United States Office of Water (4303) EPA-821-R-01-002 Environmental Protection Washington, DC 20460 January 2001 Agency 

# Environmental and Economic Benefit Analysis of Proposed Revisions to the National Pollutant Discharge Elimination System Regulation and the Effluent Guidelines for Concentrated Animal Feeding OperationsENVIRONMENTAL AND ECONOMIC BENEFIT ANALYSIS OF THE PROPOSED

REVISIONS TO THE NATIONAL POLLUTANT DISCHARGE ELIMINATION SYSTEM REGULATION AND THE EFFLUENT GUIDELINES FOR CONCENTRATED ANIMAL FEEDING OPERATIONS

U.S. Environmental Protection Agency 1200 Pennsylvania Avenue NW Washington, DC 20460

January, 2001i TABLE OF CONTENTS

INTRODUCTION AND SUMMARY

................................... CHAPTER 1 1.1 Definition of CAFOs

................................................... 1-2 1.2 Current Issues Related to CAFOs

......................................... 1-3 1.2.1 Potential Environmental Impacts of CAFOs

........................... 1-4 1.2.1.1 Water Quality Impairments

.................................. 1-4 1.2.1.2 Ecological Impacts

......................................... 1-5 1.2.1.3 Human Health Effects

...................................... 1-5 1.2.2 Recent Industry Trends

........................................... 1-5 1.2.2.1 Increased Production and Industry Concentration

................. 1-6 1.2.2.2 Location of Animal Operations Closer to Consumer Markets

....... 1-6 1.2.2.3 Advances in Agriculture Production Practices to Manage and Dispose Manure

................................. 1-7 1.3 Proposed Changes to CAFO Regulations

................................... 1-7 1.3.1 Changes to NPDES Regulations

.................................... 1-7 1.3.2 Changes to ELGs

................................................ 1-9 1.3.3 Number of Regulated Operations

.................................. 1-10 1.4 Analytic Methods and Results

........................................... 1-10 1.5 Organization of Report

................................................ 1-11 1.6 References

.......................................................... 1-13

POTENTIAL IMPACTS OF AFOs ON ENVIRONMENTAL QUALITY AND HUMAN HEALTH

.................. CHAPTER 2 2.1 Pathways for the Release of Pollutants from AFOs

............................ 2-2 2.1.1 Overland Discharge

.............................................. 2-4 2.1.1.1 Surface Runoff

............................................ 2-4 2.1.1.2 Soil Erosion

.............................................. 2-4 2.1.1.3 Acute Events

............................................. 2-5ii TABLE OF CONTENTS (continued)

2.1.2 Leaching to Groundwater

.......................................... 2-6 2.1.3 Discharges to the Air and Subsequent Deposition

....................... 2-6 2.2 Potential Ecological Hazards Posed by AFO Pollutants

........................ 2-7 2.2.1 Nutrients and Eutrophication

....................................... 2-9 2.2.1.1 Nitrogen and Nitrogen Compounds

............................ 2-9 2.2.1.2 Phosphorus

.............................................. 2-10 2.2.1.3 Eutrophication

........................................... 2-12 2.2.2 Pathogens

..................................................... 2-12 2.2.3 Organic Compounds and Biochemical Oxygen Demand (BOD)

.......... 2-14 2.2.4 Solids and Siltation

............................................. 2-15 2.2.5 Salts and Trace Elements

......................................... 2-16 2.2.6 Odorous/Volatile Compounds

..................................... 2-17 2.2.7 Other Pollutants and Ecosystem Imbalances

.......................... 2-17 2.3 Human Health Impacts Related to AFO Pollutants

........................... 2-18 2.3.1 Health Impacts Associated with Nitrates

............................. 2-19 2.3.2 Health Impacts Associated with Algal Blooms

........................ 2-20 2.3.3 Health Impacts Associated with Pathogens

........................... 2-21 2.3.4 Health Impacts Associated with Trace Elements and Salts

............... 2-22 2.3.5 Other Health Impacts

............................................ 2-22 2.4 References

.......................................................... 2-24

CONCEPTUAL FRAMEWORK AND OVERVIEW OF METHODS

.......... CHAPTER 3 3.1 Possible Environmental Improvements and Resulting Benefits

.................. 3-1 3.2 Specific Benefits Analyzed

.............................................. 3-3 3.3 Predicting Change in Environmental Quality and Resulting Beneficial Use

......... 3-4 3.4 Valuing Benefits

...................................................... 3-6 3.4.1 Overview of Economic Valuation

................................... 3-6 3.4.2 Primary Approaches for Measuring Benefits

........................... 3-7iii TABLE OF CONTENTS (continued)

3.4.3 Valuation of CAFO Regulatory Benefits Based on Previous Studies

........ 3-8 3.4.4 Aggregating Benefits

............................................. 3-9 3.5 Summary

........................................................... 3-10 3.6 References

.......................................................... 3-11
MODELING OF IMPROVEMENTS IN SURFACE WATER QUALITY AND BENEFITS OF ACHIEVING RECREATIONAL USE LEVELS

.......... CHAPTER 4 4.1 Introduction and Overview

.............................................. 4-1 4.2 Model Facility Analysis

................................................. 4-2 4.3 Edge-of-Field Loadings Analysis

.......................................... 4-6 4.3.1 Loadings from Manure Application

.................................. 4-6 4.3.2 Loadings from Lagoons and Other Storage Structures

................... 4-7 4.3.3 Loadings from Feedlots

........................................... 4-8 4.3.4 Model Loadings Under Regulatory Scenarios

.......................... 4-8 4.4 Analysis of AFO/CAFO Distribution

...................................... 4-9 4.4.1 Approach

...................................................... 4-9 4.4.2 Estimated Number of AFOs and CAFOs

............................. 4-11 4.4.3 Geographic Placement of Facilities

................................. 4-13 4.5 Surface Water Modeling

............................................... 4-13 4.5.1 Defining the Hydrologic Network

.................................. 4-15 4.5.2 Distributing AFOs and CAFOs to Agricultural Land

................... 4-16 4.5.3 Calculating AFO/CAFO-Related Loadings to Waterbodies

.............. 4-16 4.5.4 Loadings from Other Sources

..................................... 4-16 4.5.5 Fate and Transport Modeling

...................................... 4-17 4.5.6 Estimated Changes in Loadings

.................................... 4-17 4.6 Valuation of Water Quality Changes

...................................... 4-17 4.6.1 Support of Designated Uses

....................................... 4-22 4.6.2 Application of CV Study

......................................... 4-23 4.6.3 Estimated Benefits

.............................................. 4-25iv TABLE OF CONTENTS (continued)

4.7 References

.......................................................... 4-26 Appendix 4-A: NWPCAM Calculation of the Economic Benefits of Improved Surface Water Quality

.............................................. 4A-1

REDUCED INCIDENCE OF FISH KILLS

................................ CHAPTER 5 5.1 Introduction

.......................................................... 5-1 5.2 Analytic Approach

..................................................... 5-2 5.2.1 Data Sources and Limitations

...................................... 5-2 5.2.2 Predicted Change in Fish Kills Under Alternate CAFO Regulations

........ 5-4 5.2.2.1 Baseline Scenario

.......................................... 5-4 5.2.2.2 Regulatory Scenarios

....................................... 5-7 5.2.3 Valuation of Predicted Reduction in Fish Kills

......................... 5-8 5.3 Results

............................................................. 5-10 5.4 Limitations and Caveats

................................................ 5-10 5.5 References

.......................................................... 5-11 Appendix 5-A: Calculation of Annual Benefits Using Minimum and Maximum Fish Replacement Values

........................................... 5A-1

IMPROVED COMMERCIAL SHELLFISHING

........................... CHAPTER 6 6.1 Introduction

.......................................................... 6-1 6.2 Analytic Approach

..................................................... 6-1 6.2.1 Data on Shellfish Harvest Restrictions Attributed to AFOs

............... 6-1 6.2.2 Estimated Impact on Shellfish Harvests

.............................. 6-4 6.2.2.1 Baseline Annual Shellfish Landings

........................... 6-5 6.2.2.2 Estimated Acreage of Harvested Waters

........................ 6-5v TABLE OF CONTENTS (continued)

6.2.2.3 Average Annual Yield of Harvested Waters

..................... 6-6 6.2.2.4 Characterization of Waters that are Unharvested Due to Pollution from AFOs

....................... 6-6 6.2.2.5 Estimated Impact of Pollution from AFOs on Commercial Shellfish Landings

............................... 6-7 6.2.3 Estimated Impact of Alternate Regulations on Commercial Shellfish Harvests

..................................... 6-8 6.2.4 Valuation of Predicted Change in Shellfish Harvests

.................... 6-9 6.2.4.1 Characterization of Consumer Demand for Shellfish

............. 6-11 6.2.4.2 Determining the Change in Consumer Surplus Associated with Increased Harvests

........................... 6-11 6.3 Results

............................................................. 6-13 6.4 Limitations and Caveats

................................................ 6-14 6.5 References

.......................................................... 6-15

REDUCED CONTAMINATION OF PRIVATE WELLS

.................... CHAPTER 7 7.1 Introduction

.......................................................... 7-1 7.2 Analytic Approach

..................................................... 7-3 7.2.1 Relationship Between Well Nitrate Concentrations and Nitrogen Loadings

............................................... 7-3 7.2.1.1 Included Variables and Data Sources

.......................... 7-3 7.2.1.2 Omitted Variables

......................................... 7-6 7.2.2 Modeling of Well Nitrate Concentrations Under Alternate Regulatory Scenarios

............................................. 7-6 7.2.3 Discrete Changes from above the MCL to below the MCL

............... 7-7 7.2.4 Incremental Changes below the MCL

................................ 7-8 7.2.5 Valuation of Predicted Reductions in Well Nitrate Concentrations

......... 7-9 7.2.5.1 Poe and Bishop (1992)

..................................... 7-11 7.2.5.2 Crutchfield et al. (1997)

.................................... 7-12 7.2.5.3 De Zoysa (1995)

.......................................... 7-13 7.2.5.4 Adjustments to the Values

.................................. 7-13vi TABLE OF CONTENTS (continued)

7.2.5.5 Timing of Benefits

........................................ 7-14 7.3 Results

............................................................. 7-15 7.4 Limitations and Caveats

................................................ 7-15 7.5 References

.......................................................... 7-19 Appendix 7-A: Model Variables

.............................................. 7A-1 Appendix 7-B: The Gamma Model

............................................ 7B-1 Appendix 7-C: Literature Search and Evaluation

.................................. 7C-1

INTEGRATION OF RESULTS

........................................ CHAPTER 8 8.1 Introduction

.......................................................... 8-1 8.2 Integration of Analytic Results

........................................... 8-1 8.3 Present Value of Benefits

................................................ 8-2 8.4 Annualized Benefits Estimates

........................................... 8-6 8.5 Limitations of the Analysis and Implications for Characterizing Benefits

.......... 8-8 Appendix 8-A: Impact of Alternative Time Frames on Present Value and Annualized Benefits Estimates

............................................... 8A-1 Appendix 8-B: Calculation of Present Values

.................................... 8B-1 Appendix 8-C: Calculation of Annualized Benefits

................................ 8C-11-1

INTRODUCTION AND SUMMARY CHAPTER 1

The U.S. Environmental Protection Agency (EPA) is revising and upd ating the two primary regulations that ensure that manure, wastewater, and other process waters generated by concentrate d animal feeding operations (CAFOs) do not impair water quality. EPA's proposed regulatory change s affect the existing National Pollutant Discharge Elimination System (NPDES) provisions that defin e and establish permit requirements for CAFOs, and the existing effluent limitations guidelines (ELGs ) for feedlots, which establish the technology-based effluent discharge standard that is applied t o specified CAFOs. Both of these existing regulations were originally promulgated in the 1970s. EP A is revising the regulations to address changes that have occurr ed in the animal industry sectors over the last 25 years, to clarify and improve implementation of CAFO requirements, an d to improve the environmental protection achieved under these rules. This repo rt addresses the environmental and economic benefits of several alternativ e regul atory

scenarios, including two scenarios that EPA is proposing. It examines in detail fou r environmental quality improvements that would result from the regulatory changes: improvements in the suitability of freshwater resources for fishing and swimming; r educed incidence of fish kills; improved commercial shellfishing; and reduced contamination of private wells. Because these are not the only beneficial impacts of the regulatory scenarios considered by EPA — and because, in gen eral, EPA takes a conservative approach to quantifying the benefits analyzed — the Agenc y belie ves that this report presents a lower-bound estimate of the beneficial impacts of the proposed scenarios. This chapter first defines and describes animal feeding operations and CAFOs, then briefly summ arizes the environmental problems and industry changes associated with animal feedin g operatio ns that EPA is addressing with its proposed regulations. Finally, the chapter outlines th e regulatory changes and alternatives that EPA is considering, and provides a summary of the method s and results of the more detailed benefits analyses presented in the remaining chapters.Animal units are defined in EPA's current regulations at 40 CFR 122 and vary by animal 1 type. An AU is considered equivalent to one beef cow. 1-2 1.1 DEFINITION OF CAFOS The term CAFO is a regulatory designation that describes cer tain animal feeding operations (AFOs). AFOs are defined by federal regulation as lots or fa cilities where animals "have been, are, or will be stabled or confined and f ed or maintained for a total of 45 days or more in any 12 month period and crops, vegetation forage growth, or post-harvest residues are not sustained in the normal gr owing season over any portion of the lot or facility" (40 CFR 122.23(b)(1)). AFOs congregat e animals on a small land area where feed must be brought to the animals. Winter feeding of animals on pasture or rangeland is not normally considered an AFO. Current EPA regulations employ a three-tier structure to identify AFOs that are subject t o regulation as CAFOs. Tier 1 facilities include any animal feeding operation whe re more than 1,000 "animal units" (AUs) ar e confined; such facilities are by definition CAFOs unless discharges from the operation occur only as the result of a 25-year, 24-hour (or more severe) storm event. Tier 2 1 facilities include AFOs that confine 301 to 1000 AUs; these facilities are defined as CAFOs if:

• Polluta nts are discharged into navigable waters through a manmade ditch , flushing system, or other similar man-made device; or

• Pollutant s are discharged directly into waters that originate outside of an d pass over, across, or through the facil ity or come into direct contact with the confined animals.

The regulatory definition of a CAFO does not extend to operations with 300 or fewer AUs (i.e., Tie r 3 facilities). Under certain circumstances, however (e.g., a facility causing significan t surface water impairment), a permitting authority may designate such facilities as CAFOs. Current CAFO regulations address only those facilities with wet-manure managemen t systems; this eliminates most poultry operations from regulation under the Clean Water Act becaus e they use dry manure management systems. In addition, the current definition of CAFO includes onl y swine over 55 pounds and mature dairy cat tle, assuming that immature swine and heifers would be raised in the same operations as adults. As a result, the regulatory definition does not address th e "stand-alone" immature swine or heifer operations that have proliferated in the last two decades. USDA reports that there were 1.2 million livestock and poultry operations in the Unite d States in 199 7. This number includes all operations that raise beef or dairy cattle, hogs, chicken s (broilers or layers), and turkeys , and includes both confinement and non-confinement (i.e., grazingEPA's proposed regulatory changes do not address certain types of animal confinemen t 2 operati ons, such as farms that raise sheep, lambs, goats, horses, and other miscellaneous anima l species, as well as nontraditional animals, such as bison and various exotic species. 1-3 and range fed) production. Of these, EPA estimates that there are about 376,000 AFOs that rais e 2 or house animals in confinement, as defined by the existing regulations. For many of the anima l sec tors, it is not possible to estimate from available data what proportion of the total livestoc k operations have feedlots (i.e., confinement) and what proportion are grazing operations only. For analytical purposes, EPA has therefore assumed that all dairy, hog, and poultry operations are AFOs

. Exhibit 1-1 summarizes the estimated total number of AFOs of all sizes in each of the four majo r livestock categories, based on 1997 data. EPA estimates that only a subset of these AFOs will be regulated as CAFOs.

Exhibit 1-1 NUMBER OF ANIMAL FEEDING OPERATIONS

(based on 1997 data) Sector Total AFOs Beef operations, including both cattle and veal operations. 106,930 Dairy operations, including both milk and heifer operations. 118,130 Hog operations, including both "farrow to finish" and "grower to finish" operations. 117,860 Poultry operations, including broilers, layers (both wet and dry operations) and turkeys. 123,750 Sum Total 466,670 Total AFOs 375,740

1 Source: EPA estimates derived from published USDA/NASS data, including 1997 Census of Agriculture. For mor e information, see Technical Development Document of Proposed Effluent Limitations Guidelines for Animal Feeding Operations

. "Total AF Os" eliminates double counting of operations with mixed animal types. Based on survey leve l 1 Census data, operations with mixed animal types account for roughly 20 percent of total AFOs.

1.2 CURRENT ISSUES RELATED TO CAFOS AFOs (including CAFOs) pr oduce and manage large amounts of animal waste, most in the form of manure. USDA estimates that 291 billion pounds (132 million metric tons) of "as excreted " manure wer e generated in 1997 from major livestock and poultry operations. Despite the existing ELG and NPDES regulations that define CAFOs and regulate their discharges, the management of animal wastes at AFOs has continued to be associated with environmental problems, including larg e spills of manure, fish kills, and outbreaks of Pfiesteria . In addition, industry changes in recent year s may contribute to an d exacerbate the problems caused by releases of manure from AFOs. EPA is revising the existing regulations with the following goals:The National Water Quality Inventory 1998 Report to Congress notes that 28 states an d 3 tribes reported impairment by agricultural subcategory. Specifically, these states and tribes repo rted that ani mal feeding operations degraded 16 percent of impaired river miles; range and pastur e grazin g degraded 11 and 6 percent of impaired river miles, respectively; and irrigated and non

irrigated crop production degraded 18 and 27 percent of impaired river miles, respectively. 1-4 • To address reports of continued discharge and runoff of manure and nutrient s from livestock and poultry farms;

• To update the existing regulations to reflect structural changes in thes e industries over the last few decades; and

• To improve the effectiveness of the CAFO regulation.

Below we summarize the potential environmental impacts of manure releases from AFOs, and outline the recent industry changes that may exacerbate these impacts.

1.2.1 Potential Environmental Impacts of CAFOs Manure management practices at AFOs can include storage in piles or in open waste lagoons , follo wed by land application to agricultural fields as fertilizer. While some discharges fro m regula ted CAFOs are governed as point sources, unregulated releases of manure from waste pile s or lagoons and overapplication of manure to agricultural lands can affect nearby surface an d groundwater. National and local studies have confirmed the presence of manure pollutants in surfac e waters. Once contaminants from manure have reached surface waters they can cause a variety o f ecological and human health problems, including water quality impairments, ecological impacts, an d human health effects from recreational exposure or from contaminated drinking water.

1.2.1.1 Water Quality Impairments EPA's 1998 National Water Quality Inventory , prepared under Section 305(b) of the Clean Water Act, identifies agricult ure (including irrigated and non-irrigated crop production, rangeland, feedlots, pastureland, and animal holding areas) as the leading contributor to identified water qualit y impairments in the nation’s rivers and lakes, and the fifth leading contributor to identified wate r quality imp airments in the nation’s estuaries. The report also identifies the key pollutants an d stre ssors that impair the nation's waters. Among the most problematic pollutants are several

- inc luding pathogens, nutrients, and oxygen depleting substances - that are associated commonly , although not exclusively, with animal waste. 31-5

1.2.1.2 Ecological Impacts
T h e most dramatic ecological impacts associated with manure pollutants in surface waters are massive fish kills. Incomplete records indicate that every year dozens of fish kills associated wit h AFOs result in the deaths of hundreds of thousands of fish. In addition, manure pollutants such as nutrients and suspended solids can seriously disrupt aquatic systems by over-enrich ing water (in the case of nutrie nts) or by increasing turbidity (in the case of solids). Excess nutrients caus e fast-grow ing algae blooms that reduce the penetration of sunlight in the water column, and reduce the amou nt of available oxygen in the water, reducing fish and shellfish habitat and affecting fis h and invertebrates. Ma

nure pollutants can also encourage the growth of toxic organisms, including Pfi esteria , which has also been associated with fish kills and fish disease events. Reduction i n biodiv ersity

due to animal feeding operations has also been documented; for example, a study o f three Indiana stream systems found fewer fish and more limited diversity of fish species downstrea m of CAFOs than were found downstream of study reference sites.

1.2.1.3 Human Health Effects Manu re contains over 100 human pathogens; contact with some of these pathogens during recreational activities in surface water can result in infectio ns of the skin, eye, ear, nose, and throat. Eutrophication due to excess nutrients can also promote blooms of a variety of organisms that are to xic to humans either through ingestion or contact. This includes the estuarine dinoflagellat e Pfiesteria piscicida. While Pfiesteria is primarily associated with fish kills and fish disease events, the organism has also been linked with human health impacts through dermal exposure. Finally , even with no visible signs of algae blooms, shellfish such as oysters, clams and mussels can carry toxin s produced by some types of algae in their tissue. These can affect people who ea t contaminated shellfish. Contaminants from manure, including nitrogen, algae, and pathogens, can also affect huma n healt h through drinking water sources and can result in increased drinking water treatment costs

. Fo r example, nitrogen in manure can be transported to drinking water as nitrates, which ar e associated with human health risks. EPA h as identified nitrate as the most widespread agricultural conta minant

in drinking water wells. Algae blooms triggered by nutrient pollution can affec t drinking water by clogging treatment plant intakes, producing objectionable tastes and odors, an d reacting with the chlorine used to disinfect drinking water to produce harmful chlorinated byproduct s (e.g., trihalomethanes).

1.2.2 Recent Industry Trends Since EPA promulgated the existing ELG and NPDES regulation s governing CAFOs in the 1970s, a number of trends in the livestock and poultry industries have influenced the nature o f pollution from AFOs and the potential for contamination of surface and gr oundwater. These trendsThis more than two-fold increase in the number of broilers raised annually signals the need 4 to review t

he existing CAFO regulations, which effectively do not cover broiler operations sinc e virtually no such operations use wet manure management systems. 1-6 include a co mbination of industry growth and concentration of animals on fewer, larger farms ; location of farms closer to population centers; and advances in farm p roduction practices and waste management te chniques. The changes in the industry have limited the effectiveness of the current regulations that define and govern releases from CAFOs.

1.2.2.1 Increased Production and Industry Concentration U.S. livestock and poultry production has risen sharply since the 1970s, resulting in a n increase in the amount of manure and wastewater generated annually. The Census of Agriculture reports 19 97 turkey sales of 299 million birds, compared to 141 million sold in 1978. Sales o f broi lers increased to 6.4 billion in 1997 from 2.5 billion in 1974. Red meat production also rose 4 during the 1 974-1997 period; the number of hogs and pigs sold in 1997 totaled 142.6 million , compared to 79.9 million in 1974. As production has increased, the U.S. livestock and poultry sectors have also consolidated an imal production into a smaller number of larger-scale, highly specialized operations tha t concentrate more animals (and m anure) in a single location. At the same time, significant gains in production efficiency have increased per-animal yields and the rate of turnover of animals between farm and market. These large AFOs can present considerable environmental risks, because they ofte n do not have an adequate land base for manure disposal through land application. As a result, large facilities must incur the risks associated with storing significant volumes of manure, or must attemp t to maximize the application of manure to the limited land they have available. By comparison , smaller AFOs manage fewer animals and tend to concentrate less manure nutrients at a singl e location. These operations are more likely to have sufficient cropland and fertilizer needs to lan d apply manure nutrients generated at a livestock or poultry business.

1.2.2.2 Location of Animal Operations Closer to Consumer Markets Since the 1970s, the combined forces of population growth and re-location of operation s closer to consumer markets and processing sectors have resulted in more AFOs located near densel y populated areas. Surface waters in the se areas face additional stresses from urban runoff and other point sour ces. The proximity of large AFOs to human populations thus increases the potential for human health impacts and ecological damage if manure and wastewater at AFOs is improperl y discharged.1-7

1.2.2.3 Advances in Agriculture Production Practices to Manage and Dispose Manure Continued research by USDA, state agencies and universities has led to advances i n technolo gies and management practices that minimize the potential environmental degradatio n attributable to discharge and runoff of manure and wastewater. Today, there are many mor e practicable

options to properly collect, store, treat, transport, and utilize manure and wastewater tha n there were in the 1970s, when the existing regulations were instituted. As a result, curren t regulations do not reflect the full range of management practices and technologies that may b e impl emented to achieve greater protection of the environment (e.g., by more effectively treatin g certain constituents present in animal manure or by converting manure into a more marketable form)

. In additi on, during the time since promulgation of the existing regulation, certain practices hav e proven to be relatively less protective of the environment. There is documented evidence tha t lagoons may leak if not properly maintained, and evidence of overapplication of manure and nutrien t saturation of soils in some parts of the country.

1.3 PROPOSED CHANGES TO CAFO REGULATIONS
In response to persistent reports of environmental problems, and to changes in the industries and technologies associated with AFOs, EPA is proposing changes to both the NPDES regulations for CAFOs and the ELG r egulations for feedlots. Proposed changes to the NPDES regulations for CAFOs affect which animal feeding operations are defined as CAFOs and are therefore subject to the NPDES permit program. Changes to the ELG regulations for feed lots affect which technologybased requirements will apply to CAFOs. EPA' s analysis of the benefits of revised regulations considers four alternatives for th e NPDE S definition of a CAFO (described as Scenarios 1, 2/3, 4a, and 4b), combined with tw o alt ernative ELG regulations (Options 1 and 2), yielding a total of eight regulatory scenarios. EPA is co-proposing two of these scenarios. The first incorporates NPDES scenario 2/3 and ELG Optio n 2; thi s scenario would preserve the current three-tier structure for identifying facilities that ar e CAFOs (though with r evised conditions for identifying CAFOs within the tiers), and would revise the ELG to establish a phosphorus-based manure application limit. The second proposed scenario incorporates NPDES scenario 4a and ELG Option 2; this scenario would replace the current threetier struct ure with a two-tier structure, and would also incorporate a phosphorus-based ELG

. Specific proposed changes a re described in more detail below, and are summarized in Exhibit 1-2.

1.3.1 Changes to NPDES Regulations EPA considered four regulatory scenarios that reflect changes to the current approach t o determining which facilities are CAFOs that are subject to NPDES requirements. Scenario 1 would retain the existing three-tier structure for identifying CAFOs (described in section 1.1). Scenario 2/ 3 would also retain the current three-tier structure, but would revise the condi tions within the tiers for determining which facilities are CAFOs. Scen ario 4a would replace the current three-tier structureEach of the regulatory scenarios analyzed also reflects sev eral proposed structural changes 5 that would revise the CAFO definition and permit require ments under the NPDES permit program. For example, EPA is proposing to include dry poultry and stand-alone immature swine and heifer operations as AFOs; this change would increase the number o f facilities that meet the definition of a CAFO and must obtain an NPDES permit. In addition, EPA is proposing several clarification s designed to assure that all facilities meeting the CAFO definition obtain an NPDES permit

. Similarl y, EPA is proposing changes to the ELGs for feedlots that would clarify the developmen t of technical standards for manure storage and la nd application operations. These changes from the current baseline are reflected in all of the regulatory scenarios. 1-8 with a two-tier structure that would alt er the definition of a CAFO to include all AFOs with 500 or more AU s; operations with fewer than 500 AUs would be regulated at the discretion of th e permitting authority (si milar to the current Tier 3 facilities). Finally, Scenario 4b would change to a t wo-tier structure similar to that in Scenario 4a, but would define as a CAFO any operation with 300 or more animal units. 5
As noted above, EPA has chosen to co-propose N PDES Scenario 2/3 and NPDES Scenario 4a. I n doing so, the Agency is soliciting comments on regulatory approaches that, on a nationa l ba sis, yield similar environmental benefits, but offer different administrative benefits and hav e differing impacts on regulated industry sectors. Specifically:

• Scenario 2/3 would apply a three-tier structure combined with a risk-base d approach to identify which AFOs pose a potential to discharge. This scenari o would automatically define all operations over 1,000 AUs as CAFOs. AFOs with bet ween 300 and 1,000 AUs would be required to either apply for a

n NPDES permit or certify to the permitting authority that they do not meet an y of the conditions that define a CAFO. An advantage of this approach is that it would offer states flexibility in developing requirements and programs tha t could reduce the number of facilities needing NPDES permits. A potential disadvantage, however, is the com plexity associated with administering this app roach, as well as the cost associated with extending th e certification/application requirement to facilities as small as 300 AUs.

• In contrast to Scenario 2/3, the two-tier structure of Scenario 4a would defin e all operations with at least 500 AUs as CAFOs. As such, all facilities wit h at least 500 AUs would be required to obtain and comply with an NPDE S permit; ope rations with fewer than 500 AUs would be subject to permitting only i f designated by the permitting authority as a significant contributor of pollution. An advantage of this approach is that it simplifies the structure of the regulations and supports EPA's goal of clarifying their scope. In addition , operations with at least 300 but fewer than 500 AUs would not automaticall y incur permitting or certification costs; however, the potential benefit s associated with a more flexible, risk-based approach to permitting operation s with between 500 and 1,000 AUs would be foregone.1-9 Exhibit 1-2 REGULATORY SCENARIOS CONSIDERED IN

THE BENEFITS ANALYSIS Regulatory Scenario NPDES Revisions ELG Revisions Baseline CAFOs include any AFO with over 1,000 AUs, as well as AFOs with Manure application

fewer AUs that meet certain requirements. not regulated Option 1- Baseline scenario plus dry poultry and immature swine and heifer Nitrogen-based Scenario 1 operations. manure application Option 1- New NPDES conditions for identifying CAFOs among AFOs with 300 Nitrogen-based Scenario 2/3 - 1000 AUs, plus dry poultry and immature swine and heifer operations. manure application Option 1- CAFOs include all AFOs with 500 or more AUs, plus dry poultry, Nitrogen-based Scenario 4a immature swine and heifer operations. manure application Option 1- CAFOs include all AFOs with 300 or more AUs, plus dry poultry, Nitrogen-based Scenario 4b immature swine and heifer operations. manure application Option 2- Baseline scenario plus dry poultry and immature swine and heifer Phosphorus-based Scenario 1 operations. manure application Option 2- New NPDES conditions for identifying CAFOs among AFOs with 300 Phosphorus-based Scenario - 1000 AUs, plus dry poultry and immature swine and heifer operations. manure application 2/3* Option 2- CAFOs include all AFOs with 500 or more AUs, plus dry poultry, Phosphorus-based Scenario 4a* immature swine and heifer operations. manure application Option 2- CAFOs include all AFOs with 300 or more AUs, plus dry poultry, Phosphorus-based Scenario 4b immature swine and heifer operations. manure application * Proposed scenarios
.

1.3.2 Changes to ELGs EPA' s proposed changes to the effluent limitation guidelines would include a technica l standard for nutrient-b ased land application of manure. The Agency is considering two regulatory options. Option 1 would limit manure application to a nitrogen-based agronomic application rate (i. e., manure application could not exceed the soil and crop demand for the nitrogen within th e manure)

. Option 2 would limit manure application to a phosphorus-based agronomic applicatio n rate (i.e., manure application cou ld not exceed the soil and crop demand for the phosphorus within the manure).1-10

EPA's proposed regulatory scenarios both reflect the phosphorus standard . Because manure is phosphorus rich, nitrogen-based manure application is likely to result in application of phosphoru s in exce ss of crop requirements. Although excess phosphorus does not usually harm crops and i s often ads orbed by soils, the capacity of soil to adsorb phosphorus will vary by soil type. Recen t observ ations indicate that soils can and do become saturated with phosphorus. When saturatio n occurs, continued application of phosphorus in excess of what can be used by the crop and soil will result in phosphorus leaving the field with storm water via leaching or runoff; eutrophication o f surface waters can result.

1.3.3 Number of Regulated Operations EPA has estimated the likely number of AFOs that would be regulated under the revise d definition of CAFO in each of the four NPDES scenarios (i.e., Scenarios 1, 2/3, 4a, and 4b). EPA analyzed data from the USDA's 1997 Census of Agriculture to identify AFOs and CAFOs. EPA firs t determined the number of operations that raise animals under confinement by using available data on the total number of livestock and poultry facilities. Next, EPA determined the number of CAFO s based on the number of facilities that discharge or have the potential to discharge to U.S. waters a nd which meet a minimum size threshold (i.e., number of animals) as defined by the regulatory options

. Exhibit 1-3 shows the number of CAFOs estimated for each scenario.

1.4 ANALYTIC METHODS AND RESULTS To determine the economic benefits of the regulatory scenarios, EPA performed four separat e anal yses of expected changes in environmental quality that would likely result from reduced AFO pollution. These include:

• Impr ovements in Water Quality and Suitability for Recreationa l Act ivities: this analysis estimates the economic value of improvements i n inland surface water quality that would increase opportunities for recreationa l fishing and swimming;

• Reduced Incidence of Fish Kills: this analysis estimates the economi c val ue of a potential reduction in the number of fish kills caused by AFO

related waste;

• Improved Commercial Shellfishing: this analysis characteriz es the impact of po llution from AFOs on access to commercial shellfish growing waters , and value s the potential increase in commercial shellfish harvests that ma y result from improved control of that pollution; and1-11 Exhibit 1-3 ESTIMATED NUMBER OF CAFOS UNDER ALTERNATIVE REGULATORY SCENARIOS* Production Currently NPDES NPDES NPDES NPDES Sector Regulated Scenario 1 Scenario 2/3 Scenario 4a Scenario 4b Beef 2,220 2,290 2,720 3,080 4,080 Dairy 3,150 3,560 5,430 3,760 7,140 Heifers 620 590 830 800 1,050 Veal 20 20 70 90 210 Swine 5,260 5,630 7,520 8,550 14,370 Layers 470 870 1,420 1,640 2,050 Broilers 620 4,320 13,830 9,780 14,140 Turkeys 50 420 1,680 1,280 2,100 Total 12,410 17,700 33,500 28,980 45,140 * AFOs with more than one animal type are counted more than once; numbers have been rounded to nearest ten.

• Red uced Contamination of Private Wells: this analysis examines th e impa ct of the revised regulations on groundwater quality, and value s predicted improvements in the quality of aquifers that supply private wells. Exhibit 1-4 summarizes the results of these four studies for each of the regul atory scenarios. It is important to note that these results are not intended to represent the total value of all benefit s assoc iated with a reduction in AFO pollutants; they include only the subset of benefits that i s addressed by EPA's analyses. Moreover, EPA 's analyses generally take a conservative approach to quantifying benefits; therefore, the results are likely to reflect conservative estimat es of the specific benefits that EPA has examined.

1.5 ORGANIZATION OF REPORT The remainder of this report presen ts EPA's analysis of the benefits expected under each of the regulatory scenarios considered. Specifically:

• Ch apter

2 provides a detailed description of the potential impacts of AFO s on environmental quality and human health;1-12 Exhibit 1-4 ESTIMATED ANNUALIZED BENEFITS OF CHANGES IN REGULATION OF CAFOS (1999 dollars, millions)

Regulatory Scenario Benefits Fish Kills Shellfishing Pollution Total Recreational Reduced and Non-use Reduced Improved Private Well
Option 1- Scenario 1 $4.9 $0.1 - $0.2 $0.1 - $1.8 $33.3 - $49.0 $38.4 - $55.9 Option 1- Scenario 2/3 $6.3 $0.1 - $0.3 $0.2 - $2.4 $33.3 - $49.1 $39.9 - $58.0 Option 1- Scenario 4a $5.5 $0.1 - $0.3 $0.2 - $2.2 $35.5 - $52.2 $41.2 - $60.2 Option 1- Scenario 4b $7.2 $0.1 - $0.3 $0.2 - $2.6 $35.5 - $52.2 $43.0 - $62.3 Option 2- Scenario 1 $87.6 $0.2 - $0.3 $0.2 - $2.1 $35.4 - $52.1 $123.3 - $142.1 Option 2- Scenario 2/3* $127.1 $0.2 - $0.4 $0.2 - $2.7 $35.4 - $52.1 $163.0 - $182.3 Option 2- Scenario 4a* $108.5 $0.2 - $0.4 $0.2 - $2.4 $36.6 - $53.9 $145.5 - $165.1 Option 2- Scenario 4b $145.0 $0.2 - $0.4 $0.2 - $3.0 $36.6 - $53.9 $182.1 - $202.2 * Proposed scenarios.

