each regulatory option that fall within each of the
categories presented in Table 5-2 by the percentages in Table 5-2 to estimate the total number of potential
facility closures. Table 5-3 presents the results of this analysis by regulatory option.

Table 5-3: Facility Closure Extrapolation Results









Option 1 with

Option 2 with

Option 3 with



Option 1

Option 2

Option 3

chlorides

chlorides

chlorides

Number of estimated

16

22

53

26

30

54

facility closures













Number of facilities

845

845

1,620

946

946

1,621

with costs













Number of dischargers

3,879

3,879

3,879

3,879

3,879

3,879

% of facilities with

1.9%

2.6%

3.3%

2.7%

3.2%

3.3%

costs













% of all dischargers

0.4%

0.6%

1.4%

0.7%

0.8%

1.4%

Source: U.S. EPA Analysis, 2023.

5.8 Uncertainties and Limitations

The main sources of uncertainty for the facility closure analysis presented in this chapter are:

• EPA received limited financial data from responses to the MPP detailed questionnaire. As a
result, not all categories of process type, discharge type, and production size are represented in
the DCF closure analysis, and the facilities that are included may not be representative of the
financial status of the entire MPP industry. The number of facility closures may by over- or
underestimated.

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•	EPA assumed constant values over the analysis period. EPA does not have any data to determine
if, or how, specific metrics may change for individual facilities. Changes in production or prices,
for example, could affect facility revenue and therefore the facility's business value.

•	There are limitations in how well the DCF analysis can predict facility closures. For example,
EPA identified some facilities with DCFBL < 0 as baseline closures, despite those facilities
indicating they are currently operating. In addition, EPA received incomplete financial
information about some facilities and thus made assumptions about certain metrics (e.g., WACC),
potentially resulting in inaccurate results.

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6: Market Impact Analysis

6 Market Impact Analysis

6.1	Analysis Overview

EPA examined the effects of the proposed revisions to the MPP ELGs on the national markets for beef,
pork, chicken, and turkey. To do this, EPA constructed linear supply and demand equations for each meat
product market based on the pre-regulatory market price and quantity (pre-regulatory equilibrium) and
estimated how equilibrium quantity and price in each market will shift due to changes to the MPP ELGs
(post-regulatory equilibrium).

Section 6.2 describes the methodology used to derive the model functions as well as the pre- and post-
regulatory market equilibria. Section 6.3 presents the data sources used in the analysis including trade
data, baseline price and quantity data, and elasticity estimates. Section 6.4 presents the results of the pre-
regulatory equilibrium calculations, the method for determining average per-unit compliance costs for
each meat product market, and the resulting estimated market-level impacts of the regulatory options.
Section 6.5 presents the barrier-to-entry analysis of the proposed rule, and Section 6.6 presents
uncertainties and limitations to the market impact analysis.

6.2	Analysis Methodology

In this section, EPA presents the methodology used to specify the domestic and trade demand and supply
functions as well as calculate the pre- and post-regulatory equilibria. This methodology is based on the
methodology previously used by U.S. EPA (2002).

6.2.1 Domestic and Trade Demand and Supply Functions
Linear domestic and trade demand and supply equations are expressed as:

where U.S. demand for meat product i (Q?) is a function of the U.S. price of meat product i (Pi), and the
U.S. prices of other meat products j (Pj). The U.S. supply for meat product i (Qf), the rest of the world
(ROW) demand for U.S. meat product i (Qf), and the U.S. demand for ROW meat product i (Qf) are all
modeled as functions of U.S. price for meat product i (Pt) only. The parameters du, su, xu rrii represent
the slopes of their respective functions. The parameters aDi, asi, axi, aMi represent the intercepts of their
respective functions.

The slopes of the demand functions for each meat product represent the own-price elasticity of demand
(da, sa, X(, rrii) for each meat product, as well as the cross-price elasticities (dtj) with relation to the
other three meat products in the case of domestic demand. Calculating the slope of the demand functions
in this way helps account for cross-market effects that may affect the post-regulatory equilibrium of each

Qf = <*Si + SuPi

Qf = ocxi + xtPt

Qf = ccMi +

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meat market. For instance, an increase in the price of pork due to regulatory changes could increase
demand in the beef market if beef is a substitute for pork. Functions of import supply and export demand
are included in the model to account for international trade. For U.S. supply, export demand, and import
supply functions, the slopes were calculated using the own-price elasticity of supply and the export and
import elasticities calculated by EPA (Table 6-6). These elasticities were linearized by multiplying the
elasticity by baseline quantity and price values. Elasticity is described as:

= SQf Pj
£i] SPj Qf

The slope may be described as:

, _ SQf _ Qf

ij SPj Pj £ij

where £tj is the elasticity of demand for meat product i with respect to the price of meat product j. Pj and
Qf refer to the baseline price and quantity for meat product j and i, respectively.

The slopes of U.S. supply (su), export demand (x;). and import supply (m^ are similarly defined as:

= £G? = 9i

su SPi p. Yii

SQf Qf
Xi SPt Pt Vxi

SQf Q™
mi SPi p. Vmi

where Yu, Vxi- Vmi are elasticities with respect to U.S. price.

6.2.2 Pre-Regulatory Equilibrium
To estimate market equilibrium for each meat market, the sum of domestic demand (Qf) and export
demand (Qf) must equal the sum of domestic supply (Qf) and import supply (Qf1):

Qf + Qf = Qf + Qf

This can also be expressed as:

Qf + Qf ~ Qf ~ Qf = o

or:

&Di d-nPi + ^ ' dijPj I + (cTja + X[P[) (&si ^ii^i) C^Mi	0

i*J

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This expression can be simplified as:

(aDi + axi - asi - aMi) + (du + xt - % - m^Pi + ^ dijPj = 0

i*j

ni + ^iPl + ^ d-ijPj = 0
i*j

A-iPi + dijPj — 77";
i*j

Because each supply and demand function in the model is specified linearly, the model components are
additive. Given this, EPA simultaneously solved for the pre-regulatory equilibrium. This is expressed in
the matrix form:16

XB dBP dBC dBT

dPB A.p d>pc dpT

d-CB dCP Ac dCT

-djB dTP dTC







nB



Pp



TC p



Pc



-Kc



-Pt-



TTj^

This matrix is expressed in vector notation as A x P = n, so the Agency solved for the intercept for each
excess demand equation, —n:t using the baseline prices (matrix/') and the price parameters (Ai and dLj) in
matrix A.

6.2.3 Post-Regulatory Equilibrium
To estimate the impacts of the regulatory options, EPA respecified the domestic supply curve to
incorporate the compliance costs incurred by processors in each meat product market. The Agency
expects that the compliance costs incurred by processors will decrease the domestic supply of each meat
product (a shift in the supply curve). The magnitude of the decrease in supply for each meat product will
be based on the average compliance costs per unit of output incurred in each meat product market (see
Section 6.4.1 on how EPA derived the average per-unit compliance costs by meat product). The decrease
in supply in each meat product market due to compliance costs is expressed as a decrease in the intercept
of the supply function (asi — saSi) while the slope remains the same, defined as:

Q? = asi + Su(Pi - 8t)

where 8i represents the average per-unit compliance costs for meat product i. Based on this new supply
function, the post-regulatory excess demand function can be written as:

^ ' dijPj
i*j

sii$i H-i

This is expressed in the matrix form:

16 Within this matrix, subscript B refers to beef, P refers to pork, C refers to chicken, and T refers to turkey.

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ab

dBP

d-BC

dBT



\P'b]



SBB^B nB

dps

AP

dpC

dpT



P'p



SppSp TCp

d-CB

dCp

^c

dCr



P'c



scc^c~nc

dTs

dTp

dTc





[p'T\



-Stt TTj*-

In this equation, the elements of matrix A (i.e., Ah d^) and the elements of the new vector II* (i.e., su. St,
Tij) are known. Matrix P can be solved for by multiplying the inverse of matrix A by the vector II* to
estimate the post-regulatory equilibrium prices for each meat product (i.e., P{ = /P1 11*). The new
equilibrium prices (P/) can then be substituted into each model equation to estimate post-regulatory U.S.
demand {Qf), U.S. supply (Qf), export demand (Qf), and import supply (Qf)'.

aDi + duPi + ^ dijPj' = Qf
i*i

asi + sa(Pl - = Qf
axi + XiPi' = Qf
aMi + miPi = Q

6.3 Data

In this section, EPA presents data sources for baseline domestic quantities and price, imports, exports, and
Armington trade elasticity17 for the four meat categories of interest. EPA also presents the estimates of the
elasticity of demand and elasticity of supply for each meat product used in the market impact analysis.

6.3.1 Trade Data and Baseline Quantity and Price Data
Table 6-1 presents the data sources the Agency used in the market impact analysis for the following
model parameters, based on the analysis presented in U.S. EPA (2002): domestic price and quantity, U.S.
imports and exports (total and as share of world production), and Armington trade elasticity. For each
field, EPA also reports the data vintage. Table 6-2 presents the values of baseline price and quantities
taken from the sources in Table 6-1. The value of the Armington trade elasticity used in this analysis is
4.36 (Ahmad & Riker, 2020).

Table 6-1: Data Sources by Data Requirement

Data Requirement

Data Source

Vintage

Baseline domestic quantity

USDA Livestock, Dairy, and Poultry Outlook

2022

Baseline domestic price

Wholesale prices from USDA Livestock and Meat Domestic
Data

2022

U.S. import quantity

USDA Livestock and Meat International Trade Data

2022

U.S. export quantity

USDA Livestock and Meat International Trade Data

2022

Armington elasticity3

Ahmad and Riker (2020) - U.S. International Trade Commission
working paper

2017

The Armington elasticity measures the percentage change in market share of an imported good relative to a
domestically produced good due to changes in the price of the domestic and imported good and is used to calculate
import and export elasticities.

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Table 6-1: Data Sources by Data Requirement

Data Requirement

Data Source

Vintage

Share of U.S. exports as % of rest of
world (ROW) production

UNFAOdata

2021

Share of U.S. imports as % of U.S.
quantity

UNFAOdata

2021

a. The estimate of the Armington trade is estimated for the animal slaughtering and processing sector (NAICS code 3116).
Sources: Economic Research Service, 2023a, 2023b; Food and Agriculture Organization, 2022; Knight et al., 2023.

Table 6-2: Baseline Prices and Quantities by Meat Product

Meat Product

Prices (2022$ per Million
Pounds)3

Baseline Quantities (Million Pounds)

Domestic
Production

Foreign Imports

U.S. Exports

Beef

$2,632,438

28,290

3,391

3,536

Pork

$1,113,816

26,994

1,344

6,338

Chicken

$1,405,267

46,206

176

7,278

Turkey

$1,496,779

5,222

85

407

a. See Table 2-5 for EPA's method for calculating baseline prices for each meat product market.

Source: Economic Research Service, 2023a, 2023b; Food and Agriculture Organization, 2022; Knight et al., 2023.

6.3.2 Elasticity Estima tes
6.3.2.1 Elasticity of Demand Estimates

EPA reviewed the available literature to obtain estimates of own-price and cross-price elasticity of
demand. Table 6-3 and Table 6-4 present the identified studies, along with the reported estimates of own-
price and cross-prices elasticities. EPA used the estimates of own-price elasticity of demand from Yang et
al. (2019) in the market impact analysis, as these estimates are based on more recent data. Okrent and
Alston (2012) and Lee et al. (2020) also report estimates of cross-price elasticity of demand for each meat
product of interest. EPA used the estimates for cross-price elasticity of demand from Lee et al. (2020).
Though Okrent and Alston (2012) also report cross-price elasticity, the Agency omitted this study as the
estimates from Lee et al. (2020) are based on more recent data and are reported to have a higher degree of
statistical significance.

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Table 6-3: Sources of Own-Price Elasticity of Demand

Source

Meat Product

Data Sourceb

Data
Years

Beef

Pork

Chicken3

Turkey3

Okrent and Alston
(2012)°

0.70

1.26

-0.81

-0.81

CES & CPI (U.S.
BLS)

1998-
2010

Lee et al. (2020)

0.98

0.98

-0.8

-0.80

CES & CPI (U.S.
BLS)

1984-
2012

Yang et al. (2019)d

0.54

0.69

-0.77

-0.77

CES & CPI (U.S.
BLS)

2009-
2016

a.	Elasticity estimates for turkey and chicken are based on data for the total U.S. poultry market in each study.

b.	CES = Consumer Expenditure Surveys, CPI = Consumer Price Index, U.S. BLS = U.S. Bureau of Labor Statistics.

c.	This is a USDA study and is the most recent update of the estimates used in U.S. EPA (2002).

d.	This study does not contain cross-price elasticity estimates for meat categories of interest.

Table 6-4: Estimates of Cross-Price Elasticities of Demand

Meat Product

Cross-Price Elasticity Estimates

Beef

Pork

Chicken

Turkey

Beef

-

0.11

-0.03

-0.03

Pork

0.14

-

-0.06

-0.06

Chicken

-0.04

-0.07

-

-0.80

Turkey

-0.04

-0.07

-0.80

-

Source: Lee et al. (2020)

6.3.2.2 Elasticity of Supply Estima tes

EPA also reviewed available studies with estimates of long-run own-price elasticity of supply for each
meat product.18 Table 6-5 presents the range of values from the literature. Differences in elasticity
estimates arise due to differences in the data years and methodologies used by the authors. To account for
these differences, EPA calculated the average long-run elasticity of supply for each meat product using
the elasticity estimates in Table 6-5 for use in the analysis.

