United States Office of Water EPA-821-B-00-008
Environmental Protection (4303) December 2000
Agency
& EPA Economic, Environmental,
and Benefits Analysis of the
Proposed Metal Products
and Machinery Rule
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Economic, Environmental, and Benefits Analysis
of the Proposed
Metal Products and Machinery Rule
U.S. Environmental Protection Agency
Office of Science and Technology
Engineering and Analysis Division
Washington, DC 20460
December 2000
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This document was prepared by the Office of Water staff. Abt Associates provided assistance and support in performing the
underlying analysis supporting the conclusions detailed in this report.
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MP&M EEBA Table of Contents
Table of Contents
EXECUTIVE SUMMARY
ES. 1 Overview of the MP&M Industry and its Effluent Discharges ES-1
ES.2 Description of the Proposed Rule ES-3
ES.3 Economic Impacts and Social Costs of the Proposed Rule ES-5
ES.3.1 Economic Impacts ES-5
ES.3.2 Social Costs ES-12
ES.4 Benefits of the Proposed Rule ES-13
ES.4.1 Reduced Human Health Risk ES-15
ES.4.2 Ecological, Recreational, and Nonuser Benefits ES-18
ES.4.3 Reduced POTW Impacts ES-19
ES.4.4 Total Estimated Benefits of the Proposed MP&M Rule ES-20
ES.5 Comparing Estimated Costs and Benefits ES-20
ES.6 Ohio Case Study ES-22
ES.6.1 Benefits ES-22
ES.6.2 Social Costs ES-24
ES.6.3 Comparing Monetized Benefits and Costs ES-25
PART I: INTRODUCTION AND BACKSROUN& INFORMATION
Chapter 1: Introduction
1.1 Purpose 1-1
1.2 Organization 1-1
1.3 Readers' Aids 1-2
Chapter 2: The MP&M Industry and the Need for Regulation
2.1 Overview of the Facilities Potentially Subject to Regulation 2-1
2.2 MP&M Discharges and the Need For Regulation 2-2
2.2.1 Baseline MP&M Discharges 2-3
2.2.2 Discharges under the MP&M Regulation 2-5
2.3 Addressing Market Imperfections 2-6
2.4 Achieving a More Complete and Coherent Regulatory Framework for the Metals Industries 2-7
2.5 Meeting Legislative and Litigation-Based Requirements 2-10
Glossary 2-12
Acronyms 2-14
Chapter 3: Profile of the MP&M Industries
3.1 Data Sources 3-1
3.2 Overview of the MP&M Industry and Industry Trends 3-2
3.2.1 Aerospace 3-5
3.2.2 Aircraft 3-6
3.2.3 Electronic Equipment 3-6
3.2.4 Hardware 3-6
3.2.5 Household Equipment 3-7
3.2.6 Instruments 3-7
3.2.7 Iron and Steel 3-7
3.2.8 Job Shops 3-8
3.2.9 Motor Vehicle and Bus & Truck 3-8
3.2.10 Mobile Industrial Equipment 3-8
3.2.11 Office Machine 3-8
3.2.12 Precious Metals and Jewelry 3-9
3.2.13 Printed Wiring Boards 3-9
3.2.14 Railroad 3-9
3.2.15 Ships and Boats 3-9
3.2.16 Stationary Industrial Equipment 3-10
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MP&M EEBA Table of Contents
3.3 Characteristics of MP&M Manufacturing Sectors 3-10
3.3.1 Domestic Production 3-11
3.3.2 Industry Structure and Competitiveness 3-16
3.3.3 Financial Condition and Performance 3-19
3.4 Characteristics of MP&M Non-Manufacturing Sectors 3-20
3.4.1 Domestic Production 3-20
3.4.2 Industry Structure and Competitiveness 3-22
3.5 Characteristics of Potentially-Regulated MP&M Facilities 3-24
Glossary 3-28
Acronyms 3-30
References 3-31
Chapter 4: Regulatory Options
4.1 Subcategorization 4-1
4.2 Technology Options 4-2
4.3 BPT/BAT Options for Direct Dischargers 4-3
4.4 PSES Options for Indirect Dischargers 4-4
4.5 NSPS and PSNS Options for New Sources 4-4
4.6 Summary of the Proposed Rule and Regulatory Alternatives 4-5
Glossary 4-6
Acronyms 4-7
PART II: COSTS AN& ECONOMIC IMPACTS
Chapter 5: Facility Impact Analysis
5.1. Data Sources 5-2
5.2 Methodology 5-2
5.2.1 Converting Engineering Compliance Costs and Financial Data 5-3
5.2.2 Market-Level Impacts and Cost Pass-through Analysis 5-4
5.2.3 Impact Measures for Private Facilities 5-4
5.2.4 Impact Measures for Railroad Line Maintenance Facilities 5-8
5.2.5 Impact Measures for Government-Owned Facilities 5-8
5.3 Results 5-10
5.3.1 Baseline Closures 5-10
5.3.2 Price Increases 5-11
5.3.3 Overview of Impacts 5-12
5.3.4 Results for Indirect Dischargers 5-13
5.3.5 Results for Direct Dischargers 5-14
5.3.6 Results for Private Facilities 5-15
5.3.7 Results for Government- Owned Facilities 5-16
5.3.8 Results by Subcategory 5-18
Glossary 5-20
Acronyms 5-21
References 5-22
Chapter 6: Employment Effects
6.1 Job Losses Due to Closures 6-2
6.2 Job Gains Due to Compliance Requirements 6-2
6.2.1 Direct Labor Requirements 6-2
6.2.2 Indirect and Induced Labor Requirements 6-4
6.3 Net Effects on Employment 6-5
Glossary 6-7
Acronym 6-8
References 6-9
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MP&M EEBA Table of Contents
Chapter 7: Government and Community Impact Analysis
7.1 Impacts on Governments 7-1
7.1.1 Impacts on Governments that Operate MP&M Facilities 7-1
7.1.2 Government Administrative Costs 7-1
7.2 Community Impacts of Facility Closures 7-5
Glossary 7-7
Acronyms 7-8
Chapter 8: Foreign Trade Impacts
8.1 Data Sources 8-1
8.2 Methodology 8-2
8.3 Results 8-2
References 8-4
Chapter 9: Firm Level, New Source and Industry Impacts
9.1 Firm Impacts 9-1
9.1.1 Sources 9-1
9.1.2 Methodology 9-1
9.1.3 Results 9-2
9.2 New Source Impacts 9-3
9.2.1 Methodology 9-3
9.2.2 Results 9-4
9.3 Industry Impacts 9-5
Glossary 9-6
Acronyms 9-7
References 9-7
Chapter 10: Regulatory Flexibility Analysis/SBREFA
10.1 Defining Small Entities 10-2
10.2 Methodology 10-3
10.3 Results 10-3
10.3.1 Number of Affected Small Entities 10-3
10.3.2 Impacts on Facilities Owned by Small Entities 10-4
10.3.3 Impacts on Small Firms 10-6
10.4 Detailed Analysis of the Two Subcategories with Most of the Impacts 10-6
10.4.1 Severe and Moderate Impacts in the Metal Finishing Job Shops Subcategory 10-7
10.4.2 Moderate Impacts in the Printed Wiring Board Subcategory 10-8
10.5 Consideration of Small Entity Impacts in the Selection of the Proposed Rule 10-9
Glossary 10-12
Acronyms 10-13
References 10-14
Chapter 11: Social Costs
11.1 Components of Social Costs 11-1
11.2 Resource Costs of Compliance 11-2
11.3 POTW Administration Costs 11-2
11.4 Social Costs of Unemployment 11-3
11.4.1 Social Cost of Worker Dislocation 11-3
11.4.2 Cost of Administering Unemployment 11-4
11.4.3 Total Cost of Unemployment 11-5
11.5 Total Social Costs 11-5
Glossary 11-6
References 11-7
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MP&M EEBA Table of Contents
PART III: BENEFITS
Chapter 12: Benefit Overview
12.1 MP&M Pollutants 12-1
12.1.1 Characteristics of MP&M Pollutants 12-2
12.1.2 Effects of MP&M Pollutants on Human Health 12-2
12.1.3 Environmental Effects of MP&M Pollutants 12-6
12.1.4 Effects of MP&M Pollutants on Economic Productivity 12-7
12.2 Linking the Regulation to Beneficial Outcomes 12-8
12.3 Qualitative and Quantitative Benefits Assessment 12-9
12.3.1 Overview of Benefit Categories 12-10
12.3.2 Human Health Benefits 12-12
12.3.3 Ecological Benefits 12-12
12.3.4 Economic Productivity Benefits 12-13
12.3.5 Methods for Valuing Benefit Events 12-13
Glossary 12-15
Acronyms 12-18
References 12-19
Chapter 13: Human Health Benefits
13.1 Methodology & Data Sources 13-2
13.1.1 Cancer from Fish Consumption 13-3
13.1.2 Cancer from Drinking Water Consumption 13-6
13.1.3 Exposures Above Systemic Health Thresholds 13-8
13.1.4 Human Health AWQC 13-11
13.2 Results 13-14
13.2.1 Fish Consumption Cancer Results 13-14
13.2.2 Drinking Water Consumption Cancer Results 13-16
13.2.3 Systemic Health Threshold Results 13-16
13.2.4 Human Health AWQC Results 13-17
13.3 Limitations and Uncertainties 13-17
13.3.1 Sample Design & Analysis of Benefits by Location of Occurrence 13-17
13.3.2 In-Waterway Concentrations of MP&M Pollutants 13-18
13.3.3 Joint Effects of Pollutants 13-18
13.3.4 Background Concentrations of MP&M Pollutants 13-18
13.3.5 Downstream Effects 13-19
13.3.6 Exposed Fishing Population 13-19
13.3.7 Cancer Latency & Human Health 13-19
Glossary 13-21
Acronyms 13-22
References 13-23
Chapter 14: Lead-Related Benefits
14.1 Overview of Lead-Related Health Effects 14-2
14.1.1 Children Under Age One 14-3
14.1.2 Children Between The Ages of One and Six 14-3
14.1.3 Adults 14-3
14.2 Children Health Benefits 14-4
4.2.1 PbB Distribution of Exposed Children 14-6
14.2.2 Relationship Between PbB Levels and IQ 14-8
14.2.3 Value of Children's Intelligence 14-8
14.2.4 Value of Additional Educational Resources 14-10
14.2.5 Changes in Neonatal Mortality 14-12
14.3 Adult Health Benefits 14-12
14.3.1 Estimating Changes in Adult PbB Distribution Levels 14-15
14.3.2 Men Health Benefits 14-17
14.3.3 Women Health Benefits 14-21
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14.4 Lead-Related Benefit Results 14-23
14.4.1 Preschool Age Children Lead-Related Benefit Results 14-23
14.4.2 Adult Lead-Related Benefit Results 14-24
14.5 Limitations and Uncertainties 14-25
14.5.1 Excluding Older Children 14-25
14.5.2 Compensatory Education Costs 14-26
14.5.3 Dose-Response Relationships 14-26
14.5.4 Absorption Function for Ingested Lead in Fish Tissue 14-26
14.5.5 Economic Valuation 14-26
Glossary 14-28
Acronyms 14-31
References 14-32
Chapter 15: Recreational Benefits
15.1 Improvements from MP&M Regulation 15-2
15.1.1 Ecological Improvements 15-2
15.1.2 Quantification of Ecological Improvements 15-3
15.1.3 AWQC Exceedances for Human Health 15-3
15.1.4 Benefiting Reaches 15-3
15.1.5 Geographic Characteristics of Benefiting Reaches 15-5
15.1.6 Extrapolating Sample-based Results to the National Level 15-5
15.2 Valuing Economic Recreational Benefits 15-5
15.2.1 Transferring Values from Surface Water Valuation Studies 15-5
15.2.2 Recreational Fishing 15-8
15.2.3 Wildlife Viewing 15-11
15.2.4 Recreational Boating 15-14
15.2.5 Nonuse Benefits 15-16
15.3 Summary of Recreational Benefits 15-16
15.4 Limitations and Uncertainties Associated with Estimating Recreational Benefits 15-17
Glossary 15-21
Acronyms 15-22
References 15-23
Chapter 16: POTW Benefits
16.1 Reduced Interference with POTW Operations 16-2
16.2 Assessing Benefits from Reduced Sludge Contamination 16-2
16.2.1 Data Sources 16-2
16.2.2 Sludge Generation, Treatment, and Disposal Practices 16-3
16.2.3 Overview of Improved Sludge Quality Benefits 16-6
16.2.4 Sludge Use/Disposal Costs and Practices 16-7
16.2.5 Quantifying Sludge Benefits 16-9
16.3 Estimated Savings in Sludge Use/Disposal Costs 16-13
16.4 Methodology Limitations 16-14
Glossary 16-16
Acronyms 16-17
References 16-18
Chapter 17: Environmental Justice Analysis and Protection of Children
17.1 Environmental Justice 17-1
17.1.1 Changes in Health Risk for Subsistence Anglers 17-1
17.1.2 Demographic Characteristics of Populations Living in the Counties Near MP&M Facilities 17-3
17.2 Protection of Children from Environmental Health And Safety Risks 17-8
Glossary 17-10
Reference 17-11
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MP&M EEBA Table of Contents
PART IV: COMPARISON OF COSTS AND BENEFITS
Chapter 18: MP&M Benefit/Cost Comparison
18.1 Social Costs 18-1
18.2 Benefits 18-1
18.3 Comparing Monetized Benefits and Costs 18-2
18.4 Comparing Monetized Benefits and Costs at the Sample Facility Level 18-2
Chapter 19: Social Costs and Benefits of Regulatory Alternatives
19.1 Estimated Social Costs 19-1
19.1.1 Compliance Costs for MP&M Facilities 19-1
19.1.2 Government Administrative Costs 19-2
19.1.3 Cost of Unemployment 19-3
19.1.4 Total Social Costs 19-4
19.2 Estimated Benefits 19-5
19.2.1 Human Health Benefits 19-5
19.2.2 Recreational Benefits 19-5
19.2.3 Avoided Sewage Sludge Disposal or Use Costs 19-6
19.2.4 Total Monetized Benefits 19-6
19.3 Comparison of Estimated Benefits and Costs 19-6
Glossary 19-8
Acronym 19-9
PART V: OHIO CASE STUDY
Chapter 20: Baseline Conditions in Ohio
20.1 Overview of Ohio's Geography, Population, and Economy 20-2
20.2 Profile of MP&M Facilities in Ohio 20-3
20.3 Ohio's Water Resources 20-4
20.3.1 Aquatic Life Use 20-6
20.3.2 Water Recreation In Ohio 20-8
20.3.3 Commercial Fishing in Ohio 20-9
20.3.4 Surface Water Withdrawals 20-9
20.4 Surface Water Quality in Ohio 20-10
20.4.1 Use Attainment in Streams and Rivers in Ohio 20-10
20.4.2 Lake Erie and Other Lakes Use Attainment 20-10
20.4.3 Causes and Sources of Use Non-Attainment in Ohio 20-11
20.5 Effects of Water Quality Impairments on Water Resource Services 20-12
20.5.1 Effect of Water Quality Impairment on Life Support for Animals and Plants 20-12
20.5.2 Effect of Water Quality Impairment on Recreational Services 20-13
20.6 Presence and Distribution of Endangered and Threatened Species in Ohio 20-15
20.6.1 E&T Fish 20-15
20.6.2 E&T Mollusks 20-15
20.6.3 Other Aquatic E&T Species 20-16
Glossary 20-19
Acronyms 20-22
References 20-23
Chapter 21: Modeling Recreational Benefits in Ohio with a RUM Model
21.1 Methodology 21-2
21.1.1 Overview 21-2
21.1.2 Modeling the Site Choice Decision 21-3
21.1.3 Modeling Trip Participation 21-4
21.1.4 Calculating Welfare Changes from Water Quality Improvements 21-7
21.1.5 Extrapolating Results to the State Level 1 -7
21.2 Data 21-8
21.2.1 The Ohio Data 21-8
21.2.2 Estimating the Price of Visits to Sites 21-11
21.2.3 Site Characteristics 21-11
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21.3 Site Choice Model Estimates 21-13
21.3.1 Fishing Model 21-14
21.3.2 Boating Model 21-14
21.3.3 Swimming Model 21-15
21.3.4 Viewing (Near-water Activity) Model 21-15
21.4 Trip Participation Model 21-15
21.5 Estimating Benefits from Reduced MP&M Discharges in Ohio 21-18
21.5.1 Benefiting Reaches in Ohio 21-18
21.5.2 Estimating Recreational Benefits in Ohio 21-18
21.6 Limitations and Uncertainty 21-20
21.6.1 One-State Approach 21-20
21.6.2 Including One-Day Trips Only 21-20
21.6.3 Considering Only Recreational Values 21-20
21.6.4 Potential Sources of Survey Bias 21-20
21.6.5 Using IWB2 to Predict Recreational Behavior 21-21
Glossary 21-22
Acronyms 21-24
References 21-25
Chapter 22: MP&M Benefit-Cost Analysis in Ohio
22.1 Benefits of the Proposed Regulation 22-1
22.1.1 Human Health Benefits (Other than Lead) 22-2
22.1.2 Lead-Related Benefits 22-2
22.1.3 Economic Productivity Benefits 22-3
22.1.4 Total Monetized Benefits 22-3
22.2 Social Costs of Proposed Regulation 22-4
22.2.1 Baseline and Post-Compliance Closures 22-4
22.2.2 Compliance Costs for MP&M Facilities 22-5
22.2.3 Government Administrative Costs 22-5
22.2.4 Costs of Unemployment in Ohio 22-6
22.2.5 Total Social Costs 22-7
22.3 Comparison of Monetized Benefits and Costs 22-7
Glossary 22-8
Acronyms 22-9
APPENDICES
Appendix A: Detailed Economic Impact Analysis Information
A.I MP&M SIC and NAICS Codes A-l
A.2 Annual Establishment "Births" and "Deaths" in MP&M Industries A-30
A.3 Description of MP&M Surveys A-33
A.3.1 Screener Surveys A-33
A.3.2 Ohio Screener Surveys A-33
A.3.3 Detailed MP&M Industry Surveys A-33
A.3.4 Iron and Steel Survey A-33
A.3.5 Municipality Survey A-33
A.3.6 Federal Facility Survey A-34
A.3.7 POTW Survey A-34
References A-35
Appendix B: MP&M Sector Cost Pass-Through Potential
B.I Historical Changes in Output Prices Relative to Changes in Input Costs B-l
B.2 Market Structure Effects B-4
B.3 Combining the Measures of Pass-Through Potential B-7
B.4 Adjusting the Composite Estimate of Pass-Through Potential for Share of Output Bearing Compliance Costs . . B-8
B.5 Using the Estimated Cost Pass-Through Potential in the Facility-Level Financial Analysis B-10
Glossary B-ll
Acronyms B-12
References B-13
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MP&M EEBA Table of Contents
Appendix C: POTW Administrative Costs
C. 1 Effluent Guidelines Permitting Requirements C-l
C.I.I NPDES Basic Industrial Permit Program C-l
C. 1.2 Pretreatment Program C-2
C.2 Methodology C-2
C.2.1 Data Sources C-2
C.2.2 Overview of Methodology C-2
C.3 Unit Costs of Permitting Activities C-3
C.3.1 Permit Application and Issuance C-3
C.3.2 Inspection C-6
C.3.3 Monitoring C-6
C.3.4 Enforcement C-8
C.3.5 Repermitting C-8
C.4 POTW Administrative Costs by Option C-8
Appendix C Exhibits C-10
Appendix D: Baseline and Post-Compliance Pollutant Loads
Table D.I: Baseline Toxic-Weighted Discharges by Type of Pollutant for Facilities
Regulated under the Proposed Rule: Direct Dischargers (Pounds Equivalent) D.2
Table D.2: Post-Compliance Toxic-Weighted Discharges by Type of Pollutant: Proposed Rule Direct Dischargers
(Pounds Equivalent) D.3
Table D.3: Baseline Pollutant Discharges by Type of Pollutant for Facilities Regulated under the Proposed Rule:
Direct Dischargers (Pounds) D.4
Table D.4: Post-Compliance Pollutant Discharges by Type of Pollutant: Proposed Rule Direct Dischargers (Poundsฎ.5
Table D.5: Baseline Toxic-Weighted Discharges by Type of Pollutant for Facilities Regulated under the Proposed
Rule Indirect Dischargers (Pounds Equivalent) D.6
Table D.6: Post-Compliance Toxic-Weighted Discharges by Type of Pollutant: Proposed Rule Inirect Dischargers
(Pounds Equivalent) D.7
Table D.7: Baseline Pollutant Discharges by Type of Pollutant for Facilities Regulated under the Proposed Rule
Indirect Dischargers (Pounds) D.8
Table D.8: Post-Compliance Pollutant Discharges by Type of Pollutant: Proposed Rule Indirect Dischargers (Pound3)9
Appendix E: Environmental Assessment
E.I. MP&M Pollutant Characteristics E-4
E.I.I Identifying MP&M Pollutants E-4
E.I.2 Physical-Chemical Characteristics and Toxicity Data of MP&M Pollutants E-9
E.I.3 Grouping MP&M Pollutants Based on Risk to Aquatic Receptors E-21
E.I.4 Assumptions and Limitations E-22
E.2. Methodology E-22
E.2.1 Sample Set Data Analysis and National Extrapolation E-22
E.2.2 Water Quality Modeling E-22
E.2.3 Impact of Indirect Discharging Facilities on POTW Operations E-24
E.2.4 Assumptions and Limitations E-25
E.3 Data Sources E-26
E.3.1 Facility-Specific Data E-26
E.3.2 Waterbody-Specific Data E-26
E.3.3 Information Used to Evaluate POTW Operations E-27
E.4 Results E-31
E.4.1 Human Health Impacts E-31
E.4.2 Aquatic Life Effects E-33
E.4.3 POTW Effects E-34
Glossary E-37
Acronyms E-40
References E-41
Appendix F: Differential Sample Weighting Technique
F. 1 Methodology for Developing Sample-Weighted Estimates for Sites with more than One MP&M Facility F-l
Glossary F-8
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Appendix &'- Fate and Transport Model for DW and Ohio Analyses
G. 1 Model Equations G-l
G.2 Model Assumptions G-3
G. 2.1 Steady Flow Conditions Exist Within
the Stream or River Reach G-3
G.2.2 Longitudinal Dispersion of the Pollutant Is Negligible G-3
G.2.3 Flow Geometry, Suspension of Solids, and Reaction Rates Are Constant Within a River Reach G-3
G.3 Hydrologic Linkages G-3
G.4 Associating Risk with Exposed Populations G-3
G.5 Data Sources G-4
G.5.1 Pollutant Loading Data Used in the Drinking Water Risk Analysis G-4
G.5.2 Pollutant Loading Data Used in the Ohio Case Study Analysis G-4
Glossary G-6
Acronyms G-7
Appendix H: Special Distribution of Benefiting Reaches, MP&M Facilities, and
Benefiting Populations
Figure H.I: Location of Benefiting Reaches in Relation to Sample MP&M Facilities by County and
Population Reaches Benefiting from MP&M Regulation (EPA Regions I, II, and III) H-3
Figure H.2: Location of Benefiting Reaches in Relation to Sample MP&M Facilities by County and
Population Reaches Benefiting from MP&M Regulation (EPA Region IV) H-4
Figure H.3: Location of Benefiting Reaches in Relation to Sample MP&M Facilities by County and
Population Reaches Benefiting from MP&M Regulation (EPA Region V and VII) H-5
Figure H.4: Location of Benefiting Reaches in Relation to Sample MP&M Facilities by County and
Population Reaches Benefiting from MP&M Regulation (EPA Region VI) H-6
Figure H.5: Location of Benefiting Reaches in Relation to Sample MP&M Facilities by County and
Population Reaches Benefiting from MP&M Regulation (EPA Regions VIII and X) H-7
Figure H.6: Location of Benefiting Reaches in Relation to Sample MP&M Facilities by County and
Population Reaches Benefiting from MP&M Regulation (EPA Region IX) H-8
Table H.I: Distribution of MP&M Facilities and Participants of Water Based Recreation by State H-9
Figure H.7: Cumulative Distribution of Facilities and Participants H-l 1
Appendix I: Selecting WTP Values for Benefits Transfer
1.1 Desvousges et al., 1987. Option Price Estimates for Water Quality Improvements: A Contingent Valuation Study
for the Monongahela River
-6
-6
.7 Phaneuf etal., 1998. "Valuing Water Quality Improvements Using Revealed Preference Methods When Corner
Solutions are Present" 1-8
Glossary 1-10
Acronyms 1-11
References 1-12
.2 Farber and Griner, 2000. Valuing Watershed Quality Improvements Using Conjoint Analysis
.3 Jakus et al., 1997. Do Sportfish Consumption advisories Affect Reservoir Anglers' Site Choice?
.4 Lant and Roberts, 1990. Greenbelts in the Cornbelt: Riparian Wetlands, Intrinsic Values, and Market Failure .
.5 Audrey Lyke, 1993. Discrete Choice Models to Value Changes in Environmental Quality: A Great Lakes Case
Study
.6 Montgomery and Needelman, 1997. The Welfare Effects of Toxic Contamination in Freshwater Fish
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MP&M EEBA
Executive Summary
executive Summary
INTRODUCTION
EPA is proposing effluent limitations guidelines and
standards for the Metal Products and Machinery (MP&M)
industry. This document presents EPA's economic and
environmental analyses supporting the proposed rule. The
Executive Summary provides an overview of the costs and
benefits of the regulation.
Overall, EPA finds that the proposed rule provides
significant benefits that are likely to outweigh the social
costs of the rule. Moreover, the rule has modest economic
impacts. The Agency is continuing to develop and refine its
methodologies for estimating the benefits of improved water
quality resulting from effluent guidelines, and has used new
approaches in some cases in the benefits analyses presented
in these reports. EPA recognizes that estimates of both
costs and benefits are uncertain, and therefore conducted a
number of checks on the reasonableness of the analysis
results. In particular, EPA undertook the Ohio case study to
perform more detailed and complete benefits analyses than
were feasible for the nation as a whole. The Agency is
seeking comment on the methodologies and results of both
the national analyses and the Ohio case study. Additional
information on issues associated with extrapolation of the
benefit results can be found in Section E.4.
Detailed descriptions of the analytic methodologies and
results are presented in the Economic, Environmental, and
Benefit Assessment (EEBA). In addition, the EEBA
presents costs, benefits, and economic impacts for
alternatives to the proposed rule that were considered by
EPA.
ES. 1 OVERVIEW OF THE MP&M
INDUSTRY AND ITS EFFLUENT
DISCHARGES
The proposed regulation will apply to process wastewater
discharges from MP&M facilities performing
manufacturing, rebuilding, or maintenance on a metal part,
product, or machine using an MP&M operation and
discharging process wastewater either directly or indirectly
to surface waters. These potentially-regulated MP&M
facilities represent only a portion of all facilities in the
relevant industrial sectors, since some facilities do not
generate or discharge process wastewater.
EXECUTIVE SUMMARY CONTENTS:
ES.l
ES.2
ES.3
ES.4
ES,
ES,
4
ES,
ES,
ES,
ES,
ES.5
ES.6
ES
ES
ES
Overview of the MP&M Industry and its
Effluent Discharges
Description of the Proposed Rule
Economic Impacts and Social Costs of the
Proposed Rule
3.1 Economic Impacts
3.2 Social Costs
Benefits of the Proposed Rule
4.1 Reduced Human Health Risk
Ecological, Recreational, and
Nonuser Benefits
Reduced POTW Impacts
Total Estimated Benefits of the
Proposed MP&M Rule
Comparing Estimated Costs and Benefits .
Ohio Case Study
6.1 Benefits
6.2 Social Costs
6.3 Comparing Monetized Benefits
and Costs
4.2
4.3
4.4
. ES-1
. ES-3
. ES-5
. ES-5
ES-12
ES-13
ES-15
ES-18
ES-19
ES-20
ES-20
ES-22
ES-22
ES-24
ES-25
Department of Commerce data indicate that there are more
than 1.3 million establishments operating in potential MP&M
sectors. The MP&M survey results indicate that there are
approximately 89,000 MP&M facilities that manufacture,
rebuild, or repair metal machines, parts, products, or
equipment using processes covered by the proposed rule. Of
these 89,000, approximately 26,000 do not use or discharge
water or use a contract hauler for their wastewater. Only
62,752 facilities, or 71 percent of the MP&M facilities, are
water-discharging facilities that could be potentially subject
to the MP&M regulation. These 62,752 water-discharging
facilities include 57,948 indirect dischargers (i.e., facilities
discharging effluent to a publicly-owned sewage treatment
works or POTWs) and 4,804 direct dischargers (i.e., facilities
discharging effluent directly to a waterway under a NPDES
permit).
Table ES.l shows the estimated number of MP&M facilities
(water dischargers and zero dischargers) and total discharge
flow (prior to implementation of the proposed rule) by type
of facility. The largest number of sites, approximately
44,000, perform "rebuilding/maintenance only" and account
ES-1
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MP&M EEBA
Executive Summary
for approximately 9 percent of the total estimated discharge
flow for the industry. "Manufacturing only" represents the
next largest number of facilities (27,000) and represents the
largest percentage of the total estimated discharge flow for
the industry (75 percent).
Table ES.l: Number of MP&M Facilities (Water- Discharging and Zero-
Discharge) and Total Discharge Flow by Type of Facility
Type of Facility
Manufacturing &
Rebuilding/Maintenance
Manufacturing Only
Rebuilding/Maintenance
Only
Unknown/others
Total
Number of
Facilities
7,400
27,000
44,000
10,500
89,000
Total
Estimated
Discharge
Flow
(million
gal.yr)
11,200
91,700
11,100
8,100
122,000
Percent of
Facilities
8.3%
30.4%
49.5%
11.8%
100.0%
Percent of
Total
Discharge
Flow
9.1%
75.2%
9.1%
6.6%
100.0%
Source: U.S. EPA analysis. See Technical Development Document for the proposed rule.
Table ES.2 compares the number of potentially-regulated
facilities with the number that are actually subject to
requirements under the proposed rule. Of the 62,752 water
discharging facilities, 3,766 are predicted to close in the
baseline, leaving 58,986 facilities operating in the baseline
that EPA estimates could be regulated. The proposed rule
would regulate 9,839 of these facilities, including 5,186
indirect discharging facilities and 4,653 direct dischargers.
The estimated 9,839 water-discharging facilities that are
regulated under the preferred option represent less than 0.8
percent of all facilities in the MP&M industries, and 17
percent of those that are potentially regulated. Over 90
percent of the potentially-regulated indirect dischargers will
not be subject to requirements under the proposed rule,
whereas the proposed rule will regulate all of the direct
dischargers operating in the baseline.
Table ES.2: Number of MP&M Facilities Potentially-Regulated and Subject
to Requirements under the Proposed Rule
Direct
Indirect
Total
All Water-
Discharging
MP&M
Facilities
4,804
57,948
62,752
Operating in
the Baseline
4,653
54,333
58,986
Regulated
under the
Proposed
Rule
4,653
5,186
9,839
Percent of
Facilities
Operating in
the Baseline
that are
Regulated
100%
10%
17%
Source: U.S. EPA analysis.
The following are important characteristics of the MP&M
industries as a whole and of the portion of those industries
potentially-regulated under the proposed rule.
Many potentially-regulated MP&M facilities produce goods
and services that serve multiple market sectors. It is not
possible to associate regulatory costs and benefits to
particular sectors, because EPA is not able to link regulated
processes to specific sectors for facilities operating in
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MP&M EEBA
Executive Summary
multiple sectors. The results of EPA's cost and economic
impact analyses are disaggregated by type of facility but not
by sector.
Establishments in the relevant MP&M industries are located
in every state, with a particular concentration in the heavy
industrial regions along the Gulf Coast, both East and West
Coasts and the Great Lakes Region. Moreover, MP&M
facilities are frequently located in highly populated regions.
Based on survey information, 24% of facilities receiving
detailed MP&M questionnaires are located in counties with
populations of at least 1 million people, and 42% of
facilities sampled are located in counties with populations of
at least 500 thousand people.1
EPA is regulating the MP&M industry because the industry
releases substantial quantities of pollutants, including toxic
pollutant compounds (priority and nonconventional metals
and organics) and conventional pollutants such as total
suspended solids (TSS) and oil and grease (O&G). These
MP&M industry pollutants are generally controlled by
straightforward and widely-used treatment system
technologies such as chemical precipitation and clarification
(frequently referred to as the lime and settle process).
Discharges of these pollutants to surface waters and POTWs
have a number of adverse effects, including degradation of
aquatic habitats, reduced survivability and diversity of native
aquatic life, and increased human health risk through the
consumption of contaminated fish and water. In addition,
many of these pollutants volatilize into the air, disrupt
biological wastewater treatment systems, and contaminate
sewage sludge.
ES.2 DESCRIPTION OF THE PROPOSED
RULE
EPA grouped facilities into subcategories as a basis for the
proposed regulation. The subcategories differ in part based
on the type of wastewater that facilities discharge, including:
> facilities that discharge wastewaters with high
metals content, with or without oil and grease
(O&G); and
1 EPA is not able to characterize the location characteristics
of all potentially-regulated MP&M facilities at the national level
precisely, because the MP&M survey design was not intended to
provide national results by location characteristics.
* facilities that discharge wastewaters containing
mainly O&G, with limited metals and associated
other organic constituents.
The subcategories identified by EPA in each group are:
Metal-bearing (with or without O&G):
> Non Chromium Anodizing: facilities that perform
aluminum anodizing without the use of chromic
acid or dichromate sealants;
* Metal Finishing Job Shops: facilities that perform
one or more of six metal finishing operations and
that own no more than 50 percent of the materials
undergoing metal finishing;
* Printed Wiring Board: facilities manufacture,
maintain, and repair printed wiring boards (i.e.,
circuit boards), not including job shops;
> Steel Forming & Finishing: facilities that perform
MP&M operations or cold forming operations on
steel wire, rod, bar, pipe, or tube;
> General Metals: MP&M facilities that discharge
metal-bearing wastewater, with or without oil-
bearing wastewater, that do not fit into one of the
other metal-bearing subcategories described above.
Oil-bearing only:
* Shipbuilding Dry Docks: MP&M process
wastewater generated in or around dry docks and
similar structures, such as graving docks, building
ways, marine railways, and lift barges at
shipbuilding facilities. These structures include
sumps or containment systems that enable
shipyards to control the discharge of pollutants to
the surface water.
* Railroad Line Maintenance: facilities that perform
routine cleaning and light maintenance on railroad
engines, cars, car-wheel trucks, and similar parts or
machines, and discharge only from oily operations
and/or washing of the final product.
* Oily Wastes: MP&M facilities that discharge only
oil-bearing wastewater from a specified list of unit
operations and that are not Shipbuilding Dry Dock
or Railroad Line Maintenance facilities.
EPA evaluated ten technology options that might be used to
treat wastewaters from the MP&M facilities. Table ES.3
lists these technology options:
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MP&M EEBA
Executive Summary
Table ES.3: Technology Options
Option #
Description
For metal-bearing wastes
1
segregation of wastewaters, preliminary treatment (including oil-water
separation), chemical precipitation, and sedimentation using a clarifier
(chemical precipitation with gravity clarification)
in-process flow control and pollution prevention + option 1
segregation of wastewaters, preliminary treatment (including oil
removal by ultrafiltration), chemical precipitation, and solids separation
using a micro filter
in-process flow control and pollution prevention + option 3
For oil-bearing wastes
oil-water separation by chemical emulsion breaking
in-process flow control and pollution prevention + option 5
oil-water separation by ultrafiltration
in-process flow control and pollution prevention + option 7
9
10
oil-water separation by dissolved air flotation (DAF)
in-process flow control and pollution prevention + option 9
EPA defined specific effluent limitations based on a
statistical analysis of the performance of these technologies.
The even-numbered options add in-process flow controls
and pollution prevention (i.e., pollution prevention,
recycling, and water conservation to allow recovery and
reuse of materials) to the treatment technologies specified in
the odd-numbered options. In all cases, options with in-
process flow control and pollution prevention cost less and
remove more pollutants than do the comparable options
without pollution prevention. The EEBA, therefore, did not
analyze options without flow control and pollution
prevention.
The Agency considered a range of low flow exclusions for
indirect dischargers, to reduce burdens on permitting
officials and reduce the economic impacts of the rule.
Evaluation of the low flow cutoffs considered the amount of
pollutant discharged by each subcategory and flow size
category.
Table ES.4 shows the technology options and exclusions
that EPA is proposing for each subcategory. This table also
defines two regulatory alternatives for which EPA evaluated
costs, benefits, economic impacts and cost-effectiveness.
These include:
* Option 2/6/10, which applies the same technologies
for each subcategory, and eliminates the low flow
and subcategory exclusions of the proposed rule,
and
* Option 4/8, which applies more stringent
technology requirements for all subcategories and
does not include low flow exclusions.
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MP&M EEBA
Executive Summary
Table ES.4: Summary of Proposed Rule and Regulatory Alternatives for Existing Sources
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Oily Wastes
Printed Wiring Board
Railroad Line Maintenance
Shipbuilding Dry Dock
Steel Forming & Finishing
Proposed rule
Technology option 2;
1 mgy flow cutoff for indirect
dischargers
Technology option 2
Technology option 2; no PSES
for indirect dischargers
Technology option 6;
2 mgy flow cutoff for indirect
dischargers
Technology option 2
Technology option 10; no
PSES for indirect dischargers
Technology option 10; no
PSES for indirect dischargers
Technology option 2
Option 2/6/10
Technology option 2
Technology option 2
Technology option 2
Technology option 6
Technology option 2
Technology option 10
Technology option 10
Technology option 2
Option 4/8
Technology option 4
Technology option 4
Technology option 4
Technology option 8
Technology option 4
Technology option 8
Technology option 8
Technology option 4
Note: PSES = Pretreatment Standards for Existing Sources. The standards for different classes of dischargers are discussed in Chapter 4 of the EEBA.
ES.3 ECONOMIC IMPACTS AND SOCIAL
COSTS OF THE PROPOSED RULE
EPA assessed the economic impacts and social costs
associated with the proposed rule using detailed financial
and technical data from a series of surveys of MP&M
facilities. Engineering analyses of these facilities identified
the pollution prevention and treatment systems needed to
comply with the proposed rule and other regulatory
alternatives. The estimated capital and annual operating and
maintenance costs of these systems, incremental to the costs
of systems already in place, represent the compliance costs
of the rule.2 EPA analyzed the financial performance of
potentially-regulated facilities under the current conditions
(the baseline) and subject to the proposed regulatory
requirements. The Agency used a variety of measures to
assess the economic impacts resulting from the proposed
rule, both for the regulated MP&M facilities and for the
firms and governments that own the facilities. The
economic impact analysis also considered impacts for small
entities in particular, and impacts on employment, foreign
trade and communities. The results of the analyses for
sample facilities were extrapolated using survey sample
weights for each facility, to provide national-level results.
2 The annual equivalent of capital and other one-time costs is
calculated by annualizing costs at a seven percent discount rate
over an estimated 15 year equipment life. Annual compliance costs
are annualized capital costs plus annual operating and maintenance
(O&M) costs.
ES.3.1 Economic Impacts
Overall, EPA found the economic impacts of the proposed
rule to be very modest. The following are EPA's findings
for different categories of impacts.
a. Facility impacts
The facility impact analysis assesses how facilities will be
affected financially by the proposed rule. Key outputs of the
facility impact analysis include expected facility closures in
the MP&M industries, associated losses in employment, and
the number of facilities experiencing financial stress short of
closure ("moderate impacts"). EPA performed economic
impact analyses for three categories of facilities, using
different methodologies to evaluate each of the groups. The
three groups are:
* Private MP&M Facilities. This group includes
privately-owned facilities that do not perform
railroad line maintenance and are not owned by
governments. This major category includes private
businesses in a wide range of sectors or industries,
including facilities that manufacture and rebuild
railroad equipment. Only facilities that repair
railroad track and equipment along the railroad line
are not included.
* Railroad line maintenance facilities maintain and
repair railroad track, equipment and vehicles.
> Government-owned facilities include MP&M
facilities operated by municipalities, State agencies
and other public sector entities such as State
ES-5
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MP&M EEBA
Executive Summary
universities. Many of these facilities repair,
rebuild, and maintain buses, trucks, cars, utility
vehicles (e.g., snow plows and street cleaners), and
light machinery.
The specific methodology used to assess impacts differed
for each of the three types of MP&M facilities. For private
MP&M facilities, EPA established thresholds for measures
of financial performance and compared the facilities'
performance before and after compliance with each
regulatory option with these thresholds. Impacts were
measured at the operating company level for railroad line
maintenance facilities, since firms are unlikely to keep track
of financial performance at the facility level for these sites.
For governments, EPA compared compliance costs with
facilities' baseline costs of service, and assessed the impact
of the compliance costs on the government's taxpayers and
on its ability to finance compliance costs by issuing debt.
EPA identified facilities that are financially weak and might
be expected to close under baseline conditions. Of the
estimated 62,752 discharging facilities, 6.1 percent or 3,829
facilities were assessed as baseline closures. The 3,829
baseline closures include 3,678 indirect dischargers, or 6.3
percent of indirect dischargers, and 151 direct dischargers,
or 3.1 percent of direct dischargers. These facilities were
excluded from the post-compliance analysis of regulatory
impacts.
Table ES.5 provides an overview of the facility-level
economic impacts for the proposed rule. This table shows
that less than one-half of one percent of facilities are
projected to close due to the rule, and approximately one
percent are expected to experience moderate financial stress
short of closure. The proposed rule excludes over 90
percent of the indirect discharging facilities from any
requirements.
Table ES.5: Regulatory Impacts for All Facilities, Proposed Rule, National Estimates
Number of facilities operating in the baseline: total
private MP&M and railroad line maintenance
government-owned
Number of regulatory closures
Percent of facilities operating in the baseline that are regulatory
closures
Number of facilities operating post-regulation
Number of facilities below low flow cutoffs
Number of facilities with subcategory exclusions
Percent of facilities operating in the baseline excluded or below
cutoffs
Number of facilities operating subject to regulatory requirements
Number of facilities experiencing moderate impacts
Percent of facilities operating in the baseline that experience
moderate impacts
Total
58,922
54,590
4,332
199
0.3%
58,787a
48,256a
955
83.5%
9,576
616
1.0%
Direct
4,653
3,999
654
20
0.4%
4,633
4,633
41
0.9%
Indirect
54,270
50592
3678
179
0.3%
54,154a
48,256a
955
90.6%
4,943
575
1.1%
a. Includes 64 avoided baseline closures general metals indirect dischargers below the low flow cutoffs that are projected to close in the
baseline but that remain open under the proposed rule.
Source: U.S. EPA analysis.
Table ES.6 shows the results of the analysis by subcategory
and discharge status. The table shows that substantial
portions of the General Metals and Oily Waste indirect
dischargers are excluded by the low flow cutoffs. Metal
Finishing Job Shops account for the largest number of
closures among indirect dischargers under the proposed rule,
and Printed Wiring Board and Metal Finishing Job Shop
facilities together account for the largest portion of moderate
impacts. Most of the direct discharger impacts (closures
and moderate impacts) are in the General Metals
subcategory, although the closures and moderately-impacted
facilities represent a small percentage of the General Metals
direct discharging facilities as a whole.
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MP&M EEBA
Executive Summary
Table ES.6: Regulatory Impacts by Subcategory, Proposed Rule, National Estimates
Subcategory
Indirect Dischargers
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Indirect Dischargers
Direct Dischargers
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Direct Dischargers
# Facilities
Operating
in Baseline
23,140
1,231
150
620
105
28,219
799
6
54,270
3,636
12
0
11
43
911
34
6
4,653
Regulatory
Closures
24
128
0
7
6
14
0
0
179
20
0
0
0
0
0
0
20
%
Closures
0.1%
10.4%
0%
1.1%
5.7%
<.0.1%
0%
0%
0.3%
0.6%
0%
0%
0%
0%
0%
0%
0.4%
M
Exempted
20,164a
150
28,092
799
6
49,2 lla
%
Exempted
87%
100%
99.5%
100%
100%
91%
#with
Moderate
Impacts
153
117
0
301
4
-
0
0
575
34
0
0
7
0
0
0
41
%
Moderate
Impacts
0.7%
9.5%
0%
48.7%
3.8%
-
0%
0%
1.1%
0.9%
0%
0%
16.3%
0%
0%
0%
0.9%
a. Includes 64 avoided closures general metals indirect dischargers that are projected to close in the baseline but which operate under the
proposed rule and are eligible for the low flow cutoff.
Note: may not sum to totals due to independent rounding.
Source: U.S. EPA analysis.
Table ES.7 summarizes impacts for government-owned
facilities in particular. Under the proposed rule, 83 percent
of the government-owned facilities would be excluded from
requirements because they fall below the low flow cutoff
proposed for indirect dischargers. The compliance costs of
the proposed rule do not result in significant budgetary
impacts for any of the governments that operate the
facilities.
ES-7
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MP&M EEBA
Executive Summary
Table ES.7: Regulatory Impacts for Government -Owned
Proposed Rule, National Estimates
Number of government-owned facilities operating in the baseline & post-regulation
Number of facilities below low flow cutoffs
Percent of facilities operating in the baseline below cutoffs
Number of facilities operating subject to regulatory requirements
Number of facilities experiencing impacts
Percent of facilities operating in the baseline that experience significant budgetary
impacts
Facilities,
4,332
3,603
83.2%
729
0
0%
Source: U.S. EPA analysis.
b. Firm level impacts
EPA examined the impacts of the proposed rule on firms
that own MP&M facilities, as well as on the financial
condition of the facilities themselves. A firm that owns
multiple MP&M facilities could experience adverse
financial impacts at the firm level if its facilities are among
those that incur significant impacts at the facility level. The
firm-level analysis is also used to compare impacts on small
versus large firms, as required by the Regulatory Flexibility
Act and the Small Business Regulatory Enforcement
Fairness Act.
EPA compared compliance costs with revenue at the firm
level as a measure of the relative burden of compliance
costs. EPA applied this analysis only to MP&M facilities
owned by private entities. EPA estimated firm-level
compliance costs by summing costs for all facilities owned
by the same firm that responded to the survey plus estimated
compliance costs for additional facilities for which
respondents submitted voluntary information. The Agency
was not able to estimate the national numbers of firms that
own MP&M facilities precisely, because the sample weights
based on the survey design represent numbers of facilities
rather than firms. Most MP&M facilities (43,118 of 54,590,
or 80 percent) are single-facility firms, however. These
firms can be analyzed using the survey weights. In addition,
there are 289 firms that own more than one sample facility.
These firms are included in the analysis with a sample
weight of one, since it is not known how many firms these
289 sample firms represent.
Table ES.8 shows the results of the firm-level analysis. The
results represent a total of 43,407 MP&M firms (43,118 +
289), owning 54,590 facilities (43,118 owned by single-
facility firms + 11,473 owned by multi-facility firms).
Table ES.8: Firm
as
Number of
Firms in the
Analysis3
43,407
Level Before-Tax Annual Compliance Costs
a Percent of Annual Revenues
Number and Percent with Before-Tax Annual Compliance Costs/Annual
Revenues Equal to:
Less than 1%
Number
41,236
%
95%
1-3%
Number
1,070
%
2.5%
Over 3%
Number
1,101
%
2.5%
a. Firms whose only MP&M facilities close in the baseline are excluded.
A small percentage (2.5 percent) of the firms in the analysis
incur before-tax compliance costs equal to 3 percent or more
of annual revenues. Ninety-five percent incur compliance
costs less than 1 percent of annual revenues, and the
remaining 2.5 percent incur costs between 1 and 3 percent of
revenues. Of 2,171 firms in the analysis that incur costs
greater than 1 percent of revenues, 636 are single-facility
small firms that were reported in the facility impact analysis
to close (161 firms) or experience moderate impacts (475
firms) due to the rule.
This analysis is likely to overstate costs at the firm level for
two reasons. First, it includes compliance costs for facilities
that are projected to close due to the rule. The estimated
ES-8
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MP&M EEBA
Executive Summary
compliance costs for these facilities are higher than the true
cost to the firm of shutting down the facility, as illustrated
by the detailed facility impact analysis that projects closures.
Second, the analysis does not take account of actions a
multi-facility firm might take to reduce its compliance costs
under the proposed rule. These include transferring
functions among facilities to consolidate wet processes and
take advantage of scale economies in wastewater treatment.
c. Employment effects
Changes in employment due to the rule include both job
losses that occur when facilities close and job gains
associated with facilities' compliance activities. EPA
estimated that a total of 5,916 jobs would be lost at the 199
facilities projected to close under the proposed rule. At the
same time, EPA estimated that manufacturing and installing
compliance equipment would lead to 4,488 full-time
equivalent (FTE) positions, and that operating and
maintaining compliance systems would result in another 286
FTEs per year. EPA projects a net loss in employment in the
initial years following promulgation of the proposed rule,
with net increased employment in later years due to the
continuing compliance requirements. Net impacts on
unemployment depend on how long workers displaced from
closing facilities remain unemployed. Assuming
conservatively that unemployed workers are out of work for
one year on average, the proposed rule would result in a net
gain of 2,575 years of employment (FTE-years) (-5,916
FTEs lost x 1 year + 4,488 one-time compliance FTEs + 296
continuing compliance FTEs x 15 years), or an average of
172 FTEs per year over 15 years. This estimate of
employment impacts is likely to understate the net increase,
because it ignores the fact that some production and
employment lost at closing plants is likely to result in
increased production and employment at other MP&M
facilities.
d. Community impacts
EPA also considered the potential impacts of changes in
employment due to the proposed rule on the communities
where MP&M facilities are located. Given the projected
overall increase in employment due to the proposed rule,
EPA does not expect the rule to have significant impacts at
the community level.
z. Foreign trade impacts
Facility closures caused by the proposed rule may reduce
U.S. production of MP&M goods and services. EPA
assessed the potential impact of these production changes on
the U.S. balance of trade using information provided by the
MP&M surveys on the source of competition in domestic
and foreign markets. The analysis allocates the value of
changes in output for each facility that is projected to close
due to the rule to exports, imports or domestic sales, based
on the predominant source of competition in each market
reported in the surveys.
Table ES.9 shows the results of this analysis. The table
compares the projected changes in exports, imports and
balance of trade (expressed in $1999) to baseline 1999
values for both the MP&M industries and for the U.S.
balance of trade in commodities as a whole. The projected
changes in trade under the proposed rule have a very small
impact on the balance of trade. The total U.S. balance of
trade in commodities would decline by less than 0.01
percent and the balance of trade in the MP&M industries
would decline by 0.01 percent.
Table ES.9: Potential Impacts of Proposed Rule
on U.S. Foreign Commodity Trade
(millions of 1999 dollars)
Baseline
Change due to the rule
Post-compliance
% Change from baseline
1999 Exports a
$695,797
0
$695,797
0%
1999 Imports
$1,024,618
$21.1
$1,024,235
<0.01%
Trade Balance
($328,821)
($21.1)
($328,438)
(<0.01%)
a. Only 3 regulatory closures reported exports, totaling $16,613. These facilities reported no foreign
competition in the international market.
Source: Bureau of Census and U.S. EPA analysis.
e. Impacts on new facilities
EPA assessed the impacts of the proposed rule on new
facilities based on the characteristics of a model facility in
each subcategory and (in some cases) discharge category
ES-9
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MP&M EEBA
Executive Summary
(direct and indirect). Engineering estimates of compliance
costs for Option 2/6/10 and Option 4/8 for a representative
facility reflect the typical flow size and other technical
characteristics of facilities in each category. In the absence
of the MP&M rule, new sources in the Metal Finishing Job
Shop and Printed Wiring Board subcategories would comply
with 40 CFR 433 new source requirements, and Steel
Forming & Finishing new sources would comply with 40
CFR 420 new source requirements. Therefore, the analysis
considers only the incremental costs of proposed MP&M
new source requirements beyond those baseline
requirements.
Table ES.10 shows the results of the new source analysis.
New sources in all but the Metal Finishing Job Shop direct
discharger subcategory incur costs that are below one
percent of post-regulation revenues. Cost increases of this
magnitude are unlikely to place new facilities at a
competitive disadvantage relative to existing sources.
Moreover, costs as a percentage of revenues are generally
comparable for new sources and existing sources with which
they will compete.
Table ES.10: Impacts on New Sources
Subcategory
General Metals
General Metals
Metal Finishing Job
Shops
Metal Finishing Job
Shops
Non-Chromium
Anodizing*
Oily Waste
Oily Waste
Printed Wiring Board
Printed Wiring Board
Railroad Line
Maintenance*
Shipbuilding Dry
Dock*
Steel Forming &
Finishing
Steel Forming &
Finishing
Discharge
Status
I
D
I
D
D
I
D
I
D
D
D
I
D
Proposed
Technology
Option
4
4
4
4
2
6
6
4
4
10
10
4
4
Annualized
Compliance
Costs (ACC)
($1999)
$393,220
$167,342
$65,369
$70,735
$97,108
$355,874
$37,815
$70,563
$160,184
$184,261
$220,492
$114,851
$46,945
Facility
Revenue
($1999)
$417,071,318
$398,818,659
$1,428,443
$5,089,823
$24,201,166
$474,228,616
$116,772,943
$35,030,097
$1,029,783,596
N/A
$192,018,827
$69,640,244
$32,759,295
New
Source
ACC as %
of Revenue
0.09%
0.04%
4.58%
1.39%
0.40%
0.08%
0.03%
0.20%
0.02%
N/A
0.11%
0.16%
0.14%
* EPA is not proposing Pretreatment Standards for New Sources in these subcategories.
Source: U.S. EPA analysis.
Railroad line maintenance facilities do not have revenue
reported at the facility level, and it is therefore not possible
to compare costs as a percent of facility revenue for new and
existing facilities in this subcategory. The representative
new source railroad line maintenance facility would incur
annualized costs ($184,261) that are somewhat higher than
those incurred by existing facilities in this subcategory
(which range from zero to $122,042.)
f. Impacts on small entities
Table ES. 11 shows the total number of facilities operating in
the baseline and the number owned by small entities.
Overall, approximately 80 percent of all MP&M facilities
are owned by small entities. However, it should be noted
that the low flow exclusions in the proposed rule will
exclude approximately 85 percent of the facilities owned by
small entities.
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MP&M EEBA
Executive Summary
Table ES.ll:
Type of Facility
Private MP&M3
Government-Owned
Total3
Number and Percent of
Number of Facilities of
all Sizes Operating
in the Baseline
54,591
4,332
58,923
MP&M Facilities Owned by
Number of Facilities j
i Owned by Small Entities j
44,773 I
2,672 i
I 47,445 1
Small Entities
Percent of Facilities
Owned by Small
Entities
82%
62%
81%
a. Excludes baseline closures
Source: U.S. EPA analysis.
EPA assessed impacts on small entities by comparing
compliance costs to revenues for the small entities at the
firm level and by analyzing the facility impact analysis
results for facilities owned by small firms. These analyses
indicate that 941, or 2.2% of small entities may incur costs
equal to 3 percent or more of annual revenues.
Approximately 85 percent of small entities are not projected
to incur any costs to comply with the proposed rule because
they are among the facilities covered by the low flow
exclusions. More than 95 percent of small entities incur
either no costs or compliance costs less than 1 percent of
annual revenues. An estimated 181 facilities owned by
small entities might close as a result of the proposed rule,
and 492 facilities owned by small entities are likely to
experience moderate financial impacts. ThelSl small entity
facility closures represent less than one-half of one percent
of the facilities owned by small entities that are operating in
the baseline.
Tables ES.12 and ES.13 present the results of the firm- and
facility-level analyses, respectively, for small firms. The
Agency was not able to estimate national numbers of firms
that own MP&M facilities precisely, because the sample
weights based on the survey design represent numbers of
facilities rather than firms. The results in Table ES. 12 are
reasonable approximations, however, in that 95 percent of
the facilities owned by small firms are single-facility firms,
for which sample weights could be used.
Table ES.12
Number of
Small Firms in
the Analysis*
42,509
Firm Level Bef ore-Tax Annual Compliance Costs as a Percent of
Annual Revenues for Private Small Businesses
Number and Percent with Before-Tax Annual Compliance Costs/Annual
Revenues Equal to:
Less than 1%
Number
40,560
%
95.4%
1-3%
Number
1,008
%
2.4%
Over 3%
Number
941
%
2.2%
*Firms whose only MP&M facilities close in the baseline are excluded.
Source: U.S. EPA analysis.
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MP&M EEBA
Executive Summary
Table ES.13: Closures and Moderate Impacts
Owned by Small Entities, Proposed 1
Number of facilities operating in the baseline
Number of facilities excluded
Percent excluded
Number of closures
Percent closing
Number of facilities with moderate impacts
Percent with moderate impacts
for Facilities
*ule
47,445
40,825
85%
181
0.4%
492
1.0%
Source: U.S. EPA analysis
EPA estimates that there are 2,672 facilities owned by small
governments (those with populations less than 50,000). The
low flow exclusion in today's proposed rule will exclude
2,262 of these small government-owned MP&M facilities.
Thus, the proposed rule covers 410 small government-
owned facilities. Of these facilities, only 270 incur costs,
and the average cost per facility is less than $10,000. The
total compliance cost for all the small government-owned
facilities incurring costs under today's proposed rule is $2.7
million. Only 140 of the 270 facilities have costs greater
than 1 percent of baseline cost of service (measured as total
facility costs and expenditures, including operating,
overhead and debt service costs and expenses). EPA
estimated no significant impacts for any of these facilities,
based on the combined impacts on the site cost of service,
impacts on taxpayers, and impact on government debt levels.
ES.3.2 Social Costs
The social costs of the proposed rule represent the value of
society's resources used to comply with and administer the
rule. EPA estimated three categories of social cost for the
proposed regulation:
> the cost of society's economic resources used to
comply with the proposed regulation,
> the cost to governments of administering the
proposed regulation, and
* the social costs of unemployment resulting from
the regulation.
Summing across the categories of social cost results in a
total social cost estimate of $2,033 to $2,113 million
annually (1999$) (see Table ES.14). The social costs of the
rule are dominated by the resource costs of compliance,
which account for 95 to over 99 percent of total social costs.
The midpoint value of total social costs (the simple average
of the high and low values) is $2,073.3 million (1999$).
Table ES.14: Total Social Cost: Proposed Rule
(million 1999$)
Social Cost Categories
Resource cost of compliance expenditures
Costs to POTWs of administering the rule
Social costs of unemployment
Total Social Cost
Low Value
$2,0
$0.115
$0.0
$2,033.9
High Value
33.7
$0.912
$77.9
$2,112.6
Source: U.S. EPA analysis
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MP&M EEBA
Executive Summary
a. Resource costs of compliance
Resource costs of compliance are the value of society's
productive resources including labor, equipment, and
materials expended to achieve the reductions in effluent
discharges required by the proposed rule. The social costs
of these resources are higher than the costs incurred by
facilities because facilities are able to deduct the costs from
their taxable income. The costs to society, however, are the
full value of the resources used, whether they are paid for by
the regulated facilities or by all taxpayers in the form of lost
tax revenues.
EPA did not include any costs for facilities that were
predicted to close in the baseline, but did include costs for
facilities that were projected to close due to the proposed
rule, equal to the compliance cost they would incur if they
continued to operate. This represents the value to society of
the resources that would be used to comply with the
proposed rule if all facilities continued to operate rather than
some closing due to the rule. This estimate represents an
upper-bound social value of the compliance resources
associated with the proposed rule. The total social costs of
these compliance resources is $2,034 million per year.
b. Administrative costs
The main component of this cost category is the cost of
resources used to write permits under the proposed rule, and
for compliance monitoring and enforcement activities.
POTWs will incur costs to permit additional facilities,
convert some permits from concentration-based to mass-
based, and repermit some facilities earlier than would
otherwise be required. While EPA expects that the
proposed rule will also result in cost savings to permit
writers, EPA did not include any such savings in the
estimate of social costs.
EPA estimated the low and high estimates of permitting cost
per facility, and took account of the need to repermit
indirect dischargers with existing permits within the three
year compliance period rather than on the normal five year
permitting schedule. Total estimated government
administration costs for the proposed rule range from $0.1 to
$0.9 million (1999$) annually.
c. Social cost of unemployment
EPA considered two components of the social cost of
unemployment that may result from the proposed rule:
> The cost of worker dislocation (exclusive of cash
benefits) to unemployed individuals, as measured
by their willingness to pay to avoid unemployment;
and
> The additional cost to governments to administer
unemployment benefits programs.
An estimated 5,916 jobs may be lost at facilities that close
due to the proposed rule. EPA estimates that the annualized
social costs associated with these job losses range from
$59.1 million to $77.9 million (1999$). This estimate
includes:
- $59.0 to $77.8 million (1999$) in the social cost of
involuntary unemployment, based on high and low
estimates of workers willingness to pay to avoid an
episode of unemployment; and
> $0.1 million (1999$) in the cost to governments of
administering additional unemployment claims.
The rule will also result in increased employment due to the
need to manufacture, install, operate and maintain
compliance equipment. The additional demand for labor in
complying facilities may exceed the job losses estimated to
occur in closing facilities. As a result, the net costs
associated with unemployment as a result of the regulation
may be negative. In this analysis, EPA used a range of zero
to $77.9 million (1999$) as the estimated social cost of
unemployment cost resulting from the proposed rule. To be
conservative in the analysis, EPA limited the lower value of
this range to zero. That is, EPA did not include the possible
savings in unemployment-related costs as a negative cost (a
benefit) of the proposed rule.
ES.4 BENEFITS OF THE PROPOSED RULE
The proposed regulation will reduce MP&M industry
pollutant discharges with a number of consequent benefits to
society, including:
* improved quality of freshwater, estuarine, and
marine ecosystems;
> increased survivability and diversity of aquatic and
terrestrial wildlife;
* reduced risks to human health through consumption
offish or water taken from affected waterways; and
> reduced cost of disposal or use of municipal
sewage sludge affected by MP&M pollutant
discharges.
EPA estimates that the proposed rule would substantially
reduce pollutant discharges to U.S. waters, as shown by the
loadings estimates in Table ES. 14. Loadings are shown both
in pounds of pollutant and in toxic-weighted pound
equivalents. The latter measure reflects the relative toxicity
of the various toxic pollutants. The regulation would result
in a 89 percent reduction in total toxic-weighted pollutant
Ibs. equivalent per year. The estimated toxic weighted
pollutant reductions range from 99% for cyanide to 30% for
nonconventional organics. Reductions in pounds of
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MP&M EEBA
Executive Summary
pollutants (not toxic-weighted) range from 99% for cyanide
to 51% for priority organics. The proposed rule achieves
very significant reductions for toxic metals, cyanide and
conventional pollutants (oil and grease, total suspended
solids, and chemical oxygen demand).
Table ES.14: Summary of Discharges by Pollutant Type for Potentially-Regulated MP&M Facilities"
Pollutant Category
Priority Pollutants
Metals
Organics
Cyanide (CN)
Nonconventional Pollutants
Metals
Organics
Conventional Pollutants
COD
O&G
TSS
Total
Current Releases
Pounds
34,527,668
2,095,832
4,718,247
120,756,930
50,468,179
2,445,579,193
220,782,391
231,466,565
Pounds Eq.
16,476,843
323,410
5,190,072
7,201,034
210,501
29,401,860
Releases under The Proposed
Rule
Pounds
2,018,185
1,024,636
35,881
23,723,669
9,411,727
601,888,710
20,953,718
27,404,519
Pounds Eq.
1,500,230
156,560
39,469
1,265,904
146,873
3,109,036
Percent Reduction due to the
Proposed Rule
Pounds
94%
51%
99%
80%
81%
75%
91%
88%
Pounds Eq.
91%
52%
99%
82%
30%
89%
a Includes all water-discharging facilities that continue to operate in the baseline, including facilities that are not subject to requirements under the
proposed rule. Discharges discussed in this table are facility discharges and do not account for POTW removals. EPA believes it is appropriate to
analyze wastewater discharges disregarding the POTW removals because indirect discharges present environmental risks that are not fully addressed by
POTW treatment. The MP&M industry releases 89 pollutants that cause inhibition problems at POTWs and an additional 35 hazardous air pollutants
(HAPs) that may present a threat to human health or the environment. Other MP&M pollutants released by the industry are found in POTW sludge.
Only eight of these pollutants have land application pollutant criteria that limit the uses of sludge.
Source: U.S. EPA analysis.
EPA assessed the benefits from the expected pollutant
loading reductions in three broad classes: human health,
ecological, and economic productivity benefits. EPA was
able to assess benefits within these three classes with
varying degrees of completeness and rigor. Where possible,
EPA quantified the expected effects and estimated monetary
values. Some benefit categories could not be monetized due
to data limitations and a limited understanding of how
society values certain water quality changes. EPA also
conducted a more detailed case study of the regulation's
expected benefits for the State of Ohio. The case study
addresses some of the limitations inherent in the national
analysis.
The national benefits estimates for the proposed rule
presented in this report range from $1.3 billion to $3.8
billion per year. In contrast, the preamble to the proposed
rule presents benefits estimates ranging from $0.4 billion to
$1.1 billion. The estimates in the preamble include human
health benefits (reductions in cancer and lead exposure),
recreational fishing benefits, non-use benefits, and improved
POTW sludge quality. This report includes monetized
estimates for additional benefits categories, specifically
recreational boating and near-water recreation, and higher
estimates for non-use benefits based on these additional
recreational benefits.
EPA traditionally estimates national benefits and costs from
proposed effluent limitations guidelines by extrapolating the
benefits and costs assessment results for the sample facilities
to the entire population of facilities nationwide. The
analysis assumes that facilities represented by the sample
ES-14
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MP&M EEBA
Executive Summary
facility have the same technical, economic/financial and
benefit characteristics, including:
Technical characteristics that affect costs and discharges:
* type of discharger (i.e., zero, direct, indirect);
* type and number of processes;
* number and types of metals;
* wastewater characteristics;
* treatment in place;
* flow size; and
* costs.
Economic and financial characteristics that affect
financial impacts:
* markets, including domestic and foreign sales;
* competition, including domestic competition and
imports;
* baseline financial position;
> cash flow;
* ability to borrow money; and
> liquidation values and closure costs.
Environmental and geographic characteristics that affect
benefits:
size of the receiving POTW,
> waterbody type,
* stream flow characteristics,
> populations residing near the waterbody, and
* the number of potential recreational users affected.
Extrapolation from the sample facilities to the entire
population of facilities uses sample facility weights
developed as part of the sampling plan. The sample weights
are based on the stratification of the facility population using
variables such as facility size and SIC code or industry
sector. Sometimes stratification is done on the two
previously mentioned variables alone, while other times
EPA uses a database with considerably more information for
stratification. Stratification generally does not include
variables related to non-facility characteristics that may
influence occurrence and magnitude of the expected benefits
due to paucity of the relevant data concerning these
variables at the time of sample plan design.
Not accounting for distribution of non-facility characteristics
in the sample frame may occasionally cause extrapolation
anomalies in benefits analyses and lead to a larger than
desired level of uncertainty. Despite this extrapolation
procedure shortfall, the resulting national estimates are
unbiased (i.e., they are not expected to consistently
overestimate or underestimate the parameters estimated).
Because EPA has not yet resolved some possible anomalies
in the extrapolation of this analysis to the national level, the
monetized benefits for the new categories of benefits are not
included in the summary of benefits for the proposed rule
that appears in the preamble. They are included in this
report, however, to present the methodologies and their
results as applied to the MP&M rule for public comment,
concurrent with seeking peer review of these methodologies.
Based on the results obtained using only sample facility
locations and the case study results, EPA believes that the
benefits of the MP&M regulation exceed the costs. EPA is
not equally certain of the absolute level of benefits. The
Agency is currently working on post-stratification of the
MP&M facility sample to address this issue, and expects to
have the process completed prior to the final regulation.
ES.4.1 Reduced Human Health Risk
EPA analyzed the following measures of health-related
benefits: reduced cancer risk from fish and water
consumption; reduced risk of non-cancer toxic effects from
fish and water consumption; lead-related health effects to
children and adults; and reduced occurrence of in-waterway
pollutant concentrations in excess of levels of concern. The
levels of concern include human health-based ambient water
quality criteria (AWQC) or documented toxic effect levels
for those chemicals not covered by water quality criteria.
Although some health effects are relatively well understood
and can be quantified and monetized in a benefits analysis
(e.g., cancer), others are less well understood, and may not
be assessed with the same rigor or at all (e.g., systemic
health effects). The Agency therefore monetized only two
of these health benefits: (1) changes in the incidence of
cancer from fish and water consumption, and (2) changes in
adverse health effects in children and adults from reduced
lead exposure.
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MP&M EEBA
Executive Summary
a. Benefits from reduced incidence of
cancer cases
EPA estimated aggregate cancer risk from contaminated
drinking water for populations served by drinking water
intakes on waterbodies to which MP&M facilities discharge.
This analysis is based on seven carcinogenic pollutants for
which no published drinking water criteria are currently
available. This analysis excludes six carcinogens for which
drinking water criteria are available. EPA assumed that
public drinking water treatment systems will remove these
pollutants from the public water supply.
Calculated in-stream concentrations serve as a basis for
estimating changes in cancer risk for populations served by
affected drinking water intakes. EPA estimates that the
proposed regulation would eliminate 2.24 cancer cases
associated with consumption of contaminated drinking
water, or 44 percent of the cancer cases associated with
baseline MP&M discharges, annually.
EPA valued the reduced cancer cases using estimated
willingness-to-pay (WTP) values for avoiding premature
mortality. EPA estimates the mean value of avoiding one
statistical death to be $5.8 million (1997$), based on
cancer's association with both mortality and the hardships
(e.g., psychic and other costs) from a prolonged period of
morbidity prior to death. The Agency assumed that an
individual would be willing to pay to avoid the disease at its
start. This action may significantly precede the
cancer-related death itself, if death occurs. The estimated
monetary value of benefits from reduced incidence of cancer
associated with drinking water is $17.7 million per year
(1997$), based on the above assumptions.
EPA also estimated the aggregate cancer risk to recreational
and subsistence anglers and their families from consuming
contaminated fish. This analysis is based on thirteen
carcinogenic pollutants found in MP&M effluent
discharges. Estimated contaminants in fish tissue reflect
predicted in-stream pollutant concentrations and biological
uptake factors. EPA used data on numbers of licensed
anglers by State and county, presence offish consumption
advisories, fishing activity rates, and average household size
to estimate the affected population of recreational and
subsistence anglers and their families. The analysis uses
different fish consumption rates for recreational and
subsistence anglers to estimate the change in cancer risk
within these populations.
The proposed rule eliminates an estimated 0.05 cancer cases
per year for combined recreational and subsistence angler
populations, representing a reduction of about 36 percent
from a baseline of about 0. IScases. This change translates
into $0.36 million (1997$) in annual benefits due to reduced
cancer risk from consumption of contaminated fish by these
populations.
Total benefits from reduced incidence of cancer cases,
including both drinking water and fish exposures, are $18.08
million (1997$) annually (see Table ES.15).
Table ES.15: Estimated Annual Benefits from Avoided Cancer Cases from Fish and Drinking Water Consumption
Regulatory Status
3aseline
Droposed Option
r'ercent Reduction
Drinking Water
Annual
Cancer
Cases
5.10
2.86
43.9%
Benefit Value
(million 1999$)
N/A1
$17.70
N/A
Fish Consumption
Annual
Cancer
Cases
0.126
0.081
35.7%
Benefit Value
(million 1999$)
N/A
$0.36
N/A
Total
Annual
Cancer
Cases
5.23
2.94
43.9%
Benefit Value
(million 1997$)
N/A
$18.08
N/A
1 Not Applicable
Source: U.S. Environmental Protection Agency
b. Reductions in systemic health effects
EPA estimates that the proposed rule would result in the
removal of 142 million pounds of 77 pollutants related to a
wide range of non-cancer human health effects (e.g.,
systemic effects, reproductive toxicity, and developmental
toxicity). Reducing human exposure to these pollutants via
fish and water consumption, relative to pollutant-specific
health effects thresholds, yields an additional measure of the
human health benefits likely to result from the proposed
regulation. EPA compared estimated in-stream pollutant
concentrations for 77 systemic toxicants with risk reference
doses to calculate the hazard score distributions for
populations consuming drinking water and fish. The
Agency's comparison of baseline and post-compliance
exposures shows population movement from higher to lower
risk values for both the fish and drinking water analyses.
Both analyses also show substantial increases in the
percentage of the exposed populations that would not be
exposed to any risk of systemic health hazards.
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MP&M EEBA
Executive Summary
c. Benefits from reduced exposure to lead
EPA performed a separate analysis of benefits from reduced
exposure to lead from consumption of contaminated fish
tissue. The analysis addressed three population groups:
> preschool age children,
* pregnant women, and
> adult men and women.
Unlike the analysis of systemic health risk from exposure to
other MP&M pollutants, this analysis is based on
dose-response functions tied to specific health endpoints to
which monetary values can be applied. Using blood-lead
levels as a biomarker of lead exposure, EPA estimated
baseline and post-compliance blood lead levels in the
exposed populations and then used changes in these levels
to estimate benefits in the form of avoided health damages.
EPA assessed neurobehavioral effects on children based on
a dose-response relationship for IQ decrements. The
Agency expressed avoided neurological and cognitive
damages as changes in overall IQ levels, including reduced
incidence of extremely low IQ scores (<70, or two standard
deviations below the mean) and reduced incidence of blood-
lead levels above 20 mg/dL. The analysis valued the
avoided neurological and cognitive damages by using:
> the value of compensatory education that an
individual would otherwise need, and
* the impact of an additional IQ point on individuals'
future earnings.
EPA estimated that implementing the proposed rule would
result in avoided IQ loss of 489 points across all exposed
children. The estimated monetary value of avoided IQ loss
is $4.9 million (1999$). In addition, reduced occurrences of
extremely low IQ scores (<70) and reduced incidence of
blood-lead levels above 20 mg/dL would result in a $0.1
million (1999$) decrease in the annual cost of compensatory
education for children with learning disabilities.
Prenatal exposure to lead is an important exposure route.
Fetal exposure to lead in utero due to maternal blood-lead
levels may result in several adverse health effects, including
decreased gestational age, reduced birth weight, late fetal
death, neurobehavioral deficits in infants, and increased
infant mortality. EPA assessed benefits to pregnant women
by relating changes in the risk of infant mortality to changes
in maternal blood-lead levels during pregnancy. This
analysis estimated the monetary benefit of reduced neonatal
mortality risk to be $12.7 million (1997$), based on the
estimated WTP to avoid a mortality.
Adults also suffer form adverse health effects due to lead
exposure. The adult health effects that EPA was able to
quantify all relate to lead's effects on blood pressure.
Quantified health effects include increased incidence of
hypertension (estimated for males only), initial coronary
heart disease (CHD), strokes (initial cerebrovascular
accidents (CBA) and atherothrombotic brain infarctions
(BI)), and premature mortality. This analysis does not
include other health effects associated with elevated blood
pressure, or other adult health effects of lead (e.g., nervous
system disorders in adults, anemia, and possible cancer
effects). EPA used cost of illness estimates (i.e., medical
costs and lost work time) to estimate the monetary value of
reduced incidence of hypertension, initial CHD, and strokes.
EPA then used the value of a statistical life saved to estimate
changes in the risk of premature mortality. The estimated
monetary value of health benefits to adults is $18.0 million
(see Table ES. 16).
Total benefits from reduced exposure to lead, including both
children and adults, are $35.8 million (1999$) annually under
the proposed option.
Table ES.16: National Adult Lead Benefits
(Millions of 1999$ per Year)
Category
Men
Hypertension
CHD
CBA
BI
Mortality3
Women
CHD
CBA
BI
Mortality3
Total Benefits
Proposed Option
Reduced Cases
959.85
1.24
0.52
0.29
1.7
0.39
0.17
0.10
0.41
Monetary Value
$1.00
$0.09
$0.14
$0.08
$13.41
$0.03
$0.03
$0.02
$3.24
$18.04
a. Unlike other benefits in this table, the value of avoided mortality is
expressed in 1997$.
National Level Exposed Population:
> Hypertension: 428,363 men ages 20 to 74;
> Coronary heart disease, cerebrovascular accidents, brain
infarction, and mortality: 173,386 men and 192,091
women ages 45-74.
d. Exceedances of Human Health-Based
AWQC
EPA also estimated the effect of MP&M facility discharges
by comparing the estimated baseline and post-compliance in-
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MP&M EEBA
Executive Summary
stream concentrations of 18 pollutants in affected
waterways to human health AWQC through two
consumption routes:
> water and organisms, and
* organisms alone.
Pollutant concentrations in excess of these values indicate
potential human health risks.
ซ> Consumption of water and organisms
EPA estimates that 10,310 receiving reaches nationwide
have baseline in-stream concentrations exceeding human
health AWQC for consumption of water and organisms.
The proposed rule eliminates these excess concentrations on
1,105 of those reaches.
Results also show that 382 receiving reaches will
experience partial water quality improvements from reduced
occurrence of some pollutant concentrations in excess of
AWQC limits for consumption of water and organisms.
ซ> Consumption of organisms alone
EPA estimates that 192 receiving reaches nationwide have
baseline in-stream concentrations exceeding human health
AWQC for consumption of organisms alone. The proposed
rule eliminates these excess concentrations on 121 of those
reaches.
ES.4.2 Ecological, Recreational, and
Nonuser Benefits
EPA expects the proposed regulation to provide ecological
benefits by improving the habitats or ecosystems (aquatic
and terrestrial) affected by MP&M discharges. Benefits
associated with changes in aquatic life include:
* restoring sensitive species,
* recovering diseased species,
* reducing taste-and odor-producing algae
populations,
* increasing dissolved oxygen (DO), and
* increasing the assimilative capacity of affected
waterways.
These improvements enhance the quality and value of
water-based recreation, such as fishing, swimming, wildlife
viewing, camping, waterfowl hunting, and boating. The
benefits from improved water-based recreation include the
increased value that participants derive from a day of
recreation, or the increased number of days that consumers
of water-based recreation choose to visit the cleaner
waterways. This analysis measures the economic benefit to
society based on the increased monetary value of recreational
opportunities resulting from water quality improvements.
a. Reduced aquatic life impacts
EPA estimated the cases in which in-waterway pollutant
concentrations resulting from baseline MP&M facility
discharges on affected waterways exceed recommended
acute and chronic AWQC protecting aquatic life. Pollutant
concentrations in excess of these AWQC values indicate
potential impacts to aquatic life.
The analysis compared baseline and post-compliance
exceedances of aquatic life AWQC to determine the effects
of the rule. Results show that baseline pollutant
concentrations exceed acute AWQC in 878 reaches and
chronic AWQC in 2,466 reaches nationally at baseline
discharge levels. EPA estimates that the proposed option
eliminates concentrations in excess of acute and chronic
criteria in 775 and 1,029 reaches, respectively. Results also
show that an additional 903 receiving reaches will experience
partial water quality improvements from reduced occurrence
of some pollutant concentrations in excess of acute and/or
chronic AWQC limits for protection of aquatic life.
b. Recreational benefits
EPA assessed the recreational benefits from reduced
occurrence of pollutant concentrations exceeding aquatic life
and/or human health AWQC values. Combining its findings
from both the aquatic life and human health AWQC
exceedance analyses, EPA found 10,443 stream reaches
exceeding chronic or acute aquatic life AWQC and/or human
health AWQC values at baseline discharge levels. The
Agency estimates that the proposed rule will eliminate
exceedances on 1,185 of these discharge reaches, leaving
9,258 reaches with concentrations of one or more pollutants
exceeding AWQC limits. Of these 9,258 reaches, 1,837
reaches will experience partial water quality improvements
from reduced occurrence of some pollutant concentrations in
excess of AWQC limits.
EPA attached a monetary value to reduced exceedances
based on increased values for three water-based recreation
activities (fishing, wildlife viewing, and boating) and on
nonuser values. EPA applied a benefits transfer approach to
estimate the total WTP, including both use and nonuse
values, for improvements in surface water quality. This
approach builds upon a review and analysis of the surface
water valuation literature.
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Executive Summary
EPA first estimated the baseline value of water-based
recreation for benefiting reaches, based on per-reach
estimates of:
> annual person-days of water-based recreation, and
* per-day values of water-based recreation.
EPA based baseline per-day values of water-based
recreation on studies by Walsh et. al (1992) and Bergstrom
and Cordell (1991). The studies provide values per
recreation day for a wide range of water-based activities,
including fishing, boating, wildlife viewing, waterfowl
hunting, camping, and picnicking. The mean values per
recreation day used in this analysis are $39.62, $24.72, and
$45.44 (1999$) for fishing, near-water recreation, and
boating, respectively.
EPA then applied the percentage change in the recreational
value of water resources implied by surface water valuation
studies to estimate changes in values for all MP&M reaches
in which the regulation eliminates AWQC exceedences by
one or more MP&M pollutants. The Agency selected eight
of the most comparable studies and calculated the changes
in recreation values from water quality improvements (as a
percentage of the baseline) implied by those studies.
Sources of estimates included Lyke (1993), Jakus et al.
(1997), Montgomery and Needleman (1997), Paneuf et al.
(1998), Desvousges et al. (1987), Lant and Roberts (1990),
Farber and Griner (2000), and Tudor et al. (2000). EPA
took a simple mean of point estimates from all applicable
studies to derive a central tendency value for percentage
changes in the water resource values due to water quality
improvements. These studies yielded estimates of increased
recreational value from water quality improvements
expected from reduced MP&M discharges of 12.7, 20.2,
and 12.4 percent for fishing, wildlife viewing, and boating,
respectively. Table ES. 17 provides the estimated national
recreational benefits of the proposed rule (1999$).
EPA also estimated non-market nonuser benefits. These
benefits are not associated with current use of the affected
ecosystem or habitat; instead, they arise from the value that
society places on improved water quality independent of
planned uses or based on expected future use. Past studies
have shown that nonuser values are a sizable component of
the total economic value of water resources. EPA estimated
average changes in nonuser value to equal one-half of the
recreational use benefits. The estimated increase in nonuser
value is $760.3 million (1999$).
Table ES.17: Estimated Recreational Benefits from Reduced MP&M Discharges (Proposed Option)
Recreational Activity
Fishing
Boating
Wildlife Viewing and Near- Water Recreation
Total Recreational Use Benefits (Fishing + Boating + Wildlife
Viewing)
Nonuser Benefits (1/4, Vi, and 2/3 of Total Recreational Use)
Total Recreational Benefits (million 1999$)
Low;
$196;
$265J
$500J
$961|
$240J
$1,201!
Midi
$365;
$446 !
$710!
$1,521!
$760!
$2,281!
High
$627
$672
$920
$2,219
$1,464
$3,683
Source: U.S. EPA analysis.
The recreational trips corresponding to the three activities
considered in this analysis are stochastically independent;
EPA calculated the total value of enhanced water-based
recreation opportunities by summing the three recreation
categories and nonuser value. The resulting increase in the
value of water resources to consumers of water-based
recreation and nonusers is 2,281 million (1999$) annually.
ES.4.3 Reduced POTW Impacts
EPA evaluated two productivity measures associated with
MP&M pollutants. The first measure was the pollutant
interference at publicly-owned treatment works (POTWs),
which was quantified but not monetized. The second
measure was the pass-through of pollutants into the sludge,
which limits options for its disposal.
MP&M pollutants may impair POTW treatment
effectiveness by inhibiting the biological activity of activated
sludge. EPA estimated inhibition of POTW operations by
comparing predicted POTW influent concentrations with
available inhibition levels for 89 pollutants. POTW
inhibition values come from guidance published by EPA and
other sources. At baseline discharge levels, EPA estimates
that concentrations of 18 pollutants discharged from MP&M
facilities exceed biological inhibition criteria at 515 POTWs
nationwide. The proposed regulation would eliminate
potential inhibition problems at 306 POTWs and reduce the
ES-19
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MP&M EEBA
Executive Summary
occurrence of pollutant concentrations in excess of
inhibition criteria at 82 POTWs. POTWs may impose local
limits to prevent inhibitions. If local limits are in place, the
estimated reduction in potential inhibition problems at the
affected POTWs is overstated. In this case, however, the
estimated social cost of the MP&M regulation is also
overstated.
EPA also quantified the reduced costs for managing and
disposing of sewage sludge. This analysis relied on data
from 147 POTW surveys. POTWs provided information on
sewage sludge use and disposal costs and practices, total
metal loadings to the POTW, percentage of total metal
loadings contributed by MP&M facilities, and the number of
known MP&M dischargers to the POTW. The survey also
provided information on the percentage of qualifying sludge
that is not land applied, and reasons for not land applying
qualifying sludge.
EPA estimated baseline and post-compliance sludge
concentrations of eight metals for POTWs receiving
discharges from the sample MP&M facilities. EPA
compared these concentrations with the relevant metal
concentration limits for land application and surface
disposal. EPA estimated that concentrations of one or more
metals at 6,953 POTWs would fail the land application
limits in the baseline. EPA estimated that 62 POTWs will
be able to select the lower-cost land application disposal
based on estimated reductions in sludge contamination. An
estimated 1.7 million dry metric tons (DMT) of sewage
sludge would newly qualify for land application annually.
EPA also estimated that 21 POTWs that previously met only
the land application pollutant limit would, as a result of
regulation, meet the more stringent land application
concentration limits. EPA expects these POTWs to benefit
through reduced recordkeeping requirements and exemption
from certain sludge management practices. The annual
estimated cost savings for the POTWs expected to upgrade
their sludge disposal practices are $61.3 million (1999$).
This analysis includes an adjustment to the estimate of
national sludge use/disposal cost benefits for POTWs
located at cost-prohibitive distances from agricultural,
forest, or disturbed lands suitable for sludge application.
EPA assumed that 46 percent of sludge generated in the
United States is generated by POTWs located too far from
sites suitable for sewage sludge application to make these
practices economical.
ES.4.4 Total Estimated Benefits of the
Proposed MP&M Rule
EPA estimates that total benefits for the five categories for
which monetary estimates were possible are $2.396 billion
(1999$) annually. EPA characterized uncertainty inherent in
the benefits analysis by bounding benefit estimates. The
annual lower- and upper-bound benefit estimates of the
proposed option are $1,284 and $3,833 billion (1999$),
respectively. The monetized benefits of the rule
underestimate its total benefits because they omit numerous
sources of benefits to society from reduced MP&M effluent
discharges. Examples of benefit categories not reflected in
this estimate include: non-cancer health benefits other than
benefits from reduced exposure to lead; other water-
dependent recreational benefits, such as swimming and
waterskiing; reduced cost of drinking water treatment for the
pollutants with drinking water criteria; and benefits to
wildlife and endangered species.
ES.5 COMPARINS ESTIMATED COSTS
AN& BENEFITS
EPA cannot perform a complete cost-benefit comparison
because not all of the benefits resulting from the proposed
regulatory alternative can be valued in dollar terms.
Table ES. 18 shows that combining the estimates of social
benefits and social costs yields an estimate of net
monetizable benefits ranging from negative $809 million to
positive $1,752 million annually (1999$) at the national
level. Comparing the midpoint estimate of social costs with
the midpoint estimate of monetized benefits results in a net
benefit of $311 million. The lack of a comprehensive
benefits valuation limits this assessment of the relationship
between costs and benefits of the proposed rule.
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MP&M EEBA
Executive Summary
Table ES.18: Comparison of National Annual Monetizable Benefits to Social Costs: Proposed Rule
(millions of 1999$)
Benefit and Cost Categories
Benefit Categories
Reduced Cancer Risk from Fish Consumption3
Reduced Cancer Risk from Water Consumption3
Reduced Risk from Exposure to Lead
Enhanced Water-Based Recreation
Nonuse Benefits
Avoided Sewage Sludge Disposal Costs
Total Monetized Benefits
Cost Categories
Resource Costs of Compliance
Costs of Administering the Proposed Regulation
Social Costs of Unemployment
Total Monetized Costs
Net Monetized Benefits (Benefits Minus Costs)b
Low
$0.3
$13.0
$28.0
$960.6
$240.2
$61.1
$1,303.2
$2,033.7
$0.1
$0
$2,033.9
($809.4)
Midpoint
$0.3
$13.0
$28.0
$1,520.7
$760.3
$61.3
$2,383.6
$2,033.7
$0.3
$39.0
$2,073.0
$310.6
High
$0.3
$13.0
$28.0
$2,218.7
$1,464.3
$61.5
$3,785.8
$2,033.7
$0.9
$78.0
$2,112.6
$1,751.9
a. The monetary value of benefits from reduced incidence of cancer is based on 1997$.
b. EPA calculated the low net benefit value by subtracting the high value of costs from the low value of benefits, and calculated the high net benefit value
by subtracting the low value of costs from the high value of benefits. The midpoint net benefit is based on the midpoint values for costs and benefits.
Source: U.S. EPA analysis.
As previously mentioned, extrapolating from sample facility
results to national results can introduce uncertainty into the
analysis for both the cost and the benefits estimates. EPA
therefore also compared costs and benefits for the sample
facilities alone, basing the sample results on known facility
and benefit pathway characteristics. Table ES. 19 presents
the results of this analysis. EPA found that the relationship
between benefits and costs for sample facilities alone (i.e.,
those facilities whose receiving stream characteristics are
known) are similar to that found in the national analysis.
Specifically, in both analyses the low estimate for net
benefits is negative while the midpoint and high estimates
for net benefits are positive. This similarity in the
relationship between benefits and costs in the two analyses
significantly increases EPA's confidence that the benefits of
the regulation exceed the costs, even when the estimated
total value of national benefits has some uncertainties
associated with it.
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MP&M EEBA
Executive Summary
Table ES.19: Comparison of Annual Monetizable Benefits to Social Costs for Sample Facilities
(thousands of 1999$)
Benefit and Cost Categories
Reduced Cancer Risk from Fish Consumption3
Reduced Cancer Risk from Water Consumption3
Reduced Risk from Exposure to Lead
Enhanced Water-Based Recreation
Nonuse Benefits
Avoided Sewage Sludge Disposal Costs
Total Monetized Benefits
Total Monetized Costsb
Net Monetized Benefits (Benefits Minus Costs)0
Low
$17.4
$1,057.1
$2,585.0
$68,990.4
$17,247.6
$7,532.1
$97,429.6
$121,392.9
($23,963.3)
Midpoint
$17.4
$1,057.1 ^
$2,585.0 ^
$108,803.9 ^
$54,402.0 ^
$7,532.4 ^
$174,397.8
$121,392.9
$53,004.9
Proposed Rule
High
$17.4
$1,057.1
$2,585.0
$158,121.1
$104,359.9
$7,532.7
$273,673.2
$121,392.9
$152,280.3
a. The monetary value of benefits from reduced incidence of cancer is based on 1997$.
b. Total monetized costs represent the resource cost of compliance only. This analysis does not include the cost of administering the proposed regulation
and the social cost of unemployment. Excluding these costs does not affect the conclusions of their analysis because these costs are very small relative to
the resource cost of compliance.
c. EPA calculated the low net benefit value by subtracting the high value of costs from the low value of benefits, and calculated the high net benefit value
by subtracting the low value of costs from the high value of benefits. The middle net benefit is based on the midpoint values for costs and benefits.
Source: U.S. EPA analysis.
ES.6 OHIO CASE STUDY
The Ohio case study assesses the costs and benefits of the
proposed rule for the state's facilities and waterbodies. Ohio
is among the ten states with the largest numbers of MP&M
facilities. Ohio has a diverse water resource base and a
more extensive water quality ecological database than many
other states. EPA gathered data on MP&M facilities and on
Ohio's baseline water quality conditions and water-based
recreation activities to support the case study analysis.
These data characterize current water quality conditions,
water quality changes expected from the regulation, and the
expected welfare changes from water quality improvements
at waterbodies affected by MP&M discharges. The case
study also estimates the social costs of the proposed rule for
facilities in Ohio, and compares estimated social costs and
benefits for the State.
The case study analysis supplements the national level
analysis performed for the proposed MP&M regulation in
two important ways:
> the analysis used improved data and methods to
determine MP&M pollutant discharges from both
MP&M facilities and other sources. In particular,
EPA oversampled Ohio with 1,600 screener
questionnaires to augment information on the
State's MP&M facilities. The Agency also used
information from the sampled MP&M facilities to
estimate discharge characteristics of non-sampled
MP&M facilities, as described in Appendix G of
the EEBA.
> the analysis used an original travel cost (TC) study
to value four recreational uses of water resources
affected by the regulation: swimming, fishing,
boating, and near-water activities.
The added detail provides a more complete and reliable
analysis of water quality changes from reduced MP&M
discharges. The study provides more complete estimates of
changes in human welfare resulting from reduced health
risk, enhanced recreational opportunities, and improved
economic productivity.
The case study analysis of recreational benefits combines
water quality modeling with a random utility model (RUM)
to assess how changes in water quality from the regulation
will affect consumers' valuation of water resources. The
RUM analysis addresses a wide range of pollutant types and
effects, including water quality measures not often
addressed in past recreational benefits studies. In particular,
the model supports a more complete analysis of recreational
benefits from reductions in nutrients and toxic pollutants
(i.e., priority pollutants and nonconventional pollutants with
toxic effects).
ES.6.1 Benefits
The use of an original RUM model allows the Agency to
address limitations inherent in benefits transfer used in the
analysis of recreational benefits at the national level. The
use of benefits transfer often requires additional
assumptions because water quality changes evaluated in the
ES-22
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MP&M EEBA
Executive Summary
available recreation demand studies are only roughly
comparable with the water quality measures evaluated for a
particular rule.
The RUM model estimates the effects of the specific water
quality characteristics analyzed for the proposed MP&M
regulation, such as the presence of AWQC exceedances and
concentrations of the nonconventional nutrient Total
Kjeldahl Nitrogen (TKN). This direct link between the
water quality characteristics analyzed for the rule and the
characteristics valued in the RUM analysis reduces
uncertainty in benefit estimates and makes the analysis of
recreational benefits more robust.
In addition to conventional pollutants and TKN, the
proposed MP&M regulation affects a broad range of
pollutants, many of which are toxic to human and aquatic
life but are not directly observable (i.e., priority and non-
conventional pollutants). These unobservable toxic
pollutants degrade aquatic habitats, decrease the size and
abundance offish and other aquatic species, increase fish
deformities, and change watershed species composition.
Changes in toxic pollutant concentrations may therefore
affect recreationists' valuation of water resources, even if
consumers are unaware of changes in ambient pollutant
concentrations.
The study used data from the 1993 National Demand Survey
for Water-Based Recreation (NDS), conducted by EPA and
the National Forest Service, to examine the effects of in-
stream pollutant concentrations on consumers' decisions to
visit a particular waterbody. The analysis estimated baseline
and post-compliance water quality at recreation sites actually
visited by the surveyed consumers and at all other sites
within the consumers' choice set, visited or not. The RUM
analysis of consumer behavior then estimated the effect of
ambient water quality and other site characteristics on the
total number of trips taken for different water-based
recreation activities and the allocation of these trips among
particular recreational sites. The RUM analysis is a TC
model, in which the cost to travel to a particular recreational
site represents the "price" of a visit.
EPA modeled two consumer decisions:
* how many water-based recreational trips to take
during the recreational season (the trip participation
model), and
* which recreation site to choose (the site choice
model).
Combining the trip participation model's prediction of trips
under the baseline and post-compliance scenarios and the
site choice model's per-trip welfare measure provides a
measure of total welfare. EPA calculated each individual's
seasonal welfare gain for each recreation activity from post-
compliance water quality changes, and then used Census
data to aggregate the estimated welfare change to the State
level. The sum of estimated welfare changes over the four
recreation activities yielded estimates of total welfare gain.
EPA estimated other components of benefits in Ohio using
similar methodologies to those used for the national-level
analysis. In addition to the RUM study of recreational
benefits, other analytical improvements included use of the
following:
> more detailed data on MP&M facilities, obtained
from the 1,600 additional surveys;
> data on non-MP&M discharges to estimate current
baseline conditions in the state; and
* a first-order decay model to estimate in-stream
concentrations in the Ohio waterbodies in the
baseline and post-compliance.
The Agency believes that the added level of detail results in
more robust benefit estimates.
Summing the monetary values over all benefit categories
yields total monetized benefits of $181.8 to $298.7 million
(1999$) annually for the proposed option, as shown in Table
ES.20. The midpoint estimate of monetized benefits for the
proposed option is $244.0 million (1999$). Although more
comprehensive than the national benefits analysis, the case
study benefit estimates still omit some mechanisms by which
society is likely to benefit from the proposed rule. Examples
of benefit categories not reflected in the monetized benefits
include non-lead related non-cancer health benefits and
reduced costs of drinking water treatment.
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MP&M EEBA
Executive Summary
Table ES.20: Annual Benefits from
Benefit Category
1 . Reduced Cancer Risk a
Fish Consumption
Water Consumption
2. Reduced Risk from Exposure to Lead:
Children
Adults
3. Enhanced Water-Based Recreation
4. Nonuse Benefits
5. Avoided Sewage Sludge Disposal Costs
Total Monetized Benefits
Reduced MP&M Discharges
(1999$)
Lowj
$57!
$77,40 1!
$32,509!
$25,982!
$145,365,723!
$36,341,431!
$10,000!
$181,853,103!
in Ohio: Proposed
Midpoint!
$182!
$244,587!
$63,856!
$70,661 !
$162,449,204!
$81,224,602!
$10,000!
$244,126,948!
Option
High
$313
$421,062
$96,944
$117,822
$179,532,685
$118,492,572
$10,000
$298,768,342
a. The monetary value of benefits from reduced incidence of cancer is based on 1997$.
Source: U.S. EPA analysis.
ES.6.2 Social Costs
EPA also estimated the social costs of the proposed rule for
MP&M facilities in Ohio. Predicting the number of
regulatory closures is necessary to estimate the costs and
impacts of the regulation on industry and water quality.
Facilities that are baseline closures will not be affected by
the proposed MP&M regulation.
The screener data collected for Ohio facilities did not
provide financial data to perform an after-tax cash flow or
net present value test, as done in the national analysis. EPA
therefore used data from the national analysis to estimate the
percentage of facilities that would close in the baseline and
post-compliance. EPA assumed that the ratio of facilities
that close in the national analysis would be comparable to
that for Ohio facilities with the same discharge status,
subcategory, and flow category. For example, eight percent
of indirect General Metals facilities discharging more than
6.25 million gallons per year close in the baseline in the
national data set; this same percent distribution is assumed
for Ohio screener indirect dischargers in that flow size
category.
EPA developed engineering estimates of compliance costs
for each Ohio facility, and annualized costs using a seven
percent discount rate over a 15-year period. As in the
national social cost analysis, EPA included compliance costs
for facilities that close due to the rule, as well as costs for
facilities that continue to operate subject to the proposed
regulation. Including costs for regulatory closures in effect
calculates the social costs of compliance that would be
incurred if every facility continued to operate post-
regulation. In fact, some facilities find it more economic to
close. For this reason, calculating costs as if all facilities
continue operating provides an upper-bound estimate of
social costs.
EPA used the same methods as used in the national social
cost analysis to estimate other components of social costs
for the Ohio case study. Table ES.21 shows the total
estimated social costs of the proposed rule for Ohio
facilities.
Table ES.21: Annual Social Costs for Ohio Facilities:
Proposed Option (millions 1999$, costs annualized at 7%)
Component of
Social Costs
Resource value of
compliance costs
Government
administrative costs
Social cost of
unemployment
Total Social Cost
Lower bound Midpoint Upper bound
$141.7
$0.011
$.007
$141.7
$0.025
$3.673
$145.4
$0.083
$7.338
$149.1
ES-24
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MP&M EEBA Executive Summary
ES.6.3 Comparing Monetized Benefits " the 1600 Screeners provided information on
locations of MP&M facilities in Ohio allowing the
and COStS Agency to take more accurate account of joint
discharges to the same reach;
The social cost of the proposed rule in Ohio is estimated at
$141.7 to $149.1 million annually (1999$). The sum total of ,. it includes data on non-MP&M discharges in the
benefits that can be valued in dollar terms ranges from baseline and post compliance;
$181.8 million to $298.7 million annually (1999$).
Combining the estimates of social benefits and social costs ,. it includes the affect of MP&M discharges of
yields a net monetizable benefit ranging from $32.7 million nutrients such as TKN;
to $157.0 million annually. Comparing the midpoint
estimate of social costs ($145.4 million) with the midpoint ,. it uses a first-order decay model to estimate in-
estimate of monetizable benefits ($244.1 million) results in a stream concentrations in downstream waterbodies;
net social benefit of $98.7 million. This represents a partial and
cost-benefit comparison because not all of the benefits
resulting from the proposed rule can be valued in dollar ,. it includes an additional recreational benefit
terms. The Ohio case study shows substantial net positive category (swimming) in the analysis.
benefits even for the lower-bound estimate of benefits.
In addition, the RUM model used to estimate recreational
The Ohio case study is more robust than most analyses that benefits allows EPA to estimate the effects of specific water
EPA usually performs for the following reasons: quality characteristics analyzed for the proposed MP&M
regulation, (i.e., the presence of AWQC exceedances.) This
- the study provides more detailed data on MP&M direct link between the water quality characteristics analyzed
facilities than is possible at the national level; for the rule and the characteristics valued in the RUM
analysis reduces uncertainty in benefit estimates and makes
- better water quality data were available for this the analysis of recreational benefits more robust.
state than is usually available;
ES-25
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MP&M EEBA Part I: Introduction and Background Information
Chapter 1: Introduction
Chapter 1: Introduction
INTRODUCTION
The U.S. Environmental Protection Agency (EPA) is
proposing effluent limitations guidelines and standards for
the Metal Products and Machinery (MP&M) Industry, under
Sections 301, 304, 306, 307 and 501 of the Clean Water
Act. EPA has determined that the proposed rule is likely to
result in aggregate costs to the economy that exceed $100
million annually. The Agency therefore found that the
proposed regulation is a "significant regulatory action" as
defined by Executive Order 12866 [58 Federal Register 51,
735 (October 4, 1993)] and has prepared an analysis of the
benefits and costs to society of the proposed rule, as
required by the Executive Order.
1.1 PURPOSE
This report presents the results of EPA's economic analyses
for the proposed rule. These analyses support EPA's
compliance with the requirements of the following statutes
and other rule-making provisions:
> Executive Order 12866 "Regulatory Planning and
Review", which requires analysis of costs,
benefits, and economic impacts of the proposed
rule and regulatory alternatives;
* Unfunded Mandates Reform Act (UMRA), which
requires evaluation of impacts on governments,
among other requirements;
* Regulatory Flexibility Act as amended by the Small
Business Regulatory Enforcement Fairness Act of
1996 (RFA/SBREFA), which requires
consideration of the rule's impact on small firms
and governments;
> Executive Order 12898 "Federal Actions to
Address Environmental Justice in Minority
Populations and Low-Income Populations";
> Executive Order 13084 " Protection of Children
from Environmental Health Risks and Safety
Risks";
* Executive Order 13158 "Marine Protected Areas";
and
CHAPTER CONTENTS:
1.1 Purpose 1-1
1.2 Organization 1-1
1.3 Readers' Aids 1-2
Coastal Zone Act Reauthorization Amendments
(CZARA).
1.2 ORSANIZATTON
This report is organized in five major parts, 22 chapters, and
nine appendices, as follows:
Parti "Introduction and Background Information"
(Chapters 1 though 4) describes the need for the regulation,
provides a profile of the MP&M industry, and describes the
proposed rule and other regulatory options considered by
the Agency.
Part II "Costs and Economic Impacts" (Chapters 5
through 11) presents EPA's analysis of the economic
impacts and social costs of the proposed rule. Chapter 5
presents the basic analysis of costs and impacts at the
facility level. Chapters 6 through 9 present analyses of
other types of economic impacts that derive from the basic
facility-level analysis, including impacts on employment,
governments (supporting EPA's compliance with UMRA),
communities, foreign trade, firms, and new facilities.
Chapter 10 provides an analysis of impacts on small firms
and governments, as required by RFA/SBREFA. Finally,
Chapter 11 presents the social costs of the proposed rule.
Part III "Benefits" (Chapters 12 through 17) provides
EPA's analysis of the environmental impacts and benefits of
the proposed rule. Chapter 12 provides an overview of the
benefits expected from the rule. Chapters 13 through 16
present EPA's analyses of different components of the
benefits analysis. These include human health benefits
(except for lead-related) (Chapter 13), lead-related benefits
(Chapter 14), recreational benefits (Chapter 15), and
benefits to POTWs (Chapter 16). Chapter 17 presents an
analysis of the environmental justice effects of the proposed
rule, as required by Executive Order 12898.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 1: Introduction
Partly "Comparison of Costs and Benefits" (Chapters 18
and 19) compares the social costs and benefits for the
proposed rule (Chapter 18) and for other regulatory
alternatives considered by the Agency (Chapter 19).
Part V " Ohio Case Study" (Chapters 20 through 22)
provides a detailed case study of the proposed rule's costs
and benefits for the State of Ohio. This case study includes
a more detailed and complete analysis of benefits, based on
more complete information on the number and location of
MP&M facilities and the characteristics of affected waters
than was available for the national analyses. The case study
also includes an original travel cost study to value
recreational uses affected by the proposed rule. EPA
believes that the case study provides more robust results
because it avoids the uncertainties that result from the need
to extrapolate sample facility results to the national level.
The results of the case study generally confirm the overall
results of the national analysis.
Appendices to this report provide additional material in
support of the analyses described in the chapters, including
the following:
* Appendix A: supporting material for the profile of
the MP&M industries in Chapter 3;
* Appendix B: description of the cost pass-through
analysis;
* Appendix C: description of the methodology used
to estimate POTW administrative costs;
* Appendix D: summary of MP&M facility pollutant
loadings in the baseline, and after compliance with
the proposed rule;
* Appendix E: discussion of methodologies and
results of the environmental assessment analysis;
* Appendix F: summary of the method used to
extrapolate sample facility results to the national
level;
* Appendix G: description of the fate and transport
model of pollutant releases used in the drinking
water and Ohio analyses;
> Appendix H: analyses of spatial distribution of
benefitting reaches in relation to MP&M facility
location and benefitting population; and
* Appendix I: description of the surface water
valuation studies and specific values selected for
assessing recreational benefits from the proposed
regulation.
Docket W-99-23 for the proposed rule, located at U.S. EPA
Headquarters, provides additional supporting, including:
* copies of the literature cited in the report;
> documentation of the financial and economic
portions of the MP&M Section 308 surveys; and
> datasets, spreadsheets, and programs used to
perform the analyses.
A companion to this document, Cost-Effectiveness Analysis
of Proposed Effluent Limitations Guidelines and Standards
for the Metal Products and Machinery Industry (EPA-821-
B-007), presents a cost-effectiveness analysis for the
proposed rule compared with other regulatory alternatives.
1.3 READERS AIDS
Each chapter includes a chapter-specific table of contents.
A list of references is provided at the end of each chapter.
Glossaries and lists of acronyms are also provided at the
end of the chapters, and the first usage of items listed in
them are denoted in the text with the following formats:
* Glossary indicates that a term is defined in the
chapter glossary, and
* Acronym indicates that the acronym is included
in the chapter list of acronyms.
The glossary and acronym indicators in the text are linked to
the chapter glossary and acronym sections in the .pdf
versions of the report, and can be clicked to access the
definitions.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 2: The MP&M Industry and the Need for Regulation
Chapter 2: The MP&M Industry
and the Need for Regulation
INTRODUCTION
The Metal Products and Machinery (MP&M) regulation will
apply to eight industrial subcategories based on the
production processes used and the wastes they generate.
MP&M subcategories include: general metals, metal
finishing job shops, non-chromium anodizing, printed
wiring board, steel forming & finishing, oily waste, railroad
line maintenance, and shipbuilding dry docks.
The facilities regulated under this rule produce,
manufacture, rebuild, or maintain metal parts, products, or
machines that are used in seventeen different markets.
These market sectors include: hardware, aircraft, aerospace,
ordnance, electronic equipment, stationary industrial
equipment, mobile industrial equipment, buses and trucks,
motor vehicles, household equipment, instruments, office
machines, railroads, ships and boats, precious and non-
precious metals, and other metal products. Most of the
subcategories above serve multiple markets.
This chapter provides an overview of the MP&M industry
and focuses on the pollutant discharges from MP&M
facilities potentially subject to regulation. The chapter also
reviews additional reasons why EPA is proposing to
regulate the industry's effluent discharges. This section
discusses: the need to reduce pollutant discharges from the
MP&M industry, the issue of addressing market
imperfections, the need to achieve a more coherent
regulatory framework for the industry, and requirements that
stem from the Clean Water Act (CWA) and litigation.
2.1 OVERVIEW OF THE FACILITIES
POTENTIALLY SUBJECT TO RESULATION
The proposed regulation will apply to process wastewater
discharges from MP&M sites performing manufacturing,
rebuilding, or maintenance on a metal part, product, or
machine to be used in the industrial sectors listed above.
The rule does not cover non-process wastewater, MP&M
operations that are ancillary activities at facilities outside the
industrial sectors, or MP&M operations when performed at
CHAPTER CONTENTS:
2.1 Overview of the Facilities Potentially Subject to
Regulation 2-1
2.2 MP&M Discharges and the Need For Regulation .. 2-2
2.2.1 Baseline MP&M Discharges 2-3
2.2.2 Discharges under the MP&M Regulation . 2-5
2.3 Addressing Market Imperfections 2-6
2.4 Achieving a More Complete and Coherent Regulatory
Framework for the Metals Industries 2-7
2.5 Meeting Legislative and Litigation-Based
Requirements 2-10
Glossary 2-12
Acronyms 2-14
gasoline stations or vehicle rental facilities.1 The proposed
regulatory requirements are specified for the eight
subcategories noted above, which are defined based on the
unit operations performed and the nature of the waste
generated.
"MP&M facilities" are facilities that produce metal parts,
products or machines for use in one of the market sectors,
using operations covered by one of the eight industrial
subcategories, that discharge process wastewater, either
directly or indirectly, to surface waters. Subcategory
facilities frequently produce products for multiple sectors. It
is important to note that "MP&M facilities", as defined here,
represent only a portion of all facilities in the industrial
sectors, since some facilities may perform operations that
are not covered by one of the subcategories (i.e., part
assembly or plastic molding) and some may not generate or
discharge process wastewater.
1 Section III of the preamble accompanying the proposed rule
provides a more detailed discussion of the scope of the rule.
2-1
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MP&M EEBA Part I: Introduction and Background Information
Chapter 2: The MP&M Industry and the Need for Regulation
Department of Commerce data indicate that there are more
than 1.3 million establishments operating in potential
MP&M industries. These establishments are defined by
approximately 200 SIC codes.2 The MP&M survey results
indicate that there are approximately 85,000 MP&M
facilities that manufacture, rebuild, or repair metal machines,
parts, products, or equipment using processes covered by the
proposed subcategories. Of these 85,000, approximately
22,000 do not use or discharge water or use a contract hauler
for their wastewater. Only 62,752 facilities, or 74.8 percent,
are water-discharging facilities that could be potentially
subject to the MP&M regulation. These 62,752 water-
discharging facilities include 57,948 indirect dischargers
(i.e., facilities discharging effluent to a publicly-owned
sewage treatment works or POTWs) that would be
subject to Pretreatment Standards for Existing Sources
(PSES). The remaining 4,804 facilities are direct
dischargers (i.e., they discharge effluent directly to a
waterway under a National Pollutant Discharge Elimination
System (NPDES) permit) and would thus be subject to
Best Available Technology Economically
Achievable (BAT) and Best Practicable Control
Technology Currently Available (BPT) requirements.
Of the 62,752 water discharging facilities, 3,7663 are
predicted to close in the baseline, leaving 58,986 existing
facilities that EPA estimates could be regulated.4 The
proposed rule would regulate 9,839 of these facilities,
including 5,186 indirect discharging facilities and 4,653
direct dischargers. The estimated 9,839 water-discharging
facilities that are regulated under the preferred option
represent less than 0.8 percent of all facilities in the MP&M
industries, and 15.7 percent of those that are potentially
regulated. Table 2.1 summarizes important information on
2 Appendix A provides a list of the SIC codes in each industry
sector.
3 This figure excludes an estimated 64 facilities that EPA
predicts would close in the baseline but that are expected to
continue operations under the proposed rule. Chapter 5 explains
the impact of potential revenue increases resulting from market
adjustments to the rule that may result in such "avoided closures."
4 These are facilities that are predicted to close due to weak
financial performance under baseline conditions, i.e., in the
absence of the proposed rule. EPA does not attribute the costs or
the reduced discharges resulting from these baseline closures to the
proposed rule, and therefore excludes these facilities from its
analyses of the rule's impacts. Baseline closures account for
differences between the universe of facilities discussed in this
report and the universe discussed in Section IV of the preamble and
the Technical Development Document.
the total number of MP&M facilities that could potentially
be regulated, and the number that would be regulated under
the proposed rule.
Table 2.1 shows that a substantial portion (52,762 or 91
percent) of the potentially-regulated indirect dischargers will
not be subject to requirements under the proposed rule. EPA
proposes to exclude indirect dischargers below certain low
thresholds in the General Metals and Oily Waste
subcategories (20,164 and 28,092, respectively). The
Agency also proposes to exclude indirect dischargers in
three subcategories whose effluents are not expected to
present significant environmental harm when discharged
through POTWs (150 Non-Chromium Anodizing, 799
Railroad Line Maintenance, and 6 Shipbuilding Dry Dock
facilities).5 The proposed rule will regulate 4,653 direct
dischargers ~ all of the direct discharging MP&M facilities
that continue to operate in the baseline.
2.2 MP&M DISCHARGES AN& THE NEED
FOR RESULATION
EPA is regulating the MP&M industry because the industry
releases substantial quantities of pollutants, including toxic
pollutant compounds (priority and nonconventional metals
and organics) and conventional pollutants such as total
suspended solids (TSS) and oil and grease (O&G).
These MP&M industry pollutants are generally controlled
by straightforward and widely-used treatment system
technologies such as chemical precipitation and clarification
(frequently referred to as the lime and settle process).6
Discharges of these pollutants to surface waters and POTWs
have a number of adverse effects, including degradation of
aquatic habitats, reduced survivability and diversity of native
aquatic life, and increased human health risk through the
consumption of contaminated fish and water. In addition,
many of these pollutants volatilize into the air, disrupt
biological wastewater treatment systems, and contaminate
sewage sludge.
5 Also excluded are 3,614 (out of the 57,948) indirect
dischargers EPA predicts will close in the baseline, and an
additional 151 direct dischargers predicted to close in the baseline.
6 See Chapter 12 and Appendix E for more detailed
information on the pollutants of concern in the MP&M industry.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 2: The MP&M Industry and the Need for Regulation
Table 2.1: Summary of MP&M Facilities Potentially and Actually Regulated
Under the Proposed Rule
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Indirect Dischargers
Water Dischargers
(# of facilities)
26,191
1,514
190
624
110
28,514
799
6
57,948
Regulated under
Proposed Rule
(# of facilities)
3,103
1,231
0
621
105
126
0
0
5,186
Direct Dischargers
Water Dischargers
(# of facilities)
3,784
15
0
11
43
911
34
6
4,804
Regulated under
Proposed Rule
(# of facilities)
3,636
12
0
11
43
911
34
6
4,653
Source: U.S. EPA analysis.
Metal constituents are of particular concern because of the
large amounts present in MP&M effluents. Unlike some
organic compounds and other wastes that are metabolized in
activated sludge systems to relatively innocuous
constituents, metals are elements and cannot be eliminated.
Moreover, in solution, some metals have a high affinity for
biological uptake. Depending on site-specific conditions,
metals form insoluble inorganic and organic complexes that
partition to sewage sludge at POTWs or underlying sediment
in aquatic ecosystems. The accumulated metal constituents
can return to a bioavailable form upon land application of
sewage sludge; dredging and resuspension of sediment; or as
a result of seasonal, natural, or induced alteration of
sediment chemistry.
Benefits of reducing metal and other pollutant loads to the
environment from MP&M facilities include reduced risk of
cancer and systemic human health risks, improved recreation
opportunities (e.g., fishing , swimming, boating, and other
near-water recreational activities), improved aquatic and
benthic habitats, and less costly sewage sludge disposal and
increased beneficial use of the sludge.7
The goal of the MP&M regulation is to reduce pollutant
discharges and to eliminate or reduce the level of risk and
harm caused by them. These pollutant discharges and their
harmful consequences are the externalities that the
MP&M regulation addresses, as discussed in Section 2.3.
2.2.1 Baseline MP&M Discharges
Tables 2.2 and 2.3 provide an overview of the discharges
from MP&M facilities that are potentially regulated under
the proposed rule. Loadings are defined as toxic-
weighted loadings. This measure weights quantities of
different pollutants in effluents by a measure of their relative
toxicity. Toxic-weighted loadings measures the relative
toxic effects of discharges containing different mixtures of
pollutants. MP&M discharges also contain conventional
pollutants with little or no toxic effects that nonetheless can
have adverse environmental impacts, such as O&G and
some components of TSS. Tables 2.2 and 2.3 present
discharges at baseline and under the proposed rule not
the effect of the pollutants.
Sewage sludge is also called biosolids.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 2: The MP&M Industry and the Need for Regulation
Table 2.2: Toxic- Weighted Discharges for Potentially Regulated MP&M Facilities and
Those Regulated under the Proposed Rule
Indirect Dischargers0 (Pounds Equivalent)
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Baseline Discharges
28,370,265
6,352,993
54,517
409,588
656,688
377,567
1,757
831
39,910,106
# Facilities in the
Baseline
23,204
1,231
150
621
105
28,219
799
6
54,333
Average Baseline
Loadings per
Facility
1,223
5,161
363
6,595
6,254
13
2
139
735
Remaining
Discharges
Under Proposed
Rule
20,550,241
1,978,438
54,517
2,563,010
427,646
348,803
1,757
831
25,925,243
* Excludes dischargers from facilities that are projected to close in the baseline (5,312,613 Ibs-equiv., or an average of 1,470 Ibs-equiv. per closing
facility). Discharges discussed in this table are total discharges from the facility, and do not reflect POTW pollutant removals. EPA believes it is
appropriate to analyze wastewater discharges disregarding the POTW removals because indirect discharges present environmental risks that are not fully
addressed by POTW treatment. The MP&M industry releases 89 pollutants that cause inhibition problems at POTWs and an additional 35 hazardous
air pollutants (HAPs) that may present a threat to human health or the environment. Other MP&M pollutants are found POTW in sludge. Only eight
of these pollutants have land application pollutant criteria that limit the uses of sludge.
Source: U.S. EPA analysis.
The large number of General Metals facilities account for
over 71 percent of total toxic-weighted baseline loadings
from facilities that continue to operate in the baseline,
followed by Metal Finishing Job Shop facilities (16
percent), and Printed Wiring Board facilities (10 percent).
On a per-facility basis, however, the largest toxic-weighted
discharges come from Printed Wiring Board, Steel Forming
& Finishing and Metal Finishing Job Shop facilities. These
facilities discharge an average of 5,000 to over 6,000 Ibs
equivalent each, compared with an average per facility
discharge of 735 Ibs equivalent for the potentially regulated
MP&M facilities as a whole.
Table 2.3 provides the same information for direct
discharging facilities. The large number of General Metals
direct dischargers again account for the majority (64
percent) of total toxic-weighted discharges in the baseline.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 2: The MP&M Industry and the Need for Regulation
Table 2.3: Toxic- Weighted Discharges for Potentially Regulated MP&M Facilities and
Those Regulated under the Proposed Rule
Direct Dischargers" (Pounds Equivalent)
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Baseline Discharges
1,486,108
22,496
142,535
626,274
40,634
1,267
2,667
2,321,981
# Facilities in the
Baseline
3,636
12
11
43
911
34
6
4,653
Average Baseline
Loadings per
Facility
409
1,875
12,958
14,565
45
37
445
499
Remaining
Discharges
Under Proposed
Rule
586,837
8,301
77,962
28,126
24,564
1,093
2,556
988,439
* Excludes dischargers from facilities that are projected to close in the baseline (1,780,229 Ibs-equiv., or an average of 5,167 Ibs-equiv. per closing
facility). Discharges discussed in this table are total discharges from the facility, and do not account for POTW pollutant removals. EPA believes it is
appropriate to analyze wastewater discharges disregarding the POTW removals because indirect discharges present environmental risks that are not fully
addressed by POTW treatment. The MP&M industry releases 89 pollutants that cause inhibition problems at POTWs and an additional 35 hazardous
air pollutants (HAPs) that may present a threat to human health or the environment. Other MP&M pollutants released by the industry are found in POTW
sludge. Only eight of these pollutants have land application pollutant criteria that limit the uses of sludge.
Source: U.S. EPA analysis.
2.2.2 Discharges under the MP&M
Regulation
Tables 2.2 and 2.3 also show the toxic loadings that would
remain after implementation of the proposed rule, for
indirect and direct dischargers respectively. These
reductions result from increased treatment of effluents and
pollution prevention at facilities that continue to operate
subject to the regulation, and from the elimination of
discharges at facilities that close as a result of the rule. The
proposed rule would eliminate 35 percent of the baseline
toxic-weighted discharges from indirect dischargers and 57
percent of the baseline loadings from direct dischargers.
Additional information on the environmental effects of the
proposed rule and two other options can be found in Part
III: Environmental Impacts and Benefits of this report, and
in Appendix E.
Table 2.4 shows baseline and post-regulation loadings by
type of pollutant, both as unweighted pounds and on a toxic-
weighted basis, for facilities that are regulated under the
proposed rule. The facilities that are regulated account for
70 percent of the baseline toxic-weighted releases from all
potentially-regulated facilities. The proposed rule eliminates
89 percent of the baseline toxic-weighted loadings from the
facilities that are regulated, including 92 percent of the
priority pollutants (91 percent of the metals, 52 percent
of the organics, and 99 percent of the cyanide) and 81
percent of the nonconventional pollutants (82 percent
of the metals and 30 percent of the organics). The proposed
rule also eliminates substantial portions of the baseline
discharges of conventional pollutants from the regulated
facilities, including 75 percent of the chemical oxygen
demand (COD). 90 percent of the O&G, and 88 percent of
the TSS.8
8 It is not possible to provide an overall estimate of total
pollutant pounds removed, because overlap among some of the
pollutant categories would result in double-counting if the
categories were summed. For example, TSS may include some of
the priority pollutant and nonconventional metals discharges. Use
of the toxic-weighted loadings avoids this double-counting, but
does not include conventional pollutants.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 2: The MP&M Industry and the Need for Regulation
Table 2.4: Summary of Discharges by Pollutant Type for Facilities Regulated under the Proposed Rule"
Pollutant Category
Priority Pollutants
Metals
Organics
Cyanide (CN)
Nonconventional Pollutants
Metals
Organics
Conventional Pollutants
COD
O&G
TSS
Current Releases
Pounds
34,527,668
2,095,832
4,718,247
120,756,930
50,468,179
2,445,579,193
220,782,391
231,466,565
Pounds Eq.
16,476,843
323,410
5,190,072
7,201,034
210,501
Releases under The Proposed
Rule
Pounds
2,018,185
1,024,636
35,881
23,723,669
9,411,727
601,888,710
20,953,718
27,404,519
Pounds Eq.
1,500,230
156,560
39,469
1,265,904
146,873
Proposed Rule Reductions
Pounds
32,509,483
1,071,196
4,682,366
97,033,261
41,056,452
1,843,690,483
199,828,673
204,062,046
Pounds Eq.
14,976,613
166,850
5,150,603
5,935,130
63,628
* Discharges discussed in this table are facility discharges and do not account for POTW removals. EPA believes it is appropriate to analyze wastewater
discharges disregarding the POTW removals because indirect discharges present environmental risks that are not fully addressed by POTW treatment.
The MP&M industry releases 89 pollutants that cause inhibition problems at POTWs and an additional 35 hazardous air pollutants (HAPs) that may
present a threat to human health or the environment. Other MP&M pollutants released by the industry are found in POTW sludge. Only eight of these
pollutants have land application pollutant criteria that limit the uses of sludge.
Source: U.S. EPA analysis.
2.3 A&&RESSINS MARKET
IMPERFECTIONS
Environmental legislation in general, and the CWA and the
MP&M regulation in particular, seek to correct
imperfections uncompensated environmental
externalities in the functioning of the market economy. In
manufacturing, rebuilding, and repairing metal products and
machinery, MP&M facilities release pollutants that increase
risks to human health and aquatic life and cause other
environmental harm without accounting for the
consequences of these actions on other parties (sometimes
referred to as third parties) who do not directly participate
in the business transactions of the business entities.
These costs are not borne by the responsible entities and are
therefore external to the production and pricing decisions of
the responsible entity.
A profit-maximizing firm or a cost-minimizing government-
owned facility will ignore these costs when deciding how
much to produce and how to produce it. In addition, the
externality is uncompensated because no party is
compensated for the adverse consequences of the pollution
releases.
When these external costs are not accounted for in the
production and pricing decisions of the responsible entities,
their decisions will yield a mix and quantity of goods and
services in the economy, and an allocation of economic
resources to production activities, that are less than optimal.
In particular, the quantity of pollution and related
environmental harm caused by the activities of the
responsible entities will, in general, exceed socially
optimal levels. As a result, society will not maximize
total social welfare.
In addition, adverse distributional effects may
accompany the uncompensated environmental externalities.
If the distribution of pollution and environmental harm is
not random among the U.S. population, but instead is
concentrated among certain population subgroups based on
socio-economic or other demographic characteristics, then
the uncompensated environmental externalities may produce
undesirable transfers of economic welfare among subgroups
of the population. See Chapter 17: Environmental Justice
and Protection of Children for more information.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 2: The MP&M Industry and the Need for Regulation
The goal of environmental legislation and implementing
regulations, including the proposed MP&M rule that is the
subject of this EEBA, is to correct these environmental
externalities by requiring businesses and other polluting
entities to reduce their pollution and environmental harm.
Congress, in enacting the authorizing legislation, and EPA,
in promulgating the implementing regulations, act on behalf
of society to achieve a mix of goods and services and a level
of pollution that more nearly approximates socially optimal
levels. As a result, the mix and quantity of goods and
services provided by the economy, the allocation of
economic resources to those activities, and the quantity of
pollution and environmental harm accompanying those
activities will yield higher net economic welfare to society.
Requiring polluting entities to reduce levels of pollution and
environmental harm is one approach to addressing the
problem of environmental externalities. This approach
imposes costs on the polluting entities in the form of
compliance costs incurred to reduce pollution to allowed
levels. A polluting entity will either incur the costs of
meeting the regulatory limits or will determine that
compliance is not in its best financial interest and will cease
the pollution-generating activities. This approach to
addressing the problem of environmental externalities will
generally result in improved economic efficiency and net
welfare gains for society if the cost of reducing the pollution
and environmental harm activities is less than the value of
benefits to society from the reduced pollution and
environmental harm.
It is theoretically possible to correct the market imperfection
by means other than direct regulation. For example,
negotiation and/or litigation could achieve an optimal
allocation of economic resources and mix of production
activities within the economy. However, the transaction
costs of assembling the affected parties and involving them
in the negotiation/litigation process, as well as the public
goods character of the improvement sought by negotiation or
litigation, make this approach impractical.
2.4 ACHIEVINS A MORE COMPLETE AND
COHERENT RESULATORY FRAMEWORK FOR
THE METALS INDUSTRIES
The MP&M regulation will help to achieve a more coherent
regulatory framework for the effluent discharge limitations
that apply to the MP&M industry and other metals industries
whose operations may overlap with the MP&M industry.
EPA has previously promulgated effluent guidelines
regulations for thirteen metals-related industries. In some
instances, these industries may perform operations that are
found in MP&M facilities. These effluent guidelines are:
- Electroplating (40 CFR Part 413),
- Iron & Steel Manufacturing (40 CFR Part 420),
> Nonferrous Metals Manufacturing (40 CFR Part
421),
> Ferroalloy Manufacturing (40 CFR Part 424),
- Metal Finishing (40 CFR Part 433),
- Battery Manufacturing (40 CFR Part 461),
- Metal Molding & Casting (40 CFR Part 464),
- Coil Coating (40 CFR Part 465),
- Porcelain Enameling (40 CFR Part 466),
- Aluminum Forming (40 CFR Part 467),
- Copper Forming (40 CFR Part 468),
* Electrical & Electronic Components (40 CFR Part
469), and
* Nonferrous Metals Forming & Metal Powders (40
CFR Part 471).
In 1986, the Agency reviewed coverage of these regulations
and identified a significant number of metals processing
facilities discharging wastewater that these 13 regulations
did not cover. Based on this review, EPA performed a more
detailed analysis of these unregulated sites and identified the
discharge of significant amounts of pollutants. This analysis
resulted in the formation of the "Machinery Manufacturing
and Rebuilding" (MM&R) point source category. In 1992,
EPA changed the name of the category to "Metal Products
and Machinery" (MP&M) to clarify coverage of the
category (57 FR 19748).
EPA recognizes that in some cases unit operations
performed in industries covered by the existing effluent
guidelines are the same as unit operations performed at
MP&M facilities. In general, where unit operations and
their associated wastewater discharges are already covered
by an existing effluent guideline, they will remain covered
under that effluent guideline. (See 40 CFR438. l(b)).
However, some facilities currently regulated under the
existing Electroplating (40 CFR 413) and Metal Finishing
(40 CFR 433) effluent guidelines will be covered by the
MP&M regulation instead. EPA is proposing to replace the
existing Electroplating (40 CFR 413) and Metal Finishing
(40 CFR 433) effluent guidelines with the MP&M
regulations for all facilities in the Printed Wiring Board
subcategory and the Metal Finishing Job Shops
subcategories (see Table 2.5).
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MP&M EEBA Part I: Introduction and Background Information
Chapter 2: The MP&M Industry and the Need for Regulation
When a facility covered by an existing metals effluent
guideline (other than Electroplating or Metal Finishing)
discharges wastewater from unit operations not covered
under that existing metals guideline but covered under
MP&M, it will need to comply with both regulations (see 40
CFR 438. l(c)). In those cases, the permit writer or control
authority (e.g., Publicly Owned Treatment Works) will
combine the limitations using an approach that proportions
the limitations based on the different in-scope production
levels (for production-based standards) or wastewater flows.
POTWs refer to this approach as the "combined wastestream
formula" (40 CFR 403.6(e)), while NPDES permit writers
refer to it as the "building block approach". Permit writers
and local control authorities currently issue permits and
control mechanisms for many facilities in other effluent
guidelines categories where overlaps with more than one
effluent limitation guidelines regulation occur (e.g., Organic
Chemicals, Plastics, and Synthetic Fibers; Pesticide
Manufacturing; Pesticide Formulating, Packaging, and
Repackaging; and Pharmaceutical Manufacturing).
EPA does not intend the preceding table to be exhaustive,
but rather to provide a general overview of the proposed
applicability of the Electroplating, Metal Finishing, and
Metal Products & Machinery effluent guidelines.
Figure 2.1 illustrates the relationship among the various
metals industries effluent guidelines.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 2: The MP&M Industry and the Need for Regulation
Subcategory
General Metals
Metal Finishing Job
Shops
Non-Chromium
Anodizing3
Printed Wiring
Board (Printed
Circuit Board)
Steel Forming &
Finishing
Oily Waste
Railroad Line
Maintenance
Shipbuilding Dry
Docks
Proposing to Continue Coverage
under 40 CFR Part 4 13
(Electroplating)
none
none (see non-chromium anodizing)
Existing indirect dischargers that are
currently covered by 413 AND that only
perform non-chromium anodizing (or do
not commingle their non-chromium
anodizing wastewater with other process
wastewater for discharge).
none
N/A
N/A
N/A
N/A
Table 2.5: Proposed Coverage by MP&M
Proposing to Continue Coverage under
40 CFR Part 433 (Metal Finishing)
Existing facilities that are currently covered (or
new facilities that would be covered) by 433 AND
are indirect dischargers that introduce less than or
equal to 1 million gallons per year into POTW.
none (see non-chromium anodizing)
New and existing indirect dischargers (not
covered by 413) that only perform non-chromium
anodizing (or do not commingle their non-
chromium anodizing wastewater with other
process wastewater for discharge).
none
N/A
N/A
N/A
N/A
Subcategory
Proposing Coverage under 40 CFR Part 438
(Metal Products & Machinery)
All new and existing direct dischargers in this Subcategory regardless of annual
wastewater discharge volume and all new and existing indirect dischargers in this
Subcategory with annual wastewater discharges greater than 1 million gallons per
year.
All new and existing direct and indirect dischargers under this Subcategory. These
facilities would no longer be covered by 413 or 433.
Existing and new direct dischargers that only perform non-chromium anodizing (or
do not commingle their non-chromium anodizing wastewater with other process
wastewater for discharge).
All new and existing direct and indirect dischargers under this Subcategory. These
facilities would no longer be covered by 413 or 433.
All new and existing direct and indirect discharges under this Subcategory as
described.
All new and existing direct and indirect dischargers under this Subcategory as
described.
This Subcategory excludes new and existing indirect dischargers that introduce less
than or equal to 2 MGY into a POTW. Facilities under the cutoff are not and will
not be covered by national categorical regulations.
All new and existing direct dischargers under this Subcategory as described.
There are no national categorical pretreatment standards for these facilities.
All new and existing direct dischargers under this Subcategory as described.
There are no national categorical pretreatment standards for these facilities.
* Facilities that perform anodizing with chromium or with dichromate sealants (or commingle their non-chromium anodizing process wastewater with wastewater from other MP&M subcategories) all fall
under the Metal Finishing Job Shop Subcategory and will only be covered by 438.
b Includes cold forming of steel wire, bars, rods, pipes, and tubes.
Source: U.S. EPA analysis.
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Figure 2.1: Metals Industries Effluent Guidelines Covered Under 40CFR
Mining
I
Manufacturing
Iron and Steel (420)
Nonferrous Metals (421) Ferroalloys (424)
Forming
Iron & Steel (420)
Metal Molding and Coating (454)
Aluminum Forming (467)
Copper Forming (468)
Nonferrous Forming (471)
I
Equipment Manufacturing, Assembly, Rebuilding, Maintenance & Surface Finishing
AAP&AA (438)
Metal Products and
Machinery Industry
(Manufacturing,
Rebuilding,
and Repair)*
Surface Finishing
Metal Finishing (433)
Electroplating (413)
Metal Parts, Products, & Machines
Mill Products
Coil Coating (465)
Battery Manufacturing (461)
Porcelain Enameling (466)
Electrical and Electronic Components (469)
* Includes cold forming of steel wire, bars, rods, pipes, and tubes.
Source: U.S. EPA analysis.
2.5 MEETINS LESISLATTVE AND
UTTSATTON-BASED REQUIREMENTS
EPA is proposing effluent limitations guidelines and
standards for the MP&M industry under authority of the
CWA, Sections 301, 304, 306, 307, and 501. These CWA
sections require the EPA Administrator to publish
limitations and guidelines for controlling industrial effluent
discharges consistent with the overall CWA objective to
"restore and maintain the chemical, physical, and biological
integrity of the Nation's waters." EPA's proposal of the
MP&M industry regulation responds to these requirements.
In addition, the proposed MP&M regulation responds to the
requirements of a consent decree entered by the Agency as a
result of litigation. Section 304(m) of the CWA (33 U.S.C.
1314(m)), added by the Water Quality Act of 1987, required
EPA to establish schedules for (i) reviewing and revising
existing effluent limitations guidelines and standards, and
(ii) promulgating new effluent guidelines. On January 2,
1990, EPA published an Effluent Guidelines Plan (55 FR
80), in which schedules were established for developing new
and revised effluent guidelines for several industry
categories. One of the industries for which the Agency
established a schedule was the Machinery Manufacturing
and Rebuilding Category (MM&R).9
The Natural Resources Defense Council, Inc. (NRDC) and
Public Citizen, Inc. challenged the Effluent Guidelines Plan
in a suit filed in U.S. District Court for the District of
Columbia (NRDC et al v. Reilly, Civ. No. 89-2980). The
plaintiffs charged that EPA's plan did not meet the
requirements of Section 304(m). A Consent Decree in this
litigation was entered by the Court on January 31, 1992.
This plan required, among other things, that EPA propose
effluent guidelines for the MP&M category by November,
1994 and take final action on these effluent guidelines by
May, 1996. EPA filed a motion with the Court on
September 28, 1994, requesting an extension until March
31, 1995, for the EPA Administrator to sign the proposed
regulation and a subsequent four month extension for
signature of the final regulation in September 1996. EPA
9 The name was changed to Metal Products and Machinery
(MP&M) in 1992 to avoid confusion over what was covered by the
rule.
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Chapter 2: The MP&M Industry and the Need for Regulation
published a proposal entitled, "Effluent Limitations
Guidelines, Pretreatment Standards, and New Source
Performance Standards: Metal Products and Machinery" (60
FR 28210) on May 30, 1995.
EPA initially divided the industry into two phases based on
industrial sector, as the Agency believed that would make
the regulation more manageable. The Phase I proposal
included the following industry sectors: Aerospace;
Aircraft; Electronic Equipment; Hardware; Mobile
Industrial Equipment; Ordnance; and Stationary Industrial
Equipment. At that time, EPA planned to propose a rule for
the Phase II sectors approximately three years after the
MP&M Phase I proposal.
EPA received over 4,000 pages of public comment on the
Phase I proposal. One area where commenters from all
stakeholder groups (i.e., industry, environmental groups, and
regulators) were in agreement was that EPA should not
divide the industry into two separate regulations.
Commenters raised concerns regarding the regulation of
similar facilities with different compliance schedules and
potentially different limitations for similar processes based
solely on whether the facilities were in a Phase I or Phase II
MP&M industrial sector. Furthermore, a large number of
facilities performed work in multiple sectors. In such cases,
permit writers and control authorities (e.g., POTWs) would
need to decide which MP&M rule (Phase I or 2) applied to a
facility.
Based on these comments, EPA decided to combine the two
phases of the regulation into one proposal. The proposal
addressed by this report completely replaces the 1995
proposal. Under the 304(m) decree as amended, these
MP&M rules are to be promulgated in December 2002.
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Chapter 2: The MP&M Industry and the Need for Regulation
GLOSSARY
Best Available Technology Economically
Achievable: Effluent limitations for direct dischargers,
addressing priority and non-conventional pollutants. BAT is
based on the best existing economically achievable
performance of plants in the industrial subcategory or
category. Factors considered in assessing BAT include the
cost of achieving BAT effluent reductions, the age of
equipment and facilities involved, the processes employed,
engineering aspects of the control technology, potential
process changes, non-water quality environmental impacts
(including energy requirements), economic achievability,
and such factors as the Administrator deems appropriate.
The Agency may base BAT limitations upon effluent
reductions attainable through changes in a facility's
processes and operations. Where existing performance is
uniformly inadequate, EPA may base BAT upon technology
transferred from a different subcategory within an industry
or from another industrial category.
Best Practicable Control Technology Currently
Available: Effluent limitations for direct discharging
facilities, addressing conventional, toxic, and non-
conventional pollutants. In specifying BPT, EPA considers
the cost of achieving effluent reductions in relation to the
effluent reduction benefits. The Agency also considers the
age of the equipment and facilities, the processes employed
and any required process changes, engineering aspects of the
control technologies, non-water quality environmental
impacts (including energy requirements), and such other
factors as the Agency deems appropriate. Limitations are
traditionally based on the average of the best performances
of facilities within the industry of various ages, sizes,
processes, or other common characteristics. Where existing
performance is uniformly inadequate, EPA may require
higher levels of control than currently in place in an
industrial category if the Agency determines that the
technology can be practically applied.
bioavailable: Degree of ability to be absorbed and ready
to interact in organism metabolism.
(http://www.epa.gov/OCEPAterms)
chemical oxygen demand: A measure of the oxygen
required to oxidize all compounds, both organic and
inorganic, in water.
(http://www.epa.gov/OCEPAterms/cterms.htm)
Clean Water Act: Act passed by the U.S. Congress to
control water pollution. Formerly referred to as the Federal
Water Pollution Control Act of 1972 or Federal Water
Pollution Control Act Amendments of 1972 (Public Law 92-
500), 33 U.S.C. 1251 et. seq., as amended by: Public Law
96-483; Public Law 97-117; Public Laws 95-217, 97-117,
97-440, and 100-04.
conventional pollutants: Statutorily listed pollutants
understood well by scientists. These may be in the form of
organic waste, sediment, acid, bacteria, viruses, nutrients, oil
and grease, or heat.
(http://www.epa.gov/OCEPAterms)
distributional effects: Occurs when the distribution of
pollution and environmental harm is not random among the
U.S. population, but instead is concentrated among certain
population subgroups based on socio-economic or other
demographic characteristics, then the uncompensated
environmental externalities may produce undesirable
transfers of economic welfare among subgroups of the
population.
externalities: Costs or benefits of market transactions that
are not reflected in the prices buyers and sellers use to make
their decisions. An externality is a by-product of the
production or consumption of a good or service that affects
someone not immediately involved in the transaction.
(http://www.enmu.edu/users/biced/home/glossary.html)
A type of market failure that causes inefficiency.
(http://www.amosweb.com/cgi-bin/gls_dsp.pl?term=external
ities)
nonconventional pollutants: Any pollutant not
Statutorily listed or which is poorly understood by the
scientific community.
(http://www.epa.gov/OCEPAterms)
oil and gas (O&G): These organic substances may
include hydrocarbons, fats, oils, waxes and high-molecular
fatty acids. Oil and grease may produce sludge solids that
are difficult to process.
(http://www.epa.gov/owmitnet/reg.htm)
Pretreatment Standards for Existing Sources
(PSES): Categorical pretreatment standards for existing
indirect dischargers, designed to prevent the discharge of
pollutants that pass through, interfere with, or are otherwise
incompatible with the operation of POTWs. Standards are
technology-based and analogous to BAT effluent limitations
guidelines.
priority pollutants: 126 individual chemicals that EPA
routinely analyzes when assessing contaminated surface
water, sediment, groundwater or soil samples.
publicly-owned treatment works: A treatment works
for municipal sewage or liquid industrial wastes that is
owned by a State or municipality.
socially optimal level: Situation in which it is
impossible to make any individual better off without making
someone else worse off. Also referred to as Pareto optimal.
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Chapter 2: The MP&M Industry and the Need for Regulation
social welfare: The sum of the welfare of all participants
in the society; measured by the sum of consumer surplus ~
the value consumers derive from goods and services less the
price they have to pay for the goods and services ~ and
producers' surplus ~ the revenue received by producers of
goods and services less their costs of producing the goods
and services.
third parties: Those affected by a by-product of the
production or consumption of a good or service that are not
immediately involved in the transaction.
total suspended solids: A measure of the suspended
solids in wastewater, effluent, or water bodies, determined
by tests for "total suspended non-filterable solids."
(http://www.epa.gov/OCEPAterms/tterms.html).
toxic-weighted pollutants: This measure weights
quantities of different pollutants in effluents by a measure of
their relative toxicity. Toxic-weighted loadings measures
the relative toxic effects of discharges containing different
mixtures of pollutants.
uncompensated: Where parties damaged by externalities
receive no compensation for accepting the damage.
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MP&M EEBA Part I: Introduction and Background Information Chapter 2: The MP&M Industry and the Need for Regulation
ACRONYMS
BAT: Best Available Technology Economically Achievable NPDES: National Pollutant Discharge Elimination System
BPT: Best Practicable Control Technology Currently NRDC: Natural Resources Defense Council
Available O&G: oil and grease
COD: chemical oxygen demand POTW: publicly-owned treatment works
CWA: Clean Water Act PSES: Pretreatment Standards for Existing Sources
MM&R: Machinery Manufacturing and Rebuilding TSS: total suspended solids
MP&M: Metal Products and Machinery
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
Chapter 3:
Profile of the MP&M Industries
INTRODUCTION
The proposed MP&M rule would apply to facilities that
manufacture, rebuild, or maintain metal parts, products or
machines to be used in a large number of industrial sectors.
Manufacturing is the series of unit operations necessary to
produce metal products, and is generally performed in a
production environment. Rebuilding/maintenance is the
series of unit operations necessary to disassemble used metal
products into components, replace the components or
subassemblies or restore them to original function, and
reassemble the metal product. These operations are intended
to keep metal products in operating condition and can be
performed in either a production or a non-production
environment. Manufacturing and rebuilding/maintenance
activities often occur at the same facilities.
The MP&M industry encompasses a large number of
industries that manufacture intermediate and final goods,
support transportation and other vehicle services, and repair
and maintain products and equipment. The health of the
MP&M industries is generally tied to the overall economic
performance of the economy. The MP&M industry includes
manufacturing and non-manufacturing industries defined by
224 4-digit Standard Industrial Classification (SIC)
codes, which are grouped into nineteen sectors.1 Of the 224
SIC codes, 174 are manufacturing (SICs 20 through 39) and
50 are non-manufacturing. All nineteen sectors include
manufacturing industries, and eleven include non-
manufacturing industries as well.
This chapter provides a profile of the sectors potentially
affected by the proposed MP&M rule. The profile focuses
on the economic characteristics of these sectors, and the
regulated facilities within these sectors, which may affect the
financial and economic impacts of the proposed rule.
3.1 DATA SOURCES
This profile presents data from the Economic Censuses,
Statistics of U.S. Businesses (SUSB), and Annual Survey of
CHAPTER CONTENTS;
3.1 Data Sources
3.2 Overview of the MP&M Industry and Industry
Trends
3.2.1 Aerospace
3.2.2 Aircraft
3.2.3 Electronic Equipment
3.2.4 Hardware
3.2.5 Household Equipment
3.2.6 Instruments
3.2.7 Iron and Steel
3.2.8 Job Shops
3.2.9 Motor Vehicle and Bus & Truck
3.2.10 Mobile Industrial Equipment
3.2.11 Office Machine
3.2.12 Precious Metals and Jewelry
3.2.13 Printed Wiring Boards
3.2.14 Railroad
3.2.15 Ships and Boats
3.2.16 Stationary Industrial Equipment
3.3 Characteristics of MP&M Manufacturing
Sectors
3.3.1 Domestic Production
3.3.2 Industry Structure and Competitiveness
3.3.3 Financial Condition and Performance .
3.4 Characteristics of MP&M Non-Manufacturing
Sectors
3.4.1 Domestic Production
3.4.2 Industry Structure and Competitiveness
3.5 Characteristics of Potentially-Regulated
MP&M Facilities
Glossary
Acronyms
References
3-1
3-2
3-5
3-6
3-6
3-6
3-7
3-7
3-7
3-8
3-8
3-8
3-8
3-9
3-9
3-9
3-9
3-10
10
11
16
19
20
20
22
24
28
30
31
1 Appendix A lists the nineteen sectors and their associated 4-
digit SIC codes.
Manufactures (ASM), the U.S. Industry and Trade Outlook,
EPA's Sector Notebooks, and other sources, to characterize
the MP&M sectors as a whole, including both dischargers
and non-dischargers.
This profile relies on industries defined by SICs, both
because data collection for the MP&M sectors was defined
by SICs and to allow for use of historical data. The Census
Bureau switched to use of the new North American Industry
Classification System (NAICS) codes starting with the 1997
Economic Censuses. Lack of a one-to-one correspondence
between an SIC and a NAICS code prevented the Agency
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MP&M EEBA Part I: Introduction and Background Information Chapter 3: Profile of the MP&M Industries
from matching the 1997 to earlier years' data for a number of to link facility characteristics to a specific sector. Data on
sectors. This profile therefore relies primarily on the 1992 the potentially-regulated facilities are therefore summarized
Censuses and, for manufacturing sectors, the 1996 Annual by the proposed regulatory subcategories rather than by
Survey of Manufactures. sectors.
The Agency used survey data to characterize the facilities
within the MP&M sectors that are potentially subject to the o p OVERVIEW OF THE MP&M INDUSTRY
proposed rule because they discharge process wastewater
from MP&M operations. The survey provides data such as AND INDUSTRY TRENDS
discharge type, small business status, sources of revenues,
and financial performance. Table 3.1 lists the MP&M sectors and provides a brief
description of the products and services produced by each.
The survey requested information on the sectors from which Appendix A provides a more detailed list of the 4-digit SIC
each facility derives its revenues. Many facilities derive codes in each sector.
revenues from more than one sector. It is therefore difficult
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
Table 3.1: MP&M Sector Definitions
Sector Sector Description
Aerospace Metal parts or products such as missiles, space vehicles, satellites and associated launching
equipment.
Aircraft Metal parts or products including all types of aircraft for public, private or commercial use. Includes
aircraft parts and equipment as well as aircraft maintenance activities.
Bus and Truck Metal parts or products including freight trucks and trailers as well as public, private and commercial
buses. Includes all associated equipment including equipment specific to truck and bus terminals.
Includes bus and truck maintenance activities.
Electronic Equipment Metal parts or products including general electronic components such as tubes, capacitors, and
transformers, as well as finished electronic equipment such as television, radio, and telephone.
Hardware Metal parts or products such as tools, cutlery, valves and tubing, dies, springs, sheet metal, drums, and
heat treating equipment.
Household Equipment Metal parts or products including appliances such as refrigerators, laundry equipment, lighting
equipment, cooking equipment, and vacuum cleaners. Non-communication type radios and
televisions are included in this sector.
Iron and Steel Sites engaged in iron or steel manufacturing, forming and finishing.
Instruments Metal parts or products such as laboratory and medical equipment, measuring devices, environmental
and process controls, optical equipment, surgical and dental equipment, and pens.
Metal Finishing Job Shop Facilities with more than 50 percent of their revenues coming from work on products not owned by
the site. While there are SIC codes associated with some Metal Finishing Job Shops, they sell to a
variety of markets and are not a market in and of themselves.
Mobile Industrial Equipment Metal parts or products including tractors and other farm equipment, construction machinery and
equipment, mining machinery and equipment, industrial cranes and hoists, and tracked military
vehicles.
Motor Vehicle Metal parts or products including private passenger vehicles and associated parts and accessories such
as automobiles, motorcycles, utility trailers and recreational vehicles, and mobile homes.
Office Machines Metal parts or products including office computer equipment, storage devices, printers, photocopiers
and associated parts and accessories.
Ordnance Metal parts or products including all small arms, artillery, and ammunition with the exception of
missiles (aerospace). Does not include the chemical processing or the manufacture of explosives.
Other Metal Products Metal parts or products including products and machinery not categorized into the other sectors (e.g.,
sporting goods, musical instruments).
Precious Metals and Jewelry Metal parts or products including jewelry, silverware, trophies, and clocks as well as all associated
parts and accessories.
Printed Wiring Boards Metal parts or products including printed wiring boards and printed wiring boards.
Railroad Metal parts or products including railcars, locomotives and associated parts and accessories as well as
track, switching and terminal stations.
Ships and Boats Metal parts or products including ships and boats for military, freight, and private recreation. Includes
submarines, ferries, tug boats, barges, yachts, and other recreational boats as well as all parts and
accessories. Also includes rebuilding and maintenance activities performed at marinas, dry docks, and
other on shore activities specifically related to ships and boats.
Stationary Industrial Metal parts or products including all industrial machinery, such as turbines, oil field machinery,
Equipment elevators and moving stairways, conveying equipment, chemical process industry equipment, pumps,
compressors, blowers, industrial ovens, vending machines, commercial laundry equipment,
commercial refrigeration and heating equipment, welding apparatus, motors, and generators.
Figure 3.1 shows that there MP&M facilities are located in
every state. A few MP&M sectors such as shipbuilding are
concentrated geographically, and transportation-related
MP&M facilities are found throughout the country. Overall,
however, MP&M facilities are most concentrated in the
heavy industrial regions along the Gulf Coast, both East and
West Coasts, and the Great Lakes Region (New York,
Pennsylvania, Ohio, Indiana, Illinois, and Michigan).
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Chapter 3: Profile of the MP&M Industries
Figure 3.1: Number of MP&M Facilities by State
Number of MP&M Facilties
361 - 2,572
2,927 - 6,370
6,907 - 8,825
8,993 - 14,656
15,158 - 68,359
Source: Department of Commerce, Bureau of the Census, Census of Manufactures, Census of Transportation, Census of Wholesale
Trade, Census of Retail Trade, Census of Service Industries, 1992.
Table 3.2 shows output by sector for manufactures, non-
manufactures, and sector total. In 1992, MP&M facilities
accounted for more than $1.9 trillion in output.
Manufacturing accounted for 60 percent of the total MP&M
output. Motor vehicles are the largest single MP&M sector,
accounting for almost 40 percent of all MP&M output.
While MP&M non-manufacturers outnumbered MP&M
manufacturers by more than two to one in 1996,
manufacturers' revenues were nearly $400 billion larger
than MP&M non-manufacturers' revenues.
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Chapter 3: Profile of the MP&M Industries
Table 3.2: MP&M Output and Share (millions, $1992)
Sector
Aerospace
Aircraft
Bus & Truck
Electronic Equipment
Hardware
Household Equipment
Instruments
Iron and Steel
Job Shop b
Mobile Industrial Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious Metals and Jewelry
Printed Wiring Boards
Railroad
Ships and Boats
Stationary Industrial Equipment
Total MP&M
Percent of total
Manufacturers
Output a
27,073.9
104,783.9
8,140.2
81,380.7
127,769.0
75,552.4
111,908.9
14,967.3
9,886.4
35,494.9
265,433.9
66,746.7
6,995.2
51,958.6
7,986.7
7,311.8
4,588.8
15,207.6
154,689.7
1,177,876.6
60.4%
Share
2.3%
8.9%
0.7%
6.9%
10.8%
6.4%
9.5%
1.3%
0.8%
3.0%
22.5%
5.7%
0.6%
4.4%
0.7%
0.6%
0.4%
1.3%
13.1%
100.0%
Non-Manufacturers
Output a
6,167.6
143,806.1
2,193.1
6,648.1
506,487.4
13,029.6
16,487.9
274.7
28,348.9
29,207.2
18,668.6
771,319.2
39.6%
Share
0.8%
18.6%
0.3%
0.9%
65.7%
1.7%
2.1%
0.0%
3.7%
3.8%
2.4%
100.0%
Sector Total
Output a
27,073.9
110,951.5
151,946.3
81,380.7
127,769.0
77,745.5
118,557.0
14,967.3
9,886.4
35,494.9
771,921.3
79,776.3
6,995.2
68,446.5
8,261.4
7,311.8
32,937.7
44,414.8
173,358.3
1,949,195.8
100.0%
Share
1.4%
5.7%
7.8%
4.2%
6.6%
4.0%
6.1%
0.8%
0.5%
1.8%
39.6%
4.1%
0.4%
3.5%
0.4%
0.4%
1.7%
2.3%
8.9%
100.0%
a. Value of shipments for manufacturing industries; total sales for retail and wholesale trade; total receipts for service industries; total revenue for
transportation.
b. Includes facilities in two SICs that are defined specifically as job shops (SICs 3471 and 3479.) Facilities reporting in other sectors may also operate
as job shops, so these data are likely to understate the true output of MP&M job shops.
Source: Department of Commerce, Bureau of the Census, Census of Manufactures, Census of Transportation, Census ofWholesale Trade, Census of
Retail Trade, Census of Service Industries, 1992.
The following sections describe the MP&M sectors and
briefly discusses recent industry trends in each sector. The
discussion is based on U.S. Industry and Trade Outlook
2000 (DRI-McGraw Hill), EPA's Sector Notebooks, and
other sources.
3.2.1 Aerospace
The aerospace industry includes original equipment
manufacturers (OEM) and facilities that rebuild and repair
aerospace equipment. The industry serves both military and
commercial end-uses such as space vehicles for commercial
communication satellites, although military applications
dominate. Products include guided missiles and space
vehicles, and associated propulsion units and parts. The
assembly of aerospace products draws on numerous other
industries, including plastics, rubber, fabricated metals,
metal casing, glass, textile, and electronic components.
Aerospace products are typically produced by a prime
contractor and several tiers of subcontractors. Final
assembly is performed by relatively few facilities compared
with the numerous subassembly and parts manufacturers.
There has been substantial consolidation in recent years in
the U.S. aerospace industry, due to declines in defense
spending. The number of facilities and firms as well as
sector value of shipments decreased from 1992 to 1996 in
the U.S., but value of shipments have rebounded to levels
comparable to the 1992 production levels in recent years.
This is partially due to replenishing of stocks depleted
during the bombing in Kosovo.
Growth in the industry is expected to come from lower cost
air-to-air missiles, with strong focus on increasing efficiency
in production by reducing costs. There has also been growth
in consumer demand for direct-to-home television, voice and
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data transmission, and other satellite services which has
increased the commercial demand for space vehicles needed
to launch satellites.
The aerospace industry exports a substantial share of its
output. Many North American and European governments
with large defense budgets have been seeking to reduce their
military budgets, while governments in South America (with
smaller budgets) have been maintaining or increasing their
defense spending. There has been substantial consolidation
in the European aerospace industry, which has become more
competitive with U.S. companies (U.S. EPA 1997;
DRI/McGraw Hill 2000).
3.2.2 Aircraft
Trends in the aircraft sector are heavily influenced by
changes in industry structure and in the international
political-economic arena. There has been substantial
restructuring through mergers and consolidation in the
aircraft manufacturing industry, including producers of both
aircraft and aircraft parts nationally and internationally.
Firms are focused on improving efficiency through cost
cutting efforts such as reduced staffing. Although there were
significant production increases of new aircraft in 1998 and
1999, growth in production is now expected to level off as
producers shift their focus to improving the efficiency of
existing aircraft.
Global competition in the airline industry may also reduce
the demand for U.S. aircraft products in the future. Trade
agreements in the European Union (E.U.) are expected to
limit the sale of U.S. engines and engine parts. In addition,
there is a growing trend for U.S. producers to outsource
many aircraft parts to firms in other nations, in order to
bring down costs and compete internationally.
In addition to aircraft manufacturing, this sector includes
rebuilding and repair of aircraft at manufacturers' facilities
or at airports.2 Maintenance and repair of aircraft has been
influenced by strong growth in both passenger and
commercial air traffic and by the maintenance requirements
of older aircraft.
3.2.3 Electronic Equipment
The electronic equipment sector can be divided into two
general groups of industries: microelectronics manufacturers
and telecommunications equipment.
2 EPA is proposing to cover wastewater generated from
washing vehicles only when it occurs as a preparatory step prior to
performing an MP&M unit operation (e.g., prior to disassembly to
perform engine maintenance or rebuilding). The proposed rule
does not cover the washing of cars, aircraft, or other vehicles when
it is performed only for aesthetic/cosmetic purposes.
Microelectronics industries manufacture a wide range of
products from electronic connectors to integrated circuit
panels. These products are used as material inputs in many
industries such as automotive, telecommunications,
aerospace, computer, and medical equipment. The
telecommunications industry also covers a range of
industries. These industries are focused on the production
of equipment used in network equipment, fiber optics, and
wireless communication equipment.
While the microelectronics industry covers a diverse array of
products, producers, and end-uses, there have been a number
of general trends in the industry. The electronics sectors
have shown very rapid growth over the last two decades.
The U.S. is a major producer of electronic products,
although Japan is the leading producer of consumer
electronics. With a strong increase in the use of
microelectronic products in industries throughout the
economy, this has been a rapidly growing industry. U.S.
firms face strong international competition for cutting edge
technological advances in their products. Due to the high
skill level necessary in the development of products, there is
considerable competition for skilled labor. The recent
growth in industry shipments is expected to continue,
partially due to the Information Technology Agreement,
which seeks to eliminate import duties on information
technology products by 2000.
The telecommunications industries have also experienced
considerable growth in the past few years. Much of the
growth in the industry has come from the growing use of
fiber optics and wireless end-user devices. Growth is
expected to continue, due in part to the World Trade
Organization's Agreement on Basic Telecommunications in
1998, which opened overseas markets to U.S. firms
competing to develop telecommunications networks.
3.2.4 Hardware
The hardware sector consists of many different industries,
which can be generally classified into three groups: building
hardware, conventional hardware, and tooling hardware.
Building hardware consists of a group of industries that
manufacture metal building products, including fabricated
structural metal, sheet metal work, and architectural
metalwork. This group of industries has been growing
rapidly throughout the 1990's. The building products
industry as a whole saw record sales in 1998 and again in
1999. Much of this growth is attributed to large highway
projects funded by the Transportation Efficiency Act for the
21st Century.
Conventional hardware includes products such as screws,
industrial fasteners, and valves and hose fittings. The
products produced in this industry are used in the production
of manufactured goods. Trends in this industry, therefore,
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generally reflect trends in other manufacturing industries. A
primary industry influencing conventional hardware is the
auto industry. Hardware producers have experienced
pressures from end users such as auto makers to reduce
costs.
The industry faces a continued trend of consolidation of
firms and increasing global pressure from countries with low
labor costs. Domestic producers of screws and industrial
fasteners saw growth in the real value of shipments due to
the strong U.S. economy.
The tooling hardware sector also contains a variety of
different industries that produce various types of tools for
different uses. Because these industries also face continued
globalization, many of them are impacted by changes in the
global economy. The decline in Asian markets in 1998 and
1999 resulted in a sharp decline in the value of shipments
for the machine tooling industries. Prior to the 1998
financial crisis, value of shipments were increasing annually.
The market for the power-driven segment of hand tools has
increased, however, despite troubled overseas markets.
3.2.5 Household Equipment
There are three general groups of industries included in this
sector: household furniture, household appliances, and
plumbing equipment. Generally speaking, factors that affect
this sector are consistent across these three groups. Low
interest rates, low unemployment, and increased disposable
income have stimulated growth in each of these industries.
Higher interest rates due to intervention from the Federal
Reserve and higher consumer prices for energy could result
in a leveling off in this industry. Furthermore, all three
industries face international competition as imports account
for a substantial share of domestic consumption.
Metal furniture accounts for 20 percent of the household
furniture industry. Metal components are increasingly being
added to non-metal furniture. For example, there is a trend
to increase the functionality of non-metal furniture by
equipping recliners with heat and massage. This could
increase the industry's reliance on metal parts. The industry
has integrated vertically, as large manufacturers have begun
to open their own retail stores in an effort to differentiate
their products.
There are two groups of household appliance manufacturers.
Major appliances such as washing machines and
refrigerators are produced by relatively few firms. Smaller
appliances are characterized by little product differentiation
but considerable price competition and are manufactured by
a larger number of companies.
Finally, a significant characteristic of the plumbing
equipment market is the extent of U.S. dependence on
foreign imports. While the U.S. construction market has
grown at a record pace in the past few years, increasing
demand for plumbing equipment, much of the demand has
been served by imports and this industry has a trade deficit.
3.2.6 Instruments
The instruments sector is characterized by a diverse array of
technologically advanced products and intense global
competition among many firms of varying sizes. The sector
can be generally divided into industrial measuring and
testing instruments, and medical instruments.
In the industrial measuring industry, producers of laboratory
instruments are typically integrated firms who have
consolidated and reduced costs in response to pressures
from medical and pharmaceutical customers. Producers of
measuring devices are also facing pressures to consolidate.
These firms have been hurt by low commodity prices during
the past few years, which have led to reduced investment in
measuring equipment by fuel and grain producers. Sales
should rebound, however, if Asian economies and fuel
prices continue to grow. Small companies still dominate the
electronic test equipment industry, which is characterized by
a high degree of product differentiation. Most of these firms
are not large enough to export products.
Sales for medical devices increased steadily throughout the
1990's, while employment remained relatively constant. The
industry has historically been characterized by many small to
mid-size firms and intense competition for technological
innovation. Efforts to bring down health care costs is one of
the primary challenges facing this industry. Pressure to
reduce costs has reduced insurance companies' willingness
to pay for new equipment. As the population ages, however,
demand for medical services and devices is expected to
grow. The industry should continue to grow through 2004
at a rate of 8 to 10 percent, which is somewhat less than
growth in recent years.
3.2.7 Iron and Steel
The basic iron and steel industry is regulated under 40 CFR
420, and primary iron and steel works, blast furnaces and
rolling mills are not affected by the proposed MP&M rule.
The proposed MP&M rule will regulate facilities that
perform MP&M operations or cold forming operations on
steel wire, rod, bar, pipe, or tube. This subcategory does not
include facilities that perform those operations on base
materials other than steel, nor does it include wastewater
generated from performing any hot steel forming operations
or wastewater from cold forming, electroplating or
continuous hot dip coating of steel sheet, strip, or plates.
Events in the global steel industry in the past few years have
had significant and possibly far reaching impacts on
domestic producers. In 1998, the industry experienced a
global steel crisis. This crisis was caused in part by the
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Asian financial crisis, which triggered a sharp decline in
imports of steel by major steel importing countries of Asia.
This led to a flood of steel imports into U.S., and U.S. steel
imports rose 33 percent in 1998. The situation was made
worse by global overcapacity largely derived from producers
in Russia and Latin America.
This flood of steel into the U.S. and Europe led to rapidly
declining steel prices in both regions. The "unfair" trading
prices resulted in over 20 nations taking formal trade
protection actions such as import duties and price floors.
Excess inventories that accrued during the surge of imports
hurt domestic producers. These inventories were expected
to be exhausted by 2000. The steel industry is projected to
grow along with the economy at a rate of 1 to 2 percent per
year through 2004.
3.2.8 Job Shops
MP&M metal finishing job shops are defined as those
facilities with more than 50 percent of their revenues coming
from products not owned by the site. While there are
specific SIC codes associated with some Metal Finishing
Job Shops, they sell to a variety of markets and are not a
market in and of themselves.
3.2.9 Motor Vehicle and Bus & Truck
The major trend in these industries is the continual
consolidation of firms into globalized manufacturers. Motor
vehicle manufacturers are no longer constrained within
national boundaries, as mergers and joint ventures include
some of the largest firms from different countries. Many
foreign owned manufacturers have facilities located in the
U.S., and relative production costs and exchange rates play a
greater role in determining the location of production
facilities than the national identity of parent companies.
Manufacturers have increasingly standardized the design of
motor vehicles and their parts. These changes have resulted
in much less product differentiation among manufacturers,
but also in greater product quality. However, greater
product quality has resulted in a consistently sharp increase
in price over the past three decades. This price increase may
have reached its pinnacle as prices have declined in 1998
and 1999. The real value of shipments for automobiles
increased 1.3 percent between 1996 and 2000.
3.2.10 Mobile Industrial Equipment
Mobile industrial equipment is divided among a number of
different industry segments that produce machinery for
different sets of end-users. Growth in the construction
equipment industry is typically tied to economic factors such
as housing starts, employment, and consumer confidence.
Shipments of construction equipment have risen steadily
during much of the 1990's. However, they have begun to
level off in 1999 and 2000. This is partially due to a decline
in demand caused by the Asian crisis, but may also reflect a
slowdown in the residential construction market. This
decline in demand may be offset by new spending from
Federal, State, and local governments in response to the
1998 Transportation Equity Act for the 21st Century.
The farm and mining machinery industries both have been
suffering from low commodity prices. Both industries
experienced growth in shipments throughout much of the
1990's, but were hit in!999 by low prices. Farm equipment
was hit hardest as the real value of shipments fell by 38
percent in 1999. Output is expected to continue to decrease
until grain surpluses decline and agricultural prices rise.
Declining world prices is only one of a number of trends
impacting the industry for agricultural production
equipment. The consolidation of farms has also had a
significant in impact on this industry. With the increase in
farm size, there is growing dependence upon mechanization
to farm more acres per farm.
3.2.11 Office Machine
The office machine sector is a rapidly growing and dynamic
global market. The industry has experienced 7.8 percent
growth in the real value of shipments between 1996 and
2000. While this growth was accomplished with only a 1.3
percent increase in total employment, production
employment increased by 5.4 percent. The relative
difference between total and production employment can be
attributed to increasing reliance on the Internet for sales,
thereby reducing the need for non-production employment.
The industry has undergone mergers and acquisitions to
bring down costs in order to compete. Firms also rely on
joint venturing agreements. Firms are forming alliances
with past competitors to produce complementary
components of new technologies. Consolidation also allows
firms to diversify, providing a range of products such as
PCs, software, and information technology to protect against
the strong competition in the market for any one product.
Firms have also increasingly outsourced production to
electronics manufacturers more equipped to increase
production and take advantage of economies of size, while
the original firms utilize their resources for research and
development of new technologies to stay competitive.
Globalization is an important trend in this industry as
machine components are produced in different countries.
Despite the trend toward a globalized market, the U.S. has
held a negative trade balance for over a decade. In recent
years, this has partially been due to the Asian financial
crisis. As Asian economies continue to recover the trade
balance is expected to improve for the U.S.
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3.2.12 Precious Metals and Jewelry
Domestic production in this industry is dominated by many
small firms, mostly concentrated in the northeast U.S., and is
impacted by trends in consumer behavior and the retail
market. Global competition has a significant impact on the
competitiveness of domestic firms. These factors have
provided both favorable and unfavorable conditions to the
industry.
Strong consumer spending on precious metals and costume
jewelry has been fueled by increased disposable income.
Devaluation in the price of gold due to declining world
prices has also benefitted the industry because it reduces the
cost of making jewelry.
Increases in spending have not necessarily translated into
gains for domestic producers. The lowering of tariffs has
resulted in a steady increase in imports of costume jewelry,
as labor-intensive production is often less expensive in
developing countries. Domestic producers are also hurt by
the strong U.S. dollar, which makes U.S. exports more
expensive. Another challenge comes from the retail market,
which has put strong pressure on producers to bring down
prices in order to compete. These challenges include
consolidation of retailers, giving them greater purchasing
power, increased Internet and television home shopping, and
a decrease in the number of wholesalers. The U.S. Industry
& Trade Outlook 2000 projects minimal growth in the
precious metals industry of 1 percent through 2004 and a
decline in costume jewelry of 2 percent.
3.2.13 Printed Wiring Boards
Printed wiring boards (also referred to as printed wiring
boards) are the physical structures on which electronic
components such as semiconductor and capacitors are
mounted. Computers and communications are the largest
uses for printed wiring boards. In addition, printed wiring
boards are used in a wide array of other products, including
toys, radios, television sets, electronic wiring in cars,
guided-missile and airborne electronic equipment,
biotechnology, medical devices, digital imaging equipment,
and industrial control equipment.
While some producers of PWBs produce them for their own
use, most manufacturers are independent firms that sell
PWBs to the open market. The majority of PWB
manufacturers are small firms.
The domestic industry has experienced considerable growth
throughout the 1990's. There is growing international
pressure to bring down costs, however, in order to compete
in the global economy. The real value of shipments grew
nine percent from 1996 to 2000. Growth has been spurred
by continual growth in end-use markets. In addition to the
increase value of shipments, U.S. firms have seen a 5.6
percent increase in average hourly earnings and a 16.3
percent increase in capital expenditures. High costs inhibit
the competitiveness of U.S. firms as they are already facing
tight competition from Asian producers. Consequently,
many of the larger firms are looking to relocate offshore.
3.2.14 Railroad
Railroad service consists of both freight and passenger
service. In the past few years, railroad companies have been
focusing on improving the efficiency of their lines and
services. There has been a continued trend toward
consolidation of major freight railroads. Consequently,
companies have reduced the number of lines and focused
attention on increasing the capacity of fewer lines.