• Chapte r

3 describes the range of benefits that would result from decrease d AFO loadings, and outlines EPA's general approach to quantifying an d valuing the subset of benefits analyzed;

• Chapter

4 assesses the value of changes in surface water quality that would result from a re duction in AFO loadings, focusing on changes in the quality of freshwater resources that would improve their suitability for fishing an d swimming;

• Chapter 5 assesses the value of reducing the incidence of fish kill s attributable to pollution from AFOs;

• Chapter 6 assesses the value of improved commercial shellfishing resulting from decreased AFO loadings;

• Chapter 7 assesses the value of reduced contamination of private well s associated with reductions in the pollution of groundwater by AFOs; and

• Chapter 8 provides the summary and conclusions of the benefits analysis.1-13

1.6 REFERENCES USDA/USEPA

(U.S. Department of Agriculture and U.S. Environmental Protection Agency). 1999

. Unified National Strategy for Animal Feeding Operat ions , Section 4.2. Available on EPA's web site at: http://www.epa.gov/owm/finafost.htm#1.0.This document uses the term manure to refer to both "solid" manure and urine, since these 6 wastes are typically managed together. Additional animal wastes associated with AFOs (e.g., hair, feathers, bedding material and carcasses) are identified separately in the discussion. The National Water Quality Inventory 1998 Report to Congress notes that 28 states and 7 tribes reported impairment by agricultural subcategory. Specifically, these states and tribes repo rted that ani mal feeding operations degraded 16 percent of impaired river miles; range and pastur e grazin g degraded 11 and 6 percent of impaired river miles, respectively; and irrigated and non

irrigated crop production degraded 18 and 27 percent of impaired river miles, respectively. 2-1 POTENTIAL IMPACTS OF AFOS ON ENVIRONMENTAL QUALITY AND HUMAN HEALTH CHAPTER 2

Animal ma nure, the primary cause of pollution related to AFOs, contains a variety o f pollutants that can cause environmental degradation, particularly when released to surface waters in large quantities. Documented releases from AFO s have been associated with a number of adverse 6 human health and ecological impacts, including fish kills, disease outbreaks, and degradation o f water quality and aquatic life. EPA's 1998 National Water Quality Inventory , prepared under Section 305(b) of the Clean Water A ct, presents recent information on impaired water bodies nationwide. The Inventor y identifies agriculture (includi ng irrigated and non-irrigated crop production, range grazing, pasture grazing, an d animal feeding operations) as the leading contributor to identified water qualit y impairments in the nation’s rivers and lakes, and the fifth leading contributor to identified wate r quality imp airments in the nation’s estuaries. The report also identifies the key pollutants an d stre ssors that impair the nation's waters. Among the most problematic pollutants are several

- inc luding pathogens, nutrients, and oxygen depleting substances - that are associated commonly , although not exclusively, with animal waste (USEPA, 2000). 7
The animal waste management practices and pollutant transport pathways that can lead t o contamination of surface waters are well known. Animal wastes at AFOs are typically managed by land a pplication and/or storage in waste piles or lagoons. Land application and storage of manure are centuries-old farming practices. In small or low-density farming operations these methods pose2-2

min imal pollution potential. AFOs, however, manage large amounts of manure in a concentrate d area. Under these circumstances, the following waste management failures pose an increase d potential for pollution:

• Over-application of manure: While land application of manure can provid e valua ble nutrients to soil and crops, the capacity of soil and crops to absorb nut rients over any given period is limited. Excess manure applied t o cropland can damage crops and soil, and is more likely to run off into surfac e waters or be released to air through volatilization or erosion (for example , through spray application)..

• Runo ff

from uncovered manure piles: Manure piles are frequently use d for temporary storage of animal wastes. Precipitation may wash pollutant s from uncovered manure piles into nearby surface waters.

• Lagoo n failures: AFOs frequently store large quantities of manure i n lagoons prior to land application or other disposal. While lagoons ar e design ed to prevent the release of wastes into the environment, they ar e subject t o various types of failure, including spills due to overfilling ; washouts in floods; liner failures; failures of dikes, pipes, or other above

ground structures; and accidental and intentional operator-related releases.

This chapter briefly describes the pathways, pollutants, and environmental and human health e ffects assoc iated with releases from AFOs. More detailed information is available in Environmenta l Assessm ent

of the Proposed Effluent Limitation Guidelines for Concentrated Animal Feedin g Operations (available in Section 8.1 of the Record).

2.1 PATHWAYS FOR THE RELEASE OF POLLUTANTS FROM AFOS Pollutants in animal wastes can reach surface waters by several pathways, including overlan d discharge, migration through groundwater, and atmospheric deposition. The most common pathwa y is ove rland discharge, which includes surface runoff (i.e., land-applied or piled manure that i s washed i nto surface waters by rain), soil erosion, and acute events such as spills or impoundmen t failures. Contamination can also occur when pollutants leach through soil into groundwater and the n to surface water through groundwater recharge. In addition, airborne pollutants created b y volat ilization or by spray-application of manure to land can contaminate surface water throug h atmos pheric deposition. Exhibit 2-1 illustrates the various pathways by which AFO releases ca n affect surfa ce waters and groundwater. The following discussion describes these pathways i n greater detail.Atmospheric deposition

Runoff

Groundwater recharge Infiltration Land Application Site

Direct Discharge Surface

Water Exhibit 2-1 PATHWAYS FOR AFO-RELATED POLLUTANTS

Waste Lagoon

2-3Surface discharges can also result from direct contact between confined animals and surfac e 8 waters. Certain animals, particularly cattle, will wade into the surface waters to drink, and will ofte n urinate and defecate there as well. This practice is now restricted for CAFOs, but may still occur at other types of AFOs. Experiments show that for all animal wastes, application r ates have a significant effect on 9 runoff concentrations of pollutants. See Daniel et al., 1995. 2-4 2.1.1 Overland Discharge Contamination from manure often reaches surface water though overland dischar ge; that is, by fl owing directly into surface waters from land application sites or lagoons. There are thre e distinct types of overland discharge: surface runoff, so il erosion, and direct discharge of manure to sur face water during acute events. For example, a single flood event might include lagoo n "washouts," s oil erosion and surface runoff. This section describes the various types of overlan d discharge in more detail.

2.1.1.1 Surface Runoff Surface r unoff occurs whenever rainfall or snowmelt is not absorbed by soil and flow s over land to surface waters. Runoff from land application sites or manure piles can transpor t 8 pollutant s to surface waters, especially if rainfall occurs soon after application, if manure is over

applied, or if it is misapplied. The potential for runoff of animal wastes varies considerably with 9 climate, soil conditions, and management practices. For example, manure applied to saturated o r frozen soils is more likely to runoff the soil surface (ODNR, 1997). Other factors that promot e runoff t o surface waters are steep land slope, high rainfall, low soil porosity or permeability, an d close proximity to surface waters. Surface runoff is a particularly significant transport mechanism for water soluble pollutants, including nitrogen compounds. However, runoff can also carry solids. Runoff of manure pollutants has been identified as a factor in a number of documented impacts from AFOs, including hog, cattle , and chick en operations. For example, in 1994, multiple runoff problems were cited for a ho g o p eration in Minnesota, and in 1996 runoff from manure spread on land was identified at hog and chick en operations in Ohio. In 1996 and 1997, runoff problems were identified for several cattl e operations in numerous counties in Minnesota (CWAA, 1998; ODNR, 1997).

2.1.1.2 Soil Erosion
In addition t o simple surface runoff, pollutants from animal wastes can enter surface water through erosion, in which the soil surface itself is worn away by the action of water or wind. Soil erosion often occurs in conjunction with surf ace runoff as part of rainfall events, but it represents a transp ort mechanism for additional pollutants that are strongly sorbed (i.e., chemically bound) t o2-5 Catastrophic Release of Manure: New River, North Carolina, 1995 On June 21, 1995, a breach in the dike of a 30 million gallon hog waste lagoon discharged over 25 million gallons of waste into tributaries of the New River in Onslow County, North Carolina. Within a week of the event, North Carolina state officials estimated that roughly 2,600 fish were destroyed, though monitoring indicated that oxygen levels had recovered in the river within a week of the event. JoAnne Burkholder, a North Carolina State University marine scientist, noted that the initial waste deluge probably smothered many fish. Others were killed more slowly by declining oxygen levels and the toxic effects of ammonia and bacteria in the water. Two days after the spill scientists sampling in some of the affected areas found ammonia levels of about 20 times the lethal limit for most fish. Though oxygen levels recovered rapidly, Burkholder noted that it could take years for the upper New ecosystem to fully recover and support the range of fish, clams and other creatures that existed before the spill. In addition to immediate problems, longer term problems caused by the breach would include rains churning up settled pollution and potential algae blooms. State environmental officials also confirmed that high levels of fecal coliform bacteria were detected in the river, and Onslow County healthy officials posted warnings in public recreation areas to prevent people from swimming. According to local newspaper reports, in some places fecal coliform levels were 10,000 times the state standard for swimming. Sources: Warrick and Stith,1995b; Warrick 1995b, 1995c, 1995d. soils. The most important of these pollutants is phosphorus. Because of its tendency to sorb to soils , many agricultural phosphorus control measures focus on soil erosion control. However, soils do no t have inf inite adsorption capacity for phosphorus or other pollutants, and dissolved pollutant s (inclu ding phosphates) can still enter waterways through runoff even if soil erosion is controlle d (NRC, 1993).
In spite of control efforts, soi l er osion remains a serious challenge fo r agriculture. For example, in 1997 th e USDA Natural Resources Conservatio n Servic e (NRCS) reviewed the connection between manure production, soil erosion, and wat er quality in a watershed in South Carolina. NRCS calculated that soi l erosion from the 13,000 a cres of cropland in t he watershed ranged from 9.6 to 41. 5 tons per acre per year. The report further fo und that manure and erosion-relate d pollutants such as bacteria, nutrients, and sediment are the primary contaminant s affecting streams and ponds in th e watershed (USEPA, 1997).

2.1.1.3 Acute Events
In a ddition to surface runoff an d eros ion, acute events such as spills , floods, or other lagoon or applicatio n failures ca n affect surface waters. Unlike runoff and erosion, which ge nerally affect land-applied wastes, acute event s frequently affect waste managemen t lag oons. Spills can result fro m mechanical malfunctions (e.g., pum p fa ilures, manure irrigation gu n malf unctions, and failures in pipes o r re taining walls), overfilling, or washout s during flood events. There are eve n indica tions that some operators discharge wastes into surface waters deliberately i n ord er to reduce the volume of waste i n overfull lagoons (CWAA, 1998). Acut e events frequently result in large waste discharges and are often associated with immediate ecologica l2-6

effects such as fish kills. Furthermore, In addition to immediate fish kills, large releases can b e linked with eutrophication, sedimentation, and the growth of pathogens. All of these impacts can also cause acute mortality in fish and other aquatic species.

2.1.2 Leaching to Groundwater Po llutants from animal waste can migrate to groundwater and subsequently contaminat e surf ace waters through the process of "groundwater recharge," in which hydrological connection s betwee n aquifers and surface waters allow transfer of water (and pollutants). Groundwate r contamination itself can result from leaching of land-applied pollutants into the soil, or from leakin g lagoons. Al though most lagoons are lined with clay or are designed to be "self-sealed" by manure solids that prevent infiltration of pollutants into groundwater, these methods are not alway s effective. For example, a survey of hog and poultry lagoons in the Carolinas found that the content s of nearly two-thirds of the 36 lagoons sampled had leaked into the groundwater (Meadows, 1995). Similarly, clay-lined lagoons can crack or break as they age, and are susceptible to burrowing worms

. In a three-year study of clay-lined swine lagoons on the Delmarva Penin sula, researchers found that leachat e from lagoons located in well-drained loamy sand adversely affected groundwater qualit y (Ritter et al., 1990). Surface water contamination from groundwater is most likely to occur in areas with high soi l permeability

and shallow water tables, and is most likely to involve water soluble contaminants suc h as nitrogen (S mith et al., 1997). Overall, the potential for contamination by this pathway may b e considerable. For ex ample, in the Chesapeake Bay watershed, the USGS estimates that about half of the nitrogen loads from all sources to non-tidal streams and rivers originates from groundwater (ASCE, 1998). In addition, about 40 percent of the average annual stream flow in the United States results from groundwater recharge (USEPA, 1993).

2.1.3 Discharges to the Air and Subsequent Deposition Discharges to the air from AFOs include both volatile pollutants (e.g., ammonia and various by-products of manure decomposition) an d particulate matter such as dried manure, feed, hair, and feat hers. The degree of volatilization of pollutants from manure depends on environmenta l conditions and the manure management system employed. For example, spray application of manur e increases the potential for volatilization, as does the practice of spreading manure on the lan d without incorporating it into the soil. Vol atilization is also affected by climate and soil conditions, ( e .g., soil acidity and moisture content), and is reduced by the presence of growing plants (Follett, 1995)."Respirable" generally refers to particles less than 10 microns in diameter, or PM10; thes e 10 particles are responsible for the majority of human health effects related to air pollution because the y are small enough to travel through the nasal passage and into the lungs. For more detailed discussion of the pollutants asso ciated with animal waste, see Phillips 11 et al., 1992. 2-7 Particulate matter from manure forms an organic dust made up of dried manure, feed, an d epithelial cells. These airborne particles can contain adsorbed gases, endotoxin (the toxic protoplas m libe rated when a microorganism dies and disintegrates), and possibly steroids from animal waste

. According to information presented to the Centers for Disease Control, at least 50 percent of the dus t emissions from swine operations are believed to be respirable and m ay therefore be associated with inhalation-related human health effects (Thu, 1998). 10
In addition to creating the potenti al for air-related health effects, both volatilized pollutants and parti culate matter can contaminate nearby surface waters through atmospheric deposition

. Volatilization of the ammonia in urine, in particular, has been linked with atmospheric deposition of nitrogen (Lander et al., 1998). While it is not clear what percentage of total deposition o f pollutants c an be linked to AFOs, EPA’s 1998 National Water Quality Inventory indicates tha t atmospheric d eposition from all sources is the third greatest cause of water quality impairment for estuaries, and the fifth greatest cause of water quality impairment for lakes, reservoirs and ponds.

2.2 POTENTIAL ECOLOGICAL HAZARDS POSED BY AFO POLLUTANTS The primary pollutants associated with animal waste are nutrien ts (particularly nitrogen and phosphorus), organic matter, solids , pathogens, and odorous/volatile compounds. Animal waste is also a source of salts and trace elements and, to a lesser extent, antibiotics, pesticides, and hormones

. The concentration of parti cular pollutants in manure varies with animal species, the size, maturity, and health of the individual animal, and the composition (e.g., protein content) of animal feed. Th e 11 range of p ollutants associated with manure is evident in a 1991 U.S. Fish and Wildlife Servic e (USFWS) report on suspected impacts from cattle feedlots on Tierra Blanca Creek in the Texa s Panha ndle. The impacts the USFWS reported included elevated concentrations of ammonia , coliform bacteria, chloride, nitrogen, and volatile suspended solids, as well as reduced concentration s of dissolved oxygen. In addition, USFWS found elevated concentrations of the feed additives coppe r and zinc in creek sediment (USFWS, 1991). The ecolog ical impacts of animal waste releases to surface water can range from minor , temporar y

fluctuations in water quality (e.g., associated with limited surface runoff) to chroni c degradation of ecosystems (e.g., associated with consistently poor management practices such a s over-application), to dram atic impacts such as extensive fish or wildlife kills (e.g., associated with acu te events such as spills or toxic algae blooms). In some cases, individual pollutants associated with animal waste are the clear and direct cause of observable ecological effects. In other cases ,2-8

ecological effects such as declines in aquatic populations are the result of complex systemic change s that are linked directly or indirectly to pollution from AFOs. Exhibit 2-2 lists the key pollutants associated with AFO waste, and notes their potentia l imp acts. The remainder of this section describes in more detail the relationship between AF O pollu tants and observed ecological effects. Section 2.3 focuses on the specific impacts of AF O pollutants on human health.

Exhibit 2-2 KEY POLLUTANTS IN ANIMAL WASTE

Pollutant in Animal Waste Pathways Potential Impacts

Description of Pollutant Forms

Nutrients Nitrogen Exists in fresh manure in organic (e.g., < Overland discharge < Eutrophication

ammonia in urea) and inorganic forms (e.g., < Leachate into < Animal, human ammonium and nitrate). Microbes transform groundwater health effects organic nitrogen to inorganic forms that are < Atmospheric deposition absorbed by plants. as ammonia Phosphorus Exists in both organic (water soluble) and < Overland discharge < Eutrophication

inorganic forms. As manure ages, phosphorus < Leachate into mineralizes to inorganic phosphate compounds groundwater (water that are absorbed by plants. soluble forms) Potassium Most potassium in manure is in an inorganic < Overland discharge < Eutrophication

form available for absorption by plants; it can < Leachate into < Increased salinity also be stored in soil for future uptake. groundwater Organic Compounds Carbon-based compounds in manure that are < Overland discharge < Depletion of

decomposed by surface water micro- dissolved oxygen organisms. Creates biochemical oxygen < Reduction in aquatic demand, or BOD, because decomposition life consumes dissolved oxygen in the water. Solids Includes manure itself and other elements < Overland discharge < Turbidity

(e.g., feed, bedding, hair, feathers, and < Atmospheric deposition < Siltation corpses). Pathogens Includes range of disease-causing organisms, < Overland discharge < Animal, human

including bacteria, viruses, protozoa, fungi, < Growth in waters with health effects and algae. Some pathogens are found in high nutrient, organic manure, others grow in surface water due to materials increased nutrients and organic matter. < Algal by-products Salts Includes soluble salts containing cations < Overland discharge < Reduction in aquatic

sodium and potassium (from undigested feed), < Leachate into life calcium and magnesium; and anions chloride, groundwater < Human health sulfate, bicarbonate, carbonate, and nitrate. effects Trace Elements Includes feed additives arsenic, copper, < Overland discharge < Toxicity at high

selenium, zinc, cadmium; and trace metals levels molybdenum, nickel, lead, iron, manganese, aluminum, and boron (pesticide ingredients).Exhibit 2-2 KEY POLLUTANTS IN ANIMAL WASTE

Pollutant in Animal Waste Pathways Potential Impacts

Description of Pollutant Forms

Po tassium contributes to the salinity of animal manure, which may in turn contribut e 12 salinity to surface water polluted by manure. Actual or anticipated levels of potassium in surfac e water and groundwater, however, are unlikely to pose hazards to human health or aquatic life. For more information see Wetzel, 1983. 2-9 Odorous, Volatile Compounds Includes carbon dioxide, methane, hydrogen < Inhalation < Human health

sulfide, and ammonia gases generated during < Atmospheric deposition effects decomposition of waste. of ammonia < Eutrophication Other Pollutants Includes pesticides, antibiotics, and hormones < Overland discharge < Impacts unknown

used in feeding operations.

2.2.1 Nutrients and Eutrophication EPA 's 1998 National Water Quality Inventory indicates that nutrients from all source s comprise t he leading stressor in impaired lakes, ponds, and reservoirs, and are among the mos t frequent stressors in impaired rivers, streams, and estuaries. Nutrients are naturally occurrin g elements that are necessary for plant growth. However, when excess nutrients enter surface waters they can stimulate overgrowth of algae and bacteria, changing ecosystems in a process calle d "eutrophication." In addition, nutrients (ni trogen, in particular) in high concentrations can be toxic to animals and humans. The two nutrients of most concern re lated to AFOs are nitrogen and phosphorus. Each of 12 these elements exists in several forms in the environment, and is involved in several phases of uptak e and digestion by animals and plants. This section briefly describes the p rocesses by which nitrogen and phosphorus enter aquatic ecosystems, then discusses the process and imp acts of eutrophication.

2.2.1.1 Nitrogen and Nitrogen Compounds Nitrogen, an element essential to plant growth, moves through the environment in a series of chemical reactions known as the nitrogen cycle. Nitrogen in manure exists in both organi c forms (e.g., urea) and inorganic forms (e.g., ammonium and nitrate) (NCAES, 1 982). In fresh manure, 60 to 90 percent of

total nitrogen is present in the organic form. Inorganic nitrogen can enter th e environment

by volatilizing in the form of ammonia, or through soil or water microbe processes tha t transform organic nitrogen to an inorganic for m that can be used by plants (i.e., as fertilizer). Both ammonia and ammonium are toxic to aquatic life, a nd ammonia in particular reduces the dissolved oxygen in sur face waters that is necessary for aquatic animals. Nitrites pose additional risks t o2-10 National Study of Nitrogen Sources to Watersheds
In 1994, the USGS analyzed potentia l ni trogen sources to 107 watersheds, includin g manure (from both confined and unconfined animals) , fertilizers, point sources, and atmospheric deposition

. While the study found that proportions of nitroge n originating from various sources differ according to climate, hydrolog ic conditions, land use, population, and physical geography, results for selecte d watersheds for the 1987 base year showed that i n some instances, nitrogen from manure represents a large portion of the total nitrogen added to th e waters hed. For example, in nine study watershed s more than 25 percent of nitrogen originates fro m manure. Source: Puckett, 1994. aqu atic life: if sediments are enriched with nutrients, nitrite concentrations in the water may b e raised enough to cause nitrite poisoning or "brown blood disease" in fish (USDA, 1992). A 1975 study found that up to 5 0 perce ntor more of the nitrogen in fres h manure may be in ammonia form o r con verted to ammonia relatively quickl y once manure is excreted (Vanderholm , 1975)

. Ammonia is highly volatile, an d am monia losses from animal feedin g op erations can be considerable. In Nort h Car olina, animal agriculture is responsibl e for over 90 percent of all ammoni a emissions; ammonia composes more th an 40 percent of the total estimated nitroge n emi ssions from all sources. Once airborne , these volatile pollutants may be deposite d onto near by streams, rivers, and lakes. Data from Sampson County, North Carolina show that "ammonia rain" has increased as th e hog ind ustry has grown, with ammonia levels i n ra in more than doubling between 1985 an d 1995 (Aneja et al. , 1998). Ammonia is highly toxic to aquatic life and is a leading cause of fish kills. In a May 1997 incident in Wabasha County, Minnesota, ammonia in a dairy cattle manure discharge killed 16,500 minnows and white suckers (CWAA, 1998). In addition, ammonia and other pollutants in manure exert a direct biochemical oxygen demand (BOD) on the receiving water. As am monia is oxidized, disso lved oxygen is consumed. Moderate depressions of dissolved oxygen are associated wit h reduced s pecies diversity, while more severe depressions can produce fish kills (USFWS, 1991).

2.2.1.2 Phosphorus Like nitrogen, phosphorus is necessary for the growth of plants, but is damaging in excess amounts. Phosphorus exists in solid and dissolved phases, in both organic and inorganic forms. Ove r 70 percent of the phosphorus in animal manure is in the organic form (USDA, 1992). As manure ages, phosphorus mineralizes to inorganic phosphate compounds which are available to plants

. Orga nic phosphorus compounds are generally water soluble and may leach through soil t o groundwater

or runoff into surface waters. In contrast, inorganic phosphorus tends to adhere to soil s and is less likely to leach into groundwater, though it can reach surface waters through erosion o r ove r-application. A report by the Agricultural Research Service noted that phosphorus bound t o erode d sediment particles makes up 60 to 90 percent of phosphorus transported in surface runof f from cultivated land (USDA/ARS, 1999). Animal wastes typically have lower nitrogen: phosphoru s2-11

Available Nitrogen and Phosphorus 1998 U.S. Department of Agriculture Study
In 1998, the USDA studied the amount of manure nitrogen and phosphorus produced by confine d animals re lative to crop uptake potential. USDA evaluated the quantity of nutrients available fro m recoverab le livestock manure relative to crop growth requirements, by county, based on data from th e 1992 Census o

f Agriculture. The analyses did not consider manure from grazing animals in pasture

. When calculating available nutrients, USDA also corrected for unrecoverable manure, nutrient losses tha t occur during storage and treatment, and losses to the environment that can occur through runoff, erosion , leaching to groundwater, and volatilization (especially for nitrogen in the form of ammonia). Considerin g typical management systems, U SDA estimates that average manure nitrogen losses range from 31 to 50 percent for poultry, 60 to 70 percent for cattle (including the beef and dairy categories), and 75 percent for swine. The typical phosphorus loss is 15 percent. USDA's study exam ined the potential for available manure nitrogen and phosphorus generated to meet or exceed plant uptake in each of the 3,141 mainland counties, considering harvested non-legum e cropland and hayland. Based on the analysis of 1992 conditions, available manure nitrogen exceeds cro p system needs in 266 counties, and available manure phosphorus exceeds crop system needs in 48 5 counties. The relative excess of phosphorus compared to nitrogen is expected because manure is typicall y nitrogen -deficient relative to crop needs. Therefore, when manure is applied to meet a crop’s nitrogen requirement, phosphorus is typically over-applied with respect to crop requirements (Sims, 1995). These analyses do not evaluate environmental transport of applied manure nutrie nts. Therefore, an excess of nutrient

s does not necessarily indicate that a water quality problem exists; likewise, a lack of excess nutrients does not imply the absence of water quality problems. Nevertheless, the analyse s provide a general indicator of excess nutrients on a broad basis. Source: Lander et al., 1998. rat ios than crop requirements. The application of manure at a nitrogen-based agronomic rate ca n therefore result in application of phosphorus at several times the agronomic rate. Soil test data in the United States confirm that many soils in areas dominated by animal-based agriculture exhibi t excessive levels of phosphorus (Sims, 1995).2-12

2.2.1.3 Eutrophication Eutrophication is a process in which excess phosphorus or nitrogen over-enriches wate r bodies and disrupts aquatic ecosystems. Excess nutrients cause overgrowth of plants, including fast

growing algae "blooms." Eutrophication can affect the population diversity, abundance, and biomas s of phytoplankton and zooplankton, and can increase the mortality rates of aquatic specie s (USEPA, 1991). Even when algae are not themselves directly ha rmful to aquatic life, floating algal mats can reduce the penetration of

sunlight in the water column and limit growth of seagrass beds and other submerged vegetation. Reduction in submerged aquatic vegetation adversely affects both fish and shellfish p opulations, and is the leading cause of biological decline in Chesapeake Bay (Carpenter et al. , 1998). The 1 998 National Water Quality Inventory indicates that excess algal growth alone is the seventh leading stressor in lakes, ponds, and reservoirs. Incre ased algal growth can also raise the pH of water bodies as algae consume dissolve d carbon dioxide to support photosynthesis. This elevated pH can harm the gills of aquatic organisms

. The pH may then drop rapidly at night, when algal photosynthesis stops. In extreme cases, such pH fluctuations can severely stress aquatic species. In addition, excess nitrogen ca n contribute to water quality decline by increasing the acidity of surface waters (USEPA, 1995, 1991). Damage from eutroph ication increases when algae blooms die and are digested by bacteria in a de composition process that depletes the level of oxygen in the water. Dissolved oxygen i s necess ary for the survival of aquatic life in a healthy ecosystem, and depressed levels of dissolved oxygen can cause widespread morbidity and mortality among aquatic species. Algal decay an d night-time respiration can lower the dissolved oxygen c ontent of a water body to levels insufficient to support fish and invertebrates. Severe reductions in di ssolved oxygen can result in dramatic fish kills (Carpenter et al ., 1998).
In addition to redu cing plant diversity and dissolved oxygen, eutrophication can encourage the growth of toxic microorganisms such as cyanobacteria (a toxic algae) and the dinoflagellat e Pfiesteria piscicida . These organisms can be to xic to both wildlife and humans. Researchers have documented stimulation of Pfiesteria growth by swine effluent spills, and have shown that th e organism’s growth can be highly stimulated by both inorganic and organic nitrogen and phosphorus enrichment (NCSU, 1998).

2.2.2 Pathogens Pathogens are organisms that cause disease in humans and other species; they include certai n specie s of bacteria, viruses, protozoa, fungi, and algae. Animal waste itself contains hundreds o f species of microorganisms, including bacteria, viruses, protozoa, and parasites (USDA, 1998 ; Jackson et al. , 1987; Boyd, 1990). Pathogens may be transmitted directly from manure to surface wa ter, and pathogens already in surface water may increase in number due to loadings of anima l manur e nutrients and organic matter. Of particular concern are certain pathogens associated wit h algae bloo ms. EPA's 1998 National Water Quality Inventory focuses on bacterial pathogens an d2-13 1995 Algae Blooms and Pfiesteria Outbreaks: Neuse River, North Carolina Algae blooms and pfiesteria outbreaks on the Neus e River in North Carolina during the summer and fall of 1995 were the identified causes of three major fish kills and th e suspected causes of several incidents of human illness. Heavy rains in June of 1995 caused overflows o f wa stewater

treatment plants and hog lagoons in th e watershed. Within weeks, large mats of algae and aquati c weeds were reported near the town of New Bern on th e Trent River, a tributary of the Neuse. By July, historicall y low levels of dissolved oxygen were r ecorded in a stretch of the N euse downstream from New Bern, coinciding with the deaths of over 100,000 fis h. A second fish kill in August on another Neuse tributary numbered in the thousands.
In Sept ember and October a third major fish kil l occurre d along a 35-mile stretch of the Neuse River itself ; the d ead fish were covered with sores, and the cause of the outbreak was determined to be the dino flagellate pfiesteria. After multiple reports of similar welts and sores on th e bo dies of those who went swimming or fishing i n contaminated

areas, state officials declared a healt h warni ng for the area, urging people not to swim, boat, o r fish in the affected area. In addition, the area was closed to commercial fishing for two weeks. Source: Leavenworth, 1995a, 1995b. notes that they are the leading stressors in impaired estuaries and the second most prevalent stressor s in impaired rivers and streams. Over 150 pathogens in livestock manure are associated wi th risks to humans; these include the bacteria Escheria coli and Salmonella species

. and the protozoa Cryptosporidium parvum and Giard ia species. A recent study by the USDA revealed that about half the cattle at the nation’ s fe edlots carry E. coli (NAS, 2000). The pathogens C. parvum , Giardia , and E. coli are able t o survive and remain infectious in the environment for long periods of time (Stehman, 2000). I n addition, some bacteria in livestock waste cause avian botulism and avian cholera, which have in th e past killed tens of thousands of migratory waterfowl annually (USEPA, 1993). Eutrophication is associate d with blooms of a variety of organism s that can be toxic to fish. This include s th e estuarine dinoflagellate Pfiesteri a pi scicida , which is believed to be th e primary cause of man y major fish kills and fish disease events in Nort h Carolina estuaries and coasta l areas, as well as in Maryland and Virgini a tributaries to the Chesapeake Ba y (NCS U, 1998; USEPA, 1993). I n 1997, hog operations were linked to a Pfiesteria piscicida outbreak in Nort h Carolina rivers in which 450,000 fis h died (U.S. Senate, 1997). That sam e ye ar, poultry operation wastes cause d P f iesteria outbreaks that killed tens of th ousands of fish in Maryland waters , including the Pokomoke River, King’s Cr eek, and Chesapeake Bay (Shields , 19 97; Shields and Meyer, 1997; Ne w York Times, 1997). The generation of toxin s associated with eutrophication can als o thr eaten other species. In freshwater , cyanobacterial toxins have cause d many incidents of poisoning of wil d and domestic animals that hav e consumed contaminated waters (Healt h Canada Environmental Healt h Program, 1 998; Carpenter et al. , 1998). In coastal waters, visible algae blooms known as red o r brown tides have caused significant mortality in marine mammals. Even when algae blooms are no tBio chemical oxygen demand (BOD) is an indirect measure of the concentration o f 13 biodegrada ble substances present in an aqueous solution. Anaerobic lagoon effluent from AFO s typically contains BOD values 10 to 200 times higher than treated domestic sewage. See NCAES, 1982; USDA, 1992; USDA/NRCS,1992/1996. 2-14 visible, shellfish such as oysters, cla ms and mussels can carry the toxins from certain algae in their tissue. Shellfish are filter feeders, and pass large volumes of water over their gills to obtai n nutrients. As a result, they can concentrate a broad range of microorganisms in their tissues, an d provide a pathway for pathogen transmission fr om surface water to higher trophic organisms (Chai et al. , 1994). Information is becoming available to assess the health effects of contaminated shellfis h on wildlife receptors. In 1998, the death of over 400 California sea lions was linked to ingestion of mussels contaminated by a bloom of toxic algae (Scholin et al. , 2000). Previous incidents associate d the deaths of manatees and whales with toxic and harmful algae blooms (Anderson, 1998).
In Augus t 1997, the National Oceanic and Atmospheric Administration (NOAA) release d The 1995 National Shellfish Register of C lassified Growing Waters . The register characterizes the status of 4,230 shellfish-growing water areas in 21 coastal state s, reflecting an assessment of nearly 25 million acres of estuarine and non-estuarine waters. NOAA found that 3,404 shellfish areas had some level of impairment. Of these, 110 (3 percent) were impaired to varying degrees by feedlots, and 280 (8 per cent) were impaired by "other agriculture," which could include land where manure is applied (NOAA, 1997).

2.2.3 Organic Compounds and Biochemical Oxygen Demand (BOD) Liv estock manures contain many carbon-based, biodegradable compounds. Once thes e compounds reach surface water, they are decomposed by aquatic bacteria and other microorganisms

. Durin g this process dissolved oxygen is consumed, which in turn reduces the amount of oxyge n available for aquatic animals. EPA's 1998 National Water Quality Inventoryindicates that oxygendepleting substances are the second leading stressor in estuaries. They are also the fourth leading stressor both in impaired rivers and streams and in impaired lakes, ponds, and reservoirs. Carbon compounds and associated biochemical oxyg en demand (BOD) can deplete oxygen and affect the health of aquatic ecosystems in the absence of any other pollutants (e.g., due t o decaying v egetation). When carbon compounds enter aquatic ecosystems in conjunction wit h 13 nutrients (which is generally the case in manure-related pollution), the impacts of BOD ar e compounded

by eutrophication and the presence and growth of pathogens. The result is often a rapi d decrease in biodiversity. A study of three Indiana stream systems documents such a reduction i n biodive rsity

due to AFOs (Hoosier Environmental Council, 1997). The study found that water s2-15 Arkansas Water Quality Inventory Report: Agricultural Activities and Turbidity Arkansas’ 1996 Water Quality Inventory Report discussed a sub-watershed in northwestern Arkansas. Land uses in that area, primarily poultry production and pasture management, are major sources of nutrients and chronic high turbidity, and water in the area only partially supports aquatic life. Source: USEPA, 1993. downstream of animal feedlots (mainly hog and dairy operations) contained fewer fish and a limite d number of species of fish in comparison with reference sites. It also found excessive algal growth, altered oxyge n content, and increased levels of ammonia, turbidity, pH, and total dissolved solids.

2.2.4 Solids and Siltation Solids from animal manure include the manure itself a nd any other elements that have been mixed with it, such as spilled feed, bedding, hair, feathers, and corpses. Smaller solids with les s weight remain in the water column as "suspended solids" while heav ier solids sink to the bottom of receiving waters in the gradual process of "siltation." Solids entering surface water can degrade aquatic ecosystems to the point of non-viability. Suspended

particles can reduce the depth to which sunlight can penetrate, decreasing photosyntheti c activity and th e resulting oxygen production by plants and phytoplankton. The increased turbidity also limits the growth of aquatic plants, which se rve as critical habitat for fish, crabs, shellfish, and other a quatic organisms upon which these animals feed. In addition, suspended particles can clog fish gills, reduce visibility for sight feeders, and disrupt migration by interfering with fish’s ability to navigate using chemical signals (Goldman and Horne, 1983; Abt, 1993). EPA's 1998 National Water Quality Inventory

indicates that suspended solids from all sources are the fifth leading stresso r in lakes, ponds, and reservoirs. A ma jor source of siltation i s erosion from agricultural lands, includin g AF Os, cropland, and grazing land s (USEPA, 1992b). Silt can contain heavier manure particles as well as the soil particle s carried by erosion. Such sediment ca n smo ther fish eggs and otherwise interrup t the reproduction of aquatic species (Boyd , 1990)

. It can also alter or destroy habita t for benthic organisms. Solids can als o deg rade drinking water sources, thereb y in creasing treatment costs. The 199 8 National Water Quality Inventory indica tes that siltation from all sources (including agriculture and non-agriculture) is the leading stressor in impaired rivers and the third greatest stressor in impaired lakes, ponds, and reservoirs.See Boyd, 1990 and NCAES, 1982. Other major cations contr ibuting to manure salinity 14 are calci um and magnesium; the major anions are chloride, sulfate, bicarbonate, carbonate, an d nitrate. See NRC, 1993. 2-16 2.2.5 Salts and Trace Elements Animal manur e contains a number of salts and trace elements such as metals. While these contaminants do not directly alter or interfere with ecosystem processes such as oxygen availability, they are toxic in high concentrations, both to animals and plants. For example, bottom feeding bird s may be susceptible to metal toxicity because they are attracted to shallow feedlot wastewater ponds and waters adj acent to feedlots. In addition, metals can remain in aquatic ecosystems for lon g periods of time because of adsorption to suspended or bed sediments or uptake by aquatic biota. The salinity of animal manure is due to the presence of dissolved mineral salts. In particular , significant concentrations of soluble salts containing sodium and potassium remain from undigeste d feed that passes unabsorbed t hrough animals. Salinity tends to increase as the volume of manure 14 decreases during decompo sition, and can have an adverse effect on aquatic life and drinking water supplies (Gresham et al. , 1990). Repeated appl ication of manure can lead to increased soil salinity in the root zone and on top of the soil, where it can damage crops; to reduce salinity farmers apply excess water, and salts are washed into surface waters in runoff. In f resh waters, increasing salinity can disrupt the balance of the ecosystem, making it difficult for resident species of plants an d animals to remain. For example, laboratory experiments have linked increased salinity wit h inhibited growth and slowed molting in mallard ducklings (USFWS, 1992).
Tr ace elements in manure can include arsenic, copper, selenium, zinc, cadmium , molybdenum , nickel, lead, iron, manganese, aluminum, and boron. Of these, arsenic, copper , sel enium, and zinc are often added to animal feed as growth stimulants or biocides (Sims, 1995)

. Trace metals may also end up in manure through use of pesticides that are applied to livestock t o suppress houseflies and other pests (USDA/ARS, 1998). A recent Iowa investigation of chemical and microbial contamination near large scale swine operatio ns demonstrated the presence of trace elements not only in manure lagoons used to stor e swine waste before it is land applied, but also in drainage ditches, agricultural drainage wells, til e li ne inlets and outlets, and an adjacent river (CDCP, 1998). Similarly, USFWS has reported o n su spected impacts from a large number of cattle feedlots on Tierra Blanca Creek, upstream of th e Buffalo Lake National Wildlife Refuge in the Texas Panhandle. USFWS found elevate d concentrations of the feed additives copper and zinc in the creek sediment (USFWS, 1991).2-17

2.2.6 Odorous/Volatile Compounds Sources of volatile compounds and odor from AFOs include animal confinement buildings, manure piles, waste lagoons, and land application sites, where decomposition of animal wastes by microorgan isms produces gases. The four main gases generated are carbon dioxide, methane , hydrogen sulfide, and ammoni a. Aerobic conditions yield mainly carbon dioxide, while anaerobic conditions that dominate in typical, unaerated animal waste lagoons generate both methane an d carbon dioxide. Anaerobic conditions are also associated with the generation of hydrogen sulfide an d about 40 other odorous compounds, including volatile fatty acids, phenols, mercaptans , aromatics, sulfides, and various esters, carbonyls, and amines (USDA, 1992; Bouzaher et al , 1993)

. Vola tile compounds affect aquatic ecosystems through atmospheric deposition; ammoni a (discussed

in Section 2.2.1.1) is the most important AFO-related volatile because it is itself toxic an d also contrib utes to eutrophication as a source of nitrogen. Other compounds are less clearl y associated with broad ecological impacts, but may have localized impacts.