Table 6-6 presents the average values of long-run elasticity of supply for each meat product. Marsh
(1994) and Jeong (2019) note that their long-run elasticity of supply estimates for fed cattle are larger
than previous studies. As a result, EPA excluded their estimates from the calculation of the average long-
run elasticity of supply for beef in Table 6-6. Additionally, EPA assumed that the elasticities for fed
cattle, wholesale fed cattle, and beef are similar. Thus, EPA included the elasticity values for these
different products from Table 6-5 in the calculation of the average long-run elasticity of supply for beef.

Long-run elasticity of supply is estimated to examine the impact that changes in price might have on long-run
investment decisions (e.g., plant closure). Short-run elasticity of supply estimates are used to look at how capital
expenditures may change in the short-run due to temporary shocks. EPA used long-run estimates of the elasticity of
supply for each meat category to account for the long-run impacts the proposed changes to the MPP ELGs might have
on firm-level investment decisions.

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Table 6-5: Sources of Long-Run Own-Price Elasticity of Supply

Source

Meat
Category

Product

Elasticity
Estimate

Data Sourcesa b

Data Years

McKendree et al.
(2020)

Beef

Fed cattle

0.24

LMIC, NOAA, USDA, Author
calculations, University of
Michigan, U.S. BLS, Meat
and Livestock Australia

1996 (Ql) -
2016 (Q3)

Jeong (2019)

Fed cattle

4.13

USDA, LMIC, FRED

1999-2018

Sarmiento et al. (2000)

Fed cattle

0.33

USDA

1978-1991

Marsh (1994)

Fed cattle

3.24

LMIC, USDA, SBC (U.S. BEA)

1978- 1991

Marsh (1994) (Tvedt,
et. al., 1991)

Beef

0.993

-

1960 - 1987

Marsh (1994) (Bedinger
and Bobst, 1988)

Wholesale fed
cattle

0.2

-

1965 - 1983

Holt et al. (1988)

Pork

Pork

0.628

-

1967 - 1985

Meilke et al. (1974)

Pork

0.43

-

-

0.48

-

-

Epple et al. (2006)

Chicken

Broiler

0.6

USDA, U.S. BLS, U.S. BEA

1960-1999

Holt et al. (1990)

Broiler

0.39

FIML estimator

1969 - 1986

0.587

Chavas(1982)

Turkey

Turkey

0.222

-

-

Chavas et al. (1982)

Turkey

0.21

USDA

1965 - 1975

A. Soliman (1971)

Turkey

0.518

-

1946 - 1966

a.	FIML = Full Information Maximum Likelihood, FRED = Federal Reserve Economic Data, LMIC = Livestock
Marketing Information Center; NOAA = National Oceanic and Atmospheric Administration, SBC = Survey of
Current Businesses, U.S. BEA = U.S. Bureau of Economic Analysis. U.S. BLS = U.S. Bureau of Labor Statistics,
USDA = U.S. Department of Agriculture.

b.	Information on data sources and data years are unavailable for some studies.

Table 6-6: Average Long-Run Elasticity of Supply Estimates by Meat Product

Meat Product

Average of Long-Run Elasticity of Supply Estimates

Beef3

0.44

Pork

0.51

Chicken

0.53

Turkey

0.32

a. Excludes the long-run elasticity of supply estimate calculated by Marsh (1994) and Jeong (2019).
Source: Averages of long-run elasticity of supply estimates by meat product based on sources in Table 6-5.

6.3.2.3 Import and Export Elasticity Estima tes

The elasticity of U.S. demand for imports of ROW meat product i can be expressed as a function of
U.S. elasticity of demand for meat product i (%), the ratio of ROW and U.S. market shares (djj and 9%,
respectively), and the Armington elasticity Of u). This function is described as:

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&R „

Vmi =7u (? +£«)

EPA considered only two countries in the model, the United States and the ROW, and assumed that U.S.
imports as a share of the U.S. market (9%) and U.S. production (less exports) as a share of the U.S.
market (0y) represent the entire U.S. market for meat product i (i.e., 9y = 1 — 9%). The expected sign of
rjmi is positive. EPA expects that an increase in the U.S. price of meat product i will increase the U.S.
demand for ROW meat products.

The elasticity of ROW demand for U.S. meat product i (r]xi) with respect to U.S. price can be expressed
as a function of ROW elasticity of demand for meat product i (sfj). the ratio of ROW and U.S market
shares (9§ and 9$. respectively), and the ROW's elasticity of substitution between ROW and U.S. meat
products (ifR). This function is described as:

71x1=df) +£i^ ~ ^R

The expected sign of r/xi is negative because the own-price elasticity of demand for each meat product
used in this analysis is negative. Given the limitations of available data, the model relies on several
assumptions to calculate export elasticity. The model assumes that U.S. exports as a share of ROW
market (9§) and ROW production (less exports) as a share of ROW market (9$) represent the entire
ROW market for meat product i (i.e., 9^ = 1 — 9^). Additionally, the model assumes that the ROW
elasticity of substitution for U.S. meat products is equal to the U.S. elasticity of substitution for meat
products (i.e., ^R = ^u). The model also assumes that the ROW elasticity of demand for meat products is
equal to the U.S. elasticity of demand for meat products (i.e., sft = %).19

Table 6-7 presents the estimates for import elasticity (r]mi) and export elasticity (rjxi) calculated using the
methodology described in this section.

Table 6-7: Estimated Armington Trade Elasticities with Respect to U.S. Price

Meat
Product

Elasticity of Meat Imports w.r.t. U.S. Price

Elasticity of Meat Exports w.r.t. U.S. Price

U.S.
Elasticity

of
Demand

Armington
Elasticity

[%UY

U.S.
Imports
as % of

U.S.
Market

Import
Elasticity

U.S.
Elasticity

of
Demand

Armington
Elasticity

,^)a

U.S.
Exports
as % of
ROW
Market

Export
Elasticity

Beef

-0.54

4.36

0.01

0.04

-0.54

4.36

0.002

-4.35

Pork

-0.69

4.36

0.005

0.02

-0.69

4.36

0.01

-4.33

Chicken

-0.77

4.36

0.004

0.01

-0.77

4.36

0.03

-4.23

Turkey

-0.77

4.36

0.004

0.01

-0.77

4.36

0.06

-4.13

w.r.t. = with respect to.

a. The estimate of the Armington trade is estimated for the animal slaughtering and processing sector (NAICS code 3116).

U.S. exports as a share of the ROW market is small for each meat product market (Table 6-7). Thus, the value of the
ROW trade elasticity (export elasticity) approaches the ROW elasticity of substitution for U.S. meat products (i.e.,
rjxl -> — fR). As a result, the assumption that ROW elasticity of demand is equal to U.S. elasticity of demand for meat
product i (i.e., = eu) is not critical to the results of the analysis.

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Table 6-7: Estimated Armington Trade Elasticities with Respect to U.S. Price



Elasticity of Meat Imports w.r.t. U.S. Price

Elasticity of Meat Exports w.r.t. U.S. Price







U.S.







U.S.





U.S.



Imports



U.S.



Exports





Elasticity

Armington

as % of

Import

Elasticity

Armington

as % of

Export

Meat

of

Elasticity

U.S.

Elasticity

of

Elasticity

ROW

Elasticity

Product

Demand

[%UY

Market



Demand

,^)a

Market



Source: Ahmad and Riker (2020); Food and Agriculture Organization, 2022; U.S. EPA analysis, 2023.

6.4 Pre- and Post-Regulatory Equilibria

In this section, EPA describes the approach used to estimate the market impact model.

6.4.1 Pre-Regulatory Equilibrium
Table 6-8 reports the pre-regulatory equilibrium prices and quantities for each meat product market and
the calculated intercepts (—7t{) of each excess demand equation based on the methodology in Section
6.2.2.

Table 6-8: Estimated Pre-Regulatory Quantities and Prices

Meat
Product

Prices (2021$
per Million
Pounds) [P^

Quantities Demanded and Supplied (Million Pounds)

Excess Demand
Intercepts
(Million
Pounds) (—7Tj)

Quantity
Demanded
Domestically

(0?)

Quantity
Supplied
Domestically

(Of)

Exports
Demanded

(Of)

Imports
Supplied

(Of)

Beef

$2,632,438

28,145

28,290

3,536

3,391

41,784

Pork

$1,113,816

22,000

26,994

6,338

1,344

53,508

Chicken

$1,405,267

39,105

46,206

7,278

176

117,186

Turkey

$1,496,779

4,900

5,222

407

85

11,505

Source: U.S. EPA analysis, 2023.

6.4.2 Compliance Costs

EPA estimated average compliance costs per unit of output for each meat product market based on the
steps taken by U.S. EPA (2002).20 For each facility, EPA:

•	Calculated the after-tax annualized compliance costs for each regulatory option (see sections
3.1.1.3 and 4.2).

•	Calculated the percentage of the total quantity of production each meat product represents. EPA
calculated the percentage of red meat production accounted for by beef and pork production and
the percentage of poultry production accounted for by chicken and turkey production based on the
domestic baseline values of production in 2021 from the USDA's Livestock, Dairy, and Poultry
Outlook data (Knight et al., 2023). EPA also calculated the percentage of total meat production

U.S. EPA (2002) state that the distinction between direct and indirect dischargers is not relevant when estimating per-
unit market-level compliance costs.

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each meat product (i.e., beef, pork, chicken, and turkey) represents to calculate the percentages of
rendering and mixed production accounted for by each meat product.

•	Calculated the quantity of production by facility accounted for by each meat product based on the
calculated percentages above.

•	Attributed annualized compliance costs to each meat product based on the percentage of meat
production accounted for by each meat product. For instance, if beef production accounts for

50 percent of red meat production, then 50 percent of the annualized costs for that facility will be
attributed to beef. Additionally, if beef rendering accounts for 25 percent of all rendering, then 25
percent of the annualized costs for Tenderers will be attributed to beef rendering.

•	Divided the attributable annualized compliance costs for each meat product by the quantity of that
meat product produced.

After completing these steps, EPA calculated average per-unit compliance costs of each meat product
across all subcategories. To do this, EPA calculated the weighted average of the per-unit compliance costs
of each meat product, weighted by the production of the relevant meat product. EPA also included zero
dischargers in the calculation of average per-unit compliance costs to accurately convey the impacts of
the proposed rule on each meat market. The estimates of average per-unit compliance costs are then used
to estimate the post-regulatory equilibrium of the proposed rule (see Section 6.2.3 on the methodology
EPA used to calculate the post-regulatory equilibrium).

6.4.3 Post-Regulatory Equilibrium

Table 6-9 presents the post-regulatory equilibrium prices and quantities for each meat product under each
regulatory option. These results are based on the methodology described in Section 6.2.3.

Table 6-9: Estimated Post-Regulatory Quantities and Prices

Meat
Product

Prices (2022$
per Million
Pounds)

Quantities Demanded and Supplied (Million Pounds)

Quantity
Demanded
Domestically

Quantity Supplied
Domestically

Exports Demanded

Imports Supplied

Option 1

Beef

$2,632,624

28,144

28,288

3,535

3,391

Pork

$1,113,942

21,999

26,989

6,334

1,344

Chicken

$1,405,389

39,101

46,199

7,275

176

Turkey

$1,496,822

4,899

5,221

407

85

Option 2

Beef

$2,633,012

28,142

28,284

3,533

3,391

Pork

$1,114,202

21,995

26,980

6,328

1,344

Chicken

$1,405,502

39,097

46,193

7,273

176

Turkey

$1,496,854

4,899

5,221

407

85

Option 3

Beef

$2,633,237

28,141

28,282

3,532

3,391

Pork

$1,114,357

21,993

26,973

6,324

1,344

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Table 6-9: Estimated Post-Regulatory Quantities and Prices

Meat
Product

Prices (2022$
per Million
Pounds)

Quantities Demanded and Supplied (Million Pounds)

Quantity
Demanded
Domestically

Quantity Supplied
Domestically

Exports Demanded

Imports Supplied

Chicken

$1,406,012

39,081

46,166

7,261

176

Turkey

$1,497,055

4,897

5,219

407

85

Option 1 with chlorides

Beef

$2,632,738

28,143

28,287

3,535

3,391

Pork

$1,114,019

21,998

26,986

6,333

1,344

Chicken

$1,405,500

39,097

46,193

7,273

176

Turkey

$1,496,863

4,899

5,221

407

85

Option 2 with chlorides

Beef

$2,633,126

28,142

28,283

3,532

3,391

Pork

$1,114,279

21,994

26,977

6,326

1,344

Chicken

$1,405,613

39,093

46,187

7,270

176

Turkey

$1,496,895

4,898

5,220

407

85

Option 3 with chlorides

Beef

$2,633,350

28,141

28,280

3,531

3,391

Pork

$1,114,434

21,992

26,970

6,322

1,344

Chicken

$1,406,124

39,077

46,160

7,259

176

Turkey

$1,497,096

4,896

5,218

407

85

Source: U.S. EPA analysis, 2023.

6.4.4 Market-Level Impacts
After estimating the pre- and post-regulatory equilibria for each meat product market, EPA estimated the
following market-level impacts of proposed changes to the MPP ELGs on prices and quantities:

•	Change in market price for each meat product (P/ — P,)

•	Change in U.S. demand for each meat product (Qf — Qf)

•	Change in U.S. supply of each meat product (Qf — Qf)

•	Change in foreign demand for each U.S. meat product (Qf — Qf)

•	Change in foreign sales of each meat product to the United States (Qf — Qf)

Table 6-10 and Table 6-11 present the price and quantity impacts of the proposed rule on each meat
product market based on the methodology above, respectively.