Since the 1980's railroad traffic increased by 50 percent,
while the line network decreased by 39 percent. This was
accomplished by increasing capital expenditures for
equipment such as new locomotives with greater
horsepower, installation of double tracks, and increases in
the capacity of non-railroad owned freight cars.
Consequently, freight service saw the first increase in
operating revenue since 1984, although this was coupled
with sharp decreases in employment. Passenger service has
undergone similar changes to increase efficiency by adding
new locomotives and beginning a transition to high speed
train service.
3.2.15 Ships and Boats
Ship manufacturing has experienced continual declines
throughout the 1990's. Despite efforts by the Federal
Government to stimulate investment in converting the
industry from production of military ships to merchant ships,
the U.S. Navy remains the primary customer of shipbuilders.
The U.S. Navy has dramatically reduced its orders for new
vessels since the end of the Cold War, and decommissioned
many ships and submarines. The Navy decreased its fleet by
208 ships from 1985 to 1998. Although the Navy plans to
add 66 new ships through construction and conversion from
2000 through 2004, this represents a decline of over 60
percent in the procurement of new ships since the 1980's.
The ship building industry should be helped, however, by
the Oil Pollution Act of 1990, which requires all oil tankers
entering U.S. ports to have double hulls.
This sector also manufactures boats, with sales that reflect
overall trends in recreational expenditures. The U.S. boat
building business is the world's leading supplier of
recreational craft. Rapid growth in the market for smaller
personal water craft (e.g., jet skis) has led to an increase in
imports of boats.
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3.2.16 Stationary Industrial Equipment
The stationary industrial equipment sector includes
machinery used in a number of industries, as well as
machinery parts. These industries produce machinery used
for oil, paper, and food production, printing and packaging,
as well as heaters and air conditioners, electric generating
equipment, and motor generators. These industries also
produce large metal-working machines used in making parts
for other industries.
The industries supplying oil and gas production, paper
production, and printing machinery were impacted by
similar global factors, and consequently followed similar
trends. Oil production was impacted by low petroleum
prices in 1998. Gas production has also been influenced by
low oil prices, which puts pressure on the gas industry to
reduce costs in order to compete. These factors led to a
decline of 38 percent in the real value of shipments in 1998
and 1999, although the price of petroleum has increased in
1999 and 2000 and machinery shipments grew 9.2 percent.
Paper manufacturing equipment has also suffered from
events overseas. Although the U.S. has seen a decline in the
production of paper throughout the latter half of the 1990's,
the U.S. remains the largest producer of paper
manufacturing machinery. The industry therefore relies
heavily on exports to sustain growth. With struggling
economies overseas, the industry saw a decline in the annual
value of shipments from 1996 to 2000. The printing
industry was also impacted by the Asian economy. Printing
machinery manufacturers realized strong growth during the
first half of the 1990's due to increased demand for new
digital presses, but a decline in exports resulted in slower
growth for the later half of the decade. Global events did
not have such an impact on manufacturers of packaging
machinery, as the U.S. is not only the leading producer of
this equipment but also its leading end-user.
A variety of industries manufacture equipment used to
produce energy or to power equipment. Refrigeration, air
conditioning, and heating equipment sales tend to follow
growth in housing starts and construction of new office
buildings. A number of factors contributed to strong growth
in this industry throughout the 1990's including record
housing starts, record heat in the summer of 1999,
replacement of chlorofluorocarbon (CFC) air conditioning
units, and a large percentage of new homes being built with
central air conditioning. With 66 percent of the existing air
conditioners containing CFC technology still in operation,
replacement of these machines provides an opportunity for
growth in this industry in the future. However, with rising
interest rates in the past few years, housing starts are
expected to slow, which should moderate growth.
Turbines, transformers, and switchboards are all used for the
production of electricity, which saw considerable growth
from 1990 to 1998 as the domestic economy grew. This
growth was also impacted by the financial crisis in Asia,
however. A number of advanced technologies have been
developed to meet the demands of a deregulated industry.
These technologies are capable of producing electricity from
smaller facilities at competitive costs. Implementation of
these technologies is not expected to take place for a few
years, however, as the effects of deregulation become
clearer. Consequently, growth is expected to be slow
through 2004.
3.3 CHARACTERISTICS OF MP&M
MANUFACTURINS SECTORS
The analyses presented in this section cover a nine year
period from 1988 to 1996. The data come primarily from
the 1992 Economic Censuses and from the Annual Survey of
Manufactures for other years. Data are presented over nine
years rather than ten because data are incomplete in the
Annual Survey of Manufactures for many SIC codes in
1987. OMB reclassified a number of 4-digit SIC industries
in 1987 which made it difficult to compare SIC codes before
and after this reclassification.
Trends in dollar values are shown in real terms, using the
Producer Price Index (PP\) for industrial commodities.
The PPI is family of indexes that measure price changes
from the perspective of the seller. This profile uses the PPI
to inflate nominal monetary values to constant dollars. The
PPI for industrial commodities increased slightly every year
between 1987 and 1996. Table 3.3 shows the index values
for the relevant years.
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Table 3.3: Producer Price Index for Industrial Commodities
Year
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
Producer Price Index (PPI)
102.6
106.3
111.6
115.8
116.5
117.4
119
120.7
125.5
127.3
Percent Change
n/a
3.6%
5.0%
3.8%
0.6%
0.8%
1.4%
1.4%
4.0%
1.4%
Source: Bureau of Labor Statistics, Producer Price Index.
3.3.1 Domestic Production
Q. Output
The two most common measures of manufacturing output
are value of shipments (VOS) and value added (VA).
Historical trends in these measures provide insight into the
overall economic health of an industry. Value of shipments
is the sum of the receipts a manufacturer earns from the sale
of its outputs. It is an indicator of the overall size of a
market or the size of a firm in relation to its market or
competitors. Value added is used to measure the value of
production activity in a particular industry. It is the
difference between the value of shipments and the value of
purchased non-labor inputs used to make the products sold.
Table 3.4 presents the trend in value of shipments and value
added by MP&M sector during the period 1988 to 1996.
The aerospace and ordnance industries experienced a
significant decline in VOS and VA over this period.
Aerospace value of shipments had a negative average annual
growth rate of 7.6 percent, due to the decreased military
spending during the last. Aerospace VOS has risen in recent
years, however, due in part to replenishing of stocks
depleted during the bombing in Kosovo. Railroad
equipment manufacturers enjoyed an average annual growth
of 7.6 percent in VOS, after some years of decline.
Electronic equipment experienced the next largest average
growth, with annual growth in VOS averaging 5.1 percent,
due primarily to the rapid growth in the use of
microelectronics in industries throughout the economy. Ship
and boat manufacture experienced continual declines
throughout the 1990's. The U.S. Navy remains the primary
customer of shipbuilders and the Navy has reduced its fleet
since the end of the Cold War.
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Table 3.4: Real Value of Shipments and Value Added: MP&M Manufacturing Sectors (millions, $1996)
Sector
Aerospace
Aircraft
Bus & Truck
Electronic Equipment
Hardware
Household Equipment
Instruments
Iron and Steel
Job Shops
Mobile Industrial Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious Metals and Jewelry
Printed Wiring Boards
Railroad
Ships and Boats
Stationary Industrial Equipment
Total
Value of Industry Shipments
1988
33,763
95,268
9,234
80,206
143,151
82,331
110,998
18,195
11,007
42,355
296,102
81,007
9,607
55,169
10,122
9,533
3,935
17,638
166,007
1,275,628
1996
17,928
83,394
13,473
119,464
169,567
92,649
127,935
18,727
14,003
52,683
363,557
103,270
5,222
60,034
8,670
10,702
7,067
15,634
221,591
1,505,570
Average
Annual
Growth Rate
-7.6%
-1.7%
4.8%
5.1%
2.1%
1.5%
1.8%
0.4%
3.1%
2.8%
2.6%
3.1%
-7.3%
1.1%
-1.9%
1.5%
7.6%
-1.5%
3.7%
2.1%
Value Added by Manufacture
1988
22,671
48,492
3,398
45,837
77,528
39,958
73,322
6,781
6,536
20,034
100,400
40,346
6,221
33,808
4,707
5,560
1,776
9,462
91,360
638,197
1996
9,986
45,220
5,172
62,919
92,566
42,731
83,540
6,663
7,793
22,798
122,541
41,135
3,528
35,114
4,130
6,564
2,590
7,903
117,678
720,571
Average
Annual
Growth Rate
-9.7%
-0.9%
5.4%
4.0%
2.2%
0.8%
1.6%
-0.2%
2.2%
1.6%
2.5%
0.2%
-6.8%
0.5%
-1.6%
2.1%
4.8%
-2.2%
3.2%
1.5%
Source: Department of Commerce, Bureau of the Census, Annual Survey of Manufactures.
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b. Number of facilities and firms
Table 3.5 shows the number of facilities between 1989 and
1996 and the number of firms between 1990 and 1996. The
aerospace industry is the only MP&M manufacturing sector
experiencing significant downsizing, with the numbers of
firms and facilities decreasing annually by 4.1 and 4.2
percent, respectively. The iron and steel industry
experienced a modest decrease in number of firms and
facilities.
Table 3.5: Number of Firms and Facilities: MP&M Manufacturing Sectors
Sector
Aerospace
Aircraft
Bus & Truck
Electronic Equipment
Hardware
Household Equipment
Instruments
Iron and Steel
Job Shop
Mobile Industrial Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious Metals and Jewelry
Printed Wiring Boards
Railroad
Ships and Boats
Stationary Industrial
Equipment
Total
Number of Firms
1990
109
1,428
889
5,649
34,984
6,787
7,963
597
4,798
3,318
4,991
1,828
340
11,517
3,719
1,034
147
2,511
35,231
127,840
1996
85
1,486
953
6,180
37,832
7,563
9,730
583
5,280
3,341
6,044
2,002
421
13,819
3,867
1,452
152
3,195
40,618
144,603
Average
Annual
Growth Rate
-4.1%
0.7%
1.2%
1.5%
1.3%
1.8%
3.4%
-0.4%
1.6%
0.1%
3.2%
1.5%
3.6%
3.1%
0.7%
5.8%
0.6%
4.1%
2.4%
2.1%
Number of Facilities
1989
143
1,633
1,016
6,396
37,861
7,914
8,959
784
5,104
3,606
5,977
2,050
385
12,069
3,870
1,046
180
2,708
37,261
138,962
1996
106
1,691
1,040
6,693
40,044
8,303
10,552
770
5,549
3,591
7,024
2,087
442
14,198
3,892
1,530
215
3,310
42,317
153,354
Average
Annual
Growth Rate
-4.2%
0.5%
0.3%
0.7%
0.8%
0.7%
2.4%
-0.3%
1.2%
-0.1%
2.3%
0.3%
2.0%
2.3%
0.1%
5.6%
2.6%
2.9%
1.8%
1.4%
Source: Small Business Administration, Statistics of U.S. Businesses.
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c. Employment
Employment is a measure of the level and trend of activity in
an industry. While employment growth generally signals
economic strength in an industry, strong productivity growth
and scale economies can yield growth in revenues that
exceeds growth in employment.
Table 3.6 shows that employment in the MP&M
manufacturing sectors as a whole decreased modestly
between 1988 and 1997, declining at an average rate of 0.7
percent annually. The aerospace, ordnance, and aircraft
sectors experienced the largest decreases in employment
from 1988 to 1996. The electronic equipment sector showed
the most growth in output but had less than 0.01 percent
increase in employment, reflecting an increase in real
productivity.
Table 3.6: Employment: MP&M Manufacturing Sectors
Sector
Aerospace
Aircraft
Bus & Truck
Electronic Equipment
Hardware
Household Equipment
Instruments
Iron and Steel
Job Shops
Mobile Industrial Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious Metals and Jewelry
Printed Wiring Boards
Railroad
Ships and Boats
Stationary Industrial Equipment
Total
Number of Employees
1988
223,700
596,600
63,900
602,500
1,246,200
584,900
886,500
65,500
123,300
232,400
928,000
329,800
86,500
368,100
87,100
80,900
25,900
182,900
1,269,800
7,984,500
1996
81,000
376,800
67,700
604,800
1,307,600
570,600
753,800
67,900
129,200
232,600
974,000
259,100
40,200
361,400
65,800
88,300
30,600
141,300
1,396,900
7,549,600
Average Annual
Growth Rate
-11.9%
-5.6%
0.7%
0.0%
0.6%
-0.3%
-2.0%
0.5%
0.6%
0.0%
0.6%
-3.0%
-9.1%
-0.2%
-3.4%
1.1%
2.1%
-3.2%
1.2%
-0.7%
Source: Department of Commerce, Bureau of the Census, Annual Survey of Manufactures.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
d. Capital expenditures
New capital expenditures are needed to modernize, expand,
and replace existing capacity to meet growing demand.
Table 3.7 presents new capital expenditures by sector. In
general, the MP&M industries increased their capital
expenditures by 4.3 percent annually. The only sectors that
had a decline in spending on new capital were aerospace,
aircraft, ordnance, and ships and boats.
Table 3.7: New Capita
Sector
Aerospace
Aircraft
Bus & Truck
Electronic Equipment
Hardware
Household Equipment
Instruments
Iron and Steel
Job Shops
Mobile Industrial Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious Metals and Jewelry
Printed Wiring Boards
Railroad
Ships and Boats
Stationary Industrial Equipment
Total
Expenditures: MP&M /
1988
1,229
2,828
151
2,925
3,299
2,017
3,754
394
331
1,052
5,344
2,856
184
1,659
87
403
73
453
4,065
33,104
Aanufacturing Sectors
1996
490
2,023
200
4,205
5,276
2,454
4,533
584
724
1,052
12,045
2,917
85
1,875
146
585
97
351
6,775
46,417
[millions, $1996)
Average Annual
Growth Rate
-10.9%
-4.1%
3.6%
4.6%
6.0%
2.5%
2.4%
5.0%
10.3%
0.0%
10.7%
0.3%
-9.2%
1.5%
6.7%
4.8%
3.6%
-3.1%
6.6%
4.3%
Source: Department of Commerce, Bureau of the Census, Annual Survey of Manufactures.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
3.3.2 Industry Structure and
Competitiveness
This profile shows facility and firm size and data on foreign
trade as measures of industry structure and competitiveness
in MP&M manufacturing.
a. Facility size
In general, the MP&M industries are characterized by a
large number of small businesses. Table 3.8 shows that
approximately 98 percent of all MP&M facilities employ
500 employees or less. However, those facilities only
account for 39 percent of the value of shipments. Hardware
and stationary industrial equipment represent 55 percent of
the facilities employing 19 people or less.
Table 3.8: Number of Facilities and Value of Shipments by Facility Employment Size Category:
MP&M Manufacturing Sectors
Sector
Aerospace
Aircraft
Bus & Truck
Electronic Equipment
Hardware
Household Equipment
Instruments
Iron and Steel
Job Shop
Mobile Industrial
Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious Metals and
Jewelry
Printed Wiring Boards
Railroad
Ships and Boats
Stationary Industrial
Equipment
Total
Number of Facilities
Itol9
39
900
557
3,898
26,790
5,160
6,295
297
3,651
2,362
3,604
1,370
264
10,483
3,251
735
83
2,373
29,234
101,346
20 to 99
23
466
313
2,207
10,866
2,165
2,490
278
794
927
1,625
526
77
2,207
528
423
81
467
7,799
34,262
100 to
499
35
257
128
934
2,247
1,050
1,152
182
144
326
1,002
232
58
558
120
149
30
182
2,101
10,887
500 to
2,499
24
85
17
154
151
171
296
15
2
63
235
83
26
59
11
16
10
25
294
1,737
2,500 or
more
19
37
0
17
1
8
31
0
0
8
72
16
4
4
0
1
2
6
10
236
Value of Shipments (millions, $1992)
Itol9
207
551
411
2,316
15,861
2,950
3,901
397
1,725
1,578
2,714
1,197
94
4,384
1,643
367
92
851
13,950
55,188
20 to 99
70
2,208
1,636
10,483
47,999
10,215
12,778
3,469
3,580
5,009
9,256
4,714
281
9,139
2,370
1,614
596
1,822
33,892
161,132
100 to
499
1,045
7,053
3,854
24,378
49,569
31,278
32,448
8,147
3,262
10,815
34,923
11,994
1,769
14,960
3,731
2,510
1,102
3,947
59,180
305,963
500 to
2,499
5,601
26,194
2,240
37,418
14,341
29,064
44,457
2,956
0
18,093
105,710
27,405
4,851
23,475
243
2,821
2,799
2,222
43,331
393,220
2,500 or
more
20,151
68,778
0
6,786
0
2,044
18,324
0
0
0
112,831
21,437
0
0
0
0
0
6,366
4,337
261,054
Source: Department of Commerce, Bureau of the Census, Census of Manufactures, 1992.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
b. Firm size
The Small Business Administration (SBA) defines small
businesses according to the firms' number of employees.
Table 3.9 shows that 141,048 (92 percent) of all MP&M
manufacturing facilities are owned by firms that employ 500
or fewer workers and would therefore be considered small
businesses. The remaining 12,306 facilities are owned by
firms that employ more than 500 workers and account for 72
percent of total estimated receipts.
Table 3.9: Number of Firms, Facilities, and Estimated Receipts by Firm Employment Size Category, 1996:
MP&M Manufacturing Sectors
Sector
Aerospace
Aircraft
Bus & Truck
Electronic Equipment
Hardware
Household Equipment
Instruments
Iron and Steel
Job Shops
Mobile Industrial Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious Metals and Jewelry
Printed Wiring Boards
Railroad
Ships and Boats
Stationary Industrial
Equipment
Total
Firms
Ito99
51
1,209
805
4,936
34,162
6,408
8,273
362
4,945
2,875
4,950
1,662
358
13,097
3,747
1,250
99
3,003
37,669
129,861
100 to
499
2
135
92
681
2,345
665
727
108
240
263
614
167
25
492
86
137
24
137
1,691
8,631
500 or
more
32
142
56
563
1,325
490
730
113
95
203
480
173
38
230
34
65
29
55
1,258
6,111
Facilities
Ito99
51
1,212
810
4,977
34,398
6,455
8,320
368
5,001
2,898
4,987
1,668
358
13,152
3,753
1,258
101
3,012
37,835
130,614
100 to
499
2
158
107
786
2,968
791
842
153
338
319
724
180
28
602
89
150
30
165
2,002
10,434
500 or
more
53
321
123
930
2,678
1,057
1,390
249
210
374
1,313
239
56
444
50
122
84
133
2,480
12,306
Estimated Receipts (millions,
$1996)
Ito99
0
2,301
2,129
11,404
62,437
12,007
16,180
1,890
6,714
6,255
10,614
5,040
309
12,728
3,339
2,093
306
2,532
49,438
207,715
100 to
499
0
2,664
2,475
16,279
39,927
16,334
15,238
4,152
3,271
5,930
20,053
7,069
425
10,073
1,894
2,253
465
2,771
33,418
184,691
500 or
more
17,851
88,050
6,287
76,563
57,501
62,299
90,897
11,949
2,905
30,140
343,942
60,436
3,952
28,778
2,015
5,412
5,883
10,789
111,831
1,017,479
Source: Small Business Administration, Statistics of U.S. Businesses, 1996.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
c. Foreign trade
This profile uses two measures of foreign competitiveness:
export dependence and import penetration. Export
dependence is the share of value of shipments that is
exported. Import penetration is the share of domestic
consumption met by imports. For both measures, a high
value indicates a relatively high dependence on foreign
markets.
Table 3.10 shows that in the U.S., the four industries with
the highest level of domestic consumption were motor
vehicles, stationary industrial equipment, hardware, and
electronic equipment. Of these four industries, stationary
industrial equipment is the only industry with positive net
exports (exports minus imports) in 1999. Overall, the U.S.
was a net importer of MP&M manufactured goods. The
table also shows that there is global competition in many of
the MP&M industries, which is illustrated by the number of
industries that have both large export dependence and
import penetration. For example, roughly 89 percent of U.S.
consumption of precious metals is met by imports, while
almost 70 percent of U.S. production is sold as exports.
Table 3.10
Sector
00
Aerospace
Aircraft
Bus & Truck
Electronic Equipment
Hardware
Household
Equipment
Instruments
Iron and Steel
Job Shops4
Mobile Industrial
Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious Metals and
Jewelry
Printed Wiring
Boards
Railroad
Ships and Boats
Stationary Industrial
Equipment
Total
Value of Imports
(millions, 1999$)
(b)
250
23,725
740
61,944
30,221
50,530
24,404
1,070
13,473
161,632
63,717
717
27,573
20,444
2,265
2,056
1,062
48,319
534,141
Trade Statistics, 1999: MP&M Manufacturing Sectors
Value of Exports
(millions, 1999$)
(c)
276
60,749
691
37,355
21,850
14,664
36,421
341
14,222
64,800
47,637
2,147
10,415
6,007
2,570
1,238
1,612
57,313
380,305
Value of Shipments
(millions, 1999$)
(d)
17,816
82,870
13,388
118,714
168,502
92,066
127,131
18,609
13,915
52,352
361,272
102,621
5,189
59,657
8,616
10,634
7,023
15,536
220,198
1,496,107
Implied Domestic
Consumption3
(e)
17,789
45,846
13,437
143,303
176,873
127,933
115,114
19,338
51,604
458,104
118,701
3,758
76,815
23,053
10,330
7,840
14,987
211,204
1,649,943
Import
Penetration1"
(f)
1.4%
51.7%
5.5%
43.2%
17.1%
39.5%
21.2%
5.5%
26.1%
35.3%
53.7%
19.1%
35.9%
88.7%
21.9%
26.2%
7.1%
22.9%
32.4%
Export
Dependence0
(8)
1.6%
73.3%
5.2%
31.5%
13.0%
15.9%
28.6%
1.8%
27.2%
17.9%
46.4%
41.4%
17.5%
69.7%
24.2%
17.6%
10.4%
26.0%
25.4%
a. Implied domestic consumption based on value of shipments, imports, and exports [column d + column b - column c].
b. Import penetration based on implied domestic consumption and imports [column b / column e].
c. Export dependence based on value of shipments and exports [column c / column d].
d. As explained in the text, job shops include only two SICs specific to job shops, and not facilities in other SICs that may be operating as job shops.
Note: components may not sum to totals due to rounding.
Source: Department of Commerce, Bureau of the Census.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
Table 3.11 shows the change in the value of exports and
imports from 1996 to 1999. In 1996 the U.S. had negative
net exports from MP&M industries, reflecting a trade deficit
of $70.6 million. That trade deficit increased in 1999 by
roughly $83.2 million to about $153.8 million. As is
discussed in greater detail in Section 3.4, exports for a
number of the MP&M industries grew slower from 1996 to
1999 than in previous years due to financial crises in Asia
and Latin America, while the strong domestic economy and
low commodity prices resulted in increased growth in
imports.
Table 3.11: Exports and Imports: MP&M Manufacturing Sectors
Sector
Aerospace
Aircraft
Bus & Truck
Electronic Equipment
Hardware
Household Equipment
Instruments
Iron and Steel
Job Shops
Mobile Industrial Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious Metals and Jewelry
Printed Wiring Boards
Railroad
Ships and Boats
Stationary Industrial
Equipment
Total
Value of Imports (millions, 1999$)
1996
133
13,065
382
29,344
24,939
37,938
17,702
874
10,044
115,783
62,534
604
23,568
14,765
2,486
1,126
1,008
36,178
392,473
1999
250
23,725
740
61,944
30,221
50,530
24,404
1,070
13,473
161,632
63,717
717
27,573
20,444
2,265
2,056
1,062
48,319
534,142
Average
Annual
Growth Rate
23.4%
22.0%
24.7%
28.3%
6.6%
10.0%
11.3%
7.0%
10.3%
11.8%
0.6%
5.9%
5.4%
11.5%
-3.1%
22.2%
1.8%
10.1%
10.8%
Value of Exports (millions, 1999$)
1996
133
38,479
406
28,539
19,166
15,669
29,329
245
15,506
56,878
44,543
2,603
10,481
4,295
1,815
720
1,007
52,049
321,863
1999
276
60,749
691
37,355
21,850
14,664
36,421
341
14,222
64,800
47,637
2,147
10,415
6,007
2,570
1,238
1,612
57,313
380,308
Average
Annual
Growth Rate
27.6%
16.4%
19.4%
9.4%
4.5%
-2.2%
7.5%
11.7%
-2.8%
4.4%
2.3%
-6.2%
-0.2%
11.8%
12.3%
19.8%
17.0%
3.3%
5.7%
Source: Department of Commerce, Bureau of the Census.
3.3.3 Financial Condition and
Performance
Operating margin is a partial measure of industry
financial performance. Operating margin is defined as VOS
less annual payroll and cost of materials as a percent of
VOS. This is a partial measure of profitability, as it does
not take into account costs associated with capital
expenditures or energy.
Table 3.12 presents the operating margins for each industry
for the years 1988 and 1996, as well as the change in
operating margin between the two years. Table 3.12 shows
that ten MP&M manufacturing sectors experienced
increases in their operating margins during the time period,
while nine industries experienced decreases. The greatest
increases in operating margin occurred in the aircraft, motor
vehicles, and bus & truck industries, and the greatest
decreases occurred in the aerospace, office machine, and
other metal products industries. Ten industries had
increases greater than 1 percentage point, and four had
operating margins that decreased by more than 1 percentage
point.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
Table 3.12: Operating Margin: MP&M Manufacturing Sectors (millions, $1996)
Sector
Aerospace
Aircraft
Bus & Truck
Electronic Equipment
Hardware
Household Equipment
Instruments
Iron and Steel
Job Shops
Mobile Industrial Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious Metals and Jewelry
Printed Wiring Boards
Railroad
Ships and Boats
Stationary Industrial Equipment
1988
32.4%
20.6%
18.5%
32.0%
27.5%
29.7%
37.1%
23.2%
31.8%
27.9%
20.9%
31.7%
34.3%
41.9%
27.9%
37.2%
22.4%
23.2%
29.4%
1996
28.9%
26.7%
24.4%
33.8%
29.7%
29.5%
41.1%
22.9%
30.8%
28.2%
22.4%
30.2%
39.6%
40.4%
28.2%
36.8%
22.1%
22.5%
31.5%
Change in Operating
Margin
-3.5%
6.1%
5.9%
1.8%
2.2%
-0.2%
4.0%
-0.3%
-1.0%
0.3%
1.5%
-1.5%
5.3%
-1.5%
0.3%
-0.4%
-0.3%
-0.7%
2.1%
Operating Margin is calculated as (value of shipments - cost of materials - payroll)/value of shipments
Source: Department of Commerce, Bureau of the Census, Annual Survey of Manufactures.
3.4 CHARACTERISTICS OF MP&M NON-
MANUFACTURINS SECTORS
Eleven of the 18 MP&M sectors include non-manufacturing
industries. The non-manufacturing activities are defined by
50 4-digit SIC codes: 26 transportation SIC codes, 18
service SIC codes, five retail trade SIC codes, and one
wholesale trade SIC code. MP&M facilities may perform
both manufacturing and non-manufacturing activities.
The analyses presented in this section cover 1992 only,
because the Census does not collect data annually for non-
manufacturing SICs as it does for manufacturers in the
Annual Survey of Manufacturers. The profile is based on
data from the 1992 Censuses of Transportation,
Communications, and Utilities; Service Industries; Retail
Trade; and Wholesale Trade.
3.4.1 Domestic Production
Q. Output
Table 3.13 shows sales or receipts by sector for the MP&M
non-manufacturing SIC codes. Motor vehicles repair and
maintenance accounts for almost 66 percent of the total
MP&M non-manufacturing sales and receipts.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
Table 3.13: Sales/Receipts: MP&M Non-Manufacturing Sectors
(millions, $1992)
Sector
Aircraft
Bus & Truck
Household Equipment
Instruments
Motor Vehicle
Office Machine
Other Metal Products
Precious Metals and Jewelry
Railroad
Ships and Boats
Stationary Industrial Equipment
Total
Output a
6,168
143,806
2,193
6,648
506,487
13,030
16,488
275
28,349
29,207
18,669
771,319
Share
0.8%
18.6%
0.3%
0.9%
65.7%
1.7%
2.1%
0.0%
3.7%
3.8%
2.4%
100.0%
a. Total sales for retail and wholesale trade, total receipts for service industries, total
revenue for transportation.
Source: Department of Commerce, Bureau of the Census, Census of Transportation,
Census of Wholesale Trade, Census of Retail Trade, Census of Service Industries, 1992.
b. Number of facilities and firms
Table 3.14 shows the number of facilities and firms in the
MP&M non-manufacturing sectors, with average annual
growth rates. There was a positive growth rate from 1989 to
1996 in all of the industries. Office machines, aircraft, bus
and truck, and ships and boats were the fastest growing over
the time period. The number of office machine facilities
grew by approximately 20 percent annually.
Table 3.14: Number of Firms and Facilities: MP&M Non-Manufacturing Sectors
Sector
Aircraft
Bus & Truck
Household Equipment
Instruments
Motor Vehicle
Office Machine
Other Metal Products
Precious Metals and Jewelry
Ships and Boats
Stationary Industrial Equipment
Total
Number of Firms
1990
2,024
74,719
3,234
7,214
183,986
9,206
32,865
1,379
5,739
14,672
335,038
1996
3,281
113,840
3,706
7,444
213,355
32,916
36,290
1,625
8,290
15,075
435,822
Average
Annual
Growth Rate
8.4%
7.3%
2.3%
0.5%
2.5%
23.7%
1.7%
2.8%
6.3%
0.5%
4.5%
Number of Facilities
1989
2,463
88,128
3,367
8,365
203,592
9,714
34,683
1,535
6,561
20,880
379,288
1996
4,062
127,675
3,935
9,185
234,542
35,150
37,902
1,838
9,262
21,791
485,342
Average
Annual
Growth Rate
7.4%
5.4%
2.3%
1.3%
2.0%
20.2%
1.3%
2.6%
5.0%
0.6%
3.6%
Source: Small Business Administration, Statistics of U.S. Businesses.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
c. Employment
Table 3.15 shows employment in each non-manufacturing
MP&M sector in 1992. The bus and track and motor
vehicle sectors employ nearly 77 percent of all the non-
manufacturing MP&M employment.
Table 3.15: Employment, 1992: MP&M Non- Manufacturing Sectors
Sector
Aircraft
Bus & Truck
Household Equipment
Instruments
Motor Vehicle
Office Machine
Other Metal Products
Precious Metals and Jewelry
Railroad
Ships and Boats
Stationary Industrial Equipment
Total
Employment
79,953
1,683,432
23,681
108,761
1,910,701
120,804
213,242
5,141
197,421
171,314
168,850
4,683,300
Share
1.7%
35.9%
0.5%
2.3%
40.8%
2.6%
4.6%
0.1%
4.2%
3.7%
3.6%
100.0%
Source: Department of Commerce, Census of Transportation, Census of Wholesale Trade, Census of
Retail Trade, Census of Service Industries, 1992.
3.4.2 Industry Structure and
Competitiveness
a. Facility size
The non-manufacturing facilities tend to be smaller than
manufacturing facilities. There are 204,586 facilities (54.3
percent) that employ 4 employees or less. These facilities
account for 7 percent of sales or receipts in the non-
manufacturing MP&M sectors.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
Table 3.16: Number of Facilities and Sales/Receipts by Facility Employment Size Category:
MP&M Non- Manufacturing Sectors
Sector
Aircraft
Bus & Truck
Household
Equipment
Instruments
Motor Vehicle
Office Machine
Other Metal Products
Precious Metals and
Jewelry
Ships and Boats
Stationary Industrial
Equipment
Total
Number of Facilities
Oto4
1,148
45,917
2,078
5,942
106,478
7,113
22,509
1,163
3,077
9,161
204,586
5 to 9
552
17,414
737
2,037
44,749
1,691
6,851
231
1,313
5,511
81,086
10 to 19
455
14,524
387
1,128
21,773
1,147
3,239
46
877
2,644
46,220
20 to 99
539
15,750
181
806
19,314
974
1,709
17
963
1,438
41,691
100 or
more
152
629
10
195
1,647
168
3
0
270
94
3,168
Sales/Receipts (millions, $1992)
Oto4
240
11,432
381
949
33,379
1,579
3,642
138
1,694
2,671
56,104
5 to 9
291
11,385
406
993
36,659
1,191
3,099
60
1,808
3,540
59,432
10 to 19
494
18,211
511
1,155
53,593
1,653
3,316
29
1,928
3,747
84,635
20 to 99
1,937
90,748
670
2,011
278,225
4,084
5,755
34
8,561
5,651
397,676
100 or
more
3,067
8,006
170
1,377
92,389
3,981
30
0
12,776
2,411
124,208
Source: Department of Commerce, Bureau of the Census, Census of Transportation, Census of Wholesale Trade, Census of Retail Trade, Census of
Service Industries, 1992.
b. Firm size
For most of the non-manufacturing SIC codes, SB A defines
small businesses according to the firms' total revenue.
Therefore, examining a firms employment size is somewhat
meaningless for non-manufacturers. Approximately
438,800 facilities, or 90 percent, are owned by firms
employing 99 workers or less.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
Table 3.17: Number of Firms, Facilities, and Estimated Receipts by Firm Employment Size Category, 1996:
MP&M Non- Manufacturing Sectors
Sector
Aircraft
Bus & Truck
Household Equipment
Instruments
Motor Vehicle
Office Machine
Other Metal Products
Precious Metals and Jewelry
Ships and Boats
Stationary Industrial Equipment
Total
Firms
Ito99
3,124
111,038
3,669
7,277
209,814
32,428
35,788
1,615
7,833
14,587
427,173
100 to
499
80
2,001
19
76
3,010
290
284
6
243
302
6,311
500 or
more
77
801
18
91
531
198
218
4
214
186
2,338
Facilities
Ito99
3,189
112,751
3,700
7,536
216,707
32,745
36,205
1,661
8,000
16,331
438,825
100 to
499
139
4,334
23
206
7,119
759
567
105
519
1,359
15,130
500 or
more
734
10,590
212
1,443
10,716
1,646
1,130
72
743
4,101
31,387
Estimated Receipts (millions,
$1996)
Ito99
2,549
74,421
1,906
2,926
437,146
13,872
15,712
252
8,525
14,467
571,776
100 to
499
1,186
22,461
258
527
174,565
4,503
2,165
0
5,743
4,321
215,729
500 or
more
5,695
62,021
819
3,485
81,721
9,911
4,325
0
19,225
7,260
194,463
Source: Small Business Administration, Statistics of U.S. Businesses.
3.5 CHARACTERISTICS OF PoTENTiALLy-
RESULATE& MP&M FACILITIES
The Agency is not using industrial sectors to subcategorize
the regulations for the MP&M industry. EPA has
determined that the industrial sectors are too broad for the
purposes of subcategorization, and many facilities perform
operations covered by multiple sectors. Instead, EPA is
proposing to define subcategories based on unit operations
performed and the nature of the waste generated. EPA has
determined that a basis exists for dividing the MP&M
category into the following subcategories for the proposed
rule: General Metals, Non-Chromium Anodizing, Metal
Finishing Job Shops, Printed Wiring Boards, Steel Forming
and Finishing, Oily Wastes, Railroad Line Maintenance, and
Shipbuilding Dry Dock.
Table 3.18 shows the national number of MP&M facilities
that sell products to different combinations of sectors. The
table shows that many MP&M facilities operate in multiple
market sectors. There is an overlap for almost every
combination of sectors, and some MP&M facilities report
revenues from three or more sectors.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
Table 3.18: Overlap of Sectors
Sectors
Aerospace
Aircraft
Bus and Truck
Electronic Equipment
Hardware
Household Equipment
Instrument
Mobile Industrial
Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious and Non-
Precious Metals
Railroad
Ship and Boat
Stationary Industrial
Equipment
Unknown
Aerospace
141
0
117
129
141
72
84
24
93
84
12
81
24
0
60
24
Aircraft
189
126
145
165
72
108
44
102
120
12
102
36
0
0
40
Bus and Truck
1,191
141
153
84
93
53
122
81
12
98
0
23
86
44
Electronic Equipment
225
177
107
123
47
117
100
12
93
24
12
84
63
Hardware
324
143
150
59
229
119
12
204
36
57
96
102
Household Equipment
500
153
47
186
96
12
150
12
12
72
71
Instrument
297
56
144
120
12
132
36
12
93
82
Mobile Industrial Equipment
158
83
44
12
102
12
21
41
113
Motor Vehicle
518
56
12
289
24
57
65
90
Office Machine
156
12
56
36
12
81
52
Ordnance
12
12
0
0
0
12
Other Metal Products
714
35
45
33
135
Precious/Non-Precious Metals
113
0
12
12
Railroad
174
22
22
Ship and Boat
129
46
Stationary Industrial Equip.
216
Unknown
12
Source: U.S. EPA analysis.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
The rest of this profile characterizes MP&M facilities that
are expected to incur compliance costs under the proposed
effluent guidelines.
Out of a total population of 638,696 MP&M facilities
reported in the Statistics of U.S. Businesses for 1996,
effluent dischargers identified by the MP&M surveys
number an estimated 62,752 (10 percent).
Figure 3.2 shows the breakdown of MP&M facilities by
discharge type. Of the 62,752 effluent dischargers, 57,948
(92 percent) are indirect dischargers, while the remaining
4,804 (8 percent) are direct dischargers.
Figure 3.2: Facilities by Discharge Type
Figure 3.3: Number of Private Facilities by
Revenue Source
1,596
Both Manufacturing and
Rebuilding and Maintenance
Source: U.S. EPA analysis.
Small Business Administration (SBA) thresholds for small
businesses were applied to each facility to estimate the
number of facilities that are likely to be owned by small
businesses, as defined by the SBA. By using the
methodology detailed in Regulatory Flexibility Analysis (see
Chapter 10), EPA determined that 50,620 facilities (81
percent) are owned by small entities.
Figure 3.4: Facilities by Small Business Status
Source: U.S. EPA analysis.
Figure 3.3 shows facilities by revenue source, such as
manufacturing, rebuilding and maintenance, or government.
There are 35,485 facilities (61 percent) that perform
rebuilding and maintenance and 23,280 facilities (40
percent) that do manufacturing.
Small Business
Owned Facilities
50.620
Source: U.S. EPA analysis.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
Figure 3.5 indicates that MP&M facilities derive
approximately 22 percent of their revenues from export
sales. Almost 78 percent of MP&M revenues come from
domestic non-government sources. Governments account
for a very small share of MP&M revenues overall.
Figure 3.5: Facility Revenues by Market Type
(millions, 1999$)
Export data were not available for Iron and Steel surveys.
Source: U.S. EPA analysis.
The Pre-Tax Return on Assets (PTRA) is a useful
measure of industry profitability. It is well-defined,
commonly used, and can be calculated from data reported in
the facility surveys. Profits compensate investors not only
for the use of their capital, but also for the riskiness of their
investment. One firm might have a higher PTRA than
another but not be more profitable in economic terms,
because it is riskier.
Table 3.19 shows that the steel forming and finishing
subcategory has the highest median PTRA (15.9 percent) of
all the subcategories. The MP&M facilities may not be
typical of the Iron and Steel industry as a whole since they
produce only selected finished products. The shipbuilding
drydock subcategory has the lowest PTRA (2.5 percent).
Table 3.19: Financial
Performance
Median Pre-Tax Return
Subcategory on Assets (PTRA)
Shipbuilding Dry dock
General Metals
Steel Forming & Finishing
MF Job Shop
Non-Chromium Anodizer
Oily Wastes
Printed Wiring Boards
Railroad Line Maintenance
2.5%
13.5%
15.9%
6.8%
9.0%
12.9%
14.6%
n/a
Source: U.S. EPA analysis.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 3: Profile of the MP&M Industries
GLOSSARY
capital expenditures: expenditures for permanent
additions and major alterations to facilities and equipment, as
well as replacements and additions to capacity, which are
ordinarily depreciated. Reported capital expenditures include
work done on contract and expenditures for assets leased
from other concerns through capital leases. Expenditures for
land and cost of maintenance and repairs charged as current
operating expenses are excluded
employment: total number of full-time equivalent
employees, including production workers and non-
production workers.
export dependence: the share of shipments by domestic
producers that is exported; calculated by dividing the value
of exports by the value of domestic shipments.
import penetration: the share of all consumption in the
U.S. that is provided by imports; calculated by dividing
imports by reported or apparent domestic consumption (the
latter calculated as domestic value of shipments minus
exports plus imports).
manufacturing: series of unit operations necessary to
produce metal products; generally performed in a production
environment.
American Industry Classification System:
classification system adopted beginning in 1997 to replace
SIC codes. NAICS codes will be used throughout North
American and allow for greater comparability with the
International Standard Industrial Classification System
(ISIC), which is developed and maintained by the United
Nations. The new system also better reflects the structure of
today's economy, including the growth of the service sectors
and new technologies.
nominal values: dollar values expressed in current
dollars.
operating margin: measure of the relationship between
input costs and the value of production, as an indicator of
financial performance and condition. Everything else being
equal, industries and firms with lower operating margins will
generally have less flexibility to absorb the costs associated
with a regulation than those with higher operating margins.
Operating margins were calculated in this profile by
subtracting the cost of materials and total payroll from the
value of shipments. Operating margin is only an
approximate measure of profitability, since it does not
consider capital costs and other costs. It is used to examine
trends in revenues compared with production costs within an
industry; it should not be used for cross-industry
comparisons of financial performance.
pre-tax return on assets (PTRA): the ratio of cash
operating income (net income plus depreciation) to the book
value of total assets. This ratio is a measure of facility
profitability.
primary product shipments: an establishment's
shipments of products that are considered primary to its 4-
digit SIC code. An establishment is classified in a
particular4-digit SIC code if its shipments of the primary
products of that industry exceed in value its shipments of the
products of any other single industry.
producer price index (PPI): a family of indexes that
measures the average change over time in selling prices
received by domestic producers of goods and services
(Bureau of Labor Statistics, PPI Overview). Used in this
profile to convert nominal values into real dollar values.
real values: nominal values normalized using a price
index to express values in a single year's dollars. Removes
the effects of price inflation when evaluating trends in dollar
measures.
rebuilding/maintenance: unit operations necessary to
disassemble used metal products into components, replace
the components or subassemblies or restore them to original
function, and reassemble the metal product. These
operations are intended to keep metal products in operating
condition and can be performed in either a production or a
non-production environment.
Standard Industrial Classification: classification
system used for all establishment-based Federal economic
statistics classified by industry. Each establishment is
assigned a 4-digit SIC code based on its principal product, or
service. Last revised in 1987 and currently being replaced by
the NAICS.
value added: measure of manufacturing activity, derived
by subtracting the cost of purchased inputs (materials,
supplies, containers, fuel, purchased electricity, contract
work, and contract labor) from the value of shipments
(products manufactured plus receipts for services rendered),
and adjusted by the addition of value added by
merchandising operations (i.e., the difference between the
sales value and the cost of merchandise sold without further
manufacture, processing, or assembly) plus the net change in
finished goods and work-in-process between the
beginning-and end-of-year inventories. Value added avoids
the duplication in value of shipments as a measure of
economic activity that results from the use of products of
some establishments as materials by others. Value added is
considered to be the best value measure available for
comparing the relative economic importance of
manufacturing among industries and geographic areas.
value of shipments: net selling values of all products
shipped as well as miscellaneous receipts. Includes all items
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MP&M EEBA Part I: Introduction and Background Information Chapter 3: Profile of the MP&M Industries
made by or for an establishment from materials owned by it, as a proxy for revenues. This profile uses value of shipments
whether sold, transferred to other plants of the same to indicate the size of a market and how the size differs from
company, or shipped on consignment. Value of shipments is year to year, and to calculate operating margins.
a measure of the dollar value of production, and is often used
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MP&M EEBA Part I: Introduction and Background Information Chapter 3: Profile of the MP&M Industries
ACRONYMS
SIC: Standard Industrial Classification PPI: producer price index
NAICS: North American Industry Classification System PTRA: pre-tax return on assets
VOS: value of shipments
VA: value added
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MP&M EEBA Part I: Introduction and Background Information Chapter 3: Profile of the MP&M Industries
REFERENCES
DRI/McGraw-Hill and U.S. Department of Commerce, International Trade Administration. 2000. U.S. Industry and Trade
Outlook.
U.S. Bureau of Labor Statistics. 2000. Producer Price Index.
U.S. Department of Commerce. 1992. Bureau of the Census. Census of Manufactures, Census of Transportation, Census of
Wholesale Trade, Census of Retail Trade, Census of Service Industries.
U.S. Department of Commerce. 1996. Bureau of the Census. Annual Survey of Manufactures.
U.S. Department of Commerce. 2000. Bureau of the Census. Foreign Trade Data.
U.S. Environmental Protection Agency. 1995a. Profile of the Electronics and Computer Industry. EPA Office of
Compliance Sector Notebook Project. EPA 310-R-95-002. http://es.epa.gov/oeca/sector/index.html
U.S. Environmental Protection Agency. 1995b. Profile of the Fabricated Metal Products Industry. EPA Office of
Compliance Sector Notebook Project. EPA 310-R-95-007. http://es.epa.gov/oeca/sector/index.html
U.S. Environmental Protection Agency. 1995c. Profile of the Iron and Steel Industry. EPA Office of Compliance Sector
Notebook Project. EPA 310-R-95-005. http://es.epa.gov/oeca/sector/index.html
U.S. Environmental Protection Agency. 1995d. Profile of the Motor Vehicle Assembly Industry. EPAOfficeof
Compliance Sector Notebook Project. EPA 310-R-95-009. http://es.epa.gov/oeca/sector/index.html
U.S. Environmental Protection Agency. 1995e. Printed Wiring Board Industry and Use Cluster Profile. Design for the
Environment Printed Wiring Board Project. EPA 744-R-95-005.
http://www.epa.gov/opptintr/dfe/pwb/techreports/usecluster
U.S. Environmental Protection Agency. 1997. Profile of the Shipbuilding and Repair Industry. EPA Office of Compliance
Sector Notebook Project. EPA 310-R-97-008. http://es.epa.gov/oeca/sector/index.html
U.S. Environmental Protection Agency. 1998. Profile of the Aerospace Industry. EPA Office of Compliance Sector
Notebook Project. EPA 310-R-98-001. http://es.epa.gov/oeca/sector/index.html
U.S. Small Business Administration. Statistics of U.S. Businesses. http://www.sba.gov/advo/stats/int_data.html
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MP&M EEBA Part I: Introduction and Background Information
Chapter 4: Regulatory Options
Chapter 4: Regulatory Options
INTRODUCTION
The preamble accompanying the proposed rule describes the
regulatory options considered by EPA for the proposed
MP&M effluent guidelines. This chapter provides a brief
summary of the individual technology options and the
regulatory options.
4.1 SUBCATESORIZATTON
EPA may divide a point source category into subcategories
to address variations in products, raw materials, processes,
and other factors that result in distinctly different effluent
characteristics. Defining subcategories makes it possible to
establish effluent limitations that take into account
technological achievability and economic impacts unique to
each subcategory. EPA considered the following factors in
its evaluation of potential MP&M subcategories:
* unit operation,
> activity,
* raw materials,
> products,
* size of site,
> location,
- age,
> nature of the waste generated,
* economic impacts,
> treatment costs,
* total energy requirements,
> air pollution control methods,
* solid waste generation and disposal, and
> publicly-owned treatment work (POTW) burden.
The subcategories differ in part based on the type of
wastewater that facilities discharge, including:
CHAPTER CONTENTS:
4.1 Subcategorization 4-1
4.2 Technology Options 4-2
4.3 BPT/BAT Options for Direct Dischargers 4-3
4.4 PSES Options for Indirect Dischargers 4-4
4.5 NSPS and PSNS Options for New Sources 4-4
4.6 Summary of the Proposed Rule and Regulatory
Alternatives 4-5
Glossary 4-6
Acronyms 4-7
> facilities that discharge wastewaters with high
metals content, with or without oil and grease
(O&G): and
* facilities that discharge wastewaters containing
mainly O&G, with limited metals and associated
other organic constituents.
The subcategories identified by EPA in each group are:
Metal-bearing (with or without O&G):
* Non Chromium Anodizing,
* Metal Finishing Job Shops,
* Printed Wiring Board,
* Steel Forming & Finishing, and
> General Metals; and
Oil-bearing only:
* Shipbuilding Dry Docks,
* Railroad Line Maintenance, and
- Oily Wastes.
Section VI of the preamble accompanying the proposed rule
describes the basis for defining these subcategories. The
following are brief summaries of each proposed subcategory:
Non Chromium Anodizing: This subcategory includes
facilities that perform aluminum anodizing without the use of
chromic acid or dichromate sealants. The wastewater
4-1
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MP&M EEBA Part I: Introduction and Background Information
Chapter 4: Regulatory Options
generated at these facilities contains very low levels of
metals (except for aluminum) and toxic organic pollutants.
Metal Finishing Job Shops: These facilities must perform
one or more of the six operations regulated by the existing
Metal Finishing (40 CFR 433) and Electroplating (40 CFR
413) effluent guidelines, and must meet the definition of a
"job sAiop." The six metal finishing operations are
electroplating, electroless plating, anodizing, coating,
chemical etching and milling, and printed circuit board
manufacture. A job shop is a facility that owns no more
than 50 percent of the materials undergoing metal finishing.
EPA proposes to regulate Printed Wiring Board facilities
that are job shops under this subcategory, but is seeking
comment on this proposal.
Printed Wiring Board: These facilities manufacture,
maintain, and repair printed wiring boards (i.e., circuit
boards), not including job shops. They perform some
unique operations, including applying, developing, and
stripping of photoresist; lead/tin soldering; and wave
soldering.
Steel Forming & Finishing: This subcategory applies to
facilities that perform MP&M operations or cold forming
operations on steel wire, rod, bar, pipe, or tube. Other
operations on steel, including any hot forming operations for
steel, or cold forming, electroplating, or continuous hot dip
coating of other steel products, will be regulated under the
proposed revisions to the existing Iron and Steel
Manufacturing effluent guidelines (40 CFR 420).
General Metals: This subcategory is a catch-all for MP&M
facilities that discharge metal-bearing wastewater, with or
without oil-bearing wastewater, that do not fit into one of
the other metal-bearing subcategories described above. This
broad category includes facilities in all MP&M industry
sectors except printed wiring boards, and includes facilities
operated by states and municipalities.
Shipbuilding Dry Docks: This is one of two specific
subcategories that discharge only oil-bearing wastewaters,
the other being Railroad Line Maintenance. Other facilities
discharging only oil-bearing wastewater are classified in the
general Oily Wastes subcategory. This subcategory covers
MP&M process wastewater generated in or around dry
docks and similar structures, such as graving docks, building
ways, marine railways, and lift barges at shipbuilding
facilities. These structures include sumps or containment
systems that enable shipyards to control the discharge of
pollutants to the surface water. Wastewaters generated from
other operations at shipyards are not included in this
subcategory.
Railroad Line Maintenance: These facilities perform
routine cleaning and light maintenance on railroad engines,
cars, car-wheel trucks, and similar parts or machines. They
must discharge only from MP&M operations that EPA
defines as oily operations and/or washing of the final
product. This category does not include railroad
manufacturing facilities, railroad overhaul, or heavy
maintenance facilities.
Oily Wastes: The Oily Wastes subcategory is a catch-all for
all MP&M facilities that discharge only oil-bearing
wastewater from a specified list of unit operations, and that
are not Shipbuilding Dry Dock or Railroad Line Maintenance
facilities. Facilities in this subcategory are primarily machine
shops or maintenance and repair shops, including state and
municipal MP&M facilities. Like the General Metals
subcategory, Oily Wastes may include facilities in all of the
MP&M industry sectors except printed wiring boards.
4.2 TECHNOioey OPTIONS
EPA evaluated ten technology options that might be used to
treat wastewaters from the MP&M facilities. Table 4.1 lists
these technology options:
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MP&M EEBA Part I: Introduction and Background Information
Chapter 4: Regulatory Options
Table 4.1: Technology Options
Option # Description
For metal-bearing wastes
1
segregation of wastewaters, preliminary treatment (including oil-water
separation), chemical precipitation, and sedimentation using a clarifier
(chemical precipitation with gravity clarification)
in-process flow control and pollution prevention + option 1
segregation of wastewaters, preliminary treatment (including oil
removal by ultrafiltration), chemical precipitation, and solids separation
using a micro filter
in-process flow control and pollution prevention + option 3
For oil-bearing wastes
oil-water separation by chemical emulsion breaking
in-process flow control and pollution prevention + option 5
oil-water separation by ultrafiltration
in-process flow control and pollution prevention + option 7
9
10
oil-water separation by dissolved air flotation (DAF)
in-process flow control and pollution prevention + option 9
Source: U.S. EPA analysis.
The even-numbered options add in-process flow controls
and pollution prevention (i.e., pollution prevention,
recycling, and water conservation to allow recovery and
reuse of materials) to the treatment technologies specified in
the odd-numbered options. In all cases, options with in-
process flow control and pollution prevention cost less and
remove more pollutant than do the comparable options
without pollution prevention. This document analyzes only
the even-numbered options with flow control and pollution
prevention.
EPA defined specific effluent limitations based on a
statistical analysis of the performance of these technologies.
This analysis is described in the Technical Development
Document and the Statistical Support Document.
4.3 BPT/BAT OPTIONS FOR DIRECT
DISCHARGERS
EPA selected the Best Practicable Control
Technology Currently Available (BPT) for direct
dischargers in each subcategory based on the average of the
best performances within the industry of various ages, sizes,
processes, and other characteristics. The Agency considered
the cost of these treatment technologies relative to the
effluent reductions achieved to assess the cost-
reasonableness of these limitations. EPA then considered
application of the Best Available Technology
Economically Achievable (BAT) for priority and non-
conventional pollutants and Best Conventional
Pollutant Control Technology (BCT) for conventional
pollutants. The Agency is proposing BAT equivalent to
BPT for all subcategories except Railroad Line Maintenance
and Shipbuilding Dry Docks, for which EPA is not
proposing BAT limitations. EPA is also proposing to set
BCT equal to BPT for all subcategories.
Table 4.2 shows the technology basis for the proposed
option for BPT, BCT and BAT for each subcategory.
Table 4.2: Proposed Options For Direct
Dischargers: BPT, BCT and BAT
Subcategory
For metal-bearing wastes
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
For oil-bearing wastes
Oily Wastes
Railroad Line Maintenance
Shipbuilding Dry Dock
BPT
Technology
Option
2
2
2
2
2
6
10
10
BCT/BAT
2
2
2
2
2
6
BCL= 10
BAL not
proposed
BCL= 10
BAL not
proposed
Source: U.S. EPA analysis.
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MP&M EEBA Part I: Introduction and Background Information
Chapter 4: Regulatory Options
4.4 PSES OPTIONS FOR INDIRECT
DISCHARGERS
EPA evaluated Pretreatment Standards for Existing
Sources (PSES) for indirect dischargers by evaluating
whether pollutants would "pass through" POTWs, and
whether a combination of POTW treatment and the PSES
standards would achieve limitations equivalent to those
required for direct dischargers. The Technical Development
Document discusses the pass-through analysis. The same
ten technologies were considered for BPT and for PSES.
The Agency also considered a range of low flow exclusions
for indirect dischargers, to reduce burdens on permitting
officials and reduce the economic impacts of the rule.
Evaluation of the low flow cutoffs also considered the
amount of pollutant discharged by each subcategory and
flow size category.
Table 4.3 lists the technology options and exclusions
proposed for existing indirect dischargers.
Table 4.3: Proposed Options For Indirect
Dischargers: PSES
Subcatesory
For metal-bearing wastes
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
For oil-bearing wastes
Oily Wastes
Railroad Line Maintenance
Shipbuilding Dry Dock
Exclusions
1 mgy flow
cutoff
none
not prop
none
none
2 mgy flow
cutoff
PSES
Technology
Option
2
2
osed
2
2
6
not proposed
not proposed
a. Mgy = millions of gallons per year.
Source: U.S. EPA analysis.
4.5 NSPS AND PSNS OPTIONS FOR
NEW SOURCES
EPA is proposing Pretreatment Standards for New
Sources (PSNS) for new indirect dischargers and New
Source Performance Standards (NSPS) for new
direct dischargers. New facilities have the opportunity to
incorporate the best available demonstrated technologies,
including process changes, in-plant controls, and end-of-
pipe treatment technologies, without the cost of retrofitting.
EPA considered the same technologies discussed previously
for BPT/B AT and PSES as the basis for new source
technology. The Agency strongly considered more
advanced treatment options, however, because new sites
have the potential to install pollution prevention and
pollution control technologies more cost-effectively then
existing sources.
Table 4.4 lists the technology options and exclusions being
proposed for new direct and indirect dischargers.
-------
MP&M EEBA Part I: Introduction and Background Information
Chapter 4: Regulatory Options
Table 4.4: Proposed Options For New Direct Dischargers (NSPS)
and Indirect Dischargers (PSNS)
Subcatesory
For metal-bearing wastes
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
For oil-bearing wastes
Oily Wastes
Railroad Line Maintenance
Shipbuilding Dry Dock
NSPS
Technology
Option
4
4
2
4
4
6
10
10
PSNS
Exclusions
1 mgy flow
cutoff
none
not prop
none
none
2 mgy flow
cutoff
PSNS
Technology
Option
4
4
osed
4
4
6
not proposed
not proposed
Source: U.S. EPA analysis.
4.6 SUMMARY OF THE PROPOSED RULE
AND RESULATORY ALTERNATIVES
Table 4.5 summarizes the proposed rule for existing
sources. This table also describes two regulatory options
that EPA considered in the economics analysis:
Option 2/6/10, which applies the same
technologies for each subcategory, and eliminates
the low flow and subcategory exclusions of the
proposed rule; and
Option 4/8, which applies more stringent
technology requirements for all subcategories and
does not include low flow exclusions.
Table 4.5: Summary of Proposed Rule and Regulatory Alternatives for Existing Sources
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Oily Waste
Printed Wiring Board
Railroad Line Maintenance
Shipbuilding Dry Dock
Steel Forming & Finishing
Proposed rule
Technology option 2;
1 mgy flow cutoff for
indirect dischargers
Technology option 2
Technology option 2; no
PSES/PSNS for indirect
dischargers
Technology option 6;
2 mgy flow cutoff for
indirect dischargers
Technology option 2
Technology option 10; no
PSES/PSNS for indirect
dischargers
Technology option 10; no
PSES/PSNS for indirect
dischargers
Technology option 2
Option 2/6/10
Technology option 2
Technology option 2
Technology option 2
Technology option 6
Technology option 2
Technology option 10
Technology option 10
Technology option 2
Option 4/8
Technology option 4
Technology option 4
Technology option 4
Technology option 8
Technology option 4
Technology option 8
Technology option 8
Technology option 4
Source: U.S. EPA analysis.
4-5
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MP&M EEBA Part I: Introduction and Background Information
Chapter 4: Regulatory Options
GLOSSARY
Best Practicable Control Technology Currently
Available (BPT): effluent limitations for direct
discharging facilities, addressing conventional, toxic, and
non-conventional pollutants. In specifying BPT, EPA
considers the cost of achieving effluent reductions in
relation to the effluent reduction benefits. The Agency also
considers the age of the equipment and facilities, the
processes employed and any required process changes,
engineering aspects of the control technologies, non-water
quality environmental impacts (including energy
requirements), and such other factors as the Agency deems
appropriate. Limitations are traditionally based on the
average of the best performances of facilities within the
industry of various ages, sizes, processes, or other common
characteristics. Where existing performance is uniformly
inadequate, EPA may require higher levels of control than
currently in place in an industrial category if the Agency
determines that the technology can be practically applied.
Best Available Technology Economically
Achievable (BAT): effluent limitations for direct
dischargers, addressing priority and non-conventional
pollutants. BAT is based on the best existing economically
achievable performance of plants in the industrial
subcategory or category. Factors considered in assessing
BAT include the cost of achieving BAT effluent reductions,
the age of equipment and facilities involved, the processes
employed, engineering aspects of the control technology,
potential process changes, non-water quality environmental
impacts (including energy requirements), economic
achievability, and such factors as the Administrator deems
appropriate. The Agency may base BAT limitations upon
effluent reductions attainable through changes in a facility's
processes and operations. Where existing performance is
uniformly inadequate, EPA may base BAT upon technology
transferred from a different subcategory within an industry
or from another industrial category.
Best Conventional Pollutant Control Technology
(BCT): effluent limitations for direct discharging facilities,
addressing conventional pollutants. Conventional pollutants
include biochemical oxygen demand (BOD5), total
suspended solids (TSS), fecal conform, pH, and O&G.
BCT is the equivalent of Best Available Technology (BAT)
for control of conventional pollutants. EPA evaluates the
reasonableness of BCT candidate technologies by applying a
two-part cost test: (1) the POTW test, and (2) the industry
cost-effectiveness test. In the POTW test, EPA calculates
the cost per pound of conventional pollutant removed by
industrial dischargers to upgrade from BPT to a BCT
candidate technology, and then compares this cost to the
POTW cost per pound for similar pollutant load reductions.
The upgrade cost to industry must be less than the POTW
benchmark of $0.25 per pound (in 1976 dollars). In the
industry cost-effectiveness test, the ratio of the incremental
BPT to BCT cost divided by the BPT cost for the industry
must be less than 1.29 (i.e., the cost increase must be less
than 29 percent).
job shop: a facility that owns no more than 50 percent of
the materials undergoing metal finishing.
New Source Performance Standards (NSPS):
effluent limitations for new direct dischargers based on the
best available demonstrated control technology. NSPS
represents the greatest degree of effluent reduction
attainable through the application of the best available
demonstrated control technology for all pollutants (i.e.,
conventional, non-conventional, and priority pollutants). In
establishing NSPS, EPA considers the cost of achieving the
effluent reduction and any non-water quality environmental
impacts and energy requirements.
pass-through: pollutants "pass through" a POTW if they
are not removed by treatment and are present in the POTW's
discharges to waters of the U.S. EPA compares the
percentage of a pollutant removed by well-operated POTWs
achieving secondary treatment with the percentage of the
pollutant removed by facilities meeting BAT effluent
limitations. For purposes of defining PSES and PSNS, a
pollutant is determined to pass through if the median
percentage removed by a well-operated POTW is less than
the median percentage removed under BAT limitations.
Pretreatment Standards for Existing Sources
(PSES): categorical pretreatment standards for existing
indirect dischargers, designed to prevent the discharge of
pollutants that pass through, interfere with, or are otherwise
incompatible with the operation of POTWs. Standards are
technology-based and analogous to BAT effluent limitations
guidelines.
Pretreatment Standards for New Sources (PSNS):
pretreatment standards for new indirect dischargers,
designed to prevent discharges of pollutants that pass
through, interfere with, or are otherwise incompatible with
the operation of POTWs. Addresses all pollutants (i.e.,
conventional, non-conventional, and priority pollutants).
Based on the same factors as are considered in promulgating
NSPS.
4-6
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MP&M EEBA Part I: Introduction and Background Information Chapter 4: Regulatory Options
ACRONYMS
BAT: best available technology economically achievable NSPS: new source performance standards
BCT: best conventional pollutant control technology O&G: oil and grease
BPT: best practicable control technology currently POTW: publicly-owned treatment works
available PSES: pretreatment standards for existing sources
DAF: dissolved air flotation PSNS: pretreatment standards for new sources
MGY: millions of gallons per year
4-7
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
Chapter 5: Facility Impact Analysis
INTRODUCTION
The facility impact analysis assesses whether the proposed
MP&M effluent guidelines are likely to impose severe or
moderate economic and financial impacts on MP&M
facilities. EPA conducted tests of severe economic impacts
to assess the rule's economic achievability. Severe
impacts are facility closures and the associated losses in
jobs, earnings, and output at facilities that close due to the
rule. EPA also evaluated moderate economic impacts to
support its evaluation of regulatory options and to
understand better the rule's economic impacts. Moderate
impacts are adverse changes in a facility's financial
position that are not threatening to its short-term viability.
This regulation will affect three major categories of MP&M
facilities: privately-owned, railroad line maintenance, and
government-owned facilities. EPA developed separate
analytic methodologies for each type of facility:
1. Private MP&M facilities: This group includes
all privately-owned facilities that do not perform
railroad line maintenance. This major category of
facilities operates in various subcategories and
includes private businesses in a wide range of
sectors or industries, including facilities that
manufacture and rebuild railroad equipment. Only
facilities that repair railroad track and equipment
along the railroad line are excluded. There are
57,587 private MP&M facilities other than railroad
line maintenance facilities nationally that may be
affected by the rule, representing 91.8 percent of
the 62,752 facilities that discharge process
wastewater from MP&M activities.
2. Railroad line maintenance facilities:
Railroad line maintenance facilities maintain and
repair railroad track and vehicles. EPA
administered a separate economic and financial
survey to these facilities and applied a different
impact analysis methodology than that used for
other private facilities. This methodology
evaluated the aggregate impact of compliance costs
for facilities owned by a single railroad company
on the profitability and indebtedness of the railroad
operating company as a whole. There are 832
railroad line maintenance facilities in the analysis,
representing 1.3 percent of all facilities in the
analysis.
CHAPTER CONTENTS
5.1. Data Sources 5-2
5.2 Methodology 5-2
5.2.1 Converting Engineering Compliance
Costs and Financial Data 5-3
5.2.2 Market-Level Impacts and Cost
Pass-through Analysis 5-4
5.2.3 Impact Measures for Private Facilities ... 5-4
5.2.4 Impact Measures for Railroad Line
Maintenance Facilities 5-8
5.2.5 Impact Measures for Government-
Owned Facilities 5-8
5.3 Results 5-10
5.3.1 Baseline Closures 5-10
5.3.2 Price Increases 5-11
5.3.3 Overview of Impacts 5-12
5.3.4 Results for Indirect Dischargers 5-13
5.3.5 Results for Direct Dischargers 5-14
5.3.6 Results for Private Facilities 5-15
5.3.7 Results for Government-
Owned Facilities 5-16
5.3.8 Results by Subcategory 5-18
Glossary 5-20
Acronyms 5-21
References 5-22
3. Government-owned facilities:
Government-owned facilities include MP&M
facilities operated by municipalities, state agencies
and other public sector entities such as state
universities. Many of these facilities repair,
rebuild, and maintain buses, trucks, cars, utility
vehicles (e.g., snow plows and street cleaners), and
light machinery. Government-owned facilities
operate in two major subcategories: General Metals
and Oily Waste. There are 4,332 government-
owned facilities in the analysis, representing 6.9
percent of the total.
The specific methodology used to assess impacts differs for
each of the three types of MP&M facilities. In each case,
EPA established thresholds for measures of financial
performance and compared facilities' performance before
and after compliance with each regulatory option to these
thresholds.
This chapter describes the methodology used to assess
facility-level economic impacts for the three types of
facilities, and then presents the results of the analyses.
5-1
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
5.1 DATA SOURCES
The economic impact analyses rely on data provided by the
financial portion of the detailed questionnaires distributed to
MP&M facilities by EPA under the authority of Section 308
of the Clean Water Act. The surveys were conducted in two
phases, covering different MP&M industries in each phase.
The Phase I survey covered seven industry sectors and
reported data for fiscal years 1987 to 1989. The Phase II
survey covered an additional ten industry sectors (all
remaining MP&M sectors except Steel Forming &
Finishing, which was the subject of a separate survey) and
reported data for fiscal years 1994 to 1996.' EPA
administered each survey to a random stratified sample of
facilities and assigned each facility a sample weight based
on the stratification process and the number of facilities
surveyed, so that sample-weighted results would represent
all potentially-affected MP&M facilities in the U.S. The
results of the impact analyses for the sample facilities were
extrapolated to the national level using these facility sample
weights.
The survey financial data for private businesses included
three years of facility and parent firm income statements and
balance sheets and the composition of revenues by MP&M
business sector to which the facility's goods and services are
sold. Two versions of the Phase II financial survey were
used: the long survey, which also requested information on
facility liquidation values, and the short form, which did
not request liquidation values.
Data for facilities in the railroad line maintenance
subcategory came from a modified version of the Phase II
survey administered to railroad operating companies. The
questionnaire was modified because railroad operating
companies generally do not monitor financial performance
or collect financial data at the facility level for their
numerous line maintenance facilities. The railroad operating
companies reported the number of line maintenance
facilities in each operating unit, and provided both operating
company and parent firm financial data. They also provided
technical data for each line maintenance facility.
Data for facilities in the Steel Forming & Finishing
subcategory came from a 1997 Section 308 survey of iron
and steel facilities. This survey requested financial data
generally similar to that collected by the MP&M surveys,
including income statements and balance sheets for fiscal
years 1995-1997 for the facility and the parent firm.
Government-owned MP&M facilities provided data in the
Phase II Section 308 survey of municipal and other
government agency facilities. This survey requested
information on fiscal year 1996 sources and amounts of
revenue and debt levels for both the government entity and
their MP&M facilities, and demographic data for the
population served by the government entity.
In addition to the survey data, a number of secondary
sources were used to characterize economic and financial
conditions in the industries subject to the MP&M effluent
guidelines. Secondary sources used in the analyses include:
> Department of Commerce economic census and
survey data, including the Censuses of
Manufactures, Annual Surveys of Manufactures,
and international trade data;
* The Benchmark Input-Output Tables of the United
States, published by the U.S. Department of
Commerce's Bureau of Economic Analysis;
* Price index series from the Bureau of Labor
Statistics, Department of Labor;
U.S. Industry and Trade Outlook, published by
McGraw-Hill and the U.S. Department of
Commerce; and
* Industry trade publications.
5.2 METHO&OLoey
The facility impact analysis starts with compliance cost
estimates from the EPA engineering analysis and then
calculates how these compliance costs would affect the
financial condition of MP&M facilities. EPA first
eliminated from the analysis those facilities showing
inadequate financial performance in the baseline, that is, in
the absence of the rule. Baseline closures at these
facilities would have occurred with or without the rule.
EPA performed a cost pass-through analysis based on
historical input and output price changes for the years 1982
through 1991 to estimate how much prices might rise to help
cover the costs of compliance. The Agency then evaluated
how the compliance costs would likely affect the financial
health of the facility, taking any price changes into account.
A facility is identified as a regulatory closure if it would
have operated under baseline conditions but would fall
below an acceptable financial performance level when
subject to the new regulatory requirements. An avoided
baseline closure occurs if a facility fails the baseline tests
but passes the post-compliance tests. An avoided baseline
failure is rare but can occur when a facility that is very close
to the financial thresholds benefits from industry-wide price
1 Appendix A.I provides a detailed description of the surveys
and describes how EPA combined data from different surveys.
5-2
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
increases and incurs relatively low regulatory costs
compared to its competitors.
EPA also identified private MP&M facilities that would
likely incur some moderate impacts from the rule but that are
not expected to close as a result of the rule. The test of
moderate impacts examined baseline and post-compliance
financial ratios. Incremental moderate impacts are attributed
to the rule if both financial ratios exceeded threshold values
in the baseline (i.e., there were no moderate impacts in the
baseline), but at least one financial ratio fell below the
threshold value in the post-compliance case.
5.2.1 Converting Engineering Compliance
Costs and Financial Data
EPA made three adjustments to the engineering estimates of
compliance costs to support the economic impact analyses.2
First, the costs were converted to 1999 dollars. Second, the
costs estimated for privately-owned facilities were adjusted
for the effects of taxes. Finally, one-time capital costs were
annualized, to provide a total annualized compliance cost for
each facility.
EPA used two kinds of deflators to convert dollar values
into 1999 constant dollar equivalents. The Agency used the
Construction Cost Index (CCI) to update compliance
costs. The CCI is a price index that engineers often use to
estimate costs associated with building, installing, and
operating waste treatment equipment and facilities. The CCI
includes the costs of labor and building materials in 20
major cities. Table 5.1 shows CCI values from 1996 to
1999. Costs increased by 7.8 percent from 1996 to 1999.
Table 5.
Year
1996
1997
1998
1999
1 : Constructio
Value
5620
5825
5920
6060
i Cost Index
% Change
3.6%
1.6%
2.4%
Source: Engineering Nevus-Record
EPA used the Producer Price Index (PPI) to update
financial statement data for MP&M facilities. The PPI
measures average changes in selling prices that domestic
producers receive for their output. EPA used sector-specific
PPI averages to update financial data from Phase I survey
respondents to 1996, the base year of the analysis. EPA
applied an aggregate PPI to update from 1996 to 1999
dollars for both Phase I and Phase II survey data.
Table 5.2 shows aggregate PPI values for all finished goods.
Prices increased by 1.3 (133/131.3) percent from 1996 to
1999, and by 26.2 percent from 1987 to 1999 (133/105.4).
Table 5.2: Producer Price Index
Industrial Commodities
Year
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Value
102.6
106.3
111.6
115.8
116.5
117.4
119.0
120.7
125.5
127.3
127.7
124.8
126.5
% Change
3.6%
5.0%
3.8%
0.6%
0.8%
1.4%
1.4%
4.0%
1.4%
0.3%
-2.3%
1.4%
Source: Bureau of Labor Statistics
EPA adjusted compliance costs estimated for private sector
facilities to take account of the tax deducibility of these
costs. A 34 percent marginal income tax rate was used to
adjust costs to an after-tax equivalent. This rate is the
highest marginal federal corporate income tax rate, and is
used as a proxy for the combined effect of federal and state
income taxes. This report presents costs either before-tax or
after-tax, depending on the purpose of the analysis.
Finally, EPA annualized one-time compliance costs
(primarily capital costs) to provide annual costs that could
be compared with annual facility revenues. Total annual
compliance costs (TACC) is the sum of annual
operating and maintenance (O&M) costs and the
annualized equivalent of one-time costs, calculated over 15
years assuming a seven percent discount rate. The following
is the formula used to annualize one-time costs:
2 The engineering cost estimates are described in the
Technical Development Document accompanying this rule.
Annualized Cost = PV
r x (1 + r)n
(1 + r)" - 1
(5.1)
5-3
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
where:
PV =
r
t
present value of compliance costs,
discount rate (7% in this analysis), and
amortization period (15 years).
5.2.2 Market-Level Impacts and Cost
Pass-through Analysis
Increased costs associated with the proposed rule can be
expected to affect industry level prices and output. Changes
in prices and output in turn determine the ultimate
distribution of economic impacts among directly- and
indirectly-affected industries and their customers and
suppliers. The facilities and industries directly affected by
the proposed rule might ultimately experience little adverse
impact, for example, if they are able to recover most or all of
their added costs by raising prices to their customers or
lowering the prices paid to their suppliers. Some regulated
facilities and companies could even be better off financially
as a result of the rule, if they benefit from industry-wide
product price increases and incur no or relatively-low
compliance costs (e.g., they already have treatment in place).
Understanding impacts at the industry level is therefore
important to understanding who bears the impacts of the
proposed rule.
The MP&M effluent guidelines affect facilities in a very
wide range of industries, and some of those industries
produce a diverse slate of products that are sold in multiple
industrial sectors. Detailed partial equilibrium modeling of
product-level market dynamics in each of the affected
industries was therefore not feasible. EPA instead used a
combination of quantitative and qualitative methods to
estimate a proportion of compliance costs that might be
recovered through price increases in each MP&M sector.
This cost pass-through analysis provided sector-specific
coefficients that were applied to total compliance costs in
each sector to estimate percentage changes in prices and
revenues. EPA then evaluated facility-level impacts
assuming that all analyzed facilities in each sector benefit
from the same percentage increase in prices and revenues.
EPA did not conduct a zero-cost pass-through
analysis, because results of the Phase I analysis indicated
that the complexity of presenting two sets of results were not
warranted, given the slight difference in impact results
between the two cases.
The estimated cost pass-through potential for each sector
reflects an econometric analysis of historical pricing and
cost trends in each MP&M industry, coupled with a
qualitative market structure analysis. The market structure
factors include:
* Market power based on horizontal and vertical
integration;
* Extent of competition from foreign suppliers (in
both domestic and export markets);
> Barriers to competition, as indicated by
above-normal, risk-adjusted profitability; and
* The long-term growth trend in the industry.
EPA developed cost pass-through coefficients that indicate
the percentage of compliance costs that EPA expects firms
subject to regulation to recover from customers through
increased revenues.3 This approach may either overstate or
understate the true changes in revenue for any one particular
facility, depending on the diversity of products produced by
the facility and the percentage of competitors in each
product market that incur compliance costs.
This approach to estimating market-level adjustments is a
simplification because it does not simultaneously estimate
changes in prices and output. Instead, EPA estimated price
changes and then estimated changes in output based on
predicted closures, taking into account the effect of the
predicted price increases on facilities' financial performance.
It is difficult to assess how this simplified approach might
affect the estimated economic impacts of the rule. However,
EPA does not believe that the overall impact analysis results
are highly sensitive to the potential biases introduced by this
approach.
5.2.3 Impact Measures for Private
Facilities
a. Test of severe impacts
The analysis of severe impacts estimates the number of
facilities that could potentially close due to the regulation.
EPA predicted that a facility will close if compliance costs
cause the facility's overall financial performance to fall
below threshold levels. Compliance costs are determined by
the type and number of processes that a facility performs,
the characteristics of its wastewaters, and the level of
treatment performed in the baseline. EPA took the number
and type of processes and pollutants produced into account
when subcategorizing the industry. However, EPA was not
able to link estimated compliance costs to specific products.
Nor was EPA able to link facility financial performance to
specific products. It was therefore not possible to conduct
an impacts analysis at the product level.
In particular, the analysis does not consider output
reductions short of closure ~ for example, closing one of
several production lines/processes or continuing to produce
the same products at a reduced level. It is quite possible that
a facility with no or relatively low compliance costs for most
3 Appendix A.2 provides a detailed description of the cost
pass-through analysis.
-------
MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
processes could choose to out-source products made using a
process that had significant compliance costs associated
with it, instead of performing the process in-house. This is
particularly true if it is a process that is performed
infrequently. It is also possible that firms with multiple
facilities could consolidate similar processes at individual
facilities to reduce their compliance costs. These situations
are not considered in this economic impact analysis. There
are likely to be numerous options available to firms and
facilities that EPA is unable to model. Because of these
unknowns, estimated severe impacts are worst case and are
likely to be overstated. In addition, the relationship between
the compliance costs associated with the specific processes
performed, specific products made from these processes,
and the multiple industrial sectors to which these products
are sold, is unknown and can not be accounted for in this
analysis.
The methodology examines two facility-level financial
indicators to estimate closures.
After-Tax Cash F/ow(ATCF): EPA examined ATCF
over a three-year period to determine the financial condition
of private MP&M facilities. Facilities with negative cash
flows were considered candidates for closure, since
businesses generally cannot sustain a negative cash flow for
long periods of time.
Net Present Value (NPV): The present value of the
expected future cash flows minus the cost. EPA also
performed an NPV test for facilities that provided estimates
of liquidation values. This test compared the facility
liquidation value to the present value of expected future
earnings. The conventional model of business management
states that businesses can be expected to cease operations
when the value of closing (i.e., its liquidation value) exceeds
its value as an ongoing business (i.e., the present value of its
expected future earnings).
The following sections describe the calculation of these two
measures in more detail.
*ป After-tax cash flow test
The ATCF test examined whether a facility would lose
money on a cash basis over the three years covered by the
surveys. If the facility suffers a cash loss on average, then
EPA infers that the facility's management is under pressure
to change operations or business practices to eliminate
future losses. Management might do so by closing the
facility. The ATCF test involves calculating each sample
facility's average after-tax cash flow over the years for
which survey respondents reported income statement data.
The calculations are as follows:
1. Compute after-tax cashflow in 1999 dollars: EPA
averaged income statement data over the years for
which survey respondents reported data. For example,
if a facility reported income statement data for 1995,
1996, and 1997, then a simple average was calculated
for the three reported years and indexed to 1999 values.
The ATCF is calculated from survey facility financial
data as follows:
ATCF = ATI +D
or,
ATCF = [REV - (TC+I+D+T)] + D
= REV -TC -1 -T
(5.2a)
(5.2b)
where:
ATI
D
REV
TC
I
T
after-tax income;
depreciation;
revenue;
total costs, including operating costs and
fixed costs;
interest; and
all income taxes.
EPA considered the facility to be a potential baseline closure
if it had negative average ATCF before incurring regulatory
compliance costs. Baseline closures were excluded from all
further analyses.
2. Compute the average post-regulation after-tax cash
flow (ATCF), including regulatory compliance costs
and increases in revenue. EPA then examined the
post-compliance cash flow of a facility with
non-negative baseline cash flow, to determine both its
compliance costs and the benefits from any revenue
increases based on the cost pass-through analysis. EPA
adjusted the baseline ATCF to reflect the effects of the
regulation as follows:
ATCFpC = (1-T)[(REV+AREV)-(TC+AC)-(I+AI)]
-CC+[T(D+AD)]
(5.3)
where:
ATCFpc =
AREV =
AC
AI
cc
AD
post-compliance after-tax cash flow;
post-compliance change in revenue, as
calculated in the cost pass-through
analysis;
operating and maintenance costs of
compliance;
change in interest expense after borrowing
for compliance investments;
annual capital cost of compliance;
change in depreciation expense after
compliance investments; and
the marginal corporate income tax rate
(0.34).
5-5
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
All other variables are defined as in the baseline ATCF
calculation.
The operating and maintenance cost of compliance
(AC) is the change in costs estimated to result from
operating and maintaining pollution controls adopted to
comply with effluent guidelines. Operating costs include the
costs of monitoring. The annual capital cost of compliance
represents a payment on principal for debt-financed
compliance investments. Financing costs calculated are
based on a 7 percent rate. EPA calculated the change in
depreciation (AD) for tax purposes as the straight-line
depreciation of compliance investment outlays over a
15-year recovery period.
EPA determined that a facility with negative average post-
regulation ATCF was subject to severe financial stress under
the ATCF test and would be a candidate for post-regulatory
closure.
2. Calculate total after-tax cash flow (TATCF)
available for all capital on an after-tax, total capital
basis. EPA calculated cash flow on an after-tax, total
capital basis, to make the cash NPV and liquidation
values comparable. The measure of cash flow
discounted to calculate NPV includes interest payments,
and therefore includes payments available to total
capital, i.e., debt and equity. A comparable baseline
TATCF is calculated as follows:
TATCF =
REV - (TC + T)
ATCF +1
(5.4a)
which is equivalent to:
TATCF = (1-T)(REV-TC) + T(! + D)
(5.4b)
ซ> Net present value test
EPA applied the NPV test for survey respondents that
provided liquidation values, including any post-closure
costs or liabilities. Some facilities may have a financial
incentive to remain open and comply with the proposed
MP&M rule even in the presence of negative cash flows, if
they would incur substantial closure costs that exceed the
value recovered by selling assets. NPV is the present value
of expected future earnings less the liquidation value
(including closure and post-closure costs) of the business. A
business owner with a negative NPV is financially better off
closing and liquidating than keeping the business open.
Considering both the ATCF and the NPV tests improves the
accuracy of the closure analysis, because it identifies as
closures those facilities that would lose money and would
not incur substantial costs exceeding assets if they closed.
The NPV test includes these calculations:
1. Adjust for tax losses or gains on liquidation of facility
assets. EPA compared the facility's liquidation value
with a going-concern value based on after-tax cash
flow. EPA adjusted the calculated liquidation value for
the tax cost (or benefit) resulting from capital gains (or
losses). This adjustment involved subtracting asset
book values as reported in the facility's balance sheet
from the facility's reported asset liquidation values,
yielding a capital gain (or loss, if negative) on
liquidation. EPA also subtracted any reported
extraordinary liability items accompanying liquidation,
to yield a net gain (or loss) for tax purposes at facility
liquidation. Multiplying this value by the 0.34 tax rate
provided a net tax liability (or benefit, if the value was
negative) upon liquidation. EPA subtracted this value
from the reported liquidation value to give an after-tax
liquidation value. The methodology assumes that firms
have sufficient income to use all the tax gains due to
capital losses.
where:
TATCF = total after-tax cash flow available for all
capital;
REV = revenue;
TC = total costs, including operating costs and
fixed costs;
T = all income taxes (T = T X [REV - TC -1
D]);
ATCF = after-tax cash flow (as defined in the
ATCF test above);
I = interest;
T = corporate income tax rate; and
D = depreciation.
TATCF differs from ATCF in Eq. 5.4a only by the amount
of interest payments: ATCF is after-tax cash flow available
to equity, while TATCF is after-tax cash flow available to
all capital. Interest expense is not adjusted for taxes when it
is added back to the ATCF, however, since cash flow is
increased by the tax deducibility of interest expenses. The
benefit of the tax shield for both depreciation and interest is
explicitly shown in Equation 5.4b.4
Post-compliance changes in financial parameters are the
same as in the ATCF calculation (Equation 5.2).
3. Calculate the present value of TATCF over 15 years.
EPA estimated the present value of the facility's expected
future earnings by discounting TATCF over a 15-year
period using a seven percent cost of capital. The Agency
elected 15 years as the length of the discounting period
because EPA engineers expect compliance-related
investments to have a useful life of at least 15 years.
4 See Brealey and Myers, 1996 for a discussion of this method
of cash flow analysis and valuation.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
Extending the discounting period beyond 15 years would
have had little effect on the NPV test results because
discounting progressively reduces the contribution of
out-year values to the calculated present value. The PV of
TATCF is:
PV =
TATCFt
ฃo (1 + ACC)1
(5.5)
where:
PV
N
ACC =
present value of after-tax cash flows
available for all capital i.e., the estimated
value of the facility as a going concern,
the number of years of cash flows
analyzed minus one, since the first year's
cash flow does not need to be discounted
(N=14 in this analysis); and
average cost of capital (7% in this
analysis).
4.
Compute the NPV. The facility's NPV is the present
value of its TATCF minus its after-tax, discounted
liquidation value.
The NPV test threshold is zero. EPA presumes that the
owners of a facility with an NPV less than zero would close
the facility and liquidate its assets, if its cash flow is also
negative.
ซ> Severe impacts (closure) criteria
EPA applied the ATCF alone for facilities that did not
provide liquidation values. Facilities with negative baseline
ATCF are baseline closures and are not attributed to the
rule. Facilities with non-negative ATCF in the baseline case
but negative post-compliance ATCF are regulatory closures
due to the rule.
EPA applied both the ATCF and NPV tests to respondents
that provided liquidation values. Facilities that fail both
tests under baseline conditions are baseline closures.
Facilities that pass at least one of the two tests in the
baseline case but then fail both tests post-compliance are
regulatory closures attributable to the rule.
Employment losses due to regulatory closures are equal to
the employment numbers that each facility reported in its
survey response. Output losses equal the total revenue at
regulatory closures. Avoided baseline closures result in
corresponding employment and output gains. EPA
estimated national results by multiplying facility results by
facility sample weights.
b. Test of moderate impacts
EPA also conducted an analysis of financial stress short of
closure to identify moderate impacts due to the rule.
Facilities experiencing moderate impacts are not projected to
close due to the MP&M effluent guidelines. The rule might
reduce their financial performance to the point where they
might have somewhat more difficulty obtaining financing
for future investments, however.
The analysis of moderate impacts examined two financial
indicators:
Pre-Tax Return on Assets (PTRA): The ratio of cash
operating income to assets. This ratio measures facility
profitability.
Interest Coverage Ratio (ICR): The ratio of cash
operating income to interest expenses. This ratio measures
the facility's ability to service its debt and borrow for capital
investments.
Creditors and equity investors review the above two
measures as criteria to determine whether and under what
terms they will finance a business. The PTRA and ICR also
provide insight into a firm's ability to generate funds for
compliance investments from internally-generated equity,
i.e., from after-tax cash flow. The measures are defined as
follows:
PTRA (net operating income divided by total assets) is a
measure of the return earned on a firm's capital assets,
independent of the effects of tax and financial structure.
PTRA is a comprehensive measure of a firm's economic and
financial performance. If a firm cannot sustain a
competitive PTRA on a post-compliance basis, it may have
difficulty financing the treatment investment, whether
financing is to be obtained as debt, equity, or, more likely, a
blend of the two.
PTRA =
COI
TA
(5.6)
where:
PTRA = pre-tax return on assets,
COI = cash operating income, and
TA = total assets.
Since COI = REV - TC,
PTRA =
REV - TC
TA
(5.7)
where:
PTRA
REV
pre-tax return on assets,
revenue,
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
TC = total costs, and
TA = total assets.
ICR [pre-tax andpre-interest income (cash operating
income) divided by interest expense] is a measure of a firm's
ability to service its contractual financial obligations on the
basis of current, ongoing financial performance. Investors
and creditors will be concerned about a firm whose
operating cash flow does not comfortably exceed its
contractual payment obligations. The greater the ICR, the
greater the firm's ability to meet interest payments, and,
generally speaking, the greater the firm's credit-carrying
ability. ICR also provides a measure of the amount of cash
flow available for equity after interest payments.
ICR =
COI
(5.8)
where:
ICR
COI
I
interest coverage ratio,
cash income from operations, and
interest expense.
COI = REV - TC, therefore:
ICR =
REV - TC
I
(5.9)
where:
ICR
REV
TC
I
interest coverage ratio,
revenue,
total costs, and
interest expense.
Adjusting for the effects of MP&M compliance costs,
post-compliance PTRA and ICR are:
PTRA
pc
[(REV + AREV) - (TC + ATQ]
(TA + TI)
[(REV + AREV) - (TC +ATC +AI)]
(I + AI)
(5.10)
(5.11)
where:
PTRApc =
ATC =
pre-tax return on assets, post-compliance,
interest coverage ratio, post-compliance,
change in total cost due to compliance,
including an annual capital cost,
TI = treatment investment (assuming all of the
front-end outlay would be capitalized and
reported as an addition to assets on the
balance sheet),
A = the change in the value for all variables
due to compliance, and
all other variables are defined as before.
The incremental values for revenues, expenses, and interest
are the same as described in the ATCF test discussion.
EPA compared baseline and post-compliance PTRA to an 8
percent threshold and baseline and post-compliance ICR to a
threshold of 4 in this analysis. Both measures are important
to financial success and firms' ability to attract capital. EPA
assumed that firms with acceptable PTRA and ICR would
not be subject to financial distress. Firms that do not fall
below either threshold in the baseline but that do fall below
one or both of the thresholds as a result of the rule are
judged to experience moderate impacts short of closure
attributable to the rule.
5.2.4 Impact Measures for Railroad Line
Maintenance Facilities
The MP&M rule could potentially apply to some railroad
facilities that maintain and repair railroad track and that
perform similar operations on railroad and other vehicles.
Railroad representatives indicated during data collection that
the industry does not collect or monitor significant financial
data at the facility level. These discussions led EPA to
administer a modified version of the survey to railroad
operating units and to perform the primary economic impact
analysis at the operating unit level.
The analysis of impacts for railroad line maintenance
facilities uses the same measures of impact as for other
private MP&M facilities, but applies these measures for the
railroad operating unit as a whole. Compliance costs for
each railroad are the sum of compliance costs at each
MP&M railroad line maintenance facility identified by the
operating company.
5.2.5 Impact Measures for
Government-Owned Facilities
Government-owned MP&M facilities include all facilities
owned by government entities that discharge process
wastewater from MP&M activities. Most
government-owned facilities that fall under the MP&M rule
provide or support transportation services. These facilities
repair, rebuild, and maintain buses, trucks, cars, utility
vehicles (e.g., snow-plows and street cleaners), and light
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
machinery. The MP&M profile describes government-
owned facilities in detail.
A facility whose Rc is equal to or greater than one percent
fails this test.
Each government subject to the MP&M effluent guidelines
at its facilities has a number of choices, which include:
Contracting out the service to a private provider or other
governmental agency,
Discontinuing these services altogether, or
Paying for compliance and continuing operations.
The impact analysis does not predict how the government
will respond. The analysis evaluates only whether a
community incurring compliance costs and continuing
operations under the rule would incur a severe burden. A
government may choose a different option and avoid some
of the budgetary impacts estimated here.
EPA evaluated impacts for government-owned facilities by
using three tests. A government that fails all three tests is
likely to suffer severe adverse impacts as a result of the rule.
The first test is applied at the facility level, and the other two
tests are applied at the government level.
a. Impacts on site-level cost of service
test
The impacts on site-level cost of service test considers
whether a government-owned facility's compliance costs
exceed one percent or more of its total baseline cost of
service. This test is similar to the test used to assess impacts
on private facilities and firms, which compares costs to post-
compliance revenues. The facility will likely absorb
compliance costs within its current budget if those costs do
not exceed one percent of the total. Compliance costs in this
scenario will not significantly impact the municipal budget.
Costs in excess of one percent do not, in and of itself,
indicate that a budgetary impact will occur, but only that
additional analysis should be performed to determine if there
is an impact.
EPA calculated the ratio of compliance costs to cost of
service, Rc, for each government-owned facility as follows:
Rc =
TACC
"'Baseline
(5.12)
where:
Rc = ratio of compliance costs to cost of
service,
TACC = total annualized compliance cost for the
facility, and
CR^, = total baseline cost of service at the facility.
b. Impacts on taxpayers test
The impacts on taxpayers test evaluates the significance of
compliance costs to the people served by the government. A
government will fail this test if the ratio of total annualized
pollution control costs per household to median household
income exceeds one percent, post-compliance.
Post-compliance pollution control costs include all pollution
control costs (for whatever purpose) reported by the
government in the baseline plus the sum of MP&M effluent
guideline compliance costs at all MP&M facilities owned by
the government. This test closely follows the methodology
developed for EPA's Water Quality Standards Workbook
(EPA, 1995).
The survey requests information about current municipal
expenditures on pollution control. TACC for each
government-owned facility is the sum of costs and an
amortized capital cost. The sum of TACC at all MP&M
facilities for each government, plus baseline municipal
expenditures on pollution control, yields a post-compliance
total annualized pollution control cost. EPA divided total
annualized pollution control costs by the number of
households to calculate an average cost per household. The
questionnaire also asks for median household income in the
geographic area served by the responding government.
EPA calculated a ratio of compliance costs to median
household income, RH, for each government as follows:
ETACC,
(5.13)
MHI
where:
RH
ratio of total annualized pollution control
cost to median household income,
CBPC = total baseline municipal expenditures on
pollution control, and
TACQ = total annualized compliance cost for
government-owned facility /',
MHI = median household income for the
government jurisdiction.
Governments that incur compliance costs that cause this
ratio to exceed one percent fail this test. Governments that
fail this test in the baseline as well as post-compliance are
not judged to experience major budgetary impacts
attributable to the rule. If the rule causes an increase in this
ratio to above one percent, then EPA concludes that the rule
might present a burden to the taxpayers that support the
affected government. The calculation is a conservative
estimate of the impact on taxpayers because it does not take
into account the fact that non-residential taxpayers
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
(businesses) will bear some of the tax burden or that some
costs might be recovered in fees.
This test is used in EPA's Economic Guidance for Water
Quality Standards. This guidance is used by States and
EPA Regions to assess economic factors in setting or
revising water quality standards. The guidance includes as a
screening measure of economic impact, average total
pollution control cost per household divided by median
household income. A value less than one percent indicates
that a community would incur "little economic impact".5
c. Impacts on government debt test
The impacts on government debt test assesses the
government's ability to finance compliance with the rule by
issuing debt. A government must be able to finance capital
compliance costs in addition to meeting ongoing compliance
costs. Governments often finance capital compliance costs
by issuing debt. This criterion tests each government's
capacity to issue debt by examining the ratio of
post-compliance debt service costs to the government's total
revenue. This measure is analogous to the interest coverage
ratio for private firms.
The ratio of debt service costs to revenue , RD, for each
government is:
RD =
C,,
(5.14)
This criterion is used in EPA's MUNIPAY model. This
model is used in enforcement cases to assess whether
municipalities (e.g., towns, villages, cities, counties, and
public utilities) can afford to pay a specific level of
compliance costs, Superfund cleanup contributions, or
penalties. The model's affordability assessment limits the
amount of debt that can finance these costs, capping the debt
service ratio at 25 percent.6 A higher ratio "may reduce the
confidence of creditors that the municipality can repay its
debt on time." The MUNIPAY manual states that this value
slightly exceeds the "warning marks" found in the public
finance and management literature.
5.3 RESULTS
This section presents the results of the facility impacts
analyses. The first section presents the results of the
baseline closure analysis. Section 5.3.2 covers the price
increases predicted for the proposed rule, and subsequent
sections report the results of the analyses for the proposed
rule and the two other regulatory options that EPA analyzed.
Section 5.3.3 presents an overview of impacts for all
MP&M facilities, and then results are provided for indirect
dischargers (Section 5.3.4), direct dischargers (Section
5.3.5), private facilities (Section 5.3.6), and
government-owned facilities (Section 5.3.7). Section 5.3.8
provides results by subcategory.
5.3.1 Baseline Closures
where:
RD
DB
ck
TRR
debt-to-revenue ratio;
baseline municipal debt service costs
(principal payments and interest);
annualized capital cost of compliance,
summed over all government-owned
facilities in each government; and
baseline municipal revenue.
EPA judged that debt service costs above 25 percent of
revenues might impede a government's ability to issue debt
in the future and present a burden on the budget.
Table 5.3 shows the results of the baseline closure analysis
by subcategory. A total of 3,829 facilities have negative
average After-Tax Cash Flow (ATCF) and (where
calculated) a negative Net Present Value (NPV) in the
baseline. These facilities are projected to close in the
baseline and are not considered in the analysis of impacts
attributable to the proposed rule.
Appendix A provides information on typical average closure
rates in the MP&M industries. Census data show that over
10,000 facilities, or almost eight percent of all facilities in
these industries, close annually. The number of baseline
closures predicted in this analysis is consistent with this
typical closure rate, and may even slightly understate
baseline closures.
5 Source: EPA's Economic Guidance for Water Quality
Standards: Workbook (1995) (Chapter 2 "Evaluating Substantial
Impacts: Public Sector Entities"). Values between one and two
percent indicate potential "mid-range economic impact".
Governments with values above one percent are subject to further
analysis to determine whether a significant economic impact would
in fact occur.
6 Source: EPA Office of Compliance and Enforcement
Assurance, MUNIPAY User's Manual, September 1999, p. 4-14.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
Table 5.3: Summary of Baseline Closures
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Total Number of
Dischargers
29,975
1,530
190
635
153
29,425
832
11
62,752
Number of
Baseline
Closures
3,199
286
40
3
6
295
0
0
3,829
Percent Closing
in the Baseline
10.7%
18.7%
21.1%
0.5%
3.9%
1.0%
0.0%
0.0%
6.1%
Number
Operating in the
Baseline
26,776*
1,244
150
632
147
29,130
832
11
58,922*
* Excludes 64 facilities projected to close in the baseline that remain open under the proposed rule.
Source: U.S. EPA analysis
5.3.2 Price Increases
The price increases predicted for the proposed rule are
shown in Table 5.4. The percentage price increases are
small, falling well below one percent for most sectors and
less than two percent in all cases.
Table 5.4: Cost Pass-Through Analysis:
Percentage Price Increases under the
Proposed Rule by Sector
Percent Price
Sector Increase
Aerospace
Aircraft
Bus and Truck
Electronic Equipment
Hardware
Household Equipment
Instrument
Iron and Steel
Job Shop
Mobile Industrial Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious and Non-Precious
Metals
Printed Circuit Board
Railroad
Ships and Boats
Stationary Industrial
Equipment
0.02%
0.03%
0.15%
0.07%
0.49%
0.01%
0.30%
0.81%
1.91%
0.19%
0.10%
0.06%
0.38%
0.03%
0.24%
1.59%
0.05%
0.02%
0.17%
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
5.3.3 Overview of Impacts
Table 5.5 provides an overview of the numbers of facilities
closing and experiencing moderate economic impacts, by
regulatory option. These national estimates include all types
of dischargers (direct and indirect) and types of facilities
(private MP&M, railroad line maintenance, and
government-owned facilities.)
Table 5.5: Regulatory Impacts for All
Number of facilities operating in the baseline: total
private MP&M and railroad line maintenance
government-owned
Number of regulatory closures
Percent of facilities operating in the baseline that are regulatory
closures
Number of facilities operating post-regulation
Number of facilities below low flow cutoffs
Number of facilities with subcategory exclusions
Percent of facilities operating in the baseline excluded or below
cutoffs
Number of facilities operating subject to regulatory requirements
Number of facilities experiencing moderate impacts
Percent of facilities operating in the baseline that experience
moderate impacts
racilities by Option,
Proposed Rule
58,922
54,590
4,332
199
0.3%
58,787a
48,256a
955
83.5%
9,576
616
1.0%
National Estimates
Option 2/6/10
58,922
54,590
4,332
1,282
2.2%
57,640
57,640
2,216
3.8%
Option 4/8
58,922
54,590
4,332
2,963
5.0%
55,959
55,959
2,309
3.9%
a. Includes 64 avoided baseline closures general metals indirect dischargers below the low flow cutoffs that are projected to close in the baseline but
that remain open under the proposed rule.
Source: U.S. EPA analysis.
Table 5.5 shows that the proposed rule substantially reduces
facility-level impacts, compared to the alternative options
considered by EPA. Only 199 (0.3 percent) of the facilities
that continue to operate in the baseline close due to the
proposed rule. Another 83 percent of facilities that continue
to operate in the baseline are excluded from requirements,
due to either the low flow cutoff for indirect dischargers or
the exclusion of indirect dischargers in the Non-Chromium
Anodizing, Shipbuilding Dry Dock and Railroad Line
Maintenance subcategories. Significantly larger numbers of
facilities are projected to close under Option 2/6/10 and
Option 4/8 (1,282 and 2,963 respectively). See Chapter 4
for a discussion of the options, low flow cutoffs, and
subcategory exclusions.
All facilities that are not exempted and that do not close are
subject to requirements under these options. Of the 9,577
facilities that are subject to requirements and continue
operating post-compliance, 616 facilities experience
moderate impacts. These 616 facilities represent
approximately one percent of all facilities that continue to
operate in the baseline. Of the facilities with 616 moderate
impacts under the proposed rule, the rule caused 137 to fall
below the pre-tax return on assets threshold only, 38 to fall
below the interest coverage ratio threshold only, and 441 to
fall below both thresholds. Substantially more facilities
experience moderate impacts under the other two regulatory
options than under the Proposed Rule (2,216 for Option
2/6/10 and 2,309 for Option 4/8.)
Table 5.6 shows facility compliance costs by option,
discharge status, and subcategory. These compliance costs
are adjusted for the effect of taxes for privately-owned
facilities, and therefore represent costs as experienced by the
regulated facilities.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
Table 5.6: Total Annualized Facility" Compliance Costs
by Subcategory, Discharge Status, and Regulatory Option
(after-tax, million 1999$)
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories: Annual Costs
All Categories: Number of
Facilities Operating Post-
Compliance
All Categories: Number of
Facilities Operating Post-
Compliance Subject to
Requirements
Total Costs to Industry by Option,
Directs + Indirects
Proposed Rule
Direct
$132.3
$0.8
$1.7
$20.9
$9.3
$0.8
$1.4
$167.2
4,633
4,633
Indirect
$969.9
$80.1
$0.0
$93.4
$14.0
$4.3
$0.0
$0.0
$1,161.7
54,154
4,944
$1,328.9
Option 2/6/10
Direct
$132.3
$0.8
$1.7
$20.9
$9 3
$0.8
$1.4
$167.2
4,633
4,633
Indirect
$1,295.8
$80.1
$17.5
$93.4
$14.0
$143.8
$0.2
$0.1
$1,644.9
53,008
53,008
$1,812.1
Option 4/8
Direct
$195.1
$1.5
$3.0
$22.7
$50.0
$0.9
$0.4
$273.6
4,615
4,615
Indirect
$1,885.5
$112.1
$26.0
$141.2
$21.8
$457.4
$0.4
$0.1
$2,644.5
51,344
51,344
$2,918.1
a. This table includes facility compliance costs only. Chapter 11 discusses the social costs of the proposed rule and other options.
estimates in this table exclude baseline and regulatory closures, and are post- or after-tax.
Source: U.S. EPA analysis.
The
The large number of General Metals indirect dischargers
account for 73 percent of total compliance costs under the
proposed rule. Total compliance costs incurred by facilities
that continue to operate post-compliance are 36 percent
higher under Option 2/6/10 than under the proposed rule,
and 120 percent higher under Option 4/8 than under the
proposed rule.
5.3.4 Results for Indirect Dischargers
Table 5.7 summarizes the results of the facility impact
analysis for indirect dischargers, including both private
businesses and government-owned facilities.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
Table 5.7: Regulatory Impacts for Indirect Dischargers by Option, National Estimates
Number of facilities operating in the baseline: total
private MP&M and railroad line maintenance
government-owned
Number of regulatory closures
Percent of facilities operating in the baseline that are regulatory
closures
Number of facilities operating post-regulation
Number of facilities below low flow cutoffs
Number of facilities with subcategory exclusions
Percent of facilities operating in the baseline excluded or below
cutoffs
Number of facilities operating subject to regulatory requirements
Number of facilities experiencing moderate impacts
Percent of facilities operating in the baseline that experience
moderate impacts
Proposed Rule
54,270
50,592
3,678
179
0.3%
54,154a
48,256a
955
90.6%
4,943
575
1.1%
Option 2/6/10
54,270
50,592
3,678
1,262
2.3%
53,008
53,008
2,175
4.0%
Option 4/8
54,270
50,592
3,678
2,925
5.4%
51,345
51,345
2,199
4.1%
a. Includes 64 avoided baseline closures general metals indirect dischargers below the low flow cutoffs that are projected to close in the baseline but
that remain open under the proposed rule.
Source: U.S. EPA analysis.
Since indirect dischargers account for 92 percent of all
facilities that continue to operate in the baseline, these
results are similar to those shown in Table 5.5 for MP&M
facilities as a whole. Over 90 percent of the indirect
dischargers operating post-regulation are excluded from
requirements by the low flow cutoffs and the subcategory
exclusions for Non-Chromium Anodizing, Shipbuilding Dry
Dock and Railroad Line Maintenance facilities under the
proposed rule.
5.3.5 Results for Direct Dischargers
The analysis of facility impacts reflects the combined effects
of small increases in revenues due to price increases and
increased compliance costs for some facilities. Impacts on a
specific facility depend on how its costs increase relative to
its competitors', since all facilities benefit from the industry-
wide price increases. Some facilities can even be better off
financially under the proposed rule, for example, if they do
not have costs due to flow and subcategory exclusions, or
already have treatment in place and therefore incur minimal
costs. The analysis indicated that 64 indirect discharging
facilities would close under baseline conditions, but would
continue operating under the proposed rule. All 64 facilities
are in the general metals subcategory and below the low
flow cutoff. The combination of small revenue increases
and no compliance costs improves the financial performance
of these facilities sufficiently to avoid the projected closures.
Given the small number of these avoided closures (64
facilities out of almost 63,000 discharging facilities), EPA
ignores these positive outcomes in the following discussions
of facility impacts.
Table 5.8 summarizes the facility impact results for direct
dischargers. Direct dischargers represent 8 percent of all
facilities that continue to operate in the baseline. Table 5.8
shows that most direct dischargers operate subject to
requirements under the proposed rule. Only 0.4 percent of
direct dischargers are projected to close due to the rule. All
of the MP&M facilities that discharge directly to surface
waters either close or continue to operate under the proposed
rule subject to the effluent guidelines. Impacts under the
proposed rule are the same as Option 2/6/10 impacts, since
the proposed rule does not include exclusions or low flow
cutoffs for direct dischargers.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
Table 5.8: Regulatory Impacts on Direct Dischargers by Option, National Estimates
Number of facilities operating in the baseline
private MP&M and railroad line maintenance
government-owned
Number of regulatory closures
Percent of facilities operating in the baseline that are regulatory
closures
Number of facilities operating post-regulation subject to
requirements
Number of facilities experiencing moderate impacts
Percent of facilities operating in the baseline that experience
moderate impacts
Proposed Rule
4,653
3,999
654
20
0.4%
4,633
41
0.9%
Option 2/6/10
4,653
3,999
654
20
0.4%
4,633
41
0.9%
Option 4/8
4,653
3,999
654
37
0.8%
4,616
110
2.4%
Source: U.S. EPA analysis.
5.3.6 Results for Private Facilities
Table 5.9 provides the facility impact analysis results for
privately-owned facilities, including Railroad Line
Maintenance facilities. Again, because privately-owned
facilities account for 93 percent of all MP&M facilities that
continue to operate in the baseline, these results are similar
to the results reported for all MP&M facilities in Table 5.5.
Almost 84 percent of facilities operating post-compliance
are excluded from requirements under the proposed rule,
either by the low flow cutoffs for indirect dischargers or by
the exclusion for the three subcategories of indirect
dischargers.
Table 5.9: Regulatory Impacts for Private Facilities by Option, National Estimates
Number of privately-owned facilities operating in the baseline
Number of regulatory closures
Percent of facilities operating in the baseline that are regulatory
closures
Number of facilities operating post-regulation
Number of facilities below low flow cutoffs
Number of facilities with subcategory exclusions
Percent of facilities operating in the baseline excluded or below
cutoffs
Number of facilities operating subject to regulatory requirements
Number of facilities experiencing moderate impacts
Percent of facilities operating in the baseline that experience
moderate impacts
Proposed Rule
54,591
199
0.4%
54,456a
44,654a
955
83.5%
8,848
616
1.1%
Option 2/6/10
54,591
1,282
2.3%
53,309
53,309
2,216
4.1%
Option 4/8
54,591
2,963
5.4%
51,628
51,628
2,309
4.2%
a. Includes 64 avoided baseline closures general metals indirect dischargers below the low flow cutoffs that are projected to close in the baseline but
that remain open under the proposed rule.
Source: U.S. EPA analysis.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
5.3.7 Results for Government-Owned
Facilities
Table 5.10 provides facility impact analysis results for
government-owned facilities. The 4,332 government-owned
facilities that continue to operate in the baseline represent 8
percent of all MP&M facilities operating in the baseline.
The facility impact analysis does not include a methodology
for predicting closures for government-owned facilities, and
therefore assumes that all government-owned facilities
continue operating post-compliance. EPA estimated major
budgetary impacts for these facilities and the governments
that own them instead. The analysis considers impacts at
both the facility and at the government level.
Under the proposed rule, 83 percent of the
government-owned facilities would be excluded from
requirements because they fall below the low flow cutoff
proposed for indirect dischargers. All government-owned
facilities would be subject to requirements under Option
2/6/10 and Option 4/8. None of the options impose
compliance costs for government-owned facilities that
would result in significant budgetary impacts for the
governments that operate the facilities.
Table 5.10: Regulatory Impacts for Government -Owned Facilities by Option, National Estimates
Number of government-owned facilities operating in the baseline
& post-regulation
Number of facilities below low flow cutoffs
Number of facilities with subcategory exclusions
Percent of facilities operating in the baseline excluded or below
cutoffs
Number of facilities operating subject to regulatory requirements
Number of facilities experiencing impacts
Percent of facilities operating in the baseline that experience
significant budgetary impacts
Proposed Rule
4,332
3,603
83.2%
729
0
0%
Option 2/6/10
4,332
4,332
0
0%
Option 4/8
4,332
4,332
0
0%
Source: U.S. EPA analysis.
Tables 5.11 and 5.12 provide more detail on the results of
the facility impact analysis for government-owned facilities.
Table 5.11 shows the number of government-owned
facilities by type and size of government, and the number
that fall below relevant flow cutoffs under the proposed rule.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
Table 5.11: Number of Government -Owned Facilities
by Type and Size of Government Entity
# of government entities >
flow cutoff
# of government entities <
flow cutoff
# of government entities >
flow cutoff
# of government entities <
flow cutoff
# of government entities >
flow cutoff
# of government entities <
flow cutoff
Total
Municipal
Government
Large
60
512
SmalU
410
1,781
470
2,293
2,763
State
Government
Governments (poj
183
183
governments (pop
All Governn
183
183
366
County
Government
mlation> 50,000)
77
610
ilation <= 50,000)
481
nents
77
1,091
1,167
Regional
Governmental
Authority
0
36
0
36
36
Total
319
1,341
410
2,262
729
3,603
4,332
Source: U.S. EPA analysis of Municipal Survey.
Table 5.12 provides additional detailed information on the
results of the three tests performed in the government
impact analysis. The table shows that 215 facilities incur
costs exceeding one percent of their baseline costs of
service. EPA assumes that facilities whose compliance
costs fall below that threshold are likely to be able to absorb
the costs within their current budgets. Governments that
own MP&M facilities with compliance costs above that
threshold do not necessarily experience government-level
budgetary impacts, but should be evaluated further. The
government-level analyses consider the sum of compliance
costs incurred by each government for all its affected
MP&M facilities. The test of impacts on households also
considers the baseline pollution control costs paid by
governments, and the test of impacts on government debt
also considers the baseline debt service costs of the affected
government. None of the governments analyzed incurred
compliance costs under the proposed rule that would result
in their failing either of the government-level impacts tests
(impacts on households or impacts on government debt).
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
Table 5.12: Impacts on Governments of MP&M Facility Compliance Costs by Size of Government
Number of government-owned MP&M
facilities affected
Number and percent of governments
failing all three budgetary impact criteria
Individual Test Results: number andperct
Compliance costs > one percent of
baseline cost of service test
Impacts on taxpayers test
Impacts on government debt test
Owned by Small
Governments
2,672
number
0
nt of failure
140
0
0
percent
0%
s
5.2%
0%
0%
Owned by Large
Governments
1,660
number
0
75
0
0
percent
0%
4.5%
0%
0%
All Government-
Owned Facilities
4,332
number
0
215
0
0
percent
0%
5.0%
0%
0%
Source: U.S. EPA analysis.
The fact that no governments incur budgetary impacts at the
government level is not surprising. The MP&M activities
regulated under the proposed rule typically represent a very
small portion of governments' budgets. Even a significant
percentage increase in the cost of MP&M activities (as
measured by the comparison of post-regulation costs to
baseline costs) is unlikely to present any serious burden on
the budgets of the affected governments.
Moreover, the costs to government-owned facilities are quite
low. The large majority (3,603 or 83 percent) of the 4,332
government-owned facilities are excluded by the proposed
low flow cutoffs for Oily Waste and General Metals
subcategories, and therefore incur no costs. (All
government-owned facilities fall into one of these two
subcategories.) The facilities that are regulated include 212
facilities that incur no costs, and 517 that incur annualized
costs of $27,360 on average.
5.3.8 Results by Subcategory
Table 5.13 provides a summary of facility-level impacts by
subcategory, for indirect and direct dischargers separately.
This table shows that substantial portions of the General
Metals and Oily Waste indirect dischargers are exempted by
the low flow exemptions.
Metal Finishing Job Shops account for the largest number of
closures among indirect dischargers in the proposed rule,
and Printed Wiring Board and Metal Finishing Job Shop
facilities together account for the largest portion of moderate
impacts. Most of the direct discharger impacts (closures
and moderate impacts) are in the General Metals
subcategory, although the closures and moderately-impacted
facilities represent a small percentage of the General Metals
direct discharging facilities as a whole. See the regulatory
flexibility / SBREFA analysis in Chapter 10 for more
information on the Metal Finishing Job Shop and Printed
Wiring Board subcategories.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
Table 5.13: Regulatory Impacts by Subcategory, Proposed Rule, National Estimates
Subcategory
Indirect Dischargers
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Indirect Dischargers
Direct Dischargers
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Direct Dischargers
# Facilities
Operating
in Baseline
23,140
1,231
150
620
105
28,219
799
6
54,270
3,636
12
11
43
911
34
6
4,653
Regulatory
Closures
24
128
7
6
14
179
20
0
0
0
0
0
0
20
%
Closures
0.1%
10.4%
1.1%
5.7%
<.0.1%
0.3%
0.6%
0%
0%
0%
0%
0%
0%
0.4%
Exempted
20,164a
0
150
0
0%
28,092
799
6
49,2 lla
0
0
0
0
0
0
0
0
%
Exempted
87%
0%
100%
0%
0%
99.5%
100%
100%
91%
0%
0%
0%
0%
0%
0%
0%
0%
#with
Moderate
Impacts
153
117
301
4
0
575
34
0
0
7
0
0
0
41
%
Moderate
Impacts
0.7%
9.5%
48.7%
3.8%
0%
1.1%
0.9%
0%
0%
16.3%
0%
0%
0%
0.9%
a. Includes 64 avoided closures general metals indirect dischargers that are projected to close in the baseline but which operate under the proposed
rule and are eligible for the low flow cutoff.
Note: may not sum to totals due to independent rounding.
Source: U.S. EPA analysis.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
GLOSSARY
after-tax cash flow (ATCF): after-tax cash flow
available to equity.
avoided baseline closure: occurs if a facility fails the
baseline tests but passes the post-compliance tests.
baseline closure: facilities showing inadequate financial
performance in the baseline, that is, in the absence of the
rule. These facilities closures would have occurred with or
without the rule.
Construction Cost Index (CCI): measures how much it
cost to purchase a hypothetical package of goods and
services compared to what is was in the base year. It applies
to general construction costs. The CCI can be used where
labor costs are a high proportion of total costs. The CCI uses
200 hours of common labor, multiplied by the 20-city
average rate for wages and fringe benefits.
(http://www.enr.com/cost/costfaq.asp)
cost pass-through analysis: calculates the percentage
of compliance costs that EPA expects firms subject to
regulation to recover from customers through increased
revenues.
facility: a contiguous set of buildings or machinery on a
piece of land under common ownership.
government-owned facility: includes facilities operated
by municipalities, state agencies and other public sector
entities such as state universities.
interest coverage ratio (ICR): ratio of cash operating
income to interest expenses. This ratio measures the
facility's ability to service its debt and borrow for capital
investments.
liquidation value: net amount that could be realized by
selling the assets of a firm after paying the debt.
(http://www.duke.edu/~charvey/Classes/wpg)
moderate impacts: adverse changes in a facility's
financial position that are not threatening to its short-term
viability.
net present value (NPV): present value of the expected
future cash flows minus the cost.
(http://www.duke.edu/~charvey/Classes/wpg)
operating and maintenance (O&M): costs estimated to
result from operating and maintaining pollution controls
adopted to comply with effluent guidelines. Operating costs
include the costs of monitoring.
pre-tax return on assets (PTRA): ratio of cash
operating income to assets. This ratio measures facility
profitability.
private MP&M facility: includes all privately-owned
facilities that do not perform railroad line maintenance.
Producer Price Index (PPI): a family of indexes that
measures the average change over time in the selling prices
received by domestic producers of goods and services. PPI's
measure price change from the perspective of the seller. This
contrasts with other measures, such as the Consumer Price
Index (CPI), that measure price change from the purchaser's
perspective. Sellers' and purchasers' prices may differ due to
government subsidies, sales and excise taxes, and
distribution costs.
(http://stats.bls.gov/ppifaq.htnrfl)
railroad line maintenance facility: facilities that
maintain and repair railroad track and other vehicles.
regulatory closure: a facility that is predicted to close
because it can not afford the costs of complying with the
rule.
severe impacts: facility closures and the associated
losses in jobs, earnings, and output at facilities that close
due to the rule.
total after-tax cash flow (TATCF): after-tax cash flow
available to all capital.
total annualized compliance cost (TACC): sum of
annual operating and maintenance costs and the annualized
equivalent of one-time costs, calculated over 15 years
assuming a seven percent discount rate.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 5: Facility Impact Analysis
ACRONYMS
ATCF: after-tax cash flow
CCI: construction cost index
ICR: interest coverage ratio
O&M: operation and maintenance
NPV: net present value
PPI: producer price index
PTRA: pre-tax return on assets
TACC: total annualized compliance cost
TATCF: total after-tax cash flow
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MP&M EEBA Part II: Costs and Economic Impacts Chapter 5: Facility Impact Analysis
REFERENCES
Brealey, Richard A. and Stewart C. Myers. 1996. Principles of Corporate Finance, 5th edition. New York: McGraw-Hill.
U.S. Bureau of Labor Statistics, Producer Price Index Revision-Current Series. On-line database at
http://stats.bls.gov/ppihome.htm
U.S. Department of Commerce, Bureau of the Census, Annual Survey of Manufactures. On-line database at
http://www.census.gov/prod/www/abs/industry.html
U.S. Environmental Protection Agency. 1995. Interim Economic Guidance for Water Quality Standards Workbook. Office
of Water, Economics and Statistical Analysis Branch. March.
U.S. Environmental Protection Agency. 2000. Technical Development Document for the Proposed Effluent Limitations
Guidelines and Standards for the Metal Products & Machinery Point Source Category. EPA 821-B-00-005. December.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 6: Employment Effects
Chapter 6: Employment Effects
INTRODUCTION
The proposed MP&M rule may generate both positive and
negative impacts on employment. Facility closures induced
by the rule will result in reduced demand for labor and
compliance activities at facilities that close, but will also
increase employment requirements in facilities that remain
open and continue to operate. The regulation will also
create a demand for compliance-related equipment and
installation, which will also generate new employment
requirements.
EPA assumed that all projected facility closures would result
in the loss of full-time equivalents (FTEs).
The MP&M rule may affect overall employment in three
ways.
- Direct labor requirements. Direct labor
requirements are job losses associated with closures
and job gains associated with manufacturing,
installing, and operating compliance-related
equipment. Direct labor requirements also include
labor required to implement pollution prevention
activities associated with the rule.1
- Indirect labor requirements. Compliance
expenditures may increase employment in
industries doing business with waste treatment
providers. Economists refer to these as linked
industries. For example, a firm that
manufactures a treatment system will purchase
pumps, pipes, and other intermediate goods and
services from other firms and sectors of the
economy. Employment in these linked industries
increases when treatment equipment manufacturers
purchase goods and services from them. Closures
of MP&M facilities can also lead to reduced
requirements for inputs to MP&M industry
products, and therefore indirect job losses in the
supplier industries.
- Induced labor requirements. Increased
employment in the waste treatment industry
increases spending on consumer-oriented service
and retail businesses. Economists refer to the
CHAPTER CONTENTS:
6.1 Job Losses Due to Closures 6-2
6.2 Job Gains Due to Compliance Requirements .... 6-2
6.2.1 Direct Labor Requirements 6-2
6.2.2 Indirect and Induced Labor
Requirements 6-4
6.3 Net Effects on Employment 6-5
Glossary 6-7
Acronym 6-8
References 6-9
additional labor demand in the businesses
patronized by people working in the waste
treatment industry as "induced" labor requirements.
Conversely, people who are laid off from MP&M
facilities that close due to the rule may spend less,
resulting in induced reductions in employment in
sectors providing consumer services and products.
EPA estimates that the MP&M regulation may cause the
short-term loss of 5,916 direct full-time equivalent (FTE)
jobs due to facility closures, and a short-term gain in direct
employment of 4,488 FTEs for individuals necessary to
manufacture and install compliance equipment. The
regulation will also cause a continuing direct requirement
for 286 FTEs per year to operate and maintain the
compliance equipment.
The net effect on direct employment of the proposed rule is
an estimated 2,575 increase in FTE-years, a measure that
reflects both the number and the duration of jobs lost and
gained. This number represents an average gain of 172
FTEs per year over the 15 year analysis period.
The analysis assumes that workers losing their jobs due to
closures are out of work for an average of one year. If they
were out of work less time than that, the gain would be
higher.
The net gain in employment represents a very small
percentage of the total employment in the MP&M industries.
Given the small magnitude of the job gains and job losses
compared to overall employment in these industries, EPA
did not estimate indirect and induced employment gains and
losses due to the rule. EPA also did not estimate
employment gains in engineering and consulting services
associated with the compliance requirements.
1 See the Technical Development Document for more
information on compliance costs.
6-1
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 6: Employment Effects
The rest of this chapter explains how EPA estimated the
effects of the proposed MP&M rule on employment. The
first section discusses the impact of facility closures, and the
second section discusses the new employment associated
with the proposed rule. The final section discusses net
impacts on employment.
6.1 JOB LOSSES DUE TO CLOSURES
EPA projects that 199 facilities will close rather than
continue operating under the proposed rule, as discussed in
Chapter 5. EPA assumed that all employees working at
facilities that are projected to close will lose their jobs. The
ง308 surveys provide the number of employees at each
facility, expressed in FTEs. The job losses attributable to
the proposed rule are simply the sum of employment at the
plants projected to close. EPA did not analyze the job losses
that would occur if facilities cut back on production or
ceased production of products that required certain
processes instead of closing. The projected closure of 199
facilities results in a loss of 5,916 FTEs.
Table 6.1: Job Losses by Subcategory
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Estimated
Job Losses
1,415
2,065
0
976
952
509
0
0
5,916
% of Jobs in
Subcategory
0.01%
4.0%
0%
0.7%
4.2%
0.01%
0%
0%
0.03%
Source: U.S. EPA analysis.
Job losses equal 0.3 percent of employment in all water
discharging MP&M facilities, and 0.03 percent of all
employment in the industry. These are very small
percentages of all facilities operating in the baseline. The
subcategories with the greatest job losses are the Metal
Finishing Job Shops (8.4 percent of water dischargers in the
Subcategory), Steel Forming & Finishing (4.2 percent), and
Printed Wiring Boards (2.2 percent). The lost jobs represent
4.0 percent, 4.2 percent, and 0.7 percent of the total
employment at water discharging facilities in each
Subcategory respectively
Job losses due to closures in the General Metals Subcategory
total 1,415. which represent 0.2 percent of water
discharging facilities, and 0.01 percent of all employment at
water discharging facilities in the Subcategory. All other
subcategories have job losses that are less than one percent.
6.2 JOB SAINS DUE TO COMPLIANCE
REQUIREMENTS
6.2.1 Direct Labor Requirements
Direct labor requirements arise from employment necessary
to manufacture, install, and operate equipment that MP&M
facilities need to comply with the proposed rule, as well as
pollution prevention activities undertaken to comply with
the regulation. The following sections discuss labor
requirements associated with manufacturing compliance
equipment, equipment installation, and operation,
respectively.
a. Direct labor requirements for
manufacturing treatment systems
EPA estimated the direct labor requirements for
manufacturing wastewater treatment systems using three
steps:
* Calculate the cost of compliance equipment;
> Estimate the share of the cost of compliance
equipment due to labor inputs. This estimate shows
how much money goes to employees of equipment
manufacturers; and
* Convert the dollars spent on manufacturing
employees to a full-time employment equivalent
(FTE), based on a yearly labor cost.
ซ> Treatment system equipment cost
EPA estimated the cost of manufacturing treatment system
equipment for each facility estimated to stay open and to
comply with the regulation. This information is found in
the facility-level impact analysis (Chapter 5).
6-2
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 6: Employment Effects
The national estimate of capital costs for the proposed rule
is $1,339.6 million ($1999).2 This value includes the
purchase cost paid to manufacturers of compliance
equipment, and the costs of shipping, installation, insurance,
engineering, and consultants. Table 6.2 shows the
components of total capital costs for the proposed rule.3
The basic cost of compliance equipment is $632.3 million.
Table 6.2: Components of Proposed 1
Costs (thousand 1999$, before
Cost Component
a. Direct capital equipment cost
b. Shipping (27.4% of a)
c. Installation labor (9.6% of a)
d. Total installed direct capital costs
(a + b + c)
e. Indirect costs: insurance, engineering
& consultants (47.6% of d)
Total installed capital costs
iule Capital
tax)
Cost3
$632,301.7
$181,520.5
$93,773.5
$907,602.7
$432,018.9
$1,339,621.6
a. Excludes costs for baseline and regulatory closures.
Source: U.S. EPA analysis.
ซ> Labor share of treatment system cost
The Bureau of Economic Analysis (BEA) calculates direct
requirements coefficients that measure how many
dollars of each input are purchased to produce a dollar of a
given output.4 EPA used requirements coefficients for BEA
Sector 40, the "Heating, Plumbing, and Fabricated
Structural Metal Products Industry," for the employment
analysis. MP&M project engineers identified BEA Sector
40 as the industrial sector that most nearly matches the
businesses that would make, install, and operate waste
treatment systems for MP&M facilities complying with the
rule. The inputs into Sector 40 production include
intermediate goods, materials, and services, as well as labor.
2 The $1,339.6 million is the sum of one-time outlays for
purchasing and installing the capital equipment needed to comply
with the proposed rule. This expense is not the annual equivalent
of that capital investment. The capital outlay is annualized in the
economic impact analysis over a 15-year period. The resulting
value, which is part of the total annual cost of compliance, is
$112.2 million.
3 See the Technical Development Document for a description
of the methods used to estimate capital costs.
4 See "Benchmark Input-Output Accounts for the U.S.
Economy, 1992," in Survey of Current Business, July 1997, U.S.
Department of Commerce, Bureau of Economic Analysis.
BEA's direct requirements table shows that every dollar of
Sector 40 output delivered to final demand requires $0.30632
expended to compensate Sector 40 employees. Multiplying
labor's share of output value (30.63 percent) by the value of
compliance equipment purchases for the proposed rule
($632.3 million) yields the labor cost of manufacturing
treatment system equipment: $193.7 million. EPA assumes
that one-third of the equipment purchases and associated
labor costs would be incurred in each of the first three years
after promulgation of the rule.
* FTEjobs
EPA converted the total labor cost to the number of FTE-
equivalent jobs by dividing the total labor cost by an
estimated yearly labor cost per FTE employee. EPA used the
hourly labor rate used in the engineering cost analysis -
$29.67 per hour in 1996 dollars. The $29.67 per hour rate
includes fringe benefits (e.g., holidays, vacation, and various
insurances) and payroll taxes. EPA adjusted this amount to
1999 dollars using the Bureau of Labor Statistics
Employment Cost Index for manufacturing of durable goods,
to provide an hourly rate in 1999$ of $32.02. The gross
1999$ annual labor cost per FTE position for a 2,000-hour
work year is $64,040. EPA estimated that one-time spending
on manufacturing treatment system equipment would require
3,024 FTEs. Again, EPA assumed that one third of these
FTEs (1,008) would be associated with equipment purchases
in each of the first three years after promulgation of the rule.
b. Direct labor requirements for installing
treatment systems
EPA's estimate of the direct labor requirements to install
treatment system equipment parallels its methodology for
analyzing the labor requirements for equipment manufacture.
ซ> Treatment system equipment installation labor cost
MP&M project engineers estimate that installation labor
costs are seven percent of the total installed direct cost of
compliance equipment. The estimated one-time cost of
installation labor is $93.8 million for the proposed option.
(See Table 6.2.)
* FTEjobs
EPA used the loaded hourly labor cost of $32.02 per hour
and 2,000 hours per year to convert labor costs to numbers of
FTEjobs. Complying facilities will require an estimated
1,464 person-years of full-time employment to install the
equipment needed to comply with the proposed rule. This
corresponds to 488 FTEs in each of the first three years after
promulgation of the rule.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 6: Employment Effects
c. Direct labor requirements for operating
and maintaining treatment systems
MP&M project engineers estimated that labor costs
represent one percent of total compliance operating and
maintenance (O&M) costs. For the proposed rule, the labor
cost of O&Mis $18.3 million per year (1999$),
corresponding to 286 FTE positions per year at an hourly
rate of $32.02.
d. Total direct labor requirements
The total direct labor requirement for complying with the
proposed MP&M rule is the sum of the direct labor
requirements of manufacturing, installing, and operating
treatment systems. Table 6.3 summarizes the direct labor
requirements associated with compliance expenditures
under the proposed rule. These requirements include total
one-time expenditures to manufacture and install
compliance equipment equal to 4,488 FTEs, and continuing
requirements for operating and maintenance of 286 FTEs
per year.
Table 6.3: Direct Labor Requirements of the Proposed Rule,
National Estimates (thousands 1999 Dollars, before tax)
Year 1
Manufacturing (1/3 of $632,301)
Installation labor (1/3 of $93,774)
1/3 of Annual Operating and
Maintenance Cost ($18,288)
Year 1 Total
Year 2
Manufacturing (1/3)
Installation labor (1/3)
2/3 of Annual Operating and
Maintenance Cost
Year 2 Total
Year 3
Manufacturing (1/3)
Installation labor (1/3)
Annual Operating and Maintenance
Cost
Year 3 Total
Year 4 and Thereafter
Years 3-1 5, Total
Total Capital
Equipment
Cost
$210,767
$210,767
$210,767
Labor
Share
30.63%
30.63%
30.63%
Total Labor
Cost
$64,558
$31,258
$6,095.9
$64,558
$31,258
$12,191.9
$64,558
$31,258
$18,287.8
FTEsa
1,008
488
95
1,591
1,008
488
190
1,686
1,008
488
286
1,782
286
a. Number of jobs calculated on the basis of an average hourly labor cost of $32.02 and 2,000 hours per
labor-year.
Source: U.S. EPA analysis, Bureau of Labor Statistics, Bureau of Economic Analysis.
6.2.2 Indirect and Induced Labor
Requirements
In addition to direct labor requirements, the proposed
MP&M rule may also generate employment through the
indirect and induced effects described earlier. Economists
use multipliers to measure indirect and induced input
requirements. Multipliers indicate how much a region's
economy grows when a dollar is injected into a specific
industry at a specific location. When an MP&M facility
spends a dollar on treatment equipment, the businesses that
make, install, and operate the equipment earn a dollar.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 6: Employment Effects
These businesses in turn buy from other suppliers, who in
turn buy from still other businesses. In addition, employees
in the treatment system industry spend the money they earn
on groceries, homes, and other goods and services, thus
adding to the impact of that original dollar.
EPA considered a range of multipliers in this analysis to
illustrate the possible aggregate employment effects of an
MP&M rule. These industry multipliers are averages
reflecting both input-intensive activities and activities with
relatively few links to other industries. One earlier EPA
study used multipliers ranging from 3.5 to 3.9 to estimate
employment effects of general water treatment and pollution
control activities.5 A National Utility Contractors
Association (NUCA) study of "clean water investments"
documented total employment effect multipliers ranging
from 2.8 to 4.0.6 Using the high and low values among
multipliers cited in these studies (2.8 to 4.0), EPA estimates
that the indirect and induced economic effect of 286
continuing new direct jobs per year would create 801 to
1,144 full-time jobs in the rest of the economy.
EPA is not including a total estimate of indirect and induced
job gains and losses at this time, however, because (1) the
magnitude of losses and gains is very small at the national
level and occur across all states; and (2) the number of job
gains during the first three years of the regulation is close to
the number of job losses that could occur during the first
three years of the regulation. The job gains after the first
three years are expected to be approximately 286 jobs per
year, without any regulation associated losses. The low
magnitude of these gains means that it is highly unlikely that
there will be any secondary and induced impacts associated
with the proposed regulation.
6.3 NET EFFECTS ON EMPLOYMENT
It is difficult to predict overall impacts of the proposed
MP&M rule on employment, because the timing and
duration of changes in employment depend on a number of
factors. In a full-employment economy, unemployment due
to plant closures is likely to be short-lived, and the displaced
workers are likely to be employed again quickly in other
jobs. In less robust economic times, or in locations with
substantial local unemployment, unemployment among those
laid off from plants that close due to the rule may persist
longer.
The timing of the employment created by the rule is more
predictable. The rule will create a short-term demand for
labor in the early years of implementation, as facilities are
required to purchase and install equipment to comply with
the rule. The increased employment needed to operate and
maintain compliance systems will persist, presumably for the
life of the plant.
Table 6.4 provides an estimate of the level and timing of
direct impacts of the proposed rule on employment. This
estimate assumes that displaced workers are out of work for
one year on average, that facilities come into compliance or
close over a three year period, and that the requirements to
operate and maintain compliance systems continue for 15
years.
The proposed rule would result in a small net decrease in
direct employment in each of the first three years of
implementation, and then would require 286 FTEs in each
year after that. Summing employment each year over the 15
year analysis period indicates that the proposed rule would
result in a net increase of 2,575 "FTE-years" in direct labor
requirements. Averaged over the 15 year period, this
represents a gain of 172 FTEs a year.
Some of the FTEs required to comply with the rule (the
annual operating and maintenance requirements and possibly
some of the installation labor) will be hired in the same
industry sectors that lose employment due to closures. Other
FTEs will be gained in industries that supply pollution
control equipment to the MP&M industries. EPA does not
have specific information on where these equipment
manufacturing jobs will occur, but it is likely that some of
them will be within the MP&M industries as well, given the
nature of compliance equipment. (Waste treatment
equipment is often fabricated metal products and
machinery.) While it is difficult to determine what the net
effect on specific MP&M sectors will be, comparing the
estimated annual average net change in FTEs with total
employment in the affected industries provides some
measure of the potential overall impact of the net impact on
direct employment. The average net gain of 172 FTEs
equals a negligible percent of total annual employment in the
MP&M facilities potentially subject to the rule (water-
discharging facilities) and even less compared with total
1996 employment in the industries (SICs) that make up the
MP&M industries.7
Facilities that remain open and comply with the MP&M
regulations are likely to see an increase in their business
from closing facilities, assuming no change in demand. This
5 U.S. Environmental Protection Agency, 1993.
6 Apogee Research, Inc. 1992.
7 Total employment in the potentially regulated MP&M
facilities is 20,490,006 FTEs, as reported in the Section 308
surveys.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 6: Employment Effects
analysis does not take this potential increased business into
account in the estimation of job losses and gains. EPA also
did not consider the possible effects of excess capacity or
underemployment in the equipment manufacturing and
installation industries, and assumed that all compliance
requirements would result in proportional changes in
employment.
Table 6.4: Estimated Direct Net Impacts on Employment over 15 Years, Proposed Rule
(number of FTEs per year and total FTE -years)
Year
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Total FTE-years over 15
years
One-Time
Manufacturing &
Installation3
1,496
1,496
1,496
4,488
Annual O&Ma
95
190
286
286
286
286
286
286
286
286
286
286
286
286
286
4,003
Closures'"
1,972
1,972
1,972
5,916
Net Change in
Employment
(381)
(286)
(190)
286
286
286
286
286
286
286
286
286
286
286
286
2,575
a. Assumes that one-third of facilities come into compliance in each of 3 years/
b. Assumes that one-third of the facilities projected to close do so in each of the first 3 years.
Source: U.S. EPA analysis.
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MP&M EEBA Part II: Costs and Economic Impacts Chapter 6: Employment Effects
GLOSSARY
direct labor requirements: employment losses resulting from increased purchases or reduced output in the directly
from lost MP&M output caused by the rule and employment affected industries.
gains caused by compliance expenditures resulting from the
rule in the directly-affected industries. induced labor requirements: changes in employment
in industries providing goods and services to people whose
direct requirements coefficients: Bureau of Economic employment is directly or indirectly affected by the rule.
Analysis measure of the do liar value of specific inputs
purchased to produce a dollar of a given output. linked industries: industries that sell goods and services
to or purchase output from a directly-affected industry.
full-time equivalent (FTE): hours of employment
equivalent to one full-time job multiplier: a measure of the change in some aspect of the
size of the economy per unit change in employment or
FTE-year: one year of full-time employment spending; in this report, the total changes in employment
resulting from a unit change in direct labor requirements.
indirect labor requirements: changes in employment in
industries that supply directly affected industries resulting
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MP&M EEBA Part II: Costs and Economic Impacts Chapter 6: Employment Effects
ACRONYM
FTE: full-time equivalent
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MP&M EEBA Part II: Costs and Economic Impacts Chapter 6: Employment Effects
REFERENCES
Apogee Research, Inc. 1992. A Report on Clean Water Investment and Job Creation, prepared for National Utility
Contractors Association.
U.S. Bureau of Labor Statistics. 2000. Employment Cost Index - Historical Listing. July 27.
http://stats.bls.gov/ecthome.htm.
U.S. Department of Commerce. 1992 and 1997. Bureau of Economic Analysis, Regional Multipliers: A User Handbook for
the Regional Input-Output Modeling System (RIMSII), Second Edition and Third Edition. Washington, D.C.
U.S. Department of Commerce. 1997. Bureau of Economic Analysis, The 1992 Benchmark Input-Output Accounts of the
United States.
U.S. Environmental Protection Agency, Office of Water .1993. Job Creation Fact Sheet, internal document. February.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 7: Government and Community Impact Analysis
Chapter /: Government and
Community Impact Analysis
INTRODUCTION
In this chapter, EPA examines how the MP&M rule might
affect the economic welfare of communities, where
communities are defined as States, counties and
metropolitan areas. This chapter also summarizes
information on government impacts that supports EPA's
compliance with the Unfunded Mandates Reform Act
(UMRA).
Communities may suffer adverse impacts from a rule in two
ways. First, local governments may incur costs to comply
with the rule, if they operate MP&M facilities, or to
administer the rule. Second, communities may be affected if
MP&M facility closures resulting from the rule affect the
health of their local economies.
7.1 IMPACTS ON GOVERNMENTS
The proposed MP&M rule may have two effects on
governments:
* Government-owned MP&M facilities may be
subject to the proposed rule, and therefore incur
compliance costs; and
- Municipalities that own publicly owned
treatment works (POTWs) that receive influent
from MP&M facilities subject to the rule may incur
costs to implement the proposed rule. These
include costs of permitting MP&M facilities that
have not been previously permitted, and
repermitting some MP&M facilities with existing
permits earlier than would otherwise be required.
In addition, POTWs may elect to issue mass-based
permits to some MP&M facilities that currently
have concentration-based permits, at an additional
cost.
CHAPTER CONTENTS
7.1 Impacts on Governments 7-1
7.1.1 Impacts on Governments that
Operate MP&M Facilities 7-1
7.1.2 Government Administrative Costs ..7-1
7.2 Community Impacts of Facility Closures 7-5
Glossary 7-7
Acronyms 7-8
7.1.1 Impacts on Governments that
Operate MP&M Facilities
Chapter 5 presented EPA's analysis of the proposed rule's
impacts on government-owned MP&M facilities and on the
governments that own them. The analysis shows that the
proposed rule imposes only limited costs on government-
owned facilities, because 3,603 (83 percent) of the facilities
are exempted under the low flow cutoffs (110 General
Metals facilities and 3,492 Oily Wastes facilities.)
An estimated 215 government-owned facilities (5 percent of
the total) would incur costs under the proposed rule
exceeding one percent of their baseline cost of service.
Therefore, 95 percent of the government-owned facilities
either incur no costs or are likely to be able to absorb the
added costs within their existing budgets. None of the
affected governments incur costs that cause them to exceed
the thresholds for impacts on taxpayers or for government
debt burden. EPA therefore does not expect the proposed
rule to impose budgetary burdens on any of the governments
that own MP&M facilities.
7.1.2 Government Administrative Costs
State and local governments may incur costs to implement
the proposed rule for indirect dischargers. This section
describes the administrative activities involved and presents
estimates of their costs.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 7: Government and Community Impact Analysis
The federal and state governments will implement the
requirements for direct dischargers by incorporating the new
standards in existing NPDES permits. EPA does not expect
governments to incur incremental administrative costs as a
result of this rule for direct dischargers, since all direct
dischargers must already have NPDES permits.
Publicly owned treatment works (POTWs) will incur costs
to implement the proposed rule for indirect dischargers,
however. Permitting authorities will have to issue permits
for the first time to some indirect discharging facilities and
will have to accelerate repermitting for some indirect
dischargers that currently hold permits. Communities that
own POTWs that must issue permits will therefore incur
additional costs as a result of the proposed rule.
EPA is able to estimate total costs to POTWs, but is not able
to estimate the costs to any one POTW, since it is not
possible to determine what POTWs receive discharges from
the regulated MP&M facilities. EPA is also not able to
assess budgetary impacts on community-owned POTWs,
since available data do not provide estimates of financial
characteristics for the specific POTWs receiving effluent
affected by this rule. The relatively low POTW permitting
costs per facility estimated in this section for the proposed
rule suggest, however, that impacts on individual POTWs
will be minor.
a. Permitting activities
The General Pretreatment Regulations (40 CFR Part 403)
establish procedures, responsibilities, and requirements for
EPA, States, local governments, and industry to control
pollutant discharges to POTWs. Under the Pretreatment
Regulations, POTWs or approved States implement
categorical pretreatment standards (i.e., PSES and PSNS).
Discharges from an MP&M facility to a POTW may be
permitted in the baseline.1 For example, industrial users
subject to another Categorical Pretreatment Standard would
have a discharge permit. Other significant industrial users
(SIU) that are typically permitted by POTWs include
industrial users that:
discharge an average of 25,000 gallons per day or more of
process wastewater to a POTW;
contribute a process waste stream which makes up 5 percent
or more of the average dry weather hydraulic or organic
capacity of the POTW treatment plant; or
1 Under the General Pretreatment Program, a facility's
discharges may be controlled through a "permit, order or similar
means". For simplicity, this report refers to the control mechanism
as a permit.
have a reasonable potential for adversely affecting the
POTW's operation or for violating any pretreatment
standard.
EPA does not expect the costs of administering the
pretreatment program to increase due to the MP&M
regulation for facilities that already hold a permit specifying
the allowable mass of pollutant discharge to water.
Governments will incur additional permitting costs,
however, for unpermitted facilities and for any facilities
currently with a concentration-based permit that will be
issued a mass-based permit under the proposed rule instead.
b. Data sources
EPA collected information from POTWs to support
development of the MP&M effluent guideline. Of 150
surveys mailed, EPA received responses to 147, for a 98
percent response rate. The POTW survey asked respondents
to provide information on administrative permitting costs,
sewage sludge use and disposal costs and practices, and
general information (including number of permitted users
and number of known MP&M dischargers). The
administrative cost information included the number of
hours required to complete specific permitting and
repermitting, inspection, monitoring, and enforcement
activities. Respondents were also asked to provide an
average labor cost for all staff involved in permitting
activities. EPA used the survey responses on administrative
costs to estimate a range of costs incurred by POTWs to
permit a single MP&M facility.
c. Methodology
EPA performed the following steps to estimate total POTW
administrative costs for the proposed rule and other
regulatory alternatives:
ซ> Determine the number and characteristics of indirect
dischargers that will be permitted under the proposed rule.
The cost of permitting a given MP&M facility varies
depending on whether the facility is already permitted. EPA
has information from the MP&M facility surveys on
baseline permit status. Because costs differ by type of
permit (mass-based versus concentration-based), EPA
determined how many permits of each type would be issued.
All Steel Forming & Finishing facilities will require mass-
based permits under the proposed rule. Mass-based permits
are not required for the other subcategories. Permit writers
can determine what type of permit is appropriate for
facilities in subcategories other than Steel Forming &
Finishing. EPA is encouraging permit writers and control
authorities to issue mass-based permits and control
mechanisms, however, where appropriate and feasible. For
costing purposes, the analysis of permitting costs assumes
that one-third of the new or reissued permits in
subcategories other than Steel Forming & Finishing will be
mass-based. To the degree that POTWs do not require
mass-based permits in subcategories other than Steel
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 7: Government and Community Impact Analysis
Forming & Finishing, this analysis will overestimate
administrative costs.
ซ> Use the data from the POTWsurvey to determine a
high, middle, and low hourly burden for permitting a
single facility.
EPA defined the low and high estimates of hours such that
90% of the POTW responses fell above the low value and
90% of responses fell below the high value. The median
value is used to define the middle hourly burden.
ซ> Use the data from the POTW survey to determine the
aver age frequency of performing certain administrative
functions.
For administrative functions that are not performed at all
facilities, survey data were used to calculate the portion of
facilities requiring these functions. For example, the survey
data show that on average 38.5% of facilities submit a non-
compliance report.
ซ> Multiply theper-facility burden estimate by the
average hourly wage.
EPA determined a high, middle and low dollar cost of
administering the rule for a single facility by multiplying the
per-facility hour burden by the average hourly wage. The
POTW survey reported an average hourly labor rate of
$36.98 (1999$) for staff involved in permitting. This is a
fully-loaded cost, including salaries and fringe benefits.
ซ> Calculate the annualized cost of administering the
rule.
The number of facilities, hourly burden estimate, frequency
estimates, and hourly wage estimates are all combined to
determine the total cost of administering the rule. The type
of administrative activities required varies over time and the
total administrative cost is calculated over a 15 year time
period. EPA calculated the present value of total costs using
a seven percent discount rate, and then annualized the
present value using the same seven percent discount rate.
d. Unit costs of permitting activities
EPA estimated unit costs for the following permitting
activities:
Permit application and issuance: developing and issuing
concentration-based permits at previously unpermitted
facilities; developing and issuing mass-based permits at
previously unpermitted facilities; developing and issuing
mass-based permits at facilities with concentration-based
permits; providing technical guidance; and conducting
public and evidentiary hearings;
Inspection: inspecting facilities both for the initial permit
development and to assess subsequent compliance;
Monitoring: sampling and analyzing permittee's effluent;
reviewing and recording permittee's compliance self-
monitoring reports; receiving, processing, and acting on a
permittee's non-compliance reports; and reviewing a
permittee's compliance schedule report for permittees in
compliance and permittees not in compliance;
Enforcement: issuing administrative orders and
administrative fines; and
Repermitting.
EPA believes that theses functions constitute the bulk of the
required administrative activities. There are other relatively
minor or infrequent administrative functions (e.g.,
identifying facilities to be permitted, providing technical
guidance to permittees in years other than the first year of
the permit, or repermitting a facility in significant non-
compliance), but the associated costs are likely to be
insignificant compared to the estimated costs for the five
major categories outlined above.
Table 7.1 provides a summary of the estimated unit costs for
each permitting activity. Appendix C provides a detailed
discussion of these unit costs.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 7: Government and Community Impact Analysis
Table 7.1: Government Administrative Activities for Indirect Dischargers: Per Facility Hours and Costs
Administrative Activity
Develop and issue a concentration-based
permit at a previously unpermitted
facility
Develop and issue a mass-based permit
at a previously unpermitted facility
Develop and issue a mass-based permit
at a facility holding a concentration-
based permit
Provide technical guidance to a
permittee on permit compliance
Conduct a public or evidentiary hearing
Permittee inspection for permit
development
Permittee inspection for compliance
assessment
Sample and analyze permittee's effluent
Review and data entry of permittee's
compliance self-monitoring reports
Receive, process and act on a permittee's
non-compliance reports
Review a compliance schedule report
Minor enforcement action e.g., issue an
administrative order
Minor enforcement action, e.g., impose
an administrative fine
Repermit
Percent of facilities for which
activity is required
100% of unpermitted facilities being
issued a new concentration-based permit
(2/3 of new permits)
100% of unpermitted MP&M facilities
being issued a new mass-based permit
(1/3 of new permits )
All Steel Forming & Finishing facilities
with a concentration-based permits and
1/3 of other facilities with a
concentration-based permit
100% of MP&M facilities being issued a
new concentration-based permit
100% of MP&M facilities being issued a
new mass-based permit
3.2% of MP&M facilities being issued a
new mass-based or concentration-based
permit
100% of MP&M facilities being issued a
new permit
100% of MP&M facilities being issued a
new permit
100% of MP&M facilities being issued a
new permit
100% of MP&M facilities being issued a
new permit
38.5% of all indirect dischargers
receiving a new permit.
Meeting milestones: 16.0% of all
facilities issued a new permit (94% of
the 17% who have compliance
milestones).
Not meeting milestones: 1% of all
facilities issued a new permit (6% of the
17% who have compliance milestones).
7% of MP&M facilities being issued a
new permit
7% of MP&M facilities being issued a
new permit
100% of MP&M facilities being issued a
new permit
Frequency
of activity
One time
One time
One time
One time
One time
One time
One Time
Annual
Annual
Annual
5 times per year
2 reports per year
2 reports per year
Annual
Annual
Every 5 years
Typical hours and costs
Low
3. 7 hours;
$137
4.0 hours;
$148
2.0 hours;
$74
1.0 hour;
$37
2.0 hours;
$74
2.3 hours;
$85
2.3 hours;
$85
1.8 hours;
$67
1.0 hour;
$37
0.5 hours;
$18
1.0 hour;
$37
0.5 hours;
$18
0.8 hours;
$30
1.0 hour;
$37
1.0 hour;
$37
1.0 hour;
$37
Median
9.7 hours;
$359
12.0 hours;
$444
8.0 hours;
$296
3.3 hours;
$122
3.7 hours;
$137
8.0 hours;
$296
4.7 hours;
$174
3. 7 hours;
$137
3.0 hours;
$111
1.0 hour;
$37
2.0 hours;
$74
1.0 hour;
$37
1.8 hours;
$67
3. 7 hours;
$137
5.3 hours;
$196
4.0 hours;
$148
High
30.7 hours;
$1,135
40.0 hours;
$1,479
21.0 hours;
$777 year
10.7 hours;
$396
13.0 hours;
$481
33.3 hours;
$1,231
12.0 hours;
$444
10.0 hours;
$370
14.0 hours;
$518
3.5 hours;
$129
5. 7 hours;
$211
3.0 hours;
$111
6.0 hours;
$222
13.3 hours;
$492
24.7 hours;
$913
17.0 hours;
$629
Source: U.S. EPA analysis ofPOTW survey responses.
z. Results
Table 7.2 summarizes the estimated POTW permitting costs
for the proposed rule, Option 2/6/10, and Option 4/8.
Appendix C presents detailed calculations of permitting
costs for these regulatory options. These calculations reflect
the incremental number of facilities requiring different types
of permitting, inspection, monitoring, enforcement and
repermitting in each year multiplied by the unit hours and
cost per facility for those activities.
All facilities are assumed to receive a permit within a three-
year compliance period. Some facilities with existing
permits are repermitted sooner than they otherwise would be
on the normal five-year permitting cycle. The cost analysis
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 7: Government and Community Impact Analysis
calculates incremental costs by subtracting the costs of
repermitting these facilities on a five-year schedule from the
costs of repermitting all such facilities within three years.
EPA assumes that the required initial permitting activities
will be equally divided over the three-year period. The
analysis also calculates the net increase in the number of
facilities requiring permitting by subtracting the number of
facilities that close due to the rule from the number of
facilities that will require new permits under the proposed
rule.
Table 7.2: POTW Permitting Costs by Regulatory Option
Number of facilities permitted:
new concentration-based permit
new mass-based permit
conversion of existing
concentration-based to a mass-
based permit
POTW permitting costs over 1 5 years
(million 1999$):
net present value
annualized (@ 7%)
maximum costs in any one year
Proposed Rule
432
216
223
high
$8.3
$0.9
$1.6
med.
$2.5
$0.3
$0.5
low
$1.0
$0.1
$0.2
Option 2/6/10
16,009
8,004
8,424
high
$357.7
$39.3
$55.9
med.
$107.1
$11.8
$17.2
low
$45.7
$5.0
$7.2
Option 4/8
15,119
7,559
8,422
high
$332.6
$36.5
$52.3
med.
$99.7
$10.9
$16.1
low
$42.5
$4.7
$6.7
Source: U.S. EPA analysis.
EPA estimates that POTWs as a whole will incur
incremental average annualized costs over 15 years of
between $115,000 and $912,000 under the proposed rule.
These costs include issuing new permits to facilities that do
not currently have permits, issuing mass-based permits to
some facilities that currently have concentration-based
permits, and repermitting some facilities sooner than would
otherwise be required to meet the three-year compliance
schedule. On average, a POTWs costs for the incremental
permitting are only $23 to $184 per permitted MP&M
indirect discharger under the proposed rule.
EPA expects that these increases in costs will be partially
offset by reductions in government administrative costs for
facilities that are already permitted under local limits and
that will be repermitted under this rule. The technical
guidance provided by EPA as a part of this rulemaking may
reduce the research required by permit writers in developing
Best Professional Judgement (BPJ) permits for industrial
dischargers not previously covered by a categorical standard
or a water quality standard. Further, the establishment of
discharge standards may reduce the frequency of evidentiary
hearings. The promulgation of limitations may also enable
EPA and the authorized States to cover more facilities under
general permits. EPA did not estimate these cost savings to
permitting authorities that may result from the rule.
The proposed option requires substantially less permitting
by POTWs than the other two options, because a large
percentage of facilities that would otherwise have to be
permitted are excluded by low-flow cutoffs or subcategory
exclusions. Option 2/6/10 results in slightly higher
permitting costs than Option 4/8, because more facilities
would close under Option 4/8 and therefore not have to be
permitted.
7.2 COMMUNITY IMPACTS OF FACILITY
CLOSURES
EPA considered the potential impacts of changes in
employment due to the proposed rule on the communities
where MP&M facilities are located. Changes in
employment due to the rule include both job losses that
occur when facilities close and job gains associated with
facilities' compliance activities. EPA estimated that a total
of 5,916 jobs would be lost at the 199 facilities projected to
close under the proposed rule. (See Chapter 6.) At the same
time, EPA estimated that manufacturing and installing
compliance equipment would lead to 4,488 full-time
equivalent (FTE) positions, and that operating and
maintaining compliance systems would result in another 286
FTEs per year. Over a 15 year analysis period, the net effect
of job gains and losses caused by the rule is an increase of
2,575 FTE-years or an average of 172 FTEs per year. This
estimate assumes that workers that lose their job are
unemployed for an average of one year, and that compliance
investments and closures occur evenly over the first three
years after promulgation. This estimate of employment
impacts is likely to understate the net increase, because it
ignores the fact that some production and employment lost at
7-5
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MP&M EEBA Part II: Costs and Economic Impacts Chapter 7: Government and Community Impact Analysis
closing plants is likely to result in increased production and to predict precisely where the job gains and losses will
employment at other MP&M facilities. occur. However, facilities that are projected to close due to
the rule have employment ranging from 2 to 205 FTEs.
Given the projected overall increase in employment due to MP&M facilities tend to be located in industrialized urban
the proposed rule, EPA does not expect the rule to have areas, and closures of this size are not likely to have a major
significant impacts at the community level. It is not possible impact on a local economy.
7-6
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 7: Government and Community Impact Analysis
GLOSSARY
publicly owned treatment works: a treatment works as
defined by section 212 of the Clean Water Act, which is
owned by a State or municipality. This definition includes
any devices or systems used in the storage, treatment,
recycling, and reclamation of municipal sewage or industrial
wastes of a liquid nature.
(http://www.epa.gov/owm/permits/pretreat/final99.pdf)
Unfunded Mandates Reform Act: Title II of the
Unfunded Mandates Reform Act of 1995 (UMRA), Public
Law 104-4, establishes requirements for Federal agencies to
assess the effects of their regulatory actions on State, local,
and Tribal governments and the private sector. Under ง202
of the UMRA, EPA generally must prepare a written
statement, including a cost-benefit analysis, for proposed
and final rules with "Federal mandates" that may result in
expenditures to State, local, and Tribal governments, in the
aggregate, or to the private sector, of $100 million or more
in any one year. Before promulgating an EPA rule for
which a written statement is needed, ง205 of the UMRA
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.
7-7
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MP&M EEBA Part II: Costs and Economic Impacts Chapter 7: Government and Community Impact Analysis
ACRONYMS
POTW: publicly owned treatment works UMRA: Unfunded Mandates Reform Act
7-8
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 8: Foreign Trade Impacts
Chapter 8: Foreign Trade Impacts
INTRODUCTION
EPA assessed the proposed rule's likely impacts on foreign
trade, as part of its analysis of the rule's effect on the
national economy. Changes in the balance of trade have the
potential to affect currency exchange rates, money supply,
interest rates, inflation, capital flows and labor migration.
The MP&M industries include a substantial portion of the
nation's economy, and significant impacts on the balance of
trade in these industries could have an effect on the overall
economy. The trade analysis presented in this chapter
indicates that the MP&M rule will not have a significant
impact on the balance of trade in commodities, however,
either for the MP&M industries or for the economy as a
whole.
Chapter 5 estimated price increases and losses in output
likely to result from the rule. EPA assessed the impact of
these market-level changes on the U.S. balance of trade
using information provided by MP&M private facility
surveys on the source of competition in domestic and
foreign markets. The trade analysis allocates the value of
changes in output for each facility that is projected to close
due to the rule to exports, imports or domestic sales, based
on the predominant source of competition in each market
reported in the surveys.
8.1 DATA SOURCES
The 199 facility closures identified in Chapter 5 are used to
determine foreign trade impacts. Each closed facility's
revenues are lost output that can be attributed to the rule.
The analysis uses survey responses to determine whether a
closed facility's revenues are more likely to be replaced by
either domestic or foreign producers. Question 5 in the
Phase I ง308 survey asked respondents to identify their
"major source of competition" in each of three markets:
local/regional, national, and international. Question 8 in the
Phase II survey asked respondents to identify their "most
significant source of competition" in domestic and
international markets.
Respondents selected one of the following possible
responses:
CHAPTER CONTENTS:
8.1 Data Sources 8-1
8.2 Methodology 8-2
8.3 Results 8-2
References 8-4
> domestic firms,
> foreign firms,
* no competition in this market, and
* do not operate in this market.
During the process of clarifying survey answers with
respondents, EPA found that most of those respondents who
did not select any of the sources of competition said that
they did not participate in the relevant market. Therefore, if
a respondent did not answer the question regarding the most
important source of competition in the domestic or
international markets, EPA classified the facility as not
operating in the respective market (domestic or foreign.)
The analysis also uses survey responses to determine
revenues from exports. The Phase I ง308 survey reported
the percentage of revenues earned from domestic customers
and from overseas markets. EPA used export share and total
revenues for each facility to calculate export and domestic
revenues. The Phase II survey asked respondents to report
revenues from MP&M exports. EPA then calculated
domestic sales by subtracting export revenues from total
revenues for each facility.
The Iron & Steel survey did not report comparable
information on the source of competition in domestic and
foreign markets. EPA relied on published trade statistics for
the products produced by facilities in the Steel Forming &
Finishing subcategory to assess potential impacts on trade
for these facilities.
EPA obtained 1999 import and export data from the Bureau
of the Census, Foreign Trade Division for those
commodities determined to be MP&M-related. The data
included imports and exports by all facilities in relevant
industries, including both dischargers and non-dischargers.
8-1
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 8: Foreign Trade Impacts
8.2 METHO&oioey
The effect of an increase in domestic production costs on the
foreign trade balance is influenced by a variety of factors,
including:
* the extent to which domestic producers attempt to
raise prices to recover costs,
* the price elasticity of demand in both domestic and
export markets,
* the likely pricing and supply response of foreign
producers, and
> trends in currency exchange rates.
EPA did not attempt to model changes in prices, output, and
sales in domestic and foreign markets simultaneously for all
of the products and services involved in the MP&M
industries. As in the facility impact analysis described in
Chapter 5, the trade analysis relies on a sequential analysis
that assesses price increases and then predicts output
adjustments based on closures. EPA used the facilities' own
assessments of their competitive status relative to foreign
producers, as reported in the survey, to assess impacts of
these output adjustments on the balance of trade.
EPA expects that foreign firms will replace some but not all
of the output from closing facilities. Domestic firms that
remain open or enter the market may also win customers that
used to buy from the closing facility. Revenues lost by
closing facilities are assigned to domestic or foreign
producers as follows:
Lost exports: If a closing facility stated that most of its
international competition came from foreign firms, then
EPA assigned the facility's export revenues to foreign firms.
U.S. exports would therefore decline by the amount of the
closing facility's exports. If the facility identified domestic
businesses as its greatest source of competition in foreign
markets, then EPA assigned the closing facility's export
revenues to undetermined other domestic firms. Closures of
these facilities, which reported relatively low foreign
competition for exports, will have no impact on U.S. exports
under the expected scenario.
Increased imports: If a closing facility in the domestic
sector identified foreign producers as the main source of
competition, then EPA assigned the facility's lost domestic
revenues to foreign firms. Imports would increase by the
same amount. If other domestic businesses posed the
strongest competition, then EPA assigned the closing
facility's domestic sales to undetermined other U.S.
producers, and imports would remain constant.
Six Steel Forming and Finishing facilities are projected to
close under the proposed option. These six facilities have
revenues in total of only $326,860. This represents an
insignificant portion of the total imports, $51.9 billion1 or
less than 0.01 percent. The survey data collected for the
Steel Forming and Finishing facilities did not provide export
data. EPA assumed that the ratio of exports to value of
shipments in the industry as a whole was the same as those
closing facilities in our analysis. This assumption results in
total lost exports of $28,565 which also represents less than
0.01 percent of total exports in the industry amounting to
$937.7 million. Therefore, EPA assumed that the small
output lost from closures projected for this sector would
have no impact on the balance of trade in finished steel
products.
8.3 RESULTS
Chapter 3 provides an overview of exports, imports and the
balance of trade in the MP&M industries. U.S. MP&M
producers as a group exported products with a value of
$380.3 billion in 1999. Imports to the U.S. of the same
products in 1999 totaled $534.1 billion, resulting in an
overall net MP&M commodity trade deficit of $153.8
billion. Some MP&M sectors contribute to a positive
commodity trade balance (e.g. aircraft, with a $37.0 billion
positive balance in 1999). In other sectors, substantially
more products are imported than exported (e.g. motor
vehicles, with a net negative balance of $96.8 billion.)
Table 8.1 shows that the proposed effluent guidelines will
have a negligible impact on U.S. imports, exports, and the
national trade balance. Projected imports increase by $21.1
million, or less than 0.01 percent of baseline imports, and
there is no change in exports post-compliance. The net result
is an insignificant less than 0.01 percent decline in the
national balance of trade in commodities.
1 Based on the U.S. Department of Commerce, Bureau of the
Census, Current Industrial Reports for Steel Mill Products in 1997.
Only the relevant products are included: wire products, cold
finished bar, and pipes and tubes (except seamless and large
diameter pipe).
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 8: Foreign Trade Impacts
Table 8.1 Estimated National Impacts on U.S. Foreign Commodity Trade
(millions 1999$)
Baseline
Change due to the rule
Post-compliance
% Change from baseline
1999 Exports a
$695,797
0
$695,797
-
1999 Imports
$1,024,618
$21.1
$1,024,235
<0.01%
Trade Balance
($328,821)
($21.1)
($328,438)
(0.01%)
a. Only 3 regulatory closures reported exports, totaling $16,613. These facilities reported no foreign
competition in the international market.
Source: Bureau of Census and U.S. EPA analysis.
Table 8.2 shows regulatory impacts on MP&M-related
foreign trade. The projected changes in exports and imports
also represent an insignificant percentage of commodity
trade in the MP&M industries, resulting in a 0.01 percentage
decline in the net trade balance in these industries.
Table 8.2: Estimated National Impacts on MP&M Related Foreign Trade
(millions 1999$)
Baseline
Change due to the rule
Post-compliance
% Change from baseline
1999 Exports
$380,305
0
$380,305
1999 Imports
$534,141
$21.1
$534,120
<0.01%
Trade Balance
($153,836)
($21.1)
($153,815)
(0.01%)
a. Only 3 regulatory closures reported exports, totaling $16,613. These facilities reported no foreign
competition in the international market.
Source: Bureau of Census and U.S. EPA analysis.
The analysis of trade impacts does not explicitly account for
responses to price increases caused by the rule, as noted
previously. EPA expects there to be little change in exports
and imports resulting from the minimal price increases
predicted for the proposed rule, however. The estimated
price increases are less than two percent in all sectors, and in
most cases are less than one percent. (See Table 5.4 in
Chapter 5.) Annual rates of inflation for the United States'
major trading partners are generally well above the projected
increases in MP&M prices, and price increases in the
projected range are not likely to have much impact on the
terms of U.S. trade in MP&M products.2
2 The following are 1990-98 annual inflation rates, as
measured by the GDP implicit deflator, for nine of the U.S.' s top
ten trading partners: Canada 1.4%, Mexico 19.5%, Japan 0.2%,
China 9.7%, Germany 2.2%, United Kingdom 3.0%, Republic of
Korea 6.4%, France 1.7%, and Singapore 2.1%. The annual
change in the U.S. GDP deflator over the same period is 1.9%
(Data were not reported for Taiwan.) World Bank, 2000 World
Development Indicators, Table 4.16.
3-3
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MP&M EEBA Part II: Costs and Economic Impacts Chapter 8: Foreign Trade Impacts
REFERENCES
U.S. Department of Commerce, Bureau of the Census. 1997. Current Industrial Reports: Steel Mill Products.
U.S. Department of Commerce, Bureau of Census, Foreign Trade Division. FT900. 1999.
http://www.census.gov/foreign-trade/Press-Release/99_press_releases/Final_Revisions_1999/
World Bank, 2000 World Development Indicators.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 9: Firm Level, New Source, and Industry Impacts
Chapter 9: Firm Level, New
Source, and Industry Impacts
INTRODUCTION
Previous chapters have assessed impacts on MP&M
facilities, on governments and communities, and on the
U.S. balance of trade. This chapter considers impacts on
private businesses in more detail, by addressing three
categories of impacts. The analysis of impacts on firms
builds on the facility impact analysis to assess whether
firms that own multiple facilities are likely to incur more
significant impacts than indicated by the facility impact
analysis. The new source facility impact analysis
considers whether the proposed rule might impose
disproportionate burdens on new sources relative to
existing sources, and thereby pose a barrier to new entry.
Finally, this chapter discusses potential industry-level
impacts of the proposed rule.
9.1 FIRM LEVEL IMPACTS
CHAPTER CONTENTS:
9.1 Finn Impacts 9-1
9.1.1 Sources 9-1
9.1.2 Methodology 9-2
9.1.3 Results 9-2
9.2 New Source Impacts 9-3
9.2.1 Methodology 9-4
9.2.2 Results 9-5
9.3 Industry Impacts 9-6
Glossary 9-8
Acronyms 9-9
References 9-10
A firm-level analysis is needed to assess impacts on
small businesses, as required by the Regulatory
Flexibility Act and SBREFA. (Chapter 10 presents
an analysis of small business impacts.)
EPA analyzed economic impacts on firms for three reasons: 911 SOUPCCS
Impacts may be more significant at the firm level
than at the facility level if a firm owns a number of
facilities that incur significant costs. To the extent
allowed by the available data, the analysis therefore
looks at the combined effect of the facility
compliance costs for all facilities owned by a given
firm.
Resources available to fund compliance costs are
determined by a parent firm's financial strength
rather than the individual facility's financial
position. A financially-strong firm may decide to
close a facility that incurs substantial costs and is
no longer profitable, even if it has the resources to
fund compliance costs. EPA therefore assesses
potential closures based on facility-level conditions.
However, an otherwise profitable facility would
not have to be closed due to lack of financial
resources or ability to issue debt, if its parent firm's
financial position is not adversely affected by the
proposed rule.
The firm-level analysis starts with the results of the facility-
level analysis presented in Chapter 5, supplemented by firm-
level information provided by the MP&M facility surveys
and publically available information.
EPA was not able to conduct a rigorous national analysis of
firm-level impacts because the sample frame used to provide
national estimates from surveyed facilities reflect the
population of facilities rather than firms. EPA therefore
analyzed impacts for a hybrid dataset of MP&M firms that
includes both national estimates (for single-facility firms)
and sample firms (for multiple-facility firms.) The Agency
believes that the analysis of firm-level impacts presented in
this chapter provides a useful indication of national firm-
level impacts, however, for two reasons:
> Most MP&M facilities are single-facility firms.
The survey facility sample weights can be used to
extrapolate to the national number of firms for
these single-site firms.
* EPA requested voluntary information in the Phase
II detailed questionnaires on other MP&M facilities
9-1
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 9: Firm Level, New Source, and Industry Impacts
owned by the firms responding to the survey for a
sampled facility. EPA was able to aggregate
multiple-facility compliance costs to the firm-level
by including costs for all surveyed facilities and
(for the Phase II survey) facilities identified in
these voluntary responses.
It is unlikely that there will be a large number of firm-level
impacts among all MP&M firms in the nation, if this partial
analysis does not indicate significant impacts among the
firms identified in this analysis.