2.2.7 Other Pollutants and Ecosystem Imbalances
In addition to the pollutants discussed above, pesticides, antibiotics, and hormones used in animal feeding operations may exist in anima l wastes and may be present in increased levels in the environment

(USDA/ARS, 1998). These compounds may pose risks such as chronic aquatic toxicit y (from pesticides) and reproductive impairment (from hormones). While there is limited informatio n on the quantities of these compounds that reach surface wat ers from AFOs, some research suggests that manure-related runoff may be a significant source of these contaminants.

• Pes ticides: Pesticides are used to suppress houseflies and other livestoc k pests. The re is little information on the rate at which pesticides in manur e enter surface water, but a 1999 literature review by the University o f Minne sota

notes a 1994 study that links quantities of cyromazine (used t o control flies in poultry litter) in runoff to the rate of manure application and rainfall intensity. The review also identifies a 1995 study finding that roughl y one percent of all applied pesticides enter surface water. The impacts o f these compounds on aquatic ecosystems are unclear, but there is som e concern that pesticides may contribute to endocrine disruption (Mulla, 1999)

.

• Hor mones: Animal operations use a variety of hormones such as steroid s (e.g. , estrogen, progesterone, testosterone) and proteins (e.g., prolactin , growt h hormone) to improve animal health and productivity. Studies hav e id entified hormones in animal manures. Naturally high hormon e concentrations in birds contribute to higher hormone levels in poultr y manure, including measura ble amounts of estrogen and testosterone. When pr esent in high concentrations, hormones in the environment are linked t o reduced fertility, mutations, and the death of fish. There is evidence that fishThe presence of estrogen and estrogen-like compounds in surface water has been the focu s 15 of recent research. While their ultimate fate in the environment is unknown, studies indicate that n o common soil or fecal bacteria can metabolize estrogen (Shore et al., 1995). Estradiol, an estroge n hormone, was found in runoff from a field receiving poultry litter at concentrations up to 3. 5 micrograms per litre (ug/L). Fish exposed to 0.25 ug/L of estradiol can undergo gender changes, an d exposures at levels above 10 ug/L can be fatal (Mulla, 1999). 2-18 in some streams are experiencing endocrine disruption (Shore et al., 1995 ; Mulla, 1999). 15

• Antibio tics The majority of livestock (roughly 60 to 80 percent) receiv e ant ibiotics during their productive life span. Some of these agents are used only therapeutically (e.g., to treat illness), but in both the swine and poultry indus tries, most antibiotics are administered as feed additives to promot e gr owth or to improve feed conversion efficiency. Essentially all of a n anti biotic administered is eventually excreted, either unchanged or i n metabolite form (Tetra Tech, 2000). Little information is available regardin g the concentrations of antibiotics in animal wastes, or on the fate and transpor t of antibiotics in the environment. However, the key concern related t o antibiotics in animal manure is the potential emergence of antibiotic-resistan t pathogens in surface and drinking water. As antibiotics use has increased , more strains of antibiotic resistant pathogens are emerging (Mulla, 1999).
Finally, manure pollutants of all types can affect terrestrial as well as aquatic ecosystems. Over-application of manure, in particular, can have terrestrial effects. High oxygen depletion rates du e to microbial activity have been reported in manure-amended agricultural soils. In addition , elevated microbial populations can affect crop growth by competing with plant roots for soil oxyge n and nutrients. Trace elements (e.g., feed additives such as arsenic, copper, and selenium) and salts in animal m anure can accumulate in soil and become toxic to plants (USDA, 1992 and USFWS , 1991).

2.3 HUMAN HEALTH IMPACTS RELATED TO AFO POLLUTANTS Human health impacts from manure-related contaminants are primarily associated wit h dri nking contaminated water, contact with contaminated water, and consuming contaminate d shellfis h. The most common causes of health effects are ingestion of nitrates in drinking water , ingestion of water containing pathogens from manure, and contact with or ingestion of harmful alga e or toxic algal by-products. The ingestion of elevated concentrations of trace eleme nts (e.g., arsenic, copper, selenium, and zinc) ma y also affect human health, and certain gases associated with AFOs may pose inhalation risks for nearby residents.See USEPA, 1991. In addition, studies in Austral ia found an increased risk of congenital 16 mal formations with consumption of high-nitrate groundwater. Nitrate- and nitrite-containin g compounds also have the ability to cause hypotension or circulatory collapse. Nitrate metabolites such as N-nitroso compounds (especially nitrosamines) have been linked to severe human healt h effects such as gastric cancer. See Bruning-Fann and Kaneene, 1993. 2-19 While some recorded human health effects stem from contamination of public drinking wate r supplies and ingestion of shellfish, more frequently health effects are caused by contamination o f private wells, or recreational ingestion or contact. Public water supplies are generally protected by monitoring and treatment, though contaminants and algae blooms ma y increase treatment costs and affect system

operation. Ingestion of contaminated shellfish is reduced by monitoring and closure of shellfish beds in response to excessive levels of contaminants.

2.3.1 Health Impacts Associated with Nitrates Ni trogen in manure is easily transformed into nitrate form, which can be transported t o drinking water sources (e.g., through leaching to groundwater) and presents a range of health risks. EPA found that nitrate is the most widespread agricultural contaminant in drinking wat er wells, and estimates that 4.5 million people served by wells are exposed to elevated nitrate levels (USEPA , 1990). Ele vated nitrate levels can cause nitrate poisoning, particularly in infants (this is known as methemoglobinemia

or "blue baby syndrome"), in which potentially fatal oxygen starvation gives a "blue" appe arance to the skin. In addition to blue baby syndrome, low blood oxygen due t o methemoglobinemia has also been linked to birth defects, miscarriages, and poor health in humans and animals. 16 Report ed cases of methemoglobinemia are most often associated with wells that wer e pr ivately dug and that may have been badly positioned in relation to the disposal of human an d animal excreta (Addiscott et al. , 1991). Reported cases of methemoglo binemia are rare, though the incide nce of actual cases may be greater than the number reported. Studies in South Dakota an d Nebraska have indicated that most cases of methemoglobinemia are not reported. Under-reporting may resu lt from the fact that methemoglobinemia can be difficult to detect in infants because it s symptoms are similar to other conditions. In addition, doctors are not always required to report it (Michel, 1996; Meyer, 1994).
In 1995, several private wells in North Carolina were found to be contaminated with nitrat es at levels 10 times higher than the health standard; this contamination was linked with a nearby hog operation (Warrick 1995 c, 1995d). In 1982, nitrate levels greater that 10 milligrams per liter were found in 32 percent of the wells in Sussex County, Delaware; these levels were associated with loca l poultry operations (Chapman, 1996). In southeastern Delaware and the Eastern S hore of Maryland, where poultry production is prominent, over 20 percent of wells were found to have nitrate level s2-20

Impacts of Manure Pollutants on Water Treatment Costs Public water providers may incur considerable expenses associated with removing manure-relate d contaminants and algae from public water supplies. For example:

< In Ca lifornia’s Chino Basin, it could cost over $1 million per year to remove the nitrates fro m drinking water due to loadings from local dairies.

< In Wisconsin, the City of Oshkosh has spent an extra $30,000 per year on copper sulfate to kill the algae in the water it draws from Lake Winnebago. The thick mats of algae in the lake have been attributed to excess nutrients from manure, commercial fertilizers, and soil.

< In Tulsa, Oklahoma, excessive algal growth in Lake Eucha is associated with poultry farming

. The city spends $100,000 per year to address taste and odor problems in the drinking water . Sources: For more details on these examples, see USEPA, 1993; Behm, 1989; Lassek, 1998; an d Lassek, 1997. exceeding EPA's maximum contaminant level (MCL) (Ritter et al. , 1989). Nitrate is not removed by conventional drinking water treatment processes. Its removal requires additional, relativel y expensive treatment units.

2.3.2 Health Impacts Associated with Algal Blooms Eutrophication can affect human health by encouraging the formation of algal blooms. Som e algae r elease toxins as they die and may affect human health through dermal contact or throug h consumption of contaminated water or shellfish. In marine ecosystems, algal blooms such as re d tides form toxic byproducts that can affect human health through recreational contact or consumptio n of contamin ated shellfish (Thomann and Muller, 1987). In freshwater, blooms of cyanobacteri a (bl ue-green algae) may pose a serious health hazard to those who consume the water. Whe n cyanoba cterial blooms die or are ingested, they release water-soluble compounds that are toxic t o the nervous system and liver (Carpenter et al. , 1998). Non-toxic algae blooms triggered by nutrient pollution can also affect drinking water b y cloggin g treatment plant intakes and by producing objectionable tastes and odors. In addition , increased algae in drinking water sources can increase production of harmful chlorinated byproduct s (e.g., trihalomethanes) by reacting with chlorine used to disinfect drinking water.By the year 2010, about 20% of the human population (especially infants, the elderly , and 17 those with compromised immune systems) will be classified as parti cularly vulnerable to the health effects of pathogens (Mulla, 1999). 2-21 2.3.3 Health Impacts Associated with Pathogens Over 150 pathogens in livestock manure are associated with risks to humans (Juranek, 1991 ; CAST, 1992). Although human contact can occur through contaminated drinking water, adequate treat ment of public water supplies generally prevents exposure. Most exposure occurs throug h incidental ingestion during recreation in contamin ated waters or through ingestion of contaminated shellfish (Stelma and McCabe, 1992). Relatively few microbial agents are responsible for th e majority of human disease outbreaks from water-based exposure routes. Intestinal infections are th e most common type of waterborne infection, but contact recreation with p athogens can also result in infections of the skin, eye, ear, nose, and throat (Juranek, 1995; and Stehman, 2000). In 1989, ear and skin infections and intestinal illnesses were reported in swimmers as a result of disch arges from a dairy operation in Wisconsin (Behm, 1989). A study for the period 1989 to 1996 revealed that Cryptosporidium parvum (a pathoge n associated with cows) was one of the leading c auses of infectious water-borne disease outbreaks in which an ag ent was identified. C. parvum can produce gastrointestinal illnesses such a s cryptosporidiosis, with symptoms that include severe diarrhea (Stehman, 2000). While otherwise healthy people typically recover quickly from illnesses such as cryptosporidi osis, these diseases can be fatal in certain subpopulations, including children, the elderly, people with HIV infection , ch emotherapy

patients, and those taking medications that suppress the immune system. I n 17 Milwaukee, Wisconsin in 1993, C. parvum contamination of a public water supply caused more tha n 100 deaths and an estimated 403,000 illnesses. The source was not identified, but speculated source s include ru noff from cow manure application sites (Casman, 1996). More recently, a May, 200 0 outbreak of Escherichia coli O157:H7 in Walkerton, Ontario resulted in at least seven deaths an d 1,000 cases of intestinal problems; public health officials theorize that flood waters washed manure contaminated with E. coli into the town’s drinking water well (Brooke, 2000). Algae blooms are associated with a variety of organisms that are t oxic to humans, including the a lgae associated with "red tide" and a number dinoflagellates. One pathogen of particula r concern is the estuarine dinoflagellat e Pfiesteria piscicida. While Pfiesteria is primarily associated with fish kills and fish disease events, the organism has also been linked with human health i mpacts through dermal or inhalation exposure. Researchers working with dilute toxic cultures of Pfiesteria have e xhibited symptoms such as skin sores, severe headaches, blurred vision, nausea/vomiting , su stained difficulty breathing, kidney and liver dysfunction, acute short-term memory loss, an d severe cognitive impairment. In addition, people with heavy environmental exposure have exhibite d symptoms as well. In a 1998 study, such environmental exposure was definitively linked wit h cognitive impairment, and less consistently linked with physical symptoms (NCSU, 1998; Morris et al., 1998).In a 1997 survey of drinking water standard violations in six states over a four-year period , 18 the U.S. General Accounting Office reported that bacterial standard violations occurred in up to 6 percent of community water systems each year and in up to 42 percent of private wells. Se e USGAO, 1997. 2-22 While many soil types prevent most pathogens from reaching aquifers, groundwater in areas of sandy soils, limestone formations, or sinkholes is more vulnerable to contamination. Privat e wells, in particular, are prone to contamina tion because they tend to be shallower than public wells and therefore more susceptible to contaminants leaching from the surface. While the general exten t 18 of groundwater contamination from AFOs is unknown, there are incidents that indicate a connectio n between livestock wast e and contaminated well water. For example, in cow pasture areas of Door County, Wisconsin, where a thin topsoil layer is underlain by fractured limestone bedrock , groundwater wells have commonly been shut down due to high bacteria levels (Behm, 1989).

2.3.4 Health Impacts Associated with Trace Elements and Salts Trace elements in manure include feed additives such as zinc, arsenic, copper, and selenium

. While these are necessary nutrients, they are toxic at elevated concentrations, and tend to persist in th e environment and to bioconcentrate in plant and animal tissues. Trace elements are associate d with a variety of illnesses. For example, over exposure to selenium can cause liver dysfunction and loss of hair and nails, while ingestion of too much zinc can produce changes in copper and iro n balances, particularly copper deficiency anemia (IRIS, 2000). Total concentrations of trace elements in animal manures have been re ported as comparable to those in some municipal sludges, with typical values well below the maximum concentrations tha t EPA allows in land-applied sewage sludge (Sims, 1995). Based on this informatio n, trace elements in agronomically applied manures should pose little risk to human health and the environment

. However, repeated application of manures above agronomic rates could result in exceedances of t he cumulative metal loading rates that EPA considers safe, potentially affecting human health and the environment. There is some evidence that this is happening. For example, in 1995, zinc and coppe r were found building to potentially harmful levels on the fields of a North Carolina hog far m (Warrick and Stith, 1995b). Salts in manur e can also affect the salinity of drinking water. Increased salts in drinkin g water can in turn increase blood pressure in salt-sensitive individuals, increasing the risk of stroke and heart attack (Anderson, 1998; Boyd, 1990).

2.3.5 Other Health Impacts Poten tial health effects associated with other contaminants in manure include inhalation

re lated risks associated with volatile organic chemicals and odors, and the effects of hormones , antibiotics, and pesticides that are found in animal feed.2-23

Volatile Compounds
In 1996, the Minnesota Department of Health found levels of hydrogen sulfide gas a t residences near AFOs that were high enough to cause symptoms such as headaches, nausea , vomiting, eye irritation, respiratory problems (including shallow breathing and coughing), ach y joints, dizziness, fatigue, sore throats, swollen glands, tightness in the chest, irritability, insomnia, and blackouts (Hoosier Environmental Council, 1997). In an Iowa study, neighbors within two mile s of a 4,000-sow swine facility reported more physical and mental health symptoms than a contro l gro up (Thu, 1998). These symptoms included chronic bronchitis, hyperactive airways, mucu s membra ne irritation, headache, nausea, tension, anger, fatigue, and confusion. Odor is itself a significa ntconcern because of its documented effect on moods, such as increased tension , depression, and fatigue (Schiffman et al. , 1995). Heavy odors are the most common complaint fro m neighbors of swine operations (Agricultural Animal Waste Task Force, 1996).

Pesticides Various ingredients in pesticides have been linked to a variety of human hea lth effects, such as systemic toxicity and endocrine disru ption (see below). However, information linking pesticide levels in surf

ace and drinking water to human exposure and to animal manure is currently limited. It is therefore unclear what health risks are posed by pesticide concentrations in AFO wastes.
Hormones and Endocrine Disruption Hormo nes in the environment can act as endocrine disruptors, altering hormone pathway s that regulate reproductive processes in both human and animal populations. Estrogen hormone s have been implicated in the drastic reduction in sperm counts among European and North America n men (Sharpe and Skakkebaek, 1993) and widespread r eproductive disorders in a variety of wildlife (Colb urn et al., 1993). A number of agricultural chemicals have also been demonstrated to caus e endocrine disruption as well, including pesticides (Shore et al, 1995). The effects of these chemical s on the environment and their impacts on human health through environmental exposures are no t completely understood, but they are currently being studied for evidence that they caus e neu robiological, developmental, reproductive, and carcinogenic effects (Tetra Tech, 2000). N o studies exist on the human health impact of hormones from manure watersheds.

Antibiotics and Antibiotic Resistance While an tibiotics themselves are not generally associated with human health impacts , anti biotic resistance poses a significant health threat. In April 2000, the New England Journal o f Medicine pub lished an article that discussed the case of a 12-year old boy infected with a strain of Salmonella

that was resistant to no fewer than 13 antimicrobial agents (Fey, 2000). The cause of th e child’s illness is believed to be exp osure to the cattle on his family’s Nebraska ranch. The Centers2-24

for Disease Control, the Food and Drug Administration, and the National Institutes of He alth issued a draft action plan in June, 2000, to address the increase in antibiotic resistant diseases (CDCP , 2000). The plan is intended to combat antimicrobial resistance through surveys, prevention an d control activities, research, and product development. Some actions are already underway.

2.4 REFERENCES Abt Asso ciates Inc. 1993. Human Health Risk Assessment for the Use and Disposal of Sewag e Sludge: Benefits of Regulation . Prepared for Health and Ecological Criteria Division, Offic e of Sc ience and Technology, Office of Water, U.S. Environmental Protection Agency

. January. Addiscott, T.M., A.P. Whitmore, and D.S. Powlson. 1991. Farming, Fertilizers, and the Nitrate Problem

. Rothamsted Experimental Station. C-A-B International: Oxon, United Kingdom

. Ander son, Don. 1998. "Why are outbreaks of Pfiesteria and red tides suddenly threatening ou r oceans?" Scientific American online at: http://www.sciam.com/askexpert/environment/ environment21/environment21.html Aneja, V iney, George C. Murray, and James Southerland. April 1998. Atmospheric Nitroge n Compounds: Emissions, Transport, Tra nsformation, Deposition, and Assessment. EM, Air & Waste Management Association’s Magazine for Environmental Managers , 22-25

. Available at: online.awma.org/em/april98/features/aneja/aneja.htm ASCE (American Society of Civil Engineers). Februa ry 1998. Bay Pollution Flows Underground. Civil Engineering , p. 13-14. Behm, Donald. 1989. "Ill Waters: The Fouling of Wisconsin’s Lakes and Streams." Th e Milwaukee Journal Sentinel. Special Report: A series of articles and an editorial published November 5 - 10, 1989. Bouzaher, A. , P.G. Lakshminarayan, S.R. Johnson, T. Jones, and R. Jones. 1993. The Economic and Environmental Indicators for Evaluating the National Pilot Project on Livestock and th e Environmen t, Livestock Series Report 1 . Center for Agricultural and Rural Developmen t (CARD) at Iowa

State University and Texas Institute for Applied Environmental Research at Tarleton State University. Staff Report 93-SR 64. October. Boyd, W. 1990. Effects of Poultry Waste on Ground and Surface Water. In Blake, J., and R.M

. Hulet, eds. Proceedings of the 1990 National Poultry Waste Management Symposium

. October. Bro oke, James. 2000. Few left untouched after deadly E. coli flows through an Ontario town’ s water. The New York Times. July 10, 2000.2-25

Bruning-Fann, C. S. and J. B. Kaneene. 1993. The Effects of Nitrate, Nitrite, and N-Nitros o Compounds on Human Health: A Review. Vet. Human. Toxicol. 35(6). December. Carpen ter, Stephen, N.F. Caraco, D.L. Correll, R.W. Howarth, A.N. Sharpley, and V.H. Smith

. 1998. Nonpoint Pollution of Surface Waters with Phosphorus and Nitrogen. Issues i n Ecology , Number 3. Published by the Ecological Society of America, Washington, D.C

. Summer. (Also available at: esa.sdsc.edu/). Casman, Elizabeth A. 1996. Chemical and Microbiological Consequences of A naerobic Digestion of Livestock Manure, A Literature Review. Interstate Commission on the Potomac Rive r Basin, ICPRB Report #96-6. CAST (Council for Agricultural Science and Technology). 1992. Water Quality: Agriculture' s Role . Report 120. December. CDCP (Centers for Disease Control and Prevention). 1998. Report to the State of Iowa Departmen t of Public Health on the Investigation of the Chemical and Microbial Constituents of Groun d and Surface water Proximal to Large-Scale Swine Operations

. CDCP (Centers for Disease Control and Prevention). 2000. A Public Health Action Plan to Comba t Antimicrobial Resistance. June Draft. available at: http://www.cdc.gov/drugresistance/actionplan/aractionplan.pdf Chai, T.J., Tj. Ha n and R.R. Cockey. 1994. Microbiological quality of shellfish-growing waters in Chesapeake Bay. J. Food Protect. 57:229-234. Cha pman, S.L. 1996. Soil and Solid Poultry Waste Nutrient Management and Water Quality

. Poultry Science 75:862-866. CWAA (Clean Water Action Alliance). 1998. Minnesota Manure Spills and Runoff. Dan iel, T.C., D.R. Edwards, and D.J. Nichols. 1995. Edge-of-Field Losses of Surface-Applie d Animal Manure. In: Animal Waste and the Land-Water Interface, edited by Kenneth Steele

. Fey, Paul D.; Safranek, Thomas J.; Rupp, Mark E.; Dunne, Eileen F.; Ribot, Efrain; Iwen, Peter C.; Bradford, Patricia A.; Angulo, Frederick J.; Hinrichs, Steven H. Ceftriaxone. 2000

. "Resi stant

Salmonella Infection Acquired by a Child from Cattle." The New Englan d Journal of Medicine ; 342 (17), pp 1242-1249. Follett, Ron ald F. 1995. Fate and Transport of Nutrients: Nitrogen. Working Paper No. 7. U.S. De partment

of Agriculture, Agricultural Research Service, Soil-Plant-Nutrient Researc h Unit, Fort Collins, Colorado. September. Goldman, C., and A. Horne. 1983. Limnology . New York: McGraw-Hill Publishing, Co.2-26

Gres ham, C.W., et al. 1990 . Composting of Poultry Litter, Leaves, and Newspaper. Rodal e Research Center. Health Canada Environmental Health Program. 1998. Blue-green Algae (Cyanobacteria) and their Toxins. P ublication of the Canadian federal government. Available on the Internet a t http://www.hc-sc.gc.ca/ehp/ehd/catalogue/general/iyh/algea.htm. Hoosi er Environmental Council. 1997. Internet home page. Available at: www.envirolink.org / orgs/hecweb/monitorspring97/confined.htm. IRIS (Integrated Risk Information System). 2000. Chemical Files and Background Documents an d Papers. Washington, DC. Available at: www.epa.gov/iris/subst/index.html. March. Jackson, G., et al. 1987. Agricultural Management Practices to Minimize Groundwate r Contamination. University of Wisconsin Environmental Resources Center (July). Jordan, Herbert C., and Robert E. Graves. 1987 . Poultry Manure Management, Pennsylvania Stat e University. Prepared under the direction of the Manure Management Work Group of th e Agricultural Advisory Committee to the PA Department of Environmental Resources. Juranek, D.D . 1995. Cryptosporidiosis: sources of infection and guidelines for prevention. Cli n Infect Dis. 21 (Sup. 1): S57-61. Lander, Charles H., David Moffitt, and Klaus Alt. 1998. Nutrients Available from Livestoc k Manure Relative to Crop Growth Requirements. U.S. Department of Agriculture. Natural Resources Conservation Service. Washington, DC. Available at: www.nhq.nrcs.usda.gov / land/pubs/nlweb.html. Lassek, P.J. 1997. Lake Eucha drowning in algae. The Tulsa World . August 17. Lassek, P.J. 1998. Tulsa Officials Seek Long-Term Solution to Protect Watershed. The Tuls a World, March 16. Leavenworth, Stuart. 1995a. "Airborne threats rain down on Neuse." The News and Observer Ma y 8. Available at: www.nando.net. Leavenworth , Stuart. 1995b. "Half-million fish die in Neuse River." The News and Observer September 22. Available at: www.nando.net. Meadows, R. 1995. Livestock Legacy. Environmental Health Perspectives 103(12):1096-1100. Meyer, M. October 1994. How Common is Methemoglobinemia from Nitrate Contaminated Wells ? A South Dakota Perspective . Paper presented at the 39th Annual Midwest Ground Wate r Conference, Bismarck, ND. Cited in: Michel et al., 1996.2-27

Michel, Kristi n, J.R. Bacon, C.M. Gempesaw II, and J.H. Martin, Jr. August 1996. Nutrien t Management

by Delmarva Poultry Growers: A Survey of Attitudes and Practices. Universit y of Delaware, College of Agricultural Sciences, Department of Food and Resourc e Economics. Morris, J. Glenn Jr., et al. 1998. University of Maryland School of Medicine, Baltimore, Maryland

. As report ed by David Brown: "Pfiesteria Linked to Thinking Problems," The Washingto n Post , August 14. Mulla, David; A. Sekely, A. Birr, J. Perry, B. Vondracek, E. Bean, E. Macbeth, S. Goyal, B

. W h eeler, C. Alexander, G. Randall, G. Sands, and J. Linn. 1999. Generic Environmental Impact Statement on Animal Agriculture: A Summary of the Literature Related to the Effect s of A nimal Agriculture on Water Resources (G) . Prepared for the Environmental Qualit y Boa rd by the University of Minnesota, College of Agriculture, Food, and Environmenta l Sciences. NAS (National Academy of Sciences), 2000. Proceedings of the National Academy of Science s April. NCAES (North Carolina Agricultural Extension Service). 1982 . Best Management Practices for Agr icultural

Nonpoint Source Control: Animal Waste . North Carolina State University

. Biological and Agricultural Engineering Department. Raleigh, NC. NCSU (North Carolina State University). 1998. Aquatic Botany Laboratory Pfiesteria piscicida homepage . Available at: www.pfiesteria.org/pfiestr/pfiestr.html. New York Times (editorial). 1997. Why the Fish Are Dying

. The New York Times September 22. Available at: www.nytimes.com. NOAA (National Oceanic and Atmospheric Administration). August 1997. The 1995 Nationa l Shellfish Register of Classified Growing Wa ters. Office of Ocean Resources Conservation and Assessment. National Ocean Service, U.S. Department of Commerce. NRC (National Research Council). 1993. Soil and Water Quality: An Agenda for Agriculture

. National Academy Press: Washington, D.C. ODNR (Ohio Department of Natural Resources). 1997. Division of Wildlife Pollution Investigatio n Report - Manure Related Spills and Fish and Wildlife Kills. June 9. Phillips, J. M., H. D. Scott, and D. C. Wolf. 1992. Environmental Implications of Animal Waste Application to Pastures. In: Proceedings from the South Pasture Forage Crop Improvemen t Conference. USDA/Agricultural Research Service (September). pp. 30-38.2-28

Puckett, L.J. 1994. Nonpoint and point sources of nitrogen in major watersheds of the Unite d States. U.S. Geological Survey, National Water Quality Assessment. Ritter, W.F., A.E.M. Chirnside, and R.W. Lake. 1989. Influence of Best Management Practices on Water Qualit y in the Appoquinimink Watershed. J. Environ. Sci. Health , A24(8):897-924. Ritter, W. F., and A. E. M. Chirnside. 1990. Impact of Animal Waste Lagoons on Groundwate r Quality. Biological Wastes . 34:39-54. Sc hiffman, S.S., E.A. Sattely Miller, M.S. Suggs, and B.G. Graham. 1995. The Effect o f Environmental Odors Emanating from Commercial Swine Operations on the Mood o f Nearby Residents. Brain Research Bulletin , 37:369-375. Scholin, Christopher A., et al.. 2000. "Mortality of sea lions along the central California coas t linked to a toxic diatom bloom." Nature 403, 80 - 84. Shields, T. 1997. Fish Kills Seen as 'Alarm Bell' For Chesapeake, Tributaries. The Washington Pos t 17 August. B1. Shields, T. and E.L. Meyer. 1997 . New Fish Kills Found Miles from Pocomoke. The Washington Post , September 11. A1. Si ms, J. Thomas. 1995. “Characteristics of Animal Wastes and Waste-Amended Soils: A n Overview of the Agricultural and Environmental Issues” in Animal Waste and the Land

Water Interface. Kenneth Steele, ed., CRC Press/Lewis Publishers, Boca Raton. Smith, R., G. Schwarz, and R. Alexander. 1997. Regional Interpretation of Water-Qualit y Monitoring Data. Water Resources Research. Vol. 33(12): 2781-2798. December. Stehman, Susan M. 2000. Ag-Related water borne pathogens. In: Managing Nutrients an d Pathogens from Animal Agriculture, Proceedings of a Conference for Nutrient Managemen t Consultants, Extension Educators, and Pro ducer Advisors. Natural Resource, Agriculture, and Engineering Service (NRAES). pp. 93-107. March 28-30. Tetra Tech. 2000. Literature Review and Assessment of Pathogens, Heavy Metals, and Antibiotic Content of Waste and Wastewater Generated by CAFOS . Unpublished report prepared a t the request of U.S. Environmental Protection Agency, Offi ce of Water, EPA contract 68-C99-263. Thoma nn , R. V., and J.A. Muller. 1987. Principles of Surface Water Quality Modeling an d Control. Harper Collins Publishers. Thu, Kendall. 1998. Information presented at the Center for Disease Control Workshop on Public Health Issues Related to Concentrated Animal Feeding Operations, June 23-24.2-29

USDA (U.S. Department of Agriculture). 1992. Agricultural Waste Management Field Handboo k

. 210-AWMFH. April. USDA (U.S. Department of Agriculture). 1998. Agricultural Uses of Municipal Animal, an d Industrial Byproducts. Agricultural Research Service. January. USDA/ARS (U.S. Department o f Agriculture/Agricultural Research Service). 1998. Agricultural Use s of Municipal, Animal, and Industrial Byproducts . Conservation Research Repor t Number 44. January. USDA/NRCS (U.S. Department of Agriculture/Natural Resources Conservation Service). 1992 an d 1996 revisions. Agricultural Waste Management Field Handbook. 210-AWMFH. USEPA (U.S. Environmental Protection Agency). 1990. National Survey of Pesticides in Drink ing Water Wells, Phase I Report. EPA-570990015. USEPA (U . S. Environmental Protection Agency). 1991. Nitrogen Action Plan. Draft (March)

. PM-221. 40 0/90/003. Nitrogen Work Group. USEPA (U. S. Environmental Protection Agency). 1992b. Managing Nonpoint Source Pollution : Final Report to Congress . Office of Water. USEPA (U. S. Environmental Protection Agency). 1993. The Report of the EPA/State Feedlo t Workgroup. Office of Wastewater Enforcement and Compliance. USEPA (U. S. Environmental Protection Agency). 1995. N ational Water Quality Inventory: 1994 Report to Congress . Office of Water. EPA 841-R-95-005. December. USEPA (U.S. Environmental Protection Agency). 1997. Section 319 Success Stories: Volume II

. Highlights of State and Tribal Nonpoint Source Programs (Online)

. Office of Water

. Washi ngton, D.C. EPA-R-97-001. October. Available at: www.epa.gov/owow/NPS / Section319II. USEPA (U.S. Environmental Prote ction Agency). 2000. National Water Quality Inventory: 1998 Report to Congress. EPA 841-R-00-001. USFWS (U.S. Fish and Wildlife Service). 1991. Contaminants in Buffalo Lake National Wildlife Refuge, Texas. Report by the Arlington Field Office. October. USFWS (U.S. Fish and Wildlife Service). 1992. " An Overview of Irrigation Drainwate r Tech niques, Impacts on Fish and Wildlife Resources, and Management Options" prepared for USEPA, OPP E by U.S. Fish and Wildlife Service May, 1992. Cited in: Industria l Economics, Incorporated, 1993. "Irrigation Return Flow Fee Feasibility Study," unpublishe d memorandum prepared for USEPA, Office of Policy Analysis, October.2-30

USGAO (U.S. General Accounting Office ). 1997. Drinking Water: Information on the Quality of Water Found at Community Water Systems and Private Wells . Report to Congressiona l Requesters. GAO/RCED-97-123. Available at: www.gao.gov/AIndexFY97/abstracts / rc97123.htm. June. U.S. Senate. 1997. Animal Waste Pollution in America: An emerging national problem. Repor t Compiled by the Minority Staff of the United States Senate Committee on Agriculture , Nutrition and Forestry for Senator Tom Harkin. Vanderholm, D.H. 1975. Nutrient Losses from Livestock Waste During Storage, Treatment, and Handling. Managing Livestock Wastes, p. 282. Warrick, Jo by. 1995b. Hog farm is fined $110,000 for spill. The News and Observer. August 23, 1995. Available at: www.nando.net. War rick, Joby. 1995c. Contaminated wells linked to Robeson hog operation. The News an d Observer. October 14, 1995. Available at: www.nando.net. Warrick, Joby. 1995d. Tainted wells, poisoned relations The News and Observer. October 15, 1995

. Available at: www.nando.net. Warrick, Joby and Pat Stith. 1995a. "Boss Hog: North Carolina’s P ork Revolution." The Raleigh, NC News and Observer. Five part series published from February 19-26. Available at : www.nando.net/sproject/hogs/hoghome.html Warrick, Joby and Pat Stith. 1995b. Metals present new concern for livestock producers. The New s and Observer. September 17. Available at: www.nando.net. Wetzel, R.G. 1983. Limnology . 2nd Edition. Saunders College Publishing.3-1

CONCEPTUAL FRAMEWORK AND OVERVIEW OF METHODS CHAPTER 3

________________________________________________________________________________ _
Pollutants associated with AFOs can have a range of harmful impacts on water quality, on aquatic and shoreline ecosystems, and on the range of uses (or services) that water resources provide

. While some pollutants pose a direct threat to human health (e.g., pathogens that prevent drinking or contact with contaminated water), AFO-related pollutants can also contribute to the decline o f recreationa l and commercial activities, injury to species that live in or depend on contaminate d waters (e.g., aquatic shorebirds), and even a reduction in the intrinsic "existence" value that people place on a pristine or well-protected ecosystem. The benefits of a regulation that reduces AFO pollution are reflected by identifiabl e changes in environmental quality that result from the regulation, and by the related improvements in the rang e of potential uses of the resource. The value of the regulation is then measured according to the valu e that people place on the changes in these potential uses. EPA characterizes these changes b y considering the use and non-use benefits that water resources provide under baseline conditions, an d contrasting these benefits with the enhanced benefits realized under each of the regulatory scenarios

. This chapt er describes the general approach that EPA uses to value environmental qualit y improvements associated with reduced AFO pollution. The first section describes the types o f environmental improvements and benefits to humans that would likely result from chan ges in water quality due to the regulation of CAFOs. The chapter then identi fies the key environmental changes and benefits that are the focus of the evaluation of EPA's proposed regulations, and des cribes EPA's approaches t o measuring and valuing the selected benefits. The broad methods outlined in thi s chapter form the basis of the specific benefits analyses described in Chapters 4 through 7.