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Table 6-10: Post-Compliance Meat Market Prices Compared to Baseline Prices



Baseline

Percentage Change in Price3

Meat
Product

Prices (2022$
per Million
Pounds)

Option 1

Option 2

Option 3

Option 1

with
chlorides

Option 2

with
chlorides

Option 3

with
chlorides

Beef

$2,632,438

0.01%

0.02%

0.03%

0.01%

0.03%

0.03%

Pork

$1,113,816

0.01%

0.03%

0.05%

0.02%

0.04%

0.06%

Chicken

$1,405,267

0.01%

0.02%

0.05%

0.02%

0.02%

0.06%

Turkey

$1,496,779

<0.01%

0.01%

0.02%

0.01%

0.01%

0.02%

a. The change in price is calculated as the percentage change in terms of the baseline price. Generally this is described as:

(Pi - Pi)/Pi)-

Source: U.S. EPA analysis, 2023.











Table 6-11: Post-Compliance Meat Market Quantities Compared to Baseline Prices



Baseline

Percentage Change in Quantity3

Meat
Product

Quantities
(Million
Pounds)

Option 1

Option 2

Option 3

Option 1

with
chlorides

Option 2

with
chlorides

Option 3

with
chlorides

Quantity Demanded Domestically

Beef

28,145

>-0.01%

-0.01%

-0.01%

>-0.01%

-0.01%

-0.02%

Pork

22,000

-0.01%

-0.02%

-0.03%

-0.01%

-0.03%

-0.04%

Chicken

39,105

-0.01%

-0.02%

-0.06%

-0.02%

-0.03%

-0.07%

Turkey

4,900

-0.01%

-0.02%

-0.06%

-0.02%

-0.03%

-0.07%

Quantity Supplied Domestically

Beef

28,290

-0.01%

-0.02%

-0.03%

-0.01%

-0.02%

-0.03%

Pork

26,994

-0.02%

-0.05%

-0.08%

-0.03%

-0.06%

-0.09%

Chicken

46,206

-0.01%

-0.03%

-0.09%

-0.03%

-0.04%

-0.10%

Turkey

5,222

-0.01%

-0.02%

-0.06%

-0.02%

-0.03%

-0.07%

Exports Demanded

Beef

3,536

-0.03%

-0.09%

-0.13%

-0.05%

-0.11%

-0.15%

Pork

6,338

-0.05%

-0.15%

-0.21%

-0.08%

-0.18%

-0.24%

Chicken

7,278

-0.04%

-0.07%

-0.23%

-0.07%

-0.10%

-0.26%

Turkey

407

-0.01%

-0.02%

-0.08%

-0.02%

-0.03%

-0.09%

Imports Supplied

Beef

3,391

<0.01%

<0.01%

<0.01%

<0.01%

<0.01%

<0.01%

Pork

1,344

<0.01%

<0.01%

<0.01%

<0.01%

<0.01%

<0.01%

Chicken

176

<0.01%

<0.01%

<0.01%

<0.01%

<0.01%

<0.01%

Turkey

85

<0.01%

<0.01%

<0.01%

<0.01%

<0.01%

<0.01%

a. The difference in post-regulatory quantity and baseline quantity are calculated as the percentage change in terms of the

baseline quantity. Generally, this is described as: (QV — (}{)/(}{)¦







Source: U.S. EPA analysis, 2023.











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For this market analysis, EPA focused on the cross-price elasticities between meat products produced by
the regulated industry, rather than a broader set of substitutes. However, EPA acknowledges that some
consumers would choose substitutes not included in these meat products. EPA requests comment on the
potential consideration of additional substitution effects beyond the ones considered for this market
analysis.

6.5 Barrier-to-Entry Analysis

A barrier to entry is broadly understood as fixed costs that must be incurred by a new entrant, regardless
of production or sales activities, into a market that incumbents typically do not have or have not had to
incur. New entrants often face capital-intensive requirements to begin operations, which can discourage
entry, particularly for firms with limited financial resources or access to funding. Moreover, economies of
scale tend to favor established incumbents as efficiencies in production, distribution, and procurement
allow existing firms to benefit from cost advantages that are not available to new entrants. This forces
newcomers to compete on a cost basis with larger firms, potentially dissuading their entry into the market.
Because barriers to entry protect incumbent firms and restrict competition in a market, they can contribute
to the existence of monopolies and oligopolies or give incumbent firms large amounts of market power.

For example, a potential barrier to entry in the meat products market is the incremental capital costs that
the proposed rule may impose on a new entrant. If the new entrant not only needs capital to build and
equip a new facility and start operations, but also must invest significant capital in wastewater treatment
equipment to meet the proposed effluent guidelines, then this additional financial burden could discourage
the new entrant from entering the market. EPA examined the possibility that the proposed rule may create
incremental barriers to entry in the meat products industry.

Figure 6-1 presents the average entry and exit rates for new establishments in both the meat products
market and all-U.S. industries from 2000 to 2020, based on the U.S. Census Bureau's Business Dynamic
Statistics (BDS) dataset. For the most part, since 2000, establishment exit rates have exceeded entry rates
in the MPP industry. This finding is consistent with the data that shows the overall decline in the number
of establishments in the MPP industry. Furthermore, the low entry rate, along with the declining number
of total MPP-related establishments, may indicate that consolidation has been taking place in the industry.
It is possible that large vertically integrated establishments are being retained, while smaller independent
establishments constitute the large exit rates associated with the MPP industry.

Additionally, both the entry and exit rates are lower for the MPP industry than the overall U.S. average.
This could indicate that the MPP industry is relatively stable, or less subject to changes in the form of
new establishments entering or existing businesses exiting. Moreover, an entry rate that is lower than the
exit rate and the U.S. average could be an indication that there are barriers to entry in the MPP industry.
These findings are consistent with the discussion in Section 2.4: Trends in Industry Concentration.

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Figure 6-1: Establishment Entry and Exit Rates for MPP and all U.S. Industries, from 2000-2020

£
£

J2

to
to

a?

o
+-*
<+-
o

«s
£
a

13

12

11

10

^ ^ ^ ^ ^ ^ ^ ^	^ ^ ^ -if

•3116 entry rate

•3116 exit rate

Year
U.S. entry rate

3,900
3,800
3,700

3,600 |

3,500
3,400
3,300
3,200
3,100
3,000
2,900

¦Q

n>

ts

o

.a

E

3

z

• U.S. exit rate

»# establishments (3116)

Source: U.S. Census Bureau, 2020

To further analyze the impact of the proposed rule on incremental capital requirements for new entrants,
EPA estimated the total assets owned by each in-scope facility. EPA took total assets (adjusted to 2022
dollars) from the U.S. Census Bureau's 2017 Economic Census (EC) dataset. EPA assigned average total
assets by establishment from the EC 2017 dataset to each facility based on the facility's state and NAICS.
If the facility's state information was unavailable, EPA assigned average total assets by establishment
based on the facility's NAICS at the national level. If the facility's NAICS information was unavailable at
the national level, or if a facility had associated capital costs but no NAICS, EPA assigned average total
assets by establishment for the U.S. MPP industry (NAICS 3116). Using identical methodology, EPA
calculated total baseline capital expenditures for every in-scope facility. EPA calculated capital costs
based on the treatment technology costs for each facility, by option. EPA calculated both the ratio of
incremental capital costs to total assets and baseline capital expenditures to total assets as measures of the
potential for barriers to entry due to the proposed rule.

The incremental capital costs to total asset ratio indicates the proportion of a facility's total assets that are
being used to cover capital costs associated with adhering to regulatory requirements. A larger ratio
suggests that a substantial portion of the company's assets is allocated to financing obligations,
encompassing costs related to regulatory compliance, such as compliance technology, installation, and
construction. This signifies significant financial commitments required for adherence to regulatory
standards, and a possible barrier-to-entry, as new entrants face challenges in covering compliance-
associated expenses.

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6: Market Impact Analysis

On the other hand, the total baseline capital expenditures to total asset ratio reflects the proportion of a
company's total assets allocated to all baseline capital expenditures, irrespective of regulatory obligations.
This ratio accounts for investments in operational assets, infrastructure, and equipment. Unlike the
incremental capital costs to total asset ratio, this ratio includes investments that would occur in the
absence of any regulation.

Table 6-12 presents the ratio of incremental capital costs to total assets and the ratio of total baseline
capital expenditures to total assets by processing type and regulatory options. EPA weighted the capital
costs, baseline capital expenditures, and asset values by production for facilities that are covered under
each regulatory option and have associated treatment technology-based capital costs. For some processing
types and regulatory options (e.g., meat first under Option 1), compliance capital costs are a significant
portion of total assets and larger than baseline capital expenditures, indicating a potential barrier to entry.
As expected, these ratios become larger with more stringent regulatory options. This is reflected in the
observed changes in the capital costs to assets ratio and baseline capital expenditures to assets ratio,
indicating that compliance-related capital costs may pose a more significant barrier to entry for new
entrants then non-regulatory expenditure costs, under more stringent regulatory options.

Table 6-12: Capital Cost and Baseline Expenditure Ratios by Processing Type and Regulatory
Option

Option 1

Process Type

Average Capital
Costs ($1,000)

Average Total
Baseline Capital
Expenditures
($1,000)

Average Total
Depreciable
Assets ($1,000)

Capital Costs to
Assets Ratio

Baseline Capital
Expenditures to
Assets Ratio

Meat First

$9,968

$1,769

$21,133

0.472

0.084

Meat Further

$2,112

$2,293

$29,911

0.071

0.077

Poultry First

$8,147

$6,456

$53,463

0.152

0.121

Poultry Further

$2,843

$6,490

$50,997

0.056

0.127

Render

$3,894

$5,870

$49,693

0.078

0.118

Option 2

Process Type

Average Capital
Costs ($1,000)

Average Total
Baseline Capital
Expenditures
($1,000)

Average Total
Depreciable
Assets ($1,000)

Capital Costs to
Assets Ratio

Baseline Capital
Expenditures to
Assets Ratio

Meat First

$13,454

$1,877

$24,386

0.552

0.077

Meat Further

$2,112

$2,293

$29,911

0.071

0.077

Poultry First

$12,649

$7,272

$56,398

0.224

0.129

Poultry Further

$2,843

$6,490

$50,997

0.056

0.127

Render

$6,339

$4,331

$46,462

0.136

0.093

Option 3

Process Type

Average Capital
Costs ($1,000)

Average Total
Baseline Capital
Expenditures
($1,000)

Average Total
Depreciable
Assets ($1,000)

Capital Costs to
Assets Ratio

Baseline Capital
Expenditures to
Assets Ratio

Meat First

$13,160

$1,873

$24,095

0.546

0.078

Meat Further

$7,083

$2,758

$23,251

0.305

0.119

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RIAfor Proposed Meat and Poultry Products ELGs

6: Market Impact Analysis

Table 6-12: Capital Cost and Baseline Expenditure Ratios by Processing Type and Regulatory
Option

Poultry First

$12,329

$7,239

$56,149

0.220

0.129

Poultry Further

$3,839

$5,008

$45,426

0.085

0.110

Render

$4,712

$3,406

$34,793

0.135

0.098

Option 1 + Chlorides

Process Type

Average Capital
Costs ($1,000)

Average Total
Baseline Capital
Expenditures
($1,000)

Average Total
Depreciable
Assets ($1,000)

Capital Costs to
Assets Ratio

Baseline Capital
Expenditures to
Assets Ratio

Meat First

$10,601

$1,848

$26,230

0.404

0.070

Meat Further

$1,398

$2,373

$25,693

0.054

0.092

Poultry First

$8,041

$5,728

$60,266

0.133

0.095

Poultry Further

$1,605

$5,097

$43,999

0.036

0.116

Render

$3,894

$5,870

$49,693

0.078

0.118

Option 2 + Chlorides

Process Type

Average Capital
Costs ($1,000)

Average Total
Baseline Capital
Expenditures
($1,000)

Average Total
Depreciable
Assets ($1,000)

Capital Costs to
Assets Ratio

Baseline Capital
Expenditures to
Assets Ratio

Meat First

$16,669

$1,866

$24,008

0.694

0.078

Meat Further

$1,398

$2,373

$25,693

0.054

0.092

Poultry First

$14,151

$7,159

$58,483

0.242

0.122

Poultry Further

$1,605

$5,097

$43,999

0.036

0.116

Render

$6,339

$4,331

$46,462

0.136

0.093

Option 3 + Chlorides

Process Type

Average Capital
Costs ($1,000)

Average Total
Baseline Capital
Expenditures
($1,000)

Average Total
Depreciable
Assets ($1,000)

Capital Costs to
Assets Ratio

Baseline Capital
Expenditures to
Assets Ratio

Meat First

$16,338

$1,863

$23,772

0.687

0.078

Meat Further

$7,097

$2,742

$23,070

0.308

0.119

Poultry First

$13,840

$7,139

$58,225

0.238

0.123

Poultry Further

$4,027

$5,002

$45,261

0.089

0.111

Render

$4,712

$3,406

$34,793

0.135

0.098

Source: U.S. Census Bureau, 2017a, 2017b; U.S. EPA analysis, 2023.

6.6 Uncertainties and Limitations

The main sources of uncertainty for the market impact analysis presented in this chapter are:

• EPA relied on an average long-run elasticity of supply based on estimates from a range of years.
Some of these studies are relatively old compared to the analysis period of this rule. Moreover,
for the calculation of the average long-run elasticity of supply for beef, EPA excluded estimates
from Marsh (1994) and Jeong (2019) because they are noted by the authors to be larger than other

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6: Market Impact Analysis

estimates in the existing literature. Overall, the average long-run elasticity of supply estimates for
each meat product may differ from the true elasticity of supply for each meat product in the
market impact analysis.