9.1.2 Methodology
The various surveys asked respondents to provide firm-level
revenues for the parent firm. For single-facility firms, firm
revenue and compliance costs are identical to those for the
facility. For firms that own more than one sample facility,
compliance costs are the sum of costs for all facilities
reported on in the survey.
Respondents to the Phase II survey had the option to submit
additional voluntary data for other MP&M facilities owned
by the same parent firm, in Part V of the detailed industry
questionnaire. EPA included compliance costs for these
facilities in calculating the total firm-level compliance costs
for multi-facility firms. EPA identified the subcategory,
flow range, and discharge type for each of the Part V
MP&M facilities. The analysis assumed that these
additional facilities would have the same average
compliance costs as the facilities for which detailed
technical compliance cost estimates were developed. EPA
calculated average costs by subcategory, flow range, and
discharge type from the detailed compliance cost estimates
and assigned these costs to the additional facilities identified
in Part V of the survey.
EPA then grouped together all facilities with a common
parent firm from the Phase I, Phase II and Iron and Steel
surveys. For each firm in the analysis, firm-level
compliance cost is:
where:
cc
Firm-level compliance costs were compared to firm
revenues. Firms with compliance costs less than one percent
of revenues are unlikely to have any serious impacts due to
the regulation. EPA identified firms as subject to potentially
more serious impacts if their compliance costs exceeded
three percent of revenues.
All firm-level data were inflated to 1999 dollars using the
Producer Price Index (PPI), as described in Chapter 5.
9.1.3 Results
As noted in the introduction, the Agency was not able to
estimate the national numbers of firms that own MP&M
facilities precisely, because the sample weights based on the
survey design represent numbers of facilities rather than
firms. EPA assumed that the national facilities that are
represented by the 319 single-site firms are also all single-
site firms. Based on this assumption, EPA estimated that
43,118 of 54,591 (or 79 percent) of MP&M facilities
nationwide are single-facility firms.
In addition, there are 289 firms that own more than one
sample facility. It is not known how many multi-facility
firms exist at the national level. EPA included these 289
firms identified by sample facilities in the firm-level analysis
without extrapolation to the national level.
The combined set of 43,407 firms (43,118 national-level
single-facility firms plus 289 sample multi-facility firms)
provided the basis for the firm-level analysis. This total
does not represent a valid national total for the number of
affected MP&M firms. Nonetheless, this analysis provides
a reasonable indication of likely firm-level impacts, given
the large number of single-facility firms and the use of Part
V facility data to supplement the sample facility data for
multi-facility firms.
Table 9-1 presents the number of facilities and firms in the
firm-level analysis. Nationally, there are 43,118 single-site
facilities/firms, and 11,473 facilities owned by an unknown
number of multi-site firms. Of those 43,118 facilities that
are single-facility firms, 42,422 are owned by small firms.
Of the 289 firms that own more than one sample facility, 87
are small firms. The analysis includes a total of 43,407
MP&M firms (43,118 + 289).
firm-level compliance cost
compliance cost for surveyed facility /'
owned by the firm
9-2
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 9: Firm Level, New Source, and Industry Impacts
Table 9.1: Number of Privately Owned Facilities
and Firms by Firm Type and Size
National number
of single-facility
firms (3 19
unique sample
firms)
Sample multi-
facility firms
Number of firms
in the firm-level
analysis^
Total
Firms/
Facilities
43,118
289
43,407
Owned
by a small
firm
42,422
87
42,509
Owned by a
large firm
695
202
897
Source: U.S. EPA analysis.
Table 9-2 presents estimated firm-level impacts of the
MP&M rule. A small percentage (2.5 percent) of the firms
in the analysis incur before-tax compliance costs equal to 3
percent or more of annual revenues. Ninety-five percent
incur compliance costs less than 1 percent of annual
revenues, and the remaining 2.5 percent incur costs between
1 and 3 percent of revenues. Of 2,171 firms in the analysis
that incur costs greater than 1 percent of revenues, 636 are
single-facility small firms that were reported in the facility
impact analysis to close (161 firms) or experience moderate
impacts (475 firms) due to the rule.
Table 9.2: Firm-level Bef ore-Tax Annual Compliance Costs
as a Percent of Annual Revenues
Number of
Firms in the
Analysis3
43,407
Number and Percent with Before-Tax Annual Compliance Costs/Annual
Revenues Equal to:
Less than 1%
Number %
41,236 95%
1-3%
Number %
1,070 2.5%
Over 3%
Number %
1,101 2
5%
a Firms whose only MP&M facilities close in the baseline are excluded.
Source: U.S. EPA analysis.
This analysis is likely to overstate costs at the firm level for
two reasons. First, it includes compliance costs for facilities
that are projected to close due to the rule. The estimated
compliance costs for these facilities are higher than the true
cost to the firm of shutting down the facility, as illustrated
by the detailed facility impact analysis that projects closures.
Second, the analysis does not consider actions a multi-
facility firm might take to reduce its compliance costs under
the proposed rule. These include transferring functions
among facilities to consolidate wet processes and take
advantage of scale economies in wastewater treatment.
9.2 NEW SOURCE IMPACTS
The proposed rule includes NSPS and PSNS limitations
that will apply to new direct and indirect MP&M
dischargers. In this section, EPA examines the impact of
these regulations for new dischargers to determine if they
would impose an undue economic and financial burden on
new sources seeking to enter the MP&M industry.
Disproportionate regulatory burdens for new sources could
cause adverse industry-level outcomes in the long-run in
several ways:
> Imposing more significant costs on new facilities
can make existing sources more competitive than
new sources causing barriers to new entry;
> Barriers to entry may increase the market power of
existing firms and could discourage competition
over time, with resulting losses in market
efficiencies;
* Creating a competitive advantage for existing
facilities may hinder technological innovation, with
resulting losses in productivity.
Table 9-3 describes the proposed option for new sources in
each subcategory, as well as the proposed technology option
for existing sources in the same subcategory and discharge
status.
9-3
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 9: Firm Level, New Source, and Industry Impacts
Table 9.3:
Subcategory
General Metals
Metal Finishing
Job Shops
Non-Chromium
Anodizing
Oily Wastes
Printed Wiring
Board
Railroad Line
Maintenance
Shipbuilding Dry
Docks
Steel Forming &
Finishing
Proposed Ri
Discharge
Status
D&I
D&I
D
D&I
D&I
D
D
D&I
jle for New 5
Existing
Source
Technology
Option3
2
2
2
6
2
10
10
2
Sources
New
Source
Technology
Option3
4,
with 1 mgy
low flow
cutoff for
PSNS
4
2
6, with 2
mgy low
flow cutoff
for PSNS
4
10
10
4
a Technology options 1 through 10 are described in Chapter 4.
Source: U.S. EPA analysis.
EPA is proposing the same requirements for new and
existing sources for Non-Chromium Anodizing and the oily
waste subcategories (Railroad Line Maintenance,
Shipbuilding Dry Dock, and Oily Wastes) and is proposing
more stringent standards for new sources in other
subcategories.
EPA estimated compliance costs as a percentage of
revenues and compared these percentages for new facilities
to the cost-to-revenue percentage for existing facilities in the
same subcategory. This comparison indicates whether the
proposed rule is likely to place new facilities at a
competitive disadvantage relative to existing sources, and
therefore to pose a barrier to new entry.
9.2.1 Methodology
EPA assessed the impacts of the proposed rule on new
facilities based on the characteristics of a hypothetical model
facility in each subcategory and discharge category.
Engineering estimates of compliance costs for the model
facilities reflect the typical flow size and other technical
characteristics of facilities in each subcategory.
Model facilities for indirect sources in each subcategory
were chosen based on the median baseline flow of all
existing indirect facilities in that subcategory which will not
contract haul under a regulatory option. Similarly, model
facilities for direct sources in each subcategory were chosen
based on the median baseline flow of all existing direct
facilities in that subcategory which do not contract haul
under a regulatory option. In cases where the existing
facility with the median subcategory flow performed a
representative sample of unit operations, it was chosen as
the representative model facility for that subcategory.
However, if the median flow facility did not perform
representative unit operations, another existing facility with
a flow either just above or just below the median was chosen
(based on the unit operations performed).
EPA estimated compliance costs for Option 2/6/10 and
Option 4/8 for these model facilities. Estimated capital costs
for new sources are six percent lower than similar costs for
existing sources because new sources do not have to retrofit
facilities. These compliance cost estimates are described in
more detail in the Technical Development Document (U.S.
EPA, 2000). Annualized compliance costs estimated for
model facilities under the proposed new source option are
shown in Table 9-4.
New sources in the Metal Finishing Job Shop and Printed
Wiring Board subcategories will have to comply with 40
CFR 433 new source requirements, and Steel Forming &
Finishing new sources will have to comply with 40 CFR 440
new source requirements. The analysis considers only the
incremental costs of proposed MP&M new source
requirements beyond the 40 CFR 433 and 40 CFR 440
requirements that apply in the baseline.
EPA estimated facility revenues for the model facilities
based on revenues reported for existing facilities in the
Section 308 surveys. The analysis excludes facilities that
are projected to close or to experience moderate economic
impacts in the baseline, since the economic characteristics of
these financially-weak facilities are unlikely to be
representative of new facilities. EPA sorted the existing
financially-sound facilities in each subcategory/discharge
category by flow size, and identified facilities in each
quartile based on flow size. The Agency then identified the
flow size quartile that the hypothetical new facility would
fall into, based on its flow size. Finally, EPA calculated the
average revenue for the existing facilities in that same flow
size quartile, and assumed that the hypothetical new facility
would have revenues equal to that average.
The analysis assumes that new sources would benefit from
price increases resulting from the proposed rule for existing
sources to the same degree that existing sources will. EPA
therefore increased the average baseline revenue for new
facilities by the average percentage price increase estimated
for existing facilities in each subcategory/discharge
category, to calculate post-regulation revenues for new
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 9: Firm Level, New Source, and Industry Impacts
sources. Table 9-4 shows the post-regulation revenue
estimated for each model facility.
EPA used compliance costs as a percentage of post-
regulation revenues as a measure of impacts. Comparing the
cost-to-revenue percentage for new facilities to the
percentage for existing facilities under the proposed rule
indicates whether the proposed regulation will place new
facilities at a competitive disadvantage relative to existing
sources.
9.2.2 Results
Cost-to-revenue comparisons for new facilities and existing
facilities are presented in Table 9-4. Only existing facilities
that continue operating post-compliance are considered,
since these are the facilities with which new sources will
compete. New sources in all but the Metal Finishing Job
Shop category incur costs that are below one percent of
post-regulation revenues. Costs for Metal Finishing Job
Shop direct and indirect dischargers are less than two and
five percent of estimated facility revenues, respectively.
EPA believes that cost increases of this magnitude are
unlikely to place new facilities at a competitive disadvantage
relative to existing sources. Moreover, it appears that costs
as a percentage of revenues are generally comparable for
new sources and existing sources with which they will
compete.
Subcategory
General Metals
General Metals
Metal Finishing Job Shops
Metal Finishing Job Shops
Non-Chromium Anodizing
Oily Wastes
Oily Wastes
Printed Wiring Board
Printed Wiring Board
Railroad Line Maintenance
Shipbuilding Dry Dock
Steel Forming & Finishing
Steel Forming & Finishing
Table 9.4:
Discharge
Status
I
D
I
D
D
I
D
I
D
D
D
I
D
Impacts on New
Annualized
Compliance
Costs (ACC) a
($1999)
$393,220
$167,342
$65,369
$70,735
$97,108
$355,874
$37,815
$70,563
$160,184
$184,261
$220,492
$114,851
$46,945
i Sources
Facility
Revenue b
($1999)
$417,071,318
$398,818,659
$1,428,443
$5,089,823
$24,20 1,1 66d
$474,228,616
$116,772,943
$35,030,097
$1,029,783,596
N/A
$192,018,827
$69,640,244
$32,759,295
New
Source
ACC as %
of Revenue
0.09%
0.04%
4.58%
1.39%
0.40%
0.08%
0.03%
0.20%
0.02%
N/A
0.11%
0.16%
0.14%
Existing
Source
ACC as %
of
Revenue c
0.12%
0.10%
2.97%
5.38%
d
0.01%
0.01%
0.61%
0.01%
N/A
0.03%
0.38%
2.00%
a. Incremental to baseline new source requirements for Metal Finishing Job Shop, Printed Wiring Board and Steel
Forming & Finishing new sources.
b. Equal to the average revenues of existing facilities in the same quartile based on flow size as the new source model
facility, excluding existing facilities that close or experience moderate impacts in the baseline. Assumes the same
percentage price increases for new as for existing sources under the proposed option.
c. Includes existing facilities in all flow categories that continue operating post-compliance.
d. No direct Non-Chromium Anodizer facilities were identified in the analysis of existing sources. The estimate of
facility revenue is based on the average for indirect dischargers in this subcategory.
Source: U.S. EPA analysis.
Railroad line maintenance facilities do not have revenue
reported at the facility level, and it is therefore not possible
to compare costs as a percent of facility revenue for new and
existing facilities in this subcategory. The representative
direct discharging new source railroad line maintenance
facility incurs annualized costs ($184,261) that are
somewhat higher than those incurred by existing facilities in
this subcategory (which range from zero to $122,042).
9-5
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 9: Firm Level, New Source, and Industry Impacts
9.3 INDUSTRY LEVEL IMPACTS
Potential industry-level impacts include price increases,
reduced competitiveness within the domestic industry and in
world markets, and reduced rates of innovation. EPA did
not perform a sector-specific analysis for several reasons:
> Sector-level impacts are complicated by the large
number of product and service markets included in
the MP&M category (e.g., over 200 SICs and three
activities-manufacturing, rebuilding, and repair);
* Revenue and cost information is not available on a
product by product basis, so it is impossible to link
price increases to individual products; and
* Many MP&M facilities derive revenue from
multiple industry sectors.
EPA's analysis of facility- and firm-level impacts suggests,
however, that industry-level impacts are unlikely in any of
the affected industries.
The Agency does not expect any industry level impacts due
to the MP&M regulation because of the low number of
facilities that will have costs and the low number of facilities
that have severe or moderate impacts. There are 89,000
facilities performing MP&M activities. Almost 63,000 of
these facilities discharge water, while 26,000 facilities do
not. This indicates that MP&M industries include a
substantial number of facilities that do not discharge
wastewater. Of the facilities that do discharge wastewater,
only 9,839 will have costs under the proposed rule. This
occurs because substantial numbers of facilities are
exempted under the proposed rule by the subcategory
exclusions and the low-flow cutoffs.
The percentage of facilities incurring significant or moderate
impacts is low in all subcategories, as discussed in
Chapter 5. Given the small percentages of facilities
incurring impacts under the proposed rule and the small
percentage of facilities incurring costs in any sector, EPA
concludes that the proposed rule is unlikely to impose
significant costs on a substantial number of facilities in any
MP&M industry sector.
Chapter 5 also presented information on the prices increases
predicted to occur in each industry sector due to the
proposed rule. Table 5.8 in Chapter 5 presented EPA's
estimates of price increases by sector. Projected price
increases are less than one percent for all but two sectors,
and less than two percent for those two sectors. Price
increases of these magnitudes are unlikely to impose
burdens on customers of the regulated facilities or have a
substantial effect MP&M producers' position relative to
competitive products (e.g., products made with plastics) or
foreign producers. Price increases may affect only some
components of a product. In these cases, prices to end-users
would rise even less than the amounts detailed in Chapter 5.
EPA does not expect the proposed rule to have any impact
on the rate of technological innovation in the MP&M
industries. Such impacts on innovation could result if the
rule discouraged new entry, contributed to increased
concentration in the affected industries, or specified the use
of particular technologies. The following factors suggest
that these conditions do not apply for the proposed rule:
* EPA's analysis of new source impacts presented in
the previous section suggests that the proposed rule
will not retard new entry. The proposed rule will
increase the investment required to build a new
facility somewhat. However, the increased capital
costs are generally small relative to the overall
financial resources of the MP&M facilities, as
indicated by the results of the facility impact
analysis. In addition, the low flow cutoffs
applicable to a large number of MP&M facilities
reduce the potential impacts of large capital
requirements on small facilities.
* Given the small portion of facilities regulated in
each sector and the small number of projected
closures, EPA does not expect the proposed rule to
result in increased concentration in any of the
MP&M sectors.
> The rule does not require the use of specific
production or pollution control processes or
technologies. Rather, it specifies a performance
standard, based on levels of pollutants in
wastewaters that have been shown to be achievable
by available technologies. Facilities have the
flexibility to achieve these limitations using a
variety of approaches, which is likely to encourage
rather discourage innovation in production and
pollution control processes.
For these reasons, EPA does not expect the proposed rule to
have any adverse effects on technology innovation in the
MP&M industries.
The proposed rule will affect the relative competitive
position of different firms and facilities in each MP&M
industry sectors. Facilities that do not discharge
wastewaters, that are eligible for the subcategory exclusions
and low-flow cutoffs under the proposed rule, that already
have treatment in place, or that can make process changes to
reduce pollutant loads easily are likely to gain a competitive
advantage from the proposed rule.
Facilities that have little or no treatment in place and that
discharge substantial pollutant loads are likely to become
less competitive. The proposed rule may level the
competitive playing field for facilities that have taken steps
9-6
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MP&M EEBA Part II: Costs and Economic Impacts Chapter 9: Firm Level, New Source, and Industry Impacts
to reduce their environmental impacts, relative to facilities impacts on any industry as a whole, and as long as the rule
that have avoided investments to reduce or eliminate does not disproportionately impact small entities as a group.
pollutant discharges. EPA views these effects as beneficial, Impacts on small entities are addressed in the next chapter.
given that the proposed regulation does not have significant
9-7
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 9: Firm Level, New Source, and Industry Impacts
GLOSSARY
new source: Any building, structure, facility, or
installation from which there is or may be a discharge of
pollutants, the construction of which commenced after
promulgation of standards of performance under Section
306 of the Clean Water Act which are applicable to such
source; and which (1) is constructed at a site at which no
other source is located; (2) totally replaces the process or
production equipment that causes the discharge of pollutants
at an existing source; or (3) consists of processes that are
substantially independent of an existing source at the same
site.
New Source Performance Standards (NSPS):
effluent limitations for new direct dischargers based on the
best available demonstrated control technology. NSPS
represents the greatest degree of effluent reduction
attainable through the application of the best available
demonstrated control technology for all pollutants (i.e.,
conventional, non-conventional, and priority pollutants). In
establishing NSPS, EPA considers the cost of achieving the
effluent reduction and any non-water quality environmental
impacts and energy requirements.
Pretreatment Standards for New Sources (PSNS):
pretreatment standards for new indirect dischargers,
designed to prevent discharges of pollutants that pass
through, interfere with, or are otherwise incompatible with
the operation of POTWs. Addresses all pollutants (i.e.,
conventional, non-conventional, and priority pollutants).
Based on the same factors as are considered in promulgating
NSPS.
Producer Price Index (PPI): a family of indexes that
measures the average change over time in the selling prices
received by domestic producers of goods and services. PPI's
measure price change from the perspective of the seller. This
contrasts with other measures, such as the Consumer Price
Index (CPI), that measure price change from the purchaser's
perspective. Sellers' and purchasers' prices may differ due to
government subsidies, sales and excise taxes, and
distribution costs, (http://stats.bls.gov/ppifaq.htnrfl)
9-8
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 9: Firm Level, New Source, and Industry Impacts
ACRONYMS
NSPS: New Source Performance Standards
PPI: Producer Price Index
PSNS: Pretreatment Standards for New Sources
9-9
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MP&M EEBA Part II: Costs and Economic Impacts Chapter 9: Firm Level, New Source, and Industry Impacts
REFERENCES
U.S. Bureau of Labor Statistics, Producer Price Index Revision-Current Series. On-line database at
http://stats.bls.gov/ppihome.htm
U.S. Environmental Protection Agency. 2000. Technical Development Document for the Proposed Effluent Limitations
Guidelines and Standards for the Metal Products & Machinery Point Source Category. December.
9-10
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 10: Regulatory Flexibility Analysis/SBREFA
Chapter 10: Regulatory Flexibility
Analysis / SBREFA
INTRODUCTION
The Regulatory Flexibility Act (RFA). as amended by the
Small Business Regulatory Enforcement Fairness Act
(SBREFA), requires EPA to consider the economic impacts
a rule will have on small entities RFA/SBREFA requires
an agency to prepare a regulatory flexibility analysis for any
rule subject to notice and comment rulemaking
requirements, unless the Agency certifies that the rule will
not have a significant economic impact on a substantial
number of small entities (Small Business Regulation
Enforcement Fairness Act of 1996, P.L. 104-121, Section
243).
The economic analysis prepared for the 1995 MP&M
Phase I proposal indicated that large numbers of small
facilities could be impacted by the proposed regulation and
that a significant number of publically-owned treatment
works (POTWs) would also be affected by the rule.
EPA addressed this issue by crafting the rule to exclude as
many small facilities as possible while still covering as much
of the pollutant discharge as possible. With this in mind,
EPA sought, from the beginning, to design a combined
phase regulation that would not unreasonably burden small
entities.
To make sure that all small entities were taken into
consideration in developing the MP&M regulation, EPA
developed, administered, and analyzed questionnaires for
all entities that could potentially be impacted, including:
privately- and government-owned facilities that would have
to comply with the regulation, and POTWs that receive
MP&M discharges. The Agency balanced several factors
when selecting the proposed rule, including:
* The predominance of small entities in the MP&M
industries,
* The pounds of pollutants discharged by large and
small facilities,
* The toxicity of the pollutants discharged by large
and small facilities,
CHAPTER CONTENTS:
10.1 Defining Small Entities
10.2 Methodology
10.3 Results
10.3.1 Number of Affected Small Entities .
10.3.2 Impacts on Facilities Owned by
Small Entities
10.3.3 Impacts on Small Firms
10.4 Detailed Analysis of the Two Subcategories
with Most of the Impacts
10.4. 1 Severe and Moderate Impacts in the
Metal Finishing Job Shops
Subcategory
10.4.2 Moderate Impacts in the Printed
Wiring Board Subcategory
10.5 Consideration of Small Entity Impacts in the
Selection of the Proposed Rule
Glossary
Acronyms
References
10-2
10-3
10-3
10-3
10-4
10-6
10-6
10-7
10-8
10-9
10-12
10-13
10-14 1
> The need for additional reduction in effluent
discharges from the MP&M industry,
* The need to achieve these reductions without
imposing unreasonable burdens on small entities,
and
> The need to minimize the burden on POTWs.
Given the large number of small entities potentially affected
by the proposed rule, EPA prepared an Initial Regulatory
Flexibility Analysis (IRFA). The IRFA evaluates the
impact of the proposed rule and alternative regulatory
options on small entities. The following sections of this
chapter describe the IRFA methodology and results, and
discuss EPA's consideration of small entity impacts in
designing the proposed rule.
10-1
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 10: Regulatory Flexibility Analysis/SBREFA
10.1 DEFININS SMALL ENTITIES
EPA identified small entities using Small Business
Administration (SBA) size threshold guidelines.1 These
thresholds define minimum employment or revenue sizes by
industry (four-digit SIC codes), below which a business
qualifies as a small business under SBA guidelines. The
thresholds apply at the firm level, and are used to identify
small firms that own MP&M facilities. The SBA guidelines
also set a threshold for small public sector entities. A small
government is one that serves a population of 50,000 or
less. MP&M facilities are determined to be owned by a
small entity if the parent firm or government falls below the
SBA threshold.
The SBA guidelines use either employment or revenue to
measure size, depending on the specific four-digit SIC
industry. Manufacturing industries generally have
employment size thresholds, while non-manufacturing
industries typically have revenue size thresholds. EPA used
employment-based thresholds for the manufacturing portion
of each MP&M sector, and separate non-manufacturing
thresholds for sectors that include significant non-
manufacturing activities (e.g., maintenance and repair).
EPA selected the most common SBA threshold for the four-
digit SIC codes that make up each sector as the sector
threshold.2 Table 10.1 presents the resulting employment
size thresholds for manufacturers.
Table 10.1. Small Business MP&M S
Thresholds for Manufacturers
MP&M Sector
Aerospace
Aircraft
Bus and Truck
Electronic Equipment
Hardware
Household Equipment
Instrument
Job Shop
Mobile Industrial Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious and Non-Precious Metals
Printed Circuit Board
Railroad
Ship and Boat
Stationary Industrial Equipment
Steel Forming & Finishing
ector
Employees
1,000
1,000
500
750
500
500
500
500
500
500
1,000
1,000
500
500
500
1,000
1,000
500
1,000
Source: SBA and U.S. EPA analysis.
1 The SBA website provides the most recent size thresholds at
http://www.sba.gov/regulations/siccodes.
2 The SBA thresholds for four-digit SICs were not used
directly because the Phase II ง308 survey reports revenues by
MP&M sector but does not report facility SIC codes.
Table 10.2 presents the employment size thresholds for non-
manufacturers, which are based on revenue except for the
railroad sector. Some sectors do not have non-
manufacturing industries and do not appear in this table.
10-1
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 10: Regulatory Flexibility Analysis/SBREFA
Table 10.2. Small Business MP&M Sector
Thresholds for Non-Manufacturers
MP&M Sector
Aircraft
Bus and Truck
Household Equipment
Instrument
Motor Vehicle b
Office Machine
Other Metal Products
Precious and Non-Precious Metals
Railroad
Ship and Boat c
Stationary Industrial Equipment
Revenue
$5,000,000
$5,000,000
$5,000,000
$5,000,000
$5,000,000
$18,000,000
$5,000,000
$5,000,000
l,500a
$5,000,000
$5,000,000
where:
Efi
Eft
a Employees.
b Also has a threshold of 100 employees.
c Also has a threshold of 500 employees.
Source: SBA and U.S. EPA analysis.
EPA classified facilities as manufacturing or non-
manufacturing and selected an MP&M sector threshold
based on the source from which they received the most
revenue, as reported in the ง308 surveys.3 EPA then
compared the firm-level employment or revenue for the firm
owning each facility to the appropriate manufacturing or
non-manufacturing threshold for that sector.
The Phase II survey asked each respondent to provide firm-
level employment and revenue data. The Phase I survey also
asked for firm-level revenue but not for firm employment.
This did not matter in the case of single facility businesses,
where the facility's reported employment is the firm-level
employment. EPA estimated Phase I firm-level employment
for facilities that were part of a multiple-facility firm by
assuming that the number of employees per revenue dollar
for the firm was the same as the employees per dollar at the
facility. Thus,
m = firm-level employment,
icillty = facility-level employment,
m = firm-level revenue, and
,Cj,jtv = facility-level revenue.
EPA identified facilities operated by governments that serve
a population of 50,000 or fewer as being operated by small
government entities. The ง308 municipal survey responses
provided population data in most cases, which EPA
supplemented using the Bureau of the Census online 1990
Population Census database (Bureau of the Census.)
10.2 METHO&oioey
The RFA requires EPA to determine whether the proposed
rule imposes "significant impacts" on a "substantial number"
of small entities. This determination depends both on the
severity of impacts on individual entities and on the number
of entities affected. EPA used several measures of impacts
in this analysis. First, the results of the facility impact
analyses described in Chapter 5 were disaggregated to
determine whether facilities owned by small entities are
disproportionately subject to regulatory closures or to
moderate impacts at the facility level. Second, EPA
calculated the ratio of annualized compliance costs to
facility revenues and examined the distribution of this ratio
for facilities owned by small versus large firms.
The analysis excludes facilities that the facility impact
analysis identifies as baseline failures (see Chapter 5).
10.3 RESULTS
10.3.1 Number of Affected Small
Entities
n
E = E * firm
firm facility
R
(10.1)
^facility
The proposed rule could potentially affect an estimated
59,000 MP&M facilities nationwide (excluding baseline
closures) without the subcategory exclusions and low flow
cutoffs. A large number of these facilities are owned by
small entities, as defined by SBA thresholds. Table 10.3
shows the total number of facilities operating in the baseline
and the number owned by small entities. Overall, 82 percent
of all MP&M facilities are owned by small entities.
3 The ง308 MP&M surveys did not collect firm-level
revenues by sector and therefore cannot be used to assign a unique
sector to each firm. The assignment of a threshold was therefore
based on the facility-level revenues by sector.
10-3
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 10: Regulatory Flexibility Analysis/SBREFA
Table 10.3 Number and Percent of MP&M Facilities Owned by Small Entities
Type of Facility
Private MP&M3
Government-Owned
Total3
Number of Facilities of:
all Sizes Operating-
in the Baseline;
54,591:
4,332j
5^)231
Number of Facilities-
Owned by Small Entities
44,773:
2,672J
47,445!
Percent of Facilities
Owned by Small Entities
82%
62%
81%
a. Excludes baseline closures.
Source: U.S. EPA analysis.
Table 10.4 shows that the proposed rule excludes a large
percentage of potentially-regulated small entities. The
subcategory exclusions and low flow cutoffs exclude 81
percent of the facilities owned by small entities that continue
to operate in the baseline from MP&M regulatory
requirements.
Table 10.4. Percent of Facilities Owned by Small Entities Excluded under the Proposed Rule
Type of Facility
Owned by small business
Owned by small government
Total owned by small entities
Number of Facilities
Operating in the Baseline
44,773
2,672
47,445
Number of Facilities
Excluded in the Proposed
Option
38,563
2,262
40,825
Percentage of Facilities
Excluded
86%
85%
86%
Source: U.S. EPA analysis.
10.3.2 Impacts on Facilities Owned by
Small Entities
The results of the facility impact analysis (closures and
moderate impacts) is the first basis used by EPA to assess
impacts on facilities owned by small entities. Of the 199
facilities that may close as a result of the proposed rule, 181
of these are owned by small entities. Most of the 616
facilities projected to experience moderate impacts (492, or
80 percent) are owned by small entities.
A second approach to assessing small entity impacts, based
on a comparison of compliance costs to post-compliance
revenues, indicates that 1,064 facilities owned by small
private businesses will incur costs exceeding 3 percent of
revenues. This second approach to measuring impacts
overlaps with the first approach. Of the 1,064 facilities that
will incur costs in excess of 3 percent of revenues, 181 are
the same facilities that are expected to close, and another
462 are facilities expected to experience moderate impacts
as determined by the facility impact analysis.
The percentages of facilities owned by small entities subject
to significant impacts, however, is quite small. The 181
small entity closures represent less than one-half of one
percent of the small entities that operate in the baseline.
Only 2.4 percent of the facilities owned by small private
businesses that operate in the baseline would incur costs
equal to 3 percent or more of annual revenues. Although the
percentage of facilities owned by small entities projected to
incur impacts is quite small, the number of such facilities
with costs greater that three percent is large enough that
EPA decided that a detailed small business analysis was
warranted.
Table 10.5 summarizes the results of the facility impact
analysis for facilities owned by small entities.
10-4
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 10: Regulatory Flexibility Analysis/SBREFA
Table 10.5: Closures an
Slumber of facilities operating in the baseline
Slumber of facilities excluded
r'ercent excluded
Slumber of closures
r'ercent closing
Slumber of facilities with moderate impacts
r'ercent with moderate impacts
d Moderate Impacts for
Proposed Rule
47,445
40,825
85%
181
0.4%
492
1.0%
=acilities Owned by Smal
Option 2/6/10
47,445
1,227
2.6%
755
1.6%
1 Entities
Option 4/8
47,445
2,782
5.9%
835
1.8%
Source: U.S. EPA analysis.
The projected number of closures under the proposed rule is
very small compared to the large number of facilities owned
by small entities. Less than one-half of one percent of the
facilities owned by small entities that operate in the baseline
are projected to close. The percentage of small entities
experiencing moderate impacts is also low, at one percent.
Table 10.6 shows the results of the second approach to
assessing small entity impacts, based on a comparison of
compliance costs with facility revenues. EPA conducted
this analysis only for MP&M facilities owned by private
entities (i.e., businesses, but not governments), because of
the low level of impacts on all sizes of governments.
Table 10.6: Before-Tax Annual Compliance Costs as a Percent of Annual Revenues under the Proposed Rule
for Facilities Operating in the Baseline and Owned by Private Small Businesses
Discharge
Status
Direct
Indirect
Total
Number of
Facilities Owned
by Small Private
Businesses
Operating in the
Baseline
3,237
41,536
44,773
Number and Percent of Facilities Owned by Small Businesses with Before-Tax Annual
Compliance Costs/ Annual Revenues Equal to:
No Costs
Number
0
38,435
38,435
%
0.0%
92.5%
85.8%
Less than 1%
Number
2,969
1,175
4,144
%
91.7%
2.8%
9.3%
1-3%
Number
211
920
1,131
%
6.5%
2.2%
2.5%
Over 3%
Number
57
1,007
1,064
%
1.8%
2.4%
2.4%
Source: U.S. EPA analysis.
A small percentage (2.4 percent) of all facilities owned by
small entities that operate under the proposed rule incur
before-tax compliance costs equal to 3 percent or more of
annual revenues. Over 85 percent incur no compliance
costs, 9.3 percent incur compliance costs less than 1 percent
of annual revenues, and the remaining 2.5 percent incur
costs between 1 and 3 percent of revenues. These results are
consistent with the finding that only a very small percentage
of facilities owned by small businesses will close or
experience even moderate financial impacts.
Finally, Table 10.7 compares the number of facilities owned
by small and large businesses that are projected to close
under the proposed rule with the total number of facilities
owned by small and large businesses in the MP&M sectors,
as reported by the 1996 Census Statistics of U.S.
Businesses. This universe includes facilities that are not
subject to MP&M requirements because they do not
discharge wastewater or do not perform MP&M processes
that generate wastewater. This comparison shows that a
small percentage of the facilities owned by small firms in the
MP&M sectors are potentially affected by the rule, and a
very small percentage (less than 0.02%) of facilities owned
by both small and large firms are projected to close under
the proposed rule. While the absolute numbers of affected
facilities owned by small businesses are large, the proportion
of the small entities in the MP&M sectors that would
experience significant impacts is extremely small.
10-5
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 10: Regulatory Flexibility Analysis/SBREFA
Table 10.7 Percent of All MP&M Facilities Projected to Close under the Proposed Rule
Size of Firm
Owned by small firms
Owned by large firms or
potentially large firms
Total
Total
Establishments
1,034,867
277,424
1,312,291
Total # MP&M
Facilities
Operating in
Baseline
44,773
9,817
54,590
% MP&M
4.3%
3.5%
4.2%
#MP&M
Facilities
Projected to
Close under the
Proposed Rule
181
18
199
% of All Small
Entity Facilities
Projected to
Close
0.02%
0.01%
0.02%
Sources: U.S. Bureau of Census, Statistics of U.S. Businesses and U.S. EPA analysis.
10.3.3. Impacts on Small Firms
EPA compared compliance costs with revenue at the firm
level as a measure of the relative burden of compliance
costs. EPA applied this analysis only to MP&M facilities
owned by private entities (i.e., businesses, but not
governments). Table 10.8 shows the results of this
comparison. The Agency was not able to estimate national
numbers of firms that own MP&M facilities precisely,
because the sample weights based on the survey design
represent numbers of facilities rather than firms. Most of
the facilities owned by small firms (42,422 of 44,774, or 95
percent) are single-facility firms, however. These single-
facility firms can be analyzed using the survey weights. In
addition, there are 87 small firms that own more than one
sample firm. These firms are included in the analysis with a
sample weight of one, since it is not known how many
sample firms these 87 small firms represent. The results
shown in Table 10.8 therefore represent a total of 42,509
small MP&M firms (42,422 + 87).
Table 10.8: Firm Level Bef ore-Tax Annual Compliance Costs as a Percent of
Annual Revenues for Private Small Businesses
Number of
Small Firms in
the Analysis3
42,509
Number and Percent with Before-Tax Annual Compliance Costs/Annual
Revenues Equal to:
Less than 1%
Number
40,560
%
95.4%
1-3%
Number %
1,008 2.4%
Over 3%
Number %
941 2.2%
*Firms whose only MP&M facilities close in the baseline are excluded.
Source: U.S. EPA analysis.
A small percentage (2.2 percent) of the small businesses in
the analysis incur before-tax compliance costs equal to 3
percent or more of annual revenues. More than 95 percent
incur compliance costs less than 1 percent of annual
revenues, and the remaining 2.4 percent incur costs between
1 and 3 percent of revenues. Of the 1,949 small firms in the
analysis that incur costs greater than 1 percent of revenues,
612 are single-facility small firms that were reported in the
facility impact analysis to close (149 firms) or experience
moderate impacts (463 firms) due to the proposed rule.
10.4 DETAILED ANALYSIS OF THE Two
SUBCATE6ORIES WITH MOST OF THE
IMPACTS
Two subcategories account for a majority of the projected
small entity closures and moderate impacts: Metal Finishing
Job Shops, which accounts for the largest number of small
entity closures, and Printed Wiring Board, which accounts
for the majority of small entity moderate impacts. This
section examines the effect of the rule in more detail for
these two subcategories.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 10: Regulatory Flexibility Analysis/SBREFA
10.4.1 Severe and Moderate Impacts in
the Metal Finishing Job Shops
Subcategory
The Metal Finishing Job Shop subcategory is the most
highly impacted of the subcategories, with 128 or 64 percent
of the facilities predicted to close, and 117 of the 616
predicted moderate impacts. This subcategory includes a
substantial number of facilities owned by small entities.
Table 10.9 summarizes projected impacts on Metal
Finishing Job Shop facilities owned by small entities under
the proposed rule.
Table 10.9: Regulatory Impacts for Small Entity Metal Finishing Job Shops by Option, National Estimates
Number of small entity Metal Finishing Job Shops operating in the baseline
Number of predicted regulatory closures
Percent of facilities closing due to the rule
Number of facilities operating post-regulation
Number of facilities experiencing moderate impacts
Percent of facilities operating in the baseline that experience moderate impacts
Proposed Rule
Option 2/6/10
943
117
12.4%
826
105
12.7%
Option 4/8
943
255
27.0%
688
71
7.5%
Source: U.S. EPA analysis.
Twelve percent of the facilities owned by small entities that
operate in the baseline are projected to close under the
proposed rule. This percentage is substantially higher than
the percentage of facilities projected to close under the
proposed rule for MP&M facilities as a whole.
The Metal Finishing Job Shop subcategory includes a
number of facilities that are financially weak and that may
have trouble affording the costs of the proposed rule. EPA
concluded that it would be inappropriate to provide any
further regulatory relief for this subcategory, however, for
several reasons. First, the facilities that are subject to
requirements under the rule account for significant toxic-
weighted pollutant loadings per facility. Second, excluding
facilities that are discharging substantial pollutant loads
places more modern, cleaner job shop facilities at a
competitive disadvantage.
Table 10.10 shows the average baseline toxic-weighted
loadings per facility (in Ibs. equivalent) for different groups
of Metal Finishing Job Shops owned by small entities.
Table 10.10: Small Entity Metal Finishing Job Shops Toxic- Weighted Pollutant Loadings per Facility
(Ibs. equivalent/facility)"
Average loadings per facility for all small entity Metal Finishing Job Shops operating
in the baseline
Average loadings per small entity facility for facilities that:
close due to the regulation
experience moderate impacts
incur before- tax compliance costs >3% of post-compliance revenue
incur before-tax compliance costs > 1% and < 3% of post-compliance revenue
incur before-tax compliance costs < 1% of post-compliance revenue
Proposed Rule/
Option 2/6/10
5,881
29,749
6,813
11,920
338
755
Option 4/8
5,881
16,337
2,756
7,987
317
a Discharges discussed in this table are facility discharges and do not account for POTW removals.
Source: U.S. EPA analysis.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 10: Regulatory Flexibility Analysis/SBREFA
This table indicates that the small entity Metal Finishing Job
Shops most heavily impacted under the proposed rule
contribute substantially more toxic-weighted loadings on
average than do facilities that experience less significant
impacts under the rule. For example, the facilities that close
under the proposed rule discharge an average of 29,749 Ibs.
equivalents per facility, compared with an average of 5,881
Ibs. equivalent per facility for all Metal Finishing Job Shops
that operate in the baseline. These estimates do not account
for POTW removals. In this analysis, EPA believes it is
appropriate to analyze wastewater discharges disregarding
the POTW removals because indirect discharges present
environmental risks that are not fully addressed by POTW
treatment. The MP&M industry releases 89 pollutants that
cause inhibition problems at POTWs and an additional 35
hazardous air pollutants (HAPs) that may present a
threat to human health or the environment. Other pollutants
released by the industry are found in POTW sludge. Only
eight of these pollutants have land application pollutant
criteria that limit the uses of sludge.
EPA believes that the proposed rule could not provide
further exclusions for the significantly-impacted small entity
job shops and still achieve the environmental objectives of
the regulation. The proposed rule provides regulatory relief
when compared with Option 4/8, and targets requirements
on the most serious polluters.
The multi-stakeholder Sustainable Industries Project (SIP)
for Metal Finishing (the predecessor to the Common Sense
Initiative for Metal Finishing) recognized that metal
finishers include four distinct groups with very different
environmental performance characteristics (EPA, 1994).
The SIP also recognized that these groups have very
different propensities to close in the face of declines in
financial performance. The SIP identified two particularly
problematic groups of facilities. The first group ("Tier 3"
facilities) accounts for a disproportionately large quantity of
pollutant discharges and cannot afford to invest in pollution
prevention and control technologies. This group is deterred
from closing in spite of low or non-existent profits,
however, by the threat of post-closure liabilities. The
second group of facilities ("Tier 4") is comprised of
"renegade" shops that are out of compliance and make no
attempt to improve, and often escape enforcement attention.
The problem with Tier 3 and 4 firms is that they damage the
reputation of the industry, and compete with Tier 1 firms
(those consistently in compliance with regulatory
requirements and making proactive environmental
improvements) or with Tier 2 firms (those generally in
compliance with requirements).
Unfortunately, some Tier 3 and Tier 4 firms may have an
incentive to continue operating with disappearing
profitability or even in the presence of negative cash flows,
as they would incur substantial closure costs that exceed the
value recovered by selling assets. These facilities, although
operating, are not making any additional capital investments
to improve production efficiency or environmental
performance. Since they lack internal capital and cannot
secure external financing to fund cleanups, these firms
continue to pollute and represent a significant barrier to
entry for cleaner, more efficient firms that may have higher
costs in the short run.
10.4.2 Moderate Impacts in the Printed
Wiring Board Subcategory
The Printed Wiring Board subcategory accounts for 298 or
61 percent of the 492 small entities experiencing moderate
impacts under the proposed rule. EPA considered potential
options for reducing impacts on this subcategory. Table
10.11 shows, however, that the average baseline toxic-
weighted discharges from small entity Printed Wiring Board
facilities are substantially greater on average than the
average 31 Ibs. equivalent discharged by facilities that are
excluded under the proposed option. EPA did not find it
possible to reduce impacts substantially in this subcategory
without at the same time leaving significant pollutant
loadings unregulated.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 10: Regulatory Flexibility Analysis/SBREFA
Table 10.11: Small Entity Printed Wiring Board Toxic- Weightei
(Ibs. equivalent)0
Average loadings per facility for all small entity Printed Wiring Board facilities
operating in the baseline
Average loadings per facility for small entity facilities that:
close due to the regulation
experience moderate impacts
incur before-tax compliance costs > 3% of post-compliance revenue
incur before-tax compliance costs > 1% and < 3% of post-compliance revenue
incur before-tax compliance costs < 1% of post-compliance revenue
J Pollutant Loadings
Proposed Rule
Option 2/6/10
3,258
35,645
2,643
3,099
2,990
7,057
jer Facility
Option 4/8
3,258
10,282
2,696
2,964
8,339
1,340
a. Discharges discussed in this table are total discharges and do not include POTW removals because the MP&M industry releases 89 pollutants
that cause inhibition problems at POTWs and an additional 35 hazardous air pollutants (HAPs) that may present a threat to human health or the
environment. All non-volatile pollutants released by the industry are found in sludge from POTWs, but only 8 of these pollutants have land
application pollutant criteria.
Source: U.S. EPA analysis
10.5 CONSIDERATION OF SMALL ENTITY
IMPACTS IN THE SELECTION OF THE
PROPOSED RULE
EPA gave special consideration to impacts on small entities
in selecting among regulatory options. In particular, EPA
attempted to minimize impacts on small entities while at the
same time reducing significant contributions to MP&M
pollutant loadings. The proposed rule minimizes impacts on
small entities primarily by excluding indirect dischargers
with low flows in the General Metals and Oily Waste
subcategories. As described earlier, these low flow cutoffs
exclude a substantial percentage of the small entities
potentially affected by the proposed rule, while excluding
only a modest percentage of total baseline pollutant loadings
from requirements.
Table 10.12 shows the number and percentage of facilities
owned by small versus large entities that are projected to
close under the various regulatory options.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 10: Regulatory Flexibility Analysis/SBREFA
Table 10.12: Percent of Facilities Projected to Close for Facilities Owned by Small
versus Large Entities, by Regulatory Option
Regulatory Option and Type
of Facility
Owned by Small Entities
Owned by Large Entities
Total
Owned by Small Entities
Owned by Large Entities
Total
Owned by Small Entities
Owned by Large Entities
Total
Number of Facilities
Total
Proposed R
47,445
11,478
58,923
Option 2/6
47,445
11,478
58,923
Option 4/
47,445
11,478
58,923
Projected to Close
ule
181
18
199
'10
1,227
55
1,282
8
2,920
43
2,963
Percent Closing
0.4%
0.2%
0.3%
2.6%
0.5%
2.2%
6.2%
0.4%
5.0%
Source: U.S. EPA analysis.
This table shows that the proposed rule particularly reduces
impacts on facilities owned by small entities, compared with
Options 2/6/10 and 4/8, which do not provide low flow
cutoffs for General Metals and Oily Waste indirect
dischargers or exclude Non-Chromium Anodizing, Railroad
Line Maintenance or Shipbuilding Dry Dock indirect
dischargers.
The low flow cutoffs and exclusions also substantially
reduce the number of facilities that require permits,
compared with the other regulatory options considered.
Under the proposed rule, a total of 648 facilities would
require permitting for the first time. Under Option 2/6/10,
24,013 facilities would require new permits, and Option 4/8
would require 22,678 new permits. The proposed rule
therefore substantially reduces the potential permitting
burden imposed on POTWs, including small POTWs.
Chapter 11 and Appendix C discuss POTW administrative
activities and costs under the three regulatory options.
In addition to the proposed low flow cutoffs and exclusions,
EPA considered additional options that might further reduce
impacts for facilities owned by small entities. These
options included higher flow cutoffs for indirect
dischargers. EPA concluded that excluding more facilities
owned by small entities would have excluded facilities with
unacceptably high toxic-weighted loadings, and would not
achieve the purposes of the proposed rule.
Table 10.13 shows that facilities owned by small entities
that remain regulated after the low flow cutoff and
exclusions discharge substantially more pollutants per
facility than the average toxic-weighted baseline loadings
for all indirect dischargers (733 Ibs. equivalent, not
accounting for POTW removals) and the average for
facilities excluded under the proposed rule (31 Ibs.
equivalent, not accounting for POTW removals).
10-10
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 10: Regulatory Flexibility Analysis/SBREFA
Table 10.13: Number of Regulated Indirect Dischargers Owned by Small
Entities and Average Baseline Toxic- Weighted Toxic Loadings,
Proposed Rule
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Number of Indirect
Dischargers Operating Post-
Regulation
1,640
1,228
n.a.
539
80
47
n.a.
n.a.
3,535
Average Baseline Toxic-
Wtd. Loadings per Facility"
9,568
5,130
4,157
3,658
1,472
6,957
a. Discharges discussed in this table are facility discharges and do not account for POTW removals.
Source: U.S. EPA analysis.
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MP&M EEBA Part II: Costs and Economic Impacts Chapter 10: Regulatory Flexibility Analysis/SBREFA
GLOSSARY
initial regulatory flexibility analysis: Prepared by the small business: a business with employment or revenue
EPA, the IRFA evaluates the impact of the proposed rule below the threshold specified by the Small Business
and alternative regulatory options on small entities. Administration for each 4-digit SIC.
small entity: a business, government or non-profit small government: a government that serves a
organization defined as small for purposes of RFA/SBREFA population of 50,000 or less, as defined by the Small
evaluation. Business Administration.
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MP&M EEBA Part II: Costs and Economic Impacts
Chapter 10: Regulatory Flexibility Analysis/SBREFA
ACRONYMS
HAP: hazardous air pollutant
IRFA: initial regulatory flexibility analysis
POTW: Publicly-owned treatment works
RFA: Regulatory Flexibility Act
SBA: Small Business Administration
SBREFA: Small Business Regulatory Enforcement
Fairness Act
SIP: Sustainable Industries Project
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MP&M EEBA Part II: Costs and Economic Impacts Chapter 10: Regulatory Flexibility Analysis/SBREFA
REFERENCES
U.S. Department of Commerce, Bureau of the Census, Statistics of U.S. Businesses.
U.S. Environmental Protection Agency and Industrial Economics, Incorporated. 1994. Sustainable Industry: Promoting
Strategic Environmental Protection in the Industrial Sector: Phase I Report. Office of Policy, Planning, and Evaluation.
June.
U.S. Small Business Administration, http://www.sba.gov/regulations/siccodes.
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
Chapter 12: Benefit Overview
INTRODUCTION
Part III of the EEBA assesses the benefits to society from
the reduced effluent discharges that will result from the
proposed MP&M industry regulations. EPA expects that
benefits will accrue to society in several broad categories,
including reduced health risks, enhanced environmental
quality, and increased productivity in economic activities
that are adversely affected by MP&M industry discharges.
The benefit chapters assess the national benefits expected to
accrue from the regulation. This chapter provides a
discussion of the pollutants of concern (POCs). their
effect on human health, their environmental effects, a
framework for understanding the benefits likely to be
achieved by the MP&M regulation, and a qualitative
discussion of those benefits. The following chapters
quantify and estimate the economic value of these benefit
categories. Appendices E and G provide further information
on environmental effects of MP&M pollutants and water
quality models used to assess these effects.
12.1 MP&M POLLUTANTS
EPA defines three general categories of pollutants: priority
or toxic pollutants; nonconventional pollutants; and
conventional pollutants. Priority pollutants (PPs) are
defined as any of 126 named pollutants.1 Conventional
pollutants include biological oxygen demand (BOD).
total suspended solids (TSS). oil and grease
(O&G) pH, and anything else the Administrator defines as
a conventional pollutant. Nonconventionals are a catch-all
category that includes everything that is not in the two
previously described categories. The naming system is
somewhat confusing in that some nonconventional
pollutants may be as "toxic" as, or more "toxic" than some
of the PPs.
MP&M effluents contain a variety of priority,
nonconventional, and conventional pollutants. The release
of these pollutants to our nation's surface water degrades
aquatic environments, alters aquatic habitats, and affects the
diversity and abundance of aquatic life. It also increases the
health risks to humans who ingest contaminated surface
waters or eat contaminated fish and shellfish (U.S. EPA,
CHAPTER CONTENTS:
12.1
MP&M Pollutants 12-1
12.1.1 Characteristics of MP&M Pollutants ... 12-2
12.1.2 Effects of MP&M Pollutants on
Human Health 12-2
12.1.3 Environmental Effects of MP&M
Pollutants 12-6
12.1.4 Effects of MP&M Pollutants on
Economic Productivity 12-7
12.2 Linking the Regulation to Beneficial
Outcomes 12-8
12.3 Qualitative and Quantitative Benefits
Assessment 12-9
12.3.1 Overview of Benefit Categories 12-10
12.3.2 Human Health Benefits 12-12
12.3.3 Ecological Benefits 12-12
12.3.4 Economic Productivity Benefits 12-13
12.3.5 Methods for Valuing Benefit
Events 12-13
Glossary 12-15
Acronyms 12-18
References 12-19
1 The Agency started with 129 PPs, but 3 have been dropped
from the list.
1997). A number of the pollutants commonly found in
MP&M effluents also inhibit biological wastewater
treatment systems or accumulate in sewage sludge or
sediment.
Metals are a particular concern because of their prevalence
in MP&M effluents. Metals are inorganic compounds,
generally non-volatile (with the notable exception of
mercury), and cannot be broken down by biodegradation
processes. Metals can accumulate in biological tissues,
sequester into sewage sludge in publicly owned
treatment works (POTWs). and contaminate soils and
sediments when released to the environment. Sediments
contaminated with metals become resuspended by dredging,
boat propellers, water currents or wave action, and storm
events, releasing metals back into the water column. Metals
can also become biologically available and enter terrestrial
food chains once the sludge is applied on land. Sludges
with high concentrations of metals are therefore unsuitable
for land application. Some metals are quite toxic even when
present at relatively low levels.
Human and ecological exposure and risk from
environmental releases of MP&M pollutants depend on
chemical-specific properties, the mechanism and medium of
release, and site-specific environmental conditions.
12-1
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
Chemical-specific properties include lexicological effects on
living organisms, hydrophobicity/lipophilicity,
reactivity and persistence. These properties are described
in sections 12.1.1 through 12.1.4.
12.1.1 Characteristics of MP&M
Pollutants
EPA sampled MP&M facilities nationwide to assess the
concentrations of pollutants in MP&M effluents. The
Agency collected samples of raw wastewater from MP&M
facilities and applied standard water analysis protocols to
identify and quantify the pollutant levels in each sample.
EPA used these analytical data, along with selection criteria,
to identify 132 contaminants of potential concern.2
EPA then evaluated the potential environmental fate and
transport of these pollutants and their toxicity to humans and
aquatic receptors.
Fate of the MP&M pollutants was estimated based on the
propensity of those pollutants to volatilize, adsorb onto
sediments, bioconcentrate, and biodegrade. Table E. 1 in
Appendix E lists MP&M pollutants and provides data on
human health concerns, and fate and effects.
Some of the inorganic POCs found in MP&M effluents are
also natural constituents of water, including potassium,
calcium, magnesium, iron, chlorine, fluoride, sulfate,
phosphates, silica, and a number of trace metals such as
copper and zinc.
EPA used various data sources to evaluate pollutant-specific
fate and toxicity. To evaluate potential human health
effects, the Agency relied on reference doses (RfDs)
and cancer potency slope factors (SFs). human
health-based water quality criteria (WQC).
maximum contaminant levels (MCLs) for drinking
water protection and other drinking water related criteria,
and hazardous air pollutant (HAP) and PP lists.
Appendix E.I.I provides short descriptions and definitions
for each of these measures of human health effects.
To evaluate potential fate and effects in aquatic
environments, the Agency relied on measures of acute and
chronic toxicity to aquatic species, bioconcentration
factors for aquatic species, Henry's Law constants (to
estimate volatility), adsorption coefficients (Koc) (to
estimate association with bottom sediments), and
biodegradation half-lives (to estimate the removal of
chemicals via microbial metabolism).
2 EPA identified 150 POCs. Of these 150 POCs, the Agency
estimated loadings for 132 pollutants. The benefits analysis
presented in this chapter and the following chapters addresses the
132 pollutants for which loadings are available.
The data sources used in the assessment include EPA
Ambient Water Quality Criteria (AWQC) documents
and updates, EPA's Assessment Tools for the
Evaluation of Risk (ASTER), the AQUatic
Information REtrieval System (AQUIRE). and the
Environmental Research Laboratory-Duluth
fathead minnow database, EPA's Integrated Risk
Information System (IRIS). EPA's Health Effects
Assessment Summary Tables (HEAST). EPA's 1991
and 1993 Superfund Chemical Data Matrix (SCDM).
Syracuse Research Corporation's CHEMFATEand
BIODEG databases, EPA and other government reports,
scientific literature, and other primary and secondary data
sources.
To ensure that the assessment is as comprehensive as
possible, EPA also obtained data on chemicals for which
physical-chemical properties and/or toxicity data were not
available from the sources listed above. To the extent
possible, EPA estimated values for the chemicals using the
quantitative structure-activity relationship (QSAR)
model incorporated in ASTER, and for some
physical-chemical properties, used published linear
regression correlation equations.
12.1.2 Effects of MP&M Pollutants on
Human Health
Individuals are potentially exposed to MP&M pollutants
released to the aquatic environment via consumption of
contaminated fish. Populations served by drinking water
utilities located downstream of effluent discharges from
MP&M facilities are also exposed to MP&M pollutants via
contaminated drinking water. Many of these pollutants may
increase risks to human health.
Based on the available human health toxicity data for the
132 POCs presented in Table E. 1 (Appendix E), EPA found
that:
- 77 pollutants are human systemic toxicants,
* 13 pollutants with published SFs are classified as
known, probable, or possible human carcinogens
when ingested via drinking water or food. Lead is
also classified as a possible human carcinogen in
IRIS but EPA has not developed a SF for it;
* 36 pollutants have drinking water criteria (27 with
enforceable health-based MCLs, 7 with
secondary MCLs for taste or aesthetics, and 2
with action levels for treatment);
> 35 pollutants are designated as HAPs in
wastewater;
* 43 pollutants are identified as PPs; and
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
77 pollutants have human-health based water
quality criteria (WQC) to protect against the
ingestion of water and organisms or organisms only
(see Chapter 13, Table 13.3).
The carcinogens identified by EPA in MP&M effluent
samples include known (A), probable (B1 and B2) and
possible (C) human carcinogens. These pollutants are
associated with the development of cancers in the spleen,
liver, kidney, lung, bladder, and skin, among others. These
pollutants and target organs are shown in Table 12.1.
Table 12.1: Human Carcinogens Evaluated, Weight-of -Evidence Classifications, and Target Organs
CAS Number
62533
7440382
117817
75003
75092
123911
78591
62759
86306
127184
79016
67663
Carcinogen
Aniline
Arsenic
Bis(2-ethylhexyl) phthalate
Chloroethane a
Dichloromethane
Dioxane, 1,4-
Isophorone
Nitrosodimethylamine, N-
Nitrosodiphenylamine, N-
Tetrachloroethene
Trichloroethene a
Trichloromethane
Weight-of-Evidence
Classification
B2
A
B2
B2
B2
C
B2
B2
B2
B2
Target Organs
Spleen
Liver, kidneys, lungs, bladder and skin
Liver
Liver, lungs
Liver, nasal cavity, gall bladder
Preputial gland
Liver, lungs, skin, seminal vesicle,
lymphatic/hematopoetic system
Bladder tumors, reticulum cell
sarcomas
Liver
Kidneys
A = Human Carcinogen
B1 = Probable Human Carcinogen (limited human data)
B2 = Probable Human Carcinogen (animal data only)
C = Possible Human Carcinogen
a. Pollutant has been withdrawn from the IRIS database for additional study.
Source: U.S. Environmental Protection Agency verified (IRIS) or provisional (HEAST) (U.S. EPA (1998/99d), U.S. EPA (1997)).
Noncarcinogenic hazards associated with pollutants in
MP&M effluent include systemic effects (e.g., impairment
or loss of neurological, respiratory, reproductive,
circulatory, or immunological functions), organ-specific
toxicity (e.g., kidney, small intestines, blood, testes, liver,
stomach, thyroid), fetal effects (e.g., increased fetal
mortality, decreased birth weight), other effects (e.g.,
lethargy, cataracts, weight loss, hyperactivity), and mortality.
These effects are listed by pollutant in Table 12.2.
12-3
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
Table 12.2:
CAS Number
83329
67641
98862
107028
7429905
120127
7440360
7440382
7440393
65850
100516
7440417
92524
117817
7440428
85687
7440439
75150
108907
75003
7440473
18540299
7440484
7440508
95487
106445
57125
75354
75092
68122
105679
84742
51285
606202
117840
122394
MP&M Pollutants Exhibiting Systemic
Toxicant
Acenaphthene
Acetone
Acetophenone
Acrolein
Aluminum
Anthracene
Antimony
Arsenic
Barium
Benzoic acid
Benzyl alcohol
Beryllium
Biphenyl
Bis(2-ethylhexyl) phthalate
Boron
Butyl benzyl phthalate
Cadmium
Carbon disulfide
Chlorobenzene
Chloroethane
Chromium
Chromium-hexavalent
Cobalt
Copper
Cresol, o-
Cresol, p-
Cyanide
Dichloroethene, 1,1-
Dichloromethane
Dimethylformamide, N,N-
Dimethylphenol, 2,4-
Di-n-butyl phthalate
Dinitrophenol, 2,4-
Dinitrotoluene, 2,6-
Di-n-octyl phthalate
Diphenylamine
: and Other Non-Cancer Human Health Effects"
RfD Target Organ and Effects
Liver, hepatotoxicity
Increased liver and kidney weights, nephrotoxicity
General toxicity
Cardiovascular toxicity0
Renal failure, intestinal contraction interference, adverse
neurological effects4
General toxicity
Longevity, blood glucose, cholesterol
Hyperpigmentation, keratosis and possible vascular
complications
Increased kidney weight
General toxicity
Forestomach, epithelial hyperplasia
Small intestinal lesions
Kidney damage
Increased relative liver weight
Testicular atrophy, spermatogenic arrest
Significantly increased liver-to-body and liver-to-brain
weight
Significant proteinuria (protein in urine_)
Fetal toxicity, malformations
Histopathologic changes in liver
General toxicity
Renal tubular necrosis (kidney tissue decay)4
Reduced water consumption
Heart effects4
Gastrointestinal effects, liver necrosis4
Decreased body weight and neurotoxicity
Central nervous system hypoactivity and respiratory system
distress
Weight loss, thyroid effects and myelin degeneration
Toxic effects on kidneys, spleen, lungs4; hepatic lesions
Liver toxicity
Liver and gastrointestinal system effects
Clinical signs (lethargy, prostration, and ataxia) and
hematological changes
Increased mortality
Cataract formation
Mortality, central nervous system neurotoxicity, blood
heinz bodies and methemoglobinemia, bile duct
hyperplasia, kidney histopathology
Kidney and liver increased weights, increased liver
enzymes
Decreased body weight, and increased liver and kidney
weights
12-4
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
Table 12.2:
CAS Number
100414
206440
86737
16984488
591786
7439896
78831
78591
7439965
78933
108101
80626
91576
7439987
91203
7440020
100027
59507
108952
129000
110861
7782492
7440224
100425
127184
7440280
7440315
7440326
108883
79016
75694
67663
7440622
108383
179601231
95476
MP&M Pollutants Exhibiting Systemic
Toxicant
Ethylbenzene
Fluoranthene
Fluorene
Fluoride
Hexanone, 2-
Iron
Isobutyl alcohol
Isophorone
Manganese
Methyl ethyl ketone
Methyl isobutyl ketone
Methyl methacrylate
Methylnaphthalene, 2-
Molybdenum
Naphthalene
Nickel
Nitrophenol, 4-
Parachlorometacresol
Phenol
Pyrene
Pyridine
Selenium
Silver
Styrene
Tetrachloroethene
Thallium
Tin
Titanium
Toluene
Trichloroethene
Trichlorofluoromethane
Trichloromethane
Vanadium
Xylene, m-
Xylene, m- & p_- (c_)
Xylene, o-
: and Other Non-Cancer Human Health Effects"
RfD Target Organ and Effects
Liver and kidney toxicity
Nephropathy, increased liver weights, hematological
alterations, clinical effects
Decreased red blood cell count, packed cell volume and
hemoglobin
Objectionable dental fluorosis (soft, mottled teeth)
Hepatotoxicity and ne_phrotoxcityc
Liver pathology, diabetes mellitus, endocrine disturbance,
and cardiovascular effects0
Hypoactivity and ataxia
Kidney pathology
Central nervous system effects
Decreased fetal birth weight
Lethargy, increased liver and kidney weights and urinary
protein
Increased kidney to body weight ratio
Increased uric acid
Decreased body weight
Decreased body and organ weights
Reduced fetal body weight
Kidney effects (renal tubular pathology, decreased kidney
weights)
Increased liver weight
Clinical selenosis (hair or nail loss)
Argyria (skin discoloration)
Red blood cell and liver effects
Liver toxicity, weight gain
Liver toxicity, gastroenteritis, degeneration of peripheral
and central nervous system0
Kidney and liver lesions
Considered to be physio logically inert0
Changes in liver and kidney weights
Bone marrow, central nervous system, liver, kidneys4
Histopathology and mortality
Fatty cyst formation in liver
Kidney and central nervous system effects'1
Central nervous system hyperactivity, decreased body
weight
Central nervous system hyperactivity, decreased body
weight
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
Table 12.2:
CAS Number
136777612
7440666
137304
MP&M Pollutants Exhibiting Systemic
Toxicant
Xylene, o- & p- (c)
Zinc
Ziram \ Cymate
: and Other Non-Cancer Human Health Effects"
RfD Target Organ and Effects
47% decrease in erythrocyte superoxide dismutase (ESOD)
concentration in adult human females after 10 weeks of
zinc exposure
Notes:
a. Chemicals with EPA verified (IRIS) or provisional (HEAST, or other Agency document)) human health-based RfDs, referred to as "systemic
toxicants" (U.S. EPA (1998/99d), U.S. EPA (1997)).
b. RfD based on a no-observed-adverse-effect level (NOAEL). Health effects summarized from Amdur, M.O., Doul, J., and Klaassen, C.D.,
eds. Cassarett andDoul's Toxicology, 4th edition, 1991.
c. Target organ and effects summarized from Klaassen, C.D., ed. Cassarett andDoul's Toxicology, 5th edition, 1996.
d. Target organ and effects summarized from Wexler, P., ed. Encyclopedia of Toxicology, Volumes 1-3, 1998.
12.1.3 Environmental Effects of
MP&M Pollutants
Ecological impacts of MP&M pollutants include acute
and chronic toxicity to aquatic receptors by dozens of
pollutants present in MP&M effluents, uptake of certain
pollutants into aquatic food webs, sublethal effects on
metabolic and reproductive functions, habitat degradation
from turbidity, eutrophication, dissolved oxygen
depletion, and loss of prey organisms. Metals are of
particular concern to this regulation because they (1) do
not volatilize, (2) do not biodegrade, (3) can be toxic to
plants, invertebrates and fish, (4) adsorb to sediments and
(5) bioconcentrate in biological tissues.
EPA obtained the environmental fate and toxicity
information for the 132 MP&M POCs. Table E. 1 in
Appendix E shows the environmental fate and toxicity of
each MP&M pollutant.3 EPA found that:
* 56 pollutants are not volatile or are only slightly
volatile (all metals were assumed to be
non-volatile except for mercury);
* 57 pollutants have moderate to high adsorption
potentials (all metals were assumed to have high
adsorption potential except for nickel);
* 42 pollutants have moderate to high
bioconcentration factors;
* 62 pollutants biodegrade slowly or are resistant
to biodegradation altogether (all metals were
assumed to be resistant to biodegradation);
Note that EPA was unable to obtain fate or toxicity data
for a substantial number of POCs.
> For freshwater environments, 32 pollutants have
acute toxicities to aquatic life that range from
moderate to high, and 33 pollutants have chronic
toxicities that range from moderate to high;
* For saltwater environments, 20 pollutants have
acute toxicities to aquatic life that range from
moderate to high, and 23 pollutants have chronic
toxicities that range from moderate to high.
The available information shows that dozens of the
MP&M POCs have the potential to pose significant
hazards to the aquatic environment when released to
receiving waters. A number of pollutants are of particular
concern because of their combined toxicity and fate.
These include several polyaromatic hydrocarbons
(acenaphthene, anthracene, 3,6-dimethyl-phenanthrene,
fluoranthene, phenanthrene, and pyrene), several metals
(aluminum, cadmium, copper, mercury, and selenium)
and several phthalates (di-n-octyl phthalate, butyl benzyl
phthalate, and di-n-butyl phthalate). Other pollutants are
of concern chiefly because of their toxicity (arsenic,
cyanide, chromium, lead, nickel, silver, and zinc) or their
fate (bis(2-ethylhexyl)phthalate, bromo-2-chlorobenzene,
bromo-3-chlorobenzene, dibenzofuran, dibenzothiophene,
diphenylamine, long-chained petroleum hydrocarbons,
1-methylfluorene, N-nitrosodiphenylamine, and several
metals).
The available fate and toxicity data indicate that many
MP&M pollutants tend to (1) be "toxic", (2) not readily
volatilize from the water column, (3) adsorb to sediments,
(4) bioconcentrate in aquatic organisms, and (5) do not
biodegrade. Such pollutants accumulate in sediments and
reach concentrations which can impair benthic
communities. Pollutants that have accumulated in
sediments can be released back into the water column
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
because sediments act as long-term sinks. The pollutants
can also enter soils and reach high levels over time if
present in sewage sludge that is applied to land. The
tendency of these pollutants to resist biodegradation and
to bioconcentrate in biological tissue also causes them to
be taken up into aquatic food chains where they can affect
predators or humans who consume fish and shellfish
(U.S. EPA, 1998).
The toxicity data also indicate that a sizable number of
the POCs in MP&M effluents have toxicities that result in
lethal or sub-lethal responses in aquatic receptors,
including algae, vascular plants, invertebrates, fish and
amphibians. Responses include death, which may occur
within a matter of hours to days, or longer-term sublethal
responses (such as reproductive failure or growth
impairment) that manifest themselves over weeks,
months, or even years. The effects of toxic chemicals are
not shared equally among exposed species: sensitive
species are typically more affected than species that are
more resistant. Hence, toxic conditions could selectively
remove sensitive species from receiving waters. Such a
pattern is of particular concern to threatened and
endangered (T&E) species, which may already be close
to extinction. Aquatic receptors are exposed to many
different toxicants at the same time, which may have
additive effects. The EPA assessment is based on a
chemical-by-chemical approach and therefore does not
consider additive effects. This approach may understate
the benefits of the rule.
EPA also did not evaluate the potential fate and effects of
the four conventional pollutants (BOD, pH, O&G, TSS)
and several other pollutants, including Total Petroleum
Hydrocarbon (TPH). Total Kjeldahl Nitrogen
(TKN). phosphorus, and chemical oxygen demand
(COD), which may nonetheless adversely affect aquatic
environments.4'5
- Effluents with high levels of BOD or COD
consume large amounts of dissolved oxygen in a
short time, causing surface waters to become
oxygen-depleted, thereby killing or excluding
aquatic life (U.S. EPA, 1986). At current
discharge levels, MP&M facilities discharge 414
million pounds of BOD per year.
4 TKN is defined as the total of organic and ammonia
nitrogen. It is determined in the same manner as organic
nitrogen, except that the ammonia is not driven off before the
digestion step.
5 EPA, however, considered environmental effects of TKN
in the Ohio case study. EPA evaluated the impact of in-stream
TKN concentrations on recreational value of fishing, boating,
swimming, and wildlife viewing sites. For detail see Chapter 22
of this report.
> Low pH (high acidity) water can be lethal to
aquatic organisms; sensitive species of fish and
invertebrates are eliminated from surface waters
at pH's between 6.0 and 6.5 (U.S. EPA, 1999).
* O&G and TPH can have lethal effects on fish by
coating gill surfaces and causing asphyxia,
depleting dissolved oxygen levels due to
excessive BOD, and impairing stream re-aeration
due to the presence of surface films.
Compounds present in O&G or TPH can also be
detrimental to waterfowl by affecting the
buoyancy and insulating capacity of their
feathers (U.S. EPA, 1998). At current discharge
levels, MP&M facilities discharge 221 million
pounds per year of O&G, including 73 million
pounds a year of TPH.
* TSS increases the turbidity of surface water and
impairs underwater visibility and transparency,
thereby inhibiting photosynthesis by diminishing
the amount of sunlight that reaches algae or
submerged aquatic plants. TSS also causes a
general degradation of aquatic habitats by
increasing the rate of sedimentation, which
smothers eggs, covers aquatic plants, and affects
benthic invertebrates (U.S. EPA, 1998).
* High input of nitrogen in estuarine and marine
systems or phosphorus in freshwater systems can
increase primary productivity and result in
eutrophication. Such a process overloads
surface waters with algae and reduces the
transparency of the water column. The excess
algae sink to the bottom and decompose at the
end of their life cycle. This process consumes
large amounts of dissolved oxygen and can turn
surface waters anoxic (U.S. EPA, 1998; U.S.
EPA, 1999).
12.1.4 Effects of MP&M Pollutants on
Economic Productivity
Releases of large quantities or high concentrations of
toxic pollutants in MP&M effluents may interfere with
POTW processes (e.g., inhibiting microbial degradation),
reduce the treatment efficiency or capacity of POTWs,
and reduce disposal options for the sludge. In addition,
toxic pollutants present in the effluent discharges may
pass through a POTW and adversely affect receiving
water quality, or may contaminate sludges generated
during primary or secondary wastewater treatment. EPA
expects that the proposed regulation will reduce
interferences of operations and contamination of sewage
sludge at POTWs receiving effluent discharges from
MP&M facilities.
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
Because most MP&M pollutants associated with adverse
health effects are subject to drinking water criteria,
MP&M discharges to surface water can increase the cost
of municipal water treatment by requiring investment in
chemical treatment and filtration. Public water treatment
systems must comply with drinking water criteria MCLs
and secondary standards. Compliance may require
treatment to reduce the levels of regulated pollutants
below their MCLs. Capital investment and operating and
maintenance (O&M) costs associated with treatment
technologies can be substantial. To the extent that the
proposed regulation reduces the concentration of MP&M
pollutants in source waters to values that are below
pollutant-specific drinking water criteria, public drinking
water systems will accrue benefits in the form of reduced
water treatment costs.
Releases of MP&M pollutants to surface waters may also
increase treatment costs of irrigation water and industrial
water.
12.2 LINKINS THE RESULATION TO
BENEFICIAL OUTCOMES
This section describes the linkages between promulgation
of a regulation and the expected benefits to society. As
indicated in Figure 12.1, the benefits of the proposed
regulation occur from a chain of events. These events
include: (1) Agency publication of the regulation, (2)
industry changes in production processes and/or treatment
systems, (3) reductions in pollutant discharges, (4)
changes in water quality, (5) changes in ecosystem
attributes and sewage sludge quality, (6) changes in
human responses, and (7) changes in human health and
ecological risk. The first two events reflect the
institutional and technical aspects of the regulation. The
benefit analysis begins with the third event, the changes
in the pollutant content of effluent discharges.
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
Figure 12.1: Chain of Events in a Benefits Analysis
1. EPA Publication of Regulation
2. Changes in Production Processes and/or Treatment
3. Reductions in Pollutant Discharges
4. Changes in Ambient Water Quality
(Pollutant Concentrations & Aquatic Habitat)
5. Change in Aquatic Ecosystem
(e.g., Increased Fish Populations & Diversity & Reduced
Bioaccumulation)
6. Change in Level of Demand & Value of Fishery
(e.g., Recreational & Other Benefit Categories)
7. Potential Change in Health Risk
(e.g., from Consumption of Fish Caught)
Source: U.S. EPA analysis.
In event four, changes in pollutant discharges translate into
improvements in water and sludge quality. In event five,
these improvements in turn affect in-stream and near-stream
biota (e.g., increased diversity of aquatic species and size of
species populations) and sludge disposal options. Finally,
human effects and the related valuation of benefits occur in
events six and seven. For example, improvements to
recreational fisheries and enhanced enjoyment by
recreational anglers is connected to improved water quality
and the value of reduced risk to human health. These
linkages are the basis of the benefits analysis presented in
this and the following chapters.
12.3 QUALITATIVE AND QUANTITATIVE
BENEFITS ASSESSMENT
A benefit assessment defines and quantifies the types of
improvements to human health and ecological receptors that
can be expected from reducing the amount of MP&M
pollutants released to the environment. The following
sections provide an overview of the concepts and analytic
approaches involved in the benefits assessment. The first
section describes the general categories of benefits expected
to result from the regulation and the level of analysis
undertaken for them. The following three sections review,
within the broad categories of benefits likely to be achieved
by the MP&M regulation, the specific benefits that are
evaluated in this analysis. Finally, Section 12.3.5
summarizes methods for attaching values to some of the
benefit measures. Chapters 13 through 16 present the
quantitative assessment of benefits.
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
12.3.1 Overview of Benefit Categories
The benefits of reduced MP&M discharges may be
classified in three broad categories: human health,
ecological, and economic productivity benefits. Table 12.3
summarizes the different types of benefits that fall in each of
these categories. Each category is comprised of a number of
more narrowly defined benefit categories. EPA expects that
the MP&M regulation will provide benefits to society in all
of these categories. EPA was not able to bring the same
depth of analysis to all of these categories, however, because
of imperfect understanding of the link between discharge
reductions and benefit categories, and how society values
some of the benefit events. EPA was able to quantify and
monetize some benefits, quantify but not monetize other
benefits, and assess still other benefits only qualitatively.
In addition to the national level benefits analysis, the
Agency conducted a case study in the State of Ohio to
provide in-depth analysis of the regulation's expected
benefits. The Ohio case study improves on the national
analysis in two ways. First, the analysis uses improved data
and methods to address co-occurrence of MP&M facility
benefits and other-source contributions of MP&M pollutants
in the same locations. Second, the analysis of recreational
benefits is based on original travel cost models of resource
valuation in a random utility framework. The analysis
values changes in the value of water resources for four
recreational activities ~ fishing, boating, swimming, and
near-water recreation. Due to data limitations, only three of
these four activities were valued at the national level
benefits analysis.
To provide perspective on the extent to which this regulatory
impact assessment was able to comprehensively analyze the
benefits, Table 12.3 summarizes the specific benefits within
each of the three broad benefit categories that are expected
to accrue from the MP&M regulation and the level of
analysis applied to each category. As shown in Table 12.3,
only a few of the relevant benefit categories can be both
quantified and monetized.
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
Table 12.3: Level of Analysis Performed for Specific Benefit Categories
Benefit Category
Human Health Benefits
Reduced cancer risk due to ingestion of chemically-contaminated
fish and unregulated pollutants in drinking water
Reduced systemic health hazards (e.g. reproductive,
immunological, neurological, circulatory, or respiratory toxicity)
due to ingestion of chemically-contaminated fish and unregulated
pollutants in drinking water
Reduced systemic health hazards from exposure to lead from
consumption of chemically-contaminated fish
Reduced cancer risk and health hazards from exposure to
unregulated pollutants in chemically-contaminated sewage sludge
Reduced health hazards from exposure to contaminants in waters
used recreationally (e.g., swimming)
Ecological Benefits
Reduced risk to aquatic life
Enhanced water-based recreation including fishing, near- water
recreation, and boating
Other enhanced water-based recreation such as swimming,
waterskiing; and white water rafting
Increased aesthetic benefits such as enhancement of adjoining site
amenities (e.g. residing, working, traveling, and owning property
near the water)
Nonuser value (i.e., existence, option, and bequest value)
Reduced contamination of sediments
Reduced non-point source nitrogen contamination of water if
sewage sludge is used as a substitute for chemical fertilizer on
agricultural land
Satisfaction of a public preference for beneficial use of sewage
sludge3
Economic Productivity Benefits
Reduced sewage sludge disposal costs
Reduced management practice and record-keeping costs for users of
sewage sludge that meets exceptional quality criteria
Reduced interference with POTW operations
Benefits to tourism industries from increased participation in water-
based recreation
Improved commercial fisheries yields
Addition of fertilizer to crops (nitrogen content of sewage sludge is
available as a fertilizer when sludge is land applied)3
Improved crop yield (the organic matter in land-applied sewage
sludge increases soil's water retention)3
Avoidance of costly siting processes for more controversial sewage
sludge disposal methods (e.g., incinerators) because of greater use
of land application
Reduced water treatment costs for municipal drinking water,
irrigation water, and industrial process and cooling water
Quantified
and
Monetized
X
X
X
X
X
Quantified
but Not Monetized
X
X
X
Qualitative
X
X
X
X
X
X
X
X
X
X
X
X
X
X
a. Some of these benefit categories are accounted for and quantified under the "reduced sewage sludge disposal costs."
Source: U.S. EPA analysis.
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
Each category of benefits and the level of analysis applied to
this category are discussed in greater detail below.
12.3.2 Human Health Benefits
Reduced pollutant discharges to the nation's waterways will
generate human health benefits by several mechanisms. The
most important and readily analyzed benefits stem from
reduced risk of illness associated with the consumption of
water, fish or other food that is taken from waterways
affected by MP&M discharges. Human health benefits are
typically analyzed by estimating the change in the expected
number of adverse human health events in the exposed
population resulting from a reduction in effluent discharges.
While some health effects such as cancer are relatively well
understood and thus may be quantified in a benefits analysis,
others are less well characterized and cannot be assessed
with the same rigor or at all.
EPA analyzed the following direct measures of change in
risk to human health: incidence of cancer from fish and
water consumption; reduced risk of non-cancer toxic effects
from fish and water consumption; and lead-related health
effects to children and adults. EPA was able to monetize
only two of the three measures (cancer-related and lead-
related health risks). Incidence of cancer was translated into
an expected number of avoided mortality events and, on that
basis, monetized. Lead impacts to children were evaluated
in terms of potential intellectual impairment as measured by
estimated changes in IQ. Changes in adverse health effects
to adults from lead exposure were measured in terms of
reduced risk of hypertension, non-fatal coronary heart
disease, non-fatal strokes, and mortality.
EPA also quantified but did not monetize the expected
reduction of pollutant concentrations in excess of health-
based AWQC limits. This benefit measure was obtained by
comparing in-waterway pollutant concentrations to toxic
effect levels.
In concept, the value of these health effects to society is the
monetary value that society is willing to pay to avoid the
health effects, or the amount that society would need to be
compensated to accept increases in the number of adverse
health events. "Willingness-to-pay" (WTP) values are
generally considered to provide a fairly comprehensive
measure of society's valuation of the human and financial
costs of illness associated with the costs of health care,
losses in income, and pain and suffering of affected
individuals and of their family and friends.
In some cases, available economic research provides little
empirical data for society's WTP to avoid certain health
effects. One component of the cost of an illness estimates
the direct medical costs of treating a health condition (e.g.,
hypertension), and can be used to value changes in health
risk from reduced exposure to toxic pollutants such as lead.
These estimates represent only one component of society's
WTP to avoid adverse health effects and therefore produce a
partial measure of the value of reduced exposure to MP&M
pollutants. Employed alone, these monetized effects will
significantly underestimate society's WTP.
12.3.3 Ecological Benefits
EPA expects that the ecological benefits from the regulation
will include protection of fresh- and saltwater plants,
invertebrates, fish, and amphibians, as well as terrestrial
wildlife and birds that prey on aquatic organisms exposed to
MP&M pollutants. The regulation will reduce the presence
and discharge of various pollutants and will enhance or
protect aquatic ecosystems currently under stress. The drop
in pollutant loading is expected to reestablish productive
ecosystems in damaged waterways and to protect resident
species, including T&E species. EPA also expects that the
regulation will enhance the general health offish and
invertebrate populations, increase their propagation to
waters currently impaired, and expand fisheries for both
commercial and recreational purposes. Improvements in
water quality will also favor increased recreational activities
such as swimming, boating, and water skiing. Finally, the
Agency expects that the regulation will augment nonuse
values (e.g., option, existence, and bequest values) of the
affected water resources.
It is frequently difficult to quantify and attach economic
values to ecological benefits. The difficulty results from
imperfect understanding of the relationship between changes
in effluent discharges and the specific ecological changes,
lack of water quality monitoring data for most locations, and
time lags between water quality changes and changes in
species population and composition. In addition, it is
difficult to attach monetary values to these ecological
changes because they often do not occur in markets in which
prices or costs are readily observed. As such, ecological
benefits may be loosely classified as nonmarket benefits.
This classification can be further divided into nonmarket use
benefits and nonmarket nonuse benefits.
Nonmarket use benefits stem from improvements in
ecosystems and habitats, which in turn lead to enhanced
human use and enjoyment of these areas. For example,
reduced discharges may lead to increased recreational use
and enjoyment of affected waterways in such activities as
fishing, swimming, boating, hunting or near water activities
such as bird watching. In some cases, it may be possible to
quantify and attach partial economic values to ecological
benefits using market values (e.g., an increase in tourism or
boat rentals associated with improved recreational fishing
opportunities); in this case, these benefit events might better
be classified as economic productivity related events, which
are discussed below. Economic markets, however, do not
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
provide enough information to fully capture the value of
these benefits. Such markets capture only related
expenditures made by recreationists (e.g., food and lodging)
and do not capture the value placed on the experience itself.
A variety of nonmarket valuation techniques can be used to
capture the value placed on the resource in question. These
techniques include hedonic valuation (wage-risk studies)
and travel cost methods (TCM). stated preferences
methods (i.e., contingent valuation (CM), contingent
rating (CR). contingent activity (CA)). benefits
transfer, and averting behavior models.
Nonmarket nonuse benefits are not associated with current
use of the affected ecosystem or habitat, but rather arise
from (1) the realization of the improvement in the affected
ecosystem or habitat resulting from reduced effluent
discharges and (2) the value that individuals place on the
potential for use sometime in the future. Nonmarket nonuse
benefits may also be manifested by other valuation
mechanisms, such as cultural valuation, philanthropy, and
bequest valuation. It is often extremely difficult to quantify
the relationship between changes in discharges and the
improvements in societal well-being associated with such
valuation mechanisms. That these valuation mechanisms
exist, however, is indisputable, as evidenced, for example,
by society's willingness to contribute to organizations whose
mission is to purchase and preserve lands or habitats to avert
development.
12.3.4 Economic Productivity Benefits
Reduced pollutant discharges may also benefit economic
productivity. First, economic productivity gains may occur
through reduced costs to public sewage systems (POTWs)
for managing and disposing of the sludge (i.e., biosolids)
from treating effluent discharges. For example, higher
quality sludge may be applied to agricultural land or
otherwise beneficially used rather than being incinerated or
disposed of in landfills. POTWs may also incur lower costs
because of lower record keeping requirements.
Economic productivity benefits may also accrue from
reduced treatment costs of drinking water, irrigation water,
and industrial use water. Reduced pollutant concentrations
in public water systems source water to levels at or below
MCLs or secondary standards could reduce ongoing
treatment costs and avoid the need to invest in treatment
technologies in the future. Reduced pollutant discharges
may also reduce sediment dredging costs. Contaminated
sediments may contribute substantially to contamination of
aquatic biota and human exposure to human health
toxicants. Controlling point source discharges of toxic
pollutants can prevent sediment contamination and eliminate
the need for future remediation (i.e., dredging) of
contaminated sediments.
Other economic productivity gains may result from
improved tourism opportunities in areas affected by MP&M
discharges. Improved aquatic species survival may
contribute to increased commercial fishing yield. When
such economic productivity effects can be identified and
quantified, they are generally straightforward to value
because they involve market commodities for which prices
or unit costs are readily available.
Although some of these improvements can be seen as cost
savings (i.e., reduced treatment and disposal costs), and
could be included in the economic cost analysis rather than
in the benefits analysis, they are treated in this analysis as a
benefit of the proposed effluent guideline and not included
in the cost analysis.
12.3.5 Methods for Valuing Benefit
Events
Some of the benefits expected from the MP&M regulation
will manifest themselves in economic markets through
changes in price, cost, or quantity of market-valued
activities. For benefits endpoints traded in markets, such as
increased yields from commercial fisheries, benefits can be
measured by market prices or market-based factor pricing.
Competitive prices can be also used to measure avoided
cost type of benefits. For example, reduced pollutant
loadings to public water supplies may lower costs of
drinking treatment. Similarly, improved sludge quality
resulting from the MP&M regulation would translate into an
observable reduction in sludge disposal costs for some
POTWs (see Chapter 16). Finally, market prices can be
used to value direct medical costs of illnesses associated
with exposure to pollutants. For this analysis, we used
medical costs associated with treating hypertension,
coronary heart disease, and stroke to estimate benefits from
reduced exposure to lead (see Chapter 14). The estimated
values can be used as minimum measures of the benefits
associated with reduced cases of these illnesses.
In other cases, benefits involve activities or sources of value
that either do not involve economic markets or involve them
only indirectly. Methods used to value such benefits are
described briefly below:
a. Wage-risk approach.
The wage-risk approach uses regression estimates of the
wage premium associated with greater risks of death on the
job to estimate the amount that persons are willing to pay to
avoid death. Benefit values based on this approach are used
as part of the basis for valuing reduced cancer cases due to
fish consumption in Chapter 13.
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
b. Travel cost method
The TCM uses information on the costs that people incur in
traveling to and using a particular site to estimate a demand
curve for that site. The demand curve is then used to
estimate the "consumer surplus" associated with the use of
the site, that is, the value that consumers receive from the
site over and above the costs that they incur in using it.
Consumer surplus is an estimate of the net benefits of the
resource to the people using that resource. For example, if
the resource is a recreational fishing site, the TCM can be
used to value the recreational fishing experience. TCM is
one of the approaches used to value recreational benefits in
Chapter 15. The Agency also used an original travel cost
study to value benefits from enhanced water-based
recreation in Ohio (see Part IV: Chapter 21).
c. Contingent valuation
In the CV method, surveys are conducted to elicit
individuals' WTP for a particular good, such as a fishery, or
clean water. CV is more broadly applicable than TCM.
Like TCM, CV can be used to estimate the consumer surplus
associated with recreational fisheries. CV can also be used
to estimate less tangible values, such as how much people
care about a clean environment. Values from both the CV
approach and the wage-risk approach support the estimated
value of avoided death that is used to monetize reduced
cancer cases from consumption of contaminated fish
(Chapter 13). In addition, the analysis of recreational
benefits in Chapter 15 uses a baseline value of the fishery
that is derived from CV analysis.
d. Benefits transfer
When time and resource constraints preclude primary
research, benefit assessment based on benefit transfer from
existing studies is used. This approach involves
extrapolating benefit findings for one analytic situation to
another. The relevant study situations are defined by type of
environmental resource (e.g., fishery), policy variable(s),
and the characteristics of user populations. The benefits
transfer approach is used to monetize several benefit
categories, including changes in the incidence of cancer
cases (Chapter 13) and the national-level benefits from
enhanced water-based recreation (Chapter 15).
The techniques described above form the basis of the
benefits methodologies described in Chapters 13,14 and 15.
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
GLOSSARY
acute toxicity: the ability of a substance to cause severe
biological harm or death soon after a single exposure or
dose. Also, any poisonous effect resulting from a single
short-term exposure to a toxic substance. (See: chronic
toxicity, toxicity.)
(http://www.epa.gov/OCEPAterms/aterms.html)
adsorption coefficients (Koc): represents the ratio of
the target chemical absorbed per unit weight of organic
carbon in the soil or sediment to the concentration of that
same chemical in solution at equilibrium.
ambient water quality criteria (AWQC): AWQC
present scientific data and guidance of the environmental
effects of pollutants which can be useful to derive regulatory
requirements based on considerations of water quality
impacts; these criteria are not rules and do not have
regulatory impact (U.S. EPA. 1986. Quality Criteria for
Water 1986. U.S. Environmental Protection Agency, Office
of Water Regulations and Standards, Washington, DC. EPA
440/5-86-001).
AQUatic Information REtrieval System (AQUIRE): a
web-based ecotoxicity database maintained by EPA's
Mid-Continent Ecology Division (MED) which summarizes
ecotoxicity data retrieved from the literature.
(http://www.epa.gov/med/databases/databases.htmMaquire).
Assessment Tools for the Evaluation of Risk
(ASTER): an ecological risk assessment tool developed by
EPA's Mid-Continent Ecology Division (MED); ASTER
integrates information from the AQUIRE toxic effects
database and the QSAR system (a structure activity based
expert system) to estimate ecotoxicity, chemical properties,
biodegradation and environmental partitioning.
(http://www.epa.gov/med/databases/aster.html)
avoided cost: costs that are likely to be incurred in the
future if current conditions still prevail at the time, but
which will be avoided if particular actions are taken now to
change the status quo.
benthic: relating to the bottom of a body of water; living
on, or near, the bottom of a waterbody.
BIODEG: a web-based biodegradation database developed
by Syracuse Research Corporation
(http://esc.syrres.com/efdb/BIODGSUM.HTM).
biodegradation half-lives: represents the number of
days a compound takes to be degraded to half of its starting
concentration under prescribed laboratory conditions.
biological oxygen demand (BOD): the amount of
dissolved oxygen consumed by microorganisms as they
decompose organic material in an aquatic environment.
cancer potency slope factor (SF): a plausible upper-
bound estimate of the probability of a response per unit
intake of a chemical over a lifetime. The slope factor is used
to estimate an upper-bound probability of an individual
developing cancer as a result of a lifetime of exposure to a
particular level of a potential carcinogen.
CHEMFATE: a web-based chemical fate database
developed by Syracuse Research Corporation
(http://esc.syrres.com/efdb/Chemfate.htm).
chemical oxygen demand (COD): A measure of the
oxygen required to oxidize all compounds, both organic and
inorganic, in water.
(http://www.epa.gov/OCEPAterms/cterms.html)
chronic toxicity: the capacity of a substance to cause
long-term poisonous health effects in humans, animals, fish,
and other organisms.
(http://www.epa.gov/OCEPAterms/cterms.html)
contingent activity: is one of the stated preference
methods (see: contingent valuation and contingent activity).
Survey respondents are asked how their behavior would
change in response to a proposed change in one or more
attributes of an activity (e.g., cost of the activity, site
accessibility, or site attractiveness). Given responses to this
type of question, and given information about incremental
travel costs and value of time, a revealed preference method
can be used to estimate the value of change.
contingent rating: is one of the stated preference
methods (see: contingent valuation and contingent activity).
Survey respondents are asked to rate several alternatives on
an ad hoc utility scale (e.g., 1 to 10). The choice set of
alternatives usually includes the environmental effect to be
valued, substitutes for the effect, and a good with a
monetary price to act as a threshold. Based on the
respondent's rating of the environmental effect and the
threshold good, and the monetary price of the threshold
good, the value of the environmental effect can be
determined.
contingent valuation (CV): a method used to determine
a value for a particular event, where people are asked what
they are willing to pay for a benefit and/or are willing to
receive in compensation for tolerating a cost. Personal
valuations for increases or decreases in the quantity of some
good are obtained contingent upon a hypothetical market.
The aim is to elicit valuations or bids that are close to what
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
would be revealed if an actual market existed.
(http://www.damagevaluation.com/glossary.htm)
Environmental Research Laboratory-Duluth
fathead minnow database: a data base developed by
EPA's Mid-Continent Ecology Division (MED) which
provides data on the acute toxicity of hundreds of industrial
organic compounds to the fathead minnow.
(http://www.eoa.gov/med/databases/fathead_minnow.html)
hazardous air pollutant (HAP): compounds that EPA
believes may represent an unacceptable risk to human health
if present in the air.
Health Effects Assessment Summary Tables
(HEAST): a comprehensive listing of provisional human
health risk assessment data relative to oral and inhalation
routes for chemicals of interest to EPA. Unlike data in IRIS,
HEAST entries have received insufficient review to be
recognized as high quality, Agency-wide consensus
information (U.S. EPA. 1997. Health Effects Assessment
Table; FY 1997 Update. EPA-540-R-97-036).
Henry's Law constant: a numeric value which relates the
equilibrium partial pressure of a gaseous substance in the
atmosphere above a liquid solution to the concentration of
the same substance in the liquid solution.
human health-based water quality criteria (WQC):
human health-based criteria are based on specific levels of
pollutants that would make the water harmful if used for
drinking, swimming, farming, fish production, or industrial
processes (see AWQC).
http://www.epa.gov/OCEPAterms/wterms.html)
hydrophobicity: having a strong aversion to water
(http://www.epa.gov/OCEPAterms/hterms.html)
Integrated Risk Information System (IRIS): IRIS is an
electronic data base with information on human health
effects of various chemicals. IRIS provides consistent
information on chemical substances for use in risk
assessments, decision-making and regulatory activities.
lipophilicity: having a strong attraction to oils
maximum contaminant levels (MCLs): the maximum
permissible level of a contaminant in water delivered to any
user of a public system. MCLs are enforceable standards.
(http://www.epa.gov/OCEPAterms/mterms.html)
metals: inorganic compounds, generally non-volatile, and
which cannot be broken down by biodegradation processes.
They are a particular concern because of their prevalence in
MP&M effluents. Metals can accumulate in biological
tissues, sequester into sewage sludge in POTWs, and
contaminate soils and sediments when released to the
environment. Some metals are quite toxic even when present
at relatively low levels.
microbial metabolism: biochemical reactions occurring
in living microorganisms such as bacteria, algae, diatoms,
plankton, and fungi. POTWs make use of bacterial
metabolism for wastewater treatment purposes. This process
is inhibited by the presence of toxics such as metals and
cyanide because these pollutants kill bacteria.
oil and grease (O&G): organic substances that may
include hydrocarbons, fats, oils, waxes, and high-molecular
fatty acids. Oil and grease may produce sludge solids that
are difficult to process.
(http://www.epa.gov/owmitnet/reg.htm)
pH: An expression of the intensity of the basic or acid
condition of a liquid; Natural waters usually have a pH
between 6.5 and 8.5.
(http://www.epa.gov/OCEPAterms/pterms.html)
pollutants of concern (POCs): are the 150
contaminants identified by EPA as being of potential
concern for this rule and which are currently being
discharged by MP&M facilities.
priority pollutant (PP): 126 individual chemicals that
EPA routinely analyzes when assessing contaminated
surface water, sediment, groundwater or soil samples.
publicly-owned treatment works (POTWs): a
treatment works, as defined by section 212 of the Act, that is
owned by a State or municipality. This definition includes
any devices or systems used in the storage, treatment,
recycling, and reclamation of municipal sewage or industrial
wastes of a liquid nature. It also includes sewers, pipes, or
other conveyances only if they convey wastewater to a
POTW Treatment Plant.
(http://www.epa.gov/owm/permits/pretreat/final99.pdf)
quantitative structure-activity relationship (QSAR)
model: an expert system which uses a large database of
measured physicochemical properties such as melting point,
vapor pressure and water solubility to estimate the fate and
effect of a specific chemical based on its molecular
structure, (http://www.epa.gov/med/databases/aster.html)
reference doses (RfDs): chemical concentrations
expressed in mg of pollutant/kg body weight/day, that, if not
exceeded, are expected to protect an exposed population,
including sensitive groups such as young children or
pregnant women.
secondary MCLs: human health-based drinking water
criteria to assess the health hazards associated with the
presence of certain toxic chemicals in drinking water.
SMCLs are established for taste or aesthetic effects.
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
Superfund Chemical Data Matrix (SCDM): a source
for factor values and benchmark values applied when
evaluating potential National Priorities List (NPL) sites
using the Hazard Ranking System (HRS).
(http ://www. epa. gov/superfund/resources/scdm/index. htm).
suspended solids: small particles of solid pollutants that
float on the surface of, or are suspended in, waterbodies.
(http://www.epa.gov/OCEPAterms/sterms.html)
systemic toxicants: chemicals that EPA believes can
cause significant non-carcinogenic health effects when
present in the human body above chemical-specific toxicity
thresholds.
threatened and endangered (T&E): animals, birds,
fish, plants, or other living organisms threatened with
extinction by anthropogenic (man-caused) or other natural
changes in their environment. Requirements for declaring a
species endangered are contained in the Endangered Species
Act.
Total Petroleum Hydrocarbon (TPH): a general
measure of the amount of crude oil or petroleum product
present in an environmental media (e.g., soil, water, or
sediments). While it provides a measure of the overall
concentration of petroleum hydrocarbons present, TPH does
not distinguish between different types of petroleum
hydrocarbons.
Total Kjeldahl Nitrogen (TKN): the total of organic and
ammonia nitrogen. TKN is determined in the same manner
as organic nitrogen, except that the ammonia is not driven
off before the digestion step.
total suspended solids (TSS): a measure of the
suspended solids in wastewater, effluent, or water bodies,
determined by tests for "total suspended non-filterable
solids." (See: suspended solids.)
(http://www.epa.gov/OCEPAterms/tterms.html)
total suspended particles (TSP): a method of
monitoring airborne paniculate matter by total weight.
(http://www.epa.gov/OCEPAterms/tterms.html)
travel cost method (TCM): method to determine the
value of an event by evaluating expenditures of recreators.
Travel costs are used as a proxy for price in deriving
demand curves for the recreation site.
(http://www.damagevaluation.com/glossary.htm)
uptake: the movement of one or more chemicals into an
organism via ingestion, inhalation, and or trough the skin.
vascular plants: plants that are composed of, or provided
with vessels or ducts that convey fluids.
(www.infoplease.com)
willingness to pay (WTP): maximum amount of money
one would give up to buy some good.
(http://www.damagevaluation.com/glossary.htm)
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MP&M EEBA Part III: Benefits
Chapter 12: Benefit Overview
ACRONYMS
AQUIRE: AQUatic Information REtrieval System
ASTER: Assessment Tools for the Evaluation of Risk
AWQC: ambient water quality criteria
BIODEG: biodegradation
BOD: biological oxygen demand
CA: contingent activity
CHEMFATE: chemical fate
CR: contingent rating
CV: contingent valuation
COD: chemical oxygen demand
HAP: hazardous air pollutant
HEAST: Health Effects Assessment Summary Tables
IRIS: Integrated Risk Information System
Koc: adsorption coefficient
MCL: maximum contaminant level
O&G: oil and grease
POC: pollutant of concern
POTW: publicly owned treatment work
PP: priority pollutant
QSAR: quantitative structure-activity relationship
RfD: reference dose
SCDM: Superfund Chemical Data Matrix
SF: cancer potency slope factor
T&E: threatened and endangered
TCM: travel cost method
TKN: Total Kjeldahl Nitrogen
TPH: Total Petroleum Hydrocarbon
TSS: total suspended solids
WQC: human health-based water quality criteria
WTP: willingness-to-pay
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MP&M EEBA Part III: Benefits Chapter 12: Benefit Overview
REFERENCES
Amdur, M.O., Doul, J., and Klaassen C.D., eds. 1991. Cassarett and Doul's: Toxicology, the Basic Science of Poisons. 4th
ed. McGraw-Hill Inc., New York.
Amdur, M.O., Doul, J., and Klaassen C.D., eds. 1996. Cassarett and Doul's: Toxicology, the Basic Science of Poisons. 5th
ed. McGraw-Hill Inc., New York.
Syracuse Research Corporation (BIODEG, CHEMFATE). 1999. Syracuse Research Corporation's Environmental Fate Data
Bases. Syracuse Research Corporation, Syracuse, NY. http://esc.syrres.com/efdb/BIODGSUM.HTM and
http://esc.syrres.com/efdb/Chemfate.htm.
U.S. Environmental Protection Agency. (U.S. EPA). 1980. Ambient water quality criteria documents. Washington, DC:
Office of Water, U.S. EPA. EPA 440/5-80 Series. Also refers to any update of criteria documents (EPA 440/5-85 and EPA
440/5-87 Series) or any Federal Register notices of proposed criteria or criteria corrections, and EPA 822-Z-99-001. The
most recent National Recommended Water Quality Criteria used in this report were published in the Federal Register on
December 10, 1998.
U.S. Environmental Protection Agency. (U.S. EPA). 1986. Ambient Water Quality Criteria for Dissolved Oxygen. EPA
440/5-86-003.
U.S. Environmental Protection Agency. (U.S. EPA). 1995. Proceedings of the First Gulf of Mexico Hypoxia Management
Conference. EPA-55-R-97-001.
U.S. Environmental Protection Agency. (U.S. EPA). 1997. Health Effects Assessment Summary Tables (HEAST). Office
of Research and Development and Office of Emergency and Remedial Response, Washington, DC: U.S. EPA.
U.S. Environmental Protection Agency. (U.S. EPA). 1998. National Water Quality Inventory. 1996 Report to Congress.
EPA 841-R-97-008.
U.S. Environmental Protection Agency. (U.S. EPA). 1998/99a. QSAR. Duluth, MN: Environmental Research Laboratory,
U.S. Environmental Protection Agency.
U.S. Environmental Protection Agency. (U.S. EPA). 1998/99b. Aquatic Toxicity Information Retrieval (AQUIRE) Data
Base. Mid-Continent Ecology Division (MED), Duluth, MN. U.S. Environmental Protection Agency. Database retrieval
@ http://www.epa.gov/ecotox/
U.S. Environmental Protection Agency. (U.S. EPA). 1998/99c. Assessment Tools for Evaluation of Risk (ASTER) Data
Base. Duluth, MN: Environmental Research Laboratory, U.S. Environmental Protection Agency. 1998 Database retrieval.
U.S. Environmental Protection Agency. (U.S. EPA). 1998/99d. Integrated Risk Information System (IRIS). Washington,
DC: U.S. Environmental Protection Agency. 1998 Database retrieval @ http://www.epa.gov/iris/
U.S. Environmental Protection Agency. (U.S. EPA). 1999. Progress Report on the EPA Acid Rain Program. U.S. EPA
Office of Air and Radiation. EPA 430-R-99-011.
Wexler, P., ed. 1998. Encyclopedia of Toxicology, Volumes 1-3.
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
Chapter 13: Human Health
Benefits
INTRODUCTION
EPA expects that the proposed MP&M regulation will yield
human health benefits by reducing effluent discharges to
waterways used for fishing or drinking water.
This chapter reviews four categories of expected human
health benefits. The first two categories involve reductions
in cancer cases from two exposure pathways: consumption
of contaminated fish tissue and ingestion of contaminated
drinking water. EPA evaluated the expected annual
reduction in cancer cases in the exposed population and the
associated monetary value of avoiding those cancer cases.
EPA quantified, but did not monetize, two additional
measures of human health-related benefits. The first is the
changes in fish consumption and drinking water exposures
to non-cancer causing pollutants measured against systemic
health effect reference doses (RfDs). an indicator of
non-cancer, systemic health risk. The second benefit
measure is the change in occurrence of pollutant
concentrations that are estimated to exceed human health-
based ambient water quality criteria (AWQC).
EPA also quantified and monetized changes in health risk to
adults and children from reduced exposure to lead. This
analysis is presented in Chapter 14.
The health-related measures were estimated for the baseline
and for the proposed option for all of the benefit categories
analyzed.1 The reduction in the health-related measures
(i.e., number of annual cancer cases) from baseline to the
post-compliance case is the estimated benefit of the
proposed regulation.
EPA estimated that, for combined recreational and
subsistence angler populations, the proposed option would
eliminate approximately 0.05 cancer cases per year due to
fish consumption, from a baseline of about 0.13 cases
estimated at current discharge levels, representing a
reduction of 35.7 percent. The monetary value of avoiding
1 Benefit values were also estimated for alternative options,
which EPA considered for proposal. Cost and benefit results for
these options are summarized in Chapter 19.
CHAPTER CONTENTS;
13.1 Methodology & Data Sources 13-2
13.1.1 Cancer from Fish Consumption 13-3
13.1.2 Cancer from Drinking Water
Consumption 13-6
13.1.3 Exposures Above Systemic
Health Thresholds 13-8
13.1.4 Human Health AWQC 13-11
13.2
Results 13-14
13.2.1 Fish Consumption Cancer
Results 13-14
13.2.2 Drinking Water Consumption
Cancer Results 13-16
13.2.3 Systemic Health Threshold
Results 13-16
13.2.4 Human Health AWQC Results 13-17
13.3
Limitations and Uncertainties 13-17
13.3.1
13-17
Sample Design & Analysis of
Benefits by Location of Occurrence
In-Waterway Concentrations of
MP&M Pollutants 13-18
Joint Effects of Pollutants 13-18
Background Concentrations of
MP&M Pollutants 13-18
Downstream Effects 13-19
Exposed Fishing Population 13-19
Cancer Latency & Human Health .... 13-19
Glossary 13-21
Acronyms 13-22
References 13-23
13.3.2
13.3.3
13.3.4
13.3.5
13.3.6
13.3.7
these cancer cases yields benefits of $0.3 million (1997$)
per year for the fish consumption pathway.
When considering the effect of the proposed regulation on
the drinking water pathway, this analysis differentiates
between the seven pollutants for which EPA has established
drinking water criteria and the six pollutants that do not have
criteria. This analysis assumes that public drinking water
treatment systems will reduce the levels of seven of the 13
pollutants in the public water supply to levels that meet
established criteria and are protective of human health. For
this analysis, EPA does not estimate benefits of the avoided
cancer cases associated with these seven pollutants via the
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
drinking water pathway.2 This analysis focuses on the
remaining six carcinogens for which drinking water criteria
are not available. Based on the analysis of these six
carcinogens, the proposed option would eliminate about
2.24 cancer cases per year for the drinking water pathway,
from a baseline of 5.10 cases estimated at current discharge
levels, representing a reduction of 43.9 percent. The
monetary value of these reduced cancer cases is 13.0 million
(1997$) per year. All dollar values presented throughout the
rest of this chapter are in 1997 dollars unless specified
otherwise. The total monetized human health benefits from
reduced cancer cases from both the fish consumption and
drinking water pathways is $13.3 million per year.
Additional benefits will also be realized in the form of
reductions in non-cancer, systemic health risks. For this
analysis, EPA measures the change in the population
exposed to excessive levels of MP&M pollutants from
consuming contaminated fish or ingesting contaminated
drinking water.
EPA evaluated the distribution of populations exposed to
quantities of pollutants that potentially pose a risk of
systemic health effects. The results of the analysis suggest
that the proposed option will reduce the risk of systemic
health effects for a substantial portion of the exposed
population and significantly increase the portion of the
population that is not exposed to any systemic health hazard
from MP&M pollutant discharges. However, the marginal
risk of systemic health hazard from pollutants discharged by
MP&M sample facilities alone is quite low. The
significance of the marginal risk depends on the risk related
to background exposures to pollutants from sources other
than the MP&M industries.
Finally, EPA analyzed the effect of the proposed regulation
in terms of AWQC. EPA estimated that under the proposed
option, the number of waterways with concentrations for at
least one affected pollutant that exceed human health-based
AWQC will be reduced from 10,310 in the baseline to
9,205.
13.1 METHO&oioey <& DATA SOURCES
Individuals are potentially exposed to pollutants from
MP&M facilities via consumption of contaminated fish
tissue and drinking water. Potential human health effects
include cancer and non-cancer health effects. Risks such as
skin, lung, liver, kidney, and bladder cancer and leukemia
are associated with exposure to 13 MP&M pollutants (see
Table 12.1). Non-cancer health effects are associated with
2 Due to resource constraints, EPA did not estimate the
savings in treatment costs that might accrue to drinking water
systems as a result of reduced concentrations of the seven
pollutants in the intake waters.
exposure to 77 MP&M pollutants. These effects include
increased blood pressure, gastrointestinal effects, liver and
kidney toxicity, cardiovascular and central nervous system
effects, and decreased birth weight (see Table 13.2).
This section summarizes the methodology for estimating
national benefits for three benefit categories:
1. reduced incidence of cancer from consumption of fish
taken from waterways affected by MP&M industry
discharges,
2. reduced incidence of cancer from ingestion of water
taken from waterways affected by MP&M industry
discharges, and
3. reduced occurrence of pollutant concentrations resulting
from MP&M discharges that exceed human health-
based AWQC.
Benefits for a fourth category, the reduced frequency of
ingestion of pollutants via fish and water consumption in
quantities exceeding the RfD, an indicator of non-cancer,
systemic health risk, was estimated only at the sample level
and not at the national level due to data limitations
associated with sample design.
To evaluate benefits, EPA compared discharges under the
proposed option to baseline conditions. Human health-
related benefit analyses were performed for sample MP&M
facilities using EPA engineering estimates of baseline and
option-specific pollutant loadings.
This analysis does not include all possible human health
benefits and does not provide a comprehensive estimate of
the total human health benefits associated with the proposed
rule. Analyses of health benefits are not possible for a
significant number of the pollutants whose discharges will
be reduced by the proposed regulation.
Beyond these important limitations, the methodologies used
to assess the human health benefits involve significant
simplifications and uncertainties. Elements of the analysis
involving significant simplifications and uncertainties
include the following: sample design and analysis of
benefits by location of occurrence; estimation of in-
waterway concentrations of MP&M pollutants;
consideration of the joint effects of pollutants; consideration
of background concentrations of MP&M pollutants;
consideration of downstream effects; and estimation of the
exposed fishing population. Section 13.3 provides more
detail on limitations and uncertainties associated with the
human health benefits analyses. Whether these
simplifications and uncertainties, taken together, are likely to
lead to an understatement or overstatement of the estimated
economic values for the human health benefits that were
analyzed is not known.
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
13.1.1 Cancer from Fish Consumption
The analysis of reduced annual occurrence of cancer in
exposed populations via the fish consumption pathway
involves three analytic steps:
* estimating the reduced annual risk of incurring
cancer per exposed individual;
* estimating the population that would be expected to
benefit from reduced contamination of fish; and
> calculating the change in the number of cancer
events in the exposed population. Each step is
discussed in detail below.
a. Estimating change in individual cancer
risk
The estimated marginal risk to an individual of developing
cancer is based on four factors:3
> the quantity of carcinogenic chemicals that MP&M
facilities discharge to waterways,
* the rate at which the discharged chemicals
accumulate in fish tissue,
* the cancer effect of the chemicals, and
> the rate of personal consumption of contaminated
fish.
For each sample MP&M facility and the waterway to which
it discharges, EPA calculated the marginal cancer risk to two
population classes with different fish consumption rates:
recreational anglers and subsistence anglers. EPA
calculated the marginal cancer risk values for baseline (i.e.,
before regulation) pollutant discharges and for post-
compliance discharges based on the proposed option. The
following discussion summarizes the marginal cancer risk
calculations.
EPA calculated the in-waterway pollutant concentrations for
each MP&M facility using a simplified waterway dilution
model for all chemicals for which a quantitative relationship
between ingestion rate and the annual probability of
developing cancer has been estimated. EPA used a model
that accounts for the dilution characteristics of different
waterbody types (i.e., streams, estuaries, and lakes). The
model does not account for other fate processes, such as
chemical degradation or photolysis. In addition, the analysis
considered only the discharge site and did not estimate
concentrations below the initial point of discharge. For
additional details on the calculation of waterway
concentrations, see Appendix E.
The marginal cancer risk associated with each pollutant was
calculated based on the estimated concentration of the
pollutant in the affected waterway, the assumed uptake of
the pollutant into fish flesh, the daily rate of fish ingestion,
and the cancer risk factor for each pollutant. The formula
for calculating the risk to an individual from consumption of
a given chemical is as follows:
Risk =
where:
Risk
C
CF,
CR
BCF
EF
ED
BW
LT
CF2
SF
marginal risk of incurring cancer from fish
consumption (change in probability);
pollutant concentrations in surface water
(Mg/0;
conversion factor, micrograms to
milligrams (0.001 mg/ug);
human consumption rate offish (kg/day);
bioconcentration factor of pollutant in fish
(I/kg);
exposure frequency (365 days/year);
exposure duration (years);
human body weight (70 kg);
human lifetime (70 years);
conversion factor, years to days (365
days/year); and
pollutant cancer potency factor
(mg/kg/day)"1.
3 The risk value is referred to as the marginal risk because it
is the incremental lifetime probability that an individual will
develop cancer above and beyond the baseline probability posed by
all other extant factors that contribute to a risk of developing
The pollutants analyzed and their cancer potency factors are
presented in Table 13.1. EPA used the relationship outlined
above to estimate risk values for subsistence and
recreational fishing households. The risks for these
population subgroups differ in the assumed consumption
rates. Persons living in subsistence fishing households are
assumed to consume 124.1 grams per day (0.124 kg/day) of
fish over 70 years of exposure. Persons living in
recreational fishing households are assumed to consume
12.1 grams of freshwater/estuarine fish per day (0.012
kg/day) over a 70-year period. The fish consumption values
are based on uncooked fish weights, and use data from all
ages of the population surveyed. They represent the 90th and
99th percentiles, respectively, of the empirical distribution of
the U.S. per capita freshwater/estuarine finfish and shellfish
consumption, and do not include consumption of marine
fish.
Persons in recreational fishing households associated with
marine reaches are assumed to consume 57.8 grams of
fish per day (0.0578 kg/day) over a 70-year period. Persons
13-3
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
living in subsistence fishing households associated with
marine reaches are assumed to consume 189.9 grams per day
(0.1899 kg/day) offish over 70 years of exposure. These
percentile point estimates are based on the U.S. Department
of Agriculture 1994-96 Continuing Survey of Food Intake
by Individuals (CSFII) (EPA, 2000).
To estimate the annual increased risk of cancer in
recreational and subsistence anglers and their families, the
lifetime risk values were then divided by 70 (an estimate of
lifetime).
Table 13.1: Cancer Potency Factors for MP&M Pollutants
CAS Number
62533
62759
67663
75003
75092
75354
78591
79016
86306
117817
123911
127184
7440382
Regulated Pollutant
Aniline
Nitrosodimethvlamine, N-
Trichloromethane
Chloroethane
Dichloromethane
Dichloroethene, 1,1-
Isophorone
Trichloroethene
Nitrosodiphenylamine; N-
Bis(2-ethy Ihexy 1) phthalate
Dioxane^ 1;4-
Tetrachloroethene
^rsenic^
Cancer Potency
Factor (mg/kg/day) J
0.0057
51
0.0061
0.0029
0.0075
0.6
0.00095
0.011
0.0049
0.014
0.011
0.052
1.5
Drinking
Water
Criterion?
Yes
Yes
Yes
Yes
Yes
Yes
Yes
The cancer potency factor is the incremental probability of developing cancer over a lifetime resulting from ingestion of the
indicated chemical at the rate of one milligram per day per kilogram of body mass. For the marginal rates of exposure in
this analysis and assuming reasonable background chemical exposures, the potency factor may be reasonably assumed to be
a linear constant.
Source: U.S. EPA (1998/99); U.S. EPA (1997a).
The pollutant-specific risks to recreational and subsistence
anglers from MP&M facility discharges were then summed
across pollutants for each type of angler, to obtain marginal
risks for each population group from each facility's
discharge. EPA developed separate estimates of cancer risk
for each combination of angler type and facility discharging
at least one pollutant with a cancer risk factor. The total
change in probability of developing cancer from exposure to
more than one MP&M pollutant is assumed to be the sum of
the marginal risk effects from each pollutant: that is, the
effects of the individual pollutants are assumed to be
linearly additive.4 This analysis excludes populations
4 Note that the assumption of linear additivity of cancer risk
effects applies not only to the combination of pollutants from a
single facility but also to the combined effects of multiple facility
discharges. When more than one MP&M facility discharges to the
same affected waterway a circumstance found to occur with
some frequency in the sample facility data the combination of
the multiple facility discharges may be accounted for by simply
analyzing the effects of each facility independently. The cancer
effects from multiple facilities can be aggregated to estimate cancer
cases in the exposed population.
exposed to MP&M pollutants, if the estimated individual
lifetime risk from exposure to carcinogens discharged by
MP&M facilities is less than 10"6 under the baseline
discharge levels.
b. Estimating the affected population
The population exposed to contaminated fish and thus
expected to benefit from reduced discharges includes
recreational and subsistence anglers who fish the affected
reaches, as well as members of such anglers' households. A
"reach" is a specific length of river, lake shoreline, or
marine coastline, and an "MP&M reach" is one to which an
MP&M facility discharges. The geographic area from
which anglers would travel to fish a reach is assumed to
include only those counties that abut a given reach.5 This
5 The exposed, and thus potentially benefitting, population
would also include a category of "all other individuals" who
consume freshwater and estuarine fish. Although these individuals
are expected to have a much lower average daily consumption rate
than anglers in the adjacent counties, they nevertheless would
likely receive some benefit from reduced exposure to pollutants
13-4
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
assumption is based on the finding in the 1991 National
Survey of Fishing, Hunting, and Wildlife-Associated
Recreation that 65 percent of anglers travel less than 50
miles to fish (U.S. Department of the Interior, 1993).
Estimating the number of persons fishing a reach involved
the following steps:
* Estimating the licensed fishing population in
counties abutting MP&M reaches;
* Estimating the population of subsistence fishermen
in counties abutting MP&M reaches; and
* Estimating the fraction of the total fishing
population in counties abutting an MP&M reach
that fish the MP&M reach and, from that fraction,
the size of population expected to fish each MP&M
reach.
Adjusting the calculated fishing populations for the presence
of fish advisories.
Including family members in the exposed population
estimates.
ซ> Estimating the licensed fishing population in counties
abutting MP&M reaches
The number of fishing licenses sold in counties abutting
MP&M reaches is assumed to approximate the number of
anglers residing in the abutting counties. EPA excluded the
non-resident, one-day, and three-day license categories from
the total number of licenses used in this analysis. Data on
fishing licenses are not available for every state in which
MP&M facilities are located. EPA used state-level data to
estimate the number of fishing licenses per county for those
states for which county-level data were not assembled.
Total state licenses were apportioned to counties based on
the ratio of total population in the county abutting a
discharge reach to total state population. Where an MP&M
reach spans more than one county, fishing licenses were
summed across all counties abutting the discharge reach.
Where a reach lies in more than one state, EPA separately
calculated the number of licenses for the abutting
county(ies) based on the fishing license and county
population data for the respective states.
ซ> Estimating the population of subsistence fishermen in
counties abutting MP&M reaches
Although fishing licenses may be sold to subsistence
fishermen, many of these individuals do not purchase
fishing licenses. The extent of subsistence fishing in the US
or in individual states is not generally known. For this
analysis, EPA assumed that the number of subsistence
fishermen would be an additional 5 percent of the licensed
fishing population.6 That is, after estimating the licensed
fishing population in counties abutting MP&M reaches,
EPA added 5 percent to this value as the estimated number
of subsistence fishermen.
ซ> Estimating th e population fish ing an MP&M reach
EPA assumed that fishing activity among anglers residing
within counties abutting a discharge reach is distributed
evenly among all reach miles within those counties. Thus,
the number of anglers who fish an MP&M reach was
estimated by computing the length of the reach as a
percentage of total reach miles within corresponding
counties and multiplying the estimated ratio by the total
fishing population in counties abutting the reach.
*ป Adjusting for fish advisories
For MP&M reaches where fish advisories are in place
(typically due to non-MP&M regulated pollutants such as
dioxin and mercury), EPA assumed that some proportion of
anglers would adhere to the advisory and not fish those
reaches (U.S. EPA, 1999b). Past studies suggest that
anglers have a high, although not complete, level of
awareness offish advisories. These studies further suggest
that while anglers may change their behavior in response to
fish consumption advisories, they do not necessarily refrain
from fishing in these reaches or consuming fish taken from
reaches under an advisory. For example, studies conducted
by Belton et al (1986), Knuth and Velicer (1990), Silverman
(1990), West et al. (1989), Connelly, Knuth, and Bisogni
(1992), and Connelly and Knuth (1993) indicate that 50 to
87 percent of anglers surveyed were aware of state fish
advisories on water bodies where they fish.
These studies also indicate that only 10 to 34 percent of
anglers who were aware of advisories modified their fishing
behavior in response by no longer fishing a particular
location, changing the location in which they fish, or taking
fewer fishing trips. However, 13 to 68 percent of anglers
who were aware of advisories changed their consumption or
preparation habits in response to advisories. The study by
Knuth and Velicer (1990) also found some confusion among
anglers regarding which waters were under advisory: 37
percent of fishermen actually fishing in waters under
advisory reported that they were fishing in uncontaminated
waters.
On the basis of these data, EPA assumed that recreational
fishing activity would be 20 percent less on reaches subject
to an advisory than would otherwise be estimated. EPA also
assumed that fish advisories do not affect fishing
participation by subsistence anglers; thus, no adjustment was
through fish consumption. This analysis omits this consumption
category and the associated benefit estimate.
6 It is important to estimate recreational and subsistence
populations separately because fish consumption rates for
subsistence anglers are considerably higher than those for
recreational anglers.
13-5
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
made to the estimates of the subsistence fishing population
based on the presence offish advisories.
The assumed 20 percent decrease in recreational fishing
could lead to either an overestimate or underestimate of the
risk associated with consumption of contaminated fish. For
one thing, anglers who change locations may simply be
switching to other locations where advisories are in place
and therefore maintain or increase their current risk. Also,
those who continue to fish contaminated waters may change
their consumption and preparation habits to minimize the
risks.
ซ> Including family members in the exposed population
estimates
EPA assumed that, in addition to anglers themselves,
families of anglers would also consume fish taken from
waters affected by MP&M facility discharges. Therefore,
for each MP&M reach, EPA multiplied the estimated
numbers of recreational and subsistence anglers fishing the
affected reaches by 2.65, the size of the average US
household in 1996 based on Current Population Reports,
(U.S. Bureau of the Census, 1997). These calculations
yielded the household populations of recreational and
subsistence anglers who are estimated to consume fish from
the reach to which the MP&M facility discharges, either
directly or indirectly through a POTW. EPA expects that
family members will benefit from reduced MP&M industry
discharges by consuming fish that has lower levels of
pollutant contamination.
c. Calculating the change in the number of
cancer events in the exposed population
EPA calculated the number of cancer cases associated with
the pollutant discharges (baseline and post-compliance)
from each facility by multiplying the marginal cancer risk
value for the two population classes times the estimated
sizes of the population classes living near the facility. The
product of the marginal risk value and the population size
yields the number of annual cancer events in the given
population class estimated to result from consumption of
fish taken from waterways affected by MP&M pollutant
discharges. Summing the values for the recreational and
subsistence fishing household classes yields the total
number of cancer cases associated with the sample facility
discharges. Because the number of cancer cases apply to
sample facilities, EPA extrapolated the sample results to the
total MP&M population by multiplying the result obtained
for each sample facility by its sample weight and summing
the sample-weighted facility results. The formula follows:
TCCfc =
Wt
- (POP^^ Risk^
(13.2)
where:
TCCfc
Wt,
POP,
i,sprt
POP,
i.sbst
Risk,
.,sprt
Risk,,
Total national estimate of annual cancer
cases associated with consumption of
contaminated fish tissue (baseline or post-
compliance);
Facility sample weight /' (/' = 1 to N
facilities, where N is the number of
facilities in the sample);
Exposed population in recreational fishing
households for the reach to which facility /
discharges (with adjustments as indicated
for the presence of fish consumption
advisories);
Exposed population in subsistence fishing
households for the reach to which facility /
discharges;
Marginal cancer risk from fish
consumption in the recreational fishing
household population associated with
MP&M pollutant discharges from
facility /'; and
Marginal cancer risk from fish
consumption in the subsistence fishing
household population associated with
MP&M pollutant discharges from
facility /'.
These values were calculated for the baseline and post-
compliance discharge cases. The difference is the number of
cancer cases estimated to be avoided annually through the
fish consumption pathway as a result of the proposed
regulation.
13.1.2 Cancer from Drinking Water
Consumption
The analysis of reduced cancer incidence via the drinking
water pathway involves three analytical steps that are largely
parallel to those performed for the fish consumption
pathway:
* estimating cancer risk to an exposed individual
from consumption of contaminated drinking water,
* estimating the population that would benefit, and
13-6
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
* calculating the change in the number of cancer
events in the exposed population.
The major differences in the analysis for the drinking water
pathway involve the identification of the exposed population
and the analysis of pollutant discharge effects in both the
reach to which a facility discharges and reaches downstream
of the discharge point.
a. Estimating cancer risk from drinking
water consumption
Estimating cancer risk from consumption of drinking water
affected by MP&M discharges requires calculating in-
waterway pollutant concentrations in locations where
drinking water treatment systems draw water for public
consumption. This analysis involves three elements:
Estimating in-waterway pollutant concentrations for each
pollutant in the reach to which a facility directly or indirectly
discharges. The method and formulas for this calculation
are identical to those described for the analysis of cancer
effects for the fish consumption pathway.
Estimating the pollutant concentrations over a distance of
500 kilometers downstream from each facility's discharge
reach, using an exponential decay model in which pollution
concentrations diminish below the initial point of discharge
(e.g., dilution, adsorption, partitioning, volatilization, and
hydrolysis). Methods used to calculate downstream
pollutant concentrations are described in more detail in
Appendix G.
Identifying the location of any drinking water intakes in the
initial and downstream reaches where pollutant
concentrations were calculated and assigning pollutant
concentration values to each relevant intake point. The
Water Supply Database (WSDB) file in the Graphical
Exposure Modeling System (GEMS) provided information
on drinking water intakes.
Estimated pollutant concentrations at each drinking water
intake determines cancer risk. EPA assumed drinking water
treatment systems will reduce concentrations to below
adverse effect thresholds for all chemicals for which EPA
has published a drinking water criterion. Therefore,
pollutants examined in the MP&M drinking water analysis
include only six carcinogens for which current drinking
water criteria are not available. See Table 13.1 for a list of
the pollutants, their cancer potency factors, and drinking
water criteria.
The formula for calculating the marginal risk to an
individual resulting from the discharge of a given pollutant
from a given facility at reaches with a known public
drinking water intake is as follows:
Risk =
C x CF1 x CR x EF x ED
BW * LT * CK
SF
(13.3)
where:
Risk
CF,
CR
EF
ED
BW
LT
CF2
SF
Marginal risk of incurring cancer from
drinking water consumption (change in
probability), calculated at each drinking water
intake within 500 km of the initial discharge
point;
pollutant concentration in surface water in the
reach with an intake (ug/1);
conversion factor, micrograms to milligrams
(0.001 mg/ug);
human consumption rate of water (2 I/day);
exposure frequency (365 days/year);
exposure duration (70 years);
human body weight (70 kg);
human lifetime (70 years);
conversion factor (365 days/year); and
pollutant cancer potency factor (mg/kg/day)"1.
The marginal individual risk from each facility's pollutants
are then summed over pollutants at each drinking water
intake to calculate the marginal risk at each intake resulting
from pollutant discharges by each upstream facility. The
findings carried forward to the next step include the
marginal cancer risk for each combination of facility and
associated drinking water intake(s). If the estimated lifetime
individual cancer risk is less than 10"6 under the baseline
discharge levels, then the population served by a given water
intake is excluded from further analysis.
To estimate the annual increased risk of cancer in consumers
served by drinking water intakes affected by MP&M
discharges, the lifetime risk values were then divided by 70
years ( an estimate of lifetime). These values were
calculated for both the baseline and post-compliance
discharge cases.
b. Estimating the benefiting population
The exposed population for each combination of discharging
facility and drinking water intake is the general population
served by the drinking water system for which the drinking
water intake was identified. The WSDB file in GEMS
provided populations served by drinking water intakes (U.S.
EPA, 1999c).
c. Calculating the changes in the number of
cancer events
EPA calculated the number of cancer cases for baseline and
post-compliance pollutant discharges for each combination
of facility and affected drinking water intake by multiplying
the marginal cancer risk value times the population served
by the water system drawing water at the drinking water
13-7
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
intake.
The total number of cancer cases associated with the facility
discharges is the sum of cancer cases over all drinking water
intakes. EPA extrapolated the sample results to the total
MP&M population by multiplying the result for each sample
facility by its sample weight and summing the sample-
weighted facility results. Because marginal cancer effects
are assumed to be linearly additive, cancer-risk effects are
aggregated over facilities and drinking water intakes by
simple addition of the effects calculated separately for each
combination of facility and drinking water intake. The
formula follows:
where:
TCCdw =
POP,
Risky =
N
ฃ
Wt.
M
ฃ
(POP,
R^SklJ)
(13.4)
Total national estimate of cancer cases
associated with consumption of chemically-
contaminated drinking water (baseline or post-
compliance);
Facility sample weight /' (/' = 1 to N facilities)
Population exposed to discharges by facility i
at drinking water intake j (J = 1 to M water
supply intakes); and
Marginal cancer risk for discharges by facility /'
at drinking water intake y.
EPA calculated these values for the baseline and post-
compliance discharge cases. The difference in the values is
the number of drinking water associated cancer cases
estimated to be avoided annually by reduced MP&M
industry discharges.
13.1.3 Exposures above Systemic
Health Thresholds
Exposed populations are also at risk of developing non-
cancer, systemic health problems (including reproductive,
immunological, neurological, or circulatory problems) from
fish ingestion and water consumption. Benefits from
reduced systemic risks, other than lead, cannot be
monetized.
The analysis of systemic health effects compares pollutant
ingestion rates from fish consumption and drinking water
pathways with the RfD for each pollutant. This analysis is
done for discharges from all sample facilities, but is not
performed at the national level because of analytical issues
associated with extrapolation of threshold-based effects.
The RfD of a pollutant is an estimate of the maximum daily
ingestion that is likely to be without an appreciable risk of
deleterious effects during a lifetime. RfDs are available for
77 of the 132 MP&M pollutants of concern. The pollutants
analyzed and their RfDs are listed in Table 13.2.
Table 13.2: RfDs for MP&M Pollutants
CAS j RfD! Drinking Water!
Number ! Regulated Pollutant (mg/kg/day)j Criterion?3 ! Target Organ and Effects
83329 JAcenaphthene
67641 1 Acetone
98862 iAcetophenone
107028 iAcrolein
7429905 'Aluminum
120127 1 Anthracene
7440360 'Antimony
7440382 'Arsenic
7440393 'Barium
65850 iBenzoic acid
100516 1 Benzyl alcohol
7440417 1 Beryllium
92524 'Biphenyl
JBis(2-ethylhexyl)
117817 iphthalate
7440428 1 Boron
85687 1 Butyl benzyl phthalate
7440439 iCadmium
0.060!
0.100!
0.100!
0.020!
1.000!
0.300!
0.000!
0.000!
0.070!
4.000!
0.300!
0.002!
0.050!
0.020!
0.090!
0.200!
O.OOl!
No
No
No
No
Yes
No
Yes
Yes
Yes
No
No
Yes
No
Yes
No
No
Yes
i Liver toxicity
i Increased liver and kidney weights^ nephro toxicity
i General toxicity
i Cardiovascular toxicityb
1 Renal failure, intestinal contraction interference,
i neurological effects0
:Longevity: blood glucose: cholesterol
adverse
jHyperpigmentation, keratosis and possible vascular
i complications
i Increased kidney weight
iForestomach, epithelial hyperplasia
i Small intestinal lesions
i Kidney damage
i Increased relative liver weight
iTesticular atrophy, spermatogenic arrest
1 Significantly increased liver-to-body weight and liver-to-brain
i weight ratios
i Significant proteinuria (protein in urine)
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
Table 13.2: RfDs for MP&M Pollutants
CAS I RfD! Drinking Water!
Number ! Regulated Pollutant (mg/kg/day)j Criterion?3 ! Target Organ and Effects
75 1 50 ! Carbon disulfide
108907 iChlorobenzene
75003 iChloroethane
7440473 ! Chromium
18540299 ! Chromium hexavalent
7440484 ! Cobalt
7440508 ! Copper
95487 iCresol, o-
106445 iCresol.p-
57125 ! Cyanide
75354 JDichloroethene, 1,1-
75092 iDichloromethane
60297 IDiethyl ether
1 Dimethy Iformamide,
68122 !N:N-
1 05679 ! Dimethy Iphenol, 2,4-
84742 !Di-n-butylphthalate
51285 JDinitrophenol, 2,4-
606202 !Dinitrotoluene:2:6-
1 1 7840 ! Di-n-octyl phthalate
122394 iDiphenylamine
100414 iEthylbenzene
206440 JFluoranthene
86737 JFluorene
16984488 'Fluoride
591786 !Hexanone:2-
7439896 llron
78831 ilsobutyl alcohol
78591 !Iso_phorone
7439965 iManganese
78933 'Methyl ethyl ketone
108101 ! Methyl isobutyl ketone
80626 ! Methyl methacrylate
91576 iMethylnaphthalene, 2-
7439987 [Molybdenum
91203 'Naphthalene
7440020 'Nickel
100027 'NitrophenoL 4-
59507 iParachlorometacresol
0.100!
0.020!
0.400!
1.500!
0.003!
0.060!
0.040!
0.050!
0.005!
0.020!
0.009!
0.060!
0.200!
0.100!
0.020!
0.100!
0.002!
0.001!
0.020!
0.025!
o.ioo!
0.040!
0.040!
0.060!
0.040!
0.300!
0.300!
0.200!
0.140!
0.600!
o.oso!
1.400!
0.020!
0.005!
0.020!
0.020!
0.008!
2.000!
No
No
No
Yes
Yes
No
Yes
No
No
Yes
Yes
Yes
No
No
No
No
No
No
No
No
Yes
No
No
Yes
No
Yes
No
No
Yes
No
No
No
No
No
No
Yes
No
No
! Fetal toxicitVj malformations
iHistopatho logic changes in liver
iRenal tubular necrosis (kidney tissue decay)0
! Reduced water consumption
I Heart effects0
! Gastrointestinal effects, liver necrosis0
! Decreased body weights and neurotoxicity.
1 Central nervous system hypoactivity and respiratory system
! distress
iWeight loss; thyroid effects and myelin degeneration
! Toxic effects on kidney s., spleen^ lungs0; hepatic lesions
! Liver toxicity
! Depressed body weights
iLiver and gastrointestinal system effects
1 Clinical signs (lethargy, prostration, and ataxia) and
ihematological changes
! Increased mortality
! Cataract formation
Mortality, central nervous system neurotoxicity, blood heinz
1 bodies and methemoglobinemia, bile duct hyperplasia, kidney
ihistopathology
1 Kidney and liver increased weights, liver increased SGOT and
I SGPT activity
! Decreased body weight1 and increased liver and kidney weights
iLiver and kidney toxicity
jNephropathy, increased liver weights, hematological
! alterations; clinical effects
1 Decreased red blood cell count, packed cell volume and
! hemoglobin
! Objectionable dental fluorosis (.soft, mottled teeth)
iHypatotoxicity and nephrotoxcityd
1 Liver, diabetes mellitus, endocrine disturbance, and
! cardiovascular effects4
! Hypoactivity and ataxia
! Kidney pathology
! Central nervous system effects
! Decreased fetal birth weight
jLethargy, increased liver and kidney weights and urinary
! protein
! Increased kidney to body weight ratio
! Increased uric acid
! Decreased body weight
! Decreased body and organ weights
I
13-9
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
Table 13.2: RfDs for MP&M Pollutants
CAS I RfD| Drinking Water!
Number ! Regulated Pollutant (mg/kg/day)j Criterion?3 ! Target Organ and Effects
108952 ! Phenol
7723140 ! Phosphorus (elemental)
129000 IPyrene
110861 IPyridine
7782492 ! Selenium
7440224 ! Silver
100425 IStyrene
127184 iTetrachloroethene
7440280 ! Thallium
7440315 ITin
7440326 ! Titanium
108883 ! Toluene
79016 iTrichloroethene
75694 iTrichlorofluoromethane
67663 iTrichloromethane
7440622 ! Vanadium
108383 IXylenesm-
17960123llXylenes m- &p-*
95476 IXylene, o-
136777612lXyleneso-&p-*
7440666 IZinc
137304 iziram \ Cvmate ^^
0.600!
0.000!
0.030!
o.ooi!
o.oos!
0.005!
0.200!
agio!
o.ooo!
0.600!
4.000!
0.200!
0.006!
0.300!
agio!
0.007!
2.000!
2.000!
2.000!
2.000!
0.300!
0.020!
No
No
No
No
Yes
Yes
Yes
Yes
Yes
No
No
Yes
Yes
No
Yes
No
Yes
Yes
Yes
Yes
Yes
No
i Reduced fetal body weight in rats
iParturition mortality; forelimb hair loss
i Kidney effects (renal tubular pathology, decreased kidney
i weights)
i Increased liver weight
i Clinical selenosis (hair or nail loss)
iArgyria (skin discoloration)
iRed blood cell and liver effects
i Liver toxicity, weight gain
i Liver toxicity, gastroenteritis,degeneration of peripheral and
i central nervous system*
i Kidney and liver lesions
i Changes in liver and kidney weights
iBone marrow^ central nervous system^ liver^ kidneys4
i Survival and histopathology
i Fatty cyst formation in liver
i Kidney and central nervous system effects*
I Central nervous system hyperactivity, decreased body
i Central nervous system hyperactivity, decreased body
weight
weight
J47% decrease in erythrocyte superoxide dismutase (ESOD)
i concentration in adult human females after 10 weeks of zinc
i expo sure
a. "Yes"= there is a published drinking water criterion for a given chemical.
b. Reference dose based on a no observed adverse effect level (NOAEL). Health effects summarized from Amdur, M.O.; Doul, J.; and Klaassen,
C.D.,eds. 1991. Cassarett and Doul's Toxicology, 4th edition.
c. Target organ and effects summarized from Wexler, P., ed. 1998. Encyclopedia of Toxicology, Volumes 1-3.
d. Target organ and effects summarized from Klaassen, C.D., ed.. 1996. Cassarett and Doul's Toxicology, 5th edition.
Source: U.S. EPA (1998/99); U.S. EPA (1997a).
This analysis used the hazard ratio as a systemic health
effect indicator. The hazard ratio is calculated for each
discharge reach associated with one or more MP&M sample
facilities by dividing the estimated ingestion rate of each
pollutant by the RfD value for the pollutant and summing
these ratios over pollutants. The higher the hazard score
value, the greater the risk to individuals of experiencing
adverse systemic health effects.
A hazard ratio greater than 1 indicates that individuals may
ingest MP&M pollutants at rates sufficient to pose a
significant risk of systemic health. The formula follows:
HR =
DCR
(13.5)
where:
HR
DCRV =
RfTX
hazard ratio for the pollutants discharged from
a facility and ingested by a specific
consumption pathway;
estimated daily consumption rate per kilogram
of body mass for pollutant k via a specific
consumption pathway (mg/kg/day); and
Reference dose for pollutant k (mg/kg/day).
These hazard ratios are calculated separately for the fish and
water consumption pathways, and separately for recreational
13-10
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
and subsistence fish consumption rates. The procedures and
formulas for estimating the in-waterway concentrations and
ingestion of pollutants by exposed populations are the same
as those used for the fish consumption and drinking water
cancer analyses. The only exception is that the analysis of
systemic health pathways was performed for the discharge
reach only and not for reaches downstream, due to time and
resource constraints. As a result, this analysis will likely
understate populations exposed to non-cancer systemic risks
via drinking water pathways.
EPA assumed that the combined effect of ingesting multiple
pollutants is proportional to the sum of their effects
individually. Thus, a cumulative hazard ratio applicable to
all pollutants with RfD values for each combination of
discharge reach and consumption pathway is calculated by
summing across the pollutants discharged to each reach. For
example, for three MP&M pollutants discharged from a
facility (pollutant A with a hazard ratio of 0.10, pollutant B
with a hazard ratio of 0.05, and pollutant C with a hazard
ratio of 0.15), the combined hazard ratio is 0.30.
Distributions of these systemic health hazard ratios were
calculated for the baseline and post-compliance discharge
cases. The change in hazard ratio value distributions over
the populations exposed to MP&M pollutants from the
discharges of MP&M sample facilities is a measure of
systemic health benefits from the proposed regulation. The
basis for identifying exposed populations is the same as that
described for the analysis of reduced incidence of cancer via
the fish consumption and drinking water consumption
pathways.7 Thus, the hazard ratio values calculated in this
analysis can be linked to specific exposed population
estimates. The shift in populations from a higher to a lower
hazard ratio value from the baseline to post-compliance
cases is the quantitative measure of benefits from this
analysis.
This analysis considers contributions to systemic risk
resulting only from MP&M facility discharges, and does not
take into account other sources of exposure to MP&M
pollutants, or other chemicals that may contribute to an
aggregate risk of systemic health hazard. The hazard ratios
calculated for a given population are therefore likely to be
systematically biased downwards. The net result is that the
analysis understates the numerical value estimated for
hazard ratios, but the marginal change in hazard ratios
between the baseline and the proposed option would remain
the same. EPA therefore evaluated potential marginal
changes in systemic health risks over the entire distribution
of hazard ratios, including hazard ratios below one. EPA
did not monetize these benefits.
The results from the systemic health risk analysis apply to
sample discharge locations only. Analytic tractability issues
prevented this analysis from being conducted on a sample-
weighted national basis.
13.1.4 Human Health AWQC
EPA used another approach to quantify reductions in health
risk from the proposed MP&M regulation, based on the
extent to which reduced MP&M discharges would decrease
the occurrence of pollutant concentrations in affected
waterways that exceed human health-based AWQC. This
analysis provides a measure of the change in cancer and
systemic health risk by comparing the number of discharge
reaches exceeding health-based AWQC for regulated
pollutants due to MP&M activities in the baseline to the
number exceeding AWQC under the proposed option.
AWQC are set at levels to protect human health through
ingestion of aquatic organisms and ingestion of water and
aquatic organisms. Accordingly, reducing the frequency at
which human health-based AWQC are exceeded should
translate into reduced risk to human health. This measure
should be viewed as an indirect indicator of reduced risk to
human health, because it does not reflect the size of the
exposed population and is not tied to changes in human
health riskier ses
EPA estimated the baseline concentrations of all MP&M
pollutants for each reach to which one or more MP&M
facilities discharge. The calculation of concentrations used
the same in-waterway dilution and mixing model described
in the analysis of cancer risk for the fish consumption
pathway. The baseline concentrations were compared with
human health-based AWQC values. (See Table 13.3 for a
list of MP&M pollutants with AWQC values.) Reaches in
which concentrations of one or more pollutants were
estimated to exceed an AWQC value were identified as
exceeding AWQC limits in the baseline.
This analysis was repeated using the post-compliance
discharge values for the proposed option. Reaches
estimated to have concentrations in excess of AWQC in the
baseline but not in the post-compliance case were assessed
as having substantial water quality improvements relative to
human health-based criteria as a result of regulation. EPA
deems such water quality improvements to be indicative of
reduced risk to human health. Although not explicitly
accounted for in this analysis, human health risk reductions
are also likely to occur wherever in-waterway concentrations
are reduced, regardless of whether or not they are reduced to
levels below AWQC.
7 The exposed populations for the drinking water
consumption pathway are those associated with drinking water
intakes only in a facility's discharge reach.
8 The following chapter uses this same information in part as
a direct indicator of improved water quality.
13-11
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
Table 13.3: MP&M Pollutants with Human Health-Based AWQC
Human Health-Based j
! AWQC (ug/1)
CAS j
Number Pollutant
83329 JAcenaphthene
67641 I Acetone
98862 jAcetophenone
107028 JAcrolein
7429905 JAluminum
62533 JAniline
120127 I Anthracene
7440360 JAntimony
7440382 JArsenic
7440393 JBarium
65850 iBenzoic acid
100516 I Benzyl alcohol
7440417 I Beryllium
92524 JBiphenyl
117817 1 Bis(2-ethylhexyl)
jphthalate
85687 I Butyl benzyl phthalate
7440439 jCadmium
75 1 50 I Carbon disulfide
108907 jChlorobenzene
75003 jChloroethane
18540299 I Chromium hexavalent
7440473 I Chromium
7440508 I Copper
106445 jCresol, p-
95487 iCresol, o-
57125 jCyanide
1 1 7840 1 Di-n-octyl phthalate
84742 JDi-n-butyl phthalate
75354 JDichloroethene, 1,1-
75092 iDichloromethane
60297 JDiethyl ether
131113 I Dimethyl phthalate
68122 !Dimethylformamide,N,N-
105679 JDimethylphenol, 2,4-
51285 JDinitrophenol, 2,4-
606202 JDinitrotoluene, 2,6-
Organisms | Water & \
Only i Organisms i Target Organ and Effects3
2700!
2800000!
98000!
1000!
47000 1
95!
6800!
4300!
0.16!
i
2900000!
810000!
1100!
1200!
5.9J
5200 1
84!
94000!
21000!
520!
2000!
1000000!
1200!
3100!
30000!
220000!
39J
12000!
3.2!
1600!
770000!
2900000!
220000000!
2300 !
14000!
900 1
1200! Liver, hepatotoxicity
3500!Increased liver and kidney weights; nephrotoxicity
3400 ! General toxicity
410! Cardiovascular toxicity0
20000J Renal failure, intestinal contraction interference, adverse neurolo^
! effects4
5.8! Spleen and body cavity
4 100! No observed effects
14!Longevity, blood glucose, cholesterol
0.02! Liver, kidneys, lungs, bladder and skin
1000! Increased kidney weight
1 30000 !No observed adverse effects
lOOOOjForestomach, epithelial hyperplasia
66 ! Small intestinal lesions
720! Kidney damage
1.8 1 Liver
>ical
3000 i Significantly increased liver-to-body weight and liver-to-brain weight
! ratios
14 ! Significant proteinuria (protein in urine)
3400! Fetal toxicity, malformations
680!Histopathologic changes in liver
12!
100! Reduced water consumption
50000! Renal tubular necrosis (kidney tissue decay)4
650! Gastrointestinal effects, liver necrosis4
170! Central nervous system hypoactivity and respiratory system distress
1700! Decreased body weights and neuro toxicity.
700! Weight loss, thyroid effects and myelin degeneration
37 i Kidney and liver increased weights, liver increased SGOT and SGPT
! activity
2700 ! Increased mortality
0.057! Inconclusive
4. 7! Liver, lungs
6900! Depressed body weights
310000!
3500!Liver and gastrointestinal system effects
540 1 Clinical signs (lethargy, prostration, and ataxia) and hematological
! changes
70 ! Cataract formation
34 1 Mortality, central nervous system neuro toxicity, blood heinz bodies
I and methemoglobinemia, bile duct hyperplasia, kidney
jhistopathology
13-12
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
CAS
Number
123911
122394
100414
206440
86737
591786
7439896
78831
78591
7439965
7439976
80626
78933
108101
91576
91203
7440020
100027
62759
86306
59507
108952
7723140
129000
110861
7782492
7440224
100425
127184
7440280
108883
79016
75694
67663
108383
136777612
95476
179601231
7440666
Table 13.
Pollutant
iDioxane, 1,4-
iDiphenylamine
jEthylbenzene
jFluoranthene
jFluorene
jHexanone, 2-
jlron
i Isobutyl alcohol
ilsophorone
i Manganese
i Mercury
i Methyl methacrylate
i Methyl ethyl ketone
i Methyl isobutyl ketone
jMethylnaphthalene, 2-
i Naphthalene
JNickel
iNitrophenol, 4-
iNitrosodimethylamine, N-
iNitrosodiphenylamine, N-
i Parachlorometacresol
I Phenol
i Phosphorus (elemental)
iPyrene
iPyridine
i Selenium
I Silver
i Styrene
i Tetrachloroethene
1 Thallium
i Toluene
iTrichloroethene
i Trichlorofluoromethane
i Trichloromethane
iXylene, m-
iXylene, o- & p- (c)
iXylene, o-
iXylene, m- & p- (c)
jZinc
3: MP&M Pollutants with Human Health-Based AWQC
Human Health-Based
AWQC (us/I)
Organisms j Water &
Only: Organisms
2400 1
1000 1
29000 1
370 !
14000 1
65000 1
1500000 1
2600 1
loo!
0.051 1
2300000 1
6500000 1
360000 1
84 1
21000J
4600 1
nooi
8.1J
16J
270000 1
4600000 1
2.2 !
290 1
5400 1
11000 1
11 0000 1
160000 1
3500 1
6.5J
200000J
92 1
66000 1
470 1
100000 1
100000 1
100000 1
100000 1
69000 !
3.2
470
3100
300
1300
1400
300
10000
36
50
0.05
48000
21000
2800
75
680
610
220
0.00069
5
56000
21000
0.53
230
35
170
170
6700
320
1.8
6800
3.1
9100
5.7
42000
42000
42000
42000
9100
i Target Organ and Effects3
i Liver, nasal cavity, gall bladder
i Decreased body weight gain, and increased liver and kidney weights
i Liver and kidney toxicity
jNephropathy, increased liver weights, hematological alterations,
i clinical effects
i Decreased red blood cell count, packed cell volume and hemoglobin
iHypato toxicity and nephrotoxcityb
1 Liver, diabetes mellitus, endocrine disturbance, and cardiovascular
i effects0
iHypoactivity and ataxia
iPreputial gland
i Central nervous system effects
I
i Increased kidney to body weight ratio
i Decreased fetal birth weight
i Lethargy, increased liver and kidney weights and urinary protein
I
i Decreased body weight
i Decreased body and organ weights
I
i Tumors observed at multiple sites
i Bladder tumors, reticulum cell sarcomas
I
i Reduced fetal body weight in rats
i Parturition mortality; forelimb hair loss
i Kidney effects (renal tubular pathology, decreased kidney weights)
i Increased liver weight
i Clinical selenosis (hair or nail loss)
i Argyria (skin discoloration)
iRed blood cell and liver effects
i Liver toxicity, weight gain
1 Liver toxicity, gastroenteritis,degeneration of peripheral and central
i nervous system
i Changes in liver and kidney weights
I
i Survival and histopathology
i Kidneys
i Central nervous system hyperactivity, decreased body weight
I
i Central nervous system hyperactivity, decreased body weight
I
|47% decrease in erythrocyte superoxide dismutase (ESOD)
i concentration in adult human females after 10 weeks of zinc exposure
13-13
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
Table 13.3: MP&M Pollutants with Human Health-Based
CAS
Number Pollutant
137304 Ziram \ Cymate
Human Health-Based j
AWQC (ug/1) 1
Organisms j Water & \
Only Organisms Target Organ and Effects3
AWQC
220000000J 700 1
a. Information on target organs are not available for some pollutants.
b. Reference dose based on a NOAEL. Health effects summarized from Amdur, M.O.; Doul, J.; and Klaassen, C.D.,eds. 1991. Cassarett andDouVs
Toxicology, 4th edition/
c. Target organ and effects summarized from Klaassen, C.D., ed. 1996. Cassarett and DouV s Toxicology, 5th edition.
d. Target organ and effects summarized from Wexler, P., ed. 1998. Encyclopedia of Toxicology, Volumes 1-3.
Source: U.S. EPA (1980); U.S. EPA (1997a); U.S. EPA (1998/99).
EPA estimated the occurrence of pollutant concentrations in
excess of AWQC on the basis of sample facility data. The
findings from the sample facility analyses were extrapolated
to national estimates using facility sample weights that
capture the effect of multiple dischargers to the same reach
in calculating whether pollutant concentrations would
exceed AWQC. As a result, it was necessary to use an
alternative weighting method to scale sample facility results
to national estimates (see Appendix F).
13.2 RESULTS
EPA estimated the monetary value to society associated with
reduced cancer risk from consumption offish and drinking
water affected by MP&M pollutant discharges. Little
information is available about dose-response relationships
for non-cancer systemic health outcomes or about the
monetary value of avoiding such health outcomes. As a
result, EPA was unable to assign monetary values to the
estimated reductions in systemic health risks. Such systemic
health risks include reproductive, immunological,
neurological, and circulatory problems. Although EPA was
unable to assign monetary values to the latter two benefit
measures for this regulation, the quantitative analyses of
these events provide additional insight into the human
health-related benefits likely to result from the proposed
regulation.
The following sections present the findings from the
analysis of each of the benefit measures.
13.2.1 Fish Consumption Cancer Results
Table 13.4 shows the number of cancer cases avoided by the
proposed option through both the fish consumption and
drinking water pathways. For combined recreational and
subsistence angler populations, EPA estimates that the
proposed option will eliminate approximately 0.045 cancer
cases per year from a baseline value of about 0.126 cases,
representing a reduction of 35.7 percent.
13-14
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
Table 13.4
Value of An
CAS # I Chemical
62533 ! Aniline
62759 j Nitrosodimethyl-
i amine: N-
67663 ! Trichloromethane
75003 ! Chloroethane
75092 ! Dichloromethane
75354 j Dichloroethene,
! 1,1-
78591 ! Isophorone
79016 ! Trichloroethene
86306 i Nitrosodiphenyl-
! amine: N-
117817 I Bis(2-ethylhexyl)
i phthalate
123911 !Dioxanesls4-
127184 ! Tetrachloroethene
7440382 ! Arsenic
Drinking Water
Criterion?
yes
yes
yes
yes
yes
yes
yes
Total Benefits
Estimated Avoided Cancer Cases and
nual Benefits for the Proposed Option
Fish Consumption Drinking Water
Avoided Cancer
Cases per Year
0.000033
0.010005
0.000014
-0.000003
0.000005
0.001417
-0.000004
0.00006
0.000619
0.018175
-0.000004
0.000804
0.014102
0.045223
Mean Value of j
Benefit j Avoided Cancer
(Thousand 1997$) ! Cases per Year a
0.19! 0.00001
58.03J 2.24217
0.08!
-0.02! 0.00001
0.03!
8.22J
-0.02! 0.00000
0.35!
3.59J 0.00002
105.41J
-0.02! 0.0008
4.67!
81.79!
262.3! 2.24301
Mean Value of
Benefit"
(Thousand 1997$)
0.03
13004.61
0.072
0.022
0.13
4.63
13009.49
a. Avoided cancer cases via the drinking water consumption pathway were not included for pollutants with drinking water criteria. EPA has published a
drinking water criterion for seven of the 13 carcinogens and it is assumed that drinking water treatment systems will reduce concentrations of these
chemicals to below adverse effect thresholds.
b. Estimated value of one avoided cancer case ($1997): $5.8 million
Source: U.S. EPA analysis.
The valuation of benefits is based on estimates of society's
willingness-to-pay to avoid the risk of cancer-related
premature mortality. Although it is not certain that all
cancer cases will result in death, avoided cancer cases are
valued on the basis of avoided mortality to provide a
conservative estimate of benefits.
In this analysis, EPA used the $5.8 million estimate of the
value of a statistical life sayed(VSL) recommended in
the Draft Guidelines for Preparing Economic Analysis
(EPA, 1999a).9 EPA based this value on its review and
analysis of 26 policy-relevant value of life studies (EPA,
1997b). The reviewed studies used hedonic wage and
contingent valuation analyses in labor markets to estimate
the amounts that individuals would either be willing to pay
to avoid slight increases in the risk of mortality, or would
need to be compensated to accept a slight increase in risk of
9 The value of a statistical life saved is given in 1997$ (U.S.
EPA, 1999a). This underestimates benefits from the proposed
regulation. The benefits analysis for promulgation of the MP&M
regulation will adjust this value to 1999$.
mortality.10 EPA associated the willingness to pay
(WTP) values estimated in these studies with small changes
in the probability of mortality. To estimate a WTP value for
avoiding certain or high probability mortality events, EPA
extrapolated the smaller value to that for a 100 percent
probability event.11 The Agency used the resulting estimates
of the value of a "statistical life saved" in regulatory
analyses to value regulatory effects that are expected to
reduce the incidence of mortality.
EPA estimated that the monetary benefits of reduced cancer
cases from fish consumption for the proposed option is $0.3
million (1997$) per year (see Table 13.4).
10 The question analyzed in these studies is: how much more
must a worker be paid to accept an occupation with a slightly
higher risk of mortality?
11 These estimates, however, do not represent the willingness-
to-pay to avoid the certainty of death.
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
13.2.2 Drinking Water Consumption
Cancer Results
Table 13.4 also shows the number of cancer cases estimated
to be avoided for each pollutant analyzed for drinking water
populations. EPA estimated that the proposed option would
eliminate approximately 2.24 cancer cases per year from a
baseline value of about 5.10 cases, representing a reduction
of about 44 percent. Annual monetary benefits from
reduced cancer risk for the proposed regulation are
estimated at $13.0 million (1997$) peryear.
As noted in the preceding sections, EPA has established
drinking water criteria for seven carcinogens. EPA assumes
that public drinking water treatment systems will reduce
these seven pollutants in the public water supply to levels
that are protective of human health. To the extent that the
proposed regulation reduces the concentration of MP&M
pollutants to values that are below pollutant-specific
drinking water criteria, public drinking water systems will
accrue benefits in the form of reduced water treatment costs.
EPA was not able to quantify such cost savings at the
national level, however.
13.2.3 Systemic Health Threshold
Results
Table 13.5 summarizes baseline and post-compliance
distributions of systemic health hazard ratios and associated
population estimates for each exposed population group for
the proposed option. The shift in populations from higher to
lower hazard score values between the baseline and post-
compliance cases is the measure of benefit from reduced
systemic health hazards.
Table 13.5:
Change in Risk of Systemic Health Hazards from Reduced Exposure to MP&M Pollutants
Distribution of Hazard Ratios"
Fish Consumption
Range of
Ratios
Ratio = 0.00
0.00 - ID'6
io-6 - io-3
io-3-i.oo
Score > 1.00
Totals
Baseline
Population!
o!
1,528,589!
3,392,567!
1,789,550!
16,736!
6,727,4421
Percent !
o%!
22.7%!
50.4%!
26.6%!
0.3%!
100%;
Proposed
Population
385,726
1,564,130
3,425,711
1,346,623
5,252
6,727,442
Option !
Percent!
5.8%;
; 23.2%;
; so.9%;
20.0%;
o.i%!
100!
Drinking Water Consumption
Baseline
Population!
68,000!
73,050,966!
6,871,399!
o!
0!
79,990,3651
!
Percent!
0.1%;
91.3%;
8.6%;
U /oi
U /O;
loo!
Proposed
Population i
11,074,668!
62,138,353!
6,777,344 !
o!
oj
79,990,365 I
Option
Percent
13.9%
77.7%
8.5%
0%
0%
100%
a. This analysis addresses only 77 of 132 chemicals of concern, excludes background exposures, and is based only on sample facility discharges and
associated populations. The exposed population values are not national estimates of the populations that would benefit by reduced risk of systemic
health hazard.
Source: U.S. EPA analysis.
Table 13.5 shows that the proposed option would shift
substantial numbers of exposed population from higher to
lower hazard ratio values. In particular, the population with
a zero marginal risk of systemic health hazard increases
substantially. For example, under baseline discharge
conditions, no fishermen and 0.1 percent of individuals
served by drinking water intakes are associated with hazard
ratio values equal to zero. The percent of the population
with zero marginal risk values increases to 5.8 percent for
fishermen and 13.9 percent for individuals exposed to
affected drinking water under the proposed option.
However, the marginal risk of systemic health hazard from
pollutants discharged by MP&M facilities for which
reference exposure values are available is generally quite
low. For example, analysis of the in-waterway pollutant
concentration data suggests that hazard ratios (based on both
the fish consumption and drinking water pathways) for at
least 99 percent of the population associated with sample
facilities equals less than one in the baseline. These values
do not consider background concentrations of MP&M or
other pollutants or contributions to risk from MP&M
pollutants for which reference exposure values are not
available. Whether the marginal shifts in hazard ratio
values are significant in reducing absolute systemic health
risks is therefore uncertain, and will depend on the
magnitude of pollutant exposures for a given population
from sources that are not accounted for in this analysis.
Although EPA was unable to associate an economic value
with changes in the number of individuals exposed to
pollutant levels likely to result in systemic health effects, the
reductions in health risk indicated by this benefit measure
further indicate that the proposed regulation can be expected
to yield human health benefits.
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
13.2.4 Human Health AWQC Results
The final human health benefit category is the reduced
occurrence of pollutant concentrations that are estimated to
exceed human health-based AWQC. This analysis provides
an alternative measure of the expected reduction in risk to
human health. Baseline in-waterway concentrations of
MP&M pollutants are estimated to exceed AWQC limits for
human health from consumption of water or organisms in
10,310 reaches. As shown in Table 13.6, EPA estimates
that the proposed option would reduce the occurrence of
concentrations in excess of human health AWQC limits.
The proposed option would eliminate exceedances of either
human health or aquatic life-based AWQC in 1,105 (10.72
percent) of those reaches. In addition, the proposed option
would eliminate concentrations in excess of AWQC values
for human health, consumption of organisms only, on 121 of
the 192 reaches on which baseline discharges are estimated
to cause concentrations in excess of the AWQC values.
Note that the findings from the analysis of AWQC values
for human health, consumption of organisms only, are a
subset of the findings for the analysis relative to AWQC
limits for human health from consumption of water or
organisms. Results also show that 382 receiving reaches
will experience partial water quality improvements from
reduced occurrence of some pollutant concentrations in
excess of AWQC limits for consumption of water and
organisms.
Table 13.6: MP&M Discharge Reaches with Pollutant Concentrations Exceeding Human
Health -Based AWQC Limits and Reductions Achieved by the Proposed Option
Baseline
Proposed Option
Percent Reduction
Number of Reaches with Concentrations Exceeding Health-Based AWQC
# Pollutants
(H20, Org.)
19
11
Human Health,
Consumption of Water
and Organisms
10,310
9,205
10.72%
# Pollutants
(Org. only)
6
5
Human Health,
Consumption of
Organisms Only
192
71
63.02%
Source: U.S. EPA analysis.
13.3 LIMITATIONS ANO
UNCERTAINTIES
This section discusses limitations and uncertainties in the
human health benefits analysis. The analysis does not
include all possible human health benefits, and therefore
does not provide a comprehensive estimate of the total
human health benefits associated with the proposed rule.
Quantification of changes in human health risk described in
this chapter are not possible for all pollutants whose
discharges will be reduced by the proposed regulation. Due
to current research limitations, cancer potency factors,
reference doses, and AWQC are not available for 6 metals,
27 organics, 8 nonconventional pollutants, and 3
conventional pollutants. The methodologies used also
involve significant simplifications and uncertainties, as
described below. Whether these simplifications and
uncertainties, taken together, are likely to lead to an
understatement or overstatement of the estimated economic
values/or the human health benefits that were analyzed is
not known.
13.3.1 Sample Design & Analysis of
Benefits by Location of Occurrence
The MP&M industries are estimated to include over 62,752
facilities nationwide that generate wastewater while
processing metal parts, metal products, and machinery.
Many of these facilities are quite small and, individually,
discharge relatively small quantities of pollutants. Most
individual facilities are not likely to have a significant
adverse impact on human health at any one MP&M reach.
The industry discharges a significant quantity of pollutants in
the aggregate, however, because of the large number of
facilities. Thus, the combined effect of discharges from
several facilities at a given reach may well result in
appreciable risks to human health. Multiple dischargers
affecting a single reach were found to be common, based on
the sample facility data.
The sample of MP&M facilities on which this analysis is
based (885 facilities) represents only approximately 1.5
percent of MP&M facilities nationwide. This sample was
based on basic industry characteristics rather than geographic
location. As a result, the sample does not accurately reflect
the likelihood of co-occurrence of MP&M facilities on a
reach and, therefore, the contribution to in-waterway
13-17
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
pollutant concentrations made by multiple facilities. For
example, the sample may include three MP&M facilities, all
discharging to the same reach. In reality, however, five
MP&M facilities might discharge to this reach.
The omission of co-occurrence of discharges from
additional facilities does not create a problem in the analysis
of marginal cancer risk, because each facility's contribution
to total risk can be estimated separately and is assumed be
linearly additive. The cancer effects associated with
individual facility discharges can be summed over facilities
to estimate occurrence of cancer events in the total
population. Therefore, the application of sample weights in
the cancer analysis accounts for pollutant contributions
from facilities co-occurring on MP&M reaches that are not
present in the sample of facilities.
This omission does present a problem, however, when
analyzing changes in hazard ratios and changes in in-
waterway pollutant concentrations relative to human health-
based AWQC for reaches to which more than one facility
discharge. For these reaches, changes in hazard ratios and
in-waterway pollutant concentrations from reduced
pollutant discharges should account for the total discharge
of pollutants over the several facilities whose discharges
may affect the reach. When facilities whose discharges to
the reach have unequal sample weights, however, results
from the sample facility analysis cannot be extrapolated to
the population simply by multiplying estimated benefit
values by the sum of the sample weights of the individual
facilities. See Appendix F for an explanation of the sample
weighting methodology devised to partially address this
problem.
While this weighting methodology does recognize the
contributions of facilities with different sample facility
weights to aggregate results, it still does not account for the
contributions made by co-occurring facilities not included in
the sample. The omission of the frequency of true multiple
discharger effects on aggregate instream concentrations and
pollutant exposures understate the benefits.
13.3.2 In-Waterway Concentrations of
MP&M Pollutants
Human health benefits are based on the estimated changes
in in-waterway concentrations of MP&M pollutants. A
variety of factors affect in-waterway concentrations,
including flow rates under average and low flow conditions,
flow depth, chemistry of the waterway, mixing processes,
longitudinal dispersion, flow geometry, suspension of
solids, and reaction rates. This analysis takes into account
only site-specific variations in flow rates and flow depth.
Standard values are used for other inputs to the water
quality model, due to lack of data on the reaches affected by
sample facility discharges. These standard values may not
be accurate for all the sample facility reaches. In addition,
the flow characteristics of the sample facility reaches may
not be representative of the national distribution of those
characteristics. Extrapolating the sample facility benefits to
national results based on sample facility weights may
therefore introduce distortions. The net effect of these
assumptions and extrapolations on the aggregate benefits
estimates is uncertain.
13.3.3 Joint Effects of Pollutants
The analyses of human health benefits ignore the potential
for joint effects of more than one pollutant. Each pollutant is
dealt with in isolation; the individually estimated effects are
then added together. As such, the analyses do not account
for the possibility that several pollutants may combine to
yield more or less adverse effects to human health than
indicated by the simple sum of the individual effects. The
impact of this limitation on the results of this analysis is
unknown.
13.3.4 Background Concentrations of
MP&M Pollutants
Background concentrations of MP&M pollutants are not
considered in the benefits analysis. Rather, the analysis
assumes that MP&M facilities are the only source of each of
the regulated pollutants in the waterway. Background
contributions, either from other upstream sources or
contaminated sediments from previous discharges, are not
considered. Even if discharges of these contaminants are
reduced or eliminated, sediment contamination and
subsequent accumulation of the regulated pollutants in
aquatic organisms may continue for years.
Excluding background contributions to in-waterway
pollutant concentrations affects the results for systemic risk
and changes in human health-based AWQC exceedances. In
the systemic risk analysis, hazard ratios are likely to be
systematically biased downwards by the omission of
exposures to these chemicals from other water-related and
non-water-related sources.12 The net result is understated
absolute risks of systemic health hazards. Similarly,
reductions in human health-based AWQC exceedances
calculated for a given MP&M reach are likely to be
systematically biased downwards. The analysis is therefore
likely to understate the frequency with which in-waterway
pollutant concentrations move from values exceeding
pollutant specific AWQC to values less than pollutant
specific AWQC as a result of the regulation.
12 Ideally, the analysis would include not only background
concentration and exposure effects from water-related exposures but
would also account for exposures to chemicals by other routes
including, for example: air exposures including dust inhalation, and
food contamination.
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
13.3.5 Downstream Effects
The analysis of cancer effects from drinking water
consumption considered exposures from intakes
downstream of the MP&M discharges. EPA, however, did
not evaluate cancer risk to recreational and subsistence
fishermen fishing downstream reaches, because of resource
constraints. In addition, due to differential weighting of
sample facility results, it was not possible to evaluate hazard
ratios indicating non-cancer systemic health hazards or
human health-based AWQC excursions in downstream
reaches. By omitting these downstream effects, this
analysis potentially understates baseline risks that would be
reduced by the proposed option:
> cancer cases (from fish consumption),
* populations exposed to non-cancer systemic risks,
and
> waterways with pollutant concentrations exceeding
human health-based AWQC.
13.3.6 Exposed Fishing Population
Estimating the exposed fishing populations for specific
MP&M reaches requires statistics on county fishing
licences. EPA collect these data for every state where the
MP&M facilities are located where the state collects these
data at the county level. Where fishing license data were
not available at the county level, EPA estimated the exposed
fishing population based on state fishing license statistics
and census data. This approach may under- or overstate
actual fishing populations. In addition, data limitations
hamper the estimate of the number of anglers who actually
fish a given MP&M reach. Estimating the number of
anglers fishing MP&M reaches based on the ratio of
MP&M reach length to the total number of MP&M reach
miles in the county recognizes the effect of the quantity of
competing fishing opportunities on the likelihood of fishing
a given reach, but it does not account for the differential
quality of fishing opportunities. If water quality in
substitute sites is distinctly worse or better, the estimates of
the exposed populations are likely to be overstated or
understated.