3.1 POSSIBLE ENVIRONMENTAL IMPROVEMENTS AND RESULTING BENEFITS Gr oundwater

and surface water resources (including rivers, lakes, estuaries, and oceans ) provi de a range of benefits to humans and other species that reflect the actual and potential "uses" that they support. Potential uses can include active consum ption or diversion of water for industry, agriculture, or drinking water, and can also include a range of active and passive "in-place" uses suc h as swimming, fishing, and aesthetic enjoyment.A common example of intrinsic value is the broad public support for the preservation of 19 National Parks, even by people who do not expect to visit them. 3-2 Water resou rces also provide intrinsic (or non-use) benefits that reflect the importance o f pro tecting environmental quality regardless of any specific use that humans may enjoy or intend

. Intrinsic benefits include "existence value," i.e., the sens e of well-being that people derive from the existence of pristine water resources, even when they do not expect to see or use these resources. 19 The prot ection of resources for future generations (intergenerational equity) or for non-huma n species (ecological benefits) are other key intrinsic benefits. Degradation of a water resource may restrict its use or the intrinsic benefits it provides, and therefore reduce its value. Conversely, improvement in environmental quality provides benefit s associated with an increase in the range of potential uses and intrinsic benefits that a resource can support. Exhibit 3-1 provides a summary of the potential benefits associated with an improvement in the quality of aquatic resources.

Exhibit 3-1

POTENTIAL BENEFITS OF WATER QUALITY IMPROVEMENTS Use Benefits In-Stream • Commercial fisheries, shell fisheries, and aquaculture; navigation

• Recreation (fishing, boating, swimming, etc.)

• Subsistence fishing

• Human health risk reductions Near Stream • Water-enhanced non-contact recreation (picnicking, photography, jogging, camping, etc.)

• Nonconsumptive use (e.g., wildlife observation) Option Value • Premium for uncertain future demand

• Premium for uncertain future supply Diversionary • Industry/commercial (process and cooling waters)

• Agriculture/irrigation

• Municipal/private drinking water (treatment cost savings and/or human health risk reductions) Aesthetic • Residing, working, traveling and/or owning property near water, etc. Intrinsic (Non-Use) Benefits Bequest • Intergenerational equity Existence • Stewardship/preservation

• Vicarious consumption Ecological • Reduced mortality/morbidity for aquatic and other species

• Improved reproductive success for aquatic and other species

• Increased diversity of aquatic and other species

• Improved habitat, etc.3-3

AF O pollutants have impacts on a broad range of water resource services. Pollution b y nut rients, for example, can reduce the value of both groundwater and surface water as a drinkin g water source, and algae in eutrophied surface water can reduce recreational and aesthetic uses (due to foul od or and appearance), as well as clog municipal and industrial intakes. Acute nitroge n loadings and decaying algae cause fish kill s, which affect commercial and recreational fishing, and indicate injury to natural resources; some of these injuries may require restoration in order to achiev e full recover y of the ecosystem. Both chronic and acute nutrient loadings can reduce aquati c populations and the shoreline species that depend on them; this affects both opportunities to view wildlif e and ecological "existence" values. Finally, nutrient-related red tide and Pfiesteria event s can restrict access to shellfish and beaches, affecting shellfishing and recreational opportunities. Othe r AFO pollutants have similar impacts or can cause additional effects (e.g., turbidit y from solids, human health effects from pathogens). In addition, any pollutant that reduces the qualit y of an environmental resource may adversely affect intrinsic values, such as bequest values (i.e. , preserving environmental quality for future generations). While the beneficial i mpacts of improved control of any one pollutant can be difficult to isolate, AFO-related pollution generally involves a broad ra nge of impacts that, taken together, affect to some degree most of the potential uses an d intrinsic benefits of water resources.

3.2 SPECIFIC BENEFITS ANALYZED The benefits of water quality improvements are a function of the specific pollutants reduced , the water resources affected, and the improvements in the potential uses of these resources. The ke y challenge of a benefits calculation is to establish a clear link between the implementation of a regulation, the reduction of a pollutant, the resulting improvement in environmental qu ality, and the value of that improvement. Whil e AFO-related pollutants can affect most potential uses of surface and groundwater , EPA has identified a set of environmental quality changes tha t meet three criteria: 1) they represent identifiable and measurable changes in water quality; 2) they can be linked with the proposed CAF O regulations; and 3) together, t hey represent a broad range of potential human uses and benefits and are likely to capture important environmental changes that result from the rule. Specifically, EPA implements four analyses:

• Impr ovements in Water Quality and Suitability for Recreationa l Activities: this analysis addresses increased opportunities for recreationa l fishin g and swimming, as well as the potential increase in non-use value s associated with improvements in inland surface water quality;

• Reduc ed Incidence of Fish Kills: this analysis assesses the value o f reducing the incidence of fish kills attributable to pollution from AFOs;3-4

• Improved Commercial Shell Fishing: this analysis characterizes the impac t of po llution from AFOs on access to commercial shellfish growing waters , and value s the potential increase in commercial shellfish harvests that ma y result from improved control of that pollution; and

• Reduced Contaminatio n of Private Wells: this analysis values the impact of the revised regulations in reducing the concentration of nitrates in wate r drawn from private wells. EPA's analysis does not attempt to comprehensively identify and value all potentia l environmental changes associated with proposed re visions to the CAFO regulations. For example, the analysis of the suitability of water resources for recreational use excludes the Great Lakes, as wel l as all estuari ne or marine waters. In addition, the analysis examines only a limited set of potential improvements in water quality; it does not attempt to value the improvement of non-boatable water s to boatable condition, nor does it attempt to value improvements in the quality of water resources that are already suitable for swimming. Furthermore, the analysis does not value the potential impac t of improvements in water quality on near-stream activities, such as birdwatching or camping, no r does it consider non-water related benefits, such as potential reductions in odor from wast e management areas. EPA also does not evaluate potential impacts on certain diversio nary uses (e.g., improvemen ts in the quality of reservoirs and other sources of public water supplies, and th e associated reduction in the cost of treating water to remove AFO-related pollutants). While changes in water quality res ulting from CAFO regulations may have real impacts on th ese types of uses, and may even be associated with significant benefits, several factors make i t difficult to measure the specific impacts of the regulation and identify related chan ges in value. For example, analysis of pot ential changes in estuarine or marine water quality nationwide is currently beyond the capabilities of the water quality model employed in this study. In addition, while EPA's pro posed CAFO regulations will contribute to improvements in environmental quality beyon d surface waters, it is difficult to establish clear relationships between regulation of AFOs and certain enviro nmental quality changes, such as reductions in odor or improvements in the health o f shorebirds. Although these benefits are not specifically addressed by the analysis, they likel y represent additional benefits of the regulation.

3.3 PREDICTING CHANGE IN ENVIRONMENTAL QUALITY AND RESULTING BENEFICIAL USE To calculat e the benefits associated with a proposed regulations, an analysis must explor e the difference between present conditions (i.e., the baseline scenario) and the likely future condition s that would result from the regulation. The baseline scenario is typically assessed using the best and most recently collected data that characterize existing env ironmental quality. Because likely future conditions are theoretical, the characterization of environmental quality for each of the regulator y scenario s must be evaluated through environmental modeling or other approaches designed t o3-5

simulate po ssible future conditions. The difference in environmental quality between the presen t and futur e conditions thus represents the marginal environmental quality gains or human benefit s that would be produced under each scenario. EPA 's analysis of the proposed CAFO regulations examines the difference between th e baseline and each of the regulatory scenarios for each of the four benefits categories identified above

. Ideally, the baseline scenarios would be constant across benefit categories and analyses; however, da ta limitations forced EPA to define baseline conditions based on the most up to date record o f e x isting conditions for each analysis. For instance, the analysis of increased commercial shellfish supply benefits relies upon 1995 data on shellfish bed closures to define baseline conditions, wherea s the analysi s of fish kill events relies upon data collected between 1980 and 1999. Detaile d informat ion on the time frame used to define baseline scenarios for each of the selecte d environmental benefit categories is provided for each of the analyses addressed in Chapters 4 through 7. For each of the benefit categories analyzed, post-regulatory conditions are assessed usin g mod eling approaches most applicable to the specific analysis. For each of the selected benefi t categories, EPA models post-regulatory conditions as follows:

• Impr ovements in Water Quality and Suitability for Recreationa l Activities: EPA relies o n a national water quality model to predict changes in the ambient concentration of pollutants attributable to changes in pollutan t loadings from CAFOs. Under each regulatory scenario, the model determine s whether estimated changes in pollutant concentrations would improve th e suitabi lity of water resources for recreational uses such as fishing an d swimming.

• Reduce d Incidence of Fish Kills: Through modeling of nitrogen an d ph osphorus loading reductions, the analysis estimates changes in th e frequency of fish kill events under each regulatory scenario.

• Improved Commercial Shell Fishing: EPA employs dat a on the impact of agric ultural pollution on commercial shellfish harvesting, combined wit h model ed estimates of the change in pathogen loadings from CAFOs, t o estimate the potential increase in annual shellfish harvests under eac h regulatory scenario.

• Redu ced Contamination of Private Wells: EPA employs data from th e U.S. Geological Survey (USGS), EPA, and the Bureau of Census to mode l the relationship between nitrate concentrations in private d omestic wells and sou rces of nitrogen to aquifers. EPA uses this model, combined wit h esti mates of the change in nitrogen loadings under alternate regulator y scenarios, to predict changes in well nitrate concentrations nationally.Econo mists also sometimes consider a similar concept of "willingness to accep t 20 co mpensation"; i.e., the amount of monetary compensation that would make the individua l indifferent between having an environmental improvement and foregoing the improvement. 3-6 3.4 VALUING BENEFITS The final st ep of the benefits analyses is to estimate the economic value of the modele d physical changes in environmental quality. This section provides a brief overview of economi c va luation concepts and discusses the valuation approach applied in the studies performed for th e proposed CAFO rule.

3.4.1 Overview of Economic Valuation Economists define benefits by focusing on measures of individual satisfaction or well-being , referred to as measures of welfare or utility. A fundamental assumption in economic theory is that ind ividuals can maintain the same level of utility while trading-off different "bundles" of goods , services, and money. The tradeoffs individuals make reveal information about the value they place on these goods and services. The willingness to trade-off compensation for goods or services can be measured by a n individuals' willingness to pay. While these measures can be expressed in t erms of goods, services, or money, economists generally express willingness to pay in monetary terms. In the case of a n environmental policy, willingness to pay represe nts the amount of money an individual would give up to receive an improvement (or avoid a decrement) in environmental quality. 20
The use of willingness to pay to measure benefits is closely related to the concept o f consumer surplus. Resource economists generally rely on consumer surplus as a measure of overall economic welf

are for benefits to individuals. The concept of consumer surplus is based on th e principle that some consumers benefit at curr ent prices because they are able to purchase goods (or services ) at a price that is less than their total willingness to pay for the good. For example, if a cons umer is willing to pay $4 for an additional gallon of clean drinking water that costs th e consumer only $1.50, then the marginal consumer surplus is $2.50.In the case of goods and services traded in the marketplace, net benefits also includ e 21 producer surplus: the excess of producer revenues over costs. For simplicity, we leave aside for no w any discuss ion of producer surplus in assessing the benefits associated with enjoyment of natura l resource services. These same techniques can be applied to estimate the economic damages attributable t o 22 a decline in environmental quality. 3-7 3.4.2 Primary Approaches for Measuring Benefits Economists generally define the economic benefits provided by a natural resource as the su m of individuals' willingness to pay for the goods and services the resource provides, net of any costs associated with enjoying these services. In some cases (e.g., commercial fishing), natural resourc e 21 products are traded in the marketplace, and w illingness to pay information can be directly obtained from demand for these commodities. In other cases, when natural resource goods or services are no t traded in the market, economists use a variety of analytic techniques to value them, or to estimate the economic benefits of improvements in environmental quality. These non-market methods , 22 which are grounded in the theory of consumer choice, utility maximization, and welf are economics, a t tempt to determine individuals' willingness to pay for natural resource services directly, through survey research, or indirectly, through the examination of behavior in related markets. Descriptions of market and non-market methods for analyzing benefits follow below.

• Mark et

Methods: To measure the economic value of environmenta l improvements, market methods rely upon the direct link between the quality or st ock of an environmental good or service and the supply or demand fo r that mar ket commodity. Market methods can be used, for example, t o characterize

the effect of an increase in commercial fish and shellfish harvest s on market prices. In turn, these market changes affect the welfare o f consumers and producers in quantifiable ways.

• Revealed Preference: Revealed preference approaches are premised on the assumption that the value of natural resource services to users of thos e serv ices can be inferred by indirect economic measures. For example , willi ngness to pay for recreational beach services can be estimated b y observing how the n umber of visits individuals make to a beach varies with the co st of traveling to the beach. Similarly, property values can b e in fluenced by proximity to an environmental amenity or disamenity ; econometric analysis can e stimate the nature and magnitude of such effects, providing a basis for valuing natural resource services.3-8

• Stated Preference: Stated preference models involve the direct elicitation of economic values from individuals through the use of carefully designe d and admi nistered surveys. Contingent valuation techniques are the mos t widely used stated preference approach, and rely on surveys designed t o derive people's willingness to pay for an amenity (e.g., improved wate r quality) de scribed in the study. This method can be used to estimate bot h use and non-use values.

• Averte d Cost: Changes in environmental quality can impose additiona l costs on the users of an affected resource. For example, contamination o f drinking water supplies might lead homeowners to purchase in-home water filters. A potenti al proxy measure of the benefits of preventing pollution of the resource is the averted cost of these expenditures.

3.4.3 Valuation of CAFO Regulatory Benefits Based on Previous Studies Because of their high resource demands, the use of primary approaches is beyond the scope of this analysis. Instead, the analysis draws on previous studies that evaluated similar water quality benefits issues. This approach—typically referred to as "benefits transfer"—involves the applicatio n of values, functions, or data from existing studies to estimate the benefits of the resource change s currently being considered, and is commonly used in analyzing the benefits of propose d enviro nmental regulations. The primary research material and analytic approach used for th e valuation of each benefit category are summarized below; more detailed descriptions of the method s applied are provided in subsequent chapters of this report.

• Impr ovements in Water Quality and Suitability for Recreationa l Activities: To d etermine how people value improvements in the suitability of wate r resources for recreational activities (e.g., fishing, swimming), th e analys is relies on the results of a contingent valuation survey conducted b y Carson and Mitchell (1993). Based on this study, economic benefits ar e determined

from people's willingness to pay for achievement of water qualit y levels that restore affected waters to fishable or swimmable conditions.

• Re duced Incidence of Fish Kills: The valuation of benefits from th e reduced incidence of fish kills is based on fish replacement costs, as reflecte d in an A merican Fisheries Society (1990) report. Because this valu e represents only a portion of the economic damages associated with fish kills, it likely provides a conservative estimate of the benefits of reducing th e frequency of such events.3-9

• Improv ed Commercial Shell Fishing: To value the economic benefit o f increased shellfish harvests, the analysis relies on available literature tha t models consumers' demand for shellfish. Based on the demand equation s from these primary sources, EPA determines the increase in consumer surplu s that would result from increased harvests.

• Reduced Contamination of Private Wells: The analysis surveys th e literature concerning the values people p lace on avoiding or reducing nitrate contamination in private domestic wells. Based on this review, it develops estimates of people's willingness-to-pay to reduce nitrate concentrations t o certain levels, and applies these estimates to value predicted changes in the quality of water that supplies private wells.

3.4.4 Aggregating Benefits The fi nal step in determining the benefits of the proposed CAFO regulatory scenarios i s aggregation of the benefits calculate d for each of the benefit categories. To avoid over-estimation, this requ ires consideration of the extent to which underlying analyses may double-count certai n benefits. For this analysis, however, the benefits that each of the underlying studies explore ar e relatively distinct. As a result, the potential for double-counting appears to be small. Another con sideration in aggregating benefits is ensuring that all values are reported on a comparable basis, taking into account the effects of inflation on real dollar values. For purposes of this analysis, all values are reported in 1999 dollars. The price indices employed in convertin g source data to 1999 dollars vary, depending on which index is most appropriate. Further informatio n on these adjustments is provided in the detailed discussion of each analysis. The detailed analyses presented in Chapters 4 through 7 report benefits on an annual basis. To determine the present value of these benefits, EPA employs three alternative discount rates: a 7 percent real discount rate, which is representative o f the real rate of return on private investments and consistent with the rate mandated by the Office of Management and Budget for analysis o f proposed regulations; a 3 percent real discount rate, which is representative of the social rate of tim e prefe rence for consumption of goods and services, and consistent with the rate recommended b y many economists for analysis of environmental benefits; and a 5 percent real discount rate, which represents the mid-point of the 3 and 7 percent range.
In calculating the present value of benefits at the time new regulations are implemented, EP A assumes an in finite time frame; i.e., as long as the regulations remain in effect, the associate d benefits will be enjoyed in perpetuity. EPA further assu mes that its estimates of beneficial impacts on surface water resources will be fully re alized in the year immediately following implementation of the revised regulations. This assumption reflects EPA's judgm ent that reductions in the loadings of pollutants from CAFOs will quickly yield improvements in surface water quality. With respect to reduced contamination of private wells, however, EPA assumes that several years will pass befor e the full benefits of the regulation are realized. To permit consiste nt comparison of these benefits to the ann ual benefits estimated for surface water resources, EPA presents the benefits of reduce d3-10

contaminatio n of private wells on an annualized basis, as well as on a present value basis. Th e calculation of an annua lized value for this benefits category indicates the constant flow of benefits over time that would generate the same present value as the anticipated, uneven, flow of benefits. Additional informati on on the calculation of present values and the aggregation of benefits is presented in Chapter 8.

3.5 SUMMARY Exhib it 3-2 summarizes EPA's approach to measuring and valuing the anticipated benefits of the revised CAFO regulation s. Additional information on the methods employed is provided in the detailed discussion of each analysis that follows.

Exhibit 3-2 SUMMARY OF APPROACH TO ESTIMATING REGULATORY BENEFITS Benefit Category Human Use Measurement Approach Valuation Approach Improvements in Recreational fishing, Model potential changes in Stated preference approach Water Quality and swimming, and non-use water quality based on assessing willingness-toSuitability for benefits associated with estimated changes in pay for water quality that Recreational surface water resources. loadings of CAFO-related supports recreation. Activities pollutants. Reduced Incidence Recreational fishing, near- Estimate changes in the Avoided damages based on of Fish Kills stream use and non-use frequency of fish kill events fish replacement costs.

benefits. based on estimated reductions in nutrient loadings. Improved Commercial shellfishing. Estimate increased access to Market estimate of Commercial shellfish growing waters increased consumer surplus. Shellfishing and resulting increase in annual shellfish harvests, based on modeled changes in fecal coliform concentrations. Reduced Drinking water. Model potential changes in Stated preference approach Contamination of private domestic well water assessing willingness-toPrivate Wells quality based on estimated pay to reduce the changes in loadings of concentration of nitrates in CAFO-related pollutants. water drawn from private domestic wells.3-11

3.6 REFERENCES AFS. 1990. American Fisheries Society Socioeconomics Section, A Handbook of Monetary Value s of Fishes and Fish-Kill Counting Guidelines, Draft, July 1990. Carson, Richard T. and Robert Cameron Mitchel l. 1993. "The Value of Clean Water: The Public's Willingn ess to Pay for Boatable, Fishable, and Swimmable Water Quality." Wate r Resources Research , Vol. 29, No. 7.4-1

MODELING OF IMPROVEMENTS IN SURFACE WATER QUALITY AND BENEFITS OF ACHIEVING RECREATIONAL USE LEVELS CHAPTER 4

______________________________________________________________________________
4.1 INTRODUCTION AND OVERVIEW A major component of EPA's CAFO benefits analysis is an assessment of how water quali ty in freshwater rivers and lakes would be influenced by reduced CAFO pollu tion, accompanied by an evaluation of the economic value of these changes to society. EPA has d eveloped a comprehensive analysis o f these benefits using the methodology summarized in Exhibit 4-1. As shown, ke y components of the analysis include: C Development

of model facilities that typify conditions across different production sectors, facility sizes, and geographic regions; C Modeling of "edge-of-field" pollutant releases that take into account manure managemen t practices, manure constituents, and physical conditions (e.g., soil characteristics); C Calculation of the number of AFOs in the various production sectors/size categories to allo w extrapolation of the model facility loadings estimates; C Modeling of the change in surface water pollutan t concentrations as determined by changes in loadings; and C Valuation of the water quality changes through a benefits transfer analysis focused prim arily on the public's willingness to pay for improved water conditions necessary to suppor t recreation.

EPA implements this set of analyses for baseline conditions as well as the various regulator y scenarios under consideration to allow estim ation of overall water quality benefits. The following sections summarize the five analytic components and the resulting estimates.Exhibit 4-1 OVERVIEW OF RECREATIONAL BENEFITS ANALYSIS

Model Facility Analysis Edge-of-Field Loadings Analysis

Analysis of AFO/CAFO Distribution Valuation of Water Quality Changes Surface Water Modeling

Exhibit 4-2 MODEL FACILITY ANALYSIS

• Number of Operations

• Available Land for Manure Applications

• Typical Cropping Systems and Yields

• Crop Removal Rates • Manure Production

• Nutrient Content

• Pathogen & Metal Content Agronomic Manure Application Rates 1997 Census of Agriculture Input Data: Analyses: Define

Model Facility Calculate Pollutant Production Determine Application Rates and Nutrient Removal Capabilities for Model Facility Calculate Excess Nutrients Applied

Note that for th is analysis, the term agriculture facility, facility, or operation includes the 23 feedlot and the land application area under the control of the feedlot operator. 4-2 4.2 MODEL FACILITY ANALYSIS Assessing the impacts of CAFO regulatory scenarios requires that EPA recognize th e diversity of animal feeding opera tions across the country. Exhibit 4-2 provides an overview of the analysis used to define model facilities and their associated pollution potential. For detaile d 23 information regard ing the development of model facilities, see Chapters 4 and 11 of the Technical Development

Document of Proposed Effluent Limitations Guidelines for Animal Feeding Operation s (EPA, 2000a), hereafter referred to as the "TDD".S i o u x / P o r k Y u m a P o r k L a n c a s t e r B e e f

S c o t t / B e e f W i c o m i c o P o u l t r y F r e s n o / P o u l t r y
B a r r y / P o u l t r y T u l a r e D a i r y - P o r k B e n t o n P o u l t r y D u p l i n P o r k D e a f S m i t h / B e e f M a c o n P o r k I m p e r i a l / B e e f E r a t h / D a i r y S h e l b y P o u l t r y O k e e c h o b e e B e e f

- D a i r y M a r a t h o n D a i r y W y o m i n g D a i r y 

### P a c i f i c C e n t r a l M i d w e s t

S o u t h M i d

- A t l a n t i c

A F O R e g i o n s S t a t e B o u n d a

r i e s C o u n t y w i t

h H i g h e s t P r o d u c t i o n b y S e c t o r H i s t o r i c a l C l i m a t e S t a t i o n

4-3 Exhibit 4-3 GEOGRAPHIC REGIONS FOR GROUPING AFOS First, EPA disaggregates the universe of AFOs according to a suite of characteristics directl y affecting manure generation, manure management, and pollutant loadings. AFOs are grouped into five geographic regions, as shown in Exhibit 4-3. To establ ish geographic regions, EPA developed algorithms to estimate the number of facilities by siz e (number of animals), using a combination of inventory and sales data. NASS applied the algorithms to 1997 Census of Agriculture data t o generate the output

by which EPA estimated facility counts. Due to disclosure criteria established by N ASS to protect respondent-level census data, the regions were aggregated into broade r production regions.

Within each geographic region, EPA defines model facilities by production sector, subsector , and siz e (number of animals). Based on these various dimensions, an example of a model facilit y would be a large beef facility with more than 8,000 head in the Midwest region. Exhibit 4- 4The USDA animal unit is based on average liveweight of the animal, and is markedl y 24 different from the animal unit definition in EPA’s regulations at 40 CFR 122 and 412. Me tal production (zinc, copper, cadmium, nickel, lead) is calculated in terms of pound s 25 of metals excreted per animal unit, while pathogen production (fecal coliform and feca l streptococcus) is calculated in terms of colonies per animal unit. 4-4 summarizes the key dimensions on which model facilities are defined. In all, EPA considered 200 different model facilities. The key model facilities are those that reflect the majority of production, resulting in approximately 76 different model facilities used for further analysis.

Exhibit 4-4 SUMMARY OF MODEL FACILITY DIMENSIONS Production Sector Facility Size Regions Beef, cattle >1,000 Animal Units Pacific Beef, veal 500-1,000 Animal Units Central Dairy, milk 300-500 Animal Units Midwest Dairy, heifers South Swine, farrow-finish Mid-Atlantic Swine, grower-finish Layer, wet manure system Layer, dry manure system Broiler Turkey

To guide the selection of modeling parameters related to fields and soils , EPA must identify a specif ic location for each model facility in a given geographic region. For these purposes, th e analysis assu mes that the model facility is located in the highest animal-production county of th e region's highest production state for a given animal type. EPA calculates manure production and the associated production of pollutants for each mode l facility using a process developed by Lander, et al. (1998), and refined by Kellogg, et al. (2000). Th e number of animals per operation is converted to USDA animal units using conversion factor s 24 standardi zed to a 1,000-pound beef cow. EPA multiplies the number of animal units per mode l facility by the manure production per animal unit to determine total manure production. Manur e producti on is adjusted to reflect the fraction that is recoverable, i.e., the portion of manure that i s collected, stored, or otherwise managed so as to be available for land application. Finally, EP A calculates total generation of nutrients based on the typical nitrogen and phosphorus concentrations per unit of recoverable manure for each animal type, e.g., pounds of nitrogen per ton of manure fro m finishing pigs in the swine sector. 25EPA assumes that 30 percent of the animal waste's nitrogen content volati lizes during and 26 shortly after land applicatio n. The analysis also assumes that facilities use no fertilizers other than manure. For consistency, pollutant loadings from the o ff-site cropland to which these facilities are

27 assu med to ship manure are also captured in the baseline analysis. The modeling of baselin e conditions assumes the application of commercial fertilizer to this land. 4-5 Next, EPA defines land application practices for each model facility and the capacity for soi l and crop removal of nutrients applied to the land. This analysis entails several steps. The analysis firs t considers the total nitrogen and phosphorus generated in manure at the model facility. EP A divi des these figures by the average total acreage available for land application of manure for a n operation in the given region, size class, and production sector; this average acreage is drawn from a recent NRCS study (Kellogg et al., 2000). EPA then considers the likely cropping systems at the model facilities and relates the quantit y of nutrients applied annually to cropland and pastureland nutrient requirements. For example, typica l cropping systems for the Mid-Atlantic AFO Region are corn, soybean, and wheat in two-yea r rotatio n. The ratio of nutrients applied to crop nutrient requirements provides a measure of th e excess nutrients applied in the manure. This in turn forms the foundation for loadings analyses of 26 regulat ory

scenarios that call for adherence to agronomic rates of nutrient application. T o characterize land application practices, the analysis considers three categories of facilities:

• Category 1 facilities include CAFOs with suffic ient crop- or pastureland onsite to a pply the manure they generate at agronomic rates. The analysi s ass umes that these facilities apply all manure on-site (i.e., no manure i s shipped off-site) under both baseline and post-regulatory conditions.

• Category 2 facilities include those with insufficient crop- or pastureland onsi te to apply the manure they generate at agronomic rates. For the baselin e scenario, the a nalysis assumes that these facilities apply all the manure they genera te on-site, regardless of the degree to which agronomic applicatio n rates are exceeded. For the post-regulatory scenarios, the analysis assumes that on-site manure application i s limited to the agronomic rate, and that the remaining m anure is shipped off-site for application to crop- or pastureland at agronomic ra tes. EPA's model captures the pollutant loadings associated with both on-site and off-site application of the manure generated b y Category 2 facilities. (The sole exception to this approach occurs i n

27 modeling loadings from Category 2 broiler operations. The baseline analysi s caps on-site application of thi s manure at five times the agronomic rate; any excess m anure is assumed to be shipped off-site. The analysis of post

regulatory conditions assumes that Category 2 broiler facilities apply m anure4-6 on-site only up to the agronomic rate, beyond which the excess is shipped off

site. In both cases, the manure shipped off-site is not captured in the loading s modeling.)

• Cat egory

3 facilities include CAFOs without cropland. EPA assumes tha t these facilities transfer all manure off-site for use or disposal. The pollutant loadin gs associated with this manure are not captured in modeling eithe r baseline or post-regulatory conditions.

4.3 EDGE-OF-FIELD LOADINGS ANALYSIS The second major component of the water quality analysis is estimation of pollutant loading s leaving the model facility, i.e., edge-of-field loadings. EPA estimates the loadings associated with: ( 1 ) application of manure; (2) lagoons and other storage structures; and (3) feedlots. The sections below review the methods applied for each of these analyses.

4.3.1 Loadings from Manure Application EPA's loadings analysis first examines loadings from manure application to cropland an d pastureland. The analysis combines information on manure generation and land application practice s (see above ) with data on the timing of application, hydrological conditions, geological conditions, and weather pa tterns (see Exhibit 4-5). EPA integrates these data using the Groundwater Loading Effects of Agricultural Management Systems (GLEAMS ) model. This field-scale model simulates hydrologic transport, erosion, and biochemical processes such as chemical tr ansformation and plant uptake. The model uses information on soil characteristics and climate, along with nutrien t production data, to model losses of nutrients in surface runoff, sediment , and groundwater leachate. Loadings a re modeled for the pre- and post-regulatory scenarios to estimate changes in loading s attributable to the proposed standards. The data used in the GLEAMS model runs include the following: C Soils Data : GLEAMS uses data from the State Soil Geographic (STATSGO) data bas e maintained

by USDA's Natural Resources Conservation Service. Key soil parameters draw n or estimated from the data base include permeability, soil porosity, baseline organic matter con tent, percent clay, and percent silt. EPA employs data on these parameters, i n combination with data on other factors (see below), to characterize soil erosion, surfac e runoff, and groundwater leaching at model facilities.Exhibit 4-5 EDGE-OF-FIELD LOADINGS ANALYSIS FOR MODEL FACILITIES

Excess Nutrients Applied (from model facility analysis) Farm Practice Data/Assumptions:

• Planting Date

• Harvest Data

• Manure Application Date
Soils Information (permeability, porosity, etc.)

Climate Data

Manure Characteristics GLEAMS Modeling to Calculate Pollutant Runoff from Manure Application

Calculate Seepage Losses from Lagoons and Other Storage Structures

Calculate Feedlot Runoff Total Loadings for Each Model Facility (pre-and post-regulation) Input Data Analyses

4-7 C Climate Data : EPA prepared climate data using CLIGEN, a synthetic climate generato r commonly us ed in conjunction with a variety of agricultural runoff models. CLIGE N simulates weather patterns based on 25 or more years of precipitation and temperature data. C Crop Pla nting and Harvest Dates : EPA developed assumptions for crop planting an d ha rvesting using USDA reports and determined likely manure application dates for mode l facilities based on contacts with USDA Extension Agents in relevant locations. Th e application dates are a function of the crops grown. Some single-cycle crops (e.g., corn ) allow on ly one application per year, while other crops (e.g., alfalfa) allow multipl e applications.

4.3.2 Loadings from Lagoons and Other Storage Structures Lagoons and other m anure storage structures at animal feedlots are also potential pollution sources, posing risks primarily through seepage to groundwater and subsequent discharge to surface water. For the purposes of this analysi s, EPA assumes that all lagoons and other storage structures le ak. Storage structure seepage estimates were obtained from Ham and DeSutter (1999), wh o m e asured nitrogen that leaked from three established swine-waste lagoons in Kansas. From these results, it was assumed that 2,000 pounds per acre per year leaked from manure storage structuresEPA assumes that only surface runoff occurs from the feedlot. 28 4-8 lined with silt loam soils. EPA scales seepage estimates for clay and sandy soils from thes e estimates as described in the TDD. Fo r most storage structures, EPA models transport of pollution through groundwater an d estimates the associated attenuation of pollutants. However, conditions in some cases (as defin ed by Sobe cki and Clipper, 1999) suggest that leaks from lagoons or other storage structures may see p di rectly to surface water, i.e., hydrologic conditions are such that pollutant concentrations are no t attenuated by dilution in groundwater. This might occur, for example, in the presence of sandy soil s or karst-like terrain. To characterize the potential for leaks from lago ons or other storage structures to se ep directly to surface water, EPA evaluated soil and hydrological conditions in each AF O region. Based on this evaluation, EPA determined the percentage of the region's area in which the potential for direct contamination of surface water is high. EPA's analysis assumes that thi s percentage of storage leaks in each region would result in direct contamination of surface water.

4.3.3 Loadings from Feedlots Another pollution source that EPA analy zes is runoff from feedlots. These loadings can be particularly significant in the beef sector because the animals are typically housed in open lots. To estimate feedlot runoff loadings, EPA first calculates the volume of runoff from th e feedlot at the model facility. The annual depth of runoff from the feedlot is calculated for each of the five AFO regions using average precipitation from the National Climatic Data Center. Th e volume of runof

f is calculated using this depth of runoff and the estimated area of the dry lot an d feedlot handling areas for each model facility. 28
To charac terize the loadings of pollutants in feedlot runoff, EPA assumes a solids conten t of 1.5 p ercent. The composition of these solids is estimated based on the characteristics of dr y manure, which varies across production sectors. Annual loadings of specific pollutants are the n determined, based on the estimated composition of solids, the assumed percentage of solids i n feedlot runoff, and the estimated annual volume of runoff from the feedlot.

4.3.4 Model Loadings Under Regulatory Scenarios EPA applies the data and methods described above to analyze loadings associated wit h baseline conditions and each of the various regulatory scenarios. Under all of the options, th e analysis assumes that regulated facilities modify current activities to comply with feedlot bes tIn prior years, the Census was conducted by the Department of Commerce’s Bureau of th e 29 Census. 4-9 man agement

practices, mortality handling requirements, nutrient management planning / recordkeeping, and elimination of manure application within 100 feet of surface water . Factors that vary among regulatory scenarios that may impact loadings include: C reduction of manure application to agronomic nitrogen rates; and C reduction of manure application to agronomic phosphorous rates.

4.4 ANALYSIS OF AFO/CAFO DISTRIBUTION To develop a national estimate of baseline pollutant loadings from AFOs, as well as estimate s of the change in l oadings under alternate regulatory scenarios, EPA must determine the number of operati ons that would be governed by the proposed regulations, i.e., the number of facilitie s considered to be AFOs and the num ber of AFOs considered to be CAFOs, and therefore subject to the proposed rule. These operations represent the universe to which model facility results ar e extrapolated. The se ctions below discuss EPA's approach and the resulting characterization of th e population of AFOs and CAFOs. More detailed information on the procedure used by EPA t o estimate the number of operations that may be subject to the proposed regulations can be found in the TDD (USEPA, 2000a).

4.4.1 Approach EPA e stimates the number of operations that may be affected by alternative requirement s using a two-step procedure. First, EPA determines the number of operations that raise animals unde r con finement

by using available data on the total number of livestock and poultry facilities (se e below). Next, the number of CAFOs is determined b ased on operations that are defined as CAFOs and smal ler operations that are designated as CAFOs based on site-specific conditions, a s det ermined by the permitting authority. For purposes of this discussion, the affected CAF O population includes those facilities that discharge or have the potential to discharge to U.S. waters. This definiti on does not include those smaller operations that are not defined or designated a s CAFOs. The USDA C ensus of Agriculture is a complete accounting of United States agricultura l production and is the only source of uniform, comprehensive agricultural data for every county in the na tion. The Census is conducted every five years by USDA's National Agricultural Statistic s Service (NASS). The Census is implem ented through a mail questionnaire that is sent to a list of 29 known U .S. agriculture operations from which $1,000 or more of agricultural products wer e produced and sold or normally would have been sold during the census year.Available information from USDA indicates that few large hog operations are non

30 confinement

facilities (USDA/APHIS, 1995); therefore EPA assumes that all hog operations with more than 2,500 swine are AFOs. 4-10 Aggregated 1997 Census data are readily available from USDA. In general, the published compendium provides summary invent ory and sales data for the nation and for states. The Census database itself, however, contains respondent-level information that can be aggregated into mor e precise agric ulture facility size groupings. The requested data summaries used for EPA’s analysis were compiled with the assistance of staff at USDA's NASS, who performed special tabulations of the data to obtain information on the characteristics of facilities at specific size thresholds for each sector
. All data provided to EPA were aggregated to ensure the confidentiality of an individua l operatio n. EPA supplemented the available data with information from other sources, includin g other USDA data sets and industr y publications. The following discussion briefly notes the nature of key gaps in the Census data and EPA's approach to addressing them. C All USDA data are report ed across all animal agriculture operations and do not distinguish be tween confinement and nonconfinement production types (e.g., pasture or rangelan d animals). However, only operations that raise animals under confine ment (as defined under 40 CFR 122 Appendix B) would be subject to the proposed regulations. For analytica l purposes, EPA has assumed that all animals at larger dairy and poultry operations ar e grown under confinement, which may overstate EPA’s estimate of the number of operations subjec t to the regulation. For the beef and hog sectors, the USDA has limited data on the number of ope rations that are feedlot operations only. NASS Statistical Bulletin Number 953 , Cattle: Final Estimates 1994-1998 , was used to estimate the number of beef feedlots with more than 1,000 head; 1997 Census data on "Cattle fattened on grains and concentrate s (sold)" are used to distinguish confinement from non-confinement operations with less than 1,000 head (USDA/NASS, 1999a; USDA/NASS, 1999b). Available information from USD A and industry feedback was used to adjust the total number of hog operations to exclude thos e that are pasture operations (USDA/Animal and Plant Health Inspection Service, 1995 ; NPPC, 1997). 30 C Available Census data on the number of animal facilities by inventory size distribution do not always correspond with the facility size definitions examined by EPA. Where data were not available in the desired size ranges, EPA interpolated estimates from available data by a s suming that, for a given size group, the largest 40 percent of the facilities account for 60 percent of the animal inventory.4-11

C USDA data are also not available for the number of poultry operations with wet manur e management systems. EPA estimated these figures using available data from USDA an d supplemental information from industry experts and agricultural extension agency personnel

. C Info rmation on the number of animal facilities that raise more than a single animal type i s also no t available. EPA algorithms written for use with the 1992 Census data included a n estimate of CAFOs that maintained more than one animal type. The analysis revealed that, for facilities with more than 1000 animal units, 21 pe rcent raise more than one animal type; for facilities with less than 1000 animal units, about 25 percent raise more than one animal type. To the extent that combinations of animal types are located at facilities, facility counts may be overstated. C Finally, USDA Census data report the number and s ize of livestock and poultry facilities as of ye ar-end (December 31) and may not adequately reflect seasonal fluctuations in beef , dairy, and layer inventory, or the yea r-to-year fluctuations in number of animals sold. EPA algo rithms reflect average herd sizes at larger confinement facilities over the year. Th e outputs are based on both reported inventory and sales, adjusted by expected turnovers. Thi s approach is consistent with that developed by USDA to estimate potential manure nutrient loadings from animal agriculture (Lander, et al., 1998; Kellogg, et al., 2000).