•	In calculating the weighted average compliance costs for each meat product market, the Agency
relied on limited production data from the survey and relied on estimates of production for some
facilities.

•	EPA relied data on baseline trade, production, and wholesale prices from USDA and trade share
data from UNFAO, consistent with U.S. EPA (2002). These data include estimates that may
differ from the true baseline values of the U.S. MPP market.

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RIAfor Proposed Meat and Poultry Products ELGs

7: Employment Impacts

7 Assessment of Impacts on Employment

7.1	Background and Context

In addition to addressing the costs and impacts of the regulatory options, EPA estimated the potential
impacts of this rulemaking on employment, measured in terms of changes in full-time equivalent (FTE)
labor inputs.21 Evaluation of employment impacts is required by many environmental statutes, including
the Clean Water Act (CWA section 5071, 33 U.S.C. § 13671). EPA estimated short-run employment
impacts from post-compliance closures (Section 7.2) and long-run employment impacts associated with
the operation of new treatment technology (Section 7.3) and new market equilibrium (Section 7.4) under
each regulatory option. Section 7.5 presents the total employment impacts of the proposed rule, and
Section 7.6 presents the uncertainties and limitations of the Agency's assessment of the proposed rule's
impact on employment.

7.2	Post-Compliance Closures

The Agency estimated the short-run impacts associated with post-compliance closures under each
regulatory option. To do this, EPA calculated the labor productivity22 at each facility using survey
questionnaire data where available. The Agency then calculated the average labor productivity and
average production by process type and production size. Table 7-1 presents estimates of the average
production and labor productivity by process type and production size.

One FTE equals 2,080 labor hours per year.

Labor productivity at the facility-level is calculated as the production at the facility divided by the number of
employees at the facility.

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7: Employment Impacts

Table 7-1: Average Facility Labor Productivity and Production by Process Type and Production

Size













Production size3

Process Type

< 20 M

>= 20 M, < 50 M

>= 20 M, < 100 M

>= 50 M

>= 100 M

Average labor productivity (pounds/employee)

Meat first

165,615

458,738

693,387

913,945

922,391

Meat further

106,024

208,782

311,734

384,980

367,652

Poultry first

94,288

133,714

165,293

5,623,413

5,769,791

Poultry further

95,120

662,096

477,642

305,494

226,803

Rendering

197,624

954,156

1,016,609

4,168,573

4,599,020

Average production (pounds/facility/year)

Meat first

2,084,258

32,033,800

47,601,846

1,205,942,164

1,513,620,792

Meat further

2,136,400

31,443,390

55,560,390

118,891,108

229,233,755

Poultry first

2,913,433

38,336,641

47,067,494

540,429,760

557,917,396

Poultry further

3,104,067

36,124,320

55,525,866

132,415,326

192,498,592

Rendering

4,893,616

32,616,921

62,091,549

259,546,986

276,284,524

a. EPA estimated closures for direct and indirect dischargers using different production size bins. As a result, there is overlap

in the production sizes shown in this table. The Agency calculated output loss for direct and indirect dischargers based on

the average production for the appropriate production size and process type.





Source: U.S. EPA Analysis, 2023.









EPA multiplied the number of closures (see Section 5.7 for more information of the number of facility
closures under each regulatory option), by process type and production size, by the associated average
production for those facilities to estimate the loss in output. The Agency then estimated the loss in
employment by dividing losses in output by average labor productivity. Table 7-2 presents the
employment impacts associated with facility closures by regulatory option and process type. Overall, the
Agency estimates employment losses under each regulatory option. Without chlorides, Option 3 has the
greatest short-run employment decrease, followed by Options 2 and 1. Employment decreases due to
facility closures are considered short-run. Post-compliance facility closures may not directly translate to
decreases in demand for meat products. As a result, losses in employment due to closures may be
mitigated in the long run as supply adjusts to meet demand (see Section 7.4).

Table 7-2: Employment Changes Due to Facility Closures by Regulatory Option and Process

Type (# FTE)





















Option 1

Option 2

Option 3









with

with

with

Process Type

Option 1

Option 2

Option 3

chlorides

chlorides

chlorides

Meat first

-16,410

-16,410

-16,422

-16,410

-16,410

-16,422

Meat further

0

0

-1,383

-397

-397

-1,383

Poultry first

-483

-966

-1,346

-803

-1,093

-1,442

Poultry further

0

0

-849

-881

-881

-849

Rendering

-25

-85

-205

-25

-85

-205

Total

-16,917

-17,461

-20,205

-18,516

-18,866

-20,301

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7: Employment Impacts

Table 7-2: Employment Changes Due to Facility Closures by Regulatory Option and Process
Type (# FTE)

Process Type

Option 1

Option 2

Option 3

Option 1

with
chlorides

Option 2

with
chlorides

Option 3

with
chlorides

Total employment change as
% of U.S. employment3

3.33%

3.43%

3.97%

3.64%

3.71%

3.99%

a. Total employment for the total U.S. MPP sector (NAICS 3116) was 508,781 in 2017 (U.S. Census Bureau, 2017b)

Source: U.S. EPA analysis, 2023.













7.3 New Treatment Technology

In addition to estimating the short-run employment impacts associated with post compliance closures
under each regulatory option, EPA estimated the long-run employment impacts associated with the
operation of the new treatment technologies due to the proposed rule.

To do this, EPA calculated the additional labor hours required by MPP facilities that would install
treatment technologies under each regulatory option (see TDD for details). Table 7-3 presents the
estimated change in FTE by process type associated with the required labor to operate the new treatment
technologies for each regulatory option.23 Overall, EPA estimates that the operation of the new treatment
technologies would increase labor inputs for all MPP process types, with a total increase ranging from
166 to 1,942 FTEs, depending on the regulatory option.

Table 7-3: Estimated FTE Requirements for Operation of Treatment Technology, by Process
Type and Regulatory Option

Process Type

Regulatory Option

Option 1

Option 2

Option 3

Meat first

37

221

355

Meat further

15

15

650

Poultry first

78

365

491

Poultry further

15

15

209

Rendering

21

52

237

Total

166

669

1,942

Source: U.S. EPA analysis, 2023.

7.4 New Market Equilibrium

In addition to estimating the long-run employment impacts associated with new treatment technology,
EPA estimated the employment impacts associated with the long-run changes in domestic production due
to the proposed rule (see Section 6 for more information on the market impact analysis of the proposed
rule). As a result of the long-run decrease in domestic production, MPP processors will reduce the level of
employment at facilities to adjust to new levels of production. EPA estimated this decrease in

EPA has not estimated the labor hours required for operation of high chloride wastewater treatment systems.

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7: Employment Impacts

employment based on the labor productivity and the reduction in the quantity produced in each meat
product market.

To estimate labor productivity, EPA gathered information on the number of employees under each MPP
NAICS sector (NAICS 311611, 311612, 311613, and 311615) from the 2017 Economic Census (U.S.
Census Bureau, 2017b) and on domestic production by meat product market from USDA (Knight et al.,
2023). Data on employment are available for meat first (NAICS 311611) and meat further (NAICS
311612) processors. However, information on employment for poultry first and further processers are
only available for NAICS code 311615 (poultry processing). To estimate the number of employees at
poultry first and further processing facilities separately, the Agency estimated the percentage of facilities
in the total U.S. meat and poultry markets that are first and further processors. Table 7-4 presents the
percentages of the meat and poultry industry made up of first and further processors. EPA multiplied the
number of employees under NAICS sector 311615 by the percentages of first and further processors in
the poultry industry.

Table 7-4: Percentages of Facilities Belonging to Each Meat Process

Process type

# facilities

% total facilities

Meat

Meat first

826

19%

Meat further

3,460

81%

Total

4,286

100%

Poultry

Poultry first

290

50%

Poultry further

294

50%

Total

584

100%

Source: U.S. EPA analysis, 2023.

Data on domestic production from USDA are available by meat product (i.e., beef, pork, chicken, and
turkey). EPA added the total domestic production for beef and pork to estimate total U.S. meat
production. Similarly, EPA added total domestic production for chicken and turkey to estimate total U.S.
poultry production. Then, the Agency estimated the domestic production that belongs to each process type
by multiplying the production for the total meat and poultry industries by the percentages of first and
further processors in those industries, respectively. EPA then calculated the labor productivity by dividing
production by the number of employees. Table 7-5 presents the Agency's estimates of labor productivity
by process type.

Table 7-5: Labor Productivity by Process Type

Process type

NAICS code

NAICS description

Number of
employees

Domestic
production
(pounds)

Labor productivity
(pou nds/ employee)

Meat first

311611

Animal (except
poultry) slaughtering

146,671

10,654,359,309

72,641

Meat further

311612

Meat processed from
carcasses

112,939

44,629,640,691

395,166

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7: Employment Impacts

Table 7-5: Labor Productivity by Process Type

Process type

NAICS code

NAICS description

Number of
employees

Domestic
production
(pounds)

Labor productivity
(pounds/employee)

Poultry first

311615

Poultry processing

119,211

25,537,876,712

214,224

Poultry further

311615

Poultry processing

120,856

25,890,123,288

214,224

Source: U.S. Census Bureau, 2017b; Knight et at., 2023; U.S. EPA analysis, 2023.

EPA converted the loss in production by meat product market, estimated in Section 6.4.4, to process type
by following the same approach outlined above using the percentages of facilities belonging to each
process type (Table 7-4). The Agency estimated loss in employment by dividing the loss in output by the
labor productivity.

Table 7-6 presents baseline employment and estimated long-run changes in employment by process type
and regulatory option.24 Overall, EPA estimates each regulatory option will result in a decrease in FTE
due to decreased domestic production. Option 1 has the lowest associated losses in employment and
Option 3 has the largest, with or without chlorides.

Table 7-6: Change in FTE by Process Type and Regulatory Option

Process type

Baseline
domestic
employment

Option 1

Option 2

Option 3

Option 1

with
chlorides

Option 2

with
chlorides

Option 3

with
chlorides

Meat first

146,671

-18

-54

-77

-29

-65

-88

Meat further

112,939

-14

-41

-60

-22

-50

-68

Poultry first

119,211

-17

-33

-100

-32

-48

-115

Poultry further

120,856

-17

-33

-102

-32

-48

-117

Total

499,677

-65

-161

-339

-114

-211

-389

Total employment
change as % of
U.S. employment3



-0.01%

-0.03%

-0.07%

-0.02%

-0.04%

-0.08%

a. Total employment for the total U.S. MPP sector (NAICS 3116) was 508,781 in 2017 (U.S. Census Bureau, 2017b).
Source: U.S. EPA analysis, 2023.

7.5 Estimated Impacts of the Proposed Rule

Table 7-7 presents the short- and long-run employment impacts associated with each regulatory option by
process type. These employment impacts are also presented as a percentage of the total U.S. employment
in the MPP industry (NAICS 3116). In the short run, the Agency estimates negative employment impacts
associated with each regulatory option. In the long run, EPA estimates positive employment impacts
associated with each regulatory option.

EPA does not analyze Tenderers in the market impact analysis. As a result, EPA excludes them from this analysis of
long-run employment impacts associated with changes in domestic production.

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7: Employment Impacts

Table 7-7: Short-run and Long-run Employment Impacts Associated with the Proposed Rule









Option 1

Option 2

Option 3









with

with

with

Process Type

Option 1

Option 2

Option 3

chlorides

chlorides

chlorides

Short-run employment impacts

Meat first

-16,410

-16,410

-16,422

-16,410

-16,410

-16,422

Meat further

0

0

-1,383

-397

-397

-1,383

Poultry first

-483

-966

-1,346

-803

-1,093

-1,442

Poultry further

0

0

-849

-881

-881

-849

Render

-25

-85

-205

-25

-85

-205

Total

-16,917

-17,461

-20,205

-18,516

-18,866

-20,301

Total employment change as













% of U.S. employment3

-3.3%

-3.4%

-4.0%

-3.6%

-3.7%

-4.0%

Long-run employment impacts'3

Meat first

19

167

278

8

156

267

Meat further

1

-26

590

-7

-35

582

Poultry first

61

333

391

46

318

376

Poultry further

-2

-18

107

-17

-33

92

Render

21

52

237

21

52

237

Total

101

508

1,603

52

458

1,553

Total employment change as













% of U.S. employment3

0.02%

0.10%

0.32%

0.01%

0.09%

0.31%

a. Total employment for the total U.S. MPP sector (NAICS 3116) was 508,781 in 2017 (U.S. Census Bureau, 2017b).

b. Long-run employment impacts are calculated as the sum of the employment changes related to new technology from

Table 7-3 and new market equilibria from Table 7-6 by process type and regulatory option.





Source: U.S. EPA analysis, 2023.













7.6 Uncertainties and Limitations

The main sources of uncertainty for the employment analysis presented in this chapter are:

•	EPA relied on information from the MPP detailed questionnaire to estimate labor productivity by
process type for the analysis of short-run employment impacts related to facility closures. Due to
the limited employment data available from the MPP detailed questionnaire, the results of the
short-run employment impact analysis may over or underestimate the true labor productivity and
short-run employment impacts of the proposed rule.

•	EPA did not estimate the employment requirements associated with operation of high chloride
wastewater treatment systems. EPA expects the long-run labor impacts associated with regulatory
options with chlorides to be larger than for those without chlorides. As a result, EPA may
underestimate the long-run employment impacts associated with new treatment technology.