In addition, the number of subsistence anglers was assumed
to equal 5 percent of the recreational fishing population.
The magnitude of subsistence fishing in the United States or
in individual states is not known. As a result, this estimate
may understate or overstate the actual number of
subsistence anglers.
Finally, to account for the effect of a fish advisory on
fishing activity, and therefore on the exposed fishing
population, EPA reduced the fishing population at an
MP&M reach under a fish advisory by 20 percent. This
could either overestimate or underestimate the risk associated
with consumption of contaminated fish, because (1) anglers
who change locations may simply be switching to other
locations where advisories are in place and therefore
maintain or increase their current risk, and (2) anglers who
continue to fish contaminated waters may change their
consumption and preparation habits to reduce the risks from
the contaminated fish.
13.3.7 Cancer Latency & Human Health
Cancer latency refers to the time between the initial event
that leads to cancer (e.g., chemical damage to DNA) and the
onset of cancer. Ideally, cancer would be detected at a very
early stage, when very few cells are involved. In reality,
cancer latency is a very complex issue, and the time to
detection varies considerably.
* Latency is related to health, age, immune status,
genetics and other characteristics of the individual.
> Latency is also related to the specific carcinogen,
the route of exposure, the type of cancer, the
technology used for cancer detection, and numerous
other factors.
* Environmentally induced cancers may not follow a
typical progression pattern; their latency may be
unusually shortened.
* Cancers may begin long before they are detected.
The exact progress and time of recognition/
detection of cancer cannot be predicted, because of
the numerous factors involved.
* Variations in timing of cancer detection are partially
attributable to the type of cancer involved, the
individuals affected, and differences in the medical
technology used.
* The fundamental issue is when the damage related
to cancer actually begins in an individual and when
the continued cell damage stops. Damage to the
individual begins when cancer is induced. Once
cellular changes begin, the immune system and
other body resources are diverted to limiting the
carcinogenic process and organ system damage is
occurring.
New instances of DNA mutation and cancer induction cease
when exposure ceases. Benefits of avoiding cancer begin to
accrue when cellular-level damage from the pollutant ceases.
This benefit occurs even though the benefits may not be
clinically measurable until some point in the future.
EPA assumed that benefits of avoiding cancer begin to
accrue when the initial events leading to cancer cease, even
though the benefits may not be clinically measurable until
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MP&M EEBA Part III: Benefits Chapter 13: Human Health Benefits
some point in the future. In making this assumption, the The monetary valuation of mortality risk from cancer in
Agency considered two factors: EPA benefit-cost analyses is based on the VSL. This is
derived from a number of revealed-preference studies that
> uncertainty as to how and when exposure changes estimate the value of avoided premature mortality. The
translate into reduced cancer risk, and estimates correspond to the value of unforeseen instant
death with no significant period of morbidity. The value of
> economic uncertainty associated with the value of an avoided cancer case used in this analysis may therefore
avoiding cancer and the timing at which a value of be underestimated, and ultimately the estimated value of the
cancer avoidance is recognized. human health benefit of the proposed regulation may be
understated.
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
GLOSSARY
marine reach: a specific length of marine coastline.
MP&M reach: a reach to which an MP&M facility
discharges.
Ambient Water Quality Criteria (AWQC): are
published and periodically updated by EPA under the
auspices of the Clean Water Act. The criteria reflect the
latest scientific knowledge on the effects of water pollutants
on public health and welfare, aquatic life, and recreation.
The criteria do not reflect consideration of economic
impacts or the technological feasibility of reducing chemical
concentrations in ambient water. The criteria serve as
guides to states, territories, and authorized tribes in
developing water quality standards and ultimately provide a
basis for controlling discharges or releases of pollutants into
our nation's waterways. AWQC are developed for two
exposure pathways: ingestion of the pollutant via
contaminated aquatic organisms only, and ingestion of the
pollutant via both water and contaminated aquatic
organisms.
no observed adverse effect level (NOAEL):
exposure level at which there are no statistically or
biologically significant differences in the frequency or
severity of any effect in the exposed or control populations.
reach: a specific length of river, lake shoreline, or marine
coastline
reference dose (RfD): an estimate of the maximum daily
ingestion in that is likely to be without an appreciable risk of
deleterious effects during a lifetime.
value of a statistical life saved (VSL): a monetary
value of fatalities. A statistical life is saved when the
mortality rate of a group of people is reduced sufficiently
that one less person will die than would otherwise be the
case. One must distinguish between statistical and actual
lives. An actual life is saved when the identity of the
beneficiary is know before the lifesaving expenditure is
made.
waterway: streams, lakes, bays, and estuaries.
willingness to pay (WTP): maximum amount of money
one would give up to buy some good.
(http://www.damagevaluation.com/glossary.htm)
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MP&M EEBA Part III: Benefits
Chapter 13: Human Health Benefits
ACRONYMS
AWQC: ambient water quality criteria
GEMS: Graphical Exposure Modeling System
NOAEL: no observed adverse effect level
RFD: reference dose
VSL: value of a statistical life saved
WSDB: The Water Supply Database
WTP: willingness to pay
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MP&M EEBA Part III: Benefits Chapter 13: Human Health Benefits
REFERENCES
Amdur, M.O., J. Doul, and CD. Klaassen, eds. 1991. Cassarett andDoul's: Toxicology, the Basic Science of Poisons. 4th
ed. New York, NY: McGraw-Hill Inc.
Belton, T., R. Roundy, and N. Weinstein. 1986. "Urban Fishermen: Managing the Risks of Toxic Exposure." Environment,
Vol. 28. No. 9, November.
Connelly, N. and B. Knuth. 1993. Great Lakes Fish Consumption Health Advisories: Angler Response to Advisories and
Evaluation of Communication Techniques, Human Dimensions Research Unit, Dept. of Natural Resources, NY State
College of Agriculture and Life Sciences, Cornell University, HDRU Series No 93-3, February.
Connelly, N., B. Knuth, and C. Bisogni. 1992. Effects of the Health Advisory and Advisory Changes on Fishing Habits and
Fish Consumption in New York Sport Fisheries, Human Dimensions Research Unit, Dept. of Natural Resources, NY State
College of Agriculture and Life Sciences, Cornell University, HDRU Series No 92-9, September.
Jones-Lee, M.W., M. Hammerton, and P.R. Philips. 1985. "The Value of Safety: Results of a National Sample Survey."
Economic Journal (March): 49-72.
Klaassen, C.D., ed. 1996. Cassarett andDoul's: Toxicology, the Basic Science of Poisons. 5th ed. New York, NY:
McGraw-Hill Inc.
Knuth, B. and C. Velicer. 1990. Receiver-Centered Risk Communication for Sportfisheries: Lessons from New York
Licensed Anglers. Paper presented at the American Fisheries Society Annual Meeting, Pittsburgh, Perm, August.
Silverman, W. 1990. Michigan's Sport Fish Consumption Advisory: A Study in Risk Communication. Thesis submitted in
partial fulfillment of the requirements for the degree of Master of Science (Natural Resources) at the University of Michigan,
May.
Tolley, G., D.Kenkel, and R.Fabian. 1994. "State-of-the Art Health Values." In G.Tolley et al., eds., Valuing Health for
Policy: An Economic Approach. Chicago and London: The University of Chicago Press, Ltd., pp. 323-344.
U.S. Bureau of the Census. 1997. http://www.census.gov
U.S. Department of the Interior. 1993. 1991 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation,
DOI, March.
U.S. EPA. 1980. Ambient water quality criteria documents. Washington, DC: Office of Water, U.S. EPA. EPA 440/5-80
Series. Also refers to any update of criteria documents (EPA 440/85 and EPA 440/5-87 Series) or any Federal Register
notices of proposed criteria or criteria corrections.
U.S. EPA. 1984. Summary of Current Oral Acceptable Daily Intakes (ADIs) for Systemic Toxicants. Cincinnati, Ohio:
Environmental Criteria and Assessment Office, U.S. EPA (May), 19 pp.
U.S. EPA. 1997a. Health Effects Assessment Summary Tables (HEAST). Office of Research and Development and Office
of Emergency and Remedial Response, Washington, DC: U.S. EPA. OERR 9200/6-303 (92-1).
U.S. EPA. 1997b. The Benefits and Costs of the Clean Air Act, 1970 to 1990. EPA 410-R-97-002, October, 1997. U.S.
EPA, Office of Air and Radiation
U.S. EPA. 1998/99. Integrated Risk Information System (IRIS) Retrieval. Washington, DC: U.S. EPA.
U.S. EPA. 1999a. Guidelines for Preparing Economic Analysis. Draft report. Washington, DC: U.S. EPA.
U.S. EPA. 1999b. National Listing of Fish and Wildlife Consumption Advisories. Washington, DC: U.S. EPA, Office of
Water.
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U.S. EPA. 1999c. Drinking Water Supply (DWS) File, Washington, DC: U.S. EPA, Office of Wetlands, Oceans and
Watersheds.
U.S. EPA. 2000. Estimated Per Capita Fish Consumption in the United States, Based on the Data Collected by the United
States Department of Agriculture's 1994-1996 Continuing Survey of Food Intakes by Individuals. Draft Report, March.
Viscusi, K. 1992. Fatal Tradeoffs: Public & Private Responsibilities for Risk. New York, NY: Oxford University Press.
West, P., R. Marans, F. Larkin, and M. Fly. 1989. Michigan Sport Anglers Fish Consumption Survey: A Report to the
Michigan Toxic Substances Control Commission, University of Michigan School of Natural Resources, Natural Resources
Sociology Research Lab, Technical Report #1, May.
Wexler, P., ed. 1998. Encyclopedia of Toxicology, Vol. 1-3.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
Chapter 14: Lead-Related Benefits
INTRODUCTION
The main benefits analysis performed by EPA examined
systemic health risks from exposure to MP&M
pollutants. EPA performed a separate analysis of benefits
from reduced exposure to lead. The analysis of health
effects from exposure to lead is based on dose-response
functions tied to specific health endpoints to which
monetary values can be applied. In this way it differs from
the analysis of systemic health risk from exposure to other
MP&M pollutants. This analysis assessed benefits of
reduced lead exposure from consumption of contaminated
fish tissue to three population groups: (1) preschool age
children, (2) pregnant women, and (3) adult men and
women.
EPA estimated benefits to preschool children based a dose-
response relationship for intelligence quotient (IQ)
decrements. The proposed rule would result in avoided IQ
loss of 489 IQ points. The Agency estimated monetary
values for avoided neurological and cognitive damages
based on the impact of an additional IQ point on an
individual's future earnings and the value of compensatory
education for children with learning disabilities. The
estimated monetary value of avoided cognitive damages to
children is $4.9 million (1999$) per year.
The proposed rule would also reduce the incidence of
neonatal mortality by 1.6 cases annually due to changes in
maternal blood /ead(PbB) levels during pregnancy.
Based on the willingness to pay (WTP) values for
avoiding death, the estimated monetary benefits to pregnant
women and infants are $9.33 million (1997$) annually. The
aggregated lead-related benefits for children from the
proposed rule are $14.39 million annually.
The health effects in adults that EPA was able to quantify all
relate to lead's effect on blood pressure (BP).
Quantified health effects include incidence of hypertension
in adult men, initial non-fatal coronary heart disease
(CHD). non-fatal strokes (cerebrovascular accidents
(CBA) and atherothrombotic brain infarctions (BID,
and premature mortality. EPA used cost of illness (COI)
estimates (i.e., medical costs and lost work time) to estimate
monetary values of reduced incidence of hypertension,
initial CHD, and strokes. This analysis uses the $5.8 million
CHAPTER CONTENTS:
14.1 Overview of Lead-Related Health
Effects
14.1.1 Children Under Age One
14.1.2 Children Between The Ages of One and
Six
14.1.3 Adults
14.2 Children Health Benefits
4.2. 1 PbB Distribution of Exposed
Children
14.2.2 Relationship Between PbB Levels
and IQ
14.2.3 Value of Children's Intelligence
14.2.4 Value of Additional Educational
Resources
14.2.5 Changes in Neonatal Mortality
14.3 Adult Health Benefits
14.3. 1 Estimating Changes in Adult PbB
Distribution Levels
14.3.2 Men Health Benefits
14.3.3 Women Health Benefits
14.4 Lead-Related Benefit Results
14.4.1 Preschool Age Children
Lead-Related Benefit Results
14.4.2 Adult Lead-Related Benefit
Results
14.5 Limitations and Uncertainties
14.5.1 Excluding Older Children
14.5.2 Compensatory Education Costs
14.5.3 Dose-Response Relationships
14.5.4 Absorption Function for Ingested
Lead in Fish Tissue
14.5.5 Economic Valuation
Glossary
Acronyms
References
|
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estimate of the value of a statistical life saved recommended
in the Draft Guidelines for Preparing Economic Analysis
(EPA, 1999b).'
1 The value of a statistical life saved is given in 1997$ (U.S.
EPA, 1999b). This underestimates benefits from the proposed
regulation. The benefits analysis for promulgation of the MP&M
regulation will adjust this value to 1999$.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
14.1 OVERVIEW OF LEAD-RELATED
HEALTH EFFECTS
Lead and lead compounds are toxic and pose threats to
human health and well being. The health effects of very
high levels of PbB include convulsions, coma and death
from lead toxicity. These effects have been understood for
many years. The effects of lower doses of lead are not fully
understood, however, and continue to be the subject of
intensive scientific investigation (CDC,1991b).
Lead accumulates in the body and is stored in various organ
systems. While high level exposures are of immediate
concern due to acute toxicity, exposure to small amounts
can accumulate over time to harmful levels. Accumulated
lead is very persistent, with a half-life in bone of
approximately 27 years.2 Known or strongly suspected
health effects include kidney, stomach, and respiratory
cancer, nervous system disorders, hypertension, anemia and
blood disorders, gastrointestinal disorders, renal damage and
other effects (ATSDR, 1997; CARB, 1996). Increased
mortality from these effects has been observed in studies
(ATSDR, 1997).
Many lead-associated adverse health effects are both chronic
in nature and relatively common. These effects include but
are not limited to hypertension, coronary artery disease, and
impaired cognitive function. Specific cases of these
conditions are difficult to link to lead exposure because the
same adverse health effects or endpoints can arise from a
variety of causes. Despite numerous studies conducted by
EPA and other institutions, dose-response functions are
available only for a handful of health endpoints associated
with elevated PbB levels.3 The available research does not
always allow complete economic evaluation, even for
quantifiable health effects.
Lead is harmful to any exposed individual, and the effects of
lead on children are of particular concern. Children's rapid
development rate makes them more susceptible to
neurobehavioral deficits resulting from lead exposure.
U.S. EPA identifies three sensitive populations: children
under age one, children between the ages one and six, and
adult men and women (U.S. EPA, 1990). New research
suggests that children older than six may also be a
hypersensitive population. Recent research on brain
development among 10- to 18-year-old children shows
unanticipated and substantial growth in brain development,
mainly in the early teenage years (Giedd et al., 1999). This
analysis does not, however, include this group due to data
limitations. Table 14.1 summarizes the quantifiable health
effects on children under six and adult men and women,
along with other important, non-quantified, known health
effects on these populations.
2 A half-life of 27 years means that it takes 27 years for the
levels measured in bone to decrease by 50 percent.
3 In a pioneering study, Schwartz et al. quantified a number of
health benefits that would result from reducing the lead content of
gasoline (U.S. EPA, 1985). EPA extended this work by analyzing
lead in drinking water (U.S. EPA, 1986a) and by funding the study
of lead in the air (U.S. EPA, 1987).
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
Table 14.1: Quantified and Unquantified Health Effects of Lead
Population Group
Quantified Health Effect
Unquantified Health Effect
Children ages 0-6
Neonatal mortality due to decreased gestational
age and low birth weight caused by maternal
exposure to lead
Nervous system effects in children younger than 6
years - IQ decrements, cases of IQ less than
70, PbB levels greater than 20 ug/dL
Fetal effects from maternal exposure (including
diminished IQ and reduced birth weight)
LowIQ(70
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
Agency (CEPA) has also classified lead as a carcinogen and
estimated a preliminary cancer potency value ranging from
2.8 x 10'1 to 3.88 x 10'2 per mg/kg/day for oral exposure to
lead compounds (California Air Resource Board [CARB],
1996). Reduced cancer risk associated with reduced
exposure to lead can be estimated based on cancer cases
avoided (see Section 13.2.1).
Elevated PbB has been linked to elevated BP in adults,
especially in men aged 40 to 59 (Pirkle et al., 1985).
Elevated BP, itself a health hazard, is also a risk factor for
heart attack, stroke (Shurtleff, 1974; McGee and Gordon,
1976; Pooling Project Research Group [PPRGI. 1978), and
premature death. Although elevated BP in women results in
the same effects as for men, the general relationships
between BP and these health effects differ somewhat across
gender.
Other known or strongly suspected health endpoints include
nervous system disorders in adults, anemia and blood
disorders, gastrointestinal disorders, and renal damage.
Finally, data suggest that lead is genotoxic and may cause
chromosomal damage in humans leading to birth defects.
Lead may also cause other adverse reproductive effects in
women, including increased miscarriage and stillbirth (U.S.
EPA 1990). A study of National Health and Nutrition
Examination Surveys (NHANES) II data by Silbergeld et al.
suggests that accumulated lead is stored in women's bone
tissues and is mobilized back into the blood during the bone
demineralization associated with pregnancy, lactation, and
osteoporosis (Silbergeld et al., 1988). Many of these effects
cannot be quantified due to a lack of information on the
dose-effect relationship.
14.2 CHILDREN HEALTH BENEFITS
The following analysis assesses benefits to children from
reduced lead exposure, via reduced consumption of
contaminated fish tissue.4 This analysis uses PbB
concentrations as a biomarker of lead exposure.5 EPA
measured PbB levels in the population of exposed children
to obtain both baseline and post-compliance readings.
Changes in those readings yielded estimated benefits from
reduced lead exposure in the form of avoided damages.
Avoided neurological and cognitive damages are expressed
as changes in overall IQ levels, including reduced incidence
of extremely low IQ scores (<70, or two standard deviations
below the mean), and reduced incidence of PbB levels above
20 ug/dL. The neurological and cognitive damages avoided
are then quantified using the value of compensatory
education that an individual would otherwise need, and the
impact on that individual's future earnings. This analysis
does not quantify additional benefit categories, such as the
costs of PbB screening and medical treatment. The reduced
loss in IQ points, reduced cases of IQ levels below 70
points, and reduced special education costs associated with
various PbB levels are likely to be the largest benefit
categories. This analysis does not estimate the cost of group
homes and other special care facilities.
The analysis of health benefits to children involves the
following steps:
* Estimate the baseline and post-compliance lead
discharges from MP&M facilities;
> Estimate lead concentrations in receiving water
bodies before and after proposed effluent
guidelines based on lead discharge estimates,
effluent flow, characteristics of the receiving
POTWs, and characteristics of receiving water
bodies;
> Estimate the baseline and post-compliance dietary
lead intake of children via fish consumption;
* Estimate PbB levels of exposed children before and
after the proposed regulation, based on in-stream
lead concentrations, bioaccumulation factors, and
fish consumption rates for children;
> Assess changes in health impacts to children from
reduced lead exposure, including changes in IQ
loss, changes in incidence of IQ<70, and changes
in neonatal mortality.
> Estimate monetary benefits resulting from reduced
adverse health impacts to children;
* Estimate benefits from changes in neonatal
mortality from reduced maternal exposure to lead.
Figure 14.1 depicts the above steps.
4 This analysis does not consider the beneficial effects due to
reduced drinking water exposure. EPA has issued drinking water
criteria for lead. This analysis assumes drinking water treatment
has already reduced lead content below threshold levels.
5 PbB concentration is the most common measure of body-
lead burden. Other measures of body-lead burden include lead in
bones, teeth, and hair.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
Figure 14.1 Assessing Benefits to Children from Reduced Lead Discharges from MP&M Facilities
Baseline lead discharges from MP&M
facilities
Post-compliance lead discharges
from MP&M facilities
Baseline ambient water
quality conditions
Post-compliance
ambient water quality conditions
Baseline dietary lead intake
via fish consumption
Post-compliance dietary lead intake
via fish consumption
Use IEUBK to estimate change in
children's blood lead distribution
from baseline to post-compliance
Change in IQ distribution from
baseline to post-compliance
Change in incidence
of blood-lead levels
>20
Avoided IQ loss
Change in incidence
ofIQ<70
Avoided loss in
lifetime earnings
Avoided costs
of compensatory
education
Monetary benefits from reduced
exposure of children to lead
Reduced
neonatal mortality
Value of life
Source: U.S. EPA analysis.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
The following sections summarize the relevant
dose-response relationships for children, and discuss data
sources used for the dose-response relationships. Each
section also includes the methods used to value the changes
in health effects based upon dose-response relationships.
14.2.1 PbB Distribution of Exposed
Children
This section describes the estimation of changes in PbB
distribution of exposed children.
a. Estimating lead concentrations in the
receiving water bodies
Estimating health risks associated with lead exposure from
fish consumption requires calculating in-waterway lead
concentrations. The method and formulas for this
calculation were identical to those described for the analysis
of cancer effects for the fish consumption pathway (see
Chapter 13 on Human Health Benefits and the
Environmental Assessment in Appendix E for details.)6
b. Estimating PbB levels in exposed children
This analysis considers children that are born today and live
in recreational and subsistence fishermen households. The
analysis considers a continuous exposure pattern for
children from birth through the sixth birthday. Exposure,
health effects, and benefits are calculated separately for
children living in recreational and subsistence fishing
households. This analysis relies onEPA's Integrated
Exposure, Uptake, andBiokinetics (IEUBK) Model
for Lead in Children.
ซ> Description of the IE UBK model
The IEUBK model uses exposure, uptake, and biokinetic
response information to estimate the PbB level distribution
for a population of children receiving similar exposures.
The estimated distribution may be used to predict the
probability of elevated PbB levels in children exposed to a
specific combination of environmental-lead levels. The
model addresses four components of environmental risk
assessment:
* the multimedia nature of exposure to lead;
* the differential bioavailability of various sources
of lead;
> the pharmacokinetics of internal distribution of
lead to bone, blood, and other tissues; and
* inter-individual variability in PbB levels.
The model uses estimated or measured lead concentrations
in fish tissues and other media, such as soil, dust, air, and
water, to estimate a continuous exposure pattern for children
from birth through the sixth birthday (U.S. EPA, 1995). The
model then estimates a distribution of PbB levels for a
population of children receiving similar exposures by
predicting its geometric mean (GM). The inter-
individual and biological variability in PbB levels of
children exposed to similar environmental lead levels is
represented by the geometric standard deviation
(GSD). This analysis uses an empirical estimate of the
variability in PbB concentrations, a GSD of 1.6, estimated
from residential community PbB studies (U.S. EPA, 1995).
This estimate is applied for predictions of the national
distribution of PbB concentrations.
The model has three distinct functional components that
work together in a series:
> exposure,
* uptake, and
> biokinetics response.
Each model component is a set of complex equations and
parameters. The Technical Support Document (U.S. EPA,
1995) provides the scientific basis of the parameters and
equations used in the model, while the Guidance Manual
(U.S. EPA, 1994) includes a detailed description of the
exposure pathways, absorption mechanism, biokinetic
compartments, and associated comparted transfers of lead.
* Inputs to the IEUBK model
The IEUBK model uses three sets of parameters:
* exposure parameters estimate the amount of
environmental lead taken into the body, through
breathing or ingestion;
* uptake parameters estimate the amount of lead
absorbed from environmental sources;
* biokinetic parameters characterize the transfer of
lead between compartments of the body (e.g.,
between blood and bone) and elimination of lead
from the body.
The IEUBK model allows the user to input values for most
exposure and uptake parameters. The biokinetic parameter
values cannot be altered. When exposure and uptake values
are not specified, the IEUBK model provides default values.
Table 14.2 summarizes exposure parameters used in this
analysis.
6 The water quality model used for the Ohio case study is
discussed in Appendix G.
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Chapter 14: Lead-Related Benefits
1. Exposure parameters include exposure concentrations
and exposure rates:
> Exposure concentrations: EPA used estimated in-
stream concentrations of lead to calculate lead
concentration of the dietary (i.e., fish consumption)
exposure pathway. The Agency used 1996
monitoring data on lead concentrations in air, dust,
and soil to characterize lead exposure
concentrations for pathways other than fish
consumption.7 This analysis uses median
concentration values for these three pathways as
inputs to the IEUBK to characterize background
exposure to environmental lead. EPA used the
IEUBK default value for lead concentration in
drinking water that takes into account contributions
of lead from plumbing. Because of past use of lead
in plumbing, lead concentrations in tap water are
2.
likely to be above the current water quality standard
for lead in drinking water.
> Exposure rates: Children in recreational fishing
households are assumed to consume 14.97 grams of
fish per day. Children living in subsistence
households are assumed to consume 77.95 grams of
fish per day. These fish consumption data are
based on uncooked fish weights and use data on
individuals younger than 14 years of age (U.S.
EPA, 1998d). The Agency used the IEUBK default
values to characterize exposure rates for pathways
other than fish consumption.
Uptake of ingested lead: Lead bioavailability varies
across the chemical forms in which lead can exist.
Many factors complicate the estimation of
bioavailability, including nutritional status and timing of
meals relative to lead intake. The Agency used the
default media-specific bioavailabilities in the IEUBK
model for this analysis.
Biokinetic parameters: The data on which these
parameter values are based originate from a variety of
sources, including available clinical data (U.S. EPA,
1995). These parameters cannot be changed by the
user.
7 EPA found that the typical PbB level distribution predicted
in the IEUBK Model for Lead in Children based on the default
values for air, dust, soil, and drinking water lead concentrations did
not correspond to the most recent national population PbB
distribution (NHANES III, Phase 2, 1994). Lherefore, the Agency
used more recent data to characterize the background exposure to
environmental lead. Median values from recent monitoring data
allowed the Agency to match the lEUBK-predicted PbB
distribution to the NHANES-derived distribution.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
Table 14.2: Summary of Exposure Concentrations Used in the IEUBK Model
Medium
Air
- indoor
- outdoor
Water
Soil
Dust
Fish tissue
Exposure Concentrations
0.025 ng/m3
30% of outdoor value
4_ug/L
61.78|ig/g
181.11 jjg/g
site- specific
Comments
Median value from 1 996 air monitoring data
IEUBK default value
IEUBK default value
Median value from Housing and Urban Development national survey (U.S.
Department of Housing and Urban Development, 1995)
Median value from Housing and Urban Development national survey (U.S.
Department of Housing and Urban Development, 1995)
Estimated based on predicted lead concentrations in the receiving reaches
and the bioconcentration factor for lead (49 L/kg)
Source: U.S. EPA analysis.
c. Estimating changes in the PbB level in
exposed children from reduced MP&M
discharges
EPA used the IEUBK model in this analysis to estimate the
effect of lead-contaminated fish consumption on children's
PbB concentrations. The Agency first calculated lead
concentration in fish tissue corresponding to each reach
affected by MP&M discharges to provide inputs to the
IEUBK model. The model uses the specified fish tissue
concentrations in conjunction with fish ingestion rates and
bioavailability factors to determine the dose of lead
absorbed by the body. This dose is then used to predict the
GM PbB concentration for children associated with each
reach affected by lead discharges from the MP&M facilities.
EPA used the IEUBK model to predict the baseline and
post-compliance PbB distributions for children that consume
fish from reaches affected by lead discharges from MP&M
facilities. The difference between the estimated baseline
and post-compliance PbB distribution is the basis for the
analysis of benefits to children from the MP&M regulation.
14.2.2 Relationship Between PbB Levels
and IQ
A dose-response relationship between PbB and IQ
decrements determined by Schwartz (1994) suggests that a
decrease of 0.25 IQ points can be expected for every 1
ug/dL increase inPbB(Schwartz, 1994). The p-value (<
0.0001) indicates that this relationship is highly significant.
EPA multiplied the 0.25 IQ points lost per ug/dL increase in
PbB by the average increase in PbB level for children and by
the number of exposed children to obtain the total change in
number of IQ points for the population. The average PbB
level modeled in this analysis is a GM, not the arithmetic
mean used by Schwartz (1993). To adjust for this
difference, equation 14.1 uses a ratio between the arithmetic
mean and the GM of a lognormally-distributed random
variable. The ratio between the expected value (mean) of
the distribution and the GM is 1.117 for the assumed GSD
of children's PbB levels (1.6).
The total avoided loss of IQ points for each group is
estimated as:
(AVOIDED LOSS of IQ POINTS)k
=*GMkx.25x(Popk)/6
(14.1)
where:
(Pop)k
GMk
the number of children (up to age six) in
anglers' families in the vicinity of a given
MP&M reach; and
the GM of the PbB distribution in the
population of children.
As shown in equation 14.1, the population of children up to
age six is divided by six to avoid double-counting. The
IEUBK model calculates the GM of the PbB distribution in
the population of children born today, assuming a
continuous exposure pattern for children from birth through
the sixth birthday. Assuming that children are evenly
distributed by age, this division adjusts this equation to
apply only to children age 0-1. Dividing by six undercounts
overall benefits. Children from age 1 to 6 are not accounted
for in the base year of the analysis, although they are
presumably affected by the lead exposure, because the
IEUBK model assumes a continues exposure pattern for
children from birth trough the sixth birthday.
14.2.3 Value of Children's Intelligence
Available economic research provides little empirical data
on society's overall WTP to avoid a decrease in an infant's
IQ. This analysis uses research that monetizes a subset of
effects associated with decreased IQ. These effects
represent only some components of society's WTP to avoid
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
IQ decreases, and underestimate society's WTP when
employed alone. For the purpose of this analysis, these
effects are the only ones available at this time to
approximate the WTP to avoid IQ decrements.
Recent studies provide concrete evidence of long-term
effects from childhood lead exposure. This analysis
assumes a permanent loss of IQ points based on PbB levels
estimated for children up to age six, and considers two
consequences of this IQ decrement:
> the decreased present value of the infant's expected
lifetime earnings, and
* the increased educational resources expended for
an infant who becomes mentally handicapped or
needs compensatory education as a consequence of
lead exposure.
a. Estimating the effect of IQ on earnings
Reduced IQ has direct and indirect effects on earnings. This
analysis models the overall impact from a one-point
reduction in IQ as the sum of these direct and indirect
effects on lifetime earnings. EPA used the most recent
estimates of the effects of IQ on earnings based on Salkever
(1995).8 Salkever provided updated estimates of the direct
and indirect effects of IQ loss on earnings, using the most
recent available data set, the National Longitudinal Survey
of Youth (NLSY). Salkever used regression analysis
techniques to estimate direct and indirect effects of IQ on
earnings. Three different relationships are estimated
separately for male and female respondents:
- A least-squares regression of highest grade
on IQ test scores;
- A probit regression of an 0-1 indicator of
positive earnings on highest grade and IQ test
scores;
> A least-squares regression, for persons with
positive earnings, of the logarithm of earnings on
highest grade and IQ test scores.
Other variables were included in each regression to control
for effects of family background (parents' education and
income), the age of the respondent, ethnic group, and
residence location (urban U.S., non-urban U.S., south versus
non-south).
8 EPA did not incorporate earlier studies of the effects of IQ
on earnings in this analysis, because the labor market has
undergone many changes over the quarter-century in which earlier
studies have appeared
Based on the regression results, Salkever estimated the
effects of IQ on earnings as the sum of direct and indirect
effects:
* The direct effect is the sum of effects of IQ test
scores on employment and earnings for employed
persons, holding the years of schooling constant.
* The indirect effect is the sum of effects of IQ test
scores on years of schooling attained, and the
subsequent effect of years of schooling on the
probability of employment and on earnings for
employed persons.
The analysis found that percentage effects of lead exposure
are greater for females than for males. The total estimated
effect of the loss of an IQ point on earnings, based on the
Salkever study, is an earnings reduction of 2.094 percent for
men and 3.631 percent for women. This analysis uses a
workforce participation-weighted average of 2.626 percent.
The total effect of the loss of an IQ point on earnings also
includes non-IQ effects on schooling (e.g., behavioral
problems).
b. Valuing foregone earnings
EPA monetized IQ loss effects by combining the percent
earnings loss estimate with an estimate of the present value
of expected lifetime earnings. EPA used the 1992 data on
money income for the U.S. population (U.S. Department of
Commerce, 1993) to calculate the mean present value of
lifetime earnings of a person born today. The data included
earnings for employed persons and employment rates as a
function of educational attainment, age, and gender. The
following assumptions were used to calculate the mean
present value of lifetime earnings of a person born today:
> The distribution of earnings for employed persons
and labor force participation rates remains constant
over time,
> A person earns income from age 18 through age 67,
* Real wages grow one percent per year, and
> Future earnings are discounted at a three percent
annual rate.
The money income data (U.S. Department of Commerce,
1993) form the best available basis for projecting lifetime
earnings, but involve some uncertainties. Labor force
participation rates of women, the elderly, and other groups
will likely continue to change. Currently, men tend to earn
more than women due to higher wage rates and higher labor
force participation. Expected lifetime earnings increase with
education for both men and women. Real earnings of
women will probably continue to rise relative to real
earnings of men. Educational attainment has risen over time
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
and may continue to rise. Unpredictable fluctuations in the
economy's growth rate will probably affect labor force
participation rates and real wage growth for all groups.
Medical advances that increase life expectancy will probably
increase lifetime earnings.
Although earnings data alone form an incomplete measure
of an individual's value to society, this analysis does not
account for those individuals who do not participate in the
labor force at all throughout their working years and whose
productive services are not measured by wage rates. The
largest group in this population are those who remain at
home doing housework and child rearing. Volunteer work
also contributes significantly to social welfare, and
volunteerism rates tend to increase with educational
attainment and income. Assuming that the opportunity
cost of non-wage-compensated work equals the average
wage earned by persons of the same sex, age, and education,
the average lifetime earnings estimates would be
significantly higher. Recalculating the tables using full
employment rates for all age, sex, and education groups
would provide higher lifetime earnings estimates. To be
conservative, this analysis considered only the value of lost
wages and does not include the opportunity cost of non-
wage-compensated work.
The adjusted value of expected lifetime earnings equals the
present value for an individual entering the labor force at
age 18 and working until age 67. Given a three percent
social discount rate, the other assumptions mentioned, and
current survival probabilities, the present value of lifetime
earnings of a person born today in the U.S. would be
$428,115(1999$).
c. Valuing costs of education
The increase in lifetime earnings from additional education
equals the gross return on education. The cost of education
is subtracted from the gross return to obtain the net increase
in earnings from additional education. The cost of education
has two components: the direct cost of the education, and
the opportunity cost of lost income during the education.
The marginal cost of education used in this analysis was
assumed to be $8,036 (1999$) per year. This figure was
derived from the U.S. Department of Education's reported
($6,961) average per-student annual expenditure (current
plus capital expenditures) in public primary and secondary
schools in 1995-96 (U.S. Department of Education, 1998).
EPA adjusted this value to 1999 dollars based on CPI for
education.
Salkever's study found the estimated effect of IQ on
educational attainment to be 0.1007 years per IQ point. The
estimated cost of an additional 0.1007 years of education per
IQ point is $809 (i.e., 0.1007 x $8,036). This marginal cost
was discounted to the time the exposure and damage is
modeled to occur (age zero) because this cost is incurred
after the completion of formal education. The average level
of educational attainment in the population over age 25 is
12.9 years. The marginal educational cost was therefore
assumed to occur at age 19, resulting in a discounted present
value cost of $461 (1999$).
The other component of the cost of education is the
opportunity cost of lost income while in school. Income loss
is frequently cited as a major factor in the decision to
terminate education, and must be subtracted from the gross
returns to education. An estimate of the lost income was
derived assuming that people in school are employed part-
time but that people out of school are employed full-time.
The opportunity cost of lost income is the difference
between full-time and part-time earnings. The value of lost
income associated with being in school an additional 0.1007
years is $713 (1999$) discounted to age zero.
d. Estimating the total effect of IQ on
earnings.
Combining the value of lifetime earnings ($428,115) with
the estimate of percent wage loss per IQ point yielded
$ 11,251 per IQ point. Subtracting the education and
opportunity costs reduced this value to $ 10,077 per IQ point
(1999$).
14.2.4 Value of Additional Educational
Resources
Children with IQ less than 70 and whose PbB is greater than
20 ug/dL will require additional educational resources
including an educational program tailored to the mentally
handicapped. Some children whose PbB is greater than 20
ug/dL will need additional instruction while attending
school later in life. The following sections describe
approaches used to quantify the number of children with IQs
less than 70 and to estimate increased educational costs
resulting from lead exposure.
a. Children with IQs less than 70
ซ> Quantifying the number of children with IQs
less than 70
Increases in the mean PbB levels of children results in an
increased incidence of children with very low IQ scores. IQ
scores are normalized to have a mean of 100 and a standard
deviation of 15. An IQ score of 70 is two standard
deviations below the mean, and is generally regarded as the
point below which children require significant special
compensatory education tailored to the mentally
handicapped.
The relationship presented here for estimating changes in the
incidence of IQ less than 70 used the most current IQ point
decrement function provided by Schwartz (1993). It
assumed that, for a baseline children's PbB distribution
(defined by GM and GSD), the population also has a
normalized IQ point distribution with a mean of 100 and a
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
standard deviation of 15. The proportion of the population
expected to have IQ less than 70 was determined from the
standard normal distribution function for this baseline
condition:
(14.2)
probability of IQ scores less than 70
standard normal variate (i.e., the
number of standard deviations);
computed for an IQ score of 70, with
mean IQ score of 100 and standard
deviation of 15 as:
where:
P(IQ <70)
z_70-100__2
15
(14.3)
standard normal distribution function:
9
7 U
1
' du
(14.4)
The integral in the standard normal distribution function
does not have a closed form solution. Values for <3>(z) are
usually obtained using software with basic statistical
functions or from tables typically provided in statistics texts.
The solution for $(z) where z = -2 is 0.02275. That is, for
the normalized IQ score distribution with a mean of 100 and
standard deviation of 15, approximately 2.3 percent of
children are expected to have IQ scores below 70.
EPA made two key assumptions to relate changes in the
proportion of children with IQ scores below 70 to changes
in population mean PbB levels:
1. The mean IQ score will change as a result of changes in
the mean PbB level as:
A Mean IQ = -0.25 x A Mean PbB (14.5)
where:
A Mean IO =
the change in the mean IQ score
between the baseline and post-
compliance scenarios, and
A Mean PbB =
the change in the mean PbB level
between the two scenarios.
This relationship relies on Schwartz' estimate (1993) of a
decrease of 0.25 IQ points for each ug/dL increase in PbB.
The mean PbB level referred to here is the arithmetic mean
(or expected value) for the distribution, obtained as
described previously from the GM and GSD.
2. The standard deviation for the IQ distribution is 15 for
both the baseline and the post-compliance scenario.
Using these assumptions, EPA determined the change in the
probability of children having IQ less than 70 for a given
change in mean PbB from:
(14.6)
- 0.02275
where:
= baseline standard normal distribution
function,
post-compliance standard normal
distribution function.
_ 70 - (100 + 0.25 x AMeanPbB)
Zjsr 15
(14.7)
EPA then converted a given change in the mean PbB level
between the baseline and post-compliance scenarios into a
measure of IQ. The procedure above yielded an estimate of
the percent of the population with IQs less than 70. EPA
multiplied this percent by the population of exposed children
to estimate the increased incidence of children with low IQs.
As in the IQ point loss equation, EPA applied the results of
this function to children age 0-6 and divided by six to avoid
double counting. (See discussion under equation 14.1.)
This procedure quantified only the change in the number of
children who pass below the 70 point IQ threshold. EPA
quantified other changes in children's IQ using the IQ point
loss function (Equation 14.1) described previously. Treating
these two endpoints additively does not result in double
counting, because the value associated with the IQ point loss
function is the change in individual lifetime earnings, while
the value associated with IQs less than 70 is the increased
educational costs for the individual, as discussed below.
ซ> Valuing educational costs
EPA estimated the number of avoided cases of children with
IQ less than 70. Compensatory education expenses will no
longer be incurred for these cases. Kakaliketal. (1981),
using data from a study prepared for the Department of
Education's Office of Special Education Programs,
estimated part-time special education costs for children who
remained in regular classrooms at $3,064 extra per child per
year in 1978. Adjusting for changes in the GDP price
deflator yielded an estimate of $8,036 per child in 1999
dollars. EPA used the incremental estimate of the cost of
part-time special education to estimate the annual cost per
child needing special education as a result of lead impacts
on mental development. EPA assumed that compensatory
education begins at age six and continues through age 18
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
(grades one through twelve). Discounting future expenses
at a rate of three percent yielded an expected present value
cost of approximately $72,664 per child ($1999). This
discounting underestimates the cost because Kakalik et al.
measured the increased cost to educate children attending
regular school rather than a special education program. The
costs of attending a special education program are likely to
be much higher than those associated with regular schooling.
In addition, some compensatory education programs begin
earlier than at age six. For example, some states, such as
Connecticut and Rhode Island, offer Head Start programs to
disadvantaged children beginning at age three.
b. Children with PbB levels greater than 20
ng/dL
ซ> Quantifying the number of children with PbB levels
greater than 20 ug/dL
EPA obtained the percentage of children with PbB levels
greater than 20 ug/dL directly from the estimated
distribution of PbB levels for a given location (IEUBK).
EPA then multiplied this percentage by the number of
exposed children in the vicinity of a given MP&M reach to
estimate the number of children with PbB levels greater than
20 ug/dL.9
ซ> Estimating and valuing compensatory education for
children with PbB levels greater than 20 fig/dL
EPA assumed that 20 percent of the children with PbB
levels greater than 20 ug/dL would require and receive
compensatory education for three years. After this time, no
further educational expenditures are incurred by those
children. These assumptions are conservative. Many
studies show adverse cognitive effects at PbB levels at 15
ug/dL. Some studies of the persistence of cognitive effects
indicate that the effects often last longer than three years.
The Kakalik et al. (1981) estimate of part-time special
education costs for children who remained in regular
classrooms can be used to estimate the cost of compensatory
education for children suffering low-level cognitive damage.
As indicated above, the part-time special education cost per
child is $8,036 per year in 1999 dollars. The Agency
assumes that compensatory education starts at age 6 and
continues for 3 years. Discounting future costs at a rate of 3
percent annually to account for the age at which costs are
incurred (i.e., age 6 through 8) yields a present value
estimate of $20,649 in 1999 dollars.
14.2.5 Changes in Neonatal Mortality
a. Quantifying the relationship between
maternal PbB levels and neonatal mortality
U.S. EPA (1990b) cites a number of studies linking fetal
exposure to lead (via in utero exposure from maternal lead
intake) to several adverse health effects. These effects
include decreased gestational age (i.e., premature birth),
reduced birth weight, late fetal death, and increases in infant
mortality.
The CDC (CDC, 1991a) developed a method to estimate
changes in infant mortality due to changes in maternal PbB
levels during pregnancy. The analysis linked the following
two relationships:
* Gestational age as a function of maternal PbB
(Dietrich et al., 1987), and
* Infant mortality as a function of gestational age.
This is performed using data from the Linked Birth
and Infant Death Record Project from the National
Center for Health Statistics (CDC, 1991a).
Combining the two relationships provided a decreased risk
of infant mortality of 10'4 (or 0.0001) for each 1 ug/dL
decrease in maternal PbB level during pregnancy. EPA used
this relationship for its analysis of maternal PbB levels and
neonatal mortality.
b. Valuing changes in neonatal mortality
This analysis used the estimated WTP for avoiding a
mortality event to estimate the monetary benefit associated
with reducing risks of neonatal mortality. This analysis uses
the $5.8 million (1997$) estimate of the value of a statistical
life saved recommended in the Draft Guidelines for
Preparing Economic Analysis (EPA, 1999b). For detail on
valuing reduced mortality risks see Section 13.2.1.
14.3 ADULT HEALTH BENEFITS
Lead exposure has been shown to have adverse effects on
the health of adults as well as children. The quantified adult
health effects included in the benefits analysis all relate to
lead's effects on BP.10 The estimated relationships between
these health effects and lead exposure differ between men
and women. Quantified health effects include increased
incidence of hypertension (estimated for males only), initial
9 See Section 13.1.1 for detail on estimating the affected
population. The percentage of children in the affected population
is estimated based on the Census data.
10 Citing laboratory studies with rodents, U.S. EPA (1990)
also presents evidence of the genotoxicity and/or carcinogenicity of
lead compounds. The animal lexicological evidence suggests that
human cancer effects are possible, but dose-response relationships
are not currently available.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
CHD, strokes (initial CBA and BI), and premature mortality.
This analysis does not include other health effects associated
with elevated BP, and other adult health effects of lead
including neurobehavioral and possible cancer effects.
Estimating adult health benefits from reduced exposure to
lead requires analytic steps similar to those used in
estimating children's health benefits. These steps are:
* Estimate in-stream lead concentrations in the
reaches affected by MP&M discharges;
* Estimate baseline and post-compliance adult dietary
lead intake via fish consumption. The analysis of
adult health benefits from reduced exposure to lead
via contaminated fish uses the results from water
quality modeling efforts described in Appendix E;
> Estimate changes in the PbB level distribution in
the affected adult population;
> Estimate changes in health status in the affected
population of adult men, and the monetary value of
health benefits from reduced lead discharges from
MP&M facilities; and
> Estimate changes in health status in the affected
population of adult women, and the monetary value
of health benefits from reduced lead discharges
from MP&M facilities.
Figure 14.2 depicts the above steps. Table 14.3 summarizes
per-case costs of lead-related illnesses.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
Figure 14.2 Assessing Benefits to Adults from Reduced Lead Discharges from MP&M Facilities
Baseline lead discharges from MP&M
facilities
Baseline ambient water
quality conditions
Baseline dietary lead intake
via fish consumption
Estimated baseline blood lead
distribution in exposed adults
Post-compliance lead discharges from
MP&M facilities
Post-compliance
ambient water quality conditions
Post-compliance dietary lead intake
via fish consumption
Estimated post-compliance blood lead
distribution in exposed adults
Baseline health effects to adults
Post-compliance health effects to adults
Changes in adverse health effects to adults from baseline to post-compliance
Hypertension
(males in specified age
ranges)
Non-fatal coronary
heart disease (CHD)
(males and females)
^
r
Avoided illness costs
Non-fatal strokes
(males and females)
Monetary benefits from reduced adult exposure to lead
Reduced mortality
Value of lives
Source: U.S. EPA analysis.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
Illness
Hypertension
CHD #la
Stroke3
Low Birth
Weight"
Death Any
Illness b
Gender
Male
Female
Male
Female
Male
Female
Female
Male
Female
Table 14.3
Cost per
Case (1999$)
$1,048
$1,048
$70,240
$70,240
$262,379
$196,783
$82,219
$5.8 Million
$5.8 Million
: Pen-Case Costs of Lead-Related Illnesses
Cost Description
The cost estimates were derived by taking Krupnick et al.'s average annual per-person
costs of hypertension (Krupnick et al., 1989).
The costs were estimated (Wittels et al., 1990) for three CHDs (acute myocardial
infarction, uncomplicated angina pectoris, and unstable angina pectoris) for 5
years post-diagnosis using a three percent discount rate. The probability of medical
service was multiplied by the estimated price of the service and the average cost for
the three CHD types was determined. Since the effect of elevated PbB on CHD
incidence rates is beyond the scope of this analysis, weighting factors were not used to
account for the different probabilities of contracting the three types of CHD.
The cost estimates (Taylor et al., 1996) represent the expected lifetime cost of a stroke
for males and females age 45-74, including the present discounted value of the stream
of medical expenditures and the stream of lost earnings. Note that the study used a
five percent discount rate. EPA did not adjust this value to reflect a 3 percent
discount rate used elsewhere in this analysis.
The cost estimate was extrapolated from direct costs for LEW taken from Lewitt et al.,
using a three percent discount rate (Lewitt et al., 1 995). The value includes medical,
special education, and grade repetition costs.
A range of values taken from hedonic wage studies and/or contingent valuation
studies of primarily middle aged adults was used to determine the cost of death (see
Chapter 13 for detail).
a. Costs were taken from U.S. EPA, 1999a.
b. The value of a statistical life saved is given in 1997$ (U.S. EPA, 1999b). This underestimates benefits from the proposed regulation. The benefits
analysis for promulgation of the MP&M regulation will adjust this value to 1999$.
c. Note that this analysis does not estimate occurrence of low birth weight cases, due to data limitations.
Source: U.S. EPA, 1999a.
14.3.1 Estimating Changes in Adult PbB
Distribution Levels
a. Estimating values of PbB concentrations
in exposed adults
EPA adapted the methodology described in the Interim
Approach to Assessing Risks Associated with Adult
Exposure to Lead in Soil (hereafter, Interim Guidance) to
estimate changes in the distribution of PbB levels in exposed
adults from reduced MP&M discharges (U.S. EPA, 1996).
The methodology presented in the Interim Guidance report
used a simplified representation of lead biokinetics to
predict quasi-steady-state PbB concentrations among adults
who have relatively steady patterns of exposures to lead.
This methodology is recommended by the Technical
Review Workgroup (TRW) to assess the effects of
ingesting lead-contaminated soil on PbB levels of women of
childbearing age, to derive risk-based remediation
goals (RBRG) protective of the developing fetus in
exposed adult women.11 The Interim Guidance describes the
basic algorithms to be used in the analysis and provides a set
of default parameters that can be used in cases where site-
specific data are not available. The TRW points out that this
methodology is an interim approach recommended for use
pending further development and evaluation of integrated
exposure biokinetic models for adults.
The dose-response relationship recommended in the Interim
Guidance for exposures to lead-contaminated soil can be
modified to analyze PbB levels in recreational and
subsistence anglers exposed to lead-contaminated fish
tissue. In both cases, the exposure pathways involve
ingestion. The Interim Guidance differs from this analysis
mainly in the medium containing lead (soil versus fish
tissue). Substituting ingestion of lead in fish for ingestion of
lead in soil yields the following equation:
11 EPA's TRW for lead began considering methodologies to
evaluate nonresidential adult exposure to lead in 1994. A TRW
committee on adult lead risk assessment formed in January 1996 to
develop a generic methodology that could be adapted for use in
site-specific assessments of adult health risks.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
PbB adult, central = PbB
adult, 0
Pb W x BCF x INp x AFF x BKSF xEFxCF
AT
(14.8)
where:
PbB
PbB
adult, central
idult, 0
PbW
BCF
BKSF
central tendency estimate of
PbB concentrations (ug/dL) in adults
exposed to lead in fish at a
concentration of PbW;
typical PbB concentration (ug/dL) in
adults in the absence of exposures via
fish consumption;
in-stream lead concentrations (ug/L);
bioconcentration factor of lead in fish
tissue (L/kg);
biokinetic slope factor relating
(quasi-steady state) increases in
typical adult PbB concentrations to
average daily lead uptake (ug/dL PbB
increase per mg/day lead uptake);
average daily fish consumption
(g/day);
AFB
EF
AT
CF
absolute gastrointestinal absorption
fraction for ingested lead in fish
tissue (dimensionless);
exposure frequency for ingestion of
contaminated fish (days of exposure
during the averaging period); may be
taken as days per year for continuing,
long-term exposure;
averaging time, the total period during
which fish consumption may occur;
365 days/year for continuing long-
term exposure; and
conversion factor (1(T3 kg/g).
Equation 14.8 is recommended for females aged 17 to 45
(U.S. EPA, 1996). Studies of adult males, however,
provided many of the parameters used in the Interim
Guidance. Thus, EPA judged that this model can be
applicable to all adults. Table 14.4 summarizes values for
the model parameters.
Table 14.4: Summary of Parameter Values for Estimating PbB Levels in Adults
Parameter
"bBjKjuito
BKSF
INFtfenwles)
Age 15 -44
Age > 45
INF (males):
Age 15-44
Age > 45
EF
BCF
AFF
Unit
|ig/dL
|ig/dL per
pg/day
g/day
day/yr
L/kg
dimen-
sionless
Value
4.55-3.45
0.4
7.36 109.72
17.78 108.80
15.57 150.20
32.47 165.92
365
49
0.03
Comment
Male adult PbB levels based on NHANES III Phase 2.
Female adult PbB levels based on NHANES III Phase 2 (U.S. EPA, 1996).
Based on analysis of Pocock et al. (1983) and Sherlock et al. (1984) data.
Daily fish consumption; lower value (on left) for recreational anglers and
higher value (on right) for subsistence anglers (U.S. EPA, 1998d).
Days per year for continual long-term exposure.
Bioconcentration factor of lead in fish tissue.
Absolute gastrointestinal absorption fraction for ingested lead in fish
tissue. Based on Maddaloni ( 1998).
For detailed information on the sources of the parameters and uncertainties associated with their use, see U.S. EPA, 1996.
Source: U.S. EPA analysis.
*ป Typical adult PbB concentrations at baseline
Previous research suggests males have a higher background
PbB level (TRW, 1996). This analysis uses population-
specific typical concentrations to account for differences in
background lead exposure between genders and between
two socioeconomic subgroups considered in the analysis
(i.e., recreational and subsistence fishermen). EPA used
data for adult males and females from NHANES III to
characterize the baseline distribution of PbB concentrations
in the relevant subpopulations for each MP&M reach and
affected population. The baseline PbB distribution scenario
reflects site-specific population characteristics because
baseline PbB levels differ across ethnic, income, and urban
status groups.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
ซ> Bioavailability of lead from fish tissue
To identify lead bioavailability in fish tissue, EPA reviewed
lead absorption data from various materials reported in the
leadtoxicity summary document: Toxicity Profile for Lead
(ATSDR, 1997). EPA also reviewed Measurement of
Soil-Borne Lead Bioavailability in Human Adults, and its
Application to Biokinetic Modeling (Maddaloni, 1998) and
consulted with the study author (March, 2000). Numerous
studies have found that lead ingested with food is absorbed
at a significantly lower rate than lead ingested after fasting.
The Interim Guidance reports this dynamic and notes that
"the bioavailability of ingested soluble lead in adults varies
from less than 10 percent when ingested with a meal to
between 60 and 80 percent when ingested after a fast"
(TRW, 1996). TRW uses a 20 percent lead bioavailability
factor for soil. This factor is based on lead consumption
interspersed with and between meals throughout the day,
and is therefore likely to overestimate PbB levels in adults
exposed to lead-contaminated fish. In the absence of data
on lead incorporated into food, however, EPA considered
this to be the most appropriate data to use in estimating
absorption.
In the most recent study reviewed for this analysis
(Maddaloni, 1998), non-fasted subjects showed a mean
percent absorption of 2.52 with a range of 0.2 to 5.2 percent
and a confidence value of 0.66). The male and female study
subjects had normal clinical chemistry parameters and were
between 21 and 40 years of age. The study used soil as the
dosing vehicle. Other studies have used water as the dosing
vehicle, but soil is considered to be more similar to fish
consumption.
EPA selected an absorption value of 3 percent for lead
ingested in fish tissue, based on Maddaloni's results. The
value of 3 percent provides a reasonable estimate for most
adults. This analysis does not address individuals who may
have higher lead absorption, or be at elevated risk due to
lead exposure. These individuals include pregnant women,
who have higher calcium requirements (and are therefore
more likely to be calcium-deficient), people with poor
nutritional status (including iron and calcium deficiencies),
and individuals with other metabolic disorders. By
evaluating subsistence and recreational anglers, the analysis
is already focusing on subpopulations at higher risk than the
average population. To maintain an approach that represents
likely exposures, intakes, and risks, EPA chose not to
consider individuals at unusually high risk within an
already-high risk subpopulation.
14.3.2 Men Health Benefits
This section describes the health effects of reduced lead
exposure that this analysis has quantified for men; the next
section presents a similar discussion for women.
a. Hypertension
ซ> Quantifying the relationship between PbB levels and
hypertension
Studies have linked elevated PbB to elevated BP in adult
males, especially men aged 40 to 59 (Pirkle et al., 1985).
Further studies have demonstrated a dose-response
relationship for hypertension (defined as diastolic BP above
90 mm Hg for this model) in males aged 20 to 74 (Schwartz,
1988). This relationship is:
1
2.744 - .793*(ln PbBJ
1
2.744 - 0.793*(ln/%B,)
(14.9)
where:
APr(HYP)
e
PbBj
PbB,
the change in the probability of
hypertension,
base of the natural logarithm (2.76)
PbB level in the baseline scenario,
and
PbB level in the post-compliance
scenario.
ซ> Valuing reductions in hypertension
The best measure of the social costs of hypertension,
society's WTP to avoid the condition, cannot be quantified
without basic research that is well beyond the scope of this
project. Ideally, the measure would include all the medical
costs associated with treating hypertension, the individual's
WTP to avoid the worry that hypertension could lead to a
stroke or CHD, and the individual's WTP to avoid the
behavioral changes required to reduce the probability that
hypertension leads to a stroke or CHD.
This analysis used recent research results to quantify two
benefit category components: medical costs and lost work
time. Krupnick and Cropper (1989) estimated the medical
costs of hypertension, using data from the National Medical
Care Expenditure Survey (Krupnick and Cropper, 1989).
Medical costs include expenditures for physician care,
drugs, and hospitalization. In addition, hypertensives have
more bed disability days and work-loss days than non-
hypertensives of comparable age and sex. Krupnick and
Cropper estimated the increase in work-loss days at 0.8 per
year. Valuing this estimate at the estimated mean daily wage
rate and adjusting the costs to 1999 dollars yields an
estimate of the annual cost of each case of hypertension of
$1,048.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
The benefits estimate in this analysis likely underestimates
the true social benefit of avoiding a case of hypertension for
several reasons:
* It does not include a measure of the value of pain,
suffering, and stress associated with hypertension;
> It does not value the direct costs (out-of-pocket
expenses) of diet and behavior modification (e.g.,
salt-free diets, etc.). These costs, which are typical
for severe modifications, are likely to be
significant;
* This analysis does not address the loss of
satisfaction associated with the diet and behavior
modifications;
* This analysis does not include the value of avoiding
side effects associated with the medication for
hypertension, which include drowsiness, nausea,
vomiting, anemia, impotence, cancer, and
depression; and
> The analysis does not include the effects of the
disease on family members.
b. Changes in CHD
ซ> Quantifying the relationship between PbB andBP
EPA quantified the effect of changes in PbB levels on
changes in BP to predict the probability of both
hypertension and other cardiovascular illnesses, such as
CHD, strokes, and premature mortality. Several
cardiovascular illnesses include PbB as a risk factor
(Shurtleff, 1974; McGee and Gordon, 1976; PPRG, 1978).
Based on the results of a meta-analysis of several studies,
Schwartz (1992a) estimated a relationship between a change
in BP associated with a decrease in PbB from 10 ug/dL to 5
ug/dL. The following equation uses the coefficient reported
by Schwartz to relate BP to PbB for men:
= 1.4 X
PbB,
(14.10)
where:
ADBP,,
PbBj
PbB,
the change in men's diastolic BP
expected from a change in PbB;
PbB level in the baseline scenario (in
ug/dL); and
PbB level in the post-compliance
scenario (in ug/dL).
EPA used this PbB to BP relationship to estimate the
incidence of initial CHD, strokes (BI and initial CB A), and
premature mortality in men.
ซ> Quantifying the relationship between BP and CHD
This analysis used estimated BP changes to predict the
increased probability of initial CHD and stroke occurrence
(U.S. EPA, 1987). Increased BP also increases the
probability of CHD and stroke recurrence, but EPA did not
quantify these relationships in this analysis. An equation
with different coefficients for each of three age groups can
predict first-time CHD events in men. A 1978 study by the
PPRG supplied information for men between ages 40 and 59
(PPRG, 1978). PPRG used a multivariate model
(controlling for smoking and serum cholesterol) relating the
probability of CHD to BP. The model used data from five
different epidemiological studies. The equation for the
change in 10-year probability of a first-time occurrence of
CHD related to an increase in BP is:
0-59^
1
1 + e
4.996 - 0.030365*DBP
1
1 + e
4.996 - 0.030365*DBP2
(14.11)
where:
APr(CH D40.59)
DBPj
DBP2
the change in 10-year probability
of an occurrence of a CHD event
for men between ages 40 and 59;
mean diastolic BP in the baseline
scenario. Based on the Phase 2
NHANES III, mean diastolic BP
for subsistence and recreational
fishermen aged 40 to 59 is 81.8
and 80.0, respectively; and
mean diastolic BP in the post-
compliance scenario.
Information presented in Shurtleff (1974) helped define the
relationship between BP and first-time CHD in older men.
This study used data from the Framingham Study (McGee
and Gordon, 1976) to estimate univariate relationships
between BP and a variety of health effects, by sex and for
three age ranges: 45 to 54, 55 to 64, and 65 to 74 years. The
study performed single composite analyses for ages 45 to 74
for each sex. For every equation, t-statistics on the BP
variable are significant at the 99th percent confidence
interval. EPA predicted first-time CHD related to an
increase in BP for men aged 60 to 64 from the following
equation:
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
1
1
1 + e
5.19676 - 0.02351 *DBP
1 + e
5.19676 - 0.02351
(14.12)
where:
APr(CHD60.64)
the change in 2-year probability
of occurrence of a CHD event for
men aged 60 to 64;
mean diastolic BP in the baseline
scenario; based on the Phase 2
NHANES III, mean diastolic BP
for subsistence and recreational
DBP2
fishermen aged 60 to 64 is 79.5
and 77.8, respectively; and
mean diastolic BP in the post-
compliance scenario.
The following equation uses data from Shurtleff (1974) to
predict the probability of first-time CHD related to an
increase in BP for men aged 65 to 74:
1
1
1 + e
4.90723 - 0.02031 *DBP
1 + e
4.90723 - 0.02031
(14.13)
where:
APr(CHD65.74)
DBPj
DBP2
the change in 2-year probability
of occurrence of a CHD event for
men aged 65 to 74;
mean diastolic BP in the baseline
scenario; based on the Phase 2
NHANES III, mean diastolic BP
for subsistence and recreational
fishermen aged 65 to 74 is 79.5
and 76.4, respectively; and
mean diastolic BP in the post-
compliance scenario.
EPA used the above equations to estimate the number of
CHD events avoided in a given year due to water quality
improvements from reduced MP&M lead discharges. The
resulting CHD incidence estimates include both fatal and
non-fatal events. Only the non-fatal CHD events are
considered here because mortality benefits are estimated
independently in this analysis (see Section 14.3.2.d, below).
Shurtleff (1974) reported that two-thirds of all CHD events
were non-fatal. This factor was therefore applied to the
estimate of avoided CHD events due to reductions in PbB
and BP for each age category.
ซ> Valuing reductions in CHD events
EPA first estimated the number of CHD events avoided each
year by multiplying the number of exposed recreational and
subsistence anglers in the relevant age group by the change
in annual probability of a CHD event. Changes in annual
probability of CHD events for different age groups are
calculated by dividing the change in probability over ten-
and two-year periods by the relevant number of years.
EPA then used the central tendency estimate of the COI
associated with pollution-related CHD to estimate the
benefits of avoiding an initial CHD event. The cost
estimates (Wittels et al., 1990) represent the weighted
medical costs of three separate CHDs (acute myocardial
infarction, uncomplicated angina pectoris, unstable angina
pectoris), experienced within five years of diagnosis. EPA
estimated the costs by multiplying the probability of a
medical test or treatment (within five years of the initial
CHD event) by the estimated price of the test or treatment.12
EPA then calculated the final cost estimate by taking the
simple average of the three CHD types. EPA used a three
percent discount rate to calculate the present value of these
costs. The central tendency estimate of the COI associated
with a case of pollution-related CHD is about $58,043
(1999$).
This estimate likely underestimates the full COI because it
does not include lost earnings. It likely underestimates total
WTP to avoid CHD to an even greater extent because it does
not include WTP to avoid the pain and suffering associated
with the CHD event.
This analysis combined the value of reducing CHD events
with the value of reducing hypertension, even though these
conditions often occur together. The two values represent
different costs associated with the conditions. The valuation
for hypertension includes hypertension-associated work day
loss and medical costs. CHD valuation is based on WTP to
avoid the pain and suffering of the CHD itself. EPA
estimated these two values separately and added them
together.
12 EPA obtained costs from Appendix G of the Benefits and
Costs of the Clean Air Act: 1970 to 1990, prepared for U.S.
Congress by U.S. EPA, Office of Air and Radiation, 1997.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
c. Changes in initial CBA and initial BI
ซ> Quantifying the relationship between BP and first-
time stroke
Strokes include two types of health events: initial CBA and
initial BI. The risk of CBA has been quantified for the male
population between 45 and 74 years old (Shurtleff, 1974).
For initial CBA, the equation is:
. 8.58889 - 0.04066*DBP,
1 + e '
1
1 + e
5.58889 - 0.04066*DBP2
(14.14)
where:
APr(CBAmJ=
DBPj
the change in 2-year probability of
CBA in men;
mean diastolic BP in the baseline
scenario; based on the Phase 2
NHANES III, mean diastolic BP for
subsistence and recreational
fishermen aged 45 to 74 is 81.1 and
78.8, respectively; and
DBP2 = mean diastolic BP in the post-
compliance scenario.
For initial BI, the equation is (Pirkle et al., 1985):
1
1 + e
9.9516 - 0.04840*DBP
1
1 + e
9.9516 - 0.04840*DB/>
(14.15)
where:
APr(BImJ
DBF,
the change in 2-year probability of
brain infarction in men;
mean diastolic BP in the baseline
scenario; based on the Phase 2
NHANES III, mean diastolic BP for
subsistence and recreational
fishermen aged 45 to 74 is 81.1 and
78.8, respectively; and
mean diastolic BP in the post-
compliance scenario.
Similar to CHD events, this analysis estimates only non-fatal
strokes to avoid double-counting with premature mortality.
Shurtleff reported that 70 percent of strokes were non-fatal.
EPA applied this factor to the estimates of both CBA and BI
to ensure that the estimate of avoided CBA and BI events
included only non-fatal events (Shurtleff, 1974).
ซ> Valuing reductions in strokes
Similarly to CHD events, EPA first calculates the number of
avoided strokes per year and then uses the estimated lifetime
cost of a stroke to value reductions in strokes. Taylor et al.
estimated the lifetime cost of stroke, including the present
value (in 1990 dollars) of the stream of medical
expenditures and the present discounted value of the stream
of lost earnings, using a five percent discount rate (Taylor et
al., 1996). The estimated expected lifetime cost of a non-
fatal stroke for males aged 45 to 74 is 262,379 (1999$).13
d. Changes in premature mortality
ซ> Quantifying the relationship between BP and
premature mortality
It is well-established that elevated BP increases the
probability of premature death. There are, however, several
underlying conditions that cause elevated BP (e.g.,
cholesterol level). U.S. EPA (1987) used population mean
values for serum cholesterol and smoking to reduce results
from a 12-year follow-up of men aged 40 to 54 in the
Framingham Study (McGee and Gordon, 1976) to an
equation with one explanatory variable (DBF):
13 This analysis used cost estimates from the EPA Cost of
Illness Handbook.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
1
1 + e
5.3158 - 0.03516*DBP,
1
,
1 + e
5.3158 - 0.03516*DB/>
2
(14.16)
where:
APr(MORT40.54) =
DBPj
DBP2
the change in 12-year probability
of death for men aged 40 to 54;
mean diastolic BP in the baseline
scenario; based on the Phase 2
NHANES III, mean diastolic BP
for subsistence and recreational
fishermen aged 40 to 54 is 81.9
and 79.9, respectively; and
mean diastolic BP in the post-
compliance scenario.
This analysis used information from Shurtleff (1974) to
estimate the probability of premature death in men older
than 54 years. The present analysis estimates a two-year
probability based on the Shurtleff study's two-year follow-
up period. EPA predicted mortality for men aged 55 to 64
years old using the following equation:
1
5-64^
1 + e
4.89528 - 0.01866*DBP
1
e
4.89528 - 0.01866*DBP2
(14.17)
where:
APr(MORT55.64) =
the change in two-year
probability of death in men aged
55 to 64;
mean diastolic BP in the baseline
scenario; based on the Phase 2
NHANES III, mean diastolic BP
for subsistence and recreational
DBF,
fishermen aged 55 to 64 is 80.6
and 79.0, respectively; and
mean diastolic BP in the post-
compliance scenario.
Using data from Shurtleff (1974), EPA predicted premature
mortality for men aged 65 to 74 using the following
equation:
5-74^
1
3.05723 - 0.00547*DBP
1
1 + e
3.05723 - 0.00547
(14.18)
where:
APr(MORT65.74)
DBF,
the change in two-year
probability of death in men aged
65 to 74;
mean diastolic BP in the baseline
scenario; based on the Phase 2
NHANES III, mean diastolic BP
for subsistence and recreational
fishermen aged 65 to 74 is 79.5
and 76.4, respectively; and
mean diastolic BP in the post-
compliance scenario.
ซ> Valuing reductions in premature mortality
Similarly to health outcomes discussed in the preceding
sections, EPA first estimated changes in annual probability
of premature mortality for men in different age groups. The
Agency then calculated avoided premature death cases by
multiplying the estimated change in annual probability of
premature mortality by the relevant population. This
analysis uses the $5.8 million (1997$) estimate of the value
of a statistical life saved recommended in the Draft
Guidelines for Preparing Economic Analysis (EPA, 1999b).
This value is based on WTP to avoid the risk of death.
Although the value of avoiding CHD, B A, and BI events is
based on WTP to avoid the pain and suffering of a non-fatal
CHD event, the value of the change in premature mortality is
based on the value of avoiding an event that does end in
death. These two endpoints are therefore additive.
14.3.3 Women Health Benefits
Recently expanded analysis of data from NHANES II by
Schwartz indicates a significant association between PbB
and BP in women (Schwartz, 1990). Another study, by
Rabinowitz et al. (1987), found a small but demonstrable
association between maternal PbB, pregnancy hypertension,
and BP at time of delivery.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
a. Relationship between BP and PbB
Although women are at risk for lead-induced hypertension,
no dose-response function for hypertension in women is
available at this time. Therefore, the Agency did not
quantify changes in risk for lead-induced hypertension in
women for this analysis. This analysis used an adjusted
dose-response function for a change in BP associated with a
decrease in PbB in men (Equation 14.10) to estimate lead-
induced changes in blood pressure in women. Equation
14.19 is used to provide input values for the analyses
discussed in the following sections.
A review of ten published studies examined the effect of
lead exposure on the BP of women, relative to the effect on
men (Schwartz, 1992). All of the reviewed studies included
data for men; some included data for women. Schwartz
used a concordance procedure that combined data from each
study to predict the decrease in diastolic BP associated with
a decrease from 10 ug/dL to 5 ug/dL PbB (Schwartz, 1992).
The results suggest that when PbB is decreased, women
experience a BP change that is 60 percent of the change seen
in men. Equation (14.10) can be rewritten for women as:
where:
= (0-6 x 1.4) x
ADBPwomen
PbB,
PbB,
the change in women's diastolic BP
expected from a change in PbB;
PbB level in the baseline scenario;
and
PbB level in the post-compliance
scenario.
b. Changes in CHD
ซ> Quantifying the relationship between BP and CHD
Elevated BP in women results in the same effects as for men
(CHD, two types of stroke, and premature death). However,
the general relationships between BP and these health
effects are not identical to the dose-response functions
estimated for men. All relationships presented here have
been estimated for women aged 45 to 74 years old using
information from Shurtleff (1974). EPA estimated first-time
CHD related to an increase in BP in women using the
following equation:
PbB,
(14.19)
1
1 + e
6.9401 - 0.03072*DBP
1
1 + e
6.9401 - 0.03072*DBP2
(14.20)
where:
APr(CHDwoir
DBP2
change in 2-year probability of
occurrence of CHD event for
women aged 45-74;
mean diastolic BP in the baseline
scenario; based on the Phase 2
NHANES III, mean diastolic BP
for women in subsistence and
recreational households aged 45
to 74 is 76.5 and 74.8,
respectively; and
mean diastolic BP in the post-
compliance scenario.
EPA estimated non-fatal CHD events by assuming that two-
thirds of all estimated CHD events are not fatal (Shurtleff,
1974).
ซ> Valuing reductions in CHD events
The Agency first calculated the number of avoided CHD
events for women using Equation 14.20. EPA assumed that
values of reducing CHD events for women equal those
calculated for men (above): $58,043 (1999$) per CHD
event.
c. Changes in BI and initial CBA
ซ> Quantifying the relationship between BP and first-
time stroke
EPA predicted the relationship between BP and initial CBA
for women using the following equation:
. 9.07737 - 0.04287*DBP, . 9.07737 - 0.04287'
1 + e ' 1 + e
(14.21)
where:
APr(CAwomen)= change in two-year probability of
cerebrovascular accident in women
aged 45 to 74;
= mean diastolic BP in the baseline
scenario; and
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
DBP2 = mean diastolic BP in the post-
compliance scenario.
The following equation illustrates the relationship between
BI and initial BI in women:
. 10.6716 - 0.0544*DBP,
1 + e '
1
1 + e
10.6716 - 0.0544
(14.22)
where:
APr(BIwomJ =
DBF,
change in 2-year probability of brain
infarction in women aged 45 to 74;
mean diastolic BP in the baseline
scenario; based on the Phase 2
NHANES III, mean diastolic BP for
women in subsistence and recreational
households aged 45 to 74 is 76.5 and
74.8, respectively; and
mean diastolic BP in the post-
compliance scenario.
EPA multiplied the predicted incidences of avoided BI and
CB A by 70 percent to estimate only non-fatal strokes
(Shurtleff, 1974).
ซ> Valuing reductions in strokes
EPA calculated the value of avoiding an initial CB A or an
initial BI for women in the same way as for men (see
above). EPA predicted lead-related stroke for women in the
United States between the ages of 45 and 74, of whom 38.2
percent are aged 45 to 54 and the remaining 61.8 percent are
aged 55-74. Using the gender- and age-specific values in
Taylor et al. (1996), EPA estimated the average value of
avoiding a stroke among women aged 45 to 74 to be about
$196,783 (1999$).
d. Changes in premature mortality
ซ> Quantifying the relationship between BP and
premature mortality
The following equation estimates the risk of premature
mortality in women (Shurtleff, 1974):
1
1 + e
5.40374 - 0.01511 *DBP
1
1 + e
5.40374 - 0.01511 *DBP2
(14.23)
where:
APr(MORTwomen)
DBPj
DBF,
the change in two-year
probability of death for
women aged 45 to 74;
mean diastolic BP in the
baseline scenario; based on
the Phase 2 NHANES III,
mean diastolic BP for
women in subsistence and
recreational households aged
45 to 74 is 76.5 and 74.8,
respectively; and
mean diastolic BP in the
post-compliance scenario.
ซ> Valuing reductions in premature mortality
EPA predicted changes in lead-related premature mortality
for women in the same way as for men (see above). EPA
assumed the value of reducing premature mortality in
women to be equal to that estimated for all premature
mortality, $5.8 million ($1997) per incident (see Section
13.2.1).
14.4 LEAD-RELATED BENEFIT RESULTS
This section describes the estimated benefits of reduced lead
exposure from consumption offish in three populations: (1)
preschool age children, (2) pregnant women, and (3) adult
men and women. Benefit estimates for pregnant women are
presented with those for preschool age children, because the
beneficiaries in this category are children under the age of
one who suffer in utero fetal lead exposure from maternal
lead intake during pregnancy. Benefits for both children and
adults from reduced lead-related health effects due to the
proposed rule are estimated to total $28 million (1999$)
annually.
14.4.1 Preschool Age Children Lead-
Related Benefit Results
EPA estimated the monetary value of health benefits to
children from reduced lead exposure in four categories:
> reduced neo-natal mortality,
* avoided IQ loss,
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
> reduced incidence of IQ below 70, and
> reduced incidence of PbB levels above 20 ug/dL.
Table 14.5 presents estimates of lead-related benefits from
the proposed rule for children for these four categories.
EPA estimated changes in the risk of infant mortality due to
changes in maternal PbB levels during pregnancy. The
proposed rule would reduce the incidence of neonatal
mortality by 1.6 cases annually. EPA estimated the monetary
benefits of reduced neonatal mortality based on the WTP
values for avoiding death. The estimated monetary benefits
to pregnant women and infants are $9.33 million (1997$)
annually.
The proposed rule will avoid the loss of an estimated 489 IQ
points among exposed preschool children. This translates
into $4.9 million (1999$) per year in benefits. The avoided
costs of compensatory education due to reduced incidence of
children with IQ below 70 and PbB levels above 20 ug/dL
equal about $127 thousand. The proposed rule will result in
aggregated lead-related benefits for children of $14.39
million annually. EPA believes that these estimates are
conservative, since this analysis omits other lead-related
impacts, such as the cost of group homes and other special
care facilities. Table 14.1 presents other omitted benefits
categories. Section 14.5 discusses uncertainty and
limitations inherent in this analysis.
14.4.2 Adult Lead-Related Benefit
Results
Table 14.5: National Annual Benefits from
Reduced Lead in Children ( $1999) Proposed Rule
Category
Neonatal Mortality a
Avoided IQ Loss
Reduced IQ < 70
Reduced PbB > 20 pg/L
Total Benefits
Reduced Cases i
or IQ Points i
1.6!
489. l!
1.7!
O.ll
i
Benefit Value
($1999)
$9,331,613
$4,928,514
$126,390
$746
$14,387,263
a. Unlike other benefits in this table, benefits from reduced neonatal
mortality are expressed in 1997 dollars.
Source: U.S. EPA analysis.
EPA estimated benefits to preschool children based on a
dose-response relationship for IQ decrements. The avoided
neurological and cognitive damages are expressed as
changes in overall IQ levels, including reduced incidence of
extremely low IQ scores (<70, or two standard deviations
below the mean) and reduced incidence of PbB levels above
20 ug/dL. The Agency estimated monetary values for
avoided neurological and cognitive damages based on the
impact of an additional IQ point on future earnings and the
value of compensatory education that a lower IQ individual
needs.
As discussed previously, EPA quantified only the lead-
related health effects in adults that relate to lead's effect on
BP. These health effects include increased incidence of
hypertension, initial non-fatal CHD, non-fatal stokes (CBA
and BI), and premature mortality. EPA used COI estimates
(i.e., medical costs and lost work time) to estimate monetary
values for reduced incidence of hypertension, initial CHD,
and strokes. EPA based monetary values for changes in risk
of premature mortality on estimates of the value of a
statistical life saved. The results are conservative estimates,
because this analysis does not include other health effects
associated with elevated BP or with lead. Other effects of
lead in adults can include nervous system disorders, anemia,
and possible cancer effects.
As shown in Table 14.6, the proposed rule would reduce
hypertension by an estimated 960 cases annually among
males, resulting in benefits of approximately $1,005,917
(1999$). The other health effects benefits were estimated
for both males and females. Reducing the incidence of
initial CHD, strokes, and premature mortality would result in
estimated benefits of $114,331, $266,004, and $12.23
million respectively. Overall, adult lead-related benefits are
$13.61 million annually.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
Table 14.6: National Adult Lead Annual Benefits ($1999)
Category
Men i Hypertension
JCHEJ
JCBA
JBI
! Mortality b
Women JCHD
|CBA
iBI
! Mortality b
Age 40-59
Age 60-64
Age 65-74
Age 45-74
Age 45-74
Age 40-54
Age 55-64
Age 65-74
Age 45-74
Age 45-74
Age 45-74
Age 45-74
Total Benefits
Reduced Cases-
959.8;
0.5;
0.3;
0.4;
0.5;
0.3!
0.7;
0.7;
0.3;
0.4;
0.2;
0.1;
0.4;
Proposed Rule0
Mean Value of Benefits
$1,005,917
$38,459
$19,125
$29,700
$135,579
$76,540
$4,055,744
$3,893,977
$1,901,325
$27,047
$33,385
$20,500
$2,377,236
1 $13,614,534
a. National Level Exposed Population:
Hypertension: 428,363 men ages 20 to 74;
CHD, CBA, BI, and mortality: 173,386 men and 192,091 women ages 45-74.
b. Unlike other benefits in this table, mortality is expressed in 1997 dollars.
Source: U.S. EPA analysis.
14.5 LIMITATIONS AND
UNCERTAINTIES
This section discusses limitations and uncertainties in the
lead-related benefits analysis. Developing dose-response
functions depends on relating lead exposure to PbB levels,
then evaluating PbB levels in relation to specific health
outcomes. Quantitative dose-response functions for most
health effects associated with lead exposure currently do not
exist. For this reason, the analysis does not provide a
comprehensive estimate of health benefits from reduced lead
discharges from MP&M facilities.
Table 14.1 summarizes quantified and non-quantified health
effects. Economic research does not always yield a
complete evaluation, even for those effects that can be
quantified. This uncertainly is likely to bias the estimate of
lead-related benefits of the MP&M regulation downward.
The analysis methodologies used here also involve
significant simplifications and uncertainties. Section 13.3
discusses similar limitations and uncertainties associated
with the assessment of risk associated with non-lead-related
human health hazards and the possible direction of bias
associated with sample design and benefits analysis by:
> occurrence location,
> estimated in-waterway concentrations of MP&M
pollutants, and
> estimated exposed fishing population.
The next five sections discuss other omissions, biases, and
uncertainties in the lead-benefit analysis. Table 14.7
provides a summary of this discussion.
14.5.1 Excluding Older Children
Recent research on brain development among 10- to 18-
year-old children shows unanticipated and substantial
growth in brain development, mainly in the early teenage
years (Giedd et al, 1999). This growth appears to be a
second "burst" of cell development in some brain areas, in
addition to the previously recognized period of rapid growth
during early childhood. One of lead's fundamental effects is
to disrupt the protective coating (myelin) on nerve cells.
This disruption can lead to permanent impairment if it
occurs during development. New research suggests that
older children may be a hypersensitive subpopulation, along
with children aged 0 to 6. Excluding this subpopulation
from the analysis may significantly underestimate benefits
from reduced lead discharges.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
14.5.2 Compensatory Education Costs
This analysis assumes that compensatory education is
required only for children with IQs less than 70, and that
part-time special education costs are assumed to be incurred
only from grades 1 through 12 (Section 14.2.4). This
assumption underestimates compensatory education costs
for the following reasons:
> Children with IQ scores between 70 and 85 will
likely be assigned to special education or "slow"
classes that will likely be smaller than regular
classes and require more teacher attention.
Children in this IQ range may frequently require
more than 12 years to graduate and are more likely
to drop out of school. Such children therefore
require additional education costs.
* Compensatory education may begin before grade
one. Some states (e.g., Connecticut) offer
compensatory education programs for
disadvantaged children beginning at age three.
> This analysis is based on a study that measured the
increased cost to educate children with low IQs
attending a regular school, not a special education
program (Kakalik et al., 1981). The cost to attend a
special education program is generally much higher
than that for regular schooling.
14.5.3 Dose-Response Relationships
The dose-response functions described for each health
outcome considered above generally quantify the adverse
health effects expected from increased lead exposure. For
children, these effects are defined in terms of changes in
PbB. For adults, these effects are estimated in terms of
changes in BP, which are in turn related to changes in PbB
levels. Uncertainty is inherent in the dose-response
functions, which are typically expressed in terms of the
standard deviations of the dose-response coefficients used in
the analysis. Any uncertainty affecting the dose-response
coefficients will also indirectly affect the accuracy of this
analysis.
14.5.4 Absorption Function for Ingested
Lead in Fish Tissue
Numerous research groups have evaluated lead absorption
under a variety of conditions. ATSDR reports a range of 3
percent to 45 percent in the studies they present, which
consider lead intake with and without food (ATSDR, 1997).
Absorption appears to be affected by total lead intake, with
some studies showing a higher absorption proportion with
higher doses. Animal studies show a saturation effect,
which modifies absorption.
Lead's chemical form also determines its absorption rate.
For example, lead sulfide has approximately 10 percent the
bioavailability of lead acetate (ATSDR, 1997). Particle size,
solubility, and lead's chemical form are also important
absorption factors. EPA could not obtain data to describe
lead's precise chemical form, particle size, and other
physical parameters in fish tissue, which would allow more
refined absorption estimates. These characteristics vary
because MP&M facilities produce lead using different
processes and release it in different forms.
An individual's nutritional status also affects lead
absorption rates. People who are malnourished, particularly
with respect to calcium and iron, have high absorption rates
(ATSDR, 1997). EPA assumed that anglers were not
malnourished, and made no adjustment for their nutritional
status. See the section on lead absorption in Maddaloni,
(1998) for a discussion of factors influencing absorption. In
the absence of data on lead incorporated into food, EPA
considered data from studies of lead absorption during meals
to be the most appropriate data to use in estimating
absorption.
14.5.5 Economic Valuation
This analysis used IQ differentials to represent cognitive
damage to children resulting from lead exposure. The
economic analysis relates IQ level to annual earnings, which
serve as the basis for valuing benefits from reduced lead
exposure. IQ differentials are used rather than WTP, the
preferred measure to use, because WTP values to avoid
cognitive damage are not available. This analysis likely
underestimates the value of an IQ point because special
education and lost wages form only a portion of the costs
associated with lost cognitive functioning. A simple IQ
change analysis does not capture all the ways in which a
child, family, and society are affected by the effects of lead-
induced cognitive damage.
Dollar values associated with most of the adult health and
welfare endpoints represent only some components of
society's WTP to avoid these health effects. EPA used COI
estimates to value reductions in CHD events, strokes, and
hypertension. These values are likely to be downward-
biased because the value of pain and suffering avoided is not
included. Employed alone, these monetized effects will
underestimate society's WTP.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
Table 14.7
Omissions/Biases/
Uncertainties
Excluding older children
Compensatory education
costs
Dose-response relationship
Absorption factor for lead in
fish tissue
Economic valuation
Overall impact
': Key Omissions, E
Directional
Impact on
Benefits
Estimates
downward
downward
uncertain
uncertain
downward
downward
liases, and Uncertainties in the Lead -Benefit Analysis
Comments
New research suggests that older children may be a hypersensitive
subpopulation, as children aged 0 to 6 are now considered. Excluding this
subpopulation from the analysis may significantly underestimate benefits from
reduced lead discharges.
Assuming that compensatory education is required only for children with IQs
less than 70 and that part-time special education costs are assumed to be incurred
from grades 1 through 12 underestimates the special education costs because:
> Children with IQ scores between 70 and 85 will likely be assigned to
special education or "slow" classes, requiring more teacher attention,
and taking longer to graduate or dropping out altogether.
> Compensatory education may begin before grade one.
> The cost to attend a special education program is generally much
higher than that for regular schooling.
Uncertainty is inherent in the dose-response functions (expressed in changes in
PbB for children, changes in BP for adults). Any uncertainty affecting the dose-
response coefficients will also indirectly affect the accuracy of this analysis.
Absorption rate appears to be affected by:
> Total lead intake, with some studies showing a higher absorption
proportion with higher doses.
> Lead's chemical form. Because MP&M facilities produce lead using
different processes and release it in different forms, EPA could not
obtain data to describe lead's precise chemical form, particle size, and
other physical parameters in fish tissue, which would allow more
refined absorption estimates.
> An individual's nutritional status.
> Time of lead ingestion. In the absence of data on lead incorporated
into food, EPA considered data from studies of lead absorption during
meals to be the most appropriate data to use in estimating absorption.
The values associated with cognitive damage to children and adult health effects
are likely to be downward-biased. For children, a simple IQ change analysis
does not capture all effects of lead-induced IQ loss on a child, family, and
society. The valuation of adult's health effects from lead exposure do not
include the value of avoided pain and suffering. Employed alone, these
monetized effects will underestimate society's WTP.
Source: U.S. EPA analysis.
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
GLOSSARY
absolute gastrointestinal absorption fraction: the
fraction of lead in food ingested daily that is absorbed from
the gastrointestinal tract.
acute toxicity: the ability of a substance to cause severe
biological harm or death soon after a single exposure or
dose. Also, any poisonous effect resulting from a single
short-term exposure to a toxic substance (see: chronic
toxicity, toxicity).
(http://www.epa.gov/OCEPAterms/aterms.html)
angina pectoris: a syndrome characterized by
paroxysmal, constricting pain below the sternum, most
easily precipitated by exertion or excitement and caused by
ischemia of the heart muscle, usually due to a coronary
artery disease, as arteriosclerosis, (www.infoplease.com)
arithmetic mean: the mean obtained by adding several
quantities together and dividing the sum by the number of
quantities, (www.infoplease.com)
atherothrombotic brain infarctions (Bl): scientific
name for a stroke.
bioaccumulation factors: the ratio of a substance's
steady-state concentration in the tissue of an aquatic
organism to its steady-state concentration in the ambient
water where both the organism and its food are exposed.
bioavailability: degree of ability to be absorbed and ready
to interact in organism metabolism.
(http://www.epa.gov/OCEP Aterms/bterms.html)
biokinetics: the study of movements of or within
organisms, (www.infoplease.com)
biomarker: a physical, functional, or biochemical
indicator of a certain process or event. It is commonly used
to measure the progress of a disease, the effects of
treatment, or the status of a condition.
blood lead (PbB): concentration level of lead in blood
stream; usually expressed in ug/dL.
central tendency estimate: major trend in group of
data.
cerebrovascular accident (CBA): stroke.
coronary heart disease (CHD): disorder that restricts
blood supply to the heart; occurs when coronary arteries
become narrowed or clogged due to the build up of
cholesterol and fat on the inside walls and are unable supply
enough blood to the heart.
diastolic: pertaining to or produced by diastole, or (of
blood pressure) indicating the arterial pressure during the
interval between heartbeats, (www.infoplease.com)
discounting: degree to which future dollars are
discounted relative to current dollars. Economic analysis
generally assumes that a given unit of benefit or cost matters
more if it is experienced now that if it occurs in the future.
The present is more important due to impatience,
uncertainty, and the productivity of capital. This analysis
uses a three percent discount rate to discount future benefits.
(http://www.damagevaluation.com/glossary)
dose-response functions: see dose-response
relationship.
dose response: shifts in lexicological responses of an
individual (such as alterations in severity) or populations
(such as alterations in incidence) that are related to changes
in the dose of any given substance.
dose-response assessment: 1. Estimating the potency
of a chemical. 2. In exposure assessment, the process of
determining the relationship between the dose of a stressor
and a specific biological response. 3. Evaluating the
quantitative relationship between dose and toxicological
responses.
dose response curve: graphical representation of the
relationship between the dose of a stressor and the biological
response thereto.
dose-response relationship: the quantitative
relationship between the amount of exposure to a substance
and the extent of toxic injury or disease produced.
(http://www.epa.gov/OCEPAterms/dterms.html)
encephalopathy: any brain disease.
(www.infoplease.com)
GDP price deflator: measure of the percentage increase
in the average price of products in GDP over a certain base
year published by the Commerce Department.
(http://www.damagevaluation.com/glossary.htm)
genotoxic: may cause chromosomal damage in humans
leading to birth defects.
geometric mean (GM): for a set of n numbers {xb x2, x3,
..., x,,} it is the n-th root of their product: (Xj x X2 x X3 ...
geometric standard deviation (GSD): is a measure of
the inter-individual variability in blood lead concentrations
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
in a population whose members are exposed to the same
environmental lead levels. For a lognormal distribution,
GSD is the exponential of the standard deviation of the
associated normal distribution.
half-life: time required for a living tissue, organ, or
organism to eliminate one-half of a substance which has
been introduced into it.
health endpoints: An observable or measurable
biological event or chemical concentration (e.g., metabolite
concentration in a target tissue) used as an index of an effect
of a chemical exposure.
heme synthesis: creation of heme; an iron compound of
protoporphyrin which constitutes the pigment portion or
protein-free part of the hemoglobin molecule and is
responsible for its oxygen-carrying properties.
Integrated Exposure, Uptake, and Biokinetics
(IEUBK): the IEUBK model is an exposure-response
model that uses children's environmental lead exposure to
estimate risk of elevated blood lead (typically> 10 ug/dL)
through estimation of lead body burdens in mass balance
framework.
least-squares regression: a tool of regression analysis
that computes a best-fit line to represent the relationship
between two (or more) variables based on the principle that
the squared deviations of the observed points from that line
are minimized (see also: regression analysis).
In: natural logarithm.
lognormal distribution: a distribution of a random
variable for which the logarithm of the variable has a normal
distribution, (www.infoplease.com)
lognormally-distributed random variable: same as
lognormal distribution.
marginal cost: the increase in total costs as one more unit
is produced.
(http://www.damagevaluation.com/glossary.htm)
probit regression: a regression model, where the
dependent variable is set up as a 0-1 dummy variable and
regressed on the explanatory variables. The predicted value
of the dependent variable could be interpreted as the
probability that a certain event will take place (e.g., an
individual will buy a car, visit a particular location, or get a
specific disease.)
multivariate: (of a combined distribution) having more
than one variate or variable, (www.infoplease.com)
nephropathy: any kidney disease.
(www.infoplease.com)
neurobehavioral deficits: neurologic effects as assessed
by observation of behavior. These effects may include
behavioral and attentional difficulties, delayed mental
development, lack of motor and perceptual skills, and
hyperactivity.
neurobehavioral function: see neurobehavioral deficits.
normal distribution: a random variable X is normally
distributed if its density is given by fx (x) = f (x; u, 6), where
H and 6 are the mean and the variance of the distribution.
opportunity costs: the highest-valued sacrifice needed to
get a good or service.
(http://www.damagevaluation.com/glossary.htm)
p-value: the probability of obtaining a given outcome due
to chance alone. For example, a study result with a
significance level of p<0.05 implies that 5 times out of 100
the result could have occurred by chance.
(http://www.teleport.com/~celinec/glossary.htm)
pharmacokinetics: the study of the way drugs move
through the body after they are swallowed or injected.
(http://www.epa.gov/OCEPAterms/pterms.html)
probability distribution: a distribution of all possible
values of a random variable together with an indication of
their probabilities, (www.infoplease.com)
quasi-steady state: almost not changing state.
regression analysis: a procedure for determining a
relationship between a dependent variable, such as predicted
success in college, and an independent variable, such as a
score on a scholastic aptitude test, for a given population.
The relationship is expressed as an equation for a line.
(www.infoplease.com)
risk-based remediation goals (RBRG): target human
health and environmental risk levels to be achieved via
remedial actions at Superfund sites.
systemic health risks: health risks pertaining to or
affecting the body as a whole.
Technical Review Workgroup (TRW): a workgroup
formed in 1994 to evaluate methodologies for adult lead risk
assessment.
ug/L: microgram per liter
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MP&M EEBA Part III: Benefits Chapter 14: Lead-Related Benefits
/jg/dL: microgram per decaliter one would give up to buy some good.
(http://www.damagevaluation.com/glossary.htm)
willingness to pay (WTP): maximum amount of money
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MP&M EEBA Part III: Benefits
Chapter 14: Lead-Related Benefits
ACRONYMS
ATSDR: Agency for Toxic Substances and Disease
Registry
Bl: atherothrombotic brain infarction
BP: blood pressure
CARB: California Air Resources Board
CBA: cerebrovascular accidents
CDC: Centers for Disease Control
CEPA: California Environmental Protection Agency
CHD: coronary heart disease
COI: cost of illness
GM: geometric mean
GSD: geometric standard deviation
IEUBK: Integrated Exposure, Uptake, and Biokinetics
NCHS: CDC's National Center for Health Statistics
NHANES: National Health and Nutrition Examination
Surveys
NLSY: National Longitudinal Survey of Youth
PbB: blood lead
PCS: Permit Compliance System
PPRG: Pooling Project Research Group
RBRG: risk-based remediation goals
TRW: Technical Review Workgroup
WTP: willingness to pay
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MP&M EEBA Part III: Benefits Chapter 14: Lead-Related Benefits
REFERENCES
ATSDR (Agency for Toxic Substances and Disease Registry). 1997. Draft lexicological profile for lead. Atlanta, GA.
CARB (California Air Resource Board). 1996. Draft summary of lead and lead compounds. Proposed Identification of
Inorganic Lead as a Toxic Air Contaminant, Part B: Health Assessment. Draft SRP Version, CA EPA. September.
Centers for Disease Control (CDC). 1991a. Strategic Plan for Elimination of Childhood Lead Poisoning. U.S. Department
of Health and Human Services, Public Health Service, Centers for Disease Control, Atlanta, GA. February.
Centers for Disease Control (CDC). 1991b. Preventing Lead Poisoning in Young Children. U.S. Department of Health and
Human Services, Public Health Service, Centers for Disease Control, Atlanta, GA. October.
Dietrich, K.N., K.M. Krafft, R. Shukla, R.L. Bornschein, and P.A. Succop. 1987. The Neurobehavioral Effects of Prenatal
and Early Postnatal Lead Exposure. In: Toxic Substances and Mental Retardation: Neurobehavioral Toxicology and
Teratology, S.R. Schroeder, Ed. American Association of Mental Deficiency, Washington, DC, pp. 71-95 (Monograph
No. 8).
Giedd, J.N., L. Blumenthal, N.O. Jeffries, F.X. Castellanes, Hong Liu, A. Zijdenbos, Tomas Paus, Alan C. Evans, and J.
Rapoport. 1999. Brain Development During Childhood and Adolescence: A Longitudinal MRI Study. Nature
Neuroscience, Vol. 2, No. 10, pp. 861-863, October.
Kakalik, J., et al. 1981. The Cost of Special Education. Rand Corporation Report N-1791-ED.
Krupnick, A.J. andM.L. Cropper. 1989. ValuingChronicMorbidity Damages: Medical Costs and Labor Market Effects.
Draft Final Report to U.S. Environmental Protection Agency, Office of Policy Planning and Evaluation. June 26.
Lewit, E.M., L Schuurmann Baker, Hope Gorman, and Patricia H. Shiono. 1995. "The Direct Cost of Low Birth Weight."
The Future of Children Vol 5, No 1, Spring.
Maddaloni, M. A. 1998. Measurement of Soil-Borne Lead Bioavailability in Human Adults, and Its Application in
Biokinetic Modeling. Ph.D. Dissertation. School of Public Health, Columbia University, New York.
McGee and Gordon. 1976. The Results of the Framingham Study Applied to Four Other U.S.-based Epidemiologic Studies
of Coronary Heart Disease. The Framingham Study: An Epidemiological Investigation of Cardiovascular Disease. Section
31, April.
Needleman, H.L., Riess, Y.A., Tobin, M.D., Biesecar, G.E., Greenhouse, J.B. 1996. Bone Lead Levels and Delinquent
Behavior. Journal of the American Medical Association, Vol. 275, No. 5, February 7.
NHANES III, Phase 2, National Health and Nutrition Examination Survey, 1991-1994.
Piomelli et al. 1984. "Management of Childhood Lead Poisoning." Pediatrics 4: 105.
Pirkle, J.L., J. Schwartz, J.R. Landis, and W.R. Harlan. 1985. "The Relationship Between Blood Lead Levels and Blood
Pressure and its Cardiovascular Risk Implications." American Journal of Epidemiology 121: 246-258.
Pirkle, J. L., et al. 1994. "Decline in Blood Lead Levels in the United States, the National Health and Nutrition Examination
Survey (NHANES)." JAMA 272(4): 284.
Pocock, S.J., A.G. Shaper, M. Walker, C.J. Wale, B Clayton, T. Delves, R.F. Lacey, R.F. Packham, and P. Powell. 1983.
"Effects of Tap Water Lead, Water Hardness, Alcohol, and Cigarettes on Blood Lead Concentrations." J. Epidemiol.
Commun. Health. 37: 1-7.
14-32
-------
MP&M EEBA Part III: Benefits Chapter 14: Lead-Related Benefits
Pooling Project Research Group (PPRG). 1978. "Relationship of Blood Pressure, Serum Cholesterol, Smoking Habit,
Relative Weight and ECG Abnormalities to Incidence of Major Coronary Events: Final Report of the Pooling Project."
Journal of Chronic Disease. Vol. 31.
Rabinowitz, M, D. Bellinger, A. Leviton, H. Needleman, and S. Schoenbaum. 1987. "Pregnancy Hypertension, Blood
Pressure During Labor, and Blood Lead Levels." Hypertension 10(4): October.
Salkever, D.S. 1995. "Updated Estimates of Earnings Benefits from Reduced Exposure of Children to Environmental
Lead." Environmental Research 70: 1-6.
Schwartz, J. 1988. "The Relationship Between Blood Lead and Blood Pressure in the NHANES II Survey." Environmental
Health Perspectives. 78: 15-22.
Schwartz,!. 1990. "Lead, Blood Pressure, and Cardiovascular Disease in Men and Women." Environmental Health
Perspectives, in press.
Schwartz,! 1992. "Chapter 13: Lead, Blood Pressure and Cardiovascular Disease." In H. L. Needleman, &A., Human
Lead Exposure. CRC Press.
Schwartz, J. 1993. "Beyond LOEL's, p Values, and Vote Counting: Methods for Looking at the Shapes and Strengths of
Associations." Neurotoxicology 14(2/3): October.
Schwartz, J. 1994. "Low-level Lead Exposure and Children's IQ: A Meta-analysis and Search for a Threshold."
Environmental Research 65: 42-55.
Sherlock, J.C., D. Ashby, H.T. Delves, G.I. Forbes, M. R. Moore, W. J. Patterson, S.J. Pocock, MJ. Quinn, W. N. Richards
and T.S. Wilson. 1984. "Reduction in Exposure to Lead from Drinking Water and Its Effect on Blood Lead
Concentrations." Human Toxicology. 3: 183-392.
Shurtleff, D. 1974. Some Characteristics Related to the Incidence of Cardiovascular Disease and Death. The Framingham
Study: An Epidemiological Investigation of Cardiovascular Disease. Section 30, February.
Silbergeld, E.K., J. Schwartz, and K. Mahaffey. 1988. "Lead and Osteoporosis: Mobilization of Lead from Bone in
Postmenopausal Women." Environmental Research 47: 79-94.
Taylor, T.N., P.H. Davis, J.C. Torner, J. Holmes, J.W. Meyer, and M. F. Jacobson. 1996. "Lifetime Cost of Stroke in the
United States." Stroke 27(9): 1459-1466.
U.S. Department of Commerce, Bureau of the Census. 1993. "Money Income of Households, Families, and Persons in the
United States: 1992," Current Population Reports, Consumer Income, Series P60-184, Washington, D.C..
U.S. Department of Housing and Urban Development. 1995. "The Relation of Lead Contaminated House Dust and Blood
Lead Levels Among Urban Children. Vol. I and II. Final Report to the U.S. Department of Housing and Urban
Development. Grant from the University of Rochester School of Medicine, Rochester, NY, and the National Center for
Lead-Safe Housing, Columbia, MD.
U.S. Environmental Protection Agency (U.S. EPA). 1985. Costs and Benefits of Reducing Lead in Gasoline: Final
Regulatory Impact Analysis. Prepared by U.S. Environmental Protection Agency, Office of Policy Analysis, Economic
Analysis Division. February.
U.S. Environmental Protection Agency (U.S. EPA). 1986a. Reducing Lead in Drinking Water: A Benefit Analysis.
Prepared by U.S. Environmental Protection Agency, Office of Policy Planning and Evaluation, Draft Final Report.
December.
U.S. Environmental Protection Agency (U.S. EPA). 1986b. Air Quality Criteria for Lead: Volume III. Environmental
Criteria and Assessment Office, Research Triangle Park, NC. EPA-600/8-83/028cF. June.
14-33
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U.S. Environmental Protection Agency (U.S. EPA). 1989. Air Quality Criteria Document for Lead: 1989 Addendum.
U.S. Environmental Protection Agency (U.S. EPA). 1987. Methodology for Valuing Health Risks of Ambient Lead
Exposure. Prepared by Mathtech, Inc. for U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards, Ambient Standards Branch, Contract No. 68-02-4323.
U.S. Environmental Protection Agency (U.S. EPA). 1990. Review of the National Ambient Air Quality Standards for Lead:
Assessment of Scientific and Technical Information. OAQPS Staff Paper, Air Quality Management Division, Research
Triangle Park, NC. December.
U.S. Environmental Protection Agency (U.S. EPA). 1994. Guidance Manual for the Integrated Exposure Uptake Biokinetic
Model for Lead in Children. February. EPA 540-R-93-081, PB 93-963510.
U.S. Environmental Protection Agency (U.S. EPA). 1995. "Technical Support Document: Parameters and Equations Used
in the IEUBK Model for Lead in Children." EPA 540-R-94-040.
U.S. Environmental Protection Agency (U.S. EPA). 1996. Recommendations of the Technical Review Workgroup for Lead
for an Interim Approach to Assessing Risks Associated with Adult Exposures to Lead in Soil. EPA, Technical Review
Workgroup for Lead, December 1996, pp. A16 - A17.
U.S. Environmental Protection Agency (U.S. EPA). 1997. The Benefits and Costs of the Clean Air Act: 1970 to 1990.
EPA 410-R-97-002, October, 1997. U.S. EPA, Office of Air and Radiation, Appendix G: Lead Benefits Analysis.
U.S. Environmental Protection Agency (U.S. EPA). 1998a. Economic Analysis of Toxic Substances Control Act Section
403: Hazard Standards. Prepared for EPA by Abt Associates Inc., May 1998.
U.S. Environmental Protection Agency (U.S. EPA). 1998b. Risk Analysis to Support Standards for Lead in Paint, Dust and
Soil. EPA/OPPT 747-R-97-006, Washington, D.C., June 1998.
U.S. Environmental Protection Agency (U.S. EPA). 1998c. Lead; Identification of Dangerous Levels of Lead; Proposed
Rule. Federal Register June 3, 1998, pp. 30302-30355
U.S. Environmental Protection Agency (U.S. EPA). 1998d. Daily Average per Capita Fish Consumption Estimates Based
on the Combined USD A 1988, 1990, and 1991 Continuing Survey of Food by Individuals (CSF II), Volumes I and II,
March.
U.S. Environmental Protection Agency (U.S. EPA). 1999a. Cost of Illness Handbook (Draft). OPPT, Washington, D.C.
U.S. EPA. 1999b. Guidelines for Preparing Economic Analysis. Draft report. Washington, DC: U.S. EPA.
Wittels, E.H., J.W. Hay, and A.M. Gotto, Jr. 1990. "Medical Costs of Coronary Artery Disease in the United States," The
American Journal of Cardiology 65: 432-440.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
Chapter 15: Recreational Benefits
INTRODUCTION
The proposed MP&M regulation will provide recreational
and nonuse benefits by reducing effluent discharges and
improving habitats or ecosystems (aquatic and terrestrial)
used for recreational activities. EPA estimated national
recreational benefits for three activities:
* recreational fishing,
> wildlife viewing, and
* recreational boating.
The analysis of recreational benefits presented in this
chapter uses the National Demand Study (NDS) data to
estimate the number of participants in wildlife viewing, and
boating in the counties affected by MP&M discharges. To
estimate the number of recreational fishermen, EPA used
fishing license data. The NDS survey asked respondents to
report the number of recreational trips taken annually for
the primary purpose of boating and wildlife viewing.
Additional information on the NDS survey can be found in
Chapter 21. Appendix H provides information on the
number of participants and the number of recreational trips
taken annually by state and activity type.
Recreational trips corresponding to fishing, boating, and
wildlife viewing considered in this analysis are
stochastically independent (i.e., only the primary activity is
counted on each trip occasion). Benefits from improved
recreational opportunities corresponding to these activities
are therefore additive.
EPA chose to use fish license data rather than the NDS data
to estimate the number of recreational anglers fishing the
MP&M reaches because these data are often available at the
county level and therefore provide location-specific
information. Although the use of the NDS and fish license
data yields similar estimates of the number of recreational
anglers at the state level (see Chapter 20) fish license data
are likely to be more accurate at the county level. The use
of the fish license data in the recreational fishing benefit
analysis also provides consistency with other parts of the
benefits analysis ( see Chapters 13 and 14 for detail).
This chapter also presents an estimate of nonuse benefits.
People who do not use or expect to use affected waterways
for recreational or other purposes may still value protecting
habitats and species impacted by effluent discharges.
CHAPTER CONTENTS:
15.1 Improvements from MP&M Regulation 15-2
15.1.1 Ecological Improvements 15-2
15.1.2 Quantification of Ecological Improvements ... 15-3
15.1.3 AWQC Exceedances for Human Health 15-3
15.1.4 Benefiting Reaches 15-3
15.1.5 Geographic Characteristics of Benefiting
Reaches 15-5
15.1.6 Extrapolating Sample-based Results to the
National Level 15-5
15.2 Valuing Economic Recreational Benefits 15-5
15.2.1 Transferring Values from Surface Water
Valuation Studies 15-5
15.2.2 Recreational Fishing 15-8
15.2.3 Wildlife Viewing 15-11
15.2.4 Recreational Boating 15-14
15.2.5 Nonuse Benefits 15-16
15.3 Summary of Recreational Benefits 15-16
15.4 Limitations and Uncertainties Associated with
Estimating Recreational Benefits 15-17
Glossary 15-21
Acronyms 15-22
References 15-23
EPA assessed recreational and nonuse benefits in terms of
reduced occurrences of pollutant concentrations that exceed
chronic and acute toxic effect levels for aquatic species and
human health. The analysis estimated the in-waterway
pollutant concentrations of MP&M facility discharges
for the baseline and the proposed rule. EPA identified those
reaches in which estimated facility discharges would cause
one or more pollutant concentrations to exceed ambient
water quality criteria (AWQC) for aquatic species and
human health.1
AWQC set limits on pollutant concentrations that are
assumed to be protective of aquatic life. Pollutant
concentrations that exceed AWQC can harm organisms that
live in or consume water. MP&M pollutants can also harm
other organisms that consume these organisms. These
organisms at risk include humans who may spend time in or
consume aquatic organisms.
1 For this analysis, a reach is a length of river, shoreline, or
coastline on which a pollutant discharge may be expected to have a
relatively uniform effect on concentrations. The typical length of a
reach in this analysis was five to ten kilometers, although some
were considerably longer.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
An analysis of the effect of the proposed MP&M regulation
on reducing the number of reaches with concentrations in
excess of AWQC provides a quantitative measure of the
improvement in aquatic species habitat expected to result
from the proposed regulation. Elimination of pollutant
concentrations in excess of AWQC will achieve water
quality that is protective of aquatic life and human health.
Reducing concentrations of MP&M pollutants to below
AWQC limits for protection of aquatic species and human
health will generate benefits to users of water resources for
recreation, including fishermen, boaters, and viewers.
Benefits include:
> increased value of the recreational trip or day, and
* increased number of days that consumers of water-
based recreation choose to visit the cleaner
waterways.
EPA estimated national annual recreational use benefits for
three water-based recreation activities (i.e., recreational
fishing, boating, and viewing) and nonuse benefits, but did
not estimate national swimming benefits due to data
limitations.2 EPA estimated the following recreational
benefits of the proposed MP&M rule (1999$):
* Recreational fishing benefits ranging from $ 196 to
$627 million,
> Near-water recreation (viewing) benefits ranging
from $500 to $920 million,
* Boating benefits ranging from $265 to $672
million,
> Nonuse benefits ranging from $240 to $1,464
million.
The total annual recreational benefit is estimated at $1,201
to $3,683 million (1999$), with a midpoint estimate of
$2,281 million (1999$).
Benefit categories examined in this chapter are different
from and generally do not overlap with benefits associated
with reduced risk to human health discussed in Chapter 13.
Nevertheless, there is some likelihood that the valuation of
ecological benefits based on enhanced recreational fishing
overlaps to a degree with the valuation of human health
benefits from reduced cancer risk via fish consumption.
2 Fewer waterbodies are designated for primary contact
recreation such as swimming than for secondary contact recreation
such as boating and fishing. Assessing recreational swimming
benefits requires first obtaining information on designated uses of
the sample MP&M reaches from the 305(b) database. This analysis
was not feasible due to resource and time constraints.
The rest of this chapter reviews the methodology and
findings from the recreational and nonuse benefits analysis
of the MP&M regulation. The methodology for assessing
these benefits involves two elements:
* identifying MP&M discharge reaches expected to
have a reduced occurrence of pollutant
concentrations exceeding AWQC for aquatic
species and human health as a result of the
proposed rule, and
> attaching a monetary value to occurrences of
pollutant concentrations in excess of AWQC.
15.1 IMPROVEMENTS FROM THE MP&M
RESULATION
15.1.1 Ecological Improvements
Many MP&M pollutants can adversely affect the survival,
growth, and reproduction of aquatic organisms. Such
effects are ecologically significant when they affect the size,
structure, or function of populations:
> MP&M pollutants can affect population size by
reducing prey, and by affecting development or
reproduction in sensitive life stages of target
species;
> MP&M pollutants can alter population structure
by impairing sensitive age groups or affecting the
development or maturation rates of target species;
and
> MP&M pollutants can impact population function
by decreasing genetic diversity and changing
interactions among different populations in the
affected areas.
Recreational and nonuse benefits result from ecological
improvements in aquatic habitat and associated changes in
aquatic life. Ecological effects of the proposed MP&M
regulation may include:
> recovery of populations of aquatic species that are
particularly sensitive to MP&M pollutants;
* decreases in noxious algae, which affect the taste
and odor of the receiving waters;
> increases in the concentrations of dissolved
oxygen (DO) in the water column;
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
* improvements in the natural assimilative capacity
of the affected waterways; and
> terrestrial life benefits.
15.1.2 Quantification of Ecological
Improvements
EPA quantified the ecological improvements of the
proposed regulation by comparing estimates of in-waterway
concentrations of pollutants discharged by MP&M facilities
with the estimates of concentrations within AWQC limits
for protection of aquatic species, as required by the
proposed MP&M regulation. Pollutant concentrations in
excess of AWQC limits indicate a significant detriment to
the aquatic species habitat. Eliminating these exceedances
as the result of the MP&M regulation significantly improves
aquatic species habitat.
The analysis estimates in-waterway concentrations for all
MP&M pollutants that may adversely affect aquatic life.
Table E.3 in Appendix E lists the pollutants evaluated in
this analysis and their acute and chronic aquatic life
AWQC. The acute value is the maximum allowable one-
hour average concentration at any time at which aquatic life
can survive. The chronic value is the average concentration
of a toxic pollutant over a four-day period at which aquatic
life is not unacceptably affected. The endpoints of concern
are one or more sublethal responses, such as changes in
reproduction or growth in the affected organisms. The
chronic levels should not be exceeded more than once every
three years. EPA calculated in-waterway concentrations for
acute and chronic exposure and compared the estimated
concentration values to the relevant AWQC limits.
EPA used the mixing and dilution methods outlined in
Appendix E to estimate the in-waterway concentrations
resulting from MP&M facility discharges. Acute and
chronic exposure concentrations for each pollutant are
calculated on the basis of 7Q10 and 1Q10 stream flow rates,
where 7Q10 is the lowest consecutive seven-day average
flow with a recurrence interval of ten years, and 1Q10 is the
lowest one-day average flow with a recurrence interval of
ten years.
EPA estimated baseline discharge values by identifying the
MP&M discharge reaches in which MP&M discharges
alone caused one or more pollutant concentrations to exceed
AWQC limits for aquatic species. If concentrations of all
MP&M pollutants exceeding the limits in the baseline fell
below AWQC limits as a result of the proposed rule, then
aquatic species habitat conditions on that discharge reach
would likely improve significantly as a result of the
proposed regulation. The proposed regulation would result
in partial aquatic habitat improvements if concentrations of
some, but not all, MP&M pollutants fell below their AWQC
limits.
15.1.3 AWQC Exceedances for Human
Health
EPA analyzed recreational benefits of occurrences in which
pollutants exceed AWQC limits for both aquatic life (acute
and chronic) and human health, where human-health AWQC
are established in terms of a pollutant's toxic effects,
including carcinogenic potential. Table E.2 in Appendix E
lists the pollutants evaluated in the human health analysis
and their human health-based AWQC values. The human
health-based values are set at levels to protect human health
through ingestion of water or aquatic organisms. Chapter 13
addresses the impact of the proposed MP&M regulation on
human health, while this chapter addresses the impact of
improved aquatic and human habitats on recreational
benefits.
This chapter evaluates an individuals' willingness to pay
(WTP) to recreate in areas with reduced concentrations of
pollutants affecting aquatic life and human health. Knowing
that the water is cleaner and does not contain any or contains
fewer pollutants that harm humans and aquatic life,
increases individuals enjoyment of their recreational
experience. Recent studies valuing recreational fishing
showed that the value of water resources for recreational
fishing increases as the level of toxic contamination in fish
tissue decreases (Lyke, 1993; Phaneuf et al., 1998; and
Jakusetal. 1997). Increased benefits also come from
knowing there are more fish, larger fish, healthier fish, and
more species present in the water.
Elimination of human health-based AWQC exceedances is
likely to reduce the level of toxic contamination in fish
tissue and therefore to increase the value of fishery
resources. Although EPA estimated the value of reduced
cancer risk from consumption of contaminated fish tissue,
the Agency was unable to estimate the value of reduced
systemic risk from consumption of fish caught in the reaches
affected by MP&M discharges (see Chapter 13). The
recreational benefits analysis presented in the following
sections assumes that some of the value of reduced systemic
health risk is implicitly captured in the increased value of
water resources from reduced occurrence of human health-
based AWQC exceedances.
15.1.4 Benefiting Reaches
EPA identified reaches where it expects the MP&M rule to
eliminate existing AWQC exceedances (hereafter,
benefiting reaches). These receiving waters are likely to
experience significant water quality improvements from
reduced MP&M discharges. This analysis combines two
AWQC calculation procedures:
* concentrations relative to human health AWQC
limits described in Chapter 13, and
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
* concentrations relative to aquatic life AWQC
limits described in the preceding section of this
chapter.
A reach is considered to benefit from the MP&M rule if at
least one AWQC exceedance is eliminated due to reduced
MP&M discharges. This approach differs from some past
approaches where EPA took credit for pollution reductions
only in cases where all AWQC exceedances are eliminated.
EPA believes that the latter approach significantly
underestimates benefits from reduced pollutant discharges.
AWQC are developed on a chemical-by-chemical basis,
however; they are not designed to assess the toxicity of
multiple chemicals. In most cases, the toxicities of
chemicals in a mixture are considered additive (i.e., the total
toxicity is the sum of the toxicities of the individual
chemicals). Total toxicity decreases by the amount of a
chemical removed from the mixture.
Benefits to sensitive aquatic species (i.e., amphibians, fish,
benthic invertebrates, zooplankton) could occur if the
concentration of one chemical fell below its AWQC even
when two or more other chemicals still were at or exceeding
their respective AWQC. The reason is that the total toxic
pressure in the receiving water decreases such that a smaller
fraction of the most sensitive species remain affected. For
example, three chemicals exceeding their chronic AWQC
adversely affected seven percent of all aquatic species in a
receiving water. If certain species are particularly sensitive
to one of the three chemicals, then eliminating the AWQC
exceedance for this chemical would lower the percentage of
sensitive species being adversely affected.
The effects of partially removing AWQC exceedances,
however, are difficult to generalize. The overall
improvement in surface water quality from reduced toxic
loadings will depend on the amount and duration of
exceedances, together with the kinds of chemical(s) that are
removed from the mixture by regulatory action.
Surface water valuation studies show that benefits from
partial improvements are likely to be considerable. For
example, Carson and Mitchell (1993) found that almost nine
out often individuals indicated that "halfway"
improvements are worth the same as a complete
improvement in water quality. The remaining one out of ten
individuals were willing to pay a reduced amount for partial
improvements in water quality.
EPA's analysis indicates that baseline pollutant
concentrations at current industry discharge levels exceed
acute exposure criteria for protection of aquatic species on
878 reaches, and exceed chronic exposure criteria for
protection of aquatic species on 2,466 reaches. EPA
estimates that the proposed rule would eliminate
concentrations in excess of the acute aquatic life exposure
criteria on 775 reaches, and would eliminate concentrations
in excess of the chronic aquatic life exposure criteria on
1,437 reaches. Table 15.1 summarizes these results.
Table 15.1: Estimated MP&M Discharge Reaches with MP&M Pollutant Concentrations in Excess of AWQC
Limits for Protection of Aquatic Species or Human Health
Regulatory
Status
Baseline
Preferred
Option
Number of Reaches with Concentrations
Exceeding AWQC Limits
AWQC Limits for
Aquatic Species
Acute
878
103
Chronic
2,466
1,437
AWQC Limits for Human
Health
H20 and j Organisms
Organisms i Only
10,310 1 192
9,205 1 71
Total Number of
Reaches with
Concentrations
Exceeding AWQC
Limits
10,443
9,258
Number of Benefiting Reaches
All AWQC
Exceedances
Eliminated
1,185
Reaches with
Some Exceedances
Eliminated
1,837
Note: In the baseline, the total number of reaches with concentrations exceeding AWQC limits does not equal the sum of the numbers in the separate analysis
categories because some reaches were estimated to have concentrations in excess of AWQC limits for more than one analysis category.
Source: U.S. Environmental Protection Agency.
Table 15.1 summarizes the number of reaches with
estimated baseline concentrations that exceed AWQC limits
for either human health or aquatic species, and the number
of those reaches where the regulation is estimated to
eliminate or reduce exceedances. The combined analysis
over all AWQC limit categories (i.e., acute and chronic
aquatic life and human health) indicates that MP&M
pollutant concentrations would exceed at least one AWQC
limit on 10,310 reaches as the result of baseline MP&M
discharges. The expected discharge reductions from the
proposed rule eliminate exceedances on 1,185 of these
discharge reaches, leaving 9,258 reaches with concentrations
of one or more pollutants that exceed AWQC limits. Of
these 9,258 reaches, 1,837 reaches will experience partial
water quality improvements.
15-4
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
EPA assigned full benefits in situations where all AWQC
exceedances are eliminated by the regulation and partial
benefits where the rule eliminates one or more, but not all,
AWQC exceedances. EPA calculates partial benefits as the
ratio of the AWQC exceedances removed by reducing
MP&M discharges to the total number of AWQC
exceedances caused by MP&M facilities in the baseline.
For example, if the MP&M rule removes seven out of a total
ten baseline AWQC exceedances on a benefiting reach, the
Agency attributes a 70 percent benefit to the MP&M
regulation, where 100 percent would represent a
"contaminant-free" level.
15.1.5 Geographic Characteristics of
Benefiting Reaches
EPA cannot identify all of the specific reaches affected by
MP&M facilities that reduce discharges under the proposed
rule because location is known only for the facilities
included in the random stratified sample. EPA assumes that
facilities represented by the sample facility have the same
environmental and geographic characteristics that affect
benefits from the proposed rule. These characteristics
include waterbody type and physical characteristics (e.g.,
stream flow conditions), populations residing near the
waterbody, and the number of potential recreational users
affected. Maps presented in Appendix H depict locations of
the discharge reaches estimated to benefit from reduced
sample facility discharges. These maps also show locations
of the sample MP&M facilities and provide information on
populations residing in the counties traversed by benefiting
reaches.
The analysis of the sample reach locations indicates that
reaches estimated to benefit from the proposed regulation
tend to be located in heavily populated areas (see Appendix
H). Approximately 20 percent of the sample benefiting
reaches are located adjacent to counties with populations of
at least one million residents; almost half of the benefiting
reaches are located adjacent to counties with populations of
at least 500 thousand residents. These reaches have a
greater number of potential recreation users than do reaches
in less populated areas. The estimated number of potential
beneficiaries from the proposed regulation is therefore large
(see Section 15.2 for detail).
15.1.6 Extrapolating Sample-based
Results to the National Level
EPA used facility sample weights to extrapolate the
discharge reach analysis findings from sample facility
discharges to national estimates. Where only one facility
discharged to a reach, the number of reaches expected to
benefit at the national level is the sample weight of the
facility. Where more than one sample facility discharged to
a reach, EPA used the differential sample-weighting
technique outlined in Appendix F to extrapolate national
estimates. Section 15.4 discusses limitations and
uncertainties associated with this extrapolation technique.
15.2 VALUING ECONOMIC
RECREATIONAL BENEFITS
The proposed MP&M rule will improve aquatic habitats by
reducing concentrations of priority (i.e., toxic),
nonconventional, and conventional contaminants in
water. These improvements will enhance the quality and
value of water-based recreation, such as fishing, wildlife
viewing, camping, waterfowl hunting, and boating. This
analysis measures the economic benefit of the MP&M
regulation to society by estimating the increased monetary
value of recreational opportunities resulting from water
quality improvements.
This analysis uses benefits transfer to monetize changes
in water resource recreational values for reaches affected by
MP&M discharges.3 The benefits transfer analysis estimates
the total WTP value (including both use and nonuse values)
for improvements in surface water quality. This approach
builds upon an analysis of applicable surface water valuation
literature to estimate recreational benefits from improved
water quality. The analysis estimates economic benefits for
fishing, wildlife viewing, and boating.
15.2.1 Transferring Values from
Surface Water Valuation Studies
EPA identified several surface water evaluation studies that
quantified the effects of water quality improvements on
various water-based recreational activities. The Agency
used the following technical criteria for evaluating study
transferability (Boyle and Bergstrom, 1990):
The environmental change valued at the study site must be
the same as the environmental quality change caused by the
rule (e.g., changes in toxic contamination vs changes in
turbidity);
The populations affected at the study site and at the policy
site must be the same (e.g., recreational users vs nonusers);
> The assignment of property rights at both sites must
lead to the same theoretically appropriate welfare
measure (e.g., willingness to pay vs willingness to
accept compensation).
3 Benefits transfer involves the application of value estimates,
functions, and/or models developed in one context to address a
similar resource valuation question in another context.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
In addition to the above criteria, the Agency considered
authors' recommendations regarding robustness and
theoretical soundness of various estimates.
Existing studies are unlikely to meet all of the above criteria.
Boyle and Bergstrom (1990) reported that most researchers
will likely encounter problems with at least one criterion.
This analysis is no exception. The major limitation in
performing the national analysis is the comparability of the
water quality changes considered in the original studies with
the water quality changes considered in this analysis. These
comparisons are discussed below.
The Agency used eight of the most comparable studies and
calculated the changes in recreation values resulting from
water quality improvements (as a percentage of the baseline
value) implied by those studies. EPA took a simple mean of
upper- and lower-bound estimates from these studies to
derive a range of percentage changes in the water resource
values due to water quality improvements. The studies used
for benefits transfer in the MP&M regulatory analysis
included Lyke (1993), Jakus et al. (1997), Montgomery and
Needelman (1997), Phaneuf et al. (1998), Desvousges et al.
(1987), Lant and Roberts (1990), Farber and Griner (2000),
and Tudor et al. (2000). Appendix I presents WTP values
for various water quality improvements and summarizes
EPA's reasoning for selecting specific WTP estimates for
benefits transfer. Each of the eight studies and the WTP
values selected for benefit transfer are discussed briefly
below.
> Lyke's (1993) study of the Wisconsin Great Lakes
open water sport fishery showed that anglers may
place a significantly higher value on a contaminant-
free fishery than on one with some level of
contamination. Lyke estimated the value of the
fishery to Great Lakes trout and salmon anglers if it
were improved enough to be "completely free of
contaminants that may threaten human health," and
found that this value would add between 11 and 31
percent of the fishery's current value.
> Jakus et al. (1997) used a repeated discrete choice
travel cost (TC) model to examine the impacts of
sportfishing consumption advisories in eastern
Tennessee. The model controlled for anglers'
knowledge of advisories, the type of angler (i.e.,
fish consumption vs. catch and release), and catch
rate. The estimated welfare gain (as a percentage
of baseline) from cleaning up six reservoirs and
removing these advisories ranges from six to eight
percent. These estimates are below Lyke's
estimated 11 to 31 percent range, due to the
difference in methodology used. The TC method
captures use values only, while the combined TC
and stated preferences method used in Lyke
captures both the use and nonuse components of
the resource value to users. Differences in the
fisheries and user populations may also affect the
estimated percentage changes in the resource value.
Montgomery and Needelman (1997) estimated
benefits from removing "toxic" contamination from
lakes and ponds in New York State. They used a
binary variable as their primary water quality
measure, which indicates whether the New York
Department of Environmental Conservation
considers water quality in a given lake to be
impaired by toxic pollutants. The model controls
for major causes of impairments other than "toxic"
pollutants to separate the effects of various
pollution problems that affect the fishing
experience. The estimates from Montgomery and
Needelman imply that removing "toxic"
impairments in all New York lakes and ponds
would increase recreational fishing value by 13.7
percent.
Phaneuf et al. (1998) studied angling in Wisconsin
Great Lakes. They estimated changes in
recreational fishing values resulting from a 20
percent reduction of toxin levels in lake trout flesh.
The study uses a TC model to value water quality
improvements when corner solutions are present
in the data. Corner solutions arise when consumers
visit only a subset of the available recreation sites,
setting their demand to zero for the remaining sites.
Phaneuf et al. found that improved industrial and
municipal waste management results in general
water quality improvement. This improvement
leads in turn to a 20 percent decrease in fish tissue
toxin levels, yielding a welfare gain of $156.36
(1999$) per angler per year.4 This estimate implies
that recreational fishing values would increase by
approximately 27.5 to 34.3 percent from reduced
toxin levels. This analysis estimates use values
only.
Desvousges et al. (1987) used findings from a
contingent valuation (CV) survey to estimate
WTP for improved recreational fishing from
enhanced water quality in the Pennsylvania portion
of the Monongahela River. In a hypothetical
market, each survey respondent was asked to
provide an option price for different water quality
changes, including "raising the water quality from
suitable for boating (hereafter, "beatable" water) to
a level where gamefish would survive (hereafter,
"fishable" water)."
4 The study used the 1989 survey data. Therefore, this
analysis assumes that all estimates in the original study are in 1989
dollars.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
The MP&M analysis assumed that reaches with
AWQC exceedences under the baseline conditions
are likely to support rough fishing but may not be
clean enough to support game fishing. Removing
AWQC exceedences is therefore comparable to
shifting water quality from "boatable"to "fishable."
This is a relatively conservative assumption.
Desvousges et al. found that improving water
quality from "beatable" to "fishable" would yield a
5.9 to 7.9 percent increase in water resource value
to recreational anglers.
Lant and Roberts (1990) used a CV study to
estimate the recreational and nonuse benefits of
improved water quality in selected Iowa and Illinois
river basins. River quality was defined by means of
an interval scale of "poor," "fair," "good," and
"excellent." The authors defined "fair" water
quality as adequate for boating and rough fishing
and "good" water quality as adequate for
gamefishing.
The MP&M analysis assumes that eliminating
AWQC exceedences is roughly equivalent to
shifting water quality from "fair"to "good." The
estimates from this study imply an increase of 9.7
to 13.1 percent in recreational fishing value from
improving water quality from "fair" to "good."
Farber and Griner (2000) used a CV study to
estimate changes in water resource values to users
from various improvements in water quality in
Pennsylvania. The study defines water quality as
"polluted," "moderately polluted," and
"unpolluted" based on a water quality scale
developed by EPA Region III: "Polluted" streams
are unable to support aquatic life; "moderately
polluted" streams are somewhat unable to support
aquatic life; and "unpolluted" streams adequately
support aquatic life. Streams unable to support
aquatic life (i.e., "severely polluted") are likely to
be affected by environmental stressors unrelated to
MP&M discharges, such as acidity or severe
oxygen depletion.
The MP& analysis assumes that most streams
affected by MP&M facility discharges are
moderately polluted; i.e., these streams support
aquatic life, but sensitive species may be adversely
affected by MP&M pollutants that exceed AWQC
values protective of aquatic life. Removing all
AWQC exceedences would make such streams
unpolluted. The estimates from this study imply
that improving water quality from "moderately
polluted" to "unpolluted' would yield an increase in
recreation fishery value ranging from 3.9 to 9
percent.
> Tudor et al. (2000) used a TC model to estimate
changes in water resource recreation values
resulting from eliminating MP&M pollutant
concentrations in excess of AWQC limits at
recreation sites in Ohio.5 The study involves four
recreation activities ~ fishing, boating, near-water
recreation, and swimming - and covers most
recreationally-important water bodies in all Ohio
counties. The study considers two types of water
quality effects from MP&M pollutants on
consumers' decisions to visit a particular
waterbody:
(1) visible or otherwise perceivable effects
(e.g., turbidity and odor); and
(2) "toxic" effects that are not directly
perceivable by consumers.
Because priority and nonconventional pollutants at
high enough concentrations may adversely affect
aquatic species, "toxic" effects may be indirectly
observable via species abundance and diversity.
The study uses a dummy variable to account for
effects of "toxic" MP&M pollutants, identifying
recreation sites at which estimated concentrations
of one or more MP&M pollutants exceed AWQC
for protection of aquatic life. The study estimated
that eliminating AWQC exceedances would yield
seasonal per user benefits ranging from $27.6 to
$37.0, $92.2 to $107.6, $11.2 to $16.9, and $12.06
to 13.58 (1999$) from improved fishing, boating,
wildlife viewing, and swimming opportunities,
respectively. The estimated changes in the
recreational use value of Ohio water resources,
range from 3.4 to 5.0, 13.7 to 17.0, 6.8 to 10.7
percent for fishing, boating, and wildlife viewing,
and swimming, respectively. This analysis
estimates use values only.
With the exception of the Tudor et al. (2000) study, the
types of water quality changes assessed in these studies are
only roughly comparable to those studied in the MP&M
analysis. Whereas the analysis of the proposed MP&M
regulation and Tudor et al. (2000) assessed the impact of
eliminating AWQC exceedances, the other studies used
other measures of water quality improvement. EPA
addressed the differences in measurement between the other
studies and the MP&M analysis by linking water quality
changes expected from the MP&M regulation to the type of
5 Preliminary results of this study were presented at the
annual American Agricultural Economic Association meeting (L.
Tudor et al., 1999a) and at the annual Northeastern Agricultural
and Resource Economic Association Meeting (L. Tudor et al.,
1999b). This study can be found in Chapter 21.
15-7
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
water quality changes assessed in the other studies. EPA
assumed that eliminating AWQC exceedances is roughly
comparable to the following discrete water quality changes:6
* "achieving a contaminant free fishery;"
> reducing the level of toxins in fish tissue;
* removing fish consumption advisories (FCA); and
* improving water quality from "beatable" to
"fishable," from "fair" to "good," and from
"moderately polluted" to "unpolluted."
The MP&M analysis uses the estimates derived from the
eight surface water evaluation studies described above to
calculate a range of national WTP values.
The following sections present the methodology and
relevant values used to estimate the value of improved
fishing, wildlife viewing, and boating opportunities resulting
from the MP&M regulation.
15.2.2 Recreational Fishing
The MP&M rule will improve the recreational angling
experience by reducing concentrations of priority,
nonconventional, and conventional contaminants in water.
EPA estimated the benefits of these reductions by
estimating:
> the number of recreational fishing days on
benefiting reaches;
* the baseline fishery value of each benefiting reach;
and
* changes in recreational fishery value, using values
from the available surface water valuation studies.
a. Number of recreational fishing days
EPA calculated the annual number of person-days of
recreational fishing for each benefiting reach using a two-
step approach:
ซ> Participating population
The geographic area from which anglers would travel to fish
a reach is assumed to include only those counties that abut a
given reach. As noted in Chapter 13, this assumption is
based on the finding in the 1991 National Survey of Fishing,
Hunting, and Wildlife-Associated Recreation that 65 percent
of anglers travel less than 50 miles to fish (U.S. Department
of the Interior, 1993). NDS data showed that recreational
anglers travel from 20 to 54 miles to their destination, with
an average one-way travel distance of 30 miles.7
EPA estimated the population participating in recreational
fishing using the number of licensed fishermen in counties
bordering MP&M discharge reaches using the following
steps:
> assume that fishing activity among these anglers is
distributed evenly among all reach miles within
those counties;
> compute the length of the MP&M reach as a
percentage of total reach miles within
corresponding counties;
> multiply the estimated ratio by the total fishing
population in counties abutting the reach to
estimate the number of anglers who may fish an
MP&M reach; and
* reduced the number of anglers by 20 percent in
reaches where MP&M and other pollutants have
required a fish consumption advisory. This
reduction is an estimate of angler response to the
presence of a fish consumption advisory.8
ซ> Average number of fishing days
Anglers generally participate in recreational fishing several
times a year. The U.S. Fish and Wildlife Service
(FWS) provides estimates of the average number of fishing
days per angler in each state. The FWS estimates range
from 10.5 days per angler in Arizona to 21.1 days per angler
6 Section 15.1.4 discusses a method used for estimating
partial water quality improvements.
7 See Chapter 21 for detail on the NDS data.
8 See Belton et al. (1986), Knuth and Velicer (1990),
Silverman (1990), West (1989), Connelly et al. (1992), and
Connelly and Knuth (1993) for more information on angler
response to fish advisories.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
in Alabama for freshwater fishing, and 7.3 days per angler in
Louisiana to 18.7 days per angler in Virginia for saltwater
fishing.9
EPA calculated the total number of angler days by
multiplying the number of recreational anglers for each
benefiting reach by the average number of fishing days for
the reach (based on the state in which the reach is located).
b. Baseline fishery value
The net value of a recreational fishing day is the total value
of the fishing day exclusive of any fishing-related costs
(e.g., license fees, travel costs, bait, tackle, charter boats,
etc.) incurred by the angler.
EPA used two recreational fishing valuation studies
(Bergstrom and Cordell (1991) and Walsh et al. (1992)) to
calculate the net economic value per recreational fishing day
under the baseline conditions. Both studies used a meta-
analysis of recreational fishery valuation studies to estimate
per-day values of the three types of recreational fishing:
warmwater, coldwater, and anadromous. Based on the two
studies, EPA developed an average per-day value for each
type of recreational fishing. This analysis uses low and high
average benefit values for fishing days of $26.44 and $56.85
(1999$) to estimate a range of the baseline fishery values.
Table 15.2: Baseline Values of Fishing
Fishery
Type
Warm-water
Coldwater
Anadromous
Per-day Value (1999S)a
Bergstrom
and Cordell
(1991)"
$18.36
$26.12
$34.55
Walsh et al.
(1992)c
$34.52
$44.88
$79.16
Range of above
Average
Per-day
Value
(1999$)
$26.44
$35.50
$56.85
$26.44-
$56.85
a. Original study values were adjusted to $1999 based on the relative
change in CPI from 1987 to 1999.
b. Study location: various U.S. locations. Estimating approach: meta-
analysis of TC studies.
c. Study location: various U.S. locations. Estimating approach: meta-
analysis of CV and TC studies.
EPA calculated the total baseline value for each fishery
located on a benefiting reach by multiplying the estimated
net value of a recreational fishing day by the total number of
fishing days calculated in subsection (a) above. Applying
facility weights and summing over all benefiting reaches
provides a total baseline recreational fishing value for
MP&M reaches expected to benefit from the elimination of
pollutant concentrations in excess of AWQC limits.
c. Changes in recreational fishery value
Expected benefits from the proposed MP&M regulation
include an increase in the quality of an angler's recreational
opportunities and/or the number of days an angler chooses
to fish each season.
EPA assumes that the expected welfare gain for recreational
anglers is a function of changes in the overall quality of all
recreational opportunities available to each angler.
Recreational anglers residing in the counties abutting
MP&M reaches will therefore benefit from improved
recreational opportunities whether or not they actually visit
an MP&M reach.
EPA used the eight studies discussed above to calculate the
changes in recreation values from water quality
improvements (as a percentage of baseline) implied by those
studies. Table 15.1 compiles information on the baseline
values, values of changes in water quality, and percentage
changes in values reported or implied by these studies.
9 These averages reflect participation levels in the 48
contiguous states. No sample facility is located in Hawaii or
Alaska.
15-9
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
Table 15.3: Studies Estimating Changes in Value of a Recreational Fishery
Study
Lyke(1993)
Jakus et al.
(1997)
Montgomery
and
Needelman
(1997)
Phaneuf at al.
(1998)
Desvousges
etal. (1987)
Lant and
Roberts
(1990)
Farber and
Griner (2000)
Tudor
etal. (2000) g
Type of Water Quality
Change Valued
Fish tissue is completely
free of toxic
contaminants that may
threaten human health
Lifting FCAs
Elimination of toxic
impairment
20% reduction of toxic
contamination in trout
flesh
Improvement from
"boatable" to "fishable"
Improvement from
"fair" to "good"
Improvement from
"moderately polluted"
to "unpolluted"
Elimination of AWQC
exceedances
Baseline Value of
Recreational
Angling (1999$)
$89.4-$111.9
million per year a
$24.5-$49.5
per trip
$6 17.7 per angler
per year b
$455. 8 -$569. 9 per
angler per year a
$26.44- $35.50 per
trip(1999$)c
$26.44- $35.50 per
trip(1999$)c
$26.44- $35.50 per
trip(1999$)c
$1,691-$1,933 pa-
angler per year
Value of Water
Quality Change
(1999$)
$9.9-$34.9
million per year a
$1.92-$2.97
per trip
$84.9 per
angler per year
$156. 36 per
angler per year
$2. 08 per trip
(1999$)d
$3. 45 per trip
(1999$)e
$1.40-$2.40 pa-
trip (1999$)f
$27.6-$37.0 per
angler per year
Average percentage change in recreational fishery value (based on above studies)1
Value of Change
as % of Baseline
ll%-31%a
6.0% -8.0%
13.7%
27.5% -34. 3%
5.9% -7.9%
9.7% -13.1%
3.9% -9.0%
3.4%-5.0% h
10.2% -15.2%
Type of Benefits
Included
Use and nonuse values
for recreational
anglers
Use values for
recreational anglers
Use values for
recreational anglers
Use values for
recreational anglers
Recreational and
nonuse values to users
Recreational and
nonuse values to users
Recreational use
values to users and
nonusers
Use values for
recreational anglers
Recreational and
nonuse values to users
a. The baseline fishery value for the study site location is based on the baseline fishery value reported in Lyke (1993). The study used data from two
mail surveys conducted in 1989 at the University of Wisconsin-Madison. These surveys were originally used by Lyke (1993).
b. Based on the average value for a coldwater fishing day of $35.50 ( see Table 15.2), multiplied by the average number of freshwater (non-Great
Lakes) angling days per year in New York State (17.4 days, USFWS, 1996).
c. Range based on the range of values for a fishing day used in this analysis (see Table 15.2);
d. Based on the value of water quality improvement of $34.6 Iper year (updated from 1987 dollars reported in Desvousges etal.) divided by the average
number of freshwater angling days per year in Pennsylvania (16.6 days, USFWS, 1996).
e. Based on the value of water quality improvement of $54.38 per year (updated from 1990 dollars reported in Lant and Roberts) divided by the average
number of freshwater angling days per year in Iowa and Illinois (16.6 and 15.5 days, USFWS, 1996).
f. Based on the values of water quality improvements ranging from $23.09 to $39.44 per year reported in Farber and Grimier (2000), divided by the
average number of freshwater angling days per year in Pennsylvania (16.6 days, USFWS, 1996).
g. See Chapter 21 of this report for detail. The baseline value of recreational fishery is based on the estimated mean value of water resources for
recreational anglers reported by Tudor et. al (2000). The estimated median value of recreational fishing ranges from $414.09 to $516.86.
h. To derive a range of the percentage change in water resource value for anglers, EPA estimated the lower and upper bounds of the percentage change
in resource value for each angler and then averaged these estimates over all fishing participants.
i. EPA took a simple mean of lower- and upper-bound estimates from the eight studies to calculate a range of percentage changes in the recreational
fishery value from improved water quality conditions.
EPA used the percentage change in the fishery value implied
by the eight studies to estimate increased recreational fishing
values for all MP&M reaches in which the regulation
eliminates AWQC exceedances of one or more MP&M
pollutants. That is, the Agency estimated benefits for all
MP&M discharge reaches where at least one AWQC
exceedance is eliminated due to reduced MP&M discharges.
As noted above, EPA took a simple mean of lower- and
upper-bound estimates from the eight studies described
above to calculate a range of percentage changes in the
recreational fishery value from reduced MP&M discharges.
These studies yielded estimates of increased value ranging
from 10.2 to 15.2 percent. Multiplying these percentages by
the baseline value of fisheries located on benefiting reaches
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
yielded a range of benefits from eliminating pollutant
concentrations in excess of AWQC limits.
Table 15.4 below summarizes the results of EPA's
recreational fishing benefits analysis.
Low
Estimate
High
Estimate
Number oil
Benefiting:
Reaches-
3,022j
3,022!
15.
Participating!
Population:
(millions):
20.2!
20.2!
4: Summary of Recreational Fishing Benefits
Average
Number of
Fishing Days
14.9
14.9
Total I
Angler!
Days:
(millions)-
301. l!
301. l!
Baseline!
Fishery Value/!
Recreation:
Day!
$26.4!
$56.9!
Baseline!
Fishery Value:
(S billions)!
$7.80J
$17.l!
% Change in!
Fishery:
Value-
10.2%!
15.2%!
MP&M
Benefits
(S millions)
$195.8
$627.1
Source: U.S. EPA analysis
15.2.3 Wildlife Viewing
EPA expects that water quality improvements from the
MP&M regulation will decrease the load of pollutants that
are taken up into aquatic food chains. These changes are
expected to increase the health and reproductive success of
sensitive wildlife species that feed on fish and other aquatic
organisms. In particular, Piscivorous (i.e., fish-eating)
bird species - such as the osprey (Pandion haliaetus), bald
eagle (Haliaeetus leucocephalus), great blue heron
(Ardeidae herodias), mergansers (Merginae sp.), and
cormorants (Phalacrocorax sp.) - will benefit from
increased numbers, size, and health of forage fish.
Increased food and lower pollutant levels in fish flesh will
improve reproduction in these birds, leading to healthier and
larger bird populations. Reducing conventional pollutant
loadings will also improve visual aesthetics, thereby
enhancing wildlife viewing and other near-water-based
recreation experiences, such as photography, camping,
picnicking, and waterfowl hunting (hereafter, this discussion
refers to all of these activities as "wildlife viewing").
As with the recreational fishing analysis, EPA assumes that
the expected welfare gain for consumers of viewing
activities is a function of changes in the overall quality of all
recreational opportunities available to each consumer.
Consumers of water-based recreation residing in the
counties abutting MP&M reaches are therefore likely to
benefit from improved recreational opportunities whether or
not they actually visit an MP&M reach.
EPA estimated wildlife viewing benefits using an approach
similar to that used in estimating recreational fishing
benefits. EPA estimated:
* the number of wildlife viewing days on benefiting
reaches;
* the baseline value of wildlife viewing for each
benefiting reach; and
* changes in wildlife viewing value, using values
from the available surface water valuation studies.
a. Number of wildlife viewing days
EPA calculated the annual number of person-days of
wildlife viewing for each benefiting reach using a two-step
approach:
ซ> Participating population
The analysis of the NDS data showed that participants in
viewing activities travel from 18 to 55 miles to their
destination, with an average one-way travel distance of 34
miles. EPA therefore assumes that improvements in
recreational opportunities will only benefit recreational users
residing within the counties abutting MP&M reaches. EPA
estimated the population participating in viewing activities
using the number of water-based recreation consumers
residing in the counties traversed by benefiting reaches
using the following steps:
* estimate resident populations in the counties
traversed by the benefiting reaches using Census
data;
* calculate the number of wildlife viewing
participants based on the percent of the population
engaged in wildlife viewing activities;
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
* estimate the percentage of individuals that
participate in wildlife viewing in each state using
NDS data. The total state population participating
in wildlife viewing ranges from 8.5 percent in New
Mexico to 44 percent in Maine; and
> adjust the number of wildlife viewing participants
within the affected county based on the ratio of the
affected reach length to the number of total reach
miles in the affected county to calculate the
population potentially benefiting from the rule.10'11
ซ> Average number of viewing days:
Recreators generally participate in wildlife viewing several
times a year. The Agency used NDS data on the number of
wildlife viewing trips to estimate the average number of user
days in each state. The NDS data show that the number of
wildlife viewing trips in the 48 states range from 1.07 days
per user in South Dakota to 24 days per user in
Mississippi.12
EPA multiplied the number of wildlife viewing consumers
by estimates of the average number of days per user in each
state to estimate the annual number of user days for each
benefiting MP&M reach.
b. Baseline value of wildlife viewing
EPA estimated the baseline value of wildlife viewing for the
benefiting reaches based on the estimated annual person-
days calculated in subsection (a) above and the estimated
value per person-day of wildlife viewing.
EPA used two recreational activity valuation studies
(Bergstrom and Cordell (1991) and Walsh et al. (1992)) to
calculate the net economic values per wildlife viewing day.
These studies estimate net benefit values for four
recreational activities: wildlife viewing, waterfowl hunting,
camping, and picnicking. Based on the two studies, EPA
developed an average per-day value for three of the four
activities.13 EPA's MP&M benefits analysis uses the lowest
average benefit value, $21.38, for the low estimate of
wildlife viewing benefits and the highest average value,
$27.03, for the high estimate. Table 15.5 presents
information on the relevant values reported in these studies.
10 Information in EPA's Reach File 1 indicates that the ratio of
affected reach length to the total number of reach miles within a
county ranges from 0.02 to 0.39.
11 This analysis assumes that recreation activities among
residents of the counties affected by MP&M discharges are
distributed evenly across all reach miles within those counties.
12 See Chapter 21 for details on the NDS data.
13 EPA excluded the per-day value of waterfowl hunting
($52.24) from the activities included in this analysis, because this
activity is limited to designated hunting areas only.
Using facility sample weights and summing over all
benefiting reaches provides the total baseline value of
wildlife viewing for MP&M reaches that EPA expects to
benefit by eliminating pollutant concentrations in excess of
AWQC limits.
Table 15.5: Baseline Values of Wildlife Viewing
Recreational
Activity
Camping
Picnicking
Near-water
Activities
Per-day Value (1999S)a
Bergstrom
and Cordell
(1991)"
$25.49
$17.37
$18.88
Walsh et al.
(1992)c
$28.58
$25.40
$32.54
Range of above
Average
Per-day
Value
(1999$)
$27.03
$21.38
$25.71
$21.38-
$27.03
a. Original study values were adjusted to $1999 the base year of the
analysis based on the relative change in CPI from 1987 to 1999.
b. Study location: various U.S. locations; estimating approach: meta-
analysis of TC studies.
c. Study location: various U.S. locations; estimating approach: meta-
analysis of contingent valuation (CV) and TC studies.
c. Changes in wildlife viewing value
EPA selected a subset of the candidate benefits transfer
studies discussed in Section 15.2.1 to estimate changes in
water resource value to wildlife viewers due to the MP&M
rule. The four selected studies include Tudor et al. (2000),
Desvousges et al. (1987), Lant and Roberts (1990), and
Farber and Griner (2000).14 Table 15.6 compiles
information on the baseline values of wildlife viewing,
values of changes in water quality, and percentage change in
values reported or implied by these studies.
14 The remaining four studies value changes in the value
recreational fishing only.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
Table 15.6
Study
Desvousges
etal. (1987)
Lant and
Roberts
(1990)
Farber and
Griner
(2000)
Tudor
et al. (2000)
Water Quality Change
Valued
Improvement from
"boatable" to "fishable"
Improvement from
"fair" to "good"
Improvement from
"moderately polluted"
to "unpolluted"
Elimination of AWQC
exceedances
Studies Estimating Changes in Value of Wildlife Viewing
Baseline Value of
Wildlife Viewing
(1999$)
$21. 4 -$27.0 per trip a
$21. 4 -$27.0 per trip a
$21. 4 -$27.0 per trip a
$376.3 - $427.6 per
user per year6
Value of Water
Quality Change
(1999$)
$4.70 per trip"
$8.09 per trip0
$3. 13 -$5.35 per
tripd
$11. 16 -$16. 88 per
user per year
Average percentage change (based on the above studies)8
Value of Change as
% of Baseline
17.4% -22.0%
29.9% - 37.8%
11. 6% -25.0%
6. 8% - 10.7% f
Type of Benefits
Included
Recreational and
nonuse values to users
Recreational and
nonuse values to users
Recreational and
nonuse values to users
Recreational use values
to users
16.4%-23.9%
a. Based on the range of median values for a near-water recreation day (updated to 1999 dollars) reported in Walsh et al. (1992) and Bergstrom and
Cordell (1991) (see TablelS.5).
b. Based on the value of water quality improvement of $34.6 Iper person per year (updated from 1987 dollars reported in Desvousges et al.) divided by
the average number of near-water recreation days per year in Pennsylvania (7.37 days, NDS, 1993).
c. Based on the value of water quality improvement of $54.36 per year (updated from 1990 dollars) reported in Lant and Roberts divided by the average
number of near-water recreation days per year in Iowa and Illinois (9.58 and 5.04 days, NDS, 1993).
d. Based on the value of water quality improvements ranging from $23.09 to $39.44 per person per year reported in Farber and Griner (2000) divided
by the average number of near-water recreation days per year in Pennsylvania (7.37 days, NDS, 1993).
e. The baseline value of viewing is based on the estimated mean value of water resources for wildlife viewers reported by Tudor et. al (2000). The
estimated median value of recreational fishing ranges from $108.74 to $135.41.
f. To derive a range of the percentage change in water resource value for wildlife viewers, EPA estimated the lower and upper bounds of the percentage
change in resource value for each consumer and then averaged these estimates over all viewing participants.
g. EPA took a simple mean of lower- and upper-bound estimates from the four studies to calculate a range of percentage changes in the wildlife viewing
value from improved water quality conditions.
This analysis uses the change of 16.4 percent for the low
benefits estimate and 23.9 percent for the high benefits
estimate to calculate benefits from reduced MP&M facility
discharges to users of water-based recreation. These values
represent the average of the low and high values,
respectively, estimated in the four studies.
Table 15.7 below summarizes the results of EPA's wildlife
viewing benefits analysis.
Table 15.7: Summary of Wildlife Viewing Benefits
Low
Estimate
High
Estimate
Number of! Participating
Benefiting j Population
Reaches ! (millions)
3,0221 57.1
3,022 1 57.1
Total
Ave. Number j Viewing
of Viewing! Days
Days ! (millions)
9.9 j 567
9.9 j 567
Baseline
Value/ Rec.
Day
$21.4
$27.0
Total !
Baseline
Value i % Change in
($ billions) ! Value
$12.1 ! 16.4%
$15. 3 i 23.9%
Benefit
from
MP&M
($ million)
$500.1
$919.9
Source: U.S. EPA analysis.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
15.2.4 Recreational Boating
Improvements in water quality from the proposed MP&M
rule may enhance recreational boating by (1) providing more
opportunities for companion activities (e.g., fishing and
wildlife viewing) and (2) improving visual aesthetics. EPA
assumes that the expected welfare gain for boaters is a
function of changes in the overall quality of all recreational
opportunities available to each boater on a given day.
This analysis estimates recreational boating benefits the
same way as recreational fishing and wildlife viewing
benefits. The analysis estimates:
* the number of recreational boating days on
benefiting reaches,
* the baseline value of boating for each benefiting
reach, and
> changes in recreational boating value.
a. Number of recreational boating days
EPA calculated the annual number of recreational boating
days for each benefiting reach using two steps:
ซ> Participating population
The analysis of the NDS data showed that boaters travel
from 11 to 52 miles to their destination, with an average
one-way travel distance of 32 miles. This analysis therefore
considers only boaters residing in the counties abutting
MP&M reaches. EPA estimated the number of boaters
residing in the counties traversed by benefiting reaches by
combining information from Census data and NDS data on
the proportion of individuals participating in boating in each
state. The percent of the total state population in the 48
states participating in boating ranges from 6 percent in
Colorado to 25 percent in Washington. EPA further
adjusted the number of boaters likely to use MP&M reaches
within the affected county based on the ratio of the affected
reach length to the number of total reach miles in the
affected county.15
ซ> Average number of boating days
People using benefiting reaches for boating generally
participate in this activity several times per year. The NDS
data show the number of boating trips in the 48 states
ranging from 2.2 days per user in South Dakota to 17.5 days
per user in Kansas.
EPA estimated the annual number of user days for
recreational boating activities by multiplying the number of
boaters by the average number of boating days per user in
each state.
b. Baseline value of boating
EPA estimated the baseline value of boating on benefiting
reaches using the estimated annual person-days of boating
per reach and estimated values per person-day of various
types of boating. EPA calculated a range of net economic
values per recreation day of boating based on studies by
Bergstrom and Cordell (1991) and Walsh et al. (1992).
Mean net benefit values for motorized and non-motorized
boating are $35.09 to $55.75 in 1999 dollars. Table 15.8
compiles information on the relevant values reported in
these studies.
Table 15.8: Baseline Values of a Boating Day
Recreational
Activity
Motorized
Non-
motorized
Per-day Value (1999S)a
Bergstrom
and Cordell
(1991)"
$23.92
$40.14
Walsh et al.
(1992)c
$46.26
$71.35
Boating (any type)
Average
Per-day
Value
(1999$)
$35.09
$55.75
$35.09-
$55.75
a. Original study values were adjusted to $1999 based on the relative
change in CPI from 1987 to 1999.
b. Study location: various U.S. locations. Estimating approach: meta-
analysis of TC studies.
c. Study location: various U.S. locations. Estimating approach: meta-
analysis of CV and TC studies.
Weighting by facility sample weights and summing over all
benefiting reaches provides a total baseline value of boating
for MP&M reaches expected to benefit by eliminating
pollutant concentrations in excess of AWQC limits.
c. Changes in recreational boating values
The Agency used the same four studies discussed in Section
15.2.3 to calculate the change in per-day boating value as a
result of water quality improvements. EPA expressed this
change as a percentage of the baseline value. Table 15.9
compiles information on the baseline values of boating,
values of changes in water quality, and percentage change in
boating values reported or implied by these studies.
See section 13.1.1 for detail.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
Table 15.9: Studies Estimating Changes in Value of Recreational Boating
Study
Desvousges
etal. (1987)
Lant and
Roberts
(1990)
Farber and
Griner (2000)
Tudor et al.
(2000)
Water Quality
Change Valued
Improvement from
"boatable" to
"fishable"
Improvement from
"fair" to "good"
Improvement from
"moderately
polluted" to
"unpolluted"
Elimination of
AWQC exceedances
Baseline Value of
Boating (1999$)
$35.09 - $55.75 per
trip"
$35.09 - $55.75 per
trip*
$35.09 - $55.75 per
trip"
$1,154 -$1,243 per
user per year "
Value of Water
Quality Change
(1999$)
$3. 69 per trip b
$7.44 per
trip0
$2.46 - $4.21 per
tripd
$92.15 -$107.55
per user per year
Average percentage change (based on the above studies)8
Value of Change as
% of Baseline
6.6% -10. 5%
13.3% -21.2%
4.4%-12.0%
13.7%-17%f
Type of Benefits
Included
Recreational and
nonuse values to
users
Recreational use
values to users and
nonusers
Recreational and
nonuse values to
users
Recreational values
for users
9.5%-15.2%
a. Based on the average value for a boating day (updated to 1999 dollars) reported in Walsh et al. (1992) and Bergstrom and Cordell (1991).
b. Based on the value of water quality improvement of $34.6 Iper person per year (updated from 1987 dollars) reported in Desvousges et al. divided by
the average number of boating days per year in Pennsylvania (9.37 days, NDS, 1993).
c. Based on the value of water quality improvement of $54.36 per person per year (updated from 1990 dollars) reported in Lant and Roberts divided by
the average number of boating days per year in Iowa and Illinois (9.58 and 5.04 days, NDS, 1993).
d. Based on the value of water quality improvements ranging from $23.09 to $39.44 per person per year reported in Farber and Griner (2000) divided
by the average number of boating days per year in Pennsylvania (9.37 days, NDS, 1993).
e. The baseline value of boating is based on the estimated mean value of water resources for boaters reported by Tudor et. al (2000). The estimated
median value of recreational boating ranges from $181.99 to $199.82.
f To derive a range of the percentage change in recreational boating value, EPA estimated the lower and upper bounds of the percentage change in
resource value for each consumer and then averaged these estimates over all recreational boaters.
e. EPA took a simple mean of lower- and upper-bound estimates from the four studies described to calculate a range of percentage changes in the
recreational boating value from improved water quality. When only one value is available from the study (i.e., Tudor et al.), EPA used this value in
calculating both the lower- and upper-bound estimates.
This analysis uses the change of 9.5 percent for the low
benefits estimate and 15.2 percent for the high benefits
estimate to calculate benefits to boaters from reduced
MP&M facility discharges. These values represent the
average of the low and high values, respectively, estimated
in the four studies.
Table 15.10 summarizes the results of EPA's recreational
boating benefits analysis.
Low
Estimate
High
Estimate
Number
of
Benefiting
Reaches
3,022
3,022
Table 1
Participating
Population
(millions)
33.1
33.1
5.10: Summary of Recreational Boating
Total I
Ave. Number j Boating j Baseline
of Boating i Days i Value/ Rec.
Days (millions) Day
8.9 1 296 ! $35.1
8.9 1 296 1 $55.8
Benefits
Total I
Baseline j
Value 1 % Change
($ billion) I in Value
$10.4 j 9.50%
$16.5 1 15.20%
MP&M
Benefits
($ millions)
$265.0
$672.1
Source: U.S. EPA analysis.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
15.2.5 Nonuse Benefits
Individuals who never visit or otherwise use a natural
resource may still be affected by changes in its status or
quality. Empirical estimates indicate that such "nonuse
values" may be substantial for some resources (Harpman et
al, 1993; Fisher and Raucher, 1984; Brown, 1993). Most
studies have found that nonuse values exceed use values.
Brown reviewed CV studies in which both use and nonuse
values were estimated, and calculated the ratio of nonuse
values to use values (Brown, 1993). His 34 estimated ratios
range from 0.1 to 10, with the median ratio of 1.92. Carson
and Mitchell suggested that nonuse benefits account for 19
to 39 percent of total WTP values for water quality
improvements depending on the definition of nonuse values
(Carson and Mitchell, 1993). The ratio of nonuse to use
value ranges from one-fourth to two-thirds based on the
Carson and Mitchell study (1993). Fisher and Raucher
(1984) found that nonuse benefits comprise one-half of
recreational use benefits.
EPA estimated changes in nonuse values for this analysis
because nonuse value is a sizeable portion of the total value
of water resources. Based on the studies discussed above,
this analysis estimated that nonuse benefits (i.e., benefits to
individuals who do not participate in water-based recreation)
comprise one-fourth, one-half, and two-thirds of recreational
use benefits for low, mid, and high estimate, respectively.
15.3 SUMMARY OF RECREATIONAL
BENEFITS
EPA assumes that eliminating concentrations of MP&M
pollutants in excess of AWQC limits will achieve water
quality protective of aquatic life and human health. This
improved water quality then generates benefits for both
users and nonusers of water-based recreation. These
benefits can be seen as an increase in the value of each day
spent on or near the waterway, as well as an increase in the
number of days spent on or near the waterway. EPA
estimated the monetary value of improved water-based
recreational opportunity for the 1,185 discharge reaches for
which concentrations in excess of AWQC limits would be
eliminated. The Agency also assigned partial benefits to the
1,837 reaches that would experience reduced numbers of
AWQC exceedences.
EPA first estimated the number of recreational days on
benefiting reaches for each water-based activity. The
Agency then calculated the baseline value of these activities
and then calculated the percentage changes in this value
stemming from water quality improvements.
EPA calculated partial benefits for the 1,837 reaches with
reduced numbers of AWQC exceedances by adjusting the
percentage increase in the recreational value of these
reaches. EPA made these adjustments based on the ratio of
the number of AWQC exceedances eliminated post-
compliance to the number of AWQC exceedances occurring
at baseline.
Table 15.13 summarizes benefit estimates by recreational
category. The activities considered in this analysis are
stochastically independent; EPA calculated the total value of
enhanced water-based recreation opportunities by summing
over the three recreation categories. EPA also estimated the
changes in nonuse value resulting from reduced MP&M
discharges based on the ratio of use to nonuse values
implied by the Fisher and Raucher study (Fisher and
Raucher, 1984). The estimated increase in nonuse value
ranges from $240 to $1,464 million (1999$), with a
midpoint value of $760 million (1999$) The resulting
increased value of recreational activities to consumers (users
and nonusers) of water-based recreation ranges from an
estimated $1,201 to $3,683 million (1999$) annually. The
estimated mean value of recreational benefits is $2,281
million (1999$) annually.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
Table 15.13: Estimated Recreational Benefits from Reduced MP&M Discharges
Recreational Activity
Fishing
Boating
Viewing and Near- water Activities
Total Recreational Use Benefits
Nonuse Benefits (1/2 of the Recreational Use Benefits)
Total Recreational Benefits (million 1999$)
Estimated Annual Benefits (Million 1999$)
Low Value
$195.78
$265.03
$500.12
$960.82
$240.21
$1,201.01
Midpoint Value
$365.36
$445.69
$709.96
$1,521.02
$760.33
$2,281.34
High Value
$627.13
$672.12
$919.94
$2,219.18
$1,464.25
$3,683.43
Source: U.S. EPA analysis.
15.4 LIMITATIONS AND
UNCERTAINTIES ASSOCIATED WITH
ESTIMATING RECREATIONAL BENEFITS
EPA assessed recreational benefits in terms of reduced
occurrences of pollutant concentrations exceeding acute and
chronic toxic effect levels for aquatic species. EPA also
attached a monetary value to ecological improvements
expected to result from the MP&M regulation, in the form
of the increased value of three water-based recreation
activities ~ recreational fishing, wildlife viewing, and
boating - plus the increase in nonuse value. The estimated
increase in value detailed in this chapter constitutes only a
partial measure of the value to society of improving aquatic
habitats and aquatic life. This benefits analysis is limited
because it ignores improvements to recreational activities
other than fishing, boating, and wildlife viewing (e.g.,
swimming), as well as non-recreational benefits, such as
increased assimilative capacity and improvements in the
taste and odor of the affected waters.
The methodologies used to assess ecological benefits also
involved significant simplifications and uncertainties, whose
combined effect on the estimated benefits is not known.
Estimated economic values may be under- or overestimated.
Some of these simplifications and uncertainties also apply to
the human health benefits analysis, and have been discussed
at length in the previous chapter, including those associated
with:
> developing the sample of MP&M facilities
analyzed in the EEBA,
> estimating in-waterway concentrations of MP&M
pollutants,
* considering background concentrations of MP&M
pollutants, and
* considering downstream effects.
Table 15.14 summarizes the additional elements of
uncertainty that are specific to the recreational benefits
analysis.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
Table 15.14: Key Omissions, Biases, and Uncertainties in the Analysis
for Improved Recreational and Nonuse Benefits
Assumption/Limitation
Direction of Impact
on Benefit Estimates
Scope of Recreational Benefits Analysis
Only the receiving reach itself is estimated to provide
benefits.
Water quality in reaches downstream of the reaches affected by MP&M
discharges may also improve, generating additional benefits to society.
Excluding these benefits from the analysis biases benefits estimates
downward.
Only recreational users living in the counties abutting
MP&M reaches are assumed to benefit from water
quality improvements due to the MP&M rule.
The analysis underestimates the total value of benefits from the MP&M
regulation because it does not account for people's WTP for water quality
improvements to distant waterbodies. For example, economic values for
improving nationally-significant waterbodies (e.g., Great Lakes,
Chesapeake Bay, Long Island Sound) are likely to be substantial at a
regional level or even nationwide.
The analysis of recreational fishing ignores effects that
occur in secondary industries.
The analysis of recreational benefits ignores potential economic effects on
tourism industries stemming from improved recreational opportunities.
Improved recreational fishing may have a positive effect on industries
supplying bait, tackle, charter boats, etc.
An increase in consumer demand for boating may have positive effects on
industries such as boat construction, sales, rentals, boating equipment,
marinas, racing activities, etc. Improvements in wildlife viewing and near
water recreation opportunities may benefit industries involved in providing
other recreational opportunities such as tours, books, binoculars, etc.
The analysis of recreational benefits ignores changes in
the value of water-based recreational activities other
than fishing, wildlife viewing, and boating (e.g.,
swimming or waterskiing).
The estimate of recreational benefits is incomplete because it includes only
a subset of recreational activities (i.e., fishing, wildlife viewing, and
boating) for which society may value improved aquatic habitat. It ignores
changes in value for other water-based recreational activities, such as
swimming or waterskiing. In addition, the analysis did not consider other
changes in the affected reaches, such as improved taste and odor.
Extrapolating from sample facility results to national
results is based on the sample facility weights
This extrapolation technique is not ideal and introduces uncertainty into the
analysis. Facility sample weights are based on facility size and type of
industry. These weights do not necessarily account for the frequency benefit
pathway characteristics in the MP&M facility universe. Therefore benefit
estimates may suffer from uncertainties associated with the extrapolation
method. For example, a sample facility may have a significant impact on
benefit estimates if it is more likely to be located in a densely populated
area, such a facility located in Cleveland, Ohio or a facility discharging in
Long Island Sound, than the facilities it represents. The opposite may also
be true.
Congestion Externalities
Recreational benefits associated with water quality improvements can be
eroded by congestion if policies greatly increase the number of participants.
This can be particularly problematic when policies affect geographically
scattered sites, so that there is considerable switching to the improved site
from substitute sites. Congestion may be a lesser problem for national
regulations that might affect the total number of recreation days and the
overall value of recreational opportunities, but are less likely to have a large
effects on industrial sites relative to its substitutes.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
Table 15.14: Key Omissions, Biases, and Uncertainties in the Analysis
for Improved Recreational and Nonuse Benefits
Assumption/Limitation
Direction of Impact
on Benefit Estimates
Benefits Transfer
The waters assessed by local-level studies are not
necessarily nationally representative.
The studies selected came from the Midwest and the Northeast. As a result,
the resources valued, as well as respondent preferences, may not be
representative of the rest of the country.
Types of water quality changes expected from the
MP&M rule may differ from the water quality changes
considered in the original studies.
The types of water quality changes expected from the MP&M regulation
are only roughly comparable with the majority of water quality changes
considered in the original studies (Tudor et al. is the only exception). Due
to the paucity of available studies, the Agency made simplifying
assumptions to "map" the water quality changes valued in the original
studies onto those expected from the rule. Although these assumptions are
likely to increase uncertainty associated with recreational benefits
estimates, the direction of bias is not known.
Compatibility of time periods considered in the original
studies and in the analysis of MP&M costs and benefits.
Most studies considered in the benefits transfer analysis did not specify
payment periods. The scenario in the Farber and Griner (2000) paper asked
for payments for the next five years. This scenario implies that five years of
pollution control will result in permanent water quality changes. The
analysis of the MP&M regulation assumes that pollution control continues
over 15 years and that water quality improvements depend on continued
operation of the water pollution controls. EPA therefore chose the annual
WTP values presented in the paper, as opposed to the total value paid over
five years, annualized over the 15 years considered in the cost analysis.
This assumption may result in an overestimation of the regulation's benefit.
The magnitude of this error is unlikely to be significant because this study
is used in combination with other surface water valuation studies.
Baseline Value of Fishery
Converting annual WTP values to per-trip values
EPA converted annual WTP values reported in the three CV studies used
in this analysis to per-trip values by dividing seasonal welfare gain per user
reported in the each CV study by the average number of fishing, boating, or
viewing days in a given state. This calculation implies that every
individual participates in only one activity, which may not be the
case. This implication may result in an overestimation of the per-
trip welfare gain, and, consequently, total recreational benefits from
the proposed rule.
This analysis estimates the baseline value of the fisheries
at locations across the country using a range of values
for all types of fisheries.
Site-specific fisheries may have higher or lower baseline values, and thus,
higher or lower benefits from reduced MP&M discharges.