4.4.2 Estimated Number of AFOs and CAFOs Based on the USDA data sources described above, there were 1.2 million livestock an d poultry facilities in the United States in 1997. This number includes all operations in the beef, dairy , pork , broiler, layer, and turkey production sectors, and includes both confinement and non

confinement (grazing and range fed) production. Of all these operations, EPA estimates that there are about 376,000 AFOs that raise or hous e animals in confinement, as defined by the existing regulations. Exhibit 4-6 summari zes the number of AFOs by production sector and facility size.This number is likely the upper bound estimate of the to tal number of operations that will 31 be subject to the proposed revisions. 4-12 Exhibit 4-6 TOTAL NUMBER OF AFOs BY PRODUCTION SECTOR AND FACILITY SIZE Production Sector Total AFOs >1000 AU 300 AU-1000 AU <300 AU 1 Beef: cattle 106,080 2,080 2,000 102,000 Beef: veal 850 10 200 640 Dairy: milk 116,880 1,450 5,690 109,740 Dairy: heifers 1,250 400 750 100 Hogs: FF 2 64,240 2,420 9,240 52,580 Hogs: GF 2 53,620 1,670 3,250 48,700 Broilers 34,860 3,940 10,200 20,720 Layers: wet 3 3,110 360 800 1,950 Layers: dry 3 72,060 360 1,330 70,370 Turkeys 13,720 370 1,730 11,620 Sum Total 466,670 13,060 35,190 418,420 Total AFOs 375,740 12,850 28,150 334,740

4 Source: Values presented in the table are EPA estimates, derived from published US DA/NASS data, including 1997 Census of Agriculture. For more information, see Technical Development Document of Proposed Effluent Limitation s Guidelines for Animal Feeding Operations

. As defined by the existing regulation, one animal unit (AU) is equivalent to one slaughter or feeder cattle; 0.7 m ature dairy 1 cattle; 2.5 hogs (over 55 pounds); 0.5 horses; 10 sheep or lambs; 55 turk eys; 100 laying hens or broilers (with continuous overflow watering); 30 laying hens or broilers (with liquid manure system); or 5 ducks. FF = farrow-fi nish (includes breeder and nursery pigs); GF=grower-finish. Data from USDA’s NAHMS indicate tha t 2 roughly 40 percent of hog farms are grower-finish and 60 percent are farrowing operations. The “Layers : wet” category covers operations with liquid manure systems. Such AFOs are currently defined as CAFOs 3 for operat ions with 30,000 birds (1,000 AUs). No layer operations use continuous watering systems. “Layers: dry” are defined at 1,000 AUs for operations with 100,000 birds. “Total AFOs” eliminates double counting of operations with mixed animal types. Operations with mixed animal types 4 account for roughly 20 percent of total AFOs.

Exhibit 4-7 summarizes the total number of CAFOs defined or designated un der each of the reg ulatory scenarios. Under the proposed scenarios, between about 29,000 and 33,500 AFOs will be defined or designated as CAFOs, and are therefore subject to the proposed rule. 314-13 Exhibit 4-7 TOTAL NUMBER OF CAFOs BY REGULATORY SCENARIO Regulatory Scenario Total CAFOs Option 1-Scenario 1 17,700 Option 1-Scenario 2/3 33,500 Option 1-Scenario 4a 28,980 Option 1-Scenario 4b 45,140 Option 2-Scenario 1 17,700 Option 2-Scenario 2/3* 33,500 Option 2-Scenario 4a* 28,980 Option 2-Scenario 4b 45,140 Source: Values p resented in the table are EPA estimates, derived fro m published USDA/NASS data, including 1997 Census o f Agri culture. For more information, see Technical Developmen t Document of Proposed Effluent Limitations Guidelines for Animal Feeding Operations

. * Proposed scenarios.

4.4.3 Geographic Placement of Facilities Finally, AFOs and CAFOs by region are placed into counties (and eventually watersheds ) using the pub lished county level Census data. Where county level data was not presented, th e facilities in the undisclosed counties were imputed from state- and region-level data.

4.5 SURFACE WATER MODELING EPA develops estimates of changes in surface water quality by building on the analysis of edge-of -field pollutant loadings for model facilities and the analysis of the distribution o f AFOs an d CAFOs. These data are integrated into the National Water Pollution Contro l Assessment Model (NWPCAM), a national-scale model designed to translate pollutant loadings into w ater quality changes and associated economic benefits to support policy-level regulator y decisionmaking.NWPCAM does not address water qua lity benefits in bays, estuarine waters, or the Great 32 Lakes. Both the water quality modeling and the economic benefits analysis are presented in greate r

33 detail in Estimation of National Surface Water Quality Benefits of Regulating Conce ntrated Animal Fee ding Operations (CAFOs) Using the National Water Pollution Control Assessment Mode l (NWPCAM) (USEPA, 2000b). This report is provided under separate cover as Attachment A. 4-14 NWPCAM covers virtually all inlan d waters in the U.S., allowing EPA to examine how chan ges in loadings under various regulatory scenarios would influence key water qualit y parame ters. The model incorporates routines that simulate overland transport of pollutants ,

32 disch arge of pollutants to nearby surface waters, discharges to surface water from other (non

AFO /CAFO) sources, and the fate and transport of pollutants in the interconnected network o f surface waters. Specifically, the modeling involves the following steps: C Developing the network of rivers and streams that serves as the geographic foundation fo r the modeling; C Distributing AFO/CAFOs and associated facility-level edge-of-field loadings t o agricultural lands within a defined watershed or county; C Sim ulating transport of nutrients/pollutants and subsequent discharge to nearb y waterbodies; C Delivering nutrient/pollutant loadings from point sources (e.g., municipal wastewate r treatme ntplants, industrial facilities) and non-point sources (e.g., non-AFO/CAF O agricultural run-off, municipal run-off) to waterbodies; and C Simul ating dilution, transport, and kinetics of the nutrients/pollutants loaded to th e waterbody as the nutrients/pollutants are transported along the waterbody. Exhibit 4-8 summarizes these steps and the primary data used in the analysis. The sections belo w discuss the modeling in more detail and provide an overview of the estimated changes in pollutan t loadings under the various regulatory scenarios. 33Exhibit 4-8 WATER QUALITY MODELING ANALYSIS

Analyses:

Input Data: Develop Hydrologic Network Distribute AFOs/CAFOs to Agricultural Land Calculate Nutrient/Pollutant Loadings from AFOs/CAFOs to Waterbodies

• Reach File Data on Surface Waters

• Land Use/Land Cover Data

• Watershed Data AFO/CAFO Facilities by County Edge-of-Field

Loadings Data Deliver Loadings from Other Point and Non-Point Sources to Waterbodies Simulate Fate and Transport of Pollutants

• Loadings Data for Point Sources

• Loadings Data for Non-Point Sources (other than AFOs/CAFOs)

RF3 includes numerous small tributaries and headwaters. To simplify the m odeling, EPA 34 focuses on loadings to a subset of larger rivers and streams (referred to as "RF3 Lite"). Unles s otherwise noted, the water quality and economic modeling results reported bel ow reflect changes in loadings to the RF3 Lite subset of RF3. 4-15 4.5.1 Defining the Hydrologic Network
In the init ial step of the analysis, EPA prepares the hydrological network of rivers an d streams that serves as the geographic backdrop to the modeling. The hydrological network i s developed from EPA's Reach Files, a series of hydrologic databases describing the inland surfac e waters of the U.S. Each "re ach" in the database represents a segment of a river or stream; these se gments are linked together to characterize complete systems of rivers and streams. EPA' s Reach File 3 (RF3) forms the geographic foundation for NWPCAM, allowing the model t o si mulate the flow of water and pollutants from a point of origin to major rivers, and ultimatel y to ocean discharge. 34 Once the hydr ologic network is established, EPA uses a geographic information system (G IS) approach to overlay information on land-cover, characterizing land across the U.S. at a squar e-kilometer

degree of resolution. From these data, EPA can identify areas classified a s "agricultural" land. Each land section, or "cell", is associated with a river reach in the hydrolo gic network.EPA di d not model facilities below 300 animal units. Discharges from these smal l 35 operations were included in the agriculture nonpoint source component. Non-point source data for fecal coliform, fecal streptococci, and sediments were no t 36 available at the national level; therefore, only nutrients are covered in the analysis of non-AFO nonpoint sources. 4-16 4.5.2 Distributing AFOs and CAFOs to Agricultural Land Once the hydrologic network is established, NWPCAM integrates data on the lo cation of AFOs and CAFOs to spatially orient the facilities relative to surface waters. This analytic step links directly to the analyses discussed above wherein EPA determined the numbers of AFOs an d CAFOs by county and, through analysis of model facilit ies, estimated the edge-of-field loadings associated with each facility. Here, AFOs/CAFOs and their associated edge-of-field loadings ar e rando mly distributed to agricultural land in the appropriate county. By placing each facility i n a land use cell, the facility can be linked to a river reach in the hydrologic network. 35

4.5.3 Calculating AFO/CAFO-Related Loadings to Waterbodies Once facility pollutant loadings are linked to a geographic area and river reach, thes e l o adings are delivered from the agriculture cells to the river reaches using a routine to simulate an overland transport process. Overland travel ti mes and associated nutrient decay are based on flow in a natural ditch or channel, as may typically be found on a gricultural lands. A unit runoff (ft /sec/km ) is derived for each watershed based on data compiled by the U.S. Geological Survey

. 3 2 The unit runoff therefo re represents runoff from each agricultural cell within the watershed and can be used to derive time-of-travel estimat es necessary to route pollutants from the facility to a river reach. NWPCAM also calculates nutrient/pollutant decay associated with overlan d transport. Total loadings to any given river reach are the total loadings dischar ged from all landuse cells draining to the reach (as well as discharges from upstream river reaches).

4.5.4 Loadings from Other Sources In addition to loadings from AFOs/CAFOs, NWPCAM integrates data on loadings from other pollutant sources. This complet e inventory of loadings is needed to assess the cumulative changes in water quality (i.e., the attainment of beneficial use levels) in surface waters

. Specifically, the model integrates data on discharges from municipal and industrial po int sources as well as loadings from (non-AFO) non-point sources. These loadings are constant acros s regulatory

scenarios. To model nutrient loads for non-point sources, EPA uses SPARRO W ( S PA tially R eferenced R egression O n W atershed attributes) (Smith, et al., 1997), a statistica l modeling approach for estimating major nutrient source loadings at a detailed geographic scale based on watershed characteristics. 364-17

4.5.5 Fate and Transport Modeling Onc e all loadings to surface waters have been estimated, NWPCAM routes pollutant s through the hydrologic network from upstream to downstream reaches. The model simulate s pollutant d ecay during this routing process. The resulting pollutant concentrations are the n compa red to beneficial use criteria to determine how potential recreational uses would chang e with improved water quality (see below).

4.5.6 Estimated Changes in Loadings Exhibit 4-9a sum marizes the NWPCAM estimates of baseline loadings from AFOs and CAFO s and shows loadings under the various regulatory scenarios. Similarly, Exhibit 4-9 b presents the resulting removals under each of the regulatory scenarios. As shown, reduction of nutri ent and pollutant loadings is greater under the phosphorus-based standards (Option 2) , part icularly

under Option 2-Scenario 4b. Significant reductions are also realized under th e propose d scenarios; for example, nitrogen loadings are reduced from 67 million kilograms pe r year in the baseline to between 37 and 38 million kilograms per year. Exhibits 4-10a and 4-10b present additional modeling results for metals. As shown , sign ificant

reductions in loadings of metals could be realized under the regulatory scenarios

. However, these results differ from those presented above for several reasons. First, the estimat es reflect changes in loadings to the larger set of RF3 rivers and streams as opposed to the smaller set of RF3 Lite rivers and streams. Second, EPA do es not model metals independently; instead, overland transport of metals is assumed to be similar to the overland transport of phosphorus , with th e assumption that metals adhere to soil in a manner similar to phosphorus. For thes e reasons, the metals loading reductions cannot be compared directly to the reported redu ctions for nutrients and other pollutants . The metals reductions are reported here for descriptive purposes and do not play a role in the calculation of economic benefits (see below).

4.6 VALUATION OF WATER QUALITY CHANGES To val ue predicted reductions in the pollution of rivers and streams by CAFOs , NWPCAM applies estimates of Americans' willingness to pay for improvements in water quality

. This approac h first entails relating changes in water quality parameters - e.g., concentrations of chl orophyll " - to the ability of a body of water to support fishing or swimming. Once th e potential improvement in the ability of modeled rivers and streams to support these uses i s deter mined, the analysis relies upon estimates of willingness to pay for such improvement s obtained f

rom the results of a contingent valuation survey developed by Richard Carson an d Robert Mitchell. This survey, which is national in scope, characterizes households' annua l will ingness to pay to improve freshwater resources from baseline conditions to fishable o r swimmable quality.4-18 Exhibit 4-9a ESTIMATED ANNUAL AFO/CAFO NUTRIENT/POLLUTANT LOADINGS

UNDER BASELINE AND REGULATORY SCENARIOS

Regulatory Scenario (million kg) (million kg) colonies) colonies) (billion kg) Nitrogen Phosphorus (billion (billion Sediments Fecal Fecal Coliforms Streptococci

Baseline Conditions 67 76 50 117 118
Option 1-Scenario 1 53 41 24 80 118 Option 1-Scenario 2/3 52 31 19 72 118 Option 1-Scenario 4a 53 34 21 73 118 Option 1-Scenario 4b 50 28 15 70 118 Option 2-Scenario 1 43 34 21 67 92 Option 2-Scenario 2/3 * 37 22 15 57 83 Option 2-Scenario 4a* 38 24 18 59 84 Option 2-Scenario 4b 34 17 12 52 80 Source: Estimation of National Surface Wa ter Quality Benefits of Regulating Concentrated Animal Feeding Operations (CAFOs) Using the National Water Pollution Control Assessment Model (NWPCAM) , prepared for U.S. EPA Office of Wastewater M anagement, prepared by Research Triangle Institute, August 2000. * Proposed scenarios.4-19 Exhibit 4-9b ESTIMATED ANNUAL REMOVALS UNDER REGULATORY SCENARIOS

Regulatory Scenario (million kg) (million kg) colonies) colonies) kg) Nitrogen Phosphorus (billion (billion (billion Fecal Fecal Coliforms Streptococci Sediments

Option 1-Scenario 1 14 35 26 37 0 Option 1-Scenario 2/3 15 45 31 45 0
Option 1-Scenario 4a 14 42 29 44 0 Option 1-Scenario 4b 17 48 35 47 0 Option 2-Scenario 1 24 42 29 50 26 Option 2-Scenario 2/3 * 30 54 35 60 35
Option 2-Scenario 4a* 29 52 32 58 34
Option 2-Scenario 4b 33 59 38 65 38 Source: Estima tion of National Surface Water Quality Benefits of Regulating Concentrated Animal Feeding Operation s (CAFOs) Using the National Water Pollution Control Assessment Model (NWPC AM) , prepared for U.S. EPA Office of Wastewater Management, prepared by Research Triangle Institute, August 2000. * Proposed scenarios.4-20 Exhibit 4-10a ESTIMATED ANNUAL AFO/CAFO METALS LOADINGS UNDER BASELINE AND REGULATORY SCENARIOS*

Regulatory Scenario kg) kg) kg) kg) kg) Zinc Copper Cadmium Nickel Lead (million (thousand (thousand (thousand (thousand

Baseline Conditions 27 1,495 42 572 1,143
Option 1-Scenario 1 17 949 19 353 748 Option 1-Scenario 2/3 12 727 9 277 570 Option 1-Scenario 4a 13 796 11 306 613 Option 1-Scenario 4b 12 677 8 251 545 Option 2-Scenario 1 14 796 16 286 634 Option 2-Scenario 2/3* * 9 516 5 192 405 Option 2-Scenario 4a* * 10 600 7 226 457 Option 2-Scenario 4b 8 444 3 154 366 Source: National AFO/CAFO Metals Edge-of-Field Loadings and Reduction s from Agricultural Landuse Cells to RF3 Reaches for AFO/CAFO Rulemaking Scenarios, table prepared for EPA by Researc h Triangle Institute, August 2000. * Metals loadings are estimated based on modeling of the overland transport of phosphorus. These estimates do not play a role in the subsequent modeling of economic benefits. ** Proposed scenarios.4-21 Exhibit 4-10b ESTIMATED ANNUAL METALS REMOVALS UNDER REGULATORY SCENARIOS*

Regulatory Scenario kg) kg) kg) kg) kg) Zinc Copper Cadmium Nickel Lead (million (thousand (thousand (thousand (thousand
Option 1-Scenario 1 10 546 23 219 395 Option 1-Scenario 2/3 15 768 33 295 573 Option 1-Scenario 4a 14 699 31 266 530 Option 1-Scenario 4b 15 818 34 321 598 Option 2-Scenario 1 13 699 26 286 509 Option 2-Scenario 2/3 ** 18 979 37 380 738 Option 2-Scenario 4a** 17 895 35 346 686 Option 2-Scenario 4b 19 1,051 39 418 777 Source: Nati onal AFO/CAFO Metals Edge-of-Field Loadings and Reductions from Agricultural Landuse Cells to RF 3 Reaches f

or AFO/CAFO Rulemaking Scenarios, table prepared for EPA by Research Triangle Institute, Augus t 2000. * Metals loadings are estimated based on modeling of th e overland transport of phosphorus. These estimates do not play a role in the subsequent modeling of economic benefits. ** Proposed scenarios.4-22 Exhibit 4-11 WATER QUALITY LADDER The discussion that follows summarizes the valuation approach. It begins by explaining the pr ocess by which EPA relates the results of the surface water modeling effort to the abilit y of a body of water to support a particular use. It then describes Carson and Mit chell's contingent valuation study and its use in analyzing the economic benefits of alternate CAFO regulations.

4.6.1 Support of Designated Uses EPA's approach to relatin g surface water conditions to the abilit y of a b ody of water to support a parti cular designated use is based on a water qu ality index - often referred to a s a water quality "ladder" - tha t Re sources for the Future initiall y developed to support Carson an d Mitchell's contingent valuatio n survey. As Exhibit 4-11 shows, th e ladder uses a scale that ranges from 0 to 10, with 0 representing the wors t pos sible water quality and 1 0 representing the best possible quality

. The low end of the scale represent s water qu ality so poor that it supports no p lant or animal life, and huma n conta ct with it would be unsafe; th e high end of the scale represents wate r safe enough to drink. Between these extremes, the ladder depic ts levels of water quality sufficient to suppor t boating, fishing, or swimming. Each step of the water qualit y ladde r is defined by measures of th e following parameters: C dissolved oxygen content; C biological oxygen demand; C suspended sediment concentrations;The scope of the survey excluded the Great Lakes. 37 4-23 C pathogen counts; and C chlorophyll " concentrations.

In order for a body of water to be considered boatable, fishable or swimmable, it must satisfy the minimum conditions consistent with that use for all mode led parameters. With the exception of chlorophyll " , these minimum conditio ns are the same for all areas. The maximum chlorophyll

" concentration considered consistent with a particular use varies across four geographic regions , which EPA defined specifically for this analysis. This approach takes into accou nt the impact of regional variation in factors like climate on the relationship between chlorophyll " concentration s and the trophic state of a lake or reservoir. Based o n the framework described above, NWPCAM classifies each segment of eac h modeled river or stream as swimmable, fishable, boatable, or non-supportive of any of these uses

. For each s cenario analyzed, the model calculates the total stream-miles that support eac h designated use.

4.6.2 Application of CV Study The conti ngent valuation survey upon which this analysis relies examined households ' willingness t o pay to maintain or achieve specified levels of water quality in freshwater lakes , rivers and streams throughout the United States (Carson and Mitchell, 1993). The survey was 37 conducte d in 1983 via in-person interviews at 61 sampling points nationwide, and employed a national probability sample based on the 1980 Census. Respondents were presented with th e water quality ladder depicted in Exhibit 4-11 and asked to state how much they woul d be willing to pay to maintain or achieve various levels of water qu ality throughout the country. In eliciting respo nses, the survey used a payment card showing the amounts average households were then currently paying in taxes or higher prices for certain publicly provided goods (e.g., nationa l defense); respondents were then asked their w illingness to pay for a given water quality change. The survey respondents were told that improvements in water quality would be paid for in highe r product prices and higher taxes.EPA employed the Consumer Price Index to adjust 1983 values to 1999 values. I n 38 addition, the adjustment to 1999 values takes into accou nt the increase in real per capita disposable income over the period of interest. The adjustment for changes in real income is consistent w ith the surv ey's results, which found that respondents' willingness to pay for water quality improvement s increased in almost direct proportion to household income. 4-24 Exhibit 4- 12 presents the results of the survey, adjusted to account for inflation an d chan ges in real income between 1983 and 1999. These values represent "best estimates" o f 38 mean annual househ old willingness to pay (WTP) for the specified water quality improvement.

Exhibit 4-12 INDIVIDUAL HOUSEHOLD WILLINGNESS TO PAY FOR WATER QUALITY IMPROVEMENTS

(1999 $)
Water Quality Improvement Total WTP WTP Incremental
Swimmable: WTP to raise all sub-swimmable water quality to $634 $205 swimmable Fishable: WTP to raise all sub-fishable water quality to fishable $429 $184 Boatable: WTP to maintain boatable water quality $245 $245 Source: Carson and Mitchell, 1993. The val ues originally reported have been adjusted to account for inflation and changes in real income between 1983 and 1999.
Applying the willingness to pay estimates presented above to analyze the benefits o f alter nate CAFO regulations requires consideration of how households' willingness to pay fo r water quality improvements is likely to vary with the extent and location of the resources affected

. All e lse equal, people are likely to value an action that improves water quality along a ten-mile stretch of river more highly than they would value an action that improves only a one-mile stretch

. Similarly, people are likely to place greater value on improving the quality of water resources tha t are ne arer to them. This is simply because less time and expense is typically required to reac h nea rer resources; as a result, these resources generally provide lower cost and more frequen t opport unities for recreation and enjoyment. This assumption is supported by the results of th e Carson and Mitchell survey, which asked respondents to apportion their willingness to pay value s between improving the quality of local waters - where local waters were defined as those in each respondent's own state - and improving the quality of non-local waters (i.e., those lo cated out-ofsta te). On average, respondents allocated two-thirds of their values to achieving water qualit y goals in-state, and one-third to achieving those goals in the remainder of the nation.4-25

To reflect the considerations noted above, the an alysis of the benefits of alternate CAFO reg ulations examines water quality improvements on a state-by-state basis and separatel y calculates the benefits of in-state an d out-of-state improvements, assuming that households will allocate two-thirds of their willingness to pay values to the improvement of in-state waters. In addition, the analysis takes into account the extent of each scenario's estimated impacts (i.e., the number of stream-miles that impr ove from non-supportive or boatable to fishable, or from nonsupportive , boatable or fishable to swimmable) by scaling household willingness to pay for a given improvement in the quality of the nation's waters by the proportion of total stream-miles in-state or out-of-state that are projected to make the improvement. For purposes of thes e calculations, the analysis relies on estimates of the 1999 population and the average number of individuals per household (2.62) as reported in the Statistical Abstract of the United States

. Appendix 4-A provides a detailed summary of the calculations employed. It is im portant to note that the valuation process described above does not address a number of potential improvements in water quality. For example, the analysis assigns n o economic value to improvements in the quality of waters already classified as swimmable under the baseline scenario; the Carson and M itchell contingent valuation survey did not examine this area, and thus provides no basis for valuing such changes. In addition, the analysis does not valu e the impro vement of non-boatable waters to boatable condition. Although the survey aske d respo ndents how much they would be willing to pay to avoid a drop in water quality to non

boatable conditions, the definition of non-boatable water quality - "water containing raw sew age, with str ong odors, floating garbage and pathogens that would cause illness through huma n con tact" - was so extreme that the resulting willingness to pay values may be overstated

. Consequently, EPA has chosen n ot to employ Carson and Mitchell's estimates of willingness to pay to maintain boatable wa ter quality in this analysis. EPA is reassessing the boatable level in the water quality ladder to be more consistent with the language of the Carson and Mitchell study

. Overall, the Agency believes that the benefits calculated here are conservative because the y reflect only swimming and fishing improvements, not boating improvements or improvements in the quality of waters already considered swimmable.

4.6.3 Estimated Benefits Exhibit 4-13 presents NWPCAM's estimates of the annual economic benefits associated with each regulatory scenario. As the table indicates, the estimates range from app roximately $5 million per year under Option 1-Scenario 1 to $145 million per year under Option 2-Scenario 4 b. EP A estimates that the annual benefits of the proposed scenarios range from approximatel y $1 08.5 million per year to $127.1 million per year. Roughly 80 percent of these benefits ar e derived from improving previously non-fishable waters to fishable status. The remaining benefit s are att ributed to improving a smaller number of stream miles to swimmable condition

.4-26 Exhibit 4-13 ANNUAL ECONOMIC BENEFIT OF ESTIMATED IMPROVEMENTS IN SURFACE WATER QUALITY

(1999 $, millions)

Regulatory Scenario Fishable Swimmable Total Benefits Waters Waters Improved to Improved to
Option 1-Scenario 1 $2.8 $2.1 $4.9 Option 1-Scenario 2/3 $3.2 $3.1 $6.3 Option 1-Scenario 4a $3.1 $2.4 $5.5 Option 1-Scenario 4b $3.8 $3.4 $7.2 Option 2-Scenario 1 $71.0 $16.7 $87.6 Option 2-Scenario 2/3* $102.4 $24.7 $127.1 Option 2-Scenario 4a* $84.0 $24.5 $108.5 Option 2-Scenario 4b $115.5 $29.5 $145.0 * Proposed scenarios.

4.7 REFERENCES Carso n, Richard T. and Robert Cameron Mitchell. 1993. "The Value of Clean Water: Th e Public's Willingness to Pay for Boatable, Fishable, and Swimmable Water Quality. " Water Resources Research , Vol. 29, No. 7. Ham, J. M. and T.M. DeSutter. 1999. "Seepage Losses and Nitrogen Export from Swine-Waste Lagoo ns: A Water Balance Study." Journal of Environmental Quality . 28:1090-1099

. Kellogg, Robert L., Charles Lander, David Moffitt, and Noel Gollehon. 2000. Manure Nutrient s Relative to the Capacity of Cropland and Pastureland to Assimilate Nutrients: Spatia l and Temporal Trends for the U.S. Forthcoming. U.S. Department of Agriculture , Nat ional Resources Conservation Service. Washington, DC

. Lander, C.H., D. Moffitt, and K. Alt. 1998. Nutrients Available from Livestock Manur e Relative to Crop Growth Requirements. U.S. Department of Agriculture. Natura l Resources Conservation Service. Washington, DC. February. NPPC (National Pork Producers Council). 1998. Pork facts 1998/1999. Des Moines, IA : Nati onal Pork Producers Council. http://www.nppc.org/PorkFacts/pfindex.htm l4-27

Smith, Richard A., Gregory E. Schwarz, and Richard B. Alexander. 1997. "Regiona l Interpretation of Water-Quality Monitoring Data." Water Resources Research , Vol. 33, no. 12. December. Sobecki, T.M., and M. Clipper. 1999. Identification of Acreage of U.S. Agricultural Land with a Significant Potential f

or Siting of Animal Waste Facilities and Associated Limitations from Po tential of Groundwater Contamination , Draft. U.S. Environmental Protectio n Agency, Office of Water. December. USDA/APHIS (Animal and Plant Health Inspection Service). 1995. Swine ‘95. Part III and Par t I: Reference of 1995 Swine Management Practices. October. USDA/NASS (U.S. Department of Agriculture, National Agricultural Stati stics Service). 1999a. 199 7 Census of Agriculture . Volume I, Geographic Area Series Part 51. Washington , DC. March. USDA/NASS (U.S. Department of Agriculture, National Agricultural Statistics Service). 1999b

. Cattle Final Estimates 1994-1998. January. USEPA (U.S. Environmental Protection Agency). 2000a. Technical Development Document fo r Propo sed Effluent Limitations Guidelines for Animal Feeding Operations . Office o f Water. USEPA (U.S. Environmental Protection Agency). 2000b. Estimation of National Surface Wate r Quality Benefits of Regulating Concentrated Animal Feeding Operations (CAFOs) Usin g the National Water Po llution Control Assessment Model (NWPCAM) . Office of Water. July.4A-1 Appendix 4-A NWPCAM CALCULATION OF THE ECONOMIC BENEFITS OF IMPROVED SURFACE WATER QUALITY

Definitions N = national benefits of estimated improvements in water quality S = total benefits of estimated improvements in water quality for residents of state "j" j B = benefits of in-state improvements in water quality for residents of state "j" (l, j) B = benefits of out-of-state improvements in water quality for residents of state "j" (n, j) M = total stream-miles in state "j" j M = total stream-miles outside state "j" n M = stream-miles in state "j" that achieve water quality improvement "x" (x, j) M = stream-miles outside state "j" that achieve water quality improvement "x" (x, n) H = total households in state "j" j WTP = average household willingness to pay for water quality improvement "x" x
Calculations N = 3 S j J
S = B + B j (l, j) (n, j)

B = 3 (M / M )(H )(WTP )(2/3) (l, j) (x, j) j j x X
B = 3 (M / M )(H )(WTP )(1/3) (n, j) (x, n) n j x XF or example, in 1998, the release of manure into the West Branch of Wisconsin' s 39 Pecatonica River resulted in a complete kill of smallmouth bass, catfish, forage fish, and all but the hardiest insects in a 13-mile reach. For example, in 1996, the gradual runoff of manure into Atkins Lake, a shallow lake i n 40 Arkansas, resulted in a heavy algae bloom that depleted the lake of oxygen, killing many fish. 5-1 REDUCED INCIDENCE OF FISH KILLS CHAPTER 5

___________________________________________________________________________
5.1 INTRODUCTION Episodic fish kills resulting from manure runoff , spills, and other discharges from AFOs remai n a serious problem in the United States. As described in Chapter 2, large releases o f nutrients, pathogens, and solids from AFOs can cause sudden, extensive kill events. In les s 39 dramatic cases, nutrients contained in runoff from AFOs can trigger increases in alga e growth—often called algae blooms—that reduce concentrations of dissolved oxygen in water an d can eventually cause fish to die. 40
In addition to killing and harming fish directly, pollution from AFOs can affect othe r aquatic organisms that in turn harm fish. In particular, the Eastern Shore of the United States ha s been plagu ed with problems related to Pfiesteria , a dinoflagellate algae that, under certai n circumstances , can transform into a toxin that attacks fish, breaking down their skin tissue and leaving lesions or large, gaping holes that often result in death . The transformation of Pfiesteria to its toxic form is believed to be the result of high levels of nutrients i n water. Fish kills related to Pfiesteria in North Carolina's Neuse R iver have been blamed on waste spills and runoff from the state's booming hog industry.EPA's database incorporates records on fish kills obtained from the Natural Resource s 4 1 Defense Council (NRDC) and the Izaak Walton League (IWL). For instance, in 1995 the Raleigh News & Observer reported a 19 91 manure spill incident 42 in the North Carolina town of Magnolia that neither the town nor the responsible farm reported to state water quality officials. 5-2 This chapter examines the damages attributable to AFO-related fish kills and estimate s the economi c benefits that revised CAFO standards would provide in reducing such incidents

. As explained below, the analysis employs state data on historical fish kil l events, combined with predict ed reductions in the frequency of such events under alternate regulatory scenarios, t o estimate the decrease that would occur in the number of fish killed annually in AFO-induce d incidents. It then employs data on average fish replacement costs to develop a conservativ e estimate of the economic benefits associated with the predicted reduction in fish kill incidents.

5.2 ANALYTIC APPROACH 5.2.1 Data Sources and Limitations Data on fish kill incidents are limited, with no consistent collection and reportin g requirements an d no national repository of fish kill data. States are not required to report fis h kills to EPA. As a result, EPA does not maintain a comprehensive database detailing th e frequency or severity of fish kill events. Despite the lack of EPA reporting requirements, many states do record information on fis h kills. For purposes of this analysis, EPA has compiled a data base of fish kill events in 19 states. This database incorporates a range of information on each incident. Exhibit 5-1 lists the 19 state s included in the database, the years for which data from each state were obtained, a nd the average number of fish kill events reported by each state annually. 41
As Exhibit 5-1 indicates, the data upon which this analy sis relies are not comprehensive. The fish kill database excludes 31 states, including several, such as Oklahoma, that host a relatively large number of AFOs. The period of time for which data were obtained also varies from state to state; the information collected from some states, such as Missouri, covers nearly two decades, while that collected from others, such as West Virginia, covers only a few years

. In addition, even in the stat es and years for which data were collected, it is likely that some fish kill events remain unreported, particularly if they occurred in remote areas. These data gap s 42 introduce considerable uncertainty into the analysis.5-3 Exhibit 5-1 FISH KILL EVENT DATA OBTAINED BY EPA

State Data Number of Recorded

Years for which Average Annual were Obtained Events Arkansas 1995-1999 8.6 Illinois 1987-1999 14.0 Indiana 1994-1999 27.2 Iowa 1981-1998 26.3 Kansas 1990-1999 15.7 Kentucky 1995-1998 15.5 Minnesota 1981-1991 23.9 Mississippi 1990-1998 18.6 Missouri 1980-1999 125.3 Montana 1994-1998 1.8 Nebraska 1991-1998 22.1 New Mexico 1995-1998 4.8 New York 1984-1996 18.0 North Carolina 1994-1998 41.2 Ohio 1995-1998 20.3 South Carolina 1995-1998 5.5 Texas 1990-1998 114.7 West Virginia 1995-1997 6.0 Wisconsin 1988-1998 6.4 Total 515.9

In a ddition to the data gaps cited above, the analysis is limited by inconsistencies in the information collected in state fish kill reports. Some states appear to ha ve established consistent guidelines for investigating a kill, which often include reporting the number of stream miles or lake acres affected, estimating the number of fish killed, describing the exact location of the kill, identifyi ng the source of the pollutants suspected to have caused the kill, and obtaining wate rThis may be due to a variety of circumstances. In some cases, the report may accurately 4 3 ind icate an event in which contamination occurred (such as a manure spill or municipal wast e release) but no fish were killed. In other cases, a record may indicate zero fish killed simply becaus e investigators were unable to develop a count (e.g., because the number killed was too great to count , or because the investigation was conducted too late to determine the number killed). 5-4 quality samples for testing. Other states appear to gather information on an ad hoc basis. I n addition, the data present a number of anomalies or other limitations. For example, 25 percent of the records included in EPA's database give no estimate of the number of fish killed or provid e only a qualitative description of the incident's magnitude. Another 13 percent of the record s indicate that the number of fish killed in the event was zero. In addition, most reports do not 43 indicate the type(s) of fish killed. Despite the apparent limitations of these data, they are useful for purposes of this analysis

. EPA 's database is the most comprehensive source of information on fish kill events currentl y available, and in most instances characteri zes the source of the pollutants that caused individual fish kill events. Thus, EPA can apply these data to characterize a baseline of kill event s potentially attributable to pollution from AFOs.

5.2.2 Predicted Change in Fish Kills Under Alternate CAFO Regulations To esti mate the potential benefits of alternate CAFO regulations in reducing fish kil l incidents, EPA’s analysis must first asses s the current — or baseline — number of AFO-related fish kills. It must then determine the impact of alternate regulatory scenarios in reducing these incidents. EPA's approach to this analysis is described below.