•	The Agency relied on the results of the market impact analysis (see Section 6.4.3) to estimate the
long-run impacts of the proposed rule on employment. However, the market impact analysis does
not explicitly examine rendering facilities. Because of this, the Agency does not analyze long-run

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RIA for Proposed Meat and Poultry Products ELGs	7: Employment Impacts

employment impacts related to new market equilibria under the regulatory options for rendering
facilities.

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8: Cost Pass-Through

8 Cost Pass-Through Analysis

8.1 Background and Context

Cost pass-through (CPT) refers to the process by which changes in operating costs incurred by a business
or industry are transferred to other entities within the supply chain, such as suppliers or consumers. In this
context, when businesses incur regulatory compliance costs, they may choose to pass on a portion or the
entirety of these additional expenses to other entities in the supply chain. The transfer of costs could occur
both upstream, affecting suppliers, and downstream, impacting consumers. This process has the potential
to impact the net costs incurred by MPP facilities, wholesale and retail prices for meat products, and the
prices paid to farmers for MPP inputs.

The analysis of impacts of the proposed rule presented in the main body of this RIA conservatively
assumes zero CPT. With this sensitivity analysis, EPA estimated the facility impacts of the proposed rule
using an assumption of nonzero CPT derived from the market impact analysis of the proposed rule.

Markets may have zero CPT if demand is perfectly elastic (demand is fixed at one price point) or if
supply is perfectly inelastic (production does not change due to market price changes). The estimated
demand and supply elasticities for the U.S. MPP markets taken from literature (see Section 6.3.2)
demonstrate that the supply and demand for these markets are not perfectly inelastic and elastic,
respectively.

As estimated in the market impact analysis of the proposed rule (Section 6), domestic MPP processors
will reduce the quantity produced at their facilities in response to the compliance costs of the proposed
rule. As a result, the Agency estimates that the equilibrium price for each meat product market will
increase. The higher prices MPP facilities are estimated to receive will offset a portion of their
compliance costs, resulting in lower net costs and smaller impacts. EPA assumes that MPP facilities will
only offset a portion of compliance costs to consumers via higher prices in this quantitative analysis of
CPT.

The Agency estimated CPT by regulatory option and meat product i using the pre- and post-regulatory
price and average per-unit compliance costs from the market impact analysis as follows:

P'L - Pt

Cost pass through (CPT) = —-—

Si

This equation returns the percentage of compliance costs paid by consumers via higher prices in MPP
market i. Conversely, the percentage of compliance costs incurred by MPP processors is defined as:

% compliance costs incurred by MPP processors = 1 — CPT

For instance, if CPT is 40 percent in meat market i, consumers pay $0.40 and processors pay $0.60 of
every $1 of per unit compliance costs. EPA estimated CPT under each option for each meat and poultry
product market (i.e., the beef, pork, chicken, and turkey markets). EPA then calculated the average CPT
for the total meat and poultry markets weighted by the domestic production of each meat and poultry
product in those markets, respectively. Table 8-1 presents the weighted average percentages of
compliance costs incurred by facilities (1-CPT) by total meat and poultry market. EPA used these

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weighted average percentages to conduct this sensitivity analysis. To do this, EPA estimated CPT by
facility as an average, weighted by the facility's relative production of meat and poultry. EPA then
calculated the percentage of compliance costs incurred by each facility based on this weighted average of
CPT at the facility.

Table 8-1

: Weighted Average Percentage of Compliance Costs Incurred by Facilities (1-CPT) by

Meat Product



















Option 1 with

Option 2 with

Option 3 with

Market

Option 1

Option 2

Option 3

chlorides

chlorides

chlorides

Meat

73.67%

73.35%

74.01%

73.82%

73.47%

74.02%

Poultry

80.16%

80.61%

79.93%

80.04%

80.38%

79.93%

Source: U.S. EPA Analysis, 2023.

8.2 Total Compliance Costs

EPA estimated total compliance costs assuming nonzero CPT based on facility-specific compliance costs
and CPT estimates described in Section 8.1. Table 8-2 presents estimates of the total annualized pre-tax
compliance costs by regulatory option with CPT at a 3 percent discount rate. As stated in Section 3.1.1.4,
these costs represent the social costs associated with the proposed rule assuming nonzero CPT. The total
compliance costs associated with the preferred option (Option 1) are about 22% smaller assuming
nonzero CPT compared to the compliance costs assuming zero CPT, under both discount rates (Table
3-1).

Table 8-2: Estimated Total Annualized Pre-Tax Compliance Costs with CPT, 3 percent discount
rate (in millions, 2022$, at 2025)

Regulatory Option

Direct

Indirect

Total

Option 1

$170.7

$11.8

$182.5

Option 2

$171.1

$332.4

$503.4

Option 3

$176.2

$668.1

$844.3

Option 1 with chlorides

$219.3

$84.0

$303.3

Option 2 with chlorides

$219.5

$404.2

$623.7

Option 3 with chlorides

$224.9

$740.4

$965.2

Source: U.S. EPA Analysis, 2023.

Table 8-3 presents estimates of the total annualized after-tax compliance costs with CPT, at 7.6 percent
discount rate. As in Section 4.2, EPA calculated after-tax compliance costs assuming nonzero CPT by
applying combined federal and state tax rates to pre-tax costs by facility, using a discount rate equal to the
industry's estimated private cost of capital (7.6 percent). The after-tax compliance costs assuming
nonzero CPT are about 22% smaller than the after-tax costs assuming zero CPT (Table 4-1).

Table 8-3: Estimated Total Annualized After-Tax Compliance Costs with CPT (in millions, 2022$)

Regulatory Option

Direct

Indirect

Total

Option 1

$155.1

$11.0

$166.0

Option 2

$155.4

$307.7

$463.1

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Table 8-3: Estimated Total Annualized After-Tax Compliance Costs with CPT (in millions, 2022$)

Regulatory Option

Direct

Indirect

Total

Option 3

$159.8

$621.5

$781.3

Option 1 with chlorides

$199.2

$77.0

$276.2

Option 2 with chlorides

$199.4

$373.4

$572.8

Option 3 with chlorides

$204.0

$687.6

$891.6

Source: U.S. EPA Analysis, 2023.

8.3 Facility-Level Cost-to-Revenue Analysis

EPA estimated facility-level CTR with CPT following the same steps outlined in Section 4.3 using
facility-level compliance costs assuming nonzero CPT. Table 8-4 presents the facility CTR analysis
results with CPT by regulatory option. Similar to the results presented in Section 4.3.2, EPA estimates
that most facilities would not experience costs exceeding one or three percent of revenue. Additional
facilities would experience costs greater than one percent of revenue (and less than three percent of
revenue) with regulatory Options 3 and 2 compared to Option 1. The number of facilities that would
experience costs greater than one percent of revenue (and less than three percent of revenue) and greater
than three percent of revenue for the preferred option (Option 1) is the same assuming nonzero and zero
CPT.

Table 8-4: Facility-Level After-Tax Compliance Cost-to-Revenue Analysis Results by Discharge
Type and Regulatory Option

Discharge
Type

Total
Number of
Dischargers

Total
Number

of
Facilities
with
Costs

Number of Facilities with a
Ratio of

Percent of All Dischargers with a
Ratio of

0%a

<1%

>1
and
<3%

>3%

0%a

<1%

>1
and
<3%

>3%

Option 1

Direct

171

126

45

120

5

1

26%

70%

3%

0.6%

Indirect

3,708

719

2,989

718

0

1

81%

19%

0.00%

0.03%

Total

3,879

845

3,034

838

5

2

78%

22%

0.1%

0.1%

Option 2

Direct

171

126

45

120

5

1

26%

70%

3%

0.6%

Indirect

3,708

719

2,989

709

6

4

81%

19%

0.2%

0.1%

Total

3,879

845

3,034

829

11

5

78%

21%

0.3%

0.1%

Option 3

Direct

171

135

36

128

6

1

21%

75%

4%

1%

Indirect

3,708

1,485

2,223

1,454

23

8

60%

39%

0.6%

0.2%

Total

3,879

1,620

2,259

1,582

29

9

58%

41%

0.7%

0.2%

Option 1 with chlorides

Direct

171

129

42

122

5

2

25%

71%

3%

1%

Indirect

3,708

817

2,891

811

0

6

78%

22%

0.0%

0.2%

Total

3,879

946

2,933

933

5

8

76%

24%

0.1%

0.2%

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8: Cost Pass-Through

Table 8-4: Facility-Level After-Tax Compliance Cost-to-Revenue Analysis Results by Discharge
Type and Regulatory Option

Discharge
Type

Total
Number of
Dischargers

Total
Number

of
Facilities
with
Costs

Number of Facilities with a
Ratio of

Percent of All Dischargers with a
Ratio of

0%a

<1%

>1
and
<3%

>3%

0%a

<1%

>1
and
<3%

>3%

Option 2 with chlorides

Direct

171

129

42

122

5

2

25%

71%

3%

1%

Indirect

3,708

817

2,891

803

7

7

78%

22%

0.2%

0.2%

Total

3,879

946

2,933

925

12

9

76%

24%

0.3%

0.2%

Option 3 with chlorides

Direct

171

136

35

128

5

3

20%

75%

3%

2%

Indirect

3,708

1,485

2,223

1,451

26

8

60%

39%

0.7%

0.2%

Total

3,879

1,621

2,258

1,579

31

11

58%

41%

0.8%

0.3%

a. These facilities already meet discharge requirements for the wastestreams controlled by a given regulatory option and
therefore are not estimated to incur compliance costs.

Source: U.S. EPA analysis, 2023.

8.4 Parent Entity-Level Cost-to-Revenue Analysis

EPA estimated entity-level CTR analysis following the same steps outlined in Section 4.4 using facility-
level compliance costs assuming nonzero CPT. Table 8-5 presents the entity-level impacts for each
regulatory option with CPT. The results for the preferred option (Option 1) assuming nonzero CPT match
the results of the entry-level impacts assuming zero CPT (Table 4-3).

Table 8-5: Entity-level cost-to-revenue analysis results

Regulatory
Option

Total
Number of
Entities

Number of Entities with a Ratio of

Percent of Entities with a Ratio ofb

0%a

>0 and
<1%

>1 and
<3%

>3%

0%a

>0 and
<1%

>1 and
<3%

>3%

Option 1

3,114

2,717

394

3

0

87%

13%

0.1%

0.0%

Option 2

3,114

2,717

393

3

1

87%

13%

0.1%

0.0%

Option 3

3,114

2,116

984

12

2

68%

32%

0.4%

0.1%

Option 1 with
chlorides

3,114

2,659

451

3

1

85%

14%

0.1%

0.0%

Option 2 with
chlorides

3,114

2,659

451

3

1

85%

14%

0.1%

0.0%

Option 3 with
chlorides

3,114

2,116

983

12

3

68%

32%

0.4%

0.1%

a.	These entities own only facilities that already meet discharge requirements for the wastestreams addressed by a given
regulatory option and are therefore not estimated to incur any compliance technology costs.

b.	Percentages may not add up to 100 percent due to rounding.

Source: U.S. EPA Analysis, 2023.

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8: Cost Pass-Through

8.5 Facility Closures

EPA estimated facility closures using the same extrapolation approach outlined in Section 5.6 using the
results of the facility CTR results assuming nonzero CPT. Table 8-6 presents the results of the facility
closure analysis outlined in Section 5 with CPT. EPA estimates that the number of estimated closures for
the preferred option (Option 1) is the same assuming nonzero and zero CPT.

Table 8-6: Facility Closure Extrapolation with CPT Results









Option 1 with

Option 2 with

Option 3 with



Option 1

Option 2

Option 3

chlorides

chlorides

chlorides

Number of estimated













facility closures

16

21

49

25

29

52

Number of facilities













with costs

845

845

1,620

946

946

1,621

Number of dischargers

3,879

3,879

3,879

3,879

3,879

3,879

% of facilities with













costs

1.9%

2.5%

3.0%

2.6%

3.1%

3.2%

% of all dischargers

0.4%

0.5%

1.3%

0.6%

0.7%

1.3%

Source: U.S. EPA Analysis, 2023.

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9: RFA

9 Assessment of Potential Impact of the Regulatory Options on Small
Entities - Initial Regulatory Flexibility Act (IRFA) 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
rules on small entities, to analyze alternatives that minimize those impacts,25 and to make their analyses
available for public comments. The RFA is concerned with three types of small entities: small businesses,
small nonprofits, and small government jurisdictions.

The RFA describes the regulatory flexibility analyses and procedures that must be completed by federal
agencies unless they certify that the rule, if promulgated, would not have a significant economic impact
on a substantial number of small entities. This certification must be supported by a statement of factual
basis, e.g., addressing the number of small entities affected by the proposed action, estimated cost impacts
on these entities, and evaluation of the economic impacts.

In accordance with RFA requirements and as it has consistently done in developing effluent limitations
guidelines and standards, EPA assessed whether the proposed regulatory options would have "a
significant impact on a substantial number of small entities" (SISNOSE). This assessment involved the
following steps:

•	Identifying the domestic parent entities of MPP facilities.

•	Determining which of those domestic parent entities are small entities, based on SB A size criteria
and USD A data.

•	Assessing the change in potential impact of the proposed regulatory options on those small
entities by comparing the estimated entity-level annualized compliance cost to entity-level
revenue; the cost-to-revenue ratio indicates the magnitude of economic impacts. Following EPA
and SBA guidance (U.S. EPA, 2006; U.S. Small Business Administration, 2017), EPA used
threshold compliance costs of one percent or three percent of entity-level revenue to categorize
the degree of significance of the economic impacts on small entities.