The total number of recreational person-days in the
counties abutting MP&M reaches is evenly distributed
across all reach miles in these counties
This method for estimating the number of recreational users potentially
affected by water quality improvements from the proposed regulation
accounts for the quantity but not quality of potential recreational
opportunities available to recreational users. There may be important
substitute sites in or outside the counties abutting MP&M reaches. Ignoring
recreationally importance substitute sites may result in overestimation of
benefits from the proposed regulation. Ideally the analysis would consider
recreational importance of both sites affected by MP&M discharges and
substitute sites.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
Table 15.14: Key Omissions, Biases, and Uncertainties in the Analysis
for Improved Recreational and Nonuse Benefits
Assumption/Limitation
Direction of Impact
on Benefit Estimates
Nonuse Values
Nonuse values are estimated as one-fourth, one-half, and
two-thirds of recreational use benefits.
It is unknown what bias estimating nonuse values based on recreational use
values has on benefits.
Overall Impact on Benefits Estimates (?)
+ Potential overestimate.
? Uncertain impact.
Potential underestimate.
Source: U.S. EPA analysis.
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MP&M EEBA Part III: Benefits
Chapter 15: Recreational Benefits
GLOSSARY
1Q10: the lowest one-day average flow with a recurrence
interval often years.
7Q10: the lowest consecutive seven-day average flow with
a recurrence interval of ten years.
Ambient Water Quality Criteria (AWQC): published
and periodically updated by the EPA under the Clean Water
Act. The criteria reflect the latest scientific knowledge on
the effects of specific pollutants on public health and
welfare, aquatic life, and recreation. The criteria do not
reflect consideration of economic impacts or the
technological feasibility of reducing chemical concentrations
in ambient water. The criteria serve as guides to states,
territories, and authorized tribes in developing water quality
standards and ultimately provide a basis for controlling
discharges or releases of pollutants into our nation's
waterways. AWQC are developed for two exposure
pathways: ingestion of the pollutant via contaminated
aquatic organisms only, and ingestion of the pollutant via
both water and contaminated aquatic organisms.
benefiting reaches: reaches where the MP&M rule is
expected to eliminate existing AWQC exceedences. These
receiving waters are likely to experience significant water
quality improvements as a result of the reduced MP&M
discharges. A reach is considered to benefit if at least one
AWQC exceedance is eliminated due to reduced MP&M
discharges.
benefits transfer: involves the application of value
estimates, functions, and/or models developed in one context
to address a similar resource valuation question in another
context. Often a meta-analysis is undertaken where benefits
estimates based on existing studies are used to develop new
estimates which are applicable to the scenario under
consideration. This process accounts for relevant
differences in study characteristics such as the quality of
environmental resource, the environmental change
considered, and the user population being investigated.
contingent valuation (CV): directly asks people what
they are willing to pay for a benefit and/or willing to receive
in compensation for tolerating a cost through a survey or
questionnaire. Personal valuations for increases or
decreases in the quantity of some good are obtained
contingent upon a hypothetical market. The aim is to elicit
valuations or bids that are close to what would be revealed if
an actual market existed.
conventional pollutants: biological oxygen demand
(BOD), total suspended solids (TSS), oil and grease (O&G),
pH, and anything else the Administrator defines as a
conventional pollutant.
Metal Products and Machinery (MP&M): industry
includes facilities that manufacture, rebuild, and maintain
metal parts, products, or machines.
National Demand Study (NDS): U.S. EPA and the
National Forest Service conducted the National Demand
Survey for Water-Based Recreation in 1993. The survey
collected data on demographic characteristics and water-
based recreation behavior using a nationwide stratified
random sample of 13,059 individuals aged 16 and over.
nonconventional pollutant: catch-all category that
includes everything that is not classified as a priority
pollutant or a conventional pollutant.
piscivorous: feeding preferably on fish.
toxic pollutants: EPA's Office of Water narrowly
defines a toxic pollutant as one of 126 priority pollutants.
This definition is not completely synonymous with
pollutants that have a "toxic" effect. Many nonconventional
pollutants may also be hazardous to aquatic life and human
health.
"toxic " pollutant: any pollutant that has an adverse effect
on aquatic life or human health.
travel cost (TC) model: derives values by evaluating
expenditures of recreators. Travel costs are used as a proxy
for price in deriving demand curves for the recreation site.
(http://www.damagevaluation.com/glossary.htm)
U.S. Fish and Wildlife Service (FWS): the principal
Federal agency responsible for conserving, protecting, and
enhancing fish, wildlife, and plants and their habitats for the
continuing benefit of the American people.
(http://www.fws.gov/r9extafl7pafaq/fwsfaq.html)
willingness to pay (WTP): maximum amount of money
one would give to buy some good.
(http://www.damagevaluation.com/glossary.htm)
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MP&M EEBA Part III: Benefits Chapter 15: Recreational Benefits
ACRONYMS
1Q10: the lowest 1-day average flow with a recurrence DO: dissolved oxygen
interval of 10 years MP&M: Metal Products and Machinery
7Q10: the lowest 7-day average flow with a recurrence NDS: National Demand Study
interval of 10 years TC: travel cost
AWQC: ambient water quality criteria WTP: willingness to pay
CV: contingent valuation
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MP&M EEBA Part III: Benefits Chapter 15: Recreational Benefits
REFERENCES
Belton, T., R. Roundy and N. Weinstein. 1986. Urban Fishermen: Managing the Risks of Toxic Exposure. Environment,
Vol. 28. No. 9, November.
Brown, T. 1993. "Measuring Nonuse Value: A Comparison of Recent Contingent Valuation Studies." In Bergstrom, J.C.,
Benefits and Costs Transfer in Natural Resource Planning. Sixth Interim Report, University of Georgia, Department of
Agriculture and Applied Economics; Athens, GA.
Bergstrom, J.C. andH.K. Cordell. 1991. "An analysis of the Demand for and Value of Outdoor Recreation in the United
States." Journal of Leisure Research, Vol. 23, No. 1, pp. 67-86.
Carson, R. T., and R. C. Mitchell. 1993. "The Value of Clean Water: The Public's Willingness to Pay for Beatable,
Fishable, and Swimmable Quality Water." Water Resources Research 29(7), pages 2445-2454.
Connelly, N. and B. Knuth. 1993. Great Lakes Fish Consumption Health Advisories: Angler Response to Advisories and
Evaluation of Communication Techniques, Human Dimensions Research Unit, Dept. of Natural Resources, NY State
College of Agriculture and Life Sciences, Cornell University, HDRU Series No 93-3, February.
Connelly, N., B. Knuth, and C. Bisogni. 1992. Effects of the Health Advisory and Advisory Changes on Fishing Habits and
Fish Consumption in New York Sport Fisheries. Human Dimensions Research Unit, Dept. of Natural Resources, NY State
College of Agriculture and Life Sciences, Cornell University, HDRU Series No 92-9, September.
Desvousges, W. H. et al. 1987. "Option Price Estimates for Water Quality Improvements: A Contingent Valuation Study
for the Monongahela River." Journal of Environmental Economics and Management, 14, pages 248-267.
Farber, S. andB. Griner. 2000. Valuing Watershed Quality Improvements Using Conjoint Analysis. University of
Pittsburgh, PA.
Fisher, A. and R. Raucher. 1984. Intrinsic Benefits of Improved Water Quality: Conceptual and Empirical Perspectives. In:
Advances in Applied Microeconomics, Vol. 3, V.K. Smith, editor, JAI Press.
Harpman, D.A., M.P. Welsh, and R.C. Bishop. 1993. Nonuse Economic Value: Emerging Policy Analysis Tool. Rivers,
Vol. No.4.
Jakus, P.M., M. Downing, M.S. Bevelhimer, and J.M. Fly. 1997. "Do Sportfish Consumption Advisories Affect Reservoir
Anglers' Site Choice!" Agricultural and Resource Economic Review, 26(2).
Knuth, B. and C. Velicer. 1990. Receiver-Centered Risk Communication for Sportfisheries: Lessons from New York
Licensed Anglers. Paper presented at the American Fisheries Society Annual Meeting, Pittsburgh, Perm, August.
Lant, C. L. and R.S. Roberts. 1990. "Greenbelts in the Cornbelt: Riparian Wetlands, Intrinsic Values, and Market Failure."
Environment and Planning A, Vol. 22, pp. 1375-1388.
Lyke, A.J. 1993. "Discrete Choice Models to Value Changes in Environmental Quality: A Great Lakes Case Study." PhD
dissertation, University of Wisconsin, Department of Agricultural Economics, Madison.
Montgomery, M. and M. Needelman. 1997. "The Welfare Effects of Toxic Contamination in Freshwater Fish." Land
Economics 73(2): 211-223.
Phaneuf, D. I, C. L. Kling, and J.A. Herriges. 1998. "Valuing Water quality Improvements Using Revealed Preference
Methods When Corner Solutions are Present." American Journal of Agricultural Economics 80, pp. 1025-1031.
Silverman, W. 1990. Michigan's Sport Fish Consumption Advisory: A Study in Risk Communication. Thesis submitted in
partial fulfillment of the requirements for the degree of Master of Science (Natural Resources) at the University of Michigan,
May.
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Tudor, L., E. Besedin, M. Fisher, and S. Smith. 1999a. "Economic Analysis of Environmental Regulations: Application of
the Random Utility Model to Recreational Benefit Assessment for the MP&M Effluent Guideline." Presented at the annual
American Agricultural Economics Association meeting, Nashville TN.
Tudor, L., E. Besedin, S. Smith, and L. Snyder. 1999b. " What Pollutants Matter for Consumers of Water-Based
Recreation?" Presented at the annual Northeastern Agricultural and Resource Economics Association meeting,
Morgantown, WV, June.
Tudor, L., et al. 2000. Economic Analysis of Environmental Regulations: Using a Random Utility Model to Assess
Recreational Benefits for Effluent Guidelines. Final Report, U.S. EPA, Washington, D.C. January.
US Bureau of Census. 1996. Projections of Household by Type 1995-2010 (series 1).
http://www.census.gov/population/projections/nation/hh-fam/tableln.txt
U.S. EPA (U.S. Environmental Protection Agency). 1986. Quality Criteria for Water. EPA 440/5-86-001.
USFWS (U.S. Fish and Wildlife Service). 1996. 1996 National Survey of Fishing, Hunting, and Wildlife-Associated
Recreation. U.S. Fish and Wildlife Service and Bureau of the Census.
Walsh, R.G., D.M. Johnson, and J.R. McKean. 1992. "Benefit transfer of Outdoor Recreation Demand Studies, 1968-
1988." Water Resource Research, Vol. 28, No. 3, pp. 707-713.
West, P., R. Marans, F. Larkin, and M. Fly. 1989. Michigan Sport Anglers Fish Consumption Survey: A Report to the
Michigan Toxic Substances Control Commission, University of Michigan School of Natural Resources, Natural Resources
Sociology Research Lab, Technical Report #1, May.
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
Chapter 16: POTW Benefits
INTRODUCTION
Reducing effluent discharges from the MP&M industry
should result in two categories of productivity benefits for
publicly owned treatment works (POTWs):
> reduced interference with the operations of
POTWs, and
> reduced contamination of sewage sludge (i.e.,
biosolids) at POTWs that receive discharges from
MP&M facilities.
Interference with POTW processes occurs when high levels
of toxics, such as metals or cyanide, kill bacteria required
for wastewater treatment processes. The MP&M regulation
should remove 703 million pounds of 89 such pollutants per
year from the wastewater of indirect dischargers (see Table
16.1), thereby reducing the potential for interference with
POTW operations. The removal of these pollutants would
eliminate the need for extra labor and materials to maintain
POTW operations. EPA estimated that the proposed
regulation would eliminate potential inhibition problems
caused by MP&M facilities at 306 POTWs nationwide.
This analysis is presented in Section 16.1.
Toxic priority and nonconventional pollutants may also pass
through a POTW and contaminate sludge generated during
primary and secondary wastewater treatment.1 EPA
estimates that the proposed regulation would remove 30.1
million pounds per year of the eight pollutants for which
there are published sludge concentration limits (see Table
16.1). POTW treatment of wastewater with reduced
pollutant concentrations translates into cleaner sludge,
which can be disposed of using less expensive and more
environmentally benign methods. In some cases, cleaner
sludge may have agricultural applications, which would
generate additional resource conservation benefits. EPA
estimated that potential cost savings for POTWs expected to
CHAPTER CONTENTS:
16-2
16.1 Reduced Interference with POTW Operations
16.2 Assessing Benefits from Reduced Sludge
Contamination 16-2
16.2.1 Data Sources 16-2
16.2.2 Sludge Generation, Treatment, and
Disposal Practices 16-3
16.2.3 Overview of Improved Sludge Quality
Benefits 16-6
16.2.4 Sludge Use/Disposal Costs and Practices 16-7
16.2.5 Quantifying Sludge Benefits 16-9
16.3 Estimated Savings in Sludge Use/
Disposal Costs 16-13
16.4 Methodology Limitations 16-14
Glossary 16-16
Acronyms 16-17
References 16-18
upgrade their sludge disposal practices under the
post-compliance scenario are $61.1 to $61.5 million
(1999$). This analysis is presented in Section 16.2.
Some MP&M pollutants that pass through a POTW and
contaminate sludge are not currently subject to sewage
sludge pollutant concentration limits. The proposed
regulation would reduce concentrations of these pollutants
in sewage sludge as well, which may translate into reduced
environmental and human health risks. EPA did not
estimate the reduced risk attributable to the reduction of
these pollutants.
Wastewater from MP&M facilities also contains
hazardous air pollutants (HAPs). These pollutants
may represent unacceptable health risks to POTW workers if
released into the air at high enough concentrations during
the wastewater treatment cycle. The proposed regulation is
expected to remove approximately one million pounds per
year of HAPs from wastewater transferred to POTWs. This
reduction in pollutants may translate into health benefits to
POTW workers and those living near POTWs.
1 The term sewage sludge, also called biosolids, is often
shortened to sludge throughout this chapter for simplicity.
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
Table 16.1 National Estimates of MP&M Pollutants Loadings
POTW Effects
Activated Sludge Inhibitio
# of Pollutants
million Ibs/yr
Sludge Contamination
# of Pollutants
million Ibs/yr
HAP (Explosivity)
# of Pollutants
million Ibs/yr
Baseline
n
89
1,031
8
31.7
35
2.1
Proposed
Option
89
328
8
1.61
35
1.11
Source: U.S. EPA analysis.
16.1 REDUCED INTERFERENCE WITH
POTW OPERATIONS
High levels of some MP&M pollutants (such as metals,
chlorobenzene, polyaromatic hydrocarbons, and oil and
grease) can kill bacteria that are required for the wastewater
treatment process (U.S. EPA, 1987). POTWs affected by
such "inhibition problems" may incur extra labor and
materials costs to maintain system operations. As a partial
measure of the economic benefits resulting from the
proposed regulation, EPA estimated the extent to which
reduced MP&M discharges would decrease pollutant
concentrations to below POTW pollutant inhibition
values, using the following steps:
* Estimate the baseline and post-compliance
influent concentrations for each POTW
receiving discharges from MP&M facilities, based
on annual pollutant loadings from the MP&M
facility, the number of POTW operating days per
year, and the gross volume of influent.
> Compare baseline and post-compliance influent
concentrations with available inhibition levels (see
Table E.5 in Appendix E).
> Estimate the change in the number of POTWs in
which influent concentrations of MP&M pollutants
exceed POTW inhibition values.
Adverse effects on POTW operations, including inhibition
of microbial degradation, are likely when influent
concentrations of one or more pollutants exceed an
inhibition value. EPA estimated influent concentrations in
excess of POTW inhibition values for the sample facilities,
and then extrapolated these findings to national estimates
using a differential weighting technique (see Appendix F).
EPA estimated that 515 POTWs had influent concentrations
that exceeded biological inhibition values for one or more of
18 pollutants in the baseline. (Table E. 12 in Appendix E
provides detailed information on pollutants exceeding
POTW inhibition criteria.) Exceedances would be
eliminated with post-compliance discharge levels under the
proposed option for 306 affected POTWs. Eliminating the
exceedances will result in operating cost savings to POTWs.
EPA has not estimated a monetary value for this benefit,
however, due to data limitations.
POTWs may impose local limits to prevent inhibitions. If
local limits are in place, the estimated reduction in potential
inhibition problems at the affected POTWs is overstated. In
this case, however, the estimated social cost of the MP&M
regulation is also overstated.
16.2 ASSESSING BENEFITS FROM
REDUCED SLUDSE CONTAMINATION
16.2.1 Data Sources
The analysis of POTW benefits from improved sludge
quality draws on several data sources.
The ง308 POTW surveys provide most of the required
information. EPA collected information from 147 POTWs
representing a 98 percent response rate to the 150 surveys
that were mailed. EPA also used the ง308 survey of MP&M
16-2
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
facilities. The two data collection efforts were not designed
to provide a match between the MP&M sample facilities and
the POTWs to which they discharge. EPA obtained a
significant amount of information from the POTW surveys,
but had substantially less information on the POTWs that
receive discharges from the MP&M facilities. To address
this data limitation, EPA used the POTW Survey data to
infer information on the key factors that are likely to
influence choice of sewage sludge use and disposal practices
for the POTWs receiving discharges from the MP&M
facilities. EPA also used other data sources in this analysis,
including Handbook for Estimating Sludge Management
Costs (EPA, 1985) and Regulatory Impact Analysis of the
Part 503 Sludge Regulation (EPA, 1993b).
The POTW Survey contains three sections. Section 1
provides general information on POTW location and size.
Section 2 provides data on the cost of administering
pre-treatment programs (see Appendix C). Section 3
contains data on the cost of treating and disposing of sewage
sludge and provides new and more consistent data for
analyzing the effect of reduced pollutant loadings on sewage
sludge management costs.
The POTW Survey asked for the following information:
* current sludge disposal practices;
* sludge disposal costs for one or more disposal
methods;
* reasons for not using a less expensive disposal
method;
* number of MP&M facilities discharging to the
POTW, by flow size (less than 1 million gal/year;
1-6.25 million gal/year; greater than 6.25 million
gal/year);
* total metal loadings discharged to the POTW from
all sources; and
* percentage of total metal loadings attributable to
MP&M facilities.
The POTW Survey was intended to address data limitations
encountered in the Phase 1 analysis, particularly the
inadequacy of information about POTWs that receive
discharges from the MP&M sample facilities. The only
information available for the Phase I analysis was POTW
geographic location, influent volume, and the metals content
of the discharge received from the sampled MP&M
facilities. Discharges to the POTW by non-sampled MP&M
facilities and by non-MP&M facilities were not known.
These discharges may significantly affect sewage sludge
quality, however, resulting in a discrepancy between
predicted and actual pollutant concentrations in sewage
sludge and the corresponding disposal practices. In
addition, lack of information on the factors that may
influence a POTWs decisions about sludge management
practices introduced additional uncertainty in the analysis.
EPA used the POTW Survey to calculate the following
parameters:
* baseline percentage of the total metal loadings to
POTWs by POTW flow category attributable to
MP&M facilities;
* post-compliance loading reductions for
non-sampled MP&M facilities discharging to the
receiving POTWs;
* costs of sewage sludge disposal practices; and
* percentage of qualifying sludge that is not
beneficially used for any of the following reasons:
lack of land; lower cost alternative; inability to
meet vector or pathogen requirements; poor
weather; stricter state standards; and other reasons.
16.2.2 Sludge Generation, Treatment,
and Disposal Practices
a. Sludge generation
POTWs generally treat wastewater from industrial indirect
dischargers along with domestic wastewater. Sludge results
from primary, secondary, and advanced wastewater
treatment. The extent and type of wastewater treatment
determine the chemical and physical character of the sludge.
Sludge may be conditioned, thickened, stabilized, and
dewatered to reduce its volume.
Sludge contains five classes of components: organic matter,
pathogens, nutrients, inorganic chemicals, and organic
chemicals. The mix and levels of these components
ultimately determine the human health and environmental
impact of sludge use/disposal, and so may also dictate the
most appropriate uses and disposal practices (EPA, 1993b).
Organic matter (the primary constituent of sludge) comes
from human waste, kitchen waste, and storm water runoff.
Organic and inorganic chemicals in sludge come from
industrial processes that discharge to municipal sewers. The
concentration of inorganic pollutants in sludge, including
metals, depends upon the volume and type of industrial
wastes discharged to the POTW, as well as the extent and
character of stormwater runoff.
b. Sludge use/disposal practices
After treatment, sludge can be used in the following ways:
Land Application: Spraying or spreading on the
land surface, injection below the surface, or
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
incorporation into the soil, for soil conditioning or
fertilization of crops or vegetation. Agricultural
lands (pasture, range land, crops), forest lands
(silviculture), and drastically disturbed lands
(land reclamation sites) may all receive sludge;
Bagged Application: Collection of sludge in
containers for application to land (i.e., distribution
and marketing);
Surface Disposal: Disposal on land specifically set
aside for this use, including surface impoundments
(also called lagoons), sludge monofills (i.e.,
sludge-only landfills), and dedicated sites (i.e., land
on which sludge is spread solely for final disposal);
Co-disposal: Disposal in a municipal solid
waste landfill (MSWL) or hazardous waste
landfill, and
ป Incineration: Combustion of organic and inorganic
matter at high temperatures in an enclosed device.
Land application and bagged application are beneficial uses
of sludge. Both methods can be categorized as being "high"
or "low," depending on pollutant concentrations in sewage
sludge. "High" applications meet stringent limits on the
total concentration of a given pollutant at a given application
site. "High" sludge is exempt from meeting pollutant
loading rate limits and certain record-keeping requirements.
"Low" applications meet less stringent "ceiling" limits for
pollutants. Ceiling limits govern whether a sewage sludge
can be applied to land at all. "Low" applications require
more record-keeping because POTWs must track total
(cumulative) loadings applied to each given site, in addition
to tracking the concentration of sludge applied at any given
time.
Many POTWs use more than one use/disposal practice,
which helps to maintain flexibility and avoid the capacity
limitations of a single practice. The practice chosen depends
on several factors, including:
ป cost to prepare sludge for use/disposal;
ป pollutant concentrations;
ป market demand for sludge;
ป cost to transport sludge to use/disposal sites;
ป availability of suitable sites for land application,
landfilling, or surface disposal;
ป weather and other local conditions;
ป allowance of a safety factor to account for
unplanned or unforseen conditions;
ป state environmental regulations; and
ป public acceptance (EPA, 1993b).
The choice of use/disposal method is restricted by the
quality of the sludge generated by the POTW. Sludge for
beneficial uses must meet more stringent standards for
pollutant concentrations than sludge used or disposed of in
other ways. Similarly, sludge that is surface-disposed in an
unlined unit generally must meet more stringent standards
than sludge surface-disposed in a lined unit, disposed in an
MSWL, or incinerated. Sludge disposed in a MSWL must
meet more stringent standards than incinerated sludge.
Table 16.2 summarizes sludge use/disposal methods
according to the number and percent of dry metric tons
(DMT), based on information provided in Section 3 of the
ง308 POTW Survey.
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
Table 16.2: Sludge Use/Disposal (1996) by POTWs Discharging > 2
Million Gallons/Day"
Use/Disposal Sub-Class
Total Beneficial Use
Land Application-High
Bag Application-High
Land Application-Low
Bagged Application-Low
Total Surface Disposal
Surface Disposal: Unlined Unit
Surface Disposal: Lined Unit
Co-Disposal: Municipal Landfill
Incineration
Unknown: Other
All
Thousand DMT
2,873.4
1,143.6
351.5
1,378.3
0
572.7
347.2
225.5
2,213.5
1,129.9
543.2
^332^
Percent of DMT
39.2%
15.6%
4.8%
18.8%
0%
7.8%
4.7%
3.1%
30.2%
15.4%
7.4%
100.0%
a. The ง308 POTW Survey did not collect information from POTWs discharging < 2 million
gallons per day.
Source: U.S. EPA, POTW Survey.
As Table 16.2 shows, 39 percent of total sludge tons
reported by respondents is used beneficially (land
application and bagged application). Co-disposal in a
municipal landfill is the second most frequently used
disposal method, accounting for 30.2 percent of all sludge
disposed in the U.S. Surface disposal in unlined and lined
units, incineration, and "other" disposal methods account for
4.7 percent, 3.1 percent, 15.4 percent, and 7.4 percent of all
sludge tons, respectively. No sludge was sent to a hazardous
waste landfill by the POTW Survey respondents.
c. Pollutant limits and disposal options
Section 405(d) of the Clean Water Act, as amended, requires
EPA to specify acceptable management practices and
numerical limits for certain pollutants in sludge. The
Agency published Standards for the Use/Disposal of Sludge
(40 CFR Part 503, February 1993) to protect public health
and the environment from reasonably anticipated adverse
effects of pollutants in sludge (U.S. EPA, 1993a). The
standards include general requirements, pollutant limits,
management practices, operational standards, monitoring
frequency, record-keeping, and reporting for the final use
and disposal of sludge in four circumstances:
* sludge co-disposed with household waste in an
MSWL;
* sludge land-applied for beneficial purposes
(including bagged sludge);
* sludge disposed on land or on surface disposal
sites; and
* incinerated sludge.
With the exception of MSWLs, the standards for each
practice include numerical limits on sludge pollutant
concentrations. Part 503 sets limits on pollutant
concentrations for land application at two levels:
* Land Application-Low limits, which govern
whether a sludge can be applied to land at all; and
> more stringent Land Application-High limits which
define, in part, sludge that is exempt from meeting
certain record-keeping requirements.
For sludge meeting only the Land Application-Low limits,
Part 503 contains pollutant loading rate limits. These
determine the amount of sludge and associated pollutant
content that may be applied to a particular site.
EPA did not establish pollutant-specific, numerical criteria
for toxic pollutants of concern in the sludge disposed in
MSWLs, because the design standards applicable to
MSWLs are considered adequate to protect human health
and the environment. Also, MSWL sludge is co-disposed
with household waste, making precise numerical criteria
infeasible. The Solid Waste Disposal Facility Criteria (40
CFR Part 258, Federal Register 50978, October 9, 1991)
specify that POTWs using an MSWL must ensure that their
sewage is non-hazardous and passes the Paint Filter Liquid
Test.
The pollutant limits for sludge land application, surface
disposal, and incineration constrain a POTWs choice of
sludge use/disposal practice. Table 16.3 presents numerical
limits for the three sludge use/disposal practices for eight
MP&M pollutants. The land application pollutant limits
place restrictions on concentrations of metals in sludge; the
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
surface disposal criteria cover a subset of the metals
regulated for land application. The MP&M effluent
limitations guideline covers five metals and causes
incidental removal of the remaining three metals regulated
under the Part 503 sludge regulation. The proposed
regulation would improve quality of sewage sludge
generated by POTWs receiving discharges from MP&M
facilities and, as a result, would increase sludge use/disposal
options for the affected POTWs.
Pollutant
Arsenic
Cadmium
Copper
Lead
Mercury
Nickel
Selenium
Zinc
Table 16
Application
Low Limits (Low) ;
(mg/kg dry weight) i
75 I
85 I
4,300 I
840 I
57 I
420 I
100 I
7,500 I
.3: Sludge Use/Disposal Pollutant Limits
Limits
High Limits (High) ; Surface Disposal Limits
(mg/kg dry weight) i (mg/kg dry weight)3
41 j 73
39 j
1,500 j
300 j
17 j
420 j 420
36 j
2,800 I
MP&M Pollutants of
Concern
a. Pollutant limits for active sludge unit whose boundary is greater than 150 meters from the surface disposal site property line.
Source: Standards for the Use or Disposal of Sludge; Final Rules. 40 CFR Part 257 et al. Federal Register February 19, 1993.
d. Reasons for not land-applying qualifying
sludge
POTW characteristics including location, state regulations,
and community concerns also affect use/disposal methods
for sludge. The POTW Survey provided information on the
percentage of sludge that qualified for beneficial use but was
not beneficially used. Survey data indicate that 52 percent
of qualifying sludge was not land-applied, for the following
reasons:
* land application is more expensive than another
method;
* land is not available for sludge application;
* the cumulative pollutant loads at the land
application site used had been exceeded;
- the vector or pathogen requirements to land
apply could not be met at an acceptable cost; and
* inclement weather, concern over liability,
stakeholder complaints, stricter state standards,
desire to diversify practices, or technical problems.
Of the 52 percent of sludge that was not land-applied, only
12 percent of qualifying sludge was otherwise beneficially
used (i.e., sold in bags). Therefore, only 54 percent of the
total qualifying sludge is beneficially used.2 In addition,
POTW Survey data indicate that, on average, 7.5 percent of
all sludge that qualifies for surface disposal is not surface
disposed.
16.2.3 Overview of Improved Sludge
Quality Benefits
This section discusses potential economic productivity
benefits resulting from cleaner sludge, describes the
methodology used to estimate benefits to POTWs directly
affected by the regulation, and presents the results of the
analysis.
EPA expects the proposed regulation to reduce MP&M
facility discharges of eight metals with Part 503 limits. The
influent pollutant reductions to these POTWs translate into
sludge with reduced pollutant concentrations, allowing the
sludge to meet the criteria for lower-cost use/disposal
methods. The reduction in pollutants will then provide
many POTWs with greater flexibility in the disposal of their
sludge, and for some the opportunity to use less expensive
methods of sludge use/disposal. In some cases, wastewater
treatment systems may be able to use the cleaner sludge in
agricultural applications, generating additional agricultural
2 Percent Beneficially Used =
(100% - 52%)+{(52% x 12%yiOO%}.
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
productivity benefits. Numerous benefits will result from
reduced contamination of sludge, including the following:
* POTWs may have less expensive options for
use/disposal of sludge. Methods involving stricter
criteria pollutants are generally less expensive than
the alternatives. In particular, land application
usually costs substantially less than incineration or
landfilling. As a result of the proposed regulation,
sludge from some POTWs may meet more stringent
criteria for less expensive use/disposal methods.
* Some sludge currently meeting only Land
Application-Low Concentration limits and pollutant
loading rate limits would meet the more stringent
Land Application-High Concentration limits. Users
applying sludge meeting Land Application-High
pollutant limits would be exempt from meeting
pollutant loading rate limits. They would have
fewer record-keeping requirements than users of
sludge meeting only Land Application-Low
concentration and loading rate limits.
> By land-applying sludge, POTWs may avoid costly
siting negotiations for more contentious sewage
sludge use or disposal practices, such as
incineration.
* POTW sludge provides supplemental nitrogen,
which enhances soil productivity when land-
applied. Sludge applied to agricultural land, golf
courses, sod farms, forests, or residential gardens is
a valuable source of nitrogen fertilizer.
* Nonpoint source nitrogen contamination of water
may be reduced if sludge is used as a substitute for
chemical fertilizers on agricultural land. Compared
to nitrogen in most chemical fertilizers, nitrogen in
sludge is relatively insoluble in water. The release
of nitrogen from sludge occurs largely through
continuous microbial activity, resulting in greater
plant uptake and less nitrogen runoff than from
conventional chemical fertilizers.
* The organic matter in land-applied sludge can
improve crop yields by increasing the ability of soil
to retain water.
> Reduced concentrations of sludge pollutants not
currently regulated may reduce human health and
environmental risks. Human health risks from
exposure to these unregulated sludge pollutants
may occur from paniculate inhalation, dermal
exposure, ingestion of food grown in
sludge-amended soils, ingestion of surface water
containing sludge runoff, ingestion of fish from
surface water containing sludge runoff, or ingestion
of contaminated ground water.
* Land application of sludge satisfies an apparent
public preference for this practice of sludge
disposal, apart from considerations of costs and
risk.
This analysis assumes that POTWs will choose the least
expensive sludge use/disposal practice for which their
sludge meets pollutant limits. POTWs with sludge pollutant
concentrations exceeding the Land Application-High, Land
Application-Low, or surface disposal pollutant limits in the
baseline may be able to reduce sludge use/disposal costs
after MP&M facilities have complied with the proposed
effluent limitations.
As public entities, POTWs are not forced by the market to
act as profit-maximizing or cost-minimizing agents, but
rather are assumed to optimize their jurisdictional welfare
function. POTWs take factors other than cost into
consideration when determining their sludge use/disposal
methods. These factors may include the desire to be
perceived by the public as using sludge in an
environmentally friendly way, or the desire to enhance
relationships with clients by providing no-cost or low-cost
fertilizer. Greater flexibility in disposal practices may
therefore provide benefits beyond cost savings.
16.2.4 Sludge Use/Disposal Costs and
Practices
This section summarizes the estimated cost differences of
various use and disposal methods, based on the POTW
Survey.
Alternative sludge use/disposal practices costs vary
considerably among POTWs, based on several factors, the
most important being the availability of local agricultural
land or land suitable for surface disposal of sludge. Table
16.4 lists and ranks the use/disposal methods from least
expensive to most expensive, according to the average
qualitative ranking of each method in the POTW Survey.
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
Table 16.4:
Least Expensive
I
I
I
I
Most Expensive
National Estimate of Qualitative Ranking of
Use/Disposal Methods
Mean Rankings
Land Application-High
Land Application-Low
MSWL
Bagged Application-High
Surface Disposal in Unlined Unit
Bagged Application-Low
Surface Disposal in Lined Unit
Incineration
Hazardous Waste Landfill
Source: U.S. EPA, ง308 POTW Survey.
Land Application-Low and Land Application-High were
ranked as the two cheapest sewage sludge disposal options,
supporting the assumption that beneficial use of sludge
offers cost savings. The third least expensive option
co-disposal in an MSWL costs less on average than either
bagging sludge or surface disposing in an unlined unit.
EPA used the POTW Survey data as the primary source for
estimating an average difference in costs among certain
combinations of use/disposal practices (e.g., the cost savings
achieved by switching from incineration to land application).
Table 16.5 compares the cost savings realized by switching
to sludge land application and surface disposal practices
from less stringently regulated sludge use/disposal practices.
While on average the estimates provided in Table 16.5 are
expected to hold, the cost savings will vary for individual
POTWs. POTWs whose sludge qualifies for beneficial use
post-compliance but did not qualify for such use in the
baseline may achieve cost savings in some, but not all,
circumstances. For example, a POTW may not achieve cost
savings from agricultural application due to sludge
transportation costs or because there are less expensive
alternatives for that particular facility. Switching from
sewage sludge co-disposal in a MSWL to surface disposal
offers no savings to a POTW.
Table 16.5: Cost Savings for Shifts in Sludge Use/Disposal Practices (1999$/DMT)
Switch From:
Incineration
Surface Disposal on
Lined Unit
Surface Disposal on
Unlined Unit
Co-disposal: MSWL
Land Application-
Low
Switch To:
Land
Application3
(High)
$99.20
$120.77
$6.15
$95.95
$0.65-1.30
Land Application3
(Low)
$99.20
$120.77
$6.15
$97.95
Sold in a Bag for
Land Application
$91.65
$68.69
$0.56
$66.85
Surface Disposal
on Unlined Unit
$98.5
No Saving
Surface Disposal
on Lined Unit
No Saving
No Saving
a. EPA assumes that the costs of land application to forests, public contact sites, and reclaimed land are similar to the costs of agricultural
application.
Source: U.S. EPA analysis of the ง308 POTW Survey data.
The cost section of the POTW Survey did not distinguish
between low and high land application or low and high
bagged application. Therefore, costs provided in the survey
reflect the cost of both methods. To estimate the cost
savings of avoiding these requirements by meeting Land
Application-High limits, EPA used the compliance
requirements for meeting Land Application-Low limits for
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
bulk sludge (U.S. EPA, 1997). These cost savings provide a
partial measure of the monetary benefit of improved sludge
quality.
EPA estimates that the incremental record-keeping
associated with the cumulative Land Application-Low limits
requires two to four hours per application. Materials costs
for meeting these requirements should be negligible. EPA
estimated the record-keeping costs avoided from upgrading
sludge quality from Land Application-Low to Land
Application-High standards, using the following
assumptions:
ป a 40-acre site is a typical site size for land
application (approximately 16 hectares) (US EPA,
1997);
ป the typical application rate for land application is 7
DMT per hectare per application (US EPA, 1997);
and
ป labor at POTWs costs an average of $37 per hour
(1999$), based on the ง308 POTW Survey.3
Based on these assumptions, EPA estimated that $0.65 to
$1.30 would be saved per DMT of sludge upgraded from
Land Application-Low to Land Application-High.4
16.2.5 Quantifying Sludge Benefits
EPA estimated the number of POTWs receiving MP&M
discharges and the associated quantity of sludge that would
not meet Land Application-High pollutant limits, Land
Application-Low pollutant limits, or surface disposal
pollutant limits under both the baseline and regulatory
options. EPA then assumed that, as a result of compliance
with the MP&M effluent limitations guideline, a POTW
meeting all pollutant limits for a less costly sludge
use/disposal method would benefit from the reduced cost of
that particular method. EPA estimated the reduction in
sludge use/disposal costs using the steps described below:
1. Estimate total industrial baseline and post-compliance
loadings of Part 503 regulated metals for each POTW
with MP&M sample facility discharges;
2. Calculate the baseline and post-compliance sludge
pollutant concentrations for all MP&M wastewater
discharged to the POTW;
3. Compare POTW sludge pollutant concentrations with
sludge pollutant limits for surface disposal and land
application;
4. Estimate baseline and post-compliance sludge
use/disposal practices based on the estimated pollutant
concentrations in sewage sludge;
5. Identify POTWs that upgrade their sewage sludge
disposal practices under the proposed option; calculate
the economic POTW benefits by multiplying the cost
savings for the shift in practices by the quantity of
newly qualified sludge. Adjust the estimate of benefits
for the percentage of POTWs that cannot land apply
sewage sludge due to transportation costs or other
reasons, such as cold temperature; and
6. Estimate national benefits using MP&M sample facility
weights.
a. Step 1: Estimate total industrial baseline
and post-compliance loadings of Part 503
regulated metals
EPA estimated the quantities of Part 503 metals discharged
to POTWs receiving wastewater from MP&M sample
facilities and facilities operating in other metal discharging
industries.5 EPA used POTW Survey data to estimate the
total metal loadings and percent of total loadings discharged
to POTWs by MP&M facilities.
The POTW Survey provides the following information:
number of known MP&M facilities discharging to
the POTW,
ป total loadings of each regulated metal received by
the POTW, and
ป percent of the total metal loadings attributable to
MP&M industries.
Table 16.6 summarizes this information by POTW flow
volume.
3 See Appendix C of this EIA for detail.
4 Savings per DMT are calculated by dividing the estimated
labor cost per application ($37 per Hour * Hours per Application)
by the total amount of sludge disposed of per one application (16
Hectares * 7 DMT per hectare).
5 EPA did not include metals from residential wastewater due
to lack of data. The effect on the analysis of omitting residential
metal loadings is not known.
16-9
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
Table 16.6: MP&M Contribution
to Total Industrial Loadings Received by POTWs
MP&M Contribution
MP&MfadMes
small (<1 MG/year)
medium (1-6.25 MG/year)
large (>6.25 MG/year)
Chemicals
Arsenic
Cadmium
Copper
Lead
Mercury
Nickel
Selenium
Zinc
POTW size (million gallons per day)
2-10
Average numb
33.0
2.5
1.2
MP&Mperce
7.4
16.1
18.9
13.8
7.9
25.1
7.2
20.2
11-50
er ofMP&Mfacitii
106.0
9.1
2.9
ntage of total loadi
14.0
23.4
21.6
19.8
20.8
24.4
8.5
16.0
>50
'ies per POTW
269.6
85.0
16.3
ngs by weight
7.0
12.8
10.9
10.3
6.0
15.8
3.3
8.2
Source: U.S. EPA, ง308 POTW Survey.
EPA estimated total baseline metal loadings from all MP&M sources, as follows:
PLM, . =
k, i
LMP.,,
rail, k, i XAV8 Num Sm + LMPmedlUm, k, i *Av8 Nu Med + LMPlarge, k, i *Av8 Nu L8
Sample Sm
Sample Med
Sample Lg
(16.1)
where:
PLMV
LMP,
small,k,i
AvgNumSm
Baseline loadings of pollutant k
to POTW; from all MP&M
sources (ug/year);
loadings of pollutant k from small
(< 1 MG/year) sample MP&M
facilities, discharging to POTW /'
(ug/year);
the average number of small
MP&M facilities discharging to
POTW /'; EPA estimated the
average number of MP&M
facilities of a given size (small,
medium, large) that discharge to
POTWs in given flow categories,
based on the ง308 POTW Survey
(see Table 16.6);6-7
6 EPA classified MP&M facilities as small, medium, and
large flow in the POTW Survey, based on their discharge volume.
7 This analysis considers the following POTW flow
categories: (1) from 2 MG/day tolO MG/day; (2) from 11 to 50
MG/day; and (3) greater than 50 MG/day.
SampleSm = number of MP&M small
(< 1 MG/year) sample facilities
discharging to POTW;
LMPmedll]m k j = loadings of pollutant k from
medium (1-6.25 MG/year)
sample MP&M facilities,
discharging to POTWs (ug/year);
AvgNumMed = the average number of medium
MP&M facilities discharging to
POTW / (based on the POTW
flow category (see Table 16.6));
SampleMed = number of MP&M medium (1-
6.25 MG/year) sample facilities
discharging to POTW /';
loadings of pollutant k from large
(>6.25 MG/year) sample MP&M
facilities discharging to POTW /'
(ug/year);
AvgNumLg = the average number of large
MP&M facilities discharging to
POTW/ (based on the POTW
flow category (see Table 16.6));
and
SampleLg = number of MP&M large (>6.25
MG/year) sample facilities
discharging to POTW /'.
LMP,
laige,k,i
16-10
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
EPA estimated total baseline metal loadings from all
industrial sources using data from the POTW Survey, as
follows:
PLM,
PL, =
k' ' %MP,
100%
(16.2)
where:
PLV
PLMV
100%
%MPV
total baseline loadings of pollutant k
from all industrial sources to POTW /
(ug/year),
baseline loadings of pollutant k to
POTW / from all MP&M sources
(ug/year),
the total reported POTW transfers of
pollutant k from all industrial sources,
and
the percentage of total reported
POTW transfers of pollutant k from
MP&M facilities in a given POTW
flow category (see Table 16.6),
Post-compliance pollutant loadings to POTWs are calculated
by subtracting the reduction in MP&M loadings due to the
regulation from the estimated total baseline loadings.
b. Step 2: Calculate baseline and
post-compliance sludge quality
First, for each metal with limits under the Part 503
regulation, EPA calculated POTW influent concentrations
based on the pollutant loading and POTW flow rates, as
follows:
PL,,
FL. x OD.
(16.3)
where:
OD,
POTW influent concentration of pollutant
/t(ug/liter) for POTW/;
total loading of pollutant k to POTW /
(ug/year);
POTW / flow (liters/day); and
POTW /' operation days (365 days/year).
Second, EPA calculated sludge pollutant concentrations for
each pollutant:
PC
r^
where:
TRE, x PF, x SG
(16.4)
concentration of pollutant k in POTW /'
sludge (mg/kg or ppm),
ICki = POTW /' influent concentration of
pollutant k (ug/liter or ppb),
TREk = treatment removal efficiency for pollutant
k (unitless),
PFk = sludge partition factor for pollutant k
(unitless), and
SG = sludge generation factor ((L-mg)/(ug-kg)
orppm/ppb).
The partition factor represents the fraction of the pollutant
load expected to partition to sludge during wastewater
treatment. This factor is chemical-specific. EPA used 1988
data on volume of sewage sludge produced (Federal
Register, February 19, 1993, p.9257) and volume of
wastewater treated (1988 Needs Survey, Table C-3) to
estimate the sludge generating factor. The estimated sludge
generation factor is 7.4, indicating that concentration in
sludge is 7.4 ppb dry weight for every 1 ppb of pollutant
removed and partitioned to sludge.
c. Step 3: Compare sludge pollutant
concentrations at each POTW with limits for
surface disposal and land application
EPA next compared sludge baseline and post-compliance
pollutant concentrations to pollutant limits for land
application and surface disposal using the following
formula:
PC,
SE =\ if i
p CR
(16.5)
k,P
where:
SEP
PCk
sludge exceeds concentration limits for
disposal or use practice, p;
sludge pollutant, k, concentration; and
sludge pollutant, k, criterion for disposal
or use practice, p.
If any sludge pollutant concentration at a POTW exceeds the
pollutant limit for a sludge use/disposal practice in the
baseline (i.e., PC/CR >1), then EPA assumed that the
POTW cannot use that sludge use/disposal practice. If, as a
result of compliance with the MP&M regulation, a POTW
meets all pollutant limits for a sludge use/disposal practice
(i.e., PC/CR < 1), that POTW is assumed to benefit from an
increase in sludge use/disposal options.
d. Step 4: Estimate baseline sludge
use/disposal practices at POTWs that can
meet land application or surface disposal
pollutant limits post-compliance
Benefits from changes in sludge use/disposal practices
depend on the baseline practices employed. EPA assumes
that POTWs choose the least expensive sludge use/disposal
16-11
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
practice for which their sludge meets pollutant limits.
POTWs with sludge qualifying for land application in the
baseline are assumed to dispose of their sludge by land
application; likewise, POTWs with sludge meeting surface
disposal pollutant limits (but not land application pollutant
limits) are assumed to dispose of their sludge on surface
disposal sites.
EPA assumed that the mix of surface disposal practices
employed by POTWs in the baseline (e.g., surface disposal
on a lined unit and surface disposal on an unlined unit)
matches that of national surface disposal practices as
calculated from the POTW Survey (see Table 16.2).
POTW Survey data indicate that 24 percent of total sludge
meeting Land Application-High standards is sold in bags
and 76 percent is land-applied. None of the sludge meeting
Land Application-Low standards is sold in bags. Each
POTW meeting Land Application-High standards in the
post-compliance scenario is assumed to sell 24 percent of its
sludge in bags and to land-apply the remainder.
The POTW Survey shows that 39 percent of total surface
disposed sludge is disposed of in lined units and 61 percent
in unlined units. This mix of surface disposal practices may
not match the actual sludge disposal surface practices of any
individual POTW. In aggregate, however, the assumed
surface disposal practices are consistent with actual POTW
sludge surface disposal practices. Survey data also showed
that, on average, 7.5 percent of all sludge that qualifies for
surface disposal was not surface disposed.
POTWs generating sludge exceeding land application and
surface disposal pollutant limits in the baseline are assumed
to either incinerate sludge or place sludge in a MSWL. The
survey indicates that 34 percent of sludge not land-applied
or deposited in surface disposal sites is incinerated and 66
percent is placed in MWSLs. Each POTW exceeding
surface disposal and land application limits in the baseline is
assumed to incinerate 34 percent of its sludge and
co-dispose of the remainder. Again, this mix of sludge
use/disposal practices may not match the actual sludge
disposal practices of any single POTW; in aggregate,
however, the assumed distribution corresponds to actual
practices.
Using the sludge disposal cost differentials from Table 16.5,
EPA estimated savings for shifts into land application and
surface disposal from the assumed mix of baseline
use/disposal practices (see Table 16.7). As previously
discussed, EPA assumed that 46 percent of sludge could not
be used beneficially (land-applied or sold in bags) and
disposed less expensively through agricultural application of
sludge due to transportation costs, land availability, or
weather constraints. The Agency did not estimate benefits
for this percentage of the sludge newly qualified for land
application.
z. Step 5: Calculate economic benefits for
POTWs receiving wastewater from sample
MP&M facilities
Table 16.7 shows the cost savings for shifts from composite
baseline sludge use/disposal practices to land application or
surface disposal. Reductions in sludge use/disposal costs
are calculated for each POTW receiving wastewater from a
MP&M facility, using the following formula:
SCR. = FL.
where:
SCR,
S
CD,
S
2200
CD.
(16.6)
estimated sludge use/disposal cost
reductions resulting from the proposed
regulation for POTW / (1999$);
POTW /' wastewater flow (million
gallons/year);
sludge to wastewater ratio, assumed to be
1,127 Ibs. (dry weight) per million gallons
of water (Ibs./million gallons) and divided
by 2,200 to convert pounds to metric tons;
and
estimated cost differential between least
costly composite baseline use/disposal
method for which POTW /' qualifies and
least costly use/disposal method for which
POTW / qualifies post-compliance
(1999$/DMT).
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
Table 16.7: Cost Savings from Shifts in Sludge Use/Disposal Practices from
Composite Baseline Disposal Practices (1999$/DMT)
Baseline POTW Mix of Sludge
Use/Disposal Practices
Meets Land Application-Low
pollutant limits, but not Land
Application-High limits
Meets surface disposal pollutant
limits, but not Land Application-
Low limits
Assumed disposal mix:
39% lined unit
61% unlined unit
Does not meet land application
pollutant limits or surface disposal
pollutant limits
Assumed disposal mix:
34% incineration,
66% co-disposal
Post-Compliance POTW Sludge Use/disposal Practice
Agricultural
Application-High (76%
of sludge meeting Land
Application-High
pollutant limits)
$0.65-$1.30
$120.77
$6.15
$99.20
$95.97
Bagged Sludge
(24% of sludge
meeting Land
Application-High
pollutant limits)
N/Ab
$68.69
$0.56
$91.65
$66.85
Agricultural
Application-
Low
N/A
$120.77
$6.15
$99.20
$95.97
Surface Disposal3
(Meet surface pollutant
limits; do not meet land
application pollutant
limits)
N/A
N.A.
$0-$98.5
N/A
a. Surface disposal includes monofills, surface impoundments, and dedicated sites.
b. Not applicable (i.e., there is no cost savings).
Source: U.S. EPA, POTW Survey.
EPA assumed that only 54 percent of the sludge qualified
for land application is beneficially used (i.e., land-applied or
sold in bags). The remaining 46 percent of the sludge newly
qualified for land application will be disposed of by other
methods. EPA assumed that no cost savings will be
associated with 46 percent of the sludge qualified for land
application. To ensure that these benefits are not overstated,
this analysis includes an adjustment to the estimate of
national sludge use/disposal cost benefits for POTWs that
may be located at some distance from agricultural sites.
This adjustment does not apply to benefits from shifts into
surface disposal.
f. Step 6: Estimate national sludge benefits
EPA scaled the sludge use/disposal cost reductions to the
national level as follows:
NSCR = Y, (FWl x SCRi)
(16.7)
where:
NSCR
national estimated sludge use/disposal cost
reductions resulting from the proposed
regulation (1999$);
n = number of POTWs estimated to shift into
meeting surface disposal or land
application pollutant limits as a result of
MP&M effluent limitations;
FWt = facility sample weights for facility or
facilities discharging to POTW /'; and
SCR, = estimated sludge use/disposal cost
reductions resulting from the proposed
regulation for POTW / (1999$).
16.3 ESTIMATED SAVINGS IN SLUDSE
USE/DISPOSAL COSTS
Of the POTWs receiving discharge wastewater from MP&M
facilities, 6,953 POTWs exceed the Land Application-High
pollutant limits and 4,714 exceed the Land Application-Low
pollutant limits under the baseline discharge levels. EPA
estimated that 62 POTWs will be newly qualified for
lower-cost land application based on estimated reductions in
sludge contamination. EPA also estimated that 21 POTWs
that previously met only the Land Application-Low limits
would, as a result of regulation, meet the more stringent
Land Application-High limits.
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
Table 16.8: POTW Exceeding Land Application Limits in the Baseline and Under the Proposed Rule
Numbers of POTWs
Exceeding the Limits
Land Application-High
Land Application-Low
Baseline
6,953
4,714
Proposed Rule
6,889
4,652
Change
64
62
Source: U.S. EPA analysis.
EPA used the estimated sludge use/disposal cost
differentials presented in Table 16.7 to calculate cost
savings for the POTWs expected to upgrade their sludge
disposal practices. The benefits are estimated at $61.1 to
$61.5 million (1999$) annually for the proposed option.
Table 16.9 shows the cost savings by shift in disposal
method.
These estimated benefit values reflect only part of the
economic benefits expected to result from reduced pollutant
concentrations in MP&M discharges to POTWs, and the
lower pollutant concentrations of the resulting sludge. EPA
expects but did not quantify additional benefits from
meeting the Land Application-High limits:
1. If a POTWs sludge meets Land Application-High
limits, farmers may be more easily convinced to take the
sludge, reducing the time a POTW has to spend to
locate application sites.
2. POTWs may be able to sell the sludge they currently
give away.
3. Composted sludge may command a higher price than
received for composted sludge subject to annual limits
(which apply when the sludge does not meet Land
Application-High limits).
4. Facilities whose land application is limited only by
vectors could decide to meet the more stringent Class A
pathogen and vector attraction reduction requirements
(by composting sludge, for example) if the subsequent
product is not subject to any Part 503 requirements,
increasing its ease of distribution.
These benefits are not easily monetized.
Table 16.9: National Estimate of Cost Savings from Shifts in Sludge Use/Disposal
Under the Proposed Option
Shift
Upgrade from minimum Land Application-Low limits
to Land Application-High pollutant limits
Upgrade from not meeting land application or surface
disposal limits to Land Application-High pollutant
limits
Upgrade from not meeting land application or surface
disposal limits to Land Application-Low pollutant
limits
Total
Category /Number of
POTWs
21
43
19
83
Associated Sludge
Quantity (DMT/Year)
510,600
661,227
529,945
1,701,712
Estimated Benefits
(million 1999$)
$0.33 to $0.66
$32.9
$27.9
$61.1 to $61. 5
Source: U.S. EPA analysis.
16.4 METHO&OLoey LIMITATIONS
EPA used the POTW Survey to develop estimates of the
cost-saving differentials for the various sludge use/disposal
practices. Sludge use/disposal costs vary by POTW. The
POTWs affected by the MP&M regulation may face costs
that differ from those estimated. As a result, the analysis
may over- or under-estimate the cost differentials.
16-14
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
POTW Survey data were also used to estimate metal
loadings to POTWs in the baseline analysis. There are two
major limitations associated with this approach:
* The baseline metal loadings from individual
MP&M facilities of interest may differ from this
estimate. The effect of using the ง308 survey data
to characterize the POTWs that receive MP&M
discharges is therefore not known.
> The total share of metals coming from MP&M
facilities is likely to be underestimated because
lower flow MP&M facilities are not always known
by the POTW. During the pretest of the MP&M
POTW questionnaire, POTWs told EPA that they
were not aware of many of the lower flow facilities
that were discharging to them, the POTW would
have to use the phone book in order to find and
permit these facilities. EPA is consequently
proposing to exempt low flow facilities in the
general metals and only oily wastes indirect
discharge categories.
This analysis assumes that the mix of disposal practices
estimated for a specific POTW may not match the actual
sludge disposal practices used by that POTW. We know
that the mix in the aggregate, as confirmed by the POTW
Survey, is correct. The practices used in this analysis are
therefore consistent with actual POTW sludge surface
disposal practices. Because accurate assumptions for
specific POTWs could not be made, the analysis may over-
or underestimate the cost differentials.
EPA did not estimate changes in risk associated with
changes in sludge. Nor did EPA estimate the productivity
benefits of removing any pollutants from the sludge other
than the eight metals discussed above.
EPA quantified, but did not monetize economic benefits
from reducing interference with POTW operations. EPA
did not estimate cost reductions that occur at POTWs with
sludge inhibition problems caused by MP&M discharges.
These omissions thereby underestimate the benefits of the
regulation.
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
GLOSSARY
hazardous air pollutants (HAPs): air pollutants that
are not covered by ambient air quality standards but which,
as defined in the Clean Air Act, may present a threat of
adverse human health effects or adverse environmental
effects. Such pollutants include asbestos, beryllium,
mercury, benzene, coke oven emissions, radionuclides, and
vinyl chloride. MP&M pollutants include but are not
limited to: chlorobenzene, dioxin,l,4-, isophorone, and
pyrene.
(http://www.epa.gov/OCEPAterms/hterms.html)
hazardous waste landfill: an excavated or engineered
site where hazardous waste is deposited and covered.
(http://www.epa.gov/OCEPAterms/hterms.html)
influent concentrations: measure of a pollutant's
concentration in wastewater being received by a POTW for
treatment (See also: pollutant inhibition values).
interference: is the obstruction of a routine treatment
process of POTWs that is caused by the presence of high
levels of toxics, such as metals and cyanide in wastewater
discharges. These toxic pollutants kill bacteria used for
microbial degradation during wastewater treatment (See:
microbial degradation).
microbial degradation: the breakdown of organic
molecules via biochemical reactions occurring in living
microorganisms such as bacteria, algae, diatoms, plankton,
and fungi. POTWs make use of microbial degradation for
wastewater treatment purposes. This process is inhibited by
the presence of toxics such as metals and cyanide because
these pollutants kill microorganisms.
municipal solid waste landfill (MSWL): common
garbage or trash generated by industries, businesses,
institutions, and homes. Also known as municipal solid
waste. (http://www.epa.gov/OCEPAterms/mterms.html)
pathogens: microorganisms (e.g., bacteria, viruses, or
parasites) that can cause disease in humans, animals and
plants. (http://www.epa.gov/OCEPAterms/pterms.html)
pollutant inhibition values: determined threshold
concentration for a pollutant, which when exceeded by the
pollutant's influent concentration in wastewater received for
treatment will have adverse effects on POTW operations,
such as inhibition of microbial degradation (See: microbial
degradation).
publicly owned treatment works (POTWs): a
treatment works as defined by section 212 of the Act, which
is owned by a State or municipality. This definition includes
any devices or systems used in the storage, treatment,
recycling, and reclamation of municipal sewage or industrial
wastes of a liquid nature.
(http://www.epa.gov/owm/permits/pretreat/final99.pdf)
silviculture: management of forest land for timber.
(http://www.epa.gov/OCEPAterms/sterms.html)
vector: 1. An organism, often an insect or rodent, that
carries disease. 2. Plasmids, viruses, or bacteria used to
transport genes into a host cell. A gene is placed in the
vector; the vector then "infects" the bacterium.
(http://www.epa.gov/OCEPAterms/vterms.html)
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MP&M EEBA Part III: Benefits
Chapter 16: POTW Benefits
ACRONYMS
DMT: dry metric tons
HAPs: hazardous air pollutants
MSWL: municipal solid waste landfill
POTWs: publicly-owned treatment works
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MP&M EEBA Part III: Benefits Chapter 16: POTW Benefits
REFERENCES
Solid Waste Disposal Facility Criteria (40 CFR Part 258, Federal Register 50978, October 9, 1991).
Standards for the Use/Disposal of Sludge (40 CFR Part 503, February 1993).
U.S. EPA. 1985. Handbook for Estimating Sludge Management Costs
U.S. EPA. 1987. Guidance for Preventing Interference with POTW Operations.
U.S. EPA. 1988. National Sewage Sludge Survey.
U.S. EPA. 1993a. Standards for the Use and Disposal of Sludge; Final Rules. 40 CFR Part 257 et al., Federal Register,
February 19.
U.S. EPA. 1993b. Regulatory Impact Analysis of the Part 503 Sludge Regulation. Final. Office of Water, March. EPA
821-12-93-006.
U.S. EPA. 1997. Economic Assessment for Proposed Pretreatment Standards for Existing and New Sources for the
Industrial Laundry Point Source Category. Office of Water. EPA 821-R-97-008 (pp 10-51 - 10-54).
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MP&M EEBA Part III: Benefits
Chapter 17: Environmental Justice & Protection of Children
Chapter 17: Environmental Justice
& Protection of Children
INTRODUCTION
Executive Order 12898 requires that, to the greatest extent
practicable and permitted by law, each federal agency must
make achieving environmental justice part of its mission.
EPA examined whether the proposed regulation will
promote environmental justice in areas affected by MP&M
discharges.
The proposed rule is not subject to Executive Order 13045,
"Protection of Children from Environmental Health Risks
and Safety Risks" (62 FR 19885, April 23, 1997), because it
is based on technology performance and not on health or
safety risks. The regulation is still expected to reduce lead
and other pollutants that affect children's health. EPA has
therefore analyzed the reduction of children's health impacts
associated with the MP&M regulation.
EPA concludes that the proposed rule reduces risks to
disadvantaged populations (e.g., subsistence anglers), and
that MP&M discharges have a disproportionally high
environmental impact on minority populations, based on the
demographic characteristics of the populations residing in
the counties affected by MP&M discharges.
The following three sections present EPA's environmental
justice analysis. Section 17.1.1 discusses the proposed
rule's impacts on subsistence anglers. Section 17.1.2
assesses whether MP&M discharges have a
disproportionally high impact on minority populations.
Section 17.2 addresses the proposed regulation's effects on
children from subsistence and recreational fishing families.
17.1 ENVIRONMENTAL JUSTICE
17.1.1 Changes in Health Risk for
Subsistence Anglers
Subsistence anglers include low-income and minority
populations that rely heavily on fishing for their food
supply. Subsistence anglers are at a disproportionally higher
CHAPTER CONTENTS:
17.1 Environmental Justice 17-1
17.1.1 Changes in Health Risk for Subsistence
Anglers 17-1
17.1.2 Demographic Characteristics of
Populations Living in the Counties
Near MP&M Facilities 17-3
17.2 Protection of Children from Environmental
Health And Safety Risks 17-8
Glossary 17-10
Reference 17-11
risk from MP&M pollutants than other people who eat fish
because their diets rely heavily on fish caught in local
waters.
EPA estimated changes in cancer and systemic health risk to
subsistence anglers and recreational fishermen in Chapter
13, Human Health Benefits. EPA's estimates show that
subsistence anglers have a significantly higher average
lifetime cancer risk from fish consumption than do
recreational anglers at the baseline discharge levels.
Subsistence fishing families also have a greater risk of
systemic health effects in the baseline. EPA's analysis of
changes in adverse health effects from the proposed rule
show that subsistence anglers receive a large share of
benefits, due to their disproportionately higher baseline risk.
a. Cancer risk
EPA estimates that approximately 3,772,703 subsistence
anglers fish 58,530 MP&M reaches nationwide. Individuals
in subsistence fishing households are exposed to 13 cancer
causing agents that are discharged by 62,752 MP&M
facilities to our nation's waters. The estimated average
lifetime cancer risk in the baseline for subsistence and
recreational anglers is 20.3 in one million and 8.08 in one
million, respectively. The estimated reduction in average
lifetime cancer risk for subsistence anglers is more than
double the reduction in risk for sport anglers (i.e., 7.70 in
one million vs. 3.77 in one million) (see Table 17.1).
17-1
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MP&M EEBA Part III: Benefits
Chapter 17: Environmental Justice & Protection of Children
Table 17. 1 : Estimated National Changes in Average Lifetime Cancer Risk to Subsistence vs. Recreational
Anglers
(62,752 MP&M Facilities)
Exposed Population Category
Subsistence Anglers
Recreational Anglers
Average Lifetime Cancer Risk per Individual
Baseline
0.00002030
0.00000808
Preferred Option
0.00001260
0.00000431
Estimated Changes in Individual
Lifetime Cancer Risk
Preferred Option
0.00000770
0.00000373
Source: U.S. EPA analysis.
b. Systemic health risk
The Agency conducted a similar analysis to assess
reductions in systemic health risks from fish consumption.
This study used the hazard ratio analysis performed and
discussed in Chapter 13. A hazard ratio greater than one
(HR > 1) indicates that individuals are expected to ingest
MP&M pollutants at rates sufficient to pose a significant
risk of suffering systemic health effects.
Table 17.2 presents systemic health risk analysis results for
the fish consumption pathway. These results show that
pollutant discharges from MP&M facilities are likely to
have a disproportional impact on subsistence anglers.
Approximately 320,000 subsistence anglers fish 627 reaches
to which 885 sample MP&M facilities directly or indirectly
discharge. Anglers fishing 18 of these reaches ingest
MP&M pollutants at rates sufficient to pose a significant
risk of health effects at the baseline discharge levels.
Approximately 7,000 subsistence anglers face a hazard ratio
greater than one. This figure represents 2.2 percent of all
subsistence anglers on MP&M sample facility reaches. A
much smaller proportion of recreational anglers (0.15
percent) face a hazard ratio of greater than one under
baseline conditions.
The number of subsistence anglers at systemic health risk
from the sample MP&M facility discharges is reduced by
4,616 (66 percent) (see Table 17.2). The actual number of
subsistence anglers expected to benefit from reduced
systemic health risk from the MP&M regulation is much
greater, because this analysis includes only 885 MP&M
facilities, not the full 62,752 whose discharges will be
affected by the proposed regulation.1 The proportion of
recreational anglers expected to suffer systemic health
effects after the MP&M rule is implemented declines from
0.15 to 0.05 percent. While the proposed rule does not
eliminate the differential risks to subsistence anglers, it does
provide the majority of benefits to the disadvantaged
populations at greatest risk in the baseline.
1 EPA did not evaluate non-cancer benefits at the national
level due to analytic tractability issues. These issues come about
because the exact location of facilities represented by sample
weights is unknown.
77-2
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MP&M EEBA Part III: Benefits
Chapter 17: Environmental Justice & Protection of Children
Table 17.2: Estimated Changes in Systemic Health Risk to Subsistence and Recreational Anglers
Regulatory Status
Subsistence Anglers
Baseline3
Preferred Option
Recreational Anglers
Baseline3
Preferred Option
Total Exposed
Anglers
320,366
320,366
6,407,076
6,407,076
Anglers
Exposed to HR>1
Number of
Individuals
6,971
2,355
9,765
2,897
Percent of Total
Exposed
Individuals
2.2%
0.7%
0.15%
0.05%
Anglers Benefiting from
the MP&M Rule
Number of
Individuals
4,616
6,868
Percent of
Baseline
66%
70%
a. This analysis is based on 885 facilities.
Source: U.S. EPA analysis.
17.1.2 Demographic Characteristics of
Populations Living in the Counties Near
MP&M Facilities
EPA assessed whether adverse environmental, human
health, or economic effects associated with MP&M facility
discharges are more likely to affect minorities and low-
income populations. This analysis uses the 1990 Census
data on the race, national origin, and income level of
populations residing in counties traversed by reaches
receiving discharges from 885 sample MP&M facilities.
The 885 sample facilities are located in 643 counties in 46
states (excluding Alaska, Hawaii, Nevada, and Wyoming).
This survey was designed to provide a representative
coverage of various types of MP&M facilities, but not of
their geographical location. EPA is therefore able to analyze
only the location characteristics of the sample facilities, and
not all 62,752 MP&M dischargers.
EPA compared demographic data on the counties traversed
by sample MP&M reaches with the corresponding state
level indicators. Table 17.3 presents the results of this
analysis:
> Counties affected by MP&M effluents tend to have
a larger proportion of African-Americans in their
populations than the state average in 41 of the 46
states included in the analysis. The proportion of
African-Americans in the counties affected by
MP&M discharges ranges from about 0.6 percent
in Montana to 41.4 percent in Louisiana (see Table
17.3). The state averages of the proportion of
African-Americans are lower, ranging from 0.3
percent in Montana to 35.6 in Mississippi. In five
states (District of Columbia, North Carolina, South
Carolina, Vermont, and West Virginia), the
proportion of African-Americans in MP&M
counties corresponds to the state averages. Of
these, however, only two states (NC and SC) are
associated with more than one sample MP&M
facility. The proportion of Native Americans in the
population of counties affected by MP&M
effluents is less than or equal to the state average in
42 of the 46 states. In 38 of the 46 states, counties
affected by MP&M effluents have a larger
proportion of Asians and Pacific Islanders in their
populations than the state average. Both these
population groups, however, comprise only a very
small part of the total population of most states.
Other socioeconomic characteristics of the
populations residing in the counties abutting
reaches affected by MP&M discharges generally
reflect state averages. These characteristics include
percent of population below poverty level, percent
unemployed, and percent children.
Counties abutting reaches affected by MP&M
effluents tend to have slightly higher median
17-3
-------
MP&M EEBA Part III: Benefits
Chapter 17: Environmental Justice & Protection of Children
incomes than the state-level median income. EPA
calculated median income for the group of counties
receiving MP&M discharges as an average of each
county's median household income.2 EPA
calculated this summary variable in place of the
true median household income for which
appropriate census data are not available.
Comparing this weighted average median income to
the state-level median income may introduce
uncertainty in the analysis.
2 Average income in MP&M counties =
Ij Median Income (i) x Number of Households (i)/I Number of
Households (i) where i is a sample MP&M county.
17-4
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MP&M EEBA Part III: Benefits
Chapter 17: Environmental Justice & Protection of Children
Table 17.3: County Level Comparison of Demographic Data: Counties with Sample MP&M Facilities
Versus Entire State
State
Alabama
MP&M Only
Entire State
Arizona
MP&M Only
Entire State
Arkansas
MP&M Only
Entire State
California
MP&M Only
Entire State
Colorado
MP&M Only
Entire State
Connecticut
MP&M Only
Entire State
Delaware
MP&M Only
Entire State
District of Colum
MP&M Only
Entire State
Florida
MP&M Only
Entire State
Georgia
MP&M Only
Entire State
Idaho
MP&M Only
Entire State
Illinois
MP&M Only
Entire State
Indiana
MP&M Only
Entire State
Iowa
MP&M Only
Entire State
Kansas
MP&M Only
Entire State
Counties
10
67
5
15
17
75
26
58
7
63
1
3
>ia
1
1
22
67
22
159
1
44
27
103
36
93
8
99
8
105
I % Native I
! % ! American, ! % Asian !
1 African- j Eskimo, or; or Pacific: Median
% White ; American i Aleut i Islander i Income
70.44%! 28.27%! 0.43%! 0.73%! $26:418
73.63%! 25.24%! 0.45%! 0.54%! $23:597
81.56%! 3.27%! 4.49%! 1.59%! $28:918
80.97%! 3.00%! 5.58%! 1.48%! $27:540
82.29%! 16.43%! 0.58%! 0.45%! $23:676
82.71%! 15.89%l 0.61%! 0.51%! $21,147
67.61%! 7.90%! 0.73%! 10.34%! $36:584
69.07%! 7.39%! 0.84%! 9.57%! $35:798
86.46%! 5.39%! 0.76%! 2.27%! $32:040
88.31%! 3.98%! 0.87%! 1.80%! $30:140
87.09%! 8.32%! 0.21%! 1.49%! $42:319
87.09%! 8.32%! 0.21%! 1.49%! $41,721
80.50%! 16.41%! 0.17%! 1.54%! $38:617
80.36%! 16.83%! 0.33%! 1.32%! $34:875
29.61%! 65.87%! 0.26%! 1.85%! $30:727
29.61%! 65.87%! 0.26%! 1.85%! $30:727
82.64%! 13.71%! 0.29%! 1.26%! $28:200
83.13%! 13.57%! 0.33%! 1.16%! $27:483
67.53%! 29.89%! 0.21%! 1.67%! $33:979
71.06%! 26.93%! 0.24%! 1.14%! $29:021
93.78%! 0.54%! 2.41%! 1.28%! $26:275
94.44o/0i 0.36%! 1.46%! 0.90%! $25:257
74.05%! 17.58%! 0.21%! 2.96%! $34:825
78.37%! 14.79%! 0.21%! 2.49%! $32:252
87.27%! 10.73%! 0.25%! 0.80%! $28:865
90.59%! 7.75%! 0.26%! 0.66%! $28:797
94.34o/0i 4.19%! 0.26%! 0.65%! $27:057
96.70%! 1.70%! 0.28%! 0.88%! $26:229
87.10%! 8.79%! 0.89%! 1.52%! $32:647
90.16%! 5.73%! 0.94%! 1.26%! $27:291
% Below
Poverty
Level
16.76%
18.34%
14.68%
15.74%
16.04%
19.07%
12.54%
12.51%
10.45%
11.68%
6.82%
6.82%
7.54%
8.71%
16.87%
16.87%
12.67%
12.69%
11.87%
14.65%
13.78%
13.25%
11.50%
11.91%
11.31%
10.68%
12.58%
11.48%
9.71%
11.48%
% Un-
employed
6.75%
6.87%
6.75%
7.17%
6.04%
6.76%
6.58%
6.65%
5.64%
5.74%
5.36%
5.36%
3.82%
3.99%
7.16%
7.16%
5.88%
5.78%
5.35%
5.74%
6.20%
6.15%
6.70%
6.64%
5.88%
5.74%
5.64%
4.53%
5.02%
4.70%
o/
/o
Children
26.21%
26.23%
26.45%
26.70%
25.87%
26.43%
25.90%
26.01%
25.85%
26.10%
22.81%
22.81%
23.97%
24.47%
19.22%
19.22%
21.90%
22.14%
25.85%
26.71%
32.52%
30.58%
25.97%
25.79%
25.93%
26.29%
26.54%
25.91%
27.41%
26.72%
17-5
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MP&M EEBA Part III: Benefits
Chapter 17: Environmental Justice & Protection of Children
Table 17.3: County Level Comparison of Demographic Data: Counties with Sample MP&M Facilities
Versus Entire State
State
Kentucky
MP&M Only
Entire State
Louisiana
MP&M Only
Entire State
Maine
MP&M Only
Entire State
Maryland
MP&M Only
Entire State
Massachusetts
MP&M Only
Entire State
Michigan
MP&M Only
Entire State
Minnesota
MP&M Only
Entire State
Mississippi
MP&M Only
Entire State
Missouri
MP&M Only
Entire State
Montana
MP&M Only
Entire State
Nebraska
MP&M Only
Entire State
New Hampshire
MP&M Only
Entire State
New Jersey
MP&M Only
Entire State
New Mexico
MP&M Only
Entire State
New York
MP&M Only
Entire State
Counties
38
120
10
64
4
17
9
24
9
14
22
84
16
88
10
82
18
115
1
56
8
93
2
10
12
21
3
33
32
63
I % Native I
! % ! American, ! % Asian !
1 African- j Eskimo, or; or Pacific: Median
% White ; American i Aleut i Islander i Income
88.90%! 9.98%! 0.20%! 0.68%! $25:500
92.06%! 7.11%; 0.19%! 0.47%; $22:534
56.65%! 41.40%l 0.22%! 1.17%! $22:834
67.30%! 30.77%! 0.48%! 0.94%! $21,949
98.07%! 0.58%! 0.44%! 0.75%! $29:686
98.35%! 0.44%! 0.52%! 0.56%! $27:854
66.13%! 28.97%! 0.28%! 3.50%! $40:452
71.03%! 24.87%! 0.30%! 2.88%! $39:386
89.53%! 5.20%! 0.19%! 2.41%! $37:847
89.95%! 4.94%! 0.21%! 2.34%! $36:952
77.53%! 19.72%l 0.47%! 1.27%! $32:064
83.47%! 13.87%! 0.63%! 1.11%! $31,020
92.56%! 3.40%! 0.90%! 2.59%! $35:651
94.47%! 2.17%l 1.13%! 1.75%! $30:909
61.17%! 38.23%! 0.14%! 0.35%! $24:559
63.46%! 35.59%! 0.34%! 0.49%! $20:136
79.23%! 18.78%! 0.33%! 1.10%! $28:883
87.68%! 10.69%l 0.44%! 0.77%! $26:362
97.70%! 0.59%! 0.54%! 0.35%! $22:658
92.78%! 0.26%! 5.98%! 0.53%! $22:988
90.67%! 6.67%! 0.55%! 1.20%! $29:801
93.83%! 3.62%! 0.80%! 0.80%! $26:016
97.57%! 0.77%! 0.23%! 0.97%! $39:194
98.02%! 0.65%! 0.22%! 0.81%! $36:329
77.33%! 14.43%l 0.19%! 4.03%! $42:046
79.37%! 13.39%l 0.19%! 3.49%! $40:927
76.59%! 2.51%l 4.85%! 1.35%! $27:220
75.81%! 1.97%l 8.85%! 0.95%! $24:087
71.09%! 17.98%! 0.32%! 4.31%! $34:563
74.47%! 15.90%l 0.33%! 3.83%! $32:965
% Below
Poverty
Level
15.53%
19.03%
24.40%
23.58%
9.98%
10.80%
8.73%
8.27%
8.94%
8.93%
14.05%
13.12%
8.26%
10.22%
21.21%
25.21%
12.04%
13.34%
15.20%
16.07%
9.70%
11.14%
5.77%
6.42%
7.76%
7.58%
15.16%
20.61%
13.55%
13.03%
% Un-
employed
6.48%
7.37%
10.25%
9.65%
5.97%
6.65%
4.51%
4.30%
6.75%
6.72%
8.58%
8.24%
4.53%
5.15%
7.28%
8.43%
6.27%
6.16%
6.53%
6.96%
3.89%
3.66%
6.02%
6.22%
5.96%
5.75%
6.70%
8.02%
7.08%
6.88%
o/
/o
Children
25.44%
25.93%
28.43%
29.13%
24.29%
25.19%
23.96%
24.31%
22.56%
22.46%
26.67%
26.48%
26.12%
26.69%
28.83%
29.04%
25.21%
25.71%
25.62%
27.88%
26.79%
27.19%
25.52%
25.16%
23.02%
23.27%
27.14%
29.47%
23.44%
23.66%
17-6
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MP&M EEBA Part III: Benefits
Chapter 17: Environmental Justice & Protection of Children
Table 17.3: County Level Comparison of Demographic Data: Counties with Sample MP&M Facilities
Versus Entire State
State
North Carolina
MP&M Only
Entire State
North Dakota
MP&M Only
Entire State
Ohio
MP&M Only
Entire State
Oklahoma
MP&M Only
Entire State
Oregon
MP&M Only
Entire State
Pennsylvania
MP&M Only
Entire State
Rhode Island
MP&M Only
Entire State
South Carolina
MP&M Only
Entire State
South Dakota
MP&M Only
Entire State
Tennessee
MP&M Only
Entire State
Texas
MP&M Only
Entire State
Utah
MP&M Only
Entire State
Vermont
MP&M Only
Entire State
Virginia
MP&M Only
Entire State
Washington
MP&M Only
Entire State
I % Native I
! % ! American, ! % Asian !
1 African- j Eskimo, or; or Pacific: Median
Counties i % White i American i Aleut i Islander i Income
26! 76.77%! 21.67%! 0.32%! 0.95%! $29:802
100! 75.60%! 21.96%! 1.25%! 0.76%! $26:647
l! 97.34%! 0.09%! 2.15%! 0.40%! $24:248
53! 94.71%! 0.55%! 3.96%! 0.50%! $23:213
43! 85.69%! 12.60%l 0.20%! 0.92%! $29:485
89! 87.81%! 10.62%! 0.21%! 0.82%! $28:706
5l 82.64%! 8.39%! 7.14%! 1.05%! $26:325
77! 82.26%! 7.38%! 8.03%! 1.04%! $23:577
9l 92.01%! 2.15%! 1.13%! 3.02%! $29:022
36! 92.80%! 1.60%! 1.46%! 2.38%! $27:250
39! 86.76%! 10.72%! 0.13%! 1.29%! $30:240
68! 88.57%! 9.15%! 0.13%! 1.14%! $29:069
4! 90.97%! 4.13%! 0.35%! 1.82%! $31,791
5l 91.59%! 3.79%! 0.43%! 1.76%! $32:181
15! 74.91%! 24.24%! 0.20%! 0.50%! $26:692
46! 69.05%! 29.83%! 0.26%! 0.61%! $26:256
2! 91.36%! 1.19%! 5.72%! 1.15%! $24:539
66! 91.55%! 0.45%! 7.24%! 0.48%! $22:503
21! 75.45%! 23.31%! 0.25%! 0.80%! $25:904
95! 83.01%! 15.93%! 0.26%! 0.63%! $24:807
18! 71.56%! 13.80%! 0.39%! 2.55%! $29:534
254! 75.28%! 11. 88%! 0.41%! 1.85%! $27:016
4! 93.12%! 0.85%! 0.87%! 2.42%! $30:281
29! 93.88%! 0.64%! 1.41%! 1.92%! $29:470
1! 98.69%! 0.40%! 0.30%! 0.59%! $28:485
14! 98.55%! 0.39%! 0.39%! 0.54%! $29:792
29! 75.03%! 20.17%! 0.30%! 3.49%! $38:074
135! 77.47%! 18.80%! 0.26%! 2.57%! $33:328
7! 88.93%! 3.29%! 1.34%! 5.58%! $34:174
40! 88.64%! 3.03%! 1.71%! 4.34%! $31,183
% Below
Poverty
Level
10.66%
12.97%
12.24%
14.38%
12.15%
12.54%
13.75%
16.71%
11.47%
12.42%
11.05%
11.13%
9.95%
9.61%
14.01%
15.37%
13.96%
15.86%
15.86%
15.70%
16.93%
18.10%
9.79%
11.36%
11.30%
9.86%
9.05%
10.25%
8.79%
10.92%
% Un-
employed
4.09%
4.79%
5.72%
5.30%
6.40%
6.60%
5.87%
6.87%
5.62%
6.20%
5.91%
5.97%
6.77%
6.64%
5.36%
5.58%
5.17%
4.16%
6.28%
6.41%
7.02%
7.11%
4.98%
5.32%
7.53%
5.85%
4.26%
4.48%
4.83%
5.72%
o/
/o
Children
23.62%
24.27%
27.18%
27.50%
25.67%
25.85%
26.19%
26.60%
25.10%
25.49%
23.40%
23.54%
22.48%
22.52%
25.91%
26.44%
27.67%
28.58%
24.75%
24.93%
28.23%
28.47%
34.92%
36.45%
25.06%
25.51%
24.64%
24.31%
24.87%
25.86%
77-7
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MP&M EEBA Part III: Benefits
Chapter 17: Environmental Justice & Protection of Children
Table 17.3: County Level Comparison of Demographic Data: Counties with Sample MP&M Facilities
Versus Entire State
State
West Virginia
MP&M Only
Entire State
Wisconsin
MP&M Only
Entire State
Counties
2
55
24
73
% White
98.57%
96.24%
89.07%
92.28%
I % Native I
% ! American, ! % Asian !
African- j Eskimo, orj or Pacific: Median
American i Aleut i Islander i Income
1.10%; o.io%! 0.21%; $20:6i3
3.09%! 0.17%! 0.42%! $20:795
8.00%! 0.59%! 1.16%! $30:056
4.99%! 0.81%l 1.08%l $29.442
% Below
Poverty
Level
19.06%
19.66%
11.10%
10.70%
% Un-
employed
9.12%
9.58%
5.25%
5.20%
%
Children
25.48%
24.77%
26.02%
26.39%
Note: Alaska, Hawaii, Nevada, and Wyoming are not represented because no MP&M facilities from these states were surveyed.
Source: U.S. EPA analysis of1990 Census of Population Data.
This comparison indicates that African-American
households are expected to receive a relatively larger share
of the benefits from the MP&M rule. The higher
representation of these households among the benefiting
population is to some extent likely to be explained by their
relatively higher concentration in urban areas, where most
MP&M facilities are situated and their effluents released.
17.2 PROTECTION OF CHILDREN FROM
ENVIRONMENTAL HEALTH AND SAFETY
RISKS
Lead is harmful to all exposed individuals, and its effects on
children are of particular concern. Lead exposure is more
likely to cause neurobehavioral deficits in children because
their rapid rate of development makes them more susceptible
to adverse effects. EPA expects that the proposed regulation
will benefit children in many ways, including:
> Reducing health risk from exposure to MP&M
pollutants from consumption of contaminated fish
tissue and drinking water, and
* Improving recreational opportunities for children
and their families.
In Chapter 14, EPA measured one category of benefits
specific to children: avoided health damages to pre-school-
age children from reduced exposure to lead. The analysis
considered several measures of children's health benefits
associated with lead exposure for children up to age six.
Avoided neurological and cognitive damages included:
> Lower overall IQ levels,
* Increased incidence of low IQ scores (<70), and
> Increased incidence of blood-lead levels above 20
ug/dL.
The Agency also assessed changes in incidence of neonatal
mortality from reduced lead exposure.
EPA expects the proposed rule to yield $14.4 million
(1999$) in annual benefits to children from reduced
neurological and cognitive damages and reduced incidence
of neonatal mortality.
EPA also examined whether lead discharges from MP&M
facilities are likely to have a disproportionate impact on
children in subsistence anglers' families. Table 17.4
compares risk levels and benefits to children from
subsistence fishing families and recreational fishing
families. Children from subsistence fishing families have a
much greater risk of adverse health effects from exposure to
lead due to consumption of a high proportion offish from
local waters.
EPA's analysis shows that the lead reductions under the
proposed MP&M rule are particularly beneficial for children
from subsistence fishing families. The average estimated
risk reduction per child for each of the four estimated lead-
related health effects was much larger for children in
subsistence fishing families than for those from recreational
fishing families. This finding is also supported by the
monetary estimates of benefits per child in each population
category.
-------
MP&M EEBA Part III: Benefits
Chapter 17: Environmental Justice & Protection of Children
EPA estimated that the monetary value of benefits per child
from a subsistence fishing family is $764, as compared to
$74 per child from recreational fishing families. These
benefits comprise a larger portion of subsistence fishing
families' income compared to the benefits received by a
recreational fishing family, because subsistence fishing
families generally have lower household income.
EPA estimated that the monetary value of benefits from
reduced cognitive damages to children in subsistence
household is about 2.9 percent of their current household
income, while benefits to recreational fishing families is 0.2
percent of their household income. This analysis uses
average household income in low income/minority families
and average household income of all households in the
United States (1990 Census data).
Table 17.4 summarizes estimated changes in health risk and
the monetary value of benefits to children from recreational
and subsistence fishing families.
Table 17.4: Estimated Benefits to Pre-School Children from Reduced Exposure to Lead
Benefit
Category
Neonatal
Mortality
Avoided
IQ Loss (Points)
Occurrence of
IQ<70
Occurrence of
PbB > 20 |ig/dL
Total
Population
Category
Recreation
Subsistence
Recreation
Subsistence
Recreation
Subsistence
Recreation
Subsistence
Recreation
Subsistence
All Children
Number of
Exposed Children
131,511
6,576
13^087
Reduction in the
Number of Adverse
Health Effect Cases
0.92
0.69
390.43
98.65
1.39
0.35
0.03
0.06
Estimated Monetary Value of Avoided
Health Damages to Children (1999$)
Total ! Per Child!
$5,336,000 1 $47
$4,002,000 1 $609
$3,934,410! $30
$994,104! $151
$101,3111 $1
$25,079 1 $4
$686 ; negligible
$60 1 negligible
$9,372,407 1 $74
$5,021,243 1 $764
$H39^650i $104
Source: U.S. EPA analysis
17-9
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MP&M EEBA Part III: Benefits Chapter 17: Environmental Justice & Protection of Children
GLOSSARY
hazard ratio: a ratio of the estimated ingestion rate of a expected to ingest MP&M pollutants at rates sufficient to
pollutant to the reference dose (RfD) value for the pollutant. pose a significant risk of systemic health effects.
The RfD is an estimate of the maximum daily ingestion rate
in mg/kg per day that is likely to be without an appreciable MP&M reach: a reach to which an MP&M facility
risk of deleterious effects during a lifetime. A hazard ratio discharges.
greater than one indicates that individuals would be
17-10
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MP&M EEBA Part III: Benefits Chapter 17: Environmental Justice & Protection of Children
REFERENCE
1990 Census data: http://www.census.gov/
17-11
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MP&M EEBA, Part IV: Comparison of Costs and Benefits
Chapter 18: MP&M Benefit / Cost Comparison
Chapter 18: MP&M Benefit /
Cost Comparison
INTRODUCTION
The preceding Chapters 12 through 16 provided quantitative
and qualitative assessments of the expected benefits to
society from reduced MP&M effluent discharges under the
proposed regulation. Chapter 11 assessed the regulation's
expected social costs. This chapter sums the estimated
values for the benefit categories that EPA was able to
monetize, and compares the aggregate benefits estimate with
the estimate of social costs.
18.1 SOCIAL COSTS
As discussed in Chapter 11, EPA estimated three categories
of social cost for the proposed regulation:
> the cost of society's economic resources used to
comply with the proposed regulation,
> the cost to governments of administering the
proposed regulation, and
> the social costs of unemployment resulting from the
regulation.
Summing these social cost accounts results in total social
costs ranging from $2,034 to $2,113 million annually
(1999$). The midpoint estimate of social costs for the
proposed option equals $2,073 million (1999$).
The social cost estimates do not explicitly estimate losses in
consumers' and producers' surpluses resulting from the
changed quantity of goods and services sold in affected
product markets. Instead, EPA developed an upper-bound
estimate of social costs by including compliance costs for
facilities predicted to close due to the rule. This approach
results in an upper-bound estimate of the social costs of
compliance, since the lost value incurred by closing facilities
is presumably less than the estimated cost of compliance .'
CHAPTER CONTENTS:
18.1 Social Costs 18-1
18.2 Benefits 18-1
18.3 Comparing Monetized Benefits and Costs .... 18-2
18.4 Comparing Monetized Benefits and Costs at the
Sample Facility Level 18-2
18.2 BENEFITS
EPA was able to develop a partial monetary estimate of
expected benefits for the proposed regulation in three
categories: human health, water-based recreation (including
nonuse value), and economic productivity benefits.
Summing the monetary values reported in the preceding
chapters across these categories results in total monetized
benefits of $1,284 to $3,833 million (1999$) annually for the
proposed rule (see Table 18.1). The midpoint estimate of
monetized benefits for the proposed rule equals $2,396
million (1999$). As noted in Chapter 12, this benefit
estimate is necessarily incomplete because it omits numerous
mechanisms by which society is likely to benefit from
reduced effluent discharges from the MP&M industry.
Examples of benefit categories not reflected in this
monetized estimate include:
* non-lead and non-cancer related health benefits,
* improved aesthetic quality of waters near discharge
outfalls,
* benefits to wildlife and to threatened or endangered
species,
> tourism benefits, and
* reduced costs of drinking water treatment.
1 Including costs for regulatory closures in effect calculates
the social costs of compliance incurred if every facility continued
to operate post-regulation. Calculating costs as if all facilities
continue operating will overstate social costs because some
facilities find it more economic to close.
18-1
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MP&M EEBA, Part IV: Comparison of Costs and Benefits
Chapter 18: MP&M Benefit / Cost Comparison
18.3 COMPARINS MONETIZED BENEFITS
AND COSTS
EPA cannot perform a complete cost-benefit comparison
because not all of the benefits resulting from the proposed
regulatory alternative can be valued in dollar terms.
Table 18.1 shows that combining the estimates of social
benefits and social costs yields an estimate of net
monetizable benefits ranging from negative $809 million to
positive $1,752 million annually (1999$) at the national
level. Comparing the midpoint estimate of social costs with
the midpoint estimate of monetized benefits results in a net
benefit of $311 million (1999$). The lack of a
comprehensive benefits valuation limits this assessment of
the relationship between costs and benefits of the proposed
rule. EPA believes that the benefits of regulation, even in
the low-estimate case, would likely exceed the social costs if
all of the benefits of regulation could be quantified and
monetized.
Table 18.1: Comparison of National Annual Monetizable Benefits to Social Costs: Proposed Rule
(millions of 1999$)
Benefit and Cost Categories
Benefit Categories
Reduced Cancer Risk from Fish Consumption
Reduced Cancer Risk from Water Consumption
Reduced Risk from Exposure to Lead
Enhanced Water-Based Recreation3
Nonuse Benefits
Avoided Sewage Sludge Disposal Costs
Total Monetized Benefits
Cost Categories
Resource Costs of Compliance
Costs of Administering the Proposed Regulation
Social Costs of Unemployment
Total Monetized Costs
Net Monetized Benefits (Benefits Minus Costs)b
Low
$0.3
$13.0
$28.0
$960.6
$240.2
$61.1
$1,303.2
$2,033.7
$0.1
$0
$2,033.9
($809.4)
Mid
$0.3
$13.0
$28.0
$1,520.7
$760.3
$61.3
$2,383.6
$2,033.7
$0.3
$39.0
$2,073.0
$310.6
High
$0.3
$13.0
$28.0
$2,218.7
$1,464.3
$61.5
$3J85.8
$2,033.7
$0.9
$78.0
$2,112.6
$1,751.9
a. EPA adjusted the value of recreational fishing benefits to avoid double counting the benefits from cancer case reductions resulting from avoided
consumption of contaminated fish tissue. The adjusted value is simply the difference between the estimated value of recreational fishing benefits and the
value of benefits from reducing the cancer risk caused by fish consumption.
b. EPA calculated the low net benefit value by subtracting the high value of costs from the low value of benefits, and calculated the high net benefit value
by subtracting the low value of costs from the high value of benefits. The mid value of net benefits is the mean value of benefits less the median value of
costs.
Source: U.S. EPA analysis.
18.4 COMPARINS MONETIZED BENEFITS
AND COSTS AT THE SAMPLE FACILITY
LEVEL
Extrapolating from sample facility results to national results
can introduce uncertainty into the analysis for both the cost
and the benefits estimates. EPA therefore compared costs
and benefits for the sample facilities alone, basing the
sample results on known facility and benefit pathway
characteristics. Table 18.2 presents the results of this
analysis. EPA found that the relationship between benefits
and costs for sample facilities alone are similar to that found
in the national analysis. Specifically, in both analyses the
low estimate for net benefits is negative while the midpoint
and high estimates for net benefits are positive. This
similarity in the relationship between benefits and costs in
the two analyses, which is also matched by results from the
Ohio case study (Chapter 22), increases EPA's confidence
in its extrapolation of results to the national level.
18-2
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MP&M EEBA, Part IV: Comparison of Costs and Benefits
Chapter 18: MP&M Benefit / Cost Comparison
Table 18.2: Comparison of Annual Monetizable Benefits to Social Costs for Sample Facilities: Proposed Rule
(thousands of 1999$)
Benefit and Cost Categories
Reduced Cancer Risk from Fish Consumption
Reduced Cancer Risk from Water Consumption
Reduced Risk from Exposure to Lead
Enhanced Water-Based Recreation
Nonuse Benefits
Avoided Sewage Sludge Disposal Costs
Total Monetized Benefits
Total Monetized Costs3
Net Monetized Benefits (Benefits Minus Costs)b
Low
$17.4
$1,057.1 j
$2,585.0 j
$68,990.4 j
$17,247.6 j
$7,532.1 j
$97,429.6
$121,392.9
($23.963.3^
Mid
$17.4
$1,057.1 j
$2,585.0 j
$108,803.9 j
$54,402.0 j
$7,532.4 j
$174,397.8 j
$121,392.9
$53JMV4ซ^
High
$17.4
$1,057.1
$2,585.0
$158,121.1
$104,359.9
$7,532.7
$273,673.2
$121,392.9
$152^80
a. Total monetized costs represent the resource cost of compliance only. This analysis does not include the cost of administering the proposed regulation
and the social cost of unemployment. Their relatively small size makes their exclusion unlikely to affect the conclusions that can be drawn from this analysis.
b. EPA calculated the low net benefit value by subtracting costs from the low value of benefits, and calculated the high net benefit value by subtracting costs
from the high value of benefits.
Source: U.S. EPA analysis.
18-3
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MP&M EEBA Part IV: Comparison of Costs and Benefits
Chapter 19: Social Costs and Benefits of Regulatory Alternatives
Chapter 19: Social Costs and
Benefits of Regulatory Alternatives
INTRODUCTION
EPA considered two alternative regulatory options when
developing the proposed MP&M rule. These options
(Option 2/6/10 and Option 4/8) are described in Chapter 4.
EPA estimated the social costs and benefits of these two
options, using the same methods applied in the analyses of
the proposed rule. This chapter summarizes the results of
these benefit and cost analyses.
19.1 ESTIMATED SOCIAL COSTS
EPA estimated social costs for the alternative options based
on the methodologies discussed in Chapter 11 for the
proposed regulatory option.
19.1.1 Compliance Costs for MP&M
Facilities
Table 19.1 presents the estimated resource value of
compliance costs by discharge status and subcategory under
the proposed option and Options 2/6/10 and 4/8,
respectively. These compliance costs are not adjusted for
the effect of taxes, and therefore represent the social value
of resources used for compliance. EPA annualized
compliance costs using a seven percent discount rate over a
15-year analysis period.
EPA's estimates included compliance costs for facilities that
close due to the rule and costs for facilities that continue
operating subject to the proposed regulation. This approach
results in an upper-bound estimate of the social costs of
compliance, since the lost value incurred by closing facilities
is presumably less than the estimated cost of compliance.1
1 Including costs for regulatory closures in effect calculates
the social costs of compliance incurred if every facility continued
to operate post-regulation. Calculating costs as if all facilities
continue operating will overstate social costs because some
facilities find it more economical to close.
CHAPTER CONTENTS:
19.1 Estimated Social Costs 19-1
19.1.1 Compliance Costs for MP&M Facilities . 19-1
19.1.2 Government Administrative Costs 19-2
19.1.3 Cost of Unemployment 19-3
19.1.4 Total Social Costs 19-4
19.2 Estimated Benefits 19-5
19.2.1 Human Health Benefits 19-5
19.2.2 Recreational Benefits 19-5
19.2.3 Avoided Sewage Sludge Disposal or
Use Costs 19-6
19.2.4 Total Monetized Benefits 19-6
19.3 Comparison of Estimated Benefits and Costs . 19-6
Glossary 19-8
Acronym 19-9
Under Option 2/6/10, compliance costs for indirect
dischargers and direct dischargers equal $2,585 million and
$253 million, respectively (1999$). The total annualized
compliance costs are $2,838 million, representing a 40
percent increase over compliance costs under the proposed
rule. This cost increase results from the elimination of low
flow and subcategory exclusions under Option 2/6/10.
General Metals indirect dischargers account for
approximately 71 percent of the total compliance costs under
this option.
Under Option 4/8, compliance costs for indirect dischargers
and direct dischargers equal $4,141 million and $391
million, respectively (1999$). The total annualized
compliance costs are $4,532 million, representing a 123
percent increase over compliance costs under the proposed
rule. This significantly larger cost increase results from the
more stringent technology requirements for all
subcategories, as well as the elimination of the proposed low
flow and subcategory exclusions. General Metals indirect
dischargers account for approximately 65 percent of the total
compliance costs under this option.
19-1
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MP&M EEBA Part IV: Comparison of Costs and Benefits
Chapter 19: Social Costs and Benefits of Regulatory Alternatives
Table 19.1: Resource Value of Compliance Costs under Different Options
(million 1999$)
Subcategory
General Metals
MF Job Shop
Non Chromium Anodizing
Oily Wastes
Printed Wiring Boards
Railroad Line Maintenance
Shipbuilding Dry Docks
Steel Forming & Finishing
Total
General Metals
MF Job Shop
Non Chromium Anodizing
Oily Wastes
Printed Wiring Boards
Railroad Line Maintenance
Shipbuilding Dry Docks
Steel Forming & Finishing
Total
General Metals
Steel Forming & Finishing
MF Job Shop
Non Chromium Anodizing
Oily Wastes
Printed Wiring Boards
Railroad Line Maintenance
Shipbuilding Dry Docks
Steel Forming & Finishing
Total
Indirect
Proposed Optio
$1,454.4
$149.2
$0.0
$8.5
$145.5
$0.0
$0.0
$23.4
$1,781.0
Option 2/6/10
$2,035.0
$149.2
$36.0
$195.4
$145.5
$0.3
$0.2
$23.4
$2,585.0
Option 4/8
$2,950.1
$35.3
$269.9
$53.4
$611.9
$219.8
$0.5
$0.2
$35.3
$4,141.2
Direct
n
$203.3
$1.2
$11.0
$2.4
$1.1
$2.1
$31.5
$252.7
$203.3
$1.2
$11.0
$2.4
$1.1
$2.1
$31.5
$252.7
$294.8
$34.2
$2.1
$53.7
$4.4
$1.2
$0.6
$34.2
$391.0
Total
$1,657.7
$150.4
$0.0
$19.5
$148.0
$1.1
$2.1
$54.9
$2,033.7
$2,238.3
$150.4
$36.0
$206.4
$148.0
$1.4
$2.3
$54.9
$2,837.7
$3,244.9
$69.5
$272.0
$53.4
$665.7
$224.2
$1.7
$0.7
$69.5
$4,532.2
Source: U.S. EPA analysis.
19.1.2 Government Administrative Costs
Substantially more indirect dischargers require permitting
under the alternative options than under the proposed rule,
because the alternative options do not include the proposed
low flow and subcategory exclusions. Table 19.2 shows the
number of facilities requiring permitting of different types
under the proposed option and Options 2/6/10 and 4/8.
These options require permitting for 48,065 and 46,400
more facilities, respectively, than does the proposed rule.
Option 4/8 involves more regulatory closures and thus
requires permitting for fewer facilities than does Option
2/6/10.
19-2
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MP&M EEBA Part IV: Comparison of Costs and Benefits
Chapter 19: Social Costs and Benefits of Regulatory Alternatives
Table 19.2: Permitting Requirements for Regulatory Alternatives
(number of indirect discharging facilities)
Permitting required:
Convert from existing concentration-
based to mass-based3
New concentration-based permit3
New mass-based permit3
Repermit within 5 rather than 3 years
Regulatory closures (no longer
requiring permits)b
Total with permits
Proposed Option
223
432
216
4,073
143
4,944
Option 2/6/10
8,424
16,009
8,004
20,752
1,020
53,009
Option 4/8
8,422
15,119
7,559
20,244
1,348
51,344
a. EPA assumes, for costing purposes, that permitting authorities will choose to issue mass-based permits to one-third
of the facilities requiring new permits, and one-third of the facilities with existing concentration-based permits, except
for Steel Forming & Finishing facilities. EPA assumes that all Steel Forming & Finishing facilities will be issued mass-
based permits, including the 20 facilities that currently have a concentration-based permit.
b. Some facilities with existing permits will no longer require permitting due to regulatory closures.
Source: U.S. EPA analysis.
Table 19.3 presents the estimated permitting costs to
governments of administering the proposed rule and
alternative options. These costs include the labor and
material resources required to write permits under the
regulation and conduct compliance monitoring and
enforcement activities. Chapter 7 describes the
methodology used to estimate these administrative costs.
Estimated government administration costs for Option
2/6/10 range from $5.0 million to $9.3 million (1999$). The
median cost estimate, $11.8 million, exceeds the
corresponding cost estimate for the proposed rule by $11.5
million.
Government administration costs under Option 4/8 range
from $4.7 million to $36.5 million (1999$). The median
cost estimate, $10.9 million, exceeds the corresponding cost
estimate for the proposed rule by $10.7 million. Permitting
costs are lower under Option 4/8 than under Option 2/6/20
because there are more facilities that close under Option 4/8
that no longer require permitting.
Table 19.3: Government Administrative Costs for Alternative Options
(million 1999$)
Option
Proposed Option
Option 2/6/10
Option 4/8
Low
$0.1
$5.0
$4.7
Mid
$0.3
$11.8
$10.9
High
$0.9
$39.3
$36.5
Source: U.S. EPA analysis.
19.1.3 Cost of Unemployment
Table 19.4 presents the estimated social costs of
unemployment under the proposed option and Table 19.5
presents the same information for Options 2/6/10 and 4/8.
These estimates include the estimated willingness-to-pay to
avoid cases of involuntary unemployment, and the cost of
administering the unemployment compensation system for
unemployed workers. EPA annualized costs using a seven
percent discount rate over a 15-year analysis period:
The Agency based lower-bound estimates of the number of
net job losses expected from compliance. Unlike the
proposed rule, both alternative options involve net
employment losses because the increased employment due
to compliance expenditures do not outweigh the expected
job losses from regulatory closures. Net unemployment
19-3
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MP&M EEBA Part IV: Comparison of Costs and Benefits
Chapter 19: Social Costs and Benefits of Regulatory Alternatives
expected under Option 2/6/10 and Option 4/8 is 4,811 and
20,534 jobs, respectively. The upper-bound estimate for lost
employment, which does not consider increased employment
due to compliance expenditures, is 16,834 and 48,070 lost
jobs under Option 2/6/10 and Option 4/8, respectively.
Based on these estimates for lost employment, social costs
of unemployment under Option 2/6/10 range from $168
million to $222 million (1999$). The midpoint estimate,
$195 million, exceeds the corresponding cost estimate under
the proposed rule by $156 million. Social costs of
unemployment under Option 4/8 range from $480 million to
$633 million (1999$). The midpoint estimate, $557 million,
exceeds the corresponding estimate under the proposed rule
by $518 million.
Table 19.4: Social Costs of Unemployment for The Proposed Option
(million 1999$)
Unemployment/Cost Category
Net Unemployment (FTE-years)a
Gross Unemployment (FTE-years)a
Annualized Social Cost of
Unemployment
Annualized Administrative Cost
Total Social Cost of Unemployment
Proposed Option
Low i Mid i High
(2,575)
5,916
$59.0
$0.1
$59.1
$68.4
$0.1
$68.5
$77.9
$0.1
$78.0
Number of FTE positions multiplied by the duration of employment/unemployment. EPA
assumed that workers losing jobs due to regulatory closures would be unemployed for one year.
The timing and duration of employment gains due to compliance expenditures differs for
employment associated with manufacturing and installing equipment (in the first year) and
operating and maintaining equipment (all 15 years of the analysis period).
Source: U.S. EPA analysis.
Table 19.5: Social Costs of Unemployment for Alternative Options (1999$)
Unemployment/Cost Category
Net Unemployment (FTE-years)a
Gross Unemployment (FTE-years)a
Annualized Cost of Unemployment
Annualized Administrative Cost
Total Social Cost of Unemployment
Option 2/6/10
Low i Mid i High
4,811
16,834
$167,899,414! $194,755,187! $221,610,961
$221,796! $221,796! $221,796
$168,121,209! $194,976,983! $221,832,757
Option 4/8
Low i Mid i High
20,534
48,070
$479,433,297! $556,119,402! $632,805,508
$633,333! $633,333! $633,333
$480,066,630! $556,752,736! $633,438,841
a Number of FTE positions multiplied by the duration of employment/unemployment. EPA assumed that workers losing jobs due to regulatory closures
would be unemployed for one year. The timing and duration of employment gains due to compliance expenditures differs for employment associated
with manufacturing and installing equipment (in the first year) and operating and maintaining equipment (all 15 years of the analysis period).
Source: U.S. EPA analysis.
19.1.4 Total Social Costs
Based on the cost estimates presented above, EPA estimates
the social cost of regulation under Option 2/6/10 to lie in the
range of $3,011 million to $3,099 million (1999$) annually.
The midpoint estimate, $3,045 million, represents a 47
percent increase in the social cost of regulation over the
proposed rule. This increase results because the proposed
low flow and subcategory exclusions are eliminated under
Option 2/6/10.
EPA estimates the social costs of regulation under Option
4/8 to lie in the range of $5,017 million to $5,202 million
(1999$) annually. The midpoint estimate, $5,100 million,
represents a 146 percent increase in the social cost of
regulation over the proposed rule. This increase results from
the more stringent technology requirements for all
subcategories under Option 4/8 compared to those under the
proposed rule. In addition, this alternative option eliminates
low flow and subcategory exclusions.
19-4
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MP&M EEBA Part IV: Comparison of Costs and Benefits
Chapter 19: Social Costs and Benefits of Regulatory Alternatives
19.2 ESTIMATED BENEFITS
EPA estimated the benefits for the alternative options based
on the methodologies described in Chapters 12 through 16.
19.2.1 Human Health Benefits
EPA used the methodology described in Chapter 13 to
assess human health benefits from reduced incidence of
cancer from consumption of contaminated fish tissue and
drinking water under the two alternative options.
EPA estimates that Option 2/6/10 would reduce incidence of
cancer from consumption of contaminated fish by 0.045
cases per year, representing a reduction of approximately 36
percent from the baseline level of 0.126. Option 4/8 would
eliminate approximately 0.062 cancer cases per year
representing a reduction of about 49 percent. The estimated
monetary value of reduced incidence of cancer from
consumption of contaminated fish is $0.3 million (1999$)
under Option 2/6/10 and $0.4 million (1999$) under Option
4/8. Option 4/8 has the largest benefits from reduced
incidence of cancer from contaminated fish consumption.
The proposed option and Option 2/6/10 result in the same
level of benefits and are both inferior to Option 4/8.
Under Option 2/6/10, 2.36 fewer cancer cases are expected
annually, a decline of 46 percent from the baseline level.
Similarly, under Option 4/8, 2.37 fewer cancer cases are
expected annually, a decline of 47 percent from the baseline
level. EPA estimates that the proposed option will reduce
the incidence of cancer from consumption of contaminated
drinking water by 2.24 cases per year. This figure is 0.12 or
013 cases fewer than Option 2/610 or Option 4/8,
respectively. Estimated annual monetary benefits under
Option 2/6/10 and Option 4/8 equal $13.7 and $13.8 million
(1999$), respectively.
EPA used the methodology described in Chapter 14 to
assess benefits to children and adults from reduced exposure
to lead under Option 2/6/10 and Option 4/8. EPA estimates
that reduced consumption of contaminated fish will result in
annual lead-related benefits for children equaling $14.8
million (1999$) for both Option 2/6/10 and Option 4/8.
EPA estimates neonatal mortality to decrease by 1.7 cases,
and estimates an avoided loss of 504 IQ points under both
options. Lead-related benefits for adults under both options
equal $14.1 million. Lead-related benefits for children and
adults combined equal $28.9 million, an increase of $0.9
million over the proposed option. Table 19.6 provides a
summary of all health-related benefits.
Table 19.6: Annual Human Health Benefits for the Alternative Options (1999$)
Benefit Category
Reduced Cancer Risk from Fish Consumpl
Number of Cancer Cases
Monetary Value (millions $)
Reduced Cancer Risk from Water Consum
Number of Cancer Cases
Monetary Value (millions $)
Lead Related Benefits
Children
Adult
Baseline
ion
0.126
ption
5.10
Proposed Option
0.081
$0.3
2.86
$13.0
$14.4
$13.6
Option 2/6/10
0.081
$0.3
2.74
$13.7
$14.8
$14.1
Option 4/8
0.064
$0.4
2.73
$13.8
$14.8
$14.1
Source: U.S. EPA analysis.
19.2.2 Recreational Benefits
EPA used the methodology described in Chapter 15 to
assess improvements in recreational benefits under the
alternative options. The Agency found that Option 2/6/10
eliminated the occurrence of pollutant concentrations in
excess of ambient water quality criteria (AWQC)
limits in 6,226 of the 10,443 baseline occurrences (see Table
19.7). Similarly, EPA found that Option 4/8 eliminated the
occurrence of pollutant concentrations in excess of AWQC
limits in 6,217 of the baseline occurrences. EPA estimated
that these habitat improvements would increase the
recreational value, including both use and nonuse value, of
improved reaches by $3,014.3 million to $9,261.9 million
annually under Option 2/6/10 and by $2,923.7 million to
$9,044.5 million annually under Option 4/8 (1999$). The
midpoint estimates for annual recreational benefits under
19-5
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MP&M EEBA Part IV: Comparison of Costs and Benefits
Chapter 19: Social Costs and Benefits of Regulatory Alternatives
Option 2/6/10 and Option 4/8 are $5,728.9 million and
$5,575.7 million (1999$), respectively. The midpoint
estimates of recreational and nonuse benefits are
approximately 2.5 times greater under Option 2/6/10 and
Option 4/8 than under the proposed option.
Table 19.7: Number of MP&M Discharge Reaches with MP&M Pollutant Concentrations Exceeding AWQC Limits
Regulatory Option
Baseline
Proposed Option
Option 2/6/10
Option 4/8
Number of Reaches with Concentrations Exceeding
AWQC Acute
Exposure Limits for
Aquatic Species
878
103
61
52
AWQC Chronic
Exposure Limits for
Aquatic Species
2,466
1,437
1,394
1,310
AWQC Limits for
Human Health
10,310
9,205
4,159
4,168
Number of Reaches
with Concentrations
Exceeding AWQC
Limits
10,443
9,258
4,217
4,226
Note: All reaches exceeding aquatic acute exposure limits also exceed chronic exposure limits. In order not to double count the number of reaches
expected to benefit from the regulation, the total number of reaches exceeding AWQC limits is the sum of the number of reaches that exceed human
health criteria and the number exceeding aquatic chronic criteria.
Source: U.S. EPA analysis.
19.2.3 Avoided Sewage Sludge Disposal
or Use Costs
Reduced metals discharges to POTWs resulting from
Option 2/6/10 and Option 4/8 would enable 1,408 and 1,450
POTWs, respectively, to dispose of sewage sludge by land
application. The regulations would decrease the cost to
POTWs for disposal or use of sewage sludge by an
estimated $69.6 million and $127.4 million annually (1999$)
under Option 2/6/10 and Option 4/8, respectively.
Compared to the proposed option, Option 6/2/10 and Option
4/8 offer an additional $8.3 million (1999$) and $66.1
million (1999$) in cost savings from reduced contamination
of sewage.
Table 19.8: <
Option
Baseline
Proposed Option
Option 2/6/10
Option 4/8
"ost Savings from L
# of POTWs
Land Applying
6,953
6,889
5,574
5,574
and Application
Cost Savings from
Upgrading
Sewage Sludge
Disposal Methods
61.3
68.5
127.4
19.2.4 Total Monetized Benefits
EPA estimates that total monetized benefits under Option
2/6/10 range from $3,125 million to $9,376 million (1999$)
annually, with a midpoint estimate of $5,841 million. Total
monetized benefits under Option 4/8 range from $3,092
million to $9,217 million (1999$) annually, with a midpoint
estimate of $5,746 million. The midpoint estimate of
Monetized Option 2/6/10 benefits are 145 percent higher
than the midpoint estimate of benefits for the proposed rule,
and Option 4/8 benefits are 141 percent higher than under
the proposed rule.
19.3 COMPARISON OF ESTIMATED
BENEFITS AND COSTS
Combining the estimates of social benefits and social costs
under Option 2/6/10 yields net monetized benefits ranging
from $26 million to $6,366 million annually (1999$), with a
midpoint estimate of $2,797 million (see Table 19.9). Net
monetized benefits under Option 4/8 range from a net cost
of$2,l 10 million to a net benefits of $4,200 million annually
(1999$), with a midpoint net benefit of $646 million (see
Table 19.9). As discussed in Chapter 12, the assessment of
benefits is necessarily incomplete due to the omission of
numerous mechanisms by which society is likely to benefit
from reduced effluent discharges.
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MP&M EEBA Part IV: Comparison of Costs and Benefits
Chapter 19: Social Costs and Benefits of Regulatory Alternatives
Table 19.9: Comparison of Social Benefits and Costs for Option 2/6/10 (millions of 1999$)
Benefit and Cost Categories
Low j
Mid i
High
Proposed Option
Benefit Categories
Reduced Cancer Risk from Fish Consumption
$0.3
13
$0.3
Reduced Cancer Risk from Water Consumption
$13.0
$13.0
$13.0
Reduced Risk from Lead Exposure
$28.0
Enhanced Water-Based Recreation
$960.6
$1,520.7
$2,218.7
Nonuse Benefits
$240.2
$760.3
$1,464.3
Avoided Sewage Sludge Disposal Costs
$61.1
$61.3
$61.5
Total Monetized Benefits
$1,303.2
$2,383.6
$3,785.8
Cost Categories
Resource Costs of Compliance
$2,033.7
Costs of Administering the Proposed Regulation
$0.1
_$2,033.7
$0.3
$2,033.7
$0.9
Social Costs of Unemployment
$0
$39.0
Total Monetized Costs
$2,033.9
$2,073.0
$2,112.6
Net Monetized Benefits (Benefits Minus Costs)3
($809.4)
$310.6
$1,751.9
Option 2/6/10
Benefit Categories
Reduced Cancer Risk from Fish Consumption
$0.3
13
$0.3
Reduced Cancer Risk from Water Consumption
$13.7
$13.7
$13.7
Reduced Risk from Lead Exposure
Enhanced Water-Based Recreation
$28.9
$22,411.5
$28._9
$3,819.3
$28.9
$5,579.5
Nonuse Benefits
$602.9
$1,909.6
$3,682.4
Avoided Sewage Sludge Disposal Costs
$67.8
$69.6
$71.3
Total Monetized Benefits
$3,125.1
$5,841.4
9,376.1
Cost Categories
Resource Costs of Compliance
$2,837.7
$2,837.7
$2,837.7
Costs of Administering the Proposed Regulation
$5.0
$11.8
$39.3
Social Costs of Unemployment
$168.1
$195.0
$221.8
Total Monetized Costs
$3,010
$3,044.5
$3,098.8
Net Monetized Benefits (Benefits Minus Costs)"
$26.3
$2,796.9
$6,366.1
Option 4/8
Benefit Categories
Reduced Cancer Risk from Fish Consumption
$0.4
14
$0.4
Reduced Cancer Risk from Water Consumption
$13.8
$13.5
$13.8
Reduced Risk from Lead Exposure
$28.9
Enhanced Water-Based Recreation
$2,338.9
$3,717.2
$5,448,5
Nonuse Benefits
$584.7
$125.6
$3,092.3
$1,858.6
$3,596.0
$129.2
$9,216.8
Avoided Sewage Sludge Disposal Costs
Total Monetized Benefits
$127.4
$5,746.3
Cost Categories
Resource Costs of Compliance
Costs of Administering the Proposed Regulation
4,532.2
$4.7
$4,532.2
4,532.2
$36.5
$10.9
Social Costs of Unemployment
Total Monetized Costs
Net Monetized Benefits (Benefits Minus Costs)a
$480.1
$5,017.0
($2,109.8)
$556.5
$633.4
$5,202.1
$4,199.8
$5,099.9
$646.4
a. EPA calculated the low net benefit value by subtracting the high value of costs from the low value of benefits, and calculated the high net benefit value
by subtracting the low value of costs from the high value of benefits. The mid net benefit value is the mean value of benefits less the midpoint of costs.
Note: Categories may not sum to totals due to rounding of individual estimates for presentation purposes.
Source: U.S. EPA analysis.
19-7
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MP&M EEBA Part IV: Comparison of Costs and Benefits Chapter 19: Social Costs and Benefits of Regulatory Alternatives
GLOSSARY
ambient water quality criteria (AWQC): AWQC regulatory impact (U.S. EPA. 1986. Quality Criteria for
present scientific data and guidance of the environmental Water 1986. U.S. Environmental Protection Agency, Office
effects of pollutants which can be useful to derive regulatory of Water Regulations and Standards, Washington, DC. EPA
requirements based on considerations of water quality 440/5-86-001).
impacts; these criteria are not rules and do not have
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MP&M EEBA Part IV: Comparison of Costs and Benefits Chapter 19: Social Costs and Benefits of Regulatory Alternatives
ACRONYM
AWQC: ambient water quality criteria
19-9
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MP&M EEBA Part V: Ohio Case Study
Chapter 20: Baseline Conditions in Ohio
Chapter 20: Baseline Conditions in
Oh
10
INTRODUCTION
Section IV of this EEBA focuses on the State of Ohio as a
case study of the MP&M regulation's expected benefits and
costs. Ohio has a diverse water resource base, a relatively
large number of MP&M industry facilities, and a more
extensive water quality ecological database than many other
states. EPA gathered extensive data on MP&M facilities
and on Ohio's baseline water quality conditions and water-
based recreation activities, to support the case study
analysis. These data characterize current water quality
conditions, water quality changes expected from the
regulation, and the expected welfare changes from water
quality improvements at waterbodies affected by MP&M
discharges.
The case study analysis supplements the national level
analysis performed for the MP&M regulation in two
important ways. First, the case study used improved data
and methods to determine MP&M pollutant discharges from
both MP&M facilities and other sources. In particular, EPA
oversampled the State of Ohio with 1,600 screener
questionnaires to augment information on Ohio MP&M
facilities. The Agency also used information from the
sampled MP&M facilities to assign discharge characteristics
to non-sampled MP&M facilities1. Second, the analysis
used an original travel cost study to value four recreational
uses of water resources affected by the regulation:
swimming, fishing, boating, and near-water activities. The
added detail provides a more complete and reliable analysis
of water quality changes from reduced MP&M discharges.
The case study analysis therefore provides more complete
estimates of changes in human welfare resulting from
reduced health risk, enhanced recreational opportunities, and
improved economic productivity.
The statewide case study of recreational benefits from the
MP&M regulation combines water quality modeling with a
random utility model (RUM) to assess how changes in
water quality from the regulation will affect consumer
valuation of water resources. The study addresses a wide
CHAPTER CONTENTS:
20.1 Overview of Ohio' s Geography, Population,
and Economy
20.2 Profile of MP&M Facilities in Ohio
20.3 Ohio's Water Resources
20.3.1 Aquatic Life Use
20.3.2 Water Recreation In Ohio
20.3.3 Commercial Fishing in Ohio
20.3.4 Surface Water Withdrawals
20.4 Surface Water Quality in Ohio
20.4.1 Use Attainment in Streams and Rivers
in Ohio
20.4.2 Lake Erie and Other Lakes Use
Attainment
20.4.3 Causes and Sources of Use
Non-Attainment in Ohio
20.5 Effects of Water Quality Impairments on
Water Resource Services
20.5.1 Effect of Water Quality Impairment on
Life Support for Animals and Plants . .
20.5.2 Effect of Water Quality Impairment on
Recreational Services
20.6 Presence and Distribution of Endangered and
Threatened Species in Ohio
20.6.1 E&TFish
20.6.2 E&T Mollusks
20.6.3 Other Aquatic E&T Species
Glossary
Acronyms
References
20-2
20-3
20-4
20-6
20-8
20-9
20-9
20-10
20-10
20-10
20-11
20-12
20-12
20-13
20-15
20-15
20-15
20-16
20-19
20-22
20-23
range of pollutant types and effects, including water quality
measures not often addressed in past recreational benefits
studies. The estimated model supports a more complete
analysis of recreational benefits from reductions in
nutrients and "toxic" pollutants.2
This and the next two chapters present the Ohio case study.
This chapter provides background information on the state
of Ohio, the following chapter presents the results from the
1 Appendix G provides a detailed discussion on the approach
used to estimate discharge characteristics for non-sampled MP&M
facilities.
2 The term "toxic" used here refers to the 126 priority or
toxic pollutants specifically defined as such by EPA, as well as
nonconventional pollutants that have a toxic effect on human
health or aquatic organisms.
20-1
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MP&M EEBA Part V: Ohio Case Study
Chapter 20: Baseline Conditions in Ohio
recreational benefits analysis, and the last chapter
summarizes social costs and benefits of the proposed
regulation for the state of Ohio.
20.1 OVERVIEW OF OHIO s SEOSRAPHY,
POPULATION, AND ECONOMY
Table 20.1 summarizes general information on Ohio. Ohio
is large, heavily-industrialized, and densely-populated. The
state covers a total surface area of 44,828 sq. mi. (106,607
sq. km.), of which water represents 3,875 sq. mi. (10,036 sq.
km.). About 90 percent of the water surface area consists of
Lake Erie; the remainder includes inland waters, such as
lakes, reservoirs, and rivers (including the Ohio River). The
state housed 11,173,000 people in 1996. The three largest
metropolitan areas are located on Lake Erie (Toledo and
Cleveland) and the Ohio River (Cincinnati).
Table 20.1: Facts about the State of Ohio
Geography
Location Midwest United States, northeast part:
south of Lake Erie
east of Indiana
north of the Ohio River
Total land area 40,953 sq. mi. (106,607 sq. km.)
Of the 26,451,000 acres of terrestrial surface area in Ohio:
97 percent is non-federal land (National Resources Inventory (NRI))
3,558,000 acres, representing 13.5 percent of the total area of Ohio, are developed
Lhe remaining non-federal lands are rural land, classified mostly as crop land, forest, and pasture
lands. (USDA, 1992)
Lotal water surface area 3,875 sq. mi. (10,036 sq. km.)
Approx. 90 percent is represented by Lake Erie, and 10 percent are inland waters including rivers,
lakes, and reservoirs.3
Total area II'.??:.8. sq. mi- H 1^104 sq. km.)
Demographics
Population 11,173,000 in 1996, approximately 4.2 percent of total U.S. population (U.S. Census Bureau)
Population increase: three percent from 1990 to 1996, compared to a six percent increase in the U.S.
population overall.
Most densely populated part of the state: northeastern Ohio, both urban and rural areas.
Largest cities: Cleveland, Cincinnati, and Loledo.
Economics
Ohio Midwest U.S.
Per Capita Income (1996$) $23,537 $24,166 $24,231
Rank in per capital income in
the U.S.: 21
Percent of population below 11.5% 13.8%
the poverty level (1995
Current Population Survey
data, DOC 1996)
Ohio per capita income increased by 16 percent from 1986 to 1996.
Income growth is consistent with other Midwestern states and is two percent greater than overall U.S.
per capita income growth.
G_ross State _Product (GSP) $.30_3,_5_6_9,000 (1996$), representing 4_ percent of G_ross Domestic Product (_GDP) for the U.S. in 1_9_9_6.
Percent increase in GSP/GDP Ohio GSP U.S. GDP
from 1986 to 1996 (in
adjusted 1996$) 25% 29%
a. Total water surface uses are estimated by the USDA's National Resources Inventory (NRI). See "http://www.ftw.nrcs.usda.gov/nri_data.html"
Source: U.S. EPA analysis.
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MP&M EEBA Part V: Ohio Case Study
Chapter 20: Baseline Conditions in Ohio
20.2 PROFILE OF MP&M FACILITIES IN
OHIO
EPA selected Ohio as the case study state because MP&M
industries account for a large share of the state's economy
(see Table 20.2). Data from the 1992 Economic Censuses
show that industries containing MP&M facilities employ
16.5 percent of Ohio's total industrial workers and produce
20.4 percent of industrial worker output by value. MP&M
industries also account for 21.9 percent of payroll payments,
indicating that jobs in MP&M industries are more highly
paid than industrial jobs on average in Ohio. The discussion
below explains the sources and methodology EPA used, and
then presents detailed results and caveats.
Table 20.2: MP&M Share of Industrial Output and Employment in Ohio, 1992
MP&M
TOTAL
MP&M Share
Total Employment
615,706
3,723,809
16.5%
Payroll
$18,667,630,000
$85,085,182,000
21.9%
Value of Output
$111,052,845,000
$544,340,216,000
20.4%
Source: Department of Commerce 1992 Economic Censuses.
EPA obtained employment, payroll, and output data from
the 1992 Economic Census CD-ROM, drawing from the
eight economic censuses in Table 20.3. Employment and
payroll numbers include all employees (i.e., production plus
non-production workers). The measure of output differs
according to the source, but in each case the output
measures shown in Table 20.2 correspond conceptually to
total revenue. EPA extracted the EMPLOYEE, PAYROLL,
and VALUE fields for each 4-digit SIC industry in the
MP&M category and for the entire state of Ohio. Industries
include both in-scope and out-of-scope facilities.
Table 20.3: The Economic
Source
Census of Retail Trade
Census of Wholesale Trade
Census of Service Industries3
Census of Transportation,
Communications, and Utilities
Financial, Insurance, and Real Estate
Industries
Census of Manufacturers
Census of Mineral Industries
Census of Construction Industries
Censuses
Measure of
Output
Value of sales
Value of sales
Value of receipts
Value of revenue
Value of receipts
Value of shipments
Value of shipments
Value of
construction work
a. Includes both taxable and non-taxable establishments.
Source: Department of Commerce 1992 Economic Censuses.
The MP&M industries include facilities to which the
MP&M rule may not apply. For example, MP&M industries
include non-dischargers, but census data do not distinguish
between in-scope and out-of-scope facilities.
Also, the analysis examines only the industrial sectors for
which the Department of Commerce compiles statistics in
the Economic Censuses. Published industrial employment
and output measures often exclude military and other
government personnel and farm output and employment,
whether those exclusions are noted or not. The analysis
excludes $3.9 billion in value of agricultural products sold
in 1992 by farms in Ohio, according to the U.S. Department
of Agriculture's 1992 Census of Agriculture. The Ohio
analysis also excludes the government sector, which
employed approximately 734,000 people in Ohio in 1992,
according to the U.S. Bureau of Labor Statistics.3 These
exclusions are normal when economists compare the size of
industrial groups.
If total employment in Ohio includes the government sector,
then MP&M industries account for only 13.6 percent, rather
than 16.3, percent of employment. If total industrial
manufacturing and non-manufacturing output in Ohio
includes the agricultural sector, then MP&M industries
account for only 19.8, rather than 20.0, percent of output.
This said, data from the Bureau of Labor Statistics and
USD A are not completely consistent with the Economic
Census data.
3 U.S. Bureau of the Census, Statistical Abstract of the United
States, 1993, Washington, B.C., 1993.
20-3
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MP&M EEBA Part V: Ohio Case Study
Chapter 20: Baseline Conditions in Ohio
EPA augmented information on MP&M facilities available
from published data sources and the Section 308 survey by
oversampling the State of Ohio with 1,600 screeners. The
Agency used information from the Section 308 Survey and
the 1,600 screeners to characterize discharges from MP&M
facilities in Ohio and to assess the economic impact of the
proposed regulation at the state level. Figure 20.1 depicts
locations of the Ohio facilities included in the case study
analysis.
The map of facility locations shows that additional
information from 1,600 screeners enabled EPA to perform
the benefits assessment with a greater level of detail than is
possible at the national level. The added detail results in a
more complete and reliable analysis of changes in human
welfare resulting from improved recreational opportunities.
Figure 20.1: Location of Sample MP&M Facilities in Ohio
irinafi
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MP&M EEBA Part V: Ohio Case Study
Chapter 20: Baseline Conditions in Ohio
> 200,000 acres among 450 lakes, ponds, rivers, and
reservoirs; and
> 230+miles of Lake Erie shoreline.
These water resources provide three broad categories of
services: in-stream, withdrawal, and existence
services. Water resources provide in-stream services prior
to the withdrawal of water from the waterbody. Major in-
stream services include life support for animals and plants,
water-based recreation, commercial fishing and navigation,
water storage, and aesthetics. Withdrawal services include
uses of water resources after the water is withdrawn from
the waterbody. These uses include drinking water supply,
irrigation, production and processing services, and sanitary
services. Existence services are not linked to current uses of
waterbodies, and arise from knowing that species diversity
or the natural beauty of a given waterbody is preserved.
The Ohio Environmental Protection Agency (Ohio EPA)
assesses surface waters in their Ohio Water Resource
Inventory (OWRI) report based on water resource services
provided by the assessed waterbody. The main focus of this
assessment is on beneficial uses associated with Ohio's
water resources, including aquatic life use, recreation, and
public water supply. Table 20.4 shows how Ohio surface
waters fall into these use designations.
Table 20.4: Summary of Designated Life Uses for Ohio Surface Waters (1996)
Use Designation
Total
Aquatic Life Usea
Exceptional Warm-water Habitat (EWH)
Warmwater Habitat (WWH)
Other
Recreation
Primary Contact (PCR)b
Secondary Contact (SCR)
Public Water Supply
Stream/River
(Miles)3
43,917
24,067
3,217
18,318
2,532
224,96
1,188
Lakes /
Reservoir
(Acres)3
200,000
193,903
193,903
200,000
118,801
Lake Erie
(Shore
Miles)3
236
236
236
236
a. Total river/stream miles are based on Ohio EPA estimates. U.S. EPA estimates 61,532 total river miles and
29,113 total perennial miles based on RF3, which includes many smaller undesignated streams.
b. Note that some waterbodies have more than one designated use (e.g., aquatic life and primary recreation).
Source: Ohio EPA, OWRI, 1996.
The aquatic life use category is further subdivided into
seven categories. The most widely-applied aquatic use
designation in Ohio is Warmwater Habitat (WWH).
accounting for 18,318 (76 percent) stream and river miles
(Ohio EPA, OWRI, 1996). The second most widely applied
designation is Exceptional Warmwater Habitat (EWH).
accounting for 3, 217 stream and river miles (13 percent),
236 Lake Erie shore miles (100 percent), and 193,903 acres
of inland lakes (100 percent). Other aquatic life categories
include:
- Modified Warmwater Habitat (MWH).
- Limited Resource Waters (LRW).
> Limited Warmwater Habitat (LWH).
- Seasonal Salmonid Habitat (SSH). and
- Coldwater Habitat (CWH).
Recreational uses are subdivided into Primary Contact
Recreation (PCR) and Secondary Contact
Recreation (SCR):
* Primary Contact Recreation (PCR) rivers and
streams deep enough for full human body
immersion activities such as swimming.
* Secondary Contact Recreation (SCR) only deep
enough to permit wading and incidental contact,
such as boating.
Approximately half of the designated stream miles, all
inland lakes, and all of the Lake Erie shore miles are
designated for PCR (see Table 20.4). In addition, three
percent of the designated stream miles (1,188 miles) are
suitable for SCR.
The following sections detail each category of water
resource use.
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MP&M EEBA Part V: Ohio Case Study
Chapter 20: Baseline Conditions in Ohio
20.3.1 Aquatic Life Use
The Ohio water resources support hundreds of aquatic
species and plants. Ohio water resources are also home to a
number of endangered and threatened species. Suitable
stream and lake habitat are essential for both resident and
transient animal populations, including imperiled aquatic
species. Habitats include specific biotic components (e.g.,
assemblages of plant and animal species) and physical (e.g.,
dissolved oxygen (DO) content and temperature range)
components. Water quality impairments associated with
siltation, excess nutrients, or low DO can adversely affect
habitat that supports important activities, such as
reproduction, foraging, migration, and overwintering.
The following sections briefly introduce water-dependent
biological resources Ohio. Water quality effects on life
support for animals and plants are discussed in Section 20.5
a. Ohio fish species
Fish are found throughout Ohio in almost every inland
surface waterbody and Lake Erie. Many fish species serve
important recreational or commercial functions, while others
are important forage for birds, other fish, and land-based
species. Ecosystem well-being therefore depends on the
health offish and other aquatic species populations. The
Ohio EPA monitors biological data, especially those on
sensitive aquatic species, to determine the aquatic life use
attainment of surface waters. The state gives high priority to
healthy aquatic ecosystem maintenance.
Ohio's rivers and lakes offer a variety of manmade and
natural habitats that offer excellent fishing opportunities for
numerous gamefish species. The state of Ohio spends
significant resources on fishery management, trout stocking,
and recreational area maintenance to enhance these fish
populations. Table 20.5 below provides brief summaries of
the habitat and diet of major recreational and commercial
fish species in Ohio (Ohio DNR, 1999):
Table 20.5: Recreationally or Commercially Valuable Fish Species in Ohio
Fish
Bass
Bullhead
Burbot
Carp
Catfish
(Channel,
Flathead)
Crappie,
White
Crappie,
Black
Drum
Lamprey
Native or
introduced?
Most native bass
(e.g., largemouth,
smallmouth,
spotted, and sock)
Native
Native
Introduced
Native
Native
Habitat
Ponds, lakes, rivers, and streams in
every county; Lake Erie
Lhroughout Ohio. Concentrations in
northern and west central Ohio
Lakes and rivers. Prefer deep waters,
but move inshore to spawn
Warm lakes, streams, and ponds with
abundant organic matter, in every
county
Lhroughout Ohio's rivers and lakes.
Lolerate a wide range of conditions
Larger ponds, reservoirs, and rivers,
including nearshore habitats of Lake
Erie, in most areas of Ohio
Same general habitat as white crappie,
slightly less widely distributed
Lake Erie; drums support a commercial
fishery
Lake Erie and tributaries; Ohio River
and larger tributaries
Spawning
season
Mid-April to
mid- June
Mid-May to
June
Winter
Late April to
June
When waters
reach 70ฐ Fin
temperature
May and June
May and June
Spring into
late summer
Diet
Frogs, crayfish, insects, and other
fish
Insect larvae, crayfish, snails,
dead animals
Minnows and the young of other
fish species
Insect larvae, mollusks, fish,
crustaceans
Bottom feeders with a diet of
insect larvae, mollusks, and fish
both dead and alive
Insects and small fish
Insects and small fish
Mollusks, crayfish, fish, insects
Some species parasitize other fish
by attaching themselves to a
larger host's flank and feeding on
its flesh
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MP&M EEBA Part V: Ohio Case Study
Chapter 20: Baseline Conditions in Ohio
Table 20.5: Recreationally or Commercially Valuable Fish Species in Ohio
Fish
Muskellunge
(Muskie)
Perch, White
Perch,
Yellow
Pike
Salmon
(Chinook and
Coho)
Sauger
Saugeye
(cross
between
Sauger and
Walleye)
Sucker,
White
Sunfish
Trout
Walleye
Whitefish
Native or
introduced?
Native
Introduced
Native
Native
Introduced
Native
Introduced
Native
Bluegill,
Pumpkinseed,
Green, Warmouth,
and Longear
sunfish are native;
Redear sunfish are
introduced
Lake and Brook
trout are native;
Rainbow and
Brown trout are
introduced and
maintained by
stocking
Native
Native
Habitat
Historically found in Lake Erie bays and
tributaries and streams of Ohio River
drainage; now also found in several
impoundments
Lake Erie and tributaries
Lakes, impoundments, ponds, slow-
moving rivers
Historically abundant in Lake Erie and
tributaries. Today distributed in a small
portion of Lake Erie, Sandusky Bay,
Maumee Bay, and their tributary
streams in marshes, bays, and pools
with abundant vegetation
Stocked in Lake Erie for both
recreational and commercial fishing
purposes
Lake Erie and its tributaries; Ohio River
Stocked into many Ohio impoundments
Every county; Lake Erie
Rivers, streams, and lakes throughout
Ohio, and Lake Erie
Lake trout populations are stocked in
Pennsylvania and New York and are not
highly prevalent in Ohio and Lake Erie
waters; Brook trout are stocked in
several locations throughout Ohio
Historically found in Lake Erie, but has
been stocked in the Ohio River and
reservoirs throughout the state
Shallow bays of Lake Erie's western
basin
Spawning
season
April and early
May, when
temperatures
reach low to
mid-50s
April and May
As ice breaks
in late
February and
early March
Pike is a
popular ice-
fishing species
Spring, when
water
temperatures
reach high 40s
April to May
Between May
and August
April
Diet
Suckers, gizzard shard, and other
soft-rayed fish
Insects, crustaceans, other fish
Mostly fish, but are opportunistic
feeders; will occasionally eat
frogs, muskrats, small ducks
Insects, crayfish, other small fish
during low light (dawn and dusk)
Bottom feeders, consuming
various plant and animal species
Adults feed mostly on smaller
fish, insects, crustaceans
Shiners, gizzard shad, alewives,
rainbow smelt
Bottom feeders with a diet of
mollusks and insect larvae
Source: U.S. EPA analysis.
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Chapter 20: Baseline Conditions in Ohio
b. Other species dependent on aquatic
resources
Resident and migratory bird species make extensive use of
Ohio waters. Areas along the banks or shorelines of rivers,
streams, lakes, ponds, and reservoirs provide high quality
nesting areas; the waters themselves are an abundant source
of food. Ohio waters also serve as important staging areas
for birds migrating to or from points north or south. Wading
or aquatic birds are generally unaffected by water quality
impairments directly. They are affected indirectly, however,
through feeding on fish or invertebrates whose populations
may be affected by point and nonpoint pollution sources.
The regulations aimed at protecting aquatic species will
therefore benefit wading and aquatic bird species indirectly.
More than 130 aquatic bird species rely on Lake Erie and its
tributaries. Many species are also found near inland surface
waters. Major classifications of birds in Ohio include (Ohio
DNR, 1999):
> Waterfowl, residing year-round in Ohio waters,
especially Lake Erie. Large groups of migrating
and breeding birds are also found elsewhere in the
state. More than 30 species are associated with the
Great Lakes area alone. All species depend on fish
and crustaceans or aquatic plants for feeding.
Waterfowl include loons, grebes, swans, ducks and
geese. The trumpeter swan is of particular interest
to Ohio, which became one of several states
involved in efforts to restore these birds to the
Midwest beginning in 1996 (Ohio DNR, 1999).
> Wading birds, including bitterns, herons, and
egrets. These species both reside in Ohio waters
and use them as breeding grounds. They use
"stand-and-wait" methods to catch fish or other
aquatic organisms in shallow waters. Many wading
birds, such as the great egret, black-crowned night
heron, and American bittern, frequent Lake Erie
and surrounding areas.
> Marsh birds, including rails, moorhens, coots, and
gallinules. They may feed on insects, crustaceans,
mollusks, frogs, invertebrates, and small fish.
These bird populations suffer from excessive
development and habitat destruction. Ohio surface
waters, especially those around Lake Erie, can
serve as important breeding grounds for these and
other bird species.
* Shore birds, including 42 species of plovers,
sandpipers, gulls, and terns, in the Lake Erie and
other Ohio areas. Many of them feed on aquatic
organisms from Lake Erie.
* Raptors, including the bald eagle and osprey.
These birds of prey rely on fishing for a large part
of their diet. Bald eagles are also a nationally-listed
threatened species.
> The belted kingfisher, which relies on fish in Ohio
waters as a main source of food.
Ohio's biological resources also includes reptiles. Several
species of lizards, snakes, and turtles depend on aquatic
habitats for food and breeding. These reptiles include:
> Lizards - The Five-Lined Skink, reported in areas
along Lake Erie, can be found throughout Ohio.
> Snakes - The Eastern Fox Snake, Eastern
Massassasuga, Eastern Ribbon Snake, Copperbelly
Water Snake, Lake Erie Water Snake, and Northern
Water Snake feed within aquatic habitats.
- Turtles - The Midland Smooth Softshell Turtle and
Eastern Spiny Softshell Turtle, found in the Ohio
River and tributaries, are among Ohio turtles
requiring aquatic habitats.
20.3.2 Water Recreation in Ohio
EPA used the 1993 Survey of National Demand for
Water-based Recreation (NDS) (U.S. EPA, 1993) to
characterize recreational uses of Ohio's water resources.
The 1993 survey collected data on demographic
characteristics and water-based recreation behavior using a
nationwide stratified random sample of 13,059 individuals
aged 16 and over. Respondents reported on water-based
recreation trips taken within the previous 12 months,
including the primary purpose of their trips (e.g., fishing,
boating, swimming, and viewing), total number of trips, trip
length, distance to the recreation site(s), and number of
participants. EPA estimated recreational water use in Ohio
by taking the following steps:
* Estimate the percentage of survey respondents that
visited Ohio, by state.
> Apply this percentage to the total number of state
residents aged 16 and over, to yield the total
number of participants from each state.
> Estimate the total number of recreation trips during
the 12-month period for in-state and out-of-state
participants.
> Estimate the total number of recreation trips for
out-of-state participants by multiplying an average
number of trips per Ohio waterbody visitor by the
total number of participants from each state.
* Estimate the average number of annual trips per
out-of-state visitor based on the number of times
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MP&M EEBA Part V: Ohio Case Study
Chapter 20: Baseline Conditions in Ohio
the respondents visited the site of their last
recreational trip (i.e., Ohio waterbody).4 EPA
assumed that Ohio residents whose last recreation
trip was in-state used Ohio waterbodies for all of
their recreation trips during the 12-month period.
> Estimate the total number of in-state trips, summing
the weighted number of recreation trips over all
Ohio respondents.
EPA found that:
* An estimated one million individuals made about
6.3 million boating trips to Ohio waters in 1993.
In-state residents made 90 percent of the boating
trips.
> Approximately one million people visited Ohio
waterbodies for recreational fishing.5 These
visitors accounted for about 15.6 million fishing
trips to the area. Recreational fishermen from Ohio
were the most frequent users of the state water
resources, representing approximately 97 percent of
all visitors.
- Approximately 972,000 and 896,000 visitors used
the Ohio waterbodies for near-water viewing and
swimming, respectively, in 1993. These visitors
account for approximately 9.4 and 7.8 million
viewing and swimming trips to the area. Ohio
residents account for 89 percent of viewers and 93
percent of swimmers.
> Most out-of-state recreational users came from the
states surrounding Ohio, such as Indiana,
Michigan, and Pennsylvania.
20.3.3 Commercial Fishing in Ohio
Commercial fishing is a minor activity in Lake Erie: 12
license holders share a total of 19 licenses (www.lecba.org).
Commercial catch data compiled by the Great Lakes Fishery
Commission are summarized in Table 20.6.
4 NDS collected information only on the last site visited. Its
numbers do not reflect people whose last visit was to a different
area, but who may have also visited an Ohio waterbody on a
previous trip during the year. See Section 21.3 for detail on the
NDS data.
5 EPA compared the estimated number of participants with
total fishing licenses issued by Ohio in 1996. Ohio issued a total of
895,770 licenses for resident and nonresident fishing. The NDS
data therefore provide relatively accurate information on
participation rates.
Table 20.6:
Lake
Fish
Yellow Perch
Carp
White Perch
Sheepshead
White Bass
Channel Catfish
Quillback
Buffalo
Bullheads
Suckers
Goldfish
Gizzard Shad
Lake Whitefish
Rock Bass
Commercial catches for Ohio
Erie Waters (1990)
Catch (1990 Ibs)
1,559,000
1,190,000
786,000
640,000
392,000
365,000
134,000
132,000
59,000
41,000
31,000
19,000
10,000
1,000
Source: Great Lakes Fishery Commission,
www.glfc.org/fishmgmt/comdat.
Yellow perch represents about half of the dockside value for
the entire commercial fishery in the Ohio waters of Lake
Erie. The value of this fishery ranged from $ 1.3 million to
$2.5 million between 1993 and 1998. Overfishing and
pollution have decreased the yellow perch population
throughout Lake Erie dramatically over the past 30+ years.
Annual catches averaged around 20 million pounds during
the 1960s and 70s. The Lake Erie Committee set the 1998
lakewide total allowable catch (TAG) quota for this
species at 7.44 million pounds. The yellow perch fishery
rebounded somewhat over the past couple of years, due to
strong annual recruitment, strict commercial catch
restrictions, and a strict creel limit of 30 fish per day for the
sport angler (www.lecba.org).
20.3.4 Surface Water Withdrawals
Water resources provide a wide range of services upon
being withdrawn (removed) from the waterbody. Once
used, water can be returned to its original sources, returned
to another waterbody, or consumed (e.g., for human drinking
water). Water withdrawals from surface water averaged
9,615 mgd in 1995 (http://water.usgs.gov/watuse). The
majority of this water is used in power generation,
accounting for 85 percent of all surface water withdrawals.
Public water supply accounts for ten percent of all
withdrawals. Industrial and commercial water use account
for one and four percent of the total, respectively. Water
quality and quantity impairments can have substantial
impacts on the key withdrawal services that water provides
to a wide range of economic entities.
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Chapter 20: Baseline Conditions in Ohio
20.4 SURFACE WATER QUALITY IN
OHIO
This section describes current water quality conditions in
Ohio and the effects of water quality impairments on
beneficial uses of Ohio's water resources. Ohio EPA
assessed designated use attainment in approximately 42
percent of Ohio streams and rivers; approximately 64
percent of lakes, ponds, and reservoirs; and all of the Lake
Erie shoreline (Ohio EPA, OWRI, 1996). The OWRI report
summarizes the results of this assessment. This report
provides information on designated use support by water
type and use designation, identifies major pollutant/stressors
that affect the quality of surface waterbodies and prevent
designated use attainment, and lists major sources of
impairment. The following three sections summarize
findings from the 1996 OWRI report.
20.4.1 Use Attainment in Streams and
Rivers in Ohio
Most waterbodies are designated for several uses and more
than one use can be impaired at a time. The most commonly
occurring sole impairment in fresh waterbodies is to aquatic
life support. The Ohio EPA used an ecosystem approach
that relies on various tools to determine aquatic life use
attainment. Water chemistry, physical and habitat
assessment, and direct sampling of biota all contribute to
determine whether a waterbody meets an attainment status.
Field data yield biological indices that eventually determine
a final attainment score.
Ohio EPA assessed 6,560 perennial river miles for aquatic
life use attainment. Of the 6,560 river miles assessed for
aquatic life use:
* 38.5 percent (2,536 miles) are in full attainment,
i.e., all water quality indicators meet criteria for
specific waterbodies;
* 10.8 percent (708 miles) are in full attainment, but
are threatened by pollution and other sources;
* 23.3 percent (1,528 miles ) are in partial attainment,
i.e., one of two, or two water quality indicators do
not meet criteria; and
> 27.4 percent (1,797 miles) are in non-attainment;
i.e., no criteria are met or the river experiences a
severe toxic impact.
Fecal coliform bacteria counts determine recreational use
attainment. Such counts are less stringent for SCR than for
PCR. Ohio EPA has assessed 2,402 river miles for
recreation use since 1988 (Ohio EPA, OWRI, 1996). Of the
2,402 river miles assessed for recreation use:
> 57 percent (1,370.3 miles) of the sampled rivers
and streams are in full attainment; i.e., a waterbody
meets all chemical criteria for recreational use and
human contact;
* 19.7 percent (474.1 miles) are in partial attainment;
i.e., a waterbody only partially meets human
contact criteria; and
> 23.2 percent (557.4 miles) are in non-attainment;
i.e., a waterbody fails to meet human contact
criteria.
20.4.2 Lake Erie and Other Lakes Use
Attainment
Lake Erie, which has a history of pollution problems,
currently has fish consumption advisories for carp and
channel catfish (Ohio DNR, 1999). Ohio EPA assesses
Lake Erie as having partial use attainment for aquatic life
and fish consumption, and full attainment for recreation.6
Ohio EPA used parameters specified by the Ohio EPA
Lake Condition /nctex(LCI)to develop use attainment
for other lakes. Only approximately two percent of all lakes
are in full use attainment for aquatic life, recreation, and fish
consumption. Approximately 82, 50, and 53 percent are in
full attainment for aquatic life, recreation, and fish
consumption, respectively, but are threatened for these
categories. High percentages of lake acres are in partial
attainment for recreation (38.8 percent) and public supply
(43.8 percent) use designations. Table 20.7 shows use
attainment for Lake Erie and other lakes, ponds, and
reservoirs.
6 Further methodologies to better assess use attainment in
Lake Erie are still under development by the Ohio EPA.
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Table 20.7: Use Attainment Summary for Lake Erie one Other Lakes
Use Category
Lake Erie (Unit: Shore M
Aquatic Life (EWH)
Recreation
Fish Consumption
Lakes, Ponds, & Reservoii
Aquatic Life (EWH)
Recreation (PCR)
Public Water Supply
% of Total
Units
Assessed
%
iles)
100
100
100
rs (Unit: Acres)
64.7
64.4
64.1
Full
Attainment
Units
231
1,651
1,392
1,301
%
98
2.2
1.8
1.7
Full Attainment,
threatened
Units
63,174
38,499
40,846
%
82.2
50.3
53.6
Partial
Attainment
Units
236
5
236
10,686
29,793
33,365
%
100
2
100
13.9
38.9
43.8
Non-Attainment
Units
1,302
6,582
673
%
1.7
9.0
0.9
Assessments are based on unit of measure presented in parentheses.
Source: Ohio EPA, OWRI1996.
20.4.3 Causes and Sources of Use Non-
Attainment in Ohio
Ohio EPA assessed the causes and sources of impairment to
Ohio surface waters and examined trends in major causes
and sources from previous assessment cycles. The
following discussion summarizes findings from the 1996
OWRI report (Ohio EPA, 1996).
a. Causes
Causes are the agents responsible for damage and threats to
aquatic life. The major causes of impairment in Ohio
surface waters include:
* Organic enrichment/low DO,
* Habitat modifications,
* Siltation,
* Flow alteration,
* Nutrients, and
* Metals.
Ohio EPA examined trends in these major causes from
previous assessment cycles through 1996. They found that
point source-related causes declined, while nonpoint sources
became major contributors. Ohio EPA concluded that this
trend "reflects the relative effectiveness of the programs to
control point sources compared to general lack of measures
to control many [nonpoint sources]" (Ohio EPA, OWRI,
1996).
Organic enrichment, which alters DO levels and affects
aquatic communities, is the main cause of impairment in
Ohio's rivers and streams. Inadequate wastewater treatment
from municipal and industrial point sources account for
most of this impairment. Metals are a major cause of
impairment to approximately 226 river miles, a moderate
cause of impairment to 179 river miles, and a minor cause of
impairment or threat to 165 river miles.
Nutrients, resulting mostly from agricultural nonpoint
sources, are the main cause of impairment in lakes. Metals
are a major cause for impairment in approximately 250 acres
of Ohio's lakes, ponds, and reservoirs, and form the main
cause of impairment in Lake Erie, the major water resource
in Ohio (90 percent of the surface water volume). Highly
developed areas bordering the lake contribute urban runoff,
along with discharges from industrial and municipal sources.
Other causes of impairment in Lake Erie include priority
organics, DO, and nutrients.7
b. Sources
Sources are the origins of the agents responsible for damage
and threats to water resources. The major sources of
impairment to Ohio surface waters include:
* Municipal and industrial discharges,
* Hydromodification,
> Agricultural runoff,
* Urban runoff, and
* Mining.
7 Major, moderate, and minor impacts refer to the high,
moderate, and slight magnitude codes specified by the U.S. EPA
for the 30 l(b) report.
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Point source-caused impairment has declined over time,
while that from nonpoint sources, such as agricultural and
urban runoff, has increased. Point sources remain a major
source of impairment in almost 900 miles, or 25 percent, of
Ohio's affected rivers and streams. Point sources are the
major source of impairment for Lake Erie. They form a
major source of impairment for 24 shore miles, and a
moderate source of impairment for an additional 281 shore
miles of Lake Erie. In addition, point sources adversely
affect 1,678 lake acres.
Nonpoint sources related to agricultural and urban runoff
form the major source of impairment for some 9,000 acres,
or two-thirds of Ohio's lakes, ponds, and reservoirs. In
addition, 46 Lake Erie shore miles list nonpoint sources as
their major impairment source.
20.5 EFFECTS OF WATER QUALITY
IMPAIRMENTS ON WATER RESOURCE
SERVICES
Water resource services are negatively affected by pollutants
that impair the aquatic ecosystems. Certain pollutants can
adversely affect aquatic species directly by increasing
species morbidity and/or impairing reproductive success, or
indirectly by adversely altering food chain interactions.
These direct and indirect impacts can change quantity and
type of fish and other species in the aquatic ecosystem. In
the worst case scenario, an impaired ecosystem no longer
supports any aquatic life. High pathogen counts or
excessive eutrophication in waterbodies that are suitable for
swimming may force swimmers to go elsewhere or forego
swimming altogether. Any aesthetic degradation decreases
the value of each individual's recreational experience. In
severe cases, the affected waterbodies become unsuitable for
recreation. Water quality impairments also increase the cost
of treating water to meet drinking water standards.
This section details the effects of water quality impairments
on in-stream services provided by Ohio's water resources.
20.5.1 Effect of Water Quality
Impairment on Life Support for Animals
and Plants
Deficiencies in water quantity and quality can impair the
health of aquatic ecosystems. In worst case scenarios, the
ecosystem may no longer support aquatic life at all. The
major causes of water quality impairment in Ohio include
high biological oxygen demand (BOD) from organic
enrichment, habitat and flow alterations, nutrients, siltation
and turbidity, metals, pH, ammonia, and priority
organics. Habitat, flow alterations, and thermal discharges
are unrelated to MP&M effluents and are not discussed
here. MP&M effluents contribute to the remaining major
causes of water quality impairment, with the ecological
effects outlined below.
a. BOD/COD
BOD and chemical oxygen demand (COD) are two
methods to determine the oxygen requirements of pollutants
in wastewater. Low oxygen level is the primary cause of
impairment in Ohio's rivers and streams and a major course
of impairments in Ohio' s lakes. When bacteria decompose
excess organic matter, they consume DO in surface waters.
Oxygen is needed to chemically (abiotically) oxidize the
pollutants present in wastewater. When too much oxygen is
needed to oxidize pollutants, hypoxic (oxygen deficient) or
anoxic (oxygen depleted) conditions result. Sources of high
oxygen demand include effluents from municipal treatment
plants and certain industries, and runoff from feedlots or
farms. Another source is eutrophication caused by
excessive nutrient input. The nutrients stimulate algal
blooms. Bacteria consume the algae when they die,
decreasing DO in the water column. DO is a critical
variable for fish and invertebrate survival. If oxygen
concentrations drop below a minimum level, organisms
suffocate and either move out or die (EPA, 1986). This
effect can drastically reduce the amount of useable aquatic
habitat.
b. Nutrients
Nutrients are the leading causes of impairment in Ohio lakes
and comprise one of the major causes of impairment in
rivers, streams, and Lake Erie. The overabundance of
nitrogen and phosphorus is one of the most documented
forms of aquatic ecosystem pollution. Although both
compounds are essential nutrients for phytoplankton (free-
floating algae) and periphyton (attached algae), which form
the base of the aquatic food web, too much nutrient input
overstimulates primary productivity and results in
eutrophication. The impact of these compounds has
contributed significantly to water quality decline in the
United States (EPA, 1992). Phosphorus is a limiting
nutrient in most freshwater systems (Wetzel, 1983), whereas
nitrogen is typically limited in estuarine and marine systems.
In freshwater, excess phosphate (PO4) has been linked to
eutrophication and nuisance growth of algae and aquatic
weeds (Wetzel, 1983), even though direct toxicity to fish
and other aquatic species is not a major concern. DO in the
water column decreases, however, when algae and other
aquatic plants die off, and certain toxins may be produced,
both of which can contribute to fish kills.
c. Siltation and turbidity
Siltation and turbidity are the third leading causes of
impairments in Ohio rivers and lakes, except Lake Erie.
Siltation is the most important factor in surface water
degradation in the U.S. (EPA, 1992). Major sources include
urban and storm water runoff, mining and logging activities,
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Chapter 20: Baseline Conditions in Ohio
and runoff from plowed fields (EPA, 1992). All these
inputs create cloudy water with increased turbidity and
decreased visibility and light penetration. High primary
productivity by phytoplankton following excessive nutrient
input can also increase turbidity. Excess suspended matter
decreases the amount of light penetrating the water column,
which can reduce primary productivity. This turbidity can
eliminate or displace fish species requiring clear water to
live, feed, or reproduce.
d. Metals
Metals are the leading cause of impairment in Lake Erie and
comprise one of the major causes of impairment in inland
lakes and rivers. Metals are naturally-occurring inorganic
constituents of the earth's crust. Priority pollutant metals
commonly found in the aquatic environment include
antimony, arsenic, cadmium, chromium, copper, lead,
mercury, nickel, selenium, silver, thallium and zinc (EPA,
1998a). These compounds enter the aquatic environment via
urban stormwater runoff, industrial and municipal effluents,
and atmospheric deposition. As a group, metals can be
highly toxic: water quality criteria (WQC) for acute
toxicity range from around 1,100 ug/1 (chromium VI in salt
water) to around 1 ug/1 (mercury in freshwater); WQC for
chronic toxicity range from 120 ug/1 (zinc in freshwater) to
<1.0 ug/1 (mercury in salt- and freshwater) and are therefore
an order of magnitude lower (EPA, 1998a).
Once metals reach the aquatic environment, they tend to
associate with organic and inorganic particulates in the
water column. Sediments become long-term sinks for
metals, which accumulate in the bottom. Metals can enter
the food chain when ingested by benthic invertebrates or
other burrowing organisms. Most metals have
bioconcentration factors (BCFs) ranging from 100 to
10,000 and can therefore bioaccumulate in aquatic
organisms. A few, including selenium, lead, and mercury,
may reach hazardous levels in fish or wildlife receptors and
result in avian developmental or neurological abnormalities.
z. Organic chemicals
Priority organics are the second most frequent cause of
impairment in Lake Erie and comprise one of the major
causes of impairment in rivers and streams. Thousands of
different compounds exist as organic chemicals, including
petroleum hydrocarbons and myriad industrial chemicals.
They enter the aquatic environments via municipal and
industrial effluents, stormwater runoff, contaminated
groundwater, atmospheric deposition, illegal dumping, or
accidental releases. Aquatic toxicities vary by orders of
magnitude depending on the compound. Factors influencing
toxicity and long-term ecological effects include water
solubility, volatility, biodegradation potential, and
bioaccumulation potential.
Excessive amounts of organic chemicals degrade surface
water quality by causing acute or (more typically) chronic
toxicity. This toxicity impairs growth, development, and/or
reproductive success in fish and aquatic invertebrates.
Persistent and low water-soluble organic chemicals
accumulate in sediments and are taken up into local aquatic
food chains. They can reach dangerous concentrations in
fish and avian receptors, resulting in reproductive failures or
other avian health effects.
f. pH
Approximately 180 river miles are pH-impaired in Ohio. pH
is a measure of acidity. Acid reaches surface waters via
atmospheric deposition ("acid rain"), industrial effluents,
and leachates from mine overburdens or spoils. Acidity
by itself is a key variable shaping aquatic communities: it is
a toxicant in its own right but also controls metal solubility,
and the toxicity of several metals and ammonia.
Aquatic species vary widely in their sensitivity to pH: the
most sensitive vertebrate and invertebrate species die off
when average pH ranges between 6.0 and 6.5. Most fish
species are eliminated when pH reaches 5.0. Only a few can
survive at pH 4.5 (U.S. EPA, 1999). Macro invertebrates
exhibit the same pattern, except that hardy species can
survive down to a pH of about 3.5.
g. Ammonia
Large amounts of ammonia enter lakes and rivers via
wastewater treatment plants and industrial effluents,
atmospheric deposition, and nonpoint surface runoff.
Approximately 150 river miles in Ohio are ammonia-
impaired. This compound, unique among regulated
pollutants, is also produced naturally inside fish as a
metabolic waste product. Excess ammonia usually diffuses
rapidly out of the blood stream and into the surrounding
water via the gills. High concentrations of external
unionized ammonia (NH3) reduce or reverse this diffusive
gradient and allow ammonia to build up to toxic levels
inside the organism (EPA, 1998c).
Ammonia in surface water exists in two major forms: un-
ionized ammonia (NH3), which is highly toxic to fish or
invertebrates, and ammonium ion (NH4+), which is much
less toxic. Which form prevails depends mainly upon the
pH level; temperature and ionic composition play a smaller
role. EPA calculated a WQC that becomes more severe with
decreasing acidity. For example, the acute criteria for
surface waters containing salmonids equals 36.7 mg/1 at
pH=6.0 but only 2.14 mg/1 at pH=8.5. For surface waters
without salmon, the acute criteria for the same pH equal
55.0 mg/1 and 3.2 mg/1, respectively (EPA, 1998c).
20.5.2 Effect of Water Quality
Impairment on Recreational Services
Healthy surface waters are essential to support a diversity of
recreational uses, including viewing and other near-water
activities. Industrial or other human activities impair surface
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Chapter 20: Baseline Conditions in Ohio
water quality. Certain metals and chlorinated compounds
can bioaccumulate in aquatic food chains and reach
unhealthy levels in carnivorous fish or shellfish. Health
advisories to limit or avoid their consumption may result.
High concentrations of toxic compounds can also lead to
human contact advisories. The release of untreated or
poorly treated sewage can cause high levels of pathogenic
bacteria in water and result in swimming advisories or beach
closures. All of these actions limit the full use of surface
waters and can have significant local economic impacts.
a. Fish consumption advisories
In 1997, the Ohio Department of Health (ODH) issued a
statewide fish consumption advisory to protect women of
childbearing age and children six years or younger against
mercury's neurological and developmental effects. The
advisory, which applies only to these two population groups,
recommended that these women and children eat no more
than one meal per week of any fish caught in Ohio waters.
The advisory covers all state waters because most of the
mercury measured in fish tissues originates from region-
wide fossil fuel combustion processes. The mercury reaches
surface waters via atmospheric deposition on the
surrounding landscape (Ohio DNR, 1999).
Since 1983, the ODH has developed numerous waterbody -
specific fish consumption advisories for approximately 174
waterbody segments (rivers and lakes) and Lake Erie. These
waterbodies represent a relatively small fraction of Ohio's
5,000 discrete waterbody segments, as determined by Ohio
EPA. The contaminants of greatest concern include
polychlorinated biphenyls (PCBs). mercury,
polycyclic aromatic hydrocarbons (PAHs). lead,
organometallics, Mirex, phthalate esters, Chlordane, and
hexachlorobenzene. Of these, four mercury, PAHs, lead,
and phthalates are included on the MP&M list of
pollutants of concern (POCs). As a group, these
contaminants are generally characterized as lipophilic (i.e.,
fat loving), resistant to biological degradation or cellular
metabolism, and toxic. Once they reach surface water, they
concentrate in sediments and bioaccumulate or biomagnify
through aquatic food chains. These compounds can linger
for decades in aquatic systems.
The kind of sports or recreational fish species affected by
the consumption advisories varies by waterbody segment.
More than 23 different species are covered by advisories,
including walleye, common carp, sauger, saugeye, white
crappie, freshwater drum, and various species of bass, perch,
catfish, salmon, trout, suckers, and sunfish. Restrictions
vary depending on the pollutant, the fish species concerned,
and the concentrations measured in edible tissues. The
ODH developed maximum recommended rates offish
consumption that include outright consumption bans, one
meal every two months, one meal a month, or one meal a
week. The same waterbody segments can commonly have
different advisories for different fish species (Ohio DNR,
1999).
b. Contact advisories
The ODH also issued human contact advisories for nine
waterbody segments in Ohio located on the Black River,
Little Scioto River, Mahoning River, the middle fork of the
Little Beaver Creek, and the Ottawa River. Swimming or
wading is prohibited due to the presence of high levels of
PAHs, PCBs, Mirex, phthalate esters, and/or Chlordane. Of
these, PAHs and phthalates are included on the list of
MP&M POCs. Fish consumption advisories also cover all
of these segments (Ohio DNR, 1999).
c. Beach closures
Beach closures typically occur during the summer months
when high levels of fecal coliform bacteria or other disease-
causing organisms (e.g., Escherichia coli) proliferate in
surface waters. Such waters can become contaminated from
several sources, including: agricultural runoff, sewer
overflows, boating wastes, and poor hygienic practices by
some bathers. Excessive levels of indicator pathogens in
surface waters can indicate a serious threat to human health
and may cause health departments to post warnings, restrict
access, or forbid swimming altogether. The MP&M
regulation is not expected to reduce beach closures during
summer months.
Numerous public bathing beaches dot Ohio's 262-mile
shoreline along Lake Erie. The ODH has developed a
composite metric based on E. coli counts in surface waters at
11 selected beaches along Ohio's north coast. The metric
tracks the average number of days that swimming advisories
are posted at the 11 beaches for a 15 week period beginning
around Memorial Day and continuing through Labor Day.
The most recent data available show that the 11 beaches
were under advisement an average of 21 days during the
summer months (minimum of 0 days and maximum of 49
days) in 1996.
The ODH developed a 4-tiered scale to score and track the
average number of days that the 11 public beaches are under
advisement from one year to the next. Between 1990 and
1996, the average (based on a five-year running average)
number of beach advisories scored in the "fair" category
consistently, meaning that the beaches were under
advisement between 20 and 30 days in the summer (State of
Ohio, 1998).
Ohio's lakes, ponds and reservoirs (excluding Lake Erie)
yielded no quantitative data on beach closures. The 1996
Ohio Water Resource Inventory of Public Lakes, Ponds and
Reservoirs provides a breakdown of the portion of Ohio's
446 public lakes that are threatened or impaired as a result
of high levels of fecal coliform bacteria.
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MP&M EEBA Part V: Ohio Case Study
Chapter 20: Baseline Conditions in Ohio
20.6 PRESENCE AND DISTRIBUTION OF
EN&ANSERE& AND THREATENED SPECIES
IN OHIO
Many factors can affect the survival of endangered and
threatened (E&T) species. Some factors are species-
specific; others result from one or more anthropogenic
stressors. Inherent vulnerability factors include narrow
geographic distribution, slow reproductive rates, or
requirements for large areas. Major anthropogenic stressors
include intentional taking (e.g., fishing), incidental taking,
physically altering habitat (e.g., converting wetlands into
agricultural land), water pollution, and introducing alien
species. A single stressor or a set of stressors can contribute
to a species' decline or extinction. Previous studies reported
that more than 40 percent of endangered aquatic species
were affected by five or more environmental stressors, and
only seven percent of federally-listed species had a single
threat to their survival. Although stressors seldom act alone,
water pollution is one of the major hazards to E&T aquatic
species, cited as responsible for the decline of 19 (54
percent) out of 35 E&T fish species in Ohio (Ohio DNR,
1998).
The following sections provide an overview of E&T species
found in Ohio, their distribution, and the major hazards
threatening their survival. Species discussed below include
those listed under both the federal Endangered Species
Act (50 CFR Part 17) and the Ohio Department of
Natural Resources'(DNR) Division of Natural Areas
and Preserves. The MP&M regulation concentrates on
water-related benefits; these sections therefore describe only
those species associated with aquatic environments.8 The
DNR list includes 90 E&T species with a total of 1,227
observations throughout Ohio. "Observations" refers to
locations where species were observed; most species have
multiple observations. This analysis includes observations
spanning the years 1980 to 1988.
20.6.1 E&T Fish
E&T fish inhabit almost every major waterbody in Ohio,
including Lake Erie and the Ohio River and its tributaries.
The Ohio DNR lists 35 total state-listed E&T fish species,
of which 13 are threatened and 22 endangered. The list
includes only one federally-listed species, the Scioto
Madtom.
Of the total E&T fish, approximately 12 species use Lake
Erie as a possible habitat and nine use the Ohio River. Most
of the species listed live in riverine habitats. Approximately
28 species were identified in a river system in Ohio,
including the Ohio, Scioto, Muskingham, Miami,
Walhondig, and Maumee River systems. MP&M facilities
are found on all these major river systems.
The DNR lists 384 observations of E&T fish in Ohio, of
which 240 observations of 30 different species have been
reported since 1980. Figure 20.2 maps the observations of
E&T fish in Ohio and shows the extent to which these
observations were reported in the state. Multiple
observations can occur for a single species. In southern
Ohio, most observations come from the Muskingham and
Scioto River systems and the Ohio River. Most
observations in northern Ohio came from Lake Erie
tributaries or the lake itself.
In addition to water pollution, cited above as major hazard to
E&T aquatic species, other major hazards to E&T fish
include siltation and impoundments. Approximately two-
thirds of E&T fish species are threatened by siltation, and 17
percent are threatened by impoundments or dams. MP&M
regulations can improve affected ecosystems or habitats by
reducing discharges from MP&M facilities. These
improvements can then help reduce siltation and restore
some of the E&T fish populations.
Many obscure E&T fish species have a pure existence value.
Some E&T species, like brook trout and lake sturgeon, have
high potential for consumptive uses. Restoring their
populations and those of other commercial and recreational
fish species may enhance recreational fishing opportunities.
Table 20.8 lists E&T fish in Ohio, their habitat locations,
and the cause for their E&T listing. The table lists species
alphabetically by scientific name.
20.6.2 E&T Mollusks
Mollusks yield the largest number of reported observations
of aquatic E&T species in Ohio, representing 48 percent of
the total 1,227 observations. The Ohio DNR lists 29 E&T
mollusk species, four threatened and 25 endangered. Of
these, five mollusk species are on the federal endangered
species list: Catspaw, Clubshell, Fanshell, White Catspaw,
and Pink Mucket. Ohio's E&T mo Husks concentrate in five
major areas: Lake Erie and the Grand River tributary, Scioto
River and Big Darby tributary, Muskingham River, Little
Miami River, and the Ohio River. E&T mollusk populations
reside mostly along the mainstems of large rivers and in
Lake Erie, but are also found in the St. Joseph, Sandusky,
and Cuyahoga Rivers.
8 "Aquatic species" were identified by the Ohio Department
of Natural Resources, Division of Natural Areas and Preserves.
These species include any species that are "closely associated with
aquatic habitats through their breeding or feeding requirements."
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MP&M EEBA Part V: Ohio Case Study
Chapter 20: Baseline Conditions in Ohio
Figure 20.2: E&T Fish Observances in Ohio
(1980-1997)
Ohio
Source: U.S. EPA analysis.