5.2.2.1 Baseline Scenario The EPA d atabase records fish kill events attributable to a wide range of sources an d cau ses, the classification of which varies from state to state. Exhibit 5-2 lists the sources an d causes that are potentially associated with AFOs, and indicates EPA 's assessment of the strength of the association; i.e., whether the Agency considers the link to AFOs to be definite or possible. Based on this assessment of sources and causes, EPA reviewed the data on each reported event, identi fying fish kills positively or possibly attributable to pollution from AFOs. Exhibit 5- 3 presents the results of this evaluation. As the exhibit indicates, EPA's da tabase lists 589 fish kill events that are positively or possibly attributable to pollution from AFOs. These incidents killed a reported total of approximately 4.2 million fish. Based on these data, EPA estimates that in th e states evaluated, incide nts positively attributable to pollution from AFOs kill an average of 351E PA estimates the average number of fish killed annually in the 19 states of record b y 44 dividing the total number of fish killed in each state by the number of ye ars for which data from the state are reported . EPA then sums the state averages to obtain the annual average for all 19 states. 5-5 thousand fish per year. In addition, incidents possibly attributable to pollution from AFOs kill, on aver age, another 40 thousand fish annually. In total, the database indicates that in the 1 9 states analyzed, pollution from AFOs may kill an average of 391 thousand fish each year. 44

Exhibit 5-2 SOURCES AND CAUSES OF FISH KILL EVENTS POTENTIALLY RELATED TO ANIMAL FEEDING OPERATIONS

Source AFOs Cause AFOs Relation to Relation to
animal feeding/waste Definite ammonia toxicity Definite operations agriculture Possible lagoon breaks Definite agriculture point source Possible manure Definite algae related Possible nutrients Definite algae blooms Possible dissolved oxygen Possible employee error Possible equipment failures Possible fertilizer Possible nonpoint source runoff Possible spills Possible weather Possible5-6 Exhibit 5-3 NUMBER OF FISH KILL EVENTS POTENTIALLY RELATED TO ANIMAL FEEDING OPERATIONS

Cause Operations re Source d n Source Total Number of Occurrences for Each Source

Animal cultur Feeding e Algaeand Waste Agricultu Point Relate UnknowAgriAmmonia Toxicity

- - 17 8 6 3 Ammonia Toxicity/

- Dissolved Oxygen

- 96 3 4 103 Dissolved Oxygen

- 26 1 33

- 60 Employee Error/Manure

- - - 5 3 2 Equipment Failure

- 1

- - - 1 Equipment Failure/Manure

- - - - 3 3 Equipment

- 1

- - - Failure/Fertilizer 1
Fertilizer

- 24

- - - 24 Lagoon Breaks

- - - - 5 5 Manure

- 343 74 158 1 110 Manure/Dissolved Oxygen

- - - - 2 2 Manure/Weather

- - - - 1 1 Algal Toxins/Algal

- 6

- 1

- Oxygen Deficiency 7 Nonpoint Source Runoff 5

- - - 6 1 Nutrient

- - - - 1 1 Spills

- 1

- - 4 3 Weather

- - 3

- - 3 Other / Unknown 2

- - - 3 1 Total: 191 239 15 34 110 589 Note: Numbers in bold indicate fish kill events considered to be definitely induced by AFOs.For purposes of this analysis, EPA considers all fish kill events identified as definitely or 45 possibly attributable to AFOs. Chapter 4 provides additional detail on the RF3 and RF3 Lite datasets. 46 5-7 5.2.2.2 Regulatory Scenarios Due to time and resource constraints, EPA has not conducted a detailed analysis of th e impa ct of alternate CAFO standards on the frequency or severity of fish kill events. It is likely , however, that the implementation of new regulations would have a number of beneficial effects. For exam ple, because more AFOs would be subject to regulation as CAFOs, the number of fis h kill incidents caused by lagoon breaks and similar catastrophic events would likely diminish. In addition, the improvements in manure management practices required under the new regulations would likely reduce the chronic discharge of nutrients to the nation's waters, and thus reduce the number of fish killed as a result of severe eutrophication.
In lieu of more detailed modeling, EPA has a ttempted to develop a reasonable estimate of the impact of alternate CAFO standards on fis h kills. The analysis begins with EPA's estimate of the number of fish killed annually by releases from AFOs. EPA multiplies this figure by th e 45 anticipated percentage reduction in nutrient loadings from the animal feeding operations modeled by NWPCAM (s ee Chapter 4). The resulting value, for each regulatory scenario, represents a n estimate of the reduction in the number of fish killed annually by releases from AFOs. Because t he relationship between nutrient loadings and fish kill events is complex, thi s approach provides only a rough approximation of the beneficial impacts of alternate regulations. To reflect the underlying uncertainty, the analysis employs two different scaling factors:

• the percentage reduction in phosphorus loadings; and

• the percentage reduction in nitrogen loadings.

Exhibit 5-4 summarizes the estimated percentage reduction in nitroge n and phosphorus loadings under each regulatory scenario. The values reported are those estimated by NWPCAM for th e full RF3 set of rivers and streams. The analy sis uses these values, rather than those reported for the RF3 Lite subset, in order to reflect changes in loadings to small as well as large rivers an d streams. 465-8 Exhibit 5-4 REGULATORY SCENARIO SCALING FACTORS
Regulatory Scenario Reduction Reduction Percent Nitrogen Percent Phosphorus Option 1/Scenario 1 18.10 45.53 Option 1/Scenario 2/3 23.02 59.79 Option 1/Scenario 4a 21.82 56.51 Option 1/Scenario 4b 25.66 63.00 Option 2/Scenario 1 34.55 55.22 Option 2/Scenario 2/3* 43.00 72.06 Option 2/Scenario 4a* 41.48 68.81 Option 2/Scenario 4b 47.24 77.40 * Proposed scenarios

Based on the methods described above, EPA estimates the anticipated reduction in fish kill s under each of the regulatory scenarios. Exhibit 5-5 presents the results. As the exhibit shows, EP A estimates that under the proposed scenarios, the reduction in fish killed annually would range fro m 162 thousand to 282 thousand.

Exhibit 5-5

ESTIMATED REDUCTION IN THE NUMBER OF FISH KILLED ANNUALLY DUE TO RELEASE OF POLLUTANTS FROM AFOs (thousands) Regulatory Scenario Nitrogen Reduction Phosphorus Reduction Scaling Factor Option 1/Scenario 1 71 178 Option 1/Scenario 2/3 90 234 Option 1/Scenario 4a 85 221 Option 1/Scenario 4b 100 247 Option 2/Scenario 1 135 216 Option 2/Scenario 2/3* 168 282 Option 2/Scenario 4a* 162 269 Option 2/Scenario 4b 185 303 *Proposed scenarios

5.2.3 Valuation of Predicted Reduction in Fish Kills The economic damages that stem from natural resource injuries like fish kills include the costs of restoring the resource to its prior state, any interim lost use values (e.g., the economic valu e of lost fishing days from the time the damage occurs until fish stocks are restored), and any interi mThe ana lysis employs fish replacement costs as a proxy measure for valuing anticipate d 47 reductions in fish kill incidents. The approach does not presume that all fish killed would necessaril y be restocked. To adjust replacement costs to 1999 dollars, EPA applies the Gross Domestic Produc t 48 deflator. To bound the potential uncertainty associated with fish replacement costs, the analysis als o

49 develops benefits estimates based on the averages of the minimum and maximum replacement cost s reported for each species. Appendix 5-A presents the results of this analysis. 5-9 lost n on-use values. Unfortunately, estimating these values for a large number of heterogeneous fish kill e vents nationwide is infeasible without a significant investment of analytic resources

. Determining full habitat restoration costs requires a case-by-case assessment of the nature of the injury and the restoration options available, while estimating interim lost non-use values requires the use o f stated preference techniques to explore people's willingness to pay to avoid temporary depl etions of fish stocks and associated damage to fish habitat. The economics literature doe s provide estimates of potential lost u se values— e.g., willingness to pay for another day of fishing or w illingness to pay for an additional fish caught—that could, theoretically, be applied to th e analysis using a benefits transfer approach. This assessment, however, would need to make genera l assumpti ons about a number of highly variable site-specific factors, such as the duration of th e reduction in fish stocks, the eff ect of this reduction on recreational fishing activity in the affected areas, and the availability and characteristics of alternative fishing areas. Thus, an evaluation of interim lost use values would be subject to considerable uncertainty. Because of the difficulties cited above, this analysis takes a simplified approach, estimatin g the economic benefits of reducing the frequency of fish kills based on one component of resource restoration costs: the replacement cost of the fish. Specifically, the analys is employs replacement cost estim ates presented in a report developed by the American Fisheries Society (AFS, 1990)

. These replacement values incorporate the cost of raising fish at a hatchery, transporting them, and placing them in the water. As such, they provide a conservative estimate of the ec onomic benefits of reducing the incidence of fish kills. 47
Th e American Fisheries Society report provides replacement cost estimates for a variet y of f ish species and size categories. Unfortunately, the available data on fish kills do not alway s indicate the species of fish af fected, and generally do not report mortality by size of fish. In light of thes e limitations, EPA applies a general fish replacement cost estimate, derived by selectin g species known to have been killed in incidents related to AFOs and averaging reported replacemen t costs for these species across all size classes. The resulting average replacement cost employe d in the analysis equals $1.31 pe r fish ($1999). To value the benefits of each regulatory scenario, 48 the analysi s simply multiplies this average replacement cost by the corresponding estimate d reduction in the number of fish killed each year. 495-10

5.3 RESULTS Exhibit 5-6 presents estimat es of the annual benefits attributable to the reduced incidence of fish kills un der each of the regulatory scenarios. As the exhibit indicates, these benefits range from $93 t

housand to $397 thousand, depending upon the regulatory option considered and th e scaling factor employed. Annual benefits under the proposed scenarios are estimated to range fro m $213 thousand to $369 thousand.

Exhibit 5-6 ESTIMATED ANNUAL BENEFITS ATTRIBUTED TO REDUCTION IN FISH KILLS

($1999, thousands) Regulatory Scenario Nitrogen Reduction Phosphorus Reduction Scaling Factor Option 1/Scenario 1 $93 $233 Option 1/Scenario 2/3 $118 $306 Option 1/Scenario 4a $112 $290 Option 1/Scenario 4b $132 $323 Option 2/Scenario 1 $177 $283 Option 2/Scenario 2/3* $220 $369 Option 2/Scenario 4a* $213 $353 Option 2/Scenario 4b $242 $397 *Proposed scenarios

5.4 LIMITATIONS AND CAVEATS EPA's analysis of the benefits of alternate CAFO regulations in reducing fish kills is subjec t to numerous data gaps and uncertainties. In the face of these uncertainties, the analysis employs a number of simplifying assumptions. The major limitations of the analysis are summarized below

.

• The s cope of the analysis is limited to 19 states. The data available fro m thes e states may not include all fish kill events, and the data on reporte d incide nts often fail to include estimates of the number of fish killed

. Therefore, EPA's baseline estimate is likely to understate the number of fis h kill events and the total number of fish killed nationwide each year i n incidents related to pollution from AFOs.5-11

• EPA has not undertaken a detailed analysis of the impact of alternat e regulatory s cenarios on the incidence of fish kills. In lieu of a detaile d analysis, EPA assumes that fish kills attributable to releases of pollutio n from AFO s will be reduced in proportion to estimated reductions i n loadings of nutrients from AFOs. The direction and magnitude of bia s associated with these assumptions is unknown.

• To value estimated reduction s in fish kill incidents, the analysis applies an estim ate of average fish replacement costs. Because this proxy measur e ig nores other aspects of the economic damages associated with fish kill s (i.e., habitat restoration costs, interim lost u se values, and interim lost nonuse values), i t likely understates the economic benefit of reducing fish kill incidents.

5.5 REFERENCES AFS. 199 3. American Fisheries Society Socioeconomics Section, Sourcebook for Investigation and Valuation of Fish Kills

. Grif fiths, Charles and Cynthia Morgan. 2000. "Benefits of Avoiding Fish Kills by Regulatin g Livestock Waste," National Center for Environmental Economics, U.S. Environmenta l Protection Agency. Warrick, Joby and Pat Smith. 2000. The News & Observer , "New studies show that lagoons are leaking: Groundwater, rivers affected by waste," Sunday, February 19, 1995, obtained from : http://www.nando.net/sproject/hogs/1water.html, June 28.5A-1 Appendix 5-A CALCULATION OF ANNUAL BENEFITS USING MINIMUM AND MAXIMUM FISH REPLACEMENT VALUES
Replacement values for a fish species can vary significantly de pending on the size class of the fish. This appendix presents the results of the benefits assessment using averages of th e minimum and maximum replacement values reported for each fish species. The average minimu m an d maximum replacement costs equal $0.28 and $2.37 ($1999), respectively. Exhibit 5A- 1 presents annual benefit estimates based upon the m inimum fish replacement cost; annual benefits for the proposed scenarios in this case range between $45 and $79 thousand. Exhibit 5A-2 present s an nual benefit estimates based on the maximum replacement cost; in this case, annual benefit s under the proposed scenarios range from $385 to $668 thousand

.
Exhibit 5A-1 ESTIMATED ANNUAL BENEFITS ATTRIBUTED TO REDUCTION IN FISH KILLS: MINIMUM REPLACEMENT COST

($1999, thousands) Regulatory Scenario Nitrogen Reduction Phosphorus Reduction Scaling Factor Option 1/Scenario 1 $20 $50 Option 1/Scenario 2/3 $25 $66 Option 1/Scenario 4a $24 $62 Option 1/Scenario 4b $28 $69 Option 2/Scenario 1 $38 $60 Option 2/Scenario 2/3* $47 $79 Option 2/Scenario 4a* $45 $75 Option 2/Scenario 4b $52 $85 *Proposed scenarios5A-2 Exhibit 5A-2 ESTIMATED ANNUAL BENEFITS ATTRIBUTED TO REDUCTION IN FISH KILLS: MAXIMUM REPLACEMENT COST

($1999, thousands) Regulatory Scenario Nitrogen Reduction Phosphorus Reduction Scaling Factor Option 1/Scenario 1 $168 $422 Option 1/Scenario 2/3 $213 $554 Option 1/Scenario 4a $202 $524 Option 1/Scenario 4b $238 $584 Option 2/Scenario 1 $320 $512 Option 2/Scenario 2/3* $399 $668 Option 2/Scenario 4a* $385 $638 Option 2/Scenario 4b $438 $718 *Proposed scenarios6-1

IMPROVED COMMERCIAL SHELLFISHING CHAPTER 6

_ ____________________________________________________________ _________________
6.1 INTRODUCTION The National Oceanic and Atmospheric Administration (NOAA) has identified pathogen contamination of U.S. coastal waters as a leading cause of government r estrictions on commercial shellfish harvesting. Among the sources of pollution that contribute to such contamination ar e animal feeding operatio ns (AFOs) and runoff from agricultural lands. This chapter estimates the impact of p ollution from AFOs on commercial access to shellfish growing waters, the resultin g impact on commercial shellfish harvests, and the potential increase in harvests that would result under alterna te approaches to regulating the discharge of pollutants from CAFOs. It then use s availableestimates of consumer demand for shellfish to calculate the economic benefits associate d with the predicted increase in commercial shellfish harvests under each regulatory scenario.

6.2 ANALYTIC APPROACH 6.2.1 Data on Shellfish Harvest Restrictions Attributed to AFOs EPA's analysis of the impact of pollution from AFOs on shellfish harvests is based o n inf ormation from The 1995 National Shellfish Register of Classified Growing Waters (NOAA , 1997) and related databases. NOAA produces the Register, which is published every five years, in cooperation with the nation's shellfish-producing states, federal agencies such as the U.S. Food and D rug Administration (FDA), and the Interstate Shellfish Sanitation Conference (ISSC). It s pur pose is to summarize the status of shellfish-growing waters under the National Shellfis h Sanitati on Program (NSSP), which ISSC administers. The NSSP establishes comprehensiv e guid elines to regulate the commercial harvesting, processing, and shipment of shellfish. Thes e guidelines include the measurement of fecal coliform concentrations as an indicator of pollution in shellfish-growing waters. Based in large part upon these measurements, shellfish-growing area s are designated as approved, conditionally approved, restricted, conditionally restrict ed, prohibited, or unclas sified, and subjected to appropriate harvest and processing standards. Exhibit 6- 1 describes these standards for each designation.6-2 Exhibit 6-1 NSSP STANDARDS FOR CLASSIFIED SHELLFISH GROWING WATERS Classifi Description Standard cation 1
Approv Growing waters from which shellfish may be MPN may not ed Waters harvested for direct marketing. exceed 14 per 100 ml, and not more than 10 percent of the samples may exceed an MPN of 43 per 100 ml for a 5-tube decimal dilution test. Conditi Growing waters meeting the approved onally Approved classification standards under predictable conditions. Waters These waters are open to harvest when water quality

standards are met. At all other times these waters are closed. Restrict Growing waters from which shellfish may be MPN may not ed Waters harvested only if they are relayed or depurated before exceed 88 per 100 ml, and

direct marketing. not more than 10 percent 2 of the samples may exceed an MPN of 260 per 100 ml for a 5-tube decimal dilution test. Conditi Growing waters that do not meet the criteria for onally Restricted restricted waters if subjected to intermittent Waters microbiological pollution, but may be harvested if

shellfish are subjected to a suitable purification process. Prohibit Growing waters from which shellfish may not be NA ed Waters harvested for marketing under any conditions. Unclassi Growing waters that are part of a state's shellfish NA fied Waters program but are inactive (i.e., there is no harvesting) and

unmonitored. Source: National Oceanic and Atmospheric Administration, The 1995 National Shellfish Register o f Cl assified Growing Waters , obtained from: http://seaserver.nos.noaa.gov/projects/95register/ , 11 June 2000. Notes: MPN = fecal coliform most probable number (median or geometric mean). 1 The process of relaying shellfish refers to the transfer of shellfish from restricted waters t o 2 approved wa

ters for natural biological cleansing using the ambient environment as a treatment system, usually for a minimum of 14 days before harvest. Depuration is the process of removin g impurities by placing the contaminated shellfish in clean water for a period of time.The Shellfish Register includes data for the following states: Alabama, California , 50 Connecticut, Delaware, Florida, Georgia, Louisiana, Massachusett s, Maryland, Maine, Mississippi, Nor th Carolina, New Hampshire, New Jersey, New York, Oregon, Rhode Island, South Carolina , Texas, Virginia, and Washington. 6-3 The 1995 Shellfish Register provides information on 21.4 million acres of estuarine and non

estuar ine commercial shellfish-growing waters as of January 1, 1995. A companion CD contain s a GIS-based d atabase of the location of all 4,320 shellfish growing areas in 21 coastal states, th e acreage of each growing area, and the species harvested. These species are classified into 1 3 50 categories of clams, four categories of oysters, six categories of mussels, and two categories o f scallops. I n most cases, each category represents a unique species (e.g., Blue Mussel ( Mytilu s edulis )), but in some instances a category may include two or more species (e.g., Other Mussel s ( Mytilus galloprovincialis and Mytilus edulis )). The types of species harvested vary geographi cally, with large differences between the East and West Coasts.
In addi tion to the data described above, the shellfish database notes for each growing are a any harvest limitations imposed and the known or possible source(s) of pollutants causing an y impairment

. The list of pollutant sources includes both “Animal Feedlots” and “Agricultur e Runoff.” Sources of impairment are further classified as actual or potential contributors. If a sourc e is listed as an actual contributor, its significance as a cause of impairment is rated as high, medium, or low. Exhibit 6-2 shows the acreag e of shellfish-growing waters that are potentially or known to be impai red by pollution from AFOs and/or agricultural runoff. As the exhibit indicates, AFO s and/ or agricultural runoff are known or potential contributors to the impairment of more than 1. 6 million acres of shellfish-growing waters.6-4 Exhibit 6-2 SHELLFISH HARVEST LIMITATIONS BY REGION

Region Acres Acres Runoff Approved Limited Agricultural

Harvest- AFOs and/or

Harvest-Limited Acres with Impacts from

North Atlantic (MA, ME, NH) 2,920,575 714,191 33,626 Middle Atlantic (CT, DE, MD, NJ, NY, RI, VA) 4,969,680 973,715 100,284 South Atlantic (FL, GA, NC, SC) 3,505,729 1,751,844 660,679 Gulf of Mexico (AL, LA, MS, TX) 3,238,431 3,067,730 718,828 Pacific (CA, OR, WA) 206,574 214,494 96,296 Total 14,840,989 6,721,975 1,609,713 Discrepancies between reported totals and sum of regional totals are due to rounding. Sour ce: U.S. National Oceanic and Atmospheric Administration, The 1995 National Shellfish Register o f Classified Growing Waters , U.S. Department of Commerce, Silver Spring, MD, August 1997.

6.2.2 Estimated Impact on Shellfish Harvests As a causal factor in the imposition of government restrictions or prohibitions on shellfish harvesting, pollution from AFOs likely serves to reduce shellfish landings below levels that would otherwise be realized. To evaluate the potential beneficial effects of new CAFO regulations, EPA's analysis begins by estimating the adverse impacts currently attributable to pollution from AFOs. Th e approach to this analysis involves the following steps.

• Step 1: characterize current, or baseline, annual shellfish landings.

• Step 2 : estimate the area of shellfish-growing waters from which curren t landings are harvested.

• Step 3 : calculate the average annual per-acre yield of shellfish fro m harvested waters.

• Step 4: e stimate the area of shellfish-growing waters that are currentl y unharvested as a result of pollution from AFOs.The calculation of the mean ignores years for which harvest data for a particular species 51 are unavail able. If landings in these years were actually zero, this approach will overstate average annual landings. 6-5 • Step 5: estimate the foregone harvest, i.e., the potential annual harvest o f shellf ish from waters that are currently unharvested as a result of pollutio n from AFOs.
Each of these steps is described in greater detail below.

6.2.2.1 Baseline Annual Shellfish Landings To ch aracterize the baseline quantity (Q ) of shellfish harvested in each coastal state, th e 0 analysis relies on data collected by NOAA’s National Marine Fisheries Service (NMFS), whic h repor ts commercial fishing harvests by state, year, and species (NMFS, 2000). NMFS maintain s complete commercial harvest data on various species of clams, mussels, oysters and scallops for eac h state. The data consist of total pounds harvested and total ex-vessel rev enues for harvested species. The data are pr ovided as state-wide totals only and do not disaggregate harvest quantities between shellfish growin g areas within each state. For the purpose of this analysis, EPA obtained shellfish harvest data by species and state for the five most recent years available: 1994 through 1998. The analysis employs the mean of the reported annual values for each species and state to characterize shellfish harvests under baseline conditions. 51

6.2.2.2 Estimated Acreage of Harvested Waters The available data do not indicate the distrib ution of shellfish landings from waters that the 1995 Shellfish Register identifies as approved, conditionally approved, restricted, or conditionally restricted. For purposes of this analysis, EPA assumes that baseline landings are harvested primaril y from approve d or conditionally approved waters. Thus, in a given state (j), the area of shellfis h growing waters assumed to be harvested is determined by the following calculation:

Acres Harvested = Acres Approved + Acres Conditionally Approved (j) (j) (j)In addition, NOAA staff who maintain the Register suggest that difficulty in pinpointing 52 the sou rce of pollution often results in classifying impacts from AFOs under the more genera l heading of "Agriculture Runoff." Personal communication with Jamison Higgins, NOAA, April 12 , 1999. 6-6 6.2.2.3 Average Annual Yield of Harvested Waters To calcu late the average annual yield (Y) of harvested waters for a given species (n) in a given state (j), the analysis simply divides the annual baseline harvest (Q ) for that species and state 0 by the acres assumed to be harvested:
Y = Q /Acres Harvested (n,j) 0(n,j) (j)
This calcula tion provides an estimate of the pounds of shellfish landed per year from harveste d waters.

6.2.2.4 Characterization of Waters that are

Unharvested due to Pollution from AFOs The next step in the analysis is to estimate the area of shellfish-growing waters that ar e curr ently unharvested due, at least in part, to pollution from AFOs. Consistent with the approac h ou tlined thus far, EPA assumes that waters classified in the 1995 Shellfish Register as restricted , conditionally restricted, or prohibited are essentially unharvested. Thus, in a given state (j ), the area of shellfish growing water s assumed to be unharvested is determined by the following calculation: Acres Unharvested = Acres Restricted + Acres Conditionally Restricted + Acres Prohibited (j) (j) (j) (j)
This calculation, however, includes all impa ired waters. To identify areas impaired, in whole or in part, by pollution from AFOs, EPA's analysis considers two cases. Under Case 1, EPA evaluates only those shellfish-growing waters for which AFOs are specifically identified as a contributin g source of impairment. Under Case 2, EPA expands the analysis to include shellfish-growing waters that the Register identifies as impaired, in whole or in part, by AFOs and/or agricultural runoff. Th e inclusion of Case 2 is justified by the classification of shellfish-growing wate rs on the basis of fecal coliform levels. To the extent that agricultural runoff causes elevated fec al coliform counts, animal manure, potentially from AFOs, is the likely contributing factor. 526-7

6.2.2.5 Estimated Impact of Pollution from

AFOs on Commercial Shellfish Landings To characterize the impact of pollution from AFOs on commercial shellfish landings, it i s first necessar

y to estimate the potential yield of impaired shellfish growing areas. For purposes of this analysis, EPA assumes that the average annual yield from harvested waters, as calculated above , is representative of the potential annual yield from impaired waters. Thus, the foregone harvest (Q ) F from an area of any size for a given species (n) in a given state (j) is calculated as follows: Q = Y x Acres Unharvested F(n,j) (n,j) (j)

It wo uld be inappropriate, however, to assume that pollution from AFOs accounts for th e entire foregone harvest. The Shellfish Register identifies AFOs and/or agricultural runoff as a sourc e of impairment for only a subset of impaired growing waters. Moreover, even in situations wher e AFOs and/or agricultural runoff contribute to impairment, they are not necessarily the sole source of i mpairment. Under these circumstances, it is difficult to characterize the marginal impact o f pollution from AFOs and/or agricultural runoff on annual shellfish harvests. To address this concern, EPA relies on the Shellfish Register's characterization of th e significance of pollution from AFOs and/or agricultural runoff as a source of impairme nt. As noted above, the Register indicates whether a source is an actual or potential contributor to impairment, an d when identified as an actual contributor notes the overall importance of the source (i.e., high , medium, or low). EPA uses this information to characterize the marginal impact of pollution from AFOs a nd/or agricultural runoff on shellfish harvests. It does so by subjectively assigning a weighting factor that varies with the contribution of AF Os and/or agricultural runoff to impairment of a giv en shellfish growing area; Exhibit 6-3 summarizes the weighting factors employed. EP A then applies thes e weighting factors to estimates of the foregone harvest (Q ) from each shellfish- F growing area to estimate the marginal impact o f pollution from AFOs and/or agricultural runoff on annual shellfish harvests. Mathematically, the harvest of a given species that EPA estimates as lost due to pollution from AFOs and/or agricultural runoff (Q ) in an impaired area is simply the produc t A of the foregone harvest of the species from the area (Q ) and the appropriate weighting factor(W): F Q = Q x W A F Summing Q across all impaired shellfish growing areas in a given state provides EPA's estimat e

A of the marginal impact of pollution from AFOs and/or agricultural runoff on annual commercia l harvests of each shellfish species.6-8 Exhibit 6-3 WEIGHTING FACTORS EMPLOYED TO CHARACTERIZE THE IMPACT OF AFOs AND AGRICULTURAL RUNOFF ON HARVESTS

FROM IMPAIRED SHELLFISH-GROWING WATERS Significance of Source Weighting Factor Not a contributor .00 Potential contributor .25 Actual contributor (low) .50 Actual contributor (medium) .75 Actual contributor (high) 1.0

6.2.3 Estimated Impact of Alternate Regulations on Commercial Shellfish Harvests The next step in EPA's analysis is to estimate the impact of alternate CAFO regulator y scenarios on commercial shellfish harvests. To do so, EPA employs information obtained from the surface water quality modeling effort described in Chapter 4. The modeling exercise does not exten d to estua ries or near-coastal waters, where most commercial shellfish-growing areas are located ; however, it does consider the impact of each regulatory scenario on fecal coliform counts associate d with pollution from AFOs. Since classification of shellfish-growing areas is based in part o n measurement of fecal coliform counts, the estimated impact of alternate regulatory scenar ios on this measure of water quality in upstream areas provides a reason able proxy for characterizing potential changes downstream. EPA's a pproach to estimating the beneficial impacts of new CAFO regulations o n commercial shellfish harvests assumes that the adverse impact of pollution from AFOs will b e reduced in proportion to modeled reductions in fecal coliform pollution attributable to AFOs. The details of this approach are described below.

• First, EPA assigns each coastal state included in th e shellfish analysis to one of the 18 hydroregions that EPA's water quality model evaluates. In all but one case, th e entire coastline of each state falls within a single hydroregion. The s ole exception, Virginia, was assigned to the hydroregion tha t encompasses the majority of its coastline.Region al estimates of changes in fecal coliform counts are only available for NPDE S 53 Sc enarios 1, 2/3, and 4b. For purposes of characterizing changes in fecal coliform counts unde r NPDES Scenario 4a, EPA employs the estimated percentage reduction nationwide. As discussed in Chapter 3, the c oncept of consumer surplus is based on the principle that 54 some consumers benefit at current pr ices because they are able to purchase a good at a price that is less than the amount they are willing to pay. Anecdotal evidence suggests that some shellfishing areas are leased by municipalities to 55 individual enterprises with sole rights to harvest the area. In these cases, the limits on competition could lead to positive producer surplus. The extent of this practice, however, is unclear. 6-9 • Next, for each hydroregion/state, EPA calculates the percentage reduction in fecal coliform counts predicted under each regulatory scenario. 53

• Thi rd, EPA multiplies its estimates of the percentage reduction in feca l coliform counts attributable to AFOs by its previously developed estimates of the impact of pollution from AFOs and/or agricultural runoff on shellfish harve sts (Q ). This calculation was performed separately for each specie s

A an d state. The result, Q , represents the incremental increase in harves t R associated with each regulatory alternative.
Adding Q to baseline harvests (Q ) yields an estimate of annual shellfish harvests followin g

R 0 implementation of revised CAFO regulations (Q ). This calculation is per formed for each state and 1 species. Thus: Q = Q +Q 1(n,j) 0(n,j) R(n,j)
6.2.4 Valuation of Predicted Change in Shellfish Harvests The appropr iate measure of the economic benefits of an increase in commercial shellfis h harvests is the welfare gain (i.e., the change in producer and consumer surplus) associated with the incr eased harvest. For purposes of this analysis, EPA focuses solely on changes in consume r surplus. This focus is necessary because the information required to evaluate any changes i n

54 producer surplus that might result from an increase in shellfish harvests (i.e., a long-run supply curv e for each species harvest ed) is difficult to obtain. In addition, the shellfish harvesting industry is to a signific ant extent characterized by regulated harvest levels and unregulated harvester effort (i.e., open access fisheries). Generally accepted natural resource economics theory suggests that, in ope n 55 acc ess fisheries, overcapitalization leads to zero producer surplus. Thus, although shellfis h harvesting is not entirely open access, any producer surplus in the in dustry is likely to be small, and any changes in producer surplus brought about by new CAFO regulations is likely to be minor.6-10 Price

Quantity Exhibit 6-4 CONSUMER DEMAND AND CONSUMER SURPLUS To calculate the change in consumer surplus associated with an increase in commercia l shellfis h harvests, the analysis makes use of information on consumer demand. Exhibit 6- 4 illustrates a simple demand curve. The demand curve is the downward sloping solid line l abeled D, and the initial q uantity sold is the dashed, vertical line at Q . The intersection of these two line s 0 gives the price at which quantity Q is sold. This price is marked as P and represented by the dashe d 0 0 horizontal line. The consumer surplus for quantity Q is the area below the demand curve and abov e 0 the horizontal line at P . That is, the consumer surplus for Q is the area la beled “C” in Exhibit 6-4. 0 0

The measurement of the benefits of revised CAFO regulation s relies on the assumption that a dec rease in the contamination of shellfish-growing waters would increase commercial access t o shellfish b eds, and thus increase the quantity of shellfish supplied to consumers (i.e., an increas e from Q to Q ). This in turn would result in a lower market price for shellfish (i.e., P ). The benefit 0 1 1 to consumers can be determined based on the old and new prices and quantities. Before the ch ange, the area labeled “C” in Exhibit 6-4 measures consumer surplus. After the cha nge, consumer surplus is measured by the area of A+B+C. Thus, the difference in consumer surplus between thes e scenarios (i.e., Area A + Area B) is the additional consumer surplus attributable to the proposed rul e and the appropriate economic measure of benefits to consumers.The price elasticity of demand represents the percentage change in demand for a goo d 56 brou ght about by a one percent change in its price; thus, a price elasticity of -2 implies that a on e percent increase in price will result in a two percent decrease in demand. EPA adjusts reported revenues to 1999 dollars using the Consumer Price Index. Fo r 57 purposes of cal culating P , EPA considers only those years for which harvest and revenue data are 0 available. 6-11 6.2.4.1 Characterization of Consumer Demand for Shellfish Analysis of th e changes in consumer surplus that might result from an increase in shellfish harvests requires an understanding of the effect of an increased harvest on mar ket prices. To gather the necessary information, EPA reviewed the economics literature. This review identified a numbe r of relevant studies: Lipton and Strand (1992), which estimates a demand equation for surf clams an d ocean quahogs on the East Coast; Wessells et al. (1995), which estimates a demand equation for U.S

. harvested mussels in Montreal; Cheng and Capps, Jr. (1988), which estimates demand equations fo r oysters and total shellfish in the U.S.; and Capps, Jr. and Lambregts (1991), which estimates deman d equation s for scallops and oysters in Houston, Texas. Exhibit 6-5 lists the demand elasticitie s obtained from each of these studies. These demand elasticities provide the means to determine th e 56 consumer benefits associated with changes in shellfish harvests.
Exhibit 6-5 SHELLFISH DEMAND ELASTICITIES Citation Species Elasticity Cheng and Capps oysters -1.132 Cheng and Capps total shellfish -0.885 Capps and Lambregts oysters not significant Capps and Lambregts scallops -1.84 Wessells et al. mussels -1.98 Lipton and Strand surf clams -2 Lipton and Strand ocean quahogs -0.87

6.2.4.2 Determining the Change in Consumer

Surplus Associated with Increased Harvests EPA's analysis of the benefits of an increase in shellfish harvests begins by estimating price s and quantities (i.e., P and Q ) under baseline conditions, as well as the quantity of shellfish EP A 0 0 estimat es would be harvested following the implementation of new CAFO regulations (Q )

. 1 Consistent

with the analysis of shellfish harvests described above, Q for each state and species is 0 based on NMFS data, and specified as the mean annual harvest for the years 1994 throug h 1998. P 0 is calculated by dividing the total reported revenues from 1994 through 1998 for each species and state, adjusted to 1999 dollars, by the total quantity harvested. Q is determined as described above , 57 1The analysis employs the Wessells et al. demand elastic ity for mussels and the Capps and 58 Lambregts demand elasticity for scallops for all states in which these species are harvested. When disaggregated data on surf clam or quahog harv ests are available, the analysis relies on the demand elasticities for these species developed by Lipton and Strand; in all other instances, demand for clam s is analyzed using the total shellfish price elasticity e stimated by Cheng and Capps. For oysters, the analys is relies upon the demand elasticity estimated by Cheng and Capps; this value was selecte d bec ause it was based on evaluation of a broader market than that considered by Capps an d Lambregts. Mathematically, the price elasticity of demand ( 0 ) is calculated as: 59 0 = M Q/ M P where: M Q = (Q - Q )/Q

1 0 0 M P = (P - P )/P

1 0 0 therefore: M P = M Q/ 0 P = (Q - Q )(P )/[( 0

)(Q )] + P 1 1 0 0 0 0
6-12 adding to Q the increase in shellfish harvests estimated to occur under each regulatory scenario (Q )

.

0 R EPA determined the value of these factors for each broad category of shellfish for which NMFS dat a are available: scallops, oysters, mussels, and clams. When the data allow, EPA developed separate values for quahogs, surf clams, and other clams. This approach enables the analysis to tak e advan tage, whenever possible, of the demand equations identified for the quahog and surf cla m subcategories. 58
On ce P , Q , and Q are estimated, the appropriate price elasticities of demand are applie d

0 0 1 to determine the new price (P ) associated with an increase in shellfish harvests. For purposes of thi s 1 an alysis, the percentage change in price is determined by dividing the percentage increase in th e quantity of shellfish supplied in each case by the appropriate price elasticity. This percentage chang e is then applied to the initial price (P ) to calculate the new price (P ) for each species harvested. 0 1 59The calculation of increased consumer surplus is based on a simple geometri c 60 approximation of the change in a reas under the demand curve, rather than formal integration using calculus. As a result, the estimated increase in consumer surplus may be slightly overstated. 6-13 EPA employs the estimated values for P , P , Q and Q to measure the increase in consume r 0 1 0 1 surplus associated with the projected increase in shellfish harvested and resulting reduction in marke t price under each regulatory scenario. This calculation is conducted for every state and specie s category. T he estimated annual benefit under each regulatory scenario is simply the sum of th e estimated increase in consumer surplus across states and species. 60

6.3 RESULTS Exhibit 6-6 summarizes the estimated economic benefits associated with increased shellfish harvests under each regulatory scenario evaluated. The exhibit presents two cases: Case 1, which considers beneficial impacts on shellfish growing waters that the Shellfish Register specificall y identifies as impaired by pollution from AFOs; and Case 2, which expands the analysis to consider beneficial impacts on shellfish growing waters identified as impaired by pollution from AFOs and/o r agricultura l runoff. As the exhibit indicates, EPA's estimates of annual benefits under Case 2 ar e more than an order of magnitude greater than under Case 1; this range reflects the significan t inc rease in the number and area of shellfish growing waters considered to be impaired by AFO s when runoff from agricultural land, as opposed to pollution specifically attributed to AFOs, i s included in the analysis. For the proposed scenarios, the estimate of annual benefits ranges fro m approximate ly

$195 thousand under Case 1 to $2.7 million under Case 2. Within each case, th e range of annual benefits across regulatory scenarios is relatively small: from $146 thousand to $24 5 thousand under Case 1, and from $1.8 million to $3.0 million under Case 2. In both cases, Option 1/Scenario 1 provides the lowest benefits, while Option 2/Scenario 4b provides the highest.