•	Assessing the change in whether those small entities incurring potentially significant impacts
represent a substantial number of small entities. Following EPA and SBA guidance (U.S. EPA,
2006; U.S. Small Business Administration, 2017), EPA determined whether the number of small
entities impacted is substantial based on (1) the estimated absolute numbers of small entities
incurring potentially significant impacts according to the two compliance cost impact thresholds,
and (2) the percentage of small entities in the relevant entity categories that are estimated to incur
these impacts.

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.

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EPA performed this assessment for each of the proposed options. This chapter describes why this action
is being considered (Section 9.1), the objectives and legal basis for the proposed rule (Section 9.2), the
small entities to which the proposed rule applies (Section 9.3), the compliance requirements (Section 9.4),
other relevant Federal rule (Section 9.5), potential economic impacts on small entities (Section 9.6), how
regulatory options developed by EPA served to mitigate the impact of the regulatory options on small
entities (Section 9.7), and uncertainties and limitations (Section 9.8). EPA considers this chapter to be the
Initial Regulatory Flexibility Analysis (IRFA) for this proposed rule.

9.1	Why this Action is being Considered

EPA is considering revisions to the current regulations that apply to wastewater discharges from MPP
facilities because the industry discharges large quantities of nutrients, such as nitrogen and phosphorus,
that enter the Nation's waters. Nutrient pollution is one of the most widespread, costly, and challenging
environmental problems impacting water quality in the United States. Excessive nitrogen and phosphorus
in surface water can lead to a variety of problems, including eutrophication and harmful algal blooms, that
have negative impacts on human health and the environment. For a more detailed rationale for the
proposed rulemaking see section I. A of the preamble to the proposed rule.

9.2	Objectives and Legal Basis for the Proposed Rule

The objectives of the rule are to reduce the nutrients directly discharged by the industry and to reduce the
passthrough of pollutants and/or the interference of wastewater treatment at POTWs receiving indirect
discharges from MPP facilities. For the legal basis of the proposed rulemaking see section III.C of the
preamble to the proposed rule.

9.3	Description and Number of Small Entities to Which the Proposed Rule Will Apply

9.3.1	Determining Parent Entity of MPP Facilities

Consistent with the entity-level cost-to-revenue analysis (see Chapter 4), EPA conducted the IRFA at the
highest level of domestic ownership, referred to as the "domestic parent entity" or "domestic parent firm".
As was done for the entity-level cost-to-revenue analysis in Section 4.4, EPA identified the parent entity
for each facility using responses to the census and detailed questionnaires, D&B Hoovers data, and
corporate and financial websites.

9.3.2	Determining Whether Parent Entities of MPP Facilities are Small

EPA identified the size of each parent entity using the SBA size threshold guidelines in effect as of March
17, 2023 (U.S. Small Business Administration, 2023). The criteria for entity size determination vary by
the NAICS sector of the parent entity. For entities with meat and poultry processing as a primary business
(NAICS 3116), small entities are those with less than the threshold number of employees specified by
SBA for each of the NAICS sectors (see Table 9-1). For entities with a primary business other than meat
and poultry processing, the relevant size criteria are based on revenue or number of employees by NAICS
sector.26

Certain facilities affected by this rulemaking are owned by entities whose primary business is not meat and poultry
processing. Some other primary businesses include NAICS, 445240 (Meat Retailers), 112340 (Poultry Hatcheries),
424510 (Grain and Field Bean Merchant Wholesalers), and 424470 (Meat and Meat Product Merchant Wholesalers).

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Table 9-1: NAICS Codes and SBA Size Standards for Owners of MPP Facilities

NAICS Code

NAICS Description

SBA Size Standard3

311611

Animal (Except Poultry) Slaughtering

1,150 employees

311612

Meat Processed From Carcasses

1,000 employees

311613

Rendering and Meat Byproduct Processing

750 employees

311615

Poultry Processing

1,250 employees

a. Based on size standards effective at the time EPA conducted this analysis (SBA size standards,

effective March 17, 2023).



Source: U.S. Small Business Administration, 2023



To determine whether a firm is a small entity according to these criteria, EPA compared the relevant
entity size criterion value estimated for each parent entity to the SBA threshold value. EPA used the
following data sources and methodology to estimate the relevant size criterion values for each parent
entity:

•	Employment: EPA used entity-level employment values from the detailed and census
questionnaires or D&B Hoovers, if those values were available.27

•	Revenue: EPA determined revenue values based on information reported in the detailed
questionnaire, the D&B Hoovers database, and from corporate or financial websites, if those
values were available. If parent entity revenue was unavailable from these sources, EPA
estimated revenue as the sum of facility revenue across all facilities owned by that parent entity.

Parent entities for which the relevant measure is less than the SBA size criterion were identified as small
entities and carried forward in the RFA analysis.

EPA also used revenue and employment data for some parent entities with missing NAICS codes to
identify their small business status. To do so, EPA calculated the minimum and maximum SBA
employment and revenue thresholds using the NAICS codes identified for firms with MPP dischargers.
These thresholds are presented in Table 9-2. If EPA could not identify a firm's NAICS code but had its
revenue or employment data, EPA designated a firm as a small business if its revenue or employment data
fell below the respective minimum threshold and large if its revenue or employment data fell above the
respective maximum threshold. For example, a firm that has revenue below $2.5 million or employment
under 100 employees is classified as small, while a firm with revenue over $47 million or over 1,400
employees is classified as large. EPA could not identify small business status for firms whose revenue or
employment data fell between the respective minimum and maximum thresholds.

EPA could not estimate employment for entities. The Agency reviewed the relationship between revenue and
employment and did not find a correlation between the two that allows for estimating employment.

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Table 9-2: Minimum and Maximum Revenue and Employment
Thresholds Applied to Firms with Missing NAICS Codes

Description of Threshold

Thresholds for Firms with Missing NAICS Codes

Minimum revenue

$2.5 million

Maximum revenue

$47 million

Minimum employment

100 employees

Maximum employment

1,400 employees

Source: U.S. EPA Analysis, 2023

If EPA did not have sufficient data based on the approach described above to determine T status, the
Agency used establishment size data from the USDA Meat, Poultry and Egg Product Inspection
Directory. This dataset classifies facilities as "very small," "small", or "large" based on self-reported
employment levels:

•	Very small: Less than 10 employees (or less than $2.5 million in annual sales).

•	Small: 10-499 employees.

•	Large: 500 or more employees.

EPA used these establishment sizes to classify single-facility entities as small or large. If a single-facility
entity is "very small" or "small" in the USDA data, EPA classified it as a small entity, and if a single-
facility entity is "large" in the USDA data, EPA classified it as a large business.

Table 9-3 presents the total number of entities with meat and poultry processing as a primary business as
well as the number and percentage of those entities determined to be small.

Table 9-3: Number of Entities by NAICS Code and Size

NAICS Code

Small Entity Size
Standard (# of
employees)

Entities in the MPP Industry

Total

# Small

% Small

311611

1,150

276

260

94%

311612

1,000

341

322

94%

311613

750

23

19

83%

311615

1,250

146

121

83%

Total

786

722

92%

Source: U.S. EPA Analysis, 2023.

9.4 Projected Compliance Requirements, Classes of Small Entities Subject to the
Compliance Requirements, and Professional Skills Needed to Comply

9.4.1 Projected Compliance Requirements
As described in this RIA and in the preamble for this proposed rule, EPA is proposing a regulation to
revise the technology-based ELGs for the MPP point source category. Under the proposed rule, MPP
facilities (and their owners) would be required to implement control technologies upon which the
proposed BAT and BPT limitations and pretreatment standards are based. MPP dischargers are not

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required to use the technologies specified as the basis for the rule. They are free to identify other perhaps
less expensive technologies as long as they meet the BAT limitations and pretreatment standards in the
rule.

In addition to the installation of treatment technology, MPP facilities would be subject to new reporting
and recordkeeping requirements (i.e., collect and ship samples, review and report pollutant data monthly,
and develop compliance reports).

9.4.2	Classes of Small Entities Subject to the Compliance Requirements

The small entities that would be potentially directly regulated by this rule are small entities that engage in
meat and/or poultry slaughter, further processing, and/or rendering.

9.4.3	Professional Skills Needed to Comply

EPA assumes that facility reporting and recordkeeping activity would require engineering support. For
additional discussion of reporting and recordkeeping activity, see the Information Collection Request
Supporting Statement (U.S Environmental Protection Agency, 2023).

9.5	Other Federal Rule that may Duplicate, Overlap, or Conflict with the Proposed Rule

EPA is revising the existing ELGs, which were last revised in 2004. These proposed revisions do not
duplicate, overlap, or conflict with any other existing federal rules.

9.6	Potential Economic Impact on Small Entities

As outlined in the introduction to this chapter, two criteria are assessed in determining whether the
regulatory options would qualify for a no-SISNOSE finding:

•	Is the absolute number of small entities estimated to incur a potentially significant impact, as
described above, substantial?

and

•	Do these significant impact entities represent a substantial fraction of small entities in the MPP
industry that could potentially be within the scope of a regulation?

A measure of the potential impact of the regulatory options on small entities is the fraction of small
entities that have the potential to incur a significant impact. For example, if a high percentage of
potentially small entities incur significant impacts even though the absolute number of significant impact
entities is low, then the rule could represent a substantial burden on small entities.

To assess the extent of economic/financial impact on small entities, EPA compared estimated compliance
costs to estimated entity revenue (a comparison also referred to as the "sales test"). The analysis is based
on the ratio of estimated annualized after-tax compliance costs to annual revenue of the entity. For this
analysis, EPA categorized entities according to the magnitude of economic impacts that entities would
incur due to the regulatory options. EPA identified entities for which annualized compliance costs are at
least one percent and three percent of revenue. EPA then evaluated the absolute number and the percent
of entities in each impact category.

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The Agency assumed that entities incurring costs below one percent of revenue are unlikely to face
significant economic impacts, while entities with costs of at least one percent of revenue have a higher
chance of facing significant economic impacts, and entities incurring costs of at least three percent of
revenue have a still higher probability of significant economic impacts. Consistent with the parent-level
cost-to-revenue analysis discussed in Chapter 4, EPA assumed that MPP facilities, and consequently,
their parents, would not be able to pass any of the increase in their production costs to consumers (zero
cost pass-through). This assumption is used for analytic convenience and provides a worst-case scenario
of regulatory impacts to MPP facilities. As discussed in Chapter 8, entities can be expected to pass on
some of their compliance costs upstream and/or downstream although the analysis in Chapter 8 show
small market impacts.

A detailed summary of how EPA developed these entity-level compliance cost and revenue values is
presented in Chapter 3 and Chapter 4.

As described above, EPA developed estimates of the number of small parent entities in the specified CTR
impact ranges. Table 9-4 presents the results of the CTR test for all entities that own MPP dischargers.
EPA conservatively assumes that entities with an unidentified size are large. While this assumption
potentially reduces the number of identified small entities, it provides a conservative estimate of the
percentage of small entities with impacts, since none of the entities with an unidentified size have a CTR
ratio greater than one percent under any of the regulatory options.

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Table 9-4: Entity-Level CTR Analysis Results by Entity Type





Aggregate

Cost per

Number Entities with a Ratio of

Percent of Entities with a Ratio of





Costs (in

entity (in



















Total # of

millions,

millions,



> 0 and

>1 and





> 0 and

>1 and



Entity Type

Entities

2022$)

2022$)c

0%a

<1%

<3%

>3%

0%a

<1%

<3%

>3%

Option 1

Small

2,296

$22.3

$0.01

2,200

95

1

0

96%

4%

0.0%

0.0%

Large

725

$187.5

$0.3

443

280

2

0

61%

39%

0.3%

0.0%

Unidentified



$0.6

$0.01

















sizeb

93





74

19

0

0

80%

20%

0.0%

0.0%

Total

3,114

$210.3

$0.1

2,717

394

3

0

87%

13%

0.1%

0.0%

Option 2

Small

2,296

$78.5

$0.03

2,200

94

1

1

96%

4%

0.0%

0.0%

Large

725

$502.4

$0.7

443

280

2

0

61%

39%

0.3%

0.0%

Unidentified



$9.6

$0.1

















sizeb

93





74

19

0

0

80%

20%

0.0%

0.0%

Total

3,114

$590.4

$0.2

2,717

393

3

1

87%

13%

0.1%

0.0%

Option 3

Small

2,296

$168.6

$0.1

2,034

247

11

4

89%

11%

0%

0%

Large

725

$806.1

$1.1

23

699

3

0

3%

96%

0%

0%

Unidentified



$20.9

$0.2

















sizeb

93





61

32

0

0

66%

34%

0%

0%

Total

3,114

$995.6

$0.3

2,118

978

14

4

68%

31%

0%

0%

Option 1 with chlorides

Small

2,296

$50.8

$0.02

2,158

136

1

1

94%

6%

0.0%

0.0%

Large

725

$300.8

$0.4

432

291

2

0

60%

40%

0.3%

0.0%

Unidentified



$2.6

$0.0

















sizeb

93





69

24

0

0

74%

26%

0.0%

0.0%

Total

3,114

$354.1

$0.1

2,659

451

3

1

85%

14%

0.1%

0.0%

Option 2 with chlorides

Small

2,296

$106.9

$0.05

2,158

136

1

1

94%

6%

0.0%

0.0%

Large

725

$615.7

$0.8

432

291

2

0

60%

40%

0.3%

0.0%

Unidentified



$11.6

$0.1

















sizeb

93





69

24

0

0

74%

26%

0.0%

0.0%

Total

3,114

$734.2

$0.2

2,659

451

3

1

85%

14%

0.1%

0.0%

Option 3 with chlorides

Small

2,296

$197.1

$0.1

2,034

247

11

4

89%

11%

0%

0%

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9: RFA

Table 9-4: Entity-Level CTR Analysis Results by Entity Type





Aggregate

Cost per

Number Entities with a Ratio of

Percent of Entities with a Ratio of





Costs (in

entity (in



















Total # of

millions,

millions,



> 0 and

>1 and





> 0 and

>1 and



Entity Type

Entities

2022$)

2022$)c

0%a

<1%

<3%

>3%

0%a

<1%

<3%

>3%

Large

725

$919.4

$1.3

23

699

3

0

3%

96%

0%

0%

Unidentified



$22.9

$0.2

















sizeb

93





61

32

0

0

66%

34%

0%

0%

Total

3,114

$1,139.4

$0.4

2,118

978

14

4

68%

31%

0%

0%

a. These entities own only facilities that already meet discharge requirements for the wastestreams addressed by a given regulatory option and are therefore not estimated

to incur any compliance technology costs. Entities with no MPP dischargers are excluded from this table.











b. EPA could not identify the small business status of these entities since their revenue or employment values fall between the thresholds presented in Table 9-2.



c. EPA calculated the cost per entity by dividing aggregate costs by the total number of entities.