20.6.3 Other Aquatic E&T Species
Improved water quality resulting from the MP&M
regulation may also benefit other aquatic E&T species.
Unlike fish and mollusks, whose primary habitat is a surface
waterbody at all times, these species may use only surface
water-related habitats for breeding or feeding. Improved
water quality may benefit these populations indirectly by
enhancing the quality and quantity of aquatic biological
resources.
Other aquatic-associated E&T species of Ohio include:
* Birds ten state-listed species, one threatened and
nine endangered, include one federally-listed
threatened species, the Bald Eagle. The state-listed
species include: American and Least Bitterns,
Common and Black Terns, Yellow- and Black-
Crowned Night-Herons, King Rail, Osprey, and
Snowy Egret. These species are observed mostly
along the Lake Erie coast. The Bald Eagle is
observed mostly in Ohio's northeast corner.
* Amphibians three state-listed endangered
species: Blue-Spotted Salamander, observed in the
very northwest section of the state along small
streams and near the Maumee River; Eastern
Spadefoot, found near the Ohio and Muskingham
Rivers; and Eastern Hellbender, observed along the
Muskingham and Scioto River systems and
tributaries of the Ohio River.
Reptiles two species: the Copperbelly Water
Snake, a state-listed endangered and federally-listed
threatened species found in lakes and ponds in the
northwest corner of Ohio; and the Lake Erie Water
Snake, state-listed as threatened and a proposed
threatened species for the federal list, found only
along the edges of the Lake Erie islands.
Mammals the River Otter is state-listed as
endangered. Sparse observations of the animal
come from various small creeks and lakes in the
eastern part of Ohio.
Crustaceans the state-listed endangered Sloan's
Crayfish has been observed in several small
tributaries of the Great Miami River system.
Insects nine state-listed species, one threatened
and eight endangered, are reported throughout the
state.
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MP&M EEBA Part V: Ohio Case Study
Chapter 20: Baseline Conditions in Ohio
Table 20.8: Endangered and Threatened Fish Species of Ohio
Common Name i Scientific Name
Lake Sturgeon \Acipenserfulvescens
Longnose Sucker \Catostomus catostomus
Rosyside Dace \Clinostomusfunduloides
Cisco \Coregpnus artedi
Blue Sucker \Cycleptus elongatus
Lake Chubsucker \Erimyzon sucetta
Bluebreast Darter \Etheostoma camurum
Spotted Darter \Etheostoma maculatum
Tippecanoe Darter \Etheostoma tippecanoe
Tonguetied Minnow \Exoglossum laurae
Western Banded \Fundulus diaphanus menona
Killifish 1
Goldeye \Hiodon alosoides
Mississippi Silvery \Hybognathus nuchalis
Minnow i
Ohio Lamprey \Ichthyomyzon bdellium
Northern Brook \Ichthyomyzonfossor
Lamprey i
Mountain Brook \Ichthyomyzon greeleyi
Lamprey [
Silver Lamprey \Ichthyomyzon unicuspis
Blue Catfish \Ictalurusfurcatus
Spotted Gar \Lepisosteus oculatus
Shortnose Gar \Lepisosteus platostomus
Speckled Chub \Macrhybopsis aestivalis
Greater Redhorse \Moxostoma valenciennesi
Popeye Shiner \Notropis ariommus
Bigeye Shiner \Notropis hoops
Number of
Observations
3
1
53
1
2
28
19
8
11
16
9
16
1
4
25
6
40
j
9
12
4
22
Last
Observed
1979
1950
1997
1976
1985
1994
1995
1992
1994
1996
1994
1989
1983
1992
1992
1993
1993
1987
1978
1981
1990
1989
1993
1995
Federal
Status
State j
Status Habitat iCauses for Listing
E |Lake Erie, spawning in larger rivers such as iPollution and dams
iMaumee and Auglaize
E |Lake Erie iPollution creating low-oxygen
i levels
T jSmall, upland streams of Teay s and Little jRunoff and siltation
iScioto River systems
E iLake Erie iPollution and overfishing
E jOhio River and lower reaches of large iPollution, dams, increases in
itributaries iturbidity and siltation
T iLakes (not Erie} and larger streams ilncreased turbidity and siltation
T jScioto and Muskingham River systems, large iPollution and siltation
i streams
E jLarge streams of Muskingham and Scio to iPollution and siltation
i systems
T iMuskingham and Scioto River systems i
T jGreat Miami River system iUndetermined, likely pollution and
i i siltation
E jLake Erie and larger tributaries i Siltation
E JOhio River and lower reaches of large iPollution
itributaries i
E JOhio River and tributaries i Siltation
E JOhio River and lower reaches of large iPollution and siltation
itributaries i
E JSmall streams, tributaries of Grand and Scioto iPollution, siltation, and dams
irivers i
E jMahoning River and tributaries iPollution, siltation, and dams
T iLake Erie and larger tributaries :Pollution: siltationj and dams
E iScioto River
E iLake Erie i Siltation and dredging
E iScioto River and tributaries iPollution and siltation
E iOhio and Muskingham rivers^ large rivers iPollution and siltation
T iMaumee river system, large streams iPollution and siltation
E lExtirpated from Ohio, creeks and small rivers i Siltation
iof Maumee system
T iGreat Miami River and Ohio River systems, i Siltation and impoundments
iupland streams
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Chapter 20: Baseline Conditions in Ohio
Table 20.8: Endangered and Threatened Fish Species of Ohio
Common Name i Scientific Name
Bigmouth Shiner \Notrapis dorsalis
Blackchin Shiner \Notropis heterodon
Blacknose Shiner \Notropis heterolepis
Mountain Madtom \Noturus eleutherus
Northern Madtom \Noturus stigmosus
Scioto Madtom \Noturus trautmani
Pugnose Minnow :Opsopoeodus emiliae
Channel Darter \Percina copelandi
River Darter \Percina shumardi
Paddlefish \Polyodon spathula
Brook Trout \Salvelinusfontinalis
Number of
Observations
16
2
7
11
10
6
18
8
11
1
Last
Observed
1994
1983
1983
1991
1989
1957
1982
1991
1989
1996
1997
Federal
Status
E
State i
Status Habitat iCauses for Listing
T jBlack and Rocky river systems, brooks and ICompetition with silver minnow
i small streams
E iLake Erie and other lakes ilncreased turbidity and siltation
E iLake Erie and other lakes i Siltation
E jOhio River tributaries, larger streams and iPollution and siltation
irivers
E iMuskingham, Little Miami, Walhondis Rivers i
E iBig Darby Creek: tributary of Scioto iPollution and siltation
E iLakes, canals, streams, and Lake Erie ilncreased turbidity and siltation
T iLake Erie and Ohio River i Siltation
T iLake Erie and larger tributaries of Ohio River iPollution and siltation
T JOhio River tributaries, larger streams and iPollution and siltation
irivers
T jTributaries of Lake Erie iHabitat destruction - timbering and
^^^ non-native species
Source: Division of Natural Areas and Preserves, Ohio Department of Natural Resources, Natural Heritage Program 1998
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MP&M EEBA Part V: Ohio Case Study
Chapter 20: Baseline Conditions in Ohio
GLOSSARY
ammonia: a compound of nitrogen and hydrogen (NH3). It
is a colorless, pungent gas.
biological oxygen demand (BOD): the amount of
dissolved oxygen consumed by microorganisms as they
decompose organic material in polluted water.
bioconcentration factors (BCFs): indicators of the
potential for chemicals dissolved in the water column to be
taken up by aquatic biota across external surface
membranes, usually gills.
biotic: pertaining to the characteristics of a naturally
occurring assemblage of plants and animals that live in the
same environment and are mutually sustaining and
interdependent.
chemical oxygen demand (COD): The amount of
oxygen consumed in the complete chemical oxidation of
matter, both organic and inorganic, present in polluted
water.
Coldwater Habitat (CWH): a designation assigned to a
waterbody based on the potential aquatic assemblage.
conventional pollutants: biological oxygen demand
(BOD), total suspended solids (TSS), oil and grease (O&G),
pH, and anything else the Administrator defines as a
conventional pollutant.
dissolved oxygen (DO): oxygen freely available in
water, vital to fish and other aquatic life and for the
prevention of odors. DO levels are considered a most
important indicator of a waterbody's ability to support
desirable aquatic life. Secondary and advanced waste
treatment are generally designed to ensure adequate DO in
waste-receiving waters.
(http://www.epa.gov/OCEPAterms/dterms.html)
endangered and threatened (E&T): animals, birds,
fish, plants, or other living organisms threatened with
extinction by anthropogenic (i.e., man-caused) or other
natural changes in their environment. The Endangered
Species Act contains requirements for declaring a species
endangered.
Endangered Species Act: federal legislation enacted in
1973 that protects animals, birds, fish, plants, or other living
organisms threatened with extinction by anthropogenic or
other natural changes in their environment. For a species to
be protected under this act it must be "listed" as either an
"endangered" or "threatened" species.
eutrophication: process by which bodies of water receive
increased amounts of dissolved nutrients, such as nitrogen
and phosphorus, that encourage excessive plant growth and
result in oxygen depletion.
Exceptional Warmwater Habitat (EWH): the aquatic
life use designed to protect aquatic communities of
exceptional diversity and biotic integrity. Such communities
typically have a high species richness; often include strong
populations of rare, endangered, threatened, and declining
species; and/or are exceptional sport fisheries.
existence: services that are not linked to current uses of
waterbodies. They arise from the knowledge that species
diversity or the natural beauty of a given waterbody is being
preserved.
in-stream: water use taking place within the stream
channel for purposes such as life support for animals and
plants, water-based recreation, hydroelectric power
generation, navigation, commercial fishing, water storage,
and aesthetics.
Limited Resource Waters (LRW): an aquatic life use
assigned to streams with very limited aquatic life potential,
usually restricted to highly acidic mine drainage streams, or
highly modified small streams (<3 sq. mi. drainage area) in
urban or agricultural areas with little or no water during the
summer months.
Limited Warmwater Habitat (LWH): see limited
resource waters.
metals: inorganic compounds, generally non-volatile (with
the notable exception of mercury), that cannot be broken
down by biodegradation processes. They are of particular
concern due to their prevalence in MP&M effluents. Metals
can accumulate in biological tissues, sequester into sewage
sludge in POTWs, and contaminate soils and sediments
when released into the environment. Some metals are quite
toxic even when present at relatively low levels.
ug/l: micrograms per liter.
Modified Warmwater Habitat (MWH): aquatic life use
assigned to streams that have irretrievable, extensive, man-
induced modifications that preclude attainment of the
Warmwater Habitat use, but which harbor the semblance of
an aquatic community. Such waters are characterized by
poor chemical quality (low and fluctuating dissolved
oxygen), degraded habitat conditions (siltation, habitat
simplification), and species that are tolerant of these effects.
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Chapter 20: Baseline Conditions in Ohio
nonconventional pollutants: a catch-all category that
includes everything not classified as either a priority or
conventional pollutant.
nutrients: any substance, assimilated by living things, that
promotes growth. The term is generally applied to nitrogen
and phosphorus in wastewater, but is also applied to other
essential and trace elements.
(http://www.epa.gov/OCEPAterms/nterms.html)
Ohio EPA Lake Condition Index (LCI): an
ecologically-based index that aggregates results across ten
ecological metrics.
Ohio Water Resource Inventory (OWRI): a biennial
report to U.S. EPA and Congress required by Section 305(b)
of the Clean Water Act. The report is composed of four
major sections: (1) inland rivers and streams, wetlands, Lake
Erie, and water program description; (2) fish tissue
contaminants; (3) inland lakes, ponds, and reservoirs; and
(4) groundwater.
overburdens: rock and soil cleared away before mining.
(http://www.epa.gov/OCEPAterms/oterms.html)
pH: an expression of the intensity of the basic or acid
condition of a liquid; Natural waters usually have a pH
between 6.5 and 8.5.
(http://www.epa.gov/OCEPAterms/pterms.html)
pollutants of concern (POCs): the 131 contaminants
identified by EPA as being of potential concern for this rule
and that are currently being discharged by MP&M facilities.
EPA used fate and toxicity data, in conjunction with various
modeling techniques, to identify these pollutants and assess
their potential environmental impacts on receiving
waterbodies and POTWs. MP&M pollutants of concern
include 43 priority pollutants, 3 conventional pollutants, and
86 non-conventional pollutants.
polychlorinated biphenyls (PCBs): group of toxic,
persistent chemicals that are mixtures of chlorinated
biphenyl compounds having various percentages of chlorine.
PCBs are industrial chemicals formerly used in electrical
transformers and capacitors for insulating purposes, and in
gas pipeline systems as a lubricant.
polycyclic aromatic hydrocarbons (PAHs): class of
organic compounds with a fused-ring aromatic structure.
PAHs result from incomplete combustion of organic carbon
(including wood), municipal solid waste, and fossil fuels, as
well as from natural or anthropogenic introduction of
uncombusted coal and oil. PAHs include benzo(a)pyrene,
fluoranthene, and pyrene.
Primary Contact Recreation (PCR): water recreation
activities requiring full human body immersion, such as
swimming, diving, water skiing, and surfing.
priority organics: prority pollutants that are organic
chemicals.
priority pollutants: 126 individual chemicals that EPA
routinely analyses when assessing contaminated surface
water, sediment, groundwater, or soil samples.
random utility model (RUM): a model of consumer
behavior. The model contains observable determinants of
consumer behavior and a random element.
Secondary Contact Recreation (SCR): water
recreation activities requiring some direct contact with water
but where swallowing of water is unlikely, such as paddling,
wading, and boating.
siltation: deposition of finely divided soil and rock
particles on the bottom of stream and river beds and in
reservoirs.
Survey of National Demand for Water-based
Recreation (NDS): a U.S. EPA survey of recreational
behavior. The 1993 survey collected data on socioeconomic
characteristics and water-based recreation behavior using a
nationwide stratified random sample of 13,059 individuals
aged 16 and over (http://www.epa.gov/opei).
total allowable catch (TAG): amount offish permitted to
be removed under a fishery management regime in which the
total catch allowed of a certain species for a fishing season
has been fixed in advance.
"toxic" pollutants: refers to the 126 priority or toxic
pollutants specifically defined as such by EPA, as well as
nonconventional pollutants that have a toxic effect on
human health or aquatic organisms.
turbidity: cloudy condition in water that interferes with the
passage of light through the water column. It is caused by
the presence of suspended silt or organic matter in the
waterbody.
unionized: neutral form of an ionizable compound. With
reference to ammonia, it is the neutral form of ammonia-
nitrogen in water, usually occurring as NH4OH. Unionized
ammonia is the principal form of ammonia that is toxic to
aquatic life. The relative proportion of unionized to ionized
ammonia (NH4+) is controlled by water temperature and pH.
Warmwater Habitat (WWH): a designation assigned to a
waterbody based on the potential aquatic assemblage.
water quality criteria (WQC): specific levels of water
quality that, if reached, are expected to render a body of
water suitable for certain designated uses.
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MP&M EEBA Part V: Ohio Case Study Chapter 20: Baseline Conditions in Ohio
withdrawal: water removed from the ground or diverted supply, irrigation, production and processing services, and
from a surface-water source for uses such as drinking water sanitary services.
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MP&M EEBA Part V: Ohio Case Study
Chapter 20: Baseline Conditions in Ohio
ACRONYMS
BCFs: bioconcentration factors
BOD: biological oxygen demand
COD: chemical oxygen demand
CWH: Coldwater Habitat
DO: dissolved oxygen
E&T: endangered and threatened
EWH: Exceptional Warmwater Habitat
LRW: Limited Resource Waters
LWH: Limited Warmwater Habitat
MWH: Modified Warmwater Habitat
ODH: Ohio Department of Health
DNR: Ohio Department of Natural Resources
LCI: Ohio EPA Lake Condition Index
OWRI: Ohio Water Resource Inventory
POCs: pollutants of concern
PCBs: polychlorinated biphenyls
PAHs: polycyclic aromatic hydrocarbons
PCR: Primary Contact Recreation
RUM: random utility model
SSH: Seasonal Salmonid Habitat
SCR: Secondary Contact Recreation
NDS: Survey of National Demand for Water-based
Recreation
TAG: total allowable catch
WWH: Warmwater Habitat
WQC: water quality criteria
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MP&M EEBA Part V: Ohio Case Study Chapter 20: Baseline Conditions in Ohio
REFERENCES
Department of Agriculture, National Resources Conservation Services, 1992 National Resources Inventory.
http://www.ftw.nrcs.usda.gov/nri_data.html.
Department of Commerce. 1992. Bureau of the Census. Census of Manufactures, Census of Transportation, Census of
Wholesale Trade, Census of Retail Trade, Census of Service Industries.
Department of Commerce, U.S. Census Bureau. 1999. Ohio Population, Demographic, and Housing Statistics.
http://www.census.gov/cgi-bin/datamap/state739.
Ohio Department of Natural Resources, Ohio Division of Wildlife. 1999. Fish Consumption Advisories.
http://www.dnr.state.oh.us/odnr/wildlife/index.html.
Ohio Department of Natural Resources, Division of Natural Areas and Preserves. 1998. Database File of Aquatic and
Associated Aquatic Endangered & Threatened Animals.
Ohio Environmental Protection Agency. 1998. State of the Lake Report (www.epa.ohio.gov/oleo/leqi/leqi.html)
Ohio Environmental Protection Agency. 1996. Ohio Water Resource Inventory. Volume 1: Summary, Status, and Trends
and 3: Ohio's Public Lakes, Ponds, and Reservoirs (chagrin.epa. state.oh.us/document index)
USDA (U.S. Department of Agriculture). 1992. Agricultural Waste Management Field Handbook. National Engineering
Handbook Series, Part 651. 210-AWMFH, 4/92.
United States Geological Survey (USGS). 1995. Water Use in the United States (http://water.usgs.gov/watuse).
U.S. EPA (U.S. Environmental Protection Agency). 1986. Ambient Water Quality Criteria for Dissolved Oxygen. EPA
440/5-86-003.
U.S. EPA (U.S. Environmental Protection Agency). 1992. Managing Nonpoint Source Pollution: Final Report to Congress.
EPA-506/9-90.
U.S. EPA (U.S. Environmental Protection Agency). 1998a. National Recommended Water Quality Criteria; Notice;
Republication. 63(237:68354-68364).
U.S. EPA (U.S. Environmental Protection Agency). 1998b. Condition of the Mid-Atlantic Estuaries. EPA 600-R-98-147.
U.S. EPA (U.S. Environmental Protection Agency). 1998c. 1988 Update of Ambient Water Quality Criteria for Ammonia.
EPA 822-R-98-008.
U.S. EPA (U.S. Environmental Protection Agency). 1999. Progress Report on the EPA Acid Rain Program. U.S. EPA
Office of Air and radiation. EPA 430-R-99-011.
Wetzel, R.G. 1983. Limnology, 2nd ed. Saunders College Publishing.
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Chapter 21: Modeling Recreational Benefits in Ohio with a RUM Model
Chapter 21: Modeling Recreational
Benefits in Ohio with a RUM
Model
INTRODUCTION
The recreational benefits analysis outlined in this chapter
focuses on Ohio as a case study of the MP&M regulation's
expected benefits. EPA combined water quality modeling
and a random utility model of consumer behavior
(RUM) to assess how changes in water quality from the
MP&M regulation will affect consumer valuation of water
resources for recreational uses. The RUM analysis provides
a framework for estimating the effect of ambient water
quality and other site characteristics on the total number of
trips taken for different water-based recreation activities and
the allocation of these trips among particular sites.
The Agency used this case study to address limitations
inherent in the benefits transfer method used in the analysis
of recreational benefits at the national level (see Chapter 15
for detail). The RUM model assesses water quality
characteristics directly affected by the MP&M regulation,
such as presence of ambient water quality criteria
(AWQC) exceedences and nonconventional nutrient Total
Kjeldahl Nitrogen (TKN) concentrations and their effect
on recreation behavior.
The direct link between the water quality measures included
in the RUM model and the water quality measures used in
developing the regulation reduces uncertainty in benefit
estimates. Two studies that use the same water quality
measures to analyze recreational benefits are more reliable
than other analyses that require additional assumptions to
transfer value from one study to the other.
Benefits transfer often requires additional assumptions
because water quality changes evaluated in available
recreation demand studies are only roughly comparable with
water quality measures considered in regulatory
development. This case study analysis improves upon
previous recreation demand studies that focused mainly on
directly observable water quality effects: e.g., designated use
support (i.e., whether a water body supports fishing), the
presence of fish advisories, an oil sheen, or eutrophication.
CHAPTER CONTENTS:
21.1
Methodology 21-2
21.1.1 Overview 21-2
21.1.2 Modeling the Site Choice Decision 21-3
21.1.3 Modeling Trip Participation 21-4
21.1.4 Calculating Welfare Changes from Water
Quality Improvements 21-7
21.1.5 Extrapolating Results to the State Level . 21-7
21.2 Data 21-8
21.2.1 The Ohio Data 21-8
21.2.2 Estimating the Price of Visits to Sites . 21-11
21.2.3 Site Characteristics 21-11
21.3 Site Choice Model Estimates 21-13
21.3.1 Fishing Model 21-14
21.3.2 Boating Model 21-14
21.3.3 Swimming Model 21-15
21.3.4 Viewing (Near-water Activity) Model . 21-15
21.4 Trip Participation Model 21-15
21.5 Estimating Benefits from Reduced MP&M
Discharges in Ohio 21-18
21.5.1 Benefiting Reaches in Ohio 21-18
21.5.2 Estimating Recreational Benefits
in Ohio 21-18
21.6 Limitations and Uncertainty 21-20
21.6.1 One-State Approach 21-20
21.6.2 Including One-Day Trips Only 21-20
21.6.3 Considering Only Recreational Values . 21-20
21.6.4 Potential Sources of Survey Bias 21-20
21.6.5 Using IWB2 to Predict Recreational
Behavior 21-21
Glossary 21-22
Acronyms 21-24
References 21-25
The Ohio case study includes unobservable water quality
effects as well. The MP&M regulation affects a broad range
of pollutants, many of which are toxic to human and aquatic
life but are not directly observable (i.e., priority and non-
conventional pollutants). These unobservable toxic
pollutants degrade aquatic habitats, decrease the size and
abundance offish and other aquatic species, increase fish
deformities, and change watershed species composition.
21-1
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MP&M EEBA Part V: Ohio Case Study
Chapter 21: Modeling Recreational Benefits in Ohio with a RUM Model
Water quality changes (i.e., changes in toxic pollutant
concentrations) affect consumers' water resource valuation
for recreation, even if consumers are unaware of changes in
ambient pollutant concentrations.
This study allows for a more complete estimate of
recreational benefits from reduced discharges of MP&M
pollutants. In addition to estimates of recreational benefits
from reduced frequency of AWQC exceedences, the Ohio
case study evaluated changes in the water resource values
from reduced discharges of TKN. The analysis also values
additional recreational uses affected by the regulation, such
as swimming.
The study used data from the National Demand Survey
for Water-Based Recreation (NDS). conducted by U.S.
EPA and the National Forest Service, to examine the effects
of in-stream pollutant concentrations on consumer decisions
to visit a particular waterbody (U.S. EPA, 1993).
21.1 METHO&oioey
21.1.1 Overview
The Ohio study combines direct simulation and inferential
analyses to assess how changes in water quality will affect
consumer valuation of water resources.
> The direct simulation analysis component estimates
baseline and post-compliance water quality at
recreation sites actually visited by the surveyed
consumers and all other sites within the
consumers' choice set, visited or not.
* The inferential analysis component, a RUM
analysis of consumer behavior, estimates the effect
of ambient water quality and other site
characteristics on the total number of trips taken for
different water-based recreation activities and the
allocation of these trips among particular
recreational sites. The RUM analysis is a TCM, in
which the cost to travel to a particular recreational
site represents the "price" of a visit.
EPA modeled two consumer decisions:
* how many water-based recreational trips to take
during the recreational season (the trip
participation model), and
> conditional on the first decision, which recreation
site to choose (the site choice model).
The econometric estimation proceeded in two steps; each
corresponding to the above decisions. The Agency
estimated these decisions in reverse order (i.e., EPA
modeled the second decision, site choice, first).
Modeling the Site Choice Decision. Assuming a
consumer decides to take a water-based recreation
trip, EPA estimated the likelihood that the
consumer will choose a particular site as a function
of site characteristics, the price paid per site visit,
and household income.
EPA estimated the RUM using a two-level nested
multinomial loqit (NMNL) procedure. Level one
was a choice among inland Ohio water sites (i.e.,
rivers, small lakes and reservoirs), Lake Erie sites
in Ohio, and sites outside Ohio; the second level
was the choice of the actual site within one of these
categories. EPA estimated the value to the
consumer of being able to choose among Ohio
inland recreation sites, Ohio Lake Erie recreation
sites, and sites outside Ohio on a given day using
the site-choice model coefficients. This measure is
referred to as the "inclusive value."
Modeling Trip Frequency. The NMNL model
estimated in the previous step treats the total
number of recreational trips taken each season as
exogenous to the site selection. The Agency
estimated the expected number of trips taken during
the recreation season using a Negative Binomial
Poisson model (Hausman et al., 1995; Feather et
al., 1995; and Creel and Loomis, 1992), which
treats trip frequency as a pre-season decision
regarding total participation.
EPA estimated the total number of trips during the
recreation season as a function of the expected
maximum utility (inclusive value) from recreational
activity participation on a trip, and socioeconomic
characteristics affecting demand for recreation trips
(e.g., number of children in the household). The
coefficient on the inclusive value (i.e., the
individual's expected maximum utility of taking a
trip) provided a means of estimating the seasonal
welfare effect of water quality improvements,
because changes in water quality change the value
of available recreation sites.
Estimating site choice and total trip participation models
jointly is theoretically possible, but computational
requirements make an integrated utility-theoretic model
infeasible. EPA estimated separate site choice and trip
frequency models for four recreational activities: boating,
swimming, fishing, and near-water recreation, (e.g., viewing
wildlife).
The Agency used estimated coefficients of the indirect
utility function with estimated changes in water quality to
calculate per-trip changes in consumer welfare from
21-2
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MP&M EEBA Part V: Ohio Case Study
Chapter 21: Modeling Recreational Benefits in Ohio with a RUM Model
improved water quality at recreation sites within each
consumer choice set. Trip frequency per season
increases if site water quality changes are substantial. A
sample consumer's expected seasonal welfare gain is
therefore a function of both welfare gain per trip and the
estimated change in number of trips per season.
Combining the trip frequency model's prediction of trips
under the baseline and post-compliance and the site choice
model's corresponding per-trip welfare measure yields the
total seasonal welfare measure.
EPA calculated each individual's seasonal welfare gain for
each recreation activity from post-compliance water quality
changes, then used Census data to aggregate the estimated
welfare change to the state level. The sum of estimated
welfare changes over the four recreation activities yielded
estimates of total welfare gain.
To analyze water quality improvement benefits in the RUM
framework, EPA used available discharge, ambient
concentration, and other relevant data to show baseline and
post-compliance water quality at the impact sites. Appendix
G provides detail on water quality modeling used in this
analysis.
21.1.2 Modeling the Site Choice
Decision
EPA used the RUM framework to estimate the probability of
a consumer visiting a recreation site. This framework is
based on the assumption that a consumer derives utility from
the recreational activity at each recreation site. Each visit
decision involves choosing one site and excluding others.
The consumer's decision involves comparing each site and
choosing the site that produces the maximum utility. An
observer cannot measure all potential determinants of
consumer utility, so the indirect utility function will have a
non-random element (V) and a random error term (ฃ), such
that the actual determinants of consumer utility V = V +
E,. The probability (iijn) that site j will be visited by an
individual n is defined as:
jn
v >V
jn sn
(21.1)
where:
ฃjn= utility of visiting site j, and
^sn= utility of visiting a substitute site.
Estimating the model requires specifying the functional form
of the indirect utility function, V, in which site choice is
modeled as a function of site characteristics and the "price"
to visit particular sites. For example, a set of conditional
utility functions (one for each site alternative j in the choice
set) can be determined as follows:
(21.2)
where:
Vjn = the utility realized from a conventional budget-
constrained, utility maximization model
conditional on choice of site j by consumer n;
PM = marginal utility of income;
Mjn = the income of individual n available to visit site
j;
Pjn = a composite measure of travel and time costs
for consumer n on site alternative y;
a = a vector of coefficients representing the
marginal utility of a specified site characteristic
to be estimated along with PM (e.g., size of the
waterbody, presence of boating ramps); and
Xjn = a vector of site characteristics for site
alternative j as perceived by consumer n.
These characteristics include the actual
monitored and/or modeled water quality
parameters that are hypothesized to be
determinants of consumer valuation of water-
based recreation resources, and that may also
be affected by the MP&M regulation.
The magnitude of the coefficients in Equation 21.2 reflects
the relative importance of site characteristics when
consumers decide which site to visit. The coefficients (P) of
water quality characteristics of recreation sites are expected
to be positive; that is, all else being equal, consumers of
water-based recreation would prefer "cleaner" recreation
sites. The coefficient on travel cost is expected to be
negative, i.e., consumers prefer lower travel costs.
To estimate the site choice probabilities, EPA specified and
estimated a nested multinomial logit model (NMNL). The
nested structure explicitly groups similar alternatives, which
allows for a richer pattern of substitution among alternative
sites. The NMNL is based on the assumption that an
individual chooses first between groups of alternatives and
then, within the chosen group, between individual
alternatives. For this analysis, EPA grouped all recreational
sites by location based on site similarities. The model uses
three site groups:1
1 Three of the four models (fishing, boating, and viewing)
passed specification tests for appropriateness of the nested structure
that includes all three site groups (see Section 21.3 for detail). Test
results showed that only two site groups are appropriate for the
21-3
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MP&M EEBA Part V: Ohio Case Study
Chapter 21: Modeling Recreational Benefits in Ohio with a RUM Model
> inland sites in Ohio (i.e., rivers and lakes),
* Lake Erie sites, and
* out-of-state sites.
Lake Erie is a unique water resource that offers a large
variety of recreation opportunities. This analysis therefore
assumed that Lake Erie recreation sites are likely to be more
similar to each other than to inland sites in Ohio. The
Agency also assumed that sites outside of Ohio offer
recreational alternatives that may be different from those
found in Ohio.
The model assumes that an individual first decides to visit
inland waterbodies, Lake Erie, or sites outside of Ohio, then
decides which site within each group to visit. An individual
probability of visiting site j, given the choice of region,/?, is
a simple multinomial logit. If the random terms ฃnj for
individual n at site j are independently and identically
distributed and have an extreme value Weilbull distribution,
then ii jn takes the form (McFadden, 1981):
(21.3)
JEr
where:
Jr
I
-
the consumer's utility from visiting site j;
regions - "Great Lakes," "inland," or "out-of-
state;" and
the sum of the consumer's utility at each site j
for all sites in the opportunity set for region R.
Estimated parameters of the indirect utility function are then
used to estimate the inclusive value. For consumer n, the
inclusive value measures the overall quality of recreational
opportunities for each water-based activity and represents
the expected maximum utility of taking a trip. Note that
although EPA used a random draw from the opportunity set
for the purpose of estimating the model parameters, the
Agency calculated the inclusive value (i.e., the expected
maximum utility) using all recreation sites in the consumer's
opportunity set in a given region.
The inclusive value is calculated as the log of the
denominator in Equation 21.2 (McFadden, 1981).
j
I =\n(5^ eVi"(W)) (21.4)
where:
Ir = inclusive value for sites associated with
region,/?;
e Jn
individual w's utility from visiting site j;
and
W = a vector of baseline water quality
characteristics.
The probability of choosing a particular region is:
e rYr
r=R
r=\
(21.5)
where:
r =
the inclusive values for a given region; and
"Lake Erie," "inland," and "out-of-state."
To estimate the model described by equations 21.2 and 21.5,
EPA used a standard statistical software package, LIMDEP.
21.1.3 Modeling Trip Participation
After modeling the site choice decision, the next step
modeled the determinants of the number of water-based
recreation trips a consumer takes during a season. To link
the quality of available recreation sites with consumer
demand for recreation trips, EPA modeled the number of
recreation trips taken during the recreation season as a
function of the inclusive value estimated in the previous step
and socioeconomic characteristics affecting demand for
recreation activities. The dependent variable, the number of
recreation trips taken by an individual during the recreation
season, is an integer value greater than or equal to zero. To
account for the non-negative property of the dependent
variable, EPA used count data models based on probability
densities that have the non-negative integers as their domain.
One of the simplest count data models is a Poisson
estimation process, which is commonly used with count
data, such as number of recreation trips during the recreation
season. Inherent in the model specification is the
assumption that each observation of a number of trips is
drawn from a Poisson distribution. Such a distribution
favors a large number of observations with small values
(e.g., two trips, four trips) or zeros, resulting in its being
skewed toward the lower end. Due to the nature of the
observed number of trips, it is quite reasonable to assume
that the underlying distribution can be characterized as a
Poisson distribution. Figure 21.1 shows the number of
recreation trips taken per year and the number of
respondents who reported taking that number of trips.
swimming model Ohio sites, including inland lakes and Lake
Erie, and out-of-state sites.
21-4
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MP&M EEBA Part V: Ohio Case Study
Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
Figure 21.1: Number of Trips Per Year By Activity Type
Number of Trips Per Year: Fishing
Number of Trips Per Year: Swimming
2 I 4 I 6 I 8 10 I 12 I 14 I 16 I 18 I 20 I 22 I 24 I 26 I 28 I 30 I 32 I 34 I 36 I 38 I 40 I 42 I 44
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45
>
?
=e
I
o:
ฃ
20
18
16
14
12
10
2 I 4 I 6 I 8 10 I 12 I 14 I 16 I 18 I 20 I 22 I 24 I 26 I 28 I 30 I 32 I 34 I 36 I 38 I 40 I 42 I 44
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45
Number of Trips
Number of Trips
Number of Trips Per Year: Viewing
Number of Trips Per Year: Boating
I I 20 I 22 I 24 I 26 I 28 I 30 I 32 I 34 I 36 I 38 I 40 N
2 I 4 I 6 I 8 10 I 12 I 14 I 16 I 18 I 20 I 22 I 24 I 26 I 28 I 30 I 32 I 34 I 36 I 38 I 40 I 42 I 44
3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45
Number of Trips
60
55
50
45
40
35
30
25
20
15
10
2 I 4 I 6 I 8 10 I 12 I 14 I 16 I 18 I 20 I 22 I 24 I 26 I 28 I 30 I 32 I 34 I 36 I 38 I 40 I 42 I 44
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45
Number of Trips
Source: U.S. EPA analysis.
21-5
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MP&M EEBA Part V: Ohio Case Study
Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
Estimating the Poisson model is similar to estimating a
nonlinear regression. The single parameter of the Poisson
distribution is A, which is both the mean and variance of yn.
The probability that the actual number of trips taken is equal
to the estimated number of trips is estimated as follows
(Green, 1993):
the Poisson regression model, which allows the variance of
the number of trips to differ from the mean. In the negative
binomial model, A is respecified so that (Green, 1993):
In
(21.8)
Prob(Y=y}=-
(21.6)
where:
Yn = the actual number of trips taken by an
individual in the sample;
yn = the estimated number of trips taken by an
individual in the sample;
n = 1, 2,..., N, the number of individuals in the
sample; and
An = P 'X, expected number of trips for an
individual in the sample, where X is a vector of
variables affecting the demand for recreational
trips (e.g., inclusive value and socioeconomic
characteristics) and b is the vector of estimated
coefficients.
From Equation 21.6, the expected number of trips per
recreation activity season is given by:
(21.7)
where the error term (e) has a gamma distribution,
E[exp(j)] is equal to 1.0, and the variance of e is a.
The resulting probability distribution is:
Prob[Y=yn\e]= (21.9)
where:
Yn
0,1,2... number of trips taken by individual n in
the sample;
1,2,..., N number of individuals in the sample;
and
expected number of trips for an individual in
the sample.
Integrating a from Equation 21.9 produces the unconditional
distribution of yn. The negative binomial model has an
additional parameter, a, which is the overdispersion
parameter, such that:
Var\yn]=E\yn](l+aE\yn])
(21.10)
where:
E[ynxJ
the expected number of trips, yn, given
Var[yn|xJ = the variance of the number of trips, yn,
given x,,;
P = a vector of coefficients on x; and
x = a matrix of socioeconomic variables
and inclusive values.
An empirical drawback of the Poisson model is that the
variance of the number of trips taken must be equal to the
mean number of trips, and this equality is not always
supported by actual data. In particular, the NDS survey data
exhibit overdispersion, a condition where variance
exceeds the mean. The estimated variance to mean ratios of
the number of trips in the NDS data sample are 31, 27.9,
35.6, and 10.5 for fishing, swimming, viewing, and boating
trips, respectively. Overdispersion is therefore present in the
data set.
To address the problem of overdispersion, EPA used the
negative binomial regression model, an extension of
The overdispersion rate is then given by the following
equation:
(21.11)
EPA used the negative binomial model to predict the
seasonal number of recreation trips for each recreation
activity based on the inclusive value, individual
socioeconomic characteristics, and the overdispersion
parameter, . If the inclusive value has the anticipated
positive sign, then increases in the inclusive value stemming
from improved ambient water quality at recreation sites will
lead to an increase in the number of trips. The combined
MNL model site choice and count data trip participation
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MP&M EEBA Part V: Ohio Case Study
Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
models allowed the Agency to account for changes in per-
trip welfare values, and for increased trip participation in
response to improved ambient water quality at recreation
sites.
21.1 A Calculating Welfare Changes
from Water Quality Improvements
EPA estimated the welfare change associated with water
quality improvements from the baseline to post-compliance
conditions as a compensating variation (CV). that
equates the expected value of realized utility under the
baseline and post-compliance conditions. The expected
seasonal change in welfare attributed to the quality
improvements for an individual n in the sample consists of
two components:
* per trip welfare gain, and
> increased number of trips under the post-
compliance water quality condition.
The Agency first calculated the welfare gain from water
quality improvement for each consumer on a given day by
using a CV measure for consumer n (Kling and Thompson,
1996):
CV =
In
R Jr
ฃ(ฃ^Vj'"(W/))
r= 1 j= 1
-In
ซ ', ,
E/V^ V- (W ).
(L e J )
r= 1 j= 1
(21.12)
JM
where:
Cvn
R
In
W ฐ
W1
PM
the compensating variation for individual
n at site j on a given day;
"Lake Erie," "inland," and "out-of-state;"
l,...Jr represents a set of alternative sites
for a given recreational activity in region
the inclusive value index (I);
a vector of information describing baseline
water quality;
a vector of information describing post-
compliance water quality; and
the implicit coefficient on income that
influences recreation behavior.
In deriving Equation 21.12, EPA assumed that the marginal
utility of income, P M, is constant across alternatives (as well
as across quality changes). If this assumption does not
apply, the derivation of Eq. 21.12 is more complicated
(Hausmanetal., 1995).
EPA then estimated the low and high values of the seasonal
welfare gain for individual n in the sample as follows:2
W,
low, n
w,,
(71 - 7ฐ) x Fฐ
" ^
= (71 - 7ฐ) x F1
= IS
(21.13)
(21.14)
where:
Wlo
ww
I1
Y1
1ฐ
Yฐ
PM
lower bound estimate of the seasonal
welfare gain for individual n;
upper bound estimate of the seasonal
welfare gain for individual n;
the post-policy inclusive value;
the estimated number of trips after water
quality improvement;
the baseline inclusive value;
the estimated number of trips in the
baseline; and
the implicit coefficient on income that
influences recreation behavior.
These estimates are per individual in the population for
those individuals meeting qualifications for inclusion in the
NDS response set (i.e., respondents whose home state is
Ohio and respondents from the neighboring states whose
last trip was to Ohio's sites).3 EPA extrapolated the
estimates of value per individual to the Ohio state level
based on Census data (U.S. Bureau of the Census, 1999).
The following section details the extrapolation method used
in the analysis.
21.1.5 Extrapolating Results to the
State Level
EPA used a simplified extrapolation technique to estimate
the state-level benefits. EPA first estimated the number of
participants in fishing, swimming, boating, and wildlife
viewing in Ohio, based on the estimated percentage of the
NDS survey respondents residing in Ohio who participate in
2 EPA selected this approach for calculating seasonal welfare
gain per individual based on Dr. Parsons' recommendation (G.R.
Parsons, 1999).
3 Section 21.2.1 provides a detailed description of the data
sample used in the analysis.
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Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
a given activity and the state adult population. The 1990
Census data provides information on the number of Ohio
residents aged 16 and older. EPA then multiplied the
estimated average seasonal welfare gain per participant in a
given recreational activity by the corresponding number of
recreational users. The total welfare gain to the users of
water-based recreation in Ohio is the sum of fishing,
swimming, boating, and wildlife viewing benefits.
21.2
This section describes the data and supporting analyses
required to implement the RUM analysis. The following
general categories of data and supporting analyses are
required:
* information on the consumers of water-based
recreation responding to the NDS in Ohio;
> recreation sites identified for the water quality and
RUM analyses, including the sites visited by
consumers of water-based recreational activity and
supplemental sites in their choice sets;
* estimated price of visiting the sites. The "visit
price" is estimated as a function of travel distance
(and travel time) between each consumer's
hometown and each site in the choice set;
* information on site characteristics likely to be
important determinants of consumer behavior. Of
particular importance to this analysis are the water
quality and related characteristics of sites in the
choice set, and how those characteristics may be
expected to change as a result of regulation.
The following sections discuss each category of data and/or
supporting analysis below.
21.2.1 The Ohio Data
EPA obtained information on survey respondent
socioeconomic characteristics and recreation behavior from
the NDS (U.S. EPA, 1993). The 1993 survey collected data
on demographic characteristics and water-based recreation
behavior using a nationwide stratified random sample of
13,059 individuals aged 16 and over. Respondents reported
on water-based recreation trips taken within the past 12
months, including the primary purpose of their trips (e.g.,
fishing, boating, swimming, and viewing), total number of
trips, trip length, distance to the recreation site(s), and
number of participants. Where fishing was the primary
purpose of a trip, respondents were also asked to state the
number of fish caught. Table 21.1 shows the number of
trips taken per year by primary recreation activity, as
reported in the NDS.
EPA selected case study observations for Ohio residents
who took trips within or outside of that state. Trips to Ohio
recreation sites by residents of neighboring states were also
included in the site choice models, but not in the trip
participation models4. All four activity models included
single-day trips only. EPA included only activity
participants with valid hometown ZIP codes, whose
destination site was uniquely identified. The Agency used
data on both Ohio participants and Ohio non-participants to
estimate total seasonal trips, but included only Ohio
participants and several residents of nearby states in the site
choice models. Unusable site choice participant
observations from Ohio with missing location information
were used to analyze the number of trips. Tables 21.1 and
21.2 list valid observations by activity, residence, and model
type. Figure 21.2 illustrates the distribution of the sample
observations in relation to the location of MP&M facilities
in Ohio.
4 These additional observations total 10 across the four
activities and represent only a small fraction of total observations.
Including only Ohio respondents in the trip participation models
underestimates the benefits associated with water quality
improvements, because the welfare gains to recreators from
neighboring states are ignored.
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MP&M EEBA Part V: Ohio Case Study
Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
Table 21.1: Classification of Sample Observations for Estimation of the Site Choice Models
Participants (Total)
Fishing
Swimming
Viewing
Boating
Total Ohio
Residents
609
122
147
231
109
Ohio
Residents
with Last
Trip In-State
408
103
100
126
79
Valid Ohio
Residents
with Last
Trip In-State
227
69
53
56
49
Valid Ohio
Residents
with Last
Trip Outside
State
34
4
9
7
14
Valid Non-
Residents
with Last
Trip in Ohio
10
1
2
5
2
Valid for
Site Choice
Model
271
74
64
68
65
Source: U.S. EPA analysis.
Table 21.2: Classification of Sample Observations for Estimation of the Trip Participation Models
Ohio Residents
Non-Participants
Participants (Total)
Fishing
Swimming
Viewing
Boating
Total Observations
Total
300
609
909
122
147
231
109
Residents with Last
Trip In-State
408
408
103
100
126
79
Residents with Last
Trip Outside State
34
34
4
9
7
14
Valid for Trip
Participation
Model
291
322
613
84
78
75
85
Source: U.S. EPA analysis.
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Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
Figure 21.2: Location of MP&M Facilities in Relation to the Origin of Recreational Trips
Location of MP&M Facilities in Relation
to the Origin of Recreational Trips
Origin of:
Viewing Trips >* Fishing Trips
Swimming Trips J& Boating Trips
Ohio MP&M
Facilities
Rf 1 Reach
Source: U.S. EPA analysis.
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Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
21.2.2 Estimating the Price of Visits to
Sites
The Agency estimated trip "price" as the sum of travel costs
plus the opportunity cost of time. Based on Parsons and
Kealy (1992), EPA assumed that time spent "on-site" is
constant across sites and can be ignored in the price
calculation. To estimate travel cost, the Agency multiplied
round-trip distance by average motor vehicle cost per mile
($0.29, 1993 dollars), and by the respondent family's share
of total recreation party size, to estimate consumer travel
cost.5'6 EPA used trip time and hourly wage to compute the
consumer's opportunity cost of time. The Agency divided
round-trip distance by 40 miles per hour to estimate trip
time, and used one-half the average hourly income to yield
the opportunity cost of time.7 Visit price was thus calculated
as:
Visit Price = Round Trip Distance
x $.29 x %Paid
Round Trip Distance
40mph xQ.5 x Hourly Income
(21.16)
21.2.3 Site Characteristics
EPA identified 1,954 recreation sites on 1,631 reaches in the
universal opportunity set. Of these, 580 observations are
known recreational sites (e.g. parks); 1,366 observations are
Reach File 1 (RF1) reaches without a known recreational
site, and eight observations are neither located in RF1 nor
identified as known recreation sites but were visited by an
NDS respondent.
Each consumer choice set theoretically includes hundreds of
substitutable recreation sites in Ohio and in the neighboring
states. To prevent the recreation site analysis from
becoming unmanageable, EPA analyzed a sample of
recreation sites for each consumer observation. The Agency
then created randomly-chosen reduced choice sets consisting
often Lake Erie sites, ten inland recreation sites, and a
dummy variable representing sites outside of Ohio for each
participant in the three nested models.8 The choice set for
the fourth model, swimming, consisted of 20 Ohio sites
(including inland and Lake Erie) and a dummy variable
representing sites outside Ohio. Each participant choice set,
by definition, includes the site actually visited by the
respondent. For each consumer, EPA drew additional sites
from a geographic area defined by a travel time constraint.
The Agency defined the limit for inland recreation sites and
all sites chosen in the swimming model as the greater of:
> 120 miles, or
> the estimated travel distance to the visited site.
All Lake Erie sites are eligible for inclusion in the choice
sets for the fishing, boating, and wildlife viewing models.
EPA assumed that consumers of water-based recreation
would be willing to travel farther to visit Lake Erie sites,
because this water resource presents unique recreational
opportunities.9 EPA used the resulting aggregate choice set
of sites for all individuals participating in a given recreation
activity to model consumer decisions regarding trip
allocation across recreation sites.
The Agency used two classes of characteristics to estimate
site choice:
* those unaffected by the MP&M regulation, but
likely to determine valuation of water-based
recreational resources; and
* those affected by the regulation and hypothesized
to be significant in explaining recreation behavior
and resource valuation.
Regulation-independent site characteristics include
waterbody type and size, location characteristics, and the
presence of site amenities (e.g., boat ramps, swimming
beaches, picnic areas). Regulation-dependent site
characteristics include regulation-affected water quality
variables.
5 Note that all expenditures are in 1993 dollars because the
trip choices and the associated expenditure occurred in 1993.
6 The estimate of motor vehicle cost per mile was based on
estimates compiled by the Insurance Information Institute.
7 For respondents who did not report household income, EPA
estimated household income using a simple OLS regression that
modeled income as a function of employment status, years of
schooling, age, gender, number of adults in the household, and a
dummy variable indicating whether the respondent participated in
water-based recreation activities.
a. Regulation-independent site
characteristics
Site characteristics that are likely to be important
determinants of consumer valuation of water-based
recreational resources but that are independent of the
MP&M regulation include general site descriptors. These
8 McFadden (1981) has shown that estimating a model using
random draws can give unbiased estimates of the model with the
full set of alternatives.
9 Travel distance from respondents hometown to the Lake
Erie sites did not exceed 200 miles.
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descriptors include the type and size of the waterbody and
location characteristics, and the presence of site amenities.
EPA obtained data on regulation-independent site
characteristics from two main sources, RF1 and the Ohio
Department of Natural Resources (ODNR).
RF1 provided waterbody type (i.e., lake, river, or reservoir)
and physical dimension (i.e., length, width, and depth). The
dummy variable, RIVER, characterizes waterbody type. If
a river waterbody, RIVER takes the value of 1; 0 otherwise.
EPA used the logarithm of the waterbody area LN_ACRE to
define waterbody size.10 EPA multiplied reach width by
segment length to yield waterbody area. Waterbody size
data for sites not located in RF1 came from the ODNR.
ODNR, supplemented by the Ohio Atlas and Gazetteer,
provided data on recreational amenities and site setting (e.g.,
presence/absence of boat ramps, swimming beaches, or
picnic areas; public accessibility; and size of land available
for recreation). EPA used land available for recreation,
LN_LNDAC, (e.g., state park acreage, fishing, hunting, and
other recreation areas) to approximate site setting and
attractiveness. Dummy variables represent the presence of
three recreational amenities: BEACH is a swimming beach;
DOCK is a boating dock; and PARK indicates a park. In the
case of the swimming model, EPA included a dummy
variable for whether or not a site is on Lake Erie (Great
Lake = 1) because no explicit nest is present in the model.
b. Regulation-dependent site characteristics
Selecting regulation-dependent site characteristic variables
that are both policy-relevant and significant in explaining
recreation behavior proved challenging. MP&M facilities
discharge many pollutants, most of them unlikely to have
visible indicators of degraded water quality (e.g., odor,
reduced turbidity, etc). EPA hypothesized that pollutant
loadings can, nonetheless, reduce the likelihood of selecting
a recreation site. Reduced pollutant discharges improve
water quality and aquatic habitat, thereby increasing fish
populations and enhancing the recreational fishing
experience. In addition, in-stream nutrient concentrations
are good predictors of eutrophication, which causes
aesthetic losses and may thus affect the utility of a water
resource for all four recreational uses.
The connection between the policy variables (i.e., the
change in concentrations of MP&M pollutants) and the
effects perceived by consumers (e.g., increased catch rate,
increased size of fish, greater diversity of species, or
improved aesthetic qualities of the waterbody) are not
modeled directly, but are captured implicitly in the
differential valuation of water resources as reflected in the
RUM analyses.
EPA considered two types of pollutant effects in defining
water quality variables for model inclusion:
* visible or otherwise directly observable effects
(e.g., TKN); and
* unobservable toxic effects likely to impact aquatic
habitat and species adversely.
The Agency accounted for directly observable effects using
the ambient concentrations of nutrients (e.g., TKN) as an
explanatory variable.
Rather than include the concentrations of all toxic pollutants
separately, EPA constructed a variable to reflect the adverse
impact potential of toxic pollutants on aquatic habitat. EPA
identified recreation sites at which estimated concentrations
of one or more MP&M pollutants exceed AWQC limits for
aquatic life protection, to assess the likely adverse impacts
on aquatic organisms. A dummy variable, AWQC_EX,
takes the value of 1 if in-stream concentrations of at least
one MP&M pollutant exceed AWQC limits for aquatic life
protection, 0 otherwise. This approach accounts for the fact
that adverse effects on aquatic habitat are not likely to occur
below a certain threshold level.
c. Biological factors
Numerous biological parameters (e.g., abundance of sport
fish) that are a function of the availability and quality of
suitable habitat for breeding and feeding are also likely to
affect recreation behavior. To account for biological
parameters affecting the demand for water-based recreation,
EPA used the index of well being (IWB2) obtained from
the Ohio Water Resource Inventory (OWRI) database
(OH EPA, 1996). The index is defined as follows:
(21.17)
relative number of all species (i.e., number
offish per unit distance);
relative weight of all species (i.e., weight
of all species per unit distance);
Shannon diversity index based on relative
numbers of species (i.e., number of all fish
species per unit distance); and
Shannon diversity index based on relative
weight of all fish species in the sample.
where:
N
B =
H(no) =
H(wt) =
10 EPA uses the logarithm of acres because it expects effect of
waterbody size on utility to diminish as that size increases.
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The Shannon diversity index, H , is defined as follows:
a- -
N
N
(21.18)
where:
N
relative numbers or weight of the rth
species, and
total number or weight in the sample.
Chemical properties of the waters (e.g., pollutant
concentrations) are likely to affect the diversity and
abundance of the fishery resources. Biological parameters
may also be affected by numerous anthropogenic stressors
unrelated to water quality, such as over-fishing, physical
alteration of habitat, invasion of exotic species, etc.
Although EPA used the baseline values of IWB2 to estimate
the site choice models, the Agency did not estimate changes
in biological parameters in the following analysis due to data
limitations and the challenges posed by modeling population
impacts of abroad spectrum of pollutants at hundreds of
recreation sites.
d. Presence of fish advisories
Another important factor that may affect a recreational
consumer's decision to visit a particular site is presence of
fish consumption or contact advisories (FCAs).
EPA obtained information on fish consumption advisories
and contact advisories at reaches in Ohio from the ODNR
(Ohio DNR, 1999). Fish consumption advisories and
contact advisories were listed by the name of the stream or
river with the consumption advisory. An advisory that
applied to only part of the river included the names of cities,
towns, or highways to identify the stretch of the reach for
which the advisory was relevant. The name of the river and
the other geographic identifiers were used to assign reach
numbers from RF1 to the consumption advisories. EPA
created a dummy variable for each type of advisory (i.e., fish
advisories and contact advisories). The variable takes the
value of 1 if the relevant advisories are present; 0 otherwise.
21.3 SITE CHOICE MODEL ESTIMATES
EPA estimated four separate models of recreational demand:
fishing, boating, swimming, and viewing. The Agency
classified trips by the primary activity listed by the
respondent. All four activity models cover single-day trips.
EPA estimated the site choice model using the site actually
visited, 19 randomly drawn sites from the choice set for each
recreation activity, and an alternative constant representing
sites outside of Ohio.
EPA estimated activity models for five alternative choice
sets (i.e., five random draws from the universal choice set),
producing five sets of estimated coefficients. Median
estimates from the five alternative draws represent EPA's
best estimate of actual coefficient values. Table 21.3 lists
the variables used as arguments in the utility function and
presents the median estimation results for the four models.
The following sections provide a short description of the
results of the site choice model corresponding to each
recreation activity.
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Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
Table 21.3: Site Choice Model Estimation Results
(Median parameter estimates from five random draws) ฐ
Variable
Price"
Ln Lndac c
Ln_Acred
Dock6
Beachf
Park8
AWQC_Exh
IWB21
TKN
River1
ASC1
Great Lake m
IV on Great Lakes
IV on Inland Sites
I Von ASC (Fixed)
Fishing
-0.08 (-18.83)
0.26 (8.24)
0.54 (9.25)
1.42 (7.43)
N/A
N/A
-0.97 (-4.48)
0.12 (2.79)
-0.34 (-1.58)
1.69 (3.4)
3.51 (3.04)
N/A
0.76 (6.95)
0.65 (6.33)
1.00
Boating
-0.11 (-17.7)
0.22 (3.88)
0.99 (8.01)
N/A
N/A
N/A
-1.51 (-6.31)
-0.25 (-3.8)
-1.49 (-6.87)
6.81 (6.42)
0.19 (0.28)
N/A
0.33 (6.91)
0.25 (4.75)
1.00
Swimming
-0.08 (-13.85)
0.05 (1.89)
-0.11 (-2.63)
N/A
0.93 (4.34)
2.82 (8.1)
-0.39 (-1.93)
N/A
-0.01 (-0.04)
-2.21 (-9.63)
-1.45 (-4.72)
2.22 (5.17)
N/A
N/A
1.00
Viewing
-0.12 (-22.19)
0.24 (6.39)
0.70 (9.38)
N/A
N/A
0.36 (1.22)
-1.05 (-4.73)
0.12 (2.97)
-0.84 (-4.47)
0.17 (0.33)
-1.06 (-2.77)
N/A
0.24 (9.52)
0.30 (9.12)
1.00
a. EPA performed this analysis based on five alternative draws to assess sensitivity of the estimated coefficients with respect to random draws.
Swimming model median estimates are from seven random draws. Extra draws were required to ensure stability of model estimates.
b. Price is calculated as 0.5 x opportunity cost + travel cost.
c. Log of the number of land acres.
d. Log of the number of water acres.
e. 1 if a boating dock is present, and 0 otherwise.
f. 1 if a swimming beach is present, and 0 otherwise.
g. 1 if the site is a park, and 0 otherwise.
h. 1 for any reach if in-stream concentrations of at least one MP&M pollutant exceed the AWQC limits for protection of aquatic life, and 0
otherwise.
i . Index of well being representing biological factors, such as species abundance and diversity.
j. In-stream concentrations of TKN (mg/1).
k. 1 if the site is a river, and 0 otherwise (e.g., lake or reservoir).
1. 1 if visited a site outside of Ohio, and 0 otherwise.
m. 1 if the site is on Lake Erie, and 0 otherwise.
Note: L-statistic for test that coefficient equals 0 is given in parentheses beside coefficient estimates.
N/A indicates that the variable was not included in the estimation for this activity.
Source: U.S. EPA analysis.
21.3.1 Fishing Model
The most significant variables in determining fishing site
choice are price, presence of boating docks, waterbody size
(log of water acres), whether the site is a river, the IWB2,
exceedences of AWQC limits, and land available for
recreation (Ln_Lndac). All coefficients have the expected
sign and are significantly different from zero at the 95th
percentile. The estimated coefficient on TKN has the
expected sign but is significant only at the 90th percentile.
Estimated inclusive values on Lake Erie sites and inland
sites are positive and significantly different from 1 at the
95th percentile, indicating that the nested choice structure is
appropriate.11
11 Inclusive values equal to 1 cause the model to collapse to a
flat multinomial logit.
EPA found other variables, tested as explanatory variables,
to be insignificant, including the presence of FCAs. It might
be expected, a priori, that the presence of an FCA decreases
a site's likelihood as a fishing choice. In fact, the existence
of FCAs did not significantly affect a site's probability of
being chosen; 59 percent of the sites actually chosen by
NDS respondents had an FCA in place. Creel surveys
provided by ODNR indicated that, on average, anglers
released 70 percent of their catch (ODNR, 1997). This
finding suggests that recreational anglers are aware of
FCAs, and catch but do not consume fish in the affected
areas.
21.3.2 Boating Model
Boaters prefer to visit cheaper, cleaner, larger river sites. Of
the variables representing site amenities and attractiveness,
only the acres of land available for recreation is significant.
All coefficients on water quality variables are significantly
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Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
different from zero at the 95th percentile. The IWB2
coefficient has a negative sign. As with the fishing model,
the estimated inclusive values for Lake Erie sites and inland
recreation sites are significantly different from 1 at the 95th
percentile supporting the nested model framework. This
finding is likely to be due to colinearity between the AWQC
and the IWB2 variables. Colinearity between these two
variables did not present a problem in the fishing and
viewing models. The boating model restricts the opportunity
set to the site where boating is allowed. This additional
restriction may have exacerbated the colinearity problem.
21.3.3 Swimming Model
Price, the presence of a park with a beach, and location on
Lake Erie affect the probability of a particular site being
chosen for swimming. Swimmers are less likely to visit
large sites, sites located on a river, sites with AWQC
exceedences, and sites with relatively high in-stream
concentrations of TKN.
Again, some variables expected to be significant, such the
presence of contact advisories, are not. This variable's
insignificance probably stems from its scarcity. Of 1,954
sites included in the universal opportunity set, contact
advisories are in place for only 13. (None of the sites
actually visited had contact advisories in place.) The
probability that a chosen site has contact advisories in place
is very small, because individual choice sets are randomly
selected. The IWB2 variable representing biological
characteristics of a waterbody did not have a significant
influence on consumer decisions to visit a particular site and
was dropped from the model. This outcome is not
surprising, since abundant aquatic life may, in fact, interfere
with swimming activities. All coefficients have the expected
signs and are significantly different from zero with the
exception of the coefficient on TKN.
21.3.4 Viewing (Near-water Activity)
Model
The probability of choosing a site for near-water activities is
most significantly related to visit price, waterbody and land
size, whether the site is on a river, IWB2, the presence of
AWQC exceedences, and in-stream concentrations of TKN.
All coefficients have the correct sign and, with the exception
of the coefficient on the RIVER variable, are significantly
different from zero.
Estimated inclusive values for Lake Erie sites and inland
sites are significantly different from 1, supporting the nested
model structure.
21.4 TRIP PARTICIPATION MODEL
EPA estimated the determinants of individual choice
concerning how many trips to take during a recreation
season with a separate model for each of the four activities.
These participation models rely on socioeconomic data, and
on estimates of individual utility (the inclusive value)
derived from the site choice models. Variables of
importance include age, ethnicity, gender, education, and the
presence of young or older children in the household.
Whether or not the individual owns a boat is particularly
important in boating participation, and is included in the
model for that activity only. Variable definitions for trip
participation model are:
* IVBASE: the inclusive value is estimated using the
coefficients obtained from the site choice models;
* #TRIPS: number of trips taken by the individual;
* AGE: individual's age. If the individual did not
report age, their age is set to the sample mean;
* MALE: equals 1 if the individual is a male, 0
otherwise;
* NOHS: equals 1 if the individual did not complete
high school, 0 otherwise;
* COLLEGE: equals 1 if the individual completed
college, 0 otherwise;
> AFAM: equals 1 if the individual is African
American, 0 otherwise;
* YNGKIDS: equals 1 if there are kids 6 years or
younger, 0 otherwise;
* OLDKIDS: equals 1 if there are kids 7 years or
older, 0 otherwise;
* OWNBT: equals 1 if individual owns a boat, 0
otherwise;
> Constant: a constant term representing each
individual's utility associated with not taking a trip;
and
> a (alpha): overdispersion parameter estimated by
the Negative Binomial Model.
Table 21.4 presents explanatory variables and a mean value
for each.12
12 The data on the number of trips in the season from the
NDS suffer from overdispersion. EPA used a negative binomial
model in place of the simple Poisson model to correct for this
overdispersion.
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Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
Table 21.4: Mean Values for Explanatory Variables Used in the Participation Models
Variables
(Mean)
# TRIPS
AGE
MALE
NOHS
COLLEGE
AFAM
YNGKIDS
OLDKIDS
OWNBT
Non-Participant
(N=291)
0.00
43.99
0.33
0.17
0.15
0.11
0.18
0.38
0.00
Boating
(N=85)
7.71
39.06
0.49
0.09
0.32
0.02
0.26
0.48
0.53
Fishing
(N=84)
10.07
38.53
0.65
0.14
0.20
0.05
0.24
0.58
N/A
Swimming
(N=78)
9.46
34.76
0.47
0.13
0.32
0.03
0.24
0.56
N/A
Viewing
(N=75)
9.59
36.91
0.47
0.13
0.35
0.12
0.27
0.48
N/A
Source: U.S. EPA analysis.
Table 21.5 presents the results for the participation models of the four recreation activities.
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Table 21.5: Trip Participation Negative Binomial Model Estimates
Variables/
Statistics
IVBASE
AGE
MALE
NOHS
COLLEGE
AFAM
YNGKIDS
OLDKIDS
OWNBT
Constant
Alpha a
Boating
0.12
(0.71)
-0.07
(-4.73)
1.23
(2.75)
1.29
(2.37)
-0.19
(-0.29)
-3.74
(-1.81)
1.51
(2.96)
-1.67
(-3.58)
3.82
(5.26)
0.20
(0.11)
5.77
(5.85)
Fishing
0.82
(2.86 )
-0.04
( -2.06)
2.22
(3.25)
-1.09
(-1.56)
-0.40
(-0.721 )
-1.44
(-1.53)
-0.95
(-1.26)
1.11
( 2.78)
N/A
-5.74
(-3.01)
9.03
(7.16)
Swimming
0.72
(4.57)
-0.06
( -2.24)
1.15
(1.52)
-0.92
( -0.96)
0.53
(0.71)
-4.07
( -2.68)
0.35
(0.42 )
0.4
(0.65)
N/A
-0.1
( -0.06)
8.92
( 6.78)
Viewing
0.47
( 3.66)
-0.05
( -2.77)
0.91
(2.00)
0.1
(0.17)
1.22
(2.05)
-1.16
(-1.34)
-0.17
(-0.38)
0.8
(1.81)
N/A
-1.98
(-1.6)
8.17
(6.03)
Note: T-statistic for test that coefficient equals 0
N/A indicates that the variable was not included
Source: U.S. EPA analysis.
is given in parentheses below coefficient estimates.
in the estimation for this activity.
All parameter estimates of the inclusive value index
(IVBASE) are within the unit interval [0,1], which ensures
that the model does not violate random utility maximization
assumptions. IVBASE coefficients in the swimming,
fishing, and viewing models are positive and differ
significantly from zero at the 95th percentile, indicating that
water quality improvements have a positive effect on the
number of trips taken during a recreation season.
The estimated coefficient on IVBASE in the boating model,
while positive, was not statistically significant. Taking a
boating trip often requires more preparation (e.g., taking a
boat to the waterbody) than taking other trips. Therefore,
although water quality improvements increase the value of a
boating day, factors other than water quality are likely to
have a stronger impact on the number of boating trips per
season.
The AGE variable is negative and significant for all four
recreation activities: younger people are likely to take more
recreation trips. Ethnicity and gender (the AFAM and
MALE variables) also have a significant impact on whether
an individual participates in water-based recreation.
African-Americans living in Ohio are less likely to
participate in any of the four recreation activities than
representatives of other ethnic groups. Males are more
likely than females to participate in any of the recreation
activities.
Education also influences trip frequency significantly.
People who did not complete high school (NOHS=1) tend to
take fewer fishing or swimming trips. Those with a college
degree (COLLEGE=1) are more likely to participate in
swimming and viewing. Respondents who attended college
are less likely, however, to participate in fishing and boating
than those who completed only a high school education. For
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the boating model, the COLLEGE variable is not
significantly different from zero.
The presence of older children (OLDKIDS) in the
household is associated with greater participation in
swimming, viewing (near-water recreation), and fishing
activities, but is not a significant determinant in decisions to
participate in boating. Younger children in the household
(YNGKIDS) tend to lead to greater participation in boating
and swimming, but lead to fewer fishing or viewing trips.
21.5 ESTIMATINS BENEFITS FROM
REDUCED MP&M DISCHARGES IN OHIO
21.5.1 Benefiting Reaches in Ohio
EPA identified reaches where it expects the MP&M rule to
eliminate or reduce the number of existing AWQC
exceedances (hereafter, benefiting reaches). The Agency
first identified the reaches in which baseline discharges from
industrial sources, including both MP&M and non-MP&M
facilities, caused one or more pollutant concentrations to
exceed AWQC limits for aquatic species. A reach is
considered to benefit from the MP&M rule if at least one
AWQC exceedance is eliminated due to reduced MP&M
discharges. Although the method for identifying benefiting
reaches is similar to the method used in the national analysis
(see Chapter 15 for detail), there are three notable
differences:
> Unlike the national analysis, the Ohio case study
incorporates information on all industrial and
municipal point source discharges and nonpoint
sources to assess in-stream concentrations of toxic
and non-conventional pollutants in the baseline and
post-compliance. Appendix G provides detail on
the water quality model used in this analysis. The
appendix also provides information on the data
sources and methods used to assess ambient water
quality conditions in Ohio.
> The analysis of recreational benefits in Ohio takes
into account only aquatic life-based AWQC
exceedences to avoid any potential double counting
of human health and recreational benefits.
* The analysis of recreational benefits accounts for
changes in TKN concentrations.
EPA's analysis indicates that baseline pollutant
concentrations at discharge levels from all industrial sources
exceed acute exposure criteria on 124 reaches, and exceed
chronic exposure criteria for protection of aquatic species on
169 reaches. EPA estimates that the proposed rule would
eliminate concentrations in excess of the acute aquatic life
exposure criteria on 113 reaches, and would eliminate
concentrations in excess of the chronic aquatic life exposure
criteria on 73 reaches. Table 21.6 summarizes these results.
In addition, the proposed regulation is estimated to reduce
in-stream concentrations of TKN in the affected reaches.
The estimated average reductions are 7.7 percent in lakes
and 12.2 percent in rivers and streams.
Table 21.6.: Estimated MP&M Discharge Reaches with MP&M Pollutant Concentrations
in Excess of AWQC Limits for Protection of Aquatic Species or Human Health
Regulatory Status
Baseline
Proposed Regulation
Number of Reaches with
Concentrations Exceeding AWQC
Limits for Aquatic Species
Acute
124
11
Chronic
169
96
Number of Benefiting Reaches
All AWQC
Exceedances
Eliminated
74
Partial AWQC
Exceedance
Elimination
91
Source: U.S. EPA analysis.
21.5.2 Estimating Recreational
Benefits in Ohio
To estimate peoples' willingness to pay for water quality
improvements, the Agency first calculated per person
seasonal welfare gain corresponding to the proposed
regulation. Table 21.7 presents, for each recreation activity,
the compensating variation per trip (averaged over all
individuals in the sample) associated with the reduced
MP&M discharges. Because the trip choices and the
associated expenditures occurred in 1993, the welfare gain
was calculated in 1993 dollars and then adjusted to 1999
dollars based on CPI.
The model indicates that the reductions in MP&M
discharges from the proposed regulation result in a
substantial increase in per-trip values for all recreation
activities. Note that the per trip-welfare gain for boaters is
greater than for participants in other activities. This result is
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Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
not intuitive. One possible explanation is that boating was
the only activity for which multiple day trips were modeled.
Multi-day trips may also be multi-activity trips. For
example, people may have participated in fishing and
swimming while on a boating trip. Because the NDS data
provided information on the primary purpose of the trip
only, apportioning welfare gain among various activities that
may have taken place during boating trips is not feasible.
This finding is consistent, however, with the existing
literature. Previous economic studies have found that per-
trip welfare gain from water quality improvements is likely
to be greater for multi-day trips than for single-day trips
(Jones and Sung, 1993).
Table 21
Activity
Fishing
Boating
Viewing
Swimmina
.7: Average Welfare Gain per Recreational
User in Ohio
1 Seasonal Welfare Range (in 1999$)
Per Trip!
Welfare inj
1999$!
$3.93=
$9.10=
$4.01=
$^5^
Lower!
Bound!
$27.56=
$92.15=
$11.16=
$12.06!
Mid!
$32.26=
$99.85=
$14.02=
$12.82!
Upper
Bound
$36.97
$107.55
$16.88
$13.58
Table 21.7 also reports seasonal compensating variation per
individual. As noted before, seasonal welfare gain is
derived from both the increase in the utility from better
water quality at the available recreation sites receiving
MP&M discharges and the increase in utility from greater
recreational trip participation.
Both the per trip and seasonal welfare estimates are
consistent with values reported in the existing studies, with
the exception of welfare estimates from improved boating
opportunities. This estimate is somewhat higher than
expected, and is likely to be due to the fact that boating is
often a multi-activity trip.
To calculate state-level recreational benefits from the
proposed rule, EPA first calculated seasonal welfare gain
from water quality improvements per individual in the
sample. The Agency then multiplied the average welfare
gain per individual by the corresponding number of
participants in a given activity (see section 21.1.5 above for
detail). The resulting product is the annual benefit from the
proposed MP&M rule to consumers of a given water-based
recreation activity in Ohio. Table 21.8 summarizes state
level results.
Source: U.S. EPA analysis.
Table 21.8: Estimated Recreational and Nonuse Benefits from Reduced MP&M Discharges in Ohio
Ohio State Recreational Benefits
Activity
Fishing
Boating
Viewing.
Swimming
Total Recreational
Use Benefit
Nonuse Benefits
Total Recreational
Benefits (Use +
Nonuse^^
Percentage j
Participating in i
the Activity (from j Number of
the NDS) ! Particinants3
14.2%! 1*143A691
11.5%! 932^360
15.8%! 1*280,441
14.0%! U31A263
!
!
Estimated Recreational Benefits (million 1999$)
Low
$31.5
$85.9
$14.3
$13.6
$145.4
$36.3
$18^
Mid
$36.9
$93.1
$18.0
$14,5
$162.5
$81.2
$243^
High
$42.3
$100.3
$21.6
$15.4
$179.5
$118.5
$2981)
a. EPA estimated the number of participants in each recreation activity by multiplying the percent of NDS survey respondents from Ohio
participating in each activity by the total adult population (8,080,452). This analysis uses the 1990 Census data to estimate current population
in Ohio.
Source: U.S. EPA analysis.
Under the proposed regulation, the extrapolation from the
sample to the adult population in Ohio yields average annual
benefits estimates of $36.9, $14.5, $18.0, and $93.1 million
(1999$) for fishing, swimming, viewing, and boating,
respectively. The total recreational use benefits range from
$145.4 to $179.5 million (1999$). The Agency used the
same approach as in the national analysis to estimate nonuse
benefits. EPA estimated nonuser benefits as one-fourth,
one-half, and two-thirds of recreational use benefits for low,
mid, and high estimates, respectively. The estimated nonuse
benefits range from $36.3 to $118.5 million (1999$).
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MP&M EEBA Part V: Ohio Case Study
Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
21.6 LIMITATIONS AND UNCERTAINTY
21.6.1 One-State Approach
Some benefits are likely to be missed by a state-level case
study. For example, residents from neighboring states
undoubtedly recreate in Ohio waters, and residents of Ohio
undoubtedly recreate in neighboring states. A state-by-state
approach that restricts its analysis to recreation activities
within the state misses these categories of benefits.13 This
omission is likely to be more significant for unique locations
of high quality (e.g., Lake Erie), where participants travel
significant distances, and for sites very close to state
boundaries.
21.6.2 Including One-Day Trips Only
Use of day-trips only tends to understate recreational
benefits for swimming, fishing, and viewing, since
recreation as part of multi-day trips is excluded. Inclusion
of multi-day trips, however, can be problematic. Multi-day
trips are frequently multi-activity trips. An individual might
travel a substantial distance, participate in several recreation
activities, go shopping and sightseeing, all as part of one
trip. Recreational benefits from improved recreational
opportunities for the primary activity are overstated if all
travel costs are treated as though they are associated with the
one recreational activity of interest. The total benefits per
trip from water quality improvements are not overstated,
however, if individuals participated in several water-based
activities.
21.6.3 Considering Only Recreational
Values
This study understates the total benefits of water quality
improvements because estimates are limited to recreation
benefits, when many other forms of benefits are also likely
to be important. Other benefits include aesthetic benefits for
residents living near waterbodies, habitat values for a variety
of species (in addition to recreational fish), nonuse values,
etc. To correct for this limitation inherent in travel cost
models, EPA quantified nonuse values in proportion to
recreation values. This approach provides only a rough
approximation of the value of water resources to nonusers.
For example, some natural resources have high use values
but small or negligible nonuse values (e.g., cows), while
other species have very high nonuse values but small or
negligible use values (e.g., blue whales). This approach may
therefore lead to either overestimation or underestimation of
benefits.
21.6 A Potential Sources of Survey Bias
The survey results could suffer from bias, such as recall bias
(e.g., Westat, 1989), nonresponse bias, and sampling effects.
a. Recall bias
Recall bias can occur when respondents are asked the
number of days in which they recreate over the previous
season, such as in the NDS survey. Some researchers
believe that recall bias tends to lead to an overstatement of
the number of recreation days, particularly for more avid
participants. Avid participants tend to overstate the number
of recreation days, since they count days in a "typical" week
and then multiply them by the number of weeks in the
recreation season.14 They often neglect to consider days
missed due to bad weather, illness, travel, or when fulfilling
"atypical" obligations. Some studies also found that the
more salient the activity, the more "optimistic" the
respondent tends to be in estimating number of recreation
days. Individuals also have a tendency to overstate the
number of days they participate in activities that they enjoy
and value. Taken together, these sources of recall bias may
result in an overstatement of the actual number of recreation
days.
b. Nonresponse bias
A problem with sampling bias may arise when extrapolating
sample means to population means. This could happen, for
example, when avid recreation participants are more likely
to respond to a survey than those who are not interested in
the forms of recreation, are unable to participate, assume
that the survey is not meant for them, or consider the survey
not worth their time.
c. Sampling effects
Recreational demand studies frequently face two types of
observations that do not fit general recreation patterns:
non-participants and avid participants:
Non-participants are those individuals who would not
participate in the recreation activity under any conditions.
This analysis assumes that an individual is a non-participant
in a particular activity if he or she did not participate in that
activity at any site. This assumption tends to understate
benefits, since some individuals may not have participated
during the sampling period simply by chance, or because
price/quality conditions were unfavorable during the
sampling period.
13 Note that EPA used a few observation on visitors from
neighboring states to estimate site choice models. The analysis does
not include these observations in calculating state-level benefits
from water quality improvements.
14 Westat (1989) uses ten or more activity-days per year as an
indicator of an "avid" user.
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Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
Avid participants can also be problematic because they
claim to participate in an activity an inordinate number of
times. This reported level of activity is sometimes correct,
but often overstated, perhaps due to recall bias (see Westat,
1989). Even where the reports are correct, these
observations tend to be overly influential. EPA dropped
observations of participants who reported more than 100
trips per year when estimating trip participation models, to
correct for potential bias caused by these observations.
21.6.5 Using IWB2 to Predict
Recreational Behavior
Using IWB2 in the model can be counterproductive for
welfare measurement unless policy-related pollution
reductions are linked to associated changes in the index.
EPA used the IWB2 index to predict site choice (with the
exception of the swimming model) because biological
factors are usually significant determinants of recreational
behavior. Excluding the IWB2 from the model would
reduce the accuracy of the site choice estimates. The IWB2
index, however, may extract explanatory power from other
water quality measures to the extent that IWB2 is correlated
with these other measures, unless changes in IWB2 resulting
from policies to control MP&M pollutants are predicted.
Benefits of water quality improvements may therefore be
understated. As noted in Section 21.2.3, the act of modeling
changes in IWB2 is beyond the scope of this study.
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MP&M EEBA Part V: Ohio Case Study
Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
GLOSSARY
ambient water quality criteria (AWQC): levels of
water quality expected to render a body of water suitable for
its designated use. Criteria are based on specific levels of
pollutants that would make the water harmful if used for
drinking, swimming, farming, fish production, or industrial
processes. (http://www.epa.gov/OCEPAterms/aterms.html)
compensating variation (CV): the amount of money a
person would need to pay or receive in order to leave that
person as well off as they were before a change.
consumer choice set: the set of alternatives from which
a consumer may choose.
exogenous: external to the inner workings of a system or
model; variables are exogenous to the extent that they are
"given" and not the result of the operation of the system or
anything going on in the model itself.
expected maximum utility of a trip: see
"inclusive value."
fish consumption advisories (FCAs): an official
notification of the public about specific areas where fish
tissue samples have been found to be contaminated by toxic
chemicals which exceed FDA action limits or other accepted
guidelines. Advisories may be species specific or
community wide.
inclusive value: the value to the consumer of being able
to choose among X alternatives (e.g., among a number of
recreational sites) on a given trip occasion.
index of well being (IWB2): a composite index of
diversity and abundance measures (density and biomass)
based on fish community data.
indirect utility function: gives the maximum value of
utility for any given prices and money income. The indirect
utility function is obtained when quantity of goods that
maximize consumer utility subject to the budget constraint
are substituted into a utility function.
inferential analysis: based on interpretation.
multinomial logit (MNL): a utility maximization model.
In this model, an individual is assumed to have preferences
defined over a set of alternatives (e.g., recreation sites). The
choice model takes the form of comparing utilities from
different alternatives and choosing the one that produces the
maximum utility. In this framework, observed data consist
of attributes of the choices (e.g., available recreational
amenities at different sites) and the choice actually made.
Usually no characteristics of the individuals are observed
beyond their actual choice.
National Demand Survey for Water-Based
Recreation (NDS): a U.S. EPA survey of recreational
behavior. The 1993 survey collected data on socioeconomic
characteristics and water-based recreation behavior using a
nationwide stratified random sample of 13,059 individuals
aged 16 and over (http://www.epa.gov/opei).
negative binomial regression model: an extension of
the Poisson regression model that allows the variance of the
process to differ from the mean (see also Poisson
distribution and Poisson estimation process).
Negative binomial Poisson model: (see negative
binomial regression model).
nested multinomial logit model (NMNL): an
extension of MNL (see above). In this model, an individual
is assumed to choose among different groups of alternatives
first (i.e., Great Lakes or inland recreation sites) and then to
choose elemental alternatives (e.g., a particular river reach,
lake, or Great Lakes site) in the choice set.
non-conventional pollutants: a catch-all category that
includes everything that is not classified as a priority
pollutant or a conventional pollutant.
Ohio Water Resource Inventory (OWRI): a biennial
report to U.S. EPA and Congress required by Section 305(b)
of the Clean Water Act. The report is composed of four
major sections: (1) inland rivers and streams, wetlands, Lake
Erie, and water program description; (2) fish tissue
contaminants; (3) inland lakes, ponds, and reservoirs; and
(4) groundwater.
overdispersion: condition for a distribution where the
variance exceeds the mean. It usually signifies a nonrandom
dispersion, for example the case where a small minority of
the population is responsible for the majority of recreational
trips taken.
Poisson distribution: a random variable X is defined to
have a Poisson distribution if the probability density of X is
given by fx(X)= fx (X;A) = eA Ax / x! forx = 0,1,2.., and 0
otherwise. In this model, e is both the mean and variance of
X.
Poisson estimation process: is used to model discrete
random variables. Typically, a Poisson random variable is a
count of the number of events that occur in a certain time
interval or spatial area. For example, the number of
recreational trips taken during a recreational season.
priority pollutants: 126 individual chemicals that EPA
routinely analyzes when assessing contaminated surface
water, sediment, groundwater, or soil samples.
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MP&M EEBA Part V: Ohio Case Study
Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
random utility model (RUM): a model of consumer
behavior. The model contains observable determinants of
consumer behavior and a random element.
ReacAl File 1 (RF1): a database of approximately 700,000
miles of streams and open waters in the conterminous
United States. The database contains information on
streamflow, time travel velocity, reach length, width, depth,
and other stream attributes.
site choice model: is used to determine which
recreational site is chosen by the consumer. EPA estimated
the likelihood that the consumer will choose a particular site
as a function of site characteristics, the price paid per site
visit, and household income.
Total Kjeldahl Nitrogen (TKN): TKN is defined as the
total of organic and ammonia nitrate. It is determined in the
same manner as organic nitrogen, except that the ammonia is
not driven off before the digestion step.
travel cost model (TCM): method to determine the value
of an event by evaluating expenditures of recreators. Travel
costs are used as a proxy for price in deriving demand
curves for the recreation site.
(http://www.damagevaluation.com/glossary.htm)
total seasonal welfare: see "welfare effect."
trip participation model: is used to estimate the number
of water-based recreational trips taken during the recreation
season. EPA estimated the total number of trips during the
recreation season as a function of the expected maximum
utility (inclusive value) from recreational activity
participation on a trip, and socioeconomic characteristics
affecting demand for recreation trips (e.g., number of
children in the household).
utility-theoretic: consistent with the behavioral postulate
of maximum utility that underlines the structure of models
of consumer behavior.
welfare effect: gain or loss to the group of individuals
(e.g., fishermen) as a whole.
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MP&M EEBA Part V: Ohio Case Study
Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
ACRONYMS
AWQC: Ambient Water Quality Criteria
CV: compensating variation
FCAs: fish consumption advisories
IWB2: index of well being
LIMDEP: Limited Dependent Variable
MNL: multinomial logit
MP&M: Metal Product and Machinery industries
NDS: National Demand Survey for Water-Based
Recreation
NMNL: nested multinomial logit model
ODNR: Ohio Department of Natural Resources
OWRI: Ohio Water Resource Inventory
RUM: random utility model
RF1: Reach File 1
TKN: Total Kjeldahl Nitrogen
TCM: travel cost model
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MP&M EEBA Part V: Ohio Case Study Chapter 21: Modeling Recreational Benefits in Ohio With a RUM Model
REFERENCES
Bockstael, N.E., I.E. Strand, and W.M. Hanemann. 1987. Time and the Recreation Demand Model. American Journal of
Agricultural Economics 69:213-32.
Creel, M. and J. Loomis. 1992. Recreation Value of Water to Wetlands in the San Joaquin Valley: Linked Multinomial Logit
and Count Data Trip Frequency Models. Water Resource Research. Vol 28. No 10 pp.2597-2606, October.
Feather, Peter M. ; Daniel Hellerstein, and Theodore Tomasi. 1995. A Discrete-Count Model of Recreation Demand.
Journal of Environmental Economics and Management, 29:214-227.
Green, W.H. 1993. Econometric Analysis. New York, NY: Macmillan Publishing Company.
Hausman, J., G. Leonard, and D. McFadden. 1995. A Utility-Consistent, Combined Discrete Choice and Count Data Model:
Assessing Recreational Use Losses Due to Natural Resource Damage. J. of Public Economics No 56 pp. 1-30.
Jones, C.A. and Y.D. Sung. 1993. Valuation of Environmental Quality at Michigan Recreational Fishing Sites:
Methodological Issues and Policy Application. Final Report. EPA Contract No. CR-816247-01-2. September.
Kling, C.L. and CJ. Thomson. 1996. "The Implication of Model Specification for Welfare Estimation in Nested Logit
Model." American Journal of Agricultural Economics Association,No. 78, February, pp. 103-114.
McFadden, D. 1981. "Econometric Models of Probabilistic Choice." In C.F. Manski and D.L. McFadden, eds., Structural
Analysis of Discrete Data. Cambridge, MA: MIT Press.
Ohio Atlas and Gazetteer, The. 1995. Freeport, ME: Delorme.
Ohio Department of Natural Resources, Division of Wildlife. Creel Survey Summaries from 1992 to 1997.
Ohio Department of Natural Resources, Division of Wildlife. 1999. Fish Consumption Advisories.
Ohio EPA. 1996. Ohio Waste Resource Inventory Volume 1: Summary Status, and Trends; and Volume 3: Ohio Public
Lakes, Ponds, and Reservoirs. Chagrin.EPA.State.OH.US/document index.
Parsons, G. and M. J. Kealy. 1992. Randomly Drawn Opportunity Sets in a Random Utility Model of Lake Recreation
Land Economics 68 No. 4(1992): pp. 418-33.
Parsons, G.R. 1999. Comments on Assessing the Recreational Benefits of the MP&M Regulation: a State-level Case Study
Based on the Random Utility Model Approach. Memo to Abt Associates Inc., August.
U.S. Bureau of the Census. 1999. Internet web site: http://www.state.oh.us/odhs/octf/stats/gjcs/ohio.pdf
U.S. EPA. 1993. National Demand for Water-Based Recreation Survey. Washington, D.C.: Office of Policy Evaluation
and Information.
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MP&M EEBA Part V: Ohio Case Study
Chapter 22: MP&M Benefit Cost Analysis Ohio
Chapter 22: MP&M Benefit-
Cost Analysis in Ohio
INTRODUCTION
This chapter presents estimated benefits and costs of the
proposed MP&M regulation in Ohio. The preceding chapter
summarized the methodology and results of the case study
of the expected recreational benefits from water quality
improvements in Ohio. This chapter first presents estimates
of the remaining three benefit categories, including:
* reduced human health risk from exposure to
carcinogens and systemic health toxicants,
> changes in health risk from exposure to lead for
adults and children, and
- publicly-owned treatment works (POTW)
benefits.
Then, the chapter presents the social costs of the proposed
regulation for the state of Ohio. Finally, the chapter
compares the aggregate benefits and social costs estimates
for the proposed regulation in Ohio. Analysis of the
benefits and costs of the proposed regulation shows that the
proposed regulation will have net benefits in Ohio ranging
from $40.3 to $149.2 million (1999$).
EPA estimated MP&M costs and benefits in Ohio using
similar methodologies to those used for the national-level
analysis. In addition to the RUM study of recreational
benefits discussed in the previous chapter, the additional
analytical improvements included the following:
* the use of more detailed data on MP&M facilities.
EPA oversampled the state of Ohio with 1,600
screeners to obtain information on co-occurrence of
MP&M discharges;
> the use of data on non-MP&M discharges to
estimate current baseline conditions in the state;
and
> the use of a first-order decay model to estimate in-
stream concentrations in the Ohio waterbodies.
This model allows the assessment of the
CHAPTER CONTENTS:
22.1 Benefits of the Proposed Regulation 22-1
22.1.1 Human Health Benefits
(Other than Lead) 22-2
22.1.2 Lead-Related Benefits 22-2
22.1.3 Economic Productivity Benefits 22-3
22.1.4 Total Monetized Benefits 22-3
22.2 Social Costs of Proposed Regulation 22-4
22.2.1 Baseline and Post-Compliance Closures 22-4
22.2.2 Compliance Costs for MP&M Facilities . 22-5
22.2.3 Government Administrative Costs 22-5
22.2.4 Costs of Unemployment in Ohio 22-6
22.2.5 Total Social Costs 22-7
22.3 Comparison of Monetized Benefits and Costs 22-7
Glossary 22-8
Acronyms 22-9
environmental effects of MP&M discharges on the
reaches receiving MP&M discharges and
downstream reaches.
Appendix G describes the water quality model used in this
analysis and the approach and data sources used to estimate
total pollutant loadings from all industrial and municipal
sources to Ohio's waterbodies. The Agency believes that
the added level of detail results in more robust benefit cost
estimates.
22.1 BENEFITS OF THE PROPOSED
RESULATION
EPA estimates that approximately 564 million pounds of
pollutants per year are discharged to POTWs, and
approximately 615 million pounds of pollutants are
discharged directly to surface water in Ohio. The proposed
regulation is estimated to remove 503 million pounds
discharged to POTWs and 31 million pounds discharged
directly to surface waters.
22-1
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MP&M EEBA Part V: Ohio Case Study
Chapter 22: MP&M Benefit Cost Analysis Ohio
22.1.1 Human Health Benefits (Other
than Lead)
Benefits from the reduced number of cancer cases from
consumption of drinking water account for the bulk of the
monetized human health benefits. Total monetized human
health benefits from the proposed regulation are $142.6
thousand (1999$). Chapter 13 details the methodologies
used to estimate human health benefits from reduced
exposure to carcinogens and systemic health toxicants other
than lead.
a. Reduced incidence of cancer cases from
consumption of contaminated fish and
drinking water
Table 22.1 shows the number of cancer cases avoided by the
proposed regulation through both the drinking water and fish
consumption pathways. EPA estimates that improved water
quality resulting from the proposed regulation will reduce
the incidence of cancer cases via the drinking water and fish
consumption pathways from the total of 0.036 cases
respectively in the baseline to 0.012 cases under the
proposed regulation. Monetized benefits from reduced
cancer incidence from drinking water are $142.6 thousand.
Estimated benefits from reduced cancer risk associated with
fish consumption pathways are negligible.
Table 22.1: Estimated Annual Benefits from Avoided
Cancer Cases from Fish and Drinking Water
Consumption
Cancer!
Cases;
Benefits
(1999$)
Baseline
i Drinking Water
I Fish Consumption
Total
0.036:
0.00001!
0.036J
Proposed Regulation
i Drinking Water
i Fish Consumption
Total
0.012!
0.00001!
0.012!
$142,600
$39
$142,639
Source: U.S. EPA analysis.
b. Systemic health effects
EPA's analysis of the in-waterway pollutant concentration
data suggests that baseline hazard ratios, for both the fish
consumption and drinking water pathways, for the
population associated with sample facilities only are less
than one. The results of the analysis show shifts in
populations from higher (but less than 1.0) to lower hazard
score values between the baseline and post-compliance
scenarios.
c. Reduced frequency of human-health
based AWQC exceedances in Chios
waterbodies
Baseline in-waterway concentrations of MP&M pollutants
exceed human health-based ambient water quality
criteria (AWQC) limits for consumption of water or
organisms in 11 reaches. No reaches exceeded human-
health based AWQC for consumption of organisms only.
The proposed regulation will eliminate exceedences of
human health AWQC in six (45.5 percent) of these reaches.
22.1.2 Lead-Related Benefits
Total monetized lead-related benefits in Ohio for children
and adults combined under the proposed regulation are
$104,951 (1999$). Chapter 14 of this report describes the
methodologies used to estimate these benefits.
a. Estimated benefits to Ohios children
Table 22.2 presents lead-related benefits from the proposed
regulation for preschool age children and pregnant women
in Ohio. The proposed regulation will reduce the incidence
of neonatal mortality by 0.005 cases annually. This yields
the monetary value of benefits of $33,668 (1999$).
The proposed regulation will avoid the loss of an estimated
1.74 IQ points among preschool children in Ohio, which
translates into $17,538 (1999$) per year in benefits. The
avoided costs of compensatory education due to reduced
incidence of children with IQ below 70 and blood-lead
levels above 20 ug/dL equal about $459. The proposed
regulation will therefore result in aggregated lead-
relatedbenefits for children in Ohio of $51,665 (1999$).
Table 22.2: Ohio Child Lead Annual Benefits (1999$)
Proposed Regulation
Category
Neonatal Mortality
Avoided IQ Loss
Reduced IQ < 70
Reduced PbB > 20
Total Benefits
Reduced Cases! Monetary Value
or IQ Points i of Benefits
0.005; $33,668
1.741; $17,538
0.001; $453
negligible; $6
I $51,665
Source: U.S. EPA analysis.
b. Adult benefits
Table 22.3 presents benefit estimates for reduced lead-
related health effects in adults. These health effects include
increased incidence of hypertension, initial non-fatal
coronary heart disease (CHD). non-fatal stokes
(cerebrovascular accidents rCBAI and brain
infarction IBII) and premature mortality. The proposed
22-2
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MP&M EEBA Part V: Ohio Case Study
Chapter 22: MP&M Benefit Cost Analysis Ohio
regulation would reduce hypertension in Ohio by an
estimated 3.6 cases annually among males, resulting in
benefits of approximately $3,796 (1999$). Reducing the
incidence of initial CHD, strokes, and premature mortality
among adult males and females in Ohio would result in
estimated benefits of $449, $1,052, and $47,989
respectively. Overall, adult lead-related benefits of $53,286.
This analysis does not include other health effects associated
with elevated blood pressure IBP) or with lead, such as
nervous system disorders, anemia, and possible cancer
effects.
Table
Category
Men
Women
22.3: Ohio Adult
Proposed
Hypertension
iCHD
!CBA
I.BI
i Mortality
iCHD
!CBA
I.BI
i Mortality
Lead Benefits (1999$)
Regulation
Reduced i
Cases!
3.623!
0.005!
0.002!
o.ooi!
0.006!
o.ooi!
o.ooi!
o.ooo !
o.ooi!
Total Benefits
Monetary Value of
Benefits
$3,796
$343
$538
$304
$38,741
$105
$130
$80
$9,248
$53,286
Source: U.S. EPA analysis.
22.1.3 Economic Productivity Benefits
EPA estimates that the proposed regulation would remove
3.5 million pounds of the eight pollutants in Ohio for which
there are published sludge concentration limits. EPA
estimated the total monetized POTW benefits for the
proposed regulation to be $10,000 (1999$). Chapter 16
describes the methodologies used to estimate these benefits.
The Agency estimated that 28 POTWs in Ohio exceed the
Land Application-High pollutant limits and 20 exceed the
Land Application-Low pollutant limits under the baseline
discharge levels. EPA estimated that four POTWs will be
newly qualified for lower-cost land application based on
estimated reductions in sludge contamination, and that
approximately 200 dry metric tons (DMT) of sludge will
be newly qualified for land application.1
EPA also estimated that 11.6 DMT of sewage sludge
generated by two POTWs that previously met only the Land
Application-Low limits would, as a result of regulation,
meet the more stringent Land Application-High limits.
These two POTWs will benefit from reduced recordkeeping.
22.1.A Total Monetized Benefits
Summing the monetary values over all benefit categories
(Chapters 21 and 22) yields total monetized benefits in Ohio
of $182.0 to $298.3 million (1999$) annually for the
proposed regulation (see Table 22.4). The midpoint
estimate of monetized benefits for the proposed regulation is
$243.9 million (1999$). As noted in Chapter 12, this benefit
estimate is necessarily incomplete because it omits some
mechanisms by which society is likely to benefit from
reduced effluent discharges from the MP&M industry.
Examples of benefit categories not reflected in this
monetized estimate include: non-lead related non-cancer
health benefits, improved aesthetic quality of waters near
discharge outfalls, benefits to wildlife and to threatened or
endangered species, tourism benefits, and reduced costs of
drinking water treatment.
1 This newly qualified sludge can meet either Land
Application-High or -Low pollution limits.
22-3
-------
MP&M EEBA Part V: Ohio Case Study
Chapter 22: MP&M Benefit Cost Analysis Ohio
Table 22.4: Estimated Benefits
Benefit Category
1. Reduced Cancer Risk:
Fish Consumption
Water Consumption
2. Reduced Risk from Exposure to Lead:
Children
Adults
3. Enhanced Water-Based Recreation
4. Nonuse benefits
5. Avoided Sewage Sludge Disposal Costs
Total Monetized Benefits
in Ohio from Reduced MP&M Discharges under
(Annual Benefits - 1999$)
Low j
$39!
$142,600!
$51,665!
$53,286!
$145,365,723!
$36,341,431!
$10,000!
$181,964,744!
the Proposed
Midj
$39!
$142,600!
$51,665!
$53,286!
$162,449,204!
$81,224,602!
$10,000!
$243,931,396!
Regulation
High
$39
$142,600
$51,665
$53,286
$179,532,685
$118,492,572
$10,000
$298,282,847
Source: U.S. EPA analysis.
22.2 SOCIAL COSTS OF PROPOSED
RESULATION
22.2.1 Baseline and Post-Compliance
Closures
The methodology used to assess baseline and post-
compliance closures differed from the methodology used for
the national analysis presented in Chapter 5. The screener
data collected for Ohio facilities did not provide financial
data to perform an after-tax cash flow or net present value
test. EPA therefore used data from the national analysis to
estimate the percentage of facilities that close in the baseline
and post-compliance. EPA assumed that the ratio of
facilities that close in the national analysis with the same
discharge status, subcategory, and flow category would be
comparable to the facilities in Ohio. For example, eight
percent of indirect general metals facilities discharging more
than 6.25 million gallons per year close in the baseline in the
national data set, and this same percent distribution is
assumed for Ohio screener indirect dischargers in that flow
size category.
Table 22.5 provides an overview of the numbers of facilities
in Ohio closing or excluded in the proposed regulation by
discharge status. There are 607 facilities that do not close in
the baseline, subject to flow or subcategory exclusions, and
are therefore subject to requirements under the proposed
regulation. Approximately 84 percent of the indirect
dischargers operating post-regulation are excluded from
requirements by the low flow cutoffs and the subcategory
exclusions. All of the 215 direct dischargers operating in
the baseline are subject to regulatory requirements.
Table 22.5: Regulatory Impacts for All Ohio
Facilities by Discharge Type
Number of facilities
operating in the
baseline
Number of regulatory
closures
Number of facilities
operating post-
regulation
Number of facilities
below low flow cutoffs
Number of facilities
with subcategory
exclusions
Percent of facilities
operating in the
baseline that are
regulatory closures
Percent of facilities
operating in the
baseline excluded or
below cutoffs
Number of facilities
operating subject to
regulatory
requirements
Indirect
2,518
26
2,492
2,080
20
1.0%
84.3%
392
Direct
215
0
215
0.0%
215
Total
2,733
26
2,707
2,080
20
1.0%
77.6%
607
Source: U.S. EPA analysis.
22-4
-------
MP&M EEBA Part V: Ohio Case Study
Chapter 22: MP&M Benefit Cost Analysis Ohio
22.2.2 Compliance Costs for MP&M
Facilities
The calculation of annualized compliance costs in Ohio uses
the methodology presented in Chapter 11. These
compliance costs are not adjusted for the effect of taxes, and
therefore represent the social value of resources used for
compliance. Compliance costs are annualized using a seven
percent discount rate over a 15-year life of the plant. EPA
developed estimates of compliance costs for each Ohio
facility, and then calculated an average annualized
compliance cost by subcategory, flow range, and discharge
status for the Ohio facilities. The Agency was not able to
determine which specific facilities would close in the
baseline and due to the regulation; EPA therefore used these
average compliance costs, along with the percent of facilities
remaining open in the baseline and post-compliance, to
calculate total compliance costs.
As in the national social cost analysis reported in Chapter
11, EPA included compliance costs for facilities that close
due to the regulation, as well as costs for continuing to
operate subject to the proposed regulation. This inclusion
results in an upper-bound estimate of the social costs of
compliance, since the lost value incurred by closing facilities
is presumably less than the estimated cost of compliance.2
Table 22.6 shows the estimated resource value of
compliance costs by discharge status and subcategory.
General Metals and MF Job Shop indirect dischargers
together account for approximately 89 percent of the total
compliance costs under the proposed regulation. The total
estimated annualized compliance costs are $141.7 million.
Table 22.6: Resource Value of Compliance Costs
(1999$) in Ohio
Subcategory
General
Metals
Steel Forming
& Finishing
MF Job Shop
Non
Chromium
Anodizer
Oily Waste
Printed Wiring
Boards
Railroad Line
Maintenance
Total
Indirect
$67,404,989
$147,485
$58,218,101
$0
$0
$8,096,391
$0
$133,866,966
Direct
$5,426,008
$114,124
$24,831
$28,551
$23,597
$0
$2,250,001
$7,867,112
Total
$72,830,997
$261,609
$58,242,932
$28,551
$23,597
$8,096,391
$2,250,001
$141,734,078
Source: U.S. EPA analysis.
22.2.3 Ohio Government Administrative
Costs
The calculation of government administrative costs in Ohio
uses the methodology presented in Chapter 7 and Appendix
C. The screener data collected for Ohio facilities did not
provide information on the types of permits currently held
by facilities. It was therefore necessary to estimate the
number of indirect-discharging facilities that currently hold
a concentration-based permit, a mass-based permit, or no
permit. EPA assumed that the screener Ohio facilities'
baseline permit status is the same as the permit status of
facilities in the national analysis in the same subcategory
and discharge status. For example, 43 percent of Oily Waste
indirect dischargers in the national data set have a
concentration-based permit in the baseline, less than 1
percent have a mass-based permit, and 57 percent have no
permit. EPA assumes that the same percent distribution
applies to Ohio screener indirect dischargers in the Oily
Waste subcategory.
Table 22.7 shows the estimated numbers of Ohio facilities
by baseline permit status, and the numbers of facilities
requiring various types of permits under the proposed
regulation. EPA calculated the costs in Ohio using the
POTW administrative cost model described in Appendix C.
2 Including costs for regulatory closures in effect calculates
the social costs of compliance that would be incurred if every
facility continued to operate post-regulation. In fact, some
facilities find it more economic to close, and calculating costs as if
all facilities continue to operate will overstate social costs.
22-5
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MP&M EEBA Part V: Ohio Case Study
Chapter 22: MP&M Benefit Cost Analysis Ohio
Table 22.7: Estimated Number of Ohio Indirect Dischargers by Permit Status:
Baseline and Proposed Regulation
Permit Status
Baseline Permit Status
Concentration-based
Mass-based
None
Total
Proposed Regulation:
Requiring new
concentration-based
Requiring new mass-
based
Requiring upgrading
from concentration-to
mass-based
Earlier repermitting:
concentration-based
Earlier repermitting:
mass-based
Excluded under
proposed regulation
Regulatory closure
Total
Subcategory
Gen'l
Metals
(forfactth
1,065
217
774
2,056
43
22
30
60
18
1,882
2,055
Steel
Forming
&
Finishing
ties operating
1
2
3
1
2
3
MFJob
Shops
ป in the bos
63
125
3
191
2
1
18
37
108
26
192
NonCh
Anodiz
eline):
1
6
1
14
15
15
Oily
Waste
87
115
202
1
1
1
1
198
202
PWBs
6
40
46
2
4
40
46
RRLine
Maint
5
5
5
5
Dry
Docks
Total
1,229
390
898
2,518
46
24
52
102
168
2,100
26
2,518
Source: U.S. EPA analysis.
Ohio permit writers would need to issue 46 new
concentration-based permits and 24 new mass-based
permits, and to upgrade an estimated 52 concentration-based
permits to mass-based permits, under the proposed
regulation. In addition, they would have to reissue 102
concentration-based permits and 168 mass-based permits
within the three-year compliance period, rather than on the
normal five-year schedule.
The estimated annualized costs of these permitting activities
ranges from $10,649 to $83,328, with a median estimate of
$25,364. As described in Chapter 7, this estimate assumes
that all Steel Forming & Finishing facilities will be issued a
mass-based permit, that one-third of the existing
concentration-based permits will be revised to a mass basis,
and that one third of new permits issued will be mass-based.
22.2A Costs of Unemployment in Ohio
Chapter 11 described the methodology used to estimate the
social costs of unemployment caused by the regulation.
Because it is not possible to determine which Ohio facilities
would close under the proposed regulation, EPA estimated
employment (FTEs) at the closing Ohio facilities by
assuming that these facilities have the same employment as
the average for closing facilities in the national analysis, in
the same subcategory, flow size category, and discharge
status.
EPA estimates that closures due to the proposed regulation
would result in lost employment of up to 557 FTEs in Ohio.
The upper-bound estimated social costs of 557 job losses is
$7,338,313, based on the methodology used for the national
analysis. This estimate includes the estimated willingness-
to-pay to avoid 557 cases of involuntary unemployment,
plus the cost of administering the unemployment
compensation system for 557 unemployed workers. EPA
22-6
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MP&M EEBA Part V: Ohio Case Study
Chapter 22: MP&M Benefit Cost Analysis Ohio
estimated that the costs of unemployment would range from
$7,337 to $7,338,313 because the regulation will also result
in increased employment due to compliance expenditures,
which are likely to more than offset the proposed regulation
job losses. This is the same approach that EPA used to
estimate a range as the Agency used for the national social
cost analysis.
22.2.5 Total Social Costs
Table 22.8 shows the total estimated social costs of the
proposed regulation in Ohio. The social costs range from
$141.7 to $149.1 million 1999$. As in the national analysis,
the resource value of compliance costs account for virtually
all of the estimated social costs.
Table 22.8: Annual Social Costs for Proposed
Regulation in Ohio
(millions 1999$, costs annual ized at 7%)
Component of
Social Costs
Resource value of
compliance costs
Government
administrative costs
Social cost of
unemployment
Total Social Cost
Lower Upper
bound Median bound
$141.7
$0.011
$.007
$141.7
$0.025
$3.673
$145.4
$0.083
$7.338
$149.1
Source: U.S. EPA analysis.
22.3 COMPARISON OF MONETIZED
BENEFITS AND COSTS IN OHIO
EPA cannot perform a complete cost-benefit comparison
because not all of the benefits resulting from the proposed
regulatory alternative can be valued in dollar terms. The
social cost of the proposed regulation in Ohio is estimated at
$141.7 to $149.1 million annually (1999$). The sum total of
benefits that can be valued in dollar terms ranges from
$182.0 million to $298.3 million annually (1999$).
Combining the estimates of social benefits and social costs
yields a net monetizable benefit ranging from $32.9 million
to $156.6 million annually. Comparing the midpoint
estimate of social costs ($145.4 million) with the mean
estimate of monetizable benefits ($243.9 million) results in a
net social benefit of $98.5 million.
In contrast to the national estimates of costs and benefits for
the proposed regulation, the Ohio case study shows
substantial net positive benefits even for the lower-bound
estimate of benefits. This difference is in part due to EPA's
ability in the Ohio case study to take more accurate account
of baseline water quality. EPA also included an additional
recreational benefit category in the Ohio analysis -
swimming. Although the estimated per-trip welfare gain to
swimmers is lower than to users of other water-based
activities, this benefit category accounts for a sizable portion
of the state-level benefits. Other factors that affect the Ohio
benefit cost comparison results include a large number of
MP&M facilities in the state and the presence of unique
water resources. Ohio is one of the six states with large
numbers of MP&M facilities.3 The state also has unique
water resources such as Lake Erie that offer numerous
recreational opportunities. The estimated benefits for Ohio
are therefore likely to reflect the upper bound estimates for
the nation.
3 Other states with large numbers of MP&M facilities include
New York, Pennsylvania, Indiana, Illinois, and Michigan.
22-7
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MP&M EEBA Part V: Ohio Case Study
Chapter 22: MP&M Benefit Cost Analysis Ohio
GLOSSARY
ambient water quality criteria (AWQC): levels of
water quality expected to render a body of water suitable for
its designated use. Criteria are based on specific levels of
pollutants that would make the water harmful if used for
drinking, swimming, farming, fish production, or industrial
processes. (http://www.epa.gov/OCEPAterms/aterms.html)
blood pressure (BP): the pressure of the blood on the
walls of the arteries.
brain infarction (Bl): stroke.
cerebrovascular accidents (CBA): stroke.
coronary heart disease (CHD): disorder that restricts
blood supply to the heart; occurs when coronary arteries
become narrowed or clogged due to the build up of
cholesterol and fat on the inside walls and are unable supply
enough blood to the heart.
publicly-owned treatment works (POTW): a
treatment works as defined by section 212 of the Act, which
is owned by a State or municipality. This definition includes
any devices or systems used in the storage, treatment,
recycling, and reclamation of municipal sewage or industrial
wastes of a liquid nature.
(http://www.epa.gov/owm/permits/pretreat/final99.pdf)
-------
MP&M EEBA Part V: Ohio Case Study
Chapter 22: MP&M Benefit Cost Analysis Ohio
ACRONYMS
AWQC: ambient water quality criteria
Bl: brain infarction
BP: blood pressure
CBA: cerebrovascular accidents
CHD: coronary heart disease
DMT: dry metric tons
FTE: full-time employment
POTW: publicly-owned treatment works
22-9
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MP&M EEBA: Appendices
Appendix A: Detailed Economic Impact Analysis Information
Appendix A: Detailed Economic
Impact Analysis Information
INTRODUCTION
This appendix provides information to support the economic
analyses of MP&M industries presented in Chapter 3 to
Chapter 11 of the EEBA. The first section below provides
the SIC and NAICS codes that define the MP&M sectors.
The second section presents information on the annual
turnover of establishments ("births" and "deaths") in the
MP&M manufacturing industries. The third section
provides a description of the MP&M surveys that supported
the economic impact and benefits analyses presented in the
EEBA.
A.I MP&M SIC AND NAICS CODES
Table A. 1 lists and describes the 4-digit Standard Industrial
Classification (SIC) codes that make up the MP&M industry
sectors. These codes were used until recently to define
industries for reporting of Federal Census and other data,
CHAPTER CONTENTS:
A.I MP&M SIC and NAICS Codes A-l
A.2 Annual Establishment "Births" and "Deaths"
in MP&M Industries A-30
A.3 Description of MP&M Surveys A-33
A.3.1 Screener Surveys A-33
A.3.2 Ohio Screener Surveys A-33
A.3.3 Detailed MP&M Industry Surveys A-33
A.3.4 Iron and Steel Survey A-33
A.3.5 Municipality Survey A-33
A.3.6 Federal Facility Survey A-34
A.3.7 POTW Survey A-34
References A-35
and are the basis for the portion of the industry profile that
was prepared from publically available materials in
Chapters.
Table A.I: MP&M Sectors and SIC Codes
.....................1[[[
SIC Code Standard Industrial Classification Groups
Aerospace
...................... [[[
3761 Guided Missiles and Space Vehicles
3764 Guided Missile and Space Vehicle Propulsion
3769 Other Space Vehicle and Missile Parts
Aircraft
3721 Aircraft
3724 Aircraft Engines and Engine Parts
3728 Aircraft Parts and Auxiliary Equipment
4581 Airports, Flying Fields, Airport Terminal Services
Bus And Truck
3713 Truck and Bus Bodies
...................... [[[
3715 Truck Trailers
...................... [[[
4111 Local And Suburban Transit
-------
MP&M EEBA: Appendices
Appendix A: Detailed Economic Impact Analysis Information
Table A.I: MP&M Sectors and SIC Codes
.....................1[[[
SIC Code Standard Industrial Classification Groups
4142 Bus Charter Service, Except Local
4173 Bus Terminal And Service Facilities
4212 Local Trucking without Storage
4213 Trucking, Except Local
4214 Local Trucking with Storage
4215 Courier Services, Except by Air
4231 Trucking Terminal Facilities
Electronic Equipment
...................... [[[
3661 Telephone and Telegraph Apparatus
3663 Radio and Television Broadcast and Communications Equipment
3669 Communications Equipment, N.E.C.
3671 Electron Tubes
3675 Electronic Capacitors
3677 Electronic Coils and Transformers
3678 Connectors for Electronic Applications
3679 Electronic Components, N.E.C.
3699 Electrical Machinery, Equipment, And Supplies, N.E.C.
Hardware
2796 Platemaking and Related Services
3398 Metal Heat Treating
3412 Metal Shipping Barrels, Drums, Kegs, Pails
3421 Cutlery
3423 Hand And Edge Tools, Except Machine Tools and Handsaws
3425 Hand Saws and Saw Blades
3429 Hardware, N.E.C.
3433 Heating Equipment, Except Electric and Warm Air Furnace
3441 Fabricated Structural Metal
3443 Fabricated Plate Work (Boiler Shops)
3444 Sheet Metal Work
3446 Architectural and Ornamental Metal Work
3448 Prefabricated Metal Buildings And Components
3449 Miscellaneous Metal Work
3451 Screw Machine Products
3452 Bolts, Nuts, Screws, Rivets, and Washers
3462 Iron and Steel Forgings
3466 Crowns and Closures
3469 Metal Stamping, N.E.C.
3492 Fluid Power Valves and Hose Fittings
3493 Steel Springs
3494 Valves And Pipe Fittings, Except Brass
-------
MP&M EEBA: Appendices
Appendix A: Detailed Economic Impact Analysis Information
Table A.I: MP&M Sectors and SIC Codes
.....................1[[[
SIC Code Standard Industrial Classification Groups
3541 Machine Tools, Metal Cutting Types
3542 Machine Tools, Metal Forming Types
3544 Special Dies and Tools, Die Sets, Jigs and Fixtures, and Industrial Molds
3545 Machine Tool Access and Measuring Devices
3546 Power Driven Hand Tools
3965 Fasteners, Buttons, Needles, Pins
Household Equipment
...................... [[[
2514 Metal Household Furniture
2522 Office Furniture, Except Wood
2531 Public Building and Related Furniture
2542 Partitions and Fixtures, Except Wood
2591 Drapery Hardware and Window Blinds/shades
2599 Furniture and Fixtures, N.E.C.
3431 Metal Sanitary Ware
3432 Plumbing Fittings and Brass Goods
3442 Metal Doors, Sash, and Trim
3631 Household Cooking Equipment
3632 Household Refrigerators and Home and Farm and Freezers
3633 Household Laundry Equipment
3634 Electric Housewares and Fans
3635 Household Vacuum Cleaners
3639 Household Appliances, N.E.C.
3641 Electric Lamps
3643 Current-carrying Wiring Devices
3644 Noncurrent-carrying Wiring Devices
3645 Residential Electrical Lighting Fixtures
3646 Commercial, Industrial, and Institutional
3648 Lighting Equipment, N.E.C.
3651 Radio/television Sets Except Communication Types
7623 Refrigeration and Air-conditioning Service and Repair Shops
Instruments
3812 Search, Detection, Navigation, Guidance, Aeronautical, Nautical Systems and Instruments
3821 Laboratory Apparatus and Furniture
3822 Automatic Environmental Controls
3823 Process Control Instruments
3824 Fluid Meters and Counting Devices
3825 Instruments to Measure Electricity
3826 Laboratory Analytical Instruments
3827 Optical Instruments and Lenses
3829 Measuring and Controlling Devices, N.E.C.
3841 Surgical and Medical Instruments and Apparatus
-------
MP&M EEBA: Appendices
Appendix A: Detailed Economic Impact Analysis Information
Table A.I: MP&M Sectors and SIC Codes
.....................1[[[
SIC Code Standard Industrial Classification Groups
3845 Electromedical Equipment
3851 Ophthalmic Goods
7629 Electric Repair Shop
Iron and Steel
...................... [[[
3315 Steel Wiredrawing and Steel Nails and Spikes
3316 Cold-Rolled Steel Sheet, Strip, and Bars
3317 Steel Pipe and Tubes
Job Shop
3471 Plating and Polishing
3479 Metal Coating and Allied Services
Mobile Industrial Equipment
3523 Farm Machinery and Equipment
...................... [[[
3524 Garden Tractors and Lawn and Garden Equipment
...................... [[[
3531 Construction Machinery and Equipment
...................... [[[
3532 Mining Machinery and Equipment, Except Oil Field
...................... [[[
3536 Hoists, Industrial Cranes and Monorails
...................... [[[
3537 Industrial Trucks, Tractors, Trailers
...................... [[[
3795 Tanks and Tank Components
Motor Vehicle
immmmmmmmmmmmmmmmmmmmm mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm,
3465 Automotive Stampings
3592 Carburetors, Piston Rings, Valves
3647 Vehicular Lighting Equipment
3694 Electrical Equipment for Motor Vehicles
3711 Motor Vehicle and Automobile Bodies
3714 Motor Vehicle Parts and Accessories
3716 Mobile Homes
3751 Motorcycles
3792 Travel Trailers and Campers
3799 Miscellaneous Transportation Equipment
-------
MP&M EEBA: Appendices
Appendix A: Detailed Economic Impact Analysis Information
Table A.I: MP&M Sectors and SIC Codes
.....................1[[[
SIC Code Standard Industrial Classification Groups
7549 Auto Services, Except Repair and Carwashes
Office Machine
...................... [[[
3571 Electronic Computers
3 5 72 Typewriters
3575 Computer Terminals
3577 Computer Peripheral Equipment, N.E.C.
3578 Calculating, Accounting Machines Except Computers
3579 Office Machines, N.E.C.
7378 Computer Maintenance and Repairs
7379 Computer Related Services, N.E.C.
Ordnance
3482 Small Arms Ammunition
3483 Ammunition, Except for Small Arms
3484 Small Arms
3489 Ordnance and Accessories, N.E.C.
Other Metal Products
3497 Metal Foil and Leaf
...................... [[[
3861 Photographic Equipment and Supplies
...................... [[[
3931 Musical Instruments
...................... [[[
3944 Games, Toys, Children's Vehicles
...................... [[[
3949 Sporting and Athletic Goods, N.E.C.
...................... [[[
3951 Pens and Mechanical Pencils
...................... [[[
3953 Marking Devices
...................... [[[
3993 Signs and Advertising Displays
...................... [[[
3995 Burial Caskets
...................... [[[
3999 Manufacturing Industries, N.E.C.
...................... [[[
7692 Welding Repair
...................... [[[
7699 Repair Shop, Related Serv
Precious Metals and Jewelry
-------
MP&M EEBA: Appendices
Appendix A: Detailed Economic Impact Analysis Information
Table A.I: MP&M Sectors and SIC Codes
.....................1[[[
SIC Code Standard Industrial Classification Groups
4412 Deep Sea Foreign Transportation
4424 Deep Sea Domestic Transportation
4432 Freight Transportation Great Lakes
4449 Water Transportation of Freight, N.E.C.
4481 Deep Sea Passenger Transportation
4482 Ferries
4489 Water Passenger Transportation, N.E.C.
4491 Marine Cargo Handling
4492 Towing and Tugboat Service
4493 Marinas
4499 Water Transportation Services, N.E.C.
Stationary Industrial Equipment
...................... [[[
3511 Steam, Gas, Hydraulic Turbines, Generating Units
3519 Internal Combustion Engines, N.E.C.
3533 Oil Field Machinery and Equipment
3534 Elevators and Moving Stairways
3535 Conveyors and Conveying Equipment
3543 Industrial Patterns
3547 Rolling Mill Machinery and Equipment
3548 Electric and Gas Welding and Soldering
3549 Metal Working Machinery, N.E.C.
3552 Textile Machinery
3553 Woodworking Machinery
3554 Paper Industries Machinery
3555 Printing Trades Machinery and Equipment
3556 Food Products Machinery
3559 Special Industry Machinery, N.E.C.
3561 Pumps and Pumping Equipment
3562 Ball and Roller Bearings
3563 Air and Gas Compressors
3564 Blowers and Exhaust and Ventilation Fans
3565 Industrial Patterns
3566 Speed Changers, High Speed Drivers and Gears
3567 Industrial Process Furnaces and Ovens
3568 Mechanical Power Transmission Equipment, N.E.C.
3569 General Industrial Machinery, N.E.C.
3581 Automatic Merchandising Machines
3582 Commercial Laundry Equipment
3585 Refrigeration and Air and Heating Equipment
3586 Measuring and Dispensing Pumps
-------
MP&M EEBA: Appendices
Appendix A: Detailed Economic Impact Analysis Information
SIC Code
3599
3612
3613
3621
3629
7353
7359
Table A.I: MP&M Sectors and SIC Codes
Standard Industrial Classification Groups
Machinery, Except Electrical, N.E.C.
Transformers
Switchgear and Switchboard Apparatus
Motors and Generators
Electric Industrial Apparatus, N.E.C.
Heavy Construction Equip Rental, Leasing
Equipment Rental, Leasing, N.E.C.
N.E.C. = Not Elsewhere Classified
Source: Executive Office of the President, Office of Management and Budget, Standard Industrial Classification Manual 1987
In 1997, the Census Bureau has adopted the new North
American Industry Classification System to replace the SIC
codes. NAICS codes will be used throughout North American.
The new system allows for greater comparability with the
International Standard Industrial Classification System (ISIC),
which is developed and maintained by the United Nations. The
new system also better reflects the structure of today's economy,
including the growth of the service sectors and new technologies,
than does the decades-old SIC system.
The switch to the NAICS makes it difficult to report historic;
trends for some industries when there is more than one NAK
code for a single SIC code or more than one SIC code for a
single NAICS code. If a one-to-one relationship exists betwe
a 4-digit SIC and a new NAICS code, combining data based i
the two systems poses no difficulties.
Table A.2 provides the cross-walk between SIC codes and th
new NAICS codes.
A-7
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
2514 j Household Eq. j Metal Household Furniture
2522 i Household Eq. i Office Furniture, Except Wood
. , . , 1 , . , _ 1 Public Buildng & Relatd
2531 i Household Eq. : fe
: Furniture
. , . , 1 , . , _ 1 Public Buildng & Relatd
2531 i Household Eq. : fe
: Furniture
. , . , 1 , . , _ 1 Public Buildng & Relatd
2531 i Household Eq. : fe
: Furniture
2542 i Household Eq. i Partitions & Fixtures, Exc Wood
icm 'TT i, UT- ' Drapery Hrdwr and Window
2591 : Household Eq. :.. j /. ,
H i Blinds/Shades
2599 j Household Eq. ! Furniture and Fixtures, N.E.C.
2599 i Household Eq. i Furniture and Fixtures, N.E.C.
i . i Platemaking and Related
2796 i Hardware ; 5
: : Services
3398 i Hardware i Metal Heat Treating
-.,_ iTT , i Metal Shipping Barrels, Drums,
3412 : Hardware : _ ., fe
: Kegs, Pails
3421 I Hardware j Cutlery
- , _ - i T T , ' Hand & Edge Tools, Except
3423 : Hardware : , , . _ . fe ^
: Mach. Tools, Saws
i i
3425 i Hardware i Hand Saws and Saw Blades
3429 j Hardware ! Hardware NEC
3429 j Hardware ! Hardware NEC
3429 j Hardware j Hardware NEC
3431 I Household Eq. j Metal Sanitary Ware
1997 NAICS j
Code j 1997 NAICS Industry
33712400 I Metal household furniture manufacturing
33721400 Office furniture (except wood) manufacturing
->->r->->r> = Motor vehicle seating and interior trim
33636030 f +, , ^\
: manulacturing (part)
33712710 ! Institutional furniture manufacturing (part)
33994210 ! Lead pencil and art goods manufacturing (part)
--_, . .. i Showcase, partition, shelving, and locker
JJ/2iJj(j ฃ. . / :\
: manulacturing (part)
33792000 i Blind and shade manufacturing
33712720 I Institutional furniture manufacturing (part)
-5 -: n 1 1-31 r\ ': Surgical appliance and supplies manufacturing
jjyiuiu , ^,
i(part)
323 12220 i Prepress services (part)
33281100 I Metal heat treating
33243910 I Other metal container manufacturing (part)
33221 110 '* Cutlery and flatware (except precious)
i manufacturing (part)
3 322 1 2 1 0 I Hand and edge tool manufacturing (part)
I
33221300 Saw blade and handsaw manufacturing
33243920 | Other metal container manufacturing (part)
33251010 Hardware manufacturing (part)
-j -j i n i n i n i Other metal valve and pipe fitting manufacturing
j jLy iy 1U ; , ,
:(part)
-j-jinnonn i Enameled iron and metal sanitary ware
jjzyyouu .-
: manulactunng
Number of
Establishments,
1997
420
359
184
267
17
926
488
727
16
1,276
808
151
164
1,069
176
117
952
16
88
Sales,
Shipments or
Receipts, 1997
($1,000)
2,422,853
8,230,935
6,060,320
1,697,870
110,985
5,249,474
2,393,564
2,305,770
645,688
2,663,020
3,485,459
1,310,595
2,198,365
5,677,903
1,452,540
402,378
10,359,952
n/a
1,575,505
Number of
Employees,
1997
22,835
44,222
20,784
15,254
941
44,472
19,617
22,448
2,925
24,942
22,674
6,318
11,129
42,947
9,149
4,135
70,884
n/a
9,994
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC
3432
3432
3433
3441
3442
3443
3443
3443
3443
3444
3444
3446
3448
3449
3449
3449
3449
3451
3452
MP&M Sector i Industry
,, . ., i Plumbing Fittings and Brass
Household Eq. Ir d
,, . ., i Plumbing Fittings and Brass
Household Eq. Ir d
,, , iHeatg. Equip. Except Elec. &
Hardware , \-r
: Warm Air Fmc.
Hardware j Fabricated Structural Metal
Household Eq. i Metal Doors, Sash, and Trim
, ! Fabricated Plate Work (Boiler
Hardware !, , v
: Shops)
, ! Fabricated Plate Work (Boiler
Hardware !, , v
: Shops)
, ! Fabricated Plate Work (Boiler
Hardware !, , v
: Shops)
, ! Fabricated Plate Work (Boiler
Hardware : . .
i Shops)
Hardware i Sheet Metal Work
Hardware ! Sheet Metal Work
,, , i Architectural and Ornamental
Hardware i, , , . , .
i Metal Work
,, , i Prefabricated Metal Buildings &
Hardware ! ,
: Components
Hardware i Miscellaneous Metal Work
Hardware j Miscellaneous Metal Work
Hardware i Miscellaneous Metal Work
Hardware i Miscellaneous Metal Work
Hardware j Screw Machine Products
,, , i Bolts, Nuts, Screws, Rivets, and
Hardware !, .
: Washers
1997 NAICS j
Code j 1997 NAICS Industry
33291300 jPlumbing fixture fitting and trim manufacturing
,,.. i All other miscellaneous fabricated metal product
i manufacturing (part)
m/n/nn i Heating equipment (except warm air furnaces)
JJJ4141U ,- , / .\
: manufacturing (part)
33231210 JFabricated structural metal manufacturing (part)
33232120 Metal window and door manufacturing (part)
33231300 i Plate work manufacturing
3 324 1 000 ! Power boiler and heat exchanger manufacturing
33242000 ! Metal tank (heavy gauge) manufacturing
I Air-conditioning and warm air heating equipment
33341510 i and commercial and industrial refrigeration
I equipment manufacturing (part)
33232200 i Sheet metal work manufacturing
33243930 | Other metal container manufacturing (part)
0 0 - 0 - 0 , : Ornamental and architectural metal work
33232310 ,. , . , ,,
: manufacturing (part)
': Prefabricated metal building and component
3323 1 100 *- .
: manufactunng
33211400 I Custom roll forming
3323 1220 I Fabricated structural metal manufacturing (part)
33232130 Metal window and door manufacturing (part)
------. 1 Ornamental and architectural metal work
Jj2j2j2(j ,- , / .\
: manufacturing (part)
3 3272 1 00 I Precision turned product manufacturing
33272200 i Bolt, nut, screw, rivet, and washer manufacturing
Number of
Establishments,
1997
116
5
453
2,900
1,384
1,035
472
614
9
4,479
126
1,744
604
401
152
33
6
2,745
1,040
Sales,
Shipments or
Receipts, 1997
($1,000)
3,590,128
118,059
3,387,391
14,200,270
9,876,049
2,806,913
3,849,100
4,764,118
43,264
15,957,992
275,440
3,536,413
4,199,550
3,074,662
2,166,021
364,564
91,939
8,326,077
8,134,661
Number of
Employees,
1997
16,202
474
22,495
84,704
2,970
25,453
27,542
33,704
339
129,826
2,074
30,960
25,946
15,219
8,729
1,974
349
80,404
52,995
A-9
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
3462 j Hardware j Iron and Steel Forgings
3465 i Motor Vehicle i Automotive Stampings
3466 j Hardware j Crowns and Closures
3469 i Hardware i Metal Stamping NEC
3469 j Hardware j Metal Stamping NEC
3471 i Job Shop i Plating and Polishing
3479 i Job Shop i Metal Coating & Allied Services
3479 j Job Shop j Metal Coating & Allied Services
3479 j Job Shop j Metal Coating & Allied Services
3479 i Job Shop i Metal Coating & Allied Services
3482 i Ordnance i Small Arms Ammunition
-> A 01 -^ j ' Ammunition, Except for Small
3483 i Ordnance i . > r
:Arms
3484 j Ordnance j Small Arms
3489 i Ordnance i Ordnance and Accessories NEC
..,:,,, i Fluid Power Valves and Hose
3492 i Hardware : ....
: Fittings
3493 j Hardware j Steel Springs
IM\A :^^ j i Valves & Pipe Fittings, Except
3494 i Hardware ' ^ b ^
: : Brass
IM\A :^^ j i Valves & Pipe Fittings, Except
3494 i Hardware ' ^ b ^
: : Brass
3495 i Hardware i Wire Springs
3495 j Hardware j Wire Springs
-,M\S :^^ j i Miscellaneous Fabricated Wire
3496 i Hardware ! , ,
: : Products
3497 j Other j Metal Foil and Leaf
1997 NAICS j
Code j 1997 NAICS Industry
33211100 I Iron and steel forging
33637000 Motor vehicle metal stamping
3321 1500 I Crown and closure manufacturing
33211600 I Metal stamping
3 322 1 400 I Kitchen utensil, pot, and pan manufacturing
'Electroplating, plating, polishing, anodizing, and
33281300 ,
: colonng
i Metal coating, engraving (except jewelry and
I silverware), and allied services to manufacturers
33991 1 10 Jewelry (except costume) manufacturing (part)
33991210 I Silverware and plated ware manufacturing (part)
i Costume jewelry and novelty manufacturing
I (part)
33299200 i Small arms ammunition manufacturing
33299300 i Ammunition (except small arms) manufacturing
33299400 | Small arms manufacturing
33299500 i Other ordnance and accessories manufacturing
inm -i i n i Fluid power valve and hose fitting manufacturing
j j2y IzlU : , ,x
:(part)
33261100 I Spring (heavy gauge) manufacturing
i Other metal valve and pipe fitting manufacturing
I (part)
i All other miscellaneous fabricated metal product
I manufacturing (part)
33261200 Spring (light gauge) manufacturing
33451810 jWatch, clock, and parts manufacturing (part)
': Other fabricated wire product manufacturing
33261830 i , ,x
i(part)
i Laminated aluminum foil manufacturing for
32222500 i n -i i i
: flexible packaging uses
Number of
Establishments,
1997
421
810
67
2,166
77
3,404
2,156
22
12
16
113
53
198
70
424
129
222
23
394
2
1,253
43
Sales,
Shipments or
Receipts, 1997
($1,000)
4,924,426
23,668,110
969,982
12,041,638
1,369,914
5,979,405
8,460,896
5,798
6,296
2,257
938,818
1,497,045
1,251,792
1,750,485
6,602,909
761,711
2,753,397
73,983
2,481,151
n/a
4,587,656
1,546,143
Number of
Employees,
1997
26,432
126,905
4,682
93,086
7,724
74,640
55,904
79
103
29
6,863
9,427
9,907
12,285
37,132
5,381
17,652
564
18,798
n/a
41,821
4,967
A-10
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
3497 I Other j Metal Foil and Leaf
.. i,, , i Fabricated Pipe and Fabricated
3498 i Hardware ;. .,,. F
: Pipe Fitting
3499 j Hardware j Fabricated Metal Products NEC
3499 i Hardware i Fabricated Metal Products NEC
3499 j Hardware j Fabricated Metal Products NEC
3499 i Hardware i Fabricated Metal Products NEC
3499 i Hardware i Fabricated Metal Products NEC
3499 i Hardware i Fabricated Metal Products NEC
3499 i Hardware i Fabricated Metal Products NEC
i Stationary Ind. j Steam, Gas, Hydraul. Turbines,
j Eq. j Gen. Units
i Stationary Ind. j Internal Combustion Engines
JEq. JNEC
i Stationary Ind. j Internal Combustion Engines
JEq. JNEC
3523 i Mobile Ind. Eq. i Farm Machinery and Equipment
3523 i Mobile Ind. Eq. i Farm Machinery and Equipment
3523 j Mobile Ind. Eq. j Farm Machinery and Equipment
3523 i Mobile Ind. Eq. i Farm Machinery and Equipment
,,_. i,,... T , T, i Garden Tractors & Lawn &
3524 i Mobile Ind. Eq. ! , ^ .
: H : Garden Equipment
,,_. i,,... T , T, i Garden Tractors & Lawn &
3524 i Mobile Ind. Eq. ! , ^ .
: H : Garden Equipment
1997 NAICS j
Code j 1997 NAICS Industry
33799940 ^^ other miscellaneous fabricated metal product
i manufacturing (part)
33799670 '* Plicated pipe and pipe fitting manufacturing
I (part)
3 32 1 1 700 I Powder metallurgy parts manufacturing
33243940 i Other metal container manufacturing (part)
33251020 JHardware manufacturing (part)
i Other metal valve and pipe fitting manufacturing
I (part)
i All other miscellaneous fabricated metal product
I manufacturing (part)
--_,.. . . i Showcase, partition, shelving, and locker
33/21340 *- . , .ป
: manufacturing (part)
i Costume jewelry and novelty manufacturing
I (part)
i Turbine and turbine generator set unit
I manufacturing
33361810 ! Other engine equipment manufacturing (part)
i All other motor vehicle parts manufacturing
I (part)
3 322 1 220 Hand and edge tool manufacturing (part)
------. 1 Ornamental and architectural metal work
Jj2j2jj(j ฃ. . / :\
: manutacturing (part)
33311100 I Farm machinery and equipment manufacturing
: Conveyor and conveying equipment
33392210 *- . , .ป
: manufacturing (part)
33221230 ! Hand and edge tool manufacturing (part)
': Lawn and garden tractor and home lawn and
333 1 1200 , , *- .
: garden equipment manufacturing
Number of
Establishments,
1997
64
856
128
98
58
7
2,592
78
82
86
297
7
1
140
1,339
28
3
145
Sales,
Shipments or
Receipts, 1997
($1,000)
1,711,600
4,024,999
1,317,301
273,541
435,815
n/a
7,558,137
123,057
49,953
5,783,057
n/a
123,954
n/a
380,152
15,921,455
33,377
n/a
7,454,511
Number of
Employees,
1997
5,648
29,364
10,760
2,331
3,401
n/a
63,736
1,295
568
19,529
n/a
896
n/a
3,082
66,370
320
n/a
28,617
A-ll
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
3531 j Mobile Ind. Eq. j Constr Mach and Eq.
3531 i Mobile Ind. Eq. i Constr Mach and Eq.
3531 i Mobile Ind. Eq. i Constr Mach and Eq.
TCI-. U,r t_-i T j T- i Mining Mach. & Equip., Except
3532 i Mobile Ind. Eq. ;.. . ฐ, H F F
H i Oil Field
, . , , i Stationary Ind. i Oil Field Machinery and
i Eq. i Equipment
.... i Stationary Ind. :. , , ,, . , .
3534 ip J i Elevators and Moving Stairways
, . , . i Stationary Ind. j Conveyors and Conveying
i Eq. i Equipment
ICIA U,r t_-i T j T- i Hoists, Industrial Cranes &
3536 i Mobile Ind. Eq. i,, ..
: Monorails
TCTT i-m- t_-i T j T- i Industrial Trucks, Tractors,
3537 i Mobile Ind. Eq. i^ ,
: Trailers
TCTT i-m- t_-i T j T- i Industrial Trucks, Tractors,
3537 i Mobile Ind. Eq. i^ ,
: Trailers
TCTT i-m- t_-i T j T- i Industrial Trucks, Tractors,
3537 i Mobile Ind. Eq. ' ..
: Trailers
.-.,:,,, i Machine Tools, Metal Cutting
3541 i Hardware ' ฐ
: Types
.-.,:,,, i Machine Tools, Metal Forming
3542 i Hardware : fe
: Types
.... i Stationary Ind. i , , ,.,,,
3543 : J i Industrial Patterns
:Eq.
....:,,, i Special Dies & Tools, Die Sets,
3544 i Hardware i T. ,
: Jigs, Etc.
....:,,, i Special Dies & Tools, Die Sets,
3544 i Hardware i T. ,
: Jigs, Etc.
.... i,, , i Machine Tool Access &
3545 i Hardware i,, . .
: Measunng Devices
3545 j Hardware ! Machine Tool Access &
1997 NAICS j
Code j 1997 NAICS Industry
33312000 I Construction machinery manufacturing
: Overhead traveling crane, hoist, and monorail
jjjyzjio , *- . , .ป
: system manufacturing (part)
33651010 Railroad rolling stock manufacturing (part)
33313100 ! Mining machinery and equipment manufacturing
i-m-nnn 1 Oil an^ 8as fi6!^ machinery and equipment
JJJij2(j(j ฃ. .
: manulactunng
3 3 3 92 1 00 ! Elevator and moving stairway manufacturing
-----. 1 Conveyor and conveying equipment
jjjy222(j r. . / ,\
: manulactunng (part)
-----. 1 Overhead traveling crane, hoist, and monorail
Jjjy2j2(j . r. . , .-.
: system manulactunng (part)
33243950 i Other metal container manufacturing (part)
,,. i All other miscellaneous fabricated metal product
i manufacturing (part)
---.. i Industrial truck, tractor, trailer, and stacker
Jjjyz4uu , . r. .
: machinery manulactunng
mcmn i Machine tool (metal cutting types) manufacturing
jjjj[2i(j : , .-.
:(part)
mcnnn i Machine tool (metal forming types)
JJJjlJUU ฃ. .
: manulactunng
33299700 i Industrial pattern manufacturing
33351100 ! Industrial mold manufacturing
1 1 1 * i A nn i Special die and tool, die set, jig, and fixture
JJJjl4UU r .
: manulactunng
3 322 1 240 ! Hand and edge tool manufacturing (part)
33351 500 I Cutting tool and machine tool accessory
Number of
Establishments,
1997
785
87
25
292
563
196
871
220
4
19
461
393
225
673
2,529
4,746
185
1,920
Sales,
Shipments or
Receipts, 1997
($1,000)
21,965,455
1,805,198
346,760
2,710,923
6,240,079
1,607,066
6,346,525
1,340,561
6,775
27,488
5,538,326
5,183,521
2,255,011
623,927
5,116,635
8,244,855
714,277
5,347,173
Number of
Employees,
1997
74,965
10,263
2,379
13,547
29,451
9,442
39,279
7,751
64
240
25,953
28,849
14,185
7,959
48,657
80,113
6,379
47,925
A-12
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
! Measuring Devices
3546 i Hardware i Power Driven Hand Tools
, . ._ i Stationary Ind. j Rolling Mill Machinery and
i Eq. i Equipment
, . . i Stationary Ind. j Elec and Gas Welding and
i Eq. i Soldering
, . . i Stationary Ind. j Elec and Gas Welding and
i Eq. i Soldering
3549 j Stationary Ind. 1 Metal Working Machinery NEC
i Eq. fe J
.... i Stationary Ind. : ... ,, ..
3552 ip J i Textile Machinery
.--. i Stationary Ind. :, , .. , , ..
3553 ip J i Woodworking Machinery
.... i Stationary Ind. : T , , . , , ..
3554 ip J i Paper Industries Machinery
, . . . i Stationary Ind. j Printing Trades Machinery and
i Eq. i Equipment
.-., i Stationary Ind. : , _ , , ,, .
3556 : J i Food Products Mach
:Eq.
3559 j Stationary Ind. j Speclal Industry Machmery ^c
:iiq.
3559 j Stationary Ind. j Speclal Industry Machmery ^c
:iiq.
3559 j Stationary Ind. j Speclal Industry Machmery ^c
:iiq.
3559 j Stationary Ind. j Speclal Industry Machmery ^c
:iiq.
.-,, i Stationary Ind. : , _ .
3561 ip J i Pumps and Pumping Equipment
:iiq.
.-,. i Stationary Ind. : ,
3562 : J i Ball and Roller Bearings
iEq. fe
3563 j Stationary Ind. j Air and Gas Compressors
1997 NAICS j
Code j 1997 NAICS Industry
I manufacturing
33399100 Power-driven handtool manufacturing
-..-., i Rolling mill machinery and equipment
JJJjlOUU r. .
: manutactunng
33399? 1 0 '* ^e^m8 and soldering equipment manufacturing
I (part)
iizimn i Power, distribution, and specialty transformer
J J J J 111U ฃ. . / :\
: manutactunng (part)
33351800 ! Other metalworking machinery manufacturing
33329210 ! Textile machinery manufacturing (part)
---.. i Sawmill and woodworking machinery
JJj2i(j(j(j ฃ. .
: manutactunng
33329100 ! Paper industry machinery manufacturing
1 1 11 m i n i Printing machinery and equipment manufacturing
jjjZyj 1U : , ,x
:(part)
33329400 i Food product machinery manufacturing
----. 1 Plastics and rubber industry machinery
jjj22(j(j(j r. .
: manutactunng
33329500 i Semiconductor machinery manufacturing
11 1 -i r, o m 1 All other industrial machinery manufacturing
jjj2yoi(j : , ,,
:(part)
1 1 1 1 1 r, i n i Other commercial and service industry machinery
JJJJiyiU ฃ. . / :\
: manutactunng (part)
mnmn i PumP and pumping equipment manufacturing
JJjyillU ;, ,x
:(part)
33299100 ! Ball and roller bearing manufacturing
33391200 I Air and gas compressor manufacturing
Number of
Establishments,
1997
217
100
244
0
474
478
327
366
546
597
455
257
1,677
78
489
185
314
Sales,
Shipments or
Receipts, 1997
($1,000)
3,609,779
700,084
4,433,877
0
3,463,811
1,779,034
1,321,752
3,438,235
n/a
2,877,841
3,584,992
11,158,627
n/a
644,019
6,826,043
6,120,940
5,633,008
Number of
Employees,
1997
16,816
4,149
22,434
0
19,023
13,600
9,117
18,594
n/a
19,026
18,574
40,087
n/a
2,890
36,552
36,991
24,821
A-13
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
JEq.
i Stationary Ind. i Blowers and Exhaust and
j Eq. j Ventilation Fans
i Stationary Ind. i Blowers and Exhaust and
j Eq. j Ventilation Fans
--,- i Stationary Ind. i, , ,-,,,,,
3565 ^ Industrial Patterns
:Eq.
i Stationary Ind. i Speed Changers, High Speed
j Eq. j Drivers & Gears
. , ,_ i Stationary Ind. i Industrial Process Furnaces and
jjo / i^ !
: Eq. : Ovens
i Stationary Ind. j Mechanical Power Transmission
j Eq. j Equip. NEC
i Stationary Ind. i General Industrial Machinery
3j69 i T^ i-KTT^^
iEq. iNEC
3571 i Office Machine i Electronic Computers
3572 j Office Machine j Typewriters
3575 i Office Machine i Computer Terminals
3577 i Office Machine i Computer Peripheral Eq NEC
.._ :. ,, .. i Calculating, Accting Mach
3578 i Office Machine , fe ' fe
: except Computers
.._ :. ,, .. i Calculating, Accting Mach
3578 i Office Machine , fe ' fe
: except Computers
3579 j Office Machine j Office Machines, N.E.C.
3579 j Office Machine ! Office Machines, N.E.C.
3579 j Office Machine j Office Machines, N.E.C.
i Stationary Ind. j Automatic Merchandising
3 JO 1 T^ ! n ,r 1
: Eq. : Machines
-co, i Stationary Ind. : . ., , .
3582 ip i Commercial Laundry Equipment
3585 i Stationary Ind. i Refrigeration & Air and Heating
1997 NAICS j
Code j 1997 NAICS Industry
I
33341100 ! Air purification equipment manufacturing
i Industrial and commercial fan and blower
I manufacturing
33399300 i Packaging machinery manufacturing
': Speed changer, industrial high-speed drive, and
JJJolzOO i *- .
: gear manufacturing
i Industrial process furnace and oven
I manufacturing
i Mechanical power transmission equipment
I manufacturing
i All other miscellaneous general-purpose
I machinery manufacturing (part)
33411100 Electronic computer manufacturing
33411200 I Computer storage device manufacturing
3341 1300 Computer terminal manufacturing
33411910 '* Oth61 comPuter peripheral equipment
i manufacturing (part)
33331310 ! Office machinery manufacturing (part)
33411970 '* Oth61 comPuter peripheral equipment
i manufacturing (part)
33331320 I Office machinery manufacturing (part)
3345 1 820 Watch, clock, and parts manufacturing (part)
33994220 | Lead pencil and art goods manufacturing (part)
33331100 ! Automatic vending machine manufacturing
-m-n inn ': Commercial laundry, drycleaning, and pressing
JJJJ1200 , *- .
: machine manufacturing
33341520 Air-conditioning and warm air heating equipment
Number of
Establishments,
1997
370
204
689
268
404
299
1,257
563
211
142
1,006
35
61
134
16
13
121
68
792
Sales,
Shipments or
Receipts, 1997
($1,000)
2,174,729
1,901,196
4,858,270
2,402,392
2,871,475
3,301,091
7,991,746
66,331,909
13,907,367
1,483,460
25,130,308
144,380
1,870,426
3,047,549
n/a
257,020
1,325,960
604,966
22,846,865
Number of
Employees,
1997
16,183
13,723
31,581
16,231
17,585
21,604
50,088
100,115
42,364
5,764
87,253
966
6,717
13,865
n/a
1,234
8,178
4,523
119,456
A-14
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
i Eq. i Equip.
. . . i Stationary Ind. j Refrigeration & Air and Heating
Jjoj : ^ : ^
: Eq. : Equip.
.., i Stationary Ind. j Measuring and Dispensing
JjoO : ^ IT-.
: Eq. : Pumps
3589 i^tionarylnd- | Servlce Industry Machines, NEC
3592 JMotorVehicle j C^buretors, Piston Rings,
: Valves
,-, i Stationary Ind. j Fluid Power Cylinders and
i Eq. i Actuators
... i Stationary Ind. ^I-JTI JTM +
3594 ip J i Fluid Power Pumps and Motors
,., i Stationary Ind. j Scales and Balances, except
i Eq. i Laboratory
,.qq i Stationary Ind. j Machinery, Except Electrical
JEq. JNEC
,.qq i Stationary Ind. i Machinery, Except Electrical
JEq. JNEC
,.qq i Stationary Ind. i Machinery, Except Electrical
JEq. JNEC
,.qq i Stationary Ind. i Machinery, Except Electrical
JEq. JNEC
. , , . i Stationary Ind. i
3612 : J i Transformers
:Eq.
,,., i Stationary Ind. i Switchgear and Switchboard
i Eq. i Apparatus
.,,, i Stationary Ind. i,,, , _
3621 : J i Motors and Generators
:Eq.
, ,. q i Stationary Ind. j Electric Industrial Apparatus
j Eq. j NEC
3631 j Household Eq. j Household Cooking Equipment
1997 NAICS j
Code j 1997 NAICS Industry
i and commercial and industrial refrigeration
i equipment manufacturing (part)
33639100 ! Motor vehicle air-conditioning manufacturing
33391300 iMeasuring and dispensing pump manufacturing
1 1 1 1 1 n-> n i Other commercial and service industry machinery
JJJJiy2(j ฃ. . / :\
: manutacturing (part)
lit;-! iinn \ Carburetor, piston, piston ring, and valve
j JQJ 1 1UU r. .
: manutactunng
,,,qq . . i Fluid power cylinder and actuator manufacturing
I (part)
3339961 0 '* ^u^ Power pump and motor manufacturing
I (part)
33399700 '* ^ca^e anc^ balance (except laboratory)
i manufacturing
33271000 ! Machine shops
,,-qqq_n i All other miscellaneous fabricated metal product
i manufacturing (part)
iiii i nin i Other commercial and service industry machinery
JJJJiyj(j ฃ. . / :\
: manutacturing (part)
,,,qqq-n i All other miscellaneous general-purpose
i machinery manufacturing (part)
nc-m i Power, distribution, and specialty transformer
JJjJllZU ฃ. . / :\
: manutacturing (part)
nc-mnn i Switchgear and switchboard apparatus
JJjJUUU ฃ. .
: manutactunng
33531210 ! Motor and generator manufacturing (part)
,, J.QQQI Q ! All other miscellaneous electrical equipment and
i component manufacturing (part)
3 3 522 1 00 I Household cooking appliance manufacturing
Number of
Establishments,
1997
60
71
1,165
141
320
170
122
23,619
132
50
836
318
583
528
413
84
Sales,
Shipments or
Receipts, 1997
($1,000)
5,626,596
1,316,899
7,596,253
2,755,311
3,528,906
2,712,058
682,940
27,143,131
506,611
172,536
1,146,348
4,716,162
7,609,164
11,788,281
2,838,366
3,543,231
Number of
Employees,
1997
21,522
6,824
44,172
17,518
23,062
15,482
4,871
290,951
4,199
1,335
11,063
26,638
41,291
71,112
18,682
17,543
A-15
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
-,-, i,, . ., i Household Refrig. & Home &
3632 i Household Eq. : r fe
: Farm & Freezers
3633 j Household Eq. j Household Laundry Equipment
3634 i Household Eq. i Electric Housewares and Fans
3634 i Household Eq. i Electric Housewares and Fans
3635 i Household Eq. i Household Vacuum Cleaners
3639 i Household Eq. i Household Appliances NEC
3639 j Household Eq. j Household Appliances NEC
3639 i Household Eq. i Household Appliances NEC
364 1 j Household Eq. j Electric Lamps
3643 i Household Eq. i Current-Carrying Wiring Devices
,,,.. iTT . .JT, i Noncurrent-Carrying Wiring
3644 i Household Eq. ; . J fe fe
: Devices
.,.. i,, . . , _ i Residential Electrical Lighting
3645 i Household Eq. ;. , & &
: Fixtures
.,., i,, . .,_ i Commercial, Industrial, and
3646 i Household Eq. iT ... ,. .
: Institutional
3647 j Motor Vehicle ! Vehicular Lighting Equipment
3648 i Household Eq. i Lighting Equipment NEC
.,,. i,, . .,_ i Radio/Television Sets Except
3651 i Household Eq. ; r
: Commun. Types
.,,, :. , . _ i Telephone and Telegraph
3661 i Electronic Eq. A *
: Apparatus
.,,, :. , . _ i Telephone and Telegraph
3661 i Electronic Eq. A *
: Apparatus
.,,, :. , . _ i Telephone and Telegraph
3661 i Electronic Eq. A t
: Apparatus
.,,. i_. , . _ i Radio and Television Broadcast
3663 i Electronic Eq. ,
: and Comm Eq
1997 NAICS j
Code j 1997 NAICS Industry
---,,, i Household refrigerator and home freezer
jjj222(j(j ,- ,
: manutactunng
3 3 522400 | Household laundry equipment manufacturing
i Heating equipment (except warm air furnaces)
I manufacturing (part)
i Electric housewares and household fan
I manufacturing
33521210 Household vacuum cleaner manufacturing (part)
----. jAll other industrial machinery manufacturing
Jjj2yo2(j : , ,,
:(part)
3 3 52 1 220 I Household vacuum cleaner manufacturing (part)
33522800 i Other major household appliance manufacturing
33511000 I Electric lamp bulb and parts manufacturing
33593100 Current-carrying wiring device manufacturing
33593200 i Noncurrent-carrying wiring device manufacturing
1 1 * 1-1 n n i Residential electric lighting fixture
jjj[2i2(j ,- , / .\
: manutactunng (part)
---.,, i Commercial, industrial, and institutional electric
JJJi22(j(j I,- , , t~ : ฃ :
: lighting tixture manutactunng
33632100 I Vehicular lighting equipment manufacturing
33512910 Other lighting equipment manufacturing (part)
33431000 ! Audio and video equipment manufacturing
3 342 1 000 ! Telephone apparatus manufacturing
T, T.44 1 6 1 0 '* Electronic coil, transformer, and other inductor
i manufacturing (part)
n/i/noin i Printed circuit assembly (electronic assembly)
JJ441olU ,- , / .\
: manutactunng (part)
1 1 /n T n i n i Radio and television broadcasting and wireless
JJ4zzUlU ,- , ,- , , .-.
: communications equipment manutactunng (part)
Number of
Establishments,
1997
27
17
16
138
34
4
0
36
82
519
219
497
356
106
327
554
598
7
20
1,091
Sales,
Shipments or
Receipts, 1997
($1,000)
4,887,364
3,723,375
329,270
3,488,251
2,399,206
n/a
0
3,300,662
3,306,009
5,877,522
4,451,186
2,177,355
4,047,437
3,282,824
3,054,806
8,454,194
38,300,044
8,904
1,364,671
37,042,241
Number of
Employees,
1997
24,597
14,801
2,171
17,058
10,537
n/a
0
13,309
15,903
44,907
23,540
16,395
23,090
16,506
18,274
31,727
104,262
63
6,083
148,156
A-16
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
3669 j Electronic Eq. j Communications Eq, NEC
3671 i Electronic Eq. i Electron Tubes
3672 j Printed Circuits j Printed Circuit Boards
3675 i Electronic Eq. i Electronic Capacitors
., !. . i Electronic Coils and
3677 i Electronic Eq. '
: Transformers
-,rna IT-I t T- i Connectors for Electronic
3678 i Electronic Eq. ;. ....
: Applications
3679 i Electronic Eq. i Electronic Components NEC
3679 i Electronic Eq. i Electronic Components NEC
3679 j Electronic Eq. ! Electronic Components NEC
3679 i Electronic Eq. i Electronic Components NEC
_. i, , , ,,,-, i Electrical Equipment for Motor
3694 i Motor Vehicle i,, . . . H ^
: : Vehicles
i^ '1-1 i !- i Electronic Mach., Equipment, &
3699 i Electronic Eq. . -.-^^
H i Suppl. NEC
i^ '1-1 i !- i Electronic Mach., Equipment, &
3699 i Electronic Eq. , -.-^^
H i Suppl. NEC
i^ '1-1 i !- i Electronic Mach., Equipment, &
3699 i Electronic Eq. ! . -,.-,,-,,-,
H i Suppl. NEC
i^ '1-1 i !- i Electronic Mach., Equipment, &
3699 i Electronic Eq. , -.-^^
H i Suppl. NEC
i^ '1-1 i !- i Electronic Mach., Equipment, &
3699 i Electronic Eq. ! . -,.-,,-,,-,
H i Suppl. NEC
i^ '1-1 i !- i Electronic Mach., Equipment, &
3699 i Electronic Eq. , T.^^
H i Suppl. NEC
i^ '1-1 i !- i Electronic Mach., Equipment, &
3699 i Electronic Eq. , ^.T^^
H i Suppl. NEC
3699 i Electronic Eq. i Electronic Mach., Equipment, &
1997 NAICS j
Code j 1997 NAICS Industry
33429000 I Other communications equipment manufacturing
3 344 1 1 00 Electron tube manufacturing
3 344 1 200 I Bare printed circuit board manufacturing
3 344 1 400 Electronic capacitor manufacturing
,,...,. i Electronic coil, transformer, and other inductor
i manufacturing (part)
3 344 1 700 ! Electronic connector manufacturing
--.,,, i Radio and television broadcasting and wireless
JJ4zzUzU ,- , r. . , .-.
: communications equipment manutactunng (part)
ii/i/no^n ! Printed circuit assembly (electronic assembly)
JJ441OZU ฃ. . / :\
: manutactunng (part)
3 344 1 900 I Other electronic component manufacturing
- - , - , , , i Other motor vehicle electrical and electronic
33632210 . , ,. , . , ,,
: equipment manufactunng (part)
,,,,,,,., : Other motor vehicle electrical and electronic
33632220 , c ^ , ^
: equipment manufactunng (part)
33221250 ! Hand and edge tool manufacturing (part)
33329220 i Textile machinery manufacturing (part)
: Printing machinery and equipment manufacturing
33329320 i , ,x
i(part)
33331410 ! Optical instrument and lens manufacturing (part)
': Photographic and photocopying equipment
33331510 *- . , .ป
: manufacturing (part)
-,-,-,-,ir,Ar, ': Other commercial and service industry machinery
33331940 ,. , . - ,-
: manufacturing (part)
i Machine tool (metal cutting types) manufacturing
333 j 1220 i , ,x
i(part)
33361820 Other engine equipment manufacturing (part)
Number of
Establishments,
1997
497
159
1,401
129
426
347
126
695
1,851
253
569
4
0
5
5
0
57
8
2
Sales,
Shipments or
Receipts, 1997
($1,000)
4,233,288
3,858,499
9,787,576
2,482,163
1,512,232
5,598,906
2,265,873
24,704,154
10,547,090
1,420,996
9,074,335
140,811
0
n/a
7,320
0
934,728
151,363
n/a
Number of
Employees,
1997
25,187
21,976
76,702
18,882
19,178
37,232
16,305
104,971
92,200
12,786
52,216
424
0
n/a
56
0
8,513
522
n/a
A-17
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC
3699
3699
3699
3699
3699
3699
3699
3699
3699
3711
3711
3711
3711
3711
3713
3714
MP&M Sector i Industry
! Suppl. NEC
. , . _ i Electronic Mach., Equipment, &
Electronic Eq. ; . ..,,-,.-,
H i Suppl. NEC
. , . _ i Electronic Mach., Equipment, &
Electronic Eq. ! . -,.-,,-,,-,
H i Suppl. NEC
. , . _ i Electronic Mach., Equipment, &
Electronic Eq. ! . -,.-,,-,,-,
H i Suppl. NEC
T-,, , y, i Electronic Mach., Equipment, &
Electronic Eq. : . , = n r
H i Suppl. NEC
. , . _ i Electronic Mach., Equipment, &
Electronic Eq. i . , n r
H i Suppl. NEC
. , . _ i Electronic Mach., Equipment, &
Electronic Eq. i . , n r
H i Suppl. NEC
. , . _ i Electronic Mach., Equipment, &
Electronic Eq. i . , n r
H i Suppl. NEC
. , . _ i Electronic Mach., Equipment, &
Electronic Eq. i . , n r
H i Suppl. NEC
. , . _ i Electronic Mach., Equipment, &
Electronic Eq. i . , n r
H i Suppl. NEC
, , , , . . . . i Motor Vehicle and Automobile
Motor Vehicle ' ,.
: Bodies
, , , , . . . . i Motor Vehicle and Automobile
Motor Vehicle ' ,.
: Bodies
, , , , . . . . i Motor Vehicle and Automobile
Motor Vehicle ' ,.
: Bodies
, , , , . . . . i Motor Vehicle and Automobile
Motor Vehicle ' ,.
: Bodies
, , , , . . . . i Motor Vehicle and Automobile
Motor Vehicle ' ,.
: Bodies
Bus & Truck ! Truck and Bus Bodies
, , , , . . . . i Motor Vehicle Parts and
Motor Vehicle i .
: Accessories
1997 NAICS I
Code j 1997 NAICS Industry
I
i Welding and soldering equipment manufacturing
I (part)
i Other computer peripheral equipment
I manufacturing (part)
': Electromedical and electrotherapeutic apparatus
334jlUlU *- . , .ป
: manufacturing (part)
Search, detection, navigation, guidance,
33451 1 10 i aeronautical, and nautical system and instrument
i manufacturing (part)
ii/ifiฃin i Analytical laboratory instrument manufacturing
j J4j lolU : , ,x
:(part)
33451910 '* Oth61 measuring and controlling device
i manufacturing (part)
335 12920 ! Other lighting equipment manufacturing (part)
,,.. i All other miscellaneous electrical equipment and
i component manufacturing (part)
nmi/nn i Dental equipment and supplies manufacturing
Jjyil41U ;, ,x
:(part)
33611100 ! Automobile manufacturing
3361 1200 ! Light truck and utility vehicle manufacturing
33612000 ! Heavy duty truck manufacturing
33621 1 10 ! Motor vehicle body manufacturing (part)
->->mn^ i n = Military armored vehicle, tank, and tank
33699210 ,, . , .
: component manutacturing (part)
33621 120 I Motor vehicle body manufacturing (part)
33621130 ! Motor vehicle body manufacturing (part)
Number of
Establishments,
1997
6
0
11
7
10
5
4
567
0
194
112
84
76
6
715
23
Sales,
Shipments or
Receipts, 1997
($1,000)
11,101
0
52,855
77,832
36,473
6,174
859
4,051,267
0
95,385,563
110,400,169
14,490,344
82,633
n/a
8,719,326
265,552
Number of
Employees,
1997
71
0
542
604
159
29
8
26,072
0
114,060
94,033
28,214
404
n/a
41,779
1,201
A-18
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC
3714
3714
3714
3714
3714
3714
3715
3716
3721
3724
3728
3728
3728
3728
3731
3732
3732
3743
3743
3751
MP&M Sector i Industry
, , , , . . . . i Motor Vehicle Parts and
Motor Vehicle i .
: Accessories
, , , , , . . . i Motor Vehicle Parts and
Motor Vehicle i .
: Accessories
, , , , , . . . i Motor Vehicle Parts and
Motor Vehicle i .
: Accessories
, , , , , . . . i Motor Vehicle Parts and
Motor Vehicle i .
: Accessories
, , , , , . . . i Motor Vehicle Parts and
Motor Vehicle i .
: Accessories
, , , , , . . . i Motor Vehicle Parts and
Motor Vehicle i .
: Accessories
Bus & Truck j Truck Trailers
Motor Vehicle i Mobile Homes
Aircraft j Aircraft
. . , i Aircraft Engines and Engine
Aircraft , b b
i Parts
. . , i Aircraft Parts and Auxiliary
Aircraft i^ . ,
: Equipment
. . , i Aircraft Parts and Auxiliary
Aircraft i^ . ,
: Equipment
. . , i Aircraft Parts and Auxiliary
Aircraft i^ . ,
: Equipment
. . , i Aircraft Parts and Auxiliary
Aircraft i^ . ,
: Equipment
Ship i Ship Building and Repairing
Ship j Boat Building and Repairing
Ship i Boat Building and Repairing
Railroad i Railcars, Railway Systems
Railroad j Railcars, Railway Systems
Motor Vehicle i Motorcycles
1997 NAICS j
Code j 1997 NAICS Industry
3363 1200 ! Gasoline engine and engine parts manufacturing
,,,,,,,,,, i Other motor vehicle electrical and electronic
33632230 . ,, . , .
: equipment manulactunng (part)
--,-. 1 Motor vehicle steering and suspension
JJoJJUUU , , , x r. .
: component (except spring) manulactunng
33634020 i Motor vehicle brake system manufacturing (part)
-.,.- i Motor vehicle transmission and power train parts
JJoJjUUU r. .
: manulactunng
3363QQ70 '* ^ omer motor vehicle parts manufacturing
I (part)
33621200 I Truck trailer manufacturing
33621300 Motor home manufacturing
33641100 I Aircraft manufacturing
33641200 ! Aircraft engine and engine parts manufacturing
': Fluid power valve and hose fitting manufacturing
Jj2y 1220 i , ,x
i(part)
i Fluid power cylinder and actuator manufacturing
I (part)
i Fluid power pump and motor manufacturing
I (part)
i Other aircraft parts and auxiliary equipment
I manufacturing
33661100 Ship building and repairing
33661200 I Boat building
81149020 I Boat repair
mmi i PumP and pumping equipment manufacturing
j j jy 1 IzU : , ,x
[(part)
33651020 I Railroad rolling stock manufacturing (part)
336991 10 Motorcycle, bicycle, and parts manufacturing
Number of
Establishments,
1997
881
193
212
269
523
1,508
390
88
204
369
0
0
0
1,138
700
1,043
1,739
0
207
385
Sales,
Shipments or
Receipts, 1997
($1,000)
25,974,369
6,446,681
10,750,312
10,033,288
33,288,093
34,193,298
5,507,768
3,943,709
56,273,651
22,617,284
0
0
0
20,073,061
10,571,810
5,622,040
821,273
0
7,916,635
n/a
Number of
Employees,
1997
81,368
30,489
48,944
43,132
111,954
173,569
30,678
18,086
200,961
82,557
0
0
0
127,729
97,385
41,422
9,454
0
31,633
n/a
A-19
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC
3761
3764
3769
3792
3795
3799
3799
3799
3812
3821
3822
3823
3824
3825
3825
3826
MP&M Sector i Industry
!
i Guided Missiles and Space
Space |
^ : Vehicles
i Guided Missile and Space
P j Vehicle Propulsion
i Other Space Vehicle and Missile
Space i-n _t
F i Parts
Motor Vehicle i Travel Trailers and Campers
Mobile Ind. Eq. i Tanks and Tank Components
, , , , . . . . i Miscellaneous Transportation
Motor Vehicle ' . , r
: Equipment
, , , , . . . . i Miscellaneous Transportation
Motor Vehicle ' . , r
: Equipment
, , , , . . . . i Miscellaneous Transportation
Motor Vehicle ' . , r
: Equipment
T , , i Search, Det, Nav, Ggnc, Aero,
Instruments :,, _ ' , ฐ
iNaut Sys/Inst
, , , i Laboratory Apparatus and
Instruments i^ .,
: Furniture
, , , i Automatic Environmental
Instruments ; , .
: Controls
Instruments i Process Control Instruments
, , , i Fluid Meters and Counting
Instruments ' . ฐ
: Devices
, , , i Instruments to Measure
Instruments ' . ....
: Electricity
, , , i Instruments to Measure
Instruments ' . ....
: Electricity
Instruments ! Laboratory Analytical
1997 NAICS j
Code j 1997 NAICS Industry
I (part)
33641400 ! Guided missile and space vehicle manufacturing
i Guided missile and space vehicle propulsion unit
I and propulsion unit parts manufacturing
i Other guided missile and space vehicle parts and
I auxiliary equipment manufacturing
33621410 Travel trailer and camper manufacturing (part)
->->rr,rv.-.r> = Military armored vehicle, tank, and tank
33699220 ,, . , ,
: component manufacturing (part)
3 322 1 260 ! Hand and edge tool manufacturing (part)
33621420 ! Travel trailer and camper manufacturing (part)
33699900 i All other transportation equipment manufacturing
I Search, detection, navigation, guidance,
3345 1 120 i aeronautical, and nautical system and instrument
I manufacturing (part)
': Laboratory apparatus and furniture
3391 1 100 *- .
: manufacturing
i Automatic environmental control manufacturing
I for residential, commercial, and appliance use
Instruments and related products manufacturing
3345 1 300 i for measuring, displaying, and controlling
i industrial process variables
ii/ifi/inn i Totalizing fluid meter and counting device
JJ4jl4UU r. .
: manufacturing
,,...,, i Electronic coil, transformer, and other inductor
i manufacturing (part)
,, . . 1 ,_ _ i Instrument manufacturing for measuring and
i testing electricity and electrical signals
33451620 I Analytical laboratory instrument manufacturing
Number of
Establishments,
1997
22
28
49
315
37
1
498
378
680
385
317
1,002
222
17
826
664
Sales,
Shipments or
Receipts, 1997
($1,000)
14,791,466
3,239,033
898,758
3,076,049
n/a
n/a
1,485,367
4,557,989
32,497,776
2,471,153
2,935,692
7,890,923
3,765,769
24,303
13,852,897
7,157,038
Number of
Employees,
1997
52,158
18,540
6,110
20,112
n/a
n/a
13,240
19,466
187,557
18,253
21,450
49,196
17,390
190
63,332
38,200
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC
3827
3829
3829
3841
3842
3842
3842
3842
3843
3844
3845
3851
3861
3861
3873
3911
3914
3914
MP&M Sector i Industry
! Instruments
Instruments i Optical Instruments and Lenses
, , , i Measuring and Controlling
Instruments ; . ฐ ฐ
: Devices NEC
, , , i Measuring and Controlling
Instruments ; . ฐ ฐ
: Devices NEC
, , , i Surgical & Medical Instruments
Instruments i c A *,
: & Apparatus
, , , i Orthopedic, Prosthetic &
Instruments i . , ' .
: Surgical Suppl.
, , , i Orthopedic, Prosthetic &
Instruments i . , ' .
: Surgical Suppl.
, , , i Orthopedic, Prosthetic &
Instruments i . , ' .
: Surgical Suppl.
, , , i Orthopedic, Prosthetic &
Instruments i . , ' .
: Surgical Suppl.
Instruments i Dental Equipment and Supplies
Instruments ! X-Ray Apparatus and Tubes
Instruments i Electromedical Equipment
Instruments i Ophthalmic Goods
, i Photographic Equipment &
i Supplies
, i Photographic Equipment &
i Supplies
TI A , + , ' Watches, Clocks, and
Precious Metals , . ,
: Watchcases
Precious Metals ! Jewehy, Precious Metal
. ,,,-, : Silverware, Plated Ware &
Precious Metals i , . .