Exhibit 6-6 ESTIMATED ANNUAL BENEFITS OF INCREASED COMMERCIAL SHELLFISH HARVESTS (1999 $, thousands) Regulatory Scenario Case 1: AFOs Agricultural Runoff Case 2: AFOs and Option 1/Scenario 1 $146 $1,816 Option 1/Scenario 2/3 $198 $2,357 Option 1/Scenario 4a $178 $2,204 Option 1/Scenario 4b $221 $2,564 Option 2/Scenario 1 $165 $2,141 Option 2/Scenario 2/3* $219 $2,717 Option 2/Scenario 4a* $195 $2,417 Option 2/Scenario 4b $245 $2,960 * Proposed scenarios6-14

6.4 LIMITATIONS AND CAVEATS The a nalysis set forth above is subject to a number of uncertainties and relies upon several simplifying assumptions. These factors may lead to a potential under- or over-estimation of th e benefit s of decreasing AFO-related contamination of commercial shellfish growing waters. Th e most significant of these limitations are described below.

• The ana lysis assumes that a reduction in pollution from AFOs will result in an increase in commercial shellfish harvests. While this ass umption appears reasonable in light of the extent to which AFOs contribute to curren t restrictions or prohibitions on shellfish harvesting, the act ual impact of these restrictions or prohibitions on annual shellfish landings is unknown.

• To estimate the potential impact of pollution on annual shellfish landings, th e analysis calculates an average annual yield (pounds per acre) for shellfis h growing waters. The calculation of this f igure assumes that current harvests are obtained from waters classified as approved or conditionally approved

. To the extent that this approach over- or understates the increase in annual yields that might be realized from waters currently subject to harves t re strictions or prohibitions, the analysis may either over- or understate th e impact of pollution on annual shellfish landings.

• The actual contribution of AFOs to the impairment of shellfish growin g waters is unclear. In light of ambiguities in the data and uncertaintie s associate d with the impact of pollution from other sources, the analysi s considers two cases and employs subjectively developed weighting factor s to characterize the impact of pollution from AFOs on shellfish harvests. Th e degree o f judgment required in the analysis and the broad range of result s across the cases analyzed suggests considerable uncertainty concerning th e impact of pollution from AFOs.

• Similar ly, in characterizing the impact of alternate regulatory scenarios, the an alysis assumes that the adverse impact of pollution from AFOs (i.e., th e foreg one harvest) will be reduced in proportion to modeled reductions i n fecal c oliform pollution. While this approach may provide a reasonabl e approximation of the relative impacts of alternate CAFO regulations, it is les s reli able than detailed modeling of pathogen concentrations in shellfish

growing areas. The nature and magnitude of any bias i ntroduced by reliance on this approach is unclear.6-15

• The analysis relies on estimates of the price elasticity of demand for shellfis h that are not n ecessarily representative of current conditions or of conditions nationwide. The nature and magnitude of any bias introduced by reliance on these estimates, however, is unclear.

6.5 REFERENCES Capps , Oral Jr. and Johannes Adrianus Lambregts. 1991. "Assessing Effects of Prices an d Advertisi ng on Purchases of Finfish and Shellfish in a Local Market in Texas," Souther n Journal of Agricultural Economics , Vol. 23, July, pp. 181-194. Cheng, Hsiang-tai and Oral Capps, Jr. 1998. "Demand Analysis of Fresh and Frozen Finfish and Shel lfish in the United States," American Journal of Agricultural Economics , Vol. 70 , August, pp. 533-542. Griffiths, Charles and Sabrina Lovell. 2000. "Benefits of Proposed CAFO Rules to Shellfish Beds, " Office of Economy and Environment, U.S. Environmental Protection Agency, July 28. Lipton, D.W. and I. Strand. 1992. "Effect of Stock Size and Regulations on Fishing Industry Cost and Structure: The Surf Clam Industry," American Journal of Agricultural Economics , V ol. 64, February, pp. 197-208. U.S. National Oceanic and Atmospheric Administration. 1997. The 1995 National Shellfish Registe r of C lassified Growing Waters , Office of Ocean Resources Conservation and Assessment , Silver Spring, MD. Available from: http://seaserver.nos.noaa.gov/projects/95register/. U.S. National Oceanic and Atmospheric Administration, Fisheries Statistics and Economic s Di vision, "Commercial Fisheries," U.S. Department of Commerce, obtained fro m http://www.st.nmfs.gov/st1/commercial/index.html. We ssells, Cathy R., Christopher J. Miller and Priscilla M. Brooks. 1995. "Toxic Alga e Contaminati on and Demand for Shellfish: A Case Study of Demand for Mussels i n Montreal," Marine Resource Economics , Vol. 10, pp. 143-159.No other health impacts are consistently attributed to elevated nitrate concentrations i n 61 drinking water. As discussed in Chapter 2, however, other health effects are suspected. 7-1 REDUCED CONTAMINATION OF PRIVATE WELLS CHAPTER 7

______________________________________________________________________________
7.1 INTRODUCTION CAF Os can contaminate aquifers and thus impose health risks and welfare losses on those who rely on groundwater for drinking water or other uses. Of particular concern are nitrogen an d other animal waste-related contaminants (which come from manure and liquid wastes) that leac h through s oils and ultimately reach groundwater. Nitrogen loadings convert to elevated nitrat e con centrations at household and community system wells, and elevated nitrate levels in turn pos e a risk to human health. The federal health-based National P rimary Drinking Water Standard for nitrate is 10 mg/L. This Maximum Contaminant Level (MCL) applies to all Community Water Supply systems, but no t to households that rely on private wells. As a result, households served by private wells are at risk to e xposure to nitrate concentrations above 10 mg/L, which EPA considers unsafe for sensitiv e subpopulations (e.g., infants). Nitrate above concentrations of 10 mg/L can caus e methemo globinemia

(“blue baby syndrome”) in bottle-fed infants (National Research Council , 1997), which causes a blue-gray skin color, irritableness or lethargy, and potentially long-ter m developmental or neurological effects. Generally, once nitrate i ntake levels are reduced, symptoms abate. If the condition is untreated, however, methemoglobinemia can be fatal. 61
The most recent U.S. Census data show that approximately 13.5 mill ion households located in counties with AFOs are served by dom estic wells. A number of sources provide information on the percenta ge of such wells with nitrate concentrations in excess of 10 mg/L. As indicated i n Exhibit 7-1, the values reported vary widely, depending on the location studied, local hydrology, an d other factors. According to the nationwide USGS Retrospective Database, however, th e concentration of nitrate in 9.5 percent of domestic wells in the U.S. exceeds the 10 mg/L threshold. Thus, EPA estimates that approximately 1.3 million households in counties with AFOs are served by domestic wells with nitrate concentrations above 10 mg/L.7-2 Exhibit 7-1 PERCENTAGE OF WELLS EXCEEDING THE MCL FOR NITRATE Study Location Well 10 mg/L Type of Percent Exceeding CDC, 1998 Illinois, Iowa, Kansas, Minnesota, Domestic 13.4%

Missouri, Nebraska, North Dakota, South Dakota, Wisconsin Agriculture Ontario Domestic 13% Canada, 1991 (as farm cited by Giraldez and Fox, 1995) Kross et al., 1993 Iowa Rural 18% Retrospective National Domestic 9.5% Database (USGS) Richards et al., Indiana, Kentucky, Ohio, West Rural 3.4% 1996 Virginia Spalding and Iowa, Kansas, Nebraska, North Rural 20%, 20%, 20%, Exner, 1993 Carolina, Ohio, Texas 3.2%, 2.7%, 8.2%, respectively Swistock et al., 1993 Pennsylvania Private 9% U.S. EPA, 1990 National Rural 2.4% domestic USGS, 1985 Upper Conestoga River Basin Rural 40+% USGS, 1998 Nemaha Natural Resources District, Nebraska Rural 10% Vitosh, 1985 (cited in Southern Michigan Rural 34% Walker and Hoehn, 1990)

EPA's proposed revisions to the NPDES regulation and eff luent guidelines would affect the numbe r and type of facilities subject to regulation as CAFOs, and would also introduce ne w requirem ents governing the land application of manure. As a result, EPA anticipates that it s regulatory proposal will reduce nitrate levels in household wells. In light of clear empirical evidenc e from the economics literature that households are willing to pay to reduce nitrate concentrations in their w ater supplies -- especially to reduce concentrations below the MCL — the anticipate d improvement

in the quality of water drawn from private domestic wells represents a clear economi c ben efit. This chapter estimates these benefits for each of the eight regulatory scenarios evaluated.Cita tions provided here and in Section 7.2.1.2 are suggestive of the literature on thes e 62 issues. A more comprehensive review of the literature is provided in Attachment B. 7-3 7.2 ANALYTIC APPROACH Exhibit 7-2 provides an overview of EPA's approach to estimating the benefits of well nitrat e reductions. A s the exhibit indicates, the analysis begins by developing a statistical model of th e relationship between nitrate concentrations in private domestic wells and a number of variable s found to affect nitrate levels, including nitrogen loadings from AF Os. It then applies this model, in co mbination with the projected change in nitrogen loadings from CAFOs under each regulator y scenario, to cha

racterize the distribution of expected changes in well nitrate concentrations. Next, the analysis applies this distribution to the number of households served by private domestic wells to calculate (1) the increase in the number of households served by wells with nitrate concen trations that are below the MCL and (2) the marginal change in nitrate concentrations for household s currently served by wells with nitrate concentrations below the MCL. Finally, the analysis employs estimates of households’ values for reducing well nitrate concentrations to develop a profile of the economic benef

its of anticipated improvements in well water quality. Additional detail on EPA's analytic approach is provided below.

7.2.1 Relationship Between Well Nitrate Concentrations and Nitrogen Loadings EPA's approach begins with the use of regression analysis to develop a model characterizin g the empirical relationship between well nitrate concentrations and a number of variables that may aff ect nitrate levels, including nitrogen loadings from AFOs. The variables included in the model are based on a review of hydrogeological studies that have observed statistical relationships betwee n groundwater nitrate concentrations and various other hydrogeological and land use factors. Th e follo wing discussion describes the variables included in EPA's model and the sources of data fo r each vari able. It also notes potentially significant variables that the model does not include

. Appendix 7-A and Appendix 7-B provide additional detail on the model's development.

7.2.1.1 Included Variables and Data Sources
Althou gh the groundwater monitoring and modeling studies that EPA reviewed covere d different geographic areas and focused on varying nitrate sources (e.g., septic systems, agricultural fertilizers, animal feedlots), they often found similar variables to be significant. In particular , nitrogen application or loadings rates, whether from animal wastes, private septic systems, o r agricultural fertilizers, were the most consistent and significant factor affecting well nitrate level s (e.g., Burrow, 1998; CDC, 1998). EPA's model includes variables characterizing nitrogen loading s 62 from each of these sources:

### Exhibit 7-2 OVERVIEW OF ANALYTIC APPROACH

NPLA Retrospective Database U.S. Census Ag Census

NPLA scenarios

U.S. Census

Benefits Transfer Baseline model: Statistical model estimation Nitrates = ∝ + β o χ o +
... + β n χ n + ,

Calculation of changes in well nitrates under options/scenarios

• Change in number of households above 10 mg/L MCL

• Change in nitrates 1 < N < 10 mg/L

Annual benefit estimates for CAFO regulatory options DATA SOURCES ANALYSIS

7-47-5

• AFOs — S tudies that addressed the effect of animal manure production o n groundwater

nitrate concentrations found a positive correlation between thes e variable s (e.g., Ritter and Chirnside, 1990; Division of Water Quality , Groundwater Section, 1998). EPA's model therefore includes a variable that character izes nitrogen loadings from AFOs. EPA obtained data on thes e loadings, aggregated at the county level, from the National Pollutant s Loadings Analysis (Tetra Tech, 2000).

• Septic Systems — Several studi es found that the proximity of septic systems to wells is a small, but significant, contributing factor to elevated nitrat e concentra tions (e.g., Carleton, 1996; Richards et al., 1996). As a prox y measure for loadings from septic systems, EPA's model includes a variable characterizing the use of priva te septic systems in each county. Information on septic system use was drawn from the 1990 U.S. Census.

• Other Sources — Several studies found that the type of crop cultivate d in the vicinit y of wells significantly influences well nitrate levels, reflectin g vari ation in the crops’ nutrient and water needs and suggesting tha t agricultural fertilizers are a significant source of nitrogen to groundwate r (e.g., Swistock et al., 1993; Lichtenberg and Shapiro, 1997). EPA obtained data o n nitrogen loadings associated with agricultural fertilizers and othe r sources (e.g., atmospheric deposition) from the USGS Retrospectiv e Database (1996).

In addition to variables characterizing nitrogen loadings, EPA's model includes the followin g varia bles describing well, soil, and land use characteristics found to significantly influence wel l nitrate concentrations:

• Well Depth -- Several studies found well depth to be a significant variable , inverse ly correlated with well nitrate concentrations, regardless of nitrat e source (e.g., Detroy, 1988; Ham et al., 1998).

• Soil Group: A number of studies identified at least one hydrogeologica l characteristic, such as aquifer composition and soil type, as a significan t factor affecting well nitrate concentrations (e.g., Lichtenberg and Shapiro , 1997; Lindsey, 1997).

• Land

Use: Agricultural land use in the vicinity of wells was found to b e as sociated with higher groundwater nitrate in several studies (e.g., Muelle r et al., 1995; Carleton, 1996).7-6

For purposes of model development, EPA obtained data on these variables from the USG S Retrospective Database.

7.2.1.2 Omitted Variables Because o f incomplete or unreliable national data, EPA's model does not include all of the poten tially

significant variables the literature identifies. For example, several studies cite wel l construct ion and age as significant variables with respect to well nitrate concentrations (e.g. , Spa lding and Exner, 1993; Swistock et al., 1993). In general, older wells are more vulnerable t o nitrate contamination because their casings are more likely to be cracked, allowing surfac e contaminants to enter the well. Different construction materials and methods also affect how easily nitrate or other pollutants can reach groundwater via dire ct contamination at the wellhead. Data on thi s variable, however, are often unreliable because they are generally obtained by surveying wel l own ers and relying on their subjective assessment of when and how a well was constructed; n o reliable, nationally comprehensive data on well construction are available. Several studies also found the distance from a pollutant source to the well to be signific antly correlated with well nitrate concentrations (e.g., Swistock et al., 1993; Division of Water Quality, Groundwate r

Section, 1998). Although spatial data for well locations are available, data on th e location of animal feedlots, cropland, and septic systems are not; therefore, the model excludes this variable.

7.2.2 Modeling of Well Nitrate Concentrations Under Alternate Regulatory Scenarios To estimate the impact of selected variables on well nitrate concentrations, EPA compiled a database of 2,928 records. Each record provides information characterizing a different well , including the observed well nitrate concentration; well depth, soil, and land use information; dat a on baseline nitrogen loadings from AFOs; and data characterizing nitrogen loadings from septi c systems, agricultural fertilizer, and other sources. EPA develope d its regression model on the basis of this database. Af ter estimating the regression model using baseline loading information, EPA estimate d expected va lues for well nitrate concentrations, both for the baseline and for each of the eigh t alternative regulatory scenarios. The cal culation of expected values under each scenario employed data on AFO nitrogen loadings obtained from the National Pollutants Loadings Analysis (Tetra Tech , 2000); these loadings vary across the regulatory scenarios, reflecting different manure applicationFor additional information on the development of pollutant loadings estimates unde r 63 alternate regulatory scenarios, see Chapter 4. Test ing of EPA's model indicates that it underestimates well nitrate concentrations (se e 64 At tachment

B). As a result, comparing predicted values under alternate regulatory scenarios t o observed baseline values would bias the analysis. To avoid this bias, EPA compares the well nitrat e concentrations the model predicts under each regulatory scenario to the values it predicts unde r baseline conditions. The benefits assessment is based on the resulting projected percentage cha nges in expected well nitrate concentrations.

7-7 rates , manure management practices, and other factors. To examine the impact of alternat e 63 regulator y

scenarios on well nitrate concentrations, the AFO loadings variable is the onl y independent variable that changes value; the values for all other variables are held constant. Exhibi t 7-3 summarizes the expected percentage changes in well nitrate concentrations under each scenario. 64
Exhibit 7-3 PERCENT REDUCTION IN PROJECTED NITRATE CONCENTRATIONS Regulatory Scenario Mean Percent Reduction Median Percent Reduction Projected Nitrate Concentration (mg/L) Option 1 — Scenario 1 3.0 0.8 Option 1 — Scenario 2/3 3.2 0.8 Option 1 — Scenario 4a 3.7 0.8 Option 1 — Scenario 4b 3.7 0.8 Option 2 — Scenario 1 3.5 0.8 Option 2 — Scenario 2/3* 3.7 0.8 Option 2 — Scenario 4a* 4.3 0.9 Option 2 — Scenario 4b 4.3 0.9 *Proposed scenarios

7.2.3 Discrete Changes from above the MCL to below the MCL As note d above, the most recent U.S. Census data show that approximately 13.5 millio n households located in counties with AFOs are served by domestic wells. The USGS Retrospective Database indicates that the concentration of nitrate in 9.47 percent of U.S. domestic wells exceeds 10 m g/L. Thus, under the baseline scenario, EPA estimates that approximately 1.3 millio n househ olds in counties with AFOs are served by domestic wells with nitrate concentrations above 10 mg/L.EPA's analysis also ignores marginal reductions in nitrate concentrations for wells tha t 65 would remain above the MCL. The Agency's review of the economics literature failed to identify studies that would provide an adequate basis for valuing such changes. 7-8 To estimate the impact of alternative CAFO standards on the number of wells that woul d exceed the nitrate MCL, EPA applied the mean percentage reduction in nitrate concentration s predicted under each regulatory scenario to the nitrate concentration values that the USG S Retrospective Database reports. Based on the resulting values, EPA calculated the percentag e reduction in the number of wells with nitrate concentrations exceeding 10 mg/L. As shown i n Exhibit 7-4, it then applied these values to EPA's baseline estimate of the number of households in counties with AFOs that are served by domestic wells with nitrate concentrations above 10 mg/L. Based on this analysis, EPA estimates that the regulatory scenarios evaluated would bring between 152,000 and 166,000 households under the 10 mg/L nitrate threshold.

Exhibit 7-4 EXPECTED REDUCTIONS IN NUMBER OF HOUSEHOLDS WITH WELL

NITRATE CONCENTRATIONS ABOVE 10 mg/L

Regulatory Scenario Option/Scenario above the MCL Percentage of Wells above MCL at Baseline Expected Reduction in Number of to Achieve MCL under Households Option 1 — Scenario 1 11.9% 152,204 Option 1 — Scenario 2/3 11.9% 152,204 Option 1 — Scenario 4a 12.6% 161,384 Option 1 — Scenario 4b 12.6% 161,384 Option 2 — Scenario 1 12.6% 161,384 Option 2 — Scenario 2/3* 12.6% 161,384 Option 2 — Scenario 4a* 13.0% 165,974 Option 2 — Scenario 4b 13.0% 165,974 * Proposed scenarios

7.2.4 Incremental Changes below the MCL Ho useholds currently served by wells with nitrate concentrations below the 10 mg/L leve l may also benefit from margi nal reductions in nitrate concentrations. For purposes of this analysis, EPA assumes tha t such incremental benefits would be realized only for wells with baseline nitrate concentrat ions between 1 and 10 mg/L; presumably, an individual would not benefit if nitrat e concentrations were reduced to below background levels, which for purposes of this analysis ar e assumed to be 1 mg/L. Exhibit 7-5 shows, for each regulatory scenario, EPA's estimate of th e 65The information reported in Exhibit 7-5 pertains only to wells with baseline nitrat e 66 concentrations below the MCL. Information for wells with baseline nitrate concentrations above th e MCL is not included, since the benefits associated with reducing nitrate concentrations in these well s to below the MCL are potentially captured in valuing the achievement of safe nitrate concentrations

. 7-9 mean and m edian reduction in nitrate concentrations for wells with baseline values between 1 and 10 mg/L. The exhibit also indicates for these wells the aggregate expected reduction in nitrate levels , expressed in mg/L. EPA estimates that approximately 600,000 households would benefit fro m 66 these marginal reductions.
Exhibit 7-5 MEAN AND MEDIAN REDUCTIONS IN NITRATE CONCENTRATIONS FOR WELLS WITH

CONCENTRATIONS BETWEEN 1 AND 10 mg/L AT BASELINE
Regulatory Scenario (mg/L) (mg/L) (mg/L) Mean Nitrate Median Nitrate Total Expected National Reduction Reduction Nitrate Reduction Option 1 — Scenario 1 0.16 0.12 961,741 Option 1 — Scenario 2/3 0.16 0.12 1,007,611 Option 1 — Scenario 4a 0.19 0.15 1,186,423 Option 1 — Scenario 4b 0.19 0.15 1,186,423 Option 2 — Scenario 1 0.18 0.14 1,103,166 Option 2 — Scenario 2/3* 0.19 0.15 1,159,907 Option 1 — Scenario 4a* 0.22 0.18 1,374,990 Option 2 — Scenario 4b 0.22 0.18 1,374,990 * Proposed scenarios

7.2.5 Valuation of Predicted Reductions in Well Nitrate Concentrations EPA's analysis relies upon a benefits transfer approach to value p redicted reductions in well nitrate concentrations. EPA used three general steps to identify and apply values for benefit s transfer: (1) A literature search to identify potentially applicable primary studies. (2) Evaluatio n of the validity and reliability of the studies identified. Primar y evaluation criteria included:7-10 • the relevance (applicability) of the commodity being valued in th e origina l studies to the policy options being considered for CAFOs ; and

• th e robustness (quality) of the original study, evaluated on multipl e criteria such as sample size, response rates, significance of finding s in statistical analysis, etc. (3) Selection and adjustment of values for application to CAFO impacts.
Append ix 7-C provides detailed information on EPA's literature search and the criteria applied t o evaluate and select the studies employed in the benefits assessment. Thro ugh its review and evaluation of the relevant literature, EPA selected three studies t o provide the primary values used for the benefit transfer:

• A study by Poe and Bishop (1992), which the analysis employs to valu e change s in well nitrate concentrations from above the MCL to below th e MCL.

• A study by Crutc hfield et al. (1997), which EPA employs to value marginal changes in nitrate concentrations below the MCL.

• A study by De Zoysa (1995), which EPA employs to value marginal chan ges in nitrate concentrations below the MCL. The discussion below briefly summarizes these studies. Additional information is provided i n Exhibit 7-6.7-11 Exhibit 7-6 SUMMARY INFORMATION ON STUDIES USED FOR BENEFITS TRANSFER Study Reference Poe and Bishop Crutchfield et al. De Zoysa Year of Analysis 1992 1997 1995 Place Portage County, WI IN, Central NE, PA, WA Maumee River Basin, northwest Ohio Household Water 100% on private wells IN 73%; NE 31%; PA 47%; Not specified Supply/ WA 26% non-municipal Groundwater Use Groundwater An increase in the number of None given Typical N concentrations Baseline Scenarios wells in Portage County with range from 0.5-3 mg/L,

nitrate contamination although some are much higher Change in Groundwater protection If tap water has 50% greater Reduce levels to Groundwater program to keep nitrate levels N levels than EPA’s MCL, 0.5-1 mg/L Scenario below EPA standards how much to reduce to min. safety standards; how much to eliminate Source of Agricultural activities Not specified Agricultural fertilizer Contaminants Types of Values Option price (use value) Total value Total value Estimated Duration of Payment Annually, for as long as Monthly, in perpetuity One time Vehicle respondent lives in the county Mean HH WTP in $412.00 (25% reduction in $21.72 to reduce from 10 $59.33 (lower bound 1999 Dollars nitrates to safe level) mg/L to 0 mg/L ($2.17 per mean)

$484.00 (households with mg/L) $1.78 per mg/L (using 3% 100% probability of future discount rate) contamination)

7.2.5.1 Poe and Bishop (1992) Poe and Bishop (1992, 1999) and Poe (1993) re port on the results of a contingent valuation study conducted in rural Portage County, Wisconsin, to estimate the conditional incremental benefit s of reduci ng nitrate levels in household wells. The area has had extensive nitrate problems, an d previous research suggested that 18 percent of private wells in the area exceeded the MCL. Th e survey comprised two stages. In the first stage, individuals were asked to submit water samples fro m their tap and to complete an initial questionnaire. In the second stage, individuals were provide d with their nitrate test results, general information about nitrates, and a graphical depiction of their exp osure levels relative to both natural levels and the MCL; they then were asked to respond t o contingent valuation questions ( ex post ).7-12

The respondents' willingness-to-pay values varied, as expected, in accordance with the result s of the ir wells' nitrate tests and other information provided to them. Poe (1993) reports tha t househo lds' whose wells were considered certain at some point in the future to exceed the nitrat e MCL would be willing to pay, on average, $484 per year for a program to keep all wells in Portage County at or below the MCL. Poe and Bishop (1999) expand on the results of the survey b y developing a non-linear valuation function tha t characterizes how household willingness to pay for a 25 percent reduction in well nitrate concentrations varies with the initial extent of nitrat e contamination. Their analysis shows that household willingness to pay for such a program increase s as baseline well nitrate concentrations increase from 2 mg/L to 14.5 mg/L, then declines to zero at a baseline concentration of approximately 22.5 mg/L. Based on their valuation function, Poe an d Bishop estimate that households would be willing to pay an average of $412 per year for a 25 percen t reduction from a baseline nitrate contamination level of 14.5 mg/L. Since such a change woul d reduce nitrate concentrations to very near the MCL, EPA considers it representative of househol d wi llingness to pay to reduce such concentrations to safe levels. Taking the mid-point of the $48 4 and $412 values reported by Poe (1993) and Poe and Bishop (1999), respectively, EPA estimates tha t households whos e wells exceed the nitrate MCL would be willing to pay $448 per year to reduc e nitrate concentrations to safe levels. The reliability of these results appears to be reasonably high because the contingent valuatio n (CV) instrument was developed and implemented with careful attention to detail and established C V research protocol. A potential limitation is th at the study is based on a relatively small sample size (480 households); however, good response rates were obtained from this sample (approximately 80 percent for the first stage and 64 percent for the ex post stage). The Poe and Bishop study is the onl y study EPA reviewed that elicited such informed ex post values. These value statements may b e considere d more reliable than others because respondents knew more about the condition of thei r own water supply and thus were able to make bette r informed decisions. Moreover, in comparison to the other studies evaluated, the value estimates from this study seemed to represent a conservativ e lower bound on households’ values for reducing nitrates to the MCL.

7.2.5.2 Crutchfield et al. (1997) Crutchfield et al. (1997 ) evaluated the potential benefits of reducing or eliminating nitrates in drinking water by estimating average willingness to pay f or safer drinking water. They surveyed 800 people in rural and non-rural areas in four regions of the United States (Indiana, Nebraska , Pennsylvania, Washington), using the contingent valuation metho d (CVM) and posing questions in a dichotomo us choice format. Respondents were specifically asked what their willingness to pa y wou ld be to have the nitrate levels in their drinking water (a) reduced to “safe levels,” an d (b ) completely eliminated. Respondents were told that this would be accomplished using a filte r installed at their tap, and the cost would be included in their monthly water bill. Respondents were also asked questions regarding sociodemographic characteristics such as income, age, education, an d whether they currently use treate d or bottled water. Across all regions, the resulting willingness to pay, per hous ehold, to reduce nitrates to safe levels ranged from $45.42 per month to $60.76 pe r7-13

month, with a mean of $52.89. The willingness to pa y to completely remove nitrates from drinking water ranged from $48.26 per month to $65.11 per month, with a mean of $54.50. The study found two va riables to be significantly related to a respondent’s willingness to pay: “years lived in ZI P code,” which was positively correlated with willingness to pay, and “age of respondent,” which was negatively correlated.

7.2.5.3 De Zoysa (1995) De Zoysa (1995) applied the contingent valuation method to evaluate the benefits of a number o f programs to enhance environmental quality in Ohio's Maumee River basin, including a program to stabilize an d reduce groundwater nitrate levels. The study solicited willingness-to-pay values from residents of both rural and urban areas in the river basin, as well as residents of one out

of-basin urban area. A portion of respondents were asked whether they would pay different amounts , via a one-time special tax, to reduce nitrate contamination from fertilizer applied to fields. Under the hypothetical scenarios, nitrate concentrations would be reduced from the current range of 0.5-3. 0 mg/L to a range of 0.5-1.0 mg/L. Individuals were also asked questions regarding sociodemographi c characteris tics, preferences for priorities for public spending, and how they used the resource i n question. Ba sed on the lower bound of the mean values reported, the study found an average onetime househo ld willingness to pay of $52.78 for a 1 mg/L reduction in groundwater nitrat e concentr ations. The study also found that income, the level of priority placed on groundwate r protection, and interest in increasing government spending on education, h ealthcare, and vocational trai ning all were positively and significantly correlated with willingness to pay to improv e groundwater quality.

7

. 2.5.4 Adjustments to the Values EPA employs the results of the Crutchfield et al. and De Zoysa reports to estimate annua l household willingness to pay to reduce well nitrate concentrations when those concentrations ar e already below the nitrate MCL. EPA derives the appropriate value from Crutchfield by comparing the reporte d monthly willingness-to-pay values for reducing nitrate concentrations from above the MCL to the MCL and from above the MCL to zero. The difference between these values is $1.61 per mon th. For a change between the MCL of 10 mg/L and 0 mg/L, this represents a per mg/ L mo nthly willingness to pay of $0.16, or $1.92 annually (1997$). To derive a comparable annua l value f rom De Zoysa, EPA annualizes the willingness to pay value obtained from that study (a n averag e one-time household willingness to pay of $52.78 for a 1 mg/L reduction in groundwate r nitrate concentrations) at an annual discount rate of 3 percent. This calculation yields an estimated annual household willingness to pay for a 1 mg/L reduction in nitrate concentrations of $1.5 8CPI-U Series ID CUUR0000SA0, not seasonally adjusted, U.S. city average, all items. 67 7-14 (1995$). EPA applied the Consumer Price Index (CPI) to convert these values to 1999 dollars. 67 The Agency then applied the midpoint of the two values, $1.97 per mg/L per household per year, to val ue changes in well nitrate concentrations between 10 mg/L and 1 mg/L. Reductions in wel l nitrate concentrations below 1 mg/L are not valued, since EPA assumes a natural nitrate backgroun d level of 1 mg/L. As noted above, EPA relies on the findings of Poe and Bishop to estimate that households wh ose wells exceed the nitrate MCL would be willing to pay $448 per year to reduce nitrat e concent rations to safe levels. These values are expressed as willingness to pay per year as long as the individual lives in the county, and thus can be directly translated to the policy scenarios. Exhibit 7-7 summarizes the point value estimates used for benefits transfer.

Exhibit 7-7 WILLINGNESS-TO-PAY VALUES APPLIED TO BENEFITS TRANSFER Study Value 1999$ Poe and Bishop Annual WTP $448.00 Average of Crutchfield et al. and De Zoysa Annual WTP per mg/L between 10 mg/L and 1 mg/L. $1.97

7.2.5.5 Timing of Benefits It is unlikely that change s in CAFO regulations would immediately result in the changes in well nitrate concentrations that EPA's statistical mode l predicts. While hydrogeological conditions and other factors may vary significantly from case to case, considerable time may pass before most wells reach the steady state nitrate concentratio ns the model forecasts. Therefore, it is necessary to develop a time profile of the anticipated benefits of revised CAFO standards. EPA estimates that approximately 75 percent of affected wells would realize the full benefit s of reduced nitrogen loadings within 20 years (Hall, 1996). Assuming that the number of well s achieving new steady state c onditions increases linearly over time, this translates to approximately 3.7 percent of wells achieving new steady state conditions each year . At this rate, all affected wells would achieve new steady state conditions in approximately 27 years. For purposes of characterizin g the benefi ts of reduced contamination of private wells, EPA's analysis adopts these assumptions

.7-15

7.3 RESULTS Exhibit 7-8 illustrates the time profile of benefits for EPA's proposed revisions to the CAFO s t andards. As the exhibit shows, annual benefits increase from approximately $3 million per year in the first year following implementation to between $70 million and $80 million annually in the twenty-seventh and subsequent years. The prof ile of benefits over time for all regulatory scenarios is similar, but in each case reaches a different steady-state level. Exhibit 7-9 summarizes th e estima ted annual benefits, once steady state conditions are achieved, for each of the regulator y scenarios evaluated. As the exhibit indicates, these benefits range from a low of approximately $70 million p er year, the estimate arrived at for Option 1-Scenario 1, to a high of approximately $7 7 million per year, the estimate developed for both Option 2-Scenario 4a and Option 2 Scenario 4b.