Source: U.S. EPA Analysis, 2023

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9: RFA

Overall, this analysis suggests that the analyzed regulatory options are unlikely to have a significant
economic impact or a substantial impact on small entities. Table 9-5 summarizes the results of the
analysis.

Table 9-5: Estimated Cost-to-Revenue Impact on Small Parent

Entities, by Facility Type









Cost-to-revenue



>1%

>3%a

Type of dischargers

Number of

% of all

Number of

% of all

owned by parent

small

small

small

small

entities

entities

entities'3

entities

entities'3

Option 1

Direct only

1

3%

0

0%

Indirect only

0

0%

0

0%

Both

0

0%

0

0%

Total

1

3%

0

0%

Option 2

Direct only

1

3%

0

0%

Indirect only

0

0%

1

0%

Both

0

0%

0

0%

Total

1

3%

1

0%

Option 3

Direct only

1

3%

1

3%

Indirect only

9

1%

3

0%

Both

1

13%

0

0%

Total

11

16%

4

4%

Option 1 with chlorides

Direct only

1

3%

0

0%

Indirect only

0

0%

1

0%

Both

0

0%

0

0%

Total

1

3%

1

0%

Option 2 with chlorides

Direct only

1

3%

0

0%

Indirect only

0

0%

1

0%

Both

0

0%

0

0%

Total

1

3%

1

0%

Option 3 with chlorides

Direct only

1

3%

1

3%

Indirect only

9

0%

3

0%

Both

1

13%

0

0%

Total

11

16%

4

4%

a. The number of entities with cost-to-revenue impact of at least three percent is a

subset of the number of entities with such ratios exceeding one percent.

b. The percent of all small entities is rounded.





Source: U.S. EPA Analysis, 2023

Table 9-6 presents aggregate revenue and costs for small firms by process type. EPA summed process
type-specific production for all facilities owned by each parent entity and assigned process type at the
firm-level based on the category with the highest production. For small firms with costs under each of the

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9: RFA

regulatory options, EPA summed firm-level revenue (based on the approach to estimating revenue
described in Sections 4.3.1.3 and 9.3.2) and costs. Of the 2,296 small firms EPA identified, 96 would
incur $22.3 million in costs under Option 1 (also reported in Table 9-4). EPA estimated an aggregate
revenue of approximately $180 billion.

Table 9-6: Aggregate Revenue and Costs for Small Firms by Process Type

Option 1



Total # Small Firms

Total # Small Firms

Aggregate Revenue

Aggregate Costs

Process Type3

with Dischargers

with Costs

(millions, 2022$)

(millions, 2022$)

Meat first

372

22

$83,328

$4.5

Meat further

1,799

31

$61,517

1

o

¦uy

Poultry first

55

16

$20,008

$13.6

Poultry further

47

20

$9,363

$3.0

Render

23

7

$6,019

$1.0

Total

2,296

96

$180,235

$22.3

Option 2



Total # Small Firms

Total # Small Firms

Aggregate Revenue

Aggregate Costs

Process Type3

with Dischargers

with Costs

(millions, 2022$)

(millions, 2022$)

Meat first

372

22

$83,328

$32.7

Meat further

1,799

31

$61,517

1

o

¦uy

Poultry first

55

16

$20,008

$41.6

Poultry further

47

20

$9,363

$3.0

Render

23

7

$6,019

$1.0

Total

2,296

96

$180,235

$78.5

Option 3



Total # Small Firms

Total # Small Firms

Aggregate Revenue

Aggregate Costs

Process Type3

with Dischargers

with Costs

(millions, 2022$)

(millions, 2022$)

Meat first

372

54

$97,768

$44.8

Meat further

1,799

149

$151,897

$38.8

Poultry first

55

25

$20,627

$63.1

Poultry further

47

25

$9,521

$11.9

Render

23

9

$6,029

$10.0

Total

2,296

262

$285,841

$168.6

a. Process type assigned to firms based on highest production.

9.7 Minimization of Economic Impacts on Small Entities Consistent with Statutory
Objectives, and Consideration of Alternatives

As described in the introduction to this chapter, the RFA requires federal agencies to consider the impact
of their regulatory actions on small entities and to analyze alternatives that minimize those impacts. As
shown in Table 1-1, EPA defined the regulatory options to exclude the smallest facilities and reduce
impacts on small businesses. In conjunction with the Office of Management and Budget and the Small
Business Administration, EPA convened a Small Business Advocacy Review (SBAR) panel, and EPA
adopted the recommendations of the panel. The SBAR panel was meant to give small businesses an
opportunity to provide input into the rulemaking process to ensure that their unique concerns were
carefully considered. As detailed in this chapter, EPA conducted a SBREFA screening analysis which
demonstrates that none of the considered options are likely to have a significant impact on a substantial
number of small businesses within the MPP industry. Therefore, the rule is presumed not to have a

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RIA for Proposed Meat and Poultry Products ELGs	9: RFA

significant economic impact on a substantial number of small entities, and the EPA certifies that the
proposed rule has no SISNOSE.

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9: RFA

9.8 Uncertainties and Limitations

Despite EPA's use of the best available information and data, the IRFA discussed in this chapter has
sources of uncertainty, including:

•	EPA was unable to identify NAICS codes, revenue, or employment information for some parent
entities and therefore could not determine their small business status. EPA also could not
determine the small business status of entities whose revenue or employment values are between
the minimum and maximum SBA thresholds. While these data gaps limit EPA's ability to fully
characterize impacts on small entities, none of the entities of undetermined size under any
regulatory option were assessed to have costs greater than 1 percent of revenue and therefore the
findings that the analyzed regulatory options are unlikely to have a significant economic impact
or a substantial impact on small entities would hold even if the Agency were to conservatively
assume that all of the entities of undetermined size are small.

•	In cases where EPA estimated entity-level revenue from facility revenue, there is uncertainty
regarding both an entity's small business designation and ratio of costs to revenue, as actual
facility and entity revenue may differ from estimated revenue.

•	EPA's assumptions regarding small business determinations based on USDA establishment size
do not account for firm-specific NAICS codes and SBA thresholds. In addition, the information is
self-reported to USDA and may contain errors. As a result, some firms may be misclassified as
small or large based on this approach. However, EPA considers its assumptions to be reasonable
based on USDA's establishment size definitions and the typical small business thresholds across
relevant industries.

•	As discussed in Chapter 4, the zero-cost pass-through assumption represents a worst-case
scenario from the perspective of the facilities and parent entities. To the extent that some entities
can pass at least some compliance costs downstream to consumers or upstream to farmers, this
analysis overstates the potential impact of the regulatory options on small entities.

•	If EPA could not find ownership data for a facility, the Agency assumed that facility is a single-
facility entity. As a result, the analysis may be underestimating entity-level compliance costs if an
entity classified as a single-facility entity owns multiple facilities, but the ratio of costs to revenue
could be smaller or larger depending on the overall entity revenue.

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10: UMRA

10 Unfunded Mandates Reform Act (UMRA) Analysis

Title II of the Unfunded Mandates Reform Act 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, EPA generally must prepare a written statement, including a cost-benefit
analysis, for proposed and final rules with "Federal mandates" that might result in expenditures by State,
local, and Tribal governments, in the aggregate, or by the private sector, of $100 million (adjusted
annually for inflation) or more in any one year (i.e., about $184 million in 2022 dollars). 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 adopt the least costly,
most cost-effective, or least burdensome alternative that achieves the objectives of the rule." (2 U.S.C.
1535(a)) 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 that
alternative was not adopted. Before EPA establishes any regulatory requirements that might significantly
or uniquely affect small governments, including Tribal governments, it must develop a small government
agency plan, under UMRA section 203. The plan must provide for notifying potentially affected small
governments, enabling officials of affected small governments to have meaningful and timely input in the
development of EPA regulatory proposals with significant intergovernmental mandates, and informing,
educating, and advising small governments on compliance with regulatory requirements.

EPA estimated the compliance costs associated with each of the regulatory options for different categories
of entities. No MPP facilities are owned by government entities, nor do the regulatory options result in
material administrative costs to government entities. The proposed rule therefore does not contain a
federal mandate on the basis of expenditures incurred by State, local, and Tribal governments. The
maximum compliance cost in any given year to the private sector ranges from $1,034 million under
Option 1 to $6,388 million under Option 3 with chlorides. Accordingly, EPA determined that the
proposed rule does contain a federal mandate that may result in expenditures of $ 184 million (in 2022
dollars) or more for the private sector in any one year.

This chapter contains additional information to support the above statements, including information on
compliance and administrative costs, and on impacts to small governments. The annualized costs
presented in this UMRA analysis are calculated using the social cost framework presented in Chapter 3 of
this RIA. Specifically, this analysis uses costs in 2024 stated in 2022 dollars and accounts for costs in the
year they are anticipated to be incurred between 2024 and 2063. The discounted stream of costs is then
annualized over a 40-year period. As discussed in Chapter 11 (Other Administrative Requirements; see
Section 11.6) in this document, this proposed rule would increase the reporting and recordkeeping burden
for the review, oversight, and administration of the rule relative to baseline requirements.

10.1 UMRA Analysis of Impact on Government Entities and the Private Sector

This section reports the compliance costs projected to be incurred by government and private entities.

Table 10-1 summarizes the total annualized costs (at a 3 percent discount rate), maximum one-year costs,
and the year when maximum costs are incurred by government entities and the private sector. EPA

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10: UMRA

estimates the total annualized pre-tax compliance costs for private entities to range from $232 million
under Option 1 to $1,234 million under Option 3 with chlorides.

Table 10-1: Compliance Costs by Sector (in millions, 2022$)

Sector

Total Annualized

Maximum One-

Year of Maximum

Costs (3%)

Year Costs

Costs

Option 1

Government (excl. federal)

$0.2

$0.5

2028

Private

$231.5

$365.2

2049

Option 2

Government (excl. federal)

$0.2

$0.5

2028

Private

$642.5

$2,403.2

2028

Option 3

Government (excl. federal)

$0.4

$0.9

2028

Private

$1,076.7

$4,941.0

2028

Option 1 with chlorides

Government (excl. federal)

n.e.

n.e.

n.e.

Private

$389.2

$879.8

2028

Option 2 with chlorides

Government (excl. federal)

n.e.

n.e.

n.e.

Private

$800.2

$2,930.4

2028

Option 3 with chlorides

Government (excl. federal)

n.e.

n.e.

n.e.

Private

$1,234.4

$5,468.3

2028

n.e. = not estimated







Source: U.S. EPA Analysis, 2023.







10.2 UMRA Analysis Summary

EPA estimates that the private sector would incur expenditures greater than $184 million, in the
aggregate, in any one year. Furthermore, as discussed above, permitted facilities and permitting
authorities are estimated to incur minor additional administrative costs as the result of the regulatory
options.

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11: Other Administrative Requirements

11 Other Administrative Requirements

This chapter presents analyses conducted in support of the regulatory options to address the requirements
of applicable Executive Orders and Acts. These analyses complement EPA's assessment of the
compliance costs, economic impacts, and economic achievability of the proposed rule, and other analyses
done in accordance with the RFA and UMRA, presented in previous chapters.

11.1 Executive Order 12866: Regulatory Planning and Review and Executive Order 14094:
Modernizing Regulatory Review

Under Executive Order (E.O.) 12866 (58 FR 51735, October 4, 1993), as amended by E.O. 13563 (76 FR
3821, January 21, 2011)28 and E.O. 14094 (88 FR 21879, Apr. 11, 2023), EPA must determine whether
the regulatory action is "significant" and therefore subject to review by the Office of Management and
Budget (OMB) and 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 $200 million or more (adjusted every 3 years by the
Administrator of the Office of Information and Regulatory Affairs (OIRA) for changes in gross
domestic product), 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 for which centralized review would meaningfully further the
President's priorities or the principles set forth in this Executive order, as specifically authorized
in a timely manner by the Administrator of OIRA in each case.

Pursuant to the terms of E.O. 12866, as amended by E.O. 14094, EPA determined that the proposed rule
is a "significant regulatory action" because the action is likely to have an annual effect on the economy of
$200 million or more. As such, the action is subject to review by OMB. 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 of the BCA (U.S. Environmental Protection Agency, 2023a).

28	E.O. 13563 was issued on January 18, 2011 and 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. E.O. 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.	