: Stainless
Precious Metals i Silverware, Plated Ware &
1997 NAICS I
Code j 1997 NAICS Industry
I (part)
3 3 3 3 1 420 Optical instrument and lens manufacturing (part)
33451970 '* Oth61 measurmg and controlling device
i manufacturing (part)
iimmn i Surgical and medical instrument manufacturing
JjyilzlU ;, ,x
:(part)
limn i Surgical and medical instrument manufacturing
j jy 1 IzzU : , ,x
:(part)
322 1 2 1 30 i Paper (except newsprint) mills (part)
32229120 ! Sanitary paper product manufacturing (part)
n/icimn i Electromedical and electrotherapeutic apparatus
JJ4jlUZU ฃ. . / :\
: manulacturing (part)
iimn i Surgical appliance and supplies manufacturing
j jy 1 1 JzU : , ,x
:(part)
iimi/i i Dental equipment and supplies manufacturing
j jy 1 14zU : , ,x
:(part)
33451700 jlrradiation apparatus manufacturing
i Electromedical and electrotherapeutic apparatus
I manufacturing (part)
3391 1500 Ophthalmic goods manufacturing
3? 599700 '* Pnotographic fihn, paper, plate, and chemical
i manufacturing
iiii i nn i Photographic and photocopying equipment
JJJJij2(j ฃ. . / :\
: manulacturing (part)
3345 1 830 ! Watch, clock, and parts manufacturing (part)
33991 120 I Jewelry (except costume) manufacturing (part)
': Cutlery and flatware (except precious)
33221120 *- . , .ป
: manufacturing (part)
33991220 Silverware and plated ware manufacturing (part)
Number of
Establishments,
1997
495
853
6
1,598
2
16
74
1,636
877
155
460
575
311
428
128
2,272
11
151
Sales,
Shipments or
Receipts, 1997
($1,000)
3,174,652
5,114,547
62,148
18,450,024
n/a
651,398
807,427
14,743,779
2,699,867
3,942,256
10,567,566
3,607,813
12,895,637
8,410,124
718,191
5,416,836
8,032
899,684
Number of
Employees,
1997
20,801
33,904
521
107,298
n/a
2,236
6,722
82,390
18,072
14,276
47,121
26,366
38,935
24,707
5,646
34,694
101
6,356
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
! Stainless
.,- : . , , , . i Jewelers' Materials & Lapidary
3915 i Precious Metals ;, . F 3
iWork
3931 i Other i Musical Instruments
->nAA ': r^.i i Games, Toys, Children's
3944 i Other ;,, , . . J
: Vehicles
->nAA ': r^.i i Games, Toys, Children's
3944 i Other ;,, , . . J
: Vehicles
3949 i Other j Sporting and Athletic Goods,
3951 j Other j Pens and Mechanical Pencils
3953 i Other i Marking Devices
3961 i Precious Metals i Costume Jewelry
3965 i Hardware i Fasteners, Buttons, Needles, Pins
3993 j Other j Signs and Advertising Displays
3995 j Other j Burial Caskets
3999 j Other j Manufacturing Industries, N.E.C.
3999 j Other j Manufacturing Industries, N.E.C.
3999 i Other i Manufacturing Industries, N.E.C.
3999 i Other i Manufacturing Industries, N.E.C.
3999 i Other i Manufacturing Industries, N.E.C.
3999 j Other j Manufacturing Industries, N.E.C.
3999 i Other i Manufacturing Industries, N.E.C.
3999 j Other j Manufacturing Industries, N.E.C.
3999 i Other i Manufacturing Industries, N.E.C.
3999 j Other j Manufacturing Industries, N.E.C.
1997 NAICS j
Code j 1997 NAICS Industry
I
i Jewelers' material and lapidary work
I manufacturing
33999200 i Musical instrument manufacturing
336991 70 '* Motorcycle, bicycle, and parts manufacturing
I (part)
33993200 i Game, toy, and children's vehicle manufacturing
33992000 ! Sporting and athletic goods manufacturing
33994100 I Pen and mechanical pencil manufacturing
33994300 i Marking device manufacturing
33991430 ! Costume jewelry and novelty manufacturing
I (part)
,,,. i Fastener, button, needle, and pin manufacturing
I (part)
33995000 I Sign manufacturing
33999500 i Burial casket manufacturing
3 1 499950 '* ^ otner miscellaneous textile product mills
I (part)
3 1 6 1 1 020 I Leather and hide tanning and finishing (part)
i All other miscellaneous wood product
I manufacturing (part)
i All other converted paper product manufacturing
I (part)
323 1 1 030 Commercial lithographic printing (part)
323 1 1 1 30 I Commercial gravure printing (part)
323 1 1230 Commercial flexographic printing (part)
323 1 1 340 I Commercial screen printing (part)
323 1 1 930 Other commercial printing (part)
32599840 | All other miscellaneous chemical product and
Number of
Establishments,
1997
394
576
4
785
2,571
112
634
826
249
5,709
177
52
26
0
0
0
0
0
0
0
9
Sales,
Shipments or
Receipts, 1997
($1,000)
919,066
1,356,651
n/a
4,534,497
10,591,160
1,590,770
643,007
1,223,475
n/a
7,910,809
1,271,184
173,353
24,625
0
0
0
0
0
0
0
80,624
Number of
Employees,
1997
5,396
13,411
n/a
29,622
69,664
8,394
7,831
13,976
n/a
82,956
6,962
2,167
329
0
0
0
0
0
0
0
572
A-22
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC ! MP&M Sector i Industry
i i
3999 i Other i Manufacturing Industries, N.E.C.
3999 ! Other j Manufacturing Industries, N.E.C.
3999 i Other i Manufacturing Industries, N.E.C.
3999 i Other i Manufacturing Industries, N.E.C.
3999 i Other i Manufacturing Industries, N.E.C.
3999 j Other j Manufacturing Industries, N.E.C.
4011 i Railroad i Railroad Transportation*
4013 j Railroad j Railroad Transportation*
4111 i Bus & Truck i Local & Suburban Transit
4111 j Bus & Truck j Local & Suburban Transit
4111 i Bus & Truck i Local & Suburban Transit
4111 j Bus & Truck j Local & Suburban Transit
4111 i Bus & Truck i Local & Suburban Transit
4119 JBus&Truck j Local Passenger Trans, N.E.C.
4119 iBus&Truck i Local Passenger Trans, N.E.C.
4119 JBus&Truck j Local Passenger Trans, N.E.C.
4119 iBus&Truck i Local Passenger Trans, N.E.C.
4119 JBus&Truck j Local Passenger Trans, N.E.C.
4119 iBus&Truck i Local Passenger Trans, N.E.C.
4121 j Motor Vehicle j Taxicabs
4131 i Bus & Truck i Intercity & Rural Bus Trans
4141 j Bus & Truck j Local Bus Charter Service
4142 i Bus & Truck i Bus Charter Service, Exc Local
4173 ; Bus & Truck 1 Bus Terminal & S vce Facilities
1997 NAICS j
Code j 1997 NAICS Industry
I preparation manufacturing (part)
326 1 9920 All other plastics product manufacturing (part)
3 322 1 270 I Hand and edge tool manufacturing (part)
i All other miscellaneous fabricated metal product
I manufacturing (part)
': Residential electric lighting fixture
JJjIzlJO *- . , .ป
: manufacturing (part)
33712740 Institutional furniture manufacturing (part)
33999920 | All other miscellaneous manufacturing (part)
i
I
485 1 1 1 00 Mixed mode transit systems
485 1 1200 I Commuter rail systems
485 1 1 300 Bus and motor vehicle transit systems
485 1 1 900 I Other urban transit systems
48599910 I Scheduled airport shuttle service
48532000 I Limousine service
4854 1 020 Employee bus service
48599100 I Special needs transportation
48599920 i All other passenger transportation
4871 1010 I Sightseeing buses
62 1 9 1 090 Ambulance or rescue service (except by air)
48531000 I Taxi service
4852 1 000 Interurban and rural bus transportation
48551010 I Charter bus service, local
48551020 Charter bus service, interstate/interurban
... i Terminal and maintenance facilities for motor
4oo4yulU 1-1 i ^ j.-
: vehicle passenger transportation
Number of
Establishments,
1997
140
7
185
53
5
2,284
n/a
n/a
28
16
542
32
534
3,234
158
1,789
232
307
3,275
3,184
407
482
1,049
26
Sales,
Shipments or
Receipts, 1997
($1,000)
319,241
n/a
285,362
69,864
28,296
7,183,815
n/a
n/a
51,567
n/a
1,152,525
n/a
601,988
1,873,924
158,947
1,141,413
67,395
462,186
4,443474
1,280,597
1,147,432
459,953
1,308,246
15,253
Number of
Employees,
1997
3,141
n/a
3,231
1,216
329
60,397
n/a
n/a
759
n/a
27,448
n/a
13,435
29,432
4,223
31,791
1,078
6,858
106,354
27,850
19,900
8,694
22,789
220
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC
4212
4212
4212
4212
4212
4212
4212
4212
4212
4212
4213
4213
4213
4213
4213
4213
4214
4214
4214
4214
MP&M Sector
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Bus & Truck
Industry
Local Trucking w/o Storage
Local Trucking w/o Storage
Local Trucking w/o Storage
Local Trucking w/o Storage
Local Trucking w/o Storage
Local Trucking w/o Storage
Local Trucking w/o Storage
Local Trucking w/o Storage
Local Trucking w/o Storage
Local Trucking w/o Storage
Trucking, Except Local
Trucking, Except Local
Trucking, Except Local
Trucking, Except Local
Trucking, Except Local
Trucking, Except Local
Local Trucking w/ Storage
Local Trucking w/ Storage
Local Trucking w/ Storage
Local Trucking w/ Storage
1997 NAICS I
Code ! 1997 NAICS Industry
A o A 1 1 n i n i General freight trucking without storage, local,
4841 lUlU , , , j ,,1X
i truckload (tl)
A o A 1 1 n-> n i General freight trucking without storage, local,
4841 lUzU :, ,, , i i j /i,i\
i less than truckload (Itl)
A o /i <> i n i n i Used household and office goods moving, local,
484zlUlU -,i , ,
: without storage
A o /i <> T n i n i Hazardous materials trucking (except waste),
484zzUlU :, ,
i local
..,,, i Agricultural products trucking without storage,
4o4zzUzU : , ,
i local
48422030 | Dump trucking
48422040 i Specialized trucking without storage, local
562 1 1 1 00 I Solid waste collection
5621 1200 Hazardous waste collection
562 1 1 900 I Other waste collection
': General freight trucking, long-distance, truckload
48412100 i-,-
;(ti)
i General freight trucking, long-distance, less than
I truckload (Itl)
': Used household and office goods moving, long-
48421020 i i- ,
: distance
i Hazardous materials trucking (except waste),
I long-distance
48423020 i Agricultural products trucking, long-distance
48423030 | Other specialized trucking, long-distance
': General freight trucking with storage, local,
48411030 , , , , ,,1X
i truckload (tl)
i General freight trucking with storage, local, less
I than truckload (Itl)
': Used household and office goods moving, local,
48421030 -,, ,
: with storage
48422050 i Specialized trucking with storage, local
Number of
Establishments,
1997
10,296
4,249
3,259
1,434
8,065
17,440
7,996
7,083
414
827
23,111
6,210
3,555
2,043
5,389
7,007
542
373
2,286
543
Sales,
Shipments or
Receipts, 1997
($1,000)
7,783,545
3,324,800
1,198,983
1,267,441
2,785,495
9,748,351
5,131,564
18,211,495
1,095,553
837,625
51,142,148
25,010,091
9,111,477
3,840,724
3,693,332
12,966,336
678,272
486,659
2,273,241
782,939
Number of
Employees,
1997
73,967
47,246
20,858
10,951
29,925
81,553
56,450
137,049
8,468
7,227
425,758
258,972
65,734
28,396
32,371
103,860
7,468
6,096
34,958
9,227
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
4215 j Bus & Truck j Courier Svces, Exc by Air
4215 i Bus & Truck i Courier Svces, Exc by Air
423 1 i Bus & Truck i Trucking Terminal Facilities
44 1 2 j Ship j Deep Sea Foreign Trans
4424 i Ship i Deep Sea Foreign Trans
4432 j Ship j Freight Trans Great Lakes
4449 j Ship jWtr Trans of Freight, N.E.C.
448 1 j Ship j Deep Sea Passenger Trans
4481 iShip i Deep Sea Passenger Trans
4482 jShip j Ferries
4482 iShip j Ferries
4489 j Ship j Water Passenger Trans, N.E.C
4489 j Ship j Water Passenger Trans, N.E.C
4491 j Ship j Marine Cargo Handling
4491 i Ship i Marine Cargo Handling
4492 j Ship j Towing & Tugboat Service
4492 i Ship i Towing & Tugboat Service
4492 i Ship i Towing & Tugboat Service
4493 iShip j Marinas
4499 j Ship j Water Trans Svces, NEC
4499 iShip j Water Trans Svces, NEC
4499 j Ship j Water Trans Svces, NEC
1997 NAICS j
Code j 1997 NAICS Industry
492 1 1 0 1 0 I Courier services (except by air)
4922 1 000 Local messengers and local delivery
.., i Motor freight terminal and j oint terminal
4oo4yUzU , r. -,-. . , ,-
: maintenance lacihty transportation
483 1 1 1 00 I Deep sea freight transportation
48311310 Coastal and intercoastal freight transportation
A 01 1 n -in i Great Lakes - St. Lawrence Seaway freight
4oJ 1 1 j2(j . , ,
: transportation
/i 001 1 1 1 n i Inland waterways freight transportation (except
4oJzl 1 1U , x
: towing)
483 1 1200 I Deep sea passenger transportation
i Coastal and Great Lakes - St. Lawrence Seaway
I passenger transportation
i Coastal and Great Lakes - St. Lawrence Seaway
I ferry transportation
48321210 Inland waterways ferry transportation
A o 1-1 n T n i Other water passenger transportation (including
4oJzlzzU A A -\
: water taxi)
A o-7-i i n i n i Excursion and sightseeing boats (including
4o /zlUlU : j- x
: dinner cruises)
48831010 I Operation of port and waterfront terminals
48832000 I Marine cargo handling
483 11330 I Coastal and intercoastal towing service
48321 120 Inland waterways towing transportation
.... i Tugboat service (including fleeting and harbor
4ooJJUlU x
: service)
71393000 I Marinas
48831 020 Seaway and lighthouse operations
48833020 | Navigational services
iMarine salvaging and wrecking (including
4oo33030 i T ,,- i- i \
: dismantling of ships)
Number of
Establishments,
1997
2,362
5,384
14
487
292
32
222
80
64
61
76
154
654
168
623
292
161
361
4,217
0
461
43
Sales,
Shipments or
Receipts, 1997
($1,000)
19,289,602
3,519,100
12,989
11,570,718
3,114,639
519,863
2,821,121
3,908,143
89,597
92,493
121,992
171,135
861,001
889,125
4,456,243
1,043,440
566,027
1,014,026
2,541,481
0
377,596
121,580
Number of
Employees,
1997
317,630
67,413
120
18,542
12,547
1,614
10,628
12,266
923
879
1,017
1,877
10,827
6,802
48,463
7,529
5,035
7,989
22,765
0
2,142
669
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC
4499
4499
4581
4581
4581
4581
5013
5013
5013
5013
5013
5013
5013
5013
5511
5521
5561
5571
MP&M Sector i Industry
Ship ! Water Trans Svces, NEC
Ship ! Water Trans Svces, NEC
. . f \ Airports, Flying Fields, Arpt
/\lTCr3.It ; i-p i ci
: Terminal Svcs
. . f i Airports, Flying Fields, Arpt
/\lTCr3.It ; i-p i ci
: Terminal Svcs
. . f i Airports, Flying Fields, Arpt
/\lTCr3.It ; i-p i ci
: Terminal Svcs
. . f i Airports, Flying Fields, Arpt
/\lTCr3.It ; i-p i ci
: Terminal Svcs
, , , , , . . . i Motor Vehicle Supplies&New
Motor Vehicle ; , ^
i Parts
, , , , , . . . i Motor Vehicle Supplies&New
Motor Vehicle ; , ^
i Parts
, , , , . . . . i Motor Vehicle Supplies&New
Motor Vehicle ; , ^
i Parts
, , , , . . . . i Motor Vehicle Supplies&New
Motor Vehicle ; , ^
i Parts
, , , , . . . . i Motor Vehicle Supplies&New
Motor Vehicle ; , ^
i Parts
, , , , . . . . i Motor Vehicle Supplies&New
Motor Vehicle ; , ^
i Parts
, , , , . . . . i Motor Vehicle Supplies&New
Motor Vehicle ! , ^
i Parts
, , , , . . . . i Motor Vehicle Supplies&New
Motor Vehicle ; , ^
i Parts
, , , , . . . . i Motor Vehicle Dealers (New and
Mo tor Vehicle iTT ,, v
i Used)
, , , , . . . . i Motor Vehicle Dealers (New and
Mo tor Vehicle iTT ,, v
i Used)
Motor Vehicle ! Recreational Vehicle Dealers
Motor Vehicle i Motorcycle Dealers
1997 NAICS I
Code j 1997 NAICS Industry
48839010 I Other services incidental to water transportation
5 324 1 1 1 0 Commercial vessel rental and leasing
48811110 ! Nongovernment air traffic control
48811910 ! Airport operation and terminal services
4881 9000 ! Other support activities for air transportation
561 72020 ! Airplane cleaning and janitorial services
47117010 '* Mฐtor vehicle supplies and new parts -
i warehouse distributors
47117010 '* Mฐtor vehicle supplies and new parts -
i warehouse distributors
421 12020 ! Motor vehicle supplies and new parts - jobbers
421 12020 ! Motor vehicle supplies and new parts - jobbers
/m i imn i Petroleum products marketing equipment
4zl IzUJU iii i
: wholesalers
/m i imn i Petroleum products marketing equipment
4zl IzUJU iii i
: wholesalers
44 1 3 1 030 '* Mฐtor vehicle supplies and new parts jobbers
I (retail)
44 1 3 1 030 '* Mฐtor vehicle supplies and new parts jobbers
I (retail)
44 1 1 1 000 ! New car dealers
44112000 ! Used car dealers
44 1 2 1 000 I Recreational vehicle dealers
44 1 22 1 00 I Motorcycle dealers
Number of
Establishments,
1997
640
126
114
1,699
2,400
127
4,357
5,095
6,942
5,732
583
507
16,253
16,253
25,897
23,340
3,014
3,635
Sales,
Shipments or
Receipts, 1997
($1,000)
444,499
454,392
43,450
3,243,149
5,859,631
203,918
19,025,397
30,313,120
51,468,506
20,760,962
1,433,102
1,070,443
22,093,428
22,093,428
518,971,824
34,680,468
10,069,749
7,369,260
Number of
Employees,
1997
4,389
1,657
502
61,547
53,318
5,843
59,564
67,362
84,003
57,724
4,673
4,376
150,408
150,408
1,046,243
92,752
29,463
29,026
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
5599 j Motor Vehicle j Automotive Dealers, NEC
i Stationary Ind. j Heavy Construction Equip
j Eq. j Rental, Leasing
i Stationary Ind. j Heavy Construction Equip
j Eq. j Rental, Leasing
_.. i Stationary Ind. : . , . , . ,
7359 ip J i Equip Rental, Leasing, NEC
_.. i Stationary Ind. : . , . , . ,
7359 ip J i Equip Rental, Leasing, NEC
_.. i Stationary Ind. : . , . , . ,
7359 ip J i Equip Rental, Leasing, NEC
_.. i Stationary Ind. : . , . , . ,
7359 ip J i Equip Rental, Leasing, NEC
_.. i Stationary Ind. : . , . , . ,
7359 ip J i Equip Rental, Leasing, NEC
_.. i Stationary Ind. : . , . , . ,
7359 ip J i Equip Rental, Leasing, NEC
_.. i Stationary Ind. : . , . , . ,
7359 ip J ; Equip Rental, Leasing, NEC
_.. i Stationary Ind. : . , . , . ,
7359 ip J ; Equip Rental, Leasing, NEC
7378 i Office Machine i Comp Maintenance/Rep
7379 ! Office Machine j Computer Rel Ser, NEC
7379 j Office Machine j Computer Rel Ser, NEC
7379 j Office Machine j Computer Rel Ser, NEC
7379 j Office Machine j Computer Rel Ser, NEC
7514 j Motor Vehicle j Passenger Car Rental
75 1 5 i Motor Vehicle i Passenger Car Lease
-7cm \, * T7i-i i Utility Trailer and Recreational
7519 ; Motor Vehicle i,, , . , , .
: Vehicle Rental
1997 NAICS j
Code j 1997 NAICS Industry
44122900 I All other motor vehicle dealers
23499020 i All other heavy construction (part)
': Rental and leasing of heavy construction
33241210 , -,, , ,
: equipment without operators
53221000 ! Consumer electronics and appliances rental
53229990 i Other consumer goods rental and leasing
53231000 ! General rental centers
5 324 1 1 90 ! Aircraft rental and leasing
i Oilfield and well drilling equipment rental and
I leasing
5 32420 1 0 ! Office machinery rental and leasing
53249020 i Industrial equipment rental and leasing
56299120 i Portable toilet rental
81 121230 Computer maintenance and repair
33461100 I Software reproducing
': Computer systems consultants (except systems
j41 j [220 i , , >
: integrators)
i Computer consultants (except computer systems
I consultants)
54 1 5 1 990 All other computer related services
53211100 I Passenger car rental
53211200 Passenger car leasing
.... , _ _ i Utility trailer, and RV (recreational vehicle)
jjzizuyu , , j ,
: rental and leasing
Number of
Establishments,
1997
1,678
2,295
3,286
3,011
3,133
6,509
498
671
400
3,408
563
6,087
124
20,233
7,604
801
4,367
879
360
Sales,
Shipments or
Receipts, 1997
($1,000)
2,517,267
2,734,732
5,339,163
1,790,890
2,133,450
3,910,618
n/a
1,555,089
436,178
6,775,140
n/a
7,565,169
1,258,435
15,942,861
3,432,145
907,844
14,783,704
3,800,424
256,119
Number of
Employees,
1997
9,145
94,344
32,848
17,491
26,134
40,284
n/a
8,697
2,895
40,122
n/a
60,406
8,027
129,785
27,598
9,516
102,623
8,325
1,890
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
7532 j Motor Vehicle j Top,Body,Uphol,Paint
7532 j Motor Vehicle j Top,Body,Uphol,Paint
7532 j Motor Vehicle j Top,Body,Uphol,Paint
7533 i Motor Vehicle i Auto Exhaust Systems
7537 j Motor Vehicle j Auto Transmission Rp
7538 i Motor Vehicle i Gen Automotive Repair
7539 j Motor Vehicle j Auto Repair Shop, NEC
7539 j Motor Vehicle j Auto Repair Shop, NEC
7539 j Motor Vehicle j Auto Repair Shop, NEC
7539 j Motor Vehicle j Auto Repair Shop, NEC
7539 j Motor Vehicle j Auto Repair Shop, NEC
7549 j Motor Vehicle j Auto Serv,Ex RepAVash
7549 j Motor Vehicle j Auto Serv,Ex RepAVash
7549 j Motor Vehicle j Auto Serv,Ex RepAVash
7623 j Household Eq. j Refrig,Air Condition
7623 i Household Eq. i Refrig, Air Condition
7629 i Instruments i Electric Repair Shop
7629 j Instruments j Electric Repair Shop
7629 i Instruments i Electric Repair Shop
7629 i Instruments i Electric Repair Shop
7629 i Instruments i Electric Repair Shop
763 1 j Precious Metals j Watch, Clock, Jewelry Rp
7692 j Other j Welding Repair
7699 ! Other j Repair Shop, Rel Serv
1997 NAICS j
Code j 1997 NAICS Industry
81112110 I Paint or body repair shops
81112120 Van conversion services
81112130 JUpholstery and interior repair shops
8111 1200 Automotive exhaust system repair
8 1 1 1 1 300 I Automotive transmission repair
81111100 General automotive repair
81111810 I Carburetor repair shops
8 1 1 1 1 820 Brake, front end, and wheel alignment
81111830 I Electrical repair shops, motor vehicle
81111840 i Radiator repair
8 1 1 1 1 890 All other motor vehicle repair shops
4884 1 000 I Motor vehicle towing
81119100 Automotive oil change and lubrication shops
cm no-m i All other motor vehicle services (except repair
oil iy8zu j , x
: and carwashes)
81131030 I Commercial refrigeration equipment repair
': Refrigeration and air-conditioning service and
81 141220 , , , 1X
: repair shops (except commercial)
81121210 Business and office machine repair, electrical
81121310 I Telephone set repair
': Electrical equipment repair and maintenance,
81121910 i- 11- i- i ,
: including medical equipment
': Consumer equipment repair (except computer,
81141120 i, , T 7^T-. i ^ \
i television, VCR, and stereo)
81141210 Electric appliance and washing machine repair
81 149010 I Watch, clock, and jewelry repair
81 149030 I Welding repair
48839030 | Ship scaling
Number of
Establishments,
1997
33,144
639
1,786
5,251
6,768
77,751
1,091
3,741
1,679
2,295
868
5,893
7,413
1,646
2,343
1,671
1,538
201
2,033
579
4,327
1,716
4,840
12
Sales,
Shipments or
Receipts, 1997
($1,000)
16,645,229
723,189
386,878
1,985,377
2,431,584
25,598,455
363,763
1,553,732
494,744
728,297
354,107
2,295,188
2,787,318
798,626
1,890,237
789,622
913,258
231,458
2,509,452
185,507
3,125,853
345,774
1,640,808
4,737
Number of
Employees,
1997
192,853
6,507
5,812
23,015
29,442
290,634
4,802
18,216
6,890
8,372
3,954
36,845
57,083
11,789
16,281
9,174
9,735
2,294
20,446
2,171
42,324
5,599
22,291
49
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 2: Relationships between SIC and NAICS Codes for MP&M Industries
SIC i MP&M Sector i Industry
7699 ! Other j Repair Shop, Rel Serv
7699 j Other j Repair Shop, Rel Serv
7699 j Other j Repair Shop, Rel Serv
7699 j Other j Repair Shop, Rel Serv
7699 j Other j Repair Shop, Rel Serv
7699 j Other j Repair Shop, Rel Serv
7699 j Other j Repair Shop, Rel Serv
7699 j Other j Repair Shop, Rel Serv
7699 j Other j Repair Shop, Rel Serv
7699 j Other j Repair Shop, Rel Serv
7699 ; Other j Repair Shop, Rel Serv
1997 NAICS j
Code j 1997 NAICS Industry
56162200 I Locksmiths
561 790 1 0 Furnace, duct, chimney, and gutter cleaning
56179030 I Drain cleaning
562991 10 Cesspool cleaning, sewer cleaning, and rodding
8 1 1 2 1 220 I Typewriter repair
i Dental and lab instrument, and other precision
I equipment repair (except typewriters)
81131010 Industrial machines and equipment repair
01141110 1 Home and garden equipment repair and
i maintenance (except consumer equipment repair)
o 1 1 /i i -> nn i Nonelectrical appliances and other nonelectronic
oi i4izyu ,
: equipment repair
81 143010 I Leather goods, luggage, and pocketbook repair
81 149090 -All other repair and related services
Number of
Establishments,
1997
3,799
878
376
2,538
104
838
16,404
3,032
181
82
3,946
Sales,
Shipments or
Receipts, 1997
($1,000)
1,081,317
n/a
n/a
n/a
23,844
404,627
13,600,413
816,008
59,338
18,294
1,362,271
Number of
Employees,
1997
14,501
n/a
n/a
n/a
291
4,183
131,793
9,726
659
349
18,854
Source: Department of Commerce, Bureau of the Census, 1997 Economic Census, Bridge Between NAICS and SIC.
-------
MP&M EEBA: Appendices Appendix A: Detailed Profile Information
A. 2 ANNUAL ESTABLISHMENT BIRTHS Table A-3 shows ^ averaงe number of facilities
(establishments) operating at the beginning of each year for
AND DEATHS IN MP&M INDUSTRIES the period 1989 through 1997, the number of facility
"births" and "deaths", and the average "birth rate" and
EPA used the Statistics of U.S. Businesses (SUSB) dynamic "death rate" for each of the major 3-digit manufacturing SIC
data to estimate the rate at which MP&M facilities enter and codes that include an MP&M 4-digit SIC codes.1 This table
leave the industry each year. The SUSB dynamic data report shows that, over the period 1989-1997, annual closure rates
numbers of facilities starting up, closing, expanding ranged from 6 to over 12 percent in the different industries,
employment and contracting employment each year from with an overall average of almost 8 percent.
1989 through 1997 (the latest currently available.)
1 The data are disaggregated only to the 3-digit SIC level,
and EPA therefore was unable to calculate closure rates for the
specific 4-digit SICs that comprise the MP&M industries. The
analysis does not include 3-digit SICs that may include large
numbers of non-metal products producers, for example SIC 241
(furniture, both wood and metal.)
A-30
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 3: Annual MP&M Establishment Births and Deaths by 3 Digit SIC Codes (1989-1997)
SIC i SIC Description
, . , I Metal Cans And Shipping
1 Containers
3420 i Cutlery, Handtools, And Hardware
, . , j Plumbing And Heating, Except
1 Electric
3440 i Fabricated Structural Metal Products
3450 i Screw Machine Products, Bolts, Etc.
3460 i Metal Forgings And Stamping
3470 i Metal Services, Nee
3480 i Ordnance & Accessories, Nee
3490 i Misc. Fabricated Metal Products
3510 i Engines And Turbines
3520 i Farm And Garden Machinery
Construction And Related
I Machinery
3540 i Metalworking Machinery
3550 i Special Industry Machinery
3560 i General Industrial Machinery
3570 i Computer And Office Equipment
. . ! Refrigeration And Service
j joU : , , , .
i Machinery
3590 i Industrial Machinery, Nee
3610 i Electric Distribution Equipment
3620 i Electrical Industrial Apparatus
3630 i Household Appliances
Electric Lighting And Wiring
3640 ; ^
i Equipment
3650 i Household Audio & Video Equip
3660 i Communications Equipment
, , j Electronic Components And
1 Accessories
i Misc. Electrical Equipment &
I Supplies
3710 i Motor Vehicles And Equipment
3720 i Aircraft And Parts
,, j Ship And Boat Building And
1 Repairing
3740 i Railroad Equipment
3750 i Motorcycles, Bicycles, & Parts
Guided Missiles, Space Vehicles,
1 Parts
, j Miscellaneous Transportation
1 Equipment
3810 i Search & Navigation Equipment
3820 i Measuring And Controlling Devices
3840 i Medical Instruments And Supplies
3850 i Ophthalmic Goods
3860 i Photographic Equip & Supplies
3 870 i Watches, Clocks, Watchcases &
Average #
Establishments at
the
Beginning of the
Year
464
2,294
687
12,268
2,436
3,812
5,028
390
7,084
346
1,711
3,165
11,072
4,427
3,961
2,025
2,104
21,972
764
2,024
461
1,905
766
1,794
6,068
1,890
4,477
1,633
2,669
189
256
127
962
758
4,209
3,770
536
784
159
Average
Establishment
Births
22
143
45
853
84
199
341
39
606
26
133
217
672
307
243
262
154
1,996
53
117
44
123
96
169
614
136
387
122
343
15
38
7
106
34
275
334
40
71
12
Average
Establishment
Deaths
35
139
53
908
111
226
340
40
531
24
129
230
660
317
225
246
165
1,659
51
130
41
143
87
159
522
157
372
127
339
15
25
11
109
60
295
289
48
72
20
% Births
4.7%
6.2%
6.6%
7.0%
3.4%
5.2%
6.8%
10.0%
8.6%
7.5%
7.8%
6.9%
6.1%
6.9%
6.1%
12.9%
7.3%
9.1%
6.9%
5.8%
9.5%
6.5%
12.5%
9.4%
10.1%
7.2%
8.6%
7.5%
12.9%
7.9%
14.8%
5.5%
11.0%
4.5%
6.5%
8.9%
7.5%
9.1%
7.5%
% Deaths
7.5%
6.1%
7.8%
7.4%
4.6%
5.9%
6.8%
10.2%
7.5%
6.8%
7.5%
7.3%
6.0%
7.1%
5.7%
12.1%
7.9%
7.5%
6.6%
6.4%
8.9%
7.5%
11.4%
8.9%
8.6%
8.3%
8.3%
7.8%
12.7%
7.7%
9.7%
8.4%
11.3%
7.9%
7.0%
7.7%
8.9%
9.1%
12.7%
A-31
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
Table A. 3: Annual MP&M Establishment Births and Deaths by 3 Digit SIC Codes (1989-1997)
SIC i SIC Description
i Parts
Jewelry, Silverware, And Plated
j Ware
3930 i Musical Instruments
3940 i Toys And Sporting Goods
3950 i Pens, Pencils, Office, & Art Supplies
3960 i Costume Jewelry And Notions
3990 i Miscellaneous Manufactures
TOTAL !
Average #
Establishments at
the
Beginning of the
Year
2,606
434
2,843
975
1,010
7,338
136,653
Average
Establishment
Births
246
46
384
62
105
784
11,103
Average
Establishment
Deaths
275
35
345
70
128
740
10,698
% Births
9.4%
10.6%
13.5%
6.4%
10.4%
10.7%
8.1%
% Deaths
10.6%
8.0%
12.1%
7.2%
12.7%
10.1%
7.8%
Source: Small Business Administration, Statistics of U.S. Businesses.
A-32
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
A.3 DESCRIPTION OF MP&M SURVEYS
EPA collected financial and technical data from a sample of
facilities that might be subject to the proposed MP&M rule,
including two screener and seven detailed questionnaires
(surveys) between 1989 and 1996. The responses to these
surveys provided the basic financial and economic
information used in the facility and firm impact analyses. In
addition, the POTW survey provided information on facility
permitting costs. EPA used the POTW survey data to
calculate government administrative costs associated with
the rule. The various surveys are described below as they
relate to the financial and economic analyses. The MP&M
rulemaking docket provides copies of the survey instruments
and detailed information on the conduct of the surveys.
A.3.1 Screener Surveys
In 1990, EPA distributed 8,342 screener surveys to sites
believed to be engaged in the original seven Phase I MP&M
sectors. In 1996, EPA distributed 5,325 screener surveys to
sites believed to be engaged in the eleven Phase II MP&M
sectors. The screener surveys helped EPA to identify sites
to receive the more detailed follow-up surveys and to make a
preliminary assessment of the MP&M industry. EPA
identified the SIC codes applicable to the respective MP&M
sectors and randomly selected names and addresses in those
SICs to receive the screener surveys based on Dun &
Bradstreet databases.
A.3.2 Ohio Screener Surveys
EPA also sent the 1996 screener survey to 1,600 randomly
selected sites in Ohio to support the Ohio case study.
A.3.3 Detailed MP&M Industry Surveys
Based on responses to the screener surveys, EPA sent a
more detailed survey to a selected group of water-using
MP&M sites. EPA collected financial and technical data
from sample facilities in two phases.
Based on responses to the 1990 screener, EPA sent the
Phase I detailed survey to a select group of water-using
MP&M sites. The Agency designed this survey to collect
detailed technical and financial information. EPA selected
1,020 detailed survey recipients from water-discharging
screener respondents, water-using screener respondents that
did not discharge process water, and water-discharging sites
from well-known MP&M companies that did not receive the
screener.
EPA used information from the first two groups of survey
recipients to develop pollutant loadings and reductions and
to develop compliance cost estimates. Because EPA did not
randomly select the third group of recipients, EPA did not
use the data to develop national estimates.
To reduce burden on survey recipients for Phase II of the
data collection effort, EPA developed two similar detailed
surveys. Based on the development of the 1995 MP&M
proposal, EPA chose to collect more detailed information
from sites with annual process wastewater discharges greater
than one million gallons per year (1 MGY). EPA sent the
"long" detailed survey to all 353 1996 screener respondents
who indicated they discharged one million or more gallons
of MP&M process wastewater annually and performed
MP&M operations. The Agency sent the "short" detailed
survey to 101 randomly selected 1996 screener respondents
who indicated they discharged less than one million gallons
of MP&M process wastewater annually and performed
MP&M operation
The detailed surveys responses provide site number of
employees and detailed financial and economic information
about the site or the company owning the site. In addition,
the 1996 long detailed questionnaire included a section that
requested supplemental information on other MP&M
facilities owned by the company. EPA included this
voluntary section to measure the combined impact of
proposed MP&M effluent guidelines on companies with
multiple MP&M facilities that discharge process
wastewater. This section requested the same information
collected in the 1996 MP&M screener survey. Responses to
questions in this section provided information on the size,
industrial sector, revenue, unit operations, and water usage
of the company's other MP&M facilities.
The 1996 short survey included the identical general site and
economic information collected in the long detailed survey,
with one exception. Short survey recipients were not asked
to provide information on the liquidation value of their
plant.
A.3.4 Iron and Steel Survey
EPA also developed a detailed survey, under a separate
rulemaking effort, to collect detailed information from
facilities that are currently covered by the Iron and Steel
Manufacturing effluent guidelines. Following field
sampling of iron and steel sites and review of the completed
industry surveys, EPA decided that some iron and steel
operations would be more appropriately covered by the
MP&M rule because they were more like MP&M
operations. EPA relied on the Iron & Steel survey for
financial and economic information on 47 iron and steel
facilities.
A.3.5 Municipality Survey
EPA distributed surveys in 1996 to city and county facilities
that might operate MP&M facilities. The Agency designed
A-33
-------
MP&M EEBA: Appendices
Appendix A: Detailed Profile Information
this survey to measure the impact of this rule on
municipalities and other government entities that perform
maintenance and rebuilding operations on MP&M products
(e.g., bus and truck, automobiles). The Agency sent the
municipality survey to 150 city and county facilities
randomly selected from the Municipality Year Book-1995
based on population and geographic location. EPA
allocated sixty percent of the sample to municipalities and
40 percent to counties. The 60/40 distribution was
approximately proportional to their aggregate populations in
the frame. EPA divided the municipality sample and the
county sample into three size groupings as measured by
population. The surveys collected information on MP&M
site costs of service and on the financial and economic
characteristics of the governments operating the MP&M
facilities.
A.3.6 Federal Facility Survey
EPA designed this survey to assess the impact of the
MP&M effluent limitations guidelines and standards on
federal agencies that operate MP&M facilities. EPA
distributed the survey to federal agencies likely to perform
industrial operations on metal products or machines. The
Agency requested that the representatives of the seven
chosen federal agencies voluntarily distribute copies of the
survey to sites they believed performed MP&M operations.
The information collected in the 1996 federal survey was
identical to the long survey. After engineering review and
coding, EPA entered data from 44 federal surveys into the
database. Because EPA did not randomly select the survey
recipients, data from these questionnaires was not used to
develop national estimates.
A.3.7 POTW Survey
EPA distributed the Publicly Owned Treatment Works
(POTW) survey in November 1997. The Agency designed
this survey to estimate possible costs and burden that
POTWs might incur in writing MP&M permits or other
control mechanisms and to estimate benefits associated with
implementation of the MP&M regulations. The Agency sent
the POTW survey to 150 POTWs with flow rates greater
than 0.50 million gallons per day. EPA randomly selected
the recipients from the 1992 Needs Survey Review, Update,
and Query System Database (RUQus), and divided the
POTW sample into two strata by daily flow rates: 0.50 to
2.50 million gallons, and 2.50 million gallons or more.
In addition to the total volume of wastewater treated at the
site, the POTW survey requested the number of industrial
permits written, the cost to write the permits, the permitting
fee structure, the percentage of industrial dischargers
covered by National Categorical Standards (i.e., effluent
guidelines), and the percentage of permits requiring specific
administrative activities. EPA used this information to
estimate administrative burden and costs. In addition, EPA
requested information on the use or disposal of sewage
sludge generated by the POTW. The Agency only required
POTWs that received discharges from an MP&M facility to
complete those questions. The sewage sludge information
requested included the amount generated, use or disposal
method, metal levels, use or disposal costs, and the
percentage of metal loadings from MP&M facilities. The
Agency used this information to assess the potential changes
in sludge handling resulting from the MP&M rule and to
estimate economic benefits to the POTW
A-34
-------
MP&M EEBA: Appendices Appendix A: Detailed Profile Information
REFERENCES
U.S. Bureau of the Census. 2000. The Bridge Between NAICS and SIC Report. March.
http://www.census.gov/epcd/www/naicensu.html
Small Business Administration. Statistics of U.S. Businesses. http://www.sba.gov/advo/stats/int_data.html
A-35
-------
MP&M EEBA: Appendices
Appendix B: MP&M Sector Cost Pass-Through Potential
Appendix B:
MP&M Sector Cost Pass-Through
Potential
INTRODUCTION1
This appendix describes the methodology used to calculate
compliance cost pass-through coefficients for each sector.
The cost pass-through coefficient is a measure of how much
of compliance-related cost increases a sector can be
expected to pass on to its consumers. EPA conducted a two-
part analysis, including an econometric analysis of the
historical relationship of output prices to changes in input
costs and an analysis of market structure characteristics.
These analyses together provide a numerical estimate of
pass-through potential at the MP&M sector level.
This appendix includes five sections. The first describes the
econometric analysis of cost pass-through potential based on
the historical changes in output prices relative to changes in
input costs. The second discusses the market structure
factors that are expected to affect the recovery of costs.
Section B.3 describes how the results of the econometric
and market structure analyses are combined to develop a
quantitative estimate of cost pass-through potential. Section
B.4 discusses adjustments to that estimate to take account of
the portion of each sector that will incur costs. Finally, the
last section describes the use of the estimated cost pass-
through values in the facility-level financial analysis.
B. 1 HISTORICAL CHANGES IN OUTPUT
PRICES RELATIVE TO CHANGES IN INPUT
COSTS
Two factors determine the share of a cost increase that a
facility can pass through to its customers: the elasticity of
demand and the elasticity of supply in the facility's market.
Both factors are difficult to measure accurately. One reason
APPENDIX CONTENTS:
B. 1 Historical Changes in Output Prices Relative to
Changes in Input Costs B-l
B.2 Market Structure Effects B-4
B.3 Combining the Measures of Pass-Through
Potential B-7
B.4 Adjusting the Composite Estimate of Pass-
Through Potential for Share of Output Bearing
Compliance Costs B-8
B.5 Using the Estimated Cost Pass-Through Potential
in the Facility-Level Financial Analysis B-10
Glossary B-ll
Acronyms B-12
References B-13
1 This analysis was performed to support the Phase I MP&M
proposal, and will be updated prior to promulgation of the final
MP&M rule.
for the difficulty is that observed changes in price are due to
simultaneous changes in demand and supply. In view of this
difficulty, this pass-through analysis does not decompose
cost pass-through into the separate effects stemming from
elasticity of demand and elasticity of supply. This
restriction is reasonable because the value of interest is the
composite of the two elasticity effects: that is, the change in
equilibrium revenue due to a change in input costs.
An additional analytic challenge involves joint consideration
of quantity and price effects. Specifically, the amount of
cost increase that a firm may recover through a revenue
increase may generally be decomposed into a change in
price and a change in quantity. In most markets, increased
prices (in response to increased costs) translate into reduced
quantity of sales. Whether or not total revenue increases
depends on the interaction of supply and demand elasticities.
For practical reasons, this analysis focused on the change in
equilibrium price due to a change in input costs. Changes in
market quantities were determined from closures, rather than
by estimating changes in output in non-closing facilities.
B-l
-------
MP&M EEBA: Appendices
Appendix B: MP&M Sector Cost Pass-Through Potential
The analysis assumes that the quantity of shipments or sales
does not vary with the increase in fixed and average costs,
unless the facility closes.
The methodology measures the sensitivity of equilibrium
prices to changes in input costs. The "cost elasticity of
price," denoted Ep, measures the percentage change in
output price per percent change in unit input costs.2 The
cost elasticity of price was estimated by linear regression on
ten years of annual input price indices, for 15 MP&M
sectors.3 The 15 MP&M industry sectors encompass 163
industrial 4-digit SIC codes. Estimation of Ep requires for
each MP&M sector a measure of the change over time in
input costs (input cost index) and a measure of the change in
output price (output price index).
The input cost index is an average of the producer price
index values for commodity inputs to the sector in question,
weighted by the share of each input to sector output. The
weighted average calculation involves two steps.
First, at the 4-digit SIC level, an aggregate measure of input
cost was developed from yearly Producer Price Index (PPI)
values from the Bureau of Labor Statistics, weighted by the
direct requirement coefficients from the 1982 Benchmark
Input-Output Tables of the United States.4 The Employment
Cost Index (ECI) from the Bureau of Labor Statistics for all
private manufacturers was used for the value-added
component of production cost. Estimating a contribution to
value-added from labor costs alone excludes consideration
of changes in payments to equity capital. However,
available measures of payments to capital are not likely to
improve the accuracy of the input cost index. Furthermore,
the direct requirements coefficients from the input-output
table include information on the purchase of capital goods,
and changes in the cost of capital goods are reflected in the
PPI series for the associated industries. The input cost index
for a 4-digit SIC group was calculated as a weighted average
of prices of a sample bundle of inputs comprised of the most
significant inputs that collectively account for at least 50
percent of the total input cost associated with the relevant
4-digit SIC industry.
The Bureau of Economic Analysis' Input-Output Table uses
its own industry classification system, which is similar to the
Standard Industrial Classification (SIC) used in the Census
of Manufactures. This classification system is referred to in
this appendix as the BEA classification. The BEA
classification has more categories than the SIC system, but
the BEA classification codes were grouped so that they map
to the more aggregate SIC codes that form the MP&M
sectors.
Second, at the MP&M sector level, the input cost index was
developed by weighting the individual 4-digit SIC group
cost index values by 4-digit SIC value of shipments from the
Census of Manufactures and various Annual Surveys of
Manufactures from the corresponding years. The resulting
values provided an aggregate measure of input costs over the
10-year period 1982-1991 for each MP&M sector.
To summarize, the input cost index was calculated as
follows:
For each 4-digit SIC industry, i, that uses non-labor inputs,
j, the average input price for the year k is:
(B.I)
where:
lk = average input price index for SIC industry i,
yeark;
= direct requirements coefficient for input
commodity j by industry i; and
j k = Producer Price Index, commodity j, year k.
For each MP&M industry sector, containing N 4-digit SIC
industries, the average input price in each year k is:
ฃ
-------
MP&M EEBA: Appendices
Appendix B: MP&M Sector Cost Pass-Through Potential
Similarly, the output price index, which is the dependent
variable, is the weighted average of Producer Price Indices
for the goods produced by the industries in each sector and
is calculated as follows:
E
-------
MP&M EEBA: Appendices
Appendix B: MP&M Sector Cost Pass-Through Potential
Table B.I: Cost
Pass-Through Regression Results
By Sector
Regression Coefficients
(t-statistics in parenthesis)
MP&M Sector
Aerospace
Aircraft
Bus & Truck
Electronic Equipment
Hardware
Household Equipment
Instruments
Mobile Industrial Equipment
Motor Vehicle
Office Machines
Ordnance
Input Price j Employment Cost j
Index i Index i
.7735!
....a.2,73)i..
.9241 !
(.37.22)!
.9301!
(30.91)!
.8990!
(25.28)!
.8888!
(27.02)1
.9205!
(43.033)!
.9231!
(46.44)!
.9010!
(23.94)!
.8984!
(27.85)!
.9201 !
(35.05)1
.9068!
(29.05)!
Precious and Non-Precious Metals .9383 j
(24.82)!
Railroad
Ships and Boats
Stationary Industrial Equipment
.9106!
(.30.52)!
.9703!
(34.68)!
.9090;
^^ (2&smi
.0098 !
..(4,21).l..
.0031 !
(3.32)!
.0028 i
..(2,46).!
.0047 !
(3.46)!
.0046 !
(3.68)1
.0034 !
(4.16)!
.0033 i
..(4,34).!
.0039 !
(2.68)!
.0042 i
..(3;36)j
.0035 !
(3.52)1
.0038 !
(3.18)!
.0024 !
(1.68)!
.0037!
(3.23)!
.0010!
(0.93)!
.0038 i
(3.06)1
Rank3
1
12
13
4
2
10
11
5
3
9
6
14
8
15
7
a Rank from lowest to highest cost pass-through potential as measured by the regression-based input price
index.
Source: U.S. EPA analysis.
The median pass-through coefficient over the 15 MP&M
sectors is 0.91.
The direct estimation used in this methodology measures
actual changes in output price with respect to changes in
input costs. It has the advantage of taking into account the
full range of possible mechanisms by which input costs
affect output prices, including technical changes,
substitution, non-competitive pricing mechanisms,
imperfect information phenomena and any other shifts or
irregularities in the supply and demand functions.
B.2 MARKET STRUCTURE EFFECTS5
The second part of the analysis of cost pass-through potential
builds from an analysis of current market structure in the
MP&M industry sectors and uses information from the
industry profile and the Phase I Section 308 Survey of
MP&M facilities. This second method for estimating Ep
gives ordinal rather than numerical results.
Information on the competitive structure and market
characteristics of an industry provide insight into the likely
ranges of values for supply and demand elasticities and the
sensitivity of output prices to input costs. When an input
cost increases, the profit-maximizing firm attempts to
5 This analysis was performed only for the Phase I sectors. It
will be updated and expanded to include the Phase II sectors prior
to promulgation of the final MP&M rule.
B-4
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MP&M EEBA: Appendices
Appendix B: MP&M Sector Cost Pass-Through Potential
maintain its profits by increasing output prices
accordingly. How much of the cost increase the firm can
pass on through higher prices depends on the relative
market power of the firm and its customers. The following
discussion identifies six indicators of market power used to
assess cost pass-through potential. The first five of these
indicators depend on analysis at the MP&M sector level,
while the sixth indicator uses facility-specific information.
As a result, the estimate of cost pass-through potential
from this analysis is facility-specific, but the variation
between facilities in the same sector is small. These six
indicators are as follows:
1. Concentration. The extent of concentration among a
group of market participants is an important determinant of
that group's market power. A group of many small firms
typically has less market power than a group of a few large
firms. Eight-firm concentration ratios measure the
percentage of value of shipments concentrated in the top
eight companies in each four-digit industry. Sector
concentration ratios are the weighted averages of
component industry concentration ratios, weighted by
value of shipments. As the sector concentration ratio
increases, firms in an industry are expected to be better
able to pass on input cost increases, all other things being
equal.
2. Vertical Integration. Specialization ratios, also
from the Department of Commerce, provide a measure of
vertical concentration. A vertically integrated industry
includes firms that produce several commodities that are
typically sequentially ordered in production. The
specialization ratio is not a direct measure of the
relationship between products produced by an industry; no
such measure is readily available. The specialization ratio,
however, does measure the percentage of the value of
shipments by an industry outside of the industry's primary
commodity. Accordingly, a high specialization ratio
means that the firms in an industry cannot have significant
vertical concentration. Alternatively, a lower
specialization in an industry means more production of
other commodities, which permits the possibility of
vertical integration. Thus, a lower specialization ratio
increases the potential that the firms in an industry produce
commodities that are vertically linked in production, which
in turn would imply higher market power.
3. Import Competition. Import penetration, defined as
the ratio of imports in a sector to the total value of
domestic consumption in that sector, measures the
availability of substitutes from abroad. Higher import
penetration generally means that firms are exposed to
greater competition from foreign producers and will thus
possess less market power to increase prices in response to
regulation-induced increases in production costs. The
Census Bureau provides import data at the 4-digit SIC
code level.
If historical changes in input costs have affected both
domestic and foreign firms more or less uniformly, then the
econometrically estimated Ey would not address situations in
which only domestic firms face higher costs. Foreign firms
could offer a substitute supply of goods that is not subject to
the compliance costs of the proposed rule, which would
reduce the cost pass-through potential that would apply if
there were only domestic competition in a sector.
4. Export Competition. Export dependence, defined as
the percentage of shipments from a sector that is exported,
measures the degree to which that sector is exposed to
competitive pressures abroad in export sales. The MP&M
regulation is not expected to increase the production costs of
foreign producers, with whom domestic firms must compete
in export markets. As a result, sectors that rely more on
export sales are expected to have less latitude to increase
prices of their exported products in response to regulation-
induced increases in production costs, other things being
equal. The fact that domestic producers export a substantial
share of their input does not necessarily imply that they are
subject to more competition than they face in domestic
markets. U.S. producers could be the dominant suppliers
world-wide. It is likely that export sales are subject to more
international competition on average than are domestic sales,
however, and therefore that a high export share would imply
less ability to pass on domestic production cost increases.
5. Long-Term Industry Growth. The competitiveness of an
industry and the ability of facilities to engage in price
competition differ between declining industries and growing
industries. EPA compared the average growth rate in the
value of shipments between 1982 and 1991 for each sector to
the median of those average growth rates among the 15
sectors. Those with higher than median growth rates are
deemed to be better positioned to pass through compliance
costs, rather than absorb cost increases in order to retain
market share.
6. Competition Barriers. Barriers to entry and exit help a
concentrated industry exert market power by deterring
potential competitors from entering the market. Without
these barriers, a firm that tries to pass on compliance costs by
raising its prices would risk losing market share to new firms
that see an opportunity to compete at these higher prices.
Entry barriers include high capital costs, brand name
reputations that would require a large advertising expense to
overcome, a long learning curve, and any other factors that
make the fixed cost for new entrants higher than the fixed
cost of existing firms.
Exit barriers include factors that make it difficult for a firm
to liquidate its assets, such as specialized machinery that
cannot be sold or converted to alternative uses, brand names
that cannot transfer well to other products, or substantial
shutdown liabilities that would offset the value of assets in
liquidation. If entry barriers are the fixed costs of beginning
B-5
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MP&M EEBA: Appendices
Appendix B: MP&M Sector Cost Pass-Through Potential
business in an industry, then exit barriers are the fixed
costs that cannot be salvaged upon leaving the industry.
They are sometimes called sunk costs and are measured
as the difference between the replacement value of a
facility's capital and its liquidation value. It is difficult to
estimate accurately the capital valuations needed to
measure exit barriers. One way to avoid the data
availability problem is to identify directly the presence of
above-normal profits that entry and exit barriers permit.
A facility's risk-normalized profit rate is measured as its
pre-tax return on assets (ROA), as calculated from survey
data, divided by that facility's beta. A facility's beta is a
measure of its riskiness as an investment relative to the
market for equity investments as a whole. Each Phase I
survey facility was assigned to the sector from which it
receives the largest portion of its revenues, as indicated on
the facility's survey response. EPA calculated, for each
sector, the revenue-weighted average of risk-normalized
ROAs for facilities assigned to the sector.6 The revenue-
weighted average of risk-normalized ROAs by sector was
used as a measure of above-normal profits in a sector,
which in turn was taken as an indicator of barriers to entry
and exit.
This measure does not state that MP&M industries face
high or low barriers to competition in absolute terms; it
only assigns them relative rankings. Above-median profits
indicate sectors with above average market power and the
likely presence of entry and exit barriers.
EPA used these six measures to assign each sector a cost
pass-through score. For some variables (e.g., industry
concentration), higher numerical values indicate greater
cost pass-through potential, while for other variables (e.g.,
specialization ratio), higher numerical values indicate
lower cost pass-through potential. A value that, relative to
the median, indicates greater cost pass-through potential
receives a score of+1 and a value that indicates lower cost
pass-through potential than the median receives a score of
-1. The sector at the median is assigned a score of 0.
Table B.2 summarizes the specific scoring definitions for
each variable.
This measure was calculated only for the seven sectors
covered by the Phase I survey. This analysis will be expanded to
all sectors prior to promulgation of the final rule.
B-6
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MP&M EEBA: Appendices
Appendix B: MP&M Sector Cost Pass-Through Potential
Table B.2: Summary of Scoring Rules for Assessing Relative
Pass-Through Potential Based on Market Structure Considerations"
Variable
8-Firm Concentration Ratio (CR8)
Specialization Ratio (SR)
Ratio of Imports to Shipments (M)
Ratio of Exports to Shipments (X)
Average Growth Rate of Shipments (G)
Risk-Adjusted Pre-Tax Return on Assets (P)
Variable Indicates
Greater Pass-Through
Potential (Score +1)
Greater than median
Lower than median
Lower than median
Lower than median
Greater than median
Greater than median
Variable Indicates Lower ! Variable Indicates
Pass-Through Potential j Neutral Pass-Through
(Score -1) I Potential (Score 0)
Lower than median j Equal to median
Greater than median j Equal to median
Greater than median j Equal to median
Greater than median j Equal to median
Lower than median j Equal to median
Lower than median i Equal to median
a. All assessments of pass-through potential are relative among the 15 MP&M Sectors.
Source: U.S. EPA analysis.
On the basis of this scoring system, the possible scores from
the market structure analysis range from -6 to +6. These
point scores based on the individual market structure
variables are in turn used to assign summary scores of
structure-based pass-through potential. Sectors with a score
of 2 or greater are assigned a summary score +1, while
sectors with scores of -2 or less are assigned a summary
score of -1. Sectors with scores of 1, -1 or 0 are assigned a
summary score of 0.
B.3 COMBININS THE MEASURES OF
PASS-THROUSH POTENTIAL
The regression analysis provides a quantitative assessment
of what the cost pass-through ability of each sector appears
to be. The market structure analysis yields a judgment of
what the pass-through ability ought to be. Information from
both analyses contribute to the assignment of cost pass-
through estimates to facilities in each sector.
The procedure for assigning a composite score of cost
pass-through potential involved three steps:
1.Define high, medium and low ranges of cost pass-through
elasticity. These ranges are defined by the cost pass-through
elasticities estimated for the top third, middle third and
lower third of all MP&M sectors, ranked by elasticity of
output price. These ranges are defined relative to other
MP&M sectors, and do not indicate high, medium, or low
cost pass-through potential in an absolute sense.
2. Assign each sector a high, medium, or low pass-through
potential based on the econometric estimate of pass-through
elasticity. Each sector was assigned a +1, -1 or 0 rating
depending on whether its estimated Ep is in the top, bottom
or middle third, respectively, of the estimated values of Ep
across all MP&M sectors.
3. Assign each sector a high or low pass-through potential
based on the market structure analysis of pass-through
potential. As discussed in the preceding section, each sector
received a +1, -1, or 0 score based on the number of market
structure considerations that indicate relatively higher or
relatively lower expected cost pass-through potential.
4. Combine the assigned pass-through potential scores
from the econometric estimation and market structure
analysis techniques to yield a composite measure of
pass-through potential, E"1. If the sum of the structural
analysis and the direct estimation scores is positive, then that
sector was assigned to the high range of observed Ep values.
Conversely, if the sum is negative, it was assigned to the low
value range ofEp. When the sum is zero, the sector was
assigned to the middle range of Ep values.
Table B.3 summarizes the resulting assignments of MP&M
sectors to the estimated pass-through potential range.
7 The "'" in the E' term identifies the cost pass-through value
as that assigned to the given sector based on the composite cost
pass-through analysis and subsequent adjustment. The "'"
distinguishes the cost pass-through value from the Ep values that
were estimated by sector and that form the basis for the numerical
ranges of cost pass-through potential to which MP&M sectors were
assigned.
B-7
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MP&M EEBA: Appendices
Appendix B: MP&M Sector Cost Pass-Through Potential
Table B.3: Estimated Pass-Through Potential by MP&M Sector
Combined Econometric and Structural Scores
Sector
Aerospace
Aircraft
Bus and Truck
Electronic Equipment
Hardware
Household Equipment
Instruments
Iron & Steel
Job Shops
Mobile Industrial Equipment
Motor Vehicle
Office Machine
Ordnance
Other Metal Products
Precious and Non-Precious Metals
Printed Circuit Boards
Railroad
Shipbuilding
Stationary Industrial Equipment
Econometric
Estimation Score3
-1
1
1
-1
-1
0
1
N/A
N/A
-1
-1
0
0
N/A
1
N/A
0
1
0
Structural Analysis
Score
1
0
N/A
0
0
N/A
N/A
N/A
N/A
-1
N/A
N/A
0
N/A
N/A
N/A
N/A
N/A
-1
Assigned Pass-
Through Range
Middle
High
N/A
Low
Low
N/A
N/A
N/A
N/A
Low
N/A
N/A
Middle
N/A
N/A
N/A
N/A
N/A
, Low
* This score is +1, 0, or -1, depending on whether the econometric estimate of cost pass-through coefficient for the sector is in the
high, middle or low end of the range, respectively. These ranges were defined as follows:
Low =0.773 to 0.901
Middle = 0.907 to 0.921
High = 0.923 to 0.937
Source: U.S. EPA analysis.
B.4 A&jusTiNe THE COMPOSITE
ESTIMATE OF PASS-THROUSH POTENTIAL
FOR SHARE OF OUTPUT BEARING
COMPLIANCE COSTS
The cost effects of an effluent guideline differ from those of
an across-the-board change in the cost of a production input
(e.g., energy costs). Although cost increases for general
production inputs such as energy may affect essentially all
of the facilities in an industry, the cost effects of an effluent
guideline are likely to be less pervasive. In particular,
MP&M facilities that do not discharge process wastewater
will not incur costs due to the proposed rule. Even among
those facilities that do discharge wastewater, the costs of
achieving compliance with the proposed regulation will vary
in their impact on facility finances and business operations.
In general, facilities that incur little or no costs to achieve
compliance with the proposed regulation will compete with
facilities that incur higher costs, and limit their ability to
raise prices.
A final adjustment was undertaken to the estimated cost
pass-through coefficients to reflect the presence of facilities
that are expected to bear no compliance-related cost
increases as a result of regulation. From the analysis of
survey responses, EPA estimated the total business revenue
in each MP&M sector that is associated with water-
discharging facilities and thus likely to be affected by
compliance-related cost increases.8 Separately, from
Department of Commerce data, EPA estimated the total
revenues by MP&M facilities, regardless of discharge status.
The ratio of these values revenues in water-discharging
facilities divided by total revenues in the MP&M sector
provided a measure of the fraction of production in the
MP&M sector likely to be affected by compliance cost
increase. For each sector, the ratio was multiplied by the
estimated cost pass-through potential to yield an adjusted
estimate of compliance cost pass-through potential, taking
into account competition from same-industry facilities that
are not expected to incur compliance-related cost increases.
Table B.4 summarizes the final adjustment to the estimates
of cost pass-through potential. The first column lists the
pass-through potential value assigned to each sector before
8 This analysis included only the seven sectors addressed by
the Phase I rule. This analysis will be expanded to all sectors prior
to promulgation of the final rule.
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MP&M EEBA: Appendices
Appendix B: MP&M Sector Cost Pass-Through Potential
adjustment for the share of sector output bearing
compliance costs. The second column gives each sector's
adjustment coefficient (i.e., the fraction of business activity
that is expected to incur compliance-related cost increases),
and the final column shows the resulting pass-through
values that were used in the facility impact analysis.
Table B.4: Adjusted Estimates of Compliance Cost Pass-Through
Potential by MP&M Sector
Sector
Aerospace
Aircraft
Bus & Truck
Electronic Equipment
Hardware
Household Equipment
Instruments
Iron & Steel
Job Shops3
Mobile Industrial Equipment
Motor Vehicle
Office Machinery
Ordnance
Other Metal Products3
Precious and Non-Precious Metals
Printed Circuit Boards3
Railroad
Ships and Boats
Stationary Industrial Equipment
Unadjusted Cost
Pass-Through
Potential
0.914
0.937
.9301
0.872
0.872
.9205
.9231
.9076
.9076
0.872
.8984
.9201
0.914
.9076
.9383
.9076
.9106
.9703
0.872
Estimated
Fraction of
Revenue Subject to
Regulation
100.0%
100.0%
N/A
100.0%
34.8%
N/A
N/A
N/A
N/A
100.0%
N/A
N/A
100.0%
N/A
N/A
N/A
N/A
N/A
39.7%
Adjusted Cost Pass-
Through Potential
0.914
0.937
.9301
0.872
0.303
.9205
.9231
.9076
.9076
0.872
.8984
.9201
0.914
.9076
.9383
.9076
.9106
.9703
0.346
Source: U.S. EPA analysis.
As shown by the table, the fraction of business activity to
which the regulation is expected to apply varies considerably
by sector. The survey data indicate, for Aircraft, Electronic
Equipment, Ordnance, Aerospace, and Mobile Industrial
Equipment, that essentially all of the business operations
within the sector will be subject to regulatory effects.
However, for Hardware and Stationary Industrial
Equipment, the fraction of business operations within the
sector expected to incur compliance costs is much smaller.
The resulting adjusted cost pass-through potential values
also vary quite broadly from a low of 0.303 for Hardware to
a high of 0.937 for Aircraft. Note that these values are
elasticity values that is, the percentage change in output
revenues for a percentage change in input prices and are
not cost pass-through fractions that is, the fraction of
compliance-related cost increase expected to be recovered
from customers through increased revenues. The use of the
elasticity values in the facility impact analysis to calculate
cost pass-through fractions is described in the last section of
this appendix.
B-9
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MP&M EEBA: Appendices
Appendix B: MP&M Sector Cost Pass-Through Potential
B.5 USINS THE ESTIMATED COST
PASS-THROUSH POTENTIAL IN THE
FACILITY-LEVEL FINANCIAL ANALYSIS
The estimated cost elasticity of price E" for each sector was
used to develop an estimated percentage price increase for
each sector and for each regulatory option considered. Total
compliance costs for all facilities in a sector were divided by
total baseline costs for same facilities, as reported in the
surveys. This percentage price increase multiplied by E"
provided a percentage price increase expected to result from
the increased costs in each sector. That is,
PJ = EJ x
> >
E ABC,
(B.6)
where
percentage sectary price increase,
cost elasticity of price for sectary,
ACQ = annualized compliance cost for facility /' in
sectary,
ABQ = annualized baseline cost for facility /' in sector
j, and
n = number of facilities in sectary.
This analysis assumes that all facilities in a given sector
benefit from the same price increase, regardless of their own
compliance costs. The percentage of compliance costs that
any given facility recovers through price increases varies
across facilities within a sector. Whether a facility's profits
increase or decrease as a result of the rule depends on the
sector cost elasticity of price and that facility's compliance
costs relative to those incurred by other facilities in the same
sector. Facilities that do not incur any compliance costs
enjoy increased profits, because their revenues increase as a
result of the price increase without any increase in costs.
Facilities that incur large costs relative to their competitors
will suffer a decrease in profitability.
Table 5 A in Chapter 5 reports the percentage price increases
predicted for each sector for the proposed rule. Price
increases range from 0.01 percent to 1.91 percent, with
increases less than one percent for all but two sectors.
B-10
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MP&M EEBA: Appendices
Appendix B: MP&M Sector Cost Pass-Through Potential
GLOSSARY
barriers to entry: Factors that hinder or prevent firms
from entering a market. Examples include economies of
scale, absolute cost advantages, high capital cost
requirements, and product differentiation.
barriers to exit: Factors that hinder or prevent firms from
liquidating its assets and ceasing production. Examples
include high shutdown costs (e.g., due to employee
termination costs or environmental liabilities) and
investments in specialized equipment that cannot be
transferred (a form of sunk costs).
beta: A firm's beta is a measure of its riskiness as an
investment relative to the market for equity investments as a
whole. Calculated by comparing the firm's return to a
measure of market-wide returns over time.
Concentration ratio: A way of measuring the
concentration of market share held by particular suppliers in
a market. An eight-firm concentration ratio is the total
market share of the eight firms with the largest market
shares. In this analysis, measured as the percentage of value
of shipments accounted for by the top eight companies in
each 4-digit SIC, as reported by the Census Bureau.
Employment Cost Index (ECI): ECI measures changes
in labor costs for money wages and salaries and noncash
fringe benefits in nonfarm private industry and state and
local governments for workers at all levels of responsibility.
Published by the Bureau of Labor Statistics.
export dependence: The share of shipments by
domestic producers that is exported; calculated by dividing
the value of exports by the value of domestic shipments.
import penetration: The share of all consumption in the
U.S. that is provided by imports; calculated by dividing
imports by reported or apparent domestic consumption (the
latter calculated as domestic value of shipments minus
exports plus imports).
input cost index: An average of the Producer Price Index
values for commodity inputs to the sector in question,
weighted by the share of each input to sector output. Used
in this analysis as a measure of sector-level cost increases.
output price index: The weighted average of Producer
Price Indices for the goods produced by the industries in
each sector. Used in this analysis as a measure of sector-
level output price increases.
Producer Price Index (PPI): A family of indexes that
measures the average change over time in selling prices
received by domestic producers of goods and services
(Bureau of Labor Statistics, PPI Overview).
return on assets (ROA): The ratio of annual income to
assets, a measure of profitability. In this analysis, measured
as the ratio of pre-tax cash income divided by the book value
of assets, as reported in the MP&M surveys.
specialization ratio: The ratio of primary product
shipments to total product shipments (primary and
secondary, excluding miscellaneous receipts) for the
establishments classified in a particular industry (4-digit SIC
code). An industry with a specialization ratio of 100 percent
would, by definition, produce only its primary products. In
contrast, a low specialization ratio indicates that much of an
industry's output consists of secondary products.
sunk costs: The portion of fixed costs that is not
recoverable.
vertical integration: Production by a single firm in
different stages of production in the same industry. For
example, a vertically-integrated petroleum company would
explore for and extract crude oil, refine the oil, distribute the
petroleum-based products, and sell gasoline and other
products to end-users.
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MP&M EEBA: Appendices Appendix B: MP&M Sector Cost Pass-Through Potential
ACRONYMS
ECl: Employment Cost Index ROA: return on assets
PPI: Producer Price Index SIC: Standard Industrial Classification
B-12
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MP&M EEBA: Appendices Appendix B: MP&M Sector Cost Pass-Through Potential
REFERENCES
U.S. Bureau of Labor Statistics. Producer Price Index Revision-Current Series. On-line database at
http://stats.bls.gov/ppihome.htm
U.S. Bureau of Labor Statistics. 2000. Employment Cost Index - Historical Listing. July 27.
http://stats.bls.gov/ecthome.htm.
U.S. Department of Commerce (1997). Bureau of Economic Analysis, The 1992 Benchmark Input-Output Accounts of the
United States.
B-13
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MP&M EEBA: Appendices
Appendix C: POTW Permitting Costs
Appendix C:
POTW Administrative Costs
INTRODUCTION
Effluent guidelines and limitations are implemented by
Federal, State and local government entities through the
NPDES permit program (for direct dischargers) and the
General Pretreatment Regulations (for indirect dischargers).
A new effluent guideline rule may require that some
facilities be permitted for the first time, may require that
some facilities that already have permits be issued a
different form of permit, and may require repermitting of
facilities sooner than would otherwise be required. In these
cases, the permitting authority will incur additional costs to
implement the effluent guideline rule. This appendix
provides information on the unit costs of these permitting
activities, based on information reported by POTWs in the
Metal Products and Machinery (MP&M) POTW Survey,
and describes the calculation of government permitting costs
for the proposed MP&M rule and regulatory alternatives.
The first section of this appendix provides an overview of
permitting requirements under the NPDES Permit Program
and the General Pretreatment Regulations. The second
section describes the MP&M POTW Survey and the
methods used to develop unit cost estimates from the survey
responses. The third section presents the estimates of unit
costs by permitting activity, and the final section lists the
steps involved in applying these unit costs to calculate
administrative costs for a particular regulatory option.
C.I EFFLUENT GUIDELINES PERMITTING
REQUIREMENTS
Any facility that directly discharges wastewater to surface
water is required to have a permit issued under the National
Pollution Discharge Elimination System (NPDES) permit
program. Facilities that discharge indirectly through a
publicly-owned treatment works (POTW) are regulated by
the General Pretreatment Regulations for Existing and New
Sources of Pollution (40 CFR Part 403). The major portion
of government administrative costs associated with
implementing an effluent guidelines rule are the costs of
managing the NPDES and Pretreatment programs for the
regulated facilities. Permitting under these two programs is
discussed below.
APPENDIX CONTENTS:
C.I Effluent Guidelines Permitting Requirements C-l
C.I.I NPDES Basic Industrial Permit Program . C-l
C.I.2 Pretreatment Program C-2
C.2 Methodology C-2
C.2.1 Data Sources C-2
C.2.2 Overview of Methodology C-2
C.3 Unit Costs of Permitting Activities C-3
C.3.1 Permit Application and Issuance C-3
C.3.2 Inspection C-6
C.3.3 Monitoring C-6
C.3.4 Enforcement C-8
C.3.5 Repermitting C-8
C.4 POTW Administrative Costs by Option C-8
Appendix C Exhibits C-10
C.I.I NPDES Basic Industrial Permit
Program
Effluent guidelines Best Available Technology (BAT) and
New Source Performance Standards (NSPS) regulations will
be implemented through the NPDES industrial permit
program. In general, EPA does not expect the
administrative costs associated with the NPDES industrial
permit program to increase as a result of the proposed
MP&M rule. The Clean Water Act prohibits discharge of
any pollutant to a water of the U.S. except as permitted by a
NPDES permit. Therefore, every facility that discharges
wastewater directly to surface water must hold a permit
specifying the mass of pollutants that can be discharged to
waterways. The proposed rule will affect the terms of the
permits but is unlikely to increase the administrative costs
associated with permitting.
In fact, the proposed rule may decrease the administrative
burden of NPDES permits. The technical guidance
provided by EPA as a component of rulemaking provides
valuable information to permitting authorities that is likely to
reduce the research required to develop Best Professional
Judgment (BPJ) permits.1 Further, establishing discharge
1 Permits issued to facilities not covered by effluent
guidelines or water quality-based standards are developed based on
BPJ.
C-7
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MP&M EEBA: Appendices
Appendix C: POTW Permitting Costs
standards may reduce time spent by permitting authorities
establishing limits and the frequency of evidentiary hearings.
The promulgation of limitations may also enable EPA and
the authorized States to cover more facilities under general
permits. General permits are single permits covering a
common class of dischargers in a specified geographic area.
C.I.2 Pretreatmcnt Program
The General Pretreatment Regulations (40 CFR Part 403)
establish procedures, responsibilities, and requirements for
EPA, States, local governments, and industry to control
pollutant discharges to POTWs. Under the Pretreatment
Regulations, POTWs or approved States implement
categorical pretreatment standards (i.e., PSES and PSNS).
Discharges from an MP&M facility to a POTW may be
permitted in the baseline.2 For example, industrial users
subject to another Categorical Pretreatment Standard would
have a discharge permit. Other significant industrial users
(SIU) that are typically permitted by POTWs include
industrial users that:
> discharge an average of 25,000 gallons per day or
more of process wastewater to a POTW,
* contribute a process waste stream that makes up 5
percent or more of the average dry weather
hydraulic or organic capacity of the POTW
treatment plant, or
> have a reasonable potential for adversely affecting
the POTW's operation or for violating any
pretreatment standard.
EPA does not expect the costs of administering the
pretreatment program to increase due to the MP&M
regulation for facilities that already hold a permit specifying
the allowable mass of pollutant discharge to water.
Governments will incur additional permitting costs,
however, for unpermitted facilities and for any facilities
currently with a concentration-based permit that will be
issued a mass-based permit under the proposed rule instead.
The remainder of this section estimates these cost increases.
As with direct industrial dischargers, promulgation of the
MP&M rule may cause some administrative costs to
decrease. EPA has not estimated potential reductions in
government administrative costs.
C.2 METHO&oioey
C.2.1 Data Sources
EPA collected information from Publicly Owned Treatment
Works (POTWs) to support development of the MP&M
effluent guideline. Of 150 surveys mailed, EPA received
responses to 147, for a 98 percent response rate. The
POTW survey asked respondents to provide information on
administrative permitting costs, sewage sludge use and
disposal costs and practices, and general information
(including number of permitted users and number of known
MP&M dischargers). The administrative cost information
included the number of hours required to complete specific
permitting and repermitting, inspection, monitoring, and
enforcement activities. Respondents were also asked to
provide an average labor cost for all staff involved in
permitting activities. EPA used the survey responses on
administrative costs to estimate a range of costs incurred by
POTWs to permit a single MP&M facility.
C.2.2 Overview of Methodology
EPA estimated increases in government administrative costs
only for indirect discharging MP&M facilities. This section
describes the steps used to develop these estimates.
a. Determine the number and
characteristics of indirect dischargers that
will be permitted under the proposed rule.
The cost of permitting a given MP&M facility varies
depending on whether the facility is already permitted. EPA
has information from the MP&M facility surveys on
baseline permit status. Because costs differ by type of
permit (mass-based versus concentration-based), EPA
determined how many permits of each type would be issued.
All Steel Forming & Finishing facilities will require mass-
based permits under the proposed rule. Mass-based permits
are not required for the other subcategories. Permit writers
can determine what type of permit is appropriate for
facilities in subcategories other than Steel Forming &
Finishing. EPA is encouraging permit writers and control
authorities to issue mass-based permits and control
mechanisms, however, where appropriate and feasible. For
costing purposes, the analysis of permitting costs assumes
that one-third of the new or reissued permits in
subcategories other than Steel Forming & Finishing will be
mass-based. To the degree that POTWs do not require
mass-based permits in subcategories other than Steel
Forming & Finishing, this analysis will overestimate
administrative costs.
2 Under the General Pretreatment Program, a facility's
discharges may be controlled through a "permit, order or similar
means". For simplicity, this document refers to the control
mechanism as a permit
C-2
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MP&M EEBA: Appendices
Appendix C: POTW Permitting Costs
b. Use the data from the POTW survey to
determine a high, middle, and low hourly
burden for permitting a single facility.
EPA defined the low and high estimates of hours such that
90% of the POTW responses fell above the low value and
90% of responses fell below the high value. The median
value is used to define the middle hourly burden.
c. Use the data from the POTW survey to
determine the average frequency of
performing certain administrative functions.
For administrative functions that are not performed at all
facilities, survey data were used to calculate the portion of
facilities requiring these functions. For example, the survey
data show that on average 38.5% of facilities submit a non-
compliance report.
d. Multiply the per-facility burden estimate
by the average hourly wage.
EPA determined a high, middle and low dollar cost of
administering the rule for a single facility by multiplying the
per-facility hour burden by the average hourly wage. The
POTW survey reported an average hourly labor rate of
$36.98 ($1999) for staff involved in permitting. This is a
fully-loaded cost, including salaries and fringe benefits.
e. Calculate the annualized cost of
administering the rule.
The number of facilities, hourly burden estimate, frequency
estimates, and hourly wage estimates are all combined to
determine the total cost of administering the rule. The type
of administrative activities required varies over time and the
total administrative cost is calculated over a 15 year time
period. EPA calculated the present value of total costs using
a seven percent discount rate, and then annualized the
present value using the same seven percent discount rate.
C.3 UNIT COSTS OF PERMITTING
ACTIVITIES
This section presents unit costs for the following permitting
activities:
> Permit application and issuance: developing and
issuing concentration-based permits at previously
unpermitted facilities; developing and issuing mass-
based permits at previously unpermitted facilities;
developing and issuing mass-based permits at
facilities with concentration-based permits;
providing technical guidance; and conducting
public and evidentiary hearings;
> Inspection: inspecting facilities both for the initial
permit development and to assess subsequent
compliance;
* Monitoring: sampling and analyzing permittee's
effluent; reviewing and recording permittee's
compliance self-monitoring reports; receiving,
processing, and acting on a permittee's non-
compliance reports; and reviewing a permittee's
compliance schedule report for permittees in
compliance and permittees not in compliance;
> Enforcement: issuing administrative orders and
administrative fines; and
> Repermitting.
EPA believes that these functions constitute the bulk of the
required administrative activities. EPA recognizes that there
are other relatively minor or infrequent administrative
functions (e.g., identifying facilities to be permitted,
providing technical guidance to permittees in years other
than the first year of the permit, or repermitting a facility in
significant non-compliance) but expects the associated costs
to be insignificant compared to the estimated costs for the
five major categories outlined above.
For each major administrative function, this section provides
below: (1) a description of the activities involved, (2) the
estimated percentage of facilities that require the
administrative function; (3) the frequency with which the
function is performed, and (4) high, medium and low
estimates of per facility hours and costs.
C.3.1 Permit Application and Issuance
Before issuing a wastewater discharge permit to a facility,
the permit authority typically inspects the facility, monitors
the facility's wastewater, and completes pollutant limits
calculations and permit paperwork. This section discusses
the costs of completing limits calculations and paperwork;
subsequent sections address inspection and monitoring
costs. This section also discusses the costs of technical
assistance that the control authority may provide facilities to
facilitate compliance with new limits. Finally, this section
includes the costs of public and evidentiary hearings that
may be required for some permits.
a. Issue a concentration-based permit at a
previously unpermitted facility
To issue a concentration-based permit, permit authorities
first review permit applications for completeness. If an
application is incomplete, the authorities notify the applicant
and request the missing information. Completed
applications are assigned to permit writers, who review the
applications in more detail as they develop permit
conditions. The effort required to complete these activities
C-3
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MP&M EEBA: Appendices
Appendix C: POTW Permitting Costs
depends, in part, on the extent to which the permit authority
has automated the permitting process.
EPA assumed that one-third of facilities are permitted in
each of the three years following the rule's effective date
because compliance is mandated within three years of the
date the standard is effective (40 CFR Section 403.6). EPA
further assumed that facilities are repermitted in five year
cycles. (The administrative costs of repermitting are
discussed separately below.) The actual number of facilities
that are permitted each year is likely to differ somewhat
from EPA's simplifying assumption. The Agency would
prefer to receive baseline facility monitoring reports from all
facilities early in the permitting process. Control authorities
are then expected to place a priority on issuing mass-based
permits. These minor differences in permit timing are not
expected to significantly change the estimated administrative
costs.
Table C.I: Administrative Activity
Percent of facilities for which
activity is required
100% of unpermitted MP&M facilities
that will be issued a concentration-based
permit (for costing purposes, this is
assumed to be 2/3 of all facilities being
issued a permit for the first time)
Develop and issue a concentration-based permit at a previously
unpermitted facility
Frequency
of activity
Onetime
Typical costs
Low
3.7 hours;
$137
Median
9.7 hours;
$359
High
30.7 hours;
$1,1345
b. Issue a mass-based permit for a
previously unpermitted facility
The administrative activities required to issue a
concentration-based permit are also required for a mass-
based permit. In addition, for mass-based permits issued
under the MP&M rule, the permit writer must determine
whether the facility practices pollution prevention and water
conservation methods equivalent to those specified as the
basis for BPT. If so, the permitting authority must
determine the facility's historical flow rate. If not, the
authority must derive a mass-based limit based on other
factors such as production rates. When a facility matches
BPT water conservation practices and provides historic flow
data, development of a mass-based permit is a relatively
straight-forward process. However, the task will be more
challenging at a facility practicing only limited water
conservation, particularly if the facility has multiple
production units and generates integrated process and
sanitary wastewaters.
Table C.2: Administrative Activity: Develop and issue a mass-based permit at a previously
unpermitted facility
Percent of facilities for which
activity is required
100% of unpermitted MP&M facilities that will be issued a
mass-based permit (for costing purposes, this is assumed to be
1/3 of all facilities being issued a permit for the first time)
Frequency
of activity
One time
Typical costs
Low
4.0 hours;
$148
Median
12.0 hours;
$444
High
40.0 hours;
$1,479
c. Issue a mass-based permit for a facility
with a concentration-based permit
Some of the activities described above for issuing a mass-
based permit will be simplified in cases where the facility
already holds a concentration-based permit. For example,
much of the basic information required in the permitting
application will already be in the permitting authorities'
records. However, the potentially labor-intensive task of
determining the flow basis for the permit remains.
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MP&M EEBA: Appendices
Appendix C: POTW Permitting Costs
Table C.3: Administrative Activity: Develop and issue a mass-based permit at a facility holding a
concentration -based permit
Percent of facilities for which
activity is required
100% of Steel Forming & Finishing facilities that currently
have a concentration-based permit, plus 1/3 of all other
MP&M facilities that currently hold a concentration-based
permit
Frequency
of activity
One time
Typical costs
Low
2.0 hours;
$74
Median
8.0 hours;
$296
High
21.0 hours;
$777
d. Provide technical guidance to a permittee
Technical guidance is frequently provided by permit
authorities to permittees concurrent with the issuance of a
new permit. There are no legal requirements that a permit
authority provide a permittee with technical guidance.
However, such guidance is generally in the interest of all
parties as it can expedite the permitting process, accelerate
the permittee's compliance, and reduce the compliance
burden. The extent of technical guidance provided varies
dramatically among permit authorities. In some cases, a
permit authority may hold a one-day workshop to provide
information on a new pretreatment standard to facilities. In
other cases, a permit authority may meet extensively with
individual permittees to educate them regarding their
responsibilities under pretreatment standards. The range of
technical guidance appears to depend on whether the
permittee already has a wastewater permit, whether the
permittee is part of a multi-facility company, the resources
of the permit authority, and the extent to which the permit
authority has written or standardized guidance available for
dissemination.
EPA assumed that permit authorities provide technical
guidance to all facilities being issued a new mass-based or
concentration-based permit under the MP&M pretreatment
standards. Costs for technical guidance were estimated
separately for facilities receiving a concentration-based
permit and facilities receiving a mass-based permit. EPA
assumed that technical guidance is provided in the year the
initial permit is issued.
Table C.4: Administrative Activity: Provide technical guidance to permittee on permit compliance
Percent of facilities for which
activity is required
100% of MP&M facilities being issued a new concentration-
based permit
100% of MP&M facilities being issued a new mass-based
permit
Frequency
of activity
One time
One time
Typical costs
Low
1.0 hour;
$37
2.0 hours;
$74
Median
3.3 hours;
$122
3.7 hours;
$137
High
10.7 hours;
$396
13.0 hours;
$481
z. Conduct a public or evidentiary hearing
on a proposed permit
Federal regulations provide for a period during which the
public may submit written comments on a proposed permit
for direct dischargers and/or request that a public hearing be
held. Permitting authorities for indirect dischargers may
have the same requirements. Thus, proposed permits for
indirect dischargers may be subject to public comments and
hearings. Pretreatment public hearings are typically
conducted at a scheduled local government (e.g., City
Council) meeting. The meetings may require substantial
preparation.
Federal regulations also provide for evidentiary hearings
following final permit determination for direct dischargers.
Again, permitting authorities for indirect dischargers may
have these requirements as well. Thus, final permit
determinations for indirect dischargers may be subject to
evidentiary hearings.
Data from the POTW survey indicated that a public or
evidentiary hearing would be required for 3.6% of indirect
dischargers being issued a new mass-based or concentration-
based permit, on average.
C-J
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MP&M EEBA: Appendices
Appendix C: POTW Permitting Costs
Table C.5: Administrative Activity: Conduct a public or evidentiary hearing
Percent of facilities for which
activity is required
3.6% of MP&M facilities being issued a new mass-based or
concentration-based permit
Frequency
of activity
One time
Typical costs
Low
2.3 hours;
$85
Median
8.0 hours;
$296
High
33.3 hours;
$1,231
C.3.2 Inspection
Permit authorities may choose to integrate their inspection
and monitoring work force or to administer these functions
separately. This discussion covers inspections only;
monitoring is discussed below. Inspections are performed
both to assess conditions for initial permitting and to
evaluate compliance with permit requirements. Inspections
involve record reviews, visual observations, and evaluations
of the treatment facilities, effluents, receiving waters, etc.
EPA assumed that the initial inspection would occur in the
same year a new permit is issued, and that all permitted
facilities would be inspected annually to assess compliance.
Table C.6: Administrative Activity: Inspect facility for permit development
Percent of facilities for which
activity is required
100% of MP&M facilities being issued a new permit
Frequency
of activity
One Time
Typical costs
Low
2.3 hours;
$85
Median
4.7 hours;
$174
High
12 hours;
$444
Table C.7: Administrative Activity: Inspect facility for compliance assessment
Percent of facilities for which
activity is required
100% of MP&M facilities being issued a new permit
Frequency
of activity
Annual
Typical costs
Low
1.8 hours;
$67
Median
3.7 hours;
$137
High
10.0 hours;
$370
C.3.3 Monitoring
Permitting authorities monitor facilities both to gather data
needed for permit development and to assess compliance
with permit conditions. Monitoring includes sampling and
analysis of the permittee's effluent, review of the permittee's
compliance self-monitoring reports, receipt of non-
compliance reports, and review of compliance schedule
reports. These activities are discussed below.
a. Sample and analyze permittees effluent
As noted above, inspection and monitoring staff may be
integrated or distinct. The costs of inspection were
presented above. Federal regulations require that the permit
authority "randomly sample and analyze the effluent from
industrial users...independent of information supplied by
industrial users" (40 CFR Part 403.8). The permit authority
obtains samples required by the permit and performs
chemical analyses. The results are used to verify the
accuracy of the permittee's self-monitoring program and
reports, determine the quantity and quality of effluents,
develop permits, and provide evidence for enforcement
proceedings where appropriate.
EPA estimated sampling costs for all facilities issued a new
permit under the MP&M rule, and assumed annual
monitoring. Although EPA requires only annual effluent
sampling, some localities sample more frequently. EPA
encourages this practice.
Table C.8: Administrative Activity: Sample and analyze permittees effluent
Percent of facilities for which
activity is required
100% of MP&M facilities being issued a
new permit
Frequency
of activity
Annual
Typical costs
Low
1.0 hour;
$37
Median
3.0 hours;
$111
High
14.0 hours;
$518
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MP&M EEBA: Appendices
Appendix C: POTW Permitting Costs
b. Review and record permittees compliance
self-monitoring reports
40 CFR Part 403.12 specifies that: "Any Industrial User
subject to a categorical pretreatment standard...shall submit
to the Control authority during the months of June and
December...a report indicating the nature and concentration
of pollutants in the effluent which are limited by such
categorical pretreatment standards." The permit authority
briefly reviews these submissions and may enter the
information into a computerized system and/or file the data.
EPA estimated the costs of handling annual self-monitoring
reports for all facilities being issued a new permit under the
MP&M rule.
Table C.9: Administrative Activity: Review and enter data from permittees compliance self-
monitoring reports
Percent of facilities for which
activity is required
100% of MP&M facilities being issued a
new permit
Frequency
of activity
Annual
Typical costs
Low
0.5 hours;
$18
Median
1.0 hour;
$37
High
3.5 hours;
$129
c. Receive, process, and act on a
permittees non-compliance report
Generally, when a permittee violates a permit condition, it
must submit a non-compliance report to the permit authority.
Permittees report both unanticipated bypasses or upsets and
violations of maximum daily discharge limits. The permit
authority receives and processes both verbal and written
non-compliance reports. In some cases, immediate action by
the permit authority is required to mitigate the problem.
Data from the POTW survey indicate that 38.5 percent of all
facilities submit at least one non-compliance report annually.
Of facilities that submit at least one non-compliance report,
the median number of reports filed per year is 5 reports.
Table C.10: Administrative Activity: Receive, process and act on a
permittees non-compliance reports
Percent of facilities for which
activity is required
38.5% of all indirect dischargers receiving a
new permit.
Frequency
of activity
5 times per year
Typical costs
Low
1.0 hour;
$37
Median
2.0 hours;
$74
High
5.7 hours;
$211
d. Review a permittees compliance schedule
report
Permittees submit reports to permit authorities that state
whether compliance schedule milestones contained in their
permits have been met. If the facility is in compliance, the
permit authority reviews and files the report.
Data from the POTW survey indicate that approximately
17% of all facilities are issued compliance milestones. Of
these facilities, 94% meet the milestones. Facilities submit
an average of two compliance milestone reports per year.
The cost of handling the report depends on whether the
facility is in compliance with the schedule.
Table C.ll: Administrative Activity: Review a compliance schedule report
Percent of facilities for which
activity is required
Meeting milestones: 16.0% of all facilities issued a new permit
(94% of the 17% who have compliance milestones).
Not meeting milestones: 1% of all facilities issued a new
permit (6% of the 17% who have compliance milestones).
Frequency
of activity
2 reports per
year
2 reports per
year
Typical costs
Low
0.5 hours;
$18
0.8 hours;
$30
Median
1.0 hour;
$37
1.8 hours;
$67
High
3.0 hours;
$111
6.0 hours;
$222
C-7
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MP&M EEBA: Appendices
Appendix C: POTW Permitting Costs
C.3.4 Enforcement
When a permitting authority identifies a permit violation, the
authority determines and implements an appropriate
enforcement action. Considerations when determining
enforcement response include (1) the severity of the permit
violation, (2) the degree of economic benefit obtained by the
permittee through the violation, (3) previous enforcement
actions taken against the violator, (4) the deterrent effect of
the response on similarly situated permittees, and (5)
considerations of fairness and equity. EPA estimated
administrative costs for two levels of enforcement actions:
(1) less severe actions such as issuing an administrative
order, and (2) more severe activities such as levying an
administrative fine.
EPA estimated that, annually, seven percent of facilities
issued a new permit under the MP&M rule will require a
minor enforcement action, such as issuing an administrative
compliance order. In addition, EPA estimated that seven
percent of facilities receiving a new permit will require more
severe enforcement actions such as a fine or penalty.
Table C. 12: Adm|m^
Percent of facilities for which
activity is required
Seven percent of MP&M facilities being issued a new permit
Frequency
of activity
Annual
Low
1.0 hour;
$37
Typical costs
Median
3.7 hours;
$137
iy*LA?t!'y!tyA.*\i!??r..?!?f?j^
Percent of facilities for which
activity is required
Seven percent of MP&M facilities being issued a new permit
Frequency
of activity
Annual
Low
1.0 hour;
$37
Typical costs
Median
5.3 hours;
$196
C.3.5 Repermitting
The duration of permits cannot exceed five years. Renewing
a permit for a facility in compliance with an existing permit
is expected to be a relatively straightforward task. The data
required in the permit application generally requires few
changes, although pollutant limits may need to be
recalculated in some cases. The labor required for
repermitting depends, in part, on the extent to which the
permit authority has automated the paperwork.
Percent of facilities for which
activity is required
100% of MP&M facilities being issued a new permit
Frequency
of activity
every 5 years
Low
1.0 hour;
$37
Typical costs
Median
4.0 hours;
$148
CA POTW ADMINISTRATIVE COSTS BY
OPTION
Exhibits C. 1 through C.7 at the end of this chapter present
the calculation of POTW permitting costs for the proposed
rule and the two regulatory alternatives considered by EPA.
Exhibit Cl provides an overview of the permitting activities,
the estimated percentage of facilities that require the
administrative function, the frequency with the function is
performed, and per facility hours and costs for each
function.
Exhibit C.2 contains the per facility hour burden and other
assumptions described above for each of the three types of
permitting (new concentration-based permit, new mass-
based permit, and converting a concentration-based to a
mass-based permit.)
Exhibits C.3 through C.5 show hours by type of permit for
the low, medium, and high estimate of per-facility burden,
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MP&M EEBA: Appendices
Appendix C: POTW Permitting Costs
respectively. These exhibits also summarize costs and
dollars by year and permit type.
Exhibit C.6 presents the number of facilities requiring
different types of permitting, for each of the regulatory
options. The exhibit shows the total number of facilities that
will be subject to requirements, the baseline permit status of
those facilities, and the number of facilities by expected
post-compliance permit status. These estimates are based on
facility survey information about baseline permit status, the
results of the facility impact analysis described in Chapter 5,
and EPA's assumption for costing purposes that as many as
one-third of all MP&M facilities (except Steel Forming &
Finishing) could be issued mass-based permits by the
permitting authority. The exhibit also shows the number of
currently-permitted facilities that are projected to close as a
result of the rule, and which will therefore no longer require
permitting.
Finally, Exhibit C.6 shows the resulting calculation of
POTW administrative hours and costs by year for each
regulatory option. This exhibit also shows the present value
of these costs, the annualized cost, and the maximum hours
and costs incurred in any one year, for each option. These
calculations reflect the incremental number of facilities
requiring different types of permitting, inspection,
monitoring, enforcement and repermitting in each year
multiplied by the unit hours and cost per facility for those
activities. All facilities are assumed to receive a permit
under the proposed rule within the three-year compliance
period. Some facilities with existing permits are repermitted
sooner than they otherwise would be on the normal five-year
permitting cycle. The cost analyses calculates incremental
costs by subtracting the costs of repermitting these facilities
on a five-year schedule from the costs of repermitting all
such facilities within three years. EPA assumes that the
required initial permitting activities will be equally divided
over the three-year period. The analysis also calculates the
net increase in the number of facilities requiring permitting
by subtracting the number of facilities that close due to the
rule from the number of facilities that will require new
permits under the proposed rule.
More detailed information on these cost calculations is
provided in the docket for the proposed rule.
C-9
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MP&M EEBA: Appendices
Appendix C: POTW Permitting Costs
APPENDIX C EXHIBITS
Exhibit C-l: Government Administrative Activities for Indirect Dischargers: Per Facility Hours and Costs
Exhibit C-2: Per-Facility Hours and Assumptions
Exhibit C-3: Low Estimate of Hours and Costs per Facility
Exhibit C-4: Medium Estimate of Hours and Costs per Facility
Exhibit C-5: High Estimate of Hours and Costs per Facility
Exhibit C-6: Number of Facilities Requiring Additional Permitting
Exhibit C-7: POTW Administrative Costs by Option
C-10
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MP&M EEBA: Appendices
Appendix C: POTW Permitting Costs
Exhibit C.I: Government Administrative Activities for Indirect Dischargers: Per Facility Hours and Costs
Administrative Activity
Develop and issue a concentration-based
permit at a previously unpermitted facility
Develop and issue a mass-based permit at
a previously unpermitted facility
Develop and issue a mass-based permit at
a facility holding a concentration-based
permit
Provide technical guidance to a permittee
on permit compliance
Conduct a public or evidentiary hearing
Inspect facility for permit development
Inspect facility for compliance assessment
Sample and analyze permittee's effluent
Review and enter data from permittee' s
compliance self-monitoring reports
Receive, process and act on a permittee's
non-compliance reports
Review a compliance schedule report
Minor enforcement action e.g., issue an
administrative order
Minor enforcement action, e.g., impose
an administrative fine
Repermit
Percent of facilities for which
activity is required
100% of unpermitted facilities being
issued a new concentration-based permit
(2/3 of new permits)
100% of unpermitted MP&M facilities
being issued a new mass-based permit
(1/3 of new permits )
All Steel Forming & Finishing facilities
with a concentration-based permits and
1/3 of other facilities with a
concentration-based permit
100% of MP&M facilities being issued a
new concentration-based permit
100% of MP&M facilities being issued a
new mass-based permit
3 .2% of MP&M facilities being issued a
new mass-based or concentration-based
permit
100% of MP&M facilities being issued a
new permit
100% of MP&M facilities being issued a
new permit
100% of MP&M facilities being issued a
new permit
100% of MP&M facilities being issued a
new permit
38.5% of all indirect dischargers
receiving a new permit.
Meeting milestones: 16.0% of all
facilities issued a new permit (94% of
the 17% who have compliance
milestones).
Not meeting milestones: 1% of all
facilities issued a new permit (6% of the
17% who have compliance milestones).
7% of MP&M facilities being issued a
new permit
7% of MP&M facilities being issued a
new permit
100% of MP&M facilities being issued a
new permit
Frequency
of activity
One time
One time
One time
One time
One time
One time
One Time
Annual
Annual
Annual
5 times per year
2 reports per year
2 reports per year
Annual
Annual
Every 5 years
Typical hours and costs
Low
3. 7 hours;
$137
4.0 hours;
$148
2.0 hours;
$74
1.0 hour;
$37
2.0 hours;
$74
2.3 hours;
$85
2.3 hours;
$85
1.8 hours;
$67
1.0 hour;
$37
0.5 hours;
$18
1.0 hour;
$37
0.5 hours;
$18
0.8 hours;
$30
1.0 hour;
$37
1.0 hour;
$37
1.0 hour;
$37
Median
9.7 hours;
$359
12.0 hours;
$444
8.0 hours;
$296
3.3 hours;
$122
3. 7 hours;
$137
8.0 hours;
$296
4.7 hours;
$174
3. 7 hours;
$137
3.0 hours;
$111
1.0 hour;
$37
2.0 hours;
$74
1.0 hour;
$37
1.8 hours;
$67
3. 7 hours;
$137
5.3 hours;
$196
4.0 hours;
$148
High
30.7 hours;
$1,135
40.0 hours;
$1,479
21.0 hours;
$777 year
10.7 hours;
$396
13.0 hours;
$481
33.3 hours;
$1,231
12.0 hours;
$444
10.0 hours;
$370
14.0 hours;
$518
3.5 hours;
$129
5. 7 hours;
$211
3.0 hours;
$111
6.0 hours;
$222
13.3 hours;
$492
24.7 hours;
$913
17.0 hours;
$629
c-n
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Exhibit C.2: Per-Facility Hours and Assumptions
Activity
Low
Medium | High | % Facil
x/yr
Notes
New concentration-based permit
develop and issue permit
provide technical guidance
conduct public or evidentiary hearings
inspection for permit development
inspection for compliance assessment
sample and analyze effluent
review & record self-monitoring reports
process & act on non-compliance reports
review compliance schedule report - in compliance with schedule
review compliance schedule report - not in compliance with schedule
minor enforcement action (e.g., admin order)
minor enforcement action (e.g., admin fine)
repermit
3.7
1.0
2.3
2.3
1.8
1.0
0.5
1.0
0.5
0.8
1.0
1.0
1.0
9.7
3.3
8.0
4.7
3.7
3.0
1.0
2.0
1.0
1.8
3.7
5.3
4.0
30.7
10.7
33.3
12.0
10.0
14.0
3.5
5.7
3.0
6.0
13.3
24.7
17.0
100.0%
100.0%
3.2%
100.0%
100.0%
100.0%
100.0%
38.5%
16.0%
1.0%
7.0%
7.0%
100.0%
1
1
1
1
1
1
1
5
2
2
1
1
1
one-time
one-time
one-time, 3.2% of facilities
one-time
annual
annual
annual
5x/year, 38.5% of facilities
2x/yr, 17% of facilities with compliance milestones, of which 94% in compliance
2x/yr, 17% of facilities with compliance milestones, of which 6% not in compliance
annual, 7% of facilities
annual, 7% of facilities
every three years
New mass-based permit
develop and issue permit
provide technical guidance
conduct public or evidentiary hearings
inspection for permit development
inspection for compliance assessment
sample and analyze effluent
review & record self-monitoring reports
process & act on non-compliance reports
review compliance schedule report - in compliance with schedule
review compliance schedule report - not in compliance with schedule
minor enforcement action (e.g., admin order)
minor enforcement action (e.g., admin fine)
repermit
4.0
2.0
2.3
2.3
1.8
1.0
0.5
1.0
0.5
0.8
1.0
1.0
1.0
12.0
3.7
8.0
4.7
3.7
3.0
1.0
2.0
1.0
1.8
3.7
5.3
4.0
40.0
13.0
33.3
12.0
10.0
14.0
3.5
5.7
3.0
6.0
13.3
24.7
17.0
100.0%
100.0%
3.2%
100.0%
100.0%
100.0%
100.0%
38.5%
16.0%
1.0%
7.0%
7.0%
100.0%
1
1
1
1
1
1
1
5
2
2
1
1
1
one-time
one-time
one-time, 3.2% of facilities
one-time
annual
annual
annual
5x/year, 38.5% of facilities
2x/yr, 17% of facilities with compliance milestones, of which 94% in compliance
2x/yr, 17% of facilities with compliance milestones, of which 6% not in compliance
annual, 7% of facilities
annual, 7% of facilities
every three years
Converting concentration-based to mass-based
develop and issue permit
provide technical guidance
conduct public or evidentiary hearings
inspection for permit development
inspection for compliance assessment
sample and analyze effluent
review & record self-monitoring reports
process & act on non-compliance reports
review compliance schedule report - in compliance with schedule
review compliance schedule report - not in compliance with schedule
minor enforcement action (e.g., admin order)
minor enforcement action (e.g., admin fine)
repermit
2.0
1.8
1.0
0.5
1.0
0.5
0.8
1.0
1.0
1.0
8.0
3.7
3.0
1.0
2.0
1.0
1.8
3.7
5.3
4.0
21.0
10.0
14.0
3.5
5.7
3.0
6.0
13.3
24.7
17.0
100.0%
100.0%
100.0%
100.0%
38.5%
16.0%
1.0%
7.0%
7.0%
100.0%
1
1
1
1
5
2
2
1
1
1
one-time
annual
annual
annual
5x/year, 38.5% of facilities
2x/yr, 17% of facilities with compliance milestones, of which 94% in compliance
2x/yr, 17% of facilities with compliance milestones, of which 6% not in compliance
annual, 7% of facilities
annual, 7% of facilities
every three years
Source: estimates of hours by activity and average hourly rate from the 1996 MP&MPOTW Survey.
Discount rate: 7%
Average hourly rate: $36.98 (1999$)
-------
Exhibit C.3: Low Estimate of Hours and Costs per Facility
(average considering frequency of activity and percent of facilities requiring activity)
Activity
Initial Year
Annual (non-
permitting year)
Repermit Year
New concentration-based permit
develop and issue permit
provide technical guidance
conduct public or evidentiary hearings
inspection for permit development
inspection for compliance assessment
sample and analyze effluent
review & record self-monitoring reports
process & act on non-compliance reports
review compliance schedule report - in compliance with schedule
review compliance schedule report - not in compliance with schedule
minor enforcement action (e.g., admin order)
minor enforcement action (e.g., admin fine)
repermit
Total Hours by Year
Total Dollars by Year
4
1
0
2
2
1
1
2
0
0
0
0
13
$466
2
1
1
2
0
0
0
0
6
$205
2
1
1
2
0
0
0
0
1
7
$242
New mass-based permit
develop and issue permit
provide technical guidance
conduct public or evidentiary hearings
inspection for permit development
inspection for compliance assessment
sample and analyze effluent
review & record self-monitoring reports
process & act on non-compliance reports
review compliance schedule report - in compliance with schedule
review compliance schedule report - not in compliance with schedule
minor enforcement action (e.g., admin order)
minor enforcement action (e.g., admin fine)
repermit
Total Hours by Year
Total Dollars by Year
4
2
0
2
2
1
1
2
0
0
0
0
14
$515
1
1
1
2
0
0
0
0
6
$205
1
1
1
2
0
0
0
0
1
7
$242
Upgrading from concentration-based to mass-based
develop and issue permit
provide technical guidance
conduct public or evidentiary hearings
inspection for permit development
inspection for compliance assessment
sample and analyze effluent
review & record self-monitoring reports
process & act on non-compliance reports
review compliance schedule report - in compliance with schedule
review compliance schedule report - not in compliance with schedule
minor enforcement action (e.g., admin order)
minor enforcement action (e.g., admin fine)
repermit
Total Hours by Year
Total Dollars by Year
2
0
0
0
2
1
1
2
0
0
0
0
8
$279
1
1
1
2
0
0
0
0
6
$205
1
1
1
2
0
0
0
0
1
7
$242
annualized over 15 year period at 7 %
-------
Exhibit C.4: Medium Estimate of Hours and Costs per Facility
(average considering frequency of activity and percent of facilities requiring activity)
Activity
Initial Year
Annual (non-
permitting year)
Repermit Year
New concentration-based permit
develop and issue permit
provide technical guidance
conduct public or evidentiary hearings
inspection for permit development
inspection for compliance assessment
sample and analyze effluent
review & record self-monitoring reports
process & act on non-compliance reports
review compliance schedule report - in compliance with schedule
review compliance schedule report - not in compliance with schedule
minor enforcement action (e.g., admin order)
minor enforcement action (e.g., admin fine)
repermit
Total Hours by Year
Total Dollars by Year
10
3
0
5
4
3
1
4
0
0
0
0
30
$1,128
4
3
1
4
0
0
0
0
13
$464
4
3
1
4
0
0
0
0
4
17
$612
New mass-based permit
develop and issue permit
provide technical guidance
conduct public or evidentiary hearings
inspection for permit development
inspection for compliance assessment
sample and analyze effluent
review & record self-monitoring reports
process & act on non-compliance reports
review compliance schedule report - in compliance with schedule
review compliance schedule report - not in compliance with schedule
minor enforcement action (e.g., admin order)
minor enforcement action (e.g., admin fine)
repermit
Total Hours by Year
Total Dollars by Year
12
4
0
5
4
3
1
4
0
0
0
0
33
$1,227
4
3
1
4
0
0
0
0
13
$464
Upgrading front concentration-based to mass-based
develop and issue permit
provide technical guidance
conduct public or evidentiary hearings
inspection for permit development
inspection for compliance assessment
sample and analyze effluent
review & record self-monitoring reports
process & act on non-compliance reports
review compliance schedule report - in compliance with schedule
review compliance schedule report - not in compliance with schedule
minor enforcement action (e.g., admin order)
minor enforcement action (e.g., admin fine)
repermit
Total Hours by Year
Total Dollars by Year
8
0
0
0
4
3
1
4
0
0
0
0
21
$759
4
3
1
4
0
0
0
0
13
$464
4
3
1
4
0
0
0
0
4
17
$612
4
3
1
4
0
0
0
0
4
17
$612
annualized over 15 year period at 7 %
-------
Exhibit C.5: High Estimate of Hours and Costs per Facility
(average considering frequency of activity and percent of facilities requiring activity)
Activity
Initial Year
Annual (non-
permitting year)
Repermit Year
New concentration-based permit
develop and issue permit
provide technical guidance
conduct public or evidentiary hearings
inspection for permit development
inspection for compliance assessment
sample and analyze effluent
review & record self-monitoring reports
process & act on non-compliance reports
review compliance schedule report - in compliance with schedule
review compliance schedule report - not in compliance with schedule
minor enforcement action (e.g., admin order)
minor enforcement action (e.g., admin fine)
repermit
Total Hours by Year
Total Dollars by Year
31
11
1
12
10
14
4
11
1
0
1
2
97
$3,575
10
14
4
11
1
0
1
2
42
$1,561
10
14
4
11
1
0
1
2
17
59
$2,190
New mass-based permit
develop and issue permit
provide technical guidance
conduct public or evidentiary hearings
inspection for permit development
inspection for compliance assessment
sample and analyze effluent
review & record self-monitoring reports
process & act on non-compliance reports
review compliance schedule report - in compliance with schedule
review compliance schedule report - not in compliance with schedule
minor enforcement action (e.g., admin order)
minor enforcement action (e.g., admin fine)
repermit
Total Hours by Year
Total Dollars by Year
40
13
1
12
10
14
4
11
1
0
1
2
108
$4,004
10
14
4
11
1
0
1
2
42
$1,561
Upgrading front concentration-based to mass-based
develop and issue permit
provide technical guidance
conduct public or evidentiary hearings
inspection for permit development
inspection for compliance assessment
sample and analyze effluent
review & record self-monitoring reports
process & act on non-compliance reports
review compliance schedule report - in compliance with schedule
review compliance schedule report - not in compliance with schedule
minor enforcement action (e.g., admin order)
minor enforcement action (e.g., admin fine)
repermit
Total Hours by Year
Total Dollars by Year
21
0
0
0
10
14
4
11
1
0
1
2
63
$2,338
10
14
4
11
1
0
1
2
42
$1,561
10
14
4
11
1
0
1
2
17
59
$2,190
10
14
4
11
1
0
1
2
17
59
$2,190
annualized over 15 year period at 7 %
-------
Exhibit C.6: Number of Facilities Requiring Additional Permitting
Proposed Rule
Number of facilities operating post-regulation requiring a permit
4,944
Of facilities operating post-regulation:
existing concentration-based
existing mass-based
no permit in baseline
concentration based to be converted to mass-based
new concentration-based
new mass-based
Number of currently permitted facilities closing (no longer requiring a permit)
629
3,667
648
223
432
216
143
Of facilities closing due to the rule:
existing concentration-based
existing mass-based
12
131
Option 2/6/10
Number of facilities operating post-regulation requiring a permit
53,009
Of facilities operating post-regulation:
existing concentration-based
existing mass-based
no permit in baseline
concentration based to be converted to mass-based
new concentration-based
new mass-based
Number of currently permitted facilities closing (no longer requiring a permit)
Of facilities closing due to the rule:
existing concentration-based
existing mass-based
25,232
3,764
24,013
8,424
16,009
8,004
1,020
889
131
Option 4/8
Number of facilities operating post-regulation requiring a permit
51,344
Of facilities operating post-regulation:
existing concentration-based
existing mass-based
no permit in baseline
concentration based to be converted to mass-based
new concentration-based
new mass-based
Number of currently permitted facilities closing (no longer requiring a permit)
25,226
3,440
22,678
8,422
15,119
7,559
1,348
Of facilities closing due to the rule:
existing concentration-based
existing mass-based
894
454
-------
Exhibit C.7: POTW Administrative Costs by Option (@ 7% discount rate)
Proposed Rule
Year Relative to Promulgation of Rule
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Total Hours
High
Medium
Low
29,254
8,658
3,173
36,360
10,768
4,106
43,466
12,879
5,038
6,225
2,780
1,910
6,225
2,780
1,910
34,241
9,372
3,558
34,241
9,372
3,558
34,241
9,372
3,558
6,225
2,780
1,910
6,225
2,780
1,910
34,241
9,372
3,558
34,241
9,372
3,558
34,241
9,372
3,558
6,225
2,780
1,910
6,225
2,780
1,910
Total Costs
High
Medium
Low
$1,081,831
$320,171
$117,330
$1,344,609
$398,209
$151,823
$1,607,388
$476,248
$186,316
$230,212
$102,791
$70,649
$230,212
$102,791
$70,649
$1,266,244
$346,563
$131,592
$1,266,244
$346,563
$131,592
$1,266,244
$346,563
$131,592
$230,212
$102,791
$70,649
$230,212
$102,791
$70,649
$1,266,244
$346,563
$131,592
$1,266,244
$346,563
$131,592
$1,266,244
$346,563
$131,592
$230,212
$102,791
$70,649
$230,212
$102,791
$70,649
NPV
Max One Year Hours
Max One Year Costs
Annualized Cost
High
$8,310,860
43,466
$1,607,388
$912,488
Medium
$2,483,585
12,879
$476,248
$272,684
Low
$1,047,744
5,038
$186,316
$115,037
Option 2/6/10
Year Relative to Promulgation of Rule
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Total Hours
High
Medium
Low
863,939
272,917
109,027
1,187,479
368,999
151,496
1,511,019
465,082
193,965
868,565
264,235
121,404
868,565
264,235
121,404
1,168,950
334,913
139,073
1,168,950
334,913
139,073
1,168,950
334,913
139,073
868,565
264,235
121,404
868,565
264,235
121,404
1,168,950
334,913
139,073
1,168,950
334,913
139,073
1,168,950
334,913
139,073
868,565
264,235
121,404
$868,565
$264,235
$121,404
Total Costs
High
Medium
Low
$31,948,466
$10,092,463
$4,031,823
$43,912,970
$13,645,595
$5,602,326
$55,877,474
$17,198,727
$7,172,829
$32,119,541
$9,771,403
$4,489,511
$32,119,541
$9,771,403
$4,489,511
$43,227,754
$12,385,100
$5,142,936
$43,227,754
$12,385,100
$5,142,936
$43,227,754
$12,385,100
$5,142,936
$32,119,541
$9,771,403
$4,489,511
$32,119,541
$9,771,403
$4,489,511
$43,227,754
$12,385,100
$5,142,936
$43,227,754
$12,385,100
$5,142,936
$43,227,754
$12,385,100
$5,142,936
$32,119,541
$9,771,403
$4,489,511
$32,119,541
$9,771,403
$4,489,511
NPV
Max One Year Hours
Max One Year Costs
Annualized Cost
High
$357,680,237
1,511,019
$55,877,474
$39,271,367
Medium
$107,121,278
465,082
$17,198,727
$11,761,340
Low
$45,719,037
193,965
$7,172,829
$5,019,704
Option 4/8
Year Relative to Promulgation of Rule
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Total Hours
High
Medium
Low
812,714
257,134
102,504
1,112,853
346,267
141,902
1,412,992
435,400
181,299
798,371
243,389
112,189
798,371
243,389
112,189
1,089,320
311,847
129,304
1,089,320
311,847
129,304
1,089,320
311,847
129,304
798,371
243,389
112,189
798,371
243,389
112,189
1,089,320
311,847
129,304
1,089,320
311,847
129,304
1,089,320
311,847
129,304
798,371
243,389
112,189
798,371
243,389
112,189
Total Costs
High
Medium
Low
$30,054,148
$9,508,810
$3,790,616
$41,153,303
$12,804,958
$5,247,531
$52,252,458
$16,101,105
$6,704,445
$29,523,746
$9,000,507
$4,148,760
$29,523,746
$9,000,507
$4,148,760
$40,283,052
$11,532,108
$4,781,660
$40,283,052
$11,532,108
$4,781,660
$40,283,052
$11,532,108
$4,781,660
$29,523,746
$9,000,507
$4,148,760
$29,523,746
$9,000,507
$4,148,760
$40,283,052
$11,532,108
$4,781,660
$40,283,052
$11,532,108
$4,781,660
$40,283,052
$11,532,108
$4,781,660
$29,523,746
$9,000,507
$4,148,760
$29,523,746
$9,000,507
$4,148,760
NPV
Max One Year Hours
Max One Year Costs
Annualized Cost
High
$332,591,953
1,412,992
$52,252,458
$36,516,809
Medium
$99,684,264
435,400
$16,101,105
$10,944,796
Low
$42,526,298
181,299
$6,704,445
$4,669,159
-------
MP&M EEBA: Appendices
Appendix D: Baseline and Post-Compliance Pollutant Loads
Appendix D'- Baseline and Post-
Compliance Pollutant Loads
INTRODUCTION
This appendix provides detailed information on baseline and
post-compliance pollutant discharges by pollutant type,
subcategory and discharge status. The reported loadings for
indirect dischargers are facility discharges, and do not take
account of POTW removals. The data include only loadings
from water-discharging facilities potentially subject to the
proposed MP&M regulation. They exclude discharges from
facilities that are projected to close in the baseline, as described
in Chapter 5 of the EEBA. Post-compliance discharges under
the proposed rule include no change in loadings for facilities
excluded under the rule by the subcategory exclusions or the low
flow cutoffs, and include zero discharges for facilities that are
projected to close due to the rule. Loadings are reported both as
pounds of pollutant and as toxic-weighted pound-equivalents.
The unweighted pounds are not summed across the types of
pollutants to show total pollutant dischargers because some of
the non-toxic pollutant categories overlap. These categories
have zero toxic weights, so that the overlap does not cause
double-counting when summing toxic-weighted pounds-
equivalent.
APPENDIX CONTENTS:
Table D. 1: Baseline Toxic-Weighted Discharges
by Type of Pollutant for Facilities Regulated
under the Proposed Rule Direct
Dischargers (Pounds Equivalent) D.2
Table D.2: Post-Compliance Toxic-Weighted
Discharges by Type of Pollutant:
Proposed Rule Direct Dischargers
(Pounds Equivalent) D.3
Table D.3: Baseline Pollutant Discharges by Type of
Pollutant for Facilities Regulated
under the Proposed Rule Direct
Dischargers (Pounds) D.4
Table D.4: Post-Compliance Pollutant Discharges
by Type of Pollutant: Proposed Rule
Direct Dischargers (Pounds) D.5
Table D.5: Baseline Toxic-Weighted Discharges by
Type of Pollutant for Facilities Regulated
under the Proposed Rule Indirect
Dischargers (Pounds Equivalent) D.6
Table D.6: Post-Compliance Toxic-Weighted
Discharges by Type of Pollutant:
Proposed Rule Inirect Dischargers
(Pounds Equivalent) D.7
Table D.7: Baseline Pollutant Discharges by
Type of Pollutant for Facilities Regulated
under the Proposed Rule Indirect
Dischargers (Pounds) D.8
Table D.8: Post-Compliance Pollutant Discharges
by Type of Pollutant: Proposed Rule
Indirect Dischargers (Pounds) D.9 I
D-l
-------
MP&M EEBA: Appendices
Appendix D: Baseline and Post-Compliance Pollutant Loads
Table D.I: Baseline Toxic- Weighted Discharges by Type of Pollutant
for Facilities Regulated under the Proposed Rule
Direct Dischargers" (Pounds Equivalent)
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Priority Pollutants
Metals
298,514
3,897
21,484
50,190
7,695
532
950
383,262
Organics
44,397
410
717
7,529
1,859
120
233
55,265
Cyanide
6,254
6,288
1,809
2,496
33
0
0
16,880
Nonconventional
Pollutants
Metals
311,753
4,364
29,310
61,415
10,677
410
530
418,459
Organics
20,694
193
6,020
3,342
795
66
102
31,212
Conventional Pollutants
COD
0
0
0
0
0
0
0
0
Oil & Gas
0
0
0
0
0
0
0
0
TSS
0
0
0
0
0
0
0
0
Total
681,612
15,152
59,340
124,972
21,059
1,128
1,815
905,078
a. Excludes discharges from facilities that are projected to close in the baseline.
Source: U.S. EPA analysis.
D-l
-------
MP&M EEBA: Appendices
Appendix D: Baseline and Post-Compliance Pollutant Loads
Table D.2: Post-Compliance Toxic- Weighted Discharges by Type of Pollutant: Proposed Rule
Direct Dischargers" (Pounds Equivalent)
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Priority Pollutants
Metals
50,763
401
3,761
16,039
3,870
602
894
76,330
Organics
9,923
47
564
4,655
1,237
174
243
16,843
Cyanide
2,772
41
331
1,268
26
0
0
4,438
Nonconventional
Pollutants
Metals
45,828
508
4,192
17,333
16,817
419
656
85,753
Organics
5,890
191
3,075
1,957
585
72
103
11,873
Conventional Pollutants
COD
0
0
0
0
0
0
0
0
Oil & Gas
0
0
0
0
0
0
0
0
TSS
0
0
0
0
0
0
0
0
Total
115,176
1,188
11,923
41,252
22,535
1,267
1,896
195,237
a. Excludes discharges from facilities that are projected to close in the baseline.
Source: U.S. EPA analysis.
D-3
-------
MP&M EEBA: Appendices
Appendix D: Baseline and Post-Compliance Pollutant Loads
Table D.3: Baseline Pollutant Discharges by Type of Pollutant
for Facilities Regulated under the Proposed Rule
Direct Dischargers" (Pounds)
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Priority Pollutants
Metals
766,448
14,521
53,752
108,058
9,170
455
2,466
954,870
Organics
286,837
1,836
4,406
38,894
9,406
604
1,875
343,858
Cyanide
5,686
5,716
1,645
2,269
30
0
0
15,346
Nonconventional
Pollutants
Metals
4,331,006
27,813
221,206
688,851
599,419
54,261
86,024
6,008,580
Organics
4,782,918
3,804
30,203
129,267
125,673
988
4,524
5,077,377
Conventional Pollutants
COD
176,757,897
266,693
1,722,113
6,044,202
6,406,304
169,844
976,452
192,343,505
Oil & Gas
5,392,931
16,574
261,999
195,070
964,705
51,978
8,496,729
15,379,986
TSS
9,407,387
17,747
100,432
873,450
413,961
18,180
18,402
10,849,559
a. Excludes discharges from facilities that are projected to close in the baseline.
Source: U.S. EPA analysis.
D-4
-------
MP&M EEBA: Appendices
Appendix D: Baseline and Post-Compliance Pollutant Loads
Table D.4: Post -Compliance Pollutant Discharges by Type of Pollutant
Direct Dischargers" (Pounds)
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Priority Pollutants
Metals
47,761
399
3,248
13,806
3,434
513
1,813
70,974
Organics
66,405
260
3,584
23,864
8,476
859
2,345
105,793
Cyanide
2,520
38
301
1,153
23
0
0
4,035
Nonconventional
Pollutants
Metals
1,118,109
7,796
72,616
390,447
621,142
176,677
87,112
2,473,899
Organics
114,424
837
9,202
68,448
55,322
1,229
4,782
254,244
Proposed Rule
Conventional Pollutants
COD
5,220,923
46,895
382,100
1,514,238
5,626,916
129,791
1,224,437
14,145,300
Oil & Gas
298,025
2,907
23,686
93,865
123,264
6,767
46,242
594,756
TSS
313,681
2,561
20,868
82,700
233,648
9,254
56,260
718,972
a. Excludes discharges from facilities that are projected to close in the baseline.
Source: U.S. EPA analysis.
D-5
-------
MP&M EEBA: Appendices
Appendix D: Baseline and Post-Compliance Pollutant Loads
Table D.5: Baseline Toxic- Weighted Discharges by Type of Pollutant
for Facilities Regulated under the Proposed Rule
Indirect Dischargers0 (Pounds Equivalent)
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Priority Pollutants
Metals
13,665,657
2,296,974
20,090
909,088
248,286
98,038
1,083
94
17,239,310
Organics
207,071
25,403
4,701
12,091
3,873
26,814
304
23
280,280
Cyanide
542,448
7,537,115
0
860,587
1,239
358
0
0
8,941,747
Nonconventional
Pollutants
Metals
5,004,316
1,076,583
15,749
908,363
142,400
171,988
217
129
7,319,745
Organics
111,124
47,443
2,171
27,378
1,446
13,051
108
11
202,732
Conventional Pollutants
COD
0
0
0
0
0
0
0
0
0
Oil & Gas
0
0
0
0
0
0
0
0
0
TSS
0
0
0
0
0
0
0
0
0
Total
19,530,616
10,983,518
42,711
2,717,507
397,244
310,249
1,712
257
33,983,814
a. Excludes discharges from facilities that are projected to close in the baseline. Discharges discussed in this table are total discharges from the facility, and do not account for POTW pollutant removals.
Source: U.S. EPA analysis.
D-6
-------
MP&M EEBA: Appendices
Appendix D: Baseline and Post-Compliance Pollutant Loads
Table D.6: Post-Compliance Toxic- Weighted Discharges by Type of Pollutant: Proposed Rule
Indirect Dischargers" (Pounds Equivalent)
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Priority Pollutants
Metals
1,214,023
66,434
20,090
44,709
5,502
105,183
1,083
94
1,457,118
Organics
88,546
12,693
4,701
8,942
1,604
29,250
304
23
146,063
Cyanide
27,558
5,036
0
4,074
521
360
0
0
37,549
Nonconventional
Pollutants
Metals
895,856
70,283
15,749
50,424
7,016
175,617
217
129
1,215,291
Organics
64,162
37,185
2,171
35,107
740
14,110
108
11
153,594
Conventional Pollutants
COD
0
0
0
0
0
0
0
0
0
Oil & Gas
0
0
0
0
0
0
0
0
0
TSS
0
0
0
0
0
0
0
0
0
Total
2,290,145
191,631
42,711
143,256
15,383
324,520
1,712
257
3,009,615
a. Excludes discharges from facilities that are projected to close in the baseline. Discharges discussed in this table are total discharges from the facility, and do not account for POTW pollutant removals.
Source: U.S. EPA analysis.
D-7
-------
MP&M EEBA: Appendices
Appendix D: Baseline and Post-Compliance Pollutant Loads
Table D.7: Baseline Pollutant Discharges by Type of Pollutant
for Facilities Regulated under the Proposed Rule
Indirect Dischargers" (Pounds)
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Priority Pollutants
Metals
27,760,005
5,543,839
177,159
2,236,621
472,602
137,453
1,124
256
36,329,059
Organics
1,383,262
147,997
21,800
81,786
19,394
167,038
1,513
124
1,822,914
Cyanide
493,134
6,851,923
0
782,352
1,127
326
0
0
8,128,862
Nonconventional Pollutants
Metals
95,980,460
14,358,652
388,738
6,887,964
2,081,063
2,127,850
10,599
25,432
121,860,758
Organics
39,487,326
492,517
174,836
217,284
79,957
5,173,619
2,872
199
45,628,610
Conventional Pollutants
COD
1,776,191,763
60,965,863
164,682,687
34,193,167
4,871,904
239,789,613
670,587
72,786
2,281,438,370
Oil & Gas
81,421,271
11,454,626
729,817
15,517,754
114,938
11,582,618
27,504
364
120,848,892
TSS
199,145,183
8,757,513
725,193
3,965,947
867,392
11,306,816
43,632
4,992
224,816,668
a. Excludes discharges from facilities that are projected to close in the baseline. Discharges discussed in this table are total discharges from the facility, and do not account for POTW
pollutant removals.
Source: U.S. EPA analysis.
D-l
-------
MP&M EEBA: Appendices
Appendix D: Baseline and Post-Compliance Pollutant Loads
Table D.8: Post -Compliance Pollutant Discharges by Type of Pollutant: Proposed Rule
Indirect Dischargers" (Pounds)
Subcategory
General Metals
Metal Finishing Job Shop
Non-Chromium Anodizing
Printed Wiring Board
Steel Forming & Finishing
Oily Waste
Railroad Line Maintenance
Shipbuilding Dry Dock
All Categories
Priority Pollutants
Metals
1,543,930
59,746
177,159
40,640
6,017
148,211
1,124
256
1,977,083
Organics
591,995
78,435
21,800
65,697
9,119
189,378
1,513
124
958,061
Cyanide
25,053
4,578
0
3,704
474
327
0
0
34,136
Nonconventional
Pollutants
Metals
16,822,356
1,423,781
388,738
971,318
158,675
2,160,760
10,599
25,432
21,961,659
Organics
3,429,204
177,876
174,836
179,122
46,752
5,235,563
2,872
199
9,246,424
Conventional Pollutants
COD
163,208,391
6,702,696
164,682,687
4,682,307
733,041
250,342,263
670,587
72,786
591,094,758
Oil & Gas
8,068,222
415,781
729,817
290,422
40,820
10,993,924
27,504
364
20,566,854
TSS
13,314,727
366,327
725,193
255,937
42,272
12,115,630
43,632
4,992
26,868,710
a. Excludes discharges from facilities that are projected to close in the baseline.
removals.
Source: U.S. EPA analysis.
Discharges discussed in this table are total discharges from the facility, and do not account for POTW pollutant
D-9
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Appendix E: Environmental
Assessment
INTRODUCTION
This Environmental Assessment for the proposed rule
estimates the environmental impact of MP&M discharges on
waterbodies and POTWs under both current conditions and
those corresponding to three regulatory options: the
proposed option, Option 2/6/10, and Option 4/8. EPA
estimates four types of environmental impacts:
* the occurrence of pollutant concentrations in excess
of EPA ambient water quality criteria
(AWQC) for protection of human health in
waterways (e.g., streams, lakes, bays, and estuaries)
receiving discharges from MP&M facilities;
> the occurrence of pollutant concentrations in excess
of AWQC for protection of aquatic species in
waterways receiving discharges from MP&M
facilities;
> the occurrence of POTW inhibition problems
resulting from MP&M facilities' discharges; and
> barriers to POTWs' use of preferred sewage sludge
management or disposal methods (i.e., beneficial
land application or surface disposal), due to metals
discharges from MP&M facilities.
EPA also estimated changes in human health risk from
reduced exposure to MP&M pollutants via consumption of
contaminated fish and drinking water. Chapters 13 and 14
of this EIA present both the methodology used to estimate
human health impacts from exposure to MP&M pollutants
and the results of this analysis.
EPA assessed potential environmental impacts of MP&M
discharges on the receiving waterbodies and POTWs by
using pollutant fate and toxicity data in conjunction with
various modeling techniques. EPA quantified the releases
of 132 pollutants of concern under both baseline conditions
APPENDIX CONTENTS:
E.I. MP&M Pollutant Characteristics
E.I.I Identifying MP&M Pollutants
E. 1.2 Physical-Chemical Characteristics and
Toxicity Data of MP&M Pollutants
E. 1.3 Grouping MP&M Pollutants Based on Risk to
Aquatic Receptors
E. 1.4 Assumptions and Limitations
E.2. Methodology
E.2.1 Sample Set Data Analysis and National
Extrapolation
E.2.2 Water Quality Modeling
E.2.3 Impact of Indirect Discharging Facilities
on POTW Operations
E.2.4 Assumptions and Limitations
E.3 Data Sources
E.3.1 Facility-Specific Data
E.3.2 Waterbody-Specific Data
E.3.3 Information Used to Evaluate POTW
Operations
E.4 Results
E.4.1 Human Health Impacts
Aquatic Life Effects
POTW Effects
E.4.2
E.4.3
Glossary .
Acronyms
References
. E-4
. E-4
. E-9
E-21
E-22
E-22
E-22
E-22
E-24
E-25
E-26
E-26
E-26
E-27
E-31
E-31
E-33
E-34
E-37
E-40
E-41
and the proposed rule. EPA then evaluated potential
site-specific aquatic life and human health impacts resulting
from the baseline and post-regulation pollutant releases.
EPA compared projected water concentrations for each
pollutant to either (a) EPA water quality criteria, or (b) toxic
effect levels (i.e., lowest reported or estimated toxic
concentration that cause a problem) in the absence of water
quality criteria for a pollutant. Figure E-l depicts steps used
in the environmental assessment. The following sections
detail these analytic steps.
E-l
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Figure E.la: MP&M Environmental Impact Assessment
Exclude Facility
Loads from Model
C ombine all
MP&M Indirect
Loads for POCs
Identify POTWs
with Potential for
Inhibition Problems
Calculate POC
Concentration in Effluent &
Compare to Inhibition
C riteria
Identify Sludge
Disposal Practices
Available to POT W
at B aseline and
Options
Calculate POC
Concentration in Sludge &
Compare to Contamination
C riteria
Adjust MP&M POC Loadings
for POTW Removal
MP&M Pollutants of Concei
(POCs)
Gather Acute & Chronic
Water Quality Criteria
Acquire Slope Factors for
Carcinogens &Reference
Doses for Systemic Toxicants
Acquire Human Health
C riteria for D rinking W ater
and Consumption of
Organism s
Obtain POTW Inhibition
Criteria & Sludge
Concentration Limits
Calculate Toxic Weighting
Factors (TWFs) & Pollutant
Weighting Factors
Add Direct MP&M and
POTW Loadings to
the Sam e Reach
Perform In-Stream
Environm ental
Assessment
[See Figure E-lb]
Source: U.S. EPA analysis.
E-2
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Figure E.lb: MP&M Environmental Impact Assessment (Continued)
C
Direct and POTW
Adjusted MP&M
Facility Loadings
Calculate POC Concentration
at Harmonic Mean & Compare to
Chronic Criteria for
Human Health & Aquatic Life
Calculate POC Concentration
at 7Q10 Flow & Compare to
Acute Criteria for
Human Health & Aquatic Life
Calculate POC
Cone entration in
Fish Tissue Using
Bioconcentration
Factor (BCF)
Calculate POC
Cone entration in
Drinking W ater
C
Pollutant Specific
Inform ation
Identify Stream s
With Exceedance
Problem s
Calculate Risk
(DW Concentration x
Consumption Rate x
Cancer Potency Slope
Factor)
Calculate Systemic Risk
(DW Concentration x
Consumption Rate x
Non-cancer Reference
Dose {RfD})
Calculate # Recreational
& Subsistence Anglers
Using Impacted Streams
& # F ishing Days
C omp are w ith
Fish Advisories
(Tissue Concentration x
Cancer Potency Slope
Calculate System ic
Health Risk (Tissue
Cone entration x
Consumption Rate x
Dose {RfD})
^
Estimate # Cancer Cases
Population)
Estimate Population at
Health Hazards
Estimate # Cancer Cases
(Risk x Exposed
Population)
Estimate Population at
Risk from Systemic
Health Hazards
Source: U.S. EPA analysis.
E-3
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
The remainder of this Appendix is organized as follows.
Section E. 1 provides information on the pollutants found in
MP&M discharges. Section E.2 describes the methodology
used to estimate environmental impacts, including
extrapolation of sample sets to the national level and
estimates of water quality impacts. Section E.3 describes
data sources for both MP&M facilities and POTWs.
Section E.4 presents the environmental assessment results.
E.I. MP&M POLLUTANT
CHARACTERIZATION
The extent of human and ecological exposure and risk from
environmental releases of toxic chemicals depends on
chemical-specific properties, the mechanism and media of
release, and site-specific environmental conditions.
Chemical-specific properties include toxic effects on living
organisms, and the fate of chemicals in the environment.
EPA estimated the fate of MP&M pollutants based on their
propensity to volatilize, adsorb onto sediments,
bioconcentrate, and biodegrade.
EPA characterized the fate and toxicity of MP&M pollutants
in three steps:
> identifying pollutants of concern in MP&M
discharges,
> compiling physical-chemical and toxicity data for
those pollutants, and
> grouping pollutants based on their characteristics.
The pollutant-specific fate and toxicity data were used in
various portions of the quantitative benefits assessment. In
addition, EPA summarized the distribution of MP&M
pollutants based on their fate and toxicity properties using
the groupings developed in the third step. This summary is
presented in Chapter 12.
E.I.I Identifying MP&M Pollutants
EPA sampled MP&M facilities nationwide to assess the
concentrations of pollutants in MP&M effluents. The
Agency collected samples of raw wastewater from MP&M
facilities and applied standard water analysis protocols to
identify and quantify the pollutant levels in each sample.
EPA used these analytical data, along with selection criteria,
to identify 132 contaminants of potential concern. MP&M
pollutants of concern (POCs) include 43 priority pollutants
(PP), 3 conventional pollutants, and 86 non-conventional
pollutants.
EPA then evaluated the potential environmental fate of these
pollutants and their toxicity to humans and aquatic receptors.
EPA was able to assess the potential fate and toxicity of 119
of these pollutants, including 43 priority pollutants (33
priority organics, nine priority metals and one inorganic) and
75 non-conventional pollutants (50 non-conventional
organics, 18 non-conventional metals, and seven non-
conventional inorganics). Table E.I presents the potential
fate and toxicity, based on known characteristics of each
chemical, of 132 pollutants of concern. Potential fate and
toxicity data are not available for three conventional and
eight bulk non-conventional pollutants (also listed in Table
E.I) associated with adverse water quality impacts, as
described in Section 12.1.3 of this report.
E-4
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.I: Potential Fate and Toxicity of Pollutants of Concern
Type3 ! Pollutant
Q ;Acenarjhthene.
O -Acetone
O Acetophenone
Q ;Acrolein
Q i Aniline.
O Anthracene
O jBenzoic acid
Q {B.enzyl.alcohol.
Q ;Bij>henyl
O JBisฃ-erhylhexyl).p.hthalate
O Bromo-2-chlorobenzene.j 1-
Q ;Bromo.-3.-cUp.robenzene,. 1 ;
Q ;Butjl.b.enzyl.rjhthalate
O Carbon disulfide
Q iChlorobenzene.
Q ichloroethane
Q ;Cre.s.gL.p.-.
O jcresol^p-
O Cyanide
Q ;Cymene,.r>
O iDecane^n-
O Dibenzothio_rjhene
O JDichloroethene.U-
Q j.P.i*loromethane
O Dimethyl phthalate
O IDimethylformamide^N-
Q LDrmethjljjhenoL.2,4.-
Q ;Di-n-butylฃhthalate
O : Dinitrophenol^ 2,4-
Q iDimtrptpluene^.e-
Q ;P.i-n-octj;l .phthalate
Q iP.ioxane.JJ.-
O -.Diphenylanine
O Diphenyl ether
O ;Dode.cane,.n;
O Eicosane, n-
Q iE%lbenzene
P. {Huoranthene.
Q ;Fluorene
O -.Hexacosane, n-
O Hexadecane^n-
Q ;Hexanoi.c.a.cid
P. j.Hexanone,.2.-
O Isobutyl alcohol
,....P. .isophorpne.....
CAS
.....83329....
67641
98862
....107.Q28...
.....62.5.33....
120127
65850
....1.005.16...
.....9.2.524....
117817
694804
....!.08372...
.....856.87....
75150
....1.08907...
.....750.03....
.....9.5.487....
106445
57125
.....9.9.8.76....
....1.24185...
132650
75354
.....75092....
....I.3.U.I.3....
.....68.122....
1576676
....1.0.5.679...
....84742....
51285
....60620.2....
....11.78.40...
....1239.1.1...
....1.22394...
101848
629970
....1.12403...
112958
....1.0.Q414...
....2.06440...
....86737....
630013
544763
....1.4.2621...
....59178.6...
78831
.....7859!....
Toxicity to
Aquatic Life
(Freshwater)
Acute
...Mp.4e.E9te...
Low
Low
High....
...Moderate..
High
Low
.....Low.....
...Mp.4e.E9te...
Unknown
Low
Low.....
...Mp.4e.E9te...
Low
Low.....
.....Low.....
Low.....
Low
High
Low.....
Low.....
Moderate
Low
.....Low.....
Low.....
Low.....
Low.....
...Mp.4e.E9ie...
Low
Low.....
...Mp.4e.E9ie...
Low.....
Low.....
Moderate
Low.....
Low
Low.....
High....
...Mp.4e.E9ie...
Low
Low
Low.....
.....Low.....
Low
Low....,
Chronic
Low.....
Low
Low
High....
High....
High....
Low
Low.....
Low.....
Unknown
Low
Low.....
Low.....
High
Low.....
Low.....
Low.....
Low
High
Low.....
Low.....
Low
Low
Low.....
Low.....
Low.....
Low.....
Low.....
Low
...Moderate..
...Mp.4e.E9ie...
Low.....
Low.....
Low
Low....
Low
Low.....
High....
High....
Low
Low
Low.....
Low.....
Low
Low.....
Toxicity to
Aquatic Life
(Saltwater)
Acute
...Mp.4e.E9ie...
Low
Unknown
High....
.....Low.....
High
Unknown
.....Low.....
Low.....
Unknown
Unknown
...Unknown..
...Mp.4e.E9ie...
Unknown
Low.....
...Unknown..
Low.....
Unknown
High
Low.....
Low.....
Unknown
Low
.....Low.....
Low.....
...Unknown..
...Unknown..
...Mp.4e.E9ie...
Low
...Unknown..
...Unknown..
...Unknown..
...Unknown..
Low
Low.....
Low
...Moderate..
High....
...Mp.4e.E9ie...
Low
Low
...Unknown..
...Unknown..
Low
Low....,
Chronic
Low.....
Low
Unknown
High....
Low.....
Moderate
Unknown
Low.....
Low.....
Unknown
Unknown
...Unknown..
Low.....
High
Low.....
...Unknown..
Low.....
Unknown
High
Low.....
Low.....
Unknown
Low
Low.....
Low.....
...Unknown..
...Unknown..
High....
Low
...Unknown..
...Unknown..
...Unknown..
...Unknown..
Unknown
Low.....
Low
...Moderate..
...Moderate..
...Mp.4e.E9ie...
Low
Low
...Unknown..
...Unknown..
Low
Low.....
Volatility
Moderate....
Moderate
Low
Moderate....
Low.
Moderate
Low
Low.
Moderate....
Nonvolatile
Moderate
Moderate....
Low.
High
High
Kgh
Low.
Low
Unknown
.High
.....Unknown....
Moderate
High
Kgh
....N.onvolatile...
....Nonvolatile...
Low.
Low.
Low
Low.
Low.
Low.
Low.
Moderate
.....Unknown....
Unknown
Kgh
Moderate....
Moderate....
Unknown
Unknown
Moderate....
Moderate....
Moderate
Low.
Adsorption
Moderate
Low
Low
. . . MP.iBds.orp.tiye. . .
Low
Kgh
Low
...Np.nadsprp.tiye...
Moderate
Kgh
Moderate
Moderate
Kgh
Low
Low
Low
Low.
Low
Low
Moderate
Kgh
Kgh
Low
Low
Low.
Nonadsorptive
Kgh
Low.
Moderate
Moderate
Low
Moderate
Low.
Moderate
Moderate
Kgh
Kgh
Kgh
Low
Kgh
Moderate
Unknown
Kgh
Low.
Low
Low
.....Low....
BCF"
....Mp.4e.E9te....
Insignificant
Low
....Mp.4e.E9te....
Low.
Moderate
Low
..Jn.signific.ant..
....MP.4e.E9te....
Moderate
Moderate
....Mp.4e.E9te....
....Mp.4e.E9te....
Low
Low.
Low.
Low.
Low
Insignificant
High
High
High
Low
..Jn.signific.ant..
Low.
Insignificant
High
....Mp.4e.E9te....
....Mp.4e.E9te....
Insignificant
Low.
High
..Mignificant..
....Moderate...
Moderate
High
High
High
Low.
High
Low.
Unknown
High
Low.
Low.
Insignificant
...Insignificant..
Biodegc
Low.
Moderate
Moderate
Low.
Moderate....
Resistant
Moderate
Moderate....
Moderate....
Moderate
Low
Low.
Moderate....
Unknown
Low.
Low.....
Moderate....
High
Moderate
Low.
Moderate....
Unknown
Resistant
Low.
Moderate....
Moderate
Moderate....
Moderate....
Resistant
Resistant.....
Low.
Resistant....
Moderate....
Moderate
Moderate....
Moderate
Moderate....
Resistant....
Low.
Moderate
Moderate
Moderate....
Moderate....
Moderate
Low.....
RfDd
/
/
/
/
/
/
/
/
/
/
/
/
/.
/
/
/
/
/
/
/
/
/
/
/
<
/
/
/
/
/.....
SFe
/
/
:::::::::::::::::
/
/
/
/....
DWC f g
M
M
M
M
M
M
HAP11
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/.....
pp.
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/.....
E-5
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.I: Potential Fate and Toxicity of Pollutants of Concern
Type3 ! Pollutant
O : Methyl ethyl ketone
O Methyl isobutyl ketone
O Methyl methacrylate
O iM.eth^lfluprene,.!.-.
O Methylnaphthalene^ 2-
Q iMe.^lphenanflirene,.!-.
Q {Naphthalene
Q iNitrpEhenqU.
O JNitrophenoL. 4-
O Nitrosodimethylaminej N-
Q iNitrpsodiphenylamine.N;
O ;Nitrpsorji.rjeridine,.N.-.
O Octacosane1 n-
O jOctadecane, n-
Q LParachlorpmetacresol
Q ;Phe.nanrhr.ene
O {.Phenol
O Pyrene
Q ;Pyridine
Q istyrene
O Terpineo^ alpha-
Q iT.etachlorgelhene
O iTeteacosane^n;
Q iTeteadecane^n-
O {.Toluene
O Triacontanej n-
Q ;Trichlproefliene
P. jTricmprottaqrome|hane
O Trichloromethane
O Tripropyleneglycolmethylether
P. {.Xylene,!!!-.
P. ;Xylene,m-.&.r>.*.
O [Xylene, o-
O Xylene^ o- & p-*
P. ;Ziram.\Cymate
.....M {.Aluminum
M Antimony
M -.Barium
.....M ;Be.KlKum
.....M iPadmium
M -.Calcium
M Chromium
.....M ;Ctoom.um.hexaval.ent
.....M Lcobalt
M Copper
.....M LSol.d....
CAS
2027170
78933
108101
.....8.06.26....
....173.0376...
91576
....832699...
.....9.1203....
.....88755....
100027
62759
.....8.6306....
.....10075.4...
630024
593453
.....595.07....
....8501.8....
108952
129000
.....11.Q861...
.....1.00425...
98555
.....1.271.84...
....6.4631.1...
....62959.4...
108883
638686
.....7.9.0.1.6....
.....75.6.94....
67663
20324338
.....108.383...
...1.796.0.123.1.
95476
136777612
....1.37304...
...7429905...
7440360
7440393
...7440417...
...7440439...
7440702
7440473
...1.8.5.402.99..
...7440484...
7440508
...744.0575..
Toxicity to
Aquatic Life
(Freshwater)
Acute
Low
Low
Low.....
...Moderate..
Low
...Moderate..
.....Low.....
Low.....
Low
Low
Low.....
Low.....
Low
Low
.....Low.....
...Mp.4e.rate..
Low
Moderate
Low.....
.....Low.....
Low
Low.....
Low.....
Low.....
Low
Low
Low.....
.....Low.....
Low
Low
.....Low.....
Low.....
Low
Low
High....
...Moderate..
Low
Low
...Mp.4e.rate..
High....
Unknown
Moderate
High....
.....Low.....
High
...Unknown..
Chronic
Low
Low
Low.....
Low.....
Low
...Moderate..
Low.....
Low.....
Low
Low
Low.....
Low.....
Low
Low
Low.....
...Mp.4e.rate..
Low
Moderate
Low.....
Low.....
Low
Low.....
Low.....
Low.....
Low
Low
Low.....
Low.....
Low
Low
Low.....
Low.....
Low
Low
High....
...Moderate..
Low
Low
High....
High....
Low
Moderate
...Mp.4e.rate..
...Moderate..
High....
...Unknown..
Toxicity to
Aquatic Life
(Saltwater)
Acute
Low
Low
...Unknown..
...Unknown..
Moderate
...Unknown..
.....Low.....
Low.....
Low
Low
Low.....
...Unknown..
Low
Low
...Unknown..
...Mp.4e.rate..
Low
Unknown
...Unknown..
.....Low.....
Unknown
Low.....
Low.....
Low.....
Low
Low
Low.....
...Unknown..
Low
Unknown
.....Low.....
Low.....
Low
Low
Low.....
...Unknown..
Low
Unknown
...Unknown..
High....
Unknown
Low
Low.....
...Unknown..
High
...Unknown..
Chronic
Low
Low
...Unknown..
...Unknown..
Moderate
...Unknown..
Low.....
Low.....
Low
Low
Low.....
...Unknown..
Low
Low
...Unknown..
...Mp.4e.rate..
Low
Unknown
...Unknown..
Low.....
Unknown
Low.....
Low.....
Low.....
Low
Low
Low.....
...Unknown..
Low
Unknown
Low.....
Low.....
Low
Low
Low.....
...Unknown..
Low
Unknown
...Unknown..
High....
Unknown
Moderate
...Mp.4e.rate..
...Moderate..
High....
...Unknown..
Volatility
Moderate
Moderate
Moderate....
Moderate....
Moderate
Low.
Moderate....
Low.
Nonvolatile
Nonvolatile
Low.
....N.onvqi.atile...
Unknown
Unknown
Low.
Moderate....
Low
Moderate
Low.
Kgh
Moderate
Kgh
.....Unknown....
.....Unknown....
High
Unknown
Kgh
Kgh
Kgh
Nonvolatile
Kgh
Kgh
Kgh
Kgh
....Uonvolatile...
....Nonvolatile...
Nonvolatile
Nonvolatile
....Uonvolatile...
....N.onyolatile...
Nonvolatile
Nonvolatile
....Uonvolatile...
....Nonvolatile...
Nonvolatile
....Nonvolatile...
Adsorption
Kgh
Nonadsorptive
Low
Low.
Kgh
Moderate
Kgh
Low
Low.
Low
Low
Moderate
. . . M pnads.orp.tiye. . .
Unknown
Kgh
Low
Kgh
Low
Kgh
. . . M pnads.orp.tiye. . .
Low
Low
Low
Kgh
Kgh
Low
Unknown
Low.
Low
Low
Low
Low
Low.
Low
Low
. . . M pnads.orp.tiye. . .
Kgh
Kgh
Kgh
Kgh
Kgh
Kgh
Kgh
Kgh
Kgh
Kgh
.....Kgh....
BCF"
High
Insignificant
Insignificant
Low.
High
High
High
Low.
Low.
Moderate
Insignificant
....Mp.4e.rate...
... Insignificant..
Unknown
High
....Mp.4e.rate...
....Mp.4e.rate...
Insignificant
High
... Insignificant..
Low.
Low
Low.
High
High
Low
Unknown
Low.
Low.
Insignificant
Insignificant
....Mp.4e.rate...
....Mp.4e.rate...
Moderate
Moderate
... Insgni.fic.ant..
....Mp.4e.rate...
Insignificant
Unknown
Low.
....Mp.4e.rate...
Unknown
Low
Low.
....Unknown...
Moderate
....Unknown...
Biodegc
Moderate
Moderate
Low.
.....Unknown....
Moderate
.....Unknown....
Moderate....
Low.
Moderate
Resistant
Low.
Resistant.....
Moderate
Moderate
Low.
Resistant....
High
Resistant
Moderate....
Low.....
Moderate
Resistant.....
Moderate....
Moderate....
Moderate
Moderate
Resistant....
Resistant.....
Resistant
Moderate
Low.
Low.
Low
Low
Resistant.....
Resistant.....
Resistant
Resistant
Resistant.....
Resis.tent.....
Resistant
Resistant
Resis.tent.....
Resistant.....
Resistant
....Resistant....
RfDd
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/.
/
SFe
/
/
/
/
/
DWC f g
M
M
M
M
THM
M
M
M
M
SM
M
M
M
M
M
M
TT
HAP11
/
/
/
/
/
/
/
<
/
/
/
/
/
/
/
pp.
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
E-6
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.I: Potential Fate and Toxicity of Pollutants of Concern
Type3 ! Pollutant
.....M [Lead.
M Magnesium
.....M iManganese.
.....M J.MBEHK
M Molybdenum
.....M [Nickel
.....M : selenium.
.....M [Silver
M -.Sodium
M Thallium
.....M JJjn.
.....M jTitonium
M Vanadium
.....M [Yttrium
.....M lane
.....QI ;Ammgnia.as.N.
OI -.Arsenic
OI Boron
.....QI [Chloride
.....QI [Fluoride
OI : Phosphate
01 [Sulfate
.....O.I [Sutfide.
.....QI LP.hosphorus.(.asP04J
CP -.BOD 5-day (carbonaceous)
CP : Oil and Grease
.... CP .... [Qil.and Grease. (as.H.enjl
.... .QF. .... ilfM .Suspended Solids. H SSI
BNCP : Amenable Cyanide
. . BNCP. . . [Chemical Oxygen Demand.CCOD} ....
. . BNCP. . . [Total. Dis.solved Solids. ff.DS)
..BNGE...Ll(M.Kid.
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.I: Potential Fate and Toxicity of Pollutants of Concern
Typel
...BNCP...
BNCP
RWPP
Pollutant
Total Petroleum Hydrocarbons
fe.งg.t.-te.rn).
Total Recoverable Phenolics
WpaK^H n;ซซnhlp r\raHp
CAS
.....C.-.037....
C-020
r.nd9
Toxicity to
Aquatic Life
(Freshwater)
Acute
Chronic
Toxicity to
Aquatic Life
(Saltwater)
Acute
Chronic
Volatility
Adsorption
BCF"
Biodegc
RfDd
SFe
DWC f/g
HAP11
pp.
Table Notes:
Unless indicated otherwise, all metals are assumed to be nonvolatile, to have high adsorption, and to be
resistant to biodegradation.
a. Type
O = Organic
M = Metal
OI = Other Inorganic
CP = Conventional Pollutant
BNCP = Bulk Non-Conventional Pollutant
b. BCF = Bioconcentration Factor
c. Biodeg = Biodegradation Potential
d. RfD = Reference Dose
e. SF = Slope Factor
f. DWC = Drinking Water Criteria
g. Drinking Water Criteria Codes
M = Maximum Contaminant Level established for health-based effect
SM = Secondary Maximum Contaminant Level (SMCL) established for taste or aesthetic
effect
THM = MCL established for trihalomethanes
TT = Treatment technology action level established
h. HAP = Hazardous Air Pollutant
i. PP = Priority Pollutant
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
E.I.2 Physical-Chemical Characteristics
and Toxicity Data of MP&M Pollutants
Pollutants present in MP&M effluents can have significant
effects on human health and aquatic receptors. EPA used
various data sources to evaluate both pollutant-specific fate
and toxicity and potential human health effects, including:
- reference doses (RfDs),
- cancer potency slope factors (SFs).
- human health-based water quality criteria
(WQC).
- maximum contaminant levels (MCLs) for
drinking water protection and other drinking water
related criteria, and
- hazardous air pollutant (HAP) and priority
pollutant (PP) lists.
To evaluate potential fate and effects in aquatic
environments, the Agency relied on:
> measures of acute and chronic toxicity to aquatic
species,
* bioconcentration factors for aquatic species,
- Henry's Law(Hl constants (to estimate volatility),
> adsorption coefficients (to estimate association with
bottom sediments), and
> biodegradation half-lives (to estimate the removal
of chemicals via microbial metabolism).
The data sources used in the assessment include:
* EPA ambient WQC documents and updates;
- EPA's Assessment Tools for the Evaluation
of Risk (ASTER):
- the AQUatic Information REtrieval System
(AQUIRE) and the Environmental Research
Laboratory-Duluth fathead minnow database;
- EPA's Integrated Risk Information System
(IRIS):
- EPA's Health Effects Assessment
Summary Tables (HEAST);
- EPA's 1991 and 1993 Superfund Chemical
Data Matrix (SCDM):
* Syracuse Research Corporation's CHEMFATE and
BIODEG databases; and
* EPA and other government reports, scientific
literature, and other primary and secondary data
sources.
EPA also obtained information on chemicals for which the
sources listed above did not provide physical-chemical
properties and/or toxicity data, to ensure that the assessment
be as comprehensive as possible. To the extent possible,
EPA estimated values for the chemicals using the
quantitative structure-activity relationship (QSAR)
model incorporated in ASTER. The Agency also used
published linear regression correlation equations to
determine some physical-chemical properties.
a. Human health effects
EPA used various data sources to determine
pollutant-specific toxicity to human health. EPA obtained
RfDs and SFs from IRIS, HEAST, and EPA's Region II
Risk-Based Concentration (RBC) table. EPA developed
drinking water criteria and human health-based AWQC
values for two exposure routes: (1) ingesting the pollutant
via contaminated aquatic organisms only (carcinogens and
noncarcinogens), and (2) ingesting the pollutant via both
water and contaminated aquatic organisms (noncarcinogens
only). Table E.2 summarizes pollutant toxicity data
pertaining to human health. In addition to fate and toxicity
data, Table E. 1 also includes HAP and PP lists. Short
descriptions and definitions for each of the measures of
human health effects are provided below.
E-9
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.2: Human Health Data for 132 MP&M Pollutants of Concern
CAS Number
51285
57125
59507
62533
62759
65850
67641
67663
68122
75003
75092
75150
75354
75694
78591
78831
78933
79016
80626
83329
84742
85018
85687
86306
86737
88755
91203
91576
92524
95476
95487
98555
98862
99876
100027
100414
100425
100516
100754
101848
105679
106445
107028
108101
108372
108383
108883
108907
Pollutant Name
;Dinitroghenol, 2,4-
! Cyanide
; Parachlorometacresol
I Aniline
;Nitrosodimethylamine, N-
;Benzoic acid
; Acetone
I Trichloromethane
;Dimethylformamide, N,N-
! Chloroethane
; Dichloromethane
I Carbon disulfide
;Dichloroethene, 1,1-
! Trichlorofluoromethane
;Isophorone
;Isobutyl alcohol
I Methyl ethyl ketone
I Trichloroethene
; Methyl methacrylate
;Acenaphthene
! Di-n-buty 1 phthalate
;Phenanthrene
; Butyl benzyl phthalate
;Nitrosodiphenylamine, N-
;Fluorene
;Nitrophenol, 2-
; Naphthalene
;Methylnaphthalene, 2-
;Biphenyl
;Xylene, o-
jCresol, o-
! Terpineol, alpha-
;Acetophenone
;Cymene,p-
;Nitrophenol, 4-
;Ethylbenzene
! Styrene
I Benzyl alcohol
;Nitrosopiperidine, N-
;Diphenyl Ether
;Dimethylphenol, 2,4-
! Cresol, p-
;Acrolein
I Methyl isobutyl ketone
;Bromo-3-chlorobenzene, 1-
;Xylene, m-
; Toluene
I Chlorobenzene
Human Health
Ingesting |
Water and:
Organisms!
(Mfifl)!
70;
700;
56000;
5.8;
0.00069;
130000;
3500;
5.7;
3500;
12;
4.7;
3400;
0.057;
9100;
36;
10000;
21000;
3.1;
48000;
1200;
2700;
I
3000;
5;
1300;
I
680;
75;
720;
42000;
1700;
I
3400;
I
220;
3100;
6700;
10000;
I
540;
170;
410;
2800;
42000;
6800;
680;
AWQC Values !
Ingesting j
Organisms i
Only! Slope Factor
(ug/1); (fmg/kg-dayl-1)
14000;
220000;
270000;
95! 0.0057
8.1; 51
2900000!
2800000;
470! 0.0061
220000000;
520! 0.0029
1600; 0.0075
94000!
3.2; 0.6
66000!
2600; 0.00095
1500000!
6500000;
92; 0.011
2300000;
2700;
12000;
i
5200;
16| 0.0049
14000;
i
21000;
84;
1200;
100000;
30000;
i
98000;
i
1100;
29000!
160000;
810000;
i
2300;
3100;
1000;
360000!
100000;
200000;
21000;
Reference Dose!
(mg/kg-day);
0.002;
0.02;
2!
i
I
4!
o.i;
o.oi!
o.i;
0.4!
0.06;
o.i!
0.009!
0.3!
0.2!
0.3!
0.6!
0.006!
1.4!
0.06!
o.i!
i
0.2!
i
0.04!
i
0.02!
0.02!
0.05!
2!
0.05!
i
o.i!
i
0.008!
o.i!
0.2!
0.3!
!
i
0.02!
0.005!
0.02!
0.08!
!
2!
0.2!
0.02!
Drinking
Water
Criteria
(ng/D
200
100
5
7
5
10000
700
100
10000
1000
100
E-10
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.2: Human Health Data for 132 MP&M Pollutants of Concern
CAS Number! Pollutant Name
108952 ! Phenol
110861 jPyridine
112403 jDodecane, n- (a)
112958 ;Eicosane,n-(a)
117817 ; Bis(2-ethy Ihexyl) phthalate
1 1 7840 ! Di-n-octy 1 phthalate
120127 ; Anthracene
122394 jDiphenylamine
123911 jDioxane, 1,4-
124185 ;Decane,n-
1 27 1 84 Tetrachloroethene
129000 jPyrene
131113 ; Dimethyl phthalate
132650 jDibenzothiophene
1 37304 ; Ziram \ Cymate
142621 jHexanoic acid
206440 jFluoranthene
544763 jHexadecane, n- (a)
591786 jHexanone, 2-
593453 ; Octadecane, n- (a)
606202 jDinitrotoluene, 2,6-
629594 ! Tetradecane, n- (a)
629970 jDocosane, n-
6300 1 3 ! Hexacosane, n- (b)
630024 ; Octacosane, n- (b)
638686 | Triacontane, n- (b)
6463 1 1 Tetracosane, n- (b)
694804 ;Bromo-2-chlorobenzene, 1-
832699 jMethylphenanthrene, 1-
1576676 jDimethylphenanthrene, 3,6-
1730376 jMethylfluorene, 1-
2027170 jlsopropyhiaphthalene, 2-
7429905 jAluminum
7439896 jlron
7439921 jLead
7439954 jMagnesium
7439965 jManganese
7439976 jMercury
7439987 jMolybdenum
7440020 jNickel
7440224 ! Silver
7440235 ! Sodium
7440280 ! Thallium
7440315 jTin
7440326 ; Titanium
7440360 jAntimony
7440382 jArsenic
7440393 jBarium
Human Health AWQC Values
Ingesting
Water and
Organisms
(ng/D
21000
35
1.8
37
4100
470
3.2
320
230
310000
700
300
1400
34
20000
300
50
0.05
610
170
1.8
14
0.02
1000
Ingesting
Organisms
Only
(ug/1)
4600000
5400
5.9
39
6800
1000
2400
3500
290
2900000
220000000
370
65000
900
47000
100
0.051
4600
110000
6.5
4300
0.16
Slope Factor
(fmg/kg-dayl-1)
0.014
0.011
0.052
1.5
Reference Dose
(mg/kg-day)
0.6
0.001
0.02
0.02
0.3
0.025
0.01
0.03
0.02
0.04
0.04
0.001
1
0.3
0.14
0.005
0.02
0.005
0.00007
0.6
4
0.0004
0.0003
0.07
Drinking
Water
Criteria
(ng/D
6
5
50
300
15
50
2
100
100
2
6
50
2000
E-ll
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.2: Human Health Data for 132 MP&M Pollutants of Concern
CAS Number! Pollutant Name
7440417 ! Beryllium
7440428 ! Boron
7440439 ; Cadmium
7440473 ! Chromium
7440484 ! Cobalt
7440508 'Copper
7440575 'Gold
7440622 ! Vanadium
7440655 ! Yttrium
7440666 jZinc
7440702 ! Calcium
76644 1 7 | Ammonia as N
7782492 ; Selenium
14265442 'Phosphate
14808798 jSulfate
16887006 ! Chloride
16984488 ; Fluoride
18496258 jSulfide
1 8540299 ; Chromium hexavalent
i Tripropyleneglycolmethyl
20324338 I ether
136777612 jXylene, o- &p- (c)
179601231 ;Xylene,m-&p-(c)
C003 JBOD 5-day (carbonaceous)
i Chemical Oxygen Demand
C004 I (COD)
C009 ; Total Suspended Solids (TSS)
CO 1 0 ! Total Dissolved Solids (IDS)
CO 1 2 ; Total Organic Carbon (TOC_)
C020 ! Total Recoverable Phenolics
C02 1 ; Total Kjeldahl Nitrogen
C025 jAmenable Cyanide
C036 ; Oil And Grease (as Hem)
i Total Petroleum
C037 1 Hydrocarbons (as Sgt-hem)
i Weak-acid Dissociable
C042 ; Cyanide
'Phosphorus (as PO4)
Oil and Grease
Human Health AWQC Values
Ingesting
Water and
Organisms
(wsfl)
66
14
50000
650
9100
170
100
42000
42000
Ingesting
Organisms
Only
(MS/1)
1100
84
1000000
1200
69000
11000
2000
100000
100000
Slope Factor
(fmg/kg-dayl-1)
Reference Dose
(mg/kg-day)
0.002
0.09
0.0005
1.5
0.06
0.04
0.007
0.3
0.005
0.06
0.003
2
2
Drinking
Water
Criteria
(ng/D
4
5
100
1300
5000
50
250000
250000
4000
100
10000
10000
Sources: U.S. EPA (1980), U.S. EPA (1984), U.S. EPA (1997), U.S. EPA (1998), U.S. EPA (1998/99), Worthing (1987).
E-12
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
ซ> Systemic toxicants
Systemic toxicants are chemicals that EPA believes can
cause significant non-carcinogenic health effects when
present in the human body above chemical-specific toxicity
thresholds. These effects may result from acute or chronic
chemical exposures, and include:
systemic health effects (i.e., loss of one or more
neurological, respiratory, reproductive, immunological, or
circulatory functions);
organ-specific toxicity (e.g., liver and kidney effects);
developmental toxicity (e.g., reduced weight in newborns or
loss of IQ); and
lethality.
EPA typically relies on animal toxicity data to develop RfDs
for systemic toxicants that can enter the human body via
ingestion. These values represent chemical concentrations
expressed in mg of pollutant/kg body weight/day. Certain
exposed populations are considered to be protected if these
chemical concentrations are not exceeded. These
populations include sensitive groups, such as young children
or pregnant women. EPA included all available RfD data
for the MP&M pollutants of concern (POCs) in the
analysis.
ซ> Carcinogens
Carcinogens are chemicals that EPA believes can cause or
have the potential to cause cellular damage, which can lead
to tumors or cancers in humans, either directly or indirectly.
Unlike systemic toxicants, most carcinogens are not believed
to have a toxicity threshold. Any amount of a carcinogen
therefore has the potential to result in a cancer event, even
though such a probability can be very small at low
concentrations. The Agency has developed SFs, using
animal or epidemiological data, that express the probability
that a chemical will induce tumor or cancer development.
EPA included all available SF data for the MP&M POCs in
the analysis.
ซ> Drinking water criteria
EPA developed human health-based drinking water criteria
to assess the health hazards associated with the presence of
certain toxic chemicals in drinking water. The criteria are
usually presented as MCLs. MCLs for non-carcinogens
represent chemical-specific concentrations (expressed in
ug/1) that are not expected to result in adverse health effects
in exposed populations if not exceeded in drinking water.
MCLs for carcinogens represent chemical-specific
concentrations (expressed in ug/1) that are expected to result
in less than one additional cancer case per million lifetime
exposures if not exceeded in drinking water. The Agency
also investigated additional drinking water criteria,
including:
- Secondary Maximum Contaminant Levels
(SMCLs) established for taste or aesthetic effects,
> MCLs established specifically for trihalomethanes,
and
* action levels developed on the basis of treatment
technology.
EPA included all the available primary and secondary
drinking water criteria for the MP&M POCs in the analysis.
ซ> Pollutant uptake via water and/or organisms
EPA has developed WQC for numerous priority toxic
pollutants to protect the health of humans who consume
water and organisms or only organisms obtained from
aquatic habitats contaminated by those PPs. The criteria,
expressed in ug/1, represent concentrations in surface waters
that will cause adverse health effects in humans when
exceeded. EPA obtained all available human health WQC
for the MP&M POCs and included them in the analysis.
ซ> Priority pollutants (PPs)
Priority pollutants are 126 individual chemicals, defined by
the Agency as toxic, that EPA routinely analyzes when
assessing contaminated surface water, sediment,
groundwater, or soil samples. These chemicals are of
particular concern to the Agency because of their high
toxicity or persistence in the environment. EPA identified
all MP&M PPs and included them in the analysis.
*ป Hazardous air pollutants (HAPs)
HAPs are compounds that EPA believes may represent an
unacceptable risk to human health if present in the air.
HAPs, expressed in ug/m3, can be of particular concern to
POTW workers if released into the air at high enough
concentrations during the wastewater treatment cycle. EPA
identified all HAPs among the MP&M POCs analyzed.
b. Aquatic receptor effects
The potential impact of chemicals on aquatic receptors can
be assessed qualitatively based on five effect and fate
parameters:
* aquatic toxicity (acute and chronic),
> bioconcentration,
* volatilization,
> adsorption, and
* biodegradation.
Site-specific risks require a measure of exposure and cannot
be quantified using this approach. Chemicals can be
classified and ranked in terms of their impacts on aquatic
receptors, however, by using the five parameters discussed
below. Table E.3 summarizes the measured or estimated
E-13
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
values of these parameters for the MP&M POCs. Each
effect and fate parameter is described below.
Biological oxygen demand (BOD), oil and grease
(O&G). pH, and total suspended solids (TSS): These
fate/effect parameters are relevant only for specific
chemicals. These parameters are not available for the
conventional pollutants or bulk non-conventional pollutants,
such as total petroleum hydrocarbons (TPH).
alkalinity, total organic carbon (TOO, or total
Kjeldahl nitrogen (TKN). Most of these pollutants are
responsible for significant environmental impacts, however.
Section 12.2.4 outlines these impacts in greater detail.
ซ> Aquatic toxicity data
The Agency addressed two general classes of aquatic
toxicity:
> Acute toxicity (AT) assesses the impacts of a
pollutant after a relatively short exposure duration,
typically 48 and 96 hours for invertebrates and fish,
respectively. The endpoint of concern is mortality,
reported as the LC50. This value represents the
concentration lethal to 50 percent of the test
organisms for the duration of the exposure.
- Chronic toxicity (CT) assesses the impact of a
pollutant after a longer exposure duration, typically
from one week to several months. The endpoints
of concern are one or more sublethal responses,
such as changes in reproduction or growth in the
affected organisms. The results are reported in
various ways, including EC1 or ECS (i.e., the
concentration at which one percent or five percent
of the test organisms show a significant sublethal
response), NOEC (No Observed Effect
Concentration), LOEC (Lowest Observed
Effect Concentration), or MATC (Maximum
Allowable Toxicant Concentration).
ซ> Bioconcentrotion factor (BCF) data
The bioconcentration factor (BCF. measured in I/kg) is
a good indicator of the potential for a chemical dissolved in
the water column to be taken up by aquatic biota across
external surface membranes, usually fish gills. The BCF is
defined as follows:
BCF =
equilibrium chemical concentration in
target organism (mg/kg, wet weight)
mean chemical concentration in surrounding water (jJg/L)
EPA analyzes POCs with elevated BCF values because
these pollutants can bioconcentrate in aquatic organisms and
transfer up the food chain if they are not metabolized and
excreted. This transfer can result in significant exposures to
predators (including humans) consuming contaminated fish
or shellfish.
ซ> Volatilization data
Volatilization is a process whereby chemicals dissolved in
water escape into the air. Chemicals with higher
volatilization potential are typically of less concern to
aquatic receptors because they tend to be removed quickly
from the water column. These volatile pollutants are a
concern to human health when inhaled. For aquatic
receptors, however, POCs with higher volatilization
potential present lower hazards.
EPA used the air/water partitioning coefficient H to estimate
a chemical's volatilization potential. H represents the ratio
of a chemical's aqueous phase concentration to its
equilibrium partial pressure in the gas phase (at 25 ฐ C); units
are typically expressed as atm.m3/mole. Metals do not
have measurable partial pressures (with some notable
exceptions, including several organic mercury compounds),
and are therefore considered to be non-volatile unless
otherwise indicated.