7.4 LIMITATIONS AND CAVEATS Omissions, biases, and uncertainties are inherent in any analy sis relying on several different data source s, particularly those that were not developed specifically for that analysis. Exhibit 7-10 summarizes key omissions, uncertainties, and potential biases for this analysis.Exh i b it 7-8
ANN UAL B ENEFIT

S O F R EDUCING PRIVATE WELL CONTAMINATION

$0 .00 $10 .00 $20 .00 $30 .00 $40 .00 $50 .00 $60 .00 $70 .00 $80 .00 $90 .00

0 10 20 30 40 50 60 70 80 90 100 Y ear s After Imp

le mentationAnnual Benefits (1999 $MM) Opt ion 1-Scenario 1 Opt ion 1-Scenario 2/3 Opt ion 1-Scenario 4b Opt ion 1-Scenario 4a Opt ion 2-Scenario 1 Opt ion 2-Scenario 2/3 Opt ion 2-Scenario 4a Opt ion 2-Scenario 4b

7-167-17 Exhibit 7-9 ESTIMATED ANNUAL BENEFITS OF REDUCED CONTAMINATION OF PRIVATE WELLS UNDER STEADY

STATE CONDITIONS ($1999, millions) Regulatory Scenario Annual Benefits Option 1-Scenario 1 $70.08 Option 1-Scenario 2/3 $70.17 Option 1-Scenario 4a $74.64 Option 1-Scenario 4b $74.64 Option 2-Scenario 1 $74.47 Option 2-Scenario 2/3* $74.59 Option 2-Scenario 4a* $77.07 Option 2-Scenario 4b $77.07 * Proposed scenarios7-18 Exhibit 7-10 OMISSIONS, BIASES, AND UNCERTAINTIES IN THE NITRATE LOADINGS ANALYSIS

Variable Benefit Comment Likely Impact on Net Well, land, and nitrate data Geographic coverage Unknown Data availability limited the well samples used in the statistical modeling to those from 138 counties nationwide. Well location selection Positive Wells sampled in the USGS Retrospective database may or may not be random. Samples may be focused on areas with problems with nitrate. Year of sample Unknown Samples taken over 23 years. Land use and other factors influencing nitrate concentrations in the vicinity of the well may have changed over time. Nitrate loadings from AFOs with 0- Positive Data for the smallest AFOs were not included in this analysis 300AU because they will not be affected by the proposed regulations. This may subsequently underestimate total loadings, resulting in an overestimate of the impact of nitrogen loadings on well nitrate concentrations. Percent of wells above 10 mg/L Unknown Based on the USGS Retrospective database, EPA assumes that 9.74 percent of wells currently exceed the MCL. If the true national percent is lower (higher), EPA's analysis overstates (understates) benefits. Sampling methods Unknown Data set compiled from data collected by independent state programs, whose individual methods for measuring nitrate may differ. Model Variables Well construction and age Unknown No reliable data available nationally. Spatial data Unknown No national data available on the distance from well to pollutant source. Benefit Calculations Per household value for reducing well Negative The Poe and Bishop values generally appear to be a lower nitrates to the MCL bound estimate of households' WTP for reducing nitrates to the MCL. Years until wells achieve steady state. Negative The analysis assumes a linear path over 27 years until reduced nitrogen loadings would result in most wells achieving reduced nitrate concentrations. A large portion of wells (especially shallower wells) may achieve this on a much faster time path. Values for marginal reductions below Positive If most of the benefits from reductions in nitrate the MCL concentrations below the MCL are related to a threshold effect or removing all human induced nitrates, then the assumption that benefits increase linearly with reductions in nitrate concentrations from 10 mg/L to 1 mg/L will overstate the benefits of marginal reductions. Baseline characterization Negative Baseline well concentrations are based on observed levels that are in some cases more than 20 years old. These reflect AFO loadings from past decades that likely understate current loadings and, hence, underestimate anticipated well concentrations absent regulations. Exclusion of values for reduced nitrate Negative Reductions in nitrate concentrations in wells that would concentrations in wells that would remain above the MCL after the implementation of new remain above the MCL after the regulations are not valued. The Agency's review of the implementation of new regulations economics literature failed to identify studies that would provide an adequate basis for valuing such changes. Exclusion of values for marginal Negative The benefits of marginal changes in nitrate concentrations reductions in nitrate concentrations between 10 mg/L to 1 mg/L for wells with nitrate levels above below the MCL, for wells with nitrate the MCL at baseline and below the MCL after implementation concentrations above the MCL at of new regulations are not calculated. These benefits are baseline and below the MCL after potentially captured in valuing the achievement of safe nitrate implementation of new regulations concentrations.7-19

7.5 REFERENCES Agricultur e Canada. 1991. Ontario Farm Groundwater Quality Survey. Agriculture Canada , Ottawa. Burrow, K.R. 1998. Occurrence of Nitrate and Pesticides in Groundwater beneath Thre e Agricultural Land-Use Settings in the Eastern San Joaquin Valley, California. USGS , Denver, CO. Carleton, G.B. 1996. Nitrate in Groundwater and Surface Water in a Residential Subdivision, Wes t Mercer Township, New Jersey. USGS, Denver, CO. CDC. 1998. A Survey of the Quality of Water Drawn from Domestic Wells in Nine Midwes t States. NCEH 97-0265. Centers for Disease Control and Analysis. National Center fo r Environmental Health. Crutchfield, S.R., J.C. Cooper, and D. Hellerstein. 1997. Benefits of Safer Drinking Water: Th e Val ue of Nitrate Reduction. Agricultural Economic Report 752. U.S. Department o f Agriculture, Economic Research Service, Food and Consumer Economics Division. De Zoysa, A.D.N. 1995. A Benefit Evaluation of Programs to Enhance Groundwater Quality , Surface Water Quality and Wetland Habitat in Northwest Ohio. Dissertation, The Ohio Stat e University, Columbus. Desvousge s, W.H., M.C. Naughton, and G.P. Parsons. 1992. “Benefit Transfer: Conceptua l Problems in Estimating Wat er Quality Benefits Using Existing Studies.” Water Resources Research 28(3):675-683. Detroy, M.G. 1988. Groundwater Q uality Monitoring Program in Iowa: Nitrate and Pesticides in Shallow Aquifers. USGS, Denver, CO. Divis ion of Water Quality, Groundwater Section. 1998. Impact of Animal Waste Lagoons o n Ground Water Quality. Draft Repo rt. Department of Environment and Natural Resources, Raleigh, NC. Giraldez , C. and G. Fox. 1995. “An Economic Analysis of Groundwater Contamination fro m Ag ricultural Nitrate Emissions in Southern Ontario.” Canadian Journal of Agricultura l Economics 43:387-402. Hall. 1996. Simulation of Nitrates in a Regional Subsurface System: Linking Surface Managemen t with Ground Water Quality. Ph.D. Thesis. Colorado State University.7-20

Ham, J.M., L.N. Reddi, C.W. Rice and J.P. Murphy. 1998. Evaluation of Lagoons for Containmen t of Animal Waste. Manhattan: Department of Agronomy, Kansas State University. Kross, B.C., G.R. Hallberg, and D.R. Bruner. 1993. “The Nitrate Contamination of Private Well Water in Iowa.” American Journal of Public Health 83:270. Lic htenberg, E. and L.K. Shapiro. 1997. “Agriculture and Nitrate Concentrations in Marylan d Community Water System Wells.” Journal of Environmental Quality 26:145-153. Lindsey, B.D. 1997. Nitrate in Groundwater and Streambase Flow in the Lower Susquehanna Rive r Basin, Pennsylvania and Maryland. USGS, Denver, CO. Mueller, D.K., P.A. Hamilton, D.R. Helsel, K.J. H itt, and B.C. Ruddy. 1995. Nutrients in Ground Water and Sur face Water of the United States -- An Analysis of Data through 1992. U.S

. Geological Survey Water-Resources Investigations Report 95-4031. Nat ional Research Council. 1997. Valuing Ground Water: Economic Concepts and Approaches

. National Academy Press, Washington, DC. Poe, G.L. 1993. Information, Risk Perceptions, and Contingent Value: The Case of Nitrates i n Groundwater. Ph.D. Dissertation, University of Wisconsin-Madison. Poe, G.L. and R.C. Bishop. 1992. Measuring the Benefits of Groundwater Protection fro m Agricultural Contamination: Results from a Two-Stage Contingent Valuation Study. Staff Paper Series, University of Wisconsin-Madison. Poe, G.L. and R.C. Bishop. 1999. "Valuing the Incremental Benefits of Groundwater Protectio n When Exposure Levels Are Known." Environmental and Res ource Economics 13:341-367. Randall, A . and D. de Zoysa. 1996. Groundwater, Surface Water, and Wetlands Valuation fo r Benefits Transfer: A Progress Report. W-133 Benefits and Costs Transfer in Natura l Resource Planning, Ninth Interim Report, Department of Economics, Iowa State Univer sity, Ames, IA. Richards, R .P. et al. 1996. “Well Water Quality, Well Vulnerability, and Agricultura l Contamination in the Midwestern United States.” Journal of Environmental Quality 25:389

- 402. Ritter, W.F. and A.E.M. Chirnside. 1990. “Impact of Animal and Waste L agoons on Groundwater Quality.” Biological Wastes 34:39-54. Spalding, R. F. and M.E. Exner. 1993. “Occurrence of Nitrate in Groundwater -- A Review. ” Journal of Environmental Quality 22:392-402.7-21

Stratus. 2000. The Benefits of Reducing Nitrate Contamination in Private Domestic Wells. Repor t prepared for U.S. Environmental Protection Agency, Office of Science and Technology. Sw istock, B.R., W.E. Sharpe, and P.D. Robillard. 1993. “A Survey of Lead, Nitrate, and Rado n Contamin ation of Individual Water Systems in Pennsylvania.” Journal of Environmenta l Health 55:6. Tetra Tech. 2000. Development of Pollutant Loading Reductions from the Implementation o f Nutrient Management and Best Management Practices. Draft report prepared fo r U.S. Environmental Protection Agency, Office of Science and Technology. U.S. EPA. 19 90. National Survey of Pesticides in Drinking Water Wells. U.S. Environmenta l Protection Agency. USGS. 1985. Occurrence of Nitrate and Herbicides in Groundwater in the Upper Conestoga River Basin, Pennsylvania. Water Resources Investigations Report 85-4202. USGS. 1996. Retrospective Database for Nutrients in Groundwater and Surface Water. USGS

. http://water.usgs.gov/nawqa/nutrients/datasets/retrodata.html. Accessed 6/1/00. USGS. 1998. Nitrate Concentrations in Ground Water in the Pale ovalley Alluvial Aquifiers of the Nemaha Natural Resources District, Nebraska, 1989 and 1994-96. USGS Water-Resources Investigations Report 98-4106. USGS, Lincoln, NE. Vitosh, M.L. 1985. “Nitrogen Management Strategies for Corn Producers.” Extension Bulleti n WQ06. Cooperative Extension Service, Michigan State University. August. Walker, D.R. and J.P. Hoehn. 1990. “The Economic Damages of Groundwater Contamination in Sma ll Rural Communities: An Application to Nitrates.” Northcentral Journal o f Agricultural Economics 12:47-56.7A-1 Appendix 7-A MODEL VARIABLES

EPA's statistical analysis of the relationship between nitrogen loadings and well nitrat e concentrations is based on the following linear model:

Nitrate (mg/L) = ß + ß Ag Dummy + ß Soil Group + ß Well Depth 0 1 2 3 + ß Septic Ratio + ß Alt N Source + ß Loadings Ratio + , 4 5 6 i,
where nitrate concentration (mg/L) is the dependent variable. The variables used to explain nitrate concentrations in well water (i.e., the model' s independent

variables) can be classified into two groups: well and land characteristics, and nitroge n inputs. Definitions of thes e variables are provided below. Unless otherwise noted, EPA obtained the data used in developing the model from the USGS Retrospective Database.

Well and Land Characteristics Ag Dummy: This variable describes the predominant land use at the well's location (1 fo r agr icultural land; 0 otherwise). Other land uses identified in the database include woods, range , urban, and other. Soil Group: The soil group variable is an index that i ntegrates several factors — including runoff potential, permeability, depth to water table, depth to an impervious layer, water capacity, an d shrink-swell potential — to characterize hydrological conditions in the vicinity of the well. Possibl e values range from a minimum of 1 to a maximum of 4. Well Depth: The well depths reported in the USGS database range from 1 foot to 5,310 feet

. For observations used in the regression analysis, the maximum well depth is 1,996 feet.
Nitrogen Inputs AFO Load ings Ratios and Scenarios: The AFO loadings ratio is a unique value for eac h count y. It is calculated by dividing estimated leached nitrate loadings for the county (pounds pe r year) by the county's total area (acres). The analysis em ploys baseline loadings data to estimate the7A-2

coefficients for the independent variables. It applies these coefficients, combined with loadings dat a representative of post-regulatory conditions, to estimate changes in well nitrate concentrations unde r each regulatory scenario. Septic Ratio: The septic ratio is a proxy me asure of potential nitrogen loadings from septic systems. The analysis develops a unique value for each county. This value is calculated by dividin g the number of housing units in the county that use septic systems by the county's total area (acres). EPA obtained data on septic system use from the 1990 U.S. Census. Alternate N Source: Alternate nitrogen sources include fertilizer and atmospheric deposition

. Values for this variable are reported in pounds per acre per year.
Summary Statistics Exhibit 7A-1 reports summary statistics on the variables used in the analysis.
Exhibit 7A-1 SUMMARY STATISTICS
Variable N Mean Deviation Minimum Maximum Standard
Nitrate Concentrations 2928 3.585 6.552 0.050 84.300 Ag Dummy 2928 0.775 0.418 0.000 1.000 Soil Group 2928 2.418 0.658 1.000 4.000 Well Depth 2928 169.191 133.468 1.000 1,996.000 Septic Ratio 2928 0.029 0.028 0.000 0.151 Alternate N Source 2928 28.890 18.981 0.869 99.631 Loadings Ratio (Baseline Scenario) 2928 6.626 14.022 0.003 63.3541 y ) y exp( ) ( ) y ( f − α α θ

− α Γ θ
=



## ( ) ( ) ( ) ( )



## [ ] 

## ∑

− +

− Γ

− = i i i i i i i y y x y L log 1 log log , ; log a q a q a b a

7B-1

Appendix 7-B THE GAMMA MODEL

The anal ysis uses a gamma model to fit the right skew of observed values for well nitrat e concentrations as well as the nonnegative constraint on the dependent variable. Visual inspection of the nitrate concentration distribution suggests a gamma distribution with density function:

.

Let For this distribution, the expected value of y is i

+ (y ) = " / 2 = " exp ( $P ) i i i The use of the gamma distribution instead of the more commonly employed exponential distributio n is appropriate because " is assumed to equal 1 i n the exponential distribution, but was estimated to be significantly different than 1 in EPA's empirical work. The gamma distribution also offers th e advantag es of making the density function more flexible and giving more curvature to th e distribution. The likelihood function is:

Ex hibit 7B-1 provides statistical results from the gamma model. All coefficients are of th e expected sign and significant at the 1 percent level. In particular, the coefficient for the Loadings Ratio variable is positive, as expected, indicating that an increase in nitrogen loadings leads t o increased well nitrate concentrations.7B-2 Exhibit 7B-1 GAMMA REGRESSION RESULTS

Variable Estimate Standard Error Statistic Significance

Parameter Asymptotic TIntercept 1.492 0.151 9.891 0.000 Ag Dummy 0.691 0.066 10.452 0.000 Soil Group -0.335 0.043 -7.725 0.000 Well Depth* -0.106 0.015 -7.178 0.000 Septic Ratio 2.623 1.102 2.380 0.009 Alt N Source* 20.258 1.628 12.444 0.000 Loadings Ratio 0.010 0.002 5.037 0.000 Alpha 0.498 0.011 46.368 0.000 Mean log-likelihood = -1.854 N = 2,928 *The raw data were scaled by a factor of 100 for Well Depth and 1,000 for Alt N Source in order for the GAUSS program to converge to a solution.7C-1 Appendix 7-C LITERATURE SEARCH AND EVALUATION

Literature Search The o bjective of EPA's literature search was to identify prior studies that had developed o r eli cited values for changes in groundwater quality, focusing in particular on values for reduce d nitrates. The search drew in part upon two databases: the Colorado Association of Researc h Libraries (CARL), which includes the holdings of several university libraries in Colorado and th e West; a nd the Environmental Valuation Resource Inventory (EVRI), a database compiled b y Envi ronment

Canada that includes empirical studies on the economic value of environmenta l benefits and human h ealth effects. In addition, EPA solicited suggestions for studies pertaining to grou ndwater

valuation and nitrate contamination through the ResEcon listserver, which reaches a netwo rk of approximately 700 academics, professionals, and other individuals with interests i n natural resource and environmental economics. Through this extensive search and additional revie w of selected bibliograp hies, EPA identified 11 potentially relevant studies. Since most households’ values for reducing nitrates in private domestic wells are primarily nonmarket values, most of the identified studies involve stated preference value elicitation (e.g., contingent valuation).
Evaluating Studies for Benefits Transfer The economics literature suggests several criteria in evaluating primary studies for undertakin g benefits transfer. Desvousges et al. ( 1992) develop five criteria to guide the selection of studies for appl ication to a surface water quality issue: that the studies to be transferred (1) be based o n adequ ate data, sound economic method, and correct empirical technique (i.e., “pass scientifi c muster”); (2) evaluate a change in water quality similar to that expected at the policy site; (3) contai n regression results that describe willingness to pay as a function of socioeconomic characteristics; (4 ) have a study site that is similar to the policy site (in terms of site characteristics and populations); and (5) have a study site with a similar market as the policy site. NOAA condenses the fiv e De svousges criteria into three considerations: (1) comparability of the users and of the resource s and/or services being valued and the changes resulting from the discharge of concern; (2 ) comparability

of the change in quality or quantity of resources and/or services; and (3) the quality of the studies bei ng used for transfer [59 FR 1183]. In a general sense, items (2), (4), and (5) o f Desvousges et al. and items (1) and (2) of NOAA are concerned with the applicability of an origina l study to a policy site. Items (1) and (3) of Desvousges et al. and item (3) of NOAA are concerned with the quality of the original study. To assess original studies for use in valuing estimated changes in well nitrate levels unde r alternate CAFO regulations, EPA evaluat ed the applicability and the quality of the original studies on several cri teria. To the extent feasible, EPA obtained or derived information from each of th e7C-2

reports or papers for 28 categories of information used to characterize the studies. Becaus e applicability

to CAFOs and quality of the value estimates are distinct concepts, EPA evaluated thes e characteristics of the studies separately. Overall, the goal of the rating process was to identify studie s that elicited high-quality value estimates (reliable and valid) and which were most applicable to the benefits assessment. There were three steps in the rating process: (1) identify study characteristics upon which to judge applicability and quality; (2) assign scores to the studies based on these characteristics; (3) assi gn weights to these scores for aggregating scores into unidimensiona l measures of applicability and quality.
Criteria for Ranking based on Applicability Applicabil ity

refers to the relationship between values elicited in the primary groundwate r valuation studies and be nefit estimates necessary for application to the analysis of alternate CAFO regula tions. EPA's criteria for evaluation of applicability included comparison of the followin g characteristics of studies with likely CAFO situations:

• location (urban, rural, etc.);

• water supply/groundwater use (percentage on wells);

• type of contaminants (scenario involved nitrate contamination of groundwater) ;

• source of contaminants (scenario involved conditions similar t o those relevant for CAFOs);

• value estimates are for the correct theoretical construct (e.g., total willingness to pay for reducing groundwater contamination from nitrates).
Criteria for Ranking based on Quality Analysis of study quality was based on evaluation of the validity and reliability of the value estimates derived in the primary groun dwater valuation research. Most of the 11 identified studies involved stated preference elicitation using survey methods. Based on professional experience as to wha t constitutes a valid and reliable stated preference valuation study, EPA identifie d characteristics of these studies that indicat e reliability and validity. Criteria for evaluation of study quality included:7C-3

• whether the study was published or peer reviewed;

• whether the survey implementation met professional standards;

• how many respondents there were and what the response rate was;

• whether and how the groundwater baseline was characterized and what chang e was presented in the groundwater scenario;

• whether the credibility of scenario change was assessed;

• what v aluation methodology was used and whether it was appropriate fo r eliciting the intended value measures;

• the type and duration of payment vehicle;

• whether appropriate empirical estimation was undertaken;

• whether expected explanatory variables were found to be significant.The NWPCAM analysis addresses changes in the quality of lakes, rivers, and stream s 68 above the h ead of tide, and considers recreational swimming, fishing, and non-use values. Th e assessment

of potential improvements in shell fishing opportunities focuses on marine and estuarin e waters and the commercial use of shellfish resources. The assessment of pote ntial reductions in the contaminati on of private wells considers the use of groundwater as a source of domestic wate r supplies. 8-1 INTEGRATION OF RESULTS CHAPTER 8

8.1 INTRODUCTION
T h is chapter summarizes EPA's estimates of the benefits associated with potential revisions to the NPDES provisions and Effluent Li mitation Guidelines (ELGs) pertaining to CAFOs. It first describes th e Agency's approach to aggregating the results of the studies described in Chapters 4 through 7. It then describes EPA's approach to discounting future benefits and presents th e ag gregated benefits of each regulatory scenario analyzed, both in a single present value and as a n annualized benefits stream. Finally, the chapter discusses the key limitations of the ana lysis and the implications of these limitations in characterizing the benefits of revised CAFO standards.

8.2 INTEGRATION OF ANALYTIC RESULTS To develop an integrated assessment of the benefits of each alternative regulatory scenario , EPA simply adds the results of the analyses presented in Chapters 4 through 7. To the extent that these analyses address similar benefits, this approach may lead to double-counting an d overestimation of benefits. In this case, however, EPA has determined that the potential for double

counting is small. The analyses that generate the largest benefits estimates — the NWPCA M analysis of the benefits of improved surface water quality, the evaluation of poten tial improvements in commer cial shell fishing opportunities, and the assessment of potential reductions in th e contamina tion of private wells — examine different water resources and different uses of thos e resources. Thus, the benefits estimated in these analyses are clearly additive. The only possible

68 source of double -counting, therefore, lies in integrating the results of the NWPCAM analysis with EPA's evaluation of the ben efits attributable to reducing the frequency and magnitude of fish kills.The data upon which the fish kills analysis is based include fish kill incidents below the 69 head of tide. The NWPCAM analysis extends only to freshwater resources. 8-2 The extent to which the NWPCAM analysis and the fish kills analysis may double-coun t benefi ts is unclear, but unlikely to be significant. Both analyses address changes in the quality o f riv ers, lakes, and streams. In addition, at least some of the benefits of reducing the incidence o f 69 fi sh kills likely stem from the associated improvement in recreational fishing opportunities, a be neficial use which the NWPCAM analysis considers. Thus, some double-counting is possible

. Th e NWPCAM analysis, however, is based upon modeling of surface water quality under stead y state conditions; the analysis is not likely to capture all of the impacts of revised CAFO standards on circumstances (e.g., the overflow of a lagoon under severe storm conditions) that may lead to fis h kills. In addition, the approach employed in valuing the reduced incidence of fish kills explicitl y ex cludes lost use values, such as those associated with recreational fishing. These consideration s suggest that at least some, if not all, of the benefits estimated in the fish kills analysis are incrementa l to those estimated in the NWPCAM analysis. From a practical standpoint, the implications of any double-c ounting between the NWPCAM analysis and the fish kills analysis are minim al. At most, the estimated annual benefits of reducing the incidence of fish kills amount to no more than approximately 5 percent of the annual benefit s estim ated in the NWPCAM analysis; this is the case for Option 1-Scenario 4a. Under EPA' s proposed regulatory sc enarios, the estimated annual benefits of reducing the incidence of fish kills equal less than 0.4 percent of the a nnual benefits estimated in the NWPCAM analysis. Thus, EPA has concluded that its approach to integrating the findings of the underlying analyses do es not result in any significant degree of double-counting.

8.3 PRESENT VALUE OF BENEFITS The results of the analys es in Chapters 4 through 7 are expressed as annual benefits streams. To calcul ate the present value of these benefits at the time new regulations are implemented, EPA employs th ree alternative real discount rates: three, five, and seven percent. The seven percen t discount rate represents the real rate of return on private investments and is consistent with the rate mandated by the Office of Management Budget for analysis of proposed regulations. The thre e percent disc ount rate reflects the social rate of time preference for consumption of goods an d services , and is consistent with the rate recommended by many economists for analysis o f environmental benefits. The five percent discount rate represents the mid-point of the three to seve n percent range. In calculating the present value o f benefits, EPA assumes an infinite time frame; i.e., as long as the r egulations remain in effect the associated benefits will be enjoyed in perpetuity. As a practical matter, this approach is equivalent to assuming that the regulations will remain in effect fo r several generations, since the present value of benefits beyond this point appro aches zero; however,8-3

it avoids the need to arbitrarily specify a period of time over which the regulations are assumed to remain in effect, and allows EPA to represent fu lly the present value of the benefits estimated. For purposes of illustrating the sensitivity of EPA's results to this assumption, Appendix 8-A illustrates the i mpact of alternative time frames on present value estimates developed for one of EPA' s proposed regulatory scenarios. Appendix 8-B provides additional detail on the calculation of presen t values. Exhibits 8-1 through 8-4 present the results of the present value calculations for each of the benefit c ategories addressed in Chapters 4 through 7. As shown, the estimated benefits fo r alternative regulatory scenarios vary significantly, with scenarios that employ Option 2 (which woul d es tablish a phosphorus-based manure application limit) generally providing higher benefits tha n scenarios e mploying Option 1 (a nitrogen-based manure application limit). In all cases, Option 2- Scenario 4b yields the highest benefits, while Option 1-Scenario 1 yields the lowest. Within benefit s categories, benefits are lowest using the seven percent discount rate and highest using the thre e percent discount rate, reflecting the impact of alternative discounting assumptions on the presen t value of future benefits.

Exhibit 8-1 PRESENT VALUE OF ESTIMATED BENEFITS: ACHIEVING RECREATIONAL USE LEVELS

(1999 dollars, millions)

Regulatory Scenario 3 Percent 5 Percent 7 Percent Discount Rates

Option 1-Scenario 1 $163.3 $98.0 $70.0 Option 1-Scenario 2/3 $210.0 $126.0 $90.0 Option 1-Scenario 4a $183.3 $110.0 $78.6 Option 1-Scenario 4b $240.0 $144.0 $102.9 Option 2-Scenario 1 $2,920.0 $1,752.0 $1,251.4 Option 2-Scenario 2/3* $4,236.7 $2,542.0 $1,815.7 Option 2-Scenario 4a* $3,616.7 $2,170.0 $1,550.0 Option 2-Scenario 4b $4,833.3 $2,900.0 $2,071.4 * Proposed scenarios8-4

Exhibit 8-5 presents, on a present value basis, EPA's aggregated estimate of the benefits o f alt ernative revisions to the CAFO standards. As the exhibit shows, the present value of benefit s under EPA's proposed regulatory scenarios ranges from approximately $2.1 billion dollars (assumin g a discoun t rate of seven percent and employing the low-end of the estimated range of benefits fo r Option 2-Scen ario 4a) to $6.1 billion dollars (assuming a discount rate of three percent an d employing the high-end of the estimated range of benefits for Option 2-Scenario 2/3).

Exhibit 8-2 PRESENT VALUE OF ESTIMATED BENEFITS: REDUCED INCIDENCE OF FISH KILLS

(1999 dollars, millions)

Regulatory Scenario 3 Percent 5 Percent 7 Percent Discount Rates

Option 1-Scenario 1 $3.1 - $7.8 $1.9 - $4.7 $1.3 - $3.3 Option 1-Scenario 2/3 $3.9 - $10.2 $2.4 - $6.1 $1.7 - $4.4 Option 1-Scenario 4a $3.7 - $9.7 $2.2 -$5.8 $1.6 - $4.1 Option 1-Scenario 4b $4.4 - $10.8 $2.6 - $6.5 $1.9 - $4.6 Option 2-Scenario 1 $5.9 - $9.4 $3.5 -$5.7 $2.5 - $4.0 Option 2-Scenario 2/3* $7.3 - $12.3 $4.4 - $7.4 $3.1 - $5.3 Option 2-Scenario 4a* $7.1 - $11.8 $4.3 - $7.1 $3.0 - $5.0 Option 2-Scenario 4b $8.1 - $13.2 $4.8 - $7.9 $3.5 - $5.7 * Proposed scenarios8-5 Exhibit 8-3 PRESENT VALUE OF ESTIMATED BENEFITS: IMPROVED COMMERCIAL SHELL FISHING

(1999 dollars, millions)

Regulatory Scenario 3 Percent 5 Percent 7 Percent Discount Rates

Option 1-Scenario 1 $4.9 - $60.5 $2.9 - $36.3 $2.1 - $25.9 Option 1-Scenario 2/3 $6.6 - $78.6 $4.0 - $47.1 $2.8 - $33.7 Option 1-Scenario 4a $5.9 - $73.5 $3.6 - $44.1 $2.5 - $31.5 Option 1-Scenario 4b $7.4 - $85.5 $4.4 - $51.3 $3.2 - $36.6 Option 2-Scenario 1 $5.5 - $71.4 $3.3 - $42.8 $2.4 - $30.6 Option 2-Scenario 2/3* $7.3 - $90.6 $4.4 - $54.3 $3.1 - $38.8 Option 2-Scenario 4a* $6.5 - $80.6 $3.9 - $48.3 $2.8 - $34.5 Option 2-Scenario 4b $8.2 - $98.7 $4.9 - $59.2 $3.5 - $42.3 * Proposed scenarios

Exhibit 8-4 PRESENT VALUE OF ESTIMATED BENEFITS: REDUCED CONTAMINATION OF PRIVATE WELLS

(1999 dollars, millions)

Regulatory Scenario 3 Percent 5 Percent 7 Percent Discount Rates

Option 1-Scenario 1 $1,633.2 $798.2 $475.6 Option 1-Scenario 2/3 $1,635.3 $799.2 $476.2 Option 1-Scenario 4a $1,739.4 $850.0 $506.5 Option 1-Scenario 4b $1,739.4 $850.0 $506.5 Option 2-Scenario 1 $1,735.6 $848.2 $505.4 Option 2-Scenario 2/3* $1,738.2 $849.5 $506.1 Option 2-Scenario 4a* $1,796.0 $877.7 $523.0 Option 2-Scenario 4b $1,796.0 $877.7 $523.0 * Proposed scenarios8-6 Exhibit 8-5 PRESENT VALUE OF AGGREGATED BENEFITS

(1999 dollars, millions)

Regulatory Scenario 3 Percent 5 Percent 7 Percent Discount Rates

Option 1-Scenario 1 $1,804.5 - $1,864.9 $900.9 - $937.1 $549.0 - $574.9 Option 1-Scenario 2/3 $1,855.9 - $1,934.1 $931.5 - $978.5 $570.7 - $604.2 Option 1-Scenario 4a $1,932.4 - $2,005.9 $965.8 - $1,009.9 $589.2 - $620.7 Option 1-Scenario 4b $1,991.2 - $2,075.6 $1,001.1 - $1,051.8 $614.4 - $650.6 Option 2-Scenario 1 $4,667.0 - $4,736.4 $2,607.0 - $2,648.7 $1,761.7 - $1,791.4 Option 2-Scenario 2/3* $5,989.5 - $6,077.7 $3,400.2 - $3,453.2 $2,328.1 - $2,365.9 Option 2-Scenario 4a* $5,426.2 - $5,505.0 $3,055.9 - $3,103.1 $2,078.8 - $2,112.5 Option 2-Scenario 4b $6,645.5 - $6,741.2 $3,787.4 - $3,844.8 $2,601.4 - $2,642.4 * Proposed scenarios

8.4 ANNUALIZED BENEFITS ESTIMATES
In additi on to calculating the present value of estimated benefits, EPA has developed a n estimate of the annualized benefits attributable to each of the regulatory scenarios analyzed; these annualized values reflect the constant flow of benefi ts over time that would generate the associated present value. Appendix 8-C provides additional detail on the calculation of annualized benefits. EPA assu mes that benefits related to surface water quality improvements will begi n immediately after the revised regulat ions are implemented (i.e., because loadings will immediately decrease), and that these benefits will be constant from year-to-year. As a result, the annualize d bene fits in these categories (improved surface water quality, reduced fish kills, and improve d shellf ishing) are equivalent to the annual benefits estimated in Chapters 4 through 6, regardless of the discount rate employed. In the case of private well contamination, however, EPA assumes an uneven annual stream of benefits. As a result, EPA's estimates of the annualized benefits of reduce d private well contamination depend upon the discount rate employed. Exhibit 8-6 summarizes the range of annualized benefits for each benefit category under eac h of the regulatory scenarios analyzed. Note that the range of benefits associated with reduce d contaminat ion of private wells reflects the variation in discount rates employed in developing th e annualized benefits estimate (three to seven p ercent). In contrast, the range of values presented for reduced fish kill and shellfishing benefi ts is based solely on uncertainty in the underlying analyses.8-7

There is considerable variation in the range of benef its across regulatory scenarios, as well as some variation within scenarios with respect to the rel ative magnitude of surface water and groundwater benefits. I n particular, under scenarios that employ Option 1, the annualized benefits of reduce d private well contamination exceed those associated with other benefits categories. In contrast, unde r scenar ios that employ Option 2, the recreational and non-use benefits associated with improve d surface water quality account for the greatest share of benefits.

Exhibit 8-6 ESTIMATED ANNUALIZED BENEFITS OF REVISED CAFO REGULATIONS (1999 dollars, millions)

Regulatory Scenario Benefits Kills Shellfishing Contamination Recreational Reduced Private and Non-use Reduced Fish Improved Well
Option 1- Scenario 1 $4.9 $0.1 - $0.2 $0.1 - $1.8 $33.3 - $49.0 Option 1- Scenario 2/3 $6.3 $0.1 - $0.3 $0.2 - $2.4 $33.3 - $49.1 Option 1- Scenario 4a $5.5 $0.1 - $0.3 $0.2 - $2.2 $35.5 - $52.2 Option 1- Scenario 4b $7.2 $0.1 - $0.3 $0.2 - $2.6 $35.5 - $52.2 Option 2- Scenario 1 $87.6 $0.2 - $0.3 $0.2 - $2.1 $35.4 - $52.1 Option 2- Scenario 2/3* $127.1 $0.2 - $0.4 $0.2 - $2.7 $35.4 - $52.1 Option 2-Scenario 4a* $108.5 $0.2 - $0.4 $0.2 - $2.4 $36.6 - $53.9 Option 2- Scenario 4b $145.0 $0.2 - $0.4 $0.2 - $3.0 $36.6 - $53.9 * Proposed scenarios

Exhib it 8-7 presents EPA's aggregated estimate of annualized benefits for each of th e regulatory scenarios analyzed. Under the proposed regulatory scenarios, annualized benefits range from $146 million (Option 2 -Scenario 4a, assuming a seven percent discount rate) to $182 million (Opt ion 2-Scenario 2/3, assuming a three percent discount rate). Again, note that variation i n discount rates affects only the annualized benefits associated with reduce d contamination of private wells; other annualized benefits remain constant regardless of discount rates.8-8 Exhibit 8-7 SUMMARY OF ANNUALIZED BENEFITS

(1999 dollars, millions)

Regulatory Scenario Low High Low High Low High Discount Rates 3 Percent 5 Percent 7 Percent

Option 1-Scenario 1 $54.1 $55.9 $45.0 $46.9 $38.4 $40.2 Option 1-Scenario 2/3 $55.7 $58.0 $46.6 $48.9 $39.9 $42.3 Option 1-Scenario 4a $58.0 $60.2 $48.3 $50.5 $41.2 $43.4 Option 1-Scenario 4b $59.7 $62.3 $50.1 $52.6 $43.0 $45.5 Option 2-Scenario 1 $140.0 $142.1 $130.4 $132.4 $123.3 $125.4 Option 2-Scenario 2/3* $179.7 $182.3 $170.0 $172.7 $163.0 $165.6 Option 2-Scenario 4a* $162.8 $165.1 $152.8 $155.2 $145.5 $147.9 Option 2-Scenario 4b $199.4 $202.2 $189.4 $192.2 $182.1 $185.0 * Proposed scenarios

8.5 LIMITATIONS OF THE ANALYSIS AND IMPLICATIONS FOR CHARACTERIZING BENEFITS The results presented above are based on the four separate analyses presented in Chapters 4 through 7, and are subject to the specific uncertainties an d limitations that are discussed in detail in eachof these chapters. Beyond these limitations, however, it is important to note that EPA's analysi s does not attempt to comprehensively identify and value all potential environmental change s associated with proposed revisions to the CAFO regulations. Instead, the Agency focuses on specifi c id entifiable and measurable benefits. The impacts of the regulatory proposal likely includ e additional benefits not addressed in these analyses, such as reductions in the cost of treating public water sup plies; improved recreational opportunities in the Great Lakes, estuaries, and other near

coastal wa ters; improvement in the condition of non-boatable waters to boatable condition ; imp rovements in the quality of water resources that are already suitable for swimming ; improvements in commercial fishing; improvements in near-stream activities; and non-water relate d benefits, such as potential reductions in odor from waste management areas. In light of thes e limitations, EPA believes that the benefits quantified in this report represent a conservative e stimate of the total benefits of revised CAFO standards.8A-1 Appendix 8-A IMPACT OF ALTERNATIVE TIME FRAMES ON PRESENT VALUE AND

ANNUALIZED BENEFITS ESTIMATES

Exhibit 8A-1 PRESENT VALUE OF BENEFITS: OPTION 2-SCENARIO 4a

(1999 dollars, millions)

Discount Rate 3 Percent 5 Percent 7 Percent Time Period Low High Low High Low High 25 years $2,466.8 $2,508.0 $1,958.3 $1,991.6 $1,589.8 $1,617.3 50 years $4,012.2 $4,073.0 $2,731.5 $2,774.6 $1,988.6 $2,021.2 75 years $4,750.9 $4,821.0 $2,960.1 $3,006.1 $2,062.2 $2,095.7 100 years $5,103.7 $5,178.3 $3,027.6 $3,074.5 $2,075.7 $2,109.4 Infinite $5,426.2 $5,505.0 $3,055.9 $3,103.1 $2,078.8 $2,112.5

Exhibit 8A-2 ANNUALIZED BENEFITS: OPTION 2-SCENARIO 4a

(1999 dollars, millions)

Discount Rate 3 Percent 5 Percent 7 Percent Time Period Low High Low High Low High 25 years $141.7 $144.0 $138.9 $141.3 $136.4 $138.8 50 years $155.9 $158.3 $149.6 $152.0 $144.1 $146.5 75 years $160.0 $162.3 $151.9 $154.3 $145.3 $147.6 100 years $161.5 $163.9 $152.5 $154.9 $145.5 $147.8 Infinite $162.8 $165.1 $152.8 $155.2 $145.5 $147.98B-1 Appendix 8-B CALCULATION OF PRESENT VALUES

The present value ( PV

) of a benefit ( B ) to be received t years from now is determined by the following equation:
PV = B / (1 + r ) t t

where r represents the annual discount rate. Thus, the present value of an annual stream of benefits from Year 1 through Year n is calculated as follows:

n PV = 3 B / (1 + r )

t t t = 1

When B is constant S

i.e., when benefits ( B) each year are the same S and n approaches infinity, th e t equation above can be simplified to: PV = B / r

EPA employs the above equation to calculate present values for all categories of benefits tha t are assumed to remain constant from Year 1 onward; i.e., for all categories except reduce d contamination of private wells. In the latter case, benefits are assumed to increase in a linear fashio n until Year 27, and then to remain constant. Thus, the value in Year 27 ( V ) of the constant, infinite 27 stream of benefits ( B ) expected to accrue from that year forward is calculated as:
V = B / r 27

In calculating the present value of reduced contamination of private wells, EPA sets the value of B 27 equal to that of V . The present value of benefits is then determined using the following equation: 27

27

PV = 3 B / (1 + r )

t t t = 18C-1 Appendix 8-C CALCULATION OF ANNUALIZED BENEFITS

The const ant annual benefit A that, over a period of n years, equals the estimated presen t value ( PV ) of benefits is determined by the following equation:

A = PV( r ) / (1-[1 / (1 + r ) ]) n
wher e r represents the annual discount rate. As n approaches infinity, this equation simplifies to: A = PV ( r )
EPA uses the equation above to calculate the annualized benefits reported in this analysis.