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11: Other Administrative Requirements

11.2 Executive Order 12898: Federal Actions to Address Environmental Justice in Minority
Populations and Low-Income Populations, Executive Order 14008: Tackling the Climate
Crisis at Home and Abroad, and Executive Order 14096: Revitalizing our Nation's
Commitment to Environmental Justice for All

Executive Order 12898 (59 FR 7629 (Feb. 16, 1994)) establishes federal executive policy on
environmental justice. Its main provision directs federal agencies, to the greatest extent practicable and
permitted by law, to make environmental justice part of their mission by identifying and addressing, as
appropriate, disproportionately high and adverse human health or environmental effects of their programs,
policies, and activities on minority populations and low-income populations in the United States.
Executive Order 14008 (86 FR 7619, February 1, 2021) expands on the policy objectives established in
E.0.12898 and directs federal agencies to develop programs, policies, and activities to address the
disproportionately high and adverse human health, environmental, climate-related and other cumulative
impacts on disadvantaged communities, as well as the accompanying economic challenges of such
impacts.

EPA analyzed the distribution of impacts of this proposed regulatory action across all potentially affected
communities and sought input from stakeholders representing communities with potential EJ concerns.
The analysis included a literature search of the effects MPP operations may have on potential population
groups of concern, multiple analyses to identify which communities and populations within tribal areas
may be impacted by MPP facilities, and an assessment of how water quality improvements may be
distributed across population groups. Findings from these analyses are listed below:

•	The relevant literature reviewed in this effort suggests that communities and surrounding
watersheds in close proximity to MPP facilities could be at risk of pollutant exposure via
wastewater piped directly into waterways, sprayed onto land, or sent to a nearby town or county
wastewater treatment plant, even with some level of treatment. The literature suggested that these
communities are frequently located in rural, low-income communities (Pelton, 2018; The
Environmental Integrity Project, 2018; Winders et al., 2021).

•	EPA found that approximately 26 million people live within one mile of an MPP facility, and
communities within this buffer distance have greater proportions of low-income individuals and
individuals identifying as Asian, Black, and/or Hispanic than the national average. EPA also
found that communities living within one mile of the 25-mile downstream path from MPP direct
discharge process wastewater outfalls had a higher proportion of low-income individuals than the
national average.

•	EPA estimated that over 7.5 million people are served by a public water system (PWS) whose
source water is downstream of an MPP direct discharge process wastewater outfall. EPA found
that these communities have greater proportions of low-income individuals and those identifying
as Black individuals than the national average.

•	EPA estimates that around 13 million people live within 50 miles of the downstream path from an
MPP direct discharge process wastewater outfall (representing the population that may be willing
to travel to those waterbodies to fish) and that communities within that distance have greater
proportions of low-income individuals than the national average.

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11: Other Administrative Requirements

•	EPA found that there are 10 unique direct dischargers in the general proximity (within five miles)
of seven unique tribal lands and 135 unique indirect dischargers in the general proximity of 66
unique tribal lands. EPA also found that there are 50 unique MPP direct dischargers whose
downstream flowpath is within 50 miles of 44 unique tribal areas.

•	As a result of these analyses, EPA presented an overview of the rulemaking to the Office of
Environmental Justice and External Civil Rights management team and held a discussion session
with participants of the National Environmental Justice Community Engagement Call in early
2023.

See Chapter 7 of the EA for additional discussion of the EJ analysis (U.S. EPA, 2023b).

11.3	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 action is not subject to E.O. 13045 because the EPA does not believe the environmental health risks
or safety risks addressed by this action present a disproportionate risk to children.

11.4	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.

EPA has concluded that this action will not have federalism implications. No MPP facilities are owned by
government entities. As discussed in earlier chapters of this document, EPA anticipates that the proposed
rule will impose only a minor incremental administrative burden on States from issuing, reviewing, and
overseeing compliance with discharge requirements.

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11: Other Administrative Requirements

EPA estimated the compliance costs associated with each of the regulatory options for different categories
of entities. The maximum compliance cost in any given year to government entities is $0.5 million under
Options 1 and 2, and $0.9 million under Option 3. The maximum compliance cost in any given year to the
private sector ranges from $365.2 million under Option 1 to $5,468.3 million under Option 3 with
chlorides (see Chapter 9, Unfunded Mandates Reform Act (UMRA), for details).

11.5 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."

EPA assessed potential tribal implications for the regulatory options arising from three main changes, as
described below: (1) direct compliance costs incurred by MPP facilities; (2) impacts on drinking water
systems downstream from MPP dischargers; and (3) administrative burden on governments that
implement the NPDES program.

•	Direct compliance costs: EPA's analyses show that no MPP facility estimated to be affected by
the regulatory options is owned by tribal governments.

•	Impacts on drinking water systems: Building from the drinking water service are analysis
described in Section 7.4 of the Environmental Assessment, EPA determined that none of the
impacted drinking water systems are located on tribal land or operated by a tribe.

•	Administrative burden: No tribal governments are currently authorized pursuant to section 402(b)
of the CWA to implement the NPDES program.

Due to the above findings, EPA determined that EO 13175 does not apply to this rulemaking. However,
consistent with EPA Policy on Consultation and Coordination with Indian Tribes, EPA consulted with
tribal officials during the development of this action.

Before initiating outreach, EPA conducted a proximity analysis to determine potential impacts MPP
facilities and their wastewater discharge may have to tribes or tribal lands. First, EPA screened a five-mile
buffer zone around each direct discharging MPP facility. Over with these buffers and EJSCREEN tribal
datasets, which include including National Land Area Representation, American Indian Alaska Native,
and Tribal Statistical Areas, was determined. Through this analysis, EPA identified 145 MPP facilities in
the general proximity of 73 unique tribal lands.29 Second, to identify potential surface waters that may be
used or valued by tribes that are impacted by MPP wastewater discharge, the overlap between 50-mile
buffers30 around 25-mile flow paths downstream of MPP process wastewater outfalls and EJSCREEN

29

30

Within a five mile distance of

The 50-mile buffer distance is based on observations of fishers' behavior and practices have made similar observations
in terms travel distance ("e.g., Sohngen et al., 2015 and Sea Grant - Illinois-Indiana, 2018).	

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11: Other Administrative Requirements

tribal area datasets were determined. This analysis resulted in 46 unique tribal areas identified as having
overlap with these buffer zones.

EPA initiated consultation and coordination with federally recognized tribal governments in January
2023. EPA shared information about the Meat and Poultry Products effluent guidelines rulemaking (MPP
ELG) with all federally recognized tribes by sending a letter and detailed plan describing the rulemaking
(available in the docket), the potential impact to tribes, and opportunities for tribal involvement. Tribes
identified as being in close proximity to either 10 or more MPP facilities or a waterbody potentially
impacted by MPP wastewater discharge, were notified of these screening results in the letter they were
sent to promote awareness.31

EPA continued this government-to-government dialogue by hosting two identical listening sessions as
webinars on February 6 and 13, 2023, attended by ten and seven tribal representatives, respectively.

Tribal representatives were invited to participate in further discussions about the rulemaking process and
objectives, with a focus on identifying specific ways the rulemaking may affect tribes.

The consultation process ended on March 10, 2023. No tribal governments requested direct government-
to-government consultations, and EPA has not received written comments from any tribes to date.

11.6 Paperwork Reduction Act of 1995

The Paperwork Reduction Act of 1995 (PRA) (superseding the PRA of 1980) is implemented by 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.

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.

The statistics reported in these letters have since been updated to reflect the most current MPP facility location
information and therefore are not aligned with the data presented in this analysis.

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11: Other Administrative Requirements

Agencies must provide information to OMB on the parties affected, the annual reporting burden, 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.

EPA is proposing new reporting and recordkeeping requirements under 40 CFR Part 432.32 The proposed
rule would require:

•	Certain MPP facilities to control for additional pollutants, resulting in new burden for completion
of a compliance monitoring program (i.e., burden to collect and ship samples, review and report
pollutant data monthly, and develop compliance reports).

•	Control authorities to establish monitoring requirements and review pollutant data submitted by
MPP facilities.

•	EPA to review pollutant data submitted by MPP facilities.

Table 11-1 Facilities will incur additional O&M costs through sampling materials, sample preservation,
shipping, and sample analysis costs. Under the preferred option (Option 1), the estimated total annual
O&M costs are $1,338,087. There are no capital costs associated with any of the monitoring or reporting.
For additional discussion of this estimated burden, see the Information Collection Request Supporting
Statement (U.S Environmental Protection Agency, 2023).

11.7 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 the OMB, explanations when the Agency decides not to use
available and applicable voluntary consensus standards.

The regulatory options do not involve technical standards, for example in the measurement of pollutant
loads. Nothing in the regulatory options would prevent the use of voluntary consensus standards for such
measurement where available, and EPA encourages permitting authorities and regulated entities to do so.
Therefore, EPA did not include any voluntary consensus standards in the proposed rule.

OMB has assigned control number 2040-0306 to this information collection request (ICR number 2701.02).

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ERS https://www.ers.usda.gov/publications/pub-details/?pubid=37607
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Holt, M. T., & Johnson, S. R. (1988). Supply Dynamics in the U.S. Hog Industry. Canadian Journal of
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Futures Prices in Estimating the Price Elasticities. Retrieved from

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Knight, R., Hahn, W., Taylor, H., Teran, A., Haley, M., Grossen, G., & Valcu-Lisman, A. (2023).
Livestock, Dairy, and Poultry Outlook: April 2023. from USDA ERS
https://www.ers.usda.gov/publications/pub-details/?pubid=106355
Lee, J. Y., Qian, Y., Gustavsen, G. W., Nayga Jr, R. M., & Rickertsen, K. (2020). Effects of consumer
cohorts and age on meat expenditures in the United States. Agricultural Economics, 57(4), 505-
517. doi:https://doi.org/10.1111/agec. 12568
MacDonald, J. M., Hoppe, R. A., & Newton, D. (2018). Three decades of consolidation in US
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details/?pubid=88056#:~:text=Crop%20production%20has%20seen%20a.the%20associated%20c
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American journal of agricultural economics, 82(2), 334-346.

MacDonald, J. M., Ollinger, M. E., Nelson, K. E., & Handy, C. R. (2000). Consolidation in US

meatpacking. Retrieved from https://www.ers.usda.gov/publications/pub-details/?pubid=41120
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journal of agricultural economics, 76(3), 444-453. doi:https://doi.org/10.2307/1243656
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12: References

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A Review. Food Science of Animal Resources, 42(5), 762.

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Yang, R., Raper, K. C., & Pruitt, J. R. (2019). The influence of recession and income strata on consumer
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doi: 10.1080/00036846.2019.1593940

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Appendix A: Costs at 7 Percent

Appendix A. Proposed Rule Costs at 7 Percent Discount Rate

Table 12-1 and Table 12-2 present the total social costs of the proposed rule, discounted at 7 percent, by
regulatory option and discharge type.

Table 12-1: Estimated Total Social Costs by Regulatory Option and Discharge
Type (in millions, 2022$, at 2025)

Regulatory Option

7 percent discount rate

Direct

Indirect

Total

Option 1

$211.7

$15.3

$227.0

Option 2

$211.7

$420.0

$631.7

Option 3

$218.7

$848.9

$1,067.5

Option 1 with chlorides

$273.7

$107.9

$381.7

Option 2 with chlorides

$273.7

$512.7

$786.4

Option 3 with chlorides

$280.7

$941.5

$1,222.2

Source: U.S. EPA Analysis, 2023.

Table 12-2: Time Profile of Costs to Society (in millions, 2022$)

Year

Option 1

Option 2

Option 3

Option 1 with
chlorides

Option 2 with
chlorides

Option 3 with
chlorides

2025

$0.0

$0.0

$0.0

$0.0

$0.0

$0.0

2026

$191.9

$191.9

$198.1

$251.1

$251.1

$257.3

2027

$229.7

$229.7

$237.2

$300.2

$300.2

$307.7

2028

$353.1

$2,403.8

$4,942.3

$880.4

$2,931.1

$5,469.5

2029

$321.7

$682.8

$1,043.3

$499.6

$860.7

$1,221.2

2030

$361.3

$722.4

$1,084.2

$550.4

$911.5

$1,273.4

2031

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2032

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2033

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2034

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2035

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2036

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2037

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2038

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2039

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2040

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2041

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2042

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2043

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2044

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2045

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2046

$316.1

$677.2

$1,037.6

$490.9

$852.0

$1,212.3

2047

$316.1

$677.2

$1,037.6

$490.9

$852.0

$1,212.3

2048

$316.1

$677.2

$1,037.6

$490.9

$852.0

$1,212.3

2049

$365.6

$1,909.4

$3,795.0

$792.8

$2,336.6

$4,222.2

2050

$316.1

$677.2

$1,037.6

$490.9

$852.0

$1,212.3

2051

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2052

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2053

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

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Appendix A: Costs at 7 Percent

Table 12-2: Time Profile of Costs to Society (in millions, 2022$)

Year

Option 1

Option 2

Option 3

Option 1 with
chlorides

Option 2 with
chlorides

Option 3 with
chlorides

2054

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2055

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2056

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2057

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2058

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2059

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2060

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2061

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2062

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2063

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2064

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

2065

$210.7

$571.8

$928.8

$351.9

$713.0

$1,070.0

PV, 7%

$3,025.8

$8,421.7

$14,232.1

$5,088.3

$10,484.2

$16,294.6

Annualized













costs, 7%

$227.0

$631.7

$1,067.5

$381.7

$786.4

$1,222.2

Source: U.S. EPA Analysis, 2023.

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