ซ> Adsorption data
Adsorption is a process whereby chemicals associate
preferentially with the organic carbon (OC) found in
soils and sediments. Highly-adsorptive compounds tend to
accumulate in sludge or sediments. Such chemicals are also
more likely to be taken up by benthic invertebrates and to
affect local food chains. Both accumulation in sediment and
the effect on local food chains make these chemicals more
likely to impact higher predators including humans.
EPA used the adsorption coefficient^^ to assess the
potential of organic MP&M POCs to associate with organic
carbon. Koc represents the ratio of the target chemical
absorbed per unit weight of organic carbon in the soil or
sediment to the concentration of that same chemical in
solution at equilibrium. Metals in the aquatic environment
typically end up in the sediment phase but do not bind to the
organic carbon (except for nickel). The Agency assumed
that all metals show a high affinity for sludge and sediments
independent of their negligible Koc values.
ซ> Biodegradation data
Biodegradation is a process whereby organic molecules
are broken down by microbial metabolism. Biodegradation
represents an important removal process: compounds that
are readily biodegraded generally represent lower intrinsic
hazards because they can be eliminated rapidly. These
compounds are therefore less likely to create long-term
toxicity problems or to accumulate in sludge or sediments
and organisms. Chemicals that biodegrade slowly or not at
all can accumulate and linger for longer periods of time in
sludge or sediments, and represent a higher hazard to aquatic
receptors.
E-14
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MP&M EEBA: Appendices Appendix E: Environmental Assessment
EPA used biodegradation half-life to estimate the number of days a compound takes to be degraded to half of
potential for an organic chemical to biodegrade in the its starting concentration under prescribed laboratory
aquatic environment. Biodegradation half-life represents the conditions. Metals do not biodegrade.
Table E.3 summarizes pollutant toxicity data pertaining to
aquatic life.
E-15
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.3: Aquatic Life Toxicity
Freshwater Aquatic Life j
CAS
Number
51285
57125
59507
62533
62759
65850
67641
67663
68122
75003
75092
75150
75354
75694
78591
78831
78933
79016
80626
83329
84742
85018
85687
86306
86737
88755
91203
91576
92524
1 Pollutant Name
iDinitrophenol, 2,4-
i Cyanide
i Parachlorometacresol
i Aniline
jNitrosodimethylamine, N-
iBenzoic acid
jAcetone
i Trichloromethane
jDimethylformamide, N,N-
iChloroethane
i Dichloromethane
i Carbon disulfide
iDichloroethene, 1,1-
i Trichlorofluoromethane
ilsophorone
ilsobutyl alcohol
i Methyl ethyl ketone
i Trichloroethene
i Methyl methacrylate
jAcenaphthene
jDi-n-butyl phthalate
jPhenanthrene
i Butyl benzyl phthalate
jNitrosodiphenylamine, N-
jFluorene
jNitrophenol, 2-
i Naphthalene
jMethylnaphthalene, 2-
jBiphenyl
Data for 132
MP&M Pollutants of Concern
Bio- i Adsorption j Bio-
! concentration ! Henry's Law ! Coefficient ! degradation
Saltwater Aquatic Life j Factor j Constant j (Koc) j Half-Life
Acute Value! Chronic Value! Acute Value! Chronic Value!
(ug/i)j (jig/oj (ug/i)j (ng/i)i
1160J
22J
4050J
250J
280000J
180000J
6210000J
13300J
7100000J
65614J
330000J
2100J
11600J
17387J
120000J
949000J
3220000J
40700J
191000J
580J
850J
180J
820J
5800J
212J
160000J
1600J
1133J
360J
790!
5.2!
1300!
4J
4000!
17178!
1866000!
6300!
710000!
21069!
82500!
2J
5114!
6412!
11000!
4000!
233550!
14850!
19100!
208!
500!
19!
260!
1000!
8J
3451!
370!
417!
230!
1500J
ii
i
29400J
4300000J
5640000J
19610J
I
256000J
224000J
12900J
600000J
1287000J
14000J
I
970J
450J
no:
510J
3300000J
lOOOJ
32000J
1200J
600J
4600J
940!
1!
i
2940!
430000!
10000!
1961!
i
2560!
2J
22400!
1290!
60000!
128700!
2000!
i
710!
3.4!
11!
400!
33000!
100!
16000!
120!
60!
460!
Value!
(I/kg)!
1.51J
ii
79J
19.9J
0.026J
15|
0.39J
3.75J
0.005J
7.2J
0.91J
11.5J
5.6J
49J
4.38J
2.2J
ii
10.6J
6.6J
242J
89J
486J
414J
136J
30J
13. 5J
10.5J
2566J
436J
Value (atm/!
m3-mole)!
0.000000443!
0.0000025!
0.0000019!
0.000000263!
0.00000154!
0.00004!
0.00367!
0.000000018!
0.00882!
0.00219!
0.0303!
0.0261!
0.097!
0.00000576!
0.0000118!
0.00006!
0.0103!
0.00034!
0.00009!
0.00000181!
0.00002!
0.00000126!
0.000005!
0.00006!
0.00000947!
0.00048!
0.00052!
0.0003!
Value!
23861
45J
604J
54J
12J
182J
18!
40J
6.1!
37.6J
28J
89J
343J
93J
25J
61.7J
5.2J
104J
22J
3890J
6310J
18800J
17000J
1200J
2830J
114J
871j
8500J
1400J
Value
(days)
263
16
100
26
180
16
7
180
16
28
28
180
360
28
7.2
7
360
28
102
23
200
7
34
60
28
20
20
7
E-16
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.3: Aquatic Life Toxicity Data for 132 MP&M Pollutants of Concern
CAS !
Number j Pollutant Name
95476 iXylene, o-
95487 JCresol, o-
98555 iTerpineol, alpha-
98862 JAcetophenone
99876 jCymene, p-
100027 JNitrophenol, 4-
100414 JEthylbenzene
100425 iStyrene
100516 I Benzyl alcohol
100754 JNitrosopiperidine, N-
101848 JDiphenyl Ether
105679 JDimethylphenol, 2,4-
106445 JCresol, p-
107028 JAcrolein
108101 JMethyl isobutyl ketone
108372 :Bromo-3-chlorobenzene, 1-
108383 |Xylene,m-
108883 I Toluene
108907 iChlorobenzene
108952 iPhenol
110861 jPyridine
1 12403 JDodecane, n- (a)
112958 JEicosane, n- (a)
117817 i Bis(2-ethy Ihexyl) phthalate
1 1 7840 i Di-n-octy 1 phthalate
120127 JAnthracene
122394 JDiphenylamine
123911 JDioxane, 1,4-
124185 JDecane,n-a
Freshwater Aquatic Life j Saltwater Aquatic Life
Acute Value! Chronic Value! Acute Value
(ug/l)j Qigfl)! (ug/1)
3820J 1332! 6000
14000J 2251! 10200
12742J 4879!
162000J 31094!
6500J 237! 4400
7680J 1300! 7170
9090J 4600! 430
4020J 402! 9100
lOOOOJ 1000! 15000
1019538J 282592!
780J 213! 2400
2120J 1970!
7500J 2570!
14J 5.8! 55
505000J 50445! 812000
1784J 682!
16000J 3900! 12000
5500J 1000! 6300
2370J 2100! 10500
4200J 200! 5800
93800J 25000!
18000J 1300! 500000
18000J 1300! 500000
! !
690J 69!
2.78J 2.2! 40
3790J 734!
9850000J 1457300!
18000J 1300! 500000
Chronic Value
(Eg/1)
600
1020
440
1900
43
910
1500
5.5
81200
1200
5000
1050
2410
50000
50000
16
50000
Bio- i Adsorption j Bio-
concentration i Henry's Law ! Coefficient ! degradation
Factor Constant (Koc) Half-Life
Value! Value (atm/j Value
(l/kg)| m3-mole)| Value; (days)
208J 0.00519! 129J 28
18J 0.0000012! 103J 7
48J 0.0000544! 589J 15
111 0.00001! 45J 16
770J 0.011! 4000J 100
79J 0.000000000415! 236J 7
37.5J 0.00788! 250J 10
13.5J 0.00283! 920J 28
4J 0.000000743! 6.1J 16
I 0.000000275! 9J 180
470J 0.000448! 4365J 15
94J 0.000002! 18J 7
17.6J 0.000000792! 49J 0.667
215J 0.00012! 5J 28
2.4J 0.00014! 19J 7
190J 0.00078! 1500J 100
208J 0.00719! 190J 28
10.7J 0.00664! 95J 22
10. 3J 0.00377! 275J 150
1.4J 0.000000333! 30.2J 3.5
2J 0.00000888! 5J 7
14500J 95000J 17
lOOOOOJ 30000000J 17
130J 0.0000001! 87420J 23
5460J 0.000000445! 2390J 28
478J 0.00007! 16000J 460
269J 0.000000496! 1910J 20
0.4J 0.0000048! 17J 180
8800J 58200J 17
E-17
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.3: Aquatic Life Toxicity Data for 132 MP&M Pollutants of Concern
CAS !
Number j Pollutant Name
127184 iTetrachloroethene
129000 iPyrene
131113 I Dimethyl phthalate
132650 JDibenzothiophene
1 37304 jZiram \ Cymate
142621 JHexanoic acid
206440 JFluoranthene
544763 jHexadecane, n- (a)
591786 JHexanone, 2-
593453 jOctadecane, n- (a)
606202 JDinitrotoluene, 2,6-
629594 JTetradecane,n-(a)
629970 JDocosane, n- b
630013 JHexacosane, n- (b)
630024 jOctacosane, n- (b)
638686 jTriacontane, n- (b)
6463 1 1 i Tetracosane, n- (b)
694804 JBromo-2-chlorobenzene, 1-
832699 JMethylphenanthrene, 1-
1576676 iDimethylphenanthrene, 3,6-
1730376 JMethylfluorene, 1-
2027170 jlsopropylnaphthalene, 2-
7429905 JAluminum
7439896 jlron
7439921 JLead
7439954 jMagnesium
7439965 JManganese
7439976 JMercury
7439987 JMolybdenum
Freshwater Aquatic Life | Saltwater Aquatic Life
Acute Value! Chronic Value! Acute Value
(ug/i)j (ng/i)j (ug/i)
4990J 510! 10200
591J 61!
33000J 1700! 58000
420J 122!
8J 1.8! 5200
320000J 15170!
45J 7.1! 40
18000J 1300! 500000
428000J 38868!
18000J 1300! 500000
18500J 60!
18000J 1300! 500000
530000J 68000! 500000
530000J 68000! 500000
530000J 68000! 500000
530000J 68000! 500000
530000J 68000! 500000
2942J 1196!
555J 54!
543J 21!
627J 115!
540J 78!
750J 87!
1000! 33000
65J 2.5! 210
64700J 6470!
388!
1.4J 0.77! 1.8
27.8!
Chronic Value
(Jig/1)
450
5800
520
16
50000
50000
50000
50000
50000
50000
50000
50000
3300
8.1
10
0.94
Bio-
concentration ! Henry's Law
Factor j Constant
Value! Value (atm/
(l/kg)j m3-mole)
30. 6J 0.0184
inoi o.oooon
36J 0.000000105
nooi 0.00002
o.ooii
16J 0.0000225
1150J 0.0000161
32300J
6.6J 0.000113
10100J
12J 0.000000747
19500J
lOOOOOJ
!
i
!
loooooi
240J 0.0006
4790J 0.0000078
33000J 0.0000053
3300J 0.00008
3200J 0.00063
231j
!
49J
85215J
I
5500J 0.018
I
Adsorption
Coefficient
(Koc)
Value
363
62700
40
11000
0.4
38
41700
207000
12
66900
100
126000
110000000
420000000
1500
36000
330000
33000
33000
30000
Bio-
degradation
Half-Life
Value
(days)
360
1900
7
12
440
17
16
17
180
17
17
17
17
17
17
100
20
E-18
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.3: Aquatic Life Toxicity Data for 132 MP&M Pollutants of Concern
CAS !
Number j Pollutant Name
7440020 JNickel
7440224 I Silver
7440235 I Sodium
7440280 I Thallium
7440315 I Tin
7440326 I Titanium
7440360 JAntimony
7440382 JArsenic
7440393 JBarium
7440417 I Beryllium
7440428 JBoron
7440439 jCadmium
7440473 I Chromium
7440484 I Cobalt
7440508 I Copper
7440575 I Gold
7440622 I Vanadium
7440655 I Yttrium
7440666 I Zinc
7440702 I Calcium
76644 1 7 i Ammonia as N
7782492 1 Selenium
14265442 JFhosphate
14808798 iSulfate
16887006 I Chloride
16984488 JFluoride
18496258 jSulfide
18540299 i Chromium hexavalent
20324338 JTripropyleneglycolmethylether
Freshwater Aquatic Life j Saltwater Aquatic Life
Acute Value! Chronic Value! Acute Value
(ug/l)j Qigfl)! (ug/1)
470J 52! 74
3.4J 0.34! 1.9
1640000J 1020000!
1400J 40! 2130
18.6!
191!
3500J 1600! 4800
340J 150! 69
410000J 2813!
130J 5.3!
31.6!
4.3J 2.2! 42
570J 74! 1100
1620J 49!
13J 9! 4.8
! !
11200J 9!
! !
120J 120! 90
200000!
13300J 2280! 3800
12.83J 5! 290
i i
1000000!
860000J 230000!
1600J 160!
2j
16J 11! 1100
2484600J 683870!
Chronic Value
(M6fl)
8.2
0.19
213
2900
36
9.3
50
10
3.1
81
570
71
2
50
Bio-
concentration
Factor
Value
0/kg)
47
0.5
116
1
44
19
64
16
360
47
4.8
16
0.2
Henry's Law
Constant
Value (atm/
m3-mole)
0.00032
0.0000000001
Adsorption
Coefficient
(Koc)
Value
300
3.1
46
Bio-
degradation
Half-Life
Value
(days)
16
16
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Appendix E: Environmental Assessment
Table E.3: Aquatic Life Toxicity Data for 132 MP&M Pollutants of Concern
CAS !
Number j Pollutant Name
136777612 iXylene, o- & p- c
179601231 iXylene, m- & p- c
C003 JBOD 5-day (carbonaceous)
C004 I Chemical Oxygen Demand (COD)
C009 I Total Suspended Solids (TSS)
CO 1 0 I Total Dissolved Solids (TDS)
C012 I Total Organic Carbon (TOC)
C020 I Total Recoverable Phenolics
C02 1 I Total Kjeldahl Nitrogen
C025 jAmenable Cyanide
C036 I Oil And Grease (as Hem)
! Total Petroleum Hydrocarbons (as
C037 jSgt-hem)
C042 I Weak-acid Dissociable Cyanide
iPhosphorus (as PO4)
i Oil and Grease
Freshwater Aquatic Life
Acute Value
(MS/0
2600
2600
Chronic Value
(MS/1)
1205
1205
Saltwater Aquatic Life
Acute Value
(MS/0
6000
6000
Chronic Value
(MS/1)
600
600
Bio-
concentration
Factor
Value
(I/kg)
208
208
Henry's Law
Constant
Value (atm/
m3-mole)
0.0076
0.0076
Adsorption
Coefficient
(Koc)
Value
260
260
Bio-
degradation
Half-Life
Value
(days)
28
28
Notes:
a. Aquatic toxicity data for n-decane are reported based on structural similarity
b. Aquatic toxicity data for n-docosane are reported based on structural similarity
c. Values for the most stringent isomer (p-Xylene) are assumed
Sources: Arthur D. Little (1983), Arthur D. Little (1986), Birge et al. (1979), Clay (1986), Holdway andSpraque (1979), ICF, Inc. (1985), Leblanc (1980), Lyman et al. (1981), U.S. Atomic Energy
Commission (1973), U.S. EPA (1972), U.S. EPA (1976), U.S. EPA (1980), U.S. EPA (1993), U.S. EPA (1998/99a), U.S. EPA (1998/99b), Zhang and Zhang (1982).
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
E.I.3 Grouping MP&M Pollutants Based
on Risk to Aquatic Receptors
The impact assessment for aquatic receptors looks at the six
individual fate and effects parameters for each MP&M
POC, including acute and chronic aquatic toxicities,
bioconcentration factors, Henry's Law constants, adsorption
coefficients, and biodegradation half-lives. EPA grouped
POCs with similar attributes, and assigned qualitative
descriptors of potential environmental behavior and impact
to each group. This grouping was used to describe the range
of MP&M pollutant characteristics in Chapter 12. The
grouping described below focuses specifically on aquatic
environments and their biological receptors; it does not
cover the human health toxicity data discussed in the
previous section.
Table E.4 provides a summary of the categorization scheme
for the six fate and effects parameters.
Table E.4: Summary of Categorization Scheme For Six Fate and Effects Parameters
Parameter
Acute Toxicity (AT)
Chronic Toxicity (CT)
Bioconcentration Factor (BCF)
Henry's Law Constant (H)
Adsorption Coefficient (Koc)
Biodegradation Half-Life (t1/2)
High Hazard
AT<100|ig/l
CT<10|ig/l
BCF > 500
H>10'3
Koc> 10,000
t1/2<7d
Moderate Hazard
100 < AT< l,000|ig/l
10 < CT < lOOjjg/1
50 < BCF < 500
ID'5 < H < ID'3
1,000 < KK < 10,000
7 d < t1/2 < 28 d
Low Hazard
AT>l,000|ig/l
CT>100|ig/l
5 < BCF < 50
3.0xlO-7180d
Source: U.S. EPA analysis.
a. Acute and chronic aquatic toxicity
EPA used the available AT data to group chemicals
according to their relative short-term effects on aquatic
organisms, using the following categories:
AT < 100ug/l
100ug/l < AT < l,000ug/l
AT > 1,000 ug/1
high acute toxicity
moderate acute toxicity
low acute toxicity
These categories reflect the fact that acute toxicity decreases
when higher concentrations of a pollutant are required to
induce short-term mortality in the test organisms. EPA's
Office of Pollution Prevention and Toxics (OPPT) uses this
categorization as guidance to assess data submitted in
Premanufacture Notices (PMN) (EPA. 1996).
EPA used the available CT data to group chemicals
according to their relative long-term effects on aquatic
organisms, based on the following categories:
CT < 10ug/l
10ug/l < CT < 100ug/l
CT > 100 ug/1
High chronic toxicity
Moderate chronic toxicity
Low chronic toxicity
These categories assume that CT occurs at a concentration
averaging one tenth of that responsible for acute toxicity.
They also reflect the fact that chronic toxicity decreases
when higher concentrations of a pollutant are required to
induce longer-term lethal or sublethal responses in the test
organisms.
b. Bioconcentration factor (BCF)
EPA used the available BCF data to group chemicals
according to their potential to bioconcentrate in aquatic
organisms, based on the following categories:
BCF > 500
50 10-3
10'5 < H < 10'3
High potential to volatilize
Moderate potential to volatilize
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Appendix E: Environmental Assessment
3.0xlO-7 10,000
1,000 < Koc < 10,000
10 180d
Rapid rate of biodegradation
Moderate rate of biodegradation
Slow rate of biodegradation
Resistant to biodegradation
A faster rate of biodegradation by microbial metabolism
decreases an organic chemical's hazard to aquatic receptors.
The more rapid the rate of biodegradation, the more quickly
a chemical will be removed from the aquatic environment.
Most metals occur as inorganic compounds (notable
exceptions include organic forms of certain metals, such as
mercury, lead, or selenium), and are not removed by
biodegradation. EPA assumes that all metals are resistant to
biodegradation for the purposes of this assessment.
E.I.4 Assumptions and Limitations
The following are the major assumptions and limitations
associated with the data compilation and categorization used
in the MP&M analysis.
* Some data are estimated, and subject to
uncertainty;
> Data are unavailable for some chemicals and
parameters;
The POCs considered in this study do not include
all the constituents that may be present in MP&M
pollutants;
Data derived from laboratory tests may not
accurately reflect conditions in the field; and
Available aquatic toxicity and bioconcentration test
data may not represent the most sensitive species.
E.2. METHO&oioey
E.2.1 Sample Set Data Analysis and
National Extrapolation
This analysis uses discharge information from 885 sample
MP&M facilities (excluding two sample facilities in Puerto
Rico) that discharge directly or indirectly to 627 receiving
waterways (544 rivers/streams, 55 bays/estuaries, and 28
lakes). The in-stream water quality analysis excluded four
of the 55 marine reaches due to data limitations. EPA
extrapolated the environmental assessment results for the
sample facilities to the entire population of MP&M facilities
nationwide (approximately 62,752 facilities discharging to
58,530 waterbodies). This extrapolation uses sample facility
weights developed as part of the data collection process.
See the Statistical Summary for the Metal Products &
Machinery Industry Surveys in the Administrative record for
today's rule for additional information on sample design and
facility level weights. Appendix F discusses the differential
weighting technique used to extrapolate estimated sample
facility results to the population level.
EPA evaluated the national level environmental impacts of
reducing pollutant discharges from MP&M facilities to the
nation's waterbodies for the proposed rule. EPA considered
only pollutant loadings from MP&M facilities to particular
waterbodies in the national analysis. With one exception,
EPA did not take background loadings from other sources
into account. For the analysis of sewage sludge quantity,
EPA was able to use information from the Phase 2 Section
308 survey of POTWs to estimate total metal loadings from
all sources to a POTW of a given size (i.e., small, medium,
and large). The Agency based this estimate on survey
estimates of the average number of small, medium, and large
MP&M facilities discharging to a POTW in each size
category and the percent contribution of total metal loadings
discharged from MP&M facilities.
E.2.2 Water Quality Modeling
EPA used four different equations to model the impacts of
MP&M discharges on receiving waterways. EPA used a
simple stream dilution model for MP&M facilities that
discharge into streams or rivers. This model does not
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Appendix E: Environmental Assessment
account for fate processes other than complete immediate
mixing.1 EPA derived the facility-specific data (i.e.,
pollutant loading and facility flow) used in this equation
from sources described in Sections 3.1 and 5.2 of this report.
The Agency used one of three receiving stream flow
conditions (the lowest one-day average flow with a
recurrence interval of 10 years (1Q10), the lowest
consecutive seven-day average flow with a recurrence
interval of 10 years (7Q10), and the harmonic mean flow),
depending on the criterion or toxic effect level being
considered.
The 1Q10 and 7Q10 flows are used in comparisons of in-
stream concentrations with acute and chronic aquatic life
criteria or toxic effect levels, respectively, as recommended
in the Technical Support Document for Water Quality-based
Toxics Control (U.S. EPA, 1991).
The harmonic mean flow, defined as the inverse mean of
reciprocal daily arithmetic mean flow values, is used in
comparisons of in-stream concentrations with human health
criteria or toxic effect levels based on lifetime exposure.
EPA recommends the long-term harmonic mean flow as the
design flow for assessing potential long-term human health
impacts. Harmonic mean flow is preferable to arithmetic
mean flow because in-stream pollutant concentration is a
function of, and inversely proportional to, the streamflow
downstream of the discharge.
The event frequency represents the number of times an
exposure event occurs during a specified time period. EPA
set the event frequency equal to the facility operating days to
assess impacts on aquatic life. The calculated in-stream
concentration is thus the average concentration on days the
facility is discharging wastewater. EPA set the event
frequency at 365 days to assess long-term human health
impacts. The calculated in-stream concentration is thus the
average concentration on all days of the year. This
frequency leads to a lower calculated concentration because
of the additional dilution from days when the facility is not
operating, but it is consistent with the conservative
assumption that the target population is present to consume
drinking water every day and contaminated fish throughout
an entire lifetime. The following equation calculates in-
stream concentration for streams and rivers:
C. =
L
(OD FF) + (EF SF)
(E.I)
1 EPA used an exponential decay model to estimate pollutant
concentrations for the analysis of cancer risk from drinking water
consumption for streams. This model is discussed in detail in
Appendix G.
where:
C1S
L
OD
FF
EF
SF
in-stream pollutant concentration (ug/L);
facility pollutant loading (ug/yr);
for indirect dischargers, L = L mdirectfacillty * (1-
TMT), where TMT is POTW treatment
removal efficiency (unitless);
facility or POTW operating days (days/yr);
MP&M facility flow (L/day); for indirect
dischargers, FF = POTW flow (L/day);
event frequency (days/yr); and
receiving stream flow (L/day).
EPA used the following simple steady-state model for
facilities that discharge into lakes other than the Great lakes.
This model takes into account pollutant degradation and the
hydraulic residence time of the lake:
C.
-'lake
(1 + Tw k)
(E.2)
where:
Q =
T =
A w
k =
steady -state lake concentration of pollutant
(Mg/L),
steady-state inflow concentration of pollutant
mean hydraulic residence time (yr),
first-order pollutant decay rate (yr-1),
Q
(E.3)
where:
V = lake volume (m3), and
Q = mean total inflow rate (nrVyr).
EPA used alternative means to predict pollutant
concentrations suitable for comparison with ambient criteria
or toxic effect levels for facilities discharging to
hydrologically complex waters, such as bays and estuaries.
Where possible, EPA employed site-specific critical
dilution factors (CDFs) to predict the concentration at
the edge of a mixing zone. Where CDFs were not available,
EPA used available estuarine dissolved concentration
potentials (DCPs).
EPA obtained site-specific CDFs from a survey of states and
regions conducted by EP A's Office of Pollution Prevention
and Toxics (Mixing Zone Dilution Factors for New
Chemical Exposure Assessments, U.S. EPA, 1992a). The
dilution model for estimating estuary concentrations by
using a CDF is presented below:
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Appendix E: Environmental Assessment
C =
L
EF FF CDF
(E.4)
where:
CK
L
EF
FF
CDF =
estuary pollutant concentration (ug/L);
facility pollutant loading (ug/yr);
for indirect dischargers, L = L mfcct&clllty *
(1-TMT), where TMT is POTW treatment
removal efficiency (unitless);
event frequency (days/yr);
facility flow (L/day); for indirect
dischargers, FF = POTW flow (L/day);
and
critical dilution factor (unitless).
EPA used acute CDFs to evaluate acute aquatic life effects
and chronic CDFs to evaluate chronic aquatic life or adverse
human health effects. EPA assumed that the drinking water
intake and fishing location are at the edge of the chronic
mixing zone. EPA set the event frequency equal to the
facility operating days for comparison with aquatic life
criteria or toxic effect levels, and equal to 365 days for
comparison with human health criteria or toxic effect levels.
The National Oceanic and Atmospheric
Administration (NOAA) has developed DCPs to predict
pollutant concentrations in various salinity zones for each
estuary inNOAA's National Estuarine Inventory (NED.
A DCP represents the concentration of a nonreactive
dissolved substance under well-mixed, steady-state
conditions given an annual load of 10,000 tons. DCPs
account for the effects of flushing by considering the
freshwater inflow rate, and dilution by considering the total
estuarine volume. DCPs reflect the predicted estuary-wide
response, and may therefore not be indicative of
concentrations at the edge of much smaller mixing zones.
The dilution model used for estimating pollutant
concentrations using a DCP is presented below:
CL =
L DCP
BL CF
(E.5)
where:
DCP
BL
CF
estuary pollutant concentration (ug/L);
facility pollutant loading (kg/yr); for
indirect dischargers, L = L mdirectfacillty *(1-
TMT), where TMT is POTW treatment
removal efficiency (unitless);
dissolved concentration potential (ug/L);
benchmark load (10,000 tons/yr); and
conversion factor (907.2 kg/ton).
comparing projected waterway pollutant concentrations to
EPA water quality criteria or toxic effect levels for the
protection of aquatic life and human health. EPA
determined water quality exceedences by dividing the
projected waterway pollutant concentration by the EPA
water quality criteria or toxic effect levels for the protection
of aquatic life and human health. A value greater than one
indicates an exceedance.
E.2.3 Impact of Indirect Discharging
Facilities on POTW Operations
a. Analysis of biological inhibition
Inhibition of POTW operations occurs when high levels of
toxics, such as metals or cyanide, kill the bacteria required
for the wastewater treatment process. EPA analyzed
inhibition of POTW operations by comparing calculated
POTW influent concentrations with available inhibition
levels. Exceedences are indicated by a value greater than
one. POTW influent concentrations are estimated as:
C . =
pl OD PF
(E.6)
where:
CP1 =
L =
OD =
PF =
POTW influent concentration (ug/L),
facility pollutant loading (ug/yr),
facility operating days (days/yr), and
POTW flow (L/day).
EPA determined potential water quality impacts by
b. Analysis of sludge disposal practices
EPA also analyzed the effects of MP&M discharges on
POTW operations by comparing the estimated
concentrations of metals in sewage sludge with the
published metals concentration limits for preferable sewage
sludge disposal or use practices. In particular, EPA
examined:
* whether MP&M baseline discharges would prevent
POTWs from being able to meet the metals
concentration limits required for more favorable
and lower-cost sewage sludge use/disposal
practices (i.e., beneficial land application and
surface disposal); and
> whether limitations on the selection of management
practices would be removed under the proposed
rule.
EPA estimated the sewage sludge concentrations often
metals for sample facilities under baseline and
post-regulatory option discharge levels. EPA compared
these concentrations with the relevant metals concentration
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
limits for three sewage sludge management options: Land
Application-High (Concentration Limits), Land
Application-Low (Ceiling Limits), and Surface Disposal.
Metal concentrations in sewage sludge are estimated as:
C
sp
where:
C,,
L
TMT
PART
SGF
L TMT PART SGF
OD PF
(E.I)
sewage sludge pollutant concentration
(mg/kg),
facility pollutant loading (ug/yr),
POTW treatment removal efficiency
(unitless),
pollutant-specific sludge partition factor
(unitless),
sludge generation factor (mg/kg per ug/L),
OD = POTW operating days (days/yr), and
PF = POTW flow (L/day).
EPA derived the facility-specific data to evaluate POTW
operations from the sources described in Sections 3.1 and
5.2. EPA examined multiple MP&M facilities discharging
to the same POTW by summing the individual loadings
before calculating the POTW influent and sewage sludge
concentrations.
The partition factor is a chemical-specific value
representing the fraction of the load expected to partition to
sewage sludge during wastewater treatment. EPA used 1988
data on volume of sewage sludge produced (Federal
Register, February 19, 1993, p. 9257) and volume of
wastewater treated (1988 Needs Survey, Table C-3) to
predict sewage sludge generation, and found a sludge
generation factor of 7.4 mg/kg per ug/L:
SGF =
VwwT_2&.136 x Kfggllday _ 365 day . 1 DMT _ 3.79 L . 1 mg chemical
Vssp 5,357,200 DMTIyr 1 yr 1000 kg 1 gal 1000 ug chemical
7.4 mg chemical/kg sludge
1 ug chemical/L wastewater
(E.8)
where:
SGF
WWT
sludge generation factor ug/L,
= volume of wastewater treated gal/day, and
= volume of sewage sludge produced dry
metric tons (DMT)/yr.
The resulting concentration in sewage sludge is 7.4 mg/kg
dry weight for every 1 ug/L of pollutant removed from
wastewater and partitioned to sewage sludge.
E.2.4 Assumptions and Limitations
The following discussion focuses on major assumptions and
limitations associated with these in-stream water quality
analyses.
a. Other source contributions
EPA did not account for "other source contributions" of
MP&M pollutants to estimate in-stream concentrations of
these pollutants. Accounting for the discharges from other
sources is important because assessing benefits from
reduced exceedance of AWQC limits depends on comparing
concentrations of pollutants from all sources with applicable
thresholds. Analyses must also identify situations in which
threshold criteria are exceeded in the baseline case but met
under a regulatory option. Failing to account for other
source contributions has an uncertain effect on estimated
benefits. For example, if non-sample MP&M facilities are
major contributors to aggregate pollutant discharges to a
receiving stream, then the analysis will likely understate the
extent of aquatic habitat improvements that may be
accomplished by reduced MP&M pollutant discharges.
Conversely, if the total MP&M contribution to the aggregate
pollutant discharges to a receiving stream is not significant,
then reducing MP&M discharges may reduce but not
eliminate AWQC exceedances, and the benefits of the
MP&M regulation can be overstated. The net effect of the
following are unknown:
* excluding other sources understates the number and
extent of baseline exceedances;
* excluding non-sample MP&M facilities understates
the reduction in MP&M pollutant discharges due to
the rule; and
* the number of cases in which estimated baseline
exceedances are eliminated may be either over- or
understated, depending on the contribution of
pollutants from non-MP&M sources.
ฃ-25
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
b. Waterbody modeling
EPA made four major assumptions concerning all waterbody
modeling, and two major assumptions specific to stream
modeling. These assumptions are summarized below:
* Complete mixing of POTW discharge flow occurs
immediately. This mixing results in the calculation
of an "average" concentration, even though the
actual concentration may vary across the width and
depth of the waterbody.
> Pollutant loads to the receiving waterbody are
continuous and representative of long-term facility
operations. This assumption may overestimate
long-term risks to human health and aquatic life,
but may underestimate potential short-term effects.
- In the absence of data from EPA's Permit
Compliance System (PCS) on specific
individual POTW flow, POTW daily flow rates
were set equal to the simple arithmetic mean flow
among POTWs associated with sample MP&M
facilities.
> EPA used 1Q10 and 7Q10 receiving stream flow
rates to estimate aquatic life impacts, and harmonic
mean flow rates to estimate human health impacts,
when modeling stream reaches. EPA estimated
1Q10 low flows by using the results of a regression
analysis conducted for OPPT of 1Q10 and 7Q10
flows from representative U.S. rivers and streams
(Versar, 1992). EPA estimated harmonic mean
flows from the mean and 7Q10 flows as
recommended in the Technical Support Document
for Water Quality-based Toxics Control (U.S.
EPA, 1991). These flows may not be the same as
those used by specific states to assess impacts.
Where data on stream flow parameters were not available,
EPA set mean and 7Q10 flow values equal to the
corresponding mean values associated with reaches located
upstream and downstream of the sample reach.
c. Exposure analyses
MP&M exposure assessment in freshwater locations uses
two sets of human health-based AWQC:
* AWQC for the protection of human health from the
consumption of organisms and drinking water, and
> AWQC for the protection of human health from
consumption of organisms only.
MP&M exposure assessments in marine locations use
AWQC for the protection of human health from the
consumption of organisms only, because salt water is not
used for drinking water supply.
d. Extrapolation from sample set to national
level
Although the sample set should represent a national group of
facilities discharging to waterways and POTWs, effluent
from an individual sample facility may have a different
potential environmental impact than effluent from the
facilities it is assumed to represent. For example, a facility
that discharges to a stream with a very low flow may be
similar to the facilities it represents in all aspects except
available dilution in the receiving stream. The sample frame
used in the MP&M analysis was not designed to take
receiving waterbody characteristics into account. Using
sample weights to extrapolate environmental impacts may
either under- or overstate estimated impacts.
E.3 DATA SOURCES
The following three sections describe the various data
sources used to evaluate water quality and POTW impacts.
E.3.1 Facility-Specific Data
Section E.2.1 provided detailed information on sample size
and distribution, and on receiving waterways. The names,
locations, and the flow data for the POTWs to which the
MP&M facilities discharge were obtained from the MP&M
facility level Surveys and EPA's PCS database. EPA took
alternative measures to obtain a complete set of receiving
POTWs if these sources did not yield information for a
given facility. EPA used latitude/longitude coordinates (if
available) to locate those POTWs that have not been
assigned a reach number in PCS. EPA identified the nearest
POTW in the case of facilities for which the POTW
receiving the plant discharge could not be positively
identified. EPA based its identification of the closest linear
distance on the latitude/longitude coordinates of the MP&M
facility or the city in which it was located. EPA then
identified the corresponding reach in PCS, and obtained
POTW flow from the Needs Survey or PCS.
EPA identified reaches to which direct MP&M facilities
discharge by identifying the receiving reach in PCS or by
identifying the nearest reach. EPA based its identification
of the closest linear distance on the MP&M facility's
latitude/longitude coordinates.
E.3.2 Waterbody-Specific Data
a. Streams and rivers
EPA used 1Q10, 7Q10, and mean flow data for the 544
streams and rivers. EPA obtained 7Q10 and mean flow data
from the W.E. Gates study data or from measured stream
flow data, both of which are contained in EPA's GAGE file.
The W.E. Gates study contains calculated average and low
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Appendix E: Environmental Assessment
flow statistics based on the best available flow data and on
drainage areas for reaches throughout the United States.
The GAGE file also includes average and low flow statistics
based on measured data from United States Geological
Survey (USGS) gaging stations. In the absence of data on
stream flow parameters, EPA set 7Q10 and mean flow
values equal to the corresponding median values associated
with the sample reaches. EPA used the results of a
regression analysis conducted for OPPT of 1Q10 and 7Q10
flows from representative U.S. rivers and streams (Versar,
1992) to estimate 1Q10 flows. EPA estimated harmonic
mean flows from the mean and 7Q10 flows as recommended
in the Technical Support Document for Water Quality-based
Toxics Control (U.S. EPA, 1991).
b. Lakes
EPA used data on hydraulic residence time (i.e., the amount
of time water remains in a lake) to analyze relatively small
lakes, and CDFs (which describe dilution in a portion of a
lake) to analyze large lakes.
The sample MP&M facilities discharged directly to two lake
reaches and indirectly to 26 lake reaches: 19 to small lakes,
5 to sections of Lake Erie, and 4 to sections of Lake
Michigan. EPA calculated the average hydraulic residence
time for small lakes based on lake surface and drainage
areas. EPA obtained data on lake surface and drainage area
from the US Army Corps of Engineers, Major Dams: Map
Layer Description File (USCE, 1999). CDFs were readily
available for Lake Michigan, but not for the 5 sample
reaches on Lake Erie. EPA arithmetically averaged the
seven chronic CDFs available for reaches discharging to
Lake Erie (1, 1, 4, 4, 10, 10, 4) (U.S. EPA, 1992a, p. A-4)
for the five reaches being modeled.
c. Estuaries and bays
Fifty-five bays and estuaries receive discharges from sample
MP&M facilities. Data necessary to support water quality
modeling were not available for four of the 55
bays/estuaries. A dilution model predicted pollutant
concentrations in the chronic and acute mixing zones, based
on site-specific CDFs (U.S. EPA, 1992a and Versar, 1994),
to estimate the pollutant concentrations in 23 of these
complex waterbodies.
Both acute and chronic CDFs were available for 19 of the
55 bays/estuaries. EPA estimated acute and chronic CDFs
for New York bays/estuaries by arithmetically averaging
available values for nearby New Jersey sites discharging to
the Arthur Kill (acute: 1.5, 4.0, 5.0; chronic: 5; 20; 10) and
Upper New York Bay (acute: 8.0; chronic: 22.9). Acute and
chronic CDFs for the Buzzards Bay in Massachusetts were
estimated by arithmetically averaging values for nearby
Massachusetts and Rhode Island sites discharging to the
Atlantic Ocean.
EPA could not identify or approximate chronic CDFs for the
remaining 28 sample reaches. Acute CDFs are available for
43 of the 55 bays/estuaries. EPA extrapolated acute CDFs
for two bays/estuaries in Florida by using CDFs for another
Florida bay. Likewise, EPA extrapolated acute CDFs for
four bays/estuaries in California by using CDFs for another
California bay.
EPA obtained DCP values for 11 of the 28 sample
bays/estuaries for which CDFs were not available from the
Development of Mixing Zone Dilution Factors report
(Versar, 1994). EPA then used a dilution model that
predicts pollutant concentrations in the estuarine
environment using a site-specific DCP value.
E.3.3 Information Used to Evaluate
POTW Operations
EPA used removal efficiency rates, inhibition values, and
sewage sludge regulatory levels to evaluate POTW
operations. EPA obtained POTW removal efficiency rates
from several sources. The Agency developed rates from
POTW removal data and pilot-plant studies or used
removals for a similar pollutant when data were not
available. Use of the selected removal rates assumes that the
evaluated POTWs are well-operated and have at least
secondary treatment in place (U.S. EPA, 2000).
EPA obtained inhibition values from the Guidance Manual
for Preventing Interference at POTWs (U.S. EPA, 1987a)
and from CERCLA Site Discharges to POTWs: Guidance
Manual (U.S. EPA, 1990). EPA used the most conservative
values for activated sludge (i.e., the lowest influent
concentrations that would cause inhibition). The Agency
used a value based on compound type (e.g., aromatics) for
pollutants with no specific inhibition value.
EPA obtained sewage sludge regulatory levels from the
Federal Register 40 CFR Part 257 et al., Standards for the
Use or Disposal of Sewage Sludge; Final Rules (February
19, 1993) and from the Federal Register 59(38):9095-9099
(February 25, 1994) and 60(206):54,764-54,770 (October
25, 1995) for eight metals regulated in sewage sludge. EPA
used pollutant limits established for the final use or disposal
of sewage sludge when the sewage sludge is applied to
agricultural and non-agricultural land or is applied to a
dedicated surface disposal site.
Finally, EPA obtained sludge partition factors from the
Report to Congress on the Discharge of Hazardous Wastes
to Publicly Owned Treatment Works (Domestic Sewage
Study) (U.S. EPA, 1986).
Table E.5 lists POTW treatment removal efficiency rates,
inhibition values, sewage sludge partition factors, and
sewage sludge regulatory levels used in the evaluation of
POTW operations.
ฃ-27
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.5: POTW-Related Data for
CAS I
Number i Pollutant Name
51285 iDinitrophenoL^-
57125 iCyanide
59507 iParachlorometacresol
62533 iAniline
62759 iNitrosodimethylamine, N-
65850 iBenzoic acid
67641 ! Acetone
67663 iTrichloromethane
68122 iDimethylformamide, N;N-
75003 iChloroethane
75092 iDichloromethane
75 1 50 ! Carbon disulfide
75354 ! Dichloroethene, 1 J -
75694 iTrichlorofluoromethane
78591 ilsophorone
78831 ilsobutyl alcohol
78933 iMethyl ethyl ketone
79016 iTrichloroethene
80626 JMethyl methacrylate
83329 iAcenaphthene
84742 iDi-n-butyl phthalate
85018 iPhenanthrene
85687 ! Butyl benzyl phthalate
86306 iNitrosodiphenylamine^N-
86737 iFluorene
88755 iNitrophenoL.2-
91203 iNaphthalene
91576 iMethylnaphthalene^-
92524 iBiphenyl
95476 iXylene^o-
95487 iCresoLo-
98555 :TerpineoL_alpha-
98862 iAcetophenone
99876 iCymene.p-
100027 iNitrophenoL.4-
100414 iEthylbenzene
100425 iStyrene
100516 ! Benzyl alcohol
100754 iNitrosopiperidine^ N-
101848 iDiphenyl Ether
105679 lDimethylphenol: 2,4-
106445 iCresoL,p-
107028 iAcrolein
108101 iMethyl isobutyl ketone
108372 :Bromo-3-chlorobenzene, 1-
108383 iXylene^m-
108883 ! Toluene
108907 iChlorobenzene
POTWJ
Inhibition Level:
Value!
fus/ni
1000!
soooi
soooi
1000!
10000!
120000!
soooooi
1000!
isooooi
sooooi
isooooi
700i
120000!
1000000!
120000!
20000!
120000!
sooooo!
10000!
sooooo!
10000!
sooooo!
soooo!
sooooo!
sooo!
sooo!
sooo!
90000!
1000000!
120000!
sooo!
soooo!
200000!
sooooo!
1000000!
1000!
1000!
40000!
90000!
so!
120000!
100!
sooo!
200000!
140000!
132 MP&M Pollutants
Sludge Criteria
POTW Sludge! Value
Partition Factor! (ma/ks)
0.10000000149!
0.07900000364!
O.l!
o.i!
o.i!
o.i!
o.ois!
o.i!
0.0075!
0.1395!
0.0075!
0.079!
o.i!
o.i!
0.0578!
0.366!
0.216!
0.366!
0.452!
0.366!
0.275!
0.079!
0.366!
0.149!
0.079!
O.l!
o.i!
0.0075!
o.i!
0.06!
0.149!
o.i!
0.079!
0.079!
0.10000000149!
o.i!
0.149!
0.278!
0.154!
POTW Removal
Efficiency Rate
(Percentage)
77.51
70.44
63
93.41
77.51
80.5
83.75
87
77.51
54.28
84
77.51
77.32
77.51
28
96.6
77.51
99.96
98.29
84.66
94.89
81.65
90.11
69.85
26.83
94.69
28
96.28
77.32
52.5
94.4
95.34
99.79
77.51
93.79
93.65
78
77.32
77.32
77.51
71.67
77.51
87.87
77.32
95.07
96.18
96.37
E-28
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.5: POTW-Related Data for
CAS I
Number i Pollutant Name
108952 iPhenol
110861 IPyridine
1 12403 iDodecane: n- (a)
112958 iEicosane^n- (a)
117817 ! Bis(2-ethy Ihexyl) phthalate
1 1 7840 ! Di-n-octy 1 phthalate
120127 iAnthracene
122394 iDiphenylamine
123911 iDioxane, 1^4-
124185 !Decane,n-
127184 iTetrachloroethene
129000 iPyrene
131113 ! Dimethyl phthalate
132650 iDibenzothiophene
1 37304 iZiram \ Cymate
142621 iHexanoic acid
206440 iFluoranthene
544763 iHexadecane^n- (a)
591786 iHexanone, 2-
593453 iQctadecanein-..(a)
606202 iDinitrotoluene^ 2^6-
629594 iTetradecane^n- (a)
629970 iDocosane, n-
630013 iHexacosane^ n- (b)
630024 iOctacosane^n- (b)
638686 :Triacontane; n- (b)
6463 1 1 i Tetracosane^ n- (b)
694804 :Bromo-2-chlorobenzene, 1-
832699 lMethylphenanthrene: 1-
1 576676 :DimethylphenanthreneA 3A6-
1730376 iMethylfluorene, 1-
2027170 ilsopropyhiaphthalene_12-
7429905 'Aluminum
7439896 ilron
7439921 iLead
7439954 iMagnesium
7439965 iManganese
7439976 'Mercury
7439987 iMolybdenum
7440020 iNickel
7440224 ! Silver
7440235 ! Sodium
7440280 ! Thallium
7440315 Ilin
7440326 ! Titanium
7440360 lAntimony
7440382 iArsenic
7440393 iBarium
POTWJ
Inhibition Level:
Value!
fu2/l)i
90000!
1000!
10000!
10000!
soooooi
1000!
120000!
20000!
sooooo!
sooo!
so!
10000!
sooo!
120000!
sooo!
100!
sooo!
sooooo!
sooooo!
sooooo!
sooo!
100!
1000000!
10000!
100!
sooo!
30!
3500000!
9000!
40!
132 MP&M Pollutants
Sludge Criteria
POTW Sludge! Value
Partition Factor! (ma/ks)
0.146!
o.i!
0.728!
0.075!
0.55!
o.os!
o.i!
0.034!
0.366!
o.i!
0.366!
0.366!
O.i!
0.366!
0.366!
0.366!
O.i!
l! 300
l! 17
l! 420
l! 41
l!
POTW Removal
Efficiency Rate
(Percentage)
95.25
95.4
59.78
68.43
77.51
77.32
45.8
9
84.61
83.9
77.51
84.68
84
42.46
77.32
77.51
88
77.32
84.55
84.55
84.55
77.32
91.36
81.99
77.45
14.14
35.51
71.66
18.93
51.44
88.28
2.69
71.66
42
91.82
66.78
65.77
15.98
E-29
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.5: POTW-Related Data for 132 MP&M Pollutants
CAS I
Number i Pollutant Name
7440417 ! Beryllium
7440428 iBoron
7440439 iCadmium
7440473 ! Chromium
7440484 ! Cobalt
7440508 ! Copper
7440575 iGold
7440622 ! Vanadium
7440655 lYttrium
7440666 iZinc
7440702 ! Calcium
76644 1 7 i Ammonia as N
7782492 1 Selenium
14265442 iPhosphate
14808798 iSulfate
16887006 ! Chloride
16984488 'Fluoride
18496258 ISulfide
18540299 i Chromium hexavalent
20324338 iTripropyleneglycolmethylether
136777612 iXylene^ o- & p- (c)
179601231 iXylene^m- & p- ฃc)
C003 iBOD 5-day (carbonaceous)
C004 ! Chemical Oxygen Demand (COD)
C009 ! Total Suspended Solids (TSS)
CO 1 0 ! Total Dissolved Solids (TDS)
CO 1 2 ! Total Organic Carbon (TOC)
C020 i Total Recoverable Pheno lies
C02 1 ! Total Kjeldahl Nitrogen
C025 iAmenable Cyanide
C036 ! Oil And Grease (as Hem)
1 Total Petroleum Hydrocarbons (as
C037 JSgt-hem)
C042 i Weak-acid Dissociable Cyanide
iPhosphorus (as PO4J
Oil and Grease
POTW
Inhibition Level
Value
(us/I)
1000
500
1000
1000
20000
5000
2500000
480000
25000
1000
120000
5000
POTW Sludge
Partition Factor
1
1
1
1
1
1
1
1
1
1
1
1
1
0.149
Sludge Criteria
Value
(mz/kz)
39
1500
2800
100
POTW Removal
Efficiency Rate
(Percentage)
71.66
30.42
90.05
80.33
6.11
84.2
32.52
9.51
32.52
79.14
8.54
38.94
34.33
57.41
84.61
57.41
61.35
57.41
57.41
52.4
36832
89.12
81.3
70.28
57.41
57.41
57.41
86.08
Sources: U.S. EPA (1985), U.S. EPA (1987), U.S. EPA (1990).
In the absence of data on POTW flow rates, EPA set the
POTW flow rate equal to the arithmetic mean flow among
POTWs associated with the sample MP&M facilities, using
the following steps:
1. Calculate arithmetic mean flow among POTWs
associated with the sample MP&M facilities. The
estimated arithmetic mean flow for POTWs associated
with the sample MP&M facilities is 61.4 million gallons
per day (MOD).
2. Set POTW flow rate equal to the relevant arithmetic
mean flow. For all POTWS with missing flow data,
EPA set their flow rates equal to the arithmetic mean
flow rate for sample POTWs, 61.4 MOD.
E-30
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
E.4 RESULTS
MP&M facilities nationwide currently discharge an
estimated 5,025 million pounds of pollutants per year to
publicly-owned treatment works (POTWs) and
approximately 410 million pounds of pollutants directly to
surface waters. MP&M facility effluents contain 43 priority
or toxic pollutants, 86 non-conventional pollutants, and
three conventional pollutants (BOD, TSS, and O&G).
EPA estimates that the proposed rule would reduce pollutant
discharges to the waters of the U.S. substantially, as shown
by the loadings estimates in Table E.6 for five categories of
pollutants. The regulation would result in total removals of
3,872 million pounds per year. These removals include a 30
million pound per year reduction in eight sewage sludge
contaminants and a 703 million pound per year reduction in
89 pollutants causing inhibition of sewage sludge. The
regulation would reduce discharges of 35 HAPs by about
one million pounds per year. The regulation would also
reduce discharges of pollutants with acute and chronic
effects on aquatic life by 823 and 1,035 million pounds per
year, respectively. These reductions result from increased
wastewater treatment, pollution prevention, and regulatory
closures. EPA evaluated the national environmental impacts
of reducing pollutant discharges from MP&M facilities to
the nation's waterbodies for the proposed rule. The
following sections present results of this analysis.
Table E.6 National MP&M Facility Discharges
Category
n of Pollutants
Million Ibs/yr
Million Ibs/yr
Million Ibs/yr
Million Ibs/yr
POTW Impacts
Activated Sludge
Inhibition
89
1,031
Remai
328
Rei
266
R
484
Biosolids
Contaminants
Baseline Loading
8
31.7
tiing with the Propo
1.61
tnaining with Optior
0.54
emaining with Opti(
0.43
HAP
sa
35
2.1
sed Option
1.11
1 2/6/10
0.89
m4/8
1.05
Receiving Stream Impacts:
Aquatic Life Toxicity
Acute
107
1,252
430
364
595
Chronic
116
1,758
723
647
895
a. Excludes loadings from facilities projected to close in the baseline. See Chapter 5.
Source: U.S. EPA analysis.
E.4.1 Human Health Impacts
This analysis compares the estimated baseline and
post-compliance in-stream pollutant concentrations with
AWQC. The comparison included AWQC both for
protection of human health through consumption of
organisms and for consumption of organisms and water.
Pollutant concentrations in excess of these values indicate
potential risks to human health.
EPA extrapolated the findings from the analysis of reaches
affected by sample facility discharges to national estimates
using facility sample weights, as described in Appendix F.
EPA's modeling results estimate that baseline in-stream
concentrations of 18 pollutants exceed human health criteria
for consumption of water and organisms in 10,310 receiving
reaches nationwide (Table E.7). The total number of
estimated baseline exceedences is 11,341. The proposed
rule eliminates concentrations in excess of the criteria for
consumption of water and organisms on 1,105 of these
reaches. EPA also estimates that the proposed rule
eliminates the occurrence of concentrations exceeding
human health criteria only for consumption of organisms on
121 of the 192 reaches on which EPA estimates baseline
discharges cause concentrations exceeding AWQC values.
Results also show that 382 receiving reaches will experience
partial water quality improvements from reduced occurrence
of some pollutant concentrations exceeding AWQC limits
for consumption of water and organisms. The total number
of exceedences is reduced to 9,789.
Table E.8 presents results for individual pollutants estimated
to affect water quality in the receiving stream.
E-31
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.7: Summary of Projected National
Criteria Exceedences
for MP&M Dischargers
Policy Option
Baseline
Streams (No.)
Pollutants (No.)
Total Exceedences
Proposed Option
Streams (No.)
Pollutants (No.)
Total Exceedences
Option 2/6/10
Streams (No.)
Pollutants (No.)
Total Exceedences
Option 4/8
Streams (No.)
Pollutants (No.)
Total Exceedences
Human Health
Water and
Organisms
10,310
18
11,341
9,205
11
9,789
4,151
11
4,720
4,160
13
4,711
Human
Health
Organisms
Only
192
6
256
71
5
107
71
5
107
65
5
100
Source: U.S. EPA analysis.
Table E.8: National Summary of Pollutants Projected to Exceed Human Health-Based AWQC
Pollutant
Aniline
Arsenic
Bis (2-ethylhexyl)
phthalate
Chloroethene
Cresol, p-
Dichloroethene, 1,1-
Dichloromethane
Dinitrophenol, 2,4-
Dinitrotoluene, 2,6-
Dioxane, 1,4-
Iron
Isophorone
Manganese
Nitrosodimethylamine, n-
Nitrosodiphenylamine, N-
Pyridine
Trichloroethene
Tricoloromethane
Total Exceedences
Human Health Water and Organisms
(# of reaches)
Baseline
12
474
59
9
9
143
12
9
9
12
7
9
224
10,310
12
9
12
12
11,343
Proposed
Option
12
433
15
9
0
57
12
0
0
12
0
0
0
9,205
12
0
12
12
9,791
Option
2/6/10
12
433
15
9
0
42
12
0
0
12
0
0
0
4,151
12
0
12
12
4,722
Option
4/8
12
372
15
9
9
67
12
0
0
12
0
0
0
4,160
12
9
12
12
4,713
Human Health Organisms Only
(# of reaches)
Baseline
0
117
26
0
0
12
0
0
0
0
0
0
72
20
9
0
0
0
256
Proposed
Option
0
50
12
0
0
12
0
0
0
0
0
0
0
20
12
0
0
0
106
Option
2/6/10
0
50
12
0
0
12
0
0
0
0
0
0
0
20
12
0
0
0
106
Option 4/8
0
44
12
0
0
12
0
0
0
0
0
0
0
20
12
0
0
0
100
Source: U.S. EPA analysis.
E-32
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
The alternative options would eliminate instances of in-
stream pollutant concentrations exceeding AWQC limits for
consumption of water and organisms in 6,159 (Option2) and
6,150 (Option 4/8) reaches. Options 2/6/10 and 4/8 would
eliminate occurrence of pollutant concentrations in excess of
AWQC values for organism consumption in 121 and 127
reaches nationwide. The total number of exceedences is
reduced to 4,827 and 4,811 under Option 2/6/10 and Option
4/8, respectively.
E.4.2 Aquatic Life Effects
EPA evaluated the effects of wastewater discharges on
receiving stream water quality under the baseline and the
proposed option. The analysis compared baseline and
post-compliance exceedances of aquatic life AWQC to
determine the effects of the rule. Table E.9 summarizes the
results extrapolated to the national level. Results show that
baseline pollutant concentrations exceed acute AWQC in
878 reaches and chronic AWQC in 2,466 reaches nationally
at baseline discharge levels. The total number of
exceedences at the baseline is 6,452.
Table E.9: Summary of Projected Criteria
Exceedences for MP&M Dischargers (National Basis)
Policy Option
Baseline
Streams (No.)
Pollutants (No.)
Total Exceedences
Proposed Option
Streams (No.)
Pollutants (No.)
Total Exceedences
Option 2/6/10
Streams (No.)
Pollutants (No.)
Total Exceedences
Option 4/8
Streams (No.)
Pollutants (No.)
Total Exceedences
Acute
Aquatic Life
878
10
1,152
103
11
188
61
8
72
52
6
62
Chronic Aquatic
Life
2,466
31
6,452
1,437
25
2,307
1,394
20
2,003
1,310
17
1,730
Source: U.S. EPA analysis.
Table E. 10 presents results for individual pollutants
estimated to affect water quality in the receiving reaches.
EPA estimates that the proposed option will eliminate
concentrations in excess of acute and chronic criteria in 775
and 1,029 reaches, respectively. Results also show that an
additional 903 receiving reaches will experience partial
water quality improvements from reduced occurrence of
some pollutant concentrations in excess of acute and/or
chronic AWQC limits for protection of aquatic life. The
proposed rule reduces the total number of exceedences to
2,495 nationwide. Options 2 and 4 would eliminate
exceedances of chronic AWQC values on 1,072 and 1,156
reaches. The alternative options would also eliminate in-
stream pollutant concentrations in excess of acute AWQC
value on 817 (Option 2/6/10) and 826 reaches (Option 4/8).
The total number of exceedences will be reduced to 2,075
and 1,792 under Option 2/6/10 and 4/8 respectively.
E-33
-------
MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.10: Summary of Pollutants Projected to Exceed Aquatic Life Based AWQC (National Basis)
Pollutant
Acrolein
Aluminum
Ammonia as N
Aniline
Anthracene
Benzoic Acid
Boron
Butyl benzyl phthalate
Cadmium
Carbon disulfide
Chromium hexavalent
Copper
Cyanide
Di-n-butyl phthalate
Dimethylphenanthrene,3,6-
Fluoranthene
Fluorene
Fluoride
[ron
Lead
Manganese
Molybdenum
Nickel
Phenanthrene
Phenol
Selenium
Silver
Sulfide
Tin
Vanadium
Zinc
Total Exceedences
Acute Aquatic Life (# of reaches)
Baseline
13
0
9
0
76
0
0
0
0
0
33
783
62
0
0
0
0
0
0
0
0
0
39
0
0
33
7
0
0
0
98
1,153
Proposed
Option
12
0
0
0
15
0
0
0
9
0
33
31
9
0
0
3
0
0
0
9
0
0
0
0
0
33
3
0
0
0
33
190
Option
2/6/10
12
0
0
0
15
0
0
0
9
0
0
13
9
0
0
3
0
0
0
9
0
0
0
0
0
0
3
0
0
0
0
73
Option 4/8
12
0
9
0
15
0
0
0
9
0
0
0
9
0
0
0
0
0
0
9
0
0
0
0
0
0
0
0
0
0
0
63
Chronic Aquatic Life (# of reaches)
Baseline
103
40
12
19
92
33
946
9
75
11
33
926
165
8
3
24
15
109
39
372
17
241
300
12
9
93
166
1,621
793
70
98
6,454
Proposed
Option
39
22
12
15
24
33
400
0
9
3
33
31
16
0
0
24
15
22
0
50
0
154
9
3
0
36
87
1,218
9
12
33
2,309
Option
2/6/10
39
13
12
15
15
0
366
0
9
3
0
13
16
0
0
15
15
22
0
9
0
130
0
3
0
3
78
1,218
0
12
0
2,008
Option
4/8
39
0
12
15
15
0
317
0
9
7
0
0
16
0
3
15
15
22
0
9
0
0
0
12
0
0
45
1,178
0
3
0
1,732
Source: U.S. EPA analysis.
E.4.3 POTW Effects
EPA evaluated the effects of indirect MP&M dischargers on
POTW operations for the baseline and the proposed option.
726 sample MP&M facilities discharge 132 pollutants to
524 POTWs. Of these, EPA evaluated 89 pollutants for
potential inhibition of POTW operations and 8 pollutants for
potential sludge contamination. The 726 indirect sample
MP&M facilities discharge 278.5 million pounds per year of
priority and non-conventional pollutants to the receiving
POTWs. EPA estimates that the proposed regulation would
reduce the MP&M loadings to the receiving POTWs to 71.6
million pounds per year. EPA extrapolated sample-level
results to the national level by using sample facility weights
and the differential weighting technique (see Appendix F for
details). At the national level, 57,707 MP&M facilities
discharge 5,025 million pounds of priority and non-
conventional pollutants. EPA estimates that the proposed
regulation would reduce the MP&M loadings to the
receiving POTWs to 1,463 million pounds per year at the
national level.
E-34
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
a. Biological inhibition
EPA estimated inhibition of POTW operations by
comparing predicted POTW influent concentrations to
available inhibition levels for 89 pollutants.
National results show that POTW influent concentrations of
18 pollutants exceed biological inhibition criteria at 515
POTWs in the baseline (see Table E. 11). The proposed
regulation would eliminate potential inhibition problems at
306 POTWs and reduce occurrence of pollutant
concentrations in excess of inhibition criteria at 82 POTWs.
Options 2/6/10 and 4/8 would eliminate influent
concentrations in excess of POTW inhibition criteria at 392
POTWs. Table E.12 presents the 18 individual pollutants
that are projected to impact POTWs because their influent
concentrations exceed biological inhibition criteria.
Table E.ll: National Summary of Projected Inhibition
and Sludge Contamination Problems
Policy Option
Baseline:
POTWs (No.)
Pollutants (No.)
Total Exceedences
Proposed Option
POTWs (No.)
Pollutants (No.)
Total Exceedences
Option 2/6/10
POTWs (No.)
Pollutants (No.)
Total Exceedences
Option 4/8:
POTWs (No.)
Pollutants (No.)
Total Exceedences
Biological
Inhibition
(# of POTWs)
515
18
1695
209
12
676
123
11
563
123
10
479
Sludge
Contamination
(# of POTWs)
6,953
8
18,782
6,889
8
18,434
5,574
8
16,934
5,574
8
16,510
Source: U.S. EPA analysis.
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Table E.12: National Summary of Pollutants Projected to Impact POTWs (National basis)
Pollutant
Acrolein
Arsenic
Benzoic acid
Boron
Bromo-2-
chlorobenzene, 1-
Bromo-3-
chlorobenzene, 1-
Cadmium
Chromium
Chromium hexavalent
Copper
Dinitrophenol, 2,4-
Iron
Lead
Mercury
Nickel
Selenium
Silver
Sodium
Sulfide
Tin
Zinc
Total Exceedences
Biological Inhibition
(# of POTWs)
Baseline
82
85
48
240
93
93
0
85
24
269
24
97
236
0
82
0
82
24
82
23
24
1,693
Proposed
Option
82
85
31
149
36
36
0
24
0
24
0
11
91
0
0
0
82
0
24
0
0
675
Option
2/6/10
82
85
0
123
36
36
0
24
0
24
0
11
36
0
0
0
82
0
24
0
0
563
Option
4/8
82
82
0
123
36
36
0
0
0
0
0
11
36
0
0
0
24
24
24
0
0
478
Sludge Contamination
(# of POTWs)
Baseline
1,553
2,159
3,804
2,515
130
3,080
1,410
3,194
17,845
Proposed
Option
1,553
2,086
3,688
2,480
130
2,964
1,410
3,146
17,457
Option
2/6/10
1,553
2,079
3,626
2,465
130
2,964
1,402
2,995
17,214
Option 4/8
1,553
2,046
3,626
2,465
130
2,964
1,360
2,995
17,139
Source: U.S. EPA analysis.
b. Sewage sludge
EPA estimated that baseline concentrations of eight metals
at the national level would fail to meet Land
Application-High limits for sludge disposal at 6,953
POTWs. These concentrations were compared with the
relevant metals concentration limits for the following
sewage sludge management options: Land Application-High
(Concentration Limits), Land Application-Low (Ceiling
Limits), and Surface Disposal. The Agency estimates that
the proposed regulation will eliminate metal concentrations
in excess of sludge contamination criteria at 64 POTWs.
EPA estimated that an additional 1,378 POTWs would meet
all Land Application-High limits as a result of the regulatory
Options 2/6/10 or 4/8. The proposed regulation would cause
an estimated 1.7 million additional DMT of annual disposal
of sewage sludge to qualify for beneficial use under the
Land Application-High limits (see Tables E. 11 and E. 12).
E-36
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
GLOSSARY
action levels: the existence of a contaminant
concentration in the environment high enough to warrant
implementation of drinking water treatment technology.
acute toxicity (AT): the ability of a substance to cause
severe biological harm or death soon after a single exposure
or dose. Also, any poisonous effect resulting from a single
short-term exposure to a toxic substance. (See also: chronic
toxicity, toxicity.)
(http://www.epa.gov/OCEPAterms/aterms.html)
adsorption: removal of a pollutant from air or water by
collecting the pollutant on the surface of a solid material; an
advanced method of treating waste in which activated
carbon removes organic matter from wastewater.
(http://www.epa.gov/OCEPAterms/aterms.html)
adsorption coefficient (Koc): represents the ratio of the
target chemical absorbed per unit weight of organic carbon
in the soil or sediment to the concentration of that same
chemical in solution at equilibrium.
alkalinity: the capacity of bases to neutralize acids (e.g.,
adding lime to lakes to decrease acidity).
(http://www.epa.gov/OCEPAterms/aterms.html)
ambient water quality criteria (AWQC): Levels of
water quality expected to render a body of water suitable for
its designated use. Criteria are based on specific levels of
pollutants that would make the water harmful if used for
drinking, swimming, farming, fish production, or industrial
processes. (http://www.epa.gov/OCEPAterms/aterms.html)
atm/m3-mole: atmosphere per cubic meter mole (see also
mole).
benthic: relating to the bottom of a body of water; living
on, or near, the bottom of a waterbody.
(http://www.ucmp.berkeley.edu/glossary/gloss5ecol.html)
bioconcentration factor (BCF): indicator of the
potential for a chemical dissolved in the water column to be
taken up by aquatic biota across external surface
membranes, usually gills.
BIODEG: a web-based biodegradation database developed
by Syracuse Research Corporation
(http://esc.sy rres.com/efdb/biodgsum.htm).
biodegradation: a process whereby organic molecules
are broken down by microbial metabolism.
biodegradation half-life: represents the number of days
a compound takes to be degraded to half of its starting
concentration under prescribed laboratory conditions.
biological oxygen demand (BOD): the amount of
dissolved oxygen consumed by microorganisms as they
decompose organic material in an aquatic environment.
cancer potency slope factors (SFs): a plausible
upper-bound estimate of the probability of a response per
unit intake of a chemical over a lifetime. The slope factor is
used to estimate an upper-bound probability of an individual
developing cancer as a result of a lifetime of exposure to a
particular level of a potential carcinogen.
carcinogens: chemicals that EPA believes can cause or
have the potential to cause tumors or cancers in humans,
either directly or indirectly.
CHEMFATE: a web-based chemical fate database
developed by Syracuse Research Corporation
(http://esc.syrres.com/efdb/Chemfate.htm).
chronic toxicity (CT): the capacity of a substance to
cause long-term toxic or poisonous health effects in humans,
animals, fish, and other organisms (see also: acute toxicity).
(http://www.epa.gov/OCEPAterms/cterms.html)
critical dilution factors (CDFs): express the
relationship between a point source loading and the resulting
concentration at the edge of the mixing zone. Typically, this
is expressed as a ratio of parts receiving water to one part
effluent.
dissolved concentration potentials (DCPs):
represents the concentration of a nonreactive dissolved
substance under well-mixed, steady-state conditions given
an annual load of 10,000 tons.
dry metric tons (DMT): dry measure is a system of units
for measuring dry commodities. 1 DMT= 1,000 kilogram.
EC1: the concentration at which one percent of the test
organisms show a significant sublethal response.
ECS: the concentration at which five percent of the test
organisms show a significant sublethal response.
Environmental Research Laboratory-Duluth
fathead minnow database: a data base developed by
EPA's Mid-Continent Ecology Division (MED) which
provides data on the acute toxicity of hundreds of industrial
organic compounds to the fathead minnow
(http://www.eoa.gov/med/databases/fathead_minnow.html)
GAGE: a U.S. Geological Survey streamflow database.
The database contains stream flow data and drainage area
measurement from all U.S. Geological Survey flow gages.
E-37
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
hazardous air pollutant (HAP): air pollutants that are
not covered by ambient air quality standards but which, as
defined in the Clean Air Act, may present a threat of adverse
human health effects or adverse environmental effects (e.g.,
beryllium, mercury, ethylbenzene, chloroethane, and
doxane). (http://www.epa.gov/OCEPAterms/hterms.html)
Health Effects Assessment Summary Tables
(HEAST): a comprehensive listing of provisional human
health risk assessment data relative to oral and inhalation
routes for chemicals of interest to EPA. Unlike data in IRIS,
HEAST entries have received insufficient review to be
recognized as high quality, Agency-wide consensus
information (U.S. EPA. 1997. Health Effects Assessment
Table; FY 1997 Update. EPA-540-R-97-036).
Henry's Law (H): chemical law stating that the amount of
a gas that dissolves in a liquid is proportional to the partial
pressure of the gas over the liquid, provided no chemical
reaction takes place between the liquid and the gas. The law
is named after William Henry (1774-1836), the English
chemist who first reported the relationship.
(www.infoplease.com)
human health-based water quality criteria (WQC):
levels of water quality expected to render a body of water
suitable for its designated use. Criteria are based on specific
levels of pollutants that would make the water harmful if
used for drinking, swimming, farming, fish production, or
industrial processes.
(http://www.epa.gov/OCEPAterms/wterms.html)
Integrated Risk Information System (IRIS): IRIS is
an electronic data base with information on human health
effects of various chemicals. IRIS provides consistent
information on chemical substances for use in risk
assessments, decision-making, and regulatory activities.
LC50 (Lethal Concentration): a standard measure of
toxicity that tells how much of a substance is needed to kill
half of a group of experimental organisms in a given time
(see: LD 50).
(http://www.epa.gov/OCEPAterms/lterms.html)
LD50 (Lethal Dose): the dose of a toxicant or microbe
that will kill 50 percent of the test organisms within a
designated period. The lower the LD 50, the more toxic the
compound.
I/kg: liter per kilogram
Lowest Observed Effect Concentration (LOEC): the
lowest level of pollutant concentration that causes
statistically and biologically significant differences in test
samples as compared to other samples subjected to no
stressor. (http://www.epa.gov/OCEPAterms)
Maximum Allowable Toxicant Concentration:
(MATC): for a given ecological effects test, the range (or
geometric mean) between the No Observable Adverse Effect
Level and the Lowest Observable Adverse Effects Level.
(http://www.epa.gov/OCEPAterms/mterms.html)
maximum contaminant levels (MCLs): the maximum
permissible level of a contaminant in water delivered to any
user of a public system. MCLs are enforceable standards.
(http://www.epa.gov/OCEPAterms/mterms.html)
mg/kg: milligram per kilogram
ug/l: microgram per liter
mole: the amount of substance that contains Avogardo's
number of atoms, molecules or other elementary units.
National Estuarine Inventory (NEI): The National
Estuarine Inventory is a series of inter-related activities that
define, characterize, and assess the Nation's estuarine
systems. NEI data are compiled in a systematic and
consistent manner that enables the Nation's estuaries to be
compared and assessed according to their environmental
quality, economic values, and resource uses. A principal
feature of the NEI is the determination of the physical
dimensions and hydrologic features of estuarine systems of
the United States which are primary determinants of
estuarine processes and ultimately affect the ecology of a
system.
National Oceanic and Atmospheric Administration
(NOAA): Organization within the Bureau of Commerce
that conducts research and gathers data about the global
oceans, atmosphere, space, and sun.
Wo Observed Effect Concentration (NOEC):
Exposure level at which there are no statistically or
biologically significant differences in the frequency or
severity of any effect in the exposed or control populations.
(http://www.epa.gov/OCEPAterms/nterms.html)
oil and grease (O&G): organic substances that may
include hydrocarbons, fats, oils, waxes, and high-molecular
fatty acids. Oil and grease may produce sludge solids that
are difficult to process.
(http://www.epa.gov/owmitnet/reg.htm)
organic carbon (OC): carbon in compounds derived
from living organisms.
partition factor: a chemical-specific value representing
the fraction of the load expected to partition to sewage
sludge during wastewater treatment.
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
Permit Compliance System (PCS): a computerized
database of information on water discharge permits,
designed to support the National Pollutant Discharge
Elimination System (NPDES).
(http://www.epa.gov/ceiswebl/ceishome/ceisdocs/pcs/pcs-e
xec.htm)
pH: an expression of the intensity of the basic or acid
condition of a liquid; Natural waters usually have a pH
between 6.5 and 8.5.
(http://www.epa.gov/OCEPAterms/pterms.html)
pollutants of concern (POCs): are the 150
contaminants identified by EPA as being of potential
concern for this rule and which are currently being
discharged by MP&M facilities.
Premanufacture Notices (PMN): a notice, required by
Section 5 of TSCA, that must be submitted to EPA by
anyone who plans to manufacture or import a new chemical
substance for a non-exempt commercial distribution. The
notice must be submitted at least 90 days prior to the
manufacture or import of the chemical.
(http://www.epa.gov/oppt/newchems/index.htm)
priority pollutant (PP): 126 individual chemicals that
EPA routinely analyzes when assessing contaminated
surface water, sediment, groundwater, or soil samples.
These chemicals are also known as toxic pollutants.
quantitative structure-activity relationship (QSAR):
an expert system that uses a large database of measured
physicochemical properties, such as melting point, vapor
pressure, and water solubility, to estimate the fate and effect
of a specific chemical based on its molecular structure
(http://www.epa.gov/med/databases/aster.html)
reference doses (RfDs): RfDs represent chemical
concentrations - expressed in mg of pollutant/kg body
weight/day - which, if not exceeded, are expected to protect
an exposed population, including sensitive groups such as
young children or pregnant women.
Secondary Maximum Contaminant Levels
(SMCLs): non-enforceable water treatment levels applying
to public water systems and specifying the maximum
contamination levels that, in the judgment of EPA, are
required to protect the public welfare. These treatment levels
apply to any contaminants that may adversely affect the odor
or ap- pearance of such water and consequently may cause
people served by the system to discontinue its use.
suspended solids: small particles of solid pollutants that
float on the surface of, or are suspended in, sew- age or
other liquids. They resist removal by conventional means.
Superfund Chemical Data Matrix (SCDM): a source
for factor values and benchmark values applied when
evaluating potential National Priorities List (NPL) sites
using the Hazard Ranking System (HRS).
(http ://www. epa. gov/superfund/resources/scdm/index. htm).
systemic toxicants: chemicals that EPA believes can
cause significant non-carcinogenic health effects when
present in the human body above chemical-specific toxicity
thresholds.
total Kjeldahl nitrogen (TKN): TKN is defined as the
total of organic and ammonia nitrate. It is determined in the
same manner as organic nitrogen, except that the ammonia is
not driven off before the digestion step.
total organic carbon (TOC): a measure of the
suspended solids in wastewater, effluent, or waterbodies,
determined by tests for "total suspended non-filterable
solids" (see also: suspended solids).
total petroleum hydrocarbons (TPH): a general
measure of the amount of crude oil or petroleum product
present in an environmental media (e.g., soil, water, or
sediments). While it provides a measure of the overall
concentration of petroleum hydrocarbons present, TPH does
not distinguish between different types of petroleum
hydrocarbons.
total suspended particles (TSP): A method of
monitoring airborne paniculate matter by total weight.
(http://www.epa.gov/OCEPAterms/tterms.html)
total suspended solids (TSS): a measure of the
suspended solids in wastewater, effluent, or waterbodies,
determined by tests for "total suspended non-filterable
solids" (see also: suspended solids).
United States Geological Survey (USGS): a
governmental organization that provides reliable scientific
information to: describe and understand the Earth; minimize
loss of life and property from natural disasters; manage
water, biological, energy, and mineral resources; and
enhance and protect our quality of life, (www.noaa.gov)
volatilization: a process whereby chemicals dissolved in
water escape into the air.
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MP&M EEBA: Appendices
Appendix E: Environmental Assessment
ACRONYMS
AQUIRE: AQUatic Information REtrieval System
ASTER: Assessment Tools for the Evaluation of Risk
AT: acute toxicity
AWQC: ambient water quality criteria
BCF: bioconcentration factor
BOD: biological oxygen demand
CDF: critical dilution factor
CT: chronic toxicity
DCP: dissolved concentration potential
DMT: dry metric tons
hh Henry's Law
HAP: hazardous air pollutant
HEAST: Health Effects Assessment Summary Tables
IRIS: Integrated Risk Information System
Kocl adsorption coefficient
LOEC: Lowest Observed Effect Concentration
MATC: Maximum Allowable Toxicant Concentration
MCL: maximum contaminant level
NEI: National Estuarine Inventory
NOAA: National Oceanic and Atmospheric Administration
NOEC: No Observed Effect Concentration
O&G: oil and grease
OC: organic carbon
PCS: Permit Compliance System
PMN: Premanufacture Notices
POC: pollutant of concern
PP: priority pollutant
QSAR: quantitative structure-activity relationship
RBC: EPA's Region III Risk-Based Concentration Table
RfD: reference dose
SCDM: Superfund Chemical Data Matrix
SF: cancer potency slope factor
SMCL: Secondary Maximum Contaminant Level
TKN: total Kjeldahl nitrogen
TOC: total organic carbon
TPH: total petroleum hydrocarbons
TSP: total suspended particulates
TSS: total suspended solids
USGS: United States Geological Survey
WQC: water quality criteria
E-40
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MP&M EEBA: Appendices Appendix E: Environmental Assessment
REFERENCES
Arthur D. Little. 1983. Evaluation ofwaterborne exposure pathways to paragraph 4 (c) pollutants. Draft Report, April 28.
Also: Paragraph 4(c) list of detected chemicals.
Arthur D. Little. 1986. Bio accumulation Study.
Birge, WJ. et al. 1979. Aquatic toxicity tests on inorganic elements occurring in oil shale. Oil Shale Symposium -
Sampling, Analysis and Quality Assurance, March. EPA-600/9-80-022.
Clay, D.R. 1986. Office of Toxic Substances, U.S. Environmental Protection Agency. Memorandum to J.M. Cordon,
OWRS, U.S. Environmental Protection Agency.
Holdway, D.A. and J.B. Spraque. 1979. "Chronic toxicity of vanadium to flagfish." Water Research 13:905-910.
Howard, P.H., Ed. 1991. Handbook of Environmental Degradation Rates. Chelsea. MI: Lewis Publishers, Inc.
ICF, Inc. 1985. Superfund Public Health Evaluation Manual - Draft.
Leblanc, G.A. 1980. "Acute toxicity of priority pollutants to water flea" (Daphnia magna). Bull Environmental
Contamination Toxicology 24:684-691.
Lyman, W.J.; W.F. Reehl, and D.H. Rosenblatt. 1981. Handbook of Chemical Property Estimation Methods -
Environmental Behavior of Organic Compounds. New York, NY: McGraw-Hill Book Company. 960 pp. (reported or
estimated using methods outlined).
Syracuse Research Corporation. 1997. CHEMFATE Datafile within the Environmental Fate Database. Syracuse, NY:
Syracuse Research Corporation.
U.S. Atomic Energy Commission. 1973. Toxicity of power plant chemicals to aquatic life. Washington, DC: U.S. Atomic
Energy Commission.
U.S. Environmental Protection Agency (U.S. EPA). 1972. "Blue Book", NAS-NAE (Water Quality Criteria -1972).
Washington, DC: U.S. EPA. EPA-R3-73-033. If the code @AA is provided with this reference, the value is an estimate
based on application factors described in the "Blue Book."
U.S. Environmental Protection Agency (U.S. EPA). 1976. "Red Book" (Quality Criteria For Water). Washington, DC: US
Environmental Protection Agency.
U.S. Environmental Protection Agency (U.S. EPA). 1980. Ambient water quality criteria documents. Washington, DC:
Office of Water, U.S. EPA. EPA 440/5-80 Series. Also refers to any update of criteria documents (EPA 440/5-85 and EPA
440/5-87 Series) or any Federal Register notices of proposed criteria or criteria corrections. The most recent National
Recommended Water Quality Criteria used in this report were published in the Federal Register on December 10, 1998.
U.S. Environmental Protection Agency (U.S. EPA). 1984. Summary of current oral Acceptable Daily Intakes (ADIs)for
systemic toxicants. Cincinnati, Ohio: Environmental Criteria and Assessment Office, U.S. EPA, May. 19pp.
U.S. Environmental Protection Agency (U.S. EPA). 1985. Report to Congress on the Discharge of Hazardous Wastes to
Publicly-owned Treatment Works (Domestic Sewage Study). Office of Water Regulations and Standards. Washington, DC:
U.S. EPA.
U.S. Environmental Protection Agency (U.S. EPA). 1987. Guidance Manual for Preventing Interference at POTWs.
Washington, DC: U.S. EPA
U.S. Environmental Protection Agency (U.S. EPA). 1990. CERCLA Site Discharges to POTWs: Guidance Manual.
Washington, DC: Office of Emergency and Remedial Response EPA/540/G-90/005.
E-41
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MP&M EEBA: Appendices Appendix E: Environmental Assessment
U.S. Environmental Protection Agency (U.S. EPA). 1997. Health Effects Assessment Summary Tables (HEAST). Office
of Research and Development and Office of Emergency and Remedial Response, Washington, DC: U.S. EPA.
U.S. Environmental Protection Agency (U.S. EPA). 1998. Risk-Based Concentration Table, October. Philadelphia, PA:
Region III, U.S. Environmental Protection Agency.
U.S. Environmental Protection Agency (U.S. EPA). 1998/99. QSAR. Duluth, MN: Environmental Research Laboratory,
U.S. Environmental Protection Agency.
U.S. Environmental Protection Agency (U.S. EPA). 1998/99a. Aquatic Toxicity Information Retrieval (AQUIRE) Data
Base. Duluth, MN: Environmental Research Laboratory, U.S. Environmental Protection Agency. 1998 Database retrieval.
U.S. Environmental Protection Agency (U.S. EPA). 1998/99b. Assessment Tolls for Evaluation of Risk (ASTER) Data
Base. Duluth, MN: Environmental Research Laboratory, U.S. Environmental Protection Agency. 1998 Database retrieval.
U.S. Environmental Protection Agency (U.S. EPA). 1998/99c. Integrated Risk Information System (IRIS) Retrieval.
Washington, DC: U.S. EPA. 1998 Data Base retrieval.
U.S. Environmental Protection Agency (U.S. EPA). 2000. Development Document for the Proposed Effluent Limitations
Guidelines and Standards for the Metal Products and machinery Point Source Category. Washington, DC: U.S. EPA.
Versar. 1992. Upgrade of Flow Statistics Used to Estimate Surface Water Chemical Concentrations for Aquatic and
Human Exposure Assessment. Prepared for the Office of Pollution Prevention and Toxics, U.S. EPA.
Versar. 1994. Development of Mixing Zone Dilution Factors. Preliminary Draft, Progress Report. Prepared for U.S. EPA,
Office of Pollution Prevention and Toxics, Economics, Exposure, and Technology Division. October 27. EPA Contract No.
68-D3-0013.
Worthing, C.R. 1987. The Pesticide Manual - a world compendium, Eighth Edition. Surry, UK: The British Crop Protection
Council. ISBN 0-948404-42-6.
Zhang, R. and Zhang, S. 1982. "Toxicity of fluorides to fishes." C.A. Selects - Environm Pollut 24,97:176354k.
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MP&M EEBA: Appendices
Appendix F: Differential Sample Weighting Technique
Appendix F: Differential Sample
Vv eighting Technique
INTRODUCTION
EPA used two methods in the benefit analysis to extrapolate
sample facility results to the national level.
- a standard linear weighting technique, and
- a differential sample weighting technique.
The choice of the weighting method depends on the
additivity of the effects being considered. In some cases,
effects are additive across facilities regardless of their
location relative to each other. In other cases, effects
depend on how many facilities discharge to the same
waterbody. The choice of sample weight used differs for the
two situations.
The standard linear weighting technique is used where the
effects being considered (e.g., compliance costs) are linearly
additive over facilities. EPA used this extrapolation method
in the economic impact analysis to calculate national
compliance costs, and in the cost-effectiveness and benefit
analyses to estimate changes in pollutant loadings. This
approach was also used in the benefits analysis to calculate
changes in cancer risk, because pollutant exposures have
marginal effects on cancer risk. These marginal effects are
linearly additive over the facilities, chemicals, and human
populations affected by changes in MP&M pollutant
discharges.
EPA used a differential sample weighting technique for all
threshold value-based analyses, such as the lead-related
benefits analysis. Threshold based analyses include
comparisons of the estimated baseline and post-compliance
POTW influent flow concentrations, sludge concentrations,
or in-waterway concentrations with the relevant threshold
values.
The differential weighting technique is identical to the
standard linear weighting method for POTWs or reaches to
which only one MP&M sample facility discharges. If a
POTW or reach receives discharges from only one sample
facility, the number of POTWs or reaches expected to
benefit in a similar fashion at the national level is simply the
sample weight of the single facility discharging to the
POTW or reach. Approximately 22.6 percent of the reaches
APPENDIX CONTENTS:
F. 1 Methodology for Developing Sample-Weighted
Estimates for Sites with more than One
MP&M Facility F-l
Glossary F-8
that have a MP&M sample facility and 18.4 percent of
POTWs that have a sample MP&M facility receive
discharges from more than one sample facility. EPA used a
different method for developing national estimates of
benefits to account for the presence of more than one facility
with different sample weights discharging to POTWs or
reaches affected by multiple MP&M dischargers. This
appendix describes this method for extrapolating sample
results to the national level.
F.I METHODOLOGY FOR DEVELOPING
SAMPLE-WEIGHTED ESTIMATES FOR
SITES WITH MORE THAN ONE MP&M
FACILITY
The MP&M analysis is based on a random stratified sample
of MP&M facilities, while the unit of environmental
assessment and analyses is a reach. It is possible to use
facility sample weights to estimate the number of similar
facilities on similar reaches nationwide with some
adjustments. These facility sample weights are designed to
provide facility characteristics. They are not reach-specific
sample weights designed to estimate reach characteristics,
however, and therefore cannot be used directly to estimate
the national occurrence of reaches associated with a specific
characteristic of MP&M discharges. For example, the sum
of MP&M sample facility weights discharging to one reach
is an accurate estimate of the number of national facilities
similar to the sample facilities, but is not a valid national
estimate of the number of reaches identically similar to that
reach.
It is not valid to assume that the co-location of sample
facilities is similar to the co-location characteristics of all
F-l
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MP&M EEBA: Appendices
Appendix F: Differential Sample Weighting Technique
MP&M facilities. This point is illustrated by the case in
which two sample facilities with different weights discharge
to the same reach. Assume that one of these two sample
facilities has a sample weight of 5 and the other has a
sample weight of 200. The sample weights indicate that
there are four additional facilities in the US that are
economically and technically similar to the facility with the
weight of five. It is also correct to estimate that the other
four facilities will discharge the same volume of the same
pollutants as the other four facilities. Now let us assume
that there are 199 other facilities nationwide similar to the
facility with the weight of 200. The more numerous
facilities represented by the facility with a weight of 200
could only rarely be co-located with one of the four facilities
represented by the sample facility with a weight of 5.
EPA developed a method that takes into consideration the
joint occurrence of facilities with different statistical weights
on reaches to estimate the number of reaches affected by
MP&M facilities nationwide. EPA created a series of new
discharge variables (a discharge event) for each reach
affected by MP&M sample facilities, and assigned weights
for the discharge events that provide a national estimate of
pollutant discharges across all reaches. The sample
discharge events (flows and pollutant loadings) are
calculated based on the sum of the flows and pollutant
loadings for subsets of the MP&M sample facilities that
discharge to that reach. The weights for the discharge
events are developed from the facility weights for those
subsets of facilities. The calculation includes direct MP&M
facility discharges and indirect discharges from POTWs
after considering pollutant removals from POTW treatment.
The number of discharge events on a sample reach equals
the number of unique sample weights for the facilities on the
reach. EPA calculated a sample weight for each discharge
event based on the sample weights of the facilities
contributing loadings and flows to the event. Table F-l
illustrates discharge event calculations and corresponding
sample weights. Steps for calculating the relevant
parameters for discharge events on reaches affected by
multiple discharges are as follows:
* Rank pollutant loadings (or discharge flows) in
ascending order of facility sample weight for each
pollutant of concern discharged by one or more of
those facilities.
> Generate the first discharge event loadings (or
flows) as the total loadings (or flows) from all
sample facilities on the reach. Assign the smallest
sample weight to the first discharge event (Wtj in
Table F-l) among the facilities discharging to the
reach. A smaller sample weight relative to the
others means that this facility represents no other
population facilities that could occur jointly with
the other facilities. The weight of the first facility
is therefore considered as "used up," and that
facility's loadings (or flows) are not included in
subsequent discharge events defined for the reach.
Generate subsequent discharge events by removing
the loadings (or flows) of facilities with the
smallest sample weight from a running sum of
loadings (or flows) of all facilities in the ranking.
The weight assigned to each subsequent event is
the remaining unused weight of the facility with the
smallest weight among the facilities remaining in
the particular discharge event. Calculate this
weight as the difference between the weight of the
next facility in the ranking and the weight of the
previous facility
EPA avoids double-counting indirect dischargers by
including the discharge flow of any given POTW into a
reach only once in any given discharge event, even when
multiple sample facilities discharge indirectly into one
POTW.
This methodology generates a set of discharge events
(loadings or flows) for each pollutant discharged to the
reach. The following steps illustrate application of the
differential weighting technique to estimating the national
number of reaches on which ambient water quality
criteria (AWQC) are exceeded:
* Assign a weight to each discharge event based on
the weights of the facilities discharging to the
reach;
> Combine the effluent flow with the stream flow of
the reach;
> Divide the pollutant loading into the stream flow to
determine the pollutant concentration caused by the
event;
> Compare pollutant concentration to AWQC values
to determine whether the concentration exceeds
those values;
> Identify an estimated AWQC "exceedence" if the
concentration is greater than a criterion; and
> Give the AWQC exceedence event the weight of
the discharge event, to establish national estimates
of the number of reaches on which an AWQC is
exceeded.
F-2
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MP&M EEBA: Appendices
Appendix F: Differential Sample Weighting Technique
Table F.I: Construction of Discharge Events for Any Pollutant Discharged to Any Reach
Event Number
One
Two
N-2
N-l
N
Loadings and Flows Assigned to
Event
N
2^ Loadi or Flowi
i = l
N-l
\ Loadi or Flowt
i=2
LoadN_2 + LoadN_! + LoadN
FlowN_2 + FlowN_! + FlowN
LoadN_! + LoadN
FlowN_! + FlowN
LoadN+FlowN
Weight Assigned to Event
Wt;
Wt2 - Wt;
WtN.2-WtN.3
Wt^-Wt^
WtN-WtN.,
Notes: N sample facilities discharge to the reach and are ranked in ascending order of sample weight and indexed by i (1 = facility with
smallest weight, N = facility with largest weight); Load; = Loading from facility i; Flow; = Flow from facility i or the POTW associated with
facility i; Wt; = Sample weight of facility i; and A POTW's flow is included only once per event, even if multiple facilities in that event
discharged through that POTW, to avoid over-counting the POTW's flow.
Source: U.S. EPA analysis.
This weighting method is a relatively simplistic approach to
a complex analytic issue, and does not provide a precise
estimate of the national distribution of in-stream MP&M
pollutant concentrations that reflects the true co-location
characteristics of MP&M facilities. A statistically-valid
estimate of that distribution is not possible given the design
of the Section 308 surveys. However, the differential
weighting technique does correct for the significant
overstatement of benefits that would result from using a
simple weighting approach to estimate national reach
characteristics. The Agency believes that this method is a
reasonable approach to addressing this issue, given time and
resource constraints. Approaches that are both more
sophisticated and more expensive might not yield
significantly different aggregate findings.
Figure F.I provides a graphic example of a hypothetical
reach to which three known sample facilities discharge.
Table F.2 provides a numeric example of this calculation for
a hypothetical reach to which three known sample facilities
discharge.
F-3
-------
MP&M EEBA: Appendices
Appendix F: Differential Sample Weighting Technique
Figure F.la: Estimating MP&M Pollutant Loadings to Receiving Streams When Using a Random Sample of MP&M
Facilities
Problem: Lack oflnformation on the Occurrence of Joint Discharges
Geographic Discharge Location of Non-Sample Facilities is Unknown
Result: Underestimation of Baseline MP&M Discharges and MP&M Contribution to Problem
Solution: None Known at this Time
MP&M sample facilities
Sample Weight j=l
Produces Chemical X
Produces Chemical Y
MP&M non-sample facilities
Sample W eight 1 =S am pie W eight2 = Sample W eights = 1
If Only Sample Facility Discharges Are Considered:
Facility 1,
Chemical X
Facility 1,
C h em ical Y
In-stream concentration (X) = 30 g/1,
which is greater than AWQC(X) = 20 g/1 .
Number of Exceedence Events = 5
In-stream concentration (Y) = 40 g/1,
which is less than AWQC(Y)= 50 g/1.
Number of Exceedence Events = 0
If All MP&M Discharges Are Considered (Chemical V)
2,3,4
In-stream concentrations (Y) = 70 g/1,
which is greater than AWQC(Y) = 50 g/1.
Number of Actual Exceedence Events =1
Number of Estimated Exceedence Events =0
Underestimation of Events =1
Source: U.S. EPA analysis.
F-4
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MP&M EEBA: Appendices
Appendix F: Differential Sample Weighting Technique
Figure F.lb: Estimating MP&M Pollutant Loadings to Receiving Streams When Using a Random Sample of MP&M
Facilities
Problem :
So lution:
Facilities W ith Different W eights Located on the Same Reaches
Use of DifferentialWeighting Method
For this illustration, assume that concentrations are different at each discharge point, but facility
and stream flow are the same.
MP&M sample facilities
Sample Weight [ =10, discharge 40 g/1
Sample Weight 2 = 6, discharge 20 g/1
Sample W eight 3 = 2, discharge 1 0 g/1
Flow! = Flow2 = Flow3 = 1000 L/day
Flow,tr,,m = 1 10ฐ L/day
MP&M non-sample facility
Differential Weighting Method
1 + 2
In-stream concentration = 70 g/1 > AWQCX = 50 g/1
"Number of Benefit Events = min{SWl SW2,SW3} =
In-stream concentrations = 60g/l > AWQCX=50 g/1
'Number of Benefit Events = minjSW 1, SW2}=4
In-stream concentrations = 40g/l > AWQCX=50 g/1
'Number of Benefit Events =0
Total Number of Benefit Events = 6
Predicted Events = 6
Note: The situation may be further complicated by actually having a non-sampled MP&M facility on the same reach. The differential weighting method
does not address this issue.
Source: U.S. EPA analysis.
F-5
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MP&M EEBA: Appendices
Appendix F: Differential Sample Weighting Technique
Figure F.lc: Estimating MP&M Pollutant Loadings to Receiving Streams When Excluding Background
Concentrations
Problem 3: Omitting Discharges from Non-MP&M Facilities
Results: Uncertainty, May Underestimate or Overestimate Benefits
MP&M samp le facilities
Sample W eight j=l 5
Non-MP&M facilities
Case I: Underestimation of Benefits When all Discharges are Considered
If Only Sample Facility Discharges Are Considered:
Baseline
Post
C o m p liance
In-stream concentration (X) = 30 g/1 AWQC(X) = 40 g/1
Number of Exceedence Events =15
In-stream concentrations (X) = 35 g/1 AWQC(X) = 20 g/1
Number of Baseline Exceedence Events = 15.
In-stream concentration (X) = 15 g/KAWQC(X)= 20 g/1
..Number of Po stcomp lianc e Exceedence Events = 0
Number of Benefit Events =15
If N o n-M P & M Discharges Are Considered
Ba seline
Post
C o m p liance
1 + 2,3,4
1 + 2,3,4
In-stream concentrations (X) = 95g/l >AWQC(X) = 20 g/1
Number of Exceedence Events =15
In-stream concentrations (X) = 80 g/1 >AWQC(X) = 20 g/1
^.Number of Exceedence Events= 15
Number of Benefit Events = 0
Source: U.S. EPA analysis.
F-6
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MP&M EEBA: Appendices
Appendix F: Differential Sample Weighting Technique
^...W^isMiiia.X^.linifly?..
Pollutant Aj
Ibs/vri
Facility
Weight
Flow
gal/year
Raw data:
10
5:
..2,000,000
4,000,000
1
12;
J-
19;
,...1.0,000,000
,...1.6,000,000
100,000,000
Total
14
.(gal/year):.
Calculating flow and pollutant loadingsfor the reach:m
1
12;
10,000,000
2;
4,000,000
1
10
5;
2,000,000
2...Galculate.flpw
!djscha.rge..eyen.t.l.with weight. =.1.
..Facility..
Pollutant A
.....Ibs/jr...
Flow!
. jฃ?JI/.y.?.?.r!... .... Remaining Weight
12
10,000,000- 0
4,000,000!
1
2,000,000:
Event.l 19 .1.6,000,000!
3. Eliminate the facility with the lowest weight and calculate flow and pollutant loadings for discharge event 2 with
4,000,000:
0
1
2,000,000:
Event 2 7 6,000,000!
4. Eliminate the facility with the next lowest weight and calculate and pollutant loadings for discharge event 3
1
2,000,000:
Event 3
2,000,000!
5. Estimate national in-stream concentrations based the flows, loadings, and weights for each discharge event and
the reach flow
Discharge
Event
Pollutant A
Loading
....l.b.s/yr....
Facility!
Flowj
gal/year:
Stream i
Flowj
&al/year[
Total i
Flow!
In-stream
Concentration
....PP.b.
.Weight.
...!....
2
19
7
.16,000,0001..
._.6,ppp,ggg!..
2,000,000!
_igg,ggg,ggg;
_igg,ggg,ggg;
100,000,000;
.116,000,000^
.1Q6,000,000[.
102,000,000;
..0.0955.
..0.0385.
0.0286
...7...
10
Total Affected
Reaches:
Source: U.S. EPA analysis.
F-7
-------
MP&M EEBA: Appendices
Appendix F: Differential Sample Weighting Technique
GLOSSARY
ambient water quality criteria (AWQC): levels of
water quality expected to render a body of water suitable for
its designated use. Criteria are based on specific levels of
pollutants that would make the water harmful if used for
drinking, swimming, farming, fish production, or industrial
processes. (http://www.epa.gov/OCEPAterms/aterms.html)
differential sample weighting technique: weighting method
for all threshold value-based analyses, such as the lead-
related benefits analysis.
standard linear weighting technique: weighting
method used where the effects being considered (e.g.,
compliance costs) are linearly additive over facilities.
reach: a specific length of river, lake, or marine shoreline
-------
MP&M EEBA: Appendices
Appendix &' Fate and Transport Mode for DW and Ohio
Appendix &'. rate and I ransport
Model for DW and Ohio Analyses
INTRODUCTION
EPA used a simplified fate and transport model to
quantify the fate and transport of MP&M pollutant
releases to surface waters in the drinking water and Ohio
analyses. This model estimates pollutant concentrations
at the initial point of discharge and below the initial
discharge reach.
The national MP&M analysis considered pollutant
concentrations only at the point of discharge (see
Appendix E.2.2). The drinking water and Ohio analyses
account for the in-stream concentrations of pollutants at
the initial point of discharge and in reaches downstream
from the initial discharge reach.
This appendix describes the equations characterizing the
model, its underlying assumptions, and the data sources
used in model estimation. EPA combined the equations
defining the model with geographic information (reach
flow, velocity, length, etc.) to estimate pollutant
concentrations at the initial point of discharge and below the
initial discharge reach.
The estimation of pollutant concentrations below the initial
discharge reach includes several factors that reduce the in-
stream pollutant concentrations with the passage of time.
These factors include: volatilization, sedimentation,
and chemical decay from hydrolysis and microbial
degradation. EPA adjusted concentrations for changes in
stream flow volume in downstream reaches. The discussion
below outlines the main assumptions of this analysis.
Although more advanced models are available that account
for time-variable flow, sediment transport, channel geometry
changes within a reach, and detailed simulation of all in-
stream processes, these models will not necessarily produce
more accurate results without sufficient data to support the
input parameters. Estimates of the input parameters required
by these models are subject to a high degree of uncertainty
when applied on a national scale, and gathering such data is
beyond the scope of this study.
EPA has previously applied the approach used in this
analysis. For example, the first-order contaminant
degradation relationship described below in Equation G. 1 is
APPEI^
G.I
G.2
G.2
G.2
G.2
G.3
G.4
G.5
G.5
G.5
Glossary
Acronyrr
j&ix CONTENTS:
Model Equations
Model Assumptions
1 Steady Flow Conditions Exist Within
the Stream or River Reach
2 Longitudinal Dispersion of the Pollutant Is
Negligible
3 Flow Geometry, Suspension of Solids, and
Reaction Rates Are Constant Within a River
Reach
Hydrologic Linkages
Associating Risk with Exposed Populations . . .
Data Sources
1 Pollutant Loading Data Used in the
Drinking Water Risk Analysis
2 Pollutant Loading Data Used in the
Ohio Case Study Analysis
is
G-l
G-3
G-3
G-3
G-3
G-3
G-3
G-4
G-4
G-4
G-6 1
currently being used by the Office of Pollution Prevention
and Toxics for exposure analysis in the ReachScan computer
program.
G. 1 MODEL EQUATIONS
The total pollution concentration in the water columns for
each reach included in the analysis is calculated by the
following equation expressed in generic terms of mass (M),
length (L), and time (T):
(G.I)
where:
CT
WT =
Q =
VT =
H =
total toxicant concentration in the water
column (M/L3),
mass input rate of toxicant (M/T),
river flow (L3/T),
overall net loss rate of chemical (L/T),
flow depth (L),
G-l
-------
MP&M EEBA: Appendices
Appendix &' Fate and Transport Mode for DW and Ohio
x = distance downstream from the point of release
(L), and
U = flow velocity (L/T).
In reaches where more than one facility is discharging, or
where pollutant loadings occur from upstream reaches, the
mass input rate (WT) represents a combined input rate from
all relevant industrial facilities affecting the reach. The
relevant industrial facilities in the drinking water risk
analysis are all MP&M sample facilities (see Chapter 13).
The relevant industrial facilities in the Ohio case study
analysis include:1
* all sample MP&M facilities,
* non-sample MP&M facilities, and
> non-MP&M facilities.
The overall net loss rate of chemical (VT) is given by:
VT- VTd + VTs = (kt + K/) * fd + vf (G.2)
vn = net loss of solids (L/T), and
fp = paniculate fraction of toxicant (unitless).
The dissolved and paniculate fractions of the pollutant,
fd, andfp , respectively, are estimated by:
1
+Kps
(G.3)
and
(G.4)
where:
VT = overall net loss rate of chemical (L/T),
VTd = dissolved chemical loss rate (L/T),
VTs = loss of chemical due to sediment interaction
(L/T),
k; = volatilization transfer coefficient (L/T),
Kd = dissolved chemical decay rate (hydrolysis and
microbial degradation) (1/T),
H = flow depth (L),
fd = dissolved fraction of toxicant (unitless),
where:
Kp = partition coefficient [L3/M], and
S = suspended solids [M/L3].
The dissolved concentration of metals and most other
pollutants in the water column is generally considered a
more accurate expression than the total concentrations of the
toxic or bioavailable fraction. For this reason, EPA
modified Equation (G. 1) to express the pollutant
concentrations in terms of dissolved concentration. The
dissolved fraction of a pollutant is estimated as:
(G.5)
Substituting equation (G.2) for CT results in the dissolved
pollutant concentration being expressed as:
1 See Chapter 22 for detail.
G-2
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MP&M EEBA: Appendices
Appendix &' Fate and Transport Mode for DW and Ohio
w
T x e
Q
/ \
(1 + K/f (1 + Kpsfi
1 +Kps
( x\
(u)
(G.6)
6.2 MODEL ASSUMPTIONS
The following three principal assumptions underlie Equation
G.5:
ฃ.2.3 Flow Geometry, Suspension of
Solids, and Reaction Rates Are Constant
Within a River Reach
6.2.1 Steady Flow Conditions Exist
Within the Stream or River Reach
EPA assumes the data that describe a river reach and that are
calculated for a reach to be constant for the full extent of the
reach.
This assumption is necessary due to this study's broad
geographical coverage. This assumption significantly
reduces the computational effort and input parameter
requirements and still produces a good first fate and
transport modeling of pollutants in surface waters.
The pollutant concentration is completely mixed, both
laterally (across the stream) and vertically (with depth)
within each reach. The approach involves a two-
dimensional model in which the concentration is uniform
over the entire cross-section of the stream reach but varies
with the distance of the reach. EPA assumed that the
contaminant completely mixes at the point of release. This
assumption will likely underestimate the concentration of a
contaminant release in areas where mixing is incomplete
(e.g., shore-hugging plume) and overestimate concentrations
in areas beyond the point showing incomplete mixing (e.g.,
in areas beyond a shore-hugging plume).
ฃ.2.2 Longitudinal Dispersion of the
Pollutant Is Negligible
6.3 Hy&Roi_oeic UNKASES
EPA modeled pollutant concentrations for a distance of 500
km downstream from the discharge point in the drinking
water risk analysis. In the Ohio case study analysis, EPA
used the lesser of 500 km or the distance to the Ohio border
from the initial discharge point to identify reaches
potentially affected by pollutant discharges from this
discharge point. The Agency obtained Information on the
hydrologic linkages between reaches from the REACH2 file
of EPA's Graphical Exposure Modeling System
(GEMS). The GAGE file in GEMS provided flow (mean
flow, 7Q10) and velocity (mean, low) data for each reach.
EPA used the process equations listed above to estimate
both the initial pollutant concentrations at the beginning of
each reach and the changes in concentrations as pollutants
traveled to the end of the reach. The concentration at the
end of each reach served as the value for the beginning of
the next reach.
The model does not account for mixing outside the plane of
discharge along the river reach, although it predicts variation
in pollutant concentrations over distance due to both
pollutant fate and decay and the differing hydrology of
downstream reaches. In natural streams, longitudinal
velocity gradients due to channel irregularities can cause
mixing, thereby decreasing the peak concentrations as the
contaminant moves downstream from the point of release.
Under steady-state situations, however, the longitudinal
dispersion of the pollutant is assumed to be negligible.
The solution of the dispersion equation approximates a first-
order decay function such as the one shown in Equations
G. 1 and G.5 under steady flow conditions and complete
lateral and vertical mixing.
&A ASSOCIATING RISK WITH EXPOSED
POPULATIONS
The number of individuals served by each drinking water
intake is an output of the fate and transport model described
in this Appendix. If a drinking water intake exists on the
initial reach or any downstream reach, then the model
calculates the in-stream pollutant concentration at that
intake. Data on the population served by the intake is saved
with the concentration for further analysis (see Chapter 13
for a discussion of the cancer risk assessment).
G-3
-------
MP&M EEBA: Appendices
Appendix &' Fate and Transport Mode for DW and Ohio
6.5 DATA SOURCES
Data sources used for the fate and transport model are
discussed briefly in the section below, by categories of
information.
ฃ.5.1 Pollutant Loading Data Used in
the Drinking Water Risk Analysis
EPA estimated annual pollutant loadings (kg/yr) for the
direct and indirect sample MP&M facilities analyzed under
the various regulatory options. The Agency first adjusted
pollutant loadings for indirect dischargers to reflect POTW
treatment, and then divided annual pollutant loadings by the
number of days in one year (365) to establish daily pollutant
loadings.
ฃ.5.2 Pollutant Loading Data Used in
the Ohio Case Study Analysis
EPA estimated pollutant discharges from both MP&M and
significant non-MP&M sources at the reaches included in
the Ohio case study analysis. Consumer perception and
valuation of enhanced water-based recreational
opportunities depend on the absolute level of pollutant
contamination at recreation sites, and on the change in
contamination from the baseline to the post-compliance
cases. For this reason, capturing the effect of concurrent
discharges from all MP&M and other pollutant sources is
particularly important for the recreational benefits analysis.
EPA used the Office of Water's BASINS software package
to identify all possible point source dischargers contributing
to ambient pollutant concentrations at a given reach.
BASINS is a GIS-based system that serves as a database
management system for water quality monitoring,
point-source pollutant discharge, and various geo-technical
data. Several sources provide information on point source
discharges to BASINS, including the Permit Compliance
System (PCS) and Toxic Release Inventory (TRI)
databases. Version 2.0 includes data reported through 1996.
Preprogrammed queries in BASINS generate information on
various point source discharge variables at either the state or
watershed level. BASINS data on point source dischargers
include:
* location information on major industrial
dischargers, including PCS facilities and facilities
reporting under TRI;
- SIC codes;
> flow volume; and
* discharge characteristics for up to 50 pollutants or
parameters for PCS facilities.
The following sections describe steps used to characterize
both MP&M and non-MP&M discharges in Ohio.
a. Characterize MP&M facility discharges
EPA used different approaches to assign discharge
characteristics to MP&M facilities in Ohio, based on the
level of information available for each facility. The Agency
divided all MP&M facilities into three groups, based on the
level of information provided by different sources:
ซ> Facilities covered by the detailed Phase 1 and 2
questionnaire (hereafter, sampled MP&M facilities)
The detailed surveys contain data on:
* discharge status;
* discharge volume;
* industrial processes used;
* pollution prevention activities;
* employment, revenue, and costs.
EPA engineers estimated loadings of 131 MP&M pollutants
using information on facilities' processes and pollution
prevention activities. All MP&M facilities in this group
therefore have extensive data on their location, size, and
discharge characteristics.
ซ> Facilities covered by the detailed Iron and Steel
questionnaire (hereafter sampled I&S facilities)
The detailed I&S survey contained data similar to the
detailed MP&M survey. EPA engineers used data on I&S
facilities' processes and pollution prevention activities to
estimate pollutant loadings from these facilities.
ซ> Facilities covered by the Phase 2 screener
questionnaire or that were covered by the Phase 1
mini-DCP (hereafter, MP&M screener facilities).
The screener surveys contain significantly fewer data on
MP&M facilities. The data collected from the screener
survey recipients include:
* facility location, which can be used to assign the
facilities to receiving waterways or receiving
POTWs;
- SIC codes;
* discharge status (i.e., whether the facility
discharges process wastewater and the approximate
amount);
G-4
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MP&M EEBA: Appendices
Appendix &' Fate and Transport Mode for DW and Ohio
* employment and revenue data;
> whether the facility is engaged in manufacturing,
maintenance or repairing activities; and
* data on MP&M unit operations (including type of
MP&M unit operations performed at the site, and
whether process wastewater is discharged as a
result of each operation).
The project engineers used these data to estimate pollutant
loadings for these facilities. Loading estimates for the
screener facilities, which are based on less comprehensive
information, involve greater uncertainty.
ซ> Facilities that respond to neither the screener nor
detailed questionnaires (hereafter referred to as
non-sampled MP&M facilities)
To address the problem of omitted discharge information on
non-sampled MP&M facilities, EPA used information from
the 1600 screener MP&M facilities and a random draw
approach to assign the relevant characteristics for
non-sampled MP&M facilities. Each screener facility
represents n non-sampled facilities, where n is determined
by the screener facility sample weight. All non-sampled
facilities are smaller indirect dischargers because all direct
MP&M facility dischargers and large indirect discharging
facilities in Ohio are covered by the long, short, or screener
questionnaire.
The exact location of non-sampled facilities is unknown.
All non-sampled facilities discharge to one of the Ohio's
POTWs because they are indirect dischargers. The Agency
assigned n facilities represented by each screener facility to
the receiving POTWs by drawing a random sample of n
POTWs from the universe of POTWs in Ohio.2 The Agency
assigned screener facility characteristics (i.e., pollutant
loadings) to all n facilities represented by the screener
facility.
EPA used a random draw procedure for all observations
from the screener survey that have a sample weight greater
than one.
b. Characterize non-MP&M point source
discharges
EPA used preprogrammed queries in BASINS to obtain
information on all non-MP&M point source discharges in
Ohio. BASINS data on non-MP&M point source
dischargers include:
2 The Agency was unable to validate random assignments
because POTWs do not know all of their MP&M dischargers. For
the final rule, the Agency will perform a sensitivity analysis based
on alternative draws to test the stability of the results.
> location,
- SIC codes,
* flow volume, and
> discharge characteristics for up to 50 pollutants or
parameters for PCS facilities.
The Agency assigned discharge characteristics to all non-
MP&M industrial direct discharges based on the information
provided in BASINS. POTW effluent may contain
pollutants from both MP&M and non-MP&M discharges.
The Agency combined information from BASINS with
loading estimates provided by the project engineers to
estimate total pollutant loadings from a given POTW. This
analysis used the following assumptions to estimate total
POTW pollutant loadings under the baseline discharge
levels:
* If a POTW was not estimated to receive discharges
from the MP&M facilities, then the analysis used
POTW loadings reported in BASINS.
* If a pollutant or a parameter was not reported in
BASINS, then the analysis used aggregate loadings
from all MP&M facilities discharging to a given
POTW to calculate total POTW loadings of a given
pollutant.
> If a POTW was estimated to receives discharges
from MP&M facilities and a given pollutant was
reported in BASINS, then the analysis used the
greater of the aggregate loadings from all MP&M
facilities or POTW loadings reported.
EPA estimated post-compliance pollutant loadings from
each POTW by subtracting the estimated reduction in the
MP&M facility loadings for a given pollutant from its total
baseline loadings for a given POTW.
c. Characterize nonpoint source discharges
The water quality analysis in Ohio used empirical data on
Total Kjeldahl Nitrogen (TKN) concentrations to
characterize the baseline water quality conditions. Empirical
data on in-stream concentrations captured TKN contribution
from both point and nonpoint sources under baseline
conditions. EPA estimated changes in TKN concentrations
resulting from the proposed rule by using the estimated
pollutant loading reductions from MP&M sources and the
water quality model described above. The Agency assumed
that the non-point source contribution of toxic pollutants
found in MP&M effluent to ambient concentrations of these
pollutants in Ohio's streams and lakes is negligible.
G-5
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MP&M EEBA: Appendices
Appendix &' Fate and Transport Mode for DW and Ohio
GLOSSARY
BASINS: a software package that serves as a database
management system for water quality monitoring, point-
source pollutant discharge, and various geo-technical data,
and also provides an analytic platform for modeling in-
stream pollutant concentrations over an entire watershed
based on multiple sources of pollutants withing the
watershed. (http://www.epa.gov.OST/BASINS)
Graphical Exposure Modeling System (GEMS): A
computer system designed for exposure modeling and
assessment.
hydrolysis: the decomposition of organic compounds by
interaction with water. (http://www.epa.gov/OCEPAterms)
metals: inorganic compounds, generally non-volatile, and
which cannot be broken down by biodegradation processes.
They are a particular concern because of their prevalence in
MP&M effluents. Metals can accumulate in biological
tissues, sequester into sewage sludge in POTWs, and
contaminate soils and sediments when released to the
environment. Some metals are quite toxic even when
present at relatively low levels.
microbial degradation: a process whereby organic
molecules are broken down by microbial metabolism.
Permit Compliance System (PCS): a computerized
database of information on water discharge permits,
designed to support the National Pollutant Discharge
Elimination System (NPDES).
(http://www.epa.gov/ceiswebl/ceishome/ceisdocs/pcs/pcs-e
xec.htm)
MP&M reach: a reach to which an MP&M facility
discharges.
sedimentation:: letting solids settle out of wastewaterby
gravity. (http://www.epa.gov/OCEPAterms)
Total Kjeldahl Nitrogen (TKN): the total of organic and
ammonia nitrogen. TKN is determined in the same manner
as organic nitrogen, except that the ammonia is not driven
off before the digestion step.
Toxic Release Inventory (TRI): database of toxic
releases in the United States compiled from SARA Title III
Section 313 reports. ( http://www.epa.gov/OCEPAterms)
volatilization: a process whereby chemicals dissolved in
water escape into the air.
(http://www.epa.gov/OCEPAterms)
G-6
-------
MP&M EEBA: Appendices Appendix &' Fate and Transport Mode for DW and Ohio
ACRONYMS
GEMS: Graphical Exposure Modeling System TKN: Total Kjeldahl Nitrogen
IFD: Industrial Facility Discharge TRI: Toxic Release Inventory
MMR: manufacturing, maintenance or repairing activities
PCS: Permit Compliance System
G-7
-------
MP&M EEBA: Appendices
Appendix H: Spacial Distribution of Benefiting Reaches, MP&M Facilities, and Benefiting Populations
Appendix H: Spacial Distribution of
Benefiting Reaches, MP&M
Facilities, and Benefiting Populations
INTRODUCTION
This appendix presents six maps showing a distribution, by
geographic location and population, of the sample discharge
reaches estimated to benefit from reduced MP&M
discharges. EPA used a U.S. Counties data layer developed
by the Environmental System Research Institute (ESRI) as a
base map. The Agency then used ESRI's Arc View 3.2 to
display the benefiting reaches and the sample MP&M
facilities data layers.
The Benefiting Reaches data layer depicts all reaches in
which at least one MP&M pollutant exceeding the AWQC
limits for human health or aquatic species fell below the
AWQC limit as a result of the proposed rule. EPA used the
Office of Water's BASINS software package to identify
locations of the sample benefiting reaches.
The Agency geocoded the sample MP&M facilities to
display their locations by county and population, in two
ways:
* by using latitude and longitude coordinates
gathered during Phase I; or
> in the absence of those coordinates, by matching
the reported ZIP code of the facility to the ZIP code
centroid data layer provided by ESRI.
ESRI provided information on the 1999 county population
estimates. EPA then estimated population categories for
each map using a least-squares process. The least-squares
process minimizes the differences within groups while
maximizing the differences between them. The Agency
applied this process to the population ranges of only those
counties found within the regions depicted on the map.
APPENDIX CONTENTS;
Figure H.I: Location of Benefiting Reaches in Relation
to Sample MP&M Facilities by County
and Population Reaches Benefiting
from MP&M Regulation
(EPA Regions I, II, and III) H-3
Figure H.2: Location of Benefiting Reaches in Relation
to Sample MP&M Facilities by County
and Population Reaches Benefiting
from MP&M Regulation
(EPA Region IV) H-4
Figure H. 3: Location of Benefiting Reaches in Relation
to Sample MP&M Facilities by County
and Population Reaches Benefiting
from MP&M Regulation
(EPA Region V and VII) H-5
Figure H.4: Location of Benefiting Reaches in Relation
to Sample MP&M Facilities by County
and Population Reaches Benefiting
from MP&M Regulation
(EPA Region VI) H-6
Figure H. 5: Location of Benefiting Reaches in Relation
to Sample MP&M Facilities by County
and Population Reaches Benefiting
from MP&M Regulation
(EPA Regions VIII and X) H-7
Figure H. 6: Location of Benefiting Reaches in Relation
to Sample MP&M Facilities by County
and Population Reaches Benefiting
from MP&M Regulation
(EPA Region IX) H-8
Table H.I: Distribution of MP&M Facilities and
Participants of Water Based Recreation
by State H-9
Figure H.7: Cumulative Distribution of Facilities
and Participants H-ll
This appendix also compares the national distribution of all
MP&M facilities by state and the national distribution of
recreational participants by state (see Table H. 1 and Figure
H.7). EPA based the distribution of MP&M facilities by
H-l
-------
MP&M EEBA: Appendices Appendix H: Spacial Distribution of Benefiting Reaches, MP&M Facilities, and Benefiting Populations
state on Census data on total numbers of facilities in the and by type of recreation activity on information provided
SICs that make up the MP&M industries, not just water by the National Demand Study data. This comparison
dischargers. This comparison assumes that the state suggests that the reaches that benefit from the proposed rule
distribution of water-discharging MP&M facilities is the are also those where a very large percentage of all
same as the overall distribution of MP&M facilities. EPA recreational participants reside and recreate.
based the distribution of recreational participants by state
H-2
-------
MP&M EEBA: Appendices
Appendix H: Spacial Distribution of Benefiting Reaches, MP&M Facilities, and Benefiting Populations
Figure H.I: Location of Benefiting Reaches in Relation to Sample MP&M Facilities by County and Population
Reaches Benefiting from MP&M Regulation (EPA Regions I, II, and III)
Location of Reaches
Benefiting from MP&M
Regulation
Benefitting Readies
MP&M Sample Facilities
Counties by Population
429 - 87,608
87,609 - 284,026
284,027 - 655,174
655,175- 2,111,966
2,111,967 - 5,192,105
EPA Regions
Source: U.S. EPA analysis.
H-3
-------
MP&M EEBA: Appendices Appendix H: Special Distribution of Benefiting Reaches, MP&M Facilities, and Benefiting Populations
Figure H.2: Location of Benefiting Reaches in Relation to Sample MP&M Facilities by County and Population
Reaches Benefiting from MP&M Regulation (EPA Region IV)
Location of Reaches Benefiting
from MP&M Regulation
^=^= Benefitliiig Reaches
i- MP&M Sample Facilities
IV EPA Regions
Counties by Population
1,614-72,787
72,788 - 219,081
219,082- 471,927
| 471,928 - 1,052,250
1,052,251 -2,180,128
Source: U.S. EPA analysis.
H-4
-------
MP&M EEBA: Appendices Appendix H: Spacial Distribution of Benefiting Reaches, MP&M Facilities, and Benefiting Populations
Figure H.3: Location of Benefiting Reaches in Relation to Sample MP&M Facilities by County and Population
Reaches Benefiting from MP&M Regulation (EPA Region V and VII)
Location of Reaches
Benefiting from MP&M
Regulation
^=^= Benefitting Reaches
O MP&M Sample Facilities
Counties by Population
429 - 87,608
| 87,609 - 284,026
284,027 - 655,174
655.175-2,111.966
2,111.967-5,192,105
Source: U.S. EPA analysis.
H-5
-------
MP&M EEBA: Appendices
Appendix H: Spacial Distribution of Benefiting Reaches, MP&M Facilities, and Benefiting Populations
Figure H.4: Location of Benefiting Reaches in Relation to Sample MP&M Facilities by County and Population
Reaches Benefiting from MP&M Regulation (EPA Region VI)
Location of Reaches
Benefiting from MP&M
Regulation
Benefitting Reaches
MP&M Sample F.cilltie,
Counties by Population
114 - 50,051
| 50,052-147,107
147,108-353,375
353,376 - 726,284
726.285 - 3,259.207
Source: U.S. EPA analysis.
H-6
-------
MP&M EEBA: Appendices
Appendix H: Spacial Distribution of Benefiting Reaches, MP&M Facilities, and Benefiting Populations
Figure H.5: Location of Benefiting Reaches in Relation to Sample MP&M Facilities by County and Population
Reaches Benefiting from MP&M Regulation (EPA Regions VIII and X)
Location of Reaches
Benefiting from MP&M
Regulation
Benefiting Reaches
MP&M Sample Facilities
Counties by Population
55 -50613
50614 - 186412
186413-410809
410810-860126
860127 - 1674255
Source: U.S. EPA analysis.
H-7
-------
MP&M EEBA: Appendices
Appendix H: Spacial Distribution of Benefiting Reaches, MP&M Facilities, and Benefiting Populations
Figure H.6: Location of Benefiting Reaches in Relation to Sample MP&M Facilities by County and Population
Reaches Benefiting from MP&M Regulation (EPA Region IX)
tOO O 1OO Kilometers
Location of Reaches
Benefiting from MP&M
Regulation
BeneHttiiig Reaches
O MP&M Sample Facilities
Counties by Population
1,119-321,232
321,233- 936,268
936.269- 1.664,869
1,664,870 - 2,871,024
2,871,025 - 9,284,693
Source: U.S. EPA analysis.
H-t
-------
MP&M EEBA: Appendices
Appendix H: Spacial Distribution of Benefiting Reaches, MP&M Facilities, and Benefiting Populations
Table H.I: Distribution of MP&M Facilities and Participants of Water Based Recreation by State
: _ , ,_, , _ , ,. Average # of Per Person
Percent of State Population : _, . ,
Participating by Activity ! Trips per Season by
F 6 J J : Activity
State i Boat i View j Fish j Swim j Boat
CA ill.7%!36.9%il3.6%!20.1%l 5.4
TX 1 12.8%! 16.4%! 18.9%! 14.5%! 7.2
NY i 12 4%^ 25 6%^ 1 1 2%^ 20 5%^ 7 9
FL !l8.7%!32.6%!20.5%!24.2%! 10.1
IL 111 .8%! 17.2%! 14.6%! 9.4% ! 9.6
OH ! 11.5%! 15.8%! 14.2%! 14.0%! 8
PA 1 10.5%! 14.4%! 15.2%! 13.7%! 9.4
MI !l6.0%!24.8%!l8.4%J20.8%! 8.6
NJ ! 15.9%! 32.3%! 15.9%J23.9%! 10.9
NC I 8.8%! 17.9%! 16.5%! 13.5%! 7.7
IN ! 14.3%! 15.0%l20.3%! 16.3%! 7.7
MA !l5.7%!30.9%!l5.7%J28.9%! 8.7
WI J15.7%!22.1%i 18.1%! 19.7%! 10
GA ! 11.5%! 13.9%! 16.6%! 11.5%! 11.4
MO 1 13.0%! 12.6%! 18.8%! 15.2%! 5.2
VA 1 13.4%! 17.0%! 16.2%! 13.4%! 9
WA !25.0%!39.2%!l8.8%!25.9%! 5.8
MN 1 17.6%! 19.6%! 19.6%! 17.6%! 5.4
TN i 17 9%^ 13 5%b2 6%^ 14 5%^ 7 5
MD 1 14.8%! 18.7%! 17.1%! 12.1%! 8.8
AL j 14.7%! 11. 9%J20.6%! 13.8%! 7.5
CT ! 16.4%! 37.1%! 14.5%! 27.0%! 7.7
LA j 16.4%! 15. 3%J27.0%! 13.8%! 4
CO ! 6.6% J13.2%J25.9%! 11.3%! 17.2
OR !20.3%!37.8%!24.9%!23.0%! 8.8
KY ! 11.9%! 12.3%J22.4%! 10.0%! 6.5
AZ ! 7.3% j 11.2%! 11.8%! 10.7%! 7.2
View
14
5
57
17.9
9
8?
74
Q4
64
59
9
11 6
6.1
4.1
4
4?
11 7
16.5
37
12.1
9.2
6.8
3.4
14.8
7?
3
8
Fish
71
106
92
171
137
13 1
10.9
12
63
136
11 8
143
11.5
10.3
5
84
18?
11.5
15 1
13.2
18.6
7.7
13.4
13.1
13?
9.4
8.3
Swim
11.7
6.5
87
15.4
5.7
8.8
8
8.5
7.3
7.4
5.5
9.5
6.2
7.4
8
6.1
5.8
6.8
67
8.4
10.6
12.3
4.4
5.2
7.4
17.5
5.7
Total State
Pop.
(1990)
(Millions)
29.8
17.0
180
12.9
11.4
10.8
11.9
9.3
7.7
6.6
5.5
6.0
4.9
6.5
5.1
6.2
4.9
4.4
4 9
4.8
4.0
3.3
4.2
3.3
2.8
3.7
3.7
Potential (Extrapolated) # Participants Based on
State Population
Boat
3,490,513
2,171,791
2231 374
2,423,418
1,349,105
1,251,590
1,249,014
1,484,665
1,225,246
586,317
794,663
942,332
768,940
746,819
665,035
827,102
1,216,673
767,875
873 280
706,988
593,114
537,516
692,165
217,554
576,323
437,524
267,685
View
10,992,849
2,792,303
4 602 209
4,221,438
1,962,335
1,718,851
1,713,391
2,307,687
2,495,046
1,188,920
831,624
1,860,501
1,079,788
903,129
646,562
1,049,783
1,907,623
857,162
659 079
893,037
481,905
1,219,747
647,509
435,109
1,074,057
454,352
411,823
Fish
4,057,154
3,205,978
2022 183
2,657,943
1,667,985
1,535,284
1,809,469
1,710,593
1,225,246
1,091,201
1,127,312
942,332
883,463
1,076,808
960,606
1,002,066
916,260
857,162
1 103 957
818,617
834,066
475,495
1,138,723
854,678
707,306
824,564
432,415
Swim
5,983,736
2,456,192
3 695714
3,126,991
1,079,284
1,518,596
1,633,326
1,936,520
1,849,008
895,762
905,546
1,739,689
965,266
746,819
775,874
827,102
1,261,735
767,875
708,510
576,753
556,044
888,969
580,525
372,950
654,913
370,212
391,232
Nat'l # oi
MP&M
Facilities
68,359
38,176
36 329
30,198
28,343
26,460
26,237
23,662
19,805
15,158
14,656
13,915
13,845
13,747
13,395
12,829
11,991
11,272
10,808
8,993
8,825
8,593
8,500
8,231
7,978
7,822
7,799
State %of
National
Facilities
11.9%
6.6%
63%
5.2%
4.9%
4.6%
4.6%
4.1%
3.4%
2.6%
2.5%
2.4%
2.4%
2.4%
2.3%
2.2%
2.1%
2.0%
1.9%
1.6%
1.5%
1.5%
1.5%
1.4%
1.4%
1.4%
1.4%
Cum.
ST % of
Facilitie
s
11.9%
18.5%
24 8%
30.0%
34.9%
39.5%
44.1%
48.2%
51.6%
54.3%
56.8%
59.2%
61.6%
64.0%
66.3%
68.6%
70.6%
72.6%
74.5%
76.0%
77.6%
79.1%
80.5%
82.0%
83.3%
84.7%
86.1%
Cumulative Percent Distribution of
Participants by State
Boat
10.3%
16.7%
23 3%
30.5%
34.5%
38.2%
41.9%
46.3%
49.9%
51.6%
54.0%
56.8%
59.0%
61.2%
63.2%
65.7%
69.3%
71.5%
74.1%
76.2%
77.9%
79.5%
81.6%
82.2%
83.9%
85.2%
86.0%
View
19.5%
24.5%
32 6%
40.1%
43.6%
46.6%
49.7%
53.8%
58.2%
60.3%
61.8%
65.1%
67.0%
68.6%
69.8%
71.6%
75.0%
76.5%
77.7%
79.3%
80.1%
82.3%
83.4%
84.2%
86.1%
86.9%
87.7%
Fish
9.4%
16.8%
21 5%
27.7%
31.5%
35.1%
39.3%
43.2%
46.1%
48.6%
51.2%
53.4%
55.4%
57.9%
60.1%
62.5%
64.6%
66.6%
69.1%
71.0%
72.9%
74.0%
76.7%
78.7%
80.3%
82.2%
83.2%
Swim
13.8%
19.4%
27 9%
35.1%
37.6%
41.1%
44.8%
49.3%
53.5%
55.6%
57.7%
61.7%
63.9%
65.6%
67.4%
69.3%
72.2%
73.9%
75.6%
76.9%
78.2%
80.2%
81.5%
82.4%
83.9%
84.8%
85.7%
H-9
-------
MP&M EEBA: Appendices
Appendix H: Spacial Distribution of Benefiting Reaches, MP&M Facilities, and Benefiting Populations
Table H.I: Distribution of MP&M Facilities and Participants of Water Based Recreation by State
State
IA
OK
sc
KS
AR
MS
NE
UT
WV
RI
ME
NH
NM
ID
NV
MT
SD
ND
HI
VT
DE
WY
AK
T, i *n.i ฑ r, , ฑ- Average # of Per Person
Percent of State Population : T . ,
Participating by Activity ! Trips per Season by
1 6 J J Activity
Boat | View i Fish i Swim i Boat
13.5%! 16.4%! 18.7%! 13.5%! 5
11.2%! 12.6%J25.2%! 14.0%! 4.9
13.8%! 19.9%J26.0%! 15.5%! 9.8
6.7% ! 17.0%! 18.5%! 13.3%! 17.6
14.1%! 12.5%J28.1%! 18.0%! 4.6
13.6%! 12. 1%J23.6%! 15.7%! 6.3
10.7%! 15.5%! 10.7%! 15.5%! 3.9
8.1% ! 17.1%! 13.5%! 12.6%! 6.6
9.5% ! 10.3%! 18.3%! 15.9%! 6.6
15 8%i40 4%l 19 3%! 36 8%l 6 9
22.2%!44.4%J27.8%J37.5%! 7.6
18.8%! 31.2%! 14.1%! 34.4%! 3.3
6.7%! 8.6% ! 12.4%! 9.5%! 3.7
24.1%!25.3%J20.5%J20.5%! 5.8
17.3%J21.3%! 13.3%! 12.0%! 4.8
14.5%!20.0%J34.5%J29.1%! 7.8
16 7%bl 4%^ 16 7%bl 4%^ 2 3
15.0%! 15. 0%J25.0%! 15.0%! 3.7
16.4%! 58.2%! 18.2%J47.3%! 6.7
20.6%! 17.6%! 8.8%J20.6%! 7.1
15.7%J41.2%! 15.7%! 13.7%! 6.4
19 4%! 16 1%J48 4%! 6 5% 1 6 3
34.5%! 41.4%! 37.9%! 6.9%! 5.4
View
4.4
3.4
8.5
9
10.2
24.2
2.1
3.5
46
46
5.7
14.9
5.6
4.3
7.3
15.6
1 8
3
33.9
5.5
11
46
71
Fish
13.8
14.6
16.2
12.9
13.3
17.4
13.9
3.6
17?
8 3
10.5
13.2
9.8
13.4
15.4
20.7
6
4.5
6.6
8.7
11.5
8 1
174
Swim
2.7
4.2
7.5
6.2
7.3
12.9
3.9
6.8
6.7
7
10.3
15.7
3.8
9.5
6.3
8.3
7
11.5
15.5
10.4
6.9
8
2
Total State
Pop.
(1990)
(Millions)
2.8
3.1
3.5
2.5
2.4
2.6
1.6
1.7
1.8
1.0
1.2
1.1
1.5
1.0
1.2
0.8
0.7
0.6
1.1
0.6
0.7
0.5
0.6
Potential (Extrapolated) # Participants Based on
State Population
Boat
373,482
351,954
481,589
165,172
330,571
349,222
169,113
139,691
170,807
158,442
272,873
207,985
101,005
242,590
208,318
116,228
116,001
95,820
181,347
115,862
104,497
87,791
189,670
View
454,673
395,948
693,488
422,105
293,841
312,462
244,274
294,902
185,041
404,907
545,746
346,641
129,863
254,720
256,391
159,813
149,144
95,820
644,788
99,310
274,305
73,159
227,604
Fish
519,627
791,896
905,387
458,810
661,141
606,544
169,113
232,818
327,381
193,651
341,091
155,989
187,580
206,202
160,244
276,041
116,001
159,700
201,496
49,655
104,497
219,478
208,637
Swim
373,482
439,942
539,380
330,343
422,396
404,363
244,274
217,296
284,679
369,697
460,473
381,305
144,292
206,202
144,220
232,455
149,144
95,820
523,890
115,862
91,435
29,264
37,934
Nat'l # oi
MP&M
Facilities
7,661
6,972
6,907
6,370
5,825
5,165
4,424
3,633
3,442
3,106
2,980
2,960
2,927
2,572
2,406
2,204
2,049
1,749
1,677
1,488
1,379
1,309
1,156
State %of
National
Facilities
1.3%
1.2%
1.2%
1.1%
1.0%
0.9%
0.8%
0.6%
0.6%
0.5%
0.5%
0.5%
0.5%
0.4%
0.4%
0.4%
0.4%
0.3%
0.3%
0.3%
0.2%
0.2%
0.2%
Cum.
ST % of
Facilitie
s
87.4%
88.6%
89.8%
90.9%
91.9%
92.8%
93.6%
94.2%
94.8%
95.3%
95.9%
96.4%
96.9%
97.3%
97.7%
98.1%
98.5%
98.8%
99.1%
99.3%
99.6%
99.8%
100.0%
Cumulative Percent Distribution of
Participants by State
Boat
87.1%
88.2%
89.6%
90.1%
91.1%
92.1%
92.6%
93.0%
93.5%
94.0%
94.8%
95.4%
95.7%
96.4%
97.0%
97.4%
97.7%
98.0%
98.5%
98.9%
99.2%
99.4%
100.0%
View
88.5%
89.2%
90.4%
91.1%
91.7%
92.2%
92.7%
93.2%
93.5%
94.2%
95.2%
95.8%
96.0%
96.5%
96.9%
97.2%
97.5%
97.7%
98.8%
99.0%
99.5%
99.6%
100.0%
Fish
84.4%
86.2%
88.3%
89.4%
90.9%
92.3%
92.7%
93.3%
94.0%
94.5%
95.3%
95.6%
96.1%
96.5%
96.9%
97.5%
97.8%
98.2%
98.7%
98.8%
99.0%
99.5%
100.0%
Swim
86.5%
87.5%
88.8%
89.5%
90.5%
91.4%
92.0%
92.5%
93.1%
94.0%
95.1%
95.9%
96.3%
96.7%
97.1%
97.6%
97.9%
98.2%
99.4%
99.6%
99.8%
99.9%
100.0%
H-10
-------
MP&M EEBA: Appendices
Appendix H: Spacial Distribution of Benefiting Reaches, MP&M Facilities, and Benefiting Populations
Figure H.7: Cumulative Distribution of Facilities and Participants
120.0%
100.0%
80.0%
? 60.0%
40.0% -
20.0%
0.0% 4
c\ic\ic\ic\ic\icococococo
^ CO LO 1^ O5
^r ^r ^r ^r ^r
Number of states
Note: The numbers refer to States in the order they appear in the above table. Therefore, 1 is California, 2 is Texas, 3 is New York, etc.
Sources: Information on total MP&M facilities by State is from Census Data; information on where recreating people live is from NDS data.
- -
Facilities
- -Viewing
Fishing
Swimming
H-ll
-------
MP&M EEBA: Appendices
Appendix I: Selecting Values for Benefits Transfer
Appendix I: Selecting WTP
Values for Benefits Transfer
INTRODUCTION
EPA identified eight surface water evaluation studies that
quantified the effects of water quality improvements on
various water-based recreational activities. As noted in
Chapter 15 of this report, the Agency selected these
studies based on the technical criteria for evaluating study
transferability (Desvousges et al, 1987; and Boyle and
Bergstrom, 1990):
* The environmental change valued at the study
site must be the same as the environmental
quality change caused by the rule (e.g., changes
in toxic contamination vs changes in nutrient
concentrations);
> The populations affected at the study site and at
the policy site must be the same (e.g.,
recreational users vs nonusers);
> The assignment of property rights at both the
study and policy sites must lead to the same
theoretically appropriate welfare measure (e.g.,
willingness to pay (WTP) vs willingness to
accept compensation); and
* The candidate studies should be based on
defensible research methods. Six of the eight
studies are published in peer reviewed journals.
One study, Tudor et al. (2000), was presented at the
annual American Agricultural Economic
Association and the Northeastern Resource and
Environmental Economic meetings. The eighth
study, Lyke (1989), is an unpublished Ph.D.
dissertation.
In addition to the above criteria, the Agency considered
authors' recommendations regarding the robustness and
theoretical soundness of various estimates in selecting point
estimates for benefits transfer.
The rest of this appendix presents welfare estimates from
seven studies used in estimating recreational benefits from
the proposed regulation and provides EPA's reasons for
selecting specific values from each study. The study by
Tudor et al. (2000) is discussed in detail in Chapter 21. All
APPENDIX CONTENTS;
1.1 Desvousges et al., 1987. Option Price Estimates
for Water Quality Improvements: A Contingent
Valuation Study for the Monongahela River 1-1
1.2 Farber and Griner, 2000. Valuing Watershed Quality
Improvements Using Conjoint Analysis 1-3
1.3 Jakus et al., 1997. Do Sportfish Consumption
Advisories Affect Reservoir Anglers' Site Choice? ... 1-5
1.4 Lant and Roberts, 1990. Greenbelts in the Cornbelt:
Riparian Wetlands, Intrinsic Values, and
Market Failure 1-6
1.5 Audrey Lyke, 1993. Discrete Choice Models to Value
Changes in Environmental Quality: A Great Lakes
Case Study 1-6
1.6 Montgomery and Needehnan, 1997. The Welfare
Effects of Toxic Contamination in Freshwater Fish . . . 1-7
1.7 Phaneuf et al., 1998. "Valuing Water Quality
Improvements Using Revealed Preference Methods
When Comer Solutions are Present" 1-8
Glossary 1-10
Acronyms 1-11
References 1-12
welfare estimates from this study are eligible for use in
benefits transfer, because the study is based on the policy
scenarios specific to the MP&M regulation.
I.I DESVOUSSES ET AL., 1987.
OPTION PRICE ESTIMATES FOR WATER
QUALITY IMPROVEMENTS: A
CONTTNSENT VALUATION STUDY FOR THE
MONONSAHELA RlVER
This study used findings from a contingent valuation
(CV) survey to estimate WTP for improved recreational
fishing from enhanced water quality in the Pennsylvania
portion of the Monongahela River. In a hypothetical market,
each survey respondent was asked to provide an option price
for different water quality changes, such as "raising the
water quality from suitable for boating (hereafter, 'beatable'
water) to a level where gamefish would survive (hereafter,
'fishable' water)." Table I.I lists water quality changes
-------
MP&M EEBA: Appendices
Appendix I: Selecting Values for Benefits Transfer
evaluated in the study and the corresponding WTP
estimates. The following discussion provides justification
for selecting the point estimates EPA used in the benefits
transfer analysis in Chapter 15.
Table I.I: Changes in the Resource Value from a Specified Water Quality Improvement from
Desvousges et al. (1987)
Adjusted to 1999$
Water Quality Change Valued User Nonuseri Combined-
Unsuitable to Boatable
Boatable to Fishablea
?ishable to Swimmable
Boatable.to.Swimmable
Jnsuitable to Swimmable
Jnsuitable to Boatable
Boatable to Fishable
"ishable to Swimmable
Boatable to Swimmable
Jnsuitable to Swimmable
Iterative Bidding: $25 starting point
$50.2! $54.4! $53. ij
$346L
$21.61
$.5.8.8!.
$109. Ol
Iterative Bidding:
$173.5!
$106.4!
$60.6!
$182.6!
$356. l!
$26.6- $29. li
$13.2! $15.9!
...$.39/7!. .$46,0;
$94. l! $99. li
$725 startingjpoint
$71. li $105. li
$48.2! $67.6!
$21.21 $34.4!
$74.2! $110.3!
$145. li $215.4!
Original Estimates (1981$)
User
$27.4!
S18.9!
$11.8!
$.324
$59.5!
$94.7!
$58. l!
$33.l!
$99.7!
$194.4!
Nonuseri
$29.7!
$.1.1.5!..
$7.2!
SKLZL.
$51.4!
$38.8!
$26.3!
$11.6!
$40.5!
$79.2!
Combined
$29.0
$15.9
$8.7
$25..1
$54.1
$57.4
$36.9
$18.8
$60.2
$117.6
Direct Question: no payment card
Boatable to Unsuitable
Boatable to Fishable
"ishable to Swimmable
Boatable to Swimmable
Jnsuitable to Swimmable
$83. Oi
$57.3!
$37.0!
$96.9!
$179.9!
$26. 0! $44.9!
$19.8! $32.2!
$15.6! $22.7!
$37.2! $57. li
$63.2! $102.0!
$45.3!
$31.3!
$20.2!
$52.9!
$98.2!
$14.2!
$10.8!
$8.5!
$20.3!
$34.5!
$24.5
$17.6
$12.4
$31.2
$55.7
Direct Question: payment card
Boatable to Unsuitable
Boatable to Fishable
"ishable to Swimmable
Boatable to Swimmable
Jnsuitable to Swimmable
$85.7!
$83. Oi
$41.9!
$130.4!
$216ฃ\
$97. li $93.4!
$40. li $53.7!
$14. l! $22.9!
$54.8! $78.6!
$151.71 $172. Ol
$46.8!
$45.3!
$22.9!
$71.2!
$117.91
$53.0!
$21.9!
$7.7!
$29.9!
$82.81
$51.0
$29.3
$12.5
$42.9
$93.9
Location: Pennsylvania portion of the Monongahela River
Estimating Approach: CV
Survey Population : Recreational Users and Nonusers
a. The value selected for benefits transfer is given in bold.
EPA judged that only one value from this study met the
requirements for the quality of research methods and was
compatible with the environmental changes and population
characteristics considered in the analysis of recreational
benefits from the MP&M rule. EPA selected this value for
the following reasons:
* Environmental quality change. The Desvousges
et al. (1987) study derived WTP values for five
different changes in water quality, as shown in
Table I.I above. EPA judged that only one of these
improvements, from "beatable" to "fishable," is
compatible with the changes in water quality
expected under the MP&M rule. Streams
unsuitable for recreational activities such as boating
are likely to be affected by multiple environmental
stressors from many sources including many that
are not related to MP&M discharges (e.g., severe
oxygen depletion.) In these cases it is reasonable to
assume that changes in concentrations of MP&M
pollutants would reduce or eliminate one of the
stressors on the reach, but would be unlikely to
change the designation of the reach.
The analysis in Chapter 15 assumes that reaches
with ambient water quality criteria (AWQC)
exceedances under the baseline conditions are
beatable and likely to support rough fishing, but
may not be clean enough to support game fishing.
AWQC are set at a level below which pollutant
1-2
-------
MP&M EEBA: Appendices
Appendix I: Selecting Values for Benefits Transfer
concentrations are not expected to cause significant
harm to human health or aquatic life. Exposure to
pollutant concentrations above the AWQC levels
are expected to have a harmful effect. Therefore,
by definition, water with pollutant levels that
exceed criteria set to protect human health or
aquatic life are not suitable waters for sensitive
aquatic species or ideal as a sources of fish for
consumption.
Removing AWQC exceedances is therefore
comparable to shifting water quality from
"beatable"to "fishable." The Agency did not use
the beatable to swimmable designation because a
more limited number of reaches are suitable for
swimming nationally due to reasons not related to
MP&M discharges (e.g., amenities, pathogens).
Determining national level locations affected by
MP&M pollutants that are suitable for swimming
required more resources than were available for the
national analysis, but may be done in the future
analyses.
Research methods. The authors used four
different payment vehicles in their CV study. For
the recreational benefits analysis, EPA decided to
use the WTP estimates derived from the "iterative
bidding" (IB) payment vehicle, because it is
universally preferred to the "direct
question/open-ended^' format for eliciting
option price bids.
Survey respondents in the direct question format
are asked to state the most that they would be
willing to pay for the program or policy. This
format confronts respondents with an unfamiliar
choice. Studies that use this approach usually have
high non-response rates.
Respondents in the IB format are asked whether
they would be willing to pay a given amount. If the
answer is yes, then this amount is raised in pre-set
increments until the respondent says that he or she
will not pay the last amount given. If the answer is
no, then the amount is decreased until the
respondent indicates WTP the stated amount.
Some studies found that the respondent's final
WTP amount depends on the initial amount offered
(e.g., Boyle and Bishop, 1988). This problem is
referred to in economic literature as starting point
bias. The Agency selected the WTP estimates
derived using the $25 starting point IB process to
avoid upward starting point bias. Table 1.1 shows
that the selected estimates are the most conservative
among all the payment vehicles used.
* Population characteristics. EPA selected WTP
values for the user population to match population
characteristics considered in our analysis (i.e.,
recreational anglers, boaters, and wildlife viewers).
1.2 FARBER AN& SRINER, 2000.
VALUING WATERSHED QUALITY
IMPROVEMENTS USINS CONJOINT
ANALYSIS
Farber and Griner (2000) used a CV study to estimate
changes in water resource values to users from various
improvements in Pennsylvania's water quality. The study
defines water quality as "polluted," "moderately polluted,"
and "unpolluted" based on a water quality scale developed
by EPA Region III. "Polluted" streams are unable to
support aquatic life, "moderately polluted" streams are
somewhat unable to support aquatic life, and "unpolluted"
streams adequately support aquatic life. Farber and Griner
developed WTP estimates for water quality improvements
for the following three water quality changes:
* From "moderately polluted" to "unpolluted,"
* From "severely polluted" to "moderately polluted,"
and
* From "severely polluted" to "unpolluted."
The authors used six different model variations to estimate
the WTP for the three improvements scenarios for various
population groups (e.g., users, nonusers, and a mix of users
and nonusers). Table 1.2 presents the estimated WTP
values. The following discussion provides EPA's reasons
for selecting point estimates for the use in benefits transfer.
1-3
-------
MP&M EEBA: Appendices
Appendix I: Selecting Values for Benefits Transfer
Table 1.2: Estimate WTP for Specified Water Quality Improvements from Farber and Sriner (1999$)
Water Quality Change Valued
Moderately Polluted to Unpolluted
Severely Polluted to Moderately Polluted
Severely Polluted to Unpolluted
Moderately Polluted to Unpolluted
Severely Polluted to Moderately Polluted
Severely Polluted to Unpolluted
Moderately Polluted to Unpolluted a
Severely Polluted to Moderately Polluted
Severely Polluted to Unpolluted
Binary Choice Model
User Nonuseri Combined-
Basic
$46.77! $5.95!
$62.91! $5.50!
$110.35! $42.20!
Interactive
$45.36! $3.05!
$61.29! $1.39!
$108.68! $38.87!
Fixed Effects
$23.09! $15.45!
$39.93! $10.01!
$81.42J $45.5l|
$38.04!
$52.30!
$90.01!
$35.76!
$49.62!
$87.43!
$26.63!
$35.90!
$75.631
Intensity of Preference
User
$52.85!
$69.42!
$121.90!
$53.56!
$70.63!
$125.25!
$39.34!
$59.67!
$103.931
Model
Nonuseri Combined
$13.13!
$48.36!
$54.26!
$12.55!
$47.61!
$54.22!
$5.17!
$28.50!
$29.151
$51.02
$66.70
$109.92
$51.35
$67.64
$112.44
$38.59
$55.46
$92.76
Location: Lower Allegheny Watershed in Western Pennsylvania
Estimating Approach: Conjoint Analysis
Survey Population: Recreational users and nonusers
a. Values selected for the use in benefits transfer are given in bold.
The Agency selected only two values from this study based
on their compatibility with the environmental changes and
population characteristics considered in both the original
study and the analysis of recreational benefits from the
MP&M rule. The following discussion summarizes EPA's
reasons used in the selection process:
* Environmental quality change. EPA judged that
only one water quality improvement scenario
change from "moderately polluted" to "unpolluted"
is compatible with the environmental quality
change expected from the proposed regulation
AWQC are set at a level below which pollutant
concentrations have not been demonstrated to cause
significant harm to human health or aquatic life.
Exposure to pollutant concentrations above the
AWQC levels are expected to have a harmful
effect. Therefore, by definition, water with
pollutant levels that exceed criteria set to protect
human health or aquatic life are polluted waters.
EPA chose the case where the policy variable
changed from moderately polluted to unpolluted
because this is likely to be the most frequently
occurring scenario for reaches with MP&M
discharges. Streams unable to support any aquatic
life (i.e., "severely polluted") are likely to be
affected by numerous environmental stressors, in
addition to MP&M discharges. Eliminating
MP&M related AWQC exceedences would
eliminate or reduce one of the stressors, but is
unlikely to change the quality of the water from
severely polluted to unpolluted. It is more
realistic to assume that most streams affected by
MP&M facility discharges are moderately polluted,
i.e., these streams support some aquatic life; but
sensitive species are adversely affected by MP&M
pollutants exceeding AWQC values protective of
aquatic life. Removing all AWQC exceedances
would make such streams unpolluted.
* Research methods. EPA considered only two of
the six versions of the benefits transfer model
based on the authors' recommendations. The
authors appear to prefer the "fixed effects" versions
of both the binary choice (BC) and intensity of
preference (IP) models. Specifically, they note
that, "A likelihood ratio test, with degrees of
freedom being the number of individuals in the
estimating sample, can be used to test the
superiority of the fixed effects model. Such a test
shows the fixed effects model to be a statistical
improvement over either the basic or interactive
models" (see Table 1.2). In addition, they state that,
"the purpose of estimating a fixed effects model
was to account for the possibility that some
respondents may approve of all changes, regardless
of price and quality. If this behavior existed in the
sample, not controlling for it would result in
overestimates of marginal valuations for each type
of quality change. This expectation is supported by
the fact that the fixed effects valuation estimates
are lower than the others."
* Population characteristics. EPA selected WTP
values for the user population to match population
characteristics considered in our national analysis
1-4
-------
MP&M EEBA: Appendices
Appendix I: Selecting Values for Benefits Transfer
(i.e., recreational anglers, boaters, and wildlife
viewers).
1.3 JAKUS ETAL., 1997. Do
SPORTFISH CONSUMPTION ADVISORIES
AFFECT RESERVOIR ANSLERS SITE
CHOICE?
Jakus et al. (1997) used a repeated discrete choice travel
cost (TC) model to examine the impacts of fish
consumption advisories (FCA) in eastern and middle
Tennessee. The estimated consumer surplus from
recreational fishing in middle and east Tennessee is $24.48
and $49.45 per angler per day, respectively, under the
baseline water quality conditions. The estimated welfare
gain from removing FCAs is $1.92 and $2.97 per angler per
day , respectively. Table 1.3 summarizes the study's
estimates.
Table I.3:Consumer Surplus from Recreational Fishing from Jakus et al. (1997)ฐ
Consumer Surplus: Consumer Surplus
Water Quality Change Valued Adjusted to 1999$! ($1997)
Site Choice Model multinomial lagit
Average surplus per trip in middle TN (baseline water quality conditions_)
Benefit per trip from removing all advisories in middle TN
Average surplus per trip in East TN (baseline water quality conditions)
Benefit per trip from removing all advisories in east TN
Benefit per trip from removing Watts Bar advisory
$24.48!
$1.92!
$49.45!
$2.97!
$1.65!
$23.60
$1.85
$47.67
$2.86
$1.59
Repeated Discrete Choice Model repeated nested lagit model
Seasonal benefit from removing all advisories in middle TN
Seasonal benefit from removing all advisories in east TN
Seasonal benefit from removing Watts Bar advisory ^^^
$22.78!
$49.17!
$2^i
$21.96
$47.40
$27.60
Location: Tennessee
Estimating Approach: TC
Survey Population: Tennessee residents; anglers and non-anglers
a. Values selected for the use in benefits transfer are given in bold.
EPA selected two values from this study for use in benefits
transfer, based on their compatibility with the environmental
quality change and population characteristics at both the
original study and policy sites, for the following reason:
* Environmental quality change. FCAs are usually
triggered by the presence of toxic pollutants in fish
tissue. EPA expects the proposed regulation to
reduce discharges of toxic pollutants, including
those linked to FCAs (e.g., mercury and lead). The
Agency therefore assumed that the removal of
FCAs is compatible with water quality
improvement expected from the proposed
regulation.
The recreational benefits analysis uses consumer
surplus estimates for both regions studied by the
authors, because MP&M facilities are located in
these regions as well as throughout heavily
populated regions of the U.S. EPA did not include
the value corresponding to the Watts Bar lake in the
benefit transfer analysis because this lake is
included in the set of fishing areas for east
Tennessee.
7-5
-------
MP&M EEBA: Appendices
Appendix I: Selecting Values for Benefits Transfer
1.4 LANT AND ROBERTS, 1990.
6REENBELTS IN THE CORNBELT: RIPARIAN
WETLANDS, INTRINSIC VALUES, AND
MARKET FAILURE
Lant and Roberts (1990) used a CV study to estimate the
recreational and nonuse benefits of improved water quality
in selected Iowa and Illinois river basins. River quality was
defined by means of an interval scale of "poor," "fair,"
"good," and "excellent." The authors defined the four water
quality intervals as follows:
> "poor" water quality is inadequate to support any
recreation activity,
> "fair" water quality is adequate for boating and
rough fishing,
* "good" water quality is adequate for gamefishing,
and
* "excellent" is adequate to support swimming and
exceptional fishing.
Table 1.4 summarizes WTP values for specified water
quality improvements from this study.
Table 1.4: WTP Values for a Specified Water Quality Improvement from Lant and Roberts (1990)
Water Quality Change Valued
Poor to Fan-
Fair to Good a
Good to Excellent
Adjusted to 1999$
Use Value ! Nonuse Value
$44.70! $55.12
$54.38! $69.12
$60.84! $63.35
Original Study Values $1987
Use Value ! Nonuse Value
$30.50! $37.61
$37.10! $47.16
$41.51 $43.22
Location: Selected Iowa and Illinois river basins
Estimating Approach: CV
Survey Population: Recreational users and nonusers
a. The values given in bold were selected for the use in benefits transfer.
The Agency judged that only one value from this study is
compatible with the environmental changes and population
characteristics considered in the analysis of recreational
benefits from the MP&M rule, for the following reasons:
* Environmental quality change. The Agency
judged that only one of the three possible water
quality changes considered in this study "fair" to
"good" was compatible with the water quality
change expected under the MP&M rule. EPA
assumed in its analysis of recreational benefits
expected from the MP&M rule that reaches with
AWQC exceedances under the baseline conditions
are may support rough fishing, but may not be
clean enough to support more sensitive species
such as those desired for game fishing. Removing
AWQC exceedances will shift water quality from
"fair"to "good."
Population characteristics. EPA selected WTP
values for the user population only to match
population characteristics considered in our
analysis (i.e., recreational anglers, boaters, and
wildlife viewers).
1.5 AUDREY LYKE, 1993. DISCRETE
CHOICE MODELS TO VALUE CHANGES IN
ENVIRONMENTAL QUALITY: A GREAT
LAKES CASE STUDY
Lyke's (1993) study of the Wisconsin Great Lakes open
water sport fishery showed that anglers may place a
significantly higher value on a contaminant-free fishery than
on one with some level of contamination. Lyke estimated
the value of the fishery to Great Lakes trout and salmon
anglers if it was improved enough to be "completely free of
contaminants that may threaten human health." The author
also estimated various policy scenarios that affect the value
of recreational fishing in the Wisconsin Great Lakes,
1-6
-------
MP&M EEBA: Appendices
Appendix I: Selecting Values for Benefits Transfer
including reducing the daily bag limit for lake trout and
restoring naturally reproducing populations of lake trout.
Table 1.5 presents welfare estimates from this study.
Table 1.5: WTP Estimates for a Specified Water Quality Improvements from Lyke (1993)
Water Quality Change Valued
CV- linei
1990 fishing conditions remain the same as 1989
WI daily bag limit for lake trout reduced to one a day
Great Lakes fish are free of pollutants affecting human health
Restoring naturally reproducing populations of lake trout
WI inland fishing conditions remain the same as 1989
Restoring naturally reproducing populations of lake trout in WI
waters of Great Lakes (inland anglers only)
CV constant elasticity t
1990 fishing conditions remain the same as 1989
Great Lakes fish are free of pollutants affecting human health
CV constant elasticity oj
1990 fishing conditions remain the same as 1989
Great Lakes fish free of pollutants that affect human health
Adjusted to 1999$
Value of WI: Change in
Fishing! Value
ir logit model
$89j426;613!
$41,356,4521 -$48,070,161
$99,362,903! $9^36,290
$16,247,177! $16,247,177
$907,156,452!
$0! $0
/substitution model (mean)
$111,850,403!
$146,761,694! $34,911,290
r substitution model (median)
$25,243,548!
$38,133,87lj $12,890,323
Original Study Value (1989$)
Value of WI: Change in
Fishing! Value
$66;600jOOO!
$30,800,000! -$35,800,000
$74,000,000! $7j400,000
$12,100,000! $12,100,000
$675,600,000!
$0! $0
$83,300,000!
$109,300,000! $26,000,000
$18,800,000!
$28,400,000! $9,600,000
Location: Wisconsin
Estimating Approach: TC and CV
Survey Population: Wisconsin Great Lakes and inland anglers
a. The values selected for the use in benefits transfer are given in bold.
EPA selected two WTP values from this study for use in
benefits transfer for the following reasons:
* Environmental quality change. EPA judged that
only one policy scenario Great Lakes fish that
are free from contaminants harmful to human
health is compatible with water quality
improvements expected under the proposed
regulation (i.e., removal of AWQC exceedances).
Other scenarios, such as reducing daily bag limit
for lake trout to one per day and restoring naturally
reproducing populations of lake trout, are irrelevant
to the MP&M regulation. The Agency used
estimates from the "no change in 1990 fishing
conditions compared to 1989" scenario as an
estimate of the baseline value of recreational
fishing in Wisconsin.
> Research methods. The Agency did not consider
estimates from the TC model because the author
noted that "the nested logit travel cost model
results seem too high."
1.6 MONTSOMERY AN& NEE&ELMAN,
1997. THE WELFARE EFFECTS OF Toxic
CONTAMINATION IN FRESHWATER FISH
Montgomery and Needelman (1997) estimated benefits from
removing "toxic" contamination from lakes and ponds in
New York State. They used a binary variable as their
primary water quality measure, which indicates whether the
New York Department of Environmental Conservation
considers water quality in a given lake to be impaired by
toxic pollutants. Their model controls for major causes of
impairments other than "toxic" pollutants, to separate the
effects of various pollution problems that affect the fishing
experience. Table 1.6 lists environmental quality changes
considered in the study and the WTP values corresponding
to a specified water quality change.
1-7
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MP&M EEBA: Appendices
Appendix I: Selecting Values for Benefits Transfer
Table 1.6: Welfare Estimates from fl
Water Quality Change Valued
Eliminate toxic contamination in all lakes a
All toxic lakes are closed to fishing
Raise pH in acidic lakes (none are threatened or impaired.)
Close all acidic lakes to fishing
Eliminate toxic contamination and raise pH in acidic lakes
Aontcjomery and Needelman (
Compensating Variation!
per Capita per Season:
(1999$)!
$84.93!
$116.94!
$18.56!
$19.94!
$K)6^i
1997)
Compensating Variation
per Capita per Season
(1989$)
$63.25
$87.09
$13.82
$14.85
$79.44
Location: New York State
Estimating Approach: TC Repeated discrete choice model
Survey Population: New York State residents; anglers and non-anglers
a. The values selected for the use in benefits transfer are given in bold.
The Agency selected only one value from this study for use
in the benefits transfer based on its compatibility with
environmental quality changes at both the original study and
the MP&M sites, for the following reason:
> Environmental quality change. Only one of the
five policy scenarios considered removing toxic
contamination in all lakes is directly compatible
with the potential changes brought about by the
MP&M rule. The MP&M rule is unlikely to
significantly affect the acidity in lakes and streams
affected by MP&M discharges. The last three
policy scenarios in Table 1.6 involve changes in pH
levels, and are therefore not included in the benefits
transfer. The Agency also did not consider the
estimate from the second scenario in table 1,6
closing all toxic lakes to fishing in benefits
transfer, because it does not consider water quality
improvement per se.
1.7 PHANEUF ET AL. , 1998. VALUING
WATER QUALITY IMPROVEMENTS USINS
REVEALED PREFERENCE METHODS WHEN
CORNER SOLUTIONS ARE PRESENT
Phaneuf et al. (1998) studied angling in Wisconsin Great
Lakes. They estimated changes in recreational fishing
values resulting from a 20 percent reduction of toxin levels
in lake trout flesh. The study uses a TC model to value
water quality improvements when corner solutions are
present in the data. Corner solutions arise when consumers
visit only a subset of the available recreation sites, setting
their demand to zero for the remaining sites. Phaneuf et al.
found that improved industrial and municipal waste
management results in general water quality improvement.
Table 1.7 presents findings from this study based on two
policy scenarios and four different model specifications.
Water Quality
20% reduction
Table
Change Valued
in toxins
Loss of South Lake Michigan
1.7: WeJ-
RNL!
$39.15!
$218.42!
:.o.r.e..Est.imoles..frQm
Adjusted to 1999$
RPRNL!
$11.79!
$132.05!
KT!
$156.36!
$1,140.11!
.J?.han.e.uf.
System!
$14.76!
$415.19!
et
.a| .(1
J
RNL!
$29.16!
$162.67!
99.80
Jtudy Values
RPRNL!
$8.78!
$98.34!
(1989$)
KT!
$116.45!
$849.09!
System
$10.99
$309.21
Location:
Estimating Approach:
Survey Population:
Wisconsin Great Lakes
TC models, including:
RNL: Repeated Nested Logit Model;
RPRNL: Random Parameters Repeated Nested Logit Model;
KT: Kuhn-Tucker Model; and
System: Systems of Demands Model
Wisconsin anglers; Great Lakes and inland anglers
7-6
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MP&M EEBA: Appendices
Appendix I: Selecting Values for Benefits Transfer
The Agency selected only one value for use in benefits
transfer for the following reasons:
* Environmental quality change. Only one policy
scenario evaluated in this study a 20 percent
reduction in the toxin levels in fish tissue is
compatible with the water quality changes expected
from the MP&M regulation (i.e., removal of
aquatic life-based AWQC exceedances. The
second scenario loss of South Lake Michigan
is irrelevant to the proposed regulation.
Research methods. Phaneuf et al. estimated four
different models and provided WTP estimates
based on each of them. The authors indicated,
however, that" the KT model comes closest to
matching the ideal theoretical model" (see authors
conclusions, page 1030). Other models either rely
on more restrictive assumptions or require
additional research. The Agency chose the value
from the KT model based on the authors'
recommendation, which is one of the selection
criteria for values used in the benefits transfer.
1-9
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MP&M EEBA: Appendices
Appendix I: Selecting Values for Benefits Transfer
GLOSSARY
ambient water quality criteria (AWQC): Levels of
water quality expected to render a body of water suitable for
its designated use. Criteria are based on specific levels of
pollutants that would make the water harmful if used for
drinking, swimming, farming, fish production, or industrial
processes. (http://www.epa.gov/OCEPAterms/aterms.html)
binary choice (BC): offers respondents to a contingent
valuation survey specific dollars and cents choices, for
example, would you be willing to pay between $10 and $20
per year to improve visibility at the Grand Canyon.
conjoint analysis: CJ is defined as "any decompositional
method that estimates the structure of consumer's
preferences... given his or her overall evaluations of a set of
alternatives that are prespecified in terms of levels of
different attributes. Price typically is included as an
attribute." (Green and Srinivasan, 1990).
contingent valuation (CV): a method used to determine
a value for a particular event, where people are asked what
they are willing to pay for a benefit and/or are willing to
receive in compensation for tolerating a cost. Personal
valuations for increases or decreases in the quantity of some
good are obtained contingent upon a hypothetical market.
The aim is to elicit valuations or bids that are close to what
would be revealed if an actual market existed.
(http://www.damagevaluation.com/glossary.htm)
corner solutions: a corner solution arise when a
consumer who has a choice of two goods, xl and x2, chooses
to consume no xl at the utility maximum.
direct question/open-ended (OE): in the OE approach,
respondents are asked the most they would be willing to pay
for the program or policy. This approach has a virtue of not
providing any hints about what might be a reasonable value.
This approach, however, confronts respondents with an
unfamiliar choice (i.e., placing a price on environmental
commodities). Studies that use the OE approach have high
item non-response rates.
fish consumption advisory (FCA): an official
notification of the public about specific areas where fish
tissue samples have been found to be contaminated by toxic
chemicals which exceed FDA action limits or other accepted
guidelines. Advisories may be species specific or
community wide.
intensity of preference (IP): the experimental design
allows individuals to state an intensity of preferences for or
against the alternative to the status quo. For example, the
individual designates they would "probably yes" or
"definitely yes" prefer the alternative to the status quo.
iterative bidding (IB): with IB, respondents are asked
whether they would be WTP a given amount. If the answer
is yes, this amount is raised in pre-set increments until the
respondent says that he will not pay the last amount given.
If the answer is no, then the amount is decreased until the
respondent indicates a willingness to pay the stated amount.
starting point bias: because survey interviewers suggest
the first bid this can influence the respondents answer and
cause the respondent to agree too readily with bids in the
vicinity of the initial bid.
(http://www.damagevaluation.com/glossary.htm)
travel cost (TC): method to determine the value of an
event by evaluating expenditures of recreators. Travel costs
are used as a proxy for price in deriving demand curves for
the recreation site.
(http://www.damagevaluation.com/glossary.htm)
willingness to pay (WTP): maximum amount of money
one would be willing to pay or give up to buy some good.
(http://www.damagevaluation.com/glossary.htm)
I-10
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MP&M EEBA: Appendices
Appendix I: Selecting Values for Benefits Transfer
ACRONYMS
AWQC: ambient water quality criteria
BC: binary choice
CV: contingent valuation
FCA: fish consumption advisory
IB: iterative bidding"
IP: intensity of preference
TC: travel cost
WTP: willingness to pay
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MP&M EEBA: Appendices Appendix I: Selecting Values for Benefits Transfer
REFERENCES
Boyle, K. J. and J.C Bergstrom. 1992. "Benefit Transfer Studies: Myths, Pragmatism and Idealism." Water Resources
Research, Vol. 28, No.3 pages 657-663, March.
Desvousges, W. H. et al. 1987. "Option Price Estimates for Water Quality Improvements: A Contingent Valuation Study
for the Monongahela River." Journal of Environmental Economics and Management, 14, pages 248-267.
Desvousges, W. H. et al. 1992. "Benefit Transfer: Conceptual Problems in Estimating Water Quality Benefits Using
Existing Studies." Water Resources Research, Vol. 28, No.3 pages 675-683, March.
Farber, S. andB. Griner. 2000. Valuing Watershed Quality Improvements Using Conjoint Analysis. University of
Pittsburgh, PA.
Fisher, A. and R. Raucher. 1984. "Intrinsic Benefits of Improved Water Quality: Conceptual and Empirical Perspectives."
In: Advances in Applied Microeconomics, Vol. 3, V.K. Smith, editor, JAI Press.
Jakus, P.M., M. Downing, M.S. Bevelhimer, and J.M. Fly. 1997. "Do Sportfish Consumption Advisories Affect Reservoir
Anglers' Site Choice?" Agricultural and Resource Economic Review, 26(2).
Lant, C. L. and R.S. Roberts. 1990. "Greenbelts in the Cornbelt: Riparian Wetlands, Intrinsic Values, and Market Failure."
Environment and Planning A, Vol. 22, pages 1375-1388.
Lyke, AJ. 1993. "Discrete Choice Models to Value Changes in Environmental Quality: A Great Lakes Case Study." PhD
dissertation, University of Wisconsin, Department of Agricultural Economics, Madison.
Montgomery, M. and M. Needelman. 1997. "The Welfare Effects of Toxic Contamination in Freshwater Fish." Land
Economics 73(2): 211-223.
Phaneuf, D. J., C. L. Kling, and J.A. Herriges. 1998. "Valuing Water quality Improvements Using Revealed Preference
Methods When Corner Solutions are Present." American Journal of Agricultural Economics 80, pages 1025-1031.
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